Estimating heterotrophic respiration at large scales: challenges, approaches, and next steps

Abstract

Abstract. Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomicspecific global models is not imminent, we suggest that a useful step to improve this situation would be the development of "Decomposition Functional Types" (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing modelers and experimentalists to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present an example clustering analysis to show how annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from (but complementary to) already-existing PFTs. A similar analysis incorporating observational data could form the basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with rigorous testing of analytical results; using point measurements and realistic forcing variables to constrain process-based models; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR.

Historical climate controls soil respiration responses to current soil moisture

“…If historical contingencies in soil respiration prove to be widespread, then moisture functions in C models should be both spatially and temporally dynamic, whereas current models use static moisture functions (2, 7, 8, 28). One possibility for scaling up local respiration-moisture relationships is the development of functional types defined to capture these dynamics (29). Such efforts will require an improved understanding of the spatial and temporal scales at which historical contingencies occur and persist and how those will impact microbial C cycling in the face of a changing climate.…”

New Techniques and Data for Understanding the Global Soil Respiration Flux

“…Starting with Schlesinger (), estimates of regional to global R s fluxes have generally used either simple upscaling of land cover mean rates, or linear regressions driven by climate data and land area. This has been necessary because we have no reliable way of measuring R s at areas larger than ~0.1 m −2 (Bond‐Lamberty et al, ), unlike, for example, net carbon exchange or net primary production, for which robust larger‐scale measurement methods exist. Only recently have we begun to leverage these small‐scale but extensive and informative data (Phillips et al, ).…”

Optimizing an Environmental Observatory Network Design Using Publicly Available Data

“…This quantitative approach is comparable to the delineation of the National Ecological Observatory Network domains, which were derived from eco‐climatic properties in the United States (Keller et al, ; Schimel & Keller, ). However, to improve our understanding of the land‐atmosphere interactions, we propose that it is also needed to include information about ecosystem functionality (Bond‐Lamberty et al, ; Petrakis et al, ; Reichstein et al, ). The addition of information on ecosystem functional attributes has enhanced biodiversity models (Alcaraz‐Segura et al, , ; Armas et al, ) and is useful for network design and assessment (Villarreal et al, ).…”