US Long-Term Ecological Research Network

North Temperate Lakes LTER: Chemical Limnology of Primary Study Lakes: Major Ions 1981 - current

Abstract
Parameters characterizing the major ions of the eleven primary lakes (Allequash, Big Muskellunge, Crystal, Sparkling, Trout, bog 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 chloride, sulfate, calcium, magnesium, sodium, potassium, iron, manganese, and specific conductance (northern lakes only). Sampling Frequency: quarterly (winter, spring and fall mixis, and summer stratified periods) Number of sites: 11
Core Areas
Dataset ID
2
Date Range
-
Maintenance
ongoing
Metadata Provider
Methods
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.
Short Name
NTLCH02
Version Number
34

North Temperate Lakes LTER: High Frequency CO2 and YSI AutoProfiler Data - Sparkling Bog North Buoy 2008

Abstract
The instrumented buoy on Sparkling Bog North is equipped with a CO2 monitor and a YSI AutoProfiler that measures several parameters including dissolved oxygen, water temperature, conductivity, pH, ORP, turbulence and chlorophyll-a. The buoy is also equipped with a thermistor chain and a D-OPTO dissolved oxygen sensor at depth .5 m as well as meteorological sensors that provide fundamental information on lake thermal structure, weather conditions, and lake metabolism. Data are usually collected either at 1 minute or 10 minute intervals. Sampling Frequency: varies for instantaneous sample. Generally 1 minute or 10 minutes. Number of sites: 1
Core Areas
Dataset ID
229
Date Range
-
Instrumentation
<p>YSI AutoProfiler</p>
Maintenance
completed
Metadata Provider
Methods
see abstract for methods description.
Short Name
NSPBBUOY3
Version Number
19

Little Rock Lake Experiment at North Temperate Lakes LTER: Physical Limnology 1983 - 2000

Abstract
The Little Rock Acidification Experiment was a joint project involving the USEPA (Duluth Lab), University of Minnesota-Twin Cities, University of Wisconsin-Superior, University of Wisconsin-Madison, and the Wisconsin Department of Natural Resources. Little Rock Lake is a bi-lobed lake in Vilas County, Wisconsin, USA. In 1983 the lake was divided in half by an impermeable curtain and from 1984-1989 the northern basin of the lake was acidified with sulfuric acid in three two-year stages. The target pHs for 1984-5, 1986-7, and 1988-9 were 5.7, 5.2, and 4.7, respectively. Starting in 1990 the lake was allowed to recover naturally with the curtain still in place. Data were collected through 2000. The main objective was to understand the population, community, and ecosystem responses to whole-lake acidification. Funding for this project was provided by the USEPA and NSF. Parameters characterizing the physical limnology of the treatment (north basin, stations 1 and 3) and reference basin (south basin, station 2 and 4) are usually measured at one station in the deepest part of each basin (stations 1 and 2) at 0.5 to 1-m depth intervals depending on the parameter. Parameters measured at depth include water temperature, vertical penetration of photosynthetically active radiation (PAR), dissolved oxygen, chlorophyll and phaeopigments. Additional derived parameters include fraction of surface PAR at each depth and percent oxygen saturation. Auxiliary data include time of day, air temperature, cloud cover, and wind speed and direction and secchi depth. Sampling Frequency: varies - Number of sites: 4
Core Areas
Dataset ID
248
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Reading Temperature and Dissolved Oxygen1. Before leaving to sample a lake, check to make sure that there are no air bubbles under the probe membrane of the YSI TemperatureorDissolved Oxygen meter. If there are air bubbles or if it has been several months since changing the membrane (or if the instrument does not calibrate well or the oxygen readings wander), change the membrane as explained in the manual. Note: We have always used the Standard membranes. If adding water to new membrane fluid bottle (KCl), make sure to add Milli-Q water and not the CFL distilled water.2. Be sure to always store the probe in 100percent humidity surrounded by a wet sponge or paper towel.3. Turn on the temperatureordissolved oxygen meter at least 30 minutes before using it. It is best to turn it on before leaving to sample a lake as it uses up batteries slowly.4. Calibrate the meter using the chart on the back of the instrument (adjusted to the Madison altitude - 97percent oxygen saturation). Leave the plastic cap on the probe (at 100percent humidity). The temperature should not be changing during the calibration. Zero the instrument. When the temperature equilibrates, adjust the oxygen to correspond to the chart. After calibrating the instrument, switch the knob to percent oxygen saturation to make sure it is close to 97percent.5. Take readings at 1 meter intervals making sure to gently jiggle the cord when taking the oxygen readings (to avoid oxygen depletion). Jiggling the cord is not necessary if using a cable with a stirrer. Take half meter readings in the metalimnion (when temperature andoror oxygen readings exhibit a greater change with depth). A change of temperature greater than 1degreeC warrants half-meter intervals.6. Record the bottom depth using the markings on the temp.oroxygen meter cord and take a temperature and dissolved oxygen reading with the probe lying on the lake bottom. Dont forget to jiggle the probe to remove any sediment.7. If any readings seem suspicious, check them again when bringing the probe back up to the surface. You can also double check the calibration after bringing the probe out of the water (and putting the cap back on). Light (PAR) extinction coefficient is calculated by linearly regressing ln (FRLIGHT (z)) on depth z where the intercept is not constrained. FRLIGHT(z) = LIGHT(z) or DECK(z) where LIGHT(z) is light measured at depth z and DECK(z) is light measured on deck (above water) at the same time.For open water light profiles, the surface light measurement (depth z = 0) is excluded from the regression.For winter light profiles taken beneath the ice, the first light data are taken at the bottom of the ice cover and are included in the regression. The depth of uppermost light value is equal to the depth of the ice adjusted by the water level in the sample hole, i.e., the depth below the surface of the water. The water level can be at, above or below the surface of the ice. If the water level was not recorded, it is assumed to be 0.0 and the calculated light extinction coefficient is flagged. If ice thickness was not recorded, a light extinction coefficient is not calculated.For light data collected prior to March, 2007, light values less than 3.0 (micromolesPerMeterSquaredPerSec) are excluded. For light data collected starting in March 2007, light values less than 1.0 (micromolesPerMeterSquaredPerSec) are excluded. Except for bog lakes before August 1989, a light extinction coefficient is not calculated if there are less than three FRLIGHT values to be regressed. For bog lakes before August 1989, a light extinction coefficient is calculated if there are least two FRLIGHT values to be regressed. In these cases, the light extinction coefficient is flagged as non-standard.FRLIGHT values should be monotonically decreasing with depth. For light profiles where this is not true, a light extinction coefficient is not calculated.For samples for which light data at depth are present, but the corresponding deck light are missing, a light extinction coefficient is calculated by regressing ln (LIGHT (z)) on depth z. Note that if actual deck light had remained constant during the recording of the light profile, the resulting light extinction coefficient is the same as from regressing ln(FRLIGHT(z)). In these cases, the light extinction coefficient is flagged as non-standard.
Short Name
LRPHYS1
Version Number
4

Landscape Position Project at North Temperate Lakes LTER: Vertical Lake Profiles 1998 - 1999

Abstract
Parameters characterizing the chemical limnology and spatial attributes of 45 lakes were surveyed as part of the Landscape Position Project. Parameters are measured at or close to the deepest part of the lake. A vertical profile of temperature, dissolved oxygen, and conductivity are collected at 1 meter increments Sampling Frequency: generally monthly for one summer; for some lakes, one or two samples in one summer Number of sites: 45
Dataset ID
95
Date Range
-
Maintenance
completed
Metadata Provider
Methods
We sample at the deepest part of the lake, taking a temperature and oxygen profile at meter intervals from the surface to within 1 meter of the bottom using a YSI Pro-ODO temp/DO meter.
Short Name
LPPPROF1
Version Number
8

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

Allequash Creek sonde measurements summer 2006

Abstract
A sonde was used to measure conductivity, do, oxygen saturation, water temperature, pH, and oxidation-reduction potential. Sampling took place in Allequash creek above and below a bog and close to the lake. Sampling Frequency: 15 minutes Number of sites: 3
Core Areas
Dataset ID
253
Data Sources
Date Range
-
Maintenance
completed
Metadata Provider
Methods
see abstract for methods used.
Short Name
LOTTIG1
Version Number
28

Zooplankton of Small Lakes and Wetland Ponds in Wisconsin - North Temperate Lakes LTER 1996

Abstract
We sampled zooplankton communities from 54 small water bodies distributed throughout Wisconsin to evaluate whether a snap-shot of zooplankton community structure during early spring could be used for the purpose of differentiating lakes from wetlands. We collected a single set of zooplankton and water chemistry data during a one-month time window (synchronized from south to north across the state) from an open water site in each basin as a means to minimize and standardize sampling effort and to minimize cascading effects arising from predator-prey interactions with resident and immigrant aquatic insect communities. We identified 53 taxa of zooplankton from 54 sites sampled across Wisconsin. There was an average of 6.83 taxa per site. The zooplankton species were distributed with a great deal of independence. We did not detect significant correlations between number of taxa and geographic region or waterbody size. There was a significant inverse correlation between number of taxa and the concentration of calcium ion, alkalinity and conductivity. One pair of taxa, Lynceus brachyurus and Chaoborus americanus, showed a significant difference in average duration of sites of their respective occurrence. All other pairs of taxa had no significant difference in average latitude, waterbody surface area, total phosphorus, total Kjeldahl nitrogen, alkalinity, conductivity, calcium ion, sulfate, nitrate, silicate or chloride. Taxa were distributed at random among the sites - there were no statistically significant pairs of taxa occurring together or avoiding each other. Multivariate analysis of zooplankton associations showed no evidence of distinct associations that could be used to distinguish lakes from wetlands. Zooplankton community structure appears to be a poor tool for distinguishing between lakes and wetlands, especially at the relatively large scale of Wisconsin (dimension of about 500 km). The data suggest that a small body of water in Wisconsin could be classified as a wetland if it persists in the spring and summer for only about 4 months, and if it is inhabited by Lynceus brachyurus, Eubranchipus bundyi, and if Chaoborus americanus and Chydorus brevilabris are absent. Schell, Jeffery M., Carlos J. Santos-Flores, Paula E. Allen, Brian M. Hunker, Scott Kloehn, Aaron Michelson, Richard A. Lillie, and Stanley I. Dodson. 2001. Physical-chemical influences on vernal zooplankton community structure in small lakes and wetlands of Wisconsin, U.S.A. Hydrobiologia 445:37-50 Number of sites: 54
Creator
Dataset ID
224
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Schell, Jeffery M., Carlos J. Santos-Flores, Paula E. Allen, Brian M. Hunker, Scott Kloehn, Aaron Michelson, Richard A. Lillie, and Stanley I. Dodson. 2001. Physical-chemical influences on vernal zooplankton community structure in small lakes and wetlands of Wisconsin, U.S.A. Hydrobiologia 445:37-50
Short Name
DODSON3
Version Number
25

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 &quot;cross-lake comparison&quot; 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
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