Predicting the habitat suitability of Vitellaria paradoxa under climate change scenarios
Paper Details
Predicting the habitat suitability of Vitellaria paradoxa under climate change scenarios
Abstract
In Côte d’Ivoire, agroforestry parklands dominated by the Vitellaria paradoxa (shea tree) play a role in smallholder agriculture, soil conservation and food security within the Sudanian and Sudan–Guinean zones. Despite its ecological and socio-economic importance, this species, listed as Vulnerable by the IUCN, is increasingly threatened by overexploitation, habitat degradation, recurrent bush fires, poor natural regeneration and climate change, raising concerns about its long-term persistence. To assess the current and future distribution of V. paradoxa in Côte d’Ivoire, 135 occurrence records from the CNF herbarium and GBIF were modelled using multiple algorithms and WorldClim v2.1 bioclimatic variables under current and future climate scenarios (SSP245 and SSP585). Multicollinearity was reduced using Pearson correlation coefficients and variance inflation factors (|r| < 0.7; VIF < 8), and model performance was evaluated through bootstrap-based random subsampling (70% training, 30% validation) using AUC and TSS metrics. The results showed that eight predictors were retained, dominated by temperature variables, particularly temperature seasonality (45%), followed by precipitation. Temperature and precipitation are the dominant drivers, while wind plays a secondary role, indicating a narrow ecological niche and high sensitivity to climate change. Currently, suitable habitats cover 36,673 km² in northern and central Côte d’Ivoire. Projections indicate a northward expansion by 2050, reaching 179,568 km²under SSP-245-2050 and 144,338 km² under SSP-585-2050. They also reveal a more pronounced reduction in habitat suitability as the intensity of climate change increases. These results provide spatially explicit guidance for climate-adaptive agroforestry planning, identifying priority areas for conservation, regeneration, and sustainable shea-based expansion.
Allal F, Sanou H, Millet L, Vaillant A, Camus-Kulandaivelu L, Logossa ZA, Lefèvre F, Bouvet JM. 2011. Past climate changes explain the phylogeography of Vitellaria paradoxa over Africa. Heredity 107(2), 174–186. https://doi.org/10.1038/hdy.2011.5
Attikora AJP, Diarrassouba N, Yao SDM, De Clerck C, Silué S, Alabi T, Lassoisl L. 2023. Morphological traits and sustainability of plus shea trees (Vitellaria paradoxa C.F. Gaertn.) in Côte d’Ivoire. Biotechnologie, Agronomie, Société et Environnement.
Avaligbé YJF, Chabi F, Gnanglè CP, Bello OD, Yabi I, Ahoton L, Saïdou A. 2021. Modelling the current and future spatial distribution area of shea tree (Vitellaria paradoxa C.F. Gaertn.) in Benin under climate change. American Journal of Climate Change 10(3), 263–280. https://doi.org/10.4236/ajcc.2021.103012
Bhuyan A, Bawri A, Saikia BP, Baidya S, Hazarika S, Thakur B, Chetry V, Deka B, Bharali P, Prakash A, Sarma K, Devi A. 2025. Predicting habitat suitability of Illicium griffithii under climate change using an ensemble modelling approach. Scientific Reports 15(1), 9691. https://doi.org/10.1038/s41598-025-92815-x
Chevalier M, Zarzo-Arias A, Guélat J, Mateo RG, Guisan A. 2022. Accounting for niche truncation to improve spatial and temporal predictions of species distributions. Frontiers in Ecology and Evolution 10, 944116. https://doi.org/10.3389/fevo.2022.944116
Citores L, Ibaibarriaga L, Lee DJ, Brewer MJ, Santos M, Chust G. 2020. Modelling species presence–absence using shape-constrained GAMs in the ecological niche theory framework. Ecological Modelling 418, 108926. https://doi.org/10.1016/j.ecolmodel.2019.108926
Dakhil MA, Yang X, Yuan Z, Hao Z, Bebber DP, Halmy MWA. 2025. Ensemble modelling of dominant tree communities for smart afforestation planning in China. Landscape Ecology 40(11), 203. https://doi.org/10.1007/s10980-025-02223-9
Daru BH. 2025. Tracking hidden dimensions of plant biogeography from herbaria. New Phytologist. https://doi.org/10.1111/nph.70002
Deekshith ADA. 2016. Machine learning algorithms for predictive analytics: a review and evaluation. International Journal of Innovations in Engineering Research and Technology 3(12), 56–66. https://doi.org/10.26662/ijiert.v3i12.pp56-66
Doffou SC, Kouadio H, Dibi HN. 2021. Effets des variations climatiques à l’horizon 2050 sur la distribution de Tieghemella heckelii (Sapotaceae) en Côte d’Ivoire. International Journal of Biological and Chemical Sciences 15(2), 679–694. https://doi.org/10.4314/ijbcs.v15i2.23
Dyderski MK, Paź-Dyderska S, Jagodziński AM, Puchałka R. 2024. Shifts in native tree species distributions in Europe under climate change. Journal of Environmental Management 373, 123504. https://doi.org/10.1016/j.jenvman.2024.123504
El-Khalafy MM, Hatab AA, Al-Sodany YM, Shaltout KH, Bedair H. 2025. Assessing the environmental and conservation status of three endangered endemic plants under climate change in Egypt. BMC Plant Biology 25(1), 1203. https://doi.org/10.1186/s12870-025-07127-z
Ganglo JC. 2023. Ecological niche model transferability of Chrysophyllum albidum under climate and global changes. Scientific Reports 13(1), 2430. https://doi.org/10.1038/s41598-023-29048-3
Guillaumet JL, Adjanohoun E. 1971. La végétation de la Côte d’Ivoire. In Le milieu naturel de Côte d’Ivoire. Mémoires ORSTOM 50, 161–263.
Hamilton CW, Smithwick EAH, Spellman KV, Baltensperger AP, Spellman BT, Chi G. 2024. Predicting suitable habitat distribution of berry plants under climate change. Landscape Ecology 39(2), 18. https://doi.org/10.1007/s10980-024-01839-7
Hosseini N, Mehrabian A, Nasab FK, Mostafavi H, Ghorbanpour M. 2025. Forecasting climate change effects on the potential distribution of Zhumeria majdae. BMC Ecology and Evolution 25(1). https://doi.org/10.1186/s12862-025-02431-6
Jepsen T, Stopponi G, Jørgensen NOG. 2024. Vitellaria paradoxa agroforestry systems in Northern Ghana: population structure and below-canopy microclimate. Agroforestry Systems 98(6), 1493–1505. https://doi.org/10.1007/s10457-024-01019-1
Júnior PM, Nóbrega CC. 2018. Evaluating collinearity effects on species distribution models using virtual species. PLoS ONE 13(9), e0202403. https://doi.org/10.1371/journal.pone.0202403
Konowalik K, Nosol A. 2021. Evaluation metrics of presence-only SDMs using maps with varying coverage. Scientific Reports 11(1). https://doi.org/10.1038/s41598-020-80062-1
Kouassi J, Wandan N, Mbow C. 2022. Observed climate trends, perceived impacts and community adaptation practices in Côte d’Ivoire. Environmental & Socio-Economic Studies 10(3), 43. https://doi.org/10.2478/environ-2022-0016
Molano-Flores B, Johnson SA, Marcum PB, Feist MA. 2023. Using herbarium specimens to assist with rare plant listing. Frontiers in Conservation Science 4. https://doi.org/10.3389/fcosc.2023.1144593
Mushagalusa FC, Bauman DE, Bazirake BM, Mleci Y, Kalenga M, Shutcha MN, Meerts P. 2020. Phenotypic plasticity explains the wide niche of an African woodland tree. Environmental and Experimental Botany 178, 104186. https://doi.org/10.1016/j.envexpbot.2020.104186
Ploton P, Mortier F, Réjou-Méchain M, Barbier N, Picard N, Rossi V, Dormann CF, Cornu G, Viennois G, Bayol N, Lyapustin A, Gourlet-Fleury S, Pélissier R. 2020. Spatial validation reveals poor predictive performance of large-scale ecological mapping models. Nature Communications 11(1), 4540. https://doi.org/10.1038/s41467-020-18321-y
Ræbild A, Larsen AS, Jensen JS, Ouédraogo M, De Groote S, Van Damme P, Bayala J, Diallo BO, Sanou H, Kalinganiré A, Kjær ED. 2010. Advances in domestication of indigenous fruit trees in the Sahel. New Forests 41(3), 297–315. https://doi.org/10.1007/s11056-010-9237-5
Salamanca AJA, Navarro-Cerrillo RM, Quero-Pérez JL, Gallardo B, Crozier J, Stirling C, Sousa K, De González-Moreno P. 2023. Vulnerability of cocoa-based agroforestry systems to climate change in West Africa. Scientific Reports 13(1), 10033. https://doi.org/10.1038/s41598-023-37180-3
Senkoro AM, Draper D, Shackleton CM, Ribeiro-Barros AI, Voeks RA. 2024. A threatened medicinal tree with optimistic prospects under climate change. Global Ecology and Conservation 54, e03126. https://doi.org/10.1016/j.gecco.2024.e03126
Song L, Frazier AE, Kedron P, Araujo D, Cui D, Enquist BJ, Maitner B, Merow C, Moulatlet GM, Nikolopoulos EI, Roehrdanz PR. 2024. Explainable AI to interpret spatial impacts of future climate change on species distribution. https://doi.org/10.5703/1288284317811
Souza ML, Duarte AA, Lovato MB, Fagundes M, Valladares F, Filho JPL. 2018. Climate drivers of intraspecific leaf trait variation in a neotropical tree. PLoS ONE 13(12), e0208512. https://doi.org/10.1371/journal.pone.0208512
Tagliari MM, Danthu P, Tsy JLP, Cornu C, Lenoir J, Carvalho-Rocha V, Vieilledent G. 2021. Not all species will migrate poleward as climate warms: the seven baobabs of Madagascar. Global Change Biology 27(23), 6071–6085. https://doi.org/10.1111/gcb.15859
Tang CQ, Zhang ZY, Ding Z, Fang Y, Zhou R, Sun H, Chen X, Song K, He JS, Fang JY. 2022. Long-term stable refugia for dominant Castanopsis species in East Asia. Biological Conservation 273, 109663. https://doi.org/10.1016/j.biocon.2022.109663
Traoré S, Zo-Bi IC, Piponiot C, Aussenac R, Hérault B. 2023. Fragmentation is the main driver of residual forest aboveground biomass in West African low forest–high deforestation landscapes. Trees, Forests and People 15, 100477. https://doi.org/10.1016/j.tfp.2023.100477
Urbina-Cardona JN, Blair ME, Londoño MC, Loyola R, Velásquez-Tibatá J, Morales-Devia H. 2019. Species distribution modelling in Latin America: A 25-year review. Tropical Conservation Science 12. https://doi.org/10.1177/1940082919854058
White N, Parsons R, Collins GS, Barnett A. 2023. Evidence of questionable research practices in clinical prediction models. BMC Medicine 21(1). https://doi.org/10.1186/s12916-023-03048-6
Franck Placide Junior Pagny*, Anthelme Gnagbo, Dofoungo Kone, Blaise Kabré, Marie-Solange Tiébré6,, 2026. Predicting the habitat suitability of Vitellaria paradoxa under climate change scenarios. Int. J. Biosci., 28(1), 73-83.
Copyright © 2026 by the Authors. This article is an open access article and distributed under the terms and conditions of the Creative Commons Attribution 4.0 (CC BY 4.0) license.


