Predicting suitable habitats of the African cherry (Prunus africana) under climate change in Tanzania
(2020) In Atmosphere 11(9).- Abstract
Prunus africana is a fast-growing, evergreen canopy tree with several medicinal, household, and agroforestry uses, as well as ecological value for over 22 countries in sub-Saharan Africa. This species is under immense pressure from human activity, compounding its vulnerability to the effects of climate change. Predicting suitable habitats for P. africana under changing climate is essential for conservation monitoring and planning. This study intends to predict the impact of climate change on the suitable habitats for the vulnerable P. africana in Tanzania. We used maximum entropy modeling to predict future habitat distribution based on the representative concentration pathways scenario 4.5 and 8.5 for the mid-century 2050 and... (More)
Prunus africana is a fast-growing, evergreen canopy tree with several medicinal, household, and agroforestry uses, as well as ecological value for over 22 countries in sub-Saharan Africa. This species is under immense pressure from human activity, compounding its vulnerability to the effects of climate change. Predicting suitable habitats for P. africana under changing climate is essential for conservation monitoring and planning. This study intends to predict the impact of climate change on the suitable habitats for the vulnerable P. africana in Tanzania. We used maximum entropy modeling to predict future habitat distribution based on the representative concentration pathways scenario 4.5 and 8.5 for the mid-century 2050 and late-century 2070. Species occurrence records and environmental variables were used as a dependent variable and predictor variables respectively. The model performance was excellent with the area under curve (AUC) and true skill statistics (TSS) values of 0.96 and 0.85 respectively. The mean annual temperature (51.7%) and terrain ruggedness. index (31.6%) are the most important variables in predicting the current and future habitat distribution for P. africana. Our results show a decrease in suitable habitats for P. africana under all future representative concentration pathways scenario when compared with current distributions. These results have policy implications for over 22 countries of sub-Saharan Africa that are facing problems associated with the sustainability of this species. Institutional, policy, and conservation management approaches are proposed to support sustainable practices in favor of P. africana.
(Less)
- author
- Giliba, Richard A. and Yengoh, Genesis Tambang LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Climate change, Conservation, Habitat suitability, P. africana, Species distribution
- in
- Atmosphere
- volume
- 11
- issue
- 9
- article number
- 988
- publisher
- MDPI AG
- external identifiers
-
- scopus:85094149598
- ISSN
- 2073-4433
- DOI
- 10.3390/atmos11090988
- language
- English
- LU publication?
- yes
- id
- 0679e1ad-d680-4379-babe-d405d79aa4c7
- date added to LUP
- 2020-11-10 10:23:06
- date last changed
- 2022-04-19 01:53:05
@article{0679e1ad-d680-4379-babe-d405d79aa4c7,
abstract = {{<p>Prunus africana is a fast-growing, evergreen canopy tree with several medicinal, household, and agroforestry uses, as well as ecological value for over 22 countries in sub-Saharan Africa. This species is under immense pressure from human activity, compounding its vulnerability to the effects of climate change. Predicting suitable habitats for P. africana under changing climate is essential for conservation monitoring and planning. This study intends to predict the impact of climate change on the suitable habitats for the vulnerable P. africana in Tanzania. We used maximum entropy modeling to predict future habitat distribution based on the representative concentration pathways scenario 4.5 and 8.5 for the mid-century 2050 and late-century 2070. Species occurrence records and environmental variables were used as a dependent variable and predictor variables respectively. The model performance was excellent with the area under curve (AUC) and true skill statistics (TSS) values of 0.96 and 0.85 respectively. The mean annual temperature (51.7%) and terrain ruggedness. index (31.6%) are the most important variables in predicting the current and future habitat distribution for P. africana. Our results show a decrease in suitable habitats for P. africana under all future representative concentration pathways scenario when compared with current distributions. These results have policy implications for over 22 countries of sub-Saharan Africa that are facing problems associated with the sustainability of this species. Institutional, policy, and conservation management approaches are proposed to support sustainable practices in favor of P. africana.</p>}},
author = {{Giliba, Richard A. and Yengoh, Genesis Tambang}},
issn = {{2073-4433}},
keywords = {{Climate change; Conservation; Habitat suitability; P. africana; Species distribution}},
language = {{eng}},
number = {{9}},
publisher = {{MDPI AG}},
series = {{Atmosphere}},
title = {{Predicting suitable habitats of the African cherry (Prunus africana) under climate change in Tanzania}},
url = {{http://dx.doi.org/10.3390/atmos11090988}},
doi = {{10.3390/atmos11090988}},
volume = {{11}},
year = {{2020}},
}