Multifactor Synergistic Drivers of First Arrival Dates in Chinese Birds: Nationwide Evidence from Audio-Video Fusion Monitoring

We leveraged deep-learning–enabled autonomous acoustic recorders and high-definition cameras to quantify how climate, upper-level winds, and vegetation cover influence first arrival dates (FADs) of birds across the subtropical–temperate transition zone of China. From December 2021 to June 2025, we conducted continuous monitoring at 81 wetland and forest stations spanning 22–45° N and established an end-to-end workflow covering data acquisition, quality control, modeling, and validation. In total, we extracted 5,796 FADs encompassing 618 resident and migratory species along the East Asian–Australasian Flyway. We linked FADs to daily mean temperature, daily cumulative precipitation, tailwind anomaly, crosswind strength, and vegetation anomaly. Using covariates averaged over a backward 30-day window, we fitted linear mixed-effects models (LMMs) and generalized additive mixed models (GAMMs) with species and region as random effects. Results were consistent across model classes: warming is associated with delayed arrivals—each +1 °C in 30-day mean temperature corresponds to a ~2.58–3.60-day delay in FAD. Precipitation and stronger crosswinds likewise tend to delay arrival, whereas higher vegetation anomalies and favorable tailwinds advance arrival. Collectively, our findings clarify how climate, upper-level wind fields, and vegetation jointly shape avian phenology across continental scales.