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Chemical cues are thought to play an important role in mate identification in the solitary giant panda (Ailuropoda melanoleuca). The goal of this study was to detect and identify volatile compounds present in the enclosure air of captive giant pandas. We hypothesized that a subset of compounds produced from breeding animals would be detected in environmental samples because highly volatile chemicals are likely to facilitate mate detection. Samples were collected from the enclosures of 8 giant pandas (n = 4 male, n = 4 female) during the Mar-June breeding season and the Aug-Jan non-breeding period from 2012-2015. Volatile compounds were captured by securing a solid phase micro extraction fiber approximately 3 meters above the ground within a panda enclosure for 6-12 hours. Compounds adsorbed onto the SPME fibers were analyzed by gas chromatography mass spectrometry. Thirty-three compounds were detected in at least 10% of all samples within individual and season and across all subjects within each season. Aromatic compounds made up 27.3% of the enclosure volatile profile, while 21.2% was made of cyclic aliphatic compounds and 51.5% of the enclosure profile was comprised of acyclic aliphatic compounds. Three compounds were likely to be present in male enclosures regardless of season, while Undecane, 4-methyl had a significant (p

Abstract Scent originates from excretions and secretions, and its chemical complexity in mammals translates into a diverse mode of signalling. Identifying how information is encoded can help to establish the mechanisms of olfactory communication and the use of odours as chemical signals. Building upon existing behavioural and histological literature, we examined the chemical profile of secretions used for scent marking by a solitary, non-territorial carnivore, the brown bear (Ursus arctos). We investigated the incidence, abundance, and uniqueness of volatile organic compounds (VOCs) from cutaneous glandular secretions of 12 wild brown bears collected during late and post-breeding season, and assessed whether age-sex class, body site, and individual identity explained profile variation. VOC profiles varied in the average number of compounds, compound incidence, and compound abundance by age-sex class and individual identity (when individuals were grouped by sex), but not by body site. Mature males differed from other age-sex classes, secreting fewer compounds on average with the least variance between individuals. Compound uniqueness varied by body site and age for both males and females and across individuals. Our results indicate that brown bear skin-borne secretions may facilitate age-sex class and individual recognition, which can contribute towards further understanding of mating systems and social behaviour.

Abstract Grizzly bears (Ursus arctos) in west‐central Alberta occupy an increasingly human‐dominated landscape. Natural resource extraction activities are hypothesized to increase stress in animals that reside in such changing landscapes by influencing habitat and resource availability. Our study aimed to determine whether stress, represented by hair cortisol concentration (HCC), was associated with variables related to landscape conditions in a population that increased by 7% annually from 2004 to 2014. Hair samples (n = 157) were collected using barbwire hair snags placed throughout the Yellowhead bear management area in Alberta, Canada. Candidate models were developed a priori representing hypotheses related to biologically and ecologically plausible relationships between HCC and landscape variables. Generalized linear model analysis with landscape attributes representing anthropogenic disturbance, food resource availability, and terrain conditions was used to determine potential drivers of HCC. We found support (ΔAICc ≤ 2.00) for three models that included variables from each hypothesis. Anthropogenic variables had the greatest impact on HCC; increasing oil and gas well‐site density resulted in reduced HCC, while increasing distance to coal mines resulted in elevated HCC. Hair cortisol concentration also increased as forest crown closure became more variable, while HCC decreased as the soil wetness (represented by compound topographic index) increased. Some forms of anthropogenic disturbance have been linked to increased food availability for this species. Therefore, we suggest that changes in landscape conditions from 2004 to 2014 may have indirectly increased food abundance and ultimately resulted in a reduction in HCC at a population level during this time period. Measuring HCC provides a non‐invasive and important monitoring strategy to assess the impact of environmental change on residing species and should be considered in landscape management decisions.

Abstract Environmental change has been shown to influence mammalian distribution, habitat use, and behavior; however, few studies have investigated the impact on physiological function. This study aimed to determine the influence of landscape condition on the expression of target proteins related to energetics, reproduction, and stress in grizzly bears. We hypothesized that changes in landscape condition explains protein expression. Skin biopsies were collected from free-ranging grizzly bears in Alberta, Canada from 2013–2019 (n = 86 individuals). We used an information theoretic approach to develop 11 a priori candidate generalized linear mixed models to explain protein expression. We compared models using Akaike Information Criteria (AICc) weights and averaged models with ΔAICc

Enzyme immunoassays (EIAs) are a common tool for measuring steroid hormones in wildlife due to their low cost, commercial availability, and rapid results. Testing technologies improve continuously, sometimes requiring changes in protocols or crucial assay components. Antibody replacement between EIA kits can cause differences in EIA sensitivity, which can hinder monitoring hormone concentration over time. The antibody in a common cortisol EIA kit used for long-term monitoring of stress in wildlife was replaced in 2014, causing differences in cross reactivity and standard curve concentrations. Therefore, the objective of this study was to develop a method to standardize results following changes in EIA sensitivity. We validated this method using cortisol concentrations measured in the hair of brown bears (Ursus arctos). • We used a simple linear regression to model the relationship between cortisol concentrations using kit 1 and kit 2. • We found a linear relationship between the two kits (R2 = 0.85) and used the regression equation (kit2 = (0.98 × kit1) + 1.65) to predict cortisol concentrations in re-measured samples. • Mean predicted percent error was 16% and 72% of samples had a predicted percent error