5/21/2015  |   10:30 - 10:45   |  103C

BASEFLOW PATTERNS OF GEOMORPHIC HETEROGENEITY IN STREAM NETWORKS ACROSS BIOMES Using geomorphology to predict ecological processes in streams is challenging, in part, because geomorphological studies typically describe bankful flow channel morphology rather than baseflow conditions that prevail most of the time. We surveyed selected baseflow geomorphic metrics throughout five stream networks spanning subtropical rainforest to arctic tundra biomes. We measured canopy cover, width, depth, and sediment size at transects in reaches covering the discharge gradients in each network and hypothesized that structural heterogeneity was higher at smaller scales and patterns of heterogeneity within networks were biome-specific. Nested ANOVAs revealed significant differences among biomes for all variables except sediment size, while reaches within biomes differed significantly for all metrics. Biome accounted for most variation in canopy cover and reaches accounted for most variation in width, but a large portion of variation in depth and sediment size remained unexplained by either. Geomorphic characteristics were predicted by upstream drainage area within biomes, but the functional form (e.g., power or logarithmic) and parameters depended on both metric and biome. Surveys of baseflow geomorphic patterns may increase our ability to scale ecological processes they structure.

Janine Rüegg (Primary Presenter/Author), University of Lausanne, janine.ruegg@unil.ch;


Ken Sheehan (Co-Presenter/Co-Author), University of New Hampshire, ken.r.sheehan@gmail.com;


Christina Baker (Co-Presenter/Co-Author), University of Alaska Fairbanks, christina.l.baker@gmail.com;


Melinda Daniels (Co-Presenter/Co-Author), Stroud Water Research Center, mdaniels@stroudcenter.org;


Walter Dodds (Co-Presenter/Co-Author), Kansas State University, wkdodds@ksu.edu;


Kaitlin J. Farrell (Co-Presenter/Co-Author), University of Georgia, farrellkj2@gmail.com;


Michael Flinn (Co-Presenter/Co-Author), Murray State University, mflinn@murraystate.edu;


Keith Gido (Co-Presenter/Co-Author), Kansas State University, kgido@ksu.edu;


Tamara Harms (Co-Presenter/Co-Author), University of California Riverside, tharms@ucr.edu;


Jeremy B. Jones (Co-Presenter/Co-Author), University of Alaska Fairbanks, jbjonesjr@alaska.edu;


Lauren Koenig (Co-Presenter/Co-Author), University of New Hampshire, lauren.koenig@unh.edu;


John S. Kominoski (Co-Presenter/Co-Author), Florida International University, jkominoski@gmail.com;


William H McDowell (Co-Presenter/Co-Author), University of New Hampshire, bill.mcdowell@unh.edu;


William Breck Bowden (Co-Presenter/Co-Author), University of Vermont, breck.bowden@uvm.edu;


Amy D. Rosemond (Co-Presenter/Co-Author), University of Georgia, rosemond@uga.edu;


Matt Trentman (Co-Presenter/Co-Author), Flathead Lake Biological Station, University of Montana, matt.trentman@flbs.umt.edu;


Matt Whiles (Co-Presenter/Co-Author), University of Florida, mwhiles@ufl.edu;


Wilfred M. Wollheim (Co-Presenter/Co-Author), University of New Hampshire, wil.wollheim@unh.edu;


Samuel P. Parker (Co-Presenter/Co-Author), University of Vermont, samuel.parker@uvm.edu;

5/21/2015  |   10:45 - 11:00   |  103C

USING A SENSOR NETWORK TO UNDERSTAND DRIVERS OF NUTRIENT AND ORGANIC MATTER CONCENTRATIONS AT MULTIPLE SPATIAL AND TEMPORAL SCALES Understanding, predicting, and controlling water quality across multiple scales is an important goal in watershed management. Two solutes, nitrate and dissolved organic matter, are important for watershed management and can be effectively measured with in situ sensors. Here we report on 2-3 years of water quality data collected continuously at 9 stream and river sites in New Hampshire that span a range of land use. Extensive comparison of sensor results with traditional grab samples demonstrates that sensors can provide reliable estimates of nitrate concentrations; estimates of dissolved organic matter concentrations with sensors are less certain. Deconstruction of variability in nitrate concentrations shows that the greatest variability occurs at the scale of days to a week, with few streams showing strong seasonal patterns in nitrate concentrations or strong relationships with stream discharge. Diel patterns in dissolved oxygen and nitrate are surprisingly common, with clear patterns observed in both shaded headwater streams and larger rivers. Intensive monitoring in heavily developed watersheds shows much higher average nitrate concentrations but reduced variability at scales of minutes to days when compared to more rural watersheds.

William H McDowell (Primary Presenter/Author), University of New Hampshire, bill.mcdowell@unh.edu;


Jody Potter (Co-Presenter/Co-Author), University of New Hampshire, jody.potter@unh.edu;


Lisle Snyder (Co-Presenter/Co-Author), University of New Hampshire, lisle.snyder@unh.edu;


Michelle Daley (Co-Presenter/Co-Author), University of New Hampshire, michelle.daley@unh.edu;


Alison Appling (Co-Presenter/Co-Author), US Geological Survey, alison.appling@gmail.com;


Lauren Koenig (Co-Presenter/Co-Author), University of New Hampshire, lauren.koenig@unh.edu;


Bianca Rodriguez-Cardona (Co-Presenter/Co-Author), University of New Hampshire, bianca.rodz.pr@gmail.com;


Adam Wymore (Co-Presenter/Co-Author), University of New Hampshire, adam.wymore@unh.edu;
Dr. Adam Wymore is a Research Assistant Professor at University of New Hampshire.

Richard Brereton (Co-Presenter/Co-Author), University of New Hampshire, richard.brereton@unh.edu;

5/21/2015  |   11:00 - 11:15   |  103C

MODELING WATER QUALITY AND BIOLOGICAL CONDITION IN STREAMS AT MULTIPLE SCALES: APPLICATIONS OF THE ENVIROATLAS DATASET Predictive models of water quality condition using landscape attributes are not novel; but, the USEPA EnviroAtlas, which provides landscape predictors at the NHD catchment scale for the CONUS, makes possible the analysis of landscape effects on water quality and biological condition at a variety of spatial scales (from headwaters to the entire CONUS), for a wide variety of novel attributes (traditional land cover to novel flow path lengths). Therefore, we developed a series of demonstrative predictive models of water quality and biological condition using the EnviroAtlas dataset at a variety of spatial scales. We used EnviroAtlas predictors and nutrient data from USGS/USEPA for sites across the CONUS and developed nutrient predictive models. Models identified both watershed and riparian predictors, but these varied with spatial scale and region. Novel flow path attributes demonstrated varied predictive behavior. We then developed models of biological condition from several state and national programs to predict deviation from mean condition. Again, predictors at the national and local scale varied, and novel predictors (such as flow path attributes) provide interesting insights.

Michael Paul (Primary Presenter/Author), U.S. Environmental Protection Agency, Paul.Michael@epa.gov;


Peter Cada (Co-Presenter/Co-Author), Tetra Tech Inc., Peter.Cada@tetratech.com;

5/21/2015  |   11:15 - 11:30   |  103C

UNDERSTANDING LAND USE AND CLIMATE IMPACTS ON WATER QUALITY ACROSS SPATIAL SCALES: INTERACTIONS OF SCALE, INTENSITY, DILUTION, AND ECOSYSTEM SERVICES (iSIDES) At regional scales, water quality is spatially varied and temporally dynamic due to interactions of upstream land use, hydrologic conditions, and aquatic processes. We apply a conceptual framework that synthesizes the factors controlling water quality across spatial scales, the iSIDES concept: impact=f(Scale * Intensity * Dilution * Ecosystem Services). We integrate this concept with a river network process-based model, the Framework for Aquatic Modeling of the Earth System (FrAMES), to understand spatial and temporal variability of water quality throughout the Merrimack River watershed. We simultaneously predict spatially distributed flow, water temperature, chloride, and dissolved inorganic nitrogen to understand their coupled responses at the regional scale. We find that wetter summers result in increased proportion of the river length above temperature thresholds for fish, reduced N removal, increased N export fluxes, but reduces the downstream extent of chloride impairment. We suggest that the iSIDES concept integrated with a process-based network model is helpful for understanding potential future water quality at regional scales as land use and climate continue to change.

Wilfred M. Wollheim (Primary Presenter/Author), University of New Hampshire, wil.wollheim@unh.edu;


Robert Stewart (Co-Presenter/Co-Author), University of New Hampshire, rob.stewart@unh.edu;


Madeleine Mineau (Co-Presenter/Co-Author), University of New Hampshire, m.m.mineau@unh.edu;


Nihar Samal (Co-Presenter/Co-Author), University of New Hampshire, nihar.samal@unh.edu;


Shan Zuidema (Co-Presenter/Co-Author), University of New Hampshire, shan.zuidema@unh.edu;


Tao Huang (Co-Presenter/Co-Author), University of New Hampshire, tao7753@gmail.com;


Zaixing Zhou (Co-Presenter/Co-Author), University of New Hampshire, zaixing.zhou;

5/21/2015  |   11:30 - 11:45   |  103C

ASSESSING HUMAN ALTERATIONS OF STREAM WATER CHEMISTRY FROM MODELED REFERENCE CONDITIONS One approach to assessing human impacts on streams is to compare observed conditions to those at environmentally similar streams in relatively natural condition. However, intensively managed landscapes have too few unaltered streams to establish high-quality reference conditions. We examine if empirical models predicting natural specific electrical conductivity (EC) and total phosphorus (TP) effectively estimate site-specific chemical reference conditions for areas without high-quality reference sites. We determined the models were applicable to 95% of the 1922 probabilistic survey sites sampled by the National Rivers and Streams Assessment by applying a multivariate nearest-neighbor technique. Streams outside of model experience had higher geologic sulfur (EC model) or were dryer (TP model) than calibration sites. Observed ECs were > 200 µS/cm higher than predicted natural conditions at > 30% of sites, and TP concentrations were > 50 µg/l higher than background at > 40% of sites. Modeled background conditions can provide a meaningful benchmark for assessment of stream chemistry in highly altered landscapes, and potentially could be applied to assessing thermal, hydrological, or biological conditions.

John Olson (Primary Presenter/Author), Dept of Applied Environmental Science, California State University Monterey Bay, CA, USA, joolson@csumb.edu;


Charles Hawkins (Co-Presenter/Co-Author), Utah State University, chuck.hawkins@usu.edu;

5/21/2015  |   11:45 - 12:00   |  103C

POTENTIAL BENEFITS OF CONSERVATION STRATEGIES FOR STREAM BIODIVERSITY IN AN AGRICULTURAL LANDSCAPE The implementation of best management practices offers great potential for improving the environmental sustainability of agriculture. However, potential tradeoffs associated with their implementation (e.g., agricultural production costs versus environmental benefits) remain poorly understood at spatial scales relevant for management. Herein, we examine potential biodiversity benefits of conservation strategies (e.g., reduction of a single stressor vs. multiple stressors) for streams in the largest agricultural watershed in the Laurentian Great Lakes region, the Western Lake Erie Basin (WLEB). Our findings show that 68% and 90% of the streams in the WLEB exceed eutrophication thresholds for phosphorus and nitrogen, respectively, and nearly half of these streams surpass recommended levels for suspended sediments. Our findings also show that stream biotic integrity has been compromised in many parts of the WLEB. Although these threats and impacts are diffuse, using a novel modeling approach that is broadly applicable to any watershed, we are able to identify specific watersheds and streams within the WLEB to focus conservation efforts. This information is vital for developing effective strategies that improve the environmental sustainability of agriculture.

Steven Keitzer (Primary Presenter/Author), The Ohio State University, keitzer.2@osu.edu;


Stu Ludsin (Co-Presenter/Co-Author), The Ohio State University, ludsin.1@osu.edu;


Scott Sowa (Co-Presenter/Co-Author), The Nature Conservancy, ssoaw@tnc.org;


Anthony Sasson (Co-Presenter/Co-Author), The Nature Conservancy, asasson@tnc.org;


Matthew Herbert (Co-Presenter/Co-Author), The Nature Conservancy, mherbert@tnc.org;


Gust Annis (Co-Presenter/Co-Author), The Nature Conservancy, gannis@tnc.org;


August Froelich (Co-Presenter/Co-Author), The Nature Conservancy, afroelich@tnc.org;


Carrie Volmer-Sanders (Co-Presenter/Co-Author), The Nature Conservancy, csanders@tnc.org;


Jeff Arnold (Co-Presenter/Co-Author), USDA-ARS, Jeff.Arnold@ars.usda.gov;


Mike White (Co-Presenter/Co-Author), USDA-ARS, Mike.White@ars.usda.gov;


Haw Yen (Co-Presenter/Co-Author), Texas A&M University, hyen@brc.tamus.edu;


Prasad Daggupati (Co-Presenter/Co-Author), Texas A&M University, pdaggupati@tamu.edu;


Lee Norfleet (Co-Presenter/Co-Author), USDA-NRCS, lnorfleet@brc.tamus.edu;


Mari-Vaughn Johnson (Co-Presenter/Co-Author), USDA-NRCS, mjohnson@brc.tamus.edu;


Jay Atwood (Co-Presenter/Co-Author), USDA-NRCS, jatwood@brc.tamus.edu;


Charlie Rewa (Co-Presenter/Co-Author), USDA-NRCS, Charles.Rewa@wdc.nrcs.gov;