Species distribution modelling of Egyptian plants under climate change

It is thought that climate change will have a major impact on species distributions by changing the habitat suitability for species. Species distribution modelling is a modern approach to assess the potential effect of climate change on biodiversity. We used 11 environmental variables with the MaxEnt algorithm to model the distributions of 114 Egyptian medicinal plant species under current conditions, then projecting them into three different future times (2020, 2050, and 2080) under two different climate-change emission scenarios (A2a and B2a), under two hypotheses about the capability of the species for dispersal (unlimited and no dispersal). Species richness maps for current and future times were produced. We tested the value of Egypt’s Protected Areas under climate change by estimating the species richness inside and outside under each scenario. We assessed Egyptian medicinal plants based on IUCN Red List categories and criteria, and then used the SDMs for conservation planning with and without consideration of socioeconomic factors using Zonation software. The A2 emission scenario was more harmful than B2 under all assumptions. Species richness inside Protected Areas was significantly higher than outside for all models. Based just on the records, between 75% and 90% of species could be classified as Least Concern, according to the assumptions made. Similarly, based on SDMs all species could be classified as LC at the current time, whilst in the future under climate change, up to 18% of species face the risk of extinction, depending on assumptions and based on the absolute time gap between the two future times. Based on 10 years, most species were assigned as Least Concern. Areas within PAs were no better in conservation prioritization value than area outside when socioeconomic costs (especially the Human Influence Index) were taken into account. Species distribution models appear to be extremely useful for conservation planning under climate change, particularly when only sparse data are available. Socioeconomic information adds a new dimension to conservation planning, which is actually misleading and incomplete without it