The Science

Finding the ideal measurable characteristics to accurately represent complex ecological interactions is the holy grail of modeling research. Sometimes, measurements of a system are not easily obtainable or even impossible to acquire, and thus a substitute variable known as a proxy is used in place of the more complex variable. Ideal proxies are easy to measure and have high predictive value for the characteristic or system they are attempting to represent, but in practice have a range of ease and value. This paper emphasizes the thoughtful use of proxies to maximize predictive value and illustrates this concept with practical examples, outlining future measurements and techniques for modeling soil carbon dynamics.

The Impact

In the search to manage, measure, and predict climate change interactions with terrestrial ecosystems, researchers provide a staunch reminder of thoughtfulness in choosing variables for terrestrial models. With the flood of data from new imaging and genetic techniques it is important not to lose sight of less complex and cheaper proxies that could provide just as much value. A closer examination of the current knowledge gaps in soil carbon cycling and of the proxies researchers already use may allow us to develop new hypotheses and specify criteria for new and needed proxies.

Summary

The soil carbon cycle is highly complex and driven by a vast suite of environmental, physical, and biological factors. Various proxies for soil characteristics are evaluated as correlative representations (meaning they can be used in place of more complex variables) or integrative frameworks (combinations of measurements used to describe the underlying mechanism) for soil carbon dynamics. The authors provide a glimpse into the future with new and emerging proxies focusing predominantly on genome-sequence data and how they will help evolve our understanding of the terrestrial ecosystem.

Principal Investigator

Joshua B. Fisher
UCLA, JPL
joshbfisher@gmail.com

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
daniel.stover@science.doe.gov

Funding

DOE BER Environmental System Science (formerly Terrestrial Ecosystem Science) program and the NSF Ecosystem Science program.

References