Document Type : Research Paper

Authors

1 Researcher, Forest and Rangeland Research Division, Baluchestan Agriculture and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization (AREEO), Iranshahr, Iran

2 Research Professor, Rangeland Research Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran

3 Ph.D. of Range Management, Isfahan Agriculture and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization (AREEO), Isfahan, Iran

10.22092/ijrdr.2024.132036

Abstract

Abstract
   
Background and objectives:
Knowing the effective environmental factors in the establishment of vegetation can help the proper management of pasture ecosystems. A suitable habitat has a significant effect on the survival and reproduction of species. Revealing changes in climate parameters indicates that climate changes have started in Iran and it is necessary to determine the potential habitats of indicator species, now and in the coming years, under climate warning models. With the advancement of statistics and geographic information system, it has become possible to predict the habitat of plant species using modeling methods. Therefore, this research was conducted with the aim of preparing a forecast map of Platychaete aucheri habitats based on the climate forecast model in Sistan and Baluchestan province.
Methodology:
First, using 8 synoptic stations inside and nearby areas, the database including precipitation variables, night temperature, daily temperature and average temperature, from the year of establishment of each station until 2019, and 19 climate parameters were calculated. Also, three physiographic variables, including slope, direction and height, were prepared using a digital height model with an accuracy of 30 meters. Then, by using the updated maps of the ecological zones recognition plan and field visits, the presence and absence points of P.aucheri species were determined. The basis of the analysis used in this research is logistic regression, which is based on environmental values related to the presence and absence of species. Using logistic regression, the growth behavior of this species in Sistan and Baluchestan region was determined and the map was modeled and the relevant equations were calculated in the current conditions. After ensuring the efficiency of the model, the climate data predicted by the general circulation model MRI-ESM2-0 were used under the scenarios 4.5 and 8.5, and by using the current equations and placing the data extracted from the database, Worldclime, the future distribution map of the species P.aucheri was produced for 2050 under RCP4.5 and RCP8.5 climate scenarios. In this way, at the stage of defining the logistic regression model in ArcGIS, instead of the map of the climate variables that exist in the model, the maps of the same variables predicted for the year 2050 were placed.
Results:
The results of the potential maps showed that the current distribution of the species, P.aucheri, had a more colorful presence in the central and southern parts, and the percentage of the presence of the species decreased by moving towards the northern regions. The area of suitable habitat (probability of occurrence greater than 75%) of P.aucheri species in the province is equal to 12873269 hectares, approximately 71%. The evaluation of the model was done using the data of the presence and absence of the species and using the Kappa statistical coefficient. In this connection, the value of the Kappa statistical coefficient was obtained as 0.85, which according to the presented classification of the Kappa coefficients, the model has good and acceptable accuracy. It is acceptable. The maps resulting from the prediction of the logistic regression model show that the habitat area of ​​P.aucheri species will increase significantly in 2050 under both RCP4.5 and RCP8.5 scenarios, and it is observed that the habitat area of ​​P.aucheri species is more than 75% more likely to occur. In the province, it will be equal to 15506391 and 17788376 hectares, respectively, which will occupy a surface equivalent to 85.3 and 97.85%, respectively. Under the RCP8.5 scenario, the probability of the presence of the species will increase greatly, and it can be seen that the probability of the presence of this species in the lower floors reaches 50% to zero.
 
Conclusion:
In general, climate change and the consequent increase in temperature indicators will preserve the current habitat, increase the probability of the presence of the species in the entire province, and the vertical expansion of the P.aucheri species and its movement to higher latitudes along the altitude gradient of the region. Therefore, the expected upper limit of the vegetative range of P. aucheri species will undergo changes during the next three decades.
 

Keywords

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