Although there are concerns about the impact of climate change on forests, the impact of future climate change on tree species in the Hyrcanian forests has been less studied. The effect of climate change on the distribution of species usually leads to the movement of species to higher altitudes and latitudes. Hornbeam is the most abundant tree species in the Hyrcanian forests, which is distributed in a large part of northern Iran. In this study, the effect of climate change on the change of hornbeam species height using species distribution models are currently being studied under different climate change scenarios for 2050 and 2070. In this study, various statistics including TSS, AUC, KAPPA, Sensitivity and Specificity were used to evaluate the performance of species distribution models. According to the model evaluation criteria, the random forest model had a higher efficiency than other models in the distribution of hornbeam in northern Iran. The future prediction of species distribution models showed that climate change will have a negative impact on the distribution of hornbeam, which will significantly reduce the areas with the potential for the presence of this species under RCP2.6 and RCP8.5 in 2050 and 2070. The results showed that the hornbeam species currently has the greatest potential for presence up to an altitude of 1000m, but also expands to an altitude of 2500m and with climate change will have the greatest potential for presence at an altitude of more than 1000m. Although very complex mechanisms justify the distribution of tree species in mountainous areas, climate is one of the most important of these mechanisms and the results of this study can be a criterion for future planning in Hyrcanian forests.

Species distribution models (SDMs) are the most important ecological models used to model species distribution, identify new habitats, and protect endangered species. In this study, habitat potential modeling and determine the most important factors affecting on distribution of Persian oak (Quercus brantii Lindl.) was investigated using MaxEnt model in Lorestan province. To map the potential distribution of Persian oak, 22 environmental layers were prepared in ArcGIS 10.4.1 and converted to ASCII format. Then 5064 species presence points were extracted using 1.5 × 1.5 km grid from the map of geographical distribution of the Persian oak species (1:250000) and converted to CSV format. After preparing the layers, MaxEnt 3.3.3 software was used to model distribution of the species. The results showed that 7 variables were more important among of the 22 environmental variables affecting on distribution of Persian oak. Annual mean temperature, Precipitation of wettest quarter and Min temperature of coldest month had the highest impact on distribution of the species with 38, 24.2 and 13.3 %, respectively. The area under the curve (AUC) of the model was 0.669 and the threshold value of 0.33 was used to convert the probability map to the presence and absence maps. The potential vegetation map of Persian oak shows that approximately 62.5% of the area of Lorestan province has the potential for growing Persian oak. The main new habitat is located in Khorramabad, Aligudarz, Kuhdasht and Poldokhtar, which recommended for restoration and rehabilitation.

Biodiversity is one of the most important indicators of ecosystem diversity and dynamism. Birds, as a clinker indicator of ecosystem biodiversity, are considered as the habitat suitability and other necessary living conditions for any species. Therefore, the study of birds, especially migratory birds, is of particular importance as a clinker indicator. Due to the need for studies in this field, the present study was conducted to investigate the desirability of the habitat and identify the most important environmental variables affecting the distribution of the Anser anser species as a migratory and index species in Iran. Using 23 environmental variables and the nine models in the BIOMOD software package under R software, the Anser anser species is distributed in three types of habitats including winter-passing, summer-passing and breeding and stopeover modeling. The findings from species modeling showed that the models, used in species distribution modeling, have high accuracy in studying species distribution. In general, temperature and precipitation variables are the most important, while the variables such as vegetation and distance to roads are less important in the distribution of Anser anser species in Iran.  According to the results, 15.91% of the surface of Iran was identified as a desirable habitat for Anser anser species, which overlaps with 15.95% of the protected areas. Therefore, the used method in this study identifies the desired habitats of the species correctly. Besides, it can be applied as a suitable method to model the habitat suitability of similar species, which is essential from the perspective of conservation providing comprehensive and practical wildlife management programs.

Bird watching or the scientific study of birds is one of the oldest environmental sciences. The migration of birds, especially aquatic species, has long been of interest to many researchers. Birds, as a clinker indicator of ecosystem biodiversity, are considered as the habitat suitability and other necessary living conditions for any species. Therefore, the study of birds, especially migratory waterfowl, is of particular importance. Due to the need for studies in this field, the present study aims to investigate the desirability of the habitat and identify the most important environmental variables affecting the distribution of Anser anser species as a migratory and index aquatic species in Iran.

In this study, 10 presence spots for the summer-passing and breeding population, 116 presence spots for overwintering population and 25 presence spots for the passing population of Anser anser have been applied in order to model the distribution of Anser anser species in three habitat types including winter-passing, summer-passing and hatchery, as well as stopping places in Iran. These spots were obtained from the bird census reports of the Environmental Protection Agency. Three groups of environmental variables including topography, climate and land use / land cover were used to investigate the factors affecting the distribution of Anser anser species. Finally, 23 environmental variables were called for modeling in the biomod software package.

The values ​​of accuracy evaluation indices reveal that models such as FDA and RF have high accuracy in the modeling process out of the nine models implemented in modeling Anser anser stopover. Moreover, variables such as seasonal rainfall, distance to rural areas and the amount of rainfall in the least rainy season play an important role in the selection of stopover by the Anser anser. According to the results of the overlap analysis of the total area of ​​Iran, only 20.99% is known as desirable habitats of this species, which includes 18.69% of the total desirable habitats in protected areas.
Based on from modeling the habitat of summer Anser anser, all the models used in this study have high accuracy in studying the species distribution. On the other hand, the distribution of this species in Iran depends on factors such as distance to wetlands, distance to forest and distance to streams. According to the findings, 3.22% of the total area of ​​Iran is known as a suitable habitat summer Anser anser and overlaps with the presence of species, which is 4.09% of the total summer habitats. Optimal laying and hatching of this species is covered by protected areas.
The results of modeling the Anser anser species in the surface of wintering habitats indicate that all models have high accuracy. The distribution of this species in the surface of wintering habitats is affected by factors such as rainfall, distance to the city and the warmest rainfall of the year. Optimal habitats of this species cover 23.52% of Iran, which is 25.09% of the total desirable habitats of the studied species overlap with protected areas.
Examining the distribution of species at the level of ecological nests and understanding the relationship between environmental variables and the distribution of species using a biomod software package show how species respond to environmental changes at the present time. The findings from evaluating the algorithms used in modeling the habitat types of the Anser anser species reveal that the biomod software package has a high ability to predict the optimal habitats of this species. Thus, it has identified desirable species habitats at the present time, habitats that can be used in the future and have favorable conditions for species introduction, as well as habitats that had ideal conditions in the past. In this regard, the species of Anser anser Choose to spend winters in areas such as Urmia Lake, Fars province, Sistan and Baluchestan, Azerbaijan, Kurdistan and the southern parts of the Caspian Sea and in some eastern and northern areas of the country that have ideal biological conditions. According to the frindings from modeling, the Anser anser is mainly present in summers in Azerbaijan province, especially Urmia Lake and the surrounding wetlands. These areas are more preferred than other parts of the country due to favorable weather conditions, adequate security and availability of food resources. Locations of Anser anser in the country include areas such as the southern shores of the Caspian Sea, parts of the west and northwest, as well as northeastern areas. Proper identification of stops and providing applications to protect these areas is important due to the functional role of stopping places in meeting the needs of migratory species. In general, in the present study, it is found that 15.95% of the total habitats of the Anser anser species are located in protected areas. This indicates the existence of a large part of the desirable habitats of this species outside the protected areas. Therefore, the results of the present study show the need to reconsider the demarcation of protected areas in the future more than in the past in Iran.

The current study aims to investigate the distribution of Anser anser species and the effect of environmental variables on the distribution of this species in Iran using a biomod software package.  Based on the results, the method used in this study correctly identifies the desired habitats of the species and can be used as a suitable method to model the habitat suitability of similar species and also to study the biodiversity of habitats. This is essential from the point of view of conservation and the presentation of comprehensive and practical wildlife management programs.

Proper and efficient management of forests requires adequate knowledge of environmental factors and their impact on vegetation. This study aimed to develop a model of the spatial distribution pattern of Cercis griffithii based on physiographic factors (slope, aspect, altitude, and distance from river and determine the most important factors influencing the distribution of physiographic love tree and prepare the spatial distribution map of this species. Therefore, the slope, altitude, and aspect maps and also waterways map in GIS environment using digital topographic maps of the study area were prepared by the scale 1/25000. To examine the effects of environmental variables and model the distribution map of the species, logistic regression was used. The results showed that altitude and the distance from waterways had significant relationship with the distribution of Cercis griffithii. Modeling was performed based on two variables that were significantly associated with the distribution of this species and coefficients obtained from the logistic regression analysis. Nagelkerke R squared and ROC of the model were 0.556 and 0.871, respectively, which demonstrate the proper accuracy and credibility of the logistic model in species distribution modeling.

Taxus baccata is an indigenous and valuable species of Hyrcanian Forests. According to recent studies, the presence of this species in the areas where distribution is declining; therefore, preserving and restoring this valuable species is essential. One of the most strategies for conservation and rehabilitation of valuable species is identification of its potential distribution and prioritization of areas with potential of presence of species using species distribution models. The purpose of this study was to prioritize desirable habitats for preservation and restoration of yew in Hyrcanian forest. In this study, the Boosted Regression Tree (BRT) algorithm was used to model the distribution of yew species in relation to climatic, edaphic, and topographic variables and identification of the most important variables affecting the distribution of yew. The results showed that the model constructed with climate variables in terms of model evaluation criteria by average of TSS (0.83) and AUC (0.97), has better performance in comparison to edaphic and topographic models. Also, among the climate variables, mean temperature of driest quarter and precipitation of warmest quarter has the most effect on the distribution of yew species. Soil organic carbon, sand percent, cation exchange capacity, altitude, and slope percent were also other important factors affecting the distribution of yew species. Finally, by combining the suitability maps of climatic, topographic, and edaphic models, a map of the priority of conservation and restoration of yew species was prepared, which is very valuable in planning for restoration of this species in Hyrcanian Forests.

Due to the insufficient information about the distribution of plant and animal species, the use of modeling to predict the distribution of species has increased in recent years. For this purpose, a wide range of modeling techniques has been developed. In this study, the potential distribution map of Ferula ovina Boiss.was prepared using the environmental factors and occurrences data and genetic algorithms model (GARP). Species occurrences (137 sites) were collected using stratified random sampling method and all environmental layers including physiographic layers (slope, aspect and elevation derived from digital elevation model), climate and soil layers were produced using interpolation methods in ARCGIS (with a pixel size of 70 × 70 m). All data were analyzed by Desktop Garp and the distribution map of Ferula ovina was prepared. The model evaluation was performed by AUC of ROC plot, indicating a good performance of this model (AUC=0.766). According to the results of sensitive analysis, silt and elevation were the most important factors affecting the distribution of Ferula ovina. This model could be used in the interpretation of relationships between species and environment and assessing areas with high protection potential as well as determining suitable areas for the revival of Ferula ovina and climate change and management scenarios.

Factors affecting the distribution of plant species include climate, soil properties, topography, land use, and total biological relationships. Climate is one of the most important factors in the distribution of plant species. The present study was conducted to predict the geographical distribution of Acacia tortilis (Forssk. Hayne), to find important environmental factors and to investigate the tolerance of the species to environmental factors in Hormozgan province. According to the purpose, vegetation information and habitat factors such as elevation, climate, geology and soil were collected. Vegetation sampling was done randomly-systematically by plotting along 4 transects of 200-1000 m. Map of environmental variables was prepared using GIS. Then, prediction maps related to species distribution were prepared using entropy modeling method. The accuracy of the obtained prediction models was evaluated using AUC statistics. In general, the results showed that the variables of total rainfall in the hottest season, seasonal changes of rainfall (coefficient of variation), total rainfall of the lowest rainfall of the year, average temperature of the driest season, average of the warmest season are the most important climatic characteristics. They affect the distribution of Acacia tortilis (Forssk. Hayne).characteristics. They affect the distribution of Acacia tortilis (Forssk. Hayne).The results of this study can solve the problems facing habitat management. In fact, when a species is threatened by habitat destruction, by recognizing the factors to which the species is highly dependent, conservation plans can be proposed according to the habitat needs of the species.

This study aimed at predicting the effect of climate change on the geographic distribution of Thymus kotschyanus Boiss and Hohen in Mazandaran province. Species presence data were recorded via the Global Positioning System (GPS). The distribution of T. kotschyanus Boiss and Hohen under current and future climatic conditions 2050 and 2070 (1428- 1448 Solar) applying  two scenarios of RCP 4.5 and RCP 8.5 climate change by using the GCM data series of general circulation models BCC-CSM1-1، CCSM4 and MRI-CGCM3  and the five species distribution models such as Generalized Linear Model, Generalized Additive Model, Classification Tree Analyses, Generalized Boosting Model and Random Forest methods was investigated. For this purpose, layers of environmental factors, including six bioclimatic and two physiographic variables, were used as inputs to species distribution models. Among the environmental variables, precipitation seasonality, precipitation in the coldest quarter, and isotherm had the greatest impact on habitat suitability. The assessment of the modelling indicated that the Generalized Additive Model and Generalized Boosting Model had better predictions of climate habitat than the other models. The results also indicate that climate change will change the range size of the T. kotschyanus Boiss and Hohen, and will move toward higher elevations in the future. The results of the present study may be used to plan habitat protection for the medicinal species of T. kotschyanus Boiss and Hohen, as well as its restoration and rehabilitation in the vast regions of the country.

Predicting the effect of climate change on the distribution of valuable and endangered plant species is essential for their conservation and management. In this study, the MaxEnt model and 10 environmental variables were used to predict the current and future distribution of E. amoenum and E. italicum in response to climate change. Also, to predict the effect of climate change in the future (the 2050s and 2070s), two climate scenarios of RCP 2.6 and RCP8.5 were used under the CCSM4 general circulation model. Evaluating the accuracy of the models based on the AUC index indicates their excellent performance (<0.9). Resutls  of this study reveal that the most important variables affecting the distribution of E. amoenum species are slope (38.8%), annual temperature range (11.5%), and precipitation in the driest season (31.9%) are. Also, the solar radiation (37.6%), slope (36.4%), and the average temperature of the coldest season (11.5%) are the most important environmental factors affecting the distribution of E. italicum. In addition, the results show that the distribution of the studied species will decrease in response to climate change and under RCP2.6 and RCP8.5 in the 2050s and 2070s. Therefore, the results of this study emphasize the need to develop  conservation strategies to prevent the extinction of these species.

The climate changes have an important role in distribution of plant species. Statistical species distribution models (SDMs) are widely used to predict the changes in species distribution under climate change scenarios. In the peresent study, the distribution of Alopecurus textilis in the current and future climate condition (2050) under the influence of climate change and two scenarios of RCP 4.5 and RCP 8.5 with the GCM data series of general circulation models BCC-CSM1-1، CCSM4 and MRI-CGCM3 by using of Five species distribution models such as Generalized Linear Model, Generalized Additive Model, Classification Tree Analyses, Generalized Boosting Model and Random Forest method in Mazandaran province were investigated. For this purpose, the number of 92 species presence data was recorded using Global Positioning System and along with layers of environmental factors including six bioclimatic variables and two physiographic variables were used in modeling. Among the environmental variables, mean temperature of driest quarter, precipitation seasonality, precipitation of warmest quarter and precipitation of coldest quarter had the most impact on the habitat suitability. Modeling evaluation indicated that the random forest and generalized boosting model had better predictions of climatic habitat than other models. Results showed that in comparison with current conditions under the emission scenarios of RCP 4.5 and RCP 8.5 respectively 22.25 and 36.22 percent of the climatic suitable area for this species will be reduced by 2050. Finally, the results of the present study can be an efficient tool for biodiversity protection, ecosystem management, and species re-habitation planning under future climate change scenarios.