Across‐model spread and shrinking in predicting peatland carbon dynamics under global change
[1];
[4];
[8];
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[12];
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[13]
- Center for Ecosystem Science and Society Northern Arizona University Flagstaff Arizona USA, Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical Garden, Chinese Academy of Sciences Guangzhou China
- Center for Ecosystem Science and Society Northern Arizona University Flagstaff Arizona USA, Jet Propulsion Laboratory California Institute of Technology Pasadena California USA
- CSIRO Oceans and Atmosphere Aspendale Victoria Australia
- Center for Ecosystem Science and Society Northern Arizona University Flagstaff Arizona USA, Graduate School of Geography Clark University Worcester Massachusetts USA
- Department of Environmental Science and Ecological Engineering Korea University Seoul South Korea
- Department of Ecoscience, Arctic Research Centre Aarhus University Roskilde Denmark, Department of Environment and Minerals Greenland Institute of Natural Resources Nuuk Greenland
- Center for Ecosystem Science and Society Northern Arizona University Flagstaff Arizona USA
- Research Center for Global Change and Complex Ecosystems School of Ecological and Environmental Sciences, East China Normal University Shanghai China
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science Tsinghua University Beijing China
- Graduate School of Geography Clark University Worcester Massachusetts USA
- School of GeoSciences University of Edinburgh Edinburgh UK
- Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge Tennessee USA
- School of Integrative Plant Science Cornell University Ithaca New York USA
Abstract Large across‐model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across‐model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO 2 levels and five temperature levels. We developed a matrix‐based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter‐model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter‐model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO 2 (eCO 2 ) concentrations in the measurements, simulated NEP responded positively to eCO 2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across‐model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-00OR22725; SC0020227
- OSTI ID:
- 1958675
- Journal Information:
- Global Change Biology, Journal Name: Global Change Biology Journal Issue: 10 Vol. 29; ISSN 1354-1013
- Publisher:
- Wiley-BlackwellCopyright Statement
- Country of Publication:
- United Kingdom
- Language:
- English
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