Striving for population-level conservation: integrating physiology across the biological hierarchy.

The field of conservation physiology strives to achieve conservation goals by revealing physiological mechanisms that drive population declines in the face of human-induced rapid environmental change (HIREC) and has informed many successful conservation actions. However, many studies still struggle to explicitly link individual physiological measures to impacts across the biological hierarchy (to population and ecosystem levels) and instead rely on a 'black box' of assumptions to scale up results for conservation implications. Here, we highlight some examples of studies that were successful in scaling beyond the individual level, including two case studies of well-researched species, and using other studies we highlight challenges and future opportunities to increase the impact of research by scaling up the biological hierarchy. We first examine studies that use individual physiological measures to scale up to population-level impacts and discuss several emerging fields that have made significant steps toward addressing the gap between individual-based and demographic studies, such as macrophysiology and landscape physiology. Next, we examine how future studies can scale from population or species-level to community- and ecosystem-level impacts and discuss avenues of research that can lead to conservation implications at the ecosystem level, such as abiotic gradients and interspecific interactions. In the process, we review methods that researchers can use to make links across the biological hierarchy, including crossing disciplinary boundaries, collaboration and data sharing, spatial modelling and incorporating multiple markers (e.g. physiological, behavioural or demographic) into their research. We recommend future studies incorporating tools that consider the diversity of 'landscapes' experienced by animals at higher levels of the biological hierarchy, will make more effective contributions to conservation and management decisions.