2509.02201
Prospects for Acoustically Monitoring Ecosystem Tipping Points
Neel P. Le Penru, Thomas M. Bury, Sarab S. Sethi, Robert M. Ewers, Lorenzo Picinali
correctmedium confidence
- Category
- Not specified
- Journal tier
- Specialist/Solid
- Processed
- Sep 28, 2025, 12:57 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
The supporting information explicitly derives the OU linearization near a stable equilibrium and shows ρ(τ)=e^{λτ} and Var(η)=−σ^2/(2λ) in the stationary regime, with both trending toward 1 and ∞ respectively as λ→0−. The same file also gives the discrete-time AR(1) form with lag-1 autocorrelation ρ(1)=α and Var(η)=σ^2/(1−α^2), and notes α=e^{λΔt}, so ρ(1)→1 and the variance diverges as α→1 when approaching critical slowing down. These match the candidate solution exactly; the model further provides the exact discrete-time noise mapping from the continuous OU, which the paper summarizes but does not detail. See the SI summary and derivations for these formulas and limits , and the detailed continuous-time and discrete-time derivations .
Referee report (LaTeX)
\textbf{Recommendation:} minor revisions \textbf{Journal Tier:} specialist/solid \textbf{Justification:} The SI reproduces standard, correct OU/AR(1) derivations and clearly connects them to early warning signals of critical slowing down. Minor improvements would clarify the mapping between continuous-time noise intensity and discrete-time innovations and briefly note limitations (e.g., colored noise, Hopf bifurcations). Overall, the mathematical presentation is sound and useful to practitioners.