TY - JOUR
T1 - Using atlas data to model the distribution of woodpecker species in the Jura, France
AU - Tobalske, Claudine
AU - Tobalske, Bret W.
PY - 1999/8
Y1 - 1999/8
N2 - Breeding bird atlases providing distribution data at a regional scale are becoming increasingly common. To assess the ability of such data to develop broad-scale bird-habitat models, we used data from a breeding bird atlas and landscape variables obtained from a geographic information system (GIS) to study the distribution of seven woodpecker species in the Jura, France: the Black (Dryocopus martius), Green (Picus viridis), Grey-headed (P. canus), Great Spotted (Dendrocopos major), Middle Spotted (D. medius), and Lesser Spotted (D. minor) Woodpeckers, and the Wryneck (Jynx torquilla). We used logistic regression to develop predictive models from variables that described each 575-ha atlas cell in terms of forest composition, forest class richness, edge density, and elevation. For all seven species, prediction rates were better than chance; however, improvements over chance classification varied from 14-39%, indicating that predictive ability was species-specific. From our study, we identified limitations inherent to working with gridded data, including grid positioning problems and inability to compute spatial variables. In spite of these limitations, our models could be used for simulations, to improve the atlas itself, and to identify potential suitable habitat.
AB - Breeding bird atlases providing distribution data at a regional scale are becoming increasingly common. To assess the ability of such data to develop broad-scale bird-habitat models, we used data from a breeding bird atlas and landscape variables obtained from a geographic information system (GIS) to study the distribution of seven woodpecker species in the Jura, France: the Black (Dryocopus martius), Green (Picus viridis), Grey-headed (P. canus), Great Spotted (Dendrocopos major), Middle Spotted (D. medius), and Lesser Spotted (D. minor) Woodpeckers, and the Wryneck (Jynx torquilla). We used logistic regression to develop predictive models from variables that described each 575-ha atlas cell in terms of forest composition, forest class richness, edge density, and elevation. For all seven species, prediction rates were better than chance; however, improvements over chance classification varied from 14-39%, indicating that predictive ability was species-specific. From our study, we identified limitations inherent to working with gridded data, including grid positioning problems and inability to compute spatial variables. In spite of these limitations, our models could be used for simulations, to improve the atlas itself, and to identify potential suitable habitat.
KW - Breeding bird atlas
KW - Grid data
KW - Habitat model
KW - Woodpecker distribution
UR - http://www.scopus.com/inward/record.url?scp=0032799927&partnerID=8YFLogxK
U2 - 10.2307/1370177
DO - 10.2307/1370177
M3 - Article
AN - SCOPUS:0032799927
SN - 0010-5422
VL - 101
SP - 472
EP - 483
JO - Condor
JF - Condor
IS - 3
ER -