US Long-Term Ecological Research Network

LAGOS - Lake nitrogen, phosphorus, and stoichiometry data and geospatial data for lakes in a 17-state region of the U.S.

Abstract
This dataset includes information about total nitrogen (TN) concentrations, total phosphorus (TP) concentrations, TN:TP stoichiometry, and 12 driver variables that might predict nutrient concentrations and ratios. All observed values came from LAGOSLIMNO v. 1.054.1 and LAGOSGEO v. 1.03 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS contains a complete census of lakes great than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 54 different sources of data were compiled for this dataset and were mostly generated by government agencies (state, federal, tribal) and universities. Here, we compiled chemistry data from lakes with concurrent observations of TN and TP from the summer stratified season (June 15-September 15) in the most recent 10 years of data included in LAGOSLIMNO v. 1.054.1 (2002-2011). We report the median TN, TP and molar TN:TP values for each lake, which was calculated as the grand median of each yearly median value. We also include data for lake and landscape characteristics that might be important controls on lake nutrients, including: land use (agricultural, pasture, row crop, urban, forest), nitrogen deposition, temperature, precipitation, hydrology (baseflow), maximum depth, and the ratio of lake area to watershed area, which is used to approximate residence time. These data were used to identify drivers of lake nutrient stoichiometry at sub-continental and regional scales (Collins et al, submitted). This research was supported by the NSF Macrosystems Biology program (awards EF-1065786 and EF-1065818) and by the NSF Postdoctoral Research Fellowship in Biology (DBI-1401954).
Dataset ID
332
Methods
See Soranno, P.A., Bissell, E.G., Cheruvelil, K.S., Christel, S.T., Collins, S.M., Fergus, C.E., Filstrup, C.T., Lapierre, J.F., Lottig, N.R., Oliver, S.K., Scott, C.E., Smith, N.J., Stopyak, S., Yuan, S., Bremigan, M.T., Downing, J.A., Gries, C., Henry, E.N., Skaff, N.K., Stanley, E.H., Stow, C.A., Tan, P.-N., Wagner, T., and Webster, K.E. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse. Gigascience 4: 28. doi: 10.1186/s13742-015-0067-4 for details on how the observed values were obtained.
See Collins et al. Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales, Submitted to Ecological Applications, for details on data filtering and relationships between nutrient chemistry and landscape characteristics
Version Number
12

Saint Louis River Estuary Water Chemistry, Wisconsin, Minnesota, USA 2012 - 2013

Abstract
These data pertain to water and sediments collected from the Saint Louis River Estuary (SLRE) and its nearby water sources by Luke Loken and collaborators for his Masters thesis and additional publications. In brief, we sampled SLRE surface waters and sediments for a variety of physical, chemical, and biological attributes. Ten estuary stations were sampled approximately monthly from April 2012 through September 2013. On four of the sampling campaigns, water was collected from an additional 20 sites. Sites were selected to represent a gradient from the Saint Louis River to Lake Superior and included several tributaries that drain directly into the estuary. This design aimed to understand the spatial and temporal mixing pattern of the estuary as it receives water from several rivers, 2 waste water treatment plant, and Lake Superior. We sampled the estuary to assess the magnitude and timing of source water contributions to the estuary and establish a baseline of chemical and physical measurements to aid in future limnological research. Additionally, we performed nitrogen and carbon cycling rate experiments to determine the estuary-wide influence on nitrate, ammonium, and dissolved organic carbon. This included 8 sediment denitrification, 1 nitrification, and 2 breakdown dissolved organic carbon (BDOD) surveys. This work was funded by the Minnesota and Wisconsin Sea Grant and in coordination with the establishment of the Lake Superior National Estuary Research Reserve (LSNERR).
Contact
Dataset ID
322
Date Range
-
DOI
10.6073/pasta/08fdc0fb8528e37dd7ef6d6ad2b77f99
Maintenance
completed
Metadata Provider
Methods
We collected water samples from 10 estuary stations to represent a gradient from river to lake on 13 dates between April 2012 and September 2013. Stations 1-5 represented upper estuary sites, while stations 6-10 were lower. Stations were situated near the thalweg, but were shifted laterally to avoid traffic within the shipping channel. Sampling occurred approximately monthly during the open water season when sites were accessed by boat, and once during winter ice cover when a subset of sites were visited on foot. In addition to the core 10 stations, we sampled an additional 20 sites, four times over the two-year study during a high flow and baseflow period. These sites include 7 end members (Saint Louis River, Nemadji River, Bluff Creek, Kinsbury Creek, Pokegama River, and Lake Superior) and an additional 15 in-estuary sites (i.e., stations 16-30). Additional sites were occasionally visited and geographic locations to all stations are provided in SLRESitesTable.Physical LimnologyWe used a YSI EXO2 or 6-Series sonde (Yellow Springs, OH) to measure temperature, specific conductivity, dissolved oxygen, pH, turbidity, and algae fluorescence. Briefly, the sonde was lowered to appr. 0.5 m depth and allowed to stabilize. The sonde was calibrated in the lab that morning according to Lake Superior National Estuary Research Reserve (LSNERR) protocols.Light extinction was determined by lowering a photosynthetically active radiation (PAR) sensor (Licor model 192 or 193) attached to a light meter (Licor model 250A) through the water column. The sensor was allowed to stabilize at 0.25 m depth intervals. We linearly regressed the natural log of the measured light intensity against depth. The slope of this regression is the negative light extinction coefficient (k). Briefly k values closer to zero indicate clearer waters that transit more light.Water ChemistrySurface water from each station was collected into an HDPE carboy and processed in the lab within 10 h of collection. We processed samples in the lab (instead of on the boat) to expedite sample collection so that all stations could be visited within a single day (or within 2 days for spatial intensive surveys). Integrated water samples were taken from 0-2 m using a peristaltic pump or an integrated water sampler and stored in a cooler to maintain ambient temperature. Samples for dissolved solute analysis were filtered through a 0.45 microm Geotech capsule filter. All samples were refrigerated, frozen, or acidified (dependent on the analysis in question) within 12 h of collection. See meta data for SLREWaterChemTable for specifics regarding lab responsible for analyses.Samples for major cations (Calcium (Ca), Iron (Fe), Potassium (K), Sodium (Na), Magnesium (Mg), and Manganese (Mn)) were filtered upon collection into 60 mL acid-washed HDPE bottles, acidified to 1 percent ultrapure hydrochloric acid (HCl) and stored at room temperature until analysis (within 6 months). Cations were analyzed simultaneously on an optical inductively-coupled plasma emission on a Perkin-Elmer model 4300 DV ICP spectrophotometer according to methods outlined at the North Temperate Lakes- Long Term Ecological Research site.Samples for major anions (Chloride (Cl) and sulfate (SO4)) were filtered into a new 20 mL HDPE scintillation vials and stored at 4degree C until analysis (within 3 months). Anion samples were analyzed simultaneously by Ion Chromatography, using a hydroxide eluent determined by a Dionex model ICS 2100 using an electro-chemical suppressor.Samples for dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) were analyzed on a Shimadzu TOC analyzer. DOC and DIC samples were filtered into acid-washed 24 mL glass vials and capped with septa, leaving no headspace. DOC samples were acidified with 100 microL of 2 M HCL upon collection. Both DOC and DIC were stored at 4 degreeC, and then analyzed within three weeks at the University of Minnesota-Twin Cities. Both DOC and DIC were collected in duplicate and reported as means.Samples for UV absorbance were filtered into ashed 40 mL glass amber vials and stored at 4degree C until analysis (within 2 months). We measured UV absorbance at 254 nm (Abs254) using a spectrophotometer (Cary 50 UV-Vis Spectrophotometer, Varian, Palo Alto, CA). Specific UV absorbance at 254 nm (SUVA254) was then calculated by dividing Abs254 by the DOC concentration of the water sample.Nitrate plus nitrite nitrogen (referred to as NO3-N), ammonium plus ammonia nitrogen (referred to as NH4-N), and soluble reactive phosphorus (SRP) were analyzed colormetrically. Samples were filtered into new 20 mL plastic scintillation vials and frozen within 8 h of collection. Samples were thawed within 4 months and were analyzed in parallel by automated colorimetric spectrophotometry, using an Astoria-Pacific Astoria II segmented flow autoanalyzer. NO3-N was determined using the automated cadmium reduction method with absorption monitored at lambda=520 nm. NH4-N was determined using the Berthelot Reaction, producing a blue colored indophenol compound, where the absorption was monitored at lambda=660 nm. SRP was determined by forming a phosphoantimonymoledbeun complex and was measured as lambda=880nm.Samples for total and dissolved nitrogen and phosphorus analysis were collected together and in-line filtered (dissolved nitrogen and phosphorus only) into 60 ml LDPE bottles and acidified to a 1 percent HCl. Once acidified, the samples were stored at room temperature until analysis, which occurred within one year. The samples were first prepared for analysis by adding a NaOH–Persulfate digestion reagent and heated for 1 h at 120 degreeC and 18-20 pounds per square inch (psi) in an autoclave. The samples were 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 where the absorption is monitored at 520 nm; total phosphorus is determined using ascorbic acid-molybdate method where the absorption is monitored at 880 nm. Both are described in LTER standard methods.We determined dual isotopic natural abundance of nitrate (NO3) and water (H2O) from a subset of collected water samples. Samples for delta18O-NO3 and delta15N-NO3 were filtered into acid-washed 60 mL HDPE bottles and frozen within 8 h of collection. Nitrate isotope samples were analyzed using the denitrifier method at the Colorado Plateau Stable Isotope Laboratory. delta18O-NO3 and delta15N-NO3 isotopes were reported as the per mil (per-mille) deviation from Vienna Standard Mean Ocean Water (VSMOW) and air standards, respectively. Samples for isotopes of water (delta18O-H2O and delta2H-H2O) were collected without headspace in glass vials and measured using isotope ratio infrared spectroscopy at the University of Minnesota – Biometeorology lab. Six replicates were run per sample, and delta18O-H2O and delta2H-H2O were determined relative to VSMOW.Chlorophyll ALaboratory analysis of chlorophyll A (ChlA) uses the Turner Designs model 10-AU fluorometer, following improvements described in Welschmeyer (1994). In this method, ChlA in 90percent acetone is separated from other pigments by the use of specialized optical filters. ChlA samples were preserved within 24 h of water sampling, by collecting filtrand on a 0.2 microm cellulose nitrate filter, placing the filter in a 15 mL falcon tube, and freezing it. Between 200 and 1000 mL of sample was based through the filter until the filter was moderately stained and filtering speed slowed. Within three weeks of collection, filters were thawed, and 12.0 mL of acetone was added to tube, which was allowed to steep for 18-24 h in the dark at 4 degreeC. After steeping, samples were centrifuged at high speed in Sorvall GLC-2B centrifuge for 20 min and warmed to room temperature. Sample fluorescence was then measured on a calibrated Turner Designs model 10-AU fluorometer (excitation 436 nm, emission 680 nm). Sample fluorescence was then converted to a water column concentration by multiplying by the extract volume (i.e., 12 mL) and divided by the volume of water that passed through the filter (i.e., 200-1000 mL).ParticulatesSimilar to ChlA, particulate carbon, nitrogen, and phosphorus samples were collected by passing 200-1000 mL of water through a pre-combusted 0.7 glass fiber filter (GFF) and analyzing the filtrand. Filters were frozen immediately after filtration, and then dried at 60 degreeC for at least 48 hours. Particulate carbon and nitrogen was measured using a Thermo Fisher Flash 2000 elemental analyzer. Particulate phosphorus was determined from a separate filter. Filters were digested in 5 mL potassium persulfate and phosphorus was analyzed spectrophotometrically using the ascorbic acid-molybdate method (Menzel and Corwin 1965).NitrificationWater column nitrification rates were determined on 30 July 2013 for a subset of the water chemistry sampling stations (n = 15) that represented the full spatial extent and previously observed NH4-N range of the estuary. Water from each station was transferred to 333 mL polycarbonate bottles within 10 h of collection and spiked with 15NH4Cl to achieve a concentration of 0.03 micromol 15NH4 L-1. Samples were incubated at ambient temperature (20 degreeC ) in a dark cooler for 20 h. Pre- and post-incubation samples were filtered through 0.45 microm filters and analyzed for NO3-N, NH4-N and delta15N-NO3. Nitrification rates were determined based on changes in NO3-N, NH4-N, and delta15N-NO3 according to methods outlined in Small et al. (2013). Analysis for each station was performed in duplicate and reported as the mean.SedimentsSediments were collected on 8 of the water chemistry survey dates from stations 2-9 to determine spatial and temporal patterns of denitrification and sediment organic content. We also collected a single sediment sample from additional lower (n = 17) and upper (n = 6) stations on 19 June 2012 and 24 June 2013, respectively, to increase the spatial extent of our survey. In total, 56 and 42 individual sediment collections were made in 2012 and 2013, respectively. Sediments were collected from the upper 5-20 cm of the benthic zone using an Ekman dredge. At least 500 mL of benthic material was transferred to 1-L widemouth Nalgene containers and used in denitrification rate experiments. Fifteen mL of the uppermost sediment layer was transferred into sterile 100 mL disposable plastic screw-top containers to be analyzed for sediment composition content. Sediments were stored in a cooler while on the boat and transferred to 4 degreeC within 6 h.To assess the effects of sediment composition on denitrification, dry:wet ratios, bulk density, particle size distributions, loss-on-ignition (LOI), percent carbon, and percent nitrogen were determined from the 15 mL sediment subsamples. Sediments were weighed before and after drying at 60 degreeC for at least 48 h to determine dry:wet ratios and bulk density. Sediment particle size composition was determined optically using a Coulter LS-10 particle size analyzer and sizes were binned into percent clay (0-2.0 microm), silt (2.0-63.0 microm) and sand (63-2000 microm) (Scheldrick and Wang 1993). LOI was determined by the loss in mass of 2.0plus/-0.2 g dried homogenized sediment combusted at 550 degree Celsius for 4 h. Sediments were ground and analyzed for percent carbon and nitrogen using a Thermo Fisher Flash 2000 elemental analyzer.Sediment denitrificationWe determined actual (DeN) and potential (DEA) sediment denitrification rates in the laboratory using the acetylene block technique modified from Groffman et al. (1999) within 48 h of collection. We incubated 40±2 g of wet sediment saturated with 40±0.1 mL of estuary water in 125 mL glass Wheaton bottles at 20 degreeC. DEA incubations were spiked with glucose and NO3-N to a final concentration of 40 mg C L-1 and 100 mg N L-1, respectively; DeN incubations were given no amendments. All incubations were augmented with 10 mg L-1 chloramphenicol to inhibit microbial proliferation (Smith and Tiedje 1979). Samples were capped with rubber septa, flushed with helium (He) for 5 min to remove oxygen (O2), and injected with 10 mL acetylene. We allowed the acetylene 30 min to fully diffuse into the sediment slurry before taking the initial headspace sample (T0). Samples were placed on a shaker table in the dark for 2.6 h then sampled the final headspace (T1). The change in headspace N2O partial pressures (pN2Ofinal - pN2Oinitial) was used to determine the denitrification rate using the Bunsen correction and the ideal gas law. For both T0 and T1 samples, 10 mL of headspace was withdrawn from incubation bottles and injected into a He-flushed 12 mL gas-tight glass vials (Exetainers) sealed with rubber septa. We determined pN2O and pO2 in parallel on a gas chromatograph equipped with an electron capture detector (ECD) and thermal conductivity detector (TCD) using methods outlined in Spokas et al. (2005). Gas samples with O2 concentrations greater than 5percent were removed from analysis due to potential gas leakage. Denitrification rates were standardized to sediment dry mass. Samples collected on or before 6 June 2013 were incubated in triplicate; samples collected after were incubated in duplicate.Denitrification controls were further investigated by amending sediments with combinations of NO3-N and two types of organic carbon: glucose and natural organic matter (NOM; supplied by the International Humic Substance Society). On two dates in 2013, we incubated sediments from five of our core stations that spanned a gradient of sediment organic content with the following amendments: NO3-N only, NO3-N and glucose (DEA), NO3-N and NOM, glucose only, NOM only, and no amendments (DeN). The two carbon treatments were intended to test for possible effects of carbon quality, with NOM representing a recalcitrant, humic-rich carbon source similar to allochthonous materials in the SLRE to contrast the labile glucose treatment. Both carbon sources were amended to 40 mg C L-1, and NO3-N was amended to 100 mg N L-1. Sediments were incubated in parallel (see above).Breakdown Dissolved Organic Carbon (bDOC)Breakdown of DOC (bDOC) was determined from core stations (1-10) from water collected on 23 April and 30 July 2012. Briefly, 250 mL of estuary water was filtered through a 0.45 microM Geotech flow-through filter using a peristaltic pump into sealable glass jars. 25 mL of 2.0 microm filtered water from a common estuary source was added to the filtered jars. DOC samples were collected after 0, 1, 2, 4 ,8, 16, and 32 d and analyzed for DOC (see above). A linear model was fit between time since inoculation and DOC concentration to determine the breakdown of DOC from water column microbes.ReferencesMeyers PA, Teranes JL. 2001. Sediment organic matter. Pages 239-269, In: Track Enviornmental Change Using Lake Sediments Vol 2 Phys Geochemical Methods. Dordrecht: Kluwer Academic Publishers.Groffman, Peter M, Holland EA, Myrold DD, Robertson GP, Zou X. 1999. Denitirification. Pages 272-288 in Standand Soil Methods Long-Term Ecological Research, Oxford University, New York.Menzel DW, Corwin N. 1965. The measurement of total phosphorus in seawater based on the liberation of organically bound fractions by persulfate oxidation. Limnol and Oceanogr 10: 280–282.Scheldrick HB, Wang C. 1993. Particle size distribution. Pages 499-512 In: Soil Sampling and Methods of Analysis. Boca Raton: CRC Press LLC.Small GE, Bullerjahn GS, Sterner RW, Beall BFN, Brovold S, Finlay JC, McKay RML, Mukherjee M. 2013. Rates and controls of nitrification in a large oligotrophic lake. Limnol Oceanogr. 58:276–86.Smith MS, Tiedje JM (1979) Phases of denitrification following oxygen depletion in soil. Soil Biol Biochem 11:261-267Spokas K, Wang D, Venterea R. 2005. Greenhouse gas production and emission from a forest nursery soil following fumigation with chloropicrin and methyl isothiocyanate. Soil Biol Biochem. 37:475–85.Welschmeyer, N.A. 1994. Fluorometric analysis of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnol Oceanogr 39:1985-1992. 
Version Number
17

A Global database of methane concentrations and atmospheric fluxes for streams and rivers

Abstract
This dataset, referred to as MethDB, is a collation of publicly available values of methane (CH4) concentrations and atmospheric fluxes for world streams and rivers, along with supporting information on location, geographic, physical, and chemical conditions of the study sites. The data set is composed of four linked tables, corresponding to the data sources (Papers_MethDB), the study sites (Sites_MethDB), concentrations (Concentrations_MethDB), and influx/efflux rates (Fluxes_MethDB). Information was extracted from journal articles, government reports, book chapters, and similar sources that were acquired before 15 September 2015. Concentrations and fluxes were converted to a standard unit (micromoles per liter for concentration and millimoles per square meter per day for flux) and both the author-reported and converted data are included in the database. MethDB was assembled as part of a larger synthesis effort on stream and river CH4 dynamics, and assembled data were used to identify large-scale patterns and potential drivers of fluvial CH4 and to generate an updated global-scale estimate of CH4 emissions from world rivers.
Dataset ID
321
Date Range
-
DOI
10.6073/pasta/21f5bd6642e9689baf90262f3c85ac4a
Metadata Provider
Methods
CH4 data from streams and rivers are widely scattered, as values are often included as end-member in studies focused on other processes or types of ecosystems. Thus, while we sought to be as complete as possible in compiling existing data, some sources have undoubtedly been overlooked. Sources included journal articles, book chapters, dissertations, USGS open file reports, meeting proceedings, and unpublished results provided by individual investigators. Data incorporated into MethDB were strictly limited to surface waters of rivers and streams; values for groundwater, porewater, saturated soils, lakes, reservoirs, wetlands, estuaries, and floodplains were not included. Some papers were excluded because essential supporting information was missing (e.g., units), or extracting data from complex graphs was considered to be unwise. Data sources are listed in the Notes and Comments section below.
Version Number
5375866

LTREB Lake Mývatn Midge Emergence 2008-2011

Abstract
Adjacent ecosystems are influenced by organisms that move across boundaries, such as insects with aquatic larval stages and terrestrial adult stages that transport energy and nutrients from water to land. However, the ecosystem-level effect of aquatic insects on land has generally been ignored, perhaps because the organisms themselves are individually small. Between 2008-2011 at the naturally productive Lake Myvatn, Iceland we measured total insect emergence from water using emergence traps suspended in the water column. These traps were placed throughout the south basin of Lake Myvatn and were sampled every 1-3 weeks during the summer months (May-August). The goal of this sampling regime was to estimate total midge emergence from Lake Myvatn, with the ultimate goal of predicting, in conjunction with land-based measurements of midge density (see Lake Myvatn Midge Infall 2008-2011) the amount of midges that are deposited on the shoreline of the lake. Estimates from emergence traps between 2008-2011 indicated a range of 0.15 g dw m-2 yr-1 to 3.7 g dw m-2 yr-1, or a whole-lake emergence of 3.1 Mg dw yr-1 to 76 Mg dw yr-1.
Additional Information
<p>Portions of Abstract and methods edited excerpt from Dreyer et al. <em>in Press</em> which was derived, in part, from these data.</p>
Contact
Dataset ID
305
Date Range
-
Maintenance
Ongoing
Metadata Provider
Methods
I. Study System Lake Mývatn, Iceland (65&deg;36 N, 17&deg;0&prime; W) is a large (38 km<sup>2</sup>) shallow (4 m max depth) lake divided into two large basins that function mostly as independent hydrologic bodies (Ólafsson 1979). The number of non-biting midge (Diptera: Chironomidae) larvae on the lake bottom is high, but variable: midge production between 1972-74 ranged from 14-100 g ash-free dw m<sup>-2</sup> yr<sup>-1</sup>, averaging 28 g dw m<sup>-2</sup> yr<sup>-1</sup> (Lindegaard and Jónasson 1979). The midge assemblage is mostly comprised of two species (&gt; 90% of total individuals), Chironomus islandicus (Kieffer) and Tanytarsus gracilentus (Holmgren) that feed as larvae in the sediment in silken tubes by scraping diatoms, algae, and detritus off the lake bottom (Lindegaard and Jónasson 1979). At maturity (May-August) midge pupae float to the lake surface, emerge as adults, and fly to land, forming large mating swarms around the lake (Einarsson et al. 2004, Gratton et al. 2008). On land, midges are consumed by terrestrial predators (Dreyer et al. 2012, Gratton et al. 2008), or enter the detrital pool upon death (Gratton et al. 2008, Hoekman et al. 2012). Midge populations naturally cycle with 5-8 year periodicity, with abundances fluctuating by 3-4 orders of magnitude (Einarsson et al. 2002, Ives et al. 2008). II. Midge Emergence Measurement We used submerged conical traps to estimate midge emergence from Lake Mývatn. Traps were constructed of 2 mm clear polycarbonate plastic (Laird Plastics, Madison, WI) formed into a cone with large-diameter opening of 46 cm (0.17 m<sup>2</sup>). The tops of the cones were open to a diameter of 10 cm, with a clear jar affixed at the apex. The trap was weighted to approximately neutral buoyancy, with the jar at the top containing air to allow mature midges to emerge. Traps were suspended with a nylon line ~1 m below the surface of the lake from an anchored buoy. For sampling, traps were raised to the surface and rapidly inverted, preventing midges from escaping. Jars and traps were thoroughly rinsed with lake water to collect all trapped midges, including unmetamorphosed larvae and pupae, and scrubbed before being returned to the lake to prevent growth of epiphytic algae and colonization by midges. We assume that the emergence traps collect all potentially emerging midges from the sampling area, though it is likely an underestimate, since some midges initially captured could fall out of the trap. Thus, our results should be considered a conservative estimate of potential midge emergence from the surface of the lake.We sampled midge emergence throughout the south basin of Lake Mývatn. Emergence was sampled at six sites in 2008 and 2011 and ten sites in 2009 and 2010, with locations relocated using GPS and natural sightlines. Each site had two traps within 5 m of each other that were monitored during midge activity, approximately from the last week of May to the first week of August. Midge emergence outside of this time frame is extremely low (Lindegaard &amp; Jónasson 1979) and we assume it to be zero. Traps were checked weekly during periods of high emergence (initial and final 2-3 weeks of the study), and bi-weekly during low emergence periods in the middle of the study (July). III. Identification, Counts, and Conversions Midges were counted and identified to morphospecies, small and large. The midge (Diptera,Chrionomidae) assemblage at Mývatn is dominated by two species, Chironomus islandicus (Kieffer)(large, 1.1 mg dw) and Tanytarsus gracilentus (Holmgren)(small, 0.1 mg dw), together comprising 90 percent of total midge abundance (Lindegaard and Jonasson 1979). First, the midges collected in the infall traps were spread out in trays, and counted if there were only a few. Some midges were only identified to the family level of Simuliidae, and other arthropods were counted and categorized as the group, others. Arthropods only identified to the family level Simuliidae or classified as others were not dually counted as Chironomus islandicus or Tanytarsus gracilentus . If there were many midges, generally if there were hundreds to thousands, in an infall trap, subsamples were taken. Subsampling was done using plastic rings that were dropped into the tray. The rings were relatively small compared to the tray, about 2 percent of the area of a tray was represented in a ring. The area inside a ring and the total area of the trays were also measured. Note that different sized rings and trays were used in subsample analysis. These are as follows, trays, small (area of 731 square centimeters), &ldquo;large1&rdquo; (area of 1862.40 square centimeters), and large2 (area of 1247 square centimeters). Rings, standard ring (diameter of 7.30 centimeters, subsample area is 41.85 square centimeters) and small ring (diameter of 6.5 centimeters, subsample area is 33.18 square centimeters). A small ring was only used to subsample trays classified as type &ldquo;large2.&rdquo;The fraction subsampled was then calculated depending on the size of the tray and ring used for the subsample analysis. If the entire tray was counted and no subsampling was done then the fraction subsampled was assigned a value of 1.0. If subsampling was done the fraction subsampled was calculated as the number of subsamples taken multiplied by the fraction of the tray that a subsample ring area covers (number of subsamples multiplied by (ring area divided by tray area)). Note that this is dependent on the tray and ring used for subsample analysis. Finally, the number of midges in an infall trap accounting for subsampling was calculated as the raw count of midges divided by the fraction subsampled (raw count divided by fraction subsampled).Other metrics such as total insects in meters squared per day, and total insect biomass in grams per meter squared day can be calculated with these data. In addition to the estimated average individual midge masses in grams, For 2008 through 2010 average midge masses were calculated as, Tanytarsus equal to .0001104 grams, Chironomus equal to .0010837 grams. For 2011 average midge masses were, Tanytarsus equal to .000182 grams, Chironomus equal to .001268 grams.
Version Number
13

LTREB Biological Limnology at Lake Myvatn 2012-current

Abstract
These data are part of a long-term monitoring program in the central part of Myvatn that represents the dominant habitat, with benthos consisting of diatomaceous ooze. The program was designed to characterize import benthis and pelagic variables across years as midge populations varied in abundance. Starting in 2012 samples were taken at roughly weekly inervals during June, July, and August, which corresponds to the summer generation of the dominant midge,<em>Tanytarsus gracilentus</em>.
Creator
Dataset ID
296
Date Range
-
Maintenance
Ongoing
Metadata Provider
Methods
Benthic Chlorophyll Field sampling (5 samples) (2012, 2013)1. Take 5 cores from the lake2. Cut the first 0.75 cm (1 chip) of the core with the extruder and place in deli container. Label with date and core number.3. Place deli containers into opaque container (cooler) and return to lab. This is the same sample that is used for the organic matter analysis.In 2014, the method for sampling benthic chlorophyll changed. The calculation of chlorophyll was changed to reflect the different area sampled. Below is the pertinent section from the methods protocols. Processing after the collection of the sample was not changed.Take sediment samples from the 5 cores collected for sediment characteristics. Take 4 syringes of sediment with 10mL syringe (15.96mm diameter). Take 4-5cm of sediment. Then, remove bottom 2cm and place top 2cm in the film canister.Filtering1. Measure volume of material in deli container with 60mL syringe and record.2. Homogenize and take 1mL sample with micropipette. The tip on the micropipette should be cut to avoid clogging with diatoms. Place the 1mL sample in a labeled film canister. Freeze sample at negative 20 degrees Celsius unless starting methanol extraction immediately.3. Add 20mL methanol. This methanol can be kept cool in the fridge, although then you will need a second bottle of methanol for the fluorometer. Shake for 5 sec.4. After 6-18 hours, shake container for 5 sec.Fluorometer1. Allow the film canisters to sit at room temperature for approximately 15 min to avoid excessive condensation on the glass tubes. Shake tubes for 5 sec after removing from fridge but then be careful to let them settle before removing sample.2. Record the sample information for all of the film canisters on the data sheet.3. Add 4mL of sample to a 13x100mL glass tube.4. Insert the sample into the fluorometer and record the reading in the Fluor Before Acid column. The sample reading should be close to one of the secondary solid standards (42ug/L or 230ug/L), if not, dilute the sample to within 25 per cent of the secondary solid standards (30-54ug/L or 180-280ug/L). It is a good idea to quickly check 2mL of a sample that is suspected to be too high to get an idea if other samples may need to be diluted. If possible, read the samples undiluted.5. If a sample needs to be diluted, use a 1000 microLiter pipette and add 2mL of methanol to a tube followed by 2mL of undiluted sample. Gently invert the tube twice and clean the bottom with a paper towel before inserting it into the fluorometer. If the sample is still outside of the ranges above, combine 1 mL of undiluted sample with 3 mL of methanol. Be sure to record the dilution information on the data sheet.6. Acidify the sample by adding 120microLiters of 0.1 N HCl (30microLiters for every one mL of sample). Then gently invert the sample and wait 90 seconds (we used 60 seconds in 2012, the protocol said 90) before putting the sample into the fluorometer and recording the reading in the Fluor After Acid column. Be sure to have acid in each tube for exactly the same amount of time. This means doing one tube at a time or spacing them 30-60 seconds apart.7. Double check the results and redo samples, which have suspicious numbers. Make sure that the after-acidification values make sense when compared to the before acidification value (the before acid/after acid ratio should be approximately the same for all samples).Clean up1. Methanol can be disposed of down the drain as long as at least 50 times as much water is flushed.2. Rinse the film canisters and lids well with tap water and scrub them out with a bottle brush making sure to remove any remaining filter paper. Give a final rinse with distilled water. Pelagic Chlorophyll Field sampling (5 samples)1. Take 2 samples at each of three depths, 1, 2, and 3m with Arni&rsquo;s zooplankton trap. For the 1m sample, drop the trap to the top of the chain. Each trap contains about 2.5L of water when full. 2. Empty into bucket by opening the bottom flap with your hand.3. Take bucket to lab.Filtering1. Filter 1L water from integrated water sample (or until the filter is clogged) through the 47 mm GF/F filter. The pressure used during filtering should be low ( less than 5 mm Hg) to prevent cell breakage. Filtering and handling of filters should be performed under dimmed lighting.2. Remove the filter with forceps, fold it in half (pigment side in), and put it in the film canister. Take care to not touch the pigments with the forceps.3. Add 20mL methanol. This methanol can be kept cool in the fridge, although then you will need a second bottle of methanol for the fluorometer. Shake for 5 sec. and place in fridge.4. After 6-18 hours, shake container for 5 sec.5. Analyze sample in fluorometer after 24 hours.Fluorometer1. Allow the film canisters to sit at room temperature for approximately 15 min to avoid excessive condensation on the glass tubes. Shake tubes for 5 sec after removing from fridge but then be careful to let them settle before removing sample.2. Record the sample information for all of the film canisters on the data sheet.3. Add 4mL of sample to a 13x100mL glass tube.4. Insert the sample into the fluorometer and record the reading in the Fluor Before Acid column. The sample reading should be close to one of the secondary solid standards (42ug/L or 230ug/L), if not, dilute the sample to within 25 percent of the secondary solid standards (30-54ug/L or 180-280ug/L). It is a good idea to quickly check 2mL of a sample that is suspected to be too high to get an idea if other samples may need to be diluted. If possible, read the samples undiluted.5. If a sample needs to be diluted, use a 1000uL pipette and add 2mL of methanol to a tube followed by 2mL of undiluted sample. Gently invert the tube twice and clean the bottom with a paper towel before inserting it into the fluorometer. If the sample is still outside of the ranges above, combine 1 mL of undiluted sample with 3 mL of methanol. Be sure to record the dilution information on the data sheet.6. Acidify the sample by adding 120 microLiters of 0.1 N HCl (30 microLiters for every one mL of sample). Then gently invert the sample and wait 90 seconds (we used 60 seconds in 2012, the protocol said 90) before putting the sample into the fluorometer and recording the reading in the Fluor After Acid column. Be sure to have acid in each tube for exactly the same amount of time. This means doing one tube at a time or spacing them 30-60 seconds apart.7. Double check the results and redo samples, which have suspicious numbers. Make sure that the after-acidification values make sense when compared to the before acidification value (the before acid/after acid ratio should be approximately the same for all samples).Clean up1. Methanol can be disposed of down the drain as long as at least 50 times as much water is flushed.2. Rinse the film canisters and lids well with tap water and scrub them out with a bottle brush making sure to remove any remaining filter paper. Give a final rinse with distilled water. Pelagic Zooplankton Counts Field samplingUse Arni&rsquo;s zooplankton trap (modified Schindler) to take 2 samples at each of 1, 2, and 3m (6 total). For the 1m sample, drop the trap to the top of the chain. Each trap contains about 2.5L of water when full. Integrate samples in bucket and bring back to lab for further processing.Sample preparation in lab1. Sieve integrated plankton tows through 63&micro;m mesh and record volume of full sample2. Collect in Nalgene bottles and make total volume to 50mL3. Add 8 drops of lugol to fix zooplankton.4. Label bottle with sample date, benthic or pelagic zooplankton, and total volume sieved. Samples can be stored in the fridge until time of countingCounting1. Remove sample from fridge2. Sieve sample with 63 micro meter mesh over lab sink to remove Lugol&rsquo;s solution (which vaporizes under light)3. Suspend sample in water in sieve and flush from the back with squirt bottle into counting tray4. Homogenize sample with forceps or plastic pipette with tip cut off5. Identify (see zooplankton identification guide) using backlit microscope and count with multiple-tally counter. i. Set magnification so that you can see both top and bottom walls of the tray. ii. Change focus depth to check for floating zooplankton that must be counted as well.6. Pipette sample back into Nalgene bottle, add water to 50mL, add 8 drops Lugol&rsquo;s solution, and return to fridgeSubsamplingIf homogenized original sample contains more than 500 individuals in the first line of counting tray, you may subsample under the following procedure.1. Return original sample to Nalgene bottle and add water to 50mL2. Homogenize sample by swirling Nalgene bottle3. Collect 10mL of zooplankton sample with Hensen-Stempel pipette4. Empty contents of Hensen-Stempel pipette into large Bogorov tray5. Homogenize sample in tray with forceps or plastic pipette with tip cut off6. Identify (see zooplankton identification guide) using backlit microscope and count with multiple-tally counter. i. Set magnification so that you can see both top and bottom walls of the tray. ii. Change focus depth to check for floating zooplankton that must be counted, too! 7. Pipette sample back into Nalgene bottle, add water to 50mL, add 8 drops Lugol&rsquo;s solution, and return to fridge Benthic Microcrustacean Counts Field samplingLeave benthic zooplankton sampler for 24h. Benthic sampler consists of 10 inverted jars with funnel traps in metal grid with 4 feet. Set up on bench using feet (on side) to get a uniform height of the collection jars (lip of jar = 5cm above frame). Upon collection, pull sampler STRAIGHT up, remove jars, homogenize in bucket and bring back to lab. Move the boat slightly to avoid placing sampler directly over cored sediment.Sample preparation in lab1. Sieve integrated samples through 63 micrometer mesh and record volume of full sample2. Collect in Nalgene bottles and make total volume to 50mL3. Add 8 drops of lugol to fix zooplankton.4. Label bottle with sample date, benthic or pelagic zooplankton, and total volume sieved. Samples can be stored in the fridge until time of countingCounting1. Remove sample from fridge2. Sieve sample with 63 micrometer mesh over lab sink to remove Lugol&rsquo;s solution (which vaporizes under light)3. Suspend sample in water in sieve and flush from the back with squirt bottle into counting tray4. Homogenize sample with forceps or plastic pipette with tip cut off5. Identify (see zooplankton identification guide) using backlit microscope and count with multiple-tally counter. i. Set magnification so that you can see both top and bottom walls of the tray. ii. Change focus depth to check for floating zooplankton that must be counted, too!6. Pipette sample back into Nalgene bottle, add water to 50mL, add 8 drops Lugol&rsquo;s solution, and return to fridgeSubsamplingIf homogenized original sample contains more than 500 individuals in the first line of counting tray, you may subsample under the following procedure.1. Return original sample to Nalgene bottle and add water to 50mL2. Homogenize sample by swirling Nalgene bottle3. Collect 10mL of zooplankton sample with Hensen-Stempel pipette4. Empty contents of Hensen-Stempel pipette into large Bogorov tray5. Homogenize sample in tray with forceps or plastic pipette with tip cut off6. Identify (see zooplankton identification guide) using backlit microscope and count with multiple-tally counter. i. Set magnification so that you can see both top and bottom walls of the tray. ii. Change focus depth to check for floating zooplankton that must be counted, too! 7. Pipette sample back into Nalgene bottle, add water to 50mL, add 8 drops Lugol&rsquo;s solution, and return to fridge Chironomid Counts (2012, 2013) For first instar chironomids in top 1.5cm of sediment only (5 samples)1. Use sink hose to sieve sediment through 63 micrometer mesh. You may use moderate pressure to break up tubes.2. Back flush sieve contents into small deli container.3. Return label to deli cup (sticking to underside of lid works well).For later instar chironomids in the section 1.5-11.5cm (5 samples)4. Sieve with 125 micrometer mesh in the field.5. Sieve through 125micrometer mesh again in lab to reduce volume of sample.6. Transfer sample to deli container or pitfall counting tray.For all chironomid samples7. Under dissecting scope, pick through sieved contents for midge larvae. You may have to open tubes with forceps in order to check for larvae inside.8. Remove larvae with forceps while counting, and place into a vial containing 70 percent ethanol. Larvae will eventually be sorted into taxonomic groups (see key). You may sort them into taxonomic groups as you pick the larvae, or you can identify the larvae while measuring head capsules if chironomid densities are low (under 50 individuals per taxanomic group).9. For a random sample of up to 50 individuals of each taxonomic group, measure head capsule, see Chironomid size (head capsule width).10. Archive samples from each sampling date together in a single 20mL glass vial with screw cap in 70 percent ethanol and label with sample contents , Chir, sample date, lake ID, station ID, and number of cores. Chironomid Cound (2014) In 2014, the method for sampling chironomid larvae changed starting with the sample on 2014-06-27; the variable &quot;top_bottom&quot; is coded as a 2. In contrast to previous measurements, the top and bottom core samples were combined and then subsampled. Below is the pertinent section of the protocols.Chironomid samples should be counted within 24 hours of collection. This ensures that larvae are as active and easily identified as possible, and also prevents predatory chironomids from consuming other larvae. Samples should be refrigerated upon returning from the field.<strong>For first instar chironomids in top 1.5cm of sediment only (5 samples)</strong>1. Use sink hose to sieve sediment through 63&micro;m mesh. You may use moderate pressure to break up tubes.2. Back flush sieve contents using a water bottle into small deli container.3. Return label to deli cup (sticking to underside of lid works well).<strong>For larger instar chironomids in the section 1.5-11.5cm (5 samples)</strong>4. Sieve with 125&micro;m mesh in the field.5. Sieve through 125&micro;m mesh again in lab to reduce volume of sample and break up tubes.6. Transfer sample to deli container with the appropriate label.<strong>Subsample if necessary</strong>If necessary, subsample with the following protocol.a. Combine top and bottom samples from each core (1-5) in midge sample splitter.b. Homogenize sample thoroughly, collect one half in deli container, and label container with core number and &ldquo;1/2&rdquo;c. If necessary, split the half that remains in the sampler into quarters, and collect each in deli containers labeled with core number, &ldquo;1/4&rdquo;, and replicate 1 or 2d. Store all deli containers in fridge until counted, and save until all counting is complete&quot; Chironomid Size (head capsule width) 1. Obtain picked samples preserved in ethanol and empty onto petri dish.2. Sort larvae by family groups, arranging in same orientation for easy measurment.3. Set magnification to 20, diopter, x 50 times4. Take measurments for up to 50 or more individuals of each taxa. Round to nearest optical micrometer unit.5. Fill out data sheet for number of larvae in each taxa, Chironomid measurements for each taxa, date of sample, station sample was taken from, which core the sample came from, who picked the core, and your name as the measurer.6. Enter data into shared sheetSee &quot;Chironomid Counts&quot; for changes in sampling chironomid larvae in 2014.
Version Number
17

LTREB Kalfastrond Peninsula Experiment (KAL) Midge Counts at Lake Myvatn 2008-2011

Abstract
A cross ecosystem resource blocking experiment was conducted on the Kalfastrond peninsula, known as the KAL experiment or KAL midge blocking experiment, at Lake Myvatn to determine the influence of an aquatic resource on a terrestrial food web over time. A manipulative field experiment was used in conjunction with a stable isotope analysis to examine changes in terrestrial arthropod food webs in response to the midge subsidy. Cages were established at 2 by 2 meter plots in 6 blocks spread across the site. Each block included 3 treatment levels, an open control plot, a full exclusion cage and a partial exclusion cage, for a total of 18 experimental plots. Midge exclusion cages were designed to prevent midges from entering plots with such cages. Control open pit midge cages were set as a control which allowed complete access to all arthropods. Partial midge exclusion cages were designed and used to examine any effects of cages themselves on terrestrial responses while minimally affecting midge inputs into the plots and arthropod movement. All cages were set at the middle to end of May to the beginning of August in each year, the period corresponding to the active growing season of plants and the flight activity of midges at this site. Midge activity was measured in all plots to document changes in midge abundance over the course of a season and between years and to assess the degree to which cages excluded midges.Midge abundance in the plots was continuously measured using passive aerial infall traps. Midges from infall traps were counted and identified to morphospecies, where the small species is Tanytarsus gracilentus and the large species is Chironomus islandicus. Some arthropods were only identified to the family level Simuliidae, and other arthropods were lumped in a category named others. If the infall trap contained hundreds to thousands of a particular midge species a subsample for each species was performed to estimate the number of midges trapped. These data are the results of the midge counts from the infall traps.
Contact
Core Areas
Dataset ID
284
Date Range
-
Maintenance
Ongoing
Metadata Provider
Methods
I. Field MethodsThe site where this manipulative field experiment was conducted on the Kalfastrond peninsula at Lake Myvatn is approximately 150 meters long and 75 meters wide. The vegetation consists of grasses Deschampsia spp., Poa spp., and Agrostis spp.), sedges (Carex spp.), and forbs (Ranunculus acris, Geum rivale,and Potentilla palustris). The experimental midge exclusions occurred from the middle or end of May to the beginning of August in each year, the period corresponding to the active growing season of plants and the flight activity of midges at this site. 2 by 2 meter plots were established in 6 blocks spread across the site. Each block included 3 treatment levels, an open control plot, a full exclusion cage and a partial exclusion cage, for a total of 18 experimental plots. Control plots were open to allow complete access to all arthropods. Experimental midge exclusion cages were 1 meter high and constructed from white PVC tubing affixed to rebar posts on each corner of the plot, Plate 1. Full exclusion cages were entirely covered with white polyester netting, 200 holes per square inch, Barre Army Navy Store, Barre VT, USA, to prevent midges from entering the plot. The mesh netting completely enclosed the 2 by 2 by 1 meter frame to prevent flying insects from entering, however the mesh was not secured to the ground in order to allow non flying,ground crawling, arthropods to freely enter and exit the cages. Partial exclusion cages had one 0.5 meter strip of mesh stretched around the outside of the frame and another 0.75 meter strip draped over the top. Partial cages were designed to examine any effects of cages themselves on terrestrial responses while minimally affecting midge inputs into the plots and arthropod movement.The partial exclusion treatment was discontinued in 2011. Each plot contains a pitfall and an infall trap that are continuously sampled during the summer, while the cages are up. Vacuum samples were taken from the plots about once per month in 2008 through 2010 and only once per summer for subsequent summers.Midge activity was measured in all plots to document changes in midge abundance over the course of a season and between years and to assess the degree to which cages excluded midges. Midge abundance in the plots was continuously measured using passive aerial infall traps consisting of a 1000 milliliter clear plastic cup, 95 square centimeter opening, attached to a post 0.5 meters high and filled with 250 milliliters of a 1 to 1 ethylene glycol to water solution and a small amount of unscented detergent to capture and kill insects that alighted upon the surface. Infall traps were emptied about every 10 days.II. AnalysisMidges were counted and identified to morphospecies, small and large. The midge (Diptera,Chrionomidae) assemblage at Myvatn is dominated by two species,Chironomus islandicus (Kieffer)(large, 1.1 mg dw) and Tanytarsus gracilentus(Holmgren)(small, 0.1 mg dw), together comprising 90 percent of total midge abundance (Lindegaard and Jonasson 1979). First, the midges collected in the infall traps were spread out in trays, and counted if there were only a few. Some midges were only identified to the family level of Simuliidae,and other arthropods were counted and categorized as the group, others. Arthropods only identified to the family level Simuliidae or classified as others were not dually counted as Chironomus islandicus or Tanytarsus gracilentus. If there were many midges, generally if there were hundreds to thousands, in an infall trap,subsamples were taken. Subsampling was done using plastic rings that were dropped into the tray. The rings were relatively small compared to the tray, about 2 percent of the area of a tray was represented in a ring. The area inside a ring and the total area of the trays were also measured. Note that different sized rings and trays were used in subsample analysis. These are as follows, Trays, small (area of 731 square centimeters), large1 (area of 1862.40 square centimeters), and large2 (area of 1247 square centimeters). Rings, standard ring (diameter of 7.30 centimeters, subsample area is 41.85 square centimeters) and small ring (diameter of 6.5 centimeters, subsample area is 33.18 square centimeters). A small ring was only used to subsample trays classified as type large2.The fraction subsampled was then calculated depending on the size of the tray and ring used for the subsample analysis. If the entire tray was counted and no subsampling was done then the fraction subsampled was assigned a value of 1.0. If subsampling was done the fraction subsampled was calculated as the number of subsamples taken multiplied by the fraction of the tray that a subsample ring area covers (number of subsamples multiplied by (ring area divided by tray area)). Note that this is dependent on the tray and ring used for subsample analysis. Finally, the number of midges in an infall trap accounting for subsampling was calculated as the raw count of midges divided by the fraction subsampled (raw count divided by fraction subsampled).Other metrics such as total insects in meters squared per day, and total insect biomass in grams per meter squared day can be calculated with these data. in addition to the estimated average individual midge masses in grams, For 2008 through 2010 average midge masses were calculated as, Tanytarsus equal to .0001104 grams, Chironomus equal to .0010837 grams. For 2011 average midge masses were, Tanytarsus equal to .000182 grams, Chironomus equal to .001268 grams.
Version Number
15

WDNR Yahara Lakes Fisheries: Fish Lengths and Weights 1987-1998

Abstract
These data were collected by the Wisconsin Department of Natural Resources (WDNR) from 1987-1998. Most of these data (1987-1993) precede 1995, the year that the University of Wisconsin NTL-LTER program took over sampling of the Yahara Lakes. However, WDNR data collected from 1997-1998 (unrelated to LTER sampling) is also included. In 1987 a joint project by the WDNR and the University of Wisconsin-Madison, Center for Limnology (CFL) was initiated on Lake Mendota. The project involved biomanipulation of fish communities within the lake, which was acheived by stocking game fish species (northern pike and walleye). The goal was to induce a trophic cascade that would improve the water clarity of Lake Mendota. See Lathrop et al. 2002. Stocking piscivores to improve fishing and water clarity: a synthesis of the Lake Mendota biomanipulation project. Freshwater Biology 47, 2410-2424. In collecting these data, the objective was to gather population data and monitor populations to track the progress of the biomanipulation. The data is dominated by an assesssment of the game fishery in Lake Mendota, however other Yahara Lakes and non-game fish species are also represented. A combination of gear types was used to gather the population data including boom shocking, fyke netting, mini-fyke netting, seining, and gill netting. Not every sampling year includes length and weight data from all gear types. The WDNR also carried out randomized, access-point creel surveys to estimate fishing pressure, catch rates, harvest, and exploitation rates. Five data files each include length-weight data, and are organized by the type of gear or method which was used to collect the data: 1) fyke, mini-fyke, and seine netting 2) boom shocking 3) gill netting (1993 only) 4)walleye age as determined by scale and spine analysis (1987 only), and 5) creel survey. The final data file contains creel survey information: number of anglers fishing the shoreline, and number of anglers that started and completed trips from public and private access points.
Core Areas
Dataset ID
279
Date Range
-
Metadata Provider
Methods
BOOM SHOCKING1987:A standard WDNR electrofishing boat was used on Lake Mendota set at 300 volts and 2.5 amps (mean) DC, with a 20 % duty cycle and 60 pulses per second. On all sampling dates two people netted fish, the total electrofishing crew was three people. Shocking was divided into stations. For each station, the actual starting and ending time was recorded. Starting and ending points of each station were plotted on a nap. A 7.5 minute topographic map (published 1983) and a cartometer was used to develop a standardized shoreline mileage numbering scheme. Starting at the Yahara River outlet at Tenney Park and measuring counterclockwise, the shoreline was numbered according to the number of miles from the outlet. The length of shoreline shocked for each station was determined using the same maps. The objectives of the fall 1987 electrofishing was: to gather CPE data for comparison with previous surveys of the lake; develop a database for relating fall electroshocker CPE to predator density; collect fall predator diet data; make mark-recapture population estimates of YOY predators; and determine year-class-strength of some nonpredators (yellow perch, yellow bass, and white bass).1993: Electrofishing was used to continue marking largemouth and smallmouth bass (because of low CPE in fyke nets), to recapture fish marked in fyke netting, and to mark and recapture walleyes ( less than 11.0 in.) on Lake Mendota. Four person crews electrofished after sunset from May 05 to June 03, 1993. A standard WDNR electrofishing boat was used, set at about 300 volts and 15.0 amps (mean) DC, with a 20 % duty cycle at 60 pulses per second. On all sampling dates two people netted fish; thus, CPE data are given as catch per two netter hour or mile. Shocking was divided into stations. For each station the actual starting and ending time and the generator s meter times was recorded. Starting and ending points of each station were plotted on a map. 7.5 minute topographic maps (published in 1983) were used in addition to a cartometer to develop a standardized shoreline mileage numbering scheme. Starting at the Yahara River outlet at Tenney Park and measuring counterclockwise the shoreline was numbered according to the number of miles from the outlet. The length of shoreline shocked for each station was determined using these maps. The 4 person electroshocker crews were used again from September 20 to October 19. Fall shocking had several objectives: to gather CPE data for comparison with previous surveys of the lake; develop a database for relating fall electroshocker CPE to piscivore density; and make mark recapture population estimates of young of year (YOY) piscivores.1997:5/13/1997-5/20/1997: Electrofishing was completed at night on lakes: Mendota, Monona, and Waubesa. A standard WDNR electrofishing boat was used, set from 320-420 volts and 16-22 amps DC, with a 20 % duty cycle at 50 pulses per second. Two netters were used for each shocking event. At a particular station, starting and ending times where shocking took place were recorded. The location of the designated shocking stations is unknown.9/23/1997-10/14/1997: Electrofishing was completed at night on Mendota, Monona, Waubesa, and Wingra. A standard WDNR electrofishing boat was used, set from 315-400 volts and 16-24 amps DC, with a 20% duty cycle at 60 pulses per second. Two netters were used for each shocking event. Starting and ending time at each shocking station was listed. The location of the designated shocking stations is unknown.1998:Electrofishing was completed at night on Mendota, Monona, Wingra, and Waubesa from 5/12/1998- 10/28/1998. A standard WDNR electrofishing boat was used, set from 240-410 volts and 15-22 amps DC, with a 20% duty cycle at 50-100 pulses per second. Two netters were used for each shocking event. Starting and ending time at each shocking station was listed. The location of the designated shocking stations is unknown. FYKE NETTING1987:Fyke nets were fished daily from March 17 to April 24, 1987 on Lake Mendota. The nets were constructed of 1.25 inch (stretch) mesh with a lead length of 50 ft. (a few 25 ft. leads were used). The hoop diameter was 3 ft. and the frame measured 3 ft. by 6 ft. Total length of the net was 28 ft. plus the lead length. Nets were set in 48 unknown locations. Initially, effort was concentrated around traditional northern pike spawning sites (Cherokee Marsh, Sixmile Creek, Pheasant Branch Creek, and University Bay). As northern pike catch-per-effort (CPE) declined some nets were moved onto rocky shorelines of the lake to capture walleyes. All adult predators (northern pike, hybrid muskie, largemouth and smallmouth bass, walleye, gar, bowfin, and channel catfish) captured were tagged and scale sampled. Measurements on non-predator species captured in fyke nets were made one day per week. This sampling was used to index size structure and abundance, and to collect age and growth data. In each net, total length and weight of 20 fish of each species caught was measured, and the remaining caught were counted.1993:Same methods as 1987, except fyke nets were fished from 4/8/1993-4/29/1993 on Lake Mendota. The 1993 fyke net data also specifies the &ldquo;mile&rdquo; at which the fyke net was set. This is defined as the number of miles from the outlet of the Yahara River at Tenney Park, moving counterclockwise around the lake. In addition, abundance and lengths of non-gamefish species captured in fyke nets were recorded one day per week. Six nets were randomly selected to sample for non-gamefish data. This sampling was used to index size structure and abundance, and to collect age and growth data. In each randomly selected net, total length and weight was measured for 20 fish of each species, and the remaining caught were counted.1998:There is no formal documentation for the exact methods used for fyke netting from 3/3/1998-8/12/1998 on Lake Mendota. However, given that the data is similar to data collected in 1987 and 1993 it is speculated that the same methods were used.MINI-FYKE NETTING1989:There is no formal documentation for the exact methods used for mini-fyke netting on Lake Mendota and Lake Monona from 7/26/1989-8/25/1989. However, given that the data is similar to data collected from 1990-1993 it is speculated that the same methods were used. In the sampling year of 1989, mini-fyke nets were placed at 22 different unknown stations.1990-1993: Mini-fyke nets were fished on Lake Mendota and Lake Monona during July-September at 20, 29, 13, and 15 sites per month during 1990, 1991, 1992, and 1993, respectively to estimate year-class strength, relative abundance, and size structure of fishes in the littoral zone. Nets were constructed with 3/16 in. mesh, 2 ft. diameter hoops, 2 ft. x 3 ft. frame, and a 25 ft. lead. Sites were comparable to seine sites used in previous surveys. Sites included a variety of substrate types and macrophyte densities. To exclude turtles and large piscivores from minifyke nets, some nets were constructed with approximately 2 in. by 2 in. mesh at the entrance to the net. Thus, mini-fyke net data are most accurate for YOY fishes, and should not be used to make inferences about fishes larger than the exclusion mesh size. 1997:There is no formal documentation for the mini-fyke methods which were used on Lake Waubesa and Lake Wingra from 9/16/1997-9/18/1997. However, given that the data is similar to data collected in 1989, and 1990-1993, it is speculated that the methods used during 1997 are the same. SEINE NETTING1989, 1993: Monthly shoreline seining surveys were conducted on Lake Mendota and Lake Monona during June through September to estimate year class-strength, relative abundance, and size structure of the littoral zone fish community. Twenty sites were identified based on previous studies. Sites included a variety of substrate types and macrophyte densities. Seine hauls were made with a 25ft bag seine with 1/8 inch mesh pulled perpendicular to shore starting from a depth of 1 m. Twenty fish of each species were measured from each haul and any additional fish were counted. Gill Netting (1993)Experimental gill nets were fished in weekly periods during June through August, 1993. Gill nets were used to capture piscivores for population estimates of fish marked in fyke nets. All nets were constructed of five 2.5-4.5 in. mesh panels, and were 125 ft. long. Nets set in water shallower than 10 ft. were 3ft. high or less; all others were 6ft. high or less. Sampling locations were selected randomly from up to three strata: 1) offshore reef sets, 2) inshore sets, 6.0-9.9 ft. deep, and 3) mid-depth sets, 10-29.9 ft. deep. The exact location at which the gill nets were set on the lake is unknown because the latitude and longitude values which were recorded by the WDNR are invalid. Temperature and dissolved oxygen profiles were used to monitor the development of the thermocline and guide net placement during July and August. After the thermocline was established nets were set out to the 30 ft. contour or to the maximum depth with dissolved oxygen greater than 2 ppm. Walleye Age: Scale and Spine Analysis (1987) Scales were taken from walleye that were shocked during the fall of 1987 electrofishing events on Lake Mendota. Scales were taken from 10 fish per one-inch length increment. The scales were removed from behind the left pectoral fin, and from the nape on the left side on esocids. In addition, the second dorsal spine was removed from 10 walleyes per sex and inch increment (to age and compare with scale ages for fish over 20 inches). CREEL SURVEYS1989:Fishing pressure, catch rates, harvest, and exploitation rates were estimated from a randomized, access-point creel survey. The schedule was stratified into weekday and weekend/holiday day types. Shifts were selected randomly and were either 07:00-15:00 h or 15:00-23:00 h. In addition, two 23:00-03:00 h shifts and two 03:00-07:00 h shifts were sampled per month to estimate the same parameters during night time hours. During the ice fishing season (January-February) 22 access points around Lake Mendota and upstream to the Highway 113 bridge were sampled. The clerk counted the number of anglers starting and completing trips during the scheduled stop at each access point. During openwater (March-December) 13 access points were sampled; 10 were boat ramps and 3 were popular shore fishing sites<strong>. </strong>At each of these sites, an instantaneous count of shore anglers was made upon arrival at the site, continuous counts of anglers starting and completing trips at public and private access points were made. Boat occupants and ice fishing anglers were only interviewed if they were completing a trip. Both complete and incomplete interviews were made of shore anglers. Number caught and number kept of each species, and percent of time seeking a particular species were recorded. All predators possessed by anglers were measured, weighed, and inspected for finclips and tags. We measured a random sample of at least 20 fish of each non-predator species per day.1990-1993: Same as 1989, except 23 access points were used during the ice fishing season. In addition, 13 access points were sampled during the openwater (May-December) season; 9 sites were boat ramps and 4 sites were popular shore fishing sites. 1994-1999: No formal documentation exists, but given the similarity in the data and consistency through the years; it is speculated tha tthe methods are the same.
Version Number
19

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

North Temperate Lakes LTER: Sparkling Lake Invertebrates 1994 - 2010

Abstract
Invertebrate counts from Sparkling Lake and Trout Lake between 1994 and 2010.The invertebrate counts from NTL dendy samples were integrated into the general dataset &#39;North Temperate Lakes LTER: Benthic Macroinvertebrates 1981 - 2008&#39; and are kept here only for documentation purposes. They should be accessed from the other database as the taxonomic information is consistent with other NTL samples.
Core Areas
Dataset ID
271
Date Range
-
LTER Keywords
Maintenance
completed
Metadata Provider
Methods
Benthic macroinvertebrates were sampled in August from 2002-2003 and from 2008-2010 along 5 transects that corresponded to crayfish survey sites and represented a range of habitat types and crayfish abundance in 2002 when sampling began. Samples were collected at 1, 3, and 5 m depths, although not all depths were sampled for all transects in all years. Three replicate samples were collected at each site/depth combination in each year using an underwater vacuum air-lift sampler (Wahle and Steneck 1991; Butkas et al. 2010). The sampler consists of a length of PVC attached to a SCUBA tank with a 500 micrometer mesh bag attached to the top of the PVC. We sampled a 0.09 m2 area delimited by a circular quadrat and placed haphazardly at the appropriate depth perpendicular from shore at the transect location.All surfaces potentially available as macroinvertebrate habitat were sampled within a quadrat. For example, macrophytes contained within the quadrat were placed inside the PVC tube prior to opening the SCUBA tank to sample invertebrates living on macrophyte surfaces. In cobble habitat, the upper surface of the rocks were suctioned and then all rocks contained inside the quadrat were picked up, suctioned on all surfaces, and placed outside of the quadrat. Substrate exposed when cobble was removed was also suctioned. Samples were sealed in plastic bags with lake water, placed on ice, and separated live within 48 hours. Invertebrates were separated from substrate, preserved in 95% EtOH, and later identified to the lowest practical taxonomic level (genus in most cases).
Version Number
21
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