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18 results for “salmon aquaculture”
Survey data on attitudes towards salmon aquaculture industry in Norway, Iceland, and Tasmania (AU)
<p>The following data is from an online survey conducted in Norway, Tasmania (Australia), and Iceland. Respondents were recruited by survey companies that distributed e-mail invitations to their panels. A minimum respondent quotas was established for each region, with individuals under the age of 18 being exluded from participating in the survey. The dataset consists of a total of 2085 respondents, comprising 1183 participants from Norway, 406 from Tasmania, and 496 from Iceland. Questions were presented in their respective native language, namely Norwegian, English, and Icelandic.</p> <p>This survey data encompasses various aspects of perceptions of salmon aquaculture industry. Data was generated by the SoLic (Social License to operate for aquaculture) project (2019 - 2022), and funded by The Research Council of Norway (no. 295114). The survey was designed by the SoLic project group. </p> <p>The data and supplementary material is divided in 3 files:</p> <p>The raw survey data in .csv file format (Dataset Solic_2085 respondents.csv). The data file contains 71 variables and data from each of the 2085 respondents. Blank entries in the dataset indicate either a lack of response from the respondents or that specific questions were not applicable to certain respondents (questions exclusively posed to respondents in one country).</p> <p>Overview of survey questions and answer options (Survey.doc). The survey encompassed 28 questions related to the aquaculture industry, along with demographics, respondents’ knowledge of industry, trust in governance system, and environmental concerns. Some demographic variables were sourced from the existing panel data, while others were provided to respondents for their input.</p> <p>The codebook (Codebook.doc). The codebook provides explanations and details regarding all variables included in the survey data file. It includes coding information for each survey question, response options provided in the raw data, and further clarifies the purpose and origin of variables computed by the research group (e.g., variable on aquaculture municipality) or the survey company (e.g., weight variables for data from Norway and Iceland). When used in conjunction with the raw data, this codebook serves as a valuable guide for navigating the dataset. </p>
FIGURE 8 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 8 Mean (S.E.; n = 30) relative gene transcription values for (a) mef2c () Reference, and () Preline, (b) gata4 () Reference, and () Preline and (c) vegf () Reference, and () Preline using ef1α as standard in Salmo salar heart, both in fresh water and after rearing in Preline semiclosed containment system (S-CCS;) and reference group open pen () for 4 months in seawater. Significant differences between groups are indicated by different lower-case letters
FIGURE 7 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 7 Mean (S.E.; n = 30) relative gene transcription values for (a) Igf-I () Reference, and () Preline, (b) igf1ra () Reference, and () Preline, and (c) igf1bp1a () Reference, and () Preline using ef1α as standard in Salmo salar muscle, both in fresh water and during rearing in Preline semiclosed containment system (S-CCS;) and reference group (). Significant differences through time are denoted with capital letters within the reference group and lower-case letters within Preline S-CCS. SW, seawater
FIGURE 3 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 3 Mean [S.E.; n = 30; (a), (c), (d)] Salmo salar growth in mass (M) fork length (LF) and Fulton's condition factor (K) measured in freshwater (15 April 2016) and during the post-smolt phase (1–2 June; 1–2 June and 29–30 August 2016) (a) Measured mass () Preline, and () Reference, (b) estimated mean mass (Fishtalk calculations, CEF = 1.1) () Reference, and () Preline, (c) mean fork length () Preline, and () Reference and (d) condition factor (K) () Preline, and () Reference. Estimated mean mass covers both the post-smolt phase 5 May to 30 August, and the growth phase 31 August to 30 November. Changeover is indicated with a dot in the figure. SW, seawater. Significant difference between groups; *p <0.05; ***p <0.001
FIGURE 4 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 4 Accumulated mortality of Salmo salar in the Preline semiclosed containment system (S-CCS) 30 April to 30 August followed by the open pen growth phase (Buholmen) from 1 September to 30 November (;, changeover from S-CCS to open pen). The accumulated mortality in the reference group covers the period 5 May to 30 November ()
FIGURE 5 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 5 Mean (+S.E.) Salmo salar skeletal muscle fibre diameter frequency distribution reared in Preline semi-closed containment system () and reference S. salar () after 4 months in seawater. Significant difference between groups; *p <0.05; ***p <0.001
FIGURE 2 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 2 (a) Alternate day mean water temperature and (b) salinity at the Salmo salar post- smolt Preline semi-closed containment system () and reference group () rearing systems between 5 May and 30 November 2016. Data from Preline S-CCS represents the Buholmen open-pen between 31 August and 30 November 2016
FIGURE 1 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 1 (a) Location of experiment area in Norway and (b) locations of the Preline semi-closed containment system (S-CCS), reference, freshwater and growing phase groups of Salmo salar post-smolts in Hordaland region; (c) schematic of the S-CCS; (d) standard open sea cages for S. salar production in Norway; (e) drawing of an open conical pen used to hold the reference group of fish
FIGURE 6 in Comparison between Atlantic salmon Salmo salar post-smolts reared in open sea cages and in the Preline raceway semi-closed containment aquaculture system
FIGURE 6 Mean (S.E.; n = 30) plasma IGF-I concentration of Salmo salar in both fresh water and during rearing in Preline S- semi-closed containment system (S-CCS;) and reference group (). Significant differences trough time are denoted with capital letters within the reference group, lower-case letters within the Preline S-CCS group and significant differences between rearing systems are shown: **p <0.01; ***p <0.001. SW, seawater
Parasites under pressure: salmon lice may adapt to depth-based preventions in aquaculture
<p>Experiment 1. Vertical distribution of copepodids (mixed family groups) in 80 cm columns over time (min) at two pressures.</p> <p>Experiment 2. Vertical distribution of copepodids (individual families) in 80 cm columns at three pressures.</p> <p>Experiment 2 (traits). For each family: body size, egg string length, estimated fecundity and estimated egg size of mother; development times and column distributions (i.e. proportion of copepodids at top of columns) of offspring.</p>
Aquaculture-driven evolution of the salmon louse mtDNA genome
<p><span>Resistance towards the antiparasitic pyrethroid, deltamethrin, is reported in the Atlantic salmon louse (<em>Lepeophtheirus</em> <em>salmonis</em> <em>salmonis</em>), a persistent ectoparasite of farmed and wild salmonids. The resistance mechanism is linked to mitochondrial DNA (mtDNA), where genetic markers for resistance have been identified. Here, we investigated how widespread pyrethroid use in aquaculture may have influenced mtDNA variation in lice, and the dispersion of resistant haplotypes across the North Atlantic, using historical (2000–2002 "pre-resistance") and contemporary (2014–2017 "post-resistance") samples. To study this, we sequenced ATPase 6 and cytochrome b, genotyped two genetic markers for deltamethrin resistance, and genotyped microsatellites as "neutral" controls of potential population bottlenecks. Overall, we observed a modest reduction in mtDNA diversity in the period 2000–2017, but no reduction in microsatellite variation was observed. The reduction in mtDNA variation was especially distinct in two of the contemporary samples, fixed for one and two haplotypes respectively. By contrast, all historical samples consisted of close to one mtDNA haplotype per individual. No population genetic structure was detected among the historical samples for mtDNA nor microsatellites. By contrast, significant population genetic differentiation was observed for mtDNA among some of the contemporary samples. However, the observed population genetic structure was tightly linked with the pattern of deltamethrin resistance, and we therefore conclude that it primarily reflects the transient mosaic of pyrethroid usage in time and space. Two historically undetected mtDNA haplotypes dominated in the contemporary samples, both of which were linked to deltamethrin resistance, demonstrating primarily two origins of deltamethrin resistance in the North Atlantic. Collectively, these data demonstrate that the widespread use of pyrethroids in commercial aquaculture has substantially altered the patterns of mtDNA diversity in lice across the North Atlantic, and, that long-distance dispersion of resistance is rapid due to the high level of genetic connectivity that is observed in this species.</span></p>
Biomonitoring planktonic threats to salmon aquaculture: morphological and eDNA metabarcoding data
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Aquaculture-driven evolution of the salmon louse mtDNA genome
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Data from: Impacts on microbial communities in sediment by aquaculture farming during one salmon cycle
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Data from: Salmon behavioural response to robots in an aquaculture sea cage
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Depth-based preventions in aquaculture exert selection on salmon louse behaviour
<p>Model outputs from a biological-hydrodynamic dispersal model, summarising the horizontal and vertical dispersion of salmon louse (Lepeophtheirus salmonis) larvae through the Hardangerfjord region, Norway.</p>
Data from: SNPs to discriminate different classes of hybrid between wild Atlantic salmon and aquaculture escapees
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Responses to crowding stress in Atlantic salmon reared in different aquaculture systems
GEO Series GSE173229. Salmo salar. 48 samples. Type: Expression profiling by array.
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