2022
DOI: 10.1088/2516-1083/ac702a
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An ecosystem-based natural capital evaluation framework that combines environmental and socio-economic implications of offshore renewable energy developments

Abstract: There is about to be an abrupt step-change in the use of coastal seas around the globe, specifically by the addition of large-scale offshore renewable energy developments to combat climate change. Developing this sustainable energy supply will require trade-offs between both direct and indirect environmental effects, as well as spatial conflicts with marine uses like shipping, fishing, and recreation. However, the nexus between drivers, such as changes in the bio-physical environment from the introduction of s… Show more

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Cited by 7 publications
(6 citation statements)
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“…As mentioned in G2, work within core Supergen ORE has seen the application of pragmatic Bayesian ecosystem modelling that has allowed a novel, whole system perspective to translate dynamic evidence-based ecosystem effects into natural, social, and economic metrics. The approach provides a common 'currency' to communicate and generalise modelling outputs that works across different disciplines and user groups (Trifonova et al 2022b). The Bayesian network approach enables a more accurate spatial overlap analysis which includes the outcomes of interactions between a variety of existing marine uses (renewables, fisheries), the results from which will be able to support marine spatial planners to balance the need for profitability with the need to minimise conflicts and tensions amongst existing and any future planned marine uses of natural resources.…”
Section: G3 Ecosystem Modellingmentioning
confidence: 99%
See 2 more Smart Citations
“…As mentioned in G2, work within core Supergen ORE has seen the application of pragmatic Bayesian ecosystem modelling that has allowed a novel, whole system perspective to translate dynamic evidence-based ecosystem effects into natural, social, and economic metrics. The approach provides a common 'currency' to communicate and generalise modelling outputs that works across different disciplines and user groups (Trifonova et al 2022b). The Bayesian network approach enables a more accurate spatial overlap analysis which includes the outcomes of interactions between a variety of existing marine uses (renewables, fisheries), the results from which will be able to support marine spatial planners to balance the need for profitability with the need to minimise conflicts and tensions amongst existing and any future planned marine uses of natural resources.…”
Section: G3 Ecosystem Modellingmentioning
confidence: 99%
“…fish biomass), social (e.g. ecosystem services) via natural capital/ ecosystem services estimates and can be fed into gross value added (GVA) models (Trifonova et al 2022b) ensuring that policies can be developed in a coherent manner for the maximal benefit of society as a whole and will ideally enable the integration of fisheries activities in order to better assess issues, such as potential fisheries displacement and encourage involvement of the industry at the beginning of the planning processes. Table A1 in the appendix summarises other ongoing and recent projects related to Theme G3.…”
Section: G3 Ecosystem Modellingmentioning
confidence: 99%
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“…Moreover, such a modelling approach will highlight which MSFD descriptors are more ecologically significant when assessing overall GES and CIA (Elliott et al, 2015b). The larger ecosystem modelling will also contribute to a better understanding of ecosystem services and their socio-economic implications on other activities, such as fisheries likely to be displaced under MREDs and climate change scenarios (Kafas, 2018;Trifonova et al, 2022;Van de Pol et al, 2023). However, our proposed holistic approach integrating the MSFD into the SEA and EIA processes requires using an open-source national scheme for data sharing of ecosystem modelling outputs and needs to link MEDIN and MDE (grey bubbles and yellow arrows in Fig.…”
Section: Tool 2: Ecosystem Modelling Frameworkmentioning
confidence: 99%
“…The Millennium Ecosystem Assessment (MA) classifies ESs into four broad categories: provisioning, regulating, supporting, and cultural services [3]. Because ESs can characterize elements and functions of ecosystems, they have become essential indicators for studying ecological and environmental issues [4]. However, ESs are influenced by both natural and socioeconomic factors [5,6].…”
Section: Introductionmentioning
confidence: 99%