Selection of conservation areas with high biodiversity by Marxan software (Case study: Coastal area at the west of Hormozgan Province)
Subject Areas : environmental managementazadeh vaziri nahad 1 , Seyed Ali Jozi 2 * , Rokhshad Hejazi 3 , Mohammad Reza Shokri 4 , SAEED MALMASI 5
1 - Ph.D. Candidate in Environmental Management, Faculty of Marine Science and Technology, Islamic Azad University, North Tehran Branch, Tehran, Iran.
2 - Full Professor, Department of Environment, Faculty of Marine Science and Technology, Islamic Azad University, North Tehran Branch, Tehran, Iran. *(Corresponding Author)
3 - Assistant Professor, Department of Environmental Management, Faculty of Marine Science and Technology, Islamic Azad University, North Tehran Branch, Tehran, Iran.
4 - Assistant Professor, Department of Ecology and Marin Conservation, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran.
5 - Assistant Professor, Department of Environmental Management, Faculty of Marine Science and Technology, Islamic Azad University, North Tehran Branch, Tehran, Iran.
Keywords: Hormozgan Province, Pollutant resources, Conservation criteria, Biodiversity, Marxan software.,
Abstract :
Background and Objective: In order to preserve diversity of habitats and wildlife, it is inevitable to select the suitable conservation areas representing biodiversity. One of the ways to select conservation areas with high biodiversity is to use Marxan software. The aim of this study was to determine suitable conservation patches with high biodiversity by Marxan software and to identify conservation patches under the pressure of pollutant hotspots in the coastal area at the western part of Hormozgan Province. Material and Methodology: In order to identify the conservation areas with high biodiversity, simulated annealing algorithm of Marxan software was used in two scenarios and for this purpose, 36 protection criteria were examined. ArcGIS 10.3 software was also employed to determine the distributions of plant and animal species, as conservation criteria, pollutant hotspots and the existing protected areas. The conservation patches under the pressure of pollutant hotspots were identified by integrating the results of the selected scenario into the map of pollutant sources. Findings: Results of Marxan software which was done in 2020, revealed that the selected conservation areas and the existing areas protected by the Department of Environment were not compatible in terms of biodiversity conservation, nearly 801349 hectares was required to protect 50% of each conservation criterion (second scenario), and the pressure of industrial centers on the eastern and central parts of Kal-Mehran basin should be reduced. Discussion and Conclusion: Since the second scenario covered all the conservation criteria, except for one criterion, it was considered as the best scenario for achieving the conservation goals. Integration of the results from the second scenario into the map of pollutant resources indicated that the conservation patches at the eastern and central parts of the study area were under pressure. Therefore, it was recommended to expand the current protected areas towards the western parts of the study area.
1. Mehri, A., Mahini A.S., Mirkarimi, S.H. and Rezaee, H.R., 2014, Selecting of the most suitable network of protected areas Using an intelligent algorithm (Case Study: Mazandaran Province). Journal of natural environment, Vol. 67, pp. 222-207. (In Persian)
2. Studwell, A., Hines, E., Nur, N. and Jahncke, J., 2021. Using habitat risk assessment to assess disturbance from maritime activities to inform seabird conservation in a coastal marine ecosystem. Ocean and Coastal Management, Vol.199, pp.1-10.
3. Tang, J., Lu, H., Xue, Y., Li, G., Mao, Y., Deng, Ch. and Li, D., 2021.Data-driven planning adjustments of the functional zoning of Houhe National Nature Reserve. Journal of Global Ecology and Conservation, Vol. 29, pp.1-10.
4. Mazor, T., Runting, R.K., Saunders, M.I., Huang, D., Friess, D.A., Nguyen, N.T.H., Lowe, R.J., Gilmour, J.P., Todd, P.A. and Lovelock, C.E., 2021, Future-proofing conservation priorities for sea level rise in coastal urban ecosystems, Biological Conservation, Vol.260.
5. Teschke, K., Brtnike, P., Hain, S., Herata, H., Liebschner, A., Pehlke, H. and Brey, Th., 2021, Planning marine protected areas under the CCAMLR regime – The case of the Weddell Sea (Antarctica). Marine Policy, Vol. 124, PP.1-11.
6. Janßen, H. and Göke, C., Luttmann, A., 2019. Knowledge integration in Marine Spatial Planning: A practitioners' view on decision support tools with special focus on Marxan. Ocean & Coastal Management. Vol. 168, PP. 130-138.
7. Rodríguez-Basalo, A., Sánchez, F., Punzóna, A. and Gómez-Ballesterosb, M., 2019. Updating the master management plan for El Cachucho MPA (Cantabrian sea) using a spatial planning approach. Continental Shelf Research, Vol. 184, PP. 54-65.
8. 8. Appolloni, L., Sandulli, R., Vetrano, G. and Russo, G.F., 2018. Assessing the effects of habitat patches ensuring propagule supply and different costs inclusion in marine spatial planning through multivariate analyses. Journal of Environmental Management, Vol.214, pp. 45-55.
9. Bax, V. and Francesconi, W., 2019. Conservation gaps and priorities in the Tropical Andes biodiversity hotspot: Implications for the expansion of protected areas. Journal of Environmental Management. Vol. 232, pp. 387-396.
10. Salinas-R, M., Sajama, M., Guti´errez-Ortega, J.S., Ortega-Baes, P. and Estrada-Castillon, A.E., 2018. Identification of endemic vascular plant species hotspots and the effectiveness of the protected areas for their conservation in Sierra Madre Oriental, Mexico. Journal of Nature Conservation. Vol. 46, pp. 6-27.
11. House, Ch., Redmond, D. and Phillips, M.R., 2017. An assessment of the efficiency and ecological representativity of existing marine reserve networks in Wales, UK. Ocean & Coastal Management. Vol. 149, pp. 217-230.
12. Tantipisanuh, N., Savini, T., Cutter, P. and Gale, G.A., 2016. Biodiversity gap analysis of the protected area system of the Indo-Burma Hotspot and priorities for increasing biodiversity representation. Biological Conservation, Vol. 195, pp.203-213.
13. Tsang, Y.P., Tingley, R.W., Hsiao, J. and Infante, D.M., 2019. Identifying high value areas for conservation: Accounting for connections among terrestrial, freshwater, and marine habitats in a tropical island system. Journal of Nature Conservation, Vol. 50, pp.1-14.
14. Luz Fernandes, M.D., Quintela, A. and Alves, F.L., 2018. Identifying conservation priority areas to inform maritime spatial planning: A new approach. Science of Total Environment. Vol. 639, pp. 1088-1098.
15. PMOI, 2019a. Water resources and hydrology of coastal area, Hormozgan Province. Ports and Maritime Organization of Iran. pp.1-10. (In Persian)
16. PMOI, 2019b. Coastal area wildlife, Hormozgan Province. Ports and Maritime Organization of Iran. pp.5-20. (In Persian)
17. PMOI, 2019c. Vegetation of coastal area, Hormozgan Province. Ports and Maritime Organization of Iran. pp. 5-20. (In Persian)
18. PMOI, 2019d. Investigation of the controlled and susceptible areas in the coastal area of Hormozgan Province. Ports and Maritime Organization of Iran. pp.30-40. (In Persian)
19. PMOI, 2019e. Environmental contaminants and threats to coastal area, Hormozgan Province. Ports and Maritime Organization of Iran. pp.1-20. (In Persian)
20. Mehri, A.; Mahini, A.S.; Mirkarimi, S.H.; Rezaee, H.R., 2014. A performance comparison of three computer algorithms in the selection of best protected areas (Case study: Mazandaran province of Iran). Journal of Environmental Studies, 40(1), pp. 4-16. (In Persian)
21. Esfandeh, S.; Kaboli, M.; Eslami, L., 2017. Simulated annealing algorithm as a tool for systematic prioritization of protected area in Alborz province. Journal of Animal Environment. Vol. 9(1), pp.105-122. (In Persian)
22. Game, E. and Grantham, H., 2008. Marxan User Manual for marxan version 1.8.10, Pacific Marine Analysis and Research Association. Vancouver, British Columbia, Canada.
23. Mehri, A.; Mahini A.S.; Mirkarimi, S.H.; Rezaee, H.R., 2012. Prioritization and selection of protected areas using simulated annealing algorithm. Environment and Development Journal. Vol. 3(6). pp. 68-80. (In Persian)
24. Aerts, J.C.J.H and Heuvelink, G.B.M.; 2003. Using simulated annealing for resource allocation, International Journal of Geographical Information Science, Vol.16, pp.571-587.