HR: 16:45h
AN: B54A-04    [Abstracts]
TI: Contributions of Land Inventory and Biometrics for Characterizing Disturbance in Ecosystem and Carbon Accounting Models
AU: * Birdsey, R
EM: rbirdsey@fs.fed.us
AF: USDA Forest Service, 11 Campus Blvd Suite 200, Newtown Square, PA 19073 United States
AU: Pan, Y
EM: ypan@fs.fed.us
AF: USDA Forest Service, 11 Campus Blvd Suite 200, Newtown Square, PA 19073 United States
AB: Nearly all forest lands of the U.S. are disturbed or affected by disturbance. Each decade about half of the total forest land area is disturbed by harvesting, grazing, wildfire, pests, and other natural causes. Because of the patchy nature of forest disturbances and the amount of edges, a large proportion of undisturbed interior forest area is affected by disturbances. Some ecosystem and carbon accounting models require spatially explicit input data about frequency or effects of disturbance. Current and historical information about forest disturbances includes both geospatial and statistical data. Examples of geospatial data sets from land inventories include maps of insect defoliation and N deposition. Examples of primarily statistical data sets that can be made into geospatial data sets include county-level statistics from forest inventory and other census data about land use or cover. A variety of techniques are available to manipulate statistical data sets into geospatial data sets. Many ecosystem and carbon accounting models lack ability to simulate the dynamics of disturbance and instead only represent potential forest vegetation. Several techniques are being developed in large-scale ecosystem models to address this issue. One approach is illustrated by Production Efficiency Models (PEMs) that use satellite-derived information to estimate vegetation productivity and C changes affected by landscape changes and climatic variability. Models that rely primarily on remote-sensing information lack ability to separate kinds of disturbances that may have similar canopy impacts, such as forest management and land use change. Also, PEMs lack the capacity to detect impacts of global change stressors such as CO2, N deposition and ozone. Another approach is to combine disturbance models with ecosystem models. Such model combinations use different integration approaches. Whether using ecosystem models to provide growth information to parameterize disturbance models, or using disturbance models to pass the age cohort information to ecosystem models, ground-based disturbance information is required to verify remote sensing information and initialize succession stages. Besides spatially explicit characterization of disturbance, accurate characterization of forest processes in ecosystem and carbon accounting models requires parameters from disturbed sites. However, study areas with sufficient data available for model parameterization are typically undisturbed interior forest. Thus there is a great need for establishment of intensive monitoring in landscapes that include disturbances. Protocols for landscape-scale intensive monitoring are being developed and applied in a pilot mode under the North American Carbon Program.
DE: 1699 General or miscellaneous
DE: 1600 GLOBAL CHANGE (New category)
DE: 1615 Biogeochemical processes (4805)
DE: 0400 Biogeosciences
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting