Advances in Fish Tagging and Marking Technology

In-Stream Monitoring of PIT-tagged Wild Spring/Summer Chinook Salmon Juveniles in Valley Creek, Idaho

Stephen Achord, Benjamin P. Sandford, Steven G. Smith, William R. Wassard, and Earl F. Prentice

doi: https://doi.org/10.47886/9781934874271.ch11

Abstract.—Recent advances in passive integrated transponder (PIT) tag technology have allowed the development of in-stream fish-monitoring systems. We installed two such systems in Valley Creek near its confluence with the Salmon River in summer 2002. In the summers of 2003–2005 we collected and PIT tagged wild spring/summer Chinook salmon parr Oncorhynchus tshawytscha in natal rearing areas upstream from the monitors. Although subsequent detection numbers between fall 2003 and spring 2006 were low and variable, they were sufficient to determine timing and estimate survival. We defined migrational groups by period of detection: late summer and fall (August–October), winter (November–February), and the following spring (March–June). Combining 3 years of data, the mean proportions of fish detected during these three respective detection periods were 60.6, 27.7, and 11.7%. Mean probability estimates of survival from Valley Creek to Lower Granite or Little Goose Dams were 9.2, 23.4, and 40.8% for the respective late summer and fall, winter, and spring periods. Estimated overall mean probabilities of survival were 46.6% from tagging as parr to movement into the mouth of Valley Creek and 17.3% from Valley Creek to Lower Granite Dam. The overall mean parr-to-smolt survival estimate from tagging to arrival at Lower Granite Dam was 9.0%. The unexpectedly high proportion of fish migrating in winter has important implications for fish monitoring studies that use rotary screw or scoop traps: these traps are generally inoperable during winter near most natal rearing areas and thus may result in biased estimates of fish population status and migration timing. Advancements in technologies and methodologies to instream PIT-tag monitoring systems will improve data quality to assist recovery planning for threatened and endangered fish species.