BUSCADOR RECOLECTA

5 tables, 3 figures, Supplementary Table 1. Conversion factors applied to δ15N and δ13C for lipid normalization in taxa associated to seaweeds on Cíes Archipelago. (-) normalization not required.-- Supplementary Table 2. Relative abundances (%) in epifauna identified in 2017-2018 (spring, summer and autumn) on canopy-forming seaweeds in Cíes Archipelago. * indicates <0.01%.-- Supplementary Table 3. Summary table for Multipatt results (p-value) showing taxa significantly associated to Year (2017 – 2018) and Season (Sp – Spring; Su – Summer; Au – Autumn).-- Supplementary Table 4. Taxa richness (S), Shannon diversity (H’), Simpson dominance (D’), and Pielou’s evenness (J’) in epifaunal assemblages associated to Codium spp. and Gongolaria baccata.-- Supplementary Table 5. Summary table for Multipatt results (p-value) showing taxa significantly associated to seaweed (Codium spp and G. baccata) assemblages seasonally sampled from Summer-2017 (Su17) to Autumn-2018 (Au18).-- Supplementary Table 6. Syngnathid specimens (recaptured specimens not included) collected in 2017 and 2018 (spring, summer and autumn) by UVC on Cíes Archipelago.-- Supplementary Figure 1. Two-dimensional non-metric multidimensional scaling (NMDS; Bray–Curtis similarities) plot of the variation in stable isotopes (δ13C and δ15N) in syngnathids (H. guttulatus, E. aequoreus and S. acus) collected in spring, summer and autumn (2017 and 2018).-- Supplementary Figure 2. Two-dimensional convex hulls of the variation in δ13C and δ15N in epifauna community and syngnathids, considering Year (2017 – 2018), functional groups (FG), and main taxa (Taxa).-- Supplementary Figure 3. Seasonal fluctuations of epifaunal taxa (bars; relative abundance in taxa contributing to syngnathid feeding regimes) in canopy-forming assemblages (Codium spp. and Gongolaria baccata), and syngnathids abundance (dotted lines) on Cíes Archipelago in surveys carried out in 2017 – 2018, Peer reviewed

4 files, 1. Understanding the responses of aquatic animals to temperature variability is essential to predict impacts of future climate change and to inform conservation and management. Most ectotherms such as fish are expected to adjust their behaviour to avoid extreme temperatures and minimize acute changes in body temperature. In coastal Skagerrak, Norway, sea surface temperature (SST) ranges seasonally from 0 to over 20 °C, representing a challenge to the fish community which includes both cold-, cool- and warm-water affinity species. 2. By acoustically tracking 111 individuals of Atlantic cod (Gadus morhua), pollack (Pollachius pollachius) and ballan wrasse (Labrus bergylta) in 2015 - 2018, we examined how coexisting species within a fish community adjusted their behaviour (i.e. vertical distribution in the water column and habitat selection) to cope with the thermal variation. 3. Mixed-effect models showed that thermal preference was a main driver of behaviour and habitat use of the fish community in a southern Norwegian fjord. Cod used colder waters, compared with pollack and ballan wrasse. Increases in SST during summer were associated with the use of deeper, colder waters by cod, especially by larger individuals, and conversely with the occupancy of shallower areas by pollack and ballan wrasse. During winter, when SST dropped and the thermal stratification reversed, pollack and ballan wrasse moved to deeper, relatively warmer areas, while cod selected shallower, colder habitats. Though habitat selection was affected by temperature, species-specific habitat selection was observed even when temperature was similar throughout habitats. 4. This study shows how cohabiting fish species respond to thermal heterogeneity, suggesting that i) temperature regulates the access to the different depths and habitats and ii) behavioural plasticity may be an important factor for coping with temperature variability and potentially for adaptation to climate change, The Research Council of Norway, Award: 294926; European Union’s Horizon 2020, Award: 793627; Regionale forskningsfond Oslofjordfondet, Award: 272090, Peer reviewed

6 figures, 3 tables, Supplementary material for the article https://doi.org/10.1016/j.marenvres.2021.105315, Figure S1. Results of Vtg mRNA expression in females after normalization process with a different number of reference genes.-- Figure S2. Results of Vtg mRNA expression in males after normalization process with a different number of reference genes.-- Figure S3. Individual observation of RT-qPCR data for female and male different Vtg domains normalized with different number of reference genes.-- Figure S4. Bioanalizer profiles of three samples of RNA selected to assess RNA quality.-- Figure S5. Melt curve analysis of reference genes and vitellogenin primer pairs.-- Figure S6. Results of 1% agarose gel electrophoresis of PCR product using all primer pairs tested.-- Table S1. Equations of standard curves for primers pair efficiency.-- Table S2. Power analysis showing the effect size that could be confidently detected (% change in comparison with control values) in our RT-qPCR analyses results using a sample size of 3, and the averaged observed standard deviation (SD) in our samples.-- Table S3. Results of Two-Way ANOVA performed in females and males respectively to evaluate the effect of factor "time” (t4 and t24), factor “chemical” (C, SC and EE2) and the interaction of the two factors on Vtg mNRA normalized expression levels with different number of reference genes.-- Zip mmc2. Sequences.-- Zip mmc3. Alignments, Peer reviewed

5 files, Supplementary data for the article https://doi.org/10.1098/rstb.2020.0165, MGR_conserved_miRNAs.fas.-- PFU_conserved_miRNAs.fas.-- RPH_conserved_miRNAs.fas.-- SBR_conserved_miRNAs.fas.-- TGR_conserved_miRNAs.fas, Peer reviewed

1 file, Supplementary information for the article https://doi.org/10.1016/j.scitotenv.2021.146570, Figure S1. Distribution of samples in the Argentine Basin by month.-- Figure S2. Number of samples by year and layer.-- Figure S3. Vertical profile of Cant (red) and xc[CO3 2-] (black) for all the samples available in the Argentine Basin over the time period 1972-2019.-- Figure S4. Mean water mass natural fraction of dissolved inorganic carbon (DICnat, μmol kg-1) versus atmospheric CO2 concentration (ppm) in the Argentine Basin.-- Figure S5. Mean water mass property versus atmospheric CO2 concentration (ppm) in the Argentine Basin.-- Table S1. List of selected cruises in the Argentine Basin (western South Atlantic).-- Table S2: Observed trends in Argentine Basin water masses.-- Table S3: Observed trends in Argentine Basin water masses versus time (years), Peer reviewed

The folder contains a metadata sheet describing the datasets included in the LOTVS collection, and a proposal template to be used in data requests. Metadata will be regularly updated., Peer reviewed

The folder contains a metadata sheet describing the datasets included in the LOTVS collection, and a proposal template to be used in data requests. Metadata will be regularly updated., Peer reviewed

Proposal template to be used in data requests., Peer reviewed

The folder contains a metadata sheet describing the datasets included in the LOTVS collection, and a proposal template to be used in data requests. Metadata will be regularly updated., Peer reviewed

18 pages, Supporting information for the article https://doi.org/10.1016/j.scitotenv.2021.145020, Peer reviewed