Browsing by Author "Bajcz, Alex W"

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    Data and R-code for "Aquatic Macrophyte and Water Quality Response to Aluminum Sulfate Treatments"
    (2025-03-05) Hembre, Kaitlyn; Newman, Raymond M; Bajcz, Alex W; Berg, Matt; James, William; newma004@umn.edu; Newman, Raymond; Minnesota Aquatic Invasive Species Research Center (MAISRC); water
    This study examines data from 6 lakes in Minnesota and 2 in Wisconsin to assess the response of aquatic plants and water quality to aluminum sulfate (alum) treatments. The dataset spans from 2011 to 2023 and includes measurements of total epilimnetic phosphorus, Secchi depths, and the frequency of native and invasive macrophyte species. Data were collected directly by project personnel but we also include data provided by project collaborators that were used in the formal analysis. Additional data collected by project personnel, including all point intercept aquatic plant data, temperature, light and dissolved oxygen profiles, and additional water chemistry data are included to facilitate further analysis in the future. Results indicate a marked reduction in total epilimnetic phosphorus levels and improved water clarity (Secchi) after alum treatment, with notable increases in native macrophyte occurrence. Invasive species such as curly-leaf pondweed decreased after alum treat, while Eurasian watermilfoil exhibited variable responses. This comprehensive dataset highlights the effectiveness of alum treatments in enhancing water quality and supporting macrophyte health, with considerations for ongoing invasive species management.
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    R Code, Data, and Output Supporting: A within-lake occupancy model for starry stonewort, Nitellopsis obtusa, to support early detection and monitoring
    (2022-12-19) Bajcz, Alex W; Glisson, Wesley; Larkin, Daniel J; Fieberg, John; bajcz003@umn.edu; Bajcz, Alex W; Minnesota Aquatic Invasive Species Research Center (MAISRC); Department of Fisheries, Wildlife, and Conservation Biology
    These data and files support the published paper "A within-lake occupancy model for starry stonewort, Nitellopsis obtusa, to support early detection and monitoring" | Scientific Reports (nature.com). It contains both input files and data as well as processed output files from the modeling effort described in the paper, which uses predictor variables to predict both occupancy and detection for within-lake locations by starry stonewort, an invasive aquatic macrophyte. The files being submitted include everything needed to fully replicate and further interpret our results and provide a framework for constructing similar models in similar contexts.