title: Population estimation and trappability of the European badger (Meles meles): implications for tuberculosis management.
abstract: Estimates of population size and trappability inform vaccine efficacy modelling and are required for adaptive management during prolonged wildlife vaccination campaigns. We present an analysis of mark-recapture data from a badger vaccine (Bacille Calmette-Guérin) study in Ireland. This study is the largest scale (755 km(2)) mark-recapture study ever undertaken with this species. The study area was divided into three approximately equal-sized zones, each with similar survey and capture effort. A mean badger population size of 671 (SD: 76) was estimated using a closed-subpopulation model (CSpM) based on data from capturing sessions of the entire area and was consistent with a separate multiplicative model. Minimum number alive estimates calculated from the same data were on average 49-51% smaller than the CSpM estimates, but these are considered severely negatively biased when trappability is low. Population densities derived from the CSpM estimates were 0.82-1.06 badgers km(-2), and broadly consistent with previous reports for an adjacent area. Mean trappability was estimated to be 34-35% per session across the population. By the fifth capture session, 79% of the adult badgers caught had been marked previously. Multivariable modelling suggested significant differences in badger trappability depending on zone, season and age-class. There were more putatively trap-wary badgers identified in the population than trap-happy badgers, but wariness was not related to individual's sex, zone or season of capture. Live-trapping efficacy can vary significantly amongst sites, seasons, age, or personality, hence monitoring of trappability is recommended as part of an adaptive management regime during large-scale wildlife vaccination programs to counter biases and to improve efficiencies.
authors.affiliation: Teagasc, Mellows Campus, Athenry, County Galway, Ireland. andrew.byrne@teagasc.ie
authors.forename: Andrew W
authors.initials: AW
authors.lastname: Byrne
authors.forename: James
authors.initials: J
authors.lastname: O'Keeffe
authors.forename: Stuart
authors.initials: S
authors.lastname: Green
authors.forename: D Paddy
authors.initials: DP
authors.lastname: Sleeman
authors.forename: Leigh A L
authors.initials: LA
authors.lastname: Corner
authors.forename: Eamonn
authors.initials: E
authors.lastname: Gormley
authors.forename: Denise
authors.initials: D
authors.lastname: Murphy
authors.forename: S Wayne
authors.initials: SW
authors.lastname: Martin
authors.forename: John
authors.initials: J
authors.lastname: Davenport
mesh_terms: D000818:Animals; D007494:Ireland / Q000453:epidemiology; D016015:Logistic Models; D008954:Models, Biological; D045969:Mustelidae / Q000254:growth & development* / Q000382:microbiology*; D010571:Pest Control; D016012:Poisson Distribution; D011156:Population Density; D011158:Population Growth; D014376:Tuberculosis / Q000453:epidemiology / Q000517:prevention & control* / Q000662:veterinary*