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Biological Sciences Division
Research Highlights

November 2017

The Power of Traditional Proxies for Measuring the Soil Carbon Cycle

Solid standbys should not be displaced by new imaging and genetics techniques.

Proxy figure
Correlative proxies may not be directly causative of the process/feature of interest, however, the relationship between a proxy and the feature of interest can suggest new hypotheses. Integrative proxies are measurements that reflect a collection of features, and how they work as a system. These can be valuable for high-level inferences, but extracting mechanistic understanding from integrative proxies may be difficult.

In the long history of environmental, soil, and climate change sciences, researchers have always needed proxy variables to improve how complex variables and processes are measured and represented.

They have used tree ring chronologies to infer past climate conditions, for instance. And both experimentalists and modelers have widely used clay content as a proxy for properties like bulk density, water-holding capacity, and soil organic matter.

Land management and policy decisions depend on proxies, which are surrogates for soil features and processes that affect long-term projections of Earth system responses to change. A new paper co-authored by PNNL researchers Vanessa Bailey, Ben Bond-Lamberty, and Kathe Todd-Brown reviews and classifies the types of proxies used for environmental research.

Two Types

Ecologists often use two types of proxies. Correlative proxies represent soil characteristics that cannot be directly measured. Integrative proxies aggregate information about multiple soil characteristics into one variable.

In soil carbon (C) cycle measurements both proxies have continuing importance. They yield significant insight, and are simpler, easier, and cheaper to measure than the actual feature being represented. For example, it is easier to measure clay content as an indicator of soil porosity or carbon storage potential. But understanding which feature is being inferred is important to interpreting the research.

Meanwhile, new advances in imaging and proteomics have added capabilities and variables to studying the soil C cycle. But so far, the authors say, these methods are often more expensive and more difficult to measure directly.

Bailey and Bond-Lamberty argue that the thoughtful use of proxies can lead to new hypotheses and experiments to identify causative relationships. Not using proxies, on the other hand, may give correlations too much weight in explaining research results and may misrepresent mechanisms.


This paper was the product of a working group assembled at a workshop sponsored by the Carbon Cycle Interagency Working Group via the U.S. Carbon Cycle Science Program under the auspices of the U.S. Global Change Research Program, "Celebrating the 2015 International Decade of Soil - Understanding Soil's Resilience and Vulnerability," Boulder, CO, March 2016. VLB, BBL, RP, and KD were supported by grants from the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Terrestrial Ecosystem Sciences Program. KL was supported by NSF DEB-1257032.  KTB was supported by Linus Pauling Distinguished Postdoctoral Fellowship program, part of the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory.

Research Area: Biological Sciences

Research Team: Vanessa Bailey and Ben Bond-Lamberty of PNNL.


V. Bailey, et al. "Effective Soil Process and Property Proxies are Key to Predicting Climate Change Interactions with Terrestrial Systems." Global Change Biology, 1-11(2017) [DOI 10.1111/gcb.13926].

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