Jianfeng Tong

The Japanese sardine (Sardinops melanostictus) is a key species in the North Pacific Ocean, providing ecological support for regional fisheries. The conservation of its stock requires accurate and sustainable population monitoring. Conventional biomass estimation methods are inadequate for addressing the challenges posed by increasingly large datasets, resulting in high variance as the scope of the study area expands. This situation highlights the need for K-means model analysis of trawl data as a basis for stratification in biomass estimation, considering its ability to capture complex data structures and utilize geostatistics to spatially predict biological biomass values. The results of the study show that this framework, with a K-means validation value of 0.78 and estimates sardine biomass at approximately 22.7–67.3 ton. The shift in biomass distribution from the southeast to the northwest reflects the active migration patterns of sardines. Annual validation using the Ordinary Kriging method yielded a root mean square error of 6.84 in 2022 and 19.27 in 2023, while the Kriging with External Drift method, which included temperature as a covariate, yielded a root mean square error of 11.77 in 2024. Both the Ordinary Kriging and Kriging with External Drift models were deemed suitable for describing biomass distribution. This study provides a scientific basis for statistical and spatial estimates of sardine biomass in the North Pacific region.

The sound scattering layer (SSL) plays an important role in maintaining the structure and functioning of marine ecosystems. The spatiotemporal distribution of the SSL largely reflects the distribution of pelagic communities within the water column. Although acoustic data are widely used to investigate the distribution of communities within SSLs, a systematic framework for analyzing underlying environmental mechanisms remains limited. To address this, this study developed a model using SSL descriptors. SSL descriptors provide a new perspective for investigating community distributions in large marine ecosystems by capturing spatiotemporal variability in the structure and functioning of pelagic communities. We characterized the SSL using a suite of SSL descriptors. Descriptors indicative of community biomass then were used to fit generalized additive models. We applied this approach to an acoustic dataset collected in the Northwest Pacific Ocean during 2022–2024 to assess pelagic community distribution patterns and the key environmental drivers. This SSL descriptor‐based modeling framework provides an innovative and robust approach for analyzing relationships between marine environmental variables and pelagic community distributions. Our results indicated that SSL descriptors are effective for monitoring and analyzing large‐scale aggregations of pelagic communities. They support standardized monitoring of pelagic ecosystems and have high practical value in regions where species identification is difficult due to a lack of net sampling. This study provides a reference for further applications of SSL descriptors.

Underwater acoustic technologies have emerged as indispensable tools for advancing research, management, and conservation across aquatic ecosystems

Aim: The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean).Location: Worldwide, 12,343 sites, all ecosystem types.Time Period: 1991 to present.Major Taxa Studied: All soniferous taxa.Methods: We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms.Results: Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm²) than aquatic sampling (0.3 and 1.8 sites/Mkm² in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds.Main Conclusions: PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio‐temporal replication in freshwater habitats. Overall, this worldwide PAM network holds promise to support cross‐realm biodiversity research and monitoring efforts.

With the rise of underwater unmanned platforms like unmanned boats, ROVs, and AUVs, there’s an increasing need for underwater detection technologies. Researchers have merged scientific echosounders with these platforms for biometric applications. However, current detection models are too parameter-heavy to embed in echosounders and struggle with noisy, irregular, and dense echograms. This paper introduces YOLOv8-SBE, a lightweight fish detection model based on YOLOv8, addressing these issues by enhancing feature extraction, information fusion, and small object recognition. YOLOv8-SBE adds the C2f_ScConv module to improve efficiency and reduce parameters, incorporates the BiFPN structure to enhance information transfer, and uses the EMA attention module for better small target recognition. It reduces computational complexity by 18.5%, decreases model parameters by 40%, and improves mAP_0.5 to 79.5% and mAP_0.5:0.95 to 58.2%, making it suitable for echosounders with limited resources.

Target strength (TS) is an acoustic property of individual marine organisms and a critical factor in acoustic resource assessments. However, previous studies have primarily focused on measuring TS at narrowband, typical frequencies, which cannot meet the requirements of broadband acoustic technology research. Additionally, for marine fish, conducting in situ TS measurements is challenging due to environmental constraints. Rapidly freezing and preserving fish samples for transfer to the laboratory is a common method currently used. However, the impact of freezing preservation during transportation on the swimbladder morphology and TS of swimbladder-bearing fish remains unclear. This study investigated the differences in swimbladder morphology and TS of Chub mackerel (Scomber japonicus) before and after freezing. Then, we compared different TS measurement methods through ex situ TS measurements (45–90 kHz, 160–260 kHz) and the Kirchhoff-ray mode model (KRM) simulations (1–300 kHz) and studied the broadband scattering characteristics of Chub mackerel based on the KRM model. The results showed that the morphology of the swimbladder was reduced after freezing, with significant changes in swimbladder height and volume. However, the trends of TS were not consistent and the changes were small. The difference between the KRM model and ex situ measurements was −0.38 ± 1.84 dB, indicating good applicability of the KRM. Based on the KRM results, the TS exhibited significant directivity, with fluctuations gradually decreasing and stabilizing as frequency increased. In the broadband mode, the relationship between TS and body length (L) of Chub mackerel was TS = 20log(L) − 66.76 (30 > L/λ >10). This study could provide a reference for acoustic resource estimation and species identification of Chub mackerel in the Northwest Pacific Ocean.