Predicting the distribution of oceanic-stage Kemp's ridley sea turtles

Putman, Nathan F.; Mansfield, Katherine; He, Ruoying; Shaver, Donna J.; Verley, Philippe

doi:10.1098/rsbl.2013.0345

Cited by 42 publications

(40 citation statements)

References 17 publications

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“…Our findings support the growing consensus that additional, possibly combined factors, such as mortality [4,5], sporadic meteorological and oceanographic events [6], and swimming and foraging behaviours [2,3] may play key roles in driving distributions and connectivity of marine populations. Studies increasingly indicate that marine animals do not randomly search out food patches, but rather follow somewhat-fixed migratory routes that coincide with typically productive oceanic regions [2,59,60].…”

Section: Palmyra and Regional Rookeriessupporting

confidence: 86%

“…Marine connectivity is thought to be greatly influenced by source population size and ocean circulation processes [1]. However, recent work has revealed increasingly complex scenarios with other factors, such as swimming behaviour [2,3], mortality [4,5] or intermittent climatic events like storms [6] playing key roles in determining the distributions of marine organisms. In numerous animal species with life cycles characterized by ontogenetic shifts in habitat utilization, population distribution remains insufficiently understood owing to cryptic stages and poorly defined linkages among stages [7].…”

Section: Introductionmentioning

confidence: 99%

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Predicting connectivity of green turtles at Palmyra Atoll, central Pacific: a focus on mtDNA and dispersal modelling

Naro‐Maciel

Gaughran

Putman

et al. 2014

J. R. Soc. Interface.

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Population connectivity and spatial distribution are fundamentally related to ecology, evolution and behaviour. Here, we combined powerful genetic analysis with simulations of particle dispersal in a high-resolution ocean circulation model to investigate the distribution of green turtles foraging at the remote Palmyra Atoll National Wildlife Refuge, central Pacific. We analysed mitochondrial sequences from turtles ( n = 349) collected there over 5 years (2008–2012). Genetic analysis assigned natal origins almost exclusively (approx. 97%) to the West Central and South Central Pacific combined Regional Management Units. Further, our modelling results indicated that turtles could potentially drift from rookeries to Palmyra Atoll via surface currents along a near-Equatorial swathe traversing the Pacific. Comparing findings from genetics and modelling highlighted the complex impacts of ocean currents and behaviour on natal origins. Although the Palmyra feeding ground was highly differentiated genetically from others in the Indo-Pacific, there was no significant differentiation among years, sexes or stage-classes at the Refuge. Understanding the distribution of this foraging population advances knowledge of green turtles and contributes to effective conservation planning for this threatened species.

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Section: Palmyra and Regional Rookeriessupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Predicting connectivity of green turtles at Palmyra Atoll, central Pacific: a focus on mtDNA and dispersal modelling

Naro‐Maciel

Gaughran

Putman

et al. 2014

J. R. Soc. Interface.

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“…Using well-established techniques (e.g. Putman et al, 2010bPutman et al, , 2012Putman et al, , 2013b, ICHTHYOP v2.21 particletracking software tracked the paths of 'virtual turtles' ( particles) released into the surface currents of the Global Hybrid Coordinate Ocean Model (HYCOM) (Bleck, 2002). Global HYCOM has output at 00:00 h GMT with a spatial resolution of 0.08 deg (∼7 km at mid-latitudes).…”

Section: Simulating Magnetic Navigationmentioning

confidence: 99%

Magnetic navigation behavior and the oceanic ecology of young loggerhead sea turtles

Putman

Verley

Endres

et al. 2015

Journal of Experimental Biology

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During long-distance migrations, animals navigate using a variety of sensory cues, mechanisms and strategies. Although guidance mechanisms are usually studied under controlled laboratory conditions, such methods seldom allow for navigation behavior to be examined in an environmental context. Similarly, although realistic environmental models are often used to investigate the ecological implications of animal movement, explicit consideration of navigation mechanisms in such models is rare. Here, we used an interdisciplinary approach in which we first conducted lab-based experiments to determine how hatchling loggerhead sea turtles (Caretta caretta) respond to magnetic fields that exist at five widely separated locations along their migratory route, and then studied the consequences of the observed behavior by simulating it within an ocean circulation model. Magnetic fields associated with two geographic regions that pose risks to young turtles (due to cold wintertime temperatures or potential displacement from the migratory route) elicited oriented swimming, whereas fields from three locations where surface currents and temperature pose no such risk did not. Additionally, at locations with fields that elicited oriented swimming, simulations indicate that the observed behavior greatly increases the likelihood of turtles advancing along the migratory pathway. Our findings suggest that the magnetic navigation behavior of sea turtles is intimately tied to their oceanic ecology and is shaped by a complex interplay between ocean circulation and geomagnetic dynamics.

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“…Information about sea turtle dispersal and behaviour during the "lost years" has been gained through modelling approaches (Hays et al, 2010;Shillinger G. L. et al, 2012;Putman et al, 2013;Casale and Mariani, 2014), telemetry (Nagelkerken et al, 2003;Witherington et al, 2012;Mansfield et al, 2014;Scott et al, 2014), and other emerging technologies, such as stable isotopes (Bowen and Karl, 2007;Reich et al, 2007;Snover et al, 2010;López-Castro et al, 2014). Due to a lack of information on active dispersal capacity, modelling efforts rely heavily on classifying young turtles as "passive drifters, " with little influence on their environment (Hays et al, 2010;Gaspar et al, 2012;Shillinger G. L. et al, 2012;Putman and Mansfield, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Due to a lack of information on active dispersal capacity, modelling efforts rely heavily on classifying young turtles as "passive drifters, " with little influence on their environment (Hays et al, 2010;Gaspar et al, 2012;Shillinger G. L. et al, 2012;Putman and Mansfield, 2015). Biophysical models can be strengthened and verified by incorporating behavioural data, such as swim speed and orientation (Putman et al, 2012(Putman et al, , 2013Kobayashi et al, 2014;Briscoe et al, 2016), as both swim behaviour and ocean currents control young sea turtles' directionality and influence dispersal outcomes Putman and Mansfield, 2015;Briscoe et al, 2016). Behavioural data can be collected by deploying instruments to track turtle movements (Putman et al, 2012;Thums et al, 2013;Mansfield et al, 2014;Scott et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Comparing Acoustic Tag Attachments Designed for Mobile Tracking of Hatchling Sea Turtles

et al. 2017

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The poorly understood movements of sea turtles during the "lost years" of their early life history have been characterized as a "passive drifter" stage. Biologging technology allows us to study patterns of dispersal, but the small body size of young life stages requires particular consideration that such tagging does not significantly impede animal movements. We tested the effect of instrument attachment methods for mobile acoustic tracking of hatchling sea turtles, including a design that would be suitable for leatherback turtles (Dermochelys coriacea). We obtained 8-week-old hatchery-reared green sea turtles (Chelonia mydas) (n = 12 individuals) and examined the effect of attaching Vemco V5 acoustic tags. Each animal's swim speed, swimming depth, and stroke frequency were determined under three scenarios: control, direct Velcro ® attachment to the carapace, and harness attachment, to determine if there was a significant difference amongst treatments. Turtle swimming speed was significantly slower during the middle period of the trial for the harness attachment compared with the control. No significant change in swim speed was observed when the tag was attached directly with Velcro ® , and no significant change in dive depth was observed for either treatment compared to the control. Stroke frequency was significantly greater compared to the control at the end of the trial for the Velcro ® attachment only, although there was no corresponding increase in swimming speed. This information can be used to design effective approaches for actively tracking free-ranging hatchling sea turtles to understand dispersal and survival of these vulnerable marine species.

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Predicting the distribution of oceanic-stage Kemp's ridley sea turtles

Cited by 42 publications

References 17 publications

Predicting connectivity of green turtles at Palmyra Atoll, central Pacific: a focus on mtDNA and dispersal modelling

Predicting connectivity of green turtles at Palmyra Atoll, central Pacific: a focus on mtDNA and dispersal modelling

Magnetic navigation behavior and the oceanic ecology of young loggerhead sea turtles

Comparing Acoustic Tag Attachments Designed for Mobile Tracking of Hatchling Sea Turtles

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