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BEYOND POTENTIAL VEGETATION: COMBINING LIDAR DATA AND A HEIGHT‐STRUCTURED MODEL FOR CARBON STUDIES
Abstract
Carbon estimates from terrestrial ecosystem models are limited by large uncertainties in the current state of the land surface. Natural and anthropogenic disturbances have important and lasting influences on ecosystem structure and fluxes that can be difficult to detect or assess with conventional methods. In this study, we combined two recent advances in remote sensing and ecosystem modeling to improve model carbon stock and flux estimates at a tropical forest study site at La Selva, Costa Rica (10°25′ N, 84°00′ W). Airborne lidar remote sensing was used to measure spatial heterogeneity in the vertical structure of vegetation. The ecosystem demography model (ED) was used to estimate the consequences of this heterogeneity for regional estimates of carbon stocks and fluxes. Lidar data provided substantial constraints on model estimates of both carbon stocks and net carbon fluxes. Lidar‐initialized ED estimates of aboveground biomass were within 1.2% of regression‐based approaches, and corresponding model estimates of net carbon fluxes differed substantially from bracketing alternatives. The results of this study provide a promising illustration of the power of combining lidar data on vegetation height with a height‐structured ecosystem model. Extending these analyses to larger scales will require the development of regional and global lidar data sets, and the continued development and application of height structured ecosystem models.
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Cites
Estimating historical changes in global land cover: Croplands from 1700 to 1992
Ramankutty, N., & Foley, J. A. (1999) · Global Biogeochemical Cycles · doi:10.1029/1999gb900046 · Cited by 2,074
Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988
Skole, D., & Tucker, C. (1993) · Science · doi:10.1126/science.260.5116.1905 · Cited by 1,590
Cited by
Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., Hofton, M., Hurtt, G., Kellner, J., Luthcke, S., et al. (2020) · Science of Remote Sensing · doi:10.1016/j.srs.2020.100002 · Cited by 1,042
Self-citationVegetation demographics in Earth System Models: A review of progress and priorities
Fisher, R. A., Koven, C. D., Anderegg, W. R. L., Christoffersen, B. O., Dietze, M. C., Farrior, C. E., Holm, J. A., Hurtt, G. C., Knox, R. G., Lawrence, P. J., et al. (2018) · Global Change Biology · doi:10.1111/gcb.13910 · Cited by 768
Self-citationHURTT, G. C., FROLKING, S., FEARON, M. G., MOORE, B., SHEVLIAKOVA, E., MALYSHEV, S., PACALA, S. W., & HOUGHTON, R. A. (2006) · Global Change Biology · doi:10.1111/j.1365-2486.2006.01150.x · Cited by 531
Self-citationFrolking, S., Palace, M. W., Clark, D. B., Chambers, J. Q., Shugart, H. H., & Hurtt, G. C. (2009) · Journal of Geophysical Research: Biogeosciences · doi:10.1029/2008jg000911 · Cited by 428
Self-citationForest carbon storage: ecology, management, and policy
Fahey, T. J., Woodbury, P. B., Battles, J. J., Goodale, C. L., Hamburg, S. P., Ollinger, S. V., & Woodall, C. W. (2010) · Frontiers in Ecology and the Environment · doi:10.1890/080169 · Cited by 357
Metadata
- Authors
- Hurtt, G. C., Dubayah, R., Drake, J., Moorcroft, P. R., Pacala, S. W., Blair, J. B., & Fearon, M. G.
- Venue
- Ecological Applications
- Publisher
- Wiley
- Published
- 2004-06
- Volume
- 14
- Issue
- 3
- Pages
- 873-883
- ISSN
- 1051-0761 (ISSN-L)
- 1939-5582
- OpenAlex
- W2063093293
- Cited by
- 165
- References
- 2
- FWCI
- 7.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- Hurtt, G. C., Dubayah, R., Drake, J., Moorcroft, P. R., Pacala, S. W., Blair, J. B., & Fearon, M. G. (2004). BEYOND POTENTIAL VEGETATION: COMBINING LIDAR DATA AND A HEIGHT‐STRUCTURED MODEL FOR CARBON STUDIES. Ecological Applications. https://doi.org/10.1890/02-5317
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