Free Access
Aquat. Living Resour.
Volume 25, Number 1, January-March 2012
Page(s) 1 - 14
Published online 02 April 2012
  • Andersen L.N., 2001, The new Simrad EK60 scientific echosounder system. J. Acoust. Soc. Am. 109, 2336. [Google Scholar]
  • Azarovitz T.R., 1981, A brief historical review of Woods Hole Laboratory trawl survey time series. In: Doubleday, W.G., Rivard, D. (eds.), Bottom Trawl Surveys. Ottawa, Dep. Fisheries and Oceans. Canadian Special Publication of the Fisheries and Aquatic Sciences 58, pp. 62–67. [Google Scholar]
  • Bakun A., Babcock E.A., Santora C., 2009, Regulating a complex adaptive system via its wasp-waist: grappling with ecosystem-based management of the New England herring fishery. ICES J. Mar. Sci. 66, 1768–1775. [CrossRef] [Google Scholar]
  • Barange M., 1994, Acoustic identification, classification and structure of biological patchiness on the edge of the Agulhas Bank and its relation to frontal features. S. Afr. J. Mar. Sci. 14, 333–347. [Google Scholar]
  • Bodholt H., Nes H., Solli H., 1989, A new echosounder system. Proc. Inst. Acoustics, 11, 123–130. [Google Scholar]
  • Cabreira A.G., Tripode M., Madirolas A., 2009, Artificial neural networks for fish-species identification. ICES J. Mar. Sci. 66, 1119–1129. [CrossRef] [Google Scholar]
  • Cushing D.H., 1973, The detection of fish. Pergamon Press, NY. [Google Scholar]
  • De’ath G., 2007, Boosted trees for ecological modeling and prediction. Ecology 88, 243–251. [Google Scholar]
  • De’ath G., Fabricius K.E., 2000, Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81, 3178–3192. [CrossRef] [Google Scholar]
  • Diner N., 2001, Correction on school geometry and density: approach based on acoustic image simulation. Aquat. Living Resour. 14, 211–222. [CrossRef] [EDP Sciences] [Google Scholar]
  • Fablet R., Lefort R., Karoui I., Berger L., Massé J., Scalabrin C., Boucher J.M., 2009, Classifying fish schools and estimating their species proportions in fishery-acoustic surveys. ICES J. Mar. Sci. 66, 1136–1142. [CrossRef] [Google Scholar]
  • Fernandes P.G., 2009, Classification trees for species identification of fish-school echotraces. ICES J. Mar. Sci. 66, 1073–1080. [CrossRef] [Google Scholar]
  • Foote K.G., Knudsen H.P., Vestnes G., MacLennan D.N., Simmonds E.J., 1987, Calibration of acoustic instruments for fish density estimation: A practical guide. ICES Coop. Res. Rep. 44. [Google Scholar]
  • Fréon P., Gerlotto F., Soria M., 1996, Diel variabilityof school structure with special reference to transition periods. ICES J. Mar. Sci. 53, 459–464. [Google Scholar]
  • Fréon P., Misund O.A., 1999, Dynamics of pelagic fish distribution and behaviour: effects on fisheries and stock assessment. Fishing News Books, Blackwell Science Ltd., Oxford. [Google Scholar]
  • Gerlotto F., Jones E., Bez N., Reid D.G., 2010, When good neighbours become good friends: observing small scale structures in fish aggregations using multibeam sonar. Aquat. Living Resour. 23, 143–151. [CrossRef] [EDP Sciences] [Google Scholar]
  • Gerlotto F., Paramo J., 2003, The three-dimensional morphology and internal structure of clupeid schools as observed using vertical scanning multibeam sonar. Aquat. Living Resour. 16, 113–122. [CrossRef] [EDP Sciences] [Google Scholar]
  • Gong Z., Andrews M., Jagannathan S., Patel R., Jech J.M., Makris N.C., Ratilal P., 2010, Low-frequency target strength and abundance of shoaling Atlantic herring (Clupea harengus) in the Gulf of Maine during the Ocean Acoustic Waveguide Remote Sensing 2006 Experiment. J. Acoust. Soc. Am. 127, 104–123. [CrossRef] [PubMed] [Google Scholar]
  • Haralabous J., Georgakarakos S., 1996, Artificial neural networks as a tool for species identification of fish schools. ICES J. Mar. Sci. 53, 173–180. [CrossRef] [Google Scholar]
  • Harris B.P., Stokesbury D.E., 2010, The spatial structure of local surficial sediment characteristics on Georges Bank, USA. Cont. Shelf Res. 30, 1840–1853. [CrossRef] [Google Scholar]
  • Jech J.M., 2011, Interpretation of multi-frequency acoustic data: Effects of fish orientation. J. Acoust. Soc. Am. 129, 54–63. [CrossRef] [PubMed] [Google Scholar]
  • Jech J.M., Michaels W.L., 2006, A multifrequency method to classify and evaluate fisheries acoustics data. Can. J. Fish. Aquat. Sci. 63, 2225–2235. [Google Scholar]
  • Jech J.M., Michaels W., Overholtz W., Gabriel W., Azarovitz T., Ma D., Dwyer K., Yetter R., 2000, Fisheries acoustic surveys in the Gulf of Maine and on Georges Bank at the Northeast Fisheries Science Center. In: Proc. 6th International Conference on Remote Sensing for Marine and Coastal Environments. 1–3 May, Charleston, South Carolina, Veridian ERIM International, Ann Arbor, Michigan, pp. 168–175. [Google Scholar]
  • Kelly K.H., Moring J.R., 1986, species profiles: life histories and environmental requirements of coastal fishes and invertebrates (North Atlantic)- Atlantic Herring. U.S. Fish Wildl. Serv. Biol. Rep. 82, 22. [Google Scholar]
  • Kieser R., Mulligan T.J., Richards L.J., Leaman B.M., 1993, Bias correction of rockfish school cross-section widths from digitized echo sounder data. Can. J. Fish. Aquat. Sci. 50, 1801–1811. [CrossRef] [Google Scholar]
  • Korneliussen R.J., Heggelund Y., Eliassen I.K., Johansen G.O., 2009, Acoustic species identification of schooling fish. ICES J. Mar. Sci. 66, 1111–1118. [CrossRef] [Google Scholar]
  • Lawson G.L., Barange M., Fréon P., 2001, Species identification of pelagic fish schools on the South African continental shelf using acoustic descriptors and ancillary information. ICES J. Mar. Sci. 58, 275–287. [Google Scholar]
  • Lefeuvre P., Rose G.A., Gosine R., Hale R., Pearson W., Khan R., 2000, Acoustic species identification in the northwest Atlantic using digital image processing. Fish. Res. 47, 137–147. [CrossRef] [Google Scholar]
  • MacLennan D.N., Fernandes P.G., Dalen J., 2002, A consistent approach to definitions and symbols in fisheries acoustics. ICES J. Mar. Sci. 59, 365–369. [Google Scholar]
  • Nakamura T., Hamano A., 2009, Seasonal differences in the vertical distribution pattern of Japanese jack mackerel, Trachurus japonicus: changes according to age? ICES J. Mar. Sci. 66, 1289–1295. [Google Scholar]
  • Nero R.W., Magunson J.J., 1989, Characterization of patches along transects using high-resolution 70-kHz integrated acoustic data. Can. J. Fish. Aquat. Sci. 46, 2056–2064. [Google Scholar]
  • Óskarsson G.J., Gudmundsdottir A., Sigurdsson T., 2009, Variation in spatial distribution and migration of Icelandic summer-spawning herring. ICES J. Mar. Sci. 66, 1762–1767. [CrossRef] [Google Scholar]
  • Óskarsson G.J., Taggart C.T., 2009, Spawning time variation in Icelandic summer-spawning herring (Clupea harengus). Can. J. Fish. Aquat. Sci. 66, 1666–1681. [CrossRef] [Google Scholar]
  • Overholtz W.J., 2002, The Gulf of Maine-Georges Bank Atlantic herring (Clupea harengus): spatial pattern analysis of the collapse and recovery of a large marine fish complex. Fish. Res. 57, 237–254. [CrossRef] [Google Scholar]
  • Overholtz W.J., Jech J.M., Michaels W.L., Jacobson L.D., Sullivan P.J., 2006, Empirical comparisons of survey designs in acoustic surveys of Gulf of Maine-Georges Bank Atlantic herring. J. Northw. Atl. Fish. Sci. 36, 127–144. [CrossRef] [Google Scholar]
  • Paramo J., Gerlotto F., Oyarzun C., 2010, Three dimensional structure and morphology of pelagic fish schools. J. Appl. Ichthyol. 26, 853–860. [Google Scholar]
  • Petitgas P., Levenez J.J., 1996, Spatial oranisiations of pelagic fish: echogram strucure, spatio-temporal condition, and biomass in Senegalese waters. ICES J. Mar. Sci. 53, 147–153. [CrossRef] [Google Scholar]
  • Petitgas P., Massé J., Beillois P., Labarbier E., LeCann A., 2003, Sampling variance of species identification in fisheries-acoustic surveys based on automated procedures associating acoustic images and trawls. ICES J. Mar. Sci. 60, 437–445. [CrossRef] [Google Scholar]
  • Pitcher T.J., 2001, Fish Schooling. In: Steele J.H., Turekian K.K., Thorpe S.A. (eds.), Encyclopedia of Ocean Sciences, Academic Press, pp. 975–987. [Google Scholar]
  • Pitcher T.J., Parrish J.K., 1993, Functions of shoaling behaviour in teleosts. In: Pitcher T.J. (ed.), Behaviour of Teleost Fishes, Chapman and Hall, London, pp. 363–439. [Google Scholar]
  • R: A Language and Environment of Statistical Computing, 2009, R Foundation for Statistical Computing, Vienna, Austria, [Google Scholar]
  • Reid D.G. (ed.), 2000. Report on echo trace classification. ICES Coop. Res. Rep. 238. [Google Scholar]
  • Reid D., Scalabrin C., Petitgas P., Massé J., Aukland R., Carrera P., Georgakarakos S., 2000, Standard protocols for the analysis of school based data from echo sounder surveys. Fish. Res. 47, 125–136. [Google Scholar]
  • Reid R.N., Cargnelli L.M., Griesbach S.J., Packer D.B., Johnson D.L., Zetlin C.A., Morse W.W., Berrien P.L., 1999, Atlantic herring, Clupea harengus, life history and habitat characteristics. NOAA Technical Memorandum NMFS-NE-126. [Google Scholar]
  • Richards L.J., Kieser R., Mulligan T.J., Candy J.R., 1991, Classification of fish assemblages based on echo integration surveys. Can. J. Fish. Aquat. Sci. 48, 1264–1272. [CrossRef] [Google Scholar]
  • Robotham H., Castillo J., Bosch P., Perez-Kallens J., 2011, A comparison of multi-class support vector machine and classification three methods for hydroacoustic classification of fish-schools in Chile. Fish. Res. 111, 170–176. [CrossRef] [Google Scholar]
  • Secor D.H., Kerr L.A., Cadrin S.X., 2009, Connectivity effects on productivity, stability, and persistence in a herring metapopulation model. ICES J. Mar. Sci. 66, 1726–1732. [CrossRef] [Google Scholar]
  • Skaret G., Nøttestad L., Fernö A., Johannessen A., Axelsen B.E., 2003, Spawning of herring: day or night, today or tomorrow. Aquat. Living Resour. 16, 299–306. [CrossRef] [EDP Sciences] [Google Scholar]
  • Stephenson R.L., Melvin G.D., Power M.J., 2009, Population integrity and connectivity in northwest Atlantic herring: a review of assumptions and evidence. ICES J. Mar. Sci. 66, 1733–1739. [CrossRef] [Google Scholar]
  • Stevenson D.K., Scott M.L., 2005, Essential Fish Habitat Source Document: Atlantic herring, Clupea harengus, life history and habitat characteristics. NOAA Technical Memorandum NMFS-NE-192. U.S. Dept. Commerce, Washington, DC. [Google Scholar]
  • Tupper M.H., Anthony V.C., Chenoweth S.B., MacCluen H.A., 1998, Biology and assessment of Gulf of Maine herring stocks. Gulf of Maine Aquarium, Portland, Maine. [Google Scholar]
  • Vabø R., Skaret G., 2008, Emerging school structures and collective dynamics in spawning herring: a simulation study. Ecol. Model. 214, 125–140. [CrossRef] [Google Scholar]
  • Wheeler J.P., Purchase C.F., Macdonald P.D.M., Fill R., Jacks L., Wang H., Ye C., 2009, Temporal changes in maturation, mean length-at-age, and condition of spring-spawning Atlantic herring (Clupea harengus) in Newfoundland waters. ICES J. Mar. Sci. 66, 1800–1807. [CrossRef] [Google Scholar]
  • Woillez M., Poulard J.-C., Rivoirard J., Petitgas P., Bez N., 2007, Indices for capturing spatial patterns and their evolution in time, with application to European hake (Merluccius merluccius) in the Bay of Biscay. ICES J. Mar. Sci. 64, 537–550. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.