The DOI matches its Crossref record; 212 of the 212 references it cites were found in a registry or an index.
Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges
Open accessAbstract
[1] Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process-based procedures and algorithms to quantify the immediate and long-term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty.
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A large and persistent carbon sink in the world’s forests
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., et al. (2011) · Science · doi:10.1126/science.1201609 · Cited by 8,458
Self-citationTemperature sensitivity of soil carbon decomposition and feedbacks to climate change
Davidson, E. A., & Janssens, I. A. (2006) · Nature · doi:10.1038/nature04514 · Cited by 6,919
THE VERTICAL DISTRIBUTION OF SOIL ORGANIC CARBON AND ITS RELATION TO CLIMATE AND VEGETATION
Jobbágy, E. G., & Jackson, R. B. (2000) · Ecological Applications · doi:10.1890/1051-0761(2000)010[0423:tvdoso]2.0.co;2 · Cited by 5,428
The Ecology of Natural Disturbance and Patch Dynamics.
Proctor, J., Pickett, S. T. A., & White, P. S. (1986) · The Journal of Applied Ecology · doi:10.2307/2403105 · Cited by 3,949
Baldocchi, D., Falge, E. M., Gu, L., Olson, R., Hollinger, D. Y., Running, S. W., Anthoni, P. M., Bernhofer, C., Davis, K. J., Evans, R., et al. (2001) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(2001)082<2415:fantts>2.3.co;2 · Cited by 3,787
Analysis of Factors Controlling Soil Organic Matter Levels in Great Plains Grasslands
Parton, W. J., Schimel, D. S., Cole, C. V., & Ojima, D. S. (1987) · Soil Science Society of America Journal · doi:10.2136/sssaj1987.03615995005100050015x · Cited by 3,759
Ecology of Coarse Woody Debris in Temperate Ecosystems
Harmon, M. E., Franklin, J. F., Swanson, F. J., Sollins, P., Gregory, S. V., Lattin, J. D., Anderson, N. H., Cline, S. P., Aumen, N. G., Sedell, J. R., et al. (1986) · Advances in Ecological Research · doi:10.1016/s0065-2504(08)60121-x · Cited by 3,749
MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., & Huang, X. (2010) · Remote Sensing of Environment · doi:10.1016/j.rse.2009.08.016 · Cited by 3,473
Total carbon and nitrogen in the soils of the world
BATJES, N. H. (1996) · European Journal of Soil Science · doi:10.1111/j.1365-2389.1996.tb01386.x · Cited by 3,213
Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences
Oreskes, N., Shrader-Frechette, K., & Belitz, K. (1994) · Science · doi:10.1126/science.263.5147.641 · Cited by 3,010
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Land use and land cover change effect on surface temperature over Eastern India
Gogoi, P. P., Vinoj, V., Swain, D., Roberts, G., Dash, J., & Tripathy, S. (2019) · Scientific Reports · doi:10.1038/s41598-019-45213-z · Cited by 268
Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO2 exchange
Keenan, T. F., Baker, I., Barr, A., Ciais, P., Davis, K., Dietze, M., Dragoni, D., Gough, C. M., Grant, R., Hollinger, D., et al. (2012) · Global Change Biology · doi:10.1111/j.1365-2486.2012.02678.x · Cited by 264
Invasive alien pests threaten the carbon stored in Europe’s forests
Seidl, R., Klonner, G., Rammer, W., Essl, F., Moreno, A., Neumann, M., & Dullinger, S. (2018) · Nature Communications · doi:10.1038/s41467-018-04096-w · Cited by 153
A proxy for all seasons? A synthesis of clumped isotope data from Holocene soil carbonates
Kelson, J. R., Huntington, K. W., Breecker, D. O., Burgener, L. K., Gallagher, T. M., Hoke, G. D., & Petersen, S. V. (2020) · Quaternary Science Reviews · doi:10.1016/j.quascirev.2020.106259 · Cited by 113
The role of forest residues in the accounting for the global warming potential of bioenergy
Guest, G., Cherubini, F., & Strømman, A. H. (2013) · GCB Bioenergy · doi:10.1111/gcbb.12014 · Cited by 70
Metadata
- Authors
- Liu, S., Bond-Lamberty, B., Hicke, J. A., Vargas, R., Zhao, S., Chen, J., Edburg, S. L., Hu, Y., Liu, J., McGuire, A. D., Xiao, J., Keane, R., Yuan, W., Tang, J., Luo, Y., Potter, C., & Oeding, J.
- Venue
- Journal of Geophysical Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 2011-11-08
- Volume
- 116
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W2088812394
- Cited by
- 466
- References
- 212
- FWCI
- 23.98
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Liu, S., Bond-Lamberty, B., Hicke, J. A., Vargas, R., Zhao, S., Chen, J., Edburg, S. L., Hu, Y., Liu, J., McGuire, A. D., Xiao, J., Keane, R., Yuan, W., Tang, J., Luo, Y., Potter, C., & Oeding, J. (2011). Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges. Journal of Geophysical Research. https://doi.org/10.1029/2010jg001585
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
