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Abstract Much historic work has focused on establishing geographical and ecological rules that broadly explain patterns in size variation. We examined geographic variation in Spotted Hyena skull size using geometric morphometrics and spatial statistics. We quantified size variation and sexual size dimorphism of the skull, and evaluated the influence of temperature, precipitation, land cover type, and population density on skull size. We found that female spotted hyenas are slightly larger on average than males. Our analysis of regional differences did not indicate geographic variation in sexual size dimorphism. Skull size of Spotted Hyenas varies with geography but does not adhere to Bergmann’s Rule. The smallest individuals of both sexes occur between −5.00° and 10.00° latitude and east of 28.50° longitude, with larger individuals being found elsewhere. Although Spotted Hyena skull size co-varies in some views with such variables as habitat type and climate indicators, skull size in this species most strongly co-varies with population density. The highest population densities are associated with the smallest skull size, possibly reflecting a relationship between high population density and access to resources. These results suggest that geographic variation in Spotted Hyena skull size is better explained by the energetic equivalence rule than Bergmann’s Rule. 

Abstract Fission–fusion dynamics describe the tendency for members of some animal societies to associate in subgroups that change size and structure fluidly over time. These dynamics shape social complexity and social structure, but are difficult to study because they unfold simultaneously over large spatial scales. Here we use simultaneous, fine-scale GPS data from spotted hyenas to examine fission–fusion dynamics through a dyadic analysis ofmerge-split eventsbetween pairs of individuals. We introduce a species-agnostic framework for identifying merge-split events and discretizing them into three phases (merging, together, and splitting), enabling analysis of each phase as well as the connections among phases. Applying this framework to the hyena data, we examine the temporal and spatial properties of merges and splits between dyads and test the extent to which social encounters are driven by key locations. Specifically, we focus on communal dens—shelters for juvenile hyenas where classical observational studies often report large aggregations of adults. We find that overall, 62% of merges occurred at communal dens, supporting the idea that dens facilitate meet-ups and subsequent social behavior. Social encounters most commonly involved close approaches within a few meters between hyenas, while co-travel together occurred in only 11% of events. Comparison to permutation-based reference models suggests that independent movement decisions structure broad-scale patterns of social encounters but do not explain the fine-scale dynamics of interactions that unfold during these encounters. We reflect on how physical features such as dens can become social hotspots, causing social and spatial processes to become fundamentally intertwined. 

Abstract Integrated community models—an emerging framework in which multiple data sources for multiple species are analyzed simultaneously—offer opportunities to expand inferences beyond the single‐species and single‐data‐source approaches common in ecology. We developed a novel integrated community model that combines distance sampling and single‐visit count data; within the model, information is shared among data sources (via a joint likelihood) and species (via a random‐effects structure) to estimate abundance patterns across a community. Parameters relating to abundance are shared between data sources, and the model can specify either shared or separate observation processes for each data source. Simulations demonstrated that the model provided unbiased estimates of abundance and detection parameters even when detection probabilities varied between the data types. The integrated community model also provided more accurate and more precise parameter estimates than alternative single‐species and single‐data‐source models in many instances. We applied the model to a community of 11 herbivore species in the Masai Mara National Reserve, Kenya, and found considerable interspecific variation in response to local wildlife management practices: Five species showed higher abundances in a region with passive conservation enforcement (median across species: 4.5× higher), three species showed higher abundances in a region with active conservation enforcement (median: 3.9× higher), and the remaining three species showed no abundance differences between the two regions. Furthermore, the community average of abundance was slightly higher in the region with active conservation enforcement but not definitively so (posterior mean: higher by 0.20 animals; 95% credible interval: 1.43 fewer animals, 1.86 more animals). Our integrated community modeling framework has the potential to expand the scope of inference over space, time, and levels of biological organization, but practitioners should carefully evaluate whether model assumptions are met in their systems and whether data integration is valuable for their applications. 

Abstract As fecal steroid methods increasingly are used by researchers to monitor the physiology of captive and wild populations, we need to expand our validation protocols to test the effects of procedural variation and to identify contamination by exogenous sources of steroid hormones. Mammalian carnivore feces often contain large amounts of hair from the prey they consume, which itself may contain high concentrations of hormones. In this study, we report first a validation of two steroid hormone antibodies, corticosterone and progesterone, to determine fecal concentrations of these hormones in wild spotted hyenas (Crocuta crocuta). Next, we expand on these standard validation protocols to test two additional metrics: (i) whether hair from consumed prey or (ii) the specific drying method (oven incubation vs. lyophilization) affect steroid hormone concentrations in feces. In the first biological validation for the progesterone antibody in this species, progesterone concentrations met our expectations: (i) concentrations of plasma and fecal progesterone were lowest in immature females, higher in lactating females, and highest in pregnant females; (ii) across pregnant females, fecal progesterone concentrations were highest during late pregnancy; and (iii) among lactating females, fecal progesterone concentrations were highest after parturition. Our additional validation experiments indicated that contamination with prey hair and drying method are hormone-specific. Although prey hair did not release hormones into samples during storage or extraction for either hormone, its presence appeared to “dilute” progesterone (but not corticosterone) measures indirectly by increasing the dry weight of samples. In addition, fecal progesterone, but not corticosterone, values were lower for lyophilized than for incubated samples. Therefore, in addition to the standard analytical and biological validation steps, additional methodological variables need to be tested whenever we measure fecal hormone concentrations, particularly from predatory mammals. 

Abstract Individual differences in behavior are the raw material upon which natural selection acts, but despite increasing recognition of the value of considering individual differences in the behavior of wild animals to test evolutionary hypotheses, this approach has only recently become popular for testing cognitive abilities. In order for the intraspecific approach with wild animals to be useful for testing evolutionary hypotheses about cognition, researchers must provide evidence that measures of cognitive ability obtained from wild subjects reflect stable, general traits. Here, we used a multi-access box paradigm to investigate the intra-individual reliability of innovative problem-solving ability across time and contexts in wild spotted hyenas (Crocuta crocuta). We also asked whether estimates of reliability were affected by factors such as age-sex class, the length of the interval between tests, or the number of times subjects were tested. We found significant contextual and temporal reliability for problem-solving. However, problem-solving was not reliable for adult subjects, when trials were separated by more than 17 days, or when fewer than seven trials were conducted per subject. In general, the estimates of reliability for problem-solving were comparable to estimates from the literature for other animal behaviors, which suggests that problem-solving is a stable, general trait in wild spotted hyenas. 

Abstract Populations of large carnivores are declining in many parts of the world due to anthropogenic activity. Some species of large carnivores, however, are able to coexist with people by altering their behavior. Altered behaviors may be challenging to identify in large carnivores because these animals are typically cryptic, nocturnal, live at low densities, and because changes in their behavior may be subtle or emerge slowly over many years. We studied the effects of livestock presence on the movements of one large carnivore, the spotted hyena (Crocuta crocuta). We fit 22 adult female spotted hyenas with GPS collars to quantify their movements in areas with and without livestock or herders present, in and around a protected area in southwestern Kenya. We investigated anthropogenic, social, and ecological effects on the speed of movement, distances traveled, long-distance movements, and extraterritorial excursions by spotted hyenas. Hyenas living primarily within the protected area, but in the presence of livestock and herders, moved faster, traveled over longer distances, and were more likely to be within their territories than did conspecifics living in areas without livestock and herders. Hyenas of low social rank were more likely than hyenas of high social rank to engage in long-distance travel events, and these were more likely to occur when prey were scarce. The movement patterns of this large African carnivore indicate a flexibility that may allow them to persist in landscapes that are becoming increasingly defined by people. 

Animal behavior can be decomposed into a sequence of discrete activity bouts over time. Analyzing the statistical structure of such behavioral sequences can provide insights into the drivers of behavioral decisions. Laboratory studies, predominantly in invertebrates, have suggested that behavioral sequences exhibit multiple timescales and long-range memory, but whether these results can be generalized to other taxa and to animals in natural settings remains unclear. By analyzing accelerometer-inferred predictions of behavioral states in three species of social mammals (meerkats, white-nosed coatis, and spotted hyenas) in the wild, we found surprisingly consistent structuring of behavioral sequences across all behavioral states, all individuals, and all study species. Behavioral bouts were characterized by decreasing hazard functions, wherein the longer a behavioral bout had progressed, the less likely it was to end within the next instant. The predictability of an animal’s future behavioral state as a function of its present state always decreased as a truncated power-law for predictions made farther into the future, with very similar estimates for the power law exponent across all species. Finally, the distributions of bout durations were also heavy-tailed. Why such shared structural principles emerge remains unknown, and we explore multiple plausible explanations, including environmental nonstationarity, behavioral self-reinforcement, and the hierarchical nature of behavior. The existence of highly consistent patterns in behavioral sequences across our study species suggests that these phenomena could be widespread in nature, and points to the existence of fundamental properties of behavioral dynamics that could drive such convergent patterns. 

Collective action problems arise when cooperating individuals suffer costs of cooperation, while the benefits of cooperation are received by both cooperators and defectors. We address this problem using data from spotted hyenas fighting with lions. Lions are much larger and kill many hyenas, so these fights require cooperative mobbing by hyenas for them to succeed. We identify factors that predict when hyena groups engage in cooperative fights with lions, which individuals choose to participate and how the benefits of victory are distributed among cooperators and non-cooperators. We find that cooperative mobbing is better predicted by lower costs (no male lions, more hyenas) than higher benefits (need for food). Individual participation is facilitated by social factors, both over the long term (close kin, social bond strength) and the short term (greeting interactions prior to cooperation). Finally, we find some direct benefits of participation: after cooperation, participants were more likely to feed at contested carcasses than non-participants. Overall, these results are consistent with the hypothesis that, when animals face dangerous cooperative dilemmas, selection favours flexible strategies that are sensitive to dynamic factors emerging over multiple time scales. 

Animal activity patterns are highly variable and influenced by internal and external factors, including social processes. Quantifying activity patterns in natural settings can be challenging, as it is difficult to monitor animals over long time periods. Here, we developed and validated a machine-learning-based classifier to identify behavioural states from accelerometer data of wild spotted hyenas(Crocuta crocuta), social carnivores that live in large fission–fusion societies. By combining this classifier with continuous collar-based accelerometer data from five hyenas, we generated a complete record of activity patterns over more than one month. We used these continuous behavioural sequences to investigate how past activity, individual idiosyncrasies, and social synchronization influence hyena activity patterns. We found that hyenas exhibit characteristic crepuscular-nocturnal daily activity patterns. Time spent active was independent of activity level on previous days, suggesting that hyenas do not show activity compensation. We also found limited evidence for an effect of individual identity on activity, and showed that pairs of hyenas who synchronized their activity patterns must have spent more time together. This study sheds light on the patterns and drivers of activity in spotted hyena societies, and also provides a useful tool for quantifying behavioural sequences from accelerometer data.