Ecosystem resilience models: Comparison, evaluation, and environmental applications
Subject Areas : planning; Environmental education and managementمحمد جواد تجدد 1 * , Bahram Malek Mohamadi 2 , mokarram ravanbakhsh 3 , طوبی عابدی 4
1 - 1- Research Expert, Department of Natural Environment, Environmental Research Institute, Academic Center for Education Culture & Research (ACECR), Rasht, Iran.
2 - 2- Associate Professor, Department of Planning, Environmental Management and HSE, Faculty of Environment, University of Tehran, Tehran, Iran
3 - 3- Assistant Professor, Department of Natural Environment, Environmental Research Institute, Academic Center for Education Culture & Research (ACECR), Rasht, Iran
4 - Assistant Professor, Department of Natural Environment, Environmental Research Institute, Academic Center for Education Culture & Research (ACECR), Rasht, Iran
Keywords: Phytoplankton, Per Ecosystem, Resilience, Modeling, Environment,
Abstract :
Ecosystem resilience is defined as the capacity of an ecosystem to resist and recover after natural or human-induced disturbances and threats. This paper compares and evaluates different ecosystem resilience models and examines their environmental applications. The models are categorized into four groups: theoretical, statistical, agent-based, and hybrid models. The performance and effectiveness of each model are assessed in response to various environmental changes and threats. Furthermore, the environmental applications of these models in conserving and managing natural resources, improving environmental quality, and promoting sustainable development are reviewed. This paper also explores the related concepts and their connection to resilience, elaborates on the concept of ecosystem services and its relationship with resilience, and analyzes the InVEST software along with a case study. Based on the comparisons, no single model can be considered the best under all circumstances. The selection of an appropriate model depends on the research objectives, the type of ecosystem under study, and the availability of data.
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