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Browsing by Author "Johnson, Lucinda"

Now showing 1 - 11 of 11
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    A Blueprint for Creating The Institute on the Environment for the University of Minnesota
    (University of MInnesota: Provost's Advisory Committee for the Institute on the Environment, 2006-09-25) Swackhamer, Deborah; Polasky, Stephen; Foufoula-Georgiou, Efi; Johnson, Lucinda; Kapuscinski, Anne; Karkkainen, Bradley; McMurry, Peter; Mulla, David; Reich, Peter; Thorleifson, Harvey; Tilman, David; Binks, Jonathan
    In the words of University of Minnesota President Robert H. Bruininks: “The environment poses such a broad and important array of interrelated issues that the participation of scholars from diverse fields will be critical to our efforts to understand and offer solutions to protect our natural world.” This document lays out the anticipated role, structure and operation, or “blueprint,” of a new University of Minnesota Institute on the Environment (IonE).
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    Detailed Hydrology for Stormwater BMPs
    (2020-03) Herb, William; Johnson, Lucinda; Gulliver, John
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    Ecosystem Services Technical Work Team Report: Minnesota Water Sustainability Framework, January 2011
    (University of Minnesota. Water Resources Center, 2011-01) Wright, Dave; Johnson, Lucinda
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    Environmental controls of wood entrapment in upper Midwestern streams
    (2010-07-20) Merten, Eric, C.; Finlay, Jacques; Johnson, Lucinda; Newman, Raymond; Stefan, Heinz; Vondracek, Bruce
    Wood deposited in streams provides a wide variety of ecosystem functions, including enhancing habitat for key species in stream food webs, increasing geomorphic and hydraulic heterogeneity and retaining organic matter. Given the strong role that wood plays in streams, factors that influence wood inputs, retention and transport are critical to stream ecology. Wood entrapment, the process of wood coming to rest after being swept downstream at least 10 m, is poorly understood, yet important for predicting stream function and success of restoration efforts. Data on entrapment were collected for a wide range of natural wood pieces (n D 344), stream geomorphology and hydraulic conditions in nine streams along the north shore of Lake Superior in Minnesota. Locations of pieces were determined in summer 2007 and again following an overbank stormflow event in fall 2007. The ratio of piece length to effective stream width (length ratio) and the weight of the piece were important in a multiple logistic regression model that explained 25% of the variance in wood entrapment. Entrapment remains difficult to predict in natural streams, and often may simply occur wherever wood pieces are located when high water recedes. However, this study can inform stream modifications to discourage entrapment at road crossings or other infrastructure by applying the model formula to estimate the effective width required to pass particular wood pieces. Conversely, these results could also be used to determine conditions (e.g. pre-existing large, stable pieces) that encourage entrapment where wood is valued for ecological functions.
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    Factors influencing wood mobilization in streams
    (2010) Merten, Eric; Finlay, Jacques; Johnson, Lucinda; Newman, Raymond; Stefan, Heinz; Vondracek, Bruce
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    Maps of wind-wave height on Minnesota lake shorelines
    (2022-01-27) Herb, William; Janke, Ben; Cai, Meijun; Stefan, Heinz; Johnson, Lucinda; herb0003@umn.edu; Herb, William; University of Minnesota St. Anthony Falls Lab; University of Minnesota Duluth Natural Resources Research Institute
    This data set provides maps of typical wind-wave height and energy on Minnesota lakes to inform shoreline and near-shore habitat restoration projects. The data set consists of a set of ArcMap shape files which map out simulated wave height and energy parameters for a series of points around the shoreline of 460 lakes in Minnesota, with separate files for annual wave statistics and monthly wave statistics. The wave statistics were calculated for each lake based on airport wind data and the open water distance (fetch) across the lake for each wind direction. Each shapefile contains information on multiple wave statistics, including the mean and significant wave height, the number of days wave height exceeds thresholds, and cumulative wave energy over the time period.
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    Measuring what matters: Assessing the full suite of benefits of OHF investments
    (2021-01-08) Noe, Ryan; Locke, Christina; Host, George; Gorzo, Jessica; Johnson, Lucinda; Lonsdorf, Eric; Grinde, Alexis; Joyce, Michael; Bednar, Josh; Dumke, Josh; Keeler, Bonnie
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    Minnesota Restorable Wetland Index
    (2024-01-11) Johnson, Lucinda; Bartsch, Will; Kovalenko, Katya; Kloiber, Steve; Nixon, Kristi; wbartsch@d.umn.edu; Bartsch, Will; Natural Resources Research Institute
    The Minnesota Restorable Wetland Index (RWI) was developed by the Natural Resources Research Institute (NRRI) in collaboration with the Minnesota Department of Natural Resources (MN DNR). The RWI was developed statewide on a 3m grid by applying machine learning models to predict the location of existing and restorable wetlands based on hydrological, geomorphological, and geological variables. Post-processing was done to remove existing wetlands and smooth the results. This data layer replaces the original NRRI Restorable Wetland Inventory that was developed statewide on a 30m grid using a different methodology.
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    Quantifying Wave Energy on Minnesota Lakes
    (2022-01) Herb, William; Janke, Ben; Stefan, Heinz; Cai, Meijun; Johnson, Lucinda
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    Restorable Wetland Decision Support Data, 2014
    (2024-02-01) Johnson, Lucinda; Brady, Valerie; Erickson, Jeremy; Brown, Terry; Gernes, Mark; ljohnson@d.umn.edu; Johnson, Lucinda; Natural Resources Research Institute
    The Minnesota Restorable Wetland Decision Support Data were developed in combination with the Minnesota Restorable Wetland Index to: predict likely locations of restorable wetlands; locate highly stressed areas most in need of water quality or habitat improvement; prioritize areas that already are or are most likely to result in high functioning, sustainable wetlands; identify areas that will provide the greatest benefits in the form of water quality and habitat. Data include: Minnesota Restorable Wetland Decision Support - Viability, Minnesota Restorable Wetland Decision Support - Water Quality Benefits, Minnesota Restorable Wetland Decision Support - Habitat Stress, Minnesota Restorable Wetland Decision Support - Habitat Benefits, Minnesota Restorable Wetland Decision Support - Nitrogen Stress, and Minnesota Restorable Wetland Decision Support - Phosphorus Stress. This data had previously been available within the Minnesota Restorable Wetland Prioritization Tool (2013-2024).
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    Watershed-based Stressors for the Great Lakes Basin
    (2024-01-11) Host, George; Kovalenko, Katya; Brown, Terry; Johnson, Lucinda; Ciborowski, Jan; ljohnson@d.umn.edu; Johnson, Lucinda; Natural Resources Research Institute
    The Watershed-based Stressors for the Great Lakes Basin dataset includes component and aggregated measures of environmental stress to coastal ecosystems from watersheds of the Great Lakes Basin. Stressors include the amount of agricultural and developed land use, as well as road and population density. These summaries are based on a set of 5971 watersheds that cover the US and Canadian Great Lakes basin, derived using methods from Hollenhorst et al. (2007). Indices presented in this dataset include SumRel (Host et al. 2011) and the more recent combined Agriculture and Development - AgDev index (Host et al. 2019). These were developed as part of the Great Lakes Environmental Indicators II (GLEI-II) project, funded through the Great Lakes Restoration Initiative and used to quantify the response of biota (birds, fish, macroinvertebrates, diatoms and wetland vegetation) to varying degrees of watershed stress (Kovalenko et al. 2014). As of 2015, a more recent version of watersheds has been created by the Great Lakes Aquatic Habitat Framework and stressors recalculated based on those watersheds.