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Data from: Extreme operative temperatures are better descriptors of the thermal environment than mean temperatures

Cite this dataset

Camacho, Agustín; Trefaut Rodrigues, Miguel; Navas, Carlos Arturo; Navas, Carlos (2016). Data from: Extreme operative temperatures are better descriptors of the thermal environment than mean temperatures [Dataset]. Dryad. https://doi.org/10.5061/dryad.42p4q

Abstract

In ecological studies of thermal biology the thermal environment is most frequently described using the mean or other measures of central tendency in environmental temperatures. However, this procedure may hide biologically relevant thermal variation for ectotherms, potentially misleading interpretations. Extremes of operative temperatures (EOT) can help with this problem by bracketing the thermal environment of focal animals. Within this paper, we quantify how mean operative temperatures relate to the range of simultaneously available operative temperatures (a measure of error). We also show how EOT: 1) detect more thermal differences among microsites than measures of central tendency, like the mean OT, 2) allow inferring on microsite use by ectothermic animals, and 3) clarify the relationships between field operative temperatures and temperatures measured at weather stations (WS). To do that, we explored operative temperatures measured at four sites of the Brazilian Caatingas and their correspondent nearest weather stations. We found that the daily mean OT can hide temperature ranges of 41 °C simultaneously available at our study sites. In addition, EOT detected more thermal differences among microsites than central quantiles. We also show how EOT allow inferring about microsite use of ectothermic animals in a given site. Finally, the daily maximum temperature and the daily temperature range measured at WSs predicted well the minimum available field OT at localities many kilometers away. Based on our results, we recommend the use of EOT, instead of mean OT, in thermal ecology studies.

Usage notes

Location

Caatinga
Northeast Brazil