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Record W1995820880 · doi:10.1890/03-5425

RESPONSES OF SOIL BIOTA TO ELEVATED CO<sub>2</sub>IN A CHAPARRAL ECOSYSTEM

2005· article· en· W1995820880 on OpenAlexaff
Michael F. Allen, John N. Klironomos, Kathleen K. Treseder, Walter C. Oechel

Bibliographic record

VenueEcological Applications · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of Guelph
FundersOffice of ScienceNational Science Foundation
KeywordsEcosystemBiologySoil biologyChaparralEcologyBiotaAgronomySoil waterSoil food webEnvironmental science

Abstract

fetched live from OpenAlex

Atmospheric CO2 is rapidly increasing without an integrative understanding of the responses of soil organisms. We sampled soils in a chaparral ecosystem at 18 intervals over a 3-yr period in replicated field chambers ranging from 250 to 750 ppm CO2 at 100 ppm increments. We assessed three distinct soil energy channels: mycorrhizal fungi, saprotrophic fungi-mite/collembola, and bacteria-protozoa/nematode. C allocation belowground increased with elevated CO2. Standing crops of fungi and bacteria rarely changed with CO2. Mass of bacteria-feeding nematodes increased during wet periods, but the effects on soil bacteria were not detectable. However, grazing of fungi by mites increased with increasing CO2 up to 550 ppm CO2. Above this threshold, allocation of C to the fungal channel declined. Direct measures of mycorrhizal fungi (percentage infection, arbuscular mycorrhizal [AM] fungal hyphal length) showed no changes with CO2 enrichment, but indirect measures (macroaggregates with newly fixed C) increased suggesting increasing allocation of C through this channel. We postulate that the lack of change in standing crop in microbes to elevated CO2 is due to increasing turnover and to increasing N deficiency. Assessing C sequestration and other impacts of elevated CO2 on ecosystems requires a comprehensive, interactive, and dynamic evaluation of soil organismal responses.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.018
GPT teacher head0.241
Teacher spread0.223 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations43
Published2005
Admission routes1
Has abstractyes

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