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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Manning, Cara C M; Zheng, Zhiyin; Fenwick, Lindsay; McCulloch, Ross D; +6 Authors

    This dataset contains methane and nitrous oxide dissolved gas concentration, dissolved methane carbon isotope, and ancillary hydrographic data from research cruises in the North American Arctic Ocean between 2015-2018. Ocean samples for methane and nitrous oxide analysis were collected from Niskin bottles mounted on a CTD rosette. Water was collected into glass serum bottles and allowed to overflow three times before preserving with mercuric chloride and sealing with with butyl rubber stoppers and aluminum crimp seals. Gas concentrations were determined using a purge and trap system coupled to a gas chromatograph/mass spectrometer, following the method of Capelle et al. (2015). Equilibrium dry atmospheric concentrations were 328.25, 329.14, 330.11, and 330.96 ppb for N2O and 1919.64, 1933.67, 1934.92, and 1933.50 ppb for CH4 in 2015, 2016, 2017, and 2018, respectively. Equilibrium dissolved concentrations were calculated from the measured temperature and salinity following Wiesenburg and Guinasso (1979) for CH4 and Weiss and Price (1980) for N2O. Equilibrium concentrations were calculated based on sample temperature and salinity and the atmospheric N2O or CH4 concentrations measured at Barrow, Alaska by the NOAA Earth System Research Laboratory Global Monitoring Division (Dlugokencky et al., 2020a,b), with corrections to local sea level pressure and 100% humidity. Oxygen concentration was determined using an oxygen sensor mounted on the Niskin rosette, calibrated with discrete samples analyzed by Winkler titration. The mixed layer depth was defined based on a potential density difference criterion of 0.125 kg/m³ relative to the density at 5 m depth, using CTD profiles binned to 1 m. The mixed layer depth was set to 5 m as a minimum. The instantaneous gas transfer velocities and fluxes are based on the instantaneous wind speed at the time of sampling. The 30-day weighted gas transfer velocities and fluxes are integrated over the residence time of the gas in the mixed layer, using up to the prior 30 days of observations, following the method of Teeter et al. (2018) as described in the main manuscript of Manning et al. (2022). The 60-day weighted gas transfer velocities and fluxes are integrated over the residence time of the gas in the mixed layer, using the prior 60 days of observations, following the method of Teeter et al. (2018) as described in the main manuscript of Manning et al. (2022). Atmospheric sea level pressure was obtained from the NCEP/NCAR reanalysis product, which is provided by the NOAA-ESRL Physical Sciences Laboratory (https://psl.noaa.gov/data/gridded). Fractional ice cover was obtained from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (https://osi-saf.eumetsat.int). Sea ice concentration product AMSR-2 (identifier OSI-408) was used in 2017–2018 and SSMIS (identifier OSI-401-b) was used in 2015–2016.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Background: The origin of powered avian flight was a locomotor innovation that expanded the ecological potential of maniraptoran dinosaurs, leading to remarkable variation in modern birds (Neornithes). The avian sternum is the anchor for the major flight muscles and, despite varying widely in morphology, has not been extensively studied from evolutionary or functional perspectives. We quantify sternal variation across a broad phylogenetic scope of birds using 3D geometric morphometrics methods. Using this comprehensive dataset, we apply phylogenetically informed regression approaches to test hypotheses of sternum size allometry and the correlation of sternal shape with both size and locomotory capabilities, including flightlessness and the highly varying flight and swimming styles of Neornithes. Results: We find evidence for isometry of sternal size relative to body mass and document significant allometry of sternal shape alongside important correlations with locomotory capability, reflecting the effects of both body shape and musculoskeletal variation. Among these, we show that a large sternum with a deep or cranially projected sternal keel is necessary for powered flight in modern birds, that deeper sternal keels are correlated with slower but stronger flight, robust caudal sternal borders are associated with faster flapping styles, and that narrower sterna are associated with running abilities. Correlations between shape and locomotion are significant but show weak explanatory power, indicating that although sternal shape is broadly associated with locomotory ecology, other unexplored factors are also important. Conclusions: These results display the ecological importance of the avian sternum for flight and locomotion by providing a novel understanding of sternum form and function in Neornithes. Our study lays the groundwork for estimating the locomotory abilities of paravian dinosaurs, the ancestors to Neornithes, by highlighting the importance of this critical element for avian flight, and will be useful for future work on the origin of flight along the dinosaur-bird lineage.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DRYAD; Federated Res...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    figshare
    Collection . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    figshare
    Collection . 2021
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DRYAD; Federated Res...arrow_drop_down
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      figshare
      Collection . 2021
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      figshare
      Collection . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Rasman, Brandon G; Forbes, Patrick A; Peters, Ryan M; Ortiz, Oscar; +4 Authors

    Instructions for Matlab code and main result figures: 1- Download all data files and Matlab functions (see requirements) and ensure they are all in the same directory. 2- Open SourceCode_GroupFigures_RasmanEtAl_Elife2021.m with Matlab. 3- Make sure Matlab is currently in the folder where you put the files or add that folder to the path. 4- Run the code. All group result figures will be generated. Matlab will output warning when running the exponential fit procedure, but this is expected for the code. Instructions for LabVIEW code: 1- Download .vi file and open with compatible LabVIEW software. Download associated sampledummydata to be used with LabVIEW vi. 2- View annotated instructions in LabVIEW front panel. 3- Load sample data and run program. Requirements: Matlab toolboxes required: curve fitting toolbox, statistics and machine learning toolbox For several figures, hline and vline functions will be needed for plotting. These functions are available at https://www.mathworks.com/matlabcentral/fileexchange/1039-hline-and-vline REFERENCE: Brandon Kuczenski (2021). hline and vline (https://www.mathworks.com/matlabcentral/fileexchange/1039-hline-and-vline), MATLAB Central File Exchange. Retrieved August 1, 2021. For Figure 4, boxplotgroup function is needed for plotting. This function can be downloaded at https://www.mathworks.com/matlabcentral/fileexchange/74437-boxplotgroup REFERENCE: Adam Danz (2021). boxplotGroup (https://www.mathworks.com/matlabcentral/fileexchange/74437-boxplotgroup), MATLAB Central File Exchange. Retrieved August 1, 2021. Please reference this work using: Data and code: Rasman BG, Forbes PA, Peters RM, Ortiz O, Franks I, Inglis JT, Chua R, and Blouin JS. 2021, "Data and code for "Learning to stand with unexpected sensorimotor delays", DOI: https://doi.org/10.5683/SP2/IKX9ML, Scholars Portal Dataverse Paper: Rasman BG, Forbes PA, Peters RM, Ortiz O, Franks I, Inglis JT, Chua R, and Blouin JS. Learning to stand with unexpected sensorimotor delays. eLife. 2021: e65085. DOI: https://doi.org/10.7554/eLife.65085 These files consist of data and Matlab code needed to reproduce the main result figures from Experiments 1, 2 and 3 of "Learning to stand with unexpected sensorimotor delays". Additionally, LabVIEW code is provided to produce robust Bayesian fits for perceptual data. Data and results include: standing balance behavior (sway velocity variance, percent time within balancing limits) with imposed delays, vestibular-evoked muscle responses (coherence, gain, cross-covariance) when standing with imposed delays, and perceptual thresholds to detecting unexpected standing motion when standing with imposed delays. Data are provided in spreadsheets (for viewing purposes) and also in .mat matlab files (to run with source code).

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Lunarisarrow_drop_down
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    Lunaris
    Dataset . 2021
    Data sources: Lunaris
    Borealis
    Dataset . 2021
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Lunarisarrow_drop_down
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      Lunaris
      Dataset . 2021
      Data sources: Lunaris
      Borealis
      Dataset . 2021
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bradbury, Ian R.; Wringe, Brendan F.; Watson, Beth; Paterson, Ian; +10 Authors

    Individual assignment and genetic mixture analysis are commonly utilized in contemporary wildlife and fisheries management. Although microsatellite loci provide unparalleled numbers of alleles per locus, their use in assignment applications is increasingly limited. However, next-generation sequencing, in conjunction with novel bioinformatic tools allows large numbers of microsatellite loci to be simultaneously genotyped, presenting new opportunities for individual assignment and genetic mixture analysis. Here we scanned the published Atlantic salmon genome to identify 706 microsatellite loci, from which we developed a final panel of 101 microsatellites distributed across the genome (average 3.4 loci per chromosome). Using samples from 35 Atlantic salmon populations (n=1485 individuals) from coastal Labrador, Canada, a region characterized by low levels of differentiation in this species, this panel identified 844 alleles (average of 8.4 alleles per locus). Simulation-based evaluations of assignment and mixture identification accuracy revealed unprecedented resolution, clearly identifying 26 rivers or groups of rivers spanning 500 km of coastline. This baseline was used to examine the stock composition of 696 individuals harvested in the Labrador Atlantic salmon fishery and revealed that coastal fisheries largely targeted regional groups (<300km). This work suggests that the development and application of large sequenced microsatellite panels presents great potential for stock resolution in Atlantic salmon and more broadly in other exploited anadromous and marine species. Labrador Atlantic Salmon Sequenced Microsatellite DataGenepop file of sequenced microsatellite genotype data for 35 salmon populations in Labrador Canada.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODO; Federated Re...arrow_drop_down
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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODO; Federated Re...arrow_drop_down
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Savoie, Amanda M.; Saunders, Gary W.;

    There is currently conflict in the literature on the taxonomic status of the reportedly cosmopolitan species Neosiphonia harveyi, a common red alga along the coast of Atlantic Canada and New England, USA. Neosiphonia harveyi sensu lato was assessed using three molecular markers: COI-5P, ITS and rbcL. All three markers clearly delimited three genetic species groups within N. harveyi sensu lato in this region, which we identified as N. harveyi, N. japonica and Polysiphonia akkeshiensis (here resurrected from synonymy with N. japonica). Although Neosiphonia harveyi is considered by some authors to be introduced to the Atlantic from the western Pacific, it was only confirmed from the North Atlantic suggesting it is native to this area. In contrast, Neosiphonia japonica was collected from only two sites in Rhode Island, USA, as well as from its reported native range in Asia (South Korea), which when combined with data in GenBank indicates that this species was introduced to the Northwest Atlantic. The GenBank data further indicate that N. japonica was also introduced to North Carolina, Spain, Australia and New Zealand. Despite the fact that all three markers clearly delimited N. harveyi and N. japonica as distinct genetic species groups, the ITS sequences for some N. harveyi individuals displayed mixed patterns and additivity indicating introgression of nuclear DNA from N. japonica into N. harveyi in the Northwest Atlantic. Introgression of DNA from an introduced species to a native species (i.e. “genetic pollution”) is one of the possible consequences of species introductions, and we believe this is the first documented evidence for this phenomenon in red algae. ITS sequence alignmentAn alignment of ITS sequences that were used to create a neighbor-joining tree for Figure 1COI-5P sequence alignmentAn alignment of COI-5P sequences that were used to create a neighbor-joining tree for Figure 1rbcL sequence alignmentAn alignment of rbcL sequences that were used to create a neighbor-joining tree for Figure 3Figure 3 rbcL treeA neighbor-joining tree generated from rbcL sequence dataFigure 1 COI-5P treeA neighbor-joining tree generated from COI-5P sequence dataFigure 1 ITS treeA neighbor-joining tree generated from ITS sequence data

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    DANS-EASY
    Dataset . 2015
    Data sources: B2FIND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODO; Federated Re...arrow_drop_down
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      DANS-EASY
      Dataset . 2015
      Data sources: B2FIND
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    Authors: Chen, Yining; Clark, Oliver; Woolley, Sarah C.;

    The performance of courtship signals provides information about the behavioural state and quality of the signaller, and females can use such information for social decision-making (e.g. mate choice). However, relatively little is known about the degree to which the perception of and preference for differences in motor performance are shaped by developmental experiences. Furthermore, the neural substrates that development could act upon to influence the processing of performance features remains largely unknown. In songbirds, females use song to identify males and select mates. Moreover, female songbirds are often sensitive to variation in male song performance. Consequently, we investigated how developmental exposure to adult male song affected behavioural and neural responses to song in a small, gregarious songbird, the zebra finch. Zebra finch males modulate their song performance when courting females, and previous work has shown that females prefer the high-performance, female-directed courtship song. However, unlike females allowed to hear and interact with an adult male during development, females reared without developmental song exposure did not demonstrate behavioural preferences for high-performance courtship songs. Additionally, auditory responses to courtship and non-courtship song were altered in adult females raised without developmental song exposure. These data highlight the critical role of developmental auditory experience in shaping the perception and processing of song performance. EGR1_dataNumber of EGR1 neurons/mm2 in the NCM, CMM and IC.preference_score_by_maleIDAverage preference scores of all females tested on each male stimulus.preference_scores_all_femalesraw data for call back preference tests for normally-reared and song-naive females tested on stimuli from different malespreference_score_vs_song_measuresPercent difference for measures of song between courtship and non-courtship singing. Measures include the number of introductory notes and motifs, syllable entropy, CV of the fundamental frequency and song tempo (motif duration).

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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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    Authors: Bitton, Pierre-Paul; Yun Christmann, Sebastian Alejandro; Santon, Matteo; Harant, Ulrike K.; +1 Authors

    Active sensing has been well documented in animals that use echolocation and electrolocation. Active photolocation, or active sensing using light, has received much less attention, and only in bioluminescent nocturnal species. However, evidence has suggested the diurnal triplefin Tripterygion delaisi uses controlled iris radiance, termed ocular sparks, for prey detection. While this form of diurnal active photolocation was behaviourally described, a study exploring the physical process would provide compelling support for this mechanism. In this paper, we investigate the conditions under which diurnal active photolocation could assist T. delaisi in detecting potential prey. In the field, we sampled gammarids (genus Cheirocratus) and characterized the spectral properties of their eyes, which possess strong directional reflectors. In the laboratory, we quantified ocular sparks size and their angle-dependent radiance. Combined with environmental light measurements and known properties of the visual system of T. delaisi, we modeled diurnal active photolocation under various scenarios. Our results corroborate that diurnal active photolocation should help T. delaisi detect gammarids at distances relevant to foraging, 4.5 cm under favourable conditions and up to 2.5 cm under average conditions. To determine the prevalence of diurnal active photolocation for micro-prey, we encourage further theoretical and empirical work. Average gammarid body reflectanceSpectrophotometric data for body reflectance of Cheirocratus gammaridsAverage gammarid body transmissionSpectrophotometric transmission measurements of Cheirocratus gammarid bodyBackground reflectance Haliopteris filicianaSpectrophotometric measurements of Haliopteris filicianaCoaxial reflectance values categoricalReflective properties of Gammarid eyes measured with coaxial light sourceDownwelling and sidewelling illuminant for analysesDownwelling and sidewelling light fieldsEye reflectance conversion values categoricalConversion factors to produce non-coaxial reflectance values from co-axial reflectance values for gammarid eyesOcular media valuesTransmission properties of the ocular media of Tripterigyon delaisiOcular spark conversion on continuous scaleConversion curves for transforming downwelling irradiance into ocular spark radianceSA scores Gammarid as perceived by Td pupilSolid angle of the gammarid eye as perceived from the pupil of T. delaisi based on the interaction distanceSA scores Os as perceived by Gammarid eye MATRIXSolid angles of the Ocular spark from T delaisi as perceived by the gammarid eye based on the interaction distance

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    DRYAD; ZENODO
    Dataset . 2019
    License: CC 0
    Data sources: Datacite; ZENODO
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      DRYAD; ZENODO
      Dataset . 2019
      License: CC 0
      Data sources: Datacite; ZENODO
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    Authors: Xia, Wenjing; Nielly-Thibault, Lou; Charron, Guillaume; Landry, Christian R.; +3 Authors

    Genetic diversity in experimental, domesticated and wild populations of the related yeasts, Saccharomyces cerevisiae and S. paradoxus has been well described at the global scale. We investigated the population genomics of a local population on a small spatial scale to address two main questions. First, is there genomic variation in a S. paradoxus population at a spatial scale spanning centimeters (microsites) to tens of meters? Second, does the distribution of genomic variants persist over time? Our sample consisted of 42 S. paradoxus strains from 2014 and 43 strains from 2015 collected from the same 72 microsites around four host trees (Quercus rubra and Q. alba) within 1km2 in a mixed hardwood forest in southern Ontario. Six additional S. paradoxus strains recovered from adjacent maple and beech trees in 2015 are also included in the sample. Whole-genome sequencing and genomic SNP analysis revealed five differentiated groups (clades) within the sampled area. The signal of persistence of genotypes in their microsites from 2014 to 2015 was highly significant. Isolates from the same tree tended to be more related than strains from different trees, with limited evidence of dispersal between trees. In growth assays, one genotype had a significantly longer lag phase than the other strains. Our results indicate that different clades co-exist at fine spatial scale, and that population structure persists over at least a one year interval in these wild yeasts, suggesting the efficacy of yearly sampling to follow longer term genetic dynamics in future studies. cohort SNP filevariant file of all strains, contains all single nucleotide polymorphic sites that are bi-allelic only.all_bi-allelic-non-missing.vcf.gz

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    DANS-EASY
    Dataset . 2016
    Data sources: B2FIND
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      Dataset . 2016
      Data sources: B2FIND
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    Authors: Bernhardt, Boris C.; Fadaie, Fatemeh; Liu, Min; Caldairou, Benoit; +6 Authors

    OBJECTIVE. To assess whether HS severity is mirrored at the level of large-scale networks. METHODS. We studied preoperative high-resolution anatomical and diffusion-weighted MRI of 44 TLE patients with histopathological diagnosis of HS (n=25; TLE-HS) and isolated gliosis (n=19; TLE-G), and 25 healthy controls. Hippocampal measurements included surface-based subfield mapping of atrophy and T2 hyperintensity indexing cell loss and gliosis, respectively. Whole-brain connectomes were generated via diffusion tractography and examined using graph theory along with a novel network control theory paradigm which simulates functional dynamics from structural network data. RESULTS. Compared to controls, we observed markedly increased path length and decreased clustering in TLE-HS compared to controls, indicating lower global and local network efficiency, while TLE-G showed only subtle alterations. Similarly, network controllability was lower in TLE-HS only, suggesting limited range of functional dynamics. Hippocampal imaging markers were positively associated with macroscale network alterations, particularly in ipsilateral CA1-3. Systematic assessment across several networks revealed maximal changes in the hippocampal circuity. Findings were consistent when correcting for cortical thickness, suggesting independence from grey matter atrophy. CONCLUSIONS. Severe HS is associated with marked remodeling of connectome topology and structurally-governed functional dynamics in TLE, as opposed to isolated gliosis which has negligible effects. Cell loss, particularly in CA1-3, may exert a cascading effect on brain-wide connectomes, underlining coupled disease processes across multiple scales. Data_phen_conn_dryadPhenotypic information and mean connectome feature data for Bernhardt et al. (2019) Temporal lobe epilepsy: hippocampal pathology modulates white matter connectome topology and controllability. Neurology

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    DANS-EASY
    Dataset . 2019
    Data sources: B2FIND
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    DRYAD; ZENODO
    Dataset . 2019
    License: CC 0
    Data sources: ZENODO; Datacite
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      Dataset . 2019
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      DRYAD; ZENODO
      Dataset . 2019
      License: CC 0
      Data sources: ZENODO; Datacite
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    Authors: Dalziel, Anne C.; Martin, Nicolas; Laporte, Martin; Guderley, Helga; +1 Authors

    The physiological mechanisms underlying local adaptation in natural populations of animals, and whether the same mechanisms contribute to adaptation and acclimation, are largely unknown. Therefore, we tested for evolutionary divergence in aerobic exercise physiology in laboratory bred, size-matched crosses of ancestral, benthic, normal Lake Whitefish (Coregonus clupeaformis) and derived, limnetic, more actively-swimming ‘dwarf’ ecotypes. We acclimated fish to constant swimming (emulating limnetic foraging) and control conditions (emulating normal activity levels) to simultaneously study phenotypic plasticity. We found extensive divergence between ecotypes: dwarf fish generally had constitutively higher values of traits related to oxygen transport (ventricle size) and use by skeletal muscle (percent oxidative muscle, mitochondrial content), and also evolved differential plasticity of mitochondrial function (Complex I activity and flux through Complexes I-IV and IV). The effects of swim-training were less pronounced than differences among ecotypes and the traits which had a significant training effect (ventricle protein content, ventricle MDH activity and muscle Complex V activity) did not differ among ecotypes. Only one trait, ventricle mass, varied in a similar manner with acclimation and adaptation and followed a pattern consistent with genetic accommodation. Overall, the physiological and biochemical mechanisms underlying acclimation and adaptation to swimming activity in Lake Whitefish generally differ. R code for nested, two-way ANOVAsR code for nested, two-way ANOVAs (example for Fig. 1A)Figs1-6_MixedEffectsModel_Code.RR_Code_for_DFAR_Code_for_DFA (Fig. 7)Fig7_DFA_Code.RFig1A_HematocritData for Figure 1AFig1B_VentricleMassData for Figure 1BFig2_HeartEnzymesData for Figure 2Fig3A_PercentRMData for Figure 3AFig3C,E_CapillaryDensityData for Figure 3C,EFig4_MuscleEnzymesData for Figure 4Fig5_MitoRespirationData for Figure 5Fig6_ETCenzymesData for Figure 6Fig7_DF(tank_means)Data for Figure 7 - tank means for all significant variables

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    DANS-EASY
    Dataset . 2015
    Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Manning, Cara C M; Zheng, Zhiyin; Fenwick, Lindsay; McCulloch, Ross D; +6 Authors

    This dataset contains methane and nitrous oxide dissolved gas concentration, dissolved methane carbon isotope, and ancillary hydrographic data from research cruises in the North American Arctic Ocean between 2015-2018. Ocean samples for methane and nitrous oxide analysis were collected from Niskin bottles mounted on a CTD rosette. Water was collected into glass serum bottles and allowed to overflow three times before preserving with mercuric chloride and sealing with with butyl rubber stoppers and aluminum crimp seals. Gas concentrations were determined using a purge and trap system coupled to a gas chromatograph/mass spectrometer, following the method of Capelle et al. (2015). Equilibrium dry atmospheric concentrations were 328.25, 329.14, 330.11, and 330.96 ppb for N2O and 1919.64, 1933.67, 1934.92, and 1933.50 ppb for CH4 in 2015, 2016, 2017, and 2018, respectively. Equilibrium dissolved concentrations were calculated from the measured temperature and salinity following Wiesenburg and Guinasso (1979) for CH4 and Weiss and Price (1980) for N2O. Equilibrium concentrations were calculated based on sample temperature and salinity and the atmospheric N2O or CH4 concentrations measured at Barrow, Alaska by the NOAA Earth System Research Laboratory Global Monitoring Division (Dlugokencky et al., 2020a,b), with corrections to local sea level pressure and 100% humidity. Oxygen concentration was determined using an oxygen sensor mounted on the Niskin rosette, calibrated with discrete samples analyzed by Winkler titration. The mixed layer depth was defined based on a potential density difference criterion of 0.125 kg/m³ relative to the density at 5 m depth, using CTD profiles binned to 1 m. The mixed layer depth was set to 5 m as a minimum. The instantaneous gas transfer velocities and fluxes are based on the instantaneous wind speed at the time of sampling. The 30-day weighted gas transfer velocities and fluxes are integrated over the residence time of the gas in the mixed layer, using up to the prior 30 days of observations, following the method of Teeter et al. (2018) as described in the main manuscript of Manning et al. (2022). The 60-day weighted gas transfer velocities and fluxes are integrated over the residence time of the gas in the mixed layer, using the prior 60 days of observations, following the method of Teeter et al. (2018) as described in the main manuscript of Manning et al. (2022). Atmospheric sea level pressure was obtained from the NCEP/NCAR reanalysis product, which is provided by the NOAA-ESRL Physical Sciences Laboratory (https://psl.noaa.gov/data/gridded). Fractional ice cover was obtained from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (https://osi-saf.eumetsat.int). Sea ice concentration product AMSR-2 (identifier OSI-408) was used in 2017–2018 and SSMIS (identifier OSI-401-b) was used in 2015–2016.

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Background: The origin of powered avian flight was a locomotor innovation that expanded the ecological potential of maniraptoran dinosaurs, leading to remarkable variation in modern birds (Neornithes). The avian sternum is the anchor for the major flight muscles and, despite varying widely in morphology, has not been extensively studied from evolutionary or functional perspectives. We quantify sternal variation across a broad phylogenetic scope of birds using 3D geometric morphometrics methods. Using this comprehensive dataset, we apply phylogenetically informed regression approaches to test hypotheses of sternum size allometry and the correlation of sternal shape with both size and locomotory capabilities, including flightlessness and the highly varying flight and swimming styles of Neornithes. Results: We find evidence for isometry of sternal size relative to body mass and document significant allometry of sternal shape alongside important correlations with locomotory capability, reflecting the effects of both body shape and musculoskeletal variation. Among these, we show that a large sternum with a deep or cranially projected sternal keel is necessary for powered flight in modern birds, that deeper sternal keels are correlated with slower but stronger flight, robust caudal sternal borders are associated with faster flapping styles, and that narrower sterna are associated with running abilities. Correlations between shape and locomotion are significant but show weak explanatory power, indicating that although sternal shape is broadly associated with locomotory ecology, other unexplored factors are also important. Conclusions: These results display the ecological importance of the avian sternum for flight and locomotion by providing a novel understanding of sternum form and function in Neornithes. Our study lays the groundwork for estimating the locomotory abilities of paravian dinosaurs, the ancestors to Neornithes, by highlighting the importance of this critical element for avian flight, and will be useful for future work on the origin of flight along the dinosaur-bird lineage.

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    figshare
    Collection . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Collection . 2021
    License: CC BY
    Data sources: Datacite
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      figshare
      Collection . 2021
      License: CC BY
      Data sources: Datacite
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      Collection . 2021
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    Authors: Rasman, Brandon G; Forbes, Patrick A; Peters, Ryan M; Ortiz, Oscar; +4 Authors

    Instructions for Matlab code and main result figures: 1- Download all data files and Matlab functions (see requirements) and ensure they are all in the same directory. 2- Open SourceCode_GroupFigures_RasmanEtAl_Elife2021.m with Matlab. 3- Make sure Matlab is currently in the folder where you put the files or add that folder to the path. 4- Run the code. All group result figures will be generated. Matlab will output warning when running the exponential fit procedure, but this is expected for the code. Instructions for LabVIEW code: 1- Download .vi file and open with compatible LabVIEW software. Download associated sampledummydata to be used with LabVIEW vi. 2- View annotated instructions in LabVIEW front panel. 3- Load sample data and run program. Requirements: Matlab toolboxes required: curve fitting toolbox, statistics and machine learning toolbox For several figures, hline and vline functions will be needed for plotting. These functions are available at https://www.mathworks.com/matlabcentral/fileexchange/1039-hline-and-vline REFERENCE: Brandon Kuczenski (2021). hline and vline (https://www.mathworks.com/matlabcentral/fileexchange/1039-hline-and-vline), MATLAB Central File Exchange. Retrieved August 1, 2021. For Figure 4, boxplotgroup function is needed for plotting. This function can be downloaded at https://www.mathworks.com/matlabcentral/fileexchange/74437-boxplotgroup REFERENCE: Adam Danz (2021). boxplotGroup (https://www.mathworks.com/matlabcentral/fileexchange/74437-boxplotgroup), MATLAB Central File Exchange. Retrieved August 1, 2021. Please reference this work using: Data and code: Rasman BG, Forbes PA, Peters RM, Ortiz O, Franks I, Inglis JT, Chua R, and Blouin JS. 2021, "Data and code for "Learning to stand with unexpected sensorimotor delays", DOI: https://doi.org/10.5683/SP2/IKX9ML, Scholars Portal Dataverse Paper: Rasman BG, Forbes PA, Peters RM, Ortiz O, Franks I, Inglis JT, Chua R, and Blouin JS. Learning to stand with unexpected sensorimotor delays. eLife. 2021: e65085. DOI: https://doi.org/10.7554/eLife.65085 These files consist of data and Matlab code needed to reproduce the main result figures from Experiments 1, 2 and 3 of "Learning to stand with unexpected sensorimotor delays". Additionally, LabVIEW code is provided to produce robust Bayesian fits for perceptual data. Data and results include: standing balance behavior (sway velocity variance, percent time within balancing limits) with imposed delays, vestibular-evoked muscle responses (coherence, gain, cross-covariance) when standing with imposed delays, and perceptual thresholds to detecting unexpected standing motion when standing with imposed delays. Data are provided in spreadsheets (for viewing purposes) and also in .mat matlab files (to run with source code).

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    Lunaris
    Dataset . 2021
    Data sources: Lunaris
    Borealis
    Dataset . 2021
    Data sources: Datacite
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      Lunaris
      Dataset . 2021
      Data sources: Lunaris
      Borealis
      Dataset . 2021
      Data sources: Datacite
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    Authors: Bradbury, Ian R.; Wringe, Brendan F.; Watson, Beth; Paterson, Ian; +10 Authors

    Individual assignment and genetic mixture analysis are commonly utilized in contemporary wildlife and fisheries management. Although microsatellite loci provide unparalleled numbers of alleles per locus, their use in assignment applications is increasingly limited. However, next-generation sequencing, in conjunction with novel bioinformatic tools allows large numbers of microsatellite loci to be simultaneously genotyped, presenting new opportunities for individual assignment and genetic mixture analysis. Here we scanned the published Atlantic salmon genome to identify 706 microsatellite loci, from which we developed a final panel of 101 microsatellites distributed across the genome (average 3.4 loci per chromosome). Using samples from 35 Atlantic salmon populations (n=1485 individuals) from coastal Labrador, Canada, a region characterized by low levels of differentiation in this species, this panel identified 844 alleles (average of 8.4 alleles per locus). Simulation-based evaluations of assignment and mixture identification accuracy revealed unprecedented resolution, clearly identifying 26 rivers or groups of rivers spanning 500 km of coastline. This baseline was used to examine the stock composition of 696 individuals harvested in the Labrador Atlantic salmon fishery and revealed that coastal fisheries largely targeted regional groups (<300km). This work suggests that the development and application of large sequenced microsatellite panels presents great potential for stock resolution in Atlantic salmon and more broadly in other exploited anadromous and marine species. Labrador Atlantic Salmon Sequenced Microsatellite DataGenepop file of sequenced microsatellite genotype data for 35 salmon populations in Labrador Canada.

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