Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Peer-reviewed

Research Article

Movement patterns and habitat use of tiger sharks (Galeocerdo cuvier) across ontogeny in the Gulf of Mexico

  • Matthew J. Ajemian ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

    majemian@fau.edu

    Affiliation Harbor Branch Oceanographic Institute, Florida Atlantic University, Fort Pierce, Florida, United States of America

    ⨯
  • J. Marcus Drymon,

    Roles Conceptualization, Data curation, Investigation, Writing – original draft, Writing – review & editing

    Affiliations Coastal Research and Extension Center, Mississippi State University, Biloxi, Mississippi, United States of America, Mississippi-Alabama Sea Grant, Ocean Springs, Mississippi, United States of America

    ⨯
  • Neil Hammerschlag,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliations Rosenstiel School of Marine & Atmospheric Science, University of Miami, Causeway, Miami, Florida, United States of America, Abess Center for Ecosystem Science & Policy, University of Miami, Miami, Florida, United States of America

    ⨯
  • R. J. David Wells,

    Roles Conceptualization, Data curation, Funding acquisition, Investigation, Writing – review & editing

    Affiliations Department of Marine Biology, Texas A&M University at Galveston, Galveston, Texas, United States of America, Department of Wildlife & Fisheries Sciences, Texas A&M University, College Station, Texas, United States of America

    ⨯
  • Garrett Street,

    Roles Data curation, Formal analysis, Writing – review & editing

    Affiliations Quantitative Ecology & Spatial Technologies Laboratory, Mississippi State University, Starkville, Mississippi State, United States of America, Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Starkville, Mississippi State, United States of America

    ⨯
  • Brett Falterman,

    Roles Data curation, Funding acquisition, Writing – review & editing

    Affiliation Louisiana Department of Wildlife and Fisheries, New Orleans, Louisiana, United States of America

    ⨯
  • Jennifer A. McKinney,

    Roles Investigation, Methodology, Writing – review & editing

    Affiliation Louisiana Department of Wildlife and Fisheries, New Orleans, Louisiana, United States of America

    ⨯
  • William B. Driggers III,

    Roles Formal analysis, Investigation, Writing – review & editing

    Affiliation NOAA Fisheries, Southeast Fisheries Science Center, Mississippi Laboratories, Pascagoula, Mississippi, United States of America

    ⨯
  • Eric R. Hoffmayer,

    Roles Formal analysis, Investigation, Writing – review & editing

    Affiliation NOAA Fisheries, Southeast Fisheries Science Center, Mississippi Laboratories, Pascagoula, Mississippi, United States of America

    ⨯
  • Christopher Fischer,

    Roles Data curation, Funding acquisition, Methodology, Resources, Writing – review & editing

    Affiliation OCEARCH, Park City, Utah, United States of America

    ⨯
  • Gregory W. Stunz

    Roles Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing

    Affiliation Harte Research Institute for Gulf of Mexico Studies, Texas A&M University-Corpus Christi, Corpus Christi, Texas, United States of America

    ⨯

Abstract

The tiger shark (Galeocerdo cuvier) is globally distributed with established coastal and open-ocean movement patterns in many portions of its range. While all life stages of tiger sharks are known to occur in the Gulf of Mexico (GoM), variability in habitat use and movement patterns over ontogeny have never been quantified in this large marine ecosystem. To address this data gap we fitted 56 tiger sharks with Smart Position and Temperature transmitting tags between 2010 and 2018 and examined seasonal and spatial distribution patterns across the GoM. Additionally, we analyzed overlap of core habitats (i.e., 50% kernel density estimates) among individuals relative to large benthic features (oil and gas platforms, natural banks, bathymetric breaks). Our analyses revealed significant ontogenetic and seasonal differences in distribution patterns as well as across-shelf (i.e., regional) and sex-linked variability in movement rates. Presumably sub-adult and adult sharks achieved significantly higher movement rates and used off-shelf deeper habitats at greater proportions than juvenile sharks, particularly during the fall and winter seasons. Further, female maximum rate of movement was higher than males when accounting for size. Additionally, we found evidence of core regions encompassing the National Oceanographic and Atmospheric Administration designated Habitat Areas of Particular Concern (i.e., shelf-edge banks) during cooler months, particularly by females, as well as 2,504 oil and gas platforms. These data provide a baseline for future assessments of environmental impacts, such as climate variability or oil spills, on tiger shark movements and distribution in the region. Future research may benefit from combining alternative tracking tools, such as acoustic telemetry and genetic approaches, which can facilitate long-term assessment of the species’ movement dynamics and better elucidate the ecological significance of the core habitats identified here.

Citation: Ajemian MJ, Drymon JM, Hammerschlag N, Wells RJD, Street G, Falterman B, et al. (2020) Movement patterns and habitat use of tiger sharks (Galeocerdo cuvier) across ontogeny in the Gulf of Mexico. PLoS ONE 15(7): e0234868. https://doi.org/10.1371/journal.pone.0234868

Editor: Heather M. Patterson, Department of Agriculture, Water and the Environment, AUSTRALIA

Received: January 20, 2020; Accepted: June 3, 2020; Published: July 15, 2020

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: The underlying data is publicly available at DataONE (https://doi.org/10.24431/rw1k44e). Users can also access this project interactively through the IOOS ATN portal: https://portal.atn.ioos.us/?ls=bd5a0806-2762-8766-fb63-e0c319c12c33#metadata/fb73a274-3bdd-4315-ac5a-105d450e4058/project.

Funding: This research was funded by grants from the Texas State Aquarium to GWS and MJA and the Aquarium at Moody Gardens to RJDW.

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

Introduction

Understanding movement patterns and dynamic habitat use for widely ranging species is a significant challenge in the marine environment. This is especially true for highly migratory sharks, which often traverse regional, national, and international boundaries, thus encountering a broad range of environmental and anthropogenic stressors [1,2,3,4]. Alarmingly, more than one-fourth of highly migratory sharks are characterized by the International Union for the Conservation of Nature as Critically Endangered, Endangered or Vulnerable [5]. Clearly, a thorough understanding of highly migratory shark movement patterns and habitat preferences is urgently needed for developing comprehensive management and conservation strategies [6–8].

Despite the highly mobile nature of many sharks, these animals have been shown to exhibit extended residence within certain oceanographic features characterized by high productivity [8]. These habitats can be dynamic and include meso-scale eddies [9,10] and ocean-estuarine interfaces [11], while others can be fixed and more structurally complex, such as reefs, ridges, seamounts and banks [12–14]. However, the remoteness and ephemeral nature of some of these features often requires sophisticated tools to reveal individual use patterns by free-ranging sharks. Fortunately, satellite telemetry has emerged as a powerful tool that has increased our ability to assess habitat preferences and movement patterns for highly mobile species, including sharks [15]. Continued increases in battery life, coupled with decreases in the size and cost of transmitters, have resulted in a more complete understanding of dynamic habitat use for otherwise elusive species [16]. In fact, recent collaborative efforts have provided estimates of space use for several species of sharks spanning much of the globe [8]. Despite these advances, gaps remain in our understanding of the spatial dynamics of many highly mobile sharks, including variability across ontogeny and over their ranges.

The tiger shark (Galeocerdo cuvier) is a globally distributed, highly mobile species with established coastal and open-ocean movement patterns that have been revealed via satellite telemetry [17]. Previous studies have noted variable patterns of space use in tiger sharks, ranging from resident to highly migratory behavior [17]. The majority of this work occurred around the Hawaiian Islands in the eastern central Pacific Ocean where tiger sharks typically display site fidelity to core islands but also move between islands for foraging purposes [18–21]. Similar patterns have been observed off the Galápagos Islands, where tiger sharks can have highly resident behavior within the marine reserve but often traverse deep waters outside the reserve and visit areas off continental South America [22]. In the western North Atlantic Ocean, adult tiger sharks tagged near Bermuda show considerable basin-wide connectivity, integrating multiple ecosystems (temperate to tropical); however, these findings were almost exclusively based on male sharks [4]. Similarly, tiger sharks (predominately female) tagged off south Florida and the northern Bahamas appear to exhibit associations with the Gulf Stream, presumably due to the high productivity, and thus food availability, in this current system [23,24]. By combining tracks from mostly adult female tiger sharks tagged in Florida and the Bahamas with remotely sensed environmental data, Calich et al. [25] predicted large areas of suitable habitat off the southeast United States, including the Gulf of Mexico (GoM). However, actual use of the predicted suitable habitat by tiger sharks remains unknown as does the importance of these habitats for males and juveniles.

The GoM is a highly productive marginal sea, home to a diverse community of coastal sharks [11,26,27], including tiger sharks [28]. To date, satellite telemetry has been used to describe the movement patterns and habitat preferences of multiple GoM shark species including scalloped hammerhead (Sphyrna lewini) [29,30], dusky sharks (Carcharhinus obscurus) [31] shortfin makos (Isurus oxyrinchus) [32], and whale sharks (Rhincodon typus) [33,34]. While all life stages of tiger shark are known to occur in the GoM [11,25,28], detailed habitat use has never been quantified. This is striking as the GoM faces numerous anthropogenic stressors [35–37], complex tri-national management [38,39], and indications of size reductions in recreational landings for large sharks [40,41]. Additionally, the potential for ontogenetic and sex-specific habitat partitioning by tiger sharks remains unknown in these waters. Although the species does not use discrete nurseries for parturition in the GoM, it has been suggested that the nearshore waters of the region are important for neonates [28,42] and by extension, could also serve a critical role for gravid females. A recent study demonstrated the capacity of tiger sharks to traverse tri-national boundaries within the GoM, particularly during the winter [39]. However, the former study did not include: 1) an assessment of sex-based differences in distribution patterns, 2) quantification of movement rates, and 3) potential interactions with large-scale habitat features, all of which have been identified as information-deficient areas in need of additional research [17]. Therefore, the goals of this study were to address these aforementioned knowledge gaps for tiger sharks in the GoM.

Methods

Ethics statement

This study was carried out in strict accordance with the Animal Welfare Act and other Federal statutes and regulations relating to animals. The protocol was approved by the Institutional Animal Care and Use Committee at Texas A&M University-Corpus Christi (Animal Use Protocol: #08-18) and permitted under a Letter of Acknowledgement (SHK-LOA-14-08) from the National Marine Fisheries Service, Highly Migratory Species Division. All efforts were made to minimize animal suffering during collection and tagging procedures.

Animal collection and tagging

Tiger sharks (n = 56; 32 ♀, 24 ♂) were captured and tagged throughout the northern GoM from 2010 to 2018, spanning shelf waters from south Texas to south Florida (Table 1). Sharks were collected using bottom longline (BL, n = 32), drum-line (DL, n = 17), and hook-and-line (HL, n = 7) gears. The BL and DL captured individuals were retrieved from the water and secured to a platform along either the stern or gunwale of the vessel. The HL-caught sharks remained submerged following capture and secured alongside the vessel with the leader and a tail rope. Body length measurements included pre-caudal length (PCL, cm), fork length (FL, cm) and stretched total length (STL, cm). In those cases when only STL was recorded, FL was estimated using the equation derived from our capture data: (1)

The sex of each individual was determined and maturity state was assigned for males via established methods such as physical examination of clasper rotation and calcification [43]. Following Branstetter et al. [44], in cases where maturity could not be assessed, sharks were considered mature at 265 and 258 cm FL for females and males, respectively. A conventional mark-recapture tag was attached on the trunk of each individual at the base of the first dorsal fin and a Smart Position and Temperature (SPOT) transmitting tag (Wildlife Computers, Inc.) secured behind the anterior margin of the first dorsal fin.

thumbnail
Download:
Table 1. Collection information and tag performance of individuals tagged in study.

https://doi.org/10.1371/journal.pone.0234868.t001

Data processing and analyses

Animal position estimates were downloaded from Argos satellites (CLS America, Inc.). For analyses, we included all position estimates of class B or higher (A, 0, 1, 2, and 3) and excluded Z class transmissions [45]. The following metrics were calculated for each individual: 1) days at liberty (days from release to last transmission), 2) number of locations, and 3) transmit days (number of days with at least a single position). Linear regressions were performed on these metrics to assess the potential effect of shark size on the length of the transmission period. A correlated random walk state-space model was used to regularize daily positions using the FoieGras package (https://github.com/ianjonsen/foieGras) in R (R Core Team, Vienna, Austria) [46]. This model also provided estimates of east-west and north-south velocity, from which a resultant overall velocity metric, or rate of movement (ROM), was computed using the Pythagorean Theorem. For instances where intervals between consecutive position estimates exceeded 4 days, daily positions were not interpolated. Only data from individuals with at least 10 transmit days were included in statistical analyses (n = 38).

Underlying bottom depths were extracted in ArcMap from regularized position estimates using the ETOPO1 bathymetry raster data sets [47]. To facilitate general spatial and ontogenetic analyses of habitat use, FoieGras-based positions were assigned one of three underlying depth categories: 1) shelf (0 – 200 m), 2) slope (200 – 1000 m), and abyssal (>1000 m). Additionally, individual shark sizes were placed into three size bins to conceptualize distribution patterns by life stage: 1) small (<200 cm FL; n = 18), 2) medium (200 – 250 cm FL; n = 15), and 3) large (>250 cm FL; n = 5), reflecting immature, transitional, and mature sizes, respectively.

We used General Linear Models (GLMs) to examine the potential effects of the factors sex, season (winter, spring, summer, and fall), and region (shelf, slope, abyssal) on two response variables: 1) maximum ROM and 2) maximum underlying depth used by sharks. The GLMs for maximum ROM included separate two-way analyses of sex and season and sex and region. A three-way analysis (sex, season, and region) was not possible due to insufficient numbers of individuals (replicates) of a given sex during certain seasons or regions. The GLM for maximum underlying depth included a single two-way analysis of the factors sex and season; region was not used as a factor in this model since underlying depth was used to define region (see above). All GLMs used FL as a covariate in the model to control for effects of shark size. In cases where significant effects of factors were found, post-hoc comparisons were run using Tukey’s pairwise comparisons. Where necessary, both ROM and depth data were square-root transformed prior to analyses in order to meet assumptions of parametric statistics. All GLMs were run using Minitab 19.1.1 (Minitab LLC) with an α value of 0.05.

The regularized daily position estimates were used to build 50% and 95% kernel density estimates (KDEs) for each individual in R using the adehabitatHR package with the “href” bandwidth estimator. The resulting KDEs were plotted in ArcMap 10.3 (ESRI, Inc.) to identify overall distribution patterns as well as core areas of use. We used a general linear model to assess potential sex- and size-based differences in 50% and 95% KDEs, using transmission days and FL as covariates. Data were checked prior to analysis for normality (Shapiro-Wilk) and homogeneity of variances (Levene’s Test). Following Graham et al. [2], we considered the 50% KDE as core habitat use areas. Therefore, interactions between shark core habitat use areas and underlying habitat features (e.g. bathymetry, oil and gas structures, natural banks) was explored by examining the overlap of 50% KDEs with features of interest in ArcMap. Overlapping polygons were joined into a single feature class, with centroids (points) used to define the number of individual overlaps via the join tool. This polygon data set was then converted to a raster to facilitate extraction of values from underlying habitat features.

Results

Shark size distribution

The relationship between FL and STL was strongly linear (R2 = 0.95) and was used to estimate FL for individuals with missing data (n = 5). Shark size ranges were similar between males and females (Fig 1), with females ranging from 102–335 cm FL (mean ± s.d. = 200 cm ± 54 cm FL) and males ranging from 107–266 cm FL (mean ± s.d. = 198 ± 44 cm FL). Mean FL was not statistically different between sexes (two-sample t-test, t = -0.155, d.f. = 54, P = 0.877). Only five individuals were presumably mature at the time of tagging, which included three females (Shark-10, Shark-26, and Shark-56) and two males (Shark-42, Shark-46); as such, most of the individuals tagged were likely immature or sub-adult.

thumbnail
Download:
Fig 1. Frequency histogram of tiger shark sizes (fork length, FL) tagged in this study.

Data are presented in 50 cm size bins. Sexes are represented by color (blue = male, pink = female). Vertical dotted line represents size-at-maturity break.

https://doi.org/10.1371/journal.pone.0234868.g001

Days at liberty and transmission days

Days at liberty varied among individuals, ranging from 6 to 695 d (mean = 107.1 ± 125.1 d). Two individuals (both females) were tracked greater than 12 months: Shark-25 (233 cm FL at tagging; 695 d) and Shark-43 (250 cm FL at tagging; 415 d), both released off the Texas coastal bend region. The three next longest tracking durations all came from females (204−298 cm FL at tagging). Given these results, we ran linear regressions on days at liberty and transmit days using FL as a continuous predictor and sex as a categorical predictor. Regression analyses indicated a significantly positive impact of fork length on transmission days (F1,51 = 17.82; P < 0.0001; R2 = 0.28), and days at liberty (F1,51 = 8.22; P = 0.006; R2 = 0.10); however, this effect was independent of sex (P > 0.05). The scatterplot of these relationships suggested that they were driven by substantially higher transmit days and liberty for the medium to large size classes (i.e., > 200 cm FL; Fig 2).

thumbnail
Download:
Fig 2. Scatterplot of track duration by shark size.

Data are presented by transmit days (left axis, blue dots) and days at liberty (right axis, orange dots) by fork length (FL, cm). Linear regressions and r-squared values are indicated by dashed lines.

https://doi.org/10.1371/journal.pone.0234868.g002

Movement patterns and distribution by size, sex, and season

Regularized daily position estimates (n = 5,513) were obtained for 52 of the 56 tagged sharks and were somewhat evenly distributed across small (n = 2,022), medium (n = 1,680), and large (n = 1,811) size classes. Tracks generated from these positions were variable; many were tightly coupled to the continental shelf edge, while others extended across the GoM basin (Fig 3A). In general, tracks across the basin appeared more directed, and became more circuitous as they approached the continental slope and shelf. Cross-basin movements were most apparent in late-fall through early winter (Fig 3B). All three size categories of sharks (small, medium, and large) occurred in waters overlying shelf, slope, and abyssal habitats. There was evidence of intermediate size classes of both sexes over the interior of the GoM, beyond the U.S. Exclusive Economic Zone in Mexican and Cuban waters; however, there appeared to be a general ontogenetic transition from inshore to offshore waters with size (Fig 3C). Male and female distributions overlapped throughout the GoM, with a dominance of mature individuals along the shelf-edge and slope habitats, and immature sharks along the nearshore region (Fig 3D).

thumbnail
Download:
Fig 3. Maps of tiger shark tracks and distribution.

A: Tag release locations (white stars) and individual tracks (colored lines) of tiger sharks fitted with SPOT transmitters from 2010 to 2018. Tracks are based on daily position estimates from the down-sampled data set. Inset map with red box delineates the Gulf of Mexico Large Marine Ecosystem. B: Tracks and positions displayed by month (color) to document seasonality of positions. C: Position estimates plotted by shark size (at time of tagging) category, small (100-200 cm FL, blue), medium (201-250 cm FL, yellow), and large (251-400 cm FL; red), and D: Position estimates based on maturity (squares = immature; triangles = mature) and sex (blue = males, pink = females).

https://doi.org/10.1371/journal.pone.0234868.g003

The relative proportional use of waters overlying the three habitat categories was variable by both time of year and size class (Fig 4). Small sharks (<200 cm FL; n=18) were detected from 0-335 km offshore (mean = 73.4 ± 65.2 km) and primarily found in shelf habitats throughout the year (91% of positions; Fig 4A). These smaller individuals were positioned nearshore along the Florida coast, particularly during the summer months (Fig 3C). That said, there was some evidence of slope water use from April to June, and again from September to November (7% of positions; Fig 4A). Relatively few positions were estimated from small sharks over abyssal waters in October and November (2% of total positions), and all came from a single individual. No small sharks transmitted in February. Medium-sized sharks (200-250 cm FL; n=15) had a similar distribution of positions (mean = 87.0 ± 72.1 km) as the smaller sharks, with most coming from shelf waters (77% of positions); however, there was a higher proportion of positions over slope waters (9% of positions) and abyssal waters (14% of positions). Medium-sized sharks were primarily positioned along shelf waters from May to August, and increased occupancy over deeper slope and abyssal waters through December. A transition from these waters overlying deep habitats to slope waters was evident in early winter to spring. Large individuals (>250 cm FL; n=6) ranged from 0-413 km offshore (mean = 113.2 ± 72.9 km) and had the least number of positions over shelf waters (59%) among size classes, and highest number of positions over slope waters (31%). Shelf habitats were primarily used by large sharks between May and September, after which a stark transition to slope and abyssal waters (10%) was evident for the majority of individuals, primarily from October through April.

thumbnail
Download:
Fig 4. Relative distribution of positions by month for three size classes of tiger sharks across three regions.

Data are pooled across individuals presented as 100% stacked bars per month, with colors representing different regions: continental shelf (white bars), continental slope (gray bars), and abyssal plain (black bars).

https://doi.org/10.1371/journal.pone.0234868.g004

Rates of movement and depth use statistics

Regression analysis of maximum ROM by fork length showed a weak but significant positive linear relationship (F1,38 = 4.7; P = 0.036; R2 = 0.11). We therefore incorporated size into subsequent analyses that involved ROM. General linear models run on maximum ROM revealed a significant effect of the covariate size (F1,69 = 5.13; P = 0.027), but not season (F3,69 = 0.20; P = 0.897), sex (F1,69 = 3.24; P = 0.077), or the interaction of the two factors (F3,69 = 1.01; P = 0.395; Table 2). Analysis of square-root transformed maximum ROM found significant effects of region (F2,59 = 3.74; P = 0.030) and sex (F1,59 = 5.35; P = 0.025), but not for the interaction between the two factors (F1,59 = 1.80; P = 0.175) or the size covariate (F1,59 = 2.30; P = 0.135; Table 2). Pairwise comparisons showed that maximum ROM was significantly higher in waters above abyssal depths (average = 139.1 ± 37.8 km·d-1; compared to shelf waters (average = 61.7 ± 8.4 km·d-1;), but not slope waters (average = 94.5 ± 13.2 km·d-1; Fig 5). Furthermore, female max ROM (average = 98.7 ± 14.8 km·d-1) was significantly higher than males (average = 63.6 ± 8.8 km·d-1).

thumbnail
Download:
Fig 5. Vertical bar chart of average maximum rate rate of movement by region.

Data are presented across continental zones in the GoM. Error bars represent standard errors of the mean and letters designate statistically significant groups as revealed by Tukey’s pairwise comparisons. Regions that share at least one letter are not significantly different from one another (i.e,. P > 0.05), whereas those that do not share a letter are statistically distinct (i.e., P < 0.05).

https://doi.org/10.1371/journal.pone.0234868.g005

thumbnail
Download:
Table 2. General linear model results on square-root transformed maximum rate of movement.

https://doi.org/10.1371/journal.pone.0234868.t002

Average maximum underlying depth was significantly influenced by size (F1,69 = 6.98; P = 0.010) and season (F3,69 = 3.09; P = 0.034), but not sex (F1.69= 0.04; P = 0.022), or the interaction between sex and season (F3,69 = 0.26; P = 0.853; Table 3, Fig 6). Pairwise comparisons revealed that mean underlying depths during fall (mean = 1240 ± 372 m) were significantly greater than both spring (mean = 446 ± 136 m) and summer (mean = 363 ± 162 m), but not winter (mean = 1071 ± 346 m).

thumbnail
Download:
Fig 6. Vertical bar chart of average maximum underlying bottom depths by season.

Mean values are individual averages. Error bars represent standard errors of the mean and letters designate statistically significant groups as revealed by Tukey’s pairwise comparisons. Seasons that share at least one letter are not significantly different from one another (i.e,. P > 0.05), whereas those that do not share a letter are statistically distinct (i.e., P < 0.05).

https://doi.org/10.1371/journal.pone.0234868.g006

thumbnail
Download:
Table 3. General linear model results on maximum underlying depth used by sharks.

https://doi.org/10.1371/journal.pone.0234868.t003

Kernel density estimates and core use areas

Average size of female 50% (39.9 ± 18.2 km2) and 95% (202.3 ± 86.5 km2) KDEs were, on average, twice that of males (18.7 ± 8.65 km2 and 91.5 ± 43.6 km2). However, statistical analyses showed that KDEs were strongly influenced by the transmission days covariate (F1,37 = 13.72; P = 0.001) and not the predictors sex (F1,37 = 0.01; P = 0.926) or fork length (F1,37 = 1.14; P = 0.293). Polygon overlap analysis of 50% KDEs revealed two distinct regions of intensive use (i.e., join polygon counts >5; Fig 7A). The first occurred along the shelf-edge region between Louisiana and Texas, the core of which (>7 individuals; Fig 7B) encompassed major hardbottom habitats of the Flower Garden Banks National Marine Sanctuary (FGBNMS) (West and East Flower Garden Banks) and Coffee Lump. Additionally, considerably high overlap was observed above several additional banks and Habitat Areas of Particular Concern designated by the National Oceanographic and Atmospheric Administration such as Stetson Bank (also part of FGBNMS), Appelbaum Bank, Claypile Bank, MacNeil Bank, 29 Fathom Bank, Rankin Bank, 28 Fathom Bank, and Geyer Bank. The core area had a largely east-west distribution, similar to the continental shelf edge contour (i.e., 200 m isobath) of the region.

thumbnail
Download:
Fig 7. Map of core habitat use areas of tiger sharks in the GoM.

Imagery represents results from 50% KDE overlap analysis relative to other features in the GoM. Overview map (A) shows KDE overlap relative to bathymetry (black lines) and large habitat features such as oil and gas platforms (black dots), National Oceanographic and Atmospheric Administration designated Habitat Areas of Particular Concern (white boxes) and benthic hardbottom (brown polygons). Yellow dashed boxes denote shelf-edge “hot-spot” areas off Texas-Louisiana (B), including the Flower Garden Banks National Marine Sanctuary (FGBNMS; red borders) and adjacent banks, as well as Pinnacles region off the Mississippi-Alabama shelf (C).

https://doi.org/10.1371/journal.pone.0234868.g007

A second area with considerable overlap of 50% KDEs was the Pinnacles region off the edge of the Mississippi-Alabama shelf (Fig 7C). It is worth noting that this region was also adjacent to an area of significant tagging efforts (>10 individuals). While these hardbottom habitats did not intersect with the same join count as in the western GoM, many were apparently used by >5 individuals. This core region had a northeast to southwest distribution, similar to the continental shelf edge contour (i.e., 200 m isobath) of the region.

The various 50% KDEs also overlapped with 2,504 oil and gas platforms ranging from Texas to Alabama. Of this total, 1,756 were from the Louisiana-Texas shelf (western region) and 748 were from the Mississippi-Alabama shelf (eastern region). The majority of platform join counts (77% west, 22% east) intersected with single individual KDEs. However, there were approximately 32 platforms in the western region (1.8%) and 3 (0.4%) from the east that were situated in some of the highest use areas, with join counts as high as 7.

Discussion

Our findings provide the first insights into the movements and habitat use of tiger sharks across life-stages within an important, yet understudied, portion of their range. Previous investigations into tiger shark horizontal movements in the western North Atlantic Ocean have been restricted primarily to males [4] or females [23] separately, in disparate locations. By simultaneously tracking many males and females of varying life stages within the same region, we observed sex and size-specific differences in distribution and movement rates, as well as associations with large-scale habitat features. While we encountered limitations due to sample size (i.e., comparatively few adult sharks tagged), these data help address knowledge gaps identified for this species [17], as well as provide baseline information to support future studies in the GoM region.

Spatiotemporal patterns in movement and distribution

Our work documented both ontogenetic and seasonal patterns in tiger shark distribution in the GoM that are consistent with observations from other subtropical systems [48]. Individuals transition from primarily shelf-based lifestyles when <200 cm FL, to increased use of continental slope and deepwater habitats by intermediate sizes, and the highest use of slope habitats by the largest individuals. Additionally, the duration of these transitions appears to be related to ontogeny. Of the few small sharks that left the shelf, most only did so periodically over a few months in spring and summer. Medium-sized sharks that left the shelf initiated this behavior beginning in August, and gradually moved offshore from September through December, after which they slowly returned to shelf waters from February through April. Large adults, on the other hand, made rapid, pronounced offshore migrations in October, with most remaining off the shelf until April. These inshore-offshore patterns in seasonality are consistent with nearshore landings from recreational fishers off the Texas coast, who report the highest occurrence of large tiger sharks in summer followed by a disappearance in fall [40]. Additionally, the cross-basin movements within the GoM appear somewhat consistent with findings from mark-recapture tagging [49], although we found no evidence of GoM departure from the two individuals tracked beyond a year, suggesting a portion of sharks are resident in this large marine ecosystem.

The increased offshore habitat use and rapidity of inshore-offshore transitions observed with ontogeny is likely facilitated by the ability of large individuals to achieve higher rates of movement, as reported elsewhere [4]. This may be due to changes in caudal fin morphology with size, which increases in symmetricity and likely improves long-distance swimming performance [50]. These changes in distribution coincide with life-stage specific resource needs, such as food maximization in juveniles or reproductive opportunities as adults. For example, since they are rapidly growing and require access to consistent food resources early in life, young tiger sharks may benefit from living principally on the GoM shelf where primary productivity and prey densities are considerably higher than deeper depths and/or more consistently encountered [51,52].

Conversely, larger juvenile and adult sharks may venture more frequently off-shelf to partake in seasonal migrations or to access unique and ephemeral food resources that may arise in open-ocean habitats such as sea turtles [4]. Although the northwestern GoM shelf is generally characterized by a persistent western boundary current, simulations from climatological data indicate that several regions along the shelf edge become seasonally conducive to cross-shelf exchange [53]. Periodically, this may help animals from the shelf access deeper water environments. These slope habitats were most frequented by large adult sharks, and may be indicative of orientation with seasonally variable currents in the region [54] in order to find conspecifics for mating, or areas of dense prey. Regardless, the increased use of offshore waters as adults is consistent with other regions. For example, dietary and stable isotope analyses on samples of tiger sharks captured off South Africa demonstrated the increased reliance of this species on offshore waters with increasing size, coinciding with a more pelagic and variable diet [55]. Off eastern Australia, males are apparently absent from nearshore shark catches at the onset of maturity, which has been associated with a transition to deeper offshore waters at this life stage [17]. As such, these offshore excursions may represent preparatory movements for more of an off-shelf lifestyle typical of adults [19].

While tiger sharks are well known for their low at-vessel mortality [56–59], extraordinarily high fecundity [60], and rapid growth rates [61], the wide-ranging distribution of this species can be challenging to fisheries management. For example, our findings add to those of Rooker et al. [39] by identifying that individuals using the high-seas territory outside of the U.S. Exclusive Economic Zone were immature. Juvenile presence means that individuals may be exploited in this unregulated region prior to reproducing, which could have population-level consequences for the species despite its resilience to capture stress and its reproductive potential.

Large-scale habitat features

Despite strong characterization of bony fish assemblages along the northwestern GoM shelf-edge banks [62,63] and the FGBNMS [64], there have been limited studies on sharks in this region. The discovery of high overlap in tiger shark core ranges along two shelf-edge systems in the GoM highlights the potential influence of these features on the species’ distribution as recently demonstrated for scalloped hammerhead sharks [30]. The only study to document use of shelf-edge banks by tiger sharks in the GoM was conducted by Childs [65], who compiled visual observations from divers and boaters around the FGBNMS and adjacent area. Childs [65] reported the species as present between December and March, with sightings that were either females or an unconfirmed sex across a range of sizes (100–400 cm, total length, TL, which would be approximately 74–335 cm FL). Our results support these previous findings as four of five individuals detected within the boundaries of the sanctuary were females (102–233 cm FL) and observed during the months of January (n=1), March (n=2), April (n=2), May (n=1), September (n=1), and December (n=2). The only male to be detected within the FGBNMS boundaries was mature, and detected in December. Female presence at the FGBNMS, and at times in groups as large as 5 individuals [65], could be indicative of an aggregation site [66] of mixed life stages as has been recently demonstrated for Tiger Beach, Bahamas [67]. A similar function has been suggested for Sackett Bank, a similar habitat in the GoM region known support aggregations of female dusky shark [31]. Childs’ [65] observations of female sharks in the 300-400 cm TL (i.e., 249–335 cm FL) suggests that mature individuals also use the FGBNMS, which overlaps with one of the two putative tiger shark pupping regions along the GoM shelf proposed by Driggers et al. [28], one of which (93−95°W) is located inshore of the FGBNMS. These findings may also explain the higher rates of movement observed in females compared to males, which may exhibit fidelity to these sites and require rapid seasonal migrations to return to them. Together, these findings suggest shelf-edge banks of the northwestern GoM are used by female tiger sharks during cooler months of the year; however, additional tagging of males is needed as only 3 were tagged (compared to 9 females) in the region. Despite these limitations, the data herein suggest shelf-edge habitats may be related to reproduction (i.e., female aggregation sites) for multiple large shark species in the GoM.

Oil and gas platforms were also in the core habitat of tiger sharks in this study. These structures, which span the offshore region from Texas to Alabama, comprise one of the largest unintended artificial reef complexes in the world [68] that are well-known for their capacity to support exceptionally high fish densities [69], and are indeed used by multiple shark species [70]. There are considerable fishery activities associated with production platforms, including recreational hook-and-line (bottom fishing, surface trolling) and commercial vertical longline for a suite of target snapper-grouper species [71]. Tiger shark associations with these structures are not yet well understood, although two individuals tagged in this study (Shark-24 and 25) were collected within a few hundred meters of a production platform, and a recent study confirmed this species interacts with the base of these structures along the continental slope [72]. Such affinities may expose tiger sharks to blowouts similar to Deepwater Horizon, which impacted surface and bottom waters of the north-central GoM region where we documented significant core habitat use [73]. Uptake and trophic transfer of petroleum-based pollutants, which accumulate in sharks [74,75] and are at significantly higher levels in sediments adjacent to platforms [76], needs further research in order to clarify the potential impacts of these anthropogenic activities on tiger shark health and biology.

Long-term and integrative sampling approaches may help further reveal the extent of tiger shark associations with both natural and artificial habitats. Such data can reveal the importance of these habitats over multiple years, and how residency within these systems changes with sex and size class. We suggest future studies incorporate technologies such as acoustic telemetry, which does not require animals to bear large external transmitters or to surface, and has already been applied to tiger sharks elsewhere [25,77,78]. Such data would also provide a glimpse into inter-bank and platform connectivity, site fidelity, and the role of tiger sharks in transporting nutrients across these various sites (i.e., allochthonous inputs). Additionally, given the relatively high water clarity of the FGBNMS and other banks in the region, an integrated baited remote underwater video approach may also help reveal association patterns and size structure of tiger sharks from these habitats, as done recently in the Galápagos Marine Reserve [79].

Study limitations and recommendations

Our tagging efforts uncovered some potential limitations in the application of satellite telemetry to tiger sharks, particularly with respect to shark size. That is, we found that tags affixed to multiple individual sharks <200 cm FL did not transmit. Additionally, of those that transmitted, none were tracked beyond 60 days. While post-release mortality is possible, this is unlikely given that previous research has revealed that tiger sharks are relatively robust to capture stress, exhibiting high at-vessel and post-release survival in experimental studies [56–58].

One explanation for transmission failure could be the relatively smaller sized and thin first dorsal fin of young tiger sharks, and thus reduced potential for the fin to stay erect when above water due to the gravitational pull on the tag. Males and females grow at rapid rates (20-40 cm·yr-1) until they reach 200–250 cm FL [80]. How these changes in growth rate translate to first dorsal fin shape has not yet been quantified, although some morphological differences are likely between adults and juveniles [50]. These higher growth rates may also encapsulate the SPOT transmitter within animal tissue, preventing wet-dry sensors from operating normally, or alternatively may eject the transmitter as a foreign body [81,82].

A more likely explanation for lower transmission rates at smaller sizes is behavioral, namely that smaller animals simply spend less time at the surface than larger individuals. Younger individuals in the GoM are reported to forage disproportionately on benthic gastropods [83], whereas adults, which are known to spend the majority of their time at depths <5 m [48,84], more commonly consume sea turtles and fishes [83]. Additionally, smaller individual tiger sharks are likely more susceptible to predation from larger sharks and as such may avoid these areas at younger life stages to improve survival. Regardless, given the expansion of coastal acoustic tracking arrays along the continental shelf, acoustic telemetry approaches may be a preferred way to track migrations and habitat use of younger tiger sharks in the GoM.

The only sharks to surpass one year of tracking duration were programmed with a maximum rate of 70 transmissions per day, whereas all other tags were programmed with the default rate of 250 transmissions per day. As such, battery exhaustion may have played a role in the overall longevity of the tags. The SPOT tags from these two individuals were also coated in black antifouling paint (Interlux, inc.). Although it has not been demonstrated experimentally, biofouling purportedly decreases transmission rates and potentially track durations [85]. Indeed, Shark-45 (141 cm FL) was fitted with a SPOT in May 2016, yet never transmitted position estimates. This individual was captured by a collaborator in December 2016, 67 km from the release site. Although this tag was coated in clear antifoulant, after being at large for seven months all sensors on the tag were severely biofouled (Fig 8). While the general lack of transmissions for this individual is also likely behavioral as mentioned above, highly biofouled tags have been reported previously for the species [86], and highlight technical limitations to be considered when using transmitters in productive coastal environments like portions of the GoM. Unfortunately, we are unable to isolate the source of variation for tag performance due to lack of replication and a variety of confounding factors (tagging location, antifoulant, transmission cycles, animal size). Further research into ways to increase the longevity of these transmitters is thus warranted, and could benefit from balanced and replicated experimental designs.

thumbnail
Download:
Fig 8. Photographs of a recaptured shark and transmitter.

Photographs indicate biofouling on Wildlife Computers SPOT 258-A from Shark-45 after 7 months at liberty. Photos show an overview of the tag and relative placement on the dorsal fin (A), and a closeup of the wet-dry sensors and other internal components (B).

https://doi.org/10.1371/journal.pone.0234868.g008

Conclusions

The present study examined ontogenetic and sex-related movement and distribution patterns of tiger sharks within the GoM. These data provide a baseline for comparison against, and/or predicting their vulnerability to, future environmental change, such as climate variability or oil spills. Future research can benefit from combining alternative tracking approaches that facilitate long-term assessment of the species’ ecological dynamics, particularly for the vulnerable young life stages. Further, additional tracking efforts are needed for adults, which were highly underrepresented in this data set and thus limit inferences on mating and parturition grounds. The revelation of core habitat use areas encompassing National Oceanographic and Atmospheric Administration designated Habitat Areas of Particular Concern, where anthropogenic activities are restricted, as well as highly modified environments such as artificial reefs and heavily exploited nearshore habitats, demonstrates the complex across-shelf habitat connectivity exhibited by tiger sharks and potentially other large mobile predators in this highly dynamic system.

Acknowledgments

We would like to thank the various volunteers and field support staff who made our tagging efforts possible, in particular members of the Center for Sportfish Science and Conservation (C. Downey, Q. Hall, R. Brewton, K. Gibson, T. Topping, and J. Curtis), the M/V OCEARCH (B. McBride) and the crew of NOAA Ship Oregon II. Additional logistical support was provided by the Harte Research Institute for Gulf of Mexico Studies, the Harte Research Institute Foundation, the Harbor Branch Oceanographic Institute Foundation, and the University of Miami Shark Research and Conservation Program.

References

  1. 1. Dunn DC, Crespo GO, Halpin PN. Incorporating the dynamic and connected nature of the open ocean into governance of marine biodiversity beyond national jurisdiction. In: Predicting Future Oceans. Elsevier; 2019. pp. 425–35.
    • 2. Graham F, Rynne P, Estevanez M, Luo J, Ault JS, Hammerschlag N. Use of marine protected areas and exclusive economic zones in the subtropical western North Atlantic Ocean by large highly mobile sharks. Diversity and Distributions. 2016 May;22(5):534–46.
    • 3. Daly R, Smale MJ, Singh S, Anders D, Shivji M, K. Daly CA, et al. Refuges and risks: Evaluating the benefits of an expanded MPA network for mobile apex predators. Diversity and Distributions. 2018 Sep;24(9):1217–30.
    • 4. Lea JSE, Wetherbee BM, Queiroz N, Burnie N, Aming C, Sousa LL, et al. Repeated, long-distance migrations by a philopatric predator targeting highly contrasting ecosystems. Sci Rep [Internet]. 2015;5(January):11202. Available from: http://www.nature.com/doifinder/10.1038/srep11202 pmid:26057337
    • 5. Lascelles B, Notarbartolo Di Sciara G, Agardy T, Cuttelod A, Eckert S, Glowka L, et al. Migratory marine species: their status, threats and conservation management needs. Aquatic Conservation: Marine and Freshwater Ecosystems. 2014 Nov;24(S2):111–27.
    • 6. Heupel MR, Simpfendorfer CA, Espinoza M, Smoothey AF, Tobin A, Peddemors V. Conservation challenges of sharks with continental scale migrations. Front Mar Sci [Internet]. 2015 Feb 24 [cited 2020 Jan 20];2. Available from: http://journal.frontiersin.org/Article/10.3389/fmars.2015.00012/abstract
    • 7. Hays GC, Bailey H, Bograd SJ, Bowen WD, Campagna C, Carmichael RH, et al. Translating Marine Animal Tracking Data into Conservation Policy and Management. Vol. 34, Trends in Ecology and Evolution. Elsevier Ltd; 2019. p. 459–73. https://doi.org/10.1016/j.tree.2019.01.009 pmid:30879872
      • 8. Queiroz N, Humphries NE, Mucientes G, Hammerschlag N, Lima FP, Scales KL, et al. Ocean-wide tracking of pelagic sharks reveals extent of overlap with longline fishing hotspots. Proc Natl Acad Sci U S A. 2016 Feb 9;113(6):1582–7. pmid:26811467
      • 9. Gaube P, Braun CD, Lawson GL, McGillicuddy DJ, Penna A Della, Skomal GB, et al. Mesoscale eddies influence the movements of mature female white sharks in the Gulf Stream and Sargasso Sea. Sci Rep. 2018; 8(1):1−8. pmid:29311619
      • 10. Carlisle A, Litvin S, Hazen E, Madigan D, Goldman K, Lea R, et al. Reconstructing habitat use by juvenile salmon sharks links upwelling to strandings in the California Current. Mar Ecol Prog Ser [Internet]. 2015 Apr 9 [cited 2019 Jun 16];525:217–28. Available from: http://www.int-res.com/abstracts/meps/v525/p217-228/
      • 11. Drymon JM, Powers SP, Dindo J, Dzwonkowski B, Henwood TA. Distributions of sharks across a continental shelf in the northern Gulf of Mexico. Mar Coast Fish Dyn Manag Ecosyst Sci [Internet]. 2010;2(1):440–50. Available from: http://www.scopus.com/inward/record.url?eid=2-s2.0-84863853183&partnerID=tZOtx3y1
      • 12. Hearn A, Ketchum J, Klimley AP, Espinoza E, Peñaherrera C. Hotspots within hotspots? Hammerhead shark movements around Wolf Island, Galapagos Marine Reserve. Mar Biol. 2010;157(9):1899–915. pmid:24391250
      • 13. Barnett A, Abrantes KG, Seymour J, Fitzpatrick R. Residency and spatial use by reef sharks of an isolated seamount and its implications for conservation. PLoS One. 2012;7(5):e36574. pmid:22615782
      • 14. Klimley AP, Le Boeuf BJ, Cantara KM, Richert JE, Davis SF, Van Sommeran S, et al. The hunting strategy of white sharks (Carcharodon carcharias) near a seal colony. Mar Biol. 2001;138(3):617–36.
      • 15. Hammerschlag N, Gallagher AJ, Lazarre DM. A review of shark satellite tagging studies. Journal of Experimental Marine Biology and Ecology. 2011 Feb 28;398(1-2):1–8.
      • 16. Hussey NE, Kessel ST, Aarestrup K, Cooke SJ, Cowley PD, Fisk AT, et al. Aquatic animal telemetry: A panoramic window into the underwater world. Science [Internet]. 2015;348(6240):1255642-. Available from: http://www.sciencemag.org/content/348/6240/1255642.full?utm_campaign=email-sci-toc&utm_src=email pmid:26068859
      • 17. Holland KN, Anderson JM, Coffey DM, Holmes BJ, Meyer CG, Royer MA. A Perspective on Future Tiger Shark Research. Front Mar Sci [Internet]. 2019 Feb 14 [cited 2020 Jan 20];6. Available from: https://www.frontiersin.org/article/10.3389/fmars.2019.00037/full
      • 18. Holland KN, Wetherbee BM, Lowe CG, Meyer CG. Movements of tiger sharks (Galeocerdo cuvier) in coastal Hawaiian waters. Mar Biol. 1999;134(4):665–73.
      • 19. Papastamatiou YP, Meyer CG, Carvalho F, Dale JJ, Hutchinson MR, Holland KN. Telemetry and random-walk models reveal complex patterns of partial migration in a large marine predator. Ecology [Internet]. 2013 Nov [cited 2019 Dec 1];94(11):2595–606. Available from: pmid:24400511
      • 20. Meyer CG, Clark TB, Papastamatiou YP, Whitney NM, Holland KN. Long-term movement patterns of tiger sharks Galeocerdo cuvier in Hawaii. Mar Ecol Prog Ser. 2009;381:223–35.
      • 21. Meyer CG, Papastamatiou YP, Holland KN. A multiple instrument approach to quantifying the movement patterns and habitat use of tiger (Galeocerdo cuvier) and Galapagos sharks (Carcharhinus galapagensis) at French Frigate Shoals, Hawaii. Mar Biol. 2010;157(8):1857–68.
      • 22. Acuña-Marrero D, Smith ANH, Hammerschlag N, Hearn A, Anderson MJ, Calich H, et al. Residency and movement patterns of an apex predatory shark (Galeocerdo cuvier) at the Galapagos Marine Reserve. Schmidt J V., editor. PLoS One [Internet]. 2017 Aug 22 [cited 2020 Jan 20];12(8):e0183669. Available from: pmid:28829820
      • 23. Hammerschlag N, Gallagher AJ, Wester J, Luo J, Ault JS. Don’t bite the hand that feeds: assessing ecological impacts of provisioning ecotourism on an apex marine predator. Funct Ecol. 2012 Jun 1;26(3):567–76.
      • 24. Hammerschlag N, Broderick AC, Coker JW, Coyne MS, Dodd M, Frick MG, et al. Evaluating the landscape of fear between apex predatory sharks and mobile sea turtles across a large dynamic seascape. Ecology [Internet]. 2015 Aug [cited 2020 Jan 20];96(8):2117–26. Available from: pmid:26405737
      • 25. Calich H, Estevanez M, Hammerschlag N. Overlap between highly suitable habitats and longline gear management areas reveals vulnerable and protected regions for highly migratory sharks. Mar Ecol Prog Ser [Internet]. 2018 Aug 23 [cited 2020 Jan 20];602:183–95. Available from: https://www.int-res.com/abstracts/meps/v602/p183-195/
      • 26. Bethea DM, Ajemian MJ, Carlson JK, Hoffmayer ER, Imhoff JL, Grubbs RD, et al. Distribution and community structure of coastal sharks in the northeastern Gulf of Mexico. Environ Biol Fishes. 2014;98(5).
      • 27. Plumlee JD, Dance KM, Matich P, Mohan JA, Richards TM, TinHan TC, et al. Community structure of elasmobranchs in estuaries along the northwest Gulf of Mexico. Estuar Coast Shelf Sci. 2018 May 1;204:103–13.
      • 28. Driggers W, Ingram G, Grace M, Gledhill C, Henwood T, Horton C, et al. Pupping areas and mortality rates of young tiger sharks Galeocerdo cuvier in the western North Atlantic Ocean. Aquat Biol [Internet]. 2008 May 15 [cited 2020 Jan 20];2:161–70. Available from: http://www.int-res.com/abstracts/ab/v2/n2/p161-170/
      • 29. Hoffmayer ER, Franks JS, Driggers WB, Howey PW. Diel vertical movements of a scalloped hammerhead, Sphyrna lewini, in the northern Gulf of Mexico. Bull Mar Sci. 2013 Apr;89(2):551–7.
      • 30. Wells RJD, TinHan TC, Dance MA, Drymon JM, Falterman B, Ajemian MJ, et al;. Movement, Behavior, and Habitat Use of a Marine Apex Predator, the Scalloped Hammerhead. Frontiers in Marine Science. 2018 Sep 10;5:321.
      • 31. Hoffmayer ER, Franks JS, Driggers WB, McKinney JA, Hendon JM, Quattro JM. Habitat, movements and environmental preferences of dusky sharks, Carcharhinus obscurus, in the northern Gulf of Mexico. Marine biology. 2014 Apr 1;161(4):911–24.
      • 32. Vaudo JJ, Byrne ME, Wetherbee BM, Harvey GM, Shivji MS. Long‐term satellite tracking reveals region‐specific movements of a large pelagic predator, the shortfin mako shark, in the western North Atlantic Ocean. Journal of applied ecology. 2017 Dec;54(6):1765–75.
      • 33. Hueter RE, Tyminski JP, de la Parra R. Horizontal Movements, Migration Patterns, and Population Structure of Whale Sharks in the Gulf of Mexico and Northwestern Caribbean Sea. Schmidt J V., editor. PLoS One [Internet]. 2013 Aug 21 [cited 2020 Jan 20];8(8):e71883. Available from: pmid:23991000
      • 34. Tyminski JP, de la Parra-Venegas R, González Cano J, Hueter RE. Vertical Movements and Patterns in Diving Behavior of Whale Sharks as Revealed by Pop-Up Satellite Tags in the Eastern Gulf of Mexico. Lee SY, editor. PLoS One [Internet]. 2015 Nov 18 [cited 2020 Jan 20];10(11):e0142156. Available from: pmid:26580405
      • 35. Rabalais NN, Turner RE, Wiseman WJ. Gulf of Mexico Hypoxia, A.K.A. “The Dead Zone.” Annu Rev Ecol Syst [Internet]. 2002;33(1):235–63. Available from: http://www.annualreviews.org/doi/abs/10.1146/annurev.ecolsys.33.010802.150513
      • 36. McCrea-Strub A, Kleisner K, Sumaila UR, Swartz W, Watson R, Zeller D, et al. Potential Impact of the Deepwater Horizon Oil Spill on Commercial Fisheries in the Gulf of Mexico. Fisheries [Internet]. 2011 Jul 22 [cited 2019 Dec 6];36(7):332–6. Available from: http://doi.wiley.com/10.1080/03632415.2011.589334
      • 37. Estabrook B, Ponirakis D, Clark C, Rice A. Widespread spatial and temporal extent of anthropogenic noise across the northeastern Gulf of Mexico shelf ecosystem. Endanger Species Res [Internet]. 2016 Aug 10 [cited 2019 Dec 6];30:267–82. Available from: http://www.int-res.com/abstracts/esr/v30/p267-282/
      • 38. Cruz I, McLaughlin RJ. Contrasting marine policies in the United States, Mexico, Cuba and the European Union: Searching for an integrated strategy for the Gulf of Mexico region. Ocean Coast Manag. 2008 Dec;51(12):826–38.
      • 39. Rooker JR, Dance MA, Wells RJD, Ajemian MJ, Block BA, Castleton MR, et al. Population connectivity of pelagic megafauna in the Cuba-Mexico-United States triangle. Sci Rep. 2019 Dec 1;9(1):1663. pmid:30733508
      • 40. Ajemian MJ, Jose PD, Froeschke JT, Wildhaber ML, Stunz GW. Was everything bigger in Texas? Characterization and trends of a land-based recreational shark fishery. Mar Coast Fish. 2016;8(1):553–6.
      • 41. Powers SP, Fodrie FJ, Scyphers SB, Drymon JM, Shipp RL, Stunz GW. Gulf-Wide Decreases in the Size of Large Coastal Sharks Documented by Generations of Fishermen. Mar Coast Fish [Internet]. 2013;5(March 2015):93–102. Available from: http://www.tandfonline.com/doi/abs/10.1080/19425120.2013.786001
      • 42. Drymon JM, Feldheim K, Fournier AM V, Seubert EA, Jefferson AE, Kroetz AM, et al. Tiger sharks eat songbirds: scavenging a windfall of nutrients from the sky. 2019 [cited 2020 Jan 20]; Available from: https://ebird.org
      • 43. Clark E, von Schmidt K. Sharks of the Central Gulf Coast of Florida. Bull Mar Sci. 1965;15(1):13–83.
      • 44. Branstetter S, Musick JA, Colvocoresses JA. A comparison of the age and growth of the tiger shark, Galeocerdo cuvier, from off Virginia and from the northwestern Gulf of Mexico. Fish Bull. 1987;85(2):269−279.
      • 45. Boyd JD, Brightsmith DJ. Error properties of Argos satellite telemetry locations using least squares and Kalman filtering. PLoS ONE. 2013;8(5): e63051. pmid:23690980
      • 46. Jonsen ID, McMahon CR, Patterson TA, Auger‐Méthé M, Harcourt R, Hindell MA, et al. Movement responses to environment: fast inference of variation among southern elephant seals with a mixed effects model. Ecology. 2019 Jan;100(1):e02566. pmid:30467837
      • 47. Amante C, Eakins BW. ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis. NOAA Technical Memorandum NESDIS NGDC-24. National Geophysical Data Center, NOAA. 2009. https://doi.org/10.7289/V5C8276M [1 January 2020].
        • 48. Afonso AS, Hazin FH V. Vertical Movement Patterns and Ontogenetic Niche Expansion in the Tiger Shark, Galeocerdo cuvier. Tsikliras AC, editor. PLoS One [Internet]. 2015 Jan 28 [cited 2019 Dec 1];10(1):e0116720. Available from: pmid:25629732
        • 49. Kohler NE, Casey JG, Turner P a. NMFS Cooperative Shark Tagging Program, 1962-93: An Atlas of Shark Tag and Recapture Data. Mar Fish Rev. 1998;60(2):1–87.
        • 50. Fu AL, Hammerschlag N, Lauder G V., Wilga CD, Kuo C-Y, Irschick DJ. Ontogeny of head and caudal fin shape of an apex marine predator: The tiger shark (Galeocerdo cuvier). J Morphol [Internet]. 2016 May [cited 2019 Dec 1];277(5):556–64. Available from: pmid:26869274
        • 51. Lohrenz S, Fahnenstiel G, Redalje D, Lang G, Chen X, Dagg M. Variations in primary production of northern Gulf of Mexico continental shelf waters linked to nutrient inputs from the Mississippi River. Mar Ecol Prog Ser [Internet]. 1997 [cited 2019 Dec 1];155:45–54. Available from: http://www.int-res.com/abstracts/meps/v155/p45-54/
        • 52. Murawski SA, Peebles EB, Gracia A, Tunnell JW, Armenteros M. Comparative Abundance, Species Composition, and Demographics of Continental Shelf Fish Assemblages throughout the Gulf of Mexico. Mar Coast Fish [Internet]. 2018 Jun [cited 2019 Dec 1];10(3):325–46. Available from: http://doi.wiley.com/10.1002/mcf2.10033
        • 53. Gough MK, Beron-Vera FJ, Olascoaga MJ, Sheinbaum J, Juoanno J, Duran R. Persistent Lagrangian transport patterns in the northwestern Gulf of Mexico. 2017 Oct 11 [cited 2019 Dec 1]; Available from: http://arxiv.org/abs/1710.04027
        • 54. Garavelli L, Studivan MS, Voss JD, Kuba A, Figueiredo J, Chérubin LM. Assessment of Mesophotic Coral Ecosystem Connectivity for Proposed Expansion of a Marine Sanctuary in the Northwest Gulf of Mexico: Larval Dynamics. Front Mar Sci [Internet]. 2018 May 22 [cited 2019 Dec 1];5. Available from: https://www.frontiersin.org/article/10.3389/fmars.2018.00174/full
        • 55. Dicken ML, Hussey NE, Christiansen HM, Smale MJ, Nkabi N, Cliff G, et al. Diet and trophic ecology of the tiger shark (Galeocerdo cuvier) from South African waters. PloS one. 2017;12(6): e0177897. pmid:28594833
        • 56. Morgan A, Burgess GH. At-Vessel Fishing Mortality for Six Species of Sharks Caught in the Northwest Atlantic and Gulf of Mexico. 2007;19(2).
        • 57. Gallagher AJ, Serafy JE, Cooke SJ, Hammerschlag N. Physiological stress response, reflex impairment, and survival of five sympatric shark species following experimental capture and release. Mar Ecol Prog Ser. 2014;496:207–18.
        • 58. Gallagher AJ, Orbesen ES, Hammerschlag N, Serafy JE. Vulnerability of oceanic sharks as pelagic longline bycatch. Glob Ecol Conserv. 2014 Aug 1;1:50–9.
        • 59. Bègue M, Clua E, Siu G, Meyer C. Prevalence, persistence and impacts of residual fishing hooks on tiger sharks. Fish Res [Internet]. 2020 Apr [cited 2019 Dec 7];224:105462. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0165783619303170
        • 60. Randall JE. Review of the biology of the tiger shark (Galeocerdo cuvier). Mar Freshw Res. 1992;43(1):21–31.
        • 61. Afonso AS, Hazin FH V., Barreto RR, Santana FM, Lessa RP. Extraordinary growth in tiger sharks Galeocerdo cuvier from the South Atlantic Ocean. J Fish Biol [Internet]. 2012 Nov [cited 2020 Jan 20];81(6):2080–5. Available from: pmid:23130703
        • 62. Dennis GD, Bright TJ. Reef fish assemblages on hard banks in the northwestern Gulf of Mexico. Bulletin of Marine Science. 1988 Aug 1;43(2):280–307.63.
        • 63. Rezak R, Gittings SR, Bright TJ. Biotic assemblages and ecological controls on reefs and banks of the Northwest Gulf of Mexico. Integr Comp Biol. 1990;30(1):23–35.
        • 64. Schmahl GP, Hickerson EL, Precht WF. Biology and Ecology of Coral Reefs and Coral Communities in the Flower Garden Banks Region, Northwestern Gulf of Mexico. In: Coral Reefs of the USA [Internet]. Dordrecht: Springer Netherlands; 2008 [cited 2018 Jan 26]. p. 221–61. Available from: http://link.springer.com/10.1007/978-1-4020-6847-8_6
          • 65. Childs JN. The occurrence, habitat use, and behavior of sharks and rays associating with topographic highs in the northwestern Gulf of Mexico. MS Thesis, Texas A&M University. 2001. Available from: https://oaktrust.library.tamu.edu/handle/1969.1/ETD-TAMU-2001-THESIS-C45
            • 66. Chapman DD, Feldheim KA, Papastamatiou YP, Hueter RE. There and Back Again: A Review of Residency and Return Migrations in Sharks, with Implications for Population Structure and Management. Ann Rev Mar Sci [Internet]. 2015 Jan 3 [cited 2019 Dec 1];7(1):547–70. Available from: http://www.annualreviews.org/doi/10.1146/annurev-marine-010814-015730
            • 67. Sulikowski JA, Wheeler CR, Gallagher AJ, Prohaska BK, Langan JA, Hammerschlag N Seasonal and life-stage variation in the reproductive ecology of a marine apex predator, the tiger shark Galeocerdo cuvier, at a protected female-dominated site. Aquat Biol. 2016 24(3):175–184.
            • 68. Scarborough Bull A, Kendall J Jr. An indication of the process: offshore platforms as artificial reefs in the Gulf of Mexico. Bull Mar Sci. 1994;55(2–3):1086–98.
            • 69. Gallaway BJ, Szedlmayer ST, Gazey WJ. A life history review for red snapper in the Gulf of Mexico with an evaluation of the importance of offshore petroleum platforms and other artificial reefs. Reviews in Fisheries Science. 2009.
            • 70. Ajemian MJ, Wetz JJ, Shipley-Lozano B, Dale Shively J, Stunz GW. An analysis of artificial reef fish community structure along the northwestern gulf of Mexico Shelf: Potential impacts of “rigs-to-reefs” Programs. PLoS One. 2015;10(5).
            • 71. Gallaway BJ, Szedlmayer ST, Gazey WJ. A Life History Review for Red Snapper in the Gulf of Mexico with an Evaluation of the Importance of Offshore Petroleum Platforms and Other Artificial Reefs. Rev Fish Sci. 2009;17(1):48–67.
            • 72. Benfield MC, Kupchik MJ, Palandro DA, Dupont JM, Blake JA, Winchell P. Documenting deepwater habitat utilization by fishes and invertebrates associated with Lophelia pertusa on a petroleum platform on the outer continental shelf of the Gulf of Mexico using a remotely operated vehicle. Deep Res Part I Oceanogr Res Pap. 2019 Jul 1;149:103045.
            • 73. Valentine DL, Fisher GB, Bagby SC, Nelson RK, Reddy CM, Sylva SP, et al. Fallout plume of submerged oil from Deepwater Horizon. PNAS. 2014;111(45):15906−11. pmid:25349409
            • 74. Al-Hassan JM, Afzal M, Rao CVN, Fayad S. Petroleum hydrocarbon pollution in sharks in the Arabian Gulf. Bull Environ Contam Toxicol. 2000;65(3):391–8. pmid:10903364
            • 75. Cullen JA, Marshall CD, Hala D. Integration of multi-tissue PAH and PCB burdens with biomarker activity in three coastal shark species from the northwestern Gulf of Mexico. Sci Total Environ. 2019 Feb 10;650:1158–72. pmid:30308804
            • 76. Montagna PA, Jarvis SC, Kennicutt II MC. Distinguishing between contaminant and reef effects on meiofauna near offshore hydrocarbon platforms in the Gulf of Mexico. Can J Fish Aquat Sci [Internet]. 2002 Oct 1 [cited 2020 Jan 12];59(10):1584–92. Available from: http://www.nrcresearchpress.com/doi/10.1139/f02-131
            • 77. Meyer CG, Anderson JM, Coffey DM, Hutchinson MR, Royer MA, Holland KN. Habitat geography around Hawaii’s oceanic islands influences tiger shark (Galeocerdo cuvier) spatial behaviour and shark bite risk at ocean recreation sites. Sci Rep. 2018 Dec 1;8(1):1−8. pmid:29311619
            • 78. Hammerschlag N, Gutowsky LFG, Gallagher AJ, Matich P, Cooke SJ. Diel habitat use patterns of a marine apex predator (tiger shark, Galeocerdo cuvier) at a high use area exposed to dive tourism. J Exp Mar Bio Ecol. 2017 Oct 1;495:24–34.
            • 79. Acuña-Marrero D, Smith A, Salinas-de-León P, Harvey E, Pawley M, Anderson M. Spatial patterns of distribution and relative abundance of coastal shark species in the Galapagos Marine Reserve. Mar Ecol Prog Ser [Internet]. 2018 Apr 12 [cited 2019 Dec 1];593:73–95. Available from: http://www.int-res.com/abstracts/meps/v593/p73-95/
            • 80. Kneebone J, Natanson LJ, Andrews AH, Howell WH. Using bomb radiocarbon analyses to validate age and growth estimates for the tiger shark, Galeocerdo cuvier, in the western North Atlantic. Mar Biol. 2008 May;154(3):423–34.
            • 81. Hammerschlag N, Sulikowski J. Killing for conservation: the need for alternatives to lethal sampling of apex predatory sharks. Endanger Species Res [Internet]. 2011 Jun 22 [cited 2017 Jul 6];14(2):135–40. Available from: http://www.int-res.com/abstracts/esr/v14/n2/p135-140/
            • 82. Jewell OJD, Wcisel MA, Gennari E, Towner A V., Bester MN, Johnson RL, et al. Effects of Smart Position Only (SPOT) Tag Deployment on White Sharks Carcharodon carcharias in South Africa. Gratwicke B, editor. PLoS One [Internet]. 2011 Nov 14 [cited 2019 Dec 1];6(11):e27242. Available from: pmid:22110620
            • 83. Aines AC, Carlson JK, Boustany A, Mathers A, Kohler NE. Feeding habits of the tiger shark, Galeocerdo cuvier, in the northwest Atlantic Ocean and Gulf of Mexico. Environ Biol Fishes. 2018 Mar 1;101(3):403–15.
            • 84. Vaudo JJ, Wetherbee BM, Harvey G, Nemeth RS, Aming C, Burnie N, et al. Intraspecific variation in vertical habitat use by tiger sharks (Galeocerdo cuvier) in the western North Atlantic. Ecol Evol [Internet]. 2014 May [cited 2020 Jan 20];4(10):1768–86. Available from: pmid:24963376
            • 85. Hays GC, Bradshaw CJA, James MC, Lovell P, Sims DW. Why do Argos satellite tags deployed on marine animals stop transmitting? J Exp Mar Bio Ecol. 2007 Sep 28;349(1):52–60.
            • 86. Hammerschlag N, Cooke SJ, Gallagher AJ, Godley BJ. Considering the fate of electronic tags: interactions with stakeholders and user responsibility when encountering tagged aquatic animals. Freckleton R, editor. Methods Ecol Evol [Internet]. 2014 Nov [cited 2020 Jan 20];5(11):1147–53. Available from: http://doi.wiley.com/10.1111/2041-210X.12248