PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The role of predation by harp seals (Phoca groenlandica) in the collapse and non-recovery of northen Gulf of St. Lawrence cod (Gadus morhua)
Emmanuel Chassot, Daniel Duplisea, Mike Hammill, Andrea Caskenette, Nicolas Bousquet, Yvan Lambert and Gary Stenson
Marine Ecology Progress Series 2009.

Abstract

A statistical catch-at-age model was developed to assess the effects of predation by the northwest Atlantic harp seal population on Northern Gulf of St. Lawrence (NGSL) cod by estimating the relative importance of different sources of mortality that affected the stock during a period of collapse and non-recovery. Cod recruitment at age 1 is modeled via a non-linear stock-recruitment relationship based on total egg production and accounts for changes in female length-at-maturity and cod condition. Natural mortality other than seal predation also depends on cod condition used as an integrative index of changes in environmental conditions.The linkage between seals and cod is modeled through a multi-age functional response that was derived from the reconstruction of the seal diet using morphometric relationships and stomach contents of more than 200 seals collected between 1998 and 2001.The model was fitted following a maximum likelihood estimation approach to a scientific survey abundance index (1984-2006). Model results show that the collapse of the Northern Gulf of St. Lawrence cod stock was mainly due to the combination of high fishing mortality rates and poor environmental conditions in the early to mid-1990s contributing to the current state of recruitment overfishing.The increase in harp seal abundance during 1984-2006 was reflected by an increase in predation mortality for the young cod age-classes targeted by seals. Although current levels of predation mortality affect cod spawning biomass, the lack of recovery of the NGSL cod stock seems mainly due to the situation of strong overfishing.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5369
Deposited By:Nicolas Bousquet
Deposited On:31 March 2009