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Updated: Jan 9, 2026

Use of a Filter Cartridge for Filtration of Water Samples and Extraction of Environmental DNA
Published on: November 25, 2016
Environmental DNA-based tracking and mapping reveal process-driven seasonal dynamics in fish diversity and community
Songsong Gu1, Xiongfeng Du2, Jie Su3
1State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; CAS Key Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
None:
Freshwater ecosystems harbor exceptional biodiversity and are highly threatened, making understanding their response to seasonal changes and urbanization pressures vital for conservation. Here, we investigated the spatiotemporal dynamics of fish assemblages across the Basin of Xuzhou city, a typical dense river networks with intense human interference and complex hydrological conditions, using multi-season environmental DNA (eDNA) surveys. Our findings revealed strong seasonal restructuring of taxonomic and structure, with peak richness, niche breadth, and network robustness observed in summer, while communities in spring and autumn exhibited increased filtering and structural fragility. Species turnover, rather than nestedness, dominated temporal β-diversity, indicating compositional replacement across seasons. Ecological niche expansion was positively linked to water temperature (WT) and river width but negatively affected by eutrophication markers (i.e., total phosphorus and chlorophyll-a). Neutral and phylogenetic modeling highlighted dispersal limitation as the prevailing assembly process, modulated seasonally by deterministic environmental filtering. Network analysis revealed dynamic shifts in complexity and cohesion, with spring and autumn seasons marked by higher modularity and vulnerability. Collectively, our results demonstrate that urbanizing watersheds act as temporally dynamic mosaics of biodiversity, shaped by the interplay between stochasticity, environmental gradients, and network architecture. These findings underscore the importance of multi-temporal monitoring in assessing aquatic ecosystem resistance and designing effective conservation strategies.
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