Regional Analysis of Net Ecosystem Productivity of Pacific Northwest Forests

Summary

Net ecosystem productivity (NEP) is a critical characteristic of terrestrial ecosystem response to environment. Processes controlling NEP operate on a variety of temporal and spatial scales and are influenced by physiology, allocation, forest development, climate and disturbance. We are simulating NPP and NEP in Oregon and Washington using a combination of remote sensing, site data, and process models. Model outputs are being tested using detailed ecosystem studies at intensive sites, more basic ecological measurements at other existing intensive sites, and survey data from Forest Health Monitoring (FHM), Forest Inventory and Analysis (FIA) plots, and Current Vegetation Survey (CVS) plots. In spatially explicit applications, we are predicting and evaluating forest productivity for an east-west longitudinal swath along a steep climatic gradient through central Oregon from the coast to the semi-arid east side of the Cascade Mountains, and a north-south latitudinal swath from the southern Oregon border to southern Washington. These swaths encompass:

• Six Oregon Transect Ecosystem Research (OTTER) project sites across central OR.
• Two tower flux sites in young and old ponderosa pine (green stars at Metolius).
• Two tower flux sites in young and old Douglas-fir/hemlock in WA (green star at Wind River).
• Long-term vegetation plots at HJ Andrews LTER.
• Cascade Head Experimental Forest.
• FHM, FIA, CVS survey data for the PNW region (not shown).
• 36 intensive field sites (at Cascade Head, HJ Andrews, and Metolius).
• 60 extensive field sites (red triangles).
  

With BIOME-BGC, a physiologically-based process model, we are generating current NEP, NPP, and "carbon stress index" surfaces for the regions for a mean climate year, 1999, and 2000. We will use STANDCARB, an ecosystem process model, to estimate current carbon pools by accounting for long-term trends in NEP. BIOME-BGC will be initialized using remote sensing (Thematic Mapper) estimates of forest cover type, age class and LAI and soil survey data (FHM, STATSGO). The model is driven by spatially distributed climate data based on interpolations of weather station data by the PRISM and DAYMET models. Remotely sensed variables are validated with data from intensive sites, FHM, FIA, CVS, and new measurements in underrepresented forests. Short-term predictions (monthly, annual) of NEP are validated against tower flux data. Annual predictions of aboveground NPP and its components are validated with intensive site measurements of stemwood and litter production. Predictions of carbon stores are validated with FHM, FIA, and CVS data. We are evaluating sensitivity of NEP to forest type, developmental stage, disturbance, and interannual variability