Regional growth estimates of Atlantic cod, Gadus morhua: Applications of the maximum likelihood GROTAG model to tagging data in the Gulf of Maine (USA/Canada) region

Tallack, Shelly M. L.

doi:10.1016/j.fishres.2009.05.014

Cited by 20 publications

(17 citation statements)

References 24 publications

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“…Reference lengths for α and β which are well represented by the length distribution of the tagging data should be chosen (Francis, 1988a). In our study, the 5th percentile value of L 1 measurements was adopted for α and the 95 th percentile value of L 1 measurements was adopted for β (as in Tallack, 2009; see also Mion et al., 2020).…”

Section: Methodsmentioning

confidence: 99%

“…The GROTAG model was selected since it incorporates individual variation in growth rate, is suitable for handling large datasets (Tallack, 2009) and has been successfully applied to tagging data to estimate growth rates of cod (McQueen et al., 2019; Mion et al., 2020; Tallack, 2009).…”

Section: Methodsmentioning

confidence: 99%

“…By contrast, tagging methods provide valid data for length‐based growth modelling for many fish families, including gadoids (e.g. cod; McQueen et al., 2019; Shackell et al., 1997; Tallack, 2009). Those data have also been integrated into stock assessment as in the case of some tuna species (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Multidecadal changes in fish growth rates estimated from tagging data: A case study from the Eastern Baltic cod (Gadus morhua, Gadidae)

Mion

Haase²,

Hemmer‐Hansen

et al. 2020

Fish and Fisheries

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Long time series of reliable individual growth estimates are crucial for understanding the status of a fish stock and deciding upon appropriate management. Tagging data provide valuable information about fish growth, and are especially useful when age‐based growth estimates and stock assessments are compromised by age‐determination uncertainties. However, in the literature there is a lack of studies assessing possible changes in growth over time using tagging data. Here, data from tagging experiments performed in the Baltic Sea between 1971 and 2019 were added to those previously analysed for 1955–1970 to build the most extensive tagging dataset available for Eastern Baltic cod (Gadus morhua, Gadidae), a threatened stock with severe age‐determination problems. Two length‐based methods, the GROTAG model (based on the von Bertalanffy growth function) and a Generalized Additive Model, were used to assess for the first time the potential long‐term changes in cod growth using age‐independent data. Both methods showed strong changes in growth with an increase until the end of the 1980s (8.6–10.6 cm/year for a 40 cm cod depending on the model) followed by a sharp decline. This study also revealed that the current growth of cod is the lowest observed in the past 7 decades (4.3–5.1 cm/year for a 40 cm cod depending on the model), indicating very low productivity. This study provides the first example of the use of tagging data to estimate multidecadal changes in growth rates in wild fish. This methodology can also be applied to other species, especially in those cases where severe age‐determination problems exist.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Multidecadal changes in fish growth rates estimated from tagging data: A case study from the Eastern Baltic cod (Gadus morhua, Gadidae)

Mion

Haase²,

Hemmer‐Hansen

et al. 2020

Fish and Fisheries

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“…The two management units consist of: 1) cod from Georges Bank, offshore of Cape Cod, and in the waters of southern New England; and 2) a group consisting of cod from the western, central, and eastern GoM (Fig 1). However, genetic data [23–28], differences in growth rates [29,30], timing of spawning [19,31], larval dispersal patterns [32,33], movement patterns [18,34–36], spawning site fidelity [37–39], and differences in life history strategy [40,41] all confirm that there is biocomplexity in US cod that conflicts with the stock designations (for a review see REF 20). The misalignment of stock designations with this biocomplexity is implicated as a contributing factor in the failure of these stocks to rebuild despite decades of intensive management [42].…”

Section: Introductionmentioning

confidence: 99%

Adaptive genetic variation underlies biocomplexity of Atlantic Cod in the Gulf of Maine and on Georges Bank

et al. 2019

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Atlantic cod ( Gadus morhua ) populations in the Gulf of Maine (GoM) are at a fraction of their historical abundance, creating economic hardships for fishermen and putting at risk the genetic diversity of the remaining populations. An understanding of the biocomplexity among GoM populations will allow for adaptive genetic diversity to be conserved to maximize the evolutionary potential and resilience of the fishery in a rapidly changing environment. We used restriction-site-associated DNA sequencing (RADseq) to characterize the population structure and adaptive genetic diversity of five spawning aggregations from the western GoM and Georges Bank. We also analyzed cod caught in the eastern GoM, an under-sampled area where spawning aggregations have been extirpated. Using 3,128 single nucleotide polymorphisms (SNPs), we confirmed the existence of three genetically separable spawning groups: (1) winter spawning cod from the western GoM, (2) spring spawning cod, also from the western GoM, and (3) Georges Bank cod. Non-spawning cod from the eastern GoM could not be decisively linked to either of the three spawning groups and may represent a unique component of the resource, a mixed sample, or cod from other unsampled source populations. The genetic differentiation among the three major spawning groups was primarily driven by loci putatively under selection, particularly loci in regions known to contain genomic inversions on linkage groups (LG) 7 and 12. These LGs have been found to be linked to thermal regime in cod across the Atlantic, and so it is possible that variation in timing of spawning in western GoM cod has resulted in temperature-driven adaptive divergence. This complex population structure and adaptive genetic differentiation could be crucial to ensuring the long-term productivity and resilience of the cod fishery, and so it should be considered in future management plans.

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“…Furthermore, results of this study shed some light on the connectivity between GOM cod stock and the two neighbor stocks (i.e., GB stock on the south and the 4× stock on the east). Limited inter‐stock mixing keeps these stocks distinct from each other in demographics and genetics (Miller and Tallack, ; Tallack, ). The limited exchange of adult cod is often attributed to natal homing or spawning site fidelity, despite a lack of the underlying mechanisms.…”

Section: Discussionmentioning

confidence: 99%

Evaluating spatio‐temporal variability in the habitat quality of Atlantic cod (Gadus morhua) in the Gulf of Maine

Guan

Chen

Wilson

2016

Fisheries Oceanography

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Reduced abundance and contracted spatial distribution of Atlantic cod, Gadus morhua, in the Gulf of Maine (GOM) may indicate large spatio‐temporal variation in their habitat quality. Season‐specific Habitat Suitability Index (HSI) models were developed to quantify such variation in the offshore GOM management area. Data used were non‐zero cod catch rates with calibrations from the Northeast Fisheries Science Center (NEFSC) spring and fall bottom trawl surveys over the period 1982–2013 and key physical environmental variables including depth, bottom temperature, bottom salinity and sediment types. Significant declines were found in the average HSI across the study area in the springs of early 2000s and 2010s. These low average HSI values coincide with reduced age‐1 recruitment of GOM cod stock after the mid‐1990s. Moreover, the western coastal areas of the GOM generally exhibited higher average HSI values than the eastern coastal areas, whereas the offshore areas always had the lowest average HSI. Relatively higher cod survey catch rates in the western GOM may imply positive influences of environmental controls on the distribution of GOM cod.

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Regional growth estimates of Atlantic cod, Gadus morhua: Applications of the maximum likelihood GROTAG model to tagging data in the Gulf of Maine (USA/Canada) region

Cited by 20 publications

References 24 publications

Multidecadal changes in fish growth rates estimated from tagging data: A case study from the Eastern Baltic cod (Gadus morhua, Gadidae)

Multidecadal changes in fish growth rates estimated from tagging data: A case study from the Eastern Baltic cod (Gadus morhua, Gadidae)

Adaptive genetic variation underlies biocomplexity of Atlantic Cod in the Gulf of Maine and on Georges Bank

Evaluating spatio‐temporal variability in the habitat quality of Atlantic cod (Gadus morhua) in the Gulf of Maine

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