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Marine Biology

, Volume 162, Issue 3, pp 571–593 | Cite as

Foraging ecology of silky sharks, Carcharhinus falciformis, captured by the tuna purse-seine fishery in the eastern Pacific Ocean

  • Leanne M. DuffyEmail author
  • Robert J. Olson
  • Cleridy E. Lennert-Cody
  • Felipe Galván-Magaña
  • Noemi Bocanegra-Castillo
  • Petra M. Kuhnert
Original Paper

Abstract

Diet studies are an essential component of ecosystem-based approaches to fisheries management. In the eastern Pacific Ocean (EPO), the silky shark (Carcharhinus falciformis) is the most common species of shark in the bycatch of the tuna purse-seine fishery. A rare, comprehensive dataset of stomach contents of 786 silky sharks sampled in mostly tropical regions of the EPO (25°N–15°S; 79°W–162°W) during 1992–1994 and 2003–2005 was analyzed via classification tree and quantile regression methodologies to gain insight into its ecosystem role. Results suggest that the silky shark is an opportunistic predator that forages on a variety of prey. Broad-scale spatial and shark size covariates explained the feeding habits of silky sharks captured in sets on floating objects, primarily drifting fish-aggregating devices (FADs). A strong spatial shift in diet was identified by the tree analysis, with different foraging patterns in the eastern (inshore) and western (offshore) regions. Greater proportions of FAD-associated prey than non-FAD-associated prey were observed in the diet throughout the EPO, with the greatest proportion in the offshore region. Thus, silky sharks appear to take advantage of the associative behavior of prey fishes to increase their probability of encountering and capturing prey. Evaluation of prey–predator size relationships showed that maximum prey size increased with increasing silky shark size, but minimum prey size remained relatively constant across the range of shark sizes. Results such as these from spatially oriented analyses of predator feeding habits are essential for populating ecosystem models with space-based food webs, which otherwise suffer from generic representations of food webs.

Keywords

Quantile Regression Prey Size Full Dataset Yellowfin Tuna Eastern Pacific Ocean 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This project was partly funded by Cooperative Agreement NA17RJ1230 between the Joint Institute for Marine and Atmospheric Research (JIMAR) and the US National Oceanic and Atmospheric Administration (NOAA). The views expressed herein are those of the authors and do not necessarily reflect the views of NOAA or any of its subdivisions. This project was also partly supported by a special appropriation of the US Congress in 1992 for research leading to new methods of catching tuna without the incidental capture of dolphins. We also acknowledge the funding support from Commonwealth Scientific and Industrial Research Organization (CSIRO) through the Julius Award that was granted to P. Kuhnert. F. Galván-Magaña was supported by the Instituto Politécnico Nacional [Comisión de Operación y Fomento de Actividades Académicas (COFAA) and Estímulos al Desempeño de los Investigadores (EDI)], and N. Bocanegra-Castillo was supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT). We are grateful to many observers in Ecuador, Venezuela, and Mexico for collecting stomach samples at sea, with the valuable assistance of Inter-American Tropical Tuna Commission (IATTC) staff E. Largacha, H. Pérez, K. Loor, V. Fuentes, C. de la A.-Florencia, A. Basante, W. Paladines, F. Cruz, and C. Maldonado and the captains and crews of numerous purse-seine vessels. Assistance with stomach-content analysis was provided in Ecuador by L. Cedeño, J. Morales, and M. Loor, and in Venezuela by J. Martinez. We also thank IATTC staff members A. Aires-da-Silva, for making the R code and resources available for producing the maps, C. Patnode, for modifying and improving the graphics, and D. Fuller, for assistance with figures. We thank W. Bayliff (IATTC) and J. Young (CSIRO) for their thoughtful, constructive reviews of this manuscript. We are grateful to the Integrated Marine Biogeochemistry and Ecosystem Research (IMBER, formerly GLOBEC) regional program Climate Impacts on Oceanic Top Predators (CLIOTOP) for sponsoring a workshop to develop Classification and Regression Tree (CART) methodologies for analyzing diet data for top predators on a global scale, with special thanks to F. Ménard and J. Young for their leadership.

Supplementary material

227_2014_2606_MOESM1_ESM.pdf (51 kb)
Supplementary material 1 (PDF 50 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Leanne M. Duffy
    • 1
    Email author
  • Robert J. Olson
    • 1
  • Cleridy E. Lennert-Cody
    • 1
  • Felipe Galván-Magaña
    • 2
  • Noemi Bocanegra-Castillo
    • 2
    • 4
  • Petra M. Kuhnert
    • 3
  1. 1.Inter-American Tropical Tuna CommissionLa JollaUSA
  2. 2.Centro Interdisciplinario de Ciencias MarinasInstituto Politécnico NacionalLa PazMéxico
  3. 3.CSIROGlen OsmondAustralia
  4. 4.Centro de Investigaciones Biológicas del Noroeste, S.C.Instituto Politécnico NacionalLa PazMéxico

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