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Evaluating the combined effect of climate and anthropogenic stressors on marine coastal ecosystems : Insights from a systematic review of cumulative impact assessment approaches

Simeoni, Christian ; Furlan, Elisa ; Pham, Hung Vuong ; Critto, Andrea ; de Juan, Silvia ; Trégarot, Ewan ; Cornet, Cindy C. ; Meesters, Erik ; Fonseca, Catarina and Botelho, Andrea Zita , et al. (2023) In Science of the Total Environment 861.
Abstract

Cumulative impacts increasingly threaten marine and coastal ecosystems. To address this issue, the research community has invested efforts on designing and testing different methodological approaches and tools that apply cumulative impact appraisal schemes for a sound evaluation of the complex interactions and dynamics among multiple pressures affecting marine and coastal ecosystems. Through an iterative scientometric and systematic literature review, this paper provides the state of the art of cumulative impact assessment approaches and applications. It gives a specific attention to cutting-edge approaches that explore and model inter-relations among climatic and anthropogenic pressures, vulnerability and resilience of marine and... (More)

Cumulative impacts increasingly threaten marine and coastal ecosystems. To address this issue, the research community has invested efforts on designing and testing different methodological approaches and tools that apply cumulative impact appraisal schemes for a sound evaluation of the complex interactions and dynamics among multiple pressures affecting marine and coastal ecosystems. Through an iterative scientometric and systematic literature review, this paper provides the state of the art of cumulative impact assessment approaches and applications. It gives a specific attention to cutting-edge approaches that explore and model inter-relations among climatic and anthropogenic pressures, vulnerability and resilience of marine and coastal ecosystems to these pressures, and the resulting changes in ecosystem services flow. Despite recent advances in computer sciences and the rising availability of big data for environmental monitoring and management, this literature review evidenced that the implementation of advanced complex system methods for cumulative risk assessment remains limited. Moreover, experts have only recently started integrating ecosystem services flow into cumulative impact appraisal frameworks, but more as a general assessment endpoint within the overall evaluation process (e.g. changes in the bundle of ecosystem services against cumulative impacts). The review also highlights a lack of integrated approaches and complex tools able to frame, explain, and model spatio-temporal dynamics of marine and coastal ecosystems' response to multiple pressures, as required under relevant EU legislation (e.g., Water Framework and Marine Strategy Framework Directives). Progress in understanding cumulative impacts, exploiting the functionalities of more sophisticated machine learning-based approaches (e.g., big data integration), will support decision-makers in the achievement of environmental and sustainability objectives.

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@article{a9775bf3-9fe7-4952-a67f-cc1ff727efeb,
  abstract     = {{<p>Cumulative impacts increasingly threaten marine and coastal ecosystems. To address this issue, the research community has invested efforts on designing and testing different methodological approaches and tools that apply cumulative impact appraisal schemes for a sound evaluation of the complex interactions and dynamics among multiple pressures affecting marine and coastal ecosystems. Through an iterative scientometric and systematic literature review, this paper provides the state of the art of cumulative impact assessment approaches and applications. It gives a specific attention to cutting-edge approaches that explore and model inter-relations among climatic and anthropogenic pressures, vulnerability and resilience of marine and coastal ecosystems to these pressures, and the resulting changes in ecosystem services flow. Despite recent advances in computer sciences and the rising availability of big data for environmental monitoring and management, this literature review evidenced that the implementation of advanced complex system methods for cumulative risk assessment remains limited. Moreover, experts have only recently started integrating ecosystem services flow into cumulative impact appraisal frameworks, but more as a general assessment endpoint within the overall evaluation process (e.g. changes in the bundle of ecosystem services against cumulative impacts). The review also highlights a lack of integrated approaches and complex tools able to frame, explain, and model spatio-temporal dynamics of marine and coastal ecosystems' response to multiple pressures, as required under relevant EU legislation (e.g., Water Framework and Marine Strategy Framework Directives). Progress in understanding cumulative impacts, exploiting the functionalities of more sophisticated machine learning-based approaches (e.g., big data integration), will support decision-makers in the achievement of environmental and sustainability objectives.</p>}},
  author       = {{Simeoni, Christian and Furlan, Elisa and Pham, Hung Vuong and Critto, Andrea and de Juan, Silvia and Trégarot, Ewan and Cornet, Cindy C. and Meesters, Erik and Fonseca, Catarina and Botelho, Andrea Zita and Krause, Torsten and N'Guetta, Alicia and Cordova, Fabiola Espinoza and Failler, Pierre and Marcomini, Antonio}},
  issn         = {{0048-9697}},
  keywords     = {{Complex inter-relations; Cumulative impact assessment; Ecosystem services; Machine learning; Multi-risk}},
  language     = {{eng}},
  month        = {{02}},
  publisher    = {{Elsevier}},
  series       = {{Science of the Total Environment}},
  title        = {{Evaluating the combined effect of climate and anthropogenic stressors on marine coastal ecosystems : Insights from a systematic review of cumulative impact assessment approaches}},
  url          = {{http://dx.doi.org/10.1016/j.scitotenv.2022.160687}},
  doi          = {{10.1016/j.scitotenv.2022.160687}},
  volume       = {{861}},
  year         = {{2023}},
}