globalchange  > 气候减缓与适应
DOI: 10.1002/2017JG004040
Scopus记录号: 2-s2.0-85044314752
论文题名:
Forecasting Responses of a Northern Peatland Carbon Cycle to Elevated CO2 and a Gradient of Experimental Warming
作者: Jiang J.; Huang Y.; Ma S.; Stacy M.; Shi Z.; Ricciuto D.M.; Hanson P.J.; Luo Y.
刊名: Journal of Geophysical Research: Biogeosciences
ISSN: 21698953
出版年: 2018
卷: 123, 期:3
起始页码: 1057
结束页码: 1071
语种: 英语
英文关键词: data assimilation ; EcoPAD ; model-data fusion ; model-experiment ; SPRUCE ; uncertainty
Scopus关键词: Anthropocene ; carbon cycle ; carbon dioxide ; carbon flux ; data assimilation ; experiment ; forecasting method ; Internet ; land management ; peatland ; stochasticity ; temperature ; uncertainty analysis ; warming ; Picea
英文摘要: The ability to forecast ecological carbon cycling is imperative to land management in a world where past carbon fluxes are no longer a clear guide in the Anthropocene. However, carbon-flux forecasting has not been practiced routinely like numerical weather prediction. This study explored (1) the relative contributions of model forcing data and parameters to uncertainty in forecasting flux- versus pool-based carbon cycle variables and (2) the time points when temperature and CO2 treatments may cause statistically detectable differences in those variables. We developed an online forecasting workflow (Ecological Platform for Assimilation of Data (EcoPAD)), which facilitates iterative data-model integration. EcoPAD automates data transfer from sensor networks, data assimilation, and ecological forecasting. We used the Spruce and Peatland Responses Under Changing Experiments data collected from 2011 to 2014 to constrain the parameters in the Terrestrial Ecosystem Model, forecast carbon cycle responses to elevated CO2 and a gradient of warming from 2015 to 2024, and specify uncertainties in the model output. Our results showed that data assimilation substantially reduces forecasting uncertainties. Interestingly, we found that the stochasticity of future external forcing contributed more to the uncertainty of forecasting future dynamics of C flux-related variables than model parameters. However, the parameter uncertainty primarily contributes to the uncertainty in forecasting C pool-related response variables. Given the uncertainties in forecasting carbon fluxes and pools, our analysis showed that statistically different responses of fast-turnover pools to various CO2 and warming treatments were observed sooner than slow-turnover pools. Our study has identified the sources of uncertainties in model prediction and thus leads to improve ecological carbon cycling forecasts in the future. ©2018. American Geophysical Union. All Rights Reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/114402
Appears in Collections:气候减缓与适应

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作者单位: Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province, Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province, Nanjing Forestry University, Nanjing, China; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, United States; Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States; University of Oklahoma Information Technology, Norman, OK, United States; Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States; Department of Earth System Science, Tsinghua University, Beijing, China

Recommended Citation:
Jiang J.,Huang Y.,Ma S.,et al. Forecasting Responses of a Northern Peatland Carbon Cycle to Elevated CO2 and a Gradient of Experimental Warming[J]. Journal of Geophysical Research: Biogeosciences,2018-01-01,123(3)
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