Standardizing fishery-dependent catch and effort data in complex fisheries with technology change

Standardizing fishery-dependent catch and effort data in complex fisheries with technology change Standardization of commercial catch and effort data is important in fisheries where standardized abundance indices based on fishery-dependent data are a fundamental input to stock assessments. The goal of the standardization is then to minimize bias due to the confounding of apparent abundance patterns with fishing power. There is a high risk of confounding between fishing power and abundance in fisheries where the fleet has altered their fishing technology over the years. Also, the spatial aspects and the fishing history can be so heterogeneous that any standardization really involves an extrapolation, for example to a hypothetical standard vessel. When the standardization involves an extrapolation, then the appropriate modeling strategy is to build a so-called estimation model, rather than a predictive model. Strategies to build such an estimation model from fishery-dependent data include: pay careful attention to subject matter, and collect information about potential confounding effects to include in the model (putting a high value on the acquisition of data on covariates); model variable catchability at a highly disaggregated scale; aim for realistic coefficients when fitting the model and pay relatively less attention to achieving precision or maximizing explained variance; adopt modern statistical methods to combine data from different sources; and if data are deficient, then apply precautionary allowances. These strategies offer some protection against bias due to confounding, in the absence of formal criteria for identifying the best model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Reviews in Fish Biology and Fisheries Springer Journals

Standardizing fishery-dependent catch and effort data in complex fisheries with technology change

Loading next page...
 
/lp/springer_journal/standardizing-fishery-dependent-catch-and-effort-data-in-complex-ljjvbr0nY6
Publisher
Springer Journals
Copyright
Copyright © 2006 by Springer Science+Business Media B.V.
Subject
Life Sciences; Zoology ; Freshwater & Marine Ecology
ISSN
0960-3166
eISSN
1573-5184
D.O.I.
10.1007/s11160-006-0004-9
Publisher site
See Article on Publisher Site

Abstract

Standardization of commercial catch and effort data is important in fisheries where standardized abundance indices based on fishery-dependent data are a fundamental input to stock assessments. The goal of the standardization is then to minimize bias due to the confounding of apparent abundance patterns with fishing power. There is a high risk of confounding between fishing power and abundance in fisheries where the fleet has altered their fishing technology over the years. Also, the spatial aspects and the fishing history can be so heterogeneous that any standardization really involves an extrapolation, for example to a hypothetical standard vessel. When the standardization involves an extrapolation, then the appropriate modeling strategy is to build a so-called estimation model, rather than a predictive model. Strategies to build such an estimation model from fishery-dependent data include: pay careful attention to subject matter, and collect information about potential confounding effects to include in the model (putting a high value on the acquisition of data on covariates); model variable catchability at a highly disaggregated scale; aim for realistic coefficients when fitting the model and pay relatively less attention to achieving precision or maximizing explained variance; adopt modern statistical methods to combine data from different sources; and if data are deficient, then apply precautionary allowances. These strategies offer some protection against bias due to confounding, in the absence of formal criteria for identifying the best model.

Journal

Reviews in Fish Biology and FisheriesSpringer Journals

Published: Aug 16, 2006

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off