5/19/2015  |   10:30 - 10:45   |  102D

FLOWING INTO THE FUTURE: APPROACHES AND PERSPECTIVES TO GUIDE FLOW MANAGEMENT FOR SOCIETY AND THE ENVIRONMENT As we consider the future of flow management, current and historic environmental degradation coupled with society’s demands create issues that are real and vast. However, we demonstrate, in part through this session, that a multi-scale, interdisciplinary approach to research and management has tangible benefits and long-term value for the conservation of species and habitats. Three themes emerge from this session and recent contributions to the subdisciplines of ecohydraulics and ecohydrology. The first theme is partnership as an increase in collaborative, interdisciplinary research on all facets of the biological and hydrological continuum contributes to models and environmental solutions. Second, is the reemphasis on individual life histories and organismal properties as the organisms we investigate possess dual roles as both targets of conservation and an effective means to assess the condition of their habitat. Thirdly, new technological and analytical tools enable researchers and managers to collect higher resolution data more quickly and efficiently than ever before. Here, we attempt to synthesize the contributions of this session and emphasize the benefits of these themes for building a stronger freshwater future.

Jessica Orlofske (Primary Presenter/Author), University of Wisconsin - Parkside, orlofske@uwp.edu;


Wendy Monk (Co-Presenter/Co-Author), Environment and Climate Change Canada @ Canadian Rivers Institute, Faculty of Forestry and Environmental Management, University of New Brunswick, Fredericton, NB, Canada, wmonk@unb.ca;

5/19/2015  |   10:45 - 11:00   |  102D

SOMETHING OLD, SOMETHING NEW, SOMETHING BORROWED… BRINGING TOGETHER DIVERSE METHODS TO QUANTIFY FLOW-RESPONSE RELATIONSHIPS FOR ENVIRONMENTAL FLOW MANAGEMENT Despite decades of research using traditional techniques in stream ecology, we still have little ability to make specific predictions of the ecological benefits of environmental flows. Adapting methods developed in other fields of research, we developed new approaches to synthesizing literature (systematic review), capturing expert knowledge (expert elicitation), and statistical modelling of data (hierarchical Bayesian analysis). We used these methods to predict ecological responses to changing flow regimes, here presenting an example for bankside vegetation. This approach allowed us to make best use of all the information that could be brought to bear on the problem of quantifying flow-response relationships. Specifically, we were able to demonstrate that each component improves our ability to predict responses to future flow regimes. Our work demonstrates the potential of using novel tools and information sources to develop predictive flow-ecology models. Nevertheless, some of the resulting predictions have large uncertainties. The freshwater science community needs to continue to develop new approaches for combing theory and data, including drawing on methods from other disciplines, if it is to improve the predictive capacity of flow-ecology models.

Angus Webb (Primary Presenter/Author), The University of Melbourne, angus.webb@unimelb.edu.au;
Dr Angus Webb is a Senior Lecturer in Environmental Hydrology and Water Resources at the University of Melbourne, Australia. He originally trained as a marine ecologist before moving into the study and restoration of large-scale environmental problems in freshwater systems. Much of his research centers on improving the use of the existing knowledge and data for such problems. To this end he has developed innovative approaches to synthesizing information from the literature, eliciting knowledge from experts, and analyzing large-scale data sets. He is heavily involved in the monitoring and evaluation of ecological outcomes from the Murray-Darling Basin Plan environmental watering, leading the program for the Goulburn River, Victoria, and advising on data analysis at the basin scale. Angus is currently a co-editing a major new text book on environmental flows science and management. He was awarded the 2013 prize for Building Knowledge in Waterway Management by the River Basin Management Society, and the 2012 Australian Society for Limnology Early Career Achievement Award.

Michael Stewardson (Co-Presenter/Co-Author), University of Melbourne, mjstew@unimelb.edu.au;


Kim Miller (Co-Presenter/Co-Author), University of Melbourne, kim.miller@unimelb.edu.au;


Siobhan de Little (Co-Presenter/Co-Author), University of Melbourne, siobhan.delittle@unimelb.edu.au;

5/19/2015  |   11:00 - 11:15   |  102D

PREDICTABILITY OF HYDROLOGIC INDICES: IMPLICATIONS FOR STREAMFLOW REGIME CHARACTERIZATION AND DEVELOPMENT OF REGIONAL ENVIRONMENTAL FLOW STANDARDS Characterizing flow regimes using hydrologic indices is common to river research and stream classification. A vast number of hydrologic indices have been developed to capture key flow characteristics of the hydrograph that vary in ecological relevance and sensitivity to human perturbation. Because the natural flow regime reflects the unique climatic, geologic, and topographic characteristics of its drainage basin, it is logically assumed that hydrologic indices are strongly related to physical basin characteristics. However, relationships between hydrologic indices and basin characteristics have not been systematically examined. We developed random forest statistical models to predict over 1000 hydrologic indices using basin predictor variables at USGS reference gages in the coterminous United States. We found that only 202 hydrologic indices (20%) could be reliably predicted. These findings suggest that many hydrologic indices should not be used for regional stream flow classification and environmental flow assessment purposes.

Ted Grantham (Primary Presenter/Author), U.S. Geological Survey, tgrantham@usgs.gov;


Ken Eng (Co-Presenter/Co-Author), U.S. Geological Survey, keng@usgs.gov;


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


David Wolock (Co-Presenter/Co-Author), U.S. Geological Survey, dwolock@usgs.gov;

5/19/2015  |   11:15 - 11:30   |  102D

MODELING FISH SPECIES RESPONSE TO CHANGES IN WATER AVAILABILITY AND CLIMATE IN THE NORTH CAROLINA PIEDMONT, USA Streamflows are essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Changes in climate, land and water use practices are altering the availability of water throughout the Southeast US. Understanding the potential impact of these changes on aquatic ecosystems is critical for long-term water management. Boosted regression trees and WaSSI, a rainfall-runoff model, were used to predict the relation between streamflow and fish species richness under plausible scenarios of projected future water withdrawal, climate change, and increases in impervious surfaces. Streamflow variability, monthly discharge, the fraction of flow originating on impervious surfaces, and river basin accounted for 44% of the variability in the training data. On average, fish species richness was predicted to decline significantly with increased withdrawals and impervious surfaces, but only a slight decrease was seen under future climate scenarios. Hot spot analyses identified regions that are predicted to change faster than average. Such findings may help resource agencies and stakeholders develop management strategies that prioritize watersheds vulnerable to altered streamflow and better support the protection and long-term conservation of species of special concern.

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


Ernie Hain (Co-Presenter/Co-Author), Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Campus Box 7106, Raleigh, NC 27695, ernie_hain@ncsu.edu;


Peter Caldwell (Co-Presenter/Co-Author), USDA Forest Service, Center for Forest Watershed Science, Coweeta Hydrologic Lab 3160 Coweeta Lab Road, Otto, NC 28763, pcaldwell02@fs.fed.us;


Stacy Nelson (Co-Presenter/Co-Author), Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Campus Box 7106, Raleigh, NC 27695, sanelso2@ncsu.edu;


Ge Sun (Co-Presenter/Co-Author), USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, 920 Main Campus Drive, Venture II, Suite 300, Raleigh, NC 27606, gesun@ncsu.edu;


Steve McNulty (Co-Presenter/Co-Author), USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, 920 Main Campus Drive, Venture II, Suite 300, Raleigh, NC 27606, steve_mcNulty@ncsu.edu;

5/19/2015  |   11:30 - 11:45   |  102D

AN ASSEMBLAGE-LEVEL TRAIT MODEL PREDICTS POPULATION-LEVEL LIFE HISTORY VARIATION AND RESPONSE TO FLOW REGIME IN THREE STREAM FISHES Trait-based approaches could generate a mechanistic understanding of community assembly. However, such approaches generally assume that trait-environment relationships are consistent across space and time, and that interspecific variation exceeds population-level variation. There is little information on these assumptions available for most groups, and thus assessing population-level trait-environment relationships could test the generality of trait-based models while evaluating intraspecific variation. We evaluated the generality of the trilateral life history model (TLHM) for fishes - well-studied at the assemblage level - to populations of three stream fishes in the midwestern US. The TLHM adequately described the major trade-offs in traits among populations in all three species, but the flow-based predictions of the TLHM were only well-supported in one species. Intraspecific trait variability was of similar magnitude or higher for some traits compared to interspecific ranges. Such high variability could affect studies that assign mean trait values to species. This, coupled with the explanatory power of the TLHM at the population level, suggests that a synthesis of environmental filtering or habitat template models with modern life history theory could be valuable.

Micah Bennett (Primary Presenter/Author), U.S. Environmental Protection Agency, Office of Research and Development, bennett.micah@epa.gov;


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


Gregory Whitledge (Co-Presenter/Co-Author), Southern Illinois University, gwhit@siu.edu;

5/19/2015  |   11:45 - 12:00   |  102D

ASSOCIATIONS BETWEEN STREAM HYDROGEOMORPHOLOGY AND FISH ASSEMBLAGES IN AN URBAN LANDSCAPE Urbanization of watersheds can result in considerable changes to stream hydrogeomorphology, including abrupt changes in substrate composition, channel geometry, gradient, and flow characteristics. In this study, we investigated potential influences of urban-induced changes in fluvial geomorphology on fish assemblages in 23 stream reaches of the Columbus Metropolitan Area, OH. Results suggest that a number of hydrogeomorphic factors influenced fish assemblage species richness, diversity, and composition. Channel slope was negatively related to species richness, evenness, and diversity; fish abundance was positively related to channel widening; and the relative abundance of tolerant individuals within the fish assemblage was negatively associated with bankfull flow velocity. At a subset of 12 stream reaches where we monitored coordinated fish-geomorphic changes over four years, we observed that increasing channel entrenchment led to lower assemblage diversity, fewer sensitive darter species, and decreases in the relative abundance of predators. Collectively, these results indicate that hydrogeomorphic variables contribute to the suite of environmental determinants of fish assemblages in urban landscapes and that rapid fluvial geomorphic adjustment can prompt ecologically-meaningful changes in community structure and function.

Leslie O. Rieck (Primary Presenter/Author), The Ohio State University, rieck.6@osu.edu;


S. Mažeika Patricio Sulliván (Co-Presenter/Co-Author), The Ohio State University, sullivan.191@osu.edu;