Tracing Eastern Wolf Origins From Whole-Genome Data in Context of Extensive Hybridization.

Southeastern Canada is inhabited by an amalgam of hybridizing wolf-like canids, raising fundamental questions regarding their taxonomy, origins, and timing of hybridization events. Eastern wolves (Canis lycaon), specifically, have been the subject of significant controversy, being viewed as either a distinct taxonomic entity of conservation concern or a recent hybrid of coyotes (C. latrans) and grey wolves (C. lupus). Mitochondrial DNA analyses show some evidence of eastern wolves being North American evolved canids. In contrast, nuclear genome studies indicate eastern wolves are best described as a hybrid entity, but with unclear timing of hybridization events. To test hypotheses related to these competing findings we sequenced whole genomes of 25 individuals, representative of extant Canadian wolf-like canid types of known origin and levels of contemporary hybridization. Here we present data describing eastern wolves as a distinct taxonomic entity that evolved separately from grey wolves for the past ∼67,000 years with an admixture event with coyotes ∼37,000 years ago. We show that Great Lakes wolves originated as a product of admixture between grey wolves and eastern wolves after the last glaciation (∼8,000 years ago) while eastern coyotes originated as a product of admixture between "western" coyotes and eastern wolves during the last century. Eastern wolf nuclear genomes appear shaped by historical and contemporary gene flow with grey wolves and coyotes, yet evolutionary uniqueness remains among eastern wolves currently inhabiting a restricted range in southeastern Canada.

Highly Pathogenic Avian Influenza A(H5N1) Virus Clade 2.3.4.4b Infections in Wild Terrestrial Mammals, United States, 2022.

We describe the pathology of natural infection with highly pathogenic avian influenza A(H5N1) virus of Eurasian lineage Goose/Guangdong clade 2.3.4.4b in 67 wild terrestrial mammals throughout the United States during April 1‒July 21, 2022. Affected mammals include 50 red foxes (Vulpes vulpes), 6 striped skunks (Mephitis mephitis), 4 raccoons (Procyon lotor), 2 bobcats (Lynx rufus), 2 Virginia opossums (Didelphis virginiana), 1 coyote (Canis latrans), 1 fisher (Pekania pennanti), and 1 gray fox (Urocyon cinereoargenteus). Infected mammals showed primarily neurologic signs. Necrotizing meningoencephalitis, interstitial pneumonia, and myocardial necrosis were the most common lesions; however, species variations in lesion distribution were observed. Genotype analysis of sequences from 48 animals indicates that these cases represent spillover infections from wild birds.

Susceptibility of Wild Canids to SARS-CoV-2.

We assessed 2 wild canid species, red foxes (Vulpes vulpes) and coyotes (Canis latrans), for susceptibility to SARS-CoV-2. After experimental inoculation, red foxes became infected and shed infectious virus. Conversely, experimentally challenged coyotes did not become infected; therefore, coyotes are unlikely to be competent hosts for SARS-CoV-2.

Evolutionary legacy of the extirpated red wolf clings to life in gulf-coast canids.

Before Europeans colonized North America, a uniquely American wolf roamed the eastern forests of southern Canada to Florida and west to the Great Plains. Known today as "red wolf" (Canis rufus) in the south and "eastern wolf" (Canis lycaon) in the north, evidence suggests that these indigenous forest wolves shared a common evolutionary history until only a few centuries ago when they were extirpated from the intervening majority of their historical range. While the eastern wolf persists today primarily as a small population in Algonquin Provincial Park, Canada, the red wolf was ostensibly driven from its last stronghold in gulf-coastal Louisiana and Texas by 1980. The last-known red wolves were taken captive for propagation and reintroduction. Today, the red wolf exists as ~250 descendants of 12 founders and are distributed among 42 captive breeding facilities and one reintroduced population in coastal North Carolina. As red and eastern wolves declined in the 20th century, coyotes expanded from the west into the eastern forests, replacing them. Along with human persecution, coyote hybridization has been blamed for the late 20th century demise of the red wolf. However, rather than helping to drive the red wolf to extinction, coyote hybridization may have instead helped to preserve it. In this issue of Molecular Ecology, vonHoldt and colleagues provide the most comprehensive description yet of the substantial quantity and distribution of red wolf ancestry sequestered in southeastern coyote populations. They find the highest frequency of red wolf genes in coyotes from the gulf-coastal sites where the last known wild red wolves occurred, but also present evidence for a high prevalence of red wolf genes in coyotes throughout the southeastern expansion zone. Given the significant reduction in genetic diversity in extant red wolves owing to their late 20th century population bottleneck, this coyote-sequestered reservoir of red wolf genes could prove an important resource for red wolf conservation.

Volumetric and connectivity assessment of the caudate nucleus in California sea lions and coyotes.

In addition to a large (chimpanzee-sized) and heavily convoluted brain, one of the most striking neurobiological features in pinnipeds is the large size of the head of the caudate nucleus, which dwarfs the rest of the striatum. Although previous research has suggested carnivore striatum is small in comparison to that of primates, there are limited volumetric data on separate striatal structures in carnivores. Therefore, the apparent functional implication of a potentially hypertrophic caudate to carnivores has not been discussed. Here, for the first time, we obtained separate volumetric measurements of caudate and putamen in California sea lions and coyotes. Exemplars of both species had very large caudate nuclei, approximately 1/75th of total brain volume. In both the sea lion and coyote, the caudate dwarfed the putamen at a ratio of 13 to 1 or greater, a finding in strong contrast to measurements showing larger putamen than caudate in primates. In addition, using post-mortem diffusion tensor brain imaging, we mapped and compared white matter connections between the dorsal caudate and the motor, premotor and frontopolar, and orbitofrontal cortices in healthy adult sea lions and healthy adult coyotes. The sea lions showed some evidence of greater premotor and frontopolar connectivity. These findings bear on previously underexplored striatal characteristics of large carnivores, and we discuss potential interpretations related to cognitive flexibility and sensorimotor transformation.

Risky business: How an herbivore navigates spatiotemporal aspects of risk from competitors and predators.

Understanding factors that influence animal behavior is central to ecology. Basic principles of animal ecology imply that individuals should seek to maximize survival and reproduction, which means carefully weighing risk against reward. Decisions become increasingly complex and constrained, however, when risk is spatiotemporally variable. We advance a growing body of work in predator-prey behavior by evaluating novel questions where a prey species is confronted with multiple predators and a potential competitor. We tested how fine-scale behavior of female mule deer (Odocoileus hemionus) during the reproductive season shifted depending upon spatial and temporal variation in risk from predators and a potential competitor. We expected female deer to avoid areas of high risk when movement activity of predators and a competitor were high. We used GPS data collected from 76 adult female mule deer, 35 adult female elk, 33 adult coyotes, and six adult mountain lions. Counter to our expectations, female deer exhibited selection for multiple risk factors, however, selection for risk was dampened by the exposure to risk within home ranges of female deer, producing a functional response in habitat selection. Furthermore, temporal variation in movement activity of predators and elk across the diel cycle did not result in a shift in movement activity by female deer. Instead, the average level of risk within their home range was the predominant factor modulating the response to risk by female deer. Our results counter prevailing hypotheses of how large herbivores navigate risky landscapes and emphasize the importance of accounting for the local environment when identifying effects of risk on animal behavior. Moreover, our findings highlight additional behavioral mechanisms used by large herbivores to mitigate multiple sources of predation and potential competitive interactions.

Living in the concrete jungle: carnivore spatial ecology in urban parks.

People and wildlife are living in an increasingly urban world, replete with unprecedented human densities, sprawling built environments, and altered landscapes. Such anthropogenic pressures can affect multiple processes within an ecological community, from spatial patterns to interspecific interactions. We tested two competing hypotheses, human shields vs. human competitors, to characterize how humans affect the carnivore community using multispecies occupancy models. From 2017 to 2020, we conducted the first camera survey of city parks in Detroit, Michigan, and collected spatial occurrence data of the local native carnivore community. Our 12,106-trap night survey captured detection data for coyotes (Canis latrans), red foxes (Vulpes vulpes), raccoons (Procyon lotor), and striped skunks (Mephitis mephitis). Overall occupancy varied across species (Ψcoyote = 0.40, Ψraccoon = 0.54, Ψred fox = 0.19, Ψstriped skunk = 0.09). Contrary to expectations, humans did not significantly affect individual occupancy for these urban carnivores. However, co-occurrence between coyote and skunk increased with human activity. The observed positive spatial association between an apex and subordinate pair supports the human shield hypothesis. Our findings demonstrate how urban carnivores can exploit spatial refugia and coexist with humans in the cityscape.

Evaluating and integrating spatial capture-recapture models with data of variable individual identifiability.

Spatial capture-recapture (SCR) models have become the preferred tool for estimating densities of carnivores. Within this family of models are variants requiring identification of all individuals in each encounter (SCR), a subset of individuals only (generalized spatial mark-resight, gSMR), or no individual identification (spatial count or spatial presence-absence). Although each technique has been shown through simulation to yield unbiased results, the consistency and relative precision of estimates across methods in real-world settings are seldom considered. We tested a suite of models ranging from those only requiring detections of unmarked individuals to others that integrate remote camera, physical capture, genetic, and global positioning system (GPS) data into a hybrid model, to estimate population densities of black bears, bobcats, cougars, and coyotes. For each species, we genotyped fecal DNA collected with detection dogs during a 20-d period. A subset of individuals from each species was affixed with GPS collars bearing unique markings and resighted by remote cameras over 140 d contemporaneous with scat collection. Camera-based gSMR models produced density estimates that differed by <10% from genetic SCR for bears, cougars, and coyotes once important sources of variation (sex or behavioral status) were controlled for. For bobcats, SCR estimates were 33% higher than gSMR. The cause of the discrepancies in estimates was likely attributable to challenges designing a study compatible for species with disparate home range sizes and the difficulty of collecting sufficient data in a timeframe in which demographic closure could be assumed. Unmarked models estimated densities that varied greatly from SCR, but estimates became more consistent in models wherein more individuals were identifiable. Hybrid models containing all data sources exhibited the most precise estimates for all species. For studies in which only sparse data can be obtained and the strictest model assumptions are unlikely to be met, we suggest researchers use caution making inference from models lacking individual identity. For best results, we further recommend the use of methods requiring at least a subset of the population is marked and that multiple data sets are incorporated when possible.

A multi-state occupancy model to non-invasively monitor visible signs of wildlife health with camera traps that accounts for image quality.

Camera traps are an increasingly popular tool to monitor wildlife distributions. However, traditional analytical approaches to camera trap data are difficult to apply to visible wildlife characteristics in single images, such as infection status. Several parasites produce visible signs of infection that could be sampled via camera traps. Sarcoptic mange Sarcoptes scabiei is an ideal disease to study using cameras because it results in visible hair loss and affects a broad host range. Here, we developed a multi-state occupancy model to estimate the occurrence of mange in coyotes Canis latrans across an urban gradient. This model incorporates a secondary detection function for apparent by-image infection status to provide detection-corrected estimates of mange occurrence. We analysed a multi-year camera trap dataset in Chicago, Illinois, United States, to test whether the apparent occurrence of sarcoptic mange in coyotes Canis latrans increases with urbanization or varies through time. We documented visible signs consistent with current or recovering mange infection and variables we hypothesized would improve mange detection: The proportion of the coyote in frame, image blur and whether the image was in colour. We were more likely to detect coyotes with mange in images that were less blurry, in colour, and if a greater proportion of the coyote was visible. Mangy coyote occupancy was significantly higher in urban developed areas with low housing density and higher canopy cover whereas coyote occupancy, mangy or otherwise, decreased with urbanization. By incorporating image quality into our by-image detection function, we provide a robust method to non-invasively survey visible aspects of wildlife health with camera traps. Apparently mangy coyotes were associated with low-density forested neighbourhoods, which may offer vegetated areas while containing sources of anthropogenic resources. This association may contribute to human-wildlife conflict and reinforces posited relationships between infection risk and habitat use. More generally, our model could provide detection-corrected occupancy estimates of visible characteristics that vary by image such as body condition or injuries.

Individual and Site-Specific Variation in a Biogeographical Profile of the Coyote Gastrointestinal Microbiota.

Most knowledge of the vertebrate gut microbiota comes from fecal samples; due to difficulties involved in sample collection, the upper intestinal microbiota is poorly understood in wild animals despite its potential to inform broad interpretations about host-gut microbe relationships under natural conditions. Here, we used 16S rRNA gene sequencing to characterize the microbiota of wild coyotes (Canis latrans) along the gastrointestinal tract, including samples from the duodenum, jejunum, ileum, caecum, ascending and descending colon, and feces. We used this intestinal profile to (1) quantify how intestinal site and individual identity interact to shape the microbiota in an uncontrolled setting, and (2) evaluate whether the fecal microbiota adequately represent other intestinal sites. Microbial communities in the large intestine were distinct from those in the small intestine, with higher diversity and a greater abundance of anaerobic taxa. Within each of the small and large intestine, individual identity explained significantly more among-sample variation than specific intestinal sites, revealing the importance of individual variation in the microbiota of free-living animals. Fecal samples were not an adequate proxy for studying upper intestinal environments, as they contained only half the amplicon sequence variants (ASVs) present in the small intestine at three- to four-fold higher abundances. Our study is a unique biogeographical investigation of the microbiota using free-living mammals rather than livestock or laboratory organisms and provides a foundational understanding of the gastrointestinal microbiota in a wild canid.

Urbanization's influence on the distribution of mange in a carnivore revealed with multistate occupancy models.

Increasing urbanization and use of urban areas by synanthropic wildlife has increased human and domestic animal exposure to zoonotic diseases and exacerbated epizootics within wildlife populations. Consequently, there is a need to improve wildlife disease surveillance programs to rapidly detect outbreaks and refine inferences regarding spatiotemporal disease dynamics. Multistate occupancy models can address potential shortcomings in surveillance programs by accounting for imperfect detection and the misclassification of disease states. We used these models to explore the relationship between urbanization, slope, and the spatial distribution of sarcoptic mange in coyotes (Canis latrans) inhabiting Fort Irwin, California, USA. We deployed remote cameras across 180 sites within the desert surrounding the populated garrison and classified sites by mange presence or absence depending on whether a symptomatic or asymptomatic coyote was photographed. Coyotes selected flatter sites closer to the urban area with a high probability of use (0.845, 95% credible interval (CRI): 0.728, 0.944); site use decreased as the distance to urban areas increased (standardized [Formula: see text] = - 1.354, 95% CRI - 2.423, - 0.619). The probability of correctly classifying mange presence at a site also decreased further from the urban area and was probably related to the severity of mange infection. Severely infected coyotes, which were more readily identified as symptomatic, resided closer to the urban area and were most likely dependent on urban resources for survival; urban resources probably contributed to sustaining the disease. Multistate occupancy models represent a flexible framework for estimating the occurrence and spatial extent of observable infectious diseases, which can improve wildlife disease surveillance programs.

Optimum Placement of Distribution Generation Units in Power System with Fault Current Limiters Using Improved Coyote Optimization Algorithm.

Electric power frameworks become intensely loaded because of the expanded power demand, and as a result, the power system faces great power losses and fault currents. The integration of Distribution Generation (DG) units plays a key role in minimizing the load pressure on a power system. DGs are transmitted with a high fault current, which surpasses the evaluations of circuit breakers. This paper presents various DG units' optimal placement with Fault Current Limiters (FCLs) in different phases. The Improved Coyote Optimize Algorithm (ICOA) and Electrical Transient Analyzer Program (ETAP) are assessed for the proposed technique in terms of normal and faulty working status. Similarly, to enhance the efficiency of a distribution system, a fuzzy-based multi-objective mechanism is applied. The proposed method is employed on an IEEE 21-bus and 28-bus distribution system. The simulation analysis proved that the power losses and fault levels are reduced at an acceptable level.

Rolling Bearing Fault Diagnosis Based on Refined Composite Multi-Scale Approximate Entropy and Optimized Probabilistic Neural Network.

A rolling bearing early fault diagnosis method is proposed in this paper, which is derived from a refined composite multi-scale approximate entropy (RCMAE) and improved coyote optimization algorithm based probabilistic neural network (ICOA-PNN) algorithm. Rolling bearing early fault diagnosis is a time-sensitive task, which is significant to ensure the reliability and safety of mechanical fault system. At the same time, the early fault features are masked by strong background noise, which also brings difficulties to fault diagnosis. So, we firstly utilize the composite ensemble intrinsic time-scale decomposition with adaptive noise method (CEITDAN) to decompose the signal at different scales, and then the refined composite multi-scale approximate entropy of the first signal component is calculated to analyze the complexity of describing the vibration signal. Afterwards, in order to obtain higher recognition accuracy, the improved coyote optimization algorithm based probabilistic neural network classifiers is employed for pattern recognition. Finally, the feasibility and effectiveness of this method are verified by rolling bearing early fault diagnosis experiment.

A New Method Based on Time-Varying Filtering Intrinsic Time-Scale Decomposition and General Refined Composite Multiscale Sample Entropy for Rolling-Bearing Feature Extraction.

The early fault diagnosis of rolling bearings has always been a difficult problem due to the interference of strong noise. This paper proposes a new method of early fault diagnosis for rolling bearings with entropy participation. First, a new signal decomposition method is proposed in this paper: intrinsic time-scale decomposition based on time-varying filtering. It is introduced into the framework of complete ensemble intrinsic time-scale decomposition with adaptive noise (CEITDAN). Compared with traditional intrinsic time-scale decomposition, intrinsic time-scale decomposition based on time-varying filtering can improve frequency-separation performance. It has strong robustness in the presence of noise interference. However, decomposition parameters (the bandwidth threshold and B-spline order) have significant impacts on the decomposition results of this method, and they need to be artificially set. Aiming to address this problem, this paper proposes rolling-bearing fault diagnosis optimization based on an improved coyote optimization algorithm (COA). First, the minimal generalized refined composite multiscale sample entropy parameter was used as the objective function. Through the improved COA algorithm, optimal intrinsic time-scale decomposition parameters based on time-varying filtering that match the input signal are obtained. By analyzing generalized refined composite multiscale sample entropy (GRCMSE), whether the mode component is dominated by the fault signal is determined. The signal is reconstructed and decomposed again. Finally, the mode component with the highest energy in the central frequency band is selected for envelope spectrum variation for fault diagnosis. Lastly, simulated and experimental signals were used to verify the effectiveness of the proposed method.

Seasonal and daily shifts in behavior and resource selection: how a carnivore navigates costly landscapes.

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.

Evaluation of an automated magnetic bead-based DNA extraction and real-time PCR in fecal samples as a pre-screening test for detection of Echinococcus multilocularis and Echinococcus canadensis in coyotes.

Efficient and sensitive diagnostic tools are essential for the study of the eco-epidemiology of Echinococcus species. We evaluated an automated magnetic bead-based DNA extraction commercial kit followed by qPCR (MB-qPCR), for the detection of Echinococcus multilocularis and Echinococcus canadensis in coyote (Canis latrans) fecal samples. The diagnostic sensitivity was determined by validating the method against the scraping, filtration, and counting technique (SFCT) for samples collected in Canada. From the 60 samples tested, 27 out of 31 SFCT positives samples for Echinococcus cestodes were positive in the MB-qPCR for E. multilocularis, with a sensitivity of 87.1% (95% CI 70.2 to 96.4%). Two samples were also positive for E. canadensis in the MB-qPCR and confirmed by morphological identification of adult worms. The agreement of the MB-qPCR and the SFCT was statistically significant with a kappa value of 0.67 (95% CI 0.48-0.85; p value < 0.001). The magnetic bead-based DNA extraction followed by qPCR proved to have a sensitivity comparable to the SFCT to detect E. multilocularis. Although the diagnostic sensitivity for E. canadensis was not estimated, MB-qPCR identified E. canadensis cases previously overlooked when using SFCT. We propose a combination of molecular and morphological identification using the MB-qPCR and the SFCT to detect both parasites, allowing for a more efficient large-scale surveillance, and detecting co-infections of Echinococcus species that can be difficult to identify when only based on morphology.

Spatial processes decouple management from objectives in a heterogeneous landscape: predator control as a case study.

Predator control is often implemented with the intent of disrupting top-down regulation in sensitive prey populations. However, ambiguity surrounding the efficacy of predator management, as well as the strength of top-down effects of predators in general, is often exacerbated by the spatially implicit analytical approaches used in assessing data with explicit spatial structure. Here, we highlight the importance of considering spatial context in the case of a predator control study in south-central Utah. We assessed the spatial match between aerial removal risk in coyotes (Canis latrans) and mule deer (Odocoileus hemionus) resource selection during parturition using a spatially explicit, multi-level Bayesian model. With our model, we were able to evaluate spatial congruence between management action (i.e., coyote removal) and objective (i.e., parturient deer site selection) at two distinct scales: the level of the management unit and the individual coyote removal. In the case of the former, our results indicated substantial spatial heterogeneity in expected congruence between removal risk and parturient deer site selection across large areas, and is a reflection of logistical constraints acting on the management strategy and differences in space use between the two species. At the level of the individual removal, we demonstrated that the potential management benefits of a removed coyote were highly variable across all individuals removed and in many cases, spatially distinct from parturient deer resource selection. Our methods and results provide a means of evaluating where we might anticipate an impact of predator control, while emphasizing the need to weight individual removals based on spatial proximity to management objectives in any assessment of large-scale predator control. Although we highlight the importance of spatial context in assessments of predator control strategy, we believe our methods are readily generalizable in any management or large-scale experimental framework where spatial context is likely an important driver of outcomes.

Endocranial Development in the Coyote (Canis latrans) and Gray Wolf (Canis lupus): A Computed Tomographic Study.

The purpose of this study was to examine the pattern of postnatal brain growth in two wild canid species: the coyote (Canis latrans) and gray wolf (Canis lupus). Adult regional and total brain volume differences were also compared between the two species as well as within each species by sex. Three-dimensional virtual endocasts of endocranial airspace were created from computed tomography scans of 52 coyote skulls (28 female, 24 male; 1 day to 13.4 years) and 46 gray wolf skulls (25 female, 21 male; 1 day to 7.9 years). Age was known in coyotes or estimated from dentition patterns in wolves. The 95% asymptotic growth of the endocranium is completed by 21 weeks in male and 17.5 weeks in female coyotes and by 27 weeks in male and 18.5 weeks in female wolves. These ages are well before age at first reproduction (coyote - 40.4 weeks; wolf - 91.25 weeks). Skull growth as measured by centroid size lags behind endocranial growth but is also completed before sexual maturity. Intra- and interspecific comparisons of brain volumes in the adult wolves and coyotes revealed that relative anterior cerebrum (AC) volume was greater in males than females in both species. Relative brain size was greater in the coyote than in the wolf as was relative cerebrum volume. However, relative AC volume and relative cerebellum and brainstem volume was greater in the wolf than coyote. One explanation for the increased AC volume in males compared to females may be related to the role of social information processing. However, additional data are needed to determine the correspondence between regional volumes and functional differences either between or within these species. Nonetheless, these findings provide important baseline data for further studies on wild canid brain variations and development.

TREATMENT OF SUSPECTED EXERTIONAL MYOPATHY USING DANTROLENE IN A COYOTE ( CANIS LATRANS).

A 3-yr-old spayed female coyote ( Canis latrans) developed clinical signs of exertional myopathy after fighting with a conspecific. A diagnosis of exertional myopathy was made based on physical examination findings, probable myoglobinuria, and elevations in serum creatinine kinase activity, alanine aminotransferase activity, and potassium concentration. Dantrolene, a hydantoin analog, as well as supportive and symptomatic therapies, was used to successfully treat exertional myopathy. This is the first reported use of dantrolene in wildlife or zoo animals.

Improving the assessment of predator functional responses by considering alternate prey and predator interactions.

To improve understanding of the complex and variable patterns of predator foraging behavior in natural systems, it is critical to determine how density-dependent predation and predator hunting success are mediated by alternate prey or predator interference. Despite considerable theory and debate seeking to place predator-prey interactions in a more realistic context, few empirical studies have quantified the role of alternate prey or intraspecific interactions on predator-prey dynamics. We assessed functional responses of two similarly sized, sympatric carnivores, lynx (Lynx canadensis) and coyotes (Canis latrans), foraging on common primary (snowshoe hares; Lepus americanus) and alternate (red squirrels; Tamiasciurus hudsonicus) prey in a natural system. Lynx exhibited a hyperbolic prey-dependent response to changes in hare density, which is characteristic of predators relying primarily on a single prey species. In contrast, the lynx-squirrel response was found to be linear ratio dependent, or inversely dependent on hare density. The coyote-hare and coyote-squirrel interactions also were linear and influenced by predator density. We explain these novel results by apparent use of spatial and temporal refuges by prey, and the likelihood that predators commonly experience interference and lack of satiation when foraging. Our study provides empirical support from a natural predator-prey system that (1) predation rate may not be limited at high prey densities when prey are small or rarely captured; (2) interference competition may influence the predator functional response; and (3) predator interference has a variable role across different prey types. Ultimately, distinct functional responses of predators to different prey types illustrates the complexity associated with predator-prey interactions in natural systems and highlights the need to investigate predator behavior and predation rate in relation to the broader ecological community.