Ecosystem Demography (ED) Model
The ED model is an individual-based model of vegetation dynamics with integrated submodels of plant growth, mortality, phenology, biodiversity, disturbance, hydrology, and soil biogeochemistry. Individual plants of different functional types compete mechanistically in ED under local environmental conditions for light, water, and nutrients. ED differs from most other terrestrial models by formally scaling up physiological processes through individual-based vegetation dynamics to ecosystem scales, while simultaneously modeling natural disturbances, land use,and the dynamics of recovering lands.
ED has been implemented for the Amazon, the U.S. and is now a global model. It has been used to study the effects of land-use change, fires and tropical cyclones on regional carbon balances. Because trees in ED have an explicit height, it fascilitates direct connection to structure data and has been used for high-resolution height-initialized estimates of carbon stocks and fluxes in the tropics and over complex mountainous terrain. Currently, ED is being used as part of a framework to estimate statewide high-resolution (90m) carbon stocks, fluxes and sequestration potential for Maryland. More information on this project can be found here.
In addition, we have developed a new coupled framework, the Integrated Ecosystem Demography (iED) Model, to study linked human and natural systems. iED combines the advanced ecosystem dynamics from ED with socioeconomics from the Global Change Assessment Model (GCAM) and land-use algorithms from the Global Land-use Model (GLM). This work aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. More information on this project can be found here. We are also using iED to study how changes in future disturbance rates will affect our ability to meet future demands for wood, fuel and fiber, and our ability to meet future climate mitigation goals. More information on this project can be found here.
Currently, the ED model is being integrated into the NASA Carbon Monitoring System baseline monitoring maps for the northeast United States. Additionally, the model is being run globally in the context of NASA GEDI and the NASA IDS project for the GSFC GEOS system.
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- Hurtt GC, Moorcroft PR, Pacala SW and Levin SA (1998) Terrestrial models and global change: challenges for the future. Global Change Biology. 4(5): 581-590. (Abstract)
- Moorcroft PR, Hurtt GC, and Pacala SW (2001) A method for scaling vegetation dynamics: The Ecosystem Demography Model (ED). Ecological Monographs. 71(4): 557-586. (Abstract)
- Hurtt GC, Pacala SW, Moorcroft PR, Caspersen J, Shevliakova E, Houghton RA and Moore, B (2002) Projecting the future of the U.S. carbon sink. Procedings of the National Academy of Sciences. 99: 1389-1394. (Paper)
- Hurtt GC, Dubayah R, Drake J, Moorcroft PR, Pacala SW, Blair JB and Fearon MG (2004) Beyond potential vegetation: combining lidar data and a height-structured model for carbon studies. Ecological Applications. 14(3): 873-883. (Abstract)
- Thomas RQ, Hurtt GC, Dubayah R and Shilz MH (2008) Using lidar data and a height-structured ecosystem model to estimate forest carbon stocks and fluxes over mountainous terrain. Canadian Journal of Remote Sensing. 34(S2): S351-S363. (Abstract)
- Hurtt GC, Fisk JP, Thomas RQ, Dubayah R, Moorcroft PR and Shugart HH (2010) Linking models and data on vegetation structure. Journal of Geophysical Research. 115(G2). (Abstract)
- Fisk JP, Hurtt GC, Chambers JQ, Zeng H, Dolan KA and Negrón-Juárez RI (2013) The impacts of tropical cyclones on the net carbon balance of eastern US forests (1851-2000). Environmental Research Letters. 8(4). (Paper)
- Flanagan, S. A., Hurtt, G. C., Fisk, J. P., Sahajpal, R., Zhao, M., Dubayah, R., Hansen, M. C., Sullivan, J. H., Collatz, G. J. (2019). Potential Transient Response of Terrestrial Vegetation and Carbon in Northern North America from Climate Change. Climate, 7(9), 113. (Abstract)
- Hurtt G. C., M. Zhao, R. Sahajpal, A. Armstrong, R. Birdsey, E. Campbell, K. Dolan, R. Dubayah, J. P. Fisk, S. Flanagan, C. Huang, W. Huang, K. Johnson, R. Lamb, L. Ma, R. Marks, D. O’Leary III, J. O’Neil-Dunne, A. Swatantran, H. Tang. (2019) Beyond MRV: High-resolution forest carbon modelling for climate mitigation planning over MD, USA. Environmental Research Letters. (Abstract)