Investigating cumulative effects across ecological scales

Resilience assessment in complex natural systems

Ecological resilience is the capability of an ecosystem to maintain the same structure and function and avoid crossing catastrophic tipping points (i.e. undergoing irreversible regime shifts). While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are still lacking. Here, we develop an empirical approach to estimate resilience based on the stochastic cusp model derived from catastrophe theory. The cusp model models tipping points derived from a cusp bifurcation. We extend cusp in order to identify the presence of stable and unstable states in complex natural systems. Our Cusp Resilience Assessment (CUSPRA) has three characteristics: (i) it provides estimates on how likely a system is to cross a tipping point (in the form of a cusp bifurcation) characterized by hysteresis, (ii) it assesses resilience in relation to multiple external drivers and (iii) it produces straightforward results for ecosystem-based management. We validate our approach using simulated data and demonstrate its application using empirical time series of an Atlantic cod population and marine ecosystems in the North Sea and the Mediterranean Sea. We show that Cusp Resilience Assessment is a powerful method to empirically estimate resilience in support of a sustainable management of our constantly adapting ecosystems under global climate change.

Quantifying a mass mortality event in freshwater wildlife within the Lower Odra River: Insights from a large European river

In the summer of 2022, the River Odra in Europe witnessed a significant ecological disaster, leading to an unprecedented mass mortality among fish, bivalves, and water snails. The disaster was attributed to toxins released by the haptophyte golden algae, Prymnesium parvum. This study primarily focused on the river's lower section, where the disaster's impacts were exacerbated by the downstream flow of deceased organisms. The Unionidae mussels' mortality rate in this section was estimated at 65 million individuals, marking an 88 % decline in their population. The native mussel, Anodonta anatina, saw the steepest decline at 95 %, while the invasive Sinanodonta woodiana decreased by 15 %. Additionally, a minimum of 147 million dead water snails, predominantly Viviparus viviparus, were found ashore, indicating an 85 % population decline. An estimated 3.3 million fish, predominantly ruffe (Gymnocephalus cernua), bream (Abramis brama), and perch (Perca fluviatilis), were found deceased along the lower Odra, amounting to a biomass of 1025 tons. Across the entire 560 km affected stretch of the river, the estimated fish mortality was 1650 tons, a 60 % decline from pre-disaster levels. The swift deterioration of the river's ecosystem underscores the need for further studies on its adaptive capacity and potential recovery.

Framing future trajectories of human activities in the German North Sea to inform cumulative effects assessments and marine spatial planning

The global industrialization of seascapes and climate change leads to an increased risk of severe impacts on marine ecosystem functioning. While broad scale spatio-temporal assessments of human pressures on marine ecosystems become more available, future trajectories of human activities at regional and local scales remain often speculative. Here we introduce a stepwise process to integrate bottom-up and expert-driven approaches for scenario development to inform cumulative effects assessments and related marine spatial planning (MSP). Following this guidance, we developed optimistic, realistic, and pessimistic scenarios for major human pressures in the German North Sea such as bottom trawling, offshore wind, nutrient discharge, and aggregate extraction. The forecasts comprise quantitative estimates in relation to spatial footprint, intensity, and technological advancements of those pressures for the years 2030 and 2060. Using network analyses, we assessed interactions of the current and future trajectories of pressures thereby accounting for climate change and the growing need for marine conservation. Our results show that future scenarios of spatial distributions could be developed for activities that are spatially refined and included in the current MSP process. Further our detailed analyses of interdependencies of development components revealed that forecasts regarding specific targets and intensities of human activities depend also strongly on future technological advances. For fisheries and nutrient discharge estimates were less certain due to critical socio-ecological interactions in the marine and terrestrial realm. Overall, our approach unraveled such trade-offs and sources of uncertainties. Yet, our quantitative predictive scenarios were built under a sustainability narrative on a profound knowledge of interactions with other sectors and components in and outside the management boundaries. We advocate that they enable a better preparedness for future changes of cumulative pressure on marine ecosystems.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Evaluating the combined effect of climate and anthropogenic stressors on marine coastal ecosystems: Insights from a systematic review of cumulative impact assessment approaches

Cumulative impacts increasingly threaten marine and coastal ecosystems. To address this issue, the research community has invested efforts on designing and testing different methodological approaches and tools that apply cumulative impact appraisal schemes for a sound evaluation of the complex interactions and dynamics among multiple pressures affecting marine and coastal ecosystems. Through an iterative scientometric and systematic literature review, this paper provides the state of the art of cumulative impact assessment approaches and applications. It gives a specific attention to cutting-edge approaches that explore and model inter-relations among climatic and anthropogenic pressures, vulnerability and resilience of marine and coastal ecosystems to these pressures, and the resulting changes in ecosystem services flow. Despite recent advances in computer sciences and the rising availability of big data for environmental monitoring and management, this literature review evidenced that the implementation of advanced complex system methods for cumulative risk assessment remains limited. Moreover, experts have only recently started integrating ecosystem services flow into cumulative impact appraisal frameworks, but more as a general assessment endpoint within the overall evaluation process (e.g. changes in the bundle of ecosystem services against cumulative impacts). The review also highlights a lack of integrated approaches and complex tools able to frame, explain, and model spatio-temporal dynamics of marine and coastal ecosystems' response to multiple pressures, as required under relevant EU legislation (e.g., Water Framework and Marine Strategy Framework Directives). Progress in understanding cumulative impacts, exploiting the functionalities of more sophisticated machine learning-based approaches (e.g., big data integration), will support decision-makers in the achievement of environmental and sustainability objectives.

Response of rove-beetle (Staphylinidae) assemblages to the cumulative effect of wildfire and linear footprint in boreal treed peatlands

Cumulative effects of anthropogenic and natural disturbances have become increasingly relevant in the context of biodiversity conservation. Oil and gas (OG) exploration and extraction activities have created thousands of kilometers of linear footprints in boreal ecosystems of Alberta, Canada. Among these disturbances, seismic lines (narrow corridors cut through the forest) are one of the most common footprints and have become a significant landscape feature influencing the maintenance of forest interior habitats and biodiversity. Wildfire is a common stand-replacing natural disturbance in the boreal forest, and as such, it is hypothesized that its effects can mitigate the linear footprint associated with OG exploration, but only a few studies have examined its effectiveness. We studied the short-term (1 year post-fire) response of rove-beetle assemblages to the combined effects of wildfire and linear footprint in forest, edge, and seismic line habitats at burned and unburned peatlands along the southwest perimeter of the 2016 Horse River wildfire (Fort McMurray). While rove-beetle species richness was higher in seismic lines in both the burned and unburned habitats compared with the adjacent peatland, diversity was greater only in seismic lines of burned areas. Abundance was lower in the burned adjacent peatland but similarly higher in the remaining habitats. Assemblage composition on seismic lines was significantly different from that in the adjacent forest and edge habitats within both burned and unburned sites. Moreover, species composition in burned seismic lines was different from either unburned lines or burned forest and edge. Euaesthethus laeviusculus and Gabrius picipennis were indicator species of burned line habitats, are sensitive to post-fire landscapes and can occupy wet habitats with moss cover more efficiently than when these habitats are surrounded by unburned forest. Although these results are based on short-term responses, they suggest that wildfire did not reduce the linear footprint, and instead, the cumulative effect of these two disturbances had a more complex influence on rove-beetle recovery at the landscape level than for other invertebrates. Therefore, continued monitoring of these sites can become useful to evaluate changes over time and to better understand longer-term biodiversity responses to the cumulative effects of wildfire and linear disturbances in boreal treed peatlands, given the long-lasting effect of such disturbances.

The impact of cumulative stressor effects on uncertainty and ecological risk

To enable environmental management actions to be more effectively prioritized, cumulative effects between multiple stressors need to be accounted for in risk-assessment frameworks. Ecological risk and uncertainty are generally high when multiple stressors occur. In the face of high uncertainty, transparent communication is essential to inform decision-making. The impact of stressor interactions on risk and uncertainty was assessed using generalized linear models for additive and multiplicative effect of six anthropogenic stressors on the abundance of estuarine macrofauna across New Zealand. Models that accounted for multiplicative stressor interactions demonstrated that non-additive effects dominated, had increased explanatory power (6 to 73 % relative increase between models), and thereby reduced the risk of unexpected ecological responses to stress. Secondly, 3D-plots provide important insights in the direction, magnitude and gradients of change, and aid transparency and communication of complex stressor effects. Notably, small changes in a stressor can cause a disproportionally steep gradient of change for a synergistic effect where the tolerance to stressors are lost, and would invoke precautionary management. 3D-plots were able to clearly identify directional shifts where the nature of the interaction changed from antagonistic to synergistic along increasing stressor gradients. For example, increased nitrogen load and exposure caused a shift from positive to negative effect on the abundance of a deposit-feeding polychaete (Magelona). Assessments relying on model coefficient estimates, which provide one effect term, could not capture the complexities observed in 3D-plots and are at risk of mis-identifying interaction types. Finally, visualising model uncertainty demonstrated that although error terms were higher for multiplicative models, they better captured the uncertainty caused by data availability. Together, the steep gradients of change identified in 3D-plots and the higher uncertainty in model predictions in multiplicative models urges more conservative limits to be set for management that account for risk and uncertainty in multiple stressor effects.

Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Using both real and simulated data, we show sample sizes typical of many experiments (<6) can (i) only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed, and (ii) potentially lead to mostly statistical outliers being reported. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user-defined responses and sample sizes, and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect nonadditive. However, estimates of power need to be made while considering the smallest interaction of interest, i.e., the lower limit for a biologically important interaction, which is likely to be system-specific, meaning a general guide is unavailable. We discuss ways in which the smallest interaction of interest can be chosen, and how sample sizes can be increased. Our main analyses relate to the additive null model, but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand or the definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.

Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Using both real and simulated data, we show sample sizes typical of many experiments (<6) can (i) only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed, and (ii) potentially lead to mostly statistical outliers being reported. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user-defined responses and sample sizes, and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect nonadditive. However, estimates of power need to be made while considering the smallest interaction of interest, i.e., the lower limit for a biologically important interaction, which is likely to be system-specific, meaning a general guide is unavailable. We discuss ways in which the smallest interaction of interest can be chosen, and how sample sizes can be increased. Our main analyses relate to the additive null model, but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand or the definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.

Assessing the Cumulative Social Effects of Projects: Lessons from Canadian Hydroelectric Development

Cumulative effects assessments are often expected to include an analysis of cumulative social effects to people, their communities, and livelihoods caused by resource development projects and land use activities. Understanding cumulative social effects is important for decisions about prospective resource development projects, but there has been limited attention devoted to how to complete such an assessment. This paper critically examines how cumulative effects frameworks are applied to social impacts during environmental assessments. We do this by analyzing semi-structured interviews exploring practitioner experience in environmental assessments for hydroelectric development in British Columbia and Manitoba, Canada. The results provide a conceptual framework for cumulative social effects and illustrate how identified challenges for cumulative effects assessment are exacerbated by social impacts that introduce additional complexities in impact identification, assessment, and decision-making. The paper concludes with a discussion of how these challenges can be addressed and recommendations for improving environmental assessment practice.

A Pragmatic Approach for Developing Landbase Cumulative Effects Assessments with Aggregated Impacts Crossing Multiple Ecological Values

In strategic cumulative effects assessments, significant methodological challenges exist for classifying and aggregating impacts when using multiple indicators to determine relative risks upon ecological values from anthropogenic developments. We present a strategic spatial modeling case study CEA (2012-2112) in a 909,000 ha forested landscape of Southwestern British Columbia. We explore decisions needed to calculate and aggregate modeled indicators of cumulative anthropogenic footprints on landscape conditions by examining the choice of quantitative methods. We compare how aggregated impact conclusions may differ for seven indicators grouped in two ways to represent three ecological values (Forest Ecosystems, Riparian Ecosystems and Species at Risk): four expert-defined policy-driven valued components (VCs) or three analytically derived environmental resource factors (ERFs). By explicitly demonstrating methodological choices at each step of impact estimation and aggregation, we outline a practical systematic approach to customize strategic CEAs of this type and retain transparency for interpreting impacts among values. Aggregated impacts for VCs appeared dominated by those estimated from "condition" indicators describing the degree of expected deviations in indicator states from desired conditions; aggregated impacts of ERFs were dominated by "pressure" indicators linked to underlying causal processes assumed important for describing changes in future ecological conditions. High spatial congruence occurred between impact statements for some VCs compared to ERFs representing the same ecological value; poor congruence between others likely occurred because they represented different ecological processes. Aggregated impact classifications may usefully signal impact severity and risk but are dependent on indicator grouping, hence choices for aggregation are integral to the assessment process.

Practical implementation of cumulative‐effects management of marine ecosystems in western North America

Globally, ecosystem structure and function have been degraded by the cumulative effects (CE) of multiple stressors. To maintain ecosystem resilience, there is an urgent need to better account for CE in management decision‐making at various scales. Current laws and regulations are supported by a multitude of frameworks and strategies that vary in application and terminology use across management agencies and geopolitical boundaries. We synthesized management frameworks that accounted for CE in marine ecosystems at the regional and national levels across western North America (Canada, United States, Mexico) to identify similarities and shared challenges to successful implementation. We examined examples of solutions to the identified challenges (e.g., interagency and cross‐border partnerships to overcome challenges of managing for ecologically relevant spatial scales). Management frameworks in general consisted of 3 phases: scoping and structuring the system; characterizing relationships; and evaluating management options. Challenges in the robust implementation of these phases included lack of interagency coordination, minimal incorporation of diverse perspectives, and data deficiencies. Cases that provided solutions to these challenges encouraged coordination at ecological rather than jurisdictional scales, enhanced involvement of stakeholders and Indigenous groups, and used nontraditional data sources for decision‐making. Broader implementation of these approaches, combined with increased interagency and international coordination and collaboration, should facilitate the rapid advancement of more effective CE assessment and ecosystem management in North America and elsewhere.

Monitoring the Characteristics of Ecological Cumulative Effect Due to Mining Disturbance Utilizing Remote Sensing

This study conducted land cover classification and inversion analysis to estimate land surface temperature, soil moisture, specific humidity, atmospheric water vapor density, and relative humidity using remote sensing and multi-source mining data. Using 1990–2020 data from the Shendong mining area in Inner Mongolia, China, the eco-environmental evolution and the ecological cumulative effects (ECE) of mining operations were characterized and analyzed at a long-term scale. The results show that while the eco-environment was generally stable, mining activities affected the eco-environment at the initial stage (1990–2000) to a certain degree. During the rapid development stage of coal mining, the eco-environment was severely damaged, and the ECE were significant at the temporal scale. The absolute value of the change rate of ecological parameters was increasing. Due to an increased focus on ecological restoration, starting in 2010, the environmental indicators gradually stabilized and the eco-environment improved considerably, ushering in a period of stability for coal mining activities. The absolute value of the change rate of ecological parameters became stable. Analysis of the change in eco-environmental indicators with distance and comparison to the contrast area showed the ECE characteristics from mining disturbance at the spatial scale. This study shows that remote sensing technology can be used to characterize the ECE from mining operations and analyze eco-environmental indicators, providing crucial information in support of ecological protection and restoration, particularly in coal mining areas.

On the sensitivity of food webs to multiple stressors

Evaluating the effects of multiple stressors on ecosystems is becoming increasingly vital with global changes. The role of species interactions in propagating the effects of stressors, although widely acknowledged, has yet to be formally explored. Here, we conceptualise how stressors propagate through food webs and explore how they affect simulated three-species motifs and food webs of the Canadian St. Lawrence System. We find that overlooking species interactions invariably underestimate the effects of stressors, and that synergistic and antagonistic effects through food webs are prevalent. We also find that interaction type influences a species' susceptibility to stressors; species in omnivory and tri-trophic food chain interactions in particular are sensitive and prone to synergistic and antagonistic effects. Finally, we find that apex predators were negatively affected and mesopredators benefited from the effects of stressors due to their trophic position in the St. Lawrence System, but that species sensitivity is dependent on food web structure. In conceptualising the effects of multiple stressors on food webs, we bring theory closer to practice and show that considering the intricacies of ecological communities is key to assess the net effects of stressors on species.

Classifying ecosystem stressor interactions: Theory highlights the data limitations of the additive null model and the difficulty in revealing ecological surprises

Understanding how multiple co-occurring environmental stressors combine to affect biodiversity and ecosystem services is an on-going grand challenge for ecology. Currently, progress has been made through accumulating large numbers of smaller-scale empirical studies that are then investigated by meta-analyses to detect general patterns. There is particular interest in detecting, understanding and predicting 'ecological surprises' where stressors interact in a non-additive (e.g. antagonistic or synergistic) manner, but so far few general results have emerged. However, the ability of the statistical tools to recover non-additive interactions in the face of data uncertainty is unstudied, so crucially, we do not know how well the empirical results reflect the true stressor interactions. Here, we investigate the performance of the commonly implemented additive null model. A meta-analysis of a large (545 interactions) empirical dataset for the effects of pairs of stressors on freshwater communities reveals additive interactions dominate individual studies, whereas pooling the data leads to an antagonistic summary interaction class. However, analyses of simulated data from food chain models, where the underlying interactions are known, suggest both sets of results may be due to observation error within the data. Specifically, we show that the additive null model is highly sensitive to observation error, with non-additive interactions being reliably detected at only unrealistically low levels of data uncertainty. Similarly, plausible levels of observation error lead to meta-analyses reporting antagonistic summary interaction classifications even when synergies co-dominate. Therefore, while our empirical results broadly agree with those of previous freshwater meta-analyses, we conclude these patterns may be driven by statistical sampling rather than any ecological mechanisms. Further investigation of candidate null models used to define stressor-pair interactions is essential, and once any artefacts are accounted for, the so-called 'ecological surprises' may be more frequent than was previously assumed.

The consequences of null model selection for predicting mortality from multiple stressors

Many ecological systems are now exposed to multiple stressors, and ecosystem management increasingly requires consideration of the joint effects of multiple stressors on focal populations, communities and ecosystems. In the absence of empirical data, ecosystem managers could use null models based on the combination of independently acting stressors to estimate the joint effects of multiple stressors. Here, we used a simulation study and a meta-analysis to explore the consequences of null model selection for the prediction of mortality resulting from exposure to two stressors. Comparing five existing null models, we show that some null models systematically predict lower mortality rates than others, with predicted mortality rates up to 67.5% higher or 50% lower than the commonly used Simple Addition model. However, the null model predicting the highest mortality rate differed across parameter sets, and therefore there is no general ‘precautionary null model’ for multiple stressors. Using a multi-model framework, we re-analysed data from two earlier meta-analyses and found that 54% of the observed joint effects fell within the range of predictions from the suite of null models. Furthermore, we found that most null models systematically underestimated the observed joint effects, with only the Stressor Addition model showing a bias for overestimation. Finally, we found that the intensity of individual stressors was the strongest predictor of the magnitude of the joint effect across all null models. As a result, studies characterizing the effects of individuals stressors are still required for accurate prediction of mortality resulting from multiple stressors.

Climate impacts on organisms, ecosystems and human societies: integrating OCLTT into a wider context

Physiological studies contribute to a cause and effect understanding of ecological patterns under climate change and identify the scope and limits of adaptation. Across most habitats, this requires analyzing organism responses to warming, which can be modified by other drivers such as acidification and oxygen loss in aquatic environments or excess humidity or drought on land. Experimental findings support the hypothesis that the width and temperature range of thermal performance curves relate to biogeographical range. Current warming causes range shifts, hypothesized to include constraints in aerobic power budget which in turn are elicited by limitations in oxygen supply capacity in relation to demand. Different metabolic scopes involved may set the borders of both the fundamental niche (at standard metabolic rate) and the realized niche (at routine rate). Relative scopes for aerobic performance also set the capacity of species to interact with others at the ecosystem level. Niche limits and widths are shifting and probably interdependent across life stages, with young adults being least thermally vulnerable. The principles of thermal tolerance and performance may also apply to endotherms including humans, their habitat and human society. Overall, phylogenetically based comparisons would need to consider the life cycle of species as well as organism functional properties across climate zones and time scales. This Review concludes with a perspective on how mechanism-based understanding allows scrutinizing often simplified modeling approaches projecting future climate impacts and risks for aquatic and terrestrial ecosystems. It also emphasizes the usefulness of a consensus-building process among experimentalists for better recognition in the climate debate.

A review of the combined effects of climate change and other local human stressors on the marine environment

Climate change (CC) is a key, global driver of change of marine ecosystems. At local and regional scales, other local human stressors (LS) can interact with CC and modify its effects on marine ecosystems. Understanding the response of the marine environment to the combined effects of CC and LS is crucial to inform marine ecosystem-based management and planning, yet our knowledge of the potential effects of such interactions is fragmented. At a global scale, we explored how cumulative effect assessments (CEAs) have addressed CC in the marine realm and discuss progress and shortcomings of current approaches. For this we conducted a systematic review on how CEAs investigated at different levels of biological organization ecological responses, functional aspects, and the combined effect of CC and HS. Globally, the effects of 52 LS and of 27 CC-related stressors on the marine environment have been studied in combination, such as industrial fisheries with change in temperature, or sea level rise with artisanal fisheries, marine litter, change in sediment load and introduced alien species. CC generally intensified the effects of LS at species level. At trophic groups and ecosystem levels, the effects of CC either intensified or mitigated the effects of other HS depending on the trophic groups or the environmental conditions involved, thus suggesting that the combined effects of CC and LS are context-dependent and vary among and within ecosystems. Our results highlight that large-scale assessments on the spatial interaction and combined effects of CC and LS remain limited. More importantly, our results strengthen the urgent need of CEAs to capture local-scale effects of stressors that can exacerbate climate-induced changes. Ultimately, this will allow identifying management measures that aid counteracting CC effects at relevant scales.

Evaluating multiple stressor research in coastal wetlands: A systematic review

Multiple stressors are ubiquitous in coastal ecosystems as a result of increased human activity and development along coastlines. Accurately assessing multiple stressor effects is essential for predicting stressor impacts and informing management to efficiently and effectively mitigate potentially complex ecological responses. Extracting relevant information on multiple stressor studies conducted specifically within coastal wetlands is not possible from existing reviews, posing challenges in highlighting knowledge gaps and guiding future research. Here, we systematically review manipulative studies that assess multiple anthropogenic stressors within saltmarsh, mangrove, and seagrass ecosystems. In the past decade, there has been a rapid increase in publications, with seagrasses receiving the most attention (76 out of a total of 143 studies). Across all studies, nutrient loading and temperature were tested most often (N = 64 and N = 48, respectively), while the most common stressor combination was temperature with salinity (N = 12). Stressor application and study design varied across ecosystems. Studies are mostly conducted in highly controlled environments, without considering how natural variations in the physicochemical environment of coastal ecosystems may influence stressor intensity and timing under these conditions. This may result in vastly different ecological responses across levels of biological organisation. Shifting focus from univariate analytical approaches to multivariate, particularly path analysis, will help elucidate complex ecological relationships and highlight direct and indirect effects of multiple stressors in coastal ecosystems. There is a solid foundation of multiple stressor research in coastal wetlands. However, we recommend future research enhance ecological realism in experimental design by studying the effects of stressor combinations whilst accounting for spatiotemporal variability that reflects natural conditions of coastal ecosystems.

Ecosystem-Based MSP for Enhanced Fisheries Sustainability: An Example from the Northern Adriatic (Chioggia—Venice and Rovigo, Italy)

Human pressures on marine ecosystems significantly increased during last decades. Among the intense anthropic activities, industrial fisheries have caused the alteration of habitats, the reduction of biodiversity and the main fish stocks. The aim of this research, carried out in the Adriatic Sea, was to test a repeatable Marine Spatial Planning framework aimed at enhancing fisheries sustainability through the application of Decision Support Tools and the composition of a catalog of possible measures. The use of these tools proved very useful to identify possible criticalities and facilitate an effective exchange with fisheries stakeholders, local authorities, and fishermen, whose involvement was an indispensable step in the process. Tool-based analyses allowed to assess the spatial footprint of a range of anthropogenic pressures from human activities (e.g., fisheries, maritime traffic, and aquaculture). Within this multi-pressure scenario, special attention was paid to fishing-related disturbances and potential conflicts across different fishing métier and with other sectors. Specifically, results highlighted the spatial features of the major fishing pressures (e.g., abrasion from trawling) affecting essential fish habitats, marine mammals and turtles in the study area. A portfolio of possible management measures is identified for the study area. It provides clear evidence that, in order to mitigate emerging conflicts and cumulative impacts, it is necessary to combine and integrate different types of measures: spatial measures modulated over time, monitoring and control, actions to fill knowledge gaps, concertation—involvement—co-management actions, improvement of governance systems, actions to support innovation in the sector, etc. Given the complex set of measures discussed, this work can provide a useful contribution to the management of fisheries both at local and regional level, fostering the transition to sustainable fisheries.

Cumulative stressors reduce the self-regulating capacity of coastal ecosystems

Marine ecosystems are prone to tipping points, particularly in coastal zones where dramatic changes are associated with interactions between cumulative stressors (e.g., shellfish harvesting, eutrophication and sediment inputs) and ecosystem functions. A common feature of many degraded estuaries is elevated turbidity that reduces incident light to the seafloor, resulting from multiple factors including changes in sediment loading, sea-level rise and increased water column algal biomass. To determine whether cumulative effects of elevated turbidity may result in marked changes in the interactions between ecosystem components driving nutrient processing, we conducted a large-scale experiment manipulating sediment nitrogen concentrations in 15 estuaries across a national-scale gradient in incident light at the seafloor. We identified a threshold in incident light that was related to distinct changes in the ecosystem interaction networks (EIN) that drive nutrient processing. Above this threshold, network connectivity was high with clear mechanistic links to denitrification and the role of large shellfish in nitrogen processing. The EIN analyses revealed interacting stressors resulting in a decoupling of ecosystem processes in turbid estuaries with a lower capacity to denitrify and process nitrogen. This suggests that, as turbidity increases with sediment load, coastal areas can be more vulnerable to eutrophication. The identified interactions between light, nutrient processing and the abundance of large shellfish emphasizes the importance of actions that seek to manage multiple stressors and conserve or enhance shellfish abundance, rather than actions focusing on limiting a single stressor.

Perspectives from landscape ecology can improve environmental impact assessment

The outcomes of environmental impact assessment (EIA) influence millions of hectares of land and can be a contentious process. A vital aspect of an EIA process is consideration of the accumulation of impacts from multiple activities and stressors through a cumulative effects assessment (CEA). An opportunity exists to improve the rigor and utility of CEA and EIA by incorporating core scientific principles of landscape ecology into EIA. With examples from a Canadian context, we explore realistic hypothetical situations demonstrating how integration of core scientific principles could impact EIA outcomes. First, we demonstrate how changing the spatial extent of EIA boundaries can misrepresent cumulative impacts via the exclusion or inclusion of surrounding natural resource development projects. Second, we use network analysis to show how even a seemingly small, localized development project can disrupt regional habitat connectivity. Lastly, we explore the benefits of using long-term historical remote sensing products. Because these approaches are straightforward to implement using publicly available data, they provide sensible opportunities to improve EIA and enhance the monitoring of natural resource development activities in Canada and elsewhere.

Projecting the effects of agricultural conservation practices on stream fish communities in a changing climate

How anticipated climate change might affect long-term outcomes of present-day agricultural conservation practices remains a key uncertainty that could benefit water quality and biodiversity conservation planning. To explore this issue, we forecasted how the stream fish communities in the Western Lake Erie Basin (WLEB) would respond to increasing amounts of agricultural conservation practice (ACP) implementation under two IPCC future greenhouse gas emission scenarios (RCP4.5: moderate reductions; RCP8.5: business-as-usual conditions) during 2020-2065. We used output from 19 General Circulation Models to drive linked agricultural land use (APEX), watershed hydrology (SWAT), and stream fish distribution (boosted regression tree) models, subsequently analyzing how projected changes in habitat would influence fish community composition and functional trait diversity. Our models predicted both positive and negative effects of climate change and ACP implementation on WLEB stream fishes. For most species, climate and ACPs influenced species in the same direction, with climate effects outweighing those of ACP implementation. Functional trait analysis helped clarify the varied responses among species, indicating that more extreme climate change would reduce available habitat for large-bodied, cool-water species with equilibrium life-histories, many of which also are of importance to recreational fishing (e.g., northern pike, smallmouth bass). By contrast, available habitat for warm-water, benthic species with more periodic or opportunistic life-histories (e.g., northern hogsucker, greater redhorse, greenside darter) was predicted to increase. Further, ACP implementation was projected to hasten these shifts, suggesting that efforts to improve water quality could come with costs to other ecosystem services (e.g., recreational fishing opportunities). Collectively, our findings demonstrate the need to consider biological outcomes when developing strategies to mitigate water quality impairment and highlight the value of physical-biological modeling approaches to agricultural and biological conservation planning in a changing climate.

Cumulative impact assessment for ecosystem-based marine spatial planning

Claims for ocean space are growing while marine ecosystems suffer from centuries of insufficient care. Human pressures from runoff, atmospheric emissions, marine pollution, fishing, shipping, military operations and other activities wear on habitats and populations. Ecosystem-based marine spatial planning (MSP) has emerged worldwide as a strategic instrument for handling conflicting spatial claims among competing sectors and the environment. The twofold objective of both boosting the blue economy and protecting the environment is challenging in practice and marine planners need decision support. Cumulative Impact Assessment (CIA) was originally developed to provide an overview of the human imprint on the world's ocean ecosystems. We have now added a scenario component to the CIA model and used it within Swedish ecosystem-based MSP. This has allowed us to project environmental impacts for different planning alternatives throughout the planning process, strengthening the integration of environmental considerations into strategic decision-making. Every MSP decision may entail a local shift of environmental impact, causing positive or negative consequences for ecosystem components. The results from Swedish MSP in the North Sea and Baltic Sea illustrate that MSP certainly has the potential to lower net cumulative environmental impact, both locally and across sea basins, as long as environmental values are rated high and prevailing pressures derive from activities that are part of MSP. By synthesizing innumerous data into comprehensible decision support that informs marine planners of the likely environmental consequences of different options, CIA enables ecosystem-based MSP in practice.

A meta-analysis of multiple stressors on seagrasses in the context of marine spatial cumulative impacts assessment

Humans are placing more strain on the world’s oceans than ever before. Furthermore, marine ecosystems are seldom subjected to single stressors, rather they are frequently exposed to multiple, concurrent stressors. When the combined effect of these stressors is calculated and mapped through cumulative impact assessments, it is often assumed that the effects are additive. However, there is increasing evidence that different combinations of stressors can have non-additive impacts, potentially leading to synergistic and unpredictable impacts on ecosystems. Accurately predicting how stressors interact is important in conservation, as removal of certain stressors could provide a greater benefit, or be more detrimental than would be predicted by an additive model. Here, we conduct a meta-analysis to assess the prevalence of additive, synergistic, and antagonistic stressor interaction effects using seagrasses as case study ecosystems. We found that additive interactions were the most commonly reported in seagrass studies. Synergistic and antagonistic interactions were also common, but there was no clear way of predicting where these non-additive interactions occurred. More studies which synthesise the results of stressor interactions are needed to be able to generalise interactions across ecosystem types, which can then be used to improve models for assessing cumulative impacts.

Operationalizing risk-based cumulative effect assessments in the marine environment

Ecosystem-based management requires an assessment of the cumulative effects of human pressures and environmental change. The operationalization and integration of cumulative effects assessments (CEA) into decision-making processes often lacks a comprehensive and transparent framework. A risk-based CEA framework that divides a CEA in risk identification, risk analysis and risk evaluation, could structure such complex analyses and facilitate the establishment of direct science-policy links. Here, we examine carefully the operationalization of such a risk-based CEA framework with the help of eleven contrasting case studies located in Europe, French Polynesia, and Canada. We show that the CEA framework used at local, sub-regional, and regional scales allowed for a consistent, coherent, and transparent comparison of complex assessments. From our analysis, we pinpoint four emerging issues that, if accurately addressed, can improve the take up of CEA outcomes by management: 1) framing of the CEA context and defining risk criteria; 2) describing the roles of scientists and decision-makers; 3) reducing and structuring complexity; and 4) communicating uncertainty. Moreover, with a set of customized tools we describe and analyze for each case study the nature and location of uncertainty as well as trade-offs regarding available knowledge and data used for the CEA. Ultimately, these tools aid decision-makers to recognize potential caveats and repercussions of management decisions. One key recommendation is to differentiate CEA processes and their context in relation to governance advice, marine spatial planning or regulatory advice. We conclude that future research needs to evaluate how effective management measures are in reducing the risk of cumulative effects. Changing governance structures takes time and is often difficult, but we postulate that well-framed and structured CEA can function as a strategic tool to integrate ecosystem considerations across multiple sectorial policies.

Activity-footprints, pressures-footprints and effects-footprints - Walking the pathway to determining and managing human impacts in the sea

Determining the overall effects of human activities on the estuaries, seas and coasts, as a precursor to marine management, requires quantifying three aspects. These are: (a) the area in which the human activities take place, (b) the area covered by the pressures generated by the activities on the prevailing habitats and species, in which pressures are defined as the mechanisms of change, and (c) the area over which any adverse effects occur. These features can be respectively termed the activities-footprints, the pressures-footprints and the effects-footprints. The latter in turn incorporates both the effects on the natural system and the effects on ecosystem services from which society extracts goods and benefits. This viewpoint article explains the rationale behind this typology and proposes definitions for each of these three types of footprints.

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.

Food availability modulates the combined effects of ocean acidification and warming on fish growth

When organisms are unable to feed ad libitum they may be more susceptible to negative effects of environmental stressors such as ocean acidification and warming (OAW). We reared sea bass (Dicentrarchus labrax) at 15 or 20 °C and at ambient or high PCO2 (650 versus 1750 µatm PCO2; pH = 8.1 or 7.6) at ad libitum feeding and observed no discernible effect of PCO2 on the size-at-age of juveniles after 277 (20 °C) and 367 (15 °C) days. Feeding trials were then conducted including a restricted ration (25% ad libitum). At 15 °C, growth rate increased with ration but was unaffected by PCO2. At 20 °C, acidification and warming acted antagonistically and low feeding level enhanced PCO2 effects. Differences in growth were not merely a consequence of lower food intake but also linked to changes in digestive efficiency. The specific activity of digestive enzymes (amylase, trypsin, phosphatase alkaline and aminopeptidase N) at 20 °C was lower at the higher PCO2 level. Our study highlights the importance of incorporating restricted feeding into experimental designs examining OAW and suggests that ad libitum feeding used in the majority of the studies to date may not have been suitable to detect impacts of ecological significance.

Uncoupled phytoplankton-bacterioplankton relationship by multiple drivers interacting at different temporal scales in a high-mountain Mediterranean lake

Global-change stressors act under different timing, implying complexity and uncertainty in the study of interactive effects of multiple factors on planktonic communities. We manipulated three types of stressors acting in different time frames in an in situ experiment: ultraviolet radiation (UVR); phosphorus (P) concentration; temperature (T) in an oligotrophic Mediterranean high-mountain lake. The aim was to examine how the sensitivity of phytoplankton and bacterioplankton to UVR and their trophic relationship change under nutrient acclimation and abrupt temperature shifts. Phytoplankton and bacteria showed a common pattern of metabolic response to UVR × P addition interaction, with an increase in their production rates, although evidencing an inhibitory UVR effect on primary production (PP) but stimulatory on bacterial production (HBP). An abrupt T shift in plankton acclimated to UVR and P addition decreased the values of PP, evidencing an inhibitory UVR effect, whereas warming increased HBP and eliminated the UVR effect. The weakening of commensalistic and predatory relationship between phyto- and bacterioplankton under all experimental conditions denotes the negative effects of present and future global-change conditions on planktonic food webs towards impairing C flux within the microbial loop.