Progress in Oceanography 179 (2019) 102204

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Progress in Oceanography
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Numerical studies on snow crab (Chionoecetes opilio) larval survival andtransport in the Sea of JapanT

Xinyan Maoa, Xinyu Guob, , Taishi Kubotab, Yucheng Wangb⁎ab

Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao, China
Center for Marine Environmental Studies, Ehime University, Matsuyama, Japan

ARTICLE INFOABSTRACT

Keywords:
Snow crab larvae
Survival and transport
Larval settlement
Numerical simulation
Sea of JapanThe snow crab Chionoecetes opilio is an important fishery species in Japan. Hydrodynamics are vital to the
distribution, recruitment and settlement of crab larvae in nursery areas. In this study, we developed a survival
and transport model of snow crab larvae to investigate the interannual variability in larval settlement in threefishing areas: west of Toyama (region A), west of Niigata (region B) and west of Hokkaido (region C). We foundthat the female crab stock abundance determined the modeled number of zoea in regions A and B, whereas watertemperature played a major role in the initial number of zoea in region C. As for larval settlement, the ocean
current impacted settlement in region B, and water temperature was vital to settlement in region C. Both female
crab abundance and hydrodynamics contributed to variability in settlement in region A. The results revealed
contrasting recruitment patterns in the three fishing areas. Self-recruitment was the primary form in regions A
and C, whereas both self-recruitment and recruitment from upstream sources were important in region B.

1. Introduction
The snow crab Chionoecetes opilio is a spider crab that inhabits deep,
cold waters in high latitudes in the northern hemisphere. It exists in the
Sea of Japan, Okhotsk Sea, Bering Sea, and the northwest Atlantic
Ocean (Charmantier and Charmantier-Daures, 1995). This is an important fishery species, particularly in Japan, Alaska, and Atlantic Canada. In the mid- and late 20th century, snow crab stocks declined
drastically in the Sea of Japan and eastern Bering Sea due to overfishing(National Federation of Bottom Trawler’s Union, 2006; North PacificFishery Management Council, 2000). To help stocks recover, a combination of permanent and seasonal marine protected areas was introduced following the management strategies of the snow crab bottom
fishery off Kyoto Prefecture, Japan that began in 1983 (Makino, 2008).
The 1999 landings recovered to the levels of the early 1970s (National
Federation of Bottom Trawler’s Union, 2006). For snow crab in theeastern Bering Sea, a rebuilding plan was enacted by the North PacificFishery Management Council (2000) to return mature male crab bio-⁎

mass to a sustainable level within two consecutive years. The stock
recovered in 2011, but then dropped again; however, it appears to have
improved in more recent years (Szuwalski, 2018). Low recruitment
below average was likely a contributing factor to the rebuilding failure
before 2010 (Szuwalski and Punt, 2013).
As indicated by previous studies, ocean climate is thought to be theprimary driver for the decline in the Newfoundland and Labrador snow
crab stocks (Mullowney et al., 2014). However, crab stocks in Alaska
and the eastern Bering Sea were not related to decadal shifts in climate
and physical oceanography (Zheng and Kruse, 2000, 2006). Althoughseveral hypotheses of either climate forcing (bottom-up) or groundfish
predation (top-down) for crab recruitment have been presented, allhave failed to show significant relevance between snow crab and largescale environmental indices. A piece-wise regression model was proposed by Szuwalski and Punt (2013) to successfully correlate the regime shift with snow crab recruitment in the eastern Bering Sea, but it
was impossible to present spatial dynamics using that simple model. As
Zheng and Kruse (2006) suggested, hydrodynamic simulations are

Corresponding author at: Center for Marine Environmental Studies, Ehime University, Matsuyama 790-8577, Japan.
E-mail address: guoxinyu@sci.ehime-u.ac.jp (X. Guo).

https://doi.org/10.1016/j.pocean.2019.102204
Received 8 February 2019; Received in revised form 6 August 2019; Accepted 21 October 2019
Available online 24 October 20190079-6611/ © 2019 Elsevier Ltd. All rights reserved.

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Fig. 1. Model domain and bathymetry. (a) Bathymetry of the Sea of Japan with regions A, B, C and D; (b) Magnification of region A: yellow and green lines are theisobaths of 200 m and 500 m, respectively. Seven subareas related to the distribution of initial larval density are separated by gray lines. (For interpretation of thereferences to color in this figure legend, the reader is referred to the web version of this article.)needed to clarify crab larval distributions and settlement in nurseryareas, which are two of the most critical processes for crab survival andrecruitment (Kruse et al., 2007).
To date, three numerical studies have simulated snow crab larvaltransport (Parada et al., 2010a, b; Okuno et al., 2010). Parada et al.
(2010a) built a preliminary coupled model of circulation and crab
larval drift in the eastern Bering Sea, covering the zoea I, zoea II andmegalopal larval stages. They later improved their simulation by using2

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Fig. 2. Annual stock (105 kg) of instar 11 female snow crab in the seven subareas of region A during 1999–2013. Data are digitized from Supplementary Fig. 3-3 in
Ueda et al. (2017).

temperature (Parada et al., 2010b). In Okuno et al. (2010), larvaltransport was simulated only in the southern part of the Sea of Japanand no consideration was given to survival processes. In the present
study, we aimed to build a larval survival and transport model in the
Sea of Japan and to investigate the factors leading to interannual
variability in larval settlement, as well as recruitment patterns.
2. Model description and configuration
2.1. Life history basis for snow crab model in the Sea of Japan
C. opilio eggs remain attached to the pleopods of the female crab forat least 1 year (Ito, 1967), and prezoea are hatched from February to
April on the seabed at water depths of 225–275 m (Kon, 1980). Theyrise toward the surface by phototaxis in less than 1 h, and develop into
the zoea I stage before reaching the surface (Kon, 1967).
Most of the first zoea are distributed in the 0–50 m layer right above
the hatching site. It takes 20–30 days to develop into zoea II, which isaccompanied by horizontal transport and sinking to depths shallower
than 150 m. The zoea II stage lasts another 30 days and then the larval
crab turns into megalopa and sinks down to depths of 150–200 m beginning in early April. Megalopa gradually concentrate in the layer
deeper than 200 m where the water temperature is less than 6–7 °C, andsettlement generally occurs in June when the megalopa metamorphosize into first stage benthic crabs (Kon, 1980; Kon et al., 2003). It isestimated that the total duration of the pelagic larval stage in the watercolumn is approximately 100–130 days.
Kon et al. (2003) partially addressed diurnal vertical migration

Fig. 3. Spatial locations of particle origins.

realistic initial conditions of each year from 1978 to 2003 and developing a spatial index of larval abundance for each modeled year basedon mature female abundance, fecundity-at-size, clutch fullness index
and annual/biennial reproductive schedule (Parada et al., 2010b).
Another improvement was to vary the duration of the pelagic stage, i.e.
explicitly modeling zoea I and zoea II stage durations based on water3

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Fig. 4. Time-series of released number of particles in seven subareas during 1999–2013.

(DVM) for the second zoea and megalopa stages. Zoea II were mainly
distributed at 0–50 m at night, and at 100–150 m at noon, migrating
approximately 100 m day−1. The full DVM range of megalopa was notassessed, due to constrains on water depth at the stations in the study.
After megalopa settle on the seabed, snow crabs do not migrate long
distances in the Sea of Japan (Yamamoto et al., 2014). Juvenile crabs
gather on the seabed at depths of more than 250 m before growing into
instar 7, and then move to the seabed shallower than 250 m. The instarof crab increases with molting, and the gender is not resolved until theeleventh molt. In instar 9 and 10 stages, they assemble on the seabed at
depths of approximately 225 m, where female crabs undergo a terminal
molt to maturity and males live until molting to instar 11. After that,males begin moving to depths of 275–400 m and will stay there on theseabed for up to 6 years (Kon, 1980).

temperature data in the Sea of Japan from 1999 to 2013. The model
domain is shown in Fig. 1a. The horizontal resolution is (1/12)° in thezonal direction and (1/15)° in the meridional direction. There are 38
layers in the vertical direction (4 m, 10 m, 15 m, 22 m, 30 m, 39 m,
50 m, 64 m, 81 m, 100 m, 120 m, …, 5674 m).
Nine larval release-drift events were simulated every year from1999 to 2013 at 10-day intervals beginning on February 1st. Each event
lasted 120 days. The durations of the zoea I, zoea II and megalopa
stages were hypothesized to be 30, 30 and 60 days, respectively(Yamamoto et al., 2014, 2015).
Particles representing zoea I were released at the sea surface between isobaths of 200 m and 500 m (Ueda et al., 2017) when the sea
surface temperature (SST) was within the range of 5 °C to 16 °C(Yamamoto et al., 2014). Once the larvae were released, they weretransported by ocean currents. The particle tracking method used in ourmodel was as follows:

2.2. Model description
Hydrodynamics play an important role in the larval planktonic
phase (Kon, 1970, 1973; Davidson and Chin, 1991), in addition to theavailability of food (Kon, 1979; Squires and Dawe, 2003) and predation(Forward, 2009). In this study, daily reanalysis from the Data Assimilation Research of the East Asian Marine System (DREAMS) (Hirose
et al., 2013) datasets were used to provide 3-D water velocity and waterx (t + t ) = x (t ) + u t +

2AH t

(1)

y (t + t ) = y (t ) + v t +

2AH t

(2)

z (t + t ) = z (t ) + w t + ws t + D (t ) t(3)

where (u , v , w ) is the velocity vector and (x , y , z ) denotes the particle’s
position at moment t or t + t . t denotes the time step, which is set

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Fig. 5. Larval distribution during one release-drift event with a 30-day interval. (a) The initial distribution of larvae. Start date and number of released particles areshown in the top left; (b)–(e) The distribution of drifting larvae on day 30, 60, 90 and 120. Both the time and number of drifting particles are shown in the top left andthe depth of existing particles is indicated by color; (f) The distribution of successfully settled larvae within the depth of 200–500 m. The number of settled larvae isshown in the top left.

3600 s. Both and AH are parameters related to turbulence. is arandom number in the range of [−1, 1], and AH is the horizontal eddy
diffusivity, recalculated by the Smagorinsky scheme (Smagorinsky,1963) using the horizontal water velocity data. ws denotes the sinking
velocity. Based on Kon et al. (2003), the distribution of larval crab increases 50–60 m in depth in each month from zoea I to megalopa.
Therefore, ws is set as 2 m day−1 in the model. D (t ) represents the DVM
speed and is set as a piecewise function of time t with unit of m hour−1
and a positive downward direction.

0
0 < day 30
5hour=23 or 0 hour < 9, 30 < day 60
D (t )= 12.5 9 hour < 13, 30 < day 60
10 13 hour < 23, 30 < day 60
060 < day 120(4)During larval transport, we set the following water temperature
range as a survival condition: 5–16 °C for zoea development (first
60 days in each cycle), and 5–14 °C for megalopa stage (second 60 days)

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survival was highest at a salinity between 20 and 38.
As for settlement on the seabed, there are two conditions for crab
larvae. The first is that the larvae have been transported for longer than
90 days (Kon et al., 2003), meaning that they are in the late megalopa
stage and are getting ready to settle on the seabed. The second is thatthe larvae must be hyperbenthic and located horizontally between
isobaths of 200 m and 500 m.
2.3. Model configurations(1) Hindcast calculation for 1999–2013
Since the fishery in western Toyama Prefecture accounts for thehighest snow crab catches in the Sea of Japan, a 15-year hindcast was
carried out in this zone (referred as region A in this study). Following
Ueda et al. (2017), we divided this area into seven subareas: Hamada,around Oki, north of Oki, Tajima, Wakasa, Kaga and Noto (Fig. 1b). In
the model, for grids where depth and temperature meet the conditions
mentioned above, the modeled number of zoea was set as a spatiotemporal variable proportional to annual mature female abundance.
More specifically, seven spatial density indices were introduced in eachmodeled year, based on the stock abundance of instar 11 female crab,
which were digitized from Supplementary Fig. 3-3 in Ueda et al. (2017)(Fig. 2). The number of particles released in one grid was set as the
product of 25 and the density index.

Fig. 6. Distribution of the total settled particles (shading) over 1999–2013 in
the hindcast simulation. The number of released particles in the Sea of Japanwas 2,013,975, among which 16,085 particles successfully settled.

based on Yamamoto et al. (2014). If one larva stayed out of the proper
temperature range for 24 consecutive hours, it “died” and was removed
from the model simulation. Considering that snow crab larvae in the
Sea of Japan do not experience large salinity fluctuations (Kon, 1980),
we did not take salinity into account. This was also supported by thelaboratory study of Yamamoto et al. (2015), in which crab larval(2) Sensitivity experiments
In addition to the hindcast simulation, additional three experiments

Fig. 7. Annual mortality rate in the 1999–2013 hindcast simulation. Shading denotes mortality rate with water temperatures > 16 °C (zoea) or > 14 °C (megalopa),
solid line denotes mortality rate with water temperatures < 5 °C; dashed line denotes total mortality rate.

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Fig. 8. Number of settled particles (red line) and stock abundance of instar 10 snow crab (black line, from Ueda et al., 2017) in region A. (For interpretation of thereferences to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 9. Time-series of released number of particles in different regions in case “JS”.

were carried out to evaluate effects of female crab abundance, watertemperature and ocean circulation on crab larvae.
The first experiment was simulated for the Japan Sea (case “JS”), in
which a uniform distribution of released particles was adopted all
around the Sea of Japan. Specifically, 25 particles were regularly

distributed in the surface layer of one grid that met the water depthpreconditions of crab larval survival (200–500 m). As long as the SST of
the grid fell within the range of 5–16 °C, the particles could be released
from five zones, i.e. regions A, B, C, D and Other (Fig. 3). Regions B andC, following Ueda et al. (2017), are two other important snow crab

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fishing areas in the Sea of Japan, located in western Niigata Prefecture
and western Hokkaido Prefecture, respectively. Region D is east of the
Korean Peninsula; crab larvae from this area were speculated to driftwith the Ulleung Warm Eddy and Tsushima Warm Current (TWC) andsettle in region A (Hogan and Hurlburt, 2006; Kim et al., 2008). The
fifth zone, “Other”, is the northwest region in the Sea of Japan (Fig. 3).
The other two experiments were initialized the same as case “JS”.
One of these was named “Tclim”, in which the actual water temperaturefield was replaced by the multi-year mean temperature field, i.e., removing interannual variation in water temperature during 1999–2013.
The other was named “UVclim”, in which the actual current field was
replaced by multi-year mean current field, i.e. removing interannual
variation in current field during 1999–2013. The multi-year climatology was a 366-day dataset obtained by averaging 15-year ofDREAMS data at the same calendar day.
3. Hindcast results for 1999–2013
The annual number of zoea released from the seven subareas during
1999–2013 is shown in Fig. 4. More particles were released from subareas west of Tajima than from the other subareas. After release, mostparticles moved northeastward following the TWC and were graduallywidely distributed near middle and northern Honshu Island (Fig. 5).
Vertically, larva kept settling to deeper layers over time. Mean depth oflarval distribution increased from 4 m at release (Fig. 5a) to approximately 90 m at day 30 (Fig. 5b), 130 m at day 60 (Fig. 5c) and 160 m atday 90 (Fig. 5d), which is consistent with Kon et al. (2003). At the endof the calculation for the 2004/02/01 release-drift event, 20% of theparticles remained drifting in the ocean, and 1.3% settled on theseabed, 3/5 of which settled in region A (Fig. 5f). “Dead” particles
caused by temperatures that were too-low or too-high accounted for 3/
4 of all released particles.
Among the 2 million particles released over the 15-year simulation
period, approximately 16,000 particles successfully settled on theseabed (settling rate, 0.8%), with settlement in regions A and B accounting for 76.8% and 17.8%, respectively (Fig. 6). Both regions A and
B are known as typical nursery areas of young snow crab in the Sea ofJapan. The remaining particles settled west of the Tsugaru Strait andwest of Hokkaido. As for the larval mortality (Fig. 7), more than 3/4 ofthe released particles “died” due to improper water temperatures. The
maximum mortality rate was 86% in 2008, and the minimum was 69%
in 2012. The change in mortality rate was certainly related to variability in water temperature, but was also affected by that in the flow
field. Additionally, as shown in Fig. 7, low temperatures induced moredeaths than did high temperatures.
Due to a lack of information on in-situ settlement numbers of crab
larvae, it was difficult to directly verify our larval model results using
field data. Nevertheless, we have annual stock abundance of instar 10
snow crab at hand. In general, it takes benthic crab 6–7 years to undergo ten molts (Kyoto Prefectural Agriculture, Forestry and Fisheries
Technology Center, 1994). Consequently, we compared the estimatedstock abundances of instar 10 snow crab from Ueda et al. (2017) withthe simulated settlement 6 years earlier in Fig. 8. Stock abundance from2007 to 2014 followed the same trend as simulated settlement 6 years
earlier from 2001 to 2008, but the other years did not. The peak in 2006
and trough in 2014 in the stock series seemed to represent a 5-year lagof extreme values in the settlement series. Although the model evaluation is not enough, we assume that the model results reflect major
variation in transport and survival of crab larvae in the Sea of Japanand will discuss these factors in the next session.

Fig. 10. Classification of interannual SST variation in (a) February, (b) Marchand (c) April. The color red indicated that the SST within the grid always fell inthe suitable temperature range (5–16 °C) during 1999–2013; the color brown
indicated that the SST within the grid was out of the suitable range in someyears; the color blue indicated that the SST within the grid was always out of
the suitable range. (For interpretation of the references to color in this figurelegend, the reader is referred to the web version of this article.)8

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Fig. 11. Number of settled particles sorted by its origin in the hindcast simulation.
Table 1
Numbers of settled particles sorted by origin and destination in the hindcast simulation from 1999 to 2013.
OriginHamadaNorth of Oki
Around Oki
TajimaWakasa
Kaga
Noto
Sum

Destination
HamadaNorth of Oki

Around Oki

TajimaWakasaKaga

NotoRegion A

Region B

Region C

10
0
0
0
0
0
0
10

49
41
67
0
0
0
0
157

538
241
1092
46
44
3
0
1964

125
63
84
12
1
0
0
285

413
263
570
90
92
13
0
1441

593
462
1227
259
247
31
0
2819

1473
1126
1950
326
452
283
69
5679

3201
2196
4990
733
836
330
69
12,355

347
750
800
199
244
205
311
2856

18
48
17
4
1
0
1
89

4. Discussion

on the variation in the abundance of female crabs. Additionally, there
was little variation in the number of particles released in region D,
while the relative variation in the higher-latitude zone (regions C andOther) reached more than 50%, obviously affected by the interannualchange in SST in spring (Fig. 10).

4.1. Initial number of crab larvae
In case “JS”, the modeled number of zoea was set irrelevant of theabundance of female crab. The numbers of particles released in regions
A and B did not change throughout the 15 years during 1999–2013(Fig. 9), because the SST of these two regions in February, March andApril were always within the range of 5–16 °C (labeled in red inFig. 10). Considering the modeled number of zoea did not vary in case“JS”, in which the water temperature and velocity had interannual
variations, it can be inferred that the interannual variation in crab
spawning in regions A and B in hindcast simulation depended entirely

4.2. Controlling factors for settlement
To link the initial number of zoea with final megalopa settlement,
we sorted settlements of the hindcast simulation by the origins of theparticles (Fig. 11). Settlement peaked in 2004 and 2011 due to higher
initial numbers in those years than in the other years (Fig. 2). Settlement was positively related to the initial number of particles in some9

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subareas. For example, the number released from Hamada in 2004 was
the highest in the seven subareas, and the settled number was also thegreatest, although most of the larvae settled in the other subareas,
implied by the first line in Table 1. However, there were also exceptions. Settlement was considerably lower in 2005 than in 2004, withsimilar densities of female crab (Fig. 2), but 10% higher low-temperature mortality (Fig. 7). This suggests that hydrodynamics during larvaltransport can also influence final larval settlement.
With three sensitivity experiments (cases “JS”, “Tclim” and“UVclim”), the effects of hydrodynamics on larval transport and settlement were separated, neglecting the effects of female crab abundance. Settlement in regions A, B and C were compared spatially(Fig. 12) and temporally (Fig. 13). By removing the interannual
variability in hydrodynamics, the number of settling megalopa decreased, especially in region C in case “Tclim” (Fig. 12b). Furthermore,
the distribution of settlement in region A changed markedly in case
“UVclim” (Fig. 12c). In the time-series (Fig. 13), the variability in theflow field seemed to have a great impact on settlement in region B, andthat in water temperature was vital to settlement in region C. Both theinterannual variations in water temperature and the flow field wererelated to the variation in settlement in region A.
The impact of the flow field upon the settlement in region A can also
be confirmed from Table 1, which is a connectivity matrix of the settlement destination and release origin from the hindcast results. Larvae
settling in one subarea were generally released from the TWC upstream
areas, so the least settlement occurred in Hamada, which is in the most
upstream (i.e. western) subarea of the seven subareas. The subarea
around Oki was an exception, since the maximum proportion of larvae
settling there originated from the same subarea, and larvae fromdownstream also made a positive contribution to settlement, particularly in 2005, 2007 and 2008, and less so in 2004 and 2009 (data notpresented).
Taking the second release-drift event in 2007 and 2004 as examples,particles released from around Oki moved counterclockwise in 2007
(Fig. 14a), but they went much further northeastward in 2004, evenreaching the vicinity of the Tsugaru Strait (Fig. 14c). Trajectories ofparticles released from Wakasa in 2007 were mainly westward, andthen circled around counterclockwise at 134°E (Fig. 14b), whereas they
moved more northeastward in 2004 (Fig. 14d) like the particles released from around Oki. A clockwise eddy existed in the layer shallower
than 50 m in early spring of 2007, which was centered in Tajima around
37°N (Fig. 15a, b). Due to the southeastern half of the eddy, the particles released from Wakasa moved westward to 134°E, and were thenrestricted by local cyclonic circulation. The joint effect of the clockwise
eddy and local cyclonic circulation resulted in the particle pathway
shown in Fig. 14a and b. The clockwise eddy in early spring of 2004 was
located more northeastward (Fig. 15c, d) and its center shifted to Wakasa and north of 37.5°N. Consequently, the particles released fromaround Oki, Tajima and Wakasa could easily leave region A and driftwith the current towards the Tsugaru Strait (Fig. 14c, d).
4.3. Pattern of crab recruitment
Fig. 12. Distribution of settled particles in case “JS”, “Tclim” and “UVclim”.
The values inside each panel have the same meaning as those in Fig. 6.

The pattern of crab recruitment in the Sea of Japan could be obtained from case “JS” by distinguishing whether the settled particles in
one region mainly originated from the region itself or not.

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Fig. 13. Time-series of number of settled particles in regions (a) A, (b) B, and (c) C in cases “JS” (solid black line), “Tclim” (solid gray line) and “UVclim” (dashedgray line).

Fig. 14. Particle trajectories in two release-drift events: 2007/02/11–2007/06/11 (upper panels); 2004/02/11–2004/06/10 (lower panels), released from aroundOki (left panels) and from Wakasa (right panels). Magenta diamonds denote the initial release location; red, blue and green lines are the trajectories of three particles;
and black dots denote the final location of particles. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of thisarticle.)11

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Consequently, two patterns were observed: self-recruitment and recruitment from upstream sources, which we named “upstream-recruitment”. Both patterns play significant roles in the sustainability ofthe snow crab fishery in the Sea of Japan.
As shown in Table 2, particles released from region A accounted for
97.3% (10,007/10,287) of the settlement in the same region, while
particles originating from upstream (region D) only accounted for 2.6%.
Therefore, region A was regarded as having a self-recruitment pattern.
This also suggested that crab larvae from east of the Korea Peninsula
had little linkage to the benthic crab fishery in the area west of Toyama.
In settlement in region B, the ratio of particles released from upstream (regions A and D) to that from region B itself was roughly 1.7((4202 + 15)/2478), meaning the two patterns (self-recruitment andupstream-recruitment) were equally important to local recruitment.
The pattern in region C was self-recruitment, because more than 96% of
the particles settling there were released from the same area.
4.4. Limitations of the present model
There are several limitations in the present larval model. The first is
related to the initial number of zoea in each release-drift event. It might
be inaccurate because higher stocks of instar 11 female crab do notnecessarily mean that more larvae will be hatched (Kruse et al., 2007).
Another limitation is that the duration of zoea I, zoea II and megalopa isfixed in the model, which is virtually variable with water temperature(Yamamoto et al., 2014). Thirdly, this study considered only temperature as the cause of larval mortality, but food availability and predationof crab larvae also affect survival in wild crab populations. Consequently, discrepancies are likely to exist between the simulated andactual settlement. Although the benthic phase of snow crab was excluded from the pelagic larval model, it should be stressed that predation of juvenile crab by benthic fish and cannibalism by elder crabs
can lead to mortality of metamorphosed benthic crabs, which willprobably reduce the 6-year lagged stock of adolescent crabs.
5. Conclusion
In this study, we developed a transport and survival model for crab
larvae in the Sea of Japan which considered DVM during the second
zoea stage, and regarded water temperature as the sole factor affecting
survival. The model can generally reproduce the distribution of larval
drifting and settlement on the seabed. The settling rate of crab larvae
was only about 1% of released particles. More than 3/4 of the released
particles “died”, most of which were the result of low temperatures.

Fig. 15. Monthly-mean velocity (vector) and temperature (shading) in region A
at 4 m in (a) 2007/02 and (c) 2004/02; and at 100 m in 2007/04 (b) and 2004/
04 (d). Blue and green lines show the isobaths of 200 m and 500 m, respectively. (For interpretation of the references to color in this figure legend, thereader is referred to the web version of this article.)

Table 2
Numbers of released and settled particles in case “JS” sorted by particle origin and settlement region.
OriginRegion A

Region B

Region C

Region D

Other region

Sum

Number of released particles
Number of settled particles in region A
Number of settled particles in region B
Number of settled particles in region C
Number of settled particles in other regions
Total settled
Settling rate

1,606,500
10,0074202
10883
15,1020.9%

452,250
14
2478
11
522
3025
0.7%

553,625
0
0
590
32
622
0.1%

261,725
266
15
0
10
291
0.1%

48,3000000002,922,400
10,287
6695
611
1447
19,0400.7%

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Sensitivity experiments revealed that variation in initial number ofzoea in regions A and B depended entirely on the stock abundance offemale crabs, while in the higher-latitude region C, modeled number ofzoea varied with the water temperature on the interannual scale. As forlarval settlement, the flow field likely had a great impact on settlement
in region B and water temperature was vital to settlement in region C.
Both variations in female crab abundance and hydrodynamics contributed to settlement in region A, where the influence of the flow field
was significant, especially with respect to the clockwise eddy at TajimaWakasa. Finally, the recruitment patterns in the three fishing areas
were presented. Regions A and C predominantly showed self-recruitment, while self- and upstream-recruitments played a major role inregion B.
The numerical model can be improved in the future by considering
effects of water temperature on the durations of the zoea and megalopa
stages, and those of larval starvation and predation on survival conditions.

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Acknowledgements
This work was supported by the Environment Research andTechnology Development Fund (S-13) of the Ministry of theEnvironment, Japan, and the National Natural Science Foundation ofChina (41576010). We would like to thank Prof. Naoki Hirose and Dr.
Katsumi Takayama at Kyushu University who provided the data ofDREAMS for this study. We also thank Prof. Yasunori Sakurai at
Hokkaido University for his advice on our model calculations.
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