| 20 May 2026
Quantifying Patterns and Drivers of Larval Dispersal in Japanese Anchovy (Engraulis japonicus) in the China Seas
Abstract. Larval dispersal is a fundamental process linking marine populations and shaping individual fitness and population connectivity, making its quantification essential for understanding recruitment dynamics in fisheries. However, larval dispersal of the commercially and ecologically important Japanese anchovy (Engraulis japonicus), one of the most abundant pelagic fishes in the China Seas, remains poorly understood. Here, we applied 1D and 2D dispersal kernels to quantify larval dispersal outputs from previously published Lagrangian particle-tracking simulations, in which particles were released from seven spawning grounds across the China Seas during April–August (1987–2004 and 2016) and tracked for 30–60 days. We evaluated the relative influences of spawning ground, spawning month and year, and larval travel duration, on dispersal patterns and connectivity. Larval settlement was concentrated in the Bohai Sea, the northern Yellow Sea and along the southern coast of the Shandong Peninsula, with peak densities near 39°N; a Weibull 1D dispersal kernel best described larval dispersal patten, with modal dispersal distances ranges from 44.53–150.56 km, identifying these regions as major nursery grounds. Among all factors examined, spawning ground was the dominant driver of dispersal and connectivity, explaining 31.1% of the variance. Larvae from Changjiang Estuary spawning ground dispersed more broadly to the Yellow Sea, Sea of Japan, and the northwestern Pacific, whereas larvae from other grounds were largely retained within the China Seas, highlighting the pivotal role of this ground in linking stocks between these regions. Dispersal patterns exhibited strong seasonal shifts, with enhanced eastward and northward export in spring–early summer and increased retention in late summer. Increasing larval travel duration promoted directional long-range transport while reduced occupied area, local retention, and self-recruitment, indicating that longer dispersal does not imply broader spatial occupation. Pelagic larval duration captured mean dispersal trends but was a poor predictor of individual dispersal outcomes. The relatively minor contribution of interannual variability compared to spatial factors suggests that management should focus more on persistent spatial structures rather than short-term fluctuations. Overall, these findings provide a comprehensive framework for understanding larval dispersal dynamics and offer a robust scientific basis for fisheries management of Japanese anchovy.
Quantification has long been an important issue in larval dispersal research. The Japanese anchovy (Engraulis japonicus) is one of the most ecologically and economically important small pelagic fish in the China Seas. However, a comprehensive and quantitative understanding of its larval dispersal patterns and underlying drivers has been lacking. This manuscript applies both 1D and 2D dispersal kernels to give a high spatiotemporal resolution, multi-factor, quantitative analysis of larval dispersal in Japanese anchovy across the China Seas, providing some new insights into the quantification of larval dispersal patterns. It also reveals the critical connectivity role of the Changjiang Estuary spawning ground, which is quite interesting and beyond expectations. However, I still have some concerns on the manuscript, and addressing them would, in my view, improve its quality.
Main concerns:
Connectivity matrices have been used primarily for reef fish, where reef areas can function simultaneously as spawning grounds and nursery grounds. In this study, the y‑axis of connectivity matrices represents spawning locations, but the x‑axis represents settlement locations rather than nursery grounds. What, then, is the meaning of connectivity between a spawning location and a settlement location?
I suggest that the authors provide a more detailed explanation of the connectivity matrices, including their ecological interpretation and limitations.
I do not think that the connectivity (dispersal rate) of larvae from the CJ spawning ground to the TWC and PS spawning grounds is sufficient to prove that the Chinese stock and the Japanese stock are connected. Although some larvae originating from CJ may reach the TWC region, larvae spawned at TWC may already have been advected further eastward by that time, resulting in limited spatial or temporal overlap between the two groups. Under such circumstances, the mere arrival of CJ larvae at TWC does not necessarily imply effective stock connectivity. Stronger evidence would come from demonstrating that larvae originating from CJ and TWC are transported to the same or nearby nursery habitats and overlap in space and time, thereby increasing the likelihood of mixing and subsequent recruitment into a common population. Such convergence of dispersal trajectories would provide a more convincing mechanism linking the two stocks.
I suggest that the authors discuss this point and greater caution should be exercised in both the wording and the conclusions of the manuscript, particularly when inferring stock connectivity from modeled dispersal pathways alone.
Minor suggestions:
L21: pattern, instead of patten.
L21: ranges from 44.53 to 150.56, replace “-” with “to”.
L100: hydrodynamic model, instead of modal.
L128: you said “30 days” in L81, but why you used 30, 40, 50, 60 days here.
L130: 15 times, instead of 15 days.
L131: The position of a particle stopped at the end…
L255-260: I think you need a Table S2 to give the values of modal dispersal distance, median-dispersal distance, and long-distance dispersal. It’s hard to read these values from the figure.
L372: dispersal kernels, instead of dispersal kernel.
L365: need a figure S2 to show the correlation between individual dispersal distances and PLD.
L366: The suggestion that PLD is not a reliable predictor of dispersal distance at the individual level, yet can capture broad average trends in dispersal potential, is interesting. Alvarez-Noriega et al. (2020), in their study "Global biogeography of marine dispersal potential," used PLD multiplied by average flow velocity to estimate mean dispersal distance and quantified the overall latitudinal gradient in larval dispersal distance. You could discuss this study to further contextualize or support your findings.
L402: as stated above, you can change the descriptions here, for example, we suggest that they may be connected through Changjiang spawning ground.