We report statistically significant genetic structure among samples of Greenland halibut (Reinhardtius hippoglossoides), rejecting the null hypothesis of panmixia in the North Atlantic. The species appears instead to be subdivided into partially isolated populations, with some evidence for isolation by distance. However, there is a dichotomy between transatlantic sample comparisons and those within a regional current system, even when geographic distance is similar. Calculating geographic distance along the flow of ocean currents gave a more linear correlation with genetic differentiation than straight-line geographic distances, suggesting that gene flow follows ocean currents. We hypothesize that gene flow is mediated by drift of eggs and larvae with ocean currents, a hypothesis that is consistent with the extended pelagic phase of Greenland halibut larvae. This implies an important role for ocean currents in shaping the genetic structure of this and potentially other deep-sea species.
The distribution of cod along the Norwegian coast and in fjords from 62°N north to the Russian border was examined using data from annual trawl surveys carried out between 1995 and 2001. Based on differences in growth zones of the otoliths, cod are traditionally classified into two types: Northeast Arctic cod and coastal cod. Both types were found throughout the area investigated. The catch rate of both increased northwards and from offshore to inshore. In a statistical model of length at age, abiotic factors such as area and year of capture explained more of the variance than biotic factors such as sex, stage of maturity, and type of cod. Length at age increased in a southward direction and was higher for cod captured offshore than for those captured inshore. In a statistical model of the proportion mature at age, area, type, and year of capture explained more of the variance than sex and depth of capture. On average, coastal cod attained 50% maturity (M50) more than a year younger than a year younger than Northeast Arctic cod attained maturity. Although there were relatively large differences in age at maturity between neighbouring areas, age at maturity was lowest in the south and inshore, and in general, lower inshore than offshore. As genetic analysis clearly indicates that cod in the study area consist of at least two genetically separated stocks, it is likely that the differences found here in age at M50 might have a genetic component.
The age structure of a fish population has important implications for recruitment processes and population fluctuations, and is a key input to fisheries-assessment models. The current method of determining age structure relies on manually reading age from otoliths, and the process is labor intensive and dependent on specialist expertise. Recent advances in machine learning have provided methods that have been remarkably successful in a variety of settings, with potential to automate analysis that previously required manual curation. Machine learning models have previously been successfully applied to object recognition and similar image analysis tasks. Here we investigate whether deep learning models can also be used for estimating the age of otoliths from images. We adapt a pre-trained convolutional neural network designed for object recognition, to estimate the age of fish from otolith images. The model is trained and validated on a large collection of images of Greenland halibut otoliths. We show that the model works well, and that its precision is comparable to documented precision obtained by human experts. Automating this analysis may help to improve consistency, lower cost, and increase the extent of age estimation. Given that adequate data are available, this method could also be used to estimate age of other species using images of otoliths or fish scales.
Impacts of climate change on ocean productivity sustaining world fisheries are predominantly negative but vary greatly among regions. We assessed how 39 fisheries resources-ranging from data-poor to data-rich stocks-in the North East Atlantic are most likely affected under the intermediate climate emission scenario RCP4.5 towards 2050. This region is one of the most productive waters in the world but subjected to pronounced climate change, especially in the northernmost part. In this climate impact assessment, we applied a hybrid solution combining expert opinions (scorings)-supported by an extensive literature review-with mechanistic approaches, considering stocks in three different large marine ecosystems, the North, Norwegian and Barents Seas. This approach enabled calculation of the directional effect as a function of climate exposure and sensitivity attributes (life-history schedules), focusing on local stocks (conspecifics) across latitudes rather than the species in general. The resulting synopsis (50-82°N) contributes substantially to global assessments of major fisheries (FAO, The State of World Fisheries and Aquaculture, 2020), complementing related studies off northeast United States (35-45°N) (Hare et al.,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.