Summary

We will tag Chinook salmon, coho salmon, steelhead, and bull trout with a combination of acoustic tags and pop-up satellite tags (PST) to provide critical information on spatial and temporal distribution of salmonids to inform salmon management and Southern Resident Killer Whale (killer whale) management. Fishery independent data that delineates the distribution of salmonids within the Pacific Ocean is lacking, especially in winter. The Olympic Coast National Marine Sanctuary, off the coast of Washington, is an important habitat for populations of Pacific salmonids, many of which are listed as threatened or endangered under the Endangered Species Act. Importantly, we know very little about the occurrence and movements of threatened salmonid populations, beyond locations where most fishing and scientific sampling occurs. Conditions in the ocean are highly influential for salmonid growth, survival, and population dynamics and have been identified as an important area where fish-eating killer whales forage on salmonids.

Salmonids are of particular interest to killer whale managers because they are important prey for this endangered species. Similarly, there is evidence that salmonid abundance affects killer whale survival and fitness. The overlap of resident killer whales and salmonids in space and time affects the distribution and effort expended by foraging killer whales, and the resulting impact on salmonid survival. A better understanding of the distribution of salmon in the ocean would improve U. S. National Oceanic and Atmospheric Administration Fisheries (NOAA Fisheries) decisions for both salmonids and killer whales.

We will employ two types of tags with advanced-technology. Pop-up satellite tags are attached externally on the dorsal muscle of a fish. These tags are programmed to detach from the fish at a specified time, float to the surface, and transmit the location via ARGOS satellite. The second type (acoustic) of tags is surgically implanted internally in the fish. These tags emit sonic pings at 69 kHz every 60-120 seconds and have a range of approximately one kilometer. Fish will be tracked with stationary acoustic receivers, which decode the ping to identify the date, time and individual ID of the fish. We will also conduct coastal shelf surveys to detect acoustically tagged species using an AUV (Slocum Glider) integrated with VEMCO acoustic receivers. Our team has extensive experience capturing and handling salmonids in the coastal environment off the coast of Washington, and we anticipate few difficulties capturing or obtaining fish. PSTs have been successfully attached to steelhead, Atlantic salmon (Hedger et al. 2017), Dolly Varden, eels, juvenile Atlantic bluefin tuna, and albacore tuna. Acoustic tags have been successfully implanted in many species of fish including salmonids (Smith et al. 2015). Therefore, we believe that we will have a high probability of successful tagging.

To develop a better understanding of the overlap between salmonids and killer whales, we propose to tag fish with PSTs and acoustic tags to document their marine movement patterns. To maximize success, we propose to focus our initial efforts on threatened steelhead and Chinook salmon. Adult steelhead that return to sea after spawning (kelts; > 65 cm fork length) will be obtained from kelt reconditioning ponds and outfitted with state-of- the-art PSTs (archival) that record temperature, depth, and location information or an acoustic tag. Female steelhead kelts, which are post-spawning steelhead that migrate to the ocean before spawning again, have a high probability of surviving for a year or more in the marine environment. Moreover, as full-grown adults, these fish are large enough to be ideal killer whale prey. Acoustic tags allow smaller individuals to be tagged (~25 cm) than PSTs (> 65 cm). We will also tag sub-adult Chinook salmon captured by hook and line sampling in the coastal ocean or coastal rivers that could interact with killer whales.

We will combine the remotely sensed and modeled oceanographic data to characterize the conditions these species experienced during their marine residence. This technology will result in more precise and comprehensive distribution information, improving assessments of salmonid distribution in ocean and coastal environments. We will use oceanographic models to determine spatially explicit environmental conditions within the ocean. Coupling this information with temporally explicit detection data we can determine the relationship between salmonid distributions and specific habitat attributes. Using this information, we will estimate the travel route, residence time and rate of movement for each tagged fish and build species distribution models that characterizes their occupancy.

Objective:Our objective is to describe the distribution, behavior, and habitat relationships of salmon species in the nearshore coastal California Current north of the Columbia River. We will focus on first-winter (Age 2) Chinook salmon and steelhead kelts (post-spawning).

Questions

Will response (behavior) variables will have a relationship with physical habitat features and individual fish metrics?

Will Chinook salmon exhibit similar behaviors to each other or will they be idiosyncratic?

Are there distribution and behavior differences nearshore vs. offshore?

Do spatial hotspots, where fish are present more often than random (likely influenced by habitat) exist?

Modelling approaches

Linear relationships (linear mixed effects model)

Creating groups (ordination/cluster)

Multivariate groups (e.g., MANOVA)

Species distribution modelling (e.g., maxent)

Literature Cited

Hedger, R. D., A. H. Rikardsen, and E. B. Thorstad. 2017. Pop-up satellite archival tag effects on the diving behaviour, growth and survival of adult Atlantic salmon Salmo salar at sea. Journal of Fish Biology 1758:1–17.

Smith, J. M., K. L. Fresh, A. N. Kagley, and T. P. Quinn. 2015. Ultrasonic telemetry reveals seasonal variation in depth distribution and diel vertical migrations of sub-adult Chinook and coho salmon in Puget Sound. Marine Ecology Progress Series, 532: 227–242.