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      Leatherback Turtle Movements, Dive Behavior, and Habitat Characteristics in Ecoregions of the Northwest Atlantic Ocean

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          Abstract

          Leatherback sea turtles, Dermochelys coriacea, are highly migratory predators that feed exclusively on gelatinous zooplankton, thus playing a unique role in coastal and pelagic food webs. From 2007 to 2010, we used satellite telemetry to monitor the movements and dive behavior of nine adult and eleven subadult leatherbacks captured on the Northeast USA shelf and tracked throughout the Northwest Atlantic. Leatherback movements and environmental associations varied by oceanographic region, with slow, sinuous, area-restricted search behavior and shorter, shallower dives occurring in cool (median sea surface temperature: 18.4°C), productive (median chlorophyll a: 0.80 mg m −3), shallow (median bathymetry: 57 m) shelf habitat with strong sea surface temperature gradients (median SST gradient: 0.23°C km −1) at temperate latitudes. Leatherbacks were highly aggregated in temperate shelf and slope waters during summer, early fall, and late spring and more widely dispersed in subtropical and tropical oceanic and neritic habitat during late fall, winter and early spring. We investigated the relationship of ecoregion, satellite-derived surface chlorophyll, satellite-derived sea surface temperature, SST gradient, chlorophyll gradient and bathymetry with leatherback search behavior using generalized linear mixed-effects models. The most well supported model showed that differences in leatherback search behavior were best explained by ecoregion and regional differences in bathymetry and SST. Within the Northwest Atlantic Shelves region, leatherbacks increased path sinuosity (i.e., looping movements) with increasing SST, but this relationship reversed within the Gulf Stream region. Leatherbacks increased path sinuosity with decreasing water depth in temperate and tropical shelf habitats. This relationship is consistent with increasing epipelagic gelatinous zooplankton biomass with decreasing water depth, and bathymetry may be a key feature in identifying leatherback foraging habitat in neritic regions. High-use habitat for leatherbacks in our study occurred in coastal waters of the North American eastern seaboard and eastern Caribbean, putting turtles at heightened risk from land- and ocean-based human activity.

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          How to reliably estimate the tortuosity of an animal's path: straightness, sinuosity, or fractal dimension?

          The tortuosity of an animal's path is a key parameter in orientation and searching behaviours. The tortuosity of an oriented path is inversely related to the efficiency of the orientation mechanism involved, the best mechanism being assumed to allow the animal to reach its goal along a straight line movement. The tortuosity of a random search path controls the local searching intensity, allowing the animal to adjust its search effort to the local profitability of the environment. This paper shows that (1) the efficiency of an oriented path can be reliably estimated by a straightness index computed as the ratio between the distance from the starting point to the goal and the path length travelled to reach the goal, but such a simple index, ranging between 0 and 1, cannot be applied to random search paths; (2) the tortuosity of a random search path, ranging between straight line movement and Brownian motion, can be reliably estimated by a sinuosity index which combines the mean cosine of changes of direction with the mean step length; and (3) in the current state of the art, the fractal analysis of animals' paths, which may appear as an alternative and promising way to measure the tortuosity of a random search path as a fractal dimension ranging between 1 (straight line movement) and 2 (Brownian motion), is only liable to generate artifactual results. This paper also provides some help for distinguishing between oriented and random search paths, and depicts a general, comprehensive framework for analysing individual animals' paths in a two-dimensional space.
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            Persistent Leatherback Turtle Migrations Present Opportunities for Conservation

            Introduction Leatherback turtles (Dermochelys coriacea) in the eastern Pacific (EP) have exhibited population declines of up to 90% during the past two decades [1,2]. These declines have been driven by a number of factors, including incidental mortality in fisheries, loss of nesting habitats, and unsustainable egg harvest [1,3]. Of the extant leatherback nesting beaches in the EP, Playa Grande in Parque Nacional Marino Las Baulas (PNMB), Costa Rica, supports the largest nesting colony [1]. After the nesting period (approximately 60 d), EP leatherbacks perform long-distance migrations from breeding areas to feeding areas, where they remain for 2 to 7 y [4]. Therefore, while protection of nesting habitat is important to enhance recruitment into the population, an improved understanding of the at-sea distribution and movements of EP leatherbacks is vital to ensuring their long-term survival. In particular, long-range tracking studies using electronic tags can inform conservation efforts by identifying high-use areas for leatherbacks in time and space, as well as environmental influences on leatherback behavior [5]. Leatherback turtles globally undertake long-distance migrations over thousands of kilometers [6–14]. Morreale et al. [6] first described the movements of EP leatherbacks from the tracks of eight turtles (durations 3–87 d) and identified a persistent southbound migration corridor from PNMB toward the Galápagos Islands. Additional tagging efforts at a nesting beach in Mexiquillo, México, about 965 km north of Costa Rica, revealed that leatherbacks traveled routes that shared the same directional heading and general high seas habitats in the eastern South Pacific as those traveled by Costa Rican turtles [7]. In contrast, leatherbacks from other populations demonstrate inter-individual behavioral variation with respect to post-nesting migration routes [8–10,13,14]. The apparent persistence of the EP leatherback migration pattern provides a unique opportunity to generate a cohesive conservation management approach for this endangered population. Conservation of highly migratory marine species requires international cooperation for implementation of transboundary management strategies. Specifically, information on movements and distributions of large marine predators collected by electronic tracking devices can provide guidance to the development of national and multinational fisheries management strategies and bycatch mitigation efforts, as well as support related policy efforts [15]. One such framework is the Eastern Tropical Pacific Seascape (ETPS) initiative [16], which is a multinational coordination of marine resource management within the combined exclusive economic zones of Costa Rica, Panama, Colombia, and Ecuador. The ETPS is an area that is home to several marine protected areas (MPAs) (e.g., PNMB) and World Heritage sites (e.g., Cocos Island, Coiba Island National Park, Malpelo Island, Galápagos Islands and Marine Reserve). Thus, the ETPS represents a framework through which habitat use and movement data for migratory animals, such as leatherbacks, can be translated into tangible management actions. Here we present the largest multi-year tracking data set collected for this species, based on 46 individuals satellite-tagged during 2004–2007 at PNMB. Our approach is consistent with a recent review [17], which emphasized the importance of tracking large sample sizes and an interdisciplinary approach integrating oceanographic cues with behavior. These data enabled us to (1) describe the distribution and horizontal movements of leatherbacks in the EP, (2) examine the influence of oceanic currents on leatherback migrations, (3) assess leatherback high-use habitats, (4) confirm and elucidate a leatherback migration corridor from the nesting beach to 5 °S, and (5) describe leatherback movements beyond 10 °S into the South Pacific. In addition, these data identify critical areas for directed conservation efforts to ensure the survival of this species in the EP. Results We tagged 46 female leatherback turtles during oviposition, resulting in 12,095 tracking days spanning 21 January 2004–5 July 2007, with a mean track duration of 263 d, a distance of 8,070 km, and a travel speed of 37.7 km d−1 (Table 1). Movements by cohorts from a given year displayed cohesion, even though initiation of the post-nesting migration among individuals differed by up to several weeks (Figure 1). Only one individual tagged in 2005 (tag ID 56280) remained in coastal waters off Costa Rica and Panama for the entire tag duration (Figure 1A). Table 1 Tracking Data from 46 Satellite-Linked Tags Deployed on Leatherback Turtles on Playa Grande, Costa Rica, 2004–-2007 Figure 1 Map and Timeline of Leatherback Sea Turtle Tracking Data (A) Satellite transmission positions for 46 leatherback turtles from 2004 (n = 27, orange), 2005 (n = 8, purple), and 2007 (n = 11, green), tagged at Playa Grande, Costa Rica, overlaid on bathymetry (in m). Prominent bathymetric features and island groups are labeled (EPR = East Pacific Rise). (B) Timeline of satellite transmissions for each tag (tag ID is the ARGOS-assigned transmitter number). Upon completion of nesting activity, leatherbacks embarked on rapid (42.9 km d−1, standard deviation (sd) = 27.7 km d−1) directed southward migrations through the equatorial region. Once south of 5 °S, the turtles dispersed throughout the South Pacific Gyre following slower (23.8 km d−1, sd = 16 km d−1), meandering paths, and remained there through the duration of the tracking period (Figure 2A–2C). Across their migrations, turtles experienced a wide range of surface temperatures (11.2–32.7 °C, mean = 25.2 °C, sd = 3.2 °C; Table 1). They encountered areas of high–eddy kinetic energy (EKE) in the equatorial region (>100 cm2s−2), and areas of very low EKE ( 0.3 mg m−3), and lowest in the South Pacific Gyre ( + ). These calculations were performed separately for the February–April period of each tracking year, since the emphasis was on assessing the impact of inter-annual variability in geostrophic current strength on turtle migration while crossing the equatorial region. On the other hand, we computed EKE as a long-term mean for the period 14 October 1992–18 April 2007 from the mean geostrophic velocity anomalies (u′ and v′), as EKE = 0.5*( + ). In this case, the emphasis was on examining turtle distribution in relation to a region of low mesoscale variability in the South Pacific Gyre. Phytoplankton CHL concentration. The distribution of phytoplankton standing stock is a useful indicator of biogeography and ecosystem structure [24]. Near-surface CHL concentration, a proxy for phytoplankton standing stock, was obtained from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean-color observations at 9-km resolution. We computed a long-term mean for the period September 1997–March 2007 for comparison of turtle movements in relation to phytoplanktonic biomass distribution throughout their range. Individual 8-d averages were also obtained for each turtle median daily position. The relationship between CHL and the turtles' median daily speed was investigated using linear regression, after log- and square-root-transformation, respectively, to meet normality assumptions. Digital bathymetry. We extracted bathymetry from the global sea-floor topography of Smith and Sandwell [52], version 8.2 (November 2000) (http://topex.ucsd.edu/WWW_html/mar_topo.html). This dataset combines all available depth soundings with high-resolution marine gravity information provided by the Geosat, ERS-1/2, and TOPEX/Poseidon satellite altimeters, and has a nominal resolution of 2 arc min (∼4 km). The 2000-m isobath was extracted from this dataset to obtain the outline of the Cocos Ridge, the most prominent bathymetric feature in the migration corridor region (12 °N–5 °S) running northeast (∼43° azimuth) for ∼1,200 km between Galápagos and Central America. Geomagnetism. Data on Earth's magnetic field (force and inclination) in the study area were calculated using the software GeoMag 6.0, available from the NOAA National Geophysical Data Center (http://www.ngdc.noaa.gov/seg/geom_util/geomutil.shtml), and the most recent (2005) International Geomagnetic Reference Field 10th generation (IGRF-10) coefficients. Supporting Information Figure S1 Surface Currents and Vertical Thermal Structure in the Eastern Tropical and South Pacific Schematic representation of near-surface currents and vertical thermal structure in the eastern tropical and South Pacific, based on climatological annual data. (A) Current vectors (black) overlaid on current magnitude (colors; in cm s−1). Dashed black line denotes subsurface flow; dashed white line indicates a section along 95 °W. (B) Surface zonal (black arrows) and meridional (orange arrows) velocities (in cm s−1) along 95 °W. (C) Water-column temperature (colors; in °C) and the 15, 20, and 25 °C isotherms (black contours) along 95 °W. Zonal currents are represented as encircled x's for westward flows and encircled dots for eastward flows. Abbreviations are defined in the text. (2.57 MB TIF) Click here for additional data file. Text S1 Currents and Thermal Structure of the Eastern Tropical and South Pacific (29 KB DOC) Click here for additional data file.
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              At-sea distribution and scale-dependent foraging behaviour of petrels and albatrosses: a comparative study.

              1. In order to study and predict population distribution, it is crucial to identify and understand factors affecting individual movement decisions at different scales. Movements of foraging animals should be adjusted to the hierarchical spatial distribution of resources in the environment and this scale-dependent response to environmental heterogeneity should differ according to the forager's characteristics and exploited habitats. 2. Using First-Passage Time analysis, we studied scales of search effort and habitat used by individuals of seven sympatric Indian Ocean Procellariiform species fitted with satellite transmitters. We characterized their search effort distribution and examined whether species differ in scale-dependent adjustments of their movements according to the marine environment exploited. 3. All species and almost all individuals (91% of 122 individuals) exhibited an Area-Restricted Search (ARS) during foraging. At a regional scale (1000s km), foraging ranges showed a large spatial overlap between species. At a smaller scale (100s km, at which an increase in search effort occurred), a segregation in environmental characteristics of ARS zones (where search effort is high) was found between species. 4. Spatial scales at which individuals increased their search effort differed between species and also between exploited habitats, indicating a similar movement adjustment for predators foraging in the same habitat. ARS zones of the two populations of wandering albatross Diomedea exulans (Crozet and Kerguelen) were similar in their adjustments (i.e. same ARS scale) as well as in their environmental characteristics. These two populations showed a weak spatial overlap in their foraging distribution, with males foraging in more southerly waters than females in both populations. 5. This study demonstrates that predators of several species adjust their foraging behaviour to the heterogeneous environment and these scale-dependent movement adjustments depend on both forager and environment characteristics.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                19 March 2014
                : 9
                : 3
                : e91726
                Affiliations
                [1 ]Department of Biological Sciences, University of New Hampshire, Durham, New Hampshire, United States of America
                [2 ]Large Pelagics Research Center, University of Massachusetts Amherst, Gloucester, Massachusetts, United States of America
                [3 ]National Marine Fisheries Service, Northeast Fisheries Science Center, Woods Hole, Massachusetts, United States of America
                Institut Pluridisciplinaire Hubert Curien, France
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: KD ML. Performed the experiments: KD. Analyzed the data: KD BG TM. Wrote the paper: KD BG TM ML.

                Article
                PONE-D-13-38979
                10.1371/journal.pone.0091726
                3960146
                24646920
                5aa26501-0632-46c1-adfa-e5a3eb8a8c43
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 September 2013
                : 14 February 2014
                Page count
                Pages: 17
                Funding
                KD was supported by a University of New Hampshire Marine Program Fellowship administered by the Large Pelagics Research Center. This study was funded by a National Oceanic and Atmospheric Administration Grant #NA04NMF4550391 ( www.noaa.gov) and National Fish and Wildlife Foundation Grant #2008-0076-000 ( www.nfwf.org) to ML. Additional funding was provided by the Cape Cod Commercial Fishermen's Alliance ( www.capecodfishermen.org). Turtle disentanglement was supported by the Massachusetts Division of Marine Fisheries through National Oceanic and Atmospheric Administration Grant #NA07NMF4720052. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Ecology
                Behavioral Ecology
                Coastal Ecology
                Marine Ecology
                Spatial and Landscape Ecology
                Marine Biology
                Marine Conservation
                Zoology
                Animal Behavior
                Reptile Biology
                Earth sciences
                Geophysics
                Physical Oceanography
                Marine and aquatic sciences
                Aquatic Environments
                Marine Environments
                Bodies of water
                Oceans
                Atlantic Ocean
                Oceanography
                Biological Oceanography
                Ecology and Environmental Sciences
                Conservation Science

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