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The Central Valley of California is one of the most important regions for wintering waterbirds in North America despite extensive anthropogenic landscape modification and decline of historical wetlands there. Like many other mediterranean-climate ecosystems across the globe, the Central Valley has been subject to a burgeoning human population and expansion and intensification of agricultural and urban development that have impacted wildlife habitats. Future effects of urban development, changes in water supply management, and precipitation and air temperature related to global climate change on area of waterbird habitat in the Central Valley are uncertain, yet potentially substantial. Therefore, we modeled area of waterbird habitats for 17 climate, urbanization, water supply management, and wetland restoration scenarios for years 2006-2099 using a water resources and scenario modeling framework. Planned wetland restoration largely compensated for adverse effects of climate, urbanization, and water supply management changes on habitat areas through 2065, but fell short thereafter for all except one scenario. Projected habitat reductions due to climate models were more frequent and greater than under the recent historical climate and their magnitude increased through time. After 2065, area of waterbird habitat in all scenarios that included severe warmer, drier climate was projected to be >15% less than in the \"existing\" landscape most years. The greatest reduction in waterbird habitat occurred in scenarios that combined warmer, drier climate and plausible water supply management options affecting priority and delivery of water available for waterbird habitats. This scenario modeling addresses the complexity and uncertainties in the Central Valley landscape, use and management of related water supplies, and climate to inform waterbird habitat conservation and other resource management planning. Results indicate that increased wetland restoration and additional conservation and climate change adaptation strategies may be warranted to maintain habitat adequate to support waterbirds in the Central Valley.

While wild waterfowl are known reservoirs of avian influenza viruses and facilitate the movement of these viruses, there are notable differences in the response to infection across species. This study explored differential responses to infection with highly pathogenic avian influenza in Snow Geese ( Anser caerulescens ) located in the California Central Valley. Though H5 antibody prevalence was high across years among birds sampled in the winter (75% in both years via hemagglutination inhibition), these values were even higher among birds sampled in summer that failed to migrate (i.e., August 2023 = 100% and August 2024 = 93% via hemagglutination inhibition). Birds that failed to migrate were also generally lighter than birds sampled in the winter and presented notable damage to cerebrum and cerebellum. In December 2022, a single individual positive for infection with H5N1 at the time of sampling indicated reduced movement during the 14 days following sampling but completed spring migration comparably with uninfected conspecifics. However, while no birds were actively infected during sampling and marking in 2023, two marked geese departed for migration late and one did not migrate at all. Additional banded birds marked in August have been reencountered in scenarios ranging from hunter harvest at a different site over a year later to found dead shortly after banding. Our data indicate that Snow Geese infected with HPAI have the potential to express variable outcomes following infection with highly pathogenic H5N1, ranging from rapid recovery within a migratory season to death. These data also suggest that the abnormal failure of some Snow Geese to migrate from the Central Valley is likely driven by HPAI infection.

Emerging infectious diseases pose threats to wildlife populations, as exemplified by recent outbreaks of avian influenza viruses in wild birds. Climate change can affect infection dynamics in wildlife through direct effects on pathogens (e.g., environmental decay rates) and changes to host ecology, including shifting migration patterns. Here, we adapt an existing mechanistic model that couples migration and infection to study how traits of highly pathogenic avian influenza (HPAI) viruses contribute to HPAI outcomes in migratory waterfowl, then apply this model to explore potential impacts of climate change on HPAI dynamics. We find that the simulated impacts of HPAI on the host population under baseline climate conditions varied from no impact to 100% mortality, depending on viral traits. In most cases, traits related to transmission (i.e., contact rates, shedding rates) were more important for HPAI establishment probability, infection prevalence, and mortality than were other viral traits (e.g., environmental temperature sensitivity, cross-protective immunity). We then simulated the effects of climate change (i.e., altered temperature regimes) on HPAI dynamics both via viral environmental decay and via changes in bird migration phenology. In these simulations, we found that a 9-day advancement in spring migration timing increased the duration of HPAI outbreaks by increasing time birds spent at their breeding grounds, leading to higher mortality and fewer infections. In contrast, increased viral decay in warmer years had a smaller, but opposite impact. These patterns depended on the primary transmission mode of HPAI (i.e., direct vs. environmental) and its sensitivity to environmental temperatures. Together, these results suggest that climate change is likely to increase the impacts of HPAI on waterfowl populations if HPAI relies strongly on direct transmission and birds advance their spring migration. Further integrating host-viral co-evolution and other climatic changes (e.g., salinity, humidity) could provide more precise predictions of how HPAI dynamics could change in the future.

The Central Valley of California (CVC) and Mid‐Atlantic (MA) in the U.S. are both critical sites for nationwide food security, and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using boosted regression tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance 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 relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance 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 relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting ~600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long‐term waterfowl GPS tracking dataset (16 species) with on‐ground disease surveillance data (county‐level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was effective for wild waterfowl, but predictions lagged HPAIv detections in poultry facilities and among some highly impacted nonmigratory species. Our results offer critical advance warning for applied biosecurity management and planning and demonstrate the importance and utility of extensive multispecies tracking to highlight potential high‐risk disease spread locations and more effectively manage outbreaks.

Understanding relationships between infection and wildlife movement patterns is important for predicting pathogen spread, especially for multispecies pathogens and those that can spread to humans and domestic animals, such as avian influenza viruses (AIVs). Although infection with low pathogenic AIVs is generally considered asymptomatic in wild birds, prior work has shown that influenza‐infected birds occasionally delay migration and/or reduce local movements relative to their uninfected counterparts. However, most observational research to date has focused on a few species in northern Europe; given that influenza viruses are widespread globally and outbreaks of highly pathogenic strains are increasingly common, it is important to explore influenza–movement relationships across more species and regions. Here, we used telemetry data to investigate relationships between influenza infection and movement behavior in 165 individuals from four species of North American waterfowl that overwinter in California, USA. We studied both large‐scale migratory and local overwintering movements and found that relationships between influenza infection and movement patterns varied among species. Northern pintails (Anas acuta) with antibodies to avian influenza, indicating prior infection, made migratory stopovers that averaged 12 days longer than those with no influenza antibodies. In contrast, greater white‐fronted geese (Anser albifrons) with antibodies to avian influenza made migratory stopovers that averaged 15 days shorter than those with no antibodies. Canvasbacks (Aythya valisineria) that were actively infected with influenza upon capture in the winter delayed spring migration by an average of 28 days relative to birds that were uninfected at the time of capture. At the local scale, northern pintails and canvasbacks that were actively infected with influenza used areas that were 7.6 and 4.9 times smaller than those of uninfected ducks, respectively, during the period of presumed active influenza infection. We found no evidence for an influence of active influenza infection on local movements of mallards (Anas platyrhynchos). These results suggest that avian influenza can influence waterfowl movements and illustrate that the relationships between avian influenza infection and wild bird movements are context‐ and species‐dependent. More generally, understanding and predicting the spread of multihost pathogens requires studying multiple taxa across space and time.

While wild waterfowl are known reservoirs of avian influenza viruses and facilitate the movement of these viruses, there are notable differences in the response to infection across species. This study explored differential responses to infection with highly pathogenic avian influenza in Snow Geese (Anser caerulescens) located in the California Central Valley. Though H5 antibody prevalence was high across years among birds sampled in the winter (75% in both years via hemagglutination inhibition), these values were even higher among birds sampled in summer that failed to migrate (i.e., August 2023 = 100% and August 2024 = 93% via hemagglutination inhibition). Birds that failed to migrate were also generally lighter than birds sampled in the winter and presented notable damage to cerebrum and cerebellum. In December 2022, a single individual positive for infection with H5N1 at the time of sampling indicated reduced movement during the 14 days following sampling but completed spring migration comparably with uninfected conspecifics. However, while no birds were actively infected during sampling and marking in 2023, two marked geese departed for migration late and one did not migrate at all. Additional banded birds marked in August have been reencountered in scenarios ranging from hunter harvest at a different site over a year later to found dead shortly after banding. Our data indicate that Snow Geese infected with HPAI have the potential to express variable outcomes following infection with highly pathogenic H5N1, ranging from rapid recovery within a migratory season to death. These data also suggest that the abnormal failure of some Snow Geese to migrate from the Central Valley is likely driven by HPAI infection.

Interactions between wildlife and livestock can lead to cross‐species disease transmission, which incurs economic costs and threatens wildlife conservation. Wild waterfowl are natural hosts of avian influenza viruses (AIVs), are often abundant near poultry farms, and have been linked to outbreaks of AIVs in poultry. Interspecific and seasonal variation in waterfowl movement and habitat use means that the risk of disease transmission between wild birds and poultry inevitably varies across species, space, and time. Here, we used GPS telemetry data from 10 waterfowl species in and near California's Central Valley, a region where both wild waterfowl and domestic poultry are abundant, to study selection of poultry farms by waterfowl across diel, seasonal, and annual cycles. We found that waterfowl selected for wetlands, open water, protected areas, and croplands, which meant that they generally avoided habitats that were likely to be used for poultry farming. These selection patterns were linked to species' ecology and diel behavioral patterns, such that avoidance of poultry habitats was stronger for local or partial migrants than for long‐distance migrants, and stronger during daytime than at night. We then combined these habitat selection results with data on poultry farm locations to map risk of waterfowl–poultry contact across the Central Valley. Average selection strength at poultry farms was low, suggesting that current placement of poultry farms is generally effective for limiting risk of contact with wild birds. When we combined these habitat selection results with data on species' abundances and AIV infection prevalence, we found dramatic variation in potential AIV transmission risk among species. These results could be used to prioritize surveillance and biosecurity efforts for regions and times of relatively high risk. More generally, these results highlight that fine‐scale movement data can help identify interspecific, seasonal, and diel patterns in animal behaviors that affect wildlife and poultry health.

While wild waterfowl are known reservoirs of avian influenza viruses and facilitate the movement of these viruses, there are notable differences in the response to infection across species. This study explored differential responses to infection with highly pathogenic avian influenza in Snow Geese (Anser caerulescens) located in the California Central Valley. Though H5 antibody prevalence was high across years among birds sampled in the winter (75% in both years via hemagglutination inhibition), these values were even higher among birds sampled in summer that failed to migrate (i.e., August 2023 = 100% and August 2024 = 93% via hemagglutination inhibition). Birds that failed to migrate were also generally lighter than birds sampled in the winter and presented notable damage to cerebrum and cerebellum. In December 2022, a single individual positive for infection with H5N1 at the time of sampling indicated reduced movement during the 14 days following sampling but completed spring migration comparably with uninfected conspecifics. However, while no birds were actively infected during sampling and marking in 2023, two marked geese departed for migration late and one did not migrate at all. Additional banded birds marked in August have been reencountered in scenarios ranging from hunter harvest at a different site over a year later to found dead shortly after banding. Our data indicate that Snow Geese infected with HPAI have the potential to express variable outcomes following infection with highly pathogenic H5N1, ranging from rapid recovery within a migratory season to death. These data also suggest that the abnormal failure of some Snow Geese to migrate from the Central Valley is likely driven by HPAI infection.