A Review of Interaction Between Neon Flying Squid (Ommastrephes bartramii) and Oceanographic Variability in the North Pacific Ocean

YU Wei, CHEN Xinjun,, YI Qian, and TIAN Siquan

1)College of Marine Sciences,Shanghai Ocean University,Shanghai201306,P. R. China

2)National Engineering Research Center for Oceanic Fisheries,Shanghai Ocean University,Shanghai201306,P. R. China

3)Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources of Ministry of Education,Shanghai Ocean University, Shanghai201306,P. R. China

4)Collaborative Innovation Center for Distant-water Fisheries,Shanghai201306,P. R. China

A Review of Interaction Between Neon Flying Squid (Ommastrephes bartramii) and Oceanographic Variability in the North Pacific Ocean

YU Wei1),4), CHEN Xinjun1),2),3),4),*, YI Qian1),2),3),4), and TIAN Siquan1),2),3),4)

1)College of Marine Sciences,Shanghai Ocean University,Shanghai201306,P. R. China

2)National Engineering Research Center for Oceanic Fisheries,Shanghai Ocean University,Shanghai201306,P. R. China

3)Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources of Ministry of Education,Shanghai Ocean University, Shanghai201306,P. R. China

4)Collaborative Innovation Center for Distant-water Fisheries,Shanghai201306,P. R. China

The neon flying squid (Ommastrephes bartramii) is a short-lived opportunistic species widely distributed in subtropical and temperate waters in the North Pacific Ocean. The life cycle ofO. bartramiifrom planktonic eggs to nektonic adults is closely linked to oceanographic conditions. The fluctuations inO. bartramiiabundance and distribution tend to increase and widen continuously due to the heavy influences of ocean-climate events on various spatio-temporal scales. In this study, we reviewed the interaction betweenO. bartramiiand oceanography variability in the North Pacific with respect to large-scale climatic-oceanic phenomena including El Ni?o, La Ni?a, Kuroshio, Oyashio and Pacific Decadal Oscillation (PDO), as well as regional environmental variables such as sea surface temperature (SST), sea surface height (SSH), sea surface salinity (SSS), chlorophyll-a (Chl-a) concentration, and plankton density. The population dynamics ofO. bartramiiis mediated mainly by meso- and large-scale climatic-oceanic events (e.g., Kuroshio and Oyashio Currents) rather than other local environmental conditions (e.g., SST and Chl-aconcentration), because all of the oceanographic influences are imposed on the context of large-scale climate changes (e.g., PDO). An unstructured-grid finitevolume coastal ocean model coupled with an individual-based model is proposed to simulate relevant physical-biological oceanographic processes for identifying ocean-climate influence and predictingO. bartramiidistribution and abundance in the North Pacific. Future research needs to be focused on improving the knowledge about early life history ofO. bartramiiand evaluating the relationship between marine physical environment and two separate passive drifting life stages ofO. bartramiiincluding free-floating eggs and planktonic paralarvae.

Ommastrephes bartramii; oceanographic influence; early life history; physical-biological model; North Pacific Ocean

1 Introduction

Cephalopods, characterized by fast growth and a short life span, are widely distributed in oceanic and neritic environments (Chenet al., 2009a). Over the last several decades, there has been a continuously increasing trend in the commercial catches of cephalopods, especially the most important squid in the family Ommastrephidae (Lipinski, 1973). However, the annual catch of squid fluctuates greatly probably due to the influence of inter- and intra-annual oceanographic variability of their feeding and spawning grounds (Boletzky, 1986; Boyle, 1990; Piatkowskiet al., 2001; Rodhouse, 2001; Rochaet al., 2001; Guerra, 2004; Boyle and Rodhouse, 2005). This is because the abundance and distribution of squid popula-tions are highly susceptible to climate changes and environmental conditions on a range of spatio-temporal scales (Pierceet al., 2008).

Extensive studies have found the strong relationship between ommastrephid squid abundance and marine environmental conditions on different scales. For example, Rosaet al.(2011) found that long-term (1970s-2000s) change in sea surface temperature (SST) impacted on the distribution of spawning grounds of Japanese common squid (Todarodes pacificus) which inhabited waters with the SST of 19.5 to 23℃. Similarly, Sakuraiet al. (2000) reported that SST had great impacts on the spawning areas and recruitment ofT. pacificusin the northern part of East China Sea and the southwestern Sea of Japan. Regarding large-scale climatic-oceanic phenomena, Xuet al. (2012) suggested that the El Ni?o/La Ni?a events were closely related to the distribution of fishing grounds of the Humboldt squid (Dosidicus gigas) which moved further northward in La Ni?a years than that in El Ni?o years.Anderson and Rodhouse (2001) suggested that El Ni?o conditions could support more successful paralarvae recruitments ofD. gigas. Additionally, Daweet al. (2000) reported that the abundance of short-finned squid (Illex illecebrosus) was correlated negatively with North Atlantic Oscillation (NAO) index and positively with SST off Newfoundland and meander of the Gulf Stream. Waludaet al. (1999, 2001a, 2001b) showed that the variability in SST, Falkland Current, and Patagonian shelf waters impacted on the distribution of spawning and fishing grounds ofIllex argentines, thereby influencing recruitment success and squid distribution.

The neon flying squid (Ommastrephes bartramii) is commonly known as the most abundant and economically important oceanic species in the family Ommastrephidae (Roperet al., 1984; Murata, 1990; Chenet al., 2009b).O. bartramiiis widely distributed in the North Pacific Ocean where its abundance and distribution are strongly influenced by marine environmental conditions on different spatio-temporal scales (Chenet al., 2007). In recent years, the impacts of large- and regional-scale oceanographic variability on the distribution and abundance ofO. bartramiihave become apparent (Caoet al., 2010), the recurring or occasional ocean-climate phenomena possibly result in dramatic booms or collapses in squid fishery. Therefore, to better understand the population dynamics ofO. bartramii, it is crucial to understand the interaction betweenO. bartramiiand environment.

In this paper, we summarize the life history ofO. bartramiiin the North Pacific regarding its population structure, distribution and abundance, age and growth, and migration behaviors. Further, we discuss the impacts of oceanographic variability onO. bartramiion large and regional scales. Finally, a mathematical modeling technique is proposed to describe the relationship betweenO. bartramiicharacteristics and oceanographic conditions based on a good understanding of relevant physical-biological processes and mechanisms. Our trials will contribute to developing the capacity of forecastingO. bartramiipopulation dynamics and improving the sustainable management of squid fishery resources.

2 Squid Life History in Relation to Oceanography

O. bartramiiis a short-lived (1-year life span) species mainly distributed between 20° and 50°N in the North Pacific (Roperet al., 1984). The population ofO. bartramiicomprises two putative seasonal cohorts (Yatsuet al., 1998)： an autumn cohort hatching between September and February with peak months of spawning in October (Chen and Chiu, 2003), and a winter-spring cohort with a putative hatching period from January to May with the peak month of spawning in March (Murata and Hayase, 1993). The spawning grounds ofO. bartramiiare inferred in the waters between 130° and 170°E and between 130° and 170°W (Murakamiet al., 1981; Young and Hirota, 1990) where the SST ranges from 21 to 25℃ (Saito, 1994; Bower, 1996; Moriet al., 1999a, 1999b; Sakai and Ichii, 2003).O. bartramiiparalarvae of the autumn cohort are mainly distributed in the latitude of 29°-34°N, while those of the winter-spring cohort move to 21°-30°N as a result of seasonal SST changes (Yatsuet al., 1997).

Researchers have examined life history difference between the two cohorts ofO. bartramiiin relation to the optimum spawning zone defined by SST and the foodrich zone defined by the transition zone chlorophyll front (Ichiiet al., 2009). There are evidences that the difference in the oceanographic environment leads to the variability in size structures (Murakamiet al., 1981; Murata, 1990; Yatsuet al., 1997; Chen and Chiu, 2003) and growth patterns ofO. bartramiipopulations (Chen and Chiu, 2003; Ichiiet al., 2004). Comparing to the stock of winterspring cohort, the autumn cohort comprises an extra large (LL) group with fast growth during the first half of the life cycle, while the winter-spring cohort is a mixture of individuals from large (L), small (S), and extra small (SS) groups which commonly grow fast in the second half of the life span (Ichiiet al., 2004).

O. bartramiiperforms extensive seasonal north-south migrations between subarctic feeding grounds and subtropical spawning waters (Fig.1; Gonget al., 1991; Seki, 1993; Murata and Nakamura, 1998). There are abundant stocks of the autumn cohort in the central and eastern North Pacific Ocean (Yatsuet al., 1998; Ichiiet al., 2009). This cohort begins to migrate southward from July to September and spawns in the subtropical frontal zone, yielding productive habitat, whereas females move northward in May and feed in the southern part of the subarctic frontal zone in June to July (Yatsuet al., 1997). The winter-spring cohort undertake migration from subtropical waters to the subarctic boundary during the first half of summer and shift northward into waters of the subarctic domain during August to November, whereas the spawning migration starts in October and November (Murata and Nakamura, 1998; Ichiiet al., 2006).

Fig.1 The migration pattern of neon flying squid (Ommastrephes bartramii) and the circulations in the North Pacific Ocean.

Additionally,O. bartramiiis characterized by diurnal vertical migration changing with the growth and geography (Yuet al., 2013). ParalarvalO. bartramiiare generally concentrated in the sea surface waters, such as the upper 40 m in Hawaiian waters (Young and Hirota, 1990) and the upper 25 m in Kuroshio Region (Saito and Kubodera, 1993). A diurnal vertical migration pattern of adultO. bartramiiin the North Pacific has been proposed as follows, 0-40 m depths during the nighttime and 150-300 m depths during the daytime (Murata, 1988). The changing patterns of light intensity and prey distributions are thought to be responsible for diurnal vertical movement ofO. bartramiipopulations (Murata and Nakamura, 1998).

Research on statolith microstructure can yield reliable information on the growth and habitat ofO. bartramii(Chenet al., 2006). Previous measurements of daily growth increments within the statoliths showed thatO. bartramiihad a 1-year life span and matured in approximately 7-10 months; and its size-at-maturity is approximately 30-33 cm for males and 40-55 cm for females, with generally higher growth rates in the latter than in the former (Yatsuet al., 1997). PlanktonicO. bartramiiparalarvae of the winter-spring cohort were predicted to grow exponentially during the first 35 days after hatching, and mantle lengths of 15-, 25- and 35-day-old paralarvae were estimated to be 1.6, 4.3 and 12.1 mm, with the growth rates of 0.16, 0.45 and 1.25 mm d-1, respectively (Bigelow and Landgraf, 1993). Yatsu and Mori (2000) further confirmed that there existed an exponential relationship between mantle length and age of the autumn cohort ofO. bartramiifor at least 33 days post hatching. Moreover, Sakaiet al. (2004) identified and quantified the relationship between paralarval growth ofO. bartramiiand SST in northern waters of Hawaii Islands. The two cohorts ofO. bartramiifollow different growth patterns, both of which are closely related to age (Mori, 1998; Yatsuet al., 1998).

The whole life cycle ofO. bartramiifrom eggs to adults is closely linked to oceanographic variability. The timing and location of squid breeding behavior may depend on the SST across the spawning grounds, whereas regional and seasonal variability in food availability and maturation processes are likely the determinants of the larval growth ofO. bartramii(Welch and Morris, 1993; Bigelow, 1994). During migration, the transitional areas between the Kuroshio and Oyashio Currents have great impacts on the transport, distribution, abundance, mortality, and recruitment ofO. bartramii(Bigelow, 1994). On the fishing ground, the distribution and abundance ofO. bartramiiare closely related to environmental variables and abnormal events on different scales, such as the big meanders of Kuroshio and Oyashio Currents (Anderson and Rodhouse, 2001), El Ni?o and La Ni?a (Chenet al., 2007), sea surface salinity (SSS), SST (Chen and Chiu, 1999; Chenet al., 2005), chlorophyll-a(Chl-a) concentration (Ichiiet al., 2011), and vertical temperature structure in waters of the fishing ground (Chenet al., 2010a). Global climate anomalies and regional environmental change can easily lead to the fluctuation of squid fishery resources (Yamagataet al., 1985; Argüelleset al., 2001; Rodhouse, 2001).

3 Impacts of Large-scale Oceanographic Variability

3.1 El Ni?o and La Ni?a

Being short-lived ecological opportunists,O. bartramiiinhabit the North Pacific Ocean, one of the most dynamic oceanographic environments with high variability on local to large scales (Chenet al., 2012). Abundance of the squid typically fluctuates as influenced by normal and/or extreme environmental conditions, in particular the El Ni?o and La Ni?a events that begin with a band of anomalously warm/cold water temperatures developed in the central and eastern equatorial Pacific (Sheinbaum, 2003). The evolution of El Ni?o and La Ni?a can be identified in the spatio-temporal changes of SST, Chl-aconcentration, primary productivity, zonal wind, and 20℃isotherm depth (a proxy for thermocline depth) anomalies of the TAO/TRITON array data along the equator (Wanget al., 2012a).

El Ni?o and La Ni?a events impose pronounced impacts on theO. bartramiidistribution and abundance. For example, Yatsuet al. (2000) first reported the fundamental consequences of inter-annual variability of La Ni?a/El Ni?o events forO. bartramiiin the North Pacific. Based on an analysis of long-term fluctuations in catch per unit effort (CPUE, 1979-1998), Yatsuet al. (2000) found that winter and summer water temperatures were lower in El Ni?o years than those in normal years, accounting for significantly reduced recruitment rate of the autumn cohort ofO. bartramii. Chenet al. (2007) analyzed Chinese commercial fisheries data of the winter-spring cohort ofO. bartramiiwith respect to environmental variables and suggested that the La Ni?a/El Ni?o events could cause differences in squid recruitment as a result of the influence of environmental conditions on the spawning grounds. Additionally, a La Ni?a event would result in a decrease in squid recruitment on the spawning ground with northward shifts of the fishing ground, whereas an El Ni?o event could yield a favorable habitat forO. bartramiion the spawning ground with southward shifts of the fishing ground (Chenet al., 2007).

In addition, the relationship between El Ni?o/La Ni?a and other squid or long-lived species has been studied. Nevárez-Martínezet al. (2000) noted that an El Ni?o event would cause a sharp decrease in the resources ofD. gigasand that the forces of upwelling currents strengthened in a La Ni?a year which led to an increase in the squid abundance. Jackson and Domeier (2003) examined the sizes of market squid (Loligo opalescens) hatched and grew in an El Ni?o year and found that the squid was strikingly smaller with lower growth rate than those in a La Ni?a year. Sugimotoet al. (2001) detailed the impacts of El Ni?o events and climate regime shifts on the living resources including short- and long-lived species in the western North Pacific. However, the existing studies are mainly focused on determining the correlation between squid abundance/distribution and El Ni?o/La Ni?a, and only described how the recruitment, abundance, and distribution of squid populations might change corresponding to the environmental variability on their spawning and feeding grounds. Our understanding of the mechanisms through which the El Ni?o/La Ni?a events result in the spatio-temporal variability in squid abundance and distribution is still limited so far.

3.2 The Kuroshio and Oyashio Currents

The oceanographic environment in the Northwest Pacific Ocean is dominated by the Kuroshio and Oyashio Currents, showing inter-annual and decadal variability including regime shifts (Yatsuet al., 2013). Being the western boundary currents in the North Pacific, both the Kuroshio and Oyashio Currents have great effects on fisheries, ecosystems and climate (Aoki and Miyashita, 2000; Sakuraiet al., 2000; Sakurai, 2007). ForO. bartramiilarvae that appear in the Kuroshio-Oyashio transition region in the western North Pacific (Fig.1; Sassaet al., 2007), their distribution and transport patterns from spawning to feeding grounds may be influenced by the Kuroshio meanders. Magnitude of the Oyashio Current can also affect the distribution and abundance ofO. bartramii(Shaoet al., 2005).

Generally, the Kuroshio and Oyashio Currents are of good spatial coincidence with the fishing grounds ofO. bartramiiin the latitude of 35°-50°N. Previous studies considered 0.2, 0.35 and 0.5 mg m-3surface Chl-aconcentration contours and 15, 10, and 5℃ temperature isolines at 100 m depth as the indicators of the Kuroshio Current front zone, current convergence, and Oyashio fronts, respectively (Chenet al., 2010a; Wanget al., 2010). Chenet al. (2010b) suggested that SST would decrease when a large meander occupied the Kuroshio Current on the fishing grounds ofO. bartramii. Chenet al. (2010a) suggested that recruitment ofO. bartramiiwas affected by magnitude of the Kuroshio meanders on the spawning grounds in waters of 20°-30°N and 130°-170°E. Additionally, the strength and position of the Kuroshio Current were found closely related to monthly latitudinal center of gravity of CPUE ofO. bartramii; and the strength and transport path of the Kuroshio influenced the north-south migration ofO. bartramiipopulations, especially in the area of 40°-43°N and 150°-155°E (Chenet al., 2012). Wanget al. (2010) clearly identified seasonal spatial patterns of the Kuroshio and Oyashio with respect to the distribution ofO. bartramiistocks, with high CPUE coincident with the steep sea color gradients between 0.15 and 0.5 mg m-3surface Chl-aconcentration contours.

Based on previous studies (Chenet al., 2003; Shaoet al., 2005; Fanet al., 2010; Tanget al., 2011), we can draw a conclusion that the meandering pattern of the Kuroshio Current and the force of the Oyashio Current affect spatial distribution of fishing grounds ofO. bartramii. Strong Kuroshio force is associated with early fishing seasons, northward moving fishing grounds, and high CPUE ofO. bartramii, whereas strengthened intensity of Oyashio force is associated with delay of fishing seasons and dispersive distribution of fishing grounds. Large Kuroshio meanders reduce the recruitment ofO. bartramii. The squid populations undertake horizontal migratory behavior from planktonic paralarvae to micro-nektonic juvenile aggregated in the Kuroshio/Oyashio transition regions in the western North Pacific, but knowledge regarding this stage of life history strategies is limited. Recruitment of larvae from the spawning grounds will be transported to the feeding waters by the Kuroshio Current, greatly affecting the growth, mortality, distribution, and abundance of larvae and early juvenile ofO. bartramii. Future studies should pay more attention to this process for both the autumn and winter-spring cohorts ofO. bartramii.

3.3 Pacific Decadal Oscillation

The Pacific Decadal Oscillation (PDO) is a pattern of climate variability on at least an inter-decadal time scale, reflecting the long-term environmental background in the Pacific Ocean. Actually, the variability in PDO coincides with the dynamic of some fisheries resources, such as Pacific saury (Cololabis saira) (Tianet al., 2004) and skipjack tuna (Katsuwonus pelamis) ( Lehodeyet al., 2013). Mantua and Hare (2002) reviewed the impacts of inter-decadal changes in Pacific climate on many marine fisheries in the North Pacific. However, previous studies were focused on long-lived demersal fish stocks, whereas less work investigated PDO-squid interactions.

Recently, Litzet al. (2011) have indicated that seasonal occurrence ofD. gigasin the northern California Current was related to PDO, whereas the density of the squid coincided with the amount of juvenile hake, corresponding to the same trends in the SST and PDO indices. Paralarval abundance ofL. opalescenswas found correlated to both the El Ni?o-Southern Oscillation (ENSO) and PDO indices, which could be used in the development of adaptive management of market squid fishery (Koslow and Allen, 2011). In the Northwestern Pacific Ocean, significant influence of PDO combined with temporal variations in the Kuroshio changed the latitudinal distribution ofO. bartramii(Chenet al., 2012), whereas the CPUE of albacore (Thunnus alalunga) was positively correlated with the PDO index with a lag period of 13 months (Zhanget al., 2011).

The PDO pattern provides an inter-decadal climatic background for ENSO, El Ni?o/La Ni?a, and Kuroshio/ Oyashio Currents, which is likely to continuously exist during the 21stcentury (Yatsuet al., 2013). Previous studies proposed the interactive relationships among the large-scale oceanographic factors above (Luet al., 2005; Wanget al., 2012b). The El Ni?o events tend to occur with high intensity in a warm phase of PDO, while the La Ni?a events occur more frequently with strong intensity in a cold phase of PDO (Luet al., 2005). The SST in Kuroshio extension has significant temporally-lag correlations with the PDO and ENSO indices, which can be used to forecast SST variations in the Kuroshio (Wanget al., 2012b).

Based on the relationships among the large-scale ocean climate variables and their influences on marine fisheries, the following hypothesis can be formulated： the recruitment, migration, distribution, and abundance ofO. bartramiichange with SST variations in the Kuroshio and Oyashio Currents under the El Ni?o/La Ni?a events in the corresponding PDO phase; the SST affects the primaryproductivity and further influences the survival of prey; and the whole processes last for several months, resulting in an observed time lag in the effects of oceanographic/ climatic conditions on the population dynamics of squid. To better describe the fisheries oceanography and relevant mechanisms, more field observations and numerical modeling studies on the relationship betweenO. bartramiiand PDO are needed.

4 Impacts of Regional-Scale Environmental Conditions

In the North Pacific Ocean,O. bartramiihas become the main economic species for fishing fleets of China, Japan, and South Korea (Roperet al., 1984; Wang and Chen, 2005). Many studies described the distribution and abundance ofO. bartramiiin relation to regional-scale environmental conditions. Compared with other local oceanographic variables, SST is generally considered to be the most suitable indicator of searching for fishing grounds ofO. bartramii, which also has a superior predictive power to estimate squid abundance (Chen and Chiu, 1999).

The central fishing ground ofO. bartramiiis normally formed in the areas with dense distribution of isotherm surface water layer, convergence of cold and warm waters, and thermal layer (Chen, 1995; Shenet al., 2004a). Abundance ofO. bartramii, as quantified by CPUE, depends on the areas, timing, and depth of fishing. Chen and Liu (2006) documented monthly distribution patterns of SST on the main fishing ground suitable for squid,i.e., 12-14℃ in May, 15-16℃ in June, 14-16℃ in July, 18-19℃ in August, 16-17℃ in September, 15-16℃ in October, and 12-13℃ in November. The 20 and 17℃isotherms are considered to be good indicators of the fishing grounds ofO. bartramiiin west waters of 155°E and 155°-160°E, respectively (Chen, 1997). In addition, the squid are likely to concentrate in waters of 10-15℃, 9-10℃, 8-9℃ temperature isolines at 100, 200, and 300 m depth, respectively (Murata and Nakamura, 1998; Liu and Chen, 2002).

The Kuroshio and Oyashio Currents provide high primary productivity for the formation ofO. bartramiifishing grounds whose spatial distribution is highly consistent with Chl-aconcentration (Wanget al., 2003). The fishing grounds ofO. bartramiiwere found in areas containing 0.1-0.6 mg m-3Chl-a, with high frequency of occurrence present in the gradient belt of 0.12-0.14 mg m-3Chl-a(Fanet al., 2004; Shenet al., 2004b).

Both water temperature and Chl-aconcentration have great influences on the distribution and abundance ofO. bartramiiin their whole life cycle (Yuet al., 2013). However, relevant studies are mainly based on remotelysensed ocean surface data, whose accuracy and reliability are thought to be questionable becauseO. bartramiiexperiences diurnal vertical movements and spends little time to stay in the sea surface layers. Still, studies regarding the recruitment ofO. bartramiibased on variations in the SST and Chl-aconcentration on the spawning grounds are considered reasonable because planktonic paralarvae of the squid inhabit the sea surface waters (Young and Hirota, 1990).

The abundance ofO. bartramiiis also linked to SSS in some studies (Liuet al., 2001; Chenet al., 2010c). The fishing grounds of squid are thought to locate in folding zones of lower-salinity tongue and warmer temperature tongue (Liuet al., 2001). Yatsu and Watanabe (1996) reported that large females ofO. bartramiipreferred to stay in waters with the salinity of 33.75-34.00 at 200 m depth, whereas Chen and Huang (2003) indicated that SSS had unspecific distribution characteristics and un-conspicuous correlation with the central fishing ground ofO. bartramii. More studies are needed to evaluate the SSS as a potential indicator ofO. bartramiifishing grounds.

Sea surface height (SSH, also expressed as sea level height, SLH or sea level anomaly, SLA) is another useful environmental indicator for evaluating inter-annual variation in the distribution ofO. bartramiiduring spawning and nursery periods in the subtropical frontal zone (Ichiiet al., 2011). The optimal ranges of SSH for squid habitats are between -20 and -4 cm (Tianet al., 2009b). Other available data including rip current and eddy may implicitly provide indirect information on the distribution of fishing grounds ofO. bartramii. The fishing grounds, which depend on the location and force of rip current (Tang, 1996), can be divided into three main distribution patterns (tongue type, branch type, and eddy type) according to the types of eddy (Shaoet al., 2004).

Lastly, biomass estimation of zooplankton provides an effective way to explore the fishing grounds ofO. bartramiibased on field survey in the Northwestern Pacific. Location of the central fishing ground coincides well with the areas of relatively high density of zooplankton (250-500 mg m-3), especially in or near the areas with high abundance of crustacean (50-100 ind m-3).O. bartramiiparalarvae are likely to occur in waters with abundant euphausiacea and amphipoda (Chen and Huang, 2003; Xuet al., 2004). Effects of other oceanographic variables on the recruitment, distribution, and abundance ofO. bartramiiare poorly known.

5 Perspectives and Conclusions

According to the reviews mentioned above, the abundance and distribution ofO. bartramiiare highly sensitive to and strongly affected by the changes in oceanographic conditions. The population dynamics ofO. bartramiiin the North Pacific Ocean is mediated mainly by meso- and large-scale climatic-oceanic phenomena (e.g., Kuroshio and Oyashio Currents) rather than small-scale environmental phenomena (e.g., SST and Chl-aconcentration), because all of the oceanographic influences are imposed under the context of large-scale climate change (e.g., PDO). Similarly, Chen (2010) proved thatO. bartramiistocks exhibit more strong reactions in their abundance with large-scale environmental factors in the Northwest and Northeast Pacific.

It should be noted that two cohorts ofO. bartramiire-spond differentially to the same oceanographic conditions, whose variability varies over time and location with seasonal and geographical characteristics. Clearly, the existing studies which reveal significant relationships between environment factors andO. bartramiipopulations can explain the mechanism of oceanographic influences to some extent. However, there remain difficulties in the use of environmental variables for predicting squid abundance and distribution precisely, for the uncertainty and time-lagged effects of climate. Responding to the changing marine environmental conditions,O. bartramiipopulations are typically subjected to great fluctuations in their abundance (Bazzinoet al., 2005; Waludaet al., 2006). It is urgently needed to pave a rational way of the stock assessment ofO. bartramiiin order to achieve better fishery management.

In addition to the analysis of short- and medium-term variability in the environment, long-term changes in marine ecosystems associated with decadal-scale variations in the structure and abundance ofO. bartramiishould be studied. Decadal fluctuation in the abundance ofC. sairahas been demonstrated by assessing its response to climatic/oceanic regime shifts (e.g., Southern Oscillation Index, Arctic Oscillation Index, Monsoon Index, and PDO) in the northwestern subtropical Pacific for 60 years (Tianet al., 2004; Gong and Suh, 2013). This method can be applied to detecting the regularity and long-term variability ofO. bartramiipopulation dynamics which undergoes the same regime shifts.

Life cycles for cephalopods can be classified into two phases： passive phase when drifting to areas with more favorable environmental conditions, and active phase when using optimum environmental conditions to reach certain life stages at different growth rates between generations (Pierceet al., 2008). For the economic purpose of fishing, most studies are focused on the active phase of adultO. bartramii, while fundamental research for early life stages, especially passive planktonic phase of paralarvae and juvenileO. bartramii, are scarce.

Facts prove that both physical environment and biological factors (swimming behavior and spawning water depth and areas) affect fish transport and recruitment in the early life (Bratsch and Coombs, 2004). For example, the distribution and settlement of sea scallop during their four pelagic life stages depend on local physical-biological environment in the Middle Atlantic Bight and over Georges Bank, where upstream flow conditions and climate forcing playing significant roles in the transport of the scallop populations (Tianet al., 2009a).O. bartramiiis characterized by short life cycle and dies immediately after spawning, whose abundance completely depends on the recruitment. Because of the high natural mortality in embryonic and larval developmental stages ofO. bartramii, any minor variation in marine environment is likely to affect the growth, survival and recruitment on the squid stocks (Lasker, 1975).

Fig.2 Flowchart of technical route coupling physical and biological models for neon flying squid (Ommastrephes bartramii).

Knowledge regarding early life history ofO. bartramiiand interaction between its paralarvae and physical environment are of great importance to the prediction of squid abundance. Therefore, fundamental studies should be continuously carried out to better understand potential impacts of ocean-climate events on biological behaviors of the squid. More importantly, the question of how physical forces drive the variability ofO. bartramiistocks needs to be addressed. Emphasis on future research is suggested as follows (Fig.2)：

1) Thoroughly understanding the basic biology and early life ofO. bartramii. According to their growth and age, we divide the whole life cycle of squid into two phases： passive stage including free-floating eggs, and planktonic paralarvae, and nektonic active stage including juvenile, subadult, and adult. Biological equations as a function of length and temperature are used to parameterize the growth and mortality processes precisely for the early life passive processes. A preliminary individual-based population dynamics model (IBM) is built, in which large numbers of eggs and larvae are represented by Lagrangian ensemble particles.

2) Establishing physical fields with time series, high-resolution three-dimensional flow fields, temperature and salinity, mixed diffusion coefficient, and optional vertical turbulent closure schemes in the North Pacific Ocean using an appropriate ocean dynamics model. The unstructured-grid finite-volume coastal ocean model (FVCOM) provides an effective tool for predicting spatial-temporal variations in oceanographic conditions related to the transport, growth, recruitment, and mortality ofO. bartramii.

3) Coupling physical and biological models, simulating squid population dynamics (growth, transport, abundance, distribution, and mortality) based on Lagrange particle tracking, identifying true dynamic factors that affect the passive drifting life cycle processes, and conducting various modeling experiments to assess the influence of physical-biological processes onO. bartramiipopulations.

4) Performing sensitivity tests and comparing modeling results with observational and/or laboratory test data to ensure high reliability.

5) Back calculating the survival rate and distribution pattern ofO. bartramiilarvae and forecasting squid distribution and abundance in the future.

In summary, we presented a review on the life history ofO. bartramiiand discussed the variability of squid distribution and abundance relating to large-scale ocean climate phenomena (El Ni?o, La Ni?a, Kuroshio, Oyashio, and PDO) and regional environmental variables (e.g., SST, Chl-aconcentration, and SSS). The stocks ofO. bartramiiare thought to be driven by large-scale ocean climate events. It is recommended to evaluate the population dynamics ofO. bartramiiby coupling physical and biological models (e.g., FVCOM-IBM) for simulation of the early life cycle process of the squid based on accurate understanding of its early life history.

Acknowledgements

This work was financially supported by the National High-Tech R&D Program (863 Program) of China (2012AA092303), the Project of Shanghai Science and Technology Innovation (12231203900), the Industrialization Program of National Development and Reform Commission (2159999), the National Key Technologies R&D Program of China (2013BAD13B00), the Shanghai Universities First-Class Disciplines Project (Fisheries A), and the Funding Program for Outstanding Dissertations in Shanghai Ocean University.

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(Edited by Qiu Yantao)

(Received December 17, 2013; revised March 14, 2014; accepted April 1, 2015)

? Ocean University of China, Science Press and Spring-Verlag Berlin Heidelberg 2015

* Corresponding author. Tel： 0086-21-61900306 E-mail： xjchen@shou.edu.cn