دورية أكاديمية

Bacteria versus fungi for predicting anthropogenic pollution in subtropical coastal sediments: Assembly process and environmental response

التفاصيل البيبلوغرافية
العنوان: Bacteria versus fungi for predicting anthropogenic pollution in subtropical coastal sediments: Assembly process and environmental response
المؤلفون: Zelong Zhao, Hongjun Li, Yi Sun, Aibin Zhan, Wenlu Lan, Sau Pinn Woo, Aileen Tan Shau-Hwai, Jingfeng Fan
المصدر: Ecological Indicators, Vol 134, Iss , Pp 108484- (2022)
بيانات النشر: Elsevier, 2022.
سنة النشر: 2022
المجموعة: LCC:Ecology
مصطلحات موضوعية: Biomonitoring, Coastal ecosystem, Community assembly, Metacommunity, Random forest analysis, Ecology, QH540-549.5
الوصف: Coastal regions support the most threatened ecosystems on Earth, and anthropogenic activities have been significantly affecting both habitat structure and ecological quality. Understanding the dynamics of ecological response to multiple stresses is a precondition for management and restoration of largely disturbed coastal ecosystems. Among diverse taxa in coastal regions, benthic organisms are widely recognized as promising targets for assessing ecological causes and consequences of anthropogenic activity-derived stressors, such as environmental pollution. However, spatial and local environmental factors play important but different roles in shaping community structure of different benthic taxa, mainly owing to their distinct body size, mobility, and metabolic capacity. Here, we applied metabarcoding, coupled with physicochemical analyses, to determine the benthic microbial community composition in a typical subtropical coast area, Beibu Gulf in Southern China. Stochastic processes were found as the dominant ecological driver in shaping the community assembly of both bacteria and fungi. Moreover, environmental factors explained a considerable portion of variation in bacterial communities, while spatial factors were more influential in structuring larger body size and weak mobility fungal communities. Mantel tests and network analysis revealed significant relationships between several environmental variables and bacterial communities. More importantly, the concentrations of heavy metals, particularly Cr and Zn, could be predicted using the constructed random forest model based on bacterial communities. The results obtained here provide new insights into causes and consequences of various factors for influencing healthy coasts, thus further clearing the road to the integration of biological information into routine ecological monitoring of coastal ecosystems.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1470-160X
Relation: http://www.sciencedirect.com/science/article/pii/S1470160X21011493; https://doaj.org/toc/1470-160X
DOI: 10.1016/j.ecolind.2021.108484
URL الوصول: https://doaj.org/article/5cf09eda47924cfc9d38b7137a02f256
رقم الأكسشن: edsdoj.5cf09eda47924cfc9d38b7137a02f256
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1470160X
DOI:10.1016/j.ecolind.2021.108484