Catch number of true tuna (Thunnus spp.) larvae collected in the Gulf of Mexico before (2007-2009), during (2010), and after (2011-2013; 2015) the Deepwater Horizon Oil Spill (DWHOS)
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Gulf of Mexico Research Initiative (GoMRI)
Deep-Pelagic Nekton Dynamics of the Gulf of Mexico (DEEPEND)
Jay R. Rooker
Texas A&M University at Galveston / Marine Biology Department
2007-06-20 to 2015-07-25
Sea Surface Temperature, Salinity, Latitude, Longitude, Environmental data, Surface, neuston net, paired bongo net, Ichthyoplankton, Pelagic fish, Early life habitat, Tuna larvae, Recruitment, Scombridae, Thunnus, Blackfin tuna, Yellowfin tuna, Bluefin tuna, Bigeye tuna
Catch number of true tunas (Thunnus thynnus [bluefin tuna], T. albacares [yellowfin tuna], T. obesus [bigeye tuna] and T. atlanticus [blackfin tuna]) before, during, and after the oil spill will be compared to improve our understanding of the causes of temporal variability as it relates to the DWHOS. This dataset contains historical catch data from 2007-2015 collected in the northern Gulf of Mexico. Generalized additive models will be developed for periods before the event (2007-2009) to characterize habitat associations of each species, and then used to estimate the spatial extent of suitable habitats of true tunas (2010-2015) and identify areas of high quality habitat that overlapped with regions exposed to surface oil. Sampling data from 2015 are available in dataset R4.x257.227:0002.
Jay R. Rooker, R.J. David Wells, Maelle Cornic. 2017. Catch number of true tuna (Thunnus spp.) larvae collected in the Gulf of Mexico before (2007-2009), during (2010), and after (2011-2013; 2015) the Deepwater Horizon Oil Spill (DWHOS). Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7610XFM
Surface surveys conducted by DEEPEND in shelf and slope waters during the primary spawning period of tunas provide information on the distribution and abundance of Thunnus larvae (T. thynnus, T. albacares, T. atlanticus, and T. obesus). Natural variability in larval abundance and occurrence is high for post-spill years, and thus examining the factors influencing the distribution and abundance of Thunnus larvae before, during, and after the DWHOS is critical for characterizing natural variability. Moreover, habitat suitability models are being developed for tuna larvae from 2007-2015 collections that will ultimately be used to predict the probability of occurrence of Thunnus species in future years.
Data Parameters and Units:
Cruise, Year, Month, Collection date (MO/DD/YYYY), Station, Latitude (DD), Longitude (DD), Time (HH:MM), Sea Surface temperature- SST (°C), Salinity, Sea surface height anomaly- SSHA (cm), Sargassum NN500 (lbs wet weight in net), Sargassum NN1200 (lbs wet weight in net), Flowmeter NN500 (out-in), Flowmeter NN1200 (out-in), Flowmeter BN333 (out-in), Flowmeter BN500 (out-in), Station genetically identified (ID), Number of larvae at each station (species code_net): Th_NN500, Th_NN1200, Th_BN333, Th_BN500, BK_NN500, BK_NN1200, BE_NN500, BE_NN1200, YF_NN500, YF_NN1200, BF_NN500, BF_NN1200, BK_BN333, BK_BN500, BE_BN333, BE_BN500, YF_BN333, YF_BN500, BF_BN333, BF_BN500 NN500- Neuston Net with 500 micron mesh, NN1200- Neuston Net with 1200 micron mesh, BN333- Bongo net with 333 micron mesh, BN500- Bongo net with 500 micron mesh, Th- Thunnus, BK- Blackfin tuna, BE- Bigeye tuna, YF- Yellowfin tuna, BF- Bluefin tuna
Sea surface temperature and salinity were measured at each station. GPS location was recorded at each station. NA denotes three different situations 1) specific net was not used to collect larva, 2) environmental data missing, 3) stations where Thunnus larvae were not genetically identified. Larvae at each station were collected from 2007 to 2010 with two neuston nets (2 m width x 1 m height frame) with 500 and 1200 micron mesh, and with two different sampling gears from 2011 to 2015: 1) neuston net (2 m width x 1 m height frame) with 1200 micron mesh 2) a paired 61-cm bongo nets with 333 and 500 micron mesh. Neuston nets were towed through the upper meter of the water column while oblique tows to ca. 100 m were made with the paired bongo nets. General Oceanics flow meters (Model 2030R, Miami, FL) were placed within net frames determine the volume of water sampled by each net. Fish larvae and early juveniles collected with net gears were preserved onboard in 95% ethanol. Tuna larvae were sorted to the genus level using a Leica MZ stereomicroscope, and Thunnus larvae were identified to the species level using a genotyping method (high-resolution melting analysis). From 2007 to 2009 due to a large number of Thunnus larvae in our samples, HRMA was performed on larvae from a subset of positive stations (Thunnus larvae present). For stations examined with HRMA containing less than 100 Thunnus larvae, each individual was genetically identified to species. If more than 100 Thunnus larvae were present, 100 randomly selected larvae were genetically identified. An unlabeled probe (UP) HRMA assay was developed for Gulf of Mexico tuna species genetic identification (Smith et al. submitted). A non-destructive sodium hydroxide DNA isolation method (Alvarado-Bremer et al. 2014) was utilized for DNA isolation on each larva. The mitochondrial DNA gene NADH dehydrogenase subunit 4 (ND4) was amplified in 10 µL volumes by asymmetric polymerase chain reactions (PCR) with 10 ng of DNA template, 1 X EconoTaqPlus (Lucigen), and 1 X LC Green Plus (Biofire Diagnostics, Inc.), and 0.200 µM of the forward primer (5’-AGCAGAAAAGAGCGGAGGAG-3’), 0.028 µM of the diluted reverse primer (5’-ACAGGCTCAATCTGTCTCCCG-3’), and 0.200 µM of an unlabeled phosphorylated probe (5’-GAGGCTTTACGGGGGGCCCTTATCCTT/3Phos/-3’), which is complementary for T. maccoyii (Cornic et al. in review).
Sonde 6920 Environmental Monitoring System (YSI Inc.) (Salinity, Dissolved Oxygen, Sea Surface Temperature); Garmin GPSmap76 (Latitude and Longitude); General Oceanic’s flow meters Model 2030R (determine volume sampled by each net); Leica MZ stereomicroscope; LightCycler 480 Real-Time PCR system (Roche Applied Science, USA).
Cornic, M., Smith, B. L., Kitchens, L. L., Alvarado Bremer, J. R., & Rooker, J. R. (2017). Abundance and habitat associations of tuna larvae in the surface water of the Gulf of Mexico. Hydrobiologia. doi:10.1007/s10750-017-3330-0
Cornic, M., & Rooker, J. R. (2018). Influence of oceanographic conditions on the distribution and abundance of blackfin tuna ( Thunnus atlanticus ) larvae in the Gulf of Mexico. Fisheries Research, 201, 1–10. doi:10.1016/j.fishres.2017.12.015