{"id":{"repo_id":"umn","oai_identifier":"oai:conservancy.umn.edu:11299/277990"},"canonical_url":"https://search.dev.ndltd.org/etd/umn/oai:conservancy.umn.edu:11299/277990","repository":{"repo_id":"umn","name":"University of Minnesota","base_url":"https://conservancy.umn.edu/server/oai/request"},"display":{"title":"Optimizing a long-term monitoring program to track toxic cyanobacteria blooms in a Great Lakes estuary","abstract":"Recent observations indicate cyanobacterial harmful algal blooms (cHABs) have become increasingly frequent and severe in the St. Louis River Estuary (SLRE) since 2018. Given the novelty of cHABs in the SLRE, the locations, timing, and environmental conditions associated with past cHABs have remained largely unknown, complicating efforts to establish comprehensive but resourceful monitoring of cHAB-relevant data. We aimed to answer several questions in an effort to optimize future monitoring: (1) What are the critical environmental parameters that should be measured, and how do environmental conditions in the SLRE relate to cyanobacteria biovolume and phytoplankton community structure? (2) What temporal resolution and sampling window should a future monitoring program use, and can lagged effects of environmental conditions be used to predict cHABs? (3) What locations should be monitored to capture spatial heterogeneity in environmental conditions and phytoplankton communities? We employed a high-frequency oversampling approach from fall 2022 through fall 2024 at eight spatially heterogeneous SLRE stations. Random forest analysis in conjunction with constrained ordination were used to examine relationships between phytoplankton and water quality. Warm, late-summer temperatures were an important predictor of cyanobacteria, but nitrogen and other drought-mediated variables may have determined dominant cyanobacteria species, carrying implications in a changing climate. Analysis of water quality and phytoplankton variability combined with artificial reduction of sampling frequency revealed no ideal sampling frequency, but late-summer, weekly sampling and as-needed bloom response collections were deemed critical for tracking cHABs. A 30-40-day lag effect between water temperature and cyanobacterial abundance suggested temperature may be an early summer predictor of bloom intensity. Spatial redundancy analysis indicated that water quality was much more heterogeneous throughout the SLRE compared to phytoplankton communities, and a smaller subset of sites could be monitored going forward, though greater spatial coverage may be needed at times of peak cHAB occurrence. Our findings inform an optimized approach to monitoring in the SLRE that can be iteratively refined in future work. Focused monitoring optimization efforts such as this should be applied elsewhere to track risk from cHABs and other stressors.","abstract_html":"Recent observations indicate cyanobacterial harmful algal blooms (cHABs) have become increasingly frequent and severe in the St. Louis River Estuary (SLRE) since 2018. Given the novelty of cHABs in the SLRE, the locations, timing, and environmental conditions associated with past cHABs have remained largely unknown, complicating efforts to establish comprehensive but resourceful monitoring of cHAB-relevant data. We aimed to answer several questions in an effort to optimize future monitoring: (1) What are the critical environmental parameters that should be measured, and how do environmental conditions in the SLRE relate to cyanobacteria biovolume and phytoplankton community structure? (2) What temporal resolution and sampling window should a future monitoring program use, and can lagged effects of environmental conditions be used to predict cHABs? (3) What locations should be monitored to capture spatial heterogeneity in environmental conditions and phytoplankton communities? We employed a high-frequency oversampling approach from fall 2022 through fall 2024 at eight spatially heterogeneous SLRE stations. Random forest analysis in conjunction with constrained ordination were used to examine relationships between phytoplankton and water quality. Warm, late-summer temperatures were an important predictor of cyanobacteria, but nitrogen and other drought-mediated variables may have determined dominant cyanobacteria species, carrying implications in a changing climate. Analysis of water quality and phytoplankton variability combined with artificial reduction of sampling frequency revealed no ideal sampling frequency, but late-summer, weekly sampling and as-needed bloom response collections were deemed critical for tracking cHABs. A 30-40-day lag effect between water temperature and cyanobacterial abundance suggested temperature may be an early summer predictor of bloom intensity. Spatial redundancy analysis indicated that water quality was much more heterogeneous throughout the SLRE compared to phytoplankton communities, and a smaller subset of sites could be monitored going forward, though greater spatial coverage may be needed at times of peak cHAB occurrence. Our findings inform an optimized approach to monitoring in the SLRE that can be iteratively refined in future work. Focused monitoring optimization efforts such as this should be applied elsewhere to track risk from cHABs and other stressors.","abstract_has_math":false,"creators":["Birschbach, Peter"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-08","date_published":"2025-08","updated_at":"2026-07-24T05:19:52Z","subjects":["algal blooms","aquatic ecology","cHABs","cyanobacteria","monitoring","phytoplankton","Plan As (thesis-based master's degrees)","Master of Science","Master of Science in Water Resources Science","Swenson College of Science and Engineering","University of Minnesota Duluth"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/11299/277990","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Birschbach, Peter"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-02-03T19:56:19Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-08"]},{"key":"dc:type","label":"Dc Type","values":["Thesis or Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["algal blooms","aquatic ecology","cHABs","cyanobacteria","monitoring","phytoplankton","Plan As (thesis-based master's degrees)","Master of Science","Master of Science in Water Resources Science","Swenson College of Science and Engineering","University of Minnesota Duluth"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/11299/277990"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["University of Minnesota M.S. thesis. August 2025. Major: Water Resources Science. Advisor: Euan Reavie. 1 computer file (PDF); v, 99 pages."]},{"key":"dc:description.abstract","label":"Abstract","values":["Recent observations indicate cyanobacterial harmful algal blooms (cHABs) have become increasingly frequent and severe in the St. Louis River Estuary (SLRE) since 2018. Given the novelty of cHABs in the SLRE, the locations, timing, and environmental conditions associated with past cHABs have remained largely unknown, complicating efforts to establish comprehensive but resourceful monitoring of cHAB-relevant data. We aimed to answer several questions in an effort to optimize future monitoring: (1) What are the critical environmental parameters that should be measured, and how do environmental conditions in the SLRE relate to cyanobacteria biovolume and phytoplankton community structure? (2) What temporal resolution and sampling window should a future monitoring program use, and can lagged effects of environmental conditions be used to predict cHABs? (3) What locations should be monitored to capture spatial heterogeneity in environmental conditions and phytoplankton communities? We employed a high-frequency oversampling approach from fall 2022 through fall 2024 at eight spatially heterogeneous SLRE stations. Random forest analysis in conjunction with constrained ordination were used to examine relationships between phytoplankton and water quality. Warm, late-summer temperatures were an important predictor of cyanobacteria, but nitrogen and other drought-mediated variables may have determined dominant cyanobacteria species, carrying implications in a changing climate. Analysis of water quality and phytoplankton variability combined with artificial reduction of sampling frequency revealed no ideal sampling frequency, but late-summer, weekly sampling and as-needed bloom response collections were deemed critical for tracking cHABs. A 30-40-day lag effect between water temperature and cyanobacterial abundance suggested temperature may be an early summer predictor of bloom intensity. Spatial redundancy analysis indicated that water quality was much more heterogeneous throughout the SLRE compared to phytoplankton communities, and a smaller subset of sites could be monitored going forward, though greater spatial coverage may be needed at times of peak cHAB occurrence. Our findings inform an optimized approach to monitoring in the SLRE that can be iteratively refined in future work. Focused monitoring optimization efforts such as this should be applied elsewhere to track risk from cHABs and other stressors."]},{"key":"dc:title","label":"Title","values":["Optimizing a long-term monitoring program to track toxic cyanobacteria blooms in a Great Lakes estuary"]}]}],"canonical_facts":{"dc:creator":["Birschbach, Peter"],"dc:date.accessioned":["2026-02-03T19:56:19Z"],"dc:date.issued":["2025-08"],"dc:description":["University of Minnesota M.S. thesis. August 2025. Major: Water Resources Science. Advisor: Euan Reavie. 1 computer file (PDF); v, 99 pages."],"dc:description.abstract":["Recent observations indicate cyanobacterial harmful algal blooms (cHABs) have become increasingly frequent and severe in the St. Louis River Estuary (SLRE) since 2018. Given the novelty of cHABs in the SLRE, the locations, timing, and environmental conditions associated with past cHABs have remained largely unknown, complicating efforts to establish comprehensive but resourceful monitoring of cHAB-relevant data. We aimed to answer several questions in an effort to optimize future monitoring: (1) What are the critical environmental parameters that should be measured, and how do environmental conditions in the SLRE relate to cyanobacteria biovolume and phytoplankton community structure? (2) What temporal resolution and sampling window should a future monitoring program use, and can lagged effects of environmental conditions be used to predict cHABs? (3) What locations should be monitored to capture spatial heterogeneity in environmental conditions and phytoplankton communities? We employed a high-frequency oversampling approach from fall 2022 through fall 2024 at eight spatially heterogeneous SLRE stations. Random forest analysis in conjunction with constrained ordination were used to examine relationships between phytoplankton and water quality. Warm, late-summer temperatures were an important predictor of cyanobacteria, but nitrogen and other drought-mediated variables may have determined dominant cyanobacteria species, carrying implications in a changing climate. Analysis of water quality and phytoplankton variability combined with artificial reduction of sampling frequency revealed no ideal sampling frequency, but late-summer, weekly sampling and as-needed bloom response collections were deemed critical for tracking cHABs. A 30-40-day lag effect between water temperature and cyanobacterial abundance suggested temperature may be an early summer predictor of bloom intensity. Spatial redundancy analysis indicated that water quality was much more heterogeneous throughout the SLRE compared to phytoplankton communities, and a smaller subset of sites could be monitored going forward, though greater spatial coverage may be needed at times of peak cHAB occurrence. Our findings inform an optimized approach to monitoring in the SLRE that can be iteratively refined in future work. Focused monitoring optimization efforts such as this should be applied elsewhere to track risk from cHABs and other stressors."],"dc:identifier.uri":["https://hdl.handle.net/11299/277990"],"dc:language.iso":["en"],"dc:subject":["algal blooms","aquatic ecology","cHABs","cyanobacteria","monitoring","phytoplankton","Plan As (thesis-based master's degrees)","Master of Science","Master of Science in Water Resources Science","Swenson College of Science and Engineering","University of Minnesota Duluth"],"dc:title":["Optimizing a long-term monitoring program to track toxic cyanobacteria blooms in a Great Lakes estuary"],"dc:type":["Thesis or Dissertation"]},"updated_at":"2026-07-24T05:19:52Z"}