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Present and future distribution of Faidherbia albida in Cabo Verde as revealed by climatic modelling and LULC analysis

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Resumo:Climate change poses one of the most significant challenges to conserve biodiversity, especially in tropical dry islands, as is the case of Cabo Verde (northeast Atlantic Ocean). This archipelago has a low percentage of forest cover and hosts only seven native tree species, among them, Faidherbia albida (Delile) A.Chev. (Fabaceae). Therefore, protective afforestation is extremely important in Cabo Verde, one of the most vulnerable West African countries to climate change. With this work, we aimed to estimate the current distribution and potential shifts in suitable areas for F. albida under climate change, using species distribution models (i.e., random forest, generalized linear and additive models), covering its distribution range in Cabo Verde and mainland Africa. The best model was then projected for the studied area, at two different slice times, using Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. Based on current bioclimatic variables, we estimated that almost two thirds of Cabo Verde’s territory is highly suitable for F. albida, which contrasts with its current occurrence. By overlaying the present habitat suitability with land use and land cover data, we concluded that habitat availability and suitability could be constrained by that factor. On average, the predicted suitable habitat for future distributions gradually decreases by 2080 under both scenarios compared with the current, with a smaller effect of RCP4.5 than of RCP8.5. Local authorities can benefit from this research and develop actions to promote sustainable reforestation in Cabo Verde, which should include native tree species that are best adapted to the local climate and could thus contribute to mitigate the effects of climate change.
Autores principais:Varela, Danilson Mascarenhas
Outros Autores:Romeiras, Maria M.; Silva, Luís
Assunto:Cabo Verde climate change habitat suitability native tree species species distribution models tropical dry islands West Africa Ecology, Evolution, Behavior and Systematics Ecology SDG 13 - Climate Action SDG 15 - Life on Land
Ano:2023
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:Climate change poses one of the most significant challenges to conserve biodiversity, especially in tropical dry islands, as is the case of Cabo Verde (northeast Atlantic Ocean). This archipelago has a low percentage of forest cover and hosts only seven native tree species, among them, Faidherbia albida (Delile) A.Chev. (Fabaceae). Therefore, protective afforestation is extremely important in Cabo Verde, one of the most vulnerable West African countries to climate change. With this work, we aimed to estimate the current distribution and potential shifts in suitable areas for F. albida under climate change, using species distribution models (i.e., random forest, generalized linear and additive models), covering its distribution range in Cabo Verde and mainland Africa. The best model was then projected for the studied area, at two different slice times, using Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. Based on current bioclimatic variables, we estimated that almost two thirds of Cabo Verde’s territory is highly suitable for F. albida, which contrasts with its current occurrence. By overlaying the present habitat suitability with land use and land cover data, we concluded that habitat availability and suitability could be constrained by that factor. On average, the predicted suitable habitat for future distributions gradually decreases by 2080 under both scenarios compared with the current, with a smaller effect of RCP4.5 than of RCP8.5. Local authorities can benefit from this research and develop actions to promote sustainable reforestation in Cabo Verde, which should include native tree species that are best adapted to the local climate and could thus contribute to mitigate the effects of climate change.