Animal Control - What constitutes a reliable cue to stop animal movement ?

Controlling free-ranging livestock requires low-stress cues to alter animal behaviour. Recently modulated sound and electric shock were demonstrated to be effective in controlling free-ranging cattle. In this study the behaviour of 60, 300 kg Belmont Red heifers were observed for behavioural changes when presented cues designed to impede their movement through an alley. The heifers were given an overnight drylot shrink off feed but not drinking water prior to being tested. Individual cattle were allowed to move down a 6.5 m wide alley towards a pen of peers and feed located 71 m from their point of release. Each animal was allowed to move through the alley unimpeded five times to establish a basal behavioural pattern. Animals were then randomly assigned to treatments consisting of sound plus shock, vibration plus shock, a visual cue plus shock, shock by itself and a control. The time each animal required to reach the pen of peers and feed was recorded. If the animal was prevented from reaching the pen of peers and feed by not penetrating through the cue barrier at set points along the alley for at least 60 sec the test was stopped and the animal was returned to peers located behind the release pen. Cues and shock were manually applied from a laptop while animals were observed from a 3.5 m tower located outside the alley. Electric shock, sound, vibration and Global Position System (GPS) hardware were housed in a neck collar. Results and implications will be discussed.

Step by step: reconstruction of terrestrial animal movement paths by dead-reckoning

BACKGROUND: Research on wild animal ecology is increasingly employing GPS telemetry in order to determine animal movement. However, GPS systems record position intermittently, providing no information on latent position or track tortuosity. High frequency GPS have high power requirements, which necessitates large batteries (often effectively precluding their use on small animals) or reduced deployment duration. Dead-reckoning is an alternative approach which has the potential to 'fill in the gaps' between less resolute forms of telemetry without incurring the power costs. However, although this method has been used in aquatic environments, no explicit demonstration of terrestrial dead-reckoning has been presented.

RESULTS: We perform a simple validation experiment to assess the rate of error accumulation in terrestrial dead-reckoning. In addition, examples of successful implementation of dead-reckoning are given using data from the domestic dog Canus lupus, horse Equus ferus, cow Bos taurus and wild badger Meles meles.

CONCLUSIONS: This study documents how terrestrial dead-reckoning can be undertaken, describing derivation of heading from tri-axial accelerometer and tri-axial magnetometer data, correction for hard and soft iron distortions on the magnetometer output, and presenting a novel correction procedure to marry dead-reckoned paths to ground-truthed positions. This study is the first explicit demonstration of terrestrial dead-reckoning, which provides a workable method of deriving the paths of animals on a step-by-step scale. The wider implications of this method for the understanding of animal movement ecology are discussed.

Animal movement in dynamic landscapes : interaction between behavioural strategies and resource distributions

Most ecological and evolutionary processes are thought to critically depend on dispersal and individual movement but there is little empirical information on the movement strategies used by animals to find resources. In particular, it is unclear whether behavioural variation exists at all scales, or whether behavioural decisions are primarily made at small spatial scales and thus broad-scale patterns of movement simply reflect underlying resource distributions. We evaluated animal movement responses to variable resource distributions using the grey teal (Anas gracilis) in agricultural and desert landscapes in Australia as a model system. Birds in the two landscapes differed in the fractal dimension of their movement paths, with teal in the desert landscape moving less tortuously overall than their counterparts in the agricultural landscape. However, the most striking result was the high levels of individual variability in movement strategies, with different animals exhibiting different responses to the same resources. Teal in the agricultural basin moved with both high and low tortuosity, while teal in the desert basin primarily moved using low levels of tortuosity. These results call into question the idea that broad-scale movement patterns simply reflect underlying resource distributions, and suggest that movement responses in some animals may be behaviourally complex regardless of the spatial scale over which movement occurs.

Measurement error causes scale-dependent threshold erosion of biological signals in animal movement data

Recent advances in telemetry technology have created a wealth of tracking data available for many animal species moving over spatial scales from tens of meters to tens of thousands of kilometers. Increasingly, such data sets are being used for quantitative movement analyses aimed at extracting fundamental biological signals such as optimal searching behavior and scale-dependent foraging decisions. We show here that the location error inherent in various tracking technologies reduces the ability to detect patterns of behavior within movements. Our analyses endeavored to set out a series of initial ground rules for ecologists to help ensure that sampling noise is not misinterpreted as a real biological signal. We simulated animal movement tracks using specialized random walks known as Lévy flights at three spatial scales of investigation: 100-km, 10-km, and 1-km maximum daily step lengths. The locations generated in the simulations were then blurred using known error distributions associated with commonly applied tracking methods: the Global Positioning System (GPS), Argos polar-orbiting satellites, and light-level geolocation. Deviations from the idealized Lévy flight pattern were assessed for each track after incrementing levels of location error were applied at each spatial scale, with additional assessments of the effect of error on scale-dependent movement patterns measured using fractal mean dimension and first-passage time (FPT) analyses. The accuracy of parameter estimation (Lévy μ, fractal mean D, and variance in FPT) declined precipitously at threshold errors relative to each spatial scale. At 100-km maximum daily step lengths, error standard deviations of ≥10 km seriously eroded the biological patterns evident in the simulated tracks, with analogous thresholds at the 10-km and 1-km scales (error SD ≥ 1.3 km and 0.07 km, respectively). Temporal subsampling of the simulated tracks maintained some elements of the biological signals depending on error level and spatial scale. Failure to account for large errors relative to the scale of movement can produce substantial biases in the interpretation of movement patterns. This study provides researchers with a framework for understanding the limitations of their data and identifies how temporal subsampling can help to reduce the influence of spatial error on their conclusions.

An animal movement model incorporating home range and habitat selection

Wildlife biologists are often interested in how an animal uses space and the habitat resources within that space. We propose a single model that estimates an animal’s home range and habitat selection parameters within that range while accounting for the inherent autocorrelation in frequently sampled telemetry data. The model is applied to brown bear telemetry data in southeast Alaska.

Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.

Retention Time Variability as a Mechanism for Animal Mediated Long-Distance Dispersal

Long-distance dispersal (LDD) events, although rare for most plant species, can strongly influence population and community dynamics. Animals function as a key biotic vector of seeds and thus, a mechanistic and quantitative understanding of how individual animal behaviors scale to dispersal patterns at different spatial scales is a question of critical importance from both basic and applied perspectives. Using a diffusion-theory based analytical approach for a wide range of animal movement and seed transportation patterns, we show that the scale (a measure of local dispersal) of the seed dispersal kernel increases with the organisms' rate of movement and mean seed retention time. We reveal that variations in seed retention time is a key determinant of various measures of LDD such as kurtosis (or shape) of the kernel, thinkness of tails and the absolute number of seeds falling beyond a threshold distance. Using empirical data sets of frugivores, we illustrate the importance of variability in retention times for predicting the key disperser species that influence LDD. Our study makes testable predictions linking animal movement behaviors and gut retention times to dispersal patterns and, more generally, highlights the potential importance of animal behavioral variability for the LDD of seeds.

Emergent group level navigation: an agent-based evaluation of movement patterns in a folivorous primate.

The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus), testing for: the effects of memory type (Euclidian or landmark based), amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led). Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group's step length, whereas the type of memory had the highest impact on a group's path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns.

Environmental context explains Lévy and Brownian movement patterns of marine predators

An optimal search theory, the so-called Levy-flight foraging hypothesis(1), predicts that predators should adopt search strategies known as Levy flights where prey is sparse and distributed unpredictably, but that Brownian movement is sufficiently efficient for locating abundant prey(2-4). Empirical studies have generated controversy because the accuracy of statistical methods that have been used to identify Levy behaviour has recently been questioned(5,6). Consequently, whether foragers exhibit Levy flights in the wild remains unclear. Crucially, moreover, it has not been tested whether observed movement patterns across natural landscapes having different expected resource distributions conform to the theory's central predictions. Here we use maximum-likelihood methods to test for Levy patterns in relation to environmental gradients in the largest animal movement data set assembled for this purpose. Strong support was found for Levy search patterns across 14 species of open-ocean predatory fish (sharks, tuna, billfish and ocean sunfish), with some individuals switching between Levy and Brownian movement as they traversed different habitat types. We tested the spatial occurrence of these two principal patterns and found Levy behaviour to be associated with less productive waters (sparser prey) and Brownian movements to be associated with productive shelf or convergence-front habitats (abundant prey). These results are consistent with the Levy-flight foraging hypothesis(1,7), supporting the contention(8,9) that organism search strategies naturally evolved in such a way that they exploit optimal Levy patterns.

A reliable externally fixated murine femoral fracture model that accounts for variation in movement between animals.

Fifty-two CFLP mice had an open femoral diaphyseal osteotomy held in compression by a four-pin external fixator. The movement of 34 of the mice in their cages was quantified before and after operation, until sacrifice at 4, 8, 16 or 24 days. Thirty-three specimens underwent histomorphometric analysis and 19 specimens underwent torsional stiffness measurement. The expected combination of intramembranous and endochondral bone formation was observed, and the model was shown to be reliable in that variation in the histological parameters of healing was small between animals at the same time point, compared to the variation between time-points. There was surprisingly large individual variation in the amount of animal movement about the cage, which correlated with both histomorphometric and mechanical measures of healing. Animals that moved more had larger external calluses containing more cartilage and demonstrated lower torsional stiffness at the same time point. Assuming that movement of the whole animal predicts, at least to some extent, movement at the fracture site, this correlation is what would be expected in a model that involves similar processes to those in human fracture healing. Models such as this, employed to determine the effect of experimental interventions, will yield more information if the natural variation in animal motion is measured and included in the analysis.

Environmental context explains Levy and Brownian movement patterns of marine predators

An optimal search theory, the so-called Levy-flight foraging hypothesis(1), predicts that predators should adopt search strategies known as Levy flights where prey is sparse and distributed unpredictably, but that Brownian movement is sufficiently efficient for locating abundant prey(2-4). Empirical studies have generated controversy because the accuracy of statistical methods that have been used to identify Levy behaviour has recently been questioned(5,6). Consequently, whether foragers exhibit Levy flights in the wild remains unclear. Crucially, moreover, it has not been tested whether observed movement patterns across natural landscapes having different expected resource distributions conform to the theory's central predictions. Here we use maximum-likelihood methods to test for Levy patterns in relation to environmental gradients in the largest animal movement data set assembled for this purpose. Strong support was found for Levy search patterns across 14 species of open-ocean predatory fish (sharks, tuna, billfish and ocean sunfish), with some individuals switching between Levy and Brownian movement as they traversed different habitat types. We tested the spatial occurrence of these two principal patterns and found Levy behaviour to be associated with less productive waters (sparser prey) and Brownian movements to be associated with productive shelf or convergence-front habitats (abundant prey). These results are consistent with the Levy-flight foraging hypothesis(1,7), supporting the contention(8,9) that organism search strategies naturally evolved in such a way that they exploit optimal Levy patterns.

The Movebank data model for animal tracking

Studies of animal movement are rapidly increasing as tracking technologies make it possible to collect more data of a larger variety of species. Comparisons of animal movement across sites, times, or species are key to asking questions about animal adaptation, responses to climate and land-use change. Thus, great gains can be made by sharing and exchanging animal tracking data. Here we present an animal movement data model that we use within the Movebank web application to describe tracked animals. The model facilitates data comparisons across a broad range of taxa, study designs, and technologies, and is based on the scientific questions that could be addressed with the data.