Time after time: detecting annual patterns in stream bacterial biofilm communities

Abstract

Summary To quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rRNA bacterial gene sequencing of 892 stream biofilm samples, collected monthly for 36‐months from six streams. The streams were located a maximum of 118 km apart and drained three different catchment types (forest, urban and rural land uses). We identified repeatable seasonal patterns among bacterial taxa, allowing their separation into three ecological groupings, those following linear, bloom/trough and repeated, seasonal trends. Various physicochemical parameters (light, water and air temperature, pH, dissolved oxygen, nutrients) were linked to temporal community changes. Our models indicate that bloom events and seasonal episodes modify biofilm bacterial populations, suggesting that distinct microbial taxa thrive during these events including non‐cyanobacterial community members. These models could aid in determining how temporal environmental changes affect community assembly and guide the selection of appropriate statistical models to capture future community responses to environmental change.

Toward a Predictive Understanding of Cyanobacterial Harmful Algal Blooms through AI Integration of Physical, Chemical, and Biological Data

“…Moreover, cyanobacteria are known to form symbiotic relationships with higher organisms and other bacteria in their marine ecosystems . In addition, local environmental conditions may drive differences in bacterial community composition in freshwater ecosystems. , Increased knowledge about community composition at cyanoHAB sites may provide insight into the identification of sentinel species that may help predict cyanoHAB formation, toxicity, or other dynamics.…”

“…45 In addition, local environmental conditions may drive differences in bacterial community composition in freshwater ecosystems. 21,46 Increased knowledge about community composition at cyanoHAB sites may provide insight into the identification of sentinel species that may help predict cyanoHAB formation, toxicity, or other dynamics. Therefore, while axenic cultures have long been considered the standard for research, it has become evident that a holistic approach is necessary to model and characterize the HAB dynamics found in both natural and laboratory settings.…”

Temporal disturbance of a model stream ecosystem by high microbial diversity from treated wastewater

“…Although microbial activity has been considered important for ecosystem integrity (Cotner & Biddanda, 2002; Fasching et al, 2020), most studies have not considered microbial communities when studying the biome of streams (Gautam et al, 2022; Zeglin, 2015). Typically, experiments on stressor effects in streams have focused solely on higher organisms such as fish or invertebrates (Kim et al, 2020; Wright & Ryan, 2016), thus neglecting a major part of biodiversity, that is, prokaryotes and viruses.…”

“…Although microbial activity has been considered important for ecosystem integrity (Cotner & Biddanda, 2002;Fasching et al, 2020), most studies have not considered microbial communities when studying the biome of streams (Gautam et al, 2022;Zeglin, 2015).…”

Spatial scale impacts microbial community composition and distribution within and across stream ecosystems in North and Central America

“…At large scales where aquatic ecosystems are not connected through surface freshwater, streams in separate catchments differ in many factors. Interactions between abiotic (e.g., dissolved organic matter [Judd et al, 2006], inorganic nutrients [Rubin & Leff, 2007], pH [Fierer et al, 2007], temperature [Shiah & Ducklow, 1997], redox potential [Zeng et al, 2008], seasonality [Sutton & Findlay, 2003, Santmire & Leff, 2006, Gautam et al, 2022]) and biotic (e.g., competition [Hibbing et al, 2010], predation [Thelaus et al, 2008], and viral infection [Bouvier & del Giorgio, 2007]) factors determine microbial abundance and distribution. Partially through species sorting, local habitat variations can influence community composition.…”