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.

As social media becomes an ever-increasing staple of everyday life and a growing percentage of people turn to community driven platforms as a primary source of information, the data created from these posts can provide a new source of information from which to better understand an event in near real-time. The 2018-2020 outbreak of virulent Newcastle Disease (vND) in Southern California is the third outbreak of vND in Southern California within a 50-year time span. These outbreaks are thought to be primarily driven by non-commercial poultry (i.e. backyard and game fowl) in the region. Here we employed a commercial “web crawling” tool between June of 2018 and July of 2020 which encompassed the majority of the outbreak in order to collect all available online mentions of virulent Newcastle Disease (vND) in relation to the outbreak. A total of 2,498 posts in English and Spanish were returned using a Boolean logic-based string search. While the number of posts was relatively small, their impact as measured by the number of visitors to the website and the number of people viewing the post (where provided) was much larger. Using views as a metric, Twitter was identified as the most significant source of comments over blogs, forums and other news sites. Posts with negative sentiment were found to have a larger audience relative to posts with a positive sentiment. In addition, posts with negative sentiment peaked in May of 2019 which preceded the formation of the anti-depopulation group Save Our Birds (SOB). As the usage and impact of social media grows, the ability to utilize tools to analyze social media may improve both response and outreach-based strategies for various disease outbreaks including vND in Southern California which has a large non-commercial poultry population.