For the New England/New York regional GIS, a 30 arc-second (approximately 1 km.) digital elevation model (DEM, Figure 1) was obtained from the USGS, and a 1 km. land use/land cover (LULC) map (Figure 2) was derived from AVHRR satellite data that identifies current vegetation as hardwood, spruce-fir, pine and mixed forest types (Lathrop and Bognar, Rutgers University). In the absence of a successfully-validated soil WHC coverage (Lathrop et al. 1994), we have used a regional mean value of 12 cm. Mean monthly climate values are determined as functions of latitude, longitude and elevation, using a statistical climate model developed for the region in combination with the DEM (e.g. temperature Figure 3, precipitation Figure 4; Ollinger et al. 1995). Existing data on wet deposition and atmospheric concentrations of dry deposition components were used to derive regional patterns in deposition of all major ions (e.g. nitrogen Figure 5, sulfur Figure 6; Ollinger et al. 1993, 1995). In concert with the development of the regional GIS we began to work on a new forest ecosystem model which would summarize accepted physiological controls on water, C and N dynamics in as simple a structure as possible, requiring only those inputs which could be defined within a regional GIS. The result of this effort to date is PnET, a nested series of lumped-parameter models of carbon, nitrogen and water fluxes in temperate and boreal forest ecosystems (Figure 7). The different versions of PnET are modular and build out from simplest to most complex. Algorithms such as photosynthesis which are common to all versions are identical between versions. Increasing complexity occurs by layering additional algorithms, representing additional processes, over the core processes in simpler or included versions.

PnET-Day uses foliar mass, specific leaf weight, foliar N concentration, temperature and radiation flux to predict daily gross and net photosynthesis of whole forest canopies, and has been validated against daily summaries of eddy correlation carbon balance measurements from the Harvard Forest (Aber et al. 1996). PnET-II adds carbon allocation and respiration terms, as well as a full water balance to predict NPP, transpiration and runoff. An empirical soil respiration terms allows prediction of total ecosystem carbon balance under ambient conditions. This version has been validated against annual NPP and monthly water yield data from the Harvard Forest and Hubbard Brook ecosystems and is used to predict the combined effects of climate change and increased atmospheric CO2 on these processes (Aber et al. 1995). An earlier version (Aber and Federer 1992) was also validated against data from 10 additional forest types across North America, and a recent modification has extended the model to predict effects of tropospheric ozone concentrations (Ollinger et al. 1997).

PnET-CN adds compartments for woody biomass and soil organic matter, as well as algorithms for biomass turnover and litter and soil decomposition to allow calculation of complete carbon and nitrogen cycles. This version maintains the predictions for NPP and water balance used for validation in PnET-II, and also compares well with field data in predicting total annual, mean seasonal, and actual time series rates of nitrate loss in streams (Aber et al. 1997a, 1997b). An additional version of the model (PnET-BGC) is under development. This uses multiple element limitations on NPP and element concentrations in all pools to calculate cycling rates for all ../elements. This version has been combined with the soil chemistry model CHESS (Santore and Driscoll, Syracuse University) and used to predict stream and soil chemistry (Postek et al. 1995). Both the PnET-CN and PnET/CHESS versions represent significant collaborative efforts with Dr. Charles Driscoll and other cooperators from the Hubbard Brook LTER site.