Ecosystem-based management (EBM) is promoted as the solution for sustainable use. An ecosystem-wide assessment methodology is therefore required. In this paper, we present an approach to assess the risk to ecosystem components from human activities common to marine and coastal ecosystems. We build on: (i) a linkage framework that describes how human activities can impact the ecosystem through pressures, and (ii) a qualitative expert judgement assessment of impact chains describing the exposure and sensitivity of ecological components to those activities. Using case study examples applied at European regional sea scale, we evaluate the risk of an adverse ecological impact from current human activities to a suite of ecological components and, once impacted, the time required for recovery to pre-impact conditions should those activities subside. Grouping impact chains by sectors, pressure type, or ecological components enabled impact risks and recovery times to be identified, supporting resource managers in their efforts to prioritize threats for management, identify most at-risk components, and generate time frames for ecosystem recovery.
Our oceans are heavily utilized by a wide variety of human activities that exert pressures which negatively impact marine ecosystems, occasionally leading to unsustainable rates of exploitation. A linkage framework approach can be used to make independent associations between sectors, activities, and the pressures they introduce. However, in reality, many different sectors and their associated activities overlap in time and space, potentially changing the severity of their impact as pressures combine, and undermine the efforts of environmental managers to mitigate the harmful effects of those activities. Here, we present a spatially resolved approach to assess the potential for combined effects using a linkage framework assessment. Using illustrative examples from the Northeast Atlantic, we show the likelihood of changes in pressure severity as a result of multiple overlapping activities. Management options to limit pressure introduction are explored and their benefit—measured as a reduction in the area of seabed impacted—assessed. In its simplest form, the approach can be used to develop potential precautionary management options in areas where data availability is poor and more comprehensive management measures where data are more widely available.
Biological effects techniques have been used with the aim to further integrate biological effects measurements with chemical analysis and apply these methods to provide an assessment of mussel health status. Live native mussels were collected from selected coastal and estuarine sites around the British Isles, including the rivers Test, Thames, Tees, and Clyde, and Lunderston Bay. A suite of biological effects techniques was undertaken on these mussels, including whole organism responses (scope for growth), tissue responses (histopathology), and subcellular responses (lysosomal stability, multi-xenobiotic resistance [MXR], and Comet assay). In addition, whole mussel homogenates were used to measure organic (polycyclic aromatic hydrocarbons [PAH], polychlorinated biphenyls [PCB]) and metal concentrations. Overall the mussels collected from the Thames were in relatively poor health, based on histopathological markers, significantly higher DNA damage, and elevated expression of MXR detoxifying proteins. In contrast, the mussels collected from the River Test were in the best health, based on histopathological markers, respiration rate (SFG), and low frequency of DNA damage. In conclusion, the biological effects techniques were able to distinguish between relatively contaminated and clean environments, with the Thames mussels in worst health. Mussel tissue chemistry data were not able to explain the variations in biological response. Evidence indicates that the difference in the health of the mussels between the different sites was due to either effects of contaminants that were not measured, or the combined effects of mixture toxicity resulting in a threshold effect.
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