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Zhang Z.,Beijing Normal University | Zhang Z.,Central South University of forestry and Technology | Hou D.,Central South University of forestry and Technology | Xun Y.,Conservation Institute of Daweishan Nature Reserve | And 2 more authors.
Journal of Natural History | Year: 2016

Previous studies of nest-site selection on a fine scale may reveal limiting resources within habitat types. The red-billed leiothrix (Leiothrix lutea Scopoli, 1786) is a common bird species that lives in the subtropical forests of Asia. Despite many reports of this species from introduced populations, little information has been obtained from its native range. From 2011 to 2013, we studied nest-site selection of red-billed leiothrix at micro-scales in Daweishan Nature Reserve, Hunan Province, central China. A total of 363 nests were found in five vegetation types. We measured the habitat variables and constructed nest-site selection models for nests found in the forest and scrub-grassland. Among the 18 variables measured in the forest, six variables were selected to construct the nest-site selection model: distance to forest edge (DTE), distance to water (DTW), vegetation comprehensive coverage, tree coverage, bamboo coverage and shrub height. According to Akaike’s information criterion, the best model consisted of five of these variables (excluding vegetation comprehensive coverage), and distance to forest edge, distance to water, tree coverage and bamboo coverage had negative effects on nest-site selection. In scrub-grassland, the DTE, DTW, and bush coverage (BUC) were selected from the 13 variables measured, and, accordingly, the best model consisted of DTE and BUC. Model averaging suggested that BUC had a positive effect on nest-site selection. In contrast, DTE has a reverse effect. In addition, DTE differed significantly between successful and failed nests in forest and scrub-grassland. More successful nests were found near the forest edge. Taken together, these findings emphasise the power of fine-scale habitat selection models in identifying relevant habitat variables with a significant effect on preferred habitat and eventually, breeding success. © 2016 Taylor & Francis

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