Why Do Foresters 
 Always Aim for Their Feet?

Why Do Foresters Always Aim for Their Feet?
(When It Comes to Calculating Tree Value Growth)

I wrote this one mainly to sort out for myself why there is so little good information on tree value growth.  I was just starting to wonder whether the problem might be  more political than technical.

It's a Puzzlement

I've been working as a consulting forester for over 20 years now.  This question has been a continual source of puzzlement.  I recently spent some time in the library going over research papers on tree value growth in an effort to answer this question.  It seems that there are some good reasons for the lack of good information, and some bad reasons too. 

Foresters complain about not getting enough professional respect and not enough compensation for their efforts.  This is analagous to investment advisors who only earn 3-5% for their clients complaining about their lack of recognition and compensation.  These foresters' complaints are particularly ironic when one recognizes that in many cases their clients' forest values really are growing at 10-15% per year, but the foresters just don't realize it!  Foresters are in the dark and pass on the darkness to their clients and the public.

Well-managed hardwood forests in southern New England--and elsewhere in the Northeast and North Central regions--typically grow at 3-5% per year in volume, 3-5% per year in grade value, and 3-5% per year in real market value (Davies 1991, 1996).  When you add up these three ways that trees grow in value, you get 9-15% per year in real (without inflation) value.  Softwood forests tend to grow at slower value rates. 

Trees and forests also produce values such as outdoor recreation, wildlife habitats, scenic amenities, watershed protection and biodiversity protection which are not currently measured by markets, but which likely will be in the future.  The following will explore why foresters tend not to recognize how well they're really doing for their clients.

Good Volume Increase Data

Most of the research studies on tree value growth are based on statewide continuous forest inventory (CFI) data (McCay and DeBald 1972, Arner et al 1990, Buongiorno and Hseu 1993, Strong et al 1995, Niese et al 1995, Hseu and Buongiorno 1997, Reed and Mroz 1997).  These data are from permanent inventory plots which are remeasured every 5-20 years.  Species, diameters, and log heights are recorded, resulting in good data on total tree volume increase. 

Despite these good data, many foresters still use tables like the one below, which has been used for decades to calculate annual rates of growth.  Foresters bore trees, count the rings, and look up the rate of growth in the table.  But the table only measures basal area growth, or growth in two dimensions.  Increases in the merchantable height of trees (third dimension) are not accounted for by this table.  Trees which do not have `height stoppers` such as forks, large limbs, or crooks will increase in volume about 40% faster than the rates in the table (Godman and Mendel 1978, Davies 1991).

                                                                                       Rings per Radial Inch

DBH

4

5

6

7

8

9

10

11

12

13

14

15

4"

28.2%

22.5%

18.8%

16.1%

14.1%

12.5%

11.3%

10.2%

9.4%

8.7%

8.0%

7.5%

6"

18.1%

14.5%

12.1%

10.3%

9.1%

8.0%

7.2%

6.5%

6.0%

5.6%

5.2%

4.8%

8"

13.2%

10.6%

8.9%

7.6%

6.7%

5.9%

5.3%

4.8%

4.4%

4.1%

3.8%

3.5%

10"

10.5%

8.4%

7.0%

6.0%

5.3%

4.7%

4.2%

3.8%

3.5%

3.2%

3.0%

2.8%

12"

8.7%

7.0%

5.8%

5.0%

4.4%

3.9%

3.5%

3.2%

2.9%

2.7%

2.5%

2.3%

14"

7.4%

5.9%

4.9%

4.2%

3.7%

3.3%

3.0%

2.7%

2.5%

2.4%

2.1%

2.0%

16"

6.4%

5.2%

4.3%

3.7%

3.2%

2.9%

2.6%

2.3%

2.1%

2.0%

1.8%

1.7%

18"

5.7%

4.6%

3.8%

3.3%

2.9%

2.5%

2.3%

2.1%

1.9%

1.8%

1.6%

1.5%

20"

5.1%

4.1%

3.4%

2.9%

2.5%

2.3%

2.0%

1.9%

1.7%

1.6%

1.5%

1.4%

22"

4.6%

3.7%

3.1%

2.7%

2.3%

2.1%

1.9%

1.7%

1.5%

1.4%

1.3%

1.2%

Table 1.  Rate of growth/Growth factor table. Adapted from Ashley 1989. 

Fairly Good Market Value Data  

There are some good data on timber market values over the periods between inventory measurements (Dennis 1987, Sendak 1994, Nolley 1994, Luppold and Baumgrass 1995 ).

Even though large year-to-year fluctuations in market prices can occur, sophisticated analysis techniques can smooth these fluctuations and establish trends over longer periods of time.  Trends allow for calculation of rates of value increase.  These rates can be added to the rates of volume increase to more accurately measure tree value growth. 

Although real (without inflation) market stumpage values have increased at about 2% per year for the past 200 years (Rose et al 1988), they did not maintain these historical rates during the 1960's and 1970's (Buongiorno and Hseu 1993).  When the rates for some species started to increase at faster rates in the late 1970's and 1980's, most forest researchers were slow to realize that significant changes were taking place.  Now they recognize that high-grade hardwood stumpage values have been increasing at 4-8% per year in real terms.

Although it may be risky to project increasing price trends into the future, it is undeniable that increasing worldwide demand and decreasing worldwide supply of high grade timber are here to stay--barring some catastrophic change in demographics.  There will always be substitution of other products like plastics and fiber board, but there will always be demand for high grade wood products.

Therefore tree species without `market stoppers` such as difficulty in drying and planing, undistinguished grain, inherent defect, or inherently small size, should continue to increase in market value into the foreseeable future.  Increases should be at least at the historical rates, and possibly much higher.  This is particularly the case for hardwood species which are currently fashionable in furniture, cabinetry and other products.

Fuzzy Grade Value Data

Most trees increase in grade value (or unit value) as they grow into higher grade categories by virtue of increasing the amount of quality lumber that can be obtained from logs.  On high grade trees without `grade stoppers` such as seams, cankers, or knots, this grade value increase factor is equal to or greater than volume growth (Godman & Mendel 1978, Davies 1991, Niese et al 1995, Davies 1996).

Most statewide CFI data do not include tree grades.  But some university and Forest Service research studies have used various Forest Service tree and log grading systems (McCay and DeBald 1972, Strong et al 1995, Reed and Mroz 1997).  None of these grading systems have been accepted for general use by industrial or consulting foresters.  They complain that the Forest Service grading systems are too complicated for field use and don't account for the grade value of large, high quality trees.   

Another big problem with grade value increase data concerns the probabilities that trees of given species, diameters, heights, and grades will grow into higher tree grades with time.  For unmanaged or poorly managed forests, these probabilities can be rather low.  Several studies have dealt with this rather difficult question (Trimble 1965, McCay and DeBald 1972, Ernst and Marquis 1979), but only one study has really approached the question in a systematic manner (Yaussey 1993).

This study was motivated by the need to calculate probabilities of grade increase for the Forest Service's TWIGS computer model of tree growth.  TWIGS and the Tennessee Valley Authority's INFORM program are the only two (out of dozens) of computer programs that have this capability.  Yet even the Yaussey study did not allow for a distinction between managed and unmanaged stands of trees.  This is a serious deficiency in view of the fact that most silvicultural treatments will remove the trees that have lower probabilities for grade value increase, and concentrate growth on trees that do have that capability.

Another recent study has shown that the returns from well-managed stands are enormously higher than those from unmanaged stands (Niese et al 1995).  This study attributed most of the difference to the forester's ability to distinguish the potential for grade value increase among trees, and to eliminate the ones with the low potentials.  Increases in value due to tree grade increase are at least equal to the rates of volume growth, or 3-5% per year.

Emerging Nonmarket Value Data

Trees and forests produce non-timber values such as outdoor recreation, wildlife habitats, scenic amenities, watershed protection and biodiversity protection (van Kooten 1995).  These values may accrue to landowners or to the public--or to both, depending upon how landowners control access to their properties.  Because these values generally do not pass through the market, they are very difficult to measure.  Contingent valuation questionnaires may be used to estimate nonmarket values by gathering data from individuals about their willingness to pay for unpriced goods and services under specific conditions, but contingent valuation is a relatively new and controversial methodology. 

As it is now, there is no compensation to forest landowners for the nonmarket values that they provide to society.  But there are research efforts underway to determine how much it might cost, for example, to buy incentive contracts from landowners to manage their forests for old-growth habitats (Lippke and Fretwell 1997).  These research efforts also try to estimate the value to the public of such incentive contracts by way of job creation from early thinning activities and higher tax revenues from higher value products at harvest.   

Other recent studies have tried to quantify the value of ecosystem services provided by forests and other natural systems (Costanza et al 1997).  Forest ecosystem services include, in addition to the non-timber values indicated above, climate regulation, water cycling, soil formation, nutrient cycling, purification of wastes, carbon fixation and preservation of genetic resources.  Landowners don't get paid for providing these services either, but with better value data in the future, it could happen.  Conservation restrictions designed to maximize these ecosystem services should be eligible for some form of tax deduction.         

Psycho-Social Factors

Foresters tend to be a conservative lot.  They don't like to promise more than they can produce.  Generally speaking, this as is very good characteristic.  But if it causes one to sell oneself and one's clients short, it can become a liability.  There is also the problem of lack of training in financial analysis among foresters.  Such training is necessary to make accurate projections of value increase.  Without the necessary analytical skills, foresters will tend to err on the side of caution.   

Another factor is that, like all professionals, foresters tend to protect the interests of their employers.  They also like to protect their own careers.  In the case of industrial foresters who represent companies that lease land from private landowners, it is not in their companies' interest to inform landowners how fast their trees are growing because this information could motivate landowners to demand higher lease payments. 

In the case of public service foresters, it is not in their interest to have the general public aware of tree value growth because the general public could well ask `Why then do we need to subsidize these landowners with publicly funded forestry services?`  This calculation of self interest may not actually take place on a conscious level among public service foresters, but it probably does influence their thinking in subtle ways.

We all have a lot to learn about nonmarket forest values and ecosystem services.  Measuring and accounting for these values and services will become increasingly important as human populations and environmental impacts increase.  Whether these values will ever show up on the bottom line for forest landowners is unclear, but it will certainly take much longer if foresters are unaware of the latest developments in this field.

Questions and Possible Answers

Would it be possible for consulting and industrial foresters to agree on simple, practical  tree grading systems that would work with all the species and growing conditions that they encounter? Could comprehensive tables of tree grade increase probabilities be created for different species, site indices, and management regimes?  Could the value of preserving or creating old-growth habitats be calculated for different forest types?  Could the value of ecosystem services be calculated for different forest types? 

Could these grading systems and data be incorporated into all computer growth simulation models?  Could forestry schools put more emphasis on teaching students about forest investment analysis and nonmarket values?  Could extension service programs do the same for consulting, industrial and public service foresters? 

Of course the answers to all these questions are `Yes.`  But what would it actually take to make all these things happen?  It seems that the first two questions would have to be dealt with first.  Hopefully the Society of American Foresters and the Association for Consulting Foresters will develop the needed grading systems.  Hopefully Forest Service researchers will find the time and money to put together the needed grade increase probability data.  Hopefully the same will happen for nonmarket and ecosystem service values.

References

Arner, SL, DA Gansner and TW Birch.  1990.  Rate of value change in New England timber stands.  USDA Forest Service Research Paper NE-639.

Ashley, BS.  1989.  Reference Handbook for Foresters.  USDA Forest Service NA-FR-15.

Buongiorno, J and J-S Hseu.  1993.  Volume and value growth of hardwood trees in Wisconsin. Northern Journal of Applied Forestry 10(2):63-69).

Costanza, R, R d'Arge, R de Groot, S Farber, M Grasso, B Hannon, K Limburg, S Naeem, RV O'Neill, J Paruelo, RG Raskin, P Sutton and M van den Belt.  1997.  The value of the world's ecosystem services and natural capital.  Nature 387:253-259.

Davies, K.  1991.  Forest investment considerations for planning thinnings and harvests.  Northern Journal of Applied Forestry 8(3):129-131.

Davies, K.  1996.  Toward more accurate growth simulations and appraisals: Using INFORM to project tree grade and market value increases.  The Compiler 14(1):18-23.

Dennis, DF.  1987.  Rates of value change on uncut forest stands in New Hampshire.  Northern Journal of Applied Forestry 4:64-66.

Ernst, RL and DA Marquis.  1979.  Tree grade distribution in Allegheny hardwoods.   USDA Forest Service Research Note NE-275.

Hseu, J-S and J Buongiorno.  1997.  Financial performance of maple-birch stands in Wisconsin: Value growth rate versus equivalent annual income.  Northern Journal of Applied Forestry 14(2):59-66.

Lippke, BF and HL Fretwell.  1997.  The market incentive for biodiversity.  Journal of Forestry 95(1):4-7.

Luppold, WG and JE Baumgrass.  1995.  Price trends and relationships for red oak and yellow poplar stumpage, sawlogs and lumber in Ohio: 1975-1993.  Northern Journal of Applied Forestry 12(4):168-173.

McCay, RE and PS DeBald.  1972.  A probability approach to sawtimber tree-value projections. USDA Forest Service Research Paper NE-254.

Niese, JN, TF Strong and GG Erdmann.  1995.  Forty years of alternative management practices in second-growth, pole-size northern hardwoods. II. Economic evaluation.  Canadian Journal of Forest Research 25:1180-1188.

Reed, DD and GD Mroz.  1997.  Rate of sawtimber volume and value growth of individual sugar maple trees in managed, uneven-aged stands in the Lake States.  Northern Journal of Applied Forestry 14(2):78-82.

Rose, DW, CR Blum and GJ Brand.  1988.  A guide to forestry investment analysis.  USDA Forest Service Research paper NC-284.

Sendak, PE.  1994.  Northeastern regional timber stumapge prices: 1961-1991.  USDA Forest Service Research Paper NE-683.

Strong, TF, GG Erdmann and JN Niese.  1995.  Forty years of alternative management practices in second-growth, pole-size northern hardwoods. I. Tree quality development.  Canadian Journal of Forest Research 25:1173-1179.

Trimble, GR Jr.  1965.  Improvements in butt-log grade with increase in tree size for six hardwoos species.  USDA Forest Service Research Paper NE-31.

van Kooten, GC.  1995.  Can nonmarket values be used as indicators of forest sustainability?  Forestry Chronicle 71(6):702-711.

Yaussey, DA.  1993.  Method for estimating potential tree-grade distributions for Northeastern forest species.  USDA Forest Service Research Paper NE-670.

Karl Davies
November, 1997