Most studies on nest site selection in multiple-brooded birds indicate that breeders tend to reuse the original nest site for subsequent breeding attempts within the same season. However, there are also some instances that many breeders may choose to move and build a new nest. The factors of habitat affecting nest switching of multiple-brooded avian species are poorly investigated. In this study, we investigated whether facultatively double-brooded Japanese tits (Parus minor) adapt their nest site characteristics in response to changes in environmental conditions during the second breeding attempt. Our results showed that second breeding nest boxes of Japanese tits had lower shrub height and fewer total number of tree species, but taller nest box height and higher shrub density compared to the control nest boxes. Compared with first-breeding nest boxes, second-breeding nest boxes used by Japanese tits had lower shrub height and higher shrub density. Our results suggested that Japanese tits selected nest sites for second breeding based on nest site characteristics, which may be related to food availability or predator avoidance.

Fieldwork

Since 2009, we have provided roughly 450 nest boxes per year for secondary cavity-nesting birds such as Japanese tits, yellow-rumped flycatcher (Ficedula zanthopygia), Eurasian Nuthatches (Sitta europaea), and Daurian redstart (Phoenicurus auroreus), and have conducted many types of studies (E et al., 2019; Fan et al., 2021; Shen et al., 2021; Yu et al., 2021). The inner dimensions of nest boxes are 12 cm × 12 cm × 25 cm, the diameter of the entrance hole is 5 cm, and its lower end is 155 mm from the floor. All nest boxes were attached to the trees and were about 2-3m from the ground, with each nest box 30-50 m apart. The tree species and orientation of the hanging nest boxes were randomly selected. 

We usually cleaned the old nesting materials from occupied nest boxes during the pre-breeding period. To keep track of Japanese tit breeding attempts and reproductive information (e.g., egg-laying date, clutch size, hatching date, brood size, and the number of fledglings), we monitored the nest boxes at least once every week. When the parents entered the nest box to feed the nestlings (6–7 days old) during the first and second brooding periods, they were caught using a spring trap. All adults have ringed for individual identification and then released within 1–2 minutes. A nest was considered successful if at least one young fledged. We considered a nest unsuccessful if, during a visit before the expected fledge date, we found that the nest bowl was empty or contained eggshell fragments or dead young, or if there was no parental activity during three successive visits to the nest (i.e. eggs cold and wet, no adults observed). All second-breeding individuals occupied the empty nest boxes that were unused by any birds in the current year. 

Measuring nest site characteristics

We measured 13 nest site characteristics of the nest boxes occupied by the Japanese tits during the first and second breeding attempts and corresponding randomly selected control nest boxes (unoccupied by any birds in the current year). The nest site characteristics including orientation, the diameter at breast height (DBH), nest box height, tree height, tree species, the diameter at breast height of surrounding trees (SDBH), surrounding tree height, canopy cover, total number of tree species, the total number of surrounding trees, entrance inclination, shrub density, shrub height (for more complete descriptions of all variables' measurements, see Li et al., 2023). We used the handheld GPS to identify the nest boxes' longitude and latitude. The characteristics of the nest site were measured by X. L. Furthermore, L. W. and Y. Y., two researchers, helped with the nest site characteristics after receiving training from X. L. to standardize the measurements and minimize human error.

Statistical analysis

In order to evaluate the impact of the 13 nest site characteristics on the selection of nest site for the second breeding attempt, we used a generalized linear mixed model (GLMM) with a logit-link and binomial distribution to compare the differences of the nest site characteristics between second breeding nests of all individuals and control nest boxes (second breeding nests = 1, control nest box = 0). “year” and “identity of the second breeding/control nest box” were included as random effect. The 13 nest site characteristics were explanatory variables. To evaluate whether the Japanese tits would adjust the decision-making of nest site selection according to environmental changes over time, we used a GLMM with a logit-link and binomial distribution to compare the differences of the nest site characteristics between first- and second-breeding nests of all individuals (first-breeding nests = 0, second-breeding nests = 1). “year” and “identity of the first /second breeding nest box” were included as random effect. The 13 nest site characteristics were explanatory variables. In addition, we used additional data, including second-breeding pairs that were recaptured from their first breeding attempt to test whether the results were consistent. No substantially associated explanatory variables were detected when we screened explanatory variables before developing the model (Pearson's correlation coefficients < 0.65 and variance inflated factors (VIF) < 2 for all explanatory variables, Menard, 2002). Only the orientation and tree species were categorical variables among the 13 nest site characteristics, whereas the remaining 11 were continuous variables. Prior to analysis, we normalized all continuous variables (by subtracting the mean and dividing by the standard deviation), resulting in a mean of 0 and a standard deviation of 1.

We used the Akaike information criterion (AIC) to select the model in all analyses. And we used AICc to rank competing models and selected the top-ranked model with the ∆AICc ≤ 2 (Burnham & Anderson, 2002). Then, we select the model with the fewest variables as the best model from the list of models. By measuring the receiver operating characteristic's (ROC) area under the curve for the best model, we were able to assess the performance of the models (Fielding & Bell, 1997). We regarded a model as a good predictor if its AUC value was between 0.7-0.9. If the categorical factors (orientation and tree species) had a significant effect, we also did Tukey's honest significant difference (HSD) post hoc pairwise comparisons using the “lsmeans” package to find differences between categorical variables (Lenth, 2016), and we applied the Bonferroni correction to adjust the P-values.

All analyses were conducted in the R software version 4.2.1. The GLMMs were created with the “lme4” package (Bates et al., 2015) and the model selection was done using the multi-model inference “MuMIn” package (Barton, 2019). The data were reported with means indicated as the mean ± standard error (SE), and all statistical tests were performed with a significance threshold of 0.05 (P). The results of the GLMMs are presented with Wald Chi-squared tests.