Enhancing the use of Argos satellite data for home range and long distance migration studies of marine animals

Accurately quantifying animals' spatial utilisation is critical for conservation, but has long remained an elusive goal due to technological impediments. The Argos telemetry system has been extensively used to remotely track marine animals, however location estimates are characterised by substantial spatial error. State-space models (SSM) constitute a robust statistical approach to refine Argos tracking data by accounting for observation errors and stochasticity in animal movement. Despite their wide use in ecology, few studies have thoroughly quantified the error associated with SSM predicted locations and no research has assessed their validity for describing animal movement behaviour. We compared home ranges and migratory pathways of seven hawksbill sea turtles (Eretmochelys imbricata) estimated from (a) highly accurate Fastloc GPS data and (b) locations computed using common Argos data analytical approaches. Argos 68(th) percentile error was <1 km for LC 1, 2, and 3 while markedly less accurate (>4 km) for LC ≤ 0. Argos error structure was highly longitudinally skewed and was, for all LC, adequately modelled by a Student's t distribution. Both habitat use and migration routes were best recreated using SSM locations post-processed by re-adding good Argos positions (LC 1, 2 and 3) and filtering terrestrial points (mean distance to migratory tracks ± SD = 2.2 ± 2.4 km; mean home range overlap and error ratio = 92.2% and 285.6 respectively). This parsimonious and objective statistical procedure however still markedly overestimated true home range sizes, especially for animals exhibiting restricted movements. Post-processing SSM locations nonetheless constitutes the best analytical technique for remotely sensed Argos tracking data and we therefore recommend using this approach to rework historical Argos datasets for better estimation of animal spatial utilisation for research and evidence-based conservation purposes.     

AN ALGORITHM TO IMPROVE GEOLOCATION POSITIONS USING SEA SURFACE TEMPERATURE AND DIVING DEPTH

The at-sea movement of marine mammals is an important component of their foraging ecology, but has been difficult to study. Geolocation timed-data recorders (GLTDRs) estimate positions using measured light level to calculate day length and local noon. It is well known that these location estimates are imprecise (mean error of > 1°). Satellite telemetry generally provides a more accurate, but also more expensive means of monitoring movement. We evaluated the accuracy and precision of geolocation positions by comparing these locations with satellite data from Service Argos for eight free-ranging gray seals ( Halichoerns grypus ) equipped with both a satellite-linked data recorder (SDR) and a GLTDR. Geolocation positions differed by 1,026.0 ± 292.28 km from the corresponding Argos locations. We developed an algorithm to correct geolocation positions by comparing surface water temperature (ST) and dive depth collected by GLTDRs with existing sea-surface temperature and bathymetry databases. The corrected positions were significantly closer (P < 0.025) to the Argos locations of these seals (94.2 ± 8.22 km). The original geolocation positions would have led to incorrect conclusions about the use of space by gray seals; however, the corrected positions can be reliably used to study the large-scale spatial distribution of individuals.     

Evaluation of Argos Telemetry Accuracy in the High-Arctic and Implications for the Estimation of Home-Range Size

Animal tracking through Argos satellite telemetry has enormous potential to test hypotheses in animal behavior, evolutionary ecology, or conservation biology. Yet the applicability of this technique cannot be fully assessed because no clear picture exists as to the conditions influencing the accuracy of Argos locations. Latitude, type of environment, and transmitter movement are among the main candidate factors affecting accuracy. A posteriori data filtering can remove “bad” locations, but again testing is still needed to refine filters. First, we evaluate experimentally the accuracy of Argos locations in a polar terrestrial environment (Nunavut, Canada), with both static and mobile transmitters transported by humans and coupled to GPS transmitters. We report static errors among the lowest published. However, the 68^th error percentiles of mobile transmitters were 1.7 to 3.8 times greater than those of static transmitters. Second, we test how different filtering methods influence the quality of Argos location datasets. Accuracy of location datasets was best improved when filtering in locations of the best classes (LC3 and 2), while the Douglas Argos filter and a homemade speed filter yielded similar performance while retaining more locations. All filters effectively reduced the 68^th error percentiles. Finally, we assess how location error impacted, at six spatial scales, two common estimators of home-range size (a proxy of animal space use behavior synthetizing movements), the minimum convex polygon and the fixed kernel estimator. Location error led to a sometimes dramatic overestimation of home-range size, especially at very local scales. We conclude that Argos telemetry is appropriate to study medium-size terrestrial animals in polar environments, but recommend that location errors are always measured and evaluated against research hypotheses, and that data are always filtered before analysis. How movement speed of transmitters affects location error needs additional research.     

HARBOR SEAL TRACKING AND TELEMETRY BY SATELLITE

We tested a satellite Platform Transmitter Terminal (PTT) in the laboratory (on a float and on captive seals) and on a free-ranging harbor seal in the Southern California Bight to investigate the utility of satellite telemetry in documenting seals'at-sea behavior and movements. We used records from a microprocessor-based time-depth recorder (TDR) to interpret location and diving records from the PTT. For the free-ranging harbor seal, we obtained at least one uplink during 70% (while the seal was at sea) to 82% (while she was ashore) of satellite passes and at least one location each day. Of 62 locations determined by Service Argos for the free-ranging seal, 20 were verified from TDR records to have been at sea; these indicated that the seal may have ranged up to 48 km from the haul-out site, although most locations were within 5 km. The accuracies of locations calculated when the seal was at sea (±15 km) were substantially less than when it was ashore (±1.5 km), thus limiting at-sea tracking of seals by satellite to rather gross movements. Fewer transmissions were detected and locations calculated when the seal was actively diving than when it was swimming near the surface as it departed from or returned to the haul-out site. Consequently, average dive durations indicated by the PTT were substantially shorter than those calculated from TDR records. Documentation of foraging areas and detailed at-sea movements using satellite technology may not be possible for pinnipeds unless PTT-transmission rates are increased substantially from the 1 per 45 set maximum rate now permitted by Service Argos.     

Performance and accuracy of Argos transmitters for wildlife monitoring in Southern Russia

Satellite telemetry is a powerful tool for monitoring animal movements, and Argos transmitters have been widely used. Unfortunately, only few studies have systematically evaluated the performance of Argos satellite collars for wildlife monitoring. We tested Argos satellite telemetry transmitters at two power levels in Southern Russia (five transmitters at 0.5 W and three at 1 W). Performance metrics were derived from the number and accuracy of location estimates and the number of days on which collars transmitted or failed to transmit data. Our results suggest that the performance of Argos collars in our study region was poor. At the power level of 0.5 W, 55% of the sessions resulted in at least one transmission, but only 21% provided a location estimate. The percentage of successful sessions did not increase much after setting the power level to 1.0 W (63%), but the increase in the number of location estimates was considerable (54%). At either power level, the majority of the location estimates were in the low quality classes though (80% nonstandard locations with 0.5 W and 45% with 1 W). Positional accuracies were 0.5, 0.7, 1.5, and 4.6 km for location classes 3, 2, 1, and 0, respectively. For nonstandard location classes A and B, positional accuracies were 2.1 and 18.3 km. Careful testing of transmitters is recommended before deployment, as the location of the study area can seriously affect performance.

     

Long-Term GPS Tracking of Ocean Sunfish Mola mola Offers a New Direction in Fish Monitoring

Satellite tracking of large pelagic fish provides insights on free-ranging behaviour, distributions and population structuring. Up to now, such fish have been tracked remotely using two principal methods: direct positioning of transmitters by Argos polar-orbiting satellites, and satellite relay of tag-derived light-level data for post hoc track reconstruction. Error fields associated with positions determined by these methods range from hundreds of metres to hundreds of kilometres. However, low spatial accuracy of tracks masks important details, such as foraging patterns. Here we use a fast-acquisition global positioning system (Fastloc GPS) tag with remote data retrieval to track long-term movements, in near real time and position accuracy of <70 m, of the world''s largest bony fish, the ocean sunfish Mola mola. Search-like movements occurred over at least three distinct spatial scales. At fine scales, sunfish spent longer in highly localised areas with faster, straighter excursions between them. These ‘stopovers’ during long-distance movement appear consistent with finding and exploiting food patches. This demonstrates the feasibility of GPS tagging to provide tracks of unparalleled accuracy for monitoring movements of large pelagic fish, and with nearly four times as many locations obtained by the GPS tag than by a conventional Argos transmitter. The results signal the potential of GPS-tagged pelagic fish that surface regularly to be detectors of resource ‘hotspots’ in the blue ocean and provides a new capability for understanding large pelagic fish behaviour and habitat use that is relevant to ocean management and species conservation.     

Evaluation of fast-acquisition GPS in stationary tests and fine-scale tracking of green turtles

Fastloc GPS (FGPS) is a variant of Global Positioning System (GPS) technology that offers important new utility for investigating fine-scale movements of marine animals like green turtles that surface too briefly for effective use of standard GPS. I report here on the accuracy and efficiency of this novel technology, compare it with two alternative methods, namely boat-based ultrasonic tracking and Argos Platform Transmitter Terminals (PTTs), and provide new data on the vagility and habitat selection of green turtles in shallow coastal foraging habitat. I used a combined FGPS receiver and PTT transmitter (Sirtrack, Havelock North, New Zealand) mounted together with an ultrasonic transmitter and time-depth recorder in a tether-attached housing that allowed automatic detachment and subsequent retrieval of the equipment without the requirement to recapture turtles. With this equipment I conducted short deployments (4.5 to 16.8 d) on 3 free-living adult-size green turtles in coastal foraging habitat in Queensland, Australia. In addition, stationary tests in air and afloat were conducted at the same site. FGPS location error (mean ± SD) increased as the number of satellites used in each computation decreased, from 26 m ± 19.2 (8 satellites) to 172 m ± 317.5 (4 satellites). During live tracking the frequency of FGPS locations greatly exceeded Argos PTT, such that screened data comprised about 50 times more FGPS locations despite a much tighter screening threshold for FGPS (250 m) than for Argos PTT (1000 m). FGPS locations showed the three study turtles used modest short-term activity ranges with Minimum Convex Polygon area mean ± SD 662 ha ± 293.9. They all remained within < 4.7 km of their capture-release locations and favoured shallow water, with 86% of locations at charted depths ≤ 3 m and the deepest location at 5.9 m. Fine-scale movements of each turtle varied from day to day with respect to tortuosity and areas traversed. Statistically significant day-night differences were evident in average rates of movement (greater by day) and in habitat selection, where diurnal locations had greater seagrass density while nocturnal locations featured deeper bathymetry. Individual turtles revisited some of their centres of activity (identified from 50% fixed kernel utilisation distributions) on multiple occasions but none of the study turtles travelled consistently between the same day-night pair of sites as has been reported elsewhere. Such disparity and the day-to-day variation in movements revealed by these short-term findings highlight the need for detailed tracking over longer periods at multiple locations. Fastloc GPS technology proved an effective new tool for this area of research.     

Accuracy of Lightweight Satellite Telemetry: A Case Study in the Iberian Peninsula

Abstract: Here we provide the first assessment of the accuracy of lightweight satellite transmitters (<80 g) under actual operating conditions and the performance of the Argos system in southern Europe. To estimate transmitter accuracy we used transmitters equipped with a Global Positioning System (GPS) and compared the location estimates provided by Argos with the estimates provided by the GPS. Using the 68th percentile to define the accuracy of locations estimates, observed accuracy was 4 km for Location Class (LC) 1, 15 km for LC 0, 20 km for LC A, and 59 km for LC B, which is in line with estimates reported by other authors. Yet, the error of the remaining 32% of the data ranged between 4 km and 11 km, 15 km and 217 km, 20 km and 145 km, and 59 km and 493 km, respectively, suggesting that using the 68th percentile to estimate accuracies might give misleading confidence on the accuracy of location estimates. Using the 90th percentile is probably more appropriate. Less than 10% of the locations we obtained corresponded to the more accurate LCs (3, 2, and 1), with Argos failing to provide a position estimate in 45% of the attempts. The low number of high-quality location estimates is likely a consequence of the electromagnetic interference reported for our study area, rather than a defect of the Platform Transmitter Terminals (PTTs), which under good conditions of signal reception seem to be as reliable as heavier ones. The recent advent of lightweight GPS transmitters overrides most of these problems. Yet, whereas the smallest Argos-GPS PTTs weigh 30 g, which restricts their use to animals weighting > 1,000 g, conventional PTTs can be as small as 9.5 g, allowing their use with animals weighting 250-300 g.     

Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology

In the past decade, ecologists have witnessed vast improvements in our ability to collect animal movement data through animal-borne technology, such as through GPS or ARGOS systems. However, more data does not necessarily yield greater knowledge in understanding animal ecology and conservation. In this paper, we provide a review of the major benefits, problems and potential misuses of GPS/Argos technology to animal ecology and conservation. Benefits are obvious, and include the ability to collect fine-scale spatio-temporal location data on many previously impossible to study animals, such as ocean-going fish, migratory songbirds and long-distance migratory mammals. These benefits come with significant problems, however, imposed by frequent collar failures and high cost, which often results in weaker study design, reduced sample sizes and poorer statistical inference. In addition, we see the divorcing of biologists from a field-based understanding of animal ecology to be a growing problem. Despite these difficulties, GPS devices have provided significant benefits, particularly in the conservation and ecology of wide-ranging species. We conclude by offering suggestions for ecologists on which kinds of ecological questions would currently benefit the most from GPS/Argos technology, and where the technology has been potentially misused. Significant conceptual challenges remain, however, including the links between movement and behaviour, and movement and population dynamics.     

Fix Success and Accuracy of Global Positioning System Collars in Old-Growth Temperate Coniferous Forests

Abstract: Global Positioning System (GPS) telemetry is used extensively to study animal distribution and resource selection patterns but is susceptible to biases resulting from data omission and spatial inaccuracies. These data errors may cause misinterpretation of wildlife habitat selection or spatial use patterns. We used both stationary test collars and collared free-ranging American black bears (Ursus americanus) to quantify systemic data loss and location error of GPS telemetry in mountainous, old-growth temperate forests of Olympic National Park, Washington, USA. We developed predictive models of environmental factors that influence the probability of obtaining GPS locations and evaluated the ability of weighting factors derived from these models to mitigate data omission biases from collared bears. We also examined the effects of microhabitat on collar fix success rate and examined collar accuracy as related to elevation changes between successive fixes. The probability of collars successfully obtaining location fixes was positively associated with elevation and unobstructed satellite view and was negatively affected by the interaction of overstory canopy and satellite view. Test collars were 33% more successful at acquiring fixes than those on bears. Fix success rates of collared bears varied seasonally and diurnally. Application of weighting factors to individual collared bear fixes recouped only 6% of lost data and failed to reduce seasonal or diurnal variation in fix success, suggesting that variables not included in our model contributed to data loss. Test collars placed to mimic bear bedding sites received 16% fewer fixes than randomly placed collars, indicating that microhabitat selection may contribute to data loss for wildlife equipped with GPS collars. Horizontal collar errors of >800 m occurred when elevation changes between successive fixes were >400 m. We conclude that significant limitations remain in accounting for data loss and error inherent in using GPS telemetry in coniferous forest ecosystems and that, at present, resource selection patterns of large mammals derived from GPS telemetry should be interpreted cautiously.     

Satellite tracking of kereru (

Satellite transmitters (PTTs) were attached to four kereru (New Zealand pigeon, Hemiphaga novaeseelandiae) in Invercargill, Southland, New Zealand, during 2005?06. The transmitters were used to monitor the birds? locations, movements and home ranges. Attachment of the transmitters affected the behaviour and body condition of one of the kereru; no other negative effects, such as skin abrasion, were noticed. Fifty-four percent of locations recorded were of Argos location classes 1, 2 or 3 (accuracy of ?1 km), and were used to determine the birds? movements and home range areas. Three of the kereru made flights across Foveaux Strait (a minimum distance of 33 km) to Stewart Island; the other remained around Invercargill. The maximum distance between their locations ranged from 11.4 to 101.9 km. Home ranges, as determined by cluster analysis, ranged from 619 ha to 31,732 ha, 100?1000 times greater than kereru home range areas estimated in previous studies. Given the long-distance movements kereru make, often to locations distant from roads and tracks, satellite telemetry is probably the most reliable and cost-effective method of determining their locations.     

A low-cost GPS GSM/GPRS telemetry system: performance in stationary field tests and preliminary data on wild otters (Lutra lutra)

Background

Despite the increasing worldwide use of global positioning system (GPS) telemetry in wildlife research, it has never been tested on any freshwater diving animal or in the peculiar conditions of the riparian habitat, despite this latter being one of the most important habitat types for many animal taxa. Moreover, in most cases, the GPS devices used have been commercial and expensive, limiting their use in low-budget projects.

Methodology/Principal Findings

We have developed a low-cost, easily constructed GPS GSM/GPRS (Global System for Mobile Communications/General Packet Radio Service) and examined its performance in stationary tests, by assessing the influence of different habitat types, including the riparian, as well as water submersion and certain climatic and environmental variables on GPS fix-success rate and accuracy. We then tested the GPS on wild diving animals, applying it, for the first time, to an otter species (Lutra lutra). The rate of locations acquired during the stationary tests reached 63.2%, with an average location error of 8.94 m (SD = 8.55). GPS performance in riparian habitats was principally affected by water submersion and secondarily by GPS inclination and position within the riverbed. Temporal and spatial correlations of location estimates accounted for some variation in the data sets. GPS-tagged otters also provided accurate locations and an even higher GPS fix-success rate (68.2%).

Conclusions/Significance

Our results suggest that GPS telemetry is reliably applicable to riparian and even diving freshwater animals. They also highlight the need, in GPS wildlife studies, for performing site-specific pilot studies on GPS functioning as well as for taking into account eventual spatial and temporal correlation of location estimates. The limited price, small dimensions, and high performance of the device presented here make it a useful and cost-effective tool for studies on otters and other aquatic or terrestrial medium-to-large-sized animals.     

Accuracy of ARGOS Locations of Pinnipeds at-Sea Estimated Using Fastloc GPS

Background

ARGOS satellite telemetry is one of the most widely used methods to track the movements of free-ranging marine and terrestrial animals and is fundamental to studies of foraging ecology, migratory behavior and habitat-use. ARGOS location estimates do not include complete error estimations, and for many marine organisms, the most commonly acquired locations (Location Class 0, A, B, or Z) are provided with no declared error estimate.

Methodology/Principal Findings

We compared the accuracy of ARGOS locations to those obtained using Fastloc GPS from the same electronic tags on five species of pinnipeds: 9 California sea lions (Zalophus californianus), 4 Galapagos sea lions (Zalophus wollebaeki), 6 Cape fur seals (Arctocephalus pusillus pusillus), 3 Australian fur seals (A. p. doriferus) and 5 northern elephant seals (Mirounga angustirostris). These species encompass a range of marine habitats (highly pelagic vs coastal), diving behaviors (mean dive durations 2–21 min) and range of latitudes (equator to temperate). A total of 7,318 ARGOS positions and 27,046 GPS positions were collected. Of these, 1,105 ARGOS positions were obtained within five minutes of a GPS position and were used for comparison. The 68^th percentile ARGOS location errors as measured in this study were LC-3 0.49 km, LC-2 1.01 km, LC-1 1.20 km, LC-0 4.18 km, LC-A 6.19 km, LC-B 10.28 km.

Conclusions/Significance

The ARGOS errors measured here are greater than those provided by ARGOS, but within the range of other studies. The error was non-normally distributed with each LC highly right-skewed. Locations of species that make short duration dives and spend extended periods on the surface (sea lions and fur seals) had less error than species like elephant seals that spend more time underwater and have shorter surface intervals. Supplemental data (S1) are provided allowing the creation of density distributions that can be used in a variety of filtering algorithms to improve the quality of ARGOS tracking data.     

Effects of Number of Animals Monitored on Representations of Cattle Group Movement Characteristics and Spatial Occupancy

The number of animals required to represent the collective characteristics of a group remains a concern in animal movement monitoring with GPS. Monitoring a subset of animals from a group instead of all animals can reduce costs and labor; however, incomplete data may cause information losses and inaccuracy in subsequent data analyses. In cattle studies, little work has been conducted to determine the number of cattle within a group needed to be instrumented considering subsequent analyses. Two different groups of cattle (a mixed group of 24 beef cows and heifers, and another group of 8 beef cows) were monitored with GPS collars at 4 min intervals on intensively managed pastures and corn residue fields in 2011. The effects of subset group size on cattle movement characterization and spatial occupancy analysis were evaluated by comparing the results between subset groups and the entire group for a variety of summarization parameters. As expected, more animals yield better results for all parameters. Results show the average group travel speed and daily travel distances are overestimated as subset group size decreases, while the average group radius is underestimated. Accuracy of group centroid locations and group radii are improved linearly as subset group size increases. A kernel density estimation was performed to quantify the spatial occupancy by cattle via GPS location data. Results show animals among the group had high similarity of spatial occupancy. Decisions regarding choosing an appropriate subset group size for monitoring depend on the specific use of data for subsequent analysis: a small subset group may be adequate for identifying areas visited by cattle; larger subset group size (e.g. subset group containing more than 75% of animals) is recommended to achieve better accuracy of group movement characteristics and spatial occupancy for the use of correlating cattle locations with other environmental factors.     

Performance of a satellite-linked GPS on Pacific walruses (<Emphasis Type="Italic">Odobenus rosmarus divergens</Emphasis>)

We evaluated the utility of a satellite-linked GPS in obtaining location data from Pacific walruses (Odobenus rosmarus divergens). A unit was attached to one of the tusks of each of three adult male walruses in Bristol Bay, Alaska. The units were designed to relay GPS positions through the Argos Data Collection and Location System. The GPS was only minimally effective in obtaining location data. An average of only 5% of the attempts yielded a position, and only a small number of these were locations at sea. The paucity of successful attempts was probably due to infrequent and brief surfacings of the GPS, the proximity of cliffs to predominant haul-out sites in the study region, and the packing of animals when they were hauled out in herds. Argos was effective in relaying GPS positions in this study, but as GPS technology advances, and its application to marine mammal studies becomes more prevalent, it seems that the greatest challenge to the study of many species will be in data retrieval.     

Estimating resource selection with count data

Resource selection functions (RSFs) are typically estimated by comparing covariates at a discrete set of “used” locations to those from an “available” set of locations. This RSF approach treats the response as binary and does not account for intensity of use among habitat units where locations were recorded. Advances in global positioning system (GPS) technology allow animal location data to be collected at fine spatiotemporal scales and have increased the size and correlation of data used in RSF analyses. We suggest that a more contemporary approach to analyzing such data is to model intensity of use, which can be estimated for one or more animals by relating the relative frequency of locations in a set of sampling units to the habitat characteristics of those units with count‐based regression and, in particular, negative binomial (NB) regression. We demonstrate this NB RSF approach with location data collected from 10 GPS‐collared Rocky Mountain elk (Cervus elaphus) in the Starkey Experimental Forest and Range enclosure. We discuss modeling assumptions and show how RSF estimation with NB regression can easily accommodate contemporary research needs, including: analysis of large GPS data sets, computational ease, accounting for among‐animal variation, and interpretation of model covariates. We recommend the NB approach because of its conceptual and computational simplicity, and the fact that estimates of intensity of use are unbiased in the face of temporally correlated animal location data.     

Stochastic modelling of animal movement

Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal ‘settling down’, accomplished by including one or more focal points that attract the animal''s movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Lévy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.     

Global positioning system and associated technologies in animal behaviour and ecological research

Biologists can equip animals with global positioning system (GPS) technology to obtain accurate (less than or equal to 30 m) locations that can be combined with sensor data to study animal behaviour and ecology. We provide the background of GPS techniques that have been used to gather data for wildlife studies. We review how GPS has been integrated into functional systems with data storage, data transfer, power supplies, packaging and sensor technologies to collect temperature, activity, proximity and mortality data from terrestrial species and birds. GPS ‘rapid fixing’ technologies combined with sensors provide location, dive frequency and duration profiles, and underwater acoustic information for the study of marine species. We examine how these rapid fixing technologies may be applied to terrestrial and avian applications. We discuss positional data quality and the capability for high-frequency sampling associated with GPS locations. We present alternatives for storing and retrieving data by using dataloggers (biologging), radio-frequency download systems (e.g. very high frequency, spread spectrum), integration of GPS with other satellite systems (e.g. Argos, Globalstar) and potential new data recovery technologies (e.g. network nodes). GPS is one component among many rapidly evolving technologies. Therefore, we recommend that users and suppliers interact to ensure the availability of appropriate equipment to meet animal research objectives.     

Animal ecology meets GPS-based radiotelemetry: a perfect storm of opportunities and challenges

Global positioning system (GPS) telemetry technology allows us to monitor and to map the details of animal movement, securing vast quantities of such data even for highly cryptic organisms. We envision an exciting synergy between animal ecology and GPS-based radiotelemetry, as for other examples of new technologies stimulating rapid conceptual advances, where research opportunities have been paralleled by technical and analytical challenges. Animal positions provide the elemental unit of movement paths and show where individuals interact with the ecosystems around them. We discuss how knowing where animals go can help scientists in their search for a mechanistic understanding of key concepts of animal ecology, including resource use, home range and dispersal, and population dynamics. It is probable that in the not-so-distant future, intense sampling of movements coupled with detailed information on habitat features at a variety of scales will allow us to represent an animal''s cognitive map of its environment, and the intimate relationship between behaviour and fitness. An extended use of these data over long periods of time and over large spatial scales can provide robust inferences for complex, multi-factorial phenomena, such as meta-analyses of the effects of climate change on animal behaviour and distribution.     

Filtering and interpreting location errors in satellite telemetry of marine animals

Argos telemetry offers a powerful means of tracking wild animals in their habitat, yet the delivered locations are subject to complex errors and random coverage. Bayesian filters and statistical models allow for objective trajectory estimates and inference on movement rates. As an alternative to Monte-Carlo methods, we investigate here how classic time series technique, such as the Kalman Filter, can be made robust to uncover patterns in the data. Our approach relies on a composite measurement model to account for outliers, and makes use of all the Location Classes to smooth observations and regularize the track to a regular time grid. Two application examples are presented. Using data from freely-swimming leatherback turtles, we confirm that locations of class A (LCA) are more accurate on average than class 0, and we recommend their use in tracking studies. We further show how measurement errors (and their geometry) interact with the assumed movement model, further modulating the final location error and the discriminating ability of the filter. The choice of the movement model appears important, since a model with no velocity constraint may fit observational errors at the expense of trajectory smoothness, while a speed-based model is better behaved but less forgiving for data fitting and outlier identification. Varying sea surface temperatures also appear to degrade the quality of locations and increase the occurrence of outliers, possibly in relation to thermal stratification and depth behavior. These results have important implications when inferring changes in behavior from long-term movements.