US Long-Term Ecological Research Network

Lake snow removal experiment phytoplankton community data, under ice, 2019-2021

Abstract
Although it is a historically understudied season, winter is now recognized as a time
of biological activity and relevant to the annual cycle of north-temperate lakes. Emerging
research points to a future of reduced ice cover duration and changing snow conditions that
will impact aquatic ecosystems. The aim of the study was to explore how altered snow and ice
conditions, and subsequent changes to under-ice light environment, might impact ecosystem
dynamics in a north, temperate bog lake in northern Wisconsin, USA. This dataset resulted from
a snow removal experiment that spanned the periods of ice cover on South Sparkling Bog during
the winters of 2019, 2020, and 2021. During the winters 2020 and 2021, snow was removed from
the surface of South Sparkling Bog using an ARGO ATV with a snow plow attached. The 2019
season served as a reference year, and snow was not removed from the lake. This dataset
represents phytoplankton community samples (pooled epilimnion and hypolimnion samples
representative of 7 m water column) both under-ice and during some shoulder-season (open
water) dates. Samples were collected into amber bottles and preserved with Lugol's solution
before they were sent to Phycotech Inc. (St. Joseph MI, USA) for phytoplankton taxonomic
identification and quantification.<br/>
Core Areas
Creator
Dataset ID
418
Data Sources
Date Range
-
Methods
Phytoplankton samples were obtained from the epilimnion and hypolimnion by
slowly lowering weighted Tygon tubing through the water column to a depth of 7 m, such
that the tubing was filled with a representative water column sample. Based on the inner
diameter of the tubing, 205 mL of water was pumped from the tubing for the epilimnion
sample. Next, 267 mL of water was pumped from the tubing for the hypolimnion sample. Each
sample was collected into a 250 mL amber bottle that contained 2 mL of Lugol’s solution.
Phytoplankton samples were pooled by sampling date and sent to Phycotech Inc. (St. Joseph
MI, USA) for phytoplankton identification, and concentration and biovolume
quantification.<br/>
Publication Date
Version Number
1

Fish catch and biomass per unit effort from McDermott and Sandy Beach Lakes 2017-2020

Abstract
Centarchidae spp., a warm-adapted group of fishes including basses and sunfishes, has increased in recent decades in Wisconsin. Concurrently, declines in cool-adapted species, including Walleye (Sander vitreus), have occurred but the cause is not understood. Multiple factors have been associated with these declines, including rising lake temperatures, habitat degradation, harvest, and species interactions. To quantify the role that competition and/or predation between increasing centrarchids and the rest of the fish community plays, we are conducting a whole-lake experiment to remove centrarchids from an experimental lake in northern Wisconsin while measuring the response of all other fish species. In 2018 and 2019, ~200,000 centrarchid individuals were removed, while species-specific catch-per-unit-effort (CPUE) and biomass-per-unit-effort (BPUE) were measured. Yellow Perch have increased in CPUE and BPUE, while centrarchid abundances have declined. We will continue removing centrarchids in 2021 and monitoring these populations. This information will be used to inform an understanding of the conditions necessary to support self-sustaining fish populations given global environmental change.<br/>
Core Areas
Creator
Dataset ID
398
Date Range
-
Maintenance
ongoing
Methods
Study area
The experimental (McDermott Lake; 46.00299280, -90.16081610) and reference (Sandy Beach Lake (46.10614350, -89.97131020) systems are located in Iron County in Northern, Wisconsin. McDermott Lake has a surface area of 33.1 ha and a mean depth of 3.0 m, while Sandy Beach Lake has a surface area of 44.5 ha and a mean depth of 2.1 m. Maximum depth in McDermott Lake is 5.7 m and in Sandy Beach Lake is 4.0 m. Both lakes include a variety of substrates (e.g., rock, gravel, and sand) and areas of submerged and emergent vegetation. At the start of the study, McDermott and Sandy Beach Lake fish communities were similar with high Centrarchidae spp. (i.e., centrarchid) abundances, few adult walleye, and a history of natural walleye recruitment. Other species present include yellow perch, northern pike, muskellunge, black bullhead, and white sucker (Table 1).
Fish sampling
Standardized surveys
From 2017-2020, we conducted fish population sampling on the experimental (McDermott) and reference (Sandy Beach) lakes. Every year of the study, we have conducted standardized monitoring surveys employing numerous sampling techniques to detect changes in the fish community relative to 2017-baseline information (Fig. 1). Sampling began immediately following ice-out (~mid-April) with the deployment of five fyke nets for one week. The fyky surveys served two purposes: 1) to serve as the capture method for marking walleye as part of the mark-recapture survey to attain a population estimate, and 2) to estimate other focal species (i.e., black crappie, yellow perch, muskellunge, northern pike) relative abundances. During these surveys, all collected walleye were measured (total length (TL); mm), sexed, checked for a Passive Integrated Responder (PIT) tag, and if one was not present, marked with a unique PIT tag. We also removed a dorsal spine sample for aging. Adult (mature) walleyes were defined as all fish 381 mm and all fish for which sex could be determined (regardless of length). Walleye of unknown sex &lt;381 mm were classified as juvenile (immature). McDermott and Sandy Beach Lakes have both had walleye population estimates previously conducted by the Wisconsin Department of Natural Resources (WDNR) therefore the goal was to mark 10% of the anticipated spawning population (based off of previous population estimates). Marking continued until the target number was reached or spent females began appearing in the fyke nets. Walleye were recaptured using an AC boat electrofishing survey within one week (typically 1-4 days) after netting and marking were completed. In each lake, the entire shoreline was sampled. All captured walleyes were measured and examined for marks. Based on electrofishing mark-recapture data, population estimates were calculated using the Chapman (1951) modification of the Petersen Estimator as:
N=((M+1)(C+1))/((R+1))
where N was the population estimate, M was the number of fish marked and released, C was the total number of fish captured and examined for marks in the recapture sample, and R was the total number of marked fish observed in C. The Chapman Modification method was used because it provides more accurate population estimates in cases when R is relatively small (Ricker 1975).

From early-May to mid-June, we sampled larval fishes using a 1,000m mesh conical ichthyoplankton net towed for five minutes immediately below the lake surface. Weekly samples were taken at night at five sampling locations in each lake. Each lake was divided into five quadrats and sites were established at a randomly selected nearshore (&lt;100 m of shore) location in each quadrat on each sampling date. Once selected, locations remained fixed throughout the study. Volume of water filtered during each tow was estimated using a General Oceanics© model 2030R flowmeter mounted in the center of the net frame. Samples were transferred to containers and stored in 90% ethanol. Collected fishes were identified to species according to Auer (1982) and enumerated.
In addition to the adult walleye population, we were interested in estimating the size of the adult largemouth bass population. We performed early summer (late-May) mark-recapture surveys using AC boat electrofishing (Wisconsin‐style; AC; 2.0–3.0 amps, 200–350 V, 25% duty cycle with two netters) to sample largemouth bass. Collected largemouth bass were measured, checked for a top caudal fin clip, and if not present, marked with a top caudal fin clip and released. Adult (mature) largemouth bass were defined as all fish 203 mm. We aimed to recapture 10% of the marked population. Largemouth bass are in very low abundance in Sandy Beach Lake therefore a population estimate was not possible. In McDermott Lake, due to the small population size of largemouth bass we completed multiple marking surveys from late-May to early June to achieve this recapture rate. From electrofishing mark-recapture information, population estimates were calculated using the Schnabel (1938) modification of the Lincoln-Petersen method:
where N was the population estimate, M was the number of fish marked and released in sample t, C was the number of fish captured in sample t, and R was the number of fish already marked when caught in sample t.
To obtain centrarchid population demographic data, current standardized WDNR surveys of inland lakes consist of early summer (water temperature range = 13.0–21.0°C) AC boat electrofishing surveys or mid‐summer (18.3–26.7°C) mini‐fyke net (Simonson et al. 2008). To encompass this range of water temperatures, we performed a combination of surveys starting at the end of May with an AC boat electrofishing survey. Then, fish were sampled once monthly when lake surface water temperatures were ≥13.0°C in both lakes (June–September). Both lakes were sampled during 1‐week each month using three gears (AC boat electrofishing, mini-fyke nets, cloverleaf traps). Lakes were sampled on consecutive nights in each 1‐week period but only one gear type was employed per night.
All gears sampled shallow shorelines (0–5 m from bank, depth ≤2 m) and were deployed in fixed locations following standard approaches (Bonar et al. 2009). Sampling locations were evenly distributed along the shoreline of the lake, and all gears were deployed in similar habitat types. Five 10‐min nighttime boat electrofishing (Wisconsin‐style; AC; 2.0–3.0 amps, 200–350 V, 25% duty cycle) transects were conducted using two dipnetters. Five mini‐fyke nets (0.9‐m × 0.61‐m frames, 3.2‐mm mesh [bar measure], 7.6‐m‐long lead, and a double throat) were deployed in areas where the net frames would be in 1.0–1.5 m of water, and leads were fixed onshore. Five cloverleaf traps (three lobed, height = 41 cm, 50 cm diameter, 6.0‐mm bar wire mesh with 12.7‐mm‐wide openings between lobes, and an attractant [liver]) were deployed in littoral habitats. Both mini‐fyke nets and cloverleaf traps were set in early afternoon, fished overnight, and retrieved the following afternoon (~24‐h soak time). All catches were standardized according to gear-specific effort. For boat electrofishing, catch per unit effort (CPUE) is presented as fish/hr. For mini-fyke nets and cloverleaf traps, CPUE is calculated as fish/net night or fish/trap night.
To quantify walleye recruitment in each lake, we employed multiple gears throughout the sampling season including micromesh gillnets, beach seines, and boat electrofishing. In late July/early August, we deployed four 46-m x 1.2-m gillnets with 0.95-cm bar mesh. Sampling locations were evenly distributed along the shoreline and locations were fixed each year. Gillnets were set at night and at depths ranging from 0-5 m. Set duration ranged 1-2 hours to minimize bycatch, thus catches were standardized to age-0 walleyes collected per 10 hours of soak time. In late August, we pulled .24-m long beach seines with 0.64-cm mesh at five sites in each lake. Sites were chosen to represent a variety of habitat types and based on ability to effectively use the seine. Seining sites remained fixed for the duration of the study. Seines were used during daylight hours on each lake. Catch per unit effort was calculated as the number of individuals per seine haul. When water temperatures fell below 21°C (early September), we sampled age-0 walleyes using nighttime boat electrofishing (Wisconsin‐style; AC; 2.0–3.0 amps, 200–350 V, 25% duty cycle, two netters). The entire shoreline of each lake was sampled. Surveys were conducted prior to walleye fingerling stocking. All collected walleye were measured (TL, mm). Catch per unit effort was calculated as the number of age-0 walleyes per meter shoreline.
Removal efforts
In addition to standardized surveys in our experimental lake, in 2018 we began centrarchid removal efforts using a variety of techniques including fyke nets, boat electrofishing, mini-fyke nets, and cloverleaf traps (Fig. 1). Following annual spring fyke net surveys, fyke nets remained in the experimental lake to remove centrarchids. In 2018, we sampled 10 fyke nets from May 14 to June 7 when centrarchid catches started to decline. Due to personnel limitations, in 2019 and 2020 only five fyke nets were used from late spring (May 9, April 30) until late June (June 27, June 25). Additionally, we sampled five mini-fyke nets and 21 cloverleaf traps from late May through mid-August. All gears were emptied every 1-2 days and sites were rotated to maximize centrarchid catches. Collected fish were identified to species and measured (TL, mm). Centrarchid species were retained while other species were returned to McDermott Lake.
NTL Themes
Version Number
1

Lake Mendota, Wisconsin, USA, Zebra Mussel Body Size and Biomass Biometrics 2018

Abstract
We sampled 98 individuals of the zebra mussel (Dreissena polymorpha) population of Lake Mendota from many littoral zone sites in 2018 to create biometric relationships between several metrics of body size and several metrics of biomass, including length, width, height, living weight, wet weight, dry weight, shell weight, shell-free dry weight, and ash-free dry weight. We selected individuals to span a wide range of body sizes and found strong relationships between most combinations of body size and biomass metrics.<br/>
Dataset ID
395
Date Range
-
LTER Keywords
Methods
In the laboratory, three measurements of body size and seven measurements of biomass were captured. First, any foreign material found adhering to the external surface of specimens was completely removed. Body size directional measurements of shell length (L), width (W), and height (H) were recorded for every specimen with the aid of callipers (0.01 mm). Following this, any excess water was removed from surfaces by drying the external shell with tissue paper. Further, using a scalpel blade and tweezers, excess water was removed from the mantle cavity by gently forcing bivalves to gape, taking care not to cut the adductor muscle or damage tissues. Using high-resolution scales, living-weight (LW) was obtained for each specimen. Then each specimen was fully opened, which in most cases involved cutting of the adductor muscles. To remove additional fluid from the mantle and other cavities, each specimen was then placed with the valve gape (flesh) facing downwards onto absorbent tissue, for ~5-10 minutes. A wet-weight (WW) was obtained for each specimen. Following this, the soft tissue was dissected from the shell, then both soft tissue and shell were dried together within an oven (60-72 degreeC) for ~48 hrs, or until they reached a constant weight. Specimens were cooled to room temperature in a desiccator before final weighing. A combined dry-weight (DW) was recorded, as were weights for the soft tissue and shell separately, i.e. shell free dry-weight (SFDW) and dry shell-weight (SW), respectively. Following the establishment of SW, SFDW was calculated subtracting SW from the total DW (i.e. SFDW = DW–SW). To obtain an ash-weight (AW), the soft and hard tissue structures of specimens were incinerated (500–550 degreeC) together within a muffle furnace for 4–6 hrs. In all cases, the ash free dry-weight (AFDW) was then calculated for the entire specimen (soft tissue and shell) by subtracting the AW from DW, i.e. AFDW = DW–AW.<br/>
Version Number
1

North Temperate Lakes LTER Zooplankton conversion formulas length to biomass

Abstract
Formulas for calculating zooplankton biomass based on measured length for species encountered in NTL's northern lakes. Formulas are either based on literature reports or measurements in particular research lakes.
Core Areas
Dataset ID
376
LTER Keywords
Maintenance
completed
Methods
formulas are based on data in literature or were determined in samples from research lakes:

Culver D.A. et.al. 1985. Can. J. Fish. Aquat. Sci. Vol 42, 1380-1390.
Biomass of freshwater crustacean zooplankton from length-weight regressions.

Downing, John A. and Frank H. rigler. 1984.
A manual on methods for the assessment of secondary productivity in fresh waters. Second edition.

Dumont, H.J., I. Van de Velde and S. Dumont. Ref??
The dry weight estimate of biomass in a selection of cladocera, copepoda and rotifera from the plankton, periphyton and benthos of continental waters.

Hawkins, Bethany E. and M.S. Evans. 1979. J.Great Lakes Res. 5(3-4):256-263
Seasonal cycles of zooplankton biomass in southeastern Lake Michigan

Lawrence, S.G., D.F. Malley, W.J. Findlay, M.A. MacIver and I.L. Delbaere. 1987. Can J. Fish. Aquat. Sci. 44: 264-274.
Methods for estimating dry weight of freshwater planktonic crustaceans from measures of length and shape.

Pace M.L. and J.D. Orcutt. 1981. Limnol. Oceanogr. 26(5), 822-830.
The relative importance of protozoans, rotifers, and crustaceans in a freshwater zooplankton community.

Yan N.D. and G.L. Mackie. 1987. Can. J. Fish. Aquat. Sci. Vol 44, 382-389.
Improved estimation of the dry weight of Holopedium gibberum using clutch size, a body fat index, and lake water total phosphorus concentration.

Ruttner-Kolisko A. 1977. Arch. Hydrobiol. Beih. Ergebn. Limnol. 8, 71-76.
Suggestions for biomass calculations of plankton rotifers.
Version Number
1

Production, biomass, and yield estimates for walleye populations in the Ceded Territory of Wisconsin from 1990-2017

Abstract
Recreational fisheries are valued at $190B globally and constitute the predominant use of wild fish stocks in developed countries, with inland systems contributing the dominant fraction of recreational fisheries. Although inland recreational fisheries are thought to be highly resilient and self-regulating, the rapid pace of environmental change is increasing the vulnerability of these fisheries to overharvest and collapse. We evaluate an approach for detecting hidden overharvest of inland recreational fisheries based on empirical comparisons of harvest and biomass production. Using an extensive 28-year dataset of the walleye fisheries in Northern Wisconsin, USA, we compare empirical biomass harvest (Y) and calculated production (P) and biomass (B) for 390 lake-year combinations. Overharvest occurs when harvest exceeds production in that year. Biomass and biomass turnover (P/B) both declined by about 30% and about 20% over time while biomass harvest did not change, causing overharvest to increase. Our analysis revealed 40% of populations were production-overharvested, a rate about 10x higher than current estimates based on numerical harvest used by fisheries managers. Our study highlights the need for novel approaches to evaluate and conserve inland fisheries in the face of global change.
Contact
Core Areas
Dataset ID
373
Date Range
-
LTER Keywords
Methods
All methods describing the calculation of these data can be found in Embke et al. (in review)
Version Number
1

Cascade project at North Temperate Lakes LTER - Daily Chlorophyll Data for Whole Lake Nutrient Additions 2013-2015

Abstract
Daily chlorophyll for surface water samples in Paul, Peter, and Tuesday lakes from mid-May to early September for the years 2013, 2014 and 2015. Inorganic nitrogen and phosphorus were added to Peter and Tuesday lakes each year while Paul Lake was an unfertilized reference.
Contact
Core Areas
Dataset ID
372
Date Range
-
Maintenance
completed
Methods
Methods are described in Wilkinson et al. 2018 (Ecological Monographs 88:188-203) and Pace et al. 2017 (Proceedings of the National Academy of Sciences USA 114: 352-357). These publications including supplements should be consulted for details.

Version Number
1

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

Abstract
Zooplankton data from 1984-2016. Sampled approximately weekly with two net hauls through the water column (30 cm diameter net, 80 um mesh). There have been over eight zooplankton counters during this period, so species-level identifications (TAX, below) are not as consistent as those for some of the other datasets. Sampling Frequency: varies; Number of sites: 8
Core Areas
Dataset ID
355
Date Range
-
Maintenance
completed
Methods
Sampling:
Zooplankton were sampled approximately weekly with two net hauls through the water column (30 cm diameter net, 80 um mesh). Tows were taken at standard depths for almost all years. The standard depths are as follows: Peter, East Long, West Long, Crampton and Tuesday Lakes: 12m, Paul Lake: 8m, Ward Lake: 6m; exceptions are: for 2012 and beyond Tuesday Lake was sampled at 10m, Peter was sampled at 10m from 1984-1986, Paul was sampled at 7.5m in 1995. Samples were preserved with cold sugared formalin or Lugol's solution.
Version Number
16

Fluxes project at North Temperate Lakes LTER: Spatial Metabolism Study 2007

Abstract
Data from a lake spatial metabolism study by Matthew C. Van de Bogert for his Phd project, "Aquatic ecosystem carbon cycling: From individual lakes to the landscape."; The goal of this study was to capture the spatial heterogeneity of within-lake processes in effort to make robust estimates of daily metabolism metrics such as gross primary production (GPP), respiration (R), and net ecosystem production (NEP). In pursuing this goal, multiple sondes were placed at different locations and depths within two stratified Northern Temperate Lakes, Sparkling Lake (n=35 sondes) and Peter Lake (n=27 sondes), located in the Northern Highlands Lake District of Wisconsin and the Upper Peninsula of Michigan, respectively.Dissolved oxygen and temperature measurements were made every 10 minutes over a 10 day period for each lake in July and August of 2007. Dissolved oxygen measurements were corrected for drift. In addition, conductivity, temperature compensated specific conductivity, pH, and oxidation reduction potential were measured by a subset of sondes in each lake. Two data tables list the spatial information regarding sonde placement in each lake, and a single data table lists information about the sondes (manufacturer, model, serial number etc.). Documentation :Van de Bogert, M.C., 2011. Aquatic ecosystem carbon cycling: From individual lakes to the landscape. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 156. Also see Van de Bogert, M.C., Bade, D.L., Carpenter, S.R., Cole, J.J., Pace, M.L., Hanson, P.C., Langman, O.C., 2012. Spatial heterogeneity strongly affects estimates of ecosystem metabolism in two north temperate lakes. Limnology and Oceanography 57, 1689-1700.
Core Areas
Dataset ID
285
Date Range
-
Metadata Provider
Methods
Data were collected from two lakes, Sparkling Lake (46.008, -89.701) and Peter Lake (46.253, -89.504), both located in the northern highlands Lake District of Wisconsin and the Upper Peninsula of Michigan over a 10 day period on each lake in July and August of 2007. Refer to Van de Bogert et al. 2011 for limnological characteristics of the study lakes.Measurements of dissolved oxygen and temperature were made every 10 minutes using multiple sondes dispersed horizontally throughout the mixed-layer in the two lakes (n=35 sondes for Sparkling Lake and n=27 sondes for Peter Lake). Dissolved oxygen measurements were corrected for drift.Conductivity, temperature compensated specific conductivity, pH, and oxidation reduction potential were also measured by a subset of sensors in each lake. Of the 35 sondes in Sparkling Lake, 31 were from YSI Incorporated: 15 of model 600XLM, 14 of model 6920, and 2 of model 6600). The remaining sondes placed in Sparkling Lake were 4 D-Opto sensors, Zebra-Tech, LTD. In Peter Lake, 14 YSI model 6920 and 13 YSI model 600XLM sondes were used.Sampling locations were stratified randomly so that a variety of water depths were represented, however, a higher density of sensors were placed in the littoral rather than pelagic zone. See Van de Bogert et al. 2012 for the thermal (stratification) profile of Sparkling Lake and Peter Lake during the period of observation, and for details on how locations were classified as littoral or pelagic. In Sparkling Lake, 11 sensors were placed within the shallowest zone, 12 in the off-shore littoral, and 6 in each of the remaining two zones, for a total of 23 littoral and 12 pelagic sensors. Similarly, 15 sensors were placed in the two littoral zones, and 12 sensors in the pelagic zone.Sensors were randomly assigned locations within each of the zones using rasterized bathymetric maps of the lakes and a random number generator in Matlab. Within each lake, one pelagic sensor was placed at the deep hole which is used for routine-long term sampling.Note that in Sparkling Lake this corresponds to the location of the long-term monitoring buoy. After locations were determined, sensors were randomly assigned to each location with the exception of the four D-Opto sensor is Sparkling Lake, which are a part of larger monitoring buoys used in the NTL-LTER program. One of these was located near the deep hole of the lake while the other three were assigned to random locations along the north shore, south shore and pelagic regions of the lake. Documentation: Van de Bogert, M.C., Bade, D.L., Carpenter, S.R., Cole, J.J., Pace, M.L., Hanson, P.C., Langman, O.C., 2012. Spatial heterogeneity strongly affects estimates of ecosystem metabolism in two north temperate lakes. Limnology and Oceanography 57, 1689-1700.
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

Macrophyte Sampling - Yahara Lakes District

Macrophyte Sampling Schedule
1.       Macrophytes are sampled on Lakes Mendota, Monona, Waubesa, Wingra, and Fish Lake. Follow past years sampling order (Waubesa, Wingra, Fish, Monona, Mendota) and keep the dates as consistent to past years as possible (see list of dates). Working around the routine LTER sampling, schedule the macrophyte sampling well in advance in order to sign out a vehicle and boat when necessary.
 

Macrophyte Sampling Preparation
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