Spatial and temporal overlap between hatchery- and natural-origin steelhead and Chinook salmon during spawning in the Klickitat River, Washington, USA
A goal of many segregated salmonid hatchery programs is to minimize potential interbreeding between hatchery- and natural-origin fish. To assess this on the Klickitat River, Washington, USA, we used radiotelemetry during 2009–2014 to evaluate spatiotemporal spawning overlap between hatchery-origin and natural-origin steelhead Oncorhynchus mykiss and spring Chinook Salmon O. tshawytscha. We estimated percentages of tagged fish that spawned naturally in the Klickitat River subbasin, emigrated from the Klickitat River, or died before spawning. For steelhead, 12% of hatchery-origin and 50% of natural-origin fish spawned naturally. For spring Chinook Salmon, 18% of hatchery-origin and 44% of natural-origin fish spawned naturally. Tag loss may result in underestimates in these percentages. Most hatchery-origin steelhead (90%) spawned downstream of rkm 32 and 75% spawned from November to mid-March, while the majority of natural-origin steelhead (64%) spawned upstream of rkm 32 and 75% spawned from mid-March to late May. Spawn timing of hatchery-origin Chinook Salmon (early August to mid-September) overlapped with that of natural-origin Chinook Salmon (late July to late September), and fish of both origins spawned in the same 30-km reach of the river. We estimated the percent of hatchery-origin spawners on the natural spawning grounds (pHOS) to be 12% for steelhead and 40% for spring Chinook Salmon across all study years. A kernel density analysis was used to estimate probability of spatiotemporal overlap between hatchery- and natural-origin spawners. For steelhead, we estimated this overlap to be 25% (95% CI 22.5–28%). For spring Chinook Salmon, tight spatial clustering of hatchery-origin fish resulted in a lower overlap estimate of 21% (13%-31%). We suggest adjusting pHOS estimates using these overlap estimates or similar spatiotemporal data on actual spawner proximity and possible interactions, and that these types of analyses be used in conjunction with gene flow analysis to accurately evaluate effects of individual hatchery programs.