Net primary production and canopy nitrogen in a temperate forest landscape: An analysis using imaging spectroscopy, modeling and field data

Understanding spatial patterns of net primary production (NPP) is central to the study of terrestrial ecosystems, but efforts are frequently hampered by a lack of spatial information regarding factors such as nitrogen availability and site history. Here, we examined the degree to which canopy nitrogen can serve as an indicator of patterns of NPP at the Bartlett Experimental Forest in New Hampshire by linking canopy nitrogen estimates from two high spectral resolution remote sensing instruments with field measurements and an ecosystem model. Predicted NPP across the study area ranged from less than 700 g m(-2) year(-1) to greater than 1300 g m(-1) year(-1) with a mean of 951 g m(-2) year(-1). Spatial patterns corresponded with elevation, species composition and historical forest management, all of which were reflected in patterns of canopy nitrogen. The relationship between production and elevation was nonlinear, with an increase from low- to mid-elevation deciduous stands, followed by a decline in upper-elevation areas dominated by evergreens. This pattern was also evident in field measurements and mirrored an elevational trend in foliar N concentrations. The increase in production from low-to mid-elevation deciduous stands runs counter to the generally accepted pattern for the northeastern U.S. region, and suggests an importance of moisture limitations in lower-elevation forests. Field measurements of foliar N, wood production and leaf litterfall were also used to evaluate sources of error in model estimates and to determine how predictions are affected by different methods of acquiring foliar N input data. The accuracy of predictions generated from remotely sensed foliar N approached that of predictions driven by field-measured foliar N. Predictions based on the more common approach of using aggregated foliar N for individual cover types showed reasonable agreement in terms of the overall mean, but were in poor agreement on a plot-by-plot basis. Collectively, these results suggest that variation in foliar N exerts an important control on landscape-level spatial patterns and can serve as an integrator of other underlying factors that influence forest growth rates.