Simulated annealing algorithm as a tool for systematic prioritization of protected area in Alborz province, Iran
Abstract:
Regarding to importance and necessity of biodiversity conservation to preserve wildlife habitats and populations, representative natural areas should be selected. The aim of this research is prioritization of candidate areas for environmental protection in Alborz Province. For this purpose, habitats of 5 mammal species, reptile species and important distribution area for raptors and waterfowl birds were used as input criteria. Maximum Entropy (MaxEnt) method was used to model the mammals’, reptiles and birds habitats. Simulated annealing was used for prioritization through Marxan software. The goal is to preserve 20, 30,40 and 60 percent of each protection criteria. Based on the results of different scenarios, current protected areas network in Alborz Province were found inadequate to achieve the required conservation goals. These areas only provided the set goals for 4 protection criteria. In most scenarios, overlap between the proposed conservation network and current protected areas were less than 49.5 percent. Results show that different parameters including conservation goals, scale, algorithms and compactness of zones affect the systematic prioritization and selection of protected areas. Consequently, determination of appropriate values for these parameters is among the most important steps in conservation planning. The parameters investigated in this research showed that the simulated annealing algorithm provides plausible results in all cases and its application helps identify the best zones for protection. Therefore, using this method to modify boundaries of current protected areas and introduce new sites for protection of animal species is proposed in the Alborz Province.
Language:
Persian
Published:
Journal of Animal Environment, Volume:9 Issue:1, 2017
Pages:
105 - 122
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