Assessing the influence of prey–predator ratio,prey age structure and packs size on wolf kill rates

Traditional predation theory assumes that prey density is the primary determinant of kill rate. More recently, the ratio of prey‐to‐predator has been shown to be a better predictor of kill rate. However, the selective behavior of many predators also suggests that age structure of the prey population should be an important predictor of kill rate. We compared wolf–moose predation dynamics in two sites, south‐central Scandinavia (SCA) and Isle Royale, Lake Superior, North America (IR), where prey density was similar, but where prey age structure and prey‐to‐predator ratio differed. Per capita kill rates of wolves preying on moose in SCA are three times greater than on IR. Because SCA and IR have similar prey densities differences in kill rate cannot be explained by prey density. Instead, differences in kill rate are explained by differences in the ratio of prey‐to‐predator, pack size and age structure of the prey populations. Although ratio‐dependent functional responses was an important variable for explaining differences in kill rates between SCA and IR, kill rates tended to be higher when calves comprised a greater portion of wolves’ diet (p =0.05). Our study is the first to suggest how age structure of the prey population can affect kill rate for a mammalian predator. Differences in age structure of the SCA and IR prey populations are, in large part, the result of moose and forests being exploited in SCA, but not in IR. While predator conservation is largely motivated by restoring trophic cascades and other top–down influences, our results show how human enterprises can also alter predation through bottom–up processes.     

Consequences of ratio-dependent predation by wolves for elk population dynamics

A growing number of studies suggest ratio-dependence may be common in many predator–prey systems, yet in large mammal systems, evidence is limited to wolves and their prey in Isle Royale and Yellowstone. More importantly, the consequences of ratio-dependent predation have not been empirically examined to understand the implications for prey. Wolves recolonized Banff National Park in the early 1980s, and recovery was correlated with significant elk declines. I used time-series data of wolf kill rates of elk, wolf and elk densities in winter from 1985–2007 to test for support for prey-, ratio-, or predator dependent functional and numeric responses of wolf killing rate to elk density. I then combined functional and numeric responses to estimate the total predation response to identify potential equilibrium states. Evidence suggests wolf predation on elk was best described by a type II ratio-dependent functional response and a type II numeric response that lead to inversely density-dependent predation rate on elk. Despite support for ratio-dependence, like other wolf-prey systems, there was considerable uncertainty amongst functional response models, especially at low prey densities. Consistent with predictions from ratio-dependent models, however, wolves contributed to elk population declines of over 80 % in our Banff system. Despite the statistical signature for ratio-dependence, the biological mechanism remains unknown and may be related to multi-prey dynamics in our system. Regardless, ratio-dependent models strike a parsimonious balance between theory and empiricism, and this study suggests that large mammal ecologists need to consider ratio-dependent models in predator–prey dynamics.     

Spatial decomposition of predation risk using resource selection functions: an example in a wolf–elk predator–prey system

Predation is a fundamental ecological and evolutionary process that varies in space, and the avoidance of predation risk is of central importance in foraging theory. While there has been a recent growth of approaches to spatially model predation risk, these approaches lack an adequate mechanistic framework that can be applied to real landscapes. In this paper we show how predation risk can be decomposed into encounter and attack stages, and modeled spatially using resource selection functions (RSF) and resource selection probability functions (RSPF). We use this approach to compare the effects of landscape attributes on the relative probability of encounter, the conditional probability of death given encounter, and overall wolf and elk resource selection to test whether predation risk is simply equivalent to location of the predator. We then combine the probability of encounter and conditional probability of death into a spatially explicit function of predation risk following Lima and Dill's reformulation of Holling's functional response. We illustrate this approach in a wolf–elk system in and adjacent to Banff National Park, Alberta, Canada. In this system we found that the odds of elk being encountered by wolves was 1.3 times higher in pine forest and 4.1 times less in grasslands than other habitats. The relative odds of being killed in pine forests, given an encounter, increased by 1.2. Other habitats, such as grasslands, afforded elk reduced odds (4.1 times less) of being encountered and subsequently killed (1.4 times less) by wolves. Our approach illustrates that predation risk is not necessarily equivalent to just where predators are found. We show that landscape attributes can render prey more or less susceptible to predation and effects of landscape features can differ between the encounter and attack stages of predation. We conclude by suggesting applications of our approach to model predator–prey dynamics using spatial predation risk functions in theoretical and applied settings.     

Building a mechanistic understanding of predation with GPS-based movement data

Quantifying kill rates and sources of variation in kill rates remains an important challenge in linking predators to their prey. We address current approaches to using global positioning system (GPS)-based movement data for quantifying key predation components of large carnivores. We review approaches to identify kill sites from GPS movement data as a means to estimate kill rates and address advantages of using GPS-based data over past approaches. Despite considerable progress, modelling the probability that a cluster of GPS points is a kill site is no substitute for field visits, but can guide our field efforts. Once kill sites are identified, time spent at a kill site (handling time) and time between kills (killing time) can be determined. We show how statistical models can be used to investigate the influence of factors such as animal characteristics (e.g. age, sex, group size) and landscape features on either handling time or killing efficiency. If we know the prey densities along paths to a kill, we can quantify the ‘attack success’ parameter in functional response models directly. Problems remain in incorporating the behavioural complexity derived from GPS movement paths into functional response models, particularly in multi-prey systems, but we believe that exploring the details of GPS movement data has put us on the right path.     

Spatial extinction or persistence: landscape‐temperature interactions perturb predator–prey dynamics

Recognising that species interact across a range of spatial scales, we explore how landscape structure interacts with temperature to influence persistence. Specifically, we recognise that few studies indicate thermal shifts as the proximal cause of species extinctions; rather, species interactions exacerbated by temperature result in extinctions. Using microcosm‐based experiments, as models of larger landscape processes, we test hypotheses that would be problematic to address through field work. A text‐book predator–prey system (the ciliates Didinium and Paramecium) was used to compare three landscapes: an unfragmented landscape subjected to uniform temperatures (10, 20, 30°C); a fragmented landscape (potentially hosting metapopulations) subjected to these three temperatures; and a fragmented landscape subjected to a spatial temperature gradient (～ 10 to 30°C) – despite the prevalence of natural temperature ecoclines this is the first time such an analysis has been conducted. Initial thermal response‐analysis (growth, mortality, and movement measured between 10 and 30°C) suggested that as temperature increased, the predator might drive the prey to extinction. Thermal preferences (measured at 5 temperatures between 10 and 30°C), indicated that both predator and prey preferred warmer temperatures, with the predator exhibiting the stronger preference, suggesting that cooler regions might act as a prey‐refuge. The landscape level observations, however, did not entirely support the predictions. First, in the unfragmented landscape, increased temperature led to extinctions, but at the highest temperature (where the predator growth can be reduced) the prey survived. Second, at high temperatures the fragmented landscape failed to host metapopulations that would allow predator–prey persistence. Third, the thermal ecocline did not provide heterogeneity that improved stability; rather it forced both species to occupy a smaller realized space, leading toward extinctions. These findings reveal that temperature‐impacted rates and temperature preferences combine to drive predator–prey dynamics and persistence across landscapes.     

Habitat heterogeneity and mammalian predator–prey interactions

• 1 In predator–prey theory, habitat heterogeneity can affect the relationship between kill rates and prey or predator density through its effect on the predator's ability to search for, encounter, kill and consume its prey. Many studies of predator–prey interactions include the effect of spatial heterogeneity, but these are mostly based on species with restricted mobility or conducted in experimental settings.
• 2 Here, we aim to identify the patterns through which spatial heterogeneity affects predator–prey dynamics and to review the literature on the effect of spatial heterogeneity on predator–prey interactions in terrestrial mammalian systems, i.e. in freely moving species with high mobility, in non‐experimental settings. We also review current methodologies that allow the study of the predation process within a spatial context.
• 3 When the functional response includes the effect of spatial heterogeneity, it usually takes the form of predator‐dependent or ratio‐dependent models and has wide applicability.
• 4 The analysis of the predation process through its different stages may further contribute towards identifying the spatial scale of interest and the specific spatial mechanism affecting predator–prey interactions.
• 5 Analyzing the predation process based on the functional response theory, but separating the stages of predation and applying a multiscale approach, is likely to increase our insight into how spatial heterogeneity affects predator–prey dynamics. This may increase our ability to forecast the consequences of landscape transformations on predator–prey dynamics.

     

Territory surveillance and prey management: Wolves keep track of space and time

Identifying behavioral mechanisms that underlie observed movement patterns is difficult when animals employ sophisticated cognitive‐based strategies. Such strategies may arise when timing of return visits is important, for instance to allow for resource renewal or territorial patrolling. We fitted spatially explicit random‐walk models to GPS movement data of six wolves (Canis lupus; Linnaeus, 1758) from Alberta, Canada to investigate the importance of the following: (1) territorial surveillance likely related to renewal of scent marks along territorial edges, to reduce intraspecific risk among packs, and (2) delay in return to recently hunted areas, which may be related to anti‐predator responses of prey under varying prey densities. The movement models incorporated the spatiotemporal variable “time since last visit,” which acts as a wolf's memory index of its travel history and is integrated into the movement decision along with its position in relation to territory boundaries and information on local prey densities. We used a model selection framework to test hypotheses about the combined importance of these variables in wolf movement strategies. Time‐dependent movement for territory surveillance was supported by all wolf movement tracks. Wolves generally avoided territory edges, but this avoidance was reduced as time since last visit increased. Time‐dependent prey management was weak except in one wolf. This wolf selected locations with longer time since last visit and lower prey density, which led to a longer delay in revisiting high prey density sites. Our study shows that we can use spatially explicit random walks to identify behavioral strategies that merge environmental information and explicit spatiotemporal information on past movements (i.e., “when” and “where”) to make movement decisions. The approach allows us to better understand cognition‐based movement in relation to dynamic environments and resources.     

Conservation of wildlife populations: factoring in incremental disturbance

Progressive anthropogenic disturbance can alter ecosystem organization potentially causing shifts from one stable state to another. This potential for ecosystem shifts must be considered when establishing targets and objectives for conservation. We ask whether a predator–prey system response to incremental anthropogenic disturbance might shift along a disturbance gradient and, if it does, whether any disturbance thresholds are evident for this system. Development of linear corridors in forested areas increases wolf predation effectiveness, while high density of development provides a safe‐haven for their prey. If wolves limit moose population growth, then wolves and moose should respond inversely to land cover disturbance. Using general linear model analysis, we test how the rate of change in moose (Alces alces) density and wolf (Canis lupus) harvest density are influenced by the rate of change in land cover and proportion of land cover disturbed within a 300,000 km² area in the boreal forest of Alberta, Canada. Using logistic regression, we test how the direction of change in moose density is influenced by measures of land cover change. In response to incremental land cover disturbance, moose declines occurred where <43% of land cover was disturbed; in such landscapes, there were high rates of increase in linear disturbance and wolf density increased. By contrast, moose increases occurred where >43% of land cover was disturbed and wolf density declined. Wolves and moose appeared to respond inversely to incremental disturbance with the balance between moose decline and wolf increase shifting at about 43% of land cover disturbed. Conservation decisions require quantification of disturbance rates and their relationships to predator–prey systems because ecosystem responses to anthropogenic disturbance shift across disturbance gradients.     

Optimal predator management for mountain sheep conservation depends on the strength of mesopredator release

Large predators often suppress ungulate population growth, but they may also suppress the abundance of smaller predators that prey on neonatal ungulates. Antagonistic interactions among predators may therefore need to be integrated into predator–prey models to effectively manage ungulate–predator systems. We present a modeling framework that examines the net impact of interacting predators on the population growth rate of shared prey, using interactions among wolves Canis lupus, coyotes Canis latrans and Dall sheep Ovis dalli dalli as a case study. Wolf control is currently employed on approximately 16 million ha in Alaska to increase the abundance of ungulates for human harvest. We hypothesized that the positive effects of wolf control on Dall sheep population growth could be counteracted by increased levels of predation by coyotes. Coyotes and Dall sheep adult females (ewes) and lambs were radiocollared in the Alaska Range from 1999–2005 to estimate fecundity, age‐specific survival rates, and causes of mortality in an area without wolf control. We used stage‐structured population models to simulate the net effect of wolf control on Dall sheep population growth (λ). Our models accounted for stage‐specific predation rates by wolves and coyotes, compensatory mortality, and the potential release of coyote populations due to wolf control. Wolves were the main predators of ewes, coyotes were the main predators of lambs, and wolves were the main source of mortality for coyotes. Population models predicted that wolf control could increase sheep λ by 4% per year in the absence of mesopredator release. However, if wolf control released coyote populations, our models predicted that sheep λ could decrease by up to 3% per year. These results highlight the importance of integrating antagonistic interactions among predators into predator–prey models, because the net effect of predator management on shared prey can depend critically on the strength of mesopredator release.     

Linking anti‐predator behaviour to prey demography reveals limited risk effects of an actively hunting large carnivore

Ecological theory predicts that the diffuse risk cues generated by wide‐ranging, active predators should induce prey behavioural responses but not major, population‐ or community‐level consequences. We evaluated the non‐consumptive effects (NCEs) of an active predator, the grey wolf (Canis lupus), by simultaneously tracking wolves and the behaviour, body fat, and pregnancy of elk (Cervus elaphus), their primary prey in the Greater Yellowstone Ecosystem. When wolves approached within 1 km, elk increased their rates of movement, displacement and vigilance. Even in high‐risk areas, however, these encounters occurred only once every 9 days. Ultimately, despite 20‐fold variation in the frequency of encounters between wolves and individual elk, the risk of predation was not associated with elk body fat or pregnancy. Our findings suggest that the ecological consequences of actively hunting large carnivores, such as the wolf, are more likely transmitted by consumptive effects on prey survival than NCEs on prey behaviour.     

Wolves,white‐tailed deer,and beaver: implications of seasonal prey switching for woodland caribou declines

Population increases of primary prey can negatively impact alternate prey populations via demographic and behavioural responses of a shared predator through apparent competition. Seasonal variation in prey selection patterns by predators also can affect secondary and incidental prey by reducing spatial separation. Global warming and landscape changes in Alberta's bitumen sands have resulted in prey enrichment, which is changing the large mammal predator–prey system and causing declines in woodland caribou Rangifer tarandus caribou populations. We assessed seasonal patterns of prey use and spatial selection by wolves Canis lupus in two woodland caribou ranges in northeastern Alberta, Canada, that have undergone prey enrichment following recent white‐tailed deer Odocoileus virginianus invasion. We determined whether risk of predation for caribou (incidental prey) and the proportion of wolf‐caused‐caribou mortalities varied with season. We found that wolves showed seasonal variation in primary prey use, with deer and beaver Castor canadensis being the most common prey items in wolf diet in winter and summer, respectively. These seasonal dietary patterns were reflected in seasonal wolf spatial resource selection and resulted in contrasting spatial relationships between wolves and caribou. During winter, wolf selection for areas used by deer maintained strong spatial separation between wolves and caribou, whereas wolf selection for areas used by beaver in summer increased the overlap with caribou. Changing patterns in wolf resource selection were reflected by caribou mortality patterns, with 76.2% of 42 adult female caribou mortalities occurring in summer. Understanding seasonal patterns of predation following prey enrichment in a multiprey system is essential when assessing the effect of predation on an incidental prey species. Our results support the conclusion that wolves are proximately responsible for woodland caribou population declines throughout much of their range.     

The landscape of fear as an emergent property of heterogeneity: Contrasting patterns of predation risk in grassland ecosystems

The likelihood of encountering a predator influences prey behavior and spatial distribution such that non‐consumptive effects can outweigh the influence of direct predation. Prey species are thought to filter information on perceived predator encounter rates in physical landscapes into a landscape of fear defined by spatially explicit heterogeneity in predation risk. The presence of multiple predators using different hunting strategies further complicates navigation through a landscape of fear and potentially exposes prey to greater risk of predation. The juxtaposition of land cover types likely influences overlap in occurrence of different predators, suggesting that attributes of a landscape of fear result from complexity in the physical landscape. Woody encroachment in grasslands furnishes an example of increasing complexity with the potential to influence predator distributions. We examined the role of vegetation structure on the distribution of two avian predators, Red‐tailed Hawk (Buteo jamaicensis) and Northern Harrier (Circus cyaneus), and the vulnerability of a frequent prey species of those predators, Northern Bobwhite (Colinus virginianus). We mapped occurrences of the raptors and kill locations of Northern Bobwhite to examine spatial vulnerability patterns in relation to landscape complexity. We use an offset model to examine spatially explicit habitat use patterns of these predators in the Southern Great Plains of the United States, and monitored vulnerability patterns of their prey species based on kill locations collected during radio telemetry monitoring. Both predator density and predation‐specific mortality of Northern Bobwhite increased with vegetation complexity generated by fine‐scale interspersion of grassland and woodland. Predation pressure was lower in more homogeneous landscapes where overlap of the two predators was less frequent. Predator overlap created areas of high risk for Northern Bobwhite amounting to 32% of the land area where landscape complexity was high and 7% where complexity was lower. Our study emphasizes the need to evaluate the role of landscape structure on predation dynamics and reveals another threat from woody encroachment in grasslands.     

Not attackable or not crackable—How pre‐ and post‐attack defenses with different competition costs affect prey coexistence and population dynamics

It is well‐known that prey species often face trade‐offs between defense against predation and competitiveness, enabling predator‐mediated coexistence. However, we lack an understanding of how the large variety of different defense traits with different competition costs affects coexistence and population dynamics. Our study focusses on two general defense mechanisms, that is, pre‐attack (e.g., camouflage) and post‐attack defenses (e.g., weaponry) that act at different phases of the predator—prey interaction. We consider a food web model with one predator, two prey types and one resource. One prey type is undefended, while the other one is pre‐ or post‐attack defended paying costs either by a higher half‐saturation constant for resource uptake or a lower maximum growth rate. We show that post‐attack defenses promote prey coexistence and stabilize the population dynamics more strongly than pre‐attack defenses by interfering with the predator's functional response: Because the predator spends time handling “noncrackable” prey, the undefended prey is indirectly facilitated. A high half‐saturation constant as defense costs promotes coexistence more and stabilizes the dynamics less than a low maximum growth rate. The former imposes high costs at low resource concentrations but allows for temporally high growth rates at predator‐induced resource peaks preventing the extinction of the defended prey. We evaluate the effects of the different defense mechanisms and costs on coexistence under different enrichment levels in order to vary the importance of bottom‐up and top‐down control of the prey community.     

Separating spatial search and efficiency rates as components of predation risk

Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk—the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)—imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator–prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk.     

Reintroduced wolves and hunting limit the abundance of a subordinate apex predator in a multi-use landscape

Top-down effects of apex predators are modulated by human impacts on community composition and species abundances. Consequently, research supporting top-down effects of apex predators occurs almost entirely within protected areas rather than the multi-use landscapes dominating modern ecosystems. Here, we developed an integrated population model to disentangle the concurrent contributions of a reintroduced apex predator, the grey wolf, human hunting and prey abundances on vital rates and abundance of a subordinate apex predator, the puma. Increasing wolf numbers had strong negative effects on puma fecundity, and subadult and adult survival. Puma survival was also influenced by density dependence. Overall, puma dynamics in our multi-use landscape were more strongly influenced by top-down forces exhibited by a reintroduced apex predator, than by human hunting or bottom-up forces (prey abundance) subsidized by humans. Quantitatively, the average annual impact of human hunting on equilibrium puma abundance was equivalent to the effects of 20 wolves. Historically, wolves may have limited pumas across North America and dictated puma scarcity in systems lacking sufficient refugia to mitigate the effects of competition.     

Boreal predator co‐occurrences reveal shared use of seismic lines in a working landscape

Interspecific interactions are an integral aspect of ecosystem functioning that may be disrupted in an increasingly anthropocentric world. Industrial landscape change creates a novel playing field on which these interactions take place, and a key question for wildlife managers is whether and how species are able to coexist in such working landscapes. Using camera traps deployed in northern Alberta, we surveyed boreal predators to determine whether interspecific interactions affected occurrences of black bears (Ursus americanus), coyotes (Canis latrans), and lynx (Lynx canadensis) within a landscape disturbed by networks of seismic lines (corridors cut for seismic exploration of oil and gas reserves). We tested hypotheses of species interactions across one spatial‐only and two spatiotemporal (daily and weekly) scales. Specifically, we hypothesized that (1) predators avoid competition with the apex predator, gray wolf (Canis lupus), (2) they avoid competition with each other as intraguild competitors, and (3) they overlap with their prey. All three predators overlapped with wolves on at least one scale, although models at the daily and weekly scale had substantial unexplained variance. None of the predators showed avoidance of intraguild competitors or overlap with prey. These results show patterns in predator space use that are consistent with both facilitative interactions or shared responses to unmeasured ecological cues. Our study provides insight into how predator species use the working boreal landscape in relation to each other, and highlights that predator management may indirectly influence multiple species through their interactions.     

Statistical Methods for Identifying Wolf Kill Sites Using Global Positioning System Locations

Abstract: Accurate estimates of kill rates remain a key limitation to addressing many predator—prey questions. Past approaches for identifying kill sites of large predators, such as wolves (Canis lupus), have been limited primarily to areas with abundant winter snowfall and have required intensive ground-tracking or aerial monitoring. More recently, attempts have been made to identify clusters of locations obtained using Global Positioning System (GPS) collars on predators to identify kill sites. However, because decision rules used in determining clusters have not been consistent across studies, results are not necessarily comparable. We illustrate a space—time clustering approach to statistically define clusters of wolf GPS locations that might be wolf kill sites, and we then use binary and multinomial logistic regression to model the probability of a cluster being a non—kill site, kill site of small-bodied prey species, or kill site of a large-bodied prey species. We evaluated our approach using field visits of kills and assessed the accuracy of the models using an independent dataset. The cluster-scan approach identified 42–100% of wolf-killed prey, and top logistic regression models correctly classified 100% of kills of large-bodied prey species, but 40% of small-bodied prey species were classified as nonkills. Although knowledge of prey distribution and vulnerability may help refine this approach, identifying small-bodied prey species will likely remain problematic without intensive field efforts. We recommend that our approach be utilized with the understanding that variation in prey body size and handling time by wolves will likely have implications for the success of both the cluster scan and logistic regression components of the technique. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):798–807; 2008)     

Individual variation in prey choice in a predator-prey community

One predator-two prey community models are studied with an emphasis on individual variation in predator behavior. The predator behaves according to a well-known prey choice model. The behavioral model predicts that predators should always attack the primary prey (more profitable prey of the two), but only attack the alternative prey (less profitable prey of the two) when the density of the primary prey is below a threshold density. The predator that accepts the alternative prey does not discriminate between the primary and alternative prey (all-or-nothing preference for the alternative prey). However, empirical studies do not result in clear all-or-nothing responses. Previous models examined the relaxation of the all-or-nothing response by assuming partial preference (e.g., predators preferentially forage on the primary prey even when they also attack the alternative prey). In this study, I consider individual variation in two predator traits (prey density perception and handling time) as the sources of the variation in the threshold density, which can make empirical data appear deviated from the expectation. I examine how community models with partial preference and individual variation differ in their dynamics and show that the differences can be substantial. For example, the dynamics of a model based on individual variation can be more stable (e.g., stable in a wider parameter region) than that of a model based on partial preference. As the general statistical property (Jensen’s inequality) is a main factor that causes the differences, the results of the study have general implications to the interpretation of models based on average per-capita rates.     

Influence of intra‐ and interspecific variation in predator–prey body size ratios on trophic interaction strengths

1. Predation is a pervasive force that structures food webs and directly influences ecosystem functioning. The relative body sizes of predators and prey may be an important determinant of interaction strengths. However, studies quantifying the combined influence of intra‐ and interspecific variation in predator–prey body size ratios are lacking.
2. We use a comparative functional response approach to examine interaction strengths between three size classes of invasive bluegill and largemouth bass toward three scaled size classes of their tilapia prey. We then quantify the influence of intra‐ and interspecific predator–prey body mass ratios on the scaling of attack rates and handling times.
3. Type II functional responses were displayed by both predators across all predator and prey size classes. Largemouth bass consumed more than bluegill at small and intermediate predator size classes, while large predators of both species were more similar. Small prey were most vulnerable overall; however, differential attack rates among prey were emergent across predator sizes. For both bluegill and largemouth bass, small predators exhibited higher attack rates toward small and intermediate prey sizes, while larger predators exhibited greater attack rates toward large prey. Conversely, handling times increased with prey size, with small bluegill exhibiting particularly low feeding rates toward medium–large prey types. Attack rates for both predators peaked unimodally at intermediate predator–prey body mass ratios, while handling times generally shortened across increasing body mass ratios.
4. We thus demonstrate effects of body size ratios on predator–prey interaction strengths between key fish species, with attack rates and handling times dependent on the relative sizes of predator–prey participants.
5. Considerations for intra‐ and interspecific body size ratio effects are critical for predicting the strengths of interactions within ecosystems and may drive differential ecological impacts among invasive species as size ratios shift.