State-space models for bio-loggers: A methodological road map

Jonsen, Ian D.; Basson, M.; Bestley, Sophie; Bravington, Mark V.; Patterson, Toby A.; Pedersen, Martin Wæver; Thomson, Robin B.; Thygesen, Uffe Høgsbro; Wotherspoon, Simon

doi:10.1016/j.dsr2.2012.07.008

Cited by 205 publications

(232 citation statements)

References 70 publications

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“…Further, Argos positions are estimated at irregular intervals (especially for diving animals) but SSSM position estimates can be regularized. Detailed descriptions of SSSMs are provided in Breed et al (2009), Jonsen et al (2005Jonsen et al ( , 2007Jonsen et al ( , 2013, Morales et al (2004) and Patterson et al (2008).…”

Section: State Space Switching Modelsmentioning

confidence: 99%

“…A state-space switching approach was used to model the killer whales' movements and estimate behavioural modes from the Argos position estimates, while simultaneously accounting for uncertainty in the movement dynamics and observations (Jonsen et al, 2005(Jonsen et al, , 2007(Jonsen et al, , 2013Morales et al, 2004;Patterson et al, 2008). A state-space switching model (SSSM) (Jonsen et al, 2005(Jonsen et al, , 2007 has two components: the process model describing the movement process of interest and the observation model relating the unobserved state (location) predictions of the process model to the observed data.…”

Section: State Space Switching Modelsmentioning

confidence: 99%

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Movement and diving of killer whales ( Orcinus orca ) at a Southern Ocean archipelago

Reisinger

Keith

Andrews

et al. 2015

Journal of Experimental Marine Biology and Ecology

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Eleven satellite tags were deployed on 9 killer whales at the Prince Edwards Islands in the Southern Ocean. State-space switching models were used to generate position estimates from Argos location data, while two behavioural modes were estimated from the data. Individuals were tracked for 5.6-53.2 days, during which time they moved 416-4,470 km (mean 82.7 km day -1 ) but 69% of position estimates were within the 1000 m depth contour around the islands (<35 km from the tagging site). Killer whales showed restricted behaviour close to the islands, particularly inshore where they can effectively hunt seals and penguins, and at seamounts to the north of the islands.Generalized linear mixed effect models were used to explore the relationship between environmental variables and behavioural mode. The best model included depth, sea surface temperature, latitude, sea surface height anomaly and bottom slope, but killer whales did not clearly target features such as fronts and apparent mesoscale eddies. Killer whales showed restricted behaviour in shallow water, at high latitudes and low sea surface temperature -the conditions characterising the archipelago.Dive data from two individuals largely revealed shallow dives (7.5-50 m deep), but deeper dive bouts to around 368 m were also recorded. Dives were significantly deeper during the day and maximum dive depths were 767.5 and 499.5 m, respectively. This suggests that killer whales might also prey on vertically migrating cephalopods and perhaps Patagonian toothfish.Three individuals made rapid and directed long-distance movements northwards of the islands, the reasons for which are speculative.

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Section: State Space Switching Modelsmentioning

confidence: 99%

Section: State Space Switching Modelsmentioning

confidence: 99%

Movement and diving of killer whales ( Orcinus orca ) at a Southern Ocean archipelago

Reisinger

Keith

Andrews

et al. 2015

Journal of Experimental Marine Biology and Ecology

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“…A short track, run individually through the model, could not produce accurate behavioral states but when run with other tracks in the hSSM, behaviors can then be categorized (Breed et al, 2009). The hSSM is ideal when behaviors cannot be directly observed throughout the track, such as with the olive ridley turtles, therefore data such as speed and turn angle are used to delineate probable behavior (Jonsen et al, 2013).…”

Section: Track Analysis and State-space Modelmentioning

confidence: 99%

“…All Argos location quality points except for 0 and Z were used in the movement analysis (i.e., location classes 3, 2, 1, A, B) and a hierarchal state-space model (hSSM) with a time interval of 3.5 h was used to filter the location data and determine internesting behavior (Breed et al, 2009;Jonsen et al, 2013). SSMs use parameters associated with an animal's position (Jonsen et al, 2003) and determine a behavioral state for each point in time (Breed et al, 2009;Jonsen et al, 2013).…”

Section: Track Analysis and State-space Modelmentioning

confidence: 99%

“…SSMs use parameters associated with an animal's position (Jonsen et al, 2003) and determine a behavioral state for each point in time (Breed et al, 2009;Jonsen et al, 2013). Through the use of a two part model, an equation is used to determine how behavioral states change randomly in time and previous locations are used to estimate the next location based on an independent random walk model and biological constraints of the animal, such as how far they can travel in a day (Jonsen et al, 2013). SSMs are used to draw inferences from data on behavioral changes through time and how it can be related to actual biological processes (e.g., foraging, breeding, or migrating).…”

Section: Track Analysis and State-space Modelmentioning

confidence: 99%

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Informing Marine Protected Area Designation and Management for Nesting Olive Ridley Sea Turtles Using Satellite Tracking

Dawson

Formia²,

Agamboué³

et al. 2017

Front. Mar. Sci.

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Understanding the horizontal and vertical habitat of olive ridley sea turtles (Lepidochelys olivacea), a threatened species, is critical for determining regions for protection and relevant gear modifications that may effectively reduce bycatch, the largest threat to this species. Satellite transmitters were used to determine the movement and dive behavior of 21 female olive ridley turtles tagged in Pongara National Park, Gabon during the 2012, 2013, and 2015 nesting seasons. A switching state-space model was used to filter the tracking data and categorize the internesting and post-nesting movements. Gridded utilization distribution (UD) home range analysis of tracking data revealed that the entire core habitat occurred in the Komo Estuary during the internesting period. Within the Komo Estuary, 58% of this core UD occurred in shipping lanes. Dive data from the 2015 tagging season revealed that during the internesting period, turtles spent the majority of their time resting on the estuary seabed. Approximately 20% of all dive time was spent on the bottom and all maximum dive depths corresponded to the depth of the seabed, indicating that bottom set gear during the internesting period may pose the greatest potential for fisheries interactions. National parks currently protect many of the nesting sites and the Gabon Bleu initiative has formally designated 10 new marine parks and a network of community and industrial fishing zones; this data was a layer used in determining the park and zone boundaries. Shared use of the estuary by fisheries, shipping, and olive ridley turtles creates a need for management measures to reduce interactions. Thus, the results from this study can further provide detailed information that can be used to support the development of evidence-based management plans.

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Seasonal movements of immature Kemp's ridley sea turtles (Lepidochelys kempii) in the northern gulf of Mexico

Coleman

Pitchford

Bailey

et al. 2016

Aquatic Conservation

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ABSTRACT1. Seasonal movements and core habitat areas of immature Kemp's ridley sea turtles (Lepidochelys kempii) in the northern Gulf of Mexico were tracked via satellite telemetry. Tagged turtles were incidentally captured by recreational fishermen and rehabilitated at the Institute for Marine Mammal Studies in Gulfport, Mississippi.2. The average size of the core habitat areas (50% KDE (kernel density estimation)) was 1660.2 km 2 ± 3438.2 SD. Turtles displayed strong intra-and inter-annual site fidelity to the Mississippi Sound during the spring, summer, and autumn months. During the winter months, most turtles, probably influenced by water temperatures, migrated to nearshore waters of Louisiana on either side of the Mississippi River Delta. However, other migration strategies were also observed. 3. Overall, these data indicate that the Mississippi Sound is an important developmental habitat for this critically endangered species. In addition, their wintering grounds in Louisiana are utilized by adult Kemp's ridleys and other sea turtle species as foraging grounds and migratory corridors. The high use of these areas by sea turtle populations increases the potential for negative impacts from anthropogenic disturbances (e.g. shrimp trawling, oil production, hypoxia) that occur there.

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State-space models for bio-loggers: A methodological road map

Cited by 205 publications

References 70 publications

Movement and diving of killer whales ( Orcinus orca ) at a Southern Ocean archipelago

Movement and diving of killer whales ( Orcinus orca ) at a Southern Ocean archipelago

Informing Marine Protected Area Designation and Management for Nesting Olive Ridley Sea Turtles Using Satellite Tracking

Seasonal movements of immature Kemp's ridley sea turtles (Lepidochelys kempii) in the northern gulf of Mexico

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