The impact of flooding from the Minjiang River on the succession of harmful algal blooms (HABs) caused by diatoms in China's offshore waters.

This study examines diatom assemblages in the Matsu Archipelago, an area influenced by Minjiang River runoff. It focuses on harmful algal blooms (HABs) that occurred between August 2021 and July 2022. Utilizing 18S rRNA metabarcoding and microscopic analysis, we observed a significant diatom bloom during early summer runoff, peaking at 5 × 105 cells L-1. The research reveals dynamic community changes during the runoff season, with dominant genera including Pseudo-nitzschia, Chaetoceros, and Skeletonema. Skeletonema cell density correlated with NO3 levels, Chaetoceros had a slight PO4 affinity, and Pseudo-nitzschia showed a negative correlation with Skeletonema. Pseudo-nitzschia, which prefers high light and pH conditions, had notably high concentrations in the flood season and in the autumn. In both, it was dominated by potential toxin-producing species - P. multistriata and P. pungens during the flooding, and P. cuspidate in the autumn. These findings highlight the intricate relationship between diatom dynamics and environmental factors, providing essential insights for managing HABs, especially Pseudo-nitzschia species, amidst environmental changes.

How Communities of Marine Stramenopiles Varied with Environmental and Biological Variables in the Subtropical Northwestern Pacific Ocean.

MArine STramenopiles (MASTs) have been recognized as parts of heterotrophic protists and contribute substantially to protist abundances in the ocean. However, little is known about their spatiotemporal variations with respect to environmental and biological factors. The objectives of this study are to use canonical correspondence analysis to investigate how MASTs communities are shaped by environmental variables, and co-occurrence networks to examine their potential interactions with prokaryotic communities. Our dataset came from the southern East China Sea (sECS) in the subtropical northwestern Pacific, and involved 14 cruises along a coastal-oceanic transect, each of which sampled surface water from 4 to 7 stations. MASTs communities were revealed by metabarcoding of 18S rDNA V4 region. Most notably, MAST-9 had a high representation in warm waters in terms of read number and diversity. Subclades of MAST-9C and -9D showed slightly different niches, with MAST-9D dominating in more coastal waters where concentrations of nitrite and Synechococcus were higher. MAST-1C was a common component of colder water during spring. Overall, canonical correspondence analysis showed that MASTs communities were significantly influenced by temperature, nitrite and Synechococcus concentrations. The co-occurrence networks showed that certain other minor prokaryotic taxa can influence MAST communities. This study provides insight into how MASTs communities varied with environmental and biological variables.

Estimating Finite Rate of Population Increase for Sharks Based on Vital Parameters.

The vital parameter data for 62 stocks, covering 38 species, collected from the literature, including parameters of age, growth, and reproduction, were log-transformed and analyzed using multivariate analyses. Three groups were identified and empirical equations were developed for each to describe the relationships between the predicted finite rates of population increase (λ') and the vital parameters, maximum age (Tmax), age at maturity (Tm), annual fecundity (f/Rc)), size at birth (Lb), size at maturity (Lm), and asymptotic length (L∞). Group (1) included species with slow growth rates (0.034 yr(-1) < k < 0.103 yr(-1)) and extended longevity (26 yr < Tmax < 81 yr), e.g., shortfin mako Isurus oxyrinchus, dusky shark Carcharhinus obscurus, etc.; Group (2) included species with fast growth rates (0.103 yr(-1) < k < 0.358 yr(-1)) and short longevity (9 yr < Tmax < 26 yr), e.g., starspotted smoothhound Mustelus manazo, gray smoothhound M. californicus, etc.; Group (3) included late maturing species (Lm/L∞ ≧ 0.75) with moderate longevity (Tmax < 29 yr), e.g., pelagic thresher Alopias pelagicus, sevengill shark Notorynchus cepedianus. The empirical equation for all data pooled was also developed. The λ' values estimated by these empirical equations showed good agreement with those calculated using conventional demographic analysis. The predictability was further validated by an independent data set of three species. The empirical equations developed in this study not only reduce the uncertainties in estimation but also account for the difference in life history among groups. This method therefore provides an efficient and effective approach to the implementation of precautionary shark management measures.