Julie K. Nielsen

The Pacific sleeper shark (Somniosus pacificus) is a long-lived, deep-water, sub-polar species that exhibits flexible foraging strategies, likely combining scavenging with active predation on a broad range of prey, yet their role in marine food webs and impact on commercial species remain undetermined. Tracking the location of Pacific sleeper sharks in Alaskan coastal waters is extremely challenging given the predominantly aphotic depths that these sharks occupy, often in spatially constrained and critically under-sampled regions: deep, steep-flanked, convoluted fjords of Prince William Sound (PWS). From the first ever, year-long depth and temperature records recovered from archiving pop-up satellite-linked transmitters (n = 7), we characterized the residence distributions, depth, and thermal habitat for sharks within the PWS fjords and identified seasonal and temporal variation in habitat use. Depths recorded from the seven sharks ranged from 3 to 572 m, and pop-up tag locations suggested a high degree intra-annual residency within western PWS. Ambient water temperatures ranged from 2.65 to 11.1 °C, with little deviation from the median of 5.9 °C. Seasonal patterns emerged within and across individuals relative to the variation in vertical movements, ambient temperatures, and horizontal movements that could reflect resource-oriented strategies. The high degree of residency combined with extensive use of the water column facilitates the use of physically recoverable, high-resolution behavioral and environmental samplers on Pacific sleeper sharks. This adaptive sampling using Pacific sleeper sharks as platforms of opportunity may in turn enable the use of Pacific sleeper sharks as climate and ecosystem sentinels.

The Pacific sleeper shark (Somniosus pacificus, PSS) is a long-lived, deep-water and sub-polar species that exhibits flexible foraging strategies, likely combining scavenging with active predation on a broad range of prey, yet their role in marine food chains and impact on commercial species remain undetermined. Tracking the location of PSS in Alaskan coastal waters is extremely challenging given the predominantly aphotic depths that these sharks occupy, often in spatially constrained and critically under-sampled regions: deep, steep-flanked, convoluted fjords of Prince William Sound (PWS). From the first ever, year-long depth and temperature records recovered from archiving pop-up satellite-linked transmitters (n=7), we characterized the residence distributions, depth, and thermal habitat for sharks within the PWS fjords and identified seasonal and temporal variation in habitat use. Depths recorded from the seven sharks ranged from 3-572m, and pop-up tag locations suggested a high degree intra-annual residency within western PWS. Ambient water temperatures ranged from 2.65 to 11.1⁰C, with little deviation from the median of 5.9⁰C. Seasonal patterns emerged within and across individuals relative to the variation in vertical movements, ambient temperatures, and horizontal movements that could reflect resource-oriented strategies. The high degree of residency combined with extensive use of the water column facilitates the use of physically recoverable, high-resolution behavioral and environmental samplers on PSS. This adaptive sampling using PSS as platforms of opportunity may in turn enable the use of PSS as climate and ecosystem sentinels.

The summertime distribution of Pacific cod in the Bering Sea shifted dramatically northward into the Northern Bering Sea (NBS) during 2017–2019 in conjunction with unprecedented ocean warming. In 2019, we tagged 38 NBS Pacific cod with pop-up satellite archival tags during summer foraging to characterize seasonal migration to winter spawning locations. Geolocation results for 31 Pacific cod indicate that tagged Pacific cod moved out of the NBS shelf area beginning in November ahead of oncoming winter sea ice. Most tagged fish (77% geolocation probability) moved to traditional spawning areas in the Eastern Bering Sea during the peak spawning period, but some crossed international and internal management boundaries by moving into Russian waters and the Gulf of Alaska (16% and 7% geolocation probability, respectively). Our results demonstrate that Pacific cod are tightly coupled to seasonal environmental changes and suggest that recent northward shifts in summertime distributions are tied to warm-water expansion of foraging habitat. Our findings underscore the need for adaptive management strategies to address the challenges of shifting fish distributions under changing environmental conditions.

Background: Fish geolocation methods are most effective when they are customized to account for species behavior and study area characteristics. Here, we provide an example of customizing a hidden Markov model (HMM) for reconstructing movement pathways of a high-latitude demersal fish species in a remote island chain using Pop-up Satellite Archival Tag (PSAT) data. Adult Pacific cod were tagged with PSATs while occupying winter spawning grounds in the Aleutian Islands in February 2019. We adapted a demersal fish application of the HMM to (1) add light-based longitude to the data likelihood model, (2) account for possible off-bottom behavior of demersal fishes in the maximum daily depth likelihood, and (3) modify the model framework to accommodate convoluted island topography in the study area. A simulation study was conducted to explore the two primary modifications to the model framework, reflecting boundary for the movement kernel and the Viterbi method of pathway reconstruction, under known conditions. Results: Geolocation was performed on satellite-transmitted and detailed archival data sets from 6 adult Pacific cod at liberty for 21–277 days. Migration from winter spawning to summer foraging areas (range 60–395 km) was detected for the 4 tagged fish that were at liberty for more than 90 days. Light-based longitude was the primary geolocation variable for detecting migrations with precision (root mean square error) estimates of 0.56 degrees during winter and 1.3 degrees during the summer. Simulation studies confirmed the effectiveness of model framework modifications and generated guidelines for use in specific applications. Conclusions: This study demonstrates that post-spawning migrations of Pacific cod in the Aleutian Islands can be detected and characterized using PSAT data. Initial insights into migrations, summer foraging areas, and associated development of appropriate analysis tools will support future Pacific cod movement studies in the Aleutian Islands as well as other regions of Alaska. The adaptations to the HMM presented here will benefit current and future research on demersal fish in other regions as well as fish species that occupy areas with convoluted shorelines or island chain topography.

Fisheries scientists and managers must track rapid shifts in fish spatial distribution to mitigate stakeholder conflict and optimize survey designs, and these spatial shifts result in part from animal movement. Information regarding animal movement can be obtained from selection experiments, tagging studies, flux through movement gates (e.g. acoustic arrays), fishery catch‐per‐unit effort (CPUE), resource surveys and genetic/chemical markers. However, there are few accessible approaches to combine these data types while accounting for spatially correlated residual patterns. We therefore discuss a movement model involving diffusion (random movement), taxis (movement towards preferred habitat) and advection (passive drift following ocean currents). We specifically outline how these movement processes can be fitted to data while discretizing space and time and estimating non‐linear habitat preferences using environmental layers as well as spatial process errors. Finally, we introduce an R package, ATM, by fitting the model to bottom trawl survey, longline fishery and tagging data for Pacific cod (Gadus macrocephalus, Gadidae) in the Bering Sea during winter/summer seasons from 1982 to 2019. Combining data types predicts an increasing proportion of cod residing in the northern Bering Sea from 2013 to 2019, and estimates are informative in a recent stock assessment model. We fit sensitivity analyses by dropping tag, survey or fishery data, and this analysis shows that tagging data are necessary to identify diffusion rates, while survey data are informative about movement among biogeographic strata. This “hybrid” species distribution model can help explain poleward movement, project distributions under future climate conditions and evaluate alternative tag‐deployment scenarios to optimize tagging designs.

Background: Archival tags that measure the Earth’s magnetic field could provide a new geolocation method for demersal fishes in the North Pacific Ocean. However, the presence of local magnetic field anomalies caused by geological formations such as volcanic rock and temporal fluctuations from solar storms could complicate its use in some high-latitude areas of the North Pacific Ocean. We assessed the potential value of adding geomagnetic data to a depth-based state-space model for geolocation of demersal fishes in Glacier Bay National Park, USA, a high-latitude magnetic anomaly area. We developed a high-resolution (100 m) magnetic field map of the study area and assessed in situ tag resolution by deploying 5 geomagnetic archival tags on a stationary mooring for 8 months. We compared performance of 4 theoretical geomagnetic tag measurement resolutions (low = ± 1000 nT, medium = ± 500 nT, high = ± 300 nT, and very high = ± 150 nT), 2 map resolutions (coarse- or fine-scale), and 5 methods of geomagnetic variance specification by estimating locations of simulated random walk trajectories under the different treatment scenarios using a hidden Markov model. Results: Geomagnetic data improved model performance for both fine-scale and coarse-scale magnetic maps when tag resolutions were medium to very high and geomagnetic variance specification was based on error between measured and mapped values instead of study area attributes such as slope or roughness. Overall, the best model performance was observed for the highest tag resolution, the fine-scale map, and variance based on anomaly magnitudes. However, the coarse-scale map with a constant variance of 165 nT resulted in improvements over depth alone for all tag resolutions. In situ testing of mooring data suggests that the precision of the geomagnetic archival tags was comparable to the low and medium tag measurement resolutions tested in simulations, but variation in performance was high among tags. Conclusions: Our results suggest that inclusion of geomagnetic data could improve geolocation of demersal fishes in the North Pacific Ocean, but improvements to geomagnetic tags and additional information on magnetic field values measured at the seafloor compared to the sea surface are needed to ensure its utility.