1. For large predators living in seasonal environments, patterns of prédation are likely to vary among seasons because of related changes in prey vulnerability. Variation in prey vulnerability ...underlies the influence of predators on prey populations and the response of predators to seasonal variation in rates of biomass acquisition. Despite its importance, seasonal variation in prédation is poorly understood. 2. We assessed seasonal variation in prey composition and kill rate for wolves Canis lupus living on the Northern Range (NR) of Yellowstone National Park. Our assessment was based on data collected over 14 winters (1995-2009) and five spring-summers between 2004 and 2009. 3. The species composition of wolf-killed prey and the age and sex composition of wolf-killed elk Cervus elaphus (the primary prey for NR wolves) varied among seasons. 4. One's understanding of prédation depends critically on the metric used to quantify kill rate. For example, kill rate was greatest in summer when quantified as the number of ungulates acquired per wolf per day, and least during summer when kill rate was quantified as the biomass acquired per wolf per day. This finding contradicts previous research that suggests that rates of biomass acquisition for large terrestrial carnivores tend not to vary among seasons. 5. Kill rates were not well correlated among seasons. For example, knowing that early-winter kill rate is higher than average (compared with other early winters) provides little basis for anticipating whether kill rates a few months later during late winter will be higher or lower than average (compared with other late winters). This observation indicates how observing, for example, higherthan-average kill rates throughout any particular season is an unreliable basis for inferring that the year-round average kill rate would be higher than average. 6. Our work shows how a large carnivore living in a seasonal environment displays marked seasonal variation in prédation because of changes in prey vulnerability. Patterns of wolf prédation were influenced by the nutritional condition of adult elk and the availability of smaller prey (i.e. elk calves, deer). We discuss how these patterns affect our overall understanding of predator and prey population dynamics.
Raptors exert top‐down influences on ecosystems via their effects on prey population dynamics and community composition. Most raptors are sympatric with other predators, thus complicating our ...understanding of their relative influence in these systems. Estimates of kill rates and prey biomass recycling have been used as predation metrics that allow quantitative comparison among species and assessment of the relative role of single species within complex food webs. Few studies have produced findings of kill rates or prey biomass recycling for raptors. We used a supervised machine learning algorithm to behaviourally classify high resolution accelerometer informed GPS locations of tagged adult non‐breeding martial eagles Polemaetus bellicosus in the Maasai Mara region of Kenya to estimate kill rates and prey biomass recycling. Eagle locations classified as feeding were clustered using distance and time thresholds to identify kills and calculate kill rates. Identified kill sites were quickly ground‐truthed to confirm kills and identify prey species. We estimated kill rates for martial eagles at 0.59 kills day‐1 for males and 0.38 kills day‐1 for females, and we estimated biomass recycling per ground‐truthed kill at 1796 g for males and 3860 g for females. From our sample of identified ground‐truthed kills, ‘gamebirds' was the most frequently recorded prey category for male eagles and ‘small ungulates' was the most frequently recorded prey category for female eagles. These results position martial eagles close to sympatric mammalian top predators in trophic pyramids and provide evidence for their classification as a top predator.
Ecological communities are fundamentally connected through a network of trophic interactions that are often complex and difficult to model. Substantial variation exists in the nature and magnitude of ...these interactions across various predators and prey and through time. However, the empirical data needed to characterize these relationships are difficult to obtain in natural systems, even for relatively simple food webs. Consequently, prey-dependent relationships and specifically the hyperbolic form (Holling’s Type II), in which prey consumption increases with prey density but ultimately becomes saturated or limited by the time spent handling prey, are most widely used albeit often without knowledge of their appropriateness. Here, we investigate the sensitivity of a simplified food web model for a natural, boreal system in the Kluane region of the Yukon, Canada to the type of functional response used. Intensive study of this community has permitted best-fit functional response relationships to be determined, which comprise linear (type I), hyperbolic (type II), sigmoidal (type III), prey- and ratio-dependent relationships, and inverse relationships where kill rates of alternate prey are driven by densities of the focal prey. We compare node- and network-level properties for a food web where interaction strengths are estimated using best-fit functional responses to one where interaction strengths are estimated exclusively using prey-dependent hyperbolic functional responses. We show that hyperbolic functional responses alone fail to capture important ecological interactions such as prey switching, surplus killing and caching, and predator interference, that in turn affect estimates of cumulative kill rates, vulnerability of prey, generality of predators, and connectance. Exclusive use of hyperbolic functional responses also affected trends observed in these metrics over time and underestimated annual variation in several metrics, which is important given that interaction strengths are typically estimated over relatively short time periods. Our findings highlight the need for more comprehensive research aimed at characterizing functional response relationships when modeling predator-prey interactions and food web structure and function, as we work toward a mechanistic understanding linking food web structure and community dynamics in natural systems.
An increasing number of GPS telemetry studies have helped to gain important insights into predator-prey relationships in recent years. However, considerable time and effort is needed to evaluate ...whether GPS location clusters (GLCs) reflect predation events. To reduce field effort, predictive models are being developed to calculate predator kill intervals, but few studies have attempted to do this for a specific species of prey. Between 2013 and 2018, we studied predation by 13 GPS-collared Eurasian lynx (
Lynx lynx
) on Alpine chamois (
Rupicapra rupicapra
) in the northwestern Swiss Alps. Our objectives were to predict the total number of killed chamois, including potential kills in unchecked GLCs, and to evaluate if model predictions were sufficiently accurate. We built a set of generalized linear models (GLM) predicting the occurrence of GLCs containing lynx-killed chamois (1) versus GLCs containing other prey types or no prey (0) and compared their predictive performance by means of k-fold cross-validation. We found that model performance was very similar for all candidate models, with the full model yielding the best cross-validation result (accuracy = 0.83, sensitivity = 0.43, specificity = 0.94). Female lynx killed on average one chamois every 11.9 days (10.6–13.0 days, 95% CI); male lynx killed one chamois every 7.2 days (6.7–7.6 days, 95% CI). Our model showed high specificity for detecting non-chamois GLCs, but sensitivity for detection of GLCs with actual chamois kills was low. We conclude that the sensitivity of the models should be further improved, but the results can be sufficient for practical application. Predictive modelling approaches do not replace extensive fieldwork but require large sets of field data, high individual variability and thorough knowledge of a predator’s ecology and prey community. Our approach may provide useful results for binary classifications in rather simple predator-prey systems, but extrapolations from one study system to another might be difficult.
Variation in predation can have important consequences for predators and prey, but little is known about associated mechanisms. Diel interactions between predators and prey are commonly assumed to be ...influenced by movement speeds of both predators and prey individuals, sensu the ideal gas model, but the influencing factors of diel predation dynamics have yet to be empirically examined.
In this study, we apply principles of the ideal gas model to predict diel variation in kill frequency of moose (Alces alces) by wolves (Canis lupus) in northern Ontario, Canada based on GPS radio‐telemetry data combined with field verification of kills.
We used GPS telemetry data from wolves and moose combined with a unique data set on the diel pattern of wolf kills to test whether predator movement rate, prey movement rate, and ambient light condition influence diel variation in kill rates of wolves on moose.
Our results indicate that the kill rate between wolves and moose was principally related to the effective movement rate of predators and prey, as predicted by the ideal gas model. We found little evidence that light conditions had any effect on kill rates, but rather the majority of kill rate variation corresponded to wolf movement rate, which was over an order of magnitude higher than that of moose.
Lay Summary
Assessing the impact of large carnivores on ungulate prey has been challenging in part because even basic components of predation are difficult to measure. For cougars (Puma concolor), limited field ...data are available concerning fundamental aspects of predation, such as kill rate, or the influence of season, cougar demography, or prey vulnerability on predation, leading to uncertainty over how best to predict or interpret cougar–ungulate dynamics. Global Positioning System (GPS) telemetry used to locate predation events in the field is an efficient way to monitor large numbers of cougars over long periods in all seasons. We applied GPS telemetry techniques combined with occasional snow-tracking to locate 1,509 predation events for 53 marked and an unknown number of unmarked cougars and amassed 9,543 days of continuous predation monitoring for a subset of 42 GPS-collared cougars in west-central Alberta, Canada. Cougars killed ungulates at rates near the upper end of the previously recorded range, and demography substantially influenced annual kill rate in terms of both number of ungulates (subad F SAF = 24, subad M SAM = 31, ad M = 35, ad F = 42, ad F with kittens <6 months = 47, ad F with kittens >6 months = 67) and kg of prey (SAF = 1,441, SAM = 2,051, ad M = 4,708, ad F = 2,423, ad F with kittens <6 months = 2,794, ad F with kittens >6 months = 4,280). Demography also influenced prey composition; adult females subsisted primarily on deer (Odocoileus spp.), whereas adult males killed more large ungulates (e.g., moose Alces alces), and subadults incorporated the highest proportion of nonungulate prey. Predation patterns varied by season and cougars killed ungulates 1.5 times more frequently in summer when juveniles dominated the diet. Higher kill rate in summer appeared to be driven primarily by greater vulnerability of juvenile prey and secondarily by reduced handling time for smaller prey. Moreover, in accordance with predictions of the reproductive vulnerability hypothesis, female ungulates made up a higher proportion of cougar diet in spring just prior to and during the birthing period, whereas the proportion of males increased dramatically in autumn during the rut, supporting the notion that prey vulnerability influences cougar predation. Our results have implications for the impact cougars have on ungulate populations and have application for using cougar harvest to manage ungulates.
Abstract Background Actinobacillus pleuropneumoniae is a serious pathogen in pigs. The abundant application of antibiotics has resulted in the gradual emergence of drugresistant bacteria, which has ...seriously affected treatment of disease. To aid measures to prevent the emergence and spread of drug-resistant bacteria, herein, the kill rate and mutant selection window (MSW) of danofloxacin (DAN) against A. pleuropneumoniae were evaluated. Methods For the kill rate study, the minimum inhibitory concentration (MIC) was tested using the micro dilution broth method and time-killing curves of DAN against A. pleuropneumoniae grown in tryptic soy broth (TSB) at a series drug concentrations (from 0 to 64 MIC) were constructed. The relationships between the kill rate and drug concentrations were analyzed using a Sigmoid E max model during different time periods. For the MSW study, the MIC 99 (the lowest concentration that inhibited the growth of the bacteria by ≥ 99%) and mutant prevention concentration (MPC) of DAN against A. pleuropneumoniae were measured using the agar plate method. Then, a peristaltic pump infection model was established to simulate the dynamic changes of DAN concentrations in pig lungs. The changes in number and sensitivity of A. pleuropneumoniae were measured. The relationships between pharmacokinetic/pharmacodynamic parameters and the antibacterial effect were analyzed using the Sigmoid E max model. Results In kill rate study, the MIC of DAN against A. pleuropneumoniae was 0.016 µg/mL. According to the kill rate, DAN exhibited concentration-dependent antibacterial activity against A. pleuropneumoniae . A bactericidal effect was observed when the DAN concentration reached 4–8 MIC. The kill rate increased constantly with the increase in DAN concentration, with a maximum value of 3.23 Log 10 colony forming units (CFU)/mL/h during the 0–1 h period. When the drug concentration was in the middle part of the MSW, drugresistant bacteria might be induced. Therefore, the dosage should be avoided to produce a mean value of AUC 24h /MIC 99 (between 31.29 and 62.59 h. The values of AUC 24h /MIC 99 to achieve bacteriostatic, bactericidal, and eradication effects were 9.46, 25.14, and > 62.59 h, respectively. Conclusion These kill rate and MSW results will provide valuable guidance for the use of DAN to treat A. pleuropneumoniae infections.
We wished to study the detailed and precise antibacterial activity of cefquinome against
(APP)
and
. We analyzed the relationships between kill rate and cefquinome concentration in broth and between ...pharmacokinetic/pharmacodynamic (PK/PD) parameters and antibacterial effect in serum and tissue cage fluid (TCF) of piglets. Cefquinome exhibited time-dependent antibacterial activity against APP according to the kill rate. The maximum kill rate was 0.48 log
CFU/mL/h at the 0-9-h period in broth. In the
PK/PD study, the maximum concentration (C
), time to reach the maximum concentration (T
), terminal half-life (T
), and area under the concentration time curve (AUC
) were 5.65 μg/ml, 0.58 h, 2.24 h, and 18.48 μg·h/ml in serum and 1.13 μg/ml, 2.60 h, 12.22 h, and 20.83 μg·h/ml in TCF, respectively. The values of area under the curve during 24 h/minimum inhibitory concentration (AUC
/MIC) for bacteriostatic, bactericidal, and bacterial eradication effects were 18.94, 246.8, and 1013.23 h in serum and 4.20, 65.81, and 391.35 h in TCF, respectively. Our findings will provide a valuable basis for optimization of dosage regimens when applying cefquinome to treat APP infection.
Recent recolonization of mountain lions (Puma concolor) into the Little Missouri Badlands of North Dakota has led to questions regarding the potential impacts of predation on prey populations in the ...region. From 2012 to 2013, we deployed 9 real-time GPS collars to investigate mountain lion feeding habits. We monitored mountain lions for 1,845 telemetry-days, investigated 506 GPS clusters, and identified 292 feeding events. Deer (Odocoileus spp.) were the most prevalent item in mountain lion diets (76.9%). We used logistic regression to predict feeding events and size of prey consumed at an additional 535 clusters. Our top model for predicting presence of prey items produced a receiver operating characteristic score of 0.90 and an overall accuracy of 81.4%. Application of our models to all GPS clusters resulted in an estimated ungulate kill rate of 1.09 ungulates/week (95% confidence interval CI = 0.83–1.36) in summer (15 May–15 November) and 0.90 ungulates/week (95% CI = 0.69–1.12) in winter (16 November–14 May). Estimates of total biomass consumed were 5.8kg/day (95% CI = 4.7–6.9) in summer and 7.2kg/day (95% CI = 5.3–9.2) in winter. Overall scavenge rates were 3.7% in summer and 11.9% in winter. Prey composition included higher proportions of nonungulates in summer (female = 21.5%; male = 24.8%) than in winter (female = 4.8%; male = 7.5%). Proportion of juvenile ungulates in mountain lion diets increased during the fawning season (June–August) following the ungulate birth pulse in June (June–August = 60.7%, 95% CI = 43.0–78.3; September–May = 37.2%, 95% CI = 30.8–43.7), resulting in an ungulate kill rate 1.61 times higher (1.41 ungulates/week, 95% CI = 1.12–1.71) than during the remainder of the year (0.88 ungulates/week, 95% CI = 0.62–1.13). Quantifying these feeding characteristics is essential to assessing the potential impacts of mountain lions on prey populations in the North Dakota Badlands, where deer dominate the available prey base and mountain lions represent the lone apex predator.
1. Understanding the role of predation in shaping the dynamics of animal communities is a fundamental issue in ecological research. Nevertheless, the complex nature of predator-prey interactions ...often prevents researchers from modelling them explicitly. 2. By using periodic Leslie-Usher matrices and a simulation approach together with parameters obtained from long-term field projects, we reconstructed the underlying mechanisms of predator-prey demographic interactions and compared the dynamics of the roe deer-red fox-Eurasian lynx-human harvest system with those of the moose-brown beargray wolf-human harvest system in the boreal forest ecosystem of the southern Scandinavian Peninsula. 3. The functional relationship of both roe deer and moose λ to changes in predation rates from the four predators was remarkably different. Lynx had the strongest impact among the four predators, whereas predation rates by wolves, red foxes, or brown bears generated minor variations in prey population λ. Elasticity values of lynx, wolf, fox and bear predation rates were -0157, -0.056, -0.031 and -0.006, respectively, but varied with both predator and prey densities. 4. Differences in predation impact were only partially related to differences in kill or predation rates, but were rather a result of different distribution of predation events among prey age classes. Therefore, the age composition of killed individuals emerged as the main underlying factor determining the overall per capita impact of predation. 5. Our results confirm the complex nature of predator-prey interactions in large terrestrial mammals, by showing that different carnivores preying on the same prey species can exert a dramatically different demographic impact, even in the same ecological context, as a direct consequence of their prédation patterns. Similar applications of this analytical framework in other geographical and ecological contexts are needed, but a more general evaluation of the subject is also required, aimed to assess, on a broader systematic and ecological range, what specific traits of a carnivore are most related to its potential impact on prey species.
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