Iranian Journal of Applied Ecology

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  In recent decades due to steady human population growth coupled with increased use of resources and habitat degradation, conflicts between humans and carnivores have greatly been expanded. In order to mitigate these conflicts based on a clear understanding of conflict patterns, applying the species distribution models as helpful methods has been suggested. Occurring the recent conflict between wolves and local communities in Hamedan province is a clear case of this problem. In this study, capabilities of the genetic algorithm (GARP) were assessed in the modeling spatial distribution of wolf attacks in Hamedan province during 2006-2012. The area under the receiver operating characteristic curve (ROC) was used to evaluate performance of the model. Findings indicated that the applied modelingapproach has a very good performance (area under curve=0.856) inpredicting the spatial distribution of wolf attacks on humans. In addition, based on the results of sensitivity analysis, land-cover t ype, human population density and distance from main road were the most effective parameters. Findings of the present study can be applied in formulation of an adaptive management plan for wolf conservation and mitigation of the conflicts with local communities.

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Constant urban development in today’s world has turned urban growth management into a main challenge in the 21st century. Obtaining spatiotemporal information about the pattern and rate of urban growth is critical to a better understanding of the urban growth process and practicing appropriate management policies. The present study investigated the trend of urban sprawl in Sari, Iran. First, land use and cover maps of the study area were prepared by processing multitemporal Landsat images from 1992, 2002, and 2010. Moreover, the urban growth of the city in 2010 was predicted by combining the Markov-cellular automata model with multi-criteria evaluation (overall Kappa = 83.80% area under the receiver operating characteristic curve ≈ 0.69). Afterward, the same model was applied to simulate urban development in 2021 and 2031. Built-up area per capita and Shannon entropy were then measured to assess urban sprawl in Sari. According to the results of change detection and simulation of urban growth of the study area, the built-up area had increased proportional to population growth since 1992. The same trend is expected to continue until 2031 when the urban area will exceed 2800 hectares. In addition, based on the relative values of Shannon entropy, although Sari has not yet faced the urban sprawl phenomenon, the absence of physical barriers around the city necessitates comprehensive urban management approaches to control urban sprawl and prevent future environmental problems.