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This preprint presents a comprehensive metacommunity analysis evaluating how landscape composition, forest fragmentation metrics, topography, and climate influence sand fly vector assemblages in central Panama. Utilizing Joint Species Distribution Models (JSDMs) on a dataset of 1,692 individuals across 30 species (including 9 epidemiologically important anthropportunist taxa), the authors demonstrate that sand fly communities exhibit strong nestedness, low species turnover, and species-specific responses to environmental modifications. Notably, grassland cover and forest edge density strongly enhanced vector occurrence and abundance, whereas artificial surfaces and elevated temperatures had negative effects on several taxa. This work significantly advances the field by moving beyond single-species distribution models to a community-level framework, offering actionable insights for landscape-informed vector control and surveillance at disturbed ecotones.
Sampling Completeness & Effort: With 1,692 individuals collected across 30 species, it would be beneficial to report species accumulation curves or sample-coverage estimators (e.g., Chao1 or coverage-based rarefaction). This would clarify whether sampling saturation was achieved across all habitat types and ensure low-abundance vector taxa were not underrepresented
Spatial Resolution of Landscape Metrics: The abstract highlights land-cover composition and fragmentation metrics as key explanatory variables. However, the spatial buffer radii (e.g., 50m, 100m, 500m) used to quantify these metrics around sampling traps should be explicitly detailed, along with a discussion of how these spatial scales align with known sand fly dispersal distances.
Microclimatic Buffering at Edges: While macroclimatic variables (temperature and precipitation) are evaluated, edge habitats often exhibit distinct microclimatic variations in relative humidity and canopy closure. A deeper discussion on how microclimates might mediate temperature sensitivity in fragmented edge zones would strengthen the ecological conclusions.
Terminological Consistency: Clearly define the ecological distinction between "anthropportunist" and "anthropophilic" species early in the manuscript to ensure consistent usage throughout the text.
Data Visualization: Suggest adding correlation matrices or heatmaps in the main figures to illustrate species-specific JSDM regression coefficients and residual species-species association networks.
Surveillance Translation: Expand briefly on practical, field-ready recommendations for public health authorities to implement "landscape-informed surveillance" at grassland-forest interfaces.
The author declares that they have no competing interests.
The author declares that they used generative AI to come up with new ideas for their review.
I used AI (Gemini) to help structure the review, synthesize key critical points based on the preprint details, and refine the clarity and formatting of the feedback.
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