Ecosystems are increasingly under pressure from a wide variety of human impacts, which are likely to become more severe as human populations continue to grow. Various stressors seldom occur in isolation, and co-occurrence of multiple biotic and abiotic stressors is the norm, rather than the exception. For ensuring the persistence of services provided by ecosystems, appropriate assessment and management are essential. These depend on understanding core mechanisms by which stressors influence organisms and how stressors interact in combination. Here we apply a population model of a freshwater amphipod Gammarus pseudolimnaeus, feeding on leaf litter in streams to simulate impacts of hypothetical stressors on individual-, population-, and ecosystem-level properties. Ecosystem properties were approximated as the amount of unprocessed allochthonous leaf litter, a major contributor to the nutrient cycle in forested streams. Hypothetical stressors were targeting feeding, maintenance, growth and reproduction in individual amphipods.
Results/Conclusions
We defined several types of interactions of stressors, including additive, synergistic and antagonistic. We found that the combination of stressors influencing feeding and reproductive rates or maintenance costs, had synergistic impacts on most measured responses. The combination of stressors targeting costs of somatic growth and reproduction had least impact, yielding mostly additive interactions. Combined stressors had effects that were mostly less negative than expected at the level of individual reproduction, but were negatively synergistic on body sizes. Population abundance and biomass tended to be synergistically impacted by stressor combinations. At the ecosystem processing level, we observed mostly positive synergistic impacts of stressor combinations. Our study provides a foundation on which we can build and empirically test multiple stressors with different modes of action. We can advance our understanding of how stressors impact ecosystems and services they provide by integrating stressor impacts on organismal physiology with other relevant information on species biology, their interactions and relevant feedbacks in predictive modeling frameworks.