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Mauto (Lysiloma divaricatum, Fabaceae) Allometry as an Indicator of Cattle Grazing Pressure in a Tropical Dry Forest in Northwestern Mexico

2005· article· en· W2800923983 on OpenAlex
Aurora Breceda, Víctor Ortiz-Somovilla, Ricardo A. Scrosati

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Range Management · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgroforestry and silvopastoral systems
Canadian institutionsSt. Francis Xavier University
FundersCentro de Investigaciones Biológicas del NoroesteConsejo Nacional de Ciencia y Tecnología
KeywordsGrazingAllometryCanopyBasal areaFabaceaeGrazing pressureBiologyTropical and subtropical dry broadleaf forestsTropicsAgronomyForestryEcologyGeography

Abstract

fetched live from OpenAlex

Mauto (Lysiloma divaricatum (Jacq.) J. F. Macbr.; Fabaceae) is a thornless, arborescent legume that is abundant in tropical dry forests in northwestern Mexico. To test whether mauto allometry may be used as an indicator of cattle grazing pressure, we compared plant height, canopy cover, and basal trunk diameter between an area where cattle had been excluded for 12 years with an area under continuous heavy cattle grazing. Mauto plants that had mostly avoided grazing grew to 12 m in height, with an average basal trunk diameter of 11 cm. Under intense grazing, many plants appeared as a bonsai, that is, as small pruned trees with a relatively thick trunk. Such differences were expressed in the linearized (log-log) slopes of the height-diameter and cover-diameter allometric relationships, which varied significantly between the grazed and ungrazed areas. Basal trunk diameter increased faster per unit increase in plant height and canopy cover in the grazed area than in the ungrazed area. Therefore, these morphological or allometric relationships of mauto could be useful for quickly assessing cattle grazing pressure in tropical dry forests.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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