Physiologically informed organismal climatologies reveal unexpected spatiotemporal trends in temperature

Author:

Foulk Aubrey1ORCID,Gouhier Tarik1ORCID,Choi Francis1ORCID,Torossian Jessica L12,Matzelle Allison1,Sittenfeld David34,Helmuth Brian14ORCID

Affiliation:

1. Northeastern University Marine Science Center Department of Marine and Environmental Sciences, , Nahant, MA 01908, USA

2. U.S. Department of Transportation Volpe Center, , Cambridge, MA 02142, USA

3. Museum of Science Center for the Environment, , Boston, MA 02114, USA

4. Northeastern University School of Public Policy and Urban Affairs, , Boston, MA 02115, USA

Abstract

Abstract Body temperature is universally recognized as a dominant driver of biological performance. Although the critical distinction between the temperature of an organism and its surrounding habitat has long been recognized, it remains common practice to assume that trends in air temperature—collected via remote sensing or weather stations—are diagnostic of trends in animal temperature and thus of spatiotemporal patterns of physiological stress and mortality risk. Here, by analysing long-term trends recorded by biomimetic temperature sensors designed to emulate intertidal mussel temperature across the US Pacific Coast, we show that trends in maximal organismal temperature (‘organismal climatologies’) during aerial exposure can differ substantially from those exhibited by co-located environmental data products. Specifically, using linear regression to compare maximal organismal and environmental (air temperature) climatologies, we show that not only are the magnitudes of body and air temperature markedly different, as expected, but so are their temporal trends at both local and biogeographic scales, with some sites showing significant decadal-scale increases in organismal temperature despite reductions in air temperature, or vice versa. The idiosyncratic relationship between the spatiotemporal patterns of organismal and air temperatures suggests that environmental climatology cannot be statistically corrected to serve as an accurate proxy for organismal climatology. Finally, using quantile regression, we show that spatiotemporal trends vary across the distribution of organismal temperature, with extremes shifting in different directions and at different rates than average metrics. Overall, our results highlight the importance of quantifying changes in the entire distribution of temperature to better predict biological performance and dispel the notion that raw or ‘corrected’ environmental (and specially air temperature) climatologies can be used to predict organismal temperature trends. Hence, despite their widespread coverage and availability, the severe limitations of environmental climatologies suggest that their role in conservation and management policy should be carefully considered.

Funder

National Science Foundation

Publisher

Oxford University Press (OUP)

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