REAL-TIME WATERFOWL MAPPING WEB APP: A CRITICAL & NOVEL TOOL FOR AVIAN INFLUENZA SURVEILLANCE TO IMPROVE FOOD SECURITY IN COMMERCIAL POULTRY

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: AFRI COMPETITIVE GRANT
• Reporting Frequency: Annual
• Accession No.: 1022185
• Grant No.: 2020-68014-30975
• Cumulative Award Amt.: $1,000,000.00
• Proposal No.: 2019-08260
• Project Start Date: Jul 1, 2020
• Project End Date: Jun 30, 2024
• Grant Year: 2020
• Program Code: [A1181]- Tactical Sciences for Agricultural Biosecurity

Recipient Organization
UNIV OF CALIFORNIA (VET-MED)
(N/A)
DAVIS,CA 95616

Performing Department
VM: Extension/Public Programs

Non Technical Summary
This proposal aims to develop and validate a near-real-time predictive waterfowl tracking system in two areas (Central Valley of California and Mid-Atlantic coast across Delaware, Maryland, Virginia, and North Carolina) with high waterfowl and commercial poultry populations (Figure 1). After validation, this approach could be further expanded to other poultry dense areas of the U.S. that spatially and temporally interface with waterfowl. Our goal is to leverage a series of well- demonstrated and cutting edge remote sensing technologies and research products including:NEXt generation RADar (NEXRAD) for waterfowl roosting location and densityHigh spatial resolution and temporal frequency waterfowl telemetry (i.e. location tracking) dataSatellite imagery and land-based sensing for tracking dynamic changes in surface water and land cover (i.e. waterfowl habitat) which are used to build predictive statistical models with respect to waterfowl location and density in near real-time in the Central Valley of California and the Mid-Atlantic coast andHigh-sensitivity ultra-filtration of wetland water and whole-segment M-RTPCR of AIV of wetland water, sediment and cloacal waterfowl samples . We will leverage NEXRAD, telemetry, and the geospatial habitat data to identify and target selected habitat (water and sediment) at high and low waterfowl densities in order to understand the viral ecology of AIV in wetlands in close proximity to commercial poultry.Specifically, we will collect cloacal swabs from waterfowl, wetland sediment and water for ultra-filtration (e.g. 10 gallons of wetland water will be filtered to less than 50 ml in order to concentrate virus). Subsequent M-segment RT-qPCR, whole-segment M-RTPCR and sequencing will be used to establish the relationship between waterfowl density and AIV viral prevalence in water, sediment and associated waterfowl. Our initial results which are in review by the Journal Transboundary & Emerging Diseases4 demonstrate that ultra-filtration in combination with the whole segment RT-PCR is superior to commonly used detection methods for AIV in water (i.e. no filtration with M-segment qPCR) which are well known to lack sensitivity and are not considered representative of AIV prevalence.5The above described data will be integrated into near-real-time predictive models which will be further validated and subsequently deployed as a web-app that poultry farmers, veterinarians, and regulators (USDA-APHIS and state departments of agriculture) can use as a risk-management tool to assess and manage risk related to AIV transmission to poultry from waterfowl.The combined analysis of waterfowl location, density, AIV presence and the molecular ecology of AIVs in waterfowl and the associated environment can better inform producers and other stakeholders enabling enhanced biosecurity practices (i.e. changes in husbandry practices, repairs to farm facilities and equipment, increased utilization of car-wash stations, foot baths, limiting sharing of equipment and workers between risky and non-risky farms). Similarly, the analysis of these data could significantly improve decision making (i.e. processing a flock early, placing of a flock later, and triaging veterinary visits) at an individual farm level during times of increased risk. To promote enhanced biosecurity decisions, from an extension perspective in year one we will use our university extension capabilities to develop a multi-disciplinary advisory team which will help guide web-app development with the goal of maximizing adoption of the web-app for various stakeholders. During years 2-4, the web-app will be beta tested and disseminated to stakeholders in a series of extension- based workshops across the Central Valley of California and the Mid-Atlantic Coast area by UC Davis and University of Delaware faculty and extension faculty. Additionally, surveys evaluating the web-app will be delivered to producers and other relevant stakeholders in years 2-4 electronically and via in-person extension based meetings in order to optimize the functionality/usability of the web-app.

Animal Health Component

100%

Research Effort Categories

Basic

(N/A)

Applied

100%

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
311	0820	1101	50%
311	0820	1170	50%

Knowledge Area
311 - Animal Diseases;

Subject Of Investigation
0820 - Wild birds;

Field Of Science
1101 - Virology; 1170 - Epidemiology;

Keywords

avian influenza

remote sensing

surveillance

waterfowl tracking

wetland water

whole segment pcr

Goals / Objectives
Process recent NEXRAD observations of waterfowl distributions in CA and Mid-Atlantic.Analyze historical telemetry data of waterfowl distributions in the Pacific Flyway.Collect new telemetry data of waterfowl distributions in the Mid-Atlantic.Develop statistical models to predict waterfowl distributionsbased upon NEXRAD and telemetry observations and remotely-sensed environmental predictor variables including satellite imagery.Sample water, sediment & waterfowl for AIV abundance in 6 watersheds (3 in CA & 3 in the Mid-Atlantic).Link waterfowl species within sampled watersheds to likely AIV host species and test for correlation between AIV abundance and various waterfowl density model outputs.Develop web-app of near-real-time predicted waterfowl distributions in the Central Valley of California and the Mid-Atlantic.Extension Tasks:Develop multi-disciplinary extension advisory team (separate bi-annual meetings in CA and DE.In order to evaluate progress: survey producers & other stakeholders to optimize web-app development.Hold extension based meeting for beta testing, feedback, and analytics of the web-app.?From a broader perspective:A. Produce near real time predictions of wild waterfowl distributions in regions of high commercial poultry density in the Central Valley of California and the Mid-Atlantic coast based on NEXRAD (Figure 1 and 2b), models that utilize satellite and land-based remote sensing (Figure 2a) and waterfowl telemetry data (Figure 3).Use historical waterfowl distribution data collected in Objective I to identify 6 wetlands across the Pacific and Atlantic Flyways of high waterfowl density (i.e., potentially high AIV risk) to further validate the efficacy of sampling wetlands (water and sediment) for AIVs using ultrafiltration of wetland water linked to whole-segment RT-PCR and metagenomics of those whole-segment AIVs in wetlands. These results will be compared to direct sampling of waterfowl via standard molecular and virus isolation methods. Samples (sediment and 10L water samples) will be taken from each wetland and associated waterfowl quarterly over a 2-year period in order to better understand the qualitative and quantitative ebb and flow of the virus in the wetland environment. We will use e-Bird 15, a citizen science dataset of bird observations, to identify waterfowl species present in the study areas and link the results to our wetland sequencing data. These data will be used to help validate the species information gained by comparing the AIV sequences (from the whole-segment M-RTPCR) with the hosts those sequences were associated with using the NIAID Influenza Research Database (IRD).16Develop a user-friendly web-app that stakeholders and poultry producers in California Central Valley and the Mid-Atlantic (Figure 1) can use as a near real-time predictive tool to understand waterfowl location, density, and AIV presence and type.Develop a robust extension-based advisory team and associated extension-based workshops and on-line tools to increase awareness and adoption of the predictive web-app.

Project Methods
Process recent NEXRAD observations of waterfowl distributions in CA and Mid-Atlantic.Analyze historical telemetry data of waterfowl distributions in the Pacific Flyway.Collect new telemetry data of waterfowl distributions in the Mid-Atlantic.Develop statistical models to predict waterfowl distributionsbased upon NEXRAD and telemetry observations and remotely-sensed environmental predictor variables including satellite imagery.Sample water, sediment & waterfowl for AIV abundance in 6 watersheds (3 in CA & 3 in the Mid-Atlantic) (Table 2).Link waterfowl species within sampled watersheds to likely AIV host species and test for correlation between AIV abundance and various waterfowl density model outputs.Develop web-app of near-real-time predicted waterfowl distributions in the Central Valley of California and the Mid-Atlantic.Extension Tasks:Develop multi-disciplinary extension advisory team (separate bi-annual meetings in CA and DE.In order to evaluate progress: survey producers & other stakeholders to optimize web-app development.Hold extension based meeting for beta testing, feedback, and analytics of the web-app.

Progress 07/01/20 to 06/30/24

Outputs
Target Audience:The target audience are poultry companies and state and federal departments of agriculture. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?We have graduated 2 MS students and have worked with poultry veterinarians from multiple companies with a focus on training farmers and their company veterinarians how best to mitigate HPAI exposure with a focus on off-farm factors. How have the results been disseminated to communities of interest?See above comments. In short we have given over 50 extension and scientific talks. What do you plan to do during the next reporting period to accomplish the goals?N/A

Impacts
What was accomplished under these goals? The above radar and telemetry models have been expanded to over 20 states in the U.S. over 50 meetings with poultry producers have been completed representing the majority of the U.S. poultry, turkey and broiler producers We have developed risk models for one large turkey company that showed an increase in the postiive predictive value (predictive ability to identify HPAI outbreaks) by 3.5x over the method that just uses farm level biosecurity We have developed a web-app in over 20 states that has been commercialized and further expanded into Canada.

Publications

• Type: Peer Reviewed Journal Articles Status: Accepted Year Published: 2021 Citation: Acosta, Sarai, Todd Kelman, Shane Feirer, Elliott Matchett, Jaclyn Smolinsky, Maurice Pitesky, and Jeffrey Buler. "Using the California waterfowl tracker to assess proximity of waterfowl to commercial poultry in the central valley of California." Avian Diseases 65, no. 3 (2021): 483-492.
• Type: Peer Reviewed Journal Articles Status: Published Year Published: 2020 Citation: McCuen, Madeline M., Maurice E. Pitesky, Jeffrey J. Buler, Sarai Acosta, Alexander H. Wilcox, Ronald F. Bond, and Samuel L. D�az?Mu�oz. "A comparison of amplification methods to detect Avian Influenza viruses in California wetlands targeted via remote sensing of waterfowl." Transboundary and Emerging Diseases 68, no. 1 (2021): 98-109.
• Type: Peer Reviewed Journal Articles Status: Accepted Year Published: 2024 Citation: Teitelbaum, Claire S., Michael L. Casazza, Cory T. Overton, Jeffery D. Sullivan, Elliott L. Matchett, Fiona McDuie, Austen A. Lorenz, Joshua T. Ackerman, Susan EW De La Cruz, and Diann J. Prosser. "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." Ecography (2024): e06939.
• Type: Other Journal Articles Status: Published Year Published: 2024 Citation: Hardy, Matthew J., Christopher K. Williams, Brian S. Ladman, Maurice E. Pitesky, Cory T. Overton, Michael L. Casazza, Elliott L. Matchett, Diann J. Prosser, and Jeffrey J. Buler. "Examining inter?regional and intra?seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways." Journal of Avian Biology (2024): e03296.

Progress 07/01/22 to 06/30/23

Outputs
Target Audience:Commercial poultry producers accross the U.S. and the entire commercial poultry industry. We have given over 25 extension based talks on how to use the waterfowl alert network to understand waterfowl abundance and occupancy in close proximity to commercial poultry. We have also presented telemetry based disease modeling that demonstated during the summer of 2022 that we were likely to have a high amount of infected wild species of birds which could severely impact the U.S. poultry industry. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?We have a MS student at University of Delaware who is using the radar and telemetry modeling for his MS How have the results been disseminated to communities of interest?We have reported the disease modeling and radar/telemetry modeling at over 25 extension based meeting in anticipation of the current and at the time expanding HPAI outbreak. What do you plan to do during the next reporting period to accomplish the goals?Further telemetry modeling in the Delmarva. Complete sequencing analysis of wetlands and waterfowl

Impacts
What was accomplished under these goals? Radar and Telemetry based predictive modeling for the Central Valley of California and the Delmarva (radar only) Enhanced user interface Commercial licensure and expansion of the tool accross the midwest of the U.S.

Publications

• Type: Journal Articles Status: Accepted Year Published: 2021 Citation: McCuen, Madeline M., Maurice E. Pitesky, Jeffrey J. Buler, Sarai Acosta, Alexander H. Wilcox, Ronald F. Bond, and Samuel L. D�az?Mu�oz. "A comparison of amplification methods to detect Avian Influenza viruses in California wetlands targeted via remote sensing of waterfowl." Transboundary and emerging diseases 68, no. 1 (2021): 98-109.

Progress 07/01/21 to 06/30/22

Outputs
Target Audience:The primary target audience are various stakeholders associated with poultry including commercial, backyard, state departments of food and agriculture and the USDA. Changes/Problems:The current outbreak of HPAI has been significant for this project. Because there has been so much interest we were encouraged by several poultry companies and the USDA to commercial the waterfowl tracker. We have just been granted the license for the waterfowl tracker from UC Davis and we are now commercializing the tool with the goal of making it a sustainable tool (as opposed to a grant which has some instability based on consistent acceptance of the grant). We believe this will make this tool robust and help utilize the remote technology developed under this grant for various stakeholders in the commercial poultry industy including commercial poultry, backyard poultry owners and state and federal departments of food and agriculture. What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?Yes. I have given multiple extension talks about using radar as a remote sensing tool for waterfowl presence/absence and density at high spatial resolution. Talk include:USAHA, National Turkey Federation, Pacific Egg and Poultry Association, California Poultry Federation annual meetings. What do you plan to do during the next reporting period to accomplish the goals?Continued sampling of waterfowl per our objectives to understand the relationship between waterfowl and AI prevelanece and distribution in wetlands in California and the Delmarva Peninsula.

Impacts
What was accomplished under these goals? We have a functioning web app for the California Central Valley that operates between 11/1 and 3/31 and gives daily predictions Our advisory team has given us further insights on what aspects of the web-app are most relevant to the commercial poultry industry and beyond. Our preliminary PCR and sequencing results suggest that the mutli-segment PCR is more sensitive and amplifiies a wider range of influenza viruses than the traditional Spackman primers The ability to use remote sensing to understand waterfowl distributions using a combination of radar, satellite imagery and various environmental paramers (as determined using a Boosted Regression Tree (BRT) model) effectively predicts waterfowl presence/absence and density

Publications

• Type: Journal Articles Status: Published Year Published: 2021 Citation: Using the California Waterfowl Tracker to Assess Proximity to Commercial Poultry in the Central Valley of California

Progress 07/01/20 to 06/30/21

Outputs
Target Audience:Commercial poultry producers in California and the Delmarva Peninsula and associated state and federal stakeholders who are keen to better understand how best to do surveillance for Avian Influenza. Changes/Problems:Supply chain challenges have made it difficult to order certain supplies including our pump drive and even pipette tips. This has caused some delays in sampling. What opportunities for training and professional development has the project provided?This grant supports Matthew Hardy who is a MS student at the University of Delaware How have the results been disseminated to communities of interest?Results have been presented at the 2021 AAAP (American Association of Avian Pathologists) annual meeting. Results have also been shared in the extension newsletter: Poultry Ponderings. What do you plan to do during the next reporting period to accomplish the goals?Now that our wetland locations in the Delmarva Peninsula and Central Valley of California have been selected we will be sampling AI in the wetland environment and waterfowl in these selected locations. Transition of the current CA waterfowl tracker (CWT) to an app and also development of a similiar tool for the Delmarva Peninsula. Continued discussions with our advisory team for feedback the CWT and the Delmarva equivalent.

Impacts
What was accomplished under these goals? We are processing radar data using two approaches. The first is to process bird flight activity throughout the day using all radar scans within a 24-hour period (144 to 360 scans per day per radar). All radar scans to quantify bird flight activity have been processed for winters of 2019-2021 across all 3 radars in the Mid Atlantic and 2 out of 3 radars in CA. For the second approach we are quantifying waterfowl locations at the ground at evening flight exodus. This approach requires manually screening data as a quality control step. We have pre-screened 42 winter seasons from all 6 radars. Waterfowl exodus screening is currently underway. GPS/GSM telemetry tags have been deployed on 21 individuals (1 Mallard, 10 Canada Goose, 10 Greater Snow Goose). Telemetry data from a further 19 Canada Geese and ~52 Greater Snow Geese has been acquired through cooperative data-sharing agreements with Canadian counterparts. Mallard trapping will continue in the upcoming winter with 9 more tags left to be deployed. Initial analysis evaluating home ranges and movement tracks (between areas) in the Central Valley of California for 8 species of ducks that were marked with telemetry tracking devices during 2015-2020. USGS also has progressed significantly in the development of a geoprocessing tool using Google Earth Engine, R programming scripts, and three remote sensing satellite imagery products recorded at staggered intervals to determine flooded and managed habitats used by ducks in near real-time across the Central Valley landscape and potentially the Pacific and other Flyways. We expect the habitat geoprocessing tool will be fully operational and to be used to calculate habitat attributes to include in modeling of predicted waterfowl distributions in 2022-2023.Data for movement tracks of California ducks were shared with University of Delaware to use in conjunction with NEXRAD-based statistical models to improve performance in predicting waterfowl movement patterns, and ultimately, distributions.Additionally, results for home ranges and movement tracks were presented to poultry stakeholders. Home range results are currently being used to help identify habitats of relatively high- and low-use by ducks for environmental sampling of avian influenza this August (2021) in California. Development of advsiory committee and first advisory team meeting to discuss how best to improve participation with resepct to stakeholder use of the California Waterfowl Tracker (CWT).

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Oral paper titled: Linking Remote Sensing to Targeted PCR based Environmental Sampling for Detection of Avian Influenza in Waterfowl in the 2021 AAAP Annual Meeting.
• Type: Journal Articles Status: Accepted Year Published: 2021 Citation: Using the California Waterfowl Tracker to Assess Proximity of Waterfowl to Commercial Poultry in the Central Valley of California (Accepted, Avian Diseases)
• Type: Other Status: Accepted Year Published: 2021 Citation: February 2021. Buler, J. J. Surveillance of Waterfowl Distributions with Radar to Improve Food Security in Commercial Poultry. DARWIN Computing Symposium, University of Delaware, Newark, DE. Online.
• Type: Other Status: Accepted Year Published: 2021 Citation: April 2021. Buler, J. J. Whats new about birds on the move? Delaware Ornithological Society, virtual