Australian Forestry
Australian Forestry is published by the Institute of Foresters of Australia (IFA) for technical, scientific and profes­
sional communication relating to forestry in Australia and adjacent geographic regions. The views expressed in this
journal are not necessarily those of the IFA. The journal is included in the Register of Refereed Journals maintained
by the Australian Government Department of Education, Science and Training, and as from the first issue in 2008, in
Science Citation Index Expanded (SCIE).
Managing Editor: Dr Colin Matheson
Production Editor: Mr Alan Brown
Editorial Panel: Dr Stuart Davey
Mr Neil (Curly) Humphreys
Dr Grant Wardell-Johnson
Dr Brian Turner
Dr Ian Bevege
Dr Humphrey Elliott
Mr Jack Bradshaw
Dr John Herbohn
Contributions
Contributions to this journal are sought covering any aspect of forest ecology, forest management, forest policy and
land use related to Australia and the South Pacific region. Contributions related to the performance of Australian
tree genera elsewhere in the world are also welcome. Instructions to authors are given inside the back cover of each
issue. Contributions should be sent to the Executive Director at the address below.
Past issues
Full-text copies of the journal for the years 2001–2004 are available to the public on our website,
http://www.forestry.org.au/ifa/f/f15-ifa.asp
Journal subscriptions 2009
A$260 including GST within Australia
A$290 per year in all other countries
The above prices are for hardcopy. For information about options for electronic access and pricing, please contact
the Executive Director at the address below.
All correspondence relating to subscriptions should be addressed to:
Executive Director, The Institute of Foresters of Australia, PO Box 7002, Yarralumla, ACT 2600, Australia.
Phone: 61 2 6281 3992. Fax: 61 2 6281 4693. Email: [email protected] Web: http://www.forestry.org.au
Cover
The front cover features Corymbia hybrids and their parents Corymbia torelliana (cadaga) and C. citriodora subsp.
variegata (spotted gum). The hybrids are promising plantation varieties for subtropical and tropical environments
in the 700 to 1300 mm MAR zone. The development of these hybrids was described by David Lee in Australian
Forestry Vol. 70, pages 11–16. David also selected the photos on the cover.
Main photo (No. 6): In the foreground is one replicate (a five-tree row plot) of a six-year-old Corymbia hybrid
family, with a mean height of 14.8 m and a diameter at breast height over bark (dbhob) of 13.8 cm, on a black earth
soil near Gympie, Queensland. Behind David (standing) is a C. torelliana family with a mean height of 7.7 m and a
dbhob 8.5 cm. The C. citriodora subsp. variegata controls, which were badly damaged by frost, had a mean height
of 7.2 m and a dbhob of 5.8 cm at the same age. (Photo courtesy of Elizabeth Lee.)
Photo 1: Corymbia citriodora subsp. variegata buds developing on a grafted tree in a clone bank at Gympie in
January 2008. (Photo courtesy of David Lee.)
Photo 2: Grafted, potted clone bank established to aid production of Corymbia hybrids. These C. citriodora subsp.
variegata clones are 18 months old and already yielding good quantities of pollen. (Photo courtesy of David Lee.)
Photo 3: Healthy three-year-old Corymbia hybrids (on left of photo) with frost-killed C. citriodora subsp. variegata
on the right. (Photo courtesy of David Lee.)
Photo 4: One of many selected Corymbia hybrid trees harvested at age 3.6 years for evaluation of a range of wood
properties. Coppice that developed on the stumps has been propagated and clonal testing of the hybrids is underway,
with two-year-old clonal trials continuing to demonstrate the early good potential of the hybrids. (Photo courtesy of
David Lee.)
Photo 5: Ends of butt logs from selected 3.6-year-old Corymbia hybrids (diameter range 12–23 cm). These logs
were used to study the wood properties of early-age Corymbia hybrid selections. Properties evaluated included
sawing, splitting and pulping. (Photo courtesy of David Lee.)
ISSN 0004-9158
ACN 083 197 586
Australian Forestry
The Journal of the Institute of Foresters of Australia
Volume 72 Number 1, 2009
ISSN 0004-9158
blank page
blank
Graham Wilkinson
1
Guest editorial
Transparent forestry – seeing is believing
A locked gate on a forest road is a sad symbol of a breakdown in
trust and transparency. Forest managers may need to close their
doors to potential thieves and vandals, but they should not close
their doors to public scrutiny. My role as an independent forest
regulator gives me the privilege to see what is happening ‘beyond
the locked gate’. What I have seen, by and large, is evidence
of good forest practices by dedicated and professional people;
evidence that needs to be transparently available to the public.
Transparency applies equally to forest managers in both the public
and private sectors. Values such as biodiversity, water quality and
yield, amenity and clean air do not respect property boundaries,
and increasingly, neither does the public. Nearly two-thirds of
the complaints investigated by the Forest Practices Authority
in Tasmania each year relate to private property. Neighbours,
local communities and the general public are demanding more
information and evidence of sustainable forest management
across all tenures.
Forest managers in Australia continue to walk precariously
along the tightrope of public opinion in their quest to achieve
a reasonable mixture of environmental, economic and social
outcomes from their forests. Never before has the task seemed so
complex and the operating environment so changeable. It’s fair to
say that decisions about forest management are never fully ‘right’
or ‘wrong’; they are, after all, value judgements made for specific
situations at specific times. Therefore whilst the decisions about
forest management are important, the context within which the
decisions are made is of more enduring importance.
The public will always hold differing views on forest management
and these views will change over time. A good example is the
change in attitudes towards the clearing of native forest for
agriculture and other land use, including plantations. Up until
about the 1970s clearing was actively promoted and subsidised
by governments for economic and social development. This
was followed by a period of governmental ambivalence. Since
the 1990s governments have responded to environmental and
social concerns by imposing increasingly stricter restrictions on
clearing, with severe penalties for unauthorised clearing. These
dramatic changes have occurred within the lifespan of the current
generation of landowners and forest managers. Similar changes
in social attitudes are forcing a rethink on many other aspects of
contemporary forest management, including intensive silviculture
in native forests, smoke emissions from the burning of logging
residues, the use of chemicals and the role and impact of forest
plantations on a range of social and environmental values. What
was right in the past is not necessarily right for the future. Foresters
have an obligation to promote informed discussion about forest
management. However, ultimately it is the community, well
informed or otherwise, that makes the value judgments upon
which forest management must be based.
It is often said that truth is the first casualty of war, and this
is certainly the case in the ongoing war of words over forest
management in parts of Australia. Both sides of the forestry
debate are guilty of using selective information, simplifications
and distortions in their attempt to sway public opinion. However,
what really matters is whether the public has transparent access
to the information and basis upon which decisions are made,
so that they can better understand and judge the validity and
appropriateness of the decisions. Of course it is naïve to think
that most people will go to the trouble of accessing relevant
information before they form an opinion. However, for many it
is important to know that they have a right to information, if only
a few ever fully exercise that right.
A social licence, whether for forestry or any other business, is
only earned by going beyond the minimum requirements of the
law. Socially responsible organisations are those that promote
transparency and accountability in a proactive manner. Relying
upon Freedom of Information legislation is generally a sign of a
failure in transparency and accountability.
So what does this mean for forest managers within both the public
and private sectors? Forest management plans have traditionally
provided the strategic framework for forest management
decisions. They should record what the forest manager knows
about the assets and values of the forest and the supply and demand
for products and services. They should also be upfront about the
limits to the knowledge. Forest management plans should be
developed with public input, with periodic review and reporting
of actual versus planned outcomes. The public has a right to know
not only the outcomes of forest management but also the reasons
for any variations in planned outcomes.
Operational plans are important because they directly affect a
piece of land and its surrounds. Neighbours and other directly
affected parties have a right to information about both the planned
and actual outcomes of forest operations so that they can take
account of any impacts on their land or values. The broader public
also has a right to this information given that many of the values
potentially affected by forest operations, including water values,
biodiversity and air quality, are not vested as private rights or
‘owned’ by the forest manager, but belong to the common good.
This means that operational plans should be publicly available,
together with the planning tools and assessments that provide
the technical basis for the plan. This also places an obligation
on forest managers to monitor and report on the outcomes of
forest operations, including both compliance with the required
standards and the effectiveness of the actions in achieving the
stated objectives of management.
Transparency means making available as much information as
possible, not just glossy summaries. Many forest managers have
Australian Forestry 2009 Vol. 72 No. 1 pp. 1–2
2
Transparent forestry – seeing is believing
shied away from this in the past because of the logistics and cost of
publishing or providing large databases and reports. However, this
is no longer the case with modern electronic media. The challenge
is to manage information so that it can be made readily available
to the public in an efficient and affordable manner. The issue is
one of ethics. Ask not ‘what information should be available?’ but
‘what information should be withheld and for what reason?’.
There are risks involved in being transparent, including the risk of
increased public criticism and penalty if management practices are
revealed to be deficient. However, socially responsible managers
should consider public transparency to be an important adjunct
to the processes of internal review and continuing improvement.
There are far greater risks in not being transparent; raising
suspicions about why information is being hidden and inviting
more adversarial ways of extracting information or opposing
forest management practices for which there may be perfectly
good justification. For example, if the public is denied information
about the success or otherwise of regeneration practices it can
simply assume the worst and accept the myth that logging destroys
forests. In my experience foresters have much to be proud of, and
much to gain from transparent reporting.
I recently attended a forestry workshop within the Asia-Pacific
region where in the context of international concerns about illegal
and unsustainable logging an enlightened Director of Forests
called upon the delegates to find out what was happening in their
forests and to transparently report ‘the good, the bad and the
ugly. It is only through reliable monitoring and reporting systems
that we can properly report on the standards being achieved
and the progress or otherwise that is being made to improve
those standards. Australia, with its long history of formal forest
management has a leadership role to play within the region and we
could set a good example by demonstrating our own commitment
to socially responsible forest management in a fully transparent
and accountable manner.
Graham Wilkinson RPF, FIFA
Chief Forest Practices Officer
Forest Practices Authority
30 Patrick Street
Hobart, Tasmania 7000
Email: [email protected]
What lies beyond the locked gate?
Australian Forestry 2009 Vol. 72 No. 1 pp. 1–2
Dane Thomas, Michael Henson, Bill Joe, Steve Boyton and Ross Dickson
3
Review of growth and wood quality of plantation-grown Eucalyptus dunnii Maiden
Dane Thomas1,3, Michael Henson1, Bill Joe2, Steve Boyton1 and Ross Dickson2
1Forests
NSW, Land Management and Forestry Services, PO Box J19, Coffs Harbour, NSW 2450, Australia
NSW, Land Management and Forestry Services, PO Box 100, Beecroft, NSW 2119, Australia
3Email: [email protected]
2Forests
Revised manuscript received 5 September 2008
Summary
Forests NSW manages Eucalyptus plantations on the north coast
of NSW, Australia, for high-value timber production. One species
increasingly being planted both in Australia and overseas is
Eucalyptus dunnii Maiden. For a species to be considered suitable
for forestry, criteria to be met include successful establishment,
growth and suitability for end use, be that pulp, solid wood or
veneer production.
Historic data from E. dunnii plantations aged from 3 to 34 y
were reviewed. Growth and wood quality using a range of
non-destructive and destructive measurements are reported.
Eucalyptus dunnii typically grew equally well as some alternative
species, although species ranking was affected by the growing
site. Eucalyptus dunnii produced high-quality wood chips with
average pulp yield from three NSW plantations aged 8–10 y
of 53% and 265 kg m–3. This yield is comparable with that of
10-y-old E. globulus plantation material from Tasmania. Wood
density increased with tree age from about 500 kg m–3 at age 10 y
to 600 kg m–3 at age 25 y, and more slowly beyond that age. Many
solid-wood quality traits such as hardness and strength could be
positively correlated with both tree age and basic density. This
has implications for the timber industry as it is intended that
plantation trees will be harvested at younger ages than native
forest trees, but wood quality in such younger material may not
satisfy minimum product performance requirements. However,
trees selected for higher density achieved strength group ratings at
age 9 y that would normally be achieved at age 25–30 y. It is not
known if similar improvements can be made in other wood quality
traits. Quality traits requiring further examination are growth
stresses and endsplitting of logs, and shrinkage of sawn timber.
Collapse (reversible shrinkage) and non-reversible shrinkage are
positively related to wood density, but a greater concern is the high
ratio of tangential shrinkage compared to radial shrinkage. This
ratio, which can be 2.5 or greater in E. dunnii, leads to excessive
distortion in sawn material. It may be possible to reduce overall
wood shrinkage and the ratio of tangential to radial shrinkage, as
well as other unfavourable wood quality traits, through genetic
selection as these traits in related eucalypts (e.g. blackbutt,
E. pilularis) are heritable.
Keywords: plantations; growth rate; wood properties; pulpwood; yields;
wood density; growth stress; modulus of elasticity; hardness; shrinkage;
genetic improvement; Dunn’s white gum; Eucalyptus dunnii
Introduction
Eucalyptus dunnii Maiden (Dunn’s white gum) naturally occurs
in two small disjunct populations on north-eastern New South
Wales (NSW) and south-eastern Queensland, Australia, primarily
on the margins of rainforests (Boland et al. 2006). These sites, at
between 400 m and 650 m altitude, have a mean annual rainfall
of 1100–1500 mm with a summer maximum, and typically fertile
basaltic or alluvial soils (Benson and Hager 1993). Eucalyptus
dunnii has recently gained favour as an alternative plantation
species to E. grandis because it is better suited to drier and or
more frost-prone sites (Darrow 1994; Johnson and Arnold 2000).
This has lead to its establishment mostly on higher-altitude sites
(> 500 m asl), or on lower-lying creek flats prone to frost. In
NSW, Forests NSW (FNSW) has established over 8500 ha, mostly
since 1994. This review uses available data from Australian and
international research to report on growth of plantation-grown
E. dunnii, and the suitability of the plantation-grown wood for a
variety of end uses. Wood properties of plantation-grown E. dunnii
of different ages and of mature E. dunnii from the native forest
resource are reported to illustrate the development of wood
characteristics with tree maturity, and to identify differences
between material from plantations and native forests. We have
included all available data in the figures presented to display
relationships and to compare the characteristics of wood from
Australian plantations of E. dunnii with those of wood grown
elsewhere, but have used only data from NSW (or Queensland if
that was available) plantations for regressions.
Growth
Several trials from NSW were available to examine growth
of E. dunnii including species trials established between 1972
and 1976 on a range of soil types, climate and local within-site
environments that are useful to compare the performance of
E. dunnii with alternative forestry species such as E. pilularis
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Quality of plantation-grown Eucalyptus dunnii
4
and E. grandis (Johnson and Stanton 1993). These trials were
planted at 1111 stems ha–1 (sph) (3 m espacements between and
within rows) and were not thinned during the rotation. The trial
sites include:
• Bulahdelah State Forest (SF) (latitude 32°24′S, longitude
152°15′E), sandstone or mudstone, mean annual rainfall (MAR)
1360 mm, altitude 60 m
• Cascade SF (30°13′S, 152°46′E), siliceous argillates and slates,
MAR 1280 mm, altitude 640 m
• Chichester SF (32°14′S, 151°46′E) carboniferous sediments,
MAR 1550 mm, altitude 800 m
• Yabbra SF (28°32′S, 152°34′E), siltstone or sandstone, MAR
1080 mm, altitude 520 m.
Figure 1 shows diameter over bark at 1.3 m (dbhob) and tree height
of E. dunnii, E. grandis and E. pilularis grown in these species
trials at ages between 14 and 18 y (typically when the last age
measurements were taken) (Johnson and Stanton 1993). The data
show growth was comparable between the three species within a
site, signifying that E. dunnii performs as well as an alternative
species, although site effects existed for all species.
Figure 1 shows growth of E. dunnii at two of these species trials,
at Cascade SF and Chichester SF, in greater detail as these sites
have been used for wood quality assessments. Figure 1 also
shows growth over time for two FNSW E. dunnii progeny trials
planted in 1995 at:
• Boambee SF (30°18′S, 153°03′E), yellow podzolic soils, MAR
1700 mm, altitude 60 m
• Megan SF (30°17′S, 152°47′E), yellow podzolic soils, MAR
1600 mm, altitude of 730 m.
The Boambee SF and Megan SF progeny trials were planted at
1388 sph on rows 3 m apart and 2.4 m apart within the rows.
Both trials were thinned from 1388 sph to 694 at age 4.5 y. The
Boambee SF progeny trial was thinned to 347 sph in late 2007.
These data show growth at the two progeny trials was similar to
that at the earlier-planted species trials, although site effects are
noticeable. Boambee SF is a higher-quality site with predicted
MAI at 20 y of 20 m3 ha–1 compared to 15 m3 ha–1 at Megan SF
(Henson and Vanclay 2004). Growth of 9- and 14-y-old E. dunnii
in Argentina was comparable to these reported values (Marco and
Lopez 1995), but diameter growth of E. dunnii in Brazil aged
8–19 y was almost double that observed in NSW, although height
growth was similar (Trugilho et al. 2005).
Although the growth of E. dunnii in NSW plantations — measured
as diameter, height or volume — is similar to that of other betterknown species such as E. pilularis and E. grandis, ‘growth’ is
only one attribute of a species grown for timber. The end use
of the timber also has to be considered. A study is in progress
to examine potential end uses of E. dunnii from plantations of
various ages — the Boambee SF trial was harvested in 2007 at
age 12 y, and the properties of solid wood, veneer and pulp wood
from this high-performing young stand are being assessed; two
other sites aged 17 y (Newry SF) and 34 y (Cascade SF) were
also harvested in 2007 and similar end uses evaluated. Records
of destructive and non-destructive assessments of growth and
wood quality traits relevant to pulping and solid-wood products
are available for these three sites.
Density
Wood is often characterised by density because this property is
correlated, although perhaps not always causally related, with
many other quality traits. Denser wood tends to be stronger, but
may have greater shrinkage and more checks when dried. Denser
wood contains more wood per unit volume and tends to give a
higher yield of pulp in paper manufacturing. Thus information
about wood density is useful to plantation management.
Overall wood density typically increases with tree age as the
proportion of lower-density material formed early in a tree’s life
is reduced by the formation of higher-density material in older
trees (e.g. de Silva et al. 2004). Basic density of native forest
(a)
(b)
40
35
30
35
Chichester
Cascade
25
20
Buladehlah
15
10
Yabbra
5
0
Chichester
30
Tree height (m)
Diameter breast height (cm)
40
Yabbra
25
Buladelah
20
15
Cascade
10
5
0
0
5
10
15
20
25
30
35
0
10
Age (y)
20
30
40
Age (y)
Figure 1. Mean diameter over bark at 1.3 m (a), and mean tree height (b) at last formal measurement of E. dunnii (open square), E. grandis (open
triangle) and E. pilularis (open circle) from four trials. The measurements of the four trials are encircled. Mean tree growth of E. dunnii over time
for two of these trials at Cascade (solid square) and Chichester (solid diamond) is shown. Mean growth at two E. dunnii progeny trials at Boambee
SF (solid triangle) and Megan SF (solid circle) is shown.
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Dane Thomas, Michael Henson, Bill Joe, Steve Boyton and Ross Dickson
E. dunnii is reported to be 610 kg m–3 (Bootle 2005). These data
would have been based on tests of wood from mature stands. Data
on basic density from 12-mm diametric (bark-to-bark) cores and
whole disks at breast height (1.3 m), and estimates of whole-tree
density, were used to develop a relationship with tree age for
material grown in NSW plantations. Data on plantation-grown
material from NSW and elsewhere shows a trend of increasing
basic density in older trees to about 600 kg m–3 at 25 y, although
there is some variability with method of sampling and or site
with non-NSW sites (predominantly South American) (Ribeiro
and Filho 1993; Marco and Lopez 1995; Calori and Kikuti 1997;
Ferreira et al. 1997; Backman and deLeon 1998; Dickson et al.
2003; Arnold et al. 2004; Henson et al. 2004; Trugilho et al.
2005; Muneri et al. 2007) (Fig. 2). The (log transformed) density
of Australian plantation-grown E. dunnii was highly correlated
with tree age, with a coefficient of determination (R 2) of 0.85,
n = 17.
Basic density (kg m–3)
700
500
400
300
200
0
R 2 = 0.85, n = 17
0
10
20
Pulp characteristics
Site and age can affect pulp yield and quality. Pulp characteristics
of E. dunnii from a number of sites have been evaluated (Table 1).
Eucalyptus dunnii from 8-y-old trees grown at Boambee SF were
easier to pulp, produced 53% screened pulp and had a higher pulp
yield of 277 kg m–3 compared to trees of the same age grown at
Megan SF which produced 50% screened pulp and a pulp yield of
237 kg m–3 (Muneri et al. 2007). Trees at Boambee SF were also
about twice the height and diameter and four times the volume
of trees at Megan SF (Fig. 1). The pulping results at Boambee
SF are similar to both 9-y-old E. dunnii grown at Newry SF in
northern NSW and 12-y-old material from Gympie, Queensland
(Hicks and Clark 2001); and to E. dunnii aged 9 y in South Africa
(Swain et al. 2000) and 4 y in Uraguay (Backman and deLeon
1998). The screened pulp yield of 55% for the 9-y-old Newry site
was higher than 10-y-old E. globulus from Tasmania (Hicks and
Clark 2001). Furthermore Hicks and Clark (2001) rated E. dunnii
from Newry amongst the top three of 23 combinations of species
and sites for value as woodchips based on bulk densities, alkali
requirements and pulp yields, and over 10% better than Tasmanian
export woodchips from native forests.
Site also affected pulp quality, the average fibre length being
longer, 0.86 mm, at Boambee SF than the 0.74 mm at Megan
SF, the latter being similar to results reported from South Africa
(Muneri et al. 2007). This is important as fibre length can affect
paper quality (Wimmer et al. 2002). Silvicultural practices
such as stocking can also affect pulp productivity of E. dunnii
(Ferreira et al. 1997) through, amongst other factors, changes
in pulping characteristics, tree diameter and height growth, and
wood density.
600
100
5
30
Age (y)
Figure 2. Basic density of E. dunnii as a function of tree age. NSW
plantation data were estimated from whole trees (solid diamond),
calculated from disks (small solid circle), or wood cores (solid square).
Data from one Queensland plantation using whole-tree data are shown
(open diamond). The logarithmic regression with a coefficient of
determination of 0.85 was calculated with data from 16 NSW plantations
and one Queensland plantation where density was derived from wood
samples and not Pilodyn needle penetration. Data from overseas
plantations are shown (solid triangle). Density of mature trees from native
forest is shown as a large solid circle plotted as an age of 36 y for the
purpose of graphic display, but was not used in the regression.
Pulp yield of 8-y-old E. dunnii growing at Boambee SF and
Megan SF plantations was recently estimated using near-infrared
spectroscopy (Muneri et al. 2005). This technique offers fast,
cost-effective evaluation of the economic potential of trees. The
predicted values were within 2% of observed values, with high
correlation coefficients. It is recommended that this technique
be tested on other sites and older trees to determine its wider
application.
Table 1. Pulping characteristics of plantation-grown Eucalyptus dunnii, with 10-y-old plantation-grown E. globulus
from Tasmania as a comparison
Plantation location
Age
(y)
Active alkali
(% Na2O)
Pulp yield
(%)
Yield
(kg m–3)
Boambee SF, NSW
Megan SF, NSW
Newry SF, NSW
Gympie, Qld
08
08
09
12
12.8
13.8
12.3
13.9
53.3
50.1
54.8
51.6
277
237
282
276
Muneri et al. 2007
Muneri et al. 2007
Hicks and Clark 2001
Hicks and Clark 2001
South Africa
Uruguay
09
04
NA
14.6
50.3
50.1
256
245
Swain et al. 2000
Backman and deLeon 1998
Tasmania, E. globulus
10
11.5
53.8
268
Hicks and Clark 2001
NA denotes data not available
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Reference
6
Quality of plantation-grown Eucalyptus dunnii
Solid wood
Growth stresses
Solid-wood properties of E. dunnii are in many ways more difficult
to ascertain than density or pulping characteristics. A common
problem of plantation-grown wood as opposed to native forest
material is related to growth stresses. It is generally accepted
among researchers that growth stresses are generated in the
secondary xylem during cell maturation (Jacobs 1938; Kubler
1987). However, theories put forward to explain the generation
mechanism remain controversial and unresolved. Two theories
that have survived to the present day are the ‘lignin swelling’
theory advanced by Boyd (1972, 1985) and the ‘cellulose tension’
theory advanced by Bamber (1979, 1987). Neither theory appears
to apply in all circumstances. More recently, Yamamoto (1998)
introduced a unified hypothesis that incorporated both lignin
swelling and cellulose tensioning, and implicated microfibril
angle (MFA), in generating growth stresses. The lignin swelling
hypothesis became relevant in the region of the cell wall with a
large MFA (i.e. compression wood fibre), whilst the cellulose
tension hypothesis became relevant in the region of the cell wall
with a small MFA (i.e. normal and tension wood fibre).
Regardless of the mechanism of generation, the occurrence of
growth stresses is not in doubt and is thought to be related to the
growth rate of trees; the stresses or stress gradients often decline
with tree age. Excessive growth stresses can result in endsplitting
of logs after they are felled and considerable downgrading of log
quality. Growth stress manifested in the form of endsplitting is
under genetic control in E. dunnii (Anonymous 1999; Swain et al.
2000), which suggests the possibility of using genetic selection
to reduce losses from endsplitting. Silvicultural management
may also affect growth strains and hence endsplitting. Peripheral
growth strains in 9-y-old E. dunnii grown at Boambee SF were
evaluated by Murphy et al. (2005). Growth strain was found to
be heritable, but it was also observed that taller thinner trees had
higher growth strain than short thick trees (Murphy et al. 2005),
suggesting strain may be altered by site and the influences of
silvicultural practices on stem taper.
Growth stresses are also a major concern when processing
timber. It has been estimated that one-third of material sawn from
plantation-grown E. dunnii may suffer degrade attributable to
growth stress (Matos et al. 2003). Similar degrade was reported
in 10-y-old plantation-grown E. globulus, where 30% of boards
were rejected due to excessive distortion and 40% of this distortion
could be attributed to growth stress (Yang et al. 2001, 2002). It
is therefore not surprising that methods have been examined to
reduce losses due to growth stress. Alternative sawing techniques
are available which rely on removing stresses over the entire
log, which increases timber recovery. These techniques have
allowed the successful production of structural timber from young
plantation-grown material of several eucalypts. Additionally
various methods have been used to reduce and release growth
stresses prior to harvest (Malan 1995). Techniques such as
girdling of standing trees, or partial defoliation prior to harvest,
were shown to reduce growth stresses of E. grandis although
variation between trees and decay of girdled trees was excessive
(Malan 1995). Herbicide and radial cuts were most effective in
reducing growth stresses of E. dunnii (Matos et al. 2003). Postharvest steaming treatments prior to milling were also effective
in reducing splitting and other growth-stress-related defects in
E. dunnii (Severo and Tomaselli 2000).
Mechanical properties
Modulus of elasticity (MOE) and modulus of rupture (MOR)
are the principal mechanical properties dictating uses of solid
wood.
Modulus of elasticity
Modulus of elasticity is a measure of stiffness of wood and
has traditionally been determined by static bending of standard
clearwood specimens. It is less of a problem with hardwoods than
softwoods, although juvenile wood from plantation-grown trees
of both may have unacceptable MOE. Static bending MOE in
E. dunnii increased with wood density in five NSW plantations,
but the relationship with tree age was weaker (Fig. 3). Data from
Brazil also show that MOE (measured in tension) increased
with tree age and or wood density (Fig. 3) (Trugilho et al. 2005).
However, wood from these Brazilian plantations had much higher
MOE than that from NSW plantations.
MOE increases over time, although neither tree age nor basic
density was a wholly satisfactory explanatory variable. MOE
is influenced by density and microfibril angle, with that angle
accounting for more variation than density (Evans and Ilic 2001;
Yang and Evans 2003). In combination, density and microfibril
angle can account for over 90% of MOE in plantation eucalypts
(Evans and Ilic 2001; Yang and Evans 2003). The relationship
between MOE and density (Fig. 3a) shows MOE of wood
from mature E. dunnii was higher than predicted using data
from plantation-grown E. dunnii despite having similar basic
density. As microfibril angle typically declines with tree age (e.g.
Lindstrőm et al. 1998; Evans et al. 1999), and as large gains in
MOE are realised with relatively small changes in microfibril
angle (e.g. Yang and Evans 2003), it seems likely that the MOE
of mature native forest material is more influenced by lower
microfibril angle than younger plantation material, despite having
similar basic density.
MOE can also be predicted from acoustic measurements such as
the FAKOPP microsecond timer. Of three acoustic instruments
tested, Henson et al. (2004) found the FAKOPP microsecond
timer gave the most accurate predictions of MOE. MOE of
older E. dunnii plantations predicted using a linear relationship
between MOE and the FAKOPP readings showed MOE to be
greater than 14 GPa in stands aged 12 y or older. This MOE is
similar to that predicted from the relationship between age and
MOE (Fig. 3b).
Management of stem taper may also affect strength of processed
timber as stem taper has also been related, albeit weakly, to
strength of loblolly pine (Pinus taeda L.) solid wood and
veneer (Floyd et al. 2006). It has yet to be determined if similar
relationships exist in eucalypts.
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Dane Thomas, Michael Henson, Bill Joe, Steve Boyton and Ross Dickson
(b)
30
30
25
25
20
20
MOE (GPa)
MOE (GPa)
(a)
15
10
15
10
5
5
0
7
R 2 = 0.63, n = 5
300
400
500
600
R 2 = 0.36, n = 5
0
700
0
5
10
Basic density (kg m–3)
15
20
25
30
35
Age (y)
Figure 3. Modulus of elasticity (MOE) of static bending as a function of basic density (a), and of age (b) of E. dunnii. Material from NSW plantations
(solid square) was used for the linear regressions which had coefficients of determination of 0.63 and 0.36 for the relationship with basic density
and with age respectively. Data from mature trees in native forest are shown as a large solid circle and plotted as an age of 36 y for the purpose of
graphic display, but were not used in the regressions. MOE in tension values of Brazilian material are also included (solid triangle).
Modulus of rupture
Modulus of rupture (MOR) was found to be related to density and
to age in plantation-grown E. dunnii (Fig. 4). Both correlations
were highly positive, with a coefficient of determination of 0.91
for the relationship with basic density and 0.67 for the relationship
with tree age. The MOR data for E. dunnii from mature native
forest (Bootle 2005) were comparable to the experimental data
for plantation wood of similar density (Fig. 4a).
Strength group (SD)
MOR and MOE are the key determinants of quality of solid-wood
products used in structural applications (e.g. floor joists, lintels,
trusses, girders). Under the Australian strength classification
system using AS/NZS2878:2000 (Standards Australia 2000),
species are classified into ‘strength groups’ based on minimum
mean MOR and MOE values. Individual sawn boards are then
assigned stress grades (F-grades) depending on the size and type
of defects present. For seasoned timber, there are eight strength
groups from SD1 to SD8 in descending order of strength. Figure 5
shows the strength grouping of plantation-grown E. dunnii
improving with age. This is an important relationship as it
indicates that the utilisation potential improves with plantation
age. The predictive equation indicates that a tree age of 22 y is
necessary before SD4 is attained, and 30 y for SD3; the latter
corresponds to stress grades from F14 to F27 depending the extent
of strength-reducing characteristics present in the boards. Material
selected from a progeny trial at age 9 y for high density had a
(b)
160
140
140
120
120
MOR (MPa)
MOR (MPa)
(a)
160
100
80
60
80
60
40
40
20
20
0
300
100
2
R = 0.91, n = 5
400
500
600
700
R 2 = 0.67, n = 5
0
0
Basic density (kg m–3)
10
20
30
Age (y)
Figure 4. Modulus of rupture (MOR) of E. dunnii as a function of basic density (a) and of age (b) of NSW plantation material (solid square), and
the regressions calculated using these data. Material from NSW plantations (solid square) was used for the linear regressions which had coefficients
of determination of 0.91 and 0.67 for the relationship of MOR with basic density and with age respectively. Data from mature trees in native forest
are shown as a large solid circle plotted as an age of 36 y for the purpose of graphic display, but were not used in the regressions.
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Quality of plantation-grown Eucalyptus dunnii
8
superior strength group (i.e. SD3) than the general relationship
with plantation age would suggest (i.e. SD5, which corresponds
to stress grades F8 to F17). The general relationship predicts trees
would be 20 y older before a similar SD rating was achieved
in unselected material. It would be assumed that this selected
material would maintain its overall stronger SD rating as it
continues to grow, and that newly established plantations using
genetically improved material could produce better timber at a
younger plantation age.
Hardness
Wood hardness is a measure of resistance to indentation, and
provides an indication to how well the wood in service performs
8
7
SD group
6
5
4
3
2
1
R 2 = 0.84, n = 4
0
0
5
10
15
20
25
30
35
Age (y)
Figure 5. Seasoned strength (SD) group as a function of age for E. dunnii
grown in NSW plantations (solid square) and of 9-y-old material selected
for high density (solid diamond). Only the four data points of nonselected material were used to develop the linear regression which had
a coefficient of determination of 0.84. Data from mature trees in native
forest are shown as a large solid circle plotted as an age of 36 y for the
purpose of graphic display, but were not used in the regression. (Strength
is inversely related to the group category number.)
in relation to wear and marking. It is an important quality trait
for flooring and furniture, but less important for other solid-wood
products. The Janka method (Mack 1979) was used to determine
the hardness values reported here. Phenotypic correlations
between hardness and density of eucalypts including E. dunnii
have been shown to be positive (e.g. Dickson et al. 2003). The
regressions of hardness and density, and hardness and tree age,
using NSW plantation-grown E. dunnii were positive and highly
correlated (Fig. 6). Data from mature E. dunnii and E. dunnii
grown in Brazil agree with these relationships, suggesting
hardness will increase with plantation age because density will
increase with plantation age.
Shrinkage and collapse
It is generally accepted that denser woods will shrink (and swell)
more than lower-density woods as they have proportionately
more cell wall and less lumen (e.g. Kollman and Côté 1977; West
2006). The cell wall of denser wood contains larger amounts of
water such that as water is removed from the cell wall during
drying, the volume of cell wall decreases (i.e. shrinks) by an
equivalent amount. The relationship between basic density and
shrinkage after reconditioning to overcome collapse or reversible
shrinkage during drying for NSW plantation-grown E. dunnii
was positive (Fig. 7). The corresponding values for wood from
mature trees provided by Bootle (2005) generally agree with
those for plantation-grown E. dunnii. Recoverable shrinkage
(collapse) accounted for about 4% tangentially and 1% radially
in this NSW plantation material irrespective of density (or age),
which meant that the relationship between density and shrinkage
was not affected.
Bootle (2005) lists tangential shrinkage of mature native forest
E. dunnii of an unknown age to be 10% and radial shrinkage at
5%, giving a ratio between tangential and radial shrinkage of 2.0.
Lower shrinkage ratios are desirable as cupping of boards during
drying would be reduced with more uniform shrinkage. Older
plantation-grown E. dunnii has shrinkage comparable to that of the
mature trees whose properties are given in Bootle (2005) (Fig. 8).
(b)
8
7
7
Hardness (Janka) (kN)
Hardness (Janka) (kN)
(a)
8
6
5
4
3
2
5
4
3
2
1
1
0
6
R 2 = 0.94, n = 5
300
400
500
600
R 2 = 0.90, n = 5
0
700
0
5
–3
Basic density (kg m )
10
15
20
25
30
35
Age (y)
Figure 6. Hardness of E. dunnii as a function of basic density (a) and of age (b) for NSW plantation material (solid square) and non-NSW data (solid
triangle). The linear regressions were calculated using plantation-grown material from NSW. These regressions had coefficients of determination
of 0.94 and 0.90 for the relationship of hardness with basic density and with age respectively. Data from mature trees in native forest are shown as
a solid circle plotted as an age of 36 y for the purpose of graphic display, but were not used in the regressions.
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Dane Thomas, Michael Henson, Bill Joe, Steve Boyton and Ross Dickson
Tangential shrinkage of 10.2% and radial shrinkage of 6.2% were
found in 20-y-old Brazilian plantation E. dunnii, giving a lower
ratio between tangential shrinkage and radial shrinkage of almost
1.5 (Calori and Kikuti 1997). Shrinkage after reconditioning to
recover collapse of 29-y-old E. dunnii at Chichester, NSW, was
8.4% tangentially and 3.2% radially (Joe, FNSW, unpublished
data), while shrinkage after reconditioning to recover collapse
of 6-y-old E. dunnii was 6.2% tangentially and 2.2% radially
(Joe, FNSW, unpublished data). These shrinkage values are
less than those for the Brazilian trees, but in each case the ratio
between tangential and radial shrinkage was higher at 2.6 for the
29-y-old material and 2.8 for the 6-y-old material. Recoverable
collapse in the NSW plantation material accounted for about 4%
of tangential shrinkage but less than 1% of the radial shrinkage
(Joe, FNSW, unpublished data). Recovery of this collapse could
lead to checking and be detrimental to appearance-grade products
(Harwood et al. 2005).
Shrinkage in 6- and 9-y-old plantation-grown E. dunnii from
NSW has also been examined on 12-mm diametric (bark-tobark) pseudo-cores (Arnold et al. 2004; Bandara 2006; Johnson
FNSW, unpublished report). Total tangential shrinkage before
reconditioning of the 9-y-old material was 17.4% — tangential
shrinkage measured after reconditioning was 7.1% while collapse
was found to be 10% (Bandara 2006). No data were available of
radial variation in these shrinkage or collapse values. However,
Henson et al. (2004) reported tangential and radial shrinkage
of boards — obtained from this material and dried quickly to
(a)
(b)
40
7
35
6
Radial shrinkage (%)
Tangential shrinkage (%)
9
30
25
20
15
10
5
0
5
4
3
2
1
0
300
400
500
600
700
300
400
Basic density (kg m )
500
600
700
Basic density (kg m )
–3
–3
Figure 7. Tangential (a) and radial (b) shrinkage before and after reconditioning of plantation-grown E. dunnii as a function of basic density.
Shrinkage was measured on blocks or boards before reconditioning (solid square) and after reconditioning (open square); or on 12-mm diametric
cores before reconditioning (solid diamond) and after reconditioning (open diamond). Non-NSW data are shown as solid triangle and it is unknown
if this is before or after reconditioning. Data from mature trees in native forest are shown as a large solid circle.
(b)
7
12
6
Radial shrinkage (%)
Tangential shrinkage (%)
(a)
14
10
8
6
4
4
3
2
1
2
0
5
0
5
10
15
20
25
30
35
0
0
5
10
15
20
25
30
35
Age (y)
Age (y)
Figure 8. Tangential (a) and radial (b) shrinkage before and after reconditioning of plantation-grown E. dunnii as a function of age. Shrinkage was
measured on blocks or boards before reconditioning (solid square) or after reconditioning (open square). Non-NSW data are shown as solid triangles
and it is unknown if this is before or after reconditioning. Data from mature trees in native forest are shown as a large solid circle, and plotted as
an age of 36 y for the purpose of graphic display.
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
10
Quality of plantation-grown Eucalyptus dunnii
exacerbate distortion — to be 11.7% and 3.1% respectively. This
corresponds to a ratio of tangential to radial shrinkage of 3.8, a
value higher than in other reports.
The high ratio of tangential to radial shrinkage in wood from
NSW plantations is of concern as sawn material will be under
differential stresses while drying, which may lead to dryingrelated defects such as cupping (Harwood et al. 2005). Harwood
et al. (2005) and Bandara (2006) noted that a high percentage of
boards sawn from 9-y-old material displayed cupping after drying.
Following reconditioning, 27% of these boards had unrecoverable
collapse-related defects on an average of 60% of their length,
while surface checking was visible on less than 0.1% of the board
length (Harwood et al. 2005; Bandara 2006).
It is interesting to note that the higher ratio of tangential to radial
shrinkage in material from NSW plantations is different to that
in material from both the older native forest resource and the
20-y-old plantations in Brazil. This suggests this difference is
not solely related to age of the material. The higher ratio in the
NSW plantation material was due more to proportionally much
lower radial shrinkage in the NSW plantation material than to
differences in tangential shrinkage between the trees from the
three sources. Why NSW plantation material would have less
radial shrinkage is unclear. Differential transverse shrinkage can
be due to many factors including gross anatomical structures such
as cell lumen size or cell wall thickness, or the presence of wood
rays, or more detailed structure such as cell wall microfibril angle,
or composition of the middle lamella (Kollman and Côté 1977).
Clearly the higher ratio of tangential shrinkage to radial shrinkage
of NSW plantation-grown E. dunnii needs to be addressed. Gains
could be made through greater use of improved genetic material as
it has been shown that wood traits are highly heritable, and that in
E. pilularis tangential and radial shrinkage and their ratio is under
genetic control (Pelletier 2006; Raymond et al. 2007).
Shrinkage of wood is a further quality attribute that is correlated
with both growth stress and density. Ten-year-old E. nitens
with low growth stress had less shrinkage (Chauhan and
Walker 2004), while Yang et al. (2002) found a weak negative
relationship between tangential shrinkage and growth stress
of 10-y-old E. globulus. A strong positive relationship existed
between growth stress and the difference in shrinkage between
heartwood and sapwood of E. nitens (Chauhan and Walker 2004).
Shrinkage of E. globulus sapwood was typically low, being about
half that of outer heartwood (Yang and Pongracic 2004). These
shrinkage results may in part be due to differences in density or
extractives content (which act as a bulking agent) between the
outer heartwood and sapwood. It is clear the relationship between
growth stress and shrinkage requires further research.
Conclusion
Wood from E. dunnii plantations shows increasing basic density
as stands age. Basic density was correlated, although perhaps
not causally related, with many other wood quality traits. These
traits, including shrinkage and structural characteristics such as
hardness, MOE and MOR, showed linear increases with both
basic density and stand age. The increasing MOR and MOE
corresponded to increased strength and improved strength group
(SD grade), highlighting the higher quality of denser material from
older stands. As these traits, along with growth characteristics
such as tree volume and diameter, heavily influence end product
recovery and value, it should be realised that plantation-grown
material which is usually harvested at younger ages than trees in
native forest material may be of different quality.
References
Anonymous (1999) Preliminary study of end splitting in young E. dunnii
billets in Boambee family trial. Forests NSW, 5 pp.
Arnold, R.J., Johnson, I.G. and Owen, J.V. (2004) Genetic variation in
growth, stem straightness and wood properties in Eucalyptus dunnii
trials in northern New South Wales. Forest Genetics 11, 1–12.
Backman, M. and de Leon, J.P.G. (1998) Pulp and paper properties
of four-year-old eucalyptus trees for early species selection.
In: Brown, P. (ed.) Proceedings 52nd APPITA Annual General
Conference. Brisbane, 11–14 May 1998. APPITA, Melbourne,
Volume 1, pp. 7–14.
Bamber, R.K. (1979) The origin of growth stresses. Forpride Digest
8(1), 75–96.
Bamber, R.K. (1987) The origin of growth stresses: a rebuttal. IAWA
Bulletin 8, 80–84.
Bandara, K.M.A. (2006) Genetic improvement of solid wood product
value of subtropical eucalypts: a case study of Eucalyptus grandis
and E. dunnii. PhD thesis, Australian National University,
Canberra.
Benson, J.S. and Hager, T.C. (1993) The distribution, abundance and
habitat of Eucalyptus dunnii (Myrtaceae) (Dunn’s white gum) in
New South Wales. Cunninghamia 3, 123–145.
Boland, D.J., Brooker, M.I.H., Chippendale, G.M., Hall, N., Hyland,
B.P.M., Johnston, R.D., Kleinig, D.A., McDonald, M.W. and
Turner, J.D. (2006) Forest Trees of Australia. 5th edition. CSIRO
Publishing, Collingwood, Victoria, Australia, 736 pp.
Bootle, K.R. (2005) Wood in Australia: Types, Properties and Uses.
Second edition. McGraw-Hill, 452 pp.
Boyd, J.D. (1972) Tree growth stresses — part 5: evidence of an origin
in differentiation and lignification. Wood Science and Technology
6, 251–262.
Boyd, J.D. (1985) The key factor in growth stress generation in trees:
lignification or crystallisation? IAWA Bulletin 6, 139–150.
Calori, J.V. and Kikuti, P. (1997) Physical and mechanical properties of
wood from E. dunnii of 20 years of age. In: Conference IUFRO
Sobre Silvicultura e Melhoramento de Eucalyptus. Salvador, Brazil.
Embrapa, Brazil, pp. 321–326.
Chauhan, S.S. and Walker, J. (2004) Relationships between longitudinal
growth strain and some wood properties in Eucalyptus nitens.
Australian Forestry 67, 254–260.
de Silva, J.C., da Oliveira, J.T.S., Tomazello Filho, M., Keinert Junior,
S. and de Matos, J.L.M. (2004) Influence of age and radial position
on the density of the wood of Eucalyptus grandis Hill ex. Maiden.
Floresta 1, 13–22.
Dickson, R.L., Raymond, C.A., Joe, W. and Wilkinson, C.A. (2003)
Segregation of Eucalyptus dunnii logs using acoustics. Forest
Ecology and Management 179, 243–251.
Dickson, R.L., Joe, W., Johnson, D., Austin, S. and Ribton-Turner, F.
(2005) Pre-processing prediction of wood quality in peeler logs
grown in northern New South Wales. Australian Forestry 68,
186–191.
Evans, R. and Ilic, J. (2001) Rapid prediction of wood stiffness from
microfibril angle and density. Forests Products Journal 51,
53–57.
Evans, R., Hughes, N. and Menz, D. (1999) Microfibril angle variation
by scanning X-ray diffractometry. Appita Journal 52, 363–367.
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Dane Thomas, Michael Henson, Bill Joe, Steve Boyton and Ross Dickson
Ferreira, G.W., Gonzaga, J.V., Foelkel, C.E.B., Assis, T.F. de, Ratnieks, E.
and de Silva, M.C.M. (1997) Kraft-anthraquinone pulp properties
of Eucalyptus dunnii obtained from five tree plantation spacings
and compared with commercially planted Eucalyptus grandis and
Eucalyptus saligna. Ciencia Florestal 7, 41–63.
Floyd, S.L., Miltimore, Y.C. and Huang, C-L. (2006) Method of
evaluating logs to predict properties of lumber or veneer produced
from the logs. US Patent US 6,996,497B2.
Harwood, C., Bandara, K., Washusen, R., Northway, R., Henson, M.
and Boyton, S. (2005) Variation in Wood Properties of Plantation
Grown Eucalyptus dunnii Relevant to Solid Wood Products. Project
PN04.3003, Forest and Wood Products Research and Development
Corporation, Melbourne, 37 pp.
Henson, M. and Vanclay, J.R. (2004) The value of good sites and good
genotypes: an analysis of Eucalyptus dunnii plantations in NSW. In:
The Economics and Management of High Productivity Plantations.
IUFRO. 4.04.06 International Meeting. Escuela Politécnica
Superior Universidad de Santiago de Compostela, Lugo, 27–30
September 2004. ISBN 84 609 3061 0. 6 pp.
Henson, M., Boyton, S., Davies, M., Joe, B., Bandara, K., Murphy, T.N.,
Palmer, G. and Vanclay, J.K. (2004) Genetic parameters of wood
properties in a 9-year-old E. dunnii progeny trial in NSW, Australia.
In: Borralho, N.M.G., Pereira, J.S., Marques, C., Coutinho, J.,
Madeira, M. and Tome, M. (eds) Eucalyptus in a Changing World.
11–15 October, Aveiro, Portugal, 83 pp.
Hicks, C.C. and Clark, N.B. (2001) Pulpwood Quality of Thirteen
Eucalypt Species with Potential for Farm Forestry. Publication
01/164, RIRDC, Canberra. 38 pp.
Jacobs, M.R. (1938) The Fibre Tension of Woody Stems, with Special
Reference to the Genus Eucalyptus. Bulletin No. 22, Common­
wealth Forestry Bureau, Australia, 37 pp.
Johnson, I.G. and Arnold, R.J. (2000) Age 3 Year Assessment of
Cooperative SFNSW/CSIRO Eucalyptus dunnii Provenance–
Family Trials in Northern New South Wales. Research Paper 37,
Forest Research and Development Division, State Forests of New
South Wales, Sydney, 28 pp.
Johnson, I.G. and Stanton, R.R. (1993) Thirty Years of Eucalypt Species
and Provenance Trials in New South Wales — Survival and Growth
in Trials Established from 1961 to 1990. Research Paper No. 20.
Forestry Commission of New South Wales, Sydney, 92 pp.
Kollman, F.F.P. and Côté, W.A. (1977) Principles of Wood Science and
Technology. Springer-Verlag, Berlin, Germany, 592 pp.
Kubler, H. (1987) Growth stresses in trees and related wood properties.
Forestry Abstracts 48, 131–189.
Lindstrőm, H., Evans, J.W. and Verrill, S.P. (1998) Influence of cambial
age and growth conditions on microfibril angle in young Norway
spruce (Picea abies (L.) Karst.). Holzforschung 52, 573–581.
Mack, J.J. (1979) Australian Methods for Mechanically Testing Small
Clear Specimens of Timber. CSIRO Division of Building Research
Paper (2nd Series) No. 31.
Malan, F.S. (1995) Eucalyptus improvement for lumber production.
Semonario Internacional de Utiliizacao de Madeira de Eucalypto
para Serraria. In: IPEF, IPT, IUFRO and ESALQ (eds) Anais do
Seminário Internacional de Utilização da Madeira de Eucalipto
para Serraria. São Paulo, Brazil, pp. 1–19.
Marco, M.A. and Lopez, J.A. (1995) Performance of Eucalyptus grandis
and Eucalyptus dunnii in the Mesopotamia region, Argentina. In:
Potts, B.M., Borralho, N.M.G., Reid, J.B., Cromer, R.N., Tibbits,
W.N. and Raymond, C.A. (eds) Eucalypt Plantations – Improving
Fibre Yield and Quality. Proceedings CRCTHF–IUFRO Confer­
ence, Hobart, 19–24 February. CRC for Temperate Hardwood
Forestry, Hobart, pp. 40–45.
11
Matos, J.L.M., Iwakiri, S., da Rocha, M.P., Paim, R.M. and de Andrade,
L.O. (2003) Reduction of growth stress effects in the logs of
Eucalyptus dunnii. Scientia Forestalis 64, 128–135.
Muneri, A., Diado, T. and Henson, M. (2005) Near infrared spectroscopy
calibrations for pulp yield and basic density of 8-year-old Eucalyptus
dunnii using samples from contrasting sites. In: Coghill, R. (ed.)
Proceedings 59th APPITA Annual General Conference. 16–19 May,
Auckland, New Zealand. APPITA, Melbourne, pp. 431–434.
Muneri, A., Daido, T., Henson, M. and Johnson, I. (2007) Variation in
pulpwood quality of superior Eucalyptus dunnii families grown in
NSW. APPITA Journal 60, 74–77.
Murphy, T.N., Henson, M. and Vanclay, J.K. (2005) Growth stress in
Eucalyptus dunnii. Australian Forestry 68, 144–149.
Pelletier, M-C. (2006) Genetic variation in shrinkage properties of
Eucalyptus pilularis (Smith) using increment cores. Honours thesis.
Southern Cross University, Lismore, Australia. 75 pp.
Raymond, C.A., Henson, M., Peletier, M-C., Boyton, S., Joe, W., Thomas,
D.S., Smith, H. and Vanclay, J. (2007). Improving Dimensional
Stability in Plantation-Grown E. pilularis and E. dunnii. Project
PN06.3017, Forest and Wood Products Australia, Melbourne,
68 pp.
Ribeiro, F. de A. and Filho, J.Z. (1993) Variacao da densidade basica
da madeira em especies/procedencias de Eucalyptus spp. IPEF,
Piracicaba 46, 76–85.
Severo, E.T.D. and Tomaselli, I. (2000) Vaporization on the release
of growth stresses in logs of Eucalyptus dunnii from two origin.
Scientia Agraria 1, 29–32.
Standards Australia (2000) Timber – Classification into Strength Groups.
AS/NZS 2878:2000. Standards Australia, Sydney.
Swain, T.L., Gardner, R.A.W. and Chiappero, C.C. (2000) Final Results
of Three ICFR Eucalyptus dunnii Trials in Kwazulu-Natal, South
Africa. ICFR Bulletin series number 02/2000, 15 pp.
Trugilho, P.F., Lima, J.T. and Rosado, S.C.S. (2005) Longitudinal growth
stress in Eucalyptus dunnii Maiden. In: Li Xuiwei, Liu Jing, Gai Yu
and Li Feng (eds) Proceedings of the International Conference on
Plantation Eucalyptus. Zhanjiang, Guangdong, China, November
28–December 1, 2005. Science Press, China, pp. 68–73.
West, P.W. (2006) Growing Plantation Forests. Springer-Verlag, Berlin,
Germany. 304 pp.
Wimmer R., Downes, G.M., Evans, R., Rasmussen, G. and French, J.
(2002) Direct effects of wood chaacteristics on pulp and handsheet
properties of Eucalyptus globulus. Holzforschung 56, 244–252.
Yamamoto, H. (1998) Generation mechanism of growth stresses in wood
cell walls: role of lignin deposition and cellulose microfibril during
cell wall maturation. Wood Science and Technology 32, 171–182.
Yang, J.L. and Evans, R. (2003) Prediction of MOE of eucalypt wood
from microfibrial angle and density. Hotz als Roh-und Werkstoff
61, 449–452.
Yang, J.L. and Pongracic, S. (2004) The Impact of Growth Stress on Sawn
Distortion and Log End Splitting of 32-Year-Old Plantation Grown
Blue Gum. Project PN3.1312, Forest and Wood Products Research
and Development Corporation, Melbourne, 31 pp.
Yang, J.L., Fife, D. and Matheson, A.C. (2001) Growth strain in three
provenances of plantation grown Eucalyptus globulus Labill.
Australian Forestry 64, 248–256.
Yang, J.L., Fife, D., Waugh, G., Downes, G. and Blackwell, P. (2002)
The effect of growth strain and other defects on the sawn timber
quality of 10-year-old Eucalyptus globulus Labill. Australian
Forestry 65, 31–37.
Australian Forestry 2009 Vol. 72 No. 1 pp. 3–11
Failure of Eucalyptus globulus plantations on previously irrigated pasture sites
12
Failure of Eucalyptus globulus (Labill.) plantations on previously irrigated pasture sites
in south-eastern South Australia
D.N. Fife1,2 and M. Michael1
1CSIRO
Forest Biosciences, PO Box 946. Mt Gambier, South Australia 5290, Australia
2Email: [email protected]
Revised manuscript received 19 September 2008
Summary
From the mid-1990s onwards large areas of Eucalyptus globulus
(Labill.) were planted in south-eastern South Australia and
south-western Victoria (the Green Triangle region) on land which
had been under pasture for decades. Within these plantations
some well-defined areas had poor tree growth, and in extreme
cases trees died in circular patches. The geometry of the
affected areas strongly suggested an association with previous
irrigation practices: very clear boundaries separated healthy
and affected trees. Foliar analyses of both healthy and affected
trees indicated adequate levels of most major nutrients (N, P,
K and Ca). There were, however, marked differences in foliar
manganese concentrations. Analysis of soil from previously
irrigated areas showed increased soil bicarbonate concentration
and pH compared to soil from areas with no history of irrigation.
There was a strong negative correlation between soil pH and
DTPA-extractable manganese. Concomitantly, foliar manganese
concentrations decreased significantly to deficient levels as the
soil-extractable manganese decreased. We conclude that the severe
growth problems in E. globulus commonly found in circular
patches of previously irrigated areas are due to acute manganese
deficiency as a result of increased soil pH caused by irrigation
with water containing high levels of bicarbonate. At one site
where pasture grass was analysed, manganese concentration in
pasture was considerably lower than in pasture from unirrigated
areas, suggesting there could be problems in future for other
crops in the region receiving repeated irrigation. The evidence
that the pre-planting history dramatically influenced the growth of
E. globulus plantations is important because plantations were not
irrigated after planting, and areas of current eucalypt plantations
in the region include land which had been under irrigation.
Keywords: plantations; growth; mortality; nutrition; nutrient deficiencies;
irrigation; soil pH; bicarbonates; manganese; Eucalyptus globulus
Introduction
In the Green Triangle region of south-eastern South Australia
(SA) and south-western Victoria, establishment of commercial
plantations of E. globulus started in the mid-1990s. By March
2007, 150 000 ha had been established (Green Triangle Regional
Plantation Committee 2007) on land previously under pasture.
In some plantations, young trees (within 12 mo of planting)
had stunted growth and with small chlorotic leaves. In extreme
cases, patches of trees died. Such adversely affected areas
overlaid circles of land previously irrigated with bore water for
pasture production; trees outside the circles grew normally. The
boundary between healthy and unhealthy areas was sharp and
well delineated.
Two irrigation systems, flood irrigation and centre pivot systems,
are commonly used. Under flood irrigation, water pumped from
underground is allowed to flow over the entire pasture. Under
centre pivot irrigation, water pumped from a central bore is spayed
in a circle by sprinklers mounted on a rotating water supply
line. The circular area covered by one centre pivot unit varies
from about 1 ha to 80 ha. The largest in this study was 80 ha.
The frequency of centre pivot installations and area covered by
irrigation varies from farm to farm, but the area can be up to 60%
of the land surface in some locations.
Based on the distribution of stunted and unhealthy trees and their
location in the paddock, we hypothesised that the irrigation history
of the land had induced changes in the soil, sometimes critically,
which in young eucalypts induced nutrient deficiency or toxicity,
poor tree health and death. This hypothesis was investigated on a
number of farms in the Wattle Range area west of Penola in SA.
After planting E. globulus none of the areas received irrigation.
This investigation is thus a study of the effects of pre-planting
irrigation history on E. globulus. For simplicity of description,
hereafter we refer to areas formerly irrigated (typically circles) as
irrigated and those outside the irrigated areas as unirrigated.
The main objectives were:
• to seek the cause of poor health and growth, chlorosis and often
death of trees by comparing the nutritional status of trees in
adjacent areas with contrasting irrigation histories
• to measure the differences in selected soil properties between
unirrigated and irrigated areas, and link those to the adverse
effects on trees.
Materials and methods
Sites
In the Wattle Range area of south-eastern SA, 50 km west of
Penola, we selected five plantations where significant problems of
tree growth and mortality had been observed. Four sites had been
irrigated by centre pivot and one by flood irrigation (Table 1).
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
D.N. Fife and M. Michael
13
Table 1. Nature of previous irrigation, age, survival and height of trees in selected stands
Site
Nature of prior
irrigation
A
B
C
D
E
Centre pivot
Centre pivot
Centre pivot
Centre pivot
Flood
Survival (%)
Height (cm)
Stand age
(y)
Unirrigated
Irrigated
Unirrigated
Irrigated
1
1
2
2
1
99
95
95
99
95
01
01
50
75
01
200
180
180
200
180
010
010
030
100
010
The soil in the area is described as a humus nomopodsol and
classified as a Short Sand (Stephens et al. 1941). It had an
A1 horizon (0–25 cm) of dark-grey sand with organic matter
decreasing with depth, and light-grey sand to 60 cm. A band
of dark-brown sand overlaid pale-yellow clay extending
from 70 cm.
The type of past irrigation, and age and health of the stands
Records were not available of the duration of the irrigation at all
these sites and the nature of the crop, although most would have
been pasture. However, one of the centre pivot sites (site D) had
been irrigated for 6 mo for a single crop of potatoes and another
(site A) had been irrigated for 12 y under pasture. Irrigation
stopped at least 1 y before planting eucalypts. An example of
the pattern of occurrence of the healthy and unhealthy areas of
plantation can be seen in an aerial photograph of site A (Fig. 1):
the entire area was planted 4 y before this photograph was
taken. In the irrigated circle, all trees have died and many have
disappeared. Isolated stunted trees with chlorotic foliage were
scattered around the margins of the circular area. In sites B, C
and D, unhealthy trees occurred in a similar geometric fashion,
but their survival and growth were not as severely affected as in
site A. At the flood-irrigated site (site E, Table 1) mortality was
very high but some healthy trees were present on mounds that
had been raised between the irrigated bays.
The appearance of recently expanded foliage on affected trees
differed between sites, depending on the severity of the impact.
At the least-affected site (site D) the foliage was as described by
Dell et al. (2001) p. 95 and Fig. 120: margins pale green or yellow
with chlorosis spreading between the lateral veins towards the
midrib. At this site the leaf size was similar to that of leaves at a
similar stage of development in adjacent healthy trees. At the more
severely affected sites the leaves were much reduced in size and
rounded compared to leaves from healthy trees. The margins of
affected leaves at these sites were inevitably necrotic.
Figure 1. Aerial photograph of site A 4 y after planting Eucalyptus
globulus. One-year-old seedlings were planted outside and within the
irrigated circular area (arrows) at the same time. All the trees in the
irrigated areas were seriously unhealthy or have died, leading to the
distinct and sharp difference in vegetation cover. Trees outside the circle
grew well.
surface before sampling. The undisturbed cores were placed in
a plastic bag, sealed and stored in a cool room at 4°C until they
were air-dried and sieved (< 2 mm).
At each site, pairs of plots (each plot 4 m × 4 m) were established
to form five replicate pairs. Each pair of plots had one plot in the
irrigated area and the other in the adjacent unirrigated area. These
plots were used for soil, foliage and grass sampling.
Sampling of eucalypts
Soil sampling
Sampling of grass
Soil was sampled in June from all paired plots. Five soil cores
(0–30 cm soil) were taken at random points using PVC pipe
of 50 mm internal diameter. Grass was removed from the soil
Grasses were sampled from a 50 cm × 50 cm area within each of
the paired plots in site A.
Concurrent with the soil sampling, four recently fully expanded
(juvenile leaves) from three E. globulus trees per plot were
sampled and bulked as a plot sample.
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
14
Failure of Eucalyptus globulus plantations on previously irrigated pasture sites
Water sampling
Nutrient status of eucalypt leaves
At sites A, B, D and E the bore which had supplied irrigation water
was located. A water sample was collected once after flushing the
water line for 15 minutes to ensure the water sample was freshly
extracted from the water table.
The nutrient concentrations in leaves of E. globulus on unirrigated
and irrigated plots are presented in Figure 2. Concentrations of
nitrogen, phosphorus and potassium in trees from irrigated areas
were consistently higher than in trees from unirrigated land (Fig. 2a
to 2c). Differences in concentrations of calcium, sodium, chloride,
magnesium, zinc, copper, iron and boron were small and showed
no consistent effects of irrigation history (Fig. 2d to g, i to l).
Sample processing and analyses
Soil
The soil cores were separated into 0–7.5, 7.5–15 and 15–30 cm
layers. The samples from each layer from the five cores per plot
were mixed and air-dried. A sub-sample was used for the following
measurements for each layer:
• pH and electrical conductivity (EC) in a 1 : 5 soil : water extract
(Rayment and Higginson 1992)
• concentration of K, Ca, Na, Mg and bicarbonate (Rayment and
Higginson 1992)
• Cu, Zn, Mn and Fe in diethylene triamine pentaacetic acid
(DTPA) extracts (Rayment and Higginson 1992).
Leaves and grass
Samples were dried at 70°C, ground, digested and analysed for
N, P, K, Ca, Na and Mg (Lowther 1980) and B, Cu, Fe, Mn and
Zn by inductively coupled plasma spectrometry (ICP). Chloride
was measured by titration with silver nitrate after water extraction
with clarifying agents (Lowther CSIRO unpublished).
Water
Samples were analysed for pH, EC, bicarbonate concentration,
Na, K and Ca and Mg (Rayment and Higginson 1992).
Statistical analysis and data presentation
One-way analysis of variance was used for testing differences in
results between unirrigated and irrigated areas within sites. Figures
in the text and tables are the means of five replications. Values
in brackets following the mean and error bars in figures are the
standard errors of the means for five replications.
There was a marked difference in the concentration of manganese
in leaves (Fig. 2h). Leaves from unirrigated areas had a
concentration of 206.8 mg kg–1 (se = 6.9), whilst those from
irrigated areas had a concentration of 69.7 (44.6) mg kg–1. In
four of the five sites (sites A, B, C and E, Table 2) manganese
concentrations were significantly higher in foliage from un­
irrigated than in that from irrigated areas. For example, at site A in
healthy trees the foliar manganese concentration was 225.2 (18.0)
mg kg–1 compared to 4.9 (1.2) mg kg–1 in leaves of unhealthy
trees growing on irrigated areas. At the site D, which had been
irrigated for the shortest period, there was no significant difference
in manganese concentration between the two areas (Table 2),
somewhat paralleling the results in survival.
Soil properties
The pH of the surface 7.5 cm of soil was significantly lower in
unirrigated soils than in irrigated soils in all sites (Fig. 3a). Values
of pH ranged from 5.5 to 6.4 in unirrigated areas to 6.0 to 7.2
in irrigated areas, an increase of 0.7–1.7 units due to irrigation.
Soil pH did not alter significantly with depth to 30 cm in either
unirrigated and irrigated areas (Fig. 4a) but tended to decrease
with depth.
Electrical conductivity (EC) of surface soil in unirrigated areas
ranged from 0.009 to 0.036 mS cm–1 (Fig. 3b). At all sites EC was
higher in irrigated areas and ranged from 0.015 to 0.056 mS cm–1
(Fig. 3b). EC decreased with depth at all sites and was always
lower from unirrigated areas (Fig. 4b).
Tree survival and growth
The concentration of bicarbonate in the surface soil was
sig­nificantly higher in irrigated areas at all sites except for
site D (Fig. 3c). For example, at site A (Fig. 3c) bicarbonate
con­cen­tra­tion in the surface soil from the unirrigated plot was
7.1 (0.6) mg L–1 compared with 26.1 (3.6) mg L–1 in the irrigated
plot. Bicarbon­ate concentrations decreased with depth at all sites
(Fig. 4c), with concentrations at all depths in previously irrigated
areas being higher than in unirrigated areas.
The areas where tree growth was adversely affected overlaid
precisely the areas formerly irrigated (Fig. 1). An identical
circular pattern was evident at sites A, B, C and D. At site E, the
rectangular blocks of affected trees were within the levee banks
of the flood irrigation system. At A and B the trees were only
12 mo old and tree survival within the irrigated area at the two
sites was just 1% (Table 1). We were unable to find remnants of
dead trees, suggesting that they may have died soon after planting
and may have partly decomposed or blown away. Those which
had survived in the irrigated area were smaller (Table 1). In stark
contrast, trees in the unirrigated areas had grown to 2 m in height
within 12 mo. At site D, which had been irrigated for less than
12 mo, survival was up to 75%.
Extractable manganese concentrations in the soil from irrigated
areas at all sites were lower than in soil from unirrigated areas
(Fig. 3d). At site A, manganese concentration in the unirrigated
plot was 3.24 (0.33) mg kg–1 but only 0.98 (0.07) mg kg–1 in
the irrigated plot (Fig. 3d), a significant difference. At site D,
manganese concentration in the soil from the unirrigated
plot was 3.02 (0.31) mg kg–1, and from the irrigated plot
2.14 (0.28) mg kg–1, a non-significant difference. On average,
the concentration of manganese in surface soil of irrigated areas
was half of that in unirrigated areas. Manganese concentrations
decreased sharply with depth (Fig. 4d) and below the surface soil
there was no difference in manganese concentration of unirrigated
and irrigated soils.
Results
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
D.N. Fife and M. Michael
(a) Nitrogen
(b) Phosphorus
0.3
3.0
1.0
2.5
0.2
2.0
1.0
0.5
0.0
0.0
(f) Chloride
0.3
0.6
0.2
0.5
0.0
0.0
(e) Sodium
0.5
0.4
0.3
0.2
0.1
0.0
(g) Magnesium
0.5
Unirrigated
0.2
0.4
0.6
1.0
0.4
0.1
(d) Calcium
1.5
0.6
1.5
Concentration (%)
(c) Potassium
0.8
2.0
15
Irrigated
0.3
0.1
0.2
0.1
0.0
0.0
Concentration (mg kg–1)
(h) Manganese
250
(i) Zinc
20
2.5
200
16
2.0
150
12
1.5
100
8
1.0
50
4
0.5
10
0
0
0.0
0
(j) Copper
60
(l) Boron
(k) Iron
40
50
30
40
30
20
20
10
0
Figure 2. Concentration of nutrients in foliage of Eucalyptus globulus growing on unirrigated and on irrigated areas. Vertical bars are the standard
errors of the means of the five sites.
Table 2. Manganese concentration in recently expanded leaves of young Eucalyptus globulus
grown on unirrigated and irrigated areas
Concentration (mg kg–1)
Site
A
B
C
D
E
Unirrigated
Irrigated
Average
se
Average
se
225.2
183.3
210.9
201.9
212.6
18.0
14.7
10.0
16.6
28.6
004.9
005.7
005.7
237.8
014.7
01.2
00.7
00.7
22.5
05.8
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
Significance
level
P
< 0.001
< 0.001
< 0.001
ns
< 0.001
Failure of Eucalyptus globulus plantations on previously irrigated pasture sites
8
(a) pH
(b) Electrical conductivity
0.07
Unirrigated
0.06
4
2
0
0.04
0.03
0.02
2
15
10
0.00
0
0.8
3
20
5
(d) Manganese
(e) Copper
6
0
A
B
C
D
0.4
0.0
E
(f) Zinc
5
0.6
4
3
2
0.2
1
(c) Bicarbonate
25
0.01
Cu (mg kg–1)
Mn (mg kg–1)
4
Irrigated
0.05
Zn (mg kg–1)
E. C. (mS cm–1)
pH
6
30
HCO3– (mg L–1)
16
1
A
B
C
Site
D
0
E
A
B
Site
C
D
E
Site
Figure 3. Properties of the surface soil (0–7.5 cm). Vertical bars are the standard errors of the means of five samples from each
site.
Depth (cm)
0
4
(c) HCO3– (mg L–1)
(b) EC (mS cm–1)
(a) pH
5
6
7
8
0.0
1.0
2.0
3.0
4.0
5.0
0
5
5
10
10
15
15
20
20
25
25
(d) Mn (mg kg–1)
0
0
1
2
(e) Cu (mg kg–1)
3
4
0.1
0.2
0.3
0
4
8
12
16
20
(f) Zn (mg kg–1)
0.4
0.5
0
1
2
3
4
Depth (cm)
5
10
15
20
25
Unirrigated
Irrigated
Figure 4. Distribution of soil properties in relation to soil depth. Horizontal bars are the standard errors of the means of the five sites.
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
D.N. Fife and M. Michael
Copper concentrations were lower in soil from irrigated areas
than in soil from irrigated areas (Fig. 3e) but the differences
were not statistically significant. The irrigation history had no
significant effect on the zinc concentration in the surface 0–7.5 cm
soil at any site (Fig. 3f) and was not consistent across sites. Zinc
concentrations decreased with soil depth and were little different
between unirrigated and previously irrigated soils at any depth.
Water
Because irrigation was suspended several years prior to sample
collection the water samples we gathered may not be strictly
representative of the quality of the water used for irrigation,
but given the strong association between some foliage and soil
analyses we chose to examine the properties of water from the
bores, expecting the results to be indicative of water quality and
relativity between sites. The ranges of pH and EC between the
sites were very small; pH ranged from 7.6 to 7.9 and EC from
1.4 to 1.6 mS cm–1. Bicarbonate concentrations ranged from
650 to 780 mg–1 whilst potassium, calcium, sodium and chloride
concentrations ranged from 1.5 to 5.8, 92 to 113, 159 to 168 and
290 to 616 mg L–1 respectively.
Nutrients in grass
At site A, nitrogen concentration in grass from the unirrigated
plot was significantly lower than in grass from the irrigated plot,
1.7 (0.2)% compared to 2.4 (0.2)%. The difference between
phosphorus concentrations was small, 0.42 (0.01)% compared to
0.57 (0.04)%. There was a large and highly significant (P < 0.001)
difference in manganese concentrations, values being 90.2 (6.2)
mg kg–1 from the unirrigated plot and 11.5 (1.0) mg kg–1 from the
irrigated plot. There were statistically insignificant differences in
copper and zinc concentrations. Copper concentrations in grass
from unirrigated and irrigated plots were 3.22 (02) and 2.22 (0.44)
mg kg–1 respectively. Zinc concentrations were 24.2 (1.05) and
22.2 (2.42) mg kg–1.
17
within the range considered adequate for young E. globulus in
plantations (Dell et al. 2001). Concentrations of these nutrients in
adjacent trees on unirrigated areas, where trees grew well, were
lower — suggesting that these nutrients were not limiting growth.
The clearest effects were found in the foliar concentrations of
manganese (Fig. 2). Foliar manganese averaged 207 mg kg–1 in
trees from the unirrigated areas but only 70 mg kg–1 in samples
from irrigated areas. Site A had been irrigated for about 12 y, and
site D for less than 12 mo, both by centre pivot. At site A, there
was a highly significant difference in manganese concentration
in foliage from unirrigated and irrigated areas (225 (18.0) c.f. 4.9
(1.2) mg kg–1, Table 2). At site D, where the irrigation history
was much shorter, the difference in foliar manganese was not
significant, 201.9 (16.6) in unirrigated areas compared with
237.8 (22.5) mg kg–1 in irrigated areas (Table 2). Survival was
also considerably higher at site D than at site A, suggesting a link
between manganese deficiency and poor tree health (Table 1).
Foliar manganese concentrations in samples from irrigated areas
with the exception of site D ranged from 5 to 85 mg kg–1, well
below adequate levels of 90–134 mg kg–1 cited by Dell et al.
(2001) and indicating mild to severe manganese deficiency.
Manganese can exist in the soil in a divalent, trivalent or tetra­
valent form (Mengel and Kirby 1982), the divalent form being
the most important for plant nutrition. This form of manganese
decreases with increasing soil pH above pH 6 (Attiwill and
Leeper 1987; Uren 1999). In this study soil pH was significantly
and negatively correlated with available manganese in the soil
(Fig. 6a), irrigated areas having higher soil pH (Fig. 3a) and less
available manganese (Fig. 3d). The concentration of available
manganese in the soil was in turn significantly correlated with
manganese concentrations in foliage (Fig. 6b). Increased soil pH
has been associated with manganese deficiency in silver fir, with
higher concentrations of oxidised (unavailable) manganese in
soils with pH > 5.2 than in soils with pH < 5.2 (Hiltbrunner and
Flückiger 1996). A strong negative correlation between soil pH and
extractable manganese concentration has also been demonstrated
Relationships between soil properties
The relationships between soil pH and the amount of DTPAextractable copper, zinc, iron and manganese were examined.
Coefficients of determination (r2) between soil pH and these
elements in the soil were 0.002, 0.21, 0.26 and 0.76 respectively. In
contrast, soil pH and DTPA-extractable manganese in the surface
soil were significantly negatively correlated (Fig. 6a).
8
y = 5.505 + 0.098x – 1.158x 2
n = 50
r 2 = 0.79
7
pH
The concentration of bicarbonate in the surface 7.5 cm of soil
was significantly correlated with the pH of soil in that layer
(Fig. 5). Low or undetectable concentrations of bicarbonate were
associated with a soil pH of 6 or less. These were from areas
that had been unirrigated or from site D with a short history of
irrigation. In contrast, soil samples with the highest concentration
of bicarbonate and highest pH came from irrigated areas at the
sites which had previously had most irrigation.
Site A
6
B
C
D
E
Unirrigated
Previously
irrigated
5
0
5
10
15
20
25
30
35
40
Bicarbonate concentration (mg L–1)
Discussion
Foliar concentrations of nitrogen, phosphorus and potassium
within foliage of unhealthy trees at all sites (Fig. 2) were
Figure 5. Relationship between bicarbonate concentration and pH in the
surface soil (0–7.5 cm) of unirrigated and irrigated areas
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
Failure of Eucalyptus globulus plantations on previously irrigated pasture sites
18
Irrigated
r 2 = 0.76
(b)
r 2 = 0.70
300
3
Mn concentration
(mg kg–1) in foliage
Mn concentration
(mg kg–1) in soil
4
Unirrigated
(a)
2
1
0
200
100
0
5
6
7
8
Soil pH
0
1
2
3
4
–1
Mn concentration (mg kg ) in soil
Figure 6. Regressions relating (a) soil pH to the concentration of extractable manganese in the soil, and (b) extractable
manganese in the soil and foliar manganese in Eucalyptus globulus, on areas previously unirrigated and irrigated areas
in an experiment comparing a range of management options in
cropping in mid-northern SA (Xu et al. 2002). Applications of
bauxite sand residue (Gerhardi and Rengel 2001) and limestone
(Bolland et al. 2002), both with a high pH, resulted in increased
soil pH and reduced manganese availability. Fertiliser manganese
sulphate rapidly became unavailable when applied to soils of high
pH (Gerhardi and Rengel 2001).
High soil pH associated with the use of crushed limestone as roadbuilding material has been suggested as the reason for chlorosis of
foliage of mature eucalypts adjacent to roads in south-eastern SA;
the chlorosis can spread through the canopy and ultimately lead
to tree death (Czerniakowski et al. 2006). This disorder, known as
Mundulla Yellows, is a form of lime chlorosis associated with low
levels of micronutrients (Cu, Fe and Mn) and has been reviewed
by Parsons and Uren (2007).
As noted earlier, at each site the area where E. globulus was
adversely affected closely matched the area previously under
the irrigation. Water from the bores at the sites had a pH of 7.8,
compared to 7.6 of water from the confined aquifer (the water
supply for the city of Mount Gambier, Brown et al. 2001) and an
electrical conductivity of 1.6 mS cm–1 compared to 1.3 mS cm–1.
There were, however, very large differences in bicarbonate
concentration — 713 mg L–1 compared to 435 mg L–1 in the
confined aquifer. It is very likely that bore water is the source of
the high levels of bicarbonate in the soil that was irrigated. The
concentration of bicarbonate in the soil and soil pH was highly
and positively correlated (Fig. 5). Irrigation with water containing
high levels of bicarbonate increased soil pH in western Victoria
(Gardner 2004).
In the areas of high soil pH tree survival was very poor, and
the growth of the few remaining trees adversely affected.
The surviving trees on irrigated areas had foliar manganese
concentrations well below deficient levels (Dell et al. 2001). It
is very clear that irrigation history induced a serious problem for
E. globulus growth, although the trees were never irrigated. The
total area affected in this way, however, is a small proportion of
the current estate of E. globulus plantations. Current and planned
areas of E. globulus plantation, however, include many parcels of
land which have been subjected to irrigation, so the extent of the
problem will be much greater than the five sites studied here.
We examined the effect of irrigation on the nutrient concentration
of pasture at only one site. There, the manganese concentration
was 11.5 mg kg–1, a level less than is considered to be deficient
for a range of pasture species (15–20 mg kg–1, Pinkerton et al
1997). To put this potential impact on pasture in perspective, we
note that the area of pastures that are irrigated for crop production
is substantial — 75 000 ha in 1999 (Binks 2000).
We did not study the extent to which the manganese deficiency
encountered here in E. globulus can be corrected by manganese
addition. The latter is unlikely to be a useful option because
soil-applied manganese is likely to be rendered unavailable to
trees in these soils, and repeated foliar sprays are not practicable
in forestry. In the long term the current irrigation practice may
also adversely affect crop production, as manganese deficiency
is a widespread and well known historical problem in SA soils.
It was the first widespread trace element deficiency recorded in
Australia (Reuter et al. 1988).
Although the concentration of copper in E. globulus foliage
was not statistically significantly affected by previous land use,
concentrations in foliage from irrigated areas were lower than
in that from unirrigated areas (Fig. 2j). In both cases copper
concentrations were within deficiency levels (Dell et al. 2001).
Even where tree growth was adequate, copper concentrations
were low. Copper deficiency is a common problem in soils in
the area.
A measure of the sustainability of management practices on soil
used for production is the suitability of the soil for diverse land
uses in response to changing needs of land owners. In this case
the irrigation history clearly induced a serious adverse effect on
the utility of the soil for farm-scale forest plantations.
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
D.N. Fife and M. Michael
Acknowledgements
We acknowledge the assistance of Steven Dawes, previously of
Woakwine Forests, who managed the areas when this matter was
drawn to our attention; and of D. Gritton with aspects of field work
and R. Lowther for advice on chemical analyses. Drs Mendham,
Nambiar and Smethurst provided valuable comments, as has Don
McGuire, Forestry SA, who has also offered much encouragement
to complete this work since the senior author’s departure from
CSIRO. We are also very appreciative of the comments of referees
appointed by Australian Forestry.
References
Attiwill, P.M. and Leeper, G.W. (1987) Forest Soils and Nutrient Cycles.
Melbourne University Press.
Binks, B. (2000) Profile of the South East Irrigation Industry. Report to the
South East Catchment Water Management Board. Primary Industry
and Resources South Australia Technical Report No. 275.
Bolland, M.D.A., Allen, D.G. and Rengel, Z. (2002) Response of annual
pastures to applications of limestone in the high rainfall areas
of south‑western Australia. Australian Journal of Experimental
Agriculture 42, 925–937.
Brown, K.G., Love A.J. and Harrington, G.A. (2001) Vertical
Groundwater Recharge to the Tertiary Confined Sand Aquifer,
South East, South Australia. Department for Water Resources,
South Australia. Report DWR 2001/002, 42 pp.
Czerniakowski, B., Crnov, R., Smith, I.W. and Luck, J.E. (2006) Soil
properties associated with the tree decline ‘Mundulla Yellows’.
Plant and Soil 285, 197–206.
Dell, B., Malajczuk, N., Xu, D. and Grove T.S. (2001) Nutrient Disorders
in Plantation Eucalypts. 2nd edn. ACIAR, Canberra, Monograph
No.74.
Gardner, W.K. (2004) Changes in soils irrigated with saline groundwater
containing excess bicarbonate. Australian Journal of Soil Research
42, 825–831.
19
Gherardi, M.J. and Rengel, Z. (2001) Bauxite residue sand has the
capacity to rapidly decrease availability of added manganese. Plant
and Soil 234, 143–151.
Green Triangle Regional Plantation Committee (2007) Facts and figures.
http://www.gtpantations.org
Hiltbrunner, E. and Flückiger, W. (1996) Manganese deficiency in silver
fir trees (Abies alba) as a reforested site in the Jura mountains
Switzerland: aspects of cause and effect. Tree Physiology 16,
963–975.
Lowther, J.R. (1980) Use of a single sulphuric acid-hydrogen peroxide
digest for the analysis of Pinus radiata needles. Communications
in Soil Science and Plant Analysis 11, 175–188.
Mengel, K. and Kirby E.A. (1982) Principles of Plant Nutrition. 3rd edn.
International Potash Institute, Switzerland, pp. 491–500.
Parsons, R.F. and Uren, N.C. (2007) The relationship between lime
chlorosis, trace elements and Mundulla Yellows. Australian Plant
Pathology 36, 415–418.
Pinkerton, A., Smith, F.W. and Lewis, D.C. (1997) Pasture species.
In: Reuter, D.J. and Robinson, J.B. (eds). Plant Analysis: An
Interpretation Manual. 2nd edn. CSIRO Australia, pp. 545–546.
Rayment, G.E. and Higginson, F.R. (1992) Australian Laboratory
Handbook of Soil and Water Chemical Methods. Inkata Press.
Reuter, D.J. et al. (1988) Trace Elements in South Australian Agriculture.
Department of Agriculture, South Australia. Technical Report No.
139, pp. 20–22.
Stephens, C.G., Crocker, R.L., Butler, B. and Smith, R. (1941) A Soil
and Land Use Survey of the Hundreds of Riddoch, Hindmarsh,
Grey, Young and Nangwarry, County Grey, South Australia. CSIRO
(Aust.) Bulletin No. 142.
Uren, N.C. (1999) Manganese. In: Peverill, K.I., Sparrow, L.A. and
Reuter, D.J. (eds) Soil Analysis : An Interpretation Manual. CSIRO
Australia, pp. 287–294.
Xu, R.K., Coventry, D.R., Farhoodi, A. and Schultz, J.E. (2002) Soil
acidification as influenced by crop rotations, stubble management,
and application of nitrogenous fertiliser, Tarlee, South Australia.
Australian Journal of Soil Research 40, 483–496.
Australian Forestry 2009 Vol. 72 No. 1 pp. 12–19
20
Lyctine hardwood susceptibility
Lyctine susceptibility of selected hardwoods
Laurie J. Cookson1,2, Jenny Carr1, Narelle Chew1 and Jim W. Creffield1
1CSIRO
Materials Science & Engineering, Private Bag 10, Clayton, Victoria 3169, Australia
2Email: [email protected]
Revised manuscript received 7 October 2008
Summary
The lyctine susceptibility of 16 timber species, hybrids and geo­
graphical types was examined in this study. Several of the timbers
had been placed previously in a ‘rarely susceptible’ category,
but such uncertain ratings are not acceptable for standards and
compliance purposes. Timber specimens were exposed to three
species of lyctine beetles in an insectary. New criteria were
developed to divide the problematic ‘rarely susceptible’ species,
including designating a species as non-susceptible if significant
damage was limited to 6 mm depth, as this outer region is routinely
lost upon sawing or peeling. Lyctine-susceptible species were
Erythrophleum chlorostachys, Eucalyptus delegatensis grown
in Tasmania but not Victoria or NSW, Eu. regnans × Eu. obliqua
hybrid, Corymbia nesophila, Eu. fibrosa, Eu. grandis, Eu. crebra,
Eu. argophloia, Eu. dunnii, Eu. regnans from Tasmania and
Eu. saligna. Eu. grandis × Eu. saligna hybrid is probably
lyctine-susceptible as both parent species were susceptible. The
non-lyctine-susceptible species were Eu. cloeziana, Eu. pilularis,
Eu. sieberi and Eu. tetradonta.
Keywords: hardwoods; sapwood; wood borers; lyctine; Lyctus;
Lyctus brunneus; Minthea rugicollis; Lyctus discedens; Eucalyptus;
Erythrophleum; Corymbia
Introduction
The sapwood of certain hardwoods is susceptible to lyctine beetle
damage. The significance of the damage varies according to the
proportion of sapwood present in the timber piece. If the sapwood
band is thin, then a small amount of damage in a structural member
may be tolerated. In New South Wales (NSW) and Queensland,
however, where there is a history of using hardwood species with
thick bands of sapwood, state legislation constrains the sale and
use of lyctine-susceptible timber. Similarly, even minor damage to
appearance-grade products such as flooring and furniture can be
unacceptable and lyctine-susceptible sapwood is not permitted by
AS 2796.2-2006 (Standards Australia 2006). Susceptible timbers
therefore require some form of preservative treatment to enable
greater sawn recovery and utilisation of the hardwood resource.
Most studies on lyctine susceptibility were conducted from the
1940s to 1970s on mature trees that were more than 80 y old
(CSIRO 1950; Fairey 1975). Lyctine susceptibility can vary with
forest location and tree age. For example, Eucalyptus delegatensis
(alpine ash) from Victoria is said to be non-susceptible, while the
same species from Tasmania and NSW has been reported with
varying degrees of susceptibility (Fairey 1975). Creffield et al.
(1995) showed differences in susceptibility between samples of
some regrowth and old-growth Western Australian hardwood
species. More recently, Peters et al. (2002) reviewed the biology
and behaviour of Lyctus brunneus and provided guidelines on
methods for determining lyctine susceptibility.
Significant savings can accrue from using species or timber
sources shown to have non-susceptible sapwood. Treatment costs
can be avoided and the timber will be preservative-free. The main
nutrient for lyctines is starch, which the tree produces to store
energy. Starch content can vary with season. In cool temperate
regions, starch usually accumulates over winter, but at other times
concentrations may be below that needed to support the successful
development of lyctines.
A key aim of the current research was to give more detailed
information on a number of ‘borderline’ timber species that
historically have been termed ‘rarely susceptible’. As the state
acts of Queensland (Timber Utilisation and Marketing Act 1987,
TUMA) and NSW (Timber Marketing Act 1977, TMA), and AS
5604-2005 (Standards Australia 2005b) recognise only susceptible
or non-susceptible categories (and provide clear guidance on
whether to treat the timber with preservatives), better information
was needed on how to classify these borderline species.
The test timbers were exposed to three lyctine beetle species:
Lyctus brunneus which is found Australia wide, and the smaller
species L. discedens and Minthea rugicollis. Results from these
bioassays are presented and the implications for industry are
discussed in this paper.
Materials and methods
While Peters et al. (2002) described the preferred steps in lyctine
testing, resource restrictions for this project necessitated some
short-cuts and variations, as indicated in this section.
Timber sources
The timber species examined were:
Corymbia nesophila (Melville Island bloodwood) from Cape
York, Queensland
Australian Forestry 2009 Vol. 72 No. 1 pp. 20–24
Laurie J. Cookson, Jenny Carr, Narelle Chew and Jim W. Creffield
Erythrophleum chlorostachys (Cooktown ironwood) from Cape
York, Queensland
Eucalyptus argophloia (western white gum) from Queensland
Eucalyptus cloeziana (Gympie messmate) from Queensland
Eucalyptus crebra (narrow-leaved red ironbark) from NSW
Eucalyptus delegatensis (alpine ash) from Tasmania, Victoria and
one collection from NSW
Eucalyptus dunnii (Dunn’s white gum) from NSW and Queens­
land
Eucalyptus fibrosa (broad-leaved red ironbark) from NSW
Eucalyptus grandis (rose gum) from NSW
Eucalyptus pilularis (blackbutt) from NSW
Eucalyptus regnans (mountain ash) from Tasmania
Eucalyptus regnans × Eu. obliqua hybrid from Tasmania
Eucalyptus saligna (Sydney blue gum) from NSW
Eucalyptus sieberi (silvertop ash) from Victoria
Eucalyptus tetradonta (Darwin stringybark) from Cape York,
Queensland
Efforts to obtain authentic Eu. grandis × Eu. saligna hybrid were
unsuccessful.
The initial plan was for forestry collaborators to supply samples
containing sapwood at three-monthly intervals for two years or
until there was earlier demonstration of lyctine susceptibility
(Peters et al. 2002). At each sampling, five trees were to be
sampled from three to four regions throughout the natural
distribution of regrowth or plantation for each timber species.
Regrowth timber from trees in the 25–50-y age group was targeted
as being more representative of the future timber supply than
samples from old-growth trees. Younger trees were examined
when the 25–50-y age group was not available. One problem
encountered with tree sampling was that the number of samples
and the geographical distribution sought were difficult to achieve
for some species. For example, mature trees of Western white
gum (Eu. argophloia) are relatively rare, and most occur in
reserves, so that the level of sampling desired was not possible.
The Victorian alpine fires in early 2003 also rendered some sites
for collection of Eu. delegatensis unsuitable for the trial. At other
times it was difficult for cooperating agencies to roster staff to
the project in the face of competing demands and organisational
changes. Nevertheless in total 777 test specimens, representing
772 different trees, were examined.
Sapwood samples, with heartwood attached, were cut at breast
height as a disc from felled trees (within 48 h of felling). Bark was
removed immediately in the field and the sample forwarded to
CSIRO for air drying. Timber was stored indoors and uncovered,
to avoid mould growth.
Prior to bioassay, the sapwood was spot tested for starch using an
iodine indicator as described in Australian Standard 1604.1-2005
(Standards Australia 2005a). The timber was then cut to obtain
heartwood–sapwood test specimens with dimensions greater
than 100 mm long × 25 mm wide × full sapwood depth. Test
specimens were cut using a tungsten-tipped saw, to prevent
burring and the blocking of vessels (which may inhibit lyctine
oviposition). All test specimens, regardless of the result of the
starch test, were subjected to lyctine bioassay. With each round
of bioassay, jars containing untreated sapwood samples of black
bean (Castanospermum australe) were also prepared as a check
on the viability of the lyctine test cultures.
21
Peters et al. (2002) suggested that a starch test should be used in
the field to determine which timbers to test against lyctines. For
this project, however, all timber samples collected were placed
into bioassay, for two reasons:
• As timber was being collected by many different collaborators it
was not certain that the starch test would be used and interpreted
consistently, which could have lead to some bias in the selection
of samples to be tested.
• Most timber species to be examined in this work were in the
previously-assigned ‘rarely susceptible’ category and as a
consequence we believed that assessment of starch alone may
not have been a reliable indicator of susceptibility of these
species.
Another departure from Peters et al. (2002) is that the diameter of
pores in test samples was not determined. Most Eucalyptus species
have mean pore diameters greater than the 70 µm threshold for
lyctine susceptibility — 46 out of 50 Eucalyptus species examined
by Bamber and Erskine (1965) had mean pore diameters > 70 µm.
Therefore effort was directed towards the bioassay of every test
specimen as the final arbiter on lyctine susceptibility.
Lyctine bioassays
The test specimens including black bean were heated at 60°C
overnight to kill any mites that might be present on the received
timber samples. They were then equilibrated in a conditioned
insectary at 26°C and 70% relative humidity for seven days
prior to inoculation with test insects. Each test specimen was
exposed to not less than 20 unsexed adult beetles of each species
of lyctine (Lyctus brunneus, L. discedens and Minthea rugicollis).
Three lyctine species rather than L. brunneus alone (Peters et al.
2002) were used in the bioassay. This was to avoid any problem
arising from variations between beetle species that might have
affected results for the ‘rarely susceptible’ timbers. Inoculation
with the lyctine species occurred consecutively, each lyctine
species inoculation being separated by two weeks or more. For
each lyctine species, a second inoculation of 20 unsexed adult
beetles was made three weeks after the first inoculation. Therefore,
test specimens were inoculated on six different occasions. The
duration of the tests was at least three months from the time of
the last inoculation.
Ratings
The test specimens were assessed by splitting them longitudinally
and evaluating any larval channelling thereby revealed, using the
following subjective rating system (Creffield et al. 1995; Peters
et al. 2002):
• NS: non-susceptible — no channelling
• S1: slightly susceptible — small amount of larval channelling,
sometimes only 10 mm in length along the vessel. Emergence
holes absent, and frass not expelled from wood
• S2: moderately susceptible — moderate amount of larval
channelling
• S3: highly susceptible — large amount of larval channelling.
Broad frass-packed larval galleries.
Australian Forestry 2009 Vol. 72 No. 1 pp. 20–24
22
Lyctine hardwood susceptibility
Results and discussion
Criteria for susceptibility
In this work a species was considered to be non-susceptible when
all test specimens lacked larval channelling. Further, species of
which a minor percentage of test specimens rated no more than S1
were considered non-susceptible. The S1 rating is light damage,
with no frass discharge from the test specimen and no emergence
holes, indicating that the lyctines had insufficient starch to
continue development and had died. They could not re-infest the
original host specimen nor extend their activity to new wood.
The S1 ratings were often evident only under magnification and
would be largely unnoticeable in service. We also found that
if a timber species had only S1 damage the percentage of test
specimens damaged was also small. For example, the worst rating
we gave to any sample of Eu. tetradonta was S1, and this rating
applied to only 3% of test specimens.
Timber species where any replicate had S2 (moderate) or S3
(heavy) damage through most of the sapwood were considered
susceptible (with the following caveat), even if only one or a few
replicates were involved. The caveat is that if the S2 or S3 damage
was confined to the outer 6 mm of sapwood (and the remainder of
the sapwood was not damaged or had S1 damage only), the timber
was considered non-susceptible. During normal sawmilling, at
least the outer 6 mm of sapwood is lost due to kerf and the need
to have some wood on either side of the blade to provide stability
during sawing. Similarly, when logs are peeled to produce veneer,
the outer 10–15 mm (three log revolutions) is usually removed to
waste (S. Dorries, PAA Newstead, 2007 pers. comm.). For these
examples, iodine tests usually confirmed that significant starch
was present only in the outer sapwood bands. It would be useful
to verify the consistency in industry of the depth of these sapwood
losses during machining. Our finding that susceptibility in some
timber species can vary according to sapwood depth may account
for some of the discrepancies in the rating of certain species by
previous studies. Likewise, sawmills experiencing problems of
differing lyctine susceptibility of the same timber species may
be routinely removing varying depths of outer sapwood during
conversion. Details on the depth of damage to each test specimen
can be found in Cookson et al. (2007).
Susceptibility results
The highly lyctine-susceptible species, C. australe, was included
in the bioassays to check that the lyctine beetles were active. Of
the 78 C. australe test specimens exposed, one had no damage,
nine had slight (S1) damage, five had moderate (S2) damage
and 63 were heavily damaged (S3), confirming the viability of
the lyctine beetles used in the project. The source billet of the
C. australe samples that had little or no damage was checked and
found to contain little starch.
The number of samples received of each timber species is
shown in Table 1. Also shown is whether most trees came from
plantations or natural regrowth.
The results of the lyctine bioassays are shown in Table 1, along
with the recommended susceptibility ratings resulting from this
work. Further discussion of the suggested ratings of some of the
species follows:
• Eucalyptus delegatensis grows in the colder regions of
Tasmania, Victoria and south-eastern NSW (Bootle 2005). In
Table 1. Lyctine susceptibility results and suggested ratings
Timber species and source details
Number of test
specimens
Fraction with
any damage
(%)
Fraction with S2 or S3b
damage deeper than 6 mm
(%)
Suggested ratingc
Er. chlorostachys (PY)
Eu. saligna (R)
Eu. delegatensis, Tas (R)
Eu. regnans × Eu. obliqua, Tas (R)
C. nesophila (PY)
Eu. fibrosa (R)
Eu. grandis (PR)
Eu. crebra (RP)
Eu. argophloia (PRY)
Eu. dunnii (PY)
Eu. regnans, Tas (R)
Eu. delegatensis, mainland (RO)
Eu. pilularis (PR)
Eu. sieberi (R)
Eu. tetradonta (PY)
Eu. cloeziana (PY)
046
002
040
028
067
018
052
040
039
021
024
055
089
091
135
025
100
100
058
057
054
061
037
055
015
043
017
016
011
008
003
000
091
100
052
046
025
017
010
008
008
005
004
000
000
000
000
000
S
S
S
Sd
S
Sd
Sd
Sd
Sd
S
Sd
NSd
NS
NS
NSd
NS
a
a
Tas = trees from Tasmania; P = plantations, R = natural regrowth, with main type listed first; Y = some trees < 20 y old, O = some trees 50–70 y old
See text for explanation of S2 and S3
c
S = susceptible, NS = non-susceptible
d
Differs from AS 5604-2005, or was not listed
b
Australian Forestry 2009 Vol. 72 No. 1 pp. 20–24
Laurie J. Cookson, Jenny Carr, Narelle Chew and Jim W. Creffield
NSW, the species is confined to the southern tablelands and
grows best around Batlow and Tumbarumba (Bootle 1971)
(Fig. 1). The appearance of bark, leaves and fruit of Tasmanian
Eu. delegatensis differs from that of the mainland population
of the species (Boland et al. 1984). CSIRO (1950) listed alpine
ash (Eu. gigantea = Eu. delegatensis) as rarely susceptible, but
the source of the trees that were the basis of this assessment
was not specified. In further research, Fairey (1975) noted that
Eu. delegatensis grown in Victoria was not susceptible, that
trees from NSW were rarely susceptible and that Tasmaniangrown material was susceptible. The current lyctine bioassay
results support the view that mainland and Tasmanian
populations are different, as Tasmanian Eu. delegatensis was
readily damaged, whereas using the new criteria suggested
here, Victorian-grown material should remain listed as nonsusceptible. Only five trees from NSW were sampled, and all
were non-susceptible. Due to close proximity (Fig. 1), NSWand Victorian-grown Eu. delegatensis probably mix genetically
and could be considered the one population. Therefore, based
on existing information, mainland-grown Eu. delegatensis
should be considered non-susceptible, while Tasmanian-grown
Eu. delegatensis is susceptible.
• Eucalyptus regnans grows naturally in the mountainous regions
of Tasmania and eastern Victoria (Bootle 2005), while Eu.
obliqua (messmate) also grows in Tasmania, Victoria and the
tableland districts of NSW and southern Queensland (Bootle
2005). Eu. obliqua is known to be lyctine susceptible (AS
5604-2005). The Eu. regnans × Eu. obliqua hybrid came from
Tasmania where the appearance of the tree closely resembles
that of Eu. regnans (P. Bennett, FIAT Hobart, 2006 pers.
comm.), while anatomically the timber looks more like Eu.
obliqua (J. Ilic, CSIRO Clayton, 2006 pers. comm.). Boland et
al. (1984) noted that ‘in southern Victoria and parts of Tasmania
gum-topped forms intermediate between Eu. regnans and Eu.
obliqua are not uncommon’. The method used to collect samples
of Eu. regnans rather than hybrids for the current study was to
obtain the material from higher altitudes (where Eu. obliqua
does not occur) in areas regenerated after wildfire without
23
supplementary aerial sowing (P. Bennett, FIAT Hobart, 2006
pers. comm.). The bioassay found that 46.4% of hybrid test
specimens from Tasmania had lyctine damage, while only one
test specimen (4.2% of those collected) of Eu. regnans from
Tasmania had significant (S3) damage. Results were sufficient
to consider both timbers lyctine susceptible, although further
study on the differences between these timbers seems warranted.
Note that Eu. regnans from the mainland is non-susceptible (as
for Eu. delegatensis). Potentially, non-susceptible Eu. regnans
could be distinguished and also separated from hybrid material
at the sawmill by testing logs for the presence of starch.
• Eucalyptus argophloia grows naturally in a small area northeast of Chinchilla in south-eastern Queensland, from Burncluith
to Burra Burri (Boland et al. 1984). It is a potential plantation
species for Queensland and parts of NSW, and its lyctine
susceptibility is not listed in AS 5604-2005. No specimens from
25–50-y old trees of Eu. argophloia from Queensland collected
on three separate occasions were lyctine susceptible, which
supports the finding from the iodine test that these specimens
had starch contents that were low or not detectable. However,
many test specimens from young plan­ta­tions (trees 8 and 12 y
old) had medium or high starch contents and several were
lyctine susceptible. It is not known if this difference is due to
tree age, different growing locations or month of collection.
• Eucalyptus grandis grows naturally along the east coast of
NSW from the Hunter River to northern Queensland (Bootle
2005). It has been listed in AS 5604-2005 as not susceptible to
lyctines. CSIRO (1950) considered that Eu. grandis was rarely
susceptible, as did Fairey (1975). Only 5 out of 52 specimens
(9.6%) of Eu. grandis had significant S2 or S3 damage, yet this
is sufficient to consider the species lyctine susceptible. There
appears to be some potential for avoiding lyctine-susceptible
sapwood in this species by selecting the month of harvest. The
highest proportion of susceptible Eu. grandis specimens was
harvested in September, although some level of susceptibility
continued for the remaining months and into February (Fig. 2).
Humphreys and Humphreys (1966) found that the starch content
of Eu. grandis also peaked in spring and early summer. We
attempted to investigate the susceptibility of hybrid Eu. grandis
× Eu. saligna but unfortunately authentic hybrid samples could
not be obtained. Nevertheless, as Eu. grandis has been
shown here to be susceptible and Eu. saligna has even
greater susceptibility, it is likely that the hybrid would
follow suit and, without further information, should be
considered susceptible.
• Eucalyptus tetradonta grows naturally in the northern
and northern coastal regions of the Northern Territory,
the Kimberley region of Western Australia, and Cape
York Peninsula (Bootle 2005). Most of this distribution
is north of 17°S latitude (Boland et al. 1984). It is being
grown as a plantation species in Cape York and, in an
Aboriginal community enterprise, is being salvaged
from rehabili­tated mine sites. While AS 5604-2005
lists Eu. tetradonta as lyctine susceptible, it should be
noted that this rating arose from an earlier interpretation
of the current results when it was assumed that even
limited S1 damage could be used to classify a timber
as susceptible.
Figure 1. Collection sites (●) for Eu. delegatensis on the mainland
Australian Forestry 2009 Vol. 72 No. 1 pp. 20–24
Incidence of damaged samples (%)
24
Lyctine hardwood susceptibility
References
40
NS
35
S1
30
S2
25
S3
20
15
10
5
0
Ja
Fe
Ma
Ap
Ma
Ju
Ju
Au
Se
Oc
No
De
Month collected
Figure 2. Eu. grandis lyctine susceptibility results in relation to month
of sample collection. See text for key to the categories of damage
(NS–S3).
This project was undertaken during drought conditions in much of
the country, and drought may have reduced starch levels in trees
of some species at some collection sites. Consequently, lyctine
damage to sapwood may have been abnormally low in some
specimens. Our assessment of 11 of the 16 timbers examined as
lyctine susceptible would not have been affected in this way. The
conditions under which the timbers were sampled may reflect
future supply conditions, but whether in the longer term global
warming will change relevant climatic conditions is not known.
Those timbers that are lyctine susceptible could be preservative
treated using methods described and reviewed by Cookson et al.
(1998) and Cookson (2004).
Acknowledgements
We thank the following people and organisations for providing
timber samples: Tim Cleary and Boris Iskra formerly of the
Timber Promotion Council of Victoria; Peter Bennett and Larry
Henderson of the Forest Industries Association of Tasmania; staff
of the Huon and Derwent Districts of Forestry Tasmania; Greg
Deambrogio, Arthur Johnson, Harry Callope, Andy Page, Russell
Vance and Matt Armstrong through the Queensland Department
of State Development and Timber Queensland; Brinos Notaras
of J. Notaras & Sons Pty Ltd; and Peter Paunovic, Peter Tarjanyi,
Alan Davidson and David Wilson through State Forests of NSW.
We also thank the FWPA for providing funding towards this
project.
Bamber, R.K. and Erskine, R.B. (1965) Relationship of Vessel Diameter
to Lyctus Susceptibility in some New South Wales Hardwoods.
Research Note No. 15, Division of Wood Technology, Forestry
Commission of NSW, 18 pp.
Boland, D.J., Brooker, M.I.H., Chippendale, G.M., Hall, N., Hyland,
B.P.M., Johnson R.D., Kleinig, D.A. and Turner, J.D. (1984)
Forest Trees of Australia. Thomas Nelson and CSIRO, Melbourne,
677 pp.
Bootle, K.R. (1971) The Commercial Timbers of New South Wales and
their Uses. Angus and Robertson, Sydney, 276 pp.
Bootle, K.R. (2005) Wood in Australia. Types, Properties and Uses.
McGraw-Hill, Sydney, 452 pp.
Cookson, L.J. (2004) Treatment Methods for the Protection of Hardwood
Sapwood from Lyctine Borers. CSIRO Technical Report No. 145.
FWPRDC Project No. PN03.1313, 23 pp. http://www.fwpa.com.
au/content/pdfs/PN03.1313.pdf.
Cookson, L.J., Scown, D.K. and McCarthy, K. (1998) Boron treatment
methods for lyctid susceptible hardwoods growing in Tasmania.
The International Research Group on Wood Protection. Document
No. IRG/WP 98-30168, 12 pp.
Cookson, L.J., Carr, J., Chew, N. and Creffield, J. (2007) Reassessment
of Lyctine Susceptible Sapwood. FWPRDC Project No. PN03.1313,
67 pp. http://www.fwpa.com.au/content/pdfs/new%20pdfs/
PN03.1313_lyctine-report.pdf.
Creffield, J.W., Brennan, G.K., Chew, N. and N.-K. Nguyen (1995) Reassessing the susceptibility of karri (Eucalyptus diversicolor) and
jarrah (E. marginata) sapwood to attack by the powder post borer
(Lyctus brunneus). Australian Forestry 58, 72–79.
CSIRO Division of Forest Products (1950) Lyctus susceptibility list.
Proceedings 5th Forest Products Research Conference, Melbourne,
Topic 8B, 24 pp.
Fairey, K.D. (1975) Lyctus Susceptibility of the Commercial Timbers
Used in New South Wales. Forestry Commission of NSW Technical
Publication No. 19, 8 pp.
Humphreys, F.R. and Humphreys, N. (1966) Starch levels in flooded
gum sapwood. Australian Forest Research 2, 35–40.
Peters, B.C., Creffield, J.W. and Eldridge, R.H. (2002) Lyctine
(Coleoptera: Bostrichidae) pests of timber in Australia: a literature
review and susceptibility testing protocol. Australian Forestry 65,
107–119.
Standards Australia (2005a) Australian Standard 1604.1 Specification for
Preservative Treatment. Part 1. Sawn and Round timber. Standards
Australia, Sydney, 41 pp.
Standards Australia (2005b) Australian Standard 5604. Timber — Natural
Durability Ratings. Standards Australia, Sydney, 22 pp.
Standards Australia (2006) Australian Standard 2796.2 Timber —
Hardwood — Sawn and Milled Products — Grade Description.
Standards Australia, Sydney, 33 pp.
Australian Forestry 2009 Vol. 72 No. 1 pp. 20–24
Jo Sasse, Stephen Elms and Peter Kube
25
Genetic resistance in Pinus radiata to defoliation by the pine aphid Essigella californica
Jo Sasse1,2, Stephen Elms3 and Peter Kube4
1Sassafras
Group, 2 O’Farrell St, Yarraville, Victoria 3013, Australia
2Email: [email protected]
3HVP Plantations, PO Box 385, Churchill, Victoria 3842, Australia
4CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania 7001, Australia
Revised manuscript received 13 November 2008
Summary
The Monterey pine aphid, Essigella californica, has been
associated with extensive defoliation and growth losses in radiata
pine plantations in south-eastern Australia since it was first
detected in 1998. HVP Plantations (HVPP) observed variation
in the level of defoliation between clones in clonal seed orchards
and archives, and initiated a program of assessment of progeny
trials. Between 2001 and 2005, defoliation was assessed in a
provenance trial, a subset of clones within a seed orchard, and
18 progeny trials (some repeatedly). Needle retention in upper
crowns was scored on a scale of 1–10, rather than needle loss,
because this ensured higher scores equated to the desirable state
of the assessed trait. There were significant differences in the
extent of retained foliage between populations, and between subpopulations within populations. The inland northern (Coastways
Ranch) sub-population of Año Nuevo population had the highest
level of retained foliage in the upper crown (mean score of 8.3),
and the northern (Pico Creek, Haarst Ranch) sub-population of
the Cambrian population had the least retained foliage (5.0).
Estimates of heritability from progeny trials ranged from 0 to
0.9, and averaged about 0.5 in trials where there was a significant
family (maternal) effect. Cross-site analysis using a family model
resulted in an overall heritability of 0.4. Genetic correlations
between assessments across two trials in 2004 and those in 2001
and 2003 were high, suggesting that defoliation due to aphids
is consistent across years and can be considered to be the same
trait. In addition to the observed differences between provenances
and families, there were significant differences between clones,
and average levels of retained foliage among clones ranged
from 1.9 to 9.4. HVPP has used this information to develop an
aphid-resistant breed of radiata pine which has been deployed on
an increasing scale since 2005 into the most susceptible areas of
its Victorian estate.
Keywords: defoliation; genetic variation; clones; families; provenance;
resistance; heritability; radiata pine; Monterey pine aphid; Essigella
californica; Victoria
Introduction
The Monterey pine aphid, Essigella californica, was first detected
in plantations of radiata pine in south-eastern Australia in 1998
(Carver and Kent 2000). It causes yellowing and premature drop
of needles, typically in the upper third to quarter of the crown of
older trees (20–25 y), but has also been observed in young trees
(4–6 y, Carver and Kent 2000; 1–5 y, Smith et al. 2008). In Victoria
and South Australia, damage is greatest during late summer and
early autumn and needles are shed a few months later (May and
Carlyle 2003). Defoliation has been associated with significant
growth losses. High correlations between defoliation and growth
loss have been reported, with a 10% loss of foliage estimated to
reduce growth by about 5% (Hopmans et al. 2008) to 8% (May
and Carlyle 2003).
The extent of defoliation has been observed to vary with lo­ca­tion,
nutritional status (Smith et al. 1999; Hopmans et al. 2008), stand
age and condition (i.e. defoliation increases with age, Smith et al.
2008; and thinning, May 2004), and from tree to tree (Smith et
al. 1999). In Victoria, defoliation has been regularly monitored
from 2002 as part of HVP Plantations’ (HVPP) routine health
surveillance program. Defoliation due to aphids has been
consistently highest in the north-east. Some plots lost 50–70% of
the upper crown over successive years, and average upper crown
defoliation for all stands above 11 y old has generally been low
to moderate (11–30%). Plantations south of the Great Dividing
Range had much less damage in 2002–2003, but have experienced
damage comparable to that in the north-east during the period
2004–2007 (Smith et al. 2008). Defoliation of individual trees
has been observed to vary between 0 and 100% within a locality
and this, together with observations of a range of consistent
degrees of defoliation among ramets within clones in clonal seed
orchards and archives on the HVPP estate, suggests the presence
of a genetic component to resistance to defoliation.
Genetic variation in the extent of defoliation of conifers by
aphids has been observed at varied levels in a number of species.
Simpson and Ades (1990) reported variation in susceptibility of
provenances of P. radiata and P. muricata to the woolly aphid
Pineus pini and the needle aphid Eulachnus thunbergia. The
green spruce aphid (Elatobium abietinum) causes defoliation and
consequently growth losses and mortality in Sitka spruce in the
British Isles (Leibhold and Csóka 2001); resistance to defoliation
is variable, heritable and stable (Harding et al. 2003), enabling
effective breeding for increased resistance.
Observations in 1999 of more than 240 clones in three of HVPP’s
clonal seed orchards confirmed that there was variation between
Australian Forestry 2009 Vol. 72 No. 1 pp. 25–31
26
Genetic resistance to defoliation by aphids in radiata pine
clones in the extent of defoliation due to aphids, and that these
differences were reasonably consistent between sites.
More progeny trials where defoliation was evident were then
opportunistically assessed between 2001 and 2005 to confirm
the presence of a genetic component to resistance to defoliation,
and to identify selections that could be captured and quickly
incorporated into a deployment program. Heritability and
genotype × environment interactions were estimated, and pheno­
typic and genetic correlations between assessments in different
years calculated. Selections were made and brought into the HVPP
nursery program as an Aphid-Resistant (AR) Breed, and deployed
as family cuttings in the most seriously affected plantation areas
from 2005.
In 2005, aphid defoliation was observed in a mature provenance
trial. The extent of foliage retained in the upper crown was
assessed and the data analysed to establish whether defoliation
differed between populations.
A number of concurrent projects were also initiated to evaluate
population levels and dynamics, resistance screening options,
impacts of defoliation on growth and silvicultural management
options.
This paper summarises the results of the assessment of defoliation
by aphids in a provenance trial, in progeny trials and in clonal seed
orchards across the HVPP estate over a number of years.
Materials and methods
Defoliation by aphids is assessed by HVPP using a standard
technique. The extent of foliage retained in the upper crown
(RUC) of individual trees is scored on a scale of 1–10, where 10
represents 91–100% foliage retained (i.e. little or no defoliation
due to aphids). Needle retention rather than loss is assessed
because a high score reflects the desirable state of the assessed
trait. Each block was assessed by only one person, and the
assessor’s identity was recorded. RUC is typically assessed in late
autumn to early winter, when needles are in an advanced stage of
chlorosis or have been shed already.
Foliage retention was assessed in clonal seed orchards, progeny
trials and a provenance trial (Table 1). Consistent differences
were first observed in clonal seed orchards in 1999 (data not
shown). The foliage retained in the upper crowns of a subset of
12 clones in Lal Lal clonal seed orchard was assessed in 2002.
Clonal identities were arbitrarily recoded using the letters A to L.
These data were analysed separately from those of progeny trials.
The clones included in the assessment were part of a trial testing
the effectiveness of two formulations of gibberellin (GA4/7)
in promoting cone retention, and the data on retained upper
foliage were analysed in Genstat (v.9.2, 2007) using a two-way
ANOVA (treatment × clone) to confirm that there was no effect
of GA treatment on the extent of retained foliage. Data were
then analysed using a two-way ANOVA to test the interaction of
clone × assessor.
Table 1. Trials assessed from 2001 to 2005 for defoliation by aphids
Trial
Year
Location
established
Design summary
Number of
trees assessed
Number of
families
Average trees
per family
Year
assessed
VRC025
RAD114
RAD117
1979
1967
1967
Flynn
Warrenbayne
Warrenbayne
Provenance trial
CP families
CP families
1348
0354
0237
16
52
36
84.3
06.9
08.9
RAD148
1972
Narbethong
0425
48
09.0
RAD150
RAD151
RAD152
1972
1972
1972
Narbethong
Narbethong
Narbethong
0154
0176
0118
20
20
23
08.1
09.3
05.4
2004
2004
2004
RAD153
RAD154
RAD155
1972
1972
1972
Narbethong
Narbethong
Narbethong
0172
0082
0154
42
32
26
04.2
02.6
06.2
2004
2004
2004
RAD156
RAD157
1972
1972
Narbethong
Narbethong
0360
0079
61
19
06.0
04.4
2004
2004
RAD162
RAD168
1973
1976
Narbethong
Warrenbayne
Heritability trial,
NCI design CP families
NSW OP SO families
Vic and Tas OP SO families
CP families,
density × spiral grain
SA IGP OP families
ACT IGP OP families
Qld IGP OP families
and Vic OP SO families
NSW IGP OP families
Guadalupe, Cedros,
Cambria OP families ex ACT
CP families
Heritability trial,
NCI design CP families
12 × 3 CP factorial
CP families
4 × 4 2G CP factorial
4 × 4 CP factorial
3 × 4 CP factorial
Clonal seed orchard
2005
2001
2001, 2003,
2004
2004
0376
0600
62
54
06.2
12.2
0216
1344
0129
0442
0233
0254
34
36
14
26
16
12 clones
06.5
28.6
09.9
17.7
15.5
21.0
2002
2001, 2003,
2004
2001
2003
2001
2001
2001
2002
RAD170
RAD195
RAD205
RAD225
RAD226
Lal Lal SO
1978
1985
1986
1989
1989
Various
Toorour
Myrtleford
Rennick
Rennick
Rennick
Lal Lal
Australian Forestry 2009 Vol. 72 No. 1 pp. 25–31
Jo Sasse, Stephen Elms and Peter Kube
A total of 18 progeny trials established between 1967 and 1989
were opportunistically assessed between 2001 and 2005. Details
are given in Table 1. Of these trials, 11 were from controlpollinated (CP) seed and seven from open-pollinated (OP) seed.
Most trials had been thinned. Trials RAD148 to RAD157 at
Narbethong formed part of the International Gene Pool trials
planted in 1972. These trials, in particular, often had limited
numbers of families represented, and had been heavily thinned,
further compromising their design.
A Californian provenance trial established in 1979 was assessed in
2005. The data were analysed separately from those of the progeny
trials (Elms and Sasse 2005). The data on retained foliage were
square-transformed to overcome skewness. Analysis of variance
was used to examine differences between sub-populations
within populations. Regression analysis was used to examine
relationships between diameter growth and retained foliage.
The progeny trial data were analysed using Excel (MS Office
2003) and Genstat (v9.2, 2007). Pedigree information for each
trial was combined with the assessment data of each trial. A master
dataset of all data from all trials in all years was collated, treating
each year’s assessment as a different trait. Care was taken to
ensure that linkage between the families represented in the trials,
particularly the International Gene Pool trials, was identified. For
analysis, pedigree information was converted to numeric codes
where parents had a lower number than progeny, and control
seedlots (bulked seedlots) and selfed families were excluded.
Basic statistics were collated using Excel. Individual trials were
separately analysed in Genstat using a family model, and the
heritability calculated. A combined site analysis was done to
estimate the genotype × site interactions and to estimate acrosssite heritability. In this analysis, it was assumed assessments in
different years were measures of the same trait. The following
steps were followed in the analysis:
(a) Each trial was analysed using the model y = mean + rep +
assessor + mother + father + mother.father + error where rep
and assessor were fixed effects and the others random. The
variance components were recorded and used to estimate
heritability: h2 = (2σ2mother + 2σ2father) / (σ2mother + σ2father + σ2mother.
2
father + σresid) and its standard error. Open-pollinated trials were
assessed using the same model, but omitting terms involving
fathers; i.e. y = mean + rep + assessor + mother + error, and
h2f = 4σ2mother / (σ2mother + σ2resid). Trials with non-significant
genetic effects were excluded from further analysis.
(b) Genetic correlations between years were calculated for those
trees (excluding controls) measured on all occasions in the
two trials RAD117 and RAD168, and between defoliation in
2004 and diameter in RAD151 (dbh at age 10 y and 20 y),
RAD117 (dbh age 15 y) and RAD168 (dbh age 11 y). Corre­
lations were calculated as rg = σfam(x,y) / (σ2fam(x) + σ2fam(y)),
where σfam(x,y) = (σ2fam(x + y) – σ2fam(x) – σ2fam(y) )/ 2.
(c) A combined site analysis using data from all years (first year
of assessment if multiple years were assessed) for all trials
was done to examine the interaction between mother and site,
as maternal linkage was strongest between trials. This was
done for all trials except those where genetic effects were
non-significant and RAD225, a second-generation trial. Of
the 187 mothers in the reduced dataset, 70 were represented
27
on two or more sites. The model used was y = mean + site
+ rep + assessor + mother + mother.site + error, and cross-site
heritability was estimated using the OP calculation.
Results
Provenance trial
Trait means by sub-population are summarised in Table 2. There
were significant differences in growth between populations in
dbh (P < 0.001), with the seed orchard stock (30.4 cm) being
significantly larger than the population seedlots (average of all
three populations 27.4 cm). There were no differences between
the Californian populations in growth. There were, however,
significant differences between populations and between subpopulations within populations in the proportion of upper crown
retained (Table 3). The Año Nuevo population had the greatest
proportion of retained foliage in the upper crown (transformed
data, RUC2; 62.4), and Cambria had the least (36.3). The foliage
retention for the seed orchard material was most similar to, but
significantly greater than, that of the Monterey population from
which it is probably derived (55.3 and 51.5, respectively). The
sub-population with the greatest RUC2 was the inland northern
(Coastways Ranch) sub-population of the Año Nuevo population,
and the population with the least RUC2 was the northern (Pico
Creek, Haarst Ranch) sub-population of Cambria population.
There were significant differences between sub-populations within
all populations except the seed orchard populations.
There is a broad relationship between diameter and the amount
of retained foliage in the upper crown, that is between diameter
class and mean RUC score for all populations (R2 = 0.81, Elms and
Sasse 2005). At an individual-tree level, however, the relationship
is much weaker, explaining about 6% of the variation in RUC
on average (varying from 1% to 10% between populations, data
not shown).
Progeny trials
Between 2001 and 2004, a total of 5427 trees in 18 trials from a
pedigree of 315 genotypes were assessed (Table 4). On average
there were about 34 families (31 excluding controls and selfs)
per trial, and about nine trees per family. The average score
for retained foliage was 7.0 in 2001–2002, 8.5 in 2003 and
6.8 in 2004. There was generally significant variation within
sites in average retained foliage scores, indicated by significant
differences between replicates within trials. Mean scores between
replicates within trials typically varied by 1.5–3.0 points in 2001,
less than 1 in 2003, and 1.0–2.5 in 2004.
Heritabilities for the trials assessed ranged between 0.32 and
0.95 (Table 5). RAD117 at Warrenbayne consistently had a high
heritability: about 0.9 in 2001 and 2003, and 0.5 in 2004. One
trial (RAD195) had very little variability in defoliation (minimum
defoliation score was 7, 94% of trees scored 9 or 10), and was not
further analysed. Several trials had heritabilities that were either
very low, could not be calculated, or had very high standard errors
(RAD150, 151, 154, 155, 156, 157 and 170); these trials were
trials with little structure (RAD154, 157; small trials of ACT and
Californian population material, respectively), poor design (low
Australian Forestry 2009 Vol. 72 No. 1 pp. 25–31
28
Genetic resistance to defoliation by aphids in radiata pine
Table 2. Mean DBH and retained upper crown score (RUC) by population and sub-population in the Flynn
provenance trial. Population and sub-population nomenclature follows that of Eldridge (1998)
No. of
trees
Dbh
(cm)
RUC
RUC
t’formeda
Coastal Strip, Highway 1
Inland Coastal, Last Chance Road
Inland Northern, Coastways Ranch
Inland Southern, Swanton
030
028
028
026
26.9
26.0
27.0
26.5
.7.8
.7.5
.8.3
.7.3
63.4
58.0
70.6
57.7
Cambria
Furthest Inland, Scott Rock
Main Stand, Cambria Town
Northern, Pico Creek, Haarst Ranch
028
035
027
27.8
26.2
25.0
.6.1
.6.1
.5.0
39.8
39.9
29.2
Monterey
Coastal Northern, Sand Dunes
Coastal Southern, Point Lobos
Furthest Inland, Jacks Peak Park
Inland Southern, Highest Altitude
Inland, Huckleberry Hill
Inland, Town Area
041
034
035
027
030
026
26.9
28.5
28.4
26.6
28.2
25.6
.7.4
.6.8
.6.3
.7.3
.7.0
.6.6
56.7
49.1
43.0
57.7
53.2
49.0
Saxtons SO
1976 Harvest 601/101L
1977 Harvest 601/106M
046
079
30.7
30.2
.6.9
.7.4
51.8
57.0
520
27.6
07.0
52.1
Population
Sub-population
Año Nuevo
Total or overall average
a
RUC transformed to remove skewness in data by squaring the scores
Table 3. Comparisons between populations and sub-population for transformed retained upper crown scores (RUC2)
Año Nuevo
Coastal Strip, Highway 1
Inland Coastal, Last Chance Rd
Inland Northern, Coastways Ranch
Inland Southern, Swanton
63.8
59.6
70.8
57.8
ab
ab
a
ab
Furthest Inland, Scott Rock
Main Stand, Cambria Town
Northern, Pico Creek, Haarst Ranch
40.8
39.8
29.0
a
a
ab
Monterey
Coastal Northern, Sand Dunes
Coastal Southern, Point Lobos
Furthest Inland, Jacks Peak Park
Inland Southern, Highest Altitude
Inland, Huckleberry Hill
Inland, Town Area
56.3
49.5
42.2
57.0
52.5
47.8
ab
abc
ab cd
a
abc
ab cd
Saxtons SO
1976 Harvest 601/101L
1977 Harvest 601/106M
51.8
57.0
a
a
Overall average
b
Group in
populationa
Sub-population
Cambria
a
RUC 2
Population
52.1
Population
average
Group between
populationsb
62.4
A
36.3
D
51.5
C
55.3
B
52.1
Sub-populations within populations with different lower case letters are in significantly different groups within the population (Fisher’s PLSD at 5%)
Populations with different upper case letters are significantly different (Fisher’s PLSD at 5%)
or variable replication or family numbers; RAD151, 155, 156), or
unbalanced family representation following thinning (RAD150).
RAD154 and 170 had little variation in defoliation — in both
trials about 85% of trees scored 7 or above. In each of these
trials (except RAD154), there was no significant family effect
when analysed in a fixed-effects model. Excluding these trials,
heritability averaged about 0.5, suggesting that retention of the
upper crown is heritable.
The combined site analysis, excluding the above trials, showed
that the maternal × site variance component was less than 10% of
the total observed (σ2mother = 0.41; σ2mother.site = 0.30; σ2resid = 2.94)
Australian Forestry 2009 Vol. 72 No. 1 pp. 25–31
Jo Sasse, Stephen Elms and Peter Kube
29
Table 4. Summary statistics for trials assessed for aphid defoliation between 2001 and 2004
Trial
RAD114
RAD117
RAD117
RAD117
RAD148
RAD150
RAD151
RAD152
RAD153
RAD154
RAD155
RAD156
RAD157
RAD162
RAD168
RAD168
RAD168
RAD170
RAD195
RAD205
RAD225
RAD226
Year of
assessment
Number of
trees assessed
Number of families
(exc. controls)
Av. trees
per family
(exc. controls)
Average
Min.
Max.
2001
2001
2003
2004
2004
2004
2004
2004
2004
2004
2004
2004
2004
2002
2001
2003
2004
2001
2003
2001
2001
2001
0354
0312
0236
0237
0425
0154
0176
0118
0172
0082
0154
0359
0079
0376
0644
0602
0600
0216
1344
0129
0442
0233
50
31
20
20
46
16
16
20
39
29
22
60
08
53
50
50
50
31
32
13
22
12
06.9
08.5
09.8
09.8
09.1
08.3
09.6
05.3
03.9
02.8
06.2
06.0
04.6
05.5
11.8
11.6
11.5
06.5
29.2
09.9
15.8
14.6
6.7
6.9
7.1
6.6
6.1
6.5
6.3
5.3
7.4
7.8
7.4
7.5
7.8
7.7
6.9
7.5
6.9
8.1
9.4
4.6
6.7
7.3
1.0
0.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
4.0
1.0
1.0
2.0
2.0
1.0
0.0
1.0
1.0
7.0
2.0
2.0
0.5
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
10.0
09.0
09.5
09.5
and that the across-site heritability was 0.45 (se = 0.13). Part of
the maternal × site interaction was due to differences in paternal
contribution between sites that arose because a different suite of
fathers was used at each site. A pseudo-F test (F = s21 / s22) of the
stratum variances (s2mother = 10.08, effective d.f. =116; s2mother.site
= 5.48, effective d.f. = 87; F = 1.84) was significant, showing that
variation due to maternal contribution was significantly greater
than the variation due to the interaction between mother × site,
which suggests differences in paternal contributions between sites
did not have a strong effect.
The phenotypic correlations between the three traits (foliage
retained in the upper crown 2001, 2003 and 2004) measured in
RAD117 and RAD168 were moderate (0.4–0.5), but the genetic
correlations were about 0.9 between 2004 and the other two years
(Table 6), suggesting that the traits can probably be considered
to be the same. The correlations between 2003 and the other
two years were lower, perhaps because defoliation was more
uniform in 2003. The high rg implies that the analysis can be
done independently between years, and the results for each trial
measured in each year should be comparable.
Correlations between aphid defoliation in 2004 and diameter
at a range of ages were examined at RAD117 (age 15 y, dbh),
RAD151 (age 10 and 20 y, dbh) and RAD168 (age 11 y, dbh).
The correlations (Table 7) varied between both the trials and ages.
At RAD151, the genetic correlations were moderate to strong
and positive, but at RAD168 and RAD117 they were moderately
negative. Greaves (2001) reported a genetic correlation of 0.77
between foliage retention in 2001 and diameter at age 8 y in
RAD114.
Retained foliage score
σtrees
σfam
1.9
2.1
2.0
2.0
2.3
2.4
2.2
2.3
1.7
1.3
1.8
1.8
1.7
1.5
1.9
1.6
1.8
2.1
0.6
1.7
1.4
1.6
1.1
1.5
1.0
1.3
1.2
1.0
1.0
1.4
1.2
1.1
1.0
0.8
0.7
1.1
1.2
0.9
0.9
1.2
0.2
0.9
0.6
0.7
Clonal orchards
Mean scores for retained foliage in the upper crowns of the 12
clones assessed at Lal Lal Seed Orchard ranged from 1.9 to 9.4.
Levels of defoliation were unaffected by gibberellin treat­ment
(P = 0.103), but there was a significant interaction between clone
and assessor (P < 0.001, Table 8). However, the effect of clone is
dominant (P < 0.001 for clone, after eliminating assessor effect),
and 10 of the 12 clones could be classified into three distinct groups
(Fig. 1) with mean defoliation scores of 8.5, 6.2 and 2.4 (Clones
G and C were intermediate between the top two groups and could
not be classified to either). Other data (not shown) suggest that
levels of defoliation within clones are consistent across sites (39
clones from three seed orchards, assessed in 1999).
Discussion
These results show that resistance to defoliation by aphids is both
variable and moderately to highly heritable. This encourages
selection and breeding as a strategy to reduce productivity losses,
and results from these analyses have been used to identify existing
and new selections to develop an ‘aphid-resistant’ breed within
HVPP’s deployment program. About 20 parents contribute to this
breed, the first plants of which were distributed for establishment
in 2005.
Although the genetic correlations between foliage retention and
growth estimated from the progeny trial data were variable, it
appears that the ‘aphid resistant’ breed currently being deployed
by HVPP has overall Treeplan® breeding values for productivity
similar to those of the standard breed. This suggests that gains in
Australian Forestry 2009 Vol. 72 No. 1 pp. 25–31
30
Genetic resistance to defoliation by aphids in radiata pine
Table 5. Variance components and heritabilities for trials assessed for aphid defoliation between 2001 and 2004
Trial
RAD114
RAD117
RAD117b
RAD117
RAD148b
RAD152 a
RAD153 a
RAD162a
RAD168
RAD168b
RAD168
RAD225
a
b
Year
assessed
σ2mother (se)
σ2father (se)
σ2mother.father (se)
σ2resid (se)
h2 (se)
2001
2001
2003
2004
2004
2004
2004
2002
2001
2003
2004
2001
0.24 (0.26)
0.94 (0.60)
0.77 (0.46)
0.23 (0.55)
0.39 (0.22)
0.86 (0.58)
0.54 (0.31)
0.26 (0.13)
0.74 (0.32)
0.34 (0.15)
0.34 (0.21)
0.18 (0.14)
0.30 (0.27)
1.23 (1.09)
1.92 (1.57)
0.75 (0.90)
0.45 (0.31)
—
—
—
0.34 (0.25)
0.12 (0.09)
0.18 (0.18)
0.15 (0.13)
0.13 (0.27)
0.35 (0.40)
∼0
0.74 (0.61)
∼0
—
—
—
0.04 (0.21)
—
0.10 (0.19)
0.04 (0.04)
2.73 (0.23)
2.44 (0.23)
2.98 (0.32)
2.03 (0.22)
4.08 (0.30)
3.46 (0.53)
2.58 (0.34)
1.75 (0.16)
2.59 (0.16)
2.03 (0.13)
2.49 (0.15)
1.12 (0.09)
0.32 (0.21)
0.88 (0.32)
0.95 (0.31)
0.52 (0.47)
0.34 (0.12)
0.80 (0.45)
0.70 (0.36)
0.52 (0.23)
0.58 (0.17)
0.37 (0.10)
0.33 (0.16)
0.45 (0.20)
OP trial
mother.father variance estimated to be negative or close to 0, or completely aliased with other terms, and therefore excluded from model
Table 6. Phenotypic (above diagonal) and genotypic (below diagonal)
correlations between retained foliage in 2001, 2003 and 2004,
calculated from trees in RAD117 and RAD168 which were assessed
on all occasions
2001
2003
2004
2001
0.73
0.92
2003
2004
0.42
0.53
0.52
0.90
Table 7. Genetic and phenotypic correlations between growth at
various ages and defoliation in 2004, calculated from trees in
RAD117, RAD151 and RAD168
Trial
RAD151
RAD151
RAD168
RAD117
No.
observations
rg
rp
10
20
11
15
153
123
571
196
–0.22
–0.52
–0.28
–0.25
0.04
0.03
0.00
0.02
Clone code
Assessor 1
Assessor 2
A
B
C
D
E
F
G
H
I
J
K
L
09.5
09.0
07.4
08.3
07.9
05.6
06.7
01.6
06.0
10.0
07.0
09.7
8.2
8.0
6.7
8.0
5.3
6.3
8.2
3.0
6.3
7.8
5.4
8.1
(6.2)
(2.4)
10
10
9
9
8
8
7
7
6
6
5
5
4
4
3
3
2
2
1
1
0
Age of dbh
assessment (y)
Table 8. Mean retained upper crown score (RUC)
by clone and assessor at Lal Lal Seed Orchard
Mean RUC score
rg \ rp
(8.5)
L
A
J
B
D
G
C
E
I
K
F
H
0
Clone
Assessor 1
Assessor 2
Mean
Figure 1. Retained upper crown score (RUC) by assessor, and mean
score adjusted for assessor, for the 12 clones assessed at Lal Lal Seed
Orchard. Lines show the three groups (and their mean score) that could
be identified amongst the 12 clones. (The groups were identified by
post-hoc analysis of LSDs — using Fisher’s PLSD at 5%.) Clones G and
C were intermediate between the upper and medium groups, and could
not be classified to either.
Australian Forestry 2009 Vol. 72 No. 1 pp. 25–31
Jo Sasse, Stephen Elms and Peter Kube
aphid resistance can be made without compromising productivity,
and the genetic correlations are likely to be positive.
The pedigree of the current aphid-resistant deployment breed
used by HVPP is limited and needs expansion. Therefore further
assessment of progeny trials is required, and the data should be
included with the current data in the national analysis of radiata
pine as coordinated by the Southern Tree Breeding Association.
Assessing second- and third-generation progeny trials would
allow comparison of genetic parameters with first-generation
trials, provide greater depth to the pedigree, and enable BLUPs
(Best Linear Unbiased Predictors) to be estimated for material
relevant to current deployment populations. Analysis of the data
using Treeplan® would allow multivariate analysis of defoliation
between years, integration of the aphid BLUPs with those of
other traits and expansion of aphid BLUPs to a broader suite
of genotypes through the pedigree. Identification of secondgeneration progeny trials that are in aphid-affected districts and
that have already been thinned, or thinning some candidate trials
and possibly fertilising them with high levels of nitrogen to induce
aphid attack, may be worth consideration. Screening methods are
also needed to evaluate the resistance of genotypes to defoliation
at a young age, to enable efficient selection for breeding and
deployment. Investigating the feeding preferences of the aphids
and or defence mechanisms of the trees may provide clues to
possible methods.
Conclusions
Resistance to defoliation by aphids has been shown to have a
significant genetic component. At a provenance level, foliage
retained in the upper crown was greatest in the Año Nuevo
population, and greatest in the inland northern (Coastways Ranch)
sub-population from Año Nuevo. At a clonal level, clones had
significantly different amounts of retained foliage. At a family
level, the extent of retained foliage was found in progeny trials
to be highly heritable, consistent between years, and with little
genotype × environment interaction evident. Heritability estimates
varied between sites and between years. The reasons for this
are not entirely clear, but there were indications that defoliation
was more variable in some years and on some sites than others,
suggesting that genetic effects are better estimated in years and
on sites expressing greater variability. These results have been
used to initiate development of an ‘aphid resistant’ breed for
operational deployment in plantations.
31
References
Carver, M. and Kent, D.S. (2000) Essigella californica (Essig) and
Eulachnus thunbergii Wilson (Hemiptera: Aphididae: Lachninae)
on Pinus in south-eastern Australia. Australian Journal of
Entomology 39, 62–69.
Eldridge, K.G. (1998) Australian Radiata Provenance Trials. Client
Report 416. CSIRO Division of Forestry and Forest Products,
Canberra.
Elms, S. and Sasse, J. (2005) Defoliation by aphids in Californian
provenances of radiata pine at RES0024 (Flynn, 1979). Internal
Research Report, Hancock Victorian Plantations.
Greaves, B.L. (2001) Quantitative analysis of aphid defoliation score.
Consultancy report to Hancock Victorian Plantations.
Harding, S., Roulund, H. and Wellendorf, H. (2003) Consistency of
resistance to attack by the green spruce aphid (Elatobium abietinum
Walker) in different ontogenetic stages of Sitka spruce. Agricultural
and Forest Entomology 5, 107–112.
Hopmans, P., Collett, N., Smith , I.W. and Elms, S. (2008) Growth and
nutrition of Pinus radiata in response to fertilizer applied after
thinning and interaction with defoliation associated with Essigella
californica. Forest Ecology and Management 255, 2118–2128.
Leibhold, A. and Csóka, G. (2001) Risks posed by exotic forest pests –
foliage feeding insects. In: Exotic Forest Pests Online Symposium
– http://www.apsnet.org/online/proceedings/ExoticPest/Papers/
Leibhold.htm (verified 22 April 2008)
May, B.M. (2004) Assessment of the Causality of Essigella-Ascribed
Defoliation of Mid-Rotation Pine and its National Impact in
Terms of Cost of Lost Wood Production. Final Report for Project
PN04.4002 to Forest and Wood Products Research and Develop­
ment Corporation, Melbourne.
May, B.M. and Carlyle, J.C. (2003) Effect of defoliation associated with
Essigella californica on growth of mid-rotation Pinus radiata.
Forest Ecology and Management 183, 297–312.
Simpson, J.A. and Ades, P.K. (1990) Variation in susceptibility of Pinus
muricata and Pinus radiata to two species of Aphidoidae. Silvae
Genetica 39, 202–206.
Smith, I.W., Collett, N.G. and Hopmans, P. (1999) Impact on growth
of defoliation associated with Essigella californica infestation
of 23-year-old thinned P. radiata at Warrenbayne, Victoria. In
Collett, N., Simpson, J. and Schoenborn, C. (eds) A Review of the
Current Status of the Monterey Pine Aphid in Australia. Workshop
Proceedings, Centre for Forest Tree Technology, Heidelberg,
Victoria.
Smith, I., Smith, D., Collett, N. and Elms, S.R. (2008) Forest health
surveillance in Victoria. Australian Forestry 71, 188–195.
Acknowledgements
Defoliation in provenance and progeny trials and clonal seed
orchards was assessed by staff from HVP Plantations, including
Peter Buxton, Robyn Pearson and Warwick Williams; and teams
from the Centre for Forest Tree Technology (Department of
Sustainability and Environment, now University of Melbourne)
including Nick Collett, Carolien Schoenborn, David Smith, Paul
Clements and Matthew Hamilton. Dr Bruce Greaves (Strategic
Forest Research Pty Ltd) completed the first analysis of aphid
defoliation for HVP Plantations. Dr Peter Hopmans (Timberlands
Research) and Nick Collett (University of Melbourne) have
provided valuable feedback and guidance to the HVP Plantations
research program into defoliation by aphids.
Australian Forestry 2009 Vol. 72 No. 1 pp. 25–31
32
Scaling export pulpwood
A sampling system for scaling partly segregated export pulpwood
J.C. Ellis1,2 and M.O. Kimberley3
1Scaling
Research International, Private Bag 12501, Tauranga 3143, New Zealand
2Email: [email protected]
3Scion, Private Bag 3020, Rotorua 3046, New Zealand
Revised manuscript received 14 November 2008
Summary
Estimates of pulpwood volumes exported from Australia and
New Zealand are generally based on stratified samples of logs.
This study investigates the possibility of modifying the existing
sampling technique to cover consignments of logs only partly
segregated on log size. A data set of 10 export consignments
consisting of 193 truckloads containing 12 150 logs was used
to compare 100% scale, 10% stratified sampling, and a revised
system involving 10% sampling of logs below a small-end
diameter limit of 26 cm and complete scaling of logs above
that limit. Compared with 10% stratified sampling, the revised
system reduced the average bias for a typical consignment of
pulpwood and improved the precision, with the 95% confidence
interval of mean log volume being reduced from 7.9% to 3.9%
of the mean.
Keywords: pulpwood; scaling; sampling; volume determination
Introduction
Complete scaling of pulpwood is expensive and difficult because
of the small piece size and consequent large number of logs in
a typical load or shipment (Ellis and Kimberley 1995). This is
especially so given the generally lower value per unit volume of
pulpwood compared with sawlogs (Blythe 1945).
Before 1991, pulpwood exported from New Zealand to Asia was
either fully scaled or the volume was estimated from a sample
of truckloads, with all logs in each sampled truckload being
scaled (Ellis and Kimberley 1995). Typically one truckload in
ten was fully scaled. This often caused severe traffic congestion.
Moreover, volume estimates using this sampling method often
had poor precision because of the variation between truckloads,
and costs could be high because of the large number of truckloads
required to obtain reasonable levels of precision. Measuring all
the logs within each sample truckload was also expensive and
prone to error because of the large number of logs in a load,
which typically number 60 to 180 for pulpwood. Because of the
difficulty in identifying the small end of logs in the centre of a
load, large-end diameters were sometimes measured, leading to
a volume overestimate.
An improved stratified sampling technique was therefore
developed and this has been used in New Zealand since 1991
(Ellis and Kimberley 1995). This method involves measuring a
10% sample of logs from each truckload as it arrives at the scaling
area or wharf marshalling area. To apply the method, the total
number of logs in each load is firstly counted, and the number
of sample logs required calculated to obtain a 10% sample. Logs
against the bolster at the edge of the load are then measured until
a sufficient number of sample logs is obtained. Loads with fewer
than 26 logs are fully scaled. This procedure has been found to
give a representative sample of logs with little bias. Because of
their position at the edge of the load, the small ends of the logs
can be identified and measured easily and quickly along with
the log length. Volumes of the sampled logs are estimated using
the appropriate log volume formulae, and standard stratified
sampling formulae applied to estimate the mean log volume of a
total consignment. Each truck or trailer load is treated as a sample
stratum in this procedure. This stratified sampling method gave
greatly improved precision compared to the previous system,
with standard errors typically being reduced by two-thirds (Ellis
and Kimberley 1995).
Where the system has been applied on log populations with a
restricted range of diameters it has worked well, and importers
and exporters have not had cause for concern. Where the method
has been used on unsegregated pulplogs (Fig. 1), however, there
have been claims of volume bias. With the number of log grades
generated in bush landings, it is often difficult to segregate pulp
logs into large and small sizes, and unsegregated pulplogs are
consequently placed onto trucks. While there may be a large
number of pieces, the wide range of sizes compromises the
precision of the stratified sampling system. To overcome this
problem, some exporters ignore measurements of a small number
of oversized logs in the sample, but count them as a small pulp
piece. However, this is certain to give a negative bias to the
estimated average piece size.
A similar system of sampling export pulplogs has been used in
Tasmania, although scaling is performed on log stacks (Fig. 2)
rather than bunks on truck or rail wagon. An important difference
from the New Zealand system is that larger-diameter logs in the
stack are fully scaled, and the sampling procedure is applied only
to the smaller-diameter logs in the stack. Typically, all pieces are
butt marked so that the (unpainted) small end can be identified. All
pieces with a small-end diameter of 26 cm and over are ticketed
and scaled. The remaining pieces have numerically sequenced
paper tickets placed on the small end and every 10th number
is used as a sample. In other parts of Australia where logs are
Australian Forestry 2009 Vol. 72 No. 1 pp. 32–38
J.C. Ellis and M.O. Kimberley
33
Figure 1. A truckload of unsegregated pulplogs
Figure 2. Pulp pieces sampled along the top of a pulp load in Geelong,
Victoria
stacked without any butt or small-end marks, samples are taken
from the top of the stack where the small end can be positively
identified. To achieve a sample of about 10% in pulp stacks less
than two metres in height, half the logs along the top of the stack
or truckload (those with the small end on one chosen side of the
stack) are measured. In stacks over two metres in height, all the
logs along the top of the stack are measured.
Trial data
The current trial was set up to determine whether the New
Zealand pulplog stratified sampling system could be improved
by measuring all large logs in a consignment, and applying a
sampling system to the smaller logs. Specifically the objective
was to determine whether volume estimates with better precision
and less bias could be obtained by scaling all larger logs and a
sample of smaller logs in each load.
Consignments of pulp logs delivered to the New Zealand North
Island log export ports of Northport and Mount Maunganui were
used for test data. All of the logs in each truckload were ticketed
and measured. The sequence of ticketing started with the sample
logs against the bolster and continued with the remainder of the
load. The first ticketed logs provided the 10% sample, and the
remaining logs gave the true volume of the load. Note that a
consignment consists of a group of truckloads (dockets) in one
location at the storage facility. Characteristics of each consignment
are shown in Table 1.
The data sets from Northport and Mount Maunganui differed
in piece size, the number of pieces per truck, and the number of
Table 1. Study data for each consignment
Port and
consignment
Northport
G045
G096
G098
G137
G147
H112
Overall
Mount
Maunganui
W1219
W1829
W2129
W4191
Overall
Overall combined
Small-end diameter
(cm)
Loads
Logs
Min.
Max.
Mean
Min.
Max.
Mean log
volume
(m3)
3.8
3.8
3.8
3.9
3.8
3.0
012
019
015
019
031
015
111
01 549
01 268
00736
01 679
01 649
01 507
08 388
41
12
01
10
01
02
01
187
132
106
161
171
134
187
129
067
049
088
053
100
076
11
10
11
10
10
09
09
72
96
50
92
62
48
96
0.137
0.218
0.157
0.165
0.151
0.115
0.155
3.9
3.9
3.9
3.9
030
017
018
017
082
00782
01 119
00902
00959
03 762
01
03
01
01
01
138
107
103
143
143
026
066
050
056
046
08
14
13
10
08
58
42
70
62
70
0.190
0.271
0.299
0.196
0.242
193
12 150
01
187
063
08
96
0.182
Log
length (m)
Number of
Number of logs per load docket
Australian Forestry 2009 Vol. 72 No. 1 pp. 32–38
34
Scaling export pulpwood
‘pseudo-loads’ added to locations as rejects from sawing-grade
logs. A load signifies a log or logs belonging to a single docket.
The average log size for the Northport population was somewhat
smaller than for the Mount population. Both populations show
a small but significant number of larger logs in the upper range
of the distribution, which are most likely reject sawlogs (Figs 3
and 4).
(b) For logs equal to or greater than 6 m long:
Sampling methods
Note that (L′ – 4)/2 is the factor for taper.
The volume of each log in the study data set was calculated
from the small-end diameter and log length using the Japanese
Agricultural Standard (JAS) (Ellis and Elliott 2001), that is:
For each consignment in the study, the actual total JAS volume
was calculated along with volume estimates using the standard
‘10% stratified sampling method’ and a revised method in which
larger-diameter logs were fully scaled and the remaining logs
sampled using the 10% sampling method. For the standard
method, a 10% sample of logs was used for loads with more than
25 logs, but loads with 25 or fewer logs were fully scaled. For the
revised method, all logs with a small-end diameter greater than the
specified limit of 26 cm were scaled. For loads with more than 25
logs below the diameter limit, a 10% sample of these remaining
(a) For logs less than 6 m long:
D2 L
,
10 000
V =
(1)
where D is the shortest diameter in centimetres, L is the length in
metres and V is the volume in cubic metres.
V =
(D + (L� − 4)/2)2 L
,
10 000
where D is the shortest diameter in centimetres, L is the length in
metres, L′ is the length in metres rounded down to a whole metre
and V is the volume in cubic metres.
700
Population
Number of logs
600
Sample*10
500
400
300
200
100
0
8 10 12 14 18 22 26 30 34 38 42 46 50 54 58 62 66 70 74 78 82 86 90 94
JAS small-end diameter class (cm)
Figure 3. Diameter distribution, Northport logs
2000
1800
Population
Sample*10
Number of logs
1600
1400
1200
1000
800
600
400
200
0
(2)
8 10 12 14 18 22 26 30 34 38 42 46 50 54 58 62 66 70 74 78 82 86 90 94
JAS small end-diameter class (cm)
Figure 4. Diameter distribution, Mount Maunganui logs
Australian Forestry 2009 Vol. 72 No. 1 pp. 32–38
J.C. Ellis and M.O. Kimberley
logs was scaled. Loads with 25 or fewer logs below the limit were
fully scaled. The effect of using a size limit other than 26 cm
was then explored by varying it from zero (effectively complete
sampling of all logs in the consignment) to 100 cm (effectively
the standard method as no individual log in the study exceeded
this limit) in 2-cm steps. For convenience, logs with diameter
less than or greater than the specified size limit are referred to
in the remainder of this paper as ‘undersized’ or ‘oversized’ logs
respectively. Finally, the effect of using a sampling percentage
of undersized logs other than 10% was explored by varying it
from 5% to 20%.
The revised sampling method consists of a stratified sample
of the undersized logs combined with complete measurement
of the oversized logs. The estimated mean log volume of the
consignment is obtained using the following formula. This and the
following variance equation are essentially those used in stratified
random sampling (e.g. Cochran 1977):
�a
(v̄i Ni ) + v̄o no
�a
V̄ m = i=1
,
(3)
i=1 Ni + no
where a is the number of truckloads, v̄i is the average piece size
(m3 JAS) of the sampled logs below the diameter limit in the ith
load, Ni is the total number of undersized logs in the ith load, and
no and v̄o are the number and mean piece size of all the oversized
logs in the consignment.
The variance of V̄m is estimated using:
var(V̄ m ) =
2
2
i=1 ((si /ni )Ni (1 − (ni /Ni ))
� �a
�2
i=1 Ni + no
�a
(4)
,
where s2i is the variance between sample logs in the ith load, ni is
the number of undersized logs in the ith load, and other symbols
are as before.
35
Probable limits of error (PLE, equal to half the 95% confidence
interval expressed as a percentage of the mean) are calculated
using:
�
100 tn−a var(V̄ m )
,
(5)
PLE =
V̄ m
where n = ni, and tn–a is the t-value with n – a degrees of freedom
(2-tailed, P = 0.05).
The total volume for a consignment is obtained by multiplying
the mean log volume (Equation 3) by the total number of logs in
� �a
�
the consignment
i=1 Ni + no .
Results
In eight of the ten consignments, the volume bias was reduced by
the revised method compared with the standard method (Table 2).
Average bias across the ten consignments in the study was 0.96%
for the revised method compared with 1.39% for the standard
method. The PLE for the revised method was generally about
half that of the original system: the average PLE was 3.87%
compared with 7.93% for the original system. For populations
of 1000 logs or more, a PLE of less than 5% is achievable using
the revised method. In the study data set, however, this superior
precision and reduced bias was achieved at the expense of scaling
on average 24% of all logs compared with less than 13% for the
standard sampling system.
The relationship between the small-end diameter size limit and
PLE for the revised method along with the percentage of logs
scaled is shown for each port in Figure 5. Note that the percentage
of logs scaled is always higher than the nominal undersized log
sampling percentage of 10% even for large size limits. This is
because all the consignments included some loads of fewer than
26 logs, which were therefore fully scaled. As the small-end
Table 2. Comparative precision and bias between original and new systems
Population
Consignment
Standard sampling method
Logs sampled
Revised sampling method
Logs sampled
Bias
(%)
PLE
(%)
No.
Fraction
(%)
Bias
(%)
PLE
(%)
Loads
Logs
No.
Fraction
(%)
G137
G045
G096
G098
G147
H112
W1219
W1829
W2129
W4191
19.0
12.0
19.0
15.0
31.0
15.0
30.0
17.0
18.0
17.0
1679
1549
1268
0736
1649
1507
0782
1119
902
959
178
155
199
081
203
152
171
152
154
121
10.6
10.0
15.7
11.0
12.3
10.1
21.9
13.6
17.1
12.6
–4.65
–2.52
–4.88
–4.04
–4.8
–8.75
–3.32
–0.03
–0.29
–6.23
08.42
06.53
06.25
10.19
06.86
09.64
10.94
05.36
05.32
09.75
247
216
291
146
278
251
244
513
461
271
14.7
13.9
22.9
19.8
16.9
16.7
31.2
45.8
51.1
28.3
–2.97
–0.23
–5.02
–2.35
–0.74
–0.04
–0.47
–1.01
–0.71
–1.50
3.61
4.88
3.12
6.77
3.79
4.47
5.19
1.61
1.37
3.84
Northport mean
Mount mean
18.5
20.5
1398
0941
161
150
11.6
16.3
–2.75
–0.65
07.98
07.84
238
372
17.5
39.1
–1.82
–0.33
4.44
3.00
Overall mean
19.3
1215
157
13.5
–1.39
07.93
292
26.1
–0.96
3.87
Australian Forestry 2009 Vol. 72 No. 1 pp. 32–38
Scaling export pulpwood
100
10
90
9
80
8
70
7
60
Mount sample %
50
North sample %
40
30
6
5
Mount PLE
4
North PLE
3
20
2
10
1
0
10
20
30
40
PLE (%)
Log sampled (%)
36
0
60
50
SED (cm)
Figure 5. Percentage of logs scaled and precision at each port versus
small-end diameter size limit
diameter limit is reduced, the PLE also reduces, but at the expense
of having to scale a greater percentage of logs. There was a
noticeable difference between the two ports, with the PLE being
larger and the scaling percentage smaller for a given small-end
diameter size limit at Northport compared with Mount Maunganui.
At both ports, however, similar precision was achieved for the
same scaling percentage. For example for the Mount Maunganui
log population, a size limit of 32 cm produced a PLE of 5% and a
scaling percentage of 20%. For the Northport population, a similar
PLE was achieved using a size limit of 28 cm, which required a
scaling percentage of 17%.
Potentially, both the sampling percentage of undersized logs
and the small-end diameter size limit could be varied to achieve
higher or lower precision. Table 3 shows various combinations
of these parameters which all achieve an average PLE of about
5% for the ten consignments in the trial data set. Using a 10%
nominal sampling percentage, a small-end diameter limit of 30 cm
is required to achieve a mean PLE of 5%. The same precision
can be obtained either by reducing the sampling percentage to
7.5% and the diameter limit to 28 cm, or by raising sampling
percentage to 15% and the diameter limit to 40 cm. Under both
these alternative systems, however, the overall percentage of
logs scaled is greater than required by the 10% sampling system.
Note also that to achieve a 5% PLE using the standard sampling
system, a nominal sampling percentage of 22% is required. Of the
various sampling systems shown in Table 3, the one using a 10%
sample of undersized logs and a 30 cm diameter limit results in
the smallest overall percentage of scaled logs. This indicates that
a sampling percentage of about 10% combined with a suitable
diameter limit is likely to provide an acceptable level of precision
in the most cost-effective manner.
Discussion and conclusions
The study data set provided an excellent test of the original
stratified system and the revised sampling systems using varying
diameter size limits. One anomaly in the data was the inclusion
of 66 loads with 25 or fewer logs, which under both the standard
and revised sampling systems were fully scaled. The numbers of
logs in these ‘loads’ ranged from 1 to 24, and as many of the loads
contained large logs, this limited the opportunity for sampling
bias. Thus it is believed that the bias and precision figures for
the standard 10% sampling method obtained in this study may
be less than would be typical in practice.
The use of a diameter restriction in conjunction with stratified
sampling has been successful in Tasmania for a number of years.
This was made possible by bush gangs marking the large end
of each piece. Measurement and therefore sampling challenges
occur where pulp logs are not marked at the large end. In export
operations in New South Wales and Victoria, logs are sampled
along the top of the stack or truckload so that small ends can be
positively identified. In New Zealand, logs are sampled on truck
against the bolster so that the small end can be easily identified.
Potentially, selecting sample logs along the top of a stack or
along the bolster in a truckload could produce biased samples.
For example, there is evidence that when unsegregated pulp logs
are being placed on truck it may be practice to put large-diameter
logs on the outside of the load, and this could lead to bias in the
sample. Under the revised method, such logs would most likely
be included in the fully-scaled oversized portion of the log
population, reducing this potential bias.
However, when the complete study data set was analysed as if it
was a single very large consignment, the average bias using the
standard 10% sampling method with no diameter restriction was
only 1.9 ± 2.4% (mean and 95% confidence interval), indicating
that any bias under this method is minimal. Using the revised
method, the average bias was even smaller — only 1.1 ± 1.1%.
Therefore, the evidence of this study is that both the standard
method and especially the revised method of selecting sample logs
will produce estimates within a typical customer’s expectations
that bias should be no more than 2%. It has to be accepted that
any non-random method of sampling is potentially biased, but
as long as the bias is small it may be acceptable if the method
Table 3. Combinations of undersized log sampling percentages and small-end diameter limits
that achieve a mean PLE of 5%
Sampling system
SED limit (cm)
Revised sampling system
Standard sampling system
24
28
30
40
—
Sampling fraction of
undersized logs (%)
05.0
07.5
10.0
15.0
22.0
Australian Forestry 2009 Vol. 72 No. 1 pp. 32–38
Total fraction of
logs scaled (%)
27.3
17.4
17.3
19.1
25.3
J.C. Ellis and M.O. Kimberley
gives good precision and is cost-effective. It is doubtful whether
100% scaling could achieve an estimate closer than 1%, when one
considers the likelihood of scaling errors in pulpwood because
of small piece size and inability to validate the identification of
the small ends of logs.
To apply the revised method in practice, it is necessary that the
small ends of all logs be readily identifiable so that oversized logs
can be correctly identified and measured. Without the marking
of all logs, identifying the oversized logs at time of scaling is
probably not practical as it is impossible to recognise the small
ends of logs in the centre of loads or stacks. Therefore the large
ends of all logs should be marked in some way prior to loading,
so that the absence of a mark on a log end can be used to indicate
that it is the small end. As long as the logs are clearly marked,
application of the revised method should not cause any significant
complication during the scaling operation, although data capture
and management systems will have to be changed to cope with
the two ‘pseudo loads’ on each docket. However, the end result
will be a robust pulp sampling system.
Stratification is an important feature of both the revised sampling
system described in this paper and the original 10% sampling
system described by Ellis and Kimberley (1995). Substantial
improvements in accuracy and precision over simple random
sampling can potentially be achieved using stratification with
virtually no increase in sampling costs. Stratification is worthwhile
when logs within each stratum are more uniform than in the overall
population. The original system was developed in New Zealand
for scaling logs on truck or rail wagon bunks, a situation in which
each load forms a natural stratum. The variation in log size within
loads was generally found to be considerably lower than in the
overall population, making stratification worthwhile (Ellis and
Kimberley 1995). Similar systems have been used in Australia
where sampling and scaling occurs on log piles or stacks, but it is
less obvious how strata should be defined in these situations. As a
minimum, each stack or pile should be treated as a single stratum.
However, when stacks are large, and especially when logs from
mixed sources are stacked together, improved estimates may be
obtained by dividing stacks into multiple strata.
Selection of strata is especially important when logs are stacked
without any butt or small-end marks. As mentioned above, the
revised sampling procedure cannot be readily used in this situation
because the lack of log end markings makes it impossible to
accurately identify oversized logs in the stack. However, a
stratified sampling system similar to the original method can still
be applied using samples taken from the top of the stack where
the small end can be positively identified. Under this system, the
sampling percentage will vary if the stack height is not constant or
if log size varies along the stack, and potentially this could cause
bias in the estimated mean log size. To overcome this, long stacks
should be divided into strata (e.g. on the basis of distance along the
stack, stack height or sources of logs within the stack) by marking
vertical lines on face of the stack. On one end of each stratum,
any log touching the line should be included in the stratum, while
any log touching the line on the other end of the stratum should
be excluded. Once the strata have been delineated along the
stack, the log count and the average log size of the sampled logs
should be obtained for each stratum, and an overall mean across
the combined strata calculated using Equation 3. As long as the
sampling percentage remains constant within each stratum, there
37
should be little bias using this procedure. The sampling percentage
can vary between strata without causing bias. In this situation,
stratification will not only improve the precision of the estimate
but more importantly will reduce its bias.
Stack sampling issues caused by variation in stack height or log
size are only problematic when logs are sampled on the basis of
their position in the stack (e.g. along the top row). They are not a
problem in the Tasmanian sampling system in which numerically
sequenced paper tickets are placed on the small ends of all pieces
in the stack and a fixed proportion (e.g. every 10th number) is
used as a sample. In natural populations, systematic sampling
systems such as this usually provide more precise estimates
than simple random sampling (Cochran 1977). In this case the
advantage of using stratification is less clear. Because logs are
sampled representatively both within and across potential strata,
the estimate of mean log size under stratification is essentially
identical to a simple mean across all strata. However, stratification
may still be worthwhile as it should provide better estimates of
precision (e.g. the PLE). The revised sampling system described
in this paper can also readily be applied in this case because
oversized logs can be easily identified and measured.
This study identified differences between the log populations at
Northport and Mount Maunganui, the average piece size generally
being larger at the Mount. The consequence was that a common
size limit of 26 cm for both ports resulted in far larger percentage
of logs being scaled at the Mount than at Northport, producing
an unnecessarily high level of precision at the Mount. It may be
practical to vary the size limit depending on the characteristics
of the populations being sampled. For example, to achieve a PLE
of 5%, a size limit of 32 cm could be appropriate for the Mount
but a limit of 28 cm is necessary at Northport.
When choosing an appropriate log scaling system, there must
be a balance between scaling cost and the risk of over- or
under-payment. A 100% scale costs about 5% of the total value
of a consignment to gain a volume estimate within 1% of total
value. Using the revised method, the likely range of over- or
under-payment is increased to 4% for a scaling cost of 1% of
total revenue. The original 10% method costs only 0.5% of total
revenue but estimates of value could vary by as much as 10%.
In the earlier study that led to the development of the standard
10% sample method for pulp logs (Ellis and Kimberley 1995), it
was shown that increasing the sampling percentage above 10%
gave minimal gain in precision. This study shows that real gains in
reduced bias and increased precision can be achieved by sampling
logs below a given diameter limit and complete scaling of logs
above that limit. However, segregating logs before measurement
is still the simplest system.
Acknowledgements
This work was made possible through Ian Leslie of Pacific Forest
Products allowing the free use of data. Thanks are due to Quality
Marshalling (Mount Maunganui) and C3 Limited (Northport)
for the collection of trial data. The authors are grateful to Jerry
Leech and Shayne Jenkins for helpful comments on the draft.
This project was funded through the generosity of Scion Research
and C3 Limited.
Australian Forestry 2009 Vol. 72 No. 1 pp. 32–38
38
Scaling export pulpwood
References
Blythe, R.H. (1945) The economics of sample size applied to the scaling
of sawlogs. Biometrics Bulletin 1, 67–70.
Cochran, W.G. (1977) Sampling Techniques. 3rd edition. John Wiley and
Sons, New York, 428 pp.
Ellis, J.C. and Kimberley, M.O. (1995) Volume estimation of export
pulplogs. New Zealand Journal of Forestry Science 25, 123–132.
Ellis, J.C. and Elliott, D.A. (2001) Log Scaling Guide for Exporters.
Forest Research Bulletin No. 221. Forest Research, Rotorua, NZ,
53 pp.
Appendix. Suggested operational procedures
(truck or stack)
On truck
1. Every log should be butt marked so that small ends can be
identified in the load.
2. Every truck must be sampled.
3. Pulpwood pieces are to be selected and measured for JAS at
the marshalling point as follows:
•Count the number of pieces on each truck unit.
•Ticket and scale for JAS all logs that are greater than the
specified diameter limit (oversized logs).
•If there are fewer than 26 remaining undersized logs, all
remaining logs must be scaled.
•If there are 26 or more undersized logs, 10% (one tenth)
of the remaining undersized logs are sampled and scaled
for JAS. These sample pieces (all below the specified
diameter limit) must be resting against the bolster of the
Oversized logs
Load
1
2
3
4
Totals
Number
Mean log
volume (m3)
Total number
of undersized
logs
12
03
06
00
21
1.10550
0.29800
0.30533
—
0.76152
000
064
066
132
262
truck or trailer unit so that the small end can be positively
identified (as an additional check of correct butt marking)
and measured. Selection of sample pieces should begin on
the bottom of the left side of every load, with logs taken
in order up the side of the load until the required number
of samples is chosen. If insufficient logs are available on
the left side of the load, sampling should continue from the
bottom of the right side of the load.
In stack where small ends of all logs can be identified
(e.g. by butt marking of large ends of all logs)
1. Every stack must be sampled.
2. Pulpwood pieces are to be selected and measured for JAS on
each stack as follows:
•Ticket and measure all logs with small-end diameter greater
than 26 cm.
•Ticket (and count) the unmeasured pieces in each stack.
•Sample 10% of the logs by measuring those logs that have
tickets ending in zero, or some other digit in the range
between zero and nine.
Note that where logs in stacks are unmarked and the sample
logs are taken from the top row of the stack, the revised method
described in this paper cannot be applied because accurate
identification of oversized logs is not feasible.
An example of the volume calculations for a small consignment
is shown below. Note that Load 1 has no undersized logs and
Load 4 has no oversized logs.
Sampled undersized logs
Volume estimates (m3)
Number
Mean log
volume (m3)
Mean log
volume
Total volume
00
07
07
13
27
—
0.19200
0.21529
0.18700
0.19563
1.10550
0.19675
0.22279
0.18700
0.23736
13.266
13.182
16.041
24.684
67.173
Australian Forestry 2009 Vol. 72 No. 1 pp. 32–38
Julian C. Fox, Fiona Hamilton and Sharon Occhipinti
39
Tree hollow incidence in Victorian state forests
Julian C. Fox1,2, Fiona Hamilton3 and Sharon Occhipinti4
1Department
of Forest and Ecosystem Science, Melbourne School of Land and Environment, The University of Melbourne,
Burnley Campus, 500 Yarra Blvd, Richmond, Victoria 3121, Australia
2Email: [email protected]
3Department of Sustainability and Environment, 3/8 Nicholson Street, East Melbourne, Victoria 3002, Australia
4URS Australia Pty Ltd, Level 6, 1 Southbank Boulevard, Southbank, Victoria 3006, Australia
Revised manuscript received 4 December 2008
Summary
The availability of tree hollows in timber production forests is a
contentious issue facing forest and wildlife managers in Australia.
To integrate conservation priorities for hollow-dependent fauna
in forest stewardship, public land managers need information
on the quantity and spatial distribution of hollow-bearing trees.
This information has previously been lacking, but an extensive
hollows database exists in the Victorian Statewide Forest Resource
Inventory (SFRI). We use the SFRI to estimate simple stand-level
models for the density of hollow-bearing trees, and the density
of hollow size classes. Models were of borderline predictive
ability but were statistically significant. This is consistent with
previous models of hollow incidence that have found hollow
formation to be intrinsically stochastic. We then applied these
models in a geographic information system (GIS) to generate
spatial predictions of hollow availability in Victorian state forests.
The resulting GIS layers are available from the Department of
Sustainability and Environment (DSE) and are a valuable resource
for forest and wildlife managers, researchers and the interested
public. We also created tables describing hollow abundance for
different forest types, and important stand-level trends in hollow
availability emerged. We found that hollow density in ash forests
(Eucalyptus regnans, Eucalyptus delegatensis) was consistently
low and strongly influenced by the presence of non-ash species
that are more susceptible to hollow formation. Hollows occurred
in E. regnans forest at particularly low density, with less than
37% of trees having hollows until diameter exceeded 125 cm.
The density of hollows in non-ash forests was comparatively
greater, with more than 49% of trees containing hollows when
their diameter exceeded 75 cm.
Keywords: forest management; wildlife; cavities in trees; habitats;
models; state forests; Victoria
Introduction
Managing state forests for net social benefit requires an ap­pro­
priate balance of timber production and conservation priorities
(Ferguson 1996). Forest managers trying to strike this balance
face many challenges, and amongst the most contentious is the
availability of tree hollows, with previous studies indicating that
a limited availability constrains populations of forest-dwelling
species (Ambrose 1982; Smith and Lindenmayer 1988; Loyn
1993). These include species listed as threatened under the
Environment Protection and Biodiversity Conservation Act 1999
(EPBC Act), and for this reason loss of hollow-bearing trees has
recently been listed as a ‘Key Threatening Process’ under the
EPBC Act. In Victoria, much of the hollow-based habitat for
these species may occur within state forests (Attiwill 1995), but
little is known of the availability and distribution of tree hollows
in these forests.
Tree hollows form as a result of stochastic, episodic events such
as fire, decay by fungal or insect attack, and mechanical damage
from other trees, wind or lightning. Given the stochastic nature
of hollow development and a paucity of information from which
to develop and parameterise predictive models (Gibbons and
Lindenmayer 1996), previous modelling attempts have had
modest success. Models previously developed in Victoria are
those of Lindenmayer et al. (1993), who examined 2315 trees in
the central highlands of Victoria, and Bennett et al. (1994), who
studied 1120 trees on the northern plains of Victoria. Although
both studies identified useful relationships between the incidence
of hollows and individual-tree attributes, the developed models
had limited predictive ability. In a small number of studies trees
have been felled for a more detailed examination of hollow size
and abundance. The extent of such work has been limited because
of the expense of tree felling and dissection and restrictions on
this practice in national parks and state forests (Lindenmayer
et al. 2000), but the studies of Mackowski (1987), Gibbons
(1999), Whitford and Williams (2002) and Koch et al. (2008)
are notable. Unfortunately the limited size of the samples in
these studies hindered the usefulness of the models developed
(Gibbons 1999).
Several studies have attempted to build predictive models for
the incidence of tree hollows, using biotic and abiotic factors to
explain the variation. Studies have used generalised linear models
and have assumed either that counts of hollow incidence follow
a Poisson distribution (e.g., Lindenmayer et al. 1993; Bennett
et al. 1994; Gibbons 1999) or that the presence or absence of
hollows follows a binomial distribution (Lindenmayer et al. 1991;
Gibbons 1999; Fox et al. 2008). These studies indicated that biotic
factors including tree diameter, crown form, age, species and
understorey composition (Lindenmayer et al. 1993; Bennett et
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
40
Tree hollows in Victorian forests
al. 1994; Gibbons 1999), as well as abiotic factors including site
characteristics such as slope, latitude and rainfall (Lindenmayer et
al. 1993; Bennett et al. 1994) influence the incidence of hollows.
The models developed had limited predictive ability, however,
and researchers resigned themselves to identifying simple rules
of thumb that can be coarsely applied (Lindenmayer et al. 2000).
Researchers have speculated that the poor precision of previous
predictive models indicates a need to collect further data at several
spatial scales and to ensure that variables are measured at the
appropriate level of resolution (Lindenmayer et al. 1993).
Victoria’s Statewide Forest Resource Inventory (SFRI) provides
an opportunity to overcome the limitations facing previous
modelling (Fox et al. 2008). As part of SFRI, information on the
incidence of tree hollows was collected in state forests across
Victoria. This information on the distribution and abundance of
tree hollows is critical given the aims of forest management to
balance timber extraction with wildlife conservation (Department
of Natural Resource and Environment 1999). SFRI sampling was
restricted to state forest that is available for timber production.
National park, reserves and areas within state forest that are
unavailable for timber production due to low productivity, steep
slope or proximity to water courses were not sampled in the SFRI.
Despite the sample being restricted to productive and available
state forest, information on tree hollows collected in the SFRI
represents the most extensive database of hollow incidence in
Australian forests.
A methodology for modelling tree-level hollow incidence has
been developed and applied to SFRI data (Fox et al. 2008).
The developed tree-level models can be used to estimate the
probability that any individual tree will have a hollow and can
be used for creating guidelines for tree retention strategies or
for assessing the habitat potential of particular retained trees.
However, the models of Fox et al. (2008) cannot be applied for
stand-level predictions of hollow incidence, and cannot generate
landscape-level information on hollow availability. The models of
Fox et al. (2008) are generalised linear mixed models (GLMMs)
that incorporate a hierarchy of nested and spatial dependence.
Although statistically elegant and theoretically sound, such
complexity may hinder the application of models by forest
management agencies. In this paper, simpler stand-level models
are developed that can be directly applied using existing GIS
layers to generate a spatial layer of hollow density for hollows
of different sizes across Victorian state forest.
The objective of this study was to develop a modelling method
with improved predictive utility that could be readily applied by
practitioners. Models are needed that are capable of generating
spatial predictions of hollow incidence in the form of GIS layers.
Such spatial information is a valuable tool for forest stewardship,
and can facilitate the improved integration of conservation
priorities for hollow-dependent fauna in forest management.
Methods
SFRI hollows database
SFRI hollows data were collected in two stages; in the first stage
the presence or absence of visible hollows was estimated from the
ground for every live or dead tree included in SFRI variable-radius
plots (basal area factor of 3). The first-stage database consists of
25 361 ground-based assessments of hollow presence or absence
across 2683 variable-radius plots. In the second stage the size and
quantity of hollows was measured in three randomly-sampled
trees that were felled for a subset of randomly-selected plots
(Department of Natural Resource and Environment 1999; Fox et
al. 2008). In total 1326 trees were felled for 423 randomly-selected
plots. The dimensions of entries to hollows in felled trees were
categorised into four size classes: 2–5 cm, 5–10 cm, 10–20 cm
and > 20 cm. Dead trees were included in the modelling, as
they often contain hollows: this is particularly the case for ash
forests where pre-1939 stags are an important source of hollows
(Lindenmayer et al. 1990). Therefore we have a large dataset of
first-stage hollow presence or absence, and a smaller subset of
second-stage hollow size and quantity. We used SFRI ground
plots from state forests in Central, Dandenong, Tambo, Central
Gippsland and East Gippsland Forest Management Areas. State
forest in western Victoria and in North-East and Benalla/Mansfield
FMAs was not included due to problems with data consistency
and quality.
Associated with each SFRI ground plot are the attributes of the
aerial photograph interpretation (API) polygon within which the
plot falls. The entire state forest area sampled in the SFRI has
been divided into uniform API polygons that were classified for
species composition, tree height and crown cover (Department
of Natural Resource and Environment 1997), and for which a
number of derived BIOCLIM environmental (McMahon et al.
1995) and radiometric variables (DPI 2005) were generated.
Therefore models relating the number of hollows on SFRI plots
to API polygon and other derived predictors can be applied to the
entire forest estate for spatial predictions of hollow incidence in
state forests.
Modelling hollow-bearing trees per hectare
Several alternative statistical methodologies were tested for standlevel modelling. Using hollow counts in a Poisson regression
resulted in very poor models because hollows were absent in
many plots. Logistic models were also applied to predict the
presence or absence of hollows on SFRI plots but also performed
poorly. For clarity and simplicity we transformed hollow counts
to a continuous metric facilitating the use of classical statistical
methods. Hollow presence on each SFRI tree was converted to
hollow-bearing trees per hectare (HBTHA) based on the diameter
at breast height over bark (dbhob) using equation 1.
HBTHA =
3
dbhob2 (π/40 000)
.
(1)
The sum of HBTHA for all hollow-bearing trees in each plot
resulted in a continuous metric of hollow trees per hectare for
each SFRI plot. This conversion weights the contribution of each
tree according to dbhob to create a statistically valid per-hectare
representation for the variable-radius SFRI plots. The application
of equation 1 resulted in a very large hollow-tree-per-hectare
estimate when a small tree had a visible hollow. These large values
distorted plot-level estimates. To alleviate this it was assumed
that trees of less than 35 cm dbhob do not contain hollows, and
recorded visible hollows in these trees were omitted from the
modelling dataset. This affected only 0.01% of trees.
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
Julian C. Fox, Fiona Hamilton and Sharon Occhipinti
Previous modelling has found that tree diameter is the best
predictor of hollow presence or absence (Bennett et al. 1994;
Fox et al. 2008). To include some indication of tree size in
plot-level estimates, hollow-tree-per-hectare estimates were
calculated for the following diameter classes: 35–75 cm, 75–100
cm, 100–125 cm, 125–150 cm and >150 cm. The sum across
all diameter classes was equivalent to the original plot-level
estimate of hollow trees per hectare. Modelling by diameter
class incorporates information on the size of trees that contain
hollows and can be used as the basis for predicting quantities of
hollow sizes.
For each diameter class, linear regression was applied with
hollow-bearing trees per hectare as the dependent variable,
and 75 API and 38 environmental and radiometric variables
as independent variables. The all-possible-subset algorithm of
SAS PROC REG (SAS Institute Inc. 1996) was used to identify
optimal subsets of predictors. These subsets were then examined
for ‘biological reality’ to ensure that relationships were consistent
with what is known of hollow formation and hollow incidence.
If a biological explanation could not be identified then predictors
were rejected. Finally, models were subject to diagnostic
testing for multicollinearity, influential observations, and the
assumptions of normal and independent errors (Rawlings 1988).
Spatial dependence among model residuals was examined using
correlograms and was found to negligible.
After modelling the number of hollow-bearing trees per hectare
in each diameter class, we estimated the average quantity of the
four hollow size classes (2–5 cm, 5–10 cm, 10–20 cm and >20 cm)
for felled trees. This allowed an estimate of the quantity of each
hollow size class for the stand by multiplying the hollow-bearing
trees per hectare by the mean number of each hollow size class. To
accomplish this, the average number of hollows for each hollow
size class was calculated for each diameter class for felled trees.
Only felled trees with a hollow present were included in this
analysis (164 of the 1326 felled trees). Where diameter classes
were under-sampled, they were combined across diameter classes
to create an adequate sample size of more than ten samples.
Stratification
The SFRI hollows database covers an extensive area of diverse
forest, so stratification was required to improve model precision.
We stratified the database initially into East Gippsland and nonEast Gippsland forest. East Gippsland forests have quite different
characteristics compared to other FMAs, and constitute a large
dataset in their own right (1305 plots). To identify trends in hollow
incidence based on forest type, remaining areas were stratified by
the dominant species classification of the API polygon. The final
stratification and the number of plots were as follows:
East Gippsland
• All forest types — 1305 plots
41
• Messmate (E. obliqua forest) — 167 plots
• Mixed species forest (all remaining stands) — 491 plots
The modelling was undertaken separately in each of the five
forest types to generate diameter class models of hollow-bearing
trees per hectare, and to estimate the availability of each hollow
size class.
Validation
Given the extensive nature of the SFRI hollows database, there
was an opportunity to keep a portion of the database separate
from model building for model validation, which is an important
step in the development of robust predictive models (Vanclay
and Skovsgaard 1997). Validation becomes crucial when the
data are divided into forest-type categories and diameter classes
within forest types, and can test whether models are performing
within these classes and more globally when hollows are summed
across classes. Validation datasets for each model were created
by randomly selecting 25% of SFRI first- and second-stage
samples. The validation datasets for the first-stage plot sample
consisted of 325 and 345 plots from East Gippsland and non-East
Gippsland respectively. For the second stage sample, 40 of the
164 felled trees with hollows were set aside. Models were built
and parameterised using the remaining 75% of plot data, and then
applied to the validation dataset for an independent assessment
of predictive capabilities. Following validation, models were
re-examined and re-parameterised using all the data combined.
Results
Validation
Figures 1 and 2 illustrate the degree of concurrence between
actual and predicted values for the validation datasets within the
75–100 cm diameter class, and summed across diameter classes
respectively. Figure 1 is unconvincing because most trees do not
have hollows, and the actual values tend to be banded. The R 2
is therefore low (0.23), and the linear regression does not pass
through zero. Despite this unconvincing result, the significant
relationship between predicted and observed suggests we should
proceed. Figure 2 demonstrates that models of total hollow trees
per hectare are performing more satisfactorily when applied to the
valida­tion dataset: the simple linear regression has a higher R 2 (0.3)
and graphical correspondence between predicted and observed
values is improved. These results concur with previous studies
that hollow-incidence models explain only small to moderate
amounts of the variability in what appears to be a highly stochastic
event. Figures 1 and 2 are for non-East Gippsland; graphs for East
Gippsland and for other diameter classes demonstrated similar
low to moderate predictive strength (R 2 between 0.2 and 0.35).
Following model validation, all data were combined and final
models were parameterised as described below.
Eucalyptus delegatensis forest
Non-East Gippsland: Dandenong, Central, Tambo, Central
Gippsland
• Alpine ash (E. delegatensis forest) — 381 plots
• Mountain ash / shining gum (E. regnans and E. nitens forest)
— 339 plots
Models of hollow-bearing trees per hectare for E. delegatensis
are shown in Table 1, and varied in strength from 12% to 21%
explained variability. Despite explaining only a small amount of
variability, the models were significant and provided an acceptable
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
Tree hollows in Victorian forests
12
10
8
6
4
2
0
R 2 = 0.2335
0
5
10
15
20
25
30
35
40
Actual number of hollow-bearing trees per hectare
45
Figure 1. Validation for the number of hollow-bearing trees per hectare,
75–100 cm diameter class, for Non-East Gippsland
Predicted number of hollowbearing trees per hectare
Predicted number of hollowbearing trees per hectare
42
70
60
50
40
30
20
10
R 2 = 0.3032
0
0
50
100
150
200
Actual number of hollow-bearing trees per hectare
Figure 2. Validation for the number of hollow-bearing trees per hectare,
summed across all diameter classes for Non-East Gippsland
Table 1. Models for Eucalyptus delegatensis forest
Diameter class (cm)
Model
0–74.9
75–99.9
100–124.9
125–149.9
150 +
Hollow trees per hectare
PredictorsA
Intercept
Mature SFRI
Vi Percent
Potassium
Cm Regir
Mix Ash Percent
Cy Percent
Rsquare
Mean Tree/ha
Mean HolTree/ha
Mean DeHolTree/ha
% hollow trees De
% trees with hollows
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
–3.545
–2.954
< 0.1880
< 0.0280
< 0.0240
< 0.0001
0.412
2.335
< 0.0000
< 0.0001
–1.450
< 0.0000
< 0.0070
< 0.0001
< 0.0001
< 0.0010
0.553
1.880
–6.649
–1.659
–2.581
–0.248
–0.050
< 0.0001
0.018
< 0.0360
–0.126
–1.364
–0.017
< 0.0001
< 0.0001
< 0.0001
1.379 < 0.0001
000.17
291.00
004.79
000.83
017.33
001.65
Hollow size classes per hollow treeB
Hollow size class (cm)
Samples Average
02.1–5
05.1–10
10.1–20
20.1 +
9
9
9
9
1.000
0.444
0.111
0.000
00.12
15.44
02.69
00.93
34.57
17.42
00.16
03.22
01.56
00.82
52.56
48.45
0.21
1.34
0.96
0.54
56.25
71.64
00.20
00.66
00.58
00.30
51.72
87.88
Samples Average
Samples Average
Samples Average
Samples Average
13
13
13
13
0.833
0.615
0.667
0.167
11
11
11
11
1.000
0.909
0.818
0.545
15
15
15
15
0.866
0.800
0.933
0.733
15
15
15
15
0.866
0.800
0.933
0.733
Top row of the table are diameter classes, Mean DeHolTree/ha is the mean number of E. delegatensis that contain hollows per hectare, and % hollow trees De is the
percentage of hollow trees that are E. delegatensis. For hollow size classes; Samples is the number of felled trees used to compute the Average of hollow size class
per tree. Mature SFRI; identifies stands where crown cover is dominated by mature or older crowns. Vi Percent; percent of eucalypt crown cover that is E. viminalis.
Potassium; radiometeric energy spectrum which relates to the decay of K40 (Potassium) isotopes. Crn Reglr; percent of regular crowns. MixAsh Percent; percent of
crown cover that is ash. Cy Percent; percent of crown cover that is E. cypellocarpa.
predictive framework for a highly stochastic event such as
hollow formation. The ‘Mature SFRI’ predictor identified mature
E. delegatensis forests, and the parameter estimate indicated that
these forests have more hollow-bearing trees. ‘Potassium’ is a
radiometric variable that measures the potassium response, and
has been associated with drier sites. It could be hypothesised that
hollow formation is more likely on these drier sites as trees are
more susceptible to fire (an important agent of hollow formation)
and are under stress, making them susceptible to disease and insect
attack. Other predictors such as ‘Vi Percent’, ‘MixAsh Percent’
and ‘Cy Percent’ identify the presence of non-ash (E. viminalis,
E. cypellocarpa and minor mixed species) that are contributing
to the number of hollow-bearing trees. To investigate this further
we calculated the percentage of E. delegatensis that contained
hollows. It is important to understand this incidence in ash forests,
where hollow-bearing trees may be predominately non-ash
species. This is confirmed for E. delegatensis as the species rarely
contained hollows; only 17% of hollow trees were E. delegatensis
for the < 75-cm diameter class, whilst this rose to 52% for the
> 150-cm diameter class.
Very few trees in the smaller diameter classes contain hollows:
only 2% of trees < 75 cm dbhob. This increases for the larger
diameter classes until 88% of trees > 150 cm contain hollows. The
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
Julian C. Fox, Fiona Hamilton and Sharon Occhipinti
overall number of hollow-bearing trees per hectare is small, rang­
ing from 5 ha–1 for the smallest diameter class (mainly be­cause
there are so many small trees) to 0.6 ha–1 for the largest diameter
class. Therefore on average there is a single hollow-bearing tree
>150 cm dbhob for every 2 ha of E. delegatensis forest.
The average number of each hollow size class for hollow-bearing
trees indicates that a hollow-bearing tree can be expected to
contain about one hollow of the smallest size class. However,
larger hollows occur only in larger trees — that is hollows above
20 cm in diameter occur at the rate of 0.7 per hollow-bearing tree
when dbhob exceeds 125 cm.
Eucalyptus regnans and Eucalyptus nitens forest
Predictors for E. regnans and E. nitens detailed in Table 2 were
similar to those for E. delegatensis: the potassium radiometric
response, that identifies drier sites, indicated more hollow-bearing
trees per hectare; ‘Mature SFRI’, an indicator for mature stands,
and the presence of non-ash species (‘High Cover Mx Perc’ and
‘Ra Percent’) were also indicative of more hollow-bearing trees
per hectare. ‘Crn Irreg’, which identifies the proportion of the
irregular component of eucalypt crown cover, was also associated
with more hollow-bearing trees; trees with irregular crowns are
more likely to contain hollows as they are generally senescent
stags, or are under stress.
43
Models for E. regnans were quite weak, with R-square values
between 0.09 and 0.18. Although the models are statistically
significant, the small amount of variability explained signifies the
unpredictable nature of hollow occurrence in these forests. The
predicted incidence of hollow-bearing trees per hectare is very
small, with less than two hollow trees per hectare for all diameter
classes except the smallest.
For E. regnans-dominated forest, even fewer hollow-bearing
trees were actually E. regnans: only 15% were E. regnans for
the < 75 cm class, whilst this rose to 31% for the > 150 cm class.
This indicates the importance of minor non-ash species in these
forests for providing hollow-based habitat.
Eucalytpus obliqua forest
Table 3 indicates that E. obliqua-dominated forest contained
more hollow-bearing trees than ash forests; 11 ha–1 for dbhob
< 75 cm falling to 1 ha–1 for dbhob > 150 cm. The proportion of
hollow-bearing trees that were actually E. obliqua was greater
than in ash; 29% for the < 75 cm class that rose to 54% for the
> 150 cm class. These statistics indicate that E. obliqua is more
prone to hollow formation, perhaps because the trees have more
branches and less regular crowns, and are more susceptible to
fire, rot and insect attack.
Table 2. Models for Eucalyptus regnans and E. nitens forest
Diameter class (cm)
Model
0–74.9
75–99.9
100–124.9
125–149.9
150 +
Hollow trees per hectare
PredictorsA
Parameter
Intercept
Potassium
Ra Percent
High Cover Mx Perc
Mature SFRI
Crn Irreg
Rsquare
Mean Tree/Ha
Mean HolTree/Ha
Mean ReHolTree/Ha
% Re with hollows
% trees with hollows
–8.58281 < 0.0005
14.73904 < 0.0001
03.79434 < 0.0030
Pr > F
Pr > F
–2.46297
04.45376
3.1440
00.07143
< 0.0099
< 0.0001
< 0.0001
< 0.0005
13
13
13
13
0.917
1.000
1.308
0.615
Parameter
Pr > F
Parameter
Pr > F
Parameter
–1.61902 < 0.0122
03.06176 < 0.0001
–0.47579
01.07301
0.2047
0.0132
02.08125 < 0.0001
–1.59049 < 0.0059
00.04245 < 0.0022
0.8157 < 0.0139
00.02782
0.0005
00.17
16.46
01.79
00.36
02.19
20.11
00.10
03.89
01.42
00.22
05.66
15.49
00.08564 0.0020
00.08
01.22
00.79
00.15
12.30
18.99
Samples Average
Samples Average
Samples Average
000.09
222.91
004.07
000.59
000.26
014.50
Hollow size classes per hollow treeB
Hollow size class (cm)
Samples Average
02.1–5
05.1–10
10.1–20
20.1 +
Parameter
13
13
13
13
0.917
1.000
1.308
0.615
9
9
9
9
1.333
0.556
0.889
0.667
9
9
9
9
1.333
0.556
0.889
0.667
Pr > F
00.74115 < 0.0043
00.14395 < 0.0001
00.08
01.45
01.25
00.39
26.90
31.20
Samples Average
9
9
9
9
1.333
0.556
0.889
0.667
A
Potassium = radiometeric energy spectrum which relates to the decay of K40 (potassium) isotopes. Ra Percent = percent of eucalypt crown cover that is E. radiata.
High Cover Mx Perc = percent crown cover of mixed species with high productivity. Mature SFRI identifies stands where crown cover is dominated by mature or
older crowns. Crn Irreg = percent of irregular crowns. Mean Tree/Ha = the mean number of trees per hectare. Mean HolTree/Ha = the mean number of trees that
contain hollows per hectare. Mean ReHolTree/Ha = the mean number of E. regnans that contain hollows per hectare. % Re with hollows = the percentage of
E. regnans trees that have hollows.
B
For ‘Hollow size classes per hollow tree’, Samples = the number of felled trees used to compute the average of hollow size class per tree.
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
44
Tree hollows in Victorian forests
Table 3. Models for Eucalyptus obliqua forest
Diameter class (cm)
Model
0–74.9
75–99.9
100–124.9
125–149.9
150 +
Hollow trees per hectare
PredictorsA
Intercept
Site Index
Di Percent
Logn Elevation
Mean temp cold quart
FaCyObSiViMixAshP
Rsquare
Mean Tree/Ha
Mean HolTree/Ha
Mean ObHolTree/Ha
% Ob with hollows
% trees with hollows
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
46.309
–1.735
01.098
0.002
0.013
0.001
01.686
–0.703
0.863
0.003
70.225
0.011
44.636
0.004
03.182
< 0.0001
02.833
0.025
–7.630
–3.309
0.026
0.002
–4.811
–2.192
0.012
0.000
–0.053
< 0.0520
00.11
05.48
03.46
02.06
37.59
59.54
00.17
02.43
01.96
1.2
49.38
61.22
Samples Average
Samples Average
Samples Average
Samples Average
000.16
180.82
011.09
003.26
001.80
029.40
Hollow size classes per hollow treeB
Hollow size class (cm)
Samples Average
02.1–5
05.1–10
10.1–20
20.1 +
00.09
14.22
04.88
02.31
16.24
47.34
–0.395 < 0.0000
00.019 < 0.0000
00.19
01.23
01.14
00.62
50.41
54.39
13
13
13
13
0.750
0.583
0.083
0.308
13
13
13
13
0.750
0.583
0.083
0.308
8
8
8
8
2.625
1.625
0.375
1.000
8
8
8
8
2.625
1.625
0.375
1.000
8
8
8
8
2.625
1.625
0.375
1.000
A
Site Index = site productivity estimate based on stand height. Di Percent = percent of eucalypt crown cover that is E. dives. Logn Elevation = natural log of
elevation. Mean temp cold quart = BIOCLIM variable describing mean temperature of the coldest quarter. FaCyObSiViMixAshP = percentage eucalypt crown
cover that is E. fastigata, E. cypellocarpa, E. obliqua, E. sieberi, E. viminalis ssp. viminalis and mixed ash. Mean Tree/Ha = the mean number of trees per hectare.
Mean HolTree/Ha = the mean number of trees that contain hollows per hectare. Mean ObHolTree/Ha = the mean number of E. obliqua that contain hollows per
hectare. % Ob with hollows = the percentage of E. obliqua trees that have hollows.
B
For ‘Hollow size classes per hollow tree’, Samples = the number of felled trees used to compute the average of hollow size class per tree.
Significant predictors were ‘Site Index’, ‘Di Percent’, ‘Logn
Elevation’, ‘Mean temp cold quarter’, and ‘FaCyObSiViMixAshP’.
Forest of higher site index had fewer hollow-bearing trees per
hectare because on better sites trees will be under less stress,
resulting in better form, more regular crowns and reduced
susceptibility to agents of hollow formation such as fire, insects
and rot. Similarly, lower elevations had more hollows (indicated
by the negative parameter on ‘Logn Elevation’), perhaps due to
sites being poorer at lower elevations. ‘Mean temperature of the
coldest quarter’ is a BIOCLIM variable that may result in fewer
hollow-bearing trees due to a warmer winter creating better
growing conditions for E. obliqua forests.
Models were of similar strength to those for ash, if not marginally
stronger, with R 2 values from 0.09 to 0.19. The average number of
hollows per hollow-bearing tree was also greater, with 2.6 hollows
of < 5 cm, and 1 hollow of > 20 cm on each hollow-bearing tree
> 100 cm in dbhob.
Mixed-species forests
This forest type consisted of stands not dominated by ash or
E. obliqua in non-East Gippsland FMAs. The models are shown
in Table 4, and were of similar strength to previous models. The
number of hollow-bearing trees per hectare was similar to that
found in E. obliqua but with more smaller hollow-bearing trees,
and fewer larger hollow-bearing trees. However, the average
number of hollows per hollow-bearing tree was relatively
small.
Larger stand heights resulted in more large hollow-bearing trees,
perhaps because taller forests are more likely to have larger
trees. Higher percentages of pure ash (‘Pure Ash Percent’) and
E. nitens (‘Ni Percent’) resulted in fewer hollow trees because,
as observed before, these species have fewer hollows. Higher
proportions of irregular and regular crowns (‘Crown Irreg Reglr’)
resulted in more hollow trees because irregular crowns are more
likely to contain hollows. ‘Wetness index’ and ‘Precipitation’ are
BIOCLIM variables that indicated fewer hollow-bearing trees,
perhaps because they provided better growing conditions.
East Gippsland — all forest types
Table 5 indicates that models for East Gippsland were stronger
for the larger diameter classes (R 2 of 0.31 for dbhob > 150 cm).
Important predictors identified hollow-prone species such as
E. croajingolensis and E. fastigata (‘Cr Percent’ and ‘Fa Percent’
respectively). Higher site index resulted in more hollow-bearing
trees, an opposing relationship to that observed in non-East
Gippsland forests. This may be due to the varied forest types
present in East Gippsland, and the large range in site index
from nutrient-poor coastal sites to more productive inland sites.
‘Max temp’ was a BIOCLIM variable estimating the maximum
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
Julian C. Fox, Fiona Hamilton and Sharon Occhipinti
45
Table 4. Models for mixed species forest
Diameter class (cm)
Model
0–74.9
75–99.9
100–124.9
125–149.9
150 +
Hollow trees per hectare
PredictorsA
Intercept
Stand Ht
Potassium
Crown Irreg Reglr
Wetness index
Precipitation
Pure Ash Percent
Rsquare
Mean Tree/Ha
Mean HolTree/Ha
% trees with hollows
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
Parameter
Pr > F
48.560
–0.666
08.244
00.217
–4.784
< 0.0002
< 0.0001
< 0.0284
< 0.0002
< 0.0040
09.211
0.017
–3.670
00.070
0.003<
0.018<
–2.898
00.093
< 0.0001
< 0.0001
00.056
0.006
–1.274
0.027
00.021
0.004
–0.086
0.009
00.06
14.56
07.14
49.04
00.034
0.001<
–2.057
00.092
–0.602
< 0.0001
< 0.0001
< 0.002
00.020
0.0001
–0.064 0.000<
00.12
04.68
03.32
70.94
00.007 < 0.001
–0.031 < 0.001
00.10
01.56
01.31
83.97
–0.016 < 0.002
00.21
00.75
00.67
89.33
Samples Average
Samples Average
Samples Average
Samples Average
000.12
192.05
016.56
008.62
Hollow size classes per hollow treeB
Hollow size class (cm)
Samples Average
02.1–5
05.1–10
10.1–20
20.1 +
25
25
25
26
0.520
0.320
0.160
0.269
30
30
30
30
0.867
0.667
0.267
0.033
18
18
18
18
0.444
0.500
0.944
0.556
18
18
18
18
0.444
0.500
0.944
0.556
18
18
18
18
0.444
0.500
0.944
0.556
A
Stand Ht = height of dominant crown cover component. Potassium = radiometeric energy spectrum which relates to the decay of K40 (potassium) isotopes. Crown
Irreg Reglr = percent of irregular and regular crowns. Wetness index = BIOCLIM variable for the steady state wetness index. Precipitation = BIOCLIM variable for
annual precipitation. Pure Ash Percent = crown cover of stands consisting entirely of E. delegatensis, E. regnans, E. nitens or E. denticulata. Mean Tree/Ha = the
mean number of trees per hectare. Mean HolTree/Ha = the mean number of trees that contain hollows per hectare.
B
For ‘Hollow size classes per hollow tree’, Samples = the number of felled trees used to compute the average of hollow size class per tree.
Table 5. Models for East Gippsland — all species
Diameter class (cm)
Model
0–74.9
75–99.9
100–124.9
125–149.9
150 +
Hollow trees per hectare
PredictorsA
Intercept
Is Tfire 1983
Max temp
Site Index
Cr Percent
Fa Percent
Rsquare
Mean Tree/Ha
Mean HolTree/Ha
% trees with hollows
Parameter
Pr > F
Parameter
Pr > F
65.560
04.549
–1.264
–1.379
00.284
< 0.0001
< 0.0001
< 0.0080
< 0.0001
< 0.0001
26.725
02.055
–0.966
< 0.0001
< 0.0001
< 0.0001
00.089
< 0.0001
02.1–5
05.1–10
10.1–20
20.1 +
27
27
27
27
0.926
0.519
0.185
0.037
Pr > F
Parameter
Pr > F
Parameter
Pr > F
05.122
< 0.0002
03.494
–0.270
–0.292
00.210
< 0.0014
< 0.0069
< 0.0001
< 0.0001
00.08
13.64
04.64
34.02
11.680 < 0.0001
01.192 < 0.0001
–0.618 < 0.0001
00.256 < 0.0001
00.023 < 0.0220
00.042 < 0.0001
00.17
04.53
02.34
51.66
–0.318 < 0.0001
00.167 < 0.0001
00.010 < 0.0441
00.049 < 0.0001
00.25
01.53
00.95
62.09
Samples Average
Samples Average
Samples Average
000.09
176.41
011.83
006.71
Hollow size classes per hollow treeB
Hollow size class (cm)
Samples Average
Parameter
27
27
27
27
0.926
0.519
0.185
0.037
14
14
14
14
1.071
0.929
0.786
0.357
A
14
14
14
14
1.071
0.929
0.786
0.357
00.039 < 0.0001
00.31
00.85
00.59
69.41
Samples Average
14
14
14
14
1.071
0.929
0.786
0.357
Is Tfire 1983 = stands affected by the 1983 fire. Max temp = BIOCLIM variable for maximum temperature. Site Index = site productivity estimate based on stand
height. Cr Percent = percent of eucalypt crown cover that is Eucalyptus croajingolenisis. Fa Percent = percent of eucalypt crown cover that is E. fastigata.
B
For ‘Hollow size classes per hollow tree’, Samples = the number of felled trees used to compute the average of hollow size class per tree.
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
46
Tree hollows in Victorian forests
temperature of the warmest period, and indicated fewer hollowbearing trees for higher values. The predictor ‘Is Tfire 1983’
identified stands affected by fires in 1983; these stands had more
hollow-bearing trees. This can be explained by the influence of
fire in initiating or advancing hollow formation due to scarring,
damage and stress. Each hollow-bearing tree was predicted to
have a single hollow 2–5 cm in diameter, whist larger hollows
were less frequent.
Comparing trends across forest types
Figure 3 shows trends in the incidence of trees with hollows across
diameter classes for different forest types. All species show an
increase in the percentage of trees with hollows as the size of the
trees increases. E. delegatensis and E. regnans show lower initial
values for smaller diameters, after which there is a steady increase
in the percentage of trees with hollows. For other species initial
values are higher, and the trend is more asymptotic, starting to
level off beyond 100 cm. Different trends between ash and non-ash
forests reflect differing susceptibility to hollow formation across
diameter classes; non-ash species appear more susceptible for
smaller diameters, while ash forests resist hollow formation until
trees move into the largest diameter classes.
Model application
Percentage of trees with hollows
The models related the number of hollows on SFRI plots to
API polygon predictors and spatially continuous climatic and
radiometric variables. Therefore they can be applied to GIS layers
to create a spatially continuous prediction of the incidence of
hollow-bearing trees per hectare and the number of hollows in
each size class per hectare across state forest in eastern Victoria.
The resulting spatial predictions were examined to ensure that
models were behaving realistically. An example application to a
section of Central Gippsland is provided in Figure 4, and shows
how hollow occurrence tends to be spatially clumped — that is,
stands with more hollow-bearing trees tend to occur in spatial
proximity. GIS layers describing hollow density in each tree size
class and the density of hollows of different sizes are available
from the Department of Sustainability and Environment (DSE)
Corporate Spatial Data Library (CSDL). External access to this
100
90
80
70
60
E. delegatensis
E. regnans
E. obliqua
Mixed spp.
East Gippsland
50
40
30
20
10
0
0–74.9
75–99.9
100–124.9 125–149.9
150 +
Diameter classes (cm)
Figure 3. Trends in percent trees with hollows across diameter classes
for forest types
data can be arranged through the Data Distribution Manager: data.
[email protected].
Discussion
Previous studies have indicated that tree size (dbhob) is the most
important predictor of hollow incidence (Fox et al. 2008; Koch
et al. 2008), and this was incorporated in stand-level models
by modelling hollow occurrence within diameter classes. Tree
diameter is a useful proxy for tree age, and given the various
stochastic events capable of initiating hollow development (fire
damage, limb breakage and external damage from falling timber
due to strong winds, snow and lightning strike), the older the
tree, the more likely it is that such stochastic events will have
occurred (Mackowski 1984; Lindenmayer et al. 1993; Bennett
et al. 1994).
Several important stand-level trends for ash forests emerged:
drier sites and more mature forests tended to have higher
densities of hollows, but hollow density in E. delegatensis and
E. regnans forest was consistently low and strongly influenced
by the presence of minor non-ash species. Ash species may only
rarely develop hollows as they tend to be healthy and vigorous,
and relatively free of decay by fungal or insect attacks that may
initiate hollow formation. Hollow formation may occur only when
stands become senescent and more prone to decay and damage.
For this reason some researchers have estimated that it may take
120–200 y before ash develops hollows (Smith 1982; Smith and
Lindenmayer 1992). The trend in hollow density across diameter
classes for E. regnans (Fig. 3) supports this, with low hollow
densities (<36% of trees) until trees are > 100 cm when it rises
to 65%. The ash forests sampled in the SFRI are dominated by
1939 regrowth consisting of largely mono-specific stands with
a few remnant stags that predate 1939, many of which are dead.
Previous studies have indicated that these dead stags are an
important source of hollows and that their collapse is depleting
the resource further (Lindenmayer et al. 1990). It is intuitive that
the brittle timber of dead trees is highly susceptible to hollow
formation due to limb breakage and the lack of mechanisms to
respond to hollow-causing agents such as fungal infection and
insect attack including excavation by termites.
Non-ash (E. obliqua and mixed) forests contained comparatively
more hollows than ash forests, particularly in the smaller diameter
classes (29% of trees < 75 cm dbhob contained a hollow for
E. obliqua compared with 15% for E. regnans). This result
sug­gests that tree species in these forests are more prone to
hollow formation. The physiology and morphology of different
tree species will be important as they determine the extent of
branch shedding, the ability to survive fire events, and they
influence timber properties that dictate susceptibility to a variety
of hollow-causing agents (Lindenmayer et al. 1993; Bennett et
al. 1994; Lindenmayer et al. 2000). Particular species may also
have a higher incidence of defect in the stem, which will result in
more hollows. Sensitivity to fire is also important as species able
to survive fire events are very likely to develop hollows (Taylor
and Haseler 1993).
A suite of models for predicting hollow-bearing trees per
hectare, and the abundance of hollows of various size on these
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
Julian C. Fox, Fiona Hamilton and Sharon Occhipinti
47
Legend
0.0–4.0
4.1–10.0
10.1–20.0
20.1–25.0
25.1–30.0
30.1–40.0
40.1–50.0
50.1–100.0
100.1–200.0
Metres
10000
N
Figure 4. Example application of a model to an area of Central Gippsland for the 2–5-cm hollow size class. The
predicted attribute is the number of hollows 2–5 cm in diameter per hectare. Blank areas are non-state forest.
hollow-bearing trees, were parameterised using SFRI data. The
central modelling objective was to ensure models were relatively
simple and could be readily applied, whilst still being mindful of
statistical assumptions. This objective was met by transforming
hollow occurrence to a continuous dependent variable that could
be modelled against stand-level predictors. With a prediction of
hollow-bearing trees per hectare, the number of each hollow size
class on these trees could be estimated using averages from the
second-stage SFRI sample of felled trees. A validation exercise
using independent data demonstrated that models of hollowbearing trees per hectare provided predictions of borderline but
acceptable accuracy. Hollow formation is intrinsically stochastic
and therefore explained variation was generally less than 25%,
but the models were statistically significant and the parameters
were biologically plausible. The models were used to generate GIS
layers of hollow abundance for state forests in eastern Victoria that
will be useful for improving forest stewardship and conservation
efforts for hollow-dependent fauna.
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
48
Tree hollows in Victorian forests
The models detailed in this paper can be used to improve the
integration of conservation priorities for hollow-dependent fauna
in the management of timber production forests. Their application
at the stand level yielded a prediction of hollow incidence in
some of Victoria’s most contentious timber production forests.
This information will be useful for testing hypothesis as to the
limited availability of hollows in state forests (e.g. Lindenmayer
1995), and may help resolve contentions surrounding this (e.g.
Macfarlane and Loyn 1994; Attiwill 1995).
References
Ambrose, G.J. (1982) An ecological and behavioural study of vertebrates
using hollows in eucalypt branches. Unpublished PhD thesis, La
Trobe University, Melbourne.
Attiwill, P.M. (1995) Managing Leadbeater’s possum in the mountain
ash forests of Victoria, Australia — Reply. Forest Ecology and
Management 74, 233–237.
Bennett, A.F., Lumsden, L.F. and Nicholls, A.O. (1994) Tree hollows as
a resource for wildlife in remnant woodlands: spatial and temporal
patterns across the northern plains of Victoria, Australia. Pacific
Conservation Biology 1, 222–235.
Department of Natural Resources and Environment (1997) SFRI,
Victoria’s Statewide Forest Resource Inventory Program Overview.
Forests Service Technical Reports 97-1. Department of Natural
Resources and Environment, Victoria.
Department of Natural Resources and Environment (1999) Victoria’s
Statewide Forest Resource Inventory: Bennalla/Mansfield,
Wangaratta and Wodonga Forest Management Areas. Forests
Service Technical Reports 99-2. Department of Natural Resources
and Environment, Victoria.
Department of Primary Industries (2005) Digital geophysical data for
Victoria: statewide gridded airborne magnetic and radiometric
data and located and gridded gravity data. GDA94 data released
October 2005. Geoscientific Data Package. Melbourne, Victoria,
Australia.
Ferguson, I.S. (1996) Sustainable Forest Management. Oxford University
Press, Melbourne, 162 pp.
Fox, J.C., Hamilton, F. and Ades, P.K. (2008) Models of tree-level
hollow incidence in Victorian state forests. Forest Ecology and
Management 255, 2846–2857.
Gibbons, P. (1999) Habitat-tree retention in wood production forests.
Unpublished PhD thesis, Australian National University, 242 pp.
Gibbons, P. and Lindenmayer, D.B. (1996) Issues associated with the
retention of hollow-bearing trees within eucalypt forests managed
for wood production. Forest Ecology and Management 83,
245–279.
Koch, A.J., Munks, S.A., Driscoll, D. and Kirkpatrick, J.B. (2008). Does
hollow occurrence vary with forest type? A case study in wet and
dry Eucalyptus obliqua forest. Forest Ecology and Management
255, 3938–3951.
Lindenmayer, D.B. (1995) Forest disturbance, forest wildlife
conservation and the conservative basis for forest management in
the mountain ash forests of Victoria — comment. Forest Ecology
and Management 74, 223–231.
Lindenmayer, D.B., Cunningham, R.B., Tanton, M.T. and Smith, A.P.
(1990) The conservation of arboreal marsupials in the montane ash
forests of the central highlands of Victoria, South-Eastern Australia:
II. The loss of trees with hollows and its implications for the
conservation of Leadbeater’s possum Gymnobelideus leadbeateri
McCoy (Marsupialia: Petauridae). Biological Conservation 54,
131–145.
Lindenmayer, D.B., Cunningham, R.B., Nix, H.A., Tanton, M.T. and
Smith, A.P. (1991) Predicting the abundance of hollow-bearing trees
in montane forest of southeastern Australia. Australian Journal of
Ecology 16, 91–98.
Lindenmayer, D.B., Cunningham, R.B., Donnelly, C.F., Tanton, M.T.
and Nix, H.A. (1993) The abundance and development of cavities
in Eucalyptus trees: a case study in the montane forests of Victoria,
southeastern Australia. Forest Ecology and Management 60,
77–104.
Lindenmayer, D.B., Cunningham, R.B., Pope, M.L., Gibbons, P.
and Donnelly, C.F. (2000) Cavity sizes and types in Australian
eucalypts from wet and dry forest types — a simple rule of thumb
for estimating size and number of cavities. Forest Ecology and
Management 137, 139–150.
Loyn, R.H. (1993) Effects of Previous Logging on Bird Populations in
East Gippsland: VSP Retrospective Study. VSP Technical Report
No. 18. Department of Conservation and Natural Resources,
Melbourne.
Macfarlane, M.A. and Loyn, R.H. (1994) Management for the
conservation of Leadbeater’s possum (Gymnobelideus leadbeateri)
— a reply. Pacific Conservation Biology 1, 84–86.
Mackowski, C.M. (1984) The ontogeny of hollows in blackbutt,
Eucalyptus pilularis, and its relevance to the management of forests
for possums, gliders and timber. In: Smith, A.P. and Hume, I.D.
(eds) Possums and Gliders. Surrey Beatty, Sydney, pp. 517–525.
Mackowski, C.M. (1987) Wildlife hollows and timber management
in blackbutt forest. Unpublished MSc thesis. University of New
England, Armidale, Australia.
McMahon, J.P. Hutchinson, M.F., Nix, H.A. and Ord, K.D. (1995)
ANUCLIM: Users Guide. Centre for Resource and Environmental
Studies, Australian National University, Canberra, ACT, Australia.
Rawlings, J.O. (1988) Applied Regression Analysis. Wadsworth &
Brooks/Cole, Belmont, California.
SAS Institute, Inc. (1996) SAS/STAT Software: Changes and Enhance­
ments through Release 6.11. SAS Institute Inc., Cary, NC.
Smith, A.P. (1982) Leadbeater’s possum and its management. In: Groves,
R.H. and Ride, W.D. (eds) Species at Risk: Research in Australia.
Australian Academy of Science, Canberra, pp. 129–145.
Smith, A.P. and Lindenmayer, D.B. (1988) Tree hollow requirements
of Leadbeater’s possum and other possums and gliders in timber
production ash forests of the Victorian Central Highlands.
Australian Wildlife Research 15, 347–362.
Smith, A.P. and Lindenmayer, D.B. (1992) Forest succession,
timber production and conservation of Leadbeater’s possum,
Gymnobelideus leadbeateri McCoy (Marsupialia: Petauridae).
Forest Ecology and Management 49, 311–332.
Taylor, R.J. and Haseler, M. (1993) Occurrence of potential nest trees
and their use by birds in sclerophyll forest in north-east Tasmania.
Australian Forestry 56, 165–171.
Vanclay, J.K. and Skovsgaard, J.P. (1997) Evaluating forest growth
models. Ecological Modeling 98, 1–12.
Whitford, K.R. and Williams, M.R. (2002) Hollows in jarrah (Eucalyptus
marginata) and marri (Corymbia calophylla) trees. II: Selecting
trees to retain for hollow dependent fauna. Forest Ecology and
Management 160, 215–232.
Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48
Book reviews
49
Book reviews
The Forest Wars
Judith Ajani
Melbourne University Press, 2007, 362 pages, paperback, ISBN 9780522854190, RRP $34.95
Tilting at sawmills
The Forest Wars offers a personal insight into two decades of
dispute in forest policy and politics by the author, Judith Ajani,
formerly Judy Clark. It is worth reading because of the insights it
offers. It is a scholarly book, carefully but selectively researched
and documented. But it is also a disturbing book because of
the views it puts forward, because of the assumptions it makes,
and because of the bias in its coverage. Ajani is up-front about
this, and admits (p. 5) that ‘My biases show through the book.
I personally favour processing over exporting raw materials. I
also privilege the environment …’. It is also disturbing because
the book — based on a PhD thesis (completed in 2002) and a
Postdoctoral Fellowship at ANU’s Fenner School of Environment
and Society — builds a grand argument based on several untested
assumptions that are not canvassed in the book. It is disturbing
to me personally because in my teaching of forest policy, I draw
upon several sources that are also used by Ajani to reach quite
different conclusions.
I was interested to review this book, in part because Ajani’s
involvement in forest policy has some parallels with mine — she
came to forestry in Victoria as an economist in the early 1980s,
while I was drawn into policy debates through forest resource
estimates for the Wet Tropics in the mid-1980s. But when I
removed the book from its packaging, by coincidence it opened to
page 255, where my eyes fell on a quote in which Ajani ridicules
a politician for expressing the view that ‘There is no basic
reason why native forests cannot be managed on an ecologically
sustainable basis.’ Ajani contends that this view ‘is fundamentally
flawed … the public knows this intuitively …’. This contention
is not explored in the book, and is not a view that I share, so I
began with a sceptical viewpoint.
Ajani opens with a 50-page overview of softwood policies
originating in the 1920s, before progressing to her major thrust,
the woodchipping and MIS plantation policies of the 1980s and
1990s. Much emphasis is devoted to the ‘who and when’ of these
issues, but the ‘how and why’ is covered more unevenly. At times
I was irritated by irrelevant name-dropping, and Chapter 12
(Parliament’s forestry myths) is boringly dominated by a long
series of half-page verbatim quotes used to ridicule politicians.
Brevity could sharpen the argument.
Ajani reflects that writing the book helped her to reach three
key findings (p. 5): that forest conflict persists only because
governments have not allowed market forces to work; that there
are alternatives to the market approach (such as those pursued
by Queensland and WA); and that entrenched conflict often takes
on a life of its own, on which some people thrive (I agree with
this third finding). Because of my work there some decades ago,
I took a particular interest in the long narrative about Queensland
(Chapter 8, Beattie’s solution), but was disappointed to find it
rather one-sided and uncritical. Ajani is obviously a great admirer
of the Queensland ‘solution’, and does not question whether
twenty-five years of logging ‘slightly more intensively than
previously’ (p. 149) proposed as part of the ‘solution’ is a Faustian
bargain, with higher ecological impacts than a continuing series
of more appropriate harvests. The book does not examine the
assumption that gazetting native forests as national parks solves
all the problems (what about fire, weeds, feral predators?), and
does not consider the utility of a biosphere approach with managed
forest providing a buffer around conservation areas. This leads
to my main criticism of the book, that it explores political and
policy issues without considering ecological underpinnings or
market realities.
In some places, readers may find unexpected relief. On page 28,
Ajani reflects on Swain’s 1928 prediction that, by 1990, Australia
would require 24 million cubic metres of logs. I’m amused that
an economist lampoons this 60-year prediction, saying that ‘As
it turned out, Australia in 1990 required only 12.5 million cubic
metres of logs.’ Her own predictions, made as Judy Clark in 1992,
that the demise of native forest timber industry in Victoria would
be complete by the end of the 1990s turned out to be somewhat
less accurate.
Like Don Quixote, Ajani expends much effort tilting at imagined
demons. With flimsy supporting evidence she imagines an
unsettling scenario, and then sets out to demolish it. For instance,
she repeatedly reiterates her criticism that ‘foresters wanted to
bring order to the forests … by converting indigenous forests
… to softwood tree crops’ (p. 77) and that ‘foresters wanted to
improve … indigenous forests by converting them into productive
softwood tree crops’ (p. 81), and so on, apparently confusing the
quantity and quality of an argument. She seems, or chooses, to
remain unaware of any enthusiasm for — and a large body of
work on — uneven-aged silviculture, including but not confined to
continuous-cover forestry and close-to-nature management. There
is an implication in the book that all harvesting is clearfelling,
and alternatives are not canvassed. There are four photos in the
book, two of sawmills, and two of land clearing showing the worst
excesses of the 1970s, reproduced from the Routley’s Fight for
the Forests. Despite all the name-dropping and her years spent
at the ANU just a stone’s thrown from ANU Forestry, there is
no mention of silviculturalists such as Ross Florence and their
enthusiasm for ecologically-appropriate forest management.
Australian Forestry 2009 Vol. 72 No. 1 pp. 49–50
50
Book reviews
Ajani also asserts that ‘The minutiae engulfing the debate over
ecologically suitable native forest logging should not be allowed
to detract Australia’s foresters from their main role … of managing
plantations to support a competitive manufacturing industry’
(p. 310). Most foresters I know don’t see that as their role, and
see themselves as environmental stewards, rightly concerned with
the ecological ‘minutiae’ not just of forests, but of the broader
environment and of our society.
Another Quixotic example is found on page 311, where Ajani
asserts that ‘The Australian public has been led to believe that
the nation’s inherent competitive advantage lies more in raw
materials exporting than in manufacturing …’ and then builds a
perfectly reasonable argument in favour of local processing. But
I’m unaware of any forester, tree grower or forestry academic who
favours roundwood exports over local processing. Even ardent
supporters of woodchipping see it as a way to rejuvenate forests,
not as a way to solve our balance of trade deficit, and all would
welcome more local value-adding.
Ajani seems to have blind faith in sources supporting her
viewpoint. On page 280, she reports that Carr ‘nearly double[d]
the area of protected public forests in New South Wales to 3.6
million hectares … the area of public native forests available …
to log had fallen by only 4 per cent … identifying more native
forests than previously reported explains this seeming miracle.’ A
discerning reader might question this ‘miracle’, and ask whether
this protection was token gazettal of lands too steep to log,
whether it was some other slight of hand, or whether there was
some more serious deceit involved. The sudden exit at this time
of Chairman John Kerin and his entire Board of Directors, along
with CEO Bob Smith and General Manager David Ridley, from
State Forests suggests that this question is not insignificant, but
this issue is not explored by Ajani.
and to process the plantation resource in Australia. Personally, I
think that these two strategies are neither necessary nor sufficient,
even though they may be desirable.
The book’s final paragraph (p. 313) sums up Ajani’s view that:
‘The governments of Western Australia and Queensland have …
positioned their states to … reap the wealth, employment and
environmental benefits [of plantation forestry]. In contrast, the
governments of New South Wales, Victoria, Tasmania and the
federal government retain out-of-date forest policies that generate
unnecessary losses all round. I challenge these four governments
to say where and why they disagree … to explain … what it is that
prevents them from acting.’ Personally, I remain to be convinced
that the two states have positioned themselves in this way, and that
the challenges for the other four governments are that simple.
Ajani’s book is worth reading to gain an insight into her view of
history, but I doubt that it is going to help solve ‘the forest wars’,
or show the way forward.
Jerry Vanclay
Lismore, NSW
Email: [email protected]
The book does raise important issues about political interference;
about distortions in stumpage schemes, especially for native
hardwoods (pp. 49, 112); about excess profits in the woodchip
and MIS sector (p. 255); about the reluctance of governments
to revise timber resource estimates objectively, regularly and
openly (p. 160); and about the lack of effective dialogue between
stakeholders (p. 113); but for many readers these points are likely
to get lost amongst the many more equivocal issues canvassed.
By the last chapter (15, What should we do?), Ajani seems to be
running out of steam. Half of this chapter is backward looking
(Recapping the story), and the five-page finale (A new forest policy
for Australia) does little more than suggest that problems would be
solved if all states simply followed the example of Queensland. In
calling for a new forest policy, Ajani proposes three core desires
(p. 309): ecological integrity of native forests, an economically
and environmentally viable forest industry, and an expansion of
employment and wealth-creation opportunities in rural Australia.
Few will disagree, but the devil is in the detail. She proposes
that these three objectives require only two strategies: to shift
commodity wood production from native forests to plantations,
Australian Forestry 2009 Vol. 72 No. 1 pp. 49–50
Book reviews
51
The Wild Trees
What if the Last Wilderness is Above our Heads?
Richard Preston
Allen Lane — an imprint of Penguin Books, 2007, hardback, 294 pages, ISBN 978 1 8641 4023 5,
$32.95, www.penguin.com
The Wild Trees is an engaging and readable account of exploration
in the redwood (Sequoia sempervirens) forests of northern
California. What sets this story apart from other tales of forest
exploration is the fact that the action takes place at dizzying
heights in the canopy of the world’s tallest trees.
This book is very much about individual trees and the select group
of people who chose to climb them. I was surprised to read that
parts of the California coastal range remain inaccessible and are
seldom visited, raising the possibility that the tallest redwoods
have yet to be discovered. Many of the largest trees have been
named, often with exotic names originating from literature and
ancient mythology. Richard Preston’s book clearly conveys the
individual character of these ancient veteran trees that may live
for several thousand years before succumbing to winter storms
sweeping in from the Pacific Ocean.
Kinglake in Victoria. The description of voracious leeches, dense
understorey and falling branches should be familiar to anyone
who has worked in tall eucalypt forests.
This worthwhile book provides new insights into old forests, and
is well worth reading.
Lachie McCaw
Manjimup, WA
[email protected]
The Wild Trees is also a story about people; some of them are
professional scientists while others are enthusiastic amateurs with
a passion for tall trees. Tree climbing is not a new past-time but
has traditionally been the domain of specialist axemen employed
to remove the tops of tall trees to enable cable logging or to
construct fire lookout towers. Having climbed fire lookout trees
in the karri (Eucalyptus diversicolor) forest of south-western
Western Australia I have the greatest respect for those prepared
to scale a large tree equipped only with a rope and basic climbing
tools. Lightweight, high technology climbing gear has allowed
a new generation of tree climbers to ascend the tallest trees
and discover the unique community of plants and animals that
inhabit the forest canopy. Salamanders, worms, mosses, lichens,
huckleberries and a host of other living organisms all depend on
the environment created by the canopies of large old trees. The
elegant line drawings that illustrate this book capture the unique
character of the redwood forest canopy.
The Wild Trees also provides a glimpse into the distinctive subculture of the new generation of tree climbers who have their
own language with colourful expressions such as ‘ninja ascent’
to describe a stealthy climb done suddenly and quietly under
cover of darkness!
Australian readers will be interested in the chapter describing
the ascent of tall Eucalyptus regnans on the Hume Plateau near
Australian Forestry 2009 Vol. 72 No. 1 p. 51
52
Book reviews
The Zealous Conservator: A Life of Charles Lane Poole
John Dargavel
University of Western Australia Press, 2008. 252 pages, paperback, ISBN 978 1 921401 14 5, $29.95
John Dargavel has done a remarkably good job of compiling
the story of the professional life of one of Australia’s pioneer
foresters, Charles Lane Poole, largely from historic records. The
result makes a very good read, giving great insights into the work
and personal characteristics of this remarkable forester, who at the
age of 19 had his left hand amputated and replaced with a steel
hook. Reading through the story, one is somewhat humbled by
the challenges that early foresters like Lane Poole endured and
surprised that some of the challenges have a nature remarkably
similar to those facing foresters today.
Born in Sussex in 1885, Charles was one of two English cadets,
sponsored by the Colonial Office, to graduate from the French
Forestry School at Nancy in 1906. He then spent more than
four years in the Transvaal Forest Department and then another
five years in Sierra Leone. For much of this time he worked
on demarcation of the best of the remaining forests as well as
establishing plantation trials. By modern standards, times were
tough. He often spent three months away from his post surveying
forests and when he married in 1911 his wife Ruth remained in
Dublin for the next five years and they corresponded regularly
by letter.
Most of Lane Poole’s working life was spent in Australia. When
he arrived in Australia in 1916 and became Western Australia’s
Conservator of Forests, he was only the second university-trained
forester working in Australia. There was so much to be done: it
was not clear how much forest there was, no one knew how fast
the trees grew or when they reached maturity, his staff could not
identify the forest flora botanically, indeed much of it had never
been classified, and wood science investigations had barely
begun. He attacked all of these problems in his first year as the
Conservator of Forests.
The book provides intriguing insights into the political dimensions
of forestry in the early part of the twentieth century in Australia.
Between 1916 and 1921, Charles put enormous personal energy
into the development of Western Australia’s first forestry
legislation. The process was long and complex and was a battle
between the forest scientist and powerful stakeholders, particularly
the owners of Millars, then the largest sawmilling company in
Western Australia, that stood to have their concessions converted
to permits and their log prices increased to levels consistent with
those of other timber permit holders. He had to do battle with the
Premier of the state, and in the end when he could not achieve the
outcome that he believed was right for the forests he tendered his
resignation. This is fascinating as one often thinks the political
challenges faced by today’s foresters are of recent making.
Lane Poole spent the next two years working in the Australian
Territories of Papua and New Guinea conducting forest assess­
ments. The description of the challenges he faced when surveying
the forests of Papua and New Guinea, including crossing flooded
rivers, dealing with malaria-infected mosquitoes and savage
attacks from indigenous tribesmen, puts today’s remote sensing
inventories into perspective.
Lane Poole always had a great interest in the education of foresters.
When he attended the third Interstate Forestry Conference in
Adelaide in 1916, he drafted a resolution that set out the need to
train foresters at the university level and apprentices in a training
school. In 1927, he became the acting principal of the Australian
Forestry School when it opened in Canberra and remained in the
post for 28 years. But this period was not without its controversies,
as he had major conflicts with his staff and more significantly with
Alfred Galbraith and Harold Swain, the respective heads of the
Victorian and NSW forest departments, both of whom Lane Poole
considered not to be properly trained foresters. These conflicts
seriously impacted on student numbers and led to the partnership
between the Creswick School of Forestry and the University of
Melbourne. This conflict explains the tensions that persisted
until the late 1970s between Victorian- and Canberra-trained
foresters.
Despite the conflicts he had with some politicians, Lane Poole
was well connected with many politicians including Prime
Minister Stanley Bruce. These connections enabled him to achieve
some of his goals, such as the establishment of the Australian
Forestry School, but weren’t sufficient to allow him to achieve
his ultimate desire of having the control of forests vested under
the Commonwealth. He also failed to get agreement for the
headwaters of the Hume Weir catchment to be managed by
the Commonwealth. He also spent about 20 years as Inspector
General of Forests trying unsuccessfully to forge the development
of a national forest policy. He was, however, more successful in
getting the Forestry and Timber Bureau established to conduct
the forest research he knew was needed to guide the management
of Australian forestry.
Lane Poole made very significant contributions to botanical
knowledge in many of the places he worked, including Africa,
Australia and Papua New Guinea. He collected 44 type specimens
during his survey work in Papua New Guinea. He also collected
specimens when on tour in Western Australia and one of them,
Eucalyptus lane poolei, was subsequently named after him.
Dargavel goes to great length to give the reader an accurate
portrayal of the personality of Charles Lane Poole, including his
advocacy regardless of the personal consequences or political
realities. Lane Poole was very strong minded and intolerant
of other’s views, including those of other ‘less well-trained’
foresters working with him and in the various forestry agencies
he interacted with. This characteristic made it very difficult for
him to achieve some of his goals as the principal of the Australian
Australian Forestry 2009 Vol. 72 No. 1 pp. 52–53
Book reviews
Forestry School and the Inspector General of Forests with the
Commonwealth government in Australia. It also explains some of
the tensions that existed in Australian forestry when I entered the
profession in the early 1970s and which persisted until a national
forest policy was agreed to in 1992.
Two other things of significant interest are described in the book.
Lane Poole’s wife Ruth had great skills in interior design and
was given the job of designing the furniture and interior colours
in both the Prime Minister’s and Governor General’s residences
which were under construction in the new national capital of
Australia. Lane Poole developed a life-long friendship with one of
Australia’s great philanthropists, Sir Russell Grimwade, who was
an early member of the Australian Forest League — the forerunner
of conservation organisations in Australia. Both Grimwade and
Lane Poole believed strongly in the importance of Australian
foresters gaining first-hand experience of the long-standing forest
management systems practised in Europe. Grimwade donated
funds to establish a prize that enabled Australian foresters to study
at the Imperial Forestry Institute at Oxford, from which nearly 30
Australian foresters have benefited.
Dargavel’s story of Lane Poole’s life is well worth the read, both
from the historical perspective and from the insights it gives into
successes and failures of a forestry leader.
Tony Bartlett
Canberra, Australia
Australian Forestry 2009 Vol. 72 No. 1 pp. 52–53
53
54
Book reviews
Plantation Eucalypts for High-Value Timber
A.G. Brown and C.L. Beadle (editors)
Rural Industries Research and Development Corporation Publication No. 08/113, 2008, x + 182 pages, paperback,
ISBN 1 74151 701 X, $25, or free online from http://www.rirdc.gov.au/reports/AFT/08-113.pdf
Plantation Eucalypts for High Value Timber is published as a re­port
of the Rural Industries Research and Development Corporation
and consists of the edited proceedings of a conference of the same
name held in Melbourne in October 2007. The report has been
edited by Alan Brown and Chris Beadle and contains 12 chapters
written by a range of authors. The hard copy is available to the
general public from http://www.rirdc.gov.au/eshop for $25.
It was assumed from the outset that plantation eucalypts for
high value timber are desirable because they reduce the demand
on native forests for such products. The aim of the conference
was to explore the challenges in creating a plantation estate of
sufficient size and security to encourage investment to develop
a viable industry sector. Consequently the target audience is
broad and includes growers, managers, processors and policy
makers, although it is probably directed mostly towards the R&D
requirements necessary to attract investment.
The subject matter covers the whole value chain from plantation
establishment through to market. Consequently the research
priorities include breeding and silviculture for preferred wood
properties; thinning and pruning strategies; harvesting and
transport; and challenges in drying, processing and process
recovery. Lott and Gooding detail research priorities in their
chapter. Tepper discusses species selection and site assessment
considerations for high-value eucalypt plantations and argues for
the use of process-based models to assist in making decisions.
Volker highlights already existing relevant silvicultural research,
particularly in thinning pruning and nutritional management.
Quill summarises existing international experience in harvesting
eucalypts and concludes there will be no particular problems
extending this knowledge to high-value regimes in Australia.
Washusen and Innes discuss processing and highlight the
challenges in limiting degrade if drying times are to be reduced.
Cannon and Innes show how Forest Enterprises Australia
Limited has made a product, EcoAshTM, from Eucalyptus nitens
grown under pulpwood regimes but suitable for some highervalue structural applications. Grealy reviews the potential and
challenges of placing naturally durable timber from eucalypt
plantations in the market. Bush discusses genetic improvement
of high-value timber species.
The report is ably introduced by Vince Erasmus and concluded by
Rod Keenan. The nature of the report, a consolidation of individual
conference presentations, inevitably must lack continuity in
substance and style and it is to the credit of the editors that they
have been able to keep this to an absolute minimum, and the report
is as close to a unified whole as could be expected. It is unusual for
conference proceedings to be promoted as a book for the general
public, but this report contains so much valuable information there
is a very good case for doing so. Research funders need to have
this information to channel investment and research providers
need to be able to adapt to the challenges identified in this report.
Policy-makers and industry need to respond in a unified manner.
The report highlights the necessity to develop a skills base capable
of serving this initiative. The report is not overly negative. It
rightly highlights the very real challenges, but also is optimistic
and points to a realisable future. I commend the report.
Roger Sands
Professor Emeritus
University of Canterbury, New Zealand
A theme throughout the report is that, if government wishes
reduced reliance on native forests for high-value timbers, it needs
a policy, developed in consultation with industry, to support the
development of a plantation resource of appropriate scale. Taylor
discusses investment strategies and the likely importance of
management investment schemes, especially now they have some
taxation advantages extolled in the report by the then Minister for
Fisheries, Forestry and Conservation, Eric Abetz.
Australian Forestry 2009 Vol. 72 No. 1 p. 54
Obituary
55
Obituary
Alfred John (Alf) Leslie
5 February 1921 – 24 January 2009
Alf Leslie was born in Melbourne, Australia, on 5 February 1921.
He was educated at University High School, where he achieved
an excellent academic record and was a long distance runner of
note. He commenced training to be a primary school teacher but
changed his mind when offered a Forests Commission Cadetship
at the Victorian School of Forestry, at Creswick, Victoria. He
studied at the school from 1938 to 1940, graduating first in his
class in 1941. He is remembered as a serious student and an
ardent tennis player.
He supervised salvage logging on the Torongo Plateau for a time
before joining the Royal Australian Navy. Alf was generally
reluctant to talk about his war service. He was seconded to a Royal
Navy submarine operating out of Western Australia during World
War II and saw active service on it. He once vividly described
an encounter between himself, as gunnery lieutenant, and an
attacking Japanese plane, in which both achieved their goals,
but leaving him with stomach and other wounds that dogged
him in later life.
After recuperation and the end of the war, he took up a field
posting with the Forests Commission at Taggerty, where he met his
wife-to-be, Jean. In 1947, he was nominated by the Commission
to undertake the Bachelor of Science (Forestry) course at the
University of Melbourne and graduated early in 1949. He and Jean
were married on 21 December 1948, so planned as to minimize
his time away from work. They later had two daughters, of whom
he was very proud.
After their marriage he was posted to Mansfield and then to
Beech Forest in the Otways in Victoria. He resigned to take up
an appointment as Wood Superintendent and then Chief Forester
with APM in Gippsland in 1951. APM was a relatively new paper
mill, then largely reliant in hardwood pulpwood from nearby
state forests. He worked closely with the late Geoff Chandler, the
General Manager of APM Forests Pty Ltd, in starting plantation
forestry in Gippsland. On a visit there two years ago, he was
greatly taken by the extent and success of the plantations, both pine
and eucalypt, which at the time must have been a risky venture
for a private enterprise.
His inclinations towards teaching resurfaced, and he took up
appointment as Lecturer in Forest Management at the University
of Melbourne in 1958 and was promoted to Senior Lecturer in
1962. He completed a Master of Science in Forestry thesis and
was editor of Australian Forestry from 1962 to 1964. Forestry
students of that era still extol his teaching in bringing economics
and business management into a course that had been dominated
by sylvan fundamentalism. He did so not as an ideologue, but
as a skeptic, always able to point to the unresolved assumptions
and logical gaps and to urge independent and critical thought and
debate. He laboured long and hard in grappling with the problems
associated with state-owned forestry, which predominated then.
His experience in private enterprise highlighted some of the
changes needed and he was not reticent in expounding on them
in dialogue with students and colleagues.
He attended a forestry conference in 1963 in Malaysia, where
he came to the attention of Jack Westoby, Head of the Forestry
Division of the Food and Agriculture Organisation (FAO) of the
United Nations. Jack recruited him to teach at the University
of Ibadan from 1964 to 1966. There, he gained a taste for the
challenges of international forestry, notwithstanding a revolution
in Nigeria late in that period. During this and the earlier period of
teaching, he read widely, especially in economics, and developed
a standing internationally as a forest economist. He was by now
a powerful speaker and although he did not publish widely, what
he did publish carried considerable weight.
In 1966, he was appointed Officer-in-Charge of Regional Stations
in the then national Forest Research Institute in Canberra,
Australia. During this time, he travelled widely and frequently
between the far-flung research stations and was highly successful
in lifting the profile of forest research and of the researchers
involved.
In 1968, he accepted an appointment as Forest Economist with
FAO in Rome. During this period, and in later service with FAO,
he encouraged and guided a number of Australian foresters into
short-term consultancies in international forestry, establishing
a core of people who later joined international organisations or
undertook bilateral and multilateral research and consultancy
projects. Teaching again called in 1974, when he took up the
aptly-titled appointment as Reader in the School of Forestry at the
University for Canterbury, New Zealand. A cohort of New Zealand
forestry students of that era attest to his continuing influence
through his teaching of forest economics and management.
In 1977, he was again recruited by Jack Westoby to take up the
position of Director of Forest Industries of FAO. He served with
Westoby and a distin­guished team of international colleagues
working on many forestry projects throughout the developing
countries until he reached compulsory retirement age. He was later
to assist a dying Westoby in writing his final book, a testimony to
the bond between them. He was one of the very few Australians
to reach a very senior and influential level in international
forestry, and many people in international forestry still refer to the
motivation or insights that he gave in addresses and discussions
during his frequent travels.
Australian Forestry 2009 Vol. 72 No. 1 pp. 55–56
56
Obituary
After his so-called ‘retirement’ in 1981, he extended his influence
as an international consultant in tropical forestry. He was invited
by Dr Freezailah, first Executive Director of the International
Tropical Timber Organization (ITTO), to assist him lay the
groundwork for the work of the organisation when it commenced
operation in 1986. He remained deeply engaged with ITTO and
its work over the next 22 years, contributing to many of the
organisation’s key initiatives. In an interview shortly before his
death, he rated his role in helping to establish ITTO as his greatest
professional achievement. His long experience in international
forestry and dealing with international bureaucracies gave him the
ability to ‘cut through the crap’, as one of his long-time colleagues
put it, in a way that was always illuminating and refreshing.
He was a bibliophile and, despite a very active professional
career, read across a prodigiously wide range of topics. His
recent book The Skeptical Forest Economist (http://repository.
unimelb.edu.au/10187/2473) encapsulates the curmudgeonly
delight he took in disputing conventional wisdom, and deflating
bureaucratic edicts and political correctness. To quote Alf: ‘After
playing around in the field of forest economics for the best part
of sixty years, I wanted to sort out my ideas on the subject’. The
book exemplifies his scholarship, prodigious memory and love
of reading. Booksellers, as well as us, will be much the worse
for his passing.
He was a skeptic who delighted in starting an argument. His
speeches often progressively developed the conventional wisdom
on a topic, before torpedoing the assumptions on which it was
founded. He took delight in exposing flaws and gaps with the
broad brush of a skeptical pragmatist, often supported by some
rough but telling calculations on the back of an envelope. If the
proponent could not immediately rebut his argument factually,
they were well advised to think again.
he spent many years teaching and was a very popular supervisor of
postgraduate students. The University of Melbourne conferred an
honorary Doctor of Forest Science on him in 1994, in recognition
of his services to international forestry. He was the recipient of
the Commonwealth Forestry Association’s ‘Regional Medal’ in
2001 and of the Council of Forest Engineering’s ‘International
Forest Engineering Achievement Award’ in 2007.
He passed away on 24 January 2009 in New Zealand following
complications from a stroke in 2008. His funeral was held on
5 February, which would have been his 88th birthday. He is
survived by his wife Jean, children Leigh Leslie, and Eleanor and
Pat Quaid; and grandchildren Tristan and Alison Leslie, Morghan
Quaid, Kiersten Leslie, Jesse-Leigh Quaid and Shannon Quaid.
Alf’s family is accepting donations for a memorial grove of trees
to be established at the Creswick campus of the University of
Melbourne’s Department of Forest and Ecosystem Science. See
http://itto.or.jp for details for those who may wish to contribute.
Vale Alf Leslie — a much respected and admired international
forester, teacher, scholar, mentor and skeptic.
Ian Ferguson
Melbourne
Ian wishes to acknowledge the assistance of many others in
preparing this obituary.
At a personal level, Alf had a gift of engaging the newly
encountered, whether young or old and no matter their ethnic
background or education, by joking about the ills of the
organisation or economy on an impersonal level. He often took
an interest in the work of younger foresters, offered support and
counsel as a mentor in a way that you did not realize you were
being mentored, and encouraged many younger foresters to lift
their aspirations, as many now in senior positions can attest. He
could also point out the need to rethink ideas in a way that neither
threatened nor embarrassed the proponent. He was a gentleman in
every respect; discourse always being lubricated with numerous
cups of tea. Whatever the topic or concern, one left a discussion
with him with a feeling that here was a person who listened,
probed and cared, as well as counselled.
He was elected a Fellow of the Institute of Foresters of Australia in
1964 and is a past President of the International Union of Societies
of Foresters. After 1981, he was a visiting fellow and guest lecturer
at many universities, notably at the University of Melbourne where
Australian Forestry 2009 Vol. 72 No. 1 pp. 55–56
57
Referees 2008
The editors of Australian Forestry are pleased to acknowledge the important contribution of referees to the journal in 2008.
Frank Batini
Chris Beadle
Chris Borough
Leon Bren
David Bush
David Butt
Angus Carnegie
Kerrie Catchpoole
Mike Connell
Dick Curtin
Bernie Dell
Ian Dumbrell
Heidi Dungey
Bob Eldridge
Ken Eldridge
Humphrey Elliott
Ian Ferguson
Janet Farr
Ross Florence
Michael Greenwood
Rod Griffin
Paul Heubner
Gary Hopewell
Dominic Kain
Roger Leakey
David Lee
Jerry Leech
Richard Loyn
Colin Matheson
Sarah Munks
Sadanandan Nambier
Doland Nichols
Greg Nolan
Richard Northway
Brenton Peters
Digby Race
John Raison
Rowan Reid
Wayne Schmidt
Jim Shield
John Simpson
Geoff Stoneman
Brian Turner
John Turner
Jerry Vanclay
Tim Wardlaw
Phil West
Kim Whitford
Graham Wilkinson
Dean Williams
Allan Wills
Ross Wylie
Australian Forestry 2009 Vol. 72 No. 1 p. 57
Australian Forestry
Notice to contributors
Scope
Australian Forestry provides a vehicle for formal publications in all areas of interest to the Institute of Foresters of Australia. The
editors welcome original scientific and technical contributions, reviews, suitably argued opinions, short communications and reviews
of books on topics related to forest research, forest management and forest policy in Australia and the South Pacific region. Papers
relating to any aspect of knowledge or management of forest species and land use matters of interest to the region will be particularly
valued. It is a condition of submission of original papers that they have not been accepted for publication elsewhere.
The Editorial Panel evaluates the suitability of material for publication. All papers submitted to the journal will be reviewed by
referees nominated by the panel.
Criteria for the assessment of papers centre on the suitability of the topic for publication in Australian Forestry, technical and scientific
quality of the work, clarity and conciseness of presentation, appropriateness of the conclusions on the basis of the evidence presented,
and suitability of the material for printing.
Manuscripts
Contributions should be printed with double spacing on one side of the paper only. Three copies of each paper should be submitted.
Following review, please submit the revised manuscript as one hard copy and an electronic file or files. The latter should be in Word
or RTF, and should include tables and illustrations. The latter should also be supplied in their original files (e.g. in Excel) or as
photographs. Low-resolution files are not acceptable.
Title
The title should be brief and where possible begin with a word suitable for indexing.
Summary
The summary should follow immediately after the author’s address and should concisely describe the aim and nature of the work, the
principal results and conclusions. It should normally not exceed 5% of the length of the paper and should be suitable for reproduction
by abstracting journals. If possible provide several keywords drawn from the CAB thesaurus; if this is not available it will be helpful
to look at the keywords assigned to similar articles in Forestry Abstracts or in previous issues of this journal.
Presentation
Authors should follow the pattern of presentation used in this issue. Figures and tables should be numbered with arabic numerals.
Photographs should be identified as figures, and numbered in a single sequence with line drawings. Photographic prints should be
of high quality on gloss paper, with a full range of tones and good contrast. Tables should be constructed in Excel or in the ‘Table’
facility of Word — not tabbed, nor as pictures. The preferred placement of tables and figures in the text should be marked with for
example ‘Figure 1 near here’. Actual tables and figures should be gathered at the end of the paper.
Illustrations
Graphical material may be submitted as computer-generated graphics or line drawings. Diagrams should be provided in postscript
(ps) or encapsulated postscript (eps) format if possible. If diagrams are supplied only as hard copy, they should be camera ready,
with labels applied at an appropriate size, printed by high quality (e.g. laser) printer. Where possible, figures will be printed within
a single column width.
References
References should be cited in the text by author and year of publication. Three or more authors should be referred to by the senior author
et al. The reference list should cite the full title of the publication. Please follow the style used in recent issues of this journal.
Submissions
Please forward your submission to: Executive Director, The Institute of Foresters of Australia, PO Box 7002, Yarralumla ACT 2600,
Australia.
Copyright protection
For the protection of authors and the IFA, a simple form of copyright agreement has been developed and is available on request
from the Executive Director. A copy of the agreement will be sent to the senior author or his or her agent with the typeset proofs; it
should be signed by the senior author or agent on behalf of all co-authors and returned to the office of the IFA. Under the terms of
this agreement the IFA will obtain an interest in copyright only if the article is published by the institute.
Offprints
A copy of the final paper in portable document format (pdf), and guidelines for the distribution of copies, will be provided to authors
after publication of their paper.
Correspondence on editorial matters should be addressed to the Managing Editor, Dr Colin Matheson, C/- The Institute of Foresters
of Australia.