Affiliation:
1. Department of Environment, Faculty of Natural Resources and Marine Sciences (FNRMS), Tarbiat Modares University, P.O. Box 46414-356, Noor 46417-76489, Mazandaran, Iran
2. Shirshov Institute of Oceanology, Russian Academy of Sciences, Nakhimovsky Pr. 36, Moscow 117997, Russia
3. Laboratory of Integrated Research of Water Resources, S.Yu. Witte Moscow University, Second Kozhukhovsky Pr. 12, Build. 1, Moscow 115432, Russia
Abstract
Protected areas are referred to around the world as the basis of conservation strategies. Designation of marine protected areas (MPAs) is to preserve marine biodiversity and protect species, habitats in the seas, and oceans. The simulated annealing algorithm (SAA) with other algorithms (swap iterative improvement, normal followed by two step, two step iterative improvement, and normal iterative improvement) in MARXAN conservation solutions software and the multi-criteria evaluation (MCE) method were used to locate MPAs in the Southern Caspian Sea. Then, four methods were examined for site selection that include: (1) Simulated annealing algorithm, (2) MCE with zonal land suitability (ZLS), (3) MCE with compactness and contiguity, and (4) combined method of multi-criteria evaluation with spatial constraints and a simulated annealing algorithm (improved MCE). In the MCE method, we applied different weighted scenarios to locate MPAs. The criteria for determining the desired regions of MPAs included 12 factors gathered in three groups, including: (1) Ecological criteria (distribution of fish Huso huso, Acipenser persicus, Acipenser stellatus, Rutilus frisii kutum, and Alosa braschnikowi; location of coastal protected areas, distance from coastal rivers (Coastline), distance from estuaries and deltas); (2) Physical criteria (distance from the coast, shore sensitive areas); and (3) Socio-economic criteria (distance from densely populated coastal cities, distance from industries near the coast). The results of comparing the algorithms in MARXAN 4.0.6 software showed that the simulated annealing algorithm has a better ratio of border-length/area than other algorithms. Also, the combined method of MCE (improved MCE) selects the best protection patches in terms of location, taking into account the seascape ecology metrics (e.g., patch compactness, edge density, normalized entropy, area metric for patches). Moreover, the results of the comparison of four methods for proposing MPAs based on seascape metrics showed that the combined method of MCE considers a protection network with more contiguity and compactness than the simulated annealing algorithm. The use of seascape ecology can help to preserve and create larger and denser patches in the arrangement of protective areas, because such a selection of protective areas is nature-inspired and can be more bold and appropriate in the course of conservation planning.
Funder
Tarbiat Modares University
Russian Science Foundation Project
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