Last month we were pleased to introduce a powerful, new technological service designed to model a number of interactive conditions and circumstances within a forest over time (up to 30 years), helping forest managers optimize sound management decisions and maximize financial returns. This service, called ForestSim™, has been developed on a complex Monte Carlo simulation software product that provides the user with the ability to easily change a variety of financial parameters and management conditions and quickly see the resulting effects on the development of the forest and the bottom line of their investment.
As previously mentioned, ForestSim™ is driven by forest stand tables which provide the number of trees by species and diameter class. From this information, basal area calculations and the corresponding stand stocking densities are processed providing the underlying growth modelling system (USFS TWIGS) with the necessary information to project growth and mortality over a period of thirty (30) years. Species composition and stand density are just a few of the variables that drive the growth projections. A variety of financial inputs can be made as well (stumpage values by species and diameter class, estimated stumpage value appreciation, investment discount rate, etc.) and integrated into the simulation model that provides either probabilistic results (multiple outcomes because the inputs have a user-defined degree of variability), or deterministic (results are single values) for a variety of circumstances selected by the user.
The ability of this system to quickly assess Net Present Value estimates of every forest stand on any property was demonstrated in the last article, and the results were presented in both tabular and spatial formats. The example given included an analysis of approximately 600 individual forest “stands” containing over 350 million board feet of sawtimber existing on about 34,000+ acres. For purposes of simplifying the outcomes, a run was chosen that didn’t include any harvesting activity, and the results were reported within five “Year of Peak NPV” timeframe categories. We also demonstrated the powerful spatial reporting component by showing a Peak Net Present Value analysis on a smaller tract where the different NPV results were color-coded, providing a very effective field map for forest managers (see FORECON’s ForestSim™ Services article in June issue ).
In this issue, we want to demonstrate the ability of ForestSim™ to predict a stand’s net present value over time involving uncertainties generated by Monte Carlo simulation. Monte Carlo simulation is a mathematical procedure that accounts for inherent risk in quantitative analysis and decision making. In general, it provides the user with a range of possible outcomes within identified probability parameters for the selected inputs/assumptions that drive the model. This simulation process provides a band of outcome possibilities that contains the mean of the results, along with the extreme outcomes due to natural randomness as well.
ForestSim™ Example #2 – Probabilistic Model (with uncertainty) Year of Sawtimber Peak Net Present Value (NPV)
This demonstration involves isolating three different forest stand types, introduces volume, value and site condition uncertainties, applies grade appreciation by diameter class, uses an annual value appreciation rate of 3% for all species and displays the change in net present value over time. Harvest activity was not introduced in this set of examples. Note that the charts show the minimum, maximum, 90% confidence interval and the mean of each 30 year run.
A) The first run involved an A4B stand of 244 acres (defined as follows):
As with the two previous examples, 50 probabilistic calculations were also modelled annually over a 30-year period for this northern hardwood stand. This curve indicates this stand’s Peak NPV is attained in Year 12 (approximately $2,175/acre) if left to grow “as-is,” and shows a somewhat balanced curve on either side of that year. The band of uncertainty also widens substantially over time as it did in the second example, with a spread of about $550/acre in Year 30.
All three stands reach economic maturity at different times based on their species mix, stocking level, and average diameter. Again, these three examples are provided without regard to any silvicultural activity which may be prescribed.
The next ForestSim™ article will demonstrate how this system analyzes the effects of a variety of harvest treatments available to the user, allowing a forest manager to maximize landowner objectives using simulated prescriptions. In the meantime, if you wish to find out more about how ForestSim™ can help you optimize your forest management objectives, please use the form below to request additional information.