Climate Change Impacts on <i>Faidherbia albida</i> (Delile) A. Chev. Distribution in Dry Lands of Ethiopia

Noulèkoun, Florent; Chude, Stella; Zenebe, Amanuel; Birhane, Emiru

doi:10.1111/aje.12345

Cited by 14 publications

(7 citation statements)

References 31 publications

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“…4A). We believed these shifts probably related to BIO14 decline from current to 2050, and BIO19 increase from current to 2070, and similar associations have also been found in other species (Bueno et al, 2017; Deb et al, 2017; Noulekoun et al, 2017; Wu et al, 2017).…”

Section: Resultssupporting

confidence: 82%

Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

Tang

Wang

et al. 2019

PeerJ

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Background As global climate change accelerates, ecologists and conservationists are increasingly investigating changes in biodiversity and predicting species distribution based on species observed at sites, but rarely consider those plant species that could potentially inhabit but are absent from these areas (i.e., the dark diversity and its distribution). Here, we estimated the dark diversity of vascular plants in China and picked up threatened dark species from the result, and applied maximum entropy (MaxEnt) model to project current and future distributions of those dark species in their potential regions (those regions that have these dark species). Methods We used the Beals probability index to estimate dark diversity in China based on available species distribution information and explored which environmental variables had significant impacts on dark diversity by incorporating bioclimatic data into the random forest (RF) model. We collected occurrence data of threatened dark species (Eucommia ulmoides, Liriodendron chinense, Phoebe bournei, Fagus longipetiolata, Amentotaxus argotaenia, and Cathaya argyrophylla) and related bioclimatic information that can be used to predict their distributions. In addition, we used MaxEnt modeling to project their distributions in suitable areas under future (2050 and 2070) climate change scenarios. Results We found that every study region’s dark diversity was lower than its observed species richness. In these areas, their numbers of dark species are ranging from 0 to 215, with a generally increasing trend from western regions to the east. RF results showed that temperature variables had a more significant effect on dark diversity than those associated with precipitation. The results of MaxEnt modeling showed that most threatened dark species were climatically suitable in their potential regions from current to 2070. Discussions The results of this study provide the first ever dark diversity patterns concentrated in China, even though it was estimated at the provincial scale. A combination of dark diversity and MaxEnt modeling is an effective way to shed light on the species that make up the dark diversity, such as projecting the distribution of specific dark species under global climate change. Besides, the combination of dark diversity and species distribution models (SDMs) may also be of value for ex situ conservation, ecological restoration, and species invasion prevention in the future.

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Section: Resultssupporting

confidence: 82%

Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

Tang

Wang

et al. 2019

PeerJ

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“…Evaluating the impacts of global climate change scenarios on the potential distributions of economically or ecologically essential species will be helpful to understanding the relationships between species niches and the corresponding environment, identifying priority cultivation areas of target species, and setting up effective strategies for species conservation and resource utilization [45][46][47][48]. MaxEnt has been commonly implemented for many species to predict potential distribution [49][50][51][52][53]. The results show that the MaxEnt model for J. regia provided an AUC value of 0.843, indicating a reliable prediction, which is consistent with previous studies [54][55][56].…”

Section: Discussionmentioning

confidence: 99%

Predicting Shifts in the Suitable Climatic Distribution of Walnut (Juglans regia L.) in China: Maximum Entropy Model Paves the Way to Forest Management

Zhang

Yue

et al. 2018

Forests

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Cultivation of woody oil plants in environmentally suitable habitats is a successful ecological solution for oil development and forest management. In this study, we predicted the influences of future climate change on the potentially suitable climatic distribution of an important woody oil plant species (walnut; Juglans regia L.) in China based on given climate change scenarios and the maximum entropy (MaxEnt) model. The MaxEnt model showed that the minimum temperature of the coldest month and annual precipitation were the most important determinant variables limiting the geographical distribution of J. regia. We have found that the current suitable environmental habitat of J. regia is mainly distributed in central and southwestern China. Results of the MaxEnt model showed that global warming in the coming half-century may lead to an increase in the area size of environmentally suitable habitats for J. regia in China, indicating more lands available for artificial cultivation and oil production. However, those suitable habitat gains may be practically inaccessible due to over-harvest and urban development, and effective management strategies are urgently needed to establish those forests. This research will provide theoretical suggestions for the protection, cultivation management, and sustainable utilization of J. regia resources to face the challenge of global climate change.

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“…The medium suitable area, on the other hand, will increase, thus globally reducing the area by only 10-14%. Even though the direct consequences of climate change indicated by the models are not severe, it is vital to consider all the impacts on the biosphere on a global scale, particularly in Africa, where climate change is expected to be more severe than in other parts of the globe (Fick and Hijmans, 2017;Noulèkoun et al, 2017;IPCC, 2018aIPCC, ,b, 2022.…”

Section: Discussionmentioning

confidence: 99%

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

2023

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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.

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Climate Change Impacts on Faidherbia albida (Delile) A. Chev. Distribution in Dry Lands of Ethiopia

Cited by 14 publications

References 31 publications

Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

Predicting Shifts in the Suitable Climatic Distribution of Walnut (Juglans regia L.) in China: Maximum Entropy Model Paves the Way to Forest Management

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

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