This paper describes the weight–length relationships (WLRs) and Fulton’s condition factors (K) of skipjack tuna (Katsuwonus pelamis) in purse seine fisheries from three cruises in the western and central Pacific Ocean (WCPO): August–September 2009 (AS09), November–December 2012 (ND12), and June–July 2013 (JJ13). The fork length and weight of a total of 1678 specimens were measured. The results showed that the fork length of more than 70% of specimens was below 60 cm (76% in AS09, 87% in ND12, and 73% in JJ13). The coefficient b in the combined sex group was 3.367, 3.300 and 3.234 in JJ13, AS09 and ND12, respectively. The b values of WLRs when fork length was >60 cm were significantly less than 3 (P = 0.062), but when fork length was <60 cm they were significantly greater than 3 (P = 0.028). The K value ranges of JJ13, AS09 and ND12 in different fork length groups were 1.3–1.84 (1.62 ± 0.18), 1.57–2.02 (1.86 ± 0.15), and 1.44–1.78 (0.65 ± 0.13), respectively. Moreover, K values in different fork length classes for each cruise had one turning point: 60–65 cm for JJ13; 60–65 cm for ND12; and 55–60 cm for AS09. The results of this study provide basic information on the WLRs and K values of skipjack tuna in different seasons and growth phases in the WCPO, which are useful for fishery biologists and fishery managers.

Accurate prediction of the central fishing grounds of chub mackerel is substantial for assessing and managing marine fishery resources. Based on the high-seas chub mackerel fishery statistics and multi-factor ocean remote-sensing environmental data in the Northwest Pacific Ocean from 2014 to 2021, this article applied the gravity center of the fishing grounds, 2DCNN, and 3DCNN models to analyze the spatial and temporal variability of the chub mackerel catches and fishing grounds. Results:1) the primary fishing season of chub mackerel fishery was April-November which catches were mainly concentrated in 39°∼43°N, 149°∼154°E. 2) Since 2019, the annual gravity center of the fishing grounds has continued to move northeastward; the monthly gravity center has prominent seasonal migratory characteristics. 3) 3DCNN model was better than the 2DCNN model. 4) For 3DCNN, the model prioritized learning information on the most easily distinguishable ocean remote-sensing environmental variables in different classifications.

Understanding and forecasting changes in marine habitats due to global climate warming is crucial for sustainable fisheries. Using future environmental data provided by Global Climate Models (GCMs) and occurrence records of Chub mackerel in the North Pacific Ocean (2014-2023), we built eight individual models and four ensemble models to simulate current habitat distribution and forecast changes under three future climate scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) for the 2050s and 2100s. Ensemble models outperformed individual ones, with the weighted average algorithm model achieving the highest accuracy (AUC 0.994, TSS 0.929). Sea Surface Temperature (SST) and chlorophyll-a (Chla) significantly influenced habitat distribution. Predictions indicate current high suitability areas for Chub mackerel are concentrated beyond the 200-nautical-mile baseline. Under future climate scenarios, habitat suitability is expected to decline, with a shift towards higher latitudes and deeper waters. High suitability areas will be significantly reduced.

To better develop and protect the pelagic fishery in the northwest Indian Ocean, China’s fishing enterprises have been producing pelagic fisheries in the said area for a long time. Based on the fishing log data of light falling gear in the northwest Indian Ocean from 2016 to 2020, this study analyzed the impact of different time scales on the catch rate and fishing ground center of gravity of light falling gear fishing grounds. We also explored the relationship between different time scales and catch per unit effort (CPUE) by using the fishing ground center of gravity, the Random Forest model (RF), and the generalized additive model (GAM). The results were shown as follows: (1) From 2016 to 2020, 76,576 t were captured, and 16,496 nets were operated; (2) The gravity center of fishing ground in the Northwest Indian Ocean moved to the northeast as a whole, and the monthly fishing ground gravity center changed first to the Southern and then to the northern; (3) RF model (R² = 0.709, RMSE = 0.2034, and prediction accuracy is 55.8%), which is better than the GAM model (R² = 0.632, RMSE = 0.2242, and prediction accuracy is 37.3%). In the RF model, the importance of time variables on CPUE was in the order of week, year, operation time, and lunar phase; in the GAM model, it was week, year, lunar phase, and operation time. On the whole, the importance of the long time scale (year, week) is greater than that of the short time scale (lunar phase and operation time). (4) The RF model and GAM model show that the most critical environmental variables were SST, DO, SSS, and Chla, and the least important were SSH, Δ50, and CV50. SST, Chla, and DO significantly impact pelagic fishing and CPUE and are critical reference indexes for predicting the Northwest Indian Ocean light falling gear fishing ground. (5) The 95% confidence interval showed that the suitable interval of time, space, and environmental variables in the RF model was much smaller than in the GAM model.

The Japanese eel Anguilla japonica is an important aquaculture fish species in the East Asian countries of Japan, China, Korea, and Taiwan. All glass eel fry are captured from the wild and understanding the recruitment patterns of the glass eel is important. The larvae of A. japonica are passively transported to the East Asian Continental Shelf by the North Equatorial Current, the Kuroshio, the Kuroshio intrusion currents, and coastal currents. In each location, recruitment time is diverse: It is November in Taiwan and April in the Yalu River. How the glass eels reach recruitment areas remains poorly understood. Here, we combine information from larval ages based on otolith increments, simulated drifting paths on the East Asian Continental Shelf, and main fishing seasons in each location of East Asia. We identify five main recruitment blocks: (1) The main Kuroshio, (2) The Taiwan Strait Warm Current, (3) The Taiwan Warm Current, (4) The Yellow Sea Warm Current and (5) The branch of Yellow Sea Warm Current. The counted age of the glass eels is significantly underestimated for the later recruits, possibly due to the cessation of the otolith edge growth under low water temperatures. This study clarifies the eel’s larval characteristics and transport mechanisms in the East Asia Continental Shelf, providing important information for its recruitment dynamics in the marine stage.