The American Woodcock Singing Ground Survey largely conforms to the phenology of male woodcock migration

American woodcock (Scolopax minor; woodcock) are monitored, in part, by counts of displaying male woodcock collected via the American Woodcock Singing Ground Survey (SGS), which suggests long-term, range-wide declines in woodcock populations. Data from the SGS have been used extensively to develop conservation plans, direct management actions, and understand causes of decline. To avoid bias, the SGS should be timed to avoid spring migration, and the distribution of survey routes should coincide with woodcock breeding distribution. Our objectives for this research were to evaluate SGS timing with the phenology of male woodcock migration, relate the spatial coverage of the SGS to male woodcock breeding distributions, and explore other sources of variation in woodcock migration timing. We marked 133 male woodcock captured throughout eastern North America with global positioning system (GPS) transmitters during 2019-2022, and compared the timing of their spring migration with the spatiotemporal stratification of the SGS. Most woodcock (74%) completed migration prior to the onset of the SGS. In the northernmost SGS zone, a greater percentage of males (34%) continued migration during the survey window; however, the influence of this mismatch is offset because SGS routes were run more frequently during the second half of the window. Young woodcock completing their first spring migration took 8.6 days longer to do so, on average, compared to adults, and so were more likely to migrate during the SGS window. We found little evidence that timing of migration varied among years. Existing SGS routes cover the majority of male woodcock post-migratory breeding distribution, with 90% of male woodcock establishing final breeding sites within the spatial coverage of the SGS. Our results confirm the SGS includes some migrating males, with the proportion relative to resident breeding males increasing in more northern survey strata. Our data suggests these errors are unlikely to bias trend estimates at large scales (e.g., within woodcock management regions), but there may be potential for bias at more local scales (e.g., state or provincial population indices).