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Information about ladeau

Published on October 21, 2007

Author: Heather


Monitoring population effects of an emergent disease in wild birds. :  Monitoring population effects of an emergent disease in wild birds. Shannon L. LaDeau Postdoctoral fellow Smithsonian Institution National Zoo-Migratory Bird Center Advisor: Peter Marra Slide2:  Avian tuberculosis (1986) Newcastle disease (1992) House Finch conjunctivitis (1994) West Nile virus (1999) H5N1-Avian flu (??) “Ready or not, here it comes. It is being spread much faster than first predicted from one wild flock of birds to another, an airborne delivery system that no government can stop. “ from coverage of M. Leavitt speech. March 2006 Disease emergence in U.S. avifauna: STEPHEN JAFFE/AFP US Army specialist Steve Richards captures mosquitos Slide3:  Identify impacts of West Nile virus in wild bird populations. Objective Slide4:  West Nile virus 1999 emergence in Queens, NY. Primary avian host. Mosquito vector 284 avian species in 48 states Positive bird surveillance: by county From CDC/USGS Slide5:  North American Breeding Bird Survey (BBS) Citizen scientists 1966 to current Over 4100 survey routes 24.5 mile along secondary roads Sauer, J. R., J. E. Hines, and J. Fallon. 2005. The North American Breeding Bird Survey, Results and Analysis 1966 - 2004. Version 2005.2. USGS Patuxent Wildlife Research Center, Laurel, MD Slide6:  2004 Population (people/per sq Mile < 3500 3500-8850 8851-20850 20851 - 55775 Route selection Mid-Atlantic states Temporal coverage: At least 80% data coverage from 1980 – 2005 with observations in 5 of 6 years after 1999. Slide7:  West Nile Footprint Crows experience high mortality. Komar et al. 2003 Eidson et al. 2001 Slide8:  Data Mean of OBSERVED counts WNV emergence in NY Average count Slide9:  Spread of West Nile virus Slide10:  West Nile Footprint Crows experience high mortality. Komar et al. 2003 Eidson et al. 2001 2. Population effects will be patchy and greater near urban areas. Kilpatrick et al. unpub Hochachka et al. 2004 Caffrey and Peterson 2003 Slide11:  For a given species, individual counts are conditionally Poisson where subscripts i and j refer to observer and route identity, respectively, and t denotes year. The expected value for a given annual count after accounting for route and observer effects is with random effects for variation among routes, years and observers. Data model Slide12:  Data Mean of OBSERVED counts WNV exposure? Average count Slide13:  Data versus Predicted Mean of PREDICTED counts Mean of OBSERVED counts Average count Slide14:  Unusual routes after 2000 Slide15:  Unusual routes before 1999 Slide16:  Summary 1. Monitoring disease in wildlife populations demands analyses that can accommodate natural stochasticity, census data and unplanned experiments without replication. We may not be collecting data at scales useful for monitoring avian disease. [Consistent sampling across rural to urban] Modeling/Analyses future: other species state-space approach using human or crow data as prior information regarding spatial exposure. Slide17:  Special thanks to…. USGS and BBS volunteers Wayne Thogmartin, Bill Link, John Sauer, Michael Lavine, and Jim Clark for discussion and modeling input. Extra slides:  Extra slides Slide19:  Monitoring wildlife disease is difficult: Can’t see the disease - Follow mortality Often there is no population data prior to disease How disease regulates/limits wildlife is largely unknown. Disease emergence in U.S. avifauna: Avian tuberculosis (1986) Newcastle disease (1992) House Finch conjunctivitis (1994) West Nile virus (1999) H5N1-Avian flu (??) Slide20:  Do we have the data we need? WNV exposure rates WNV-related mortality rates Population size prior to disease emergence Monitoring of populations at scale of disease ecology Slide21:  Data Slide22:  Trend Analysis Identify routes where trend before WNV emergence differs from post 2000 trend. Slide23:  Trend analysis Change in trend from 20 year mean Decrease in trend Increase in trend Slide24:  Spread of West Nile virus

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