MétaCan
Menu
Back to cohort
Record W7115810361

Microbial Carbon Cycling and Isotope Biosignatures

2009· dissertation· en· W7115810361 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2009
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsCarbonateMicrobial population biologyCarbon cycleCarbon fibersDissolved organic carbonMicrobial matCarbon dioxideAbiotic componentIsotopes of carbon
DOInot available

Abstract

fetched live from OpenAlex

Modern microbialites and microbial mats are the focus of ongoing research as they provide an opportunity to understand microbial-mineral interactions during carbonate precipitation and the generation of biosignatures that can inform our interpretation of the geological record. This study determined the natural abundance isotopic compositions ([13]C, [14]C) of the primary carbon pools and microbial communities associated with modern freshwater microbialites located in Pavilion Lake and in carbonate rich microbial mats on the nearby Cariboo Plateau in British Columbia, Canada. Natural abundance [14]C analysis of carbon pools associated with the Pavilion Lake microbialites demonstrated that structures were actively growing and that groundwater carbon inputs to the lake and microbialites were minimal. Rather, ambient dissolved inorganic carbon (DIC) was the primary carbon source for both microbial communities and recent carbonate. Isotopic enrichment of calcium carbonate within microbial communities associated with the microbialites was identified as a biosignature of microbial photosynthetic influence driving precipitation. Elevated oxygen concentrations and pH within the microenvironment of small, sporadic nodular microbial surface communities was concurrent with in situ precipitation of carbonate with δ[13]C values higher than predicted abiotic values and δ[13]C of bulk organic matter and phospholipid fatty acids (PLFA) that were consistent with a photosynthetically dominated community. Elevated carbonate δ[13]C values were also noted in the thin surface microbial mat recovered from shallow (11m) microbialites. These samples showed increased biomass during summer sampling periods as compared to deeper samples, consistent with expected high rates of photosynthetic activity due to higher light levels and temperature at these depths. These results contrast other recent studies of modern microbialite systems that identified biosignatures of heterotrophic influences on precipitation of carbonates. PLFA profiles demonstrated that the surface microbial mat community consisting of both photosynthetic and heterotrophic microbes was stable over seasonal and spatial changes in light and temperature. However, changes in microbial biomass with depth and season indicated that microbial activity and growth plays an important role in the development of isotopic biosignatures. Biosignatures of high levels of photosynthetic activity were also observed in carbonate, rich microbial mats that exhibited undersaturated p CO2 concentrations during the summer and DIC δ[13]C values enriched above values predicted for isotopic equilibrium with atmospheric CO2. Seasonal and annual shifts in the balance of heterotrophy and autotrophy in the lakes and microenvironment of the mat accounted for observed variations in DIC and associated carbonate δ[13]C values. In contrast to other organic rich microbial mats, bulk organic δ[13]C values were not enriched and the systems did not show evidence of CO2 limitation. Rather, these results indicated that low bulk organic δ[13]C values and large isotopic discriminations can exist under conditions of high DIC concentrations and carbonate content that provide a non limiting carbon source to replenish photosynthetic drawdown.

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)0.000
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 score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.008
GPT teacher head0.186
Teacher spread0.178 · 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueMacSphere (McMaster University)Same topicPaleontology and Stratigraphy of FossilsFrench-language works237,207