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92 results for “Mendota”
Lake Mendota Carbon and Greenhouse Gas Measurements at North Temperate Lakes LTER 2016
This original dataset contains carbon and greenhouse gas (GHG) data collected in Lake Mendota during the summer of 2016. Data were collected between 15 April 2016 and 14 November 2016 on both Lake Mendota and its surrounding streams—four major inflows and the primary outflow of Lake Mendota. The dataset is comprised of four linked tables, corresponding to carbon and GHG measurements on Lake Mendota (lake_weekly_carbon_ghg), weekly physico-chemical sonde casts on Lake Mendota (lake_weekly_ysi), ebullition rate estimates on Lake Mendota (lake_weekly_ebullition), and carbon and physico-chemical data from the four major inflows and primary outflow of Lake Mendota (stream_weekly_carbon_ysi). These data were used to explore the relationship between organic carbon dynamics and greenhouse gas production on a eutrophic lake. From these data, it is possible to estimate daily oxygen, methane, and carbon dioxide flux on Lake Mendota during the study time period. Additional methods and applications of this data can be found in J.A. Harts Masters Thesis, University of Wisconsin-Madison Center for Limnology, May 2017.
North Temperate Lakes LTER Processed eddy covariance time series fluxes from tower located on roof of the CFL building oriented toward Lake Mendota 2012 - current
We calculated eddy covariance based fluxes of CO2, H2O, heat, and momentum to study lake-atmosphere exchanges since 2012. These data were collected by Ankur Desai from 2012 to present using a CSAT-3 sonic anemometer and LI-7500 gas analyzer located on the roof of the CFL building. A footprint model (Kljun) was used to screen for lake only data.
Spatially Distributed Lake Mendota EXO Multi-Parameter Sonde Measurements Summer 2019
This data was collected over 9 sampling trips from June to August 2019. 35 grid boxes were generated over Lake Mendota. Before each sampling effort, sample point locations were randomized within each grid box. Surface measurements were taken with an EXO multi-parameter sonde at the 35 locations throughout Lake Mendota during each sampling trip. Measurements include temperature, conductivity, chlorophyll, phycocyanin, turbidity, dissolved organic material, ODO, pH, and pressure.
Lake Mendota, Wisconsin, USA, Phytobenthos Abundance and Community Composition 2016-2018
We sampled the phytobenthos (epibenthic periphyton) of Lake Mendota from 2016-2018 to track impacts of invasive zebra mussels (Dreissena polymorpha) which were discovered in Lake Mendota in 2015 and grew exponentially to densities greater than 10,000 m-2 in shallow, rocky habitat by 2018. We sampled along three transects inherited from Karatayev et al. (2013) at five different depths (1, 3, 5, 8, and 10 m) twice a summer (June and August) from 2016-2018. A pared-down version of this routine sampling continued from 2019 onward but is not included here. This dataset complements zebra mussel and zoobenthos data collected according to the same routine sampling structure, for which data is also archived with EDI.
Lake Mendota, Wisconsin, USA, Zebra Mussel Veliger Water Column Density 2016-2019
We sampled veliger (larval stage) zebra mussels (Dreissena polymorpha) from 2016-2019. Zebra mussels are invasive in Lake Mendota and were first detected in November 2015. Samples were taken at three different sites on Lake Mendota from June to August in 2016, and from June to November in 2018-2019, using a 0.5 m diameter, 64 micrometer mesh size plankton net for an 8 m depth tow. This dataset complements adult zebra mussel, zoobenthos, and phytobenthos data collected during the same time period, for which data is also archived with EDI.
Lake Mendota, Wisconsin, USA, Zebra Mussel Density and Biomass 2016-2018
We sampled adult zebra mussels (Dreissena polymorpha) in the benthos of Lake Mendota from 2016-2018 to track the growth of the population following its initial detection in fall 2015. We sampled along three transects inherited from Karatayev et al. (2013) at five different depths (1, 3, 5, 8, and 10 m) twice a summer (June and August) from 2016-2018. Because suitable zebra mussel substrate was limited at these sites, we also selected five 1 m depth, rocky sites (optimal zebra mussel sites) to track density and biomass where colonization was most intense. A pared-down version of this routine sampling continued from 2019 onward but is not included here. This dataset complements zoobenthos and phytobenthos data collected according to the same routine sampling structure, as well as larval zebra mussel (veliger) sampling for which data is also archived with EDI. Biomass data are modeled from lengths of up to 100 individuals that were measured in each sample. Those lengths were fed into Lake Mendota-specific length-to-weight power law equations parameterized by body size measurements (length, width, live weight, wet weight, dry weight, shell weight, shell-free weight, and ash-free dry weight) of 99 mussels collected at different sites across Lake Mendota in 2018.
Lake Mendota, Wisconsin, USA, (Non-Dreissenid) Benthic Macroinvertebrate Abundance, Biomass, and Community Composition 2016-2018
We sampled the zoobenthos (macroinvertebrates of the benthos) of Lake Mendota from 2016-2018 to track impacts of invasive zebra mussels (Dreissena polymorpha) which were discovered in Lake Mendota in 2015 and grew exponentially to densities greater than 10,000 m-2 in shallow, rocky habitat by 2018. The data presented here exclude all zebra mussels, which are archived in a separate datset. We sampled along three transects inherited from Karatayev et al. (2013) at five different depths (1, 3, 5, 8, and 10 m) twice a summer (June and August) from 2016-2018. These data also contain some samples opportunistically taken from deeper depths along these transects that do not follow the routine sampling structure. A pared-down version of this routine sampling continued from 2019 onward but is not included here. This dataset complements zebra mussel and phytobenthos data collected according to the same routine sampling structure, for which data is also archived with EDI.
Lake Mendota, Wisconsin, USA, Zebra Mussel Body Size and Biomass Biometrics 2018
We sampled 98 individuals of the zebra mussel (Dreissena polymorpha) population of Lake Mendota from many littoral zone sites in 2018 to create biometric relationships between several metrics of body size and several metrics of biomass, including length, width, height, living weight, wet weight, dry weight, shell weight, shell-free dry weight, and ash-free dry weight. We selected individuals to span a wide range of body sizes and found strong relationships between most combinations of body size and biomass metrics.
Lake Mendota Microbial Observatory Temperature, Dissolved Oxygen, pH, and conductivity data, 2006-present.
The Lake Mendota Microbial Observatory collects routine water physical and chemical measurements alongside their microbial samples. This dataset includes measurements of water temperature, dissolved oxygen, pH, and conductivity collected at the central Deep Hole, collocated with a weather buoy (43°05'58.2"N 89°24'16.2"W). All measurements were collected with handheld probes. Data from 2006-2014 was compiled from multiple sources and includes only water temperature and dissolved oxygen. Data from 2014-2019 is from the same probe, a YSI Pro Plus instrument, and also includes pH and specific conductance. Routine microbial observatory sampling continues into the present.
Lake Mendota Microbial Observatory Secchi Disk Measurements 2012-present
The Lake Mendota Microbial Observatory collects routine water clarity measurements alongside their microbial samples. This dataset includes measurements of water clarity collected at the central Deep Hole, collocated with a weather buoy (43°05'58.2"N 89°24'16.2"W). All measurements were collected with handheld Secchi discs. When multiple personnel performed the Secchi disc measurements, the average and standard deviation are reported. To take the Secchi depth, sunglasses are removed and the disc is lowered on the shaded side of the boat. The Secchi depth is the average between where the Secchi disc disappears while lowering it and where it reappears while raising it. Routine microbial observatory sampling continues into the present.
Lake Mendota Phosphorus Entrainment at North Temperate Lakes LTER 2005
This dataset contains total (TP) and soluble reactive phosphorus (SRP) data collected in Lake Mendota during the summer of 2005 between 6/28/2005 and 10/14/2005 as well as high-resolution temperature data for that same time period . The phosphorus data were taken at five different locations where buoys were deployed. The buoys were deployed with HOBO temperature data loggers attached at 2 - 4 m intervals. Similarly the phosphorus samples were collected at 2 - 4 m intervals throughout the water column. The position of the five buoys changed a few times during the summer in an effort to monitor circulation patterns due to different wind directions and speeds. Manuscript using this dataset: Kamarainen, A.M., H. Yuan, C. Wu, S.R. Carpenter. 2009. One-dimensional and three-dimensional approaches converge on similar estimates of phosphorus entrainment in Lake Mendota. Limnology and Oceanography Methods 7:553-567 Sampling frequency: Water temperature: generally 1 min; some at 5 min. TP and SRP: approximately at 2 weeks intervals Number of sites: 12
Lake Mendota at North Temperate Lakes LTER: Snow and Ice Depth 2009-2010
Ice core data collected by Yi-Fang (Yvonne) Hsieh and collaborators for her PhD project, “Modeling Ice Cover and Water Temperature of Lake Mendota.” Part of the project was the development of a 3D hydrodynamic-ice model that simulated both temporal and spatial distributions of ice cover on Lake Mendota for the winter 2009-2010. The parameters from these ice core data were used as model inputs to run model simulations. Parameters measured include: blue ice, white ice, snow depth, and total ice. On February 13, 2009, ice cores were taken on Lake Mendota at four different stations. From January 14, 2010 through March 3, 2010 ice cores were taken on Lake Mendota at 31 different stations. In addition, ice cores were taken on other Yahara Lakes during February of 2009: Lake Kegonsa (4 stations_February 6), Lake Waubesa (4 stations_February 7), Lake Wingra (2 stations_February 8), and Lake Monona (4 stations_February 8). Only total ice measurements are reported for 2009. Included in this data set are the ice core data, and geospatial information for ice coring stations. Documentation: Hsieh, Y.-F., 2012a. Modeling ice cover and water temperature of Lake Mendota. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 157.
Microbial Observatory at North Temperate Lakes LTER Time series of bacterial community dynamics in Lake Mendota 2000 - 2009
With an unprecedented decade-long time series from a temperate eutrophic lake, we analyzed bacterial and environmental co-occurrence networks to gain insight into seasonal dynamics at the community level. We found that (1) bacterial co-occurrence networks were non-random, (2) season explained the network complexity and (3) co-occurrence network complexity was negatively correlated with the underlying community diversity across different seasons. Network complexity was not related to the variance of associated environmental factors. Temperature and productivity may drive changes in diversity across seasons in temperate aquatic systems, much as they control diversity across latitude. While the implications of bacterioplankton network structure on ecosystem function are still largely unknown, network analysis, in conjunction with traditional multivariate techniques, continues to increase our understanding of bacterioplankton temporal dynamics.
Microbial Observatory at North Temperate Lakes LTER Spatial and temporal cyanobacterial population dynamics in Lake Mendota 2009 - 2011
Toxic cyanobacterial blooms threaten freshwaters worldwide but have proven difficult to predict because the mechanisms of bloom formation and toxin production are unknown, especially on weekly time scales. Water quality management continues to focus on aggregated metrics, such as chlorophyll and total nutrients, which may not be sufficient to explain complex community changes and functions such as toxin production. For example, nitrogen (N) speciation and cycling play an important role, on daily time scales, in shaping cyanobacterial communities because declining N has been shown to select for N fixers. In addition, subsequent N pulses from N2 fixation may stimulate and sustain toxic cyanobacterial growth. Herein, we describe how rapid early summer declines in N followed by bursts of N fixation have shaped cyanobacterial communities in a eutrophic lake (Lake Mendota, Wisconsin, USA), possibly driving toxic Microcystis blooms throughout the growing season. On weekly time scales in 2010 and *2011, we monitored the cyanobacterial community in a eutrophic lake using the phycocyanin intergenic spacer (PC-IGS) region to determine population dynamics. In parallel, we measured microcystin concentrations, N2 fixation rates, and potential environmental drivers that contribute to structuring the community.
North Temperate Lakes LTER General Lake Model Parameter Set for Lake Mendota, Summer 2016 Calibration
The General Lake Model (GLM), an open source, one-dimensional hydrodynamic model, was used to simulate various physical, chemical, and biological variables on Lake Mendota between 15 April 2016 and 11 November 2016. GLM (v.2.1.8) was coupled to the Aquatic EcoDynamics (AED) module library via the Framework for Aquatic Biogeochemical Modeling (FABM). GLM-AED requires four major “scripts†to run the model. First, the glm2.nml file configures lake metadata, meteorological driver data, stream inflow and outflow driver data, and physical response variables. Second, the aed2.nml file configures various biogeochemical modules for the simulation of oxygen, carbon, phosphorus, and nitrogen, among others. Third, aed2_phyto_pars.nml configures all parameters pertaining to phytoplankton dynamics. And fourth, aed2_zoop_pars.nml configures all parameters pertaining to zooplankton dynamics. This dataset contains parameter descriptions and values as they were used to simulate organic carbon and greenhouse gas production on Lake Mendota in summer 2016. Meteorological data and stream files used in this calibration are also included in this dataset. Additional methods and model descriptions can be found in J.A. hart’s Masters Thesis, University of Wisconsin-Madison Center for Limnology, May 2017. Readers are referred to the GLM (Hipsey et al. 2014) and AED (Hipsey et al. 2013) science manuals for further details on model configuration.
Spatial surface water chemistry of Lake Mendota with FLAMe: 2014-2016
We mapped surface water chemistry in Lake Mendota 39 times between 2014 and 2016. 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. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Dataset is used for the publication, "Large spatial and temporal variability of carbon dioxide and methane in a eutrophic lake", https://doi.org/10.1029/2019JG005186
High Frequency Under-Ice Water Temperature Buoy Data - Crystal Bog, Trout Bog, and Lake Mendota, Wisconsin, USA 2016-2020
Water temperature measurements from three Wisonsin lakes. Two bog lakes are in Northern Wisconsin, Lake Mendota is in Southern Wisconsin. Thermistor chains span the full depth of each lake. See freeze dates for periods of open or frozen lake (NTL 32, DOI 10.6073/pasta/1c1acdb5489a0355f6f8bb5c496fdf8b and NTL 33, DOI 10.6073/pasta/22a5b5f8bce193353e559918b0024f9d)
Chloride Concentrations, Conductivity, and Water Temperature Data from Lake Mendota and Lake Monona Madison, WI: December 2019 – April 2021
Conductivity and chloride were measured for 2 years in Lake Mendota and Lake Monona in Madison, WI. Conductivity was continuously measured (every 30 minutes) on under-ice buoys in the eplimnia (1-2m below the surface) and hypolimnia (1m off the bottom of the lake) of the lakes. Depth-discrete chloride grab samples were collected from the lakes quarterly. Profile sampling in Mendota, which is approximately 25 m deep, occurred every 5m from 0-20m and at 23.5m. Profile sampling in Monona, which is approximately 21m deep, occurred every 4m from 0-20m. This data was needed for a master’s research thesis with the goal of identifying the lakes' mixing dynamics and how salinization may impact them.
Molecular composition of dissolved organic matter from Lake Mendota from June – November 2017, analyzed by Fourier-transform ion cyclotron resonance mass spectrometry
Dissolved organic matter (DOM) is a complex mixture of organic compounds found in all natural waters. Its composition affects its reactivity towards numerous processes. Its composition is a function of both its source (e.g., allochthonous or autochthonous) as well as the extent of environmental processing it has undergone (e.g., chemical or biological degradation). Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) allows for the characterization of dissolved organic matter at the molecular level. The water sample was collected near the NTL-LTER research buoy on Lake Mendota. Formula assignments were made to raw mass to charge ratios detected in the mass spectrum using a custom processing script and resulting in a list of chemical formulas making up the DOM sample.
Ultraviolet-visible spectroscopy absorbances for dissolved organic matter from Lake Mendota from June – November 2017
Dissolved organic matter (DOM) is a complex mixture of organic compounds found in all natural waters. Its composition affects its reactivity towards numerous processes. Its composition is a function of both its source (e.g., allochthonous or autochthonous) as well as the extent of environmental processing it has undergone (e.g., chemical or biological degradation). Ultraviolet-visible (UV-vis) spectroscopy is an analytical technique commonly used to assess the composition of dissolved organic matter in water samples. Here, we present spectra from Lake Mendota samples collected from June - November in 2017 at the surface of Lake Mendota as well as at specific depths within the water column. All samples were collected near the NTL-LTER research buoy. Absorbance values are listed for wavelengths 200 - 800 nm for each sample.
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