Todd E. Dennis

Movement beyond the snapshot – Dynamic analysis of geospatial lifelines

Abstract Geographical Information Science is challenged by an unprecedented increase in the availability of tracking data related to human and animal movement, typically captured through location-aware portable devices such as GPS receivers. Capture of trajectory data at fine temporal and spatial granularities has allowed with the representation of detailed geospatial lifelines, opening new options for analysis. In this respect we propose a dynamic perspective to analysis which, in contrast to summary trajectory statistics on speed, motion azimuth or sinuosity, that refers to the variability of motion properties throughout the developing lifeline. Four specific lifeline context operators are identified in this paper: ‘instantaneous’, ‘interval’, ‘episodal’ and ‘total’. Using this framework, we discuss standardisations that integrate the extended set of motion descriptors within various temporal and spatial frames of reference and the proposed lifeline context operators and standardisations are illustrated using high resolution trajectory data obtained from homing pigeons carrying miniature global positioning devices.

Evidence that pigeons orient to geomagnetic intensity during homing

The influence of the Earths magnetic field on locomotory orientation has been studied in many taxa but is best understood for homing pigeons (Columba livia). Effects of experimentally induced and naturally occurring perturbations in the geomagnetic field suggest that pigeons are sensitive to changes in geomagnetic parameters. However, whether pigeons use the Earths magnetic field for position determination remains unknown. Here we report an apparent orientation to the intensity gradient of the geomagnetic field observed in pigeons homing from sites in and around a magnetic anomaly. From flight trajectories recorded by GPS-based tracking devices, we noted that many pigeons released at unfamiliar sites initially flew, in some cases up to several kilometres, in directions parallel and/or perpendicular to the bearing of the local intensity field. This behaviour occurred irrespective of the homeward direction and significantly more often than what was expected by random chance. Our study describes a novel behaviour which provides strong evidence that pigeons when homing detect and respond to spatial variation in the Earths magnetic field—information of potential use for navigation.

Investigating Behaviour and Population Dynamics of Striped Marlin (Kajikia audax) from the Southwest Pacific Ocean with Satellite Tags

Behaviour and distribution of striped marlin within the southwest Pacific Ocean were investigated using electronic tagging data collected from 2005–2008. A continuous-time correlated random-walk Kalman filter was used to integrate double-tagging data exhibiting variable error structures into movement trajectories composed of regular time-steps. This state-space trajectory integration approach improved longitude and latitude error distributions by 38.5 km and 22.2 km respectively. Using these trajectories as inputs, a behavioural classification model was developed to infer when, and where, ‘transiting’ and ‘area-restricted’ (ARB) pseudo-behavioural states occurred. ARB tended to occur at shallower depths (108±49 m) than did transiting behaviours (127±57 m). A 16 day post-release period of diminished ARB activity suggests that patterns of behaviour were affected by the capture and/or tagging events, implying that tagged animals may exhibit atypical behaviour upon release. The striped marlin in this study dove deeper and spent greater time at ≥200 m depth than those in the central and eastern Pacific Ocean. As marlin reached tropical latitudes (20–21°S) they consistently reversed directions, increased swimming speed and shifted to transiting behaviour. Reversals in the tropics also coincided with increases in swimming depth, including increased time ≥250 m. Our research provides enhanced understanding of the behavioural ecology of striped marlin. This has implications for the effectiveness of spatially explicit population models and we demonstrate the need to consider geographic variation when standardizing CPUE by depth, and provide data to inform natural and recreational fishing mortality parameters.

Effects of Temporal Resolution on an Inferential Model of Animal Movement

Recently, there has been much interest in describing the behaviour of animals by fitting various movement models to tracking data. Despite this interest, little is known about how the temporal ‘grain’ of movement trajectories affects the outputs of such models, and how behaviours classified at one timescale may differ from those classified at other scales. Here, we present a study in which random-walk state-space models were fit both to nightly geospatial lifelines of common brushtail possums (Trichosurus vulpecula) and synthetic trajectories parameterised from empirical observations. Observed trajectories recorded by GPS collars at 5-min intervals were sub-sampled at periods varying between 10 and 60 min, to approximate the effect of collecting data at lower sampling frequencies. Markov-Chain Monte-Carlo fitting techniques, using information about movement rates and turning angles between sequential fixes, were employed using a Bayesian framework to assign distinct behavioural states to individual location estimates. We found that in trajectories with higher temporal granularities behaviours could be clearly differentiated into ‘slow-area-restricted’ and ‘fast-transiting’ states, but for trajectories with longer inter-fix intervals this distinction was markedly less obvious. Specifically, turning-angle distributions varied from being highly peaked around either or at fine temporal scales, to being uniform across all angles at low sampling intervals. Our results highlight the difficulty of comparing model results amongst tracking-data sets that vary substantially in temporal grain, and demonstrate the importance of matching the observed temporal resolution of tracking devices to the timescales of behaviours of interest, otherwise inter-individual comparisons of inferred behaviours may be invalid, or important biological information may be obscured.

Extending the Functionality of Behavioural Change-Point Analysis with k-Means Clustering: A Case Study with the Little Penguin (Eudyptula minor)

We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known ‘artificial behaviours’ comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified.

Assessing Acute Effects of Trapping, Handling, and Tagging on the Behavior of Wildlife Using GPS Telemetry: A Case Study of the Common Brushtail Possum

Trapping, handling, and deployment of tracking devices (tagging) are essential aspects of many research and conservation studies of wildlife. However, often these activities place nonhuman animals under considerable physical or psychological distress, which disrupts normal patterns of behavior and may ultimately result in deleterious effects on animal welfare and the validity of research results. Thus, knowledge of how trapping, handling, and tagging alter the behavior of research animals is essential if measures to ameliorate stress-related effects are to be developed and implemented. This article describes how time-stamped location data obtained by global-positioning-system telemetry can be used to retrospectively characterize acute behavioral responses to trapping, handling, and tagging in free-ranging animals used for research. Methods are demonstrated in a case study of the common brushtail possum, a semiarboreal phalangerid marsupial native to Australia. The study discusses possible physiological causes of observed effects and offers general suggestions regarding simple means to reduce trapping-handling-and-tagging-related stress in field studies of vertebrates.

Adoption of alternative habitats by a threatened, “obligate” forest-dwelling bat in a fragmented landscape

While they are among the most ecologically important animals within forest ecosystems, little is known about how bats respond to habitat loss and fragmentation. The threatened lesser short-tailed bat (Mystacina tuberculata), considered to be an obligate deep-forest species, is one of only 2 extant land mammals endemic to New Zealand; it plays a number of important roles within native forests, including pollination and seed dispersal, and rarely occurs in modified forests. We used radiotelemetry to study the movements, roosting behavior, and habitat use of M. tuberculata within a fragmented landscape comprised of 3 main habitat types: open space (harvested forest and pastoral land), native forests, and exotic pine plantations. We found that the bats had smaller home-range areas and travelled shorter nightly distances than populations investigated previously from contiguous native forest. Furthermore, M. tuberculata occupied all 3 habitat types, with native forest being preferred overall. However, individual variation in habitat selection was high, with some bats preferring exotic plantation and open space over native forest. Roosting patterns were similar to those previously observed in contiguous forest; individual bats often switched between communal and solitary roosts. Our findings indicate that M. tuberculata exhibit some degree of behavioral plasticity that allows them to adapt to different landscape mosaics and exploit alternative habitats. To our knowledge, this is the first such documentation of plasticity in habitat use for a bat species believed to be an obligate forest-dweller.

The Space–Time Aquarium is Full of Albatrosses: Time Geography, Lifestyle and Trans-species Geovisual Analytics

The volume of research that involves movement track data sets of increasing size and complexity has grown significantly as data-capture technologies have developed and expectations for ongoing growth of research opportunities have hardened. Techniques for describing such data vary, some utilising a purely geometric measurement while others seeking to involve activity and purpose as elements of movement description. Such enriched data is typical of sentient entities that interact with their environment and other sentients. This paper is solely about such sentient, self-navigating objects. It is also restricted to consideration of movement fields through the lens of geovisual analytics, or equally, in this case, reviewing geovisual analytics through the lenses of a sample of sentient movement data sets. Fundamentally the paper asks whether different kinds of entity require adjustments to given visualisation tools, and if this is so, how such adjustments might be related to the different processes and geographies of the entities involved. The arguments are largely based around two ‘rich’ data sets: Halifax time use and Muriwai possum movement data sets.

Variability in the foraging range of Eudyptula minor across breeding sites in central New Zealand

ABSTRACT The little penguin Eudyptula minor is primarily an inshore forager with its range generally limited to c. 30 km of breeding sites during the nesting period. However, exceptions with greater foraging distances have been recorded in Australia. To investigate the foraging range plasticity in New Zealand we used GPS tracks gathered on 68 individuals in three regions of central New Zealand between 2011 and 2016. Foraging patterns varied between sites and between years. Tracks revealed that penguins can rely on distant foraging areas while incubating, with nesting birds travelling up to 214 km to feed. Isotope analyses of blood samples showed that this distant food across deep waters (0–200 m) is likely to be squid dominated. During the chick rearing period, birds undertook a diet shift to a higher trophic level while foraging closer to their colony, and possibly near river plumes. These findings highlight the need to consider the little penguins’ large potential foraging ranges when managing threats and changes to the environment.

Effects of uncertain cost-surface specification on landscape connectivity measures

Abstract Estimates of landscape connectivity are routinely used to inform decision-making by conservation biologists. Most estimates of connectivity rely on cost-surfaces: raster representations of landscapes in which cost values represent the difficulty involved with traversing an area. However, there is considerable uncertainty in the generation of cost-surfaces that have not been widely explored. We investigated the effects of four potential sources of uncertainty in the creation of cost-surfaces: 1) number of landscape classes represented; 2) spatial resolution (grain size); 3) misclassification of edges between landscape classes; and 4) cost values selected for each landscape class. Following a factorial design we simulated multiple cost-surface pairs, each comprising one true surface with no errors and one surface with uncertainty comprised of some combination of the four error sources. We evaluated the relative importance of each source of uncertainty in determining the difference between the least-cost paths (LCPs) costs and resistance distances generated for the true and erroneous cost-surfaces, using four model evaluation metrics. Errors in the underlying geospatial layers produced larger inaccuracies in connectivity estimates than those produced by cost-value errors. Incorrect grain size had the largest overall effect on the accuracy of connectivity estimates. Though the removal of an element class was found to have a large effect on the configuration of connectivity estimates, and the addition of an element class had a large effect on estimates configuration. Our results highlight the importance of minimising and quantifying the uncertainty inherent in the geospatial data used to develop cost-surfaces.