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Environmental Factors, Not Biotic Competitive Interactions, Drive the Relative Abundance of Diatoms and Chlorophyta in the Coastal Areas of the Beibu Gulf: Evidence From 18S rDNA Metabarcoding and Partial Least Squares‐Path Modeling Analysis
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Environmental Factors, Not Biotic Competitive Interactions, Drive the Relative Abundance of Diatoms and Chlorophyta in the Coastal Areas of the Beibu Gulf: Evidence From 18S rDNA Metabarcoding and Partial Least Squares‐Path Modeling Analysis
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Environmental Factors, Not Biotic Competitive Interactions, Drive the Relative Abundance of Diatoms and Chlorophyta in the Coastal Areas of the Beibu Gulf: Evidence From 18S rDNA Metabarcoding and Partial Least Squares‐Path Modeling Analysis
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Journal Article
Environmental Factors, Not Biotic Competitive Interactions, Drive the Relative Abundance of Diatoms and Chlorophyta in the Coastal Areas of the Beibu Gulf: Evidence From 18S rDNA Metabarcoding and Partial Least Squares‐Path Modeling Analysis
2025
Overview
ABSTRACT
Diatoms and Chlorophyta are two major phyla of phytoplankton in marine ecosystems. The quantitative detection of the population succession and the interaction between them in natural marine ecosystems is a key challenge that ecologists face. In this study, using high‐throughput sequencing (HTS) analysis, a negative correlation was found between Diatoms and Chlorophyta near the Dafeng River Estuary (DRE) and the Sanniang Bay (SNB) located in the Beibu Gulf, China. To clarify the underlying mechanism, a co‐occurrence network was employed to scrutinize the interspecific relationships between the two phytoplankton groups, and the Mantel test was used to evaluate their relationships with environmental factors. The results indicated that the negative correlation between Diatoms and Chlorophyta was independent of interspecies interactions. Moreover, the effects of environmental factors on Diatoms and Chlorophyta were complex, being both positive and negative across seasons, and thus, they failed to explain this correlation satisfactorily. The partial least squares‐path modeling (PLS‐PM) analysis was performed using six latent variables, including seawater properties, nutrients, biomass, alpha diversity, Chlorophyta, and Diatoms. According to the results, the mechanisms behind the negative correlation between Chlorophyta and Diatoms varied across different seasons. Overall, both the differing responses of Chlorophyta and Diatoms to changes in temperature and nutrients and the complex hydrodynamic characteristics of the estuary and the bay in the study area were the main factors causing this negative correlation. This study offers a new approach to understand the succession of some phyla in phytoplankton.
Using high‐throughput sequencing (HTS) analysis, a negative correlation was found between Bacillariophyta and Chlorophyta near the Dafeng River Estuary (DRE) and the Sanniang Bay (SNB) located in the Beibu Gulf, China. The partial least squares‐path modeling (PLS‐PM) analysis showed that both the differing responses of Chlorophyta and Bacillariophyta to changes in temperature and nutrients and the complex hydrodynamic characteristics of the estuary and the bay were the main factors causing this negative correlation.
