Developing Regional-Scale Stressor-Response Models for Use in Environmental Decision-making
Title: Application of Individual-based Fish Models to Regional Decision-making
Principal Investigators: Roland Lamberson, Steven F. Railsback
Project summary: Individual-based models (IBMs) simulate stressor effects on populations as emerging from how individual organisms interact with their environment and each other. As stressor-response models, IBMs have many potential advantages: (1) Complex, nonlinear interactions among stressors emerge naturally from the model instead of having to be written into the model (2) Population consequences of stressor effects that are known only at the individual level (e.g., from laboratory studies) can be predicted; (3) Transient responses to time varying stressors can be predicted, (4) IBMs are developed from a wide variety of information, not just calibrated to field data, (5) IBMs can be tested and validated in many ways, and (6) IBMs can be very general, needing only habitat data for application to new sites. Our IBMs for stream salmonids have undergone extensive verification and validation, and have been applied to diverse river management and research issues. These IBMs predict population dynamics as a function of: daily stream flow, temperature, and turbidity; stream channel shape; food production; and mortality risks. New stressors (e.g., toxins) are easily added.
Our objectives are to develop and demonstrate the usefulness of our salmonid IBMs for regional decision making, by (1) adapting our IBM that simulates linked stream reaches for watershed-level assessment, (2) conducting a demonstration assessment, and (3) examining uncertainties and sensitivities in the regional assessment.
Our approach will use existing models and data sets in a demonstration assessment of (1) turbidity effects of timber harvests (managed via TMDLs) and (2) instream flows at a water project (managed via FERC license requirements), interacting with (3) introduction of an exotic, piscivorous fish. Assessment endpoints will include trout population persistence, relative abundance of two competing trout species, total trout production, and reproductive success. Patterns of response over time and stream characteristics (size, slope, elevation, etc.) will be determined for scenerios representing alternative sediment TMDLs and instream flow requirements. Management for each issue will be evaluated separately, then in combination to identify interactions; these experiments will be repeated with and without the introduced piscivore. We will evaluate assessment uncertainties to determine the need for precision in model calibration and the field data describing habitat.
Expected results are assessment methods that make the benefits of IBMs available to watershed managers. Our IBMs already provide many of the capabilities sought by the EPA under this solicitation. This project will make these capabilities available for regional decision making.