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Stress-Hormone Levels of Wolves in Relation to Breeding Season, Pack Size, Human Activity, and Prey Density

  • Bieszczadzki National Park, Poland

Abstract and Figures

Human disturbance is thought to be a major source of stress for animals but breeding status, social interactions and food availability are also potential sources. Long-lasting stress may adversely affect the fitness of animals and for that reason the evaluation of stressors is important for conservation of threatened species. The aim of our study was therefore to assess which factors cause stress in wolves (Canis lupus). We evaluated the stress levels of wolves from six packs by measuring the concentration of glucocorticoid metabolites in 59 faecal samples with a Cortisol enzyme-immunoassay. During the breeding season, stress hormone concentration was higher than during the rest of the year, with two peaks around mating and begin of denning, respectively. Multiple regressions ranked by AIC showed that breeding had the highest impact on the wolves' stress levels, followed by human activity, pack size, and prey density. We conclude that human activity is only one of several factors contributing to stress in wolves and that intraspecific competition during breeding is likely to cause elevated levels of glucocorticoids.
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Ann. Zool. Fennici  
 
1)Section Biology, Faculty of Science and Technology, University of Siegen, Adolf-Reichwein-
Str. 2, D-57068 Siegen, Germany (corresponding author’s e-mail:
2)Museum and Institute of Zoology, Polish Academy of Sciences, ul. Wilcza 64, PL-00-679
Warsaw, Poland
3)Bieszczady National Park, PL-38-713 Lutowiska 2, Poland
)State Forest Superintendency of Suchedniów, ul. Bodzentyńska 16, PL-26-130 Suchedniów,
Received 5 July 2012, nal version received 20 Nov. 2012, accepted 1 Feb. 2012
 
Ann. Zool.
Human disturbance is thought to be a major source of stress for animals but breeding
status, social interactions and food availability are also potential sources. Long-lasting
stress may adversely affect the tness of animals and for that reason the evaluation of
stressors is important for conservation of threatened species. The aim of our study was
therefore to assess which factors cause stress in wolves (Canis lupus). We evaluated
the stress levels of wolves from six packs by measuring the concentration of glucocor-
ticoid metabolites in 59 faecal samples with a cortisol enzyme-immunoassay. During
the breeding season, stress hormone concentration was higher than during the rest of
the year, with two peaks around mating and begin of denning, respectively. Multiple
regressions ranked by AIC showed that breeding had the highest impact on the wolves’
stress levels, followed by human activity, pack size, and prey density. We conclude that
human activity is only one of several factors contributing to stress in wolves and that
intraspecic competition during breeding is likely to cause elevated levels of glucocor-
Centuries of wolf (Canis lupus) persecution
caused wolves to avoid humans (e.g. Thurber et
al. 1994, Theuerkauf et al. 2003a, 2003b), but
human presence does not necessarily mean that
it negatively impacts wolves. The long history
of wolf persecution has evolutionarily favoured
wolves that avoided humans but, at the same
time, has forced them to adapt to live and breed
in close proximity to them. This mixture of avoid-
ance and habituation seems to be the basis of
wolf-human coexistence in areas where wolves
occupy habitats with relatively high human activ-
ity (Theuerkauf et al. 2007). In such situations, it
is difcult to discriminate which kind of human
activity actually reduces tness of wolves and can
as such be regarded as a disturbance.
  Stress hormones in wolves 
An elevated level of glucocorticoids is a
physiological reaction allowing animals to
efciently hunt or ee. Prolonged elevation of
glucocorticoids, however, has serious negative
effects and is dened as chronic stress (McEwen
& Sapolsky 1995, Wingeld & Sapolsky 2003).
It has a considerable impact on virtually all
bodily functions and can disrupt reproduction,
alter the animal’s behaviour and cognition, and
degrade the performance of the animal’s immune
system, resulting in reduced resistance to disease
(McEwen & Sapolsky 1995, Wingeld & Sapol-
sky 2003). It is unknown which type of human
activity within the wolf environment can cause
chronic stress and adversely affect their tness.
Human recreational activity and snow sports
were shown to increase faecal glucocorticoids
in several mammalian species (Creel et al. 2002,
Taylor & Knight 2003, Arlettaz et al. 2007).
Such stress response suggests that human pres-
ence may cause prolonged stress in animals and
hence adversely affect their tness.
Wolves deal with human activity by tem-
porarily avoiding areas used by humans at that
particular moment (spatio-temporal segregation
as dened in Theuerkauf et al. 2003b). Another
possibility that allows wolves to live in the prox-
imity of humans without experiencing the nega-
tive consequence of permanent stress may be
habituation to human presence and subsequent
reduced stress response. However, empirically
little is known if these assumptions apply in
the wild, because no study so far measured the
actual levels of stress response by wolves in rela-
tion to varying intensities of human presence.
Glucocorticoids in scats were used as physi-
ological indicators of stress in a variety of spe-
cies (Touma & Palme 2005). As capture and han-
dling of the animals is omitted, stress measure-
ments from scats are unaffected by the observer
and thus reect the actual stress level of the
animal more accurately (Kotrschal et al. 1998).
Moreover, glucocorticoid metabolites in scats
are pooled over a certain period, determined
by gut passage time and dynamics of excre-
tion (Scheiber et al. 2005). Thus, hormone con-
centrations in scats represent an assessment of
chronic stress. For these reasons, we measured
faecal glucocorticoid metabolite concentrations
to assess stress levels of wolves noninvasively.
We aimed at assessing the effect of breeding,
pack size, prey abundance, and human activity
within six wolf pack home ranges on the stress
levels of wolves. We hypothesised that human
activity would not be the major factor inuenc-
ing stress in wolves.
This study was conducted in two distinct areas.
One was situated in the southeast of Poland,
in the Bieszczady Mountains (49°19´–49°50´N,
22°15´–22°45´E). We took faecal samples of
ve wolf packs that inhabited an area of about
1000 km2 (Eggermann et al. 2009). The second
region (250 km2) was situated in the Holy
Cross Forest (Puszcza Świętokrzyska) in cen-
tral Poland (51°02´N, 20°44´E). Here, we took
faecal samples of a wolf pack that was discov-
ered only in 2006, which was the rst record of
wolves in this region since they were extirpated
in 1953 (Gula 2008a, 2008b).
We collected faecal samples incidentally in
2004 and 2005 (n = 4), but carried out a system-
atic scat survey from March 2006 to March 2007
(n = 55). We searched for scats along randomly
selected transects on roads or tracks throughout
the study area. During summer and autumn,
only fresh (still humid) scats were collected to
avoid microbial fermentation (Khan et al. 2002).
Samples were frozen within a few hours after
collection and stored at –20 °C until analysis, as
recommended by Hunt and Wasser (2003). As
we did not assign faecal samples to individual
wolves, we might have sampled some wolves
more often than others.
We extracted metabolites from the scats fol-
lowing the protocol by Schatz and Palme (2001).
They yielded the highest amount of metabolites
(about 70%) with 80% methanol. For the meas-
urement of glucocorticoid metabolite concentra-
tions, we used a cortisol enzyme immunoassay
developed by Palme and Möstl (1997), which
was validated in the red wolf Canis rufus (Young
et al. 2004) and the dog Canis lupus familiaris
(Schatz & Palme 2001).
To detect potential seasonal variation, we
grouped faecal samples in ve periods and cal-
culated mean glucocorticoid metabolite concen-
 Eggermann et al.  
trations for each of them. During the breed-
ing season we chose shorter intervals, to reveal
potential peaks connected to breeding. Based on
their sampling date, we classied faecal samples
as collected during the breeding period (Febru-
ary–May) or the non-breeding period (June–
December). We considered pack size as the max-
imum number of wolves seen or snow-tracked
(Gula 2008c) during the same year we collected
the scats. We calculated prey abundance within
the home ranges of each pack as the sum of
harvest densities of ungulates (red deer Cervus
elaphus, roe deer Capreolus capreolus and wild
boar Sus scrofa; data provided by local hunting
authorities), which are the main prey of wolves
in the study areas (Gula 2004). We calculated
home ranges as MCP (minimum convex poly-
gon) of multiannual radio telemetry locations or
multiannual snow tracking data (Gula 2008c).
A magnetic trafc counter (NC-30 NU-met-
rics, Uniontown, Pennsylvania, USA) recorded
the trafc on roads within the home ranges.
We assigned roads in each MCP to four classes
(1–500, 501–5000, 5001–10 000 and more than
10 000 vehicles per week) according to the
recorded intensity of trafc. We then calculated
the road density of each class (km km–2) for
every home range and multiplied it by the aver-
age trafc in each class. We calculated a trafc
index for each pack by summing up the calcu-
lated trafc values for each road class (Table 1).
We used multiple linear regression models
(SPSS ver. 19), with the level of stress hormones
in individual wolf scats as a response variable
and breeding, pack size, prey density, and traf-
c index as predictor variables. Breeding was
entered as a nominal (0/1) variable whereas the
other three parameters were metric. We then
ranked the models by Akaike weights (w) (Burn-
ham & Anderson 2002) to assess which of the
four parameters inuenced stress hormone levels
the most. We log-transformed hormone concen-
trations for the regression analyses, because they
were not normally distributed. All means are
provided with 95% condence intervals (CI).
The mean glucocorticoid metabolite concentra-
tion of individual scats was 11.4 ± 2.8 (CI) ng g–1
of fresh faecal mass and ranged from 0.6 ng g–1
to 53.9 ng g–1. Average hormone concentrations
varied among wolf packs from 8.5 ng g–1 to
16.3 ng g–1 (Table 1). Glucocorticoid metabolite
concentrations peaked during mating and at the
beginning of denning (Fig. 1). Breeding was the
highest-ranking factor (Table 2) inuencing log-
transformed levels of glucocorticoid metabolites
(sum of Akaike weights: 0.60), followed by
trafc index (0.53), pack size (0.40), and prey
density (0.35).
Despite the intensive trafc, high density of roads
and a human density of 36 inhabitants per km
(Theuerkauf et al. 2007) within the home ranges
of the studied packs, the levels of glucocorticoids
in wolf scats were most inuenced by breed-
ing. Breeding is a period of elevated aggression
among members of a wolf pack (Rabb et al.
1967, Zimen 1976). During this period, sexual
Table 1.
      
 
      
      
      
      
      
      
  Stress hormones in wolves 
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Cortisol concentration (ng g–1)
Table 2.Δ
  wΔ 
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
competition and the related aggression can even
trigger dispersal of young, but sexually mature,
wolves (Mech & Boitani 2003). Our data sug-
gest that social interactions among wolves cause
more stress than human presence in wolf habitat.
Therefore, we argue that human activity is not
the major factor inducing stress in wolves. These
ndings support earlier conclusions that wolves
living in areas with higher human densities might
habituate to human activity (Theuerkauf et al.
2003b, 2007). Habituation and a reduced stress
response is another indication for the behavioural
plasticity of wolves, such as high variation in
their daily activity patterns (Eggermann et al.
2009) and spatio-temporal avoidance of humans
(Theuerkauf et al. 2003b). We believe that behav-
ioural plasticity is a decisive adaptation, which
allowed wolves to survive in close proximity of
people as long as they are not persecuted.
Although our sample size was too small to
produce conclusive results, it seems that wolves
experience the highest stress in two periods of
the year: during the mating period in February
and at the start of the denning period. While
stress during the rst period is likely caused by
sexual competition and the resulting conicts,
it is more difcult to explain why the denning
induces stress. An explanation might be that
wolves need more effort than usual for hunting
to provide enough food for nursing females,
and later for the growing pups. Prey availability
along with pack size and human activity was one
of the factors that also contributed to the level of
stress hormones. While the impact of pack size
is likely to be explained by the intensity of social
interactions, with higher stress levels in larger
packs, the inuence of prey availability is related
to the level of difculties in hunting and subse-
Fig. 1.  
    n 
 n 
n 
  
    
  
   
 Eggermann et al.  
quent food stress. Prey abundance is also known
to determine the habitat selection by wolves (i.e.
Eggermann et al. 2011) and their activity pat-
terns (Theuerkauf 2009). However, under the
study conditions, it does not seem that prey
availability was an important factor for stress in
wolves. We conclude that mostly intrinsic factors
inuence the level of stress in wolves and that
human activity is less important.
This study was part of the Bieszczady Wolf Project funded
by the Polish National Committee for Scientic Research
(KBN 6P04F 006), budget of the Museum and Institute of
Zoology (Polish Academy of Sciences), SAVE — Wildlife
Conservation Fund and scholarships of the “Allgemeines
Promotionskolleg” of the Ruhr University of Bochum and
the Ruhr University Research School. We thank anonymous
reviewers for useful comments.
Arlettaz, R., Patthey, P., Baltic, M., Leu, T., Schaub, M.,
Palme, R. & Jenni-Eiermann, S. 2007: Spreading free-
riding snow sports represent a novel serious threat for
wildlife. — Proceedings of the Royal Society B 274:
Burnham, K. P. & Anderson, D. R. 2002: Model selection
and multi-model inference: a practical information-the-
oretic approach, 2nd ed. — Springer-Verlag, New York.
Creel, S., Fox, J. E., Hardy, A., Sands, J., Garrott, B. & Peter-
son, R. O. 2002: Snowmobile activity and glucocorticoid
stress responses in wolves and elk. — Conservation
Biology 16: 809–814.
Eggermann, J., da Costa, G. F., Guerra, A. M., Kirchner, W.
H. & Petrucci-Fonseca, F. 2011: Presence of Iberian
wolf (Canis lupus signatus) in relation to land cover,
livestock and human inuence in Portugal. — Mamma-
lian Biology 76: 217–221.
Eggermann, J., Gula, R., Pirga, B., Theuerkauf, J., Tsunoda,
H., Brzezowska, B., Rouys, S. & Radler, S. 2009: Daily
and seasonal variation in wolf activity in the Bieszczady
Mountains, SE Poland. Mammalian Biology 74:
Gula, R. 2004: Inuence of snow cover on wolf Canis lupus
predation patterns in Bieszczady Mountains, Poland. —
Wildlife Biology 10: 17–23.
Gula, R. 2008a: Legal protection of wolves in Poland: impli-
cations for the status of the wolf population. — Euro-
pean Journal of Wildlife Research 54: 163–170.
Gula, R. 2008b: Wolves Return to Poland’s Holy Cross Pri-
meval Forest. — International Wolf Magazine Spring
2008: 17–21.
Gula, R. 2008c: Wolf depredation on domestic animals in
the Polish Carpathian Mountains. — Journal of Wildlife
Management 72: 283–289.
Hunt, K. E. & Wasser, S. K. 2003: Effect of long-term preser-
vation methods on faecal glucocorticoid concentrations
of grizzly bear and African elephant. — Physiological
and Biochemical Zoology 76: 918–928.
Khan, M. Z., Altmann, J., Isani, S. S. & Yu, J. 2002: A matter
of time: evaluating the storage of faecal samples for ster-
oid analysis. — General and Comparative Endocrinol-
ogy 128: 57–64.
Kotrschal, K., Hirschenhauser, K. & Möstl, E. 1998: The
relationship between social stress and dominance is
seasonal in greylag geese. Animal Behaviour 55:
McEwen, B. S. & Sapolsky, R. M. 1995: Stress and cogni-
tive function. Current Opinion in Neurobiology 5:
Mech, L. D. & Boitani, L. 2003: Wolf social ecology. — In:
Mech, L. D. & Boitani, L. (eds.), Wolves: behaviour,
ecology and conservation: 1–34. University of Chicago
Press, Chicago, IL.
Palme, R. & Möstl, E. 1997: Measurement of cortisol metab-
olites in faeces of sheep as a parameter of cortisol con-
centration in blood. — Zeitschrift für Säugetierkunde
62: 192–197.
Rabb, G. B., Woolpy, J. H. & Ginsburg, B. E. 1967: Social
relationships in a group of captive wolves. American
Zoologist 7: 305–311.
Schatz, S. & Palme, R. 2001: Measurement of faecal cortisol
metabolites in cats and dogs: a non-invasive method
for evaluating adrenocortical function. Veterinary
Research Communications 25: 271–287.
Scheiber, I. B. R., Kralj, S. & Kotrschal, K. 2005: Sam-
pling effort/frequency necessary to infer individual acute
stress responses from faecal analysis in greylag geese
(Anser anser). Annals of the New York Academy of
Sciences 1046: 154–167.
Taylor, A. R. & Knight, R. L. 2003: Wildlife responses to
recreation and associated visitor perceptions. — Eco-
logical Applications 13: 951–963.
Theuerkauf, J. 2009: What drives wolves: fear or hunger?
Humans, diet, climate and wolf activity patterns. —
Ethology 115: 649–657.
Theuerkauf, J., Rouys, S. & Jędrzejewski, W. 2003a: Selec-
tion of den, rendezvous and resting sites by wolves in
the Białowieża Forest, Poland. — Canadian Journal of
Zoology 81: 163–167.
Theuerkauf, J., Jędrzejewski, W., Schmidt, K. & Gula, R.
2003b: Spatiotemporal segregation of wolves from man
in the Białowieża Forest (Poland). — Journal of Wildlife
Management 67: 706–716.
Theuerkauf, J., Gula, R., Pirga, B., Tsunoda, H., Eggermann,
J., Brzezowska, B., Rouys, S. & Radler, S. 2007: Human
impact on wolf activity in the Bieszczady Mountains, SE
Poland. — Annales Zoologici Fennici 44: 225–231.
Thurber, J. M., Peterson, R. O., Drummer, T. D. & Tho-
masma, S. A. 1994: Gray wolf response to refuge bound-
aries and roads in Alaska. — Wildlife Society Bulletin
22: 61–68.
  Stress hormones in wolves 
Touma, C. & Palme, R. 2005: Measuring faecal glucocorti-
coid metabolites in mammals and birds: the importance
of validation. Annals of the New York Academy of
Sciences 1046: 54–74.
Wingeld, J. C. & Sapolsky, R. M. 2003: Reproduction and
resistance to stress: when and how. Journal of Neu-
roendocrinology 15: 711–724.
Young, K. M., Walker, S. L., Lanthier, C., Waddell, W. T.,
Monfort, S. L. & Brown, J. L. 2004: Noninvasive moni-
toring of adrenocortical activity in carnivores by faecal
glucocorticoid analysis. — General and Comparative
Endocrinology 137: 148–165.
Ziemen, E. 1976. On the regulation of pack size in wolves.
Zeitschrift für Tierpsychologie 40: 300–341.
... The monthly variation in HCC predicted by the model is consistent with the annual life cycle of wolves and with the results of fecal glucocorticoid metabolites [34][35][36] . The highest HCC was found in the winter, at the start of the mating season 37 and could be a consequence of increased social instability related to sexual and territorial behavior 11,34 . ...
... Between May and October the HCC progressively increases which could be related to the growing effort to supply pups. The peak in HCC in October coincides with juveniles leaving their homesites and start travelling with the pack 36,39 . ...
... This is supported by the observation that causes of death with an expected duration of days to weeks do not translate in higher HCC, while the small number of wolves with chronic infections, particularly sarcoptic mange, showed the highest values. The reliability of this approach is further supported as the observed annual cycle of HCC is consistent with the levels of chronic stress inferred from the wolves' life cycle and other studies measuring fecal cortisol metabolites [34][35][36] . The sex and age patterns are also similar to those reported in other studies with wolves, measuring hair cortisol or fecal cortisol metabolites 15,[34][35][36] . ...
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The grey wolf (Canis lupus) persists in a variety of human-dominated landscapes and is subjected to various legal management regimes throughout Europe. Our aim was to assess the effects of intrinsic and methodological determinants on the hair cortisol concentration (HCC) of wolves from four European populations under different legal management. We determined HCC by an enzyme-linked immune assay in 259 hair samples of 133 wolves from the Iberian, Alpine, Dinaric-Balkan, and Scandinavian populations. The HCC showed significant differences between body regions. Mean HCC in lumbar guard hair was 11.6 ± 9.7 pg/mg (range 1.6–108.8 pg/mg). Wolves from the Dinaric-Balkan and Scandinavian populations showed significantly higher HCC than Iberian wolves, suggesting that harvest policies could reflected in the level of chronic stress. A significant negative relationship with body size was found. The seasonal, sex and age patterns are consistent with other studies, supporting HCC as a biomarker of chronic stress in wolves for a retrospective time frame of several weeks. Our results highlight the need for standardization of sampling and analytical techniques to ensure the value of HCC in informing management at a continental scale.
... Therefore, a link for pathogen transmission between groups is needed. It is known that solitary males approach females during the mating season, which is a highly stressful time (Eggermann et al. 2013). In addition, the mating season coincides with the main part of the hunting season, mainly in the form of driven hunts, which represents additional stress (Güldenpfenning et al. 2020). ...
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Aujeszky disease (AD) or pseudorabies is a viral disease of domestic and wild animals caused by the Suid alphaherpesvirus 1. In wild boar infection usually undergo latent phase but under certain conditions reactivation of the virus can result in a disease. Seroprevalence in wild boars ranges from 0.8 to 100%, and is among other influenced by region, type of management, age and sex of the studied animals. In this study we analyzed blood, lungs, olfactory bulbs and spleen from 222 free-living wild boars from different localities in Croatia and compared results obtained by ELISA with PCR, sex, age and locality. Total seroprevalence was 33.78%, ranging from 25.26% in males to 40.15% in females (p = 0.0346; χ2 = 4.47). According to the age categories prevalence was 10% in offspring, 27.53% in subadults, and 66.75% in adults. Seroprevalence in adult males (66.66%) and females (65.30%) was almost identical. In males, significantly lower seroprevalence was detected in offspring compared to subadults (χ2 = 4.07, p < 0.05) and adults (χ2 = 31.04; p < 0.05), and in subadults compared to adults (χ2 = 15.13; p < 0.0001). Among females, adults had a significantly higher prevalence compared to offspring (χ2 = 19.27; p < 0.0001) and subadults (χ2 = 8.62; p < 0.01). Analysis between counties revealed Sisačko-moslavačka county as a hot-spot for AD. None of the samples was positive for ADV antigens. The observed trend in prevalence points to the fact that the main transmission occurs during one part of the year (most probably the mating season). Also, triggers for virus reactivation might be more complex than previously thought, since none of our samples, collected during the mating and hunting season, was PCR positive. Finally, we can conclude that adult males represent the main transmission link between different wild boar groups.
... Elevated basal glucocorticoid levels have been documented in dominant individuals in cooperatively breeding species (Creel 2005), including wolves (Sands andCreel 2004, Barja et al. 2008). In addition, an increase in cortisol metabolites measured in wolf feces was associated with reproductive activity during proestrous (Molnar et al. 2015), breeding, and denning seasons (Creel 2005, Eggermann et al. 2013). On average wolves are sexually mature at 22 months (Seal et al. 1979, Paquet andCarbyn 2003). ...
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The use of keratinized tissues (e.g., hair, claws) to investigate physiological effects of environmental and anthropogenic stressors in free-ranging wildlife populations has increased because these tissues retain steroid hormones during growth and are relatively easy to collect and store in the field. We measured reproductive and stress-related steroid hormones in wolves (Canis lupus ligoni; n = 31) captured on Prince of Wales Island, Alaska, USA, during 1993-1994 and 2012-2014, representing periods of time when both wolf harvest and densities ranged from high to moderate. We validated enzyme immunoassay kits to measure steroid hormone concentrations in wolf guard hair, undercoat hair, and claw tip samples. Progesterone, testosterone, and cortisol were extracted and measured in the 3 keratinous tissues from wolves of different age class, sex, residency status, and collection periods. Within each tissue type, progesterone and testosterone were positively correlated (guard hair, r = 0.59, P = 0.003; undercoat hair, r = 0.55, P = 0.011; claws, r = 0.62, P ≤ 0.001) and cortisol concentrations were not related to either reproductive hormone. We were able to measure hormone concentrations in archived keratinous tissues collected up to 25 years earlier to assess stress and reproductive activity in historical samples.
... In mammals, faecal glucocorticoid metabolites (FGM) increase around the time of major physiological events in response to a heightened metabolic demand (Romero 2002). This includes pregnancy (Cavigelli 1999;Weingrill et al. 2004;Dantzer et al. 2010;Fanson et al. 2012) and the beginning of the breeding season (Kersey et al. 2010;Fanson et al. 2012;Eggermann et al. 2013;Pavlova et al. 2014). Pubertal male cheetahs exhibited an increase in FGM concentration and amplitude during the time of pubertal onset of 18-24 months of age (Maly et al. 2018). ...
With fewer than 7500 cheetahs remaining in the wild, ex situ cheetah populations serve as an insurance policy against extinction and a resource to study species' biology. This study aimed to identify the age of pubertal onset in ex situ female cheetahs using non-invasive faecal steroid hormone monitoring and body weights. Faecal samples from nine female cheetahs were collected two to three times weekly from 2 to 36months of age and body weights were recorded every 3months. Faecal oestrogen metabolites (FOM) and faecal glucocorticoid metabolites (FGM) were analysed using enzyme immunoassays and samples were categorised into 6-month intervals to compare endocrine characteristics. Faecal hormone and body weight data were analysed using generalised linear mixed models. Age was a significant predictor of mean and baseline FOM concentrations, number of FOM peaks, mean and maximum FOM peak concentrations and the number of cycles. Female cheetahs aged 24-30months exhibited a marked rise in mean FOM concentration and the number of FOM peaks and cycles increased with age until 24-30months. Females attained adult body weight by 21months of age. Mean and baseline FGM concentrations were highest at the 0-6 and 12-18months of age groups and did not follow the same FOM patterns. Based on body weight data, the FOM concentrations and peak patterning, females were considered pubertal from 24 to 30months of age. Characterisation of cheetah puberty has direct and significant implications for the improvement of management and reproductive success of cheetahs under human care. This information is particularly informative for identifying important windows of development, littermate dispersal and breeding introductions.
... It is not clear whether high population density always leads to an increased stress response. Studies linking the GCs to conspecific density and intraspecific competition in aquatic (Leatherland, 1993;Glennemeier and Denver, 2002;Bolasina et al., 2006;Ramsay et al., 2006;Teixeira et al., 2012) and social (Hawley et al., 2006;Eggermann et al., 2013) species have shown inconsistent trends. In a non-social and aggressively territorial species like the Egyptian mongoose (Palomares and Delibes, 1993), the increased frequency of antagonistic social interactions is expected to result in increased HPA-axis activity at high population densities (Creel et al., 2013), especially during the breeding season. ...
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Understanding the causes of range expansions in abundant species can help predict future species distributions. During range expansions, animals are exposed to novel environments and are required to cope with new and unpredictable stressors. Glucocorticoids (GCs) are mediators of the hormonal and behavioural mechanisms allowing animals to cope with unpredictable changes in the environment and are therefore expected to differ between populations at expansion edge and the historic range. However, to date, very few studies have evaluated the relationship between GCs and range expansion. The Egyptian mongoose has been rapidly expanding its range in Portugal over the past 30 years. In this study, we applied an information theoretic approach to determine the most important spatial and environmental predictors of hair GCs (hGCs) in the population, after controlling for normal patterns of hGC variation in the species. We observed a decrease in hGC as distance from the historic range increased (i.e. closer to the expansion front). This distance term was present in all of the top models and had a 95% confidence interval (95% CI) that did not overlap with zero, strongly supporting its influence on hGC. We estimated a 0.031 pg/mg (95% CI: −0.057, −0.004) decrease in hGCs for each kilometre distance to the Tagus River, which was once the limit of the species’ distribution. Our results indicate that the species’ expansion is unlikely to be limited by mechanisms related to or mediated by the physiological stress response. The decrease in hGC levels towards the expansion edge coupled with limited evidence of a negative effect of human population density suggests that the species’ northward expansion in Portugal could continue.
... Land use changes other than livestock husbandry do support different activities that could also increase stress among carnivores thriving in these areas. These activities might imply loss of vegetation cover, reduction of prey abundance, vehicle traffic, urbanization, human recreation, agricultural activities, human garbage, among others, all which could generate stress in wild canids (Creel et al., 2002;Eggermann et al., 2013;Nelson et al., 2015). Increased levels of stress, regardless of the stressor, might convey reduced fitness (Rey, 2020), further threatening carnivore populations. ...
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Land use changes and associated human activities modify environmental conditions for wild carnivores. Livestock husbandry among them is regarded a major threat to wild carnivores due to their persecution and retaliatory hunt for preying upon livestock albeit other land use changes could also trigger increased stress levels. To assess these different levels, we carried out a review and a meta-analysis of publications that address changes in stress of wild canids, focusing on the effect of livestock husbandry comparing the stress of wild canids living in livestock areas, other anthropic environments and natural areas. Anthropic environments systematically generate higher stress levels than natural areas for wild canids, but existing data is insufficient to ruled out that one type of anthropic activity is more stressful than another. Efforts should be increased in the study of stress in free-living canids, especially in threatened species in order to generate an adequate baseline to inform conservation practices, particularly in livestock raising areas.
... Several other mammals show similar increases in glucocorticoids during or immediately prior to the breeding season. In most cases, this seasonal variability is due to the additional psycho-physiological pressures of breeding (e.g. from competition, social instability; Eggermann et al., 2013;Muller et al., 2007;Ostner et al., 2008;Pavitt et al., 2015). Given the agonistic nature of the humpback whale mating system (Mingramm et al., 2020;Tyack and Whitehead, 1983), it seems reasonable to expect their blubber cortisol levels to vary in a similar way, and for similar reasons. ...
Baleen whales are vulnerable to environmental impacts due to low fecundity, capital breeding strategies, and their reliance on a large amount of prey resources over large spatial scales. There has been growing interest in monitoring health and physiological stress in these species but, to date, few measures have been validated. The purpose of this study was to examine whether blubber cortisol could be used as a measure of physiological stress in humpback whales. Cortisol concentrations were initially compared between live, presumably 'healthy' whales (n = 187) and deceased whales (n = 35), which had died after stranding or entanglement, or washed ashore as a carcass. Deceased whales were found to have significantly higher cortisol levels (mean ± SD; 5.47 ± 4.52 ng/g) than live whales (0.51 ± 0.14 ng/g; p < 0.001), particularly for those animals that had experienced prolonged trauma (e.g. stranding) prior to death. Blubber cortisol levels in live whales were then examined for evidence of life history-related, seasonal, or sampling-related effects. Life history group and sampling-related factors, such as encounter time and the number of biopsy sampling attempts per animal, were found to be poor predictors of blubber cortisol levels in live whales. In contrast, blubber cortisol levels varied seasonally, with whales migrating north towards the breeding grounds in winter having significantly higher levels (0.54 ± 0.21 ng/g, p = 0.016) than those migrating south towards the feeding grounds in spring (0.48 ± 1.23 ng/g). These differences could be due to additional socio-physiological stress experienced by whales during peaks in breeding activity. Overall, blubber cortisol appears to be a suitable measure of chronic physiological stress in humpback whales.
... Based on statistical analyses, the results unveiled that there is not clearly connection between the number of visitors and behaviors of wolves. However, human activity is still considered as one of the factors affecting behaviors of wolves, the similar result can be found in the previous research about stress-hormone level in captive wolves (Julia Eggermann, 2013). Indeed, abnormal behaviors, especially pacing is observed during the investigation. ...
Full-text available
An important way to understand the behaviors of wildlife in captivity is studying about impacts of surrounding factors on the expression of their behaviors. This investigation is focused on human impacts, basically the number of visitors on behaviors of Grey Wolf (Canis lupus lupus) in a reserve in Veresegyhaz, Hungary. The hypothesis is that the wolves would have abnormal behaviors more frequently when there were more visitors standing around their enclosure. Method is used for this investigation is observation, all individuals were recorded their behaviors in a fixed period. Altogether, the number of visitors at that time was also recorded. After processing the data, the results were analyzed in every cage itself as well as compared to other cages to induce the conclusion. Although the results are still controversy, the hypothesis is not demonstrated, it is summarized that wolf behaviors in captivity including mainly inactive, pacing, walking and others. Human presence is an agent causing abnormal behaviors, typically pacing in wolves. However, it is one of many factors like age categories and enclosure size which also influenced behaviors of wolves. Younger wolves are found having abnormal behaviors more than adults. Furthermore, wolves who live in large enclosure almost spent most of their time for resting and they are not affected by human. At the end of this investigation, the results hopefully can be used in an effort of improving living condition and welfare for wildlife in captivity or in some cases, this research can be a source for conservationists to design reintroduction programs that are suitable and increase the chance of living for captive animals when they are released to natural environment.
... Currently, little is known of hypothalamic-pituitaryadrenal (HPA) axis activity during the pubertal process of non-human mammals. In adults of many species, fecal glucocorticoids have been shown to in- crease around the time of other major physiological events, such as pregnancy (Cavigelli, 1999;Dantzer et al., 2010;Fanson et al., 2012;Weingrill et al., 2004) and at the beginning of breeding season ( Eggermann et al., 2013;Fanson et al., 2012;Kersey et al., 2010;Pavlova et al., 2014), as part of the response to an intensification of metabolic demand (Romero, 2002). Due to substantial physiological changes that occur, pre-and peri-pubertal intervals are highly sensitive periods of development in mammals. ...
Cheetahs are one of the most heavily studied felid species, with numerous publications on health, disease, and reproductive physiology produced over the last 30 years. Despite this relatively long history of research, there is a paucity of crucial biological data, such as pubertal onset, which has direct and significant applications to improved management of ex situ cheetah populations. This study aimed to determine age of pubertal onset in ex situ male cheetahs using non-invasive fecal steroid hormone monitoring and body weights. Fecal samples from 12 male cheetahs from four institutions were collected 2-3 times weekly from 1 to 42 months of age. Fecal androgen and glucocorticoid metabolites were analyzed using enzyme immunoassays previously validated for use with cheetah feces. Animal body weights were recorded monthly. Fecal hormone and body weight data were analyzed using generalized linear mixed models. Androgen concentrations exhibited an increase to levels similar to those observed in adult males by 18 to 24 months of age, and males attained adult body weights by 21 months of age. Based on these weight data and the initial increase in androgens toward adult concentrations, males were considered pubertal from 18 to 24 months of age. Glucocorticoid concentrations and amplitude of concentration over baseline were also increased during this period. Knowledge about the physiological changes associated with puberty is useful for management and improving reproductive success of cheetah populations under human care, particularly for determining timing of litter separation from dam, littermate dispersal and when to introduce potential breeding pairs.
... The choice of a territory/habitat is largely influenced by social aspects such as mating and pack formation. The highest stress levels were observed during the mating season (Eggermann, Theuerkauf, Pirga, Milanowski, & Gula 2013) and habitat selection, even within packs, show an individual use of space . However, wolf habitat use depends also on human activities. ...
Since the first sporadic occurrences of grey wolves (Canis lupus) west of the Polish border in 1996, wolves have shown a rapid population recovery in Germany. Wolves are known to avoid people and wolf attacks on humans are very rare worldwide. However, the subjectively perceived threat is considerable, especially as food-conditioned habituation to humans occurs sporadically. Lower Saxony (Germany) has an exceedingly higher human population density than most other regions with territorial wolves; thus, the potential for human–wolf conflicts is higher. Using hunters’ wildlife survey data from 455 municipalities and two years (2014–2015) and data from the official wolf monitoring (557 confirmed wolf presences and 500 background points) collected between 2012–2015, grey wolf habitat selection was modelled using generalized additive models with respect to human population density, road density, forest cover and roe deer density. Moreover, we tested whether habitat use changed in response to human population and road density between 2012/2013 and 2014/2015. Wolves showed a preference for areas of low road density. Human population density was less important as a covariate in the model of the survey data. Areas with higher prey abundance (5–10 roe deer/km2) and areas with >20% forest cover were preferred wolf habitats. Wolves were mostly restricted to areas with the lowest road and human population densities. However, between the two time periods, avoidance of human density decreased significantly. Recolonization of Germany is still in its early stages and it is unclear where this process will halt. To-date authorities mainly concentrate on monitoring measures. However, to avoid conflict, recolonization will require more stringent management of wolf populations and an improved information strategy for rural populations.
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Faecal samples excreted after infusion of 14C-cortisol to sheep were used to characterise metabolites and evaluate extraction procedures in order to establish an enzyme immunoassay (EIA) for the quantification of some of the metabolites. Several (> 15) faecal metabolites were formed. Nearly all were unconjugated and showed a chromatographic mobility (straight phase HPLC, silica gel) between 20α-dihydroprogesterone and cortisol. 'Authentic' cortisol and tetrahydrocortisol were at or below the limit of detection. An 11-oxoetiocholanolone-EIA (measuring 11,17-dioxoandrostanes) was established. Extraction with methanol (80%) yielded the highest recovery. The presence of immunoreactive 14C-metabolites was confirmed by analysing the HPLC fractions with the established EIA. In addition, faecal samples were collected for four days from two rams infused with a large dose of cortisol (1 g). Only measures of the 11-oxoetiocholanolone-EIA but neither of the cortisol- nor the corticosterone-EIA showed the expected excretion patterns in the faeces. Therefore measuring 11,17-dioxoandrostanes should prove to be a valuable tool for monitoring stress in farm, zoo and wildlife ruminants, using the advantages of non-invasive sampling techniques.
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until recently. The radio tracked wolves of three packs moved throughout the day with one major peak around dawn. Wolves avoided the area around main public roads more at night (up to a distance of 1.5 km) than in the day (up to 0.5 km). Wolves avoided a 0.5-km area around secondary public roads and paved forest roads both at night and in the day but did not avoid the surroundings of settlements. As compared with other studies, wolves in this study were the least nocturnal although human density was the highest. We conclude that human activity is unlikely to be the reason for nocturnal activity in wolves.
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Wolf activity varies considerably among differentstudies that explained activity patterns by factors suchas human activity, breeding status or prey availability(Fancy and Ballard 1995; Vila` et al. 1995; Ciucci et al.1997; Theuerkauf et al. 2003; Kusak et al. 2005; Chavezand Gese 2006; Theuerkauf et al. 2007). However, it islikely that the high variability of wolf activity patterns isa result of their ability to react to various environmentalconditions (Packard 2003). Activity of individual wolvesmay also vary among days, switching from being diurnalto nocturnal. The purpose of our study was to examinethe variability of wolf activity between days and seasonsand to determine the most important factors thatinfluence activity in the Bieszczady Mountains, Poland.The study was conducted in the Bieszczady Moun-tains (Polish Carpathians) over an area of about1000km
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Sex, age, bone marrow fat (BMF) content, degree of carcass utilisation and terrain features were analysed for 118 ungulates killed by wolves Canis lupus in the Bieszczady Mountains, Poland, during the winters of 1992-1995 to assess the influence of snow depth on the wolves' predation patterns. In Bieszczady, the snow conditions during the study period were milder than average, with an average total annual snow depth of 1,372 cm and an average snow cover lasting for 94 days. Red deer Cervus elaphus were the primary wolf prey (81%), whereas wild boar Sus scrofa and roe deer Capreolus capreolus were killed less often (9% and 10%, respectively). The majority of prey (74%) was killed in creeks and ravines. The carcass exploitation by wolves was high; of the recovered prey, 55% was more than 60% consumed. The average condition of red deer, as based on BMF, was high (83.4%). BMF varied most among red deer stags and calves, and varied with annual snow depth (N = 29, P < 0.01; N = 28, P = 0.09) and monthly mean snow depth (τ = -0.37, P < 0.005; τ = -0.25, P = 0.06). Wolves killed adult red deer in creeks and ravines with the same frequency regardless of snow depth, whereas calves were killed less often in these places than should be expected from their overall proportion in the sample (N = 95, χ2 = 24.34, P < 0.001). During periods with thinner snow cover, consumption of red deer carcasses was slightly higher than during periods in which the snow cover was deep (τ = -0.42, P < 0.045).
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We studied wolf (Canis lupus) selection of 19 den, 10 rendezvous, and 31 resting sites found between 1986 and 2000 in the Biaowiea Forest (Poland). Our objective was to determine whether wolves selected sites far from vil- lages, forest edges, and roads, and whether these sites had dense ground cover for concealment. We also tested whether wolves selected a particular forest type for their den sites. Den and rendezvous sites were located at greater distances from villages, forest edges, and intensively used roads than random points. Locations of resting sites were not affected by these manmade structures. Wolves selected dry coniferous forests for den sites but also used other forest types. We concluded that the suitability of an area for pup raising depended mainly on the spatial distribution of forest, human settlements, and public roads, and to a lesser extent on habitat characteristics.
THE FIRST REAL BEGINNING to our understanding of wolf social ecology came from wolf 2204 on 23 May 1972. State depredation control trapper Lawrence Waino, of Duluth, Minnesota, had caught this female wolf 112 km ( 67 mi) south of where L. D. Mech had radio-collared her in the Superior National Forest 2 years earlier. A young lone wolf, nomadic over 100 km2 (40 mi2) during the 9 months Mech had been able to keep track of her, she had then disappeared until Waino caught her. From her nipples it was apparent that she had just been nursing pups. "This was the puzzle piece I needed," stated Mech. "I had already radio-tracked lone wolves long distances, and I had observed pack members splitting off and dispersing. My hunch was that the next step was for loners to find a new area and a mate, settle down, produce pups, and start their own pack. Wolf 2204 had done just that."
Measurement of glucocorticoid metabolites in feces has become an accepted method for the noninvasive evaluation of adrenocortical activity. The objective of this study was to determine if a simple cortisol enzyme immunoassay (EIA) was suitable for monitoring adrenocortical activity in a variety of carnivore species. Performance of the cortisol EIA was gauged by comparison to a corticosterone radioimmunoassay (RIA) that has been used for measuring glucocorticoid metabolites in feces of numerous species. Tests for parallelism and extraction efficiency were used to compare the cortisol EIA and corticosterone RIA across eight species of carnivores (Himalayan black bear, sloth bear, domestic cat, cheetah, clouded leopard, black-footed ferret, slender-tailed meerkat, and red wolf). The biological relevance of immunoreactive glucocorticoid metabolites in feces was established for at least one species of each Carnivora family studied with an adrenocorticotropic hormone (ACTH) challenge. High performance liquid chromatography (HPLC) analysis of fecal extracts for each species revealed (1) the presence of multiple immunoreactive glucocorticoid metabolites in feces, but (2) the two immunoassays measured different metabolites, and (3) there were differences across species in the number and polarities of metabolites identified between assay systems. ACTH challenge studies revealed increases in fecal metabolite concentrations measured by the cortisol EIA and corticosterone RIA of ∼228–1145% and ∼231–4150% above pre-treatment baseline, respectively, within 1–2 days of injection. Concentrations of fecal glucocorticoid metabolites measured by the cortisol EIA and corticosterone RIA during longitudinal evaluation (i.e., >50 days) of several species were significantly correlated (P<0.0025, correlation coefficient range 0.383–0.975). Adrenocortical responses to physical and psychological stressors during longitudinal evaluations varied with the type of stimulus, between episodes of the same stimulus, and among species. Significant elevations of glucocorticoid metabolites were observed following some potentially stressful situations [anesthesia (2 of 3 subjects), restraint and saline injection (2 of 2 subjects), restraint and blood sampling (2 of 6 episodes), medical treatment (1 of 1 subject)], but not in all cases [e.g., gonadotropin injection (n=4), physical restraint only (n=1), mate introduction/breeding (n=1), social tension (n=1), construction (n=2) or relocation (n=1)]. Results reinforced the importance of an adequate baseline period of fecal sampling and frequent collections to assess adrenocortical status. The corticosterone RIA detected greater adrenocortical responses to exogenous ACTH and stressful exogenous stimuli in the Himalayan black bear, domestic cat (female), cheetah, clouded leopard, slender-tailed meerkat, and red wolf, whereas the cortisol EIA proved superior to resolving adrenocortical responses in the black-footed ferret and domestic cat (male). Overall results suggest the cortisol EIA tested in this study offers a practical method for laboratories restricted in the usage of radioisotopes (e.g., zoological institutions and field facilities) to integrate noninvasive monitoring of adrenocortical activity into studies of carnivore behavior and physiology.