Data for: Using radio frequency identification (RFID) technology to characterize nest site selection in wild Japanese tits (Parus minor)

Selecting a suitable nest site is critical to the survival and reproduction of birds. Prospecting allows individuals to gather information on the local quality of potential future breeding sites, which may help them make the best nest site selection decision. However, few studies have focused on the direct links between the prospecting activity of breeders and subsequent nest site selection. In this study, we investigated the prospecting pattern of Japanese tits (Parus minor) during the pre-breeding period of the first breeding attempt and whether nest site characteristics influence their nest box visiting behaviour and occupied nest site. We used radio frequency identification (RFID) to track the movements of Japanese tits visiting nest boxes and compared nest site characteristics between visited and unvisited (control) nest boxes, as well as between visited and occupied nest boxes. We found that Japanese tits started visiting nest boxes approximately 20 days before breeding, visited a..., Study area and study species
The study area was located in the eastern Changbai Mountains in the Zuojia Nature Reserve (44°1′–45°0′ N, 126°0′–126°8′ E), situated in Jilin Province, northeastern China. The total area of the reserve is ~5,544 ha. The area is hilly in the transition from the Changbai Mountain sub-region to the western plain, with an elevation of 200-530 m. The average temperatures in March, April, and May in the Zuojia Natural Reserve area from 2005 to 2021 were -1.01 ± 0.26℃, 8.16 ±0.24℃, 15.38 ± 0.18℃, respectively. Local temperatures were obtained from Jilin Suburban Weather Station, 44 km from the study area [Chinese National Meteorological Center of CMA (http://eng.nmc.cn/), weather station No. 54172]. The main forest type in the study area is secondary broad-leaved mixed forest, and the forest age is generally 50-60 years old. The main tree species are Quercus mongolica, Sophora japonica, Ulmus japonica, Betula davurica, Fraxinus mandshurica, Tilia mandshurica, Pinus..., We performed all analyses in the program R (version 4.2.1). The GLMMs were implemented using the ‘lme4’ package (Bates et al. 2015), conditional logistic regression was performed by the ‘survival’ package (Therneau 2015), and the multi-model inference package ‘MuMIn’ was used for model selection. The results were visualized using ggplot2 (Wickham and Chang 2022).Â