Understanding the dynamic spatial distribution and characteristics of fishing activities is crucial for fisheries management and sustainable development. In recent years, small pelagic fish and cephalopods in the Arabian Sea have become new targets for light purse seine fishing; however, there is a lack of publicly available reports. This study uses automatic identification system (AIS) data from January to May and October to December of 2021 to 2022 in the region between 58°–70° E and 10°–22° N to extract spatial distribution information through three methods. The results show that with a spatial resolution of 0.25° × 0.25°, the spatial similarity index between the fishing ground information extracted in 2022 and catch data was consistently above 0.60, reaching 0.76 in March 2021 and 0.79 in November 2022, while the spatial similarity index in March 2022 exceeded 0.71. The spatial distribution of fishing effort and kernel density was similar to that of the fishing grounds, and the fishing intensity information exhibited the highest spatiotemporal similarity with commercial catch data, making it more suitable as a substitute for fishery data. Therefore, effective international cooperation and efficient joint management mechanisms for fishing vessels are needed to enhance the regulatory oversight of fishing vessels in this region. Integrating AIS data with other technological methods is crucial for more effective monitoring and management of fishing vessels. The findings presented in this paper provide both quantitative and qualitative scientific support for resource conservation and sustainable development in the region.

In aquaculture production, manual or fixed-schedule feeding often fails to match the real-time feeding level of fish schools, and overfeeding can lead to feed wastage and water-quality deterioration, which has become a major bottleneck for both large-scale farming efficiency and environmental sustainability. During feeding, intense competition and jumping behaviors generate splashes of varying magnitudes, which can serve as an indirect visual proxy for hunger intensity. In this study, we constructed a frame-level splash-annotated dataset and performed data preprocessing. Building upon YOLO11 pretrained weights, we introduced a P2–P5 four-scale detection head to enhance small-splash recognition, injected EGMA into the backbone C3k2 blocks, and replaced stride-2 downsampling convolutions with a three-branch ADown operator. On the validation set, the proposed YOLO11-PEGA achieved a precision of 0.86 and a recall of 0.80, with mAP@0.5 exceeding 0.80 and mAP@0.5–0.95 exceeding 0.30. Compared with the baseline model, the parameter count was reduced by 72.3%. The results demonstrate that the proposed model maintains stable detection and evaluation performance under complex environmental conditions, providing actionable decision support for feeding-threshold setting, feeding-time determination, and feed-amount adjustment.

This study addresses the challenges of manual measurement bias and low robustness in detecting small, occluded targets in complex marine environments during real-time onboard sorting of Portunus trituberculatus. We propose YOLO-DFAM, an enhanced YOLOv11n-based model that replaces the global average pooling in the Focal Modulation module with a spatial–channel dual-attention mechanism and incorporates the ASF-YOLO cross-scale fusion strategy to improve feature representation across varying target sizes. These enhancements significantly boost detection, achieving an mAP@50 of 98.0% and precision of 94.6%, outperforming RetinaNet-CSL and Rotated Faster R-CNN by up to 6.3% while maintaining real-time inference at 180.3 FPS with only 7.2 GFLOPs. Unlike prior static-scene approaches, our unified framework integrates attention-guided detection, scale-adaptive tracking, and lightweight weight estimation for dynamic marine conditions. A ByteTrack-based tracking module with dynamic scale calibration, EMA filtering, and optical flow compensation ensures stable multi-frame tracking. Additionally, a region-specific allometric weight estimation model (R² = 0.9856) reduces dimensional errors by 85.7% and maintains prediction errors below 4.7% using only 12 spline-interpolated calibration sets. YOLO-DFAM provides an accurate, efficient solution for intelligent onboard fishery monitoring.

The Arabian Sea is a key region for global marine biogeochemical research, yet the distribution characteristics and influencing factors of dissolved oxygen and chlorophyll a concentration in its central oxygen minimum zone still require further in-depth investigation. Based on survey data and reanalysis data from 2024, this paper analyzes the distribution characteristics and underlying causes of chlorophyll a concentration and dissolved oxygen using empirical orthogonal function (EOF) decomposition of chlorophyll a concentration and dissolved oxygen saturation along the depth direction, combined with the distribution of the barrier layer, Ekman pumping induced by wind fields, and the diagnostic vertical velocity distribution calculated from ADCP-observed flow velocities. Taking approximately 10° N as the boundary, the chlorophyll a concentration in the layer shallower than 35 m exhibits a distribution pattern of high in the northwest and low in the southeast, while the water layer between 45 m and 95 m shows a pattern of low in the northwest and high in the southeast. A thick barrier layer exists in the southeastern region, whereas the barrier layer in the northwestern region is thinner or absent, resulting in lower surface chlorophyll a concentration in the southeast. ADCP observations indicate that horizontal flow velocities are higher in the south, bringing oxygen-rich water from the south, which leads to higher dissolved oxygen saturation in the southern region compared to the northern region in water shallower than 45 m. At the 65 m water layer, the higher chlorophyll a concentration in the south may result in relatively low dissolved oxygen. The hypoxic zone (dissolved oxygen saturation less than 30%) begins to appear at depths below 105 m, with its southern boundary located between 9° N and 11° N, and this boundary gradually shifts northward as depth increases. The diagnostic vertical velocity between 9° N and 11° N is higher than that in other regions, which may hinder the northward movement of oxygen-rich water from the south. In the southern region, influenced by wind stress, the vertical water movement induced by Ekman pumping is relatively significant, which may lead to a slight increase in dissolved oxygen saturation in water layers with a depth below 125 m.