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2209.11884

Population Persistence in Stream Networks: Growth Rate and Biomass

Tung D. Nguyen, Yixiang Wu, Amy Veprauskas, Tingting Tang, Ying Zhou, Charlotte Beckford, Brian Chau, Xiaoyun Chen, Behzad Djafari Rouhani, Al-sadh Imadh, Yuerong Wu, Yang Yang, Zhisheng Shuai

correctmedium confidence
Category
Not specified
Journal tier
Specialist/Solid
Processed
Sep 28, 2025, 12:56 AM

Audit review

The paper’s main claims are correct and rigorously justified: (a) the biomass upper bound K ≤ K_env ∑_i (1+q/d)^{f(i)} with equality when all growth is allocated to the most upstream nodes (Theorem 5.6), and (b) for sufficiently small diffusion d, the network growth rate is maximized by concentrating all resources at exactly one downstream end node (Theorem 5.5(i)); the uniform-baseline perturbation result also prioritizes the most downstream nodes (Theorem 3.3) . By contrast, the candidate uses an incorrect symmetrization (they take V=diag(v) instead of the standard W=diag(√v)) and then relies on Rayleigh–Ritz with a matrix that is not symmetric under that transformation; they also assert a zero first-order effect at the uniform baseline, which contradicts the paper’s w^T E v calculation that shows a strictly positive first-order gain when increasing resources at downstream nodes (Theorem 3.3) . While their biomass bound argument can be repaired (a maximum principle works for the Laplacian-form operator without requiring symmetry), the spectral optimization and sensitivity parts contain substantive technical errors.

Referee report (LaTeX)

\textbf{Recommendation:} minor revisions

\textbf{Journal Tier:} specialist/solid

\textbf{Justification:}

The manuscript gives rigorous answers to two natural optimization problems on stream networks and exposes a clear trade-off between maximizing early growth and total biomass. The leveled-graph abstraction and homogeneous-flow modeling are well-motivated; proofs are correct and leverage monotone dynamical systems and perturbation theory sensibly. A few minor edits (typos, brief remarks on symmetrization and eigenvector normalization) would further improve readability.