Development of Abundance Indices for Atlantic Cod and Cusk in the Coastal Gulf of Maine from their Bycatch in the Lobster Fishery

• Published in: North American Journal of Fisheries Management
• Main Authors: Zhang, Chongliang, Chen, Yong
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2015
• Subjects: atlantic cod; Gadus morhua
• Online Access: http://dx.doi.org/10.1080/02755947.2015.1043413; https://afspubs.onlinelibrary.wiley.com/doi/pdf/10.1080/02755947.2015.1043413

Abstract Limited information is available about the abundance of Atlantic Cod Gadus morhua and Cusk Brosme brosme in the coastal Gulf of Maine because the presence of lobster traps limits commercial fishing and surveys for these species. We developed abundance indices for Atlantic Cod and Cusk from bycatch data obtained in a lobster sea sampling program. We applied generalized linear models (GLMs) to standardize Atlantic Cod and Cusk bycatch rates. The CPUE data, measured as the count of Atlantic Cod and Cusk observed per trap haul, are characterized by an extremely skewed distribution with a high percentage of zero observations. Two general approaches were applied to tackle the zero‐dominated data: modeling with different error distributions and aggregating data over spatial scales. We evaluated eight models: binomial, Poisson, negative binomial, Tweedie model, hurdle model (also referred to as the delta approach) with Poisson and negative binomial distribution, and zero‐inflated model with Poisson and negative binomial distribution. The data were aggregated using six grids ranging from 0.01 to 0.5 geological degrees (0.6–30 nautical miles). The standardized CPUE showed a gradual decline from 2006 to 2011, except for 2009 when a slight increase occurred for Atlantic Cod, and a general decline from 2006 to 2010 followed by an increase in 2011 for Cusk. The standardized CPUEs were consistent, in general, among the models and among different spatial aggregation scenarios, suggesting that the CPUE standardization is robust with respect to choices of data aggregation and statistical models. This study highlights the feasibility of developing abundance indices based on bycatch data for monitoring fish stock dynamics in data‐limited regions. Received September 17, 2014; accepted April 16, 2015