PROXIMATE FACTORS LIMITING POPULATION GROWTH
OF WHITE-TAILED DEER IN NOVA SCOTIA
BRENT R. PATTERSON, 1, 2 Department of Natural Resources, Wildlife Division, 136 Exhibition Street, Kentville, NS B4N 4E5,
Canada
BRUCE A. MACDONALD, 3 Center for Wildlife and Conservation Biology, Department of Biology, Acadia University, Wolfville, NS
B0P 1X0, Canada
BEVAN A. LOCK,4 Center for Wildlife and Conservation Biology, Department of Biology, Acadia University, Wolfville, NS B0P 1X0,
Canada
DON G. ANDERSON, Department of Natural Resources, Whycocomagh, NS B0E 3M0, Canada
LAWRENCE K. BENJAMIN, Department of Natural Resources, Wildlife Division, 136 Exhibition Street, Kentville, NS B4N 4E5,
Canada
Abstract: White-tailed deer (Odocoileus virginianus) densities in Nova Scotia, Canada, declined during the late 1980s
and early 1990s. We estimated population change, survival, and relative importance of mortality factors for deer in
2 geographic areas of Nova Scotia from February 1994 to January 1999. Pellet-group surveys indicated that deer
densities in both study areas increased slowly (λ ~ 1.07 and 1.05 in the Queens County and Cape Breton study areas,
respectively) during the study. Annual survival rates of adult deer did not differ among years or between the study
areas. Annual survival rates for adult females averaged 93.9 ± 4.3% (SE) and 80.4 ± 3.1% within and outside of
Kejimkujik National Park, respectively, where harvest did not occur. Annual survival rates of adult males and fawns
outside of the park, where hunting occurred, were 50.7 ± 7.6% and 36.9 ± 7.4%, respectively. No marked adult
males or fawns died within the park during the study (winter only for fawns). Annually, hunting (34.2 ± 8.2% and
8.2 ± 2.4% for adult males and females, respectively) and predation (7.2 ± 5.3% and 7.5 ± 2.3% for adult males and
females, respectively) were the largest mortality factors for adult deer. Coyote (Canis latrans) predation (27.5 ± 8.7%
during Dec–May only) was most influential for fawns. Monte Carlo simulations involving a model of adult survival
and fawn recruitment supported the results of the deer pellet-group inventories and suggested low but positive
rates of increase for both populations. Although predation and the unregistered harvest of adult females probably
slowed the growth of deer populations following the decline, the recent establishment of a zone-based antlerless
harvest quota system should allow managers to regulate deer numbers by annually adjusting the number of antlerless permits in response to estimates of hunting and nonhunting losses.
JOURNAL OF WILDLIFE MANAGEMENT 66(2):511–521
Key words: Canis latrans, coyote predation, hunting, illegal harvest, Monte Carlo simulation, Nova Scotia, Odocoileus
virginianus, population limitation, white-tailed deer.
By definition, all mortality sources must limit
population growth somewhat, and thus can be
considered limiting factors. However, only those
limiting factors whose magnitude increases with
deer density can promote stabilization of deer
abundance (i.e., act as a regulating factor). Most
studies of white-tailed deer survival have concluded that hunting is the major cause of mortality in
exploited populations (Nelson and Mech 1986a,
Fuller 1990, Dusek et al. 1992, Van Deelen et al.
1997). As such, hunting is the mortality source targeted most often in deer management plans. Typically, agencies increase the number of available
antlerless deer permits as deer densities increase.
In this sense, harvest can be density dependent
and can potentially regulate deer numbers
(Fuller 1990, Patterson and Power 2002).
Predation can be a major source of mortality
for deer along the northern extent of their geographic range in North America (Nelson and
Mech 1986a, Poulle et al. 1993, Whitlaw et al.
Eastern Canada is the northeastern extent of
the geographic range of white-tailed deer in
North America. Deer densities in this area are
lower than those throughout more southern
areas (Halls 1984, Crête 1999). Across North
America, potential rates of increase of deer populations are limited by reproductive rates and fawn
survival (McCullough 1979, Fuller 1990); however, the relative roles of various factors limiting
deer at low densities along the northern extent of
their geographic range are less clear.
1 Present address: Ontario Ministry of Natural
Resources, Wildlife Research and Development Section, 300 Water Street, Third Floor North, P.O. Box
7000, Peterborough, ON K9J 8M5, Canada.
2 E-mail: [email protected]
3 Present address: Ducks Unlimited Canada, 5017-52
Street, Yellowknife, NT X1A 1T5, Canada.
4 Present address: Stora Enso Port Hawkesbury Ltd.,
Box 59, Port Hawkesbury, NS B0E 2V0, Canada.
511
512
J. Wildl. Manage. 66(2):2002
LIMITING FACTORS FOR DEER • Patterson et al.
1998). Crête (1999) suggested that where wolves
are present, cervid densities in northeastern
North America generally are limited by predation
at a density below that at which food competition
becomes significant. The proportion of deer
removed by coyotes in Nova Scotia decreased with
increasing deer densities; thus, coyote predation
is likely to destabilize, rather than regulate, deer
densities (Patterson 1999). The abundance of
most northern deer populations is likely regulated to some extent by forage competition (Fryxell
et al. 1991, Messier 1991, Post and Stenseth 1998,
Dumont et al. 2000, Patterson and Power 2002).
However, because of a time lag between deer
density and the resulting depression of deer population growth, this regulation may result in
marked fluctuations in abundance. Although
deer population growth may be limited directly
by winter malnutrition losses (Potvin et al. 1981,
Case and McCullough 1987), winter weather cannot directly regulate ungulate populations
because it is density independent (Sinclair 1989).
In Nova Scotia, and in many other regions in
northeastern North America, a series of mild winters during the late 1970s and early 1980s seems
to have facilitated a rapid increase in densities of
white-tailed deer (Patton 1991, Parker 1995; Fig. 1).
Despite an effort to limit this increase via liberal
hunting regulations, deer in Nova Scotia had presumably exceeded K carrying capacity (sensu
McCullough 1979) and were in poor physical condition by winter of 1987 (Patton 1991, Patterson
and Power 2002). The 1987 winter was relatively
severe in Nova Scotia, and a substantial decline in
deer density began (Patton 1991; Fig. 1). By 1993,
deer densities in Nova Scotia were at their lowest
level in over 50 years (Nova Scotia Department of
Natural Resources [NSDNR], unpublished data).
Coyotes were still becoming established throughout Nova Scotia when the decline began during
1987 (Moore and Parker 1992, Patterson 1999).
Coyote predation was unable to prevent the peak
in deer density, although it probably accelerated
the subsequent decline (Patton 1991, Parker
1995, Patterson 1999). During 1993, hunting was
restricted to antlered (males >1 yr) deer throughout Nova Scotia. Despite legal protection of
antlerless deer and mild winter conditions from
1994 through 1998 (MacDonald 1996, Patterson
et al. 1998), deer densities did not increase
noticeably until 1997 (Fig. 1). Our study attempted to identify and quantify major factors limiting
the population growth of deer in Nova Scotia following a major decline in density.
STUDY AREA
Our study was conducted in 2 forested areas of
Nova Scotia, Canada. The Queens County study
area in central southwestern Nova Scotia (44°20′N,
65°15′W) included the eastern half of Kejimkujik
National Park (KNP; approx. 200 km 2) and
approximately 300 km2 of primarily forested land
directly to the east of the park. This region had
warm summers averaging 18 °C and cool winters
averaging –5 °C during January (Dzikowski et al.
1984). Queens County received little snow during
the study with accumulations generally <20 cm;
thus, deer did not aggregate in yards (MacDonald 1996, Lock 1997).
The second area, on Cape Breton Island
(45°45′N, 61°15′W, approx. 300 km2), was centered on the 24-km2 Eden deer wintering area that
typically contained approximately 200 deer from
January through March (Patterson et al. 1998).
Elevation rose from near sea level in the River
Denys Basin area to approximately 300 m in the
Creignish Mountains. The climate in Cape Breton
generally is more moist than KNP, with similar
summer temperatures as the Queens County study
area (Dzikowski et al. 1984). High elevations in the
northern section of the study area typically receive
250–300 cm of snow annually, whereas lowland
areas receive 200–250 cm of snow annually (Gates
1975). Median duration of snow cover varies from
140 days on higher elevations to 130 days on lower
elevations (Gates 1975). This contrasts with a
median duration of snow cover of 59 days in
Queens County. Information on the vegetation in
each study area was presented by Patterson et al.
(1998). Deer were legally protected from harvest
in KNP, whereas hunting was restricted to antlered
deer in all other areas during autumn 1993–1997.
Limited numbers of antlerless deer permits were
available in both study areas during autumn 1998.
METHODS
We captured deer in both study areas using box
traps, a ground-based rocket net, chemical immobilization, and a net-gun deployed from a Hughes
500 helicopter (MacDonald 1996). We fit deer
with VHF radiocollars containing mortality
switches (Lotek Engineering, Newmarket,
Ontario, Canada). We located collared deer primarily from the ground with hand-held antennas
and portable receivers. We checked for mortality
signals approximately twice a week from 1 April
to 15 October, and 4 times/week during the rest
of the year. We investigated mortality signals and
determined cause of death within 24 hr of dis-
J. Wildl. Manage. 66(2):2002
covery. We classified deer as a predator kill if
there was positive evidence of attack or chase (i.e.,
blood-soaked fur or snow, bleeding observed
around tooth puncture wounds). Predator species
involved in mortalities were identified on the basis
of tracks, bite marks, or hair or scat left by the
predator. We assumed that a deer died of malnutrition when the carcass was lying intact in a natural position with low femur marrow fat content
(Cheatum 1949, Verme and Holland 1973). We
monitored deer until 22 January 1998 in Queens
County, and 14 January 1999 in Cape Breton.
We estimated weekly survival (si ) from 1 June
(the assumed date of birth of the new fawn crop)
through 31 May the following year using the
Kaplan-Meier product-limit estimator modified
by Pollock et al. (1989) to allow the staggered
entry of animals. For each weekly estimate, we
included only deer with collars that had been
transmitting signals for >4 days. We calculated
annual survival estimates (Sann) as the product of
the 52 weekly estimates. We estimated the variance of survival estimates at time t as var(st ) = sˆt 2
[1 – (st )]/xt , where xt was the total number of
collared deer at risk at time t (Cox and Oakes
1984). Our analyses included the exposure days
of censored individuals until the date of disappearance or the end of monitoring because this
method results in the least biased survival estimates over a wide range of censoring and survival
probabilities (Tsai et al. 1999).
We estimated annual survival for adult (>1 yr)
females, adult males, and fawns. Sufficient telemetry data to estimate survival of fawns was available
only from December to May. We estimated survival
of fawns during June–November by comparing
natality rates of road-killed does examined in each
study area from 1 February through 15 May (n =
151 for Queens County, 131 for Cape Breton) with
the fawn:doe ratios observed in the road-killed
sample from each study area during the following
December and January (n = 126 for Queens County, 67 for Cape Breton). Early winter fawn:doe
ratios were adjusted to account for mortality of
adult females occurring during the summer and
autumn intervals (Nelson and Mech 1986a).
We tested for interannual differences in survival
for each age and sex class using generalized chisquare tests calculated by program CONTRAST
(Hines and Sauer 1989, Sauer and Williams 1989).
We pooled data from all years of study when the
statistical hypothesis of homogeneity among
annual survival rates was not rejected. For paired
comparisons between study areas, sexes, and age
LIMITING FACTORS FOR DEER • Patterson et al.
513
(fawns vs. adults only) we used log-rank tests
(Cox and Oakes 1984, Pollock et al. 1989) to test
the statistical hypothesis that both survival curves
came from the same true underlying survival function. We used CONTRAST for all comparisons
involving >2 rates to reduce the probability of a
Type I statistical error. Based on a visual examination of survival curves, we divided the biological year into 3 intervals with relatively constant
survival for adult deer: 1 June–12 October, 13
October–7 December (included the bow and
firearm hunting seasons), 8 December–31 May.
In the Queens County study area, we estimated
separate survival rates for deer living within KNP
because hunting was prohibited in the park.
Cause-specific mortality was defined as the
probability of a deer dying during a given interval
from a given mortality factor. We estimated mortality rates resulting from (1) predation; (2) legal
harvest (registered by licensed hunters or reported by aboriginal people); (3) unregistered harvest (including deer that were known or suspected to have been illegally harvested, abandoned,
or lost [wounding loss] or legally harvested but
not reported by aboriginal people); (4) malnutrition; and (5) other natural causes (old age, natural accidents, or injuries). The probability of a
deer dying from any given mortality source during each week, interval, and annually was calculated following Heisey and Fuller (1985). Mortality rates estimated in this manner can be seriously
biased if the assumption of a constant probability
of succumbing to each mortality factor for the
duration of each interval is violated (Pollock et
al. 1989, Tsai et al. 1999). We minimized this bias
by delineating seasonal intervals only after examining the annual survival curves and the seasonal
contributions of each mortality factor. Variance
of mortality estimates was calculated using the
Taylor series approximation method ( Johnson
1979, Heisey 1985).
We determined the relative abundance of whitetailed deer within each study area using pelletgroup counts conducted along 30 1,000 × 2-m systematic line transects during April and May
1994–1997 (Neff 1968, Patterson et al. 1998). During 1998 and 1999, we estimated deer densities in
each study area based on the relative change
between 1997–1998 and 1998–1999 indicated by
the pellet-group inventories conducted in the
counties containing each study area by the NSDNR
(n = 78, 95, and 55 plots surveyed each year in
southwestern Nova Scotia; and 64, 64, and 65
plots in Cape Breton). We converted the numbers
514
J. Wildl. Manage. 66(2):2002
LIMITING FACTORS FOR DEER • Patterson et al.
We estimated (λ 2 ) by linear regression of
loge(N ) estimated from the annual pellet group
surveys following Eberhardt and Simmons (1992).
We recalculated λ 2 1 0 0 0 t i m e s w i t h a r a n d o m
value being drawn from a normal distribution
generated using N–± SE for each area and year
specific density estimate. For each method in each
study area, we then compared the central 95% of
the λ estimates to assess the accuracy and p r e cision of these measures of population change.
of pellet groups counted/km2 in each study area
each year into estimates of deer/km2 assuming
an average date of leaf fall of 1 November and a
daily defecation rate of 16 pellet groups/day/deer.
Our assumed defecation rate was calculated
based on an iterative process whereby we incorporated the size of harvest during each year
(from mandatory registration stations) and the
estimated rates of all significant mortality factors
(this study) into a model to determine the annual population size necessary to result in observed
rates of interannual population change. We estimated standard errors for deer density estimates
based on the variance in the number of pellet
groups counted among plots in each territory.
Using 2 methods, we estimated the finite rate of
increase (λ) for deer in each study area. We estimated λ1 as λ = (1 – Ma)/(1 – R ) where Ma was
the finite annual rate of adult mortality (calculated as 1 – Sann, weighted to account for the ratio
of adult females:males in each study area, and the
respective survival estimates for each sex) and R
was the number of fawns/100 does observed during late winter in each study area (Hatter and
Bergerud 1991). We incorporated the standard
errors of Ma (calculated from the coefficient of
variation [CV] for Sann) and R (calculated from
the interannual variation among sex and age
ratios from 1994 to 1998) into a Monte Carlo simulation to assess the variance associated with λ.
For each study area, λ was recalculated 1,000 times
with a random value being drawn from a normal
distribution calculated using x– ± SE for each
parameter during each subsequent calculation.
RESULTS
We captured and radiocollared 71 deer (>6
month) in Cape Breton and 50 in the Queens
County study area from February 1994 through
April 1997. Most deer were captured between
December and March each year. Four deer (3 in
Cape Breton, 1 in Queens County) shed their collars within 24 hours of capture. Five deer died
within 1 week of marking and were eliminated
from the analysis.
No significant differences occurred in annual
survival rates among years for adult males (χ23 <
2.4, P > 0.49), or adult females (χ23 < 1.9, P > 0.38)
in any study area. Thus, for subsequent analyses,
we pooled data among years for adults of each sex.
Survival may not have been uniform among years
for fawns in Cape Breton (χ23 = 6.0, P = 0.054), but
we also pooled these across all years because sample sizes were small (n = 6, 7, 4, 4 fawns collared
during winters 1994–1997, respectively). Annual
survival rates ranged from 46.1 ± 9.8% (SE) for
adult males in CB, to 93.9 ± 4.3% for adult females
in KNP (Table 1; Figs. 1, 2). Annual survival curves
Table 1. Seasonal survival rates of radiocollared white-tailed deer monitored in the Queens County and Cape Breton study areas,
Canada, Feb 1994–Jan 1999.
Cohort
Rate
Summer
Autumn
Winter–Spring
(1 Jun–12 Oct)
(13 Oct–7 Dec)
(8 Dec–31 May)
SE
n
Annual
No.
No.
No.
No.
radio
radio
radio
radio
weeks Rate
SE
Non-park adult
females
0.985 0.011 58 2,506 0.884 0.027
Non-park adult
males
0.923 0.059 21
523 0.662 0.074
Kejimkujik Natl
Park adult
females
0.970 0.029 12
610 1.0
Kejimkujik Natl
Park adult
males
1.0
2
95 1.0
n
weeks Rate
SE
n
weeks
Rate
SE
n
weeks
56
994
0.924 0.023 59
2,875
0.804
0.031
18
161
0.830 0.047 17
447
0.507
0.076 25 1,131
10
256
0.969 0.032
12
720
0.939
0.043
2
34
2
98
1.0
1.0
62 6,375
12 1,586
2
227
J. Wildl. Manage. 66(2):2002
LIMITING FACTORS FOR DEER • Patterson et al.
515
for adults of both sexes were not different between
deer living outside KNP in Queens County and
those in the Cape Breton study area (females: logrank test, χ2 = 0.13, P = 0.72; males: χ2 = 0.42, P =
0.84; Fig. 2). Thus, for each sex, we pooled data
from these areas for further analyses. Survival of
adult females living in KNP was higher than for
adult females outside of the park (0.939 ± 0.043 vs.
0.804 ± 0.031; log-rank test, χ2 = 6.49, P = 0.011).
No adult males died in KNP (Table 1). Outside of
the park, annual survival rates were significantly
lower for adult males than females (0.507 ± 0.076
vs. 0.804 ± 0.031; χ23 = 6.75, P = 0.009; Table 1).
Seasonal Survival Rates
No seasonal differences occurred in weekly survival rates for adult female deer living within KNP
(χ22 = 0.36, P = 0.836; Table 1). For deer living outside the park, no difference occurred in weekly
survival rates between winter and autumn for
adult females (χ21 = 1.23, P = 0.268) or between
summer and winter rates for adult males (χ21 =
0.944, P = 0.331). Weekly survival rates were highest during summer for both adult female (χ2
14.6, P = 0.0001) and male (χ22 = 6.89, P = 0.032)
deer residing outside KNP (Table 1).
Fawn survival through early winter was approximately 0.63 in Cape Breton and 0.70 in Queens
County (Table 2). Fawn survival from December
through May was 0.505 ± 0.082 and 0.60 ± 0.105 in
the Cape Breton and Queens County study areas,
respectively. Estimated annual survival rates of
fawns were 0.319 and 0.422, respectively (Table 2).
Survival among age and sex classes generally
was most uniform during summer (Table 1). During autumn, adult females living in KNP had
higher survival than females outside the park (χ21
= 9.23, P = 0.002), which in turn had higher survival than adult males also living outside of the
park (χ21 = 457, P < 0.0001). Winter survival rates
were not uniform among sex and age classes (χ22
= 4.80, P = 0.090; Table 1). Fawns had significantly lower winter survival than adult females (0.584
± 0.066 vs. 0.924 ± 0.024; χ21 = 4.80, P = 0.029), but
not males (0.830 ± 0.081; χ21 = 1.50, P = 0.219).
The difference between winter survival of adult
males and females (0.094) was not significant (χ21
= 1.24, P = 0.26; Table 1).
Fig. 1. The relative abundance of white-tailed deer in the Queens
County (QC) and Cape Breton (CB) study areas, 1994–1999, as
estimated by pellet-group counts. The inset depicts provincial
deer population trends, 1983–1999, as estimated by pellet-group
counts conducted along 440 ± 3 (SE) transect lines distributed randomly throughout the province (Patton 1991). Error bars represent
the standard error associated with each deer density estimate.
Cause-specific Mortality
We documented 46 mortalities during 112,302
animal-days of telemetry contact with deer: (1) 17
due to predation (12 coyote, 1 suspected coyote,
3 bobcat [Lynx rufus], and 1 lynx [Lynx lynx]); (2)
Fig. 2. Kaplan-Meier survival curves for (a) adult female and
(b) adult male deer in Queens County and Cape Breton, Nova
Scotia, Canada, 1994–1998.
516
J. Wildl. Manage. 66(2):2002
LIMITING FACTORS FOR DEER • Patterson et al.
Table 2. Seasonal survival of fawn white-tailed deer in the Cape Breton and Queens County study areas, Nova Scotia, Canada,
1994–1997.
Cape Breton
Parameter
Jun
Jan
Fawns:doe
1.23 0.82
Number doesa 100
87.4
Number fawnsb 123
71.8
Fawn survival
0.631 c
Dec–May
0.505d
SE
Queens County
Annual
0.082 0.319
SE
Jun
Jan
1.21 0.93
100
86.1
121
79.8
0.054 e
0.704 c
Dec–May
SE
Annual
SE
0.60d
0.105
0.422
0.074e
a Hypothetical number surviving based on a starting population of 100 and seasonal survival rates calculated from telemetry
data.
b Estimated from the natality of female deer struck by automobiles Feb–May, and the fawn:doe ratios observed Dec–Jan.
Fawn:doe ratios in winter were adjusted to account for the number of does surviving Jun–Dec.
c Estimated as the number of fawns still living in Dec divided by the number born in Jun. Our initial calculation was based on
survival through the end of Dec (214 days). The rate presented here was obtained by expanding the mean daily rate during this
interval (0.9975) through the end of Nov only (183 days; i.e., 0.631 = 0.9975183).
d Based on telemetry data.
e Based on the coefficient of variation associated with the winter survival rates only; thus, this standard error estimate is minimal.
10 due to legal (registered) harvest (including 2
females harvested by native hunters and 1 female
taken with an antlerless deer permit during 1998);
(3) 10 due to unregistered harvest (2 males, including 1 wounding loss); (4) 2 died of malnutrition (1 fawn, 1 adult female); and (5) 5 died of
other natural causes (1 female fawn fell through
ice, 1 adult male became mired in mud, 1 adult
male died of a chest infection, and 2 females died
of apparent old age or other natural causes). We
could not determine the probable cause of death
for 2 adult females during early December 1996
and 1997, respectively.
Harvest-related mortality was restricted to
autumn (Fig. 3) but represented the greatest
source of mortality for adult male deer living outside of KNP (χ2 = 9.9, P = 0.0016; Table 3). Hunting (8.2 ± 2.4%) and predation (7.6 ± 2.3) were
the most significant mortality sources for adult
female deer outside the park, and the 2 rates were
not different (χ2 = 0.032, P = 0.86; Table 3). Predation rates on adult females were similar within
and outside of the park (6.1 ± 4.2% vs. 7.6 ± 2.3%,
respectively). Coyote predation removed a proportion of adult male deer similar to the number
removed by malnutrition and other natural mortality factors (0.072 ± 0.053 vs 0.066 ± 0.026; Table
3). Predation was uncommon among adult deer
during summer and occurred at a relatively constant rate from autumn to spring for adult females
(Fig. 3A). The 2 cases of predation on adult male
deer occurred during early autumn and midwinter, respectively (Fig. 3B). Although the number
of fawns monitored each winter increased as winter progressed, the 3 cases of coyote predation on
collared fawns occurred during January and early
February. In KNP, a bobcat killed 1 adult female
during November 1996 and an unknown predator(s) killed 1 adult female during July 1996.
Population Trends
Fig. 3. Cumulative number of (a) adult female and (b) adult
male deer dying of various causes in Nova Scotia, Canada,
1994–1998.
For our models of population change based on
adult survival and recruitment, late winter sex
J. Wildl. Manage. 66(2):2002
517
LIMITING FACTORS FOR DEER • Patterson et al.
Table 3. Cause-specific mortality rates of radiocollared white-tailed deer monitored in Kejimkujik National Park (KNP), Feb
1994–Jan 1998, and in the Cape Breton and Queens County study areas combined (CB/QCNP; excluding Kejimkujik National
Park), Feb 1994–Jan 1999.
Area
CB/QCNP
CB/QCNP
CB/QCNP
KNPe
Cohort
Adult females
Predationa
Registered harvestb
Unregistered harvestc
Malnutrition
Other natural mortalityd
Unknown
Adult males
Predation
Registered harvest
Unregistered harvest
Other natural mortality
Fawns
Predation
Malnutrition
Natural mortality
Adult females
Predation
Summer
Autumn
Winter–Spring
(1 Jun–12 Oct)
(13 Oct–7 Dec)
(8 Dec–31 May)
Rate
SE
Rate
SE
Rate
SE
Rate
SE
0.008
0.007
0.016
0.023
0.061
0.011
0.013
0.021
0.061
0.022
0.075
0.022
0.060
0.006
0.014
0.016
0.023
0.013
0.021
0.007
0.010
0.011
0.072
0.266
0.076
0.066
0.053
0.081
0.054
0.051
0.061
0.042
0.037
0.039
0.030
0.016
0.011
0.288
0.040
0.085
0.043
0.035
0.009
0.029
0.007
0.008
0.002
0.002
0.0572
0.0532
0.108
0.016
0.275
0.022
0.098
0.087
0.008
0.016
0.031
0.032
Annual
a Of the 17 instances of predation observed during this study, 12 were attributed to coyotes, 1 to a suspected coyote, 3 to bobcats, and 1 to a lynx.
b Includes 2 deer taken by aboriginal hunters and 1 taken in Cape Breton in 1998 under a limited antlerless deer permit system.
c Unregistered harvest indicates deer which were known or suspected to have been illegally harvested, abandoned or lost
(wounding loss), or harvested and not reported by aboriginal people.
d Natural mortality includes deaths from malnutrition, old age, accidents, or other naturally occurring sources (excluding predation).
e We recorded no mortalities of adult males during 4.4 animal-years of monitoring in Kejimkujik National Park.
and age ratios were estimated from 105 roadkilled deer examined on Cape Breton Island and
115 in southwestern Nova Scotia, during April
and May, 1994–1998. The distributions of rates of
increase estimated by our models were similar to
those estimated by the pellet-group inventories
(Queens County, λ(pellet groups) = 1.064, range =
1.02 to 1.11, vs. λ(model) = 1.048, range = 0.82 to
1.26; Cape Breton, λ(pellet groups) = 1.023, range =
0.89 to 1.16 vs. λ(model) = 1.110, range = 0.94 to
1.29; Fig. 4). In Cape Breton, the pellet-group
inventories indicated a higher mean rate of increase than our model (Fig. 4B). Although the
overall rate of population growth was positive in
both areas during this study, pellet-group inventories suggested a decline in deer densities
between 1994 and 1995 in Cape Breton but not in
Queens County (Fig. 1). Including only pelletcount data from 1995 to 1999 in the simulation
for Cape Breton resulted in a mean rate of increase of 1.055 with a range of 0.94 to 1.19.
DISCUSSION
Despite legal protection, harvest represented a
significant mortality factor for adult female deer
during this study. In Washington, several illegally
harvested female black-tailed deer (Odocoileus
hemionus columbianus) were neither recovered
nor field-dressed, suggesting that misidentification of a legal target may have been involved
(McCorquodale 1999). In all but 1 of the cases
where we suspected an antlerless deer was illegally harvested, we recovered only the severed collar,
generally from a ditch, culvert, or roadside pond.
Regardless of the ultimate cause of these losses, a
significant proportion of antlerless deer were harvested but not reported to the NSDNR each year.
Whitlaw et al. (1998) reported that the illegal
harvest of deer in New Brunswick was rare. Rates
of illegal harvest of deer in other areas ranged
from 9 to 16% of the legal harvest for white-tailed
deer in Minnesota (Nelson and Mech 1986a, Fuller
1990) to 61% of the legal harvest for deer in the
518
LIMITING FACTORS FOR DEER • Patterson et al.
Fig. 4. Distribution of rates of increase for deer estimated by
1000 replicates of a Monte Carlo simulation based on deer
pellet group inventories (PGI), and a simple population model
using estimates of adult mortality and fawn recruitment (Hatter and Bergerud 1991), in (a) Queens County and (b) Cape
Breton, Nova Scotia, Canada, 1995–1998.
Klickitat Reserve Basin of Washington (McCorquodale 1999). The illegal harvest of antlerless deer
was considerable when no antlerless deer permits
were available. The incentive to illegally harvest
antlerless deer may decrease as provincial deer
numbers and the number of antlerless deer permits available to hunters continue to increase.
The annual survival rate for adult females
exposed to hunting (80.4 ± 3.1% ) was similar to
those of adult females from populations with
light hunting pressure in northern Minnesota,
Michigan, and northern New Brunswick (Nelson
and Mech 1986a, Van Deelen et al. 1997, Whitlaw
et al. 1998), but higher than for populations subjected to heavy hunting pressure in Montana,
northcentral Minnesota, and southern New
Brunswick (Fuller 1990, Dusek et al. 1992, Whitlaw et al. 1998). Given the low deer densities we
observed relative to many areas in northeastern
North America (Fig. 1; e.g., deCalesta and Stout
1997), mild winters (MacDonald 1996, Patterson
et al. 1998), and legal protection of antlerless
deer during this study, we suggest that the survival rates we documented for adult females are
near maximal for deer in Nova Scotia.
J. Wildl. Manage. 66(2):2002
Survival rates of adult males in this study compared to those documented in Minnesota and
New Brunswick (Nelson and Mech 1986a, Fuller
1990, Whitlaw et al. 1998), but were considerably
higher than for an intensely harvested population
in northern Michigan where the annual survival
was 0.22 (Van Deelen et al. 1997). During this study,
age-specific natality rates remained high despite
some skewing of the adult sex ratio during 5 years
of male-only hunting (NSDNR, unpublished
data). Thus, it appears that increased harvesting
pressure on adult males in Nova Scotia had little
effect on herd productivity. The fact that some
adult females were harvested each year despite
legal protection (Table 3) probably also helped
prevent excessive skewing of the adult sex ratio.
During winter, rates of predation and natural
mortality for fawns were considerably higher
than observed for older deer (Table 3). A concurrent study of coyote predation on deer suggested a more subtle difference in predation
rates of fawn and adult deer during winter (Patterson 1999, Patterson and Messier 2000). Patterson and Messier (2000) relied on tracking radiocollared coyotes to kill sites during intensive
winter snow tracking. These authors noted that
fawns were completely consumed more rapidly
than adults and acknowledged that they may
have underestimated the number of fawns killed
per coyote family group during winter. Although
the variance of our estimates of coyote predation
rates during winter was large (CV = 0.32), our
study supports this contention.
Our estimates of annual survival rates for fawns
(approx. 37%; Table 2) are similar to those for
fawns in northcentral New Brunswick (0.21–0.30;
Ballard et al. 1999) and northcentral Minnesota
(0.35; Fuller 1990). Poor fawn survival (due largely to predation in early summer) was believed to
be a major factor contributing to declines in deer
populations in both of these studies. We could
not determine the causes of summer fawn mortality, but summer fawn survival in Nova Scotia
was positively correlated with snowshoe hare
(Lepus americanus) densities (the major alternative food of coyotes during this study; Patterson et
al. 1998), suggesting that predation was a major
source of mortality for fawns (Patterson and
Power 2002). Black bears (Ursus americanus) and
bobcats also appeared to be common in both
study areas and are recognized as important limiting factors for northern deer populations
(Mathews and Porter 1988, Kunkel and Mech
1994, Ballard et al. 1999).
J. Wildl. Manage. 66(2):2002
Although legal hunting was restricted to
antlered male deer only throughout Nova Scotia
during 1993 and winters were mild during this
study, there was little increase in deer numbers
until winter 1997 (Fig. 1). Our estimates of positive
but relatively low rates of increase for deer in
both study areas, derived from our model of adult
survival and fawn recruitment, were corroborated
by annual deer pellet-group inventories (Fig. 4).
However, despite considerable effort by the staff
of the NSDNR in conducting the annual pellet
group surveys, and a relatively large sample of
both radiocollared and vehicle-struck deer for
the demographic analyses, substantial variation
occurred in both estimates of deer population
change (Fig. 4). Further, the variance associated
with the pellet-group counts represented a minimum estimate because we only considered variation in the number of pellets among plots and
not potential differences in pellet-group detectability and deposition rates. The use of pellet group
counts as an index of deer numbers has been criticized (Fuller 1991, 1992). However, pellet group
counts in Nova Scotia were closely related to
autumn harvest during 10 years of any age–any sex
hunting from 1983 to 1992 (r 2 = 0.87, P = 0.001;
Patterson et al. 1998). The annual pellet-group
counts in Nova Scotia are useful for determining
regional trends in deer population change.
There was no indication that any harvesting of
deer occurred within KNP during this study, yet
deer densities in KNP were no higher than those
in surrounding areas (Table 1; Patterson and
Messier 2000). Similarly, it may seem curious that
deer densities in Queens County were lower than
those in Cape Breton (Fig. 1; Patterson et al.
1998) despite the observation that Cape Breton
deer experienced more severe winter weather.
Compared with Cape Breton, the forests in the
Queens County study area consisted of relatively
large, mature stands of mature softwood or hardwood-dominated mixed-wood (Lock 1997). This
was particularly evident in KNP, where forest harvesting has not occurred since the early 1960s.
Deer thrive in young, heterogeneous forests
(Halls 1984, Mooty et al. 1987), and we suggest
that higher densities of deer in Cape Breton
resulted from generally more favorable habitat
conditions. The mature, relatively unbroken
forests in KNP provide relatively little browse for
deer (Drysdale 1986, Lock 1997). Following the
province-wide population boom in deer densities
during the early 1980s, deer in KNP experienced
an equal if not greater decline in densities (Drys-
LIMITING FACTORS FOR DEER • Patterson et al.
519
dale 1986, Patterson 1995). Prior to the decline,
this population was at high densities and in poor
physical condition (Drysdale 1986), suggesting that
the lack of hunting was largely compensated for
by high density-dependent winter mortality or
reductions in recruitment. Although we did not
detect significant differences in recruitment or
adult survival between Cape Breton and Queens
County, such differences may become more pronounced as each area approaches its respective K
or when winter severity is high.
MANAGEMENT IMPLICATIONS
Wolves are not present east of the Saint
Lawrence River. Some researchers have suggested that coyotes have replaced wolves as a significant predator of white-tailed deer in northeastern North America (Brundige 1993, Ballard et al.
1999). Although coyote predation was secondary
in importance to harvest as a limiting factor for
deer during this study, Patterson (1999) concluded that coyote predation could severely limit deer
population growth when deer densities were very
low (<0.5/km2) or when winter severity was high.
Similarly, Messier et al. (1986) concluded that
coyote predation could limit deer densities in
southern Québec. During our study, deer densities appeared to be well below K (Lock 1997) and
winters were quite mild. This, coupled with the
apparently good condition of most deer killed by
predators, suggests that predation losses were
largely additive. Similarly, there was no increase
in any other mortality factor when deer were protected from harvest within KNP, suggesting that
harvest mortality was also largely additive.
Fuller ( 1990 ) demonstrated that excessive
hunting is more likely to initiate or contribute to
population declines when winter severity is high.
Similarly, killing rates of deer by predators are
positively associated with winter severity (Messier
and Barrette 1985, Nelson and Mech 1986b, Patterson and Messier 2000). Following the peak in
deer densities in Nova Scotia during 1986, deer
densities began to decline sharply and winter
severity was above average during 1986–1990 and
1992–1993 (NSDNR, unpublished data). However, for political or bureaucratic reasons, the
antlered-male-only hunting regulations were not
established until autumn 1993. Continued high
harvests following the peak in deer densities during 1986 accelerated and prolonged the subsequent decline in deer densities (Fig. 1). The
establishment of a zone-based antlerless harvest
quota system during 1998 should allow managers
520
LIMITING FACTORS FOR DEER • Patterson et al.
to regulate deer numbers by annually adjusting
the number of antlerless permits in response to
estimates of hunting and nonhunting losses. Harvest and predation were the largest proximate
limiting factors for deer during this study, during
a period of low deer densities and relatively mild
winters. Over a longer time frame, density-dependent forage competition is the ultimate regulatory factor for deer in the Northeast (Messier 1991,
Post and Stenseth 1998, Dumont et al. 2000, Patterson and Power 2002), with other limiting factors such as harvest and predation temporarily
altering the equilibrium around which deer densities fluctuate. In addition to understanding the
effects of major proximate mortality sources on
deer population growth, managers must be aware
of the status of the deer populations they manage
in relation to carrying capacity. Our study
demonstrates that recovery of deer numbers after
a population crash can be prolonged despite apparently favorable conditions for rapid growth.
ACKNOWLEDGMENTS
We thank D. Banks, S. Bondrup-Nielsen, G.
Boros, M. J. Boudreau, H. J. Broders, R. Charlton, C. L. Cushing, C. Doliver, A. P. Duke, T. M.
Fitzgerald, C. Frail, K. Huskins, A. Kennedy, K. G.
Lock, C. MacDonald, S. F. Morrison, E. M. Muntz,
M. O’Brien, D. Richards, M. Robinson, D. Shaw,
and G. Tatlock for logistical support and V. A.
Power and A. L. Nette of the NSDNR, Wildlife
Division, for providing data on vehicle-struck
deer and the provincial deer pellet-group inventories. We thank the staff of the Air Services division of NSDNR for their expert assistance with
the aerial tracking flights, and D. O. Joly and M.
Crête for comments on an earlier draft of the
manuscript. Financial and logistical support for
this study was provided by the NSDNR, Parks
Canada, and Forestry Canada, under the Cooperation Agreement for Forestry Development.
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Received: 15 September 2000.
Accepted: 15 November 2001.
Associate Editor: Krausman.