DOI: 10.5061/dryad.g4f4qrfxh
title: Data for: Reintroduced Oriental stork bayesian hierarchical model data

description: Long-lived territorial bird populations often consist of a few territorial
 breeding adults and many non-breeding individuals. Some populations are
 threatened by anthropogenic activities, because of human conflicts for
 high-quality breeding habitat. Therefore, habitat restoration projects
 have been widely implemented to improve avian population status. In
 conjunction with habitat restoration, conservation translocations have
 been increasingly implemented. Adequate non-breeder survival can be a key
 factor in the success of these attempts because non-breeding birds may
 represent reservoirs for the replacement of breeders. The maintenance of
 breeding pair numbers is also influenced by the transition rate of
 non-breeders to breeders. The reintroduction of Oriental stork (Ciconia
 boyciana), a long-lived, territorial, endangered species, was initiated in
 Japan in 2005 using captive birds in hopes of increasing the population’s
 use of restored habitat. Our objective of this study was to elucidate the
 factors determining reintroduced stork survival and recruitment to the
 breeding populations. We estimated the survival rate and breeding
 participation rate by sex, age, generation, wild-born or not, haplotypes,
 and breeding status in storks reintroduced during 2005–2022 using Bayesian
 hierarchical models. There was no significant difference in survival rate
 between non-breeders and breeders. However, the survival rate was lower in
 wild-born birds than released birds, which may be related to the
 longer-distance natal dispersal of new generations. Accelerated habitat
 restoration around breeding areas and preventive measures for collision
 with human-built structures should be implemented for the sustained growth
 of reintroduced populations. A low survival rate was also detected for a
 specific mtDNA haplotype that accounts for the majority of the
 reintroduced population. This phenomenon might be explained by
 mtDNA-encoded mutations. Moreover, captive breeding and release history
 might contribute to an increase in the proportion of this haplotype in the
 wild.
description: Oriental stork observation records were collected from Hyogo Park
 of the Oriental white stork, which is also the repository for all
 observation records of ringed storks by the general public and media, as
 well as the home of the Inter-institutional Panel on Population Management
 of the Oriental white stork.
description: # Reintroduced Oriental Stork Bayesian hierarchical model data
 To estimate annual
 survival rates based on mark-resight histories, the Cormack-Jolly-Seber
 (CJS) model was adapted (Cormack 1964, Jolly 1965, Seber 1965),
 incorporating state-space likelihood as outlined by Gimenez et al. (2007)
 and Kéry and Schaub (2011).  The data of released (*n* = 74) and wild-born
 (*n* = 274) birds during 2005­–2019 were used for this analysis. The
 breeding participation rate was modelled using hierarchical logistic
 regression. Released (*n* = 56) and wild-born (*n* = 165) birds aged more
 than three years old in the wild were used for this analysis. ##
 Description of the data and file structure Data of "wild.csv",
 "release.csv", "wild_age.csv",
 "released_age.csv", "wild_breeding.csv",
 "released_breeding.csv", "cjs_wild.csv", and
 "cjs_released.csv" are for hierarchical CJS model. Bird
 characters are included in "wild.csv" and
 "release.csv". Sex (F: female, M: male) and release (H:
 hard-release, S: soft-release) are categorical data. Data of
 "rs_id.csv", "rs_age.csv", and "rs_cjs.csv"
 are for hierarchical logistic regression model. Wild1 Capt0 cell indicates
 wild-born (1) or released (0) bird. Class cell indicates released females
 (1), released males (2), wild-born females (3), and wild-born males (4).
 First and Max cells indicate year period for this analysis. NA included in
 above data files indicates no data, such as not born or breed yet, or
 already died. ## Code/Software Our codes for statistical analysis using R
 4.0.0 and JAGS 4.3.0.