Methods

1. Dataset: sr1 - Surface Water Resource Inventory (SWRI) Wisconsin. Temporal coverage: 1960-1980. Original description found in the preface of each Wisconsin Department of Natural Resources (WDNR) SWRI report, published by county.Data manipulation for incorporation into database: Original source of data is WDNR SWRI printed reports. An electronic version (MS Excel spreadsheet) of the data was available (the origin of this spreadsheet was unknown) and was used in preparation of this database. Some discrepancies observed between printed version and electronic version of the dataset: 1) in the printed reports, alkalinity is expressed either as methyl orange or methyl purple; varies from county to county. The electronic format does not contain any metadata or explanation regarding alkalinity. 2) in the printed reports, sometimes max depth provided, sometimes known depth, and sometimes Secchi depth- these values seem to have been transcribed as Secchi depth in the electronic dataset. 3) values of area, conductivity, alkalinity, and depth in electronic format have been rounded up from values in the books. 4) a field in the spreadsheet named "Cl" has no match in books and was not included in the final dataset. 5) color code was not defined in electronic format. It was deciphered and checked against a few lakes from different counties in the printed reports. Final color codes: 1 - Light brown. 2 - Medium brown. 3 - Dark brown. 4 - Clear. 5 - TurbidIssues specific to the electronic format: 13822 records originally. After eliminating all records without WBICs (Water Body Identification Code) or with duplicate WBICs, the dataset reduced to 12638 records with unique WBICs. Of these, 151 records (with area >10 acres) had no or zero data for some chemical parameters. Checked these records using WDNR SWRI reports. Eliminated any record that couldn't be resolved using the books and WDNR WBICs file.. Most records contain both alkalinity and conductivity data, although some do not contain both parameters. Final dataset sr1 has 12383 records2. Dataset: sr2 - Pieter Johnson. Temporal coverage: not specified. Original description: Combination of WDNR Register of Waterbodies (ROW) file, Wisconsin Lakes Book (wilk), and SWRI. Selected lakes with areas >= 10 acres, and lakes in at least 2 of the 3 datasets. Lakes with missing WBIC were not included. Lakes with missing surface area were not included.Data manipulation for incorporation into database: Received original dataset from Jake Vander Zanden (UW-Madison, Center Data manipulation for incorporation into database: Received original dataset from Jake Vander Zanden (UW-Madison, Center for Limnology). The dataset was used in the following publication: Johnson, P.T., J.D. Olden, M.J. Vander Zanden. 2008. Dam invaders: impoundments facilitate biological invasions in freshwaters. Frontiers in Ecology and the Environment 6:357-363. Original dataset contained 5213 records; . Eliminated 8 records without WBIC, legal (TRS) description, and no values for lake characteristics. Note: Many records are repeated from sr1 dataset. Final dataset sr2 has 5205 records.3. Dataset: sr3 - Biocomplexity Project. Temporal coverage: 2001-2004. Original description: Data Set Title: Biocomplexity; Coordinated Field Studies: Chemical Limnology. Investigators: Steve R. Carpenter, Jim Kitchell, Timothy K. Kratz, John J. Magnuson. Contact:NTL LTER Information Manager; Center for Limnology, 680 N Park St, Madison, WI, 53706-1492, USA;(phone) 608-262-2573;(fax) 608-265-2340;(email) infomgr@lter.limnology.wisc.edu; 62 Vilas County lakes were sampled from 2001-2004 (approximately 15 different lakes each year)Data manipulation for incorporation into database: Original dataset had 62 records. Replicate samples per lake averaged to single measurements. Two records represented a single lake (Little Rock, North and South basins); these were merged into one record. Final dataset sr3 has 61 records.4. Dataset: sr4 - Landscape Position Project. Temporal coverage: 1998. Original description: Data Set Title: Landscape Position Project: Chemical Limnology. Investigators: Ben Greenfield, Thomas Hrabik, Timothy K. Kratz, David Lewis, Amina Pollard, Karen Wilson. Contact: NTL LTER Information Manager; Center for Limnology, 680 N Park St, Madison, WI, 53706-1492, USA;(phone) 608-890-3446;(fax) 608-265-2340;(email) infomgr@lter.limnology.wisc.edu; Parameters characterizing the chemical limnology and spatial attributes of 51 lakes were surveyed as part of the Landscape Position Project.Data manipulation for incorporation into database: WBICs added. Ward Lake removed from data. Parameters values over multiple sampling events were averaged. Info regarding depth at which samples were taken was not retained. Final dataset sr4 has 50 records.5. Dataset: sr5 - Lillie and Mason. Temporal coverage: 1979. Original description: printed report WI DNR Technical Bulletin no.138. 1983. Limnological characteristics of Wisconsin LakesData manipulation for incorporation into database: Original file containing 667 records received from Paul Garrison (WDNR). 88 records lacked WBICs but 65 of these were assigned using WDNR lakes shapefile, matching names and areas of lakes. Final 23 records without WBICs were removed. Note: Since lake / impoundment classification doesn't seem to match Johnson's dataset (sr2), it was not included. Note from Richard Lathrop (WDNR): total P measurements are probably unreliable due to method used not being sensitive enough. Final dataset sr5 has 644 records.6.Dataset: sr6 - EPA- Eastern Lakes Survey (1984): Temporal coverage: 1984. Original description: Data Set Title: National Surface Water Survey: Eastern Lake Survey-Phase I. The Eastern Lake Survey-Phase I (ELS-I), conducted in the fall of 1984, was the first part of a long-term effort by the U.S. Environmental Protection Agency known as the National Surface Water Survey. It was designed to synoptically quantify the acid-base status of surface waters in the United States in areas expected to exhibit low buffering capacity. The effort was in support of the National Acid Precipitation Assessment Program (NAPAP). The survey involved a three-month field effort in which 1612 probability sample lakes and 186 special interest lakes in the northeast, southeast, and upper Midwest regions of the United States were sampled.Data manipulation for incorporation into database: Original dataset, downloaded from EPA website, has over 100 parameters. Only a small subset of interest was retained. Original documentation for full dataset available is available. Dataset includes 285 Wisconsin lakes. WBICs were assigned using geographic coordinates from dataset. WBIC for one lake could not be determined and was excluded.. Note regarding conductivity parameter: value represents calculated conductivity, as the sum of concentrations of each major cation and anion. It is not a parameter measured in the field or lab. Actual formula used to calculated conductivity was not discovered. Final dataset sr6 has 284 records7. Dataset: sr7 - Environmental Research Lab Duluth (ERLD). Temporal coverage: 1979-1982. Original description: ERLD Lake Survey. Contact(s): NTL LTER Information Manager; Center for Limnology, 680 N Park St, Madison, WI, 53706-1492, USA;(phone) 608-262-2573;(fax) 608-265-2340;(email) infomgr@lter.limnology.wisc.edu; Chemical survey of 832 lakes in Minnesota, Michigan, Wisconsin and Ontario conducted by ERL-Duluth and UMD between 1979 and 1982 for evaluation of trophic state and sensitivity to acid deposition Glass, G.E. and Sorenson, J.A. (1994) USEPA ERLD-UMD acid deposition gradient-susceptibility database. U.S. EPA Environmental Research Laboratory - Duluth and University of Minnesota at Duluth, MN.Data manipulation for incorporation into database: Dataset included 428 Wisconsin records for which WBICs were included. Note: Original dataset had several errors in WBIC assignment: 1179900 was assigned to three different water bodies; correct WBICs are: 1503000, 1502400, 1481100; also 1515800 changed to 1516000. Lake Clara had 5 different stations for most parameters sampled. First station that had values for all parameters was included in final dataset. Final dataset sr7 has 428 records.8. Dataset: sr8 - Birge-Juday Historical Dataset. Temporal coverage: 1925-1941. Original description: Birge-Juday Historical Lake Data. Investigator(s): Edward A. Birge, Chauncy Juday. Contact: NTL LTER Information Manager; Center for Limnology, 680 N Park St, Madison, WI, 53706-1492, USA;(phone) 608-262-2573;(fax) 608-265-2340;(email) infomgr@lter.limnology.wisc.edu; Data collected by Birge, Juday, and collaborators, mostly in north-central Wisconsin, from 1925 through 1941; generally one sample per lake during the summer, but on some lakes, especially around Trout Lake Station, samples were taken on several successive years. Note that not all variables were measured on all lakes (scarce data for nutrients and ions). Documentation: Johnson, M.D. (1984) Documentation and quality assurance of the computer files of historical water chemistry data from the Wisconsin Northern Highland Lake District (the Birge and Juday data).WDNR Technical Report. Number of sites: 608 (generally one sampling point per lake; occasionally, several sampling points per lake on multibasin, large lakes).Data manipulation for incorporation into database: Original dataset downloaded from UW-Madison, Center for Limnology LTER website. Values averaged for lakes with multiple samples. WBICs assigned to 577 lakes via GIS spatial join using site coordinates and WDNR lake shapefile. Note from Johnson, M.D. (1984): the units for alkalinity (fixed CO2) changed from cc/L to mg/L sometime between Aug 1926 and May 1927. 17 entries were originally cc/l. Thus there might be inconsistencies in the alkalinity data. Final dataset sr8 has 577 records.9. Dataset: sr9 - USGS National Water Inventory System (NWIS). Temporal coverage: 1969-2009. Original description: U.S. Geological Survey. This file contains selected water-quality data for stations in the National Water Information System water-quality database (http://nwis.waterdata.usgs.gov/nwis/). Explanation of codes found in this file are followed by the retrieved data. The data you have secured from the USGS NWIS Web database may include data that have not received Director's approval and as such are provisional and subject to revision. The data are released on the condition that neither the USGS nor the United States Government may be held liable for any damages resulting from its authorized or unauthorized use.Data manipulation for incorporation into database: Data downloaded for 240 lakes for the following parameters: calcium, conductivity, alkalinity, pH. Original parameter codes (USGS NWIS schema): p00915 p00095 p00400 p00916 p29801 p39086 p90095. Data are averaged for multiple measurements. WBICs assigned via GIS spatial join using site coordinates and WDNR lake shapefile. Final dataset sr9 has 240 records.10. Dataset: sr10 - WI Department of Natural Resources (WDNR) Temporal coverage: 1969-2009 Original description: available at http://dnr.wi.gov/org/water/swims/Data manipulation for incorporation into database: Original data received from Jennifer Filbert (WDNR). Data were extracted from WDNR Surface Water Integrated Monitoring System (SWIMS) database (http://dnr.wi.gov/org/water/swims/). Lakes represented had one or more of the following parameters: Secchi depth, calcium, conductivity, alkalinity, pH, total P, turbidity,, chlorophyll a. Data were averaged where multiple measurements were available. Final dataset sr10 has 53 records.The Data Source data table contains a summary of the 10 data sources with information on temporal coverage and record counts. It also includes information on the availability of calcium and conductivity data from the data sources.

Methods

We collect water samples for color at the deepest part of the lake four times per year: February under ice, spring mixis, August stratification, and fall mixis. The samples are surface water, filtered in the field through 0.45u polycarbonate membrane filters. We run a wavelength scan from 800 to 200nm, using a 5cm rectangular quartz cell in a Beckman Coulter Model DU800 spectrophotometer. Any samples that display absorbance values above 2AU are run again from 400 to 200nm using a 1cm quartz cuvette. Inititally the full range of wavelengths were run again and two values may be found in the database even if the original measurement with the large cuvette did not exceed 2AU. The user should discard values above 2AU and use values from the smaller cuvette instead. All values are given as measurements at the path lenth of the employed cuvette and need to be devided by the cuvette length for a comparable value at a pathlength of 1 cm.The single beam Beckman Coulter DU800 spec is blanked first on a sample of DI water. Additional blank values are from a scan run on DI after that blanking as a check and are reported alongside the scans but are not subtracted from the scan values. Protocol Log: 1990 -- we began running color scans, using a 10cm cylindrical cell with a Kontron spectrophotometer. 2001 -- we added scans in a 1cm cell for samples with high absorbance. July 2008 -- changed to Beckman Coulter DU800 spectrophotometer. At same time changed from 10cm to 5cm cell.

Methods

methods described in abstract

Methods

see abstract for secchi disc measurements. Otherwise, these are observations made by the crew while out sampling.

Methods

Light (PAR) extinction coefficient is calculated by linearly regressing ln (FRLIGHT (z)) on depth z where the intercept is not constrained. FRLIGHT(z) = LIGHT(z) or DECK(z) where LIGHT(z) is light measured at depth z and DECK(z) is light measured on deck (above water) at the same time. For open water light profiles, the surface light measurement (depth z = 0) is excluded from the regression. For winter light profiles taken beneath the ice, the first light data are taken at the bottom of the ice cover and are included in the regression. The depth of uppermost light value is equal to the depth of the ice adjusted by the water level in the sample hole, i.e., the depth below the surface of the water. The water level can be at, above or below the surface of the ice. If the water level was not recorded, it is assumed to be 0.0 and the calculated light extinction coefficient is flagged. If ice thickness was not recorded, a light extinction coefficient is not calculated. For light data collected prior to March, 2007, light values less than 3.0 (micromolesPerMeterSquaredPerSec) are excluded. For light data collected starting in March 2007, light values less than 1.0 (micromolesPerMeterSquaredPerSec) are excluded. Except for bog lakes before August 1989, a light extinction coefficient is not calculated if there are less than three FRLIGHT values to be regressed. For bog lakes before August 1989, a light extinction coefficient is calculated if there are least two FRLIGHT values to be regressed. In these cases, the light extinction coefficient is flagged as non-standard. FRLIGHT values should be monotonically decreasing with depth. For light profiles where this is not true, a light extinction coefficient is not calculated. For samples for which light data at depth are present, but the corresponding deck light are missing, a light extinction coefficient is calculated by regressing ln (LIGHT (z)) on depth z. Note that if actual deck light had remained constant during the recording of the light profile, the resulting light extinction coefficient is the same as from regressing ln(FRLIGHT(z)). In these cases, the light extinction coefficient is flagged as non-standard. Oxygen and Temperature: We sample at the deepest part of the lake, taking a temperature and oxygen profile at meter intervals from the surface to within 1 meter of the bottom using a YSI Pro-ODO temporDO meter. We sample biweekly during open water and approximately every five weeks during ice cover. Protocol Log: Prior to 2011, we used a YSI Model 58 temporDO meter.

Methods

Standard water level measurements in ground water wells. See abstract for more methods descriptions.

Methods

see abstract for methods description

Methods

The instrumented raft on Sparkling Lake is equipped with a D-Opto dissolved oxygen sensor, a thermistor chain, and meteorological sensors that provide fundamental information on lake thermal structure, weather conditions, evaporation rates, and lake metabolism. Estimating the flux of solutes to and from lakes requires accurate water budgets. Evaporation rates are a critical component of the water budget of lakes. Data from the instrumented raft on Sparkling Lake includes micrometeorological parameters from which evaporation can be calculated. Raft measurements of relative humidity and air temperature (2 m height), wind velocity ( at 1, 2, and 3 m heights; but beginning in 2008, only at 2 m) ,and water temperatures (from thermistors placed throughout the water column at intervals varying from 0.5 to 3m) are combined with measurements of total long-wave and short-wave radiation data from a nearby shore station to determine evaporation by the energy budget technique. Comparable evaporation estimates from mass transfer techniques are calibrated against energy budget estimates to produce a lake-specific mass transfer coefficient for use in estimating evaporation rates. After correcting for flux to or from the atmosphere and vertical mixing within the water column, high frequency measurements of dissolved gases such as carbon dioxide and oxygen can be used to estimate gross primary productivity, respiration, and net ecosystem productivity, the basic components of whole lake metabolism. Other parameters measured include precipitation, wind direction (beginning in 2008), and barometric pressure (beginning in 2008). Sampling Frequency: one minute; averaged to hourly and daily values as well as higher resolution values such as 2 min and 10 min.Dissolved oxygen sensors: 2004-2006: Greenspan Technology series 1200; 2007-2016: Zebra-Tech Ltd. D-Opto; 2018+: OTT HydrolabCO2 sensors: 2018+: ProOceanos MiniCO2 for dissolved CO2; Eosense Inc. eosGP for atmospheric CO2

Methods

The instrumented buoy on Sparkling Bog North is equipped with a thermistor chain that measures water temperature at the surface, at 0.25 m and at every .5 m from 0.5 m to 4.5 m. The buoy is also equipped with a dissolved oxygen sensor, meteorological sensors, a CO2 sensor and a YSI AutoProfiler that provide fundamental information on lake thermal structure, weather conditions, and lake metabolism. Prior to May 2009, data were collected at 1 minute or 10 minute intervals. Since May 2009, data are being collected each minute. Hourly and daily water temperature averages are computed from high resolution data. Hourly and daily values may not be current with high resolution data. In 2008, the instrumented buoy was deployed in Sparkling Bog North from March 24 to November 10. In 2009, the buoy was deployed on the ice on March 7 and was not removed for the winter of 2009 to 2010. Sampling Frequency: varies for instantaneous sample.

Methods

see abstract for methods description