A Rapid-Assessment Method to Estimate the Distribution of Juvenile Chinook Salmon in Tributary Habitats Using eDNA and Occupancy Estimation

Abstract

Identification and protection of water bodies used by anadromous species are critical in light of increasing threats to fish populations, yet often challenging given budgetary and logistical limitations. Noninvasive, rapid-assessment, sampling techniques may reduce costs and effort while increasing species detection efficiencies. We used an intrinsic potential (IP) habitat model to identify high-quality rearing habitats for Chinook Salmon Oncorhynchus tshawytscha and select sites to sample throughout the Chena River basin, Alaska, for juvenile occupancy using an environmental DNA (eDNA) approach. Water samples were collected from 75 tributary sites in 2014 and 2015. The presence of Chinook Salmon DNA in water samples was assessed using a species-specific quantitative PCR (qPCR) assay. The IP model predicted over 900 stream kilometers in the basin to support high-quality (IP ≥ 0.75) rearing habitat. Occupancy estimation based on eDNA samples indicated that 80% and 56% of previously unsampled sites classified as high or low IP (IP < 0.75), respectively, were occupied. The probability of detection (p) of Chinook Salmon DNA from three replicate water samples was high (p = 0.76) but varied with drainage area (km2). A power analysis indicated high power to detect proportional changes in occupancy based on parameter values estimated from eDNA occupancy models, although power curves were not symmetrical around zero, indicating greater power to detect positive than negative proportional changes in occupancy. Overall, the combination of IP habitat modeling and occupancy estimation provided a useful, rapid-assessment method to predict and subsequently quantify the distribution of juvenile salmon in previously unsampled tributary habitats. Additionally, these methods are flexible and can be modified for application to other species and in other locations, which may contribute towards improved population monitoring and management.