Forest Growth Model, 3-PG
Foresters recognize that it is necessary to take climatic variation into account to predict the growth of forests and conditions that make them vulnerable to natural disturbances. Scientists have constructed computer simulations models to address this challenge. Such models require information on seasonal and interannual changes in weather, as well as how much water and nutrients are available from the soil, as these factors combine to impose limitations on photosynthesis, and ultimately, on how growth is distributed above- and belowground (see diagram).
The computer model, 3-PG (Physiological Principles Predicting Growth), is more complicated than shown in the above diagram, but contains four simplifying assumptions that make it practical:
- If only sunlight limits production, growth increase linearly as the canopy of leaves intercepts and absorbs more light.
- half of gross photosynthesis is respired away in the construction of new growth and in the maintenance of live tissue
- Monthly mean maximum and minimum temperature data are sufficient, with knowledge of a site's location, to derive good estimates of incident solar radiation, frequency of frost, and humidity deficit of the air, which, along with monthly precipitation, are the essential climate variables required to drive the model.
- The model reduces photosynthesis as a simple function of stand age rather than accounting for reductions in water transport through roots, stems, and branches
If you would like to run the model, download the Excel spreadsheet used in a course that I teach. A series of exercises with answers are provided below. More detailed background material as well as a spatial version of the model programmed in C++ can be obtained from the 3-PG website located at the University of British Columbia, which was established by Dr. Nicholas C. Coops.
Ex. 1. Estimating soil fertility and stand biomass when self-thinning begins in a coast range Douglas-fir forest
Ex. 2. Solar radiation, vapor pressure deficits, and frost frequency from monthly temperature extremes
Ex. 3. Modeling thinning and defoliation effects on the growth of forests
Ex. 4. Modeling the effects of drought and soil water storage capacity on pinyon pine
Ex. 5. Assessing the effects of nutrient additions on the growth of eucalyptus
Ex. 6. Comparing ponderosa pine and Douglas-fir responses in different climates
Ex. 7. Accessing the importance of groundwater to eucalyptus forests in western Australia
Ex. 8. Sensitivity analysis to assess interactions between soil water storage capacity and soil fertility