Grantee Research Project Results
2000 Progress Report: Regional Analysis of Net Ecosystem Productivity of Pacific Northwest Forests: Scaling Methods, Validation and Results Across Major Forest Types and Age Classes
EPA Grant Number: R828309Title: Regional Analysis of Net Ecosystem Productivity of Pacific Northwest Forests: Scaling Methods, Validation and Results Across Major Forest Types and Age Classes
Investigators: Law, B. E. , Harmon, M. E. , Daly, Christopher , Turner, D. , Unsworth, M. , Cohen, W.
Institution: Oregon State University
EPA Project Officer: Packard, Benjamin H
Project Period: July 1, 2000 through June 30, 2003 (Extended to June 30, 2004)
Project Period Covered by this Report: July 1, 2000 through June 30, 2001
Project Amount: $1,848,927
RFA: Regional Scale Analysis and Assessment (1999) RFA Text | Recipients Lists
Research Category: Aquatic Ecosystems , Ecological Indicators/Assessment/Restoration
Objective:
Our objectives are to: (1) develop and test a regional scale approach that combines modeling, data from remote sensing, sample surveys and intensive research sites to better estimate variation in the carbon balance of forest ecosystems in the Pacific Northwest; and (2) apply our strategy to investigate how processes controlling variation in net ecosystem productivity are influenced by forest development, disturbances, and contrasting climatic conditions.Progress Summary:
Field sampling: We conducted field sampling on 60 extensive plots (LAI, canopy and soil chemistry, wood increment and stem dimensions, litter quality and quantity?) and 36 chronosequence plots across Oregon and Washington. For the extensive plots, we developed an approach to defining plot locations that are representative of the variation in forest types and age classes across the climate space in the region, in collaboration with EPA statistician, T. Olsen. Data were collected across this spectrum of conditions using consistent methodologies defined in our field protocols manual, and consistent personnel. The data are to be used for analysis of carbon storage and productivity across age classes and climatic gradients, and to develop and test remote sensing algorithms (forest type, age, leaf area index), develop parameterization schemes for the Biome-BGC and LANDCARB models (e.g., foliar nitrogen, soil chemistry, coarse-woody debris, live biomass), and test model estimates of biomass and production. We established chronosequence plots in three forest types along a climatic gradient, where we are making periodic measurements of processes in addition to the variables measured on the extensive plots. The chronosequence measurements will be used to develop carbon budgets, produce biometric estimates of NEP, and estimate carbon allocation patterns by age class and forest type. The respiration, NPP, and biomass data also will be used to evaluate model predictions prior to regional applications of the models.Periodically, we measured soil surface CO2 fluxes (soil respiration) at the chronosequence plots in the three forest types and climatic conditions. Soil respiration is the largest source of CO2 returned to the atmosphere from terrestrial ecosystems. We found that the respiration rates were highest in the Cascade Mountains (H.J. Andrews LTER site, Douglas-fir), lowest on the dry east side of the Cascades, and intermediate at the Coastal Sitka spruce forests, which experience a mild maritime climate throughout the year. We also found that microbes are responsible for the majority of soil respired CO2 at the coastal sites (~65 percent), whereas roots and microbes contributed about the same amount at the other two sites. Turnover rates and soil nitrogen are higher in the coastal Sitka spruce, and because the climate is milder and growing conditions are good, we expect that less carbon is allocated to roots at the coastal sites. This could explain why root respiration was relatively low there. We expected that across sites, the young regenerating forests were likely to have the largest soil respiration rates among age classes of forests, but that was only true at H.J. Andrews. The soil respiration data will be used to determine carbon allocation patterns and how they vary with climatic zone and forest development, and this information will be used to test Biome-BGC model assumptions.
We also acquired FIA, FHM, and CVS data, and assembled GIS data layers for Biome-BGC modeling, and we began inventory estimates of NPP (10-year average from biomass estimates at two points in time). These plots are more numerous, but we expect a lower level of precision in the NPP estimates because of the limited number of measurements made in these programs (e.g., tree height).
Remote Sensing. The role of remote sensing in this project is to develop methods for estimating stand age, and leaf area index (LAI), and to provide spatial estimates of forest type, age, and leaf area index for the spatially explicit modeling of productivity and NEP. Major progress on the two main remote sensing tasks (remote sensing of LAI and stand age) was made in the past year. Preliminary analyses indicate that there is a strong, linear, relationship between a number of satellite vegetation indices and LAI measured using the LAI-2000 optical instrument during the summer of 2001. An LAI coverage suitable for the modeling component of the study will be available by the end of 2001. We have completed updating an existing map of the date of forest disturbance in western Oregon between 1972 and 1995 to reflect disturbance between 1995 and 2000. We have begun to extend the same disturbance mapping to the east side of the Cascade Range. Preliminary accuracies for the mapping of disturbance exceed 90 percent. Mapping of stand ages before 1972 for western Oregon and Washington will be updated by the end of 2001, and for the eastside of the Cascades by spring 2002. We also have developed a technique to predict net primary productivity (NPP) using lidar remote sensing and estimates of stand age from our change detection analysis. Although our results are preliminary, the use of such a technique has the potential to allow rapid verification of some aspects of the productivity modeling aspects of this project, and is being pursued for this purpose.
Figure 1. A section of the disturbance map of Oregon and Washington indicates the importance of working at regional and landscape scales. Patterns of disturbance are dramatically different in the H.J. Andrews Experimental Forest, indicated by the black boundary, and in adjacent areas. The H.J. Andrews LTER site is the location of one of our chronosequence sites (4 age classes, 3 reps, totaling 12 plots), which likely reflect characteristics of the same classes outside the LTER site. Our regional modeling and mapping will take into account disturbance effects on productivity and NEP.
Modeling. The modeling strategy is to use carbon pools estimated from the LANDCARB model to "nudge" the Biome-BGC process model that will be used to estimate net primary productivity and net ecosystem productivity (NPP - heterotrophic respiration, or net carbon uptake by ecosystems).
(1) Climate Modeling (PRISM) - The PRISM model was used to produce a 30-year mean "spin-up" climate data set at H.J. Andrews to drive Biome-BGC, which allows the model to reach an equilibrium. PRISM is being used to produce spatially distributed daily weather data for 1999 and 2000, which will be used in Biome-BGC to model NPP and NEP for those years. The primary activity has been to work towards producing 1 km spatially derived climate data from 4 km resolution data (stations used in study region are shown in Figure 2). Solar radiation is an important driver variable for Biome-BGC, and climate models often have difficulty producing reasonable data in complex terrain. C. Daly is developing an approach to modeling incident solar radiation in the PRISM model that incorporates topographic influences on radiation.
(2) Modeling of live and dead carbon pools (LANDCARB) - We evaluated
which model was most appropriate for this application, STANDCARB or REGIONCARB.
The decision was that we needed somewhat of a hybrid of the two models for the
carbon pools at the landscape scale (LANDCARB). We initiated development of this
model, and plan to have it completed by the end of year 2.
Figure 2. Locations of the weather stations used in PRISM. The bold red rectangle shows the modeling region.
(3) Biogeochemistry model of carbon, nitrogen and water cycling (Biome-BGC) - A critical tool for preparing spatial maps of NEP in this project is the Biome-BGC model. In the first year of the project, we accomplished the following steps:
- Acquired the model code and ran it locally.
- Developed a graphical user interface (in IDL software) to readily analyze all model inputs, internal variables and outputs over annual model runs and multiyear (successional timeframe) model runs (e.g., Figure 3).
- Developed computer code (in C++) that runs the model in a spatially distributed mode (e.g., Figure 4).
- Developed computer code that allows us to bring modeled leaf area index (LAI) into agreement with the LAI prescribed by our remote sensing analysis. We are generally able to achieve close agreement.
- Acquired an 18-year time series climate data set at 1 km resolution over the study area for use in model "spin-ups" (i.e., 1,000-year model runs to bring the nonliving carbon pools into equilibrium with the local climate).
- Completed prototype spatial model runs (10 x 10 km) at the Wind River Canopy Crane site, the Metolius site, and the H.J. Andrews Long-Term Ecological Research site.
- For the Wind River and Metolius sites, acquired 1 or more years of meteorological and carbon flux data and generated initial model runs for comparison of simulated and observed gross primary production (GPP) and net ecosystem production (NEP).
- For H.J. Andrews prototype study, compared simulated bole production with
that indicated by inventory data from a relevant set of USFS CVS inventory
plots.
Figure 3. Simulated NEP over succession for Douglas-fir hemlock at H.J. Andrews.
Figure 4. NEP in the H.J. Andrews LTER study area for a moderate climate year.
Future Activities:
In the next year, we plan to analyze the field data and investigate variation in productivity, carbon allocation, and carbon storage with successional stages and climatic conditions. We plan to complete the remote sensing mapping of forest types, age classes, and leaf area index, and evaluate remote sensing estimates with field data. The spatially derived climate data set from PRISM for 1998 and 2000 will be completed for Biome-BGC model runs. We plan to complete development of the LANDCARB model for regional estimates of live and dead carbon pools necessary for Biome-BGC initialization. We intend to do spatial model runs over the complete East-West transect associated with this study using the new land cover and LAI data layers derived from remote sensing. We will continue to acquire flux tower GPP and NEP estimates as they become available and compare them to our model simulations. As site-specific estimates of the bole carbon stocks and production become available from the inventory data and our plot data, we will make comparisons with simulated values derived from the Biome-BGC and LANDCARB models.Journal Articles on this Report : 12 Displayed | Download in RIS Format
Other project views: | All 38 publications | 25 publications in selected types | All 24 journal articles |
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Campbell JL, Sun OJ, Law BE. Supply-side controls on soil respiration among Oregon forests. Global Change Biology 2004;10(11):1857-1869. |
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Cohen WB, Maiersperger TK, Spies TA, Oetter DR. Modelling forest cover attributes as continuous variables in a regional context with Thematic Mapper data. International Journal of Remote Sensing 2001;22(12):2279-2310. |
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Cohen WB, Spies TA, Alig RJ, Oetter DR, Maiersperger TK, Fiorella M. Characterizing 23 years (1972-95) of stand replacement disturbance in western Oregon forests with Landsat imagery. Ecosystems 2002;5(2):122-137. |
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Davidson EA, Savage K, Bolstad P, Clark DA, Curtis PS, Ellsworth DS, Hanson PJ, Law BE, Luo Y, Pregitzer KS, Randolph JC, Zak D. Belowground carbon allocation in forests estimated from litterfall and IRGA-based soil respiration measurements. Agricultural and Forest Meteorology 2002;113(1-4):39-51. |
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Harding DJ, Lefsky MA, Parker GG, Blair JB. Laser altimeter canopy height profiles--methods and validation for closed-canopy, broadleaf forests. Remote Sensing of Environment 2001;76(3):283-297. |
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Law BE, Van Tuyl S, Cescatti A, Baldocchi DD. Estimation of leaf area index in open-canopy Ponderosa pine forests at different successional stages and management regimes in Oregon. Agricultural and Forest Meteorology 2001;108(1):1-14. |
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Law BE, Sun OJ, Campbell J, Van Tuyl S, Thornton PE. Changes in carbon storage and fluxes in a chronosequence of Ponderosa pine. Global Change Biology 2003;9(4):510-524. |
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Law BE, Turner D, Campbell J, Sun OJ, Van Tuyl S, Ritts WD, Cohen WB. Disturbance and climate effects on carbon stocks and fluxes across Western Oregon USA. Global Change Biology 2004;10(9):1429-1444. |
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Lefsky MA, Cohen WB, Spies TA. An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon. Canadian Journal of Forest Research 2001;31(1):78-87. |
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Lefsky MA, Cohen WB, Parker GG, Harding DJ. Lidar Remote Sensing for Ecosystem Studies: Lidar, an emerging remote sensing technology that directly measures the three-dimensional distribution of plant canopies, can accurately estimate vegetation structural attributes and should be of particular interest to forest, landscape, and global ecologists. Bioscience 2002;52(1):19-30. |
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Parker GG, Lefsky MA, Harding DJ. Light transmittance in forest canopies determined from airborne laser altimetry and in-canopy quantum measurements. Remote Sensing of Environment 2001;76(3):298-309. |
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Sun OJ, Campbell J, Law BE, Wolf V. Dynamics of carbon stocks in soils and detritus across chronosequences of different forest types in the Pacific Northwest, USA. Global Change Biology 2004;10(9):1470-1481. |
R828309 (2000) R828309 (2001) R828309 (2002) R828309 (Final) |
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Supplemental Keywords:
atmosphere, land, soil, global climate, ecosystem, regionalization, scaling, terrestrial, integrated assessment, ecology, modeling, monitoring, analytical, surveys, measurement methods, climate models, satellite, landsat, remote sensing, Pacific Northwest., RFA, Scientific Discipline, Air, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, Ecology, Ecosystem/Assessment/Indicators, Ecosystem Protection, Environmental Chemistry, climate change, State, Ecological Effects - Environmental Exposure & Risk, Forestry, Regional/Scaling, Pacific Northwest, anthropogenic stresses, ecological effects, ecological exposure, carbon allocation, semi-arid environments, ecosystem assessment, survey data, Oregon, forest ecosystems, natural stressors, forest inventory and analysis, climate, Washington (WA), ecosystem indicators, regional scale impacts, forests, forest resources, ecosystem stress, remote sensing imagery, ecological response, validation, carbon stress index, scaling methodsRelevant Websites:
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.