TERRESTRIAL CARBON MODEL
Dennis Ojima
William J. Parton
David S. Schimel
Table of Contents
Proposal SummaryModel DevelopmentProject Management
Input Parameter Development and Analysis
Validation and Data Assimilation MethodologiesVitas
Dennis Ojima
William J. Parton
David S. Schimel
Lawrence E. Band
Michael B. Coughenour
Scott Denning
Niall Hanan
Timothy G.F. Kittell
Ronald P. Neilson
Keith Paustian
Roger A. Pielke, Sr.
Steven W. Running
Atmospheric CO2 is a major control 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 US 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 (VEMAP 1995, Schimel et al. 1997) relevant to the US carbon budget. In addition, 'inverse' analyses of atmospheric data (Enting et al. 1995, Ciais et al. 1995) are beginning to provide information on continental scales (Rayner et al. in press, Fan et al. 1998). 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 systems 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 (Hunt et al. 1996, Baldocchi et al. 1997) 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 four year project concentrating on the conterminous US, an area identified as significant in recent atmospheric analyses (Rayner et al. in press, Fan et al. 1998). 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:
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, in order 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 operated on multiple platforms and remotely. 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.
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 (www.u.cgd.car.edu/VEMAP/: Kittel et al. 1997, NCEP re-analysis climate data, Kalnay et al., 1996). 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.
The analysis of the US carbon budget. We will begin by evaluating our model system against 'traditional' in situ observations such as 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 used 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.
NSF: Integrated Research Challenges:
Biological Control of Terrestrial Carbon Fluxes
Principal Investigators:
Dennis Ojima, Colorado State UniversityCo-Principal Investigators:
William J. Parton, Colorado State University
David S. Schimel, Colorado State University and Max Planck Institute
Roger A. Pielke Sr., Colorado State University
Ron P. Neilson, USFS, Oregon State University
Steven W. Running, University of Montana
A. Scott Denning, Colorado State University
Larry E. Band, University of North Carolina
Keith Paustian, Colorado State University
Michael B. Coughenour, Colorado State University
Tomi Vukicevic, Colorado State University
Timothy G.F. Kittel, National Center for Atmospheric Research
Niall Hanan, Colorado State University
Atmospheric CO2 is an important control 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 (Schimel 1995, Schimel et al. 1996, 1997, Houghton et al. 1998). From a domestic perspective, understanding the US carbon budget is a foundation requirement for sound planning and ecosystem management. Great progress has been made in recent years in measurement networks (e.g., LTER, AmeriFLUX, SOMnet), in the re-analysis of inventory data and in modeling (VEMAP 1995, Schimel et al. 1997, Paustian et al. 1996) relevant to the US C budget. In addition, 'inverse' analyses of atmospheric data (Enting et al. 1995, Ciais et al. 1995) are beginning to provide information on continental scales (Rayner et al. in press, Fan et al. 1998). Carbon research requires a high degree of integration between disciplines; and, the tools of ecology and atmospheric science have reached a point where an ambitious synthesis is feasible. We can now develop an integrated data-model system that allows us to analyze consequences of different assumptions about biology and land management on spatial patterns of atmospheric CO2 and its stable isotopic composition. This is a powerful complement to traditional model testing against site-specific data, but the development of measurement networks and gradient studies (Hunt et al. 1996, Baldocchi et al. 1996) also greatly improves the power of in situ data-model comparisons (Schimel et al. 1997). Thus the time is ripe for an ambitious integrated analysis of terrestrial ecosystems and the carbon cycle.
The carbon cycle links biological, geochemical and atmospheric processes. For several decades, uncertainty has persisted about a major term in the carbon cycle, the so called 'missing' sink. The missing sink is associated with biological processes and stems from an imbalance in the estimated global carbon budget and is widely assumed to result from these processes in Northern Hemisphere ecosystems. However, while atmospheric inversion methods have persistently identified a CO2 sink in Northern Hemisphere ecosystems (and one recent analysis places the bulk in North America; Fan et al. 1998), direct evidence from field studies, inventories and process modeling cannot fully account for this flux. It is unacceptable that the degree of uncertainty and conflict regarding the terrestrial sink has persisted for over a decade. To date, strategies for identifying the sink have been largely directed by geoscientists, have relied on local process studies, or have been reliant only on models without adequate validation. Our basic hypothesis is that the magnitude and spatial distribution of net carbon fluxes (storage or release) between ecosystems and the atmosphere is controlled mainly by prior disturbance and land use, controlling the sensitivity of ecosystem carbon storage to 'ecosystem physiological' controls by CO2 , climate, nitrogen deposition and other factors.
Studies of the terrestrial carbon cycle pose a serious methodological problem of scale. Processes in terrestrial ecosystems exhibit high variability in time and space, yet from the perspective of the global carbon cycle, we are interested in ecosystem's aggregate impact on the atmosphere. Spatial variability is high enough that measurements alone cannot provide adequate estimates of either fluxes or pools over large regions, implying that models must be used for interpolation of observations. This is particularly true given our basic postulate: that prior disturbance and land use dominate present-day fluxes. This is because disturbance and land use vary in a fine-grained fashion. Yet, without regional observations, such models cannot be convincingly evaluated. Several types of measurements provide regional data not derived from point measurements. Remote sensing techniques are our principal source of wall-to-wall data and have advanced dramatically over the past few years, yet provide only weak constraints on carbon budgets (providing, basically, information on photosynthetic potential and phenology: Running et al. 1994, 1995, Hunt et al. 1996, Asner et al. 1998). Atmospheric CO2 measurements can be analyzed to produce estimates of regional to continental net CO2 exchange, but have wide confidence intervals and almost no spatial resolution (Enting et al., 1995, Fan et al., 1998).
We propose an innovative approach to dealing with this problem of scale mismatch by designing a model-data fusion system to allow simultaneous validation at multiple scales. We will develop a terrestrial ecosystem model drawing on the scientific advances in ecosystem modeling over the past decade (VEMAP 1995, Pan et al. 1998, Schimel et al 1997) coupled to an atmospheric model. The results of the coupled model will include:
| site-specific pools and fluxes, which can be compared to site and regional inventory data, as in conventional modeling. Fluxes due to physiological processes and disturbance (fire, harvest) will be accounted for separately. | |
| simulated leaf area, albedo and vegetative cover, and the resulting computed spectral reflectance, for direct comparison to remote sensing products. This will allow rigorous evaluation of spatial patterns of leaf area and of phenology. | |
| computed CO2 concentrations and isotopic composition at the location of extant atmospheric sampling sites. By coupling the ecosystem and atmospheric models, we can translate the CO2 fluxes into 'maps' of surface and upper air concentrations. Comparisons can also be made to aircraft missions. |
1) Local fluxes and pools, hence the basic processes in the model;Satisfying these three constraints will provide strong evidence of whether the model estimates are reasonable, and the extent to which the underlying processes are represented correctly. While there may be multiple explanations consistent with these constraints, systematic evaluation will also certainly exclude many hypotheses.
2) Spatial-temporal patterns of leaf area and hence phenology; and
3) The continental scale integral of the fluxes.
Our approach to the scaling problem is thus to develop hierarchical methods, each of which can be tested and evaluated against specific extant data. The process-based model components developed by the project will be tested against plot- to landscape-scale data (e.g., inventory, FACE, and eddy covariance studies) for well-studied sites across gradients in climate, edaphic setting, and land-use. The model will then be used to predict spatial patterns and mosaics of biological properties over larger areas using climate and soils data and land-use data, and these scaling algorithms will be tested against remotely sensed vegetation state (AVHRR, MODIS, LandSat 7, Running et al. 1994, 1997). In addition, the interactions between ecological and atmospheric processes in the model will be tested across spatial scales at the tall tower sites in Wisconsin and Oklahoma.
The 450 m tall WLEF-TV tower in Wisconsin has been instrumented for measurement of climate and CO2 at 6 levels (11 m to 400 m), and for fluxes of CO2, heat, and moisture at 3 levels (30 m, 122 m, 396 m) since 1996 (Bakwin et al., 1998). In 1998, a boundary-layer wind profiling radar was installed at the site (Angevine et al., 1998; Ken Davis, personal communication), allowing a quantitative evaluation of the coupling between ecosystem fluxes and atmospheric mixing at the site. The system allows direct evaluation of simulated fluxes from a heterogeneous forest landscape across scales with a footprint of 104 m2 at the bottom of the tower to 107 m2 at the top (http://biocycle.atmos.colostate.edu/WLEF). A second 100 m tall tower is being instrumented in Oklahoma (Joe Berry, Stanford University, personal communication), which will allow us to test scaling algorithms over grassland and cropland ecosystems. Ancillary data available at this site includes detailed meteorological data (radiation, winds, boundary-layer height). Using the observational constraints available at the tall tower sites, the scaling algorithms can be confidently applied to make continental scale estimates of ecosystem carbon exchange in a completely self-consistent manner with the simulated atmospheric transport in RAMS. These calculations will produce full 3-dimensional gridded estimates of the concentration and isotopic composition of atmospheric CO2 over the US, which can be directly compared to flask samples, in situ-data, and aircraft sampling which will take place in 2000 and beyond (S. Wofsy, COBRA program, personal communication).
We will use a powerful mathematical technique in operating this system. In meteorology "data assimilation" is used to continually adjust model state variables towards observations. The atmosphere is chaotic (in the mathematical sense) and hence models are dependent upon imperfectly-observed initial conditions. Data assimilation adjusts all of the state variables in a model domain towards observations, interpolating between observations in a manner consistent with the model physics. Thus, a knowledge of fluid dynamics and thermodynamics 'constrains' the interpolation, blending a knowledge of theory with observations. We will operate the coupled atmosphere-ecosystem model in a data assimilation mode, relying at least initially, on atmospheric observations. This will allow us to use the atmospheric model to provide radiation, temperature and precipitation to the ecosystem model in a way completely consistent with the computed transport of CO2. We will also assimilate site and satellite data experimentally in order to test whether they can be used operationally to improve the fidelity of ecosystem models.
Developing the data assimilation system also requires the development of an important mathematical tool for understanding the system. This tool, known in the earth sciences as the 'adjoint' can, in this application, be thought of as a transformation of the matrix of partial derivatives of the state variables with respect to the model parameters. While this is used in the interpolation process, it also provides a powerful tool for sensitivity analysis. Specifically, it helps identify the parameters that most influence the model solution and under what conditions (values of state variables) those influences change. We will develop the adjoint to the entire coupled model and it will be available for a unique analysis of the sensitivity of the ecosystem processes to their controls as well as a tool for the potential 'assimilation' of ecosystem observations. This proposal is a serious effort to deal 1) to multiple scales in ecosystem dynamics, 2) to deal up-front with the dominant role of land use in North American ecosystems, and also 3) an initiative to introduce powerful new analytical (mathematical) tools into ecology, a tool that provide a new formalism for ecologists to blend theory and observations.
We will conduct a detailed analysis of data and models of carbon fluxes to test the hypothesis that the United States region is a large sink of CO2. Our hypothesis is that the magnitude and spatial distribution of a sink in the US must be determined by prior land use and disturbance, modifying the sensitivity of ecosystems to other controls (e.g., CO2, climate, N deposition). Preliminary results suggest that ecosystem physiological processes can result in a sink in 1990 of about 0.1-0.3 gigatons of carbon based on an intercomparison of 8 models. Direct analyses of inventory data suggest a sink of 0.4 (by inventory) to 1.7 (by atmospheric inversion) for southern North America. We further hypothesize that community processes (forest regrowth) initiated by logging and disturbance dominate sink processes, in synergism with direct physiological effects of CO2 and nitrogen deposition.
While a comprehensive experimental and empirical effort to quantify the terrestrial sink is beyond the scope of this program, we propose a systematic study integrating extant observational data (flux and inventory studies), experimental data and modeling, and results from global and regional scale atmospheric analyses. This activity builds on a number of ongoing, but fragmented, initiatives and links them using an overarching biological framework. We bring as tools to this study the detailed climate data for 1895-1995 prepared by the Vegetation and Ecosystem Modeling and Analysis Project (VEMAP). In addition we will incorporate the biological expertise developed during the past decade on biological determinants affecting carbon assimilation, storage, fluxes, and losses of the terrestrial biosphere.
Our understanding of the biological controls of carbon fluxes between the atmosphere and the land surface (referring to the soil, vegetation, water system) is critical to our estimation of net terrestrial carbon fluxes and the connection of key natural resources (e.g., water, vegetation, soils, etc.) to climate and land use changes (Figure 1). Terrestrial biological processes respond strongly to atmospheric temperature, humidity, CO2 levels, N-deposition, precipitation, and radiative transfers. In addition, biological changes due to disturbances such as fire, pest outbreaks, herbivory, cultivation, or deforestation, have a large impact on the processes that affect the net carbon exchange. Changes in the plant community and the composition of plant functional types alter the rate of carbon assimilation and carbon released through decomposition.
Integration of land use with biological, atmospheric and hydrological processes will allow us to estimate net carbon exchange from the terrestrial biota.. However, proper handling of scale is critical to the success of the analysis of this set of complex interactions (Rastetter et al. 1993). Some of our recent efforts have made progress in the understanding of the ecosystem metabolic feedbacks that couple the terrestrial biosphere to the atmosphere (i.e., photosynthesis, decomposition, evaporation, transpiration) (Figure 1) which control carbon, energy, and water exchanges (Walko et al. in press, Vidale et al. 1997, Eastman et al. 1998). These feedbacks operate rapidly and are calculated many times each hour. Biogeochemical and ecosystem interactions with atmospheric processes have recently been implemented using the Century-RAMS models at Colorado State University (Lu et al. 1997, Ojima et al. 1997, Pielke et al. 1997). These research efforts have been directed at developing a better understanding of how the biosphere coupling to the atmosphere change over time as ecosystem processes changes the constraints on water, carbon, and energy fluxes (Schimel et al., 1990, 1994, Ojima et al., 1991, Ojima 1992). Slower changes in ecosystem state through woody biomass and soils also affect net carbon exchanges in response to climate and land use changes. Our understanding of the long term changes in the terrestrial
Figure 1. Conceptual framework for understanding and evaluating net carbon fluxes from terrestrial ecosystems. Atmospheric component includes processes needed to predict precipitation, temperature, shortwave and longwave radiation, humidity, winds, and atmospheric chemical composition of CO2 and nitrogen. The biophysical processes include photosynthesis, transpiration, stomatal conductance, and respiration and provides estimates of fluxes of carbon, water, and energy exchange. The hydrology components represent processes controlling runon/runoff, infiltration, evaporation, storage and flow of water. The biogeochemical component represents the decomposition, allocation, nutrient turnover, and microbial process accumulation. The vegetation component represents the plant community dynamics related to competition, land use management, disturbance responses, and successional dynamics that affect land cover dynamics, stand age, and vegetation structure. A disturbance generator is included to trigger fire, grazing, and other land use events which are appropriate for the biome and land use.
biosphere will provide greater insight to the environmental sustainability under different stresses and provide an indication of how different regions may respond to changes in climate, disturbance regimes, and land use (Schimel et al., 1991, Schimel 1992).
| Model Development. The project will develop a modular framework linking disturbance and management to life form distribution and biogeochemistry to 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 operated remotely and on multiple platforms. Both model code and large output data sets from important experiments will be made available to the community, with documentation and metadata. This model will take advantage of lessons learned by the participants and will use science from extant models. However, instead of simply 'linking' extant models, we will integrate the important components and processes in order to evaluate changes in terrestrial carbon fluxes. | |
| Input Parameter Development. We will a synthesize existing data needed to operate the model. These include soils, meteorology and land use histories. The soils and weather data are straightforward (www.ucar.cgd.edu/VEMAP/: Kittel et al. 1997, NCEP re-analysis, Kalnay et al., 1996). We will emphasize the development of spatial land use histories (e.g., LUHNA, FIA, NRI, Crop statistics) containing sufficient information to operate the model. This activity will draw on existing efforts being conducted by Ojima, Parton, Paustian, Joyce, in developing agricultural, forestry, and natural disturbance patterns for biomes in the United States. This is a large task, that will be progressively refined over time. | |
| Validation and Data Development for the analysis of the US carbon budget. We will begin by evaluating our model system against 'traditional' in situ observations such as NPP, soil carbon/biomass data. We will then integrate the continental model and compare the simulated patterns of atmospheric CO2 against observations. This requires coupling the terrestrial model and estimated spatial/seasonal fossil fuel fluxes to an atmospheric model. We will use a well-tested model (RAMS, Pielke et al. 1992, Uliasz et al. 1996) 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. We will thus evaluate the carbon budget spatially, and against pools and processes in an integrated fashion via the atmospheric winds. |
Carbon is the major building block of life on Earth, and is also, as CO2 , a major greenhouse gas. One cannot adequately address the changing atmospheric CO2 concentrations without understanding the dynamics of the terrestrial biota. This proposal addresses the 1) the role of terrestrial biological systems in modifying net carbon exchange and 2) evaluating the consequences of global environmental change on terrestrial biosphere. The interdisciplinary research team will incorporate analysis of field experimentation into the development of a multi-scaled, multi-process terrestrial biosphere model linked to hydrological and atmosphere transfer models to assess the net carbon exchange from terrestrial ecosystems.
We build upon several recent advances in evaluating interactions among plant physiology, plant community, land use management, ecosystem, and biogeochemical processes which affect carbon exchange and biogeochemical cycles of terrestrial ecosystems. Recent analyses indicate that changes in climate modify properties of the terrestrial biosphere and biogeochemical processes that cause lags in the exchange of carbon and water (Braswell et al. 1997, Houghton et al. 1998). In addition, changes in plant communities and disturbances regime, such as fire patterns, may be altered and modify the vegetation structure resulting in changes in the terrestrial biosphere properties (Ojima et al. 1997, Lenihan et al. 1998). Analysis of these interactions between long-term changes in the terrestrial biosphere and the fast response time of biophysical-atmosphere feedback is a fundamental component of the carbon exchange being studied in the global sciences (Ojima 1992). The focus of the project will be the development of an integrated approach to evaluate terrestrial biological controls on carbon dynamics and estimate the net carbon fluxes from managed and natural ecosystems of the conterminous United States.
The project will be implemented to accomplish the three sets of tasks identified above:
| Model Development | |
| Input Parameter Development and Analysis | |
| Validation Data Development |
MODEL DEVELOPMENT: Nature of the Interacting Processes
Parton, Ojima, Neilson, Band, Running, Pielke, Coughenour, Schimel in collaboration with Wedin, Chapin, Joyce
Modern landscapes are diverse mosaics where lands that were originally native grasslands or forests have been heavily modified for agriculture, urban, or industrial uses. We will define various submodel components such as photosynthesis model, carbon allocation, biogeochemisty, disturbance generator, land use management, soil hydrology, succession, plant community development. We will use scientific concepts developed from field and laboratory analysis and evaluated in models. The plant community will be represented as plant functional types ( e.g., evergreen needle-leaf trees, deciduous broadleaf trees, evergreen shrubs, N-fixing shrubs, cool season tall-grasses, warm season short-grasses, etc). The biogeography will determine the structural attributes of the plant community and leaf longevity and type (e.g., broadleaf-needleleaf, evergreen-deciduous and other physiognomic characteristics). Each of these plant functional types will be defined by structural, lifeform, physiological, biogeochemical, and disturbance response characteristics (Neilson 1995). Crop types will be included with the definition of the different plant functional types. The vegetation structure will have a multiple layer structure to represent canopy and understory components. The soil processes will be represented with multiple soil water layers to represent rooting depth of different functional types and water availability for different soil conditions. This soil profile representation will accommodate root differentiation and soil water dynamics which would control plant and near surface layer for soil microbial processes.
The atmospheric CO2 levels affect the land surface-atmosphere interactions since these interactions control the transpiration from terrestrial ecosystems. These processes are tightly coupled through biophysical and atmospheric processes with rapid feedbacks (i.e., minutes to hours) of water and energy fluxes between these two components. The land surface biophysical properties are controlled by the state of the soil moisture and the vegetation (Schimel 1992). The rate of transpiration, evaporation, and carbon assimilation, are affected by the partitioning of water and energy fluxes from the land surface. These rates are also dependent on the amount of leaf area, dead plant material, and bare ground.
Plant carbon uptake responds rapidly to changes in temperature, light, moisture, and CO2 levels. We will capture diurnal processes such as leaf and soil energy balance and photosynthesis, and longer temporal domains for other plant growth processes (i.e., weekly to monthly; Schimel et al. 1991, Chen et al 1994, Coughenour and Chen 1997). Daily weather data will be used to modify these processes. Photosynthesis will be based on concepts of Farquhar et al. (1980), that considers the relative limitations of rates of ribulose 1,5-biphosphate (RUbP) carboxylase fixation of internal leaf CO2 and RUbP regeneration, and RUbP oxygenation. Reaction rates respond to temperature according to Arrhenius functions, that generally exhibit temperature optima. The CO2 fixation of RUbP is limited by mesophyll CO2 concentration in C3 species and by bundle sheath CO2 concentration in C4 species. Assimilation rate is reduced by low soil water content and leaf nitrogen. Dark respiration responds to temperature with a Q10 function.
Net fixed carbon can be stored as labile carbon within the plant. Respiration costs associated with tissue biosynthesis and maintenance are calculated after Ryan (1991). Maintenance respiration is a function of nitrogen content, as well as temperature according to a Q10 function. Carbon is allocated to structural root vs. shoot tissues dependent upon water and nitrogen stress (Coughenour 1991, 1993, Coughenour and Chen 1997). Tissue mortality rates respond to water stress, and to tissue age in the case of leaves. Nitrogen is taken up by roots and allocated in relationship to leaf age. Nitrogen is retranslocated during tissue mortality to still living tissues. Biomass production models interact with tillering and phenology submodels. Tillering depends on water, temperature, nitrogen and labile carbon. Phenology advances in response to growing degree day sums and daylength, but soil temperature and moisture may also trigger phenological change. Carbon assimilation concepts will be related to plant community type, stand age, resource limitations, phenology, and plant functional type.
The biogeochemical scheme will be based on multi-pool soil organic matter representation utilized by Parton and others (Parton et al., 1987, 1996, Jenkinson 1990, Jenkinson et al. 1991). Processes related to soil-plant interactions controlling organic matter dynamics will be represented in three major components which include active, slow, and passive soil C. Active SOM includes live soil microbes plus microbial products (the total active pool is approximately 2 to 3 times the live soil microbial biomass), the slow pool includes resistant plant material (for instance, lignin-like components) and soil-stabilized plant and microbial material, while the passive material is very resistant to decomposition and includes physically and chemically stabilized SOM. The flows of C are controlled by the inherent maximum decomposition rate of the different pools and the water and temperature-controlled decomposition factor. Microbial respiration occurs for each of the decomposition flows. The partitioning of decomposition between stabilized SOM and CO2 flux is a function of soil texture for the stabilization of active C into slow C (increasing CO2 flux for sandy soils and less soil C storage). Justification for these assumptions are presented in the earlier CENTURY paper (Parton et al., 1987, 1994, 1996).
The N submodel has the same general structure as the soil C model. The organic-N flows follow the C flows and are equal to the product of the carbon flow and the N:C ratio of the state variable that receives the C. Each soil state variable has prescribed bounds on its C:N ratio, and within those bounds, the C:N ratio varies as a function of soil mineral N. Based on the C:N ratio, and microbial respiration, each compartment can either release or take up N. The model also uses simple equations to represent N inputs due to atmospheric deposition and N fixation and calculates N losses due to N2, NO, N2O, and NH3 gas fluxes and NO3 leaching. A more complete description and justification for the N submodel is presented by Parton et al., (1987, 1994, 1996).
Disturbance regimes, such as storm, fire and grazing, will be either endogenous to the system or prescribed from local land use histories. When simulated, fire regimes will be triggered by combinations of climatic and vegetation characteristics (Lenihan et al., 1998). The frequency and intensity of fires can be generated within the disturbance generator. The fire model determines when to burn and the characteristics of the burn. Detailed information about the burn is communicated back to the biogeochemistry model for adjustments of carbon and nitrogen pool sizes in numerous live and dead vegetation compartments. The fire model contains an allometric rulebase for detailed determination of 'stand' structure and calculations of live and dead fuel loadings (Rothermal 1972). The allometry includes height information useful for succession and biosphere-atmosphere feedbacks. Grazing impacts will be prescribed based on known patterns of herbivory of shoots and leaves. Losses of carbon and nitrogen through erosional events will also be included.
The model will be represented for grain, vegetable, and tuber crops. Fruit-bearing systems will be represented as a modified forest. In cropping system, the impact of different land management practices on crops and on soil organic matter dynamics will be represented. These include types of tillage practices, harvesting techniques, crop residue management, irrigation, fertilizer application and herbicide use. The managed forest systems include management practices such as harvest rotations, fire regime, clear felling, selective harvesting, seedling establishment and so on.
The agricultural systems will be tested against a number of crop data sets including detailed analysis of the impact of different organic and fertilizer inputs. Historical patterns (1930-1990) for crop yields for irrigated and dryland crops in the Great Plains are available for different counties across the United States and can be used to evaluate the trends in crop yields as a function of changes in management practices (e.g. fertilizer and tillage practices) and crop varieties. The managed ecosystems will be evaluated and tested against site and regional data sets of different land use practices on plant production, nutrient cycling, soil organic matter dynamics and other environmental factors used earlier by our research team (Schimel et al., 1990; Paustian et al. 1992, Burke et al., 1991, 1994, Ojima et al., 1993; Parton et al., 1993, Parton and Rasmussen 1994, Kelly et al. 1997).
Simulations and long-term observations strongly suggest land use changes influence climate and feeds back to land surface processes, vegetation changes, and watershed hydrology (Baron et al. 1998, Stohlgren et al. 1998, Chase et al. 1997). The net flux of carbon is affected by a number of process interactions between components of the land-atmosphere, and are presented in Figure 1. These include atmosphere-biophysical transfers with rapid response times (e.g., minutes to hours); interactions with hydrological routing that modifies soil water balance, runon-off partitioning, snow-melt and streamflow. Biogeochemical processes also interact with the biophysical-atmosphere interactions and the hydrologic routing. Hydrological and climate properties affect process rates of decomposition, mineralization, trace gas fluxes, mass loss of nutrients and carbon. Vegetation processes, including establishment, competition, mortality, and community development, determines vegetation type (Sykes et al., in press). The vegetation type and state of the vegetation determine land surface properties related to leaf area, woodiness, height of vegetation, allocation of biomass to shoots and roots. These properties have major influences on biogeochemical cycling and on the biophysical processes (Ojima et al., 1991).
Hydrological Considerations
Hydrological processes are potentially important to tracking carbon. Non-uniform
redistribution of water may have a significant and nonlinear impact on soil
moisture and hence biogeochemistry. Bob Stallard (1998) recently advanced the
hypothesis that burial of carbon eroded from managed lands in local depositional
sites and in reservoirs could be quantitatively significant in the carbon cycle.
We will, in an experimental fashion, design our modeling system to couple to
a spatially-explicit hydrological model. The hydrological representation related
to different land surface characteristics will be important for us in evaluating
the importance of these erosional events. The issue of subgrid-scale variability
has been a concern in land surface process modeling due to the potential bias
in mean grid cell computed storage and flux. Within the dimensions of grid
cells we will be using (10-50km.) there will be a range of surface conditions
characterized by varying topography (altitude, slope, exposure, upstream drainage
area), land use, soils and vegetation. Locally, this can cause significant
variation in the storage and flux of carbon, water, and energy. We have experimented
with a number of ways of representing and computing the range of landscape
soils, topography, vegetation and wetness conditions within watersheds by coupling
TOPMODEL with FOREST-BGC and BIOME-BGC over a range of watershed sizes (Band
1993, White and Running 1994, Baron et al. 1998), using a statistical area-weighting
of flux. This approach has been extended to include an interacting, rather
than prescribed, atmosphere by coupling LEAF with TOPMODEL as a distributed
land surface process model for RAMS (Walko et al. in press). We will continue
developing this approach with a goal of finding the minimum number of land
surface elements that need to be represented and area weighted to gain unbiased
estimates of grid cell flux. Much of this work will begin by running the land
surface process models off-line for a set of different physiographic, climatic
and land cover scenarios to find the optimal weighting schemes (minimum number
of land elements gaining a prescribed level of accuracy) appropriate for the
different regions of the country. Part of this work will be used to define
those cases in which sub-grid scale variability is significant or is not significant,
and can be ignored. For those cases in which land use and topography vary significantly
within a grid cell, we may need to combine the areal weighting approach within
grid cell mosaics.
Programming Framework:
During the past decade, terrestrial biologists have made great strides in better
understanding process linkages across fields of community, landscape, and ecosystem
level dynamics. The integration of these biological fields has been a major
aspect of environmental studies during the past decade. Projects like the Vegetation
Ecosystem Model and Analysis Project (VEMAP) exemplify the level of development
in the integration of terrestrial biology to investigate the impact of climate
change on biomes in the United States. Building on the experimental, analytical,
and theoretical development of our understanding of the biosphere interactions
with other environmental components, we will begin to fully integrate this
knowledge into a modular framework which will incorporate the best aspects
of terrestrial biosphere models.
This modular framework will integrate portions of existing models that have been tested and evaluated over the past decade. This development will greatly improve current linked model studies since it will reduce the redundancies among the models and provide an additional benefit to allow for testing of alternate hypotheses of various representations of different processes. This framework will assist in model development and experimentation since the support routines are common across submodels. The essential nature of this framework is:
| Modularize the model to separate out the science modules | |
| Centralize uniform I/O set routines | |
| Integrate space and time coordination among processes | |
| Provide distributed computing support | |
| Support a friendly user interface |
INPUT PARAMETER DEVELOPMENT AND ANALYSIS: Model Input Requirements and Output
Parameters
(Ojima, Paustian, Parton, Kittel, in collaboration with Joyce, Wedin, Harmon,
Houghton, Chapin, Foley, Brown)
The project will develop a modeling framework to incorporate the critical biological components controlling carbon dynamics. It integrates aspects of disturbance regimes and management activities to estimate net carbon exchange in the conterminous United States. This framework will be used in conjunction with a range of observational and experimental data bases, and considerable effort will be put into organizing and synthesizing these data so they can be used in tandem with models and other analyses. We will reconstruct historical industrial fossil fuel emissions for the US based on compiled information available at the Carbon Data Information Analysis Center (CDIAC, Marland et al., 1999, http://cdiac.esd.ornl.gov/ndps/ndp030). Data sets include reprocessed data from the USFS Forest Inventory Assessment (FIA, http://srsfia.usfs.msstate.edu), process-level data from the LTER network and other similar studies, such as the Oregon Transect and the La Copita, TX savanna site, soils data from USDA data bases as well as the VEMAP project gridded climatology of the US. Land use patterns for cropping systems across the US will be developed for analysis and input into models. We will incorporate information from the National Resource Inventory and the NASS data bases of land use in the nation for the past 3 decades. Longer-term land use patterns will be developed using historical data, county level statistics of agricultural yields, and from information compiled by the USGS Land Use History of North America (website: www/biology.usgs.gov/luhna). While the available data are insufficient to use alone in calculating a carbon balance, they provide strong multiple constraints on model based estimates. Thus, we will emphasize a model-data fusion approach to produce improved estimates and most importantly estimates in which sources and magnitude of uncertainty are well-defined.
We are actively engaged in assembling a variety of national level database on climate, soils, landuse and management of US agricultural lands, many of which are fully spatial and incorporated into GIS. Some of the major databases being used to support regional and national analysis and modeling of soil C dynamics in agricultural lands are listed in Table 1.
Table 1. Land use management data sources.
| Database | Description | Source |
| PRISM - climate | precipitation, max and min temperature for 4 km2 grids, topographically adjusted, for conterminous US | Natural Resource Conservation Service (NRCS) |
| STATSGO (Soil Survey Geographic Data Base) | Comprehensive soil properties for assoc-iations 1:250,000 for conterminous US | NRCS |
| MUIR (Map Unit Interpretation Record) | Soil characteristics for soil series in the US | NRCS |
| NRI (National Resources Inventory) | Land use, management and soils information for > 800,000 points in the US, with re-measurement in 1982, 1987, 1992 and 1997 | NRCS |
| GIRAS | Land-cover and vegetation (50 m2 resolution), derived from air photos, for conterminous US | USGS |
| AVHRR based landcover maps | 1 km2 resolution for land-cover and vegetation in conterminous US | USGS |
| CTIC (Conservation Tillage Information Center) | County-level information on crop acreage by tillage practice for 1978-present, for conterminous US | CTIC, Purdue Univ. |
| Conservation Reserve Program (CRP) database | Acreage, soil type, yields and type of conservation practice for all CRP contracts (since 1985) in US (> 350,000) | USDA |
| NASS (National Agriculture Statistics Service) | Crop yield and acreage for all major crops, at the county-level, for US (1972-present); state-totals from 1866-present | USDA |
| Agriculture census | Crop acreage, crop yields, economic information, at county level for conterminous US ( most recent in 1997) | Bureau of the Census, Dept. of Commerce |
| Long-term agricultural experiment network | Soil C and N measurements, crop yields, climate summaries, detailed management histories for 40 long-term experiments (> 10- > 100 years in duration) in US and Canada | Colorado State University |
VALIDATION AND DATA ASSIMILATION METHODOLOGIES:
(Schimel, Pielke, Denning, Running, Hanan, Vukicevic in collaboration with
Wofsy, Baldocchi, Randerson)
Validation.
Selected sites, such as the First ISLSCP Field Experiment (FIFE) site and the
Cooperative Atmosphere Surface Exchange (CASES) at the Walnut River Watershed
in Kansas, provide invaluable information of fluxes of water, energy, and
CO2 , simultaneous observations of meteorological conditions,
soil moisture status, and vegetation condition for several time periods across
different years. Data to test the coupled model will take advantage of the
LTER sites, such as the Harvard Forest, HJ Andrews, Coweeta Watershed, the
Short-Grass-Steppe, and the tallgrass prairie site at Konza. In addition,
land surface flux studies are available from the CASES data (LeMone and Grossman
in eastern Kansas), FIFE data, and other data sets that will be available
as part of the Department of Energy Atmospheric Radiation Measurements (ARM)
Program's Cloud And Radiation Testbed (ARM/CART) sites in Kansas and Oklahoma
and the Global Continental-Scale International Project (GCIP) of Global Energy
and Water Experiment (GEWEX) initiatives of NOAA in the central U.S. resource
systems to extreme hydrological events. This evaluation of the model at these
sites will provide a critical test of the overall structure of interactions
implemented in the model.
Biogeochemical and vegetation components will be evaluated by grid cell comparison to Long Term Ecological Research (LTER) observations and with remote sensing data sets. We will verify hydrological routing by comparing simulated hydrological output with observations from unregulated stream flow data for areas of the Rocky Mountains and other regions (USGS records). We will use satellite data to estimate snow cover and water equivalent in various areas, as well as moisture stress indices.
In addition to comparing simulation results with observations from intensive study sites, we will make use of remote sensing data to perform extensive spatial and temporal evaluations of several of the key model prognostic variables. The past decade or more of AVHRR data provides a long baseline period for evaluating modeled phenology and for use in the analysis of terrestrial biosphere dynamics in conjunction with the observed historical atmospheric CO2 data. New sensors will provide similar data but of much higher quality. In particular, we will be able to take great advantage of the daily 1-km2 resolution multispectral data collected by the MODIS instrument. MODIS (Moderate Resolution Imaging Spectroradiometer) is the primary daily global monitoring sensor on the NASA Earth Observing System (EOS) satellites, scheduled for launch in 1999 and 2002 (Running et al., 1994). These satellite data from TM, AVHRR, and MODIS sensors will provide spatial and temporal estimate of land surface features such as, vegetation LAI, vegetation structure using BRDF algorithms, and productivity over complex terrain and larger regions (Asner et al. 1998). The availability of new sensors that provide greater information of atmospheric and land surface vegetation and soil moisture conditions will enhance our ability to test the new model. The combined analysis of MODIS and MISR sensors in the coming year will provide an ideal verification data set of several important parameters.
As the primary EOS sensor collecting data relevant to terrestrial biospheric processes, the MODIS instrument is designed to provide the land science community with information critical to the investigation of carbon cycles and human-induced changes at large spatial scales (Asrar and Dokken, 1993, Running et al. 1994). There are two such sets of products particularly relevant to our proposal: landcover and landcover change (LC-LCC), and leaf area index and fractional absorption of photosynthetically active radiation (LAI-FPAR). The LC-LCC products are updated annually, and the LAI-FPAR products are generated once every eight days using composited daily data. Both sets of products have global coverage on a grid with 1 km spacing.
There is a clear conjunction between these MODIS products and the prognostic variables of the terrestrial biosphere NEP model we aim to create, and the spatial and temporal coverage of the MODIS products will provide us with a unique opportunity for model evaluation. There are three groups of model prognostic variables of fundamental importance to the goal of a regional carbon cycle assessment that can be directly compared with MODIS products for model evaluation: landcover and landcover change, leaf area index and radiation absorption, and the seasonal timing of changes in leaf area.
In addition to an analysis of the spatial patterns of LAI and FPAR on the basis of landcover type, the MODIS LAI-FPAR products will provide a powerful tool for assessing the seasonal dynamics of leaf area change (leaf phenology). The model logic will include predictions of the timing of new leaf growth and leaf litterfall, based on reasoning from plant physiology as well as empirical parameterizations (e.g. White et al., 1997, Thornton et al., in prep.). The 8-day frequency of the MODIS LAI-FPAR products will permit a direct comparison of modeled and observed relationships between leaf area changes and climatic indices over a range of landcover types.
Model predictions of ecosystem flux will be tested across spatial and temporal scales by prediction of the concentration and isotopic composition of atmospheric CO2. This approach allows a direct evaluation of scaling algorithms across the model components, as described above. In addition, the atmospheric properties allow evaluation of the integrated performance of the model at the largest spatial scales, by comparison to data collected by flask sampling networks, in situ sampling, and aircraft.
Simulation of the continental-scale CO2 in the atmosphere is an ambitious task, requiring more than correct representation of ecosystem processes. Covariance between photosynthesis and atmospheric mixing must be correctly simulated (Denning et al., 1995, 1996, 1999), fossil-fuel emissions must be correctly prescribed, and the spatial and temporal structure of atmospheric properties at the lateral boundaries must be specified. We have developed methods for quantitative simulation of the ecosystem-atmosphere covariance ("rectifier") effects in RAMS (Denning et al., 1996). Anthropogenic emissions will be specified from monthly data recently collated by Bob Andres at the University of Alaska and distributed according to population density. Lateral boundary conditions for the concentration and stable isotopic composition of atmospheric CO2 will be specified from global simulations using the CSU GCM (Denning et al., 1996). Carbon isotopic fractionation will be calculated by methods similar to those of Fung et al. (1997), and the isotopic composition of oxygen in CO2 will be determined by methods similar to those of Ciais et al. (1997).
Data Assimilation.
We will develop new applications of data assimilation from physical sciences
for ecological systems. These advanced optimal data assimilation techniques
have been developed for large forecast systems: 1) Kalman Filter (KF) based
techniques (Cohn and Toddling, 1996) such as the Physical-space Statistical
Analysis System (PSAS, developed at NASA Goddard) and 2) variational techniques
such as the Statistical Spectral Interpolation (SSI) scheme (Parish and Derber,
1992; NCEP's global data analysis system) or regional 4D Variational (4DVAR)
systems at NCEP and NCAR (Zupanski and Zupanski, 1996; Vukicevic and Bao,
1998; Zou and Kuo, 1996). These advanced techniques, although more demanding
computationally, have significant advantages over more traditional local
interpolation techniques. These advantages are: {1.} Data analysis is performed
in a physically and dynamically consistent manner with a physical and dynamical
model involved in the analysis; This model represents complex relations between
different observed and unobserved quantities. {2.} Model and observation
error statistics are included explicitly in the analysis procedure and the
resulting analysis (data) errors are either given by definition (i.e., in
KF techniques) or can be objectively derived. These error statistics are
very useful because uncertainties associated with terrestrial and climate
system model results using these data as input can be then accessed objectively.
{3.} The optimality of data analysis is global over the entire spatial domain
of interest (i.e., global or regional domain) and over a temporal domain,
if temporal evolution is included in producing the analysis such as in the
Kalman Smoother (Cohn et al., 1994) or in the 4DVAR systems (Zupanski and
Zupanski, 1996; Vukicevic and Bao, 1998, Zou and Kuo, 1996). {4.} The analysis
system is extremely flexible to adding new diverse observations such as precipitation
products (Zupanski and Mesinger, 1995; Kou et al., 1996), radar reflectivity
(Sun and Crook, 1997), satellite radiance (Eyre, 1989; Thepaut and Moll,
1990), and in situ and remote observed ecosystem properties.
These features are desirable when attempting to design a data set of terrestrial biosphere and land surface parameters of a large region. This is because the number of direct in situ or satellite observations of these parameters is too small to sample the existing spatial and temporal variability. In meteorological studies, this interpolation technique is necessary to incorporate observations, such as meteorological observations, that are related to the surface forcing via dynamical and physical interactions in the atmosphere and to interpolate them in a consistent fashion. We propose that our ability to make inferences related to net carbon exchange will be improved by using data assimilation techniques applied to a coupled land surface and atmosphere model, together with remote sensing data.
The successful integrations of regional climate models with interactive land surface physics [e.g., Giorgi et al., 1993a,b; participants of Regional-Scale Climate Model Inter-comparison Study, ({http://www.physics.iastate.edu/atmos/pircs.html})] suggest that the data driven/constrained integrations in our experiments will produce realistic results. This is because extant climate integrations using the regional models are constrained by the observations only via the lateral boundary forcing when this forcing is obtained from the actual atmospheric analysis (not from the global model integration). The boundary constraint is, however, weaker than the data constraint we will apply in the data assimilation procedure. Consequently, the influence of observations on the regional model solution will be much stronger in this study.
We will also take advantage of recent atmospheric developments and make use of the National Center for Environmnetal Prediction (NCEP) reanalyses of the large scale wind and temperature fields (e.g. as described by Kalnay et al.,1996), the Regional Atmospheric Modeling System (RAMS; Pielke et al. 1992, Uliasz et al. 1996, Pielke and Uliasz 1998) will be used in a four dimensional data assimilation mode (4DDA) (Vukicevic and Bao 1998) to diagnose wind, turbulence, and other weather variables at 10 kilometer intervals across the continental United States. The NCEP data is currently available up to 1998, and is routinely updated. The NCEP data is used as lateral boundary conditions for RAMS at 6 hour intervals and, in the interior of the RAMS domain, as constraints on the RAMS higher spatial and temporal diagnosis of the weather fields. RAMS will be integrated for consecutive 12 hour periods for the time period since 1981 to obtain the needed weather analyses.
Using RAMS with the NCEP re-analyses will provide the most accurate characterization available of the atmospheric influences on the carbon fluxes, and the vertical and horizontal carbon dioxide transport and dispersion. RAMS includes a representation of landscape at scales as small as 1 km, so that realistic influences of the specific type of land surface on the turbulent fluxes are included. The landscape representation in RAMS will be integrated with the ecosystem model as part of this project.
Advanced analysis techniques such as the `adjoint analysis' (section 5) are being used in meteorological and atmospheric chemistry transport studies to specifically address problems of interactions between different components of the time evolving systems (Rabier, 1993; Vukicevic and Raeder, 1995; Vukicevic and Bao 1998; Vukicevic 1998; Marchuk, 1995; Kaminski et al., in press). Applications of the `adjoint analysis' technique require existence of an adjoint model. We will take advantage of the adjoint model to apply this model in the analysis of the coupling between the atmosphere and the land surface during the data assimilation period. Specifically, we will examine `conditional' interactions between atmospheric state and land surface state, focusing on how the previous state of the system influences its subsequent evolution. We will ask questions such as: Are there conditions of soil moisture, LAI or atmospheric state (e.g., stability, humidity, etc.) that predispose the coupled system to strong interaction of the carbon and climate systems? How do these interactions affect the comparison of models and observed CO2?
Research Timeline
Year 1: Workshop of Core Research Team and Collaborators. The objective of the workshop is to define the priorities of model development and land use data synthesis. Basic structure of analytical framework will be determined. Data bases will be identified and specific parameter scalars will be defined. Define specific needs from FIA and NRI/NASS data sets for managed systems. Qualifications of programming and post-doctoral fellows will be determined. Individuals for these positions will be hired.
Year 2: Design team will test portions of net carbon exchange model against selected site flux observations. Plant community dynamics will be integrated into biophysical-biogeochemical model. Disturbance generator implemented. Strategy for defining and developing short-term and long-term land use histories will be finalized. Data structure for carbon analysis will finalized and data integration will begin. Data assimilation techniques will be tested against distribution of point data of flux observations, interpolated with regional vegetation and land use information.
Year 3: Data set development near completion Testing of model code with different biomes and land use systems. Verify net carbon exchange model against site flux data for different regions of the US. Verify data assimilation structure against distributed flux data.
Year 4: Complete analysis of conterminous US net carbon exchange. Verify that estimates correspond to site and regional estimates for different years. Verify 4D analysis of terrestrial carbon exchange.
During the four years, we will generate several papers on the data base developments, modeling techniques and tests, data assimilation applications to biological studies, and preliminary and final findings related to net carbon fluxes from terrestrial systems. The progress of this project will also be posted on a project website, which will serve as a major communication interface among participating researchers.
Personnel Responsibilities:
The research proposed here will be directed by a scientific steering committee,
with Ojima, Parton, and Schimel as the principal investigators. Ojima will
serve as the project coordinator, and also lead the data development activity.
Parton will be responsible for model development. Schimel will be responsible
for validation and data assimilation developments. SSC members will participate
in all phases of the research development and implementation, though primary
responsibilities will be assigned according to expertise. Neilson will be work
on the biogeographical aspects of model and data inputs. Running will provide
expertise for development and implementation of remote sensing derived land
surface characteristics. Coughenour will provide expertise in physiological
and community processes. Kittel will provide expertise in biogoegraphical and
climatological relationships and data development. Pielke will provide 4D atmospheric
transfer scheme and weather dynamics for terrestrial systems. Band will provide
hydrological expertise for development of routing, soil moisture, and evaporation
processes. Denning will provide global to regional atmospheric CO2 interpolation
techniques for regional verification of aggregated net carbon exchange. Hanan
will provide site carbon flux interpolation for validation tests. Vukicevic
will provide methodological approaches to data assimilation and test these
against data integrated on vegetation, physiological, carbon flux, and land
use dynamics.
Programmers, Post-doctoral fellows, and students will implement much of the research designed jointly with the SSC. Additional expertise will be incorporated into the SSC as needed, for instance we have discussed with Dr. Linda Joyce of the USFS (see letter of collaboration) to join us in this project to work more directly with the FIA data; Steve Wofsy has agreed to work us to better integrate the Ameriflux data sets into this study; and we have contacted the LTER national office indicating our desire to work closely with as many of the LTER sites as possible (see letter from LTER).
Management Strategy:
This proposal describes an ambitious amount of work, even given the large budget.
We propose to make use of three major resources in order to achieve these goals.
First is integration. We propose a core team of programmers, students and post-docs,
mostly co-located on the CSU campus. This team will work together with the
PIs, rather than being allocated to different institutions or subprojects.
While the programmers and junior scientific staff will have specialities, we
have a history of encouraging collaboration, sharing of code, skills and tools
and communication. Thus as new components are developed, we expect the group
to work together to ensure compatability and minimize problems. While this
is an idealistic management style, we have successfully carried out several
projects using such teams with great success (the support for the VEMAP data
sets was provided by such a team, working with Schimel and Ojima and provided
a terabyte-size, quality-controlled data base to the entire US National Assessment
in 12 months). We will also take advantage of the project web site to make
interim data sets and codes, together with graphics and documentation available
to the whole project as it is developed. Thus the distributed team will be
able to see the entire group's progress in near real time.
The second resource is time. We will carry out our activities in a careful sequence. The development of the 'community ecosystem model' from precursor models will take place in years 1 and 2. The development of the data assimilation system (largely with DOD support for Vukicevic) for RAMS coupled to the BGC model will proceed in parallel, allowing the coding of the assimilation system to proceed in parallel with the assimilation system. Adaptation of the LUHNA and NRI data bases will also be done during this period as the model must be designed around the characteristics of this crucial data base. Once these two major codes are developed, they will be tested and debugged during year three separately and in coupled model. In year 4 we will conduct the major suite of model experiments and analyze the results. By phasing these large activities over time, but co-developing the components that must be coupled, we will use our staff resources with efficiency.
The third "resource" is our colleagues in the research community. Developing an integrated assessment of a continental carbon balance requires inputs from scientists with many specialities, as does designing a modeling system that can serve flexibly for many researchers. Accordingly, we plan a 'working group' of colleagues who will work with the PIs and core programmers and post-docs, providing input on data, model design and interpretation of results. The working group will bring a much wider range of expertise to the project and will also foster broad involvement in the development of community data sets and modeling tools. Membership in the working group will evolve, but we will ask members of other modeling teams, community and physiological ecologists, eddy flux measurement experts, and land use ecologists and historians to participate. Candidates for the working group include: Sandra Brown, Terry Chapin, John Foley, Lisa Graumlich, Mike Gulden, R.A. Houghton, Linda Joyce, Sandra Lavorel, David McGuire, Mark Harmon, Ian Noble, Jim Randerson David Wedin, and Steve Wofsy.
Drs. Ojima and Parton:
We have been awarded a number of NSF grants during the past 5 years. We will
summarize some of the relevant results for this specific proposal.
List of recent NSF projects include:
DEB- 9632852, Long Term Ecological Research Program: Shortgrass Steppe, NSF-Biological Centers, 11/01/96-10/31/02Model development of CENTURY was funded by several US-National Science Foundation projects in which Drs. Parton and Ojima participated. These projects are the Great Plains Agroecosystem Project (BSR-8406628 and -8105281), the Tall Grass Ecosystem Fire project (BSR-82007015), and the Central Plains Experimental Range-Long-Term Ecological Research Project (BSR-865195 and 9011659). The projects tested CENTURY across a variety of ecosystems, land use practices, and environmental conditions. Recent projects have been funded to study the impact of climate change across the network of LTER sites. These analyses of ecosystem response to changing environmental factors provided further insight into the sensitivity of ecosystem processes at a variety of ecosystems across North america. From these projects, we can make three summary conclusions. First, the biogeochemical constraints are critical in prediction ecosystem dynamics and C storage and fluxes due to feedbacks in physiological and biogeochemical processes. Second, the effect of land use management on ecosystem processes can often outweigh the impact of climate change and needs to be considered in global change studies. Third, soil texture is an important determinant of soil C, biogeochemical cycles, and ecosystem dynamics. In subsequent and concurrent funding from NSF, NASA, DOE, EPRI, and the DOI, the CENTURY model has incorporated the direct and indirect effects of elevated atmospheric CO2 changes. For the MMIA project, Century is the center piece for evaluating social-cultural, economic, and environmental factors affecting land use dynamics in the Great Plains (Ojima et al., in press). The TRAGnet project has continued development of Century for trace gas modeling (Parton et al 1998) and has been employed in cross-model comparisons of trace gas emissions (Frolking et al 1998). Century has been evaluated for land use impacts on ecosystem dynamics in the US and in the Mongolian Plateau.DEB-9523612, Models and Methods of Integrated Assessment (MMIA) of Climate and Land Use Changes in the Central US, 10/95 - 9/98
DEB-9416813, Trace Gas Cross-Site Comparison (TRAGnet), 10/94-3/99
DEB- Grassland Ecosystem Dynamics on the Mongolian Plateau, 3/95-6/99
Selected Publications from these projects:
Parton, W.J., D.S. Ojima, and D.S. Schimel. 1996. Models to evaluate soil organic matter storage and dynamics. Pp 421-448 In M.R. Carter (ed.) Structure and Organic Matter Storage in Agricultural Soils. CRC Press, Inc.
Ojima, D. S., D. S. Schimel, W. J. Parton, and C. Owensby. 1994. Short- and long-term effects of fire on N cycling in tallgrass prairie. Biogeochemistry 24:67-84.
Parton, W. J. and P. E. Rasmussen. 1994. Long-term effects of crop management in a wheat/fallow system: II. Modelling change with the CENTURY model. SSSAJ 58:530-536.
Seastedt, T. R., C. C. Coxwell, D. S. Ojima, and W. J. Parton. 1994. Impacts of photosynthetic pathways, management and climate on plant and soil carbon of semihumid temperate grasslands. Ecological Applications 4(2)244-253.
Parton, W. J., D. S. Schimel, D. S. Ojima. 1994. Environmental change in grasslands: assessment using models. Climatic Change 28:111-141.
Parton, W. J., D. S. Schimel, D. S. Ojima and C. V. Cole. 1994. A general model for soil organic matter dynamics: sensitivity to litter chemistry, texture and management. p. 137-167 in R.B. Bryant and R.W. Arnold (eds) Quantitative modeling of soil forming processes. SSSA Spec. Publ. 39. ASA, CSSA and SSA, Madison, WI.
Burke, I. C., W. K. Lauenroth, W. J. Parton and C. V. Cole. 1994. Interactions of landuse and ecosystem structure and function: A case study in the Central Great Plains. In Likens, G.E. and P.M. Groffman (eds.) Integrated Regional Models: Interactions Between Humans and Their Environment. Chapman and Hall, ITP, New York.
Metherell, A. K., C. A. Cambardella, W. J. Parton, G. A. Peterson, L. A. Harding, and C. V. Cole. 1995. Simulation of soil organic matter dynamics in dryland wheat-fallow cropping systems. Chapter 22 pp 259-270 In R. Lal, J. Kimball, E. Levine, B.A. Stewart (eds.) Soil Management and Greenhouse Effect, Lewis Publishers, Boca Raton, Fl.
Mosier, A.R., W.J. Parton, D.W. Valentine, D.S. Ojima, D.S. Schimel and O. Heinemeyer. 1997. CH4 and N2O fluxes in the Colorado shortgrass steppe: 2. Long-term impact of land use change. Global Biogeochemical Cycles 11:29-42.
Kelly, R.H., W.J. Parton, G.J. Crocker, P.R. Grace, J. Klir, M. Korschens, P.R. Poulton, and D.D. Richter. 1997. Simulating trends in soil organic carbon in long-term experiments using the Century model. Geoderma 81:75-90.
Ojima, D.S., K.A. Galvin and B.L. Turner II. 1994. The global impact of land-use change. BioScience 44(5):300-304.
Baron, J., D.S. Ojima, E.A. Holland, and W.J. Parton. 1994. Analysis of nitrogen saturation potential in Rocky Mountain tundra and forest: Implications for aquatic systems. Biogeochemistry 27:61-82.
Xiao, X., D.S. Ojima, W.J. Parton, Z. Chen and D. Chen. 1995. Sensitivity of Inner Mongolia grasslands to climate change. Journal of Biogeography 22:643-648.
Ojima, D.S., L. Stretch, T. Chuluun, L. Tieszen, A. Andreev, G. Erdenejav, H. Liu, S. Khudulmur, A. Preshchepa, B. Reed, H. Yamamoto, Z. Yu, S. Zhu. 1997. Development of the temperate east Asia land-cover (TEAL) database. In Y. Himiyama and L. Crissman (eds.) Proceedings of the IGU-LUCC '97 Meeting on Information Bases for Land Use/Cover Change Research, Brisbane, Australia 1-4 July 1997. pp. 77-83.
Ojima, D.S., W.E. Easterling, W.J. Parton, R. Kelly, B. McCarl, L. Bohren, K. Galvin, and B. Hurd. Integration of ecosystem and economic factors determining land use in the central Great Plains. Book Chapter in P. Puntenney (ed.) A Lasting Impression: Interpreting the Human Dimension of Global Environmental Issues. Lynne Reinner Press, Boulder, CO. (in press)
Frolking, S., A. R. Mosier, D.S. Ojima, C. Li, W.J. Parton, C. Potter, E. Priesack, R. Stenger, C. Haberbosch, P. Dorsch, H. Flessa and K.A. Smith. 1998. Comparison of N2O emissions from soils at three temperate agricultural sites: Simulations of year-round measurements by four models. Nutrient Cycles in Agroecosystems 52: 77-105.
David Schimel:
Research conducted at the National Center of Atmospheric Research is funded
largely by NSF, the David Schimel has been successful in diversifying his
external funding, he has a significant amount of research being conducted
through NSF resources. We provide a brief overview of three areas of research
pertinent to this proposal.
The Effects of Interannual Climate Variability on Terrestrial Ecosystems
This research area involves David Schimel and collaborators Bobby Braswell,
Berrien Moore III, and Ernst Linder (all of University of New Hampshire).
In earlier modeling work, we suggested, based on the responses of the Century
ecosystem model, that a substantial portion of the response of ecosystems
to temperature anomalies should be lagged relative to the forcing. These
lags occur in the model because of the long turnover times of soil organic
matter and deep soil moisture compartments. We found a weak, instantaneous,
positive correlation between temperature and growth rate, and a significant
anti-correlation lagged 1.5 to 3 years. The sign and timing of this correlation
are consistent with model-predicted responses. We conducted a further analysis
of the satellite vegetation index, derived from the NOAA Advanced Very High
Resolution Radiometer (AVHRR) instrument. This work provided important observational
evidence for the mechanisms linking temperature to ecosystem dynamics but
also showed that different biomes (northern versus tropical forests and grasslands)
behave differently with respect to climate change. This work was published
in Science in October, 1997.
Ecosystem Dynamics and the Atmosphere Section (EDAS) scientists (David Schimel and Rebecca McKeown), working with Robert Braswell (University of New Hampshire) and Tomislava Vukicevic (Cooperative Institute for Research in the Atmosphere, Colorado State University), developed a simplified terrestrial carbon model. The model parameters are estimated by inversion against global temperature and CO2 growth rate anomalies. Constraints on the model parameters were derived from observations where possible and from a global forward integration of the Century model, when observations were unavailable. Sensitivity analysis of the model showed that coupling of terrestrial carbon dynamics to N cycling in soils was responsible for much of the signal observed in the atmosphere: inversion without an N cycle results in much lower modeled terrestrial fluxes.
Historical (1895-1993) "Bioclimate" and Future Climate Scenarios for VEMAP
and the U.S. National Assessment
The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) is a
multi-agency, international collaboration aimed at improving and intercomparing
biospheric models for predicting the effects of climate and climate change
on terrestrial ecosystems. The project is now in its second phase, after completing
an analysis of ecosystem responses to current climatology and equilibrium climate
change scenarios. The objectives of Phase 2 are to compare time-dependent ecological
responses of biogeochemical models and dynamic global vegetation models (that
simulate coupled biogeochemical biogeographical processes) to historical and
projected transient forcings across the conterminous U.S.
An Integrated Land Model for the CSM
During the development of the Climate System Model (CSM), it has become apparent
that a from-the-ground-up effort was needed to develop a new land model.
Linking the existing NCAR codes (Land Surface Model (LSM) of Bonan and Century
of Schimel and collaborators), while complementary in the processes and timescales
they address, presented major conceptual problems. In addition, neither model
addresses changes to vegetation type. As a consequence, a collaboration has
developed with Jon Foley (University of Wisconsin) to develop a new version
of Foley's IBIS model that would combine the science in LSM and Century.
This model will be adapted for studying climate change, land use change,
and paleoclimate interactions. It will be formulated for long-term climatological
applications of the CSM, while Century and LSM will remain as alternate approaches
with compatible mechanisms to the integrated model.
Ron Neilson:
DEB-952361, Vegetation Response to Mesoscale Climate Variability in the Mountainous West.
P.I. S.A. Ferguson, University of Washington; co-P.I.s L.O. Mearns, NCAR; R.P. Neilson, C. Daly, Oregon State University. (9/95-9/98, extended to 9/99).The OSU component of this NSF grant was to develop the gridded 2.5' monthly temperature and precipitation 40 yr timeseries over Oregon (Daly) and the Dynamic General Vegetation Model to be implemented on the grid (Neilson). The climate data task has been completed and the full set of climate data, requiring all three groups has now been completed.
Development of the BIOMAP Dynamic Global Vegetation Model (DGVM) has also been completed and results from the coupling of the biogeographical model MAPSS (Neilson 1995) with the biogeochemical model BIOME-BGC. When linking both models with overlapping processes a single code is selected from one and shared by both, for example soil hydrology, and timesteps are reconciled (Neilson and Running 1996). A fire sub-model was added to the hybrid model (BIOMAP) to account for fire disturbance. BIOMAP was adapted to run on a full grid, to accept up to five soil layers and to simulate life form competition for light, water and nutrients.
BIOME-BGC simulates the processes involved in the water, carbon and nitrogen budgets and operates on daily and annual time steps. It simulates a single tree, shrub or grass lifeform over one soil layer. MAPSS is an equilibrium biogeography model that simulates the potential climax vegetation under any average monthly climate. It uses physiologically-based rules to determine woody lifeform type and simulates the competition for light and water between a woody overstory (tree or shrub) and a grass understory over three soil layers. A second rulebase uses the simulated information of overstory lifeform type, and the leaf area indices (LAI) (including phenology) of over and understory to arrive at a physiognomic community classification, such as xeromorphic subtropical shrubland.
Before coupling the two models, BIOME-BGC was generalized to the MAPSS structure with overstory/understory competition for light, water and nutrients. Beer's Law determines the understory light environment based on overstory LAI. Water uptake is determined by canopy demand and taken from the soil as a linear function of vertical root distribution. Competition for water is a function of the lifeform proportionality of roots within each soil layer. Nitrogen competition is treated in a similar way. The hybrid model is now complete and being tested over the VEMAP2 transient climate database and the new Oregon transient climate database. Early results indicate that the model appears to be performing quite well.
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CURRICULUM VITAE
DENNIS SHOJI OJIMA
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, CO 80523
Phone: (303) 491-1976
E-mail: dennis @ nrel.colostate.edu
Academic Training:
B.A. - 1975 - Pomona College
M.Ag. - 1978 - University of Florida
Ph.D. - 1987 - Colorado State University
Professional Experience:
1996 - Sr. Research Scientist, Natural Resource Ecology Laboratory, CSU
1993-1996 - Research Scientist, Natural Resource Ecology Laboratory, CSU
1992 - Assistant Professor, Rangeland Ecosystem Science Dept., CSU
1990-1991 - Visiting Scientist, Office for Interdisciplinary Earth Studies,
UCAR
1988-1990 - Programme Officer, International Geosphere-Biosphere Programme
Professional Organizations and Committees:
American Geophysical Union; AAAS; Ecological Society of America; International
Social Science Council/International Geophere Biosphere Programme ad hoc Committee
on Land Cover/Use, Committee Member, 1991-1993; International Global Atmospheric-Biospheric
Chemistry (IGAC) Program Steering Committee Member on Activity 7.2: Trace-Gas
Fluxes in Mid-Latitude Terrestrial Ecosystems, 1990-present; Biosphere-Atmosphere
Trace Gas Network US (BAGNET) Steering Committee Member, 1992-present; Land-Use/Cover
Changes in Temperate East Asia (LUTEA) Steering Committee Chair, 1996-present;
Covenor of the Central Great Plains Regional Assessment, 1997-1998
Ojima's Recent Research Seeks:
| To integrate a market-level agricultural sector model (ASM or FASOM) with a farm level optimization model, supplemented by a sub-county level analysis of non-market land use drivers (social, cultural, and environmental) with the CENTURY model. | |
| Understanding of the complex interactions of climate and human activities in a region is needed to predict the outcome of various land use options set by land resources managers and policy entities that integrate across various environmental, economic, social, and political systems. | |
| Analyze the impact of changes in climate, land use, and vegetation of the Asian and North American grasslands. |
Using Multi-sensor Data to Model Factors Limiting Carbon Balance in Global Grasslands (NASA) (PI). Funded: 1/1/91-12/31/98
Biological Hysteresis in Climate Change Models for the Great Plains: Implications of Plant Community Changes on Biogeochemical Feedbacks (DOE-NIGEC) (PI). 7/1/92-6/30/93
Modeling of CO2 Impact on a Grassland System (DOE-KSU subcontract) (Co-PI). 1/1/91-12/31/94
Predicting the Effect of Global Change on Vegetation in Park Landscapes in the Central Grasslands Biogeographical Area (NPS) (PI). Funded: 3/1/93-3/31/98
Vegetation Ecosystem Modeling and Analysis Project (VEMAP- Phase I and II), (USDA-FS and NASA) (PI). Funded: 11/93-12/98.
A Hierarchical Approach to Integrated Assessment of Climate and Land Use Changes with an Application to the Central US (CLUC). (NSF) (PI). Funded: 10/1/95-9/30/98.
Publications:
Ojima, D.S., T.G.F. Kittel, T. Rosswall, and B.H. Walker. 1991. Considerations
for studying global change effects on terrestrial ecosystems. Ecological Applications
1:316-325.
Hobbs, N.T., D.S. Schimel, C.E. Owensby and D.S. Ojima. 1991. Fire and grazing in the tallgrass prairie: contingent effects on nitrogen budgets. Ecology 72:1374-1382.
Ojima, D.S. (ed.) 1992. Earth System Modeling. Proceedings from the 1990 Global Change Institute on Earth System Modeling. Snowmass, Colorado, 16-27 July 1990. UCAR/OIES. Global Change Institute Vol 3. 488 pp.
Ojima, D.S., W.J. Parton, D.S. Schimel, J.M.O. Scurlock and T.G.F. Kittel. 1993. Modeling the effects of climatic and CO2 changes on grassland storage of soil C. Water, Air and Soil Pollution 70:643-657.
Parton, W.J., J.M.O. Scurlock, D.S. Ojima, T.G. Gilmanov, R.J. Scholes, D.S. Schimel, T. Kirchner, J-C. Menaut, T. Seastedt, E. Garcia Moya, A. Kamnalrut and J.L. Kinyamario. 1993. Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Global Biogeochemistry Cycles 7:(4):785-809.
Ojima, D.S., K.A. Galvin and B.L. Turner, II. 1994. The global impact of land-use change. BioScience 44:300-304.
Ojima, D.S., D.S. Schimel, W.J. Parton and C.E. Owensby. 1994. Long- and short-term effects of fire on nitrogen cycling in tallgrass prairie. Biogeochemistry 24:67-84.
Schimel, D.S., B.H. Braswell Jr., E.A. Holland, R. McKeown, D.S.Ojima, T.H. Painter, W.J. Parton and A.R. Townsend. 1994. Climatic, edaphic and biotic controls over storage and turnover of carbon in soils. Global Biogeochemical Cycles 8(3):279-293.
Xiao, X., D.S. Ojima, W.J. Parton, Z. Chen and D. Chen. 1995. Sensitivity of Inner Mongolia grasslands to climate change. Journal of Biogeography 22:643-648.
Ojima, D.S., W.J. Parton, M.B. Coughenour, J.M.O. Scurlock, T. Kirchner, T.G.F. Kittel, D.O. Hall, D.S. Schimel, E. Garcia Moya, T.G. Gilmanov, T.S. Seastedt, Apinan Kamnalrut, J.I. Kinyamario, S.P. Long, J-C. Menaut, O.E. Sala, R.J. Scholes and J.A. van Veen. 1996. Impact of climate and carbon dioxide changes on grasslands of the world. Chapter 12 In: A.I Breymeyer, D.O. Hall, J.M. Melillo and G.I. Ågren (eds.) Global Change: Effects on Coniferous Forests and Grasslands. John Wiley & Sons Ltd.
Conflict of Interest: Archer, S., Baron, J., Braswell, Jr., B.H., Bromberg, J.G., Brown, V.B., Cole, C.V., Coughenour, M.B., Coxwell, C., Kirchner, T., McGuire, A.D., McKeown, R., Mosier, A.R., Neilson, R.P., Parton, W.J., Paustian, K., Pielke, R.A., Pulliam, W.M., Reiners, W.A., Running, S.W., Schimel, D.S., Scurlock, J.M.O., Valentine, D.W., Wessman, C.A., Xiao, X., Zuozhong, C.
Graduate and Undergraduate Advisors and Advisees: J.J. Ewel, A.E. Lugo,
W.J. Parton, D.S. Schimel, C.V. Cole, G. Innis, J.K. Detling, Robin Martin,
Xiao Xiangming, Laura Stretch
CURRICULUM VITAE
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, CO 80523
Phone: (970) 491-1987; Fax: (970) 491-1965;
email: billp@nrel.colostate.edu
Education:
B.S. - 1966 - Pennsylvania State University - Meteorology
M.S. - 1968 - University of Oklahoma - Meteorology
Ph.D. - 1972 - University of Oklahoma - Meteorology
Professional Experience:
1966-1968 - Research Assistant, University of Oklahoma
1966-1968 - Teaching Assistant, University of Oklahoma
1968-1971 - Special Instructor, University of Oklahoma
1971-1974 - Postdoctoral Fellowship, Natural Resource Ecology Lab, Colorado
State University
1974-1975 - Postdoctoral Fellowship, National Center for Atmospheric Research
1975-1982 - Research Associate, NREL, Colorado State University
1982-1988 - Senior Research Scientist, NREL, Colorado State University
1988-1989 - Program Director, Division Of Biotic Systems and Resources, Ecosystem
Studies Program, National Science Foundation, Washington, DC 20550
1989-present - Professor and Senior Research Scientist, Range and Ecosystem
Science Department and NREL, Colorado State University
Professional and Honorary Societies, Committees:
Chi Epsilon Pi, Sigma Xi, The Ecological Society of America, SCOPE Grassland
Modeling Committee Member, LTER Cross Site Decomposition Committee, EPA Climatic
Change Review Committee Member, Scientific Advisor for the TSBF Program, Global
Change Committee for Trace Gas and Nutrient Fluxes, Assoc. Editor for Ecological
Applications, NSF Ecosystem Panel (1984-86), Climate System Modeling Program
Advisory Committee Member, NSF LTER Technology Transfer Committee (1988-90),
Global Change and Terrestrial Ecosystem (GCTE) Scientific Steering Committee
Member, GCTE Focus 1.4 Activity Leader, National Research Council Committee
on Geophysical & Environmental Data - Member, McMurdo Dry Valley LTER Advisory
Committee Member, Glossary of Meteorology Editorial Board, American Meteorology
Society
Relevant Publications: (60 Journal Articles and Book Chapters Since
1991)
Parton, W.J., J.M.O. Scurlock, D.S. Ojima, D.S. Schimel, D.O. Hall, M.B. Coughenour,
E. Garcia Moya, T.G. Gilmanov, Apinan Kamnalrut, J.I. Kinyamario, T.B. Kirchner,
S.P. Long, J-C. Menaut, O.E. Sala, R.J. Scholes and J.A. van Veen. 1995. Impact
of climate change on grassland production and soil carbon worldwide. Global
Change Biology 1:13-22.
Parton, W.J. and P.E. Rasmussen. 1994. Long-term effects of crop management in a wheat/fallow system: II. Modelling change with the CENTURY model. Soil Sci. Soc. A. J. 58:530-536.
Parton, W.J., D.S. Schimel, and D.S. Ojima. 1994. Environmental change in grasslands: Assessment using models. Climatic Change 28:111-141.
Riebsame, W.E., W.J. Parton, K.A. Galvin, I.C. Burke, L. Bohren, R. Young, and E. Knop. 1994. Integrated modeling of land use and cover change in the Great Plains. BioScience 44(5):350-356.
Mosier, A., D. Schimel, D. Valentine, K. Bronson and W. Parton. 1991. Methane and nitrous oxide fluxes in native, fertilized and cultivated grasslands. Nature 350:330-332.
Additional Publications:
Parton, W.J., A.R. Mosier, D.S. Ojima, D.W. Valentine, D.S. Schimel, K. Weier,
and A.E. Kulmala. 1996. Generalized model for N2 and N2O
production from nitrification and denitrification. Global Biogeochemical Cycles
10:401-412.
Mosier, A.R., D.W. Valentine, W.J. Parton, D.S. Ojima, D.S. Schimel and J.A. Delgado. 1996. CH4 and N2O fluxes in the Colorado shortgrass steppe: 1. Impact of landscape and nitrogen addition. Global Biogeochemical Cycles 10:387-399.
Parton, W.J., J.M.O. Scurlock, D.S. Ojima, T.G. Gilmanov, R.J. Scholes, D.S. Schimel, T. Kirchner, H-C. Menaut, T. Seastedt, E. Garcia Moya, Apinan Kamnalrut, and J.L. Kinyamario. 1993. Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Global Biogeochemical Cycles 7(4):785-809.
Parton, W. J., J. A. Morgan, J. M. Altenhofen, and L. A. Harper. 1988. Ammonia volatilization from spring wheat plants. Agronomy J. 80:419-425.
Ojima, D. S., A.R. Mosier, W.J. Parton, D.S. Schimel, and D.W. Valentine. 1993. Effects of land use change on soil methane oxidation in temperate forest and grassland soils. Chemosphere 26:675-685.
Collaborators:
S. Archer, B.H. Braswell, V.B. Brown, M.R. Carter, D.P. Coffin, B. Curtis,
E.T. Elliott, S.B. Frey, F. Giorgi, E.R. Hunt, W.K. Lauenroth, A. Martin, A.D.
McGuire, A.K. Metherell, A.R. Mosier, P.P. Motavalli, R.P. Neilson, C. Owensby,
C.A. Palm, K. Paustian, W.M. Pulliam, C. Rowland, S. Running, R.L. Sanford,
J.E. Schultz, T. Seastedt, H.H. Shugart, T.M. Smith, G.R. Steed, D.R. Turner,
D.L. Urban, D.W. Valentine, P.M. Vitousek, B. Walker, C.A. Wessman, P. Woomer,
Jr., X. Xiao, C. Zuozhong
Graduate Advisors & Advisees: G. Amos Eddy, Dennis Ojima, David
Swift, John Zachariassen, Kim Eisele, Thomas Peterson, Dominque Bachelet, Paul
Hook, Greg McMaster, Weihong Fann, By Brown, Robin Martin
CURRICULUM VITAE
David Steven Schimel
Born: 1955
Education:
B.A. - 1977 - Hampshire College, Amherst, Massachusetts
Ph.D. - 1982 - Colorado State University, Fort Collins
Professional Experience:
1986-present - Research Scientist, NREL, Colorado State University
1988-1989 - National Research Council Senior Fellow, NASA/Ames Research Center
1989-present - Associate Professor, Department of Forest & Wood Science
1990-present - Project Scientist, Climate System Modeling Program, University
Corporation for Atmospheric Research (UCAR)
1992-1995 - Scientist III, National Center for Atmospheric Research (NCAR)
1992-present - Section Head, Climate and Global Dynamics Division, NCAR
1995 - Senior Research Scientist, NREL, Colorado State University
1995 - Senior Scientist, NCAR
Professional and Honorary Societies, Committees:
American Geophysical Union
Ecological Society of America
International Geosphere-Biosphere Program: Task Force on Global Analysis, Interpretation
and Modeling
NASA Earth Observing System Project, Biogeochemistry Panel, chairman
NASA Topographic Science Working Group
SCOPE Working Group on Biogenic Trace Gases
Intergovernmental Panel on Climate Change (IPCC), Convening Lead Author, 1994
and 1995 Reports
U.S. National Academy Committee on Global Change
Working groups on Biological Systems and Dynamics, Earth system Models, Nutrient
Fluxes, and Dynamics
U.S. National Academy Committee on Global Change Research
1990 Global Change Institute, steering committee
Committee on Global Change Research in China, National Academy of Sciences
National Research Council Committee on Atmospheric Chemistry
National Research Council Committee on Global Change Research
Recent Publications: (Out of 98)
Schimel, D.S., B.H. Braswell and W.J. Parton. 1997. Equilibration of the terrestrial
water, nitrogen, and carbon cycles. Proceedings of the National Academy
of Sciences
94:8280-8283.
Schimel, D.S., M. Grubb, F. Joos, R. Kaufmann, R.H. Moss, W. Ogana, R. Richels and T.M.L. Wigley. 1997. Stabilization of Atmospheric Greenhouse Gases: Physical, Biological and Socio-economic Implications. IPCC Technical Paper III, 52pp.
Mosier, A.R., W.J. Parton, D.W. Valentine, D.S. Ojima, D.S. Schimel, and O. Heinemeyer. 1997. CH4 and N2O fluxes in the Colorado shortgrass steppe: 2. Long-term impact of land use change. Global Biogeochemical Cycles 11:29-42.
Schimel, D.S., VEMAP Participants, and B.H. Braswell. 1997. Spatial variability in ecosystem processes at the continental scale: models, data, and the role of disturbance. Ecological Monographs 67:251-271.
Braswell, B.H., D.S. Schimel, J.L. Privette, B. Moore III, W.J. Emery, E.W. Sulzman, and A.T. Hudak. 1996. Extracting ecological and biophysical information from AVHRR optical measurements: A new algorithm based on inverse modeling. Journal of Geophysical Research 101:23,335-23,348.
Relevant to project:
Schimel, D.S., B.H. Braswell, R. McKeown, D.S. Ojima, W.J. Parton, and W. Pulliam.
1996. Climate and nitrogen controls on the geography and time scales of terrestrial
biogeochemical cycling. Global Biogeochemical Cycles 10:677-692.
Ciais, P., P.P. Tans, J.W.C. White, M. Trolier, R.J. Francey, J.A. Berry, D.R. Randall, P.J. Sellers, J.G. Collatz, and D.S. Schimel. 1995. Partitioning of ocean and land uptake of CO2 as inferred by d13C measurements from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network. J. Geophys. Res. (Atmospheres) 100 (D3):5051-5070.
Friedlingstein, P., I. Fung, E. Holland, J. John, G. Brasseur, D. Erickson, and D. Schimel. 1995. On the contribution of CO2 fertilization to the missing biospheric sink. Global Biogeochemical Cycles 9(4):541-556.
Schimel, D.S. 1995. Terrestrial Biogeochemical cycles: Global estimates with remote sensing. Remote Sensing of Environment51:49-56. ISLSCP-Americas Special Issue.
Schimel, D.S., B.H. Braswell, Jr., E.A. Holland, R. McKeown, D.S. Ojima, T.H. Painter, W.J. Parton, A.R. Townsend. 1994. Climatic, edaphic and biotic controls over storage and turnover of carbon in soils. Global Biogeochemical Cycles 8(3):279-293.
Collaborators:
Steve Archer, Texas A&M University; Greg Asner, University of Colorado;
Jeff Borchers, USDA, Oregon State University; Bobby Braswell, University of
New Hampshire; John Chaney, USDA, Oregon State University; Chris Field, Carnegie
Institute of Washington; Hank Fisher, National Center for Atmospheric Research;
William Emanuel, University of Virginia; Alex Haxeltine, University of Lund,
Sweden; Kathy Hibbard, University of Montana; David Kicklighter, Marine Biological
Laboratory; Timothy Kittel, National Center for Atmospheric Research; A. David
McGuire, Marine Biological Laboratory; Rebecca McKeown, National Center for
Atmospheric Research; Jerry Melillo, Marine Biological Laboratory; Russ Monson,
University of Colorado; Ron Neilson, USDA, Oregon State University; R. Nemani,
University of Montana; Dennis Ojima, Colorado State University; Thomas Painter,
National Center for Atmospheric Research; Yude Pan, Marine Biological Laboratory;
William Parton, Colorado State University; Lars Pierce, University of Montana;
Colin Prentice, University of Lund, Sweden; Brian Rizzo, University of Virginia;
Nan Rosenbloom, National Center for Atmospheric Research; Steve Running, University
of Montana; Stephen Sitch, University of Lund, Sweden; Tom Smith, University
of Virginia; Carol Wessman, University of Colorado; F. Ian Woodward, University
of Sheffield, UK
Students:
Greg Asner, University of Colorado; Rob Braswell, University of New Hampshire;
Virginia Brown, Colorado State University; Andrew Hudak, University of Colorado;
Jeff Privette, University of Colorado; Nan Rosenbloom, National Center for
Atmospheric Research; Meg Walsh, Colorado State University (total of 14 students)
Postdocs:
Harald Bugmann, National Center for Atmospheric Research; Emil Cienciala, National
Center for Atmospheric Research; James Famiglietti, University of Texas; Flint
Hughes, University of Colorado (total of 7 postdocs)
Advisors:
Ph.D. - Robert Woodmansee, Colorado State University
Postdoc - William Parton, Colorado State University
CURRICULUM VITAE
LAWRENCE E. BAND
Voit Gilmore Professor, Department of Geography, University of North Carolina,
Chapel Hill, NC 27599
Phone: 919-962-3921
fax: 919-962-1537
email: lband@email.unc.edu
Degrees
Ph.D., 1983, Geography, University of California, Los Angeles
M.A., 1979, Geography, University of California, Los Angeles
B.A., Geography, S.U.N.Y. at Buffalo, Summa Cum Laude, 1977
Relevant Publications 1995-present:
Band, L.E., R. Vertessey and R.B. Lammers, 1995. The effect of different terrain
representation schemes and resolution on simulated watershed processes. Zeitschrift
fur Geomorphologie, Suppl-Bd. 101, p.187- 199.
Band, L.E., D.S. Mackay and I.F. Creed, R. Semkin and D. Jeffries 1996. Ecosystem processes at the watershed scale: Sensitivity to potential climate change. Limnology and Oceanography, v.41, p.928-938.
D.S. Mackay and L.E. Band 1997. Forest ecosystem processes at the watershed scale: Dynamic coupling of distributed hydrology and canopy growth. Hydrological Processes, v.11, p.1197-1217.
R.B. Lammers Band, L.E. Band C. Tague 1997. Scaling water and carbon budgets to regional extents: Simulation approach. SEB Seminar Series --- Scaling Up, P. Van Gardingen, ed., Cambridge University Press, Cambridge, p.295-318.
Baron, J.S., M.D. Hartman, T.G.F. Kittel, L.E. Band, D.S. Ojima and R.B. Lammers 1998. Effects of land cover, water redistribution and temperature on ecosystem processes in the South Platte Basin. Ecological Applications, v.8, p.1037-1051.
Other Publications 1995-Present:
Band, L.E. and I.D. Moore, 1995. Scale: Landscape attributes and GIS. Hydrological
Processes, v.9, p.401-422.
I.F. Creed, L.E. Band, N.W. Foster, I.K. Morrison, J.A. Nicolson, R.S. Semkin and D.S. Jeffries, 1996. Regulation of nitrate-N release from temperate forests: A test of the N flushing hypothesis. Water Resources Research., v.32, p.3337-3354.
Mackay, D.S. and L.E. Band 1998. Topographic partitioning of watersheds with lakes and other flat areas on digital elevation models. Water Resources Research, v.34, p.297-902.
I.C. Creed and L.E. Band 1998. Export of nitrogen from catchments within a temperate forest: Evidence for a unifying mechanism regulated by variable source area dynamics. Water Resources Research, v.34, p.3105-3120.
I.C. Creed and L.E. Band 1998. Exploring similarity in the export behavior of nitrate-N from forested catchments: A mechanistic modeling approach. Water Resources Research, v.34, p.3079-3093.
Collaborators
J. Baron (Col. State Univ.), I.C. Creed (U. Western Ontario), F. Csillag
(U. Toronto), J. Desloges (U.Toronto), N.W. Foster, R. Grayson (U. Melbourne),
M. Hartman (Col. State Univ.), D.S. Jeffries (Env. Canada), T. Kittel (NCAR),
D.S. Mackay (U. Wisconsin), I.K. Morrison, R. Nemani (U.Montana), J.A. Nicolson
(For. Canada), D. Ojima (Col. State Univ.), R. Pielke (Col. State Univ.), S.
Running (U.Montana), R.S. Semkin, C.Tague (U. Toronto), R. Vertessy (CSIRO),
F. Watson (Cal. State Monterey Bay), A. Zhu (U. Wisconsin).
Graduate student supervision (last five years):
Christina Tague Msc. - Completed 1994.
Axing Zhu Phd. - Completed 1994 - Currently Asst. Professor, University
of Wisconsin
David Baldwin MSc. - Completed 1997
Anastasia Svirejeva Msc. - Completed 1997
Xuewen Wang Phd. - Continuing
Richard Lammers Phd. - Completed 1998 - Currently Post-Doc, UNH
Irena Creed Phd. - Completed 1998 - Currently Asst. Professor, University
of Western Ontario
Richard Fernandes Phd. - Continuing
Christina Tague Phd. - Continuing
Tongzhin Zhu Phd. - Completed 1998 - Currently Asst. Professor, University
of Minnesota, Duluth
D. Scott Mackay Phd. - Completed 1997 - Currently Asst. Professor, University
of Wisconsin
Masters and Phd. Advisor: Dr. A.R. Orme, Dept. Geography, UCLA
CURRICULUM VITAE
MICHAEL B. COUGHENOUR
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, CO 80523
Phone: (970) 491-5572
email: mikec@nrel.colostate.edu
Academic Training:
B.S. 1973 University of Illinois Biology
M.S. 1974 University of Illinois Biology
Ph.D. 1978 Colorado State University Systems Ecology
Professional Experience:
1974-1978, Graduate Research Assistant, Natural Resource Ecology Laboratory,
Colorado State University, Fort Collins, CO
1978-1983, Postdoctoral Research Associate, Department of Biology, Syracuse
University
1983-1985, Postdoctoral Research Associate, Natural Resource Ecology Laboratory,
Colorado State University, Fort Collins, CO
1985-1986, Research Associate, Natural Resource Ecology Laboratory, Colorado
State University, Fort Collins, CO
1986-1991, Research Scientist, Natural Resource Ecology Laboratory, Colorado
State University, Fort Collins, CO
1991-present, Senior Research Scientist, Natural Resource Ecology Laboratory,
Colorado State University, Fort Collins, CO
Other Appointments:
1990-present, Associate Professor (Affiliate), Range Science Department, Colorado
State University
1992-present, Adjunct Assistant Professor, University of Oklahoma
Professional and Honorary Societies:
Ecological Society of America
Society for Range Management
African Wildlife Society
Sigma Xi
Program for Ecological Studies, Colorado State University
Five Relevant Publications
Coughenour, M. B. 1992. Spatial modeling and landscape characterization of
an African pastoral ecosystem: a prototype model and its potential use for
monitoring drought. pp. 787-810 in: D.H. McKenzie , D.E. Hyatt
and V.J. McDonald (eds.). Ecological Indicators, Vol. I. Elsevier Applied
Science, London and New York.
Coughenour, M. B., and J. E. Ellis. 1993. Landscape and climatic control of woody vegetation in a dry tropical ecosystem: Turkana District, Kenya. J. Biogeogr. 20:107-122.
Coughenour, M.B. 1993. The SAVANNA Landscape Model - Documentation and Users Guide. Natural Resource Ecology Laboratory, Colorado State University, Ft. Collins CO.
Coughenour, M.B. and W.J. Parton. 1996. Integrated models of ecosystem function: a grassland case study. Chap. 6 in B.H. Walker and W.L. Steffen (eds.). Global Change and Terrestrial Ecosystems, Cambridge University Press.
Coughenour, M.B. and D.X. Chen. 1997. An assessment of grassland ecosystem responses to atmospheric change using linked ecophysiological and soil process process models. Ecological Applications 7:802-827.
Five Additional Publications
Coughenour, M. B. 1984. A mechanistic simulation analysis of water
use, leaf angles, and grazing in East African graminoids. Ecological
Modelling 26:203-220.
Coughenour, M. B. 1985. Graminoid responses to grazing by large herbivores: Adaptations, exaptations and interacting processes. Annals Missouri Bot. Garden 72:852-863.
Coughenour, M. B., D. L. Coppock, J. E. Ellis, and M. Rowland. 1990. Herbaceous forage variability in an arid pastoral region of Kenya: Importance of topographic and rainfall gradients. J. Arid Environ. 19:147-159.
Chen, D.X., M.B. Coughenour, C. Owensby and A. Knapp. 1993. Mathematical simulation of C4 grass photosynthesis in ambient and elevated CO2. Ecol. Model. 73:63-80.
Stohlgren, T.J., M.B. Coughenour, G.W. Chong, D. Binkley, M.A. Kalkhan, L.D. Schell, D.J. Buckley, and J.K. Berry. 1997. Landscape analysis of plant diversity. Landscape Ecology (in press).
Collaborators:
D. Binkley, D. Chen, T. Elliott, K. Galvin, T. Kittel, A. Knapp, C. Owensby,
T. Stohlgren, D. Valentine, L. Wallace, J. Welker.
Post-doctoral, Graduate and Undergraduate Advisors and Advisees:
B. Hannon, J. Dodd, D. Coleman, J. Ellis, S. McNaughton
CURRICULUM VITAE
A. SCOTT DENNING
Department of Atmospheric Science, Colorado State University, Fort Collins,
CO 80523-1371
(970)491-6936 denning@atmos.colostate.edu FAX 491-8449
Education:
B.A., Geological Sciences, 1984. University of Maine, Orono, Maine. Highest
Honors.
M.S., Atmospheric Science, 1993. Colorado State University, Ft. Collins,
Colo.
Ph.D. Atmospheric Science, 1994. Colorado State University, Ft. Collins, Colo.
Professional Experience:
1998B : Assistant Professor, Department of Atmospheric Science, Colorado State
University
Atmosphere-biosphere interactions. Global biogeochemical cycles. Land-surface
climate..
1996B98 : Assistant Professor, Donald Bren School of Environmental Science
and Management,
University of California, Santa Barbara.
1994B96: Postdoctoral Research Associate, Department of Atmospheric Science,
Colorado State
University, Fort Collins, CO. David A. Randall, supervisor. (NASA supported).
Global-scale atmosphere-biosphere interactions using a general circulation
model.
1990B94: Graduate Research Assistant, Department of Atmospheric Science, Colorado
State University,
Fort Collins, CO. David A. Randall, supervisor. (NASA supported).
Synthesis inversion of the global carbon budget using a general circulation
model.
1986B90: Research Associate, Natural Resource Ecology Laboratory, Colorado
State University, Fort
Collins, CO. Jill S. Baron, supervisor. (NPS supported).
Biogeochemical and hydrologic dynamics of an alpine-subalpine watershed.
1985B86: Wellsite Geochemist, GEO Inc., Denver, CO.
Gas chromatographic and lithologic analyses in support of oil exploration objectives.
1980B85: Research Assistant, Department of Geological Sciences, University
of Maine.
Paleolimnologic Investigation and Reconstruction of Lake Acidification.
Awards and Honors:
1977: National Merit Scholar
1984: Phi Beta Kappa
1992-94: National Aeronautic and Space Administration Global Change Research
Fellow.
1994: Outstanding Student Paper, American Geophysical Union
1995: Phi Kappa Phi
Selected Publications:
Denning, A. S., I. Y. Fung, and D. A. Randall, 1995: Latitudinal gradient of
atmospheric CO2 due to seasonal exchange with land biota. Nature, 376,
240-243.
Denning, A. S., J. G. Collatz, C. Zhang, D. A. Randall, J. A. Berry, P. J. Sellers, G. D. Colello, and D. A. Dazlich, 1996. Simulations of terrestrial carbon metabolism and atmospheric CO2 in a general circulation model. Part 1: Surface carbon fluxes. Tellus, 48B, 521-542.
Denning, A. S., D. A. Randall, G. J. Collatz, and P. J. Sellers, 1996. Simulations of terrestrial carbon metabolism and atmospheric CO2 in a general circulation model. Part 2: Spatial and temporal variations of atmospheric CO2. Tellus, 48B, 543-567.
Law, R. M., P. J. Rayner, A. S. Denning, D. Erickson, M. Heimann, S. C. Piper, M. Ramonet, S. Taguchi, J. A. Taylor, C. M. Trudinger, and I. G. Watterson, 1996. Variations in modelled atmospheric transport of carbon dioxide and the consequences for CO2 inversions Global Biogeochemical Cycles, 10, 783-796.
Sellers, P. J., R. E. Dickinson, D. A. Randall, A. K. Betts, F. G. Hall, J. A. Berry, C. J. Collatz, A. S. Denning, H. A. Mooney, C. A. Nobre, and N. Sato, 1997. Modeling the exchanges of energy, water, and carbon between the continents and the atmosphere. Science, 275, 502-509.
Ciais, P., A. S. Denning, P. P. Tans, J. A. Berry, D. A. Randall, G. J. Collatz, P. J. Sellers, J. W. C. White, M. Trolier, H. J. Meijer, R. J. Francey, P. Monfray, and M. Heimann, 1997: A three-dimensional synthesis study of ?18O in atmospheric CO2. Part 1: Surface fluxes. Journal of Geophysical Research, 102, 5857-5872.
Fung, I., C. B. Field, J. A. Berry, M. V. Thompson, J. T. Randerson, C. M. Malmstrom, P. M. Vitousek, G. J. Collatz, P. J. Sellers, D. A. Randall, A. S. Denning, F. Badeck, and J. John, 1997. Carbon-13 exchanges between the atmosphere and biosphere. Global Biogeochemical Cycles, 11, 507-534.
Pielke, R. A., R. Avissar, M. Raupach, H. Dolman, X. Zeng, and S. Denning, 1998. Interactions between the atmosphere and terrestrial ecosystems: influence on weather and climate. Global Change Biology, 4, 101-115.
Denning, A. S., M. Holzer, K. R. Gurney, M. Heimann, R. M. Law, P. J. Rayner, I. Y. Fung, S.-M. Fan, S. Taguchi, P. Friedlingstein, Y. Balkanski, J. Taylor, M. Maiss, and I. Levin, 1999. Three-dimensional transport and concentration of SF6: A model intercomparison study (TransCom 2). Tellus, in press.
Denning, A. S., T. Takahashi and P. Friedlingstein, 1999. Can a strong atmospheric CO2 rectifier effect be reconciled with a Areasonable@ carbon budget? Tellus, in press.
Collaborators: last 4 years
Co-Authors
R. Avissar, Rutgers, U.; P. S. Bakwin, NOAA/CMDL; Y. Balkanski, LMCE, CNRS;
J. A. Berry, Stanford; A.K. Betts, Atmos. Research; P. Ciais, CEA, CNRS; G.
D. Colello, Stanford; J. A. Collatz, NASA GSFC; D. A. Dazlich, Colorado
State University; R. E. Dickinson, U. of Ariz.; H. Dolman, DLO Winand Staring
Centre; D. Erickson, NCAR; S.-M. Fan, Princeton; C. B. Field, Stanford; R.
J. Francey, CSIRO; P. Friedlingstein, CEA-CNRS, France; W. Fu, Stanford; Inez
Y. Fung, UC Berkeley; K. R. Gurney, Colorado State University; F. G. Hall,
NASA/Goddard; M. Heimann, MPI Jena; M. Holzer, Canadian Climate Centre; J.
John, UC Berkeley; C. O. Justice, U. Va; R.M. Law, Monash Univ; I. Levin, Heidelberg
University; S. O. Los, NASA, Goddard; M. Maiss, MPI; C. Malmstrom, Stanford;
H. J. Meijer, Univ of Groningen, NL; P. Monfray, LMCE, CNRS; H. A. Mooney,
Stanford; C. A. Nobre, CPTEC, Brazil; P. Peylin, CEA-CNRS, France; P. Pielke,
Colorado State University; S. C. Piper, Scripps; M. Potosnak, Columbia;
M. Ramonet, CEA, CNRS; D. A. Randall, Colorado State University; J. Randerson,
UC Berkeley; M. Raupach, CSIRO, CEM, Canberra; P. J. Rayner, CMC-SHM, CSIRO;
Jorge Sarmiento, Princeton; N. Sato, Japan Met Agency; P. J. Sellers, NASA;
Katerina Six, MPI Hamburg; S. Taguchi, NIRE, Japan; P. P. Tans, NOAA; J. A.
Taylor, Australia National Univ.; M. Thompson, Harvard; M. Trolier, U C Boulder;
C. M. Trudinger, CMC-SHM, Monash Univ; C. J. Tucker, NASA/GSFC; Susan Ustin,
UC Davis; P. Vitousek, Stanford; I.G. Watterson, CSIRO; J. W. C. White, U C
Boulder; S. C. Wofsy, Harvard; C. Zhang , CSU; X. Zeng , Univ of Arizona
Advisees and PostDocs:
Lara Prihodko, CSU; Ni Zhang, CSU; Kevin Gurney, CSU; Christopher Eller, CSU
My own graduate and postdoctoral advisor: David Randall, CSU
CURRICULUM VITAE
NIALL P. HANAN B.Sc., Ph.D.
Natural Resource Ecology Laboratory (NREL)
Colorado State University, Fort Collins, CO 80523
Tel: 970-491-0240
Fax: 970-491-1965
Email: niall@NREL.Colostate.edu
RESEARCH AREA
Land surface-atmosphere interactions. Ecophysiology of carbon, water and energy
exchange between plants and atmosphere. Ecosystem carbon and energy balance
measurement and modeling. Radiative and aerodynamic transfer in Soil-Vegetation-Atmosphere
Transfer (SVAT) schemes. Scaling of leaf-level processes to predict emergent
canopy processes. Remote sensing of surface biophysics.
EDUCATION
DOCTOR OF PHILOSOPHY, Biology (1990)
School of Biological Sciences, Queen Mary College, University of London, Dissertation
title: "Vegetation indices and the measurement of vegetation growth in semi-arid
West African grasslands using satellite imagery".
BACHELOR OF SCIENCE, Applied Biology (1985)
Department of Biology, Liverpool Polytechnic, U.K.
EMPLOYMENT
Senior Research Scientist (July 1998 - present). Natural Resource Ecology Laboratory,
Colorado State University.
Research Scientist (January 1998 - June 1998). Donald Bren School of Environmental
Science and Management,
University of California, Santa Barbara and Carnegie Institution of Washington,
Department of Plant Biology, Stanford. Soil-vegetation-atmosphere exchange
using eddy covariance measurements from sites in Wisconsin and Oklahoma and
the Simple Biosphere Model (SiB2).
Research Scientist (May 1995 - August 1997). Winand Staring Centre (SC-DLO),
Wageningen, The Netherlands.
Research into the effects of land use and land cover change on ecosystem function,
energy balance and mesoscale climate in Africa. Research in ecosystem photosynthesis
and carbon balance using HAPEX-Sahel and Euroflux eddy covariance measurements.
Assistant Research Scientist: (August 1993 - February 1995). Geography Department,
University of Maryland.
Analysis and modeling of the biophysical and physiological controls on ecosystem
function, carbon and energy balance in semi-arid Sahelian ecosystems.
Faculty Research Assistant: (September 1990 - July 1993). Geography Department,
University of Maryland.
Responsibility for extensive and intensive biophysical and physiological measurement
programs in semi-arid savanna, fallow and agricultural vegetation during the
HAPEX-Sahel field experiment in Niger, West Africa (1991-1992).
Ecologist: (September 1988-February 1989). Ecological Monitoring Center/United
Nations Development Program, 2
Senegal. Research into methods for the measurement of savanna production in
the Senegalese Sahel, savanna ecology, livestock utilization and vegetation
degradation.
Assistant Scientific Officer: (July 1986-September 1986). Tropical Development
and Research Institute, Zimbabwe. Environmental impact assessment of tsetse
control in Mutoko district, north-east Zimbabwe.
Assistant Scientific Officer: (July 1985-December 1985). Pest & Vector
Management Department, Tropical Development & Research Institute, London
U.K.
Field Trials Officer: (September 1983-September 1984). Agricultural Development
and Advisory Service, Ministry of Agriculture, Fisheries & Food, Cambridge,
U.K.
RELEVANT PUBLICATIONS
Hanan, N. P., Kabat, P., Dolman, A. J. and Elbers, J. A., 1998, Photosynthesis
and carbon balance of a Sahelian fallow savanna, Global Change Biology, 4,
523-538.
Hanan, N.P. and Prince, S.D., 1997, Stomatal conductance of West Central Supersite
vegetation in HAPEX-Sahel:
measurements and empirical models. Journal of Hydrology, 188-189, 536-562.
Hanan, N.P., Prince, S.D. and Bégué, A., 1997, Modelling vegetation primary production during HAPEX-Sahel using production efficiency and canopy conductance model formulations, Journal of Hydrology, 188-189, 651-675.
Hanan, N. P., Elbers, J. A., Kabat, P., Dolman, A. J. and De Bruin, H. A. R., 1996, CO2 flux and photosynthesis of a Sahelian savanna during HAPEX-Sahel, Physics and Chemistry of the Earth, 21, 135-141.
RELATED PUBLICATIONS
Hanan, N. P., Bégué, A. and Prince, S. D., 1997, Errors in remote
sensing of intercepted photosynthetically active radiation: an example from
HAPEX-Sahel, Journal of Hydrology, 188-189, 676-696.
Bégué, A., Roujean, J. L., Hanan, N. P., Prince, S. D., Thawley, M., Huete, A. and Tanré, D., 1996, Shortwave radiation budget of Sahelian vegetation. 1. Techniques of measurement and results during HAPEX-Sahel, Agricultural and Forest Meteorology, 79, 79-96.
Bégué, A., Prince, S. D., Hanan, N. P. and Roujean, J. L., 1996, Shortwave radiation budget of Sahelian vegetation. 2. Radiative transfer models, Agricultural and Forest Meteorology, 79, 97-112.
Hanan, N.P. and Bégué, A., 1995, A method for the estimation of instantaneous and daily intercepted photosynthetically active radiation using a hemispherical sensor. Agricultural and Forest Meteorology , 74, 155-168.
Hanan, N.P., Prevost, Y., Diouf, A. and Diallo, O., 1991, Assessment of desertification around deep wells in the Sahel using satellite imagery. Journal of Applied Ecology, 28, 173-186.
CONFLICT OF INTEREST COLLABORATORS
Begue, A., CIRAD, Montpellier, France
De Bruin, H. A. R., Wageningen Agricultural University, The Netherlands
Dolman, A. J., Winand Staring Centre, The Netherlands
Elbers, J. A., Winand Staring Centre, The Netherlands
Kabat, P., Winand Staring Centre, The Netherlands
Prince, S. D., University of Maryland
Roujean, J.-L., Meteo-France, Toulouse, France
Graduate/Post Graduate advisor: Dr. S. D. Prince, University of Maryland
CURRICULUM VITAE
Ecosystem Dynamics and the Atmosphere Section email: kittel@ucar.edu
Climate and Global Dynamics Division phone: +1 303 497-1606
National Center for Atmospheric Research fax: +1 303 497-1695
Box 3000
Boulder, CO 80307-3000
web page: http://www.cgd.ucar.edu/edas/tim/
Born: 1952
Education
B.S. - 1975 - University of California, Davis Environmental Science
M.S. - 1978 - University of California, Davis Ecology
Ph.D. - 1986 - University of California, Davis Ecology
Professional Experience
1976: Lecturer, Sierra Nevada College, Incline Village, NV.
1977-1983: Research and Teaching Assistant, Division of Environmental
Studies and Department of Land, Air, and Water Resources, University of California,
Davis.
1984: Visiting Lecturer, Dept of Land, Air, and Water Resources, University
of California, Davis.
1985-1986: Postdoctoral Fellow, Cooperative Institute for Research in
the Atmosphere, Colorado State University
1987-1990: Research Associate, Cooperative Institute for Research in
the Atmosphere, Colorado State University
1987-1997: Research Associate, Natural Resource Ecology Laboratory, Colorado
State University
1991-1996: Deputy Project Scientist, Climate System Modeling Program,
University Corporation for Atmospheric Research, Boulder, CO.
1991-1997: Scientific Visitor, Ecosystem Dynamics and the Atmosphere
Section, Climate and Global Dynamics Division, National Center for Atmospheric
Research, Boulder.
1997-present: Research Scientist, Natural Resource Ecology Laboratory,
Colorado State University
1997-present: Scientist II, Ecosystem Dynamics and the Atmosphere Section,
Climate and Global Dynamics Division, National Center for Atmospheric Research,
Boulder.
1998-present: Deputy Section Head, Ecosystem Dynamics and the Atmosphere
Section, Climate and Global Dynamics Division, National Center for Atmospheric
Research, Boulder.
Professional Committees and Science Teams
Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC)
User Working Group.
1997-present.
NASA EOS Algorithm Theoretical Basis Document (ATBD) Review Panel. 1997.
National Technical Advisory Committee, DOE National Institute for Global Environmental
Change (NIGEC). 1996-present.
Climate Scenario Task Force, USDA Forest Service Global Change Research Program. 1994-present.
Vegetation/Ecosystem Modeling Analysis Project (VEMAP) Participant. 1993-present.
Model Evaluation Consortium for Climate Assessment (MECCA) Analysis Team. 1992-1995.
NASA EOS Pathfinder AVHRR Land Surface Science Working Group. 1992-1994.
Steering Committee, 2nd International Conference on Integrating GIS and Environmental
Modeling, National Center for Geographical Information and Analysis (NCGIA). Aug
1992-Sept 1993.
Climate System Modeling Program (CSMP) Science Team, University Corporation
for Atmospheric Research (UCAR). 1991-1996.
Hatch Fund Panel, Agricultural Experiment Station, University of Nevada, Reno. 1989,
1990.
Long-Term Ecological Research (LTER) Program Climate Committee. 1990-present.
First ISLSCP Field Experiment (FIFE) Science Team, NASA. 1987-1992.
Ten Most Related and Significant Publications (Out of 94)
Kittel, T.G.F. 1998. Effects of climatic variability on herbaceous
phenology and observed species richness in temperate montane habitats, Lake
Tahoe Basin, Nevada. Madroño, in press.
Kittel, T.G.F., F. Giorgi, G.A. Meehl. 1998. Intercomparison of regional biases and doubled CO2-sensitivity of coupled atmosphere-ocean general circulation model experiments. Climate Dynamics 14:1-15.
Baron, J.S., M.D. Hartman, T.G.F. Kittel, L.E. Band, D.S. Ojima, and R.B. Lammers. 1998. Effects of land cover, water, redistribution, and temperature on ecosystem processes in the South Platte Basin. Ecological Applications 8:1037-1051.
Pielke Sr., R.A., J. Eastman, T.N. Chase, J. Knaff, and T.G.F. Kittel. 1998. 1973-1996 trends in depth-averaged tropospheric temperature. Journal of Geophysical Research-Atmospheres 103 (D14): 16927-16933. [Errata: J. Geophys. Res. 103: in press]
Stohlgren, T.J., T.N. Chase, R.A. Pielke, Sr., T.G.F. Kittel, and J. Baron. 1998. Evidence that local land use practices influence regional climate, vegetation, and stream flow patterns in adjacent natural areas. Global Change Biology 4:495-504.
Schimel, D.S., VEMAP Participants [includes T.G.F. Kittel], and B.H. Braswell. 1997. Spatial variability in ecosystem processes at the continental scale: Models, data, and the role of disturbance. Ecological Monographs 67: 251-271.
Chase, T.N., R.A. Pielke, T.G.F. Kittel, R. Nemani, and S.W. Running. 1996. Sensitivity of a general circulation model to global changes in leaf area index. Journal of Geophysical Research 101:7393-7408.
Kittel, T.G.F., N.A. Rosenbloom, T.H. Painter, D.S. Schimel, and VEMAP Modeling Participants. 1995. The VEMAP integrated database for modeling United States ecosystem/vegetation sensitivity to climate change. Journal of Biogeography 22: 857-862.
Sulzman, E.W., K.A. Poiani, and T.G.F. Kittel. 1995. Modeling human-induced climatic change: A summary for environmental managers. Environmental Management 19:197-224.
VEMAP Members [includes T.G.F. Kittel]. 1995. Vegetation/Ecosystem Modeling and Analysis Project (VEMAP): Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochemical Cycles 9:407-437.
Collaborators:
R.R. Bachand, Colorado State University; D. Bachelet, Oregon State University;
L.E. Band, University of North Carolina; Jill Baron, Colorado State University;
R. Braswell, University of New Hampshire; T.N. Chase, Colorado State University;
C. Daly, USDA, Oregon State University; J. Eastman, Colorado State University;
W. Emanuel, University of Virginia; F. Giorgi, National Center for Atmospheric
Research; David Greenland, University of North Carolina; M.D. Hartman, Colorado
State University; K. Hibbard, University of New Hampshire; David Kicklighter,
Marine Biological Laboratory; J. Knaff, Colorado State University; R.B. Lammers,
University of Toronto; J Lenihan, USDA, Oregon State University; R. McKeown,
National Center for Atmospheric Research; G.A. Meehl, National Center for Atmospheric
Research; Jerry Melillo, Marine Biological Laboratory; Ron Neilson, USDA, Oregon
State University; R. Nemani, University of Montana; D.S. Ojima, Colorado State
University; T.H. Painter, University of California, Santa Barbara; Yude Pan,
Marine Biological Laboratory; W.J. Parton, Colorado State University; R.A.
Pielke, Sr., Colorado State University; L. Pitelka, University of Maryland;
K.A. Poiani, Cornell University; Colin Prentice, University of Lund, Sweden;
William Reiners, University of Wyoming; N.A. Rosenbloom, National Center for
Atmospheric Research; Steve Running, University of Montana; David S. Schimel,
National Center for Atmospheric Research; T. Smith, University of Virginia;
Tom Stohlgren, Colorado State University; E. Sulzman, Colorado State University;
M. Sykes, University of Lund, Sweden; P. Thornton, University of Montana; F.
Ian Woodward, University of Sheffield, UK
Number of graduate students and postdocs sponsored: 0
Dissertation advisor: John J. Carroll, III, University of California,
Davis
Postdoctorate sponsor: Thomas Vonder Haar, Colorado State University
CURRICULUM VITAE
RONALD P. NEILSON
BioClimatologist, USDA Forest Service, Pacific Northwest Research Station
Professor (Courtesy), Oregon State University
3200 S.W. Jefferson Way
Corvallis, Oregon. 97331
Phone: 503-750-7303, Fax: 503-750-7329, Email: neilson@fsl.orst.edu.
Education:
Ph.D. - 1981 - University of Utah
M.S. - 1975 - Portland State University
B.A. - 1971 - University of Oregon
Positions Held:
1992 - present: BioClimatologist, USDA Forest Service, Pac. NW Res. Stn.
1996 - present: Professor, Dept. Botany and Plant Pathology, Dept. Forest Science,
Oregon State University, Corvallis, Oregon
1989 - 1996: Associate Professor, Dept. General Science and Dept. Botany and
Plant Pathology, Oregon State University, Corvallis, Oregon
1987 - 1989: Assistant Professor, Dept. General Science, OSU
1987 - 1994: Senior Scientist (OSU cooperator), U.S. EPA, Corvallis, Oregon
1985 - 1987: Senior Research Scientist, Env. Studies Lab., Univ. Utah Res.
Inst.
1984 - 1985: Research Associate, Dept. Ecol. and Evol. Biol., Univ. Arizona
1984 - 1985: Research Associate, Arizona-Sonora Desert Museum
1982 - 1984: Research Associate/Assistant Prof., Dept. of Biol., New Mexico
St. Univ.
Research Interests:
Dr. Neilson has focused on the theory, mechanisms and simulation of vegetation
distribution for over two decades. He won the Cooper Award from ESA for
his early researches on this topic and has been honored by use of his MAPSS
model output for national and global assessment purposes by the Intergovernmental
Panel on Climate Change (IPCC) and the U.S. Global Change Research Program. His
current work extends into both Earth System Modeling and Landscape System Modeling
to cover most of the ecological scale spectrum.
Awards:
Cooper Award, Ecological Society of America, 1987.
Technical Contribution Awards, U.S. Environmental Protection Agency, 1988,
1990.
Outstanding Performance Award, USDA Forest Service 1998.
Certificate of Merit, USDA Forest Service 1998.
Selected Relevant Publications:
Neilson, R.P and R.J. Drapek. 1998. Potentially Complex Biosphere Responses
to Transient Global Warming. Global Change Biology 4:
505-521.
Neilson, R.P. and S.W. Running. 1996. Global dynamic vegetation modelling: coupling biogeochemistry and biogeography models. Pages 451-465 in B. Walker and W. Steffen, editors. Global Change and Terrestrial Ecosystems. Cambridge University Press, Cambridge.
Neilson, R.P. 1995. A model for predicting continental scale vegetation distribution and water balance. Ecological Applications 5:362-385.
Neilson, R.P. and D. Marks. 1994. A global perspective of regional vegetation and hydrologic sensitivities and risks from climatic change. Journal of Vegetation Science 5:715-730.
Neilson, R.P. 1993. Vegetation redistribution: A possible biosphere source of CO2 during climatic change. Water, Air & Soil Pollution 70:659-673.
Neilson, R.P. 1993. Transient Ecotone Response to Climatic Change: Some Conceptual and Modeling Approaches. Ecological Applications 3:385-395.
Selected Other Publications:
Shriner, D., R. Street, R.P. Neilson et. al. 1998. North America. Pages
253-330 in Watson, R.T., M.C. Zinyowera, and R.H. Moss, eds., IPCC, Special
Report on Regional Climate Impacts. Contribution of the Intergovernmental Panel
on Climate Change.
Neilson, R.P., I.C. Prentice, B. Smith et. al. 1998. Annex C. Simulated Changes in Vegetation Distribution under Global Warming, Pages 439-456, in: Watson, R.T., M.C. Zinyowera, and R.H. Moss, eds., IPCC, Special Report on Regional Climate Impacts. Contribution of the Intergovernmental Panel on Climate Change.
VEMAP Members. 1995. Vegetation/Ecosystem Modeling and Analysis Project (VEMAP): Comparing Biogeography and Biogeochemistry Models in a Continental-Scale Study of Terrestrial Ecosystem Responses to Climate Change and CO2 Doubling. Global Biogeochemical Cycles 9(4):407-437.
King, G.A. and R.P. Neilson. 1992. The transient response of vegetation to climate change: A potential source of CO2 to the atmosphere. Wat., Air & Soil Poll. 64:365-383.
Collaborators:
D. Bachelet, W. Cramer, C. Daly, S. Ferguson, T. Kittel, R. Leemans, J. Lenihan,
R. Leung, J. Melillo, D. Ojima, W. Parton, C. Prentice, W. Reiners, S. Running,
D. Schimel, T. Smith, M. Wigmosta, F.I. Woodward
Students and Post-docs:
J. Lenihan, J. Borchers, C. Daly, K. Bredensteiner, M. Brugnach, S.Waichler
Graduate Advisors:
R.B. Forbes, L.H. Wullstein
CURRICULUM VITAE
Keith H. Paustian
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, CO 80523
Phone: (970) 491-1547; Fax: (970) 491-1965
email: keithp@nrel.colostate.edu
Education:
1977 - B.Sc., Forest Biology, Colorado State University, Fort Collins
1980 - M.Sc., Forest Ecology, Colorado State University, Fort Collins
1987 - Ph.D. Systems Ecology, Swedish U. Agric. Sciences, Uppsala
Professional Experience:
1996-present: Senior Research Scientist, Natural Resource Ecology Lab,
Colo. State Univ.
1993-1995: Research Scientist, NREL, Colorado State University
1991-1993: Research Asst. Prof., W.K. Kellogg Biol. Sta., Michigan State
Univ.
1989-1990: Research Assoc., W.K. Kellogg Biol. Sta., Michigan State Univ.
1987-1989: Research Sci., Dept. Ecol. and Environ. Res., Swedish U. of
Agric. Sciences
1980-1986: Research Associate, Swedish U. of Agricultural Sciences
Editorial Board member for Applied Soil Ecology.
Guest Editor on C sequestration issues of Climatic Change and Soil Tillage
Research
Working Group Member: IPCC 1995 Assessment - Greenhouse Gas Mitigation Options
in Agriculture
Co-chair for IPCC/OECD Working Group on Methodologies for Country Inventories
of Greenhouse Gases: CO2 from Soils
Lead Author - IPCC Special Report on Landuse, Landuse Change and Forestry
Steering Committee member - OSTP/USGCRP Agricultural Sector Assessment Team
Steering Committee member - IGBP/GCTE Focus 3 - Soil organic matter
Publications:
Paustian, K., E. Levine, W.M. Post and I.M. Ryzhova. 1997. The use of
models to integrate information and understanding of soil C at the regional
scale. Geoderma 79:227-260.
Paustian, K., G. Agren and E. Bosatta. 1996. Modeling litter quality effects on decomposition and soil organic matter dynamics. In: G. Cadisch and K.E. Giller (eds.) Driven by Nature: Plant Lifter Quality and Decomposition. CAB International, UK, pp. 313-336.
Paustian, K., H.P. Collins, and E.A. Paul. 1997. Management controls on soil carbon. In: E.A. Paul, K. Paustian, E.T. Elliott and C.V. Cole (eds.) Soil Organic Matter in Temperate Agroecosystems: Long-term Experiments in North America, pp. 15-49. CRC Press, Boca Raton, FL, USA.
Paustian, K., C.V. Cole, D. Sauerbeck and N. Sampson. 1998. CO, mitigation by agriculture: An overview, Climatic Change 40:135-162.
Paustian, K., E.T. Elliott, G.A. Peterson, C.V. Cole and K. Killian. 1996. Modelling climate, CO, and management impacts on soil carbon in semi-arid agroecosystems. Plant and Soil 187:351-365.
Paustian, K., O. Andren, H. Janzen, R. Lai, P. Smith, G. Tian, H. Tiessen, M. Van Noordwijk and P. Woomer. 1997. Agricultural soil as a C sink to offset CO, emissions. Soil Use and Management 13:1-15.
Six, J. E.T. Elliott, K. Paustian and J.W. Doran. 1998 Aggregation and organic matter accumulation in cultivated and native grassland soils. Soil Sci. Soc. Am. J. 62:1367-1377..
Frey, S.D., E.T. Elliott and K. Paustian. Bacterial and fungal abundance and biomass in conventional and no-tillage agroecosystems along two climatic gradients. Soil Biol. Biochem. (In press).
Six, J. E.T. Elliott and K. Paustian. Aggregate turnover and SOM dynamics in conventional and no-tillage soils. Soil Sci. Soc. Am. J. (In press).
Paustian, K., E.T. Elliott, J. Six and H.W. Hunt. Management options for reducing CO2 emissions from agricultural soils. Biogeochemistry (In press).
Collaborators:
G. Agren (Swedish Univ. of Agricultural Sci.), O. Andren (Swedish Univ. of
Agricultural Sci.), J.M. Antle (Montana State Univ.), E. Bosatta (Swedish
Univ. of Agricultural Sci.), I. Burke (Colorado State. Univ.), S. Capalbo
(Montana State Univ.), M.R. Carter (Agriculture Canada), C.V. Cole (Colorado
State. Univ.), E. Davidson (Woods Hole Research Institute), J.W. Doran (USDA/ARS),
J. Dumanski (World Bank), Duxberry (Cornell Univ.), E.T. Elliott (Colorado
State. Univ.), E. Fernandes (Cornell Univ.), R. Follett (USDA/ARS), S. Frey
(Colorado State. Univ.), P. Grace (CIMMYT), G. Guggenberger (Univ. of Bayreuth),
R. Houghton (Woods Hole Research Institute), H.W. Hunt (Colorado State. Univ.),
H. Janzen (Agriculture Canada), J. Kimble (USDA/NRCS), R. Lal (Ohio State
Univ.), A. Mosier (USDA/ARS), D. Ojima (Colorado State. Univ.), W. Parton
((Colorado State. Univ.), E.A. Paul (Michigan State Univ.), G.A. Peterson
(Colorado State. Univ.), D. Powlson (NERC-Rothamsted), G.P. Robertson (Michigan
State Univ.), N. Rosenberg (Pacific NW National Labs), N. Sampson (American
Forest), D. Sauerbeck (Univ. of Braunsweig), M. Scoles (Univ. of Wittersaand),
P. Smith (NERC-Rothamsted), G. Tian (IITA), H. Tiessen (Univ. of Saskatchewan),
M. van Noordwijk (ICRAF), P. Woomer (Univ. of Nairobi).
Advisees:
R. Conant (Colorado State. Univ.), M. Eve (Colorado State. Univ.), S. Frey
(Colorado State. Univ.), J. Six (Colorado State. Univ.), M. Sperow (Colorado
State. Univ.).
Advisors:
Goran Agren (Swedish Univ. of Agr. Sciences)
G. Philip Robertson (Michigan State Univ.).
CURRICULUM VITAE
Roger A. Pielke
Professor, Department of Atmospheric Science, Colorado State University, Fort
Collins, Colorado
B.A., Mathematics, Towson State College, 1968
M.S., Ph.D., Meteorology, Pennsylvania State University, 1969, 1973
For the last 25 years, he has concentrated on the study of terrain-induced mesoscale systems, including the development of a three-dimensional mesoscale model of the sea breeze, for which he received the NOAA Distinguished Authorship Award for 1974. Dr. Pielke has worked for NOAA's Experimental Meteorology Lab (1971-1974), The University of Virginia (1974-1981), and Colorado State University (1981-present). He is currently a Professor of Atmospheric Science at CSU. He has served as Chairman and Member of the AMS Committee on Weather Forecasting and Analysis, and was Chief Editor for the Monthly Weather Review for 5 years from 1981 to1985. In 1977, he received the AMS Leroy Meisinger Award for "fundamental contributions to mesoscale meteorology through numerical modeling of the sea breeze and interaction among the mountains, oceans, boundary layer, and the free atmosphere." Dr. Pielke received the 1984 Abell New Faculty Research and Graduate Program Award, and also received the 1987/1988 Abell Research Faculty Award. He was declared ``Researcher of 1993'' by the Colorado State University Research Foundation. He has authored a book published by Academic Press entitled Mesoscale Meteorological Modeling (1984), a book for Routledge Press entitled The Hurricane (1990), a book for Cambridge Press entitled Human Impacts on Weather and Climate (1995), and a book (with R.A. Pielke, Jr.) entitled Hurricanes: Their Nature and Impacts on Society published in 1997 by John Wiley and Sons. He was elected a Fellow of the AMS in 1982. From 1993-1996, he served as Editor-in-Chief of the US National Science Report (1991-1995) for the American Geophysical Union. Starting in January 1996, he was appointed to a three-year term as Co-Chief Editor of the Journal of Atmospheric Science.
He has published over 200 papers in peer-reviewed journals, 25 chapters in books, and co-edited 4 books.
PUBLICATIONS
Cotton, W.R. and R.A. Pielke, 1995: Human Impacts on Weather and
Climate, Cambridge University Press, New York, 288 pp.
Eastman, J.L., R.A. Pielke, and D.J. McDonald, 1998: Calibration of soil moisture for large eddy simulations over the FIFE area. J. Atmos. Sci., 55, 1131-1140.
Pielke, R.A., 1984: Mesoscale meteorological modeling. Academic Press, New York, N.Y., 612 pp.
Pielke, R.A., J.H. Rodriguez, J.L. Eastman, R.L. Walko, and R.A. Stocker, 1993: Influence of albedo variability in complex terrain on mesoscale systems. J. Climate, 6, 1798-1806.
Pielke, R.A. and P.L. Vidale, 1995: The boreal forest and the polar front. J. Geophys. Res., 100, 25755-25758.
Pielke, R.A., T.J. Lee, J.H. Copeland, J.L. Eastman, C.L. Ziegler, and C.A. Finley, 1997: Use of USGS-provided data to improve weather and climate simulations. Ecological Applications, 7, 3-21.
Pielke, R.A., R. Avissar, M. Raupach, H. Dolman, X. Zeng, and S. Denning, 1998: Interactions between the atmosphere and terrestrial ecosystems: influence on weather and climate. Global Change Biology, 4, 101-115.
Pielke, R.A. Sr., G.E. Liston, L. Lu, R.A. Pielke, Jr., and R. Avissar, 1998: Land-atmosphere hydrology -- heterogeneity and preliminary assessment of feedbacks. J. Hydrology, submitted.
Stohlgren, T.J., T.N. Chase, R.A. Pielke, T.G.F. Kittel, and J. Baron, 1998: Evidence that local land use practices influence regional climate and vegetation patterns in adjacent natural areas. Global Change Biology, in press.
Vidale, P.L., R.A. Pielke, A. Barr, L.T. Steyaert, 1997: Case study modeling of turbulent and mesoscale fluxes over the BOREAS region. J. Geophys. Res., 102, 29167-29188.
List of Collaborators
Roni Avissar, Rutgers, NJ
Jill Baron, CSU, Fort Collins, CO
Bill Cotton, CSU, Fort Collins, CO
Mike Coughenour, CSU, Fort Collins, CO
Giovanni Dalu, Institute Di Fisica Dell Atmosfera, Italy
Scott Denning, CSU, Fort Collins, CO
Han Dolman, Winand Stairing Center, The Netherlands
Filipo Giorgi, NCAR, Boulder, CO
Tim Kittel, NCAR, Boulder, CO
John Knaff, CIRA, Fort Collins, CO
Walt Lyons, FMA Research, Fort Collins, CO
Tom McKee, CSU, Fort Collins, CO
R. Nemani, Univ. of Montana, Missoula, MT
Mel Nicholls, CSU, Fort Collins, CO
Dennis Ojima, CSU, Fort Collins, CO
R.A. Pielke, Jr., NCAR, Boulder, CO
Michael Raupach, CSIRO, Canberra, Australia
William Reiners, Univ. of Wyoming, Laramie, WY
Steve Running, Univ. of Montana, Missoula, MT
Tom Stohlgren, CSU, Fort Collins, CO
Chris Taylor, Wallingford, UK
Craig Tremback, MRC, ASTeR Div., Fort Collins, CO
Marek Uliasz, CSU, Fort Collins, CO
Bob Walko, CSU, Fort Collins, CO
Conrad Ziegler, NSSL, Norman, OK
Advisers:
Hans Panofsky (M.S. degree -- Penn State, 1969), Al Blackadar (Ph.D. degree
-- Penn State, 1973).
Advisees:
R.W. Arritt, R. Artz, D.O. Blanchard, T.N. Chase, M. Coskun, J.M. Cram, J.
Cramer, J.L. Eastman, C. Finley, E. Greene, M.G. Hadfield, J.B. Knowles, T.J.
Lee, C.G. Lindsey, L. Lu, C.L. Martin, M. McCoy, M. McCumber, R.T. McNider,
J.T. McQueen, P. Mehring, A.P. Mizzi, M.D. Moran, L. Olivier, J. Papineau,
G.S. Poulos, H. Rodriguez, P. Schultz, J. Snook, J.L. Song, A.D. Tunick, P.L.
Vidale,
D.A. Wesley, X. Zejin, C.-H. Yu, and X. Zeng.
Post-Doctoral Scholars Sponsored:
Dr. Shigehira Ozono, Research Institute for Applied Mechanics, Kyushu University,
Kasuga, Japan (11/95-10/96).
Mr. Olivier Chomette, Laboratoire D'Optique Atmospherique - URA CNRS. 713,
Universit\'{e} des Sciences et Technologies de Lille, U.F.R. de Physique
- Batiment P5, 59655 Villeneuve d' Ascq Cedex, France (July 1996 - June 1997).
Ms. Sabine Issler, Geographic Institute ETH, Winterthurerstr 190, 8057 Zurich,
Switzerland (September 1996 - April 1997).
CURRICULUM VITAE
Steven W. Running
Professor, School of Forestry, University of Montana Born: April
18, 1950; Spokane, Washington
Missoula, Montana 59812
U.S. Citizen
Phone: (406) 243-6311 Fax: (406) 243-4510
Home: 1419 Khanabad Drive, Missoula, MT 59802
E-mail: swr@ntsg.umt.edu
Home Page: http://www.forestry.umt.edu/ntsg Phone: (406)
721-5096
Education:
B.S. - Botany; Oregon State University, Corvallis - 1972
M.S. - Forest Management; Oregon State University 1973
Ph.D. - Forest Ecophysiology; Colorado State University 1979
Experience:
1993: Visiting Sabbatical Scientist, Lund University, Sweden.
1988: Professor, Forest Ecology, School of Forestry, University of
Montana
1986-87: Visiting Sabbatical Scientist, CSIRO Division of Forest Research,
Canberra, Australia
1983-1988: Associate Professor, Forest Ecophysiology, School of Forestry,
Univ. of Montana, Missoula
1979-1983: Assistant Professor, Forest Ecophysiology, School of Forestry,
Univ. of Montana, Missoula
1979: Senior Research Associate, Natural Resource Ecology Laboratory,
Colorado State University
1976-1979: Research Forester, Forest and Mtn. Meteorol. Project, Rocky
Mtn. Forest and Range Experiment Station, Fort Collins, Colorado
Committee Appointments:
International Geosphere-Biosphere Program, Biospheric Aspects of the Hydrologic
Cycle, Vice-Chair - 1991-1996.
NASA Earth Observing System, Land Science Panel, Chair - 1994-1998.
National Academy of Sciences, National Research Council, Climate Research
Committee - 1996-1999.
Terrestrial Observation Panel for Climate of the World Climate Research Program,
WMO - 1995-1998.
Publications 1994-present (from 150+):
Running, S.W., C.O.Justice, V.Salomonson, D.Hall, J.Barker, Y.J.Kaufmann, A.H.Strahler,
A.R.Huete, J-P.Muller, V.Vanderbilt, Z.M.Wan, P.Teillet, D.Carneggie. (1994). Terrestrial
remote sensing science and algorithms planned for EOS/MODIS. International
Journal of Remote Sensing 15:3587-3620.
Running, S.W., T.R.Loveland, L.L.Pierce and E.R.Hunt Jr. (1995). A remote sensing based vegetation classification logic for global land cover analysis. Remote Sensing of Environment 51:39-48.
VEMAP Members. (1995). Vegetation/ecosystem modeling and analysis project : Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochemical Cycling 9(4):407-437.
Nemani, R. and S.W. Running. (1995). Satellite monitoring of global land cover changes and their impact on climate. Climate Change 31:395-413.
Baldocchi, D., Valentini, R., Running, S., Oechel, W., and Dahlman, R. (1996). Strategies for measuring and modeling carbon dioxide and water vapour fluxes over terrestrial ecosystems. Global Change Biology 2:159-168
Hunt, E.R., Jr., S.C. Piper, R. Nemani, C.D. Keeling, R.D. Otto, and S.W. Running. (1996). Global net carbon exchange and intra-annual atmospheric CO2 concentrations Predicted by an Ecosystem Process Model and Three-Dimensional Atmospheric Transport Model. Global Biogeochemical Cycles 10(3):431-456.
Thornton P.E.,S.W. Running, and M.A. White. (1997). Generating surfaces of daily meteorological variables over large regions of complex terrain. Journal of Hydrology 190:214-251.
White, M.E., P.E. Thornton, and S.W. Running. (1997). A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global Biogeochemical Cycles 11(2):217-234.
Running, S.W., G.J. Collatz, J. Washburne, and S. Sorooshian. (1997). Chapter 7. Land Ecosystems and Hydrology. In: NASA EOS Science Implementation Plan.
Waring, R., and S.W. Running. (1998) Forest Ecosystems: Analysis at Multiple Scales. Academic Press.
Collaborators with Dr. Steve W. Running (January 15, 1999)
Baldocchi, D. - NOAA, Oak Ridge, TN; Chase, T.N.; Churkina, G. - University
of Bayreuth, Bayreuth, Germany; Cienciala, E.; Collatz, G.J.; Coughlan, J.C.
- NASA/Ames Research Center Defries, R.; Fagre, D.B. - Science Center, Glacier
National Park; Glassy, J.M. - University of Montana, Missoula, MT; Gower, S.T.
- University of Wisconsin, Madison, WI; Hall, D.K.; Hasenauer, H.; Hibbard,
K. - University of New Hampshire, Durham, NH; Huete, A.R. - University of Arizona,
Tucson, AZ; Hunt Jr., E.R. - University of Wyoming, Laramie, WY; Justice, C.O
- NASA/Goddard Space Flight Center; Keane, R.E.; Keeling - D.SCRIPPS Inst.
Of Oceanography, La Jolla, CA; Kimball, J. - University of Montana, Missoula,
MT; Kittel, T.G.; Korol, R.L. - Forest Science Lab, Missoula, MT; Kremer, R.G.;
Loveland, T.R.; McGuire, A.D.; Melillo, J.M.; Milner, K.S. - University of
Montana, Missoula, MT; Myneni, R.B.; Neilson, R.P. - USDA Forest Service, Corvallis,
OR; Nemani, R.R. - University of Montana, Missoula, MT; Ojima, D.S. - Colorado
State University, Ft. Collins, CO; Otto, R.D.; Parton, W.J.; Pielke, R.A. -
Colorado State University, Ft. Collins, CO; Pierce, L.L. - California State
University Monterey Bay; Piper, S.C. - SCRIPPS Inst. Of Oceanography, La Jolla,
CA; Privette, J.L.; Rosenbloom, N.A.; Ryan K.C. - Intermountain Fire Sciences
Lab, Missoula, MT; Salomonson, V.V.; Schadauer, K.; Schimel, D.S. - UCAR/NCAR,
Boulder, CO; Schloss, A.L; Sorooshian, S. - University of Arizona, Tucson,
AZ; Strahler, W.; Thornton, P.E. - University of Montana, Missoula, MT; Townshend,
J.R.G.; Valentini, R. - University of Tuscia, Italy; Vermote, E.; Waring, R.H.
- Oregon State University, Corvallis, OR; Washburne, J.; White, J.D. - Baylor
University, Waco, TX; White, M.A. - University of Montana, Missoula, MT; Zheng,
D.
Dr. Steve W. Running's Graduate School Advisors:
M.S. - Oregon State University, 1973 -- Dr. Richard Waring
Ph.D. - Colorado State University, 1979 -- Dr. C.P.P. Reid
Dr. Steve W. Running's Graduate Students for last 5 years:
Churkina, G. - University of Bayreuth, Bayreuth, Germany; Coughlan, J.C. -
NASA/Ames Research Center; Glassy, J.M. - University of Montana, Missoula,
MT; Hibbard, K. - University of New Hampshire, Durham, NH; Hunt Jr., E.R. -
University of Wyoming, Laramie, WY; Keane, R.E.; Kimball, J. - University of
Montana, Missoula, MT; Korol, R.L. - Forest Science Lab, Missoula, MT; Kremer,
R.G.; Nemani, R.R. - University of Montana, Missoula, MT; Pielke, R.A. - Colorado
State University, Ft. Collins, CO; Ryan K.C. - Intermountain Fire Sciences
Lab, Missoula, MT; Thornton, P.E. - University of Montana, Missoula, MT; Thornton,
P.E. - University of Montana, Missoula, MT; White, J.D. - Baylor University,
Waco, TX; White, M.A. - University of Montana, Missoula, MT; Zheng, D.
CURRICULUM VITAE
TOMISLAVA VUKICEVIC
Born: 4 September 1959
Yugoslavia
Education:
B.S. - 1983 - University of Beograd, Yugoslavia (Meteorology)
M.S. - 1986 - University of Utah (Meteorology)
Ph.D. - 1989 - University of Utah (Meteorology)
Dissertation: The Influence of Lateral Boundary Conditions, Fixed Surface Forcings, and Synoptic Situations Upon Predictability Estimates Using LImited Area Numerical Models.Professional Experience:
Advisor: Dr. Jan Paegle
1984-1989: Graduate Teaching and/or Research assistant, Department of Meteorology, University of Utah, Salt Lake City, Utah.
1989-1991: Postdoctoral Fellow, Advanced Study Program, National Center for Atmospheric Research, Boulder, Colorado.
1991-1993: Visiting Scientist, Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado.
1993-1997: Scientist I, Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado.
1997-1998: Scientist II, Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado.
1998-date: Research Scientist, Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado.
Publications:
Errico, E.M., and T. Vukicevic, 1992: Sensitivity analysis using an adjoint
of the PSU/NCAR mesoscale model. Mon. Wea. Rev., 120, 1644-1660.
Vukicevic, T., 1993: Possibility of skill forecast based on the finite-time dominant linear solutions for a primitive equation regional model. J. Atmos. Sci., 50, 1777-1791.
Vukicevic, T., and R.M. Errico, 1993: Linearization and adjoint of parameterized diabatic processes. Tellus, 45 A, 493-510.
Errico, R.M., T. Vukicevic and K. Raeder, 1993: Examination of the accuracy of a tangent linear model. Tellus, 45 A, 462-477.
Errico, R.M., T. Vukicevic and K. Raeder, 1993: Comparision of initial and lateral boundary condition sensitivity for a limited-area model. Tellus, 45 A, 539-557.
Courtier, P., J. Derber, R.M. Errico, J.F. Louis, and T. Vukicevic, 1993: Important literature on the use of adjoint, variational methods and the Kalman filter in meteorology. Tellus, 45 A, 342-357.
Ehrendorfer, M., R.M. Errico, and T. Vukicevic, 1994: Optimal perturbations for a primitive-equation regional model. Preprints: International Symposium on the Life Cycles of Extratropical Cyclones, Bergen, Norway.
Errico, R.M., T. Vukicevic, and K. Raeder, 1994: Description of the NCAR Mesoscale Adjoint Modeling System Version 1 (MAMS1). NCAR Technical Note-410+IA. [Available from the authors: National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000, USA.]
Vukicevic, T., and K. Raeder, 1995: Usa of an adjoint model for finding triggers for Alpine lee cyclogenesis. Mon. Wea. Rev., 123, 800-816.
Vukicevic, T., and J.W. Bao, 1995: 4DVAR using an adjoint model with moist physics: Possibilities and limitations. Preprints: Second International Symposium on Assimilation of Observations in Meteorology and Oceanography. Tokyo, Japan, 13-17 March, 1995. WMO/TD-No. 651.
Vukicevic, T., and J.W. Bao, 1996. Study of extratropical cyclogenesis as initial value problem using optimal modes. Preprints: 11th Conference on Numerical Weather Prediciton, Norfolk, Virginia.
Vukicevic, T., and J.W. Bao. 1998. The efect of linearization errors on 4DVAR data assimilation. Mon. Wea. Rev., 126.
Vukicevic, T. 1998. Optimal initial perturbations for two cases of extratropical cyclogenesis. Tellus 50A:143-166.
Funding history:
1993-1998 NASA's Earth Observing System
Interdisciplinary Science Investigation entitled:
"NCAR Project to Interface
Climate
Modeling on Global and Regional Scales with EOS Observations." PI; Robert
Dickinson, University
of
Arizona.
1998-date CIRA-Geoscience Project