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Refocusing multiple stressor research around the targets and scales of ecological impacts.

Benno I SimmonsPenelope S A BlythJulia L BlanchardTom CleggEva DelmasAurélie GarnierChristopher A GriffithsUte JacobFrank PennekampOwen L PetcheyTimothée PoisotThomas J WebbAndrew P Beckerman
Published in: Nature ecology & evolution (2021)
Ecological communities face a variety of environmental and anthropogenic stressors acting simultaneously. Stressor impacts can combine additively or can interact, causing synergistic or antagonistic effects. Our knowledge of when and how interactions arise is limited, as most models and experiments only consider the effect of a small number of non-interacting stressors at one or few scales of ecological organization. This is concerning because it could lead to significant underestimations or overestimations of threats to biodiversity. Furthermore, stressors have been largely classified by their source rather than by the mechanisms and ecological scales at which they act (the target). Here, we argue, first, that a more nuanced classification of stressors by target and ecological scale can generate valuable new insights and hypotheses about stressor interactions. Second, that the predictability of multiple stressor effects, and consistent patterns in their impacts, can be evaluated by examining the distribution of stressor effects across targets and ecological scales. Third, that a variety of existing mechanistic and statistical modelling tools can play an important role in our framework and advance multiple stressor research.
Keyphrases
  • human health
  • climate change
  • risk assessment
  • machine learning
  • deep learning
  • cancer therapy