Azadeh Vaziri Nahad; Seyed Ali Jozi; Rokhshad Hejazi; Mohammad Reza Shokri; Saeid Malmasi
Abstract
Introduction: One of the ways to select conservation areas is to use decision support tools such as Marxan. The main purpose of this study is to prioritize and select suitable conservation areas in the coastal area of Kal-Mehran Sub-basin in Hormozgan Province under the different scenarios by using Marxan ...
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Introduction: One of the ways to select conservation areas is to use decision support tools such as Marxan. The main purpose of this study is to prioritize and select suitable conservation areas in the coastal area of Kal-Mehran Sub-basin in Hormozgan Province under the different scenarios by using Marxan software and comparing the conservation areas selected by Marxan with those introduced by the Department of Environment (DoE). Material and methods: In this study, the dispersion of 36 types of animal and plant species was used as conservation criteria to prioritize the conservation patches in the coastal areas using the decision support tool. Geographic Information System (ArcGIS software, v. 10.3) was used to generate the criterion layers and to provide the planning unit layer. Then, the dispersion map of each of these criteria was prepared as Boolean layers (zero and one) for entering into the Marxan decision support software, which is the most commonly used conservation planning software. After preparing the 5 input files of Marxan software (planning unit file, conservation feature file, planning unit versus conservation feature file, boundary length file, and input parameters file), the software was run in the form of three scenarios designed with the goal of protecting 30, 50, and 100% of each criterion and the most suitable patches were introduced for conservation. These patches were then compared with the areas protected by the DoE. Finally, the most suitable scenario was selected by comparing the three scenarios. Results and discussion: The results showed that the first scenario with the goal of protecting 30% of each criterion was successful in fulfilling the conservation goal of all 34 criteria and in total, 14.73% of the existing areas protected by DoE overlapped with those conservation areas selected by the first scenario. In the second scenario, the study area was prioritized with the aim of protecting 50% of each criterion. This scenario was successful in fulfilling the conservation goal of 35 criteria and in total, 26.27% of the selected areas overlapped with the existing protected areas of the DoE. In the third scenario, the study area was prioritized with the aim of protecting 100% of each criterion. This scenario was successful in fulfilling the conservation goal of 30 criteria, and 96.75% of the selected areas overlapped with the existing protected areas of the DoE. Finally, by comparing the results of the mentioned scenarios, it was found that in all three scenarios, the areas under the DoE's protection in the study area did not perform well in terms of achieving the different goals. The second scenario yields more acceptable results than the other scenarios and is only incapable of achieving the conservation goal of just one criterion. Conclusion: In this study, the scenario 2 (with the aim of protecting 50% of each protection criterion) can be considered as the most effective scenario. It is suggested that this scenario be used as a model to modify the boundaries of the DoE’s protected areas in the coastal area of Kal-Mehran Sub-basin in Hormozgan Province, in which case 87.373% (801349 ha) should be added to the current protected areas to remove the existing protective gaps.
