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).