Informed decisions about land use require estimates of future yields and returns. Yield tables are a convenient way to document likely yields from tree plantations. This paper outlines a pragmatic procedure to compile yield tables for smallholder plantings in Leyte, Philippines

Baynes, Jack S

Vanclay, Jerome K.

Jerome K. Vanclay

Jack Baynes

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Constructing a yield table for smallholder forests

University of Queensland eSpace

14. CONSTRUCTING A YIELD TABLE FOR 
SMALLHOLDER FORESTS 
 
Jerry Vanclay and Jack Baynes 
 
 
INTRODUCTION 
 
Informed decisions about land use require estimates of future yields and returns. Yield tables 
are a convenient way to document likely yields from tree plantations. This paper outlines a 
pragmatic procedure to compile yield tables for smallholder plantings in Leyte, Philippines. 
 
Yield tables were first compiled in Europe about 1787 (Reventlow 1787), but comparable 
forest management guidelines have been in existence for much longer (e.g., the Chinese 
Lung Ch'uan codes). These early yield tables were simple lists indicating the expected 
volume at a given age. Since then, yield tables have become more diverse and 
sophisticated, and modern examples include yield tables that report both total and 
merchantable volumes for a range or site conditions, alignment charts that allow inference of 
volumes to any merchantable limit (e.g., Bruce 1929), and computer simulation packages 
that allow yields to be simulated for diverse silvicultural regimes (Vanclay 1994). However, 
these approaches share the common goal of informing users of the expected timber harvest 
at a given time in the future. For many smallholders, this goal implies simplicity and 
timeliness. This paper outlines how to quickly construct a yield table with limited data. 
Although the resulting yield table should be considered a ‘first approximation’ which should 
be revised as additional data become available, it will nonetheless provide objective data to 
assist landholders and extension officers to make objective decisions about likely returns to 
tree growers. 
 
When sufficient data are available, the construction of a yield table for an established 
industrial plantation owner is a relatively easy matter. Such a yield table can be created by 
measuring the volume per plot on a range of plantings, and fitting a yield function using 
linear regression (Vanclay 1994). This is easy for an established industrial plantation estate, 
where plantings tend to be large, uniformly managed, and confined to a limited range of site 
conditions. Constructing a yield table for smallholder forests in Leyte is more challenging 
because there are few old plantations, and because the large range of site (e.g., geology, 
topography, elevation) and stand conditions (spacing, thinning, fertilizing, pest and control) 
means that yields may vary greatly from one smallholder forest to another. 
 
Obviously, the initial spacing of seedlings has a major effect on their growth rate and the age 
at which they attain a merchantable size. The wide range of different spacings adopted by 
smallholders poses some challenges, but long-standing research into the influence of 
spacing on volume production offers a solution. A series of experiments with conifers in 
Europe (Wiedemann 1932, Langsæter 1941, Møller 1944) and with Eucalypts in South 
Africa (O'Connor 1935) demonstrated that the total woody volume production per hectare is 
relatively unaffected by stand density, for a wide range of density. Thus a yield table based 
on the total woody volume per hectare should be relatively insensitive to the variations in 
stand density observed in smallholder woodlots. 
 
Our interest in not only in the total woody yield, but also in the merchantable yield above a 
specified merchantability limit. Thus, in addition to the yield table, we need a basis for 
estimating the merchantable fraction of the total woody volume production. 
 
 
 107 
Constructing a Yield table for Smallholder Forests 
DATA REQUIREMENTS 
 
An efficient system for predicting future plantation yields requires three components: 
 
1. A yield table to predict gross wood volume at a given age 
2. An adjustment to estimate the merchantable component of individual stems 
3. A system to predict the variation in stem size for a stand of a given stocking. 
 
A yield table can be constructed from observations of yield per hectare for a range of stand 
ages. Obviously, we expect that yields may vary according to site, so it is appropriate to 
stratify according to site quality and/or soil type. In the longer term, repeated measurements 
will reveal the precise stand development trajectory and confirm the adequacy of the 
stratification, but measurements of temporary plots should provide an adequate interim yield 
table. Thus the first approximation to a yield table requires data to be collected on the total 
woody volume per hectare of selected species (e.g., gmelina, mahogany, mangium) in 
stands of known age (Figure 1), within defined strata based on environmental attributes such 
as underlying geology and elevation. 
 
 
0
20
40
60
0 2 4 6Age
V
ol
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e
8
Figure 1. Hypothetical illustration of data used to construct a yield table. 
 
Clearly, the total woody volume is of limited interest. Smallholders considering tree planting 
also need to know the wood volume exceeding a given size limit, that may be saleable to a 
sawmill or logbuyer. Fortunately, it is relatively easy to infer this merchantable fraction of the 
total woody volume. It is well established that tree trunks tend approximate the frustrum of a 
parabola in shape, and this means that the sectional area (i.e., diameter squared) tends to 
vary linearly with position on the stem (relative height). This means that the merchantable 
fraction of a tree can be estimated from the equation: 
 
vm=vt * {1 –(sed/d)2}                                             (1) 
 
where vm is the merchantable volume exceeding a specified small end diameter (sed), and vt 
is the total woody volume of a tree with basal diameter d. For many trees, the diameter 
under bark at stump height d, is approximately the same as the diameter over bark at breast 
height (dbh), and this can be used as an interim measure until a reliable relationship is 
calibrated for this relationship between diameter over bark at breast height and diameter 
under bark at stump height. Similarly, equation (1) is a first approximation, and can be 
replaced with a more sophisticated stem form equation (e.g., Vanclay 1982, Goodwin 2004) 
as data become available. 
 
 108 
Improving Financial Returns to Smallholder Tree Farmers in the Philippines 
In a well-managed even-aged planting where all the trees are approximately the same size, 
equation (1) can be used to estimate the merchantable fraction of the yield predicted in 
Figure 1. However, smallholder stands vary considerably in spacing, and as a result, may 
have wide range of stem sizes (dbh) within any age class, especially in stands with high 
stocking. These stands will have a larger merchantable volume than is indicated by the naive 
application of Figure 1 and Equation 1, because the largest trees have a much larger volume 
than the average tree, while the smaller trees tend to have a slightly smaller volume than the 
average tree. This does not mean that an overcrowded stand will have a higher 
merchantable volume than a well-stocked stand, but that an overcrowded stand may have a 
merchantable volume slightly greater than that indicated by the tree of mean volume. The 
difference is not large, but may influence smallholder decisions, so the yield table should be 
adjusted for the variability within stands. To calibrate this relationship, we simply need to 
examine the diameter distributions gathered during routine inventory in stands with a range 
of stand density. 
 
A further adjustment needs to be made for stem straightness, as a substantial number of 
trees in many smallholder plantings, especially in gmelina plantings, many be too crooked to 
yield any merchantable material. A simple adjustment based on the likely recovery is likely to 
be adequate (Figure 3). 
 
FIELD PROCEDURES 
 
Field inventory should record the diameters of each stem within each inventory plot. Other 
project objectives require that these yield plots be co-located with the biodiversity plots 
(Wardell-Johnson, this volume), and there are operational efficiencies in using compatible 
plot designs. In addition, there are dangers in using rectangular plots of fixed area, as these 
may introduce bias unless carefully aligned with the centre of planted inter-rows. Thus it is 
proposed to sample stands using circular plots of 5 metres radius, and thus 78.5 square 
metres. Many smallholder plantings were established at 1x1 or 1.5x1.5 metre spacings, and 
such a circular plot will involve the measurement of 50 to 75 trees. Although this is a 
relatively large number of trees, it should be achieved quickly and easily in these young 
stands. In older, thinned stands, this plot size is likely to require the measurement of 15 to 25 
trees, an ideal sample size. Mature stands that have been thinned several times may have a 
stand density as low as 400 trees/hectare, and in these situations, it is proposed that the plot 
area should be increased (to 10 m radius) to ensure a sample size of at least 7 trees/plot. 
Thus, in any plot, if a 5 m radius plot fails to include at least 7 crop trees, the radius should 
be doubled to 10 metres. 
 
On each plot, the diameter of each tree should be recorded. Unless a good single-tree 
volume equation is available (Baynes, this volume), it will also be necessary to measure 
upper stem diameters and heights to allow volumes to be inferred. In addition, it would be 
useful to measure the total height of the tallest tree on each plot to assist in the future 
development of site index equations. 
 
 
 109
Constructing a Yield table for Smallholder Forests 
0% 100% 50% 
 
Figure 3. Simple visual adjustment to likely recovery from sections of logs. 
 
At least two plots should be established within each planting selected for sampling. This will 
allow within stand variation to be determined. In plantings covering a larger area, it may be 
appropriate to stratify by age class and site attributes (e.g., soil, slope) and sample within 
each stratum. 
 
The quality of the resulting yield table will depend on the total number and the variability of 
plots sampled, but it is envisaged that thirty sites (for each species; each site with at least 
two plots) should be sufficient, especially if a wide range of ages is sampled. 
 
CONCLUSION 
 
Yield tables can be compiled from data from diverse stands, if the yield table is based on 
total woody volume. Taper equations can be used to generate log assortment tables and 
infer the merchantable volume exceeding a specified small end diameter. 
 
REFERENCES 
 
Vanclay, J.K. (1982), Volume to any utilization standard for plantation conifers in Queensland, 
Queensland Department of Forestry, Research Note No. 36, 8 p. 
Vanclay, J.K. (1982), Stem form and volume of slash pine thinnings in south east Queensland, 
Queensland Department of Forestry, Technical Paper No. 34, 17 p. 
Vanclay, J.K. (1994), Modelling Forest Growth and Yield: Applications to Mixed Tropical 
Forests, CAB International, Wallingford, U.K. xvii+312 p. 
 110 


Constructing a Yield Table for Smallholder Forests

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Constructing a Yield Table for Smallholder Forests

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