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Title: Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks

Abstract

The complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the C fate and persistence under future climate scenarios. As these proxies are used at increasingly larger scales, the C pools and processes that proxies represent must be thoughtfully considered in order to minimize uncertainties in empirical understanding, as well as in model parameters and in model outcomes. The importance of these uncertainties is further amplified by the current need to make predictions of the C cycle for the non steady state environmental conditions resulting from global climate change. To clarify the appropriate uses of proxy variables, we provide specific examples of proxy variables that could improve decision making, adaptation choices, and modeling skill, while not foreclosing on – and also encouraging – continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used tomore » study soil organic matter: metabolic quotient, clay content, and physical fractionation. We also consider emerging data types, specifically genome-sequence data, and how these serve as proxies for microbial community activities. We opine that the demand for increasing mechanistic detail, and the flood of data from new imaging and genetic techniques, does not replace the value of correlative and integrative proxies--variables that are simpler, easier, or cheaper to measure. By closely examining the current knowledge gaps and broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.« less

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [1];  [10]
  1. Pacific Northwest National Laboratory, Richland WA USA
  2. Pacific Northwest National Laboratory, Joint Global Change Research Institute, University of Maryland, College Park MD USA
  3. Department of Microbiology, University of Massachusetts Amherst, Amherst MA USA
  4. Department of Natural Resources and Environment, University of New Hampshire, Durham NH USA
  5. Department of Integrative Biology, University of Texas at Austin, Austin TX USA
  6. Northern Research Station, USDA Forest Service, Houghton MI USA
  7. Department of Crop and Soil Sciences, Oregon State University, Corvallis OR USA
  8. Department of Biology, Indiana University Bloomington, Bloomington IN USA
  9. Program in Atmospheric and Oceanic Sciences, Department of Geosciences, Princeton University, Princeton NJ USA
  10. Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins CO USA
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1438975
Report Number(s):
PNNL-SA-128644
Journal ID: ISSN 1354-1013; KP1702010
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Volume: 24; Journal Issue: 3; Journal ID: ISSN 1354-1013
Publisher:
Wiley
Country of Publication:
United States
Language:
English

Citation Formats

Bailey, Vanessa L., Bond-Lamberty, Ben, DeAngelis, Kristen, Grandy, A. Stuart, Hawkes, Christine V., Heckman, Kate, Lajtha, Kate, Phillips, Richard P., Sulman, Benjamin N., Todd-Brown, Katherine E. O., and Wallenstein, Matthew D. Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks. United States: N. p., 2017. Web. doi:10.1111/gcb.13926.
Bailey, Vanessa L., Bond-Lamberty, Ben, DeAngelis, Kristen, Grandy, A. Stuart, Hawkes, Christine V., Heckman, Kate, Lajtha, Kate, Phillips, Richard P., Sulman, Benjamin N., Todd-Brown, Katherine E. O., & Wallenstein, Matthew D. Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks. United States. doi:10.1111/gcb.13926.
Bailey, Vanessa L., Bond-Lamberty, Ben, DeAngelis, Kristen, Grandy, A. Stuart, Hawkes, Christine V., Heckman, Kate, Lajtha, Kate, Phillips, Richard P., Sulman, Benjamin N., Todd-Brown, Katherine E. O., and Wallenstein, Matthew D. Mon . "Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks". United States. doi:10.1111/gcb.13926.
@article{osti_1438975,
title = {Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks},
author = {Bailey, Vanessa L. and Bond-Lamberty, Ben and DeAngelis, Kristen and Grandy, A. Stuart and Hawkes, Christine V. and Heckman, Kate and Lajtha, Kate and Phillips, Richard P. and Sulman, Benjamin N. and Todd-Brown, Katherine E. O. and Wallenstein, Matthew D.},
abstractNote = {The complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the C fate and persistence under future climate scenarios. As these proxies are used at increasingly larger scales, the C pools and processes that proxies represent must be thoughtfully considered in order to minimize uncertainties in empirical understanding, as well as in model parameters and in model outcomes. The importance of these uncertainties is further amplified by the current need to make predictions of the C cycle for the non steady state environmental conditions resulting from global climate change. To clarify the appropriate uses of proxy variables, we provide specific examples of proxy variables that could improve decision making, adaptation choices, and modeling skill, while not foreclosing on – and also encouraging – continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil organic matter: metabolic quotient, clay content, and physical fractionation. We also consider emerging data types, specifically genome-sequence data, and how these serve as proxies for microbial community activities. We opine that the demand for increasing mechanistic detail, and the flood of data from new imaging and genetic techniques, does not replace the value of correlative and integrative proxies--variables that are simpler, easier, or cheaper to measure. By closely examining the current knowledge gaps and broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.},
doi = {10.1111/gcb.13926},
journal = {Global Change Biology},
issn = {1354-1013},
number = 3,
volume = 24,
place = {United States},
year = {2017},
month = {11}
}