PnET-BGC is a deterministic dynamic ecosystem model that includes physiological and biogeochemical processes and uses generalized empirical relationships among water, nitrogen and carbon. It was developed by linking a forest-soil-water model PnET-CN [Aber et al., 1997], with a biogeochemical cycling sub-model BGC [Gbondo-Tugbawa et al., 2001]. Through this coupling, PnET-BGC accounts for both water and N limitations on forest productivity. A strength of this model is its ability to simultaneously simulate fluxes of energy, water and major elements (Ca2+, Mg2+, K+, Na+, C, N, P, S, Si, Al3+, Cl-, and F-) in forest ecosystems. The model considers major ecosystem processes, including atmospheric deposition, CO2 effects on vegetation, canopy interactions with precipitation and atmospheric deposition, root uptake, litterfall, soil organic matter dynamics, nitrification, mineral weathering, chemical reactions involving gas, solid and solution phases, and surface water processes [Gbondo-Tugbawa et al., 2001]. PnET-BGC has been used to assess the effects of climate change on hydrology [Campbell et al., 2011] and biogeochemistry [Pourmokhtarian et al., 2012] at Hubbard Brook, as well as atmospheric deposition and land disturbance on soil and surface waters in northern forest ecosystems at local and regional scales [Chen and Driscoll, 2004; Chen et al., 2004; Chen and Driscoll, 2005; Zhou et al., 2015]. One limitation of the PnET-BGC model is the assumption of a homogeneous distribution of vegetation at the watershed scale and constant forest composition during the simulation (i.e., no changes in species assemblages). Therefore, the model does not consider vegetation changes that may occur as climate changes, as well as other factors (e.g., pests, pathogens), which could alter hydrologic (e.g., transpiration) and biological (e.g., uptake, growth) processes.
PnET-BGC requires inputs of meteorological data, atmospheric deposition, forest disturbance history, vegetation, soil, and site parameters. Meteorological inputs include a time-series of monthly maximum and minimum air temperature (°C), photosynthetically active radiation (PAR; mmol m-2 s-1), precipitation (cm), and atmospheric CO2 concentration (ppm). Atmospheric deposition includes monthly wet and constant dry to wet ratios of major elements. PnET-BGC uses the dominant forest cover type (i.e., northern hardwood trees, spruce-fir, red oak/red maple, and red pine) and its associated generalized physiological characteristics. Soil information includes soil mass per unit area, cation exchange capacity, cation exchange and anion adsorption coefficients, water holding capacity, element weathering rates, and elemental stoichiometry. Site characteristics include historical land disturbance (e.g., forest harvesting, hurricane, ice storm, fire) as well as latitude, longitude and elevation [Chen and Driscoll, 2005; Gbondo-Tugbawa et al., 2001; Zhai et al., 2008]. The effects of atmospheric CO2 on vegetation, including response of stomatal conductance and a CO2 fertilization effect on biomass, were implemented by a multi-layered sub-model of photosynthesis and phenology developed by Ollinger et al. [1997, 2002] using a constant ratio of leaf internal to ambient concentration of CO2 (Ci/Ca). A detailed description of PnET-BGC is provided by Aber and Driscoll  and Aber et al. , and a detailed sensitivity analysis of parameters and state variables are provided by Gbondo-Tugbawa et al.  and Pourmokhtarian et al. . Model simulations run on a monthly time step with an initiation period starting at year 1000 to allow for the soil and vegetation pools to reach steady-state. Model hydrological outputs include monthly streamflow, transpiration, evaporation, water use efficiency, soil moisture, water stress index (DWater), snow pack, and snowmelt.
Person Responsible For Model Simulations In This Simulation Round: Afshin Pourmokhtarian
Spatial Aggregation: forest stand
Additional Spatial Aggregation & Resolution Information: Model output is per square meter and can represent site level to watershed level.
New development in the model is the ability to run at a regional scale and daily time scale and the resolution could be as fine as 30x30 meters although the inputs need to be at the same resolution.
Temporal Resolution Of Input Data: Climate Variables: daily
Temporal Resolution Of Input Data: Land Use/Land Cover: annual
Temporal Resolution Of Input Data: Soil: constant
Additional Temporal Resolution Information: The model can run at daily, monthly, and annual time-step based on user's preferences.
Input data sets used
Climate Variables: tasmax, tasmin, rlds, rsds, pr
Was A Spin-Up Performed?: Yes
Spin-Up Design: Model simulations were run on a monthly time step with an initiation period starting at year 1000 to allow for the soil and vegetation pools to reach steady-state.
Key model processes
nitrogen limitation: Yes
CO2 effects: Yes
light interception: Yes
light utilization: Yes
phenology: Yes, growing degree days
water stress: Yes.
The DWater term is a model-calculated estimate of the degree of stomatal closure due to sub-optimal water availability. It is a unitless metric of water stress which ranges from 0 (full water stress) to 1 (absence of water stress). Soil water stress (DWater) and actual evapotranspiration are functions of plant water demand and available soil water for each time step of a simulation (monthly for this analysis). If the plant water demand is higher than available soil water for a month, water stress occurs and the value of DWater decreases to less than 1 (e.g., a DWater value of 0.9 indicates that there is a 10% shortage of available soil water for trees in that month of model simulation). Therefore, if the sum of DWater for all months of an annual simulation is 12, there is no water stress for any month during that year. An annual DWater value less than 12 indicates that trees experience water stress in some months over an annual simulation. For this analysis we subtracted mean of simulated DWater values for the reference period (1970-2000) from simulated DWater values for the period of 2070-2100 (∆ DWater). Therefore, more negative ∆ DWater values indicate greater water stress of trees compared to the reference period. The DWater index shows the effects of water stress on forest net carbon gain, carbon allocation, and transpiration loss, which is reflected by changes in hydrology.
heat stress: Yes. Based on optimum photosynthesis temperature for each type of forest cover.
Evapo-transpiration approach: Yes.
Differences in rooting depth: No.
Root distribution over depth: No.
closed energy balance: No.
Coupling/feedback between soil moisture and surface temperature: No.
latent heat: No.
sensible heat: No.
Causes of mortality in vegetation models
Age/Senescence: Mortality could be prescribed as a constant annual percentage of wood turn over rate.
Fire: Could be prescribed based on year and month, intensity, and disturbance to soil and vegetation.
Stochastic random disturbance: No.
Fire: Burn and release to the atmosphere.
Land-use change: Deforestation. Intensity, percentage of biomass that is left to decompose.
Harvest: Yes, same as land-use change.
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