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Animal Vigilance builds on the author's previous publication with Academic Press (Social Predation: How Group Living Benefits Predators and Prey) by developing several other themes including the development and mechanisms underlying vigilance, as well as developing more fully the evolution and function of vigilance.Animal vigilance has been.

THE NEUROETHOLOGY OF PREDATION AND ESCAPE To eat and not get eaten is key to animal survival, and the arms race between predators and prey has driven the evolution of many rapid and spectacular behaviours. This book explores the neural mechanisms controlling predation and escape, where specialisations in afferent pathways, central circuits, motor control and biomechanics can be traced through to natural animal behaviour. Each chapter provides an integrated and comparative review of case studies in neuroethology. Ranging from the classic studies on bat biosonar and insect counter-measures, through to fish-eating snails armed with powerful neurotoxins, the book covers a diverse and fascinating range of adaptations. Common principles of biological design and organization are highlighted throughout the text. The book is aimed at several audiences: * for lecturers and students. This synthesis will help to underpin the curriculum in neuroscience and behavioural biology, especially for courses focusing on neuroethology * for postgraduate students. The sections devoted to your area of specialism will give a flying start to your research reading, while the other chapters offer breadth and insights from comparative studies * for academic researchers. The book will provide a valuable resource and an enjoyable read Above all, we hope this book will inspire the next generation of neuroethologists.

Better known as the predator-prey relationship, the consumer-resource relationship means the situation where a single species of organisms consumes for survival and reproduction. For example, Escherichia coli consumes glucose, cows consume grass, cheetahs consume baboons; these three very different situations, the first concerns the world of bacteria and the resource is a chemical species, the second concerns mammals and the resource is a plant, and in the final case the consumer and the resource are mammals, have in common the fact of consuming. In a chemostat, microorganisms generally consume (abiotic) minerals, but not always, bacteriophages consume bacteria that constitute a biotic resource. The Chemostat book dealt only with the case of abiotic resources. Mathematically this amounts to replacing in the two equation system of the chemostat the decreasing function by a general increasing then decreasing function. This simple change has greatly enriched the theory. This book shows in this new framework the problem of competition for the same resource.

Studies that focus on single predator-–prey interactions can be inadequate for understanding antipredator responses in multi-predator systems. Yet there is still a general lack of information about the strategies of prey to minimize predation risk from multiple predators at the landscape level. Here we examined the distribution of seven African ungulate species in the fenced Karongwe Game Reserve (KGR), South Africa, as a function of predation risk from all large carnivore species (lion, leopard, cheetah, African wild dog, and spotted hyena). Using observed kill data, we generated ungulate-specific predictions of relative predation risk and of riskiness of habitats. To determine how ungulates minimize predation risk at the landscape level, we explicitly tested five hypotheses consisting of strategies that reduce the probability of encountering predators, and the probability of being killed. All ungulate species avoided risky habitats, and most selected safer habitats, thus reducing their probability of being killed. To reduce the probability of encountering predators, most of the smaller prey species (impala, warthog, waterbuck, kudu) avoided the space use of all predators, while the larger species (wildebeest, zebra, giraffe) only avoided areas where lion and leopard space use were high. The strength of avoidance for the space use of predators generally did not correspond to the relative predation threat from those predators. Instead, ungulates used a simpler behavioral rule of avoiding the activity areas of sit-and-pursue predators (lion and leopard), but not those of cursorial predators (cheetah and African wild dog). In general, selection and avoidance of habitats was stronger than avoidance of the predator activity areas. We expect similar decision rules to drive the distribution pattern of ungulates in other African savannas and in other multi-predator systems, especially where predators differ in their hunting modes.

Individual predator and prey species exhibit coupled population dynamics in simple laboratory systems and simple natural communities. It is unclear how often such pairwise coupling occurs in more complex communities, in which an individual predator species might feed on several prey species and an individual prey species might be attacked by several predators. To examine this problem, we applied multivariate autoregressive state-space (MARSS) models to 5-year time-series of monthly surveys of a predatory fish, the eastern mosquitofish (Gambusia holbrooki), and its littoral zone prey species, the least killifish (Heterandria formosa), in three locations in north Florida. The MARSS models were consistent with coupled predator–prey dynamics at two of the three locations. In one of these two locations, the estimated densities of the two species displayed classic predator–prey oscillations. In the third location, there was a positive effect of killifish density on mosquitofish density but no detectable effect of mosquitofish density on killifish density. In all three locations, increased submergent vegetation cover was associated with increased prey density but not increased predator density. Eigenvalues analyses for the joint predator–prey dynamics indicated that one of the cyclic locations had more stable dynamics than the other locations. The three different patterns demonstrate that the dynamics of a pairwise predator–prey interaction emerge not only from the characteristics of the prey and the predator, but also those of the habitat and trophic web in which the predator and prey are embedded.

Reaction-diffusion (RD) systems with time delays have been commonly used in modeling biological systems and can significantly change the dynamics of these systems. For predator-prey model with modified Leslie-Gower and Holling-type III schemes governed by RD equations, instability induced by time delay can generate spiral waves. Considering that populations are usually organized as networks instead of being continuously distributed in space, it is essential to study the predator-prey model on complex networks. In this paper, we investigate instability induced by time delay for the corresponding network organized system and explore pattern formations on several different networks including deterministic networks and random networks. We firstly obtain instability condition via linear stability analysis and then the condition is applied to study pattern formations for the model in question. The simulation results show that wave patterns can be generated on different networks. However, wave patterns on random networks differ significantly from patterns on deterministic networks. Finally, we discuss the influences of network topology on wave patterns from the aspects of amplitude and period, and reveal the ecology significance implied by these results.

Background Studies that attempt to measure shifts in species distributions often consider a single species in isolation. However, understanding changes in spatial overlap between predators and their prey might provide deeper insight into how species redistribution affects food web dynamics. Predator–prey overlap metrics Here, we review a suite of 10 metrics [range overlap, area overlap, the local index of collocation (Pianka's O), Hurlbert's index, biomass‐weighted overlap, asymmetrical alpha, Schoener's D, Bhattacharyya's coefficient, the global index of collocation and the AB ratio] that describe how two species overlap in space, using concepts such as binary co‐occurrence, encounter rates, spatial niche similarity, spatial independence, geographical similarity and trophic transfer. We describe the specific ecological insights that can be gained using each overlap metric, in order to determine which is most appropriate for describing spatial predator–prey interactions for different applications. Simulation and case study We use simulated predator and prey distributions to demonstrate how the 10 metrics respond to variation in three types of predator–prey interactions: changing spatial overlap between predator and prey, changing predator population size and changing patterns of predator aggregation in response to prey density. We also apply these overlap metrics to a case study of a predatory fish (arrowtooth flounder, Atheresthes stomias) and its prey (juvenile walleye pollock, Gadus chalcogrammus) in the Eastern Bering Sea, AK, USA. We show how the metrics can be applied to understand spatial and temporal variation in the overlap of species distributions in this rapidly changing Arctic ecosystem. Conclusions Using both simulated and empirical data, we provide a roadmap for ecologists and other practitioners to select overlap metrics to describe particular aspects of spatial predator–prey interactions. We outline a range of research and management applications for which each metric may be suited.

1. In response to multiple Stressors, coral reef health has declined in recent decades, with reefs exhibiting reduced living coral and structural complexity, and a concomitant rise in the dominance of algal resources. Reef degradation alters food availability and reduces the diversity and density of refuges for prey. These changes affect predator-prey interactions and can have cascading impacts on food webs and fisheries productivity. 2. We use a size-based ecosystem model of coral reefs that incorporates the influence of structural complexity, benthic primary production and detrital recycling to explore how predator-prey interactions and fisheries productivity respond to a gradient of reef degradation. 3. We show that fisheries productivity overall may be robust to initial stages of reef degradation because the benefits of increased resources outweigh the costs of moderate refuge decline. However, the assemblage composition and size structure of reef fish will differ on degraded reefs, with herbivores and invertivores contributing relatively more to productivity. 4. More significant losses of refuges associated with the erosion of structural complexity correspond to fisheries productivity losses of at least 35% compared to healthy reefs. 5. Synthesis and applications. Our model provides fisheries managers with quantitative predictions about how fisheries productivity may change in response to the ongoing degradation of coral reefs. We predict an initial increase in productivity at intermediate reef degradation, followed by a drastic decline when structural complexity is lost. We also capture subtle changes to potential catch composition and fish size, including increases in smaller herbivorous and invertivorous fish from degraded reefs, which will undoubtedly impact fisheries value. On the one hand, our results reassure for continued productivity in the short term, but on the other, we warn against complacency. Management must change to capture any potential benefits to fisheries, and long-term sustainability still depends on the maintenance of complex coral reef habitats.

Summary Predator–prey interactions are mediated by the structural complexity of habitats, but disentangling the many facets of structure that contribute to this mediation remains elusive. In a world replete with altered landscapes and biological invasions, determining how structure mediates the interactions between predators and novel prey will contribute to our understanding of invasions and predator–prey dynamics in general. Here, using simplified experimental arenas, we manipulate predator‐free space, whilst holding surface area and volume constant, to quantify the effects on predator–prey interactions between two resident gammarid predators and an invasive prey, the Ponto‐Caspian corophiid Chelicorophium curvispinum. Systematically increasing predator‐free space alters the functional responses (the relationship between prey density and consumption rate) of the amphipod predators by reducing attack rates and lengthening handling times. Crucially, functional response shape also changes subtly from destabilizing Type II towards stabilizing Type III, such that small increases in predator‐free space to result in significant reductions in prey consumption at low prey densities. Habitats with superficially similar structural complexity can have considerably divergent consequences for prey population stability in general and, particularly, for invasive prey establishing at low densities in novel habitats. Lay Summary

1. Ecologists have long searched for a framework of a priori species traits to help predict predator–prey interactions in food webs. Empirical evidence has shown that predator hunting mode and predator and prey habitat domain are useful traits for explaining predator–prey interactions. Yet, individual experiments have yet to replicate predator hunting mode, calling into question whether predator impacts can be attributed to hunting mode or merely species identity. 2. We tested the effects of spider predators with sit-and-wait, sit-and-pursue and active hunting modes on grasshopper habitat domain, activity and mortality in a grassland system. We replicated hunting mode by testing two spider predator species of each hunting mode on the same grasshopper prey species. We observed grasshoppers with and without each spider species in behavioural cages and measured their mortality rates, movements and habitat domains. We likewise measured the movements and habitat domains of spiders to characterize hunting modes. 3. We found that predator hunting mode explained grasshopper mortality and spider and grasshopper movement activity and habitat domain size. Sit-and-wait spider predators covered small distances over a narrow domain space and killed fewer grasshoppers than sit-and-pursue and active predators, which ranged farther distances across broader domains and killed more grasshoppers, respectively. Prey adjusted their activity levels and horizontal habitat domains in response to predator presence and hunting mode: sedentary sit-and-wait predators with narrow domains caused grasshoppers to reduce activity in the same-sized domain space; more mobile sit-and-pursue predators with broader domains caused prey to reduce their activity within a contracted horizontal (but not vertical) domain space; and highly mobile active spiders led grasshoppers to increase their activity across the same domain area. All predators impacted prey activity, and sit-and-pursue predators generated strong effects on domain size. 4. This study demonstrates the validity of utilizing hunting mode and habitat domain for predicting predator–prey interactions. Results also highlight the importance of accounting for flexibility in prey movement ranges as an anti-predator response rather than treating the domain as a static attribute.