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Potential future distribution shifts for Afzelia africana Sm. ex Pers. and Pterocarpus erinaceus Poir. in the context of climate change in Benin

Open Access
|Oct 2025

References

  1. Adomou, A.C., Akoègninou, A., Sinsin, B., de Foucault, B., van der Maesen, L.J.G. 2009. Semi-deciduous forest remnants in Benin: patterns and floristic characterisation. – Acta Botanica Gallica, 156(2), 159–171.
  2. AFR100 (African Forest Landscape Restoration Initiative). 2022. Benin Country Profile. Factsheet-Forests4Future Benin. [WWW document]. – URL https://afr100.org. [Accessed 3 September 2024].
  3. Agbodan, K.M.L., Akodewou, A., Amegnaglo, K.B., Bawa, A., Akpavi, S., Akpagana, K. 2023. Ethnobotanical survey on threatened medicinal plants in Togo. – Moroccan Journal of Agricultural Sciences, 4(4), 164176.
  4. Akoègninou, A., van der Burg, W.J., van der Maesen, L.J.G. 2006. Analytical Flora of Benin. (Flore Analytique du Bénin). Leiden, Netherlands, Backhuys Publishers. 1034 pp. (In French).
  5. Bamigboye, S.O., Jimoh, M.O., Lawal, F.A., Osiyemi, Z.T., Laubscher, C.P., Kambizi, L. 2024. Utilization of Afzelia africana Sm. ex Pers. (Magnoliopsida: Fabales: Fabaceae) in Nigeria and its implications for conservation. – Journal of Threatened Taxa, 16(2), 24795–24803. https://doi.org/10.11609/jott.8582.16.2.24795-24803.
  6. Boakye, E.A., Ceesay, A., Osemwegie, I., Kapoury, S., Hounkpevi, A., Matchi, I.I., Tetteh, E.N. 2023. Climate change has limited effect on the growth of Afzelia africana Sm. and Anogeissus leiocarpus (DC.) Guill. and Perr. in riparian forests in the savannas of Ghana. – Forestry, 96(3), 316–325. https://doi.org/10.1093/forestry/cpac057.
  7. Camenen, E. 2015. Understanding tree invasions under climate change: a modelling approach. – Master thesis. Bordeaux, France, Université de Bordeaux. 64 pp.
  8. DIVA-GIS. 2023. Free spatial data by country. [WWW document]. – URL http://www.divagis.org/datadown. [Accessed 9 September 2024].
  9. Dowling, C.R. 2015. Using Maxent modeling to predict habitat of mountain pine beetle in response to climate change. – Master thesis. University of Southern California, Faculty of the USC Graduate School. 58 pp.
  10. Duvall, C.S. 2008. Pterocarpus erinaceus Poir. – Louppe, D., Oteng-Amoako, A.A., Brink, M. (eds.). Plant Resources of Tropical Africa 7(1). Timbers 1. PROTA Foundation, Wageningen, Netherlands. Leiden, Backhuys Publishers, 478–482.
  11. Ekka, P., Patra, S., Upreti, M., Kumar, G., Kumar, A., Saikia, P. 2023. Land degradation and its impacts on biodiversity and ecosystem services. – Raj, A., Jhariya, M.K., Banerjee, A., Nema, S., Bargali, K. (eds.). Land and Environmental Management through Forestry. Hoboken, NJ, USA, Wiley and Scrivener Publishing LLC, 77–101.
  12. Fandohan, A.B., Oduor, A.M.O., Sodé, A.I., Wu, L., Cuni-Sanchez, A., Assédé, E., Gouwakinnou, G.N. 2015. Modeling vulnerability of protected areas to invasion by Chromolaena odorata under current and future climates. – Ecosystem Health and Sustainability, 1(6), 20. https://doi.org/10.1890/EHS15-0003.1.
  13. FAO (Food and Agriculture Organization of the United Nations). 2022. The State of the World’s Forests 2022. Forest pathways for green recovery and building inclusive, resilient and sustainable economies. Rome, Italy, FAO. 141 pp.
  14. Feng, X., Peterson, A.T., Aguirre-López, L.J., Burger, J.R., Chen, X., Papeş, M. 2024. Rethinking ecological niches and geographic distributions in face of pervasive human influence in the Anthropocene. – Biological Reviews, 99(4), 1481–1503. https://doi.org/10.1111/brv.13077.
  15. Fick, S.E., Hijmans, R.J. 2017. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. – International Journal of Climatology, 37(12), 4302–4315. https://doi.org/10.1002/joc.5086.
  16. GEOLocate. 2023. Software for georeferencing biodiversity data. [WWW document]. – URL https://www.geo-locate.org/. [Accessed 7 September 2024].
  17. Gérard, J., Louppe, D. 2011. Afzelia africana Sm. ex Pers. Record from PROTA4U. – Lemmens, R.H.M.J., Louppe, D., Oteng-Amoako, A.A. (eds.). PROTA (Plant Resources of Tropical Africa / Ressources végétales de l’Afrique tropicale), Wageningen, Netherlands. [WWW document]. – URL https://prota.prota4u.org. [Accessed 16 October 2024].
  18. GLCF. 2023. Global Land Cover Facility (GLCF). [WWW document]. – URL https://geog.umd.edu/. [Accessed 2 October 2024].
  19. Global Forest Watch. 2023. Global Forest Watch’s 2023 tree cover loss data explained. [WWW document]. – URL https://www.globalforestwatch.org/blog/data-and-tools/2023-tree-cover-loss-data-explained/. [Accessed 2 October 2024].
  20. Guillera-Arroita, G., Lahoz-Monfort, J.J., Elith, J., Gordon, A., Kujala, H., Lentini, P.E., McCarthy, M.A., Tingley, R., Wintle, B.A. 2015. Is my species distribution model fit for purpose? Matching data and models to applications. - Global Ecology and Biogeography, 24(3), 276–292. https://doi.org/10.1111/geb.12268.
  21. Gyamfi, B.A., Adebayo, T.S., Bekun, F.V., Agboola, M.O. 2023. Sterling insights into natural resources intensification, ageing population and globalization on environmental status in Mediterranean countries. – Energy & Environment, 34(5), 1471–1491.
  22. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A. 2005. Very high resolution interpolated climate surfaces for global land areas. – International Journal of Climatology, 25(15), 1965–1978. https://doi.org/10.1002/joc.1276.
  23. Hills, R. 2020. Afzelia africana. The IUCN Red List of Threatened Species 2020: e.T33032A67742420. [WWW document]. – URL https://dx.doi.org/10.2305/IUCN.UK.2020-3.RLTS.T33032A67742420.en. [Accessed 11 November 2024].
  24. Houehanou, T.D., Prinz, K., Koua, D., Hellwig, F., Ebou, A., Gouwakinnou, G., Assogbadjo, A.E., Glele Kakaï, R.L., Zézé, A. 2023. Genetic diversity and population structure of a threatened tree species Afzelia africana Sm. ex Pers. among climatic zones for conservation challenges in Benin (West Africa). – Genetic Resources and Crop Evolution, 70, 1617–1632. https://doi.org/10.1007/s10722-022-01523-2.
  25. Idohou, R., Assogbadjo, A.E., Glèlè-Kakaï, R., Peterson, A.T. 2017. Spatio-temporal dynamic of suitable areas for species conservation in West Africa: eight economically important wild palms under present and future climates. – Agroforestry Systems, 91, 527–540. https://doi.org/10.1007/s10457-016-9955-6.
  26. Inatimi, S.A. 2023. The need to conserve and protect forest resources: African perspective. – Izah, S.C., Ogwu, M.C. (eds.). Sustainable Utilization and Conservation of Africa’s Biological Resources and Environment. Singapore, Springer, 203–233.
  27. IPCC. 2013. Climate change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK, New York, USA, Cambridge University Press. 1535 pp.
  28. IPCC. 2021. Climate Change 2021: The Physical Science Basis. Working Group I Contribution to the IPCC Sixth Assessment Report. Cambridge, UK, New York, USA. [WWW document]. – URL https://www.ipcc.ch/report/ar6/wg1/. [Accessed 4 October 2024].
  29. Kakpo, S.B., Aoudji, A.K.N., Gnanguènon-Guéssè, D., Gbètoho, A.J., Koura, K., Djotan, G.K., Ganglo, J.C. 2021. Spatial distribution and impacts of climate change on Milicia excelsa in Benin, West Africa. – Journal of Forestry Research, 32(1), 143–150. https://doi.org/10.1007/s11676-019-01069-7.
  30. Knoke, T., Hanley, N., Roman-Cuesta, R.M., Groom, B., Venmans, F., Paul, C. 2023. Trends in tropical forest loss and the social value of emission reductions. – Nature Sustainability, 6(11), 1373–1384. https://doi.org/10.1038/s41893-023-01175-9.
  31. Lim, C., Kang, J.H., Bayartogtokh, B., Bae, Y.J. 2024. Climate change will lead to range shifts and genetic diversity losses of dung beetles in the Gobi Desert and Mongolian Steppe. – Scientific Reports, 14(1), 15639. https://doi.org/10.1038/s41598-024-66260-1.
  32. Lissovsky, A.A., Dudov, S.V. 2021. Species-distribution modeling: advantages and limitations of its application. 2. MaxEnt. – Biology Bulletin Reviews, 11(3), 265–275.
  33. Lobo, J.M., Jiménez-Valverde, A., Real, R. 2008. AUC: a misleading measure of the performance of predictive distribution models. – Global Ecology Biogeography, 17(2), 145–151. https://doi.org/10.1111/j.1466-8238.2007.00358.x.
  34. Maclean, I.M.D., Early, R. 2023. Macroclimate data overestimate range shifts of plants in response to climate change. – Nature Climate Change, 13, 484–490. https://doi.org/10.1038/s41558-023-01650-3.
  35. Monzón, J., Moyer-Horner, L., Palamar, M.B. 2011. Climate change and species range dynamics in protected areas. – BioScience, 61(10), 752–761. https://doi.org/10.1525/bio.2011.61.10.5.
  36. Ndukwe, G.I., Gabriel, B.O., Okhiku, J.O., Obomanu, F.G. 2023. Afzelia africana seed extract: toxicity, antidiarrhoeal and chemical assays. – Algerian Journal of Natural Products, 11(1), 944–951.
  37. Ngwa, A.N. 2023. Management constraints and perspectives for sustainable use of Pterocarpus erinaceus in Cameroon case study: the benue division of the north region. – Master thesis. Seville, Spain, International University of Andalucía (UNIA). 81pp.
  38. Nodza, G.I., Tochukwu, E., Igbari, A.D., Onuminya, T.O., Ogundipe, O.T. 2024. Application of IUCN Red List criteria for assessment of some savanna trees of Nigeria, West Africa. Version 1. [WWW document]. – URL https://doi.org/10.21203/rs.3.rs-4187370/v1. [Accessed 5 August 2024]. (Preprint).
  39. Orwa, C., Mutua, A., Kindt, R., Jamnadass, R., Anthony, S. 2009. Agroforestree Database: a tree reference and selection guide version 4.0. Pterocarpus erinaceus. [WWW document]. – URL http://www.worldagroforestry.org/treedb/AFTPDFS/Pterocarpus_erinaceus.PDF. [Accessed 7 September 2024].
  40. Pearson, R.G. 2010. Species’ Distribution Modeling for Conservation Educators and Practitioners. American Museum of Natural History. Lessons in Conservation, 3, 54–89. [WWW document]. – URL http://ncep.amnh.org. [Accessed 9 September 2024].
  41. Peterson, A.T., Papeş, M., Soberón, J. 2008. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. – Ecological Modelling, 213(1), 63–72. https://doi.org/10.1016/j.ecolmodel.2007.11.008.
  42. Peterson, A.T., Soberón, J., Pearson, R.G., Anderson, R.P., Martínez-Meyer, E., Nakamura, M., Araújo, M.B. 2011. Ecological Niches and Geographic Distributions. Princeton, Princeton University Press. 328 pp.
  43. Peterson, A.T., Yao, Y., Cobos, M.E., Xiao, X. 2024. Correlative ecological niche model applications to predicting landscape-scale woody plant encroachment in Kansas tallgrass prairie systems. – PLoS ONE, 19(6), e0305168. https://doi.org/10.1371/
  44. Phillips, S.J., Anderson, R.P., Schapire, R.E. 2006. Maximum entropy modeling of species geographic distributions. – Ecological Modelling, 190(3–4), 231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026.
  45. Rabiou, H., Diouf, A., Bationo, B.A., Mahamane, A., Segla, K.N., Adjonou, K., Radji, R., Kokutse, A.D., Kokou, K., Saadou, M. 2015. Demographic structure of natural population and spatial distribution of Pterocarpus erinaceus Poir seedlings in the Tiogo forest in the Sudanian zone of Burkina Faso. (Structure démographique de peuplement naturel et répartition spatiale des plantules de Pterocarpus erinaceus Poir. dans la forêt de Tiogo en zone soudanienne du Burkina Faso). - International Journal of Biological and Chemical Sciences, 9(1), 69–81. http://dx.doi.org/10.4314/ijbcs.v9i1.7. (In French).
  46. Redon, M., Luque, S. 2011. Presence-only modelling for indicator species distribution: Biodiversity monitoring in the French Alps. – Proceedings of the 6th Spatial Analysis and Geomatics International Conference (SAGEO 2010), France, Nov. 2010. Toulouse, 42–55.
  47. Rubenstein, M.A., Weiskopf, S.R., Bertrand, R., Carter, S.L., Comte, L., Eaton, M.J., Johnson, C.G., Lenoir, J., Lynch, A.J., Miller, B.W., Morelli, T.L., Rodriguez, M.A., Terando, A., Thompson, L.M. 2023. Climate change and the global redistribution of biodiversity: substantial variation in empirical support for expected range shifts. – Environmental Evidence, 12, 7. https://doi.org/10.1186/s13750-023-00296-0.
  48. Sakketa, T.G. 2023. Urbanisation and rural development in sub-Saharan Africa: A review of pathways and impacts. – Research in Globalization, 6, 100133. https://doi.org/10.1016/j.resglo.2023.100133.
  49. Sanchez, A.C., Osborne, P.E., Haq, N. 2011. Climate change and the African baobab (Adansonia digitata L.): the need for better conservation strategies. – African Journal of Ecology, 49(2), 234–245. https://doi.org/10.1111/j.1365-2028.2011.01257.x.
  50. Sanneh, O. 2023. Assessing natural regeneration of Pterocarpus erinaceus in Kiang West National Park, The Gambia. – Master thesis. Baeza, Spain, International University of Andalucía (UNIA). 45 pp.
  51. Shah, M.I., Abbas, S., Olohunlana, A.O., Sinha, A. 2023. The impacts of land use change on biodiversity and ecosystem services: An empirical investigation from highly fragile countries. – Sustainable Development, 31(3), 1384–1400. https://doi.org/10.1002/sd.2454.
  52. Sher, H., Ali, A., Sher, H., Bussmann, R.W., Rahman, I.U., Ullah, H., Ali, A., Ullah, Z. 2023. Sustainability and socio-economic impacts of plant resources utilization in Valley Lalku, District Swat, Pakistan. – Ethnobotany Research and Applications, 26, 1–18.
  53. Taylor, K.E., Stouffer, R.J., Meehl, G.A. 2012. An overview of CMIP5 and the experiment design. – Bulletin of the American Meteorological Society, 93(4), 485–498. https://doi.org/10.1175/BAMS-D-11-00094.1.
  54. Warren, D.L., Glor, R.E., Turelli, M. 2010. ENMTools: a toolbox for comparative studies of environmental niche models. – Ecography, 33(3), 607–611. https://doi.org/10.1111/j.1600-0587.2009.06142.x.
  55. WRI (World Resources Institute). 2023. Global Forest Review: 2023 update on forest loss. [WWW document]. – URL https://www.globalforestwatch.org. [Accessed 4 October 2024].
  56. Wudu, K., Abegaz, A., Ayele, L., Ybabe, M. 2023. The impacts of climate change on biodiversity loss and its remedial measures using nature based conservation approach: a global perspective. – Biodiversity and Conservation, 32, 3681–3701. https://doi.org/10.1007/s10531-023-02656-1.
  57. Xu, Q., Wang, X., Yi, J., Wang, Y. 2024. Bias correction in species distribution models based on geographic and environmental characteristics. – Ecological Informatics, 81, 102604. https://doi.org/10.1016/j.ecoinf.2024.102604.
DOI: https://doi.org/10.2478/fsmu-2024-0012 | Journal eISSN: 1736-8723 | Journal ISSN: 1406-9954
Language: English
Page range: 37 - 50
Published on: Oct 30, 2025
Published by: Estonian University of Life Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2025 Donald Romaric Yehouenou Tessi, Sunday Berlioz Kakpo, Jean Ganglo, published by Estonian University of Life Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.