Citation:

Cyterski, M J., R S. Parmar, M C. Barber, B Rashleigh, J M. Johnston, AND K Wolfe. PREDICTION OF FUNDAMENTAL ASSEMBLAGES OF MID-ATLANTIC HIGHLAND STREAM FISHES. Presented at EPA Science Forum 2004, Washington, DC, June 1-3, 2004.

Impact/Purpose:

The overall objective is to develop watershed modeling tools for the immediate client (CVI) and their stakeholders in the Mid-Atlantic Highlands. This research continues the contributions that REVA has made to the CVI toolset and adds modeling and decision support capabilities for more general use by managers. To facilitate the prediction and analysis of fish health issues by EPA Program and Regional Offices and other environmental agencies, process-based models that describe these processes will be implemented:

1. the expected trophic dynamics of the dominant fish species

2. the spawning and recruitment dynamics of the dominant fish species

3. the bioaccumulation of organic chemicals and metals in aquatic biota

4. how physical habitat and chemical water quality impact fish feeding, reproduction, survival, and migration

To facilitate the use and application of these models, graphical user interfaces (GUI), supporting databases, and libraries of management scenarios will also be developed. Models will be linkable to integrated water quality and hydrologic models that simulate habitat characteristics (e.g., water depth, current velocity, water temperature and sediment loadings) that determine the survival, reproduction, and recruitment of fish and aquatic invertebrates. Similar to what has been achieved in REVA, frameworks based on the biogeography of fish will be developed to apply these models spatially for regional assessments of important fish health issues.

Objectives of this task between FY03 and FY05:

To provide modeling and decision support capabilities for aquatic resources compatible with existing geographic information (GIS) frameworks to evaluate effectiveness (and ultimately cost-benefit) of restoration activities planned in Region 3, initially the Mid-Atlantic Highlands region. This includes the primary interests in evaluating riparian zone restoration (using Rosgen methods) and acid mine drainage remediation.

To develop methods that explicitly link process models and spatial analysis methods across spatial and temporal scales.

To identify knowledge and information gaps in the integration of REVA and process models that enable projections of future ecosystem state.

To create a new generation of quantitative environmental assessment tools that explicitly address issues of scale, are not restricted in extent of application, and enable efficient rescaling (both spatial and temporal).

This research supports long-term goals established in ORD's multi-year research plans for Both GPRA Goal 2 (Water Quality) and Goal 8.1.1 (Sound Science/Ecological Research). This research will provide the tools to assess and diagnose impairment in aquatic ecosystems and the sources of associated stressors and to forecast the ecological, economic and human health outcomes of alternative solutions. Central to this task (as described in Goal 8) is the development and demonstration of methods to the states, tribes and local managers to: (1) assess the condition of waterbodies in a scientifically-defensible and representative way while allowing for aggregation and assessment of trends at multiple scales, (2) diagnose cause and forecast future condition in a scientifically defensible fashion to more effectively protect and restore valued ecosystems, and (3) assess current and future ecological conditions, probable causes of impairments and management alternatives.

Description:

A statistical software tool, the Stream Fish Assemblage Predictor (SFAP), based on stream sampling data collected by the EPA in the mid-Atlantic Highlands, was developed to predict potential stream fish communities using characteristics of the stream and its watershed.
Step one in the tool development was a cluster analysis that formed groups of streams with similar fish species. Twenty-three clusters, each defined by a fundamental fish assemblage, resulted. Step two was a discriminant analysis, which produced a system of equations to predict a stream's fundamental fish assemblage (its cluster) based on characteristics of that stream and its watershed (e.g., stream slope, percent forested area in the watershed, stream bank vegetation, latitude, longitude).
The discriminant equations, when tested using our sample data, correctly predicted a stream's fish assemblage with approximately 35% accuracy. The chance of randomly choosing the correct cluster would be approximately 4% (1 chance in 23). The actual stream cluster was one of the three most probable predictions in 65% of the test cases. Randomly, given three choices, one would only have a 3 in 23 chance of picking the correct assemblage (13%).
These predicted fish assemblages can be used to estimate stream health. This software also allows users to investigate potential impacts of environmental restoration or degradation by altering stream and watershed characteristics, then examining changes in the predicted fish community. This tool was developed specifically for stakeholders of the Canaan Valley Institute, West Virginia, but can be implemented by all parties interested in stream fish communities of the Mid-Atlantic Highlands region. This tool is currently available from the Canaan Valley Institute's website at http://www.canaanvi.org/

Record Details: