SFS Annual Meeting

6/06/2024  |   15:30 - 15:45   |  Freedom Ballroom H/G

Microbial Ecology of South African Rivers: Unraveling Urban-Industrial and Peri-Urban/Rural Changing Aspects The microbial ecology of rivers plays an essential role in evaluating water quality and understanding the changing aspects of the ecosystem, particularly in areas with diverse anthropogenic influences. This study aims to study the unfolding of microbial patterns of two South African rivers—Swartkops and Kat rivers, one located in an urban-industrial context and the other in a peri-urban/rural, non-industrialized area, respectively. This study will employ metagenomic sequencing and explore taxonomic composition, diversity metrics, and functional potential. It is expected that the microbial signatures of Kat River will be distinct from Swartkops River influenced by industrial effluents. A more diverse microbiome shaped by agricultural and residential inputs is expected in the Kat River. This research contributes to South African water resource management by providing an understanding of the microbial response to wide-ranging anthropogenic pressures. This study is expected to offer valued inferences for sustainable river management practices in urban-industrial and peri-urban/rural settings.

Chika Nnadozie (Primary Presenter/Author), Institute for Water research, Rhodes University, c.nnadozie@ru.ac.za;

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6/06/2024  |   15:45 - 16:00   |  Freedom Ballroom H/G

An evidence map of research assessing the effects of timber harvesting on water quality and aquatic biodiversity We create an evidence map of research assessing the effects of timber harvesting on water quality and aquatic biodiversity of running waters in boreal and temperate forests. We identified 9394 potentially relevant publications, 534 of which contained qualitative or quantitative information regarding the effects of timber harvesting. From these, we compiled information about: 1) location, 2) the range and frequency of biodiversity and water quality outcomes assessed, as well as the timeframes over which these were assessed, 3) the types and spatial extents of timber harvesting assessed, and 4) the study designs that were used. More than half the studies were conducted in the United States of America (n = 358, 55%). Indicators of water quality were more frequently assessed (80 % of studies, n = 511) than biodiversity (46 % of studies, n = 293). The majority of studies (67 %, n = 313 studies) only collected data up to 5 years after harvesting. They also did not contain watershed-scale information about the extent of timber harvesting (58%, n = 349). Three future research priorities emerged from findings, including the need to: 1) capture a broader scope of effects, particularly when it comes to biodiversity, 2) increase the ability of research to detect long-term effects of harvesting, and 3) better account for hydrological connectivity. The data compiled in this evidence map provides a starting point to address these priorities, and utilize findings to inform improved and evidence-based best management practices for timber harvesting that minimize effects on freshwaters.

Dalal Hanna (Primary Presenter/Author), Carleton University, dalalhanna@cunet.carleton.ca;

Trina Rytwinski (Co-Presenter/Co-Author), Canadian Centre for Evidence-Based Synthesis , TrinaRytwinski@cunet.carleton.ca ;

John Richardson (Co-Presenter/Co-Author), Department of Forest and Conservation Sciences, University of British Columbia, john.richardson@ubc.ca;

Joseph Bennett (Co-Presenter/Co-Author), Carleton University, josephbennett@cunet.carleton.ca;

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6/06/2024  |   16:00 - 16:15   |  Freedom Ballroom H/G

A mechanistic modeling framework for aquatic invertebrates in dammed rivers, Colorado River below Glen Canyon Dam, AZ, USA Damming alters the physical and chemical characteristics of a river, enabling invasive species that are adapted to constant-flow environments to colonize affected river reaches. Field experiments that test how the frequency and intensity of high flow events affect invasive species have shown reductions in invasive species abundances, but these studies are difficult to perform and economically impractical in large, regulated rivers, like the Colorado River. Mathematical models offer a method for predicting the outcomes of various flows to inform management decisions prior to expensive field experiments. We have developed a novel framework for a stage-structured matrix population model that forecasts how future flow event frequencies and magnitudes, temperature regimes, and hydropeaking interact to influence native and invasive aquatic invertebrate abundances in dammed rivers. Sensitivity analyses of model outputs allow for better understanding of the specific interactions between species. This framework is useful for identifying flow management scenarios that optimize native species’ populations and characterize environmental and biological relationships in Grand Canyon. Of the species included in the model, one is invasive (Potamopyrgus antipodarum, New Zealand Mud Snail) and two are native taxa (Hydropsyche spp., net-spinning caddisfly; Chironomidae, Midges). Mechanistic models allow us to address management questions regarding population-level responses to novel flows caused by climate change or flow regime shifts.

Angelika Kurthen (Primary Presenter/Author), Oregon State University, kurthena@oregonstate.edu;

Ted Kennedy (Co-Presenter/Co-Author), USGS Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, tkennedy@usgs.gov;

Dave Lytle (Co-Presenter/Co-Author), Oregon State University, lytleda@oregonstate.edu;

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6/06/2024  |   16:15 - 16:30   |  Freedom Ballroom H/G

Estimating stream water temperature trends and summary statistics from long-term monitoring datasets in the presence of sampling artifacts Long-term river water temperature datasets collected from regional and national monitoring programs are typically characterised by the presence of sampling artifacts and low-frequencies of sampling. These characteristics can disrupt the collection of regular, evenly spaced datasets and produce timeseries which may include observations unevenly spaced across seasons or hour-of-the-day, changes to routine sampling frequencies, and/or improvements in the accuracy of measurements over time. However, there exists limited understanding of how these types of sampling artifacts affect the accuracy and uncertainty of estimates of trends and summary statistics (such as site means) from commonly used mathematical models. We constructed Monte-Carlo experiments to examine how commonly encountered sampling artifacts and model choice influence the accuracy of estimates of trends and site means from long-term stream temperature datasets. Stream temperature timeseries of sub-daily resolution from tropical, temperate and cold climates were used for determining a “truth.” A range of common sampling artifacts were then applied to these datasets to simulate datasets typical of those gathered from long-term stream temperature networks. Trends and site means were then estimated using a range of commonly used models and compared to the “truth.” The process was repeated 1,000 times for each climate, artifact and model, allowing examination of the impact of individual sampling artifacts and model choice on the accuracy of trend and site mean estimates. The findings from this work will enable robust analysis of regional and national monitoring datasets, facilitating insights into the effects of climate change on stream ecosystems and effectively direct management interventions.

Vaughn Grey (Primary Presenter/Author), University of Melbourne, vgrey@student.unimelb.edu.au;

Belinda Hatt (Co-Presenter/Co-Author), Melbourne Water, Belinda.Hatt@melbournewater.com.au;

Tim Fletcher (Co-Presenter/Co-Author), University of Melbourne, timf@unimelb.edu.au;

Kate Smith-Miles (Co-Presenter/Co-Author), University of Melbourne, smith-miles@unimelb.edu.au;

Rhys Coleman (Co-Presenter/Co-Author), Melbourne Water, Rhys.Coleman@melbournewater.com.au;

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6/06/2024  |   16:30 - 16:45   |  Freedom Ballroom H/G

The development of automated solutions for Alaska’s biennial Integrated Water Quality Monitoring and Assessment Report (IR) process. Every two years, the Alaska Department of Environmental Conservation (AK DEC) assesses the water quality of the state’s waterbodies and submits an Integrated Water Quality Monitoring and Assessment Report (IR) to the U.S. Environmental Protection Agency. The assessment of waterbodies and required reporting is currently conducted manually by analysts and consumes a significant amount of energy and time, exacerbated by a vast quantity of waterbodies, a large amount of data, and a small staff size. Recognizing the need for efficiency, AK DEC sought to develop automated technologies to improve the IR process to alleviate bottlenecks, create reproducible processes, reduce error, and increase efficiency and transparency. In Phase 1 of the project, Alaska’s IR process was reviewed in detail to identify areas most in need of improvement. Other state IR processes and automation tools were reviewed for context. Phase 2, an ongoing effort, involves the development of automated code-based tools to streamline the IR process. Automation objectives include data retrieval from the Water Quality Portal, QA/QC review, comparison against Alaska's water quality standards, decision-making in the assessment process, and data output for reporting purposes. Leveraging the open-source R programming language, we have developed a series of scripts and functions that will improve the efficiency of the IR process by making previously manual tasks automatic which allows AK DEC staff more time for interpretation and decision-making. This presentation highlights a systemic approach to implementing automated solutions in organizational processes, which can be adapted elsewhere.

Benjamin Block (Primary Presenter/Author), Tetra Tech, ben.block@tetratech.com;

Amber Crawford (Co-Presenter/Co-Author), Alaska Department of Environmental Conservation, amber.crawford@alaska.gov;

Kateri Salk (Co-Presenter/Co-Author), Tetra Tech, Kateri.SalkGundersen@tetratech.com;

Hannah Ferriby (Co-Presenter/Co-Author), Tetra Tech, Hannah.Ferriby@tetratech.com;

Morgan Brown (Co-Presenter/Co-Author), Alaska Department of Environmental Conservation, morgan.brown@alaska.gov;

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6/06/2024  |   16:45 - 17:00   |  Freedom Ballroom H/G

A blank slate: revealing the eco-geomorphic dynamics of emergent reservoir landscapes using remote sensing data As the world's reservoirs experience drawdowns from reduced precipitation and increased water demand, expanses of sediment are being exposed and colonized by both native and non-native vegetation. Within Lake Powell, the second largest reservoir in the U.S., drought in the Colorado River Basin has led to a rapid decrease in water level since ~2000. Here we use multispectral satellite and aerial imagery and airborne lidar to quantify vegetation dynamics across more than 400 km2 of backwater sediment between 2000-present. Our findings indicate that sediment deposits, which are up to 50 m thick and contain interbedded lacustrine, fluvial, and alluvial material, provide habitat for mesic (i.e., near-channel) riparian plants immediately following reservoir decline. With progressive drawdown and exposure time, colonization shifts to drought-tolerant species, particularly the non-native shrub tamarisk (Tamarix spp.), which comprises approximately 20% of subaerial surfaces at present. With continued water recession, vegetation becomes disconnected from the water table, leading to nearly complete mortality and subsequent recolonization by xeric species. Finally, we compare current vegetation composition to the pre-reservoir ecosystem found along the Colorado and San Juan Rivers. Between dam closure and present, mesic riparian plant communities nearly doubled in area (91% increase), while more distal xeric communities increased by approximately 70%. Quantifying the dynamics of sediment exposure and vegetation provides opportunities for reservoir management to encourage the maintenance of native and/or culturally-valued ecosystems. The views expressed in this abstract are those of the authors and do not necessarily represent the views or policies of the US Government.

Alan Kasprak (Primary Presenter/Author), U.S. Environmental Protection Agency, kasprak.alan@epa.gov;

Henry Barth (Co-Presenter/Co-Author), Fort Lewis College, hobarth@fortlewis.edu;

Brenda Bowen (Co-Presenter/Co-Author), University of Utah, brenda.bowen@utah.edu;

Mike DeHoff (Co-Presenter/Co-Author), Returning Rapids Project, Glen Canyon Institute, mike@returningrapids.com;

Cynthia Dott (Co-Presenter/Co-Author), Fort Lewis College, dott_c@fortlewis.edu;

Gary Gianniny (Co-Presenter/Co-Author), Fort Lewis College, gianniny_g@fortlewis.edu;

Cari Johnson (Co-Presenter/Co-Author), University of Utah, cari.johnson@utah.edu;

Joel Sankey (Co-Presenter/Co-Author), U.S. Geological Survey, jsankey@usgs.gov;

Michael Scott (Co-Presenter/Co-Author), U.S. Geological Survey, scottmikeski@gmail.com;

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