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Record W2109758285 · doi:10.1029/2003gl018910

Multiple equilibrium states and the abrupt transitions in a dynamical system of soil water interacting with vegetation

2004· article· en· W2109758285 on OpenAlexaff
Samuel S. P. Shen, Xubin Zeng, Robert E. Dickinson

Bibliographic record

VenueGeophysical Research Letters · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Alberta
FundersNational Aeronautics and Space Administration
KeywordsEnvironmental scienceGrasslandBiomass (ecology)EcosystemVegetation (pathology)Water contentAridPrecipitationAtmospheric sciencesTemperate climateRange (aeronautics)Hydrology (agriculture)Soil scienceEcologyGeologyPhysicsMeteorology

Abstract

fetched live from OpenAlex

In semi‐arid areas, multiple equilibrium states of an ecosystem (e.g., grassland and desert) are found to coexist, and the transition from grassland to desert is often abrupt at the boundary. A simple ecosystem model is developed to provide the biophysical explanation of this phenomenon. The model has three variables: living biomass, wilted biomass, and soil wetness. The moisture index, which is the ratio of the annual precipitation to potential evaporation, is the only external climate driving force, and the key mechanism is the vegetation‐soil interaction. It is found that the maintenance of a grassland requires a minimum moisture index, and the abrupt transition occurs when the moisture index is around this critical value. These results are robust within a wide range for most model parameters, suggesting that the model may be applicable to other temperate grasslands. The characteristics of the wilted biomass also strongly influence the ecosystem's dynamics.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.237
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations64
Published2004
Admission routes1
Has abstractyes

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