Kansas State University
205 Leasure Hall
Manhattan, KS 66506-3501
Phone: (785)532-6070
Fax: (785)532-7159


About the Unit
Mission Statement
Unit News


Faculty and Staff
Graduate Students

Current Projects
Completed Projects
Technical Assistance
Research Experience for Undergraduates (REU)

Resources and Employment
Graduate School
Graduate Applications

Forms and Manuals
Assistantships and Positions

Occurrence and Prediction of Avian Disease Outbreaks in Kansas

Thomas Becker

Project Supervisor:
Dr. David Haukos
Dr. Peg McBee

Kansas Department of Wildlife, Parks, and Tourism
U.S. Fish and Wildlife Service

Shane Hesting
Dr. Tom Roffe

Location: Throughout Kansas

Completion: December 2015

Status: Initiation March 2014

(1) Compile all known records of avian disease outbreaks in Kansas.
(2) Associate each record with available environmental data (e.g., precipitation index, temperature) and, if possible, estimated population at risk during each outbreak.
(3) Create a historical data base and a web-based reporting form for avian disease outbreaks in Kansas.
(4) Construct predictive models for environmental conditions that may support a disease outbreak.

Progress and Results:
There are a wide variety of diseases that affect birds. These diseases can be bacterial, viral, fungal, parasitic, and toxic (i.e., environmental contaminant). Of the diseases that affect migratory, wild birds, those of primary concern are avian cholera, avian botulism, duck plague, aspergillosis, West Nile, Newcastle disease, and avian influenza. Avian cholera and avian botulism are bacterial diseases, Pasteurella multocida and Clostridium botulinum, respectively, that typically affect waterfowl and shorebird species. Occurence, causes, and impacts of disease in wild bird populations are rarely studied beyond documentation of large outbreaks in terms of date, duration, species affected, and estimated number of individuals affected. These records are stored throughout many different venues. For many avian diseases, certain environmental conditions are hypothesized to be necessary prior to the occurrence of epizootic events. By location in the middle of the Central Flyway, Kansas provides critical habitat for breeding, migrating, and wintering migratory birds. In addition, several areas (e.g., Cheyenne Bottoms, Quivira, Jamestown, and McPherson wetland habitats) support large populations of migratory waterfowl and other waterbirds that would result in a major mortality event should a disease outbreak occur. Further, survey evidence f indicate that migratory birds are staging for longer periods in Kansas compared to historical duration, increasing the likelihood of increased impacts of disease outbreaks in the state. All records of disease outbreaks will be compiled through a comprehensive search of all potential locations that may house any such reports. Once all possible records are compiled, a data base will be generated that includes all potential information related to disease outbreaks (e.g., date, location, duration, species involved, number of dead birds counted). Upon completion of the historical data base, a web-based reporting process will be developed for use by anyone in the state of Kansas. We will use one of the suite of available models and software (e.g., MaxEnt, Environmental-Niche Factor Analysis, Genetic Algorithm for Rule-Set Prediction) used to develop predictive models based on known occurrence of a disease outbreak and the environmental conditions associated with the outbreak.

Becker, Thomas. 2016. A Retrospective Surveillance Study of Avian Disease Outbreaks in Kansas. Kansas Natural Resources Conference, Wichita, KS.

Becker, T., P. McBee, and D. Haukos. 2015. Occurrence and predictions of avian disease outbreaks in Kansas. Annual meeting of the Central Mountains and Plains Section of The Wildlife Society, Manhattan, Kansas.

Becker, T., P. McBee, and D. Haukos. 2015. Occurrence and prediction of avian disease outbreaks in Kansas. Joint meeting of American Ornithologists' Union and Cooper Ornithological Society, Norman, OK.