Simulation Results

Below, some general patterns that emerged from the simulation runs for the Sierra Nevada data sets are presented in summary. The detailed results of the simulations are also available in a zipped archive that contains a series of Microsoft Excel 97 spreadsheet files. If you download the files, please make sure you read the corresponding explanation before you use the results.

Basal Area

Fig. 1: Development of the basal area for one plot over time. The plot is assigned a stand type description of P3G. The different data series represent different treatment scenarios for the trees with DBH larger than 30 inches.

Quadratic Mean Diameter QMD

Fig. 2: Development of the quadratic mean diameter over time.

Standing Live Volume

Fig. 3: Development of the standing live volume (stemwood only) over time.

Unmerchantable Volume Removed

Fig. 4: Development of the unmerchantable volume removed over time. This biomass is considered to be available for energetic purposes such as ethanol production and (co)firing in power plants.

Accretion (Gross Growth)

Fig. 5: Development of the gross growth over time. The sudden decrease at the end of the simulation period is a computational artifact.

Mortality

Fig. 6: Development of the mortality over time. Mortality is an important source of dead fuel, which is not included in any of the volume calculations. As with growth (cf. Fig. 5), the sudden decrease at the end is a computational artefact.

Canopy Closure Within DBQ Diameter Range

Fig. 7: Development of the canopy closure resulting from trees within the DBQ diameter range over time. The canopy closure serves as a substitute measure for the fuel bulk density.

Canopy Closure Above DBQ Diameter Range

Fig. 8: Development of the canopy closure resulting from trees above the DBQ diameter range over time.

Total Canopy Closure

Fig. 9: Development of the total canopy closure resulting from trees within and above the DBQ diameter range over time.

Although the figures above do only represent a very limited selection of the simulation results, they show some important general pattern that emerged in all the runs for the Sierra Nevada.

First, there are two distinct phases in the stand development. In an initial period (lasting approximately 40 years and including 2 interventions), the fuel loads are reduced and the stand structure is brought close to the target DBQ distribution. Afterwards, the variables show a much more stable behavior. Either does their value remain more or less unchanged, or else is their rate of change almost constant. This second phase represents a sustainable "biological automaton", i.e. a system that works with discrete or continuous input and output signals (fluxes or stocks) of a constant or linear nature.

Second, although they account only for a very small number of the trees in the stand, the treatment of the big trees over 30 inches diameter has a very crucial effect on the total stand development. Depending on how many trees are left in an intervention, the time when the stand reaches a quasiconstant state (i.e. one with no temporal variation of the stand characteristic) can shift by as much as a century. But he different large tree treatments not only affect the speed with which such a constant state is achieved, but also the quality of this state. This is also evident if some stand visualizations are compared. Fig. 10 below shows some SVS images of the stand after 100 years. [Note that in some cases, the arrangement of the trees may give a distorted impression of the stand density.]

Fig. 10: Visualization of the stand after application of different treatments for 100 years. The number next to each image represents the percentage of trees over 30 inches DBH removed every 20 years.

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