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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Contrasting Community Assembly Forces Drive Microbial Structural and Potential Functional Responses to Precipitation in an Incipient Soil System

Microbial communities in incipient soil systems serve as the only biotic force shaping landscape evolution. However, the underlying ecological forces shaping microbial community structure and function are inadequately understood. We used amplicon sequencing to determine microbial taxonomic assembly and metagenome sequencing to evaluate microbial functional assembly in incipient basaltic soil subjected to precipitation. Community composition was stratified with soil depth in the pre-precipitation samples, with surficial communities maintaining their distinct structure and diversity after precipitation, while the deeper soil samples appeared to become more uniform. The structural community assembly remained deterministic in pre- and post-precipitation periods, with homogenous selection being dominant. Metagenome analysis revealed that carbon and nitrogen functional potential was assembled stochastically. Sub-populations putatively involved in the nitrogen cycle and carbon fixation experienced counteracting assembly pressures at the deepest depths, suggesting the communities may functionally assemble to respond to short-term environmental fluctuations and impact the landscape-scale response to perturbations. We propose that contrasting assembly forces impact microbial structure and potential function in an incipient landscape; in situ landscape characteristics (here homogenous parent material) drive community structure assembly, while short-term environmental fluctuations (here precipitation) shape environmental variations that are random in the soil depth profile and drive stochastic sub-population functional dynamics.

16S amplicon sequencing↗
DOE OSTI2021

Impact of Harvest on Switchgrass Leaf Microbial Communities

Switchgrass is a promising feedstock for biofuel production, with potential for leveraging its native microbial community to increase productivity and resilience to environmental stress. Here, we characterized the bacterial, archaeal and fungal diversity of the leaf microbial community associated with four switchgrass (Panicum virgatum) genotypes, subjected to two harvest treatments (annual harvest and unharvested control), and two fertilization levels (fertilized and unfertilized control), based on 16S rRNA gene and internal transcribed spacer (ITS) region amplicon sequencing. Leaf surface and leaf endosphere bacterial communities were significantly different with Alphaproteobacteria enriched in the leaf surface and Gammaproteobacteria and Bacilli enriched in the leaf endosphere. Harvest treatment significantly shifted presence/absence and abundances of bacterial and fungal leaf surface community members: Gammaproteobacteria were significantly enriched in harvested and Alphaproteobacteria were significantly enriched in unharvested leaf surface communities. These shifts were most prominent in the upland genotype DAC where the leaf surface showed the highest enrichment of Gammaproteobacteria, including taxa with 100% identity to those previously shown to have phytopathogenic function. Fertilization did not have any significant impact on bacterial or fungal communities. We also identified bacterial and fungal taxa present in both the leaf surface and leaf endosphere across all genotypes and treatments. These core taxa were dominated by Methylobacterium, Enterobacteriaceae, and Curtobacterium, in addition to Aureobasidium, Cladosporium, Alternaria and Dothideales. Local core leaf bacterial and fungal taxa represent promising targets for plant microbe engineering and manipulation across various genotypes and harvest treatments. Our study showcases, for the first time, the significant impact that harvest treatment can have on bacterial and fungal taxa inhabiting switchgrass leaves and the need to include this factor in future plant microbial community studies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

A Flight Research Overview of WSPR, a Pilot Project for Sonic Boom Community Response

In support of NASAs ongoing effort to bring supersonic commercial travel to the public, NASA Dryden Flight Research Center and NASA Langley Research Center, in cooperation with other industry organizations, conducted a flight research experiment to identify the methods, tools, and best practices for a large-scale quiet (or low) sonic boom community human response test. The name of the effort was Waveforms and Sonic boom Perception and Response. Such tests will go towards building a dataset that governing agencies like the Federal Aviation Administration and International Civil Aviation Organization will use to establish regulations for acceptable sound levels of overland sonic booms. Until WSPR, there had never been an effort that studied the response of people in their own homes and performing daily activities to non-traditional, low sonic booms.WSPR was a NASA collaborative effort with several industry partners, in response to a NASA Aeronautics Research Mission Directorate Research Opportunities in Aeronautics. The primary contractor was Wyle. Other partners included Gulfstream Aerospace Corporation, Pennsylvania State University, Tetra Tech, and Fidell Associates, Inc.A major objective of the effort included exposing a community with the sonic boom magnitudes and occurrences expected in high-air traffic regions with a network of supersonic commercial aircraft in place. Low-level sonic booms designed to simulate those produced by the next generation of commercial supersonic aircraft were generated over a small residential community. The sonic boom footprint was recorded with an autonomous wireless microphone array that spanned the entire community. Human response data was collected using multiple survey methods. The research focused on essential elements of community response testing including subject recruitment, survey methods, instrumentation systems, flight planning and operations, and data analysis methods.This paper focuses on NASAs role in the efforts logistics and operations including human response subject recruitment, the operational processes involved in implementing the surveys throughout the community, instrumentation systems, logistics, flight planning, and flight operations. Findings discussed in this paper include critical lessons learned in all of those areas. The paper also discusses flight operations results. Analysis of the accuracy and repeatability of planning and executing the unique aircraft maneuver used to generate low sonic booms concluded that the sonic booms had overpressures within 0.15 pounds-per-square-feet of the planned values for 76 of t he attempts. Similarly, 90 of the attempts to generate low sonic booms within the community were successful.

sonic booms↗
NASA NTRS2014

A Flight Research Overview of WSPR, a Pilot Project for Sonic Boom Community Response

In support of the ongoing effort by the National Aeronautics and Space Administration (NASA) to bring supersonic commercial travel to the public, the NASA Armstrong Flight Research Center and the NASA Langley Research Center, in cooperation with other industry organizations, conducted a flight research experiment to identify the methods, tools, and best practices for a large-scale quiet (or low) sonic boom community human response test. The name of the effort was Waveforms and Sonic boom Perception and Response (WSPR). Such tests will be applied to building a dataset that governing agencies such as the Federal Aviation Administration and the International Civil Aviation Organization will use to establish regulations for acceptable sound levels of overland sonic booms. The WSPR test was the first such effort that studied responses to non-traditional low sonic booms while the subject persons were in their own homes and performing daily activities.The WSPR test was a NASA collaborative effort with several industry partners, in response to a NASA Aeronautics Research Mission Directorate Research Opportunities in Aeronautics. The primary contractor was Wyle (El Segundo, California). Other partners included Gulfstream Aerospace Corporation (Savannah, Georgia); Pennsylvania State University (University Park, Pennsylvania); Tetra Tech, Inc. (Pasadena, California); and Fidell Associates, Inc. (Woodland Hills, California).A major objective of the effort included exposing a community to the sonic boom magnitudes and occurrences that would be expected to occur in high-air traffic regions having a network of supersonic commercial aircraft in place. Low-level sonic booms designed to simulate those produced by the next generation of commercial supersonic aircraft were generated over a small residential community. The sonic boom footprint was recorded with an autonomous wireless microphone array that spanned the entire community. Human response data were collected using multiple survey methods. The research focused on essential elements of community response testing including subject recruitment, survey methods, instrumentation systems, flight planning and operations, and data analysis methods.This paper focuses on the NASA role in the logistics and operations of the effort, including human response subject recruitment, the operational processes involved in implementing the surveys throughout the community, instrumentation systems, logistics, flight planning, and flight operations. Findings discussed in this paper include critical lessons learned in all of the above-mentioned areas, as well as flight operations results. Analysis of the accuracy and repeatability of planning and executing the unique aircraft maneuver used to generate low sonic booms concluded that the sonic booms had overpressures within 0.15 lbft2 of the planned values for 76 percent of the attempts. Similarly, 90 percent of the attempts to generate low sonic booms within the community were successful.

community response↗
NASA NTRSDate not supplied

Effective Engagement for Community Action with NASA’s Indigenous Peoples Initiative

NASA’s Indigenous Peoples Initiative (IPI) seeks to support and cultivate efforts within Indigenous communities and NASA to increase the use of Earth Observations (EO) to inform decisions, policies, and actions. IPI is dedicated to building lasting relationships with Indigenous communities by creating a trusted, reliable, and Indigenous-centric geospatial community with a focus on environmental justice and climate issues on Indigenous lands and territories. Indigenous communities through conservation, restoration, and adaptation have the opportunity to further empower their landscape work through the potential use of EO and other NASA data and tools. We will outline our guiding principles, multiple approaches, and lessons learned for working alongside Indigenous communities in a respectful and reciprocal manner. These include the recognition of multiple ways of knowing, co-development of trainings, acknowledgement of all sovereignty, maintaining healthy relationships with tribal natural resource managers and building bridges for their engagement with NASA researchers and other federal agency partners, and making space for reflection and adaptation of our practices as we grow. Future activities, such as dialogue sessions with Indigenous communities around EO needs, aim to enhance these practices and ultimately benefit the ability for Indigenous communities to maintain and protect their lands, people, and practices in the face of environmental injustices and climate change.

Effective↗
DOE OSTI2023

Operating-Envelopes-Aware Decentralized Welfare Maximization for Energy Communities: Preprint

We propose an operating-envelope-aware, prosumer-centric, and efficient energy community that aggregates individual and shared community distributed energy resources downstream of a regulated distribution system operator's (DSO) net energy metering revenue meter. Due to the elevated risk of grid constraint violations and to ensure safe network operation, the DSO imposes dynamic export and import limits, known as dynamic operating envelopes, on end-users' revenue meters. Given the operating envelopes, the proposed community market mechanism maximizes the community's social welfare in a decentralized fashion while every community member abides by its own operating envelopes. We show that the proposed market mechanism conforms with the cost-causation principle and guarantees community members a surplus level no less than their maximum surplus when they autonomously face the DSO. Lastly, a numerical study is implemented to showcase and compare the community's welfare under the proposed operating-envelopes-aware mechanisms to others, including the welfare of customers under the DSO's regime.

distributed energy resources aggregation↗
DOE OSTI2023

A Methodology for Defining Affordability in Commercial Buildings and its Impact on Underserved Communities

Commercial buildings are at the heart of any community. Investments towards the health and performance of community buildings can support a wide range of critical community and individual benefits; however, many buildings have been left behind in these investments due to a spectrum of barriers, especially those located in underserved communities. This portfolio of work stands with the intent that if we can create solutions to support the hardest-to-reach commercial buildings in gaining equitable access to energy efficiency, zero energy, and zero carbon solutions, we can support all commercial buildings with these goals. To understand success and barriers, and identify new, innovative, and impactful solutions, NREL is taking a four-part approach to: 1. Develop a methodology for defining affordability in commercial buildings and understand its impact on underserved communities, 2. Work with trusted, local organizations to address barriers that impede access to cost-effective, holistic, building performance improvements, 3. Support minority-focused developer incubator programs for, and within, underserved communities, and 4. Identify overlapping value streams that support underserved community and utility needs.

building electrification↗
DOE OSTI2022

Communities in energy transition: exploring best practices and decision support tools to provide equitable outcomes

Abstract The U.S. coal industry has been in a state of decline for the past decade, a trend ushered by flat electricity demand, increased regulatory pressure, and market competition from cost-competitive clean energy sources. The receding economic viability of the coal industry has been acutely felt by the communities with immediate economic ties to coal-fired generation. With the energy transition underway, the question of how to engage communities as stakeholders in the decision-making process and address their needs through an equitable and just transition remains unresolved. To that end, this paper explores the economic, environmental, and social challenges presented by the energy transition at the community level, highlighting four case studies from transitioning coal-dependent communities across the United States to ultimately identify best practices in coal plant decommissioning processes. This paper weaves these community-identified best practices into two support tools—a decommissioning checklist and a redevelopment decision-making framework—that can be used to engage communities in the power plant retirement decision, the site reclamation phase, and eventual redevelopment of the site and revitalization of the surrounding community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗
DOE OSTI2021

The sum is greater than the parts: exploiting microbial communities to achieve complex functions

We report multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology. The rational intervention of microbial communities for the purpose of improved function has been facilitated in part by developments in multi-omics approaches, synthetic biology, and computational methods. Recent studies have demonstrated the benefits of rational interventions to human and animal health as well as agricultural productivity. Emergent technologies, such as in situ modification of complex microbial community and community metabolic modeling, represent an avenue to engineer sustainable microbial communities. In this opinion, we review relevant computational and experimental approaches to study and engineer microbial communities and discuss their potential for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Direct evidence for the role of microbial community composition in the formation of soil organic matter composition and persistence

The largest terrestrial carbon sink on earth is soil carbon stocks. As the climate changes, the rate at which the Earth’s climate warms depends in part on the persistence of soil organic carbon. Microbial turnover forms the backbone of soil organic matter (SOM) formation and it has been recently proposed that SOM molecular complexity is a key driver of stability. Despite this, the links between microbial diversity, chemical complexity and biogeochemical nature of SOM remain missing. Here we tested the hypotheses that distinct microbial communities shape the composition of SOM, and microbial-derived SOM has distinct decomposition potential depending on its community of origin. We inoculated microbial communities of varying diversities into a model soil matrix amended with simple carbon (cellobiose) and measured the thermal stability of the resultant SOM. Using a Rock-Eval ® ramped thermal analysis, we found that microbial community composition drives the chemical fingerprint of soil carbon. While diversity was not a driver of SOM composition, bacteria-only communities lead to more thermally labile soil C pools than communities with bacteria and fungi. Our results provide direct evidence for a link between microbial community structure, SOM composition, and thermal stability. This evidence demonstrates the relevance of soil microorganisms in building persistent SOM stocks.

Domeignoz-Horta, Luiz A. (ORCID:0000000346186253)↗
DOE OSTI2024

Soil microbial community response to corrinoids is shaped by a natural reservoir of vitamin B12

Abstract Soil microbial communities perform critical ecosystem services through the collective metabolic activities of numerous individual organisms. Most microbes use corrinoids, a structurally diverse family of cofactors related to vitamin B12. Corrinoid structure influences the growth of individual microbes, yet how these growth responses scale to the community level remains unknown. Analysis of metagenome-assembled genomes suggests that corrinoids are supplied to the community by members of the archaeal and bacterial phyla Thermoproteota, Actinobacteria, and Proteobacteria. Corrinoids were found largely adhered to the soil matrix in a grassland soil, at levels exceeding those required by cultured bacteria. Enrichment cultures and soil microcosms seeded with different corrinoids showed distinct shifts in bacterial community composition, supporting the hypothesis that corrinoid structure can shape communities. Environmental context influenced both community- and taxon-specific responses to specific corrinoids. These results implicate corrinoids as key determinants of soil microbiome structure and suggest that environmental micronutrient reservoirs promote community stability.

58 GEOSCIENCES↗
DOE OSTI2025

The overlooked interaction of emerging contaminants and microbial communities: a threat to ecosystems and public health

Abstract Context and aims Emerging contaminants (ECs) and microbial communities should not be viewed in isolation, but through the One Health perspective. Both ECs and microorganisms lie at the core of this interconnected framework, as they directly influence the health of humans, animals, and the environment. The interactions between ECs and microbial communities can have profound implications for public health, affecting all three domains. However, these ECs-microorganism interactions remain underexplored, potentially leaving significant public health and ecological risks unrecognized. Therefore, this article seeks to alert the scientific community to the overlooked interactions between ECs and microbial communities, emphasizing the pivotal role these interactions may play in the management of ‘One Health.’ Results The most extensively studied interaction between ECs and microbial communities is biodegradation. However, other more complex and concerning interactions demand attention, such as the impact of ECs on microbial ecology (disruptions in ecosystem balance affecting nutrient and energy cycles) and the rise and spread of antimicrobial resistance (a growing global health crisis). Although these ECs-microbial interactions had not been extensively studied, there are scientific evidence that ECs impact on microbial communities may be concerning for public health and ecosystem balance. Conclusions So, this perspective summarizes the impact of ECs through a One Health lens and underscores the urgent need to understand their influence on microbial communities, while highlighting the key challenges researchers must overcome. Tackling these challenges is vital to mitigate potential long-term consequences for both ecosystems and public health.

Gomes, Inês B. (ORCID:0000000207313662)↗
DOE OSTI2021

An evolutionary algorithm for designing microbial communities via environmental modification

Despite a growing understanding of how environmental composition affects microbial communities, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbour thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and metabolic modelling that selects optimal environmental compositions to produce target community phenotypes. In this framework, dynamic flux balance analysis is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behaviour of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to approach this target. We apply this iterative process to thousands of in silico communities of varying sizes, showing how it can rapidly identify environments that yield desired taxonomic compositions and patterns of metabolic exchange. Moreover, this combination of approaches produces testable predictions for the assembly of experimental microbial communities with specific properties and can facilitate rational environmental design processes for complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Community detection robustness of graph neural networks

Graph neural networks (GNNs) are increasingly widely used for community detection in attributed networks. They combine structural topology with node attributes through message passing and pooling. However, their robustness or lack thereof with respect to different perturbations and targeted attacks in conjunction with community detection tasks is not well understood. To shed light on latent mechanisms behind GNN sensitivity on community detection tasks, we conduct a systematic computational evaluation of six widely adopted GNN architectures graph convolutional network, graph attention network, graph sample and aggregate (GraphSAGE), differentiable pooling (DiffPool), minimum cut pooling (MinCUT), and deep modularity networks (DMoN). The analysis covers three perturbation categories: node attribute manipulations, edge topology distortions, and adversarial attacks. We use element-centric similarity as the evaluation metric on synthetic benchmarks and real-world citation networks. Our findings indicate that supervised GNNs tend to achieve higher baseline accuracy, while unsupervised methods, particularly DMoN, maintain stronger resilience under targeted and adversarial perturbations. Furthermore, robustness appears to be strongly influenced by community strength, with well-defined communities reducing performance loss. Across all models, node attribute perturbations associated with targeted edge deletions and shifts in attribute distributions tend to cause the largest degradation in community recovery. These findings highlight important trade-offs between accuracy and robustness in GNN-based community detection and offer insights into selecting architectures resilient to noise and adversarial attacks.

Goel, Jaidev [Virginia Polytechnic Inst. and State↗
DOE OSTI2024

The direct and indirect drivers shaping RNA viral communities in grassland soils

ABSTRACT Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from bulk metatranscriptomes sequenced from grassland soils managed for 5 years under multiple environmental conditions including water content, plant presence, cultivar type, and soil depth. More than half of the unique RNA viral contigs (64.6%) were assigned with putative hosts. About 74.7% of these classified RNA viral contigs are known as eukaryotic RNA viruses suggesting eukaryotic RNA viruses may outnumber prokaryotic RNA viruses by nearly three times in this grassland. Of the identified eukaryotic RNA viruses and the associated eukaryotic species, the most dominant taxa were Mitoviridae with an average relative abundance of 72.4%, and their natural hosts, Fungi with an average relative abundance of 56.6%. Network analysis and structural equation modeling support that soil water content, plant presence, and type of cultivar individually demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members. A significant negative influence of soil depth on soil eukaryotic richness and abundance indirectly impacts soil eukaryotic RNA viral communities. These results provide new insights into the collective influence of multiple environmental and community factors that shape soil RNA viral communities and offer a structured perspective of how RNA virus diversity and ecology respond to environmental changes. IMPORTANCE Climate change has been reshaping the soil environment as well as the residing microbiome. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil. This knowledge is critical for predicting the viral responses to climate change and the potential emergence of biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bacterial community dynamics as a result of growth-yield trade-off and multispecies metabolic interactions toward understanding the gut biofilm niche

Abstract Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces. One example is gut mucosal communities, where dense, closely packed communities develop under the concurrent influence of nutrient transport from the lumen and fluid-mediated detachment of bacteria. In this study, we model a mucosal niche through a coupled agent-based and finite-volume modeling approach. This methodology enables us to model bacterial interactions affected by nutrient release from various sources while adjusting individual bacterial kinetics. We explored how the dispersion and abundance of bacteria are influenced by biochemical kinetics in different types of metabolic interactions, with a particular focus on the trade-off between growth rate and yield. Our findings demonstrate that in competitive scenarios, higher growth rates result in a larger share of the niche space. In contrast, growth yield plays a critical role in neutralism, commensalism, and mutualism interactions. When bacteria are introduced sequentially, they cause distinct spatiotemporal effects, such as deeper niche colonization in commensalism and mutualism scenarios driven by species intermixing effects, which are enhanced by high growth yields. Moreover, sub-ecosystem interactions dictate the dynamics of three-species communities, sometimes yielding unexpected outcomes. Competitive, fast-growing bacteria demonstrate robust colonization abilities, yet they face challenges in displacing established mutualistic systems. Bacteria that develop a cooperative relationship with existing species typically obtain niche residence, regardless of their growth rates, although higher growth yields significantly enhance their abundance. Our results underscore the importance of bacterial niche dynamics in shaping community properties and succession, highlighting a new approach to manipulating microbial systems.

Microbiology↗
DOE OSTI2024

Subsurface microbial community structure shifts along the geological features of the Central American Volcanic Arc

Subduction of the Cocos and Nazca oceanic plates beneath the Caribbean plate drives the upward movement of deep fluids enriched in carbon, nitrogen, sulfur, and iron along the Central American Volcanic Arc (CAVA). These compounds fuel diverse subsurface microbial communities that in turn alter the distribution, redox state, and isotopic composition of these compounds. Microbial community structure and functions vary according to deep fluid delivery across the arc, but less is known about how microbial communities differ along the axis of a convergent margin as geological features (e.g., extent of volcanism and subduction geometry) shift. Here, we investigate changes in bacterial 16S rRNA gene amplicons and geochemical analysis of deeply-sourced seeps along the southern CAVA, where subduction of the Cocos Ridge alters the geological setting. We find shifts in community composition along the convergent margin, with communities in similar geological settings clustering together independently of the proximity of sample sites. Microbial community composition correlates with geological variables such as host rock type, maturity of hydrothermal fluid and slab depth along different segments of the CAVA. This reveals tight coupling between deep Earth processes and subsurface microbial activity, controlling community distribution, structure and composition along a convergent margin.

Science & Technology - Other Topics↗