Contributions géostatistiques à la biologie halieutique

Le travail, base sur les donnees de plusieurs campagnes scientifiques de peche, est divise en deux parties independantes. La premiere partie s'inscrit dans la recherche d'une methodologie de suivi des stocks a l'aide d'indicateurs bases sur les seules campagnes scientifiques. Pour cela, on a selectionne des indices decrivant la distribution spatiale d'une population halieutique: centre de gravite, inertie, anisotropie, microstructure, diverses mesures d'aires, etc. Ces indices ont ete choisis en particulier de facon a ne pas dependre d'une delimitation arbitraire du champ, la contribution d'un echantillon a valeur nulle de densite de poissons valant zero. Appliques a la population de merlu europeen du golfe de Gascogne, ces indices permettent de decrire la dynamique spatiale des differents groupes d'âge, ainsi que leur variabilite interannuelle. Par ailleurs, de tels indices spatiaux se revelent etre des indicateurs de la dynamique de la population, ainsi qu'en temoignent des correlations significatives avec des parametres demographiques, observees sur une variete de stocks europeens. De facon a assurer un meilleur suivi de l'etat d'un stock, indices spatiaux et indices biologiques ont enfin ete combines par la methode des MAF (Min-max Autocorrelation Factors), qui vise a reduire le bruit en extrayant les composantes les plus continues dans le temps. Cette technique a ete appliquee sur la morue de mer du Nord et l'anchois du golfe de Gascogne. La seconde partie vise a evaluer, dans l'estimation d'abondances a partir de campagnes acoustiques, la part d'incertitude provenant de l'echantillonnage spatial. L'estimation de l'abondance provenant du signal acoustique enregistre le long de transects, ainsi que de facteurs biologiques mesures en des stations de chalutage, il est necessaire de combiner les incertitudes des deux sources. On a recours pour cela a des simulations geostatistiques conditionnelles de modeles multivaries specifiques (a base de simulations gaussiennes transformees et d'un echantillonneur de Gibbs pour le traitement des nombreuses valeurs nulles de l'acoustique). La methode a ete appliquee au hareng autour des iles Shetland et a l'anchois dans le golfe de Gascogne.

[1]  P. Petitgas Geostatistics for fish stock assessments: a review and an acoustic application , 1993 .

[2]  Stephen J. G. Hall,et al.  Fishing and the Ground-Fish Assemblage Structure in the North-Western North Sea: An Analysis of Long-Term and Spatial Trends , 1996 .

[3]  Pierre Petitgas,et al.  Usefulness of the spatial indices to define the distribution pattern of key life stages: an application to the red mullet (Mullus barbatus) population in the south Tyrrhenian sea , 2007 .

[4]  Ransom A. Myers,et al.  Was an increase in natural mortality responsible for the collapse off northern cod , 1995 .

[5]  A. F. Sinclair Natural mortality of cod (Gadus morhua) in the Southern Gulf of St Lawrence , 2001 .

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

[7]  Xavier Freulon,et al.  Conditional simulation of a Gaussian random vector with non linear and/or noisy observations , 1994 .

[8]  W. C. Leggett,et al.  Effects of Biomass–Range Interactions on Catchability of Migratory Demersal Fish by Mobile Fisheries: An Example of Atlantic Cod (Gadus morhua) , 1991 .

[9]  Paul G. Fernandes,et al.  A consistent approach to definitions and symbols in fisheries acoustics , 2002 .

[10]  A. Rijnsdorp,et al.  Recruitment in flatfish, with special emphasis on North Atlantic species: progress made by the Flatfish Symposia , 2000 .

[11]  Kevin Stokes,et al.  Coping with uncertainty in ecological advice: lessons from fisheries , 2003 .

[12]  R. Sabatier,et al.  Comparative analysis of phylogenetic and fishing effects in life history patterns of teleost fishes , 2000 .

[13]  A conditional simulation of acoustic survey data: advantages and potential pitfalls , 2003 .

[14]  C. J. Kelly,et al.  ‘Cheap and dirty’ fisheries science and management in the North Atlantic , 2006 .

[15]  N. Williamson,et al.  Application of a one-dimensional geostatistical procedure to fisheries acoustic surveys of Alaskan pollock , 1996 .

[16]  Jake C. Rice,et al.  Evaluating fishery impacts using metrics of community structure , 2000 .

[17]  P. Petitgas Sole egg distributions in space and time characterised by a geostatistical model and its estimation variance , 1997 .

[18]  Pierre Petitgas,et al.  Sampling variance of species identification in fisheries-acoustic surveys based on automated procedures associating acoustic images and trawl hauls , 2003 .

[19]  M. Sinclair,et al.  Atlantic Herring: Stock Discreteness and Abundance , 1982, Science.

[20]  J. Chilès,et al.  Geostatistics: Modeling Spatial Uncertainty , 1999 .

[21]  Karim Erzini,et al.  An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data , 2005 .

[22]  E. K. Pikitch,et al.  Ecosystem-Based Fishery Management , 2004, Science.

[23]  John Shepherd,et al.  On the analysis of catch and effort data , 1983 .

[24]  William G. Cochran,et al.  Sampling Techniques, 3rd Edition , 1963 .

[25]  Pierre Petitgas,et al.  Relationships between population spatial occupation and population dynamics , 2006 .

[26]  J. Scandol,et al.  Use of Quality Control Methods to Monitor the Status of Fish Stocks , 2005 .

[27]  D. Demer An estimate of error for the CCAMLR 2000 survey estimate of krill biomass , 2004 .

[28]  J. P. Wheeler,et al.  Interaction Between Stock Area, Stock Abundance, and Catchability Coefficient , 1985 .

[29]  William J. Sutherland,et al.  Aggregation and the `ideal free ` distribution , 1983 .

[30]  M. Heath,et al.  Analysis of the spatial distributions of mature cod (gadus morhua) and haddock (melanogrammus aeglefinus) abundance in the North Sea (1980-1999) using generalised additive models , 2004 .

[31]  Jérôme Pagès,et al.  Multiple factor analysis (AFMULT package) , 1994 .

[32]  Christian Lantuéjoul,et al.  Geostatistical Simulation: Models and Algorithms , 2001 .

[33]  Pierre Petitgas,et al.  Indices for capturing spatial patterns and their evolution in time, with application to European hake (Merluccius merluccius) in the Bay of Biscay , 2007 .

[34]  T. Pitcher,et al.  Towards sustainability in world fisheries , 2002, Nature.

[35]  Richard J. Beamish,et al.  Have there been recent changes in climate? Ask the fish , 2000 .

[36]  Serge M. Garcia,et al.  Global overview of marine fisheries. , 2003 .

[37]  Julie M. Roessig,et al.  Effects of global climate change on marine and estuarine fishes and fisheries , 2004, Reviews in Fish Biology and Fisheries.

[38]  M. Mcgurk,et al.  Natural mortality of marine pelagic fish eggs and larvae: role of spatial patchiness , 1986 .

[39]  Brad deYoung,et al.  On Recruitment and Distribution of Atlantic Cod (Gadus morhua) off Newfoundland , 1993 .

[40]  Darius Bartlett Geostatistics for Estimating Fish Abundance , 2001 .

[41]  Biological Bases for Mixed-Species Fisheries: Species Co-distribution in Relation to Environmental and Biotic Variables , 1988 .

[42]  Milner B. Schaefer Some aspects of the dynamics of populations important to the management of the commercial marine fisheries , 1991 .

[43]  F. Blanchard,et al.  The impact of climate change on the fish community structure of the eastern continental shelf of the Bay of Biscay , 2005 .

[44]  X. Freulon Conditionnement du modele gaussien par des inegalites ou des randomisees , 1992 .

[45]  J. Gil,et al.  Hydrographic mesoscale structures and Poleward Current as a determinant of hake (Merluccius merluccius) recruitment in southern Bay of Biscay , 2000 .

[46]  Daniel Pauly,et al.  Systematic distortions in world fisheries catch trends , 2001, Nature.

[47]  N. Bez,et al.  On the role of sea surface temperature on the spatial distribution of early stages of mackerel using inertiograms , 2000 .

[48]  G. Begg,et al.  Spatial partitioning of relative fishing mortality and spawning stock biomass of Icelandic cod , 2003 .

[49]  J. D. Riley,et al.  Recruitment of sole stocks, Solea solea (L.), in the Northeast Atlantic , 1992 .

[50]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[51]  S. Walsh,et al.  The effect of stock abundance on range contraction of yellowtail flounder (Pleuronectes ferruginea) on the Grand Bank of Newfoundland in the Northwest Atlantic from 1975 to 1995 , 1998 .

[52]  Alain Galli,et al.  Rate of Convergence of the Gibbs Sampler in the Gaussian Case , 2001 .

[53]  A. Zuur,et al.  Dynamic factor analysis to estimate common trends in fisheries time series , 2003 .

[54]  Anthony J. Booth,et al.  Incorporating the spatial component of fisheries data into stock assessment models , 2000 .

[55]  V. Trenkel,et al.  Which community indicators can measure the impact of fishing? A review and proposals , 2003 .

[56]  D. Beare,et al.  Using survey data independently from commercial data in stock assessment: an example using haddock in ICES Division VIa , 2005 .

[57]  W. Ricker Stock and Recruitment , 1954 .

[58]  Carl Walters,et al.  Lessons for stock assessment from the northern cod collapse , 1996, Reviews in Fish Biology and Fisheries.

[59]  E. Simmonds,et al.  Changes in the spatial distribution of autumn spawning herring (Clupea harengus L.) derived from annual acoustic surveys during the period 1984-1996 , 1998 .

[60]  N. Bez,et al.  Transitive geostatistics to characterise spatial aggregations with diffuse limits : an application on mackerel ichtyoplankton , 2001 .

[61]  J. Link,et al.  Fishing effects on spatial distribution and trophic guild structure of the fish community in the Georges Bank region , 2000 .

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

[63]  W. Overholtz,et al.  Causes of Density-Dependent Catchability for Georges Bank Haddock Melanogrammus aeglefinus , 1990 .

[64]  Stephen J. Smith Bootstrap confidence limits for groundfish trawl survey estimates of mean abundance , 1997 .

[65]  John G. Field,et al.  Using size-based indicators to evaluate the ecosystem effects of fishing , 2005 .

[66]  Á. Abella,et al.  Distributional response to variations in abundance over spatial and temporal scales for juveniles of European hake (Merluccius merluccius) in the Western Mediterranean Sea , 2005 .

[67]  C. T. Marshall,et al.  Geographic Responses of Groundfish to Variation in Abundance: Methods of Detection and Their Interpretation , 1994 .

[68]  C. Walters,et al.  Quantitative fisheries stock assessment: Choice, dynamics and uncertainty , 2004, Reviews in Fish Biology and Fisheries.

[69]  J. Casey,et al.  European hake (M. merluccius) in the North-east Atlantic , 1995 .

[70]  Jérôme Pagès,et al.  Inter-laboratory comparison of sensory profiles: methodology and results , 2001 .

[71]  J. Rice Understanding fish habitat ecology to achieve conservation , 2005 .

[72]  Desire L. Massart,et al.  Multiple factor analysis in environmental chemistry , 2005 .

[73]  K. Foote Calibration of acoustic instruments for fish density estimation : a practical guide , 1987 .

[74]  Jean-Charles Poulard Distribution of hake (Merluccius merluccius, Linnaeus, 1758) in the Bay of Biscay and the Celtic sea from the analysis of French commercial data , 2001 .

[75]  Simon Jennings,et al.  Structural change in an exploited fish community: a consequence of differential fishing effects on species with contrasting life histories , 1999 .

[76]  J. Horbowy,et al.  The distribution, stock size and year-class strength of cod in the Southern Baltic in 1981-2001 based on Polish groundfish surveys , 2003 .

[77]  M. Litvak,et al.  Density‐dependent habitat selection and the ideal free distribution in marine fish spatial dynamics: considerations and cautions , 2004 .

[78]  R. Guichet The diet of European hake (Merluccius merluccius) in the northern part of the Bay of Biscay , 1995 .

[79]  Verena Trenkel,et al.  Combining indicator trends to assess ongoing changes in exploited fish communities: diagnostic of communities off the coasts of France , 2005 .

[80]  N. Bez Statistiques individuelles et géostatistique transitive en écologie halieutique , 1997 .

[81]  P. Gutierrez Distribution and abundance of European hake Merluccius merluccius (L.), eggs and larvae in the North East Atlantic waters in 1995 and 1998 in relation to hydrographic conditions , 2004 .

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

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

[84]  G. Barlow,et al.  Surveys of fisheries resources , 2004, Reviews in Fish Biology and Fisheries.

[85]  G. Lawson,et al.  Acoustic surveys in the full monte: simulating uncertainty , 2000 .

[86]  J. Pope,et al.  An investigation of the accuracy of virtual population analysis using cohort analysis , 1972 .

[87]  André E. Punt,et al.  The performance of VPA-based management , 1997 .

[88]  N. Bez,et al.  Indices for capturing spatial pattern and change across years of fish population : an application on European hake ( Merluccius merluccius ) in the Bay of Biscay , 2007 .

[89]  J. Castilla,et al.  The management of fisheries and marine ecosystems , 1997 .

[90]  Michael Pennington,et al.  Assessing the Effect of Intra-Haul Correlation and Variable Density on Estimates of Population Characteristics from Marine Surveys , 1994 .

[91]  Keith Sainsbury,et al.  Impact of fishing on size composition and diversity of demersal fish communities , 2000 .

[92]  E. Trippel Age at Maturity as a Stress Indicator in Fisheries , 1995 .

[93]  P. Walline Geostatistical simulations of eastern Bering Sea walleye pollock spatial distributions, to estimate sampling precision , 2007 .

[94]  J. Caddy Fisheries management in the twenty-first century: will new paradigms apply? , 1999, Reviews in Fish Biology and Fisheries.

[95]  Estimating uncertainty associated with acoustic surveys of spawning hoki (Macruronus novaezelandiae) in Cook Strait, New Zealand , 2004 .

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

[97]  Costas Papaconstantinou,et al.  The general specifications of the MEDITS surveys , 2002 .

[98]  D. Pauly,et al.  Algunos métodos simples para la evaluación de recursos pesqueros tropicales , 1983 .

[99]  Murdoch K. McAllister,et al.  A perspective on the use of spatialized indicators for ecosystem-based fishery management through spatial zoning , 2005 .

[100]  Evaluating the uncertainty of abundance estimates f rom acoustic surveys using geostatistical conditional simulation s , 2006 .

[101]  Peter Tyedmers,et al.  The Future for Fisheries , 2003, Science.

[102]  Michael Pennington,et al.  Assessing the precision of frequency distributions estimated from trawl-survey samples , 2002 .

[103]  V. Trenkel,et al.  Performance of indicators derived from abundance estimates for detecting the impact of fishing on a fish community , 2003 .

[104]  Nicolas Bez Global fish abundance estimation from regular sampling: the geostatistical transitive method , 2002 .