Evaluations of systematic damage assessments of 5, 10 and 20 percent of all apple trees in 12 orchards were compared. The 10% assessment technique was selected as the most accurate and efficient in estimating summer and fall damage. Analysis of several parameters of tree vigor found significant differences between browsed and unbrowsed trees for tree basal diameter and central leader diameter over 2 successive years. These subtle yet important differences in tree development were felt to severely limit the possibilities of relating browsing to growth and. later, yields. Methods and considerations for making control decisions on a per acre basis are discussed

Ellingwood, Mark R.

Fargione, Michael J.

McAninch, Jay B.

Picone, Peter

English

UNL | Libraries

University of Nebraska - Lincoln 
DigitalCommons@University of Nebraska - Lincoln 
2 - Second Eastern Wildlife Damage Control 
Conference (1985) Eastern Wildlife Damage Control Conferences 
September 1985 
ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDS 
Jay B. McAninch 
Institute of Ecosystem Studies, The New York Botanical Garden 
Mark R. Ellingwood 
Institute of Ecosystem Studies, The New York Botanical Garden 
Michael J. Fargione 
Institute of Ecosystem Studies, The New York Botanical Garden 
Peter Picone 
Institute of Ecosystem Studies, The New York Botanical Garden 
Follow this and additional works at: https://digitalcommons.unl.edu/ewdcc2 
 Part of the Environmental Health and Protection Commons 
McAninch, Jay B.; Ellingwood, Mark R.; Fargione, Michael J.; and Picone, Peter , "ASSESSING DEER 
DAMAGE IN YOUNG FRUIT ORCHARDS" (1985). 2 - Second Eastern Wildlife Damage Control Conference 
(1985). 32. 
https://digitalcommons.unl.edu/ewdcc2/32 
This Article is brought to you for free and open access by the Eastern Wildlife Damage Control Conferences at 
DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in 2 - Second Eastern Wildlife 
Damage Control Conference (1985) by an authorized administrator of DigitalCommons@University of Nebraska - 
Lincoln. 
ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDS
by Jay B. McAninch, Mark R. ELI ingwood.* Michael J. Fargione and Peter Picone00
Institute of Ecosystem Studies, The New York Botanical Garden
Millbrook, New York 12545
ABSTRACT
Evaluations of systematic damage
assessments of 5, 10 and 20 percent of
all apple trees in 12 orchards were
compared. The 10% assessment technique
was selected as the most accurate and
efficient in estimating summer and fall
damage. Analysis of several parameters
of tree vigor found significant differ-
ences between browsed and unbrowsed
trees for tree basal diameter and
central leader diameter over 2 succes-
sive years. These subtle yet important
differences in tree development were
felt to severely limit the possibilities
of relating browsing to growth and.
later, yields. Methods and considera-
tions for making control decisions on a
per acre basis are discussed.
INTRODUCTION
Assessing and controlling deer damage
in apple orchards has been a topic of
concern for many years (Berry, 1948;
Morse and Ledin. 1958- Harder. 1968;
Katsma and Rusch, 1979). Assessments
of the extent and severity of damage
have been evaluated (Harder. 1970
Katsma and Rusch. 1979) and have
proved difficult to both quantify and
express in terms of tree maturation and
yields. Although methods for assessing
damage have been proposed (Berry, 1948-
Katsma and Rusch. 1979), the use of
these techniques in making damage
control decisions has been very limit-
ed. As most control decisions are made
during the early years of tree develop-
ment (Forshey, 1976). a useful damage
assessment technique and some criteria
for making control decisions during the
first 5 years of orchard development
were considered essential to farmers,
extension agents and agents for damage
reimbursement programs.
We acknowledge the assistance of
Current addresses: °Connecticut Depart-
ment of Environmental Protection. North
Franklin, CT 06254 • "^Southington. CT
06489
Carol Dowden. Robert Mungari. Julie
Morgan and Raymond Winchcombe. This
project was a contribution to the
program of the Institute of Ecosystem
Studies, the New York Botanical Garden.
Financial support was provided by the
New York Department of Agriculture and
Markets .
METHODS
Assessment Study
In January 1985 12 orchard blocks
located in Southeastern New York were
evaluated for the presence of summer and
fall deer damage. Blocks contained from
251 to 692 trees and ranged in age from
1 to 4 years (Table 1). Trees were
recorded as damaged if at least one
browsed limb was observed. The location
of each tree in each block was mapped
for later use in deriving simulated
assessment data. Actual damage ranged
from 1.1% to 89.7% for the summer and
from 0.2% to 77.0% in the fall. Using
the mapped tree data for each block,
systematic assessments of 5. 10 and 20
percent of the total number of trees in
each block were generated. Assessments
were summed and compared to actual
damage rates. Finally, equations for
estimating damage rates from sample data
were generated with 90% prediction
intervals .
Growth Study
A stratified sample of 210 semi-dwarf
apple trees, ranging in age from 1 to 2
years and consisting of 3 varieties was
selected and tagged in Southeastern New
York orchards. Tree growth parameters
were evaluated during the fall of 1982
and 1983. Damage assessments were
conducted after leaf fall and during
March of both years. Data collected
from each tree included basal diameter,
limb diameter, and the percent of at
least 1 browsed twig. In addition, the
annual growth increment of the central
leader and 3 systematically selected
limbs were taken from each tree. Basal
215
1= A
1985
©f 12 y®samg ©Trefcsajrdl bl©sks evaluated for decir (dlaoage in
AGE
iyzs)
OF ACTUAL PAK1ACE (100%)
FALL
F
G
H
I
J
K
L
3
3
3
2
2
2
2
1
1
1
335
251
350
369
357
362
63=9
53.0
5.1
35o4
©9 = 7
11=2
54»5
1.1
18ol
&0oQ
32o3
1.8
Del
7^=0
77oO
Io2
52»S
50=7
©=2
30=7
in 12
aos®sooGmt cczipairioons toased on deer dsnage ausrveys
orchard blocks disrimg Janoaary 1985 =
F VALUE
OF EIEAM SQUARE
5%
10?
20%
22 13o83
12=23
,5)5
5=94
5=25
352o72
diameter was recorded as the average of
2 measurements taken 10 cm above the
ground surface. When the scion graft
was above the 10 cm height, basal
diameter was taken at 15 to 20 cm above
the graft, depending on scar swelling of
216
the bole.
Limbs, defined as stems 10 cms or
more in length and attached directly to
the tree bole, were systematically
selected by starting with the bottom
limb, and counting upward, selecting
limbs 1, 3 and 5 for measurement. Limb
diameters were measured approximately 2
cm from bole attachment. The growth
increment of each selected limb was the
length for all the most recent summer
growth on all twigs (excluding spurs).
Leader diameter and leader length were
measured at the point of recent growth
initiation.
Damage counts included the frequency
of browsing on the past season's growth
and, as such, occasionally resulted in a
single twig having been browsed more
than once. For this analysis, the
occurrence of 1 browsed twig was used to
classify trees as browsed.
RESULTS
Assessment Study
Analysis of the variation in the 3
sampling methods used was derived from
significance values, coefficients of
determination, coefficients of varia-
tion, mean square error and the sum of
the squared residuals. The analysis of
summer damage data resulted in the
selection of the 10% sample assessment
methods as the most accurate of the
three methods tested (Table 2). The 10%
method had the largest F value and
highest degree of association with the
actual damage values. In addition, the
10% method had the lowest coefficient of
variation as well as the least amount of
variation about the predicted line
(Fig. 1). Finally, the equation for
deriving deer damage rates from 10%
samples of fruit trees damaged in summer
was generated with a 90% prediction
interval.
The fall damage assessment analysis
found the sampling methods increased in
significance and prediction accuracy
with increased sampling rates (Table
3). Despite this trend, the relative
gains in accuracy from the 20% sampling
method over the 10% sampling method were
considered to be less than the value of
the labor needed to sample the addition-
al trees. In fact, the analysis of
variation and accuracy found very slight
differences between the 10% and 20%
methods. The prediction equation and
90% interval were developed (Fig. 2) and
were similar to the summer prediction
relationship.
Growth Study
Analysis of variance (Table 4)
indicated significant differences
(p < 0.0001) existed in almost all
growth parameters when compared between
orchards. This was likely a result of
age and varietal differences, varying
management practices and site quality.
When browsed and unbrowsed trees were
compared, significant differences
(p < 0.02) existed for tree basal
diameter in both years (Table 4). Basal
diameter, which has been traditionally
considered a good indicator of tree
vigor, was considerably less variable
than other tree growth parameters.
Central leader diameter was notably
different (p < 0.06) between browsed and
unbrowsed trees during both sample years
(Table 4). Trends for average limb
diameter measurements were that browsed
trees had greater diameters than
unbrowsed trees. This latter result
could be evidence of growth stimulated
by deer browsing. Field observations
suggested that browsing appeared to
result in more net annual limb growth
due to the release of laterals and the
continuation of terminal growth at a
time when unbrowsed twigs appeared to be
hardening off .
DISCUSSION
Based on this study, a 10% systematic
sampling of fruit trees would result in
a predicted damage rate with acceptable
accuracy. Surprisingly, the prediction
interval was not wider at low damage
levels and narrower at high damage
levels, as might be expected by sampling
theory.
The significant differences encoun-
tered between browsed and unbrowsed. 1-
and 2-year-old fruit trees were unexpec-
ted, in view of the lack of differences
reported by Harder (1970). As many
trees were not judged to be severely
browsed, the fact that overall tree
vigor differed across all browsed trees
suggests that the impact of deer
browsing over the first years of tree
development were subtle yet important.
Since browsing can occur at irregular
intervals during summer and winter of
217
E = E VALUE) ^1O24
DICTION INTERVAL
CO
LU
. .J
O
o
o
<
0
10% SAMPILE DAMAGE VALUE
l o Tto<E irelafc&romQhip ibettjGGin oanpl® atad oe t taa l ocanaer
v a l a e o 2©ir 12 ffjrtmAtt ©sretoairda aooeasod Aim Jaimt3Qiry0 11>85o
218
Table 3o Fall
corailucted in 12
assessment ccaparisons based on deer danage surveys
orchard blocks during January 1985=
F VALUE
COEFFXCXEPJT OF MEAN SQUARE SUM OF SQUARED
RESIDUALS
5%
102
201
180 o
350,,
360 o
40
21
55
,,95
.97
19 = 88
14.45
u 2 5
6.80
4-95
4o88 237o88
R e s u l t s of a n a l y s i s of vairiatEc® for 10 girrowth paraae te i rs c o l l e c t e d
210 young f r u i t fcireess duirimg the f a l l of 1982 and
BEfKTEEM ORCHARDS
F-TOLUE FKO®>IF F-VALUE
Average l iob
growth—1902
Average lirab
125ol9
,0001
,0001
0«17 ,6785
,1738
Basal
dliane t e r — 1 S>®2 = 0001 O0282
€sirstr£il leader
growth—19©2
leader
diameter—1
Average linh
lioto
Ilo36
2o26
0o29
13o39
,1072
,7482
=0001
0o02
0=04
(Esmttral leader
,0237
,0126
1 = 16 ,2830
,0596
219
y j
aE VALUE = .90CSAMPLE DAMAGE VALUE)—.15
IE
sr <s 2o Tihe s r e l s t i o n o l h i i p fee flit? Gem o a o p l e
ff©E" 12 ffirooiit ©irelbQirdSlo QOOGOOGHII ion
a c t w i a l
220
ffcilble 5= Stur^ afliry of
orchard
per acre costs of the first five years of apple
COST
CUMULATIVE REPLACMEM"
COST COS'T
Site preparation
Year 1
Year 2
Year 3
Year k
Year 5 3
$745
$1554.
S733
$875
$1059
$1029
$2299
$3032
$3096
$4965
$6174.
$15o00
$20.©0
$25=00
S32.0O
$4>0o00
opportunity eosL
on 155 trees/acreo
Encluden incrae lost ftrca fruit tevrest.
each year and then in an irregular
pattern over the first years of develop-
ment, the relationship between deer
damage and delayed tree maturity or
reduced yields may be nearly impossible
to establish. Katsma and Rusch (1979),
in their evaluation of deer damage in
mature orchards, felt that the possibil-
ity of predicting production loss
resulting from deer browsing was
remote. For immature trees, rapid
growth, recurring damage, and the nature
of pruning practices often tend to
obscure the long-term effects of deer
browsing.
The preceding discussion would
suggest that precise quantification
of browsing may accurately reflect deer
activity in orchards, yet may not reveal
the level of tree vigor and subsequent
growth and development of trees suffer-
ing damage. In the course of several
repellent, fencing and damage assessment
studies in Southeastern New York, the
authors have concluded that farmers seem
to be assessing the impact of deer
damage in terms of tree establishment
(good vigor and terminal growth in year
1) , development of tree structure (good
terminal and scaffold limb growth in
years 2 and 3) and maturity (full tree
shape and initiation of production in
years A and 5). The impact of deer
damage under these changing and somewhat
ambiguous criteria of assessment further
obscures the possibility of measuring
the benefits of damage control programs.
An additional concern of farmers has
been the assessment of loss on individu-
al trees as opposed to those lost on a
per-acro basis. Although the total cost
of replacing trees can be substantial,
particularly as trees increase in age
(Table 5), nearly all orchards are
managed on a per-acre basis (Gerling,
1981) . Compensation for losses based on
replacement costs in years 1 and 2 may
be useful, but beyond years 2 or 3,
farmers are reluctant to replant
individual trees within blocks of older
trees. Even aged orchards have been
easier and less costly to manage than
interplanted orchards (Forshey. 1976).
Assessment techniques that result in
damage estimates on a per-acre basis
allow for more direct comparisons of
damage with the costs of various damage
control measures. In the absence of
221
Prof if (Do l l a r s )
(0 68
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precise loss estimates (or benefit
project ions) . farmers might be advised
to assess the extent of damage across
blocks, judge economic r i sk from
experience, and evaluate the cost of
damage control measures against poten-
t i a l re turns . Using projections of
potential accumulated profi t per acre
(Gerling, 1981), farmers could, for
example, see that a reduction in yield
of only 200 bushels on 1 acre of trees
could resul t in $10,000 in loss over the
20-year period (Fig. 3) . Thus, if the
damage per acre was considered a high
risk to potential gains, the re la t ive
costs per acre of control measures could
be considered against potential accumu-
lated p rof i t s .
Finally, implementation of damage
control measures should be based on
dol lars spent to protect future gains
rather than on dol lars jus t i f i ed by
losses incurred. For nearly a l l other
crop damages suffered by farmers,
control measures are invoked before
losses occur or are subs tan t ia l , and
generally are implemented based on the
resu l t s of a monitoring e f fo r t .
Hopefully, deer damage will someday be
controlled by action rather than
react ion.
. 1970. Evaluating winter
deer use of orchards in western Colo-
rado. Trans. N. Amor. Wildl. Conf. 35-
35-47.
Katsma. D.E. and D.H. Rusch. 1979.
Evaluation of deer damage in mature
apple orchards. Pages 123-142 In
J.R. Beck, ed. Vertebrate pest control
and management mater ia ls . Amer . Soc.
Test. Materials. ASTM STP 680.
Morse, M. and D. Ledin. 1959. Deer,
apples and exploders. Conserv. Volun-
teer 21(121):29-31,
LITERATURE CITED
Berry. R.N. 1948. Orchards versus
deer. Am. Fruit Grower 68(11):13, 18,
26.
Forshey, C.G. 1976. The planting and
early care of the apple orchard.
Informational Bulletin 65. Cornell
University, Ithaca, NY.
Gerling, W.D. 1981. An analysis of
apple orchard replanting costs and
potential p ro f i t ab i l i t y . A.E. Ext.
81-26. 39 pp. Cornell University,
Ithaca, NY.
Harder, J.D. 1968. A l i t e r a t u r e review
on orchard damage by deer. Colo. Dept.
Game, Fish and Parks Spec. Rep. 12. 22
pp.
223


ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDS

DigitalCommons@University of Nebraska

University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln 2 - Second Eastern Wildlife Damage Control Conference (1985) Eastern Wildlife Damage Control Conferences September 1985 ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDS Jay B. McAninch Institute of Ecosystem Studies, The New York Botanical Garden Mark R. Ellingwood Institute of Ecosystem Studies, The New York Botanical Garden Michael J. Fargione Institute of Ecosystem Studies, The New York Botanical Garden Peter Picone Institute of Ecosystem Studies, The New York Botanical Garden Follow this and additional works at: https://digitalcommons.unl.edu/ewdcc2  Part of the Environmental Health and Protection Commons McAninch, Jay B.; Ellingwood, Mark R.; Fargione, Michael J.; and Picone, Peter , "ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDS" (1985). 2 - Second Eastern Wildlife Damage Control Conference (1985). 32. https://digitalcommons.unl.edu/ewdcc2/32 This Article is brought to you for free and open access by the Eastern Wildlife Damage Control Conferences at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in 2 - Second Eastern Wildlife Damage Control Conference (1985) by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDSby Jay B. McAninch, Mark R. ELI ingwood.* Michael J. Fargione and Peter Picone00Institute of Ecosystem Studies, The New York Botanical GardenMillbrook, New York 12545ABSTRACTEvaluations of systematic damageassessments of 5, 10 and 20 percent ofall apple trees in 12 orchards werecompared. The 10% assessment techniquewas selected as the most accurate andefficient in estimating summer and falldamage. Analysis of several parametersof tree vigor found significant differ-ences between browsed and unbrowsedtrees for tree basal diameter andcentral leader diameter over 2 succes-sive years. These subtle yet importantdifferences in tree development werefelt to severely limit the possibilitiesof relating browsing to growth and.later, yields. Methods and considera-tions for making control decisions on aper acre basis are discussed.INTRODUCTIONAssessing and controlling deer damagein apple orchards has been a topic ofconcern for many years (Berry, 1948;Morse and Ledin. 1958- Harder. 1968;Katsma and Rusch, 1979). Assessmentsof the extent and severity of damagehave been evaluated (Harder. 1970Katsma and Rusch. 1979) and haveproved difficult to both quantify andexpress in terms of tree maturation andyields. Although methods for assessingdamage have been proposed (Berry, 1948-Katsma and Rusch. 1979), the use ofthese techniques in making damagecontrol decisions has been very limit-ed. As most control decisions are madeduring the early years of tree develop-ment (Forshey, 1976). a useful damageassessment technique and some criteriafor making control decisions during thefirst 5 years of orchard developmentwere considered essential to farmers,extension agents and agents for damagereimbursement programs.We acknowledge the assistance ofCurrent addresses: °Connecticut Depart-ment of Environmental Protection. NorthFranklin, CT 06254 • "^Southington. CT06489Carol Dowden. Robert Mungari. JulieMorgan and Raymond Winchcombe. Thisproject was a contribution to theprogram of the Institute of EcosystemStudies, the New York Botanical Garden.Financial support was provided by theNew York Department of Agriculture andMarkets .METHODSAssessment StudyIn January 1985 12 orchard blockslocated in Southeastern New York wereevaluated for the presence of summer andfall deer damage. Blocks contained from251 to 692 trees and ranged in age from1 to 4 years (Table 1). Trees wererecorded as damaged if at least onebrowsed limb was observed. The locationof each tree in each block was mappedfor later use in deriving simulatedassessment data. Actual damage rangedfrom 1.1% to 89.7% for the summer andfrom 0.2% to 77.0% in the fall. Usingthe mapped tree data for each block,systematic assessments of 5. 10 and 20percent of the total number of trees ineach block were generated. Assessmentswere summed and compared to actualdamage rates. Finally, equations forestimating damage rates from sample datawere generated with 90% predictionintervals .Growth StudyA stratified sample of 210 semi-dwarfapple trees, ranging in age from 1 to 2years and consisting of 3 varieties wasselected and tagged in Southeastern NewYork orchards. Tree growth parameterswere evaluated during the fall of 1982and 1983. Damage assessments wereconducted after leaf fall and duringMarch of both years. Data collectedfrom each tree included basal diameter,limb diameter, and the percent of atleast 1 browsed twig. In addition, theannual growth increment of the centralleader and 3 systematically selectedlimbs were taken from each tree. Basal2151= A1985©f 12 y®samg ©Trefcsajrdl bl©sks evaluated for decir (dlaoage inAGEiyzs)OF ACTUAL PAK1ACE (100%)FALLFGHIJKL333222211133525135036935736263=953.05.135o4©9 = 711=254»51.118ol&0oQ32o31.8Del7^=077oOIo252»S50=7©=230=7in 12aos®sooGmt cczipairioons toased on deer dsnage ausrveysorchard blocks disrimg Janoaary 1985 =F VALUEOF EIEAM SQUARE5%10?20%22 13o8312=23,5)55=945=25352o72diameter was recorded as the average of2 measurements taken 10 cm above theground surface. When the scion graftwas above the 10 cm height, basaldiameter was taken at 15 to 20 cm abovethe graft, depending on scar swelling of216the bole.Limbs, defined as stems 10 cms ormore in length and attached directly tothe tree bole, were systematicallyselected by starting with the bottomlimb, and counting upward, selectinglimbs 1, 3 and 5 for measurement. Limbdiameters were measured approximately 2cm from bole attachment. The growthincrement of each selected limb was thelength for all the most recent summergrowth on all twigs (excluding spurs).Leader diameter and leader length weremeasured at the point of recent growthinitiation.Damage counts included the frequencyof browsing on the past season's growthand, as such, occasionally resulted in asingle twig having been browsed morethan once. For this analysis, theoccurrence of 1 browsed twig was used toclassify trees as browsed.RESULTSAssessment StudyAnalysis of the variation in the 3sampling methods used was derived fromsignificance values, coefficients ofdetermination, coefficients of varia-tion, mean square error and the sum ofthe squared residuals. The analysis ofsummer damage data resulted in theselection of the 10% sample assessmentmethods as the most accurate of thethree methods tested (Table 2). The 10%method had the largest F value andhighest degree of association with theactual damage values. In addition, the10% method had the lowest coefficient ofvariation as well as the least amount ofvariation about the predicted line(Fig. 1). Finally, the equation forderiving deer damage rates from 10%samples of fruit trees damaged in summerwas generated with a 90% predictioninterval.The fall damage assessment analysisfound the sampling methods increased insignificance and prediction accuracywith increased sampling rates (Table3). Despite this trend, the relativegains in accuracy from the 20% samplingmethod over the 10% sampling method wereconsidered to be less than the value ofthe labor needed to sample the addition-al trees. In fact, the analysis ofvariation and accuracy found very slightdifferences between the 10% and 20%methods. The prediction equation and90% interval were developed (Fig. 2) andwere similar to the summer predictionrelationship.Growth StudyAnalysis of variance (Table 4)indicated significant differences(p < 0.0001) existed in almost allgrowth parameters when compared betweenorchards. This was likely a result ofage and varietal differences, varyingmanagement practices and site quality.When browsed and unbrowsed trees werecompared, significant differences(p < 0.02) existed for tree basaldiameter in both years (Table 4). Basaldiameter, which has been traditionallyconsidered a good indicator of treevigor, was considerably less variablethan other tree growth parameters.Central leader diameter was notablydifferent (p < 0.06) between browsed andunbrowsed trees during both sample years(Table 4). Trends for average limbdiameter measurements were that browsedtrees had greater diameters thanunbrowsed trees. This latter resultcould be evidence of growth stimulatedby deer browsing. Field observationssuggested that browsing appeared toresult in more net annual limb growthdue to the release of laterals and thecontinuation of terminal growth at atime when unbrowsed twigs appeared to behardening off .DISCUSSIONBased on this study, a 10% systematicsampling of fruit trees would result ina predicted damage rate with acceptableaccuracy. Surprisingly, the predictioninterval was not wider at low damagelevels and narrower at high damagelevels, as might be expected by samplingtheory.The significant differences encoun-tered between browsed and unbrowsed. 1-and 2-year-old fruit trees were unexpec-ted, in view of the lack of differencesreported by Harder (1970). As manytrees were not judged to be severelybrowsed, the fact that overall treevigor differed across all browsed treessuggests that the impact of deerbrowsing over the first years of treedevelopment were subtle yet important.Since browsing can occur at irregularintervals during summer and winter of217E = E VALUE) ^1O24DICTION INTERVALCOLU. .JOoo<010% SAMPILE DAMAGE VALUEl o Tto<E irelafc&romQhip ibettjGGin oanpl® atad oe t taa l ocanaerv a l a e o 2©ir 12 ffjrtmAtt ©sretoairda aooeasod Aim Jaimt3Qiry0 11>85o218Table 3o Fallcorailucted in 12assessment ccaparisons based on deer danage surveysorchard blocks during January 1985=F VALUECOEFFXCXEPJT OF MEAN SQUARE SUM OF SQUAREDRESIDUALS5%102201180 o350,,360 o402155,,95.9719 = 8814.45u 2 56.804-954o88 237o88R e s u l t s of a n a l y s i s of vairiatEc® for 10 girrowth paraae te i rs c o l l e c t e d210 young f r u i t fcireess duirimg the f a l l of 1982 andBEfKTEEM ORCHARDSF-TOLUE FKO®>IF F-VALUEAverage l iobgrowth—1902Average lirab125ol9,0001,00010«17 ,6785,1738Basaldliane t e r — 1 S>®2 = 0001 O0282€sirstr£il leadergrowth—19©2leaderdiameter—1Average linhliotoIlo362o260o2913o39,1072,7482=00010o020=04(Esmttral leader,0237,01261 = 16 ,2830,0596219y jaE VALUE = .90CSAMPLE DAMAGE VALUE)—.15IEsr <s 2o Tihe s r e l s t i o n o l h i i p fee flit? Gem o a o p l eff©E" 12 ffirooiit ©irelbQirdSlo QOOGOOGHII iona c t w i a l220ffcilble 5= Stur^ afliry oforchardper acre costs of the first five years of appleCOSTCUMULATIVE REPLACMEM"COST COS'TSite preparationYear 1Year 2Year 3Year kYear 5 3$745$1554.S733$875$1059$1029$2299$3032$3096$4965$6174.$15o00$20.©0$25=00S32.0O$4>0o00opportunity eosLon 155 trees/acreoEncluden incrae lost ftrca fruit tevrest.each year and then in an irregularpattern over the first years of develop-ment, the relationship between deerdamage and delayed tree maturity orreduced yields may be nearly impossibleto establish. Katsma and Rusch (1979),in their evaluation of deer damage inmature orchards, felt that the possibil-ity of predicting production lossresulting from deer browsing wasremote. For immature trees, rapidgrowth, recurring damage, and the natureof pruning practices often tend toobscure the long-term effects of deerbrowsing.The preceding discussion wouldsuggest that precise quantificationof browsing may accurately reflect deeractivity in orchards, yet may not revealthe level of tree vigor and subsequentgrowth and development of trees suffer-ing damage. In the course of severalrepellent, fencing and damage assessmentstudies in Southeastern New York, theauthors have concluded that farmers seemto be assessing the impact of deerdamage in terms of tree establishment(good vigor and terminal growth in year1) , development of tree structure (goodterminal and scaffold limb growth inyears 2 and 3) and maturity (full treeshape and initiation of production inyears A and 5). The impact of deerdamage under these changing and somewhatambiguous criteria of assessment furtherobscures the possibility of measuringthe benefits of damage control programs.An additional concern of farmers hasbeen the assessment of loss on individu-al trees as opposed to those lost on aper-acro basis. Although the total costof replacing trees can be substantial,particularly as trees increase in age(Table 5), nearly all orchards aremanaged on a per-acre basis (Gerling,1981) . Compensation for losses based onreplacement costs in years 1 and 2 maybe useful, but beyond years 2 or 3,farmers are reluctant to replantindividual trees within blocks of oldertrees. Even aged orchards have beeneasier and less costly to manage thaninterplanted orchards (Forshey. 1976).Assessment techniques that result indamage estimates on a per-acre basisallow for more direct comparisons ofdamage with the costs of various damagecontrol measures. In the absence of221Prof if (Do l l a r s )(0 68©B f?R ©Wr?eOooooooooooooooooooboo"ooo"booCD"boo_—"ooo"oooU l~boo~^-^j"oooCDoooro"o8roooorororofflp)eS3%M<=»0>=)oMV©0aae0e(=*©P?©1=4=r?B(=?p)(Dfgp)oU 'ODS 5roroOr i I r i i r i i i r r i i i r i r i r 1 Iooocrc<s>•oao03ooo-cinaoprecise loss estimates (or benefitproject ions) . farmers might be advisedto assess the extent of damage acrossblocks, judge economic r i sk fromexperience, and evaluate the cost ofdamage control measures against poten-t i a l re turns . Using projections ofpotential accumulated profi t per acre(Gerling, 1981), farmers could, forexample, see that a reduction in yieldof only 200 bushels on 1 acre of treescould resul t in $10,000 in loss over the20-year period (Fig. 3) . Thus, if thedamage per acre was considered a highrisk to potential gains, the re la t ivecosts per acre of control measures couldbe considered against potential accumu-lated p rof i t s .Finally, implementation of damagecontrol measures should be based ondol lars spent to protect future gainsrather than on dol lars jus t i f i ed bylosses incurred. For nearly a l l othercrop damages suffered by farmers,control measures are invoked beforelosses occur or are subs tan t ia l , andgenerally are implemented based on theresu l t s of a monitoring e f fo r t .Hopefully, deer damage will someday becontrolled by action rather thanreact ion.. 1970. Evaluating winterdeer use of orchards in western Colo-rado. Trans. N. Amor. Wildl. Conf. 35-35-47.Katsma. D.E. and D.H. Rusch. 1979.Evaluation of deer damage in matureapple orchards. Pages 123-142 InJ.R. Beck, ed. Vertebrate pest controland management mater ia ls . Amer . Soc.Test. Materials. ASTM STP 680.Morse, M. and D. Ledin. 1959. Deer,apples and exploders. Conserv. Volun-teer 21(121):29-31,LITERATURE CITEDBerry. R.N. 1948. Orchards versusdeer. Am. Fruit Grower 68(11):13, 18,26.Forshey, C.G. 1976. The planting andearly care of the apple orchard.Informational Bulletin 65. CornellUniversity, Ithaca, NY.Gerling, W.D. 1981. An analysis ofapple orchard replanting costs andpotential p ro f i t ab i l i t y . A.E. Ext.81-26. 39 pp. Cornell University,Ithaca, NY.Harder, J.D. 1968. A l i t e r a t u r e reviewon orchard damage by deer. Colo. Dept.Game, Fish and Parks Spec. Rep. 12. 22pp.223

Evaluations of systematic damage assessments of 5, 10 and 20 percent of all apple trees in 12 orchards were compared. The 10% assessment technique was selected as the most accurate and efficient in estimating summer and fall damage. Analysis of several parameters of tree vigor found significant differences between browsed and unbrowsed trees for tree basal diameter and central leader diameter over 2 successive years. These subtle yet important differences in tree development were felt to severely limit the possibilities of relating browsing to growth and later, yields. Methods and considerations for making control decisions on a per acre basis are discussed

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ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDS by Jay B. McAninch, Hark R. Ell i ngwood.* Michael J . Forgione and Peter Picone•• Institute of Ecosystem Studi~s. The New York Botanical Garden Millbrook. Ne w York 12545 ABSTRACT Evaluations of systematic dnmage assessments of 5 , 10 and 20 percent of all apple trees in 12 orchards were compared. The 10% assessm ent techni~ue was selected as the most accurate and efficient in estimating summer and fall damage. Analysis of several parameters of tree vigor found significant differ-ences between browsed and unbrowsed trees for tree basal diameter and central leader diameter over 2 succes-sive years. These subtle yet important differences in tree development were felt to severely limit the possibilities of relating browsing to growth and . later, yields. Methods and considera-tions for making control decisions on a per acre basis are discussed. INTRODUCTION Assessing and controlling deer damage in apple orchards has been a topic of concern for many years (Berry, 1948; Horse and Ledin. 1958 · Harder. 1968; Katsma and Rusch, 1979). Assessments of the extent and severity of damage have been evaluated (Harder . 1970 Katsma and Rusch . 1979) and have proved difficult to both quantify and express in terms of tree maturation and yields. Although methods for assessing damage have been proposed (Berry , 1948 · Katsma and Rusch. 1979), the use of these techniques in making damage control decisions has been very limit-ed. As most control decisions are mode during the early years of tree develop-ment (Forshey, 1976) . a useful damage assessment technique and some criteria for making control decisions during the first 5 years of orchard development were considered essential to farmers. extension agents and agents for damage reimbursement programs. We acknowledge the assistance of Current addresses: *Connecticut Depart-ment of Environmental Protection. North Franklin, CT 06254 · ••Southington. CT 06489 215 Carol Dowden. Robert Mungari. Julie Morgan and Raymond Winchcombe. This project was a contribution to the program of the Institute of Ecosystem Studies, the New York Botanical Carden. Financial support was provided by the New York Department of Agriculture and Markets. METHODS Asse~~~~ _nt Study In January 1985 12 orchard blocks located in Southeastern New York were evaluated for the presence of summer and fall deer damage. Blocks contained from 251 to 692 trees and ranged in age from 1 to 4 years (Table 1). Trees were recorded as damaged if at least one browsed limb was observed . The location of each tree in each block was mapped for later use in deriving simulated assessment data . Actual damage ranged from 1.1% to 89.7% for the summer and from 0.2% to 77 .07. in the fall. Using the mapped tree data for each block, systematic assessments of 5 . 10 and 20 percent of the total number of trees in each block were generated. Assessments were summed and compared to actual damage rates. Finally . equations for estimating damage rates from sample data were generated with 90% prediction intervals. Growth Study A stratified sample of 210 semi-dwarf apple trees, ranging in age from l to 2 years and consisting of 3 varieties was selected and tagged in Southeastern New York orchards. Tree growth parameters were evaluated during the fall of 1982 and 1983. Damage assessments were conducted after leaf fall and during March of both years. Data collected from each tree included basal diameter. limb diameter . and the percent of at least 1 browsed twig. In addition, the annual growth increment of the central leader and 3 systematically selected limbs were taken from each tree. Basal Table 1. A description of 12 young orchard blocu eTaluated for deer d1111age•i.n January 1985. ORCHARD AGE NUlrBEX OF ACTUAL DAIIACE (100%) BLOC]{ (yrs) TREES SI.DIMlll FALL A 4 335 63.9 60.0 B 4 251 53.0 32.3 C 3 334 5.1 1.8 D 3 350 35.4 9.1 E 3 369 89.7 74.0 F 2 479 65.8 77.0 G 2 506 50.4 1.2 H 2 284 67.3 52.8 I 2 357 11.2 50.7 J 1 462 54.5 0.2 ~ l 362 ·1.1 30.7 L 1 692 18.1 21.0 Table 2. S.-er d1111age asses-ent coaparisons based on deer d1111age aurTeya conducted in 12 young orchard block.s during January 1985. SAIIPLE RATE F VAUJE COEFFICIENT OF VARIATION IIEAN S~ARE DUlOR Slnf OF ~ARED RESIDUALS 5% 10% 20% 242.22 312.31 180.72 .96 .97 .95 13.83 12.23 15.90 diameter was recorded as the average of 2 measurements taken 10 cm above the ground surface. When the scion graft was above the 10 cm height . basal diameter was taken at 15 to 20 cm above the graft, depending on scar swelling of 216 the bole. 5.94 5.25 6.83 352.72 270.01 466.45 Limbs, defined as stems 10 ems or more in length and attached directly to the tree bole. were systematically selected by starting with the bottom limb, and counting upward, selecting limbs 1, 3 and 5 for measurement. Limb diameters were measured approximately 2 cm from bole attachment. The growth increment of each selected limb was the length for all the most recent summer growth on all twigs (excludin g spurs). Leader diameter and leader length were measured at the point of recen t growth i nitiation. Damage count s included the frequency of browsing on the past season's growth and, as such, occasionally resulted in a single twig hav i ng been browsed more than once. For this analysis. the occurrence of 1 browsed twig was used to classify trees as browsed. RESULTS Assessment Study Analysis of the variation in the 3 sampling methods used was derived from significance values. coefficients of determination, coefficients of varia-tion. mean square error and the swn of the squared residuals. The analysis of summer damage data resulted in the selection of the 10% sample assessment methods as the most accurate of the three methods tested (Table 2). The 10% method had the largest F value and highest degree of association with the actual damage values. In addition. the 107. method had the lowest coefficient of variation as well as the least amount of variation about the predicted line (Fig. 1). Finally. the equation for deriving deer damage rates from 10% samples of fruit trees damaged in summer was generated with a 90% prediction interval. The fall damage assessment analysis found the sampling methods increased in significance and prediction accuracy with increased sampling rates (Table 3). Despite this trend, the relative gains in accuracy from the 207. sampling method over the 10% sampling method were considered to be less than the value of the labor needed to sample the addition-al trees. In fact, the analysis of variation and accuracy found very slight differences between the 10% and 20% methods. The prediction equation and 907. interval were developed (Fig. 2) and were similar to the summer prediction 217 relationship. Growth Study Analysis of variance (Table 4) indicated significant differences (p < 0.0001) existed in almost all growth . parameters whe n compared between orchards . This was likely a result of age and varietal differences, varying management practices and site quality. When browsed and unbrowsed trees were compared , significant differences (p < 0.02) existed for tree basal diameter in both years (Table 4). Bas~l diameter, which has been traditionally considered a good indicator of tree vigor, was considerably less variable than other tree growth parameters. Central leader diameter was notably different (p < 0.06) between browsed amd unbrowsed trees during both sample year.s (Table 4). Trends for average limb diameter measurements were that browse d trees had greater diameters than unbrowsed trees. This latter result could be evidence of growth stimulated by deer browsing. Field observations suggested that browsing appeared to result in more net annual limb growth due to the release of lateral s and the continuation of terminal growth at a time when unbrowsed twigs appeared to be hardening off. DISCUSSION Based on this study, a 10% systemat .i c sampling of fruit trees would result i ,, a predicted damage rate with acceptabl e accuracy. Surprisingly. the prediction , interval was not wider at low damage levels and narrower at high damage levels, as might be expected by sampli n g theory. The significant differences encoun-tered between browsed and unbrowsed. l-and . 2-year-old fruit trees were unexpeic-ted , in view of the lack of differences reported by Harder (1970). As many trees were not judged to be severely browsed, the fact that overall tree vigor differed across all browsed tree ·s suggests that the impact of deer browsing over the first years of tree development were subtle yet important. Since browsing can occur at irregular intervals during summer and winter of DAMAGE VALUE =.92(SAMPLE DAMAGE VALUE)+ 1.24 100 DAMAGE ± 8.64 = 90% PREDICTION INTERVAL / VALUE 90 80 -;#?. ...... 70 6 /. 1/ / 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 10% SAMPLE DAMAGE VALUES (%) Figure 1. The relationahip between aa■ple and actual aua■er da■age Tal■e• for 12 fruit orchard• •••e•••d in Jan■ar7. 1985. 218 Table 3. Fall daaage asses .. ent coaparisons based on deer daaage sur-Yeys conducted in 12 young orchard blocks during January 1985. SAMPLE RATE 5% 10% 20% F VALUE 180.40 350.21 360.55 .95 .97 .97 COEFFICIENT OF VARIATION 19.88 14.45 14.25 MF.AN S~ARE ERR~ 6.80 4.95 4.88 SUM OF SQUARED RF.SIDUALS 462.96 244. 71 237.88 Table 4. Results of analysis of Yariance for 10 ~rowth paraaeters collected froa appro.xiaately 210 young fruit trees during the fall of 1982 and 1983. BE'JVEEN ORCHARDS BROWSED/URBROWSED GROIITH PARAIIETER F-YALUE PROB>F F-YALUE PROB>F Average Ii.ab growth--1982 64.29 .0001 0.17 .6785 Average Ii.ab di-eter-1982 125.19 .0001 1.86 . 1738 Basal di-eter-1982 164. 74 .0001 4.89 .0282 Ce'!ntral leader growth--1982 11.36 .00()1 0.63 .4270 Central leader dialleter-1982 2.26 .1072 3.41 .0664 Average l:iab growth--1983 0.29 .7482 0.02 .8956 Average 1:iab di.aaeter-1983 13.39 .0001 0.04 .8478 Ba■al dialleter-1983 70.98 .0001 5.16 .0242 Central leader growth--1983 3.81 .0237 1.16 .2830 Central leader diaaeter-1983 4.47 .0126 3.59 .0596 219 100 90 80 ,..., -eP. ""' 70 en w ::) ..J 60 < > w C, 50 < ::E < 0 40 ..J < ::) f- 30 (.) < 20 10 0 DAMAGE VALUE = .90(SAMPLE DAMAGE VALUE)-.15 DAV~~~~ ± 8.14 = 90% PREDICTION INTERVAL / 10 20 30 40 50 60 70 80 90 100 10% SAMPLE DAMAGE VALUES(%) Figure 2. The relationahip between ••■ ple and actual autu■n da■ age ••l•e• for 12 fruit orchard• aaaeaaed in ~anuary. 1985. 220 Table 5. S.-nry of annual per ncre costs of the first five years of apple orchard establisment. MANA<f FJIENT CUlfUI.A TIVE REP~CDIF:.NT COST COST cos Site preparation $745 Year 1 $1554 $2299 $15.00 Year 2 S733 S3032 S20.00 Year 3 $875 $3096 $25.00 Tear 43 $1059 $4965 $32.00 Year 53 $1029 $6174 $40.00 1 2Includes opportunity cost. ;1l9•ed on 155 trees/acre. Excluden incoae lost froa fruit havrest. Adapted froa Gerling, 1981. each year and then in an irregulRr pattern over the first years of develop-ment, the relationship between deer damage and delayed tree maturity or reduced yields may be nearly impossible to establish. Katsma and Rusch ( 1979). in their evaluation of deer damage in mature orchards, felt that the possibil-ity of predicting production loss resulting from deer browsing was remote. For immature trees, rapid growth, recurring damage. and the nature of pruning practices often tend to obscure the long-term effects of deer browsing. The preceding discussion would suggest that precise quantification of browsing may accurately reflect deer activity in orchards, yet may not reveal the level of tree vigor and subsequent growth and development of trees suffer-ing damage. In the course of several repellent, fencing and damage assessment studies in Southeastern New York. the authors have concluded that farmers seem to be assessing the impact of deer damage in terms of tree establishment (good vigor and terminal growth in year 1), development of tree structure (good 221 terminnl and scaffold limb growth in yeqrs 2 and 3) and maturity (full tree shape ond initiation of production in years 4 and 5). The impact of deer damage under these changing and somewhat ambiguous criteria of assessment further obscures the possibility of measuring the benefits of damage control programs. An additional concern of farmers has been the assessment of loss on individu-al trees as opposed to those lost on a per-acre basis. Although the total cost of replacing trees can be substantial. particularly as trees increase in age (Table 5), nearly all orchards are managed on a per-acre basis (Gerling, 1981). Compensation for losses based on replacement costs in years 1 and?. may be useful. but beyond years 2 or 3, farmers are reluctant to replant individual trees within blocks of older trees. Even aged orchards have been easier and less costly to manage than interplanted orchards (Forshey. 1976). Assessment techniquPs that result in damage estimates on a per-acre basis allow for more direct comparisons of damage with the costs of various damage control measures. In the absence of 1/'1 ... 0 0 0 ... .... 0 ... a.. "O (1) E ::, E :, u u <l 23,000 21,000 19,000 17,000 15,000 13,000 I 1,000 9,000 7,000 5,000 3,000 1,000 1000 bushels per ocre , I I I I I I I I I I I I I I I I I I ~/ I I I I I I I I I / :'5' 800 bushels per acre ------------- ---- 4-- --- -:---- - - ----- 1,000 3,000 - 5,000 - 7,000 - 9,000 0 2 4 6 8 I I I I I I / I I 10 Voor _,,/ /40 bushelS oe, oc,e 12 14 If, 18 20 Figure J. Potential accu■ulated profit at three different ■ature yield le•ela at $4.50 per buahel (Cerling,1981). 222 precise loss estimates (or benefit projections). farmers might be advised to assess the extent of damage across blocks, judge economic risk from experience, and evaluat ~ the cost of damage control measures against poten-tial returns. Using projections of potential accumulated profit per acre (Gerling, 1981), farmers could, for example, see that a reduction in yield of only 200 bushels on l acre of trees could result in $10,000 in loss over the 20-year period (Fig. 3). Thus, if the damage per acre was considered a high risk to potential gains, the relative costs per acre of control measures could be considered against potential accumu-lated profits. Finally, implementation of damage control measures should be based on dollars spent to protect future gains rather than on dollars justified by losses incurred, For nearly all other crop damages suffered by farmers, control measures are invoked before losses occur or are substantial. and generally are implemented based on the results of a monitoring effort. Hopefully, deer damage will someday be controlled by action rather than reaction. LITERATURE CITED Berry. R.N. 1948. Orchards versus deer. Am. Fruit Grower 68(11):13, 18, 26. Forshey, C.G. 1976. The planting and early care of the apple orchard. Informational Bulletin 65. Cornell University, Ithaca. NY. Gerling, W.D. 1981. An analysis of apple orchard replanting costs and potential profitability. A.E. Ext. 81-26. 39 pp. Cornell University, Ithaca, NY. Harder, J.D. 1968. on orchard damage by Game, Fish and Parks pp. A literature review deer. Colo. Dept. Spec. Rep. 12. 22 223 1970. EvRl UR t i.ng winter ~eer use of orchards in western Colo-rado. Trans. N. Amer . Wildl . Conf. 35 · 35- 4 7. Katsma, D.E. and D.11. Rusch . 1979. Evaluation of deer dama8 e in mature apple orchards. Pages 123-142 In J.R. Beck, ed. Vertebrate pestc -ontrol and management materials. Amer . Soc. Test. Materials. ASTH STP 680. Horse, M. and D. Ledin. apples and exploders. teer 21(121):29-31. 1959. Deer. Conserv. Volun-

Assessing Deer Damage in Young Fruit Orchards

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ASSESSING DEER DAMAGE IN YOUNG FRUIT ORCHARDS

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