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Modelling and Quantitative Methods in Fisheries

Modelling and Quantitative Methods in Fisheries (Hardback)

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Synopsis

With numerous real-world examples, Modelling and Quantitative Methods in Fisheries, Second Edition provides an introduction to the analytical methods used by fisheries' scientists and ecologists. By following the examples using Excel, readers see the nuts and bolts of how the methods work and better understand the underlying principles. Excel workbooks are available for download from CRC Press website. In this second edition, the author has revised all chapters and improved a number of the examples. This edition also includes two entirely new chapters: *Characterization of Uncertainty covers asymptotic errors and likelihood profiles and develops a generalized Gibbs sampler to run a Markov chain Monte Carlo analysis that can be used to generate Bayesian posteriors *Sized-Based Models implements a fully functional size-based stock assessment model using abalone as an example This book continues to cover a broad range of topics related to quantitative methods and modelling. It offers a solid foundation in the skills required for the quantitative study of marine populations.

Explaining important and relatively complex ideas and methods in a clear manner, the author presents full, step-by-step derivations of equations as much as possible to enable a thorough understanding of the models and methods.

Malcolm Haddon is a senior fisheries modeller for CSIRO in Hobart, Tasmania, Australia. Prior to joining CSIRO, Dr. Haddon was an associate professor at the University of Tasmania, head of fisheries at Australian Maritime College, a senior research fellow at the University of Sydney, editor of the New Zealand Journal of Marine and Freshwater Research, and a lecturer at Victoria University of Wellington. He has conducted stock assessments on Tasmanian rock lobster, giant crab, and abalone. Now at CSIRO, he continues to produce stock assessments of abalone but also for an array of Australian Commonwealth fisheries.

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