Enhancing the ecological realism of evolutionary mismatch theory.

Following rapid environmental change, why do some animals thrive, while others struggle? We present an expanded, cue-response framework for predicting variation in behavioral responses to novel situations. We show how signal detection theory can be used when individuals have three behavioral options (approach, avoid, or ignore). Based on this theory, we outline predictions about which animals are more likely to make mistakes around novel conditions (i.e., fall for a trap or fail to use an undervalued resource) and the intensity of that mismatch (i.e., severe versus moderate). Explicitly considering three options provides a more holistic perspective and allows us to distinguish between severe and moderate traps, which could guide management strategies in a changing world.

Direct and indirect effects of chemical contaminants on the behaviour, ecology and evolution of wildlife.

Chemical contaminants (e.g. metals, pesticides, pharmaceuticals) are changing ecosystems via effects on wildlife. Indeed, recent work explicitly performed under environmentally realistic conditions reveals that chemical contaminants can have both direct and indirect effects at multiple levels of organization by influencing animal behaviour. Altered behaviour reflects multiple physiological changes and links individual- to population-level processes, thereby representing a sensitive tool for holistically assessing impacts of environmentally relevant contaminant concentrations. Here, we show that even if direct effects of contaminants on behavioural responses are reasonably well documented, there are significant knowledge gaps in understanding both the plasticity (i.e. individual variation) and evolution of contaminant-induced behavioural changes. We explore implications of multi-level processes by developing a conceptual framework that integrates direct and indirect effects on behaviour under environmentally realistic contexts. Our framework illustrates how sublethal behavioural effects of contaminants can be both negative and positive, varying dynamically within the same individuals and populations. This is because linkages within communities will act indirectly to alter and even magnify contaminant-induced effects. Given the increasing pressure on wildlife and ecosystems from chemical pollution, we argue there is a need to incorporate existing knowledge in ecology and evolution to improve ecological hazard and risk assessments.