US Long-Term Ecological Research Network

Landscape Position Project at North Temperate Lakes LTER: Chemical Limnology 1998 - 2000

Abstract
Parameters characterizing the chemical limnology and spatial attributes of 51 lakes were surveyed as part of the Landscape Position Project. Parameters are measured at or close to the deepest part of the lake. The following parameters are measured one meter from the surface and two meters from the bottom of the lake: pH, total phosphorus, total nitrogen, total silica. The following parameters are measured one meter from the surface: dissolved organic carbon, total organic carbon, dissolved inorganic carbon, total inorganic carbon, spectrophotometric absorbance (color scan), major anions and cations, alkalinity. Sampling Frequency: once for conservative parameters (major ions, carbon, color, alkalinity); monthly for one summer for other parameters (chlorophyll, nitrogen, phosphorus, pH, silica, temperature, dissolved oxygen, and conductivity) Number of sites: 51Allequash Lake, Anderson Lake, Arrowhead Lake, Beaver Lake, Big Lake, Big Crooked Lake, Big Gibson Lake, Big Muskellunge Lake, Boulder Lake, Brandy Lake, Crampton Lake, Crystal Lake, Diamond Lake, Flora Lake, Heart Lake, Ike Walton Lake, Island Lake, Johnson Lake, Katherine Lake, Kathleen Lake, Katinka Lake, Lehto Lake, Little Crooked Lake, Little Muskie, Little Spider Lake, Little Sugarbush Lake, Little Trout Lake, Lower Kaubeshine Lake, Lynx Lake, McCullough Lake, Mid Lake, Minocqua Lake, Muskesin Lake, Nixon Lake, Partridge Lake, Randall Lake, Round Lake, Sanford Lake, Sparkling Lake, Statenaker Lake, Stearns Lake, Tomahawk Lake, Trout Lake, Upper Kaubeshine Lake, Verna Lake, Ward Lake, White Birch Lake, White Sand Lake, Wild Rice Lake, Wildcat Lake, Wolf Lake, Vilas County, WI, Iron County, WI, Oneida County, WI, Gogebic County, MI, USA
Dataset ID
91
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Chloride, SulfateSamples 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, silicon, magnesium, sodium, potassium, iron, and manganeseSamples for calcium analysis (as well as dissolved nitrogen and phosphorus, silicon, 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.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.
Short Name
LPPCHEM1
Version Number
9

North Temperate Lakes LTER: Patterns of Soil Phosphorus Across an Urbanizing Agricultural Landscape 2000 - 2001

Abstract
Understanding the magnitude and location of soil phosphorus (P) accumulation in watersheds is a critical step toward managing runoff of this pollutant to aquatic ecosystems. Here, we examined the usefulness of urban-rural gradients (URGs), an emerging paradigm in urban ecology, for predicting soil P concentrations across a rapidly urbanizing agricultural watershed in southern Wisconsin. We compared several measures of an urban-rural gradient to predictors of soil P such as soil type, slope, topography, land use, land cover, and fertilizer and manure use. Most of the factors that were expected to drive differences in soil P concentrations were not found to be good predictors of soil P; while there were several significant relationships, most explained only a small proportion of the variation. There was a significant relationship between soil P concentration and each of the urban-rural gradients, but these relationships explained only a small amount of the variation in soil P concentrations. Soil P concentration, unlike some other ecosystem properties, is not well predicted by urban-rural gradients Additional Chemical Analyses: These additional analyses were done to provide comparisons to Bray-1 P. Specifically, we wanted to know whether, in Dane County, there was a consistent relationship between total P and Bray-1 P. For sample sites on private property, specific site location information, such as GPS coordinates, is not included in these datasets. If you have a need for this information, please get in touch with the contact person listed above Number of sites: 334; 20 of these sites with additional chem analyses
Core Areas
Dataset ID
105
Date Range
-
Maintenance
completed
Metadata Provider
Methods
A combination map, consisting of the information in both the population density map and the modified-distance map, was also created (Figure 2c). This map is simply based on a grid cell by grid cell multiplication of the reclassified values from the population density and the modified distance map. In this paper, I will refer to this map as the combination map.Data points for measuring soil P and associated factors were stratified by zone and randomly located within each zone according to the combination map—with approximately 70 data points per zone. Location and address of each point were determined using the Madison and Dane County parcel GIS layers. Permission was requested from landowners to take a soil sample, and the precise location of the sample on the property was determined using standard randomizing techniques. If permission was denied (2 cases out of 330) or if there was no one present at the location, a coin toss was used to determine movement one parcel to the right or to the left along the same road. Landowners were also asked about their fertilizer use practices, manure use, dog ownership, and the date the house was built, if known.Approximately 400 soil samples were taken in the top soil horizon to a depth of 13.5 cm with a standard soil corer (diameter = approximately 1.6 cm). This depth was always within the surface horizon and any grass thatch was removed from lawn samples. Other data collected include percent slope, convex or concave nature of the slope, land use, land-cover type, and percent vegetative cover. The visually perceived zone was also recorded. The visually perceived zone was determined by visual inspection using a predetermined set of definitions of each zone. For example, urban sites were those with the highest housing density or some industrial use; suburban sites were those of moderate housing density and residential character; suburban fringe were newer residential developments of low housing density and larger houses; agricultural fringe were older residential developments of low density; and agricultural were those areas that were actively farmed. A handheld global positioning device was used to determine the precise (± 1 m) location of the soil sample.Soil samples were stored for no more than 3 weeks at room temperature before analysis. They were then dried for 15–24 hours at 50–55degreeC and sieved (1.8-mm mesh). Soil samples were then analyzed for Bray-1 P at the University of Wisconsin Soil and Plant Analysis Lab. Bray-1, a measure of extractable P, is a commonly used measure of phosphorus available to plants in agricultural systems. While relationships between extractable soil P and dissolved P in runoff have been noted in some systems (Sharpley and others 1993, Sharpley 1995), these extractions were generally developed to estimate plant available P, not to reflect P storage in the soil or P runoff. Therefore, we tested a subset (60) of our samples for total P, a better measure of P storage in soils. A regression of our samples indicates a reasonably close relationship between Bray-1 P and total P in our study area soils (Figure 3), indicating that our Bray-1 P results are probably a satisfactory estimate of both extractable P and the sorbed P that tends to accumulate in agricultural soils.
Short Name
SOILPVC
Version Number
17

EPA Eastern Lake Survey original data for the Upper Midwest Region 1984

Abstract
Overton, W. S., P. Kanciruk, L. A. Hook, J. M. Eilers, D. H. Landers, D. F. BRAKKE, R. A. Linthurst, and M. D. DeHaan. 1986. Characteristics of lakes in the Eastern United States. Vol. 2. Lakes sampled and descriptive statistics for physical and chemical variables. US EPA 600/4-86/007B. 369 p. 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. This dataset includes data on 592 lakes in Michigan, Minnesota and Wisconsin. Number of sites: 592
Core Areas
Creator
Dataset ID
107
Date Range
-
Maintenance
completed
Metadata Provider
Methods
please see methods description in abstract
Short Name
RGELS
Version Number
19

Environmental Research Lab-Duluth Chemical Lake Survey 1979 - 1982

Abstract
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. Number of sites: 856 within 832 lakes
Core Areas
Dataset ID
101
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Methods are published in 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.
Short Name
RGERLD
Version Number
23
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