2023 UMSRS Poster Presentations

2023 UMSRS Poster Abstract Guide. Links to posters are provided as possible



P-01: Unintended Impacts of Stream Habitat Construction

Deserae Hendrickson, Minnesota Department of Natural Resources Area Fisheries Supervisor


A Knife River, Minnesota case study of impacts to fish populations and altered stream temperature conditions correlated with a large two year habitat project construction upstream of a long-term monitoring station. The project area covered approximately 4000 feet of stream, starting about ¼ mile above the index station. This station has been monitored annually since 1997 for both hourly summer water temperatures (June through September) and trout populations utilizing backpack electrofishing. Changes observed in the Knife River are compared with index stations on three other streams in the management area where construction disturbance did not occur.



P-02: Water Quality Screening in the Driftless Area, Using Community Scientists and the WiseH2O Mobile App
Kent Johnson Trout Unlimited, Kiap-TU-Wish Chapter Volunteer Scientist and Carter Borden, MobileH20


Poor water quality and degraded habitat are major detriments to the health of coldwater resources. Lack of data on these conditions often hinders an understanding of where trout streams need protection and restoration. Trout Unlimited (TU) is placing a high priority on Community Science, given its benefits for angler education and engagement in trout management. Through community science and crowdsourced monitoring, resource managers have access to more relevant data, allowing them to better address needs for trout stream protection and restoration.
Using patented mobile phone technology and chemical test strips, MobileH2O, LLC has developed the WiseH2O Mobile Application (WiseH2O App), a water quality screening tool that is fast, inexpensive, and easy for use by anglers wanting to understand water quality and ensure the health of their trout streams. TU and MobileH2O, LLC are partnering to promote angler use of the WiseH2O App for monitoring water quality and habitat conditions in Driftless Area (IA, IL, MN, WI) trout streams. Via the WiseH2O App, anglers can quickly make water chemistry measurements of alkalinity, hardness, nitrate-nitrogen, nitrite-nitrogen, pH, and orthophosphate. The WiseH2O App also allows anglers to record water temperatures, stream disturbances, weather conditions, and water level/clarity.
Since a pilot program in 2019, 1002 total water quality observations have been made with the WiseH2O App in 2020-2022, with most in the northern half of the Driftless Area. Of the 2020-2022 observations, 97% have been on state designated trout streams and 37% have been made on Brook Trout streams. Observations have been made by 121 unique observers (participants), and 33 new observers submitted an observation in 2022. Of the 451 observations made in 2022, 86 occurred during the “September Sampling Blitz” contest, used to encourage participants to make observations during the last part of the fishing season. Three TU Chapters have set up their own monitoring programs. Enhancements to the WiseH2O App and program infrastructure continue to be made, and 2023 will include development of an actionable data framework and use of a score card for summarizing water quality screening information collected using the WiseH2O App. More information can be found at: https://www.mobileh2o.com/driftlessprogram.



P-03 (Student): Riverbank Instability Analysis of the Red River in Fargo, North Dakota
Muhammad Shahid Iqbal and Dr. Stephanie Day, Professor and Chair of Geosciences, North Dakota State University, Fargo


Riverbank failures are an important geomorphological factor changing Earth’s surface features. However, often such riverbank failures become a significant concern when surrounding civil infrastructure and land-use are at risk. Therefore, it is important to delineate potential regions prone to such hazards in urban regions. The Red River of North meanders on glaciolacustrine deposits of Lake Agassiz at the boundary of North Dakota and Minnesota, USA. Riverbank failures recorded in this region are rotational and slow-moving. The size, type and speed of failure depend on the soil’s mechanical characteristics and the river water level changes. The current work is an effort to develop a riverbank instability map around the Red River reach passing through the urban section of Fargo, North Dakota, USA. Riverbank instability is assessed in terms of Factor of Safety (FoS) computed by traditional Slope Stability Analysis (SSA). In total, 69 locations around the Red River are subjected to SSA, and FoS are computed by using FLAC Slope 8.1 (freeware) and
Hyrcan 2.0 (freeware). To produce the riverbank instability map, the spatial interpolation technique, Kriging, is employed on the computed FoS.



P-04 (Student): Use of sand budgeting and transport modeling to infer historical geomorphic impacts in the Little Fork River Basin, MN

Andy Kasun University Minnesota Duluth and Karen Gran Earth and Environmental Science, UMD


Anthropogenic disturbances such as logging and agriculture tend to increase runoff and sediment delivery to streams. A geomorphic sediment budget is one way to quantify sediment loading of a river, serving to focus appropriate management actions and restoration funding where it can be most effective. Budgets like this rarely incorporate coarse grain sediments (sand) due to complexities related to sediment delivery and longer transport times. These complexities, however, may be used to describe a longer timescale of geomorphic impact. The Little Fork River was intensively logged in the late 1800s and early 1900s and had the latest log drives of the state of Minnesota ending in the 1940s. It has since been identified as being a significant contributor of sediment and potentially phosphorous to the Rainy-Lake of the Woods Basin. The Minnesota Pollution Control Agency has recently set a turbidity target with a need for additional information on where sediment is being sourced in the watershed. This project seeks to augment the fine sediment budget being conducted by U.S. Geological Survey by adding in sand, defining its differing origins and estimating its transport times. In addition to USGS efforts, sand targeted sampling was completed for ravines, floodplains and culvert road crossings, then grain size analyses were developed to describe sand contribution and storage across the watershed. Remote analyses of lidar topography, land cover, and surficial and bedrock geology have been used to extrapolate erosion rate data to determine watershed-wide sediment contributions. These sediment data are then combined with grain size analyses to feed a sand transport model with stream reach characteristics. Initial findings indicate that erosion in the riparian corridor is most tightly correlated to high slopes near the channel, with main-stem bank erosion being coupled with valley geometry. The sand is predominantly sourced from the stream corridor, with sand storage composing roughly a third of floodplain deposition in the lower reaches. Preliminary transport estimates show that low gradient channel segments act to limit overall transport capacity suggesting that the system is ultimately transport limited.



P-05 (Student): Channel Realignment Impacts on Flow and Aerobic Activity in the Hyporheic Zone
Bradly Evraets and David Baldus
Earth and Environmental Sciences – UMD


Channel realignment projects can have profound impacts on stream channel structure and function, yet few studies have been conducted to understand the impacts of channel realignment on basic functional processes like hyporheic exchange. To better understand how channel realignment impacts shallow hyporheic exchange, we ran tracer studies with the reactive resazurin-resorufin tracer system on three full channel realignment stream projects in Duluth, MN. This study is part of a larger project to understand the impacts of channel realignment restoration on stream function and ecology, focused on streams in northeastern Minnesota.
In June of 2012, Duluth, MN experienced an historic rainfall event resulting in 500-year flood levels on many streams. This flooding event resulted in geomorphic changes deemed to be detrimental to stream habitat. Stream restoration projects have been completed on several streams in the area to address erosion concerns and recreate habitat, particularly for charismatic cold-water fish species such as trout, and there is a need to understand how these large-scale projects impact stream function. The limited number of previous studies trying to understand the impacts of restoration on hyporheic exchange have used conservative tracers and 1D transient storage models and interpreted faster exchange rates between the main channel and transient storage in realigned reaches to be the result of reduced exchange with the hyporheic zone. However, conservative tracers and 1D transient storage models do not differentiate between surface storage and subsurface storage because there is no information specifically gathered to indicate that water has entered the subsurface. This study uses the reactive resazurin-resorufin tracer system. Resazurin is a weakly fluorescent dye that converts to the strongly fluorescent compound resorufin in the presence of aerobic respiration by the removal of an oxygen. It has been shown that the conversion mostly occurs in stream bed sediments, typically the top 5 cm, and not the water column. Thus, water carrying resorufin is labeled as having exchanged with the hyporheic zone. Using the 1D transient storage model of Knapp et al. (2018) that utilizes the reactive tracers, this study compares the differences in the hyporheic exchange parameters between the realigned and non-realigned reaches.



P-06 (Student): Making stream restoration more efficient with machine learning
Charles Nixon and Dr. Stephanie Day, Professor and Chair of Geosciences, North Dakota State University, Fargo


Machine learning is a tool for efficiently processing large amounts of data. Where a person may have to devote days, weeks, or months to poring over large and extensive datasets to extract features from that data, machine learning allows for computer resources to be devoted to the task instead. After training an algorithm to recognize the desired features, the algorithm will extract these features from the background data without further intervention. This frees the person conducting the project to engage in other work and the data mining tasks are usually completed in less time overall. Machine learning can be adapted to work with many different types of data in many fields, including stream restoration. This presentation describes a selection of stream restoration projects in which machine learning is used to process large amounts of data as well as make predictions such as determining the potential impact on water quality of proposed urban planning initiatives, finding the locations of unmapped dams or landslides in topographic data with minimal user intervention, and determining how future energy extraction in an area might affect stream health.



P-07 (Student): The impact of restoration projects on ecosystem function through changes in nutrient spiraling dynamics Watershed
David Baldus, Annika Erickson UMD Department of Earth and Environmental Sciences, Terri Jicha, USEPA, Karen Gran, UMD Department of Earth and Environmental Sciences, Valerie Brady, UMD Natural Resources Research Institute, Lucinda Johnson, UMD Natural Resources Research Institute


Millions of dollars have been spent on stream restoration and habitat improvement projects in the Lake Superior watershed. The effects of these projects on ecological function of a stream reach are not well measured or understood. This knowledge gap is echoed within restoration work worldwide. Here we provide a test case of one method for closing this knowledge gap. We use physical habitat characteristics to explain the differences seen in stream function between a restored treatment reach and an unrestored control reach on Sargent Creek (Duluth, MN) using ammonia/ammonium nutrient spiraling dynamics as a process-based measure of stream health and function. Nutrient spiraling dynamics describe the level of benthic microbial activity and hyporheic processes within the stream as well as the ability of the stream to increase uptake rates in response to increased nutrient loading. The stream’s “resilience”, the ability to adapt uptake rates, governs nutrient export within a reach, which impacts catchment-scale water quality concerns such as basin eutrophication. Thus, changes in spiraling dynamics have implications for both stream health in situ as well as for the catchment at large. Pairing process-based measures of stream function with physical habitat characteristics allows us to go beyond identifying differences in stream function and start to explain what is causing those differences. By identifying what specific elements of habitat structure drive the processes tied to stream function we can more effectively target restoration efforts to improve the function of our streams.
Nutrient dynamics were characterized at each reach through Tracer Additions for Spiraling Curve Characterization analysis. Habitat characterization surveys were conducted at each reach using standardized methods from the National Rivers and Streams Assessment and the Minnesota Stream Quantification Tool to enable comparison with existing datasets. Nutrient dynamics were compared between matched control and treatment reaches to evaluate the effect of full-channel realignment on nutrient dynamics. In this case study we find that the restored reach of Sargent Creek has stronger nutrient uptake and retention, higher biological demand for NH4, and is further from biological saturation than the unrestored reach. We were able to explain these differences in uptake behavior through the interaction of habitat characteristics altered by restoration activities (such as reach slope, pool-riffle spacing, grain size distribution, canopy cover, and riparian vegetation assemblage). This provides a strong argument for the use of paired physical habitat surveys with process-based measures of stream function in restoration monitoring and assessment.



P-08 (Student): Microplastic particle enumeration and characterization in three fish species collected from the Upper Mississippi River

Sam Munk and Eric Strauss, UW- La Crosse River Studies Center and Department of Biology


Microplastics have become a widespread pollutant in terrestrial and aquatic ecosystems over the past 50 years. Microplastics can cause a variety of negative health effects in the organisms that consume them, from changes in feeding habits to increased exposure to toxic chemicals. The majority of recent research has focused on marine microplastics, so the extent that microplastics are impacting freshwater ecosystems is less known. In this project,
microplastic pollution was assessed in three fish species collected in 2019 from Pools 4 and 8 of the Upper Mississippi River. Digestive tracts of Emerald Shiners (Notropis atherinoides) (n=89), Yellow Perch (Perca flavescens) (n=97), and Shorthead Redhorse (Moxostoma macrolepidotum) (n=95) were removed for microplastic analysis. Tissue and contents were digested, density separated and filtered for enumeration. Microplastics were counted and identified, and subsamples were verified via Raman Spectroscopy at UW-Eau Claire. In total, 891 microplastic particles were found among the 281 fish individuals and ranged from 0-22 particles per fish. The most prevalent type of microplastic found across species was fibers. Common colors included blue, black, red and clear. Within the size range of microplastics collected (250μm-5mm), across all species microplastic particle prevalence decreased as size of particle increased. Within each species, there were no significant differences in microplastic content when comparing fish from pool 4 versus pool 8 (p>0.05). In addition, habitat strata (e.g., backwater, main-channel, side-channel, etc.) did not have a significant effect on microplastic content (p>0.05). Microplastic content of fish decreased as fish length (mm) increased (p<0.05). In addition, smaller fish tended to contain proportionately more microplastics than larger fish (microplastics per mm fish length) (p<0.05). Between the three species, Emerald Shiner contained significantly more microplastics per mm fish length than both Yellow Perch and Shorthead Redhorse (p>0.05). Raman verification was conducted on 115 randomly selected particles and revealed the most common microplastic polymers as rubber, polyester (PES), and acrylonitrile butadiene styrene (ABS). This research confirms microplastic ingestion by UMR fish and identifies a need for microplastic monitoring and reducing plastic pollution.



P-09 (Student): Shoreline woody debris in Pool 8 of the Upper Mississippi River Matthew Chen and Eric Strauss, UW- La Crosse River Studies Center and Department of Biology


Woody debris is recognized as an important habitat structure within riverine ecosystems, yet we know very little about its role in large floodplain rivers such as the Upper Mississippi River. Despite its ecological importance, wood has historically been removed from culturally significant bodies of water for navigational and recreation purposes. Defining the ecological role of wood in large floodplain rivers is an important step towards developing better conservation, restoration, and management practices. The objective of this study is to identify patterns in the distribution of shoreline large woody debris in the UMR Pool 8. I surveyed 50 shoreline sites, 25 main channel and 25 side channel, for wood larger than one meter in length. Data analyzed from these sites suggests evidence for differing sources of wood between channel types. Within the main channel it appears that trans-location of wood occurs at a higher rate while side channels rely more heavily on local deposition of, highlighting the importance of riparian habitat and the floodplain forest as an important source of wood. This study as presented provides methods and evidence that more specific, more widespread, or repeated monitoring of wood within the UMR channels may produce results with significant ecological implications.



P-10: Assessing Stream Temperature Impacts of Riparian Thinning Ben Sellers, Eric Booth, Caroline Gottschalk-Druschke, UW Madison


Water temperature is one of the most important variables in stream ecosystems driving biogeochemical processes, metabolic activity for various biota, and water quality. Enhancing our understanding and ability to estimate changes in stream temperature in response to changes in stream and land management and climate is imperative for better management of these valuable ecosystems. We present a monitoring framework that captures not only changes in stream temperature following a stream restoration project but also the major drivers of stream temperature such as shading and channel geometry. This research aims to give an example of the application and benefit of cutting edge monitoring techniques and tools to restoration projects in the Driftless Area and offer a framework of continuous systematic restoration monitoring. These data are also useful for creating a model to predict stream temperature response to restoration. Our preliminary data (2 years pre, 1 year post restoration) show a heating trend after restoration, which we hypothesize results from an increase in direct solar radiation resulting from removal of the riparian canopy. While this trend is concerning, we anticipate a narrowing and deepening of the channel as a result of a change from trees to grass cover and artificially sloped banks, which may reverse the warming trend.