Spatio-temporal distributions and habitat hotspots of the winter-spring cohort of neon flying squid Ommastrephes bartramii in relation to oceanographic conditions in the Northwest Pacific Ocean

The spatio-temporal distribution and habitat hotspots of western winter-spring cohort of neon flying squid Ommastrephes bartramii in the Northwest Pacific Ocean were examined using Chinese squid-jigging fishery data and relevant environmental data during 1998-2009. An empirical cumulative distribution function approach was employed for evaluating squid's preference of biophysical environments. The following environmental variables were included because of their identified importance in influencing squid habitat: sea surface temperature (SST), sea surface height anomaly (SSHA), sea surface salinity (SSS), chlorophyll-a (Chl-a) concentration, mixed layer depth (MLD) and eddy kinetic energy (EKE). Integrated environmental probability maps were generated for identifying the squid habitat hotspots. The distribution and abundance of O. bartramii exhibited interannual and seasonal variability. Annual latitudinal and longitudinal gravity centers were mainly located in the waters between 41.7° and 43.4°N and between 154.2° and 160.4°E, respectively. The nominal catch-per-unit-effort (CPUE) was high in 2003-2005, 2007 and 2008, but was relatively low in 2001, 2002 and 2009. The highest CPUE occurred in August. The inferred optimal ranges for SST, SSHA, SSS, Chl-a, MLD and EKE, determined from the cumulative distribution curves, were 17.6-18.6°C, -5-1.5cm, 33.58-33.79psu, 0.41-0.55mgm^-3, 15.5-18.5m and 28-35.5cm²s^-2, respectively. Potential habitat hotspots identified for O. bartramii coincided with locations of subarctic front zone (SAFZ). Approximately 72% of the average O. bartramii CPUE observations were found in the regions with probability indices higher than 0.6. The O. bartramii CPUEs tended to increase with the increasing integrated environmental probability values over 1998-2007. The predicted areas of high CPUEs corresponded well with the fishery observation data in 2008 and 2009. This study improves our understanding of spatio-temporal variability in the habitat hotspots of O. bartramii. Similar approach may also be used to predict habitat hotspots distributions of other pelagic species.