Hindawi Publishing Corporation International Journal of Forestry Research Volume 2016, Article ID 7593681, 12 pages http://dx.doi.org/10.1155/2016/7593681 Research Article Tree Species Diversity, Richness, and Similarity in Intact and Degraded Forest in the Tropical Rainforest of the Congo Basin: Case of the Forest of Likouala in the Republic of Congo Suspense Averti Ifo,1 Jean-Marie Moutsambote,2 Félix Koubouana,2 Joseph Yoka,3 Saint Fédriche Ndzai,2 Leslie Nucia Orcellie Bouetou-Kadilamio,3 Helischa Mampouya,2 Charlotte Jourdain,4 Yannick Bocko,3 Alima Brigitte Mantota,2 Mackline Mbemba,2 Dulsaint Mouanga-Sokath,2 Roland Odende,2 Lenguiya Romarick Mondzali,2 Yeto Emmanuel Mampouya Wenina,2 Brice Chérubins Ouissika,2 and Loumeto Jean Joel3 1 ENS, Département de Sciences et Vie de la terre, Université Marien Ngouabi, BP 69, Brazzaville, Congo ENSAF, Laboratoire d’Ecologie Appliquée Université Marien Ngouabi, BP 69, Brazzaville, Congo 3 Faculté des Sciences, Département de Biologie et Physiologie Végétales, Université Marien Ngouabi, Brazzaville, Congo 4 Via Costantino Beltrami 2, 00154 Roma, Italy 2 Correspondence should be addressed to Suspense Averti Ifo; ifo.suspense@hotmail.fr Received 11 December 2015; Revised 24 April 2016; Accepted 30 May 2016 Academic Editor: Timothy Martin Copyright © 2016 Suspense Averti Ifo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Trees species diversity, richness, and similarity were studied in fifteen plots of the tropical rainforests in the northeast of the Republic of Congo, based on trees inventories conducted on fifteen 0.25 ha plots installed along different types of forests developed on terra firma, seasonally flooded, and on flooded terra. In all of the plots installed, all trees with diameter at breast height, DBH ≥ 5 cm, were measured. The Shannon diversity index, species richness, equitability, and species dominance were computed to see the variation in tree community among plots but also between primary forest and secondary forest. A total of 1611 trees representing 114 species and 35 families were recorded from a total area of 3.75 ha. Euphorbiaceae was the dominant family in the forest with 12 species, followed by Fabaceae-Mimosoideae (10 species) and Phyllanthaceae (6 species) and Guttiferae (6 species). The biodiversity did not vary greatly from plot to plot on the whole of the study area (3.75 ha). The low value of Shannon index was obtained in plot 11 (𝐻󸀠 = 0.75) whereas the highest value was obtained in plot 12 (𝐻󸀠 = 4.46). The values of this index vary from 0.23 to 0.95 in plots P11 and P15, respectively. Results obtained revealed high biodiversity of trees of the forest of Impfondo-Dongou. The information on tree species structure and function can provide baseline information for conservation of the biodiversity of the tropical forest in this area. 1. Introduction Tropical forests are the subject of several studies to better understand the role they could play in sustainable development, climate change, and floristic biodiversity [1, 2]. Tropical forests provide many goods and ecosystem services, such as prevention of soil erosion and preservation of habitats for plants and animals [3]. Globally, 52% of the total forests are in tropical regions and they are known to be the most important areas in terms of biodiversity [2, 4]. This diversity is an indicator that allows appreciating links between the richness and the abundance of individuals’ trees; it reflects the degree of heterogeneity or stability of vegetation [5]. In the Republic of Congo (RoC), according to the definition of the forest, forests cover 69% of the territory [6]. Sustainable management of these forests requires a good knowledge of all the natural forest resource; this knowledge could be reliable only through studies of the forest environment. 2 Vegetation’s studies led to either conducting a physiognomic research of the architectural type or identifying a number of representative reporting vegetation parameters, allowing defining simply, in order to compare it to other vegetation (Lescure, 1985). For the present study, the second approach was used, that of the floristic and structural parameters. Many tropical forests are under great anthropogenic pressure and require management interventions to maintain the overall biodiversity, productivity, and sustainability [7]. Understanding tree composition and structure of forest is a vital instrument in assessing the sustainability of the forest, species conservation, and management of forest ecosystems [8]. Long-term biodiversity conservation depends basically on the knowledge of the structure, species richness, and the ecological characteristics of vegetation. Some studies on the knowledge of the plant resource were conducted in Republic of Congo ([9–14] for the massif of Mayombe, [15]), but these studies remained generally piecemeal and predominantly localized inner protected areas and logging forest concessions. These studies were related to the ethnobotanical aspects and general knowledge of the flora of the Republic of Congo. And most of these studies were done essentially in the south of Republic of Congo and just one in the centre-west of our country. This work will provide more information on the tropical forest of Likouala, RoC. The aims of this research paper are to identify and quantify tree forest species of the tropical rainforest of Likouaka and specific objectives are (i) a floristic analysis of the forest of the axis Impfondo-Dongou, Likouala; (ii) analysis of floristic heterogeneity between interforest plots. The study area is located within the Likouala department, which is of the most important forest regions in Republic of Congo. 2. Material and Methods 2.1. Study Area. The study was carried out within the tropical rainforest of the North of Congo Brazzaville in the department of Likouala (Figure 1). The zone of study covers a total surface of 155274 ha. It lies between 1∘ 27󸀠 52,85󸀠󸀠 and 2∘ 6󸀠 55,76󸀠󸀠 of northern latitude and between 17∘ 52󸀠 35,04󸀠󸀠 and 18∘ 04󸀠 32,65󸀠󸀠 of longitude. The climate of the study area is of equatorial type. Mean rainfall is of 1760 mm y−1 , with a dry season from December to January and a long wet season from March to November (Figure 2). In the Dongou district, the soil cover is of tertiary clay sandy formation and a quaternary alluvial formation to the east. The soils derived from there are impoverished ferrilitic brown-red clay-sand soils on the Western plateau, ferralitic/hydromorphic alluvial soils on alluvial terraces, and waterlogged peat soils in flooded areas. This area has one of the very low densities of human population (0.93 km−2 ) of the Republic of Congo. The forest of Likouala contains a high diversity of trees and plants [16]. In the Dongou district, the forests of the study area are rainforest. The principal vegetation types are partially deciduous dense rainforests of Ulmaceae and Sterculiaceae, swampy flooded forest of Uapaca heudelotii, and forest of Guibourtia demeusei [17]. Tree canopy closure of the forest varies from 93% to 100% International Journal of Forestry Research Table 1: Distribution of number of plots inside each type of forest. Type of forest Plots Number of trees Density (n/ha) G (m2 /ha) DF1 P1 P2 P3 P11 67 73 212 217 268 312 848 868 6.75 9.11 34.24 26.73 P5 P6 P7 P8 P9 P10 P4 P12 P13 P14 115 103 64 70 36 115 133 132 162 121 460 412 256 280 144 460 532 528 648 484 23.06 25.88 36.37 30.80 16.01 29.20 36,38 29.51 35.54 21.60 P15 51 204 36.52 PF2 AF3 1: degraded forest; 2: primary forest; 3: agroforestry. while the tree height varies from 30 m to above 45 m (own data). 2.2. Data Collection. The tree sampling for the data collection was performed in 15 plots of 50 m × 50 m each placed in different forest strata of the study area: primary forest, secondary forest, and a mosaic of primary and secondary forest (Figure 3). Table 1 indicates the distribution of plots on the extent of the zone of study. The plot of intact forests and degraded forests inventoried was selected after image processing Landsat (OLI 8) of the study area. Coordinates GPS of the zones chosen on the satellite images were recorded in a GPS and on the ground we used the function Goto to go towards the points selected for the installation of the plot of inventories. The ground data allowed validating the classification of different type of forest in primary forest and secondary or degraded forest but also of the forest agro plot. Four plots fell into the zone from forest degraded, ten plots fell in the primary forest, and 1 plot fell into an agro drill forest. GPS points of all plots were recorded, and inside each plot all living trees with diameter at breast height (DBH) ≥ 5 cm were recorded by species using latest botanical classification. All tree species were assigned to families and relative diversity (number of species in a family) was obtained for tree species diversity classification. 2.3. Measuring Biodiversity. We apply the Shannon diversity index (𝐻󸀠 ) as a measure of species abundance and richness to quantify diversity of the woody species. This index takes both species abundance and species richness into account: 𝑠 𝐻󸀠 = −∑𝑝𝑖 ln 𝑝𝑖 , 𝑖=1 (1) International Journal of Forestry Research 3 Zone d’étude 0 (km) 50 100 150 200 250 Départment de la Likouala Autres départments 18∘ 0󳰀 0󳰀󳰀 E 18∘ 10󳰀 0󳰀󳰀 E N 2∘ 0󳰀 0󳰀󳰀 N 2∘ 0󳰀 0󳰀󳰀 N 1∘ 50󳰀 0󳰀󳰀 N 1∘ 50󳰀 0󳰀󳰀 N 1∘ 40󳰀 0󳰀󳰀 N 1∘ 40󳰀 0󳰀󳰀 N 1∘ 30󳰀 0󳰀󳰀 N 1∘ 30󳰀 0󳰀󳰀 N 18∘ 0󳰀 0󳰀󳰀 E 0 18∘ 10󳰀 0󳰀󳰀 E 5 10 15 (km) Villages District Chef lieu de département Zone d’étude Plan d’eau Réseau routier Figure 1: Localization of the department of Likouala, Congo Brazzaville. where 𝑠 equals the number of species and 𝑝𝑖 equals the ratio of individuals of species 𝑖 divided by all individuals 𝑁 of all species. The Shannon diversity index ranges typically from 1.5 to 3.5 and rarely reaches 4.5 [18]. The variance of 𝐻󸀠 is calculated by var 𝐻󸀠 = ∑ 𝑝𝑖 (ln 𝑝𝑖 ) − (∑ 𝑝𝑖 ln 𝑝𝑖 ) 𝑠−1 + 𝑁 2𝑁2 2 2 (2) International Journal of Forestry Research December October November August September July June May April March February and a 𝑡-statistic to test the significant differences between two plots or samples as Rainfall (mm) 220 200 180 160 140 120 100 80 60 40 20 0 100 90 80 70 60 50 40 30 20 10 0 January Temperature (∘ C) 4 Rainfall (mm) Temperature (∘ C) Figure 2: Ombrothermic diagram of Likouala (data from 1932 to 2015), ANAC Congo. 𝑡= 𝐻1󸀠 − 𝐻2󸀠 √var 𝐻1󸀠 + var 𝐻2󸀠 d.f. = (var 𝐻1󸀠 + var 𝐻2󸀠 ) 2 (var 𝐻1󸀠 ) /𝑁1 + (var 𝐻2󸀠 ) /𝑁2 2 N 𝑖=1 230000 Dongou 220000 220000 Bondomaka Moungouma 210000 210000 Bonzale Kanana 200000 200000 Nkoko Bobala Bokata 190000 190000 Mozaka Djemba Moyitou 180000 PK13 170000 180000 Impfondo Kombola 170000 865000 860000 855000 850000 845000 840000 830000 835000 825000 820000 Ngounda 1:260 633 0 6 (km) 12 Villages District Routes Limite de la zone Occupation du sol Forêt primaire Forêt dégradée Cultures et jachères Plantation Savane Habitat Bande sable Plan d’eau Figure 3: Cartography of land use change inside study’s area. 2 , (4) where 𝑁1 and 𝑁2 are the number of individuals in samples 1 and 2, respectively [19]. We have also considered the Simpson index (𝐷), a measure of species dominance, and the Shannon diversity index (𝐸), a measure of evenness of spread. The Simpson index is defined as 𝐷 = ∑( 865000 860000 855000 850000 845000 840000 835000 830000 825000 820000 Motaba (3) where 𝐻󸀠 is the Shannon diversity index of sample 𝑗. Degrees of freedom for this test are equal to 𝑠 230000 , 𝑛𝑖 (𝑛𝑖 − 1) ), 𝑁 (𝑁 − 1) (5) where 𝑛𝑖 is the number of individuals in the 𝑖th species and 𝑁 equals the total number of individuals. As biodiversity increases, the Simpson index decreases. Therefore to get a clear picture of species dominance, we used 𝐷󸀠 = 1 − 𝐷. The Shannon-Wiener index is defined as 𝐸= − ∑𝑠𝑖=1 𝑝𝑖 ln 𝑝𝑖 𝐻󸀠 = . 𝐻max ln 𝑠 (6) 󸀠 is the natural logarithm of the total number of species. A 𝐻max value for evenness approaching zero reflects large differences in abundance of species, whereas an evenness of one means all species are equally abundant: Margalef ’ Index (𝑑) = (𝑆 − 1) , ln (𝑁) (7) where 𝑆 is the total number of species, “𝑁” is the number of individuals, and “ln” is the natural logarithm. 2.4. Similarity. The Jaccard index was used to calculate similarities of species between the forest types in different forest fragments. These coefficients are used to measure the association between samples. The similarity of two samples (floristic sample) is based on the presence or absence of certain species in the two samples [20]. To study the similarity of our different floristic samples, we used two binary factors excluding the double zeros, that is, the coefficient of Sorensen (𝐾) and the coefficient of Jaccard (𝑆). The Sorensen coefficient provides a twice higher weight to double presence; we can consider the presence of a more informative than this absence [20]: 𝑆 (%) = 𝐾 (%) = (𝑎 × 100) (𝑎 + 𝑏 + 𝑐) (2𝑎 × 100) (2𝑎 + 𝑏 + 𝑐) (8) International Journal of Forestry Research 5 Table 2: Floristic lists and their frequencies of the study area. Family Scientific name Number of species Number of trees Caloncoba welwitschii (Oliv.) Gilg. 1 9 Pseudospondias microcarpa (A. Rich.) Engl. 2 14 2 19 Alstonia boonei De Wild. 1 1 Aptandraceae Ongokea gore (Hua) Pierre 1 1 Bignoniaceae Markhamia tomentosa (Benth.) K. 1 1 Burseraceae Dacryodes pubescens (Verm.) Lam. 1 3 Celtis adolfi-friderici Engl. 1 12 4 32 Terminalia superba Engl. et Diels. 1 3 Diospyros crassiflora Hiern 2 47 12 239 5 116 4 123 10 58 Achariaceae Anacardiaceae Trichoscypha acuminata Engl. Annonaceae Anonidium mannii (Oliv.) Engl. & Diels Monodora angolensis Welw. Apocynaceae Cannabaceae Parinari congensis F. Didr. Chrysobalanaceae Parinari congolana T. Durand et H. Durand Parinari excelsa Sabine Maranthes glabra (Oliv.) Combretaceae Ebenaceae Diospyros ituriensis (Gùrke) R. Let et F. White Cleistanthus itsogohensis Pellegr. Croton haumanianus J. Léonard Dichostemma glaucescens Pierre Grossera macrantha Pax Macaranga barteri Mull.-Arg. Euphorbiaceae Macaranga monandra Mull.-Arg. Macaranga schweinfurthii Pax Macaranga spinosa Mull.-Arg. Plagiostyles africana (Mull.-Arg.) Prain Ricinodendron heudelotii (Baill.) Pierre ex Pax Sapium ellipticum (Hochst.) Pax Tetrorchidium didymostemom (Baill.) Pax & K. Hoffm. Copaifera salikounda Heckel Daniellia pynaertii De Wild. Fabaceae-Caesalpinioideae Dialum pachyphyllum Harms Guibourtia demeusei (Harms) Léon. Swartzia Bobgunnia fistuloides (Harms) G.H Kirkpr. Angylocalyx pynaertii De Wild. Fabaceae-Faboideae Baphia dewevrei De Wild. Millettia sanagana Harms Pterocarpus soyauxii Taub. Albizia ferruginea (Guill. & Perr.) Benth. Albizia laurentii De Wild. Cathormion rhombifolium (Benth.) Hutch. & Dandy (syn: Albizia rhombifolia Benth.) Fabaceae-Mimosoideae Albizia zygia (DC) J. F. Macbr. Newtonia devredii G. C. C. Gilbert 6 International Journal of Forestry Research Table 2: Continued. Family Number of species Number of trees 6 55 3 16 Vitex pachyphylla Bak. 1 8 Persea americana L. 1 1 Petersianthus macrocarpus (P. Beauv.) Liben. 2 63 Cola nitida (Vent.) Schott & Endl. 1 2 Duboscia macrocarpa Brocq. 1 8 5 46 5 17 3 226 2 14 3 52 Panda oleosa Pierre 1 6 Barteria fistulosa Mast. 1 1 Drypetes pellegrini Léandri 2 7 Scientific name Parkia filicoidea Welw. ex Oliv. Parkia bicolor A. Chev. Pentaclethra macrophylla Benth. Piptadeniastrum africanum (Hook. F.) Bren. Tetrapleura tetraptera (Schum. & Thonn.) Taub. Allanblackia floribunda Oliv. Garcinia punctata Oliv. Guttifereae Garcinia ovalifolia Oliv. Mammea africana Sabine Symphonia globulifera L. f. Garcinia smeathmannii Oliv. Irvingia excelsa Irvingiaceae Irvingia grandifolia (Engl.) Engl. Klainedoxa gabonensis Pierre ex Engl. Lamiaceae-Viticoideae Lauraceae Lecythidaceae Brazzeia congensis Baill. Malvaceae-Sterculioideae Malvaceae-Tilioideae Carapa procera var. palustre DC Carapa procera var. procera DC Meliaceae Entandrophragma cylindricum (Sprague) Sprague Trichilia monadelpha (Thonn.) J. J. De Wild. Trichilia tessmannii Harms Antiaris toxicaria var. welwitschii Lesch. Ficus exasperata Vahl. Moraceae Ficus vogeliana (Miq.) Miq. Milicia excelsa (Welw.) C. C. Berg Trilepisium madagascariense DC. Coelocaryon preussii Warb. Myristicaceae Pycnanthus angolensis (Welv.) Exell Staudtia kamerounensis Warb. var. gabonensis Fouilloy Ochnaceae Lophira alata Banks ex Gaertn. Rhabdophyllum welwitschii Van Tiegh. Heisteria parvifolia Smith Olacaceae Strombosia grandifolia Hoof. F. Strombosia pustulata Oliv. Pandaceae Passifloraceae Putranjivaceae Drypetes leonensis (Pax) Pax et K. Hoffm. International Journal of Forestry Research 7 Table 2: Continued. Family Number of species Number of trees 6 37 5 44 1 1 4 55 4 18 Thomandersia hensii De Wild. 1 21 Musanga cecropioides R. Br. 2 235 114 1611 Scientific name Cleistanthus mildbraedii Jabl. Hymenocardia ripicola J. Léonard Phyllanthaceae Hymenocardia ulmoides Oliv. Maesobotrya dusenii (Pax) Hutch. Uapaca guineensis Mull.-Arg. Uapaca heudelotii Baill. Aidia micrantha (K. Schum.) F. White Colleactina papalis N. Hallé Massularia acuminata (G. Don) Bullock ex Hoyle Rubiaceae Morelia senegalensis A. Rich. Morinda pynaertii Benth. Oxyanthus schumannianus De Wild. et Th. Dur Psydrax subcordata DC Psydrax arnoldiana (De Wild.) Rutaceae Zanthoxylum heitzii (Aubrév. & Pellegr.) P. G. Waterman Blighia welwitschii (Hiern) Radlk. Sapindaceae Eriocoelum microspermum Radlk. Lecaniodiscus cupanioides Planch. ex Benth. Pancovia pedicellaris Radlk. & Gilg Chrysophyllum beguei Aubrév. Synsepalum brevipes (Baker) TD Penn Sapotaceae Tridesmostemom omphalocarpoides Engl. Manilkara sp. Manilkara fouilloyana Aubr. et Pellegr. Thomandersiaceae Urticaceae Myrianthus arboreus P. Beauv. Total with 𝑎 = number of common presences for both floristic samples, 𝑏 = number of presences in the first floristic sample, 𝑐 = number of presences in the second floristic sample, and 𝑑 = number of species absent in both floristic samples. According to L. Legendre and P. Legendre [20], the Sorensen coefficient is fully compared with the Jaccard coefficient; that is, if the similarity of a pair of objects computed by the Jaccard coefficient is higher than the similarity of another pair of objects, it will also be higher if we use the coefficient of Sorensen for the calculation of similarity. 3. Results 3.1. Floristic Composition and Species Richness. A total of 1611 trees representing 114 species and 35 families were identified from the total area (3.75 ha). Euphorbiaceae was the dominant family in the forest with 12 species, followed by Fabaceae Mimosoideae with 10 species. In terms of the number of trees individuals per family, Euphorbiaceae was the dominant in the whole forest with 239 trees, followed by Urticaceae with 235 trees (Table 2). In terms of characterization of forest type, this inventory allowed distinguishing several forest types like Lophira alata, Uapaca heudelotii, Guibourtia demeusei, and Celtis adolfifriderici. Inventories have revealed the existence of three vertical strata, whose upper stratum is dominated by species referred to above. The biodiversity did not vary greatly from plot to plot on the whole of the study area (3.75 ha). A low Shannon diversity index value was obtained in plot 11 (𝐻󸀠 = 0.75) whereas the highest value was obtained in plot 12 (𝐻󸀠 = 4.46). A statistical analysis made by launched ANOVA revealed that plot 11 was significantly different to the other plots (𝛼 = 0.05). A great difference was also noted in biodiversity between secondary plots and primary plots (Table 3). The evenness index was calculated. The values varied from 0.23 in plot P11 to 0.95 in plot P15. The evenness index 𝐸 was calculated for each plot. The value of equitability varied from 0 to 1. It is equal to 1 when all 8 International Journal of Forestry Research Table 3: Biodiversity values by biodiversities index and static parameters. Total individual S Shannon diversity index (𝐻) Fisher’s 𝛼 Simpson index P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 Degraded forest Degraded forest Degraded forest Primary forest Primary forest Primary forest Primary forest Primary forest Primary forest Primary forest Degraded forest Primary forest Primary forest Primary forest Agroforestry 67 79 212 132 111 102 52 61 34 106 217 126 153 109 47 26 22 38 26 24 29 15 9 12 27 10 33 31 31 20 4.33 3.54 4.13 3.57 3.97 4.14 3.36 2.46 2.93 3.94 0.75 4.47 3.89 4.38 4.12 15.76 13.99 23.23 14.92 11.3 17.39 8.39 3.81 8.13 16.32 5.85 17.76 19.03 16.54 11.37 0.05 0.14 0.08 0.14 0.08 0.07 0.11 0.22 0.16 0.09 0.05 0.05 0.1 0.06 0.04 1.2 5 1 4 0.8 3 0.6 2 0.4 1 0.2 0 0 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 6 Evenness index Type of forest Shannon index Plots 50 45 40 35 30 25 20 15 10 5 0 Evenness index = 󸀠 𝐻max 3.06 2.64 2.62 2.52 2.88 2.83 2.86 2.58 2.72 2.76 0.75 2.94 2.61 2.93 3.17 Variances (𝐻) Ecartype 0.28 0.18 0.09 0.11 0.15 0.18 0.23 0.11 0.28 0.16 0.04 0.16 0.11 0.18 0.36 0.53 0.43 0.3 0.34 0.39 0.42 0.48 0.33 0.53 0.4 0.2 0.41 0.33 0.43 0.6 44.33 37.62 29.33 28.48 23.17 17.18 AF-FP AF-FS FS-FP Plots Shannon’s index (H) Evenness index Figure 4: Shannon diversity index and evenness index trends in all the study areas. the species have same abundance and tend towards 0 when the near total of flora is concentrated on only one species. The values of this index varied from 0.23 to 0.95 in plots P11 and P15, respectively (Figure 4). The value of plot 11 confirms well conducted survey in the plot which is dominated by one species, Musanga cecropioides. The 𝐸 value obtained in plot P11 is the one with a value inferior to 0.5 out of the entire results. Two plots have value of 𝐸 superior to 0.9 (plots P1 and P15). Twelve plots have a value of 𝐸 varying between 0.7 and 0.89. 3.2. Biodiversities Indexes and Other Parameters. Other analyses of the biodiversity made by applying the other indices such as the index of Fisher 𝛼 revealed interesting information. Whereas with the Shannon diversity index, it is in plot 11 that we noted the weakest biodiversity, the application of the index Fisher 𝛼 (Table 3) showed that the low value of the Jaccard index (%) Sorensen index (%) Figure 5: Similarity index between two types of forest. AF = agroforestry, FP = primary forest, and FS = secondary forest. biodiversity was obtained in plot 08 which is a primary forest plot whereas the strongest value of 𝐹 is observed in P3 plot, which is a mosaic of secondary and primary forest. Plot 11 (monodominant plot of Musanga cecropioides) does not have the low value of the biodiversity like Shannon diversity index revealed. The species richness of 114 species was observed in 3.75 ha of the Likouala Forest Department. Musanga cecropioides was the most dominant with 222 trees censured followed by Staudtia kamerounensis var. gabonensis with 117 trees. 3.3. Similarity: Sorensen (𝐾) and Jaccard (𝑆) Index. Species similarities between the forest types were studied between primary forest and secondary forest (FS-FP), primary forest and agroforestry land (AF-FP), and agroforestry land and secondary forest (plot 15). We have noted that the lowest Jaccard index value was obtained between AF-FP (Figure 5) (17.18%). The highest value was noted between FS-FP. International Journal of Forestry Research 9 Table 4: The characteristics of ecological factors in some forests of Republic of Congo. Name of forest Forest of Impfondo-Dongou Forest of Mayombe Forest of centre-west of Congo Forests of the littoral Rainfall (mm) 1800–2000 1600 2132.6 1500 The indices of diversity enabled us to conclude that the studied zones are rich in cash. Are various studied forests similar from the floristic composition point of view? The values of coefficient of similarity vary from 17.18% to 28.48% for the index of Jaccard and 29.33% to 44.33% for the index of Sorensen. 4. Discussion The analysis of the tree flora of the study area showed that the families of Euphorbiaceae (10.53%) are the most represented, followed by the Fabaceae-Mimosoideae (8.77%), Rubiaceae (7.89%), and the Guttiferae (6.14%). Indeed, the presence of the Euphorbiaceae and Rubiaceae generally represented by species of wood is a character common to all tropical rainforests as noted by Reynal-Roques [29]. However the abundance of the Fabaceae-Mimosoideae and Guttiferae is proof of the old age or maturity of the inventoried forest [11]. From the point of view of physiognomy of forest areas studied, the results show that these are the Euphorbiaceae (14.84%) which are abundant in terms of number of trees from beneath wood and stratum average, followed by the Urticaceae (14.59%), the Myristicaceae (14.03%) of the Fabaceae-Faboideae (7.64%), and Fabaceae-Mimosoideae (7.20%). The abundance of the Urticaceae is explained by the presence of quasi-monospecific stands to Musanga cecropioides in degraded forests. However the abundance of the Myristicaceae and Fabaceae is a specific character of the forests studied axis ImpfondoDongou. Indeed, the results obtained in our study are totally different from those obtained by Kimpouni [22] in Congolese coastal forests, Koubouana et al. [30] in the forest of Western Centre at Mbomo and Kelle. Indeed the work of Kimpouni [22] performed in the littoral showed an abundance of the Fabaceae-Caesalpinioideae, followed by the Rubiaceae and Euphorbiaceae. Those of Koubouana et al. (in press) in the centre-west of the Congo showed an abundance of the Fabaceae-Caesalpinioideae (18.05%), followed by the Meliaceae (7.52%), Fabaceae-Mimosoideae (6.02%), Euphorbiaceae (5.26%), Annonaceae (4.51%), and the Myristicaceae (3.76%). In the study conducted at the Mayombe in the South of Congo by Koubouana et al. [21], the results obtained show an abundance of family Burseraceae (19.17%) followed by the Fabaceae-Caesalpinioideae (16.09%), Myristicaceae (13.18%), Annonaceae (9.49%), Euphorbiaceae (8.32%), and Fabaceae-Mimosoideae (7.32%). This variation of the floristic composition of the different forests studied is explained by the diversity of geological substrate and the diversity of climate (Table 4). Table 5 showed the characteristics of ecological factors in the forests studied. Authors Our study Koubouana et al. [21] Our own data Kimpouni [22] Length of dry season 2 4 2 4 It is important to note that Brazzaville is in the south of the Republic of Congo and Mbomo-Kelle’s locality is in the northwest of Republic of Congo. In comparison with these two localities, our study area is in the extreme northeast. Each of the study areas has a local climatic condition (Table 4). Table 3 shows the values for the assessment of the biodiversity of trees surveyed in 15 parcels that were the subject of this study on floristic biodiversity on ≥10 cm DBH trees. In this study we wanted to focus our attention on the biodiversity indices to assess the level of biodiversity across the study area, but also the microvariations that would exist between the plots of the study area. Moreover, in the scope of this study, we tested the role that vegetation indexes might play in the evaluation of forest degradation between primary and secondary forests. Considering the Shannon diversity index, our study showed that plot 15 has a lower Shannon index of 1, while two plots have clues to Shannon between 2 and 3. The rest of the plots with higher values have 3. High species richness is a hallmark of many tropical forests (Gentry et al. 2010). Our study revealed the existence of variability of biodiversity in the study area. According to Orth and Colette [31] the Shannon diversity index has strong values for species with recoveries of same importance and it takes low values, when some species have strong recoveries. Low biological diversity noted in plot 11 (𝐻󸀠 = 0.75) could be explained by the fact that it is dominated by a single species Musanga cecropioides. This species contributes nearly 90% of the total number of trees in the plot. In two plots with the highest values, the plots contain more than 30 species of trees with at least two species of codominant trees, but with lower contributions. In parcel 12 (𝐻󸀠 = 4.47), Angylocalyx pynaertii De Wild and Plagiostyles africana species each have a 13% contribution. In these same plots the other two species following in terms of specific contribution are Grossera macrantha and Strombosia grandifolia with, respectively, 7% and 6% of a total of 126 species inventoried in this plot. As shown in Table 1, the application of the other indices of biodiversity gives a different result. The Pioulou 󸀠 󸀠 ) indicates that plot 15 (𝐻max = 3.17) biodiversity index (𝐻max 󸀠 has the highest biodiversity followed by plot 1 (𝐻max = 3.06) 󸀠 and plot 12 (𝐻max = 2.94). Several causes could explain variations in the degree of biodiversity between the plots of the study area: soil type, rainfall trends, anthropogenic action, land use change, and so forth. The Shannon diversity index values obtained in this study are lower than those obtained in other studies both in the Republic of Congo and in other tropical forests in the Congo basin compared to other tropical countries. For 10 Table 5: The characteristics of ecological factors in some forests of Republic of Congo. Type of vegetation Forest Minimum tree DBH Study area (ha) DBH ≤ 10 cm 1.5 DBH ≥ 20 cm Shrub savannah 35 400 FabaceaeCaesalpinioideae DBH ≥ 20 cm Forest DBH ≥ 10 cm 88.5 Forest DBH ≥ 10 cm (monodominant Aucoumea klaineana) Forest Southwest of the Republic of Congo Plateaux Teke, Republic of Congo Northwest of Republic of Congo Plateau des Cataractes, Republic of Congo Rainfall mean (mm/year) 1200–1500 Kimpouni et al. [23] 3.75 41 1600–2100 2.16 15 16 3075 25 Mampouya Wenina [24] 1900 5.3 31 107 11012 133 Koubouana et al. (in press) 42 116 153 Kimpouni [22] 71 Kimpouni et al. [25] 93 Nangendo et al. [26] 1789 92 Premavani et al. [27] 808 72 Aigbe and Omokhua [28] 1400– 1600 mm Youbi 1200 Uganda, Youbi, Republic of Congo (southwest) 1397– 1500 mm 0.72 DBH ≥ 15 cm 1 1300 1.96 2500–3000 5076 Authors 1600 (DBH) ≥ 10 cm DBH ≥ 10 cm ShannonNumber Number of Number of Number of Wiener index of families genera trees (bit) species 1.9 ± 0.5 47 120 153 1186 4.02 3.55, 3.47, 3.48, and 3.32 3.795 26 40 73 Koubouana et al. [21] International Journal of Forestry Research Mosaics of natural forest and grassland Countries International Journal of Forestry Research 11 instance, in the forest of centre-west of Republic of Congo in Mbomo-Kelle (Republic of Congo), Shannon diversity index varies from 5.91 to 5.95 in bloc 4 and bloc 9, respectively (Koubouana et al. in press). In the southwest of the Republic of Congo, studies were conducted by Kimpouni et al. [23] and Koubouana et al. [21] and revealed different 𝐻󸀠 values. Kimpouni et al. [23] in a degraded forest in Brazzaville obtained for woody species a Shannon diversity index of 1.9 bits. But in the tropical forest of southwest of the Republic of Congo, Koubouana et al. (in press) noted an old secondary forest that the Shannon diversity index was about 3.08. Regarding heterogeneity, many authors think that the structural heterogeneity of the forests and their high species richness are often interpreted in terms of forest dynamics and relationship with the resulting phenomena of succession [5, 32]. In this work, we have mainly focused on the study of the biodiversity of trees to make a comparison between the degraded forest areas and nondegraded forest areas. Several factors could explain the variations of biodiversity in our study: the topography of the area [33, 34] or edaphic factors [35, 36] to explain the issue of floral heterogeneity of tropical forests. In our study area, three forest types were identified: flooded forests, solid ground forest, and partially flooded forest. In the context of this work we have studied the differences that exist between forest types through the Jaccard and of Sorensen similarity indexes. Moreover, (𝐾) and Jaccard (𝑆) index give a very good idea of the presence or absence of species in the different transects of the inventory. The range of this coefficient is between 0 and 1. Interpretation of the CSJ values is as follows: 1: both survey sites have only common species; 0: both survey sites have only singular species; 1/2: the two survey sites have as many common species as the sum of singular species at each survey site; [0, 1/2]: the similarity in terms of species diversity between both survey sites is rather low; [1/2.0]: the similarity in terms of species diversity between both survey sites is rather high. In our case, it ranges from 17.18 to 23.48%, taking into account the three combinations (AF-FP, AF-FS, and FSFP). This means the similarity in terms of species diversity between both survey sites is rather low. The results showed that there is a high tree biodiversity in our study area. The values of similarity index are lower than 50%, which enables us to conclude that there is obviously a difference in point of floristic composition between the primary forests and the secondary forests, thus confirming the floristic data that we presented above. of goods and services and has only limited biodiversity. Biological diversity in a degraded forest includes many nontree components which can dominate the understory vegetation cover (CBD (2005; 2001). To assess the level of forest degradation, a maximum biodiversity index has been applied and presents different values between the secondary and primary forest. These forests are characterized by a very high biodiversity, especially in the case of secondary forests of Macaranga spinosa or Macaranga barteri. In the case of plots P1 and P2 the objective of this study is to identify settings that allow assessing forest degradation. 4.1. Evaluation of Forest Degradation through the Biodiversity Indexes. Degradation is considered to be a temporal process. There is however a consensual definition that is accepted by the various stakeholders, which is as follows: forest degradation is the reduction of the capacity of the forest to provide goods and services. In the context of REDD+, forest degradation can be defined as the partial loss of biomass due to logging or other causes of removal of wood from biomass [37]. A degraded forest is a secondary forest that has lost, as a result of human activities, the structure, function, composition, or productivity of species normally associated with a natural forest. Thus, a degraded forest offers a supply [3] M. Anbarashan and N. Parthasarathy, “Tree diversity of tropical dry evergreen forests dominated by single or mixed species on the Coromandel coast of India,” Tropical Ecology, vol. 54, no. 2, pp. 179–190, 2013. 5. Conclusion The study of the biodiversity of the Likouala forests and the Impfondo-Dongou axis revealed a high floral biodiversity of trees considering a diameter of 5 cm at DBH 1.30 m. Tree biodiversity is very important in primary forests. In secondary forests, the biodiversity varies in line with the secondary forest type: secondary forest of Macaranga spinosa or secondary forest of Musanga cecropioides. Moreover, biodiversity varies according to the nature of the substrate: forest on dry land, forest in partially flooded areas, and flooded forest. Competing Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Acknowledgments The authors are thankful to GEOFORAFRI for funding the project. The authors thank Benoit Mertens for kind support during the project. References [1] S. L. Lewis, G. Lopez-Gonzalez, B. 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