Geology topics

Elliott Matchett

Publications and source records attributed to Elliott Matchett.

At least 19 recordsLinked to original sources

USGS2026

Impact of fog on California waterfowl flight activity: Historical and modern insights into effects post-Clean Air Act

Since establishment of the Clean Air Act in the early 1970s, occurrence of the dense ‘Tule Fog’, historically prevalent throughout winter across California’s Central Valley, has substantially reduced. At the same time, waterfowl body masses have generally increased. Flight is metabolically expensive, and fog visually and navigationally impairs birds in flight, likely causing them to remain aloft for longer than usual periods. If less fog results in less flight and reduced energy expenditure, then fewer winter Tule fog events could contribute to increased body masses of California waterfowl since the mid-1980’s. Therefore, we aimed to assess the relationship between waterfowl flight and fog occurrence/density with historic (1991–93) and modern (2015–23) waterfowl tracking data in the Central Valley of California (CCV). Historic tracking data showed that the probability of flight increased with increasing fog density. Birds were significantly more likely to fly in fog than when there was no fog and most likely to fly in heavy fog . Modern data showed similar responses to fog with flight occurring significantly more during dawn fog events. This relationship between improved waterfowl body mass and fewer fog events may provide an opportunity to redirect scarce funding to focus on other population requirements such as improving habitats for nesting, molting and brood rearing that are currently lacking. Unanticipated benefits of the Clean Air Act should stand as a strong recommendation to maintaining this Act into the future.

California↗

USGS2025

Host responses and viral traits interact to shape the impacts of climate warming on highly pathogenic avian influenza in migratory waterfowl

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.

Alaska, California, Oregon↗

USGS2025

Potential impacts of 2.3.4.4b highly pathogenic H5N1 avian influenza virus infection on Snow Goose (Anser caerulescens) movement ecology

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.

California↗

USGS2024

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

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.

California, Delaware, Maryland, New Jersey, North ↗

USGS2024

Imperiled Great Basin terminal lakes: Synthesizing ecological and hydrological science gaps and research needs for waterbird conservation

Terminal lakes are declining globally because of human water demands, drought, and climate change. Through literature synthesis and feedback from the resource and conservation community, we review the state of research for terminal lakes in the Great Basin of the United States, which support millions of waterbirds annually, to prioritize ecological and hydrologic information needs. From an ecological perspective, research priorities include measuring the underlying differences in waterbird resource selection and distribution, migratory connectivity, abiotic factors that interact with prey densities to affect prey availability, and waterbird fitness or demography. Integrated links between water availability, water quality, and food webs are lacking in the literature. Scarce water availability data hinder the current knowledge of water extraction and evapotranspiration rates. Research that can address these priorities would help advance our understanding of how the Great Basin terminal lakes function as an interrelated system and support conservation efforts to reverse the decline of these critical lakes.

California, Nevada, Oregon, Utah↗

USGS2024

Mitigating risk: Predicting H5N1 avian influenza spread with an empirical model of bird movement

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 (Dec 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 non-migratory species. Our results offer critical advance warning for applied biosecurity management and planning and demonstrate the importance and utility of extensive multi-species tracking to highlight potential high-risk disease spread locations and more effectively manage outbreaks.

Transboundary and Emerging Diseases↗

USGS2024

Potential use of poultry farms by wild waterfowl in California's Central Valley varies across space, times of day, and species: implications for influenza transmission risk

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.

California↗

USGS2024

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), 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.

Authorea↗

USGS2023

Waterfowl recently infected with low pathogenic avian influenza exhibit reduced local movement and delayed migration

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.

Ecosphere↗

USGS2023

Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California

In arid and Mediterranean regions, landscape-scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail ( Anas acuta ), Green-winged Teal ( Anas crecca ), and Northern Shoveler ( Anas clypeata ), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance-weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real-time (hereafter “real-time”) covariates in which duck observations were matched to the water availability within the 16-day window of a Landsat observation, (2) a combination of real-time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long-term average covariates—the most common approach to species distribution modeling—in which long-term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long-term average climate conditions were compared to models based on real-time conditions, the highest long-term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.

California↗

USGS2023

Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate

Scientists, resource managers, and decision-makers increasingly use knowledge co-production to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley, USA to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We co-produced scenario narratives, spatially-explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We document our co-production process, and using the co-produced models, we ask: “when and where do management actions make a difference?” and “when does climate override these actions?” The outcomes of this process provide lessons learned on how to co-create usable information and how to increase climate adaptive capacity in a highly managed landscape. We found that: 1) actions to restore wetlands and prioritize their water supply create habitat outcomes resilient to climate change impacts particularly in March, when habitat is most limited, 2) land protection combined with management can increase the ecosystem's resilience to climate change, and 3) the uptake and use of this information was influenced by the roles of different stakeholders, plus rapidly changing water policies, discrepancies in decision-making time frames, and immediate crises of extreme drought. While a broad stakeholder group contributed knowledge to scenario narratives and model development, to co-produce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped to build legitimacy, yet broad-scale use of climate adaptation knowledge will depend on state and local policies, engagement with decision-makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.

California↗

USGS2022

Avian influenza antibody prevalence increases with mercury contamination in wild waterfowl

Environmental contamination is widespread and can negatively impact wildlife health. Some contaminants, including heavy metals, have immunosuppressive effects, but prior studies have rarely measured contamination and disease simultaneously, which limits our understanding of how contaminants and pathogens interact to influence wildlife health. Here, we measured mercury concentrations, influenza infection, influenza antibodies, and body condition in 749 individuals from 11 species of wild ducks overwintering in California. We found that the odds of prior influenza infection increased more than five-fold across the observed range of blood mercury concentrations, while accounting for species, age, sex, and date. The prevalence of influenza infection was also higher in species with higher average mercury concentrations. We detected no relationship between influenza infection and body fat content. This positive relationship between influenza prevalence and mercury concentrations in migratory waterfowl suggests that immunotoxic effects of mercury contamination could promote the spread of avian influenza along migratory flyways, especially if influenza has minimal effects on bird health and mobility. More generally, these results show that the effects of environmental contamination could extend beyond the geographic area of contamination itself by altering the prevalence of infectious diseases in highly mobile hosts.

Proceedings of the Royal Society B↗

USGS2022

Yuma Ridgway’s rail selenium exposure and occupancy within managed and unmanaged emergent marshes at the Salton Sea

Yuma Ridgway’s rail ( Rallus obsoletus yumanensis , hereafter, rail) is an endangered species for which patches of emergent marsh within the Salton Sea watershed comprise a substantial part of habitat for the species’ disjointed range in the southwestern United States. These areas of emergent marsh include (1) marshes managed by federal (particularly the U.S. Fish and Wildlife Service’s Sonny Bono Salton Sea National Wildlife Refuge), state (California Department of Fish and Wildlife), and local (Imperial Irrigation District) resource agencies that are sustained by direct deliveries of Colorado River water and (2) unmanaged marshes sustained by agricultural drainage water. Management of rail habitat in this arid environment is complicated by increasingly limited availability of unimpaired freshwater owing to water management decisions associated with the Quantification Settlement Agreement and risks posed by potentially harmful concentrations of selenium found in agricultural drainage water that can readily bioaccumulate in aquatic food webs. To provide timely science for managers, herein we report summary statistics for managed and unmanaged emergent marshes sampled at the Salton Sea during the rail breeding season of 2016 pertaining to (1) selenium concentrations in food webs representing dietary pathways of selenium exposure and (2) patterns of rail occupancy and inter-marsh movements, estimated abundance, and regional population size of rail. For selenium-specific objectives, we sampled unfiltered surface water, midge larvae (Chironomidae), water boatmen (Corixidae), mosquitofish ( Gambusia spp.), and crayfish (Astacidae). Selenium samples were collected from 15 fixed sampling points, each in managed and unmanaged marshes, during late February, April, and June 2016, which corresponded to rail pre-nesting, nesting, and fledgling reproductive life-stages, respectively. Two areas within the two treatment types (managed versus unmanaged marsh) were of particular interest to help assess risks associated with changing sea dynamics and different water-management strategies: (1) a large unmanaged marsh (Morton Bay) unintentionally created in approximately 2008 when it became separated from the Salton Sea as water inflows began to drop and a berm formed from accumulated sediment and (2) a restored marsh (HZ9A) managed by the Sonny Bono Salton Sea National Wildlife Refuge, which is currently supplied with Colorado River water but may be sustained in the future by a blend of clean (that is, low selenium) Colorado River and agricultural drainage water with higher selenium from the Alamo River. Hence, baseline data for these marshes are important for future management decisions. We also report selenium concentrations in rail blood, head feathers, and breast feathers from rails captured as part of the movement study. Results indicated relatively higher risks from dietary selenium exposure for rails occupying unmanaged marshes compared to managed marshes and similar risks among unmanaged marshes. However, risks also were potentially elevated for rails occupying some managed marshes (that is, the Hazard Marshes), where relatively high proportions of Chironomidae and mosquitofish exceeded dietary thresholds for selenium effects on avian reproduction. For rail-specific objectives, we quantified occupancy and spatial distribution using call count data analyzed with imperfect detection models. Imperfect detection models allowed us to jointly estimate detection probability and abundance of detected rails in association with habitats. We then used estimates of detection probability and abundance at the habitat level to extrapolate rail population abundance for the Salton Sea region. Inter- and intra-marsh movements were described from over 5,000 locations obtained from 15 radio-marked rails. Resultant space use patterns indicated that, in general, selenium risk to individuals is not equally shared because of high levels of territoriality and very limited movement throughout the landscape. Moreover, the largest contiguous blocks of habitat are associated with unmanaged marshlands located on the former southeastern shoreline and outside traditional management areas and authorities. Thus, a substantial proportion of the rail population that is using unmanaged marsh on the southeastern shoreline may have disproportionate risk of elevated selenium exposure, yet how that risk translates to population-level effects remains unknown.

California↗

USGS2022

Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl

Background Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”. Methods Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models. Results Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting). Conclusions Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing.

Movement Ecology↗

USGS2022

Pathways for avian influenza virus spread: GPS reveals wild waterfowl in commercial livestock facilities and connectivity with the natural wetland landscape

Zoonotic diseases are of considerable concern to the human population and viruses such as avian influenza (AIV) threaten food security, wildlife conservation and human health. Wild waterfowl and the natural wetlands they use are known AIV reservoirs, with birds capable of virus transmission to domestic poultry populations. While infection risk models have linked migration routes and AIV outbreaks, there is a limited understanding of wild waterfowl presence on commercial livestock facilities, and movement patterns linked to natural wetlands. We documented 11 wild waterfowl (three Anatidae species) in or near eight commercial livestock facilities in Washington and California with GPS telemetry data. Wild ducks used dairy and beef cattle feed lots and facility retention ponds during both day and night suggesting use for roosting and foraging. Two individuals (single locations) were observed inside poultry facility boundaries while using nearby wetlands. Ducks demonstrated high site fidelity, returning to the same areas of habitats (at livestock facilities and nearby wetlands), across months or years, showed strong connectivity with surrounding wetlands, and arrived from wetlands up to 1251 km away in the week prior. Telemetry data provides substantial advantages over observational data, allowing assessment of individual movement behaviour and wetland connectivity that has significant implications for outbreak management. Telemetry improves our understanding of risk factors for waterfowl–livestock virus transmission and helps identify factors associated with coincident space use at the wild waterfowl–domestic livestock interface. Our research suggests that even relatively small or isolated natural and artificial water or food sources in/near facilities increases the likelihood of attracting waterfowl, which has important consequences for managers attempting to minimize or prevent AIV outbreaks. Use and interpretation of telemetry data, especially in near-real-time, could provide key information for reducing virus transmission risk between waterfowl and livestock, improving protective barriers between wild and domestic species, and abating outbreaks.

Transboundary and Emerging Diseases↗

USGS2022

Climate and land change impacts on future managed wetland habitat: A case study from California’s Central Valley

Concept California’s Central Valley provides critical habitat for migratory waterbirds, yet only 10% of naturally occurring wetlands remain. Competition for limited water supplies and climate change will impact the long-term viability of these intensively managed habitats. Objectives Forecast the distribution, abundance, and connectivity of surface water and managed wetland habitats, using 5 spatially explicit (270 m 2 ) climate/land use/water prioritization scenarios. Mapping potential future dynamic flooded habitat used by waterbirds and other wetland-dependent wildlife to inform management decisions. Methods We integrated a climate-driven hydrologic water use model with a spatially explicit land change model, to examine stakeholder-driven scenarios of future land change, climate, and water use and their impacts on future habitat availability. Results Declining water availability is the dominant driver of habitat loss across scenarios. The hot/dry scenarios showed the greatest declines in January flooded area by 2101—an important month for overwintering waterbirds. In contrast, higher water supplies in wet climates drive perennial cropland conversion and loss of potential habitat. Potential flooded cropland declined (25 and 33%) under warmer/wetter climate conditions due to this conversion to perennial crops, exposing habitat vulnerability. Conclusion Climate-driven loss of water availability had a greater impact on flooded habitat availability than land-use change. When combined, climate change and the conversion of potentially flooded cropland to perennial cropland will threaten future waterbird habitat particularly in January, the peak of the migratory bird season, even when habitat restoration goals are met. Stakeholder-informed scenario analysis can identify target areas for potential habitat change, vulnerability, and conservation.

California↗

USGS2021

Megafires and thick smoke portend big problems for migratory birds

In 2020, the fire season affecting the western United States reached unprecedented levels. The 116 fires active in September consumed nearly 20,822 km 2 ( https://inciweb.nwcg.gov/accessible-view/ Accessed 2020-09-29) with eighty percent of this footprint (16,567 km 2 ) from 68 fires occurring within California, Oregon, and Washington. Although the 2020 fire season was the most extreme on record, it exemplified patterns of increased wildfire size, number, timing, return frequency, and extent which are linked to climate-driven changes in precipitation and temperature affecting fire ignition and severity (Westerling 2016, Goss et al. 2020, Weber and Yadav 2020).

California, Oregon, Washington↗

USGS2021

Using high resolution satellite and telemetry data to track flooded habitats, their use by waterfowl, and evaluate effects of drought on waterfowl and shorebird bioenergetics in California

Wetland managers in the Central Valley of California, a dynamic hydrological landscape, require information regarding the amount and location of existing wetland habitat to make decisions on how to best use water resources to support multiple wildlife objectives, particularly during drought. Scientists from the U.S. Geological Survey Western Ecological Research Center (WERC), Point Blue Conservation Science (Point Blue), and the U.S. Fish and Wildlife Service (USFWS) partnered to learn how wetland and flooded agricultural habitats used by waterfowl and shorebirds change during the non-breeding season (July–April) particularly during drought. During extreme drought conditions, the ability to provide sufficient water for wildlife often depends on the timing of water deliveries to managed wetlands and winter-flooded crop fields and decisions on whether to fallow croplands. Waterfowl and shorebirds could be particularly affected by these decisions because they typically rest and feed in flooded habitats. Poor habitat conditions resulting from spatially or temporally suboptimal water deliveries (that is, mismatch between waterfowl habitat needs and timing and location of flooded habitats) could reduce waterfowl hunting opportunities and body condition. Point Blue scientists developed a system for near real-time tracking of habitats used by waterfowl, shorebirds, and some other wetland-dependent “waterbirds” ( www.pointblue.org/watertracker ) and to assess the impacts of drought on habitat availability and on waterfowl and shorebird bioenergetics. The WERC researchers linked these data with near real-time tracking (telemetry) data of duck locations throughout the Valley. The team used these two datasets to relate duck locations to open-water characteristics and to learn how waterfowl use habitats under spatially and temporally changing conditions during drought and non-drought periods. We found that recent extreme drought (2013–15) significantly changed the timing and magnitude of flooding and consequently reduced the availability of habitats used by waterfowl and shorebirds more than other recent historic droughts 2000–11. Drought reduced irrigations of moist soil seed plants and thus there was lower food energy available for waterfowl. Analyses using bioenergetics models indicated that, overall, extreme drought increased food energy deficits (total number of deficit days) for shorebirds and waterfowl. Our analysis indicated a strong direct relationship between duck locations and classified habitat derived from open-water data during the wintering period (October–March). This result helps confirm the application of dynamic water data to identify flooded areas that provide waterfowl habitat. Presence of open water at a 1-hectare resolution can be used effectively to identify flooded landscape areas available as habitat for ducks. Our discoveries from evaluating use of space by ducks also indicated that nighttime feeding locations of ducks were concentrated nearby primary roosts and that foraging distances could depend on hydrologic dynamics of location (Suisun Marsh versus California excluding Suisun Marsh) and time of season (early, middle, late). Other results indicated that some areas on the California landscape with extremely reliable water supplies could receive consistent use by ducks year after year (in essence, almost drought proof). The Water Tracker is set up to automatically track wetland habitat and food availability each year and is making these data available to water and wetland managers. Results from this research are a significant step toward understanding how waterfowl and shorebird habitats can be optimally managed on the landscape to support desired populations of these migratory birds during extreme drought.

California↗