US Long-Term Ecological Research Network

Crustacean Zooplankton Species Richness in 66 North American Lakes 1992 - 1993

Abstract
Data from 66 North American lakes were collected to construct a model for predicting the number of crustacean zooplankton species expected in a lake. The chosen lakes have a range from 4 sq m to 80 x 10**9 sq m surface area, range from ultra-oligotrophic to hypereutrophic, and have zooplankton species lists based of several years of observation The number of crustacean zooplankton species in a lake is significantly correlated with lake size, average rate of photosynthesis (parabolic function) and the number of lakes within 20 km. A multiple linear regression model, using these three independent variables, explains approximately 75% of the variation in log species richness. Prediction of species richness is not enhanced by the knowledge of lake depth, salinity, elevation, latitude, longitude, or distance to nearest lake. The North American species area curve is statistically different from and steeper than the corresponding European curve.Number of sites: 69
Core Areas
Creator
Dataset ID
223
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Dodson, S. 1992. Predicting Crustacean Zooplankton Species Richness. Limnology and Oceanography 37:848-856.Dodson, S. 1991. Species richness of crustacean zoo- plankton in European lakes of different sizes. Int. Ver. Theor. Angew. Limnol. Verh. 24:1223-1229.
Short Name
DODSON2
Version Number
23

Biocomplexity at North Temperate Lakes LTER; Coordinated Field Studies: Chemical Limnology 2001 - 2004

Abstract
Chemical Limnology data collected for Biocomplexity Project; Landscape Context - Coordinated Field Studies Replicate chemical samples were pumped from the surface water (0.5m depth) and secchi depth was recorded at each lake. Temperature/dissolved oxygen profiles were taken throughout the water column at one meter intervals on all lakes. For more detail see the Water Sampling Protocol. Sampling Frequency: During 2001, temperature/dissolved oxygen profiles and secchi depths were taken twice during the stratified summer period. Chemistry samples were only taken once during the 2001 stratified period. From 2002 through 2004, all chemical and physical water samples were taken once during June (or resampled during the stratified period if June samples were bad). All lakes in which color, DIC/DOC, and chlorophyll samples were taken in 2001 were resampled in 2002 due to error in collection and/or analysis. Number of sites: 62 Vilas County lakes were sampled from 2001-2004 (approximately 15 different lakes each year).
Dataset ID
41
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Environmental Sampling and Analysis: Physical, chemical and biological samples were taken above the deepest point in each lake during the summer stratification period (June, July, or August). Water samples were collected from one half meter depth using a peristaltic pump, and were analyzed for pH, alkalinity, specific conductance, water color, chlorophyll-a, dissolved organic and inorganic carbon, total phosphorus, and total nitrogen (Appendix Table 1). Secchi depth, temperature and dissolved oxygen profiles, and vertical plankton tows were also taken at the deepest point. Temperature and dissolved oxygen concentrations (DO) were measured through the water column at 1 meter increments.. Conductivity, TP-TN, alkalinity and pH water samples were collected unfiltered while water for DIC-DOC and color water samples was filtered through nucleopore polycarbonate filters. Alkalinity, pH, and DIC-DOC samples were filled to the top and sealed quickly to prevent CO2 loss or invasion. Samples containing air bubbles were recollected. Chlorophyll samples were collected on glass fiber filters in the field. Water chemistry and chlorophyll a analyses were done at the Trout Lake Biological Station, Boulder Junction, WI except for TP, TN, DIC and DOC samples, which were analyzed at the Center for Limnology-Lake Mendota Laboratory, Madison, WI.
NTL Keyword
Short Name
BIOCHEM1
Version Number
7

Biocomplexity at North Temperate Lakes LTER; Coordinated Field Studies: Lakes 2001 - 2004

Abstract
The study lakes selected for the "cross-lake comparison" segment of the Biocomplexity Project include 62 lakes located in Vilas County, Wisconsin. The lakes were chosen to represent a range of positions on gradients of both human development and landscape position.Allequash Lake, Anvil Lake, Arrowhead Lake, Bass Lake, Big Lake, Birch Lake, Ballard Lake, Big Muskellunge Lake, Black Oak Lake, Big Portage Lake, Brandy Lake, Big St Germain Lake, Camp Lake, Crab Lake, Circle Lily, Carpenter Lake, Day Lake, Eagle Lake, Erickson Lake, Escanaba Lake, Found Lake, Indian Lake, Jag Lake, Johnson Lake, Jute Lake, Katinka Lake, Lake Laura, Little Croooked Lake, Little Spider Lake, Little St Germain Lake, Little Crawling Stone Lake, Little John Lake, Lac Du Lune Lake, Little Rock Lake - North, Lost Lake, Little Rock Lake - South, Little Star Lake, Little Arbor Vitae Lake, Lynx Lake, Mccollough Lake, Moon Lake, Morton Lake, Muskellunge Lake, Nebish Lake, Nelson Lake, Otter Lake, Oxbow Lake, Palmer Lake, Pioneer Lake, Pallete Lake, Papoose Lake, Round Lake, Star Lake, Sparkling Lake, Spruce Lake, Stormy Lake, Twin Lake South, Tenderfoot Lake, Towanda Lake, Upper Buckatabon Lake, Vandercook Lake, White Sand Lake, Vilas County, WI, USA
Dataset ID
209
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Study Lakes We selected 60 northern temperate lake sites in Vilas County, Wisconsin lake district. Methods for lake choice and sampling are given in greater detail in Marburg et al. (2005) Each lake was sampled once between 2001 and 2004, in June, July, or August (15 different lakes each summer). We chose stratified lakes deeper than 4 m to insure that all the lakes contained a diverse fish community. With two exceptions (chains of lakes), lakes were chosen to be in separate watersheds. Lakes were chosen based on two criteria landscape position, using historical DNR water conductivity data as a proxy of position, and riparian housing development, measured in buildings km-1 shoreline (Marburg et al. 2005). Landscape position refers to the location of a lake along the hydrological gradient. The gradient ranges from the top of a drainage system, where seepage lakes are fed mainly by rainwater, through lakes which receive water from groundwater and have surface outflows, to lakes further down in the drainage system, which receive water from both ground and surface flow (Kratz et al. 1997).Landscape position affects lake water chemistry, because as water flows across the surface and through soil, it picks up carbonates and other ions which increase the waters electrical conductivity (specific conductance, a temperature-independent measure of salinity), alkalinity, and its ability to support algal and macrophyte production. In addition, aspects of lake morphology correlate with landscape position. Most obviously, larger lakes tend to occur lower in drainage systems (Riera et al. 2000).The riparian (near-shore terrestrial) zone around northern Wisconsin lakes is being rapidly developed for use as both summer and permanent housing (Peterson et al., 2003). Concurrent with housing development, humans often directly and indirectly remove logs (Kratz et al. 2002) and aquatic vegetation (Radomski and Goeman 2001) from the littoral zone (near shore shallow water area), resulting in reduced littoral zone complexity. The slowly-decaying logs of fallen trees create physical structure (coarse woody habitat CWH) in the littoral zone of lakes that provides habitat and refuge for aquatic organisms (Christensen et al. 1996). Fish, including plankton-eating species (planktivores), reproduce and develop in shallow water (Becker 1983). Because planktivorous fish affect zooplankton community structure through size-selective predation (Brooks and Dodson 1965), there is the potential for indirect effects of housing development on zooplankton.Lakes ranged in size from 24 to 654 ha. In 2001, 2002 and 2004 we chose lakes from the extreme ends of the conductivity and housing density gradients and in 2003 lakes were chosen to fill in the gap in the middle of the ranges. The study lakes range from oligotrophic to mesotrophic (Kratz et al. 1997 Magnuson et al. 2005).At each lake we sampled zooplankton, water chemistry, riparian and littoral vegetation, fish, crayfish, and macrophytes. Each lake was sampled only once, but given the large number of lakes sampled in this area, we expect to see relationships between variables within lakes and at a landscape scale. A snapshot sampling design maximizes sites that can be visited, and is sufficient for a general characterization of zooplankton communities (Stemberger et al. greater than 001).
Short Name
BIOLAKE1
Version Number
5

Historical Birge - Juday Lake Survey 1900 - 1943

Abstract
Data collected by Birge, Juday, and collaborators, mostly in north-central Wisconsin, from 1900 through 1943; generally one sampling event per lake during the summer, but on some lakes, especially around Trout Lake Station, several sampling events for several successive years. This data set contains both surface data (depth of zero) and multi-depth data. Note that not all variables were measured on all lakes. 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).Wisconsin DNR Technical Report. Note: Values of -99999 in water quality data indicate trace amount of parameter was present. Number of sites: 663 (generally one sampling point per lake; occasionally, several sampling points per lake on multibasin, large lakes). Note: This data set was updated in 2013 to include multi-depth and additional surface data for a large subset of lakes. These additions expanded the number of sites from 605 to 663, and expanded the date range from 1925-1942 to 1900-1943 . Furthermore, 14 lakes in Minnesota were added to the data set contributing additional surface and multi-depth data. Another dataset was added in 2013 collected by Wisconsin limnologists Chauncey Juday and Edward Birge, this data set contains variables that are still commonly used in research. For example, temperature, dissolved carbon dioxide, color, pH, secchi disk, plankton, and silica. However, the data set also includes variables that are not commonly used, for example, crude protein, non-amino nitrogen, ether extract, and total organic and inorganic material. These data are characteristic of water chemistry analysis from the time in which they were compiled (5/31/1915 - 8/29/1938). The data set features data from 586 different lakes, primarily lakes in the Northern Highland Lakes District of Wisconsin. However, there is also data from lakes in southeastern and southcentral Wisconsin. Furthermore, there is a minimal amount of data from lakes in Minnesota, Ohio,New York, Alaska, the Philippines, and the United Kingdom. Documentation:Birge, E.A., and Juday, C. 1922. The inland lakes of Wisconsin. The Plankton I. Its quantity and chemical composition. Bulletin, Wis. Geol. and Nat. Hist. Survey No. 64: (Scientific series 13), ix-222.
Core Areas
Dataset ID
106
Date Range
-
Maintenance
completed
Metadata Provider
Methods
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).Wisconsin DNR Technical Report.Methods not included in Johnson (1984):Nitrite Nitrogen- Sulphanilic acid procedure. Standard methods for the examination of water and sewage, Pub. Health Assn., New York, 5th edition, 1923, 13. Other Documentation: Domogalla, B.P., Juday, C., and Peterson, W.H. 1925. The forms of nitrogen found in certain lake waters. Jour. Biol. Chem. 63: 269-285.Ferric Ion- First calculated by subtracting ferrous ion from total iron measurements. Standard methods of water analysis. 1936. Amer. Pub. Health Assoc. P. 309. New York. Procedure was modified to determine ferric ion by acidifying samples by adding 1 milliliter of 3 N HCL to 50mL of lake water. With the iron samples in readiness, add 5 ml of the thiocyanate solution to the sample and to the standards, mix and compare immediately. (Standard Methods, Amer. Public Health Assoc. 8th ed., p. 75, 1936). Other documentation: Domogalla, B.P., Juday, C., and Peterson, W.H. 1925. The forms of nitrogen found in certain lake waters. Jour. Biol. Chem. 63: 269-285.Ferrous Ion- First calculated by ferricyanide method. Procedure was modified to determine ferrous ion by subtracting ferric ion from total iron. Documentation: Domogalla, B.P., Juday, C., and Peterson, W.H. 1925. The forms of nitrogen found in certain lake waters. Jour. Biol. Chem. 63: 269-285.Manganese- Determined by the persulfate method using the procedure described in Standard Methods of Water Analysis, Amer. Public Health Assoc., p. 84, 1936.Chlorophyll-a- A photometric method was used, in which the color of the light was confined to the wave-length 6200-6800 A which are absorbed by chlorophyll. Water samples of 5 to 15 liters (18 liters in the case of very low plankton content) were taken from different depths by using a hand operated vacuum pump), the water was the centrifuged at 25,000 rpm (for about 30 minutes). Residue was then washed with 98percent acetone, and CaCO3 was added to neutralize organic acids. This residue-acetone mixture was ground to extract the chlorophyll. The acetone extract was then filtered through filter paper into a flask, the residue being thoroughly washed with pure acetone. The light absorption of the extract was then measured. Procedure was carried out in a single day, under minimal light. Documentation: Kemmerer, G.I., and Hallett, L.T. 1938. Amount and distribution of the chlorophyll in some lakes of northeastern Wisconsin. Trans. Wisconsin Acad. Sci. 31: 411-438.Phosphate- Ceruleomolybdic method employed. Documentation: Juday, C., Birge, E.A., Kemmerer, G.I., Robinson, R.J. 1927. Phosphorus content of lake waters of northeastern Wisconsin. Trans. Wisconsin. Acad. Sci. 23: 233-248. Other Documentation: Robinson, R.J., Kemmerer, G.I. 1930. Determination of organic phosphorus in lake waters. Trans. Wisconsin. Acad. Sci. 25: 117-121.Redox Potential- Determined in situ on a given sampling date by use of a bright platinum electrode. Eh readings were made in millivolts. Documentation: Allgeier, R.J., Hafford, B.C., and Juday, C. 1941. Oxidation-reduction potentials and pH of lake waters and lake sediments. Trans. Wisconsin Acad. Sci. 33: 115-133.Note: The methodology used to determine copper, alumnium, boron, and hydrogen sulfide could not be determined.
Short Name
RGBIJD
Version Number
7

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
4

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
6
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