Accurately modeling the distribution of keystone species is of utmost importance to gain a comprehensive understanding of their complex ecological dynamics and to develop effective strategies for sustainable scientific management. In the coastal China ecosystem, the swordtip squid (Uroteuthis edulis) stands out as a keystone species with significant commercial and ecological value. Despite its importance, research on the ecological dynamics of this species remains limited and requires further investigation. To investigate the spatial and temporal variability in the distribution of U. edulis and identify the key environmental drivers in the East China Sea (ECS) and southern Yellow Sea across different seasons, we generated ensemble models using oceanographic variables and fishery-independent scientific survey data collected from 2016 to 2018. Our results revealed that U. edulis predominantly inhabited the central and southern regions of the ECS throughout the year. The primary environmental variables driving its distribution varied by season, with the sea surface temperature being the most important in spring, sea surface height in summer and autumn, and depth in winter. During summer and autumn, the suitable habitats of U. edulis were found to be largest and extended northwards towards the coastline. However, they migrated southwards to the waters near the edge of the ECS continental shelf with smaller suitable areas in the spring and winter. These results suggested that U. edulis exhibited season-specific habitat preferences and responded to changing environmental conditions throughout the year. The observed seasonal distribution patterns were likely influenced by the fluctuating mixture of waters (ocean currents) from different sources, with varying physical and chemical characteristics throughout the year. Our study provides baseline data for comprehending the population dynamics of U. edulis and highlights the significance of considering species’ habitat preferences in a dynamic environment.

Nursery habitats play a significant role in completing fish life cycles, and they are now recognized as essential habitats. Monthly variations in nursery ground distributions of Larimichthys polyactis were investigated in the southern Yellow Sea in 2019. Bayesian hierarchical models with integrated nested Laplace approximation were utilized to model the preferential nursery habitats of L. polyactis larvae. The study analyzed the spatial and temporal distributions of the larvae and juveniles based on three environmental variables: sea surface temperature, sea surface salinity, and depth. Additionally, this study examined the utilization of habitats by different fish life stages and ontogenetic shifts. A total of 3240 individuals were collected from April to June, with the peak occurring in May (0.05 ind./m³), and the distribution areas varied between different months. The prediction of the model reveals the ecological adaptability of L. polyactis to temperature variations. The optimal temperature for L. polyactis density ranges from 12.5 °C to 16.5 °C in April and 16.5 °C to 17.5 °C in May, demonstrating a broad temperature tolerance for L. polyactis survival. In addition, there are variations in distribution patterns among different developmental stages. Larimichthys polyactis spawn in the inshore and nearshore waters, and after hatching, larvae in the pre-flexion stage tend to remain aggregated near the spawning beds. However, larvae in the advanced development stage (post-flexion) and juveniles move towards the sandy ridge habitats along the coast and start to migrate offshore in June. This study provides valuable insights for the effective management of fishery resources in the area and can be utilized to identify marine areas with specific habitat features that require conservation.

Shark bycatch represents a substantial issue in the management of oceanic fisheries. Utilizing data on shark bycatch from the longline fishery, as released by the Western and Central Pacific Fisheries Commission, this study applied the boosted regression tree model to examine the impact of environmental factors on the bycatch per unit effort (BPUE) of key bycatch species, as well as to predict the spatial distribution dynamics of both BPUE and bycatch risk (BR). The findings emphasize that the oxygen concentration, sea surface temperature, and chlorophyll-a concentration are paramount to sharks’ BPUE. Furthermore, the study compared the variations in environmental preferences across diverse shark species, pinpointing key environmental attributes defining the ecological niches of distinct shark populations. The spatial predictions identified the hotspots of BPUE and BR for the bigeye thresher shark (Alopias superciliosus), longfin mako (Isurus paucus), silky shark (Carcharhinus falciformis), and oceanic whitetip shark (Carcharhinus longimanus) in tropical latitudes (10° S to 15° N), and for the blue shark (Prionace glauca) and shortfin mako (Isurus oxyrinchus) in temperate zones (south of 30° S or north of 30° N). The geometric center analysis indicated that all shark species exhibited large annual fluctuations in BPUE and BR, and most populations displayed significant shifting trends. Several grids (5° × 5°) were identified as high-risk areas due to their considerable contribution to bycatch. Furthermore, the geometric centers of BR were observed to shift eastward towards equatorial waters, compared to the geometric centers of BPUE. This underscores the necessity of considering factors beyond BPUE when identifying critical areas for the implementation of area-specific bycatch mitigation measures. The insights derived from this study can enhance and support the development and enforcement of targeted area-based fishery management initiatives.

Small-sized fish are a vital food source for large predatory commercial fish and play a key role in marine food webs, bridging lower and higher trophic levels. They are indispensable in maintaining the energy flow and material cycling within aquatic ecosystems. This study utilized bottom-trawl survey data from 2017 to 2020 along the south inshore of Zhejiang, China, complemented by concurrent environmental data, to examine the influence of environmental factors on the resource density and seasonal distribution patterns of four dominant small-sized fish species. The research findings indicated that SSH (sea surface height) and Chl (chlorophyll-a concentration) emerged as the key environmental factors influencing resource densities, with all four species exhibiting similar preferences toward these variables. However, significant disparities were observed in their preferences for SST (sea surface temperature), SSS (sea surface salinity), and DO (dissolved oxygen). The various species’ resource density and distribution patterns underwent significant seasonal variations. Additionally, the seasons and regions with the highest resource densities consistently aligned, occurring predominantly in autumn within the northern waters of the study area. This research further elucidated the environmental predilections and seasonal spatial distribution traits of small-sized fish in the south inshore of Zhejiang, an important feeding ground for economic fish species in the East China Sea. This provides scientific backing for forecasting alterations in coastal fishery resources under environmental and climate change scenarios and supports ecosystem-based fisheries management strategies.

Understanding the distribution pattern and its drivers of species is crucial for developing effective and sustainable management strategies. Amphioctopus fangsiao is the octopus of significant commercial and ecological value along the coast of China, with multiple distinct populations. However, research on their ecological dynamics remains limited and requires further investigation. Here, ensemble models were constructed to examine the spatio-temporal distribution and inter-populational differentiation in environmental adaptability of A. fangsiao in the East China Sea (ECS) and the South Yellow Sea (SYS). Specifically, we generated the ensemble models by integrating Gradient Boosting Machine (GBM), Generalized Linear Models (GLMs), and Maximum Entropy Models (MaxEnt) for the different populations across four seasons, using fishery-independent data collected from 2015 to 2021. The results revealed two hotspots of A. fangsiao in the ECS and SYS: one is the area of SYS along the coastal waters, with latitudes 33° N–34° N and longitudes 120° E–122° E (northern population, NP); the other one is near the Kuroshio-adjacent area with latitudes 28.5° N–29° N and longitudes 123° E–124.5° E (southern population, SP). Both NP and SP exhibited distinct seasonal habitat preferences, with key environmental drivers showing seasonal variations. The NP tended to inhabit coastal waters with lower sea surface heights (SSHs), shallower water depth, and a narrower sea bottom salinity range (SBS). In contrast, SP preferred marine environments with a thicker mixed layer thickness (MLT) and higher concentrations of bottom chlorophyll-a (Chl_b). The environmental characterization of suitable habitats revealed distinct patterns in resource utilization and environmental adaptation strategies between the two populations. This study provides fundamental data for understanding A. fangsiao population dynamics and underscores the importance of considering population-specific habitat preferences within dynamic marine environments.