Using species distribution models to assess the importance of Egypt’s Protected Areas for the conservation of medicinal plants

Kaky, Emad; Gilbert, Francis

Abstract

Human activities affect the distribution and abundance of plants, with impacts on ecosystem services and human well-being; it is thus vital that a network of Protected Areas is capable of conserving plants that are useful. Using the species distribution (SDM) model algorithm MaxEnt, we tested whether Egypt's network of Protected Areas performs well in conserving the region's important medicinal plant species. We constructed individual SDMs for each species, and then combined the models into a single ‘species-richness’ layer, which we then compared to the distribution of the existing Protected Areas. Temperature was the most important of eleven predictor variables used to build the SDMs. Assuming the SDM's prediction of suitable habitat was accurate and corresponded to the occurrence each of the medicinal plant species, then on average species richness was significantly higher within than outside the Protected Areas. Based on our findings, Egypt's Protected Areas are effective at conserving its medicinal plants.

Citation

Kaky, E., & Gilbert, F. (in press). Using species distribution models to assess the importance of Egypt’s Protected Areas for the conservation of medicinal plants. Journal of Arid Environments, 135, https://doi.org/10.1016/j.jaridenv.2016.09.001

• Journal Article Type: Article
• Acceptance Date: Sep 13, 2016
• Online Publication Date: Sep 21, 2016
• Deposit Date: Oct 3, 2016
• Publicly Available Date: Oct 3, 2016
• Journal: Journal of Arid Environments
• Print ISSN: 0140-1963
• Electronic ISSN: 1095-922X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 135
• DOI: https://doi.org/10.1016/j.jaridenv.2016.09.001
• Keywords: MaxEnt; Egypt; Ecosystem services; Conservation
• Public URL: https://nottingham-repository.worktribe.com/output/809999
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S0140196316301616
• Contract Date: Oct 3, 2016