DOI: 10.5061/dryad.wwpzgmsq5
title: Nest-switch and nest site selection pattern in the double-brooded Japanese tits (Parus minor)

description: 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.
description: Fieldwork
 Since 2009, we have provided
 roughly 450 nest boxes per year for secondary cavity-nesting birds such as
 Japanese tits, yellow-rumped flycatcher (<em>Ficedula</em>
 <em>zanthopygia</em>), Eurasian Nuthatches
 (<em>Sitta</em> <em>europaea</em>), and Daurian
 redstart (<em>Phoenicurus</em> <em>auroreus</em>),
 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 &lt;
 0.65 and variance inflated factors (VIF) &lt; 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.
description: 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.