Analysis of fishing intensity in the South China Sea based on automatic identification system data: A comparison between China and Vietnam

Abstract

Objective

Recently, the South China Sea has been facing a crisis of depleted fishery resources, primarily due to the impacts of illegal, unreported, and unregulated fishing activities, as well as overfishing. Accurately understanding the fishing activity intensity in the South China Sea holds significant implications for the sustainable management of fisheries resources.

Methods

Leveraging the automatic identification system trajectory data from 2018, this paper employs spatial statistical methods and fishing effort indicators to comparatively analyze the spatial variations in fishing intensity between Chinese and Vietnamese fishing vessels.

Result

The results of this study show that (1) in 2018, the total fishing effort of Chinese fishing vessels in the South China Sea was 7.65 times that of Vietnamese vessels, but during China's South China Sea fishing moratorium, the fishing effort exerted by Vietnamese vessels surpassed that of China and (2) the top 10 ports in China and Vietnam support approximately 30% and 55.13% of their respective fishing intensities in the South China Sea.

Conclusion

The study highlights significant variations in fishing intensity between Chinese and Vietnamese vessels and the substantial support provided by major ports. These findings offer valuable insights for fisheries resource monitoring and maritime spatial planning, contributing to the sustainable management of the South China Sea's fisheries resources.

INTRODUCTION

In the face of escalating global challenges such as population growth, land resource depletion, and environmental degradation, the resource-rich oceans are gradually garnering attention from various countries (Sunagawa et al. 2020). Marine fisheries, as a significant component of marine resources, play a key role in ensuring food security and driving economic growth in the oceanic domain (Paterson et al. 2013). Among the world's most crucial commercial fishing grounds, the South China Sea ranks fifth in terms of annual fish catch (Yuan et al. 2022). Its abundant fishery resources have long served as a vital source of food security for neighboring countries and regions and a fundamental economic pillar for countless fishermen's livelihoods (Zhang et al. 2018).

There is a wide range of commercial fishing activities in the South China Sea (Zhao et al. 2018). However, in recent years, its fishery resources have encountered significant challenges, including excessive fishing intensity (Arai and Azri 2019), illegal fishing (Cabral et al. 2018), and nonselective fishing (Sun et al. 2023), leading to severe degradation of the fishery grounds (Wang et al. 2018). Moreover, the absence of a collaborative mechanism among neighboring countries and regions for the protection and management of these resources has further exacerbated the decline (Cao et al. 2017). In order to promote the sustainable management of fishery resources in the South China Sea, since 1999, China has implemented a fishing moratorium in the South China Sea, that is, a fixed period of time each year during which fishing is banned and penalties are imposed on foreign and Chinese vessels that illegally fish during this period. Recognizing the significance of ports in combating illegal fishing, the Food and Agriculture Organization of the United Nations considers them primary gathering places for such activities. Port inspections and apprehensions are considered the most efficient approach compared with monitoring the vast sea (Ferrà et al. 2020). Strengthening and enhancing port management is thus essential in effectively curbing illegal fishing practices (Zubaidah and Ainun 2021). Consequently, a comprehensive understanding of the fishing dynamics in the South China Sea, particularly during China's fishing moratorium, as well as the fishing intensity supported by coastal ports, holds utmost importance in regulating and promoting the sustainable management of fishery resources in the region.

In the past, for a long time, fishing vessel activities were primarily monitored through fishing logs or surveillance data provided by fisheries management agencies (Rijnsdorp et al. 1998). However, these data suffered from limited accessibility, lacked temporal and spatial resolution, and were often subject to manual recording, resulting in nonstandardization and inaccuracies (de Souza et al. 2016). It was not until the 1990s that the implementation of the vessel monitoring system (VMS) revolutionized the monitoring of fishing activities within jurisdictions. The VMS enabled automatic reporting of fishing vessel identifiers, positions, speeds, and headings, providing fisheries management agencies with an effective means of surveillance. Extensive research has since been conducted on fisheries applications based on VMS data, leading to significant advancements in fishing behavior identification, fishing intensity measurement, fishing ground extraction, and ecological pressure assessment of fishing activities (Lee et al. 2010; Bez et al. 2011). However, one limitation of VMS systems is the reporting interval, typically set at 1–2 h, resulting in a low reporting frequency and potential oversight of short-duration fishing activities (Hinz et al. 2013; Thoya et al. 2021). Additionally, the closed nature of VMS systems, reliant on government or fisheries management agencies for data collection, coupled with limited public accessibility, further restricts its application in fine-scale temporal and spatial fisheries research.

Advancements in GPS positioning technology and maritime communication have enabled remarkable progress in ship-tracking technologies. Among them, the automatic identification system (AIS) has emerged as a valuable tool, initially designed for collision avoidance and enhancing ship safety (Perera and Soares 2015; Zaman et al. 2015). The AIS provides vessel position reports via VHF radio at intervals ranging from 2 s to 3 min (Harati-Mokhtari et al. 2007; Dunn et al. 2018; Kroodsma et al. 2018). The International Maritime Organization mandates the installation of AIS equipment on international voyaging vessels with a tonnage of 300 or above, noninternational voyaging vessels with a tonnage of 500 or above, and all passenger ships (Chircop 2016). The AIS offers nearly real-time temporal resolution, high spatial resolution, and ease of accessibility, presenting researchers with a wealth of valuable information for analyzing the spatiotemporal distribution of vessel activities at various scales (Yang et al. 2019). Consequently, scholars worldwide have utilized AIS data to study various aspects of vessel activities in the marine environment (Bye and Almklov 2019; Svanberg et al. 2019; Han et al. 2021). For instance, Guiet et al. (2019) investigated the seasonal variation of global marine fishing efforts using AIS data. Natale et al. (2015) developed an approach based on analyzing individual vessel speed profiles to identify fishing activities, generating high-resolution fishing effort maps. Additionally, Chen et al. (2020) proposed a novel convolutional neural network-based classification model that effectively improved the accuracy and performance of AIS data vessel classification models. Kerry et al. (2022) assessed fishing efforts of vessels near global seamounts based on AIS data, comparing efforts across different management areas and countries while exploring the impact of seamount depth on fishing efforts, providing crucial data support for the conservation of ecologically vulnerable seamount areas. These studies have significantly contributed to our understanding of global and regional fishing efforts (Bell et al. 2017; Hyder et al. 2018; Kroodsma et al. 2018). Despite the extensive research on fishing efforts worldwide, limited attention has been given to the South China Sea, particularly during China's South China Sea fishing moratorium, and the fishing activities supported by coastal ports. Currently, there is a scarcity of reports and studies published on this matter.

China has implemented a fishing moratorium in the South China Sea since 1999. During the fishing moratorium in the South China Sea, Chinese fishing vessels complied well with the moratorium, but there were also a small number of illegal fishing vessels. Vietnam, which has yet to reach an agreement with China on a fishing ban, strongly opposes the ban. The fishing ban in the South China Sea varies in different years. For example, the fishing ban in the South China Sea in 2015 was from May 16 to August 1 while the fishing ban in the South China Sea in 2018 was from May 1 to August 16. This paper takes the fishing moratorium in the South China Sea of a certain period as an example to try to grasp the fishing situation of Chinese and Vietnamese fishing vessels during the period of fishing moratorium, so the AIS of 2018 was chosen as the representative data source. Given the high spatiotemporal resolution characteristics of AIS, employing fishing effort to evaluate fishing intensity holds significant value in fisheries management and research (Mills et al. 2007; Lee et al. 2010). To evaluate the efficacy of China's South China Sea fishing ban and comprehend the fishing activities facilitated by coastal ports, this study focused on investigating the spatial disparities in fishing intensity between Chinese and Vietnamese fishing vessels in the South China Sea. The quantification of fishing effort was employed as a metric to assess fishing intensity, and a combination of spatial statistics and indicators of fishing effort were applied. The AIS data were utilized to conduct monthly statistical analysis of fishing effort for Chinese and Vietnamese vessels at a fine spatiotemporal scale. The study scrutinized the variations in fishing effort between Chinese and Vietnamese fishing vessels during China's South China Sea fishing moratorium, generated spatial distribution maps of fishing effort for both countries, and quantitatively calculated the fishing effort supported by Chinese and Vietnamese ports.

METHODS

Study area and data source

The South China Sea, located in the southern part of China, is connected to the Pacific Ocean in the east and communicates with the Indian Ocean in the west. It is a semienclosed sea with a northeast–southwest orientation, covering a total area of approximately 3.5 million square kilometers. The South China Sea is rich in fishery resources, including many important fishing grounds such as the Beibu Gulf fishing ground, the Xisha West fishing ground, the Nansha West fishing ground, and the Pearl River Estuary fishing ground, making it a crucial area for the fishery economic development of neighboring countries and regions. This paper focuses on the coastal waters of China and Vietnam, which are also the primary distribution areas for major fishing grounds. At present, China, Vietnam, the Philippines, and other neighboring countries in the South China Sea have sovereignty disputes over the waters. The red line in Figure 1 shows China's demarcation of seasonal no-fishing zones in the South China Sea, during which Chinese fishing vessels are forbidden to conduct illegal fishing activities. In fact, Vietnam strongly opposes China's seasonal fishing moratorium, which has been applied to some of the disputed waters in the South China Sea. This study focuses on the area within 105°E to 122°E longitude and 1°N to 25°N latitude in the South China Sea, as shown in Figure 1. The port data utilized in this study are sourced from the shipping data statistics website IHS Markit () while the AIS data are obtained from the ship information website Shipxy ().

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The AIS data employed in this study encompass a time span from January 1, 2018, to December 31, 2018, and comprise both static and dynamic information. The static data encompass attributes like Maritime Mobile Service Identity (MMSI), International Maritime Organization number, vessel name, vessel type, vessel length, and vessel width. Conversely, the dynamic data include attributes such as MMSI code, waypoint time, longitude, latitude, ground speed, and course over ground. The MMSI, a highly crucial and unique code within the AIS system, consists of nine digits. The first three digits are assigned by international organizations to individual countries and regions, thereby indicating the nationality of the fishing vessel. The subsequent six digits constitute the specific identification code for the vessel, enabling retrieval of information about the vessel's company, operator, and other relevant details. Table 1 presents the first three digits of the MMSI code corresponding to Chinese and Vietnamese fishing vessels.

TABLE 1 Maritime Mobile Service Identity maritime identification digit (MID) codes for vessels from China and Vietnam.

Country	MID
China (including Taiwan)	412, 413, 414, 453, 477, 416
Vietnam	574

Method development

Data processing

Based on the MMSI code of the vessels, trajectory records of Chinese and Vietnamese fishing vessels within the study area were selected. Records with MMSI codes greater or less than nine digits were removed (Coomber et al. 2016). For each unique MMSI identity representing a fishing vessel, duplicate coordinate records and abnormal speed records were eliminated from the trajectory points throughout the year. On this basis, records with less than 300 trajectory points for the entire year were excluded (Natale et al. 2015). To ensure the accuracy of vessel positions and eliminate incorrect data due to GPS noise or incomplete AIS transmissions, the distance and time interval between consecutive trajectory points were calculated. Trajectory segments with unrealistic distance between consecutive points, where the distance between their longitude and latitude positions significantly exceeded the distance obtained by multiplying the time interval by the average speed between the two points, were identified and separated. Similarly, trajectory segments with a time interval exceeding 24 h were also separated. The former marked the end of one trajectory segment while the latter indicated the beginning of another trajectory segment. After the preprocessing steps, the remaining data were considered to represent genuine records of vessel positions during fishing or steaming activities and were utilized in subsequent analyses.

Identification of fishing activity

Due to the lack of fishing operation status attributes in AIS trajectory data, the estimation of fishing effort relies on accurately identifying fishing and nonfishing activities of fishing vessels. Convolutional neural networks, clustering analysis, and other machine learning algorithms are considered to have relatively high accuracy in recognizing fishing activities (Kroodsma et al. 2018), but they involve complex computations.

It is generally believed that fishing boats present different speed distribution characteristics when they are in different activity states such as sailing, fishing, and anchoring. In this study, a simple approach, the velocity threshold classification method, was used to identify fishing activities of fishing vessels. Specifically, the speed histogram detection method was applied to distinguish between fishing and nonfishing activities (Rodríguez et al. 2021). In this method, the speed histogram exhibits a bimodal distribution with approximately symmetric peaks on both sides, with each peak corresponding to fishing (low speed) and sailing (high speed) activities, respectively.

Calculation of fishing effort

The study area was divided into a series of grid cells using a regular grid of 0.05° × 0.05°. Fishing activity time expenditure was aggregated on each 0.05° grid cell. For each fishing vessel's trajectory line identified by the MMSI number, the fishing activity of two consecutive points on the trajectory line was determined based on the aforementioned speed criteria. If a fishing activity was detected, the time difference between the two consecutive fishing activities was calculated. Half of this time difference was allocated to the grid cell of the first fishing activity trajectory point, and the other half was allocated to the grid cell of the second fishing activity point (Rodríguez et al. 2021). The fishing time expenditure of all vessels was subsequently summarized for each grid cell.

When computing the fishing effort supported by ports, we detected the fishing activity sequences of each fishing vessel between consecutive visits to two ports identified by their MMSI numbers. Then, half of the fishing effort was associated with each of these two ports if they were identified. If the fishing activity sequence of a fishing vessel did not include any port visits, the fishing effort of that vessel was discarded.

Especially, we considered port locations as the grid cells (0.05° latitude × 0.05° longitude) that contain at least one port and are visited by at least one fishing vessel. When fish vessels record from within 0.05° of a port, effort will not be counted (Lee et al. 2010). This is because the 0.05° (∼3 nautical miles) grid cells containing ports are generally a navigable water area, where fishing activities are prohibited.

RESULTS

Fishing vessel speed verification

This paper selected a total of 49,442 fishing vessels (38,564 Chinese-flagged and 10,878 Vietnamese-flagged vessels) with 680,565,567 trajectory records from the original AIS data in the South China Sea region in 2018. In order to reduce the influence of noise track points, after preprocessing the original track points, a total of 29,146 Chinese and Vietnamese fishing boats (23,326 Chinese and 5820 Vietnamese) were obtained, including 679,553,246 track points. The deleted track points only account for 0.15% of the original track points, and the impact of this small proportion of track points on the final result can be ignored. According to the China Fishery Statistical Yearbook and Vietnam Statistical Yearbook, the number of Chinese fishing vessels in the South China Sea in 2018 was 69,873 while the number of Vietnamese fishing vessels above class 90 was 34,563. In this paper, the number of Chinese fishing boats tracked by AIS data accounted for 33.4% of the total and the number of Vietnamese fishing boats tracked accounted for 16.8% of the total.

Based on the preprocessed fishing vessel trajectory data, we conducted statistical analysis on the distribution of vessel speeds and identified fishing activities by plotting the vessel speed distribution, as shown in Figure 2. The results revealed that vessel speeds in the South China Sea region exhibited a bimodal distribution, corresponding to fishing operations (low speed) and navigation (high speed), with a speed break point at 5 knots. Rodríguez et al. (2021) defined a fishing event as a fishing spot with a speed of less than 5 knots. This is consistent with the speed of 5 knots at the break point between the two peaks in this paper. Trajectory data with speeds below 1 knot were excluded to minimize idle or waiting-to-port trajectories. By using a speed filter between 1 to 5 knots, fishing vessel trajectory records in the fishing operation state were effectively identified. These trajectory records accounted for 50.79% of all fishing vessel trajectory records.

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Analysis of monthly variation of fishing effort of Chinese and Vietnamese fishing vessels

Following the guidelines of the fishing moratorium in the South China Sea, the moratorium span in 2018 extended from May 1 to August 16. In order to comprehensively assess the efficacy of this fishing moratorium within the South China Sea, the monthly fishing efforts of both Chinese and Vietnamese vessels were aggregated over 2018, as outlined in Table 2. Given that August is characterized by an equitable division of days within and outside the Chinese fishing moratorium period in the South China Sea, this month was segmented into two distinct time frames to facilitate a precise evaluation of fishing efforts: August 1–16 and August 17–31.

TABLE 2 Monthly fishing efforts (days) of Chinese and Vietnamese fishing vessels in the South China Sea. Abbreviations are as follows: T1 = August 1–16 and T2 = August 17–31.

Country and total	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
T1	T2
Vietnam	2561	1167	2352	2293	4426	3921	4616	3550	2739	5041	4294	3181	3108
China	23,206	17,028	32,918	40,839	3754	3020	1557	4659	32,267	45,050	39,457	46,407	40,880
Total	25,767	18,195	35,270	43,132	8180	6941	6173	8209	35,006	50,091	43,751	49,588	43,988

From Table 2, it is evident that there is a significant disparity in fishing effort between Chinese and Vietnamese vessels in the year 2018. China's total fishing effort is 7.65 times that of Vietnam for the entire year. However, considering that the number of Chinese vessels is approximately four times that of Vietnam, this indicates that the average fishing effort of Chinese vessels is higher than that of Vietnamese vessels. During the Chinese fishing moratorium in the South China Sea, the total fishing effort by Chinese vessels accounts for approximately 4% of the annual total, whereas the total fishing effort by Vietnamese vessels accounts for around 38% of their annual total. Moreover, the daily average fishing effort during the moratorium period is 27% higher for Vietnamese vessels compared with Chinese vessels. This suggests that Chinese vessels adhered more strictly to the South China Sea fishing moratorium while Vietnamese vessels continued significant fishing activities during the moratorium period. Analyzing the changes in fishing effort before and after the moratorium, it is observed that China's total fishing effort from September to December is three times that of the period from January to April. On the other hand, Vietnam's total fishing effort from September to December is 1.87 times that of the period from January to April. After the implementation of the moratorium, both China and Vietnam experienced an increase in total fishing effort compared with the premoratorium period.

Further analyzing the monthly variations in fishing effort for Chinese and Vietnamese vessels (as shown in Figure 3), it can be observed that China's fishing effort gradually increased before the moratorium (January to April, except for February), sharply declined during the moratorium period, reaching the lowest point in July, and then rapidly rebounded after the moratorium ended (September to December, except for October). The decline in fishing effort during February was due to the occurrence of the Chinese Lunar New Year, which resulted in reduced fishing activities. During the South China Sea fishing moratorium, a significant portion of Chinese vessels returned to port, leading to the sharp decrease in fishing effort. After the moratorium, Chinese vessels engaged in large-scale fishing activities, resulting in a rapid increase in fishing effort. Notably, China's traditional National Day holiday in October led to a slight decrease in fishing effort during that month, as many fishermen went home for vacation.

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In contrast, the monthly variation in fishing effort for Vietnamese vessels exhibited a different pattern from China's. Vietnamese fishing effort showed slow growth (except for February), peaked in August, and then gradually decreased, with overall fluctuations being relatively minor. Similar to China, Vietnam also experienced reduced fishing effort during February due to the Lunar New Year. After the South China Sea fishing moratorium, Vietnamese fishing vessels increased their fishing efforts, reaching a peak in August. Subsequently, the fishing effort by Vietnamese vessels gradually decreased to the same level as before the moratorium.

Analyzing the monthly trends in 2018, China's fishing effort shows significant fluctuations with a sharp decline from May to July while Vietnam's fishing effort gradually increases from May to July. During this period, the fishing effort by Vietnamese vessels surpasses that of China. This indicates that Chinese fishermen adhered more strictly to the South China Sea fishing moratorium while Vietnamese fishermen continued significant fishing activities in the South China Sea during the moratorium period.

Spatial differentiation of fishing effort between Chinese and Vietnamese fishing vessels

In order to compare and analyze the differences in the spatial distribution of fishing efforts between China and Vietnam in the South China Sea, this paper divides the entire South China Sea into grids and calculates the fishing volume of Chinese and Vietnamese fishing vessels in 2018 within each grid. Each grid cell aggregates the fishing time spent by all boats. Considering that a grid with less than 1 day of fishing effort may be a noisy grid, it is considered as a level 1 alone; according to the time span of month and season, the grids with fishing effort of more than 1 day were divided into three levels: 1–30 days, 30–120 days, and more than 120 days. Figure 4 shows the spatial distribution of fishing effort by Chinese and Vietnamese vessels. In terms of the total fishing effort grid and the number of high fishing effort grid in the South China Sea, China is significantly higher than Vietnam and there are significant differences in the spatial distribution of fishing effort between the two countries.

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As shown in Figure 4A, along the coastline from Xiamen to Zhanjiang in China, the fishing effort of Chinese fishing vessels presents an obvious banded distribution: about 80 km from the coastline, the fishing activity intensity is relatively high and the waters near Xiamen and Shantou show a high-intensity aggregation distribution, while within 80–150 km from the coastline, the intensity of fishing activities is weakened. Fishing activity is less frequent beyond about 150 km from the coast. In the Beibu Gulf, fishing activities are mainly concentrated in the waters around Beihai Port in Guangxi and the fishing effort of fishing vessels showed a cluster pattern. In the waters around Hainan Island, the fishing effort of fishing vessels presents a circular distribution: the fishing effort of fishing vessels is higher within about 80 km from the coastline while the fishing effort of fishing vessels is less frequent outside 80 km from the coastline and it is distributed in a high-intensity block around Haikou and Sanya ports. Far sea fishing boats mainly concentrated around Xisha Islands, and the intensity of fishing boat activities around other islands in the South China Sea was relatively low. In particular, there are fishing activities of Chinese fishing vessels in the waters around the port of Ho Chi Minh in Vietnam, and it may be a small number of fishing vessels carrying Chinese AIS coding receivers to carry out catch trading activities in the port of Ho Chi Minh.

As shown in Figure 4B, the fishing activities of Vietnamese fishing vessels are mainly distributed in the waters around Ho Chi Minh Port, the Beibu Gulf, and the waters around Hainan Island of China. Compared with other sea areas, the fishing intensity of Vietnamese fishing vessels was the highest in the sea area of Ho Chi Minh Port, and the fishing effort was distributed in blocks and gradations, radiating from the inner layer to the outer layer, with the fishing effort of fishing vessels gradually weakening moving outward. Fishing efforts in the central coastal area of Vietnam are small and scattered only around ports. In the waters of the Beibu Gulf, the fishing activities of Vietnamese fishing boats cover a wide range of sea areas and there are high-intensity gathering fishing activities in the waters northeast of Haiphong Port. In the waters near Hainan Island of China, the fishing activities of Vietnamese fishing boats show a scattered distribution half-surrounding Hainan Island, mainly distributed in the waters around Sanya Port.

The spatial distribution of fishing effort of Chinese and Vietnamese vessels during the fishing moratorium in the South China Sea was further analyzed. Based on the fishing boat track data of China and Vietnam from May 1 to August 16, the fishing efforts of China and Vietnam in each grid were counted respectively, and the results are shown in Figure 5. In Figure 5A, the fishing effort of Chinese fishing vessels decreased significantly during the fishing moratorium period, mainly distributed in the waters around Hainan Island, the coastal waters of Guangdong Province, and the coastal waters of Fujian Province. The South China Sea fishing ban has been well implemented in China. In Figure 5B, the fishing efforts of Vietnamese fishing vessels were mainly distributed in the waters of Ho Chi Minh Port, the Beibu Gulf, and the waters around Hainan Island, China, and intruded into China's prohibited fishing lines and there was a certain intensity of fishing activities in the waters around Hainan Island. It can be seen that during the fishing moratorium period in the South China Sea, a large number of Vietnamese fishermen did not comply with the fishing ban in the South China Sea and there were illegal fishing activities.

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In addition, we also analyzed the spatial distribution of fishing effort of Chinese and Vietnamese fishing vessels during the nonclosed season. As can be seen from Figure 6B, Vietnam still has a large number of fishing vessels in Chinese waters during China's open season. That is, Vietnam's fishing activities around Hainan are carried out all year round.

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Analysis of fishing effort support by Chinese and Vietnamese ports

Ports serve as focal points for illicit fishing endeavors. To enhance port management and effectively mitigate unlawful fishing activities, this investigation meticulously examined the fishing effort bolstered by Chinese and Vietnamese ports throughout 2018, with the objective of pinpointing the ports facilitating the highest fish landings. Owing to certain vessels deactivating their AIS systems during port ingress and egress or their embarkation or disembarkation points not being included in the port data roster employed in this study, some fishing vessels' activity sequences were devoid of port visits. Consequently, the fishing effort attributed to these vessels was deleted from the analysis. The tabulated data in Table 3 delineates the foremost 10 Chinese and Vietnamese ports separately based on fishing effort while their spatial distribution is graphically depicted in Figure 7. A scrutiny of Table 3 distinctly reveals that 30.82% of Chinese fishing efforts and 43.73% of Vietnamese fishing efforts were not accounted for within the ambit of port-supported fishing effort. Nonetheless, the considered port-supported fishing effort adequately reflects the comparative number of fishing trips landing at each port.

TABLE 3 Statistics of fishing effort (days) supported by Chinese and Vietnamese ports.

	China	Vietnam
Ranking and efforts	Port	Fishing effort	Proportion (%)	Port	Fishing effort	Proportion (%)
1	Beihai	21,593.31	6.52	Dong Thap	10,103.39	23.36
2	Yuedong	16,249.25	4.91	Danang	5655.84	13.08
3	Shanwei	15,036.98	4.54	Vung Tau	3402.87	7.87
4	Zhangzhou	12,047.25	3.64	Cat Lo	1830.68	4.23
5	Wanshan	11,191.91	3.38	Lach Huyen	1279.43	2.96
6	Yutang	10,911.58	3.30	Quy Nhon	483.97	1.12
7	Houshan Power Station	10,431.38	3.15	Navioil Port	328.81	0.76
8	Guang'ao	10,101.27	3.05	Dinh Vu	281.23	0.65
9	Ganchong	10,047.47	3.04	Campha	245.29	0.57
10	Macau	8361.10	2.53	Duyen Hai Sea Port	227.73	0.53
Other ports support fishing efforts		103,048.53	31.13		498.7	1.15
Discarded fishing efforts		102,021.95	30.82		18,911	43.73
Total efforts		331,042	100		43,249	100

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As shown in Figure 7, in terms of spatial distribution, Chinese ports are relatively dispersed and sparsely distributed along the coastal regions from Guangxi to Fujian Province. On the other hand, Vietnamese ports exhibit significant clustering, with five ports concentrated around Ho Chi Minh City. Regarding the numerical distribution of port-supported fishing effort, Chinese ports show a relatively balanced distribution, with small differences in the effort values between them. The fishing effort supported by the top-ranking port is 2.6 times that of the 10th-ranking port. In contrast, Vietnamese ports display greater disparities in the fishing effort they support, with the top-ranking port supporting 42 times the effort of the 10th-ranking port. To some extent, major Chinese ports contribute more evenly to the fishing industry while Vietnam's port contributions are more concentrated in a few key locations.

DISCUSSION

The South China Sea possesses abundant fishery resources, making it one of the world's most crucial fishing grounds (Sumaila 2015). However, the region is currently facing a crisis of fishery resource depletion due to issues like illegal, unreported, and unregulated fishing and overfishing. While the challenges posed to the neighboring countries by the predicament of South China Sea fishery resources are evident, it also presents new opportunities for coastal nations to foster cooperation. Both theory and practice suggest that effective collaboration on low-political sensitivity issues like fisheries can foster the strategic trust needed for dispute-ridden countries to cooperate in other areas. Cooperation among the South China Sea neighboring countries in the fisheries sector plays a vital role in effectively addressing the serious problem of illegal, unreported, and unregulated fishing in the region and maintaining peace and stability in the South China Sea waters.

As major fishing nations in the South China Sea, China and Vietnam are critical players in the region's fishing activities. Investigating the temporal and spatial variations in fishing intensity of Chinese and Vietnamese fishing vessels holds significant value for the development and conservation of South China Sea fisheries. This paper utilizes AIS data to identify fishing activities of Chinese and Vietnamese fishing vessels and employs a gridding approach to map the fishing efforts of both countries in the South China Sea region. The study also analyzes the fishing efforts supported by Chinese and Vietnamese ports, providing novel insights for the regulation of fisheries resources in the South China Sea region.

Although the International Maritime Organization requires that all maritime vessels over 15 m must be installed with AIS equipment, due to financial and technical restrictions, there are still a large number of fishing boats in China and Vietnam that have not installed AIS equipment and some fishing boats have violations such as unauthorized disassembly, intentional shutdown of AIS equipment, or tampering with the ship identification MMSI code. As a result, the fishing effort of Chinese and Vietnamese fishing vessels calculated in this paper may be lower than the actual level. At the same time, the paper calculated fishing effort by fishing time and did not consider fishing equipment, fishing size, and other information, so it can not reflect the real fishing amount of fishing vessels. However, using fishing time to represent fishing effort can also reveal the temporal and spatial changes of fishing activities of Chinese and Vietnamese fishing vessels to a certain extent.

Although the International Maritime Organization mandates AIS installation for all seagoing vessels exceeding 15 m, financial and technological constraints have resulted in a significant number of Chinese and Vietnamese fishing vessels lacking AIS devices. Moreover, some vessels engage in unauthorized practices, such as dismantling, deliberately disabling, or tampering with AIS devices and MMSI codes (de Souza et al. 2016), leading to potential underestimation of the calculated fishing efforts of Chinese and Vietnamese vessels in this study.

Ports serve as departure and return points for fishing vessels at sea. Ideally, the fishing efforts supported by Chinese and Vietnamese ports should correspond to their respective total fishing efforts in the South China Sea region. However, certain vessels may intentionally disable their AIS devices or manipulate their MMSI codes to evade inspection when entering or leaving ports. Additionally, some fishing vessels may not have their departure or arrival locations listed in the port data used in this study, leading to an inability to aggregate their fishing efforts at specific ports. Consequently, the reported fishing efforts supported by ports may be lower than the actual levels. Strengthening AIS system inspections in port areas could help regulate the fishing industry in the South China Sea region and counter illegal fishing activities.

CONCLUSION

Since the 1970s, the fishery resources in the South China Sea have been gradually declining. The neighboring countries of the South China Sea have realized the seriousness of the problem and have taken some measures to mitigate the trend of fishery resource depletion. For example, China has implemented a fishing moratorium in the South China Sea. This paper processed AIS data from the South China Sea region in 2018 and obtained 679,553,246 trajectory records from a total of 29,146 Chinese and Vietnamese fishing vessels. The monthly variations in fishing efforts for Chinese and Vietnamese fishing vessels were analyzed, and their spatial distribution maps were plotted.

The study revealed that Vietnamese fishing vessels continued substantial fishing activities during China's fishing moratorium, and only during this period did Vietnamese fishing efforts exceed those of China. Additionally, to strengthen the management of landed catch in ports, the paper separately analyzed the fishing efforts of Chinese and Vietnamese fishing vessels supported by different ports. The results showed that the highest fishing efforts for Chinese vessels were supported by Beihai Port in China while the highest fishing efforts for Vietnamese vessels were supported by Dong Thap Port in Vietnam.

The research findings contribute to the understanding of the spatial distribution of fishing efforts by fishing vessels in the South China Sea region for the neighboring countries. They also provide valuable decision support for fishery resource monitoring and marine spatial planning.

ACKNOWLEDGMENTS

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant XDB0740300), the National Natural Science Foundation of China (grant 42006171), and the National Key Research and Development Program of China (grants 2022YFC3103105 and 2022YFC3103100). All authors contributed to the writing and editing of the paper.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

DATA AVAILABILITY STATEMENT

The port data utilized in this study are sourced from the shipping data statistics website IHS Markit (), while the AIS data are obtained from the ship information website Shipxy ().

ETHICS STATEMENT

This study strictly adhered to ethical guidelines in conducting research involving data analysis of AIS data for fishing vessels in the South China Sea. All data used in this study were obtained from publicly available sources and complied with legal and ethical standards regarding data privacy and usage. No identifiable personal information was involved in the analysis, ensuring confidentiality and compliance with ethical research practices.

References

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