Eight habitats, 38 threats and 55 experts: Assessing ecological risk in a multi-use marine region

Challenges in expert ratings of marine habitat and species sensitivity to anthropogenic pressures

Expert knowledge can help fill gaps in quantitative empirical information about complex ecological phenomena. We examined the level of agreement between 21 studies that collected expert ratings of the sensitivity of species and habitats to human activities and their pressures as input data for mapping the human impact on marine ecosystems. Our analyses revealed broad agreement about which human activities and pressures many species and habitats are sensitive to. These agreements reflect a common view of the main threats to ocean ecosystems. In contrast, scores provided by individual experts varied both within and across studies. Sensitivity scores collected with the same method for different regions were often more similar than scores collected for the same region but with different methods. These results highlight how inconsistencies in the design of many expert surveys can lead to variable outcomes. It is important to employ more consistent and theoretically grounded methods and protocols when eliciting expert ratings of species' sensitivity to pressures, to ensure compatibility across studies and maintain rigour in analyses supporting effective ocean management.

Incorporating stressor interactions into spatially explicit cumulative impact assessments

Human-induced stressors are impacting the oceans and reducing the biodiversity of marine ecosystems. The many stressors affecting marine environments do not act in isolation. However, their cumulative impact is difficult to predict. Most of the available methods for quantifying cumulative impacts on marine ecosystems sum the impact of individual stressors to estimate cumulative impact. We demonstrate how experimental evidence from interacting stressors can be accounted for in cumulative impact assessments. We adapted a widely used additive model to incorporate nonadditive stressor interactions into a marine spatially explicit cumulative impact assessment for seagrasses. We combined experimental data on the impact of multiple stressors with spatial data on stressor intensity to test whether stressor interactions impact seagrasses in a case study region in South Australia. We also assessed how uncertainty about cumulative impacts changes when uncertainty in stressor interactions is included in the impact mapping. The results from an additive spatial cumulative impact assessment model were compared with results from the model incorporating interactions. Cumulative effects from the interaction model were more variable than those produced by the additive model. Five of the 15 stressor interactions that we tested produced impacts that significantly deviated from those predicted by an additive model. Areas of our study region that showed the largest discrepancies between the additive and interactive outputs were also associated with higher uncertainty. Our study demonstrates that the inclusion of stressor interactions changes the pattern and intensity of modeled spatial cumulative impact. Additive models have the potential to misrepresent cumulative impact intensity and do not provide the opportunity for targeted mitigation measures when managing the interactive effects of stressors. Appropriate inclusion of interacting stressor data may have implications for the identification of key stressors and the subsequent spatial planning and management of marine ecosystems and biodiversity.

Evaluation of a popular spatial cumulative impact assessment method for marine systems: A seagrass case study

Human activities put stress on our oceans and with a growing global population, the impact is increasing. Stressors rarely act in isolation, with the majority of marine areas being impacted by multiple, concurrent stressors. Marine spatial cumulative impact assessments attempt to estimate the collective impact of multiple stressors on marine environments. However, this is difficult given how stressors interact with one another, and the variable response of ecosystems. As a result, assumptions and generalisations are required when attempting to model cumulative impacts. One fundamental assumption of the most commonly applied, semi-quantitative cumulative impact assessment method is that a change in modelled cumulative impact is correlated with a change in ecosystem condition. However, this assumption has rarely been validated with empirical data. We tested this assumption using a case study of seagrass in a large, inverse estuary in South Australia (Spencer Gulf). We compared three different seagrass condition indices, based on survey data collected in the field, to scores from a spatial cumulative impact model for the study area. One condition index showed no relationship with cumulative impact, whilst the other two indices had very small, negative relationships with cumulative impact. These results suggest that one of the most commonly used methods for assessing cumulative impacts on marine systems is not robust enough to accurately reflect the effect of multiple stressors on seagrasses; possibly due to the number and generality of assumptions involved in the approach. Future methods should acknowledge the complex relationships between stressors, and the impact these relationships can have on ecosystems. This outcome highlights the need for greater evaluation of cumulative impact assessment outputs and the need for data-driven approaches. Our results are a caution for marine scientists and resource managers who may rely on spatial cumulative impact assessment outputs for informing policy and decision-making.

Relative impacts of multiple human stressors in estuaries and coastal waters in the North Sea-Baltic Sea transition zone

The objectives of this study are 1) to map the potential cumulative impacts of multiple human activities and stressors on the ecosystems in the transition zone between the North Sea and Baltic Sea, for Danish waters 2) to analyse differences in stressor contribution between the European Union's Marine Strategy Framework Directive (MSFD, off-shore waters) and Water Framework Directive (WFD, coastal waters), and 3) to assess the local relative importance of stressors for 14 areas along a land-sea gradient, from inner fjords or coastal areas to offshore waters. The mapping of cumulative impacts is anchored in 35 datasets describing a broad range of human stressors and 47 ecosystem components ranging from phytoplankton over benthic communities to fish, seabirds and marine mammals, which we combined by means of a widely used spatial human impact model. Ranking of the stressor impacts for the entire study area revealed that the top five stressors are: 'Nutrients', 'Climate anomalies', 'Non-indigenous species', 'Noise' and 'Contaminants'. The gradient studies showed that some stressors (e.g. 'Nutrients', 'Shipping' and 'Physical modification') have a relatively higher impact within the fjord/estuarine systems whilst others (e.g. 'Fisheries', 'Contaminants' and 'Noise') have relatively higher impact in the open waters. Beyond mapping of cumulative human impacts, we discuss how the maps can be used as an analytical tool to inform ecosystem-based management and marine spatial planning, using the MSFD and WFD as examples.

Uncertainty analysis and robust areas of high and low modeled human impact on the global oceans

Increasing anthropogenic pressure on marine ecosystems from fishing, pollution, climate change, and other sources is a big concern in marine conservation. Scientists have thus developed spatial models to map cumulative human impacts on marine ecosystems. However, these models are based on many assumptions and incorporate data that suffer from substantial incompleteness and inaccuracies. Rather than using a single model, we used Monte Carlo simulations to identify which parts of the oceans are subject to the most and least impact from anthropogenic stressors under 7 simulated sources of uncertainty (factors: e.g., missing stressor data and assuming linear ecosystem responses to stress). Most maps agreed that high-impact areas were located in the Northeast Atlantic, the eastern Mediterranean, the Caribbean, the continental shelf off northern West Africa, offshore parts of the tropical Atlantic, the Indian Ocean east of Madagascar, parts of East and Southeast Asia, parts of the northwestern Pacific, and many coastal waters. Large low-impact areas were located off Antarctica, in the central Pacific, and in the southern Atlantic. Uncertainty in the broad-scale spatial distribution of modeled human impact was caused by the aggregate effects of several factors, rather than being attributable to a single dominant source. In spite of the identified uncertainty in human-impact maps, they can-at broad spatial scales and in combination with other environmental and socioeconomic information-point to priority areas for research and management.

Fine sediment and particulate organic matter: A review and case study on ridge-to-reef transport, transformations, fates, and impacts on marine ecosystems

Studies documenting the effects of land-derived suspended particulate matter (SPM, i.e., particulate organic matter and mineral sediment) on marine ecosystems are typically disconnected from terrestrial studies that determine their origin, transport and fate. This study reviews sources, transport, transformations, fate and effects of SPM along the 'ridge-to-reef' continuum. We show that some of the SPM can be transported over long distances and transformed into large and easily resuspendible organic-rich sediment flocs. These flocs may lead to prolonged reductions in water clarity, impacting upon coral reef, seagrass and fish communities. Using the Great Barrier Reef (NE Australia) as a case study, we identify the latest research tools to determine thresholds of SPM exposure, allowing for an improved appreciation of marine risk. These tools are used to determine ecologically-relevant end-of-basin load targets and reliable marine water quality guidelines, thereby enabling enhanced prioritisation and management of SPM export from ridge-to-reef.

Capturing expert uncertainty in spatial cumulative impact assessments

Understanding the spatial distribution of human impacts on marine environments is necessary for maintaining healthy ecosystems and supporting 'blue economies'. Realistic assessments of impact must consider the cumulative impacts of multiple, coincident threats and the differing vulnerabilities of ecosystems to these threats. Expert knowledge is often used to assess impact in marine ecosystems because empirical data are lacking; however, this introduces uncertainty into the results. As part of a spatial cumulative impact assessment for Spencer Gulf, South Australia, we asked experts to estimate score ranges (best-case, most-likely and worst-case), which accounted for their uncertainty about the effect of 32 threats on eight ecosystems. Expert scores were combined with data on the spatial pattern and intensity of threats to generate cumulative impact maps based on each of the three scoring scenarios, as well as simulations and maps of uncertainty. We compared our method, which explicitly accounts for the experts' knowledge-based uncertainty, with other approaches and found that it provides smaller uncertainty bounds, leading to more constrained assessment results. Collecting these additional data on experts' knowledge-based uncertainty provides transparency and simplifies interpretation of the outputs from spatial cumulative impact assessments, facilitating their application for sustainable resource management and conservation.