title: Investigation of ground level and remote-sensed data for habitat classification and prediction of survival of Ixodes scapularis in habitats of southeastern Canada.
abstract: In southeastern Canada, most populations of Ixodes scapularis Say, the Lyme disease vector, occur in Carolinian forests. Climate change projections suggest a northward range expansion of I. scapularis this century, but it is unclear whether more northerly habitats are suitable for I. scapularis survival. In this study, we assessed the suitability of woodlands of the Lower Great Lakes/St. Lawrence Plain region for I. scapularis by comparing tick egg survival in four different woodlands. Woodlands where I. scapularis are established, and sand dune where I. scapularis do not survive, served as positive and negative control sites, respectively. At two woodland sites, egg survival was the same as at the positive control site, but at two of the sites survival was significantly less than either the positive control site, or one of the other test sites. Egg survival in all woodland sites was significantly higher than in the sand dune site. Ground level habitat classification discriminated among woodlands in which tick survival differed. The likelihood that I. scapularis populations could persist in the different habitats, as deduced using a population model of I. scapularis, was significantly associated with variations in Landsat 7 ETM+ data (normalized difference vegetation index [NDVI] and Tasselled Cap indices). The NDVI index predicted habitat suitability at Long Point, Ontario, with high sensitivity but moderate specificity. Our study suggests that I. scapularis populations could establish in more northerly woodland types than those in which they currently exist. Suitable habitats may be detected by ground-level habitat classification, and remote-sensed data may assist this process.
authors.affiliation: Groupe de Recherche en Epidémiologie des Zoonoses et Santé Publique, Faculté de Médecine Vétérinaire, Université de Montréal, Que., Canada.
authors.forename: N H
authors.initials: NH
authors.lastname: Ogden
authors.forename: I K
authors.initials: IK
authors.lastname: Barker
authors.forename: G
authors.initials: G
authors.lastname: Beauchamp
authors.forename: S
authors.initials: S
authors.lastname: Brazeau
authors.forename: D F
authors.initials: DF
authors.lastname: Charron
authors.forename: A
authors.initials: A
authors.lastname: Maarouf
authors.forename: M G
authors.initials: MG
authors.lastname: Morshed
authors.forename: C J
authors.initials: CJ
authors.lastname: O'Callaghan
authors.forename: R A
authors.initials: RA
authors.lastname: Thompson
authors.forename: D
authors.initials: D
authors.lastname: Waltner-Toews
authors.forename: M
authors.initials: M
authors.lastname: Waltner-Toews
authors.forename: L R
authors.initials: LR
authors.lastname: Lindsay
mesh_terms: D000818:Animals; D001096:Arachnid Vectors / Q000502:physiology*; D002170:Canada; D003198:Computer Simulation; D003625:Data Collection / Q000379:methods*; D004285:Dogs; D017753:Ecosystem; D005260:Female; D018884:Ixodes / Q000502:physiology*; D008297:Male; D008954:Models, Biological; D010058:Oviposition; D012680:Sensitivity and Specificity; D012987:Soil / Q000032:analysis; D016019:Survival Analysis; D014197:Trees
chemical_list: D012987:Soil