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Encounters between animals occur when animals are close in space and time. Encounters are important in many ecological processes including sociality, predation and disease transmission. Despite this, there is little theory regarding the spatial distribution of encounters and no formal framework to relate environmental characteristics to encounters. The probability of encounter could be estimated with resource selection functions (RSFs) by comparing locations where encounters occurred to available locations where they may have occurred, but this estimate is complicated by the hierarchical nature of habitat selection. We developed a method to relate resources to the relative probability of encounter based on a scale-integrated habitat selection framework. This framework integrates habitat selection at multiple scales to obtain an appropriate estimate of availability for encounters. Using this approach, we related encounter probabilities to landscape resources. The RSFs describe habitat associations at four scales, home ranges within the study area, areas of overlap within home ranges, locations within areas of overlap, and encounters compared to other locations, which can be combined into a single scale-integrated RSF. We apply this method to intraspecific encounter data from two species: white-tailed deer (Odocoileus virginianus) and elk (Cervus elaphus) and interspecific encounter data from a two-species system of caribou (Rangifer tarandus) and coyote (Canis latrans). Our method produced scale-integrated RSFs that represented the relative probability of encounter. The predicted spatial distribution of encounters obtained based on this scale-integrated approach produced distributions that more accurately predicted novel encounters than a naïve approach or any individual scale alone. Our results highlight the importance of accounting for the conditional nature of habitat selection in estimating the habitat associations of animal encounters as opposed to 'naïve' comparisons of encounter locations with general availability. This method has direct relevance for testing hypotheses about the relationship between habitat and social or predator-prey behaviour and generating spatial predictions of encounters. Such spatial predictions may be vital for understanding the distribution of encounters driving disease transmission, predation rates and other population and community-level processes.
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Cervos , Ecossistema , Animais , Cervos/fisiologia , Modelos Biológicos , Coiotes/fisiologia , Rena/fisiologia , Comportamento AnimalRESUMO
The dynamic environmental conditions in highly seasonal systems likely have a strong influence on how species use the landscape. Animals must balance seasonal and daily changes to landscape risk with the underlying resources provided by that landscape. One way to balance the seasonal and daily changes in the costs and benefits of a landscape is through behaviorally-explicit resource selection and temporal partitioning. Here, we test whether resource selection of coyotes (Canis latrans) in Cape Breton Highlands National Park, Nova Scotia, Canada is behaviorally-explicit and responsive to the daily and seasonal variation to presumed costs and benefits of moving on the landscape. We used GPS data and local convex hulls to estimate space use and Hidden Markov Models to estimate three types of movement behavior: encamped, foraging, and traveling. We then used integrated step-selection analysis to investigate behaviorally explicit resource selection across times of day (diurnal, crepuscular, and nocturnal) and season (snow-free and snow). We found that throughout the day and seasonally coyotes shifted foraging behavior and altered behavior and resource choices to avoid moving across what we could be a challenging landscape. These changes in behavior suggest that coyotes have a complex response to land cover, terrain, and linear corridors that are not only scale dependent but also vary by behavior, diel period, and season. By examining the resource selection across three axes (behavior, time of day, and season), we have a more nuanced understanding of how a predator balances the cost and benefits of a stochastic environment.
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Coiotes , Ecossistema , Animais , Nova Escócia , Comportamento Predatório , Estações do AnoRESUMO
For many organisms, climate change can directly drive population declines, but it is less clear how such variation may influence populations indirectly through modified biotic interactions. For instance, how will climate change alter complex, multi-species relationships that are modulated by climatic variation and that underlie ecosystem-level processes? Caribou (Rangifer tarandus), a keystone species in Newfoundland, Canada, provides a useful model for unravelling potential and complex long-term implications of climate change on biotic interactions and population change. We measured cause-specific caribou calf predation (1990-2013) in Newfoundland relative to seasonal weather patterns. We show that black bear (Ursus americanus) predation is facilitated by time-lagged higher summer growing degree days, whereas coyote (Canis latrans) predation increases with current precipitation and winter temperature. Based on future climate forecasts for the region, we illustrate that, through time, coyote predation on caribou calves could become increasingly important, whereas the influence of black bear would remain unchanged. From these predictions, demographic projections for caribou suggest long-term population limitation specifically through indirect effects of climate change on calf predation rates by coyotes. While our work assumes limited impact of climate change on other processes, it illustrates the range of impact that climate change can have on predator-prey interactions. We conclude that future efforts to predict potential effects of climate change on populations and ecosystems should include assessment of both direct and indirect effects, including climate-predator interactions.
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Mudança Climática , Ecossistema , Animais , Canadá , Bovinos , Dinâmica Populacional , Comportamento PredatórioRESUMO
Climate can have direct and indirect effects on population dynamics via changes in resource competition or predation risk, but this influence may be modulated by density- or phase-dependent processes. We hypothesized that for ungulates, climatic conditions close to parturition have a greater influence on the predation risk of neonates during population declines, when females are already under nutritional stress triggered by food limitation. We examined the presence of phase-dependent climate-predator (PDCP) interactions on neonatal ungulate survival by comparing spatial and temporal fluctuations in climatic conditions, cause-specific mortality and per capita resource limitation. We determined cause-specific fates of 1384 caribou (Rangifer tarandus) from 10 herds in Newfoundland, spanning more than 30 years during periods of numerical increase and decline, while exposed to predation from black bears (Ursus americanus) and coyotes (Canis latrans). We conducted Cox proportional hazards analysis for competing risks, fit as a function of weather metrics, to assess pre- and post-partum climatic influences on survival on herds in population increase and decline phases. We used cumulative incidence functions to compare temporal changes in risk from predators. Our results support our main hypothesis; when caribou populations increased, weather conditions preceding calving were the main determinants of cause-specific mortality, but when populations declined, weather conditions during calving also influenced predator-driven mortality. Cause-specific analysis showed that weather conditions can differentially affect predation risk between black bears and coyotes with specific variables increasing the risk from one species and decreasing the risk from the other. For caribou, nutritional stress appears to increase predation risk on neonates, an interaction which is exacerbated by susceptibility to climatic events. These findings support the PDCP interactions framework, where maternal body condition influences susceptibility to climate-related events and, subsequently, risk from predation.
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Animais Recém-Nascidos/fisiologia , Clima , Cadeia Alimentar , Rena/fisiologia , Animais , Coiotes/fisiologia , Feminino , Longevidade , Masculino , Modelos Biológicos , Terra Nova e Labrador , Comportamento Predatório , Modelos de Riscos Proporcionais , Ursidae/fisiologia , Tempo (Meteorologia)RESUMO
SNAPSHOT USA is a multicontributor, long-term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application (https://www.snapshot-usa.org/). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights (https://www.wildlifeinsights.org/), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22-5.9 arrays per 100,000 km2), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.
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Fotografação , Estados Unidos , Animais , Mamíferos , EcossistemaRESUMO
Wildlife living in proximity to people are exposed to both natural and anthropogenic factors that may influence cortisol production associated with stress response. While some species, including coyotes (Canis latrans), have become commonplace in developed areas throughout North America, urban individuals still must navigate ever-changing, novel environments and cope with frequent disturbance. Given that coyotes are relatively large predators compared to most other urban wildlife, they face unique pressures such as crossing roadways to use suitable habitat fragments and are at a greater risk of being detected and experiencing negative human interactions. To assess whether urbanization influences hypothalamic-pituitary-adrenal axis activity in free-ranging coyotes, we analyzed cortisol concentration in hair samples from 97 coyotes residing across the urbanization gradient within the Greater Chicago Metropolitan area. As the proportion of developed landcover within coyote home ranges increased, coyotes experienced more stress. Body condition and social status also had strong relationships with stress. Animals in poorer body condition experienced more stress and subordinate coyotes experienced less stress than alphas. We also found some evidence that stress varied seasonally and among different age classes. Understanding how intrinsic and extrinsic factors influence endocrine activity in urban carnivores is vital for predicting how hormone production and related behavioral patterns may change in future populations as more areas become developed.
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Invasive wild pigs (Sus scrofa) are considered one of the most damaging species globally, and once they become established in an area, they are notoriously difficult to eliminate. As such, identifying the potential pathways of invasion, especially in places with emerging populations, is critical for preventing new or continued invasion. Wild pigs have been reported in Ontario, Canada, in recent years. We tested four nonexclusive hypotheses about the source of wild pigs in Ontario: (a) escapees from captive sources within Ontario; (b) invasion from neighboring jurisdictions; (c) existing wild populations within Ontario; and (d) translocation and illegal release. We found that sightings of Eurasian wild boar were closer to premises with wild boar than were random locations; wild boar sightings were an average of 16.3 km (SD = 25.4 km, min = 0.2 km, n = 20) from premises with wild boar. We also found that sightings of domestic pigs were closer to domestic pig farms than expected. Sightings of wild pigs in groups of more than four animals were rare. Our results suggest that wild pigs observed in Ontario are recent escapes from captivity, recognizing that there may be established groups of wild pigs that we have not yet detected. While not common, we also received reports indicating that in the past, wild pigs have been translocated and illegally released. Other North American jurisdictions that have been successful at eliminating wild pigs have removed existing populations and changed regulations to limit future invasion, such as prohibiting possession and transport of wild boar and prohibiting hunting of wild pigs.
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Population monitoring is a critical part of effective wildlife management, but methods are prone to biases that can hinder our ability to accurately track changes in populations through time. Calf survival plays an important role in ungulate population dynamics and can be monitored using telemetry and herd composition surveys. These methods, however, are susceptible to unrepresentative sampling and violations of the assumption of equal detectability, respectively. Here, we capitalized on 55 herd-wide estimates of woodland caribou (Rangifer tarandus caribou) calf survival in Newfoundland, Canada, using telemetry (n = 1,175 calves) and 249 herd-wide estimates of calf:cow ratios (C:C) using herd composition surveys to investigate these potential biases. These data included 17 herd-wide estimates replicated from both methods concurrently (n = 448 calves and n = 17 surveys) which we used to understand which processes and sampling biases contributed to disagreement between estimates of herd-wide calf survival. We used Cox proportional hazards models to determine whether estimates of calf mortality risk were biased by the date a calf was collared. We also used linear mixed-effects models to determine whether estimates of C:C ratios were biased by survey date and herd size. We found that calves collared later in the calving season had a higher mortality risk and that C:C tended to be higher for surveys conducted later in the autumn. When we used these relationships to modify estimates of herd-wide calf survival derived from telemetry and herd composition surveys concurrently, we found that formerly disparate estimates of woodland caribou calf survival now overlapped (within a 95% confidence interval) in a majority of cases. Our case study highlights the potential of under-appreciated biases to impact our understanding of population dynamics and suggests ways that managers can limit the influence of these biases in the two widely applied methods for estimating herd-wide survival.
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Wildlife can respond to urbanization positively (synanthropic) or negatively (misanthropic), and for some species, this is a nonlinear process, whereby low levels of urbanization elicit a positive response, but this response becomes negative at high levels of urbanization. We applied concepts from foraging theory to predict positive and negative behavioral responses of coyotes (Canis latrans) along an urbanization gradient in the Chicago metropolitan area, USA. We estimated home range size and complexity, and metrics of 3 movement behaviors (encamped, foraging, and traveling) using Hidden Markov movement models. We found coyotes exhibited negative behavioral responses to highly urbanized landscapes: coyotes viewed the landscape as lower quality, riskier, and more fragmented (home range size and complexity, and time spent encamped increased). Conversely, we found evidence of both positive and negative responses to suburban landscapes: coyotes not only viewed the landscape as higher quality than natural fragments and equally risky, but also viewed it as fragmented (home range size decreased, time spent encamped did not change, and home range complexity increased). Although the spatial and behavioral responses of coyotes to urbanization became increasingly negative as urbanization increased, coyotes were still able to occupy highly urbanized landscapes. Our study demonstrates how wildlife behavioral responses can be dependent on the degree of urbanization and represents one of the first descriptions of apex predator space use and movement in a highly urbanized landscape.
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In ungulates, parturition is correlated with a reduction in movement rate. With advances in movement-based technologies comes an opportunity to develop new techniques to assess reproduction in wild ungulates that are less invasive and reduce biases. DeMars et al. (2013, Ecology and Evolution 3:4149-4160) proposed two promising new methods (individual- and population-based; the DeMars model) that use GPS inter-fix step length of adult female caribou (Rangifer tarandus caribou) to infer parturition and neonate survival. Our objective was to apply the DeMars model to caribou populations that may violate model assumptions for retrospective analysis of parturition and calf survival. We extended the use of the DeMars model after assigning parturition and calf mortality status by examining herd-wide distributions of parturition date, calf mortality date, and survival. We used the DeMars model to estimate parturition and calf mortality events and compared them with the known parturition and calf mortality events from collared adult females (n = 19). We also used the DeMars model to estimate parturition and calf mortality events for collared female caribou with unknown parturition and calf mortality events (n = 43) and instead derived herd-wide estimates of calf survival as well as distributions of parturition and calf mortality dates and compared them to herd-wide estimates generated from calves fitted with VHF collars (n = 134). For our data, the individual-based method was effective at predicting calf mortality, but was not effective at predicting parturition. The population-based method was more effective at predicting parturition but was not effective at predicting calf mortality. At the herd-level, the predicted distributions of parturition date from both methods differed from each other and from the distribution derived from the parturition dates of VHF-collared calves (log-ranked test: χ2 = 40.5, df = 2, p < 0.01). The predicted distributions of calf mortality dates from both methods were similar to the observed distribution derived from VHF-collared calves. Both methods underestimated herd-wide calf survival based on VHF-collared calves, however, a combination of the individual- and population-based methods produced herd-wide survival estimates similar to estimates generated from collared calves. The limitations we experienced when applying the DeMars model could result from the shortcomings in our data violating model assumptions. However despite the differences in our caribou systems, with proper validation techniques the framework in the DeMars model is sufficient to make inferences on parturition and calf mortality.
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Animais Recém-Nascidos , Parto , Animais , Feminino , Terra Nova e Labrador , Gravidez , Rena , Análise de SobrevidaRESUMO
BACKGROUND: Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises (Chelonoidis sp.) using a multi-year (2009-2014) GPS dataset from three different Galapagos Islands. RESULTS: With respect to patterns of time spent and the number of transitions between modes, our approach out-performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as "exploratory residence". CONCLUSIONS: Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.
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Peer review is pivotal to science and academia, as it represents a widely accepted strategy for ensuring quality control in scientific research. Yet, the peer-review system is poorly adapted to recent changes in the discipline and current societal needs. We provide historical context for the cultural lag that governs peer review that has eventually led to the system's current structural weaknesses (voluntary review, unstandardized review criteria, decentralized process). We argue that some current attempts to upgrade or otherwise modify the peer-review system are merely sticking-plaster solutions to these fundamental flaws, and therefore are unlikely to resolve them in the long term. We claim that for peer review to be relevant, effective, and contemporary with today's publishing demands across scientific disciplines, its main components need to be redesigned. We propose directional changes that are likely to improve the quality, rigour, and timeliness of peer review, and thereby ensure that this critical process serves the community it was created for.