## 4 Discussion
### Implications for Fisheries Management  
The mapping of fishing intensity, kernel density, and hotspots revealed a patchy spatial distribution of fishing vessel operating spaces in the Arabian Sea. Within this region, high-value patches were interspersed with 0 value patches, as confirmed by the spatial distribution map of the catch data. This patchy distribution underscores the need for fine-grained fisheries and environmental data for effective resource analysis and management in the area. Greater spatial precision in the analysis may smooth detailed information about resource distribution and potentially lead to misleading conclusions. In the patchy spatial distribution phenomenon, the substantial spatial variation in operations across different months underscores the considerable seasonal fluctuation of the fishery resources in the region. Simultaneously, the global spatial analysis, as illustrated in Table 2, indicated a non-random distribution, revealing spatial aggregation in the monthly distribution of fishing vessels engaged in catches. This suggests that despite the notable month-to-month variability in the spatial distribution of fishing vessel operations, a majority of these vessels tended to operate in clusters, particularly those affiliated with the same fishing vessel production enterprises. The patchy and spatially clustered nature of fishing vessel operating spaces highlights significant changes in the region's fishery, emphasizing that fishing vessels have yet to fully grasp the characteristics of fishery distribution and its changing patterns. Effective fishery management necessitates a comprehensive understanding of the migration and distribution of fishery resources in the region. Given that the light purse seine fishery in the area borders the exclusive economic zones of multiple countries, it becomes imperative to strengthen international cooperation in regional fishery resource management. This cooperation should focus on comprehending the migratory paths and biological habits of fishery resources in the region, establishing an effective joint fishery management mechanism, and enhancing the regulation of the fishing vessels operating in the area. The statistical analysis presented in this paper revealed a notable decline in fishing vessel operations during the period from June to September, consistent with the findings from previous fishery data studies [18; 19]. Mainland China's fishing vessels traditionally embark on fishing expeditions in September for annual operations. Notably, the fishing season in the Arabian Sea spans from October to May of the following year. Notably, engaging in fishing operations during non-fishing seasons can have severe detrimental effects on fishery resources [29]. Commencing in 2020, China implemented a high-sea fishing moratorium policy, which was effective from July 1 to September 30. In 2022, the high sea waters of the northern Indian Ocean (55\({}^{\circ}\) E-70\({}^{\circ}\) E, 0\({}^{\circ}\) N-22\({}^{\circ}\) N), excluding the SIOFA jurisdictional area, were also included in the high sea closure area, as corroborated by the absence of fishing effort in September 2022, as depicted in Figure 8. The methodology outlined in this paper demonstrates that AIS vessel position data can serve as a valuable tool for monitoring the potential violations of regulations during closed seasons. Whilethe AIS data for 2021-2022 in this study are somewhat limited, the applied methodology serves as a viable model for future studies. Moreover, inherent limitations in AIS data contribute to challenges such as short-term information gaps resulting from the brief artificial shutdowns of AIS equipment. Distinguishing this situation from data loss due to transmission issues is complex. [PERSON] et al. [30] utilized self-supervised deep learning techniques and transformer models to detect abnormal intentional AIS transponder shutdowns.