Data and code to compare acoustic ARU and point count data for shorebird species presence across Alaska's North Slope

The rapid decline of global bird populations demands effective monitoring
approaches, particularly for shorebirds, which are experiencing alarming
population decreases. Most shorebird surveys rely on traditional
visual survey methods, but face significant challenges in remote locations
like the Arctic, where high costs and logistical constraints limit survey
effort and duration. We compared visual area search surveys and
acoustic recording units (ARUs) for monitoring shorebird species in two
large regions of Alaska's Arctic Coastal Plain in 2022-2023. We
deployed ARUs at 129 sites (54 in Arctic National Wildlife Refuge, ANWR,
75 in Teshekpuk Lake Special Area, TESH; ~11,000-18,000 hours of acoustic
recordings) where visual surveys were also conducted (~83-113 hours in
total), and examined differences in species richness, encounter rates, and
predicted distribution patterns for 12 shorebird species or species
groups. ARUs detected 50% higher species richness in ANWR and 33%
at TESH (approximately 2 additional species per plot); the odds of
encountering a species were more than twice as high with ARUs compared to
visual surveys (95%CI = 1.64-5.57). Species accumulation curves
demonstrated that ARUs required fewer plots to detect the maximum number
of species. Habitat models based on ARU data produced similar predicted
distributions to visual survey data but enabled modeling for additional
species due to higher encounter rates. Different survey methods
showed consistent spatial patterns between sites, with both methods
detecting higher species richness and encounter rates in TESH than in
ANWR. Our findings demonstrate that ARUs can effectively monitor
shorebird communities in the Arctic, offering advantages in temporal
coverage and synchronous data collection across large spatial extents. The
performance of ARUs for detecting most shorebird species over long periods
supports their integration into conservation monitoring programs,
particularly in remote regions where traditional monitoring approaches are
challenging to implement and sustain.