Effects of land use and fine-scale environmental heterogeneity on net ecosystem production over a temperate coniferous forest landscape

In temperate coniferous forests, spatial variation in net ecosystem production (NEP) is often associated with variation in stand age and heterogeneity in environmental factors such as soil depth. However, coarse spatial resolution analyses used to evaluate the terrestrial contribution to global NEP do not generally incorporate these effects. In this study, a fine-scale (25 m grid) analysis of NEP over a 164-km² area of productive coniferous forests in the Pacific Northwest region of the United States was made to evaluate the effects of including fine scale information in landscape-scale NEP assessments. The Enhanced Thematic Mapper (ETM×) sensor resolved five cover classes in the study area and further differentiated between young, mature and old-growth conifer stands. ETM× was also used to map current leaf area index (LAI) based on an empirical relationship of observed LAI to spectral vegetation indices. A daily time step climatology, based on 18 years of meteorological observations, was distributed (1 km resolution) over the mountainous terrain of the study area using the DAYMET model. Estimates of carbon pools and flux associated with soil, litter, coarse woody debris and live trees were then generated by running a carbon cycle model (Biome-BGC) to a state that reflected the current successional status and LAI of each grid cell, as indicated by the remote sensing observations. Estimated annual NEP for 1997 over the complete study area averaged 230 g C m⁻², with most of the area acting as a carbon sink. The area-wide NEP is strongly positive because of reduced harvesting in the last decade and the recovery of areas harvested between 1940 and 1990. The average value was greater than would be indicated if the entire area was assumed to be a mature conifer stand, as in a coarse-scale analysis. The mean NEP varied interannually by over a factor of two. This variation was 38% less than the interannual variation for a single point. The integration of process models with ground surface information provided by remote sensing provides a framework for investigating mechanisms regulating NEP and evaluating coarse resolution globally applied NEP scaling efforts.