1. Partial migration in Oncorhynchus mykiss: A spatially and sexually explicit approach Justin Mills, USGS/OSU (MS, 2008) Jason Dunham, USGS-FRESC Chris Jordan, NOAA-Fisheries Gordie Reeves, USFS-PNW John McMillan, USGS/OSU (MS 2009) Chris Zimmerman, USGS J. McMillan photos

2. Sex and migration Costs / benefits of migrationMalesFemales Decreased age-specific survivalXX Avoid poor freshwater conditionsXX Increased body sizeXX Fitness strongly size dependentoX J. McMillan photos

3. Space: John Day River

4. Study objectives 1) Broad-scale measures of female anadromy 2) Predict patterns of female anadromy 3) Assess potential importance of local variability

5. Study design Collect juvenile O. mykiss Determine maternal origin Test for non-random distribution Sites with anadromy Broad-scale environmental variable(s) Predictive model Test for residual spatial variation Tests of model performance Collect water samples

6. Collection and maternal origin P. Stratis photos 1 1.2 1.4 1.6 1.8 2 2.2 2.4 0200400600 Distance from centrum (microns) Sr/Ca ratio Two fish + water sample Four otoliths

7. Two rainbow trout offspring Anadromy was common, widespread Offspring of # Steelhead91 Rainbow trout 58 Anadromy at 52 of 72 sites One of each Two steelhead offspring

8. How is maternal origin distributed? R R R R S R R R S S S S S S S S S S S S S S S S R R R S S S S R R R R R R R S S S S S SR = Rainbow trout offspring = Rainbow trout offspring S = Steelhead offspring = Steelhead offspring Random distribution Numerical dominance or spatial segregation

9. Maternal origin was clustered Combination at siteObservedExpected Different maternal origin11 (23%)22.4 (48%) Same maternal origin36 (77%)24.6 (52%) Both steelhead23 (49%)17.3 (37%) Both rainbow trout13 (28%)7.3 (15%) n = 47 sites; only those with 2 juveniles < 2 years old  ² = 11.15, df = 1, P < 0.001

10. Objective 2: Predictive model Sites with anadromy Broad-scale environmental variable(s) Predictive model Test for residual spatial variation Tests of model performance

11. Stream size and anadromy Associated with many ecological and physical processes –Sediment transport –Water temperature –Biological organization Readily used in spatial statistics Simple to estimate for large area

12. Anadromy varied with stream size

13. Mantel test for spatial autocorrelation A B Euclideandistance Stream network distance ΔDistance ΔResidual Autocorrelated residuals

14. No spatial autocorrelation Mantel tests non-significant Spatial gradients accounted for by model Subset of 1/5 of pairwise distances

15. Bottom lines Sampling approach proved useful Female anadromy was predictable Stream size accounted for most of the broad-scale variability in female anadromy Local factors potentially source of remaining variability J. McMillan photos

16. Improvements Model improvements –Redd counts –Combined probabilistic predictions Local factors –Bioenergetics –Species interactions –Community effects –Ecosystem processes Doesn’t address males Doesn’t address resident females

18. The process: critical periods, sexual tension, and everything in-between The evidence: observation, model, experiment – correlation vs causation? The relevance: ESA listing, modeling, monitoring, recovery du les sauvages? Discussion