Traditional approaches to forest valuation often misstate the Net Present Value of forestland resources based on simplistic interpretations of the Income Capitalization Approach. One of them involves timberland value estimates made for current standing timber. These are explained with a Faustmann Formula Value in order to claim Income Capitalization Approach value to the property. These traditional valuation estimates prove to be inconsistent with their REAL value.

In recent decades, the estimation of forestland property value has migrated to a progressively higher level of assessment. Individual timber stands explained through forest Growth & Yield modeling efforts has illuminated professional views. These fundamental timber resource data enable us to determine tree growth over time separately on each timber stand. Today, advances in Growth & Yield software programming reveal how the biological resource performs within a set of qualifying parameters. These include Site Index, precipitation, temperature, and multi-layered timber stand density factors. When expressed by different tree species co-mingled on the same property they take form and structure. Ability to grow virtual forests into the future has become a powerful tool vital for an accurate asset valuation. However, attempts at optimization of potential timber harvest, have focused only on its biological maturity. This limits us in the entirety of other possible solutions, totally excluding from consideration financial criteria of the issue.

The existing software designs for forest Growth & Yield assessments have been augmented with valuation modules – however, these generally give inadequate optimal valuation estimates.

Why? Read on…

Financially optimal timber harvest solutions, in some applications, evaluate only the current timber harvest rotation. Those are done without considering the next rotation, or each subsequent rotation after that. To further complicate the situation, Delivered Log Market Real Price Appreciation (and Devaluation) phenomenon has not been appreciated and applied. These must be applied in a temporal sense (the time effect) to match value parameters with forest growth over time. The general result has been to limit the current timber stand to a financially optimal single-rotation length only. Again, it gives no consideration to the discounted value of the next rotation, or rotations into perpetuity.

This leads to the wrong approach.

Consider forestlands as responsive biological organisms growing in size and changing in forest species composition. The events influence nutrient cycles every day through time. We can model those changes along with alterations to a host of interrelated ecosystem components. Economics is ONE of those components: understand it.

FRASS uses data collected by forestland managers as they manage their forestland properties. Some of these data are publicly available, such as Digital Elevation Models (DEM) and soil type data. On the other hand, some data are generated by the manager or purchased from analysts. We recognize the importance of these data for managing the property and their impacts on the value of the resource. As a result, management activities are engaged based on specific data analytics. It makes sense to extend the power of these data to all aspects of management. The FRASS Approach embraces these data to make them part of the solution.

At D&D Larix, LLC, we analyze natural resources data to create GIS layers, analyze the attribute contents. Through this, we conduct spatial and statistical analysis to reveal opportunities possible through management. All of this is integrated with the energy of growing trees and the environment they are part of. As you read through this site, know that we strive to generate information you need. It leads to better management of your property. The FRASS Platform enables these capabilities.

3-Legged Stool, with a Seat

At the very core of data analysis rests a 3-legged stool of 1) geospatial data (commonly just called GIS data), 2) forest Growth & Yield data, and 3) economic data. Other information are transcribed into one or all of these formats; everything is summarized into maps and tabular data. The FRASS Approach delivers these through the lens of each landowner’s view. That is the uniting factor integrating them together. Owner characteristics form the top of the three legged support – the pad.

The FRASS Approach is best thought of as a process. All information is accumulated into a uniform structure, most often it is into a database structure. Here, it can be measured, combined with other structures, and explained. Sometimes it is explained in terms of financial value. Other times it is expressed as biological diversity. In all cases, it is application of the FRASS Approach.