Albacore Occurrence Data
We used two previously published occurrence datasets for albacore tuna in the NEP (Figure 1): fishery-dependent vessel logbook records and fishery-independent archival tags. Vessel logbook data were obtained from U.S. pole-and-line and troll fisheries, which target juvenile albacore throughout the NEP (Muhling et al. 2019; Figure 1). The logbook program has been in place since the early 1970s, providing daily, set-level catch information for albacore within the spatial extent of the fishery (Frawley et al. 2020). To account for varying degrees of accuracy in occurrence locations reported, data was filtered to remove duplicates, points on land, points outside the NEP, and locations reported in whole degrees, assuming that these were approximations (Muhling et al. 2019). To align with the temporal extent at which environmental data were available, vessel logbook records were filtered to retain records between 1995 - 2019. While the proportion of active fishing vessels participating in the logbook program has varied over time, the composition of the fleet and the distribution of effort has remained relatively consistent since the 1990s, which falls within the temporal extent of this study (Frawley et al. 2020).
Fishery-independent data consisted of archival tags deployed on 25 individual juvenile albacore across the NEP from 2003 to 2016 (Figure 1). This dataset was generated by the Albacore Archival Tagging Program, which is a collaborative effort between the National Marine Fisheries Service and the American Fishermen’s Research Foundation to tag albacore in the NEP (Childers et al. 2011, Snyder et al. 2017). Albacore were fitted with one of three models of archival tags (Lotek LTD2310, LotekLAT2810, and Wildlife Computers MK9). To construct the most probable tracks from archival tagged albacore, we used a hidden Markov model (HMMoce R package; Braun et al. 2018), that compares tag-based observations against oceanographic measurements to provide daily location estimates and the associated uncertainty for each tagged individual (see additional details in Arostegui et al. 2023). To reduce the autocorrelation structure, both datasets were independently filtered to remove records with duplicate environmental conditions for each month (Varela et al. 2014). Lastly, data were filtered to include the spatial extent of 180oW - 100oW and 10oN- 57oN to focus the analysis on the NEP, as this is where the majority of logbook and tagging data were located (Figure 1) and where MHW intensities have been greatest (Welch et al. 2023).