The study provides valuable insights into climate-driven shifts in crop-pathogen interactions, but the lack of independent model validation and uncertainty quantification significantly impacts the reliability of the predictions. While AUC and TSS scores are reported, these metrics alone do not fully assess model robustness. The models may overestimate predictive accuracy without external validation (e.g., spatial cross-validation or independent test datasets). Furthermore, the absence of confidence intervals or variance estimates means that future projections are presented deterministically, despite uncertainties in climate models. This omission is particularly critical for long-term agricultural planning, as misleading certainty in risk assessments could result in misguided resource allocation and disease management strategies. Incorporating uncertainty measures and additional validation steps would enhance the credibility of the findings and provide a more reliable foundation for policymakers and stakeholders. Could the authors clarify whether any additional validation methods were considered, and how they account for uncertainty in their projections?
