DOI: 10.5061/dryad.d7wm37qdf
title: Data and code for: Pelagic sharks target long-lived, retentive anticyclonic eddies in the Northwest Atlantic Ocean

description: Open ocean ecosystems represent the largest habitat on Earth and are
 highly dynamic in time and space. Mesoscale eddies are a primary driver of
 this variability and serve a key structural role in ocean ecosystems.
 Eddies modulate marine biodiversity beyond their impacts on plankton,
 influencing many ecologically and commercially important predators that
 may preferentially occupy anticyclonic eddies. However, how animal-eddy
 interactions scale across predator species and the mechanistic drivers of
 these relationships remain an area of active research. We integrated
 satellite tracking data for sharks with observations of mesoscale eddies
 to determine how four shark species interact with eddies in the Gulf
 Stream region. Based on over 24,000 tracking days, we found that blue,
 white, and shortfin mako sharks selected for the cores of anticyclones
 while use of eddies by tiger sharks was less conspicuous. Some
 particularly large and long-lived anticyclones were occupied by tagged
 sharks for multiple weeks suggesting that these eddies may serve as
 hotspots for pelagic predators.
description: Methods of data collection/generation:
 Satellite tagging and shark movements We
 analyzed data from 108 deployments of satellite-linked electronic tags on
 four species of sharks in the North Atlantic: white shark (Carcharodon
 carcharias, n=10); tiger shark (Galeocerdo cuvier, n=21); shortfin mako
 (Isurus oxyrinchus, n=48); and blue shark (Prionace glauca, n=29). These
 tags provide relatively accurate (generally &lt;10 km error; Douglas
 et al. 2012) satellite-based positions when the tagged individual comes to
 the surface, but do not provide any information on vertical habitat use.
 Resulting locations were processed with a Kalman filtering algorithm by
 Collecte Localisation Satellites (Lopez et al., 2014) and subsequently
 assigned error flags called location classes (LC): LC 3, &lt;250 m; LC
 2, 250-500 m; LC 1, 500-1500 m; LC 0, &gt;1500 m for classes 3, 2, 1,
 0. Additional classes A, B represent positions derived from less than four
 satellite messages which result in no estimates of spatial accuracy from
 CLS; however, recent work on several marine species and platforms suggests
 error for A, B classes is order 1-10 km and nearly always &lt; 20 km
 (Lopez et al., 2014). Location class Z positions were considered invalid
 and removed from further analysis. Each individual’s tracking data was
 filtered using a speed filter (10 ms−1) to remove unrealistic locations
 and was divided into trajectories that allowed for data gaps of up to two
 days and required at least 20 locations per trajectory. These criteria
 were chosen to minimize interpolation in the modeling approach used to
 standardize the location data. The resulting filtered, individual
 trajectories were fitted in a continuous-time state-space modeling
 framework (foieGras package for R; Jonsen et al. 2020) to remove spurious
 locations and provide standardized, quality-controlled individual
 trajectories at 6-h time steps following previous work that indicates
 daily transmission rates of ∼1-4 positions per day for these species
 (Wiernicki et al., 2022). Resulting standardized trajectories were used to
 collocate shark movements to the mesoscale eddy field in the Gulf Stream
 study region, defined here to encompass 35-45ºN and 80-40ºW in the North
 Atlantic. Eddy diameters in the study area range from tens to hundreds of
 kilometers, therefore positional error inherent in the shark trajectories
 is relatively modest. Null eddy use was quantified by
 using 20 correlated random-walk simulations per tagged shark. Individual
 simulated trajectories were constructed as a correlated-random walk that
 randomly draws from the observed turn angles and step lengths in the
 observed shark movement trajectories to generate simulated movement
 trajectories (adehabitatLT package for R; Calenge 2006). The use of
 observed trajectories to parameterize the simulations ensures realistic
 movements but with the hypothesized ecological mechanism, in this case
 eddy use, removed (Gotelli and Graves, 1996). Previous studies have used
 similar simulations to generate null models for habitat selection (e.g.,
 Richard et al. 2013; Queiroz et al. 2016). To match the spatial bias in
 presence data, simulations were initiated at the tagging location for each
 individual and were constrained to realistic movements using bathymetry.
 Simulated tracks for each individual represent random eddy use based on
 the chance of encountering these features. Eddy
 tracking Eddies identified and tracked in daily maps of
 sea surface height were acquired from the Mesoscale Eddy Trajectory Atlas
 distributed by Aviso that describes daily tracks of coherent (i.e.,
 retentive) mesoscale structures (eddies) based on maps of surface
 altimetry (Mason et al., 2014; Pegliasco et al., 2022). Eddies with
 lifetimes greater than four weeks are tracked daily based on their
 signatures in sea level anomaly (SLA) fields, and the Atlas includes both
 the latitude/longitude center and speed-based radius (R) of each feature
 throughout its lifetime, where R is the radius of a circle with an area
 equal to that enclosed by the streamline of the maximum circum-average
 geostrophic speed of the eddy (equivalent to eddy length scale Ls in
 Chelton et al. 2011). This radial eddy-centric distance is used to define
 the zones of an eddy relative to its center, assuming eddies are
 isotropic, where a normalized distance of zero is the eddy center,
 distances &lt;1 indicate the core (i.e., interior) of the eddy,
 &gt;1 and &lt;2 indicate the periphery of the eddy, and &gt;2
 indicate waters outside the physical impact of the eddy (Gaube et al.,
 2017a). A custom meander filter was used to distinguish Gulf Stream
 meanders from the eddies of interest using net-zonal displacement (Gaube
 et al., 2017b; Braun et al., 2019). We extracted
 polarity (cyclone or anticyclone), age (days), radius (R), average
 rotating speed at the contour of maximum circum-average speed of the eddy
 (hereafter, "speed"), and amplitude (i.e., the deviation in SLA
 from the surrounding waters) from the metrics reported in the eddy atlas
 (for further details, see https://doi.org/10.24400/527896/a01-2022.005) for each eddy matching real and simulated shark movement trajectories. We complemented this information by calculating eddy retention (d’Ovidio et al., 2013) and non-linearity (Chelton et al., 2011) metrics. Retention is a semi-Lagrangian metric that represents how long water parcels have been circulating within the core of an eddy (defined as area of negative Okubo-Weiss parameter, Okubo 1970; Weiss 1991). In this study, we used calculations of eddy retention carried out for the North Atlantic Aerosols and Ecosystems Study (Della Penna and Gaube, 2019) that relied on the altimetry-derived geostrophic currents distributed by the Copernicus Marine Environment Monitoring Service (CMEMS, http://marine.copernicus.eu). The non-linearity of an eddy was used to characterize the ability of these features to advect a trapped fluid parcel as it translates (Chelton et al., 2011). This is commonly represented as the nondimensional ratio U/c, where U is the maximum rotational speed (as described above) and c is the translation speed of the eddy estimated at each point along the eddy trajectory from centered differences of the (x, y) coordinates of successive centroid locations. Values of U/c &gt; 1 imply that there is trapped fluid within the eddy interior that is advected with the eddy as the eddy translates. See manuscript for complete details and associated references.
description: # Data for Pelagic sharks target long-lived, retentive anticyclonic eddies
 in the Northwest Atlantic Ocean --- # Reference Information ## Provenance
 for this README * Authors: Camrin D. Braun * Other contributors: see
 manuscript citation below for all contributing authors * Date created:
 2025-08-16 * Date modified: 2025-08-16 ## Dataset Version and Release
 History * Current Version: * Number: 1.0.0 * Date: 2025-08-16 * Persistent
 identifier: 10.5061/dryad.d7wm37qdf * Summary of changes: n/a * Embargo
 Provenance: n/a * Scope of embargo: n/a * Embargo period: n/a ## Dataset
 Attribution and Usage * Dataset Title: Data for "Pelagic sharks
 target long-lived, retentive anticyclonic eddies in the Northwest Atlantic
 Ocean" * Persistent Identifier: 10.5061/dryad.d7wm37qdf * Dataset
 Contributors: * Creators: Camrin D. Braun * Date of Issue: 2024-08-16 *
 Publisher: Woods Hole Oceanographic Institution * License: Use of these
 data is covered by the MIT access license * Title: CC0 1.0 Universal (CC0
 1.0) * Specification:
 [https://creativecommons.org/publicdomain/zero/1.0/](https://creativecommons.org/publicdomain/zero/1.0/); the authors respectfully request to be contacted by researchers interested in the re-use of these data so that the possibility of collaboration can be discussed. * Suggested Citations: * Dataset citation: Braun, Camrin; Gaube, Peter; Della Penna, Alice et al. (2025). Data and code for: Pelagic sharks target long-lived, retentive anticyclonic eddies in the Northwest Atlantic Ocean [Dataset]. Dryad. https://doi.org/10.5061/dryad.d7wm37qdf * Corresponding publication: \&gt; to be added &gt; ## Contact Information * Name: Camrin D. Braun * Affiliations: Biology Department, Woods Hole Oceanographic Institution * ORCID ID: [https://orcid.org/0000-0002-9317-9489](https://orcid.org/0000-0002-9317-9489) * Email: [cbraun@whoi.edu](mailto:cbraun@whoi.edu) --- # Data and File Overview This repository contains the data and code for Braun et al. Pelagic sharks target long-lived, retentive anticyclonic eddies in the Northwest Atlantic Ocean published in Limnology & Oceanography. It includes the derived shark-eddy collocation data presented in the manuscript. ## Description of the data and file structure * observed_tracks_predicted6hr.csv This is the observed shark tracking data as output from the state-space model (to standardize the raw, temporally irregular data) after collocation with the Mesoscale Eddy Atlas from AVISO (see Methods). * simulated_tracks_predicted6hr.csv This is the simulated shark tracking data as output from the trajectory simulations and subsequently collocated with the Mesoscale Eddy Atlas from AVISO (see Methods). * collocate_eddies.txt This is the R function used to collocate shark tracking data (observed or simulated) to the eddy atlas. * hdbk_eddytrajectory_META3.2_DT-2.pdf (Supplemental Info on Zenodo) This is the Mesoscale Eddy Trajectory Atlas Product Handbook for the META3.2 Delayed Time eddy product (available here: [https://doi.org/10.24400/527896/a01-2022.005](https://doi.org/10.24400/527896/a01-2022.005)). This is included to describe the eddy* variable columns as indicated in the data, see below. --- # Data File Details ## Details for: observed_tracks_predicted6hr.csv * Description: a comma-delimited file containing the summary of observed shark tracks collocated to the eddy atlas. For full detail on the variables listed below, including source, resolution and other details, please see the manuscript. * Format(s): .csv * Size(s): 3.38 MB * Dimensions: 11,238 rows by 30 columns * Variables: * lon: longitude coordinates in degrees east * lat: latitude coordinates in degrees north * bathy: bathymetry at this location, extracted from the eTOPO dataset * minDist: distance from this shark location and the center coordinate of the nearest eddy, in km * eddy_index: identification number of the closest eddy (from above) used to identify the unique eddy in the eddy atlas * dx: eddy-centric (normalized) distance of the shark location relative to the eddy center along the x axis. Values normalized and unit-less, see Methods. * dy: eddy-centric (normalized) distance of the shark location relative to the eddy center along the y axis. Values normalized and unit-less, see Methods. * etype: eddy polarity where -1 refers to anticyclonic and 1 refers to cyclonic * tbin: eddy-centric histogram bin associated with this shark location * region: a geographic label associated with the study region, all data occurs in the 'gulfstream' region * posexit: a metric representing eddy retention, or how long a water parcel has been recirculating within the core of an eddy. See Della Penna and Gaube 2019. * eddy*: all variables that start with "eddy_" refer to values associated with individual eddies in the Mesoscale Eddy Atlas from AVISO. See details in the manuscript and refer to the Mesoscale Eddy Trajectory Atlas Product Handbook for the META3.2 Delayed Time product, included here and also available at [https://doi.org/10.24400/527896/a01-2022.005](https://doi.org/10.24400/527896/a01-2022.005) * Missing data codes: Missing values in column "posexit" indicates eddies for which the eddy retention metric were not available. See publication for additional details. ## Details for: simulated_tracks_predicted6hr.csv * Description: a comma-delimited file containing the summary of simulated shark tracks collocated to the eddy atlas. For full detail on the variables listed below, including source, resolution and other details, please see the manuscript. * Format(s): .csv * Size(s): 72.65 MB * Dimensions: 241,567 rows by 30 columns * Variables are same as observed_tracks_predicted6hr.csv above. --- # Additional Dataset Metadata ## Acknowledgements We thank D. McGillicuddy for helpful discussion of the ideas presented here, and L. Gallagher (Fishpics® & IMAR-DOP, University of the Azores) for creating the species art. This work was supported by the NASA New Investigator Program (Award #80NSSSC20K1132 to PG and CDB), the Robert L. James Early Career Scientist Fund at the Woods Hole Oceanographic Institution (to CDB), the WHOI President’s Innovation Fund (MCA), the New Zealand Royal Society Catalyst program (to ADP, CDB and MCA; contract #CSG-UOA2302), and Fundação para a Ciência e a Tecnologia (PTDC/BMA/3536/2021 to NQ). PG was supported by NASA SWOT Science Team Award #80NSSC20K1132 during the writing of the manuscript. We are incredibly grateful for the fishers, captains, crews and tagging teams who made this project possible. The altimetric Mesoscale Eddy Trajectories Atlas (META3.2 DT) was produced by SSALTO/DUACS and distributed by AVISO+ ([https://aviso.altimetry.fr](https://aviso.altimetry.fr) ) with support from CNES, in collaboration with IMEDEA. The authors declare no conflicts of interest. --- #