Additional file 2: Table S1. Raw data used for all statistical analyses.
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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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Additional file 14.
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Additional file 8. Supplementary Material 8.
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Additional file 22: Supplemental Table 9. Metabolic pathways enriched in transcripts expressed in the ceca exhibiting significant differential expression between AGPs and diets.
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Individual Kimura distances of RTE1_Sar. (CSV 44.7 kb)
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Additional file 3. Micro-habitat colonization and age-dependent incidence: Caenorhabditis colonization of orange bait samples distributed at 72 spots along trail system. At each of the 72 spots (Parare, Nouragues Natural Reserve), three baits were distributed (i.e. subsamples, labelled a, b, c) approximately 1 meter apart from each other. See also Additional file 7.
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doi: 10.26138/sxs:bbh:0397v1.4 , 10.26138/sxs:bbh:0397v1.3 , 10.26138/sxs:bbh:0397v2.0 , 10.26138/sxs:bbh:0397v1.5 , 10.5281/zenodo.13168839 , 10.26138/sxs:bbh:0397v1.2 , 10.5281/zenodo.13168838 , 10.5281/zenodo.1236539 , 10.26138/sxs:bbh:0397 , 10.5281/zenodo.2625865 , 10.5281/zenodo.2642315 , 10.5281/zenodo.1236540 , 10.5281/zenodo.3274935 , 10.5281/zenodo.3319759
doi: 10.26138/sxs:bbh:0397v1.4 , 10.26138/sxs:bbh:0397v1.3 , 10.26138/sxs:bbh:0397v2.0 , 10.26138/sxs:bbh:0397v1.5 , 10.5281/zenodo.13168839 , 10.26138/sxs:bbh:0397v1.2 , 10.5281/zenodo.13168838 , 10.5281/zenodo.1236539 , 10.26138/sxs:bbh:0397 , 10.5281/zenodo.2625865 , 10.5281/zenodo.2642315 , 10.5281/zenodo.1236540 , 10.5281/zenodo.3274935 , 10.5281/zenodo.3319759
Simulation of a black-hole binary system evolved by the SpEC code.
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doi: 10.26138/sxs:bbh:0662v1.2 , 10.26138/sxs:bbh:0662 , 10.26138/sxs:bbh:0662v2.0 , 10.26138/sxs:bbh:0662v1.5 , 10.26138/sxs:bbh:0662v1.3 , 10.5281/zenodo.13161918 , 10.26138/sxs:bbh:0662v1.4 , 10.5281/zenodo.13161919 , 10.5281/zenodo.1237243 , 10.5281/zenodo.1237244 , 10.5281/zenodo.3275544 , 10.5281/zenodo.2639220 , 10.5281/zenodo.2621943 , 10.5281/zenodo.3323699
doi: 10.26138/sxs:bbh:0662v1.2 , 10.26138/sxs:bbh:0662 , 10.26138/sxs:bbh:0662v2.0 , 10.26138/sxs:bbh:0662v1.5 , 10.26138/sxs:bbh:0662v1.3 , 10.5281/zenodo.13161918 , 10.26138/sxs:bbh:0662v1.4 , 10.5281/zenodo.13161919 , 10.5281/zenodo.1237243 , 10.5281/zenodo.1237244 , 10.5281/zenodo.3275544 , 10.5281/zenodo.2639220 , 10.5281/zenodo.2621943 , 10.5281/zenodo.3323699
Simulation of a black-hole binary system evolved by the SpEC code.
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Abstract Background Acoustic telemetry is an increasingly common method used to address ecological questions about the movement, behaviour, and survival of freshwater and marine organisms. The variable performance of acoustic telemetry equipment and ability of receivers to detect signals from transmitters have been well studied in marine and coral reef environments to inform study design and improve data interpretation. Despite the growing use of acoustic telemetry in large, deep, freshwater systems, detection efficiency and range, particularly in relation to environmental variation, are poorly understood. We used an array of 90 69-kHz acoustic receivers and 8 sentinel range transmitters of varying power output deployed at different depths and locations approximately 100–9500 m apart for 215 days to evaluate how the detection efficiency of acoustic receivers varied spatially and temporally in relation to environmental conditions. Results The maximum distance that tags were detected ranged from 5.9 to 9.3 km. Shallow tags consistently had lower detection efficiency than deep tags of the same power output and detection efficiency declined through the winter months (December–February) of the study. In addition to the distance between tag and receiver, thermocline strength, surface water velocity, ice thickness, water temperature, depth range between tag and receiver, and number of fish detections contributed to explaining variation in detection efficiency throughout the study period. Furthermore, the most significant models incorporated interactions between several environmental variables and tag–receiver distance, demonstrating the complex temporal and spatial relationships that exist in heterogeneous environments. Conclusions Relying on individual environmental variables in isolation to interpret receiver performance, and thus animal behaviour, may be erroneous when detection efficiency varies across distances, depths, or tag types. As acoustic telemetry becomes more widely used to study ecology and inform management, it is crucial to understand its limitations in heterogeneous environments, such as freshwater lakes, to improve the quality and interpretation of data. We recommend that in situ range testing and retrospective analysis of detection efficiency be incorporated into study design for telemetry projects. Furthermore, we caution against oversimplifying the dynamic relationship between detection efficiency and environmental conditions for the sake of producing a correction that can be applied directly to detection data of tagged animals when the intended correction may not be justified.
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Additional file 2: Table S1. Raw data used for all statistical analyses.
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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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Additional file 14.