Document Type : Original Article


1 Department of Natural Resources Engineering, Aras International Campous, Tehran University, Tabriz, Iran

2 Department of Environmental Sciences, Faculy of Natural Resources, University of Tethran, Tehran, Iran

3 Department of Reclamation of Arid and Mountainous Regions, Faculy of Natural Resources, University of Tehran,Tehran, Iran


The comprehensive identification of hazard risks in order to protect against them is one of the main steps in environmental management. Given the importance of environmental impact assessment in sustainable development, the development of a comprehensive system consisting of effective indicators is vital for the creation or exacerbation of environmental risks, on the one hand, and their monitoring, on the other. This comprehensive system can provide categorized information for different levels of decision-making and management. This study aims to assess the vulnerability to zoning of environmental risks by applying an ecosystem services approach. It also aims to integrate the ecosystem services concept into environmental risk assessment. 
Materials and methods:
Initially, a complete list of environmental risks was prepared by desk study, using provincial and national documents and field studies, along with meetings with different institutions. This list consists of all potential or active factors that can lead to risks. The prepared list of risks was reviewed by experts in order to have their feedbacks and to finalize it. In this study, different risks, including an imbalance in provincial development, the likelihood of water erosion and fire, land use change, and incomplete protection of biodiversity were analyzed.  AHP multi criteria decision making was applied for zoning the imbalance of industry with ecological suitability. RUSLE was applied for soil erosion and MAXENT for fire and incomplete protection of wildlife. To study land use/cover changes, cellular automata and the genetic algorithm were integrated.
 Results and discussion:
The results of setting priorities using the multi criteria decision making technique revealed that some risks, including imbalance of industry on land, erosion, vegetation and land use changes, fire and incomplete protection of wildlife are the major risks to be considered. Results show that quality of the ecological area of Alborz Province has significantly reduced in recent years due to human factors such as the establishment of factories, creation of various industrial zones, soil erosion and degradation, drought, depletion of water tables, loss of accessible water resources, improper cropping patterns, population growth due to immigration from other provinces and climate change. The results of vulnerability assessment show that a massive pressure was exerted on sustainable use of the environment of Alborz Province by human impacts. Alborz Province suffers from various risks for which applying environmental services, such as conservation of soil nutrients, biodiversity and diverse vegetation of land, can be effective in their reduction.
Environmental risks are major threats to the degradation of resources and environmental services in Alborz Province which should be controlled and prevented. Complete identification of pre-existing risks and their spatial analysis can help in the development of conservation strategies for vulnerable areas.


  1. Adriaenssens, V., De Baets, B., et al., 2004. Fuzzy rule-based models for decision support in ecosystem management. Science of Total Environment. 319, 1–12.
  2. Antonio, G., Juan-Alfonso, B., Jose-Manuel, N., 2003. Assessing landscape values: a proposal for a multidimensional conceptual model. Ecological. Modeling. 168, 319–341.
  3. Aretano, R., Semeraro, T., Petrosillo, I., De Marco, A., Pasimeni, M.R., Zurlini, G., 2015. applying ecological vulnerability to fire for effective conservation management of natural protected areas. Ecological. Modeling. 295, 163–175.
  4. Baral H., Keenan R.J., Sharma S.K., Stork N.E., Kasel S., 2014, Spatial assessment and mapping of biodiversity and conservation priorities in a heavily modified and fragmented production landscape in north-central Victoria, Australia, Ecological Indicators. 36, 552-562.
  5. Blaikie, P. et al., 2004. At risk: natural hazards, people’s vulnerability and disasters, Routledge.
  6. Burgess N.D., Hales J.D., Riketts T.H., Dinerstein E., 2006, Factoring species, non species values and threats into biodiversity prioritization across the ecorgions of Africa and its islands, Biological Conservation. 127, 383-401.
  7. Connelly J.W., Knick S.T., Schroeder M.A., Stiver S.J., 2004, Conservation assessment of Greater Sage –grouse and sage brush habitats,chapter7,276-400.
  8. Dwyer, A. et al., 2004. Quantifying social vulnerability: a methodology for identifying those at risk to natural hazards, Geoscience Australia Canberra, Australia.
  9. Dzeroski, S., 2001. Applications of symbolic machine learning to ecological. Ecological. Modeling. 146, 263–273.
  10. Eastman, J.R., Jin, W., Kyem, P.A.K. and Toledano, J., 1995. Raster procedures for multi-criteria/multiobjective decisions, Photogrammetric Engineering and Remote Sensing. 61, 539-547.
  11. Enea, M., Salemi, G., 2001. Fuzzy approach to the environmental impact evaluation. Ecological. Modeling. 135, 131–147.
  12. Ervin J., 2003. Rapid Assessment of Protected Area Management Effectiveness in Four Countries. Bio Science. 53, 833-841.
  13. Gardner T.A., Barlow J., Sodhi N.S. and Peres C.A., 2010. A multi-regional assessment of tropical forest biodiversity in a human-modified world. Biological Conservation.143, 2293-2300.
  14. Goda, T. and Matsuoka, Y., 1986. Synthesis and analysis of a comprehensive lake model—with the evaluation of diversity of ecosystem. Ecological. Modeling. 31, 11–32.
  15. Hao, Y. and Zhou, H.C.H., 2002. A grey assessment model of regional eco-environment quality and its application. Environmental Engineering. 20, 66–68.
  16. Ibisch P.L, Nowicki C., Muller R. and Araujo, N., 2002, Methods for the assessment of habitat and species conservation status in data poor countries-case study of Pleurothallidinae of the Andean rain forests of Bolivia. Congress of Conservation of Biodiversity in the Andes and Amazon, 255-246.
  17. Jarvis A., Touval J.L., Schmitz M.C., Sotomayor L. and Hyman G.G., 2010, Assessment of threat to ecosystems in South America. Nature Conservation.18, 180-188.
  18. Kangas, J., Store, R., Leskinen, P., et al., 2000. Improving the quality of landscape ecological forest planning by utilizing advanced decision-support tools. Forest Ecology Management. 132, 157–171
  19. Kazmierczak, Aleksandra & Handley, J. 2011. The Vulnerability concept: use within GRaBS. Available online at:
  20. Malczewski, J., 1999, GIS and Multi Criteria Decision Analysis (New York: Wiley).
  21. Moilanen A., 2012, Spatial Conservation Prioritization in Data-Poor Areas of the World, Brazilian Journal of Nature Conservation.10, 12-19.
  22. Nicholson E., Keith D.A. and Wilcowe, D.S., 2008. Assessing the Threat Status of Ecological Communities, Conservation Biology.23, 259-274.
  23. Omann, I., Jill J., Sigrid G. and Julia, W., 2010. Report on the development of the conceptual framework for the vulnerability assessment. The CLIMSAVE Project. SERI, Vienna, Austria.
  24. Park, Y.-S., Chon, T.-S., Kwak, I.-S., et al., 2004. Hierarchical community classification and assessment of aquatic ecosystems using artificial neural networks. Science Total Environment. 327, 105–122.
  25. Quan, R.C., Wen X. and Xiaonjun, Y., 2002, Effects of human activities on migratory water birds at Lashhai Lake, China. Biological Conservation. 1. 273-279.
  26. Regan H.M., Davis, F.W., Andelman, S.J., Widyanata, A. and Freese, M., 2007, Comprehensive criteria for biodiversity evaluation in conservation planning, Biodiversity Conservation. 2715-2728.
  27. Rodriguez-Rodriguez, D. and Martinez-Vega, J., 2012, Proposal of a system for the integrated and comparative assessment of protected areas, Ecological Indicators.23, 566-572.
  28. Rouget, M., Richardson, D.M., Cowling, R.M., Lloyd, J.W. and Lombard, A.T., 2003, Current patterns of habitat transformation and future threats to biodiversity in terrestrial ecosystems of the Cape Floristic Region, South Africa, Biological Conservation.112, 63-65.
  29. Sahoo, S. and Anirban, D.A., 2016, Environmental Vulnerability Assessment using Grey-AHP based model. Environmental Impact Assessment Review.56, 145-154.
  30. Semeraro, T., Mastroleo, G., Aretano, R., Facchinetti, G., Zurlini, G. and Petrosillo, I., 2016. GIS Fuzzy Expert System for the assessment of ecosystems vulnerability to fire in managing Mediterranean natural protected areas. Environmental Management. 168, 94–103.
  31. Shannon, C., 1948, A mathematical theory of communication. Bell System. Technical. 27, 379-423.
  32. Sik kim, H., 2006. Soil erosion modeling using RUSLE and GIS on the IMHA Watershed, MSc. Thesis. South Korea. Departmant of Civil Engineering.
  33. Thoisy, B., Richard-Hansen C., Goguillon B., Joubert P., Obstancias J., Winterton P. and Brosse, S., 2010. Biodiversity Conservation. 19, 1567-1589.
  34. Van der Knijff, J. M., Jones, R.J.A. and Montanarella , L., 1999. Soil erosion risk assessment in Italy. ISPRA: European Commission Directorate General JRC, Joint Research Centre Space Applications Institute European Soil Bureau.
  35. Wade, A.A., Theobald, D.M. and Laituri M.J., 2011, A multi-scale assessment of local and contextual threats to existing and potential U.S. protected areas, Landscape and Urban Planning.101, 215-227.
  36. Wang, S. Y., Liu, J.S. and Yang, C. J., 2008. Eco-environmental vulnerability evaluation in the Yellow River Basin, China, Pedosphere.18, 171–182.
  37. Xiaofeng, L., Yi Q., Diqiang L., Shirong L., Xiulei W., Bo W. and Chunquan, Z., 2011. Habitat evaluation of wild Ammur tiger ( Panthera tigris altacia) and conservation priority setting in north-eastern China. Environmental Management. 92, 31-42.