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36 results for “lake physics”
Figure 4 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 4. Biplot of components 1 and 2 (top) and 1 and 3 (bottom) from Principal Component Analysis of water quality variables in 27 study lakes. Variables that predominated in each component (|factor loading| ≥ 0.50) are shown on the appropriate axes. Individual lake data are represented by symbols, with open circles representing lakes without previously reported incidences of zebra mussels (absent, 16 lakes), and solid circles those known to harbor the invasive species (present, 11 lakes) at the time of sampling (October 2016). No separation between the two lake groups is evident in either of the biplots. Ca, calcium, N, nitrogen; P, phosphorous.
Figure 3 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 3. Maxent predictions of suitable quagga mussel (Dreissena bugensis) habitat in Texas. Shading indicates the logistic output of the Maxent model. Polygons represent state and national borders as well as major river basins within Texas.
The interaction of physical structure and nutrient loading drives ecosystem change in a large tropical lake over 40 years (DATA)
<p><strong><span>Datasets for manuscript entitled "The interaction of physical structure and nutrient loading drives ecosystem change in a large tropical lake over 40 years"</span></strong></p> <p><em><span>Includes data collected by Fadum and Hall as well as unplublished data from Vaux and Goldman 1984.</span></em></p> <p><span><strong>Abstract: </strong>Many lakes across the world are entering novel states and experiencing altered biogeochemical cycling due to local anthropogenic stressors. In the tropics, understanding the drivers of these changes can be difficult due to a lack of documented historic conditions or an absence of continuous monitoring that can distinguish between intra- and inter-annual variation. Over the last forty years (1980–2020), Lake Yojoa (Honduras) has experienced increased watershed development as well as the introduction of a large net-pen Tilapia farm, resulting in a dramatic reduction in seasonal water clarity, increased trophic state and altered nutrient dynamics, shifting Lake Yojoa from an oligotrophic (low productivity) to mesotrophic (moderate productivity) ecosystem. To assess the changes that have occurred in Lake Yojoa as well as putative drivers for those changes, we compared Secchi depth (water clarity), dissolved inorganic nitrogen (DIN), and total phosphorus (TP) concentrations at continuous semi-monthly intervals for the three years between 1979 and 1983 and again at continuous 16-day intervals for 2018–2020. Between those two periods we observed the loss of a clear water phase that previously occurred in the months when the water column was fully mixed. Seasonal peaks in DIN coincident with mixing suggest that an enhanced accumulation of ammonium in the hypolimnion (the bottom layer of a stratified lake) during stratification, and release to the epilimnion (the top layer of a stratified lake) with mixing maintains high algal abundance and subsequently low Secchi depth during what was previously the clear water phase. This interaction of nutrient loading and Lake Yojoa's monomictic stratification regime illustrates a key phenomenon in how physical water column structure and nutrients interact in tropical monomictic lakes. This work highlights the need to consider nutrient dynamics of warm anoxic hypolimnions, not just surface water nutrient concentrations, to understand environmental change in these societally important but understudied ecosystems.</span></p> <p> </p> <p><em><strong><span>(for more recent years of data collection see additional zenodo repositories by Fadum and/or Hall) </span></strong></em></p>
Repository for: "Using automatic calibration to improve the physics behind complex numerical models: An example from a 3D lake model"
<p>Set of numerical experiments supporting the paper entitled "Using automatic calibration to improve the physics behind complex numerical models: An example from a 3D lake model" by Marina Amadori, Abolfazl Irani Rahaghi, Damien Bouffard and Marco Toffolon. Submitted to GMD. </p> <p>The folder contains: </p> <p>simulations: DYNO-PODS + Delft3D experiments on Lake Morat. See https://github.com/louisXW/DYNO-pods for more insights on DYNO-PODS and instructions for installation.</p> <p>scripts: extraction and plotting scripts</p> <p>source_code: modified Delft3D src as available at: https://github.com/eawag-surface-waters-research/Delft3D/tree/d3d4/research/surface_heat_transfer</p>
The European Multi Lake Survey (EMLS) dataset of physical, chemical, algal pigments and cyanotoxin parameters 2015.
The European Multi Lake Survey took place in summer 2015. It was a grassroots initiative comprised 197 scientists from 26 European countries. The EMLS was a snapshot sampling effort where 369 lakes were sampled only once for various physical (e.g. temperature), chemical (total nutrients) and biological parameters (algal pigments and toxins). The sampling period for each region was defined as the locally two-week warmest period based on 10-year air temperature data. The initial purpose was to define how nutrients and temperature would interact to explain variance in algal or cyanobacterial blooms on a continental scale using a space for time substitution approach (spatial rather than temporal resolution of lake parameters). Several other scientific questions addressing what controls toxin distribution on a continental scale, or dealing with cross comparisons between algal numerical methods (microscopy vs pigments vs flowcytometry) are in preparation. Publishing this dataset will allow scientific access to a unique sampling effort over the European peninsula that can generate new research ideas.
Physical and chemical data for various lakes near Toolik Research Station, Arctic LTER. Summer 2000 to 2009
Decadal file describing the physical/chemical values recorded at various lakes near Toolik Research Station during summers from 2000 to 2009. Sample site descriptors include site, date, time, depth. Depth profiles of physical measures collected in situ with Hydrolab Datasonde in the field include temperature, conductivity, pH, dissolved oxygen in both percent saturation and mg/l, SCUFA chlorophyll-a values in both volts and µg/l, and PAR.
Physical and chemical data for various lakes near Toolik Research Station, Arctic LTER. Summer 1990 to 1999
Decadal file describing the physical/chemical values recorded at various lakes near Toolik Research Station during summers from 1990 to 1999. Sample site descriptors include site, date, time, depth. Depth profiles of physical measures collected in situ with Hydrolab Datasonde in the field include temperature, conductivity, pH, dissolved oxygen in both percent saturation and mg/l, SCUFA chlorophyll-a values in both volts and µg/l, and PAR.
Eight Mile Lake Research Watershed, Thaw Gradient Extended sites: Physical properties of soil (temperature, moisture and thaw depth).
This data set contains meausrements of soil properties (soil moisture, soil temperature, thaw depth) of sites surrounding an eddy covariance tower. The purpose was to see how physical changes in the lanscape effect carbon fluxes measurede by the EC tower.
Eight Mile Lake Research Watershed, Thaw Gradient Extended sites: Physical data from land cover classes from an upland watershed undergoing permafrost thaw.
This data set contains meausrements of soil properties (depth to permafrost and depth of organc matter) from sites throughout the wathershed within certain land cover types identified by an unsupervised landcover classification. The purpose was to see how land cover classes differed in soil properties and if we could detect diffences in classes undergoing permafrost thaw that results in thermokarst.
Soil chemical and physical property data for Green Lakes Valley, 1982 - 1983.
The genesis and water chemistry of two soil catenas and mineralogy of eolian dust were studied to evaluate the capacity of these soils to buffer acid conditions. Field and laboratory analyses of 50 soil pits and three eolian dust traps indicated that the surface horizons are mainly eolian dust accumulation and the subsurface horizons differed in texture, organic carbon percentage, bulk density, pH, concentration of soluble and exchangeable ions, dissolved organic carbon, and distribution and concentration of clay materials. The chemistry and mineralogy of the eolian dust resemble those of the surface horizons. Calcite, which increases soil buffering capacity, was found in the eolian dust. The eolian calcite probably comes from western Colorado, where limestone exposures are common. This natural liming process may reduce effects of acid rain on the aquatic system.
Biogeochemical and physical controls on methane fluxes from two ferruginous meromictic lakes
Data was collected at Brownie Lake in Minneapolis, MN, USA and at Canyon Lake in the Upper Peninsula of MI, USA. The methane flux, or the amount of methane entering the atmosphere over a given area per time, was assessed at Brownie Lake and Canyon Lake. Sampling of Brownie Lake during geochemical characterization revealed that the methane flux out of the lake was much higher than Canyon Lake, as well as other ferruginous meromictic lakes used as geochemical analogs for early Earth’s ferruginous oceans. The dataset here was used to discern why the methane flux out of Brownie Lake was high. Brownie Lake was sampled in May, July and September of 2017 and June 2018. Canyon Lake was sampled in June and September 2017 and May 2018. We used various limnological probes and sensors (LDO sensor, Hydrolab multiprobe) to collect water column profiles (temperature, dissolved oxygen, specific conductance, chlorophyll a, pH). We also analyzed water samples (cations, anions, CH4, DIC) using ion chromatography and ICP-MS and measured isotopes (CH4, DIC) utilizing isotope ratio mass spectrometry. The methane flux was constrained in two ways: taking direct samples from the surface of each lake using floating static flux chambers, which were measured by gas chromatography, and estimated from geochemical reaction-transport modeling based on the diffusional profiles of methane and other dissolved species throughout the water column.
Names, locations, sampling dates, physical characteristics, water chemistry, and plankton data in samples collected in Canadian Prairie lakes in July and August, 2023
<p>PPR Sample Lake Data.xlsx contains names, locations, sampling dates, physical characteristics, water chemistry, and plankton data in samples collected in Canadian Prairie lakes in July and August, 2023. PPR Sample Lake Fact Sheets.pdf contains fact sheets for every sampled lake including maps and essential lake, catchment, and water chemistry characteristics. </p>
Physical characteristics and chemical measurements of northern lakes in western Canada
<p>Northern lakes disproportionately influence the global carbon cycle and may do so more in the future depending on how their microbial communities respond to climate warming. Microbial communities can change because of the direct effects of climate warming on their metabolism and the indirect effects of climate warming on groundwater connectivity from thawing of surrounding permafrost, especially at lower landscape positions. Here we used shotgun metagenomics to compare the taxonomic and functional gene composition of sediment microbes in 19 peatland lakes across a 1600-km permafrost transect in boreal western Canada. We found microbes responded differently to the loss of regional permafrost cover than to increases in local groundwater connectivity. These results suggest that both the direct and indirect effects of climate warming, which were respectively associated with loss of permafrost thaw and subsequent changes in groundwater connectivity, interact to change microbial composition and function. Archaeal methanogens and genes involved in all major methanogenesis pathways were more abundant in warmer regions with less permafrost, but higher groundwater connectivity partly offset these effects. Bacterial community composition and methanotrophy genes did not vary with regional permafrost cover, and the latter changed similarly to methanogenesis with groundwater connectivity. Finally, we found an increase in sugar utilisation genes in regions with less permafrost, which may further fuel methanogenesis. These results provide the microbial mechanism for observed increases in methane emissions associated with loss of permafrost cover in this region and suggest that future emissions will primarily be controlled by archaeal methanogens over methanotrophic bacteria as northern lakes warm. Our study more generally suggests that future predictions of aquatic carbon cycling will be improved by considering how climate warming exerts both direct effects associated with regional-scale permafrost thaw and indirect effects associated with local hydrology.</p>
Physical characteristics and chemical measurements of northern lakes in western Canada
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Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling
<p><strong>Abstract:</strong><br> To simultaneously address the rising need of expressing uncertainties in deep learning models along with producing model outputs which are consistent with the known scientific knowledge, we propose a novel physics-guided architecture (PGA) of neural networks in the context of lake temperature modeling where the physical constraints are hard coded in the neural network architecture. This allows us to integrate such models with state of the art uncertainty estimation approaches such as Monte Carlo (MC) Dropout without sacrificing the physical consistency of our results. We demonstrate the effectiveness of our approach in ensuring better generalizability as well as physical consistency in MC estimates over data collected from Lake Mendota in Wisconsin and Falling Creek Reservoir in Virginia, even with limited training data. We further show that our MC estimates correctly match the distribution of ground-truth observations, thus making the PGA paradigm amenable to physically grounded uncertainty quantification.</p>
Data from: Initiation of Batrachochytrium dendrobatidis infection in the absence of physical contact with infected hosts – a field study in a high altitude lake
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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.