Modeling the natural vegetation dynamic under climate change scenarios in coastal protected dryland of southeastern Tunisia

Abstract

According to the Intergovernmental Panel on Climate Change (IPCC), climate change is mainly manifested by severe droughts and rainfall decrease. These effects are multiple and vary from one region to another around the world including rising temperatures, altered precipitation patterns and degradation of the natural flora. The Zarat region (Gulf of Gabes) is notable for its climate variation, shallow waters, high levels of temperature and salinity. Understanding the vegetation dynamics in this coastal protected region under climate change scenarios is important for projection to the whole ecosystems. The Maxent model is used to predict the potential distribution of plant groups and Soil Adjusted Vegetation Index (SAVI) classes for many future time-periods (2021-2040, 2041-2060, 2061-2080 and 2081-2100) under different climate change scenarios in the Zarat region. Main results indicate that variables related to precipitation and temperature are more significant for predicting plants and SAVI classes distributions. Our findings can provide scientific basis for the dryland sustainable management and for plant community’s behavior under climate change.