1The University of the South Pacific (USP) – School of Marine Studies, Faculty of Science, Technology and Environment, Laucala Campus, Suva, Fiji
2 CSIRO National Research Collections Australia, Australian National Fish Collection – Hobart, TAS., Australia
3 Guy Harvey Research Institute, Nova Southeastern University Oceanographic Center – 8000 North Ocean Drive, Dania Beach, FL 33004, United States
4 Independent Researcher – Gladbachstrasse 60 Zurich, Switzerland
5 The University of the South Pacific – School of Marine Studies, Faculty of Science, Technology and Environment, Laucala Campus, Suva, Fiji
6 Estaci´on Biol´ogica de Do˜nana, Consejo Superior de Investigaciones Cient´ıficas – Sevilla 41092, Spain, Spain
Knowledge about the genetic population structure is fundamental to fields ranging from evolutionary biology to species conservation management. To date and for sharks, the genetic population structure of only a few coastal species is known. Moreover, the application of whole genome-scans for non-model organisms allows genetic studies to enter a vast new stage of genomic exploration. The bull shark (Carcharhinus leucas) is a large, mobile, circumglobally distributed species that inhabits a variety of coastal habitats including freshwater environments. Combining the bull sharks’ capability for long-distant movements and the species’ longevity, significant genetic exchange is generally assumed. Here, using Single Nucleotide Polymorphisms (SNPs), we test the null-hypothesis that bull sharks are panmictic throughout a subset of the species’ Indo- Pacific range. We analyzed 2793 high-quality neutral SNP markers in 150 individual bull sharks from Fiji, the east, north, and west coasts of Australia, Banda Aceh in Indonesia, and South Africa. Genomic diversity and population connectivity estimates including average observed heterozygosity (Ho) and pairwise FST were calculated. Observed heterozygosities ranged from 0.291 + 0.165 to 0.335 + 0.173. The analyses revealed significant genetic partitioning between Fiji and all other locations sampled (FST> 0.037, P< 0.001). Contrastingly, gene flow within all the remaining locations was apparent, with highest levels of genetic connectivity between West Australia and Banda Aceh, Indonesia. The absence of population structure across the Sunda Shelf barrier indicates that oceanic expanses and land barriers in Southeast Asia are not impediments to bull shark dispersal. Our results demonstrate, that a remote island archipelago, such as Fiji, offers a great opportunity to study genetic population structure in a mobile, coastal shark. We anticipate our genomic approach to be the starting point for our future research
∗Speaker
†Corresponding author: kerstin glaus@outlook.com
which aims to understand the drivers of spatial isolation and the distinct genetic signatures in bull sharks from Fiji.
Global genetic inventory of the Silky Shark (Carcharhinus falciformis), the shark finning
industry, and DNA fingerprinting
Derek Kraft ∗ 1,2
1 Melanie Hutchinson (International Fisheries Program NOAA) – International Fisheries Program 1845 Wasp Blvd, Honolulu, HI 96818, United States
2Brian Bowen (HIMB) – Hawaii Institute of Marine Biology 46-007 Lilipuna Rd, Kaneohe, HI 96744, United States
The pelagic silky sharks (Carcharhinus falciformis) occur in all oceans and are the second most commonly harvested shark on the planet. Their habitat overlaps with commercial tuna fisheries and they account for > 90% of the shark bycatch in tropical purse seine fisheries of the western and central Pacific. Silkys’ are also one of the most abundant species in the shark fin trade; contributing to a harvest estimated at 26-73 million sharks annually. As a result of these non-regulated fisheries, this formally abundant shark has declined by > 85% in the last 20 years, and is now listed as near-threatened and declining by IUCN. In the face of this dramatic decline, there is little information on extraction rates or stock structure, which are the basic units of wildlife life management. Here we provide a global genetic inventory of the Silky shark to resolve populations and delineate stock structure. Subsequently this information will be used as a baseline to identify the origins of Silky shark in the fin markets. We have secured global sampling coverage with > 2,000 specimens. To quantify genetic structure, we use restriction site-associated DNA polymorphisms (ezRAD) in whole genome scans. Once the population structure of Silky sharks is resolved, this data is used to quantify gene flow on a global scale. Finally over 1000 fin samples have been taken over four years from the shark fin trade in China and will be compared to our global baseline, using a Bayesian mixed stock model.
This will allow the identification of sharks in the fin trade to both the species-level and oceanic region of origin, providing a much-need scientific foundation for management plans. Given that traditional extraction monitoring is not available, our assessment of stock harvest will happen at the end point of the market supply chain.
∗Speaker
Ground truthing dermal denticles to characterize shark assemblages on Palmyra
Atoll
Erin Dillon ∗† 1, Kevin Lafferty 2,1, Darcy Bradley 3, Richard Norris 4, Douglas Mccauley 1, Aaron O’dea 5
1University of California, Santa Barbara (UCSB) – Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA 93106, USA, United States
2U.S. Geological Survey (USGS) – Western Ecological Research Center, U.S. Geological Survey, Marine Science Institute, University of California, Santa Barbara, CA 93106, United States
3 University of California, Santa Barbara (UCSB) – Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA 93106, USA, United States
4 Scripps Institution of Oceanography (SIO) – University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0208, U.S.A., United States
5 Smithsonian Tropical Research Institute (STRI) – Balboa, Ancon, Panama
Assessing how and why predator assemblages vary over space and time is crucial for under- standing ecosystem trophic structure and dynamics. Historical accounts often depict extremely high densities of sharks that sharply juxtapose contemporary reports of shark abundance in the same regions. Although this suggests that shark populations have declined, evaluating the reliability of these anecdotes is challenging because detailed shark surveys began after the initial degradation of marine ecosystems. Consequently, quantitative pre-exploitation shark baselines are nearly nonexistent, so the magnitude and long-term trajectories of change in shark commu- nities are unresolved. To meet this challenge, we are reconstructing historical shark communities using dermal denticles, the small tooth-like scales covering elasmobranch skin, which accumulate and are well-preserved in modern and fossil coral reef sediments. They can be extracted and identified to reveal broad spatiotemporal patterns of relative shark abundance and diversity. To extend the utility of the denticle record as a new paleoecological proxy, we assessed its fidelity and resolution on Palmyra Atoll, a remote unfished U.S. National Wildlife Refuge in the central Pacific where shark abundance is high and well-documented. Here, we evaluated the alignment between denticle assemblages found in modern, time-averaged sediments collected from lagoonal and backreef environments with visual, video, and capture-recapture shark survey data, while also examining the extent of spatial patchiness in the denticle record across the atoll. We found rank alignment between denticle abundance per kilogram sediment and censused shark abun- dance, and denticle diversity reflected known taxa on the atoll. Comparing the outputs of these different survey methods as well as measuring and constraining potential biases of the denti- cle record can help standardize this tool, enabling comparisons between denticle assemblages
How does a shark’s paradise become a fish’s nightmare? Ecology and behaviour of reef
sharks at Fakarava, one of the world’s biggest aggregations.