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A recent field manipulation on a terrestrial vertebrate showed that the fear of predators alone altered anti-predator defences to such an extent that it greatly reduced the reproduction of prey. Because fear can evidently affect the populations of terrestrial vertebrates, we proposed a predator–prey model incorporating the cost of fear into prey reproduction. Our mathematical analyses show that high levels of fear (or equivalently strong anti-predator responses) can stabilize the predator–prey system by excluding the existence of periodic solutions. However, relatively low levels of fear can induce multiple limit cycles via subcritical Hopf bifurcations, leading to a bi-stability phenomenon. Compared to classic predator–prey models which ignore the cost of fear where Hopf bifurcations are typically supercritical , Hopf bifurcations in our model can be both supercritical and subcritical by choosing different sets of parameters. We conducted numerical simulations to explore the relationships between fear effects and other biologically related parameters (e.g. birth/death rate of adult prey), which further demonstrate the impact that fear can have in predator–prey interactions. For example, we found that under the conditions of a Hopf bifurcation, an increase in the level of fear may alter the direction of Hopf bifurcation from supercritical to subcritical when the birth rate of prey increases accordingly. Our simulations also show that the prey is less sensitive in perceiving predation risk with increasing birth rate of prey or increasing death rate of predators, but demonstrate that animals will mount stronger anti-predator defences as the attack rate of predators increases.

Invasive species threaten biodiversity globally, and invasive mammalian predators are particularly damaging, having contributed to considerable species decline and extinction. We provide a global metaanalysis of these impacts and reveal their full extent. Invasive predators are implicated in 87 bird, 45 mammal, and 10 reptile species extinctions—58% of these groups’ contemporary extinctions worldwide. These figures are likely underestimated because 23 critically endangered species that we assessed are classed as “possibly extinct.” Invasive mammalian predators endanger a further 596 species at risk of extinction, with cats, rodents, dogs, and pigs threatening the most species overall. Species most at risk from predators have high evolutionary distinctiveness and inhabit insular environments. Invasive mammalian predators are therefore important drivers of irreversible loss of phylogenetic diversity worldwide. That most impacted species are insular indicates that management of invasive predators on islands should be a global conservation priority. Understanding and mitigating the impact of invasive mammalian predators is essential for reducing the rate of global biodiversity loss.

Antagonistic selection by different predators has been suggested to underlie variation in morphological antipredator traits among and within species. Direct empirical proof is equivocal, however, given the potential interrelationships of morphological and behavioral traits. Here, we tested whether spines in larvae of the dragonfly Leucorrhinia caudalis, which are selected for by fish predators, are selected against by invertebrate aeshnid predators. Using a manipulative approach by cutting spines instead of making comparisons among species or inducing spines, we were able to decouple the presence of spines from other potentially covarying morphological antipredator traits. Results showed survival selection for the loss of spines imposed by invertebrate predation. Moreover, spined and nonspined larval L. caudalis did not differ in the key antipredator behaviors, activity level, and escape burst swimming speed. The observed higher mortality of spined larvae can therefore be directly linked to selection by aeshnid predation against spines.

It is an open question how animals find food in dynamic natural environments where they possess little or no knowledge of where resources are located. Foraging theory predicts that in environments with sparsely distributed target resources, where forager knowledge about resources' locations is incomplete, Lévy flight movements optimize the success of random searches. However, the putative success of Lévy foraging has been demonstrated only in model simulations. Here, we use high-temporal-resolution Global Positioning System (GPS) tracking of wandering (Diomedea exulans) and black-browed albatrosses (Thalassarche melanophrys) with simultaneous recording of prey captures, to show that both species exhibit Lévy and Brownian movement patterns. We find that total prey masses captured by wandering albatrosses during Lévy movements exceed daily energy requirements by nearly fourfold, and approached yields by Brownian movements in other habitats. These results, together with our reanalysis of previously published albatross data, overturn the notion that albatrosses do not exhibit Lévy patterns during foraging, and demonstrate that Lévy flights of predators in dynamic natural environments present a beneficial alternative strategy to simple, spatially intensive behaviors. Our findings add support to the possibility that biological Lévy flight may have naturally evolved as a search strategy in response to sparse resources and scant information.

Sensorimotor control in vertebrates relies on internal models. When extending an arm to reach for an object, the brain uses predictive models of both limb dynamics and target properties. Whether invertebrates use such models remains unclear. Here we examine to what extent prey interception by dragonflies ( Plathemis lydia ), a behaviour analogous to targeted reaching, requires internal models. By simultaneously tracking the position and orientation of a dragonfly’s head and body during flight, we provide evidence that interception steering is driven by forward and inverse models of dragonfly body dynamics and by models of prey motion. Predictive rotations of the dragonfly’s head continuously track the prey’s angular position. The head–body angles established by prey tracking appear to guide systematic rotations of the dragonfly’s body to align it with the prey’s flight path. Model-driven control thus underlies the bulk of interception steering manoeuvres, while vision is used for reactions to unexpected prey movements. These findings illuminate the computational sophistication with which insects construct behaviour. This study tracks dragonfly head and body movements during high-velocity and high-precision prey-capture flights, and shows that the dragonfly uses predictive internal models and reactive control to build an interception trajectory that complies with biomechanical constraints. Dragonflies use complex internal models Primates and other vertebrates use internal models to control and predict the consequences of their movements, but invertebrates were thought to rely mostly on reflexes. In a study using motion capture to track the head and body movements of dragonflies catching flying prey, Anthony Leonardo and colleagues demonstrate a complexity of behaviour not previously seen in an insect. Approaching from below, the dragonfly's head locks onto its target while its body manoeuvres to align to the prey's flight path and reduce the distance to the prey. Rather than generating these steering movements reactively, by responding only to changes in prey motion, dragonflies using both reactive and predictive control. These predictions account for the motion of the prey and the dragonfly's own body, and are consistent with generation by internal models. The experimental accessibility of the insect nervous system, combined with the load-carrying capacity of the dragonfly, opens these general principles of motor control to detailed mechanistic dissection.

The role of species interactions in controlling the interplay between the stability of ecosystems and their biodiversity is still not well understood. The ability of ecological communities to recover after small perturbations of the species abundances (local asymptotic stability) has been well studied, whereas the likelihood of a community to persist when the conditions change (structural stability) has received much less attention. Our goal is to understand the effects of diversity, interaction strengths and ecological network structure on the volume of parameter space leading to feasible equilibria. We develop a geometrical framework to study the range of conditions necessary for feasible coexistence. We show that feasibility is determined by few quantities describing the interactions, yielding a nontrivial complexity–feasibility relationship. Analysing more than 100 empirical networks, we show that the range of coexistence conditions in mutualistic systems can be analytically predicted. Finally, we characterize the geometric shape of the feasibility domain, thereby identifying the direction of perturbations that are more likely to cause extinctions. A central question in theoretical ecology is how diverse species can coexist in communities, and how that coexistence depends on network properties. Here, Grilli et al . quantify the extent of feasible coexistence of empirical networks, showing that it is smaller for trophic than mutualism networks.

This study examined the predator-prey interaction between Flaccisagitta enflata , a dominant chaetognath species, and copepods in the southwestern Gulf of Mexico to investigate the roles of environmental variables and predator-prey encounters in the feeding rate of F. enflata on copepods and to analyze the gut content of the predator throughout three seasons. Zooplankton samples were collected in summer, fall, and winter in both neritic and oceanic waters. Predator-prey encounters were examined under calm and turbulent conditions to test the influence of wind-induced turbulence. Results indicated that encounters varied across seasons and zones: under calm conditions, they ranged from 11 to 75 copepods/chaetognath.day; under turbulent conditions, encounters increased by 1.5 to 1.8 times at the surface. Statistical tests revealed significant differences in feeding rates across seasons and zones: in summer and fall, feeding rates were higher in neritic waters, whereas in winter, they were higher in the oceanic zone. The primary factors influencing feeding rates were temperature, encounter rates, and salinity. Higher summer and fall temperatures resulted in shorter digestion times and, consequently, higher feeding rates (0.44 to 0.74 copepods/chaetognath day). The encounter rates, strongly correlated with copepod density, positively influenced feeding rates, particularly in summer and fall, with the highest values in the neritic zone. The lowest salinity records, caused by river discharges and observed in winter in shelf waters, corresponded with the lowest feeding rates (0.30 copepods/chaetognath.day). Freshwater inflows carrying suspended sediments increase turbidity, which potentially interferes with the predatory mechanisms of F. enflata and diminishes its feeding rates. Specifically, the main ingested copepods were members of the genera Temora and Euaugaptilus. These findings improve our understanding of the predator-prey interaction between the most abundant zooplankton organisms.

Colonially breeding birds and mammals form some of the largest gatherings of apex predators in the natural world and have provided model systems for studying mechanisms of population regulation in animals. According to one influential hypothesis, intense competition for food among large numbers of spatially constrained foragers should result in a zone of prey depletion surrounding such colonies, ultimately limiting their size. However, while indirect and theoretical support for this phenomenon, known as “Ashmole’s halo,” has steadily accumulated, direct evidence remains exceptionally scarce. Using a combination of vessel-based surveys and Global Positioning System tracking, we show that pelagic seabirds breeding at the tropical island that first inspired Ashmole’s hypothesis do indeed deplete their primary prey species (flying fish; Exocoetidae spp.) over a considerable area, with reduced prey density detectable >150 km from the colony. The observed prey gradient was mirrored by an opposing trend in seabird foraging effort, could not be explained by confounding environmental variability, and can be approximated using a mechanistic consumption–dispersion model, incorporating realistic rates of seabird predation and random prey dispersal. Our results provide a rare view of the resource footprint of a pelagic seabird colony and reveal how aggregations of these central-place foraging, marine top predators profoundly influence the oceans that surround them.

Long-distance terrestrial migrations are imperiled globally. We determined both round-trip migration distances (straight-line measurements between migratory end points) and total annual movement (sum of the distances between successive relocations over a year) for a suite of large mammals that had potential for long-distance movements to test which species displayed the longest of both. We found that caribou likely do exhibit the longest terrestrial migrations on the planet, but, over the course of a year, gray wolves move the most. Our results were consistent with the trophic-level based hypothesis that predators would move more than their prey. Herbivores in low productivity environments moved more than herbivores in more productive habitats. We also found that larger members of the same guild moved less than smaller members, supporting the ‘gastro-centric’ hypothesis. A better understanding of migration and movements of large mammals should aid in their conservation by helping delineate conservation area boundaries and determine priority corridors for protection to preserve connectivity. The magnitude of the migrations and movements we documented should also provide guidance on the scale of conservation efforts required and assist conservation planning across agency and even national boundaries.

Numerical models indicate that collective animal behavior may emerge from simple local rules of interaction among the individuals. However, very little is known about the nature of such interaction, so that models and theories mostly rely on aprioristic assumptions. By reconstructing the three-dimensional positions of individual birds in airborne flocks of a few thousand members, we show that the interaction does not depend on the metric distance, as most current models and theories assume, but rather on the topological distance. In fact, we discovered that each bird interacts on average with a fixed number of neighbors (six to seven), rather than with all neighbors within a fixed metric distance. We argue that a topological interaction is indispensable to maintain a flock's cohesion against the large density changes caused by external perturbations, typically predation. We support this hypothesis by numerical simulations, showing that a topological interaction grants significantly higher cohesion of the aggregation compared with a standard metric one.