Woodworth-Jefcoats et al.: Oceanographic variability, fishery expansion, and longline catches in the North Pacific 
237 
quarter. Catch rates of longnose lancetfish were not 
only highest in the NW region but were also highest 
within-region in the third quarter (Fig. 3B). There¬ 
fore, the fishery deployed more effort in a region where 
longnose lancetfish were more commonly caught and 
during the season when catch rates were highest. As 
a result, catch of longnose lancetfish, all of which was 
discarded, exceeded the catch of target species for the 
last decade of the study period (Fig. 3A). The same 
spatiotemporal shift in effort also explains the change 
in the contribution of mahi mahi to annual catch (Figs. 
3B and 4), although mahi mahi are retained by the 
fishery and sold. 
As with bigeye tuna, it is possible that both fish move¬ 
ment and population dynamics could have influenced 
changes in total composition of the catch. Tagging data 
and stock assessments are lacking for many of the spe¬ 
cies caught by the Hawaii-based longline fishery, espe¬ 
cially the noncommercial species. Future research on 
the seasonal timing, location, and size structure of this 
catch may provide insight into such changes. 
When using observer data to determine catch com¬ 
position, as we did, there is a possibility that observer 
error could influence results. Such errors in the report¬ 
ing of rare or cryptic species have been noted for indi¬ 
vidual longline sets and can influence results at fine 
spatiotemporal resolutions (e.g., months and single 
geographic degrees) and when observer coverage is low 
(Walsh et al., 2002; Walsh et al., 2005). However, it 
is not clear that such errors would be distinguishable 
when observer data are aggregated more broadly, such 
as on a quarterly and regional basis. Additionally, our 
results indicate strong agreement between data col¬ 
lected from independent scientific observers and data 
reported in commercial vessel logbooks for catch rates 
of bigeye tuna (Fig. 3A) and, therefore, consistent spe¬ 
cies identification of target species. The observed in¬ 
crease in catch of longnose lancetfish is corroborated 
by the regional expansion of the fishery: catch rates of 
longnose lancetfish were much higher in the NW re¬ 
gion than elsewhere (Fig. 3B), and, in the early years 
of our study, the fishery was not operating in the NW 
region (Fig. 2A). Therefore, we conclude that the im¬ 
pacts of fishery expansion on catch composition are 
robust. 
A look ahead 
We have detailed how both fishery expansion and 
oceanographic variability have influenced catch of the 
Hawaii-based longline fishery. In particular, we found 
that the fishery has expanded into a region that has 
proven to be an efficient fishing ground by virtue of its 
local oceanography. With this perspective on past catch, 
can CPUEs continue to rise into the future? The re¬ 
sults of previous work indicate that sustained increas¬ 
es in fishing effort drive down the abundance of large, 
high-trophic-level fish, such as those targeted by the 
Hawaii-based longline fishery (Ward and Myers, 2005b; 
Polovina et al., 2009; Polovina and Woodworth-Jefcoats, 
2013). We also note that, although bigeye tuna are not 
considered to be subject to overfishing in the NE region 
(Aires-da-Silva and Maunder, 2015), overfishing of big¬ 
eye tuna has been documented to be occurring in the 
3 western regions (Harley et al., 2014). This disparity 
creates the potential for further eastward displacement 
of fishing effort (both Hawaii-based and international) 
and for hastening removals of bigeye tuna. Therefore, 
it is possible that catch rates in the NE region eventu¬ 
ally will diminish as have the catch rates in the SW 
and CW regions over the past 20 years. 
Another change that will affect the fishery in coming 
years is the recent expansion of the Papahanaumokua- 
kea Marine National Monument. In August 2016, the 
monument boundaries were expanded to encompass 
the full U. S. Exclusive Economic Zone west of 163°W, 
moving the boundaries an additional 150 nm from land 
(Federal Register, 2016). This expansion bars commer¬ 
cial fishing over a portion of the fishing grounds and 
has the greatest effect on the CW region. On average, 
21% of the effort in the CW region in the fourth quarter 
(when fishing effort in this region is the greatest) and 
25% of the bigeye tuna caught in the CW region dur¬ 
ing the fourth quarter are from waters that will now 
be off limits to the fishery. It is uncertain how the fish¬ 
ery will adjust, possibly by simply relocating fourth 
quarter effort outside the monument area or by shift¬ 
ing the allocation of that effort to another quarter or 
region. 
Finally, climate change can be expected to affect the 
Hawaii-based longline fishery in a number of ways, po¬ 
tentially driving productive fishing grounds even far¬ 
ther from Hawaii. As ocean temperatures continue to 
rise, the preferred thermal habitat of bigeye tuna will 
be displaced northward (Lehodey et al., 2010; Bopp et 
al., 2013; Woodworth-Jefcoats et al., 2017). Addition¬ 
ally, the oxygen minimum zone that covers much of 
the SE region (Fig. IB) has expanded over the past 50 
years (Stramma et al., 2008). Although climate projec¬ 
tions of further expansion are mixed (Stramma et al., 
2008; Bopp et al., 2013; Cabre et al., 2015), continued 
expansion potentially would encroach on the NE region 
and render a larger portion of the SW region inhospi¬ 
table to bigeye tuna. 
We have shown how movement of the Hawaii-based 
longline fishery, particularly its seasonally focused ex¬ 
pansion to the NE region, has helped shape the com¬ 
position, magnitude, and seasonal timing of its catch. 
This information, together with previous studies of the 
effect of the Hawaii-based fishery on the ecosystem, as 
well as future climate projections and socioeconomic 
data (such as trip cost and catch value), has the poten¬ 
tial to help guide future fishery management actions. 
For example, recent increases in CPUE of bigeye tuna 
can be placed in the context of the high catch rates 
the fishery saw in the late 1990s. Climate models could 
be used to project future changes in habitat of bigeye 
tuna. Additionally, the effect of the continued expan¬ 
sion of the fishery away from Hawaii can be assessed 
in relation to other factors, such as future fuel prices 
