Propagation dynamics of cline and gap states for spatially-periodic Lotka–Volterra competition systems in shifting media
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".