Bivalve breeding in Russia is based on the recruitment of juveniles to artificial substrates. However, larvae of competing and predatory species also settle on these substrates. In Posyeta Bay, Sea of Japan/East Sea, Russia, the wild bivalve species Mytilus trossulus, Chlamys farreri and Swiftopecten swiftii compete for nutrients and space with the cultured species Mizuhopecten yessoensis. The study focused on the number of juvenile bivalves that settle on collectors over 38years (1977-2014), looked for any patterns associated with potential harvest sites within the bay and at where on the collectors the juveniles tend to settle. There is great variation between years which is strongly influenced by the seasonal variation in wind and rain, average sea level, ice cover and sea surface temperature. No strong differences were present among potential harvest sites although M. trossulus varied a little with latitude and Ch. farreri varied a little with longitude. M. trossulus was the most prolific species dominating the first 10 m of depth. M. yessoensis was half as prolific and mainly settled 6-14m below the surface. Ch. farreri was third most prolific and mainly settled 3-9m below the surface. S. swiftii numbers were generally low. The density of juvenile M. yessoensis is strongly influenced by wind and rain, and also by ice cover (ais), salinity (sol) and sea level. In addition to predators settling in collectors, the greatest danger to M. yessoensis is posed by its competitor - M. trossulus.

Keywords: Dynamics of the number of bivalve larvae, features of spatial distribution and influencing factors

Aquaculture is a promising and rapidly growing fisheries sector producing over 50 per cent of total seafood production in four advanced mariculture countries.¹ However, this increased scale of farming has led to negative consequences in the biodiversity, ecology and productivity of farmed sites.^2,3 High densities of farmed sites, and co-cultivation of M. yessoensis and M. trossulus have caused eutrophication of the water due to increased concentrations of metabolites, leading to changes in species composition of phytobenthos and phytoplankton and an increase in non-edible and/or toxic algal species.^4,5 One solution is to reduce the farming density by identifying and farming new water areas. This requires identifying the present ecosystem, competitors, weather characteristics and oceanological processes of proposed new areas.⁶          

The aim of this study is to investigate the influence of weather and competition on bivalve population dynamics especially in relation to the settling of juvenile M. yessoensis in Posyeta Bay.

The study was undertaken in Posyeta Bay (42°30'N,130°55'E) (Figure 1) located in the northwestern part of the Sea of Japan at the junction of Russia, China and Korea. This Bay, extending 17 miles inland, is considered the cleanest bay in Peter the Great Bay due to the sparse human population and absence of large industries.⁷ It is cooled from the north by the Primorsky Current and warmed from the south by the East Korean Current (a branch of the warm Tsushima Current).⁸ Tides in the Bay are small, semidiurnal and irregular and the wind drives most water movement.⁹ Since the Bay is quite large, sampling was performed at 14 stations/locations listed in Table 1. These vary in sea depth and distance from the marine farm used as a base. The marine farm, station 14, is close to the well established seafood processing plant in the village of Posyet at the outlet of the Novgorodsky Bay (actually a shallow lake, average depth 8m) where water temperature reaches 30°C in summer.

The study focuses on the juvenile population dynamics over years and with depth, of four bivalve species: M. yessoensis, M. trossulus, Ch. farreri and S. swiftii. These species have different origin, distribution and ecology.¹⁰ Different species in the same community prefer different horizons of the "areal".¹¹ The juvenile abundance of these species varies along the garland of collectors.¹² However, there are few data on the vertical distribution of these species.¹³ One concern is that naturally occurring populations of the latter 3 species may compete with efforts to produce the cultivated M. yessoensis.

The juvenile population size of these species has been assessed every year since 1977. The three sets of data reviewed here were collected between 1977 and 2014. Japanese collector garlands are used to assess the population level. A garland consists of a series of 10-40 collectors, net bags at 0.3m intervals along the garland, anchored to the sea floor and held up with a buoy at the sea surface. The collectors essentially protect the larvae from predators. Every year from 1977-2014, one or two garlands were installed at Minonosok Inlet (station 1) when scallop larvae 250μm long appeared in the plankton. In nine of the years 1978-1989, garlands were also installed at other locations in the bay, test stations 2-14. When larvae appeared was determined as follows: from mid-May, divers sampled 25-30 mature scallops at station 1 every 10 days. These scallops were weighed for total weight and soft tissue weights (muscles and gonads). The gonadal index was then calculated by the method of Ito et al.¹⁴ The time of spawning was determined as when the gonadal index among the females reduced 9-12%. Every two-three days from a week after spawning, plankton probes were taken by the Epstein net in the horizon of 0-10 m. These probes had a sieve cell of 100 µm. In 1977-1990 and 1995-1996, soundings were conducted at 1-3 stations in Minonosok Inlet (8-11 soundings annually). The plankton probes were fixed in 4% formaldehyde. The calculation and measuring of the four types of bivalve larvae were made in the Bogorov camera under the microscope MBC9 and their quantity was expressed per m³.

The juvenile larvae settled on the newly installed collectors in June and early July. After the juvenile M. yessoensis had grown to 8-10 mm in shell height in September/October, collectors were raised for counting the number of each species in each bag. The counts were then averaged and expressed as individuals per m².

The count included dead and alive to exclude the influence of predators in the collector. Since the mollusk deaths in the collectors are not related to reproduction, the reproduction level of these mollusks includes both live and dead (empty shells) individuals. The surface area of one collector is 1,44 m². The average size of molluscs was determined from 100 specimens accurate to 0.1 mm. Daily values of water temperature and salinity, sea level, precipitation, wind speed and direction in June for 38 years (1977-2014) were collected by the Hydrometeorological Station (HMS) of Posyet (42°33'N, 130°48'E) and were used to investigate the influence of these weather variables on reproduction of these species; the spawning and pelagic period of M. yessoensis and M. trossulus in this Bay is mainly in June. The mean values were calculated. The standard error of the mean June surface water temperature was also recorded for each year. The values of solar activity expressed in Wolf numbers were taken from the website of the US National Atmospheric and Oceanic Administration: ftp://ftp.ngdc.noaa.gov. The days of ice cover in the preceding winter (including the ice release time) for each year was observed in Expedition Bay (Figure 1, station 8).

Figure 1 Study area: Posyeta Bay with Road Pallada Bay and the position of the test stations.

Analyses of juveniles per m² were performed using linear models in ASReml 4.2.¹⁵ However the counts per m² are quite skewed with the maximum being 4 to 9 times the mean. Therefore, analyses were performed on the square root scale to reduce the impact of the extreme values. This scale represents the number encountered in a 1metre square collector (count m^-2).

Three data sets were constructed.

Years and stations

This data set of 54 records combined counts from 14 stations (Table 1) collected over 8years between 1978 and 1988 of the 4 mollusc species. Information on the stations included latitude, longitude, water depth and distance from the farm. This was analyzed using univariate linear models to examine year variation, station variability and the significance of station covariates. The linear model tested the influence of year and the station covariates on count m^-2 for each species.

Sampling depth

The second data set of 55 records was a summary of mollusc counts at station 1 at regular depths along the collector garland, averaged across years as recorded for each species. A cubic smoothing spline was fitted to count m^-2 to create a density profile with respect to depth for each species.

Weather data

The third data set related the count m^-2 of each species in each year from 1977 to 2014 and a set of climate variables for each year. This was analysed as a multiple regression for each species, sequentially dropping non-significant variables. The weather variables considered were wind: mean wind speed in June m/sec; rainfall: mean precipitation in June; ais: days of ice cover; flood: mean sea level height in June, cm; sol: mean surface water salinity in June, psu; tem: mean water temperature in June, ° ; dev: variation in mean water temperature in June, °C; curwind - mean wind direction in June, °C ; W - annual solar activity in Wolf’s numbers; WW: previous solar activity in Wolf’s numbers; H: shell height of M. yessoensis as at 23 September of each year, mm.

Variation across years and stations

The linear model fitted to count m^-2 for each species included Year, the 4 station covariates as fixed effects and Stations as random effects. The summary of these analyses is in Table 2.

For M. yessoensis, the predicted year means were 57 m^-2 to 95 m^-2 in four of the years and 233 m^-2 to 1160 m^-2 in the other 4years. For M. trossulus, the predicted year means were low 87m^-2, 174 m-2 in two years, moderate 470m^-2 to 601 m^-2 in 4years and high 838m^-2 and 1238m^-2 in the other 2years. The latitude regression was 0.01016 ± 0.00491 per °E which represents a mean change of say 526 m-2 in the west to 532m^-2 in the east in a moderate year. For Ch. farreri, the predicted year means were 3m^-2 to 11 m-2 in the 3 lowest years, 25m^-2 to 71m^-2 in the 4 moderate years and 243m^-2 in the highest year. The longitude regression was -0.00414 ± 0.00152 per °N which represents a mean change of say 25m^-2 in the north to 100m^-2 in the south of the study area in a moderate year. However, there were only 33 data points. For S. swiftii, the predicted year means were low 1.4m^-2 to 6.8m^-2 in six years, higher 21m^-2 and 34m^-2 in the other 2years. The latitude regression was -0.00213 ± 0.00051 per °E which represents a mean change of say 2m^-2 in the east to 16m^-2 in the west. However, there were only 23 data points.

Variation associated with sampling depth

The cubic smoothing spline fitted as a linear mixed model involves a fixed linear regression and a set of random covariates. In every case, the splines are significant, and the association of density (on the square root scale) for each species is shown in Figure 2. This clearly shows the bulk of the M. yessoensis scallops are found from 6 to 14metres, the bulk of the M. trossulus juvenile mussels are found from 1 to 8metres, the bulk of the Ch. farreri scallops are found from 4 to 9metres, the bulk of the S. swiftii scallops are found from 8 to 16metres.

Figure 2 Juveniles per metre of four bivalve species along the collector garland.

Variation associated with weather variables

It is of general interest to see the correlations among the weather variables shown in Table 3. The scallop counts are analysed again on the square root scale. Note first that the correlations among the response variables are low except for Ch. farreri with S. swiftii.

Each response variable has been analysed as a linear model fitting the 10 weather variables and interactions among them, and dropping non-significant terms. Table 4 reports the F statistics and regression coefficients from the final 4 models.

The density of juvenile M. yessoensis is strongly influenced by wind and rain, and also by ice cover (ais), salinity (sol) and sea level. The count m^-2 is reduced by more rain, more wind, higher sea level and higher salinity. However the interactions show that wind and rain together have less individual effect. Similarly wind has slightly less effect when sea level is high. Extended ice cover increases the count m^-2 but not as much when wind is high. The count m^-2 of juvenile M. trossulus is increased with higher rain and water temperature. It is reduced though if the water temperature is variable (dev) but less so when the overall water temperature is high. The density of juvenile Ch. farreri is higher then sea level is high and when water temperature is high. The density of juvenile S. swiftii scallops increases with June rainfall, more so when sea level is also high.^16-25

The first mariculture farm in Russia was established in 1971 in Minonosok Bay, Posyeta Bay. After a decrease in fish catches, the enterprise in the village of Posyet was in dire need of raw materials for processing, and farmed mollusks were to fill this gap. However, in the process of culturing M. yessoensis, it turned out that the collection of scallop larvae from plankton showed inter-annual variability that was much higher than the variability of growth rate. To reduce rearing costs, breeding of the two trophic competitors, the scallop M. yessoensis and the mussel M. trossulus, began in 1979 in the semi-enclosed Minonosok Bay. However, this rather quickly failed due to eutrophication of the water from mollusk metabolites and reduction of growth rates, reproduction and survival of cultured objects. To increase the reproduction efficiency, it was necessary to search for alternative area with a stable collection of M. yessoensis larvae from plankton not too far from the processing plant and with depths sufficient to reduce the number of competitors settling from plankton.

The results showed that M. yessoensis has a horizon (9-13.5m) at which its abundance is maximized, in contrast to its main competitors, M. trossulus and Ch. farreri which settle at a shallower depth. M. trossulus was the most abundant species overall and in high numbers can clog all the cells in the collector leading to mass death of scallops.^25-36

There is huge annual variation in all species and this is largely explained by weather conditions. However the weather effects differ between species and the annual numbers are not highly correlated. The significant effect of wind on the reproduction of M. yessoensis seems to be related to the current it creates, bringing larvae to the collectors. The greater the volume of water filtered through the collector, the more larvae will be present. Higher rainfall resulting in more terrigenous runoff contributes to the abundance of food for larvae. The positive impact of the ice period on reproduction of cold-loving M. yessoensis is explained by the fact that lower winter temperatures inhibit their growth and the accumulated energy is directed to gonad maturation (trade-off); the longer the ice period, the higher the gonad index. Solar activity was included among the weather variables since it is known to influence weather variables.^37-41 However it was not significant among the more direct weather variables of wind, rain, ice cover and temperature.

In terms of predicting abundance, ice cover period and June weather conditions will help. The distribution of juvenile counts over the 38years of this study shows 14 M. yessoensis counts less than 300m^-2 and 14 above 500m^-2 which may assist in assessing the long term viability of the industry in the Bay.

Since there were no consistent differences in M. yessoensis establishment found among stations and station 4 (Astafjego Cape) is near the marine farm and is of sufficient water depth, we recommend it for the establishment of a marine plantation.

The Japanese technology for cultivating of M. yessoensis requires the transfer of juveniles from collectors to cages in September/October for growth to maturity. However, exposing the molluscs to the air reduces their growth rate and survival rate so that 30-50% of them are lost in the transfer process. A new style of collector-cage has been developed consisting of plastic cones covered with a mesh shell.⁴² These improve the living conditions of molluscs and can be placed at the realized niche, the depth where the abundance of competitors is lower. The large openings in the cover of the collector-cages allow the M. yessoensis to grow to marketable size without transplantation.

The results allow us to recommend Astafjego Cape for the establishment of a marine plantation. In this area, the settling of M. yessoensis larvae on collectors is always higher than in other water areas.

I wish to express my sincere gratitude to V.N. Grigorjev and G.V. Polikarpova for help in action. Dr. I.D. Rostov for the collecting of meteorology data, M.V. Maksudinova for translation of the manuscript into the English language. There are no sources of funding to declare.

1. The state of world fisheries and aquaculture – 2020. Measures to increase sustainability. Rome. FAO. 2020;1–223.
2. Waite R. Beveridge M. Brummett R, et al. Improving Productivity and Environmental Performance of Aquaculture. Working Paper, Installment 5 of Creating a Sustainable Food Future. Washington, DC: World Resources Institute. 2014.
3. Gunning D, Maguire J, Burnell G. The Development of Sustainable Saltwater–Based Food Production Systems: A Review of Established and Novel Concepts. Water. 2016;8(12):598.
4. Chauvaud L, Thouzeau G, Paulet YM. Effects of environmental factors on the daily growth rate of Pecten maximus juveniles in the Brest Bay (France). J of Exp Mar Biol and Ecol. 1998;227:83–111.
5. Gabaev DD. Reproduction level of bivalve mollusks as an indicator of ecological health of coastal areas. The Bull of the Rus Far East Malacol Soc. 2010;14:41–60.
6. Dal Bello M. Consistent patterns of spatial variability between NE Atlantic and Mediterranean rocky shores. J of the Mar Biol Ass of the Un King. 2016;97(3):539–547.
7. Kchristoforova NK, Kodzar AD, Boychenko TV, et al. Bioindication water condition of Posyeta Bay. biota and e area conserv. 2018;1:92–99.
8. Vishkvartsev DI. physiographic and hydrochemical characteristic shallow gulf of Posyeta bay. hydrobiological research of bays and gulfs of Primorye. Vladivostok: FSC AS USSR. 1984;4–11.
9. Rogachev KA, Shlyk NV. Formation of seaside coastal current as affected freshwater drainage. Vest FAB Ras. 2015;6:41–48.
10. Scarlato OA. The bivalved mollusks of temperate water of northwest part of Pacific Ocean. Leningrad: s 1981;1–480.
11. Mileikovsky SА. The larvae of bottom invertebrata. The biology of ocean. In: Vinogradov ME, Editor. The Biological Structure of Ocean. Moskow: Science. 1977;96–106.
12. Gabaev DD. 35–Year Studies of Reproduction in Marine Invertebrates and the Influence of Climatic Factors on it. J Mar Biol Oceanogr. 2013;2:4.
13. Gabaev DD. Differences in spatial distribution of juvenile bivalve mollusks in Primorsky Krai (Sea of Japan/East Sea). Abstracts of the conference: Mollusks of the Eastern Asia and Adjacent Seas. Vladivostok: Dalnauka. 2014;26–30.
14. Ito S, Kanno H, Takahashi K. Some problems on culture of the scallop in Mutsu Bay. Bulletin of Marine Biological Station Asamushi. 1975;5(2):89–100.
15. Gilmour AR, Gogel BJ, Cullis BR, et al. ASReml User Guide Release 4.2 Functional Specification, VSN International Ltd, Hemel Hempstead, HP2 4TP, UK. 2021.
16. Kasyanov VL, Yakovlev SN, Yakovlev YM. Reproduction of echinoderm and bivalve molluscs. Moskow: Science. 1980;1–135.
17. Gabaev DD. Biological substantiation of new methods cultivation of some trade bivalve molluscs in Primorye. D. thesis. 1989;1–129.
18. Gabaev DD, Taupek NY, Kolotukhina NK. Specificity of conditions of existence commercial invertebrata on artificial substrata in eutrophic Amur bay (sea of Japan). Rus J Ecology. 2005;36(4):370–377.
19. Soldatova IN, Reznichenko OG, Tchihon–Lukanina EА. Features fouling of installations mariculture of the sea scallop. Sov J Oceanology.1985;25(3):513–518.
20. Naidu KS, Scaplen R. Settlement and survival of the gigant scallop, Placopecten magellanicus, larvae on enclosed polyethylene film collectors. FAO technical conference on Aquaculture E. Preprint Kyoto. 1976. 5 p.
21. Wallace JC, Reinsnes TG. Growth variation with age and water depth in the Iceland scallop (Chlamys islandica, Pectinidae). Aquaculture. 1984;41(2):141–146.
22. Ovsjannikova II. Distribution barnacles on shells of Japanese scallop at cultivation in handing culture. Sov J Mar Biol. 1989;4:71–76.
23. Allen DM. Biological aspects of the calico scallop Argopecten gibbus, determined by spat monitoring. Nautilus. 1979;93(4):107–119.
24. Fréchette M, Gaudet M, Vigneau S. Estimating optimal population density for intermediate culture of scallops in spat collector bags. Aquaculture. 2000;183(1–2):105–124.
25. Claereboudt MR, Bureau D, Cǒté J, et al. Fouling development and its effect on the growth of juvenile giant scallops (Placopecten magellanicus) in suspended culture. Aquaculture. 1994;121(4):327–342.
26. Kashin IA, Maslennikov SI. Fouling of constructions for cultivation of the seaside scallop. Sov J Mar Biol. 1993;4:90–97.
27. Raby D, Lagadeuc Y, Dodson J, et al. Relationship between feeding and vertical distribution of bivalve larvae in stratified and mixed waters. Mar Ecol Prog Ser. 1994;103(3):275–284.
28. Kolganova TN, Khruchkova NG. To an estimation of a forage reserve of the seaside scallop to lagoon Busse (island Sakhalin). In: Proceedings of the: All–Union conference on the scientific and technical problems of mariculture. September, 27 – October 1. Vladivostok. PISFO. 1983. P. 171.
29. Kuznetsova IA. The characteristic food of a seaside scallop and edible mussels in conditions of mariculture. Biology of objects mariculture. Biology and cultivation of invertebrates and s Moskow. IO AS USSR. 1987;65–69.
30. Zvalinsky VI, Lobanov VB, Zakharkov SP, et al. Chlorophyll, the slowed down fluorescence and primary production in a northwest part Sea of Japan in the autumn of 2000. Oceanology. 2006;46(1):27–37.
31. Gabaev DD. Settlement of larvae of bivalve molluscs and starfishes on collectors in Posyeta Bay. Sov J Mar Biol. 1981;4:59–65.
32. Gabaev DD. Through–cultivation of the commercial bivalve molluscs. fishery Questions. 2008;9(33):218–243.
33. Gabaev DD. laws of settlement on collectors of some invertebrates in Posyeta Bay. In: Proceedings of the conference: Biology of shelf zones of the World ocean: Vladivostok: Fesc, Academy of the Ussr, Russia. 1982;54–55.
34. Dulenina PA, Dulenin AA. distribution, dimension age structure and growth Japanese scallop Mizuhopecten yessoensis (Bivalvia: Pectinidae) along the northwest part of Tatar Strait. Rus J Mar Biol. 2012;38(4):290–297.
35. The final report of fisheries studies for research evaluation. Fisheries Life Sciences: Aquaculture Sciences. NFRDI, Korea. 2006;105–155.
36. Kosaka Y, Ito H. Japan. Scallops: Biology, Ecology and Aquaculture. Elsevier Press, Amsterdam, the Netherlands. 2006;1093–1141.
37. Li Q, Osada M, Kashihara M, et al. Effects of ultraviolet irradiation on genetical inactivation and morphological structure of sperm of the Japanese scallop, Patinopecten yessoensis. Aquaculture. 2000;186:233–242.
38. Fuentes–Lema A, Sobrino C, González, et al. Effect of solar UVR on the production of particulate and dissolved organic carbon from phytoplankton assemblages in the Indian Ocean. Mar Ecol Prog Ser. 2015;535:47–61.
39. Reznikov AP. Forecasting sunspot activity out century. Regularity and forecasting act of nature. Moskow: Science. 1980;60–86.
40. Abdusamatov XI. The Sun dictate of climate of the Earth. S. Petersburg. «Logos». 2009;1–197.
41. Gabaev DD. about abundance forecasting juvenile of the japanese scallop patinopecten yessoensis, on plantation mariculture of primorsky t Problems of fishiries. 2020;21(3):313–330.
42. Gabaev DD. About through–cultivation of two commercial bivalve molluscs. J Aquac Mar Biol. 2017;5(5):131‒135.