US Long-Term Ecological Research Network

North Temperate Lakes LTER Regional Survey Zooplankton 2015 - current

Abstract
The Northern Highlands Lake District (NHLD) is one of the few regions in the world with periodic comprehensive water chemistry data from hundreds of lakes spanning almost a century. Birge and Juday directed the first comprehensive assessment of water chemistry in the NHLD, sampling more than 600 lakes in the 1920s and 30s. These surveys have been repeated by various agencies and we now have data from the 1920s (UW), 1960s (WDNR), 1970s (EPA), 1980s (EPA), 1990s (EPA), and 2000s (NTL). The 28 lakes sampled as part of the Regional Lake Survey have been sampled by at least four of these regional surveys including the 1920s Birge and Juday sampling efforts. These 28 lakes were selected to represent a gradient of landscape position and shoreline development, both of which are important factors influencing social and ecological dynamics of lakes in the NHLD. This long-term regional dataset will lead to a greater understanding of whether and how large-scale drivers such as climate change and variability, lakeshore residential development, introductions of invasive species, or forest management have altered regional water chemistry. Zooplankton samples were taken at approximately the deepest part of each lake, via a vertical tow with a Wisconsin net. Count of individuals and presence absence data for all lakes in study region are provided here.
Contact
Core Areas
Dataset ID
381
Date Range
-
Maintenance
ongoing
Methods
Each zooplankton sample was taken at approximately the deepest part of each lake, via a vertical tow with a Wisconsin net (20cm diameter mouth, 80µ mesh) lowered to 1 meter above the bottom of a lake and then pulled up slowly at a rate of about 3 seconds per meter. Contents of the net were preserved in 4-oz jars with 95% ethanol. One sample was taken from each lake. Samples were collected by the Regional Lakes summer sampling crew in June 2015.
Version Number
1

Little Rock Lake Experiment at North Temperate Lakes LTER: Zooplankton length 1988 - 1998

Abstract
The Little Rock Acidification Experiment was a joint project involving the USEPA (Duluth Lab), University of Minnesota-Twin Cities, University of Wisconsin-Superior, University of Wisconsin-Madison, and the Wisconsin Department of Natural Resources. Little Rock Lake is a bi-lobed lake in Vilas County, Wisconsin, USA. In 1983 the lake was divided in half by an impermeable curtain and from 1984-1989 the northern basin of the lake was acidified with sulfuric acid in three two-year stages. The target pHs for 1984-5, 1986-7, and 1988-9 were 5.7, 5.2, and 4.7, respectively. Starting in 1990 the lake was allowed to recover naturally with the curtain still in place. Data were collected through 2000. The main objective was to understand the population, community, and ecosystem responses to whole-lake acidification. Funding for this project was provided by the USEPA and NSF. Zooplankton samples are collected from the treatment and reference basins of Little Rock Lake at at two to nine depths using a 30L Schindler Patalas trap (53um mesh). Zooplankton samples are preserved in buffered formalin and archived. Data are summed over sex and stage and integrated volumetrically over the water column to provide a lake-wide estimate of average length of organisms for each species.
Core Areas
Dataset ID
375
Date Range
-
Maintenance
completed
Methods
We collect zooplankton samples at the deepest part of the lake using two different gear types. We take one vertical tow with a Wisconsin Net (80um mesh), and a series of Schindler Patalas (53um mesh) samples spanning the water column. All samples are preserved in cold 95percent EtOH.
After collection we combine subsamples of the individual Schindler Patalas trap samples to create one hypsometrically pooled sample for each lakeordate. The individual depth samples are discarded after pooling except from one August sampling date per year. The Hypsometrically Pooled sample and the Wisconsin Net sample are archived in the UW Zoology museum.
We count zooplankton in one or two subsamples, each representing 1.8L of lake water, of the hypsometrically pooled samples to calculate zooplankton abundance. We count one sample date per month from the open water season, and the February ice cover sample. We identify individuals to genus or species, take length measurements, and count eggs and embryos.
Protocol log: 1981-May1984 -- a 0.5m high, 31L Schindler Patalas trap with 80um mesh net was used. Two Wisconsin Net tows were collected. Preservative was 12percent buffered formalin.
June1984 -- changed to 53um mesh net on Schindler trap.
July1986 -- began using the 2m high, 45L Schindler Patalas trap. Changed WI Net collection to take only one tow.
2001 -- changed zooplankton preservative from 12percent buffered formalin to 95percent EtOH.
The number of sample dates per year counted varies with lake and year, from 5 datesoryear to 17 datesoryear.
1981-1983 -- pooled samples are of several types: Total Pooled (TP) were created using equal volume subsamples of the Schindler samples. Epi, Meta, Hypo pooled used equal volume subsamples from the Schindler samples collected from each of the thermal strata. Strata Pooled used equal volume subsamples from the Epi, Meta, Hypo pooled samples to create an entire lake sample. Hypsometrically Pooled (HP) is our standard, which uses subsample volumes weighted to represent the hypsometry of the lake.
Version Number
1

Long-term fish size data for Wisconsin Lakes Department of Natural Resources and North Temperate Lakes LTER 1944 - 2012

Abstract
This dataset describes long-term (1944-2012) variations in individual fish total lengths from Wisconsin lakes. The dataset includes information on 1.9 million individual fish, representing 19 species. Data were collected by Wisconsin Department of Natural Resource fisheries biologists as part of routine lake fisheries assessments. Individual survey methodologies varied over space and time and are described in more detail by Rypel, A. et al., 2016. Seventy-Year Retrospective on Size-Structure Changes in the Recreational Fisheries of Wisconsin. Fisheries, 41, pp.230-243. Available at: http://afs.tandfonline.com/doi/abs/10.1080/03632415.2016.1160894
Contact
Core Areas
Creator
Dataset ID
357
Date Range
-
Maintenance
completed
Methods
Fisheries surveys of inland lakes and streams in Wisconsin have been conducted by the Wisconsin Department of Natural Resources (WDNR) professionals and its predecessor the Wisconsin Conservation Department for >70 y. Standard fyke net and boat electrofishing surveys tend to dominate the fisheries surveys and data collected. Most fyke net data on certain species (e.g., Walleye Sander vitreus and Muskellunge Esox masquinongy) originates from annual spring netting surveys following ice-out. These data are used for abundance estimates, mark and recapture surveys for estimating population sizes, and egg-take procedures for the hatcheries. Boat-mounted boom and mini-boom electrofishing surveys became increasingly common in the late 1950s and 1960s. Boat electrofishing surveys have typically been conducted during early summer months (May and June), but some electrofishing survey data are also collected in early spring as part of walleye and muskellunge mark-recapture surveys. Summer fyke netting surveys have been collected more sporadically over time, but were once more commonly used as a panfish survey methodology. Surveys were largely non-standardized. Thus, future users and statistical comparisons utilizing these data should acknowledge the non-standard nature of their collection. More in-depth description of these data can be found in Rypel, A. et al., 2016. Seventy-Year Retrospective on Size-Structure Changes in the Recreational Fisheries of Wisconsin. Fisheries, 41, pp.230-243. Available at: http://afs.tandfonline.com/doi/abs/10.1080/03632415.2016.1160894
Version Number
3

Long-term fish abundance data for Wisconsin Lakes Department of Natural Resources and North Temperate Lakes LTER 1944 - 2012

Abstract
This dataset describes long-term (1944-2012) variations in the relative abundance of fish populations representing nine species in Wisconsin lakes. Data were collected by Wisconsin Department of Natural Resource fisheries biologists as part of routine lake fisheries assessments. Individual survey methodologies varied over space and time and are described in more detail by Rypel, A. et al., 2016. Seventy-Year Retrospective on Size-Structure Changes in the Recreational Fisheries of Wisconsin. Fisheries, 41, pp.230-243. Available at: http://afs.tandfonline.com/doi/abs/10.1080/03632415.2016.1160894
Contact
Core Areas
Creator
Dataset ID
356
Date Range
-
Maintenance
completed
Methods
Fisheries surveys of inland lakes and streams in Wisconsin have been conducted by the Wisconsin Department of Natural Resources (WDNR) professionals and its predecessor the Wisconsin Conservation Department for >70 y. Standard fyke net and boat electrofishing surveys tend to dominate the fisheries surveys and data collected. Most fyke net data on certain species (e.g., Walleye Sander vitreus and Muskellunge Esox masquinongy) originates from annual spring netting surveys following ice-out. These data are used for abundance estimates, mark and recapture surveys for estimating population sizes, and egg-take procedures for the hatcheries. Boat-mounted boom and mini-boom electrofishing surveys became increasingly common in the late 1950s and 1960s. Boat electrofishing surveys have typically been conducted during early summer months (May and June), but some electrofishing survey data are also collected in early spring as part of walleye and muskellunge mark-recapture surveys. Summer fyke netting surveys have been collected more sporadically over time, but were once more commonly used as a panfish survey methodology. Surveys were largely non-standardized. Thus, future users and statistical comparisons utilizing these data should acknowledge the non-standard nature of their collection. More in-depth description of these data can be found in Rypel, A. et al., 2016. Seventy-Year Retrospective on Size-Structure Changes in the Recreational Fisheries of Wisconsin. Fisheries, 41, pp.230-243. Available at: http://afs.tandfonline.com/doi/abs/10.1080/03632415.2016.1160894
Version Number
5

Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format

Abstract
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Core Areas
Dataset ID
349
Date Range
-
Methods
Protocol available in methods section of: http://msphere.asm.org/content/2/3/e00169-17
Prior to collection, water temperature and dissolved oxygen concentrations are measured using a YSI 550a. The ranges of the epilimnion and hypolimnion are determined based on the location of the thermocline (where temperature/oxygen is changing the fastest). The two layers are collected separately in 1 meter increments using an integrated water column sampler. Water samples are taken back to the lab, shaken thoroughly, and filtered via peristaltic pump through 0.22 micron filters (Pall Supor). Filters are temporarily stored at -20C after collection and then transferred to -80C after transport on dry ice from Trout Lake Station to UW-Madison. Nutrient samples are collected bi-weekly following standard LTER protocols. DNA is extracted from filters using a FASTDNA SpinKit for Soil with minor modifications. (In cases of low yield or specialized sequencing methods, a phenol-chloroform extraction is used instead). The protocol for sequencing and analysis of data varies by year and by sub-project.
Version Number
4

North Temperate Lakes LTER Regional Survey Macrophytes Plant Index 2015 - current

Abstract
The Northern Highlands Lake District (NHLD) is one of the few regions in the world with periodic comprehensive water chemistry data from hundreds of lakes spanning almost a century. Birge and Juday directed the first comprehensive assessment of water chemistry in the NHLD, sampling more than 600 lakes in the 1920s and 30s. These surveys have been repeated by various agencies and we now have data from the 1920s (UW), 1960s (WDNR), 1970s (EPA), 1980s (EPA), 1990s (EPA), and 2000s (NTL). The 28 lakes sampled as part of the Regional Lake Survey have been sampled by at least four of these regional surveys including the 1920s Birge and Juday sampling efforts. These 28 lakes were selected to represent a gradient of landscape position and shoreline development, both of which are important factors influencing social and ecological dynamics of lakes in the NHLD. This long-term regional dataset will lead to a greater understanding of whether and how large-scale drivers such as climate change and variability, lakeshore residential development, introductions of invasive species, or forest management have altered regional water chemistry. The purpose of the macrophyte survey is to identify, and quantify the types of aquatic plants within the various 28 regional survey lakes. The macrophyte survey consists of sampling macrophyte plants using a metal rake attached to a 15ft pole at approximately 140 spatially resolved points on a lake that are spread out in a grid like fashion, equally spaced from each other. Sampling locations were chosen such that the maximum depth at which macrophytes were surveyed was equal to or less than 15ft of water. Macrophyte sampling occurs in the latter part of the summer (after July 10) to ensure that macrophytes have had adequate time to grow and our sampling efforts capture the typical summer macrophyte community in each lake. Macrophyte sampling in these 28 lakes is ongoing and will be repeated approximately once every six years.
Core Areas
Dataset ID
338
Date Range
-
Methods
the protocol employed here is based on:
Hauxwell, J., S. Knight, K. Wagner, A. Mikulyuk, M. Nault, M. Porzky and S. Chase . 2010. Recommended baseline monitoring of aquat ic plants in Wisconsin : sampling design, field and laboratory procedures, data entry and analys is, and applica tions. Wisconsin Department of Natural Resources Bureau of Science Services, PUB-SS-1068 2010. Madison, Wisconsin, USA.
Version Number
13

Microbial Observatory at North Temperate Lakes LTER Three Bog 2005 study

Abstract
Multiple forces structure natural microbial communities, but the relative roles and interactions of these drivers are poorly understood. Gradients of physical and chemical parameters can be especially influential. In traditional ecological theory, variability in environmental conditions across space and time represents habitat heterogeneity, which may shape communities. Here we used aquatic microbial communities as a model to investigate the relationship between habitat heterogeneity and community composition and dynamics. We defined spatial habitat heterogeneity as vertical temperature and dissolved oxygen (DO) gradients in the water column, and temporal habitat heterogeneity as variation throughout the open-water season in these environmental parameters. Seasonal lake mixing events contribute to temporal habitat heterogeneity by destroying and re-creating these gradients. Because of this, we selected three lakes along a range of annual mixing frequency (polymictic, dimictic, meromictic) for our study. We found that bacterial community composition (BCC) was distinct between the epilimnion and hypolimnion within stratified lakes, and also more variable within the epilimnia through time. We found stark differences in patterns of epilimnion and hypolimnion dynamics over time and across lakes, suggesting that specific drivers have distinct relative importance for each community.
Core Areas
Dataset ID
295
Date Range
-
LTER Keywords
Maintenance
completed
Metadata Provider
Methods
The BCC of three small northern Wisconsin lakes, CB (polymictic, maximum depth 2.5 m), TB (dimictic, maximum depth 7 m) and MA (meromictic, maximum depth 21.5 m), were sampled weekly during the open-water period of 2005 (late May to early November). These lakes were chosen because of their shared dystrophy, acidity, similar surface area (range 0.6–1.2 ha), comparable physicalorchemical characteristics, proximity to one another and range of annual of mixing frequencies. Samples were collected over the deepest point of each lake. All lakes were sampled on the same day each week.Temperature and DO measurements were observed for every sample date using YSI model 58 dissolved oxygen meter (Yellow Springs, OH) calibrated at each sample date as per manufacturer s instruction. Trout Bog and MA profiles were observed at every metre and CB profiles were observed at every half metre. Integrated water column samples were collected for each thermal layer. Thermal layer boundaries were determined based on temperature profiles. The top of the hypolimnion was determined to be where the temperature decreased by 1.5–2.0degreeC over 0.5 m or less. In polymictic CB, the epilimnion was consistently sampled at 0.0–1.0 m, and the hypolimnion at 1.0–2.0 m; these depths were based on thermal profiles of CB s weak stratification (rate of change of 0.5degreeC m−1 or greater), as observed in instrumented buoy temperature profiles available from the Global Lakes Ecological Observatory Network database (GLEON, http:ororwww.gleon.org). According to buoy data temperature profiles, CB mixed a minimum of nine times over the sampling season in 2005.Bacterial cells were immediately recovered from 100 to 250 ml of lake sample water by filtration onto a 0.2 μm polyestersulfone filter (Pall, New York, NY), and stored at −80degreeC until further processing.Mean difference in DO and temperature for each layer was calculated by averaging the profile observations included in the layer of interest for each sample date, and then subtracting the average of the hypolimnion profile from the epilimnion. These differences were then averaged over the entire sampling period when a global mean was desired.Additional physical and chemical data for TB and CB were provided by the North Temperate Lakes Long-term Ecological Research (NTL-LTER) and the Center for Limnology at University of Wisconsin-Madison.
NTL Keyword
Short Name
3BOG05
Version Number
18

Microbial Observatory at North Temperate Lakes LTER North Sparkling Bog Experiment 2007 - 2009

Abstract
For lake microbes, water column mixing acts as a disturbance because it homogenizes thermal and chemical gradients known to define the distributions of microbial taxa. Our first objective was to isolate hypothesized drivers of lake bacterial response to water column mixing. To accomplish this, we designed an enclosure experiment with three treatments to independently test key biogeochemical changes induced by mixing: oxygen addition to the hypolimnion, nutrient addition to the epilimnion, and full water column mixing. We used molecular fingerprinting to observe bacterial community dynamics in the treatment and control enclosures, and in ambient lake water. We found that oxygen and nutrient amendments simulated the physical-chemical water column environment following mixing and resulted in similar bacterial communities to the mixing treatment, affirming that these were important drivers of community change. These results demonstrate that specific environmental changes can replicate broad disturbance effects on microbial communities. Our second objective was to characterize bacterial community stability by quantifying community resistance, recovery and resilience to an episodic disturbance. The communities in the nutrient and oxygen amendments changed quickly (had low resistance), but generally matched the control composition by the 10th day after treatment, exhibiting resilience. These results imply that aquatic bacterial assemblages are generally stable in the face of disturbance.
Dataset ID
294
Date Range
-
Metadata Provider
Methods
Experimental designThe experiment was conducted from 16 to 26 June 2008. In the first treatment, oxygen was added to the hypolimnion. In the second, nutrients were added to the epilimnion. The third treatment simulated a mixing event (overturn). There also was a control enclosure with no treatment and sampling of the ambient lake water. Throughout this manuscript, we refer to these as Oxygen, Nutrient, Mix, Control and Ambient.Twelve limnocorrals were constructed as enclosures for the experiment. Each limnocorral was cylindrical and extended vertically from the surface of the lake to the sediment (approximately 4 m). The total volume was approximately 5050 l. Details of limnocorral construction are provided in online Supporting Information.The limnocorrals were deployed on 15 June 2008 to allow the sediment and water column to stabilize before treatment on 16 June 2008. The limnocorrals were deployed in a random spatial arrangement throughout the lake, at a maximum depth of 3.25 to 3.5 m. Replicates from each treatment were instrumented with a chain of HOBO temperature sensors (Onset), and one replicate from each had a self-logging DO sonde (Yellow Springs Incorporated) in the hypolimnion (3 m depth). More thermistors were deployed in the Oxygen and Mix treatments because thermal stratification was important for evaluating success of these treatments.For the Mix treatment, a 60 cm flat disk was raised and lowered between 3.5 m depth and the lake surface. Holes were drilled through the disk surface to increase turbulence (Sanford, 1997; Regel et al., 2004). A brick was tied underneath the disk to maintain stability. We manually oscillated the disk every 10 min for 1 h and then, after a 1 h break, continued for an additional hour. Temperature and DO profiles were monitored within the limnocorral with a hand-held probe to track mixing progress.The goal of the Oxygen treatment was to aerate the hypolimnion water without allowing it to mix with the epilimnion. This treatment was achieved by pumping hypolimnion water from the bottom of the limnocorral into an external cooler where the water was aerated with bubble diffusers, and then returned to the bottom of the limnocorral (Fig. S1). Valves on a compressed air cylinder were used to control the delivery of air to the coolers. One cooler was maintained for each replicate limnocorral. Thermally insulated tubing was used to transport water. A thermistor was deployed in each cooler to ensure ambient hypolimnion temperature was maintained. The water was removed and returned using two linear diffusers that were 0.6 m in length, spanning a depth range of approximately 2.5–3.1 m within the hypolimnion. The diffusers faced inward with 0.5 m fixed distance between them, retained by a plastic divider. This treatment was applied continuously over 3 h, until DO concentrations increased.The Nutrient treatment was achieved by adding ammonium chloride (NH4Cl) and potassium phosphate monobasic (KH2PO4) as N and P sources. These compounds were chosen because they are commonly bioavailable sources of nutrients. P was added to the epilimnion to achieve a final concentration of 3 micro g P l−1, which was approximately the average concentration expected in the mixed water column. This value was based on nutrient analyses from integrated water collected on 9 June 2008 in North Sparkling Bog, a week prior to experiment start. Similarly, N was added to achieve a final concentration of 70 µg N l−1. The limnocorral s epilimnion volume (0–2 m integrated depth) was calculated to be 2520 l, and we used the molar mass to determine the amount of each nutrient added to the epilimnion to achieve the expected mixed concentration. Dry chemicals were dissolved into to 500 ml of surface water from each limnocorral, and then added into each separately. Rationale for directly manipulating only one layer in the Oxygen and Nutrient treatments is given in the online Supporting Information.The Control limnocorrals were left undisturbed. To prevent mixing during equipment removal, all tubing was left inside the limnocorrals until the experiment ended.
Short Name
NB0789
Version Number
13

Microbial Observatory at North Temperate Lakes LTER Mendota Six Years Bacterial Community Composition 2000 - 2005

Abstract
We investigated patterns of intra- and interannual change in pelagic bacterial community composition (BCC), assessed using automated ribosomal intergenic spacer analysis) over six years in eutrophic Lake Mendota, Wisconsin. A regular phenology was repeated across years, implying that freshwater bacterial communities are more predictable in their dynamics than previously thought. Seasonal events, such as water column mixing andtrends in water temperature, were most strongly related to BCC variation. Communities became progressively less similar across years between the months of May and September, when the lake was thermally stratified. Dissolved oxygen and nitrate + nitrite concentrations were highly correlated to BCC change within and across seasons. The relationship between BCC and seasonal drivers suggests that trajectories of community change observed over long time series will reflect large-scale climate variation.
Core Areas
Dataset ID
293
Data Sources
Date Range
-
Maintenance
complete
Metadata Provider
Methods
Sampling Frequency: bi-weekly during ice-off from 2000 to 2005Total number of observations: 82Number of sites: 1 site over the deep hole of the lake (Lake Mendota, 89degree 24 W long, 43degree 06 N lat)Sampling techniques: integrated 0-12 mNomenclature:Lake name is ME. Sample IDs are ME-date with date = MM-DD-YY.DNA extraction protocol: FastPrep DNA extraction kitBinning protocol: Manual in GeneScanorGenotyperCapillary Instrument (from Biotech Center): ABI 3700PCR DNA standardization protocol: By volume of lake water filteredPCR thermocycler protocol:RISA30x protocol: 2 min 94C, [35s. Denature 94C, 45 s. Annealing 55C, 2 min Extension 72C (rep 30x)], 2 min extension 72C.Analyses performed other than ARISA:Additional comments:Raw ABI files are in two batchesBatch 1: Duplicate samples from 2000-2004 with nomenclature basically the same as the sample IDs plus the replicate number, such as ME 2-28-02 rep1. Note that the month is not 2-digit unless it has two digits.Batch 2: Duplicate samples from 2000-2005 with nomenclature as ME-date where date is DD-month-YY and the replicate number, such as ME 27Apr00 rep1.NOTE: We are not sure which samples were used for the final analysis. They must have been a blend of the two batches. Contact Ashley Shade (ashley17061atgmail.com) for clarification if needed.
Short Name
ME0005
Version Number
17

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.
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