Response of phytoplankton community structure to environmental changes in the coastal areas of northern China

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3-N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

Unveiling the evolution of phytoplankton communities: Decades-long insights into the southern Yellow Sea, China (1959-2023)

We obtained historical and observational data on phytoplankton communities from 1959 to 2023 to explore the responses of the phytoplankton community structure to long-term environmental changes in the southern Yellow Sea (SYS), China. The results revealed a decrease in the proportions of diatom cell abundance within the phytoplankton community by 8 %, accompanied by a corresponding increase in that of dinoflagellates. Dominant phytoplankton species were mainly chain-forming diatoms before 2000, and large dinoflagellate species from the genera Tripos and Noctiluca increased their dominance after 2000. Warm-water phytoplankton species have increased in dominance over the study period. Correlation analysis revealed that the ocean warming and alterations in nutrient structure (N/P and Si/N ratios) were mostly responsible for the long-term evolution trend, and these changes may result in an increase in dinoflagellate harmful algal blooms, reduced efficiency of the biological carbon pump, and heightened hypoxia in the future, which should draw our attention.

Seasonal and spatial variations of Synechococcus in abundance, pigment types, and genetic diversity in a temperate semi-enclosed bay

Synechococcus is abundant and globally widespread in various marine environments. Seasonal and spatial variations in Synechococcus abundance, pigment types, and genetic diversity were investigated based on flow cytometric analysis and high-throughput sequencing of cpcBA operon (encoding phycocyanin) and rpoC1 gene (encoding RNA polymerase) in a temperate semi-enclosed bay. Synechococcus abundance exhibited seasonal variations with the highest value in summer and the lowest value in winter, which was consistent with temperature variation. Three pigment types of Synechococcus type 1, type 2, and type 3 were distinguished based on cpcBA operon, which displayed obvious variations spatially between the inner and the outer bay. Freshwater discharge and water turbidity played important roles in regulating Synechococcus pigment types. Synechococcus assemblages were phylogenetically diverse (12 different lineages) based on rpoC1 gene and dominated by three core lineages S5.1-I, S5.1-IX, and S5.2-CB5 in different seasons. Our study demonstrated that Synechococcus abundance, pigment types, and genetic diversity displayed variations seasonally and spatially by different techniques, which were mainly driven by temperature, salinity, nutrients, and turbidity. The combination of more technical means provides more information for studying Synechococcus distribution. In this study, three pigment types of Synechococcus were discriminated simultaneously by dual lasers flow cytometer for the first time.