Predicting suitable habitats of the African cherry (Prunus africana) under climate change in Tanzania

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Predicting suitable habitats of the African cherry (Prunus africana) under climate change in Tanzania. / Giliba, Richard A.; Yengoh, Genesis Tambang.
in: Atmosphere, Jahrgang 11, Nr. 9, 988, 15.09.2020.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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@article{a32bb16ac5e84551b6d9e2215344347a,
title = "Predicting suitable habitats of the African cherry (Prunus africana) under climate change in Tanzania",
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 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.",
keywords = "Climate change, Conservation, Habitat suitability, P. africana, Species distribution, Ecosystems Research, Biology",
author = "Giliba, {Richard A.} and Yengoh, {Genesis Tambang}",
note = "The authors acknowledge the occurrence data providers Tanzania Forest Service Agency, Global Biodiversity Information Facility and TROPICOS. Further, the authors are grateful to Mathew Mpanda for his valuable suggestions and comments on the manuscripts. Finally, the authors are grateful to Elikana John for his guidance to access the soils data. Publisher Copyright: {\textcopyright} 2020 by the authors.",
year = "2020",
month = sep,
day = "15",
doi = "10.3390/atmos11090988",
language = "English",
volume = "11",
journal = "Atmosphere",
issn = "2073-4433",
publisher = "MDPI AG",
number = "9",

}

RIS

TY - JOUR

T1 - Predicting suitable habitats of the African cherry (Prunus africana) under climate change in Tanzania

AU - Giliba, Richard A.

AU - Yengoh, Genesis Tambang

N1 - The authors acknowledge the occurrence data providers Tanzania Forest Service Agency, Global Biodiversity Information Facility and TROPICOS. Further, the authors are grateful to Mathew Mpanda for his valuable suggestions and comments on the manuscripts. Finally, the authors are grateful to Elikana John for his guidance to access the soils data. Publisher Copyright: © 2020 by the authors.

PY - 2020/9/15

Y1 - 2020/9/15

N2 - 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.

AB - 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.

KW - Climate change

KW - Conservation

KW - Habitat suitability

KW - P. africana

KW - Species distribution

KW - Ecosystems Research

KW - Biology

UR - http://www.scopus.com/inward/record.url?scp=85094149598&partnerID=8YFLogxK

U2 - 10.3390/atmos11090988

DO - 10.3390/atmos11090988

M3 - Journal articles

AN - SCOPUS:85094149598

VL - 11

JO - Atmosphere

JF - Atmosphere

SN - 2073-4433

IS - 9

M1 - 988

ER -

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