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Projected Impact of Climate Change on Habitat Suitability of a Vulnerable Endemic Vachellia negrii (pic.serm.) kyal. & Boatwr (Fabaceae) in Ethiopia

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  • Arayaselassie Abebe Semu

    (Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa 1176, Ethiopia
    Range Ecology and Biodiversity Program, College of Agriculture and Environmental Sciences, Haramaya University, Dire Dawa 3000, Ethiopia)

  • Tamrat Bekele

    (Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa 1176, Ethiopia)

  • Ermias Lulekal

    (Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa 1176, Ethiopia)

  • Paloma Cariñanos

    (Andalusian Institute for Earth System Research (IISTA-CEAMA), 18002 Granada, Spain
    Department of Botany, University of Granada, 18002 Granada, Spain)

  • Sileshi Nemomissa

    (Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa 1176, Ethiopia)

Abstract

Species tend to shift their suitable habitat both altitudinally and latitudinally under climate change. Range shift in plants brings about habitat contraction at rear edges, forcing leading edge populations to explore newly available suitable habitats. In order to detect these scenarios, modeling of the future geographical distribution of the species is widely used. Vachellia negrii (Pic.-Serm.) Kyal. & Boatwr. is endemic to Ethiopia and was assessed as vulnerable due to changes to its habitat by anthropogenic impacts. It occurs in upland wooded grassland from 2000–3100 m.a.s.l. The main objective of this study is to model the distribution of Vachellia negrii in Ethiopia by using Maxent under climate change. Nineteen bioclimatic variables were downloaded from an open source. Furthermore, topographic position index (tpi), solar radiation index (sri) and elevation were used. Two representative concentration pathways were selected (RCP 4.5 and RC P8.5) for the years 2050 and 2070 using the Community Climate System Model (CCSM 5). A correlation analysis of the bioclimatic variables has resulted in the retention of 10 bioclimatic variables for modeling. Forty-eight occurrence points were collected from herbarium specimens. The area under curve (AUC) is 0.94, indicating a high-performance level of the model. The distribution of the species is affected by elevation (26.4%), precipitation of the driest month (Bio 14, 21.7%), solar radiation (12.9%) and precipitation seasonality (Bio15, 12.2%). Whereas the RCP 8.5 has resulted in decrease of suitable areas of the species from the current 4,314,153.94 ha (3.80%) to 4,059,150.90 ha (3.58%) in 2050, this area will shrink to 3,555,828.71 ha in 2070 under the same scenario. As climate change severely affects the environment, highly suitable areas for the growth of the study subject will decrease by 758,325 ha. The study’s results shows that this vulnerable, endemic species is facing habitat contraction and requires interventions to ensure its long-term persistence.

Suggested Citation

  • Arayaselassie Abebe Semu & Tamrat Bekele & Ermias Lulekal & Paloma Cariñanos & Sileshi Nemomissa, 2021. "Projected Impact of Climate Change on Habitat Suitability of a Vulnerable Endemic Vachellia negrii (pic.serm.) kyal. & Boatwr (Fabaceae) in Ethiopia," Sustainability, MDPI, vol. 13(20), pages 1-16, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11275-:d:655013
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    References listed on IDEAS

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    1. Schmidt, Heiko & Radinger, Johannes & Teschlade, Daniel & Stoll, Stefan, 2020. "The role of spatial units in modelling freshwater fish distributions: Comparing a subcatchment and river network approach using MaxEnt," Ecological Modelling, Elsevier, vol. 418(C).
    2. Pecchi, Matteo & Marchi, Maurizio & Burton, Vanessa & Giannetti, Francesca & Moriondo, Marco & Bernetti, Iacopo & Bindi, Marco & Chirici, Gherardo, 2019. "Species distribution modelling to support forest management. A literature review," Ecological Modelling, Elsevier, vol. 411(C).
    3. Godfrey Hewitt, 2000. "The genetic legacy of the Quaternary ice ages," Nature, Nature, vol. 405(6789), pages 907-913, June.
    4. H. Oğuz Çoban & Ömer K. Örücü & E. Seda Arslan, 2020. "MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    5. Shcheglovitova, Mariya & Anderson, Robert P., 2013. "Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes," Ecological Modelling, Elsevier, vol. 269(C), pages 9-17.
    6. Vincent Devictor & Chris van Swaay & Tom Brereton & Lluís Brotons & Dan Chamberlain & Janne Heliölä & Sergi Herrando & Romain Julliard & Mikko Kuussaari & Åke Lindström & Jiří Reif & David B. Roy & Ol, 2012. "Differences in the climatic debts of birds and butterflies at a continental scale," Nature Climate Change, Nature, vol. 2(2), pages 121-124, February.
    7. Dandan Zhao & Hong S. He & Wen J. Wang & Lei Wang & Haibo Du & Kai Liu & Shengwei Zong, 2018. "Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region," Sustainability, MDPI, vol. 10(3), pages 1-14, March.
    8. Ranjitkar, Sailesh & Xu, Jianchu & Shrestha, Krishna Kumar & Kindt, Roeland, 2014. "Ensemble forecast of climate suitability for the Trans-Himalayan Nyctaginaceae species," Ecological Modelling, Elsevier, vol. 282(C), pages 18-24.
    9. Romain Bertrand & Jonathan Lenoir & Christian Piedallu & Gabriela Riofrío-Dillon & Patrice de Ruffray & Claude Vidal & Jean-Claude Pierrat & Jean-Claude Gégout, 2011. "Changes in plant community composition lag behind climate warming in lowland forests," Nature, Nature, vol. 479(7374), pages 517-520, November.
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