Glucocorticoids and land cover: a largescale comparative approach to assess a physiological biomarker for avian conservation

As humans alter landscapes worldwide, land and wildlife managers need reliable tools to assess and monitor responses of wildlife populations. Glucocorticoid (GC) hormone levels are one common physiological metric used to quantify how populations are coping in the context of their environments. Understanding whether GC levels can reflect broad landscape characteristics, using data that are free and commonplace to diverse stakeholders, is an important step towards physiological biomarkers having practical application in management and conservation. We conducted a phylogenetic comparative analysis using publicly available datasets to test the efficacy of GCs as a biomarker for large spatial-scale avian population monitoring. We used hormone data from HormoneBase (51 species), natural history information and US national land cover data to determine if baseline or stress-induced corticosterone varies with the amount of usable land cover types within each species' home range. We found that stress-induced levels, but not baseline, positively correlated with per cent usable land cover both within and across species. Our results indicate that GC concentrations may be a useful biomarker for characterizing populations across a range of habitat availability, and we advocate for more physiological studies on non-traditional species in less studied populations to build on this framework. This article is part of the theme issue 'Endocrine responses to environmental variation: conceptual approaches and recent developments'.

Land cover differentially affects abundance of common and rare birds

While rare species are vulnerable to global change, large declines in common species (i.e., those with large population sizes, large geographic distributions, and/or that are habitat generalists) also are of conservation concern. Understanding if and how commonness mediates species' responses to global change, including land cover change, can help guide conservation strategies. We explored avian population responses to land cover change along a gradient from common to rare species using avian data from the North American Breeding Bird Survey (BBS) and land cover data from the National Land Cover Database for the conterminous United States. Specifically, we used generalized linear mixed effects models to ask if species' commonness affected the relationship between land cover and counts, using the initial amount of and change in land cover surrounding each North American BBS route from 2001 to 2016. We quantified species' commonness as a continuous metric at the national scale using the logarithm (base 10) of each species' total count across all routes in the conterminous United States in 2001. For our focal 15-year period, we found that higher proportions of initial natural land cover favored (i.e., were correlated with higher) counts of rare but not common species. We also found that commonness mediated how change in human land cover, but not natural land cover, was associated with species' counts at the end of the study period. Increases in developed lands did not favor counts of any species. Increases in agriculture and declines in pasture favored counts of common but not rare species. Our findings show a signal of commonness in how species respond to a major dimension of global change. Evaluating how and why commonness mediates species' responses to land cover change can help managers design conservation portfolios that sustain the spectrum of common to rare species.