Spatio-temporal analysis of commercial trawler data using General Additive models: patterns of Loliginid squid abundance in the north-east Atlantic
General Additive Model (GAM) fitting techniques have been employed to understand and predict cephalopod abundance variations in the north-east Atlantic using data on commercial fisheries and geographic and climatic variables. Spatial patterns were studied for general average, seasonal average and mo...
| Published in: | ICES Journal of Marine Science |
|---|---|
| Main Authors: | , , |
| Format: | Text |
| Language: | English |
| Published: |
Oxford University Press
2002
|
| Subjects: | |
| Online Access: | http://icesjms.oxfordjournals.org/cgi/content/short/59/3/633 https://doi.org/10.1006/jmsc.2001.1178 |
| Summary: | General Additive Model (GAM) fitting techniques have been employed to understand and predict cephalopod abundance variations in the north-east Atlantic using data on commercial fisheries and geographic and climatic variables. Spatial patterns were studied for general average, seasonal average and monthly recruitment abundance. The capability of this method to model abundance in time and space was tested by comparing observed and calculated Catch per Unit of Effort for a 1° longitude by 0.5° latitude rectangular grid. The influence of the explanatory variables on Loliginid abundance was clearly shown. Climatic variable effects change with time scale. They vary during the year and are mainly important during the pre-recruitment month. GAM allows explanation of the main part of seasonal abundance variations of these species in time and space. GAM also provides the first means of predicting the main recruitment peak area by using previous-month climatic variables. This article demonstrates the advantages of using commercial-fisheries data for ecological studies. Copyright 2002 Published by Elsevier Science Ltd on behalf of International Council for the Exploration of the Sea |
|---|