Why do Argos satellite tags stop relaying data?
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ABSTRACT:
SUBMITTER: Hays GC
PROVIDER: S-EPMC8207149 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: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.
| S-EPMC3395646 | biostudies-literature
Project description:BackgroundState-space models are important tools for quality control and analysis of error-prone animal movement data. The near real-time (within 24 h) capability of the Argos satellite system can aid dynamic ocean management of human activities by informing when animals enter wind farms, shipping lanes, and other intensive use zones. This capability also facilitates the use of ocean observations from animal-borne sensors in operational ocean forecasting models. Such near real-time data provision requires rapid, reliable quality control to deal with error-prone Argos locations.MethodsWe formulate a continuous-time state-space model to filter the three types of Argos location data (Least-Squares, Kalman filter, and Kalman smoother), accounting for irregular timing of observations. Our model is deliberately simple to ensure speed and reliability for automated, near real-time quality control of Argos location data. We validate the model by fitting to Argos locations collected from 61 individuals across 7 marine vertebrates and compare model-estimated locations to contemporaneous GPS locations. We then test assumptions that Argos Kalman filter/smoother error ellipses are unbiased, and that Argos Kalman smoother location accuracy cannot be improved by subsequent state-space modelling.ResultsEstimation accuracy varied among species with Root Mean Squared Errors usually <5 km and these decreased with increasing data sampling rate and precision of Argos locations. Including a model parameter to inflate Argos error ellipse sizes in the north - south direction resulted in more accurate location estimates. Finally, in some cases the model appreciably improved the accuracy of the Argos Kalman smoother locations, which should not be possible if the smoother is using all available information.ConclusionsOur model provides quality-controlled locations from Argos Least-Squares or Kalman filter data with accuracy similar to or marginally better than Argos Kalman smoother data that are only available via fee-based reprocessing. Simplicity and ease of use make the model suitable both for automated quality control of near real-time Argos data and for manual use by researchers working with historical Argos data.
| S-EPMC7368688 | biostudies-literature
Project description:Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km) was nearly half that of LS estimates (11.6 ± 8.4 km). Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.
| S-EPMC3961316 | biostudies-literature
Project description:The reliable estimation of animal location, and its associated error is fundamental to animal ecology. There are many existing techniques for handling location error, but these are often ad hoc or are used in isolation from each other. In this study we present a Bayesian framework for determining location that uses all the data available, is flexible to all tagging techniques, and provides location estimates with built-in measures of uncertainty. Bayesian methods allow the contributions of multiple data sources to be decomposed into manageable components. We illustrate with two examples for two different location methods: satellite tracking and light level geo-location. We show that many of the problems with uncertainty involved are reduced and quantified by our approach. This approach can use any available information, such as existing knowledge of the animal's potential range, light levels or direct location estimates, auxiliary data, and movement models. The approach provides a substantial contribution to the handling uncertainty in archival tag and satellite tracking data using readily available tools.
| S-EPMC2758548 | biostudies-literature
Project description:BackgroundMigration research is in rapid expansion and increasingly based on sophisticated satellite-tracking devices subject to constant technological refinement, but is still ripe with descriptive studies and in need of meta-analyses looking for emergent generalisations. In particular, coexistence of studies and devices with different frequency of location sampling and spatial accuracy generates doubts of data compatibility, potentially preventing meta-analyses. We used satellite-tracking data on a migratory raptor to: (1) test whether data based on different location sampling frequencies and on different position subsampling approaches are compatible, and (2) seek potential solutions that enhance compatibility and enable eventual meta-analyses.Methodology/principal findingsWe used linear mixed models to analyse the differences in the speed and route length of the migration tracks of 36 Black kites (Milvus migrans) satellite-tagged with two different types of devices (Argos vs GPS tags), entailing different regimes of position sampling frequency. We show that different location sampling frequencies and data subsampling approaches generate large (up to 33%) differences in the estimates of route length and migration speed of this migratory bird.Conclusions/significanceOur results show that the abundance of locations available for analysis affects the tortuosity and realism of the estimated migration path. To avoid flaws in future meta-analyses or unnecessary loss of data, we urge researchers to reach an agreement on a common protocol of data presentation, and to recognize that all transmitter-based studies are likely to underestimate the actual distance traveled by the marked animal. As ecological research becomes increasingly technological, new technologies should be matched with improvements in analytical capacity that guarantee data compatibility.
| S-EPMC3498226 | biostudies-literature
Project description:Biologging technologies are changing the way in which the marine environment is observed and monitored. However, because device retrieval is typically required to access the high-resolution data they collect, their use is generally restricted to those animals that predictably return to land. Data abstraction and transmission techniques aim to address this, although currently these are limited in scope and do not incorporate, for example, acceleration measurements which can quantify animal behaviours and movement patterns over fine-scales.In this study, we present a new method for the collection, abstraction and transmission of accelerometer data from free-ranging marine predators via the Argos satellite system. We test run the technique on 20 juvenile southern elephant seals Mirounga leonina from the Kerguelen Islands during their first months at sea following weaning. Using retrieved archival data from nine individuals that returned to the colony, we compare and validate abstracted transmissions against outputs from established accelerometer processing procedures.Abstracted transmissions included estimates, across five segments of a dive profile, of time spent in prey catch attempt (PrCA) behaviours, swimming effort and pitch. These were then summarised and compared to archival outputs across three dive phases: descent, bottom and ascent. Correlations between the two datasets were variable but generally good (dependent on dive phase, marginal R2 values of between .45 and .6 to >.9) and consistent between individuals. Transmitted estimates of PrCA behaviours and swimming effort were positively biased to those from archival processing.Data from this study represent some of the first remotely transmitted quantifications from accelerometers. The methods presented and analysed can be used to provide novel insight towards the behaviours and movements of free-ranging marine predators, such as juvenile southern elephant seals, from whom logger retrieval is challenging. Future applications could however benefit from some adaption, particularly to reduce positive bias in transmitted PrCA behaviours and swimming effort, for which this study provides useful insight.
| S-EPMC5812097 | biostudies-literature
Project description:BackgroundMuscle satellite cells (MSCs) represent a devoted stem cell population that is responsible for postnatal muscle growth and skeletal muscle regeneration. An important characteristic of MSCs is that they encompass multi potential mesenchymal stem cell activity and are able to differentiate into myocytes and adipocytes. To achieve a global view of the genes differentially expressed in MSCs, myotube formed-cells (MFCs) and adipocyte-like cells (ALCs), we performed large-scale EST sequencing of normalized cDNA libraries developed from bovine MSCs.ResultsA total of 24,192 clones were assembled into 3,333 clusters, 5,517 singletons and 3,842contigs. Functional annotation of these unigenes revealed that a large portion of the differentially expressed genes are involved in cellular and signaling processes. Database for Annotation, Visualization and Integrated Discovery (DAVID) functional analysis of three subsets of highly expressed gene lists (MSC233, MFC258, and ALC248) highlighted some common and unique biological processes among MSC, MFC and ALC. Additionally, genes that may be specific to MSC, MFC and ALC are reported here, and the role of dimethylarginine dimethylaminohydrolase2 (DDAH2) during myogenesis and hemoglobin subunit alpha2 (HBA2) during transdifferentiation in C2C12 were assayed as a case study. DDAH2 was up-regulated during myognesis and knockdown of DDAH2 by siRNA significantly decreased myogenin (MYOG) expression corresponding with the slight change in cell morphology. In contrast, HBA2 was up-regulated during ALC formation and resulted in decreased intracellular lipid accumulation and CD36 mRNA expression upon knockdown assay.ConclusionIn this study, a large number of EST sequences were generated from the MSC, MFC and ALC. Overall, the collection of ESTs generated in this study provides a starting point for the identification of novel genes involved in MFC and ALC formation, which in turn offers a fundamental resource to enable better understanding of the mechanism of muscle differentiation and transdifferentiation.
| S-EPMC3818215 | biostudies-literature
Project description:Understanding how an animal utilises its surroundings requires its movements through space to be described accurately. Satellite telemetry is the only means of acquiring movement data for many species however data are prone to varying amounts of spatial error; the recent application of state-space models (SSMs) to the location estimation problem have provided a means to incorporate spatial errors when characterising animal movements. The predominant platform for collecting satellite telemetry data on free-ranging animals, Service Argos, recently provided an alternative Doppler location estimation algorithm that is purported to be more accurate and generate a greater number of locations that its predecessor. We provide a comprehensive assessment of this new estimation process performance on data from free-ranging animals relative to concurrently collected Fastloc GPS data. Additionally, we test the efficacy of three readily-available SSM in predicting the movement of two focal animals. Raw Argos location estimates generated by the new algorithm were greatly improved compared to the old system. Approximately twice as many Argos locations were derived compared to GPS on the devices used. Root Mean Square Errors (RMSE) for each optimal SSM were less than 4.25 km with some producing RMSE of less than 2.50 km. Differences in the biological plausibility of the tracks between the two focal animals used to investigate the utility of SSM highlights the importance of considering animal behaviour in movement studies. The ability to reprocess Argos data collected since 2008 with the new algorithm should permit questions of animal movement to be revisited at a finer resolution.
| S-EPMC4408085 | biostudies-literature
Project description:Spawning behaviour of Atlantic bluefin tuna (Thunnus thynnus) was investigated using electronic satellite tags deployed in the western Mediterranean spawning ground, around the Balearic Islands (years 2009-2011). All the fish were tagged underwater and released within schools. In general, the fish tagged in the same year/school displayed common migratory trends. Following extended residency around the Balearic Islands, most tagged tuna crossed the Strait of Gibraltar heading for the North Atlantic. Discrepancies between the migratory tracks reconstructed from this and previous electronic tagging studies suggest that the bluefin tuna Mediterranean population may comprise distinct units exhibiting differing migratory behaviours. The diving behaviour varied between oceanic regions throughout the migratory pathways, the shallowest distribution taking place in the spawning ground and the deepest at the Strait of Gibraltar. A unique diving pattern was found on the majority of nights while the fish stayed at the spawning ground; it consisted of frequent and brief oscillatory movements up and down through the mixed layer, resulting in thermal profiles characterized by oscillations about the thermocline. Such a pattern is believed to reflect recent courtship and spawning activity. Reproductive parameters inferred from the analysis of vertical profiles are consistent with those estimated in previous studies based on biological samples.
| S-EPMC3788109 | biostudies-other
Project description: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.
| S-EPMC3114854 | biostudies-literature