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Ecotypic Variation in Recruitment of Reintroduced Bighorn Sheep: Implications for Translocation

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European settlement led to extirpation of native Audubon's bighorn sheep (formerly Ovis canadensis auduboni) from North Dakota during the early 20th century. The North Dakota Game and Fish Department subsequently introduced California bighorn sheep (formerly O. c. californiana) that were indigenous to the Williams Lake region of British Columbia, Canada, and Rocky Mountain bighorn sheep (O. c. canadensis) that were indigenous to the Sun River region of Montana. Although California bighorn sheep are no longer recognized as a distinct subspecies, they are smaller and adapted to a milder climate than either the native bighorn sheep of North Dakota or introduced bighorn sheep from Montana. Because reintroductions still play a key role in the management of bighorn sheep and because local adaptation may have substantial demographic consequences, we evaluated causes of variation in recruitment of bighorn sheep reintroduced in North Dakota. During 2006–2011, Montana stock recruited 0.54 juveniles/adult female (n = 113), whereas British Columbia stock recruited 0.24 juveniles/adult female (n = 562). Our most plausible mixed-effects logistic regression model (53% of model weight) attributed variation in recruitment to differences between source populations (odds ratio = 4.5; 90% CI = 1.5, 15.3). Greater recruitment of Montana stock (fitted mean = 0.56 juveniles/adult female; 90% CI = 0.41, 0.70) contributed to a net gain in abundance (r = 0.15), whereas abundance of British Columbia stock declined (fitted mean = 0.24 juveniles/adult female; 90% CI = 0.09, 0.41; r = − 0.04). Translocations have been the primary tool used to augment and restore populations of wild sheep but often have failed to achieve objectives. Our results show that ecotypic differences among source stocks may have long-term implications for recruitment and demographic performance of reintroduced populations. © 2014 The Wildlife Society.
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University of Nebraska - Lincoln
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Ecotypic Variation in Recruitment of Reintroduced
Bighorn Sheep: Implications for Translocation
Bre! P. Wiedmann
North Dakota Game and Fish Department, Dickinson, ND#6*&%-"...%(/5
Glen A. Sargeant
U. S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND
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Population Ecology
Ecotypic Variation in Recruitment of
Reintroduced Bighorn Sheep: Implications for
Translocation
BRETT P. WIEDMANN,
1
North Dakota Game and Fish Department, 225 30th Avenue SW, Dickinson, ND 58601, USA
GLEN A. SARGEANT, U. S. Geological Survey, Northern Prairie Wildlife Research Center, 8711 37th Street SE, Jamestown, ND 58401, USA
ABSTRACT European settlement led to extirpation of native Audubon’s bighorn sheep (formerly Ovis
canadensis auduboni) from North Dakota during the early 20th century. The North Dakota Game and Fish
Department subsequently introduced California bighorn sheep (formerly O. c. californiana) that were
indigenous to the Williams Lake region of British Columbia, Canada, and Rocky Mountain bighorn sheep
(O. c. canadensis) that were indigenous to the Sun River region of Montana. Although California bighorn
sheep are no longer recognized as a distinct subspecies, they are smaller and adapted to a milder climate than
either the native bighorn sheep of North Dakota or introduced bighorn sheep from Montana. Because
reintroductions still play a key role in the management of bighorn sheep and because local adaptation may
have substantial demographic consequences, we evaluated causes of variation in recruitment of bighorn sheep
reintroduced in North Dakota. During 2006–2011, Montana stock recruited 0.54 juveniles/adult female
(n¼113), whereas British Columbia stock recruited 0.24 juveniles/adult female (n¼562). Our most
plausible mixed-effects logistic regression model (53% of model weight) attributed variation in recruitment to
differences between source populations (odds ratio ¼4.5; 90% CI ¼1.5, 15.3). Greater recruitment of
Montana stock (fitted mean ¼0.56 juveniles/adult female; 90% CI ¼0.41, 0.70) contributed to a net gain in
abundance (r¼0.15), whereas abundance of British Columbia stock declined (fitted mean ¼0.24 juveniles/
adult female; 90% CI ¼0.09, 0.41; r¼0.04). Translocations have been the primary tool used to augment
and restore populations of wild sheep but often have failed to achieve objectives. Our results show that
ecotypic differences among source stocks may have long-term implications for recruitment and demographic
performance of reintroduced populations. Published 2014. This article is a U.S. Government work and is in
the public domain in the USA.
KEY WORDS bighorn sheep, ecotype, North Dakota, Ovis canadensis, recruitment, reintroduction, translocation,
wild sheep.
Many species of wildlife have declined in abundance and
distribution as a result of human activity (Ceballos and
Ehrlich 2002). For example, prior to European settlement of
western North America, bighorn sheep (Ovis canadensis)
ranged from Canada southward to Mexico, and from
California eastward to the Dakotas and Nebraska. However,
by the early 1900s, bighorn sheep were extirpated from 6
states, and only 15,000–20,000 remained in the United
States and Canada (Buechner 1960, Toweill and Geist
1999).
Translocations have played a key role in restoration of
bighorn sheep, which do not readily disperse and colonize
vacant habitat (Geist 1971). During the past 90 years,
>20,000 bighorn sheep have been translocated to restore or
augment populations (Brewer et al. 2013). Although
reintroductions have expanded the distribution of bighorn
sheep throughout historical range, translocations often do
not achieve intended results (Rowland and Schmidt 1981,
Douglas and Leslie 1999). For example, Risenhoover et al.
(1988) reported that the number of bighorn sheep
populations in Colorado declined from 1944 to 1988,
despite 27 translocations during the same period. Many
reintroduced populations of bighorn sheep are at risk because
they comprise few individuals and are geographically isolated
(Wishart 1978, Thorne et al. 1985, Singer et al. 2000). Such
populations may be less likely to persist (Berger 1990). The
same is true of metapopulations numbering fewer than 150
individuals (Gilpin and Hanski 1989, Bleich et al. 1990,
Fitzsimmons and Buskirk 1992).
Characteristics of source stock, habitat suitability, presence
of domestic sheep, and numbers of individuals introduced
are thought to affect the growth and persistence of
reintroduced populations of bighorn sheep (Holl 1982,
Griffith et al. 1989, Singer et al. 2000). For example, Singer
et al. (2000) found that translocations of stock from native
sources were twice as likely to succeed as those using
descendants from reintroduced populations (i.e., dilution
translocations). Toweill and Geist (1999) suggested that
controlling predators, translocating younger animals, and
Received: 23 May 2013; Accepted: 10 December 2013
Published: 21 January 2014
1
E-mail: bwiedmann@nd.gov
The Journal of Wildlife Management 78(3):394–401; 2014; DOI: 10.1002/jwmg.669
394 The Journal of Wildlife Management 78(3)
supplementing reintroduced populations could also improve
prospects for success.
Further, wildlife populations often exhibit ecotypic
variation: differences in physical characteristics or behavior
that result from adaptation to local environmental conditions
(Geist 1991). Such differences could potentially affect
survival and reproductive success of translocated stock.
Indeed, consideration of ecotypic variation is implicit in
recent recommendations that bighorn sheep should be
translocated from source populations that are nearest to
release sites, or that have the greatest genetic or clinal
similarity to extirpated populations (Ramey 1993, Fitzsim-
mons et al. 1997, International Union for Conservation of
Nature and Natural Resources 1998, National Park Service
2006). Although wildlife managers often are limited by the
availability of stock for translocation, failure to account for
potential effects of ecotypic variation among source
populations could potentially undermine the success of
translocations (Douglas and Leslie 1999).
Management of bighorn sheep in North Dakota was
constrained for decades by classification of Rocky Mountain
(O. c. canadensis) and California bighorn sheep (formerly O. c.
californiana) as distinct subspecies (Cowan 1940, Clark
1964). The North Dakota Game and Fish Department
(NDGF) preserved the distinction by translocating only
California bighorn sheep that were indigenous to the
Williams Lake region of British Columbia, Canada.
However, in 2005 the NDGF changed policy to permit
introductions of Rocky Mountain bighorn sheep after
Audubon’s (formerly O. c. auduboni), California, and Rocky
Mountain bighorn sheep were synonymized as O. c.
canadensis (Wehausen and Ramey 1993, 2000). After
reclassification, the NDGF began introducing bighorn
sheep that were indigenous to the Sun River region of
Montana and potentially better adapted to the harsh climate
and badlands landscape of western North Dakota.
More than 1,400 translocations of wild sheep have
occurred in the United States and Canada during the past
90 years (Brewer et al. 2013). In most cases, however,
factors contributing to success or failure were not identified.
Roy and Irby (1994) contended that more rigorous
evaluations of translocations could enhance management
of wild sheep. Resource selection, birth dates, and lamb
survival to winter have since been compared for sympatric
bighorn sheep translocated from different source popula-
tions (Kauffman et al. 2009, Whiting et al. 2011); however,
ecotypic variation in recruitment has not been evaluated.
We compared recruitment of translocated bighorn sheep
descended from source populations in the Williams Lake
region of British Columbia (BC stock) and Sun River
region of Montana (MT stock). Because the native bighorn
sheep of North Dakota and Montana occupied similar
continental climates that were harsher than the temperate
climate of southern British Columbia (Shackleton 1985,
Toweill and Geist 1999), we predicted that recruitment of
MT stock would exceed that of BC stock if ecotypic
differences conferred an adaptive advantage in western
North Dakota.
STUDY AREA
Our study area included portions of Billings, Dunn, Golden
Valley, McKenzie, and Slope counties in western North
Dakota, where bighorn sheep had a discontinuous distribu-
tion in badlands habitat near the Little Missouri River.
Bighorn sheep occurred on lands managed by the United
States Forest Service, National Park Service, Bureau of Land
Management, private landowners, and several North Dakota
state agencies (Fig. 1).
Bighorn sheep were concentrated in relatively steep,
rugged terrain. Elevations ranged from 637 m to 1,050 m
above sea level. Substrates consisted of highly erodible silts
and clays, and harder materials such as sandstone and scoria
(Bluemle 1980). The climate was semi-arid, continental,
and windy, with warm summers and cold winters (Jensen
1974). Temperatures during our study ranged from
36.18C to 42.28C, and precipitation ranged from
24.6 cm to 36.8 cm annually (North Dakota State University
2011). Snowfall ranged from 84.1cm to 216.4 cm annually
(Desert Research Institute 2011). We calculated a winter
severity index (WSI) from 1 November to 30 April during
each year of our study by accumulating 1 point for each day
the mean ambient temperature was 78C, and an
additional point for each day the snow depth was 35 cm
(Brinkman et al. 2005). Index values (92–228) were above
the long-term average (199; 1950–2011) during 3 years of
our 5-year study, and the WSI during 2011 was the highest
on record.
Vegetation of the region was described previously by Wali
et al. (1980), Jensen (1988), and Feist (1997). Primary land
uses included livestock grazing, agriculture, and energy
production. Recreational activities (hunting, biking, hiking,
horseback riding, camping) also were common (Sargeant and
Oehler 2007). In addition to bighorn sheep, our study area
was occupied by cattle and horses, mule deer (Odocoileus
hemionus), white-tailed deer (O. virginianus), pronghorn
(Antilocapra americana), and elk (Cervus elaphus). Predators
of bighorn sheep included mountain lions (Puma concolor),
coyotes (Canis latrans), bobcats (Lynx rufus), and golden
eagles (Aquila chrysaetos). Female bighorn sheep were not
hunted during our study.
METHODS
Study Population
In 1956, 18 bighorn sheep (9 M, 9 F) from the Williams
Lake region of British Columbia were translocated to an
80-ha enclosure in North Dakota (Murdy 1957). The
captive bighorn sheep provided source stock used to
repopulate vacant habitat in our study area (Knue 1991,
Wiedmann 2005). Additional BC stock (31 M, 116 F) were
translocated from British Columbia in 1989 and 1996, from
the Owyhee River region of Idaho in 1990 and 1991, and
from the John Day and Deschutes River regions of Oregon
in 2003 and 2004 (Wiedmann 2005; Fig. 1). Source
populations of BC stock from British Columbia, Idaho, and
Oregon were genetically indistinguishable (O’Callaghan
1997). Numbers of native BC stock in British Columbia
Wiedmann and Sargeant Translocating Bighorn Sheep 395
increased from 1,185 in 1960 to 3,590 in 1998 despite
removal of animals for translocation to 6 western states
(Demarchi et al. 2000).
In 2006 and 2007, 39 bighorn sheep (8 M, 31 F) from the
Missouri River Breaks region of Montana were translocated to
our study area (Fig. 1). The Missouri River Breaks population
was founded in 1980 with indigenous stock from the Sun
River region of Montana (Montana Department of Fish,
Wildlife and Parks 2010). Numbers of native bighorn sheep in
the Sun River region of Montana declined slightly (8%)
from 1966 to 2008; however, contributing factors included 2
epizootics and removal of animals for translocation (Montana
Department of Fish, Wildlife and Parks 2010). The
mean lamb:female ratio observed during annual recruitment
surveys (1982–2012) was 34:100 (Butler et al. 2013).
During 2006–2011 we deployed very high frequency (VHF)
radio collars (Advanced Telemetry Systems [ATS], Isanti,
MN, and Sirtrack, Havelock North, New Zealand) on 90 BC
females within 14 distinct subpopulations. We fitted trans-
located MT stock with ATS VHF radio-collars with an
attached uniquely numbered tag. We also deployed Sirtrack
VHF radio collars on 33 additional BC females and 12 MT
females during our study. We dosed radio-marked bighorn
sheep with 3 ml of ivermectin (Ivomec
TM
; Merial Limited,
Duluth, GA) and 3 ml of Bo-Se
TM
(Schering-Plough Health
Corporation, Union,NJ) when we captured and released them.
We conducted a census of female bighorn sheep and their
offspringtwice annually, duringlatesummer and thefollowing
March 2006–2011. We used an ATS R4000 receiver and 2-
element antennas (RA-2AHS, Telonics, Mesa, AZ) mounted
to a fixed-wing aircraft to locate groups containing radio-
marked females. Thereafter, we immediately used a handheld
receiver (H.A.B.I.T. Research HR2600 Osprey, Victoria,
British Columbia, Canada) and 2-element antenna (RA-
2AK, Telonics) to relocate groups from the ground. We then
used a 20–60spotting scope to classify each individual as an
adultmale (2 yearsold), yearling male,adultfemale (2 years
old), yearling female, or juvenile (Geist 1968). We used adult
female:juvenile ratios observed during March censuses to
estimate recruitment (Festa-Bianchet 1992).
Stock from 10 of 14 BC subpopulations did not associate
with MT stock during our study. Further, MT stock
translocated in 2006 were released into unoccupied habitat,
and did not associate with nearby subpopulations of BC
stock. Individuals from MT stock translocated in 2007 did
associate with resident BC stock; however, BC and MT
females occupying sympatric ranges were distinguishable
because MT stock had much lighter pelage. Moreover,
March censuses occurred when stocks were segregated,
which was verified by identifying unique radio frequencies
from females of known origin (Fig. 2).
Females from 10 of 14 BC subpopulations associated
exclusively with BC males during the breeding season, and
MT females translocated in 2006 were observed exclusively
with MT males. Although BC and MT males did associate
with females from both types where they occupied the same
Figure 1. Origins of bighorn sheep translocated to historic range in North Dakota, USA (inset), during 1956–2007. British Columbia (BC) stock were
obtained from 1) Williams Lake, British Columbia, Canada, 2) Owyhee River, Idaho, and 3) Deschutes and John Day Rivers, Oregon. Montana (MT) stock
were obtained from 4) Upper Missouri River Breaks National Monument, Montana, and 5) Charles M. Russell National Wildlife Refuge, Montana.
396 The Journal of Wildlife Management 78(3)
range, BC and MT stock of both sexes were segregated
during the breeding season.
We followed animal capture and handling guidelines of the
NDGF, as set forth by Foster (2005) and the Animal Behavior
Society (2006). We conducted all captures with a hand-held
net-gun fired from a helicopter (Krausman et al. 1985).
Wildlife veterinarians were present during captures and while
bighorn sheep were en route to release sites in North Dakota.
Statistical Analysis
We used 6 mixed-effects logistic-regression models (Gelman
and Hill 2007) to represent various hypotheses about
recruitment:
Model 1 included an observation-level random effect, s
ijk
,
representing unstructured and unexplained extrabinominal
variation resulting from population influences that might
have varied both geographically (i), annually (k), and between
stocks (j). Such variation might result from local effects of
disease or predation.
Model 2 included a random effect for year, s
k
, representing
extrabinominal variation resulting from geographically
widespread phenomena that varied annually (e.g., regional
weather).
Models 3.1 and 3.2 extended models 1 and 2 by
incorporating b
ij
, which described combinations of geo-
graphic location and stock. These models provided for
differences between BC and MT stock and also for
geographic variation within our study area.
Models 4.1 and 4.2 extended models 1 and 2 by
incorporating g
j
, a fixed effect describing the difference
between the BC and MT stocks.
We used Akaike’s Information Criterion, adjusted for
sample size (AIC
c
), to assess evidence for competing
hypotheses represented by candidate models (Burnham
and Anderson 2002). We then 1) used the “simulate”
function from the R package lme4 (http://www.r-project.
org/, accessed 11 Jul 2012) to generate 1,000 simulated data
sets from each candidate model that was supported by our
data, 2) used the “refit” function and the simulated data to
generate 1,000 sets of parameter estimates for each model, 3)
extracted coefficients for fixed effects, and 4) used
coefficients to generate 1,000 bootstrap sets of predicted
values for each model. We used standard deviations and
quantiles of model-averaged predictions to estimate
standard errors and 90% confidence intervals (Efron and
Tibshirani 1993) that reflected both sampling variation and
uncertainty associated with model selection (Burnham and
Anderson 2002). We used v. 2.11 of the R language and
environment (R Development Core Team 2011) and
package lme4 (version 0.999375-39; Bates et al. 2011) to
fit models.
RESULTS
Our results provided greatest support for observation-level
random variation and ecotypic differences in recruitment
(model 4.1; 53% of model weight; Table 1). Model 4.1
estimated mean recruitment (^
r) of 0.56 juveniles/adult
female (90% CI ¼0.41, 0.70) for MT stock and 0.24
juveniles/adult female (90% CI ¼0.09, 0.41) for BC stock,
for an effect size (D)^
rof 0.32 juveniles/adult female (90%
CI ¼0.10, 0.53) and an odds ratio of 4.5 (90% CI ¼1.5,
15.3).
We found no support for random annual variation in
recruitment resulting from such broad-scale influences as
winter weather or drought (Akaike weights ¼0; models 2,
3.2, and 4.2; Table 1). However, model 3.1 (confounded
effects of geographic location and origin; 33% of model
weight) and, to a lesser degree, model 1 (unstructured
random variation; 14% of model weight) were plausible
alternatives to our top-ranked model (Table 1).
To control for confounding effects, we used a balanced
subset of treatment groups (i.e., study sites occupied by both
stocks) to estimate effects of origin for model 3.1 (Table 1).
Recruitment estimated from model 3.1 was 0.64 juveniles/
adult female (90% CI ¼0.44, 0.83) for MT stock and 0.24
juveniles/adult female (90% CI ¼0.10, 0.40) for BC stock,
for an effect size of 0.43 juveniles/adult female (90%
CI ¼0.14, 0.64) and an odds ratio of 6.4 (90% CI ¼1.9,
24.7).
Collectively, models 1 (Dr¼0), 3.1 (D^
r¼0.43), and 4.1
(D^
r¼0.32) resulted in a model-averaged effect size of 0.30
juveniles/adult female (90% CI ¼0.12, 0.48) and an odds
ratio of 6.2 (90% CI ¼1.6, 16.2). Stock from Montana
totaled 19.7% of the female population during our study, but
accounted for 31.6% of the total number of lambs recruited.
Taken as a whole, our results documented substantially
greater recruitment by MT females than by BC females and
suggested the effect was not due to differences among study
sites.
Mortality of adult MT females was nearly twice that of
marked BC females during 2006–2011, but greater recruit-
Figure 2. Unique radio-frequencies and tag numbers were used to
distinguish female bighorn sheep descended from source populations in
the Williams Lake region of British Columbia, Canada, and Sun River
region of Montana in North Dakota, USA, 2006–2011.
Wiedmann and Sargeant Translocating Bighorn Sheep 397
ment by MT females more than compensated for those
losses. Of the radio-marked BC females (n¼53) at the
beginning of our study, 28.3% died; however, more than half
(51.6%) of MT females (N¼31) died (N¼14) or dispersed
(N¼2) during the same period. Numbers of BC stock
nevertheless declined from 236 to 199 (15.7%, r¼0.04)
during our study, whereas numbers of MT stock increased
from 43 to 77 (þ79.1%, r¼0.15), despite greater losses of
adult MT females.
DISCUSSION
Bighorn sheep are habitat specialists (Shackleton 1985) that
exhibit high fidelity to traditional home ranges (Geist 1971),
which generally consist of open areas containing discontin-
uous patches of precipitous terrain adjacent to foraging areas
(Holl 1982; Gionfriddo and Krausman 1986; Bleich et al.
1990, 1997). Knowledge of such areas is passed down to
subsequent generations that typically are reluctant to pioneer
and colonize vacant habitats (Geist 1971, Becker et al. 1978).
Translocations of bighorn sheep have therefore played an
essential role in restoration of populations to historical
ranges. However, translocation of bighorn sheep is expen-
sive, with a typical cost of approximately $1,100 per animal
(Foster 2005).
Persistence of bighorn sheep is greatly influenced by
population size (Geist 1975, Smith et al. 1991). For example,
of the native populations studied by Berger (1990), all that
comprised <50 individuals were extirpated within 50 years.
In contrast, all populations comprising >100 individuals
persisted for 70 years. Consequently, growth of restored
populations to >100 individuals has been generally recog-
nized as the benchmark for success (Singer et al. 1999).
Based on this standard, only 41% of 100 translocations
reviewed by Singer et al. (2000) were successful.
Low success rates, coupled with high per capita costs of
capturing and transporting bighorn sheep, have greatly
reduced the cost-effectiveness of translocations. Trans-
locations also carry a biological cost in terms of impacts on
source populations (Stevens and Goodson 1993), and they
are not without risk to receiving populations and translocated
stock (Bleich et al. 1990, Whisson et al. 2012). Factors
contributing to the success or failure of reintroductions are
therefore of paramount interest for management of bighorn
sheep.
Northern populations of bighorn sheep formerly were
classified as 3 distinct subspecies, one of which (O. c.
auduboni) is extinct (Cowan 1940, Clark 1964). Although
these distinctions were recently abandoned because molecu-
lar and morphometric variation did not meet subspecific
criteria (Wehausen and Ramey 2000), they testify to
substantial variation in physical characteristics of indigenous
populations of bighorn sheep from different environments.
Such variation within taxa is a manifestation of ecotypic
variation, or genetic adaptation to local ecological conditions
(Geist 1991; Wehausen and Ramey 1993, 2000).
Ecotypic variation is a result of differential reproductive
success and survival (Van Zyll de Jong et al. 1995, Hinkes
et al. 2005) and may have substantial implications for
management (Geist 1991, Whiting et al. 2012). Prior to
reclassification of O. c. californiana as synonymous with O. c.
canadensis (Wehausen and Ramey 2000), agencies generally
maintained the distinction between the subspecies and did
not intentionally stock both into the same areas (Toweill and
Geist 1999). This practice precluded observation of
sympatric bighorn sheep from substantially different source
populations. To our knowledge, our investigation is the first
comparison of recruitment and demographic performance
between sympatric bighorn sheep of different ecotypes.
Differences we observed did not mirror population
performance of BC and MT stock on native range. Despite
decades of intensive management by the NDGF, BC stock
have consistently suffered chronically low recruitment (B.
Wiedmann, unpublished data). Meanwhile, numbers of
native BC stock increased dramatically in British Columbia
(Demarchi et al. 2000) and numbers of native MT stock
declined slightly in the Sun River region of Montana
(Montana Department of Fish, Wildlife and Parks 2010). In
contrast, abundance of BC stock declined 16% and MT stock
increased 79% during our study. Our results therefore
suggest that potential demographic performance of reintro-
duced bighorn sheep may be enhanced by selection of source
stock adapted to similar environments. For example, the
largest-bodied bighorn sheep in North America are generally
found at the northern portions of their range or at high
elevations, under conditions similar to those experienced in
North Dakota: high-quality summer forage is abundant and
winters are typically severe (Geist 1971, Blackburn et al.
1999). Larger ecotypes typically give birth to larger lambs
that are more capable of surviving inclement weather during
Table 1. Candidate models, corrected Akaike’s Information Criterion (AIC
c
) rankings and weights (w
i
), estimates of recruitment (juveniles/adult female; ^
r),
and odds ratios for bighorn sheep reintroduced in North Dakota from Montana (MT) and British Columbia (BC). Model terms include observed numbers of
juveniles/adult female (p), intercepts (a), combinations of geographic location and stock (b), stock (g), and a random effect (s). Subscripts distinguish
geographic locations (i), stocks (j), and years (k).
Juveniles/adult female Odds ratio
Model DAIC
c
w
i
^
rMT SE ^
rBC SE ^
sMT/BC 90% CI
1 logit(p
ijk
)¼aþs
ijk
2.70 0.14 0.45 0.09 0.45 0.09 1.11
2 logit(p
k
)¼aþs
k
22.99 0.00 0.44 0.04 0.44 0.04 0
3.1 logit(p
ijk
)¼aþb
ij
þs
ijk
0.99 0.33 0.64 0.12 0.24 0.09 0.84 6.4 1.9, 24.7
3.2 logit(p
ijk
)¼aþb
ij
þs
k
10.24 0.00 0.68 0.08 0.29 0.06 0.25 5.4 2.8, 12.5
4.1 logit(p
ijk
)¼aþg
j
þs
ijk
0.00 0.53 0.56 0.09 0.24 0.10 0.90 4.5 1.5, 15.3
4.2 logit(p
jk
)¼aþg
j
þs
k
13.02 0.00 0.54 0.05 0.27 0.06 0.16 3.2 1.8, 5.8
398 The Journal of Wildlife Management 78(3)
the birthing season and subsequent first winter of life
(Shackleton et al. 1999, Toweill and Geist 1999). The
superior demographic performance of MT stock in North
Dakota likely reflects an advantage conferred by larger body
size in both environments.
Bighorn sheep translocated to our study area from
Montana were relatively young (median ¼4 years old,
N¼31). However, the longevity of bighorn sheep and
late onset of reproductive senescence limited the potential for
contribution to effects we observed. For example, Be
´rube
´
et al. (1999) observed age-related decreases in survival 6–7
years before decreases in recruitment, and long-lived females
sustained high reproductive success throughout their
lifetime. Moreover, birth rates were <0.20 for 2-year-old
females and increased until 5–6 years of age, when they
exceeded 0.9. Such age-related variation in survival and
reproduction would have dampened, rather than produced,
differences in recruitment rates of BC and MT stock.
Although origins of stock for translocation may substan-
tially affect demographic performance, other factors also
commonly prevent wild sheep populations from achieving
their full potential. For example, diseases (Gross et al. 2000,
Cassirer et al. 2013), predation (Kamler et al. 2002,
Rominger et al. 2004), and possibly low genetic diversity
resulting from inbreeding within small founder groups
(Hogg et al. 2006, Foster and Whittaker 2010) may all stifle
demographic performance of reintroduced populations.
Whether timing of parturition of source stock is synchro-
nized with the availability of nutritious forage during the
lambing season may also be an important consideration
(Whiting et al. 2011, 2012).
Effects of other influences should magnify, rather than
diminish, interest in ecotypic variation because demographic
advantages of locally adapted bighorn sheep may compensate
and allow introduced populations to persist, or even increase,
under conditions that might otherwise cause translocations
to fail (Rominger et al. 2004). For example, newly introduced
MT females achieved greater recruitment and population
growth than BC stock despite greater levels of adult
mortality caused primarily by cougar predation and vehicle
collisions in the study area (B. Wiedmann, unpublished
data). In contrast, abundance of BC stock declined during
the same period despite much lower levels of adult mortality
than bighorn sheep introduced from MT.
Although adaptation to similar environments may be an
important consideration for selection of source stocks, it may
not be entirely sufficient; behavioral adaptation also may be
critical and has not always been given adequate consideration
(Hutchins and Geist 1987, Warren et al. 1996, Frair et al.
2007). Neglecting the adaptive idiosyncrasies of mountain
ungulates in management decisions may result in failure of
translocations because introduced animals that lack site-
specific knowledge of foraging areas, water sources, bedding
areas, mineral licks, and suitable lambing habitat may be at a
disadvantage (Geist 1975, Risenhoover et al. 1988, Bleich
et al. 1997, Douglas and Leslie 1999, Scillitani et al. 2013).
Further, bighorn sheep from migratory populations that are
adapted to high-elevation, alpine habitats may not acclimate
adequately to low-elevation habitats that are typically drier
and more suited to non-migratory behavior, or vice-versa
(Easterly 2009).
Adaptations of taxa to local environments can substantially
affect behavior and demography of populations (A
bjo
¨rnsson
et al. 2004, Whiting et al. 2012), particularly as they relate to
wild sheep, where female offspring typically adopt their natal
home ranges (Geist 1971). However, if reintroduced
populations of bighorn sheep realize short-term adaptations
to dissimilar habitats, it was not evident during our study.
Indeed, BC stock occupied our study area 5 decades prior to
the introduction of MT stock but realized substantially lower
recruitment and population growth than MT stock, and the
disparity was greatest where both occupied the same range.
Although initial translocations (1958–1961) of bighorn
sheep from a captive source were largely ineffective, the
Missouri River Breaks population in Montana thrived after
1980, when 56 animals were translocated from the Sun River
region of that state (Sullivan et al. 1998). The translocated
stock soon colonized most of the Breaks region and not only
provided 149 animals for translocations, but increased to
>1,000 individuals by 2008 (Montana Department of Fish,
Wildlife and Parks 2010). Not surprisingly, bighorn sheep
translocated from the Missouri River Breaks region of
Montana to the ecologically similar Little Missouri River
region of North Dakota achieved similar rates of population
growth. In contrast, BC stock have fared poorly in North
Dakota but have thrived in milder regions of Idaho, Nevada,
Oregon, Utah, and Washington (Toweill and Geist 1999).
MANAGEMENT IMPLICATIONS
Translocations are likely to be an important management
tool in the continued recovery and persistence of bighorn
sheep (Larkins 2010). Because wild sheep are widely
distributed and exhibit local adaptations to clinal disconti-
nuity throughout their global range (Clark 1964, Mitchell
and Frisina 2007), translocations may also become an
increasingly important tool used internationally for the
conservation and management of declining populations of
wild sheep throughout Europe and Asia (Kence et al. 2002,
Maroney and Paltsyn 2003). Our results suggest that
consideration of ecotypic variation among sources of
translocation stock can greatly improve prospects for
successful reintroductions of mountain sheep.
ACKNOWLEDGMENTS
We thank the North Dakota Game and Fish Department,
Wild Sheep Foundation–Midwest Chapter, the U.S.
Geological Survey Northern Prairie Wildlife Research
Center, and the Bureau of Land Management—North
Dakota Field Office for funding this project. We thank the
British Columbia Ministry of Environment, Idaho Fish and
Game Department, Montana Department of Fish, Wildlife
and Parks, and Oregon Department of Fish and Wildlife for
their generosity in supplying translocation stock to North
Dakota. We thank W. Jensen for computing winter severity
indices; B. Hosek, R. Johnson, J. Kolar, S. Richardson, B.
Stillings, and W. Tidball for their technical assistance; and
Wiedmann and Sargeant Translocating Bighorn Sheep 399
pilots B. Berentson, J. Faught, J. Rubbert, and M. Shelton
for assisting with capture operations and radio-tracking. We
are grateful to V. Bleich, M. Festa-Bianchet, K. Hurley, M.
Sullivan, and 1 anonymous reviewer for providing comments
that improved early drafts of this manuscript. Any use of
trade, firm, or product names is for descriptive purposes only
and does not imply endorsement by the U.S. Government.
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Wiedmann and Sargeant Translocating Bighorn Sheep 401
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... Bozchaloyi & Sheidai, 2018). Despite the apparent importance of ecotypes for applied conservation management (Bourret et al., 2020;Chiesa et al., 2014;Wiedmann & Sargeant, 2014), this uncertainty limits broader theoretical development and practical application (Box 1 Part A). ...
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The assessment bighorn habitat is essential to determine the distribution and the number of individuals who can support an area. In this research satellite remote sensing techniques were used to analyse availability, use and habitat selection carried out by the bighorn sheep in Sierra Santa Isabel. The study used three essential components: water, escape terrain and cover vegetation. Of the 11 water holes that are used by bighorn sheep, Zamora (n = 120) and El Cordero (n = 67) had the highest records were identified. Sites with greater availability of escape terrain were selected by groups of ewes and yearlings (χ² = 9.83, P ˂ 0.05), while groups of adults (rams and ewes) selected sites with lower availability. In dry season bighorn sheep selected sites with low vegetation cover (χ² = 11.58, P < 0.05), and during the rainy season in only one of the study sites selected sites with greater coverage (χ² = 8.72, P < 0.05). For the period post-rainfall no relationship between vegetation cover and distribution of bighorn sheep was found. Site selection of escape terrain and vegetation cover by bighorn sheep was correlated with its anti predatory strategy. The greatest record of ewes (n = 140) and yearlings (n = 62), coupled with the unfragmented habitat and availability of permanent water, confirm the importance of Sierra Santa Isabel for breeding, raising and recruitment of bighorn sheep in Baja California. The analysis of satellite images facilitate location and allow optimal evaluation, essential for monitoring and management of populations of bighorn sheep habitat.
... In contrast, populations in landscapes that are more fragmented (i.e., southern California) or heavily influenced by translocations (i.e., southeastern Utah) tended to be less genetically diverse and more isolated. This pattern is consistent with previous studies that have found low genetic diversity or fitness in reintroduced bighorn sheep populations (Whittaker et al., 2004;Wiedmann and Sargeant, 2014). Fortunately, areas that support some of the most genetically diverse and connected populations in our study area are also predicted to have relatively low climate change exposure (e.g., DEVA and GRCA). ...
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Assessments of organisms’ vulnerability to potential climatic shifts are increasingly common. Such assessments are often conducted at the species level and focused primarily on the magnitude of anticipated climate change (i.e., climate exposure). However, wildlife management would benefit from population-level assessments that also incorporate measures of local or regional potential for organismal adaptation to change. Estimates of genetic diversity, gene flow, and landscape connectivity can address this need and complement climate exposure estimates to establish management priorities at broad to local scales. We provide an example of this holistic approach for desert bighorn sheep (Ovis canadensis nelsoni) within and surrounding lands administered by the U.S. National Park Service. We used genetic and environmental data from 62 populations across the southwestern U.S. to delineate genetic structure, evaluate relationships between genetic diversity and isolation, and estimate relative climate vulnerability for populations as a function of five variables associated with species’ responses to climate change: genetic diversity, genetic isolation, geographic isolation, forward climate velocity within a population’s habitat patch (a measure of geographic movement rate required for an organism to maintain constant climate conditions), and maximum elevation within the habitat patch (a measure of current climate stress, as lower maximum elevation is associated with higher temperature, lower precipitation, and lower population persistence). Genetic structure analyses revealed a high-level division between populations in southeastern Utah and populations in the remainder of the study area, which were further differentiated into four lower-level genetic clusters. Genetic diversity decreased with population isolation, whereas genetic differentiation increased, but these patterns were stronger for native populations than for translocated populations. Populations exhibited large variation in predicted vulnerability across the study area with respect to all variables, but native populations occupying relatively intact landscapes, such as Death Valley and Grand Canyon national parks, had the lowest overall vulnerability. These results provide local and regional context for conservation and management decisions regarding bighorn populations in a changing climate. Our study further demonstrates how assessments combining multiple factors could allow a more integrated response, such as increasing efforts to maintain connectivity and thus potential for adaptation in areas experiencing rapid climate change.
... Monitoring the dispersal of released individuals is important to understand rates of spread, release-site fidelity and success of translocations and reintroductions (Singer et al. 2000;La Morgia et al. 2011;Yott et al. 2011). Understanding dispersal and habitat use of reintroduced animals that are naïve to their surroundings is critical for successful reintroductions (Griffith et al. 1989;Seddon et al. 2007;Berger-Tal and Saltz 2014), especially in cases when survival or reproductive rates are low because of acclimation to their release site (Stussy et al. 1994;Armstrong and Seddon 2008;Whiting et al. 2011;Wiedmann and Sargeant 2014;Cain et al. 2018). ...
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Whole‐genome sequencing is revolutionizing our understanding of organismal biology, including adaptations likely to influence demographic performance in different environments. Excitement over the potential of genomics to inform population dynamics has prompted multiple conservation applications, including genomics‐based decision‐making for translocation efforts. Despite interest in applying genomics to improve translocations, there is a critical research gap: we lack an understanding of how genomic differences translate into population dynamics in the real world. We review how genomics and genetics data could be used to inform organismal performance, including examples of how adaptive and neutral loci have been quantified in a translocation‐context, and future applications. Next, we discuss three main drivers of population dynamics: demographic structure, spatial barriers to movement, and introgression, and their consequences for translocations informed by genomic data. Finally, we provide a practical guide to different types of models, including size‐structured and spatial models, that could be modified to include genomics data. We then propose a framework to improve translocation success by repeatedly developing, selecting, and validating forecasting models. By integrating lab‐based and field‐collected data with model‐driven research, our iterative framework could address long‐standing challenges in restoration ecology, such as when selecting locally‐adapted genotypes will aid translocation of plants and animals. This article is protected by copyright. All rights reserved.
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Reviews the adaptive syndrome of Ovis c. canadensis and its relationship to habitat requirements of bighorn; identifies historic and present-day processes resulting in the observed pattern of decline in sheep populations; assesses the effectiveness of current bighorn sheep management strategies; and offers alternative strategies based on more intensive management of bighorn sheep habits. -from Authors
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