Synergistic interactions among growing stressors increase risk to an Arctic ecosystem

The Arctic Ocean is undergoing rapid change due to climate warming and increased human activity. These changes introduce multiple environmental stressors impacting ocean systems and the ecosystem services they provide. Traditional ecosystem models often treat the impacts of multiple stressors additively, summing individual effects or using arbitrary weighting factors. However, growing evidence shows that stressors frequently interact in non-additive ways, particularly synergistically, where the combined effect exceeds the sum of individual effects. This synergistic interaction poses a significant threat, potentially leading to greater harm than expected from individual stressors alone. A meta-analysis reveals that simple additive interactions occur in only 26% of studies, with synergistic and antagonistic interactions occurring in 36% and 38%, respectively. Despite this, direct quantification of stressor effects on ecosystems remains limited. There is a critical need to understand how multiple co-occurring stressors impact entire food webs to anticipate potential tipping points and develop effective management interventions. This study utilizes a novel modeling framework to address this gap, focusing on the rapidly changing Arctic Ocean and specifically the Chukchi Sea.

Existing ecosystem models offer relatively fine-scale predictions of individual stressor effects. However, they often fail to capture the non-linear impacts arising from synergistic interactions between stressors. These interactions can significantly underestimate the actual risk to organisms and ecosystems. Studies have demonstrated the importance of considering cumulative impacts from multiple stressors in marine systems, highlighting the need for methods to account for non-additive effects. Existing approaches such as summing individual effects, multiplying stressors without isolating interactions, or applying weighting factors, are inadequate. The lack of comprehensive analyses of multiple co-occurring stressors impacting entire food webs necessitates a more sophisticated modeling approach to forecast potential tipping points and guide management strategies.

This research employs the Ocean System Interactions, Risks, Instabilities, and Synergies (OSIRIS) framework, a novel approach for exploring stressor interactions in ecosystems. OSIRIS represents ecological systems as networks of interconnected nodes representing biotic and abiotic components. Biotic nodes represent biomass and are linked based on trophic relationships. The model accounts for interactions between any two stressors targeting the same organism with unique interaction terms. The Chukchi Sea ecosystem, known for its relatively simple food web, serves as a case study. The model simulates the ecosystem's behavior over a 20-year period (2020-2040), incorporating various stressors including climate-related chronic stressors (sea ice loss, decreased pH, warming seas) and acute stressors (shipping noise and strikes, subsistence harvesting). The model uses best-estimate parameters from the literature, and then explores the impact of varying the strength of stressor interactions from antagonistic to synergistic. For each organism, a range of interaction strengths and parameter values is used, generating 200 simulations at each level. The mean biomass and standard deviation across these simulations are examined, as is the probability of population collapse (defined as biomass falling below 10% of its initial value). Simulations are run with all interactions, only chronic interactions, and only acute interactions to assess the relative importance of different stressor types and their interactions.

The baseline simulation, using best-estimate parameters, revealed that chronic stressors (e.g., sea ice loss, decreased pH, warming seas) had a more significant negative impact on the Chukchi Sea ecosystem than acute stressors (e.g., shipping noise and strikes, subsistence harvesting). Ice algal biomass decreased, while picophytoplankton and diatoms increased due to increased open water. Higher trophic level responses were more complex, with some organisms (zooplankton, amphipods, clams, and Pacific salmon) showing increased biomass due primarily to increased SST and phytoplankton. Arctic cod, however, declined significantly due to sea ice loss and other factors. Marine mammals also exhibited declines, with some driven by sea ice loss and others by acute stressors. Changes in interaction strength significantly affected population sizes. Organisms whose biomass increased with increasing interaction strength generally responded positively to higher SSTs. Those whose biomass decreased were more sensitive to declines in sea ice or acute stressors. Increased interaction strength also increased biomass variability. Chronic stressors were more important in determining both biomass changes and variability than acute stressors. The probability of population collapse increased significantly with interaction strength, especially for organisms sensitive to chronic stressors. The risk was largely driven by chronic stressors and was significantly underestimated when interactions were neglected. Notably, the number of connections in the model was not directly correlated to the risk of population collapse.

This study demonstrates that synergistic interactions among stressors amplify adverse effects on the Chukchi Sea ecosystem. This synergistic effect is predicted to intensify with increasing stressor magnitude, making ecosystem responses less predictable. The findings highlight the limitations of single-stressor management approaches and underscore the need for holistic, ecosystem-based management strategies. The model reveals significant variation in species sensitivity to stressors and their interactions. The dominant influence of chronic stressors suggests that continued warming, ocean acidification, and ice loss will exacerbate synergistic impacts. The study emphasizes the importance of quantifying synergistic impacts to understand ecosystem risk and inform policy design for mitigating the consequences of environmental change. Uncertainty in estimating organismal responses to stressors and their future trajectories necessitates cautious management approaches.

This research demonstrates that synergistic interactions among multiple stressors substantially increase the risk of population collapse in the Chukchi Sea ecosystem, far beyond predictions based on additive models. Chronic stressors, such as warming, ocean acidification, and sea ice loss, play a more dominant role than acute stressors. This emphasizes the critical need for considering stressor interactions in Arctic ecosystem management and conservation efforts. Future work should focus on identifying strategies for mitigating impacts, particularly those resulting from synergistic interactions of chronic stressors.

The study relies on a model using best-estimate parameters from existing literature, which inherently contains uncertainties. The model’s complexity and the number of interacting factors make it difficult to isolate the precise contribution of each stressor. The extrapolation of environmental data to 2040 introduces uncertainty, particularly regarding human activities and their impacts. The model's simplified representation of complex biological interactions may also limit the accuracy of some predictions.