Global study maps how bacterial communities shape the health of lakes and reservoirs

Their findings show that sediments contain consistently higher and more variable bacterial diversity than surface waters, while global patterns are strongly shaped by temperature, nutrient levels, and latitude. By establishing a standardized worldwide microbial database, the team identifies key bacterial groups—such as Proteobacteria, Cyanobacteria, and Actinobacteria—that indicate ecological conditions and nutrient status.

Lakes and reservoirs provide drinking water, support biodiversity, and sustain agriculture and industry, yet face mounting stress from pollution, nutrient enrichment, and climate-driven hydrological changes. Microorganisms play central roles in these ecosystems by regulating carbon, nitrogen, and phosphorus cycling, underpinning food webs, and maintaining resilience against disturbances. Because microbial communities respond sensitively to temperature, oxygen, pH, and nutrient dynamics, shifts in bacterial composition act as early-warning signals of eutrophication or ecological degradation. Despite growing interest, global comparisons linking microbial biogeography to environmental gradients in both water and sediment habitats have remained limited. Addressing this knowledge gap is essential for building predictive models of ecosystem change.

A study (DOI:10.48130/biocontam-0025-0003) published in Biocontaminant on 31 October 2025 by Haihan Zhang’s team, Xi'an University of Architecture and Technology, offers new scientific foundations for microbial-based water-quality monitoring and sustainable freshwater ecosystem management.

In this study, the researchers synthesized 379 publicly available amplicon-sequencing datasets from water and sediment samples and applied a suite of analytical methods—including continental grouping, latitude-based gradients, diversity indices, Spearman correlations, Generalized Additive Models (GAM), Structural Equation Modeling (SEM), Random Forest analysis, redundancy analysis (RDA), and ecological network construction—to investigate global patterns in bacterial biogeography. This integrative methodological framework enabled the team to overcome uneven sampling across continents, capture nonlinear environmental responses, identify key predictors of community structure, and compare interaction networks between habitats. The resulting analyses revealed that although the dataset covers six continents, more than 60% of samples originated from Asia, creating a geographical imbalance that was mitigated by regional grouping and incorporation of latitude. Diversity assessments showed consistently higher Shannon and Chao1 indices in sediments than in water, with sediment samples—especially those from Asia—displaying far greater richness and variability. GAM and SEM analyses uncovered strong nonlinear environmental effects: in water, bacterial richness peaked around 7 mg/L dissolved oxygen and declined sharply above 25 °C, while diversity decreased steeply at latitudes above 60°. Nutrient effects differed between habitats, with total nitrogen and nitrate enhancing diversity in sediments but suppressing it in water. Taxonomic analyses identified Proteobacteria as globally dominant, while Cyanobacteria and Actinobacteria proliferated in eutrophic waters; other phyla exhibited distinct habitat-specific preferences. Random forest models highlighted temperature as the leading driver of water-column community structure, whereas nitrate nitrogen was most influential in sediments. RDA further confirmed strong environmental shaping of water communities, while sediment communities exhibited more moderate associations. Network analyses showed striking habitat contrasts: water communities formed dense, highly connected networks indicative of rapid interactions and dynamic environmental fluctuations, whereas sediment networks were sparser and more modular, reflecting niche specialization and geochemical filtering. Collectively, these results demonstrate that habitat type, environmental gradients, and regional context jointly regulate bacterial diversity, composition, and ecological interactions across global lakes and reservoirs.

These global biogeographic insights strengthen the scientific basis for microbial indicators in freshwater monitoring. Identifying core bacterial groups associated with nutrient levels, temperature, and geographic position provides powerful tools for early detection of eutrophication, pollution events, and ecological recovery. The global database and statistical models developed in this study offer practical guidance for water-resource managers aiming to predict ecosystem responses to nutrient loading, climate warming, and land-use change.

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References

DOI

10.48130/biocontam-0025-0003

Original Source URL

https://doi.org/10.48130/biocontam-0025-0003

Funding information

This study was funded by the Shaanxi Outstanding Youth Science Foundation Project (Grant No. 2025JC-JCQN-019), supported by the Postdoctoral Fellowship Program of CPSF (Grant No. GZC20250855), and the National Natural Science Foundation of China (Grant Nos 52270168, 52570213, and 52500012).

About Biocontaminant

Biocontaminant is a multidisciplinary platform dedicated to advancing fundamental and applied research on biological contaminants across diverse environments and systems. The journal serves as an innovative, efficient, and professional forum for global researchers to disseminate findings in this rapidly evolving field.