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

Philos Trans R Soc Lond B Biol Sci. 2024 Mar 25;379(1898):20220508. doi: 10.1098/rstb.2022.0508. Epub 2024 Feb 5.

Abstract

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'.

Keywords: HormoneBase; National Land Cover Database; birds; corticosterone; habitat.

MeSH terms

  • Animals
  • Animals, Wild
  • Biodiversity
  • Biomarkers
  • Birds / physiology
  • Conservation of Natural Resources
  • Ecosystem*
  • Glucocorticoids*
  • Humans
  • Phylogeny

Substances

  • Glucocorticoids
  • Biomarkers