Prey Tracking Research Articles

Disturbance-mediated changes to boreal mammal spatial networks in industrializing landscapes.

Compound effects of anthropogenic disturbances on wildlife emerge through a complex network of direct responses and species interactions. Land-use changes driven by energy and forestry industries are known to disrupt predator-prey dynamics in boreal ecosystems, yet how these disturbance effects propagate across mammal communities remains uncertain. Using structural equation modeling, we tested disturbance-mediated pathways governing the spatial structure of multipredator multiprey boreal mammal networks across a landscape-scale disturbance gradient within Canada's Athabasca oil sands region. Linear disturbances had pervasive direct effects, increasing site use for all focal species, except black bears and threatened caribou, in at least one landscape. Conversely, block (polygonal) disturbance effects were negative but less common. Indirect disturbance effects were widespread and mediated by caribou avoidance of wolves, tracking of primary prey by subordinate predators, and intraguild dependencies among predators and large prey. Context-dependent responses to linear disturbances were most common among prey and within the landscape with intermediate disturbance. Our research suggests that industrial disturbances directly affect a suite of boreal mammals by altering forage availability and movement, leading to indirect effects across a range of interacting predators and prey, including the keystone snowshoe hare. The complexity of network-level direct and indirect disturbance effects reinforces calls for increased investment in addressing habitat degradation as the root cause of threatened species declines and broader ecosystem change.

A peripheral subepithelial network for chemotactile processing in the predatory sea slug Pleurobranchaea californica.

Many soft-bodied animals have extensive peripheral nervous systems (PNS) with significant sensory roles. One such, the sea slug Pleurobranchaea californica, uses PNS computations in its chemotactile oral veil (OV) in prey tracking, averaging olfactory stimuli across the OV to target likely source direction, or "stimulus place". This suggests a peripheral subepithelial network (SeN) interconnecting sensory sites to compute the directional average. We pursued anatomy and connectivity of previously described ciliated putative sensory cells on OV papillae. Scanning electron microscopy (SEM) confirmed paddle-shaped cilia in clusters. Anti-tubulin and phalloidin staining showed connections to branching nervelets and muscle fibers for contraction and expansion of papillae. Ciliary cell processes could not be traced into nerves, consistent with sensory transmission to CNS via secondary afferents. Anti-tyrosine hydroxylase-stained ciliated cells in clusters and revealed an at least partially dopaminergic subepithelial network interconnecting clusters near and distant, connections consistent with PNS averaging of multiple stimulated loci. Other, unidentified, SeN neurotransmitters are likely. Confirming chemotactile functions, perfusible suction electrodes recorded ciliary spiking excited by both mechanical and appetitive chemical stimuli. Stimuli induced sensory nerve spiking like that encoding stimulus place. Sensory nerve spikes and cilia cluster spikes were not identifiable as generated by the same neurons. Ciliary clusters likely drive the sensory nerve spikes via SeN, mediating appetitive and stimulus place codes to CNS. These observations may facilitate future analyses of the PNS in odor discrimination and memory, and also suggest such SeNs as potential evolutionary precursors of CNS place-coding circuitry in the segmented, skeletonized protostomes and deuterostomes.

Energy-distributable waterborne acoustic launcher for directional sensing

Highly directional launch and intensity adjustment of underwater acoustic signals are crucial in many areas such as abyssal navigation, underwater signal communication, and detection for marine biology. Inspired by the phenomenon that aquatic animals like dolphins detect and track prey with high resolution, we propose an energy-distributable directional sensing strategy which can achieve parallel needle-like transmitting sound beams with adjustable energy based on out-coupling valley-polarized edge states. The acoustic spin angular momentum and energy flow distribution at different interfaces inside the phononic crystal are provided and they show tight coupling. Furthermore, a sound beam with a width of 20° and an acoustic intensity enhancement factor ≈ 6.6 are observed in the far field. As an application, we show that this device can be used as an acoustic energy distributor. This communication pattern with excellent functionalities and performance provides a desirable idea for high-energy-level directional collimated underwater sensing and underwater acoustic energy distribution.

A novel harbor seal whiskers optimization algorithm

A novel optimization algorithm, namely Harbor Seal Whiskers Optimization Algorithm (HSWOA) is proposed in this work. Harbor seals use their whiskers to find underwater disturbances which are in the form of oscillating spheres and track prey even though they lack lateral-line systems. HSWOA mimics the high-level sensing that seal whiskers possess. As such, HSWOA has an excellent exploration capability for the search space and a high exploitation capacity for exploiting the all-optimum solutions to reach the most optimum solution. To validate these abilities, the proposed HSWOA utilizes two sets of test functions: 33 benchmark functions and five IEEE Congress on Evolutionary Computation (CEC2019) benchmark functions. The results of HSWOA are compared with ten well-established optimization algorithms. The comparison results show that HSWOA offers superior performance indices to reach an optimum solution while requiring less control variables. The results also show that HSWOA is more efficient regarding computational demand and resolution accuracy. Finally, the HSWOA is employed to track Maximum Power Point (MPP) of Photovoltaic (PV) array with partial shading conditions (PSCs) for two case studies. The results show that HSWOA extracts maximum power in minimum tracking time and high average power capturing capability compared to other optimization techniques.

Auditory processing for action selection in bats

Bats are auditory specialists, processing acoustic signals to guide their behaviors, including prey tracking, navigation and communication. In this talk I will provide an overview of my work related to how bats analyze and process signals for action-selection; specifically prey tracking and background clutter segregation—work inspired by research from Jim Simmons’s lab. I will also give an overview of the line of research of my current lab, neural mechanisms for auditory processing of communication signals. There is strong evidence that context plays a role in the processing of acoustic signals. Yet, the mechanisms that govern this process are still not fully understood. Eptesicus fuscus bats emit a wide array of communication calls, including food claiming calls, aggressive calls and appeasement calls. We developed a novel competitive foraging task to explore the role of behavioral context in auditory responses to social calls. With this approach, we recorded neural population responses from the IC of freely interacting bats. Analysis of our neural recordings from the IC show stronger population responses to individual calls during behaviorally aggressive events. These results indicate that behavioral context plays a role in the modulation of neuronal population responses to social vocalizations in the bat IC.

Adaptive behavior in sonar prey tracking tasks: Empirical data and modeling

Echolocating bats can discriminate small differences in target range (Simmons, 1973) and show a clutter interference zone along the range axis of 8–9 cm (Simmons et al., 1988). Because bats use an active sensing system, they can employ various strategies to mitigate the effects of clutter. We studied clutter rejection behaviors of the big brown bat, Eptesicus fuscus, as it tracked a moving target under controlled conditions. We also created data-driven models using control theory and system identification techniques to evaluate oscillating target motion tracking strategies. We trained bats to rest on a stationary platform and track a moving tethered mealworm in two conditions (1) approaching and passing by stationary clutter objects at varying distances and angular offsets, and (2) moving in sinusoidal patterns in an open room. Data from the first experimental condition revealed adaptive echolocation call features and head movements that enabled target tracking in the presence of clutter. Under the oscillating target condition, we analyzed adaptive echolocation behavior to create a data-driven model that maps changes in target motion with sonar call rate. The results of this study demonstrate the bat’s use of active motor control that separates targets from clutter and to track complex motion trajectories.

A Time-Delay Feedback Neural Network for Discriminating Small, Fast-Moving Targets in Complex Dynamic Environments.

Discriminating small moving objects within complex visual environments is a significant challenge for autonomous micro-robots that are generally limited in computational power. By exploiting their highly evolved visual systems, flying insects can effectively detect mates and track prey during rapid pursuits, even though the small targets equate to only a few pixels in their visual field. The high degree of sensitivity to small target movement is supported by a class of specialized neurons called small target motion detectors (STMDs). Existing STMD-based computational models normally comprise four sequentially arranged neural layers interconnected via feedforward loops to extract information on small target motion from raw visual inputs. However, feedback, another important regulatory circuit for motion perception, has not been investigated in the STMD pathway and its functional roles for small target motion detection are not clear. In this article, we propose an STMD-based neural network with feedback connection (feedback STMD), where the network output is temporally delayed, then fed back to the lower layers to mediate neural responses. We compare the properties of the model with and without the time-delay feedback loop and find that it shows a preference for high-velocity objects. Extensive experiments suggest that the feedback STMD achieves superior detection performance for fast-moving small targets, while significantly suppressing background false positive movements which display lower velocities. The proposed feedback model provides an effective solution in robotic visual systems for detecting fast-moving small targets that are always salient and potentially threatening.

BIG HEARTS OF LITTLE FRIENDS

The article presents a literary review of scientific works related to the topic of the role of dogs in human life.
 The union of man and dog, as scientists report, dates back to ancient times, probably 14000 to 16000 years ago. In modern conditions, dogs occupy one of the main places next to people in almost all spheres of life - from protection of the rights and freedoms of citizens to sports with the use of dogs, as well as non-standard methods of treatment with the active participation of dogs.
 Dogs were the first animals domesticated by man. In this regard, they managed to overtake cows, sheep and goats. Of course, dogs were great guards and helpers during the hunt, but much more important was that you could communicate with them. They were devoted to their master and understood him better than other animals. A dog's ability to track prey and warn of danger was enough for primitive man. It freed a person from the fear of the unknown.
 It is difficult to overestimate the role of dogs in human life, because they perform many functions, in particular, they are actively used for hunting, as shepherds, in the work of the police and the military, in everyday life for people with disabilities, and dog therapy is also widely distributed, that is, work with injured people due to certain circumstances.

Prey tracking and predator avoidance in a Neotropical moist forest: a camera-trapping approach.

Whether prey species avoid predators and predator species track prey is a poorly understood aspect of predator-prey interactions, given measuring prey tracking by predators and predator avoidance by prey is challenging. A common approach to study these interactions among mammals in field situations is to monitor the spatial proximity of animals at fixed times, using GPS tags fitted to individuals. However, this method is invasive and only allows tracking of a subset of individuals. Here, we use an alternative, noninvasive camera-trapping approach to monitor temporal proximity of predator and prey animals. We deployed camera traps at fixed locations on Barro Colorado Island, Panama, where the ocelot (Leopardus pardalis) is the principal mammalian predator, and tested two hypotheses: (1) prey animals avoid ocelots; and (2) ocelots track prey. We quantified temporal proximity of predators and prey by fitting parametric survival models to the time intervals between subsequent prey and predator captures by camera traps, and then compared the observed intervals to random permutations that retained the spatiotemporal distribution of animal activity. We found that time until a prey animal appeared at a location was significantly longer than expected by chance if an ocelot had passed, and that the time until an ocelot appeared at a location was significantly shorter than expected by chance after prey passage. These findings are indirect evidence for both predator avoidance and prey tracking in this system. Our results show that predator avoidance and prey tracking influence predator and prey distribution over time in a field setting. Moreover, this study demonstrates that camera trapping is a viable and noninvasive alternative to GPS tracking for studying certain predator-prey interactions.

An End-to-End Spiking Neural Network Platform for Edge Robotics: From Event-Cameras to Central Pattern Generation

Learning to adapt one’s gait with environmental changes plays an essential role in the locomotion of legged robots which remains challenging for constrained computing resources and energy budget, as in the case of edge-robots. Recent advances in bio-inspired vision with dynamic vision sensors (DVSs) and associated neuromorphic processing can provide promising solutions for end-to-end sensing, cognition, and control tasks. However, such bio-mimetic closed-loop robotic systems based on event-based visual sensing and actuation in the form of spiking neural networks (SNNs) have not been well explored. In this work, we program the weights of a bio-mimetic multigait central pattern generator (CPG) and couple it with DVS-based visual data processing to show a spike-only closed-loop robotic system for a prey-tracking scenario. We first propose a supervised learning rule based on stochastic weight updates to produce a multigait producing spiking-CPG (SCPG) for hexapod robot locomotion. We then actuate the SCPG to seamlessly transition between the gaits for a nearest prey tracking task by incorporating SNN-based visual processing for input event-data generated by the DVS. This for the first time, demonstrates the natural coupling of event data flow from event-camera through SNN and neuromorphic locomotion. Thus, we exploit bio-mimetic dynamics and energy advantages of spike-based processing for autonomous edge-robotics.

Correlation between Feeding Behaviors and Retinal Photoreceptor Cells of Largemouth Bass, Micropterus salmoides, in Korea

The largemouth bass (Micropterus salmoides), a food resource in Korea, is a highly voracious predator, designated as an invasive species. It is both diurnal and nocturnal, with high adaptability and reproducibility. Since the predation characteristics are associated with sensitive dynamic visual acuity, we examined the ocular structure of the largemouth bass to investigate the association between photoreceptor cells and feeding behavior. Furthermore, the comparison of the prey-tracking ability of M. salmoides with that of other predatory fish (Coreoperca herzi and Lepomis macrochirus) with similar ecological characteristics revealed the structure and arrangement of photoreceptor cells, typical of a predatory fish in M. salmoides. The double and single cone cells in the retina were present in the regular mosaic patterns of the quadrilateral units, with four double cone cells surrounding a single cone cell. The photoreceptor cells, i.e., the rod, single, and double cone cells of M. salmoides, were smaller (2.3 ± 0.2, 3.82 ± 0.2, and 7.5 ± 0.2 μm, respectively) than those of other species (3.1 ± 0.24, 6.6 ± 0.5, and 11.3 ± 0.4 μm in diameter, respectively, in C. herzi). A smaller diameter of cone cells allows for a high-density arrangement of visual cells, possibly affecting the dynamic visual acuity for prey tracking.

Internal state effects on behavioral shifts in freely behaving praying mantises (Tenodera sinensis).

How we interact with our environment largely depends on both the external cues presented by our surroundings and the internal state from within. Internal states are the ever-changing physiological conditions that communicate the immediate survival needs and motivate the animal to behaviorally fulfill them. Satiety level constitutes such a state, and therefore has a dynamic influence on the output behaviors of an animal. In predatory insects like the praying mantis, hunting tactics, grooming, and mating have been shown to change hierarchical organization of behaviors depending on satiety. Here, we analyze behavior sequences of freely hunting praying mantises (Tenodera sinensis) to explore potential differences in sequential patterning of behavior as a correlate of satiety. First, our data supports previous work that showed starved praying mantises were not just more often attentive to prey, but also more often attentive to further prey. This was indicated by the increased time fraction spent in attentive bouts such as prey monitoring, head turns (to track prey), translations (closing the distance to the prey), and more strike attempts. With increasing satiety, praying mantises showed reduced time in these behaviors and exhibited them primarily towards close-proximity prey. Furthermore, our data demonstrates that during states of starvation, the praying mantis exhibits a stereotyped pattern of behavior that is highly motivated by prey capture. As satiety increased, the sequenced behaviors became more variable, indicating a shift away from the necessity of prey capture to more fluid presentations of behavior assembly.

Echolocating toothed whales use ultra-fast echo-kinetic responses to track evasive prey.

Visual predators rely on fast-acting optokinetic responses to track and capture agile prey. Most toothed whales, however, rely on echolocation for hunting and have converged on biosonar clicking rates reaching 500/s during prey pursuits. If echoes are processed on a click-by-click basis, as assumed, neural responses 100× faster than those in vision are required to keep pace with this information flow. Using high-resolution biologging of wild predator-prey interactions, we show that toothed whales adjust clicking rates to track prey movement within 50-200 ms of prey escape responses. Hypothesising that these stereotyped biosonar adjustments are elicited by sudden prey accelerations, we measured echo-kinetic responses from trained harbour porpoises to a moving target and found similar latencies. High biosonar sampling rates are, therefore, not supported by extreme speeds of neural processing and muscular responses. Instead, the neurokinetic response times in echolocation are similar to those of tracking responses in vision, suggesting a common neural underpinning.

Modeling Nonlinear Dendritic Processing of Facilitation in a Dragonfly Target-Tracking Neuron.

Dragonflies are highly skilled and successful aerial predators that are even capable of selectively attending to one target within a swarm. Detection and tracking of prey is likely to be driven by small target motion detector (STMD) neurons identified from several insect groups. Prior work has shown that dragonfly STMD responses are facilitated by targets moving on a continuous path, enhancing the response gain at the present and predicted future location of targets. In this study, we combined detailed morphological data with computational modeling to test whether a combination of dendritic morphology and nonlinear properties of NMDA receptors could explain these observations. We developed a hybrid computational model of neurons within the dragonfly optic lobe, which integrates numerical and morphological components. The model was able to generate potent facilitation for targets moving on continuous trajectories, including a localized spotlight of maximal sensitivity close to the last seen target location, as also measured during in vivo recordings. The model did not, however, include a mechanism capable of producing a traveling or spreading wave of facilitation. Our data support a strong role for the high dendritic density seen in the dragonfly neuron in enhancing non-linear facilitation. An alternative model based on the morphology of an unrelated type of motion processing neuron from a dipteran fly required more than three times higher synaptic gain in order to elicit similar levels of facilitation, despite having only 20% fewer synapses. Our data support a potential role for NMDA receptors in target tracking and also demonstrate the feasibility of combining biologically plausible dendritic computations with more abstract computational models for basic processing as used in earlier studies.

Wild bats briefly decouple sound production from wingbeats to increase sensory flow during prey captures

SummaryActive sensing animals such as echolocating bats produce the energy with which they probe their environment. The intense echolocation calls of bats are energetically expensive, but their cost can be reduced by synchronizing the exhalations needed to vocalize to wingbeats. Here, we use sound-and-movement recording tags to investigate how wild bats balance efficient sound production with information needs during foraging and navigation. We show that wild bats prioritize energy efficiency over sensory flow when periodic snapshots of the acoustic scene are sufficient during travel and search. Rapid calls during tracking and interception of close prey are decoupled from the wingbeat but are weaker and comprise <2% of all calls during a night of hunting. The limited use of fast sonar sampling provides bats with high information update rates during critical hunting moments but adds little to their overall costs of sound production despite the inefficiency of decoupling calls from wingbeats.

Pursuit and Evasion Strategies in the Predator-Prey Interactions of Fishes.

Predator-prey interactions are critical to the biology of a diversity of animals. Although prey capture is determined by the direction, velocity, and timing of motion by both animals, it is generally unclear what strategies are employed by predators and prey to guide locomotion. Here we review our research on fishes that tests the pursuit strategy of predators and the evasion strategy of prey through kinematic measurements and agent-based models. This work demonstrates that fish predators track prey with variations on a deviated-pursuit strategy that is guided by visual cues. Fish prey employ a mixed strategy that varies with factors such as the direction of a predator's approach. Our models consider the stochastic nature of interactions by incorporating measured probability distributions to accurately predict measurements of survivorship. A sensitivity analysis of these models shows the importance of the response distance of prey to their survival. Collectively, this work demonstrates how strategy affects the outcome of predator-prey interactions and articulates the roles of sensing, control, and propulsion. The research program that we have developed has the potential to offer a framework for the study of strategy in the predator-prey interactions of a variety of animals.

Active head rolls enhance sonar-based auditory localization performance.

Animals utilize a variety of active sensing mechanisms to perceive the world around them. Echolocating bats are an excellent model for the study of active auditory localization. The big brown bat (Eptesicus fuscus), for instance, employs active head roll movements during sonar prey tracking. The function of head rolls in sound source localization is not well understood. Here, we propose an echolocation model with multi-axis head rotation to investigate the effect of active head roll movements on sound localization performance. The model autonomously learns to align the bat's head direction towards the target. We show that a model with active head roll movements better localizes targets than a model without head rolls. Furthermore, we demonstrate that active head rolls also reduce the time required for localization in elevation. Finally, our model offers key insights to sound localization cues used by echolocating bats employing active head movements during echolocation.

Echolocating bats accumulate information from acoustic snapshots to predict auditory object motion

Unlike other predators that use vision as their primary sensory system, bats compute the three-dimensional (3D) position of flying insects from discrete echo snapshots, which raises questions about the strategies they employ to track and intercept erratically moving prey from interrupted sensory information. Here, we devised an ethologically inspired behavioral paradigm to directly test the hypothesis that echolocating bats build internal prediction models from dynamic acoustic stimuli to anticipate the future location of moving auditory targets. We quantified the direction of the bat's head/sonar beam aim and echolocation call rate as it tracked a target that moved across its sonar field and applied mathematical models to differentiate between nonpredictive and predictive tracking behaviors. We discovered that big brown bats accumulate information across echo sequences to anticipate an auditory target's future position. Further, when a moving target is hidden from view by an occluder during a portion of its trajectory, the bat continues to track its position using an internal model of the target's motion path. Our findings also reveal that the bat increases sonar call rate when its prediction of target trajectory is violated by a sudden change in target velocity. This shows that the bat rapidly adapts its sonar behavior to update internal models of auditory target trajectories, which would enable tracking of evasive prey. Collectively, these results demonstrate that the echolocating big brown bat integrates acoustic snapshots over time to build prediction models of a moving auditory target's trajectory and enable prey capture under conditions of uncertainty.

A numerical study of target flow field detection by autonomous underwater vehicles

ABSTRACT Sideline is a key component of fish sensory system, which has been found to affect many behaviours of fish, including manoeuvring obstacle avoidance, prey tracking and environmental mapping in complex fluid environment. In this paper, based on the sensing flow field mechanism of fish lateral line system, a sphere obstacle model is established by using the CFD method and FLUENT software, and the flow field around it is simulated and calculated. The experiment controls two variables: water flow velocity and sphere size. In this paper, the influence of velocity and obstacle size on pressure distribution is analysed, and the rectangular coordinate system is established with the spherical centre as the origin, and the characteristics of pressure distribution in X and Y directions are summarised. This research plays an important role in promoting the development of autonomous underwater vehicles.

Aquatic macrophytes and macroinvertebrate predators affect densities of snail hosts and local production of schistosome cercariae that cause human schistosomiasis.

BackgroundSchistosomiasis is responsible for the second highest burden of disease among neglected tropical diseases globally, with over 90 percent of cases occurring in African regions where drugs to treat the disease are only sporadically available. Additionally, human re-infection after treatment can be a problem where there are high numbers of infected snails in the environment. Recent experiments indicate that aquatic factors, including plants, nutrients, or predators, can influence snail abundance and parasite production within infected snails, both components of human risk. This study investigated how snail host abundance and release of cercariae (the free swimming stage infective to humans) varies at water access sites in an endemic region in Senegal, a setting where human schistosomiasis prevalence is among the highest globally.Methods/Principal findingsWe collected snail intermediate hosts at 15 random points stratified by three habitat types at 36 water access sites, and counted cercarial production by each snail after transfer to the laboratory on the same day. We found that aquatic vegetation was positively associated with per-capita cercarial release by snails, probably because macrophytes harbor periphyton resources that snails feed upon, and well-fed snails tend to produce more parasites. In contrast, the abundance of aquatic macroinvertebrate snail predators was negatively associated with per-capita cercarial release by snails, probably because of several potential sublethal effects on snails or snail infection, despite a positive association between snail predators and total snail numbers at a site, possibly due to shared habitat usage or prey tracking by the predators. Thus, complex bottom-up and top-down ecological effects in this region plausibly influence the snail shedding rate and thus, total local density of schistosome cercariae.Conclusions/SignificanceOur study suggests that aquatic macrophytes and snail predators can influence per-capita cercarial production and total abundance of snails. Thus, snail control efforts might benefit by targeting specific snail habitats where parasite production is greatest. In conclusion, a better understanding of top-down and bottom-up ecological factors that regulate densities of cercarial release by snails, rather than solely snail densities or snail infection prevalence, might facilitate improved schistosomiasis control.