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Jennifer Pett-Ridge

Publications and source records attributed to Jennifer Pett-Ridge.

9 recordsLinked to original sources
USGS2026

Optimizing cryo-focused pyrolysis GC/MS for tracing soil organic matter across diverse ecosystems

The cycling of organic matter in terrestrial soils and sediments is central to a range of biogeochemical processes that regulate nutrient cycling, crop productivity, trace gas emissions, and contaminant transport. Pyrolysis-gas chromatography/mass spectrometry (py-GC/MS) is a powerful tool for characterizing bulk soil organic matter (SOM) at the molecular level. In this study, we used a cryo-focused py-GC/MS system to analyze soil samples from seven diverse ecosystems: vernal pool, prairie pothole, temperate forest, tropical forest, tundra, wildfire-affected boreal forest, and grassland. We addressed a key bottleneck in molecular-level SOM characterization by developing an automated data analysis pipeline to optimize py-GC/MS and complementary evolved gas analysis/mass spectrometry (EGA/MS) methods, incorporating advanced tools for data deconvolution, developing a custom compound class library, and implementing fragmentation spectrum-based molecular networking for the first time. This improved workflow was applied to soil samples from all seven ecosystems, including multiple depths and density fractions. Our findings demonstrate that ecosystem type plays a dominant role in shaping compositional differences in SOM. We also identified trends in the source of SOM compounds (e.g., microbial vs. plant-derived) across soil depth and density fractions, which are critical for understanding persistence and turnover of SOM. Our molecular networking analysis indicated that although many compounds are widespread across ecosystems, others are restricted to specific environments, such as wetlands. This underscores the utility of molecular-level data in elucidating the complexity of SOM composition and the environmental drivers that shape it. Such molecular-level insights can deepen our knowledge of biogeochemical SOM cycles.

Environmental Science and Technology↗
USGS2025

STREAMS guidelines: Standards for technical reporting in environmental and host-associated microbiome studies

The interdisciplinary nature of microbiome research, coupled with the generation of complex multi-omics data, makes knowledge sharing challenging. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines provide a checklist for the reporting of study information, experimental design and analytical methods within a scientific manuscript on human microbiome research. Here, in this Consensus Statement, we present the standards for technical reporting in environmental and host-associated microbiome studies (STREAMS) guidelines. The guidelines expand on STORMS and include 67 items to support the reporting and review of environmental (for example, terrestrial, aquatic, atmospheric and engineered), synthetic and non-human host-associated microbiome studies in a standardized and machine-actionable manner. Based on input from 248 researchers spanning 28 countries, we provide detailed guidance, including comparisons with STORMS, and case studies that demonstrate the usage of the STREAMS guidelines. STREAMS, like STORMS, will be a living community resource updated by the Consortium with consensus-building input of the broader community.

Nature Microbiology↗
USGS2025

Microbiome data management in action workshop: Atlanta, GA, USA, June 12–13, 2024

Microbiome research is revolutionizing human and environmental health, but the value and reuse of microbiome data are significantly hampered by the limited development and adoption of data standards. While several ongoing efforts are aimed at improving microbiome data management, significant gaps still remain in terms of defining and promoting adoption of consensus standards for these datasets. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines for human microbiome research have been endorsed and successfully utilized by many research organizations, publishers, and funding agencies, and have been recognized as a consensus community standard. No equivalent effort has occurred for environmental, synthetic, and non-human host-associated microbiomes. To address this growing need within the microbiome research community, we convened the Microbiome Data Management in Action Workshop (June 12–13, 2024, in Atlanta, GA, USA), to bring together key decision makers in microbiome science including researchers, publishers, funders, and data repositories. The 50 attendees, representing the diverse and interdisciplinary nature of microbiome research, discussed recent progress and challenges, and brainstormed actionable recommendations and paths forward for coordinated environmental microbiome data management and the modifications necessary for the STORMS guidelines to be applied to environmental, non-human host, and synthetic microbiomes. The outcomes of this workshop will form the basis of a formalized data management roadmap to be implemented across the field. These best practices will drive scientific innovation now and in years to come as these data continue to be used not only in targeted reanalyses but in large-scale models and machine learning efforts.

Environmental Microbiome↗
USGS2021

Active virus-host interactions at sub-freezing temperatures in Arctic peat soil

Background Winter carbon loss in northern ecosystems is estimated to be greater than the average growing season carbon uptake and is primarily driven by microbial decomposers. Viruses modulate microbial carbon cycling via induced mortality and metabolic controls, but it is unknown whether viruses are active under winter conditions (anoxic and sub-freezing temperatures). Results We used stable isotope probing (SIP) targeted metagenomics to reveal the genomic potential of active soil microbial populations under simulated winter conditions, with an emphasis on viruses and virus-host dynamics. Arctic peat soils from the Bonanza Creek Long-Term Ecological Research site in Alaska were incubated under sub-freezing anoxic conditions with H 2 18 O or natural abundance water for 184 and 370 days. We sequenced 23 SIP-metagenomes and measured carbon dioxide (CO 2 ) efflux throughout the experiment. We identified 46 bacterial populations (spanning 9 phyla) and 243 viral populations that actively took up 18 O in soil and respired CO 2 throughout the incubation. Active bacterial populations represented only a small portion of the detected microbial community and were capable of fermentation and organic matter degradation. In contrast, active viral populations represented a large portion of the detected viral community and one third were linked to active bacterial populations. We identified 86 auxiliary metabolic genes and other environmentally relevant genes. The majority of these genes were carried by active viral populations and had diverse functions such as carbon utilization and scavenging that could provide their host with a fitness advantage for utilizing much-needed carbon sources or acquiring essential nutrients. Conclusions Overall, there was a stark difference in the identity and function of the active bacterial and viral community compared to the unlabeled community that would have been overlooked with a non-targeted standard metagenomic analysis. Our results illustrate that substantial active virus-host interactions occur in sub-freezing anoxic conditions and highlight viruses as a major community-structuring agent that likely modulates carbon loss in peat soils during winter, which may be pivotal for understanding the future fate of arctic soils' vast carbon stocks.

Microbiome↗
USGS2021

Response to ‘Stochastic and deterministic interpretation of pool models’

We concur with Azizi‐Rad et al. (2021) that it is vital to critically evaluate and compare different soil carbon models, and we welcome the opportunity to further describe the unique contribution of the PROMISE model (Waring et al. 2020) to this literature. The PROMISE framework does share many features with established biogeochemical models, as our original manuscript highlighted in Table 1, and our work builds upon model innovations developed by many different groups, including that of Azizi‐Rad and colleagues. Yet, the PROMISE framework is distinctive due to where it places mechanistic emphasis, and how these mechanisms are formalized in the mathematical model structure.

Global Change Biology↗
USGS2020

From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world

Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon‐climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool‐based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool‐based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. Here, we propose a novel conceptual framework to explore controls on belowground carbon cycling: P robabilistic R epresentation of O rganic M atter I nteractions within the S oil E nvironment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.

Global Change Biology↗
USGS2011

Response to comments on "A bacterium that can grow using arsenic instead of phosphorus"

Concerns have been raised about our recent study suggesting that arsenic (As) substitutes for phosphorus in major biomolecules of a bacterium that tolerates extreme As concentrations. We welcome the opportunity to better explain our methods and results and to consider alternative interpretations. We maintain that our interpretation of As substitution, based on multiple congruent lines of evidence, is viable.

Science↗
USGS2004

Evaluating the source of streamwater nitrate using δ 15 N and δ 18 O in nitrate in two watersheds in New Hampshire, USA

The natural abundance of nitrogen and oxygen isotopes in nitrate can be a powerful tool for identifying the source of nitrate in streamwater in forested watersheds, because the two main sources of nitrate, atmospheric deposition and microbial nitrification, have distinct δ 18 O values. Using a simple mixing model, we estimated the relative fractions in streamwater derived from these sources for two forested watersheds with markedly different streamwater nitrate outputs. In this study, we monitored δ 15 N and δ 18 O of nitrate biweekly in atmospheric deposition and in streamwater for 20 months at the Hubbard Brook Experimental Forest, New Hampshire, USA (moderate nitrogen export), and monthly in streamwater at the Bowl Research Natural Area, New Hampshire, USA (high nitrogen export). For rain, δ 18 O values ranged from +47 to +77‰ (mean: +58‰) and δ 15 N from −5 to +1‰ (mean: −3‰); for snow, δ 18 O values ranged from +52 to +75‰ (mean: +67‰) and δ 15 N from −3 to +2‰ (mean: −1‰). Streamwater nitrate, in contrast to deposition, had δ 18 O values between +12 and +33‰ (mean: +18‰) and δ 15 N between −3 and +6‰ (mean: 0‰). Since nitrate produced by nitrification typically has δ 18 O values ranging from −5 to +15‰, our field data suggest that most of the nitrate lost from the watersheds in streamflow was nitrified within the catchment. Our results confirm the importance of microbial nitrogen transformations in regulating nitrogen losses from forested ecosystems and suggest that hydrologic storage may be a factor in controlling catchment nitrate losses.

Hydrological Processes↗