US Long-Term Ecological Research Network

Chloride Concentrations, Conductivity, and Water Temperature Data from Upper Yahara River Watershed Tributaries in Dane County, WI: December 2019 – April 2021

Abstract
Conductivity and chloride were measured for 2 years in nine tributaries of Lake
Mendota and Lake Monona in Dane County, WI. HOBO Conductivity loggers continuously
measured absolute conductivity and water temperature every 30 minutes. Breaks in
data collection were due to a calibration period or if the loggers were out of the
water. Grab samples for chloride concentration occurred weekly or biweekly.
Conductivity and water temperature were measured with a field meter at each sampling
excursion. This data was needed for a master’s research thesis with the goal of
characterizing the spatial distribution and loading of chloride in the Upper Yahara
River Watershed.<br/>
Core Areas
Dataset ID
406
Date Range
-
Methods
Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>Field measurements and lab analyses<br/>
Version Number
1

Chloride Concentrations, Conductivity, and Water Temperature Data from Lake Mendota and Lake Monona Madison, WI: December 2019 – April 2021

Abstract
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.<br/>
Core Areas
Dataset ID
403
Data Sources
Date Range
-
Methods
Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>Field measurements and lab analysis<br/>
Version Number
1

North Temperate Lakes LTER: Physical and Chemical Limnology of Lake Kegonsa and Lake Waubesa 1994 - current

Abstract
Physical and chemicals parameters of two Madison-area lakes in the Yahara chain not included as core NTL-LTER study lakes. Parameters include intermittently sampled water temperature, dissolved oxygen, ph, total alkalinity, chloride and sulfate. Nutrient data has been collected since 2015. Number of sites: 2.
Dataset ID
401
Date Range
-
DOI
10.6073/pasta/cc6f0e4d317d29200234c7243471472a
Maintenance
ongoing
Metadata Provider
Short Name
NTLCH01
Version Number
1

Lake Mendota Multiparameter Sonde Profiles: 2017 - current

Abstract
Intermittent sensor profiling at the deep hole of Lake Mendota began in 2017 with a YSI EXO2 multiparameter sonde. Parameters include water temperature, pH, specific conductivity, dissolved oxygen, chlorophyll, phycocyanin, turbidity, and fDOM. Profiles are nominally 0 - 20 meters in depth in one meter increments, although the depth range and increments vary.

Core Areas
Dataset ID
400
Date Range
-
Instrumentation
YSI EXO2 Sonde
Publication Date
Version Number
1

Spatially Distributed Lake Mendota EXO Multi-Parameter Sonde Measurements Summer 2019

Abstract
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.
Core Areas
Dataset ID
388
Date Range
-
Maintenance
ongoing
Methods
Conducted weekly data sampling (9 boat trips in June-August 2019) using an EXO multi-parameter sonde to collect temperature, conductivity, chlorophyll (ug/L), phycocyanin (ug/L), turbidity, dissolved organic material, ODO, pH, and pressure at 35 locations based on GPS guided stratified random sampling. 35 grid boxes were generated over Lake Mendota using qGIS. Point locations within each grid box were randomized before each sampling effort. At each point, variables were recorded continuously with the EXO sonde for a two-minute period. Continuous data was overaged over the two-minute period for each sample point.
Publication Date
Version Number
1

North Temperate Lakes LTER Regional Survey water temperature DO 2015 - current

Abstract
The Northern Highlands Lake District (NHLD) is one of the few regions in the world with periodic comprehensive water chemistry data from hundreds of lakes spanning almost a century. Birge and Juday directed the first comprehensive assessment of water chemistry in the NHLD, sampling more than 600 lakes in the 1920s and 30s. These surveys have been repeated by various agencies and we now have data from the 1920s (UW), 1960s (WDNR), 1970s (EPA), 1980s (EPA), 1990s (EPA), and 2000s (NTL). The 28 lakes sampled as part of the Regional Lake Survey have been sampled by at least four of these regional surveys including the 1920s Birge and Juday sampling efforts. These 28 lakes were selected to represent a gradient of landscape position and shoreline development, both of which are important factors influencing social and ecological dynamics of lakes in the NHLD. This long-term regional dataset will lead to a greater understanding of whether and how large-scale drivers such as climate change and variability, lakeshore residential development, introductions of invasive species, or forest management have altered regional water chemistry.
Water temperature and dissolved oxygen profiles were taken on sampling days.
Contact
Dataset ID
382
Date Range
-
Maintenance
ongoing
Methods
water temperature and dissolved oxygen were measured at 1 meter intervals with a opto sonde
Version Number
1

Lake Mendota water temperature secchi depth snow depth ice thickness and meterological conditions 1894 - 2007

Abstract
Data for water temperature at different depth and different frequencies assembled from various sources by Dale Roberson. A table with additional parameters collected at the same time is also provided for dates when available. These parameters are weather observations, secchi depth, snow and ice depths.
Dataset ID
335
Date Range
-
Methods
Data were assembled from different collectors, names are given in metadata. Measurements were conducted by hand.
NTL Keyword
Version Number
14

CLA Yahara Lakes Citizen Offshore Water Quality Monitoring 2016 - 2017

Abstract
In 2013, Clean Lakes Alliance (CLA) launched a Citizen Water Quality Monitoring pilot. Objectives included evaluating and tracking nearshore water quality conditions on all five Yahara lakes: Lakes Mendota, Monona, Waubesa, Kegonsa and Wingra. In 2016, in order to fully understand the interaction between the offshore and nearshore
environment, CLA volunteers will begin sampling the deepest point (deep hole) of all Yahara lakes. The offshore monitoring program will focus on two components: water clarity sampling and dissolved oxygen and temperature measurement. Data from the offshore monitoring program will be compared to data from the nearshore program.
Contact
Creator
Dataset ID
330
Date Range
-
Methods
On Lakes Mendota, Monona, Waubesa, Kegonsa and Wingra, volunteers will use a Secchi disk to measure water clarity, and a digital handheld thermometer to measure air and surface water temperatures once per week on Thursday mornings . Secchi depth monitoring will take place at the deepest point of each lake. On Lakes Monona and Waubesa, concurrent with Secchi sampling, volunteers will use a YSI 550A multiprobe meter to measure dissolved oxygen and temperature at multiple depths. All volunteers are trained by Clean Lakes Alliance staff.
Version Number
2

LTREB Chemical and Physical Limnology at Lake Myvatn 2012-current

Abstract
These data are part of a long-term monitoring program at station 33 in the central part of Myvatn that represents the dominant habitat, with benthos consisting of diatomaceous ooze. The program was designed to characterize import benthis and pelagic variables across years as midge populations varied in abundance. Starting in 2012 samples were taken at roughly weekly inervals during June, July, and August, which corresponds to the summer generation of the dominant midge, Tanytarsus gracilentus.
Creator
Dataset ID
287
Date Range
-
Maintenance
Ongoing
Metadata Provider
Methods
Water Profile1. Take Light, DO, pH, Temp profile every 0.5mUse YSI DO probe, pH meter, and Li Cor light meter. Take the light profile from the sunny side of the boat.2. Take Secchi depthLower Secchi disk slowly until you can never see clear boundaries between white and black quarters, record this distance to the surface of the water as lower Secchi disk observation. Then pull the Secchi up until you can always see clear boundaries between white and black quarters, record this distance to the surface as the upper Secchi observation.Benthic Net Primary Production1. Measure light, temperature, percentDO, DO, and pH at 0.5m intervals at the sampling location.2. Take 10 clean/undisturbed cores. Try to get a uniform distance between the sediment and top of tube, so the cores have the same volume of water. Cover in boat with tarp to exclude light.3. Collect water from the shore of the boat and measure temp, percentDO, and DO. Save in bucket.4. Measure light intensity at 0 (out) and 0.5m depth where the cores will be incubated.5. Set up HOBO light recorder on the incubator.6. For each tube, take initial temp, percentDO, and DO. Before taking DO measurement, move the DO probe up and down three times to ensure no DO gradient (but do not disturb sediment). Add, slowly and without bubbling, 10 to 20mL of water (just the amount needed) to the core from bucket (number 3) to ensure no air space, and replace the stopper. Measure the distance from sediment to bottom of stopper to the nearest 0.5cm (column_depth).7. Place cores 1, 3, 5, and 7 in dark chambers (opaque tubes), so there are 4 dark and 6 light treatments.8. Incubate the cores using the metal structure at saturation light intensity if possible (300 mol per meter squared per second at 0.5m depth) for about 3h.9. Before taking DO measurement, move the DO probe up and down three times to ensure no DO gradient (but do not disturb sediment), and then measure percentDO, DO, and temperature in each core.Light controlsOnce a month (June, July, August), on a sunny day, incubate 10 cores for 3h with different light intensities to determine primary productivity under different light intensities and different temperatures. It would be best to do this the day after routine sampling (i.e., when retrieving the benthic sampler) so that the results can be compared to those from the routine sampling. Different light levels are obtained using white mesh bags around the core tubes.Core 1 and 6, lightCore 2 and 7, 2xCore 3 and 8, 4xCore 4 and 9, 8xCore 5 and 10, darkIMPORTANT: After the incubations, measure light intensity inside a core tube covered for the different treatments. This is done by removing the light meter from the metal holder and placing it facing up in a core using zip ties and a blue stopper at the bottom. Then place treatment bags over the top and measure light when holding the core at the level they reach in the incubator; use the marking on the light meter cord to make sure this is standardized for all measurements. This should be done 8 times total (each bag plus twice without bags).Light saturationOnce a month in the summer of 2013, we conducted sediment core incubations with varying amounts of shade cloth applied to the cores. Sediment cores received 0, 2, 4, 8, or 15 layers of shade cloth, with two cores in each treatment. All cores were then incubated in the lake over the same 3hr period at a depth of 0.5m.Sediment Dry Weight and Weight on Combustion1. Remove 0.75cm of sediment from a core into a plastic deli container. This should be done on a fresh core. This is the same sample that is used for chl analysis.2. Subsample 5 to 10mL sediment solution and place in a pre-weighed tin tray in oven at 60C for at least 12 hours. When dry, weigh for dry weight.In 2014, the method for sampling benthic chlorophyll changed. Sediment Dry Weight measurements were taken from these samples as well. Below is the pertinent section from the methods protocols. Processing after the collection of the sample was not changed.Take sediment samples from the 5 cores collected for sediment characteristics. Take 4 syringes of sediment with 10mL syringe (15.3 mm diameter). Take 4-5cm of sediment. Then, remove bottom 2cm and place top 2cm in the film canister.3. Combust at 550C for 4.5 hours. Weigh tray.4. If not analyzing combusted samples immediately, place in drying oven before weighing.
Version Number
15

Fluxes project at North Temperate Lakes LTER: Random lake survey 2004

Abstract
The overarching goal of this project is to understand carbon and nutrient cycles for a landscape on which terrestrial and freshwater systems are intimately connected in multiple and reciprocal ways. In the Northern Highlands region of Wisconsin, they are studying a spatially complex landscape in which water features make up almost half of the land area, with wetlands (27% of land surface) and lakes (13%) both prevalent throughout the region, interspersed in upland forests.Weather and limnological data from a set of 170 lakes in the NHLD samples summer 2004. The sampled lakes were from a random stratified subsample (N=300 of 7588 total) of all the lakes in the NHLD.
Contact
Core Areas
Dataset ID
277
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Hanson PC, Carpenter S, Cardille JA, Coe MT, Winslow LA. 2007. Small lakes dominate a random sample of regional lake characteristics. Freshwater Biology. 52:814-22Lakes were selected from unique Water Body Identification Codes (WBICs). Linear features and water bodies identified as impoundments or stream openings were identified from maps digitised by the Departments of Natural Resources of Michigan and Wisconsin (1 : 24 000 USGS 7.5&rsquo; topographic quadrangles) and were excluded. More than 7500 lakes ranging in size from about 0.01 to over 2800 ha remained in the data set. We used a stratified random survey, an approach consistent with the Environmental Monitoring and Assessment Program (EMAP) guidelines (Larsen et al., 1994) of the U.S. Environmental Protection Agency, to select and sample 300 lakes from the data set as follows. All lakes were ordered by area and divided into 20 bins of equal population. From each bin, 15 lakes were chosen at random. Because of logistical issues in travelling to many lakes scattered over a wide geographical region, we clustered lakes into 31 geographically small regions of about 150 km2 each. The order of regions sampled was randomised to reduce correlation of geographic region with time. For any one sampling date we visited only one region, although not all lakes in a region could be visited on a single trip. After all 31 regions were visited, the regions were again selected at random, and lakes previously not visited were sampled. There were 45 sampling days spread between May 20 and August 19. Some lakes that were chosen for sampling could not be visited. Difficulty portaging the sampling gear to a lake or failure to gain access to a lake through private property were reasons for abandoning a sampling effort.Lakes were sampled at their approximate geographic centre. Lake depth and water clarity were measured with a Secchi disk. Our measurement of lake depth was neither a measurement of the maximum nor the mean depth. Because the measurement was made in the middle of the lake and most lakes in the region tend to be bowl shaped, our measurement was probably between mean and maximum depth. Dissolved oxygen (DO) and thermal profiles were obtained from a YSI Model 58 (YSI, Inc., Yellow Springs, OH, U.S.A.) metre (DO air calibrated; temperature calibrated in the laboratory), and the approximate middle of the epilimnion was estimated from the profile. Thermal stratification was calculated from the thermal profile according to the methods listed on the Internet at the North Temperate Lakes Long Term Ecological Research (NTL-LTER) program Web site (http://lter.limnology.wisc.edu). Water samples for later analyses (Table 1, chemical variables) were obtained from the middle of the epilimnion, using a peristaltic pump. For samples that required filtration [dissolved inorganic carbon (DIC), DOC, cations and anions], a 0.45 μm filter was attached in-line. All samples were refrigerated upon returning to the vehicle, and samples for total nitrogen (TN) and total phosphorus (TP) were preserved by acidification. Acid neutralizing capacity (ANC) and pH were determined the day of sampling by Gran alkalinity titration (for ANC) and measurement by pH probe (Accumet 950; Fisher Scientific, Hanover Park, IL U.S.A.). pH was not air equilibrated. DIC and DOC were measured with a carbon analyzer (TOC-V; Shimadzu Scientific Instruments, Columbia, MD, U.S.A.). TN and TP were measured with a segmented flow auto-analyzer (Astoria-Pacific, Inc., Clackamas, OR, U.S.A.). Anions were measured using an ion chromatograph (DX500; Dionex Corporation, Sunnyvale, CA, U.S.A.), and cations using mass spectrometry (ICP-MS; PerkinElmer Life and Analytical Sciences, Shelton, CT, U.S.A.). Details of chemical analyses are available on the Internet at the NTL-LTER Web site listed above.To correct for bias introduced by not sampling all 300 lakes, we replaced missing data using multiple imputation (Levy, 1999). Multiple imputation is a technique for estimating the uncertainty of imputed variables. For each variable for each lake not sampled in a given bin, we chose at random (with replacement) a value from lakes sampled in that bin. We repeated the imputation 1000 times to provide a distribution of estimates for each variable in the lakes not sampled. The distribution mean for each variable in each lake was used in the calculation of the median for the regional lake population. We chose to present the median for the 300 lakes because distributions tended to be highly skewed. For comparison purposes, we also calculated the median from sampled lakes only (i.e. excluding imputed data). The mean cumulative distributions for some variables, including 95% confidence intervals, were plotted from the 1000 cumulative distributions generated by multiple imputation.We fit a Pareto distribution to the regional lake area data set to compare the size distribution of NHLD lakes with those of other regions. We used the maximum likelihood estimator for parameter estimates (Bernardo &amp; Smith, 2000). Of particular interest is the parameter (β) that describes the logarithmic decline in number of lakes with lake area, because this parameter has been used previously (Downing et al., 2006, Table 1) to compare lake area distributions among regions and to estimate the global abundance of lakes.Where indicated, results have been area weighted to reflect the influence of lake size. For correlations, data were transformed (log10) to normalise distributions and linearise relationships. Shoreline development factor (SDF), an index of the irregular shape of lakes, was calculated for each lake according to Kalff (2002). The minimum SDF, 1, indicates a lake is a perfect circle.
NTL Keyword
Version Number
25
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