A functional microbiome catalogue crowdsourced from North American rivers.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb).

A functional microbiome catalog crowdsourced from North American rivers.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb).

The interaction of physical structure and nutrient loading drives ecosystem change in a large tropical lake over 40 years.

Many lakes across the world are entering novel states and experiencing altered biogeochemical cycling due to local anthropogenic stressors. In the tropics, understanding the drivers of these changes can be difficult due to a lack of documented historic conditions or an absence of continuous monitoring that can distinguish between intra- and inter-annual variation. Over the last forty years (1980-2020), Lake Yojoa (Honduras) has experienced increased watershed development as well as the introduction of a large net-pen Tilapia farm, resulting in a dramatic reduction in seasonal water clarity, increased trophic state and altered nutrient dynamics, shifting Lake Yojoa from an oligotrophic (low productivity) to mesotrophic (moderate productivity) ecosystem.

Metals Alter Membership but Not Diversity of a Headwater Stream Microbiome.

Metal contamination from mining or natural weathering is a common feature of surface waters in the American west. Advances in microbial analyses have created the potential for routine sampling of aquatic microbiomes as a tool to assess the quality of stream habitat. We sought to determine if microbiome diversity and membership were affected by metal contamination and identify candidate microbial taxa to be used to indicate metal stress in stream ecosystems.

Evaluating the stoichiometric trait distributions of cultured bacterial populations and uncultured microbial communities.

We measured the stoichiometric trait distribution of cultured freshwater bacterial populations under different resource conditions and compared them to natural microbial communities sampled from three lakes. Trait distributions showed population differences among growth phases and community differences among lakes that would have been masked by only reporting the mean biomass value. The stoichiometric trait distribution of the environmental isolates changed with P availability, growth phase and genotype, with P availability having the strongest effect.

Confounding factors in algal phosphorus limitation experiments.

Assessing algal nutrient limitation is critical for understanding the interaction of primary production and nutrient cycling in streams, and nutrient diffusing substrate (NDS) experiments are often used to determine limiting nutrients such as nitrogen (N) and phosphorus (P). Unexpectedly, many experiments have also shown decreased algal biomass on NDS P treatments compared to controls. To address whether inhibition of algal growth results from direct P toxicity, NDS preparation artifacts, or environmental covariates, we first quantified the frequency of nutrient inhibition in published experiments.

Understanding how microbiomes influence the systems they inhabit.

Translating the ever-increasing wealth of information on microbiomes (environment, host or built environment) to advance our understanding of system-level processes is proving to be an exceptional research challenge. One reason for this challenge is that relationships between characteristics of microbiomes and the system-level processes that they influence are often evaluated in the absence of a robust conceptual framework and reported without elucidating the underlying causal mechanisms. The reliance on correlative approaches limits the potential to expand the inference of a single relationship to additional systems and advance the field.