Abstract
Cumulative effects result from interacting human activities across space or time, potentially involving multiple sectors, which can affect ecosystem components. Cumulative effects assessments (CEAs) systematically identify and evaluate the compound effects of multiple pressures that may occur within and across industries (and via interaction with climate change induced ecosystem shifts), causing large-scale environmental change. As offshore developments, such as marine renewable energy (MRE), expand there is increasing need for informative, robust cumulative effects assessments. These CEAs may come at great cost in terms of resources and data requirements, as well as the methodological challenges relating to the complex nature of ecosystem interactions. This paper provides a review of the current state of the science for MRE-relevant CEAs. While interest in CEAs has grown rapidly since 2000, data limitations often precluded quantitative approaches. The review highlights that MRE-related CEAs have so far used only a subset of the diverse toolbox of methods available, including expert elicitation, loop analysis, GIS-based techniques, and dynamic models. Developing MRE-specific considerations, addressing data gaps, refining assessments cost-effectively, and learning from integrated ocean management work remain important next steps. Critical research gaps identified include: the absence of standardized, jurisdiction-spanning approaches and terminology; insufficient methods for characterizing nonlinear and indirect cumulative effects; a lack of post-deployment validation of CEA predictions against realized outcomes; minimal accounting for interactions between MRE stressors and climate change; limited observational data on compound and cascading stressor-receptor interactions specific to MRE (e.g., impact-response relationships across life stages and at array scale); and the absence of regionally defined, ecosystem-specific indicator reference points for acceptable levels of effect. Addressing these gaps and additionally nesting project-level (proponent-executed) CEAs within strategic regional (government supported) frameworks, standardizing approaches and terminology across projects and jurisdictions, ensuring transparency in framing and in communicating assumptions and uncertainties, using predictive models where possible, and building centralized data infrastructure to reduce duplication are all needed to advance the impactful use MRE-related CEA. Applying lessons from other industries can help efficiently implement CEAs for MRE while avoiding past errors.