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Record W4407532597 · doi:10.1088/1361-6544/adb122

Propagation dynamics of cline and gap states for spatially-periodic Lotka–Volterra competition systems in shifting media

2025· article· en· W4407532597 on OpenAlexafffund
Hongyong Wang, Chunhua Ou

Bibliographic record

VenueNonlinearity · 2025
Typearticle
Languageen
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMathematicsCline (biology)Competition (biology)Dynamics (music)Statistical physicsVolterra equationsCompetition modelNonlinear systemPhysicsEcologyDemographyEconomics

Abstract

fetched live from OpenAlex

Abstract We study the propagation dynamics of a Lotka–Volterra competition system in which one growth rate behaves like a monotonically decreasing wave profile that shifts with a given speed and is also periodic in the first spatial variable, while the other growth rate behaves similarly, except that its profile is monotonically increasing with respect to the shifting variable. Furthermore, both growth functions are assumed to be sign-changed, which implies that the environments in which the species live switch spatially from ‘good’ regions (suitable for survival) to ‘bad’ regions (not suitable for survival) and vice versa. We reveal that the model admits a forced pulsating wave only when the forced speed lies within a finite interval ( c ∗ , c ∗ ) that contains zero. Biologically, this corresponds to the formation of a shifting cline. Moreover, we find that c ∗ < 0 and c ∗ > 0 can be calculated in terms of the Fisher-KPP speeds related to the linearized equations of each species. By applying a sliding technique, we show that the forced pulsating wave is unique. We also prove that the forced pulsating wave is Lyapunov-stable. Finally, the spreading dynamics of spatial gap formation in the two species are also investigated when the forced wave speed is either less than c ∗ or greater that c ∗ . We employ a novel approach to demonstrate how the species invade in response to a shifting environment.

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)0.004
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 score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.322
Teacher spread0.289 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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