Browsing by Author "Hansen, Gretchen JA"

Now showing 1 - 7 of 7
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    Data and R code for a zooplankton ethanol storage correction factor.
    (2023-04-05) Blechinger, Tristan; Link, Denver; Nelson, Jenna KR; Hansen, Gretchen JA; blech024@umn.edu; Blechinger, Tristan; University of Minnesota Department of Fisheries, Wildlife, and Conservation Biology
    This data set contains fresh and ethanol fixed zooplankton samples collected from five Minnesota lakes during June 2022. The data were collected with five paired sites at each lake. The samples were filtered to remove detritus, phytoplankton, and predatory invertebrates. After filtering, each sample was split between fresh processing and ethanol storage. Ethanol storage samples remained in storage for approximately one month. Samples were sent to the UC-Davis Stable Isotope Facility for analysis. Stable isotope values in addition to lake name, DOW, and site of collection are included in the data file. Bayesian Hierarchical models were used to establish correction factors for ethanol storage. Statistical analysis was performed using the R package brms and model output can be found in respective .rds files. Details for each file can be found in the readme file.
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    Data and R code for analysis of mercury concentration and food web differences in walleye and yellow perch from Minnesota lakes with and without invasive zebra mussels, 2019 - 2021
    (2023-02-24) Blinick, Naomi S; Ahrenstorff, Tyler D; Bethke, Bethany J; Fleishman, Abram B; Link, Denver; Nelson, Jenna KR; Rantala, Heidi M; Rude, Claire L; Hansen, Gretchen JA; nsblinick@gmail.com; Blinick, Naomi S; University of Minnesota Department of Fisheries, Wildlife, Conservation Biology; Minnesota Department of Natural Resources
    This dataset contains δ13C and δ15N stable isotope data for 3,765 biological samples (fish, littoral macroinvertebrates, and zooplankton) collected from 21 lakes between 2019 and 2021, collaboratively by the University of Minnesota and the Minnesota Department of Natural Resources. In addition, 403 samples have corresponding mercury data, based on laboratory analyses conducted by USGS (Tate et al. 2022).
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    Data in support of: Quantifying resilience of coldwater habitat to climate and land use change to prioritize watershed conservation
    (2021-08-06) Hansen, Gretchen JA; Wehrly, Kevin E; Vitense, Kelsey; Walsh, Jacob R; Jacobson, Peter C; ghansen@umn.edu; Hansen, Gretchen; University of Minnesota Department of Fisheries, Wildlife, Conservation Biology; Minnesota Department of Natural Resources; Michigan Department of Natural Resources
    Data for 12,450 lakes in the Upper Midwestern United States used to predict coldwater, oxygenated habitat and how it is predicted to change under scenarios of climate and land use change. Specific fields include lake size, depth, watershed landuse, air temperature characteristics, and presence of the coldwater fish Cisco (Coregonus artedi). Also included are projected air temperatures under mid-Century conditions for each lake.
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    Digitization of Minnesota and Wisconsin bathymetric maps resulting in hypsographic data
    (2020-09-09) Rounds, Christopher I; Hansen, Gretchen JA; Vitense, Kelsey; Van Pelt, Amanda; round060@umn.edu; Rounds, Christopher; University of Minnesota Fisheries Ecosystem Ecology Lab
    The data set includes hypsographic data (area-at-depth) for over 750 Minnesota and Wisconsin lakes throughout the states. The majority of these lakes (650+) did not have publicly available hypsography. The hypsography was derived by digitizing bathymetric DNR maps using ImageJ. One hundred Minnesota lakes were selected that had DNR hypsographic data (in the form of a DEM) available and a comparison between the hypsographic data derived from DEMs and ImageJ was completed. These results, as well as code and hypsographic data is all available. The purpose of this work was to release broad scale lake area-at-depth data for limnological and aquatic biology studies.
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    Isotopic Correction Factors for Zooplankton Storage
    (2023) Blechinger, Tristan; Link, Denver; Nelson, Jenna KR; Hansen, Gretchen JA
    Stable isotope analysis is an increasingly popular method of food web monitoring and is leading to an increased understanding of how energy and pollutants move within an ecosystem. This technique involves the use of δ13C and δ15N stable isotopes for specific dietary tracking among trophic levels based on their present ratios; in aquatic ecosystems, zooplankton are frequently used to represent the baseline pelagic trophic level. Upon collection, zooplankton samples are often preserved in ethanol prior to processing and analysis. However, this method has varying effects on isotopic signatures of tissues, leading to a potentially inaccurate isotopic position. In order to determine a correction factor to account for ethanol preservation, zooplankton were collected at 25 sites across five Minnesota lakes. Zooplankton stable isotope data were analyzed using a mixed effects model that showed ethanol preservation leading to significant δ13C enrichment (SE = 0.064, t-value = 17.951) and no significant change in δ15N. The random lake effect had no significant impact on the outcome. This correction factor will enhance the accuracy and efficacy of stable isotope analysis for freshwater food webs by providing more reliable baseline isotope values upon which these studies rely, and provide a procedure for other correction factors to be determined.
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    Minnesota lake ice phenology
    (2024-06-04) Walsh, Jake R; Vitense, Kelsey; Rounds, Christopher I; Peter, Boulay; Blumenfeld, Kenneth; Hansen, Gretchen JA; round060@umn.edu; Rounds, Christopher I; University of Minnesota Fisheries Systems Ecology Lab
    This dataset contains ice in, ice out and ice duration data for Minnesota lakes that have been collated by the Minnesota Department of Natural Resources State Climatology Office. Lake ice has been recorded by lake associations, community members and scientists throughout Minnesota. The definition of lake ice in and out can vary from lake to lake but observers generally use consistent criteria for determining the day ice formation occurs or ice melts for a lake. For more information see the Minnesota DNR lake ice in (https://www.dnr.state.mn.us/ice_in/index.html) and ice out (https://www.dnr.state.mn.us/ice_out/index.html) websites.
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    Seasonal influence on detection probabilities for multiple aquatic invasive species using environmental DNA
    (2023-12-14) Rounds, Christopher; Arnold, Todd W; Chun, Chan Lan; Dumke, Josh; Totsch, Anna; Keppers, Adelle; Edbald, Katarina; García, Samantha M; Larson, Eric R; Nelson, Jenna KR; Hansen, Gretchen JA; round060@umn.edu; Rounds, Christopher; University of Minnesota Fisheries Systems Ecology Lab
    Aquatic invasive species (AIS) are a threat to freshwater ecosystems. Documenting AIS prevalence is critical to effective management and early detection. However, conventional monitoring for AIS is time and resource intensive and is rarely applied at the resolution and scale required for effective management. Monitoring using environmental DNA (eDNA) of AIS has the potential to enable surveillance at a fraction of the cost of conventional methods, but key questions remain related to how eDNA detection probability varies among environments, seasons, and multiple species with different life histories. To quantify spatiotemporal variation in the detection probability of AIS using eDNA sampling, we surveyed 20 lakes with known populations of four aquatic invasive species: Common Carp (Cyprinus carpio), Rusty Crayfish (Faxonius rusticus), Spiny Waterflea (Bythotrephes longimanus), and Zebra Mussels (Dreissena polymorpha). We collected water samples at 10 locations per lake, five times throughout the open water season. Quantitative PCR was used with species-specific assays to determine the presence of species DNA in water samples. Using Bayesian occupancy models, we quantified the effects of lake and site characteristics and sampling season on eDNA detection probability. These results provide critical information for decision makers interested in using eDNA as a multispecies monitoring tool and highlight the importance of sampling when species are in DNA releasing life history stages.