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622 results for “Prey and predator”
Fig. 11 in Patterns of drilling predation of cassid gastropods preying on echinoids from the middle Miocene of Poland
Fig. 11. Drilling predation intensities recognised for the particular size classes of preys; Fq, relative frequency of drill holes; grey areas indicate size classes represented by 30 or more specimens. E. linearis and E. pusillus collected from the coarse−grained Heterostegina Sands, and E. pseudopusillus from the fine−grained Heterostegina Sands. Confidence intervals computed from the formulas presented in captions to Fig. 9.
Fig. 2 in Patterns of drilling predation of cassid gastropods preying on echinoids from the middle Miocene of Poland
Fig. 2. Relative abundances of Echinocyamus species in particular samples compared to the results of grain−size analysis of the samples.
Fig. 1 in Quantification of prey consumption by the predators Chauliognathus flavipes (Coleoptera: Cantharidae), Cycloneda sanguinea (Coleoptera: Coccinellidae), and Orius insidiosus (Heteroptera: Anthocoridae)
Fig. 1. Mean number of prey (± SE) consumed by (A) Orius insidiosus, (B) Cycloneda sanguinea, and (C) Chauliognathus flavipes predators. Columns with the same letter (within predator species) are not different (Tukey's multiple comparison test, P <0.05).
Fig. 2 in Quantifying insect predation in laboratory arenas: the effect of prey acclimation
Fig. 2. Behavioral responses of Orgyia leucostigma caterpillars that acclimated on the plant for less than 20 min (20 min), from 20 to <40 min (40 min), and from 40 to 60 min (60 min) to the attacks of Polistes fuscatus wasps. *P <0.05; ns: P> 0.05. No response = caterpillars that did not respond to predators by dropping. Drop = caterpillars that dropped from the leaf in response to the predator.
Fig. 1 in Quantifying insect predation in laboratory arenas: the effect of prey acclimation
Fig. 1. The mortality of Orgyia leucostigma caterpillars that acclimated on the plant for less than 20 min (20 min), from 20 to <40 min (40 min), and from 40 to 60 min (60 min) before exposure to Polistes fuscatus wasps. Treatments with the same letter are not significantly different (P> 0.05).
Figure 2 in Natural prey of the crab spider Thomisus onustus (Araneae: Thomisidae), an extremely powerful predator of insects
Figure 2. Some of the largest prey captured by Thomisus onustus juveniles together with their captors. (A) Syrphid fly; (B) bombyliid fly; (C) calliphorid fly; (D) Cataglyphis setipes ant.
Figure 1 in Natural prey of the crab spider Thomisus onustus (Araneae: Thomisidae), an extremely powerful predator of insects
Figure 1. Distribution of prey of different sex–age groups of Thomisus onustus (black, late instar and adult females; grey, medium-sized juveniles; dotted, adult males; white, small juveniles) in different size categories (body lengths of prey expressed as percentages of the body lengths of their captors).
Fig. 3 in Spatio-temporal correlations of large predators and their prey in western Thailand
Fig. 3. Kernel density estimates of daily predator activity patterns. A, tiger, leopard, and dhole; B, tiger and leopard; C, tiger and dhole; D, leopard and dhole. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates.
Fig. 5 in Spatio-temporal correlations of large predators and their prey in western Thailand
Fig. 5. Kernel density estimates of daily activity patterns of leopards and prey species. A, leopard and gaur; B, leopard and sambar; C, leopard and barking deer; D, leopard and tapir; E, leopard and wild boar. The dashed lines are kernel density estimates for leopards and the solid lines are kernel density estimates for the prey species. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates.
Fig. 4 in Spatio-temporal correlations of large predators and their prey in western Thailand
Fig. 4. Kernel density estimates of daily activity patterns of tigers and prey species. A, tiger and gaur; B, tiger and sambar; C, tiger and tapir; D, tiger and barking deer; E, tiger and wild boar. The dashed lines are kernel density estimates for tigers and the solid lines are kernel density estimates for the prey species. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates.
Fig. 6 in Spatio-temporal correlations of large predators and their prey in western Thailand
Fig. 6. Kernel density estimates of daily activity patterns of dholes and prey species. A, dhole and gaur; B, dhole and sambar; C, dhole and tapir; D, dhole and barking deer; E, dhole and wild boar. The dashed lines are kernel density estimates for dholes and the solid lines are kernel density estimates for the prey species. The shaded areas indicate the overlap coefficient; that is, the area under the minimum of the two density estimates.
Predator discrimination of prey promotes the predator-mediated coexistence of prey species
<p><span>The predator discrimination of prey can affect predation intensity and the prey density-dependence of predators, which has the potential to alter the coexistence of prey species. We used a predator–prey population dynamics model accounting for the predator's adaptive diet choice and predator discrimination of prey to investigate how the latter influences prey coexistence. The model revealed that: (1) prey species that are perceived as belonging to the same species by a predator are attacked in the same manner, and it is more difficult for them to coexist than those that are recognised as different prey species; and (2) prey species that are not discriminated by a predator—and therefore cannot coexist—may coexist in the presence of an alternative predator that does discriminate between them. These results suggest that prey diversity, which favours the predator discrimination of prey, and the different capabilities of predators to identify prey species both enhance prey coexistence.</span></p>
Data and code for: Changes in prey body size differentially reduces predation risk across predator and prey abundances
<p>Trophic interactions underpin the structure of ecological communities by describing the rate at which consumers exploit their resources. The rates at which predators consume their prey are influenced by prey traits, with many species inducing defensive modifications to prey traits following the threat of predation. Here we use different clonal lines of the protist <em>Paramecium</em> being consumed by <em>Stenostomum</em> predators to highlight how differences in prey traits impact rates of predation. Clonal lines differed in their body width traits and in their ability to induce changes in body width. By using a factorial cross of predator and prey abundances for different clonal lines we demonstrate how evolutionary or induced alterations in prey traits can impact the relative threat of predation. Our experiments show how interference among predators impacts predation rate and how increased body width increased predator handling times. Given that reductions in the strength of interspecific interactions are associated with increased levels of overall community stability, our results indicate how individual-level changes may scale up to impact whole communities. </p>
Data from: Dynamic balancing of risks and rewards in a large herbivore: Further extending predator-prey concepts to road ecology
<p>Animal behavior is shaped by the ability to identify risks and profitably balance the levels of risks encountered with the payoffs experienced. Anthropogenic disturbances like roads generate novel risks and opportunities that wildlife must accurately perceive and respond to. Basic concepts in predator-prey ecology are often used to understand responses of animals to roads (e.g., increased vigilance, selection for cover in their vicinity). However, prey often display complex behaviors such as modulating space use given varying risks and rewards, and it is unclear if such dynamic balancing is used by animals in the context of road crossings.</p> <p>We tested whether animals dynamically balance risks and rewards relative to roads using extensive field -based and GPS collar data from elk in Yoho National Park (British Columbia, Canada) where a major highway completely bisects their range during most of the year.</p> <p>We analyzed elk behavior by combining hidden Markov movement models with a step-selection function framework. Rewards were indexed by a dynamic map of available forage biomass and risks were indexed by road crossings and traffic volumes.</p> <p>We found that elk generally selected intermediate and high forage biomass and avoided crossing the road. Most of the time, elk modulated their behavior given varying risks and rewards. When crossing the highway compared with not crossing, elk selected for greater forage biomass and this selection was stronger as the number of highway crossings increased. However, with traffic volume, elk only balanced foraging rewards when they crossed a single time during a travel sequence.</p> <p>Using a road ecology system, we empirically tested an important component of predator-prey ecology – the ability to dynamically modulate behavior in response to varying levels of risks and rewards. Such a test articulates how decision-making processes that consider the spatiotemporal variation in risks and rewards allow animals to successfully and profitably navigate busy roads. Applying well-developed concepts in predator-prey theory helps understand how animals respond to anthropogenic disturbances and anticipate the adaptive capacity for individuals and populations to adjust to rapidly changing environments.</p>
The influence of prey density and pollen on the predation and oviposition rate of Amblyseius swirskii on Echinothrips americanus
<p>Data set of the research: "The influence of prey density and pollen on the predation and oviposition rate of Amblyseius swirskii on Echinothrips americanus". The dataset contains observations of predation and oviposition of Amblyseius swirskii on Echinothrips americanus. The different conditions were leaf area and prey density.</p>
Landscape heterogeneity provides co-benefits to predator and prey
<p>Predator populations are imperiled globally, due in part to changing habitat and trophic interactions. Theoretical and laboratory studies suggest that heterogeneous landscapes containing prey refuges acting as source habitats can benefit both predator and prey populations, although the importance of heterogeneity in natural systems is uncertain. Here, we tested the hypothesis that landscape heterogeneity mediates predator-prey interactions between the California spotted owl (<em>Strix occidentalis occidentalis</em>) – a mature forest species – and one of its principal prey, the dusky-footed woodrat (<em>Neotoma</em> <em>fuscipes</em>) – a younger forest species – to the benefit of both. We did so by combining estimates of woodrat density and survival from live-trapping and VHF tracking with direct observations of prey deliveries to dependent young by owls in both heterogeneous and homogeneous home ranges. Woodrat abundance was approximately 2.5x higher in owl home ranges (1,412 hectares) featuring greater heterogeneity in vegetation types (1,805.0 ± 50.2 SE) compared to those dominated by mature forest (727.3 ± 51.9 SE), in large part because of high densities in young forests appearing to act as sources promoting woodrat densities in nearby mature forests. Woodrat mortality rates were low across vegetation types and did not differ between heterogeneous and homogeneous home ranges, yet all observed predation by owls occurred within mature forests, suggesting young forests may act as woodrat refuges. Owls exhibited a type 1 functional response, consuming approximately 2.5x more woodrats in heterogeneous (31.1/month ± 5.2 SE) versus homogeneous (12.7/month ± 3.7 SE) home ranges. While consumption of smaller-bodied alternative prey partially compensated for lower woodrat consumption in homogeneous home ranges, owls nevertheless consumed 30% more biomass in heterogeneous home ranges – approximately equivalent to the energetic needs of producing one additional offspring. Thus, a mosaic of vegetation types including young forest patches increased woodrat abundance and availability that, in turn, provided energetic and potentially reproductive benefits to mature forest-associated spotted owls. More broadly, our findings provide strong empirical evidence that heterogeneous landscapes containing prey refuges can benefit both predator and prey populations. As anthropogenic activities continue to homogenize landscapes globally, promoting heterogeneous systems with prey refuges may benefit imperiled predators.</p>
Numerical response of predator to prey: Dynamic interactions and population cycles in Eurasian lynx and roe deer
<p>The dynamic interactions between predators and their prey have two fundamental processes; numerical and functional responses. Numerical response is defined as predator growth rate as a function of prey density or both prey and predator densities [dP/dt = f(N, P)]. Functional response is defined as the kill rate by an individual predator being a function of prey density or prey and predator densities combined. Although there are relatively many studies on the functional response in mammalian predators, numerical response remains poorly documented. We studied numerical response of Eurasian lynx (<em>Lynx lynx</em>) to various densities of its primary prey species, roe deer (<em>Capreolus</em> <em>capreolus</em>), and to itself (lynx). We exploited an unusual natural situation, spanning three decades where lynx, after a period of absence in central and southern Sweden, during which roe deer populations had grown to high densities, subsequently recolonized region after region, from north to south. We divided the study area into seven regions, with increasing productivity from north to south. We found strong effects of both roe deer density and lynx density on lynx numerical response. Thus, both resources and intraspecific competition for these resources are important to understand the lynx population dynamic. We built a series of deterministic lynx–roe deer models and applied them to the seven regions. We found a very good fit between these Lotka-Volterra-type models and the data. The deterministic models produced almost cyclic dynamics or dampened cycles in five of the seven regions. Thus, we documented population cycles in this large-predator-large-herbivore system, which is rarely done. The amplitudes in the dampened cycles decreased towards the south. Thus, the dynamics between lynx and roe deer became more stable with increasing carrying capacity for roe deer, which is related to higher productivity in the environment. This increased stability could be explained by variation in predation risk, where human presence can act as prey refugia, and by a more diverse prey guild that will weaken the direct interaction between lynx and roe deer.</p>
Predator home range size mediates indirect interactions between prey species in an arctic vertebrate community
<ol> <li>Indirect interactions are widespread among prey species that share a common predator, but the underlying mechanisms driving these interactions are often unclear, and our ability to predict their outcome is limited. </li> <li>Changes in behavioural traits that impact predator space use could be a key proximal mechanism mediating indirect interactions, but there is little empirical evidence of the causes and consequences of such behavioural-numerical response in multi-species systems. </li> <li>Here, we investigate the complex ecological relationships between seven prey species sharing a common predator. We used a path analysis approach on a comprehensive 9-year dataset simultaneously tracking predator space use, prey densities, and prey mortality rate on key species of a simplified Arctic food-web. </li> <li>We show that high availability of a clumped and spatially predictable prey (goose eggs) leads to a two-fold reduction in predator (arctic fox) home range size, which increases local predator density and strongly decreases nest survival of an incidental prey (American golden plover). On the other hand, a scattered cyclic prey with potentially lower spatial predictability (lemming) had a weaker effect on fox space use and an overall positive impact on the survival of incidental prey.</li> <li>These contrasting effects underline the importance of studying behavioural responses of predators in multi-prey systems and to explicitly integrate behavioural-numerical responses in multi-species predator-prey models.</li> </ol>
Data from: Predator-prey Interactions of Terrestrial Invertebrates are Determined by Predator Body Size and Species Identity
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Data from: Habitat edge responses of generalist predators are predicted by prey and structural resources
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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