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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

As an “international aquatic ecosystem” in Northern Iran, the Anzali wetland is a nursery for fish and a breeding and wintering area for a wide variety of waterfowl. The wetland is threatened by human activities (deforestation, hunting, tourism, and urbanization), leading to habitat destruction, eutrophication, and sediment accumulation. To stop the degradation and to set up effective protection and restoration in line with the Sustainable Development Goals, scientific insights must be integrated into a practical framework for evidence-based support for policymakers and managers of the Anzali wetland. In this study, the Drivers–Pressure–State–Impact–Response (DPSIR) framework is used as a suitable tool to link human pressures and state changes to derive an overview of the potential impacts. Population growth, intensive agriculture, increased urbanization, and industrialization are the major driving forces that have led to a complex cascade of state changes. For instance, during recent years, water quality deterioration, habitat degradation, and the overgrowth of invasive species in the Anzali wetland watershed have caused negative socio-economic and human health impacts. Integrated and innovative monitoring programs combined with socio-environmental modeling techniques are needed for a more evidence-based management approach as part of a multiresponse strategy for the sustainable development of the wetland system. In this respect, there is a critical gap in useful information concerning biological composition and innovative monitoring methods. Moreover, the relation of biota with human activity and environmental conditions needs to be better quantified. Therefore, ecological modeling techniques based on machine learning and statistics were reviewed for their advantages and disadvantages. The overview of approaches presented here can serve as the basis for scientists, practitioners, and decision-makers to develop and implement evidence-based management programs for the Anzali wetland.

Details

Title
Evidence-Based Management of the Anzali Wetland System (Northern Iran) Based on Innovative Monitoring and Modeling Methods
Author
Marie Anne Eurie Forio  VIAFID ORCID Logo  ; Long Tuan Ho  VIAFID ORCID Logo  ; Goethals, Peter L M
First page
5503
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2533036530
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.