Stressor equivalents: A framework to prevent perverse outcomes in
data-poor systems
Abstract
Environmental systems suffer from multiple interacting stressors. Each
stressor can act on different parts of the system and at different time
scales. This hampers measuring and predicting the stressors’ impacts on
ecosystems. We propose a conceptual method that integrates available
data with physical constraints over relevant time scales to predict
management outcomes in data-scarce systems affected by multiple
stressors. We first predict the combined stressor levels that threaten a
management target and then define stressor equivalents to to convert
between. These “ball-park” estimates of critical stressor levels help
to identify how the threat posed by interacting stressors responds to
its management. Our approach assists managers in the decision-making
process regarding when to manage a system and how to monitor. We
illustrate our concept with a case study of an invaded island ecosystem,
yet our approach is useful for other data-poor environmental systems
that suffer from multiple cumulative stressors.