Introduction
Small changes in temperature and rainfall regime or changes in the frequency and limit of climatic events can reduce the composition and distribution of plant species as well as their production. For the effective protection and management of natural ecosystems, it is necessary to identify the climatic factors affecting the distribution of plants in the present and use them to predict the distribution of habitats in the future. Climate change has an effect on the biological characteristics of species and therefore it is considered as a major concern for the management and protection of biodiversity. One of the important effects of climate change is to create changes in the distribution range of species. The studies conducted in the field of the effect of climate change on the distribution of plant species and communities show that in the 2030s and 2080s decreases to a large amount of domain the spread of all plant species and communities. he results of research on the effect of climate change based on species prediction models show that in the coming decades, due to the increase in temperature, they will migrate to higher altitudes and their area will decrease.
Predictive habitat models determine the suitability of the habitat for the establishment of plant species and help natural resource managers to identify factors that threaten the population of species, determine important factors in conservation planning. Climate change scenarios on the geographical distribution of species and favorable habitats of plant species. he results of the modeling of the potential habitat of some plant species in the Alborz and Zagros mountains show that in 2030 and 2080, the area of some habitats will decrease and the level of expansion of the species will be extended to higher altitudes.
One of the important effects of climate change is to create changes in the distribution range of plants, so it is necessary to investigate the effect of climate change on the distribution of plant species. Therefore, determining the prediction of the habitat of plant species using modeling methods in this direction can help in the management and exploitation of ecosystems.
In this research, by preparing a forecast occurrence map of the current and future range of A. Aucheri species under two climate warning models (Rcp4.5 and Rcp8.5 scenarios, the displacement of this species in geographical latitudes was investigated in Alborz pasture ecosystems in Mazandaran province.
Methodology
The studied area is Mazandaran province, the province with an area of 2375500 hectares, occupies about 1.46% of the total area of the country. The lowest point of the province with a height of -28 meters above sea level is located in the coastal areas of the province and the highest point is Damavand peak with a height of 5610 meters above sea level in the Alborz mountain range in the south of the province. The average annual rainfall in the coastal strip of the province is equal to 977 mm. Artemisia Aucheri species is one of the representative plants of Alborz rangelad habitats and has a relatively wide spread and plays an important role in soil protection and water storage, and for this reason, it has been studied.Occurrence points (presence and non-presence) of A. Aucheri species were initially prepared using the updated map of plant types and the initial map of the distribution areas of A. Aucheri species. Then, by visiting different areas of the habitat of the species, the minimum and maximum height of distribution was determined. Also, by using the land use map, uses other than pasture use were removed from the polygons, and in the ArcGIS ver10.5 environment, the maps were modified and the current species presence map was finalized. Using 15 synoptic stations, a database, including precipitation, night temperature, daily temperature, and the average temperature was formed, and 19 climatic variables were calculated. Also, using a digital height model with an accuracy of 30 meters, three physiographic variables, including slope, direction, and height were prepared. Then, the presence and absence points of A.Aucheri were identified using updated maps of ecological zones and field visits.
Logistic regression was used to predict the habitat distribution of A. Aucheri species. In this way, the environmental variables in the logistic regression model are entered as predictor variables (independent) and the presence and absence of the species as response variables (dependent) and the vegetative behavior of the studied species in the current conditions is calculated and the relevant relationship is determined. This relationship was used to predict the habitat in 2050 using the 0-ESM2-MRI general circulation model under RCP4.5 and RCP8.5 scenarios. This method was implemented in SPSS Ver24 software and its results were converted into a map using Arc GIS Ver10.5..
Conclusion
The current distribution map of A. Aucheri species shows that in the western, central and to some extent eastern parts of the province, this species is observed in 75-100 percent. The lowest species presence is in the 0-25 percent class. The produced map, in four classes, showed that in 64% of the entire province, the probability of this type of occurrence is 75-100%, which is equal to 1527354 hectares. In this connection, the value of Kappa coefficient was 0.85, which according to the classification of Kappa coefficients (Ilunga Nguy and Shebitz, 2019), the model has good and acceptable accuracy. The maps obtained from the prediction of the logistic regression model show that under the RCP 4.5 scenario, the presence of the species increases in high altitude areas (2500 to 3000 meters), which includes all areas in the central, western and eastern parts of the province. The percentage of presence in the 75-100% class was observed in 60.6% of the area of the province and the highest percentage is the 75-100% class. The percentage of the 0-25% class will decrease. The RCP 8.5 scenario shows that the presence of the species in the 75-100% class will decrease in the central, western and eastern parts of the province. There is a large decrease in 0-25% class and a very small increase in 50-75% class and a large increase in 25-50% class.