Aquat. Living Resour.
Volume 22, Number 2, April-June 2009
Fish Stock Assessments Using Surveys and Indicators
Page(s) 193 - 200
Published online 17 June 2009
  • Bouleau M., 2005, Combinaison géostatistique de l'acoustique et des captures dans les campagnes scientifiques de pêche par chalutage. Thèse dr Géostatistique, Ecole Nationale Supérieure des Mines, Paris.
  • Conradsen K., Ersboll B.K., Thyrsted T., 1985, A comparison of min/max autocorrelation factor analysis and ordinary factor analysis. Nordic Symposium in Applied Statistics, Lyngby, pp. 47-56.
  • Cotter J., Mesnil B., Witthames P., Uriarte A., Parker-Humphreys M., 2009, Notes on nine biological indicators estimable from trawl surveys with an illustrative assessment for North Sea cod. Aquat. Living Resour. 22, 135–153. [CrossRef] [EDP Sciences]
  • Desbarats A.J., 2001, Geostatistical modelling of regionalized grain-size distributions using min/max autocorrelation factors. In: Monestiez P., Allard D., Froidevaux R. (Eds.) Geostatistics for Environmental Applications III, Kluwer Academic Publisher, pp. 441–452.
  • Desbarats A.J., Dimitrakopoulos R., 2000, Geostatistical simulation of regionalized pore-size distributions using min/max autocorrelation factors. Math. Geol. 32, 919–942. [CrossRef]
  • Erzini K., 2005, Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables. Fish. Oceanogr. 14, 195–209. [CrossRef]
  • Erzini K., Inejih C.A.O., Stobberup K.A., 2005, An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data. ICES J. Mar. Sci. 62, 353–359. [CrossRef]
  • Hedger, R., McKenzie, E., Heath, M., Wright, P., Scott, B., Gallego, A., Andrews, J. 2004, Analysis of the spatial distribution of mature cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) abundance in the North Sea (1980-1999) using generalised additive models. Fish. Res. 70, 17–25.
  • ICES, 2003, Report of the ICES Advisory Committee on Fishery Management, ICES Coop. Res. Rep. 261.
  • Jennings S., 2005, Indicators to support an ecosystem approach to fisheries. Fish Fish. 6, 212–232.
  • Löfgren K.-G., Ranneby B., Sjöstedt S., 1993, Forecasting the business cycle without using minimum autocorrelation factors. J. Forecasting 12, 481–498. [CrossRef]
  • Pearce K.F., Frid C.L.J., 1999, Coincident changes in four components of the North Sea ecosystem. J. Mar. Biol. Assoc. UK 79, 183–185. [CrossRef]
  • R development Core Team, 2005, R: A language and environment for statistical computing. Vienna, Austria, R Foundation for Statistical Computing. URL
  • Rindorf, A., Lewy, P., 2006, Warm windy winters drive cod north and homing keeps them there. J. Appl. Ecol. 43, 445–453. [CrossRef]
  • Shapiro D.E., Switzer P., 1989, Extracting time trends from multiple monitoring sites. Department of Statistics, Stanford University. Tech. Rep. 132.
  • Solow A.R., 1994, Detecting change in the composition of a multispecies community. Biometrics 50, 556–565. [CrossRef] [PubMed]
  • Switzer P., Green A.A., 1984, Min/max autocorrelation factors for multivariate spatial imaging. Department of Statistics, Stanford University, Tech. Rep. 6.
  • Woillez M., 2007, Contributions géostatistiques à la biologie halieutique. Thèse dr. Géostatistique, Ecole Nationale Supérieure des Mines, Paris.
  • Woillez M., Poulard J-C., Rivoirard J., Petitgas P., Bez N., 2007a, 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]
  • Woillez M., Rivoirard J., Petitgas P., 2007b, Selecting and combining survey-based indices of fish stocks using their correlation in time to make diagnostics of their status. ICES CM 2007/O:07.
  • Woillez M., Rivoirard J., Petitgas P., 2009, Notes on survey-based spatial indicators for monitoring fish populations. Aquat. Living Resour. 22, 155–164. [CrossRef] [EDP Sciences]
  • Zuur A.F., Pierce G.J., 2004, Common trends in Northeast Atlantic squid time series. J. Sea Res. 52, 57–72. [CrossRef]
  • Zuur A.F., Fryer R.J., Jolliffe I.T., Dekker R., Beukema J.J., 2003a, Estimating common trends in multivariate time series using dynamic factor analysis. Environmetrics 14, 665–685. [CrossRef]
  • Zuur A.F., Tuck I.D., Bailey N., 2003b, Dynamic factor analysis to estimate common trends in fisheries time series. Can. J. Fish. Aquat. Sci. 60, 542–552. [CrossRef]

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