in young eucalypt plantations pest and disease...

S C I E N C E F O R D E C I S I O N M A K E R S

F i e l d M a n u a l f o r U s i n g t h e C r o w n D a m a g e I n d e x

PEST AND DISE ASE ASSESSMENT

IN YOUNG EUCALYPT PLANTATIONSThe Crown Damage Index is a standardised statisticallysound method for assessment of crown damage causedby pests and diseases in young eucalypt plantations. Thismanual describes how to measure the CDI of individualtrees and plantations. A worksheet that is necessary fordata entry and analysis can be downloaded from theNational Forest Inventory web site (www.affa.gov.au/

nfi).

The Crown Damage Index provides a statistically validmeasure of crown damage in a plantation. Plantationmanagers can therefore use CDI data to plan andmonitor pest and disease treatment and to providea basis for reporting to plantation owners. CDI data canalso be used to monitor research trials and to providea basis for assessment of compliance with environmentalmanagement systems and similar monitoring andreporting requirements.

The Crown Damage Index was developed by plantationhealth managers and researchers working in severalregions of Australia. This manual has been publishedso that the method can be applied and tested by otherplantation managers and contractors, tree breeders,silviculturists and forestry researchers.

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IN YOUNG EUCALYPT PLANTATIONS

BRS/Field internal.FA 15/7/03 3:19 PM Page i

© Commonwealth of Australia 2003

ISBN 0 642 47547 4

This work is copyright. Apart from any use as permitted under the Copyright Act 1968, no part may bereproduced by any process without prior written permission from the Commonwealth available from theDepartment of Communications, Information Technology and the Arts. Requests and inquiries concerningreproduction and rights should be addressed to the Commonwealth Copyright Administration, IntellectualProperty Branch, Department of Communications, Information Technology and the Arts, GPO Box 2154,Canberra ACT 2601 or at http://www.dcita.gov.au/cca.

The Commonwealth of Australia acting through the Bureau of Rural Sciences has exercised due care and skillin the preparation and compilation of the information and data set out in this publication. This notwithstanding,the Bureau of Rural Sciences, its employees and advisers disclaim all liability, including liability for negligence, forany loss, damage, injury, expense or cost incurred by any person as a result of accessing, using or relying uponany of the information or data set out in this publication to the maximum extent permitted by law.

Postal address: Copies available from: Telephone: 1800 020 157Bureau of Rural Sciences ADS Fax: 03 8379 8201GPO Box 858 PO Box 6103 Email: [email protected] Canberra ACT 2601 West Footscray Vic 3021 Internet: http://www.affa.gov.au/brs

Preferred way to cite this publication

Stone, C, Matsuki, M and Carnegie, A 2003, Pest and disease assessment in young eucalypt plantations: fieldmanual for using the Crown Damage Index, ed. Parsons, M, National Forest Inventory, Bureau of Rural Sciences,Canberra.

Author/editor details

C Stone and A Carnegie, State Forests of New South Wales, Research and Development Division, PO Box 100,Beecroft, NSW 2119.M Matsuki, Cooperative Research Centre for Sustainable Production Forestry, Private Bag 12, Universityof Tasmania, Hobart, Tas 7001.M Parsons, National Forest Inventory, Bureau of Rural Sciences, GPO Box 858, Canberra, ACT 2601.

Graphic design: Racheal Brühn Design, Canberra, ACT.

ii

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Drought, frost, waterlogging, soil nutrient deficiencies, browsing mammals, birds, insectsand fungal pathogens can all damage young eucalypts in plantations. The resulting crowndamage can reduce growth and in some cases lead to tree death.

This manual describes a procedure that enables the extent of crown damage in youngeucalypt plantations to be quantified in an objective, rigorous and repeatable way. Theoutcome—expressed as the Crown Damage Index—can be used by plantation managers,researchers and others who need a systematic procedure to assess and monitor crowndamage.

The Crown Damage Index can be used to:

• demonstrate the effectiveness of insect pest and disease control programs

• provide objective data for reporting to plantation investors on the health of their plantations

• monitor research trials and make yield projections.

It may also play a role in satisfying reporting procedures, such as those requiredby environmental management systems, forest certification systems, the AustralianForestry Standard and criteria and indicators of sustainable forest management

The Crown Damage Index has already been used by a number of plantation managersand researchers in several regions of Australia. Publication of this manual will make theprocedure available for general use.

The manual explains in detail the data collection and quality assurance proceduresnecessary to use the Crown Damage Index. Following these procedures will improveprecision, and hence improve confidence in the results.

I commend this manual to plantation managers and contractors, tree breeders,silviculturists and forestry researchers. The authors and the Bureau of Rural Scienceswelcome feedback that will assist with further development of both the Crown DamageIndex and manual.

Executive DirectorBureau of Rural Sciences

Pest and Disease Assessment in Young Eucalypt Plantations iii

Foreword

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The Crown Damage Index was developed through consultation with all members

of Research Working Group 7 (Forest Health), in particular: Tim Wardlaw (Forestry

Tasmania), Rob Floyd (CSIRO Entomology), Caroline Mohammed (CSIRO FFP),

Ross Wylie (Queensland Forestry Research Institute) and David de Little (Forest

Health Consultant, Tasmania).

Photographs were supplied by Charlma Philips (Forestry SA), Karl Wotherspoon

(Forestry Tasmania), Jane Elek (Forestry Tasmania), Anna Smith (University of Tasmania),

Grahame Price (SFNSW), Darren Waterson (SFNSW) and the Australian Centre for

International Agricultural Research.

The concept for the worksheet for data entry was developed as result of a joint project

by Timbercorp Ltd, Forestry Tasmania and the CRC for Sustainable Production Forestry,

in particular: James Bulinski (Timbercorp Ltd), Jane Elek (Forestry Tasmania), Grahame

Price and Darren Waterson (SFNSW) and Carl Mackin (Australian Bureau of Statistics).

Grahame Price (SFNSW), Darren Waterson (SFNSW) and Anna Smith (University

of Tasmania) undertook field testing of the CDI and the sampling protocols.

This publication was produced by the National Forest Inventory with funding from

the Natural Heritage Trust.

iv

Acknowledgements

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Pest and Disease Assessment in Young Eucalypt Plantations v

Foreword iii

Acknowledgements iv

1. The Crown Damage Index 1

2. Types of damage 4

3. How the Crown Damage Index works 9

3.1 Assessment of an individual tree 9

3.2 Quality control requirements for individual tree assessment 15

3.3 Collecting CDI data across a plantation 16

3.4 Summarising the CDI value for a plantation 24

3.5 Timing of CDI assessment 25

Appendix 26

Bibliography 29

Contents

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vi

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Young eucalypts in plantations are exposed to a wide range of damaging environmental

and biological agents or processes, such as drought, frost, waterlogging, soil nutrient

deficiencies, browsing mammals, birds, insect pests and fungal pathogens. These stressful

agents can adversely affect the health and condition of trees, resulting in reduced growth

and possibly leading to tree death. They can cause a direct loss of leaf tissue through

excision (that is, chewing), localised cellular death (necrotic lesions), premature leaf

abscission (defoliation) or a reduction in physiological function (shown by discolouration,

for example chlorosis).

The Crown Damage Index (CDI) was developed because plantation managers, forestry

researchers and others often need a quantitative measure of this damage.

The specific aims of the CDI are to:

provide a standardised, repeatable and statistically valid measure of pest and disease

damage so that quantitative comparisons can be made and statistical analysis can be

undertaken irrespective of the cause of the damage or site

provide a measure of damage that can be summarised for an age class, plantation,

organisation, district, region or state

be relatively quick and easy to apply, especially with the diagrammatic aids

provided in this manual and the worksheet that has been developed for data entry

and analysis.

The authors expect that the CDI will be used primarily by people with specialist training

or experience and that the results will be used to:

improve operational management by providing information for pest and disease

assessment and treatment decisions; for example, establishing a baseline level

of crown damage enables temporal and spatial trends in damage to be detected

Pest and Disease Assessment in Young Eucalypt Plantations 1

1. The Crown Damage Index

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demonstrate to investors the effectiveness of plantation protection programs

enable comparisons within research trials; for example, to show differences in pest

and disease tolerance in tree breeding programs

assist in the interpretation of remotely sensed digital imagery

meet forest health reporting requirements under regional, state and national

commitments, such as Regional Forest Agreements and the Montreal Process

criteria and indicators

fulfil the requirements and verification process associated with the Australian

Forestry Standard (Criterion 3: ‘Forest management shall maintain forest ecosystem

health and vitality’)

assist audit teams with compliance assessments for environmental management

systems and forest certification schemes

provide an indicator of the success of state and federally funded environmental

revegetation programs (for example, the Natural Heritage Trust).

The CDI can only be used if assessors can see all of the foliage in the crown. The method

of assessing CDI described in this manual is intended for use in plantations that have

not yet reached canopy closure and assumes assessment is done from the ground.

A different method is being developed for older stands.

The CDI does not deal with the causes of crown damage. The causes, and when the

damage may have occurred, must be considered when the CDI is interpreted. Some

of the many sources of guidance and information on the identity of agents that cause

crown damage are included in the Bibliography. Experts who can identify pests and

diseases include regional forestry extension workers, employees of state forestry

agencies, officers of CSIRO Forestry and Forest Products and the Australian National

Insect Collection in Canberra.

2


The CDI does not assess the potential impact of crown damage on tree growth.

Assessing the impact on growth requires knowledge of when the damage occurred,

the frequency of damaging events and the value of the damaged parts of the crown.

The eventual impact on tree growth depends on the vigour of the tree, environmental

conditions and site quality—and the nature of the damaging agents themselves.

Systematic collection of crown damage data over time will enable the relationship

between crown damage and growth to be investigated and tested. In the longer term,

this may lead to a better understanding of the timing and effectiveness of treatments

and enable quantitative analysis of the costs and benefits. Standardised historical crown

damage data will also assist in the evaluation of differences in susceptibility to a range

of damaging agents between and within eucalypt species.



The CDI takes into account the incidence and severity of missing, damaged and

discoloured foliage.

It is based on a visual estimate of the incidence, that is, extent of damage over the entire

tree crown (as a percentage) multiplied by the average level of severity at the leaf scale

(as a percentage) for three types of damage commonly observed in eucalypt crowns.

The three types of damage are described below.

2.1 Defoliation

Defoliation is when entire leaves or parts of leaves are missing (includes leaf holes and

edge scalloping). Leaves completely missing would be recorded as a value of 100% for

severity at the leaf scale (Leaves 1 to 5, page 6).

The presence of fallen leaves around the base of a tree can provide a clue to the degree

of leaf shed that has recently occurred. The distribution and density of leaves in the

crown is not only influenced by the presence of damaging agents but also tree genetics

and the overall quality of the site. The extent of damage needs to be compared with

normal healthy crown condition for a specific site. This is important, for example, when

assessing leaves shed from lower branches.

2.2 Necrosis

Leaf necrosis is the presence of dead leaf tissue, including necrotic leaf spots and leaf

blisters. Entire dead leaves still in the crown would be recorded as 100% affected at the

leaf scale (Leaves 6 to 11, page 7).

Insects (e.g. leaf blister sawfly larvae) and fungal pathogens (e.g. Mycosphaerella leaf

disease) can cause necrotic patches and spots on leaves. Several nutrient disorders

can cause leaf necrosis (Dell et al. 2001) as can drought, herbicide and other

abiotic agents.

4

2. Types of damage


2.3 Discolouration

Discolouration is when non-green leaf tissue is present, including yellowing or

reddish/purple discolouration, chlorotic spots or margins. (Leaves 12 to 17, page 8).

Discolouration can be assessed according to:

extent— the proportion of leaves that are discoloured

degree— the intensity of the discolouration (Innes 1993).

For eucalypts, in particular, the assessment of leaf discolouration is also problematic

because the healthy leaves of many species can change colour as they develop.

Expanding, immature but perfectly healthy leaves can range in colour from yellow, light

green, green, dark green, orange to red depending on the species. However, a common

symptom of stress in eucalypts is leaf reddening, which is caused by the accumulation

of anthocyanin pigments.

Both biotic and abiotic damaging agents influence leaf colour, and often there are

confounding effects (Dell et al. 2001). To ensure that the CDI is simple, easy to assess

and provides consistent results, it has been decided to treat as discoloured all leaf tissue

with colour outside the normal range of variation for that host species, irrespective of

possible causes. Discoloured leaf tissue is given equal weighting with missing or necrotic

leaf tissue.

Nutritional Disorders in Plantation Eucalypts (Dell et al. 2001) is an excellent reference

illustrating types of leaf discolouration associated with nutritional disorders.



6

< LEAF 1 — 5%

< LEAF 2 — 12%

< LEAF 3 — 20%

< LEAF 4 — 33%

< LEAF 5 — 53%

Leaves 1 to 5 Percentage of leaf chew compared to total leaf area

Defoliation



Leaves 6 to 11 Percentage of leaf necrosis compared to total leaf area

Necrosis

LEAF 10 — 60% LEAF 11 — 75%

LEAF 6 — 9%

LEAF 9 — 43%

LEAF 7 — 19% LEAF 8 — 29%


8

Leaves 12 to 17 Percentage of leaf discolouration compared to total leaf area

Discolouration

LEAF 16 — 50% LEAF 17 — 75%

LEAF 12 — 3%

LEAF 15 — 19%

LEAF 13 — 6% LEAF 14 — 10%



3.1 Assessment of an individual tree

Seven steps are required to assess the CDI of a young eucalypt:

The steps are described in detail below.

Step 1: Inspect the plantation

Before commencing the sampling routine, the assessor must inspect the whole standof trees to be assessed to become familiar with the range of features and symptoms atthe site.

Step 2: Inspect the tree

Walk around the tree and determine if the crown shows symptoms of defoliation,necrosis and discolouration. As a minimum, crowns should be viewed from at leasttwo sides.

There may be more than one example present of each type of damage, for exampleChristmas beetle defoliation of the mature foliage and defoliation of young leaves bychrysomelid leaf beetle larvae. Both examples are added to the overall estimate of defoliation (leaf tissue missing).

3. How the Crown Damage Index works

Step 1: Inspect the plantation

Step 2: Inspect the treeCanopy shapeJuvenile and adult foliage

Step 3: Estimate Incidence

Step 4: Estimate Severity

Step 5: Calculate I x S

Step 6: Sum to obtain index

Step 7: Record data

Seven steps to assess the CDI of a young eucalypt


Step 3: Estimate damage Incidence

Damage incidence (I) is the estimated percentage of the leaves in the crown affected by

each type of damage (assessed relative to the crown of an undamaged tree on that site.

Different species of eucalypts, even as young, vigorous and undamaged trees, can vary

significantly in character—including crown shape, crown size and foliar colour, density

and distribution. It is therefore very important to understand what a healthy tree looks

like. Examples of healthy young crowns of several different eucalypt species are shown

in Trees 1 to 3. These can be considered ‘Reference Trees’. The role of Reference Trees

is discussed further in the following section. The Field Guide to Eucalypts (Brooker &

Kleinig 1990) illustrates many of the species used in plantations and farm forests.

The precision of a tree’s CDI can be improved if incidence is estimated separately for

different parts of the crown. This requires a method of dividing the tree crown, which

can be done in a number of ways, for example, according to leaf growth stage and/or

position in the crown. The readily identifiable leaf growth stages would be:

leaf flush (young, expanding foliage that tends to be on the upper and outer layer

of the crown) (Tree 1)

juvenile and mature foliage (Tree 1).

Assessing the damage incidence separately for each leaf growth stage can increase

the precision of the CDI estimate for the tree because damage from biological and

environmental agents is often associated with a particular leaf phase or leaf age

grouping. However, some assessors may find it easier to simply divide the crown

into horizontal and/or vertical segments.

The proportions of each type and/or position of foliage should be estimated, followed

by an estimate of the incidence of damage within that portion of the crown.

10



Tree 1 — Eucalyptus globulus (Tasmanian Blue Gum), showing leaf flush, juvenile and

mature foliage


12

Tree 3 — Healthy Corymbia maculata (Spotted Gum)

Tree 2 — Healthy Eucalyptus cloeziana

(Gympie Messmate)



Step 4: Estimate damage Severity

‘Severity’ (S) is the average percentage of damage to the affected leaves.

The amount of missing leaf area can be estimated by visually reconstructing the outline

of the leaf before defoliation. Leaves 1 to 17 illustrate the range of potential damage

at the leaf scale and will help guide your estimation. While undertaking the preliminary

walk through the plantation collect a handful of damaged leaves and sort them into

the three types of damage (that is, defoliation, necrosis or discolouration—note some

leaves may have more than one type of damage). This will provide a guide to the types

of damage to look for on the trees assessed.

Step 5: Multiply each Incidence x Severity

To produce a continuous variable between 0 and 100, each incidence x severity product

is divided by 100. Record the I x S product for each type of damage present (defoliation,

necrosis and discolouration).

Step 6: Sum the products

The Crown Damage Index is the sum of the products of each incidence and severity.

EXAMPLE 1:

For a tree where:

+ an insect had eaten approximately half the leaf tissue (therefore severity, S = 50%)on average from leaves present in the top 25% of a tree crown (therefore incidence,I = 25%), and

+ something had caused approximately 20% necrotic damage per leaf (thereforeseverity, S = 20%) to the lower 50% of the crown (therefore incidence, I = 50%),and

+ there was no evidence of damage to the middle 25% of the crown

= then the CDI would be (25 x 50)/100 + (50 x 20/100) = 22.5.


EXAMPLE 1: SUMMARY OF CALCULATIONS

CROWN DAMAGE DAMAGE PRODUCTPORTION INCIDENCE (I) SEVERITY (S) (I X A)/100

1 (TOP 25%) 25% 50% 25 X 50 / 100 = 12.5%

2 (MIDDLE 25%) 0% 0% 0%

3 (LOWER 50%) 50% 20% 50 X 20 / 100 = 10%

CROWN DAMAGE INDEX 12.5 % + 10% = 22.5%

EXAMPLE 2:

A young eucalypt tree crown with the top half of the foliage missing—50% of crown

and 100% severity at the leaf scale = (50 x 100)/100—and no damage on the remaining

leaves, would have the same CDI (i.e. 50%) as a crown with the upper 25% of foliage

missing and 50% of the crown having, on average, leaves with 50% of their area

damaged by fungal leaf spot—CDI = (25 x 100)/100 + (50 x 50)/100.

EXAMPLE 3:

Where leaves on the top half of a young eucalypt are discoloured completely purple,

and those on the lower half are healthy, the CDI would be (50 x 100)/100 = 50.

A similar CDI would be given for a tree in which all leaves had inter-veinal chlorosis in

which approximately half the area of each leaf was yellow, that is (100 x 50)/100 = 50.

With practice, an experienced observer will be able to calculate the CDI for a tree

by simply estimating the overall photosynthetic leaf area damaged or missing,

without calculating I x S.

Step 7: Recording additional information

It is essential that the assessment date be recorded because most damaging agents

produce a range of symptoms that change over time, influenced by the length

of exposure to the damaging agent, season and tree crown growth.

14

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Additional information should be recorded along with the CDI values. For example,

tree growth parameters and the separate damage I x S products (with supporting

description), as described in Example 1, as well as the total tree CDI. This will help

with interpreting the CDI results.

While inspecting the plantation and assessing CDI values, it would also be efficient

to collect samples of damaged foliage so that the causes of disease can be diagnosed.

3.2 Quality control requirements for individual tree assessment

In order to estimate the CDI of a tree as precisely as possible it is necessary to minimise

variations not attributable to crown damage. Possible sources of variation include:

observer estimation of leaf severity and crown incidence (related to the

observer’s experience)

environmental conditions (e.g. light conditions at the time of assessment)

tree genetics (and interactions with site conditions).

Interpretation of tree crowns can be a significant source of variation between observers.

Different eucalypt species have different crown shapes, densities and habit. Tree form

can be modified by competition and past damage. Trees 1 to 3 show the typical shape

and foliar density of ‘healthy’ tree crowns for a range of species and are provided as

‘Reference Trees’. These tree crowns have no (or very little) visible foliar damage and

would be assigned a zero or very small CDI.

The two CDI parameters, leaf severity and crown incidence, may vary between 0 and

100%. The statistical method requires that assessors must estimate a value, rather than

nominate a range (for example, 0–10%; 11–20%, etc.). Some assessors will make

estimates to the nearest 10%, for example, which is acceptable.



The acceptable range of observer agreement associated with visual estimation of the

CDI is plus or minus 10% between an experienced user of the CDI procedure (the

trainer) and field assessors. It is also strongly recommended that assessors test the

repeatability of their assessments by re-assessing a sub-set of trees on consecutive days.

The acceptable level of assessor precision between repeated estimates should also be

plus or minus 10%.

3.3 Collecting CDI data across a plantation

In this section, we explain how to collect CDI data across a plantation. A plantation may

be a particular tree farm or block within a large plantation estate—it may vary from a few

tens of hectares to hundreds of hectares in size. In most cases, we are interested in a

summary of the CDI for the entire plantation, rather than the CDI values of individual

trees. There are many different ways of collecting and summarising CDI data, but the

method specified in this manual has been tested and found to provide good results and

be cost-effective. The rationale for using this method is explained in the Appendix.

There are seven steps in CDI data collection. Steps one to four can be carried out before

visiting the plantation. Steps five to seven are carried out on site. The data can be

entered into the worksheet for data entry that can be downloaded from the National

Forest Inventory web site (www.affa.gov.au/nfi).

16


Step 1: Define the plantation

The size of a plantation for which the

CDI is assessed separately is ideally

between a few tens of hectares and

hundreds of hectares in size. For

a plantation estate comprised of

separate properties or tree farms,

the separate properties or tree farms

or a group of them can be used as

the plantation for sampling purposes.

For more extensive plantation

estates, the management units

(e.g., compartments) already defined by the owner/manager can be used as the

plantation area for sampling.

A plantation with more than one species and/or planting year can be assessed

concurrently if that is more cost-effective. However, that will require additional

sampling, as described below, and the result will be a separate CDI for each species

and/or planting year.

The map of a plantation selected for assessment is shown in Figure A.


In the office:

Step 1: Define the plantation

Step 2: Divide the plantation into 8 sections

Step 3: Divide the sections into grid cells

Step 4: Select one grid cell in each section

On site:

Step 5: Locate a grid cellin the field

Step 6: Select 6 trees per grid cell

Step 7: Assessment and data entry

Figure A

Seven steps of data collection


Step 2: Divide the plantation

into 8 sections

Divide the plantation into eight sections

of approximately equal area. Sampling

from eight sections has been shown

to provide the best balance between

the economy of sampling and precision

of the data.

Figure B shows the sections defined

for this example plantation.

Step 3: Divide the sections

into grid cells

Superimpose a grid system onto a map of the plantation (Figure C). This can bedone using GIS software (eg. ArcView) or by printing a grid system on atransparency and overlaying it on a printedmap. If the plantation (or planted areas for a given species) is over 100ha, then use a 100m x 100m (1ha) grid system. Use a 50m x 50m (0.25ha) grid system for smaller areas.

If the whole plantation or the planted areafor a species is less than 2ha (i.e. less theneight 0.25ha grid cells) then there are two options:

place as many 0.25ha grid cells as can be fitted into the area

treat the whole area as one section; this option is less costly but gives less preciseresults than the first.

There will be partly stocked grid cells near the edge of the plantation and where theplanted area is narrower than 50m (e.g. along drainage lines)—partially stocked grid cellsare also included.

18

Figure B

Figure C


Step 4: Select one grid cell

in each section

One grid cell must be selected at random

in each section; this is one way to select

a cell at random:

hold a pen vertically about 10cm above

a section on the map of the plantation,

then drop the pen with eyes closed

mark a grid cell where the pen

has landed

repeat this for each section until one

cell has been selected from each section (Figure C).

In a multi-species plantation there are two options:

carry out steps three and four for each species separately, or

in each section, first locate a section by dropping a pen; the first grid cell can be

of any species, then locate grid cells for the other species by finding the closest grid

cell occupied by other species (Figure D).

In a mixed-aged plantation there are two options:

sample each age class separately or

if the age classes are of similar susceptibility to crown damage (for example, less than

two years separating the planting areas) then combine the age classes.

An alternative way to select a grid cell in each section at random is to number the rows

and columns so that each cell can be identified by coordinates. A random number

generator can then be used to select coordinates.


Figure DSpecies 1

Species 2


Step 5: Locate a grid cell in the field

Using the map of the plantation go to

where one of the marked sections should

be, then use tree spacing to roughly

measure out the distance from notable

features (e.g. edge of plantation, patch of

remnant vegetation, fire-break) to where

a corner of the section should be. A Gobal

Positioning System may be used to locate

a section.

The exact location of a grid cell is not so

important. However, assessors must always

try to go to the grid cells selected and

marked on the map in Step Four, rather

than choosing other locations for

convenience (e.g. near the road).

Once the assessor has reached a corner

of a grid cell indicated on the map, stand

where the corner should be. The exact

location of the corner is not so important.

However, assessors should not to select

particular features (e.g. small openings

in canopy or ground cover) as the corner.

If a grid cell is partly stocked, then go to

where the grid line intersects the plantation boundary and start there.

The grid cell for sampling is within the area defined by 50m (or 100m) along the closest

row and 50m (or 100m) in the direction perpendicular to the rows, either to the right

or left, depending on position which corner the assesser is standing at (Figure E).

20

Figure F

An area for sampling

Figure E


A grid cell does not have to be square or a rectangle. If there are many planted areas

smaller than 0.25ha (or 1ha), or if the planted areas are long and narrow, then a grid cell

is a planted area totalling roughly 0.25ha (or 1ha) (Figure F).

Step 6: Select 6 trees per grid cell

Go to the tree closest to the corner of the

grid cell. The first tree for assessment is the

next tree in the same row.

To locate the second tree for assessment,

walk along the row to the third tree from

the tree for the first assessment—the

adjacent tree on the next row is the

second tree for assessment (Figure G).

Repeat the above procedure until six trees

have been assessed (Figure H).

If a grid cell contains less than six rows,

select the six trees by moving back and forth

between the rows. For example, if there are

three rows, move from row one (first tree)

to row two (second tree) to row three (third

tree) to row three (fourth tree) to row two

(fifth tree) to row one (sixth tree).

Sampling six trees from each section has

been found to provide the best balance

between economy of sampling and precision

of the data.


Figure G

Corner

The

nearest

tree

Figure H

1

2

3

4

5

6


If any trees selected for assessments are

dead or runts, then skip that tree and go

to the next tree along the same row. For

example, if the tree selected for the third

assessment is dead, then go to the next

tree on the same row, instead of leaving

the third tree as missing (Figure I). A runt

is a severely under-developed tree that

is not typical of adjacent trees.

If the selected tree is alive and not a runt,

that tree needs to be assessed no matter

how it looks.

Step 7: Assessment and data entry

Each of the six trees should be assessed for CDI as the assessor locates them. If using

palmtop computers in the field, CDI scores of each tree can be directly entered into the

worksheet for data entry.

If the data is being recorded on paper, CDI scores of each tree should be recorded

on the pre-formatted data sheets in the field and entered into the worksheet later.

CDI can be scored as a single figure for a crown (e.g. 50%), or the separate agents

causing the damage can be scored separately (e.g. 25% insect damage plus 25% fungal

damage). The program will use these two (or more) figures to automatically calculate

the CDI for the tree (50%), so the overall CDI does not need to be entered also.

The sample CDI mean and the 95% confidence interval for each plantation will be

automatically calculated as the data are entered in the worksheet using the standard

formulae (Scheaffer et al. 1986).

22

X

Figure I× Dead Tree

1

2

3

4

5

6


The worksheet for data entry can be downloaded from the National Forest Inventory

web site (www.affa.gov.au/nfi).

If any of the small planted areas are treated as one large section (as described in step

three) and if only six trees are sampled from that area, then the sample CDI mean

is the mean of the CDI values of the six trees. The 95% confidence interval = standard

deviation x 2 /√6 = standard deviation x 0.8.

The palm PC version of the worksheet for data entry calculates the sample CDI mean

and 95% confidence interval after sampling from the first two sections, and after

every section thereafter. The assessor will be able to terminate the assessment before

assessing all eight grid cells if the calculated 95% confidence interval is narrower than

the desired 95% confidence interval (which should be decided before starting the

assessment—see the notes with the worksheet).

If the CDI data is recorded on paper, the assessor should visit all eight grid cells because

the assessor will not know the 95% confidence interval until the data are entered into

the worksheet for data entry.

The calculated 95% confidence interval may be much larger than desired if there is large

variation in the CDI values among trees within a plantation. If the lower bound of the

95% confidence interval is less than zero, then an additional two to four grid cells

must be selected at random (still one grid cell per section) and six trees per grid cell

assessed. If the lower bound of the 95% confidence interval is greater than zero, it is

recommended that an additional two to four grid cells be selected and six trees per grid

cell be assessed.



3.4 Summarising the CDI value for a plantation

The average CDI of plantations can be summarised to estimate sample CDI means for

an organisation, district/region/state, or age class using the worksheet for data entry.

The worksheet will automatically calculate the means and 95% confidence intervals

using standard formulae (Sukhatme et al. 1984).

The CDI data can be summarised in many ways. These are some examples

within an organisation or state:

summarise by districts to reflect management units

summarise by regions to reflect climate, geography, or biology

summarise by age class if plantations are not mixed-age.

In all these cases, the CDI data should be summarised separately for each tree species,

unless there is a specific need or justification for combining tree species.

One requirement for summarising the CDI data is that the total number of plantations

must be known. For example if the CDI data is summarised for the two year old E. nitens

in district A, then the total number of plantations of two year old E. nitens in that

district must be specified in the worksheet for data entry.

24


3.5 Timing of CDI assessment

There is an obvious trade-off between the cost of collecting CDI data and its temporal

value. The timing and frequency of assessments will depend on the intended use

of the information.

If the data are intended to contribute to demonstrating the effectiveness of a plantation

establishment program or the healthiness of a young plantation then an annual

assessment at the end of the main growing season would be appropriate. In temperate

regions this tends to be in autumn.

The CDI could also be used to demonstrate the effectiveness of pest management

programs and should, therefore, be assessed before and after control treatments.

It could also be used to quantify the extent of canopy recovery after a major

defoliation event.

It is envisaged that the CDI will become a standard indicator to be included

in assessment programs developed for the measurement of other tree parameters.



The Crown Damage Index sampling strategy

If we assess the CDI of every tree in a plantation and take the average, then we get the

plantation CDI mean—the highest quality CDI data. However, it is not usually practical

to assess every tree in a plantation. For that reason we estimate the plantation CDI

mean by assessing a small sample of trees and calculating a sample CDI mean.

Our objective when selecting the sample is to ensure that the resulting sample CDI

mean is unbiased and precise.

Theoretically speaking, a sample CDI mean is said to be unbiased if:

it is calculated from a sample of trees selected using a particular rule

different samples of trees can be selected from the same plantation using

the same selection rule

sample CDI means are then calculated for all samples of trees selected using

this same rule, and then

the mean of all the sample CDI means is equal to the plantation CDI mean.

The best-known method to arrive at an unbiased sample CDI mean is to select trees

randomly (i.e. simple random sampling). There are other rules that give unbiased

samples, but there is one common feature among all the rules—trees are selected

before they are looked at.

A sample CDI mean is said to be precise if the variance of the sample CDI mean is small.

The magnitude of the sample variance is often expressed using 95% confidence intervals

(refer to the Glossary for further explanation of confidence intervals). Sample CDI

means that have narrow confidence intervals are more precise than those with wide

confidence intervals.

26

Appendix


A narrow 95% confidence interval can be achieved by selecting trees with similar CDI

values and by increasing sample size. Unfortunately, trees with similar CDI values cannot

be selected because that would bias the result—trees must be selected before they are

looked at. The desired precision is achieved by using a sampling strategy (that is, a rule

for selecting trees) that provides a balance between sample size and precision.

The sampling strategy prescribed in this manual is called two-stage cluster sampling.

This method involves dividing a plantation into grid cells of equal size and selecting

a subset of grid cells. A small number of trees are then assessed within the selected

grid cells.

A sample CDI mean obtained using two-stage cluster sampling is an unbiased estimator

of the plantation CDI mean and can provide a good balance between precision of the

data and cost of sampling. Two-stage cluster sampling permits sampling of trees in small

areas from different parts of a plantation and reduces the travelling time between trees.

This strategy is therefore more economical than other sampling strategies (e.g. simple

random sampling).

Glossary

Confidence interval

The confidence interval is one way to compare the sample mean with some other value.

The upper bound is calculated as the sample mean plus the 95% confidence interval.

The lower bound is calculated as the sample mean minus the 95% confidence interval.

If the same number of trees is selected using the same selection rule 100 times, and 100

different sample CDI means are calculated with 95% confidence intervals then, in theory,

the plantation CDI mean is located somewhere within the 95% confidence intervals 95

out of 100 times. Therefore, a sample CDI mean with a narrow 95% confidence interval

would be more likely to be closer to the plantation CDI mean than a sample CDI mean



28

with a wide 95% confidence interval. However, it can never be certain that a sample

CDI mean is the one of the five from 100 for which the 95% confidence interval does

not span the plantation CDI mean.

If any part of one half of the 95% confidence interval for the sample CDI mean from

a plantation overlaps with one half of the 95% confidence interval for the sample CDI

mean from another plantation then, statistically speaking, the sample CDI means from

those two plantations are not significantly different.

Mean

The mean is one way to express the central tendency (i.e. average) of the data:

if all trees in a plantation are assessed, a plantation mean is obtained

a sample mean is obtained if a subset of trees in the plantation is assessed.

Standard deviation

Sample standard deviation is one way to express the similarity of the values in a sample.

Standard deviation is the square root of the sample variance. The sample standard

deviation has the same unit as the sample mean.

Sample Variance

Sample variance is another way to express the similarity between the values in a sample.

Sample variance is the sum of the square of the differences between the sample mean

and each value, adjusted for the sample size. Because each difference is squared, variance

is measured in the squared unit. For example, if tree height is measured in cm, the

variance is in cm2.


Brooker, MIH and Kleinig, DA 1990, Field Guide to Eucalypts, vol. 1 South-easternAustralia, Inkata Press, Melbourne and Sydney.

Carnegie, AJ 2002, Field Guide to Common Pests and Diseases in Eucalypt Plantationsin NSW, Research and Development Division, State Forests of NSW.

Candy, SG and Zalucki, MP, 2002, ‘Defoliation’ in Encyclopedia of Environmetrics,vol. 1 (eds El-Shaarawi, AH and Piegorsch, W), pp. 479–484, John Wiley and Sons Ltd,

Chichester, UK.

Dell, B, Malajczuk, N, Xu, D and Grove, TS 2001, Nutrient Disorders in PlantationEucalypts, 2nd edn (rev.), Australian Centre for International Agricultural Research,

Canberra.

Elliott, HJ and deLittle, DW 1985, Insect Pests of Trees and Timber in Tasmania, Forestry

Commission, Hobart, Tasmania.

Innes, JL 1993, ‘Methods to estimate forest health’, Silva Fennica, vol. 27, pp. 145–157.

Phillips, C 1996, Insects, Diseases and Deficiencies associated with Eucalypts in SouthAustralia, Primary Industries South Australia, Mt Gambier, South Australia.

Private Forests Tasmania, Farm Forestry Toolbox, Private Forests Tasmania, Kings

Meadow, Tasmania.

Scheaffer, RL, Mendenhall, W, and Ott, L 1986, Elementary Survey Sampling, 3rd edn,

Duxbury Press, Boston, Massachusetts, USA.

Stone, C, Wardlaw, T, Floyd, R, Carnegie, A, Wylie, R and de Little, D 2003,

‘Harmonisation of methodologies for the assessment and reporting of forest health

in Australia—A starting point’, Australian Forestry (In Press).

Sukhatme, PV, Sukhatme, BV, and Asok, C 1984, Sampling Theory of Surveys withApplications, 3rd edn, Iowa State University Press, Ames, Iowa, USA.

US Department of Agriculture, Forest Service 2002, Forest Inventory and AnalysisNational Core Field Guide, vol 1 Field data collection procedures for phase 2 plots,version 1.6, US Department of Agriculture, Forest Service, Forest Inventory and Analysis,

Washington, DC, www.fia.fed.us/library.htm#Manuals


Bibliography


30


S C I E N C E F O R D E C I S I O N M A K E R S



IN YOUNG EUCALYPT PLANTATIONSThe Crown Damage Index is a standardised statisticallysound method for assessment of crown damage causedby pests and diseases in young eucalypt plantations. Thismanual describes how to measure the CDI of individualtrees and plantations. A worksheet that is necessary fordata entry and analysis can be downloaded from theNational Forest Inventory web site (www.affa.gov.au/

nfi).

The Crown Damage Index provides a statistically validmeasure of crown damage in a plantation. Plantationmanagers can therefore use CDI data to plan andmonitor pest and disease treatment and to providea basis for reporting to plantation owners. CDI data canalso be used to monitor research trials and to providea basis for assessment of compliance with environmentalmanagement systems and similar monitoring andreporting requirements.

The Crown Damage Index was developed by plantationhealth managers and researchers working in severalregions of Australia. This manual has been publishedso that the method can be applied and tested by otherplantation managers and contractors, tree breeders,silviculturists and forestry researchers.

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