Forest Mensuration. Brack and Wood
Quantifying site ©
The environmental factors that influence growth include:
Site survey and classification are important in forest management for several reasons:
Site is a useful concept in plantation forestry where it is used to delineate areas of different productivity. The factors which have the greatest bearing on productivity in a region are used in the delineation. As these factors may vary from region to region, the variables used to define site may also vary between regions.
In the context of timber management, site quality can be defined as:
the potential of the site to produce timber given a particular species or forest type.Note in this definition that site quality has meaning only for the species or species composition occurring and being managed at the particular location. Of course, extremes exist which provide absolute limits for all species, e.g. latitudinal and altitudinal range limits for trees.
It is vital that forest managers measure and interpret site reliably because together with stand density, the quality of the site largely controls product size, quantity and value. Thus, it partly determines the investment justified in managing a forest stand. With respect to afforestation policy, reliable site evaluation is of importance for three major purposes:
As site maps are used to determine thinning and related logging priorities, they must be made before the time of first thinning, i.e. at age approximately 9-10 years.
Site quality is not easy to assess. The factors of the site and the plants themselves are interacting and interdependent making it difficult to assign cause and effect relationships.
Much effort has been directed towards investigating environmental characteristics in an attempt to find some single environmental factor to serve as a reliable indicator of site quality. Though this approach is practical, it frequently leaves unassigned a sizable amount of the variation in site.
Site can be evaluated in two general ways:
An evaluation of site from soil characteristics has several advantages:
A common approach is to set up the form equation:
Log H = b0 + b1 x (1/A) + b2 x B + b3 x C + b4 x D + ........+ bn-1 x N where H denotes height; A denotes age; B, C, D, ... N represent soil or other environmental factors (e.g. aspect, slope, elevation, photoperiod, air temperature, thickness of the A horizon, depth to a fine-textured horizon, i.e. any climatic or topographic factor); b0..... bn-1 are the constants to be solved by least squares.
If the standard age for site index (normally 20, 25 or 50 years) is substituted for A, then the equation becomes a site index equation:
Log SI = b1 + b2 x B + b3 x C + b4 x D + .....+ bn-1 x N where SI denotes site index, i.e. Height at standard age the other variables are as above, except that b0 + b1 (1/A) is a constant because age is now constant.
Czarnowski, Humphreys and Gentle (1971) examined dominant site factors for planted Pinus radiata across a range of geographical regions. They derived a complex equation defining site index as a function of humidity, soil cations, mean soil particle size, the proportion of large soil particles, and foliar (and indirectly soil) levels of phosphorus. They considered that their equation embraced the essential and most dominant characteristics determining site index, with the complexity of the functions reflecting the complexity of factors controlling site index. However, this complex approach has not been extended into forest management and yield prediction.
Soil profile descriptions alone can be a useful basis for defining and predicting site particularly in an area of diverse soils (Turvey, 1983). The growth of plantation trees is often observed to vary with changes in the soil profile. In Queensland, Pegg (1967) and Van Altena (1979) used soil physical and hydrological characteristics and soil colour to classify sites for Pinus elliottii and P. caribaea plantations. Turvey (1980) showed in Gippsland, Victoria, that soil map units based on soil profile criteria are strong indicators of significant differences in stand volume production at age 10 years.
Criteria of climate (rainfall, number of cloudy days, number of frosts, mean summer maximum temperature, mean winter minimum temperature, etc.) have been used successfully for broad qualitative classifications of forests, but these are unsuitable for the quantitative classification of forest stands. This simply implies that the effects of soil factors cannot be ignored in site classification.
In forests where a standard, well-established management regime is consistently applied, it is possible to use stand volume information as an indication of site quality. The system used in the Pinus radiata forests of South Australia (Lewis et al., 1976) is an excellent example of such a procedure. The specific statistic used by the South Australians as a measure of site is volume per hectare at age 10 years as determined by systematic survey.
Volume has proved useful for site classification in fully stocked or (what are described as) 'normal' stands. For example, volume MAI at 100 years is suitable for classifying site in some forests of Western Europe which have been intensively managed for a long period.
The capability of a forest site to produce wood (plant matter) at any given time depends on:
Site classification systems based on this concept have proved most successful in relatively undisturbed stands, e.g. northern forest types in Finland and Eastern Canada (extensive forests of a few species), Kaingaroa Plains in N.Z. (Ure, 1959), etc. Ure's system can be used to predict site index for native forest land being evaluated for planting and for inexpensively estimating the site index of established plantations if adjacent undisturbed native vegetation is available, e.g. on fire breaks.
The general applicability of indicator plant systems has several limitations:
In Australia, lesser vegetation is used:-
The relationship of tree height to age, called SITE INDEX, is widely used in evaluating site for even-aged stands or for stands of nearly pure composition.
The popularity of the height/age relationship as a site indicator is that:
The height/age relationship for a site is a sigmoidal curve. The procedure for compiling height/age curves as a basis for classifying site depends on circumstances: If there are no permanent sample plots in the forest:
Another variation, if the trees have annual rings, and if one can assume the present tallest trees have always been the tallest (a reasonable assumption), is to compile height/age histories for the full range of stands by stem analysis.
If the forest is well served with permanent sampling units, and has been for some time, then height/age data should be readily available and the height/age trends should already be known. Therefore, curves can be fitted with confidence to the scatter of points.
The number of site classes to fit to the splay of points depends on the number of classes required or recognised and the range of height at a given age for the range of sites represented.
The 'given age' conventionally is termed standard age (also index age or base age). Standard age must be such that the factors of the site have had an opportunity to express themselves. On the other hand, age must not be so advanced that available data will be too restricted. 20 to 25 years is a common standard age for coniferous plantations in Australia whereas 80 to 100 years is common in Europe. A useful criterion for selecting standard age is 2/3 of rotation age.
Class interval may be determined indirectly by the width of splay at standard age and the number of classes, e.g. South Australia recognises seven classes from SQ I to SQ 7. Alternatively, intervals of some specific width may be nominated, e.g. 5 m. The classes are then called site index classes, e.g. SI 20 covers the range 17.5 m to 22.4 m. The range must be specified.
In the past, site index were fitted manually using one of two methods:
Site index equations may be classified into three types according to the nature of the height/age curves they generate (Clutter et al. 1983), viz.:
|Anamorphic. In this type, the height of any one of the family of curves at any age is a constant proportion of the height of any other curve at the same age.|
|Polymorphic-disjoint. In this type, the proportionality relationship does not hold but the curves do not intersect within the age range of interest.|
|Polymorphic-nondisjoint. In this type, there is no constant proportionality relationship and at least some of the curves cross within the age range of interest.|
The Chapman-Richards function
H = n x [1 - EXP(-pA)]^(1 / (1 - m))
The von Bertalanffy model
H = [n / p x (1 - EXP(-p x (1 - m) x A) )]^(1 / (1 - m))Both of these models can be constrained so that predominant height must equal the value of site index at a specified (= standard) age. For example, constraining the von Bertalanffy model for age 20 years gives:
where H = predominant height (m) A = age (years) n, p, m = coefficients estimated by nonlinear regression.
1 - EXP -p (1-m) A H = S x [ _______________ ] ^ (1/(1-m)) 1 - EXP-p (1-m) 20 where S = site index (predominant height at age 20 years).Transposing this equation enables one to predict site index directly from predominant height and age once coefficients p and m are known:
1 - EXP -p (1-m) A S = H x [ ________________ ] ^ (1/(1-m)) 1 - EXP -p (1-m) 20Ferguson (1979) used the constrained von Bertalanffy model to produce site index curves for P. radiata in the A.C.T. His solution of the model using data available from permanent yield plots was:
H = 1.736 x S x (1-EXP-0.066 x A )^1.792 i.e. S = H / [1.736 x (1-EXP-0.066 x A )^1.792]One question which must be faced in developing site index curves is how many sample stands to select and measure. There is no simple answer to this question. The sample size used in any given situation should reflect the variability of the forest resource (height for age) and the cost of measurement.
All growth intercept methods involve measuring the length of a specified number of successive annual internodes beginning at some well-defined point on the stem, e.g. the first whorl above breast height or above some other specified height, a whorl of known age, etc. If the measurement is over five internodes, it is termed a 5-year intercept.
Growth intercept values can be used directly to assess site quality (called growth intercept indices) or they can be used to calculate site index estimates, e.g.:
Site index = a + b x (5-year intercept).
Growth intercept indices have been found to be particularly useful for classifying site in young stands (Ferree et al. 1958, Wakeley and Marrero 1958, Beck 1971). In older stands, site index is more meaningful Clutter et al. (1983). A stand value for growth intercept is obtained by averaging the individual growth intercept measurements from selected sample trees in the stand. The advantage of the growth intercept method is that stand age is not needed and the length of the required number of internodes is usually easier to obtain than the heights of dominant trees.
The relationship between height and dbh of the dominant trees is sometimes a sensitive and reliable measure of site quality (McLintock and Bickford 1957). Site index, according to this concept, is then defined as the height attained by dominant trees at a standard dbhob. A variant of this concept was applied successfully by Vanclay and Henry (1988) to classify site in indigenous cypress pine (Callitris sp.) in southern Queensland. They defined their index of site as the expected height of a 25 cm dbhob tree predicted from a stand height curve.
There seems little doubt that, in the future, a combination of detailed plot data (CFI), soil data, and phytoecological data (Cajander/Ilvessalo approach) will permit site to be classified more accurately and usefully than is possible at present.
Mon, 14 Apr. 1997