زینب عبیداوی

Monitoring and managing the wildlife populations and habitats required to model the species distribution and habitat suitability. So, Gazella subgutturosa potential distribution in Mishdagh Protected Area was modeled using fuzzy (based on ecological knowledge of local communities) and MaxEnt (based on species occurrence records) approaches; thus, in addition to model the species distribution using maximum entropy algorithm (MaxEnt approach) and fuzzy inference system (fuzzy approach), we can also assess and compare the performance of each approach. In addition, the accuracy of predictive models was tested using jackknife test. Also, we applied threshold of 10%. Based on results of fuzzy and MaxEnt approaches, the most important variables for species potential distribution modelling were land use, distance to farms and distance to water sources. Also, 47.45% and 14.08% of study area predicted as species potential presence area in fuzzy and MaxEnt approaches, respectively. According to results of jackknife test, success rates of fuzzy and MaxEnt approaches were 80.95% and 66.66%, respectively (p

Several modelling techniques have been developed for habitat suitability modelling. In the meantime, the Fuzzy Inference System (FIS) with ability to model uncertainty of input variables is an effective method to model wildlife species habitat suitability. So, Persian Leopard habitat suitability was predicted in Shimbar Protected Area using FIS. Therefore, the effective environmental variables were determined. We also defined and determined the linguistic variables, linguistic values, and range of them. Then, we designed the membership functions of the fuzzy sets of the input and output variables. Also, the definition of the fuzzy rules in the system was performed. Finally, the defuzzification of output was carried out. The accuracy of the predictive model was tested using AUC. Also, 11 FISs were developed to determine sensitivity of the models and important variables in modelling. The results showed that the predictive model was more efficient than the random model (AUC=0.960). In addition, the ‘distance to capra’ was the most important predictor. According to the success of FIS in Persian Leopard habitat suitability modelling, we suggest this method to improve and complete the existing spatial information of wildlife habitats in Iran, especially about regions and species that have been less studied.

Status determination of wildlife habitats is very important in conservation programs and management of wildlife. So, in this study Ursus arctos habitat suitability was modeled using maximum entropy algorithm (MaxEnt) in Shimbar protected area. In order to model the habitat suitability, after investigating and resolving the spatial autocorrelation of occurrence records, spatially independent localities were divided into the calibration and evaluation sets and then were combined with 10 environmental variables (VIF

Sustainable management of wildlife and natural habitats outcome of spatial, quantitative and qualitative studies of wildlife populations and habitats. Which highlights the importance of proper maintenance of existing data and organizing them to increase lifetime of such data to avoid duplication of resampling operations and to save budgets of wildlife conservation and management.So according to the advantages of using database management system for maintenance, usage and management of data, in this study we aim to design and implement spatial database of Khuzestan province wildlife. In order to design and implement the spatial database we used PostgreSQL/PostGIS object-relational database. According to results of our study, PostgreSQL/PostGIS (open source database management system) known as a viable option for the development of wildlife spatial data management capabilities. Also our study indicates that the designed management database system can support all possible queries related to wildlife spatial data, this system can also provide a solution to solve some problems related to management of large volumes of wildlife scattered data. According to the success of this research, we emphasized the necessity of attention to organize and manage the wildlife information and considered it issue in macro polices of Environmental Protection Organization of Iran. Finally, we pointed the necessity of creating and developing a universal database for the wildlife spatial data of Iran.