STAND-BGC (BioGeoChemical)

STAND-BGC is a process-based, or mechanistic, model consisting of a series of submodels that describe the operation of various physiological processes involved in the growth of individual trees, shrubs, and grasses.

process-basedmechanisticphysiological processesgrowthtreesshrubsgrasses

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Quoted from: Graduate Student Theses, Dissertations. 2000. Incorporating competition between life forms into the soil water submodel within STAND-BGC a vegetative process model. Ellen P. Voth. The University of Montana. https://scholarworks.umt.edu/cgi/viewcontent.cgi?article=7904&context=etd 

      STAND-BGC is a process-based, or mechanistic, model consisting of a series of submodels that describe the operation of various physiological processes involved in the growth of individual trees, shrubs, and grasses. It is a member of a family of models using the canopy level modeling logic and physiological growth algorithms presented by Running and Goughian in the FOREST-BGC (BioGeoChemical) model (1988) and the BIOME-BGC model (Running and Hunt, 1993). STAND-BGC takes the canopy level processes in the prior BGC models and applies them to multiple, interacting canopies thereby allowing simulation of the competitive interactions between vegetative life forms. This allows it to model both inter-specific competitions between trees and grasses as well as intra-specific competition between trees of different life-stages. The basic processes within STAND-BGC are modeled at the individual ‘entity’ level (trees are grown as individual entities; grasses and shrubs are grown as unit-area entities). The processes modeled include: radiation interception by the foliage, carbon fixation by photosynthesis, carbon losses by respiration, the water balance of the stand, (including canopy interception, evaporation, transpiration, and drainage), the allocation of carbon to the component parts of the tree, mortality, and the updating of entity attributes (e.g., diameter, height, and crown ratio).

      STAND-BGC adapted the ‘big-leaf canopy level logic of the FOREST-BGC model to function at multiple sub-canopies, thus allowing more explicit representation of the competition for light and water between individual entities. Light competition between plant size classes and life forms is represented by the attenuation of light down through the canopy. Entities receive light energy based on their vertical position in the stand and on the amount of leaf area they carry in their canopies. Larger (taller) entities capture light first, which is then subtracted from the light energy available to entities at lower canopy zones. Moisture competition is simulated in the model by assuming an entity has access to available soil water based on its leaf area proportional to the leaf area of the stand. This allows moisture competition to be modeled without defining rooting characteristics.

      Physiological processes are modeled on a daily basis for each canopy zone of an entity and are more fully described in Milner and Coble (1995). In brief, they are calculated as follows: Daily photosynthesis in a specific canopy zone of an individual entity is calculated based on the maximum photosynthetic rate, photosynthetically active radiation, LAI, and a canopy light extinction coefficient. Daily canopy stomatal conductance to water vapor for each entity/canopy zone is calculated based on maximum stomatal conductance, attenuated radiation, and LAI (Milner and Coble 1995). Daily transpiration by entity/canopy zone is calculated from the Penmon-Monteith equation (Running and Coughlan 1988). Daily maintenance respiration for an entity is calculated using leaf, stem, and root maintenance respiration constants, the average night temperature, the amount of carbon in leaf, stem or roots and daylength. Daily growth respiration for an entity is calculated as a fraction of gross photosynthesis.

      STAND-BGC is a distance independent, individual entity (tree, shrub, or grass) model, constructed to use standard forest inventory data as input, (for trees: species, diameter, height, crown ratio, and expansion factor; for shrubs and grasses: species, height, and percent cover). These input data are converted to leaf carbon, stem carbon, and root carbon units via biomass equations (biomass references cited in Milner and Coble 1995). The model is driven by soil data (soil water holding capacity and soil texture) and climate data (daily precipitation, maximum and minimum air temperatures, relative humidity, dew point, and incident short-wave radiation) for the site, along with specified default generic conifer, shrub, and grass physiological parameters. See Appendix A for a table of required daily inputs, driving variables, and outputs. Ecophysiological attributes such as boundary layer conductance, specific leaf area, maximum stomatal conductance, leaf turnover rates, and respiration coefficients, can be modified to match the information available about a particular species or life form. The hydrologic, photosynthetic, and respiration processes are simulated on a daily timestep, while carbon allocation and mortality are simulated on an annual timestep. At the end of the growth period, net photosynthesis for the year is determined (net photosynthesis = gross photosynthesis - respiration), and is allocated between leaf, stem, and root carbon pools for each entity. After the carbon is allocated to the entity carbon pools, the entity attributes are updated. For trees, the stem carbon allocation is first converted to biomass and then to volume through a set of unit conversions. Diameter increment is then calculated from the predicted stem volume increment, following Pressler’s Law (as formulated by Mitchell, 1975). Height is updated by using the predicted diameter increment in the height growth equations used in F VS (Wykoff et al. 1982, p. 65 - 67). For shrubs and grasses, changes in percent cover and height are calculated by converting the carbon increment to biomass, inverting the appropriate biomass equations, and solving the equation. The model produces a standard updated tree list with tree dimensions (DBH, height, crown ratio, density (tph), etc.) as output.

      Mortality is simulated by STAND-BGC by removing an entity from the live entity list to be grown in the next growth period. If respiration costs exceed carbon production by photosynthesis, the leaf area of an entity is reduced. Crown recession for a tree occurs when the leaf carbon pool at the end of an annual growth period is less than the leaf carbon pool at the beginning of the growth period. In this case, the tree’s crown ratio is reduced proportional to the loss of leaf carbon. When a tree’s crown ratio is reduced to zero, the tree ‘dies’, i.e., it is removed from the live tree list and added to the dead tree list. For grasses, if carbon production is less than carbon lost to maintenance costs, the leaf carbon pool for the grass entity is reduced, resulting in a comparable decrease in height and percent cover. If percent crown cover is reduced to zero, the grass entity ‘dies’ and is removed from the live entity list.

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STAND-BGC team (2020). STAND-BGC (BioGeoChemical), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/67faa569-5f6e-4aaa-97ed-3d0be2d41112
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