Quantifying regulatory limits for multiple stressors in an open and transparent way.

Biodiversity is confronted globally by multiple stressors. Environmental policies must regulate these stressors to achieve targets, but how should that be done when the outcomes of limits on one stressor are contingent on other stressors, about which there is imperfect knowledge? Deriving regulatory frameworks that incorporate these contingencies is an emerging challenge at the science-policy interface. To be fit for implementation, these frameworks need to facilitate the inherently sociopolitical process of policy implementation and account transparently for uncertainty, such that practitioners and other stakeholders can more realistically anticipate the range of potential outcomes to policy. We developed an approach to quantify stressor limits that explicitly accounts for multistressor contingencies. Using an invertebrate data set collected over 30 years throughout New Zealand, we combined ecological and ecotoxicological models to predict biodiversity loss as a function of one stressor, treating multistressor contingencies as a form of uncertainty about the outcomes of limits on that stressor. We transparently accounted for that uncertainty by presenting regulatory limits as bands bounded between optimistic and pessimistic views that practitioners may have about the local context within which limits are applied. In addition to transparently accounting for uncertainties, our framework also leaves room for practitioners to build stakeholder consensus when refining limits to suit different local contexts. A criticism of this open, transparent approach is that it creates too much scope for choosing limits that are lenient on polluters, paralyzing on-the-ground management of multiple stressors, but we demonstrate that this is not necessarily the case.