US Long-Term Ecological Research Network

Cascade Project at North Temperate Lakes LTER Core Data Carbon 1984 - 2016

Abstract
Data on dissolved organic and inorganic carbon, particulate organic matter, partial pressure of CO2 and absorbance at 440nm. Samples were collected with a Van Dorn sampler. Organic carbon and absorbance samples were collected from the epilimnion, metalimnion, and hypolimnion. Inorganic samples were collected at depths corresponding to 100%, 50%, 25%, 10%, 5%, and 1% of surface irradiance, as well as one sample from the hypolimnion. Samples for the partial pressure of CO2 were collected from two meters above the lake surface (air) and just below the lake surface (water). Sampling frequency: varies; number of sites: 14
Core Areas
Dataset ID
350
Date Range
-
Methods
Detailed field and laboratory protocols can be found in the Cascade Methods Manual, found here: https://cascade.limnology.wisc.edu/public/public_files/methods/CascadeManual1998.pdf
POC, PON and DOC: 1. 100 - 300 ml (Typically ~200mL for PML, 150 metalimnion and 75 – 100 for the hypolimnion) of lake water from each depth was filtered through 153 um mesh to remove large zooplankton. Water was then filtered through a precombusted 25mm GF/F filter (0.7 um pore size) at less than 200 mm Hg pressure. Filters were placed in drying oven at 60 C to dry for at least 48 hours. 20mL of filtered water was stored in a scintillation vial and acidified with 200uL of 2N H2SO4 for DOC analysis. Blank samples for POC and DOC were prepared with deionized water to control for contamination. All samples were sent to the Cary Institute of Ecosystem Studies for analysis.

Version Number
24

Long-term trends and synchrony in dissolved organic matter characteristics in Wisconsin, USA lakes: quality, not quantity, is highly sensitive to climate

Abstract
Dissolved organic matter (DOM) is a fundamental driver of many lake processes. In the past several decades, many lakes have exhibited a substantial increase in DOM quantity, measured as dissolved organic carbon (DOC) concentration. While increasing DOC is now widely recognized, fewer studies have sought to understand how characteristics of DOM (DOM quality) change over time. Quality can be measured in several ways, including the optical characteristics spectral slope (S275-295), spectral ratio (SR), absorbance at 254 nm (a254), and DOC-specific absorbance (SUVA; a254:DOC). However, long-term measurements of quality are not nearly as common as long-term measurements of DOC concentration. We used 24 years of DOC and absorbance data for seven lakes in the North Temperate Lakes Long Term Ecological Research site in northern Wisconsin, USA to examine temporal trends and synchrony in both DOC concentration and quality. We predicted lower SR and S275-295 and higher a254 and SUVA trends, consistent with increasing DOC and greater allochthony. DOC concentration exhibited both significant positive and negative trends among lakes. In contrast, DOC quality exhibited trends suggesting reduced allochthony or increased degradation, with significant long-term increases in SR in three lakes. Patterns and synchrony of DOM quality parameters suggest they are more responsive to climatic variations than DOC concentration. SUVA in particular tended to increase with greater moisture and decrease with drier conditions. These results demonstrate that DOC quantity and quality can exhibit different complex long-term trends and responses to climate components, with important implications for aquatic ecosystems.
Contact
Core Areas
Dataset ID
329
Date Range
-
Methods
Data contained within is derived from data publicly available through the North Temperature Lakes Long Term Ecological Research (NTL-LTER) website at the following url: https://lter.limnology.wisc.edu/. All data is for the upper meter of the water column, collected in the deepest point of the lake. For DOC concentration data and ancillary data such as pH, iron, and total N, please see the NTL-LTER website.
The file dat.w.blank.fin 7_29_16.csv contains the absorbance scans that were used to calculate the spectral metrics (NTL LTER 2012). Samples for absorbance scans were collected approximately quarterly. Absorbance scans were run on a spectrophotometer over the wavelengths from 200-800 nm. In this file, the column value is the raw value for absorbance read directly off the instrument for the corresponding wavelength. The column blank.value is the value of the DI blank taken nearest in time for the corresponding wavelength and cuvette width. The column cor.value is the blank.value column subtracted from the value column. The cor.value column was used in all subsequent analyses and calculations.
The file metrics for_analysis.csv contains the spectral metrics calculated from the absorbance scans as well as select meteorological metrics. ab.254 is raw absorbance measured by the instrument (after correcting for DI blanks), corrected for a 1 m pathlength. lin.slope.275.295 is the slope for the log transformed absorbance scan over the wavelengths 275-295 nm, determined by linear regression. nlin.slope.275.295 is the spectral slope (S275-295) over the wavelengths 275-295 nm, calculated using non-linear regression in R version 3.2.3 (R Core Team 2015), fitting the following equation:
alambda = alambdarefe-S(lambda-lambdaref)
In this equation a is the Naperian absorption coefficient (see below), lambda is the wavelength, lambdaref is the reference wavelength, and S is the spectral slope (nm-1) (Twardowski et al. 2004; Helms et al. 2008). The initial estimate supplied to the non-linear regression procedure was supplied by the value for lin.slope.275.295. lin.slope.350.400 and nlin.slope.350.400 were calculated in a similar fashion, but over the wavelengths 350-400 nm. This calculation yields the spectral slope over the wavelengths 350-400 nm (S350-400). slope.ratio is the slope ratio (SR), the ratio of S275-295 to S350-400 (Helms et al. 2008). ab.254.1cm is similar to ab.254, but is corrected for a 1 cm cuvette width. a254.nap is the Naperian absorption coefficient and is calculated from the equation:
a = 2.303A/l
In this equation, a is the Naperian absorption coefficient, A is raw absorbance measured by the spectrophotomer, and l is the path length (Green and Blough 1994). SUVA was calculated by dividing raw absorbance at 254 nm by the DOC concentration of the DOC sample collected nearest in time to the absorbance sample. SUVA is reported as Ltimesmg C-1timesm-1 (Weishaar et al. 2003).
wk.prcp, mth.prcp, and ninety prcp are precipitation totals for the 7, 30, and 90 days up to and including the sampling date (mm). These data come from the Minocqua, WI station in the Global Historical Climatology Network (GHCN) dataset (available at https://www.ncdc.noaa.gov/data-access/quick-links#ghcn) (Menne et al. 2010).
wk.tmp, mth.tmp, and ninety.tmp are mean values for the mid-daily temperature in the 7, 30, and 90 days up to and including the sampling date (°C). These are from the same data source as the precipitation data.
The l.lev column contains lake level from the NTL LTER website in meters above sea level. wk.insol, mth.insol, and ninety.insol are mean solar insolation incident on a horizontal surface in the 7, 30, and 90 days up to and including the sampling date (kWh/m2/day) (these data were obtained from the NASA Langley Research Center Atmospheric Sciences Data Center NASA/GEWEX SRB Project).
Monthly Palmer Drought Severity Index (PDSI) data corresponding to the study period can be accessed at: ftp://ftp.ncdc.noaa.gov/pub/data/cirs/climdiv/ using StateCode=47 and Division=2. These data were retrieved from the US National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Information (NCEI). These data were used to relate trends and synchrony in spectral metrics to moisture conditions.
The DOC column contains DOC concentration (mg L-1) for the corresponding sample date, obtained from the NTL LTER website.

Short Name
DOM trends data
Version Number
19

Fluxes project at North Temperate Lakes LTER: Hydrology Scenarios Model Output

Abstract
A spatially-explicit simulation model of hydrologic flow-paths was developed by Matthew C. Van de Bogert and collaborators for his PhD project, "Aquatic ecosystem carbon cycling: From individual lakes to the landscape." The model is coupled with an in-lake carbon model and simulates hydrologic flow paths in groundwater, wetlands, lakes, uplands, and streams. The goal of this modeling effort was to compare aquatic carbon cycling in two climate scenarios for the North Highlands Lake District (NHLD) of northern Wisconsin: one based on the current climate and the other based on a scenario with warmer winters where lakes and uplands do not freeze, hereinafter referred to as the "no freeze" scenario. In modeling this "no freeze" scenario the same precipitation and temperature data as the current climate model was used, however temperature inputs were artificially floored at 0 degrees Celsius. While not discussed in his dissertation, Van de Bogert considered two other climate scenarios each using the same precipitation and temperature data as the current climate scenario. These scenarios involved running the model after artificially raising and lowering the current temperature data by 10 degrees Celsius. Thus, four scenarios were considered in this modeling effort, the current climate scenario, the "no freeze" scenario, the +10 degrees scenario, and the -10 degrees scenario. These data are the outputs of the model under the different scenarios and include average monthly temperature, average monthly rainfall, average monthly snowfall, total monthly precipitation, daily evapotranspiration, daily surface runoff, daily groundwater recharge, and daily total runoff. Note that the results of how temperature inputs influence aquatic carbon cycling under these different scenarios is not included in this data set, refer to Van de Bogert (2011) for this information. Documentation: Van de Bogert, M.C., 2011. Aquatic ecosystem carbon cycling: From individual lakes to the landscape. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 156.
Core Areas
Dataset ID
286
Date Range
-
Metadata Provider
Methods
The spatially explicit Lakes, Uplands, Wetlands Integrator (LUWI) model of the NHLD was used to explore the interactions among climate, watershed connections, hydrology and carbon cycling. See Cardille et al. 2007 and Cardille et al. 2009 for details on the LUWI model. See Van de Bogert (2011) for a discussion of how these model outputs are used in conjunction with LUWI to predict the effects on lake carbon cycling under the current and "no freeze" climate scenarios.The climate data used in this modeling effort, precipitation and temperature, were obtained from Minoqua, Wisconsin, USA from 1948-2000. In order to test the effect of a climate without freezing temperatures on lake water and carbon cycling the current climate was modeled in addition to a “no freeze” scenario where a minimum air temperature of 0 degrees Celsius was imposed on the model. Note that Van de Bogert (2011) only focuses on the current and “no freeze” climate scenarios, but these data are representative of four climate scenarios: the current climate (base_minoqua_precip), the scenario where the current climate is artificially floored to zero degrees Celsius (no_below_zero), and the scenarios where the current climate is increased and decreased by 10 degrees Celsius (minus_10_degrees and plus_10_degrees).Furthermore, the temperature and precipitation data that was used for the current climate model runs was broken up into aggregates.The aggregates are the length of the 1948-2000 Minoqua temperature and precipitation data that was used in model runs. A total of seven different aggregates were used for model runs under each of the four climate scenarios. The aggregates include temperature and precipitation data from Minoqua, WI, USA for 1. the complete record from 1948-2000 (1948_2000) 2. the driest year which was 1976 (1976_driest) 3. The wettest year which was 1953 (1953_wettest) 4. the five driest years on record from 1948-2000 (5_driest) 5. the five wettest years on record from 1948-2000 (5_wettest) 6. the five coldest years on record for December, January, and February from 1948-2000 (5_coldest_djf) 7. the five warmest years on record for December, January, and February from 1948-2000 (5_warmest_djf).The volume and timing of precipitation to the region were unchanged between scenarios.Evaporation rates were derived from values obtained from the NTL-LTER study site, Sparkling Lake (46.01, -89.70). Refer to Van de Bogert (2011) for a more complete discussion of model inputs and a discussion of the results of the model output. Documentation: Van de Bogert, M.C., 2011. Aquatic ecosystem carbon cycling: From individual lakes to the landscape. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 156.Cardille, J.A., Carpenter, S.R., Coe, M.T., Foley, J.A., Hanson, P.C., Turner, M.G., Vano, J.A., 2007. Carbon and water cycling in lake-rich landscapes: Landscape connections, lake hydrology, and biogeochemistry. Journal of Geophysical Research-Biogeosciences 112.Cardille, J.A., Carpenter, S.R., Foley, J.A., Hanson, P.C., Turner, M.G., Vano, J.A., 2009. Climate change and lakes: Estimating sensitivities of water and carbon budgets. Journal of Geophysical Research-Biogeosciences 114.
Version Number
20

River Nutrient Uptake and Transport at North Temperate Lakes LTER (2005-2011)

Abstract
These data were collected by Stephen Michael Powers and collaborators for his Ph.d. research, documented in his dissertation: River Nutrient Uptake and Transport Across Extremes in Channel Form and Drainage Characteristics. A major goal of this research was to better understand how ecosystem form and landscape setting dictate aquatic biogeochemical functioning and elemental transport through rivers. To achieve this goal, major and minor ions were measured in both northern and southern Wisconsin streams located in a variety of land use settings. In total, 27 different streams were sampled at 104 different stations (multiple stations per system) from both groundwater and surface water sources. Organic and inorganic carbon and nitrogen pools were also measured in northern and southern Wisconsin streams. The streams that were sampled in northern Wisconsin flow through wetland ecosystems. In sampling such streams, the goal was to better understand how wetland ecosystems influence river nutrient deliveries. There is a large amount of stream chemistry data for Big Spring Creek, WI; where the influence of a small reservoir on solute transportation and transformation was studied in an agricultural watershed. All stream chemistry data is incorporated in a single data file, Water Chemistry 2005-2011. While the data is not included in the dissertation, a sediment core study was also done in the small reservoir and channel of Big Spring (BS) Creek, WI. The results of this study are featured in three data tables: BS Creek Sediment Core Analysis, BS Creek Sediment Core Chemistry, and BS Creek Longitudinal Profile. Finally, two data tables list the geospatial information of sampling sites for stream chemistry and sediment coring in Big Spring Creek. Documentation: Powers, S.M., 2012. River nutrient uptake and transport across extremes in channel form and drainage characteristics. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 140.
Dataset ID
281
Date Range
-
Metadata Provider
Methods
I. Stream chemistry sample collection methods: core-sediment core was taken from the benthic zone of the streamgeopump-geopump used to pump stream water into collection bottlegrab-collection bottle filled with stream water by hand and filtered in the fieldgrabfilter- stream water collected by hand and filtered in field. Unfiltered and filtered samples placed in separate collection bottles.isco- sample collected by use of an ISCO automated samplerpoint- sampled collected by method outlined in patent US8337121sedimentgrab- sediment sample taken in field by hand and placed in collection bottlesyringe- sample collected from stream by syringe and placed in collection bottlesyringe_filter- sample collected from stream by syringe filter. Unfiltered and filtered samples placed in separate collection bottles. II. Stream chemistry analytical methods: All water samples were kept on ice and in the dark following collection, then were either acidified (TN/TP, TDN/TDP) or frozen until analysis (all other analytes).no32_2- This is NO<sub>3-</sub>N which is operationally defined as nitrate nitrogen + nitrite nitrogen. Determined by flow injection analysis on Astoria Pacific Instruments Autoanalyzer (APIA).nh4_n, tn1, tp1, tdn, tdp- All analytes measured by flow injection analysis on Astoria Pacific Instruments Autoanalyzer (APIA).srp- measured colorometrically using the molybdate blue method [APHA 1995] and a Beckman spectrophotometer.doc- measured using a Shimadzu carbon analyzer.doc_qual- the goal in doing this analysis is to determine the source of dissolved organic carbon (doc) measured in a particular riverine ecosystem. This was achieved by UV absorbance which provides an estimate of the aromaticity of the doc in a sample, and by extension, the potential source of the doc.cl, no2, no3, br, and so4- all measured by ion chromatography. See http://www.nemi.gov; method number 4110C. Detection limits for method number 4110C: cl-20&micro;g/l, no2-15&micro;g/l, no3-17&micro;g/l, br-75&micro;g/l, and so4-75&micro;g/l.ysi_cond, do, ph_field, wtemp- all measured by use of a standard YSI meter.tss- measured by standard methods. A thoroughly mixed sample is filtered and dried at 103-105 degreesCelcius. The obtained residue represents the amount of solids suspended in the sample solution. See http://www.nemi.giv; method number D5907.tot_om- measured by standard methods. The residue obtained from the tss procedure is ignited at 550 degreesCelcius and weighed, the difference in weight representing total volatile solids. Total volatile solids represents the portion of the residue that is composed of organic molecules. See http://www.nemi.gov; method number 160.4.turbid- measured by use of a nephelometer. III. Big Spring Sediment Coring Methods A. Field Methods- collecting sediment coresSediment core samples taken with WDNR piston core samplerB. Sediment Analysis- HydrometerDocumentation: Robertson, G.P., Coleman, D.C., Bledsoe, C.S. and Sollins, P., 1999. Standard Soil Methods for Long-Term Ecological Research. Oxford University Press, New York, 462 pp.Hydrometer Analysis- procedure used to determine percent clay:<p style="margin-left:.25in;">1. Dry the sample in a pre-weighed aluminum pan for at least 24 hr at 105 C. Make sure sample is completely dry before weighing.<p style="margin-left:.25in;">2. Weigh the dried sample, then ash for at least 8 hr at 550 C. Make sure to break up any large clumps before ashing.<p style="margin-left:.25in;">3. Weigh the ashed sample, then crush any aggregates with a pestal. Mix sample thoroughly.<p style="margin-left:.25in;">4. Transfer 40g, plus or minus one gram, of the sample into a 500mL wide mouth bottle<p style="margin-left:.25in;">5. Add 10g of sodium hexametaphosphate to the bottle.<p style="margin-left:.25in;">6. Add approx 200mL of deionized water to bottle. Shake vigorously with hand.<p style="margin-left:.25in;">7. Stir samples on shaker table for at least 8 hr at speed 40. Putting them in a box and fastening with bungee cords works best.<p style="margin-left:.25in;">8. Transfer sample to 1L cylinder, making sure to get all of sample out of bottle. Fill cylinder with deionized water up to the 1L mark.<p style="margin-left:.25in;">9. Prepare a blank cylinder by adding 10g of sodium hexametaphosphate and filling to 1L.<p style="margin-left:.25in;">10. Allow all cylinders to equilibrate to room temperature ( approx 30 min).<p style="margin-left:.25in;">11. Starting with the blank cylinder, put stopper into cylinder and shake end-over-end for approx 5 min. Rinse stopper. Repeat this step for all cylinders, rinsing stopper between cylinders.<p style="margin-left:.25in;">12. Record the time that you stopped shaking each cylinder.<p style="margin-left:.25in;">13. At 1.5 hr from time of shaking, record temperature and hydrometer level of the blank cylinder. Then record the 1.5 hr hydrometer level for each successive cylinder.<p style="margin-left:.25in;">14. At 24 hr from time of shaking, record temperature and hydrometer level of the blank cylinder. Then record the 24 hr hydrometer level for each successive cylinder. Sieve Analysis- procedure used to determine quantity of sand and silt<p style="margin-left:.25in;">1. After hydrometer analysis, pour the entire sample into the .063mm sieve. Rinse the sample thoroughly until all the clay is out. Try to break up any clay clumps you see.<p style="margin-left:.25in;">2. Transfer the sample to a pre-weighed and labeled aluminum pan. You will probably need to backwash the sieve to get the entire sample out. You can use a syringe to pull water from the pan if it gets too full. Dry the sample for 48 hours at 50-60C.<p style="margin-left:.25in;">3. Before transferring the dried sample to the sieves, make sure you pre-weigh the sieves and put their weight on the data sheet. You will need to do this before every sample as you might not get all the sample out of the sieves from the previous sample. Stack the sieves in the following order, top to bottom : 4mm, 2mm, 1mm, 0.5mm, 0.25mm, 0.125mm, 0.063mm, and pan. Pour the sample into the top sieve. Place the lid on, located on sieve shaker, and put the stack of sieves into the sieve shaker. Fasten the tie downs. Set shaker for 3 minutes. <p style="margin-left:.25in;">4. Remove stack of sieves from shaker. It&rsquo;s ok to leave the pan behind temporarily as it might be tight. Weigh each sieve and record the weight in the data sheet. If you see any clay clumps, break them up with your fingers and re-shake the stack a little, using hands is okay.<p style="margin-left:.25in;">5. Dump the sample out in the trash and clean the sieve with the brush. At the end of the day it might be necessary to backwash the sieves with water and dry overnight in the oven. <p style="margin-left:.25in;"> Calculations:1. percent clay was determined by the hydrometer analysis- P1.5, P24, X1.5, X24, and m are the variables that were calculated to determine percent clay by the hydrometer analysis.P1.5= ((sample hydrometer reading at 1.5 hours- blank hydrometer reading at 1.5 hours)/ (sample weight)) multiplied by 100.P24= ((sample hydrometer reading at 24 hours- blank hydrometer reading at 24 hours)/ (sample weight)) multiplied by 100X1.5= 1000*(.00019*(-.164* (sample hydrometer reading at 1.5 hours)+16.3)<sup>2</sup> *8100X24=1000*(.00019*(-.164* (sample hydrometer reading at 24 hours)+16.3)<sup>2</sup> *8100m= (P1.5-P24)/(ln(X1.5/X24))percent clay = m * ln(2/X24)) + P24clay (grams) = total weight * ( percent clay/ 100)2. percent Sand and percent Silt were determined based on the results of the sieve analysis which determined the grams of sand and silt.percent sand= total weight * (percent sand/ 100)percent silt= total weight * (percent silt/ 100)3. Othersorganic matter (grams) was calculated in this analysis as dry weight (grams) &ndash; ashed weight (grams)percwnt organic matter was calculated as ((organic matter (grams))/(total dry weight (grams)) multiplied by 100 C. Sediment Chemical Analysis1. SRP/ NaOH-PChemical analysis was done according to the protocol outlined in Pionke and Kunishi (1992). Each sample was first centrifuged and separated into aqueous and sediment fractions. The sediment fraction was then dried. The aqueous fraction was analyzed for soluble reactive phosphorus (srp) by automated colorimetry Nemi Method Number 365.4; see http://www.nemi.gov. NaOH P was then determined by NaOH extractions as described in Pionke and Kunishi (1992). Documentation: Pionke HB, Kunishi HM (1992) Phosphorus status and content of suspended sediment in a Pennsylvania watershed. Soil Sci 153:452&ndash;462.2. NH4 / KCl-NH4 The exact procedure that was used to analyze samples for ammonium is unknown. However, it is known that a KCl extraction was used. The KCl-NH4 was calculated as the concentration of ammonium in milliGramsPerLiter divided by the sediment weight in grams. 3. NO3 / KCl-NO3The exact procedure that was used to analyze samples for nitrate is also unknown. Again, it is known that a KCL extraction was used. The KCl-NO3 was calculated as the concentration of nitrate in milliGramsPerLiter divided by the sediment weight in grams.Note: The same sediment sample was used to measure ammonium and nitrate IV. Big Spring Creek Longitudinal Profile A standard longitudinal stream profile was conducted at Big Spring Creek, WI (wbic=176400) on unknown date(s). It is speculated that the profile was done during the summer of 2005, during which the rest of the data for Big Spring Creek was collected. Measurements for the profile began at the Big Spring Dam site (43.67035,-89.64225), a dam which was subsequently removed. The first (x_dist, y_dist) of (2.296, 5.57) corresponds to the location where the stream crosses Golden Court Road, whereas the second coordinate pair of (-2.615, -36.303) corresponds to the point below the previous Big Spring Creek Dam site. The third (x_dist, y_dist) of (-9.472, 7.681) corresponds to the top of the dam gates and is assigned a distance=0 as it is the starting point.
Version Number
23

Cascade Project at North Temperate Lakes LTER cross-lakes comparison carbon Data 1988 - 2007

Abstract
Data on dissolved organic and inorganic carbon as well as particulate organic matter and the partial pressure of CO2. Samples were collected with a Van Dorn bottle. Organic samples were collected from the epilimnion, metalimnion, and hypolimnion. Inorganic samples were collected at depths corresponding to 100%, 50%, 25%, 10%, 5%, and 1% of surface irradiance, as well as one sample from the hypolimnion. Samples for the partial pressure of CO2 were collected from two meters above the lake surface (air) and just below the lake surface (water).
Contact
Core Areas
Dataset ID
278
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Field and laboratory protocols can be found in the Cascade Methods Manual, found here: http://c13.valuemembers.net/Pages/methods_09.htmlPOC DOC:A: To ash filters: 1. Place filters in a foil boat and cover. Put in 450 C oven for 2 hours. B: POCorPON 1. Place a 25mm ashed GForF filter into a filter holder (grid to grid) that is attached to an Erlenmeyer flask. 2. Pour 100 - 300 ml duplicate samples from each depth (PML, meta, hypo) through 153 um mesh to remove large zooplankton. (Typically ~200mL for PML, 150 meta, 75 - 100 hypo – check previous week and adjust as necessary) 3. Filter samples at less than 200 mm Hg pressure. Remove filters from towers, fold in half, and place two replicates in one labeled Petri dish. Be sure to indic ate volume of water filtered on the Petri dish and record it on the POC log . Place dish in drying oven with the cover on loosely . 4. After filters have dried (a couple of days ), remove dish from drying oven and store in desicc ator. Analyze samples at IES. 5. Each week, make 2 blank filters by filtering 200ml of DI and processing as above. C: DOC 1. Pour 20 mL of filtrate (from POC procedure) from each lake - depth into labeled , acid washed, glass scintillati on vial s and acidify with 200 uL 2N H 2 SO 4 . Prepare t wo replicate samples for each depth. Each week, make one blank sample using 20ml of DI (filtrate from POC blanks) and 200uL 2N H 2 SO 4 . Analyze samples at IES. D. COLOR 1. Fill a 60 mL HDPE bottle with GForF filtrate from each lake - depth (from POC proced ure). Store in refrigerator until it is convenient to analyze samples on a spectrophotometer. Let samples warm up to room temperature before running on spec. 2. Turn on spectrophotometer at let it warm up for 30 minutes. Set to 440 nm. After calibrating with distilled water, rinse cuvette with 10 mL of filtrate. Remove rinse, then fill with 30 mL of filtrate and measure absorbance. Continue in this manner until all samples have been measured. (See the more detailed instructions on using the GENESYS 2 s pectrophotometer at UNDERC in Spec Instructions.doc ). 3. To estimate the amount of machine drift, measure the absorbance of distilled water after measuring sample
NTL Keyword
Version Number
32

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

Trout Lake USGS Water, Energy, and Biogeochemical Budgets (WEBB) Stream Data 1975-current

Abstract
This data was collected by the United States Geological Survey (USGS) for the Water, Energy, and Biogeochemical Budget Project. The data set is primarily composed of water chemistry variables, and was collected from four USGS stream gauge stations in the Northern Highland Lake District of Wisconsin, near Trout Lake. The four USGS stream gauge stations are Allequash Creek at County Highway M (USGS-05357215), Stevenson Creek at County Highway M (USGS-05357225), North Creek at Trout Lake (USGS-05357230), and the Trout River at Trout Lake (USGS-05357245), all near Boulder Junction, Wisconsin. The project has collected stream water chemistry data for a maximum of 36 different chemical parameters,. and three different physical stream parameters: temperature, discharge, and gauge height. All water chemistry samples are collected as grab samples and sent to the USGS National Water Quality Lab in Denver, Colorado. There is historic data for Stevenson Creek from 1975-1977, and then beginning again in 1991. The Trout Lake WEBB project began during the summer of 1991 and sampling of all four sites continues to date.
Creator
Dataset ID
276
Date Range
-
Maintenance
Completed.
Metadata Provider
Methods
DL is used to represent “detection limit” where known.NOTE (1): Each method listed below corresponds with a USGS Parameter Code, which is listed after the variable name. NOTE (2): If the NEMI method # is known, it is also specified at the end of each method description.NOTE (3): Some of the variables are calculated using algorithms within QWDATA. If this is the case see Appendix D of the NWIS User’s Manual for additional information. However, appendix D does not list the algorithm used by the USGS. If a variable is calculated with an algorithm the term: algor, will be listed after the variable name.anc: 99431, Alkalinity is determined in the field by using the gran function plot methods, see TWRI Book 9 Chapter A6.1. anc_1: 90410 and 00410, Alkalinity is determined by titrating the water sample with a standard solution of a strong acid. The end point of the titration is selected as pH 4.5. See USGS TWRI 5-A1/1989, p 57, NEMI method #: I-2030-89.2. c13_c12_ratio: 82081, Exact method unknown. The following method is suspected: Automated dual inlet isotope ratio analysis with sample preparation by precipitation with ammoniacal strontium chloride solution, filtration, purification, acidified of strontium carbonate; sample size is greater than 25 micromoles of carbon; one-sigma uncertainty is approximately ± 0.1 ‰. See USGS Determination of the delta13 C of Dissolved Inorganic Carbon in Water, RSIL Lab Code 1710. Chapter 18 of Section C, Stable Isotope-Ratio Methods Book 10, Methods of the Reston Stable Isotope Laboratory.3. ca, mg, mn, na, and sr all share the same method. The USGS parameter codes are listed first, then the method description with NEMI method #, and finally DL’s:ca- 00915, mg- 00925, mn- 01056, na- 00930, sr- 01080All metals are determined simultaneously on a single sample by a direct reading emission spectrometric method using an inductively coupled argon plasma as an excitation source. Samples are pumped into a crossflow pneumatic nebulizer, and introduced into the plasma through a spray chamber and torch assembly. Each analysis is determined on the basis of the average of three replicate integrations, each of which is background corrected by a spectrum shifting technique except for lithium (670.7 nm) and sodium (589.0 nm). A series of five mixed-element standards and a blank are used for calibration. Method requires an autosampler and emission spectrometry system. See USGS OF 93-125, p 101, NEMI Method #: I-1472-87.DL’s: ca- .02 mg/l, mg-.01 mg/l, mn-1.0 ug/l, na- .2 mg/l, sr- .5 ug/l4. cl, f, and so4 all share the same method. The USGS parameter codes are listed first, then the method description with NEMI method #, and finally DL’s:cl- 00940, f-00950, so4-00945All three anions (chloride, flouride, and sulfate) are separated chromatographically following a single sample injection on an ion exchange column. Ions are separated on the basis of their affinity for the exchange sites of the resin. The separated anions in their acid form are measured using an electrical conductivity cell. Anions are identified on the basis of their retention times compared with known standards. 19 The peak height or area is measured and compared with an analytical curve generated from known standards to quantify the results. See USGS OF 93-125, p 19, NEMI method #: I-2057.DL’s: cl-.2 mg/l, f-.1 mg/l, so4-.2 mg/lco2: 00405, algor, see NWIS User's Manual, QW System, Appendix D, Page 285.co3: 00445, algor.color: 00080, The color of the water is compared to that of the colored glass disks that have been calibrated to correspond to the platinum-cobalt scale of Hazen (1892), See USGS TWRI 5-A1 or1989, P.191, NEMI Method #: I-1250. DL: 1 Pt-Co colorconductance_field: 00094 and 00095, specific conductance is determined in the field using a standard YSI multimeter, See USGS TWRI 9, 6.3.3.A, P. 13, NEMI method #: NFM 6.3.3.A-SW.conductance_lab: 90095, specific conductance is determined by using a wheat and one bridge in which a variable resistance is adjusted so that it is equal to the resistance of the unknown solution between platinized electrodes of a standardized conductivity cell, sample at 25 degrees celcius, See USGS TWRI 5-A1/1989, p 461, NEMI method #: I-1780-85.dic: 00691, This test method can be used to make independent measurements of IC and TC and can also determine TOC as the difference of TC and IC. The basic steps of the procedure are as follows:(1) Removal of IC, if desired, by vacuum degassing;(2) Conversion of remaining inorganic carbon to CO<sub>2</sub> by action of acid in both channels and oxidation of total carbon to CO<sub>2</sub> by action of ultraviolet (UV) radiation in the TC channel. For further information, See ASTM Standards, NEMI method #: D6317. DL: n/adkn: 00623 and 99894, Organic nitrogen compounds are reduced to the ammonium ion by digestion with sulfuric acid in the presence of mercuric sulfate, which acts as a catalyst, and potassium sulfate. The ammonium ion produced by this digestion, as well as the ammonium ion originally present, is determined by reaction with sodium salicylate, sodium nitroprusside, and sodium hypochlorite in an alkaline medium. The resulting color is directly proportional to the concentration of ammonia present, see USGS TWRI 5-A1/1989, p 327, NEMI method #: 351.2. DL: .10 mg/Ldo: 0300, Dissolved oxygen is measured in the field with a standard YSI multimeter, NEMI Method #: NFM 6.2.1-Lum. DL: 1 mg/L.doc: 00681, The sample is acidified, purged to remove carbonates and bicarbonates, and the organic carbon is oxidized to carbon dioxide with persulfate, in the presence of an ultraviolet light. The carbon dioxide is measured by nondispersive infrared spectrometry, see USGS OF 92-480, NEMI Method #: O-1122-92. DL: .10 mg/L.don: 00607, algor, see NWIS User's Manual, QW System, Appendix D, page 291.dp: 00666 and 99893, All forms of phosphorus, including organic phosphorus, are converted to orthophosphate ions using reagents and reaction parameters identical to those used in the block digester procedure for determination of organic nitrogen plus ammonia, that is, sulfuric acid, potassium sulfate, and mercury (II) at a temperature of 370 deg, see USGS OF Report 92-146, or USGS TWRI 5-A1/1979, p 453, NEMI method #: I-2610-91. DL= .012 mg/L.fe: 01046, Iron is determined by atomic absorption spectrometry by direct aspiration of the sample solution into an air-acetylene flame, see USGS TWRI 5-A1/1985, NEMI method #: I-1381. DL= 10µg/L.h_ion: 00191, algor.h20_hardness: 00900, algor.h20_hardness_2: 00902, algor.hco3: 00440, algor.k: 00935, Potassium is determined by atomic absorption spectrometry by direct aspiration of the sample solution into an air-acetylene flame , see USGS TWRI 5-A1/1989, p 393, NEMI method #: I-1630-85. DL= .01 mg/L.n_mixed: 00600, algor.n_mixed_1: 00602, algor.n_mixed_2: 71887, algor.nh3_nh4: 00608, Ammonia reacts with salicylate and hypochlorite ions in the presence of ferricyanide ions to form the salicylic acid analog of indophenol blue (Reardon and others, 1966; Patton and Crouch, 1977; Harfmann and Crouch, 1989). The resulting color is directly proportional to the concentration of ammonia present, See USGS OF 93-125, p 125/1986 (mg/l as N), NEMI Method #: I-2525. DL= .01 mg/L.nh3_nh4_1: 71846, algor.nh3_nh4_2: 00610, same method as 00608, except see USGS TWRI 5-A1/1989, p 321. DL = .01 mg/L.nh3_nh4_3: 71845, algor.no2: 00613, Nitrite ion reacts with sulfanilamide under acidic conditions to form a diazo compound which then couples with N-1-naphthylethylenediamine dihydrochloride to form a red compound, the absorbance of which is measured colorimetrically, see USGS TWRI 5-A1/1989, p 343, NEMI method #: I-2540-90. DL= .01 mg/L.no2_2: 71856, algor.no3: 00618, Nitrate is determined sequentially with six other anions by ion-exchange chromatography, see USGS TWRI 5-A1/1989, P. 339, NEMI method #: I-2057. DL= .05 mg/L.no3_2: 71851, algor.no32: 00630, An acidified sodium chloride extraction procedure is used to extract nitrate and nitrite from samples of bottom material for this determination(Jackson, 1958). Nitrate is reduced to nitrite by cadmium metal. Imidazole is used to buffer the analytical stream. The sample stream then is treated with sulfanilamide to yield a diazo compound, which couples with N-lnaphthylethylenediamine dihydrochloride to form an azo dye, the absorbance of which is measured colorimetrically. Procedure is used to extract nitrate and nitrite from bottom material for this determination (Jackson, 1958), see USGS TWRI 5-A1/1989, p 351. DL= .1 mg/Lno32_2: 00631, same as description for no32, except see USGS OF 93-125, p 157. DL= .1 mg/L.o18_o16_ratio: 82085, Sample preparation by equilibration with carbon dioxide and automated analysis; sample size is 0.1 to 2.0 milliliters of water. For 2-mL samples, the 2-sigma uncertainties of oxygen isotopic measurement results are 0.2 ‰. This means that if the same sample were resubmitted for isotopic analysis, the newly measured value would lie within the uncertainty bounds 95 percent of the time. Water is extracted from soils and plants by distillation with toluene; recommended sample size is 1-5 ml water per analysis, see USGS Determination of the Determination of the delta (18 O or 16O) of Water, RSIL Lab Code 489.o2sat: Dissolved oxygen is measured in the field with a standard YSI multimeter, which also measures % oxygen saturation, NEMI Method #: NFM 6.2.1-Lum.ph_field: 00400, pH determined in situ, using a standard YSI multimeter, see USGS Techniques of Water-Resources Investigations, book 9, Chaps. A1-A9, Chap. A6.4 "pH," NEMI method # NFM 6.4.3.A-SW. DL= .01 pH.ph_lab: 00403, involves use of laboratory pH meter, see USGS TWRI 5-A1/1989, p 363, NEMI method #: I-1586.po4: 00660, algor, see NWIS User's Manual, QW System, Appendix D, Page 286.po4_2: 00671, see USGS TWRI 5-A1/1989, NEMI method #: I-2602. DL= .01 mg/L.s: 63719, cannot determine exact method used. USGS method code: 7704-34-9 is typically used to measure sulfur as a percentage, with an DL =.01 µg/L. It is known that the units for sulfur measurements in this data set are micrograms per liter.sar: 00931, algor, see NWIS User's Manual, QW System, Appendix D, Page 288.si: 00955, Silica reacts with molybdate reagent in acid media to form a yellow silicomolybdate complex. This complex is reduced by ascorbic acid to form the molybdate blue color. The silicomolybdate complex may form either as an alpha or beta polymorph or as a mixture of both. Because the two polymorphic forms have absorbance maxima at different wavelengths, the pH of the mixture is kept below 2.5, a condition that favors formation of the beta polymorph (Govett, 1961; Mullen and Riley, 1955; Strickland, 1952), see USGS TWRI 5-A1/1989, p 417, NEMI method #: I-2700-85. DL= .10 mg/L.spc: 00932, algor, see NWIS User's Manual, QW System, Appendix D, Page 289.tds: 70300 and 70301, A well-mixed sample is filtered through a standard glass fiber filter. The filtrate is evaporated and dried to constant weight at 180 deg C, see " Filterable Residue by Drying Oven," NEMI method #: 160.1, DL= 10 mg/l. Note: despite DL values occur in the data set that are less than 10 mg/l.tds_1: 70301, algor, see NWIS User's Manual, QW System, Appendix D, Page 289.tds_2: 70303, algor, see NWIS User's Manual, QW System, Appendix D, Page 290.tkn: 00625 and 99892, Block digester procedure for determination of organic nitrogen plus ammonia, that is, sulfuric acid, potassium sulfate, and Mercury (II) at a temperature of 370°C. See the USGS Open File Report 92-146 for further details. DL: .10 mg/L.toc: 00680, The sample is acidified, purged to remove carbonates and bicarbonates, and the organic carbon is oxidized to carbon dioxide with persulfate, in the presence of an ultraviolet light. The carbon dioxide is measured by nondispersive infrared spectrometry, see USGS TWRI 5-A3/1987, p 15, NEMI Method #: O-1122-92. DL=.10 mg/L.ton: 00605, algor, See NWIS User's Manual, QW System, Appendix D, page 286.tp: 00665 and 99891, This method may be used to analyze most water, wastewater, brines, and water-suspended sediment containing from 0.01 to 1.0 mg/L of phosphorus. Samples containing greater concentrations need to be diluted, see USGS TWRI 5-A1/1989, p 367, NEMI method #: I-4607. tp_2: 71886, algor.tpc: 00694, The basic steps of this test method are:1) Conversion of remaining IC to CO2 by action of acid, 2) Removal of IC, if desired, by vacuum degassing, 3) Split of flow into two streams to provide for separate IC and TC measurements, 4) Oxidation of TC to CO2 by action of acid-persulfate aided by ultraviolet (UV) radiation in the TC channel, 5) Detection of CO2 by passing each liquid stream over membranes that allow the specific passage of CO2 to high-purity water where change in conductivity is measured, and 6) Conversion of the conductivity detector signal to a display of carbon concentration in parts per million (ppm = mg/L) or parts per billion (ppb = ug/L). The IC channel reading is subtracted from the TC channel reading to give a TOC reading, see ASTM Standards, NEMI Method #: D5997. DL= .06 µg/L.tpn: 49570, A weighed amount of dried particulate (from water) or sediment is combusted at a high temperature using an elemental analyzer. The combustion products are passed over a copper reduction tube to covert nitrogen oxides to molecular nitrogen. Carbon dioxide, nitrogen, and water vapor are mixed at a known volume, temperature, and pressure. The concentrations of nitrogen and carbon are determined using a series of thermal conductivity detectors/traps, measuring in turn by difference hydrogen (as water vapor), carbon (as carbon dioxide), and nitrogen (as molecular nitrogen). Procedures also are provided to differentiate between organic and inorganic carbon, if desired, see USEPA Method 440, NEMI method #: 440. DL= .01 mg/L.
Short Name
TL-USGS-WEBB Data
Version Number
15

Wisconsin Lake Historical Limnological Parameters 1925 - 2009

Abstract
This dataset is a compilation of ten sources of data representing physical and chemical properties of 13,093 Wisconsin lakes. The goal was to compile a comprehensive resource of historical and more recent lake information which would be accessible by querying a single database. Due to the wide temporal extent (1925-2009), methods used for measuring lake parameters in this dataset have varied. A careful look at the available metadata and background information is recommended.Sampling Frequency: variesNumber of sites: 13,093
Contact
Dataset ID
263
Date Range
-
Maintenance
complete
Metadata Provider
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 &gt;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 &gt;= 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.
Short Name
WILIMN1
Version Number
25

North Temperate Lakes LTER: Groundwater Chemistry 1984 - current

Abstract
Water chemistry is measured annually in 11 monitoring wells to characterize regional groundwater chemistry in the Trout Lake area. The chemical parameters measured include pH, conductivity, total alkalinity, disolved inorganic and organic carbon, total nitrogen, nitrae, ammonia, total phosphorus, calcium, magnesium, soium, potassium, chloride, sulfate, iron, manganese, total silica and dissolved reactive silica. Chemical data areavailable at a quarterly sampling frequency for some years. In addition (see related data set - Groundwater Level), water levels in 37 monitoring wells are measured several times per year. The wells are scattered throughout the Trout Lake hydrological basin and the data are used to calibrate and test regional groundwater flow models. Sampling Frequency: annually - with some earlier data from quarterly sampling Number of sites: 11
Dataset ID
10
Date Range
-
Maintenance
ongoing
Metadata Provider
Methods
Ammonium, Nitrate, Nitrit Samples for ammonium and nitrate or nitrite are collected together with a peristaltic pump and tubing and in-line filtered (through a 0.40 micron polycarbonate filter) into new, 20 ml HDPE plastic containers with conical caps. The samples are stored frozen until analysis, which should occur within 6 months. The samples are analyzed for ammonium (and nitrateornitrite) simultaneously by automated colorimetric spectrophotometry, using a segmented flow autoanalyzer. Ammonium is determined by utilizing the Berthelot Reaction, producing a blue colored indophenol compound, where the absorption is monitored at 660 nm. The detection limit for ammonium is approximately 3 ppb and the analytical range for the method extends to 4000 ppb. The detection limit for nitrateornitrite is approximately 2 ppb and the analytical range for the method extends to 4000 ppb. Method Log: Prior to January 2006 samples, ammonium was determined on a Technicon segmented flow autoanalyzer. From 2006 to present, ammonium is determined by an Astoria-Pacific Astoria II segmented flow autoanalyzer. Chloride, Sulfate Samples for chloride and sulfate are collected together with a peristaltic pump and tubing and in-line filtered (through a 0.40 micron polycarbonate filter) into new, 20 ml HDPE plastic containers with conical caps. The samples are stored refrigerated at 4 degrees Celsius until analysis, which should occur within 6 months. The samples are analyzed for chloride (and sulfate) simultaneously by Ion Chromatography, using a hydroxide eluent. The detection limit for chloride is approximately 0.01 ppm and the analytical range for the method extends to 100 ppm. The detection limit for sulfate is approximately 0.01 ppm and the analytical range for the method extends to 60 ppm. Method Log: Prior to January 1998 samples, chloride was determined on a Dionex DX10 Ion Chromatograph, using a chemical fiber suppressor. From 1998 to 2011, chloride was determined by a Dionex model DX500, using an electro-chemical suppressor. From January 2011 until present, chloride is determined by a Dionex model ICS 2100 using an electro-chemical suppressor. Calcium, magnesium, sodium, potassium, iron, and manganese Samples for calcium analysis (as well as dissolved nitrogen and phosphorus, magnesium, sodium, potassium, iron, and manganese) are collected together with a peristaltic pump and tubing and in-line filtered (through a 40 micron polycarbonate filter) into 120 ml LDPE bottles and acidified to a 1percent HCl matrix by adding 1 ml of ultra pure concentrated HCl to 100 mls of sample. For every sample acidification event, three acid blanks are created by adding the same acid used on the samples to 100 mls of ultra pure water supplied from the lab. Once acidified, the samples are stable at room temperature until analysis, which should occur within one year. Until acidification, the samples should be refrigerated at 4 degrees Celsius. Calcium, as well as magnesium, sodium, potassium, iron, and manganese are analyzed simultaneously on an optical inductively-coupled plasma emission spectrophotometer (ICP-OES). The acidified samples are directly aspirated into the instrument without a digestion. Calcium is analyzed at 317.933 nm and at 315.887 nm and viewed axially for low-level analysis and radially for high level analysis. The detection limit for calcium is 0.06 ppm with an analytical range of the method extends to 50 ppm. The detection limit for iron is 0.02 ppm with an analytical range of the method extends to 20 ppm. The detection limit for magnesium is 0.03 ppm with an analytical range of the method extends to 50 ppm. The detection limit for manganese is 0.01 ppm with an analytical range of the method extends to 2 ppm. The detection limit for potassium is 0.06 ppm with an analytical range of the method extends to 10 ppm. The detection limit for sodium is 0.06 ppm with an analytical range of the method extends to 50 ppm. Method Log: Prior to January 2002, calcium, magnesium, sodium, potassium, iron, and manganese were determined on a Perkin-Elmer model 503 Atomic Absorption Spectrophotometer. Lanthanum at a 0.8percent concentration was added as a matrix modifier to suppress chemical interferences. From January 2002 to present, samples are analyzed for calcium on a Perkin-Elmer model 4300 DV ICP. Inorganic and organic carbon Samples for inorganic and organic carbon are collected together with a peristaltic pump and tubing and in-line filtered, if necessary, (through a 0.40 micron polycarbonate filter) into glass, 24 ml vials (that are compatible with the carbon analyzer autosampler), and capped with septa, leaving no head space. The samples are stored refrigerated at 4 degrees Celsius until analysis, which should occur within 2-3 weeks. The detection limit for inorganic carbon is 0.15 ppm, and the analytical range for the method is 60 ppm. The detection limit for organic carbon is 0.30 ppm and the analytical range for the method is 30 ppm. Method Log: Prior to May 2006 samples, inorganic carbon was analyzed by phosphoric acid addition on an OI Model 700 Carbon Analyzer. From May 2006 to present, inorganic carbon is still analyzed by phosphoric acid addition, but on a Shimadzu TOC-V-csh Total Organic Carbon Analyzer. Method Log: Prior to May 2006 samples, organic carbon was analyzed by heated persulfate digestion on an OI Model 700 Carbon Analyzer. From May 2006 to present, Organic carbon is analyzed by combustion, on a Shimadzu TOC-V-csh Total Organic Carbon Analyzer. Dissolved reactive silicon Samples for silicon are collected with a peristaltic pump and tubing and in-line filtered (through a 40 micron polycarbonate filter) into 120 ml LDPE bottles and acidified to a 1percent HCl matrix by adding 1 ml of ultra pure concentrated HCl to 100 mls of sample. For every sample acidification event, three acid blanks are created by adding the same acid used on the samples to 100 mls of ultra pure water supplied from the lab. Once acidified, the samples are stable at room temperature until analysis, which should occur within one year. Until acidification, the samples should be refrigerated at 4 degrees Celsius. Dissolved reactive silica is determined by the Heteropoly Blue Method and the absorption is measured at 820 nm. The detection limit for silicon is 6 ppb and the analytical range is 15000 ppb. Method Log These determinations were performed manually using a Bausch and Lomb Spectrophotometer from the beginning of the project until April 1984. From 1984 through 2005, dissolved reactive silicon was determined on a Technicon Auto Analyzer II. From January 2006 to present, samples are run on an Astoria-Pacific Astoria II Autoanalyzer. total and dissolved nitrogen and phosphorus Samples for total and dissolved nitrogen and phosphorus analysis are collected together with a peristaltic pump and tubing and in-line filtered, when necessary, (through a 40 micron polycarbonate filter) into 120 ml LDPE bottles and acidified to a 1percent HCl matrix by adding 1 mL of ultra pure concentrated HCl to 100 mls of sample. For every sample acidification event, three acid blanks are created by adding the same acid used on the samples to 100 mls of ultra pure water supplied from the lab. Once acidified, the samples are stable at room temperature until analysis, which should occur within one year. Until acidification, the samples should be refrigerated at 4 degrees Celsius. The samples must first be prepared for analysis by adding an NaOH–Persulfate digestion reagent and heated for an hour at 120 degrees C and 18-20 psi in an autoclave. The samples are analyzed for total nitrogen and total phosphorus simultaneously by automated colorimetric spectrophotometry, using a segmented flow autoanalyzer. Total nitrogen is determined by utilizing the automated cadmium reduction method, as described in Standard Methods, where the absorption is monitored at 520 nm. The detection limit for total and dissolved nitrogen is approximately 21 ppb and the analytical range for the method extends to 2500 ppb. The detection limit for total phosphorus is approximately 3 ppb and the analytical range for the method extends to 800 ppb. Method Log: Prior to January 2006 samples, total nitrogen was determined on a Technicon segmented flow autoanalyzer. From 2006 to present, total nitrogen is determined by an Astoria-Pacific Astoria II segmented flow autoanalyzer. pH We sample at the deepest part of the lake using a peristaltic pump and tubing, monthly during open water and approximately every five weeks during ice cover. We collect two types of pH samples at each sampling depth: one in 20ml vials with cone cap inserts to exclude all air from the vial, and one in 125ml bottles to be air equilibrated before analysis. The depths for sample collection are based on thermal stratification: top and bottom of the epilimnion, mid thermocline, and top, middle,and bottom of the hypolimnion. During mixis we sample at the surface, mid water column, and bottom. We analyze for pH the same day that samples are collected, keeping them cold and dark until just before analysis. Samples are warmed to room temperature in a dark container, and the air equilibrated samples are bubbled with outside air for at least 15 minutes prior to measurement. We measure pH using a Radiometer combination pH electrode and Orion 4Star pH meter. Protocol Log: 1981-1988 -- used a PHM84 Research pH meter. 1986 -- began analyzing air equilibrated pH. 1988 - July 2010 -- used an Orion model 720 pH meter.</p>
Short Name
NTLGW02
Version Number
23

North Temperate Lakes LTER: Chemical Limnology of Primary Study Lakes: Nutrients, pH and Carbon 1981 - current

Abstract
Parameters characterizing the nutrient chemistry of the eleven primary lakes (Allequash, Big Muskellunge, Crystal, Sparkling, and Trout lakes, unnamed lakes 27-02 [Crystal Bog] and 12-15 [Trout Bog], Mendota, Monona, Wingra, and Fish) are measured at one station in the deepest part of each lake at the top and bottom of the epilimnion, mid-thermocline, and top, middle, and bottom of the hypolimnion. These parameters include total nitrogen, total dissolved nitrogen (only in the northern lakes), nitrate, ammonia, total phosphorus, total dissolved phosphorus (only in the northern lakes), dissolved reactive phosphorus (only in the southern lakes and not in Wingra and Fish after 2003), bicarbonite-reactive filtered and unfiltered silica (both discontinued in 2003), dissolved reactive silica, field pH, air equilibrated pH, total alkalinity, total inorganic carbon, dissolved inorganic carbon, total organic carbon, dissolved organic carbon, and total particulate matter (only in the northern lakes in this data set. Total particulate matter in southern lakes starting in 2000 is available in a separate dataset). Sampling Frequency: monthly during ice-free season - every 6 weeks during ice-covered season for the northern lakes. The southern lakes are similar except that sampling occurs monthly during the fall and typically only once during the winter (depending on ice conditions). Number of sites: 11
Dataset ID
1
Date Range
-
DOI
10.6073/pasta/cc6f0e4d317d29200234c7243471472a
Maintenance
ongoing
Metadata Provider
Methods
Inorganic and organic carbon: Samples for inorganic and organic carbon are collected together with a peristaltic pump and tubing and in-line filtered, if necessary, (through a 0.40 micron polycarbonate filter) into glass, 24 ml vials (that are compatible with the carbon analyzer autosampler), and capped with septa, leaving no head space. The samples are stored refrigerated at 4 degrees Celsius until analysis, which should occur within 2-3 weeks. The detection limit for inorganic carbon is 0.15 ppm, and the analytical range for the method is 60 ppm. The detection limit for organic carbon is 0.30 ppm and the analytical range for the method is 30 ppm. Method Log: Prior to May 2006 samples, inorganic carbon was analyzed by phosphoric acid addition on an OI Model 700 Carbon Analyzer. From May 2006 to present, inorganic carbon is still analyzed by phosphoric acid addition, but on a Shimadzu TOC-V-csh Total Organic Carbon Analyzer. Method Log: Prior to May 2006 samples, organic carbon was analyzed by heated persulfate digestion on an OI Model 700 Carbon Analyzer. From May 2006 to present, Organic carbon is analyzed by combustion, on a Shimadzu TOC-V-csh Total Organic Carbon Analyzer. Dissolved reactive silica Samples for silica are collected with a peristaltic pump and tubing and in-line filtered (through a 45 micron polycarbonate filter) into 120 ml LDPE bottles and acidified to a 1percent HCl matrix by adding 1 ml of ultra pure concentrated HCl to 100 mls of sample. For every sample acidification event, three acid blanks are created by adding the same acid used on the samples to 100 mls of ultra pure water supplied from the lab. Once acidified, the samples are stable at room temperature until analysis, which should occur within one year. Until acidification, the samples should be refrigerated at 4 degrees Celsius. Dissolved reactive silica is determined by the Heteropoly Blue Method and the absorption is measured at 820 nm. The detection limit for silica is 6 ppb and the analytical range is 15000 ppb. Method Log These determinations were performed manually using a Bausch and Lomb Spectrophotometer from the beginning of the project until April 1984. From 1984 through 2005, dissolved reactive silica was determined on a Technicon Auto Analyzer II. From January 2006 to present, samples are run on an Astoria-Pacific Astoria II Autoanalyzer. total and dissolved nitrogen and phosphorus Samples for total and dissolved nitrogen and phosphorus analysis are collected together with a peristaltic pump and tubing and in-line filtered, when necessary, (through a 45 micron polycarbonate filter) into 120 ml LDPE bottles and acidified to a 1percent HCl matrix by adding 1 mL of ultra pure concentrated HCl to 100 mls of sample. For every sample acidification event, three acid blanks are created by adding the same acid used on the samples to 100 mls of ultra pure water supplied from the lab. Once acidified, the samples are stable at room temperature until analysis, which should occur within one year. Until acidification, the samples should be refrigerated at 4 degrees Celsius. The samples must first be prepared for analysis by adding an NaOH–Persulfate digestion reagent and heated for an hour at 120 degrees C and 18-20 psi in an autoclave. The samples are analyzed for total nitrogen and total phosphorus simultaneously by automated colorimetric spectrophotometry, using a segmented flow autoanalyzer. Total nitrogen is determined by utilizing the automated cadmium reduction method, as described in Standard Methods, where the absorption is monitored at 520 nm. The detection limit for total and dissolved nitrogen is approximately 21 ppb and the analytical range for the method extends to 2500 ppb. The detection limit for total phosphorus is approximately 3 ppb and the analytical range for the method extends to 800 ppb. Method Log: Prior to January 2006 samples, total nitrogen was determined on a Technicon segmented flow autoanalyzer. From 2006 to present, total nitrogen is determined by an Astoria-Pacific Astoria II segmented flow autoanalyzer.
Short Name
NTLCH01
Version Number
52
Subscribe to DOC