Depth use of wild Atlantic salmon post-smolts migrating through fjords

doi:10.21203/rs.3.rs-5016368/v1

Juvenile Atlantic salmon (Salmo salar), known as post-smolt as they enter the sea, undergo an arduous migration from their natal rivers to their feeding grounds in the North Atlantic Ocean. Here, we present data on the depth use of migrating wild Atlantic salmon post-smolts. Using acoustic telemetry, tagged fish from four rivers in two fjords in western Norway were monitored as they migrated towards the open sea during two consecutive years. We found that post-smolts predominantly migrated in the top three meters of the water column throughout the length of both fjord systems. Among 61 successful migrants, 95% of detections were in the top three meters of the water column. This corresponds well with past findings showing similar depth use in hatchery-reared smolt and in adult Atlantic salmon kelts returning to their feeding grounds after spawning. We found little evidence of a consistent diel pattern in depth use. Our results support assumptions of representative sampling when trawling the upper portion of the water column for post-smolts in order to estimate sea lice infection rates and may improve the precision of efforts to model sea-lice infection risk. The results may also be valuable in evaluating other threats to wild salmon.

Atlantic salmon

smolt

migration

acoustic telemetry

depth

The post-smolt migration of juvenile Atlantic salmon from their natal rivers to their feeding grounds in the North Atlantic is fraught with danger. In addition to the constant threats of predation, starvation, and exhaustion (1), the rapid growth of the salmon farming industry over the past 40 years has led to an increase in the numbers of parasitic copepods (salmon lice, Lepeophtheirus salmonis, Caligus elongatus) that inhabit the water column throughout the coastal zones where salmon farming occurs (Dempster et al. 2021). Infection by these salmon lice can lead to substantial direct physiological costs and risks of secondary infections, exacerbating the probability that post-smolts succumb to predation and exhaustion (2). As the pelagic infectious life-stages of salmon lice are known to have specific depth preferences based on light, temperature, and salinity (3–5), it has become increasingly important to understand how the depth use of migrating salmonids react to these same environmental variables.

The depth use of salmon post-smolts is also valuable information for evaluating the impact of other threats to wild salmon, including the risk of migrating post-smolts transmitting the monogenean ectoparasite Gyrodactylus salaris between freshwater environments, the effects of disposing mine tailings in fjords on post-smolt, predation, and changing physio-chemical coastal conditions due to climate change or other anthropogenic alterations (e.g. Drinkwater & Frank, 1994).

In order to better understand these impacts, baseline data on the depth use of migrating salmon post-smolts is in high demand. Many lines of inquiry all suggest a preference for migrating within the top few meters of the water column. Efforts to sample post-smolts via trawling find most success in the upper 10 meters of the water column(7,8). Previous work using active tracking of acoustically tagged hatchery-reared post-smolts has indicated that these migrate in the top four meters of the water column and that they swim closer to the surface when the light intensity is low (9,10). Salmon post-smolts tagged with data storage tags have recorded temperatures consistent with a shallow depth use, with a clear diel pattern, along with occasional deep dives (11,12). Most recently, Newton et al., (2021) measured the depth of wild post-smolts at a transect crossing the Moray Firth, roughly 70 kilometers from the estuary. These smolts were observed at a mean depth of 0.8 meters and displayed a diel rhythm of roughly half a meter. However, direct measurements of the depth use of wild in situ Atlantic salmon post-smolts in Norwegian fjords have yet to be reported.

Here, wild Atlantic salmon post-smolts from four populations in two different fjords were tagged with acoustic transmitters equipped with a pressure sensor for measurements of swimming depth , with two years of data from each population. The two fjords are among the longest in Norway, such that migration distance from river mouth to open sea varies from 110 to 160 kilometers among these populations. A passive receiver network was deployed to gather data on these post-smolts throughout their fjord migration.

Though a passive receiver network does not allow for the near continuous observations offered by data storage tags (e.g., Einarsson et al., 2018) or the manual tracking (e.g., Davidsen et al., 2008) of acoustically tagged fish, it allows for the sampling of depth use of migrating salmon smolts across a wide span of time and space (14). Further, active tracking is a laborious procedure such that the number of fish that is feasible to track is limited, while passive receiver networks scale well with larger sample sizes. Simultaneously, advances in the miniaturization of acoustic tags now allow for the possibility of tagging wild smolts with depth-sensor tags. Previously, this was only possible to do with the typically larger hatchery-reared smolts, which may or may not represent wild fish (e.g., Jonsson et al., 1991; Urke et al., 2013).

In Norway, the smolt migration generally occurs between April and June when the fish are 1-6 years old and between 10 and 20 centimeters long (17,18). Migration is timed to coincide with the spring swell of productivity in the Atlantic Ocean (19) and requires a physiological and morphological transformation known as smoltification that allows them to osmoregulate in seawater and prepares them for their pelagic migratory lifestyle.

Key questions that we aimed to elucidate included 1) what depths do post-smolts use as they migrate through fjord systems? 2) does the depth use differ among fjords, among different parts of the fjord, or through time? 3) how do variable environmental conditions influence depth use?

Study System

This study was conducted in two different fjords in western Norway, Nordfjord and Hardangerfjord (Figure 1). With lengths of approximately 110 and 160 km respectively, Nordfjord and Hardangerfjord are among the longest fjords in Norway. Each provides a relatively complex migration route for the post-smolts to navigate, with widths ranging from 2-7 km and many branching fjord arms and inlets. Both fjords are in areas of Norway where the sea lice-induced mortality is estimated to be high (20).

Smolt individuals from two rivers in each fjord were tagged in both 2018 and 2019: Stryn and Eid in Nordfjord, and Eio and Granvin in Hardangerfjord. All of these rivers have their outlets in the inner fjord, such that smolts emigrating from these rivers must swim more than 50-120 km to reach the open sea. Similarly, each of these rivers have comparable hydrodynamics as they are all relatively short and drain from a large lake surrounded by mountains.

Due to the influx of freshwater from precipitation and snowmelt from the surrounding mountains during springtime, a brackish layer of highly variable extent is created in the upper water column of the fjords. Interannual and geographical variation in timing and magnitude of freshwater input, alongside variable hydrographic conditions in the marine environment, render this variation large at the relevant timescales of post-smolt migration. As smolts from these rivers generally do not begin their migration before the spring snowmelt has begun (21), post-smolts can use this brackish layer to graduate their acclimation to seawater (see Supplementary Materials).

In Hardangerfjord and neighboring Bjørnafjord, a total of 106 Thelma Biotel receivers (TBR700) were deployed. In Nordfjord, 71 Innovasea (VR2W) receivers were deployed (Figure 1). All receivers were moored and attached to ropes with the hydrophones oriented in a downward position, with buoys ensuring that the receivers were positioned 3-4 meters below the surface. Within each fjord, the receivers were grouped into zones A-D such that zone A consisted of the area surrounding each estuary, zone D consisted of the outer fjord near to the open sea, and zones B and C were intermediary zones between zone A and D (Figure 1). These are the same groupings used for the survival analysis in Bjerck et al., 2021.

Fish Sampling and Tagging

In April of each year, pre-smolts were captured using DC electrofishing (Ing. Paulsen, Norway, FA4 ,1600V, 80Hz) in each river. The fish were kept in 60 L holding tanks with flow of river water for 24 hours prior to tagging. These fish were then tagged with ThelmaBiotel acoustic tags (D-LP7), using the procedure described in Bjerck et al. (2021). These tags have a weight in air of 2.0 grams and a length of 21.5 millimeters and are designed to transmit both the ID of the tag and the depth of the tag with a resolution of 0.2 meters every 30-90 seconds. The pressure sensors within these tags have much higher internal resolution, but the acoustic protocol restricts the tags to transmit data as a single byte in order to minimize the amount of information being sent per transmission. This means that the maximum depth they are able to record is 51 meters. The tags transmitted signals with signal strength 139 dB Re 1 μPa @ 1 m and they were set to automatically deactivate after 155-200 days. This signal strength corresponds with a detection range on the order of 200 meters, though this is known to vary substantially through time and space with changing ocean conditions (22,23). The average length of smolts tagged with depth transmitters was 14.7 cm (SD= 1.1 cm). The tagging protocol was approved by Norwegian Authorities for animal welfare (FOTS IDs: 12002 and 15471).

Quality Control

As these tags measure depth by measuring water pressure, air pressure was controlled for by retrieving hourly weather data from the Norwegian Meteorological Institute (seklima.met.no). In Nordfjord, weather data from the Sandane Airport (SN58100) was used and, in Hardanger, weather data from Kvamsøy (SN50070) was used. There was little variation between these two stations despite the 160 kilometers separating them such that greater spatial resolution was not considered necessary. Further, variation in the calibration of the depth sensor was corrected for by retrieving the factory test value of each tag from Thelma Biotel and the air pressure from the closest weather station to the factory (Selbu II, SN68290).

The spatio-temporal migration trajectories of each individual were inspected visually in order to identify false detections and mortalities/tag losses. Detections occurring at unlikely or impossible locations in relation to the rest of an individual’s trajectory were removed. Mortality was identified based on depth data, as predated fish would often first exhibit erratic depth movements and then stop at a constant depth (or varying according to tidal cycles). Efforts were made to remove detections occurring after mortality or tag loss from the analysis.

Further, only smolts that were detected as successful migrants (i.e., smolts that were detected in the outer reaches of the fjord (zone D in Figure 1)) and which had at least 10 detections in the fjord were included in the analysis. This was a conservative approach to ensure that the data used in the quantitative analyses actually represented migrating salmon smolts rather than movements of predators (see e.g. Daniels et al., 2019). We assumed that it is unlikely that a predator of a tagged smolt will continue to exhibit a migratory trajectory similar to a post-smolt with the tag within its stomach. The use of acoustic tags designed to detect predation has revealed that this can happen within freshwater (Lennox et al. 2021), but this has yet to be documented within the fjord environment. Acoustic tagging of brown trout (Salmo trutta) from the rivers of Granvin and Eio, one of the primary potential predators of migrating smolts in these populations, showed that the majority of those that migrated did not venture out in the outer fjord (25), with similar results in Sognefjorden, a fjord in between the fjords studied here (26).

Generalized Linear Mixed Effects Modelling

In order to investigate to what extent variables of interest accounted for variation in depth use, a generalized linear mixed effects model with log-link as the link function was fitted to the data with ID as a random intercept effect using the function glmer in the R package lme4 (27). Candidate models reflecting hypotheses pertinent to the study objectives were subjected to model selection by using the Akaike Information Criterion (AIC) aiming at finding the model(s) that most efficiently explained the variance in depth use. Models attaining DAIC-values <2 were considered to have substantial support in the data (28). Variables fitted in the model included fjord zone, fjord, river of origin, waterway distance to the river mouth of origin, day of year, the position of the sun with respect to the horizon, and a parameterized version of the position of the sun.

In order to test if depth use was correlated with light conditions (sensu Davidsen et al., 2008), the sun’s vertical position was used as a predictor. The position of the sun with respect to the horizon in degrees for a given time and position was determined through the use of the R package suncalc (29). This was then parameterized with the function:

such that the parameterized values flattened out when darkness and true daylight arrived but changed continuously during dusk and dawn (see Supplementary Materials). The parameterized values therefore reflect more of a day/night switch than the raw values which change continuously through the day and night. This approach was used as, due to the high latitude of the study system, the angle at which the sun moves with respect to the horizon is very acute, leading to prolonged dusk/dawn periods. Additionally, later in the season, true darkness becomes an impossibility at these latitudes as the sun reaches its nadir just below the horizon.

After quality control, 7013 detections across 61 individuals remained (Table 1). However, the number of observations per individual ranged widely, with a median of 64 observations per individual. Median depths for individuals with at least 10 observations ranged between 0.2 and 2.3 meters. The mean of median depths across these individuals was 0.96 meters. 95 % of these observations were at 3 meters or less (Figure 2). Some outliers ranged between depths of 10-50 meters, but in all but one case, the post-smolt did not return to the upper layers of the water column (Figure 3), indicating that these outliers are likely associated with mortality.

Table 1: Summary of numbers of individuals tagged along with numbers of individuals after quality control, along with fish size at tagging (mean±SD) for individuals before quality control. Tag burden is defined as the ratio of the weight of the tag to the weight of the fish at tagging in air (mean±SD).

River Year	# Tagged	# after QC	Length (cm)	Weight (g)	Tag burden
Eid 2018	24	15	13.76±0.65	20.95±2.97	0.10±0.02
Eid 2019	32	11	15.05±0.94	28.02±6.08	0.08±0.02
Eio 2018	31	5	15.28±1.2	29.54±5.82	0.07±0.01
Eio 2019	44	5	14.62±1.01	26.95±10.36	0.08±0.02
Granvin 2018	32	9	14.73±0.88	24.86±3.96	0.09±0.01
Granvin 2019	21	5	15.47±1.24	28.46±6.1	0.08±0.02
Stryn 2018	13	3	13.79±1.17	21.88±6.85	0.10±0.02
Stryn 2019	51	8	14.46±0.96	25.04±5.41	0.09±0.01

The most supported model included an interaction effect between the sun position and fjord zone with individual ID as a random effect. Both the intercepts and the slopes of these effects were allowed to vary with individual ID in the selected model. See Table S1 in the Supplementary Materials for the model structures and AIC values of all fitted models. The fixed-effects in the model explained 6.3 % of the variation in depth-use and, by including the random-effects, the model explained 32.4 % of the variation (Table 2). The selected model did not attain overwhelmingly higher AIC-support compared to other candidate models. In total, five additional candidate models attained DAIC-values less than or equal to 2. A common feature to all these models were the inclusion of fjord zone and sun position as fixed effects.

Table 2: Model parameter estimates of the most supported model fitted to depth-use data for Atlantic salmon post-smolts in two western Norway fjord systems during 2018 and 2019. Estimates are on ln-scale. Sun position scaling parameters: mean=13.4; SD=20.6. σ²=residual variance; τ₀₀=among-individual intercept variance; τ₁₁=among-individual slope variance; ρ₀₁= the random-slope-intercept-correlation; ICC=intraclass correlation coefficient.

	Response= log(Depth)
Fixed effect terms	Estimates	CI	p
Intercept	0.07	-0.08 – 0.21	0.353
Sun Position (scaled)	0.07	-0.04 – 0.18	0.230
Zone [B]	-0.10	-0.39 – 0.19	0.494
Zone [C]	-0.37	-0.69 – -0.05	0.022
Zone [D]	-0.40	-0.60 – -0.20	<0.001
Sun Position * Zone [B]	0.38	0.21 – 0.55	<0.001
Sun Position * Zone [C]	0.12	-0.08 – 0.31	0.239
Sun Position * Zone [D]	0.13	0.04 – 0.23	0.007
Random Effects
σ²	0.51
τ₀₀ _full.id	0.13
τ₁₁ _{full.id.scale.sun.pos}	0.07
τ₁₁ _{full.id.zoneb}	0.28
τ₁₁ _{full.id.zonec}	0.38
τ₁₁ _{full.id.zoned}	0.22
ρ₀₁	0.24
	-0.77
	-0.69
	-0.68
ICC	0.28
N _full.id	61
Observations	7011
Marginal R² / Conditional R²	0.063 / 0.324

This model predicted that the average depth at daytime (sun positioned 18 degrees above the horizon) in zone A was 1.25 meters, while the average depth at nighttime (sun positioned 12 degrees below the horizon) in zone D was 0.68 meters (Table 3, Figure 4).

Adding effects of fjord or year did not improve the model (Table S1) indicating that there was no substantial difference in smolt behavior between years or fjords.

Table 3: Mean predicted depth across all individuals at nighttime (sun positioned 12 degrees below the horizon) and at daytime (sun positioned 18 degrees above the horizon) in each zone, along with standard deviations in parentheses.

Zone	Nighttime Depth (m)	Daytime Depth (m)
A	1.16 (0.58)	1.25 (0.60)
B	0.60 (0.20)	1.12 (0.39)
C	0.74 (0.57)	0.82 (0.24)
D	0.68 (0.38)	0.84 (0.29)

Throughout the fjord, outmigrating smolts were primarily detected within the top 3 meters of the water column. To our knowledge, this is the first study to report depth-use data for wild Atlantic salmon post-smolts as they migrate through fjords, though the behavior observed here is remarkably similar to that observed in wild smolts on the coasts of Scotland and Ireland (13, 30). Other studies focusing on hatchery-reared post-smolts have also reported similar results (10, 31–33), indicating that wild and hatchery-reared post-smolt have the same depth use despite the differences in size and early-life experience. Similarly, Atlantic salmon kelts (34) and domesticated salmon in net pens seem to also use the upper few meters of the water column (35), though kelts are known to occasionally dive to depths greater than 200 meters while out in the open sea (34, 36).

This study’s most supported depth-use model showed that both fjord zone and the position of the sun had statistically significant effects on the depth use of post-smolts. However, these effects were small and largely inconsistent across individuals (Fig. 4). Previous work showing diel migration behavior has had access to direct measures of light intensity (31), while we inferred light intensity through the time of day and the position of the detection. As this region of Norway is notoriously cloudy, actual light intensities may vary substantially with the position of the sun. As the work of Davidsen et al. (2009) implies, deeper depth use during daytime may be a direct reaction to light intensity rather than a true diel rhythm, reflecting that this behavior may be a tactic for reducing the risk of avian predation. That the final model included the raw values for the position of the sun rather than the parameterized values reflects that this effect is not a simple day/night switch and that the angle at which the sun’s rays penetrate the ocean surface is important.

The effect of fjord zone on depth use showed that smolts tended to swim slightly deeper in zone A, near the estuary. This effect is largely driven by the higher variance in depth use observed in the estuary. As all of the migrating smolts were detected in these bottlenecks, detections in the estuary accounted for a large portion of the detections in zone A. When the detections in the estuary were removed, the effect of fjord zone on depth use was no longer significant. The higher variance in depth use observed in the estuary is not unexpected as the transition from freshwater to seawater requires that smolts transition from dwelling within the gravelly substrate of the riverbed to swimming across an open ocean. Some of these detections may have occurred before this transition was made.

Regardless, the magnitude of the observed effects of fjord zone and sun position ranged from 0.1 to 0.5 meters (Table 3). This is on the order of our expected error due to the resolution of our measurements, wave action, and/or spatial variation in air pressure, and is arguably not a biologically significant change in depth use.

We found little support in the data for any effects of fjord, day of the year, or river of origin on depth use, though model convergence issues precluded the testing of overly complex models. Given the low amounts of variation in depth use observed, if these variables truly do have an effect on depth use, they must necessarily be small as well.

Only one dive deeper than 15 meters was recorded in the data after quality control. Though there were several deep dives in the raw data, in all but this one case the tags were not detected in the upper water column again. It was therefore assumed that these dives constituted the movements of predators and were therefore removed from the analysis. Work with data-storage tags has shown that post-smolts often undertake deep dives, but not during the first weeks of migration (11, 37). It may be that this behavior does not manifest until the post-smolts are in the open sea, beyond the reach of our receiver network. That said, Newton et al. (2021) observed one smolt at a depth greater than 25 meters which subsequently returned to shallow depths in the Moray Firth. Given the non-continuous nature of the data, it may be unlikely to record these kinds of dives if the time spent at great depths is on the order of minutes.

Post-smolts collected by trawling in this area of Norway are known to primarily feed on fish larvae and Euphasiids as they migrate (38). Though these prey items can be found at the depths at which post-smolts were observed, they seem to be found in substantially higher densities at deeper depths, especially during the day (39–41). This indicates that migrating at shallow depths is not a behavior meant to maximize the rate at which prey items are encountered. The rate at which these smolts migrate also implies that these smolts are primarily concerned with reaching the open ocean and do not spend great amounts of time foraging (21).

Our data justifies the practice of surface trawling for monitoring of sea-lice infestation data for migrating salmon post-smolts employed by the National Monitoring Program of Salmon Lice (NALO). Trawling of the top 3–4 meters of the water column should produce representative samples of in situ migrating post-smolts, regardless of the time of day for the trawling operation.

In conclusion, post-smolts seem to be traversing large fjord systems with large environmental variability in salinity and temperature at an essentially fixed depth. This indicates that post-smolts likely rely on environmental cues near the surface for navigation. This result also suggests that susceptibility to sea lice infections may be modelled using a simple behavioral model for post-smolts, along with relevant input from environmental data and sea lice depth preferences.

Ethical Approval

The sampling and tagging protocol was approved by Norwegian authorities for animal welfare (FOTS IDs: 12002 and 15471).

Availability of Data & Materials

The data presented here is available for dissemination upon reasonable request.

Acknowledgements

The authors would like to thank the river-owner’s organizations in all rivers, as well as all aquaculture companies present in the regions for facilitating our work and the deployment of equipment. A large number of people contributed during the fieldwork, a big thank you to all of them. Special thanks to John Birger Ulvund for conducting all surgery implanting the tags in the fish.

Funding

The study was conducted as a part of two long-term studies on salmonids: KLAFF and SalmonTracking 2030. The former is funded by County Governor of Vestland, Blom Fiskeoppdrett AS, Nordfjord Laks AS, Mowi AS, Coast Seafood AS, Selstad AS, Nordfjord Forsøksstasjon AS and Eid and Stryn river owner organizations and the latter is funded by PO3/4 Kunnskapsinkubator and FHF – Norwegian Seafood Research Fund (901575).

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

H.B.B. wrote the first draft, analyzed and interpreted the data, and assisted with sampling and data collection. H.A.U. designed and planned the study, assisted with interpretation of data, and carried out fish sampling and data collection. T.O.H. assisted with the design of the study, and assisted with the analysis and interpretation of data. J.A.A. assisted with the design of the study and of the methodology. T.K. assisted with the design and planning of the study, assisted with fish sampling and data collection, and assisted with the interpretation of data. All authors contributed to editing the final draft.

Consent for Publication

Not applicable.

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No competing interests reported.

depthusesuppinfo.docx

Depth use of wild Atlantic salmon post-smolts migrating through fjords

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