Climate fails to predict wood decomposition at regional scales

  • Mark A. Bradford
  • , Robert J. Warren
  • , Petr Baldrian
  • , Thomas W. Crowther
  • , Daniel S. Maynard
  • , Emily E. Oldfield
  • , William R. Wieder
  • , Stephen A. Wood
  • , Joshua R. King

Research output: Contribution to journalArticlepeer-review

322 Scopus citations

Abstract

Decomposition of organic matter strongly influences ecosystem carbon storage1. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter2-5. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading6,7. We test whether climate controls on the decomposition rate of dead wood-a carbon stock estimated to represent 73 ± 6 Pg carbon globally8-are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago9,10, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Original languageEnglish
Pages (from-to)625-630
Number of pages6
JournalNature Climate Change
Volume4
Issue number7
DOIs
StatePublished - Jul 2014

Fingerprint

Dive into the research topics of 'Climate fails to predict wood decomposition at regional scales'. Together they form a unique fingerprint.

Cite this