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Record W4396224969 · doi:10.1007/s11430-023-1326-2

Adaptive strategies of high and low nucleic acid prokaryotes in response to declining resource availability and selective grazing by protozoa

2024· article· en· W4396224969 on OpenAlexaff
Chen Hu, Liuqian Yu, Xiaowei Chen, Jihua Liu, Yao Zhang, John Batt, Xilin Xiao, Qiang Shi, Rui Zhang, Tingwei Luo, Nianzhi Jiao, Dapeng Xu

Bibliographic record

VenueScience China Earth Sciences · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBiologyProtozoaResource (disambiguation)GrazingAbundance (ecology)EcologyMicrobiologyComputer science

Abstract

fetched live from OpenAlex

Abstract Prokaryotes play a fundamental role in global ocean biogeochemical cycles. However, how the abundance and metabolic activity of ecologically distinct subgroups (i.e., high nucleic acid (HNA) and low nucleic acid (LNA) cells), and their regulating factors, change in response to changing marine environmental conditions remains poorly understood. Here, we delved into the time-evolving dynamic responses of the HNA and LNA prokaryotic subgroups to declining resource availability and selective grazing by protozoa by conducting a 73-day incubation experiment in a large-volume (117,000 L) macrocosm that facilitates community-level exploration. We found that the metabolic activity of the HNA subgroup was higher than that of the LNA subgroup when the macrocosm was resource replete but that the HNA subgroup declined more rapidly than the LNA subgroup as the resources became increasingly scarce, leading to a steadily increasing contribution of LNA cells to prokaryotic activity. Meanwhile, as resources in the macrocosm became limited, protozoan grazing preference shifted from the HNA to the LNA subgroup and the contributions of the LNA subgroup to the carbon flow within the macrocosm increased. The findings highlight the resilience of LNA cells in resource-limited environments, illuminate the critical role of selective grazing by protozoa in balancing distinct prokaryotic subgroups under changing resource conditions, and demonstrate the complex and adaptive interactions between protozoa and prokaryotes across diverse environmental contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.006
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.255
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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