Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems
A number of numerical models have been developed to quantify the magnitude, over the past 4 decades, such that we have investigated the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH 4) fluxes within terrestrial ecosystems. These CH 4 models are also used for integrating multi-scale CH 4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH 4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH 4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH 4 processes and their environmental controls, and (3) significant data–model and model–model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Furthermore three areas for future improvements and applications of terrestrial CH 4 models are that (1) CH 4 models should more explicitly represent the mechanisms underlying land–atmosphere CH 4 exchange, with an emphasis on improving and validating individual CH 4more »
- Authors:
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[1]
; [2]
; [2]
; [2]
; [2]
; [3]
; [4]
; [2]
; [5]
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- San Diego State Univ., CA (United States); Chinese Academy of Sciences (CAS), Jilin (China); Univ. of Texas, El Paso, TX (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- San Diego State Univ., CA (United States); Univ. of Texas, El Paso, TX (United States)
- Chinese Academy of Sciences (CAS), Jilin (China)
- Auburn Univ., AL (United States)
- Publication Date:
- Grant/Contract Number:
- AC05-00OR22725; AC02-05CH11231; 41125001; NNX14AO73G
- Type:
- Published Article
- Journal Name:
- Biogeosciences (Online)
- Additional Journal Information:
- Journal Name: Biogeosciences (Online); Journal Volume: 13; Journal Issue: 12; Journal ID: ISSN 1726-4189
- Publisher:
- European Geosciences Union
- Research Org:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Org:
- USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
- OSTI Identifier:
- 1259569
- Alternate Identifier(s):
- OSTI ID: 1261330; OSTI ID: 1379407
Xu, Xiaofeng, Yuan, Fengming, Hanson, Paul J., Wullschleger, Stan D., Thornton, Peter E., Riley, William J., Song, Xia, Graham, David E., Song, Changchun, and Tian, Hanqin. Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems. United States: N. p.,
Web. doi:10.5194/bg-13-3735-2016.
Xu, Xiaofeng, Yuan, Fengming, Hanson, Paul J., Wullschleger, Stan D., Thornton, Peter E., Riley, William J., Song, Xia, Graham, David E., Song, Changchun, & Tian, Hanqin. Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems. United States. doi:10.5194/bg-13-3735-2016.
Xu, Xiaofeng, Yuan, Fengming, Hanson, Paul J., Wullschleger, Stan D., Thornton, Peter E., Riley, William J., Song, Xia, Graham, David E., Song, Changchun, and Tian, Hanqin. 2016.
"Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems". United States.
doi:10.5194/bg-13-3735-2016.
@article{osti_1259569,
title = {Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems},
author = {Xu, Xiaofeng and Yuan, Fengming and Hanson, Paul J. and Wullschleger, Stan D. and Thornton, Peter E. and Riley, William J. and Song, Xia and Graham, David E. and Song, Changchun and Tian, Hanqin},
abstractNote = {A number of numerical models have been developed to quantify the magnitude, over the past 4 decades, such that we have investigated the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data–model and model–model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Furthermore three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land–atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. Finally, these improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate–carbon cycle feedbacks.},
doi = {10.5194/bg-13-3735-2016},
journal = {Biogeosciences (Online)},
number = 12,
volume = 13,
place = {United States},
year = {2016},
month = {1}
}