Habitat and Fish: correlation approaches, limitations, scale, and uncertainty

1. Habitat and Fish: correlation approaches, limitations, scale, and uncertainty

2. Correlation • Two things occur simultaneously in space or time (both) • Consistent pattern (predictions) • Does not imply causation (suggests hypotheses) • Biggest sources of uncertainty – difficulties determining causation

3. Salmonid Watershed Assessment Model (SWAM) Estimates relative distribution of fish based on broad-scale habitat features ln(redds/km + 0.5) = 6.89 - 0.3625t + 0.4216ln(w + 0.0001) + 0.0003546p

4. Salmonid Watershed Assessment Model (SWAM) Estimates relative distribution of fish based on broad-scale habitat features • map of where the highest densities of fish are likely to occur • ecological hypotheses about factors driving salmon abundances in a particular basin • factors to control when setting up monitoring projects or management experiments

5. Landscape Data Human Impacts Forest cover classes Land Surface Ownership Hydrology Geology Climate

6. SWAM CAN NOT Habitat Characterization and Capacity Historic production capacity Current production capacity Preliminary Identification of Recovery Actions Where to protect and how to protect Restoration actions Improvement per action Prioritization of actions

7. Model Uses • Identify areas likely to support high abundances • Prioritize areas for watershed assessments • Predict relative salmonid abundances behind barriers • Generate hypotheses about causal relationships • Identify important strata for monitoring programs

8. Example 2: Broad-Scale Habitat Inventory Predict fishoccupancy Predict habitat conditions Estimate habitat quantities Prioritize information needs Develop hypotheses

9. Broad-Scale Habitat Inventory I. Inventory Approach • Generate stream network • Segment network and calculate channel characteristics • Classify segments • Link segments with geospatial data II. Applications • Predicting in-stream conditions • Estimating population characteristics (extinction thresholds) • Predicting relative occupancy behind impassible barriers

11. Foster Creek, Clackamas Meets fish passage standards Deep Creek, Clackamas Does not meet fish passage standards Deep Creek, Clackamas Passage Unknown

13. Available Analysis Variables Stream Generation Model:stream gradient, stream order, valley floor width, side slope gradient Existing: precipitation, geology, land use, road density, wetlands, soil type, barriers, habitat survey data (partial coverage) Plan to Predict:channel width, pool density, bank stabilization, lateral habitat

14. Potential predictors: basin area, channel gradient, precipitation Channel Width 13 watersheds in WLC .15 < mR2 < 0.76 Overall mR2 = 0.41 Area > precip > gradient

16. Pool density (distribution) channel gradient, channel width, geology, constrained/unconstrained, land-use Probability of bank stabilization proximity to road, stream gradient, channel width, constrained/unconstrained, side slope gradient KM lateral habitat / KM main channel channel gradient, channel width, floodplain width E. Beamer

17. Uncertainty • Natural Variability • Measurement error • Parameter Uncertainty • Model Uncertainty • Prediction Uncertainty • Predictions across space, time, scale (correlation) • Mechanisms – survival as a function of habitat quality • Use of uncertain predictors • Range of conditions