Tuesday, May 19, 2015
10:30 - 12:00

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10:30 - 10:45: / 102E TWO METHODS TO ESTIMATE THE IMPORTANCE OF RIVER MANAGEMENT CRITERIA IN A MULTI-CRITERIA DECISION ANALYSIS

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

TWO METHODS TO ESTIMATE THE IMPORTANCE OF RIVER MANAGEMENT CRITERIA IN A MULTI-CRITERIA DECISION ANALYSIS Human-driven alterations to freshwater ecosystems are causing the global decline of important drivers of river health. Modern strategies for decision support aim to integrate ecology-based and socioeconomic criteria to balance management decisions. We present two methods to embed a social preference structure for river management criteria into methods for multi-criteria decision analysis. First, we used direct preference elicitation from stakeholders and the analytic hierarchy process to estimate the importance of ecological, recreation, and policy criteria in the Yampa-White River basin in Colorado. This study informs environmental flow planning. A second method was developed on a water allocation planning project in the Goulburn River catchment, Victoria, Australia. Multidimensional scaling ordination was used to objectively partition a large number of feasible water allocation projects into groups that represent logical tradeoffs between the conflicting irrigation and hydro-ecological criteria. This method complements subjective elicitation procedures for estimating the importance of river management criteria. The two case studies offer important approaches to multi-disciplinary decision support analyses around the world.

David Martin (Primary Presenter/Author), Colorado State University, davidminormartin@gmail.com;


LeRoy Poff (Co-Presenter/Co-Author), Colorado State University, n.poff@rams.colostate.edu;


Sue Powell (Co-Presenter/Co-Author), Institute for Applied Ecology, sue.powell@canberra.edu.au;


Angus Webb (Co-Presenter/Co-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.

Susan Nichols (Co-Presenter/Co-Author), University of Canberra, Australia, Sue.Nichols@canberra.edu.au;


10:45 - 11:00: / 102E INCORPORATING MANAGEMENT RISK AND VALUES INTO NATURAL RESOURCE MONITORING DESIGNS

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

INCORPORATING MANAGEMENT RISK AND VALUES INTO NATURAL RESOURCE MONITORING DESIGNS For threshold-dependent decisions, management responds to indications from monitoring data that a resource condition crossed a decision threshold (e.g., reference vs impaired conditions). However, there are risks that monitoring data will indicate incorrectly the true state of nature and either impose undue management costs (Type I error) or fail to protect the resource (Type II error). Risk tolerance for Type I and II errors is not often considered explicitly but can be accounted for when setting thresholds and designing monitoring programs by maximizing expected utility. Expected utility is a function of the relative value placed on possible outcomes of correctly or incorrectly determining resource condition. We present an example of optimizing utility values for freshwater bioassessment using benthic macroinvertebrate community data. We found that Type I error rate <0.10 was optimal only when the prior probability of remaining in reference condition was high (i.e., >0.7). We end by discussing the implications of Type I and II error tolerance on sampling designs for selenium assessment in freshwater fish populations.

David Smith (Primary Presenter/Author), U.S. Army Corps of Engineers, david.l.smith@erdc.dren.mil;


Craig D. Snyder (Co-Presenter/Co-Author), U.S. Geological Survey, csnyder@usgs.gov;


Nathaniel Hitt (Co-Presenter/Co-Author), U.S. Geological Survey, Leetown Science Center, nhitt@usgs.gov;


11:00 - 11:15: / 102E SITE-SPECIFIC BENCHMARKS TO REDUCE UNCERTAINTY DUE TO SPATIAL AND TEMPORAL VARIABILITY OF REFERENCE CONDITIONS IN THE ASSESSMENT AND MANAGEMENT OF BENTHIC COMMUNITIES

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

SITE-SPECIFIC BENCHMARKS TO REDUCE UNCERTAINTY DUE TO SPATIAL AND TEMPORAL VARIABILITY OF REFERENCE CONDITIONS IN THE ASSESSMENT AND MANAGEMENT OF BENTHIC COMMUNITIES The assessment and management of benthic invertebrates is often a challenge because communities in even the best available reference sites can vary substantially in space and time, thereby affecting the statistical power of assessments and the range of environmental quality guidelines. Characterization of appropriate reference conditions can include (a) identifying and adjusting for effects of natural or nuisance factors and (b) quantifying temporal variability and including it in assessments and the determination of management guidelines. Strategies for defining benthos reference conditions for three disturbed nearshore areas in northern Lake Superior are described. To partition out nuisance spatial variability habitat conditions, which can account for up to 70% of the variability of community descriptors among reference sites, were used to match a subset of reference sites to each assessment site. Temporal variability of benthic communities, potentially resulting in unstable or moving benchmarks of reference conditions, was examined over 10-12 years and accommodated through the delineation of time trajectories for reference and assessment sites. This allowed not only time-specific comparisons but also indications of trends such as improvement of benthic conditions.

Lee Grapentine (Primary Presenter/Author), Environment Canada, Lee.Grapentine@ec.gc.ca;


11:15 - 11:30: / 102E RESPONSES OF AQUATIC INSECTS TO MAJOR IONS ASSOCIATED WITH MOUNTAINTOP REMOVAL AND VALLEY FILL OPERATIONS

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

RESPONSES OF AQUATIC INSECTS TO MAJOR IONS ASSOCIATED WITH MOUNTAINTOP REMOVAL AND VALLEY FILL OPERATIONS Salinization of streams and rivers is considered one of the most significant environmental threats to freshwater ecosystems globally. Although laboratory experiments indicate that aquatic insects are relatively salt-tolerant, field studies have shown that some groups, especially mayflies, are absent from high conductivity streams. Based on these field studies, the USEPA recently developed a field-based conductivity benchmark of 300 µS/cm for streams affected by mountaintop removal coal mining. This benchmark has been criticized because other confounding factors (e.g., residential development) may influence responses of aquatic insects. We conducted stream microcosm experiments to measure direct effects of several major ions (MgSO4, NaHCO3, NaCl) on community metabolism, macroinvertebrate drift, community structure and survival. Although results showed considerable variation among endpoints, we observed significant conductivity-response relationships for each major ion tested. Consistent with field studies, mayflies were highly sensitive to major ions and effects were observed at conductivity levels near the proposed EPA benchmark. These results support the hypothesis that major ions are toxic to some macroinvertebrates and that effects on benthic communities in the field are likely when conductivity exceeds this benchmark.

William Clements (Primary Presenter/Author), Colorado State University, william.clements@colostate.edu;


Christopher Kotalik (Co-Presenter/Co-Author), United States Geological Survey, ckotalik@usgs.gov;


11:30 - 11:45: / 102E AN ANALYSIS OF REPLICATE MACROINVERTEBRATE SAMPLES TO ASSESS UNCERTAINTY IN MEASURES OF TAXON ABSENCE IN WEST VIRGINIA STREAMS

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

AN ANALYSIS OF REPLICATE MACROINVERTEBRATE SAMPLES TO ASSESS UNCERTAINTY IN MEASURES OF TAXON ABSENCE IN WEST VIRGINIA STREAMS Recently, field-collected data from paired macroinvertebrate and water quality surveys have been used to establish thresholds for parameters such as nutrients, sediments, and conductivity. This use differs from the use for which they were collected. If field-collected data are to be used to establish water quality thresholds, consideration must be given to study design, data usability, and quantification of the uncertainty of measures (e.g., absence of taxa) that will be used to determine effects. To assess the reliability of absence determined with 200- and 300-count samples, we analyzed macroinvertebrate data from sites on three West Virginia streams with five replicate samples per site. These results corroborate our previous analyses, and indicate that absence determination at a site based on a single fixed-count subsample has significant uncertainty. We conclude that unintended bias resulting from a suboptimal sampling design may lead to bias in field-based water quality thresholds, and that a robust data quality objective process should be used when collecting new data or making use of existing data from biomonitoring programs to avoid erroneous conclusions and unintentionally biased water quality thresholds.

Shaun Roark (Primary Presenter/Author), GEI Consultants, Inc., sroark@geiconsultants.com;


Jeniffer Lynch (Co-Presenter/Co-Author), GEI Consultants, Inc., jlynch@geiconsultants.com;


Grant DeJong (Co-Presenter/Co-Author), Pensacola Christian College, gdejong@geiconsultants.com;


Amanda Kovach (Co-Presenter/Co-Author), GEI Consultants, Inc., akovach@geiconsultants.com;


Robert Gensemer (Co-Presenter/Co-Author), GEI Consultants, Inc., bgensemer;


Steve Canton (Co-Presenter/Co-Author), GEI Consultants, Inc., scanton@geiconsultants.com;


11:45 - 12:00: / 102E ACCOUNTING FOR TEMPORAL VARIABILITY OF CONDUCTIVITY FOR EFFECTIVE MANAGEMENT OF SALINITY AS A FRESHWATER AQUATIC LIFE STRESSOR

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

ACCOUNTING FOR TEMPORAL VARIABILITY OF CONDUCTIVITY FOR EFFECTIVE MANAGEMENT OF SALINITY AS A FRESHWATER AQUATIC LIFE STRESSOR Salinization is a growing threat to freshwater biota globally, including in Appalachian headwater streams influenced by coal mining in the U.S. In such streams, bioassessment and management of salinization impacts is typically based on seasonal surveys of electrical conductivity (a salinity surrogate) and benthic macroinvertebrates. However, temporal variability of salinity can affect development and application of regulatory endpoints. To quantify and account for such variability, we monitored conductivity continuously and surveyed benthic macroinvertebrates and conductivity seasonally (spring and autumn) over 30 months in 25 headwater streams spanning a gradient of salinity where non-salinity stressors are minimized. We found that conductivity was inconstant, exhibiting a spring minimum and autumn maximum, with frequent transient dilution spikes and recovery. In addition, biological-effect endpoints for conductivity derived using our spring survey data underestimated maximum salinity concentrations to which many invertebrate taxa are likely exposed over the course their life cycles. Here we examine alternative approaches for deriving and applying biological-effect endpoints for conductivity that account for its temporal variability.

Anthony Timpano (Primary Presenter/Author), Virginia Tech, atimpano@vt.edu;


Stephen Schoenholtz (Co-Presenter/Co-Author), Virginia Tech, schoenhs@vt.edu;


David Soucek (Co-Presenter/Co-Author), Illinois Natural History Survey, soucek@illinois.edu;


Carl Zipper (Co-Presenter/Co-Author), Virginia Tech, czip@vt.edu;