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209 results for “Submergence”
CVPIA Predation Contact Point Study - 2022: The impact of submerged aquatic vegetation removal on fish predation in a tidal river channel
Proliferation of non-native submerged aquatic vegetation (SAV) has the potential to cause widespread ecosystem changes, and has been attributed to declines in native fish populations around the world. One pathway for these declines is non-native SAV may render ecosystems more hospitable to fish predator species by creating habitat structure, by altering lower trophic food webs, or by affecting predator-prey interactions. It is presumed that non-native vegetation removal will generally favor native fish, however, fish community responses to SAV removals are not well understood. Using a field-based Before-After-Control-Impact study design, we measured the impact of manual SAV removals on short-term changes in predator abundance, predation risk on juvenile Chinook salmon ( Oncorhynchus tshawytscha ; a native fish of management concern), and the aerobic scope of predator and prey in California’s Sacramento-San Joaquin Delta. We found that, while SAV removals decreased abundances of the most common SAV-associated predator, largemouth bass ( Micropterus salmoides ), they resulted in higher predation risk of tethered prey, likely due to the removal of refuge habitat and the immigration of an open-water predator, striped bass ( Morone saxatilis ). SAV removals also buffered against a seasonal decline in environmental oxygen supply, increasing the aerobic scope of juvenile Chinook salmon and largemouth bass; whether such gains for prey would outweigh the persistent aerobic advantage of predators is an open question. While limited in spatial and temporal scope, this study has put into question any short-term benefits of small-scale SAV removal efforts for native fish populations, especially in areas where open-water predator species are abundant.
Indicative distribution map for Ecosystem Functional Group M4.1 Submerged artificial structures
<p>This archive contains indicative distribution maps and profiles for <strong>M4.1 Submerged artificial structures</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Contour method and neutron diffraction dataset to determine the weld fusion zone shape on residual stress in submerged arc welding
<p>This is a dataset which formed the basis for "The effect of the weld fusion zone shape on residual stress in submerged arc welding" by A. Ishigami, M. J. Roy, J. N. Walsh and P. J. Withers appearing in the Journal of Advanced Manufacturing Technology.</p> <p>Two X-grade steel specimens with different high speed, submerged arc welds with very slight differences in fusion zone shape were compared with a novel contour method application as well as with neutron diffraction. Neutron diffraction was carried out with the SALSA instrument at the Institut Laue-Langevin in Grenoble, France with the assistance of T. Pirling. Data files with 441 in the descriptor refer to 'conventional' parameters (see publication), while 241 refers to 'new'.</p> <p>Provided in this dataset are four *.dat files, which contains data is in the form of a point cloud with one point per line, whitespace delimited in microns. Data was captured with a Nanofocus CF-4 laser profilometer sensor with point spacing 30 µm apart. Data with z coordinates below or above 500 µm are considered outside of the surface detection limits.</p> <p>Also included is an Excel worksheet, which contains the calculated residual stresses as found with LAMP (https://www.ill.eu/instruments-support/computing-for-science/cs-software/all-software/lamp/). Raw data is available here:</p> <p>P. J. Withers, A. Ishigami, T. Pirling, M. Roy, J. Walsh (2014). The effect of weld bead shape on residual stress in novel low heat input welding of steel [Data set]. ILL. http://doi.ill.fr/10.5291/ILL-DATA.1-02-145</p> <p>The authors would like to thank JFE Steel Corporation for both direct and in-direct support of this research. The authors would also like to thank the Institut Max von Laue-Paul Langevin for the allocation of beamtime at SALSA and gratefully acknowledge the help of Thilo Pirling for his assistance in performing the neutron diffraction experiments. A. Ishigami would like to thank Kenji Oi for his support of this research. M. J. Roy would like to thank Ian Winstanley for his assistance in performing the contour cuts. M. J. Roy acknowledges financial support from the EPSRC (EP/L01680X/1) through the Materials for Demanding Environments Centre for Doctoral Training.</p>
Data to reproduce the results presented in Lake et al. 2021. Journal of Soils and Sediments, https://doi.org/10.1007/s11368-021-03107-6 ("High frequency un-mixing of soil samples using a submerged spectrophotometer in a laboratory setting – implications for sediment fingerprinting")
<p>This repository contains data on (1) the absorbance data and (2) the measured concentrations, to reproduce computational results as presented in:<br> "High frequency un-mixing of soil samples using a submerged spectrophotometer in a laboratory setting – implications for sediment fingerprinting".</p> <p> <br> 1. Absorbance data (200-730 nm wavelengths):</p> <p> * Average absorbance compensated for measured concentrations (average absorbance value per concentration)<br> * Average absorbance compensated for theoretical concentrations (average absorbance value per concentration)<br> * Average raw absorbance measured (average absorbance value per concentration)<br> * Raw absorbance measured (all absorbance values for all concentrations)</p> <p> Data in all 3 files is indicated per soil sample / mixture, with corresponding fraction(s) of soil sample(s) and corresponding (theoretical) input concentration.<br> <br> 2. Measured concentration data:</p> <p> * Measured concentration (average concentrations, tested for all experiments and for all theoretical input concentrations)</p> <p> </p>
Data on submerged aquatic vegetation and its water environment in Lake Saint-Pierre, Saint Lawrence River, from 2012 to 2016
<p>This dataset is the result of a large collaborative work lead by the GRIL from 2012 to 2015 on a submerged aquatic vegetation meadow located downstream of two agricultural tributaries (Saint-François and Yamaska rivers) in Lake Saint-Pierre, a fluvial lake of the Saint Lawrence River. The data describe plants (as rake biomass and echosounding) and their environment, including water chemistry, current velocity as well as light, temperature and instantaneous meteo. Only echosounding data are available in 2016 and sediments were collected in 2015. Data are organized as a relational database and the GRIL_LSP_database.png provides keys and links between tables as well as data format. Data are in the tables mesure_integree, mesure_spatiale, mesure_verticale, plante_biomass_taxon, plante_recolte, plante_in_situ. The other tables are metadata about spatiotemporal locations and reported measures. Additional data (e.g. zooplankton, sediments) should eventually be made available and associated to this overall GRIL dataset.</p>
Submerged aquatic vegetation and nitrogen retention data from 2012 to 2017 in lake Saint-Pierre, Saint Lawrence River
<p>Here we provide seven datasets that describes plant biomass (2012 to 2016), environmental variables and nitrogen retention time series (2012 to 2016) in a submerged aquatic vegetation (SAV) meadow at the confluence of two agricultural tributaries (Saint-François and Yamaska) with the St. Lawrence River in southern Lake Saint-Pierre.</p> <p>Version 2 adds the dataset 6 and 7.</p> <p>The seven datasets are:</p> <p>1) Growing season (June 21 to September 22) daily environmental variables (water level, water temperature, light, tributaries input, and SAV biomass indicator)</p> <p>2) Mean SAV biomass measured using rake or quadrat samples in the meadow</p> <p>3) Modelled daily nitrate tributary inputs to the SAV bed</p> <p>4) Daily nitrate output to the SAV bed estimated from a sensor</p> <p>5) Daily nitrate budget</p> <p>6) Hourly nitrate output to the SAV bed and signal decomposition from ensemble empirical mode decomposition (EEMD)</p> <p>7) Hourly dissolved oxygen and gas exchange velocities at the SAV bed outflow for 2016</p> <p>Original data comes from Lake Saint-Pierre, either from publicly available government agencies data, from a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal) or from Christiane Hudon (ECCC). Data were created for an article on climate-driven variation in nitrogen retention, led by Morgan Botrel and supervisor Roxane Maranger, with Christiane Hudon, James B. Heffernan and Pascale M. Biron (https://doi.org/10.1029/2022WR032678).</p>
Data underlying the article "Effect of Submergence on the Lateral Exchange between Groyne Fields and their adjacent Main Channel"
<p>The paper addresses the identification of the mechanisms that dominate the flow around a series of obstacles placed at the sidewall of a channel, representing fluvial groynes. Accordingly, 2D velocity fields were measured through Particle Image Velocimetry in a horizontal plane spanning the area between groynes and an adjacent portion of the main channel. Four experimental cases were performed, addressing two groyne separations and two submergence conditions (emerged and submerged). For the submerged case, the ratio water depth to groyne height was 1.3. Groyne separations were characterized according to the corresponding width-to-length ratio of the groyne field (lambda = W/L = 1 and 2). A complete description of the experimental conditions, objectives and outcomes can be found in the article.</p> <p>The following data is included:</p> <ol> <li>Meanfields_[case].csv: spanwise and streamwise components of the velocity field, velocity magnitude and uv component of the Reynolds stress tensor averaged over time.</li> <li>Reynoldsstressesprofiles_[case].csv: uv component of the Reynolds stress tensor averaged over time at selected transverse profiles.</li> <li>PSD_[case].csv: power spectral densities computed from fluctuating velocity series extracted at selected locations.</li> <li>Autoccorrelation_[case].csv: normalized transverse autocorrelation functions computed from fluctuating velocity series extracted at selected locations.</li> <li>PODenergycontribution.csv: energy contribution from the first 20 POD modes computed for the case studies.</li> <li>PODtemporalcoefficients.csv: temporal coefficients obtained from the first two modes for the case studies.</li> <li>PODspectra_[case].csv: spectra of the temporal coefficients corresponding to modes 1 to 4 for the cases in study.</li> <li>PODspatialmodes_[case].csv: first two spatial modes computed for the case studies.</li> </ol>
Simulated submerged aquatic vegetation spectral signatures under different water quality conditions using Hydrolight
<p>Reflectance spectra were simulated using the Hydrolight radiative transfer model (Sequoia Scientific, Bellevue, WA) for four different submerged macrophyte species under a range of water quality conditions at two different depths. We used the four-component case-2 model with spectral reflectance of four submerged species, Egeria densa, Ceratophyllum demersum, Cabomba caroliniana, and Stukenia pectinata. These four reflectance spectra were calculated from the median of 10 measurements of the canopies of the representative species placed in clear tap-water made with a handheld ASD FieldSpec Pro spectrometer. Total suspended solids concentration was varied from 1 to 40 g·m<sup>−3</sup>, chlorophyll-a concentration was varied from 0.5 to 50 mg·m<sup>−3</sup>, and colored dissolved organic matter (CDOM) was varied from 0.25 to 3.5 m<sup>−1</sup>. A total of 4,742 spectra were simulated for all four species and a mud substrate at two different depths, 1 m and 5 m, and for optically deep water.</p>
Deep Submergence Dive location dataset from Bell et al. Sci Advances: How Little We've Seen: A Visual Coverage Estimate of the Deep Seafloor
<p><span>How Little We’ve Seen: A Visual Coverage Estimate of the Deep Seafloor </span></p> <p><span>Katherine L.C. Bell,</span><sup><span>1</span></sup><em><sup><span>∗</span></sup></em><em><sup><span> </span></sup></em><span>Kristen N. Johannes,</span><sup><span>1<em>,</em>2</span></sup><span> </span></p> <p><span>Brian R.C. Kennedy,</span><sup><span>1<em>,</em>3 </span></sup><span>Susan E. Poulton</span><sup><span>1</span></sup><span> </span></p> <p><sup><span>1</span></sup><span>Ocean Discovery League, Saunderstown, RI 02874, USA, </span></p> <p><sup><span>2</span></sup><span>Integrative Oceanography Division, Scripps Institution of Oceanography, University of California San Diego, San Diego, CA 92037, USA </span></p> <p><sup><span>3</span></sup><span>Biology Department, Boston University, Boston, MA 02215 USA </span></p> <p><em><sup><span>∗</span></sup></em><span>To whom correspondence should be addressed: croff@alum.mit.edu. </span></p> <p><span><br>Despite the importance of visual observation in the ocean, we have imaged a minuscule fraction of the deep seafloor. Sixty-six percent of the entire planet is deep ocean (≥200 m), and our data show we have visually observed less than 0.001%, a total area approximately a tenth of the size of Belgium. Data gathered from over 44 thousand deep-sea dives indicate we have also seen an incredibly biased sample. Sixty-five percent of all in situ visual seafloor observations in our dataset were within 200 nm of only three countries: the United States, Japan, and New Zealand. Ninety-seven percent of all dives we compiled have been conducted by just five countries: the United States, Japan, New Zealand, France, and Germany. This small and biased sample is problematic when attempting to characterize, understand, and manage a global ocean.</span></p>
Submerged aquatic vegetation biomass from the Saint Lawrence River (2006-2016) to compare estimation from quadrat-diver technique to rake collection and echosounding
<p>Here we provide 4 datasets that describes 1) the comparison between quadrat and rake collected biomass (QR), 2) the comparison of rake biomass and biovolume, a biomass proxy derived from echosounding (RE), 3) a validation dataset that confronts quadrat measurements to quadrat prediction measured from echosounding using two intercalibration equations (derived from QR and RE datasets), and 4) a whole-system biomass estimation comparing biomass predicted from echosounding and from rake.</p> <p>Original data comes from the Saint Lawrence River, mainly from Lac Saint-Pierre, but for the QR dataset also from Lac Saint-François and Lac Saint-Louis. Data from the QR (2006-2009) and validation dataset (2016) were collected by Christiane Hudon, Environment and Climate Change Canada, while the RE dataset and part of the validation dataset were collected as part of a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal). Data were created for an article on a method to estimate SAV biomass, led by Morgan Botrel and supervisor Roxane Maranger, with co-supervisor Christiane Hudon and Pascale Biron.</p> <p>For the second version, the data is more clearly organized in the four categories mentioned above. Additionally, revised prediction equations were applied which modifies results used in the validation and whole-system datasets (dataset 2 and 4). Equations are presented in the associated publication:</p> <p>Botrel, M., C. Hudon, P.M. Biron, R. Maranger. Combining quadrat, rake and echosounding to estimate submerged aquatic vegetation biomass at the ecosystem scale. Limnology & Oceanography: Methods. Accepted (as of 2023/02/08)</p>
Metal and nutrient content from submerged aquatic macrophytes collected from Southern Coeur d'Alene Lake, Idaho (USA) in August 2018.
<p>This repository contains data and R scripts used to produce the analyses reported in the manuscript listed below. See the Readme.txt and metadata.csv files for more explanation. The .R file can be used to unbundle the .tar.gz file via the packrat library. The data and script files are contained in the .tar.gz file. </p> <p>Scofield, B.D., Fields, S.F. & Chess, D.W. Aquatic macrophytes show distinct spatial trends in contaminant metal and nutrient concentrations in Coeur d’Alene Lake, USA. <em>Environ Sci Pollut Res</em> (2023). <a href="https://doi.org/10.1007/s11356-023-27211-x">https://doi.org/10.1007/s11356-023-27211-x</a></p>
Dataset for: African manatee (Trichechus senegalensis) habitat suitability at Lake Ossa, Cameroon using trophic state models and predictions of submerged aquatic vegetation
<p>See research article here: https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.8202</p> <p>Aim: The present study aims at investigating the past and current trophic status of Lake Ossa and evaluating its potential impact on African manatee health.</p> <p>Location: Lake Ossa is known as a refuge for the threatened African manatees in Cameroon. Little information exists on the water quality and health of the ecosystem as reflected by its chemical and biological characteristics.</p> <p>Methods: Aquatic biotic and abiotic parameters including water clarity, nitrogen, phosphorous and chlorophyll concentrations were measured monthly during four months at each of 18 water sampling stations evenly distributed across the lake. These parameters were then compared with historical values obtained from the literature to examine the dynamic trophic state of Lake Ossa.</p> <p>Results: Results indicate that Lake Ossa’s trophic state parameters doubled in only three decades (from 1985 to 2016), moving from a mesotrophic to a eutrophic state. The decreasing nutrient gradient moving from the mouth of the lake (in the south) to the north indicates that the flow of the adjacent Sanaga River is the primary source of nutrient input. Further analysis suggests that the poor transparency of the lake is not associated with chlorophyll concentrations but rather with the suspended sediments brought-in by the Sanaga River. Consequently, our model demonstrated that despite nutrient enrichment, less than 5% of the lake bottom surface sustained submerged aquatic vegetation. Thus, shoreline emergent vegetation is the primary food available for the local manatee population. During the dry season, water recedes drastically and disconnects from the dominant shoreline emergent vegetation, decreasing accessibility for manatees.</p> <p>Main conclusions: The current study revealed major environmental concerns (eutrophication and sedimentation) that may negatively impact habitat quality for manatees. Efficient land use and water management across the entire watershed may be necessary to mitigate such issues.</p>
Experimental Data for Wave Decay by Submerged Rigid Vegetation under Orthogonal Wave-Current Conditions
<p>This dataset includes wave amplitude decay data, force prediction and measurement data (organized in spreadsheets), and phase-averaged force measurement data stored in a MATLAB <code>.mat</code> file. The accompanying paper, titled <em>"Wave Decay by Submerged Rigid Vegetation under Orthogonal Wave-Current Conditions,"</em> will be published in <em>Geophysical Research Letters.</em> A detailed description of the variables is provided at the end of each spreadsheet. The detailed measurement methods are described in the paper. The data in the <code>.mat</code> file is arranged according to the experimental case order specified in the spreadsheet named <em>"force measurement."</em></p>
Data to reproduce the results presented in Sehgal et al. 2022. Water Resources Research, https://doi.org/10.1029/2021WR030624 ("Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer")
<p>This repository consists data to reproduce results as presented in: "Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer", Water Resorces Research. Kindly refer to the readme.text file to navigate through the dataset.</p> <p> </p> <p> </p>
Linked collectors and determiners for: USGS NRP - Submerged Aquatic Plants - 1966-2009.
Natural history specimen data linked to collectors and determiners held within, "USGS NRP - Submerged Aquatic Plants - 1966-2009". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/fda694ce-fb23-4c47-b765-4cd7d8b4d43d">https://bionomia.net/dataset/fda694ce-fb23-4c47-b765-4cd7d8b4d43d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/fda694ce-fb23-4c47-b765-4cd7d8b4d43d">https://gbif.org/dataset/fda694ce-fb23-4c47-b765-4cd7d8b4d43d</a>. Formatted as a Frictionless Data package.
Fig. 2 in Simple relationships to predict attributes of fish assemblages in patches of submerged macrophytes
Fig. 2. Correlation coefficients (Pearson's R) obtained from relationships between fish assemblage attributes (a: density; b: species richness) and habitat variables (macrophyte biomass, BIOM; volume, VOL; proportional volume, %VOL). We show correlation results from all patches (All), patches dominated by E. densa and patches dominated by E. najas. All correlations were statistically significant (p <0.05).
Data Set for Sandanbata et al. (2023: GRL) entitled "Two volcanic tsunami events caused by trapdoor faulting at a submerged caldera near Curtis and Cheeseman Islands in the Kermadec Arc"
<p><strong>Descriptions</strong></p> <p>This dataset contains supplementary materials for the manuscript under revision for Geophysical Research Letters; the preprint has been uploaded to ESS Open Archive:</p> <ul> <li>Sandanbata, O., Watada, S., Satake, K., Kanamori, H., & Rivera, L. (2023). Two volcanic tsunami events caused by trapdoor faulting at a submerged caldera near Curtis and Cheeseman Islands in the Kermadec Arc. <em>Geophysical Research Letters</em>, 50, e2022GL101086. <a href="https://doi.org/10.1029/2022GL101086">https://doi.org/10.1029/2022GL101086</a></li> </ul> <p>We constructed a source model for the 2017 earthquake at Curtis caldera in the Kermadec Arc. The dislocation distributions and source geometries of this source model, presented in Figure 3, are contained in this dataset.</p>
3D reconstructions of semi-transparent submerged objects: Nanomia, Cystisoma, and validation object
<p>These data were used to support the conclusions published in the article titled, "New method for rapid 3D reconstruction of semi-transparent underwater animals and structures", accepted for publication in Integrative Organismal Biology on May 9th, 2023.</p> <p>It focuses on three physical objects, two of which were live animals, collected under permit in the Monterey Bay NAtional MArine Sanctuary:</p> <ul> <li>A siphonophore of the species <em>Nanomia bijuga</em></li> <li>An amphipod of the family <em>Cystisoma</em></li> <li>A thin-walled plastic cylinder, for validation purposes.</li> </ul> <p>For each of these objects, we provide the original .cine file, as recorded by the Phantom 640S highspeed camera, and the derived high-quality .mov video file. We exported video frames as image stacks, included as ZIP files in this repository. We chose to either extract the red or green channel, or a balanced luminance value of each frame. Background subtraction was performed in some cases, by applying a minimum filter or median filter with a certain Z (time axis) extent, and subtracting this from the original frames. Furthermore, additional smoothing was performed in some cases as indicated by the filenames, in the form of a median filter with an X-by-Y-by-Z extent.</p> <p>3D Slicer software was used for segmentation, and bundled .mrb files are included, which have been tested with 3D Slicer version 5.0.3. Derived .STL or .PLY model files are included as well.</p>
Supporting isotopic data for: Differential utilization of submerged leaf litter by microbial biofilms and macroinvertebrates in a large dryland river
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Infauna shift trait-productivity relationships in submerged aquatic vegetation communities
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