Skip to content
Quick Start for:
Chapter 4
Timberland Appraisal Process

Introduction

The productivity value of an acre of timberland equals the average annual net income a prudent manager could earn from growing timber over the five-year period preceding the appraisal’s effective year, divided by a statutory capitalization rate. Net income has two parts: gross income and production cost.

Gross income is calculated by computing potential average annual timber growth per acre and multiplying this amount by timber’s average annual market price for that year. This computation is performed for each year of the five-year period.

The average annual cost of producing timber in each of the five years is subtracted from gross income to find net income for the year.

Average annual net income is computed by averaging net income for each year of the five-year period. This five-year average annual net income is then divided by the statutory capitalization rate to produce the productivity value of timberland. Timberland’s productivity value is determined in ten basic steps:

• Step One:
Classify timberland into three forest types;
• Step Two:
Classify timberland into four soil types;
• Step Three:
Estimate average annual timber growth;
• Step Four:
Convert timber growth into units for estimating gross income;
• Step Five:
Estimate average annual timber prices;
• Step Six:
Estimate average annual potential gross income of timber growth;
• Step Seven:
Estimate average annual costs of producing timber;
• Step Eight:
Estimate net income of timber growth;
• Step Nine:
Capitalize net income by statutory rate to develop per acre timber values; and
• Step Ten:
Apply timber values to timber acreage within the district.

This chapter of the manual prescribes the methodology chief appraisers must use to calculate timberland’s productivity value. The law requires chief appraisers to estimate timber productivity values for three forest types and four soil types, and apply these values to the different classes of timber within their respective districts. (At most, an appraisal district may have 12 classes of timber—four soil types for each of three forest types. Some districts may not have 12 classes of timber. For example, a district that contained only pine forest might have four classes of timber: pine soil class 1, pine soil class 2, pine soil class 3 and pine soil class 4.)

Appendix B contains tables that illustrate this methodology, and the text frequently refers to these tables.

The Tax Code, Section 23.71, requires chief appraisers to use “the land’s potential average annual growth” in computing timber’s gross income. In this context, the word “potential” does not mean actual—it means “possible.” Consequently, the gross income of an acre of timberland is equal to the value of an average year’s worth of possible growth. Chief appraisers must apply the value of a year’s worth of possible growth to all timber in each forest and soil type category, irrespective of the size of trees on any one tract.

The result of defining gross income as the value of potential growth often confuses many timber growers, because trees of dramatically different ages and sizes may have the same values. Assume, for example, two tracts of timber, both planted in loblolly pine and both having the same soil type and other characteristics. One tract has pine seedlings six inches high from a recent replanting; the other has pine trees 80 feet high and ready for harvest. If the chief appraiser is following the law’s requirements on timber appraisal, both tracts should have the same appraised values per acre.

The law uses the land’s potential income because the tax is a property tax. If individual tracts were appraised on their individual incomes, the tax would be an unconstitutional income tax.

The Tax Code, Section 23.71, requires chief appraisers to use information from four different sources to determine forest types, soil types, average growth and timber prices. These are:

These sources are mandatory and are described in Appendix A. The one exception to this requirement is discussed below in last paragraph of Step One.

As noted earlier in Chapter II of this manual, the Tax Code, Section 6.12, requires chief appraisers to appoint an “agricultural appraisal advisory board.” The function of this advisory board is to advise the chief appraiser on the use and valuation of timberland and agricultural land within the district. However, the board's advice on the appraisal of timberland does not take precedence over the law's requirements on data sources or the appraisal methodology set out in this chapter.

Before using data from any of these mandatory sources, chief appraisers should check with the relevant agency for updates. For example, the USDA Forest Service may periodically revise its published Texas timber survey numbers. The agency makes these revisions available to the Texas Forest Service. Chief appraisers should check with the Texas Forest Service for revisions to the Texas timber survey numbers before they use the survey data. In addition, chief appraisers should not use data from any of these sources in any manner different from that shown in this manual without first checking with the relevant agency to be sure they are using the data properly.

The East Texas timber-growing region is composed of the 43 counties depicted in Appendix B, Figure 1. Chief appraisers must use regional data and Texas Forest Service price data. Although the USDA Forest Service reports its Texas survey data at the county level, this agency cautions that the county data are not reliable because of large sampling errors.[5] The Texas Forest Service reports forest product price data at the region level but not at the county level.

Step One: Classify Timberland into Three Forest Types

TheTax Code, Section 23.71, requires chief appraisers to estimate timber productivity values for three forest types and four soil types. Chief appraisers should begin the appraisal process by classifying the timberland within their districts according to forest type. There are three basic forest types in Texas: pine, hardwood and mixed. These are as follows.

• Pine. Pine (and other softwood) timberland includes all forested areas in which the trees are predominately green throughout the year and do not lose their leaves. These trees are called evergreens. Forested areas where pine and other softwoods make up more than two-thirds of the trees free to grow are in this category.[6]

• Hardwood. Hardwood timberland includes all forested areas with a predominance of deciduous trees. These trees lose their leaves at the end of the frost-free season. Stands where hardwoods are more than two-thirds of the trees free to grow are in this category.

• Mixed. Mixed timberland includes all forested areas where both evergreen and deciduous trees are growing and neither predominates. An area is classified as mixed when evergreen and deciduous trees each make up more than one-third of the trees.

The Texas Agricultural Experiment Station at Texas A&M University in College Station has developed maps of forest types for Texas timber counties. These maps are available upon request for a nominal fee to cover reproduction costs.

In addition, chief appraisers may use aerial photographs, forest type maps and soil class maps from any governmental source that is recognized as competent to determine soil type, soil capability, general topography, weather, location and any other pertinent factors necessary to classify commercial timberland by forest type and soil type. If the chief appraiser elects to use maps from a data source not listed in Appendix A, the chief appraiser should exercise great care to be certain that the maps are the most current and reliable maps available and that the data source of the maps is a competent governmental source.

Step Two: Classify Timberland into Four Soil Types

The law requires chief appraisers to classify all timber-producing areas in their districts into four soil types. The chief appraiser should use data from the USDA Natural Resources Conservation Service (NRCS) soil surveys to develop soil type maps for his or her district. The NRCS does not publish soil type maps that the chief appraiser may use in appraising timberland. However, the Texas Agricultural Experiment Station at Texas A&M University has used the soil surveys to develop soil type maps for timberland within most timber-producing counties in Texas. These maps are available upon request for a nominal fee to cover reproduction costs.[7]

Where soil maps based on appropriate NRCS data are not available, or if the chief appraiser chooses to develop his or her own soil-type map, the chief appraiser may use NRCS detailed soil surveys, if available, to develop soil-type maps. These detailed soil surveys show the site index (discussed later in this chapter) for each specific soil. A soil-type map can be derived using this information.

The NRCS’s soil classification system is based on the concept of site index. Site index is a measure of the productive capacity of a forest site based on the average height of the tallest trees on the site at an arbitrarily chosen age. For example, if the average height of the five tallest loblolly pine trees in a fully stocked stand at the age of 50 years is 75 feet, the site index for loblolly pine trees on that forest site is 75. The NRCS publishes site index information in its soil surveys of Texas counties.

The NRCS soil surveys provide site index information for all land capable of growing commercial trees within each county. The NRCS site index data must be grouped into types that are generally comparable to the USDA Forest Service site classes, and this information should then be used to generate soil type maps. This is necessary because the USDA Forest Service reports timber growth data by site class, which is also a measure of soil productivity. However, the USDA Forest Service growth data by site class cannot be mapped since they were derived from a sample of selected sites in Texas.

The USDA Forest Service classifies all commercial timberland into five site classes based on the land’s potential capacity to grow commercial wood crops. Site class is a measure of timber growth in cubic feet per year. The USDA Forest Service determines site class by measuring the height of the three tallest trees at a particular site, and then selecting the tree providing the highest estimate of site class.

The USDA Forest Service has defined these five site classes as follows:

• Land capable of producing 165 cubic feet or more per acre per year;
• Land capable of producing at least 120 but less than 165 cubic feet per acre per year;
• Land capable of producing at least 85 but less than 120 cubic feet per acre per year,
• Land capable of producing at least 50 but less than 85 cubic feet per acre per year; and
• Land capable of producing less than 50 cubic feet per acre year.

To comply with the law’s requirement to use four soil types, chief appraisers must reduce these five site classes to four. The over 165 cubic feet site class should be combined with the 120-165 cubic feet site class to produce the mandatory four soil types, because this produces a classification scheme that works well with NRCS site index data discussed below.[8] In this manual, this combined site class is called the over 120 cubic feet site class.

As noted earlier, the NRCS site index data must be grouped into ranges that are roughly comparable with USDA Forest Service’s soil types. This grouping produces the following ranges shown in Exhibit 3 below.

Exhibit 3
Soil Classification Schemes
USDA Forest Service
Site Classes
USDA NRCS
Site Index Range
Over 120 cubic feet Over 95 feet
80-120 cubic feet 80-95 feet
50-84 cubic feet 60-79 feet
Under 50 cubic feet Under 60 feet

Step Three: Estimate Average Annual Timber Growth

Chief appraisers must use growth data from private timberland that is the most current and reliable data available from one of the sources required by law. (See Appendix A for a discussion of these sources.) At the time this manual was written, the most current and reliable growth data available was the 1992 survey of Texas timber conducted by the USDA Forest Service. These data are used in various tables in Appendix B.[9]

Table 1 in Appendix B contains summary growth data for private timberland from the 1992 Texas survey. These data, which were prepared by the Texas Forest Service, show the average annual growth of Texas timber during the 1986-1992 period.[10]This growth is expressed in terms of five forest products for each of three forest types and four site classes for each Texas timber region.[11]Chief appraisers should use the data in Table 1 to calculate the average annual growth per acre for each forest type expressed in terms of forest products.

The forest products are large pine sawtimber, small pine sawtimber, pine pulpwood, hardwood sawtimber, and hardwood pulpwood, and the forest types are pine, mixed and hardwood. To avoid confusion, it is important to remember that pine forests—defined above to be at least two-thirds evergreen trees—may produce both pine and hardwood forest products. Likewise, hardwood forests—defined to be at least two-thirds deciduous trees—may produce both pine and hardwood products.

Table 2 shows these calculations for the East Texas region. All calculations are based on the data in Table 1. The first page of Table 2 shows the steps necessary to compute growth for an average acre of pine in east Texas. For large pine sawtimber, for example (the forest product shown in the upper left-hand box), the chief appraiser should multiply the number of plots in each site class by the per acre growth for that site class.[12]Multiplying 220 (number of plots) by 317.43 (average growth per acre in board feet) in site class “120+” produces 69,834.60, which is the estimated total growth for this site class. The result of each calculation for the four different site classes is added and this sum is divided by the total number of plots for all four site classes. The resulting number, 203.21 board feet, is the average annual amount of large pine sawtimber grown on the average acre of pine in east Texas.

The computation methods necessary to calculate the average annual growth of the other forest products—small pine sawtimber, pine pulpwood, hardwood sawtimber, and hardwood pulpwood—are identical to those for large pine sawtimber. Table 2 shows that the average acre of pine forest in east Texas grows annually 203.21 board feet of large pine sawtimber, 111.08 board feet of small pine sawtimber, 14.14 board feet of hardwood sawtimber, 30.65 cubic feet of pine pulpwood and 3.30 cubic feet of hardwood pulpwood.

The chief appraiser should use these same procedures to compute the average annual growth of an average acre of both mixed and hardwood forests in the rest of east Texas. Complete calculations for all forest types are shown in Table 2. The results of the detailed calculations illustrated in Table 2 are summarized in Table 3.

Step Four: Convert Average Annual Timber Growth

As shown in Tables 1-3, the USDA Forest Service measures sawtimber growth estimates in the International 1/4 inch log rule and measures pulpwood growth estimates in cubic feet. A “log rule” is a scale for measuring the amount of sawtimber that can be produced from a tree.[13]The Texas Forest Service collects timber sales data bi-monthly from timber buyers and sellers; however, buyers and sellers report sawtimber transactions in tons. Consequently, the next step in the appraisal process is conversion of the growth estimates to the same scales in which forest product selling prices are reported.

The chief appraiser must use a log rule conversion table to develop factors to convert sawtimber growth from one log rule to another. Table 4 contains factors for converting board feet from the International 1/4 inch log rule to the Doyle log rule for east Texas. The individual conversion factors shown in the fifth column of these tables are for Texas timber. Chief appraisers should use these log rule conversion factors until subsequent log rule conversion factors are developed based on reliable and scientific data from sources listed in Appendix A and the factors are approved by the comptroller.

The first two columns in Table 4 are from the 1992 USDA Forest Service survey and show timber volumes by tree diameter class in east Texas. The fourth column, titled percent of total volume, shows volume for each diameter class as a percent of total volume. At the top of Table 4, for example, the reported volume for pine in diameter class 11-12.0 inches is 5195.1 million board feet. The 5195.1 million board feet is divided by total volume, 24,003.10 million board feet, to produce the percentage figure of 21.64%. The fifth column, titled conversion factor, is for Texas timber. The percentage and conversion factor for each diameter class are multiplied to produce the weighted contribution shown in the sixth column. Finally, these weighted contributions are added to produce the weighted conversion factor for pine in northeast Texas, which is 0.60258. The computations for the other conversion factors are identical. The timber volume data shown in both tables are for privately owned timberland.

After calculating the weighted conversion factors for large pine sawtimber and hardwood sawtimber as illustrated in Table 4, chief appraisers should apply these conversion factors to the sawtimber growth estimates summarized in Table 3. The results of these computations are shown in Table 5 Appendix B. For example (Table 5), the chief appraiser should multiply 203.21 board feet of large pine sawtimber in the International 1/4 inch log rule (Table 3) by the weighted conversion factor of 0.6258 to get 122.45 board feet of pine sawtimber in the Doyle log rule. To convert the 122.45 board feet to thousand board feet, the chief appraiser should divide 122.45 by 1,000 to get 0.12245. This measure of board feet must now be converted to tons to conform to the net-to-land definition in Section 23.71(2) of the Tax Code. The conversion factors for this calculation are provided by the Texas Forest Service and published in their Texas Timber Price Trends. The chief appraiser multiplies the growth in board feet measured by the Doyle Rule by the ton conversion factor. Following the example above for large pine sawtimber, the calculation is 0.12245 board feet times 8.0000 to get 0.9796 tons of growth for large pine sawtimber. The computations for hardwood sawtimber are identical.

The small pine sawtimber must also be converted from board feet measured by the International 1/4 inch log rule to tons. The chief appraiser should use the conversion factors provided by the Texas Forest Service in its bi-monthly publication, Texas Timber Price Trends. The growth rate in International 1/4 inch log rule from Table 3, 111.08 board feet, is multiplied by the cord conversion factor of 500 to determine the growth rate in cords. The indicated growth in cords, 0.22216, is multiplied by the ton conversion factor of 2.6250 to determine the growth rate in tons. These calculations are detailed in Table 5.

In addition, the pulpwood growth volumes shown in Table 3 must be converted from cubic feet into cords and then into tons. The Texas Forest Service reports the appropriate conversion factors in its bi-monthly publication, Texas Timber Price Trends. Current issues suggested conversion factors for cubic feet of pine pulpwood and hardwood pulpwood to cords are 81 and 80, respectively. The conversion factors for cords to tons are 2.5625 for pine pulpwood and 2.8 for hardwood pulpwood. The results of these calculations also are presented in Table 4.

Table 5 in Appendix B summarizes the annual average growth of an acre of timberland by forest type and forest product in East Texas. All growth is shown as tons. Based on the 1992 Forest Inventory and Analysis, the average annual growth of an acre of pine forest in east Texas is:

• 0.9796 tons of large pine sawtimber;
• 0.5832 tons of small pine sawtimber;
• 0.0789 tons of hardwood sawtimber;
• 0.9697 tons of pine pulpwood; and
• 0.1155 tons of hardwood pulpwood.

Step Five: Estimate Average Timber Prices

To determine the average annual gross income from an acre of timber, the chief appraiser should multiply timber growth by its average annual price, or stumpage price.[14]Before doing this, however, the chief appraiser must calculate the average annual stumpage price of each of the five forest products for each year of the five-year period preceding the year of appraisal.

A readily available source of stumpage price data is the Texas Forest Service, located in College Station, Texas. The Texas Forest Service is also an official source of data for timber appraisal. This agency collects timber prices in its bi-monthly surveys of forest industries, consulting foresters, government agencies, and large landowners and publishes selected summaries of price data in its publication Texas Timber Price Trends.[15]This publication reports selected price data for large and small pine and hardwood sawtimber sales, pine and hardwood pulpwood sales and other miscellaneous sales. Unpublished annual summaries of price data are available upon request.

The Texas Forest Service reports both unweighted average annual prices and weighted average annual prices for various forest products for both northeast and southeast Texas. These price reports are available upon request from the Texas Forest Service. Chief appraisers should compute a simple average of these two reported prices and use this simple average in their timber appraisals.

Table 7 shows an example of how to calculate average annual stumpage prices for five forest products for each year of the 1998-2002 period. As shown on Table 7, the average price for large pine sawtimber in 1998 was \$45.67 per ton; in 1999, \$42.01 per ton; in 2000, \$39.29 per ton, etc.

Step Six: Estimate Average Annual Potential Gross Income

This section explains how chief appraisers should calculate the average annual potential gross income of timber growth. The steps in this calculation are:

• Compute average annual gross income;
• Calculate soil productivity multipliers; and
• Use soil productivity multipliers to adjust average annual gross income to potential gross income.

First, the chief appraiser should multiply the growth of each of the five timber products (Table 6) by its respective price (from Table 7) for each year of the five-year period. Table 8, Appendix B, shows these calculations. As shown on Table 8, for example, the average annual gross income for an acre of pine forest in northeast Texas was \$73.99 in 1998 and \$55.22 in 2002. These numbers were computed by multiplying each forest product growth estimate by its respective price and then summing the products.[16]

Next, the chief appraiser must adjust these gross income estimates to reflect different soil productivities. To do this, the chief appraiser should develop productivity multipliers to adjust the average gross income. Productivity multipliers must be computed from statutory data sources that are current and reliable. (As noted earlier, Appendix A contains a listing of official data sources.) At the time this manual was written, USDA Forest Service data were the only current and reliable data available for developing soil productivity multipliers.

The USDA Forest Service data needed to compute productivity multipliers are:

• the most recent forest survey data for Texas; and
• data contained in the Boyce study, conducted by the USDA Forest Service.

The Boyce study, named after one of its authors, determined in 1975 the average annual maximum potential amount of timber that could be produced on an acre of loblolly pine east of the Mississippi River in each of four soil productivity classes.[17]The soil productivity classes used in the Boyce study correspond to the soil classification scheme developed above in Step Two of this Manual. The example in Exhibit 4 below shows the Boyce study growth estimates by soil class.

The concepts of site quality class and site index range were discussed earlier in Step Two. As used in Exhibit 4, “potential timber growth per acre per year” is the Boyce study estimates of the maximum potential growth of an acre of loblolly pine in each soil productivity class under ideal conditions.

Exhibit 4
Boyce Study Growth Estimates by Soil Class
Soil Productivity Class Site Quality Class
(cubic feet)
Site Index Range
(feet)
Potential Timber Growth per Acre per Year
(cubic feet)
Class I Over 120 Over 95 163
Class II 85-120 80-95 123
Class III 50-84 60-79 85
Class IV Under 50 Under 60 60

Table 9, Appendix B shows how to compute the average annual potential growth of an average acre. The first page of Table 9 lists acres by site class for each county in east Texas. These data are from the 1992 USDA Forest Service survey of Texas. The second page of Table 9 shows the results of multiplying the acreage in each site class in each county by the growth potentials developed in the Boyce study.

For example, the 15,300 acres in site class 165+ in Anderson County (Table 9) are multiplied by 163 (the growth potential for that site type). The result, shown on the second page of the table, is 2,493,900 cubic feet. This calculation is carried out for all site classes in each county. The resulting products are added to produce 1,351,804,300 cubic feet, which is the estimated total potential growth of timberland in east Texas. This total estimated potential growth is divided by the total number of acres, 10,990,400, to generate an estimate of the average annual potential timber growth of an acre of timberland in east Texas of 123.00 cubic feet per acre per year. As noted earlier, “average annual potential growth” is not the same as “average annual actual growth.”

Table 10, Appendix B shows how to calculate soil productivity multipliers for the four productivity classes for East Texas. Chief appraisers should compute these productivity multipliers by dividing the growth potentials from the Boyce study by the growth potential for the region. To compute the productivity multiplier for productivity class II timberland, for example, the chief appraiser should divide 123 by 123.0 to generate a productivity multiplier of 1.00.

Table 11, Appendix B shows chief appraisers how to apply productivity multipliers to the average annual gross income estimates, which were developed in Table 8. In 1998 for example, the annual gross income of pine, \$73.99, is multiplied by the productivity multiplier for each productivity class. This produces estimates of the average annual potential gross income of each productivity class in 1998.

It is important to remember that this “potential gross income” measure is not an estimate of the actual income an individual timber grower could receive from the sale of timber in a particular year. It is a measure of the value of a year’s worth of possible growth in each timber category (forest type and soil productivity class) in the region.

Step Seven: Estimate Average Annual Costs of Producing Timber

Texas law defines timber production costs as reasonable management costs and other reasonable expenses directly attributable to producing timber that a prudent manager of the land and timber, seeking to maximize return, would incur in the management of the land and timber. The costs of producing timber are expenses related to establishing, owning, protecting, maintaining, and improving timber. These costs may vary by forest type, soil productivity, management intensity and other factors.

Timber production costs include professional services, site preparation, tree planting and seeding, timber improvement, protection against fire, insects and diseases, prescribed burning, maintenance of property boundaries, road construction and maintenance, measurements of standing timber, selling costs, property taxes, equipment use, mileage traveled to/from property for timber management, personnel supervision and administration. Since many foresters may include several activities under one general classification, chief appraisers should understand the components of a particular timber management activity to avoid duplicating or omitting costs.

The cost model in Appendix C lists timber management activities and a typical frequency for each activity. The chief appraiser should use this general cost model as a basis for developing a district-specific cost model that reflects typical activities for a prudent manager in the district. Chief appraisers may add or delete activities to this model so that it reflects management activities that are typical for their respective districts.

After determining typical management activities and the frequency of each activity in the district, the chief appraiser should estimate the average annual cost of each activity. Sources of cost data are the Texas Forest Service, landowners within the district, private contractors, consulting foresters, and departments of forestry in Texas colleges and universities. The chief appraiser must develop costs that reflect typical management activities and typical frequencies for a prudent manager in the district.

Chief appraisers may develop an average, per acre cost for the typical tract in the district or an average, per acre cost for each type forest type. In either case, chief appraisers must adjust these costs to reflect different management costs for each category of timber. This is done because timber on more productive land is often managed more intensively, resulting in higher costs per acre. Adjusting average annual costs per acre for soil productivity classes is analogous to adjusting average annual gross income per acre to soil productivity classes, as discussed in Step Six.

Chief appraisers who develop one average cost for the typical tract must adjust this cost to reflect both forest type and soil productivities. To accomplish this, chief appraisers may use the following cost proration factors developed based on the Texas Forest Service’s Texas Timberland Management Cost Study shown in Exhibit 5 below.

Exhibit 5
Cost Proration Factors*
Forest Type I II III IV
Hardwood 0.45 0.40 0.30 0.20
Pine 1.20 1.00 0.80 0.35
Mixed 0.75 0.60 0.50 0.30
* Factors may change based on future data from the Texas Forest Service.

Table 12 in Appendix B shows hypothetical costs for a hypothetical county in east Texas. The numbers in this table were created to illustrate the timber appraisal process, and chief appraisers should not use these numbers in their appraisals.

Table 13 in Appendix B shows the results of applying these cost proration factors to the hypothetical costs shown in Table 12. The chief appraiser should note that these cost proration factors are applied to an average cost for a typical timber tract. The proration factors adjust costs for both forest type and soil productivity class.

If chief appraisers develop an average cost for each forest type, they must adjust each of these costs to reflect the impact of different soil productivity classes. To accomplish that, chief appraisers may apply the relationships within soil classes above to make the adjustments. For example, assume that the chief appraiser determines that the average annual management cost of hardwood is \$15.00 and that most of the hardwood in the district in soil class II. This \$15.00 figure becomes the management cost for hardwood soil class II. The management cost for hardwood soil class I would be \$15.00 x 1.125, or \$16.88. The 1.125 factor is derived by taking the relationship from the factors for hardwood in the table above (0.45 ÷ 0.40 = 1.125).

The management cost for hardwood soil class III would be \$15.00 x 0.75, or \$11.25. The 0.75 is the quotient of 0.30 divided by 0.40. The proration factor for hardwood soil class IV would be 0.20 ÷ 0.40 = 0.50 and the management cost would be \$15.00 x 0.50 = \$7.50.

Step Eight: Estimate Net Income of Timber

To calculate the average annual net income per acre for each timber type and soil productivity class, the chief appraiser must subtract the average annual cost per acre from the average annual potential gross income per acre. This calculation must be performed for each forest type and soil productivity class. The results are the average annual net income per acre by forest type and soil productivity class. Table 14 in Appendix B shows these computations for hypothetical counties in East Texas.

Step Nine: Capitalize Net Income to Develop Timber Values

To complete the timber appraisal process, chief appraisers must develop an average net income for each forest type and soil productivity class for the prior five years of average annual net incomes, capitalize this average net income and apply these productivity values to the timber acreage in their appraisal districts. Table 15 shows how to perform these calculations for hypothetical appraisal districts in East Texas.

The productivity value of an acre of timberland is determined by dividing the average net income per acre for each forest type and productivity class by the capitalization rate mandated by the Tax Code, Section 23.74. Prior to 2004, the capitalization rate was set at the interest rate specified by the Farm Credit Bank of Texas (Bank) or its successor on December 31 of the preceding year, plus 2-1/2 percentage points.

Beginning in 2004 and until the Bank’s interest rate on December 31 is greater than or equal to 7-1/2 percent, the capitalization rate will be the greater of:

• the interest rate specified by the Bank on December 31 of the preceding year plus 2-1/2 percent, or
• the capitalization rate used for the preceding tax year.

For instance, the capitalization rate used in 2003 was 6.4 percent (3.9 percent interest rate plus 2.5 percent). Assume the Bank’s interest rate on December 31, 2003 is 3.7 percent. Since 6.2 percent, the Bank’s 3.7 percent interest rate plus 2-1/2 percent, is less than the capitalization rate used in 2003, 6.4 percent, the capitalization rate for 2004 would be 6.4 percent. However, if the interest rate on December 31, 2003 had been 4.1 percent, the capitalization rate for 2004 would be 6.6 percent, the greater of 2003’s capitalization rate (6.4 percent) and the Bank’s interest rate on December 31, 2003 plus 2-1/2 percent (4.1 percent plus 2-1/2 percent, or 6.6 percent).

In the year after the Bank’s interest rate is equal to or greater than 7-1/2 percent, a different method of determining the capitalization rate will be used. The capitalization rate for years after the Bank’s interest rate first equals or is greater than 7-1/2 percent will be an average of the December 31 interest rate plus 2-1/2 percent and the capitalization rate used for each of the preceding four years; however, the capitalization rates used in the average cannot be for year’s prior to the first year the Bank’s interest rate was equal to or greater than 7-1/2 percent. The following example in Exhibit 6 will clarify the calculations, but the rates used are examples only and should not be used to determine capitalization rates for any year.

Exhibit 6
Capitalization Rate Calculation
Year Bank Interest Rate Bank Interest Rate Plus 2-1/2 Percent Capitalization Comments
1 4.50% 7.00% 7.00%
2 5.50% 8.00% 8.00%
3 4.50% 7.00% 8.00% Capitalization rate is the greater of Bank's interest rate plus 2-1/2 percent or previous year's capitalization rate.
4 3.50% 6.00% 8.00% Again, the previous year's capitalization rate is greater than the current interest rate plus 2-1/2 percent.
5 7.50% 10.00% 10.00% This is the first year the interest rate plus 2-1/2 percent is greater than or equal to 10 percent, so subsequent years' capitalization rates will be based on averages.
6 6.50% 9.00% 9.50% The calculation to determine Year 6's capitalization rate is: (10.00% + 9.00%) ÷ 2 = 9.50%, or the average of the previous year's capitalization rate and the current year's interest rate plus 2-1/2 percent. The average would not include years prior to Year 5.
7 5.50% 8.00% 9.17% The calculation to determine Year 7's capitalization rate is: (10.00% + 9.50% + 8.00%) ÷ 3 = 9.17%, or the average of the previous two years' capitalization rates and the current year's interest rate plus 2-1/2 percent. The average would not include years prior to Year 5.
8 6.50% 9.00% 9.42% The calculation to determine Year 8's capitalization rate is: (10.00% + 9.50% + 9.17% + 9.00%) 4 = 9.42%, or the average of the previous three years' capitalization rates and the current year's interest rate plus 2-1/2 percent. The average would not include years prior to Year 5.
9 7.50% 10.00% 9.62% The calculation to determine Year 9's capitalization rate is: (10.00% + 9.50% + 9.17% + 9.42% + 10.00%) ÷ 5 = 9.62%, or the average of the previous four years' capitalization rates and the current year's interest rate plus 2-1/2 percent.
10 8.00% 10.50% 9.64% The calculation to determine Year 10's capitalization rate is: (9.50% + 9.17% + 9.42% + 9.62% + 10.50%) ÷ 5 = 9.64%, or the average of the previous four years' capitalization rates and the current year's interest rate plus 2-1/2 percent.

Chief appraisers also may contact the Comptroller’s Property Tax Division to find out the current year’s capitalization rate.

Table 15 shows the results of dividing the net income per acre by a capitalization rate of 6.40 percent. For example, for pine forest, soil productivity class I, the chief appraiser would divide \$36.44, the net income per acre, by 0.0640, the capitalization rate, to get \$569.38, the productivity value of the average acre of pine forest in soil productivity class I. The chief appraiser should perform these calculations for each forest type and each soil productivity class in the appraisal district.

Step Ten: Apply Timber Values to Timber Acreage within the District

The chief appraiser should apply the per acre values developed in Step Nine to the respective acreages of each parcel of qualified timberland in each forest type and soil productivity class in each taxing jurisdiction.

In determining the forest type and soil productivity class of qualified timberland in the district, the chief appraiser should use maps from one or more of the five official sources listed in Appendix A. As noted earlier in Step One, chief appraisers may use aerial photographs, forest type maps and soil class maps from any governmental source that is recognized as competent to determine soil type, soil capability, general topography, weather, location and any other pertinent factors necessary to classify commercial timberland by forest type and soil type. If the chief appraiser elects to use maps for classifying timberland within his or her district from a data source not listed in Appendix A, the chief appraiser should exercise great care to be certain that the maps are the most current and reliable maps available and that the source of the maps is a competent governmental source.

Endnotes

[5] In its 1992 survey of Texas timber, the USDA Forest Service used sampling methods designed to achieve reasonable sampling errors and reliable estimates at the state level. Future USDA Forest Service surveys of Texas timber may be designed to produce growth estimates that are reliable at the county level. If USDA Forest Service states that its data are reliable at the county level, the comptroller will work with appraisal districts and taxpayers to develop standards for use of county level growth data.
[6] Trees free to grow are those that are not covered by brush or other trees that prevent them from getting the sunlight necessary to grow.
[7] Before using soil type maps, chief appraisers should be certain that the data used to develop the maps are appropriate for classifying soil for timber appraisal purposes.
[8] The site index data compiled by the Natural Resources Conservation Service show virtually no trees with a site index of 110 and above, which is the equivalent of site class 165 and above. Consequently, if the top two USDA Forest Service site classes were kept separate and the two lower site classes were combined, there would be no NRCS data for the "over 165 site class" in most of Texas.
[9] The 1992 survey data are available in two publications. For southeast Texas counties, see John F. Kelly, Patrick E. Miller and Andrew J. Hartsell, Forest Statistics for Southeast Texas Counties – 1992, USDA Forest Service, Southern Forest Experiment Station, New Orleans, LA. Resource Bulletin SO-172, Nov. 1992. For northeast Texas Counties, see John F. Kelly, Patrick E. Miller and Andrew J. Hartsell, Forest Statistics for Northeast Texas Counties – 1992, USDA Forest Service, Southern Forest Experiment Station, New Orleans, LA. Resource Bulletin SO-171, Nov. 1992. When the USDA Forest Service revises the published data, it makes the revisions available to the Texas Forest Service for distribution upon request. Before using any of the Texas survey data, chief appraisers should check with the USDA Forest Service, Southern Forest Experiment Station, Forest Inventory and Analysis Unit in Starkville, Mississippi, or the Texas Forest Service in College Station for revisions.
[10] The Texas Forest Service, located in College Station, maintains Texas Forest survey data collected by the USDA Forest Service.
[11] Effective January 1, 2004, the Tax Code was amended to change the definition of net-to-land for timberland to specify that growth and stumpage values were to be expressed in tons rather than cords or board feet and were to include "large pine sawtimber, small pine sawtimber, pine pulpwood, hardwood sawtimber, hardwood pulpwood, and any other significant timber product."
[12] A "plot" is an area defined by the USDA Forest Service for its survey work.
[13] There are dozens of recognized log rules in use in the United States, and each is based on various assumptions about tree taper, lumber shrinkage, cutting methods, and waste. The two log rules that are of interest to the chief appraiser are the International one-fourth inch – used by the USDA Forest Service – and the Doyle log rule, used by the Texas Forest Service.
[14] Stumpage price is the terminology used to indicate the price of uncut, marketable timber.
[15] The Texas Forest Service also provides summaries of average annual stumpage prices of various forest products for various years. It does not provide data at the county level.
[16] Although the Tax Code, Section 23.51(4), allows the chief appraiser to include "any income received from hunting or recreational leases" in the computation of net income of qualified agricultural land, nothing in the Tax Code's sections (23.71-23.79) governing timber appraisal allows inclusion of lease income in the computation of net income of qualified timberland.
[17] See: Stephen G. Boyce, Joe P. McClure and Herbert S. Sternitzke, Biological Potential for the Loblolly Pine Ecosystem East of the Mississippi River; USDA Forest Service, Southeastern Forest Experiment Station, Ashville, NC. Research Paper SE-142, Oct. 1975.