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CQUEST Partnerships & Projects
Carbon management in forest and agricultural lands of the United States is the responsibility of several Federal agencies (including the U.S. Department of Agriculture – USDA and the Department of the Interior – DOI), which, along with the Department of the Energy (DOE), have numerous programs in place to collect monitoring data on carbon sequestration at local to national scales. The NASA Ames CQUEST application seeks new and unique partnerships with these Federal agencies and their collaborators to demonstrate integration of research efforts toward verifiable reductions in greenhouse gas (GHG) emissions. Important gaps in our national database of carbon sequestration can be addressed by combining NASA remote sensing technology, ecosystem process modeling, and field-based measurements to characterize land management impacts on the carbon cycle.
Changes in Agricultural Soil Carbon
In the past, agriculture has been a notable source of carbon emissions. However, recent policy changes have encouraged producers to adopt management practices that are known to sequester carbon in soils, including reduced tillage and reduction of bare fallow. Mark Sperow (West Virginia University) and colleagues at Colorado State University and the USDA Agricultural Research Service have estimated changes in carbon stocks for U.S. agricultural soils during the period from 1982 to 1997 using the IPCC (Intergovernmental Panel on Climate Change) method for greenhouse gas inventories. Land use data from the USDA National Resources Inventory (NRI) were used as inputs, along with ancillary data sets on climate, soils, and agricultural management.
In a partnership with the CQUEST application, a new national map has been developed at 1-km resolution from the Sperow et al. data set. Non-agricultural lands (forests, wetlands, deserts) have been excluded from the mapping estimates, based on the latest 1-km land cover product from the NASA MODIS sensor. Because federal grazing lands were excluded from original NRI soil carbon samples, they have also been removed from the mapping procedure using data reported in the NRI.

Soil Carbon Changes
The units for change in soil carbon stocks have been converted to g C per m2 per year, in part to facilitate comparisons to the NASA-CASA model and other independent predictions of carbon changes in cropland and grazing land soils. Results show that changes in land use and agricultural management have resulted in a net gain of 17.1 MMT (million metric tons) C in U.S. agricultural soils over the period from 1982 to 1997.
Eve, M.D., M. Sperow, K. Paustian, and R. Follett. 2002. National-scale estimation of changes in soil carbon stocks on agricultural lands. Environmental Pollution, 116: 431-438.
Sperow, M., M. Eve, and K. Paustian. 2001. Estimating soil C sequestration potential in U.S. agricultural soils using the IPCC approach. Proceedings paper for the U.S. DOE National Energy Technology Laboratory (NETL) First National Conference on Carbon Sequestration, Washington, D.C. May 14-17, 2001.
Credits: Mark Sperow (West Virginia University), Keith Paustain (Colorado State University), Ronald Follett (USDA Agricultural Research Service), Seth Hiatt, Vanessa Genovese (California State University Monterey Bay).
Conservation Reserve Program Linkages
Evaluation of CQUEST predictions for changes in soil carbon pools resulting from conservation and restoration can be accomplished by integration with USDA research on Conservation Reserve Program (CRP) lands. The CRP was established in 1985 to control soil erosion and the loss of productivity on millions of hectares of erosion-prone croplands across the country. Increases in soil carbon storage have been measured in CRP lands where permanent grassland cover has been maintained for several years (Follett et al., 2001). Nationwide assessments are needed to determine the overall effect of the CRP on U.S. carbon budgets.
In partnership with the CQUEST application, CRP and cropped soil measurement data sets from Ronald Follett (USDA Agricultural Research Service) are used to calibrate the NASA-CASA model and extrapolate regionally using several CRP case study locations (e.g., Colorado, Texas, and Montana) described in Follett et al. (2001). USDA field studies of carbon sequestration show that high amounts "Identifiable Plant Material" (IPM) in grasslands is added to CRP plots each year and that large biomass fractions (more than 50% in some cases) can be sequestered annually in the soil organic carbon (SOC) pool, in comparison to continuously cropped soil plots at nearby study locations (Table below).
Follett, R. F., S. E. Samson-Liebig, J. M. Kimble, E. G. Preussner, and S. W. Waltman. 2001. Carbon sequestration under the CRP in the historic grassland soils of the USA, pp. 27-49, In R. Lal and K. McSweeney, eds. Soil management for enhancing carbon sequestration, Spec. Publ. 57 ed. SSSA, Madison, WI.
Credits: Ronald Follett (USDA Agricultural Research Service), Matthew Fladeland (NASA Ames Research Center).
Forest Biomass Evaluation
The USDA’s Forest Inventory and Analysis (FIA) program reports on national status and trends in forest area, tree growth, mortality, and removals by harvest. FIA-derived models (Reed et al, 2001) can generate estimates for plots and sub-regions by using overlays of digital map layers, including forest classes, tree species, soil coverages, or climate zones.
In partnership with the CQUEST application, aboveground live carbon stocks from the FIA national database (as U.S. county averages) have been compared to NASA-CASA predictions. The CQUEST algorithm for allocation of carbon to aboveground wood pools has been refined to follow the non-linear growth function (at left). This produces a potential standing wood biomass map. Results have been adjusted for mean FIA-derived stand age (by county) to generate a new national map of standing wood biomass (at right).
Carbon Allocation
Heath, L. S., and J. E. Smith. 2000. An assessment of uncertainty in forest carbon budget projections. Environmental Science & Policy, 3: 73-82.
Reed, D., K. Pregitzer, S. Pugh, and P. Miles, 2001. Fiamodel: A new link for geographic analyses of inventory data. Journal of Forestry, 99: 21-24.
Credits: Linda Heath (USDA Forest Service), Richard Birdsey (USDA Forest Service), Steven Klooster (California State University Monterey Bay), Vanessa Genovese (California State University Monterey Bay).
Forest Disturbance in the Pacific Northwest
Forest disturbance types in the Pacific Northwest (PNW) states of Oregon and Washington have included clear-cut logging and wildfires. Although large areas have been cleared, repeated stand-replacing disturbances have been rare over the time frame of the past 30 years. This permits us to develop NASA-CASA simulations with relatively long forest recovery cycles and substantial carbon accumulation rates in disturbed areas.
Healey and Cohen (in prep.) have developed a new set of Landsat-based maps for historical forest disturbance in OR and WA in support of the Effectiveness Monitoring module of the Northwest Forest Plan, a collaboration between the Bureau of Land Management (BLM) and the USDA Forest Service. These maps of stand-replacing forest disturbances in the Northwest Forest Plan area between 1972 and 2002 were generated using a change detection method that is approximately 90% accurate (Cohen et al., 2002).
In partnership with the CQUEST application, the OR and WA disturbance maps have been aggregated to a 1-km spatial grid as the primary forest land cover change drivers for input to NASA-CASA carbon flux simulations. We are generating historical reconstructions of forest biomass decomposition following disturbances and ecosystem carbon accumulation rates in the years that follow documented logging and fire disturbances.
Cohen, W., T. Spies, R. Alig, D. Oetter, T. Maiersperger, and M. Fiorella, 2002. Characterizing 23 years (1972-1995) of stand replacement disturbance in western Oregon forests with Landsat imagery. Ecosystems. 5: 122-137.
Credits: Warren Cohen (USDA Forest Service), Sean Healey (USDA Forest Service), Vanessa Genovese (California State University Monterey Bay).

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