Evolution in salmon life-history induced by direct and indirect effects of fishing

Understanding the drivers of evolution is a fundamental aim in biology. However, identifying the evolutionary impacts of human activities, both direct and indirect, is challenging because of lack of temporal data and limited knowledge of the genetic basis of most traits1. Atlantic salmon is a species exposed to intense anthropogenic pressures during its anadromous life cycle. Previous research has shown that salmon age at maturity has evolved towards earlier maturation over the last 40 years, with an 18% decrease in the allele associated with late maturation at the large-effect vgll3 locus; but the drivers of this change remain unknown. Here, we link genetic and phenotypic changes in a large Atlantic salmon population with salmon prey species biomass in the Barents Sea, temperature, and fishing effort in order to identify drivers of age at maturity evolution. We show that age at maturity evolution is associated with two different types of fisheries induced evolution acting in opposing directions: an indirect effect linked with commercial harvest of a salmon prey species (capelin) at sea (selection against late maturation), and a direct effect due to temporal changes in net fishing pressure in the river (surprisingly, selection against early maturation). Although the potential for direct and indirect evolutionary effects of fishing have been acknowledged, empirical evidence for induced changes at the genetic level has been lacking. As capelin are primarily harvested to produce fish meal and oil for aquaculture, we hereby identify an indirect path by which Atlantic salmon aquaculture may negatively affect wild populations.

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Genetic coupling of life-history and aerobic performance in juvenile Atlantic salmon

10.1101/2021.08.23.457324 ◽

2021 ◽

Author(s):

Jenni M. Prokkola ◽

Eirik R Åsheim ◽

Sergey Morozov ◽

Paul Bangura ◽

Jaakko Erkinaro ◽

...

Keyword(s):

Life History ◽

Atlantic Salmon ◽

Metabolic Rate ◽

Aerobic Performance ◽

Age At Maturity ◽

Life History Variation ◽

Early Maturation ◽

Genomic Regions ◽

Late Maturation

1. The physiological underpinnings of life history adaptations in ectotherms are not well understood. Theories suggest energy metabolism influences life history variation via modulation of resource acquisition. However, the genetic basis of this relation and its dependence on ecological conditions, such as food availability, have rarely been characterized, despite being critical to predicting the responses of populations to environmental changes. 2. The Atlantic salmon (Salmo salar) is an emerging wild model species for addressing these questions; strong genetic determination of age-at-maturity at two unlinked genomic regions (vgll3 and six6) enables the use of complex experimental designs and tests of hypotheses on the physiological and genetic basis of life-history trait variation. 3. In this study, we crossed salmon to obtain individuals with all combinations of late and early maturation genotypes for vgll3 and six6 within full-sib families. Using more than 250 juveniles in common garden conditions, we tested (i) whether metabolic phenotypes (i.e., standard and maximum metabolic rates, and absolute aerobic scope) were correlated with the age-at-maturity genotypes and (ii) if high vs. low food availability modulated the relationship. 4. We found that salmon with vgll3 early maturation genotype had a higher aerobic scope and maximum metabolic rate, but not standard metabolic rate, compared to salmon with vgll3 late maturation genotype. This suggests that physiological or structural pathways regulating maximum oxygen supply or demand are potentially important for the determination of age-at-maturity in Atlantic salmon. 5. Vgll3 and six6 exhibited physiological epistasis, whereby maximum metabolic rate significantly decreased when late maturation genotypes were present concurrently in both loci compared to other genotype combinations. 6. The growth of the feed restricted group decreased substantially compared to the high food group. However, the effects of life-history genomic regions were similar in both feeding regimes, indicating a lack of genotype-by-environment interactions. 7. Our results indicate that aerobic performance of juvenile salmon may affect their age-at-maturity. The results may help to better understand the mechanistic basis of life-history variation, and the metabolic constrains on life-history evolution.

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The use of historical catch data to trace the influence of climate on fish populations: examples from the White and Barents Sea fisheries in the 17th and 18th centuries

ICES Journal of Marine Science ◽

10.1016/j.icesjms.2005.02.011 ◽

2005 ◽

Vol 62 (7) ◽

pp. 1426-1435 ◽

Cited By ~ 21

Author(s):

Dmitry L. Lajus ◽

Julia A. Lajus ◽

Zoya V. Dmitrieva ◽

Alexei V. Kraikovski ◽

Daniel A. Alexandrov

Keyword(s):

Atlantic Salmon ◽

Gadus Morhua ◽

Statistical Data ◽

Barents Sea ◽

Fishing Effort ◽

Temperature Data ◽

Average Weight ◽

Historical Records ◽

Formal Statistical Analysis

Abstract We analysed catch records of Atlantic salmon (Salmo salar), cod (Gadus morhua), and halibut (Hippoglossus hippoglossus and Reinhardtius hippoglossoides) from the 17th and 18th centuries from several locations of the Barents and White Seas areas. Historical records, found in Russian archives, allow analysis of long-term series of catches, and sometimes of the average weight of the fish. In total, we obtained data on catches of salmon for 51 years (for the period from 1615 to 1772) and of cod and halibut for 33 years (for the period from 1710 to 1793). These data are comparable with respect to fishing effort within the series. The data on Atlantic salmon are also comparable with statistical data for the period 1875–1915. We found notable fluctuations in catches and sometimes in the average weight of salmon. There was also fluctuation in catches of cod and halibut. Both observational comparison of catch series and temperature data and formal statistical analysis showed that catches tended to decrease during relatively colder periods.

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Extraction of sea temperature in the Barents Sea by a scale space multiresolution method – prospects for Atlantic salmon

Journal of Applied Statistics ◽

10.1080/02664763.2016.1252731 ◽

2016 ◽

Vol 44 (13) ◽

pp. 2317-2336 ◽

Cited By ~ 2

Author(s):

Leena Pasanen ◽

Päivi Laukkanen-Nevala ◽

Ilkka Launonen ◽

Sergey Prusov ◽

Lasse Holmström ◽

...

Keyword(s):

Atlantic Salmon ◽

Barents Sea ◽

Scale Space ◽

Sea Temperature ◽

The Barents Sea

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Distribution of rorquals and Atlantic cod in relation to their prey in the Norwegian high Arctic

Polar Biology ◽

10.1007/s00300-021-02835-2 ◽

2021 ◽

Author(s):

Hiroko K. Solvang ◽

Tore Haug ◽

Tor Knutsen ◽

Harald Gjøsæter ◽

Bjarte Bogstad ◽

...

Keyword(s):

Prey Species ◽

Barents Sea ◽

Atlantic Cod ◽

Spatial Association ◽

High Arctic ◽

Humpback Whales ◽

Predatory Fish ◽

Detection Range ◽

Minke Whales ◽

Acoustic Methods

AbstractRecent warming in the Barents Sea has led to changes in the spatial distribution of both zooplankton and fish, with boreal communities expanding northwards. A similar northward expansion has been observed in several rorqual species that migrate into northern waters to take advantage of high summer productivity, hence feeding opportunities. Based on ecosystem surveys conducted during August–September in 2014–2017, we investigated the spatial associations among the three rorqual species of blue, fin, and common minke whales, the predatory fish Atlantic cod, and their main prey groups (zooplankton, 0-group fish, Atlantic cod, and capelin) in Arctic Ocean waters to the west and north of Svalbard. During the surveys, whale sightings were recorded by dedicated whale observers on the bridge of the vessel, whereas the distribution and abundance of cod and prey species were assessed using trawling and acoustic methods. Based on existing knowledge on the dive habits of these rorquals, we divided our analyses into two depth regions: the upper 200 m of the water column and waters below 200 m. Since humpback whales were absent in the area in 2016 and 2017, they were not included in the subsequent analyses of spatial association. No association or spatial overlap between fin and blue whales and any of the prey species investigated was found, while associations and overlaps were found between minke whales and zooplankton/0-group fish in the upper 200 m and between minke whales and Atlantic cod at depths below 200 m. A prey detection range of more than 10 km was suggested for minke whales in the upper water layers.

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Trends in phytoplankton communities within large marine ecosystems diverge from the global ocean

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2020-0423 ◽

2021 ◽

pp. 1-12

Author(s):

Kevin D. Friedland ◽

John R. Moisan ◽

Aurore A. Maureaud ◽

Damian C. Brady ◽

Andrew J. Davies ◽

...

Keyword(s):

Chlorophyll Concentration ◽

World Ocean ◽

Marine Ecosystems ◽

Fishing Effort ◽

Global Ocean ◽

Human Populations ◽

Anthropogenic Pressures ◽

Large Marine Ecosystems ◽

Phytoplankton Communities ◽

The World

Large marine ecosystems (LMEs) are highly productive regions of the world ocean under anthropogenic pressures; we analyzed trends in sea surface temperature (SST), cloud fraction (CF), and chlorophyll concentration (CHL) over the period 1998–2019. Trends in these parameters within LMEs diverged from the world ocean. SST and CF inside LMEs increased at greater rates inside LMEs, whereas CHL decreased at a greater rates. CHL declined in 86% of all LMEs and of those trends, 70% were statistically significant. Complementary analyses suggest phytoplankton functional types within LMEs have also diverged from those characteristic of the world ocean, most notably, the contribution of diatoms and dinoflagellates, which have declined within LMEs. LMEs appear to be warming rapidly and receiving less solar radiation than the world ocean, which may be contributing to changes at the base of the food chain. Despite increased fishing effort, fishery yields in LMEs have not increased, pointing to limitations related to productivity. These changes raise concerns over the stability of these ecosystems and their continued ability to support services to human populations.

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Thevgll3locus controls age at maturity in wild and domesticated Atlantic salmon (Salmo salarL.) males

10.1101/024927 ◽

2015 ◽

Cited By ~ 2

Author(s):

Fernando Ayllon ◽

Erik Kjærner-Semb ◽

Tomasz Furmanek ◽

Vidar Wennevik ◽

Monica F Solberg ◽

...

Keyword(s):

Atlantic Salmon ◽

Homo Sapiens ◽

Complex Nature ◽

Missense Mutations ◽

Age At Maturity ◽

Specific Sequence ◽

Wild Salmon ◽

Late Maturity ◽

Age At Maturation ◽

Sexually Mature

Wild and domesticated Atlantic salmon males display large variation for sea age at sexual maturation, which varies between 1-5 years. Previous studies have uncovered a genetic predisposition for age at maturity with moderate heritability, thus suggesting a polygenic or complex nature of this trait. The aim of this study was to identify associated genetic loci, genes and ultimately specific sequence variants conferring sea age at maturity in salmon. We performed a GWAS using a pool sequencing approach (20 individuals per river and trait) of salmon returning to rivers as sexually mature either after one sea winter (2009) or three sea winters (2011) in six rivers in Norway. The study revealed one major selective sweep, which covered 76 significant SNP in which 74 were found in a 370 kb region of chromosome 25. Genotyping other smolt year classes of wild salmon and domesticated salmon confirmed this finding. Genotyping domesticated fish narrowed the haplotype region to four SNPs covering 2386 bp, containing thevgll3gene, including two missense mutations explaining 33-36% phenotypic variation. This study demonstrates a single locus playing a highly significant role in governing sea age at maturation in this species. The SNPs identified may be both used as markers to guide breeding for late maturity in salmon aquaculture and in monitoring programs of wild salmon. Interestingly, a SNP in proximity of the VGLL3 gene in human (Homo sapiens), has previously been linked to age at puberty suggesting a conserved mechanism for timing of puberty in vertebrates.

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Atlantic salmon fisheries in the White and Barents Sea basins: Dynamic of catches in the 17–18th Century and comparison with 19–20th Century data

Fisheries Research ◽

10.1016/j.fishres.2007.07.001 ◽

2007 ◽

Vol 87 (2-3) ◽

pp. 240-254 ◽

Cited By ~ 12

Author(s):

Dmitry L. Lajus ◽

Zoya V. Dmitrieva ◽

Alexei V. Kraikovski ◽

Julia A. Lajus ◽

Daniel A. Alexandrov

Keyword(s):

Atlantic Salmon ◽

20Th Century ◽

Barents Sea ◽

18Th Century ◽

Salmon Fisheries

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Transcription Profiles of Age-at-Maturity-Associated Genes Suggest Cell Fate Commitment Regulation as a Key Factor in the Atlantic Salmon Maturation Process

G3 Genes|Genome|Genetics ◽

10.1534/g3.119.400882 ◽

2019 ◽

Vol 10 (1) ◽

pp. 235-246 ◽

Cited By ~ 3

Author(s):

Johanna Kurko ◽

Paul V. Debes ◽

Andrew H. House ◽

Tutku Aykanat ◽

Jaakko Erkinaro ◽

...

Keyword(s):

Atlantic Salmon ◽

Cell Fate ◽

Molecular Mechanisms ◽

Genome Wide Association Study ◽

Expression Patterns ◽

Hippo Signaling ◽

Age At Maturity ◽

Specific Expression ◽

Hpg Axis ◽

Tissue Specific

Despite recent taxonomic diversification in studies linking genotype with phenotype, follow-up studies aimed at understanding the molecular processes of such genotype-phenotype associations remain rare. The age at which an individual reaches sexual maturity is an important fitness trait in many wild species. However, the molecular mechanisms regulating maturation timing processes remain obscure. A recent genome-wide association study in Atlantic salmon (Salmo salar) identified large-effect age-at-maturity-associated chromosomal regions including genes vgll3, akap11 and six6, which have roles in adipogenesis, spermatogenesis and the hypothalamic-pituitary-gonadal (HPG) axis, respectively. Here, we determine expression patterns of these genes during salmon development and their potential molecular partners and pathways. Using Nanostring transcription profiling technology, we show development- and tissue-specific mRNA expression patterns for vgll3, akap11 and six6. Correlated expression levels of vgll3 and akap11, which have adjacent chromosomal location, suggests they may have shared regulation. Further, vgll3 correlating with arhgap6 and yap1, and akap11 with lats1 and yap1 suggests that Vgll3 and Akap11 take part in actin cytoskeleton regulation. Tissue-specific expression results indicate that vgll3 and akap11 paralogs have sex-dependent expression patterns in gonads. Moreover, six6 correlating with slc38a6 and rtn1, and Hippo signaling genes suggests that Six6 could have a broader role in the HPG neuroendrocrine and cell fate commitment regulation, respectively. We conclude that Vgll3, Akap11 and Six6 may influence Atlantic salmon maturation timing via affecting adipogenesis and gametogenesis by regulating cell fate commitment and the HPG axis. These results may help to unravel general molecular mechanisms behind maturation.

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Population Dynamics of the Arcto-Norwegian Cod

Journal of the Fisheries Research Board of Canada ◽

10.1139/f67-012 ◽

1967 ◽

Vol 24 (1) ◽

pp. 145-190 ◽

Cited By ~ 24

Author(s):

D. J. Garrod

Keyword(s):

Gadus Morhua ◽

Barents Sea ◽

Fishing Effort ◽

Catch Per Unit Effort ◽

Group Iii ◽

Spawning Stock ◽

Stock Recruitment ◽

Post War ◽

The One ◽

Definition Of

By reason of its geographical distribution, the Arcto-Norwegian cod (Gadus morhua) supports three distinct fisheries, two feeding fisheries in the Barents Sea and at Bear Island–Spitsbergen, and a spawning fishery off the Norway coast. In the past this diversity of fishing on the one stock has made it difficult to unify all the data to give an overall description of post-war changes in the stock. In this contribution three modifications of conventional procedures are introduced which enable this to be done. These are: (i) a system of weighting the catch per unit effort data from each fishery to a level of comparability; (ii) a more rigorous definition of the effective fishing effort on each age-group; (iii) a method of estimation of the effective fishing effort on partially recruited age-groups.Using these methods the analysis presents the effects of fishing on each fishery in the context of its effect on the total stock, and at the same time it indicates ways in which factors other than fishing may have influenced the apparent abundance of the stock. The treatment of the data is also used to derive estimates of spawning stock and recruitment of 3-year-old cod for subsequent analysis of stock–recruitment relationships.

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Coastal migration patterns of the four largest Barents Sea Atlantic salmon stocks inferred using genetic stock identification methods

ICES Journal of Marine Science ◽

10.1093/icesjms/fsz114 ◽

2019 ◽

Vol 76 (6) ◽

pp. 1379-1389 ◽

Cited By ~ 2

Author(s):

Martin-A Svenning ◽

Morten Falkegård ◽

Eero Niemelä ◽

Juha-Pekka Vähä ◽

Vidar Wennevik ◽

...

Keyword(s):

Atlantic Salmon ◽

Barents Sea ◽

Catch Per Unit Effort ◽

Genetic Stock ◽

Migration Patterns ◽

The North ◽

Genetic Stock Identification ◽

Temporal And Spatial ◽

Catch Composition ◽

Mixed Stock

Abstract Combining detailed temporal and spatial catch data, including catch per unit effort, with a high-resolution microsatellite genetic baseline facilitated the development of stock-specific coastal migration models for the four largest Atlantic salmon (Salmo salar) populations, Målselv, Alta, Tana and Kola rivers, contributing to the Barents Sea mixed-stock fishery. Målselv salmon displayed a restricted coastal movement with 85% of the fish captured within 20 km of their natal river. Kola salmon also demonstrated limited coastal movements in Norwegian waters, with most (> 90%) caught in eastern Finnmark. Multi-sea-winter (MSW) Alta salmon were caught west of Alta fjord across a broader stretch of coast while one-sea-winter (1SW) fish migrated more extensively along the coast prior to river entry. Tana salmon, however, were detected over a broad expanse (600 km) of the North-Norwegian coast. For all populations MSW salmon dominating catches earlier in the season (May–June) while 1SW fish were more common from July to August. This study provides an example of how traditional catch and effort information may be combined with genetic methods to obtain insights into spatial and temporal changes in Atlantic salmon catch composition and their associated migration patterns in a mixed-stock coastal fishery.

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