Abstract

Abstract Accurate assessments of ecosystem condition are needed to inform management processes such as systematic conservation planning and protected area expansion, marine spatial planning and other effective area‐based conservation measures. Yet measuring the condition of dynamic and often largely inaccessible marine ecosystems is extremely difficult and presents a global challenge. Broad‐scale cumulative impact assessments have been used in South Africa as a proxy for marine ecosystem condition in national assessments and reporting because the data are more readily available, and knowledge exists on the impacts of various human activities (or pressures) on marine ecosystems. While useful for national reporting, assessments based on in situ ecological data are also needed at finer scales relevant to management. Applying the HELCOM BEAT approach, this study used in situ ecological data to identify potential methods and indicators that can be applied in South Africa to conduct integrated ecosystem assessments and to assess the suitability of current cumulative impact assessments as a proxy for condition. Aggregated fish indicators demonstrated greater sensitivity to varying human pressures compared with benthic community indicators, with responsiveness differing by location. Notably, site‐level differences in empirical condition emerged that broad‐scale cumulative assessments often missed. The study thus highlighted the varying suitability of cumulative impact scores as proxies for condition, indicating their reliability for fish communities. However, this is also dependent on the pressure types included, the biotic indicators used and the area of focus. Conservation decisions based solely on cumulative impact scores could misrepresent the actual condition of the environment, which makes it difficult to make management decisions, especially at finer scales. As such, conservation initiatives need to be regionally adapted to effectively address the unique pressures and conditions of each area and should be tailored to account for fine‐scale variability, instead of adopting a one‐size‐fits‐all approach.

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