Use of Airborne Laser Scanning to assess effects of understorey vegetation structure on nest‐site selection and breeding performance in an Australian passerine bird

Abstract

AbstractIn wild bird populations, the structure of vegetation around nest‐sites can influence the risk of predation of dependent offspring, generating selection for nest‐sites with vegetation characteristics associated with lower predation rates. However, vegetation structure can be difficult to quantify objectively in the field, which might explain why there remains a general lack of understanding of which characteristics are most important in determining predation rates. Airborne laser scanning (ALS) offers a powerful means of measuring vegetation structure at unprecedented resolution. Here, we combined ALS with 11 years of breeding data from a wild population of superb fairy‐wrens Malurus cyaneus in southeastern Australia, a species which nests relatively close to the ground and has high rates of nest and fledgling predation. We derived structural measurements of understorey (0–8 m) vegetation from a contiguous grid of 30 × 30 m resolution cells across our c. 65 hectares study area. We found that cells with nests (nest‐cells) differed in their understorey vegetation structure characteristics compared to unused cells, primarily in having denser vegetation in the lowest layer of the understorey (0–2 m; the ‘groundstorey’ layer). The average height of understorey vegetation was also lower in cells with nests than in those without nests. However, relationships between understorey vegetation structure characteristics and breeding performance were mixed. Nest success rates decreased with higher volumes of groundstorey vegetation, as did fledgling survival rates, though only in nest‐cells with lower height vegetation. Our results indicate that ALS can identify vegetation characteristics relevant for superb fairy‐wren nest‐site selection, but that nesting preferences are not beneficial under current predation pressures. The study illustrates the potential for using ALS to investigate how ecological conditions affect behaviour and life‐histories in wild animal populations.