The impact of cumulative stressor effects on uncertainty and ecological risk

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.

A process framework for integrating stressor-response functions into cumulative effects models

Stressor-response (SR) functions quantify ecological responses to natural environmental variation or anthropogenic stressors. They are also core drivers of cumulative effects (CE) models, which are increasingly recognized as essential management tools to grapple with the diffuse footprint of human impacts. Here, we provide a process framework for the identification, development, and integration of SR functions into CE models, and highlight their consequential properties, behaviour, criteria for selecting appropriate stressors and responses, and general approaches for deriving them. Management objectives (and causal effect pathways) will determine the ultimate stressor and target response variables of interest (i.e., individual growth/survival, population size, community structure, ecosystem processes), but data availability will constrain whether proxies need to be used for the target stressor or response variables. Available data and confidence in underlying mechanisms will determine whether empirical or mechanistic (theoretical) SR functions are optimal. Uncertainty in underlying SR functions is often the primary source of error in CE modelling, and monitoring outcomes through adaptive management to iteratively refine parameterization of SR functions is a key element of model application. Dealing with stressor interactions is an additional challenge, and in the absence of known or suspected interaction mechanisms, controlling main effects should remain the primary focus. Indicators of suspected interaction presence (i.e., much larger or smaller responses to stressor reduction than expected during monitoring) should be confirmed through adaptive management cycles or targeted stressor manipulations. Where possible, management decisions should selectively take advantage of interactions to strategically mitigate stressor impacts (i.e., by using antagonisms to suppress stressor impacts, and by using synergisms to efficiently reduce them).

Cumulative effects of multiple stressors impact an endangered seagrass population and fish communities

Coastal ecosystems are becoming increasingly threatened by human activities and there is growing appreciation that management must consider the impacts of multiple stressors. Cumulative effects assessments (CEAs) have become a popular tool for identifying the distribution and intensity of multiple human stressors in coastal ecosystems. Few studies, however, have demonstrated strong correlations between CEAs and change in ecosystem condition, questioning its management use. Here, we apply a CEA to the endangered seagrass Posidonia australis in Pittwater, NSW, Australia, using spatial data on known stressors to seagrass related to foreshore development, water quality, vessel traffic and fishing. We tested how well cumulative effects scores explained changes in P. australis extent measured between 2005 and 2019 using high-resolution aerial imagery. A negative correlation between P. australis and estimated cumulative effects scores was observed (R2 = 22 %), and we identified a threshold of cumulative effects above which losses of P. australis became more likely. Using baited remote underwater video, we surveyed fishes over P. australis and non-vegetated sediments to infer and quantify how impacts of cumulative effects to P. australis extent would flow on to fish assemblages. P. australis contained a distinct assemblage of fish, and on non-vegetated sediments the abundance of sparids, which are of importance to fisheries, increased with closer proximity to P. australis. Our results demonstrate the negative impact of multiple stressors on P. australis and the consequences for fish biodiversity and fisheries production across much of the estuary. Management actions aimed at reducing or limiting cumulative effects to low and moderate levels will help conserve P. australis and its associated fish biodiversity and productivity.

Implications for the conservation of deep-water corals in the face of multiple stressors: A case study from the New Zealand region

The waters around New Zealand are a global hotspot of biodiversity for deep-water corals; approximately one sixth of the known deep-water coral species of the world have been recorded in the region. Deep-water corals are vulnerable to climate-related stressors and from the damaging effects of commercial fisheries. Current protection measures do not account for the vulnerability of deep-water corals to future climatic conditions, which are predicted to alter the distribution of suitable habitat for them. Using recently developed habitat suitability models for 12 taxa of deep-water corals fitted to current and future seafloor environmental conditions (under different future climatic conditions: SSP2 - 4.5 and SSP3 - 7.0) we explore possible levels of spatial protection using the decision-support tool Zonation. Specifically, we assess the impact of bottom trawling on predictions of current distributions of deep-water corals, and then assess the effectiveness of possible protection for deep-water corals, while accounting for habitat refugia under future climatic conditions. The cumulative impact of bottom trawling was predicted to impact all taxa, but particularly the reef-forming corals. Core areas of suitable habitat were predicted to decrease under future climatic conditions for many taxa. We found that designing protection using current day predictions alone, having accounted for the impacts of historic fishing impacts, was unlikely to provide adequate conservation for deep water-corals under future climate change. Accounting for future distributions in spatial planning identified areas which may provide climate refugia whilst still providing efficient protection for current distributions. These gains in conservation value may be particularly important given the predicted reduction in suitable habitat for deep-water corals due to bottom fishing and climate change. Finally, the possible impact that protection measures may have on deep-water fisheries was assessed using a measure of current fishing value (kg km-2 fish) and future fishing value (predicted under future climate change scenarios).

Multi-Scenario Simulation to Predict Ecological Risk Posed by Urban Sprawl with Spontaneous Growth: A Case Study of Quanzhou

The rapid expansion of different types of urban land continues to erode natural and semi-natural ecological space and causes irreversible ecological damage to rapidly industrialized and urbanized areas. This work considers Quanzhou, a typical industrial and trade city in southeastern China as the research area and uses a Markov chain integrated into the patch-generating land use simulation (PLUS) model to simulate the urban expansion of Quanzhou from 2005 to 2018. The PLUS model uses the random forest algorithm to determine the contribution of driving factors and simulate the organic and spontaneous growth process based on the seed generation mechanism of multi-class random patches. Next, leveraging the importance of ecosystem services and ecological sensitivity as indicators of evaluation endpoints, we explore the temporal and spatial evolution of ecological risks from 2018 to 2031 under the scenarios of business as usual (BAU), industrial priority, and urban transformation scenarios. The evaluation endpoints cover water conservation service, soil conservation service, biodiversity maintenance service, soil erosion sensitivity, riverside sensitivity, and soil fertility. The ecological risk studied in this work involves the way in which different types of construction land expansion can possibly affect the ecosystem. The ecological risk index is divided into five levels. The results show that during the calibration simulation period from 2005 to 2018 the overall accuracy and Kappa coefficient reached 91.77% and 0.878, respectively. When the percent-of-seeds (PoS) parameter of random patch seeds equals 0.0001, the figure of merit of the simulated urban construction land improves by 3.9% compared with the logistic-based cellular automata model (Logistic-CA) considering organic growth. When PoS = 0.02, the figure of merit of the simulated industrial and mining land is 6.5% higher than that of the Logistic-CA model. The spatial reconstruction of multiple types of construction land under different urban development goals shows significant spatial differentiation on the district and county scale. In the industrial-priority scenario, the area of industrial and mining land is increased by 20% compared with the BAU scenario, but the high-level risk area is 42.5% larger than in the BAU scenario. Comparing the spatial distribution of risks under the BAU scenario, the urban transition scenario is mainly manifested as the expansion of medium-level risk areas around Quanzhou Bay and the southern region. In the future, the study area should appropriately reduce the agglomeration scale of urban development and increase the policy efforts to guide the development of industrial land to the southeast.

Construction and Optimization of Wetland Landscape Ecological Network in Dongying City, China

Rapid urbanization has led to deteriorated wetland water quality, reduced biodiversity, and fragmented wetland landscapes, which seriously threaten the sustainable development of regional ecology. Based on land use data of Dongying City, Shandong Province, in 2020, this study selected the landscape disturbance degree and landscape fragility index to construct a landscape ecological risk evaluation model and to analyze the spatial distribution characteristics of landscape ecological risk in Dongying City in 2020. The MSPA-Conefor-MCR model was used to extract the ecological network of wetlands in Dongying City, and the topological structure indices were quantitatively analyzed. Combined with the actual situation within the study area, the source sites to be optimized were identified by risk zoning and source importance; the ecological resistance surface was modified using landscape ecological risk, and the ecological network was optimized by simulating edge increase in order to evaluate the robustness of the ecological network before and after optimization and to verify the edge increase effect. The results show that the ecological risk in Dongying is high, mainly distributed in the central region and extending to the northeast, southeast, southwest, and northwest. A total of 131 ecological source sites (6 core and 125 resting-stone source sites) and 180 ecological corridors were extracted, and the whole ecological network was found to be less stable and to have stronger network heterogeneity using a topological analysis. By simulating 11 additional edges, the robustness of the optimized ecological network was significantly improved. Optimizing the simulated-edge increase can enhance the smoothness of ecological energy flow, which can provide a scientific basis for the construction of the ecological security pattern of wetlands in Dongying City.