Publications by authors named "Jennifer D Rocca"

Temperature significantly impacts microbial communities' composition and function, which plays a vital role in the global carbon cycle that determines climate change. Nutrient influxes often accompany rising temperatures due to human activity. While ecological interactions between different microorganisms could shape their response to environmental change, we do not understand how predation may influence these responses in a warmer and increasingly nutrient-rich world.

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Temperature strongly influences microbial community structure and function, in turn contributing to global carbon cycling that can fuel further warming. Recent studies suggest that biotic interactions among microbes may play an important role in determining the temperature responses of these communities. However, how predation regulates these microbiomes under future climates is still poorly understood.

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With advances in eDNA metabarcoding, environmental microbiomes are increasingly used as cost-effective tools for monitoring ecosystem health. Stream ecosystems in Central Appalachia, heavily impacted by alkaline drainage from mountaintop coal mining, present ideal opportunities for biomonitoring using stream microbiomes, but the structural and functional responses of microbial communities in different environmental compartments are not well understood. We investigated sediment microbiomes in mining impacted streams to determine how community composition and function respond to mining and to look for potential microbial bioindicators.

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Every seed germinating in soils, wastewater treatment, and stream confluence exemplify microbial community coalescence-the blending of previously isolated communities. Here, we present theoretical and experimental knowledge on how separated microbial communities mix, with particular focus on managed ecosystems. We adopt the community coalescence framework, which integrates metacommunity theory and meta-ecosystem dynamics, and highlight the prevalence of these coalescence events within microbial systems.

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The rivers of Appalachia (United States) are among the most biologically diverse freshwater ecosystems in the temperate zone and are home to numerous endemic aquatic organisms. Throughout the Central Appalachian ecoregion, extensive surface coal mines generate alkaline mine drainage that raises the pH, salinity, and trace element concentrations in downstream waters. Previous regional assessments have found significant declines in stream macroinvertebrate and fish communities after draining these mined areas.

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Whole microbial communities regularly merge with one another, often in tandem with their environments, in a process called community coalescence. Such events impose substantial changes: abiotic perturbation from environmental blending and biotic perturbation of community merging. We used an aquatic mixing experiment to unravel the effects of these perturbations on the whole microbiome response and on the success of individual taxa when distinct freshwater and marine communities coalesce.

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A majority of environmental studies describe microbiomes at coarse scales of taxonomic resolution (bacterial community, phylum), ignoring key ecological knowledge gained from finer-scales and microbial indicator taxa. Here, we characterized the distribution of 940 bacterial taxa from 41 streams along an urbanization gradient (0%-83% developed watershed area) in the Raleigh-Durham area of North Carolina (USA). Using statistical approaches derived from macro-organismal ecology, we found that more bacterial taxa were classified as intolerant than as tolerant to increasing watershed urbanization (143 vs 48 OTUs), and we identified a threshold of 12.

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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.

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The environmental fate and potential impacts of nanopesticides on agroecosystems under realistic agricultural conditions are poorly understood. As a result, the benefits and risks of these novel formulations compared to the conventional products are currently unclear. Here, we examined the effects of repeated realistic exposures of the Cu(OH) nanopesticide, Kocide 3000, on simulated agricultural pastureland in an outdoor mesocosm experiment over 1 year.

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Predicting nanoparticle fate in aquatic environments requires mimicking of ecosystem complexity to observe the geochemical processes affecting their behaviour. Here, 12 nm Au nanoparticles were added weekly to large-scale freshwater wetland mesocosms. After six months, ~70% of Au was associated with the macrophyte Egeria densa, where, despite the thermodynamic stability of Au in water, the pristine Au nanoparticles were fully oxidized and complexed to cyanide, hydroxyls or thiol ligands.

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The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries.

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Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40-70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models.

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For any enzyme-catalyzed reaction to occur, the corresponding protein-encoding genes and transcripts are necessary prerequisites. Thus, a positive relationship between the abundance of gene or transcripts and corresponding process rates is often assumed. To test this assumption, we conducted a meta-analysis of the relationships between gene and/or transcript abundances and corresponding process rates.

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Microbes in soils and other environments produce extracellular enzymes to depolymerize and hydrolyze organic macromolecules so that they can be assimilated for energy and nutrients. Measuring soil microbial enzyme activity is crucial in understanding soil ecosystem functional dynamics. The general concept of the fluorescence enzyme assay is that synthetic C-, N-, or P-rich substrates bound with a fluorescent dye are added to soil samples.

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As a consequence of the tight linkages among soils, plants and microbes inhabiting the rhizosphere, we hypothesized that soil nutrient and microbial stoichiometry would differ among plant species and be correlated within plant rhizospheres. We assessed plant tissue carbon (C) : nitrogen (N) : phosphorus (P) ratios for eight species representing four different plant functional groups in a semiarid grassland during near-peak biomass. Using intact plant species-specific rhizospheres, we examined soil C : N : P, microbial biomass C : N, and soil enzyme C : N : P nutrient acquisition activities.

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Hurricanes have the potential to alter the structures of coastal ecosystems and generate pathogen-laden floodwaters thatthreaten public health. To examine the impact of hurricanes on urban systems, we compared microbial community structures in samples collected after Hurricane Katrina and before and after Hurricane Rita. We extracted environmental DNA and sequenced small-subunit rRNA (SSU rRNA) gene clone libraries to survey microbial communities in floodwater, water, and sediment samples collected from Lake Charles, Lake Pontchartrain, the 17th Street and Industrial Canals in New Orleans, and raw sewage.

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