Despite the evidence on the cooling effects of urban green spaces (UGS), little is known about ho... more Despite the evidence on the cooling effects of urban green spaces (UGS), little is known about how they function as an interconnected network of cold green patches or a green heat sink (GHS) within an urban landscape. This study aimed to analyze the general spatial pattern and connectivity of GHSs using the pertinent indices and Circuitcape tool in an Iranian urban area between 2000 and 2020. Initially, normalized differentiation vegetation index (NDVI) and land surface temperature (LST) maps were derived. To construct a network, GHS was extracted by Getis Ord Gi* statistic and the cost map was built by reversing the NDVI. The results showed that UGS and GHSs shrunk by 17% and 31%, respectively, and became highly fragmented, demonstrating smaller sizes but increased in number, density, and shape complexity. According to the network analysis, the overall connectivity of GHSs decreased over time. Finally, five high-priority locations were identified to increase the connectedness of vegetation cover that might improve the thermal environment of the city. This research can direct urban planning towards enhancing a green space network to mitigate the urban temperature within the urban landscape .
Journal of Animal Research#R##N#(Iranian Journal of Biology), Dec 21, 2020
The amphipods of genus Niphargus Schiödte, 1847 inhabit in subterranean waters and constitute a s... more The amphipods of genus Niphargus Schiödte, 1847 inhabit in subterranean waters and constitute a substantial part of the groundwater biodiversity. In the last decades, there have been many developments for using of modelling algorithms, although not exclusive to the specific case of subterranean habitats. In this study, ecological variables were used to investigate the effect of environmental factors on Niphargus genus distribution. The occurrence points of the genus in north, west and northwest provinces were obtained from previous studies. Then, climatic variables, topography (slope, elevation, and moisture) were used, as well as temperature and moisture data at depths of 0 to 10 cm and 10 to 40 cm. In order to evaluate the similarity between habitat areas, k-mean clustering were used. Then, species distribution modeling was performed using Maximum Entropy Method at the country scale. The results showed that among all the variables used, only Bio14 had no normal distribution (P-value>0/05). Clustering results also showed that, the occurrence points of genus members is placed in two clusters, cluster 1 in the north of Iran and cluster 2 along of Zagros mountain range. There is similarities between two clusters. Two variables include the annual rainfall and soil temperature at depths of 10 to 40 cm have the most effect on the distribution of genus Niphargus. The results also showed that due to distance from the ground surface and the environmental variables, the same conditions exist in most occurrence points of this taxon.
This study aimed to predict the potential distribution of Amygdalus scoparia and the changes in i... more This study aimed to predict the potential distribution of Amygdalus scoparia and the changes in its ecological dimension under climate change scenarios using MaxEnt model in Iran. Species presence data, current climate data and different scenarios of CCM4 in 2050 and 2070 were used. Fars Province boundary and whole area of Iran were considered as the modeling boundary and projection boundary, respectively. The predictive power of the model was within acceptable levels (AUC = 0.88). The Bio3, Bio15 and Bio4 variables had the greatest impact on predicting the potential distribution of A. scoparia. The highest percentage of potential niche of A. scoparia will occur in 2070 under RCP4.5 scenario (24.62%) in Fars Province. In Iran, however, the highest (22.57%) and lowest (16.77%) potential niche of A. scoparia belong to current and RCP8.5 scenarios in 2050. Amygdalus scoparia lacks specialization in Fars Province, but the breadth of its ecological niche will be decreased in future and i...
The endangered Yellow Spotted Mountain Newt, Neurergus microspilotus, is a poorly known species t... more The endangered Yellow Spotted Mountain Newt, Neurergus microspilotus, is a poorly known species that has been reported from highland first order streams in western Iran and eastern Iraq. We used a presence-only model to provide potential distribution for the species and identified the variables best explaining the occurrence of the species. Using available information on known localities of N. microspilotus, we developed a maximum entropy (MaxEnt) model to predict potential distribution of this species in Iran and Iraq. After the model was validated, we found that low (< 0-20) suitability scores for N. microspilotus presence corresponded to 52% of the total area considered (26,572 km 2); whereas, high (80-100) suitability scores corresponded to only 2% of this area. Of the total suitable habitat, approximately 67% is located in Iran and 33% in Iraq. The model achieved a 1.8 regularized gain value with contribution of more than 51% provided by precipitation of coldest quarter as the main factor influencing the model performance. With three protected areas in Iraq and one in Iran near or within the predicted distribution, only 2.29% of range for the species was within protected areas. The model indicated high suitability score for considerable area in Iraq that has not been searched for N. microspilotus. To preserve the species, we recommend surveys of Iraqi territory in search of N. microspilotus and to initiate studies to allocate more reserves with corridors that bridge the otherwise impermeable gaps between the breeding streams.
Assessment of local bending stiffness in timber on basis of knot area ratios, resonance frequenci... more Assessment of local bending stiffness in timber on basis of knot area ratios, resonance frequencies and measured strain fields
The striped hyena (Hyaena hyaena) is a global scale endangered species and has a high risk of loc... more The striped hyena (Hyaena hyaena) is a global scale endangered species and has a high risk of local extinction in its population, therefore, investigation and evaluation of its habitat for covered areas seems necessary. This study was done to investigate the distribution status of this species in the Shaho Mountain domain in Kermanshah province. In this study, after collecting species presence points, habitat variables including slope direction, elevation, distance from rangelands, distance from agricultural land, distance from main road, residential density, ecotone, slope percentage and viewshed was identified and used in the analysis. In this regard, firstly, using single-class support vector machine models the habitat of the species was modeled. By confirming the validity of the model output through AUC criteria was used from the binary output of the model in order to provide quasi-absence sites 10 times the presense points within almost 5 km distance. Then maximum entropy model...
Background Suitable habitat and landscape structure play a pivotal role in the success of forest ... more Background Suitable habitat and landscape structure play a pivotal role in the success of forest restoration projects. This study aimed to model the habitat suitability of wild almond (Amygdalus scoparia Spach) using three individual species distribution models (SDMs), i.e., backpropagation artificial neural network (BP-ANN), maximum entropy (MaxEnt), generalized linear model (GLM), as well as the ensemble technique along with measuring the landscape metrics and analyzing the relationship between the distribution of the suitable habitat of the species in different landform classes in Fars Province, southern Iran. Results There was no clear difference in the prediction performance of the models. The BP-ANN had the highest accuracy (AUC = 0.935 and k= 0.757) in modeling habitat suitability of A. scoparia, followed by the ensemble technique, GLM, and MaxEnt models with the AUC values of 0.890, 0.887, and 0.777, respectively. The highest discrimination capacity was associated to the BP-...
Rapid climate change has provided the opportunity for many species to learn to adapt fast enough ... more Rapid climate change has provided the opportunity for many species to learn to adapt fast enough to modify their range distribution. The positive and negative responses of the species in terms of distribution are related to parameters such as kind of species, degree of specialization, size and movement skills, and such factors. Moving to high elevations and transitions to higher latitudes are among the strategies proposed as a solution to the negative effects of climate change. Therefore, predicting how different species respond to climate change can help predict the conservation program for them. Species distribution models (SDMs) are widely used to predict the geographical distribution of habitat suitability and species occurrence. Rhinopoma muscatellum is one of the three mouse-tailed bats (Rhinopomatidae) inhabiting the southeastern, southern, and southwestern parts of Iran and its distribution range to the interior and northern parts of Iran has been limited by the Elburz and Zagros Mountain. To study the effect of climate change on this species, range shifts and coverage of protected regions, 74 presence points and environmental variables (climate, topography, anthropogenic, and vegetation) in MaxEnt software were used. Before the implementation of the model, the autocorrelation of the presence points was reduced and the selection of pseudo absent points was limited by using the bias grid. Climate variables were prepared for Mid-Holocene, Current, Climate Current, and Future scenarios in 2070 (RCP2.6, RCP4.5, RCP6, and RCP8.5). In order to evaluate the overlap of ecological niche, the Schoener’s D and I statistic metrics were used. Also, to measure the breadth of the niches, B1 (inverse concentration) and B2 (uncertainty) metrics in ENMTOOLS software were employed. TSS statistics were used as a threshold. Species distribution trend changes in climatic scenarios were performed by the Mann Kendall (MK) test. Based on the results, the AUC values for current and future climate models were calculated to be 0.89 and 0.85, respectively. The distance from settlement, soil organic carbon, and altitude variables have the greatest impact on the current distribution of the species; and among the climatic variables, Isothermality (Bio3), Temperature Seasonality (Bio4), and Max Temperature of Warmest Month (Bio5) had the greatest impact on species distribution. The results showed that in climate change scenarios by 2070, the distribution range and breadth of climatic niche of Rhinopoma muscatellum will be significantly increased (P-value <0.05), habitat fragmentation will be reduced, and in RCP8.5 scenario it will reach the maximum distribution (39.38% of total Iran). This increase will cover the Elburz and Zagros mountain ranges, and a large part of the country will be suitable for the species. In response to current climate change, migration to higher latitudes was identified in this study. Among the main different classes of protected regions in Iran (National parks, Wildlife refuges, and Protected areas), protected areas in all scenarios had the most coverage of the suitable species habitat.
Climate change, as an emerging phenomenon, has led to changes in the distribution, movement, and ... more Climate change, as an emerging phenomenon, has led to changes in the distribution, movement, and even risk of extinction of various wildlife species and this has raised concerns among conservation biologists. Different species have two options in the face of climate change, either to adopt or follow their climatic niche to new places through the connectivity of habitats. The modeling of interpatch landscape communications can serve as an effective decision support tool for wildlife managers. This study was conducted to assess the effects of climate change on the distribution and habitat connectivity of the endangered subspecies of Asian black bear (Ursus thibetanus gedrosianus) in the southern and southeastern Iran. The presence points of the species were collected in Provinces of Kerman, Hormozgan, and Sistan-Baluchestan. Habitat modeling was done by the Generalized Linear Model, and 3 machine learning models including Maximum Entropy, Back Propagation based artificial Neural Netwo...
Global climate change poses a new challenge for species and can even push some species toward an ... more Global climate change poses a new challenge for species and can even push some species toward an extinction vortex. The most affected organisms are those with narrow tolerance to the climatic factors but many large mammals such as ungulates with a wider ecological niche are also being affected indirectly. Our research mainly used wild sheep in central Iran as a model species to explore how the suitable habitats will change under different climatic scenarios and to determine if current borders of protected areas will adequately protect habitat requirements. To create habitat models we used animal-vehicle collision points as an input for species presence data. We ran habitat models using MaxEnt modeling approach under different climatic scenarios of the past, present and future (under the climatic scenarios for minimum (RCP2.6) and maximum (RCP8.5) CO 2 concentration trajectories). We tried to estimate the overlap and the width of the ecological niche using relevant metrics. In order to analyze the effectiveness of the protected areas, suitable maps were concerted to binary maps using True Skill Statistic (TSS) threshold and measured the similarity of the binary maps for each scenario using Kappa index. In order to assess the competence of the present protected areas boundary in covering the distribution of species, two different scenarios were employed, which are ensemble scenario 1: an ensemble of the binary maps of the species distribution in Mid-Holocene, present, and RCP2.6; and ensemble scenario 2: an ensemble of binary suitability maps in Mid-Holocene, present, and RCP8.5. Then, the borders of modeled habitats with the boundaries of 23 existing protected areas in two central provinces in Iran were compared. The predicted species distribution under scenario 1 (RCP2.6) was mostly similar to its current distribution (Kappa = 0.53) while the output model under scenario 2 (RCP8.5) indicated a decline in the species distribution range. Under the first ensemble scenario, current borders of the protected areas in Hamedan province showed better efficiency to cover the model species distribution range. Analyzing MaxEnt spatial models under the second climatic scenario suggested that protected areas in both Markazi and Hamedan provinces will not cover “high suitability” areas in the future. Modeling the efficiency of the current protected areas under predicted future climatic scenarios can help the related authorities to plan conservation activities more efficiently.
Mountainous rangelands play a pivotal role in providing forage resources for livestock, particula... more Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method (RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method (90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index (J) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potential habitat. Based on the values of the area under curve (AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.
Despite the evidence on the cooling effects of urban green spaces (UGS), little is known about ho... more Despite the evidence on the cooling effects of urban green spaces (UGS), little is known about how they function as an interconnected network of cold green patches or a green heat sink (GHS) within an urban landscape. This study aimed to analyze the general spatial pattern and connectivity of GHSs using the pertinent indices and Circuitcape tool in an Iranian urban area between 2000 and 2020. Initially, normalized differentiation vegetation index (NDVI) and land surface temperature (LST) maps were derived. To construct a network, GHS was extracted by Getis Ord Gi* statistic and the cost map was built by reversing the NDVI. The results showed that UGS and GHSs shrunk by 17% and 31%, respectively, and became highly fragmented, demonstrating smaller sizes but increased in number, density, and shape complexity. According to the network analysis, the overall connectivity of GHSs decreased over time. Finally, five high-priority locations were identified to increase the connectedness of vegetation cover that might improve the thermal environment of the city. This research can direct urban planning towards enhancing a green space network to mitigate the urban temperature within the urban landscape .
Journal of Animal Research#R##N#(Iranian Journal of Biology), Dec 21, 2020
The amphipods of genus Niphargus Schiödte, 1847 inhabit in subterranean waters and constitute a s... more The amphipods of genus Niphargus Schiödte, 1847 inhabit in subterranean waters and constitute a substantial part of the groundwater biodiversity. In the last decades, there have been many developments for using of modelling algorithms, although not exclusive to the specific case of subterranean habitats. In this study, ecological variables were used to investigate the effect of environmental factors on Niphargus genus distribution. The occurrence points of the genus in north, west and northwest provinces were obtained from previous studies. Then, climatic variables, topography (slope, elevation, and moisture) were used, as well as temperature and moisture data at depths of 0 to 10 cm and 10 to 40 cm. In order to evaluate the similarity between habitat areas, k-mean clustering were used. Then, species distribution modeling was performed using Maximum Entropy Method at the country scale. The results showed that among all the variables used, only Bio14 had no normal distribution (P-value>0/05). Clustering results also showed that, the occurrence points of genus members is placed in two clusters, cluster 1 in the north of Iran and cluster 2 along of Zagros mountain range. There is similarities between two clusters. Two variables include the annual rainfall and soil temperature at depths of 10 to 40 cm have the most effect on the distribution of genus Niphargus. The results also showed that due to distance from the ground surface and the environmental variables, the same conditions exist in most occurrence points of this taxon.
This study aimed to predict the potential distribution of Amygdalus scoparia and the changes in i... more This study aimed to predict the potential distribution of Amygdalus scoparia and the changes in its ecological dimension under climate change scenarios using MaxEnt model in Iran. Species presence data, current climate data and different scenarios of CCM4 in 2050 and 2070 were used. Fars Province boundary and whole area of Iran were considered as the modeling boundary and projection boundary, respectively. The predictive power of the model was within acceptable levels (AUC = 0.88). The Bio3, Bio15 and Bio4 variables had the greatest impact on predicting the potential distribution of A. scoparia. The highest percentage of potential niche of A. scoparia will occur in 2070 under RCP4.5 scenario (24.62%) in Fars Province. In Iran, however, the highest (22.57%) and lowest (16.77%) potential niche of A. scoparia belong to current and RCP8.5 scenarios in 2050. Amygdalus scoparia lacks specialization in Fars Province, but the breadth of its ecological niche will be decreased in future and i...
The endangered Yellow Spotted Mountain Newt, Neurergus microspilotus, is a poorly known species t... more The endangered Yellow Spotted Mountain Newt, Neurergus microspilotus, is a poorly known species that has been reported from highland first order streams in western Iran and eastern Iraq. We used a presence-only model to provide potential distribution for the species and identified the variables best explaining the occurrence of the species. Using available information on known localities of N. microspilotus, we developed a maximum entropy (MaxEnt) model to predict potential distribution of this species in Iran and Iraq. After the model was validated, we found that low (< 0-20) suitability scores for N. microspilotus presence corresponded to 52% of the total area considered (26,572 km 2); whereas, high (80-100) suitability scores corresponded to only 2% of this area. Of the total suitable habitat, approximately 67% is located in Iran and 33% in Iraq. The model achieved a 1.8 regularized gain value with contribution of more than 51% provided by precipitation of coldest quarter as the main factor influencing the model performance. With three protected areas in Iraq and one in Iran near or within the predicted distribution, only 2.29% of range for the species was within protected areas. The model indicated high suitability score for considerable area in Iraq that has not been searched for N. microspilotus. To preserve the species, we recommend surveys of Iraqi territory in search of N. microspilotus and to initiate studies to allocate more reserves with corridors that bridge the otherwise impermeable gaps between the breeding streams.
Assessment of local bending stiffness in timber on basis of knot area ratios, resonance frequenci... more Assessment of local bending stiffness in timber on basis of knot area ratios, resonance frequencies and measured strain fields
The striped hyena (Hyaena hyaena) is a global scale endangered species and has a high risk of loc... more The striped hyena (Hyaena hyaena) is a global scale endangered species and has a high risk of local extinction in its population, therefore, investigation and evaluation of its habitat for covered areas seems necessary. This study was done to investigate the distribution status of this species in the Shaho Mountain domain in Kermanshah province. In this study, after collecting species presence points, habitat variables including slope direction, elevation, distance from rangelands, distance from agricultural land, distance from main road, residential density, ecotone, slope percentage and viewshed was identified and used in the analysis. In this regard, firstly, using single-class support vector machine models the habitat of the species was modeled. By confirming the validity of the model output through AUC criteria was used from the binary output of the model in order to provide quasi-absence sites 10 times the presense points within almost 5 km distance. Then maximum entropy model...
Background Suitable habitat and landscape structure play a pivotal role in the success of forest ... more Background Suitable habitat and landscape structure play a pivotal role in the success of forest restoration projects. This study aimed to model the habitat suitability of wild almond (Amygdalus scoparia Spach) using three individual species distribution models (SDMs), i.e., backpropagation artificial neural network (BP-ANN), maximum entropy (MaxEnt), generalized linear model (GLM), as well as the ensemble technique along with measuring the landscape metrics and analyzing the relationship between the distribution of the suitable habitat of the species in different landform classes in Fars Province, southern Iran. Results There was no clear difference in the prediction performance of the models. The BP-ANN had the highest accuracy (AUC = 0.935 and k= 0.757) in modeling habitat suitability of A. scoparia, followed by the ensemble technique, GLM, and MaxEnt models with the AUC values of 0.890, 0.887, and 0.777, respectively. The highest discrimination capacity was associated to the BP-...
Rapid climate change has provided the opportunity for many species to learn to adapt fast enough ... more Rapid climate change has provided the opportunity for many species to learn to adapt fast enough to modify their range distribution. The positive and negative responses of the species in terms of distribution are related to parameters such as kind of species, degree of specialization, size and movement skills, and such factors. Moving to high elevations and transitions to higher latitudes are among the strategies proposed as a solution to the negative effects of climate change. Therefore, predicting how different species respond to climate change can help predict the conservation program for them. Species distribution models (SDMs) are widely used to predict the geographical distribution of habitat suitability and species occurrence. Rhinopoma muscatellum is one of the three mouse-tailed bats (Rhinopomatidae) inhabiting the southeastern, southern, and southwestern parts of Iran and its distribution range to the interior and northern parts of Iran has been limited by the Elburz and Zagros Mountain. To study the effect of climate change on this species, range shifts and coverage of protected regions, 74 presence points and environmental variables (climate, topography, anthropogenic, and vegetation) in MaxEnt software were used. Before the implementation of the model, the autocorrelation of the presence points was reduced and the selection of pseudo absent points was limited by using the bias grid. Climate variables were prepared for Mid-Holocene, Current, Climate Current, and Future scenarios in 2070 (RCP2.6, RCP4.5, RCP6, and RCP8.5). In order to evaluate the overlap of ecological niche, the Schoener’s D and I statistic metrics were used. Also, to measure the breadth of the niches, B1 (inverse concentration) and B2 (uncertainty) metrics in ENMTOOLS software were employed. TSS statistics were used as a threshold. Species distribution trend changes in climatic scenarios were performed by the Mann Kendall (MK) test. Based on the results, the AUC values for current and future climate models were calculated to be 0.89 and 0.85, respectively. The distance from settlement, soil organic carbon, and altitude variables have the greatest impact on the current distribution of the species; and among the climatic variables, Isothermality (Bio3), Temperature Seasonality (Bio4), and Max Temperature of Warmest Month (Bio5) had the greatest impact on species distribution. The results showed that in climate change scenarios by 2070, the distribution range and breadth of climatic niche of Rhinopoma muscatellum will be significantly increased (P-value <0.05), habitat fragmentation will be reduced, and in RCP8.5 scenario it will reach the maximum distribution (39.38% of total Iran). This increase will cover the Elburz and Zagros mountain ranges, and a large part of the country will be suitable for the species. In response to current climate change, migration to higher latitudes was identified in this study. Among the main different classes of protected regions in Iran (National parks, Wildlife refuges, and Protected areas), protected areas in all scenarios had the most coverage of the suitable species habitat.
Climate change, as an emerging phenomenon, has led to changes in the distribution, movement, and ... more Climate change, as an emerging phenomenon, has led to changes in the distribution, movement, and even risk of extinction of various wildlife species and this has raised concerns among conservation biologists. Different species have two options in the face of climate change, either to adopt or follow their climatic niche to new places through the connectivity of habitats. The modeling of interpatch landscape communications can serve as an effective decision support tool for wildlife managers. This study was conducted to assess the effects of climate change on the distribution and habitat connectivity of the endangered subspecies of Asian black bear (Ursus thibetanus gedrosianus) in the southern and southeastern Iran. The presence points of the species were collected in Provinces of Kerman, Hormozgan, and Sistan-Baluchestan. Habitat modeling was done by the Generalized Linear Model, and 3 machine learning models including Maximum Entropy, Back Propagation based artificial Neural Netwo...
Global climate change poses a new challenge for species and can even push some species toward an ... more Global climate change poses a new challenge for species and can even push some species toward an extinction vortex. The most affected organisms are those with narrow tolerance to the climatic factors but many large mammals such as ungulates with a wider ecological niche are also being affected indirectly. Our research mainly used wild sheep in central Iran as a model species to explore how the suitable habitats will change under different climatic scenarios and to determine if current borders of protected areas will adequately protect habitat requirements. To create habitat models we used animal-vehicle collision points as an input for species presence data. We ran habitat models using MaxEnt modeling approach under different climatic scenarios of the past, present and future (under the climatic scenarios for minimum (RCP2.6) and maximum (RCP8.5) CO 2 concentration trajectories). We tried to estimate the overlap and the width of the ecological niche using relevant metrics. In order to analyze the effectiveness of the protected areas, suitable maps were concerted to binary maps using True Skill Statistic (TSS) threshold and measured the similarity of the binary maps for each scenario using Kappa index. In order to assess the competence of the present protected areas boundary in covering the distribution of species, two different scenarios were employed, which are ensemble scenario 1: an ensemble of the binary maps of the species distribution in Mid-Holocene, present, and RCP2.6; and ensemble scenario 2: an ensemble of binary suitability maps in Mid-Holocene, present, and RCP8.5. Then, the borders of modeled habitats with the boundaries of 23 existing protected areas in two central provinces in Iran were compared. The predicted species distribution under scenario 1 (RCP2.6) was mostly similar to its current distribution (Kappa = 0.53) while the output model under scenario 2 (RCP8.5) indicated a decline in the species distribution range. Under the first ensemble scenario, current borders of the protected areas in Hamedan province showed better efficiency to cover the model species distribution range. Analyzing MaxEnt spatial models under the second climatic scenario suggested that protected areas in both Markazi and Hamedan provinces will not cover “high suitability” areas in the future. Modeling the efficiency of the current protected areas under predicted future climatic scenarios can help the related authorities to plan conservation activities more efficiently.
Mountainous rangelands play a pivotal role in providing forage resources for livestock, particula... more Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method (RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method (90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index (J) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potential habitat. Based on the values of the area under curve (AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.
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Papers by Peyman Karami