Mapping long-distance jump dispersal risk by leveraging transport infrastructure data and sampling bias correction: a case study with the invasive spotted lanternfly (Lycorma delicatula)

Jump dispersal sites for the invasive Lycorma delicatula in the United States are linked to elevated rail density and are closer than expected to 15 property types, especially distribution centers, truck rentals, flea markets, and importers.

• Why it matters: Spatial bias in invasion survey records can hide true dispersal pathways, limiting where surveillance should focus to detect future colonization risk.
• What they did: Using 82,890 agency records, a clustering algorithm identified 207 jump dispersal sites, and a bias-aware comparison dataset was built by filtering for proactive search effort near 22 co-produced property types.
• The result: After accounting for sampling bias, historical jump sites were closer than expected to 15 property types, and ensemble random forests projected high-risk areas in northeast Illinois, southeast Michigan, and central Ohio.

AI summary of the abstract · may contain errors · not medical advice · read the paper.