Pop-up archival satellite tags (PSATs)

A total of 38 silver eels were equipped with two different kinds of PSATs (Supplementary Table 1): 27 tags were X-tags from Microwave Telemetry (http://www.microwavetelemetry.com) and 11 were SeaTag-GEOs from Desert Star Company (http://desertstar.com/). Each X-tag measures 120 mm in length, has a maximum diameter of 32 mm and weighs 45 g in air. On board sensors collect and archive data on depth, water temperature and light every 2 min. X-tags were programmed to record 12-bit resolution measurements of light, temperature (range −4 °C to+40 °C, 0.23 °C accuracy) and pressure (range 0–1,296 m, 0.3–5 m resolution) and to store the records in the 64 Mb FLASH memory. At the end of each day (Universal Time Coordinates), the archived data for the previous 24 h is processed within the tag to build up a subset of the data (15-min intervals for temperature and depth, minimum and maximum light level and sunrise and sunset estimates) for transmission to the Argos low earth orbiting satellite system (http://www.argos-system.org/) after tag release. In case of premature death of the host or detachment of the tag from its host, the X-tags were programmed to initiate the pop-up procedure and transmit data after 7 consecutive days of constant depth readings (±3 m) with a 15-day delay following deployment (that is, the tag ignores constant pressure for the first 15 days). The SeaTag-GEOs are 132 mm in length, 13 mm in diameter for the main section and a weight 29 g in air. Their internal memory allowed to record temperature (−40 to +85 °C, 0.2 °C accuracy) and geomagnetic field values (3 axes) either three or four times a day during 3–4.5 months. Light sensors are also on board so day length and noon estimates are also transmitted. The SeaTag-GEOs were programmed to transmit both raw data and daily average for 2 months after the programmed dates. Unlike the X-tags, the SeaTag-GEOs have a solar battery and transmit their data continuously, that is, as soon as they are at the surface, satellites can pick up the data.

Capture and eel tagging

All eels used in the experiments were wild silver eels caught while performing their downstream migration from fresh or brackish waters. They were all caught by commercial fishermen who used fyke nets and were kept for several days in appropriate basins before retrieval. To minimize the negative effects of drag caused by the external tags, eels were selected for tagging on the basis of their large size and body mass. In 2012 and 2013, the selected eels originated from NS and were caught and released at the same location. In 2012, several locations in NS were visited in order to find the largest eels. In 2014, based on the previous year’s experiments and results, it was decided to use the largest eels that can be found in the entire species range: eels from the St. Lawrence system31. Indeed, the latter were on average 109 cm in total length (maximum of 120 cm) and 2.9 kg in body mass (maximum of 3.7 kg), whereas the largest eels that we found in NS reached a maximum of 93 cm in total length (85 cm on average) and 2.0 kg in body mass (1.4 kg on average; Supplementary Table 1). The eels from the St. Lawrence system were caught in the brackish estuary (Rivière Ouelle, 47.44°N, 70.03°W, Fig. 1) and transported by truck to the tagging and release location in Blandford, NS (Supplementary Table 1 and Fig. 1) at ca 860 km of driving from the capture location. It represents an aquatic shortcut of around 1,400 km for translocated eels, which consequently did not have to cross the lower estuary and the Gulf of St. Lawrence to reach the open ocean, thereby avoiding high predation6.

The tagging procedure (surgery and tag attachment method) was the same as previously used and detailed in Béguer-Pon et al.6 but for the last 2 years two attachment points instead of four were used. Furthermore, based on a recent study about the tag effect30, it was decided for the last year of experiment to attach the tag closer to the head of the eels (0.125 body length from the tip of the snout) instead of at their centre of mass (0.35 body length), in order to reduce the potential negative impact due to the drag of the tag.

For all years’ experiments, tagged eels were released at the same time along with 12 non-tagged eels since swimming in schools can provide fish with a number of behavioural and ecological advantages, such as reduced predation risk or energy saving32. It is not really known whether or not silver eels swim in schools during their oceanic migration but there are reports indicating eels tend to aggregate in large groups during their seaward migration33. It was also observed that silver eels migrating down the St. Lawrence River show a synchrony in the time of their passage in the brackish estuary5,34, suggesting that eels could travel together during the marine phase of the migration. In 2012, eels were released in very shallow waters, directly from the beaches or docks at the tagging locations. In 2013 and 2014, eels were transported and released 5–10 km offshore, where the water depth is 30–50 m.

This study was carried out in strict accordance with the recommendations of the Canadian Council on Animal Care. The protocol was approved by the Animal Care Committee, Laval University (Permit Number 2011101-01) and Maurice-Lamontagne Institute, Fisheries and Oceans Canada (Permit Number 12-6C). All surgery was performed under acetyleugenol (220 p.p.m.) and all efforts were made to minimize suffering.

Reconstructing the daily locations

Geolocation of ‘pop-up’/detachment events. All tags popped up earlier than the programmed dates. Except for two tags that were ingested by homeothermic fish, the reason for premature release could not be identified and could be various: failure in the attachment system, predation by ectothermic fishes or death of the eels. The release mechanism of X-tags was triggered by constant pressure during 7 consecutive days; they were actually drifting at the surface for 7 days before the first transmitting location was calculated by Argos system. Therefore, the first transmitting locations were not the locations where the tags detached and reached the surface. We thus inferred the location of their detachment using the temperature and light data collected at the surface. Sunset and sunrise estimates were used to calculate the longitude (with a 0.5° uncertainty), whereas the latitude was inferred from the surface water temperature (±1 °C). The package ‘oce’ in R35,36 was used to calculate the longitude from sunrise and sunset. For all X-tags, sunset and sunrise estimates from the day of their detachment or following it could not be used as they were clearly erroneous. We used the maximum drifting distance observed during 5 days after the beginning of the transmission to increase the longitudinal search limits, as well as the directions of currents observed while the tags were drifting. As previously mentioned, data transmitted by the SeaTag-GEOs can be received by satellites as soon as the tags are at the surface, leading to only a few hours of drift before detection in most cases. Their first transmitting Argos location may thus reflect the location where the tag reached the surface. However, for some SeaTag-GEOs it was noticed that reliable sunset and sunrise were provided 2–5 days before the first locations were calculated by the Argos system, indicating these tags were probably drifting at the surface during that period (no depth sensor on these tags) but the data were not transmitted right away (for unknown reasons). We thus used the same method as for the X-tags to infer the geolocation of the pop-up events.

Temperatures recorded by the tags at the surface were matched with strongly assimilated physical models: HYCOM for data of 2012 and 2013 experiments and the operational Mercator global ocean 1/12° analysis and forecast system for 2014 experiments as HYCOM had missing data during our 2014 tracking period.

HYCOM has 1/12° equatorial resolution and latitudinal resolution of 1/12° cos(lat) or ∼7 km for each variable at mid-latitudes. It has 40 coordinate surfaces in the vertical. The data assimilation is performed using the Navy Coupled Ocean Data Assimilation37 system with a model forecast as the first guess. Navy Coupled Ocean Data Assimilation assimilates available satellite altimeter observations (along the track obtained via the NAVOCEANO Altimeter Data Fusion Center), satellite and in situ sea surface temperatures as well as available in situ vertical temperature and salinity profiles from XBTs, ARGO floats and moored buoys.

The operational Mercator global ocean 1/12° analysis and forecast system uses the NEMO 3.1 (Nucleus for European Models of the Ocean) modelling system, coupled to the thermodynamic-dynamic sea ice model LIM2 (Louvain sea Ice Model 2). The ocean model has a horizontal resolution of 9 km at the equator, 7 km at Cape Hatteras (mid-latitudes) and 2 km towards the Ross and Weddell seas. The ocean model has 50 levels in the vertical with 1 m resolution at the surface decreasing to 450 m at the bottom, and 22 levels within the upper 100 m. The 3-hourly atmospheric fields forcing the ocean model are taken from the European Centre for Medium-Range Weather Forecasts Integrated Forecast System. This modelling system assimilates jointly satellite sea level anomaly (Jason2, Cryosat, Saral-Altika) and sea surface temperature (Reynolds AVHRR-AMSR 1/4°), and in situ profiles of temperature and salinity. A detailed description of the modelling system and the quality of its product can be found at http://www.myocean.eu/web/69-myocean-interactive-catalogue.php?option=com_csw&view=details&product_id=GLOBAL_ANALYSIS_FORECAST_PHYS_001_002. Salinity is reported using the Practical Salinity Scale.

We checked that the modelled sea surface temperature was compatible with the temperature observed by the tags during their free drifting stage. It should be noted that the modelled sea surface temperature represents the daily mean temperature of the top 1 m water column. However, the temperature sensor on the tag measures the water temperature at a depth of ∼5 cm while drifting at the surface.

For each daily reconstructed location, we calculated the distance between the minimum and maximum estimates of latitude and longitude. These distances provided a measure of the uncertainty around the daily reconstructed locations. The uncertainty around the estimated pop-up locations varied among tags and was on average 120±94 km in latitude (mean±s.d.; range: 9–288) and 77±37 km in longitude (range: 20–148; Supplementary Table 3).

Geolocation of daily tracks. Traditionally, light data are used to infer the longitude9 but as eels avoid the euphotic zone during daytime and the light sensors on the tags are not sensitive enough to record reliable sunset and sunrise estimates10, we developed another method similar to the one used in Westerberg et al.12. According to the data recorded by the two kinds of tags, we used the bathymetry, DVM behaviour and temperatures at specific depths to infer the geolocation of eels equipped with X-tags and the temperature (point records, not daily averages) and the geomagnetic field total intensity for eels equipped with SeaTag-GEOs.

In some cases, the depths recorded by X-tags were assumed to be the bottom, as a constant value for several hours and days was observed. This was the case for several tags for only a few days following their release. The daily geolocation in these cases were inferred by matching the observed water depth and associated temperature to the 30 arc-second GEBCO bathymetry and the results from the operational ocean circulation model assuming the maximum distance eels could have travelled in one day in any direction to be 60 km.

When clear DVM patterns were observed, we estimated the sunrise and sunset times from the vertical profiles using the statistical R package ‘breakpoints’, which implements the cross-entropy method38. This method is based on a stochastic optimization technique to estimate both the number and their corresponding locations of break-points in biological sequences of continuous and discrete measurements. Estimating sunrise and sunset from vertical profiles of eels was used in Westerberg et al.12 to calculate the longitude. Furthermore, Chow et al.10 tracked several Japanese eels (A. japonica) using ultrasonic transmitters and determined that eels started descending 55 min before sunrise (±10 min) and started ascending at sunset (±2 min). Considering the individual and daily variability described in Chow et al.10 and considering our sampling rate (15 min versus 2 min in the study that used acoustic tags) we decided to apply a 15-min uncertainty around the sunrise and sunset estimates. This leads to an average of±1.2° uncertainty in longitude (that is, around 400 km). The possible daily locations of eels equipped with X-tags were then further constrained by searching the modelled temperature field from the operational ocean circulation model within the range of mean±s.d. of observed temperature at the maximum depth that was reached by the eel each day and the temperature in the depth layer 0–200 m.

For eels equipped with SeaTag-GEOs, as there was no depth record, we matched the temperatures recorded by the tags with temperatures from the HYCOM model for all depth layers between the surface and 800 m. The geomagnetic field total intensity data (Gnt) recorded by the SeaTags-GEOs were matched with the modelled values from the International Geomagnetic Reference Field–IRGF- (www.ngdc.noaa.gov/IAGA/vmod/irgf.html). The real-time tracking data (while the tags were drifting) were used to calibrate the geomagnetic field values. The discrepancy between the Gnt recorded by the tags at the surface and the modelled data from IGRF was on average of 800 nT (range: 92–4,000 nT). For each tag, the calculated standard deviation of the discrepancy between the tag and the model was used as a measure of uncertainty around the Gnt value recorded by the tag for constraining the geolocation. Some Gnt values were obviously erroneous and thus not taken into account for the constraint. Although the constraint using temperature generally led to latitudinal error estimates, the Gnt constraint led to oblique strips because of the natural gradient of this environmental data.

Following the constraints from the environmental data, the inferred locations were finally constrained using both backward and forward in time tracking procedures with a maximum daily travel speed we assume the eels could have gone in any direction (60 km per day). No hypothesis about preferred directions were made.

Methodological limitations of the PSAT technology

The placing of PSAT on a relatively small marine species such as eel may adversely affect behaviour and produce distorted patterns of movement and erroneous interpretations of migratory behaviour, as observed with other species39. Several laboratory studies have shown that PSATs increase drag and can significantly impair the swimming performance of relatively small eels28,29,30. The eels tagged in 2013 were about half the body mass of the eels tagged in 2014. The ground migratory speeds between the edge of Scotian Shelf and the open waters at the exit of the Laurentian Channel was 2.2–5 times slower for the smallest eels compared with the largest eels, potentially reflecting increased drag from the PSAT affecting the smallest eels. The pop-up locations on the western part of the Scotian Shelf could also reflect the difficulty of eels to swim against the main westward current. The potential impact of carrying a PSAT on vertical migratory behaviour is unknown. As the DVM was also exhibited by eels tagged with internal acoustic tags10, the PSAT is not responsible for this behaviour. However, it remains unknown if the maximum and minimal depths at which eels swim could be affected by the external tag.

Another limitation of using PSATs comes from the data recorded by the tags and our ability to reconstruct the migratory paths. The X-tags record depth, temperature and light every 2 min but these data cannot be assessed until the tags are physically retrieved, which is just about impossible in our study area because of its vastness. A subset of data is transmitted to satellites: depth and temperature at 15-min intervals, minimal and maximum daily light levels and sunset and sunrise estimates. We used the depth data to infer the longitude, as sunset and sunrise estimates from light sensors were not available. Because of the data sampling rate and the individual and daily variability of DVM observed in another study10, the uncertainty in longitude estimate was around 1.2° (around 400 km). This uncertainty could be reduced with a higher sampling rate and better correlations between migration depth and light intensity in our study area. The latitudes were inferred using the temperature recorded at specific depths by X-tags. The uncertainty of the reconstructed latitudes thus comes from the accuracy of the recorded data and from the resolution and accuracy of the operational ocean circulation models used to compare with the archival data. In this study, the ocean models have horizontal resolutions of around 7–9 km, defining thus the minimal uncertainty of the reconstructed path and preventing assessment of finer horizontal movements. For the SeaTag-GEOs, temperature data were limited to 3–4 values a day with no depth records, forcing us to consider all depth layers in the search for matching values, thus increasing the uncertainty of locations. These tags record geomagnetic field total intensity values that allow us to constraint location in oblique strips. We noticed various issues with the geomagnetic data: we had to calibrate the values using real-time tracking data (while the tags were drifting) and high discrepancies between recorded data and the modelled data from the International Geomagnetic Reference Field (up to 4,000 nT) were noted. Furthermore, some of recorded geomagnetic values were obviously erroneous (for instance leading to inferred locations at several thousands of kilometres) and had to be discarded from the analysis. The overall uncertainty of reconstructed trajectories was higher in the case of SeaTag-GEOs compared with X-tags. X-tags have a higher sampling rate, do record depth, have more reliable data and had a higher transmitting rate (97% versus 48%).