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1,025 results for “salmon”
F I G U R E 3 in Estimating multiple years, tributary-specific, and overall Atlantic salmon smolt abundance in a large Canadian catchment using capture-mark-recapture experiments
F I G U R E 3 (a) Posterior distribution of the difference between the true value and posterior distribution estimates (in percentage of the true value) of annual total smolt abundance obtained from DM (Dirichlet-multinomial) model M5 (simulation exercise). Each line is a year, and the 10 (one for each replicate) distributions are overlaid. The overall average difference is indicated in the left corner of the panel and represented by a red dashed vertical line. (b) C.V. of the posterior distributions of total abundance obtained from DM model M5. Each blue dot corresponds to the C.V. of a unique year/replicate, and each dashed blue horizontal line corresponds to the average C.V. of a replicate across years. The average C.V. across years and replicates (red dashed line) is also indicated in the top-right corner of the panel.
F I G U R E 4 in Estimating multiple years, tributary-specific, and overall Atlantic salmon smolt abundance in a large Canadian catchment using capture-mark-recapture experiments
F I G U R E 4 (a–c) Posterior distribution of the relative contribution of the smolt abundance associated with each upstream rotary screw trap (RST) and (d) posterior distribution of the relative contribution of the "rest" of the smolt abundance in relation to the total abundance for the DM (Dirichletmultinomial) model M5 (simulation exercise). The red dots correspond to the true values in the simulated dataset.
F I G U R E 1 in Estimating multiple years, tributary-specific, and overall Atlantic salmon smolt abundance in a large Canadian catchment using capture-mark-recapture experiments
F I G U R E 1 Restigouche River catchment map with main streams and lakes. Red dots indicate the location of the rotary screw traps (RST). Black polygons indicate subcatchments draining into upstream RSTs. Top-right panels: zoom on the location of the two downstream RSTs and example of a smolt with a streamer tag. Photo credit: Marie-Camille St-Amour.
F I G U R E 5 in Estimating multiple years, tributary-specific, and overall Atlantic salmon smolt abundance in a large Canadian catchment using capture-mark-recapture experiments
F I G U R E 5 (left panels, a–e) Posterior distributions of the estimated annual catchability θt,k at each rotary screw trap (RST), (middle panels, f– h) posterior distributions of the annual smolt abundance estimates associated with each upstream RST (Nmt,i), (i) the total smolt abundance for the Restigouche catchment (Nmtot), and (right panels, j–m) posterior distributions of the annual relative proportions of the total smolt abundance t of the Restigouche catchment estimated for each upstream RST and for the unsampled areas (rest, bottom-right panel) using the Restigouche dataset. In the catchability panels (a–e), the dashed gray line is the median, and the light and dark gray areas indicate the 2.5th–97.5th and 25th– 75th interquantile ranges, respectively, of the hyperparameter μθ, that is, the average catchability of each RST of the time series. In the relative k proportions panels (f–i) the thick dashed colored line in the top three panels indicates the average proportion of the total catchment abundance estimated at the upstream RST. The thick dashed gray lines indicate the proportions of the Restigouche catchment wetted areas of the subbasins sampled at the upstream RST(j–l) and the wetted area for the remainder of the Restigouche catchment not sampled by any upstream RST (m); the proportions for the rest of the catchment area change over years based on the specific upstream RSTs that operated in a given year. For all panels, the colored dot is the median, and the thin and thick vertical segments indicate the 2.5th–97.5th and 25th–75th interquantile ranges, respectively.
F I G U R E 7 in Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar
F I G U R E 7 Model prediction of the proportion of juvenile Atlantic salmon choosing to smolt as 1-year-olds (full saturation, black = historical, green = SSP1-RCP2.6, orange = SSP3-RCP7.0, and red = SSP5-RCP8.5), 2-year-olds (medium saturation, black = historical, green = SSP1-RCP2.6, orange = SSP3-RCP7.0, and red = SSP5-RCP8.5), and 3-year-olds (low saturation, black = historical, green = SSP1-RCP2.6, orange = SSP3-RCP7.0, and red = SSP5-RCP8.5). The red line is the point of reaction norm calibration to Piggins and Mills (1985).
F I G U R E 5 in Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar
F I G U R E 5 Ensemble average daily water temperature by day of year for the future projections under the three shared socioeconomic pathways and representative concentration pathways (SSP1-RCP2.6 left, SSP5-RCP7.0 middle, and SSP5-RCP8.5 right). Each line represents the day of year average temperature for the climate forcing ensemble with colors transitioning from blue to red toward the end of the century (starting with 2020 and ending with 2100). The lower dashed line represents the lower growth threshold temperature of 7 C, and the upper dashed line represents the upper growth threshold temperature for 23 C (Elliott & Hurley, 1997).
F I G U R E 6 Projected change between 1960 and 2100 in Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar
F I G U R E 6 Projected change between 1960 and 2100 in length-at-smoltification decision (a, b, and c), length-at-smoltification as 1-year-olds (d, e, and f), and length-at-smoltification as 2-year-olds (g, h, and i) under the three shared socioeconomic pathways and representative concentration pathways: SSP1-RCP2.6 (green), SSP3-RCP7.0 (orange), and SSP5-RCP8.5 (red) for juvenile Atlantic salmon in the Burrishoole. The gray-shaded area represents the historical reference (2000 to 2020), and the red vertical line represents the historical average.
F I G U R E 4 in Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar
F I G U R E 4 Generalized linear model of body length (mm) as a function of cumulative growing degree days (CGDD, C day) for the 23 observed cohorts of juvenile Atlantic salmon in the Burrishoole watershed. The solid line represents the mean length, and the gray bands represent the 95% prediction interval. The outer lines represent the sample density.
F I G U R E 3 in Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar
F I G U R E 3 The residual error between observed and predicted water temperature (top panel), and the in-situ water temperature (black line) and long short-term memory neural network water temperature prediction (red crosses) for the training (1961–1994) and validation (1995–2019) dataset in the Mill Race (bottom panel). Years excluded due to accumulation of internal sate (green), prolonged periods of missing data (blue shaded), and measurement error (red shaded) are shown in the top panel, and the delineation of the training and validation period is shown by the vertical dashed line in both panels.
F I G U R E 5 in Migration patterns and navigation cues of Atlantic salmon post-smolts migrating from 12 rivers through the coastal zones around the Irish Sea
F I G U R E 5 Rose diagrams depicting (a) the hour of the day and (b) the direction of currents () when Atlantic salmon (Salmo salar) post-smolts were initially detected at a unique acoustic receiver on monitoring line B. The green and blue arrows show the mean hour (a) and mean current direction (b) when post-smolts were initially detected respectively (Lilly et al., 2022). The orange and yellow bands (a) show the variation in sunrise and sunset times for the total period over which any post-smolts were detected on monitoring line B (ie. April 21st–June 20th).
F I G U R E 4 in Migration patterns and navigation cues of Atlantic salmon post-smolts migrating from 12 rivers through the coastal zones around the Irish Sea
F I G U R E 4 Heatmaps displaying the number of Atlantic salmon (Salmo salar) post-smolts detected at each acoustic receiver on monitoring lines A and B (Figure 1) during the period of this study. The black stars show the location of each river (n = 11) where Atlantic salmon post-smolts originated. Rivers are grouped by coastal region where they entered the Irish Sea (Figure 1, (a) Region 1: Rivers Derwent, Nith, Bladnoch; (b) Region 2: Rivers Endrick, Gryffe; (c) Region 3: Rivers Bann, Bush, Carey, Glendun; (d) Region 4: Rivers Roe, Faughan).
F I G U R E 2 A in Migration patterns and navigation cues of Atlantic salmon post-smolts migrating from 12 rivers through the coastal zones around the Irish Sea
F I G U R E 2 A boxplot plot displaying the dates (mm-dd) when Atlantic salmon (Salmo salar) post-smolts (n = 582) were last detected in their natal river/estuary (Rivers Endrick, Gryffe, Roe, Faughan) or coastal embayment (River Burrishoole) and entered the coastal zones of the Irish Sea or the west coast of Ireland (River Burrishoole; Figure 1: Clew Bay) and were detected on monitoring lines A and B (excluding the River Burrishoole Figure 1). In the boxplots, the centre line represents the median, the box encompasses the 25 to 75% quartiles, the bars are the values within 1.5 interquartile units and the dots represent outliers. It should be noted that the dates when smolts were tagged (represented by the dashed black line) differed in each river system. The thick black lines divide rivers into their coastal regions (see methods).
F I G U R E 1 Map displaying the 14 in Migration patterns and navigation cues of Atlantic salmon post-smolts migrating from 12 rivers through the coastal zones around the Irish Sea
F I G U R E 1 Map displaying the 14 capture sites in 12 rivers where Atlantic salmon smolts (n = 1008) were captured for tagging in England, Scotland, Northern Ireland and the Republic of Ireland for this study. In addition, 60 hatchery origin smolts were tagged and released in the River Burrishoole. The coastal region each river belongs to is referenced in brackets next to the river name. Where Region one (1) refers to the Solway Firth (Rivers Derwent, Nith, Bladnoch); Region two (2) refers to the Clyde Estuary (Rivers Endrick and Gryffe); Region three (3) refers to the Bush Coastal region (rivers Bann, Bush, Carey and Glendun); Region four (4), refers to Lough Foyle (rivers Roe and Faughan); Region five (5), refers to Clew Bay (River Burrishoole). Tagged fish release sites are represented by stars, and acoustic receivers (n = 183) are represented by gray dots. Marine monitoring lines (A and B) in the Irish Sea are labeled in alphabetical order from south to north. Twenty-two acoustic receivers were initially deployed at monitoring line A. One hundred and eight acoustic receivers were deployed at monitoring line B and are labeled in numerical order from the furthest west receiver (R1) on the monitoring line to the furthest east (R108). Refer to Figure S2 for the locations of acoustic receivers that were not retrieved from marine monitoring line A (n = 2) and B (n = 9).
F I G U R E 2 in Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar
F I G U R E 2 The four-step model workflow for quantitatively estimating length-at-age and life history of juvenile Atlantic salmon in response to climate change. Step 1 describes the collation of necessary data and construction of the water temperature model. Step 2 details the data preparation and construction of the length-at-age model for juvenile Atlantic salmon. Step 3 shows the coupling of the ISIMIP phase 3B projections to the water temperature model, and the subsequent coupling with the length-at-age model. Step 4 shows the post-processing of length-at-age projections to estimate smoltification probability and proportion of 1-, 2- and 3-year-old smolts. Shapes are according to ISO 5807 standard.
F I G U R E 1 in Evidence of successful recruitment of non-native pink salmon Oncorhynchus gorbuscha in Iceland
F I G U R E 1 Distribution of pink salmon Oncorhynchus gorbuscha in Iceland. (a) Location of rivers in Iceland with reported catches of adult O. gorbuscha in 2000, 2005, and annually from 2015 according to Bárðarson et al. (2022), and (b) locations of fishing surveys in 2022 to catch smolts of O. gorbuscha in three rivers of southwest Iceland
F I G U R E 3 in Migration patterns and navigation cues of Atlantic salmon post-smolts migrating from 12 rivers through the coastal zones around the Irish Sea
F I G U R E 3 The binomial General Linear Model (GLM) model showing the effect of minimum migration distance (Distance [km]) from the exit of smolts natal river/estuary to monitoring line B on the probability of migration success (measured as minimum migration success) of Atlantic salmon (Salmo salar) post-smolt through the Irish Sea. The shaded region is the 95% confidence interval of the final model.
F I G U R E 1 in Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar
F I G U R E 1 Location of electrofishing sites (green circles) and fish traps (red circles) in the Burrishoole catchment, Co. Mayo, Ireland.
F I G U R E 1 in High summer temperatures are associated with poorer performance of underyearling Atlantic salmon (Salmo salar) in upland streams
F I G U R E 1 (a) Locations of sampling sites (circles) in the river Conon catchment, Northern Scotland. The map depicts the area within the black box in the inset map. (b) Daily maximum temperatures recorded in each stream during the study period (points represent the daily highest temperature for the entire stream, so may be either from the upper or lower sampling sites). Red values indicate temperatures>23 C, considered stressful to Atlantic salmon, while yellow values indicate temperatures between 20 C and 23 C, and blue values indicate temperatures <20 C. (c) Density and (d) biomass of underyearling Atlantic salmon, Salmo salar (both on a natural logarithmic scale, ± standard error) in relation to duration of peak temperatures (degree hours above 23 C) at sites in the River Conon catchment (n = 63 sections sampled across six sites in 2 years, 589 fish). All sites had the same initial density and genetic composition of eggs. Temperature: 0–20, 20–23, and>23. Year and sampling position: 2020 Downstream, 2020 Upstream, 2021 Downstream, and 2021 Upstream. Stream: Blackwater, Rannoch, and Vaich.
Data and custom codes from "Rapid evolution in salmon life-history induced by direct and indirect effects of fishing"
<p>Data and custom codes from Czorlich, Y., Aykanat, T., Erkinaro, J., Orell, P. & Primmer, C.R. (2021) <em>Rapid evolution in salmon life-history induced by direct and indirect effects of fishing. </em>Science.</p> <p><strong>Codes:</strong></p> <p>The R file "Fishing_effort_parallel.R" was used to estimate fishing effort/intensity (beta in equation 8) given the length distribution, the gear-specific catchability and harvest rate</p> <p>"Fishing_selection_estimate.R" was used to estimate fishery-induced selection at <em>vgll3.</em></p> <p><strong>Datasets:</strong></p> <p>Genetic_phenotypic_data.xlsx: Genetic and phenotypic data about salmon from the Teno mainstem population</p> <p>sonar_data.xlsx: Number of salmon per length class entering the river in 2018 and 2019. The length classes of salmon caught in those years by one of the fishing methods are also included</p> <p>annual_catch_data.xlsx: Total mass (kg) of salmon caught by each fishing method between 1975 to 2014.</p> <p>Environmental_data.xlsx: Data about Barents Sea temperature, biomass of key species, fishing data</p> <p>individual_weight_salmon_catches.xlsx: Individual weight of salmon caught with different fishing gears in the last decades</p> <p><strong>Data sources:</strong></p> <p>- Genetic data (Tenojoki population, random sampling): From Czorlich et al. 2018, https://datadryad.org/stash/dataset/doi:10.5061/dryad.7hm4708</p> <p>- Data about krill biomass (1980 – 2013) were taken from (<em>1</em>, <em>2</em>).</p> <p>- Capelin biomass estimated from acoustic survey and the landed capelin catches were derived from (<em>3</em>) for 1973 – 2013.</p> <p>- Herring biomass data were retrieved from (<em>4</em>) for the 1973-1998 period. Herring biomass was calculated from the number of 1-2 year old herring and the mean weight per age as reported in (<em>3</em>) for 1988 – 2013.</p> <p>- The annual biomass of cod (a predator of forage fish) was derived from VPA analyses ((<em>5</em>), table 3.24). Landed cod biomass was also taken from (<em>5</em>).</p> <p>- An index for mesozooplankton (a forage fish food source) corresponding to the sum of <em>Calanus</em> biomass indices from different parts of the Barents Sea was used (<em>6</em>).</p> <p>- The annual sea temperature in the Kola section of the Barents Sea measured in the upper 200 meters was from <a href="http://www.pinro.vniro.ru/">pinro.vniro.ru</a></p> <p>- The total number of nets used to catch salmon in the Finnmark coastal region was calculated for each year using data from (7)</p> <p>- Other data were generated for this study, please check the Material and Methods. </p> <p><em>References:</em></p> <p>1. E. Eriksen, P. Dalpadado, Long-term changes in Krill biomass and distribution in the Barents Sea: Are the changes mainly related to capelin stock size and temperature conditions? <em>Polar Biology</em>. <strong>34</strong>, 1399–1409 (2011).</p> <p>2. ICES, “Report of the Working Group on the Integrated Assessments of the Barents Sea. ICES CM 2017/SSGIEA:04. 186 pp.” (2017).</p> <p>3. ICES, “Report of the Arctic Fisheries Working Group (AFWG). ICES CM 2015/ACOM:05. 639 pp.” (2015).</p> <p>4. R. Toresen, O. J. Østvedt, Variation in abundance of Norwegian spring-spawning herring (Clupea harengus, Clupeidae) throughout the 20th century and the influence of climatic fluctuations. <em>Fish and Fisheries</em>. <strong>85</strong>, 385–391 (2000).</p> <p>5. ICES, “Report of the Arctic Fisheries Working Group (AFWG). ICES CM 2016/ACOM:06. 621 pp.” (2016).</p> <p>6. L. C. Stige et al., Spatiotemporal statistical analyses reveal predator-driven zooplankton fluctuations in the Barents Sea. <em>Progress in Oceanography</em>. <strong>120</strong>, 243–253 (2014).</p> <p>7. E. Niemelä, T. Kalske, E. Hassinen, “Numbers of fishing gears used in Kolarctic salmon project area, numbers of allowed sites for salmon fishing and numbers of salmon fishermen in Finnmark; development until the year 2013” (2013).</p>
Size data for Chinook salmon caught in the Tengu Derby and Puget Sound commercial purse seine fisheries
<p>The tengu_derby_size.csv file contains information on the following fields (columns):</p> <ol> <li>year</li> <li>members (number of anglers who participated in the derby; not all anglers fished each day the derby was open)</li> <li>n_over_10 (total number of Chinok salmon greater than 10 pounds)</li> <li>n_over_5 (total number of Chinok salmon greater than 5 pounds)</li> <li>size_1 (mass in kg of the largest fish landed)</li> <li>size_2 (mass in kg of the second largest fish landed)</li> <li>size_3 (mass in kg of the third largest fish landed)</li> <li>size_4 (mass in kg of the fourth largest fish landed)</li> <li>size_5 (mass in kg of the fifth largest fish landed) </li> </ol> <p>The wdfw_size.csv file contains the following fields (columns):</p> <ol> <li>year</li> <li>mass (mean mass in kg of natural- and hatchery-origin Chinook salmon combined)</li> </ol>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.