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Record W7010580707

Influence of crop species and weed seedbank density on extracellular DNA degradation, bacterial community structure and functional capabilities in agricultural soils in Manitoba, Canada

2024· dissertation· en· W7010580707 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2024
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsActinobacteriaWeedCropSoil waterMicrobial population biologyAgricultural soil scienceProteobacteriaNutrientSoil biologySoil microbiology
DOInot available

Abstract

fetched live from OpenAlex

Nucleic acids are abundant in terrestrial ecosystems and are degraded by DNases, mostly from microbial origin, contributing significant quantities of carbon (C), nitrogen (N) and phosphorus (P), which enter their respective nutrient cycles. However, the impact of agronomic management practices on this important soil function and the bacterial community involved has received little attention. This thesis research consisted of an indoor and a long-term field study used to determine the responsiveness of extracellular DNA (exDNA) degradation, extracellular DNase (exDNase) producing bacteria, bacterial diversity, community composition, and functional capabilities as influenced by crop species and weed seedbank density levels in agricultural soils. A high-throughput DNA methyl green (DNA-MG) spectrophotometric assay was developed and successfully adopted for estimating instantaneous exDNA degradation potential in soils. Potential DNase activity in soils was best estimated using soil leachates, and the assay was observed to be stable over a wide range of temperatures. The assay is simple, affordable, and rapid means to estimate potential DNase activity of soils. The assay demonstrated that crop species, crop developmental stages and soil properties influenced instantaneous exDNA degradation potential in agricultural bulk soils, while weed seedbank density did not have a significant effect on this soil function. Moreover, crop species, crop developmental stages, and soil type greatly shaped the populations of culturable exDNase-producing bacteria inhabiting agricultural soils. Several key exDNase-producing bacteria were identified and were dominated by Bacillota (Firmicutes) and Actinobacteria at the phyla level and the Bacillus genera group. The Proteobacteria and Actinobacteria phyla groups dominated the bacterial species in bulk soils from the field study and those positively associated with instantaneous exDNA degradation potential. The chemical fallow and prairie treatments had distinct bacterial community structures and functional groups from each other and also from the annual crop species. Finally, putative nucleotide metabolism-related genes were better predictors of instantaneous exDNA degradation potential compared with bacterial species. Additionally, the current research showed that the presence of plants significantly reduced instantaneous exDNA degradation potential in agricultural soils. In conclusion, this study provides new insights into the cycle of exDNA degradation by enzymatic restriction in agricultural soils, and how management practices contribute to shaping soil bacterial community and functions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.163
Teacher spread0.154 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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