Modeling the Current and future potential distribution of Arabis alpina using MaxEnt software in selected mountains areas of Ethiopia

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Abstract

The objective of this study was to model the current and future distributions of the plant species, Arabis alpina, using MaxEnt software. Accordingly, a total of 70 locations data were used for this investigation. The occurrence record of this species was obtained from herbarium of Ethiopian Biodiversity Institute and Google Earth version 7 from highland areas of Ethiopia.  Climate data with a spatial resolution of 30 s (approximately 1 km2), was downloaded from world climate database website. The result of this analysis confirmed that the average test of AUC is 0.970. This is an excellent model for the selected variables since the AUC value was more than 0.90. The test of the jackknife indicated the current distribution of Arabis alpina was mainly influenced by Annual Mean Temperature (Bio1) and the Min Temperature of Coldest Month (Bio6) that contributed 74.9% and 17.5% to the MaxEnt model respectively.  Regarding the future climatic condition the result of this investigation indicated that the average test of AUC was 0.959. The jackknife test was also indicated that, Precipitation of Wettest Quarter (bio16) that contributed 95.1% to the MaxEnt model. Generally, from the picture of the model of current climatic conditions indicated that Arabis alpina occurs in most highland areas of Ethiopian but the model for future climatic condition indicated that this plant will be restricted to few areas of the country. This might me due to climate change, anthropogenic degradation and Invasive Alien Species.   In addition from the picture of the model there might be shifting of habitat from the lower altitude to the higher altitude .This might be due to an increase in temperature and decrease in precipitation. Therefore, this study recommends the integration of future climate situation into current restoration and conservation policies to protect ecologically sensitive species of the country.

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Amare Seifu

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