DOI: 10.5061/dryad.s87008d
title: Data from: Cross-biome patterns in soil microbial respiration predictable from evolutionary theory on thermal adaptation

description: Climate warming may stimulate microbial metabolism of soil carbon, causing
 a carbon cycle-climate feedback whereby carbon is redistributed from soil
 to atmospheric CO2. The magnitude of this feedback is uncertain, in part
 because warming-induced shifts in microbial physiology and/or community
 composition could retard or accelerate soil carbon losses. Here, we
 measure microbial respiration rates for soils collected from 22 sites in
 each of three years, at locations spanning boreal to tropical climates.
 Respiration was measured in the laboratory with standard temperatures,
 moisture and excess carbon substrate, to allow physiological and community
 effects to be detected independent from the influence of these abiotic
 controls. Patterns in respiration for soils collected across the climate
 gradient are consistent with evolutionary theory on physiological
 responses that compensate for positive effects of temperature on
 metabolism. Respiration rates per unit microbial biomass were as much as
 2.6-times higher for soils sampled from sites with a mean annual
 temperature (MAT) of -2.0 versus 21.7ºC. Subsequent 100-day incubations
 suggested differences in the plasticity of the thermal response among
 microbial communities, with communities sampled from sites with higher MAT
 having a more plastic response. Our findings are consistent with adaptive
 metabolic responses to contrasting thermal regimes that are also observed
 in plants and animals. These results may help build confidence in soil
 carbon-climate feedback projections by improving understanding of
 microbial processes represented in biogeochemical models.
description: BradfordetalSTARObsDataThe data file is named ‘BradfordetalSTARObsData.csv’. A full description of the original purpose of these data, as well as the methods used to collect them, are described in the accepted manuscript. Data are organized across 30 columns, and 792 rows of data, with a single header row with the column title. The code file used to analyze these data is named ‘BradfordetalSTARCODE.txt’ and contains all R (the statistical freeware package) code used for data analysis in the accepted manuscript. Analytical steps are explained ahead of each section of code within the code file. Full description of the variables and their units for these field collected soils are in the associated readme.txt fileBradfordetalSTARIncDataThe data file is named ‘BradfordetalSTARIncData.csv’. A full description of the original purpose of these data, as well as the methods used to collect them, are described in the accepted manuscript. Data are organized across 31 columns, and 234 rows of data, with a single header row with the column title. The code file used to analyze these data is named ‘BradfordetalSTARCODE.txt’ and contains all R (the statistical freeware package) code used for data analysis in the accepted manuscript. Analytical steps are explained ahead of each section of code within the code file. Full description of the variables and their units for these field collected and then lab-incubated soils are in the associated readme.txt fileBradfordetalSTARCODEThe code file used to analyze the two associated data sets is named ‘BradfordetalSTARCODE.txt’ and contains all R (the statistical freeware package) code used for data analysis in the accepted manuscript. Analytical steps are explained ahead of each section of code within the code file. Full data and description of the variables and their units for the field and lab-incubated soils are in the associated csv and associated readme.txt files