Temperament and state-dependent behaviours in large herbivores

Abstract

Behavioural consistency and plasticity can both benefit fitness. Repeatability in behaviour within a specific context, termed temperament or trait-like behavioural responses, fosters adaptive responses to stimuli. Behavioural plasticity, on the other hand, enables state-like responses, aligning behaviour with internal and external conditions. The nutritional state of an organism significantly impacts behaviours and may interact with temperament. However, the specific contributions of trait-and state-like responses to stimuli remain poorly understood. Using a long-term data set on mule deer, Odocoileus hemionus, elk, Cervus canadensis, and bighorn sheep, Ovis canadensis, we assessed the interplay of temperament and nutritional state in behavioural responses during handling. We measured the repeatability of kick rates across multiple capture events over time, investigating its association with temperament, nutritional condition, age and capture frequency. Bighorn sheep and mule deer exhibited high repeatability in kicks during capture, while elk did not. State-dependent factors, such as body fat, minimally influenced kick rates during capture. In bighorn sheep and mule deer, trait-like responses were likely related to temperament, whereas elk demonstrated neither state-nor trait-like behavioural responses. Trait-like responses in these species may reflect adaptations to specific ecological niches and site-specific evolutionary pressures. Our findings advance our understanding of these mechanisms, shedding light on the complex interplay between temperament, nutritional state and behaviour. Nevertheless, our results highlight the need for caution when predicting or extrapolating behavioural responses to stressors across closely related species.

Full text

Temperament and state-dependent behaviours in large herbivores
Heather N. Abernathy
a
,
b
,
*
,
1
, Rebecca L. Levine
a
,
1
, Yasaman N. Shakeri
a
,
c
,
Jaron T. Kolek
a
,
c
, Brittany L. Wagler
a
, Rachel A. Smiley
a
,
c
, Rhiannon P. Jakopak
a
,
Mitchell J. Brunet
a
,
c
, Rebekah T. Rafferty
a
,
c
, Seth T. Rankins
a
,
c
,
Katey S. Huggler
a
,
c
,
d
, Brandon Scurlock
e
, Jill Randall
e
, Daryl Lutz
f
,
Alyson B. Courtemanch
g
, Tayler N. LaSharr
a
,
c
, Samantha P. H. Dwinnell
h
,
Lee E. Tafelmeyer
a
,
c
, Patrick W. Burke
i
, Patrick Lionberger
j
, Miguel Valdez
j
,
Gary L. Fralick
g
, Doug McWhirter
g
, Kevin L. Monteith
a
,
c
a
Haub School of the Environment and Natural Resources, University of Wyoming, Laramie, WY, U.S.A.
b
Mission Operations, Rocky Mountain Elk Foundation, Missoula, MT, U.S.A.
c
Wyoming Cooperative Fish and Wildlife Research Unit, Department of Zoology and Physiology, University of Wyoming, Laramie, WY, U.S.A.
d
College of Natural Resources, University of Idaho, Moscow, ID, U.S.A.
e
Wyoming Game and Fish Department, Pinedale Regional Office, WY, U.S.A.
f
Wyoming Game and Fish Department, Lander Regional Office, Lander, WY, U.S.A.
g
Wyoming Game and Fish Department, Jackson Regional Office, Jackson, WY, U.S.A.
h
Arctic Terrestrial Biology, University Centre in Svalbard, Longyearbyen, Norway
i
Wyoming Game and Fish Department, Green River Region, Green River, WY, U.S.A.
j
Bureau of Land Management, Rock Springs Field Office, Rock Springs, WY, U.S.A.
article info
Article history:
Received 5 December 2023
Initial acceptance 1 June 2024
Final acceptance 28 October 2024
Available online xxx
MS. number: A23-00641
Keywords:
bighornsheep
deer
elk
fitness
flexibility
nutritional condition
plasticity
wildlife capture
Behavioural consistency and plasticity can both benefitfitness. Repeatability in behaviour within a
specific context, termed temperament or trait-like behavioural responses, fosters adaptive responses to
stimuli. Behavioural plasticity, on the other hand, enables state-like responses, aligning behaviour with
internal and external conditions. The nutritional state of an organism significantly impacts behaviours
and may interact with temperament. However, the specific contributions of trait- and state-like re-
sponses to stimuli remain poorly understood. Using a long-term data set on mule deer, Odocoileus
hemionus, elk, Cervus canadensis, and bighorn sheep, Ovis canadensis, we assessed the interplay of
temperament and nutritional state in behavioural responses during handling. We measured the
repeatability of kick rates across multiple capture events over time, investigating its association with
temperament, nutritional condition, age and capture frequency. Bighorn sheep and mule deer exhibited
high repeatability in kicks during capture, while elk did not. State-dependent factors, such as body fat,
minimally influenced kick rates during capture. In bighorn sheep and mule deer, trait-like responses
were likely related to temperament, whereas elk demonstrated neither state- nor trait-like behavioural
responses. Trait-like responses in these species may reflect adaptations to specific ecological niches and
site-specific evolutionary pressures. Our findings advance our understanding of these mechanisms,
shedding light on the complex interplay between temperament, nutritional state and behaviour.
Nevertheless, our results highlight the need for caution when predicting or extrapolating behavioural
responses to stressors across closely related species.
©2024 The Authors. Published by Elsevier Ltd on behalf of The Association for the Study of Animal
Behaviour. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/
licenses/by-nc-nd/4.0/).
*Corresponding author.
E-mail address: habernathy@rmef.org (H. N. Abernathy).
1
These authors contributed equally.
Contents lists available at ScienceDirect
Animal Behaviour
journal homepage: www.elsevier.com/locate/anbehav
https://doi.org/10.1016/j.anbehav.2024.123056
0003-3472/©2024 The Authors. Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour. This is an open access article under the CC BY-NC-
ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Animal Behaviour 221 (2025) 123056

Understanding underlying mechanisms of behaviour is elusive
yet crucial to uncovering links to fitness. Behavioural responses to
external stimuli allow animals to exploit emerging resources, evade
predation and reproduce (DeCesare &Pletscher, 2006;Forrester
et al., 2015;Gehr et al., 2020), although behavioural responses
can vary in consistency across time. Behavioural consistency and
plasticity can be advantageous depending on the species, envi-
ronment and stimulus. Consistent behaviours provide predictable
benefits in productivity, social status and, ultimately, fitness (Biro &
Stamps, 2008;Dall et al., 2004;Gosling, 2001;Gosling &John,
1999S. D. Gosling &John, 1999). Yet, behavioural plasticity allows
an animal to respond in accordance with external stimuli and in-
ternal state, a strategy that may be favourable in fluctuating envi-
ronments (Dingemanse &Wolf, 2010;Koolhaas et al., 1997;Sih
et al., 2004;Sih &Bell, 2008;Wolf &Weissing, 2010). The consis-
tency or plasticity of behavioural responses across time can help us
identify the mechanisms underlying behaviour, a necessary first
step in linking behaviour and fitness.
The repeatability of behaviour in a single context or situation
across time can clarify the underlying mechanisms of trait
expression (Bell et al., 2009). A behavioural trait with high
repeatability likely is an intrinsic or a ‘trait-like’response, thus
classified as a temperament (Johnstone et al., 2021). For instance,
consistent behavioural responses to novel objects provided evi-
dence for trait-like responses in captive African penguins, Sphe-
niscus demersus (Saiyed et al., 2019). In contrast, low repeatability in
trait expression suggests that behaviour is a state-dependent or
‘state-like’response (McNamara &Houston, 1986), meaning that
behavioural responses may vary with physiological state (Koolhaas
et al., 1997;Smiley et al., 2022b)(Fig. 1). The repeatability of
behaviour exists on a spectrum, signifying that responses are rarely
trait- or state-like alone and are determined by some combination
of the two. Yet, the extent to which behavioural responses are trait-
or state-like, or a combination of both is difficult to test and has
seldom been empirically investigated. Such difficulties arise
because accurately assessing the respective contributions of
temperament and physiological state necessitates long-term ob-
servations of individuals over time and across varying physiological
conditions. Without comprehensive observations spanning a range
of states, there is a risk of misinterpreting state-dependent re-
sponses as temperament-driven.
Long-lived iteroparous species living in environments with
seasonally varying resources (e.g. temperate environments) can be
model study species to disentangle the extent to which tempera-
ment, state-dependence, or a combination of both underlie
behavioural responses. Many of these species have trait-like (Roff &
Fairbairn, 2007;Stearns, 1992) and state-like behaviours dictated
by seasonal cycles of resources and, consequently, nutritional
condition (J€
onsson, 1997). Nutritional condition, the physiological
state that integrates nutrient intake and expenditure, can vary
greatly within individuals across years and seasons (Olsson et al.,
2002;Smiley et al., 2022a;Stephens, 1981), naturally creating a
spectrum of experimental units with varying states. Furthermore,
trait- and state-like behaviours link with fitness in slightly different
yet significant ways. Long-lived, iteroparous species living in
temperate environments attempt to maximize their lifetime
reproductive output by investing in offspring when conditions are
favourable and forgoing years when offspring rearing undermines
their survival (Stearns, 1992). Because of their relatively long life-
times, these species are prone to evolving risk-averse tempera-
ments, particularly when faced with predation pressure (Dall et al.,
2004;Roff &Fairbairn, 2007;von Merten &Siemers, 2012;Wolf
et al., 2007); however, these species also may increase fitness by
matching behavioural responses to nutritional state (Denryter
et al., 2021;Monteith et al., 2014). For example, animals in poor
condition tend to limit energetically costly behaviours in favour of
survival (Jonart et al., 2007;Renison et al., 2003). The adaptive
advantages of both trait- and state-like behaviours provide a
unique opportunity to evaluate the relative contributions of each to
behavioural responses.
Capturing and marking animals is a common method of data
collection. Capture may lead to visible signs of distress, such as
struggling and kicking, in response to the handling process (Ortega
et al., 2020). Kicking presents a quantifiable behavioural response in
a single context of animal capture, allowing the opportunity to
investigate the relative contributions of temperament and nutri-
tional condition. This is because defence effort (e.g. struggle during
capture) correlates with both nutritional condition (Jonart et al.,
2007;Renison et al., 2003) and behavioural consistency (tempera-
ment; Nelson et al., 2020). To that end, we used a long-term data set
of three long-lived, iteroparous large mammals (mule deer, Odo-
coileus hemionus; elk, Cervus canadensis; bighorn sheep, Ovis cana-
densis) from a highly seasonal environment. We aimed to determine
whether the behavioural responses observed during capture and
handling were primarily trait-like, state-like, or a combination of
both factors. This distinction is important because temperament is
generally consistent over time, while physiological state is known to
vary within individuals in this system (Smiley, LaSharr, et al., 2022a)
and more broadly in other ungulate populations (Cook et al., 2010;
Monteith et al., 2014;Stephenson et al., 2020).
Time
Behavioural response
Time
Variance
Variance
Behavioural response
Individual 1
Individual 2
Population
Figure 1. Con ceptual patterns in the repeatability of behavioural responses based on
the influence of animal state (top) or temperament (bottom). If behavioural responses
are predominantly state-like (i.e. nutritional condition), which varies across time, then
we anticipated that the behaviour would have low repeatability, meaning that variance
within individuals would be large relative to the population variance. In contrast, if
responses are predominantly trait-like, which is intrinsic to individual animals, then
we expected behaviour to be repeatable, meaning that variance within individuals
would be small relative to the population variance. Animal state and temperament are
not mutually exclusive determinants of behaviour and likely influence behavioural
responses jointly.
H. N. Abernathy et al. / Animal Behaviour 221 (2025) 1230562

We evaluated contrasting, nonmutually exclusive hypotheses of
the mechanisms underlying behavioural responses to capture and
handling in female bighorn sheep, mule deer and elk. First, we
evaluated the hypothesis that behavioural responses during cap-
ture were trait-like and, thus, evidence of temperament (Hypoth-
esis 1). We predicted that the number of kicks (measured by kick
rate) expressed during handling would be repeatable across cap-
ture events and within individuals (Hypothesis 1: Prediction 1). We
evaluated a second hypothesis that behavioural responses during
capture are state-like and not repeatable, and thus vary with the
physiological state of an animal (Hypothesis 2). We predicted that
individuals in poor nutritional condition would conserve resources
by exhibiting a passive response to capture (i.e. lower kick rate)
compared with individuals in better nutritional condition (Hy-
pothesis 2: Prediction 1). Collectively, we assessed the relative
contribution of temperament and nutritional state to behaviour
exhibited in a single context (capture and handling) across three
species. Considering behavioural responses, whether associated
with temperament or nutritional condition, can hold fitness con-
sequences, comprehending the factors influencing behaviour dur-
ing capture can contribute to a better understanding of selection
pressures on life-history strategies.
METHODS
Study Area
We sampled female mule deer, bighorn sheep and elk from
several populations in western Wyoming, U.S.A. Sampling efforts
were part of long-term work studying females to understand
population level processes. Populations were distributed across the
Wyoming Basin and Middle Rocky Mountains physiographic re-
gions (Fenneman, 1917) and occupied portions of the southern
Greater Yellowstone Ecosystem. We captured mule deer from the
Wyoming and Salt River ranges (42

18
0
21
00
N, 110

42
0
5
00
W) and the
Greater Little Mountain Ecosystem (41

4
0
43
00
N, 109

3
0
46
00
W), big-
horn sheep from the Wind River Range (43

26
0
11
00
N, 109

33
0
5
00
W)
and Gros Ventre Range (43

34
0
26
00
N, 110

35
0
12
00
W) and elk from
the Greater Little Mountain Ecosystem. Public land management
designations included mixed-use (Bureau of Land Management,
U.S. Forest Service, Wyoming, U.S.A.) and wilderness areas (U.S.
Forest Service). Private lands were managed for grazing, wildlife
habitat and energy development. The study area varied from arid to
semiarid, with mean annual precipitation between 2.2 and 81.7 cm
(PRISM Climate Group, 30-year normal 1981e2020, https://prism.
oregonstate.edu/normals). Our study area ranged from high
desert ecosystems at the lowest and driest sites (~2000 m) to high-
elevation alpine ecosystems (~3600 m). Diversity in vegetation
followed the variation in moisture regimes and elevation: high
desert regions were dominated by shrubs (primarily Wyoming big
sagebrush, Artemisia tridentata, mountain big sagebrush,
A. tridentata vaseyana, and saltbush-greasewood (Sarcobatus spp.));
montane regions included pine-fir forests, quaking aspen, Populus
tremuloides, stands and subalpine tall forb communities; the
highest elevations were characterized by alpine meadows, rocky
outcrops, glaciers and permanent snowfields (LANDFIRE, 2016).
Summers were short and dry (5.5e19.6

C; PRISM Climate Group,
30-year normal 1981e2020), with long and often severe winters
(10e5.6

C; PRISM Climate Group, 30-year normal 1981e2020).
Predators within our study area included mountain lions, Puma
concolor, coyotes, Canis latrans, bobcats, Lynx rufus, black bears,
Ursus americanus, grizzly bears, Ursus arctos, and grey wolves, Canis
lupus. Finally, human presence in our study area included on-road
and all-terrain vehicles, horseback and foot travel. Only foot or
horseback travel is authorized in areas designated as wilderness.
Hunting of female deer was permitted only by youth during archery
season, and harvest of male mule deer occurred yearly from 1
September to mid-October. Female sheep experienced no direct
hunting pressure. Hunting of female elk was permitted with vari-
able regulation from 1 September to 31 December.
Capture Methods
We captured adult female mule deer, bighorn sheep and elk
using helicopter net-gunning each spring (MarcheApril) and
autumn (NovembereDecember) as part of a series of long-term
studies. The same helicopter capture crew was used for all cap-
ture events, and crew personnel were experienced in the capture
and piloting process for these ungulate species. We captured elk
from 2015 to 2019, mule deer from 2013 to 2021 and bighorn sheep
from 2015 to 2021. Captured animals were hobbled, blindfolded
and ferried to a processing location, usually within 5 km of the
capture location. Transport of animals occurred quickly and effi-
ciently; >95% of deer were moved from their capture location to the
staging area in under 5 min. Transport times occasionally could
exceed 5 min depending on weather to ensure animal and human
safety. We did not use chemical immobilizing drugs or sedatives
during capture or handling. We carried captured animals on a litter
to a rubber mat for processing. Once the animal was placed on the
mat, the data recorder and those assisting counted the number of
kicks by that restrained animal until processing was complete and
the animal was relocated to be released or ferried back to the
capture location. We defined a kick as a rapid, outward movement
of the legs. Although we acknowledge that there may have been
some variation in the consistency of recording kicks, and some may
have been missed, we sought to be diligent in recording and
anticipate the kicks recorded at least index the frequency of kicks
by an animal during handling.
We fitted captured animals with GPS radiocollars (Advanced
Telemetry 155 Systems, Inc., Isanti, Minnesota, U.S.A. or Vectronics
Aerospace, Berlin, Germany) and assigned each animal a unique
animal identification number. For all captures after 2016, animals
received an intravenous pain reliever-fever reducer (flunixin
meglumine; 50 mg/ml; Prevail, VetOne, Boise, ID, U.S.A.). We
monitored rectal temperature at roughly 5 min intervals
throughout the handling process with a hand-held thermometer
(Vicks SpeedRead Digital Thermometer, Procter &Gamble, Cin-
cinnati, OH, U.S.A.). We treated animals with elevated body tem-
perature (40

C for elk and deer, 40.56

C for sheep) with cold
water administered externally on the body's trunk, internally with
an enema, or using both methods. We measured heart rate and
oxygen saturation with a pulse oximeter on the outer rectal tissue
(Ohmeda Tuffsat, General Electric Healthcare, Chicago, IL, U.S.A.).
We measured body mass with an electronic platform or hanging
scale. We collected morphometrics, faecal pellets and blood sam-
ples on all study animals as part of the long-term studies. We
collected nasal and tonsil swabs for disease monitoring in bighorn
sheep. During spring captures, we used ultrasound to determine
the pregnancy status of all three species (Stephenson et al., 1995)
and fitted pregnant animals with vaginal implant transmitters
(Advanced Telemetry Systems, Isanti, MN, U.S.A. and Vectronic
Aerospace, Coralville, IA, U.S.A.; Bishop et al., 2007;Monteith et al.,
2014). We used horn annuli to age bighorn sheep (Geist, 1966). To
measure age using cementum annuli (Maton's Laboratory, Mill-
town, MT, U.S.A.), we extracted an incisiform canine from deer
(Swift et al., 2002). We extracted a vestigial canine from elk during
the first capture of each individual.
We evaluated the nutritional condition of animals by estimating
ingesta-free body fat (i.e. IFBFat). We estimated IFBFat using stan-
dardized approaches for mule deer, elk and bighorn sheep based on
H. N. Abernathy et al. / Animal Behaviour 221 (2025) 123056 3

body palpation and depth of rump fat measured via ultrasonogra-
phy (mule deer and elk: Cook et al., 2007,2010; bighorn sheep:
Stephenson et al., 2020). We measured the maximum depth of
subcutaneous fat at the thickest point cranial to the tuber ischium
by plucking hair to expose skin and running the ultrasound probe
(5 MHz transducer; Ibex Pro, E.I. Medical Imaging, Loveland, CO,
U.S.A.) against the exposed skin. To determine body condition via
palpation, we palpated the sacrosciatic ligament, caudal vertebrae
and sacrum (mule deer and elk: Cook et al., 2007,2010; bighorn
sheep: Stephenson et al., 2020).
Ethical Note
Capture and handling techniques of animals were performed by
trained personnel following guidelines from the American Society
of Mammologists (Sikes et al., 2019), approved by the University of
Wyoming Animal Care and Use Committee (protocol numbers
20171027KM0024-01, 20170404KM00270-02, 20180305KM0029
6-01, 20180305KM00296-02, 20180305KM00296-03 and 202103
03KM00463-01) and permitted by Wyoming Game and Fish
Department Chapter 33 (permit numbers 1278, 1038 and 1115). We
limited helicopter chase times to <5 min to reduce exertion before
handling. We captured study animals in their environment using
helicopter net gunning, transported them to a nearby processing
station and released them back to their environment. No animals
were housed or kept in captivity. Handling times were similar
among mule deer (mean ±SD ¼17.2 ±7.1 min, range 5e85 min),
bighorn sheep (20.7 ±12.9 min, range 7e83 min) and elk (16.1 ±6.7
min, range 7e52 min). We positioned study animals on their left
side to prevent ruminal tympany and aspiration of rumen. We
monitored vital rates (heart rate, respiratory rate, oxygen satura-
tion, rectal temperature). There were limited instances when ani-
mals arrived at the processing location showing abnormal signs of
distress (i.e. excessive panting). Excessive panting was typically
associated with an elevated body temperature, the primary physi-
ological marker of distress during capture and handling. We
intervened to treat elevated body temperature (40

C for elk and
deer, 40.56

C for sheep) by administering cold water to the body
or internally with an enema. Our primary variable of interest,
kicking during handling, can be perceived as a sign of distress but
this is unsubstantiated and provides motivation for the present
work. For all animals captured after 2016, we treated elevated
temperature and discomfort associated with capture with an
analgesic and antipyretic (flunixin meglumine). During captures
that involved tooth extraction, we hastened clotting with a hae-
mostatic gelatin sponge and used antimicrobial (tulathromycin)
and anaesthetic (lidocaine, bupivacaine) injections to prevent
infection and treat discomfort. All GPS radiocollars were <2% of
animal body weight. Overall, capture-related mortality (direct and
indirect) was low (<2%; Wagler et al., 2022;LaSharr et al., 2023).
Following capture, we did not perform observations, manipulations
or experiments for this study.
Statistical Methods
We evaluated individual temperament using a repeatability
measure. Repeatability (i.e. intraclass correlation coefficient) is
quantified as the proportion of variance that can be attributed to
the variance between animals and, thus, is estimated using both
within-animal and between-animal variance estimates (equation
1)(Nakagawa et al., 2017;Nakagawa &Schielzeth, 2010,2013).
Estimates of repeatability range from 0 to 1 and are considered low
from 0 to 0.3, moderate from 0.3 to 0.5 and high from 0.5 to 1
(Falconer, 1996). In equation (1), we let
s
2w
denote within-animal
variance and
s
2B
denote between-animal variance.
Repeatability ¼
s
2
B
.
s
2
B
þ
s
2
W
(1)
We used the ratio of within-animal to between-animal variance
components derived from generalized linear mixed-effects models
with a Poisson distribution and a random intercept for individuals.
Previous research has suggested that habituation to capture and
age may influence behaviour (Wheat &Wilmers, 2016). Moreover,
ungulates may have high within-animal variance in IFBFat (Smiley
et al., 2022a). Therefore, we accounted for the influence of IFBFat,
number of captures and age by including these as fixed effects in
each model. Variance explained by fixed effects was retained as a
component of the total within-animal and between-animal vari-
ance estimates (i.e. denominator of equation 1; sensu Stoffel et al.,
2017).
Poisson regression models assume that the mean and variance
of the response variable are equal (i.e. equidispersion;
Fathurahman, 2023). Thus, the number of kicks observed is ex-
pected to follow a Poisson distribution, where the kicking rate per
unit time is the parameter of interest. Considering that observation
periods differed between animals, the total number of kicks natu-
rally varied with the length of the observation period. Therefore, we
included the log-transformed capture time by offsetting the num-
ber of kicks with a log transformation of handling time. This offset
ensured that the model standardized the counts to a per-unit-time
rate, normalizing the data across varying observation periods and
ensuring the analysis aligned with the Poisson framework's as-
sumptions (Montesinos-L
opez et al., 2020). We implemented the
same model structure for mule deer, bighorn sheep and elk,
generating three species-specific models. We limited our calcula-
tion of within-animal variance to animals captured more than once
but retained all individuals in our calculation of between-animal
variance to improve this estimate.
We implemented our models of repeatability of kicks/min of
handling time using the ‘rptR’package (Stoffel et al., 2017)inpro-
gram R (R Core Team, 2023). We calculated 95% confidence in-
tervals and likelihood ratio test statistics for each model based on
1000 bootstrap iterations. Repeatability estimates are reported on
the log link scale because repeatability on the original scale would
represent measurements' precision rather than variation explained
by random effects (Stoffel et al., 2017).
To further ascertain whether animal attributes outside of tem-
peraments could explain the rate of kicks, we also evaluated
whether nutritional condition was associated with behaviour using
simple linear regression. Linear regressions examined the influence
of IFBFat, number of captures and age on the observed kicks/min
without a unique animal identification number (AID). Including the
unique AID in our analysis would essentially be equivalent to
conducting a repeatability analysis, as both approaches account for
within-animal variation. We used a similar modelling approach to
the repeatability analysis, treating the observed number of kicks/
min of handling time as the response variable. We fitted the same
models for each of the three species.
RESULTS
We had 265 bighorn sheep capture events of 102 adult females,
with 65.6% being captured more than once, 1139 mule deer capture
events of 354 adult females, with 74.0% being captured more than
once, and 122 elk capture events of 51 adult females, with 72.5% of
animals being captured more than once. Within-animal variance
was calculated from animals captured more than once, while
between-animal variance includes animals from all capture events.
On average, bighorn sheep were captured 2.6 times (range 1e
7),
mule deer 3.2 times (range 1e13) and elk 2.4 times (range 1e5). On
H. N. Abernathy et al. / Animal Behaviour 221 (2025) 1230564

average, bighorn sheep were 6.9 years old (range 1e14 years), mule
deer were 6.8 years old (range 1e15.5 years) and elk were 7.6 years
old (range 2e16 years). On average, bighorn sheep had 11.30%
IFBFat (range 0.48e31.70%), mule deer had 7.20% IFBFat (range
0.03e25.20%) and elk had 5.85% IFBFat (range 1.52e12.70%).
Repeatability of kicks/min of handling time was greatest for
bighorn sheep (0.511, 95% CI [0.347, 0.636]; Table 1,Fig. 2), followed
by mule deer (0.393 [0.318, 0.457]; Table 1,Fig. 2), and lowest for
elk (0.019, [0.000, 0.208]; Table 1,Fig. 2). Thus, kicks/min of
handling time were highly repeatable (i.e. range 0.5e1) in bighorn
sheep, moderately repeatable in mule deer (i.e. 0.3e0.5) and not
repeatable in elk (i.e. 0e0.3) (Falconer, 1996). Average kicks/min of
handling time was highest for mule deer, followed by elk and then
bighorn sheep (Table 1).
Within our repeatability analysis, IFBFat, number of captures
and age explained little of the variance in kicks/min of handling
time for all three species (Table 1). Nevertheless, because of the low
repeatability in kicks/min for elk, these fixed effects explained
more of the variance than animal identity (Table 1). The within-
animal variance was greatest for bighorn sheep (1.431, 95% CI
[0.794, 2.064]), followed by mule deer (0.572, [0.419, 0.704]) and
then elk (0.029, [0.000, 0.311]).
The results of our linear models were consistent with the
repeatability analysis in that IFBFat, number of captures and age
explained little of the variance in kicks/min of handling time
(Table 2). Each time a bighorn sheep or mule deer was captured, the
number of kicks/min increased by 0.05 (95% CI [0.0058, 0.0866],
t
261
¼2.254, P¼0.03) and 0.02 ([0.0032, 0.0283], t
113 5
¼2.459, P¼
0.01) respectively, but our models had virtually no explanatory
power (R
2
<0.02) for all species (Table 2).
DISCUSSION
We assessed how temperament and nutritional state influenced
behaviour in three species of long-lived, iteroparous ungulates.
Table 1
Repeatability for female bighorn sheep, mule deer and elk in Wyoming, U.S.A. (2013e2021)
Species Mean Individual repeatability Variance explained by fixed effects repeatability
Estimate 2.5% CI 97.5% CI Estimate 2.5% CI 97.5% CI
Bighorn sheep 0.442 0.511 0.347 0.636 0.075 0.052 0.159
Mule deer 0.534 0.393 0.318 0.457 0.109 0.099 0.135
Elk 0.455 0.019 0.000 0.208 0.107 0.079 0.237
Included are the average kicks/min (unscaled), repeatability estimates (link scale) for both individual animals (individual repeatability) and variance explained by fixed effects
(IFBFat, number of captures, age) with 95% confidence intervals. Variance explained by the fixed effects was retained as a component of the total within-animal and between-
animal variance estimates (i.e. denominator of equation 1; sensu Stoffel et al., 2017).
0
0
4
8
12
22
Density
26
0.2 0.4
Bootstra
p
re
p
eatabilit
y
estimates
0.6
Species Elk Mule deer Bighorn sheep
Figure 2. Density plots of bootstrapped repeatability estimates of kicks/min of handling time for elk, mule deer and bighorn sheep captured in western Wyoming, U.S.A. between
2013 and 2021. Repeatability is represented by the colour-coded dot and 95% confidence intervals are represented with the thin, solid line. Please note the broken Yaxis.
Table 2
Model output from our linear regression analysis
Species Estimate 2.5% CI 97.5% CI P
Bighorn sheep Intercept 0.332 -0.018 0.682 0.063
Nutritional condition 0.005 -0.014 0.024 0.609
Age -0.016 -0.056 0.024 0.432
Number of captures 0.046 0.006 0.087 0.025
Mule deer Intercept 0.459 0.354 0.563 <0.001
Nutritional condition 0.004 -0.004 0.012 0.325
Age -0.004 -0.016 0.009 0.544
Number of captures 0.016 0.003 0.028 0.014
Elk Intercept 0.680 0.280 1.079 0.001
Nutritional condition -0.018 -0.070 0.034 0.493
Age -0.006 -0.037 0.024 0.692
Number of captures -0.022 -0.090 0.047 0.533
Kicks/min handling time as a function of nutritional condition (percentage of
ingesta-free body fat), age and number of captures for female bighorn sheep, mule
deer and elk in western Wyoming, U.S.A. between 2013 and 2021. Significant out-
comes are shown in bold.
H. N. Abernathy et al. / Animal Behaviour 221 (2025) 123056 5

Kicks/min were repeatable in mule deer and bighorn sheep
(Table 1), supporting the hypothesis that behavioural responses
during capture were trait-like and, thus, evidence of temperament
(Hypothesis 1). In elk, however, behavioural responses to capture
were not repeatable and, therefore, likely not trait-like (Table 1).
Contrary to our hypothesis, we found little evidence for state-like
responses as the nutritional state of an individual had minimal
influence on kicks/min for all species (Hypothesis 2) despite
capturing animals across a range of ages and nutritional states
(Table 2). Overall, our findings suggest behavioural responses in a
single context (i.e. kicks/min in response to handling) were trait-
like rather than state-like. However, we cannot dismiss other
state-dependent processes or experiences during capture and
transport. Trait-like responses or lack thereof may instead be
influenced by the site-specific ecological niches to which these
species have adapted (western and southern Wyoming; Morrison
et al., 2021;Sawyer et al., 2019). Our findings emphasize that it is
important to exercise caution when generalizing behavioural
findings, especially among taxonomically related species, because
of inconsistencies observed across species. This cautionary note is
akin to the one expressed in discussions about overgeneralizing
migratory behaviour among ungulates (Morrison et al., 2021;
Sawyer et al., 2019).
Consistent individual differences in trait-like responses across
various situations, known as personality (Gosling, 2001), behav-
ioural syndromes (Sih et al., 2004) or temperament (R
eale et al.,
2007), have been observed in many species. These terms collec-
tively describe the extent of behavioural consistency resulting from
a combination of factors, including genetics, development, envi-
ronment and life experiences (Stamps, 2016;Stamps &Biro, 2016).
Conversely, behavioural plasticity occurs when organisms modify
behaviours to match their physiological state and environment
(Levins, 1968), which should lead to optimal behavioural responses
in the face of changing conditions. Given our study occurred in a
highly seasonal, temperate landscape, where vegetative greening
occurs at regular intervals over time, it might stand to reason that
behavioural plasticity should emerge in these herbivores. Yet, we
detected trait-like responses in mule deer and bighorn sheep but
behavioural plasticity in elk, irrespective of nutritional state. This
finding may be linked to the specific behavioural response we
measured (kicking during capture and handling), which represents
a reaction to a relatively novel and unpredictable stimulus. While
we acknowledge that our study focused on a single type of
behavioural response, which could limit the scope of our conclu-
sions, this response is relevant for understanding both trait-like
and state-like behaviours.
Struggle during capture and handling, although singular in
measure, provides insight into the broader, more consistent ge-
netic, trait-like response pattern among individuals (David et al.,
2011;Jones, 1996;Nelson et al., 2020). Much like the boldeshy
continuum in animal personalities, responses to stressors vary
along a passiveeactive continuum. Passive avoidance occurs when
animals show less physical resistance to handling (Carere &van
Oers, 2004;David et al., 2011;Nelson et al., 2020), while active
responses occur when animals react to stressful situations with a
higher frequency of struggling (Carere &van Oers, 2004;David
et al., 2011;Nelson et al., 2020). Predator avoidance and migra-
tion tactics in large ungulates vary in response to individual per-
sonality and operate under the same physiological pathways
correlated with a stress response (Bonnot et al., 2018;Found &St
Clair, 2019;Koolhaas, 2008). Therefore, we posit that consistency
in response to a stressor, as observed here, might underlie broad
patterns in behavioural consistency in bighorn sheep and mule
deer and be associated with ecosystem-specific adaptations to
avoid predation or track forage. For example, depending on their
position along the shyebold continuum, individual roe deer, Cap-
reolus, adopted contrasting habitat use tactics for forage and pre-
dation risk (Bonnot et al., 2018). In our study area, mule deer
demonstrate strong fidelity to seasonal ranges and migration
routes (Morrison et al., 2021;Sawyer et al., 2019; Wyckoff et al.,
2018), partly owing to their knowledge of risk and forage (Brown
et al., 2020; Morrison et al., 2021). Therefore, trait-like responses
might be favoured because they are adaptive to navigate risks and
forage in this system. However, behavioural responses predomi-
nantly guided by memory may be inflexible compared with those
shaped by social learning or environmental cues (Tello-Ramos et al.,
2019) and could compound the tendency of these animals to
exhibit trait-like responses (Bracis &Mueller, 2017).
Similarly, broad patterns of behavioural consistency in bighorn
sheep could be associated with predator avoidance strategies.
Predator avoidance is a major factor influencing behaviour and
habitat selection in bighorn sheep (DeCesare &Pletscher, 2006;
Smith et al., 1991). To minimize predation risk, bighorn sheep
consistently use escape terrain such as cliffs and steep hillsides
(DeCesare &Pletscher, 2006;Morrison et al., 2021;Smith et al.,
1991). Behavioural consistency in selecting escape terrain benefits
bighorn sheep because using these areas decreases predation risk
(Jones et al., 2022). Just as risk might favour the development of
behavioural consistency in antipredator behaviour, it can also
favour specific temperaments. For example, across a 25-year study,
years with high predation favoured bighorn sheep females with
‘bold’temperaments (i.e. bold and nondocile individuals). In
contrast, in years with low predation, there was no evidence of
selection based on temperament traits (R
eale &Festa-Bianchet,
2003). These forms of behavioural consistency likely benefit big-
horn sheep and mule deer by increasing access to forage or
reducing predation risk (Bleich et al., 1997; Brown et al., 2020;
Forrester et al., 2015;Gehr et al., 2020;Morrison et al., 2021; Young
&Isbell, 1991); therefore, trait-like responses to stressors are likely
adaptive for bighorn sheep and mule deer, and more broadly
improve fitness in the face of ecological challenges in our system
(Bleich et al., 1997; Brown et al., 2020; Forrester et al., 2015;Gehr
et al., 2020;Morrison et al., 2021; Young &Isbell, 1991).
However, our findings suggest that elk, unlike mule deer and
bighorn sheep, exhibit less consistent behaviour in response to this
stimulus. This unexpected plasticity in elk aligns with broader
species-specific patterns, suggesting that elk may adopt more
flexible behavioural strategies that are neither trait-like nor state-
like, potentially due to different ecological pressures or adaptive
needs (Eggeman et al., 2016;Sawyer et al., 2019). Elsewhere, it has
been emphasized that elk behaviour typically depends on prior
experience and prevailing environmental conditions (Barker, 2018;
Gower et al., 2008;Morrison et al., 2021). Indeed, among mule deer,
bighorn sheep and elk, only elk differed in their optimal ranging
behaviour based on prior experiences (Morrison et al., 2021). In
contrast to mule deer, elk adjusted their annual movements in
response to their previous spring's success in tracking food re-
sources, indicating a ‘winestay, loseeswitch’approach (Morrison
et al., 2021). The behavioural plasticity of elk is broadly recog-
nized across contexts, including plasticity in migratory and social
behaviour (Barker, 2018;Gower et al., 2008). This has been attrib-
uted to the underlying neural framework of elk that promotes
learning through experience, allowing for high cognitive flexibility
(Tello-Ramos et al., 2019). Therefore, high behavioural plasticity in
response to novel stimuli by elk might be connected to a species
level inclination towards flexibility and low adult predation pres-
sure or could be explained by unmeasured aspects of animal state.
However, it is important to note a specific limitation regarding elk
in our study, which involved a relatively small sample size of 51
individuals. Female elk can exhibit a broad spectrum of
H. N. Abernathy et al. / Animal Behaviour 221 (2025) 1230566

temperaments (Found, 2015), with a small but notable fraction (~1
in 100) displaying highly aggressive tendencies (B. Surlock, per-
sonal communication). Despite this, our analysis yielded a normal
distribution of observations (i.e. bell-curve distribution of kicks
across individuals) in behavioural responses (kicks) among the
observed individuals. Thus, including additional animals in the
study would likely not have substantially altered the results.
Across three closely related species of large ungulates, our study
highlights discernible differences in individual temperaments
revealed through their capture and handling responses. Specif-
ically, repeatability in the behavioural responses of deer and big-
horn sheep suggests an intrinsic predisposition towards stressors,
providing them with advantages when navigating predators or
unpredictable situations or environments (R
eale et al., 2007;Sih
et al., 2004). In contrast, the behaviour of elk lacked the consis-
tency seen in the other two species, reflecting outcomes of their
localized ecosystem in southwestern Wyoming, which is under-
pinned by their relatively flexible neural framework. Our findings
underscore the possibility that the observed behavioural patterns
in these species may be driven by a complex interplay of
ecosystem-specific constraints, species level neurological charac-
teristics and the unique selection pressures they face within their
localized system.
Investigations into animal temperament or personality traits
often grapple with methodological challenges, including acquiring
independent and repeatable personality assessments for in-
dividuals and considering their nutritional state (Wachs et al.,
2005). Nevertheless, our results mark an encouraging initial step
towards bridging the gap between behavioural responses during
animal capture and temperament in large herbivores, offering a
valuable framework for future studies. In a broader context, our
work contributes to a deeper understanding of the mechanisms
governing behavioural responses to stimuli. It holds promise to
refine management and conservation strategies as climate change
and land use modification continue to alter environments.
Author Contributions
Heather N. Abernathy: Writing ereview &editing, Writing e
original draft, Supervision, Project administration, Methodology,
Investigation, Data curation, Conceptualization. Rebecca L. Levine:
Writing ereview &editing, Writing eoriginal draft, Supervision,
Project administration, Investigation, Conceptualization. Yasaman
N. Shakeri: Writing ereview &editing, Writing eoriginal draft,
Investigation, Conceptualization. Jaron T. Kolek: Writing ereview
&editing, Writing eoriginal draft, Visualization, Software, Meth-
odology, Investigation, Formal analysis, Data curation. Brittany L.
Wagler: Writing ereview &editing, Writing eoriginal draft,
Validation, Software, Resources, Methodology, Investigation, Data
curation. Rachel A. Smiley: Writing ereview &editing, Writing e
original draft, Investigation, Data curation. Rhiannon P. Jakopak:
Writing ereview &editing, Writing eoriginal draft, Investigation,
Data curation, Conceptualization. Mitchell J. Brunet: Writing e
review &editing, Writing eoriginal draft, Visualization, Investi-
gation. Rebekah T. Rafferty: Writing ereview &editing, Writing e
original draft, Investigation, Data curation. Seth T. Rankins:
Writing ereview &editing, Writing eoriginal draft, Investigation.
Katey S. Huggler: Writing ereview &editing, Investigation, Data
curation. Brandon Scurlock: Writing ereview &editing, Investi-
gation, Data curation. Jill Randall: Writing eoriginal draft, Inves-
tigation, Data curation. Daryl Lutz: Writing ereview &editing,
Investigation, Data curation. Alyson B. Courtemanch: Writing e
review &editing, Investigation, Data curation. Tayler N. LaSharr:
Investigation, Data curation. Samantha P.H. Dwinnell: Investiga-
tion, Data curation. Lee E. Tafelmeyer: Investigation. Patrick W.
Burke: Investigation. Patrick Lionberger: Investigation. Miguel
Valdez: Investigation. Gary L. Fralick: Investigation. Doug
McWhirter: Investigation. Kevin L. Monteith: Writing ereview &
editing, Writing eoriginal draft, Supervision, Software, Resources,
Project administration, Methodology, Investigation, Funding
acquisition, Conceptualization.
Data Availability
Data used for analyses are stored in the Dryad Digital Re-
pository; https://doi.org/10.5061/dryad.95x69p8rf.
Declaration of Interest
The authors declare no conflicts of interest.
Acknowledgments
We thank the many technicians, volunteers and former mem-
bers of the Monteith Shop who helped collect data. We thank R.
Garrott and P. J. White, the principal investigators for the Greater
Yellowstone Area Mountain Ungulate Project, who provided GPS
data from a portion of the Upper Shoshone Sheep population. We
thank G. Anderson, C. Class and H. Edwards for their support and
involvement with the project. We thank the Vercamack and Moon
families and other countless landowners who kindly offered access
to their property for this research. Support from Wyoming Game
and Fish Department, Wyoming Game and Fish Commission, Bu-
reau of Land Management, Muley Fanatic Foundation (including
Southwest, Kemmerer, Upper Green, and Blue Ridge Chapters),
Boone and Crockett Club, Shoshone &Arapaho Game and Fish,
Wyoming Wildlife and Natural Resources Trust, Knobloch Family
Foundation, Wyoming Animal Damage Management Board,
Wyoming Governor's Big Game License Coalition, Bowhunters of
Wyoming, Wyoming Outfitters and Guides Association, Pope and
Young Club, U.S. Forest Service, Native Range Capture Services, and
U.S. Fish and Wildlife Service made this research possible. Funding
for this study was provided by Bowhunters of Wyoming, Bureau of
Land Management, Muley Fanatic Foundation, U.S. National Science
Foundation, Rocky Mountain Elk Foundation, Safari Club Interna-
tional Foundation, Wyoming Animal Damage Management Board,
Wyoming Game and Fish Department, Wyoming Governor's Big
Game License Coalition, Wyoming Wildlife and Natural Resource
Trust, The Wild Sheep Foundation, U.S. Fish and Wildlife Service,
U.S. Forest Service, Shoshone &Arapaho Game and Fish, Teton
Conservation District, Wyoming Wild Sheep Foundation, Boone
and Crockett Club, Wyoming Outfitters and Guides Association,
Pope and Young Club, Knobloch Family Foundation and Blue Ridge
Chapters.
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