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85 results for “lake assessment”
Data associated with the 2019 Freshwater Oil Spill Remediation Study (FOReSt) assessing the use of enhanced Monitored Natural Recovery (eMNR) and shoreline washing agent (SWA) of diluted bitumen spills conducted in shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2019 to 2020
The following package includes data from the 2019 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) and shoreline washing agent (SWA) as a secondary remediation method for diluted bitumen spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry, and tritium chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. Data included in this package was first collected and used in the paper by Palace et al., titled Polycyclic aromatic compounds in freshwater ecosystems following non-invasive remediation of controlled diluted bitumen spills: The Freshwater Oil Spill Remediation Study (FOReSt) at the Experimental Lakes Area, Canada.
The 2021 Freshwater Oil Spill Remediation Study (FOReSt), assessing the use of enhanced Monitored Natural Recovery (eMNR) of conventional heavy crude oil spills conducted in freshwater shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2021 to 2022.
The following package includes data from the 2021 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) as a secondary remediation method for conventional heavy crude oil spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. As well as tables detailing enclosure metrics (depth), tritium chemistry, and a treatment key. Data included in this package was first collected and used in the paper by Stanley et al., titled Rapid Chemical Remediation of Freshwater Enclosures Treated with Conventional Heavy Crude Oil Spills Followed by Enhanced Monitored Natural Recovery
2007 Environmental Protection Agency (EPA) National Lakes Assessment dataset plus derived data and additional spatially explicit ancillary environmental data.
Lake water quality is known to be affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology conceptual framework using a random forest algorithm on large, national-scale, spatially explicit dataset, the United States Environmental Protection Agency 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity).
Geographically paired lake-reservoir dataset derived from the 2007 USA EPA National Lakes Assessment
Climate change poses a significant threat to lake and reservoir ecosystems, though the exact nature of these threats may differ between lakes and reservoirs. To assess differences between lakes and reservoirs that may influence their response to climate change, we compared catchment and waterbody attributes of 132 geographically paired lakes and reservoirs from the 2007 United States Environmental Protection Agencys National Lakes Assessment (NLA) dataset. The data include the NLA IDs of each waterbody and their elevation, catchment area, surface area, perimeter, maximum depth, residence time, Secchi disk depth, surface temperature, and bottom temperature. Residence time data was collected from estimates generated by Brooks, J.R., J.J. Gibson, S.J. Birks, M.H. Weber, K.D. Rodecap, J.L. Stoddard. 2014. Stable isotope estimates of evaporation: inflow and water residence time for lakes across the United States as a tool for national lake water quality assessments. Limnology and Oceanography 59(6):2150-2165.
Assessment of dissolved iron in Iowa lakes
This study assessed the abundance of dissolved iron (DFe) in Iowa’s lakes. The micronutrient iron has been noted to play a crucial role in regulating phytoplankton growth, however most studies have focused on large lakes with persistent phytoplankton blooms that are known to undergo iron limitation, such as Lake Erie. There are few datasets of DFe in lakes, especially those that are smaller and susceptible to phytoplankton blooms. In order to assess the spatial distribution of DFe in lakes throughout Iowa, this study obtained DFe measurements over a suite of recreational lakes over a summer season in 2018. Weekly monitoring of DFe (for 15 weeks) was conducted to assess temporal trends.
Sherbo et al. 2023 Data Package. Data associated with study assessing effects of dissolved organic matter on phytoplankton productivity in boreal lakes. The majority of data was collected in 2018 at the IISD Experimental Lakes Area in Northwestern Ontario
Allochthonous dissolved organic matter (DOM) structures many physical, chemical, and biological properties of lakes, including key variables that control productivity at the base of freshwater food webs. We examined phytoplankton biomass and productivity and their drivers, across eight pristine boreal lakes with DOM ranging from 3.5 to 9.5 mg DOC L-1. Increases in DOM were associated with significant increases in epilimnetic nitrogen, phosphorus and chlorophyll a (Chl a) concentrations suggesting that nutrients associated with DOM stimulate phytoplankton biomass and productivity. Such results were misleading; there was no significant relationship between Chl a and phytoplankton biomass measured via microscopy, and results did not incorporate the effects of DOM on thermocline and euphotic depth. Chl a:biomass and Chl a: carbon ratios indicated that increases in Chl a with DOM were driven by photo-acclimation to declining light availability. Increases. Further, increases in DOM led to large declines in thermocline (~50 %) and euphotic (~75 %) depths, and depth-integrated phytoplankton biomass and primary production (~70 %).
Missouri reservoir water quality data from the Statewide Lake Assessment Program (SLAP), the Lakes of Missouri Volunteer Program (LMVP), and the Reservoir Observer Student Scientists (ROSS) program
This dataset of limnological water quality data continues from Jones et al., 2024, starting in 2017 until 2021. It is from 195 reservoirs, the majority of which are in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Water quality parameters analyzed in the MU Limnology Lab during this time frame include: areal pigment absorption coefficient, alkalinity, alpha (light utilization efficiency P-E parameter), ammonium (NH4), ammonium-debt, anatoxin, chlorophyll a (corrected and uncorrected for pheophytins), chloride, cylindrospermopsin, seston d13C, seston d15N, dissolved turbidity, dissolved organic carbon, Ek (light saturation P-E parameter), FVFM (maximum quantum yield of PSII for photochemistry), gross primary production, microcystin, nitrate & nitrite (NO3), nitrate-debt, particulate nitrogen, particulate phosphorus, phosphorus-debt, pheophytin, particulate carbon, particulate inorganic matter, particulate organic matter, phycocyanin (PHYCO), saxitoxin, Secchi disk depth, silica, soluble reactive phosphorus, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), total nitrogen (TN), total phosphorus (TP), total suspended solids (TSS), and urea. Most of the samples were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of samples were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few samples were taken from shorelines and drinking water treatment intake pipes. Most of the data come from the Statewide Lake Assessment Project (SLAP) and the Lakes of Missouri Volunteer Program (LMVP) funded by the Missouri Department of Natural Resources. This data represents duplicate or triplicate water samples collected from either the water surface, integrated over the depth of the epilimnion, or from discrete dep
Missouri reservoir water quality data (2022 - current) from the Statewide Lake Assessment Program (SLAP)
This dataset of limnological water quality data continues from North et al., 2025, starting in 2022 until present. The data is from reservoirs, primarily within the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Water quality parameters analyzed in the MU Limnology Lab during this time frame include: ammonium (NH4), anatoxin, chlorophyll a (corrected and uncorrected for pheophytins), chloride, cylindrospermopsin, dissolved organic carbon, microcystin, nitrate & nitrite (NO3), pheophytin, particulate inorganic matter, particulate organic matter, phycocyanin, saxitoxin, Secchi disk depth, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), total nitrogen (TN), total phosphorus (TP), total suspended solids, and urea. Most of the samples were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of samples were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few samples were taken from shorelines and drinking water treatment intake pipes. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. This data represents duplicate or triplicate water samples collected from either the water surface, integrated over the depth of the epilimnion, or from discrete depths in the hypolimnion.
Risk assessment (susceptibility) of thaw slumps and thermokarst lakes in the Yangtze River source region
<p>Due to the influence of climate warming, the degradation of permafrost on the Qinghai-Tibet Plateau (QTP) has become evident. The formation of thermokarst hazards induced by the degradation of ice-rich permafrost has a significant impact on infrastructure construction and local ecology; therefore, it is necessary to assess its risk. In this study, a novel multiple thermokarst hazards risk assessment framework was proposed by combining stacking machine learning and potential environmental factors (vegetation factors, terrain factors, climate factors, and soil factors) to assess the risk of thermokarst hazards in the Yangtze River source region (YRSR). The results show the risk assessment (susceptibility) of thermokarst hazards in the YRSR from 2000 to 2016 at 500 m spatial resolution. This study divided the risk into 5 levels: very low (0.0-0.2), low (0.2-0.4), moderate (0.4-0.6), high (0.6-0.8), and very high (0.8-1.0) </p>
Datasets of Radwin 2023 Great Salt Lake Remote Sensing Historical Assessment
<p>Included are the culminated datasets for an article in review to be published with the Utah Geological Association. This data helps an investigator reproduce or utilize the data. There are datasets for both Landsat and Sentinel, for both the North and South arms of the Great Salt Lake. Additionally, there are datasets documenting the NDWI threshold used for each Landsat image, the outlier images not used in analyses, NDWI error assessment, and calculation of stats/facts.</p> <p>Paper abstract:</p> <p>The Great Salt Lake has been rapidly shrinking since the highstand of the mid-1980s, creating cause for concern in recent decades as the lake has reached historic lows. Many investigators have assessed the evolution of lake elevation, geochemistry, anthropogenic impacts, and links to climate and atmospheric processes; however, the use of remote sensing to study the evolution of the lake has been significantly limited. Harnessing recent advancements in cloud-processing, specifically Google Earth Engine cloud computing, this study utilizes over 600 Landsat TM/OLI and Sentinel MSI satellite images from 1984-2023 to present time-series analyses of remotely sensed Great Salt Lake water area, exposed lakebed area, surface cover types, and chlorophyll-a analyses paired with modelled estimates for water and exposed lakebed area. Results show that since the highstand of 1986-1987, the water area has declined by 45% (~3,000 km<sup>2</sup>) and the exposed lakebed area has increased to ~3,500 km<sup>2</sup> from ~500 km<sup>2</sup>. The area of unconsolidated sediments not protected by vegetation or halite crusts has risen to ~2,400 km<sup>2</sup>. Significant halite crusts are observed in the North Arm, having a max extent of ~150 km<sup>2</sup> between 2002 and 2003, while only small extents of halite crusts are observed for the South Arm. Vegetation is more prevalent in the Bear River Bay and South Arm, with surface area increases over 400% since 1990. Gypsum is widely observed independent of halite crusts. The results highlight multiple instances of land-use/water-management that led to observable changes in water/exposed lakebed area and halite crust extent. This study demonstrates the important benefits of maintaining a lake elevation above ~4,194 ft to maximize lake and halite crust area, which would help mitigate possible dust events and maintain broad lake extent.</p> <p> </p> <p>Files should be self-explanatory based on filename, where BRB means Bear River Bay. Note there are two video files animating the evolution of the North and South Arms of the Great Salt Lake using satellite imagery from 1984 to 2023. </p> <p> </p> <p>Visit https://github.com/radwinskis for details on code used for this study.</p> <p>Please contact me at markradwin@gmail.com with any questions.</p> <p> </p>
Figure 9 in Assessing age, growth, and reproduction of Alburnus mossulensis and Acanthobrama marmid (Cyprinidae) populations in Karakaya Dam Lake (Turkey)
Figure 9. Monthly variation of gonadosomatic index (GSI) of A. marmid females and males in Karakaya Dam Lake.
Figure 8 in Assessing age, growth, and reproduction of Alburnus mossulensis and Acanthobrama marmid (Cyprinidae) populations in Karakaya Dam Lake (Turkey)
Figure 8. Monthly variation of gonadosomatic index (GSI) of A. mossulensis females and males in Karakaya Dam Lake.
Figure 7 in Assessing age, growth, and reproduction of Alburnus mossulensis and Acanthobrama marmid (Cyprinidae) populations in Karakaya Dam Lake (Turkey)
Figure 7. Length–weight relationship of A. marmid in Karakaya Dam Lake (N: number of female and male individuals).
Paleolimnological assessment of a hyper-eutrophic lake (Nowlans Lake, N.S., Canada) Cladoceran communities
<p>Mink fur farming was once a widespread agricultural activity in southwestern Nova Scotia. Some freshwaters near mink fur farm operations now show severe water quality issues. Notably, the watershed of Nowlans Lake (southwestern Nova Scotia, Canada) once contained six mink farms as well as a fish meal feed processing plant. It is now one of the most productive lakes in Atlantic Canada, with exceedingly high measured Total Phosphorus concentrations.</p> <p>Here, we provide data from a paleolimnological investigation on the long-term environmental changes that occurred in Nowlans Lake, and how these changes have impacted cladoceran communities. First, we identify abundances of cladoceran taxa throughout the sediment core, corresponding to assemblages from the ~1900s to present day (determined by 210Pb dating analyses – see Table 1 of cited manuscript), and provide raw counts. We detected shifts in the dominant pelagic cladoceran taxa beginning in the early 1900s, with decreases in small-bodied bosminids, while taxa such as <em>Chydorus brevilabris</em> and <em>Daphnia pulex</em> spp. increased. We identified assemblage "zones" using a constrained hierarchal clustering analysis, denoting three distinct assemblage groups (Script 03). We then provide empirical measures of the body sizes of bosminids in each sediment interval, as body sizes of cladocerans are good proxies of shifts in predation. We identified bottom-up ecological factors as the likely drivers of these assemblage shifts, as body sizes were found to be consistent through time with a Mann Kendall Monotonic Trend Analysis (Script 02). Finally, we reconstructed and provide data on trends in sedimentary chl-a concentrations using visible reflectance spectroscopy (VRS). After conducting a PCA on cladoceran assemblages and extracting PC1 scores, we observed a strong relationship by VRS chl-a and PC1 scores, suggesting similar timing between increases in lake productivity and major cladoceran changes (Script 01).</p>
Figure 4 in Assessing age, growth, and reproduction of Alburnus mossulensis and Acanthobrama marmid (Cyprinidae) populations in Karakaya Dam Lake (Turkey)
Figure 4. Length–weight relationship of A. mossulensis in Karakaya Dam Lake (N: number of female and male individuals).
Figure 2 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA
Figure 2. Mean posterior estimates of the probability of capturing grass carp eDNA from a site in a sample among sites (θ) from the model with the lowest WAIC score [ψ(Site)Θ(Site)p(.)]. Error bars represent 95% credible intervals. DR = Detroit River, HP = Hot Ponds, MB = Maumee Bay. All sites are located in western Lake Erie.
Figure 1 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA
Figure 1. Map denoting all monthly grass carp eDNA sampling events in 2018 (A–C) and 2019 (D–F) aggregated at each sampling location (Hot Ponds, Detroit River, and North Maumee Bay) and acoustic receiver locations (grey circles) in the western basin of Lake Erie. Positive and negative eDNA detections, defined as at least one positive qPCR detection on one replicate among all markers (GCTM10, GCTM22, GCTM32) are denoted by orange crosses and pink triangles, respectively. The 3 grass carp captured from conventional gear (total sampling events = 451) in the Detroit River (October 2018), Hot Pond (July 2019) and North Maumee Bay (July 2019) are denoted by a yellow hexagon.
Рис. 2. Ментум Λичинок роΑа Chironomus из озера Кенон Fig. 2. Mentum of the Chironomus genus larvae from Lake Kenon in Toxic pollution assessment of Chita TPP-1 cooling reservoir by applying the method of head capsule morphological deformations in chironomid larvae
Рис. 2. Ментум Λичинок роΑа Chironomus из озера Кенон Fig. 2. Mentum of the Chironomus genus larvae from Lake Kenon
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka in Toxic pollution assessment of Chita TPP-1 cooling reservoir by applying the method of head capsule morphological deformations in chironomid larvae
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka
Fig. 1 in Species-specific qPCR assays allow for high-resolution population assessment of four species avian schistosome that cause swimmer's itch in recreational lakes
Fig. 1. Abundance of cercariae by sampling site. Water samples were obtained in mid-June and cercariae abundance was determined using the pan-avian schistosomes qPCR.
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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.