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Rural System's SITE INDEX ESTIMATE, THE SIE

There is much hard work ahead and creative synthesis is badly needed to overcome and include the following critique of past work and assumptions:

Monserud (1984) analyzed the problems with site index growing from work on the topic before 1913 and used for over a century in Europe. They are the reasons why the alpha unit is needed.

1. Height of dominant trees may not (and probably is not) be the best (consistent, etc.) indicator of site potential.
2. Height is influenced by non-site factors such as socking (stem density) and site preparation.
3. Some stands stagnate at high densities (and site indices need a crown competition factor adjustment); space stands grow shorter.
4. Site preparation and prior land use influences site index curve shapes.
5. Brush and vine competition (native and invasives), insects, and small mammals influence growth.
6. It may not be (and probably is not) constant over time. (It is highly variable over time.)
7. Plantations and long-term use can for the same practices cause site index change (degradation). Irrigation and fertilizations can increase the index.
8. Climate does affect site although it is assumed not to do so. (Difficulty of getting and analyzing long-term records prevents it being included.
9. Proper tree selection is often difficulty. Large trees in adequate numbers are rarely available. Great bias in yield curves can result.
10. Good sites do not have the same shape curves as the poor sites.
11. Average site index declines over time, not on a site, but due to the harvests and shortage of old growth stands on high sites.
12. Lumping species is not appropriate when species have different growth curves.
13. Latitude influences growth in height of species and curve shape.
14. Curves differ in excessively and imperfectly drained soils.
15. "Habitat type," a confounding map unit, suggested different site indices for ponderosa pine.
16. The shape of curves, based on the procedure used (e.g., the guide curve method) has been called into question by Monserud. He found that height growth was overestimated by the traditional guide curve method before index age and when underestimated after index age.
17. Site index is not (at least, rarely) connected to a yield table. Simulations are used but most site index as an input.
18. The index concept is difficult to apply in uneven aged stands. As Monserud (1984:174) said, "By definition, site index is almost exclusively an even-aged concept. Only with difficulty can site index be successfully used in a stand that has no single meaningful age."
19. The largest or tallest trees are not necessarily the best indicators of site potential for they have survived early suppression from an older, no-longer-living portion of the stand.
20. Stands may have grossly different volume yields while having the same site index. Basal area growth potential need not be assumed correlated to height growth potential.
21. Trees can be genetically limited in height growth regardless of site quality.
22. Past, not future growth is measured (estimated).
23. It has limited value in natural stands, especially where commercially important species are shade tolerant.

Jones and others have used several factors in combination for they seem interrelated in influencing tree growth:

• land form - (believed to be expressive of the major combination of factors) still to be described and limited among elevation, mean and maximum slope, aspect, latitude,
• "soil" - some select few characteristics
• vegetation - (used as a check or balance) how other trees (especially older ones) and vegetation seem to be doing

Using modern technology and the extensive private library of Lasting Forests, a synthesis of forestry knowledge gained before 1968 has been developed. We combine knowledge of the key factors influencing tree growth to produce the best available estimate of site index for each alpha unit, the fundamental 0.025-acre unit used in most diagnostic and prescriptive work.

Site Index is a widely used index. A tree stand on a poor site may be 50 feet tall; a tree stand on a good site may be 90 feet tall. The height is the site index number. The number of logs in a tree is of primary interest to people interested in wood values (often called "stumpage"). Site index is also a measure that can be related to other factors such as the species of trees that will grow, wild animals, and understory vegetation. Site index has never been very precise. Variation has been high, but few studies have described the likely deviation or error. An index "class", some 5 units (or feet), is usually acceptable. Beck and Trousdell (1973) reported four studies of error conducted before 1973. They thought that site index curves were biased. There has typically been an age and site bias and an assumption that there is a constant curve shape. The result is that site quality is overestimated in the younger stands and underestimated in older (greater than 50) age stands. Underestimation is widespread in available curves, apparently 10 units. Curves are species specific in shape rates of height growth rise rapidly on the best quality sites and then become relatively slow. On poorer sites, growth increases slowly but is maintained. There are may problems in estimating site index, including the trees selected, past site treatments, even the accuracy of aging and tree height measurement.

A measurement called FSQI has been developed with linear categories for several land form influential measures. We prefer to seek non-linear expressions of site quality.

Using geographic information systems, an extensive data base, the work of McCombs (1997), and the older reports of Trimble and Weitzman (1956) and Yawney and Trimble (1968) (who used curves by Schnur (1937), we have begun to create the estimated site index maps for the ridge and valley province of western Virginia.

Smalley described and used land types (the smallest unit of the landscape recognized in his classification system) but now with GIS we do analyses and descriptions for very specific but realistic site areas, the alpha unit (10m x 10m). With GPS we have our location and data do not have to approximate or discriminate among "visually identifiable areas resulting from the same processes."'

These were for the oaks - red, scarlet, black, chestnut, and white oaks. The first map in the series has been dated and designated 1.0. Adjustments are being made in the equations and maps based on them as data are obtained and concepts revised. The estimates that are provided will equal or surpass in accuracy any now used for large area work and will embrace within one site-index class (plus or minus 10 feet) all serious estimates.

Improved rapid tree height measurements, GPS location, and development of non-linear models will improve the site quality estimates.

The equation for the site index estimate resulting in a map of SIE 1.0 is:

SIE = [antilog [1.9702 + 0.0618A + 0.0012P - 0.0025 - 0.1509D]] +K

based on Yawney and Trimble (1968) where:

A = transformed aspect, the sine of the azimuth of slope direction from the southeast (a deviation from the conventional digression from 45 degrees, the northeast) plus 1.0. We have concluded that the published sign of this factor (-) should have been positive as shown here. This change, however, is under investigation. (Aspect may have more than 2 categories - 315 to 135 degrees as North and all others as South).

P = slope position, using the position designations developed by McCombs (1997), was translated as approximate proportion of the distance from the ridge, the slope length. The distance proportions were as follows:

Ridge Top	0	0.025
Summit	5	0.07
Side Slope	60	0.06
Toe Slope	80	0.85
Plateau/Saddle	?	0.70
Floodplain	100	0.95
Rock Outcrop or Talus	?	?

S = slope is expressed as a percent (e.g., where 45 degrees is 100% slope) Approximate slope from 2 to 45 degrees may be most relevant, perhaps transformed by the coefficients of the Universal Soil Loss Factor using slope. "Flat" is a special condition without slope and needs to be analyzed separately. Smalley used percent slope classes of approximately:

1. 0 - 2 Flat or other; Level or Nearly Level
2. 2 - 6 Gently sloping
3. 6 - 10 Sloping
4. 10 - 15 Strongly Sloping
5. 15 - 25 Moderately Steep
6. 25 - 45 Steep
7. + 45 Very Steep

D = the reciprocal of soil depth where... the layer used to estimate D was that for landform (McCombs 1997) and the soil depths were assigned as follows:

• very convex-0.5
• convex - 1.5
• planar sloped surface - 2.0
• planar horizontal surface - 3.0
• concave - 3.5
• very concave - 4.0

Figures 1 and 2 show two areas where the site index has been calculated based.

K = moisture index (developed by Klopfer (1997)) is used to modify the results by up to 5 index points; the higher the moisture index, the greater the SIE.

C = A correction based on Beck and _______ ( ) to adjust for underestimation found in previous work and to adjust for the non-linearity in the models.

Solomon and Leak (1994) found that in New England, at present, potential ranges of the major species (in terms of elevation and regional position as potentially affected by hypothesized temperature changes) appear stable and in alignment with known site requirements.

For relevant comparisons: The number of rings in 1.5-inch radius (Staze, '63).

Literature Cited:

Whittaker, R. H. and W. A. Niering. 1965. Vegetation of the Santa Catalina Mountains of Arizona: a gradient analysis of the south slope. Ecology 46:429-452.

Beck, D.E. and K. B. Trousdell. 1973. Site index: accuracy of prediction. U.S.D.A. Forest Serv. Res. Paper SE-108, Southeastern Experiment Station, Ashville, NC. 7 pp.

Klopfer, S.D. 1997. Insolation, precipitation, and moisture maps for a Virginia geographic information system. M.S. Thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA. 84 pp.

McCombs, J.W. II. 1997. Geographic information system topographic factors maps for wildlife management. M.S. Thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA. 141 pp.

Monserud, R.A., 1984. Problems with site index: an opinionated review, p. 167-180 in J. G. Bockheim, ed., Forest land classification: experiences, problems, perspectives. A symposium, Univ. Wisc., Madison. 276 pp.

Schnur, G.L. 1937. Yield, stand, and volume tables for even-aged upland oak forests. U.S.D.A. Technical Bulletin 560, Washington, D.C. 88 pp.

Schallenberger, A. D. 1966. Food habitats, range use, and interspecific relationships of bighorn sheep in the Sun River Area, West Central Montana. Masters Thesis. Montana State University, Bozeman, Montana. 44 p.

Shoulders, E. and A. E. Tiarks. 1980. Predicting height and relative performance of major southern pines from rainfall, slope, and available soil moisture. For. Sci. 26:437-447.

Solomon, D.S. and W.B. Leak. 1994. Migration of tree species in New England based on elevational and regional analyses, USDA For. Serv. Res Paper NE-688, Northeastern Forest Exp. Station, Radnor, PA, 8 p.

Stage, A. R. 1976. An expression for the effect of aspect, slope, and habitat type on tree growth.For. Sci._22 (4): 457-460.

Swanson, F. 1., T. K. Kratz, N. Caine, and R. G. Woodmansee. '1988. Landform effects on ecosystem patterns and processes: Geomorphic features of the earth's surface regulate the distribution of organisms and processes. Bioscience 38(2)92-98.

Trimble, G.R., Jr. and S. Weitzman. 1956. Site index studies of upland oaks in the Northern Appalachians. Forest Science 2: 162-173.

Yawney, H.W. and G.R. Trimble, Jr. 1968. Oak soil-site relationships in the Ridge and Valley Region of West Virginia and Maryland. U.S.D.A. Forest Service, Research Paper NE-96, Northeastern Forest Experiment Station, Upper Darby, PA, 19 pp.

Jones, S.M. 1988. Old growth forests within the Piedmont of South Carolina. Nat. Areas J. 8:31-37.

Jones, S.M. 1989. Application of landscape ecosystem classification in identifying productive potential of pine-hardwood stands. p. 64-69. In T.A. Waldrop (ed.) Proc. of Pine Hardwood Mixtures: A Symp. on Management and Ecology of the Type. Gen. Tech. Rep., SE.58, Asheville, NC. USDA, Forest Serv., Southeastern Forest Exp. Stn., Atlanta, GA.

Jones, S.M. 1990. Application ofIandscape ecosystem classification within the southeastern United States. p. 79-83. In Proc. 1989 Soc. Am. Foresters Natl. Convention, Spokane, W A.

Jones, S.M., and LA. Churchill. 1987. The use of vegetation in assessing site potential withinthe Upper Coastal Plain of South Carolina. Castanea 52:1-8.

Jones, S.M., and B.R. Smith. 1987. A taxonomic key to soils of the Blue Ridge Mountain and Piedmont Physiographic Provinces in South Carolina. Dep. of Forestry, For. Bull. 53. Clemson Univ., College of Forest and Recreation Resources, Clemson, SC.

Jones, S.M., D.H. Van Lear, and S.K. Cox. 1984. A vegetation-landform classification of forest sites within the Upper Coastal Plain of South Carolina. Bull. Torrey Bot. Club 111(3):349-360.

Myers, R.K., R. Zahner, and S.M. Jones. 1986. Forest habitat regions of South Carolina. Dep. of Forestry, Res. Ser. 42. Clemson Univ., College of Forest and Recreation Resources. Clemson, SC.

Van Lear, D.H., and S.M. Jones. 1987. An example of site classification in the southeastern coastal plain based on vegetation and landtype. S. J. Appl. For. 11:23-28.

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Last revision January 17, 2000.