Although the economic effects of high-speed rail (HSR) are well documented, its implications for avian biodiversity remain unclear. Using a county-level panel for China from 2002 to 2020, we combine effort-adjusted indices from citizen science bird records with geospatial data on HSR lines and stations and estimate treatment effects using a Double Machine Learning (DML) framework. A hub-link decomposition indicates that the negative estimate for avian biodiversity is concentrated in counties with HSR stations, whereas pass-through corridors have no detectable average effect at the county scale. The mechanism analysis is consistent with increased human activity and land conversion around stations. A micro-spatial buffer analysis further shows that the avian estimates are most negative within 1 km of stations and diminish with distance. These findings suggest that ecological assessments of HSR projects should consider not only rail alignments but also station-area land development.
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Zhang et al. (2026) studied this question.
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