A hierarchical approach to understanding physiological associations with climate. Issue 2 (28th November 2021)

• Record Type: Journal Article
• Authors: Anderson, Rodolfo O.; White, Craig R.; Chapple, David G.; Kearney, Michael R.
• Other Names: Algar Adam handlingEditor.
• Is Part Of: Global ecology & biogeography. Volume 31:Issue 2(2022)
• Page Start: 332
• Page End: 346
• Publication Date: 2021-11-28
• Subjects: biophysical ecology -- comparative physiology -- ecophysiology -- environment -- lizards -- microclimate; Ecology -- Periodicals; Biogeography -- Periodicals; Biodiversity -- Periodicals; Macroevolution -- Periodicals; 577
• DOI: 10.1111/geb.13431
• Languages: English
• ISSNs: 1466-822X

Abstract

Abstract: Aim: Our understanding of species' responses to climate depends on choosing the scale for the analysis. Processes driving physiological adaptation that occur at the small spatial scales most relevant to animals may be masked in correlations between organismal traits and broad‐scale climatologies, but the extent to which this undermines our understanding of the macroevolution of physiological traits is unknown. Location: Global. Time period: Current. Major taxa studied: Lizards. Methods: We investigated relationships between physiological traits (water loss rate, standard and field metabolic rates, thermal preferences and critical thermal limits) and environmental conditions in 369 lizard species across sets of environmental predictors representing different processes across hierarchically nested spatial scales: macroclimate, microclimate and biophysical. Results: We found that microclimatic and biophysical predictors had greater explanatory power than macroclimatic predictors for all traits except standard and field metabolic rates. Across spatial scales, standard metabolic rate was negatively related to maximum temperatures whereas field metabolic rate was positively related to minimum temperatures. Thermal preference and critical limits showed expected relationships with environmental temperature, but preferred temperature and critical thermal maxima were most strongly associated with soil water potential, as was evaporative water loss. Main conclusions: The use of proximal environmental predictors, via the principles of microclimatic and biophysical modelling, can be more informative in comparative physiological analyses than the more traditional application of macroclimatic data. In our study it led us to new, testable hypotheses about the role of habitat structure mediated by soil moisture. New datasets and computational methods mean that proximal environmental predictors can be readily computed for any kind of organism and their application to comparative studies should improve our understanding of physiological evolution.