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How to cite this thesis
Surname, Initial(s). (2012). Title of the thesis or dissertation (Doctoral Thesis / Master’s
Dissertation). Johannesburg: University of Johannesburg. Available from:
http://hdl.handle.net/102000/0002 (Accessed: 22 August 2017).
UNDERSTANDING THE USE PATTERNS OF MEDICINAL PLANTS:
INVESTIGATING THREE ETHNOBOTANICAL HYPOTHESES IN THE
MPUMALANGA PROVINCE, SOUTH AFRICA
by
JEAN LEON ISIDORE NTENDESHA MULEBA
Thesis submitted in fulfilment of the requirements for the degree
PHILOSOPHIA DOCTOR
(PhD)
In
ENVIRONMENTAL MANAGEMENT
In
THE FACULTY OF SCIENCE
at the
UNIVERSITY OF JOHANNESBURG, SOUTH AFRICA
Supervisor: PROF. KOWIYOU YESSOUFOU
Co-supervisor: PROF. ISAAC T. RAMPEDI
NOVEMBER 2020
Table of Contents
DECLARATION................................................................................................................................ vi
LIST OF FIGURES ........................................................................................................................... vii
LIST OF TABLES ...............................................................................................................................ix
ABSTRACT .......................................................................................................................................... x
ACKNOWLEDGEMENTS ............................................................................................................. xii
DEDICATION ................................................................................................................................. xiii
LIST OF ABREVIATIONS AND ACRONYMS........................................................................ xiv
STRUCTURE OF THE THESIS ...................................................................................................... xv
CHAPTER 1 .......................................................................................................................................... 1
GENERAL INTRODUCTION AND STUDY CONTEXTUALISATION ................................ 1
1.1 INTRODUCTION .......................................................................................................................... 1
1.2 CONTEXTUALISATION OF THE PRESENT STUDY ............................................................. 1
1.3 BRIEF OVERVIEW OF ETHNOBOTANICAL HYPOTHESES ............................................... 5
1.4 PROBLEM STATEMENT AND JUSTIFICATION OF THE STUDY ................................... 12
1.5 AIM, OBJECTIVES AND HYPOTHESES ................................................................................. 15
1.5.1 Aim ...................................................................................................................................... 15
1.5.2 Objectives ........................................................................................................................... 15
1.5.3 Hypotheses......................................................................................................................... 15
1.6 STUDY SITE: THE MPUMALANGA PROVINCE ................................................................. 16
CHAPTER 2 ........................................................................................................................................ 22
LITERATURE REVIEW ON ETHNOBOTANICAL RESEARCH .......................................... 22
2.1 INTRODUCTION ........................................................................................................................ 22
2.2 OVERVIEW OF ETHNOBOTANY IN AFRICA ...................................................................... 22
2.2.1 Ethnobotany in southern Africa ...................................................................................... 23
2.2.2 Ethnobotany in South Africa ........................................................................................... 24
2.3 CURRENT MAJOR CONCEPTS AND PROBLEM IN ETHNOBOTANY .......................... 25
2.3.1 Historic context.................................................................................................................. 25
2.3.2 Approaches to Ethnobotany ............................................................................................ 26
2.3.3 Major fields of Ethnobotany ............................................................................................ 27
2.3.3.1 Quantitative ethnobotany ........................................................................................... 28
2.3.3.2 First quantitative data in ethnobotany ........................................................................ 29
iii
2.3.3.3 Experimental assessment and Hypothesis-testing .................................................... 30
2.3.3.4 Applied ethnobotany ..................................................................................................... 31
2.3.3.5 Three general approaches to analysing quantitative ethnobotanical data ............ 32
2.4 CALL FOR A PARADIGM SHIFT AND RIGOROUS QUANTITATIVE DATA ............... 36
2.5 SCOPE OF THE PRESENT THESIS........................................................................................... 38
2.6 BRIEF SUMMARY OF LITERATURE REVIEWED................................................................. 38
CHAPTER 3 ........................................................................................................................................ 40
GENERAL PATTERNS OF MEDICINAL PLANTS SELECTION BY LOCAL
COMMUNITIES ............................................................................................................................... 40
3.1 INTRODUCTION ........................................................................................................................ 41
3.2. MATERIAL AND METHODS ................................................................................................. 43
3.2.1 Study area........................................................................................................................... 43
3.2.2 Data collection ................................................................................................................... 44
3.2.3 Data analysis ...................................................................................................................... 45
3.3 RESULTS ....................................................................................................................................... 45
3.4 DISCUSSION ................................................................................................................................ 50
3.5 CONCLUSION ............................................................................................................................. 54
CHAPTER 4 ........................................................................................................................................ 56
THE USE OF ECOLOGICAL THEORIES TO GENERATE ETHNOBOTANICAL
KNOWLEDGE: APPARENCY THEORY AND RESOURCE AVAILABILITY .................... 56
4.1. INTRODUCTION ................................................................................................................... 57
4.2 MATERIALS AND METHODS ............................................................................................. 62
4.2.1 Study area........................................................................................................................... 62
4.2.2 Data Collection .................................................................................................................. 64
4.2.2.1 Source of information .................................................................................................... 64
4.2.2.2 Measuring of variables .................................................................................................. 65
4.2.3 Data analysis .......................................................................................................................... 66
4.3 RESULTS ................................................................................................................................... 67
4.3.1 Test of ecological apparency theory ............................................................................... 67
4.4 DISCUSSION ............................................................................................................................ 71
4.5 CONCLUSION ......................................................................................................................... 74
CHAPTER 5 ........................................................................................................................................ 75
ETHNOBOTANICAL KNOWLEDGE, ENVIRONMENTAL MANAGEMENT AND
POTENTIAL BARRIERS RESTRICTING KNOWLEDGE GROWTH .................................. 75
iv
5.1 INTRODUCTION .................................................................................................................... 76
5.2
MATERIAL AND METHODS ......................................................................................... 80
5.2.1 Study area............................................................................................................................... 80
5.2.1.1 Mpumalanga Province .................................................................................................. 80
5.2.1.2 Kruger National Park (KNP) ........................................................................................ 80
5.3 DEFINITION OF VARIABLES USED IN THIS STUDY ..................................................... 82
5.4 DATA COLLECTION ............................................................................................................. 82
5.5 DATA ANALYSIS .................................................................................................................... 83
5.6 RESULTS AND DISCUSSION ............................................................................................... 85
5.7. CONCLUSION ........................................................................................................................ 96
CHAPTER 6 ........................................................................................................................................ 98
CHAPTER 7 ...................................................................................................................................... 103
REFERENCES .................................................................................................................................. 103
APPENDICES .................................................................................................................................. 134
v
DECLARATION
STUDENT NUMBER: 201613201
I declare that UNDERSTANDING THE USE PATTERNS OF MEDICINAL PLANTS:
INVESTIGATING
THREE
ETHNOBOTANICAL
HYPOTHESES
IN
THE
MPUMALANGA PROVINCE, SOUTH AFRICA is my own work and that all the sources
that I have used or quoted have been indicated and acknowledged by means of complete
references.
One Paper arising from this thesis has been published.
________________________ _____________________
SIGNATURE
JEAN LEON ISIDORE NTENDESHA MULEBA
DATE :29/11/2020
vi
LIST OF FIGURES
Figure 1.1 The geographic location of the Mpumalanga Province, with a highlight of the
Kruger National Park………………………………………………………………………………26
Figure 1.2 Diagram indicates the overall structure (see below for details). Each chapter is
linked to the next through arrows. Chapter 1 (General Introduction) covers all the themes of
ethnobotany as science. While the chapters 2, 3,4 and 5 present the factors leading to the
formation of use patterns of medicinal plants selection based on the hypotheses testing in the
province. While Chapter 6 presents a general discussion and conclusions on issues of
medicinal
plants
use
patterns
in
this
thesis.
……………………………………………………………………………………………………….29
Figure 3. 1: Diagnostic plots showing non-normality of the residuals of untransformed
data………………………………………………………………. …………………………………56
Figure 3.2: Diagnostic plots showing improved normality of the residuals of untransformed
data…………………………………………………………………………………………………..57
Figure 3.3: Diagnostic using a negative binomial model. Relationships between number of
medicinally used woody plants and the total number of woody plants per family in the
Mpumalanga province, South Africa. ……………………………………………………………58
Figure 4.1 Forest cover in Mpumalanga province, South Africa………………………………73
Figure 4.2 Relationships between plant height and medicinal status. Taller plants are more
likely to be medicinal. Medicinal status is coded 1 (medicinal) and 0 (non-medicinal)
……………………………………………………………………………………………………….78
Figure 4.3. Relationships between plant height and plant use value. Taller plants tend to have
higher use value. ……………………………………………………………………………………79
Figure 4.4. Relationships between plant height and total plant use. Taller plants tend to have
more uses…………………………………………………………………………………………… 80
Figure 5.1 Meta-model illustrating the prediction of availability hypothesis. Different paths
(arrows) of the relationships of total abundance with medicinal status are colour-coded; black,
direct path, green, shortest indirect path, and red, longest, and most strong indirect path. The
width of the arrow is indicative of the strength of the relationships between two variables.
vii
Values
on
the
arrows
are
path
coefficients,
SE,
standard
error………………………………………………………………………………………………….95
Figure 5.2 Meta-model illustrating the potential influence of plant abundance outside (a)
versus inside (b) the Kruger National Park. Different paths (arrows) of the relationships of
total abundance with medicinal status is colour-coded; black, direct path, green, shortest
indirect path, and red, longest, and most strong indirect path. The width of the arrow is
indicative of the strength of the relationships between two variables. Values on the arrows are
path coefficients, SE, standard error………………………………………………………………103
Figure 5.3 The most complex meta-model illustrating the simultaneous influence of outside
and inside plant abundance on medicinal knowledge. Different paths (arrows) of the
relationships of total abundance with medicinal status are colour-coded; black, direct path,
green, shortest indirect path, and red, longest, and most strong indirect path. The width of the
arrow is indicative of the strength of the relationships between two variables. Values on the
arrows
are
path
coefficients,
SE,
standard
error…………………………………………………………………………………………………105
viii
LIST OF TABLES
Table 3.1 Residual values from various model fitting to medicinal data from Mpumalanga
province, South Africa………………………………………………………………………………60
Table 5.1 Native (shrubs and trees) medicinal distribution in the Mpumalanga province and
the Kruger National Park (KNP)…………………………………………………………………..98
ix
ABSTRACT
For centuries, humans have developed vital knowledge of interactions with their environment
and scientific decisions need to benefit from this knowledge so that human interactions with
the environment can be sustainable. Scientific decisions on conservation problems must be
culturally appropriate to the local communities living close to the environment where the
problems occur. Unfortunately, several studies that investigate the human dimension to
conservation used a multi-disciplinary approach integrating various disciplines such as
environmental anthropology, environmental sociology, human-environment geography,
environmental humanities but surprisingly without acknowledging ethnobotany as one of the
key disciplines that can inform conservation science. This is difficult to believe since
ethnobotany studies human-environment interactions with a focus on its plant components
due to complexity of current societal problems, segmentation of knowledge and management
sectors, and limited collaboration between scientists and decision makers. To address this
situation, ethnobotany as science must embrace the theory-inspired and hypothesis-driven
approach. This is the only way human-plant interactions can be better understood. This thesis
attempted to answer questions such as how and why people select particular medicinal plants
for wide range of uses in the Mpumalanga province of South Africa. By using the theoryinspired and hypothesis-driven approach, it is possible to establish the links between
botanical and cultural diversity in the province, and also develop appropriate methodologies
required for determining conservation priority of culturally important plant species in the
province. This thesis investigated three ethnobotanical hypotheses developed to further the
understanding of ethnomedicinal use processes and patterns, their potential to help facilitate
biocultural conservation in the province. The three hypotheses were as follows: - the theory
of non-random plant selection to test the general taxonomic patterns of medicinal plant
selection by local communities, followed by -the ecological apparency theory and resource
availability hypothesis to investigate how ecological theories can be integrated to generate
ethnobotanical knowledge and lastly the availability hypothesis to demonstrate how
ethnobotanical knowledge can inform conservation decisions. In the first test: the theory of
non-random plant selection tested 811 woody plants by fitting the commonly used simple
linear regression model as well as the negative binomial model. This analysis confirmed the
hypothesis and revealed that some plant families are over-utilised. The proportion of overutilised families ranges from 50% (linear regression with untransformed data) and 55% (linear
regression after log–log transformation) to 34% (negative binomial model. In the second test,
a Generalised Linear Model (GLM) was fitted to test the ecological apparency theory and
resource availability hypothesis, to find out if plant height predicts medicinal status (plant
height as the predictor and medicinal status as the response variable) and thus specifying the
binomial error family, given that the response variable is binary (a plant is either medicinal or
not). In addition, a GLM model with a Gaussian error structure was fitted to the height or life
form data. To test if these variables (height and life form) predict the total number of recorded
plants uses, the negative binomial GLM model was fitted using the glm. nb function as
x
implemented in the R library MASS (Venables and Ripley, 2002). While the resource
availability hypothesis was fitted the same way but this time using plant growth rate as a
predictor with a standardised and continuous predictor variables Hmax and growth rate
before the analysis to facilitate the interpretation. The analysis showed that plant maximum
height correlates significantly and positively with medicinal status (β=0.06±0.01, P<0.001),
suggesting that taller plants tend to be more medicinal than shorter ones. While, plant height
does not correlate with the probability of plant being medicinally overused, whether this
probability is treated as a binomial variable (β=0.004±0.01, P=0.68) or a proportion
(β=0.002±0.007, P=0.77). Regarding the resource availability hypothesis, there was no evidence
that plant growth rate predicts neither medicinal status (β=-18.64±52.71, P=0.72) nor the
probability of plant being overused irrespective of whether this probability is estimated as a
binary variable (β=11.92±49.18, P=0.80) or as a proportion (β=6.16±34.03, P=0.85). Furthermore,
plant growth rate does not correlate with Use Value (β=9.22±29.54, P=0.75) nor does it correlate
with the total number of uses (β=-9.64±26.38, P=0.71). The last analysis of the availability
hypothesis was tested using a dataset of 806 woody plants including medicinal plant uses and
their abundance inside and outside the Kruger National Park (KNP)/ South Africa (medicinal
status, total number of recipes/plants, number of plants organs/recipes). Four different
scenarios of Structural Equation Models (SEMs) were fitted to the data collected. All SEMs,
P>0.05, indicating the good fit of these SEMs. It was found that total abundance is a significant
positive predictor of medicinal status, and so is abundance outside KNP. These findings
support the availability hypothesis. However, not only abundance inside KNP is not a direct
significant correlate of medicinal status, but also the relationship between both is negative.
The lack of predictive power of inside-abundance is most likely because some species are
exclusively found inside KNP and local communities have no access to them.
KEYWORDS
Paradigm shift, quantitative ethnobotany, use patterns, medicinal plants, mass biodiversity
extinction, Kruger National Park, Mpumalanga province, South Africa.
xi
ACKNOWLEDGEMENTS
First of all, I would like to thank the Lord Almighty, the Creator of the Universe for granting
me the opportunity, the strength and the health to complete the present study. Because with
Him, nothing is impossible. He is God. He changes not (Numbers 23:19).
I gratefully acknowledge the contributions of the following individuals and institutions to this
study:
•
Professor Kowiyou Yessoufou: my research supervisor, who took time to groom me
throughout this study and never gave up on me even when I thought I could not go
on. His endless encouragement, friendship, patience, scientific discipline and excellent
guidance. His support (academic and financial) at a critical moment will always be
remembered wherever I go.
•
Professor Isaac T. Rampedi: my research co-supervisor, his endless constructive
engagement, patience, meticulous proof-reading, advice and excellent guidance have
made this research a truly wonderful learning experience.
•
The University of Johannesburg (U.J): especially for the financial support provided
through the Global Excellence Stature (GES) and Merit bursary offered by the Faculty
of Science.
•
Professor Catherine Ngila: for divine appointment and scientific advice.
•
Dr Simphiwe Ngquangweni: for being always there for us.
xii
DEDICATION
To:
Terry Ntendesha
Lynn Ntendesha
Irvine Ntendesha
Matthew Ntendesha
xiii
LIST OF ABREVIATIONS AND ACRONYMS
AIC: Akaike Information Criterion
DBH: Diameter at breast Height
FIC:
Informant consensus factor
GES: Global Excellence Stature
GLM:
Generalized Linear Model.
GDP:
Gross domestic product
KNP:
Kruger National Park
LM:
Linear Model
NTFPs: Non-timber forest products
NBT: Nature-based tourism
PAs:
Protected areas
IUCN: The International Union for Conservation of Nature
NSBA: National Spatial Biodiversity Assessment
UJ: University of Johannesburg
RCI: Relative cultural importance
SANBI: South African Institute of Biodiversity
SEM: Structural equation modelling
SEPASAL: Survey of Economic Plants for Arid and semi-Arid Lands
U.V: Use- Value
xiv
STRUCTURE OF THE THESIS
The thesis is structured around six chapters as graphically represented in Figure 1.2. The
chapter 1, is an introduction to the thesis. It introduces the project, highlights its aim and
objectives and demonstrates the importance of ethnobotany for environmental or biodiversity
management. Next is chapter 2, which is the literature review. This chapter provides an indepth presentation of what is currently known in ethnobotany and which is relevant to the
present project. While chapters 3, 4 and 5 present the findings for objectives 1,2 and 3,
respectively. However, these 3 chapters are structured in such a way that i) background and
justification of each objective are presented, ii) the readers are reminded of the study area
(even though broader details of the study area are presented in chapter 1), iii) the method
used for each objective is presented as well as iv) the corresponding results and discussion.
The thesis ends with chapter 6 which presents the overall conclusion of the project, including
the implications for environmental management with a focus on biodiversity conservation.
xv
Chapter 1
General Introduction
Chapter 2
Literature Review
Chapter 3
General Patterns of Medical Plants selection
by Local Communities
Chapter 4
The Use of Ecological Theories to Generate Ethnobotanical
Knowledge
Chapter 5
Ethnobotanical Knowledge, Environmental Management and Potential Barriers
restricting Knowledge Growth
Chapter 6
General Conclusions
Figure 1.2. Diagram indicates the overall structure of the thesis
1.1 Overview of Chapter 1
Chapter 1 is entitled “General Introduction". The objective of this chapter is to introduce the
research project, highlight its aim and objectives and presents the study area. It provides
background information and further introduces the need for a study using medicinal plants
xvi
as a model to discuss the factors leading to the formation of use patterns that explain the
selection of these medicinal plants in the Mpumalanga province.
1.2 Overview of Chapter 2
Chapter 2 of this thesis is entitled " Literature review". This chapter provides an in-depth
presentation of what is currently known in ethnobotany and which is relevant to the present
project in the context of Africa, southern Africa and South Africa.
1.3 Overview of Chapter 3
Chapter 3 is entitled “General patterns of medicinal plants selection by local communities".
Here, three relative statistic approaches were fitted including simple linear regression
analysis, with log-transformation of "count data" compared to the generalised linear model
with negative binomial to perform a robust test of the non-random hypothesis of medicinal
plant selection using the woody flora of the Mpumalanga province, South Africa. At the end,
the best statistic approach candidate for comparative analysis of plant selection is discussed.
1.4 Overview of Chapter 4
Chapter 4 is entitled " The use of ecological theories to generate ethnobotanical knowledge".
Where do medicinal values or medicinal properties reported for various plant species come
from (Gaoue et al. 2017)? Are they coming from the woody or herbaceous plants, exotic or
native plants? Understanding the origin of medicinal values and properties is critical as to
what are the major driving forces that lead to the selection of medicinal plants. These
questions are discussed by assessing the plant -herbivory interactions that lead to the human
selection of medicinal plants through rigorous testing of the ecological apparency theory
(Feeny,1976) and the resource availability hypothesis (Coley, 1987 a, b).
xvii
1.5 Overview of Chapter 5
Chapter 5 is entitled “Application of ethnobotanical knowledge for environmental
management". To date, studies that address medicinal plant use behaviour patterns are very
few. Does the presence of the Kruger National Park have an impact on human groups living
in its surroundings? Medicinal plant use behaviour patterns are discussed as well as their
possible causes. What causes plant species use behaviour to differ from one location to
another? What are the many driving factors, including the role of the environment in which
human groups are included?
1.6 Overview of Chapter 6
The last chapter highlights the general conclusion of the project, including the implications
for environmental management with a focus on biodiversity conservation.
xviii
CHAPTER 1
GENERAL INTRODUCTION AND STUDY CONTEXTUALISATION
1.1 INTRODUCTION
Changes in ecosystems have been more rapid during the past 50 years than at any other time
in human history and evidence that the world is entering the sixth mass extinction period is
actually on the increase in the history of life (Millennium Ecosystem Assessment 2005 a, b;
Chapin III et al. 2000). This extinction period is characterised by an unprecedented rate of
biodiversity loss, mediated through anthropogenic activities (Bamosky et al. 2011) and it
should be addressed as global concern urgently given the benefits humans derive from
biodiversity (shelter, food, recreation, medicine) (Gascon et al. 2015). More importantly, it is
now well understood that the bulk of these unprecedented levels of loss of biodiversity are
human-induced damage and alterations to the global environment as a result of poor and
inefficient use of natural resources (Wright 2005; WCMC 2003; Sala et al. 2000; Daily 1999).
Moreover, it should be known that forests host the richest biodiversity in the world among
the terrestrial ecosystems (Nakashizuka, 2007; Wright, 2002). But unfortunately, the long-term
sustainability of rainforests, and the wide range of goods and services they provide, may now
be under severe threat as a result of uncontrollable anthropogenic activities (Foley et al. 2007).
1.2 CONTEXTUALISATION OF THE PRESENT STUDY
As part of biodiversity, plant diversity has and will continue to play a central role in the daily
life of human beings. Globally, cultivated and wild plants provide people with food
supplements, herbal medicine, services, construction materials and resources for the
manufacture of craft, tools and ornaments. Plant’s central role in the everyday life has
significant importance in developing countries, where all aspects of daily activity involve
1
direct use of plant resources, (e.g., subsistence agriculture, livestock grazing, firewood,
medicinal plants collection (FAO 2007 a; World Development Report 2007; Hamilton et
al.2003; Ford 1978).
Evidence that the world has entered the sixth mass extinction period is on the increase, and
this period is characterised by the unprecedented rate of loss of biodiversity mediated by
anthropogenetic activities (Barnosky et al. 2011; Ceballos et al. 2015), and therefore
understanding human-plant interactions is of practical importance as this can provide
mechanisms that would regulate anthropogenic pressure on natural resources. However,
when compared with ecological studies, for example, very little effort indeed has been
devoted to uncovering the real factors that drive human selection and use of specific species.
Yet harvesting non-timber forest products (NTFPs) for medicinal, food or other purposes is
growing with significant unintended consequences not only for the livelihood of the people
who depend on it (Belcher et al. 2005; Shackleton et al. 2005) but also for the ecological
sustainability of the systems that are harvested (Gaoue et al. 2013; Moegenburg and Levey,
2002; Silvertown, 2004; Ticktin, 2004). For example, NTFPs represent more than $90 billion
worth of products harvested annually and sustain the livelihood of more than 300 million
people worldwide (Pimentel et al. 1997).
Humans form biological populations in a very rapidly changing world, and the ways that
these humans relate to nature are determined by social constructions of value or culture
(Balée, 1989). These needs can be assessed for the entire population, and how they are met
will predict the number of certain plants to meet them. Similarly, a population's use of fuel
for warmth and materials for shelter can be quantified to determine how procurement of these
materials will affect the floral environment. Further, human activity and natural
2
environmental disturbance determine the distribution and the availability of plants. The
relative quantity of a specific plant in time and space may reflect either human gathering
practices or environmental variable that are present in such a landscape, in addition, plants
have determined the very course of civilisation. Global geographical predispositions, such as
the extension of landmasses and the availability of species amenable to domestication causally
conditioned acceptance and the interchange of knowledge, technology and germplasm
(Diamond 2005).
Furthermore, over many centuries, man has developed an intricate relationship with the
natural environment, especially in using environmental resources to satisfy own subsistence
needs, thus earning a living especially when these resources are used sustainably. This is true
with water resources and geological resources but also different types of plants that occur
naturally in different biomes and ecological habitats (Londono et al. 2016; Garcia et al. 2020;
Matthews et al. 2020). However, when facing unprecedented looming extinction threats,
from climate change, deforestation, biodiversity loss and many more, there is a need to
understand through scientific study research some cultural practices and values of diverse
societies, that can promote mitigation strategies and thus enhancing conservation (Barnosky
et al. 2011; Ceballos et al. 2015).
In the present thesis, the relationship between human and plants has led to what is
increasingly regarded as the emerging study field of ethnobotany in different parts of the
world (Xolocotzi, 1983; Shava et al. 2009; de Albuquerque and Hurrell,2010; Mohammad
Hossein et al. 2019). In addition, de Albuquerque (2005) defined ethnobotany as the study of
the direct interrelations between peoples from living cultures and the plants in their
environment. Thus, ethnobotany examines these interrelations between people and plants
3
from the perspective of Western science (de Albuquerque and Hurrell, 2010) and is a relatively
new scientific discipline which, unlike other more established sciences, has not been yet
systematised and formalised (Hamilton et al. 2003). However, it has been practised by many
scientists who value this discipline and recognise that ethnobotany has a relevant role in the
development of societies (Hamilton et al. 2003).
Different studies have demonstrated that ethnobotany's history goes up to the relations
between human beings and plants and to the domains of applied botany and botanic
ethnography (Balick & Cox 1996, Hamilton et al. 2003). It is, therefore, important to
understand how local people are using plant resources and to document this knowledge
before it becomes lost in acculturation processes (Bhagwat et al. 2008; Nakashizuka, 2007;
Cunningham, 2001). In this context, ethnobotanical studies, which study the classification,
use, and management of plants by people, represent an ideal scientific approach to this
challenge (Martin, 2004). By recognising that ethnobotany concerns those who actually
manipulate or think about the local vegetation directly, the field is immediately demarcated
either to the study of self-sufficient societies or to an examination of the conduct of specific
activities. Those who must gather or raise their food and build their shelters are in actual
contact with plants. They must know how to recognise certain plants, when to gather them,
and what to expect from them. Nevertheless, people dependent upon a market economy for
provision are not removed from making decisions about plants; they select for cultural, social
and utilitarian reasons; they classify them; and they have rules for manipulating them (Ford,
1978). Ethnobotany, as the science of plant-human interactions, has for long been a discipline
that largely documents the diversity of plant uses by local people through interviews and
surveys. Recently, however, this focus on documenting traditional uses of plants is
4
increasingly being questioned. Specifically, several authors (e.g., de Albuquerque et al. 2006;
Ford and Gaoue, 2017; Hart et al. 2017) have now called for a shift toward more hypothesisdriven approach in ethnobotany because that is the only way human-plant interactions can
be better understood. Questions such as how and why people select particular plants for a
wide range of uses must be investigated. Despite the recent multiple calls for the shift, most
recent ethnobotanical studies still prefer the traditional knowledge documentation approach
(e.g., Leso et al. 2017). In contrast, over the last couple of decades, the links between biological
and cultural diversity have been investigated to develop methodologies for determining
conservation priority of culturally important plants species (de Albuquerque and Oliveira,
2007; Cristancho and Vining, 2004; Garibaldi and Turner, 2004). As a result, several theories
and hypotheses have been developed to further our understanding of local ethnomedicinal
use processes and patterns (Gaoue et al. 2017) and their potential to help facilitate biocultural
conservation (de Albuquerque and Oliveira, 2007; Cuerrier et al. 2015; Garibaldi and Turner,
2004). Though these theoretical frameworks have long been proposed, in South Africa, for
example, different uses of medicinal plants are very well documented (e.g., van Wyk, 2008),
unfortunately, very few studies have thoroughly examined and tested their major predictions.
Nonetheless, the questions of how and why some plants are preferentially used rather than
others are poorly explored (but see Yessoufou et al. 2015). This research provides some
insights regarding the contribution to why and how medicinal plants are selected in
Mpumalanga province, South Africa.
1.3 BRIEF OVERVIEW OF ETHNOBOTANICAL HYPOTHESES
Ethnobotany has evolved from a discipline that largely documented the diversity of plant use
by local people to one focused on understanding how and why people select plants for a wide
5
range of uses. This progress has been in response to a repeated call for theory-inspired and
hypothesis driven research to improve the rigor of the discipline. Ethnobotanical education
has rightly focused on training emerging ethnobotanists in key concepts and methods such as
interviews, participant observation, free-listing, livelihood analysis, and emic versus etic
approaches (Martin 2007). The potential to learn about herbal medicine, psychoactive plants,
or the natural connection to land and organisms can draw students into the discipline of
ethnobotany. However, our ability to keep them in this discipline is directly linked to the level
of mastery they have in developing research frameworks and methods that are consistent with
the scientific methods used in other disciplines. Learning the fundamental theories of a
discipline is one of the first steps in understanding that discipline, generating new knowledge,
and furthering the discipline’s understanding of patterns and processes.
Despite improvements, recent ethnobotanical research has overemphasized the use of
quantitative ethnobotany indices and statistical methods borrowed from ecology, yet
underemphasized the development and integration of a strong theoretical foundation. To
advance the field of ethnobotany as a hypothesis-driven, theoretically inspired discipline, it is
important to first synthesize the existing theoretical lines of research.
Seventeen (17) majors’ theories and hypotheses were reviewed more recently (see Gaoue et
al. 2017) that can be used as starting point for developing research questions that can advance
the understanding of people-plant interactions. These majors theories and hypotheses are as
follows: versatility hypothesis, availability hypothesis, diversification hypothesis, plant use
value hypothesis, theory of non-random plant selection, the doctrine of signature, optimal
defense theory, ecological apparency hypothesis, the resource availability theory , the
optimum foraging theory, age, gender dynamics of knowledge hypothesis, urbanisation and
knowledge loss hypothesis, social network as driver of knowledge dynamics, cultural
6
keystone species, utilitarian redundancy model hypothesis, taboo as conservation strategy
hypothesis, taboo as luxury hypothesis. Primary predictions and testable hypotheses were
identified and then discussed for each theory or major hypothesis (Gaoue et al. 2017).
The most promising hypothesis-driven approaches to date have come from testing whether
patterns of human selection for medicinal plants align with the predictions of the theoretical
frameworks from ecology (e.g. de Albuquerque 2006; de Albuquerque and Oliveira 2007;
Alencar et al. 2010; Bennett 2007; Bennett and Husby 2008; Vandebroek and Balick 2012;
Reyes-García et al. 2013b; Quiroz and van Andel 2015; Voeks and Leony 2004; Voeks 2007).
However, for such efforts to expand beyond individual research groups and sites, it is
important for ethnobotanists to recognize the breadth of current ethnobotanical theories and
understand how these theories can be used to develop testable hypotheses. Further, it is
critical for emerging ethnobotanists to be exposed to these theories in a systematic way.
Developing research to test these predictions will make significant contributions to the field
of ethnobotany and create the critical mass of primary literature necessary to develop metaanalyses and to advance new theories in ethnobotany.
From the above seveteen theories and hypotheses, three were selected to document the
diversity of plant use by local people in the Mpumalanga province, where the trade in
medicinal plants is huge, and it is highly unlikely that at current levels of exploitation, the
sustainable supply of medicinal plants will ever meet the demand.
In the present research project three theories and hypotheses were tested, including the theory
of
non-random
plant selection, the ecological apparency hypothesis and the resource
availability theory, and finally the availability hypothesis.
7
1.3.1 Why the choice of only three theories and hypotheses?
The growing number of ethnobotanical studies has revealed an imporatant finding :
behaviours related to the use of plant resources are recurrent in different human populations.
These repeated behavioural attitudes in plant use are known also as pattern which can be
expressed in general terms of pharmacopoeia (habits of dominant plantss, main therapeutic
indications of the plants), it may be further observed in the ways by which different human
populations use the same plant species (Medeiros & de Albuquerque,2015).In general,
patterns may be generated in two ways: (a) diffusion and (b) convergence (Bletter 2007).
Diffusion is the process of information transmission between individuals belonging to the
same or different human groups. Patterns generated through diffusion may occur because of
contact between individuals and exchanges of information between close or distant
populations, which occurs for members of a local population who migrate to a distant location
and transmit their knowledge to the inhabitants of this new location. When information on
plant use crosses community borders and reaches new locations, the resulting plant-use
patterns do not result from independent discoveries by the communities. Instead, the
information shared between different populations has a common origin. This process
characterises the diffusion of knowledge. Different communities may also acquire the same
plant-use behaviour independently in a process known as convergence. These patterns can be
characterised in taxonomic patterns, patterns related to plant habit, patterns related to species
origin and biogeographical distribution, patterns related to therapeutic indications and those
linked to the environment itself.
Mpumalanga province is a very interesting case study for ethnobotanical research, given the
fact that it comprise 3% of southern Africa, but yet support 21% of its species diversity. As a
8
result of this concentration of sepcies diversity, the trade in medicinal plants is huge and not
sustainable. The assumption here is that there are clear patterns in the province that justify
the trade in medicinal trade. Therefore, the only way to explore these patterns would be to
attempt to answer questions such as how and why people select particular medicinal plants
for a wide range of uses in the Mpumalanga province, South Africa would be through the
investigation and the testing of three theories and hypotheses, whose predictions are related
to the observed patterns. The theories and hypotheses included firstly the theory of nonrandom plant selection which is linked to the taxonomic pattern, because chemical
compounds with medicinal value are not equally distributed among different botanical
families (Gottlied et al. 2002), at least two behaviours can be expected : (a) certain families
have higher medicinal value and are therefore more frequently used than others and (b)
different families are used to treat different afflictions. What are the families that are most
used and traded in the province? Secondly, the ecological apparency theory & the resource
availability hypothesi, these two are related to plant habit (Stepp & Moerman, 2001). These
theories are expected to inform on which species are most important from a medicinal
perpective in the province. In Mpumalanga province, the observation will be based on trees
and shrubs, thus, contrasting with the original predictions of these theories that were based
purely on the predominance of herbs, especially ruderals, in pharmacopoeias ( Stepp &
Moerman 2001). This was followed by the third hypothesis that is related to role of the
environment, in this case the availability hypothesis to inform on how plant use behaviours
may differ from one location to another depending on many factors, including the role of the
environment in which human groups are involved. Such as the presence of the KNP and its
impact on the plant use and knowledge development in the province that is facing high trade
in medicinal plants.
9
1.3.1.1 The theory of non-random selection of plants
The theory of non-random plant selection was developed by Daniel Moerman (Moerman
1979,1991,1996). It was intended, in part to counter the belief at the time that Native American
medicine was only placebo (Moerman 1979). This theory predicts that medicinal plant
selection is not random and that the number of medicinal species in a given family in a given
region would be a linear (on a log scale) function of the total number of plant species in that
family.
1.3.1.2 The ecological apparency theory & the resource availability hypothesis
The ecological apparency hypothesis is directly related to the optimal defense theory. The
primary prediction of this hypothesis is that species with short lifespans(non-apparent) will
face lower pressure and are more likely to use inexpensive qualitative defense while species
with long lifespans (apparent) will face higher pressure from herbivore and invest in more
expensive quantitative defenses (Feeny, 1976). While the resource availability theory shares
the ecological apparency hypothesis, it suggests however, that plant defense investment is not
primarily related to the risk of herbivory but the resource level of the habitat to which the
plant is adapted (Endara and Coley, 2011). The resource availability hypothesis predicts that
species adapted to high resource environments (e.g., highlight, nutrient-rich habitats) are
more likely to grow quickly and use qualitative defense, while species adapted to low resource
environments (e.g., lowlight, nutrient-poor habitats) are more likely to grow slowly and have
high levels of defense—primarily quantitative but also qualitative (Coley et al. 1985; Endara
and Coley, 2011; Stamp 2003). Fast-growing/ short-lived species that can tolerate higher rates
10
of herbivory and invest more in qualitative defense (e.g., alkaloids) will have more medicinal
uses and will be more sought after than long-lived/slow-growing species which invest more
in quantitative defenses.
1.3.1.3 The availability hypothesis
The availability hypothesis states that plants are used for medicine because they are more
accessible or locally abundant ( de Albuquerque 2006; Voeks 2004). This hypothesis was born,
in part, out of studies revealing the importance of anthropogenic habitats or disturbed areas
in provisioning woody and introduced species for medicine (Gavin 2009; Stepp and Moerman
2001; Voeks 2004). Availability is often conceptualized as a physical distance from a home or
community to the location where a plant grows in the wild, but could also be considered in
terms of seasonality, abundance, price, as well as access to markets, gardens or natural areas
where plants are found (de Albuquerque 2006; Estomba et al., 2006). The availability
hypothesis has been tested by examining the location where people indicate they collect
medicinal plants, and, more broadly, by correlating the local abundance or dominance of
plants with use-values.
1.3.1.4 Importance of the Mpumalanga province as study site?
Mpumalanga province was chosen over other provinces such as KwaZulu-Natal, Eastern
Cape or Limpopo provinces, because the province is a unique case study that has an
extraordinary diversity in plant species (Mucina and Rutherford, 2006; Ferrar and Lötter, 2007).
It only comprises 3% of southern Africa’s surface area, yet supports 21% of its species
diversity. This diversity is not evenly distributed, but is predominantly confined to four Centres
and two Regions of Endemism. The trade in medicinal plants is huge, and it is highly unlikely
that at current levels of exploitation, the sustainable supply of medicinal plants will ever meet
the demand (Mucina and Rutherford, 2006; Ferrar and Lötter, 2007). It is important to be able
11
to identify areas that could potentially support, or provide plants to the medicinal plant trade.
Furthermore, this province is known to have two well - defined communities, namely
indigenous forests and wetlands, that occur within the broader vegetation communities of the
province. Both forests and wetlands are important for their role in ecosystem processes and
their richness in biodiversity. The indigenous forest biome is the smallest, estimated at 40 353
ha or 0.51% of the surface area, most widely distributed, and most fragmented biome in South
Africa, estimated at 0.33% of the land surface area (von Maltitz and Fleming, 1999).
1.4 PROBLEM STATEMENT AND JUSTIFICATION OF THE STUDY
The ongoing environmental crisis, e.g., biodiversity crisis or the 6th mass extinction, pointed
fingers at humans as the main drivers of the crisis (Ceballos et al. 2015). Humans drive
biodiversity loss, ecosystem disruption, etc. through their unsustainable use of their
environment, e.g., plant harvest for medicine (MEA, 2005 a, b). For centuries, humans have
developed vital knowledge of and interactions with their environment. Scientific decisions
need to benefit from this knowledge so that human interactions with the environment can be
sustainable (Poe et al. 2014). For example, scientific decisions on conservation problems must
be culturally appropriate to the local communities living close to the environment where the
problems occur. Unfortunately, several studies that investigate the human dimension to
conservation used a multi-disciplinary approach integrating various disciplines such as
environmental anthropology, environmental sociology, human-environment geography,
environmental humanities but surprisingly without acknowledging ethnobotany as one of the
key disciplines that can inform conservation science (Bennett et al. 2017). This is difficult to
believe since ethnobotany studies human-environment interactions with a focus on its plant
components. To change this, ethnobotany must embrace the theory-inspired and hypothesis-
12
driven approach (de Albuquerque, 2009; de Albuquerque and Hanazaki,2009; Bennett, 2005;
Ford, 1978; Hurrell and de Albuquerque, 2012; Martin, 2007; Gaoue et al. 2017).
Ethnobotany has, for a very long time, been concerned with the documentation of the
diversity of plants used by local people, how they use them, and which parts of the plants are
used (Balick, 1996; Etkin, 1988). This traditional approach led some authors to criticise the
discipline of ethnobotany as "weak" or "pseudoscience" (de Albuquerque and Hanazaki, 2009;
Alexiades,1996; Gaoue et al. 2017). For example, some authors wondered whether the
discipline ever has a unifying theory (Ford,1978), while others presented ethnobotany as too
descriptive without theoretical frameworks and/or methodological rigour (Phillips and
Gentry, 1993a). As a result, authors such as Bennett (2005) and de Albuquerque & Hanazaki
(2009) supported the need to shift from more quantitative ethnobotany to more theoryinspired and hypothesis-driven ethnobotany. Whilst hypotheses are proposed explanations
for an observation, theories are an "integrated and hierarchical set of empirical hypotheses
that together explain a significant fraction of a scientific observation" (Krebs, 2000). It is only
through the development of theories and hypotheses that we can understand not only how
and why people select plants for a wide range of uses, and how traditional ethnobotanical
knowledge can inform conservation decisions.
In response to critics, Martin (2007) detailed precisely how the limitations of the traditional
approach could be overcome with a hypothetico-deductive method. Begossi (1996) showed
how ecological methods could be applied in ethnobotany while Hoffman and Gallaher (2007)
utilised species-area curves to estimate the diversity of species used by cultural groups.
McClatchey et al. (2013) rather called for interdisciplinary ethnobotany that integrates
ecological knowledge as well as statistics, evolution, geography and anthropology. However,
13
these different attempts to improve the methodological and philosophical approaches of
ethnobotany (Gaoue et al. 2017) led instead to generalised use of ethnobotanical indices
(Hoffman and Gallaher, 2007). Consequently, there is still a lack of a theoretical framework
that Phillips and Gentry (1993 a, b) called for. Interestingly, these critics of ethnobotany are
evidence that the discipline is at an inflexion point on its trajectory. Other disciplines, e.g.,
ecology, faced similar challenges with several authors asking whether ecology had general
laws or a unifying theory (Aarssen, 1997; Lawton, 1999; Marquet et al. 2014; Weiner, 1995).
Gaoue et al. (2017) believed and rightfully so, that ethnobotany could be informed of the
historical trajectory of other disciplines (ecology, evolution) in response to Phillips and
Gentry's (1993 a, b) and others' call for a paradigm shift in ethnobotany (Salick et al. 2003;
Gaoue et al. 2017).
Some authors have responded to the calls for more theory-and hypothesis-driven
ethnobotany (e.g., Hart et al. 2017; Robles-Arias et al. 2020). Further examples include the
theory-based studies in cognitive ethnobotany (e.g., Atran, 1998; Alexiades, 1996; Brown,
1977; Conklin, 1954; Hunn, 1975; Medin and Atran,2004; Turner, 2000) which result in the
formulation of general principles of folk biological classification (Berlin et al. 1973; Berlin,
1973; Brown,2000). Early attempts of theory-inspired studies also include the biocultural
research in economic ethnobotany with in-depth analysis of the biochemical basis and
pharmacologic implications of food, psychoactive, and medicinal plant uses by local people
(Etkin, 1988; Johns, 1986). The majority of these studies tested whether patterns of human
selection of medicinal plants match ecology-driven predictions (e.g., de Albuquerque, 2006;
de Albuquerque and Oliveira, 2007; Alencar et al. 2010; Bennett, 2007; Bennett and Husby,
2008; Vandebroek and Balick, 2012; Reyes-García et al. 2013b; Quiroz and van Andel, 2015:
14
Voeks and Leony, 2004; Voeks, 2007). There is a need for the ongoing efforts to "expand
beyond individual research groups and sites" (Gaoue et al. 2017), and for ethnobotanists to
embrace the new directions required for the discipline such that theories can be used to
develop testable hypotheses. How can we understand the dynamic relationships between
plants and people outside theories and hypotheses? The answer is positive. The present
project aims to contribute to filling the lack or scanty theory-testing studies in ethnobotany in
such a way that ethnobotanical knowledge can inform environmental management (e.g.,
decisions for biodiversity management). Further details are provided in Chapter 2.
1.5 AIM, OBJECTIVES AND HYPOTHESES
1.5.1 Aim
The project aims to explore the importance of ethnobotany for environmental or biodiversity
management.
1.5.2 Objectives
To reach the aim of the study, the following objectives are set:
•
To test for the general patterns of medicinal plant selection by local communities.
•
To demonstrate how ecological theories can be integrated to generate ethnobotanical
knowledge.
•
To demonstrate how ethnobotanical knowledge can inform conservation decisions.
1.5.3 Hypotheses
The corresponding hypotheses to the objectives of the study are as follows:
For objective 1:
15
•
Non-random hypothesis – Medicinal plant selections are not taxonomically random.
This implies that large families are more likely to contain more medicinal plants than
small families. Details of this hypothesis are in chapter 3.
For objective 2:
•
Ecological apparency Theory – Less apparent plants (short-lived, herbaceous, early
successional) are more likely to be used for medicine than more apparent plants
(perennial, woody, dominant plants) (de Albuquerque and Lucena, 2005).
•
Resource availability hypothesis – Fast growing/short-lived species are more likely to
be medicinal than long-lived/slow-growing species (Alencar et al. 2009; Almeida et al.
2005, 2012).
Details of these hypotheses are in chapter 4.
For objective 3:
•
Availability hypothesis – Plants that are abundant or easily accessible to people are
more likely to be medicinal. Applied to a protected area, the Kruger National Park, the
test of the hypothesis provides an important biodiversity management option for local
biodiversity
Details of this hypothesis are in chapter 5.
1.6 STUDY SITE: THE MPUMALANGA PROVINCE IN SOUTH AFRICA
South Africa is one of the world’s biodiversity-rich countries with more than 19 500
indigenous plant species from around 350 plant families (Crouch et al. 2008). With a total
population estimated to 58.56 million whereas with less than one doctor per 100.000 (Statistics
16
SA, 2019). The major ethnic parts of the group are
the Zulu, Xhosa, Bapedi
(North Sotho), Tswana, South Ndebele, Basotho (South Sotho), Venda, Tsonga, and Swazi,
all of which predominantly speak Southern Bantu languages. Black South African ethnicity's
native distribution is also found across countries neighbouring South Africa. Not surprisingly,
a large pool of traditional ethnobotanical and ethno-medicinal knowledge exists, especially
regarding the use of plants (Lall, 2018). Regional studies from Fourie et al. (1992) and Arnold
et al. (2002) have shown that 243 of 300 evaluated medicinal plants show biological activity in
a range of target assays with antiplasmodial activity. In other words, biological resources and
related ethnobotanical indigenous knowledge constitute a promising starting point for
medicinal bioprospecting for the development of natural products and drugs (Lall 2018).
For example, between 1981 and 2013, an average of 30% of worldwide drug developments
was based on natural products (Wynberg et al. 2015). Apart from that, sizable economic
potential is also attributed to non-medicinal bioprospecting for a growing world market of
natural food and beverage products, fibre, botanical uses, biopesticides and organic personal
care products (Laird et al. 2010; GVR 2019). South Africa’s is one of the most biodiverse
countries in the world, and its biodiversity contributes significantly to the national economy,
and to local livelihoods. With a varied geography ranging from plains and savannas to deserts
and high mountains, South Africa’s ecosystems support over 95,000 species, and its rich
biodiversity contributes significantly to the national economy, particularly through naturebased tourism (NBT). The total contribution of Travel and Tourism to South Africa’s gross
domestic product (GDP) in 2016 is estimated at 9.3 percent (WTTC), a significant portion of
which is directly linked to natural assets, particularly protected areas (PAs). Biodiversity and
its habitats also contribute to the livelihood of the poorest segments of the population, by
17
providing a range of goods, such as food, biomass fuel, and medicine; and services such as
water.
However, the country as whole is facing some threats to its biodiversity including from the
(1) Agriculture sector due to inappropriate agricultural practices, inappropriate grazing
management (overstocking, inappropriate fire management) causing habitat loss and
disruption of the ecosystem function; (2) Plantation forestry that causes direct habitat loss; (3)
Urbanisation causing threat of bio-invasion by invasive alien species; (4) Coal mining;(5)
Climate change.
The study area of the present project is the Mpumalanga province, South Africa (Figure 1.1).
The province is located in the northeastern part of South Africa and covers an area of 76.520
Km2. It is comprised of a diversity of landscapes characterised by grassland, savannah, and
warm-temperate and subtropical forest biomes. Grasslands are most prevalent in
Mpumalanga, making up 65% of the province, while the indigenous forests occupy only 0.51%
of the Mpumalanga's territory. It contains a unique suite of plant species (316 obligate forest
taxa) not found in any other major type in the region (Lötter et al. 2014). The altitude varies
between 110 m and 2328 m above sea level while mean annual rainfall ranges between 341
and 1933 mm. The mean annual temperature ranges from100C to 230C (Schulze, 1997). Fiftyeight vegetation mapping units occur in this province as a result of a diversified topography
and climate (Mucina and Rutherford, 2006; Ferrar and Lötter, 2007).
18
Figure 1.1 The geographic location of the Mpumalanga province, with a highlight of the
Kruger National Park.
The Mpumalanga province also harbours a unique system, the Kruger National Park (KNP)
which is located in the north-eastern part of South Africa between 22o 25' and 25o 32' S and 30o
50' and 32'E (Figure 1.1). The KNP is shared with another province, the Limpopo province. It
is part of the "Greater Maputaland -Pondoland-Albany" biodiversity hotspot (Perera et al.
2011). Within the KNP, rainfall varies from 440 mm in the north to 740 mm in the south
19
(Venter, 1990). Mean annual temperature is around 21oC -23 oC, but in summer temperatures
often exceed 38 oC, whereas frost can occur sporadically during Winter. The KNP is one of the
largest natural reserves (20,000 km2) in Africa. It is a 'woodland biome' of southern Africa
(Schmidt et al. 2007) with various habitats found within its boundaries.
In the province, the indigenous forest is the smallest, widely distributed and most fragmented
biome in South Africa, estimated at 0.33% of the land surface area (von Maltitz and Fleming,
1999). In addition, forests occur in smaller size ranging from (<10ha) to patches (Cooper, 1985;
Geldenhuys, 1991; Mucina et al. 2006). These patches are relicts of past vegetation patterns
and home to numerous habitat specialists. The total indigenous forests in the province are
estimated at 40 353 ha or the equivalent of 0.51% of the province surface area (Mucina et al.
2007).
The Mpumalanga province has extraordinary diversity in plant species, with estimated 4946
taxa occurring within the province; yet it only comprises 3% of southern Africa's surface area
and supports 21% of these countries' plant taxa. However, this high level of plant diversity is
not evenly distributed across Mpumalanga. Two regions of Plant Endemism are recognised
within the province. These are the high lying Drakensberg Afromontane Region and the more
tropical Maputaland-Pondoland Region (Davis et al. 1994).
The Drakensberg Afromontane Region is an archipelago-like region which incorporates an
area of approximately 84 500 km2 in southern Africa. The number of plant species restricted
to this specific region is not known, but species endemism is high (Davis et al. 1994). However,
White (1983) broadly describes the Afromontane region (extending to Ethiopia) to have an
estimated species diversity of approximately 4000 and endemism is around 75%. This region
incorporates several distinct centres, such as the Barberton, Wolkberg and Lydenburg Centres
20
within Mpumalanga, as well as the Drakensberg Alpine Centre on the southern Drakensberg.
Threats identified include fire misuse, alien plant invasion, over-grazing, timber plantations,
uncontrolled bark-harvesting, and firewood collection (Davis et al. 1994; Site Af67).
The Maputaland-Pondoland Region is largely continuous and incorporates an area of
approximately 201 640 km2. An estimated 7.5% of the region occurs within protected areas.
Approximately 7000 plants taxa are recorded for the area, and endemism is around 26%. These
endemics are concentrated in the grasslands. Threats identified are largely attributed to the
high populations occurring in this region but also include timber plantations, extensive
agriculture, urban and industrial development, alien plant invasions and dune mining (Davis
et al. 1994; Site Af59).
In chapters 3, 4 and 5, further backgrounds of the study areas are presented with highlights
of what is relevant to each chapter.
21
CHAPTER 2
LITERATURE REVIEW ON ETHNOBOTANICAL RESEARCH
2.1 INTRODUCTION
Chapter 2 consists of a review of the relevant literature about ethnobotany in the contexts of
Africa, southern Africa, South Africa, and provides further an in-depth presentation of what
is currently known in ethnobotany as science and which is relevant to the present thesis. The
review looks at three components including Section 2.2 overview of ethnobotany in Africa
while section 2.3 deals with current major concepts and problem in ethnobotany. Section 2.4
is devoted to the call for a paradigm shift and the need for rigorous quantitative data. Also, a
summary of these sections is provided.
2.2 OVERVIEW OF ETHNOBOTANY IN AFRICA
Africa as a continent has a remarkable flora coupled with its distinctiveness and its diversity,
moreover evidenced, by as many as 88 % of endemic species (Mucina et al. 2007; Davis et al.
1994). The interaction of human-plant has a longstanding story and has been further enhanced
significantly by biotechnology even though the exploitation of the new natural products has
led to concern for their conservation (Moyo et al. 2011; Nigro et al. 2004). Some important
sources of ethnobotanical accounts in Africa include among others: Dounias' review (2000) for
Central and West Africa, Williamson (1955) and Lindsay (1978) for East African flora, while
Burkhill's (1985) volumes concentrated on West Tropical Africa' keystones. The overall plant
use on the continent has received more consideration in the literature especially during the
last three decades (see Iwu (1993) and Neuwinger (2000), and this trend is expected to
22
continue through the programmes such as the Survey of Economic Plants for Arid and semiArid Lands (SEPASAL) (Nigro et al. 2004; Davis et al. 1998; SEPASAL, 2003).
2.2.1 Ethnobotany in southern Africa
The overall ethnobotanical research in southern Africa has been extensively and thoroughly
reviewed by van Wyk (2002) as evidenced by numerous works on the useful plants of
southern Africa, including "A guide to useful plants of southern Africa" (van Wyk and
Gericke, 2000, 2018), " Medicinal plants of South Africa" (van Wyk et al. 1997, 2009) and
"Poisonous plants of South Africa" (van Wyk et al. 2002).
At the sub-regional level, very little, however, has been recorded on the traditional plant use
during the pre-colonial times (van Wyk,2002). The available information in this field is the
one that had been extracted from the current records (see Cunningham, 1988). In this context,
several publications are worth mentioning including Liengme (1983), Cunningham et al.
(1992), Cunningham (1989) and van Wyk and Gericke (2000). Additionally, very few
publications describe some outstanding contributions of ethnobotany studies such as
Liengme (1983) on Kwanyama Ovambos and Van den Eynden (1992) on the Topnaar Khoi.
While other studies present the useful plants of Lesotho (Jacot-Guillarmod (1966), the useful
plants of Zimbabwe by Ellert (1984), including a valuable account of plant use in Namibia
(Koenen,1996,2001). Whereas the useful plants of Hambukushu in Botswana were presented
by Larson (1975, 1981, 1986) and Bandeira reported the useful plants in Mozambique
(Bandeira,1994).
23
2.2.2 Ethnobotany in South Africa
In South Africa, the first ethnobotanical study was recorded in Namaqualand (Van der Stel
(1685) and Skead (2009). The study focused in the listing of some of the most important plant
families based on a simple count of species used as medicinal (Watt and BreyerBrandwijk,1962; Hutchings et al. (1996); van Wyk and Gericke (2000) and van Wyk and Wink
2004). This trend contrasted, however, with the quantitative use that had become routine in
ethnobotanical research globally (De Caluwé et al. 2009; Grace et al. 2009; Tardio and Pardo
de Santayana, 2008; Teklehaymanot and Giday, 2010; Teklehaymanot,2009).
South Africa's ethnic diversity depends on a wide variety of medicinal plants for the treatment
of ailments in both humans and animals (van Wyk,2002; van Wyk and Gericke (2000); van
Wyk and Wink 2004; Masika and Afolayan, 2000), however, there is a marked imbalance in
the existing literature among these cultures. Most of the available literature focuses on a single
region, culture or category of plant use. Certain ethnic cultures are extensively studied than
others. The most common studies concern the KwaZulu Natal province, with 1032 species
recorded as Zulu medicinal plants (Hutchings et al. 1996; Faber et al. 2007; Du Toit, 1971; Faber
et al. 2010; Corrigan et al. 2011), followed by 166 medicinal plant species frequently gathered
in the Eastern Cape province (Dold and Cocks, 2002; Cocks and Dold, 2006). Furthermore, the
use patterns of important plants of the Khoi-San (van Wyk and Gericke, 2000; van Wyk, 2008;
De Beer and van Wyk, 2011; Nortje and Van Wyk, 2015) are worthy of mentioning, including
some important contributions in the form of unpublished theses such as Van der Merwe (2000)
on Tswana ethnoveterinary medicinal plants, Mabogo (1990) on Venda ethnobotany, Eckert
(2000) on Northern Ndebele resource management and Rankoana (2000) on the ethnobotany
of Dikgale community (North Sotho).
24
Currently, little is known regarding the full extent of useful plants of Ndebele and Swazi
ethnic cultures (two of the five ethnic cultures) in our study area and there is still a need for
comprehensive and systematic documentation of the useful plants of these ethnic cultures as
well as their human-plant interactions (van Wyk,2002).
2.3 CURRENT MAJOR CONCEPTS AND PROBLEM IN ETHNOBOTANY
2.3.1 Historic context
The concept of ethnobotany since its introduction by Harshberger in 1896 has been modified
several times in terms of its definition, objectives and methods, due to its multifaceted nature.
It encompasses areas of scientific knowledge as diverse as botany, anthropology and ecology,
to name a few (de Albuquerque & Hurrell,2010). From the 1950s through the 1980s, the
cognitive and classificatory approach was concerned with the people of certain regions
classifying and ordering the plants in their environments. Finally, after the 1980s, the focus of
ethnobotanical research turned to its socio-ecological aspects, which incorporated ecological
tools, techniques and statistical measurements (Clément,1998; Oliveira et al. 2010). Over the
years, debates about the methods and purpose of ethnobotany have increased in scientific
research, specialised publications, associations and scientific events related to aspects of local
knowledge. These scientific debates in ethnobotany have naturally modified the perspective
of work in this field. From the end of the nineteenth century through the middle of the
twentieth century, ethnobotany, ethnobotanists were concerned with recording uses and
common names in a locality.
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2.3.2 Approaches to Ethnobotany
Ethnobotany is an interdisciplinary field, that combines the aspects of botany and ethnology
as well as many others, has been approached by researchers from two perspectives: the
practical or utilitarian and, the philosophical (Alcorn,1995). The "practical or the utilitarian
approach" is equated to asking a basic question as "What good is this plant?"(Alcorn,1995).
This solitary question has been the approach used by early ethnobotanists including
Harshberger (Alcorn,1995). Alcorn further suggested an additional basic question: " What
does this plant signify or what is its cultural meaning?" (Alcorn,1995). Similarly, Brent Berlin
framed the above questions by "How and in what ways do humans use nature?" And "How
do human societies view nature?"(Berlin,1992). Additionally, even Schultes, who focused
mostly on the utilitarian value of plants, described ethnobotany's scope so that it included
concepts about plant life (Schultes,1992).
The investigation of the meaning of plants within a culture largely has been the domain of
anthropologists while both anthropologists and botanists have investigated the utilitarian
aspects of plants. The utilitarian approach still dominates today's research agenda (Schultes,
1992). Further, Victoria Toledo describes ethnobotany as " a discipline-oriented towards the
exploration of new plant resources able to be converted into new raw materials for the
industry" (Toledo,1995). Whereas Michael Balick discusses the role of researchers in
germplasm conservation, ethnobotanists often have the opportunity to collect valuable
genetic material, because several researchers work in remote areas (Balick,1995). Both
anthropologists and botanists have examined practical aspects while in contrast, the
theoretical viewpoint has been the exclusive domain of anthropologists (Balick,1995).
26
2.3.3 Major fields of Ethnobotany
The science of ethnobotany encompasses four major fields, including (1) basic documentation
of traditional botanical knowledge; (2) quantitative evaluation of the use and management of
botanical resources; (3) experimental assessment of the benefits derived from plants, both for
subsistence and commercial ends, and (4) applied ethnobotany.
This section reviews three of the four major fields in ethnobotany namely: Field of quantitative
evaluation of the use and management of botanical resources (evaluation of use-values,
relative use-values, the proportion of agreement, and preference ranking; Phillips and
Gentry,1993 a, 1993 b; Assogbadjo et al. 2011; Avocevou-Ayisso et al. 2011); the field of
experimental assessment of the benefits derived from plants, both for subsistence and
commercial ends (assessment of benefits, hypothesis testing and prediction; Soleri and
Smith,1995; de Albuquerque,2006; Alencar et al. 2009); and finally, the field of applied
ethnobotany(applied projects that seek to maximise the value that local people attain from
their ecological knowledge and resources(Gustafson et al. 1992; Cox,1994).
Moreover, the ethnobotany as science encompasses three different types of studies including
descriptive studies, causality studies, and diagnostic studies (de Albuquerque and Hanazaki,
2009). "Descriptive studies" usually define a set of useful plants of a given human community
within a wide range of utilitarian categories or a certain cultural domain, while "causality
studies" seek to determine factors that could explain the use and knowledge of plants. And
finally, the "diagnostic studies" are studies that are relatively new to ethnobotanical
investigations, and are intended to seek and test the efficiency and validity of certain
techniques and methods used in ethnobotany (see Reyes-Garcia et al. 2006 a; Silva et al. 2005;
Monteiro et al. 2008; Tardio and Pardo-de-Santayana, 2008).
27
The present thesis is part of what is called "causality studies" that seek to determine factors
that could explain the use and knowledge of plants. This type of research utilises hypotheticaldeductive reasoning to test its hypotheses (Phillips and Gentry 1993 a, 1993 b; Vanderbroek
et al. 2004; Almeida et al. 2005; Estomba et al. 2006; see also Höft et al. 1999).
2.3.3.1 Quantitative ethnobotany
The concept of quantification is defined as the application of quantitative techniques to the
direct analysis of contemporary plant use data (Prance,1987, Phillips,1996). Quantification in
ethnobotany encompasses aspects related to the analysis of people's knowledge of the uses of
plant species. Further, it includes the use of indices or quantitative techniques and the
application of statistical analyses.
The term "quantitative ethnobotany" was cited first by Balée (1987) and has appeared in
various studies to confer greater robustness on the analysed data (de Albuquerque, 2009).
However, for quantification to be effective, it is necessary to trace the objectives of the work
and to define adequate methods for the questions; otherwise, an unreliable interpretation of
the data could be generated (Leonti et al. 2020). Quantitative ethnobotany was found to be
contributing to the methodological advances of ethnobotany (de Albuquerque, 2010 b),
however, de Albuquerque (2010 b) further stated that the term quantitative has become
synonymous with quantification in ethnobotany, which is not necessarily associated with the
hypothetical-deductive method that was used in the original design of Phillips and Gentry
(1993 a).
Similarly, in the last decades, ethnobotanists have broadened the discipline's methods and
goals resulting in a shift from purely descriptive to more quantitative approaches (Carneiro,
28
1978; Trotter and Logan,1986; Prance et al. 1987; Johns et al. 1990; Phillips and Gentry, 1993;
Phillips et al. 1994; Galeano, 2000; Macia et al. 2001; Collins et al. 2006; Reyes-Garcia et al. 2007;
Vandebroek, 2010).
Nonetheless, the incorporation of different methodologies and approaches by ethnobotanical
researchers highlights the need for systematisation and consolidation of current studies and
practices. Until recently, data analysis from a quantitative perspective gave ethnobotany a
subjective and descriptive character in inventories of useful plants, but this analysis has
gradually assumed a less subjective and more experimental character. Ethnobotanists by
combining ethnobotanical and ecological data have highlighted the importance of the tropical
forest to traditional peoples and, conversely, the profound effects that indigenous people may
have on "wild" vegetation (Anderson & Posey,1989; Balée & Gely,1989; Boom,1985). Since the
1990s, ethnobotanists' research of local knowledge has incorporated quantitative analysis
tools to estimate the relationship between biological and cultural diversity and to examine the
importance of natural resources for local populations (Medeiros et al. 2011). Moreover,
quantification and hypothesis-testing help to generate quality information. The techniques
used in this respect include cluster, regression analysis, analysis of variance and log-linear
modelling. Thus, quantification gave researchers the ability to assess people's knowledge of
plant resources and incorporate the perspective of many informants, as noted by Fraser &
Junqueira (2010) as some wild plant resources are severely threatened by habitat loss and
species selective overexploitation.
2.3.3.2 First quantitative data in ethnobotany
The quantification of ethnobotanical data was first undertaken in a study of the Chacabo
Indians of Amazonian Bolivia (Boom,1987). This was a major step toward a much more
29
rigorous methodology, where a statistical approach could be utilised. An ethnobotanical
study of 360 vascular plant species known by the Chacabo Indians of Amazonian Bolivia
identified plant uses for 305 species. This was a very important step that was followed later
by Phillips and Gentry (1993a) while working with mestizo people in Tambopata, Peru, they
proposed a new quantitative method for ethnobotanical studies. They studied three plots in
seven different forest types in a total of 6.1 hectares. Family use values were calculated for
plants employed in commerce, construction, food, technology, and medicine (Phillips &
Gentry,1993 b).
2.3.3.3 Experimental assessment and Hypothesis-testing
Dating from the first half of the nineteenth century, ethnobotany consisted of descriptive texts
that sought to list plants and their uses (Hunn, 2007; de Albuquerque et al. 2013; Gaoue et al.
2017). Over the last four decades, however, this type of descriptive contribution has been,
largely criticised on the basis that, while the information provided might be of interest, the
knowledge gained has a fragile or even non-existent theoretical basis and little methodological
rigour (see Phillips & Gentry,1993; de Albuquerque,2009, 2013; Gaoue et al. 2017). Due to
rapid changes in livelihood, resulting in rapid changes in the way people relate to the
environment, making the relationship between people and plants increasingly complex,
ethnobotanists have been increasingly compelled to move beyond descriptive studies and
develop a theoretical framework that explains human behaviour with plant resource use
(Gaoue et al. 2017).
In this thesis, both theory and hypothesis are defined according to (Krebs, 2000; Quinn and
Dunham,1983). Accordingly, hypotheses are proposed explanations of observed natural
phenomena or patterns, whereas a theory is an integral and hierarchical set of empirical
30
hypotheses that together explain a significant fraction of scientific observation (Krebs, 2000).
As such, theories are hypotheses which have been rigorously tested and for which support
for the generalisation has been found. Most of these theories studied in ethnobotany are
adapted from ecology or related disciplines and serve as possible explanations for
ethnobotanical patterns.
2.3.3.4 Applied ethnobotany
Applied ethnobotany can be defined as ethnobotany applied to conservation and sustainable
development. Applied ethnobotany draws on both personal (including traditional) and
scientific forms of knowledge, allowing comparisons and integration for the benefits of
conservation and sustainable development, especially for developing countries (Hamilton et
al. 2003). Unlike traditional ethnobotanical studies, applied ones are designed from the outset
using theoretical methods and references to address practical issues (Hamilton et al. 2003).
Thus, applied ethnobotany is an approach within ethnobotanical research that aims to meet
specific demands. For example, applied ethnobotany can concentrate on efforts for the
conservation and sustainable use of biodiversity or the development of drugs of medical and
/or pharmacological interest (Hamilton et al. 2003).
Applied ethnobotany and its methods are seen as a local, decentralised approach, where local
people participate and contribute to resolving conservation and resource management
problems in resourceful ways, rather than being part of the problem (Cunningham,2001).
Furthermore, applied ethnobotany encompasses some fundamental strengths in its
approaches and methods that can be used in the field of ethnobotany and these strengths are
as follows: (a)-They allow the knowledge, wisdom and practices of local people to play fuller
roles in identifying and finding solutions to problems of conservation and sustainable
31
development. (b)-Local people are involved fundamentally in investigations so that there is a
better chance of "buy-in". (c)- Realistic case- studies of ways of balancing conservation with
use become available to inform the evolution of national and other higher-level policies
(Hamilton et al. 2003).
As result of these strengths, applied ethnobotany is expected therefore, to play a significant
part in addressing the different challenges in ethnobotany including : conservation of plants
(including varieties of crops) and other forms of biological diversity; botanical inventories and
assessments of the conservation status species; sustainability in supplies of wild plant
resources, including of non-timber products; enhanced food security, nutrition and
healthcare; preservation, recovery and diffusion of local botanical knowledge and wisdom;
reinforcement of ethnic and national identity; greater security of land tenure and resource
ownership; assertion of the rights of local and indigenous people; agreements on the rights of
communities in protected areas; identification and development of new economic products
from plants, for instance crafts, foods, herbal medicines and horticultural plants and
contributions to new drug development (Campbell & Luckert,2002; Cruells,1994;
Cunningham, 2001; Laird,2002; Martin, 1995; Schultes & von Reis,1995).
2.3.3.5 Three general approaches to analysing quantitative ethnobotanical data
Quantitative approaches used for analysing informant knowledge are grouped under three
categories (Phillips & Gentry,1993 b); informant consensus, subjective allocation, and uses
totalled.
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Informant consensus
This method is used to establish the relative importance of each use, directly from the degree
of consensus in informants' responses. It requires a highly structured questionnaire. The
relative importance of each species is evaluated by the proportion of respondents who cited
it. The importance of different plants or uses is assessed by the proportion of informants who
independently report knowledge of a given or who claim to have used a plant in a specific
way (Adu-Tutu et al. 1979; Angels Bonet et al. 1992; Elvin-Lewis et al. 1985; Johns et al. 1990,
Johns & Kimanani,1991; Joly et al. 1987; Kainer & Duryea, 1992; Phillips & Gentry,1993 a,1993
b; Phillips et al. 1994; Trotter & Logan, 1986). The advantages of this approach are that this
yields data that can be tested statistically, and it is relatively reliable despite being timeconsuming because individual informants or households must be interviewed separately. In
general, procedures based on "informant consensus" tend to be more objective as they are
designed to eliminate investigator bias in attributing relative importance to a given plant
(Phillips,1996).
Subjective allocation
Subjective allocation is a set of techniques for evaluating the value or importance of a species
according to the members of a specific community. The subjective nature of this approach
stems from researchers who assign predetermined values to plants. Among the main
examples of subjective allocation is the cultural significance index (Turner,1988; Stoffle et al.
1990; Silva et al. 2010). In the subjective allocation approach, the relative importance of each
use is subjectively assigned by the researcher. The importance of different plants or uses is
estimated by the researcher based on his or her assessment of the cultural significance of each
plant or use (Berlin et al. 1966, 1974; Lee,1979; Pinedo-Vasquez et al. 1990; Prance et al. 1987;
33
Stoffle et al. 1990; Turner,1973, 1988). This is a quicker approach than informant consensus
for evaluating the cultural significance of plants. Yet, compared with informant consensus,
the results are more subjective and less amenable to statistical analysis. Data for this kind of
analysis can be collected by one or more interview techniques or by direct observation or by
both.
Uses totalled
Under this quantitative category, there is no attempt to quantify the relative importance of
each plant used. However, the number of uses (or activities) is simply totalled, by category of
plant use, plant taxon, or vegetation type. Not surprisingly this has been the most popular
approach since it is the fastest and most straightforward way to quantify ethnobotanical data
(Anderson,1990,1991; Anderson & Posey,1989; Balée & Gely,1989; Bennett,1992; Boom,
1985,1989,1990; Bye,1995; Kapur et al. 1992; Moerman,1979,1991; Paz y Miño et al. 1991, Salick,
1992; Toledo et al. 1992; Unruh & Alcorn,1988).
But uses totalled has two principal disadvantages: First, minor uses are treated as equivalent
to even the most important of uses. Second, the total numbers of uses recorded may be more
a function of research effort than of the relative significance of each use, plant, or vegetation
type. Like those for subjective allocation, data for this kind of analysis are often collected with
one or more interview techniques, and sometimes by direct observation.
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2.3.3.6 Major problem in Ethnobotany
Ethnobotany, as the science of human-plant interactions (Prance et al. 1987), has for long been
a discipline that largely has been concerned with its relationship to theory. In this section,
however, I discussed some of the trends related to the major problem existing currently in
ethnobotany.
In its early stages, ethnobotanical research largely consisted of contextual lists of plants with
their associated preparation and uses in remote areas (Balick,1996; Etkin,1988). But more
recently, the focus on documenting traditional uses of plants is increasingly being questioned.
Specifically, several authors (e.g., de Albuquerque et al. 2006; Ford and Gaoue, 2017; Hart et
al. 2017) have now called for a shift toward more hypothesis-driven approach in ethnobotany
because that is the only way human-plant interactions can be better understood. Despite the
recent multiple calls for the shift, most recent ethnobotanical studies still prefer the traditional
knowledge documentation approach (e.g., Leso et al. 2017). As a result of such approach, the
discipline of ethnobotany has been criticised as " weak", "soft subject", "hardcore science" or
" pseudoscience" (de Albuquerque and Hanazaki, 2009; Alexiades,1996).
These trends still ongoing in the field despite a few examples to the contrary. However, the
exception includes the theoretically grounded, extensive body of research in cognitive
ethnobotany (e.g., Atran,1998; Alexiades,1996; Brown,1977; Conklin, 1954; Hunn,1975; Medin
and Atran,2004; Turner et al. 2000) which led to general principles of folk biological
classification (Berlin et al. 1973; Brown, 2000).
35
2.4 CALL FOR A PARADIGM SHIFT AND RIGOROUS QUANTITATIVE DATA
Ethnobotany has incorporated over time, different theories from areas such as anthropology,
ecology, genetics, evolution, and economy, and this interdisciplinary exchange have become
allied with the studies documenting traditional botanical knowledge. As such incorporation
evolved, the science of ethnobotany becomes intrinsically interdisciplinary, thus making it
susceptible to charges of being imprecise and vague. In contrast, the scientific rigour of
ethnobotanical research has increased dramatically in the past two decades due to the
adoption of quantitative methods (Phillips,1996), by hypotheses, reproducible methods, and
statistical comparable measures of variation.
Forty-two years ago, Ford (1978) questioned whether or not the discipline has a unifying
theory, while Phillips and Gentry (1993a) criticized the predominant use of descriptive studies
in ethnobotany as well as the lack of theoretical frameworks and/or methodological rigour.
This self-criticism successfully prompted more recent ethnobotanical studies to follow the
lead of Begossi (1996) by incorporating ecological methods in ethnobotany. As a result, an
increasing number of studies, in efforts to include quantitative rigour, utilised species-area
curves, to estimate the diversity of species used by cultural groups, and ethnobotanical indices
(see Hoffman and Gallaher, 2007).
International and local meaningful protocols and procedures for conducting ethical research
are now considered essential components of the research process. Recent efforts have focused
on advancing ethnobotanical education based on interdisciplinary training, core concepts,
and competencies that bridge the natural and social sciences (McClatchey et al. 2013). Though
important, these approaches have not addressed Phillips and Gentry's (1993 a, b) call for
formulating a theoretical framework, emphasizing instead on methodological rigour (de
36
Albuquerque, 2009) and generalised use of ethnobotanical indices (Hoffman and
Gallaher,2007). Acknowledging the persistent lack of theory-inspired research in
ethnobotany, Martin (2007) detailed precisely how this progress could be achieved with a
hypothetico-deductive approach. Both Bennett (2005) and de Albuquerque and Hanazaki et
al. (2009) repeated the call for 'less quantification' and more theory-inspired and hypothesisdriven research in ethnobotany. Also, Bennett (2005) noted that ethnobotanical education also
needs a major shift to meet the needs of the discipline's evolution. The challenges faced by
ethnobotany are similar to those of other sister disciplines. For example, in the 1990s several
prominent ecologists questioned if the discipline of ecology had general laws or a unifying
theory (Aarssen, 1997; Lawton, 1999; Marquet et al. 2014; Weiner, 1995). As a result of this selfreflection, ecology progressed as a discipline, moving from simply documenting patterns to
understanding the underpinning processes that generate ecological patterns across time and
spatial scales. Ethnobotany, drawing inspiration from sister disciplines (ecology, evolution,
anthropology, archaeology, etc.), can do the same (Salick et al. 2003). The most promising
hypothesis-driven approaches to date have come from testing whether patterns of human
selection for medicinal plants align with the predictions of the theoretical frameworks from
ecology (e.g., de Albuquerque,2006; de Albuquerque and Oliveira, 2007; Alencar et al. 2010;
Bennett, 2007; Bennett and Husby, 2008; Vandebroek and Balick, 2012; Reyes-García et al.
2013b; Quiroz and van Andel, 2015: Voeks and Leony, 2004; Voeks, 2007). If there is not such
a conceptual paradigm shift in ethnobotany, some questions that have motivated researchers
for decades regarding the use of a more hypothesis-driven approach, will remain unresolved
or poorly answered. Questions such as " Why, when, how and where people select particular
plants for a wide range of uses must be investigated.
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2.5 SCOPE OF THE PRESENT THESIS
This research project is part of what is called "causalities studies" (see Section 2.3.2), that seek
to determine factors that can explain the use and knowledge of plants (evaluation of usevalues, relative use-values, preference ranking), thus moving from the traditional
identification and documentation of indigenous plants and their subsequent selection as
medicinal plants in the Mpumalanga province. Given the research aim and objectives, as
delineated above in chapter 1, the scope of this thesis will focus on a greater scientific rigour
in terms of setting and testing of ethnobotanical hypotheses, and their quantification through
different predictions. Many early ethnobotanical studies, as some still are today, were largely
or entirely descriptive, being concerned essentially with documenting the local names and
uses of plants (Cunnigham,1997; Etkin & Meilleur,1993; Fernandez, 2002; Fonseca,2000;
Martinez, 2002).
The present thesis, however, falls within the new line of ethnobotanical research and, more
importantly, aims to contribute to filling the lack or scanty theory-testing studies in
ethnobotany and can inform environmental management. In so doing, this thesis: i) advances
our understanding of human-plant interactions, ii) contributes to the long-overdue critical
mass of primary literature required to develop meta-analyses and new theories in
ethnobotany.
2.6 BRIEF SUMMARY OF LITERATURE REVIEWED
Three ethnobotanical components were reviewed in chapter 2, and more importantly, they
were very relevant to the topic studied in this thesis. The chapter described the concepts, the
major existing problem and critics born out of the major problem, approaches and majors’
fields, as well as the relative scope of the ethnobotany as science, which prompted the call for
38
a paradigm shift and the need for more quantitative data analysis leading to the adoption of
theories driven and hypothesis testing in ethnobotany. The literature reviewed has revealed
some interactions between human-plants and folk taxonomies, plant-related mythology,
ethnoveterinary medicine and pre-colonial plant use especially for some ethnic culture that
are still poorly studied and recorded, and more importantly, there is still a lack of rigorous of
quantitative data for most of the studies in ethnobotany.
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CHAPTER 3
GENERAL PATTERNS OF MEDICINAL PLANTS SELECTION BY LOCAL
COMMUNITIES
“Testing the non‑random hypothesis of medicinal plant selection using the
woody flora of the Mpumalanga Province, South Africa”
Isidore Muleba1. Kowiyou Yessoufou1. Isaac T. Rampedi1
Received: 7 August 2019 / Accepted: 29 April 2020
© Springer Nature B.V. 2020
Abstract
Medicinal plants have been used by local communities to treat all sorts of diseases, and this
unique indigenous knowledge has been documented in various studies. However, using this
vast knowledge to formulate and test hypothesis in ethnobotany is not yet a common practice
in the discipline despite recent calls for more hypothesis-driven ethnobotanical researches.
Here, we collected ethnobotanical data on 811 woody plant species in the Mpumalanga
Province of South Africa to test the non-random hypothesis of medicinal plant selection,
which predicts a positive correlation between the size of plant families and the number of
medicinal plants in the families. We tested this hypothesis by fitting the commonly used
simple linear regression model and the negative binomial model. Our analysis confirmed the
hypothesis and revealed that some plant families are over-utilised—i.e., contain more
medicinal plants than expected. The identification of over-utilised families is the first step
towards the prioritisation of research efforts for drug discovery. The proportion of overutilised families ranges from 50% (linear regression with untransformed data) and 55% (linear
regression after log–log transformation) to 34% (negative binomial model). With the simple
linear model and untransformed data, the top over-utilised families are Fabaceae (residual =
+ 34.44), Apocynaceae (+ 5.82) and Phyllanthaceae (+ 5.53). The log-transformed model
confirms these three families as the top over-utilised families but in a slightly different
sequence: Fabaceae (+ 1.55), Phyllanthaceae (+ 0.83) and Apocynaceae (+ 0.79). However, using
the negative binomial model, Fabaceae is no longer even part of the top 10 over-utilised
families, which are now Phyllanthaceae (+ 2.09), Apocynaceae (+ 1.51), Loganiaceae (+ 1.48),
Rhamnaceae (+ 1.48), Sapotaceae (+ 1.48), Oleaceae (+ 1.39), Salicaceae (+ 1.39), Clusiaceae (+
1.30), Boraginaceae (+ 1.28) and Lamiaceae (+ 1.18). This suggests that the relative medicinal
value of some families may have been over-estimated in comparison with others. Our study
is an illustration of the need to apply appropriate model while testing ethnobotanical
hypotheses to inform priority setting for drug discovery.
Keywords Ethnobotanical hypothesis · Fabaceae · Generalised linear model with negative
binomial · Phyllanthaceae
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3.1 INTRODUCTION
A tremendous amount of data on medicinal plant uses has been documented worldwide over
the years. Such data may include plants that are used to treat particular diseases, plant organs
used, how the plant parts or organs are collected and how such medicines are prepared (York
et al. 2011; Elansary et al. 2015; Leso et al. 2017). In the light of this wealthy dataset available
in ethnobotany, some authors indicated that we now have enough information with which
we should be formulating and testing theories and hypotheses that can advance the scope of
ethnobotany as a scientific discipline (e.g., Albuquerque et al. 2006; Ford and Gaoue 2017;
Gaoue et al. 2017; Hart et al. 2017).
Such paradigm shifts towards a more hypothesis or theory-driven ethnobotany are necessary
to make ethnobotany a stronger scientific discipline with theories and hypotheses that can be
used to predict new medicinal plant uses as well as explain plant-human interactions (Gaoue
et al. 2017). Interesting questions that can be investigated for a better understanding of humanplant interactions are as follows: is traditional medicine a placebo? Why some plants in a
particular family are predominantly used or over-utilised in some pharmacopoeias while
other plants are less used (under-utilised)? To answer this question, a hypothesis has been
proposed, termed a "non-random hypothesis" (Moerman, 1979,1991,1996), which predicts that
large families are more likely to be richer in medicinal plants than small-sized families. This
hypothesis implies that medicinal plants are not randomly selected by local communities such
that a linear positive relationship is expected between the number of medicinal plants in
families and the size of those families (Moerman,1979). Initially, Moerman (1979) formulated
and tested this hypothesis to demonstrate that the traditional medicine of Native Americans
41
was not a placebo. Because of this non-random selection, some plant families tend to be overor under-represented in a given pharmacopoeia (Moerman,1979,1991; Moerman and
Estabrook, 2003; Ford and Gaoue, 2017). This implies that plant family can become a strong
determinant of plant use-value (Phillips and Gentry,1993), and in one of his early studies,
Moerman (1991) already explained this by the fact that species in the same family, due to their
evolutionary relatedness, share some characteristics of plant defence inherited from common
ancestors, which influence their physiology and effectiveness as medicines. Using a
phylogenetic approach, recent studies confirmed that closely related plant families are more
likely to have similar medicinal uses than those that are phylogenetically distant (SaslisLagoudakis et al. 2013; Yessoufou et al. 2015). Several studies tested the non-random
hypothesis in several geographic contexts, e.g., in Amazonian Ecuador (Bennett and Husby,
2008), in Belize (Amiguet et al. 2006), in Kashmir (Kapur et al. 1992), and recently in Hawai'i,
USA (Ford and Gaoue, 2017) and Ecuadorian Amazon (Robles-Arias et al. 2020). These studies
reported strong support for the hypothesis. In particular, Robles-Arias et al. (2020)
demonstrated that the prediction of the hypothesis could be gender-specific. Nonetheless,
such hypothesis-driven ethnobotanical studies are scant particularly in plant-rich countries
with wealthy medicinal knowledge.
South Africa is one of these species-rich families, with a remarkable plant diversity estimated
at approximately 24,000 vascular plants, but where ethnobotanical studies still are less theorydriven. The different uses of medicinal plants are very well documented, e.g., ~3000 medicinal
plants are recorded in the country, including 350 species known to be commonly used and
traded (e.g., van Wyk and Gericke,2000; Fennell et al. 2004; van Wyk, 2008; York et al. 2011;
Elansary et al. 2015; Leso et al. 2017).
42
Furthermore, in studies that tested the non-random hypothesis, the methodological
approaches used could be improved. For example, by fitting the simple linear model to the
untransformed data he collected, Moerman (1979) did not account for normal residuals and
homogeneity of variance. Recently, Ford and Gaoue (2017) have fitted the same model but on
log-transformed data to account for that bias. Even so, the log-transformation performs poorly
on "count data" (here, the number of medicinal plants) in comparison with a generalised linear
model with negative binomial (see O'Hara and Kotze, 2010). The application of these various
statistics whilst ignoring their limitation is a potential source of bias, not necessarily in the
overall outcome of hypothesis testing, but more critically for the identification of over-utilised
versus under-utilised families. In the present study, the non-random hypothesis of medicinal
plant selection in the Mpumalanga province of South Africa was tested. Specifically, the
different statistical approaches to explore the relationships between the number of known
medicinal plants in families and the size of the family in the province were applied.
3.2. MATERIAL AND METHODS
3.2.1 Study area
Mpumalanga is one of the nine South African provinces within the Greater Maputaland
Pondoland Albany Biodiversity Hotspot, harbouring the southern half of the Kruger National
Park and other centres of endemism. The Mpumalanga Province is divided into three districts,
namely Gert Sibande, Nkangala, and Ehlanzeni. Local communities are diverse in culture, and
together with language discrepancies, there is a rich base of traditional knowledge. These
communities include Siswati (30%), while 26% of the inhabitants speak isiZulu (26%),
isiNdebele (10.3%), Sepedi (21.2%) and Xitsonga (11.6%) (Tshikalang et al. 2016). Four major
43
vegetation types are dominant in the study area, namely the highveld grasslands, escarpment
grassland-forest mosaic, eastern Lowveld savannah and the north-western bushveld
savannah (Schmidt et al. 2007). These vegetation types are represented in three distinct
biomes: forest, savannah, and grassland (Schmidt et al. 2007). The rainfall varies from a
minimum of 440 mm in the north to a maximum of 740 mm in the south of the Kruger National
Park (KNP) (Venter,1990). Mean annual temperature is around 21–23 °C, but in summer
temperatures often exceed 38 °C, and frost can occur sporadically during winter.
3.2.2 Data collection
Data on the floristic composition of the Mpumalanga Province were collected through
intensive four-year fieldwork conducted from 2008 to 2012 by (Yessoufou, 2012). These data
were supplemented by an existing database, i.e., the book entitled Trees and shrubs of
Mpumalanga and Kruger National Park by Schmidt et al. (2007). This book contains both
floristic and ethnobotanical knowledge of the region collected for more than 10 years of
fieldwork. This book provided a unique botanical knowledge (including some medicinal uses)
for a comprehensive checklist of 811 plant species representing 97 botanical families, of which
321 were reported to have some medicinal uses (Schmidt et al. 2007). Also, data were collected
from PRECIS (SANBI,2005), a comprehensive inventory of ethnomedicinal flora of Southern
Africa containing 800,000 records of taxa grouped by order and regions (Magill et al. 1983;
Germishuizen and Meyer, 2003).
More importantly, the ethnobotanical data were further collected from Prelude medicinal
plants Database (https:// www.Africanmuseum.be/en/. From these datasets, two variables
were selected including (1) the total number of plants species per family in the province and
(2) the total number of medicinal plants recorded for each family in the province
44
3.2.3 Data analysis
All analyses were done in R (R Development core Team 2017) using several medicinal species
recorded per families as response variable (count data) and the total number of species
documented in the province for each family as a predictive variable. Firstly, a simple linear
model was fitted (model 1) to the untransformed data as commonly done in previous studies
(Amiguet et al. 2006; Moerman,1996,1979). Followed by a test for normality of the residuals.
As this analysis indicated non-normality (Figure S1), the response and predictor variables
were then log(x+1)-transformed to address the normality issues (Figure 3.3). In the (model 2),
a general linear model was fitted to the transformed variables as done in a few recent studies
(e.g., Ford and Gaoue, 2017). Finally, because of the poor performance of simple linear
regression with log-transformation of "count data" compared to the generalised linear model
with negative binomial (see O'Hara and Kotze, 2010), a negative binomial model (model 3)
was fitted to the dataset (see Zeileis et al. 2008; O'Hara and Kotze, 2010). For each of these
models, over-utilised families were identified as those with positive residuals; this means
these families contain a higher number of recorded medicinal species than would be expected
from the model fitted.
3.3 RESULTS
From the woody flora of the Mpumalanga province, forty percent (~40%) of medicinal plants
were recorded from almost seventy-six (~76%) of woody plant families in this study area
(Table 3.1). Our analysis revealed that some plant families are over-utilised, while others are
under-utilised (Figure 2.3; Table 3.1). The proportion of over-utilised families ranges from 50%
in line with Moerman's linear regression approach through 55% (linear regression after log-
45
log transformation) to 34% (negative binomial model). Following Moerman's approach, the
top over-utilised families are Fabaceae (residual= +34.44), Apocynaceae (+5.82) and
Phyllanthaceae (+5.53). The log-transformed model confirms these three families as the top
over-utilised families but in a slightly different sequence: Fabaceae (+1.55), Phyllanthaceae
(+0.83) and Apocynaceae (+0.79). However, using the negative binomial model, Fabaceae is
no longer even part of the top 10 over-utilised families, which are now: Phyllanthaceae (+2.09),
Apocynaceae (+1.51), Loganiaceae (+1.48), Rhamnaceae (+1.48), Sapotaceae (+1.48), Oleaceae
(+1.39), Salicaceae (+1.39), Clusiaceae (+1.30), Boraginaceae (+1.28) and Lamiaceae (+1.18)
(Table 3.1). The top 10 under-utilised families comprise Celastraceae (− 0.05), Monimiaceae (−
0.06), Aquifoliaceae, Arecaceae, Canellaceae, Cornaceae, Gentianaceae, Hernandiaceae,
Picrodendraceae and Piperaceae (− 0.06, each).
46
Figure 3.1: Diagnostic plots showing non-normality of the residuals of untransformed data
47
Figure 3.2: Diagnostic plots showing improved normality of the residuals of untransformed
data
48
Figure 3.3: Diagnostic using a negative binomial model. Relationships between the number of
medicinally used woody plants and the total number of woody plants per family in the
Mpumalanga Province, South Africa. The names of some families could not be read clearly,
because they are superposed; Table 3.1 presents the full list of plant families with their
residual values indicating their position with the fit lines. Fit lines of different models tested
are colour-coded. Families that are above of the fit line of a model are considered over-utilised
(have a positive residual), and families below the fit line are considered under-utilised (have
a negative residual)
49
3.4 DISCUSSION
Almost 40% of the total woody species have local medicinal applications as remedies to certain
illnesses, and this proportion is approximately three times higher than the proportion (12.5%)
of the known medicinal plants in South Africa (van Wyk and Gericke, 2000; Arnold et al. 2002;
Williams et al. 2013). In addition, the medicinal plants of the Mpumalanga province are,
however, well represented at the family level since they represent nearly 76% of woody plants
families in this province. This is perhaps indicative of the richness of the province in medicinal
flora, although we only focussed on woody flora, suggesting that the proportion of medicinal
plants is likely greater than what we report here if non-woody plants were included in the
analysis. Indeed, as suggested by the optimal defense theory, non-apparent species, that is,
species with short lifespans (herbaceous, early successional plants), are subjected to lower
herbivore pressure than apparent species (e.g., perennial, dominant plants, woody plants). As
a result, non-apparent plants produce "cheap" defenses but in high quality (e.g., alkaloids),
while apparent species invest quantitatively more in "expensive" defenses, e.g., lignins
(Feeny,1976). Consequently, more herbs are likely to be medicinal than woody plants (de
Albuquerque and Lucena,2005; da Silva et al. 2018). There is, therefore, a need for future
studies to incorporate herbaceous plants into their analysis to further test the non-random
hypothesis (or other theories).
50
Table 3.1 Residual values from various model fitting to medicinal data from Mpumalanga
province, South Africa
GLM, Generalized Linear Model; LM, Linear Model. Families are ranked based on the
residuals of the GLM with negative binomial. Family names in bold are those identified by
GLM with negative binomial as medicinally over-utilized
Families
Models fitted
GLM
with
negative LM
with
log LM
with
binomial
transformed data
untransformed data
Phyllanthaceae
2.09137599
0.835053937
5.53969331
Apocynaceae
1.512669883
0.797571948
5.822771068
Loganiaceae
1.483800427
0.54292917
2.654769982
Rhamnaceae
1.483800427
0.54292917
2.654769982
Sapotaceae
1.483800427
0.54292917
2.654769982
Oleaceae
1.395826781
0.764759196
2.884923327
Salicaceae
1.395826781
0.764759196
2.884923327
Clusiaceae
1.306267267
0.628796291
2.513231103
Boraginaceae
1.284008961
0.452975379
2.026462207
Lamiaceae
1.179202762
0.383068814
1.53969331
Ochnaceae
1.091813997
0.33070534
1.283077758
Vitaceae
1.091813997
0.33070534
1.283077758
Melianthaceae
1.054285932
0.716902316
2.256615552
Ebenaceae
1.028372859
0.653876636
3.707694395
Rutaceae
1.013622608
0.353145109
1.052924413
Capparaceae
0.987603461
0.447536572
1.566155516
Solanaceae
0.90086612
0.228918134
0.53969331
Annonaceae
0.890820041
0.40565274
1.513231103
Moraceae
0.780670125
0.219613716
0.052924413
Sapindaceae
0.67899315
0.095367151
-0.088614466
Bignoniaceae
0.644334221
0.119276287
0.398154431
Proteaceae
0.585792491
0.15184317
-0.690460035
51
Balanitaceae
0.541522014
0.429220243
1.256615552
Lauraceae
0.541522014
0.429220243
1.256615552
Polygalaceae
0.541522014
0.429220243
1.256615552
Urticaceae
0.541522014
0.429220243
1.256615552
Xanthorrhoeaceae 0.479787019
-0.016686618
-0.345230018
Cannabaceae
0.468902343
0.253933572
0.884923327
Malpighiaceae
0.468902343
0.253933572
0.884923327
Salvadoraceae
0.468902343
0.253933572
0.884923327
Combretaceae
0.464496089
0.317404399
-0.292305605
Myrtaceae
0.233749663
-0.176546974
-1.46030669
Araliaceae
0.175847832
-0.168405786
-0.601845569
Celastraceae
-0.050674529
0.336270859
-1.265843398
Monimiaceae
-0.060486287
0.270807822
0.628307776
Aquifoliaceae
-0.060486287
0.270807822
0.628307776
Arecaceae
-0.060486287
0.270807822
0.628307776
Canellaceae
-0.060486287
0.270807822
0.628307776
Cornacaeae
-0.060486287
0.270807822
0.628307776
Gentianaceae
-0.060486287
0.270807822
0.628307776
Hernandiaceae
-0.060486287
0.270807822
0.628307776
Picrodendraceae
-0.060486287
0.270807822
0.628307776
Piperaceae
-0.060486287
0.270807822
0.628307776
Pittosporaceae
-0.060486287
0.270807822
0.628307776
Plumbaginaceae
-0.060486287
0.270807822
0.628307776
Ranunculaceae
-0.060486287
0.270807822
0.628307776
Velloziaceae
-0.060486287
0.270807822
0.628307776
Asparagaceae
-0.121431586
0.023755135
0.256615552
Chrysobalanacea
-0.121431586
0.023755135
0.256615552
Cyatheaceae
-0.121431586
0.023755135
0.256615552
Podocarpaceae
-0.121431586
0.023755135
0.256615552
e
52
Gerrardinaceae
-0.121431586
0.023755135
0.256615552
Rhizophoraceae
-0.121431586
0.023755135
0.256615552
Achariaceae
-0.182802184
-0.151531536
-0.115076673
Stilbaceae
-0.182802184
-0.151531536
-0.115076673
Ulmaceae
-0.182802184
-0.151531536
-0.115076673
Scrophulariaceae
-0.192652143
-0.464229047
-2.46030669
Icacinaceae
-0.244562436
-0.287494441
-0.486768897
Myricaceae
-0.244562436
-0.287494441
-0.486768897
Passifloraceae
-0.244562436
-0.287494441
-0.486768897
Burseraceae
-0.266145623
-0.509383545
-2.831998914
Verbenaceae
-0.339455167
-0.551421378
-3.203691139
Fabaceae
-0.34385417
1.558579578
34.441851
Apiaceae
-0.369100661
-0.492509295
-1.230153345
Primulaceae
-0.431799265
-0.573870894
-1.601845569
Thymelaeceae
-0.431799265
-0.573870894
-1.601845569
Malvaceae
-0.48727429
0.376352255
-1.867688967
Asteraceae
-0.527738476
-0.259957106
-5.407382277
Rosaceae
-0.684479905
-0.820923581
-3.088614466
Acanthaceae
-0.874760528
-0.956886486
-4.203691139
Euphorbiaceae
-0.882966212
0.683522402
2.043696567
Buxaceae
-1.311885364
-0.422339358
-0.371692224
Connaraceae
-1.311885364
-0.422339358
-0.371692224
Cupressaceae
-1.311885364
-0.422339358
-0.371692224
Escalloniaceae
-1.311885364
-0.422339358
-0.371692224
Hamamelidaceae
-1.311885364
-0.422339358
-0.371692224
Linaceae
-1.311885364
-0.422339358
-0.371692224
Lythraceae
-1.311885364
-0.422339358
-0.371692224
Marattiaceae
-1.311885364
-0.422339358
-0.371692224
Melastomataceae
-1.311885364
-0.422339358
-0.371692224
Nyctaginaceae
-1.311885364
-0.422339358
-0.371692224
53
Onagraceae
-1.311885364
-0.422339358
-0.371692224
Osmundaceae
-1.311885364
-0.422339358
-0.371692224
Santalaceae
-1.311885364
-0.422339358
-0.371692224
Pedaliaceae
-1.311885364
-0.422339358
-0.371692224
Portulacaceae
-1.311885364
-0.422339358
-0.371692224
Menispermaceae
-1.311885364
-0.422339358
-0.371692224
Erythroxylaceae
-1.351560192
-0.669392045
-0.743384448
Kirkiaceae
-1.351560192
-0.669392045
-0.743384448
Putranjavaceae
-1.432931235
-0.980641621
-1.486768897
Streliziaceae
-1.474574712
-1.091731403
-1.858461121
Penaeaceae
-1.516818324
-1.185656476
-2.230153345
Ericaceae
-1.559630896
-1.267018074
-2.601845569
Flacourtiacae
-2.057984046
-1.794066979
-6.690460035
Anacardiaceae
-2.060053913
-0.473216099
-13.32799566
Rubiaceae
-2.895742049
-0.924598236
-19.41661012
Families are ranked based on the residuals of the GLM with negative binomial. Family names
in bold are those identified by GLM with negative binomial as medicinally over-utilized GLM
generalized linear model, LM linear model
3.5 CONCLUSION
This study provides an overview of the test of a non-random hypothesis to assess the general
patterns of medicinal plants selection by local communities in the Mpumalanga province.
Here, relatively three statistic approaches were fitted including a simple linear regression
analysis, with log-transformation of "count data" compared to the generalised linear model
with negative binomial to perform a robust test of the non-random hypothesis of medicinal
plant selection using the woody flora of the Mpumalanga province, South Africa. This thesis
assessed one of the most common ethnobotany theories developed in the 1970s
(Moerman,1979) the non-random plant theory. The non-random medicinal plant theory
54
suggests that some plant families are bound to contain fewer species with medicinal values
and uses than expected by chance. The premise is that species in these families are
evolutionary less likely to contain secondary chemistry efficient against disease. A nonrandom hypothesis of medicinal plant selection using the woody flora of the Mpumalanga
province was performed to determine the taxonomic patterns of medicinal plants. At least
two behaviours were observed in this study: certain families have higher medicinal value and
are therefore more frequently used than others. The finding reveals that chemical compounds
with medicinal value are not equally distributed among different botanical families (Gottlied
et al. 2002). Ethnobotany needs to understand the cultural reasons for a taxon's usage or its
avoidance in this context. Moreover, it was found that overused and underused species are
not the same for each one of the three statistical analysis approaches used in this thesis.
Conversely, certain families appear to behave discrepantly in particular contexts. Important
family such as Fabaceae for example was found overused and underused according to
statistical approaches used.
This finding is consistent with taxonomic patterns observed among previous studies in
Moerman's approach that shows that certain families are over-used and others under-used in
terms of the number of species in indigenous medicinal floras when compared to the overall
available flora of a specific region (Moerman,1979). This provides additional strong evidence
to the body of literature that plant use by indigenous people does not occur randomly and
more importantly, will add to the discussion on the non-random medicinal plants by
expanding the geographical range for this theory and proposing new ways of analysing the
data.
55
CHAPTER 4
THE USE OF ECOLOGICAL THEORIES TO GENERATE ETHNOBOTANICAL
KNOWLEDGE: APPARENCY THEORY AND RESOURCE AVAILABILITY
HYPOTHESIS IN MPUMALANGA, RSA
Abstract
An ethnobotanical study was conducted to examine the selection of medicinal plants in the
Mpumalanga province in South Africa, where the ecological apparency theory and the
resource availability hypothesis were tested based on patterns related to plant habits. A
Generalised Linear model (GLM) was fitted in each scenario, to investigate if plant height
predicts medicinal status (plant height as the predictor and medicinal status as the response
variable) and specifying the binomial error family, given that the response variable is binary
(a plant is either medicinal or not). In addition, a GLM model with a Gaussian error structure
was fitted to the height or life form data to test if these variables (height and life form) predict
the total number of recorded plants uses. In addition, a negative binomial GLM model was
fitted using the glm. nb function as implemented in the R library MASS (Venables and Ripley,
2002). Another GLM model was fitted this time to test the resource availability hypothesis,
using plant growth rate as a predictor with a standardised and continuous predictor variables
Hmax and growth rate prior to the analysis to facilitate the interpretation of results. The
analysis showed that plant maximum height correlates significantly and positively with
medicinal status (β=0.06±0.01, P<0.001), suggesting that taller plants tend to be more medicinal
than shorter ones. Whereas, plant height does not correlate with the probability of plant being
medicinally overused whether this probability is treated as a binomial variable (β=0.004±0.01,
P=0.68) or a proportion (β=0.002±0.007, P=0.77). The finding from the resource availability
hypothesis showed that there was no evidence that plant growth rate predicts neither
medicinal status (β=-18.64±52.71, P=0.72) nor the probability of plant being overused
irrespective of whether this probability is estimated as a binary variable (β=11.92±49.18,
P=0.80) or as a proportion (β=6.16±34.03, P=0.85). Furthermore, plant growth rate does not
correlate with Use Value (β=9.22±29.54, P=0.75) nor does it correlate with the total number of
uses (β=-9.64±26.38, P=0.71).
Keywords: Ethnobotany, diversification hypothesis testing, versatility hypothesis testing,
native plants, exotic plants.
56
4.1. INTRODUCTION
Plant secondary metabolites play a significant role in structuring interactions between plants
and the network of organisms that comprise terrestrial communities (Ehrlich & Raven,1964;
Berenbaum,1983; Roirberg & Isman,1992; Barbosa et al. 1991). Plant secondary metabolites
play key ecological roles by defending plants from herbivore and pathogens (Goncalves et al.
2016; de Albuquerque 2006;Fraenkel,1959; Odum & Pinkerton,1955; Ehrlich & Raven, 1964;
Whittaker & Feeny, 1971), providing oviposition and feeding cues (Da Costa & Jones,1971;
Raybould & Moyes, 2001; Macel & Vrieling, 2003; Nieminen et al. 2003), and attracting natural
enemies of herbivores (Turlings et al. 1990; Dicke & van Loon, 2000; Kessler & Baldwin, 2001)
in addition to conferring an array of physiological adaptions to plants, such as pigmentation
(e.g., flavonoids and carotenoids), protection against UV (e.g., flavonoids), and structure (e.g.,
lignins). All plants invest resources in secondary metabolite production (Fraenkel, 1959;
Dethier, 1954; Whittaker & Feeny,1971) which can incur a cost (reviewed in Huot et al. 2014)
but can also lead to increased plant fitness (Ehrlich & Raven, 1964; Cornell & Hawkins, 2003;
Agrawal et al. 2012; Moore et al. 2014).
In tropical forests, the evolutionary relationships between herbivores and plant have resulted
in an impressive variety of adaptations and interactions. Herbivore pressure has led to the
evolution of chemical, mechanical, and phenological defences in plants. Herbivores in turn
have evolved to cope with food plants that are trying to starve or poison them. These
relationships affect food webs, nutrient cycling, and community diversity, and thus every
organism in tropical forests. Moreover, the environment can also strongly modify the
57
phenotypic expression of defences in everyone. In their carbon/ nutrient hypothesis, Bryant
et al. (1983) suggest that resources present more than growth demands are put into defence.
However, little is known about the relative proportion of damage caused by specialist and
generalist herbivores in the indigenous forests of the Mpumalanga province, South Africa. Yet
such information is important for understanding nature and how plants allocate resources
between defensive and physiological functions.
Feeny (1975,1976) and Rhoades & Cates (1976) formulated hypotheses explaining the
evolution of plant defences based on plant apparency. Plant apparency, or commonness, is
an important indicator of the utilisation of plant resources (Feeny, 1976; Guèze et al. 2014).
The plant apparency hypothesis implies that more apparent plants suffer more herbivory and,
thus, invest more in quantitative chemical defenses (Feeny,1976; Smilanich et al. 2016; Soldati
et al. 2016; Strauss et al. 2015).
Apparency plants were predicted to adaptively produce quantitative chemical defences (i.e.,
high concentrations) because of the longevity of their leaf tissue. Quantitative compounds
were hypothesised to defend plant tissues by reducing herbivore growth rate through
decreased digestibility of consumed leaf tissue. As outlined in the original paper, these
defences evolved to be effective against both specialist and generalist herbivores (invertebrate
folivores), although specialist was predicted to be less abundant to these types (Feeny,1975).
In the present chapter, ecological and evolutionary outcomes of the interactions between
herbivores and their host plants in a subtropical forest of the Mpumalanga province were
examined. In particular, two of the recently reviewed hypotheses in ethnobotany (Gaoue et
al. 2017): the apparency theory and the resources availability hypothesis were investigated.
58
These hypotheses have been used to make predictions regarding plant life-history traits that
correspond to classes of antiherbivore defence and have also provided useful information for
understanding how plants allocate resources between defensive and physiological functions.
Further, fast-growing/short-lived species that can tolerate higher rates of herbivory and invest
more in quantitative defence (e.g., alkaloid) will have more medicinal and will be more sought
after than long-lived/slow-growing species which invest more in quantitative defences. This
might explain why some weeds and plants in disturbed areas or secondary vegetation are
sometimes more highly sought after locally for medicinal purposes than non-weedy and those
in primary forest (Stepp and Moerman, 2001; Voeks, 2004).
As a result of their interactions with herbivores, plants develop strategies to survive herbivory
in the form of e.g., chemical defences, and in return, herbivores tailor their responses to
survive plant chemical reactions (Ehrlich and Raven,1964; Thompson,1988; Endara and Coley,
2011), a mechanism referred to an 'arms race' (Endara and Coley, 2011). Humans use these
chemicals or secondary metabolites that plant engineer in response to herbivory for medicinal
purposes. These plant-herbivore interactions that lead to a human selection of medicinal
plants are framed in several hypotheses, of which, ecological apparency theory (Feeny, 1976)
and resource availability hypotheses Coley et al. 1985) are the most debated (Endara and
Coley 2011; Gaoue et al. 2017).
The ecological apparency hypothesis was the first attempt to explain patterns of plant
chemical defences (the quantity and the differences among plants) in response to herbivory
(Feeny, 1976; see also Rhoades and Cates, 1976). According to the hypothesis, more apparent
plants are long-lived plants bound to be found by herbivores (generalists and specialists), thus
under strong herbivory pressure, and therefore would invest highly in secondary metabolites,
59
e.g., tannins, to defend themselves against herbivores (Feeny,1976). In that case, tannins are
produced in high quantity to reduce the digestibility of plant leaves as a mechanism to avoid
herbivory from both generalist and specialists (quantitative defence). In contrast, unapparent
plants are short-lived plants i.e., plants with short lifespans, and this character makes it
difficult for specialist herbivores to feed on them as opposed to generalists. To survive most
of the herbivory from generalists, unapparent plants develop what Feeny (1976) referred to as
qualitative chemical defences by producing secondary 'inexpensive' metabolites in low
concentration and of small-sized molecules, e.g., alkaloids, effective in fighting herbivores,
thus making unapparent plants more likely medicinal than apparent plants (Gaoue et al.
2017). Consequently, herbaceous, early successional plants or short plants are more likely to
be used for medicine than "apparent" plants which are perennial, woody, and dominant
plants) (de Albuquerque and Lucena, 2005).
Like the prediction of the ecological apparency hypothesis, the resource availability
hypothesis also predicts that apparent plants spend more resources on defences unlike
unapparent plants (Coley,1987 a, b). However, the latter hypothesis, instead of linking
differences in defence investment across plant species to plant apparency, predicts that
differences in defence investment are rather determined by the cost/benefit ratio of such
investment (Coley et al. 1985). This means that a plant would invest resources in defences only
if the benefits out of the investments surpass the resources invested, that is the cost of
investment, irrespective of whether the plant is apparent or not and irrespective of the level
of herbivory. For example, it is not beneficial or profitable for a fast-growing plant to invest
resources heavily on defences since they can easily and quickly replace damaged organs, e.g.,
loss of leaves to herbivory or any form of harvest (Endara and Coley, 2011). As such, plants
60
growing in resources-rich environments (e.g., high-light, nutrient-rich habitats) vs. resourcepoor environment (e.g., low-light, nutrient-poor habitats) would not invest equally in
defences: in the former environment, plants would grow faster (high growth rate), synthesize
qualitative chemicals (e.g., alkaloids) with more likely medicinal bioactivity; in the latter
environment, plants would exhibit slow growth rate and investment heavily on quantitative
defences (to protect the costly investment in defences) that are less of medicinal importance
for human, e.g. tannin (Coley et al. 1985; Endara and Coley, 2011; Stamp, 2003). Due to this
strong connection to growth rate, the resource availability hypothesis is also referred to as
growth rate hypothesis (Coley,1987 a, b: Stamp, 2003). This might explain why some weeds
and plants in disturbed areas or secondary vegetation are sometimes more highly sought after
locally for medicinal purposes than non-weedy plants and those in primary forests (Stepp and
Moerman, 2001; Voeks, 2004).
Few studies have tested the above theories in ethnobotany. Of those that have, most found no
support for the ecological apparency theory, but they did provide support for the resource
availability hypothesis (Alencar et al. 2009; Almeida et al. 2005, 2012). Almeida et al. (2012)
found that plants from a low resource environment (especially trees) tended to have high
levels of quantitative and qualitative defense compounds and have higher antimicrobial
activity than plants from a high resource environment (especially herbs), which often had
qualitative defense compounds but with lower antimicrobial activity.
Recent studies on the global patterns of plant use by human ask whether species ecological
apparency is the main drivers of their medicinal use (e.g., Dai et al. 2015, Goncalves et al.
2016). Here, the following central questions were investigated: (a) does ecological apparency
61
affect the probability of plants being medicinal or in a medicinally over-utilized family? Is
resource availability a determinant prediction of medicinal use and plant use value?
4.2 MATERIALS AND METHODS
4.2.1 Study area
The Mpumalanga Province is situated in the northeastern part of South Africa and covers an
area of 76.520 km2. It is part of the "Greater Maputaland-Pondoland-Albany "biodiversity
hotspot (Perera et al. 2011), comprising a diversity of landscapes characterised by grassland,
savannah, and warm-temperate and subtropical forest biomes. Grasslands are most prevalent
in Mpumalanga, making up 65% of the province. The altitude varies between 110 m and 2328
m above sea level while mean annual rainfall ranges between 341 and 1933 mm. The mean
annual temperature ranges from 100C to 23 0C (Schulze, 1997). Fifty-eight vegetation mapping
units occur in this province as a result of a diversified topography and climate (Mucina and
Rutherford, 2006; Ferrar and Lötter,2007). The indigenous forests are largely confined to the
north-south running Mpumalanga Escarpment and, of the 24 forest types occurring in South
Africa, five are represented in the Mpumalanga province and four major vegetation elements
are dominant including Highveld grasslands, escarpment grassland-forest mosaic, eastern
Lowveld savannah and north-western bushveld savannah. With the indigenous forests
making up 0.51% of the Mpumalanga's territory, it contains a unique suite of plant species
(316 obligate forest taxa) not found in any other major vegetation type in the region (Lötter et
al. 2014). These are represented in three distinct biomes: forest, savannah, and grassland
(Schmidt et al. 2007). Moreover, the most species-rich plant families and genera in the
province included Asplenium, Asparagus, Rhoicissus, Searsia, Maytenus and Ficus and the
most dominant growth form subcategories are small trees (31%), tall trees (16%), tall shrubs
(11%), herbs (9%), woody climbers(8%), Herbaceous climbers (6%), geophytic herbs (5%),
62
graminoids (5%), epiphytes(3%), soft shrubs 1.5%), succulent herbs (0.7%), succulent trees
(0.5%), graminoid climbers (0.2%) and tree-ferns (0.1%) ( Lötter et al. 2014). Currently, five
dominant ethnic groups are distributed in three distinct districts (www.mpumalanga.gov).
Figure 4.1 Forest cover in Mpumalanga province, South Africa
63
4.2.2 Data Collection
4.2.2.1 Source of information
Data on plant maximum height and life forms were collected through 4-year fieldwork (20082012). These data were verified and completed using the book of Schmidt et al. (2007) who
documented plant diversity and plant functional traits over 10 years of data collection in the
province of Mpumalanga.
Data on plant uses were collected through an intensive literature search. All recorded uses
were categorized into seven (07) groups: medicinal, food/fodder, ornament, cosmetic/soap,
fuel/fire/charcoal, construction, and ritual/spiritual. One source of information is the book
Trees and Shrubs of Mpumalanga and Kruger National Park (Schmidt et al. 2007). The
ethnobotanical knowledge documented in this book was collected for more than 10 years of
intensive fieldwork. Another source of data was the PhD thesis of Yessoufou (2012), who
collected botanical and ecological data in the province of Mpumalanga through 4-year
intensive fieldwork (2008-2012). The third important source of data was PRECIS (National
Herbarium (PRE) Computerised Information System databank (SANBI, 2005), a
comprehensive inventory of ethnomedicinal flora of Southern Africa containing 800.000
records of taxa grouped by order and regions (Magill et al. 1983; Germishuizen & Meyer,
2003). The last important source of data is PRELUDE. Although PRELUDE is primarily
focused on documenting plant diversity in Central Africa, it also accommodates documented
ethnobotanical knowledge (articles, publications, and papers) of various African regions
including South Africa (http://www.africamuseum.be). In the end, the resulting dataset
includes 817 vascular plants representing 98 families in 344 medicinal plant species. Plant
64
names and families follow the Angiosperm Phylogeny Group classification (APG IV) Chase
et al. (2016).
4.2.2.2 Measuring of variables
The variable apparency (predictor) was measured in two ways: plant maximum height and
life forms. Plant height was collected from Schmidt et al. (2007). Life form was defined as
shrubs (height<0.5m), trees (height>0.5m).
Then the medicinal use, which is the response variable, was measured in two ways: medicinal
status (medicinal vs. non-medicinal), and the probability of being medicinally overused.
Medicinal status was recorded as explained in section 4.2.2.1 above. In Chapter 3, species are
grouped into over- and under-utilized families. This was done using different modelling
approaches. Here the categorization based on the Negative Binomial Generalized Linear
Modeling is used, and for analysis purpose, species in over-utilized families are coded 1 and
species in under-utilized families are coded 0 such that the probability of a plant being overor under-utilised is either 1 or 0, respectively.
In addition, two more response variables were also added, the Use Value (UV) and the total
number of recorded uses. The total number of uses was determined as the sum of the number
of uses recorded for each species in the categories medicinal, food/fodder, ornament,
cosmetic/soap, fuel/fire/charcoal, construction, and ritual/spiritual. The sources of
information are presented in section 4.2.2.1 above. To measure species growth rate consistent
with the resource availability hypothesis, we retrieved their wood density from Yessoufou
(2012) who collected over 4 years wood materials of species in the study area and determined
in the lab their density. Missing values were imputed as explained in the data analysis section.
65
Species growth rate was estimated as the inverse of their wood density, consistent with King
et al. (2006). All data analysed in this chapter are presented in the appendix B.
4.2.3 Data analysis
All analyses were done in R (R Core Team 2020) and all the R scripts used are provided in the
Supplementary Information. To test if plant height predicts medicinal status, the Generalized
Linear Model (GLM) was fitted to the data, using plant height as the predictor and medicinal
status as the response variable, and specifying the binomial error family, given that the
response variable is binary (a plant is either medicinal or not). To test for correlation between
life form and medicinal status, the same model was also fitted but this time life form is the
predictor (trees, shrubs).
Furthermore, plant heigh or life form were tested to find out they could predict plant’s
probability of being overused. The plant probability was approximated in 2 ways: as a binary
variable (0/1) or as a proportion. When the probability was estimated a binary variable, a GLM
model with a binomial error structure was fitted to the plant height variable. However, when
the probability was estimated as a proportion variable, a beta-regression model was rather
fitted as implemented in the R library betareg (Cribari-Neto and Zeileis, 2010; Grün et al.
2012). The beta-regression is most appropriate when modeling a response variable that is
continuous but constrained within the interval (0,1), e.g., a proportion (Ferrari and CribariNeto, 2004; Simas et al. 2010). Such continuous variable follows a beta-distribution.
In addition, to test if the height or life form predicts UV, a GLM model with a Gaussian error
structure was fitted to the height or life form data. To test if these variables (height and life
form) predict the total number of recorded plants uses, the negative binomial GLM model
was fitted using the glm. nb function as implemented in the R library MASS (Venables and
66
Ripley, 2002). The negative binomial GLM was most indicated to model a count data, here the
total number of recorded plants uses, as demonstrated in several studies (e.g., O'hara and
Kotze, 2010).
To test the resource availability hypothesis, all alternative models mentioned above were also
fitted but this time using plant growth rate as a predictor. I standardised the continuous
predictor variables Hmax and growth rate before the analysis to aid interpretation (Gelman
and Hill, 2006).
4.3 RESULTS
4.3.1 Test of ecological apparency theory
Firstly, the analysis showed that plant maximum height correlates significantly and positively
with medicinal status (β=0.06±0.01, P<0.001), suggesting that taller plants tend to be more
medicinal than shorter ones (Figure 4.2). However, plant height does not correlate with the
probability of plant being medicinally overused, whether this probability is treated as a
binomial variable (β=0.004±0.01, P=0.68) or a proportion (β=0.002±0.007, P=0.77).
67
1.0
0.6
0.8
1
0.0
0.2
0
0.4
medicinal status
10
20
30
Height
Figure 4.2 Relationships between plant height and medicinal status. Taller plants are more
likely to be medicinal. Medicinal status is coded 1 (medicinal) and 0 (non-medicinal).
Secondly, no significant relationship was found between life-form and medicinal status
(β=0.96±0.65, P=0.14), neither do we find a relationship between life-form and the probability
of plant being medicinally overused, again irrespective of how this probability was
approximated: as a binomial variable (β=0.87±0.65, P=0.18) or as a proportion variable
(β=0.35±0.36, P=0.33).
Thirdly, on Use Value (UV), plant height correlates significantly and positively with UV
(β=0.05±0.006, P<0.001; Figure 4.3), but UV does not show such relationship with life-form
68
(β=0.41±0.32, P=0.20). Interestingly, plant height predicts the total number of uses recorded
for each species, such that taller plants (β=0.02±0.004, P<0.001) but not life form (β=0.29±0.30,
4
0
2
abs(UV)
6
P=0.32) tend to have more uses than shorter plants (Figure 4.3).
0
10
20
30
40
Height
Figure 4.3 Relationships between plant height and plant use-value. Taller plants tend to have
higher use-value.
69
1.0
0.8
5
0.6
4
3
0.0
0
0.2
1
0.4
2
total use
10
20
30
Height
Figure 4.4 Relationships between plant height and total plant use. Taller plants tend to have
more uses.
4.3.2 Test of resource availability theory
Resource availability was approximated as plant growth rate. All the analyses conducted
show no evidence that growth rate predicts neither medicinal plant status (β=-18.64±52.71,
P=0.72) nor the probability of plant being overused irrespective of whether this probability is
estimated as a binary variable (β=11.92±49.18, P=0.80) or as a proportion (β=6.16±34.03,
P=0.85). Furthermore, plant growth rate does not correlate with Use Value (β=9.22±29.54,
P=0.75) nor does it correlate with the total number of uses (β=-9.64±26.38, P=0.71).
70
4.4 DISCUSSION
Based on apparency theory, unapparent plants, e.g., species with short lifespans, face lower
herbivore pressure and consequently do not spend resources heavily in quantitative defences;
rather they use "inexpensive" qualitative defences to survive generalist herbivores
(Feeny,1976). Because these qualitative defence compounds (e.g., alkaloids) have more
medicinal bioactivity than quantitative defense compounds (e.g., lignin), it is expected that,
from an ethnobotanical perspective, unapparent plants, e.g., short-lived, herbaceous, early
successional, small-sized plants (e.g., shrubs vs. trees) are more likely to be medicinal than
apparent plants, e.g., perennial, woody, dominant plants (trees vs. shrubs) (de Albuquerque
and Lucena,2005). The present study showed that plant maximum height correlates
significantly and positively with medicinal status, suggesting that taller plants, thus apparent
plants, tend to be used medicinally than shorter ones, i.e., unapparent or less apparent plants.
In the light of the apparency theory, this finding is unexpected, adding to the lack of support
for apparency theory reported in other studies (Alencar et al. 2009; Almeida et al. 2005, 2012).
This unexpected finding could imply that more apparent species because they are easily found
by herbivores, are more likely to suffer heavy herbivory and would therefore provide a heavy
chemical response in return (secondary metabolites) as a defence mechanism (Feeny, 1976,
Rhoades, 1976), which would result in them being identified by humans as medicinal
(Albuquerque et al. 2006). The analysis further reveals that plant height correlates significantly
and positively with UV and even predicts the total number of uses recorded for each species,
such that taller plants tend to have more uses than shorter plants. These findings imply the
importance of plant height in the development of medicinal knowledge.
71
Based on these different but concordant findings, a consequential expectation would be that
taller plants, thus more apparent plants would have a higher probability of being in
medicinally over-utilised families. Such expectation was not confirmed in the present study.
This implies that being medicinal is not necessarily a guarantee that the plant would be
medicinally over-utilised. Over-utilisation maybe therefore driven by different factors other
than the medicinal status of a species, such as e.g., the effectiveness of the bioactivity of the
secondary compound synthesised by the plant, and the phylogenetic relationships of the
plants with other plant species (Saslis-Lagoudakis et al. 2012; Yessoufou et al. 2015). The
phylogenetic aspects of this question are not explored in the present study, and therefore a
conclusive direction could not be given on whether apparency theory can be linked to overutilisation or not. Similarly, there was no significant relationship between life-form and
medicinal status, or between life-form and the probability of plant being medicinally
overused, again irrespective of how this probability was approximated. There was also no
link between life form and UV or the total number of uses. These results are likely linked to
how life form was defined: plants < 0.5 m height categorized as shrubs (less apparent) and
plants >0.5 m, i.e., more apparent as trees (Maurin et al. 2014). This threshold of 0.5 m is
arbitrarily defined and does not have any ecological basis. This, perhaps, maybe not only the
underlying reason for a lack of significant relationship between life form and medicinal status
or the probability of being over-utilized but also may mirror the difficulty in the definition of
species apparency.
Indeed, defining plant species apparency is challenging (see Dai et al. 2015, Albuquerque et
al. 2006, Goncalves et al. 2016). However, a recent meta-analysis, following previous
conclusions from Coley (1989) and Chaplin (1989), suggests an alternative to the apparency
72
theory, which is the resources availability hypothesis (Endara and Coley, 2011). This
hypothesis posits that slow-growth species are more likely to invest more in secondary
chemistry to defend biomass accumulated over a long-time period at a slow rate than fastgrowing species. Surprisingly, all tests run in the present study to test the resources
availability hypothesis did not support the hypothesis. Specifically, all the analyses conducted
show no evidence that growth rate predicts neither medicinal plant status nor the probability
of plant being overused irrespective of whether this probability is estimated as a binary
variable or as a proportion. Furthermore, plant growth rate does not correlate with Use Value
nor does it correlate with the total number of uses.
Testing many of these ethnobotanical hypotheses is challenging because of difficulties in
quantitatively assessing the chemistry of plants and accounting for how compounds may
interact. For example, using dried plant material can potentially reduce actual bioactivity
(Kursar and Capson, 1999), and failing to compare the plant part used with other plant parts
not used medicinally can bias results (but see McCune and Johns, 2007). The synergistic effect
of combining multiple species in one medicine is also difficult to understand (see Coe and
McKenna, 2017). Future studies could explore the widespread practice of using certain plant
parts, harvest times, and harvest places to the genetic and phenotypic chemical variation of
plants as predicted by these two theories; and if the disproportionate use of exotic plants as
medicine in some contexts is primarily due to their high intrinsic growth rate rather than for
diversification purposes.
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4.5 CONCLUSION
Does the ecological apparency theory affect the probability of plants being medicinal or in a
medicinally over-utilised family and is resource availability a determinant prediction of
medicinal use and plant use value?
These two questions investigated were in this study and found that the ecological apparency
theory and the resource availability hypothesis do not explain all facets of the selection and
use patterns of these resources in the study. The weak predictive power that is observed in
this study may presumably because this study scoped and analysed only the medicinal woody
flora, or because the currently available evidence derives from a single geographically isolated
study with a particular methodological approach. More research avenues will be able to
discover more factors that drive these theories in ethnobotany.
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CHAPTER 5
ETHNOBOTANICAL KNOWLEDGE, ENVIRONMENTAL MANAGEMENT AND
POTENTIAL BARRIERS RESTRICTING KNOWLEDGE GROWTH
Abstract
The availability hypothesis predicts that plants that are abundant and easily accessible to
people are more likely to be medicinal than those that are not. By protecting species diversity
away from people, protected areas (PAs) may act as a limiting factor to traditional knowledge
development towards medicinal uses. To test this hypothesis, a dataset of 806 woody plants
including (medicinal status, total number of recipes/plants, number of plants organs/recipes)
was collected for almost 20 years of fieldworks on medicinal plant uses and their abundance
inside and outside the Kruger National Park, South Africa. Four different scenarios of
structural equation models (SEMs) were fitted to the data. For all SEMs, P>0.05, indicating the
good fit of these SEMs. It was found that total abundance is a significant positive predictor of
medicinal status, and so is abundance outside KNP. These findings support the availability
hypothesis. However, not only abundance inside KNP is not a direct significant correlate of
medicinal status, but also the relationship between both is negative. The lack of predictive
power of inside-abundance is most likely because some species are exclusively found inside
KNP and local communities have no access to them. It also shows that the positive and direct
correlation of total abundance with medicinal status is actually driven by outside abundance.
In addition, the negative relationships between inside abundance and medicinal status
implies that abundant plants inside KNP tend to be not-medicinal, further providing evidence
that PAs hinder the development of medicinal knowledge. Furthermore, when inside and
outside abundance were included simultaneously in the model as two distinct variables,
inside abundance was never a direct significant predictor of medicinal uses, but it was so via
an indirect path mediated by outside abundance. This suggests that outside abundance is the
key variable driving the development of medicinal plant knowledge. Cumulatively, these
findings suggest that, by strictly protecting biodiversity, PAs break or block the natural
processes or mechanisms driving the development of medicinal knowledge by local
communities.
Keywords: Availability hypothesis – Ethnobotany – Kruger National Park – Traditional
medicine
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5.1 INTRODUCTION
The environment among other factors may play a fundamental role in the observed
differences in plant use among different communities, which may result in divergent patterns
(for example, the higher use of herbs in certain environments and higher use of trees in others).
Several studies have shown that the environment plays an important role in the selection of
medicinal plants and reported that individuals from different ethnic groups or origins
inhabiting nearby or neighbouring regions in similar environments tend to use similar
repertoires of medicinal plants. Coe and Anderson (1999) compared two neighbouring
indigenous groups of different ethnicities in Nicaragua and observed that 80 % of their
medicinal plant repertoires was shared between the two groups. Similarly, de Albuquerque
et al. (2008) compared the plant components of pharmacopoeias from an indigenous group
and rural community of the Caatinga of the state of Pernambuco, Brazil, and noted similarities
among the plants used, even greater similarities when the native plants were analysed
separately.
Furthermore, the importance of the environment on plant selection can also be observed in
studies showing differences in the pharmacopoeias of peoples of the same origin that live in
different environments. Ladio et al. (2007) compared the knowledge of medicinal plants of the
Mapuche people inhabiting arid steppe and humid forest areas of the Argentinean Patagonia
and observed that only 40% of the plants were used by both groups. The high discrepancy
was attributed to the two communities inhabiting different ecosystems, which limits the
acquisition of contacts with the same plants by the two groups. Moreover, Saslis-Lagoudakis
et al. (2014) studied 12 ethnic groups in Nepal and found that local pharmacopoeias are more
similar when cultures are placed in similar floristic environments. In addition to the variations
76
in the repertoire of medicinal plants reported according to the ecosystem, the richness in
medicinal plants itself also varies because certain ecosystems can for medical practices
according to bioenvironmental logic, which is guided by the physicochemical properties of
the plants (Johnson, 2006), and certain ecosystems favour a greater presence of certain
bioactive compounds over others (see Voeks, 2004; de Albuquerque et al. 2012). Thus, certain
ecosystems may support greater use of native medicinal plants: together with historical and
cultural factors, these factors may help explain why certain areas a higher richness of native
species in their pharmacopoeias have than others depending on their local availability.
According to Gaoue et al. (2017), the availability hypothesis states that plants are used for
medicinal because they are accessible or locally abundant (see also de Albuquerque, 2006).
Thus, a plant or a drug (or anything else) needs first to be available in one way or the other
for its application to be possible. The rationale here would be that the costs invested to obtain
a certain herbal drug or remedy depend on the balance between supply and demand while
the demand may be influenced by a range of parameters (Benítez et al. 2016). But when the
availability of a product is strictly limited such as for example, with exotic and rare key plant
species or when the collection of the crude drug is laborious, the expected benefits driving the
demand have a more dramatic impact on the value chain (Lopes, 2019).
Further, the availability and cultural valuation of a product influence its use, expenditure, and
price, following economic concepts and the availability theory is already reflected in the wellestablished economic law of balance and supply (Leonti et al. 2020).
Accordingly, ethnobotany enables the identification of available and useful species in a
region, and those species with a potential use (Cartaxo et al. 2010; de Albuquerque et al. 2011a,
2011b). It determines how local communities use each species (Lucena et al. 2008; Almeida,
77
2010), coupled with the identification of preferred sites for resources collection while
providing ways in which a resource is exploited (de Albuquerque and Andrade, 2002; de
Albuquerque et al. 2005). In addition, ethnobotany assesses not only the intensity of resource
exploitation but describes also alternative management strategies from the perspective of local
communities including, different conservation priorities, and other demands that should be
addressed through public policies (de Albuquerque et al. 2007; Monteiro et al. 2010; Florentino
et al. 2007; Nascimento et al. 2009; Oliveira et al. 2007; Melo et al. 2009; de Albuquerque et al.
2009).
Documenting such people's knowledge of medicinal plants is the critical first step in the
search for drugs that improve human health (Newman and Cragg, 2012; Lahlou, 2013). How
has the traditional knowledge of medicinal plants been developed? This is a question of
interest for all ethnobotanists simply because understanding the mechanism driving the
development of traditional knowledge would inform how to manage this knowledge, how to
protect them and, more importantly, how to promote their continuous development.
One of the hypotheses that were born, in part, out of studies revealing the importance of
anthropogenic habitats or disturbed areas in provisioning weedy and introduced species for
medicine (Gavin, 2009; Stepp and Moerman, 2001; Voeks, 2004) is known as the availability
hypothesis (ease of acquisition). The availability hypothesis states that plants are used for
medicine because they are more accessible or locally abundant (de Albuquerque, 2006; Voeks,
2004), it predicts that plants that are easily accessible to people are more likely to be medicinal
than those that are not, due to the rarity or restricted distribution of the latter (Voeks, 2004; de
Albuquerque, 2006).
78
Thus, availability is often conceptualised as a physical distance from a home or community to
the location where a plant grows in the wild, but could also be considered in terms of
seasonality, abundance, price, as well as access to markets, gardens, or natural areas where
plants are found (de Albuquerque, 2006, Estomba et al. 2006). Furthermore, the availability
hypothesis has been tested by examining the location where people indicate they collect
medicinal plants and, more broadly, by correlating the local abundance or dominance of
plants with use-values. However, this hypothesis has received mixed support (de
Albuquerque, 2006; Gonçalves et al. 2016; de Oliveira Trindade et al. 2015), with native species
sometimes preferred, despite their lower abundance or accessibility.
In this study, the availability hypothesis in the Mpumalanga province was investigated,
specifically within the context of a protected area of the Kruger National Park (KNP), South
Africa. Protected areas are key ecological systems delimited to protect species-rich geographic
regions for a continued provision of ecosystem goods and services (DeFries et al. 2007;
Dudley, 2008; Heywood, 2016). The Kruger National Park (KNP) covers about 20.000 km2 and
spans across two provinces of South Africa (Mpumalanga and Limpopo). It has an entire flora
>1900 plants species, including 458 tree and shrubby plants referred to as woody flora largely
documented and its materials conserved at the University of Johannesburg in the forms of
GenBank and Herbarium as well as at other various Herbaria and Labs in South Africa
following intensive data collection between 2005-2007 (Lahaye et al. 2008) and 20082009(Yessoufou et al. 2015). It was hypothesised that protected areas (PAs) are potentially one
of those factors that may limit or prevent the development of medicinal plant knowledge by
local communities. By protecting species-rich habitats away from the frequent use of local
communities, it is expected a clear decline in available vegetation or key plant species that
79
could have been used by local people, which means that the available or remainder vegetation
will become the focus for more frequent and intensive harvesting of more high values species.
As result, PAs were expected to prevent or at least limit the development, by these
communities, of comprehensive medicinal knowledge of plants distributed within their
borders, an implication of the availability hypothesis (Voeks, 2004; de Albuquerque, 2006).
5.2
MATERIAL AND METHODS
5.2.1 STUDY AREA
5.2.1.1 Mpumalanga Province
Mpumalanga is one of the nine South African provinces within the Greater Maputaland
Pondoland Albany Biodiversity Hotspot, harbouring the southern half of the Kruger National
Park and other centres of endemism. The Mpumalanga Province is divided into three districts,
namely Gert Sibande, Nkangala, and Ehlanzeni.
Local communities are diverse in culture, and together with language discrepancies, there is
a rich base of traditional knowledge. These communities include Siswati (30%), while 26% of
the inhabitants speak isiZulu, isiNdebele (10.3%), Sepedi (21.2%) and Xitsonga (11.6%)
(Tshikalang et al. 2016). Four major vegetation types are dominant in the study area, namely
the highveld grasslands, escarpment grassland-forest mosaic, eastern Lowveld savannah and
the north-western bushveld savannah (Schmidt et al. 2007). These vegetation types are
represented in three distinct biomes: forest, savannah, and grassland (Schmidt et al. 2007).
5.2.1.2 Kruger National Park (KNP)
The Kruger National Park setting started with the British who created the Sabie Game Reserve
in South Africa in 1898, a protected area that would later become Kruger National Park, in
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1926 (Lockwood et al. 2006). It is one of the largest natural reserves covering an area of
20.000km2 in Africa. It is a woodland biome of southern Africa (Schmidt et al. 2007) with
various habitats found in its boundary. KNP is a protected area, associated with the category
II of the International Union for Conservation of Nature (IUCN), (NSBA, 2004). However, the
local African people were not consulted about their fate (Chatty and Colchester, 2002), a
removal which would later happen at Yellowstone (Spence, 1999). In both cases, the local
people were left alone to absorb their loss. Traditional uses of African land for firewood
collection, livestock grazing, hunting, plant gathering, and logging, all became instantly illegal
in the park because of the national legislation (Carruthers, 1995). Thus, the protected area of
the Kruger National Park in this study belongs to the 19th century Yellowstone Model, that is
thought of involving the expulsion of native people; preserving wilderness free from human
influence; fortress conservation, a top-down control, a non-participatory management system,
tourism and recreation (Phillips, 2003 a).
Kruger National Park indicates the presence of strict enforcement, which implies that it cannot
coexist with the protection of rights of indigenous people (Campese et al. 2009). In such
instance of restricted access, local communities including different ethnic groups in the
province may not have a say concerning the real and potential knowledge of the available
medicinal plants within the protected area of KNP. Therefore, understanding the process of
development of traditional knowledge of medicinal plants in such context as well as the
species with larger use-value can have important implications for the conservation and
management of natural resources of the Kruger National Park.
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5.3 DEFINITION OF VARIABLES USED IN THIS STUDY
The following variables are defined for data analysis. The variable inside abundance is the
number of sites where each plant is found inside the Kruger National Park (Schmidt et al.
2007). Outside abundance is the number of sites where each plant is recorded outside the
Kruger National Park (Schmidt et al. 2007). Total abundance is the sum of inside and outside
abundances. Data on abundance were collected from fieldwork complemented by various
sources indicated above. Plant medicinal knowledge is defined using three metrics, medicinal
status, number of recipes and number of organs used medicinally.
In addition, the following information was also documented for each of the 806 plant species:
point locations, medicinal status (medicinal vs non-medicinal), the number of recipes and the
total number of plant organs used for medicinal treatment. The main objective of the study
in this chapter is to use this dataset not only to test the availability hypothesis (ease of
acquisition) but more importantly, to test the potential impact of the protected area (KNP) on
the development and growth of knowledge.
5.4
DATA COLLECTION
Data used in the present study were collected over a long period of extensive effort and were
documented in multiple forms (book, papers, and online database). First, Schmidt et al. (2007),
over 10 years of the botanical survey across the Mpumalanga province, including the KNP,
published a reference book "Trees and shrubs of Mpumalanga and Kruger National Park".
This book provides photographic illustrations, different uses (including medicinal), broader
distribution including site locations of all woody species in the province and KNP. The
number of site locations for a species is used as a metric for inside or outside abundance for
the species.
82
Second, in the Department of Botany of the University of Johannesburg, multiple botanical
expeditions were also conducted. Lahaye et al. (2008) and Yessoufou et al. (2015) collected,
through intensive seven-year fieldworks in the study area (from 2005 to 2007, and 2008-2012,
respectively), plant information and plant materials that are preserved in various Herbaria
and Labs in South Africa, including the Herbarium of the University of Johannesburg. These
field collections and the book of Schmidt et al. (2007) are the main sources of species
distributions used in the present study for 806 woody plants, both found inside and outside
the KNP across the province of Mpumalanga.
Lastly, in addition to the book of Schmidt et al. (2007), data on the medicinal status of each
plant (medicinal vs non-medicinal), the total number of recipes involving each plant and the
number of plant organs (roots, leaves, barks) used in those recipes were collected from the
Prelude Database for Medicinal Plants in Africa (Royal Museum for Central Africa, 2017), a
database of all ethnobotanical studies that ever took place in Africa, country by country, since
1847. From this unique database, the focus was only on the publications on the Mpumalanga
province, South Africa and where other additional sources were explored such as
SANBIPlantZafrica (SANBI PlantZafrica, 2000) and (ethnobotanical books that focused on
southern Africa's woody flora (Coates-Palgrave, 2002; Germishuizen and Meyer, 2003; Boon,
2010; van Wyk, 2011).
5.5 DATA ANALYSIS
All analyses were done in R 3.5 (R Development Core Team 2019) in the library PiecewiseSEM
(Lefcheck, 2016), and the R scripts used are provided as supplemental information. The first
test explored whether total abundance predicts plant medicinal knowledge, which was
measured either as medicinal status, number of recipes or number of organs used. To this end,
83
a structural equation model (SEM) was fitted to the dataset as implemented in the R library
PiecewiseSEM (Lefcheck, 2016). This SEM analysis was done on the first meta-model built
based on the following assumptions: that the total abundance would predict medicinal status,
and this assumption is grounded on the availability hypothesis. As an implication of the
availability hypothesis, total abundance was further expected to predict the number of recipes
involving a given species and the number of organs used medicinally. The rationale for these
assumptions is that more abundant species are more likely to be medicinal (availability
hypothesis), and plants that have more organs used medicinally are more likely to be involved
in more recipes than not.
Finally, plants involved in a medicinal recipe are medicinal. All these expectations were
translated into the first meta-model (Figure 5.1), followed by a test of fitness of this metamodel to the data using the function GLM with specifically a binomial error structure for
medicinal status (as this is a binary variable, medicinal vs non-medicinal).
To test the potential influence of PAs on the development of medicinal plant knowledge, three
additional alternative meta-models were built. These meta-models are too based on similar
expectations explained above, and upon which the first meta-model is grounded with the
following differences. In the meta-model in Figure 5.2a, total abundance is replaced with
abundance outside the KNP; in Figure 5.2b, total abundance is replaced with abundance
inside the KNP, and in the last meta-model (Figure 5.5), total abundance is replaced by
simultaneous abundance outside and inside the KNP.
The rationale here is that plants that are inside PAs are less likely to be medicinal, even if they
are abundant inside the park because they are less often in contact with local communities
(unless they are abundant outside the KNP). In contrast, plants that are outside the park
84
would more likely be medicinal because they are in everyday contact with local communities,
particularly plants that are abundant (availability hypothesis). All these expectations were
tested fitting the SEM to all meta-models as presented in details in the R scripts (Supplemental
Information).
5.6 RESULTS AND DISCUSSION
The availability hypothesis was firstly tested by employing the structural equation modelling
(SEM) approach. The meta-model built includes total plant abundance (plant abundance
inside + outside of KNP), number of recipes for each plant and number of organs used
medicinally (see Figure 5.1 for full model). The first SEM analysis revealed a perfect fit of this
meta-model to the data collected and explains the medicinal status of plants (Fisher C = 0, df
= 2, P = 1.00). This model shows that only total plant abundance is a significant positive
predictor of medicinal status; that is, more abundant plants tend to be medicinal than not,
thus a support for the availability hypothesis (Voeks, 2004; de Albuquerque, 2006). The model
further reveals three paths through which the total abundance of plants predicts their
medicinal status. There is a direct path (black arrow in Figure 5.1) with a path coefficient β =
0.04. Then, there are two indirect paths, one through some recipes (green path on Figure 5.1,
β = 0.25), and the other one through both number of organs used and some recipes (the red
path on Figure 5.1) with the highest path coefficient (β = 1.03).
85
Figure 5.1 Meta-model illustrating the prediction of availability hypothesis. Different paths
(arrows) of the relationships of total abundance with medicinal status are the colour-coded;
black, direct path, green, shortest indirect path, and red, longest, and most strong indirect
path. The width of the arrow is indicative of the strength of the relationships between two
variables. Values on the arrows are path coefficients, SE, standard error.
Second, the main question was explored: does the establishment of such a large national park,
the Kruger National Park (20.000 km2), protecting ~ 500 woody plants (Venter, 1990; Schmidt
et al. 2007), influence the development and growth of medicinal plant knowledge in the
province? The theoretical expectation is that plants that are inside PAs would less likely be
medicinal, even if they are abundant within KNP. Alternatively, plants that are outside the
KNP would more likely be medicinal because they are easily accessible to local communities,
particularly plants that are abundant (availability hypothesis).
To explore these two alternative expectations, two meta-models were built (Figures 5.2 a, 5.2
b) in which only plant abundance outside and inside KNP were included, respectively (Figure
86
5.3), as opposed to only total abundance in Figure 5.1. The first meta-model (Figure 5.2a) that
contains only plant abundance outside the KNP (henceforth referred to as "outside
abundance") has an overall perfect fit to data (C = 0, df = 2, P = 1.00) and is similar, from all
aspects to the meta-model in Figure 5.4. Specifically, outside abundance predicts better
medicinal status through the same three paths identified in the meta-model containing total
abundance (Figure 5.1), with the red path in Figure 5.2a being the strongest (black path, β =
0.06; green path, β = 0.26 and red path, β = 1.07). This is additional support for the availability
hypothesis: more abundant plants outside KNP tend to be medicinal than not.
However, the second meta-model (Figure 5.2b), which also shows a perfect fit to the data (C
= 0, df = 2, P = 1.00), reveals one important difference from the previous models (Figures 5.1,
5.2a): not only the direct path between abundance inside KNP and medicinal status is no
longer significant, but the coefficient of this direct path is negative. If abundance inside KNP
is not a significant predictor of medicinal status, this is a piece of evidence that, by strictly
protecting biodiversity, PAs break or block the natural processes or mechanisms driving the
development of medicinal knowledge by local communities. This lack of predictive power of
inside abundance is most likely because, although both inside and outside KNP share some
common species, other species are exclusively found inside the park (Table 5.1) that local
communities may not know of or do not have access to. It also shows that the positive and
direct effect of total abundance on plant medicinal status, found in Figure 5.1, is driven by
outside abundance (Figure 5.2a).
87
Table 5.1. Native (shrubs and trees) medicinal distribution in the Mpumalanga province
and the Kruger National Park (KNP)
Families
Exclusive
Families
Exclusive
KNP
Mpumalanga
Province
Asteraceae
Brachylaena ilicifolia
Celastraceae
Salacia kraussii
Asteraceae
Gymnanthemum
Achariaceae
Xylotheca kraussiana
amygdalinum (Delile)
Sch. Bip. ex Walp
Asteraceae
Vernonia adoensis
Annonaceae
Uvaria lucida
Asteraceae
Vernonia tigna
Apocynaceae
Adenium multiflorum
Capparaceae
Boscia
foetida Apocynaceae
Holarrhena pubescens
rehmanniana
Celastraceae
Cassine peragua
Apocynaceae
Strophanthus kombe
Capparaceae
Cadaba aphylla
Apocynaceae
Strophanthus _petersianus
Capparaceae
Cadaba natalensis
Capparaceae
Capparis sepiaria
Sapotaceae
Elaeodendron croceum Euphorbiaceae
Sapotaceae
Elaeodendron zeyheri
Euphorbiaceae
Androstachys johnsonii
Croton _pseudopulchellus
88
Celastraceae
Gymnosporia
Fabaceae
Afzelia quanzensis
Fabaceae
Albizia amara
buxiffolia
Celastraceae
Pterocelastrus
rostratus
Clusiaceae
Garcinia gerrardii
Fabaceae
Albizia forbesii
Clusiaceae
Hypericum revolutum
Fabaceae
Cassia abbreviata
Clusiaceae
Hypericum
Fabaceae
Cordyla africana
Fabaceae
Newtonia hildebrandtii
roeperianum
Acanthaceae
Sclerochiton
ilicifoloius
Achariaceae
Kiggelaria africana
Fabaceae
Xeroderris stuhlmannii
Anacardiaceae
Harpephyllum
Hernandiaceae
Gyrocarpus americanus
Protorhus longifolia
Strychnaceae
Strychnos potatorum
Searsia chirindensis
(Baker f.)
Moraceae
Ficus natalensis
Monanthotaxis caffra
Rubiaceae
Hymenodictyon
caffrum
Searsia
(Anacardiaceae)
Searsia
(Anacardiaceae)
Annonaceae
parvifolium
Monimiaceae
Xymalos monospora
Rubiaceae
Pavetta harborii
89
Apocynaceae
Gonioma kamassi
Salvadoraceae
Salvadora persica
Apocynaceae
Strophanthus
Ebenaceae
Diospyros loureiriana
speciosus
Araliaceae
Schefflera umbellifera
Asparagaceae
Dracaena aletriformis
Asparagaceae
Dracaena
transvaalensis
Xanthorrhoeaceae
Aloe arborescens
Xanthorrhoeaceae
Aloe castanea
Cornacaeae
Curtisia dentata
Cyatheaceae
Cyathea dregei
Ebenaceae
Diospyros galpinii
Ebenaceae
Diospyros natalensis
Phyllanthaceae
Andrachne ovalis
Euphorbiaceae
Euphorbia grandidens
Asteraceae
Sapium ellipticum
Asteraceae
Sapium integrum
Fabaceae
Vachellia erioloba (E.
Mey.) P.J.H. Hurter
90
Fabaceae
Adenopodia spicata
Fabaceae
Bauhinia tomentosa
Fabaceae
Calpurnia glabrata
Fabaceae
Dalbergia obovata
Icacinaceae
Apodytes dimidiata
Lamiaceae
Leonotis leonurus
Lauraceae
Cryptocarya
transvaalensis
Lauraceae
Cryptocarya woodii
Rosaceae
Leucosidea sericea
Malpighiaceae
Acridocarpus
natalitius
Malpighiaceae
Triaspis hypericoides
Malvaceae
Abutilon angulatum
Malvaceae
Abutilon sonneratum
Tiliaceae
Grewia flava
Meliaceae
Turraea floribunda
Melianthaceae
Bersama lucens
91
Melianthaceae
Greyia sutherlandii
Ochnaceae
Ochna oconnori
Ochnaceae
Ochna serrulata
Ochnaceae
Ochna holstii
Laureaceae
Ocotea bullata
Laureaceae
Ocotea kenyensis
Podocarpaceae
Afrocarpus falcatus
Polygalaceae
Polygala virgata
Proteaceae
Faurea macnaughtonii
Proteaceae
Faurea rochetiana
Proteaceae
Protea caffra
Proteaceae
Protea gaguedi
Proteaceae
Protea roupelliae
Proteaceae
Protea wewitschii
Rosaceae
Prunus africana
Rhamnaceae
Scutia myrtina
Rutaceae
Calodendrum capensis
Rutaceae
Vepris lanceolata
92
Rutaceae
Zanthoxylum Capense
Rutaceae
Zanthoxylum davyi
Flacourtiaceae
Gerrardina foliosa
Flacourtiaceae
Trimeria grandifolia
Sapotaceae
Manilkara concolor
Sapotaceae
Manilkara discolor
Sapotaceae
Mimusops obovata
Solanaceae
Solanum aculeastrum
Scrophulariaceae
Halleria lucida
Ulmaceae
Chaetachne aristata
Vitaceae
Rhoicissus digitata
Vitaceae
Rhoicissus
tomentosus
Fabaceae
Lessertia microphylla
Fabaceae
Psoralea latifolia
Thymelaeceae
Peddiea africana
Scrophulariaceae
Buddleja saligna
Scrophulariaceae
Buddleja salviifolia
93
In addition, the finding of negative relationships between inside abundance and medicinal
status implies that abundant plants inside KNP tend to be not-medicinal, further providing
evidence that protected areas hinder the development and growth of medicinal knowledge.
Interestingly, while the direct path between inside abundance and medicinal status becomes
non-significant, the indirect path mediated by both the number of organs used and the
number of recipes become the strongest among all models (β = 1.66).
Figure 5.2 Meta-model illustrating the potential influence of plant abundance outside (a)
versus inside (b) the Kruger National Park. Different paths (arrows) of the relationships of
total abundance with medicinal status is the colour-coded; black, direct path, green, shortest
indirect path, and red, longest, and most strong indirect path. The width of the arrow is
indicative of the strength of the relationships between two variables. Values on the arrows are
path coefficients, SE, standard error.
94
Finally, to further clarify this negative effect of PAs on the development of medicinal plant
knowledge, a final metamodel was built, in which inside and outside plant abundances are
simultaneously included (Figure 5.4). Moreover, If PAs truly have this negative effect, then
the expectation of the positive effect of outside abundance (Figure 5.4a) can be cancelled or at
least weakened by the negative effect of inside abundance (Figure 5.4 b) such that none of
these two variables (outside and inside abundances) would be significant predictors of
medicinal status
The SEM analysis of this last meta-model (Figure 5.5) identified the path "organ used ~ inside
abundance" as a missing path, but a non-significant one with P = 0.73, meaning that plant
abundance inside KNP is not a significant predictor of the number of organs used in
traditional medicine, confirming that KNP may be limiting the development and growth of
knowledge of plant uses. As suggested above, this is most likely because KNP has plants that
are exclusively found within its borders and for which no medicinal uses could be developed
because they are not accessible to people (Table 5.1). However, when this missing path was
included in the meta-model, all endogenous variables become conditionally dependent, and
the test of directed separation becomes impossible. I, therefore, left that missing path out of
the SEM analysis. This did not affect the strength of the meta-model as the model shows a
good overall fit (C = 0.6, df = 2 and P=0.7390).
95
Figure 5.3 The most complex meta-model illustrating the simultaneous influence of outside
and inside plant abundance on medicinal knowledge. Different paths (arrows) of the
relationships of total abundance with medicinal status are a colour-coded; black, direct path,
green, shortest indirect path, and red, longest, and most strong indirect path. The width of the
arrow is indicative of the strength of the relationships between two variables. Values on the
arrows are path coefficients, SE, standard error.
5.7. CONCLUSION
Few studies have measured the impact of the protected areas on the development of
knowledge for local communities. More recently, Robles-Arias et al. (2020) suggested that the
presence of protected areas in an environment might hamper the development of medicinal
knowledge in that environment. The availability hypothesis has been tested by examining the
location where people indicate they collect medicinal plants and, more broadly, by correlating
the local abundance or dominance of plants with use-values, and has yielded in general,
mixed support (de Albuquerque, 2006; Gonçalves et al. 2016; de Oliveira, 2016; Trindade et al.
96
2015). The investigation of the availability hypothesis has revealed a lack of support in the
context of the protected area of the Kruger National Park where the plant abundance variable
had a negative relationship between inside abundance and medicinal status, contrasting thus
with the positive relationship between outside abundance and medicinal status in this study.
Few assumptions can be made concerning this finding: Firstly, due to the restricted access
inside the park, a greater harvesting rate is expected near the community or outside the
protected area regarding the shared common medicinal species (outside and inside the
protected area), meaning that the proximity with the community will not affect species
richness but will however affect the outside abundance variable. The second assumption is
that according to Phillips and Gentry (1993 b), humans will experiment with (and learn to use)
the most abundant plants in a given region, therefore, the development of full medicinal
knowledge of some twenty-four (24) key species found uniquely inside the park (see Table
5.1) should be considered ex situ.
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CHAPTER 6
GENERAL CONCLUSION
1. Major findings, discussions and contributions to the body of knowledge
Studies using rigorous approaches are very limited in the study area while considering the
potential for more theory-inspired and hypothesis-driven research in ethnobotany, regarding
the identification of culturally important plant species to inform resource management. The
extent of the use patterns of medicinal plants particularly through ethnobotanical hypotheses
testing has not been fully explained and still lags with no basic scientific framework in
Mpumalanga province. The current results presented here constitute the most comprehensive
and up-to-date in-depth analysis of more hypothesis-driven and theoretically inspired
approach.
6.1 General patterns of medicinal plants selection by local communities: non-random
hypothesis
This thesis assessed one of the most common ethnobotany' theories developed in the 1970s
(Moerman,1979) the non-random plant theory. The theory suggests that some plant families
are bound to contain fewer species with medicinal values and uses than expected by chance.
The premise is that species in these families are evolutionary and less likely to contain
secondary chemistry efficient against disease. Using the woody flora of the Mpumalanga
province, the test has revealed at least two behaviours: certain families have higher medicinal
value and are therefore more frequently used than others. Evidence that chemical compounds
with medicinal value are not equally distributed among different botanical families (Gottlied
et al. 2002). Moreover, it was found that overused and underused species are not the same
98
for each one of the three statistical analysis approaches used in this study. Conversely, certain
families appear to behave discrepantly in particular contexts. Important family such as
Fabaceae for example was found overused and underused according to statistical approaches
used. More information needs to be gathered by researchers to explain whether these
discrepancies are caused by cultural or other factors, or whether certain botanical families
(especially those with a wide distribution) include species that are strongly divergent in terms
of chemical composition. Despite the discrepancies observed through the different statistical
approaches, this finding does not invalidate the evident and universal patterns observed for
the taxonomy of medicinal species. The results confirm the strong evidence that plant use by
local populations does not occur randomly (Moerman,1979) and this is inconsistent with the
placebo effect hypothesis of popular medicine and medicinal plant selections are not
taxonomically random. This finding is consistent with taxonomic patterns observed among
previous studies in Moerman's approach (Moerman,1979). The finding does provide
additional strong evidence to the body of literature that plant use by indigenous people does
not occur randomly and more importantly will add to the discussion on the non-random
medicinal plants selection by expanding the geographical range for this theory and proposing
new ways of analysing the data.
6.2 The use of ecological theories to generate ethnobotanical knowledge: ecological
apparency theory and resource availability hypothesis
One of the research questions formulated in this thesis was specified as follows: Does the
ecological apparency theory affect the probability of plants being medicinal or in a
medicinally over-utilised family and is resource availability a determinant prediction of
medicinal use and plant use value? These two questions were investigated in this study and
99
found that the ecological apparency theory and the resource availability hypothesis do not
explain all facets of the selection and use patterns of these resources in the study. The weak
predictive power may presumably due to the fact that the current study scoped and analysed
only the medicinal woody flora, or because the currently available evidence derives from a
single geographically isolated study with a particular methodological approach. Furthermore,
in this study, plant maximum height correlates significantly and positively with medicinal
status, suggesting that taller plants, thus apparent plants, tend to be used medicinally than
shorter ones or the unapparent or less apparent plants. Thus, the apparency theory is not
supported in the present study as it does involve a qualitative strategy that implies that most
herbs have a short life cycle and are ephemeral (non-apparent), they accumulate compounds
that are strongly bioactive and consequently very useful for treating humans’ diseases. The
assumption is that the herbaceous plants used by traditional communities would form groups
of plants potentially more likely to be incorporated into a culture, as result, bioprospecting
efforts could be concentrated on these non-apparent species.
While contrasting with the ecological apparency theory, the finding is consistent with a study
conducted in a semiarid region of Ethiopia; a higher number of trees used for medicinal
purposes was observed than any other plant habit (Zone et al. 2007). In addition, the
importance of woody plants to local communities has been more evidenced in studies
conducted in the semiarid region of Brazil (de Albuquerque et al. 2007).
This is additional evidence to the body of knowledge indicating that in this subtropical
Mpumalanga province, bioprospecting efforts would be concentrated more on apparent
woody flora or trees in the form of stem bark extractions for different therapeutic indications
and targets. Furthermore, it was found that the resource availability hypothesis, proxied as
100
plant growth rate in this study, did not have empirical support. The growth rate does not
predict the medicinal status nor does it predict the probability of being overused. Contrasting
so with suggestions (see Stepp and Moerman (2001), they suggested that both the ecological
apparency theory and the resource apparency hypothesis, can explain the use and selection
of medicinal plants by local communities. This suggestion is based on simple evidence, that is
in many parts of the world, medicinal plants compiled in different human communities are
dominated by herbs. If the pattern is, in fact, a worldwide trend, it is possible to predict the
type of environments in which there is a greater likelihood of finding plants with medicinal
potential according to their floristic composition (Stepp and Moerman (2001).
6.3 Ethnobotanical knowledge, environmental management and potential barriers
restricting knowledge growth
The selection of medicinal plants is done first according to bioenvironmental logic, which is
guided by the physicochemical properties of the plants (Johnson, 2006), and secondly
according to the availability of certain ecosystems that favour a greater presence of certain
bioactive compounds over others (Voeks,2004; de Albuquerque et al. 2012). The result in this
study confirms that certain ecosystems support greater use of native medicinal plants;
together with historical and cultural factors, these factors explain why certain areas have a
higher richness of native species in their pharmacopoeias than others. However, some key
medicinal species are found exclusively within the confines of the protected area of the Kruger
National Park, thus not accessible for use by the local communities. As such, it is suggested
that some local strategies of use and conservation of local resources be constructed in a
collective and participatory manner, counting on the involvement of the local communities at
all stages, from the identification of the problems or central questions, up to the
101
implementation of the proposed solutions. Moreover, it is important to emphasise the need
to include within these local strategies of management and conservation the species that have
been proven to have a wide local use on its real use. To that end, a list of twenty-four (24) key
medicinal species recorded exclusively inside the protected area of KNP is included in this
study (Schmidt et al. 2007), these species need to be grown ex-situ in the proximity community
so to encourage human-plant interactions leading to the development and growth of
medicinal knowledge.
6.3 Recommendations for future studies
Based on the evidence highlighted in the general conclusions the following recommendations
are formulated: A follow-up research to this study is recommended with emphasis on
increasing the scope of the study, particularly the inclusion and analysis of exotic plant species
especially in the protected area of the Kruger National Park.
It is further suggested that future studies should focus on the construction of a knowledge
framework that would involve a comprehensive analysis of all other life forms including
woody flora, non-woody flora, local communities outside the Kruger National Park in the
surrounding of Mpumalanga province, Limpopo province as well as the communities on the
other side of the KNP in Mozambique as these parameters can affect the overall hypotheses
testing. Moreover, due to its complexity, testing hypotheses related to use patterns of
medicinal plants is not an easy task, but simple predictions can be made. Therefore, statistical
approaches used in this thesis could be redefined and expanded beyond the Mpumalanga
province.
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CHAPTER 7
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APPENDICES
Supplementary Information
APPENDIX A
NON-RANDOM HYPOTHESIS DATA SET
OBJECTIVE 1: TESTING NON-RANDOM HYPOTHESIS
TREES AND SHRUBS DISTRIBUTION
Family_APG_IV
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Achariaceae
Achariaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Origin
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Genus_species
Anisotes_formosissimus
Anisotes rogersii
Barleria_albostellata
Barleria_rotundifolia
Duvernoia_ aconitiflora
Duvernoia_ adhatodoides
Justicia_ campylostemon
Mackaya _bella
Metarungia_ longistrobus
Ruspolia_ hypocrateriformis
Ruttya _ovata
Sclerochiton_ harveyanus
Sclerochiton_ ilicifoloius
Kiggelaria_ africana
Xylotheca_ kraussiana
Harpephyllum _caffrum
Lannea_discolor
Lannea_edulis
Lannea_ gossweilleri
Lannea_schweinfuthii
Ozoroa__barbertonensis
Ozoroa__engleri
Ozoroa__obovata
Ozoroa _ paniculosa
Ozoroa_ paniculosa
Protorhus_ longifolia
Ozoroa _sphaerocarpa
Sclerocarya_ birrea
Rhus__batophylla
Sersia_ chirindensis
Medicinal_
status
Mpumalanga KNP
0
0
2
0
0
4
0
0
3
0
19
2
0
5
1
0
5
1
0
5
0
0
9
0
0
9
1
0
0
2
0
24
4
0
15
0
1
2
0
1
53
0
1
0
2
1
22
0
1
39
6
0
27
6
0
3
0
0
9
23
0
5
0
0
4
5
0
1
7
0
18
0
0
1
0
1
21
0
1
11
1
0
54
36
0
4
0
1
43
0
134
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Penaeaceae
Penaeaceae
Penaeaceae
Monimiaceae
Apiaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Rhus _dentata
Rhus_ discolor
Rhus__dracomontana
Rhus _engleri
Rhus__gerrardi
Rhus__gracillima
Rhus__grandidens
Rhus_ guenzii
Rhus__harveyi
Rhus _keetii
Rhus_lancea
Rhus__leptodictya
Rhus__lucida
Rhus magalismontana
Rhus__montana
Rhus__pallens
Rhus__pentheri
Rhus__pondoensis
Rhus__pygmaea
Rhus pyroides
Rhus pyroides
Rhus__rehmanniana
Rhus___sekhukhuniensis
Rhus__species
Rhus__tomentosa
Rhus__transvaalensis
Rhus__tumulicola
Rhus_ tumulicola
Rhus _tumulicola
Rhus__wilmsii
Rhus__zeyheri
Annona__senegalensis
Artabotrys__brachypetalus
Hexalobus__monopetalus
Monanthotaxis__caffra
Monodora_ junodii
Monodora__junodii__macrantha
Uvaria gracilipes
Uvaria_lucida
Xylopia_ parviflora
Olinia__emarginata
Olinia__radiata
Olinia__rochetiana
Xymalos__monospora
Heteromorpha_arborescens_Var_abyssinica
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
1
0
0
0
0
1
1
52
53
1
12
34
11
8
15
1
8
7
35
22
11
3
3
41
10
2
46
39
17
7
6
7
21
38
19
19
8
20
28
0
8
16
0
0
0
0
1
28
3
9
23
75
135
0
0
0
0
0
0
0
13
0
0
0
7
0
0
0
0
6
0
0
3
0
0
0
0
0
3
0
0
0
0
0
9
6
11
0
3
1
5
2
1
0
0
0
0
2
Apiaceae
Apiaceae
Apiaceae
Apiaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Aquifoliaceae
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Arecaceae
Arecaceae
Arecaceae
Arecaceae
Asparagaceae
Asparagaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Heteromorpha_arborescens_Var_frutescens
Heteromorpha__involucrata
Heteromorpha__pubescens
Steganotaenia__araliacea
Acokanthera__oppositifolia
Acokanthera__rotundata
Adenium__multiflorum
Adenium__swazicum
Ancyloboyrys_ capensis
Carissa__bispinosa___bispinosa
Carissa__bispinosa___Zambesiensis
Carissa__edulis
Carissa__tetramera
Diplorhynchus__condylocarpon
Gonioma__kamassi
Holarrhena__pubescens
Landolphia__kirkii
Pachypodium_saundersii
Rauvolfia__caffra
Strophanthus__gerrardii
Strophanthus__kombe
Strophanthus__petersianus
Strophanthus__speciousus
Tabernaemontana__elegans
Tabernaemontana__ventricosa
Wrightia__natalensis
Ilex__mitis
Cussonia__natalensis
Cussionia__paniculata
Cussonia__spicata
Cussonia__sphaerocephala
Cussonia__transvaalensis
Schefflera__umbellifera
Seemannaralia__gerrardii
Borassus__aethiopium
Hyphaene__coriacea
Hyphaene_ petersiana
Phoenix__reclinata
Dracaena__aletriformis
Dracaena___transvaalensis
Aloe_excelsa
Aloe__alooides
Aloe_angelica
Aloe_arborescens
Aloe_barberae
0
0
0
0
1
1
1
0
0
0
1
1
0
0
1
1
0
0
1
1
1
1
1
0
1
1
1
0
0
1
0
0
1
0
0
0
0
1
1
0
0
0
0
1
0
13
16
11
23
25
11
0
6
8
27
36
16
3
19
2
0
0
20
20
4
0
0
9
4
3
5
38
22
33
36
1
23
18
7
0
2
0
17
13
4
0
5
0
46
5
136
0
0
0
4
4
3
7
2
0
3
2
2
5
5
0
6
3
3
6
1
5
4
0
6
1
3
0
4
0
1
0
0
0
0
1
10
15
26
0
0
1
0
2
0
0
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Balanitaceae
Balanitaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Boraginaceae
Boraginaceae
Boraginaceae
Boraginaceae
Boraginaceae
Boraginaceae
Boraginaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Aloe_castanea
Aloe__littoralis
Aloe_marlothii
Aloe_spicata
Brachylaena__discolor
Brachylaena__huillensis
Anisopappus__junodii
Anisopappus_ smutsii
Brachylaena__ilicifolia
Brachylaena__rotundata
Brachylaena__transvaalensis
Eumorphia_ davyi
Eumorphia___swaziensis
Helichrysum__kraussii
Lopholaena__corifolia
Lopholaena__platyphylla
Phymaspermum__acerosum
Pulchea_dioscordia
Senecio_barbertonicus
Seriphium__plumosum
Seriphium__species
Tarchonanthus___trilobus
Vernonia__adoensis
Vernonia__amygdalina
Vernonia__aurantiaca
Vernonia_ colorata
Vernonia__tigna
Vernonia__triflora
Vernonia__wollastonii
Vernonia__myriantha
Balanites__maughamii
Balanites___pedicillaris
Kigelia_ africana
Markhamia__zanzibarica
Rhigozum__obvatum
Rhigozum_brevispinosum
Rhigozum__zambesiacum
Tecoma_capensis
Cordia__caffra
Cordia__grandicalyx
Cordia__monoica
Cordia_ovalis
Cordia__sinensis
Ehretia__amoena
Ehretia__obtusifolia
1
0
1
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
1
0
0
0
1
1
1
1
0
0
0
1
0
0
1
1
1
1
0
32
0
65
21
2
3
2
7
9
13
30
4
4
31
37
1
17
5
18
29
16
19
6
6
1
17
31
5
16
19
20
1
9
3
3
6
7
19
2
0
13
13
1
30
14
137
0
1
7
12
0
5
0
0
0
0
2
0
0
0
0
0
0
14
1
0
0
0
0
0
0
6
0
0
0
0
11
3
8
4
0
0
7
3
1
6
10
10
6
10
19
Boraginaceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Buxaceae
Canellaceae
Cannabaceae
Cannabaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Ehretia__rigida
Commiphora__africana
Commiphora__edulis
Commiphora_glandulosa
Commiphora__harveyi
Commiphora__marlothii
Commiphora_mollis
Commiphora_neglecta
Commiphora__pyracanthoides
Commiphora__schimperi
Commiphora__tenuipetiolata
Commiphora__viminea
Commiphora___woodii
Commiphora__zanzibarica
Bridelia_cathartica
Bridelia_micrantha
Bridelia_mollis
Cleistantus__schlechteri
Buxus_macowani
Warburgia__salutaris
Celtis__africana
Trema__orientalis
Boscia__albitrunca
Boscia__angustifolia
Boscia__foetida__filipes
Boscia__foetida__minima
Boscia foetida _rehmanniana
Boscia__mossambicensis
Cadaba_aphylla
Cadaba_ natalensis
Cadaba_termitaria
Capparis__fascicularis
Capparis__sepiaria
Capparis__tomentosa
Maerua__angolensis
Maerua__cafra
Maerua__decumbens
Maerua__juncea
Maerua_parvifolia
Maerua__rosmarinoides
Thilachium__africanum
Cassine_peragua
Catha_edulis
Elaeodendron__croceum
Elaeodendron__transvaalense
1
1
0
0
0
0
0
0
0
0
0
1
0
0
1
1
1
1
0
1
1
1
1
0
0
0
1
0
1
1
0
0
1
1
1
0
1
0
0
0
1
1
1
1
1
49
15
0
17
26
19
24
7
15
11
5
3
2
0
17
20
21
1
9
10
64
39
52
0
0
0
22
3
4
4
10
17
0
18
35
33
2
20
15
18
1
5
18
2
24
138
5
15
5
14
0
2
8
4
10
3
7
1
0
1
8
1
6
3
0
1
2
4
13
3
2
1
0
7
0
0
5
1
4
17
21
3
4
10
19
3
5
0
4
0
9
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Fabaceae
Fabaceae
Chrysobalanaceae
Clusiaceae
Clusiaceae
Clusiaceae
Clusiaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Exotic
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Elaeodendron__zeyheri
Gymnosporia__heterophylla
Gymnosporia__maranguensis
Gymnosporia_oxycarpa
Gymnosporia__pubescens
Gymnosporia_putterlickioides
Gymnosporia__senegalensis
Gymnosporia_buxifolia
Gymnosporia_ glaucophyllia
Gymnosporia_grandifolia
Gymnosporia__harveyana
Hippocratea__africana.
Hippocratea_crenata
Hippocratea__indica
Hippocratea__longipetiolata
Hippocratea_parvifolia
Maytenus_peduncularis
Maytenus__undata
Putterlickia_verrucosa
Salacia__kraussii
Lauridia__tetragona
Pterocelastrus___echinatus
Pterocelastrus__rostratus
Pterocelastrus_tricuspidatus
Caesalpinia__rostrata
Cassia_abbreviata
Parinari__curatellifolia
Garcinia__gerrardii
Garcinia__livingstonei
Hypericum__revolutum
Hypericum__roeperianum
Combretum__apiculatum
Combretum_ celastroides
Combretum___mkuzense
Combretum_collinum
Combretum__erythrophyllum
Combretum__hereroense
Combretum__imberbe
Combretum__kraussii
Combretum__microphyllum
Combretum__molle
Combretum_mossambicense
Combretum__nelsonii
Combretum__padoides
Combretum__woodii
1
0
0
0
0
0
1
1
0
0
1
0
0
0
0
0
0
0
0
1
0
0
1
1
0
1
1
1
1
1
1
1
0
0
0
1
1
1
1
0
1
0
0
0
0
4
16
4
0
0
0
23
47
28
5
25
3
0
0
15
3
29
38
6
0
7
45
8
0
1
19
14
1
5
17
3
65
0
0
12
65
55
24
41
11
71
5
6
5
13
139
0
0
9
3
4
6
17
0
5
0
1
3
9
4
12
6
1
2
1
3
0
0
0
0
3
1
2
0
8
0
0
44
5
1
11
7
40
41
0
16
6
30
0
3
1
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Cornacaeae
Connaraceae
Cupressaceae
Cyatheaceae
Cyatheaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ericaceae
Ericaceae
Ericaceae
Ericaceae
Ericaceae
Ericaceae
Erythroxylaceae
Erythroxylaceae
Escalloniacea
Euphorbiaceae
Euphorbiaceae
Phyllanthaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Combretum__zeyheri
Pteleopsis__myrtifolia
Terminalia__phanerophlebia
Terminalia__prunioides
Terminalia__sericea
Curtisia__dentata
Cnestis__polyphylla
Widdringtonia__nodiflora
Cyathea__capensis
Cyathea___degrei
Drypetes__arguta
Drypetes__gerrardii
Drypetes__mossambicensis
Drypetes__reticulata
Diospyros__austro_africana
Diospyros__dichrophylla
Diospyros__galpinii
Diospyros__loureiriana
Diospyros_lycioides
Diospyros__mespiliformis
Diospyros__natalensis
Diospyros__villosa
Diospyros__whyteana
Euclea__crispa
Euclea__crispa
Euclea daphnoides
Euclea__dewinteri
Euclea__linearis
Euclea_divinorum
Euclea_ natalensis
Euclea__undulata
Euclea__species
Euclea__schimperi
Erica__cafforum
Erica__drakensbergensis
Erica__natalitia__Bolus
Erica__oatesii
Erica__species
Vaccinum_exul
Erythroxylum__delagoense
Erythroxylum__emarginatum
Choristylis__rhamnoides
Acalypha__glabrata
Acalypha__pubiflora
Andrachne__ovalis
1
0
1
0
1
1
0
0
0
1
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
0
0
0
1
1
1
0
1
0
0
0
0
0
0
0
0
0
0
0
1
65
0
27
26
59
26
9
8
7
35
1
4
0
0
11
5
18
0
24
24
4
6
69
51
31
19
1
16
33
62
33
3
22
12
32
9
9
1
18
24
24
24
23
1
13
140
39
4
11
31
33
0
0
0
0
0
0
0
2
6
0
0
0
2
1
35
0
1
4
4
2
20
0
0
37
9
8
0
18
0
0
0
0
0
0
0
5
0
3
5
0
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Androstachys__johnsonii
Antidesma__venosum
Alchornea__laxiflora
Clutia___affinis
Clutia__pulchella
Croton__gratissimus
Croton__madandensis
Croton__megalobotrys
Croton__menyhartiI
Croton__pseudopulchellus
Croton__steenkampianus
Croton__sylvaticus
Erythrococca__menyharthii
Euphorbia__confinalis
Euphorbia__cooperi
Euphorbia__espinosa
Euphorbia__evansii
Euphorbia__excelsa
Euphobia__grandialata
Euphorbia__grandicornis
Euphorbia__grandidens
Euphorbia _guerichiana
Euphorbia__ingens
Euphorbia__lydenburgensis
Euphorbia__rowlandii
Euphorbia__tirucalli
Euphorbia__sekukuniensis
Euphorbia_species
Euphorbia__triangularis
Sapium__ellipticum
Sapium___integerrimum
Spirostachys_africana
Suregada_africana
Synadenium__cupulare
Acacia _ataxacantha
Acacia__borleae
Acacia__brevispica
Acacia_burkei
Acacia__caffra
Acacia__chariessa
Acacia__ebutsiniorum
Acacia__davyi
Acacia__erioloba
Acacia__erubescens
Acacia__exuvialis
1
1
0
1
1
1
0
1
0
1
1
1
0
0
0
0
0
0
0
0
1
0
1
0
0
1
0
0
0
1
1
1
0
1
0
0
0
1
1
0
0
0
1
0
0
0
24
0
15
35
31
2
6
14
0
1
6
5
3
23
0
13
4
1
2
1
1
43
5
0
22
6
2
6
9
2
34
15
8
55
3
1
40
77
1
1
24
5
8
32
141
8
4
7
1
0
10
5
15
2
3
3
1
2
7
3
4
0
0
0
0
0
1
7
0
2
8
0
0
0
0
0
20
0
2
0
12
1
21
7
0
0
0
0
26
20
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Acacia__galpini
Acacia__gerrardii
Acacia__grandicornuta
Acacia__karroo
Acacia__luederitzii
Acacia__mellifera
Acacia__nigrescens
Acacia__nilotica
Acacia__permixta
Acacia_ polyacantha
Acacia__robusta
Acacia_robusta_robust
Acacia__schweinfurthii
Acacia Senegal
Acacia_senegal_Brenan
Acacia__sieberiana
Acacia__tenuispinaL
Acacia__swazica
Acacia__tortilis
Acacia_welwitschii
Acacia__xanthophloea
Adenopodia__spicata
Aeschynomene__nodulosa
Aeschynomene__rehmannii
Afzelia__quanzensis
Albizia__adianthifolia
Albizia___amara
Albizia__anthelmintica
Albizia__brevifolia
Albizia__forbesii
Albizia__harveyi
Albizia__petersiana
Albizia__tanganyicensis
Albizia__versicolor
Baphia__massaiensis
Bauhinia_galpinii
Bauhinia_tomentosa
Bolusanthus_speciosus
Burkea_africana
Calpurnia__aurea
Calpurnia_glabrata
Calpurnia__sericea
Cassia_abbreviata
Colophospermum_mopane
Cordyla__africana
0
1
0
1
1
0
1
1
0
1
1
0
0
0
0
1
0
0
1
0
1
1
0
0
1
1
1
1
0
1
0
1
0
1
0
0
1
1
1
1
1
0
1
1
1
11
26
18
85
21
19
44
64
1
3
24
28
16
17
24
47
2
18
51
0
1
24
3
31
0
2
0
21
5
0
17
5
1
25
0
39
9
25
24
26
7
5
0
1
0
142
0
19
19
3
1
0
27
21
0
2
18
0
6
7
9
5
0
2
28
9
21
0
0
0
18
2
4
4
12
17
35
13
2
10
2
2
0
28
2
2
0
0
20
28
2
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Crotalaria___capensis
Crotalaria__doidgeae
Crotalaria__laburnifolia
Crotalaria__monteiroi
Crotalaria___natalitia
Crotalaria__pallida
Dalbergia__armata
Dalbergia__melanoxylon
Dalbergia___nitidula_ Baker
Dalbergia__obovata
Dichrostachys_cinerea_Brummitt
Dichrostachys__cinerea_ Brenan
Elephantorrhiza__burkii
Elephantorrhiza__elephantina
Elephantorrhiza__obliqua
Elephantorrhiza_praetermissa
Eriosema__psoraleoides
Elephantorrhiza__goetzei
Erythrina__humeana
Erythrina__latissima
Erythrina__lysistemon
Erythrina__zeyheri
Faidherbia__albida
Guibourtia__conjugata
Indigofera__arrecta
Indigofera__fulgens
Indigofera___homblei
Indigofera__lupatana
Indigofera___swaziensis
Indigofera__tinctoria
Indigofera__tristoides
Mundulea__sericea
Newtonia__hildebrandtii
Ormocarpum_kirkii
Ormocarpum___trichocarpum
Peltophorum_ africanum
Philenoptera__violacea
Piliostigma__thonningii
Pseudarthria__hookeri
Pterocarpus__angolensis
Pterocarpus__lucens
Pterocarpus__rotundifolius
Pterolobium__stellatum
Schotia_brachypetala
Schotia__capitata
0
0
0
0
0
0
0
1
0
1
1
1
1
1
0
0
1
1
1
0
1
0
1
0
1
0
0
0
0
0
0
1
1
0
1
1
1
1
0
1
0
0
0
1
1
21
8
12
17
4
7
40
18
5
1
68
42
21
41
4
6
39
4
15
17
55
29
9
0
17
0
7
6
24
0
27
56
0
14
18
69
24
17
26
36
0
42
11
41
8
143
0
1
13
2
0
2
0
34
4
0
33
15
5
4
0
0
6
4
10
0
3
0
9
4
2
1
0
7
5
6
0
23
2
0
23
35
36
3
2
7
1
29
0
28
14
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Flacourtiacae
Hamamelidaceae
Gentianaceae
Hernandiaceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Icacinaceae
Icacinaceae
Kirkiaceae
Kirkiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lauraceae
Lauraceae
Linaceae
Loganiaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Schotia___latifolia
Senna__petersiana
Xanthocercis__zambesiaca
Xeroderris__stuhlmannii
Xylia_torreana
Aphloia__theiformis
Trichocladus__grandiflorus
Anthocleista___grandiflora
Gyrocarpus americanus
Hippocratea_ africana
Hippocratea_ crenata
Hippocratea_ indica
Hippocratea__longipetiolata
Hippocratea_parvifolia Oliv.
Apodytes__dimidiata
Cassinopsis__ilicifolia (Hochst.) Kuntze
Kirkia__acuminata
Kirkia__wilmsii
Clerodendrum__glabrum
Clerodendrum__pleiosciadium
Karomia_speciosa
Leonotis__intermedia
Leonotis__leonurus
Leonotis__nepetifolia
Premna__mooiensis
Rhotheca__myricoides
Hemzygia__albiflora
Plectranthus__fruticosus
Hemizygia__parvifolia
Pycnostachys__urticifolia
Salvia__dolomitica
Syncolostemon__eriocephalus
Tetradenia__brevispicata
Tetradenia__riparia
Tinnea__barbata
Tinnea__rhodesiana
Vitex__ferruginea
Vitex___harveyana
Vitex___obovata
Vitex__patula
Vitex_rehmannii
Cryptocarya_ transvaalensis
Cryptocarya__woodii
Hugonia__orientalis
Strychnos__cocculoides
0
1
0
1
0
0
0
1
1
0
0
0
0
0
1
0
0
0
1
0
1
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
1
1
1
0
0
2
25
6
0
0
4
14
11
0
3
0
0
17
3
42
30
3
29
50
0
16
4
6
0
28
44
17
29
3
11
6
11
9
42
4
16
2
2
28
0
11
14
26
0
11
144
0
16
23
4
2
0
0
3
4
3
9
4
12
6
0
1
15
0
10
3
6
0
0
0
1
4
0
0
0
4
0
0
0
5
0
4
8
8
2
3
1
0
0
3
0
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
Proteaceae
Proteaceae
Rosaceae
Lythraceae
Malpighiaceae
Malpighiaceae
Malpighiaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Marattiaceae
Celastraceae
Meliaceae
Meliaceae
Meliaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Strychnos__decussata
Strychnos__henningsii
Strychnos__madagascariensis
Strychnos_potatorum
Strychnos_pungens
Strychnos__spinosa
Strychnos__usambarensis
Leucospermum__gerrardii
Leucospermum__saxosum
Leucosidea__sericea
Galpinia_transvaalica
Acridocarpus_natalitius
Triaspis_glaucophylla
Triaspis__hypericoides
Abutilon__angulatum
Abutilon__sonneratum
Adansonia_digitata
Azanza__garckeana
Cola__greenwayi
Dombeya__burgessiiae
Dombeya__cymosa
Dombeya__rotundifolia
Gossypium__herbaceum
Grewia_ bicolor
Grewia__caffra
Grewia__flavescens
Grewia__flavescens
Grewia__gracillima
Grewia__hexamita
Grewia__inaequilatera
Grewia__microthyrsa
Grewia__monticola
Grewia__sulcata
Grewia__occidentalis
Grewia__villosa
Hibiscus__calyphyllus
Hibiscus_micranthus
Sterculia__murex
Sterculia__rogersii
Triumfetta__pilosa
Marattia__faxinea
Mystroxylon__aethiopicum
Ekebergia__capensis
Ekebergia__pterophylla
Entandrophragma__caudatum
1
1
0
1
1
1
1
0
0
1
0
1
0
1
1
1
1
0
1
0
1
1
0
1
1
1
1
0
0
0
0
0
1
1
0
0
0
0
0
1
0
1
1
0
0
7
16
54
0
10
33
8
4
3
35
11
7
21
2
6
5
2
0
3
4
10
65
16
28
11
35
33
0
22
2
0
40
48
48
5
26
14
12
18
27
9
17
30
26
0
145
25
1
37
5
1
31
4
0
0
0
14
0
0
0
4
0
8
1
0
0
2
1
10
25
7
0
13
2
19
3
8
21
2
2
9
4
8
0
5
2
0
1
4
0
3
Meliaceae
Meliaceae
Meliaceae
Meliaceae
Meliaceae
Melianthaceae
Melianthaceae
Melianthaceae
Melianthaceae
Melastomataceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Myricaceae
Myricaceae
Myricaceae
Myricaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Nyctaginaceae
Ochnaceae
Ochnaceae
Ochnaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Trichilia__dregeana
Trichilia__emetica
Turraea__floribunda
Turraea__nilotica
Turraea__obtusifolia
Bersama__lucens
Bersama__tysoniana
Greyia__radlkoferi
Greyia_sutherlandii
Memecylon__natalense
Ficus__abutilifolia
Ficus__burkei
Ficus__burtt_davyi
Ficus__capreifolia
Ficus__craterostoma
Ficus_ glumosa
Ficus__ingens
Ficus natalensis
Ficus__petersii
Ficus__salicifolia
Ficus__sansibarica
Ficus__stuhlmannii
Ficus__sur__Forssk.
Ficus_sycomorus
Ficus_tettensis
Maclura_africana
Myrica_pilulifera
Morella_brevifolia
Morella_microbracteata
Morella_ serrata
Eugenia__woodii
Eugenia__mossambicencis
Eugenia__natalitia
Heteropyxis__canescens
Heteropyxis__natalensis
Syzygium__cordatum
Syzygium__gerrardii
Syzygium__guineense
Syzygium__legatii
Syzygium_species
Syzygium_species
Phaeoptilium__spinosum
Ochna__arborea
Ochna _inermis
Ochna__natalitia
0
1
1
1
1
1
1
0
1
0
0
0
0
0
0
1
0
1
0
1
0
0
1
1
0
1
0
0
0
1
0
0
0
0
1
1
1
0
0
0
0
0
0
0
1
8
20
3
9
28
4
13
29
18
1
36
39
1
8
19
33
51
0
13
36
6
14
50
25
6
4
31
6
3
26
7
6
20
9
41
45
18
22
7
1
1
0
15
14
39
146
0
8
0
2
10
0
0
0
0
0
10
0
0
6
0
4
6
1
1
2
3
0
2
20
0
9
0
0
0
3
0
3
0
0
1
17
0
14
0
0
0
1
0
9
5
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
Lauraceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Oleaceae
Oleaceae
Onagraceae
Osmundaceae
Santalaceae
Chrysobalanaceae
Passifloraceae
Passifloraceae
Passifloraceae
Passifloraceae
Pedaliaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Picrodendraceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Ochna__pulchra
Ochna__oconnori
Ochna__serrulata
Ochna__barbosae
Ochna__confusa
Ochna_gamostigmata
Ochna__holstii
Ocotea__bullata
Ocotea___kenyensis
Olax_dissitiflora
Ximenia__americana
Ximenia_ caffra
Chionanthus__battiscombei
Chionanthus__foveolatus
Chionanthus_foveolatus_Stearm
Chionanthus__peglerae
Jasmimun__abyssinicum
Jasminum_breviflorum
Jasminum__fluminense
Jasminum__multipartitum
Jasminum__stenolobum
Olea__capensis
Olea_capensis_macrocarpa
Olea__europaea
Schrebera__alata
Ludwigia_octovalvis
Todea_barbara
Osyris__lanceolata
Parinari__curatellifolia
Adenia_spinosa
Adenia_fruticosa
Adenia_gummifera
Paropsia__braunii
Sesamothamnus__lugardii
Antidesma__venosum
Bridelia_cathartica
Bridelia_micrantha
Bridelia_mollis
Flueggea__virosa
Hymenocardia__ulmoides
Margaritaria__discoidea
Phyllanthus_pinnatus
Phyllanthus__reticulatus
Pseudolachnostylis__maprouneaefolia
Androstachys__johnsonii
1
1
1
0
0
0
1
1
1
0
1
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
0
1
0
0
1
1
1
1
1
0
1
0
1
1
1
13
15
14
0
16
6
15
4
7
13
29
55
0
37
7
7
3
6
21
19
16
33
9
49
40
11
4
35
14
0
8
18
0
2
20
15
18
18
35
0
3
1
22
6
0
147
5
0
0
1
0
0
0
0
0
11
23
26
2
2
0
0
0
0
8
1
7
1
0
1
10
2
0
0
2
2
0
2
2
3
7
12
3
8
24
7
4
10
19
10
8
Piperaceae
Pittosporaceae
Plumbaginaceae
Podcarpaceae
Polygalaceae
Polygalaceae
Polygalaceae
Portulacaceae
Primulaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Rosaceae
Putranjavaceae
Putranjavaceae
Ranunculaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rosaceae
Rosaceae
Rosaceae
Rosaceae
Rosaceae
Rosaceae
Rubiaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Piper__capense
Pittosporum__viridiflorum
Plumbago__auriculata
Afrocarpus__falcatus
Podocarpus__latifolius
Securidaca__longipedunculata
Polygala__virgata
Portulacaria_afra
Maesa__lanceolata
Faurea_galpinii
Faurea__macnaughtonii
Faurea__rochetiana
Faurea__saligna
Protea__caffra
Protea__caffra__falcata
Protea__comptonii
Protea__curvata
Protea__gaguedi
Protea__laetans
Protea__parvula
Protea__roupelliae
Protea__rubropilosa
Protea__simplex
Protea___subvestita
Protea__wewitschii
Prunus__africana
Drypetes__gerrardii
Drypetes__reticulata
Clematis__brachiata
Berchemia__discolor
Berchemia__zeyheri
Helinus__integrifolius
Phylica_paniculata
Rhamnus__prinoides
Scutia__myrtina
Ziziphus_mucronata
Ziziphus__rivularis
Ziziphus__zeypherana
Cliffortia__linearifolia
Cliffortia__nitididula
Cliffortia__repens
Cliffortia___serpylliflia
Cliffortia__strobilifera
Anthospermum__welwitschii
Breonadia__salicina
1
1
1
1
0
1
1
0
1
0
1
1
0
1
0
0
0
1
0
0
1
0
0
0
1
1
0
0
1
1
1
1
0
1
1
1
0
0
0
0
0
0
0
0
0
8
52
4
19
30
3
33
6
42
17
3
32
60
60
5
4
1
29
3
13
35
8
5
1
24
20
4
0
42
6
46
38
21
38
19
65
1
24
27
22
16
4
15
14
27
148
1
1
1
0
0
1
0
3
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
1
8
4
3
2
1
0
17
6
0
0
0
0
0
0
0
4
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Burchellia__bubalina
Canthium__ciliatum
Canthium__inerme
Canthium__setiflorum
Catunaregam__spinosa
Cephalanthus__natalensis
Coddia__rudis
Crossopteryx__febrifuga
Gardenia__resiniflua
Gardenia__volkensii
Heinsia__crinita
Hymenodictyon__parvifolium
Hyperacanthus__amoenus
Keetia_ guenzii
Kraussia__floribunda
Lagynia__dryadum
Leptactina__delagoensis
Oxyanthus__speciosus
Pachystigma__bowkeri
Pachystigma__macrocalyx
Pavetta__barbertonensis
Pavetta_catophylla
Pavetta__cooperi
Pavetta_edentula
Pavetta__harborii
Pavetta__lanceolata
Plectroniella__armata
Psychotria_capensis
Psychotria___zombamontana
Psydrax_ locuples
Pyrostria__hystrix
Rothmannia__fischeri
Tarenna_supra_axillaris
Tarenna__zygon
Tricalysia__junodii
Tricalysia__lanceolata
Vangueria__infausta
Vangueria__madagascariensis
Vangueria__parvifolia
Calodendrum__capensis
Clausena_anisata
Ptaeroxylon__obliquum
Teclea__pilosa
Teclea__gerrardii
Teclea__natalensis
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
21
20
39
0
10
40
26
0
1
21
0
0
28
15
16
0
0
16
5
24
3
6
18
22
0
16
17
38
7
4
6
29
24
0
2
36
60
19
8
27
37
20
4
2
3
149
0
0
0
5
9
0
6
3
0
10
5
5
2
0
2
4
1
0
0
0
0
11
0
0
3
2
6
0
0
3
3
0
0
3
10
0
11
0
0
0
3
9
6
0
0
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Salicaceae
Gerrardinaceae
Salicaceae
Salicaceae
Salicaceae
Salicaceae
Salicaceae
Salicaceae
Salvadoraceae
Salvadoraceae
Salvadoraceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Rutaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Toddalia__asiatica
Toddaliopsis__bremekampii
Vepris__lanceolata
Vepris__reflexa
Zanthoxylum__carpense
Zanthoxylum__davyi
Zanthoxylum__humile
Zanthoxylum__leprieurii
Flacourtia__indica
Gerrardina__foliosa
Homalium_dentatum
Oncoba__spinosa
Salix__mucronata
Rawsonia__lucida
Scolopia__zeyheri
Trimeria__grandifolia
Azima__tetracantha
Salvadora__australis
Salvadora__persica
Allophylus__decipiens
Deinbollia__oblongifolia
Deinbollia__xanthocarpa
Dodonaea_angustifolia_L.f
Hippobromus__pauciflorus
Pappea__capensis
Stadmannia_oppositifolia
Ptaeroxylon__obliquum
Englerophytum__magalismontanum
Englerophytum__natalense
Manilkara__concolor
Manilkara__discolor
Manilkara__mochisia
Mimusops__obovata
Mimusops__zeyheri
Sideroxylon__inerme
Vitellariopsis__marginata
Lycium__cinereum
Lycium__shawii
Solanum__aculeastrum
Solanum__anguivi
Solanum__catombelense
Solanum_giganteum
Solanum___lichtensteinii
Solanum_kwebense
Solanum_panduriforme
0
0
1
0
1
1
0
0
1
1
0
1
1
0
0
1
1
0
1
0
1
0
1
1
1
0
1
1
0
1
1
0
1
0
1
1
0
0
1
0
0
1
1
1
1
8
0
16
43
54
16
2
0
21
9
26
9
43
15
21
37
3
4
0
0
2
0
27
38
46
0
20
70
13
8
1
15
12
46
18
4
8
3
16
13
1
32
39
2
53
150
0
3
0
8
0
0
12
3
3
0
1
5
1
0
0
0
5
4
3
1
1
3
2
2
14
3
7
4
0
0
0
22
0
13
7
3
0
1
0
0
2
2
6
2
12
Solanaceae
Scrophulariaceae
Scrophulariaceae
Stilbaceae
Stilbaceae
Stilbaceae
Stilbaceae
Stilbaceae
Streliziaceae
Thymelaeaceae
Thymelaeaceae
Ulmaceae
Urticaceae
Urticaceae
Velloziaceae
Verbenaceae
Verbenaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Menispermaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Penaeaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Rutaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Thymelaeaceae
Thymelaeaceae
Rhizophoraceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Exotic
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Exotic
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Solanum__rubetorum
Bowkeria__citrina
Bowkeria__cymosa
Halleria__lucida
Nuxia__congesta
Nuxia__floribunda
Nuxia__gracilis
Nuxia__oppositifolia
Strelitzia_caudata
Dais_cotinifolia_L
Englerodaphne__pilosa
Chaetachne__aristata
Obetia__tenax
Pouzolzia__mixta
Xerophyta_retinervis
Lantana_rugosa
Lippia_javanica
Cissus__cactiformis
Cissus__cornifolia
Rhoicissus_digitata
Rhoicissus_revoilii
Rhoicissus__tomentosus
Rhoicissus__tridentata
Kotschya__parvifolia
Kotschya__thymodora
Tiliacora__funifera
Flemingia__grahamiana
Lessertia__microphylla
Otholobium__wilmsii
Psoralea__glabra
Psoralea__latifolia
Psoralea___rhizotoma
Rhynchosia__clivorum
Sesbania__sesban
Tephrosia__cordata
Tephrosia___polystachya
Tephrosia__rhodesica
Tephrosia__subulata
Oricia__bachmannii
Margaritaria__discoidea
Margaritaria__discoidea_ subsp_Baill
Micrococca__capensis
Passerina_montana
Peddiea__africana
Cassipourea__malosana
0
0
0
1
0
1
0
1
0
0
0
1
1
1
1
1
1
1
0
1
1
1
1
0
0
0
0
1
0
0
1
0
0
1
0
0
0
0
0
0
1
0
0
1
1
12
1
22
48
43
21
5
23
9
29
3
29
22
27
52
43
57
6
8
6
15
28
50
7
5
1
18
10
32
2
23
3
15
23
9
11
22
11
2
1
3
3
21
21
12
151
0
0
0
0
0
1
0
21
0
0
0
0
5
10
3
10
4
5
19
0
5
0
2
0
0
0
1
0
0
0
0
0
0
12
0
1
9
0
0
0
4
0
0
0
0
Rhizophoraceae
Salicaceae
Salicaceae
Salicaceae
Salicaceae
Scrophulariaceae
Scrophulariaceae
Scrophulariaceae
Scrophulariaceae
Scrophulariaceae
Native
Native
Native
Native
Native
Native
Native
Native
Native
Native
Cassipourea__swaziensis
Dovyalis__caffra
Dovyalis__lucida.
Dovyalis__rhamnoides
Dovyalis__zeyheri
Buddleja_auriculata
Buddleja___dysophylla
Buddleja__puchella
Buddleja__saligna
Buddleja_salviifolia
0
0
0
0
0
0
0
0
1
1
3
19
13
13
45
36
4
6
20
60
152
0
7
0
0
2
0
0
0
0
0
APPENDIX B
APPARENCY THEORY AND RESOURCES AVAILABILITY DATA SET
family_apg_IV
origin
Acanthaceae
native Anisotes_formosissimus
Acanthaceae
native Anisotes_rogersii
Acanthaceae
native Barleria_albostellata
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Acanthaceae
Achariaceae
Achariaceae
Anacardiaceae
genus_species
native Barleria_rotundifolia
native
native
native
native
native
native
native
native
native
native
native
native
Duvernoia_aconitiflora
Duvernoia_adhatodoides
Justicia__campylostemon
Mackaya__bella
Metarungia__longistrobus
Ruspolia__hypocrateriformis
Ruttya__ovata
Sclerochiton_harveyanus
Sclerochiton_ilicifoloius
Kiggelaria__africana
Xylotheca__kraussiana
Harpephyllum__caffrum
probability_ wood density growth rate Height lifeform
overuse
653
0,001531
2,5 tree
0
645,89
0,001548
2 tree
0
678
0,001475
2 tree
0
640
0,001563
2 tree
0
0
455,3562
0,002196
3 tree
0
560
0,001786
6 tree
0
653
0,001531
2,5 tree
0
849
0,001178
4 tree
0
678
0,001475
2 tree
0
455,3562
0,002196
3 tree
0
849
0,001178
4 tree
0
849
0,001178
4 tree
0
678
0,001475
2 tree
0
545,55
0,001833
15 tree
0
640
0,001563
2 tree
0
715,8333
0,001397
15 tree
dbh
UV
0,761459
-0,19901
0,513973
-0,11662
0,513973
-0,11662
total_use
0
0
0
0,513973
-0,11662
1,049841 -0,08805
3,559476 -0,03922
0,761459
-0,1009
1,742619 -0,06778
0,513973 -0,11662
1,049841 -0,08805
1,742619 -0,06778
1,742619 -0,06778
0,513973 -0,11662
17,87948 0,025346
0,513973 -0,11662
17,87948 0,025346
1
0
1
0
2
0
0
0
0
2
4
4
3
145
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Lannea_discolor
Lannea_edulis
Lannea__gossweilleri
Lannea_schweinfuthii
Ozoroa__barbertonensis
Ozoroa__engleri
Ozoroa__obovata
Ozoroa__paniculosa
Ozoroa_paniculosa_salicina
Protorhus__longifolia
Ozoroa__sphaerocarpa
Sclerocarya__birrea
Rhus__batophylla
Sersia_chirindensis
Rhus_dentata
Rhus__discolor
Rhus__dracomontana
Rhus__engleri
Rhus__gerrardi
Rhus__gracillima
Rhus__grandidens
Rhus__guenzii
Rhus__harveyi
Rhus__keetii
Rhus_lancea
Rhus__leptodictya
Rhus__lucida
Rhus__magalismontana__magalismotana
Rhus_ magalismontana_coddi
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
485
430
401
592,56
645,89
675
675
675
675
715,8333
645
440
645,89
701,9091
498,56
774,8
645,89
455,3562
678
774,8
678
689
774,8
689
725
698,6326
455,3562
653
653
0,002062
0,002326
0,002494
0,001688
0,001548
0,001481
0,001481
0,001481
0,001481
0,001397
0,00155
0,002273
0,001548
0,001425
0,002006
0,001291
0,001548
0,002196
0,001475
0,001291
0,001475
0,001451
0,001291
0,001451
0,001379
0,001431
0,002196
0,001531
0,001531
3
14
14
15
1,5
6
7,5
7,5
6
15
1,5
18
2
23
5
1
1,5
3
2
1
2
8
1
8
12
9
3
0,5
2,1
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
shrub
tree
1,049841
15,83342
15,83342
17,87948
0,309643
3,559476
5,273421
5,273421
3,559476
17,87948
0,309643
24,65086
0,513973
37,9623
2,581718
0,151592
0,309643
1,049841
0,513973
0,151592
0,513973
5,908331
0,151592
5,908331
12,06837
7,270591
1,049841
0,044711
0,560099
-0,08805
0,020485
0,020485
0,025346
-0,13689
-0,03922
-0,02349
-0,02349
-0,03922
0,025346
-0,13689
0,038192
-0,11662
0,055464
-0,05206
-0,16546
-0,13689
-0,08805
-0,11662
-0,16546
-0,11662
-0,01895
-0,16546
-0,01895
0,009624
-0,01065
-0,08805
-0,2143
-0,11319
4
0
0
2
0
0
0
0
0
1
1
1
1
2
2
0
0
1
0
0
0
1
0
0
1
1
0
0
0
146
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Anacardiaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Annonaceae
Penaeaceae
Penaeaceae
Penaeaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Rhus__montana
Rhus__pallens
Rhus__pentheri
Rhus__pondoensis
Rhus__pygmaea
Rhus__pyroides__pyroides
Rhus__pyroides__gracilis
Rhus__rehmanniana
Rhus___sekhukhuniensis
Rhus__species
Rhus__tomentosa
Rhus__transvaalensis
Rhus_ tumulicola_tumulicola
Rhus__tumulicola___meeuseana
Rhus_ tumulicola_pumila
Rhus__wilmsii
Rhus__zeyheri
Annona__senegalensis
Artabotrys__brachypetalus
Hexalobus__monopetalus
Monanthotaxis_caffra
Monodora_junodii_junodii
Monodora__junodii__macrantha
Uvaria_gracilipes
Uvaria_lucida
Xylopia__parviflora
Olinia__emarginata
Olinia__radiata
Olinia__rochetiana
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
0
0
0
455,3562
849
762,2
774,8
653
599,9
675
675
455,3562
849
675
678
455,3562
774,8
653
653
678
603,33
510
748,6
750
712
780
593
640
786,275
498,56
786,275
849
0,002196
0,001178
0,001312
0,001291
0,001531
0,001667
0,001481
0,001481
0,002196
0,001178
0,001481
0,001475
0,002196
0,001291
0,001531
0,001531
0,001475
0,001657
0,001961
0,001336
0,001333
0,001404
0,001282
0,001686
0,001563
0,001272
0,002006
0,001272
0,001178
3
4
6
1
0,1
6
6
5
3
4
5
2
3,5
1
0,5
0,5
2
5
10
7
3
7
5
2
2
20
5
20
4
tree
tree
tree
tree
shrub
tree
tree
tree
tree
tree
tree
tree
tree
tree
shrub
shrub
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
1,049841
1,742619
3,559476
0,151592
0,002625
3,559476
3,559476
2,581718
1,049841
1,742619
2,581718
0,513973
1,377368
0,151592
0,044711
0,044711
0,513973
2,581718
8,753288
4,669952
1,049841
4,669952
2,581718
0,513973
0,513973
29,67794
2,581718
29,67794
1,742619
-0,08805
-0,06778
-0,03922
-0,16546
-0,3277
-0,03922
-0,03922
-0,05206
-0,08805
-0,06778
-0,05206
-0,11662
-0,07719
-0,16546
-0,2143
-0,2143
-0,11662
1,909382
2,397772
2,14646
1,549456
2,14646
1,909382
1,263766
1,263766
2,886162
-0,05206
0,045616
-0,06778
0
0
1
0
0
2
0
0
0
0
0
0
0
0
0
0
0
2
1
1
4
2
2
0
1
0
2
1
0
147
Penaeaceae
Apiaceae
Apiaceae
Apiaceae
Apiaceae
Apiaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Apocynaceae
Aquifoliaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Xymalos__monospora
Heteromorpha arborescensa_abyssinica
Heteromorpha arborescens_fruitescens
Heteromorpha__involucrata
Heteromorpha__pubescens
Steganotaenia__araliacea
Acokanthera__oppositifolia
Acokanthera__rotundata
Adenium__multiflorum
Adenium__swazicum
Ancyloboyrys__capensis
Carissa_bispinosa
Carissa_bispinosa
Carissa__edulis
Carissa__tetramera
Diplorhynchus__condylocarpon
Gonioma__kamassi
Holarrhena__pubescens
Landolphia__kirkii
Pachypodium_saundersii
Rauvolfia__caffra
Strophanthus__gerrardii
Strophanthus__kombe
Strophanthus__petersianus
Strophanthus__speciousus
Tabernaemontana__elegans
Tabernaemontana__ventricosa
Wrightia__natalensis
Ilex__mitis
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
529,95
749,4889
455,3562
645,89
645,89
689
603,33
700
750
745
640
750
539,8
539,8
750
727,6667
698,6326
603,33
640
603,33
691,06
700
745,2356
748
774,7667
451,2
451,2
725
609,5
0,001887
0,001334
0,002196
0,001548
0,001548
0,001451
0,001657
0,001429
0,001333
0,001342
0,001563
0,001333
0,001853
0,001853
0,001333
0,001374
0,001431
0,001657
0,001563
0,001657
0,001447
0,001429
0,001342
0,001337
0,001291
0,002216
0,002216
0,001379
0,001641
25
10
3
1,5
1,5
8
5
6
3
1
2
3
5
5
3
8
10
5
4
5
18
6
7
17
15
8
8
12
30
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
43,96834
8,753288
1,049841
0,309643
0,309643
5,908331
2,581718
3,559476
1,049841
0,151592
0,513973
1,049841
2,581718
2,581718
1,049841
5,908331
8,753288
2,581718
1,742619
2,581718
24,65086
3,559476
4,669952
22,28977
17,87948
5,908331
5,908331
12,06837
60,6202
0,061339
-0,00322
-0,08805
-0,13689
-0,13689
-0,01895
-0,05206
-0,03922
-0,08805
-0,16546
-0,11662
-0,08805
-0,05206
-0,05206
-0,08805
-0,01895
-0,00322
-0,05206
-0,06778
-0,05206
0,038192
-0,03922
-0,02835
0,034165
0,025346
-0,01895
-0,01895
0,009624
0,074185
2
1
0
0
0
0
1
1
2
0
1
1
2
2
1
3
1
1
0
1
1
1
1
1
1
0
2
2
4
148
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Araliaceae
Arecaceae
Arecaceae
Arecaceae
Arecaceae
Asparagaceae
Asparagaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Xanthorrhoeaceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Cussonia__natalensis
Cussionia__paniculata
Cussonia__spicata
Cussonia__sphaerocephala
Cussonia__transvaalensis
Schefflera__umbellifera
Seemannaralia__gerrardii
Borassus__aethiopium
Hyphaene__coriacea
Hyphaene__petersiana
Phoenix__reclinata
Dracaena__aletriformis
Dracaena___transvaalensis
Aloe_excelsa
Aloe__alooides
Aloe_angelica
Aloe_arborescens
Aloe_barberae
Aloe_castanea
Aloe__littoralis
Aloe_marlothii
Aloe_spicata
Brachylaena__discolor
Brachylaena__huillensis
Anisopappus__junodii
Anisopappus__smutsii
Brachylaena__ilicifolia
Brachylaena__rotundata
Brachylaena__transvaalensis
1
1
1
1
1
1
1
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
560
645,6
526,076
691,06
603,33
805
786,275
805
790
440
250
849
675
640
595
498,998
524,5
526,076
524,5
498,998
700
645
696,3875
655,6
645,89
653
675
689
846,8333
0,001786
0,001549
0,001901
0,001447
0,001657
0,001242
0,001272
0,001242
0,001266
0,002273
0,004
0,001178
0,001481
0,001563
0,001681
0,002004
0,001907
0,001901
0,001907
0,002004
0,001429
0,00155
0,001436
0,001525
0,001548
0,001531
0,001481
0,001451
0,001181
11
6
18
25
5
20
20
20
7
18
6
4
5
4
3
4
3
18
3
4
6
2
10
10
2
1,8
5
8
25
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
10,35343
3,559476
24,65086
43,96834
2,581718
29,67794
29,67794
29,67794
4,669952
24,65086
3,559476
1,742619
2,581718
1,742619
1,049841
1,742619
1,049841
24,65086
1,049841
1,742619
3,559476
0,513973
8,753288
8,753288
0,513973
0,426912
2,581718
5,908331
43,96834
0,003493
-0,03922
0,038192
0,061339
-0,05206
0,045616
0,045616
7,656162
6,91646
7,581925
6,807845
-0,06778
-0,05206
-0,06778
-0,08805
-0,06778
-0,08805
0,038192
-0,08805
-0,06778
-0,03922
-0,11662
-0,00322
-0,00322
-0,11662
-0,12405
-0,05206
-0,01895
0,061339
0
2
2
1
1
1
0
1
3
1
4
2
0
0
1
2
3
3
2
2
1
0
3
1
1
0
1
0
1
149
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Asteraceae
Balanitaceae
Balanitaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Bignoniaceae
Boraginaceae
native
native
exotic
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Eumorphia___davyi
Eumorphia___swaziensis
Helichrysum__kraussii
Lopholaena__corifolia
Lopholaena__platyphylla
Phymaspermum__acerosum
Pulchea_dioscordia
Senecio_barbertonicus
Seriphium__plumosum
Seriphium__species
Tarchonanthus_parvicapitulatus
Tarchonanthus___trilobus
Vernonia__adoensis
Gymnanthemum_amygdalina
Vernonia__aurantiaca
Vernonia__colorata
Vernonia__tigna
Vernonia__triflora
Vernonia__wollastonii
Vernonia__myriantha
Balanites__maughamii
Balanites___pedicillaris
Kigelia_ africana
Rhigozum__obvatum
Rhigozum__obvatum
Rhigozum_brevispinosum
Rhigozum__zambesiacum
Tecoma_capensis
Cordia__caffra
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
678
678
645,89
678
678
645,89
455,3562
645,89
774,8
475
689
749,4889
712,8
455,3562
455,3562
675
645
678
455,3562
675
932,4167
538,4
774,7667
750
750
595
498,998
370,4
748,6
0,001475
0,001475
0,001548
0,001475
0,001475
0,001548
0,002196
0,001548
0,001291
0,002105
0,001451
0,001334
0,001403
0,002196
0,002196
0,001481
0,00155
0,001475
0,002196
0,001481
0,001072
0,001857
0,001291
0,001333
0,001333
0,001681
0,002004
0,0027
0,001336
2
2
1,5
2
2
2
3,5
1,5
1
3
8
10
2,5
3
3
5
1,5
2
3
6
25
8
15
3
3
3
4
2
7
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
0,513973
0,513973
0,309643
0,513973
0,513973
0,513973
1,377368
0,309643
0,151592
1,049841
5,908331
8,753288
0,761459
1,049841
1,049841
2,581718
0,309643
0,513973
1,049841
3,559476
43,96834
5,908331
17,87948
1,049841
1,049841
1,049841
1,742619
0,513973
4,669952
-0,11662
-0,11662
-0,13689
-0,11662
-0,11662
-0,11662
-0,07719
-0,13689
-0,16546
-0,08805
-0,01895
-0,00322
-0,1009
-0,08805
-0,08805
-0,05206
-0,13689
-0,11662
-0,08805
-0,03922
0,061339
-0,01895
2,843461
1,709456
1,709456
1,709456
1,912156
1,423766
-0,02835
0
0
0
0
0
1
0
0
0
2
2
0
3
1
0
0
1
0
0
0
3
2
2
2
1
0
0
2
1
150
Boraginaceae
Boraginaceae
Boraginaceae
Boraginaceae
Boraginaceae
Boraginaceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Burseraceae
Euphorbiaceae
Buxaceae
Canellaceae
Cannabaceae
Cannabaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Cordia__grandicalyx
Cordia__monoica
Cordia_ovalis
Ehretia__amoena
Ehretia__obtusifolia
Ehretia__rigida
Commiphora__edulis
Commiphora glandulosa
Commiphora__harveyi
Commiphora__marlothii
Commiphora_mollis
Commiphora_neglecta
Commiphora__pyracanthoides
Commiphora__schimperi
Commiphora__tenuipetiolata
Commiphora__viminea
Commiphora___woodii
Commiphora__zanzibarica
Cleistantus__schlechteri
Buxus_macowani
Warburgia__salutaris
Celtis__africana
Trema__orientalis
Boscia__albitrunca
Boscia__angustifolia
Boscia__foetida__filipes
Boscia__foetida__minima
Boscia__foetida__rehmanniana
Boscia__mossambicensis
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
645,6
839,5
800
700
641,4286
535
525
749,4889
745,2356
865
400
440
630
455,3562
725
560
786,275
745,2356
645,6
640
725
780
725
748,6
640
640
595
595
770
0,001549
0,001191
0,00125
0,001429
0,001559
0,001869
0,001905
0,001334
0,001342
0,001156
0,0025
0,002273
0,001587
0,002196
0,001379
0,001786
0,001272
0,001342
0,001549
0,001563
0,001379
0,001282
0,001379
0,001336
0,001563
0,001563
0,001681
0,001681
0,001299
6
3
4
5
4
5
5
10
7
13
8
8
3
3
12
6
20
7
6
4
12
30
12
7
4
4
0,3
4
6
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
shrub
tree
tree
3,559476
1,049841
1,742619
2,581718
1,742619
2,581718
2,581718
8,753288
4,669952
13,89574
5,908331
5,908331
1,049841
1,049841
12,06837
3,559476
29,67794
4,669952
3,559476
1,742619
12,06837
60,6202
12,06837
4,669952
1,742619
1,742619
0,018182
1,742619
3,559476
-0,03922
-0,08805
-0,06778
-0,05206
-0,06778
-0,05206
3,209382
3,697772
3,44646
3,882633
3,540545
3,540545
2,849456
2,849456
3,826235
3,337845
4,186162
3,44646
-0,03922
-0,06778
0,009624
0,074185
0,009624
-0,02835
-0,06778
-0,06778
-0,25029
-0,06778
-0,03922
2
2
2
1
1
5
3
0
1
1
1
1
0
1
1
2
1
0
2
2
1
4
2
3
0
0
0
1
0
151
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Capparaceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Cadaba_aphylla
Cadaba___natalensis
Cadaba_termitaria
Capparis__fascicularis
Capparis__sepiaria
Capparis__tomentosa
Maerua__angolensis
Maerua__cafra
Maerua__decumbens
Maerua__juncea
Maerua_parvifolia
Maerua__rosmarinoides
Thilachium__africanum
Cassine_peragua
Catha_edulis
Elaeodendron__croceum
Elaeodendron__transvaalense
Elaeodendron__zeyheri
Gymnosporia__heterophylla
Gymnosporia__maranguensis
Gymnosporia_oxycarpa
Gymnosporia__pubescens
Gymnosporia_putterlickioides
Gymnosporia__senegalensis
Gymnosporia_buxifolia
Gymnosporia__glaucophyllia
Gymnosporia__grandifolia
Gymnosporia__harveyana
Hippocratae__africana
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
595
595
595
524,5
524,5
524,5
774,8
498,56
645
677,52
796,8
688,75
641,4286
675
592,56
715,8333
910
741,4
529,9
698,6326
530
455,3562
525,3214
365,8
599,9
849
689
455,3562
741,4
0,001681
0,001681
0,001681
0,001907
0,001907
0,001907
0,001291
0,002006
0,00155
0,001476
0,001255
0,001452
0,001559
0,001481
0,001688
0,001397
0,001099
0,001349
0,001887
0,001431
0,001887
0,002196
0,001904
0,002734
0,001667
0,001178
0,001451
0,002196
0,001349
3
4
3
3
3
3
1
5
2
10
3
7
4
5
10
15
1
15
1,5
9
2,5
3
15
5
4
4
8
3
15
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
1,049841
1,742619
1,049841
1,049841
1,049841
1,049841
0,151592
2,581718
0,513973
8,753288
1,049841
4,669952
1,742619
2,581718
8,753288
17,87948
0,151592
17,87948
0,309643
7,270591
0,761459
1,049841
17,87948
2,581718
1,742619
1,742619
5,908331
1,049841
17,87948
-0,08805
-0,06778
-0,08805
-0,08805
-0,08805
-0,08805
-0,16546
-0,05206
-0,11662
-0,00322
-0,08805
-0,02835
-0,06778
-0,05206
-0,00322
0,025346
-0,16546
0,025346
-0,13689
-0,01065
-0,1009
-0,08805
0,025346
-0,05206
-0,06778
-0,06778
-0,01895
-0,08805
0,025346
1
2
0
0
2
1
1
1
1
1
0
0
3
1
5
3
2
2
0
0
0
0
0
1
3
0
0
1
0
152
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Fabaceae
Fabaceae
Fabaceae
Clusiaceae
Clusiaceae
Clusiaceae
Clusiaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
exotic
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Hippocratea_crenata
Hippocratea__indica
Hippocratea__longipetiolata
Hippocratea_parvifolia
Maytenus_peduncularis
Maytenus__undata
Putterlickia_verrucosa
Salacia__kraussii
Lauridia__tetragona
Pterocelastrus___echinatus
Pterocelastrus__rostratus
Caesalpinia__rostrata
Caesalpinia_decapetala
Cassia_abbreviata
Garcinia__gerrardii
Garcinia__livingstonei
Hypericum__revolutum
Hypericum__roeperianum
Combretum__apiculatum
Combretum__celastroides
Combretum___mkuzense
Combretum_collinum
Combretum__erythrophyllum
Combretum__hereroense
Combretum__imberbe
Combretum__kraussii
Combretum__microphyllum
Combretum__molle
Combretum_mossambicense
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
675
675
689
675
741,4
741,4
220,8
750
741,4
745,2356
786,275
455,3562
455,3562
850
748,6
720,2
595
595
889,5281
640
640
774,7667
709,6611
888,2667
1112,612
786,275
641,4286
712
595
0,001481
0,001481
0,001451
0,001481
0,001349
0,001349
0,004529
0,001333
0,001349
0,001342
0,001272
0,002196
0,002196
0,001176
0,001336
0,001389
0,001681
0,001681
0,001124
0,001563
0,001563
0,001291
0,001409
0,001126
0,000899
0,001272
0,001559
0,001404
0,001681
5
5
8
4,5
15
15
3
3
15
7
20
3
3
7
15
12
3
3
9
4
4
15
12
5
20
20
4
9
3
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
2,581718
2,581718
5,908331
2,144407
17,87948
17,87948
1,049841
1,049841
17,87948
4,669952
29,67794
1,049841
1,049841
4,669952
17,87948
12,06837
1,049841
1,049841
7,270591
1,742619
1,742619
17,87948
12,06837
2,581718
29,67794
29,67794
1,742619
7,270591
1,049841
-0,05206
-0,05206
-0,01895
-0,05949
0,025346
0,025346
-0,08805
-0,08805
0,025346
-0,02835
0,045616
-0,08805
-0,08805
-0,02835
0,025346
0,009624
-0,08805
-0,08805
-0,01065
-0,06778
-0,06778
0,025346
0,009624
-0,05206
0,045616
0,045616
-0,06778
-0,01065
-0,08805
0
0
0
0
0
0
0
3
0
0
2
0
0
2
4
4
2
1
4
0
0
1
3
4
4
3
1
3
1
153
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Combretaceae
Cornaceae
Connaraceae
Cupressaceae
Cyatheaceae
Cyatheaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Combretum__nelsonii
Combretum__padoides
Combretum__woodii
Combretum__zeyheri
Pteleopsis__myrtifolia
Terminalia__phanerophlebia
Terminalia__prunioides
Terminalia__sericea
Curtisia__dentata
Cnestis__polyphylla
Widdringtonia__nodiflora
Cyathea__capensis
Cyathea___degrei
Drypetes__arguta
Drypetes___gerrardi
Drypetes__mossambicensis
Drypetes__reticulata
Diospyros__austro_africana
Diospyros__dichrophylla
Diospyros__galpinii
Diospyros__loureiriana
Diospyros_lycioides
Diospyros__mespiliformis
Diospyros__natalensis
Diospyros__villosa
Diospyros__whyteana
Eucllea__crispa__form__A
Eucllea_ crispa_form_B
Euclea_daphnoides
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
640
745,2356
714,7083
712
762,2
714,7083
1261,25
643,35
846,8333
849
749,4889
849
678
440
675
805
689
750
640
645
700
756,6
677,52
700
595
748,6
595
745,2356
640
0,001563
0,001342
0,001399
0,001404
0,001312
0,001399
0,000793
0,001554
0,001181
0,001178
0,001334
0,001178
0,001475
0,002273
0,001481
0,001242
0,001451
0,001333
0,001563
0,00155
0,001429
0,001322
0,001476
0,001429
0,001681
0,001336
0,001681
0,001342
0,001563
4
7
8
10
6
8
8
8
20
4
10
4
5
8
6
20
8
3
4
1,3
6
3
10
6
3
7
4
7
4
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
1,742619 -0,06778 0
4,669952 -0,02835 0
5,908331 -0,01895 0
8,753288 -0,00322 2
3,559476 -0,03922 1
5,908331 -0,01895 1
5,908331 -0,01895 1
5,908331 -0,01895 2
29,67794 0,045616 3
1,742619 -0,06778 0
8,753288 -0,00322 1
1,742619 -0,06778 0
2,581718 -0,05206 3
5,908331 -0,01895 1
3,559476 -0,03922 0
29,67794 0,045616 1
5,908331 -0,01895 1
1,049841 -0,08805 2
1,742619 -0,06778 0
0,240651 -0,14698 1
3,559476 -0,03922 1
1,049841 -0,08805 2
8,753288 -0,00322 3
3,559476 -0,03922 1
1,049841 -0,08805 1
4,669952 -0,02835 3
1,742619 -0,06778 2
4,669952 -0,02835 1
1,742619 -0,06778 0
154
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ebenaceae
Ericaceae
Ericaceae
Ericaceae
Ericaceae
Ericaceae
Ericaceae
Erythroxylaceae
Erythroxylaceae
Escalloniacea
Euphorbiaceae
Euphorbiaceae
Phyllanthaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Euclea__dewinteri
Euclea__linearis
Euclea_divinorum
Teclea__natalensis
Euclea__undulata
Euclea__species
Euclea__schimperi
Erica__cafforum
Erica__drakensbergensis
Erica__natalitia__Bolus
Erica__oatesii
Erica__species
Vaccinum_exulBolus
Erythroxylum__delagoense
Erythroxylum__emarginatum
Choristylis__rhamnoides
Acalypha__glabrata
Acalypha__pubiflora
Andrachne__ovalis
Androstachys__johnsonii
Antidesma__venosum
Alchornea__laxiflora
Clutia___affinis
Clutia__pulchella
Croton__gratissimus
Croton__madandensis
Croton__megalobotrys
Croton__menyhartiI
Croton__pseudopulchellus
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
645
641,4286
510
401,2867
780
640
832,6
455,3562
678
678
678
645,89
678
675
440
780
770
675
645,6
846,8333
538,4
645
849
560
948,9167
675
545,55
849
675
0,00155
0,001559
0,001961
0,002492
0,001282
0,001563
0,001201
0,002196
0,001475
0,001475
0,001475
0,001548
0,001475
0,001481
0,002273
0,001282
0,001299
0,001481
0,001549
0,001181
0,001857
0,00155
0,001178
0,001786
0,001054
0,001481
0,001833
0,001178
0,001481
2
4
10
8
30
1,5
8
3
2
2
2
1,5
2
6
5
0,5
6
6
6
20
8
1,5
4
6
12
5
15
4
5
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
shrub
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
0,513973
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1
0
3
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0
2
0
0
0
0
1
1
1
0
3
1
2
1
2
1
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1
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155
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
exotic
native
native
native
native
native
native
Croton__steenkampianus
Croton__sylvaticus
Erythrococca__menyharthii
Euphorbia__confinalis
Euphorbia__cooperi
Euphorbia__espinosa
Euphorbia__evansii
Euphorbia__excelsa
Euphobia__grandialata
Euphorbia__grandicornis
Euphorbia__grandidens
Euphorbia__guerichiana
Euphorbia__ingens
Euphorbia__lydenburgensis
Euphorbia__rowlandii
Euphorbia__tirucalli
Euphorbia__sekukuniensis
Euphorbia_species
Euphorbia__triangularis
Ricinus_communis
Sapium__ellipticum
Sapium___integerrimum
Spirostachys_africana
Suregada_africana
Synadenium__cupulare
Acacia__ataxacantha
Acacia__borleae
Acacia__brevispica
Acacia_burkei
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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734,75
723,7521
529,9
749,4889
698,6326
849
749,4889
741,4
678
678
805
762,2
725
645,89
678
675
745,2356
724,9333
440
745,2356
786,275
741,4
715,8333
675
678
749,4889
745
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0,001361
0,001382
0,001887
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0,001431
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0,001475
0,001242
0,001312
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0,001548
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0,001481
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0,002273
0,001342
0,001272
0,001349
0,001397
0,001481
0,001475
0,001334
0,001342
0,002105
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7
12
1,5
10
10
4
10
15
2
2
20
6
12
1,5
2
5
7
6
18
7
20
15
15
6
5
10
5
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27
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
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4,669952
12,06837
0,309643
8,753288
8,753288
1,742619
8,753288
17,87948
0,513973
0,513973
29,67794
3,559476
12,06837
0,309643
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2,581718
4,669952
3,559476
24,65086
4,669952
29,67794
17,87948
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3,559476
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8,753288
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1,049841
50,35189
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0,009624
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1
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1
1
3
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1
0
1
1
1
2
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1
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156
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Acacia__caffra
Acacia__chariessa
Acacia__ebutsiniorum
Acacia__davyi
Vachelia_erioloba
Acacia__erubescens
Acacia__exuvialis
Acacia__galpini
Acacia__gerrardii
Acacia__grandicornuta
Acacia__karroo
Acacia__luederitzii
Acacia__mellifera
Acacia__nigrescens
Acacia__nilotica
Acacia__permixta
Acacia__polyacantha
Acacia_robusta_robust
Acacia_robusta_clavigera
Acacia__schweinfurthii
Acacia__senegal_leiorhachis
Acacia__senegal__rostrata
Acacia__sieberiana
Acacia__tenuispinaL
Acacia__swazica
Acacia__tortilis
Acacia_welwitschii
Acacia__xanthophloea
Adenopodia__spicata
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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745
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985
850
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725,32
725
786,275
749,4889
745
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849
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741,4
800
741,4
750
849
741,4
653
630
917,5
980
895
786,275
0,002326
0,001587
0,002196
0,001342
0,001349
0,001015
0,001176
0,001282
0,001379
0,001379
0,001272
0,001334
0,001342
0,001064
0,000978
0,001178
0,001349
0,001349
0,00125
0,001349
0,001333
0,001178
0,001349
0,001531
0,001587
0,00109
0,00102
0,001117
0,001272
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3,5
3
6
15
10
5
30
12
12
20
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6
30
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15
20
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4
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tree
15,83342
1,377368
1,049841
3,559476
17,87948
8,753288
2,581718
60,6202
12,06837
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29,67794
8,753288
3,559476
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17,87948
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24,65086
0,513973
1,049841
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29,67794
2,974849
1,99807
1,889456
2,377845
3,023461
2,737772
2,249382
3,511851
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2,866235
3,226162
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3,511851
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1,603766
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3,151925
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2
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0
2
2
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1
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0
0
2
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1
3
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157
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
native
native
native
native
native
native
native
native
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native
native
native
native
native
native
native
native
native
native
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native
Aeschynomene__nodulosa
Aeschynomene__rehmannii
Afzelia__quanzensis
Albizia__adianthifolia
Albizia___amara
Albizia__anthelmintica
Albizia__brevifolia
Albizia__forbesii
Albizia__harveyi
Albizia__petersiana
Albizia__tanganyicensis
Albizia__versicolor
Baphia__massaiensis
Bauhinia_galpinii
Bauhinia_tomentosa
Bolusanthus_speciosus
Burkea_africana
Calpurnia__aurea
Calpurnia_glabrata
Calpurnia__sericea
Cassia_abbreviata
Colophospermum_mopane
Cordyla__africana
Crotalaria___capensis
Crotalaria__doidgeae
Crotalaria__laburnifolia
Crotalaria__monteiroi
Crotalaria___natalitia
Crotalaria__pallida
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0
0
0
0
0
0
0
0
0
0
0
0
0
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0
0
0
0
0
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475
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805
725
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880
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725
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645
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762,2
696,3875
780
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653
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701,9091
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455,3562
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630
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0,002105
0,00129
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0,001361
0,001136
0,001242
0,001333
0,001156
0,001379
0,001685
0,00155
0,004994
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0,001436
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0,001531
0,001176
0,001075
0,001425
0,001178
0,002196
0,001475
0,001178
0,001587
0,002196
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3
20
20
12
7
15
20
15
10
12
18
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5
6
10
15
10
5
2
7
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2
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tree
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tree
1,742619
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29,67794
29,67794
12,06837
4,669952
17,87948
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17,87948
8,753288
12,06837
24,65086
3,559476
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8,753288
17,87948
8,753288
2,581718
0,513973
4,669952
12,06837
37,9623
1,742619
1,049841
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1,742619
0,815925
1,049841
2,092156
1,889456
3,226162
3,226162
2,866235
2,48646
3,023461
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3,023461
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2,377845
2,249382
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2,737772
2,249382
1,603766
2,48646
2,866235
3,324637
2,092156
1,889456
1,603766
2,092156
1,788627
1,889456
1
2
1
4
2
3
2
1
0
2
1
1
1
0
2
3
3
2
2
0
2
3
2
1
0
1
0
0
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158
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
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native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Dalbergia__armata
Dalbergia__melanoxylon
Dalbergia___nitidula
Dalbergia__obovata
Dichrostachys_ cinerea_africana
Dichrostachys_cinerea_nyassana
Elephantorrhiza__burkii
Elephantorrhiza__elephantina
Elephantorrhiza__obliqua
Elephantorrhiza_praetermissa
Eriosema__psoraleoides
Elephantorrhiza__goetzei
Erythrina__humeana
Erythrina__latissima
Erythrina__lysistemon
Erythrina__zeyheri
Faidherbia__albida
Guibourtia__conjugata
Indigofera__arrecta
Indigofera__fulgens
Indigofera___homblei
Indigofera__lupatana
Indigofera___swaziensis
Indigofera__tinctoria
Indigofera__tristoides
Mundulea__sericea
Newtonia__hildebrandtii
Ormocarpum_kirkii
Ormocarpum___trichocarpum
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
816,6
1000
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741,4
850
850
475
539,5
645,89
678
612,231
849
750
725
725
724,9333
484,25
800
455,3562
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593
675
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593
630
780
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351
678
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0,001342
0,001349
0,001176
0,001176
0,002105
0,001854
0,001548
0,001475
0,001633
0,001178
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0,002065
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0,001563
0,001686
0,001481
0,002196
0,001686
0,001587
0,001282
0,001349
0,002849
0,001475
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6
7
15
7
7
3
1
0,3
2
5
4
3
12
12
0,5
30
12
3
2
2,5
5
3
2
3,5
5
18
9
5
tree
tree
tree
tree
tree
tree
tree
tree
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tree
tree
tree
tree
tree
tree
shrub
tree
tree
tree
tree
tree
tree
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tree
tree
tree
tree
tree
tree
17,87948
3,559476
4,669952
17,87948
4,669952
4,669952
1,049841
0,151592
0,018182
0,513973
2,581718
1,742619
1,049841
12,06837
12,06837
0,044711
60,6202
12,06837
1,049841
0,513973
0,761459
2,581718
1,049841
0,513973
1,377368
2,581718
24,65086
7,270591
2,581718
3,023461
2,377845
2,48646
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2,48646
2,48646
1,889456
1,115376
0,26706
1,603766
2,249382
2,092156
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2,866235
2,866235
0,626986
3,511851
2,866235
1,889456
1,603766
1,760992
2,249382
1,889456
1,603766
1,99807
2,249382
3,151925
2,663535
2,249382
0
2
0
2
3
3
2
2
0
1
1
1
3
1
1
1
3
1
2
1
0
0
0
0
0
2
1
1
2
159
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Flacourtiacae
Hamamelidaceae
Hernandiaceae
Gentianaceae
Celastraceae
Celastraceae
Celastraceae
Icacinaceae
Icacinaceae
Kirkiaceae
Kirkiaceae
Lamiaceae
Lamiaceae
Lamiaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Peltophorum__africanum
Philenoptera__violacea
Piliostigma__thonningii
Pseudarthria__hookeri
Pterocarpus__angolensis
Pterocarpus__lucens
Pterocarpus__rotundifolius
Pterolobium__stellatum
Schotia_brachypetala
Schotia__capitata
Schotia___latifolia
Senna__petersiana
Xanthocercis__zambesiaca
Xeroderris__stuhlmannii
Xylia_torreana
Aphloia__theiformis
Trichocladus__grandiflorus
Gyrocarpus_americanus
Anthocleista___grandiflora
Hippocratea__africana
Hippocratea_crenata
Hippocratea_parvifolia
Apodytes__dimidiata
Cassinopsis__ilicifolia
Kirkia__acuminata
Kirkia__wilmsii
Clerodendrum__glabrum
Clerodendrum__pleiosciadium
Karomia_speciosa
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1015,9
526,076
749,4889
455,3562
529,95
715,3
865
750
744,25
989,95
780
945,7
609,5
90
750
749,4889
526,076
741,4
786,275
592,56
612,231
675
805
689
775
523,175
331,2
677,52
700
0,000984
0,001901
0,001334
0,002196
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0,001398
0,001156
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0,001344
0,00101
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0,001334
0,001901
0,001349
0,001272
0,001688
0,001633
0,001481
0,001242
0,001451
0,00129
0,001911
0,003019
0,001476
0,001429
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18
10
3
30
10
10
15
16
7
10
4
30
15
15
10
18
15
20
15
5
4,5
20
8
20
12
10
2,5
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tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
7,270591
24,65086
8,753288
1,049841
60,6202
8,753288
8,753288
17,87948
20,03214
4,669952
8,753288
1,742619
60,6202
17,87948
17,87948
8,753288
24,65086
17,87948
29,67794
17,87948
2,581718
2,144407
29,67794
5,908331
29,67794
12,06837
8,753288
0,761459
3,559476
2,663535
3,151925
2,737772
1,889456
3,511851
2,737772
2,737772
3,023461
3,068935
2,48646
2,737772
2,092156
3,511851
3,023461
3,023461
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0,025346
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0,009624
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1
3
1
2
2
0
2
0
2
1
3
1
0
1
0
2
1
2
2
3
2
0
1
0
2
0
3
1
1
160
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lamiaceae
Lauraceae
Lauraceae
Linaceae
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Leonotis__intermedia
Leonotis__leonurus
Leonotis__nepetifolia
Premna__mooiensis
Rhotheca__myricoides
Hemzygia__albiflora
Plectranthus-fruticosus
Hemizygia__parvifolia
Pycnostachys__urticifolia
Salvia__dolomitica
Syncolostemon__eriocephalus
Tetradenia__brevispicata
Tetradenia__riparia
Tinnea__barbata
Tinnea__rhodesiana
Vitex__ferruginea
Vitex___harveyana
Vitex___obovata
Vitex__patula
Vitex_rehmannii
Cryptocarya__transvaalensis
Cryptocarya__woodii
Hugonia__orientalis
Strychnos__cocculoides
Strychnos__decussata
Strychnos__henningsii
Strychnos__madagascariensis
Strychnos_potatorum
Strychnos_pungens
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
1
595
595
30
745,2356
603,33
595
750
370,4
603,33
645
640
595
595
332
332
560
640
748,6
538,85
745,2356
774,7667
780
560
689
748
709,6611
727,6667
809
790
0,001681
0,001681
0,033333
0,001342
0,001657
0,001681
0,001333
0,0027
0,001657
0,00155
0,001563
0,001681
0,001681
0,003012
0,003012
0,001786
0,001563
0,001336
0,001856
0,001342
0,001291
0,001282
0,001786
0,001451
0,001337
0,001409
0,001374
0,001236
0,001266
3
3
15
7
5
3
3
2
5
2
4
3
4
4
2
6
4
7
5
7
15
10
6
8
12
12
8
15
7
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
1,049841
1,049841
17,87948
4,669952
2,581718
1,049841
1,049841
0,513973
2,581718
0,513973
1,742619
1,049841
1,742619
1,742619
0,513973
3,559476
1,742619
4,669952
2,581718
4,669952
17,87948
8,753288
3,559476
5,908331
12,06837
12,06837
5,908331
17,87948
4,669952
-0,08805
-0,08805
0,025346
-0,02835
-0,05206
-0,08805
-0,08805
-0,11662
-0,05206
-0,11662
-0,06778
-0,08805
-0,06778
-0,06778
-0,11662
-0,03922
-0,06778
-0,02835
-0,05206
-0,02835
5,503461
5,217772
-0,03922
-0,01895
0,009624
0,009624
-0,01895
0,025346
-0,02835
0
2
0
0
0
1
1
1
1
0
0
0
1
0
0
0
0
2
1
1
2
3
1
1
1
3
3
2
4
161
Loganiaceae
Loganiaceae
Proteaceae
Proteaceae
Rosaceae
Lythraceae
Malpighiaceae
Malpighiaceae
Malpighiaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Strychnos__spinosa
Strychnos__usambarensis
Leucospermum__gerrardii
Leucospermum__saxosum
Leucosidea__sericea
Galpinia_transvaalica
Acridocarpus_natalitius
Triaspis_glaucophylla
Triaspis__hypericoides
Abutilon__angulatum
Abutilon__sonneratum
Adansonia_digitata
Azanza__garckeana
Cola__greenwayi
Dombeya__burgessiiae
Dombeya__cymosa
Dombeya__rotundifolia
Gossypium__herbaceum
Grewia__bicolor
Grewia__caffra
Grewia__flavescens
Grewia__flavescens
Grewia__gracillima
Grewia__hexamita
Grewia__inaequilatera
Grewia__microthyrsa
Grewia__monticola
Grewia__sulcata
Grewia__occidentalis
1
1
1
1
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
770
510
645,6
645
745,2356
689
603,33
727,6667
595
745,2356
678
362,9563
749,4889
790
678
599,9
749,4889
849
512,26
849
678
712,8
512,26
455,3562
653
670
856,05
725
849
0,001299
0,001961
0,001549
0,00155
0,001342
0,001451
0,001657
0,001374
0,001681
0,001342
0,001475
0,002755
0,001334
0,001266
0,001475
0,001667
0,001334
0,001178
0,001952
0,001178
0,001475
0,001403
0,001952
0,002196
0,001531
0,001493
0,001168
0,001379
0,001178
7
10
0,4
2
9
8
5
5
3
3,5
2
25
10
24
5
9
10
4
5
4
2
7
5
3
2
3
4
12
4
tree
tree
shrub
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
4,669952 -0,02835 2
8,753288 -0,00322 2
0,030179 -0,23002 2
0,513973 -0,11662 0
7,270591 -0,01065 1
5,908331 -0,01895 0
2,581718 -0,05206 1
2,581718 -0,05206 3
1,049841 -0,08805 1
1,377368 -0,07719 1
0,513973 -0,11662 1
43,96834 0,061339 2
8,753288 -0,00322 0
40,91768 0,058462 3
2,581718 -0,05206 2
7,270591 -0,01065 3
8,753288 -0,00322 1
1,742619 -0,06778 0
2,581718 -0,05206 2
1,742619 -0,06778 1
0,513973 -0,11662 2
4,669952 -0,02835 1
2,581718 -0,05206 3
1,049841 -0,08805 1
0,513973 -0,11662 0
1,049841 -0,08805 0
1,742619 -0,06778 0
12,06837 0,009624 1
1,742619 -0,06778 2
162
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Malvaceae
Marattiaceae
Maytenus
Meliaceae
Meliaceae
Meliaceae
Meliaceae
Meliaceae
Meliaceae
Meliaceae
Meliaceae
Melianthaceae
Melianthaceae
Melianthaceae
Melianthaceae
Melastomataceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Grewia__villosa
Hibiscus__calyphyllus
Hibiscus_micranthus
Sterculia__murex
Sterculia__rogersii
Triumfetta__pilosa
Marattia__faxinea
Mystroxylon__aethiopicum
Ekebergia__capensis
Ekebergia__pterophylla
Entandrophragma__caudatum
Trichilia__dregeana
Trichilia__emetica
Turraea__floribunda
Turraea__nilotica
Turraea__obtusifolia
Bersama__lucens
Bersama__tysoniana
Greyia__radlkoferi
Greyia_sutherlandii
Memecylon__natalense
Ficus__abutilifolia
Ficus__burkei
Ficus_ burtt
Ficus__capreifolia
Ficus__craterostoma
Ficus__glumosa
Ficus__ingens
Ficus_ natalensis
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
1
1
1
1
1
1
1
1
70
475
689
548,75
420,14
530
774,8
725
786,275
849
805
816,6
487,9588
1000
780
90
641,4286
696,3875
640
712
849
351
427,3
607,8333
560
697,3
677,52
487,9588
805
0,014286
0,002105
0,001451
0,001822
0,00238
0,001887
0,001291
0,001379
0,001272
0,001178
0,001242
0,001225
0,002049
0,001
0,001282
0,011111
0,001559
0,001436
0,001563
0,001404
0,001178
0,002849
0,00234
0,001645
0,001786
0,001434
0,001476
0,002049
0,001242
3
3
8
12
6
2,5
1
12
20
4
20
40
25
13
10
3
10
10
6
7
4
20
18
6
6
10
10
25
20
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
1,049841
1,049841
5,908331
12,06837
3,559476
0,761459
0,151592
12,06837
29,67794
1,742619
29,67794
100,6227
43,96834
13,89574
8,753288
1,049841
8,753288
8,753288
3,559476
4,669952
1,742619
29,67794
24,65086
3,559476
3,559476
8,753288
8,753288
43,96834
29,67794
-0,08805
-0,08805
-0,01895
0,009624
-0,03922
-0,1009
-0,16546
0,009624
3,886162
2,752156
3,886162
4,374551
4,043388
3,582633
3,397772
2,549456
-0,00322
-0,00322
-0,03922
-0,02835
-0,06778
3,156162
3,081925
2,307845
2,307845
2,667772
2,667772
3,313388
3,156162
0
1
0
1
0
3
0
2
1
0
2
0
3
3
3
3
3
2
1
2
1
1
0
0
1
3
3
1
2
163
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Myricaceae
Myricaceae
Myricaceae
Myricaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Myrtaceae
Nyctaginaceae
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Ficus__petersii
Ficus__salicifolia
Ficus__sansibarica
Ficus__stuhlmannii
Ficus__sur__Forssk
Ficus_sycomorus
Ficus_tettensis
Maclura_africana
Myrica_pilulifera
Morella_brevifolia
Morella_microbracteata
Morella___serrata
Eugenia__woodii
Eugenia__mossambicencis
Eugenia__natalitia
Heteropyxis__canescens
Heteropyxis__natalensis
Syzygium__cordatum
Syzygium__gerrardii
Syzygium__guineense
Syzygium__legatii
Syzygium_species
Syzygium_species B
Phaeoptilium__spinosum
Ochna__arborea
Ochna__inermis
Ochna__natalitia
Ochna__pulchra
Ochna__oconnori
1
1
1
1
1
1
1
1
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
786,275
725,32
609,5
697,3
725,32
498
725,32
80
762,2
770
455,3562
560
715,3
595
643,35
750
698,6326
774,7667
780
774,7667
727,6667
889,5281
725
645,89
725
748,6
698,6326
603,33
875
0,001272
0,001379
0,001641
0,001434
0,001379
0,002008
0,001379
0,0125
0,001312
0,001299
0,002196
0,001786
0,001398
0,001681
0,001554
0,001333
0,001431
0,001291
0,001282
0,001291
0,001374
0,001124
0,001379
0,001548
0,001379
0,001336
0,001431
0,001657
0,001143
20
12
30
15
12
25
12
5
6
6
3
6
10
1,2
8
15
10
15
25
15
8
20
12
2
12
7
10
5
1
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
29,67794
12,06837
60,6202
17,87948
12,06837
43,96834
12,06837
2,581718
3,559476
3,559476
1,049841
3,559476
8,753288
0,209004
5,908331
17,87948
8,753288
17,87948
43,96834
17,87948
5,908331
29,67794
12,06837
0,513973
12,06837
4,669952
8,753288
2,581718
0,151592
3,156162
2,796235
3,441851
2,953461
2,796235
3,313388
2,796235
2,179382
-0,03922
-0,03922
-0,08805
-0,03922
-0,00322
-0,15262
-0,01895
0,025346
-0,00322
0,025346
0,061339
0,025346
-0,01895
0,045616
0,009624
-0,11662
0,009624
-0,02835
-0,00322
-0,05206
-0,16546
1
2
1
2
1
3
1
3
2
1
0
2
0
0
2
0
1
2
1
2
3
3
0
2
0
1
1
1
1
164
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
Ochnaceae
Lauraceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Olacaceae
Oleaceae
Oleaceae
Onagraceae
Osmundaceae
Santalaceae
Chrysobalanaceae
Passifloraceae
Passifloraceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Ochna__serrulata
Ochna__barbosae
Ochna__confusa
Ochna_gamostigmata
Ochna__holstii
Ocotea__bullata
Ocotea___kenyensis
Olax_dissitiflora
Ximenia__americana
Ximenia__caffra
Chionanthus__battiscombei
Chionanthus foveolatus_fovoelatus
Chionanthus foveolatus_major
Chionanthus__peglerae
Jasmimun__abyssinicum
Jasminum_breviflorum
Jasminum__fluminense
Jasminum__multipartitum
Jasminum__stenolobum
Olea_capensis_enervis
Olea__capensis___Macrocarpa
Olea__europaea
Schrebera__alata
Ludwigia_octovalvis
Todea_barbara
Osyris__lanceolata
Parinari__curatellifolia
Adenia_spinosa
Adenia_fruticosa
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
745
714,7083
645
640
691,06
709,6611
809
725
538,85
712
762,2
714,7083
774,7667
677,52
750
750
640
679
745
688,75
427,3
715,3
677,52
849
645
645
592,56
438,46
678
0,001342
0,001399
0,00155
0,001563
0,001447
0,001409
0,001236
0,001379
0,001856
0,001404
0,001312
0,001399
0,001291
0,001476
0,001333
0,001333
0,001563
0,001473
0,001342
0,001452
0,00234
0,001398
0,001476
0,001178
0,00155
0,00155
0,001688
0,002281
0,001475
1
8
2
2
15
12
20
12
5
7
6
8
30
18
3
3
0,3
1,5
1
6
25
10
10
4
0,3
6
15
2,5
2
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
shrub
tree
tree
tree
tree
tree
tree
tree
shrub
tree
tree
tree
tree
0,151592
5,908331
0,513973
0,513973
17,87948
12,06837
29,67794
12,06837
2,581718
4,669952
3,559476
5,908331
60,6202
24,65086
1,049841
1,049841
0,018182
0,309643
0,151592
3,559476
43,96834
8,753288
8,753288
1,742619
0,018182
3,559476
17,87948
0,761459
0,513973
-0,16546
-0,01895
-0,11662
-0,11662
0,025346
0,009624
0,045616
0,009624
-0,05206
-0,02835
-0,03922
-0,01895
0,074185
0,038192
-0,08805
-0,08805
-0,25029
-0,13689
-0,16546
-0,03922
0,061339
-0,00322
-0,00322
-0,06778
-0,25029
-0,03922
0,025346
-0,1009
-0,11662
1
0
0
4
2
3
2
0
1
2
1
0
1
1
2
2
0
2
0
0
0
0
3
0
2
1
4
1
0
165
Passifloraceae
Passifloraceae
Pedaliaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Euphorbiaceae
Euphorbiaceae
Phyllanthaceae
Phyllanthaceae
Phyllanthaceae
Picrodendraceae
Piperaceae
Pittosporaceae
Plumbaginaceae
Podcarpaceae
Polygalaceae
Polygalaceae
Polygalaceae
Portulacaceae
Primulaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
native
native
native
native
native
native
native
native
native
native
native
exotic
exotic
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Adenia_gummifera
Paropsia__braunii
Sesamothamnus__lugardii
Antidesma__venosum
Bridelia_cathartica
Bridelia_micrantha
Bridelia_mollis
Flueggea__virosa
Hymenocardia__ulmoides
Jatropha_curcas
Jatropha_gossypiifolia
Phyllanthus_pinnatus
Phyllanthus__reticulatus
Pseudolachnostylis__maprouneaefolia
Androstachys__johnsonii
Piper__capense
Pittosporum__viridiflorum
Plumbago__auriculata
Afrocarpus__falcatus
Podocarpus__latifolius
Securidaca__longipedunculata
Polygala__virgata
Portulacaria_afra
Maesa__lanceolata
Faurea_galpinii
Faurea__macnaughtonii
Faurea__rochetiana
Faurea__saligna
Protea_caffra_caffra
0
0
0
1
1
1
1
1
1
0
0
1
1
1
0
0
0
0
0
1
1
1
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1
1
1
1
1
715,8333
749,4889
849
727,6667
640
805
720,2
595
786,275
770
485
595
645,6
691,06
786,275
438,46
689
455,3562
529,95
809
712
595
612,231
438,46
677,52
709,6611
712
697,3
727,6667
0,001397
0,001334
0,001178
0,001374
0,001563
0,001242
0,001389
0,001681
0,001272
0,001299
0,002062
0,001681
0,001549
0,001447
0,001272
0,002281
0,001451
0,002196
0,001887
0,001236
0,001404
0,001681
0,001633
0,002281
0,001476
0,001409
0,001404
0,001434
0,001374
15
10
4
8
7
20
9
3
20
7
3
4,5
6
18
20
6
8
3
25
33
6
4
5
6
10
25
7
10
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tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
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tree
tree
tree
tree
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tree
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tree
tree
tree
17,87948
8,753288
1,742619
5,908331
4,669952
29,67794
7,270591
1,049841
29,67794
4,669952
1,049841
2,144407
3,559476
24,65086
29,67794
3,559476
5,908331
1,049841
43,96834
71,70184
3,559476
1,742619
2,581718
3,559476
8,753288
43,96834
4,669952
8,753288
5,908331
0,025346
-0,00322
-0,06778
-0,01895
-0,02835
0,045616
-0,01065
-0,08805
0,045616
-0,02835
-0,08805
-0,05949
-0,03922
0,038192
0,045616
-0,03922
-0,01895
-0,08805
0,061339
0,080901
-0,03922
-0,06778
-0,05206
-0,03922
-0,00322
0,061339
-0,02835
-0,00322
-0,01895
1
0
0
3
2
1
4
1
0
4
4
1
3
2
3
2
1
1
2
2
2
2
1
2
2
4
2
1
3
166
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Proteaceae
Rosaceae
Putranjavaceae
Putranjavaceae
Ranunculaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rhamnaceae
Rosaceae
Rosaceae
Rosaceae
Rosaceae
Rosaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Protea__caffra__falcata
Protea__comptonii
Protea__curvata
Protea__gaguedi
Protea__laetans
Protea__parvula
Protea__roupelliae
Protea__rubropilosa
Protea__simplex
Protea___subvestita
Protea__wewitschii
Prunus__africana
Drypetes__gerrardii
Drypetes__reticulata
Clematis__brachiata
Berchemia__discolor
Berchemia__zeyheri
Helinus__integrifolius
Phylica_paniculata
Rhamnus__prinoides
Scutia__myrtina
Ziziphus_mucronata
Ziziphus__rivularis
Ziziphus__zeypherana
Cliffortia__linearifolia
Cliffortia__nitididula
Cliffortia__repens
Cliffortia___serpylliflia
Cliffortia__strobilifera
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
1
1
1
1
1
1
1
1
1
0
0
0
0
0
595
714,7083
714,7083
595
714,7083
745
643,35
745
714,7083
603,33
645
675
525,3214
689
678
786,275
887,1875
645,6
603,33
595
643,35
709,6611
697,3
595
529,9
675
678
800
455,3562
0,001681
0,001399
0,001399
0,001681
0,001399
0,001342
0,001554
0,001342
0,001399
0,001657
0,00155
0,001481
0,001904
0,001451
0,001475
0,001272
0,001127
0,001549
0,001657
0,001681
0,001554
0,001409
0,001434
0,001681
0,001887
0,001481
0,001475
0,00125
0,002196
3
8
8
3
8
1
8
1
8
5
1,5
5
35
8
2
20
15
6
5
4
8
12
10
0,6
1,5
6
2
4
3
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
1,049841
5,908331
5,908331
1,049841
5,908331
0,151592
5,908331
0,151592
5,908331
2,581718
0,309643
2,581718
79,53233
5,908331
0,513973
29,67794
17,87948
3,559476
2,581718
1,742619
5,908331
12,06837
8,753288
0,061644
0,309643
3,559476
0,513973
1,742619
1,049841
-0,08805
-0,01895
-0,01895
-0,08805
-0,01895
-0,16546
-0,01895
-0,16546
-0,01895
-0,05206
-0,13689
-0,05206
0,085047
-0,01895
-0,11662
0,045616
0,025346
-0,03922
-0,05206
-0,06778
-0,01895
0,009624
-0,00322
-0,20146
-0,13689
-0,03922
-0,11662
-0,06778
-0,08805
0
0
2
1
3
0
1
0
0
0
3
1
0
0
1
1
1
3
1
1
2
4
2
0
1
0
0
3
0
167
Rosaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Anthospermum__welwitschii
Breonadia__salicina
Burchellia__bubalina
Canthium__ciliatum
Canthium__inerme
Canthium__setiflorum
Catunaregam__spinosa
Cephalanthus__natalensis
Coddia__rudis
Crossopteryx__febrifuga
Gardenia__resiniflua
Gardenia__volkensii
Heinsia__crinita
Hymenodictyon__parvifolium
Hyperacanthus__amoenus
Keetia__guenzii
Kraussia__floribunda
Lagynia__dryadum
Leptactina__delagoensis
Oxyanthus__speciosus
Pachystigma__bowkeri
Pachystigma__macrocalyx
Pavetta__barbertonensis
Pavetta_catophylla
Pavetta__cooperi
Pavetta_edentula
Pavetta__harborii
Pavetta__lanceolata
Plectroniella__armata
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
455,3562
780
689
455,3562
523,175
810
745,2356
455,3562
370,4
698,6326
779,5
724,9333
590
498,56
689
749,4889
640
675
455,3562
523,175
689
455,3562
678
675
865
745,2356
745,2356
849
612,231
0,002196
0,001282
0,001451
0,002196
0,001911
0,001235
0,001342
0,002196
0,0027
0,001431
0,001283
0,001379
0,001695
0,002006
0,001451
0,001334
0,001563
0,001481
0,002196
0,001911
0,001451
0,002196
0,001475
0,001481
0,001156
0,001342
0,001342
0,001178
0,001633
3
30
8
3
13
2
7
3
2
10
10
2
3
5
8
10
4
5
3
16
8
3
2
5
2
7
0,5
4
5
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
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tree
tree
tree
shrub
tree
tree
1,049841 -0,08805 0
60,6202 0,074185 0
5,908331 -0,01895 0
1,049841 -0,08805 0
13,89574 0,015263 0
0,513973 -0,11662 0
4,669952 -0,02835 0
1,049841 -0,08805 1
0,513973 -0,11662 1
8,753288 -0,00322 0
8,753288 -0,00322 0
0,513973 -0,11662 1
1,049841 -0,08805 0
2,581718 -0,05206 2
5,908331 -0,01895 0
8,753288 -0,00322 0
1,742619 -0,06778 0
2,581718 -0,05206 1
1,049841 -0,08805 0
20,03214 0,029894 0
5,908331 -0,01895 0
1,049841 -0,08805 0
0,513973 -0,11662 0
2,581718 -0,05206 0
0,513973 -0,11662 1
4,669952 -0,02835 0
0,044711
-0,2143 1
1,742619 -0,06778 2
2,581718 -0,05206 0
168
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Rutaceae
Salicaceae
Gerrardinaceae
Salicaceae
Salicaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Psychotria__capensis
Psychotria___zombamontana
Psydrax__locuples
Pyrostria__hystrix
Rothmannia__fischeri
Tarenna__supra-axillaris
Tarenna__zygon
Tricalysia__junodii
Tricalysia__lanceolata
Vangueria__infausta
Vangueria__madagascariensis
Vangueria__parvifolia
Calodendrum__capensis
Clausena_anisata
Teclea__pilosa
Teclea__gerrardii
Teclea__natalensis
Toddalia__asiatica
Toddaliopsis__bremekampii
Vepris__lanceolata
Vepris__reflexa
Zanthoxylum__carpense
Zanthoxylum__davyi
Zanthoxylum__humile
Zanthoxylum__leprieurii
Flacourtia__indica
Gerrardina__foliosa
Homalium_dentatum
Oncoba_spinosa_Forssk
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
675
745,2356
810
395,8
640
675
678
599,6667
675
758,15
689
689
805
641,4286
641,4286
688,75
714,7083
677,52
720,2
539,8
762,2
595
780
701,8
641,4286
603,33
675
750
539,8
0,001481
0,001342
0,001235
0,002527
0,001563
0,001481
0,001475
0,001668
0,001481
0,001319
0,001451
0,001451
0,001242
0,001559
0,001559
0,001452
0,001399
0,001476
0,001389
0,001853
0,001312
0,001681
0,001282
0,001425
0,001559
0,001657
0,001481
0,001333
0,001853
6
7
5
3
8
6
2
4
6
8
8
8
20
4
4
6
8
15
6
5
6
3
30
3
4
5
5
15
5
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
3,559476
4,669952
2,581718
1,049841
5,908331
3,559476
0,513973
1,742619
3,559476
5,908331
5,908331
5,908331
29,67794
1,742619
1,742619
3,559476
5,908331
17,87948
3,559476
2,581718
3,559476
1,049841
60,6202
1,049841
1,742619
2,581718
2,581718
17,87948
2,581718
-0,03922
-0,02835
-0,05206
-0,08805
-0,01895
-0,03922
-0,11662
-0,06778
-0,03922
-0,01895
-0,01895
-0,01895
0,045616
-0,06778
-0,06778
-0,03922
-0,01895
0,025346
-0,03922
-0,05206
-0,03922
-0,08805
0,074185
-0,08805
-0,06778
-0,05206
-0,05206
0,025346
-0,05206
0
0
0
0
1
0
0
0
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0
0
1
4
1
0
0
1
3
2
2
2
2
0
1
1
1
0
1
169
Salicaceae
Salicaceae
Salicaceae
Salicaceae
Salvadoraceae
Salvadoraceae
Salvadoraceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Sapindaceae
Rutaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Sapotaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
exotic
native
Salix__mucronata
Rawsonia__lucida
Scolopia__zeyheri
Trimeria__grandifolia
Azima__tetracantha
Salvadora__australis
Salvadora__persica
Allophylus__decipiens
Deinbollia__oblongifolia
Deinbollia__xanthocarpa
Dodonaea_angustifolia_L.f
Hippobromus__pauciflorus
Pappea__capensis
Stadmannia__oppositifolia
Ptaeroxylon__obliquum
Englerophytum__magalismontanum
Englerophytum__natalense
Manilkara__concolor
Manilkara__discolor
Manilkara__mochisia
Mimusops__obovata
Mimusops__zeyheri
Sideroxylon__inerme
Vitellariopsis__marginata
Nicotiana_glauca
Lycium__cinereum
Lycium__shawii
Solanum__aculeastrum
Solanum__anguivi
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
524,5
538,85
745,2356
641,4286
640
745,2356
691,06
595
714,7083
715,3
715,3
714,7083
1119,45
786,275
1079,3
595
677,52
603,33
762,2
978
809
607,8333
809
770
641,4286
677,52
440,5
539,8
595
0,001907
0,001856
0,001342
0,001559
0,001563
0,001342
0,001447
0,001681
0,001399
0,001398
0,001398
0,001399
0,000893
0,001272
0,000927
0,001681
0,001476
0,001657
0,001312
0,001022
0,001236
0,001645
0,001236
0,001299
0,001559
0,001476
0,00227
0,001853
0,001681
3
5
7
10
2
7
2,5
4
9
10
10
9
13
20
20
4
10
5
6
15
15
5
15
6
4
1,8
4
5
3
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
1,049841
2,581718
4,669952
8,753288
0,513973
4,669952
0,761459
1,742619
7,270591
8,753288
8,753288
7,270591
13,89574
29,67794
29,67794
1,742619
8,753288
2,581718
3,559476
17,87948
17,87948
2,581718
17,87948
3,559476
1,742619
0,426912
1,742619
2,581718
1,049841
-0,08805
-0,05206
-0,02835
-0,00322
-0,11662
-0,02835
-0,1009
2,322156
2,893535
2,967772
2,967772
2,893535
3,152633
3,456162
0,045616
1,782216
1,846777
1,797938
1,810785
1,875346
1,875346
1,797938
1,875346
1,810785
-0,06778
-0,12405
-0,06778
-0,05206
-0,08805
3
2
0
3
2
0
2
1
1
0
1
1
2
1
2
1
2
1
2
3
4
0
2
2
3
1
2
2
0
170
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Solanaceae
Scrophulariaceae
Scrophulariaceae
Bignoniaceae
Stilbaceae
Stilbaceae
Stilbaceae
Stilbaceae
Stilbaceae
Streliziaceae
Thymelaeaceae
Thymelaeaceae
Ulmaceae
Urticaceae
Urticaceae
Velloziaceae
Velloziaceae
Verbenaceae
Verbenaceae
Verbenaceae
Vitaceae
Vitaceae
Vitaceae
native
native
native
native
native
native
native
exotic
native
exotic
native
native
exotic
native
native
native
native
native
native
native
native
native
native
native
native
exotic
exotic
exotic
native
Solanum__catombelense
Solanum_giganteum
Solanum___lichtensteinii
Solanum_kwebense
Solanum_mauritianum
Solanum_panduriforme
Solanum__rubetorum
Bowkeria__citrina
Bowkeria__cymosa
Jacaranda_mimosifolia
Halleria__lucida
Nuxia__congesta
Nuxia__floribunda
Nuxia__gracilis
Nuxia__oppositifolia
Strelitzia_caudata
Dais_cotinifolia_L
Englerodaphne__pilosa
Chaetachne__aristata
Obetia__tenax
Pouzolzia__mixta
Xerophyta_retinervis
Duranta_erecta
Lantana_camara
Lantana_rugosa
Lippia_javanica
Cissus__cactiformis
Cissus__cornifolia
Rhoicissus_digitata
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
1
1
1
440,5
645,6
380,45
640
640
287,2
645
455,3562
849
715,8333
715,8333
741,4
715,8333
455,3562
745,2356
689
745,2356
455,3562
696,3875
790
774,8
95,85
745,2356
524,5
220,8
438,46
603,33
679
774,7667
0,00227
0,001549
0,002628
0,001563
0,001563
0,003482
0,00155
0,002196
0,001178
0,001397
0,001397
0,001349
0,001397
0,002196
0,001342
0,001451
0,001342
0,002196
0,001436
0,001266
0,001291
0,010433
0,001342
0,001907
0,004529
0,002281
0,001657
0,001473
0,001291
2
5
3
2
2
2
2
3
4
15
15
15
15
3
7
8
7
3
10
7
1
4
7
3
3
5
5
1,5
15
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
0,513973
2,581718
1,049841
0,513973
0,513973
0,513973
0,513973
1,049841
1,742619
17,87948
17,87948
17,87948
17,87948
1,049841
4,669952
5,908331
4,669952
1,049841
8,753288
4,669952
0,151592
1,742619
4,669952
1,049841
1,049841
2,581718
2,581718
0,309643
17,87948
-0,11662
-0,05206
-0,08805
-0,11662
-0,11662
-0,11662
-0,11662
-0,08805
-0,06778
0,025346
0,025346
0,025346
0,025346
-0,08805
-0,02835
-0,01895
-0,02835
-0,08805
-0,00322
-0,02835
-0,16546
-0,06778
-0,02835
-0,08805
-0,08805
-0,05206
-0,05206
-0,13689
0,025346
2
3
3
3
1
1
0
0
0
1
1
0
1
0
1
0
0
0
3
3
3
3
1
4
2
2
1
1
2
171
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Menispermaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Penaeaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Fabaceae
Rutaceae
Euphorbiaceae
Euphorbiaceae
Euphorbiaceae
Thymelaeaceae
Thymelaeaceae
Rhizophoraceae
Rhizophoraceae
Salicaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
exotic
exotic
native
native
native
native
native
native
native
native
native
native
Rhoicissus_revoilii
Rhoicissus__tomentosus
Rhoicissus__tridentata
Kotschya__parvifolia
Kotschya__thymodora
Tiliacora__funifera
Flemingia__grahamiana
Lessertia__microphylla
Otholobium__wilmsii
Otholobium_ polyphyllum
Psoralea__glabra
Psoralea__latifolia
Psoralea___rhizotoma
Rhynchosia__clivorum
Sesbania_bispinosa
Sesbania__sesban
Tephrosia__cordata
Tephrosia___polystachya
Tephrosia__rhodesica
Tephrosia__subulata
Oricia__bachmannii
Margaritaria_ discoidea_fagifolia
Margaritaria__discoidea_nitida
Micrococca__capensis
Passerina_montana
Peddiea__africana
Cassipourea__malosana
Cassipourea__swaziensis
Dovyalis__caffra
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
712
786,275
595
640
640
805
678
645,89
653
455,3562
630
455,3562
774,8
455,3562
455,3562
612,231
645,89
653
645
593
525,3214
850
850
675
750
675
689
849
675
0,001404
0,001272
0,001681
0,001563
0,001563
0,001242
0,001475
0,001548
0,001531
0,002196
0,001587
0,002196
0,001291
0,002196
0,002196
0,001633
0,001548
0,001531
0,00155
0,001686
0,001904
0,001176
0,001176
0,001481
0,001333
0,001481
0,001451
0,001178
0,001481
7
20
4
2
2
20
2
2
2
3
3
3
1
3
3
5
0,7
2
1,5
2,5
35
30
7
5
3
5
8
4
5
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
tree
4,669952
29,67794
1,742619
0,513973
0,513973
29,67794
0,513973
0,513973
0,513973
1,049841
1,049841
1,049841
0,151592
1,049841
1,049841
2,581718
0,080876
0,513973
0,309643
0,761459
79,53233
60,6202
4,669952
2,581718
1,049841
2,581718
5,908331
1,742619
2,581718
-0,02835
0,045616
-0,06778
-0,11662
-0,11662
0,045616
1,603766
1,603766
1,603766
1,889456
1,889456
1,889456
1,115376
1,889456
1,889456
2,249382
0,864064
1,603766
1,401066
1,760992
0,085047
0,074185
-0,02835
-0,05206
-0,08805
-0,05206
-0,01895
-0,06778
-0,05206
3
3
1
2
1
1
1
2
0
0
1
1
0
0
0
1
0
0
0
0
0
0
1
0
2
1
1
0
0
172
Salicaceae
Salicaceae
Salicaceae
Scrophulariaceae
Scrophulariaceae
Scrophulariaceae
Scrophulariaceae
Scrophulariaceae
Zamiaceae
Zamiaceae
Zamiaceae
Zamiaceae
Zamiaceae
Zamiaceae
Zamiaceae
Zamiaceae
Zamiaceae
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
Dovyalis__lucida
Dovyalis__rhamnoides
Dovyalis__zeyheri
Buddleja_auriculata
Buddleja___dysophylla
Buddleja__puchella
Buddleja__saligna
Buddleja_salviifolia
Encephalartos_cupidus
Encephalartos_heenanii
Encephalartos_humilis
Encephalartos_inopinus
Encephalartos_laevifolius
Encephalartos_lanatus
Encephalartos_lebomboensis
Encephalartos_middelburgensis
Encephalartos_paucidentatus
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
745,2356
745,2356
698,6326
849
745,2356
849
734,75
498,56
485
849
640
645,89
849
645,89
612,231
850
850
0,001342
0,001342
0,001431
0,001178
0,001342
0,001178
0,001361
0,002006
0,002062
0,001178
0,001563
0,001548
0,001178
0,001548
0,001633
0,001176
0,001176
7
7
10
4
7
4
7
5
0,3
4
0,3
2
4
2
5
7
7
tree
tree
tree
tree
tree
tree
tree
tree
shrub
tree
shrub
tree
tree
tree
tree
tree
tree
4,669952
4,669952
8,753288
1,742619
4,669952
1,742619
4,669952
2,581718
0,018182
1,742619
0,018182
0,513973
1,742619
0,513973
2,581718
4,669952
4,669952
-0,02835
-0,02835
-0,00322
-0,06778
-0,02835
-0,06778
-0,02835
-0,05206
-0,25029
-0,06778
-0,25029
-0,11662
-0,06778
-0,11662
-0,05206
-0,02835
-0,02835
0
0
1
0
0
1
3
2
3
1
2
2
2
1
2
2
2
173
APPENDIX C
AVAILABILITY HYPOTHESIS DATA SET
Supplementary Information Table S 5.1: List of medicinal plant species occurrence outside
and inside the Kruger National Park (KNP) (Availability Hypothesis)
Famili
es
Genus
Stat
us
Ou
tsi
de
In
si
d
e
Occ
urre
nce
Differenc
e_outside
_inside
Abund
ance_t
otale
Re
cip
es
R
o
o
t
B
a
r
k
L
e
a
f
Annon
aceae
Xylopia__parviflor
a
1
1
bot
h
0
2
0
1
0
0
Eupho
rbiace
ae
Euphorbia__gueric
hiana
1
1
bot
h
0
2
0
0
0
0
0
Fabace
ae
Acacia__brevispica
1
1
bot
h
0
2
0
0
0
0
0
Boragi
naceae
Cordia__caffra
2
1
bot
h
1
3
0
0
0
0
0
Solana
ceae
Lycium__shawii_
3
1
bot
h
2
4
0
0
0
0
0
Acanth
aceae
Duvernoia_aconitif
lora
5
1
bot
h
4
6
0
0
0
0
0
Acanth
aceae
Duvernoia_adhato
doides_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
Se
ed
fr
ui
t
0
5
1
bot
h
4
6
0
0
0
0
0
174
Fabace
ae
Crotalaria__doidg
eae
Acanth
aceae
Metarungia__long
istrobus
Fabace
ae
Tephrosia___polys
tachya_
Combr
etacea
e
Combretum__woo
dii_
Morac
eae
Ficus__petersii_
Cappa
raceae
Capparis__fascicul
aris
Fabace
ae
Flemingia__graha
miana_
Flacou
rtiacea
e
Homalium__denta
tum
Verbe
naceae
Premna__mooiens
is
Icacina
ceae
Cassinopsis__ilicifo
lia_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
8
1
bot
h
7
9
0
0
0
0
0
9
1
bot
h
8
10
0
0
0
0
0
11
1
bot
h
10
12
0
0
0
0
0
13
1
bot
h
12
14
0
0
0
0
0
13
1
bot
h
12
14
0
0
0
0
0
17
1
bot
h
16
18
0
0
0
0
0
18
1
bot
h
17
19
0
0
0
0
0
26
1
bot
h
25
27
0
0
0
0
0
28
1
bot
h
27
29
0
0
0
0
0
30
1
bot
h
29
31
0
0
0
0
0
175
Olacac
eae
Olea__europaea
Fabace
ae
Albizia__tanganyic
ensis_
Solana
ceae
Solanum__catomb
elense
Eupho
rbiace
ae
Erythrococca__me
nyharthii
Apocy
naceae
Adenium__swazic
um_
Fabace
ae
Crotalaria__pallid
a
Onagr
aceae
Ludwigia_octovalv
is
Rubiac
eae
Kraussia__floribun
da_
Fabace
ae
Crotalaria__monte
iroi_
Fabace
ae
Acacia__swazica
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
49
1
bot
h
48
50
0
0
0
0
0
1
2
bot
h
-1
3
0
0
0
0
0
1
2
bot
h
-1
3
0
0
0
0
0
5
2
bot
h
3
7
0
0
0
0
0
6
2
bot
h
4
8
0
0
0
0
0
7
2
bot
h
5
9
0
0
0
0
0
11
2
bot
h
9
13
0
0
0
0
0
16
2
bot
h
14
18
0
0
0
0
0
17
2
bot
h
15
19
0
0
0
0
0
18
2
bot
h
16
20
0
0
0
0
0
176
Acanth
aceae
Barleria_rotundifol
ia
Burser
aceae
Commiphora__ma
rlothii
Rham Phylica_paniculata
naceae
Fabace
ae
Pseudarthria__hoo
keri_
Rubiac
eae
Hyperacanthus__a
moenus
Olacac
eae
Chionanthus__fov
eolatus
Celastr
aceae
Maytenus__undat
a_
Fabace
ae
Caesalpinia__rostr
ata
Tiliace
ae
Grewia__inaequila
tera
Pedali
aceae
Sesamothamnus__
lugardii_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
19
2
bot
h
17
21
0
0
0
0
0
19
2
bot
h
17
21
0
0
0
0
0
21
2
bot
h
19
23
0
0
0
0
0
26
2
bot
h
24
28
0
0
0
0
0
28
2
bot
h
26
30
0
0
0
0
0
37
2
bot
h
35
39
0
0
0
0
0
38
2
bot
h
36
40
0
0
0
0
0
1
3
bot
h
-2
4
0
0
0
0
0
2
3
bot
h
-1
5
0
0
0
0
0
2
3
bot
h
-1
5
0
0
0
0
0
177
Celastr
aceae
Hippocratae__afri
cana.
Celastr
aceae
Hippocratea__afri
cana
Rubiac
eae
Psydrax__locuples
_
Combr
etacea
e
Combretum__pad
oides_
Morac
eae
Ficus__sansibarica
Myrta
ceae
Eugenia__mossam
bicencis
Rubiac
eae
Pyrostria__hystrix
_
Burser
aceae
Commiphora__sch
imperi
Cappa
raceae
Maerua__rosmari
noides_
Apocy
naceae
Pachypodanthium
__saundersii
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
3
3
bot
h
0
6
0
0
0
0
0
3
3
bot
h
0
6
0
0
0
0
0
4
3
bot
h
1
7
0
0
0
0
0
5
3
bot
h
2
8
0
0
0
0
0
6
3
bot
h
3
9
0
0
0
0
0
6
3
bot
h
3
9
0
0
0
0
0
6
3
bot
h
3
9
0
0
0
0
0
11
3
bot
h
8
14
0
0
0
0
0
18
3
bot
h
15
21
0
0
0
0
0
20
3
bot
h
17
23
0
0
0
0
0
178
Anacar
diacea
e
Rhus__transvaalen
sis
Eupho
rbiace
ae
Acalypha__glabrat
a
Anacar
diacea
e
Rhus__pyroides__
pyroides_
Salvad
oracea
e
Salvadora__austra
lis_
Fabace
ae
Dalbergia___nitid
ula_
Lamiac
eae
Pycnostachys__urt
icifolia_
Lamiac
eae
Tinnea__rhodesian
a
Apiace
ae
Steganotaenia__ar
aliacea
Acanth
aceae
Ruttya__ovata_
Malva
ceae
Hibiscus__calyphyl
lus
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
21
3
bot
h
18
24
0
0
0
0
0
23
3
bot
h
20
26
0
0
0
0
0
46
3
bot
h
43
49
0
0
0
0
0
4
4
bot
h
0
8
0
0
0
0
0
5
4
bot
h
1
9
0
0
0
0
0
11
4
bot
h
7
15
0
0
0
0
0
16
4
bot
h
12
20
0
0
0
0
0
23
4
bot
h
19
27
0
0
0
0
0
24
4
bot
h
20
28
0
0
0
0
0
26
4
bot
h
22
30
0
0
0
0
0
179
Rubiac
eae
Breonadia__salicin
a
Lamiac
eae
Rhotheca__myrico
ides
Eupho
rbiace
ae
Acalypha__pubiflo
ra_
Eupho
rbiace
ae
Croton__madande
nsis
Astera
ceae
Brachylaena__huill
ensis_
Cappar
aceae
Cadaba_termitaria
Stercu
liaceae
Sterculia__rogersii
Apocy
naceae
Diplorhynchus__co
ndylocarpon_
Erythr
oxylac
eae
Erythroxylum__em
arginatum_
Fabace
ae
Indigofera___swaz
iensis_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
27
4
bot
h
23
31
0
0
0
0
0
44
4
bot
h
40
48
0
0
0
0
0
1
5
bot
h
-4
6
0
0
0
0
0
2
5
bot
h
-3
7
0
0
0
0
0
3
5
bot
h
-2
8
0
0
0
0
0
10
5
bot
h
5
15
0
0
0
0
0
18
5
bot
h
13
23
0
0
0
0
0
19
5
bot
h
14
24
0
0
0
0
0
24
5
bot
h
19
29
0
0
0
0
0
24
5
bot
h
19
29
0
0
0
0
0
180
Celastr
aceae
Gymnosporia__gla
ucophyllia
Rhamn
aceae
Ziziphus__rivularis
_
Celastr
aceae
Hippocratea__par
vifolia
Celastr
aceae
Hippocratea_parvi
folia
Rutace
ae
Teclea__pilosa_
Morac
eae
Ficus__capreifolia
Fabace
ae
Acacia__schweinfu
rthii_
Astera
ceae
Vernonia__colorat
a
Rubiac
eae
Plectroniella__arm
ata_
Rubiac
eae
Coddia__rudis_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
28
5
bot
h
23
33
0
0
0
0
0
1
6
bot
h
-5
7
0
0
0
0
0
3
6
bot
h
-3
9
0
0
0
0
0
3
6
bot
h
-3
9
0
0
0
0
0
4
6
bot
h
-2
10
0
0
0
0
0
8
6
bot
h
2
14
0
0
0
0
0
16
6
bot
h
10
22
0
0
0
0
0
17
6
bot
h
11
23
0
0
0
0
0
17
6
bot
h
11
23
0
0
0
0
0
26
6
bot
h
20
32
0
0
0
0
0
181
Anacar
diacea
e
Rhus__pentheri_
Cappar
aceae
Boscia__mossambi
censis
Eupho
rbiace
ae
Euphorbia__confin
alis_
Burser
aceae
Commiphora__ten
uipetiolata
Fabace
ae
Indigofera__lupat
ana
Bignon
iaceae
Rhigozum__zambe
siacum
Olacac
eae
Jasminum__stenol
obum_
Flacou
rtiacea
e
Dovyalis__caffra_
Verbe
naceae
Vitex__ferruginea
_
Verbe
naceae
Vitex___harveyan
a_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
41
6
bot
h
35
47
0
0
0
0
0
3
7
bot
h
-4
10
0
0
0
0
0
3
7
bot
h
-4
10
0
0
0
0
0
5
7
bot
h
-2
12
0
0
0
0
0
6
7
bot
h
-1
13
0
0
0
0
0
7
7
bot
h
0
14
0
0
0
0
0
16
7
bot
h
9
23
0
0
0
0
0
19
7
bot
h
12
26
0
0
0
0
0
2
8
bot
h
-6
10
0
0
0
0
0
2
8
bot
h
-6
10
0
0
0
0
0
182
Malva
ceae
Hibiscus_micranth
us
Olacac
eae
Jasminum__flumin
ense_
Burser
aceae
Commiphora_molli
s
Rutace
ae
Vepris__reflexa_
Celastr
aceae
Gymnosporia__ma
ranguensis
Rubiac
eae
Catunaregam__spi
nosa_
Ochna
ceae
Ochna__inermis
Fabace
ae
Tephrosia__rhodes
ica
Phylla
nthace
ae
Phyllanthus__pinn
atus
Rubiac
eae
Tricalysia__junodii
_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
14
8
bot
h
6
22
0
0
0
0
0
21
8
bot
h
13
29
0
0
0
0
0
24
8
bot
h
16
32
0
0
0
0
0
43
8
bot
h
35
51
0
0
0
0
0
4
9
bot
h
-5
13
0
0
0
0
0
10
9
bot
h
1
19
0
0
0
0
0
14
9
bot
h
5
23
0
0
0
0
0
22
9
bot
h
13
31
0
0
0
0
0
1
1
0
bot
h
-9
11
0
0
0
0
0
2
1
0
bot
h
-8
12
0
0
0
0
0
183
Burser
aceae
Commiphora__pyr
acanthoides
Malva
ceae
Gossypium__herb
aceum
Cappar
aceae
Maerua__juncea
Rubiac
eae
Pavetta_catophyll
a
Rubiac
eae
Vangueria__infaus
ta_
Fabace
ae
Acacia__borleae_
Xanth
orrhoe
aceae
Aloe_spicata
Fabace
ae
Crotalaria__laburn
ifolia_
Astera
ceae
Pulchea__dioscord
ia
Lythra
ceae
Galpinia_transvaal
ica
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
15
1
0
bot
h
5
25
0
0
0
0
0
16
1
0
bot
h
6
26
0
0
0
0
0
20
1
0
bot
h
10
30
0
0
0
0
0
6
1
1
bot
h
-5
17
0
0
0
0
0
60
1
1
bot
h
49
71
0
0
0
0
0
3
1
2
bot
h
-9
15
0
0
0
0
0
21
1
2
bot
h
9
33
0
0
0
0
0
12
1
3
bot
h
-1
25
0
0
0
0
0
5
1
4
bot
h
-9
19
0
0
0
0
0
11
1
4
bot
h
-3
25
0
0
0
0
0
184
Burser
aceae
Commiphora_glandulosa
Simaro
ubace
ae
Kirkia__acuminata
Combr
etacea
e
Combretum__micr
ophyllum_
Vitace
ae
Cissus__cornifolia
Cappar
aceae
Maerua_parvifolia
Fabace
ae
Acacia__grandicor
nuta_
Ebenac Euclea__daphnoid
eae
es__Hiern
Fabace
ae
Acacia__exuvialis
Tiliace
ae
Grewia__monticol
a_
Sapota
ceae
Manilkara__mochi
sia_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
17
1
4
bot
h
3
31
0
0
0
0
0
3
1
5
bot
h
-12
18
0
0
0
0
0
11
1
6
bot
h
-5
27
0
0
0
0
0
8
1
9
bot
h
-11
27
0
0
0
0
0
15
1
9
bot
h
-4
34
0
0
0
0
0
18
1
9
bot
h
-1
37
0
0
0
0
0
19
2
0
bot
h
-1
39
0
0
0
0
0
32
2
0
bot
h
12
52
0
0
0
0
0
40
2
1
bot
h
19
61
0
0
0
0
0
15
2
2
bot
h
-7
37
0
0
0
0
0
185
Fabace
ae
Acacia__erubesce
ns
Combr
etacea
e
Terminalia__pruni
oides
Fabace
ae
Albizia__harveyi_
Lamiac
eae
Leonotis__nepetifo
lia
Anacar
diacea
e
Rhus__magalismo
ntana_magalismot
ana__coddii
Annon
aceae
Monodora__junod
ii__macrantha
Arecac
eae
Borassus__aethiop
ium
Xanth
orrhoe
aceae
Aloe_excelsa
Xanth
orrhoe
aceae
Aloe__littoralis
Burser
aceae
Commiphora__zan
zibarica
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
8
2
6
bot
h
-18
34
0
0
0
0
0
26
3
1
bot
h
-5
57
0
0
0
0
0
17
3
5
bot
h
-18
52
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
186
Cappar
aceae
Boscia__foetida__
minima
Combr
etacea
e
Combretum___mk
uzense
Fabace
ae
Indigofera__fulgen
s
Fabace
ae
Pterocarpus__luce
ns_
Malva
ceae
Azanza__garckean
a_
Nyctag
inacea
e
Phaeoptilium__spi
nosum
Ochna
ceae
Ochna__barbosae
Rubiac
eae
Leptactina__delag
oensis_
Sapin
daceae
Allophylus__decipi
ens
Acanth
aceae
Anisotes_formosis
simus
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
1
insi
de
-1
1
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
187
Acanth
aceae
Ruspolia__hypocra
teriformis
Xanth
orrhoe
aceae
Aloe_angelica
Cappar
aceae
Boscia__foetida__
filipes
Eupho
rbiace
ae
Drypetes__mossa
mbicensis_
Eupho
rbiace
ae
Euphorbia__rowla
ndii
Fabace
ae
Baphia__massaien
sis
Fabace
ae
Xylia_torreana
Tiliace
ae
Grewia__gracillim
a_
Olacac
eae
Chionanthus__bat
tiscombei
Passifl
oracea
e
Paropsia__braunii
_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
0
2
insi
de
-2
2
0
0
0
0
0
188
Acanth
aceae
Barleria_albostella
ta
Annon
aceae
Monodora__junod
ii_
Cappar
aceae
Boscia__angustifol
ia_
Celastr
aceae
Gymnosporia__ox
ycarpa_
Labiat
e
Clerodendrum__pl
eiosciadium
Verbe
naceae
Vitex__patula_
Linace
ae
Hugonia__oriental
is
Meliac
eae
Entandrophragma
__caudatum_
Rubiac
eae
Crossopteryx__feb
rifuga_
Rubiac
eae
Tarenna__zygon_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
189
Rutace
ae
Toddaliopsis__bre
mekampii_
Sapind
aceae
Deinbollia__xanth
ocarpa
Sapind
aceae
Stadmannia__opp
ositifolia_
Acanth
aceae
Anisotes_rogersii_
Celastr
aceae
Gymnosporia__pu
bescens_
Celastr
aceae
Hippocratea__indi
ca
Combr
etacea
e
Pteleopsis__myrtif
olia
Eupho
rbiace
ae
Euphorbia__espin
osa_
Fabace
ae
Guibourtia__conju
gata
Celastr
aceae
Hippocratea__indi
ca
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
3
insi
de
-3
3
0
0
0
0
0
0
4
insi
de
-4
4
0
0
0
0
0
0
4
insi
de
-4
4
0
0
0
0
0
0
4
insi
de
-4
4
0
0
0
0
0
0
4
insi
de
-4
4
0
0
0
0
0
0
4
insi
de
-4
4
0
0
0
0
0
0
4
insi
de
-4
4
0
0
0
0
0
0
4
insi
de
-4
4
0
0
0
0
0
190
Rubiac
eae
Annon
aceae
Burser
aceae
Combr
etacea
e
Rubiac
eae
Rubiac
eae
Celastr
aceae
Eupho
rbiace
ae
Fabace
ae
Eupho
rbiace
ae
Lagynia__dryadu
m_
non
me
dici
nal
Uvaria__gracilipes non
__Robson
me
dici
nal
Commiphora__edu non
lis_
me
dici
nal
Combretum__cela non
stroides_
me
dici
nal
Canthium__setiflor non
um
me
dici
nal
Heinsia__crinita
non
me
dici
nal
Gymnosporia__put non
terlickioides
me
dici
nal
Drypetes__reticula non
ta_
me
dici
nal
Indigofera__tincto non
ria
me
dici
nal
Drypetes__reticula non
ta_
me
dici
nal
0
4
insi
de
-4
4
0
0
0
0
0
0
5
insi
de
-5
5
0
0
0
0
0
0
5
insi
de
-5
5
0
0
0
0
0
0
5
insi
de
-5
5
0
0
0
0
0
0
5
insi
de
-5
5
0
0
0
0
0
0
5
insi
de
-5
5
0
0
0
0
0
0
6
insi
de
-6
6
0
0
0
0
0
0
6
insi
de
-6
6
0
0
0
0
0
0
6
insi
de
-6
6
0
0
0
0
0
0
6
insi
de
-6
6
0
0
0
0
0
191
Eupho
rbiace
ae
Alchornea__laxiflo
ra_
Eupho
rbiace
ae
Hymenocardia__ul
moides_
Celastr
aceae
Hippocratea__cren
ata__
Fabace
ae
Acacia_welwitschii
_
Celastr
aceae
Hippocratea_crena
ta
Arecac
eae
Hyphaene__peters
iana
Anacar
diacea
e
Rhus__dracomont
ana
Anacar
diacea
e
Rhus__harveyi
Araliac
eae
Cussonia__sphaer
ocephala
Astera
ceae
Lopholaena__platy
phylla
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
0
7
insi
de
-7
7
0
0
0
0
0
0
7
insi
de
-7
7
0
0
0
0
0
0
9
insi
de
-9
9
0
0
0
0
0
0
9
insi
de
-9
9
0
0
0
0
0
0
9
insi
de
-9
9
0
0
0
0
0
0
1
5
insi
de
-15
15
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
192
Astera
ceae
Vernonia__auranti
aca
Eupho
rbiace
ae
Drypetes__arguta
Ebenac Euclea__dewinteri
eae
Ericace
ae
Erica__species
Eupho
rbiace
ae
Euphobia__grandi
alata
Fabace
ae
Acacia__chariessa
Fabace
ae
Acacia__ebutsinior
um
Fabace
ae
Acacia__permixta
Melast
omata
ceae
Memecylon__nata
lense
Morac
eae
Ficus__burtt_davyi
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
193
Myrta
ceae
Syzygium_species
Prote
aceae
Protea__curvata
Protea
ceae
Protea___subvesti
ta_
Rubiac
eae
Gardenia__resinifl
ua_
Solana
ceae
Bowkeria__citrina
_
Menis
perma
ceae
Tiliacora__funifera
Eupho
rbiace
ae
Margaritaria__dis
coidea
Anacar
diacea
e
Rhus__pygmaea_
Astera
ceae
Anisopappus__jun
odii
Burser
aceae
Commiphora___w
oodii
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
1
0
outs
ide
1
1
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
194
Eupho
rbiace
ae
Euphorbia__grand
icornis
Eupho
rbiace
ae
Euphorbia__specie
s__A__Malelane
Fabace
ae
Acacia__tenuispin
aL
Fabace
ae
Schotia___latifolia
Rutace
ae
Teclea__gerrardii
Fabace
ae
Psoralea__glabra
Rutace
ae
Oricia__bachmann
ii
Anacar
diacea
e
Lannea__gossweill
eri
Anacar
diacea
e
Rhus__montana
Anacar
diacea
e
Rhus__pallens
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
2
0
outs
ide
2
2
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
195
Oliniac
eae
Olinia__radiata
Bignon
iaceae
Rhigozum__obvat
um
Ebenac Euclea__species
eae
Fabace
ae
Aeschynomene__n
odulosa
Lamiac
eae
Hemizygia__parvif
olia
Protea
ceae
Leucospermum__s
axosum
Myrica
ceae
Morella_microbrac
teata
Olacac
eae
Jasmimun__abyssi
nicum
Prote
aceae
Protea__laetans
Rubiac
eae
Pavetta__barberto
nensis
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
196
Rutace
ae
Teclea__natalensis
Thyme
laecea
e
Englerodaphne__p
ilosa
Fabace
ae
Psoralea___rhizot
oma
Eupho
rbiace
ae
Micrococca__cape
nsis_
Rhizop
horace
ae
Cassipourea__swa
ziensis
Anacar
diacea
e
Rhus__batophylla
_
Aspara
gaceae
Dracaena___trans
vaalensis
Astera
ceae
Eumorphia___dav
yi_
Astera
ceae
Eumorphia___swa
ziensis
Eupho
rbiace
ae
Drypetes___gerrar
di
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
3
0
outs
ide
3
3
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
197
Eupho
rbiace
ae
Euphorbia__excels
a_
Fabace
ae
Crotalaria___natal
itia
Fabace
ae
Elephantorrhiza__
obliqua
Flacou
rtiacea
e
Aphloia__theiform
is
Lamia
ceae
Leonotis__interme
dia_
Lamia
ceae
Tinnea__barbata_
Protea
ceae
Leucospermum__g
errardii
Stercul
iaceae
Dombeya__burges
siiae
Osmun
daceae
Todea_barbara
Prote
aceae
Protea__comptonii
_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
198
non
me
dici
nal
Rosace Cliffortia___serpyll non
ae
iflia_
me
dici
nal
Scroph Buddleja___dysop non
ulariac hylla_
eae
me
dici
nal
Acanth Justicia__campylos non
aceae
temon
me
dici
nal
Anacar Ozoroa__barberto non
diacea nensis
e
me
dici
nal
Xanth
Aloe__alooides
non
orrhoe
aceae
me
dici
nal
Xanth
Aloe_barberae
non
orrhoe
aceae
me
dici
nal
Astera Vernonia__triflora non
ceae
_
me
dici
nal
Celastr Gymnosporia__gra non
aceae
ndifolia
me
dici
nal
Ebenac Diospyros__dichro non
eae
phylla_
me
dici
nal
Eupho
rbiace
ae
Drypetes__gerrard
ii_
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
199
Eupho
rbiace
ae
Protea
ceae
Rubiac
eae
Buddl
ejacea
e
Fabac
eae
Anacar
diacea
e
Bignon
iaceae
Combr
etacea
e
Eupho
rbiace
ae
Eupho
rbiace
ae
Euphorbia__lyden
burgensis
non
me
dici
nal
Protea__simplex
non
me
dici
nal
Pachystigma__bo
non
wkeri
me
dici
nal
Nuxia__gracilis_
non
me
dici
nal
Kotschya__thymod non
ora
me
dici
nal
Rhus__species
non
me
dici
nal
Rhigozum__brevis non
pinosum
me
dici
nal
Combretum__nels non
onii
me
dici
nal
Euphorbia__sekuk non
uniensis
me
dici
nal
Euphorbia__triang non
ularis
me
dici
nal
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
5
0
outs
ide
5
5
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
200
Fabace
ae
Elephantorrhiza_p
raetermissa
Lamiac
eae
Salvia__dolomitica
Morac
eae
Ficus_tettensis
Myrica
ceae
Morella_brevifolia
Ochna
ceae
Ochna_gamostigm
ata
Olacac
eae
Jasminum_breviflo
rum
Scroph
ulariac
eae
Buddleja__puchell
a
Anacar
diacea
e
Rhus___sekhukhu
niensis
Anacar
diacea
e
Rhus__tomentosa
Araliac
eae
Seemannaralia__g
errardii
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
6
0
outs
ide
6
6
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
201
Astera
ceae
Anisopappus__sm
utsii
7
0
outs
ide
7
7
0
0
0
0
0
Celastr
aceae
Lauridia__tetrago
na_
non
me
dici
nal
non
me
dici
nal
7
0
outs
ide
7
7
0
0
0
0
0
Cyathe
aceae
Cyathea__capensis non
me
dici
nal
Indigofera___hom non
blei
me
dici
nal
Eugenia__woodii
non
me
dici
nal
Chionanthus__fov non
eolatus__Meyer_
me
dici
nal
Chionanthus__peg non
lerae
me
dici
nal
Psychotria___zom non
bamontana_
me
dici
nal
Kotschya__parvifol non
ia_
me
dici
nal
Rhus__grandidens non
me
dici
nal
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
7
0
outs
ide
7
7
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
Fabace
ae
Myrtac
eae
Olacac
eae
Olacac
eae
Rubiac
eae
Fabac
eae
Anacar
diacea
e
202
Anacar
diacea
e
Rhus__keetii
Anacar
diacea
e
Rhus__wilmsii
Apocy
naceae
Ancyloboyrys__ca
pensis_
Passifl
oracea
e
Adenia_fruticosa
Protea
ceae
Protea__rubropilo
sa
Rubiac
eae
Vangueria__parvif
olia_
Rutace
ae
Toddalia__asiatica
Solan
aceae
Lycium__cinereum
Acanth
aceae
Mackaya__bella_
Oliniac
eae
Olinia__rochetiana
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
8
0
outs
ide
8
8
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
8
0
outs
ide
8
8
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
203
Sapota
ceae
Buxus_macowani
Conna
raceae
Cnestis__polyphyll
a
Ericace
ae
Erica__natalitia__
Bolus_
Ericace
ae
Erica__oatesii
Lamiac
eae
Tetradenia__brevi
spicata
Marat
tiacea
e
Marattia__faxinea
Hetero
pyxida
ceae
Heteropyxis__cane
scens
Strelitz
iaceae
Strelitzia_caudata
Fabace
ae
Tephrosia__cordat
a
Anacar
diacea
e
Rhus__pondoensis
_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
9
0
outs
ide
9
9
0
0
0
0
0
10
0
outs
ide
10
10
0
0
0
0
0
204
Anacar
diacea
e
Rhus__gracillima_
Anacar
diacea
e
Rhus__magalismo
ntana__magalism
otana
Apiace
ae
Heteromorpha__p
ubescens_
Ebenac Diospyros__austro
eae
_africana
Fabace
ae
Acacia__galpini
Fabace
ae
Pterolobium__stell
atum
Lamiac
eae
Syncolostemon__e
riocephalus
Strych
naceae
Strychnos__coccul
oides_
Fabace
ae
Tephrosia__subula
ta
Anacar
diacea
e
Rhus__engleri
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
11
0
outs
ide
11
11
0
0
0
0
0
12
0
outs
ide
12
12
0
0
0
0
0
205
Ericace
ae
Erica__cafforum_
Stercu
liaceae
Sterculia__murex
Solana
ceae
Solanum__rubetor
um__
Apiace
ae
Heteromorpha__a
rborescens__Cham
Astera
ceae
Brachylaena__rotu
ndata
Eupho
rbiace
ae
Euphorbia__evansi
i
Prote
aceae
Protea__parvula_
Sapota
ceae
Englerophytum__n
atalense__
Solana
ceae
Solanum__anguivi
_
Flacou
rtiacea
e
Dovyalis__lucida
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
12
0
outs
ide
12
12
0
0
0
0
0
12
0
outs
ide
12
12
0
0
0
0
0
12
0
outs
ide
12
12
0
0
0
0
0
13
0
outs
ide
13
13
0
0
0
0
0
13
0
outs
ide
13
13
0
0
0
0
0
13
0
outs
ide
13
13
0
0
0
0
0
13
0
outs
ide
13
13
0
0
0
0
0
13
0
outs
ide
13
13
0
0
0
0
0
13
0
outs
ide
13
13
0
0
0
0
0
13
0
outs
ide
13
13
0
0
0
0
0
206
Flacou
rtiacea
e
Dovyalis__rhamno
ides
Fabace
ae
Ormocarpum_kirki
i
Hama
melida
ceae
Trichocladus__gra
ndiflorus_
Morac
eae
Ficus__stuhlmanni
i
Rosace
ae
Anthospermum__
welwitschii_
Acanth
aceae
Sclerochiton_harve
yanus
Eupho
rbiace
ae
Suregada__african
a__Kuntze
Rosace
ae
Cliffortia__strobilif
era
Rubiac
eae
Keetia__guenzii_
Achari
aceae
Rawsonia__lucida
_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
13
0
outs
ide
13
13
0
0
0
0
0
14
0
outs
ide
14
14
0
0
0
0
0
14
0
outs
ide
14
14
0
0
0
0
0
14
0
outs
ide
14
14
0
0
0
0
0
14
0
outs
ide
14
14
0
0
0
0
0
15
0
outs
ide
15
15
0
0
0
0
0
15
0
outs
ide
15
15
0
0
0
0
0
15
0
outs
ide
15
15
0
0
0
0
0
15
0
outs
ide
15
15
0
0
0
0
0
15
0
outs
ide
15
15
0
0
0
0
0
207
Fabace
ae
Apiace
ae
Astera
ceae
Astera
ceae
Celastr
aceae
Ochna
ceae
Rosace
ae
Rubiac
eae
Anacar
diacea
e
Astera
ceae
Rhynchosia__clivor non
um
me
dici
nal
Heteromorpha__in non
volucrata_
me
dici
nal
Seriphium__specie non
s
me
dici
nal
Vernonia__wollast non
onii
me
dici
nal
Gymnosporia__het non
erophylla
me
dici
nal
Ochna__confusa
non
me
dici
nal
Cliffortia__repens
non
me
dici
nal
Oxyanthus__speci non
osus_
me
dici
nal
Rhus__rehmannia non
na_
me
dici
nal
Phymaspermum__ non
acerosum_
me
dici
nal
15
0
outs
ide
15
15
0
0
0
0
0
16
0
outs
ide
16
16
0
0
0
0
0
16
0
outs
ide
16
16
0
0
0
0
0
16
0
outs
ide
16
16
0
0
0
0
0
16
0
outs
ide
16
16
0
0
0
0
0
16
0
outs
ide
16
16
0
0
0
0
0
16
0
outs
ide
16
16
0
0
0
0
0
16
0
outs
ide
16
16
0
0
0
0
0
17
0
outs
ide
17
17
0
0
0
0
0
17
0
outs
ide
17
17
0
0
0
0
0
208
Fabace
ae
Lamiac
eae
Prote
aceae
Anacar
diacea
e
Ericace
ae
Rubiac
eae
Anacar
diacea
e
Anacar
diacea
e
Astera
ceae
Fabace
ae
Erythrina__latissi
ma
non
me
dici
nal
Hemzygia__albiflo non
ra
me
dici
nal
Faurea_galpinii
non
me
dici
nal
Ozoroa__paniculos non
a
me
dici
nal
Vaccinum__exul__ non
Bolus_
me
dici
nal
Pavetta__cooperi
non
me
dici
nal
Rhus__tumulicola_ non
__meeuseana_
me
dici
nal
Rhus__tumulicola_ non
_forma_
me
dici
nal
Tarchonanthus___ non
trilobus
me
dici
nal
Acacia__mellifera non
me
dici
nal
17
0
outs
ide
17
17
0
0
0
0
0
17
0
outs
ide
17
17
0
0
0
0
0
17
0
outs
ide
17
17
0
0
0
0
0
18
0
outs
ide
18
18
0
0
0
0
0
18
0
outs
ide
18
18
0
0
0
0
0
18
0
outs
ide
18
18
0
0
0
0
0
19
0
outs
ide
19
19
0
0
0
0
0
19
0
outs
ide
19
19
0
0
0
0
0
19
0
outs
ide
19
19
0
0
0
0
0
19
0
outs
ide
19
19
0
0
0
0
0
209
Morac
eae
Ficus__craterosto
ma
Anacar
diacea
e
Rhus__zeyheri
Myrtac
eae
Eugenia__natalitia
Fabace
ae
Crotalaria___cape
nsis
Malpig
hiacea
e
Triaspis_glaucoph
ylla_
Rubiac
eae
Burchellia__bubali
na_
Flacou
rtiacea
e
Scolopia__zeyheri
Thyme
laecea
e
Passerina_montan
a
Anacar
diacea
e
Rhus__lucida_
Rosace
ae
Cliffortia__nitididu
la
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
19
0
outs
ide
19
19
0
0
0
0
0
20
0
outs
ide
20
20
0
0
0
0
0
20
0
outs
ide
20
20
0
0
0
0
0
21
0
outs
ide
21
21
0
0
0
0
0
21
0
outs
ide
21
21
0
0
0
0
0
21
0
outs
ide
21
21
0
0
0
0
0
21
0
outs
ide
21
21
0
0
0
0
0
21
0
outs
ide
21
21
0
0
0
0
0
22
0
outs
ide
22
22
0
0
0
0
0
22
0
outs
ide
22
22
0
0
0
0
0
210
Rubiac
eae
Pavetta_edentula
Solana
ceae
Bowkeria__cymos
a
Araliac
eae
Cussonia__transva
alensis_
Escallo
niacea
Choristylis__rham
noides
Fabace
ae
Acacia__davyi_
Rhamn
aceae
Ziziphus__zeypher
ana
Rubiac
eae
Tarenna__supraaxillaris_
Burser
aceae
Commiphora__har
veyi
Meliac
eae
Ekebergia__pterop
hylla
Fabace
ae
Indigofera__tristoi
des
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
22
0
outs
ide
22
22
0
0
0
0
0
22
0
outs
ide
22
22
0
0
0
0
0
23
0
outs
ide
23
23
0
0
0
0
0
24
0
outs
ide
24
24
0
0
0
0
0
24
0
outs
ide
24
24
0
0
0
0
0
24
0
outs
ide
24
24
0
0
0
0
0
24
0
outs
ide
24
24
0
0
0
0
0
26
0
outs
ide
26
26
0
0
0
0
0
26
0
outs
ide
26
26
0
0
0
0
0
27
0
outs
ide
27
27
0
0
0
0
0
211
Rosace
ae
Cliffortia__linearif
olia_
Oliniac
eae
Olinia__emarginat
a
Fabace
ae
Acacia__robusta
Astera
ceae
Seriphium__plumo
sum
Fabace
ae
Erythrina__zeyheri
Lamiac
eae
Plectranthus__frut
icosus_
Melian
thacea
e
Greyia__radlkoferi
Rubiac
eae
Rothmannia__fisc
heri
Thyme
laecea
e
Dais_cotinifolia_L.
Podoc
arpace
ae
Podocarpus__latif
olius_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
27
0
outs
ide
27
27
0
0
0
0
0
28
0
outs
ide
28
28
0
0
0
0
0
28
0
outs
ide
28
28
0
0
0
0
0
29
0
outs
ide
29
29
0
0
0
0
0
29
0
outs
ide
29
29
0
0
0
0
0
29
0
outs
ide
29
29
0
0
0
0
0
29
0
outs
ide
29
29
0
0
0
0
0
29
0
outs
ide
29
29
0
0
0
0
0
29
0
outs
ide
29
29
0
0
0
0
0
30
0
outs
ide
30
30
0
0
0
0
0
212
Fabace
ae
Aeschynomene__r
ehmannii_
Myrica
ceae
Myrica__pilulifera
Ericace
ae
Erica__drakensber
gensis_
Fabace
ae
Otholobium__wil
msii_
Anacar
diacea
e
Rhus__gerrardi_
Rubiac
eae
Tricalysia__lanceol
ata_
Scroph
ulariac
eae
Buddleja_auriculat
a_
Astera
ceae
Lopholaena__corif
olia
Anacar
diacea
e
Rhus__tumulicola_
_
Rubiac
eae
Psychotria__capen
sis
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
31
0
outs
ide
31
31
0
0
0
0
0
31
0
outs
ide
31
31
0
0
0
0
0
32
0
outs
ide
32
32
0
0
0
0
0
32
0
outs
ide
32
32
0
0
0
0
0
34
0
outs
ide
34
34
0
0
0
0
0
36
0
outs
ide
36
36
0
0
0
0
0
36
0
outs
ide
36
36
0
0
0
0
0
37
0
outs
ide
37
37
0
0
0
0
0
38
0
outs
ide
38
38
0
0
0
0
0
38
0
outs
ide
38
38
0
0
0
0
0
213
Anacar
diacea
e
Rubiac
eae
Buddl
ejacea
e
Celastr
aceae
Anacar
diacea
e
Anacar
diacea
e
Sapind
aceae
Apocy
naceae
Burser
aceae
Apocy
naceae
Plumb
aginac
eae
Strych
naceae
Verbe
naceae
Rhus__pyroides__
gracilis
non
me
dici
nal
Cephalanthus__na non
talensis_
me
dici
nal
Nuxia__congesta
non
me
dici
nal
Pterocelastrus___e non
chinatus
me
dici
nal
Rhus_dentata
non
me
dici
nal
Rhus__discolor
non
me
dici
nal
Deinbollia__oblon me
gifolia
dici
nal
Tabernaemontana me
__ventricosa
dici
nal
Commiphora__vim me
inea
dici
nal
Strophanthus__ge me
rrardii_
dici
nal
Plumbago__auricu me
lata_
dici
nal
Strychnos_pungen me
s_
dici
nal
Vitex__rehmannii_ me
dici
nal
39
0
outs
ide
39
39
0
0
0
0
0
40
0
outs
ide
40
40
0
0
0
0
0
43
0
outs
ide
43
43
0
0
0
0
0
45
0
outs
ide
45
45
0
0
0
0
0
52
0
outs
ide
52
52
0
0
0
0
0
53
0
outs
ide
53
53
0
0
0
0
0
2
1
bot
h
1
3
1
0
1
0
0
3
1
bot
h
2
4
1
0
1
0
0
3
1
bot
h
2
4
1
1
0
0
0
4
1
bot
h
3
5
1
0
0
0
1
4
1
bot
h
3
5
1
1
0
1
0
10
1
bot
h
9
11
1
1
0
0
0
11
1
bot
h
10
12
1
0
0
1
0
214
Eupho
rbiace
ae
Strych
naceae
Celastr
aceae
Olacac
eae
Fabace
ae
Buddl
ejacea
e
Celastr
aceae
Rhamn
aceae
Solana
ceae
Fabace
ae
Meliac
eae
Stercul
iaceae
Tiliace
ae
Sapind
aceae
Verbe
naceae
Astera
ceae
Solana
ceae
Clutia___affinis_
me
dici
nal
Strychnos__hennin me
gsii_
dici
nal
Mystroxylon__aet me
hiopicum_
dici
nal
Jasminum__multip me
artitum
dici
nal
Acacia__luederitzii me
_
dici
nal
Nuxia__floribunda me
_
dici
nal
Gymnosporia__har me
veyana
dici
nal
Rhamnus__prinoid me
es_
dici
nal
Solanum__kweben me
se
dici
nal
Acacia__polyacant me
ha_
dici
nal
Turraea__nilotica_ me
dici
nal
Dombeya__cymos me
a
dici
nal
Triumfetta__pilosa me
dici
nal
Dodonaea_angusti me
folia_L.f
dici
nal
Vitex___obovata
me
dici
nal
Brachylaena__tran me
svaalensis
dici
nal
Solanum__gigante me
um
dici
nal
15
1
bot
h
14
16
1
1
0
0
0
16
1
bot
h
15
17
1
1
1
0
0
17
1
bot
h
16
18
1
1
1
0
0
19
1
bot
h
18
20
1
1
0
0
0
21
1
bot
h
20
22
1
0
1
0
0
21
1
bot
h
20
22
1
0
0
1
0
25
1
bot
h
24
26
1
1
0
0
0
38
1
bot
h
37
39
1
0
0
1
0
2
2
bot
h
0
4
1
1
0
0
0
3
2
bot
h
1
5
1
0
1
0
0
9
2
bot
h
7
11
1
1
0
0
0
10
2
bot
h
8
12
1
1
0
0
0
27
2
bot
h
25
29
1
0
0
1
0
27
2
bot
h
25
29
1
1
0
0
0
28
2
bot
h
26
30
1
0
0
0
0
30
2
bot
h
28
32
1
0
0
0
0
32
2
bot
h
30
34
1
0
0
1
0
215
Morac
eae
Ficus__salicifolia_
Tiliace
ae
Grewia__sulcata
Balanit
aceae
Balanites___pedici
llaris
Eupho
rbiace
ae
Eupho
rbiace
ae
Sapota
ceae
Cleistantus__schle
chteri
Apocy
naceae
Acokanthera__rot
undata
Flacou
rtiacea
e
Myrica
ceae
Flacourtia__indica
Cappar
aceae
Maerua__decumb
ens_
Eupho
rbiace
ae
Eupho
rbiace
ae
Fabace
ae
Margaritaria__dis
coidea_
Malva
ceae
Abutilon__angulat
um
Strych
naceae
Strychnos__usamb
arensis_
Morac
eae
Ficus__glumosa_
Ulmac
eae
Trema__orientalis
Croton__steenkam
pianus_
Vitellariopsis__ma
rginata_
Morella___serrata
_
Margaritaria__dis
coidea_nitida_
Elephantorrhiza__
goetzei
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
36
2
bot
h
34
38
1
0
0
0
0
48
2
bot
h
46
50
0
0
0
0
0
1
3
bot
h
-2
4
1
1
0
0
0
1
3
bot
h
-2
4
1
0
1
0
0
1
3
bot
h
-2
4
1
0
0
1
0
4
3
bot
h
1
7
1
1
1
0
0
11
3
bot
h
8
14
1
1
0
0
0
21
3
bot
h
18
24
1
1
0
1
0
26
3
bot
h
23
29
1
0
0
0
0
2
4
bot
h
-2
6
1
0
0
0
0
3
4
bot
h
-1
7
1
0
1
0
0
3
4
bot
h
-1
7
1
0
1
0
0
4
4
bot
h
0
8
1
1
0
0
0
6
4
bot
h
2
10
1
1
0
0
0
8
4
bot
h
4
12
1
0
1
1
0
33
4
bot
h
29
37
1
0
0
0
1
39
4
bot
h
35
43
1
0
1
1
1
216
Cappar
aceae
Thilachium__africa
num_
Vitace
ae
Cissus__cactiformi
s
Ochna
ceae
Ochna__pulchra_
Vitace
ae
Rhoicissus__revoili
i_
Lamiac
eae
Tetradenia__ripari
a_
Fabace
ae
Acacia__sieberian
a_
Boragi
naceae
Ehretia__rigida
Boragi
naceae
Cordia__sinensis_
Lamiac
eae
Karomia_speciosa
Fabace
ae
Eriosema__psorale
oides
Ebenac Euclea__undulata
eae
_
Morac
eae
Maclura_africana_
Boragi
naceae
Cordia__monoica
Boragi
naceae
Cordia_ovalis
Boragi
naceae
Ehretia__amoena
Combr
etacea
e
Fabace
ae
Terminalia__phan
erophlebia
Sesbania__sesban
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
1
5
bot
h
-4
6
1
0
0
1
0
6
5
bot
h
1
11
1
0
0
1
0
13
5
bot
h
8
18
1
0
1
1
0
15
5
bot
h
10
20
1
1
0
0
0
42
5
bot
h
37
47
1
0
0
1
0
47
5
bot
h
42
52
1
0
1
0
0
49
5
bot
h
44
54
1
1
0
0
0
1
6
bot
h
-5
7
1
1
0
0
0
16
6
bot
h
10
22
0
0
0
0
0
39
6
bot
h
33
45
1
1
0
1
0
33
8
bot
h
25
41
1
1
0
0
0
4
9
bot
h
-5
13
1
1
0
0
1
13
1
0
bot
h
3
23
1
0
0
1
0
13
1
0
bot
h
3
23
1
0
1
0
1
30
1
0
bot
h
20
40
1
1
1
0
0
27
1
1
bot
h
16
38
1
1
1
0
0
23
1
2
bot
h
11
35
1
0
1
0
0
217
Fabace
ae
Albizia__petersian
a
Anacar
diacea
e
Fabace
ae
Rhus__guenzii_
Sapin
daceae
Pappea__capensis
Fabace
ae
Dichrostachys__ci
nerea_sp
Celastr
aceae
Gymnosporia__se
negalensis
Schotia__capitata
Ebenac Euclea__schimperi
eae
_
Fabace
ae
Acacia__robusta_
Phylla
nthace
ae
Fabace
ae
Phyllanthus__retic
ulatus_
Buddl
ejacea
e
Fabace
ae
Nuxia__oppositifol
ia
Strych
naceae
Strychnos__decuss
ata
Fabace
ae
Acacia__tortilis
Combr
etacea
e
Celastr
aceae
Combretum__apic
ulatum
Morac
eae
Ficus-_natalensis_
Acacia__gerrardii_
Acacia__nilotica
Pterocelastrus_tric
uspidatus
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
5
1
3
bot
h
-8
18
1
1
1
0
0
15
1
3
bot
h
2
28
1
0
0
0
1
8
1
4
bot
h
-6
22
1
0
1
0
0
46
1
4
bot
h
32
60
1
0
0
0
1
42
1
5
bot
h
27
57
1
0
1
0
0
23
1
7
bot
h
6
40
1
1
0
0
0
22
1
8
bot
h
4
40
1
1
1
1
0
24
1
8
bot
h
6
42
1
0
1
0
0
22
1
9
bot
h
3
41
1
0
0
1
0
26
1
9
bot
h
7
45
1
0
0
0
0
23
2
1
bot
h
2
44
1
0
0
0
0
64
2
1
bot
h
43
85
1
0
1
0
0
7
2
5
bot
h
-18
32
1
1
0
0
0
51
2
8
bot
h
23
79
1
0
1
0
0
65
4
4
bot
h
21
109
1
0
0
1
0
0
0
insi
de
0
0
0
0
0
0
0
0
1
insi
de
-1
1
1
0
1
0
0
218
me
dici
nal
Ebenac Diospyros__loureir me
eae
iana
dici
nal
Fabace Cordyla__africana me
ae
_
dici
nal
Fabace Newtonia__hildebr me
ae
andtii
dici
nal
Celastr Salacia__kraussii_ me
aceae
dici
nal
Rubiac Pavetta__harborii me
eae
dici
nal
Salvad Salvadora__persic me
oracea a
dici
e
nal
Apocy Strophanthus__pe me
naceae tersianus
dici
nal
Fabace Albizia___amara
me
ae
dici
nal
Fabace Xeroderris__stuhl
me
ae
mannii_
dici
nal
Apocy Strophanthus__ko me
naceae mbe
dici
nal
Rubiac Hymenodictyon__ me
eae
parvifolium
dici
nal
Apocy Holarrhena__pube me
naceae scens_
dici
nal
Apocy Adenium__multiflo me
naceae rum
dici
nal
Eupho Androstachys__joh me
rbiace nsonii_
dici
ae
nal
Eupho Androstachys__joh me
rbiace nsonii_
dici
ae
nal
Fabace Albizia__forbesii_
me
ae
dici
nal
Achari
aceae
Xylotheca__krauss
iana
0
2
insi
de
-2
2
1
1
0
0
0
0
2
insi
de
-2
2
1
1
1
0
0
0
2
insi
de
-2
2
1
0
1
0
0
0
2
insi
de
-2
2
1
0
1
0
0
0
3
insi
de
-3
3
1
1
0
0
0
0
3
insi
de
-3
3
1
0
0
1
0
0
3
insi
de
-3
3
1
1
0
0
0
0
4
insi
de
-4
4
1
0
0
0
1
0
4
insi
de
-4
4
1
1
0
0
0
0
4
insi
de
-4
4
1
1
0
0
0
0
5
insi
de
-5
5
1
0
0
0
1
0
5
insi
de
-5
5
1
1
0
0
0
0
6
insi
de
-6
6
4
0
0
0
0
0
7
insi
de
-7
7
1
0
1
0
0
0
8
insi
de
-8
8
1
0
1
0
0
0
8
insi
de
-8
8
1
0
1
0
1
0
1
7
insi
de
-17
17
1
0
1
0
0
219
Clusiac
eae
Garcinia__gerrardi
i
Eupho
rbiace
ae
Sapota
ceae
Euphorbia__grand
idens
Acanth
aceae
Sclerochiton_ilicifo
loius_
Apocy
naceae
Gonioma__kamass
i
Sapota
ceae
Elaeodendron__cr
oceum
Malpig
hiacea
e
Clusiac
eae
Triaspis__hyperico
ides
Stercu
liaceae
Cola__greenwayi
Prote
aceae
Faurea__macnaug
htonii
Cappar
aceae
Cadaba___natalen
sis_
Sapota
ceae
Elaeodendron__ze
yheri_
Manilkara__discol
or
Hypericum__roepe
rianum
Ebenac Diospyros__natale
eae
nsis
Melia
nthace
ae
Celastr
aceae
Bersama__lucens
Fabace
ae
Acacia__erioloba
Malva
ceae
Abutilon__sonnera
tum
Cassine__peragua
_
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
1
0
outs
ide
1
1
1
1
1
1
0
1
0
outs
ide
1
1
1
0
1
0
0
1
0
outs
ide
1
1
1
0
1
0
0
2
0
outs
ide
2
2
1
1
0
0
0
2
0
outs
ide
2
2
1
0
1
0
0
2
0
outs
ide
2
2
1
0
1
1
1
2
0
outs
ide
2
2
1
1
0
0
0
3
0
outs
ide
3
3
1
0
0
0
0
3
0
outs
ide
3
3
1
0
1
0
0
3
0
outs
ide
3
3
1
0
1
0
0
4
0
outs
ide
4
4
1
0
0
0
0
4
0
outs
ide
4
4
1
0
0
0
0
4
0
outs
ide
4
4
0
0
0
0
0
4
0
outs
ide
4
4
1
0
0
1
0
5
0
outs
ide
5
5
1
0
0
1
0
5
0
outs
ide
5
5
1
0
1
0
0
5
0
outs
ide
5
5
1
0
1
0
0
220
Astera
ceae
Vernonia__adoens
is
Astera
ceae
Gymnanthemum
amygdalinum
(Delile) Sch. Bip.
ex Walp
Lamia
ceae
Leonotis__leonuru
s
Malpi
ghiace
ae
Laure
aceae
Celastr
aceae
Sapota
ceae
Astera
ceae
Astera
ceae
Fabace
ae
Flacou
rtiacea
e
Fabace
ae
Sapota
ceae
Rhizop
horace
ae
Aspara
gaceae
Laurac
eae
me
dici
nal
me
dici
nal
6
0
outs
ide
6
6
1
0
1
1
0
6
0
outs
ide
6
6
1
0
1
1
0
me
dici
nal
Acridocarpus_nata me
litius
dici
nal
Ocotea___kenyens me
is
dici
nal
Pterocelastrus__ro me
stratus
dici
nal
Manilkara__concol me
or
dici
nal
Brachylaena__ilicif me
olia
dici
nal
Sapium__ellipticu
me
m
dici
nal
Bauhinia_tomento me
sa
dici
nal
Gerrardina__folios me
a_
dici
nal
Lessertia__microp me
hylla
dici
nal
Mimusops__obova me
ta
dici
nal
Cassipourea__mal me
osana
dici
nal
Dracaena__aletrif me
ormis
dici
nal
Cryptocarya__tran me
svaalensis
dici
nal
6
0
outs
ide
6
6
1
1
1
0
0
7
0
outs
ide
7
7
1
1
1
1
0
7
0
outs
ide
7
7
1
0
0
0
0
8
0
outs
ide
8
8
1
0
1
0
0
8
0
outs
ide
8
8
1
1
0
0
0
9
0
outs
ide
9
9
1
0
0
1
0
9
0
outs
ide
9
9
1
1
0
0
0
9
0
outs
ide
9
9
1
1
1
0
0
9
0
outs
ide
9
9
1
0
0
0
0
10
0
outs
ide
10
10
1
0
0
0
0
12
0
outs
ide
12
12
1
0
0
0
0
12
0
outs
ide
12
12
1
0
1
0
0
13
0
outs
ide
13
13
1
0
0
0
0
14
0
outs
ide
14
14
1
0
1
0
0
221
Ochna
ceae
Ochna__serrulata
Ochna
ceae
Ochna__oconnori
Ochna
ceae
Ochna__holstii
Annon
aceae
Monanthotaxis__c
affra_
Solana
ceae
Solanum__aculeas
trum_
Clusiac
eae
Hypericum__revol
utum_
Araliac
eae
Schefflera__umbel
lifera_
Ebenac Diospyros__galpini
eae
i
Melian
thacea
e
Myrta
ceae
Greyia__sutherlan
dii_
Podoc
arpace
ae
Rhamn
aceae
Afrocarpus__falcat
us
Scroph
ulariac
eae
Anacar
diacea
e
Thyme
laecea
e
Anacar
diacea
e
Cappar
aceae
Buddleja__saligna
Syzygium__gerrar
dii
Scutia__myrtina
Protorhus__longif
olia_
Peddiea__africana
_
Harpephyllum__ca
ffrum_
Boscia__foetida__
rehmanniana
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
14
0
outs
ide
14
14
1
0
0
0
0
15
0
outs
ide
15
15
1
0
1
0
0
15
0
outs
ide
15
15
1
0
1
0
0
16
0
outs
ide
16
16
1
0
0
0
1
16
0
outs
ide
16
16
1
0
0
0
1
17
0
outs
ide
17
17
1
0
0
1
0
18
0
outs
ide
18
18
1
0
0
0
0
18
0
outs
ide
18
18
1
0
0
0
0
18
0
outs
ide
18
18
1
0
0
0
0
18
0
outs
ide
18
18
1
0
1
0
0
19
0
outs
ide
19
19
1
0
1
0
0
19
0
outs
ide
19
19
1
0
0
0
0
20
0
outs
ide
20
20
1
0
0
1
0
21
0
outs
ide
21
21
1
0
0
0
0
21
0
outs
ide
21
21
1
0
1
0
0
22
0
outs
ide
22
22
1
0
1
0
1
22
0
outs
ide
22
22
1
0
0
0
1
222
Moni
miacea
e
Fabace
ae
Xymalos__monosp
ora_
Protea
ceae
Protea__wewitschi
i_
Cornac
aeae
Curtisia__dentata
Laurac
eae
Cryptocarya__woo
dii
Rutace
ae
Calodendrum__ca
pensis_
Prote
aceae
Protea__gaguedi_
Astera
ceae
Vernonia__tigna_
Xanth
orrhoe
aceae
Aloe_castanea
Prote
aceae
Faurea__rochetian
a
Polyg
alacea
e
Cyathe
aceae
Polygala__virgata
_
Tiliace
ae
Grewia__flavescen
s_
Prote
aceae
Protea__roupelliae
_
Aquifo
liaceae
Ilex__mitis
Combr
etacea
e
Combretum__krau
ssii
Psoralea__latifolia
Cyathea___degrei
_
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
23
0
outs
ide
23
23
1
0
1
0
0
23
0
outs
ide
23
23
1
1
0
0
0
24
0
outs
ide
24
24
1
1
0
0
0
26
0
outs
ide
26
26
1
0
1
0
0
26
0
outs
ide
26
26
1
0
1
0
0
27
0
outs
ide
27
27
1
0
0
1
0
29
0
outs
ide
29
29
1
1
0
0
0
31
0
outs
ide
31
31
1
1
0
0
0
32
0
outs
ide
32
32
1
1
0
0
0
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
32
0
outs
ide
32
32
1
1
0
0
0
33
0
outs
ide
33
33
1
1
0
0
0
35
0
outs
ide
35
35
1
1
0
0
0
35
0
outs
ide
35
35
1
1
0
0
0
35
0
outs
ide
35
35
1
1
0
0
0
38
0
outs
ide
38
38
1
1
0
0
0
41
0
outs
ide
41
41
1
1
0
0
0
223
Anacar
diacea
e
Celastr
aceae
Searsia__chirinden
sis
Achari
aceae
Kiggelaria__africa
na
Scroph
ulariac
eae
Celastr
aceae
Buddleja_salviifoli
a
Astera
ceae
Senecio_barberton
icus
Celastr
aceae
Maytenus_pedunc
ularis
Eupho
rbiace
ae
Croton__menyhart
iI
Flacou
rtiacea
e
Araliac
eae
Dovyalis__zeyheri
Apocy
naceae
Carissa__tetramer
a
Anacar
diacea
e
Lannea_edulis
Gymnosporia_buxi
folia
Putterlickia_verruc
osa
Cussonia__natalen
sis
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
43
0
outs
ide
43
43
1
1
0
0
0
47
0
outs
ide
47
47
2
0
0
0
0
53
0
outs
ide
53
53
0
0
0
0
0
60
0
outs
ide
60
60
0
0
0
0
0
6
1
bot
h
5
7
1
1
0
0
0
18
1
bot
h
17
19
1
0
0
1
0
29
1
bot
h
28
30
1
1
0
0
0
14
2
bot
h
12
16
1
0
0
1
0
45
2
bot
h
43
47
1
0
1
1
0
22
4
bot
h
18
26
1
0
1
0
0
3
5
bot
h
-2
8
1
0
0
0
1
27
6
bot
h
21
33
1
1
1
0
0
224
Fabace
ae
Anacar
diacea
e
Olacac
eae
Combr
etacea
e
Olacac
eae
Celastr
aceae
Celastr
aceae
Myrta
ceae
Fabace
ae
Fabace
ae
Acacia__senegal_l
eiorhachis
non
me
dici
nal
Rhus__leptodictya non
_
me
dici
nal
Schrebera__alata
non
me
dici
nal
Combretum__moll non
e_
me
dici
nal
Olax_dissitiflora_
non
me
dici
nal
Hippocratea__long non
ipetiolata
me
dici
nal
Hippocratea__long non
ipetiolata
me
dici
nal
Syzygium__guinee non
nse
me
dici
nal
Xanthocercis__za
non
mbesiaca_
me
dici
nal
Pterocarpus__rotu non
ndifolius
me
dici
nal
17
7
bot
h
10
24
1
0
0
0
1
35
7
bot
h
28
42
1
1
0
1
0
40
1
0
bot
h
30
50
1
0
0
1
0
12
1
1
bot
h
1
23
1
0
0
0
0
13
1
1
bot
h
2
24
1
0
1
0
0
15
1
2
bot
h
3
27
1
1
1
0
0
17
1
2
bot
h
5
29
1
1
1
0
0
22
1
4
bot
h
8
36
1
0
1
0
0
6
2
3
bot
h
-17
29
1
1
0
0
0
42
2
9
bot
h
13
71
1
0
1
0
0
225
Combr
etacea
e
Combretum_moss
ambicense_
Passifl
oracea
e
Adenia_spinosa
Rutace
ae
Zanthoxylum__lep
rieurii
Boragi
naceae
Cordia__grandical
yx
Herna
ndiace
ae
Gyrocarpus_ameri
canus
Prote
aceae
Protea__caffra__f
alcata
Myrta
ceae
Syzygium__legatii
Ochna
ceae
Ochna__arborea_
Erythr
oxylac
eae
Erythroxylum__del
agoense
Simaro
ubace
ae
Kirkia__wilmsii_
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
5
3
0
bot
h
-25
35
1
0
0
0
0
0
2
insi
de
-2
2
1
0
0
0
0
0
3
insi
de
-3
3
1
1
0
0
0
0
6
insi
de
-6
6
1
1
0
0
0
0
1
insi
de
-1
1
1
1
0
0
0
5
0
outs
ide
5
5
1
0
0
0
1
7
0
outs
ide
7
7
1
0
0
1
1
15
0
outs
ide
15
15
1
1
0
0
0
24
0
outs
ide
24
24
1
0
0
0
1
29
0
outs
ide
29
29
1
1
0
0
0
226
Araliac
eae
Cussionia__panicul
ata
Fabace
ae
Dalbergia__armat
a
Fabace
ae
Acacia__ataxacant
ha
Ebenac Diospyros__villosa
eae
Eupho
rbiace
ae
Rubiac
eae
Croton__sylvaticus
Pavetta__lanceola
ta
Ebenac Eucllea__crispa__f
eae
orm__A
Velloz
iaceae
Xerophyta_retiner
vis_
Fabace
ae
Albizia__anthelmi
ntica
Ebenac Euclea__crispa_
eae
Salvad
oracea
e
Flacou
rtiacea
e
Urtica
ceae
Azima__tetracant
ha
Solana
ceae
Solanum___lichten
steinii
Tiliace
ae
Grewia__caffra_
Oncoba__spinosa
Obetia__tenax
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
33
0
outs
ide
33
33
1
1
0
0
0
40
0
outs
ide
40
40
1
0
0
0
0
55
0
outs
ide
55
55
1
1
1
0
0
6
1
bot
h
5
7
1
0
0
1
0
6
1
bot
h
5
7
1
0
1
0
0
16
2
bot
h
14
18
1
0
0
0
0
31
2
bot
h
29
33
1
1
0
0
0
52
3
bot
h
49
55
1
0
0
1
0
21
4
bot
h
17
25
1
0
0
0
0
51
4
bot
h
47
55
1
0
0
1
0
3
5
bot
h
-2
8
1
1
0
0
0
9
5
bot
h
4
14
1
1
0
0
0
22
5
bot
h
17
27
1
0
1
0
0
39
6
bot
h
33
45
1
0
0
1
0
11
7
bot
h
4
18
1
0
0
0
1
227
Sapota
ceae
Sideroxylon__iner
me
Fabace
ae
Acacia__caffra_
Meliac
eae
Turraea__obtusifol
ia_
Myrta
ceae
Syzygium__cordat
um
Rhamn
aceae
Ziziphus_mucronata
Fabace
ae
Acacia__xanthophl
oea_
Fabace
ae
Ormocarpum___tr
ichocarpum
Olacac
eae
Ximenia__caffra_
Fabace
ae
Acacia__nigrescen
s
Fabace
ae
Colophospermum_
mopane
Fabace
ae
Philenoptera__viol
acea
Combr
etacea
e
Annon
aceae
Combretum__here
roense
Cappar
aceae
Capparis__sepiaria
_
Strych
naceae
Strychnos__potato
rum
Fabace
ae
Dalbergia__obova
ta_
Astera
ceae
Sapium___integerr
imum
Uvaria__lucida__B
oj__Sweet
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
18
7
bot
h
11
25
1
0
1
0
0
77
7
bot
h
70
84
1
0
0
1
0
28
1
0
bot
h
18
38
1
1
0
1
0
45
1
7
bot
h
28
62
1
1
0
1
0
65
1
7
bot
h
48
82
1
1
0
0
0
1
2
1
bot
h
-20
22
1
0
1
0
0
18
2
3
bot
h
-5
41
1
0
0
0
0
55
2
6
bot
h
29
81
1
1
0
0
0
44
2
7
bot
h
17
71
1
0
0
0
0
1
2
8
bot
h
-27
29
1
0
0
0
0
24
3
6
bot
h
-12
60
1
1
0
1
0
55
4
0
bot
h
15
95
1
0
0
0
0
0
2
insi
de
-2
2
1
1
0
0
0
0
4
insi
de
-4
4
1
1
0
0
0
0
5
insi
de
-5
5
1
0
0
1
0
1
0
outs
ide
1
1
1
0
0
0
0
2
0
outs
ide
2
2
1
1
0
0
0
228
Melia
ceae
Turraea__floribun
da_
Cappar
aceae
Cadaba_aphylla
Apocy
naceae
Strophanthus__sp
eciousus
Fabace
ae
Adenopodia__spic
ata
Ulmac
eae
Chaetachne__arist
ata
Eupho
rbiace
ae
Olacac
eae
Clutia__pulchella_
Eupho
rbiace
ae
Euphorbia__coope
ri_
Tiliace
ae
Grewia__villosa
Fabace
ae
Acacia__senegal_
_rostrata_
Annon
aceae
Hexalobus__mono
petalus
Boragi
naceae
Ehretia__obtusifoli
a_
Fabace
ae
Calpurnia__sericea
_
Olea__capensis_
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
3
0
outs
ide
3
3
1
1
0
0
0
4
0
outs
ide
4
4
1
1
0
0
0
9
0
outs
ide
9
9
1
1
0
0
0
24
0
outs
ide
24
24
1
1
0
0
0
29
0
outs
ide
29
29
1
0
0
0
0
35
0
outs
ide
35
35
1
0
0
1
0
33
1
bot
h
32
34
2
1
1
0
0
23
3
bot
h
20
26
2
1
0
0
0
5
9
bot
h
-4
14
2
1
0
0
1
24
9
bot
h
15
33
2
0
1
0
1
8
1
1
bot
h
-3
19
2
1
1
0
1
14
1
9
bot
h
-5
33
2
1
0
0
0
5
0
outs
ide
5
5
2
0
0
0
0
229
Cupres
saceae
Widdringtonia__n
odiflora
Olacac
eae
Olea__capensis__
_Macrocarpa_
Astera
ceae
Vernonia__myrian
tha
Rubiac
eae
Pachystigma__ma
crocalyx
Morac
eae
Ficus__burkei_
Hetero Heteropyxis__nata
pyxida lensis
ceae
Salica Salix__mucronata
ceae
Pittos
porace
ae
Fabace
ae
Pittosporum__virid
iflorum
Fabace
ae
Calpurnia__aurea
Canna
baceae
Celtis__africana
Apocy
naceae
Wrightia__natalen
sis_
Bignon
iaceae
Tecomaria___cape
nsis
Indigofera__arrect
a
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
8
0
outs
ide
8
8
2
1
0
0
0
9
0
outs
ide
9
9
2
1
1
0
0
19
0
outs
ide
19
19
2
1
0
0
0
24
0
outs
ide
24
24
2
1
0
0
0
39
0
outs
ide
39
39
2
1
1
1
1
41
1
bot
h
40
42
2
1
0
0
0
43
1
bot
h
42
44
2
0
1
1
0
52
1
bot
h
51
53
2
0
1
0
0
17
2
bot
h
15
19
2
0
0
0
0
26
2
bot
h
24
28
2
0
0
0
0
64
2
bot
h
62
66
2
0
1
0
0
5
3
bot
h
2
8
2
1
1
0
0
19
3
bot
h
16
22
2
0
0
0
1
230
Sapota
ceae
Myrsi
naceae
Phylla
nthace
ae
Anacar
diacea
e
Ptaer
oxylac
eae
Phylla
nthace
ae
Rubiac
eae
Phylla
nthace
ae
Fabace
ae
Eupho
rbiace
ae
Arecac
eae
Strych
naceae
Combr
etacea
e
Eupho
rbiace
ae
Fabace
ae
Fabace
ae
Phylla
nthace
ae
Englerophytum__
magalismontanum
me
dici
nal
Maesa__lanceolat me
a_
dici
nal
Bridelia_mollis_
me
dici
nal
Lannea_discolor
me
dici
nal
Ptaeroxylon__obli me
quum
dici
nal
Bridelia_mollis
me
dici
nal
Gardenia__volkens me
ii_
dici
nal
Bridelia_cathartica me
dici
nal
Mundulea__serice me
a
dici
nal
Flueggea__virosa
me
dici
nal
Phoenix__reclinata me
dici
nal
Strychnos__spinos me
a
dici
nal
Combretum__zeyh me
eri
dici
nal
Croton__pseudopu me
lchellus_
dici
nal
Afzelia__quanzens me
is_
dici
nal
Calpurnia_glabrat me
a_
dici
nal
Andrachne__ovalis me
dici
nal
70
4
bot
h
66
74
2
1
1
0
0
42
5
bot
h
37
47
2
1
0
0
0
21
6
bot
h
15
27
2
1
1
0
1
39
6
bot
h
33
45
2
1
1
0
0
20
7
bot
h
13
27
2
0
1
1
0
18
8
bot
h
10
26
2
1
0
0
1
21
1
0
bot
h
11
31
2
1
0
1
0
15
1
2
bot
h
3
27
2
1
1
0
0
56
2
3
bot
h
33
79
2
0
0
0
0
35
2
4
bot
h
11
59
2
1
0
0
0
17
2
6
bot
h
-9
43
2
0
0
1
1
33
3
1
bot
h
2
64
2
0
0
1
1
65
3
9
bot
h
26
104
2
0
0
0
0
0
3
insi
de
-3
3
2
0
0
1
0
0
1
8
insi
de
-18
18
2
0
0
0
0
7
0
outs
ide
7
7
2
0
0
0
0
13
0
outs
ide
13
13
2
1
0
0
0
231
Melia
nthace
ae
Vitace
ae
Bersama__tysonia
na
Flacou
rtiacea
e
Icacina
ceae
Trimeria__grandif
olia
Scrop
hularia
ceae
Prote
aceae
Halleria__lucida
Portul
acacea
e
Portulacaria_afra_
Cappar
aceae
Maerua__cafra
Morac
eae
Ficus__ingens_
Anacar
diacea
e
Ozoroa__obovata
Morac
eae
Ficus__abutilifolia
Rutace
ae
Zanthoxylum__hu
mile
Tiliace
ae
Grewia__hexamita
Rhoicissus__tomen
tosus
Apodytes__dimidi
ata_
Protea__caffra_
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
13
0
outs
ide
13
13
2
1
1
1
0
28
0
outs
ide
28
28
2
1
0
0
0
37
0
outs
ide
37
37
2
0
0
0
1
42
0
outs
ide
42
42
2
0
1
1
0
48
0
outs
ide
48
48
2
1
0
0
0
60
0
outs
ide
60
60
2
0
1
0
1
6
3
bot
h
3
9
3
0
0
1
0
33
3
bot
h
30
36
3
1
0
0
0
51
6
bot
h
45
57
3
0
1
1
0
1
7
bot
h
-6
8
3
0
0
1
0
36
1
0
bot
h
26
46
3
1
1
0
0
2
1
2
bot
h
-10
14
3
1
0
0
0
22
1
9
bot
h
3
41
3
1
1
0
1
232
Strych
naceae
Tiliace
ae
Rubiac
eae
Astera
ceae
Rubiac
eae
Pipera
ceae
Sapind
aceae
Gentia
naceae
Rham
naceae
Bignon
iaceae
Celastr
aceae
Apocy
naceae
Combr
etacea
e
dici
nal
Strychnos__madag non
ascariensis
me
dici
nal
Grewia__microthy non
rsa
me
dici
nal
Canthium__ciliatu non
m
me
dici
nal
Helichrysum__kra non
ussii_
me
dici
nal
Canthium__inerme non
me
dici
nal
Piper__capense
me
dici
nal
Hippobromus__pa me
uciflorus
dici
nal
Anthocleista___gr me
andiflora_
dici
nal
Helinus__integrifol me
ius
dici
nal
Markhamia__zanz me
ibarica
dici
nal
Catha_edulis_
me
dici
nal
Acokanthera__opp me
ositifolia_
dici
nal
Combretum__eryt me
hrophyllum_
dici
nal
54
3
7
bot
h
17
91
3
0
0
0
0
0
8
insi
de
-8
8
3
1
0
0
1
20
0
outs
ide
20
20
3
1
0
0
0
31
0
outs
ide
31
31
3
1
0
0
0
39
0
outs
ide
39
39
3
1
0
0
0
8
1
bot
h
7
9
3
1
1
0
0
38
2
bot
h
36
40
3
1
0
0
0
11
3
bot
h
8
14
3
0
0
0
0
38
3
bot
h
35
41
3
1
0
0
0
3
4
bot
h
-1
7
3
1
0
0
0
18
4
bot
h
14
22
3
1
0
1
0
25
4
bot
h
21
29
3
0
1
0
0
65
7
bot
h
58
72
3
1
0
0
0
233
Rham
naceae
Berchemia__discol
or
Fabace
ae
Faidherbia__albid
a
Urtica
ceae
Pouzolzia__mixta_
Verbe
naceae
Lantana__rugosa_
Morac
eae
Ficus_sycomorus_
Cappar
aceae
Maerua__angolen
sis
Fabace
ae
Acacia__burkei_
Tiliace
ae
Grewia__bicolor
Fabace
ae
Bolusanthus_speci
osus
Fabace
ae
Dalbergia__melan
oxylon
Rosace
ae
Leucosidea__seric
ea
Apocy
naceae
Carissa__bispinosa
___bispinosa_
Apocy
naceae
Landolphia__kirkii
_
Annon
aceae
Artabotrys__brach
ypetalus_
Tiliace
ae
Trichilia__dregean
a
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
6
8
bot
h
-2
14
3
1
1
0
1
9
9
bot
h
0
18
3
0
0
0
0
27
1
0
bot
h
17
37
3
1
0
1
0
43
1
0
bot
h
33
53
3
1
0
1
0
25
2
0
bot
h
5
45
3
1
0
1
1
35
2
1
bot
h
14
56
3
0
1
1
0
40
2
1
bot
h
19
61
3
0
0
0
0
28
2
5
bot
h
3
53
3
1
0
0
0
25
2
8
bot
h
-3
53
3
0
0
0
0
18
3
4
bot
h
-16
52
3
0
0
0
0
35
0
outs
ide
35
35
3
0
0
1
0
27
3
bot
h
24
30
4
1
0
0
1
0
3
insi
de
-3
3
4
0
0
0
1
0
6
insi
de
-6
6
4
1
0
0
0
8
0
outs
ide
8
8
4
0
1
0
0
234
Ebenac Euclea__linearis__
eae
Rubiac
eae
Vangueria__mada
gascariensis
Prote
aceae
Faurea__saligna
Fabace
ae
Cassia_abbreviata
Ranun
culace
ae
Passifl
oracea
e
Apocy
naceae
Clematis__brachia
ta_
Morac
eae
Ficus__sur__Forss
k.
Phylla
nthace
ae
Fabace
ae
Bridelia_micrantha
Rham
naceae
Berchemia__zeyhe
ri
Adenia_gummifer
a
Carissa__bispinosa
___Zambesiensis
Erythrina__lysiste
mon
Ebenac Diospyros__whyte
eae
ana
Apocy
naceae
Rauvolfia__caffra
Ptaero
xylace
ae
Ptaeroxylon__obli
quum_
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
16
0
outs
ide
16
16
4
1
0
0
1
19
0
outs
ide
19
19
4
1
0
0
0
60
0
outs
ide
60
60
4
1
1
0
0
19
1
bot
h
18
20
4
0
0
0
0
42
1
bot
h
41
43
4
1
1
0
1
18
2
bot
h
16
20
4
1
1
0
0
36
2
bot
h
34
38
4
1
0
0
1
50
2
bot
h
48
52
4
1
0
1
1
18
3
bot
h
15
21
4
1
0
1
1
55
3
bot
h
52
58
4
0
0
0
0
46
4
bot
h
42
50
4
0
1
0
0
69
4
bot
h
65
73
4
0
1
0
0
20
6
bot
h
14
26
4
1
1
0
0
20
9
bot
h
11
29
4
0
0
1
0
235
Tiliace
ae
Grewia__flavescen
s
me
dici
nal
Eupho Croton__megalob me
rbiace otrys
dici
ae
nal
Combr Combretum__imb me
etacea erbe
dici
e
nal
Fabace Cassia_abbreviata me
ae
dici
nal
Xanth
Aloe_arborescens
me
orrhoe
dici
aceae
nal
Arecac Hyphaene__coriac non
eae
ea
me
dici
nal
Sapota Mimusops__zeyhe non
ceae
ri_
me
dici
nal
Anacar Ozoroa__paniculos non
diacea a
e
me
dici
nal
Anacar Ozoroa__sphaeroc me
diacea arpa
dici
e
nal
Ebenac Diospyros__lycioid me
eae
es_
dici
nal
Apocy Carissa__edulis_
me
naceae
dici
nal
Vitace Rhoicissus__triden me
ae
tata
dici
nal
Rutace Clausena_anisata_ me
ae
dici
nal
Eupho Antidesma__venos me
rbiace um_
dici
ae
nal
Eupho Antidesma__venos me
rbiace um_
dici
ae
nal
33
1
3
bot
h
20
46
4
1
0
0
1
6
1
5
bot
h
-9
21
4
0
1
0
1
24
4
1
bot
h
-17
65
4
0
0
0
0
0
2
0
insi
de
-20
20
4
0
0
0
0
46
0
outs
ide
46
46
4
1
0
1
0
2
1
0
bot
h
-8
12
5
1
1
0
0
46
1
3
bot
h
33
59
5
0
1
0
1
1
0
outs
ide
1
1
5
1
2
0
0
11
1
bot
h
10
12
5
0
1
0
0
24
1
bot
h
23
25
5
1
1
0
0
16
2
bot
h
14
18
5
1
0
0
1
50
2
bot
h
48
52
5
1
0
0
0
37
3
bot
h
34
40
5
0
0
1
0
24
4
bot
h
20
28
5
1
0
0
0
20
7
bot
h
13
27
5
1
0
1
0
236
Xanth
orrhoe
aceae
Bomba
caceae
Aloe_marlothii
Fabace
ae
Erythrina__humea
na
Balanit
aceae
Balanites__maugh
amii
Cappar
aceae
Boscia__albitrunca
Olacac
eae
Ximenia__america
na_
Laure
aceae
Ocotea__bullata
Rutace
ae
Vepris__lanceolat
a
Fabace
ae
Bauhinia_galpinii
Fabace
ae
Albizia__brevifolia
_
Anacar
diacea
e
Lannea_schweinfu
thii
Phylla
nthace
ae
Stercul
iaceae
Bridelia_micrantha
Eupho
rbiace
ae
Chryso
balana
ceae
Synadenium__cup
ulare_
Adansonia_digitat
a
Dombeya__rotund
ifolia
Parinari__curatelli
folia_
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
non
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
65
7
bot
h
58
72
5
1
0
1
0
2
8
bot
h
-6
10
5
0
0
0
0
15
1
0
bot
h
5
25
5
0
0
0
0
20
1
1
bot
h
9
31
5
1
0
0
0
52
1
3
bot
h
39
65
5
1
1
1
0
29
2
3
bot
h
6
52
5
1
0
0
0
4
0
outs
ide
4
4
5
0
1
0
0
16
0
outs
ide
16
16
5
1
0
0
1
39
2
bot
h
37
41
6
0
0
0
0
5
1
2
bot
h
-7
17
6
0
0
0
0
9
2
3
bot
h
-14
32
6
1
1
0
0
20
1
bot
h
19
21
6
1
1
0
1
65
1
bot
h
64
66
6
1
0
1
0
8
2
bot
h
6
10
6
1
0
0
0
14
2
bot
h
12
16
6
0
1
0
1
237
Chryso
balana
ceae
Apiace
ae
Parinari__curatelli
folia
Ochna
ceae
Ochna__natalitia
Eupho
rbiace
ae
Phyll
antha
ceae
Euph
orbiac
eae
Labiat
ae
Euphorbia__ingen
s_
Solan
aceae
Solanum_pandurif
orme
Anaca
rdiace
ae
Sclerocarya__birre
a
Astera
ceae
Brachylaena__disc
olor
Anaca
rdiace
ae
Rhus_lancea
Fabac
eae
Burkea_africana
Tiliac
eae
Grewia__occidenta
lis
Heteromorpha__a
rborescens
Bridelia_cathartica
Pseudolachnostylis
__maprouneaefolia
Clerodendrum__gl
abrum
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
med
icin
al
med
icin
al
med
icin
al
med
icin
al
non
med
icin
al
non
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
14
2
bot
h
12
16
6
1
1
0
1
75
2
bot
h
73
77
6
1
0
0
0
39
5
bot
h
34
44
6
1
0
0
0
43
7
bot
h
36
50
6
1
1
0
0
17
8
both
9
25
6
0
0
1
0
6
1
0
both
-4
16
6
0
1
1
0
50
1
0
both
40
60
6
1
1
1
0
53
1
2
both
41
65
6
1
1
0
0
54
3
6
both
18
90
7
0
1
0
0
2
0
outs
ide
2
2
7
1
0
1
0
7
0
outs
ide
7
7
7
0
0
1
0
24
2
both
22
26
7
0
0
0
0
48
2
both
46
50
7
1
0
0
0
238
Melia
ceae
Ekebergia__capens
is_
Fabace
ae
Elephantorrhiza__
burkii
Eupho
rbiace
ae
Fabace
ae
Euphorbia__tirucal
li_
Eupho
rbiace
ae
Fabace
ae
Croton__gratissim
us
Santal
aceae
Osyris__lanceolata
Vitace
ae
Rhoicissus digitata
Rosac
eae
Prunus__africana
Rutace
ae
Zanthoxylum__Car
pense
Bignon
iaceae
Celtis__africana
Anacar
diacea
e
Ozoroa__engleri_
Apocy
naceae
Tabernaemontana
__elegans_
Polyga
laceae
Securidaca__longi
pedunculata
Araliac
eae
Cussonia__spicata
_
Albizia__versicolor
Schotia
brachypetala
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
30
4
both
26
34
7
0
1
0
0
21
5
bot
h
16
26
7
0
0
0
0
22
8
bot
h
14
30
7
1
0
1
0
25
1
0
bot
h
15
35
7
0
0
0
0
31
1
0
bot
h
21
41
7
0
0
1
0
41
2
8
bot
h
13
69
7
0
1
1
0
35
0
outs
ide
35
35
8
1
1
0
0
6
0
outs
ide
6
6
8
1
0
0
0
20
0
outs
ide
20
20
8
0
1
0
0
54
0
outs
ide
54
54
8
1
0
1
0
9
8
bot
h
1
17
9
0
1
1
1
4
5
bot
h
-1
9
10
1
0
1
0
4
6
bot
h
-2
10
10
1
0
0
0
3
1
bot
h
2
4
10
1
1
0
0
36
1
bot
h
35
37
10
1
1
0
0
239
Cappar
aceae
Capparis__toment
osa
Ebenac Diospyros__mespil
eae
iformis
Rutace
ae
Zanthoxylum__dav
yi
Burser
aceae
Commiphora_negl
ecta
Fabace
ae
Piliostigma__thon
ningii_
Fabac
eae
Acacia__karroo_
Fabac
eae
Senna__petersiana
Ebena
ceae
Euclea_divinorum
Canel
laceae
Warburgia__salut
aris
Fabac
eae
Pterocarpus__ang
olensis_
Clusia
ceae
Garcinia__livingst
onei_
Comb
retace
ae
Aster
aceae
Combretum__moll
e_
Comb
retace
ae
Fabac
eae
Terminalia__serice
a
Spirostachys__afri
cana__Sond
Dichrostachys__ci
nerea_
me
dici
nal
me
dici
nal
me
dici
nal
non
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
18
1
7
bot
h
1
35
10
1
0
0
0
24
3
5
bot
h
-11
59
10
1
1
0
1
16
0
outs
ide
16
16
10
1
1
0
0
7
4
bot
h
3
11
0
0
0
0
0
17
3
bot
h
14
20
11
1
1
0
0
85
3
both
82
88
11
1
1
0
0
25
1
6
both
9
41
11
1
0
0
0
33
3
7
both
-4
70
11
1
1
0
0
10
1
both
9
11
12
0
1
1
0
36
7
both
29
43
12
1
1
0
0
5
8
both
-3
13
12
1
1
1
1
71
6
both
65
77
13
0
0
0
0
34
2
0
both
14
54
13
0
1
0
0
59
3
3
both
26
92
13
0
1
1
0
68
3
3
both
35
101
13
0
0
0
0
240
Verbe
nacea
e
Tiliac
eae
Lippia_javanica
Sapot
aceae
Elaeodendron__tra
nsvaalense
Ebena
ceae
Teclea__natalensis
Burse
raceae
Commiphora__afri
cana
Fabac
eae
Albizia__adianthif
olia_
Fabac
eae
Elephantorrhiza__
elephantina_
Anno
nacea
e
Fabac
eae
Annona__senegale
nsis
Trichilia__emetica
_
Peltophorum__afri
canum_
me
dici
nal
me
dici
nal
med
icin
al
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
me
dici
nal
57
4
both
53
61
15
1
0
1
0
20
8
both
12
28
15
1
1
0
0
24
9
both
15
33
15
1
1
0
0
62
9
both
53
71
15
1
0
1
0
15
1
5
both
0
30
15
0
0
0
0
2
2
both
0
4
16
0
1
1
0
41
4
both
37
45
17
0
0
0
0
28
9
both
19
37
21
1
1
0
1
69
3
5
both
34
104
22
1
1
0
0
241
Isidore Muleba