Sensitivity of boreal forest regional water flux and net primary production simulations to sub‐grid‐scale land cover complexity

Abstract

Abstract. We use a general ecosystem process model (BIOME-BGC) coupled with remote sensing information to evaluate the sensitivity of boreal forest regional evapotranspiration (ET) and net primary production (NPP) to land cover spatial scale. Simulations were conducted over a 3 year period (1994)(1995)(1996) d-•). Factors responsible for differences in scaling behavior between ET and NPPincluded compensating errors for ET calculations and boreal forest spatial and temporal NPP complexity. Careful consideration of landscape spatial and temporal heterogeneity is necessary to identify and mitigate potential error sources when using plot scale information to understand regional scale patterns. Remote sensing data integrated within an ecological process model framework provides an efficient mechanism to evaluate scaling behavior, interpret patterns in coarse resolution data, and identify appropriate scales of operation for various processes. IntroductionThe boreal forest has received increasing attention from the scientific community in recent years because of its importance as a major reservoir of the world's carbon and mounting evi-

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

“…Less than 20% of the days at either site required filling in missing data with measurements from elsewhere. The effectiveness of the model itself has been documented to some degree with regard to NPP in boreal (Kimball et al, 2000(Kimball et al, , 1999(Kimball et al, , 1997 and temperate (Running, 1994) forests. The used of binned GPP data at the tower makes it difficult to closely evaluate the effectiveness of modeled GPP responses to day-to-day variation in meteorology but the model output is clearly tracking most of the oscillations during the growing season.…”

“…The process model employed for scaling GPP was the Biome-BGC model (Kimball, Keyser, Running, & Saatchi, 2000;Kimball, Running, & Saatchi, 1999;Kimball, Thornton, White, & Running, 1997;Running, 1994;Running & Hunt, 1993). A version similar to that used in this study has been applied and tested in temperate (Coops, Waring, Brown, & Running, 2001;Running, 1994) and boreal (Kimball et al, 1997(Kimball et al, , 1999 forests.…”

“…A version similar to that used in this study has been applied and tested in temperate (Coops, Waring, Brown, & Running, 2001;Running, 1994) and boreal (Kimball et al, 1997(Kimball et al, , 1999 forests. The most recent published version of Biome-BGC (Thornton et al, 2002) was not used because it does not operate in a prescribed LAI mode, as was required for this application.…”

“…Parameterization of the ecophysiological and allometric variables for each cover type, or vegetation layer within a cover type, was based on the literature review of White, and on earlier applications of Biome-BGC and similar process models in these biomes (Frolking et al, 1996;Kimball et al, 1999Kimball et al, , 1997Running, 1994). Biomass carbon pools were determined allometrically by reference to the LAI (see below).…”

Subpixel canopy cover estimation of coniferous forests in Oregon using SWIR imaging spectrometry

“…However, unresolved heterogeneity in vegetation properties in these ecosystems can be significant; Kimball et al [1999], for instance, found that subpixel-scale land cover complexity in boreal forests could lead to annual net primary production (NPP) errors of more than 14% using an ecosystem process model. In another study, Bonan et al [1993] showed that landscape heterogeneity in coniferous forests had a highly nonlinear effect on sensible heat and evapotranspiration calculations, with errors as high as 46% and 15%, respectively.…”