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    Author(s): Vanessa L. Bailey; Ben Bond-Lamberty; Kristen DeAngelis; A. Stuart Grandy; Christine V Hawkes; Kate Heckman; Kate Lajtha; Richard P. Phillips; Benjamin N. Sulman; Katherine E. O. Todd-Brown; Matthew D. Wallenstein
    Date: 2017
    Source: Global Change Biology
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (566.0 KB)


    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 fate and persistence of C under future climate scenarios. However, the C pools and processes that proxies represent must be thoughtfully considered in order to minimize uncertainties in empirical understanding. This is necessary to capture the full value of a proxy in model parameters and in model outcomes. Here, we provide specific examples of proxy variables that could improve decision-making, and modeling skill, while also encouraging continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil C cycling: metabolic quotient, clay content, and physical fractionation. We also consider how emerging data types, such as genome- sequence data, can serve as proxies for microbial community activities. By examining some 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.

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    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. 2017. Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks. Global Change Biology. 24(3): 895-905.


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    clay, CUE, models, soil carbon, soil organic matter

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