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Pacific Northwest Research Station
Mapped Atmosphere-Plant-Soil System Study

Corvallis Forestry Sciences Laboratory
3200 SW Jefferson Way
Corvallis, Oregon 97331

United States Forest Service.

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Biological Control of Terrestrial Carbon Fluxes

Atmospheric CO2 has a major influence over climate and, because of recent political initiatives, a currency of considerable consequence. From a global perspective, understanding the role of terrestrial ecosystems in the carbon cycle is crucial to quantifying carbon storage (Schimel 1995, Schimel et al. 1997). From a domestic perspective, understanding the U.S. carbon budget is a foundation requirement for sound planning and ecosystem management. Great progress has been made in recent years in measurement networks (LTER and AmeriFLUX), in the re-analysis of inventory data and in modeling (Schimel et al. 1997, VEMAP 1995) relevant to the U.S. carbon budget. In addition, "inverse" analyses of atmospheric data (Ciais et al. 1995, Enting et al. 1995) are beginning to provide information on continental scales (Fan et al. 1998; Rayner et al. in press). Carbon research requires a high degree of integration between disciplines. The tools of ecology and atmospheric science have reached a point where an ambitious synthesis is feasible. We will develop an integrated data-model system to analyze consequences of different assumptions about biology and land management on patterns of CO2 in the atmosphere. This is a powerful complement to traditional model testing against site-specific data, but the development of measurement networks and gradient studies (Baldocchi et al. 1997, Hunt et al. 1996) greatly improves the power of in situ data-model comparisons (Schimel et al. 1997). The time is ripe for an ambitious, integrated, analysis of terrestrial ecosystems and the carbon cycle.

We propose a 4-year project concentrating on the conterminous United States, an area identified as significant in recent atmospheric analyses (Fan et al. 1998; Rayner et al., in press). It is an area where data resources and validation information are unparalleled, and an area diverse enough to seriously challenge our understanding while remaining tractable (VEMAP 1995). We propose a project in three parts.

Part one is the implementation of a new framework to analyze processes controlling net carbon exchange based on recent advances of ecosystem models, process studies, and analytical technologies. The project will develop a modular framework linking disturbance and management to life-form distribution and biogeochemistry, to provide a comprehensive way to examine and estimate terrestrial net carbon exchanges. This framework will be developed by our team, but with input from colleagues and potential users on a regular basis. The model will be a "community" model designed to be remotely operated on multiple platforms. Both the model code and large output data sets from important experiments will be made available with documentation and metadata. This model will take advantage of lessons learned by the participants and will use science from extant models. However, rather than simply "linking" extant models, we will integrate key components and processes to evaluate changes in terrestrial carbon fluxes.

Part two is the development of the data sets needed to operate the model. These will include soils, meteorology, and land use histories. The soils and weather data are straightforward (Kalnay et al. 1996, Kittel et al. 1997.). The main emphasis in the data activity will be the development of spatial land use histories containing sufficient information to operate the model. This activity will draw on existing efforts and, as a huge task, will be progressively improved over time.

Part three is the analysis of the U.S. carbon budget. We will begin by evaluating our model system against "traditional" in situ observations such as net pramiary productivity (NPP), soil carbon/biomass data. We will then integrate the continental model and compare the simulated patterns of atmospheric CO2 against observations. This will require coupling the terrestrial model and estimated spatial/seasonal fossil fuel fluxes to an atmospheric model. We will use a well-tested model (RAMS) operated in a "data assimilation mode," a mathematical approach where the model is continuously adjusted to observations of key variables widely used in forecast studies. Data assimilation is a mature technology in the atmospheric sciences and will permit the model to produce transport winds, turbulent fluxes, and weather close to observed conditions. This will make both the weather used as input to the ecosystem model and the transport used to compare simulated to observed CO2 consistent and close to reality.


Kittel, T.; Royle, J.; Daly, C.; Rosenbloom, N.; Gibson, W.; Fisher, H.; Schimel, D.; Berliner, L.; VEMAP2 Participants. 1997. A gridded historical (1895-1993) bioclimate dataset for the conterminous United States. In: Proceedings of the 10th conference on applied climatology. Boston, MA: American Meteorological Society: 219-222.

Kalnay, E.; Kanamitsu, M.; Kistler, R., et al. 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society. 77: 437-470.

US Forest Service - Pacific Northwest Research Station, Mapped Atmosphere-Plant-Soil System Study
Last Modified: Monday, 16 December 2013 at 14:18:44 CST

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