On the relation between schools, clusters of schools, and abundance in pelagic fish stocks

Small pelagic fish are known to aggregate into schools and clusters of schools. It is commonly assumed that the number of such schools and clusters, as well as their size and densities, will vary with the stock abundance. We have carried out a PCA based meta-analysis, using series of acoustic survey data from five different locations in Europe to examine this assumption. The study concluded that there was no discernible relationship between stock abundance and the number of schools seen, or on the clustering of those schools. The study also showed that the number and structure of the school clusters was strongly correlated with the number of schools seen. An increased number of schools in an area tended to be linked with denser clusters (more schools per kilometre) and a higher occupation of the survey area by those clusters. There was also a weaker tendency to find more clusters. It is not clear whether these relationships and the absence of a link to abundance are due to density independence in aggregation patterns or whether such density dependence is only functional at relatively low stock abundance levels. 2001 International Council for the Exploration of the Sea

[1]  D. P. Swain,et al.  Relationships between geographic distribution and abundance of American plaice (Hippoglossoides platessoides) in the southern Gulf of St. Lawrence , 1996 .

[2]  A. F. Sinclair,et al.  Fish distribution and catchability : what is the appropriate measure of distribution ? , 1994 .

[3]  Alec D. MacCall,et al.  Dynamic Geography of Marine Fish Populations , 1990 .

[4]  Pierre Petitgas,et al.  Standard protocols for the analysis of school based data from echo sounder surveys , 2000 .

[5]  M. Iglesias,et al.  Spatio-temporal patterns and morphological characterisation of multispecies pelagic fish schools in the North-Western Mediterranean Sea , 2003 .

[6]  L. Lebart,et al.  Statistique exploratoire multidimensionnelle , 1995 .

[7]  Pierre Fréon,et al.  Dynamics of pelagic fish distribution and behaviour : effects on fisheries and stock assessment , 1999 .

[8]  Ransom A. Myers,et al.  Reducing uncertainty in the biological basis of fisheries management by meta-analysis of data from many populations: a synthesis , 1998 .

[9]  Š.,et al.  SPATIO-TEMPORAL PATTERNS IN PELAGIC FISH SCHOOL ABUNDANCE AND SIZE: A STUDY OF PELAGIC FISH AGGREGATION USING ACOUSTIC SURVEYS FROM SENEGAL TO SHETLAND , 2001 .

[10]  David G. Reid,et al.  Image Analysis Techniques for the Study of Fish School Structure from Acoustic Survey Data , 1993 .

[11]  Alain Hillion,et al.  Narrowband acoustic identification of monospecific fish shoals , 1996 .

[12]  Pierre Petitgas,et al.  Spatial organization of pelagic fish: echogram structure, spatio-temporal condition, and biomass in Senegalese waters , 1996 .

[13]  P. Petitgas.  Biomass-dependent dynamics of fish spatial distributions characterized by geostatistical aggregation curves , 1998 .

[14]  Ole Arve Misund,et al.  Cross-scale observations on distribution and behavioural dynamics of ocean feeding Norwegian spring-spawning herring (Clupea harengus L.) , 1999 .

[15]  G. Swartzman.  Fish school formation and maintenance: a random encounter model , 1991 .

[16]  Jacques Masse,et al.  The structure and spatial distribution of pelagic fish schools in multispecies clusters: an acoustic study , 1996 .

[17]  Werner Stuetzle,et al.  Relating the distribution of pollock schools in the Bering Sea to environmental factors , 1994 .

[18]  Didier Gascuel,et al.  SHADYS (‘simulateur halieutique de dynamiques spatiales’), a GIS based numerical model of fisheries. Example application: The study of a marine protected area , 1999 .

[19]  Marc Mangel,et al.  Search and Stock Depletion: Theory and Applications , 1985 .

[20]  S. Georgakarakos,et al.  Artificial neural networks as a tool for species identification of fish schools , 1996 .

[21]  B. Hambly.  Fractals, random shapes, and point fields , 1994 .

[22]  Noël Diner,et al.  MOVIES-B: an acoustic detection description software. Application to shoal species' classification , 1993 .