Satellite tracking of juvenile whale sharks, Rhincodon typus, in the Northwestern Pacific

Hsu, Hua-Hsun; Joung, Shoou‐Jeng; Liao, Yih-Yia; Liu, Kwang‐Ming

doi:10.1016/j.fishres.2006.11.030

Cited by 48 publications

(39 citation statements)

References 24 publications

(28 reference statements)

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“…In Ningaloo Reef, Western Australia, whale shark abundances have been correlated with environmental variables, such as currents, water temperatures, and the Southern Oscillation Index, which has been suggested by the authors to also serve as a proxy for food availability (Taylor & Pearce 1999, Wilson et al 2001, Sleeman et al 2010. Whale shark distribution has been linked to nutrient-rich waters with elevated chlorophyll levels in other regions, including, but not limited to, Japan, Western Australia, India, and the Galapagos Islands (Iwasaki 1970, Compagno 1984, Arnbom & Papastavrou 1988, Taylor & Pearce 1999, Hsu et al 2007, Kumari & Raman 2010. Similarly, chlorophyll a concentrations have been used to forecast fisheries catches (Solanki 2003) and to delineate mi gratory corridors and foraging habitat used by highly migratory ma rine species, such as tunas and turtles (Polovina et al 2001).…”

Section: Discussionmentioning

confidence: 99%

“…They are known to aggregate in areas of high biological productivity, such as near plankton blooms, fish spawns, and areas where changes in water temperatures occur (Compagno 1984, Taylor & Pearce 1999, Heyman et al 2001, Hoffmayer et al 2005, Taylor 2007. Their movements may correspond to bathymetric and/or oceanographic features, such as thermal fronts, eddies, currents, and zones of high chlorophyll a concentration (Taylor & Pearce 1999, Hoffmayer et al 2005, Hsu et al 2007, Kumari & Raman 2010, likely due to the presence of zooplankton assemblages and fish populations that are known to accumulate near these features (Balch & Byrne 1994). Their distri bution is also believed to be linked to specific environmental conditions, such as narrow temperature ranges and areas of upwelling (Colman 1997, Se queira et al 2011.…”

Section: Introductionmentioning

confidence: 99%

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Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

McKinney¹,

Hoffmayer²,

Wu³

et al. 2012

Mar. Ecol. Prog. Ser.

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Whale shark Rhincodon typus is a globally distributed species, but there is a lack of knowledge pertaining to their biology, seasonal occurrence, and distribution in the northern Gulf of Mexico (NGOM). Understanding critical habitat for whale sharks is essential on both a regional and global basis for proper management because of their large migratory range. The goal of the present study was to describe the regional distribution of whale shark feeding aggregations in the NGOM by exploiting a presence-only dataset collected as a part of a volunteer sighting survey. Whale shark aggregations have been documented in large numbers in the NGOM since 2003, and species distribution models provide a unique approach to analyzing these presence data. We used maximum entropy and ecological niche factor analysis, 2 algorithms designed for predicting species distribution based only on presence data, to analyze data for the summer period in 2008 and 2009. Cohen's kappa (kappa) and the 'area under the receiver operating characteristic curve' (AUC) were used to evaluate model performance with an external testing dataset. Kappa values ranged from 0.28 to 0.69, and AUC values ranged from 0.73 to 0.80, indicating that the predicted distribution had a fair to substantial agreement with the testing data. Distance to continental shelf edge, distance to adjacent petroleum platforms, and chlorophyll a were the variables most strongly related to whale shark sightings, likely due to an association of these variables with high food availability. Suitable habitat was predicted along the continental shelf edge, with the most suitable habitat predicted south of the Mississippi River Delta. The spatial distribution of suitable habitat is dynamic; therefore, a multi-year study is underway to better delineate temporal trends in regional whale shark distribution and to identify consistent areas of high suitability. Presenceonly habitat models are a powerful tool for delineating important regional habitat for a vulnerable, highly migratory species.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

McKinney¹,

Hoffmayer²,

Wu³

et al. 2012

Mar. Ecol. Prog. Ser.

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show abstract

“…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.

129

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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“…Due to depletion of whale shark populations noted in the Indo-Pacific, the category of the species was upgraded to "Endangered" (Pierce and Norman, 2016), as well as being included in Appendix I of the Convention on Migratory Species in 2017 and in Appendix II of the Convention on International Trade of Endangered Species in 2003. China is known to still catch whale sharks through unregulated fisheries, many caught in the South China Sea (Li et al, 2012), an area that whale sharks from Taiwan and the Philippines visit (Hsu et al, 2007;WWF-Philippines, Unpub. data).…”

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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Satellite tracking of juvenile whale sharks, Rhincodon typus, in the Northwestern Pacific

Cited by 48 publications

References 24 publications

Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

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

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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