Geostatistics for Estimating Fish Abundance

Geostatistics is a branch of spatial statistics that was originally developed for the mining industry. The technique is now widely recognised as an important tool for the estimation of the abundance and distribution of natural resources. However, new developments have been required to extend its application to fisheries science, particularly in variogram estimation. This important new title describes the fundamentals of geostatistics in terms more familiar to life-scientists, and uses case studies on seven commercially important fish stocks to demonstrate its application to fisheries survey data. Comprehensive and practical advice is given on how this new method can be used to estimate the abundance (with an appropriate measure of precision) of fish stocks worldwide. Geostatistics for Estimating Fish Abundance will be of vital interest to fisheries research scientists, marine biologists, oceanographers, marine and fish ecologists, environmental scientists and experts involved in the assessment of natural animal resources.The book has been developed as a result of studies carried out by a collaborative team of international researchers expert in this area with financial support from the Commission of the European Communities, AIR specific RTD programme.J. Rivoirard and N. Bez are at the Centre de G_ostatistique de Fontainebleau, Ecole des Mines de Paris, France, J. Simmonds and P. Fernandes are at the FRS Marine Laboratory, Aberdeen, UK and K. Foote is at the Institute of Marine Research, Bergen, Norway and at Woods Hole Oceanographic Institution, USA.

J. Rivoirard is at the Centre de Géostatistique de Fontainebleau, Ecole des Mines de Paris, France.

J. Simmonds is at the FRS Marine Laboratory, Aberdeen, UK.

K. G. Foote is at the Institute of Marine Research, Bergen, Norway; and at Woods Hole Oceanographic Institution, USA.

P. Fernandes is at the FRS Marine Laboratory, Aberdeen, UK.

N. Bez is at the Centre de Géostatistique de Fontainebleau, Ecole des Mines de Paris, France.