Data from: The performance of drones and artificial intelligence for monitoring sage-grouse at leks

We evaluated the effectiveness of drone-based survey protocols combined
with an AI count model relative to traditional ground-based visual surveys
for counting sage-grouse at leks. Drone-induced flushing of sage-grouse
from leks occurred in 16% of flight attempts. Point-of-interest (POI)
flight profiles outperformed linear flight profiles in counting accuracy
for both AI and manual methods. POI flights provided more images and a
larger field of view, resulting in counts similar to traditional
ground-based visual (GBV) lek surveys, while linear flights consistently
produced undercounts. Our custom AI counter (INDECS) yielded counts of
sage-grouse similar to manual counts in POI surveys, but not in linear
surveys. When integrated into modified N-mixture models, drone surveys
with POI profiles yielded precise estimates of detection probabilities and
abundance for all survey methods that resulted in similar inference to GBV
surveys. Our results suggest that AI-enhanced drone surveys, particularly
with POI flight profiles, offer a promising alternative to traditional
surveys with reduced bias and improved consistency in sage-grouse
population monitoring.