Estimating regional forest productivity and water yield using an ecosystem model linked to a GIS

We used the PnET-II model of forest carbon and water balances to estimate regional forest productivity and runoff for the northeastern United States. The model was run at 30 arc sec resolution (approximately 1 km) in conjunction with a Geographic Information System that contained monthly climate data and a satellite-derived land cover map. Predicted net primary production (NPP) ranged from 700 to 1450 g m² yr¹ with a regional mean of 1084 g m² yr¹. Validation at a number of locations within the region showed close agreement between predicted and observed values. Disagreement at two sites was proportional to differences between measured foliar N concentrations and values used in the model. Predicted runoff ranged from 24 to 150 cm yr¹with a regional mean of 63 cm yr¹. Predictions agreed well with observed values from U.S. Geologic Survey watersheds across the region although there was a slight bias towards overprediction at high elevations and underprediction at lower elevations.Spatial patterns in NPP followed patterns of precipitation and growing degree days, depending on the degree of predicted water versus energy limitation within each forest type. Randomized sensitivity analyses indicated that NPP within hardwood and pine forests was limited by variables controlling water availability (precipitation and soil water holding capacity) to a greater extent than foliar nitrogen, suggesting greater limitations by water than nitrogen for these forest types. In contrast, spruce-fir NPP was not sensitive to water availability and was highly sensitivity to foliar N, indicating greater limitation by available nitrogen. Although more work is needed to fully understand the relative importance of water versus nitrogen limitation in northeastern forests, these results suggests that spatial patterns of NPP for hardwoods and pines can be largely captured using currently available data sets, while substantial uncertainties exist for spruce-fir.     

Carbon pools and fluxes in small temperate forest landscapes: Variability and implications for sampling design

Assessing forest carbon storage and cycling over large areas is a growing challenge that is complicated by the inherent heterogeneity of forest systems. Field measurements must be conducted and analyzed appropriately to generate precise estimates at scales large enough for mapping or comparison with remote sensing data. In this study we examined spatial variability in three small temperate forest landscapes. Our objectives were (1) to quantify the magnitude and scale of variability in stand structure, carbon pools and carbon fluxes and (2) to assess how this variability influences both optimal sampling strategy and required sampling intensity. Stand structure was consistently less variable than carbon pools or fluxes, suggesting that measuring carbon dynamics may require more intense sampling than traditional forestry inventories. Likewise, the magnitude of variability differed substantially among response variables, implying that sampling efficiency can be enhanced by adopting a flexible sampling strategy that is optimized for each carbon pool. Our results indicate that plots dispersed across the study area are generally more effective than clustered plots for characterizing carbon dynamics.