US Long-Term Ecological Research Network

Lake Mendota Multiparameter Sonde Profiles: 2017 - current

Abstract
Intermittent sensor profiling at the deep hole of Lake Mendota began in 2017 with a YSI EXO2 multiparameter sonde. Parameters include water temperature, pH, specific conductivity, dissolved oxygen, chlorophyll, phycocyanin, turbidity, and fDOM. Profiles are nominally 0 - 20 meters in depth in one meter increments, although the depth range and increments vary.

Core Areas
Dataset ID
400
Date Range
-
Instrumentation
YSI EXO2 Sonde
Maintenance
on-going
Methods
see abstract
Publication Date
Version Number
3

North Temperate Lakes LTER Regional Survey water temperature DO 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.
Water temperature and dissolved oxygen profiles were taken on sampling days.
Contact
Dataset ID
382
Date Range
-
Maintenance
ongoing
Methods
water temperature and dissolved oxygen were measured at 1 meter intervals with a opto sonde
Version Number
1

North Temperate Lakes LTER Regional Survey Water Color Scans 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. Color is measured in water samples that are filtered in the field through 0.45 um nucleopore membrane filters. A spectrophotometer is used to quantify color in the lab as absorbance (unitless) at 1 nm intervals between the wavelengths of 200 and 800 nm. Absorbance data are considered suspect for values greater than 2.
Dataset ID
377
Date Range
-
LTER Keywords
Methods
We collect water samples for color at the deepest part of the lakes. The samples are surface water, filtered in the field through 0.45u polycarbonate membrane filters. We run a wavelength scan from 800 to 200nm, using a 5cm rectangular quartz cell in a Beckman Coulter Model DU800 spectrophotometer. Any samples that display absorbance values above 2AU are run again from 400 to 200nm using a 1cm quartz cuvette. Inititally the full range of wavelengths were run again and two values may be found in the database even if the original measurement with the large cuvette did not exceed 2AU. The user should discard values above 2AU and use values from the smaller cuvette instead. All values are given as measurements at the path lenth of the employed cuvette and need to be devided by the cuvette length for a comparable value at a pathlength of 1 cm.

The single beam Beckman Coulter DU800 spec is blanked first on a sample of DI water. Additional blank values are from a scan run on DI after that blanking as a check and are reported alongside the scans but are not subtracted from the scan values.
Version Number
3

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

Abstract
High frequency continuous data for temperature, dissolved oxygen, pH, chlorophyll a, and phycocyanin 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
Dataset ID
371
Date Range
-
LTER Keywords
Maintenance
complete
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.
In Paul, Peter and Tuesday lakes two sondes were deployed at 0.75 meters near lake center. One sonde was a Hydrolab (model DS5X) with temperature, oxygen, pH, phycocyanin, and chlorophyll a sensors. One sonde was a Yellow Springs Instruments (YSI) 6600-V2-4 with temperature, dissolved oxygen, pH, phycocyanin, and chlorophyll a sensors. Measurements were made every five minutes. Brief gaps in the data record due to calibration or sensor malfunction were interpolated using a bivariate autoregressive state-space model with the MARSS package in R version 3.9 to create a continuous daily time series.
Version Number
1

Ground water levels for 964 monitoring wells in Wisconsin, 1929 - 2015

Abstract
This dataset contains the daily groundwater level observations and other monitoring well attributes in Wisconsin. It covers 964 groundwater level monitoring wells and has 400,812 observations. The time span of this dataset is between February 2nd, 1929 and December 31st, 2015. The data sources include United States Geological Survey (USGS), Wisconsin Department of Natural Resources (WDNR), University of Wisconsin Extension, counties in Central Sands area, and North Temperate Lakes - Long-Term Ecological Research (NTL-LTER).
The data compilation consists of three major steps. First, the data were retrieved from different data sources. Then the data from different sources were pooled together. No well was monitored by more than one entity so none of the wells’ records were merged. Third, two rounds of quality assurance and quality control (QAQC) were conducted.
Wells in confined aquifers were not included in this dataset. The values of the USGS and Central Sands data are the depth to the water whereas LTER values are mean sea level elevations of the groundwater levels. These data could not be directly compared with each other.
This data compilation was funded by the Wisconsin Groundwater Joint Solicitation.
Dataset ID
363
Date Range
-
LTER Keywords
Methods
For detailed methods of data gathering, cleaning and compiling see attached pdf file.
Version Number
2

Lake Water Level observations for 1036 lakes in Wisconsin, 1900 - 2015

Abstract
This dataset contains the daily lake level observations and other lake attributes in Wisconsin. It covers 1036 lakes including 461 seepage lakes and 575 drainage lakes. It has 342,319 observations. The time span of this dataset is between January 1st, 1900 and December 31st, 2015. The data sources include USGS, Wisconsin Department of Natural Resources, North Temperate Lakes-Long Term Ecological Research (NTL-LTER), North Lakeland Discovery Center, Waushara County, and City of Shell Lake. Wisconsin Department of Natural Resources has two data sources: historical lake levels recorded in paper files and a recently-initiated citizen monitoring program. The latter are stored in Wisconsin DNR’s Surface Water Integrated Monitoring System (SWIMS).
The data compilation consists of four major steps. First, data were retrieved from different data sources. Then data from different sources but for the same lakes were tied together using the datum information if possible. The WISCID is used to denote unique data sets by lake and data source. If two data sources could be tied to the same datum, they share a WISCID. Third, three rounds of quality assurance and quality control (QAQC) were conducted. Finally, more attributes such as lake area, lake depth, and lake type were added to the lakes. This data compilation was funded by the Wisconsin Groundwater Joint Solicitation.

Dataset ID
362
Date Range
-
LTER Keywords
Methods
Data were compiled from many sources, each was quality controlled and merged into this dataset. For detailed methods see attached PDF file.
Version Number
4

North Temperate Lakes LTER Estimated winter inputs of stream water and groundwater to primary study lakes 1983 - 2014

Abstract
This data set integrates and summarizes daily surface and groundwater inputs to 5 primary study lakes, using model estimates from a data-driven USGS hydrologic model (Hunt et al. 2013; Hunt and Walker 2017), and ice phenology data (number of days since ice-on). The lakes are Allequash, Big Muskellunge, Crystal, Sparkling, and Trout. Powers et al. (2017) used these data to estimate upper and lower bounds for exogenous chemical inputs to the lakes during winter. For a given lake and winter year, cumulative surface water and groundwater inputs were calculated across the ice cover period. For each lake, this data set reports the mean, maximum, and minimum winter water inputs observed across years, in units of water volume, % of average lake volume, and volume per winter day.Sampling Frequency: 1 per lake, with multiple summary values reported (i.e., mean, min, max). Number of sites: 5Hunt, R.J. et al., 2013. Simulation of Climate - Change effects on streamflow, Lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin. USGS Scientific Investigations Report., pp.2013-5159. Available at: https://www.researchgate.net/publication/258363719_Simulation_of_Climate-Change_Effects_on_Streamflow_Lake_Water_Budgets_and_Stream_Temperature_Using_GSFLOW_and_SNTEMP_Trout_Lake_Watershed_WisconsinHunt, R.J., and Walker, J.F., 2017, GSFLOW groundwater-surface water model 2016 update for the Trout Lake Watershed, Wisconsin: U.S. Geological Survey data release, https://dx.doi.org/10.5066/F7M32SZ2Powers SM, Labou SG, Baulch HM, Hunt RJ, Lottig NR, Hampton SE, Stanley EH. In press (expected 2017). Ice duration drives winter nitrate accumulation in north temperate lakes. Limnology and Oceanography Letters.
Dataset ID
340
Data Sources
Date Range
-
LTER Keywords
Methods
This dataset is a compilations of:
USGS hydrologic model estimates (Hunt et al. in preparation)
and
North Temperate Lakes LTER: Ice Duration - Trout Lake Area 1981 - current
https://lter.limnology.wisc.edu/dataset/north-temperate-lakes-lter-ice-duration-trout-lake-area-1981-current
Version Number
7

Lake Mendota water temperature secchi depth snow depth ice thickness and meterological conditions 1894 - 2007

Abstract
Data for water temperature at different depth and different frequencies assembled from various sources by Dale Roberson. A table with additional parameters collected at the same time is also provided for dates when available. These parameters are weather observations, secchi depth, snow and ice depths.
Dataset ID
335
Date Range
-
Methods
Data were assembled from different collectors, names are given in metadata. Measurements were conducted by hand.
NTL Keyword
Version Number
14

CLA Yahara Lakes Citizen Offshore Water Quality Monitoring 2016 - 2017

Abstract
In 2013, Clean Lakes Alliance (CLA) launched a Citizen Water Quality Monitoring pilot. Objectives included evaluating and tracking nearshore water quality conditions on all five Yahara lakes: Lakes Mendota, Monona, Waubesa, Kegonsa and Wingra. In 2016, in order to fully understand the interaction between the offshore and nearshore
environment, CLA volunteers will begin sampling the deepest point (deep hole) of all Yahara lakes. The offshore monitoring program will focus on two components: water clarity sampling and dissolved oxygen and temperature measurement. Data from the offshore monitoring program will be compared to data from the nearshore program.
Contact
Creator
Dataset ID
330
Date Range
-
Methods
On Lakes Mendota, Monona, Waubesa, Kegonsa and Wingra, volunteers will use a Secchi disk to measure water clarity, and a digital handheld thermometer to measure air and surface water temperatures once per week on Thursday mornings . Secchi depth monitoring will take place at the deepest point of each lake. On Lakes Monona and Waubesa, concurrent with Secchi sampling, volunteers will use a YSI 550A multiprobe meter to measure dissolved oxygen and temperature at multiple depths. All volunteers are trained by Clean Lakes Alliance staff.
Version Number
2

Lake ice seasonality over the past 320 to 570 years

Abstract
Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.
Contact
Dataset ID
327
Date Range
-
Methods
Please see Sharma, S. et al. Direct observations of ice seasonality reveal changes in climate over the past 320–570 years. Sci. Rep. 6, 25061; doi: 10.1038/srep25061 (2016).
Version Number
14
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