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SFS Annual Meeting

Monday, May 21, 2018
11:00 - 12:30

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11:00 - 11:15: / 410 B INTERACTIVE EFFECTS OF HYDROGEOMORPHIC CHARACTERISTICS ON FISH COMMUNITY STRUCTURE IN A FLOODPLAIN RIVER

5/21/2018  |   11:00 - 11:15   |  410 B

INTERACTIVE EFFECTS OF HYDROGEOMORPHIC CHARACTERISTICS ON FISH COMMUNITY STRUCTURE IN A FLOODPLAIN RIVER This study examined how hydrogeomorphic attributes of off-channel habitats of a floodplain river determine composition of fish communities. Fish were collected from 27 lateral habitats in the Upper Mississippi River using multiple collecting gears. Fish data were standardized by conversion to catch-per-unit-effort followed by determination of relative abundance. Twenty-two hydrological and geomorphological variables were generated for each site. Cluster analysis of hydrogeomorphic data identified three groups: floodplain lakes (Lakes); a mixed group of floodplain lakes and backwaters that disconnected periodically (Mixed); and backwaters that remained fully connected (Backwaters). Similarity among sites within each hydrogeomorphic group was predominantly accounted for by: hydrological variables (Lakes); combination of hydrological and geomorphic variables (Mixed); geomorphic variables (Backwaters). Analysis of similarity (ANOSIM) revealed significant differences in fish community composition that correlated with hydrogeomorphic grouping. This study demonstrated that lateral habitats of the Upper Mississippi River exhibit distinct hydrogeomorphic characteristics; and, that their distinctive attributes shape organization and abundance of fish communities within this riverine landscape. This study illustrates the need to apply appropriate measures of both hydrology and geomorphology to address the complex dynamics of slackwaters for both river research and management.

Michael Delong (Primary Presenter/Author), Winnona State University, MDelong@winona.edu ;


Martin Thoms (Co-Presenter/Co-Author), University of New England, Armidale, NSW Australia, mthoms2@une.edu.au;


Ethan Sorensen (Co-Presenter/Co-Author), Winona State University, esorenson14@winona.edu;


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11:15 - 11:30: / 410 B QUANTIFYING THE EFFECTS OF STREAM FLOW ON FISH AND BENTHIC MACROINVERTEBRATE COMMUNITIES – A BAYESIAN NETWORKS MODELING APPROACH

5/21/2018  |   11:15 - 11:30   |  410 B

QUANTIFYING THE EFFECTS OF STREAM FLOW ON FISH AND BENTHIC MACROINVERTEBRATE COMMUNITIES – A BAYESIAN NETWORKS MODELING APPROACH Characteristics of fish and benthic macroinvertebrate communities are affected by anthropogenic (e.g., land-use, flow-alteration, and climate change) and natural environmental variables (e.g., elevation, stream size, and geological/soil characteristics). Establishing quantitative links between ecological characteristics and environmental variables is challenging because of the complex interactions among variables and variation in spatiotemporal scales. Consequently, we often lack the data to parameterize process-based models and the complex interactions and varying spatiotemporal scales can produce misleading correlations when developing empirical models. Bayesian network modeling can be used to establish quantitative links among multiple factors that affect stream communities using simplified mechanisms that represent scientific understanding and are appropriate for the data. We employ a continuous variable Bayesian network model to model interactions among environmental variables and effects on streamflow, fish, and benthic invertebrate communities. This model predicts changes arising from climate change and can be incorporated into a decision support system allowing managers to envision potential effects of flow changes on communities. We present the model-building process using data from two river basins in North and South Carolina and use simulation for prediction under various climate change scenarios.

Song Qian (Primary Presenter/Author), The University of Toledo, song.qian@utoledo.edu;


Jason May (Co-Presenter/Co-Author), U.S. Geological Survey, California Water Science Center, jasonmay@usgs.gov;


Jonathan Kennen (Co-Presenter/Co-Author), U.S. Geological Survey, New Jersey Water Science Center, 3450 Princeton Pike, Suite 110, Lawrenceville, NJ 08648, jgkennen@usgs.gov;


Thomas Cuffney (Co-Presenter/Co-Author), U.S. Geological Survey, South Atlantic Water Science Center, 3916 Sunset Ridge Rd., Raleigh, NC 27607, tcuffney@usgs.gov;


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11:30 - 11:45: / 410 B RELATIONS AMONG FISH AND INVERTEBRATE COMMUNITIES AND MODELED FLOW METRICS IN THE CAPE FEAR AND PEE DEE/YADKIN RIVER, NORTH CAROLINA, USA

5/21/2018  |   11:30 - 11:45   |  410 B

RELATIONS AMONG FISH AND INVERTEBRATE COMMUNITIES AND MODELED FLOW METRICS IN THE CAPE FEAR AND PEE DEE/YADKIN RIVER, NORTH CAROLINA, USA Flow-ecology relations are being investigated at 394 sites in the Cape Fear and at 599 sites in the Pee Dee/Yadkin river basins in North and South Carolina as part of the USGS’s Water Smart program. State fish and invertebrate bioassessment data are being combined with modeled (SWAT) daily flow data as a means of projecting responses (flow and biological) to climate change and land use change. Flow metrics are calculated from modeled flows using the USGS’s EflowStats R-package these metrics encompassing flow magnitude, duration, timing, frequency, and rate of change. Modeling was conducted in two phases. First, the relations with invertebrate and fish metrics and life history traits to a reduced set of least redundant flow metrics were assessed with multiple modeling techniques, such as structural equation modeling, machine learning techniques and Bayesian belief networks. Then these relations were further assessed by applying multiple scenarios of future land use change and climate change. These assessments will assist in building decision support tools that help local water resource managers plan for future scenarios of water use and availability to attempt mitigate negative impacts on local aquatic flora and fauna.

Jason May (Primary Presenter/Author), U.S. Geological Survey, California Water Science Center, jasonmay@usgs.gov;


Song Qian (Co-Presenter/Co-Author), The University of Toledo, song.qian@utoledo.edu;


Jonathan Kennen (Co-Presenter/Co-Author), US Geological Survey, New Jersey Water Science Center, jgkennen@usgs.gov;


Thomas Cuffney (Co-Presenter/Co-Author), U.S. Geological Survey, South Atlantic Water Science Center, 3916 Sunset Ridge Rd., Raleigh, NC 27607, tcuffney@usgs.gov;


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11:45 - 12:00: / 410 B EFFECTS OF ANTECEDENT STREAMFLOW AND SAMPLE TIMING ON TREND ASSESSMENTS OF FISH, INVERTEBRATE, AND DIATOM COMMUNITIES

5/21/2018  |   11:45 - 12:00   |  410 B

EFFECTS OF ANTECEDENT STREAMFLOW AND SAMPLE TIMING ON TREND ASSESSMENTS OF FISH, INVERTEBRATE, AND DIATOM COMMUNITIES Detecting changes in biological attributes is central to stream monitoring programs; however, understanding how natural variability in environmental factors affects trend results is mostly unexplored. We evaluated the influence of antecedent streamflow and sample timing on trend estimates for fish, invertebrate, and diatom taxa richness and condition from 2002 to 2012 at 51 sites. Pearson correlation analysis identified covariates strongly associated with biological endpoints. A combination of linear regression and Mann-Kendall tests were used to evaluate covariate influence on trend estimates. Meaningful correlations (|r| ? 0.60) varied by assemblage and endpoint at 47 sites. Adjusting for covariates changed trend estimates on average by 21%, most often reducing the estimated magnitude of the trend. Additionally, covariates influenced the interpretation of over 2/3 of trend estimates. Our findings clearly indicate that antecedent streamflow and sample timing influences trend estimates and subsequent interpretation. Accounting for covariates during trend analysis will enhance stream monitoring programs by providing a better understanding and interpretation of estimated changes in biological endpoints at monitored sites. Failure to account for covariates may lead to under or overestimating the likelihood of a trend estimate and/or misdiagnosing potential causes.

Robert Zuellig (Primary Presenter/Author), U.S. Geological Survey, rzuellig@usgs.gov ;


Daren Carlisle (Co-Presenter/Co-Author), U.S. Geological Survey, dcarlisle@usgs.gov;


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12:00 - 12:15: / 410 B GROUNDWATER AS A SOURCE OF EMERGING CONTAMINANTS TO STREAMS OF THE CHESAPEAKE BAY WATERSHED

5/21/2018  |   12:00 - 12:15   |  410 B

GROUNDWATER AS A SOURCE OF EMERGING CONTAMINANTS TO STREAMS OF THE CHESAPEAKE BAY WATERSHED Groundwater upwelling zones can serve as important niche environments for aquatic organisms. The use of upwelling areas for thermal refuge or spawning by fish, amphibians, and benthic invertebrates renders these organisms susceptible to focused discharge of groundwater contamination. However, there is a paucity of information on the potential for groundwater in streams as an exposure pathway of emerging contaminants for aquatic organisms. Ongoing research in the Chesapeake Bay Watershed - where surface water and adult/young-of-year smallmouth bass are sampled for contaminants – motivated this investigation on the role of groundwater as a source of contaminants in areas of known smallmouth bass spawning and rearing activity. Using thermal infrared cameras to locate areas of groundwater upwelling, we sampled groundwater using drive-point piezometers at three locations: two in the Susquehanna River Basin and one in West Virginia. Samples of shallow ground and surface water were collected monthly through September 2017. Total estrogenicity was quantified for all samples and a subset was selected for analysis of pesticide degradates, hormones and phytoestrogens. Preliminary analyses suggest that focused groundwater discharges may be an important exposure pathway for smallmouth bass and other aquatic organisms.

Martin Briggs (Co-Presenter/Co-Author), U. S. Geological Survey, Hydrogeophysics Branch, Storrs, Connecticut, USA, mbriggs@usgs.gov;


Dr. Vicki Blazer (Co-Presenter/Co-Author), U.S. Geological Survey Fish Health Branch, Leetown Science Center, vblazer@usgs.gov;


Tyler Wagner (Co-Presenter/Co-Author), U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, txw19@psu.edu;


Adam Sperry (Co-Presenter/Co-Author), National Fish Health Research Laboratory, U.S. Geological Survey, Kearneysville, WV, asperry@usgs.gov;


Tyler Thompson (Primary Presenter/Author), Pennsylvania State University, tjt5199@psu.edu;


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12:15 - 12:30: / 410 B STRANGER THINGS: QUANTIFYING BIOLOGICAL COMMUNITIES IN MICROHABITATS IN ARIDLAND RIVERS

5/21/2018  |   12:15 - 12:30   |  410 B

STRANGER THINGS: QUANTIFYING BIOLOGICAL COMMUNITIES IN MICROHABITATS IN ARIDLAND RIVERS Biological communities in aridland rivers are often reliant on a “bathtub ring” of autochthonous production. For example, the Rio Grande is an aridland river with high turbidity and shifting substrates, which confine the bathtub ring to a shallow, temporary edge. We investigated the role of hydrologic and hydraulic variables in the distribution of biological parameters in microhabitats of the Rio Grande by conducting transverse surveys at two locations in 2015 and 2016. We collected samples for biological data (chlorophyll a, abundance and diversity of diatoms and invertebrates) and quantified local hydraulics and hydrology (e.g. geomorphology, turbulence strength and intensity, velocity, and turbidity). We used this data with USGS discharge data in Classification and Regression Tree (CART) analysis. Local changes in flow (e.g. velocity, turbulence) and large-scale hydraulic events (e.g. discharge) were important variables driving differences in the biological community. However, we recognise that there are also important variables at the micro-scale that are difficult to quantify. We will discuss the complexities of understanding biological communities in aridland rivers.

Ayesha Burdett (Primary Presenter/Author), New Mexico Museum of Natural History and Science, Ayesha.Burdett@state.nm.us;


Rebecca Bixby (Co-Presenter/Co-Author), University of New Mexico, bbixby@unm.edu;


Angela Gregory (Co-Presenter/Co-Author), University of New Mexico, agregory@unm.edu;


Jonathan AuBuchon (Co-Presenter/Co-Author), US Bureau of Reclamation, jaubuchon@usbr.gov;


Nathan Schroeder (Co-Presenter/Co-Author), Santa Ana Pueblo, nathan.schroeder@santaana-nsn.gov;


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