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Record W2035367151 · doi:10.2136/sssaj2005.0473

Soil Properties along Cultivation and Fallow Time Sequences on Vertisols in Northeastern Mexico

2005· article· en· W2035367151 on OpenAlexaff
Maria R. Bravo-Garza, Rorke B. Bryan

Bibliographic record

VenueSoil Science Society of America Journal · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVertisolEnvironmental scienceAgronomySummer fallowSoil qualitySoil carbonAgricultureVegetation (pathology)AgroecosystemAgroforestrySoil waterSoil scienceBiologyEcology

Abstract

fetched live from OpenAlex

Rain‐fed agriculture in alternation with natural fallow is widespread in semiarid northeastern Mexico, but little information on changes in soil properties, soil degradation, and natural rehabilitation is available. The effects of rain‐fed agriculture and fallow on soil quality indicators on vertisols in a semiarid area near Linares, Nuevo León, were studied. One cultivated time sequence representing 3 to 30 yr of use and one fallow time sequence of 2 to 22 yr were selected. Fifty percent of soil organic carbon (SOC) and 56% of total nitrogen (TN) were lost during the first 4 yr of cultivation, but loss reached approximate equilibrium after 6 yr. The SOC showed 34% recovery and TN showed 62% recovery on sites abandoned for 22 yr. Despite this recovery after 22 yr of fallow, SOC and TN levels reached only 50% of those observed under native vegetation. Water‐stable macroaggregation declined by 14% under cultivation, but increased swiftly during fallow, showing no significant correlation with SOC. The levels of SOC and TN depletion under conventional rain‐fed agriculture observed are very difficult to mitigate by natural fallows in economically‐viable time periods. However, the precise impact of these changes on aggregation properties of these vertisols and the long‐term sustainability of present cultivation–fallow practices is not clear. Further research to determine the precise influence of individual soil organic constituents on physical properties of these vertisols is in progress.

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 score0.095

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 communication0.0000.000
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 head0.014
GPT teacher head0.217
Teacher spread0.203 · 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

Citations31
Published2005
Admission routes1
Has abstractyes

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