Predicting the Distribution of Artemisia Sieberi Besser under Climate Change in the Steppe and Semi-Steppe of Iran-Touranian Region

Document Type : Original Article

Authors

1 Ph.D. Student of Rangeland Science, Department of Natural Resources, Isfahan University of Technology, Isfahan, Iran

2 Assistant Professor, Department of Natural Resources, Isfahan University of Technolog, Isfahan, Iran

3 Associated Professor, Department of Natural Resources, Isfahan University of Technology, Isfahan, Iran

Abstract

Understanding the effect of climate change on distribution of plant species is essential for sustainable management and conservation of rangelands, especially in arid and semi-arid ecosystems which are vulnerable to desertification, because of their sensitivity and frangibility to climate change. Due to the complexity of natural systems and phenomenon of climate change, species distribution models are used to understand the impact of climate change on potential niche of species. In this study, five modeling algorithms including artificial neural network, generalized boosting method, classification tree analysis, multivariate adaptive regression splines and maximum entropy were used to predict current and future distribution of Artemisia sieberi Besser in Central Iran. First, the ensemble model as the average predicted probability of single models’ occurrence was created. Next, pessimistic (RCP 8.5) and optimistic (RCP 2.6) scenarios of CCSM4 and NorESM1-ME climate models for the years of 2050 and 2070 were evaluated to assess the trend in spatio-temporal variations of distribution. For this purpose, layers of environmental factors including six bioclimatic and two physiographic variables were used as inputs of species distribution models. Among the environmental variables, altitude, annual precipitation, isothermality, and slope had the most impact on the habitat suitability. Modeling evaluation indicated that the generalized boosting model had better predictions of climatic habitats than other models, and ensemble model than single models. Maximum probability of species presence was determined in plains and low slope areas at altitude of 1000-2000 m and annual precipitation of 100-200 mm. Analysis of the climate change scenarios showed that, the species habitat would be decreased in 2070 more than 2050, leading to the expansion of desert areas. The results can be used for planning to combat desertification in the habitat of Artemisia sieberi, as well as its restoration and rehabilitation in the vast regions of Iran.

Keywords