To go or not to go with the flow: Environmental influences on whale shark movement patterns

Sleeman, Jai C.; Meekan, Mark G.; Wilson, Stephen G.; Polovina, Jeffrey J.; Stevens, John D.; Boggs, Guy S.; Bradshaw, Corey J. A.

doi:10.1016/j.jembe.2010.05.009

Cited by 71 publications

(77 citation statements)

References 41 publications

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“…Whale sharks also undertake large-scale oceanic movements (Eckert & Stewart 2001, Hsu et al 2007, Rowat & Gore 2007, Sleeman et al 2010b), e.g. one whale shark that was satellite-tagged immediately adjacent to the current study area travelled ~1200 km in 87 days (Brunnschweiler et al 2009).…”

Section: Overall Modelmentioning

confidence: 99%

Trends in sightings and environmental influences on a coastal aggregation of manta rays and whale sharks

Rohner¹,

Pierce²,

Marshall³

et al. 2013

Mar. Ecol. Prog. Ser.

121

145

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Sightings of planktivorous elasmobranchs at their coastal aggregation sites are often linked to biological, environmental and temporal variables. Many large planktivorous elasmobranchs are also globally threatened species, so it is necessary to try and separate population trends from environmentally driven, short-term fluctuations. We investigated the influence of environmental variables on sightings of 3 species of planktivorous elasmobranchs off Praia do Tofo, Mozambique: the reef manta ray Manta alfredi, giant manta ray M. birostris and whale shark Rhincodon typus. We used 8-(2003We used 8-( to 2011We used 8-( ) and 6-yr (2005We used 8-( to 2011 logbook data for manta rays and whale sharks, respectively, and constructed a generalised linear model with animal sightings as the response. Predictors included temporal (year, month, time of day), biological (plankton categories), oceanographic (water temperature, time from high tide, current direction and strength and wave height) and celestial (moon illumination) indices. These predictors best fitted reef manta ray sightings, a coastal species with high residency, but less so for the wider-ranging giant manta rays and whale sharks. We found a significant decline in the standardised sightings time series for the reef manta ray (88%) and whale shark (79%), but not for the giant manta ray.

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Section: Overall Modelmentioning

confidence: 99%

Trends in sightings and environmental influences on a coastal aggregation of manta rays and whale sharks

Rohner¹,

Pierce²,

Marshall³

et al. 2013

Mar. Ecol. Prog. Ser.

121

145

View full text Add to dashboard Cite

show abstract

“…As illustrated here, these methods can be used to estimate currents along the length of an animal's track and thus infer what component of the path is caused by active movement versus passive drift (e.g. Gaspar et al 2006, Sleeman et al 2010. This is critical to discriminate foraging and travelling behaviour (Gaspar et al 2006, Fossette et al 2010b, Robel et al 2011, evaluate orientation and navigation abilities (Girard et al 2006, Luschi et al 2007, Mills Flemming et al 2010, or understand the influence of the ocean circulation on the spatio-temporal distribution of oceanic mi grants (Shillinger et al 2008, Campbell et al 2010, Cotté et al 2011.…”

Section: Best Uses Of Satellite-derived and Modelled Current Datamentioning

confidence: 99%

“…Lagrangian drifter buoys (see Appendix 1) provide 'direct' in situ information on surface currents (Campagna et al 2006, Horton et al 2011, although there are caveats related to buoy performance. Two additional techniques are well established: (1) satellite observations are used to infer surface current fields at regular intervals (Gaspar et al 2006, Cotté et al 2007, Seminoff et al 2008, Bailleul et al 2010, Campbell et al 2010; and (2) particles are tracked in numerical ocean circulation models to mimic Lagrangian drifter buoys (Bonhommeau et al 2009, Sleeman et al 2010, Kobayashi & Cheng 2011. While surface currents may be estimated from satellite observations at a spatial resolution of about 25 to 100 km (Rio & Hernandez 2004, Pascual et al 2006, Rio et al 2011, the current fields simulated in ocean general circulation model (OGCM) hindcasts (e.g.…”

Section: Introductionmentioning

confidence: 99%

A biologist’s guide to assessing ocean currents: a review

Fossette¹,

Putman²,

Lohmann³

et al. 2012

Mar. Ecol. Prog. Ser.

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We review how ocean currents are measured (in both Eulerian and Lagrangian frameworks), how they are inferred from satellite observations, and how they are simulated in ocean general circulation models (OGCMs). We then consider the value of these 'direct' (in situ) and 'indirect' (inferred, simulated) approaches to biologists investigating current-induced drift of strong-swimming vertebrates as well as dispersion of small organisms in the open ocean. We subsequently describe 2 case studies. In the first, OGCM-simulated currents were compared with satellite-derived currents; analyses suggest that the 2 methods yield similar results, but that each has its own limitations and associated uncertainty. In the second analysis, numerical methods were tested using Lagrangian drifter buoys. Results indicated that currents simulated in OGCMs do not capture all details of buoy trajectories, but do successfully resolve most general aspects of current flows. We thus recommend that the errors and uncertainties in ocean current measurements, as well as limitations in spatial and temporal resolution of the surface current data, need to be considered in tracking studies that incorporate oceanographic data. Whenever possible, crossvalidation of the different methods (e.g. indirect estimates versus buoy trajectories) should be undertaken before a decision is reached about which technique is best for a specific application.

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“…The largest of the shark species, whale sharks are highly mobile (e.g., Wilson et al, 2006;Sleeman et al, 2010;Berumen et al, 2014;Robinson et al, 2017), but form predictable seasonal aggregations in hotspots around the world, predominantly associated with the presence of food (e.g., Motta et al, 2010;Robinson et al, 2013;Rohner et al, 2015a). Some whale sharks display a degree of site fidelity on an annual and inter-annual basis (Graham and Roberts, 2007;Holmberg et al, 2008;Fox et al, 2013;Araujo et al, 2017), and this predictability makes the whale shark an ideal target species for wildlife tourism (Catlin and Jones, 2010;Rowat and Brooks, 2012).…”

Section: Introductionmentioning

confidence: 99%

Long-Term Photo-Identification Reveals the Population Dynamics and Strong Site Fidelity of Adult Whale Sharks to the Coastal Waters of Donsol, Philippines

McCoy

Burce²,

David³

et al. 2018

Front. Mar. Sci.

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Donsol in the Philippines is the longest running community-based whale shark (Rhincodon typus) ecotourism site in Southeast Asia, with peak visitation in 2012 of over 27,000 tourists. In order to understand this aggregation and the importance of the area to whale sharks, dedicated photographic identification (photo-ID) research began in 2007. In-water photo-ID surveys were conducted from tourism boats, weather and operator permitting, from December to June between 2007 and 2016. Visual matches of the unique spot patterns of each individual shark were validated by the pattern-recognition software Interactive Individual Identification System (I 3 S), and on the online database Wildbook for Whale Sharks (www.whaleshark.org). A total of 1,985 photo-ID trips over 895 survey days resulted in 6,786 encounters with R. typus. Combined with encounters from both dedicated research and citizen science dating back to 1998, 479 individual whale sharks were identified, making up 44% of the known whale shark population in the Philippines (n = 1,095). Of these, photographs of the pelvic region confirmed the sex for 158 males and 22 females. Visual size estimates ranged from 2 to 10 m (mean ± SD = 6.5 ± 1.6 m). Maturity in males (LT 50 ) was estimated at 6.8 ± 0.2 m total length, with 53% of males considered mature. Annually, the total number of individuals sighted varied between 15 and 185 (mean ± SD = 104 ± 55.53), with a recruitment of 3-90 new individuals yearly (mean ± SD = 46.8 ± 36.29). Modeled residency using maximum likelihood methods suggested whale sharks spent 49.8 ± S.E. 14.5 [95% CI (32.3-78.6)] days in Donsol each season, with 47.1-60.8 whale sharks at any one time during the season. Twenty individuals were recorded through photo-ID at other sites across the Philippines. The extended residency of whale sharks at Donsol, paired with the presence of sexually mature animals and the economic value of the tourism industry, highlights the importance of Donsol for this endangered species.

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To go or not to go with the flow: Environmental influences on whale shark movement patterns

Cited by 71 publications

References 41 publications

Trends in sightings and environmental influences on a coastal aggregation of manta rays and whale sharks

Trends in sightings and environmental influences on a coastal aggregation of manta rays and whale sharks

A biologist’s guide to assessing ocean currents: a review

Long-Term Photo-Identification Reveals the Population Dynamics and Strong Site Fidelity of Adult Whale Sharks to the Coastal Waters of Donsol, Philippines

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