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Original Article

Prediction of Climatic Ecological Nest of Artemisia aucheri Boiss, in Tehran Province, Iran Based on Modeling

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Abstract

Optimal habitat has a beneficial effect on species survival. In this research a logistic regression statistical method was used to prepare the potential distribution map of Artemisia aucheri Boiss. in 2020-2021. The maps of 19 bioclimatic and three physiographic variables with a resolution of 4.9 km under the current conditions prepared. Then, sampling information related to the presence and absence of species and environmental variables recorded and the relationship between species distribution and environmental factors determined using logistic regression. Finally, the map of potential distribution of Tehran province produced. The results of logistic regression model showed that in the current situation, 427057 hectares (31% of the province) has a probability of more than 75% presence of this species. The kappa coefficient for evaluating the regression model was 0.86, which according to Koch and Smith classification is one of the models with good accuracy. In order to study the effect of climate change on the geographical distribution of the species, climate bio maps were prepared based on the MRI-ESM2-0 circulation model and under two scenarios of 4.5 and 8.5 for 2050. The species under study is currently in the range of 1600 to 2800 meters. The results show that by changing the conditions from a balanced to a pessimistic situation, the area with a presence of more than 75% of the species decreases and the area with a presence of 25-50% increases. Also, results show that the minimum and maximum altitudes in scenario 4.5 will change to 1500 and 2500 meters, respectively. While according to scenario 8.5, the presence of this species is only at above 2500 meters. According to the 8.5 scenario, the species will migrate to higher altitudes. The results identify climate sensitive areas and possible future shelters of Artemisia aucheri Boiss for use in conservation and rangeland planning.

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