Environmental predictors of foraging and transit behaviour in flatback turtles Natator depressus

Thums, Michele; Waayers, David; Huang, Zhi; Pattiaratchi, Charitha; Bernus, Jeffrey; Meekan, Mark G.

doi:10.3354/esr00818

Cited by 21 publications

(15 citation statements)

References 46 publications

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“…Nevertheless, to overcome this issue the hDCRW-SSM takes into account the estimated error associated with each ARGOS LC (Jonsen et al, 2006), which ranges from 3000 m for LC B to 150 m for LC 3 (see Vincent et al, 2002;Jonsen et al, 2005 for details on how estimated errors are calculated). To incorporate GPS locations in the model, we assigned them the lowest ARGOS error (LC 3, <150 m), as per Thums et al (2017). The modeling parameters were as follows: we iterated one Markov chain Monte Carlo (MCMC) 300000 times, the first 100000 iterations were excluded (burn-in), every 100th of the remaining 200000 iterations was retained, and reconstructed locations were computed at 12-h intervals.…”

Section: Spatial Distribution Of Tracked Turtlesmentioning

confidence: 99%

Habitat Use and Behavior of Multiple Species of Marine Turtles at a Foraging Area in the Northeastern Gulf of Mexico

et al. 2019

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Multi-species conservation strategies can be useful to maximize allocation of resources. To effectively plan for multi-species management practices, it is important to have a robust understanding of the variability in the spatial and behavioral ecology of sympatric species. To address this in the context of marine turtles, this study explored fine-scale habitat use by three sympatric species [juvenile green turtles (Chelonia mydas), Kemp's ridley turtles (Lepidochelys kempii) and loggerhead turtles (Caretta caretta)] in a foraging area near Crystal River, Florida, United States. By combining sighting surveys and satellite tracking methods, we found that the distribution of the three species of marine turtles in this region overlapped both in space and time. We also observed differences in the fine-scale location of hotspots and in-water behavior among species, with some degree of apparent habitat partitioning. Habitat partitioning was particularly evident when assessing the diving and surfacing behavior of tracked turtles, with some degree of differentiation in diel diving patterns, particularly depths utilized during daytime/nighttime and the dive/surface duration. Our study provides ecological baseline data on the spatial overlap, habitat use and behavior of three sympatric marine turtle species, which can inform future management strategies at nearshore marine habitats in the Northeastern Gulf of Mexico.

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Section: Spatial Distribution Of Tracked Turtlesmentioning

confidence: 99%

Habitat Use and Behavior of Multiple Species of Marine Turtles at a Foraging Area in the Northeastern Gulf of Mexico

et al. 2019

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“…Wildlife surveying has included size and abundance estimates of nesting bird colonies and seal haul-outs (Goebel et al 2015), dugong counts (Hodgson et al 2013), orangutan nest identification (Koh & Wich 2012), nesting behaviour of crocodiles (Evans et al 2015) and assessing spatial variation in abundance of reef sharks (Kiszka et al 2016). Furthermore, UAV data have been used to assess the effects that wildlife may have on their surroundings, such as changes to local landscapes post-beaver introduction (Puttock et al 2015) and crop damage by wild boar (Michez et al 2016).…”

Section: Introductionmentioning

confidence: 99%

The potential of unmanned aerial systems for sea turtle research and conservation: a review and future directions

Rees¹,

Avens²,

Ballorain³

et al. 2018

Endang. Species. Res.

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The use of satellite systems and manned aircraft surveys for remote data collection has been shown to be transformative for sea turtle conservation and research by enabling the collection of data on turtles and their habitats over larger areas than can be achieved by surveys on foot or by boat. Unmanned aerial vehicles (UAVs) or drones are increasingly being adopted to gather data, at previously unprecedented spatial and temporal resolutions in diverse geographic locations. This easily accessible, low-cost tool is improving existing research methods and enabling novel approaches in marine turtle ecology and conservation. Here we review the diverse ways in which incorporating inexpensive UAVs may reduce costs and field time while improving safety and data quality and quantity over existing methods for studies on turtle nesting, at-sea distribution and behaviour surveys, as well as expanding into new avenues such as surveillance against illegal take. Furthermore, we highlight the impact that high-quality aerial imagery captured by UAVs can have for public outreach and engagement. This technology does not come without challenges. We discuss the potential constraints of these systems within the ethical and legal frameworks which researchers must operate and the difficulties that can result with regard to storage and analysis of large amounts of imagery. We then suggest areas where technological development could further expand the utility of UAVs as data-gathering tools; for example, functioning as downloading nodes for data collected by sensors placed on turtles. Development of methods for the use of UAVs in sea turtle research will serve as case studies for use with other marine and terrestrial taxa.

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“…Foraging mostly occurs in continental waters off northern Australia, as well as in eastern Indonesia (Kai Islands to southern Papua) and southern Papua New Guinea (Hamann, Smith, & Preston, ; Limpus, ; Limpus, Parmenter, Baker, & Fleay, ; Pendoley, Schofield, Whittock, Ierodiaconou, & Hays, ; Suarez, ). Tagging studies indicate strong fidelity to nesting beaches (Limpus, ; Limpus, Fleay, & Baker, ; Pendoley et al, ), and tagging and satellite telemetry studies have indicated substantial breeding migrations of up to 1,650 km from nesting beaches (Hamann et al, ; Limpus et al, ; Pendoley, Schofield, et al, ; Thums et al, ). In the more southern extent of their nesting range, flatback turtles nest during the austral summer, whereas nesting at the northern rookeries occurs mostly during the austral winter (Limpus, ).…”

Section: Introductionmentioning

confidence: 99%

Phylogeography, genetic stocks, and conservation implications for an Australian endemic marine turtle

FitzSimmons

Pittard

McIntyre

et al. 2020

Aquatic Conservation

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Identification of the geographic extent of population boundaries, the distribution of genetic lineages, and the amount of genetic exchange among breeding groups is needed for effective conservation of vulnerable marine migratory species. This is particularly true of the flatback turtle (Natator depressus), which only breeds in Australia but has extensive migrations that can include international waters. This study investigated the phylogeography and genetic structure among 17 flatback turtle rookeries across their range by sequencing an 810 bp portion of the mitochondrial DNA in 889 samples and genotyping 10 microsatellite loci in 598 samples. There was low phylogenetic divergence among haplotypes and evidence of recent population expansion, likely in the late Pleistocene. A predominant haplotype was found across all rookeries, but other haplotype groups were regionally specific. In general, there was agreement in patterns of genetic differentiation in the mitochondrial DNA and microsatellite data, and in some pairwise comparisons a higher mutation rate of microsatellites provided stronger evidence of differentiation. These results suggest natal philopatry operates in the choice of breeding locations for males as well as females. Evidence of genetic connectivity among neighbouring rookeries led to the identification of seven genetic stocks. Geographic boundaries of rookeries used by genetic stocks varied widely (160–1,300 km), highlighting a need for field studies to better understand movement patterns. Hierarchical analysis of molecular variance identified significant genetic differentiation based upon genetic stock, nesting phenology (summer vs. winter nesters), and a west–east discontinuity across Torres Strait. A pattern of isolation by distance was identified, which was most strongly observed in the microsatellite data. In combination with tagging and telemetry studies, these results will allow better quantification of stock‐specific threats along migratory routes and in foraging habitats. Implications of climate change will be stock specific and may depend upon the extent of genetic connectivity between neighbouring stocks.

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Environmental predictors of foraging and transit behaviour in flatback turtles Natator depressus

Cited by 21 publications

References 46 publications

Habitat Use and Behavior of Multiple Species of Marine Turtles at a Foraging Area in the Northeastern Gulf of Mexico

Habitat Use and Behavior of Multiple Species of Marine Turtles at a Foraging Area in the Northeastern Gulf of Mexico

The potential of unmanned aerial systems for sea turtle research and conservation: a review and future directions

Phylogeography, genetic stocks, and conservation implications for an Australian endemic marine turtle

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