The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are critical sites for wintering waterfowl. Mapping waterfowl distributions using weather radar aids in the targeted adaptive management by highlighting important waterfowl habitats. Additionally, mapping broadscale waterfowl distributions improves food security by allowing government agencies and commercial poultry operations to better understand the interface between wild and domestic birds that is related to risk of highly pathogenic avian influenza outbreaks. Improving understanding of predictors of wintering waterfowl distributions at both local and landscape scales will allow facility managers and regulatory agencies to make more informed risk management decisions. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl distributions in the CVC and MA as a function of weather, temporal, and environmental characteristics using boosted regression tree modelling. We captured the spatial-temporal variability in effect size of 28 different covariates within two geographic regions which are critical to nationwide waterfowl management and have a high density of commercial poultry. In general, environmental, and geographic predictors had the strongest relative effect on predicting wintering waterfowl distributions in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing waterfowl distributions in both regions throughout the winter. Increasing waterfowl densities in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl distributions in the MA increased closer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote understanding of the predictors of winter waterfowl densities in relationship with biosecurity of commercial poultry nationally.

Despite the recognized role of wild waterfowl in the potential dispersal and transmission of highly pathogenic avian influenza (HPAI) virus, little is known about how infection affects these birds. This lack of information limits our ability to estimate viral spread in the event of an HPAI outbreak, thereby limiting our abilities to estimate and communicate risk. Here we present telemetry data from a wild Lesser Scaup ( Aythya affinis), captured during a separate ecology study in the Chesapeake Bay, Maryland. This bird tested positive for infection with clade 2.3.4.4 HPAI virus of the A/goose/Guangdong/1/1996 (Gs/GD) H5N1 lineage (results received post-release) during the 2021-22 ongoing outbreaks in North America. While the infected bird was somewhat lighter than other adult males surgically implanted with transmitters (790g, mean=868g, n=11), it showed no clinical signs of infection at capture, during surgery, nor upon release. The bird died 3d later, pathology undetermined as the specimen was not able to be recovered. Analysis of movement data within the 3d window showed that the infected individual’s maximum and average hourly movements (3894.3m, 428.8m respectively) were noticeably lower than noninfected conspecifics tagged and released the same day (mean =21594.5m, mean =1097.9m, respectively; n=4). We identified four instances where the infected bird had direct contact (fixes located within 25m and 15 min) with another marked bird during this time. Collectively, these data suggest that the HPAI positive bird observed in this study may have been shedding virus for some period prior to death, with opportunities for direct bird to bird or environmental transmission. Although limited by low sample size and proximity to the time of tagging, we hope that these data will provide useful information as managers continue to respond to this ongoing outbreak event.