Seasonal dynamics of juvenile fish community and its recruitment to
the population: role of transport and fishing
1. Introduction
The transport of early life stages of fish from spawning grounds to nursery grounds
influences the recruitment of fish population. Generally, recruitment variability iscaused by interactions between the larval fish and their environment, including physicalforcing, prey availability, predator pressure, and density-dependent competition. To
study role on the larval fish transport is therefore crucial to understanding how biotic
and abiotic parameters affect survival in early stages. Zhoushan archipelocho is a
traditional spawning and nursery ground for many commercial fish species in East
China Sea. The physical and biological process to control the fish recruitment fromlarval fish is still poorly studied in this area, we made some preliminary study to
examine the various processes affecting their survival, and later population.
2. Materials and Methods
The larval samples were investigated during winter, spring, summer and autumn
cruise in 2018-2019. Around 40 stations were located around 29°~32°N, 121°
~125°E, in the East China Sea (Figure 1) . In each station, the larval fish were sampled
by type I plankton net(mouth diameter 500 mm, net length 1450mm, 0.505mm), andwere attached flow meter in the center of mouth. All the samples were preserved by 5%formalin. The species and numbers were identified and counted by microscope in thelaboratory. The juvenile fish was sampled by bottom trawl (mouth opening 6 m height× 10 m wide), with 12 mm mesh size at the cod-end. Trawls were conducted foraround one hour at each station; the average ship speed was 3.0 knots. All samples inthe trawl net were preserved using fresh ice in the ship’s refrigerator. In the laboratory,organisms were identified at the species level, counted. The numbers of samples
belonging to each species was normalized by trawling hours to yield abundance.

1 / 6

Figure 1 larval fish stations in the Zhoushan Archipelago seas (a) , cluster stations(b) andhorizontal(blue)-vertical (red)migration routes
Note: the black triangle represents the water mass in Hangzhou bay（Area I, the green square represents
upwelling water mass of Zhoushan islands (area II), and the red circle represents the offshore water mass ofZhoushan（Area III）

In the laboratory, organisms were identified at the species level, counted. The
numbers of samples belonging to each species was normalized by trawling hours toyield abundance (individual per hour). As the limitation of laboratory condition andsmall individual samples, we measured the weight of total individuals in species level,
rather than measuring individual each by each. Hence, average weight of each species in
one station was determined as total weight divided by total counts of this species. As aproxy of length, average weight was used to indicate the average size of each species.
Species with occurrence rates greater than 5 % were categorized into groups based on
the trophic level (feeding habits) and living habitat (Table 1). Generally, the fish species
were classified in to detritivores, planktivores and benthivores according to Zhang et al.
(2007)
2.1 Data analysis
Functional group assemblage structure: Station clustering were conducted byhierarchical agglomerative cluster analysis (HACA) with temperature, salinity andturbidity in the two months using Euclidean distance measure and ward’s linkage
method to identify spatial assemblages (Chen et al., 2014). Permutational multivariate

2 / 6

analysis of variance (PERMANOVA) was performed to test for significant temporal andregional differences in the abundance and size composition of group assemblages, using
pairwise tests with 999 random permutations, and habitat (bay/offshore) and month(spring/autumn) as fixed factors (Guan et al., 2017). Student t-tests were also used toevaluate the null hypothesis of no difference in abundance and size between offshoreand bay areas in the same month, and between autumn and spring in the same habitat.
2.2 Species assemblage dynamics and its factors
To investigate the driving force of marine community structure dynamics,
canonical correspondence analysis (CCA) was employed to study the functional groupassemblages in two months using software CANOCO (version 5.0). Abundance and sizeof all fish and crustacean species were (log or square-root) transformed, and rare species
were down-weighted. The relationship between marine community structure and spatialand temporal factors was examined by CCA. CCA triplot scaling with focus oninter-species distances were used. Significance of the canonical model was assigned
using Monte Carlo test (Ter Braak and Smilaeur, 2002). Forward selection and Monte
Carlo permutation test (1000 permutations) were performed to determine which
variables were statistically significant in determining fish and macro-crustacean groups
community structure (Xiong et al., 2016). Inter-set correlation coefficients were used toassess the importance of the environmental variables; variables were considered to bebiologically important when inter-set correlation greater than or equal to |0.4| (Ramos etal., 2017).
3. Results and discussions
3.1 Seasonal dynamics of larval and juvenile fish ecological groups
The larval fish abundance showed significant seasonal dynamics, with summer themost, and winter the least numbers. From winter toward autumn, the species diversity
increased until summer then decreased until autumn. The dominant species are belong
to taxa of Gobiidae, acanthogobius ommaturus, and amblycheturichthys hexanema

3 / 6

(Figure 1). From winter to autumn, the dominant juvenile fish were Gobiidae,
acanthogobius ommaturus and amblycheturichthys hexanema, respectively.
Table 1 dominant species in winter, spring, summer and autumn, respectively

Figure 2 seasonal variation of larval fish community and dominant species

The estuary larval fish groups were mainly identified in winter, spring and summer,with the dominant species were Sparidae in winter, Gobiidae in spring and Gobiidae insummer, the offshore species were mainly found offshore species, with the Lanternfish
the most during all seasons except autumn. The two abundance of GSciaenidae species
and Harpadon nehereus showed different seasonal patters. As described in figure 3. We

4 / 6

used the contours of season-longitude, season-latitude to study the migration of eachdominant juvenile fish species.
3.2 Latitudinal migration of SYC. and Hn. species
Average size showed opposite seasonal pattern, with the Small yellow croaker (SYC)
size decrease, while Harpadon nehereus(Hn.) increase. SYC. spawn in April-May, while,Hn. Spawn during summer, so the spawning time is the time with big size, recruitment
after spawning 2-3 months, which will make the numbers reaching peak, but withsmallest size.Fishing probably significantly influences the SYC, while not Hn., because
the SYC abundance rebound suddenly when the fishing close, however, the Hn.
decrease with the fishing gone, and increase with the fishing reopen (Figure 3).

Figure 3. Latitude-temporal distribution of two species Hn. And Syc.
3.3 Longitudinal migration of SYC. and Hn. species
The migration of both Hn and SYC are complex, both of Hn and SYC have a large
distribution across the Yellow Sea and East China sea, the two species have spawning,overwinter and feeding migration in the ECS areas. The zhoushan areas is a good
5 / 6spawning and nursery ground for diverse species. For Hn, the abundance is low in thelarge ECS scale probably due to movement to the island for spawning. Our data along
the longitude also showed the high numbers of Hn moved toward the island fromMarch to June. And, after summer spawning, the recruitment was initiated since fall, as
seen the numbers increase in October. After spawning during summer, they start for thefeeding nearby, and migrating more disperse. This is can be saw from large numbers
along all the longitude during the fall. The Hn. size increase to peak until summer due tomatured and large fish, it decrease during fall due to recruitment of young. The large
size seems prefer to stay offshore rather than coast side, probably reflected the goodnursery in the coast (Figure 4).

Figure 4. Longitude-temporal distribution of two species Hn. And Syc.

.

6 / 6