Literature DB >> 29558963

Traditional ecological knowledge-based assessment of threatened woody species and their potential substitutes in the Atakora mountain chain, a threatened hotspot of biodiversity in Northwestern Benin, West Africa.

Pierre Onodje Agbani1, Konoutan Médard Kafoutchoni2, Kolawolé Valère Salako3, Rodrigue Castro Gbedomon2, Ahuéfa Mauricel Kégbé2, Hahn Karen4, Brice Sinsin1.   

Abstract

BACKGROUND: Atakora mountains in Benin are a unique but fragile ecosystem, harboring many endemic plant species. The ecosystem is undergoing degradation, and the woody vegetation is dramatically declining due to high anthropogenic actions and recurrent drought. This study aimed to (i) assess the diversity of threatened woody species and (ii) identify their potential substitutes in the three regions of the Atakora mountains namely East Atakora, Central Atakora, and West Atakora.
METHODS: The data were collected during expeditions on surveyed localities through semi-structured individual interviews. Free-listing was used to record threatened woody species and which were important and why. Alpha-diversity indices were used to assess diversity of threatened and important threatened woody species. A correspondence analysis was used to determine the reason supporting their importance. Differences in species composition were assessed using analysis of similarities. A number of potential substitutes were compared among species using generalized linear models.
RESULTS: A total of 117 woody species (37 families and 92 genera) were identified. The most prominent families were Fabaceae (19.66%), Combretaceae (12.82%), and Moraceae (10.26%), and the richest genera were Ficus (10 species), Combretum (6), and Terminalia (5). Most threatened species differed across regions (East Atakora, Central Atakora, and West Atakora) and included Afzelia africana, Anogeissus leiocarpa, Borassus aethiopum, Diospyros mespiliformis, Khaya senegalensis, Milicia excelsa, and Pterocarpus erinaceus. Most socio-economically important species (K. senegalensis, Parkia biglobosa, Vitellaria paradoxa, and V. doniana) were used mainly for food, timber, and fuelwood purposes. Old and adult people, and Dendi and Fulfulde sociolinguistic groups had greater knowledge of threatened woody plant species. High intercultural differentiations in species composition were detected between Bariba-Berba and Bariba-Natimba. Knowledge of substitutes also differed across regions with P. erinaceus, Isoberlinia spp., and A. africana being the most cited substitutes.
CONCLUSION: Basic data was provided here to inform decision and guide efficient management of woody resources. There was evidence that immediate conservation measures are required for some high economic value woody taxa which were critically threatened. Ex-situ conservation of these species while promoting their integration into agroforestry-based systems were recommended. Besides, community-based management programs and community-led initiatives involving knowledgeable people from different horizons will lead to a long-lasting conservation of these threatened resources.

Entities:  

Keywords:  ANOSIM; Atakora mountain chain; Beta-diversity; Forest resources; Socio-cultural factors

Mesh:

Year:  2018        PMID: 29558963      PMCID: PMC5859633          DOI: 10.1186/s13002-018-0219-6

Source DB:  PubMed          Journal:  J Ethnobiol Ethnomed        ISSN: 1746-4269            Impact factor:   2.733


Background

Forests represent major intergenerational reservoirs of resources sustaining local economy, enhancing food security, providing non-timber forest products and wood, conserving biodiversity, and offering multiple ecosystem services [1-4]. However, forest covers are dramatically declining in West Africa [5, 6], especially in Benin [7, 8], critically threatening the species they host and compromising ecosystem services they provide [9]. Located in the so-called “Dahomey Gap” which is a low-rainfall dry corridor separating Guinean rainforest blocks [10], the Republic of Benin does not have as much forest zones compared to its neighboring countries such as Nigeria, Ghana, and Ivory Coast. Nevertheless, more than 22% of forest areas and 30% of savannah have been lost in Benin from 1995 to 2006 [8] and according to FAO [11], it was 50,000 ha. year−1 of forest cover that has been destroyed in the period from 2000 to 2010. A study on land use and land cover change in Central and Northern Benin revealed that land clearance for agriculture, wood extraction, and demographic growth are major causes of forest depletion [12]. Also, illegal settlements and agricultural encroachment on the protected forests [13] and expansion of illegal timber trade are considered as additional threats to the loss of forest resources. Yet, the most serious cause of the extinction of many woody species in the wild in Benin is undoubtedly the selective logging to which they may be subjected [2, 7, 14]. Atakora mountain chain is a region of great ecological and species diversity in the country [15]. It harbors an outstanding flora including three endemic genera (Vitellaria, Pseudocedrela, and Haematostaphis) to the Sudanian zones, two plant species endemics to Benin (Cyperus beninensis (Samain, Reynders & Goetgh) Huygh and Ipomoea beninensis Akoègninou, Lisowski & Sinsin), and Thunbergia atacorensis Akoègninou & Lisowski, an endangered species endemic to the inselbergs of Benin and Togo [16, 17]. Unfortunately, over-logging, exploitation of granitic rock plates, and agricultural exploitation of the mountain chain lead to the degradation of plant communities and threat the integrity of this ecosystem. Furthermore, the study of plant community dynamics across phytogeographical districts revealed a highly regressive ecosystem in the Atakora chain [12]. Thereof, particular attention should be devoted to this area and conservation efforts should target multiple taxa. The traditional ecological knowledge (TEK) is a valuable component in the sustainable management of resources and conservation of threatened or rare species and biodiversity, as well as protected areas [18-20]. Indeed, it is well established that the knowledge of local people, developed upon the experiences acquired over generations, can complement scientific ecological knowledge for sustainable management of forest ecosystems [21, 22]. Actually, based on ecological knowledge of local people on the decline or the conservation status of different species, many authors have proposed forest management strategies [23-25] and developed methods for using that knowledge efficiently [26]. As a prerequisite for conservation strategies of the Atakora chain, the major aim of this study was to provide the background for efficient management of the threatened woody species in the Atakora mountain chain region in Benin. Specifically, the study aims to (i) assess the diversity of threatened woody species (TWS) based on locals’ traditional ecological knowledge (TEK), (ii) assess the relationship of TEK with socio-demographic factors of informants (age, gender, and sociolinguistic groups), and (iii) identify their potential substitutes in the area.

Methods

Study area

This study was conducted in 2015, and data presented here were collected over a 6-month period. The study was carried out in the Atakora mountain chain region in Benin (6°–12°50′N and 1°–3°40′E) (Fig. 1). The Atakora chain region includes East Atakora (EA), Central Atakora (CA), and West Atakora (WA) zones. The climate is of Sudanian type and is influenced by the Atakora mountain chain in the state district of Atakora and with a tendency toward a Sahelian climate northward. The rainfall is irregular and unimodal with one rainy season and a dry season which last up to 7 months. The annual rainfall varies between 900 and 1300 mm, and the mean annual temperature is 27 °C [27]. The relief is mountainous with poor sandy, rocky, and encrusted soils and some shallows. Soil is ferruginous. The main sociolinguistic groups encountered in the area are Bariba, Berba, Biali, Dendi, Ditamari, Fulfulde, Lamba, Natimba, Otamari, and Waama [28].
Fig. 1

Map showing the study area and indicating the surveyed localities

Map showing the study area and indicating the surveyed localities

Sampling and data collection

Twelve state districts belonging to the study regions were selected, and in each district, 2 to 12 localities were randomly selected for the survey (Fig. 1). A total of 267 informants were surveyed throughout the study area, taking into account the geographical location, gender, age, and sociolinguistic group (Table 1). Only informants relatively aged who are expected to have experience and knowledge on the dynamic of woody resources over time were considered. Age of interviewees ranged from 25 to 120 years. The data were collected during expeditions using individual semi-structured interviews and field visits in the selected localities. The questionnaire for the interviews comprised two parts. The first was related to the socio-demographic data of the respondents (name, age, sex, sociolinguistic group, locality) while the second concerned the respondent’s knowledge on the TWS using the free-listing technique. In each locality, interviewees were randomly selected among men and women in different households. However, because of social constraints that made women not very accessible, the study ended up sampling a lot more men than women (16 women and 251 men). Each informant was asked first to list as much threatened woody species s/he knows. In assigning a woody species to as threatened versus not threatened, informants were asked to mainly consider the availability of the woody species through (i) whether they travel more distances or spent more energy to find a particular species that they used to find easily in the past and (ii) whether the extent of the distribution of the woody species has shrunk as compared to its pas extent of distribution. These criteria used for rigorous IUCN assessment [29] are also commonly used to assess species availability in ethnobotanical study (see de Albuquerque [30]). Finally, the informant was asked to mention whether or not each species s/he cited is important and to give the reason of its importance in terms of category of uses. Individual interviews were followed by field visits accompanied with key informants to collect species specimens.
Table 1

Sample composition according to location, gender, age, and sociolinguistic groups

ZoneTotal
EACAWA
GenderWomen311216
Men1018664251
AgeAge < 402151431
40 ≤ age ≤ 60413631108
Age > 60613631128
Sociolinguistic groupBariba7512087
Berba004343
Dendi172019
Fulfulde125017
Natimba0151530
Otamari0231841
Waama030030
Total1048776267

EA East Atakora, CA Central Atakora, WA West Atakora

Sample composition according to location, gender, age, and sociolinguistic groups EA East Atakora, CA Central Atakora, WA West Atakora

Data analysis

Collected plant samples were identified at the botanical garden at the University of Abomey-Calavi, Benin, using field herbariums. Data processing consisted in grouping interviewees by sociolinguistic group, gender, age, and zone, then computing descriptive statistics (frequencies, percentages, means ± standard error) for species, genera, and botanical families to draw barplots and generate tables at different levels. Three age groups were created: (a) ≤ 40 years old hereafter called “young,” (b) from 40 to 60 years called “adult” from now on, and (c) ≥ 60 years referred to as “old” from now on. This age categorization followed the United Nations’ World Population Aging 2013 [31] where children and adolescents are under the age of 20 years; young adults (“young” in this study) are between 20 and 39 years of age, middle-aged adults (“adult” in this study) are aged from 40 to 59 years, and older persons (“old” in this study) are aged 60 years or over. To compare the number of threatened, and important species cited by the respondents among age groups, zones and sociolinguistic groups, analysis of variance (ANOVA) or Kruskal-Wallis test was performed when appropriate. ANOVA and the Student Newman Keuls (SNK) post hoc test were used when normality and homoscedasticity assumptions were met, and Kruskal-Wallis test and the Dunn post hoc test when normality and homoscedasticity assumptions were not met [32]. The Dunn test was used as post hoc test instead of the Tukey-Kramer-Nemenyi test because it is appropriate for groups with unequal sizes [33]. Normality and homoscedasticity assumptions were tested using Shapiro-Wilk and Levene’s tests, respectively. The Dunn post hoc test was performed using the package FSA [34] in R software [35]. Since the number of women in the study (16) was very unbalanced for making robust inference [36], no statistical comparison was made regarding gender, although descriptive statistics have been reported. To assess the reason supporting the importance of threatening woody species, a correspondence analysis was applied on the contingency table of categories of use and important species. A correspondence analysis was performed using the FactomineR package [37]. To determine the most threatened woody species mentioned by the respondents in each zone, the average order of citation was computed for each species and plotted against the frequency of citation of the species. The rationale of using this method relied on the fact that when people are asked to freely list items, they tend to mention the most prominent one first [38, 39]. Most threatened species are species with high frequency of citation and low-average order of citation while least threatened species are species with low frequency of citation and high-average order of citation. Analysis of similarities (ANOSIM) [40] was used to test for differences in threatened and important woody species composition among age group, region, and sociolinguistic group. ANOSIM analysis was performed based on Jaccard dissimilarity distance and 1000 permutations in the package vegan [41]. Generalized linear models (GLM) with Poisson (or quasi-Poisson) error distribution were performed to test for differences among regions as regards the average number of substitutes cited by respondents. Relative frequency of citation of substitutes were computed by region and for each of the most threatened woody species in order to determine the most cited substitutes per region and for each TWS. A non-metric multidimensional scaling (NMDS) was used to assess the degree of distinctiveness of the substitute species across the three regions. NMDS was performed in the vegan package using the function metaMDS and based on Bray distance [42]. Finally, we looked at whether the potential substitutes belong to the same functional group as the substituted species in term of life forms. This was done to assess flexibility in identifying substitutes but also understand whether locals can go over functional group and why.

Results

Taxonomic diversity of threatened woody species

A total of 117 species belonging to 92 genera and 37 families were collected and identified as threatened woody species in the study area (Table 2). The most represented family in East Atakora (EA) was Fabaceae with 18 species, followed respectively by Moraceae (9 species), Malvaceae (7 species), Rubiaceae, Meliaceae, and Combretaceae (5 species each) (Fig. 2). In Central Atakora (CA), the richest family was also Fabaceae (17 species), followed by Moraceae (5), and Malvaceae (5). In West Atakora (WA), Fabaceae (13 species) and Combretaceae (12 species) stood respectively first and second as the families with the highest species richness (Fig. 2). Overall, in the study area, the most represented families were Fabaceae (23 species), Combretaceae (15 species), Moraceae (12 species), Malvaceae (7 species), Anacardiaceae (6 species), Rubiaceae (5 species), Meliaceae (5 species), and Arecaceae (5 species), and other families had less than 5 species (Fig. 2). Twenty-six families were represented by only one species (Table 2). The richest genera in EA were respectively Ficus (7), Lannea (3), Khaya (2), Isoberlinia (2), Combretum (2), and Bombax (2). In CA, the most represented genera were respectively Ficus (3), Khaya (2), Isoberlinia (2), and Bombax (2) while in WA, the most represented genera were Combretum (6), Terminalia (4), Lannea (3), Isoberlinia (2), and Ficus (2). Overall, Ficus stood as the first genera with 10 species, followed by Combretum (6 species), Terminalia (5 species), Lannea (3 species), and Khaya, Isoberlinia, Bombax, and Bauhinia each one represented by two species (Fig. 3).
Table 2

Threatened woody species collected in the Atakora mountain chain region in Benin

No.Voucher specimen codeBotanical familySpeciesFrequency of citations (%)CS
EA (n = 104)CA (n = 87)WA (n = 76)Whole (n = 267)BeninIUCN
12005AnacardiaceaeHaematostaphis barteri Hook. fil.0.005.750.001.87nfnf
22617AnacardiaceaeLannea acida A. Rich.8.650.002.634.12nfnf
31528AnacardiaceaeLannea barteri (Oliv.) Engl.1.920.002.631.50nfnf
41388AnacardiaceaeLannea microcarpa Engl. & K. Krause14.421.1535.5316.10nfnf
52399AnacardiaceaeSclerocarya birrea (Sond.) Kokwaro0.005.7538.1612.73nfnf
6823AnacardiaceaeSpondias mombin Jacq.0.005.750.001.87nfnf
71996AnnonaceaeAnnona senegalensis Pers.1.920.000.000.75nfnf
81749AnnonaceaeHexalobus monopetalus (A. Rich.) Engl. & Diels8.653.450.004.49nfnf
9372AnnonaceaeUvaria chamae P. Beauv.0.960.000.000.37nfnf
101818ApocynaceaeHolarrhena floribunda (G.Gon) T. Durand & Schinz7.690.000.003.00nfnf
114640ApocynaceaeSaba comorensis (Bojer) Pichon4.815.750.003.75nfnf
123680ApocynaceaeStrophanthus hispidus A.P. De Candolle9.629.200.006.74nfnf
13344AraliaceaeCussonia arborea Hochst. Ex A.Rich.6.730.000.002.62nfnf
144158ArecaceaeBorassus aethiopum Mart.83.6581.6128.9567.42VULC
154190ArecaceaeElaeis guineensis Jacq.41.3528.740.0025.47nfLC
163547ArecaceaeHyphaene thebaica (L.) Mart.0.000.0017.114.87nfnf
17578ArecaceaePhoenix reclinata Jacq.13.460.000.005.24nfnf
184437ArecaceaeRaphia sudanica A.Chev.36.5414.940.0019.10nfDD
193178BignoniaceaeKigelia africana (Sprague) Bidgood & Verdc.47.1214.940.0023.22VUnf
204284BurseraceaeCommiphora africana (Rich.) Engl.2.881.150.001.50nfnf
214459CannabaceaeCeltis integrifolia Lam.4.811.150.002.25nfnf
22940CannabaceaeChaetachme aristata Planch.0.005.750.001.87nfnf
231531ChrysobalanaceaeMaranthes polyandra (Benth.) Prance3.850.000.001.50nfnf
24375ClusiaceaePentadesma butyracea Sabine3.855.750.003.37VUnf
251053CombretaceaeAnogeissus leiocarpa (DC.) Guill. & Perr.49.0464.3792.1166.29nfnf
26637CombretaceaeCombretum adenogonium Steud. ex A. Rich.0.000.0015.794.49nfnf
271146CombretaceaeCombretum collinum (Kotschy) Okafor0.000.0015.794.49nfnf
282583CombretaceaeCombretum glutinosum Perr. Ex DC.0.000.0015.794.49nfnf
291226CombretaceaeCombretum micranthum G. Don7.694.6017.119.36nfnf
302456CombretaceaeCombretum molle R. Br. Ex G. Don0.000.0010.533.00nfnf
311295CombretaceaeCombretum platypterum (Welw.) Hutch. & Dalz.1.920.000.000.75nfnf
32Combretaceae Combretum spp 0.000.0015.794.49nfnf
332560CombretaceaeGuiera senegalensis J.F.Gmel.0.000.0015.794.49nfnf
34701CombretaceaePteleopsis suberosa Engl. & Diels2.889.202.634.87nfnf
352010CombretaceaeTerminalia avicennioides Guill. & Perr.7.690.0022.379.36nfnf
361568CombretaceaeTerminalia laxiflora Engl.0.000.002.630.75nfnf
371055CombretaceaeTerminalia macroptera Guill. & Perr.0.000.002.630.75nfnf
383639CombretaceaeTerminalia mollis M. Laws.0.000.002.630.75nfnf
395228CombretaceaeTerminalia superba Engl. & Diels0.000.000.000.00VUnf
403127DipterocarpaceaeMonotes kerstingii Gilg0.960.000.000.37nfnf
41497EbenaceaeDiospyros mespiliformis Hochst. Ex A.DC.50.9654.0286.8462.17nfnf
422488EuphorbiaceaeAlchornea cordifolia (Shumach. & Thonn.) Müll.Arg.0.000.009.212.62nfnf
433138EuphorbiaceaeEuphorbia poissonii Pax2.881.150.001.50nfnf
443537FabaceaeAcacia nilotica (L.) Willd. & Delile9.620.0013.167.49nfnf
451560FabaceaeAfzelia africana Pers.93.2793.1042.1178.65ENVU
462191FabaceaeAlbizia zygia (DC.) J.F.Macbr.1.924.600.002.25nfnf
472091FabaceaeAndira inermis (Wright) DC.0.960.000.000.37nfnf
485163FabaceaeBauhinia reticulata DC.1.920.000.000.75nfnf
491723FabaceaeBauhinia thonningii Schum.0.000.006.581.87nfnf
502518FabaceaeBerlinia grandiflora (Vahl) Hutch. & Dalziel6.739.200.005.62nfnf
51686FabaceaeBurkea africana Hook.9.6211.492.638.24nfnf
522299FabaceaeCassia sieberiana DC.5.7711.496.587.87nfnf
53629FabaceaeDaniellia oliveri (Rolfe) Hutch. & Dalziel19.231.150.007.87nfnf
541816FabaceaeDetarium microcarpum Guill. & Perr.0.000.0023.686.74nfnf
55226FabaceaeEntada africana Guill. & Perr.3.850.000.001.50nfnf
561816FabaceaeErythrina senegalensis DC.1.929.200.003.75nfnf
572500FabaceaeFaidherbia albida (Delile) A. Chev.0.001.159.213.00nfnf
581277FabaceaeIsoberlinia doka Craib & Stapf32.6911.4923.6823.22nfnf
596038FabaceaeIsoberlinia tomentosa (Harms) Craib & Stapf27.8811.4923.6821.35nfnf
604198FabaceaeParkia biglobosa (Jacq.) G. Don44.2370.1165.7958.80nfnf
611845FabaceaePericopsis laxiflora (Baker) Meeuwen12.504.600.006.37nfnf
621054FabaceaeProsopis africana (Guill. & Perr.) Taub.14.4219.5443.4224.34nfnf
631690FabaceaePterocarpus erinaceus Poir.80.7788.5185.5384.64ENnf
643516FabaceaeSwartzia madagascariensis Desv.0.003.450.001.12nfnf
651715FabaceaeTamarindus indica L.37.5013.7926.3226.59nfnf
661788FabaceaeTephrosia vogelii Hook.f.0.001.150.000.37nfnf
671851GentianaceaeAnthocleista djalonensis A. Chevalier7.699.200.005.99nfnf
68876LamiaceaeVitex doniana Sweet37.5047.1360.5347.19nfnf
692053LoganiaceaeStrychnos innocua Delile0.000.002.630.75nfnf
702269MalvaceaeAdansonia digitata L.33.6517.2440.7930.34nfnf
713984MalvaceaeBombax buonopozense Beauv.21.1518.390.0014.23nfnf
721765MalvaceaeBombax costatum Pellegrin & Vuillet48.0851.7251.3250.19nfnf
731710MalvaceaeCeiba pentandra (L.) Gaertn.62.5018.395.2631.84nfnf
744206MalvaceaeCola gigantea A. Chevalier7.690.000.003.00nfnf
751549MalvaceaeSterculia setigera Del.7.693.450.004.12nfnf
762100MalvaceaeTriplochiton scleroxylon K. Schum.2.880.000.001.12ENLC
771934MeliaceaeEkebergia capensis Sparrm.6.730.000.002.62nfnf
782136MeliaceaeKhaya grandifoliola C. DC.19.238.050.0010.11ENVU
792436MeliaceaeKhaya senegalensis (Desv.) A. Juss.97.1298.8598.6898.13ENVU
80834MeliaceaePseudocedrela kotschyi (Schweinf.) Harms21.158.052.6311.61nfnf
811299MeliaceaeTrichilia emetic Vahl0.960.000.000.37nfnf
82B163MoraceaeAntiaris toxicaria (Engl.) C. C. Berg30.7742.5346.0538.95nfnf
83910MoraceaeFicus glumosa Del.1.920.000.000.75nfnf
841275MoraceaeFicus gnaphalocarpa Steud. ex Miq.0.000.0026.327.49nfnf
852670MoraceaeFicus ingens (Miq.) Miq.0.001.150.000.37nfnf
861017MoraceaeFicus ovata D. Don0.960.000.000.37nfnf
875183MoraceaeFicus platyphylla Del.2.8820.695.269.36nfnf
882430MoraceaeFicus sur Forssk.3.850.000.001.50nfnf
89859MoraceaeFicus thonningii Bl.0.009.200.003.00nfnf
90994MoraceaeFicus trichopoda Bak.1.920.000.000.75nfnf
911226MoraceaeFicus umbellata Vahl4.810.000.001.87nfnf
922380MoraceaeFicus vallis-choudae Del.4.810.000.001.87nfnf
931476MoraceaeMilicia excelsa (Welw.) C. C.93.2772.4113.1663.67ENVU
943350MyrtaceaeSyzygium guineense Keay17.310.000.006.74nfnf
95518OchnaceaeLophira lanceolata Van Tiegh. ex Keay9.6211.490.007.49nfnf
962666OchnaceaeOchna schweinfurthiana F. Hoffm.0.0018.390.005.99nfnf
971316OlacaceaeOlax subscorpioidea Oliver2.8818.390.007.12nfnf
984284OleaceaeChionanthus niloticus (Oliv.) Stearn9.628.050.006.37nfnf
991477OpiliaceaeOpilia amentacea Roxb.1.920.000.000.75nfnf
1002032PhillanthaceaeUapaca togoensis Pax4.811.150.002.25nfnf
101346PhyllanthaceaeMargaritaria discoidea (Baill.) G.L.Webster1.920.000.000.75nfnf
1022208PoaceaeOxytenanthera abyssinica (A.Rich.) Munro15.3825.293.9515.36nfnf
103196PolygalaceaeSecuridaca longipedunculata Fresen.9.624.600.005.24nfnf
1042240ProteaceaeProtea madiensis (Beard) Chisumpa & Brummit7.690.000.003.00nfnf
1052065RubiaceaeBreonadia salicina (Vahl) Hepper & J.R.I.Wood6.732.300.003.37nfnf
106688RubiaceaeCrossopteryx febrifuga (Afzel. ex G. Don) Benth.3.850.000.001.50nfnf
1072541RubiaceaeGardenia erubescens Stapf & Hutch.1.921.150.001.12nfnf
1082089RubiaceaeMitragyna inermis (Willd.) Kuntze1.929.2035.5313.86nfnf
1092463RubiaceaeSarcocephalus latifolius (Sm) E.A.Bruce6.739.203.956.74nfnf
1101911RutaceaeAfraegle paniculata (Schum.) Engl.18.2754.0235.5334.83ENnf
1114500RutaceaeZanthoxylum zanthoxyloides (Lam.) B. Zepernick & F.K. Timler3.8528.7419.7416.48VUnf
112309SalicaceaeOncoba spinosa Forssk.0.000.002.630.75nfnf
113872SapindaceaeBlighia sapida Koenig14.4216.090.0010.86nfnf
114261SapindaceaeZanha golungensis Hiern0.960.000.000.37nfnf
1151806SapotaceaeVitellaria paradoxa C.F.Gaertn.49.0455.1744.7449.81VUVU
1161845XimeniaceaeXimenia americana L.13.460.000.005.24nfnf
1172575ZygophyllaceaeBalanites aegyptiaca (L.) Delile4.810.0018.427.12nfnf

EA East Atakora, CA Central Atakora, WA West Atakora, CS conservation status, VU vulnerable, EN endangered, LC least concern, DD data deficiency, nf not found

Fig. 2

Richer families of threatened woody species in the Atakora mountain region

Fig. 3

Richer genera of threatened woody species in the Atakora mountain region

Threatened woody species collected in the Atakora mountain chain region in Benin EA East Atakora, CA Central Atakora, WA West Atakora, CS conservation status, VU vulnerable, EN endangered, LC least concern, DD data deficiency, nf not found Richer families of threatened woody species in the Atakora mountain region Richer genera of threatened woody species in the Atakora mountain region In EA, Khaya senegalensis (Meliaceae), Afzelia africana (Fabaceae), Milicia excelsa (Moraceae), Borassus aethiopum (Arecaceae), Pterocarpus erinaceus (Fabaceae), Ceiba pentandra (Malvaceae), and Diospyros mespiliformis (Ebenaceae) were respectively the most cited woody species (cited by at least 50% of informants), while in CA, the most cited threatened woody species were respectively K. senegalensis, A. africana, P. erinaceus, B. aethiopum, M. excelsa, Parkia biglobosa (Fabaceae), Anogeissus leiocarpa (Combretaceae), Vitellaria paradoxa (Sapotaceae), Afraegle paniculata (Rutaceae), D. mespiliformis (Ebenaceae), and Bombax costatum (Malvaceae). In WA, the threatened woody species most mentioned by respondents were respectively K. senegalensis, A. leiocarpa, D. mespiliformis, P. erinaceus, P. biglobosa, Vitex doniana (Lamiaceae), and B. costatum. Three species were commonly more cited in the three regions: K. senegalensis, P. erinaceus, and D. mespiliformis (Fig. 4).
Fig. 4

Top 20 more cited threatened woody species

Top 20 more cited threatened woody species

Most threatened woody species

The most threatened woody species in East and Central Atakora (K. senegalensis, A. africana, M. excelsa, P. erinaceus, and B. aethiopum) were different from those identified in West Atakora which were K. senegalensis, A. leiocarpa, P. erinaceus, and D. mespiliformis (Fig. 5). Therefore, people from East and Central Atakora regions mentioned different woody species as the most threatened compared to people from West Atakora region, except for K. senegalensis that was considered as one of the most threatened woody species in all regions.
Fig. 5

Most threatened woody species in the Atakora chain region of Benin

Most threatened woody species in the Atakora chain region of Benin

Taxonomic diversity of threatened woody species perceived as socio-economically important

Among the inventoried threatened woody species, those that were important for the informants also varied across regions as presented on Fig. 6. For people in East Atakora (EA), K. senegalensis was the most important threatened woody species (cited by at least 50% of respondents). The species mentioned as the most important in Central Atakora (CA) were respectively K. senegalensis, P. biglobosa, and V. paradoxa. In West Atakora region (WA), K. senegalensis, V. doniana, and P. biglobosa were the most important. Irrespective of regions, Khaya senegalensis was the most important threatened woody species (Fig. 6).
Fig. 6

Top 20 threatened woody species more mentioned as important in the Atakora mountain region

Top 20 threatened woody species more mentioned as important in the Atakora mountain region Result from the correspondence analysis performed on important TWS and their use categories indicated that the two first axes encountered for 79.49% of the total variation in the data. The first axis opposed food use category (negative pole) to timber and fodder use categories (positive pole). The second axis was formed by fuelwood use-category in the positive pole (Fig. 7). Projection of the important threatened woody species into the axis system identified three groups of species. The first group included the species used mainly for food which were Adansonia digitata, B. costatum, B. aethiopum, Blighia sapida, Elaeis guineensis, P. biglobosa, Sclerocarya birrea, V. paradoxa, V. doniana, and Zanthoxylum zanthoxyloides. The second group was formed by species such as A. africana, Bombax buonopozense, K. grandifoliola, K. senegalensis, and P. erinaceus not only used mainly for timber and fodder purposes but also as service wood and for medicinal purposes. The third group formed by species mostly used as fuelwood, included Prosopis africana, A. leiocarpa, D. mespiliformis, I. doka, I. tomentosa, and Lophira lanceolata (Fig. 7).
Fig. 7

Projection of important threatened woody species in the correspondence analysis system axes formed by use categories

Projection of important threatened woody species in the correspondence analysis system axes formed by use categories

Threatened and socio-economical important woody species: gender, generation, geographical location, and sociolinguistic group differences

The number of threatened woody species (TWS) cited per respondent varied significantly among age categories (ANOVA; p = 0.030). Adult (14.82 ± 0.45) and old (14.57 ± 0.47) informants cited more species than younger ones (12.19 ± 0.54; Fig. 8). Men cited 14 ± 0.31 species, and women informant mentioned 11.38 ± 0.81 threatened woody species. The number of species was not compared between genders. Respondents from EA mentioned more threatened species (15.58 ± 0.51) compared to those from CA and WA (13.79 ± 0.49 and 13.47 ± 0.5, respectively). The number of TWS cited per respondent varied also among the sociolinguistic groups (Kruskal-Wallis test; p = 0.003). Dendi (16.58 ± 0.59) and Fulfulde (16.59 ± 1.5) people cited higher number of species while Natimba (13.07 ± 0.57), Otamari (12.59 ± 0.57), and Waama (12.8 ± 0.51) cited less species. Bariba (15.28 ± 0.62) and Berba (14.56 ± 0.78) people cited average number of species (Fig. 8).
Fig. 8

Number of threatened and socio-economically important species mentioned according to socio-demographic factors

Number of threatened and socio-economically important species mentioned according to socio-demographic factors The number of TWS rated as socio-economically important was not influenced neither by age (Kruskal-Wallis test; p = 0.798) nor by region (Kruskal-Wallis test; p > 0.05). Women mentioned 5.56 ± 0.13 species as important while men mentioned 5.42 ± 0.1 species. The number of TWS important to people also varied among sociolinguistic groups (Kruskal-Wallis test; p = 0.006). Bariba (5.52 ± 0.18), Berba (5.23 ± 0.17), Dendi (6 ± 0.67), Waama (5.6 ± 0.42), and Fulfulde (5.41 ± 0.12) mentioned significantly higher number of TWS as socio-economically important than Otamari (5.44 ± 0.13) people. Natimba (4.93 ± 0.11) mentioned less important threatened woody species (Fig. 8). The similarity among socio-demographic factors (age, zone, and sociolinguistic group) as regards the composition of TWS cited by respondents was revealed by the matrix of Jaccard’s similarity coefficient (Table 3). Threatened species composition varied significantly among age categories (R = 0.057, p = 0.0009). Coefficient of similarity between young and old people (0.374) was significantly lower resulting in a high difference between the species mentioned by younger and older informants. Moreover, the composition of TWS mentioned by respondent was very similar between adult and old, and to some extent between young and adult (Jaccard’s coefficients of 0.783 and 0.431, respectively). Analysis of similarity among regions was globally significant (R = 0.221, p = 0.0009). Threatened woody species mentioned by people from West Atakora (WA) were significantly different from those cited either by people from Central Atakora (CA) and people from East Atakora (EA) (Jaccard’s coefficients of 0.318 and 0.368, respectively, Table 3). About half of the species cited by people from WA were also cited by respondents from CA (Jaccard’s coefficient of 0.576). On the other hand, TWS composition also varied significantly among sociolinguistic groups (ANOSIM; R = 0.206, p = 0.0009). Analysis of similarity coefficient matrix revealed that TWS cited by Bariba informants were significantly different from those cited by Berba (0.275) and Natimba (0.272); meanwhile, species mentioned by the two latter were relatively more similar from each other (0.418; Table 3). Species cited by Berba were significantly more different than similar to Dendi, Fulfulde, Otamari, and Waama (Jaccard’s similarity coefficients of 0.358, 0.333, 0.355, and 0.306, respectively). Likewise, there was a highly significant difference between Bariba and Otamari (0.319), and Fulfulde and Otamari (0.370). At least 40% of the species cited by Dendi people were similar to those mentioned by Natimba (0.418) and Otamari (0.466) informants. There was no significant difference between Bariba, Dendi, Fulfulde, Otamari, and Waama regarding the species mentioned. Consequently, these sociolinguistic groups knew the same TWS. Overall, there was a great intercultural difference as regards the TWS mentioned by respondents and the greater differentiation was detected between Bariba and Berba, and between Bariba and Natimba.
Table 3

Similarity matrix (Jaccard’s coefficients) among sociolinguistic groups as regards the threatened and important woody species

BaribaBerbaDendiFulfuldeNatimbaOtamariWaama
Bariba 0.233 *** 0.317 ** 0.164 ns0.224 ns 0.305 *** 0.283 **
Berba0.275 *** 0.324 ** 0.304 ns 0.370 *** 0.387 *** 0.483 ***
Dendi0.424 ns0.358 *** 0.345 *** 0.484 * 0.405 ** 0.444 ns
Fulfulde0.412 ns0.333 ***0.558 ns 0.421 * 0.269 ns0.320 ns
Natimba0.272 *0.453 ***0.418 **0.457 * 0.429 *** 0.538 **
Otamari0.319 ***0.355 ***0.466 **0.370 **0.449 *** 0.484 ***
Waama0.360 ns0.306 ***0.491 ns0.511 ns0.447 **0.415 ns

Data in italics are Jaccard’s coefficients of important woody species

ns non-significant

*P value ≤ 0.05, **P value ≤0.01, ***P value ≤ 0.001. Differences were tested using Analysis of Similarities (ANOSIM)

Similarity matrix (Jaccard’s coefficients) among sociolinguistic groups as regards the threatened and important woody species Data in italics are Jaccard’s coefficients of important woody species ns non-significant *P value ≤ 0.05, **P value ≤0.01, ***P value ≤ 0.001. Differences were tested using Analysis of Similarities (ANOSIM) Similarity matrix based on Jaccard’s coefficient showed significant differences in the composition of important woody species among age categories (R = 0.050; p = 0.0020), zones (R = 0.109; p = 0.0009) and sociolinguistic groups (R = 0.130; p = 0.0009; Table 2). Species mentioned as important by middle-aged informants were very similar to those cited by older people (Jaccard’s coefficient of 0.703). Therefore, adults knew as much important species than old people while young informants knew lesser important woody species compared to adults and older informants (Jaccard’s coefficients of 0.403 and 0.328, respectively). The coefficient of similarity between East and West Atakora was significantly lower (0.299) likewise between EA and CA (0.362). The coefficient of similarity between Central and the West Atakora was the highest (0.452). Thus, people from EA knew very different important species compared to people from WA, and the latter knew more similar species than informants from CA. The analysis of similarity (Table 3) revealed that species cited by Bariba people as important were highly different from those cited by Berba and by Waama informants. Species composition as mentioned by respondents was moderately similar among Bariba, Berba, Dendi, Fulfulde, Natimba, and Otamari (Jaccard’s coefficient between 0.305 and 0.429). Almost half of the species mentioned by Waama people were similar to those mentioned by Berba, Natimba, Otamari, and Dendi. Therefore, there was high to moderate differences in the important woody species composition with respect to sociolinguistic groups and the higher differences were found between Bariba and Berba, and between Bariba and Waama.

Potential substitutes of threatened woody species: between-region differences

Differences in substitute species were assessed for the most threatened woody species common to the three regions (Table 4). Overall, average number of substitute species significantly differed among regions for K. senegalensis, B. aethiopum, and A. africana (GLM; p ≤ 0.05; Fig. 9). In East Atakora (EA), the average number of substitute species was highest for K. senegalensis (0.6 ± 0.12), followed by V. paradoxa (0.21 ± 0.08), A. africana (0.16 ± 0.06), and B. aethiopum (0.12 ± 0.07), while in Central Atakora (CA), K. senegalensis (0.59 ± 0.08), B. aethiopum (0.53 ± 0.12), and A. africana (0.27 ± 0.05) respectively had the higher number of substitute. In West Atakora (WA), K. senegalensis (0.25 ± 0.05) had the greater average number of substitute, followed by A. africana (0.21 ± 0.11) while no substitute was mentioned for B. aethiopum. Therefore, informants from EA and those from CA knew more substitutes of K. senegalensis than those from WA. Moreover, people from CA knew in average more substitute of B. aethiopum than people from the other regions. Although the average number of substitutes of A. africana cited by informants were relatively similar among regions, people from CA mentioned more substitute species than those from WA and EA respectively. Average number of substitute species did not vary for V. paradoxa, P. biglobosa, P. erinaceus, A. toxicaria, D. mespiliformis, and B. costatum (GLM; p > 0.05; Fig. 9). No substitute species was cited for V. doniana and A. leiocarpa in the three regions.
Table 4

Most threatened woody species common to the three zones

Threatened woody speciesZones
EACAWA
Afzelia africana Pers.xxx
Anogeissus leiocarpa (DC.) Gill. & Perr.xxx
Antiaris toxicaria (Engl.) C. C. Bergxxx
Bombax costatum Pellegrin & Vuilletxxx
Borassus aethiopum Mart.xxx
Diospyros mespiliformis Hochst. Ex A.DC.xxx
Khaya senegalensis (Desv.) A. Jussxxx
Parkia biglobosa (Jacq.)G.Donxxx
Pterocarpus erinaceus Poir.xxx
Vitellaria paradoxa C.F.Gaertnxxx
Vitex doniana Sweetxxx
Ceiba pentandra (L) Geartnxx
Elaeis guineensis Jacq.xx
Milicia excelsa (Welw.) C.C. Bergxx
Adansonia digitata L.xx
Tamarindus indica L.xx
Isoberlinia doka Craib & Stapfx
Isoberlinia tomentosa (Harms) Craib & Stapfx
Kigelia africana (Sprague) Bidgood & Verdcx
Raphia sudanica A. Chev.x
Afraegle paniculata (Schum.)xx
Prosopis africana (Guill. & Perr.)Taub.xx
Bombax buonopozense Beauv.x
Ficus platyphylla Del.x
Oxytenanthera abyssinica (A.Rich.)x
Zanthoxylum zanthoxyloides (Lam.) B.Zepernick & F.K. Timlerx
Detarium microcarpum Guill. & Perr.x
Ficus gnaphalocarpa Steud. Ex Miq.x
Lannea microcarpa Engl & K. Krausex
Mitragyna inermis (Willd.) Kuntzex
Sclerocarya birrea (Sond.) Kokwarox

EA East Atakora, CA Central Atakora, WA West Atakora

Fig. 9

Potential substitutes for the common more threatened woody species across regions. p = p value from the generalized linear model (GLM) of Poisson/quasi-Poisson

Most threatened woody species common to the three zones EA East Atakora, CA Central Atakora, WA West Atakora Potential substitutes for the common more threatened woody species across regions. p = p value from the generalized linear model (GLM) of Poisson/quasi-Poisson Most of substitutes were also woody species except for Glycine max and Arachis hypogaea, two herbs that were substitute for P. biglobosa and V. paradoxa respectively (Fig. 10, Table 5). Substitute species more cited by respondents varied across regions. P. erinaceus was mainly mentioned as substitute of A. africana in EA (25.29% of respondents) and to some extent in the CA (5.77%) while T. indica was mostly cited in WA (3.95% of informants, Table 5). Khaya spp. and P. erinaceus were equally more cited as substitute of B. aethiopum in CA (cited by 14.94% of informants). More cited substitute species for K. senegalensis were I. doka (19.24%) and I. tomentosa (13.46%) in EA, P. erinaceus and A. africana in CA (40.23 and 14.94%, respectively), and P. erinaceus in WA (23.68%). The most cited substitute species for P. biglobosa was A. digitata in the Atakora chain (2.30%), while A. digitata and G. max were respectively more cited in WA (5.26 and 2.63%). For V. paradoxa, people mentioned more P. butyracea as substitute in EA (6.73%) and in CA (4.60%) while A. hypogaea was most cited in WA (2.63%; Table 5). Overall, P. erinaceus was the most cited substitute species, mentioned by 38.2% of informants. The species was mainly mentioned as substitute for K. senegalensis, A. africana, and B. aethiopum (22.47, 10.49, and 5.24% of respondents, respectively). The second more cited substitute species was Isoberlinia doka (7.49% of all informants), followed by A. africana (6.74%), both mentioned for K. senegalensis.
Fig. 10

Number and life form of the potential substitutes for each common more threatened woody species

Table 5

Frequency of substitute mentioned by respondents for each more threatened woody species

Common more threatened speciesSubstitutesLFZones (%)
EA (n = 104)CA (n = 87)WA (n = 76)Whole (%)
Afzelia africana Khaya sppTree1.920.000.000.75
Tectona grandis L.f.Tree0.960.000.000.37
Eucalyptus sppTree0.960.000.000.37
Leucaena leucocephala (Lam.)de WitTree1.920.000.000.75
Pterocapus erinaceus Poir.Tree5.7725.290.0010.49
Isobelinia sppTree0.960.000.000.37
Tamarindus indica L.Tree0.000.003.951.12
Anogeissus leiocarpa 0.000.000.000.00
Antiaris toxicaria Pterocapus erinaceus Poir.Tree0.001.150.000.37
Bombax costatum Daniellia oliveri (Rolfe)Hutch. & DalzielTree0.001.150.000.37
Borassus aethiopum Elaeis guineensis Jacq.Tree0.960.000.000.37
Anogeissus leiocarpa (DC.) Gill. & Perr.Tree0.960.000.000.37
Khaya sppTree0.9614.940.005.24
Afzelia africana Pers.Tree0.961.150.000.75
Pterocapus erinaceus Poir.Tree0.9614.940.005.24
Isobelinia sppTree0.960.000.000.37
Diospyros mespiliformis Pterocarpus erinaceus Poir.Tree0.001.150.000.37
Khaya senegalensis Acacia sieberiana DC.Tree0.960.000.000.37
Afzelia africana Pers.Tree4.8114.940.006.74
Pterocarpus erinaceus Poir.Tree6.7340.2323.6822.47
Khaya sppTree0.000.000.000.00
Borassus aethiopum Mart.Tree0.002.300.000.75
Ekebergia capensis Sparrm.Tree19.230.000.000.75
Isoberlinia doka Craib & StapfTree13.460.000.007.49
Isoberlinia tomentosa (Harms) Craib & StapfTree4.810.000.005.24
Tectona grandis L.f.Tree5.770.000.002.25
Leucaena leucocephala (Lam.)de WitTree1.920.000.000.75
Pseudocedrela kotschyi (Schweinf.) HarmsTree6.730.000.002.62
Parkia biglobosa Adansonia digitata L.Tree0.002.305.262.25
Glycine max (L.)Merr.Herb0.000.002.630.75
Prosopis africana (Guill. & Perr.)Taub.Tree0.960.000.000.37
Acacia auriculiformis A.Cunn. ex Benth.Tree0.960.000.000.37
Pterocarpus erinaceus Acacia sieberiana DC.Tree0.960.000.000.37
Isoberlinia spp.Tree1.920.000.000.75
Tectona grandis L.f.Tree0.960.000.000.37
Khaya sppTree0.960.000.000.37
Leucaena leucocephala (Lam.)de WitTree1.920.000.000.75
Vitellaria paradoxa Anacardium occidentale L.Tree0.960.000.000.37
Mangifera indica L.Tree0.960.000.000.37
Arachis hypogaea L.Herb0.000.002.630.75
Pentadesma butyracea SabineTree6.734.600.004.12
Acacia sieberiana DC.Tree0.960.000.000.37
Prosopis africana (Guill. & Perr.)Taub.Tree0.960.000.000.37
Vitex doniana 0.000.000.000.00

LF life form, EA East Atakora, CA Central Atakora, WA West Atakora

Number and life form of the potential substitutes for each common more threatened woody species Frequency of substitute mentioned by respondents for each more threatened woody species LF life form, EA East Atakora, CA Central Atakora, WA West Atakora There was a weak discrimination of substitute species across regions (Fig. 11). A full overlap of confidence ellipses was observed between EA and CA indicating a high similarity between substitute species mentioned in these two regions. In contrast, overlapping of confidence ellipse was partial between WA and EA or CA indicating that substitute species composition was relatively distinct between WA and CA or between WA and EA.
Fig. 11

Ordination diagram of a NMDS of substitutes of 11 threatened woody species in three zones. The stress value was 0.002, and confidence ellipses were built at 95% confidence level

Ordination diagram of a NMDS of substitutes of 11 threatened woody species in three zones. The stress value was 0.002, and confidence ellipses were built at 95% confidence level

Discussion

This study assessed the traditional knowledge on threatened woody species (TWS) in the Atakora mountain chain region of Benin and its relationship with socio-demographic attributes of locals. It further evidences the substitute species as resource depletion adaptation. The diversity of TWS in the Atakora chain region is estimated at 117 species, representing about 4.17% of the national flora of Benin estimated at 2807 species [43]. About 12% of the identified TWS are red listed in Benin and in IUCN list, with Afraegle paniculata, Afzelia africana, Khaya grandifoliola, K. senegalensis, Milicia excelsa, Pterocarpus erinaceus, and Triplochiton scleroxylon, highly endangered in the country, the others being vulnerable [16]. These observations are supporting the status of Atakora region and its mountain chain, known to be a hotspot of biodiversity in Benin [15], hosting three endemic genera (Vitellaria, Pseudocedrela, and Haematostaphis) to the Sudanian zone, the two Beninese’s endemic plant species (Cyperus beninensis and Ipomoea beninensis), as well as Thunbergia atacorensis, an endangered species endemic to the inselbergs of Benin and Togo [16, 17]. The identified TWS are of different socio-economic importance to local people in Atakora region. K. senegalensis, P. biglobosa, V. paradoxa, and V. doniana were reported to be of high socio-economic importance to local people due to their use for multiple purposes including food, medicine, and culture, congruently to recent observation of Heubach [44]. Indeed, in the Atakora region, K. senegalensis is abundantly used as timber, fodder, and service wood and to some extent as medicine [45]. P. biglobosa is reported to contribute to up to 53% of income of nearly all households in the region of Atakora chain. Its fermented seeds are even richer in protein than meat [46] and are highly sought for seasoning soup [1]. V. doniana is a popular leafy vegetable with high economic importance, which sweet prune-like fruits are largely consumed and even sold whereas other parts of the plant are used in the treatment of various ailments [47]. V. paradoxa fruit’s pulp is edible and widely consumed by local people. The shea-butter obtained by processing its kernels is used in traditional medicine and cosmetic industry and is at the core of important national and international economic activities while its tree serves as fuelwood and building material [48]. However, the traditional ecological knowledge of TWS and their related socio-economic importance were influenced by geographical location, generation, and sociolinguistic group, supporting the general assumption that the relative importance of species and forest products to populations is context dependent [49]. In this study, there was a relatively higher traditional knowledge on TWS in East Atakora in comparison to other parts of the Atakora region. This discrepancy may be related to the availability of plant resources [30] and suggests that woody species might be more diverse and abundant in the East region than the others. Similarly, K. senegalensis and P. biglobosa were found to be most important TWS in the East Atakora while V. paradoxa and V. doniana were reported to be the most important in Central and West Atakora. The discrepancy in traditional ecological knowledge and its related importance were also observed within regions, ruled by age and sociolinguistic groups. With regard to age categories, the traditional knowledge on TWS was found to be higher with older people, evidencing a life learning process [50]. Finally, as also observed by Fandohan et al. [51] for Tamarindus indica in the same region, the traditional knowledge related to TWS varied among sociolinguistic groups, evidencing thus cultural-specific knowledge on TWS. As a result, future strategies for the conservation of TWS should account for geographical location, age, gender, and sociolinguistic groups to copy with the differences. Although local people in Atakora region showed extended knowledge on TWS, paradoxically, not all the TWS are of socio-economic importance to local people. These observations suggest that the threats to some woody species in Atakora regions may not be from direct pressure (overexploitation) from local people, but rather likely from indirect anthropogenic actions (e.g., forest degradation, urbanization), from global change (climate change, large conversion of landscape into farmlands), or from external sources (users from other regions, riparian to Atakora regions). Therefore, future strategies should take into account these diverse and specific threats to TWS. Whatever the threat sources, the TWS are under pressure with declining populations. Local people in Atakora develops TWS depletion adaptation strategy by using substitute plant species. The number of potential substitutes to TWS was particularly higher for some species (e.g., K. senegalensis, A. africana, and B. aethiopum), indicating a relatively high level of uses of these resources in this region and their ongoing rarefaction due to high human pressure. The substitutes to a given TWS varied with regions. For instance, P. erinaceus and T. indica were substitutes to A. africana in EA and WA, respectively, suggesting then that the mechanism of TWS substitution is spatial, probably driven socio-cultural considerations, availability and abundance of the substitute, and capacity of the substitute to adequately compensate and maximize the utility devoted to the primary TWS. In addition, the mechanism of TWS substitution appears to be temporally dynamic. Indeed, P. erinaceus reported to be substituted to A. africana and K. senegalensis during this study is getting very rare in the Atakora region with high conservation issues [52] and being replaced by Isoberlinia doka and I. tomentosa (Fabaceae) also mentioned as substitutes. From this study, the substitute species were selected mostly among the same pool of life form (tree and woody species), genera, or families to maximize the utility of the substitute. However, while guarantying the satisfaction, plant selection from the same pool may reduce the freedom level of choice and contribute to the selective depletion of plant groups (genera or families). To be sustainable, the mechanism of TWS substitution may go beyond the same pool and explore other functional groups. For instance, in Atakora regions, P. biglobosa was substituted with the soybean Glycine max while V. paradoxa was replaced by Arachis hypogea. The substitution pattern of P. biglobosa makes sense as soybean is rich enough to compensate the protein supply of the fermented and processed seeds of P. biglobosa which is a popular ingredient locally used in sauce. Overall, the substitution mechanism is not always a sustainable panacea for controlling the depletion of TWS, especially by selecting in a same pool of threatened species. However, the substitution of a perennial woody species by an annual plant could represent a sustainable alternative to slow down the decline of the TWS.

Conclusion

The study provides data on the diversity of, and local ecological knowledge on, threatened woody species currently found in the Atakora mountain chain region in Benin. Their families and genera vary with respect to the zone and informants showed a good level of knowledge about these species. Therefore, community-based management programs involving people from different areas, cultures, and ages for gender-sensitive experience sharing will be a judicious strategy for sustainable conservation of those threatened woody resources and their ecosystem in the study area. The most threatened species including Khaya senegalensis, Pterocarpus erinaceus, Borassus aethiopum, Anogeissus leiocarpa, and Diospyros mespiliformis need urgent conservation actions. We recommend ex-situ conservation of these species while promoting their integration into agroforestry-based systems. Local communities rely on a variety of substitutes as adaptation measure to the rarefaction of daily used species. The choice of surrogate is dynamic and evolves in space and time. Therefore, a threatened and socio-economically important species in one region may be a potential substitute in another, and minor species of today will likely become of great importance in the future. However, people develop unsustainable practices that compromise the survival of minor species which are prone to extinction, and in doing so, they may run out of substitutes later. Strategies for conservation of woody species should then target not only the socio-economically important threatened species but also the minor species, for the next generations. Furthermore, the central government, scientists, NGOs, and actors at different levels must be aware of their responsibility and crucial role in educating people to conserve nature as our universal common inheritance.
  5 in total

1.  Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s.

Authors:  H K Gibbs; A S Ruesch; F Achard; M K Clayton; P Holmgren; N Ramankutty; J A Foley
Journal:  Proc Natl Acad Sci U S A       Date:  2010-08-31       Impact factor: 11.205

2.  The use of plants in the medical system of the Fulni-ô people (NE Brazil): a perspective on age and gender.

Authors:  Ulysses Paulino de Albuquerque; Gustavo Taboada Soldati; Shana Sampaio Sieber; Marcelo Alves Ramos; Jemerson Caetano de Sá; Liliane Cunha de Souza
Journal:  J Ethnopharmacol       Date:  2010-11-18       Impact factor: 4.360

3.  Cocoa intensification scenarios and their predicted impact on CO₂ emissions, biodiversity conservation, and rural livelihoods in the Guinea rain forest of West Africa.

Authors:  Jim Gockowski; Denis Sonwa
Journal:  Environ Manage       Date:  2010-12-30       Impact factor: 3.266

4.  Ethnobotanical survey of medicinal plants commonly used by Kani tribals in Tirunelveli hills of Western Ghats, India.

Authors:  Muniappan Ayyanar; Savarimuthu Ignacimuthu
Journal:  J Ethnopharmacol       Date:  2011-02-01       Impact factor: 4.360

5.  Re-examining hypotheses concerning the use and knowledge of medicinal plants: a study in the Caatinga vegetation of NE Brazil.

Authors:  Ulysses Paulino de Albuquerque
Journal:  J Ethnobiol Ethnomed       Date:  2006-07-26       Impact factor: 2.733

  5 in total
  4 in total

1.  Species richness, cultural importance, and prioritization of wild spices for conservation in the Sudano-Guinean zone of Benin (West Africa).

Authors:  Konoutan Médard Kafoutchoni; Rodrigue Idohou; Anthony Egeru; Kolawolé Valère Salako; Clément Agbangla; Aristide Cossi Adomou; Achille Ephrem Assogbadjo
Journal:  J Ethnobiol Ethnomed       Date:  2018-11-15       Impact factor: 2.733

2.  Factors shaping local people's perception of ecosystem services in the Atacora Chain of Mountains, a biodiversity hotspot in northern Benin.

Authors:  Fidèle Tchossi Moutouama; Samadori Sorotori Honoré Biaou; Boateng Kyereh; Winston Adam Asante; Armand K Natta
Journal:  J Ethnobiol Ethnomed       Date:  2019-08-14       Impact factor: 2.733

3.  Local perception of ecosystem services and their conservation in Sudanian savannas of Burkina Faso (West Africa).

Authors:  Assétou Nabaloum; Dethardt Goetze; Amadé Ouédraogo; Stefan Porembski; Adjima Thiombiano
Journal:  J Ethnobiol Ethnomed       Date:  2022-02-19       Impact factor: 2.733

4.  The resource availability hypothesis (RAH) and cross-cultural patterns: which one explains West African Cochlospermum species' uses in Benin?

Authors:  Gnimansou Abraham Favi; Gbèwonmèdéa Hospice Dassou; Donald Djidohokpin; Jéronime Marie-Ange Sènamie Ouachinou; Chabi Ghyslain Kpétikou; Eutiche Gbedolo; Alain Anagonou; Noelia Hidalgo-Triana; Aristide Cossi Adomou
Journal:  J Ethnobiol Ethnomed       Date:  2022-08-23       Impact factor: 3.404

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.