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Ecosystems

pp 1–11 | Cite as

The Shifting Role of mRUE for Regulating Ecosystem Production

  • David E. ReedEmail author
  • Jiquan Chen
  • Michael Abraha
  • G. Philip Robertson
  • Kyla M. Dahlin
Article

Abstract

To create a comprehensive view of ecosystem resource use, we integrated parallel resource use efficiency observations into a multiple-resource use efficiency (mRUE) framework using a dynamic factor analysis model. Results from 56 site-years of eddy covariance data and mRUE factors for a site in the US Midwest show temporal dynamics and coherence (using Pearson’s R) among resources are associated with interannual variation in precipitation. Loading factors are derived from mRUE observations and quantify how strongly data are connected to the underlying ecosystem state. Water and light resource use loading factors are coherent at annual timescales (Pearson’s R of 0.86), whereas declining patterns of carbon use efficiency loading factors highlight the ecosystem’s trade-off between carbon uptake and respiration during the growing season. At annual and monthly timescales, influence decreases from ~ 85 to ~ 65% for loading factors for carbon use, while influence of light use loading factors peaks to ~ 60% at growing season timescales. Quantifying variation in ecosystem function provides novel insights into the temporal dynamics of changing importance of multiple resources to ecosystem function.

Keywords

multiple-resource use efficiency ecosystem production eddy covariance dynamic factor analysis carbon cycling ecosystem function 

Notes

Acknowledgements

This material is based upon work supported in part by the NASA Carbon Cycle & Ecosystems program (NNX17AE16G); the Great Lakes Bioenergy Research Center funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Numbers DE-SC0018409 and DE-FC02-07ER64494; and the Long-term Ecological Research Program (DEB 1637653) at the Kellogg Biological Station. We thank Yost R. for programming assistance with R and MATLAB, as well as Tarek El-Madany and one anonymous reviewer for their constructive comments on our work.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • David E. Reed
    • 1
    Email author
  • Jiquan Chen
    • 1
  • Michael Abraha
    • 1
  • G. Philip Robertson
    • 1
  • Kyla M. Dahlin
    • 1
  1. 1.Michigan State UniversityEast LansingUSA

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