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11 results for “Environmental chemistry”
Spatial variability in water chemistry of four Wisconsin aquatic ecosystems - High speed limnology Environmental Science and Technology datasets
Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. We developed a new sensor platform to continuously samples surface water at a range of speeds (0 to > 45 km hr-1) resulting in high-density, meso-scale spatial data. Here, we archive data associated with an Environmental Science and Technology publication. Data include a single spatial survey of the following aquatic ecosystems: Lake Mendota, Allequash Creek, Pool 8 of the Upper Mississippi River, and Trout Bog. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected).
Mississippi River spatial water chemistry Environmental Research Letters datasets
We mapped surface water chemistry along the entire length of the Upper Mississippi River (UMR) to understand spatial patterns in nitrate sources and processing. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Here, we archive data associated with an Environmental Research Letters publication (Loken et al. 2018). Data include a single spatial survey of the entire length of the UMR (Minneapolis, Minnesota to Cairo, Illinois) in August 2015 and repeat surveys in Navigation Pool 8 (located near La Crosse, WI). Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Additionally, we archive laboratory chemistry data from water samples collected during the project. Sites include a range of main channel, backwaters, and tributaries. Water chemistry samples were analyzed at the North Temperate Lakes - Long Term Ecological Research facility and linked with underway sensor measurements.
Monitoring data for oyster reefs and nearby controls, including high frequency environmental parameters, carbonate chemistry, oyster growth, and other data
<p>Data for Oyster reefs' control of carbonate chemistry - implications for oyster reef restoration in estuaries subject to coastal ocean acidification. </p>
Monitoring data for oyster reefs and nearby controls, including high frequency environmental parameters, carbonate chemistry, oyster growth, and other data
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Data from: Coupling biogeochemical tracers with fish growth reveals physiological and environmental controls on otolith chemistry
Biogeochemical tracers found in the hard parts of organisms are frequently used to answer key ecological questions by linking the organism with the environment. However, the biogeochemical relationship between the environment and the biogenic structure becomes less predictable in higher organisms as physiological processes become more complex. Here, we use the simultaneous combination of biogeochemical tracers and fish growth analyzed with a novel modeling framework to describe physiological and environmental controls on otolith chemistry in an upwelling zone. First, we develop increasingly complex univariate mixed models to describe and partition intrinsic (age effects) and extrinsic (environmental parameters) factors influencing fish growth and otolith element concentrations through time. Second, we use a multivariate mixed model to investigate the directionality and strength between element-to-element and growth relationships and test hypotheses regarding physiological and environmental controls on element assimilation in otoliths. We apply these models to continuous element (Na, Sr, Mg, Ba, Li) and growth increment profiles (monthly resolution over 17 years) derived from otoliths of reef ocean perch (Helicolenus percoides), a wild-caught, site-attached, fully marine fish. With a conceptual model, we hypothesize that otolith traits (elements and growth) driven by environmental conditions will correlate both within an otolith, reflecting the time dependency of growth and element assimilation, and among individuals that experience a similar set of external conditions. We found some elements (Sr:Ca and Na:Ca) are mainly controlled by physiological processes, while other elements (Ba:Ca and Li:Ca) are more environmentally influenced. Within an individual fish, the strength and direction of correlation varies among otolith traits, particularly those under environmental control. Correlations among physiologically regulated elements tend to be stronger than those primarily controlled by environmental drivers. Surprisingly, only Ba:Ca and growth are significantly correlated among individuals. Failure to appropriately account for intrinsic effects (e.g. age) led to inflated estimates of among individual correlations and a depression of within individual correlations. Together, the lack of among-individual correlations of otolith traits in properly formulated models and the biases that can be introduced by not including appropriate intrinsic covariates suggest that caution is needed when assuming multi-elemental signatures are reflective solely of shared environments.
Lake water and sediments chemistry data along with temporal data on environmental drivers
<p class="Abstract">Increasing iron (Fe) concentrations are found in lakes on a wide geographical scale but exact causes are still debated. The observed trends might result from increased Fe loading from the terrestrial catchment, but also from changes in how Fe distributes between the water column and the sediments. To get a better understanding of the causes we investigated whether there has been any change in the sediment formation of Fe sulfides (FeS) as an Fe sink in response to declining atmospheric sulfur (S) deposition during recent decades. For our study, we chose Lake Bolmen in southern Sweden, a lake for which we confirmed that Fe concentrations in the water column have strongly increased along with water color during 1966 to 2018. Our investigations showed that Fe accumulation and speciation varied independently of S accumulation patterns in the Lake Bolmen sediment record. Thus, we were not able to relate the positive trend in Fe concentrations to reduced FeS binding in the sediments. Furthermore, we found that Fe accumulation rates increased along with lake Fe concentrations, indicating that increased catchment loading rather than a change in the distribution between the sediments and the water column has driven the increase in Fe concentrations. The increased loading may be due to land-use change in the form of an extensive expansion of coniferous forest during the past century. Altered forest management practices and increased precipitation may have led to enhanced weathering and erosion of organic soil layers under aging coniferous forest.</p>
Data from: Coupling biogeochemical tracers with fish growth reveals physiological and environmental controls on otolith chemistry
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Lake water and sediments chemistry data along with temporal data on environmental drivers
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Supplementary Table 1. Characteristics of the Group 1 data journals that publish in the fields of biology, environmental science, chemistry, medicine, and health sciences
<p>Supplementary Table 1. Characteristics of the Group 1 data journals that publish in the fields of biology, environmental science, chemistry, medicine, and health sciences.</p> <p>This file is a digital supplement to William H. Walters, "Data journals: incentivizing data access and documentation within the scholarly communication system," <em>Insights: The UKSG Journal</em> 33, article 18 (June 10, 2020), 1–20, <a href="http://doi.org/10.1629/uksg.510">http://doi.org/10.1629/uksg.510</a>.</p>
Mirrorplots for "Quantum chemistry based prediction of electron ionization mass spectra for environmental chemicals"
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Major ion chemistry and environmental isotope data of groundwaters
<p>Major ion chemistry and environmental isotope data of groundwaters</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.