Long-term variations in fish community structure under multiple stressors in a semi-closed marine ecosystem in the South China Sea

Zhang, Kui; Guo, Jianzhong; Xu, Yongfu; Jiang, Yane; Fan, Jiangtao; Xu, Shimei; Chen, Zuozhi

doi:10.1016/j.scitotenv.2020.140892

Cited by 32 publications

(22 citation statements)

References 44 publications

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“…We reported that the dominant species on Meiji and Zhubi reefs belonged to the families Serranidae, Lutjanidae, Pentapodidae, Lethrinidae, Mullidae, and Scaridae, which is generally consistent with the types of dominant taxa found in coral reef habitats around the Nansha Islands [70]. However, the number of dominant species on Meiji Reef was lower than reported by [71], possibly because of differences in methods, duration and survey effort; Li et al [15] did not report representatives of either the Labridae (which play an important role in maintaining reef stability) or Pomacentridae (which indicate living coral cover) on Zhubi Reef. Being a closed atoll, Zhubi Reef is more susceptible to deterioration, decline of coral cover, and habitat destruction.…”

Section: Dominant Speciessupporting

confidence: 75%

“…As a closed atoll, Zhubi Reef is vulnerable to environmental change and anthropogenic disturbance [16], its ecosystem is fragile, and it warrants protection. Zhang [71] and Chen et al [39] reported fish assemblage H values at Meiji Reef of 3.58 and 0.92, while we reported a higher value of 4.37. It has been suggested that a proportion of both non-seasonal and seasonal resident fish occurs at Meiji Reef, and H values are also associated with a large number of seasonal and incidental species [29,71].…”

Section: Coral Reef Fish Diversitycontrasting

confidence: 70%

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Fish Composition and Diversity of Four Coral Reefs in the South China Sea Based on Hand-Line Catch

Chen

Zhang

2021

JMSE

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To improve the overall understanding of the fish diversity and spatial patterns of major coral reefs in the South China Sea, fish assemblage composition, dominant species, biodiversity indices, and multivariate analysis of community structure were reported for four major coral reefs based on hand-line survey data in May and September 2018. A total of five orders, 21 families, 45 genera and 121 species of fish were recorded with Perciformes (78.5%) being the most diverse. The highest number (5) of dominant species was found near Chenhang Island while the lowest (2) number was detected at Zhubi Reef. The highest abundance index (7.21) occurred at Zhubi Reef, while the Shannon–Wiener diversity (4.80), Pielou’s evenness (0.81), and Simpson’s dominance (0.95) indexes were all highest at Qiliangyu Island. Based on cluster analysis and non-metric multi-dimensional scaling (NMDS), fish communities varied more spatially than seasonally. Our results led us to hypothesize that the habitat complexity and level of anthropogenic disturbance were the main factors affecting the composition of reef-dwelling fish on each coral reef. Topography was likely responsible for most variation in the spatial pattern of fish diversity.

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Section: Dominant Speciessupporting

confidence: 75%

Section: Coral Reef Fish Diversitycontrasting

confidence: 70%

Fish Composition and Diversity of Four Coral Reefs in the South China Sea Based on Hand-Line Catch

Chen

Zhang

2021

JMSE

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“…The South China Sea (SCS) has the highest diversity of marine species in China, and it provides a rich fishery resource. Because the SCS is a semienclosed environment, replenishment of the biological resources in the northern SCS from other marine areas is limited and the quantity of resources depends largely on the region's internal primary productivity [1]. Owing to factors such as overfishing and destruction of the ecological environment, offshore fishery resources in the northern SCS are in serious decline.…”

Section: Introductionmentioning

confidence: 99%

Identification of Fishing Vessel Types and Analysis of Seasonal Activities in the Northern South China Sea Based on AIS Data: A Case Study of 2018

Guan

Zhang

et al. 2021

Remote Sensing

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In recent years, concern has increased about the depletion of marine resources caused by the overexploitation of fisheries and the degradation of ecosystems. The Automatic Identification System (AIS) is a powerful tool increasingly used for monitoring marine fishing activity. In this paper, identification of the type of fishing vessel (trawlers, gillnetters and seiners) was carried out using 150 million AIS tracking points in April, June and September 2018 in the northern South China Sea (SCS). The vessels’ spatial and temporal distribution, duration of fishing time and other activity patterns were analyzed in different seasons. An identification model for fishing vessel types was developed using a Light Gradient Boosting Machine (LightGBM) approach with three categories with a total of 60 features: speed and heading, location changes, and speed and displacement in multiple states. The accuracy of this model reached 95.68%, which was higher than other advanced algorithms such as XGBoost. It was found that the activity hotspots of Chinese fishing vessels, especially trawlers, showed a tendency to move northward through the year in the northern SCS. Furthermore, Chinese fishing vessels showed low fishing intensity during the fishing moratorium months and traditional Chinese holidays. This research work indicates the value of AIS data in providing decision-making assistance for the development of fishery resources and marine safety management in the northern SCS.

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“…Against this backdrop, a series of fishery studies has been made using various analysis such as fishing stock assessments, fishing-related habitat analysis and spatio-temporal analysis of fishing resources [9][10][11][12][13][14][15][16][17][18][19][20]. However, most studies in the SCS preferred an analysis of the small-scale fisheries at a single or inconsistent time [4,6,[21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39] and few attempts have been made to investigate large-scale fishery dynamics and access their regularity. Lacking large-scale consistent time-series fishery data is a main reason for this scarcity.…”

Section: Introductionmentioning

confidence: 99%

Satellite Observation of the Marine Light-Fishing and Its Dynamics in the South China Sea

Liu

Sun

et al. 2021

JMSE

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The South China Sea (SCS) is one of the most important fishery resource bases in the world. Marine fisheries, as a crucial component of regional food security and national revenue, raise wide concern about marine ecology, social-economic and political consequences at regional, national and local scales. The large-scale dynamic detection and analysis of fishing activity in the SCS is still unclear because of the accessibility of in-site data, finite automatic identification system (AIS) usage, complex geopolitics and poor additional data coverage. Nighttime light imagery (NTL) derived from low light imaging sensors and the popularity of light fishing in the SCS offers a unique way to unveil fishing activities and its dynamics. In this study, we proposed a set of algorithms for automatic detection of nighttime fishing activity and provided the first large-scale dynamic analysis of nighttime fishing activity in the SCS using monthly Visible Infrared Imaging Radiometer Suite (VIIRS) images between 2012 and 2019. The proposed method effectively minimized the spatio-temporal fluctuations in radiance values of background and their implications to ship detection by integrating high radiance gradient detection and local adaptive thresholding. Further, nighttime fishing activity trajectories were decomposed into trend and seasonal components by using Hilbert-Huang transformation (HHT) to accurately access general trends and the seasonality of nighttime fishing activity in the SCS. The typical subregions analysis, environmental driver analysis, correlation coefficient analysis and hot spot analysis were integrated to characterize the nighttime fishing activity. It appears that the nighttime fishing activity in the SCS exhibited spatio-temporal variability and heterogeneity and was shaped by policy and natural factors such as holidays, annual Chinese fishery moratoria in the Chinese Exclusive Economic Zone (EEZ) and seasonal tropical storm activity.

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Long-term variations in fish community structure under multiple stressors in a semi-closed marine ecosystem in the South China Sea

Cited by 32 publications

References 44 publications

Fish Composition and Diversity of Four Coral Reefs in the South China Sea Based on Hand-Line Catch

Fish Composition and Diversity of Four Coral Reefs in the South China Sea Based on Hand-Line Catch

Identification of Fishing Vessel Types and Analysis of Seasonal Activities in the Northern South China Sea Based on AIS Data: A Case Study of 2018

Satellite Observation of the Marine Light-Fishing and Its Dynamics in the South China Sea

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