Preprints
https://doi.org/10.5194/bg-2022-164
https://doi.org/10.5194/bg-2022-164
 
18 Aug 2022
18 Aug 2022
Status: this preprint is currently under review for the journal BG.

Assessing carbon storage capacity and saturation across six central US grasslands using data-model integration

Kevin R. Wilcox1, Scott L. Collins2, Alan K. Knapp3, William Pockman2, Zheng Shi4, Melinda Smith3, and Yiqi Luo5 Kevin R. Wilcox et al.
  • 1Department of Ecosystem Science and Management, University of Wyoming, Laramie, WY 82071, USA
  • 2Department of Biology, University of New Mexico, Albuquerque, NM, 87131, USA
  • 3Department of Biology & Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, 80523, USA
  • 4Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, 73019
  • 5Department of Biological Sciences, Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, 86011, USA

Abstract. Future global changes will impact carbon (C) fluxes and pools in most terrestrial ecosystems and the feedback of terrestrial carbon cycling to atmospheric CO2. Determining the vulnerability of ecosystems to future changes in C is thus vital for targeted land management and policy. The C capacity of an ecosystem (XC) is a function of its C inputs (e.g., net primary productivity – NPP) and how long C remains in the system before being respired back to the atmosphere (ecosystem C residence time – τE). The proportion of XC currently stored by an ecosystem (i.e., its C saturation – CSAT) provides information about the potential for long-term C pools to be altered by environmental and land management regimes. We estimated XC, CSAT, NPP, and τE in six US grasslands spanning temperature and precipitation gradients by integrating high temporal resolution C pool and flux data with a process-based C model. As expected, NPP across grasslands was strongly correlated with mean annual precipitation (MAP), while τE was primarily a function of mean annual temperature (MAT). We link soil temperature, soil moisture, and inherent C turnover rates (potentially due to differences in microbial function) as determinants of τE. Overall, we found that intermediates between extremes in moisture and temperature had low CSAT, indicating that ecosystem C in these systems may be buffered against global change impacts on XC. Hot and dry grasslands had greatest CSAT due to both small C inputs through NPP and high C turnover rates during periods of favorable soil conditions. CSAT also was high in tallgrass prairie due to frequent fire that reduced inputs of aboveground plant material. Accordingly, we suggest that both hot, dry ecosystems and those frequently disturbed should be subject to careful land management and policy decisions to prevent losses of C stored in these systems.

Kevin R. Wilcox et al.

Status: open (until 14 Oct 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-164', Anonymous Referee #1, 27 Sep 2022 reply

Kevin R. Wilcox et al.

Kevin R. Wilcox et al.

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Short summary
The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems will store carbon in the future. Here, we employ novel data-model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
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