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

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

Space: John Day River

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

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

Collection and maternal origin P. Stratis photos Distance from centrum (microns) Sr/Ca ratio Two fish + water sample Four otoliths

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

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

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

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

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

Anadromy varied with stream size

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

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

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

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

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