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Comparing acoustic and visual monitoring methods for assessing biodiversity and distributions of Arctic‐breeding shorebirds

Year: 2026

Type: article

Abstract: The rapid decline of global bird populations demands effective and efficient monitoring approaches, particularly for shorebirds, which are experiencing significant declines in abundance. Most shorebird monitoring programmes rely on visual surveys, but such surveys face significant challenges in remote locations such as the Arctic where high costs and logistical constraints limit survey effort and duration. We compared data collected from visual area search surveys and acoustic autonomous recording units (ARUs) for monitoring shorebird species in two large regions of Alaska's Arctic Coastal Plain in 2022–2023. We deployed ARUs at 130 sites (55 sites in Arctic National Wildlife Refuge [ANWR]; 75 in Teshekpuk Lake Special Area [TLSA]) where visual surveys were also conducted and examined differences in species richness, encounter rates and predicted distributions for 15 shorebird species. ARU surveys resulted in 50% higher species richness than visual surveys in ANWR and 33% higher at TLSA. Species accumulation curves demonstrated that ARUs required fewer plots to detect the maximum number of species. ARU data enabled species distribution modelling for additional species compared to visual data due to higher encounter rates, resulting in differences in predicted high‐use areas. Visual encounter rates were slightly higher for phalaropes than with ARUs in both regions. Additionally, several rare species were detected in the visual surveys but not in the ARU surveys (e.g. Wilson's Snipe, Western Sandpipers). Synthesis and applications . Our findings demonstrate that ARUs can effectively monitor shorebird species presence, offering advantages in temporal coverage and synchronous data collection across large spatial extents. This may be particularly important in remote regions where traditional monitoring approaches are challenging to implement and sustain.

Source: Journal of Applied Ecology

DOI: 10.1111/1365-2664.70300