Water mass characteristics and solar illumination influence leatherback turtle dive patterns at high latitudes

Hamelin, Kayla M.; Kelley, Dan; Taggart, Christopher T.; James, Michael C.

doi:10.1890/es13-00158.1

Cited by 10 publications

(19 citation statements)

References 44 publications

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“…Leatherbacks most frequently capture prey within the bottom 2 m of dives (41% of all captures) and during ascents (37% of captures), probably silhouetting prey against the illuminated ocean surface (Figure 10). This is consistent with our third hypothesis as well as previous inferences (Hamelin et al, 2014). The relatively shallow distribution of leatherback prey allows leatherbacks to avoid deep, prolonged foraging dives, thereby minimizing time transiting to and from depths at which prey are principally concentrated.…”

Section: Discussionsupporting

confidence: 93%

“…Our results also corroborate recent findings that green turtles (Chelonia mydas) modulate surface durations and number of breaths per surface interval during several consecutive foraging dive cycles to maintain aerobic activity (Okuyama et al, 2014). This pattern of shallow, frequent dives provides further empirical support for the notion that leatherback prey distributions in shelf waters off Nova Scotia appear to be physically structured by local water mass conditions-i.e., at or above the main thermocline (Hamelin et al, 2014)-and that prey are not primarily concentrated at the surface (only 4% of prey captures; Table 3, Figure 10), unlike what has been reported in some other leatherback foraging areas (Houghton et al, 2006). Leatherbacks most frequently capture prey within the bottom 2 m of dives (41% of all captures) and during ascents (37% of captures), probably silhouetting prey against the illuminated ocean surface (Figure 10).…”

Section: Discussionmentioning

confidence: 87%

“…Such analyses are rare for marine migratory species in general (e.g., Seminoff et al, 2006;Moll et al, 2007). Leatherback dives are shorter and shallower while foraging off Nova Scotia than during migration or while in lower latitudes, and feeding is restricted to daylight hours (James et al, 2005a;Casey et al, 2014;Hamelin et al, 2014). Hamelin et al (2014) used high-resolution dive data from three leatherbacks to show that turtles foraging in Atlantic Canada remain at or above the main thermocline, suggesting that prey resource distribution is associated with water mass.…”

Section: Ecology and Evolutionmentioning

confidence: 99%

“…Leatherback dives are shorter and shallower while foraging off Nova Scotia than during migration or while in lower latitudes, and feeding is restricted to daylight hours (James et al, 2005a;Casey et al, 2014;Hamelin et al, 2014). Hamelin et al (2014) used high-resolution dive data from three leatherbacks to show that turtles foraging in Atlantic Canada remain at or above the main thermocline, suggesting that prey resource distribution is associated with water mass. In addition, Heaslip et al (2012) used turtle-borne video to estimate rates of prey biomass ingestion and energy intake for leatherbacks foraging off Nova Scotia.…”

Section: Ecology and Evolutionmentioning

confidence: 99%

“…Third, leatherbacks capture prey at depth, apparently where prey is physically structured at or near the thermocline (Hamelin et al, 2014), indicating that many captures might occur at or near the bottoms of dives. However, leatherbacks are also frequently observed handling prey at the surface (James and Herman, 2001;Heaslip et al, 2012), suggesting that leatherbacks also capture prey on ascent, possibly targeting the prey silhouetted against the water surface backed by lighter sky.…”

Section: Hypothesesmentioning

confidence: 99%

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Fine-scale foraging ecology of leatherback turtles

Wallace

Zolkewitz²,

James

2015

Front. Ecol. Evol.

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Remote tracking of migratory species and statistical modeling of behaviors have enabled identification of areas that are of high ecological value to these widely distributed taxa. However, direct observations at fine spatio-temporal scales are often needed to correctly interpret behaviors. In this study, we combined GPS-derived locations and archival dive records (1 s sampling rate) with animal-borne video footage from foraging leatherback turtles (Dermochelys coriacea) off Nova Scotia, Canada (Northwest Atlantic Ocean) to generate the most highly-detailed description of natural leatherback behavior presented to date. Turtles traveled shorter distances at slower rates and increased diving rates in areas of high prey abundance, which resulted in higher prey capture rates. Increased foraging effort (e.g., dive rate, dive duration, prey handling time, number of bites) was not associated with increased time at the surface breathing to replenish oxygen stores. Instead, leatherbacks generally performed short, shallow dives in the photic zone to or above the thermocline, where they disproportionately captured prey at bottoms of dives and during ascents. This foraging strategy supports visual prey detection, allows leatherbacks to exploit physically structured prey at relatively shallow depths (typically <30 m), and increases time turtles spend in warmer water temperatures, thus optimizing net energy acquisition. Our results demonstrate that leatherbacks appear to be continuously foraging during daylight hours while in continental shelf waters off Nova Scotia, and that leatherback foraging behavior is driven by prey availability, not by whether or not a turtle is in a resource patch characterized by a particular size or particular prey density. Our study demonstrates the fundamental importance of obtaining field-based, direct observations of true behaviors at fine spatial and temporal scales to enhance our efforts to both study and manage migratory species.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 87%

Section: Ecology and Evolutionmentioning

confidence: 99%

Section: Ecology and Evolutionmentioning

confidence: 99%

Section: Hypothesesmentioning

confidence: 99%

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Fine-scale foraging ecology of leatherback turtles

Wallace

Zolkewitz²,

James

2015

Front. Ecol. Evol.

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Incidental capture of leatherback sea turtles in fixed fishing gear off Atlantic Canada

Hamelin¹,

James

Ledwell³

et al. 2017

Aquatic Conservation

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1. Incidental capture in commercial fishing gear is a threat to many populations of marine megafauna, including sea turtles. While research has largely focused on pelagic longline impacts on sea turtles, fixed-gear fisheries are a significant, historically understudied source of injury and mortality.2. The present study assesses the interaction of endangered leatherback sea turtles (Dermochelys coriacea) with fixed-gear fisheries in high-latitude seasonal foraging habitat where sub-adult and adult turtles aggregate.3. Records of leatherback-fishery interactions (n = 205) were compiled from databases of publicly-reported sea turtle sightings in Atlantic Canada (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) to identify the spatiotemporal distribution of these events; to identify corresponding fisheries and gear types; and to describe the mechanics and outcomes of entanglements in fixed gear. 4. Most reports came from coastal Nova Scotia (n = 136) and Newfoundland (n = 40), with reporting rates peaking in the mid-to-late 2000s. The majority of entanglements were reported during the summer months of July and August when leatherbacks are seasonally resident and several fisheries are active in continental shelf waters.5. Entanglements were most commonly reported in pot gear (e.g. snow crab, lobster, whelk) and trap nets (e.g. mackerel), reflecting extensive use of polypropylene lines distributed in the upper water column where leatherback foraging activity is concentrated. 6. Given reporting biases and uncertainty regarding post-release survivorship, entanglement mortalities should be considered a gross underestimate of true mortality rates.7. This study highlights both the importance of looking beyond pelagic longlines to evaluate leatherback interactions with fixed-gear fisheries in high-use continental shelf foraging habitat, and of involving the fishing industry in developing mitigation measures to reduce entanglement rates and associated turtle mortality.

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Clustering and classification of vertical movement profiles for ecological inference of behavior

et al. 2023

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Vertical movements can expose individuals to rapid changes in physical and trophic environments—for aquatic fauna, dive profiles from biotelemetry data can be used to quantify and categorize vertical movements. Inferences on classes of vertical movement profiles typically rely on subjective summaries of parameters or statistical clustering techniques that utilize Euclidean matching of vertical movement profiles with vertical observation points. These approaches are prone to subjectivity, error, and bias. We used machine learning approaches on a large dataset of vertical time series (N = 28,217 dives) for 31 post‐nesting leatherback turtles (Dermochelys coriacea). We applied dynamic time warp (DTW) clustering to group vertical movement (dive) time series by their metrics (depth and duration) into an optimal number of clusters. We then identified environmental covariates associated with each cluster using a generalized additive mixed‐effects model (GAMM). A convolutional neural network (CNN) model, trained on standard dive shape types from the literature, was used to classify dives within each DTW cluster by their shape. Two clusters were identified with the DTW approach—these varied in their spatial and temporal distributions, with dependence on environmental covariates, sea surface temperature, bathymetry, sea surface height anomaly, and time‐lagged surface chlorophyll a concentrations. CNN classification accuracy of the five standard dive profiles was 95%. Subsequent analyses revealed that the two clusters differed in their composition of standard dive shapes, with each cluster dominated by shapes indicative of distinct behaviors (pelagic foraging and exploration, respectively). The use of these two machine learning approaches allowed for discrete behaviors to be identified from vertical time series data, first by clustering vertical movements by their movement metrics (DTW) and second by classifying dive profiles within each cluster by their shapes (CNN). Statistical inference for the identified clusters found distinct relationships with environmental covariates, supporting hypotheses of vertical niche switching and vertically structured foraging behavior. This approach could be similarly applied to the time series of other animals utilizing the vertical dimension in their movements, including aerial, arboreal, and other aquatic species, to efficiently identify different movement behaviors and inform habitat models.

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Water mass characteristics and solar illumination influence leatherback turtle dive patterns at high latitudes

Cited by 10 publications

References 44 publications

Fine-scale foraging ecology of leatherback turtles

Fine-scale foraging ecology of leatherback turtles

Incidental capture of leatherback sea turtles in fixed fishing gear off Atlantic Canada

Clustering and classification of vertical movement profiles for ecological inference of behavior

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