\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[T2A]{fontenc}
\usepackage[greek,ngerman,polish,english]{babel}



\usepackage{float}








\begin{document}

\title{Altered wing phenotypes of captive-bred migratory birds incur
post-release fitness costs~}



\author[1]{Dejan Stojanovic}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 26, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup








\sloppy


\textbf{Introduction}

Captive animal phenotypes can diverge from the ideal `wild type', and
these changes can affect behavior, morphology and physiology (Crates
\emph{et al.} 2022). However, the specific nature and combination of
`captive phenotypes' can vary widely between species (Crates \emph{et
al.} 2022). Whether changes are important depends on the intended use of
captive-bred animals. For display animals, phenotypic changes may be
inconsequential. Conversely, conservation breeding programs -- a
globally popular tool to combat species extinctions (Conde \emph{et
al.}2011) -- should ideally produce animals optimized for life in the
wild after release, but this more easily said than done (Taylor \emph{et
al.}2017). If altered captive phenotypes incur a fitness cost in the
wild, conservation breeding may be less effective than hoped (Crates
\emph{et al.} 2022). Thus, it is important that conservation breeding
programs quantify optimal wild phenotypes, and be vigilant of changes
arising from life in captivity that might jeopardize survival after
release (Shier 2016; Berger-Tal \emph{et al.} 2020).

Phenotypic changes to traits involved in strenuous or high-risk phases
of life history may be disproportionately important for fitness post
release from captivity. For example, migration is a high-risk behavior
that strongly selects for the most capable individuals (Dingle 2014;
Rotics \emph{et al.} 2016). Captive-born animals are often less
successful migrants than wild-born conspecifics (Crates \emph{et
al.}2022). This is sometimes attributable to behavioral differences. For
example, some captive-born birds depart later and travel shorter
distances than wild conspecifics (Burnside \emph{et al.} 2017), and
captive-bred butterflies fail to orient themselves or even attempt
migration (Tenger-Trolander \emph{et al.} 2019). Morphological changes
also likely contribute to poor migration outcomes post release, but
evidence for their effects on fitness is surprisingly limited. Davis et
al. (2020) recently showed that captive-bred monarch butterflies
\emph{Danaus plexippus} have differently shaped wings and lower
migration success than wild conspecifics. Wing shape strongly predicts
flight efficiency (Lockwood \emph{et al.} 1998; Sheard \emph{et
al.}2020). Given that migratory birds are commonly bred in captivity for
reintroduction (Davis 2010; Burnside \emph{et al.} 2017; Hutchins
\emph{et al.} 2018; Stojanovic \emph{et al.} 2020b; Tripovich \emph{et
al.} 2021), quantifying the ubiquity of deleterious captive wing shape
phenotypes and their post-release fitness consequences is critical
information.

I aimed first to compare captive/wild wings of 16 species representing
three commonly captive-bred bird families (Phasianidae, Psittacidae,
Estrildidae) to evaluate the ubiquity of captive wing shape phenotypes.
Then, using a critically endangered migratory bird as a model, I aimed
to demonstrate that a captive wing shape phenotype incurs a fitness cost
post release.

\textbf{Methods}

\emph{Data collection (Aim 1)}

For the first aim of my study (to evaluate the ubiquity of changes to
the flight apparatus of captive birds) I measured study skins at the
Australian National Wildlife Collection, Australian Museum, American
Museum of Natural History, Harvard Natural History Museum, Museum of
Victoria, South Australian Museum and the Tasmanian Museum and Art
Gallery. I assigned individual provenance (captive/wild) based on
specimen metadata. Captive specimens were rarer in museum collections --
I aimed for at least five captive and wild specimens per species, so
some species were excluded. I selected common species in zoological and
private collections because, like multi-generational
conservation-focused captive-breeding programs, specimens were likely to
be captive-born (not wild-collected). Although I previously showed that
wing shape change in orange-bellied parrots was independent of
generations of captive breeding (Stojanovic \emph{et al.} 2021), I aimed
to minimize this risk by using older captive-bred specimens that were
less likely to be multi-generational captive-bred (however, the
individual histories of captive-born specimens in this study were
unknown). The mean collection date of captive specimens was 1955 vs.
1938 for wild specimens, reflecting the emergence of Australian
avicultural trapping and trade last century (Franklin \emph{et
al.}2014). Species inclusion was limited by (i) collection bias toward
attractive Australian native species which are preferred in captivity
(Vall-llosera \& Cassey 2017), and (ii) for non-Australian species,
absence of wild specimens for comparison.

Using electronic calipers (0.01mm) and rulers (1mm) I measured: wing
chord (L\textsubscript{W}), the length of the most distal secondary
feather (L\textsubscript{S}), the length of the longest primary feather
(L\textsubscript{P}) (per Jenni \& Winkler 1989), the distance between
the tips of the outermost eight primary flight feathers (P10-P3) to the
tip of the longest primary feather (i.e. \selectlanguage{greek}Δ\selectlanguage{english}Q, per Lockwood \emph{et
al.}1998). P10 is the most distal flight feather that forms the leading
edge of the wing, and P3 is the most proximal flight feather I measured.
In passerines p10 is vestigial (Hall 2005) and I did not measure this
feather. However, to improve visualization and interpretation of the
results, I relabel P9 of passerines as P10 because this is the most
distal functional flight feather in non-passerines. Our sample included
16 species from three families (Table S1): Phasianidae, n=1 sp.;
Estrildidae, n=6 spp.; Psittaculidae, n=9 spp. I aimed for equal sex
ratios (final sex ratio: 127 males, 123 females, 116 unknown) and the
total sample comprised 146 captive-born specimens and 220 wild-born
specimens.

\emph{Background and Data collection (Aim 2)}

For the second aim of the study (evaluate the fitness consequences of
the captive wing phenotype) I used orange-bellied parrots (Department of
Environment Land Water and Planning 2016) as a model because they: (i)
are bred in captivity and released in large numbers (Smales \emph{et
al.} 2000) which overcomes the common hindrance of small sample sizes,
(ii) undertake a migration that results in strong selection and survival
of only a fraction of individuals (Stojanovic \emph{et al.} 2020b),
(iii) their recovery program is among the largest, longest running and
most well-resourced of threatened species' recovery efforts (Department
of Environment Land Water and Planning 2016; Pritchard \emph{et
al.}2022) making it a `best case' of captive-breeding for conservation,
and (iv) I have previously demonstrated that the wings of captive and
wild parrots have different shapes (Stojanovic \emph{et al.} 2021), so
identifying fitness consequences of this difference a priority.
Captive-bred juveniles are released at the end of the breeding season so
that they can integrate with wild fledglings and migrate northward
together. This migration is demanding both physically (e.g. a sea
crossing) and behaviorally (e.g. sudden transition from supplemental to
natural food (Stojanovic \emph{et al.} 2020a)). Most captive-born
juveniles do not survive their first year of life (Stojanovic \emph{et
al.} 2020b). Their survival is monitored via daily observations of
ringed birds at supplementary food tables during the summer breeding
season (Stojanovic \emph{et al.} 2018; Stojanovic \emph{et al.} 2020b).
The captive population is held across several participating institutions
that use comparable husbandry approaches (Pritchard \emph{et al.} In
Prep) and a studbook to minimize genetic adaptation to captivity
(Morrison \emph{et al.} 2020a). Regular releases have resulted in full
admixture of the captive and wild populations (Stojanovic \emph{et
al.}2022). I measured 78 juvenile captive-bred parrots released to the
wild over three years (2019: 30, 2020: 31, and 2021: 17). Juveniles are
selected for release based on metapopulation management considerations
(Morrison\emph{et al.} 2020b; Troy \& Lawrence 2021), but not for any
particular phenotypic trait other than good body mass and general
feather condition. To reduce the welfare impact of measuring live birds,
I only measured \selectlanguage{greek}Δ\selectlanguage{english}Q for P10-P5 because these are the most likely feathers
to vary in their length (Stojanovic \emph{et al.} 2021). I also dropped
L\textsubscript{S} to further reduce handling time, but I did record
L\textsubscript{W,} tail length (L\textsubscript{T}) and body mass (g).
P9 was excluded from analysis as it was the longest feather in the wing
of each parrot (and thus there was no variation to model). As an index
of individual condition, I divided body mass by L\textsubscript{W} to
scale for body size. I scored individuals as having survived (1) or died
(0) their first year of life based on whether or not they returned from
their first migration (Troy \& Lawrence 2021).

\emph{Analytical approach}

I conducted all analyses in R (R Development Core Team 2021) and scaled
and centered all variables. Code, data summaries and full results are
supplied in a supplementary R Markdown script.

Aim 1 (evaluate the ubiquity of captive wing shape phenotypes) -- I used
the lengths of L\textsubscript{W}, L\textsubscript{S},
L\textsubscript{P}, and \selectlanguage{greek}Δ\selectlanguage{english}Q (P10-P3) the response variable in Bayesian
logistic regression (family: `gaussian') implemented in the package
\emph{MCMCglmm} (Hadfield 2010). I included a three-way interaction
between the measured feather ID, species ID and provenance
(captive/wild) as the fixed effect, and the specimen ID as the random
effect. I used inverse-Wishart priors for the random effect and residual
variance (V = 1, \selectlanguage{greek}ν \selectlanguage{english}= 0.002). I ran the model for 100,000 iterations and
set burn-in to 1,000 and used 100 for thinning for a total posterior
sample of 990. All chains were checked for proper mixing, and I checked
for auto correlation using the command `autocorr' with 0.1 as a target
threshold. I used \emph{emmeans} (Lenth 2018) to estimate Z values of
pairwise captive-wild contrasts for visualization with \emph{ggplot2}
(Wickham 2016).

Aim 2 -- To evaluate the relationship between survival of the first
migration and individual phenotype, I used the binomial juvenile
survival outcome as the response variable in Bayesian logistic
regression (family: `categorical'), implemented in the package
\emph{MCMCglmm} (Hadfield 2010). I fitted \selectlanguage{greek}Δ\selectlanguage{english}Q (P10-P5),
L\textsubscript{T}, and the index of body condition as fixed effects and
release year as a random effect. I specified priors for the fixed
effects using the `gelman.prior' command (v=1, nu=0.02) and fixed
residual variance at 1. I ran the model for 100,000 iterations and set
burn-in to 1,000 and used 100 for thinning for a total posterior sample
of 990. All chains were checked for proper mixing, and I checked for
auto correlation using the command `autocorr' with 0.1 as a target
threshold.

\textbf{Results}

\emph{Evaluate the ubiquity of captive wing shape phenotypes}

The interaction between feather ID \selectlanguage{ngerman}× species × provenance had
significant explanatory power for the length of the feathers I measured
(see R Markdown). Significant differences between captive/wild specimens
in the length of at least one flight feather occurred in one quarter of
sampled species (Figure 1). Relative to wild conspecifics: (i) captive
budgerigars \emph{Melopsittacus undulatus} had longer secondary
feathers, (ii) captive turquoise parrots \emph{Neophema pulchella} had a
longer P10, (iii) captive princess parrots \emph{Polytelis
alexandrae}had a longer P10, P9 and P3, and a shorter P8, (iv) captive
star finches\emph{Bathilda ruficauda} had shorter secondary feathers.
Although non-significant, the length of P10 in captive-born individuals
tended toward being either longer (e.g. zebra finches \emph{Taeniopygia
guttata} , Gouldian finches \emph{Chloebia gouldiae} ) or shorter (e.g.
sunset parrot \emph{Neopsephotus bourkii} , red-throated
parrotfinch\emph{Erythrura psittacea} ). L\textsubscript{W} and
L\textsubscript{P}never differed between captive and wild specimens,
regardless of whether or not there were differences in the lengths of
other feathers in the wing.

\emph{Fitness cost of captive phenotypes}

Survival of captive-bred juvenile orange-bellied parrots had a
significant negative relationship with \selectlanguage{greek}Δ\selectlanguage{english}Q P10, and to a lesser extent
L\textsubscript{T} (Table 1). Smaller values of \selectlanguage{greek}Δ\selectlanguage{english}Q P10 indicate that
feather is longer, and thus more like the wild phenotype (Figure 2).
Based on the model, the probability of survival for a juvenile
captive-born orange-bellied parrot with a \selectlanguage{greek}Δ\selectlanguage{english}Q P10 of 1mm was 4.84\%
(highest posterior density intervals: 8.75e\textsuperscript{5} -- 0.35),
compared with only 1.8\% (highest posterior density intervals:
1.34e\textsuperscript{5} -- 1.77) for an individual with a \selectlanguage{greek}Δ\selectlanguage{english}Q P10 of
2mm.~

\textbf{Discussion}

Phenotypic traits involved in arduous or risky components of life
history can exert strong selective pressure. Animals bred in captivity
for release to the wild as a conservation intervention should ideally
conform to optimal phenotypes for surviving these challenges
(Crates\emph{et al.} 2022). In this study, I present the first
multi-species evaluation of the prevalence and fitness impact of captive
wing phenotypes among birds. I found the wing shapes of captive birds
differed to wild conspecifics in a quarter of species examined. These
changes usually involved the most distal primary feathers forming the
wing tip or the secondary feather length. Wing tip shape determines
flight performance (Lockwood \emph{et al.} 1998; Swaddle \& Lockwood
2003), but whether the changes I report result in impaired flight
ability remains unclear. However, this possibility is supported by
evidence that a shorter P10 in released juvenile captive orange-bellied
parrots incurred a fitness cost. Juveniles with wild wing phenotypes
were more than twice as likely to survive the first year of life than
individuals with only a 1mm shorter P10. This is the first demonstration
that altered wing phenotypes are widespread among captive-bred birds and
that these changes incur a fitness cost post release.

Orange-bellied parrots are the beneficiary of careful genetic management
and professional husbandry techniques in the large-scale, professional
captive-breeding for reintroduction program (Pritchard \emph{et
al.}2022). Despite this care, subtle changes to wing phenotypes emerged
in captivity (Stojanovic \emph{et al.} 2021), despite similarities in
other components of phenotype like overall body size (Stojanovic
\emph{et al.}2019). Juvenile orange-bellied parrots face a gauntlet of
obstacles to survival of their first year of life (Stojanovic \emph{et
al.} 2020b; Stojanovic \emph{et al.} 2022) -- perhaps the likely
increase in drag of a rounder wing tip (Tucker 1995; Minias \emph{et
al.} 2015) is enough to further disadvantage captive phenotypes during
long flights. At the breeding ground, post-release survival of
captive-bred parrots is very high (Smales \emph{et al.} 2000),
indicating stronger selection occurs during migration when juveniles are
developing their survival skills and physical endurance.

My results raise important new questions both for orange-bellied parrots
and other conservation breeding programs more generally. Firstly, why is
the length of flight feathers of birds so plastic among so many species?
Whether wing shape is under genetic control or shaped by the environment
is not clear, and clarifying the importance of these potential forces on
feather development may provide insight into how to correct captive wing
phenotypes. Second, why are the distal feathers so prone to change? The
forces exerted by flight are greatest at the wing tip (Lockwood \emph{et
al.}1998) and many species in this study had altered P10 lengths (both
significant and indicative effects). Investigating the relationship
between feather development and curtailed flight in captive environments
may help explain why distal flight feather length is plastic. Third, can
individuals with captive wing phenotypes revert to a wild phenotype? If
feather growth is at least partly affected by environment, it is
conceivable that individuals with captive wing phenotypes could be
experimentally manipulated before release to optimize wing shape (e.g.
with flight training). Fourth, why do captive wing phenotypes incur a
fitness cost, and is this universal? Rounded wing tips produce more drag
than pointed ones (Lockwood \emph{et al.} 1998), but the direct
consequences of captive wing phenotypes on migration success is unknown,
especially because the changes I report here vary in their magnitude
among species. Understanding the aerodynamic cost of captive wing
phenotypes is important for optimizing survival of captive-bred
migratory birds.

Captive phenotypes vary from obvious to subtle deviations from the
optimal wild type. I show a mere 1mm reduction in the length of a single
feather significantly elevates juvenile mortality. This surprising
consequence of a seemingly trivial phenotypic change is an important
reminder that captive breeding for conservation is not straightforward.
Importantly, the changes to wing shape I report would go unnoticed using
indices of wing shape such as the hand wing index (Sheard \emph{et
al.}2020) because L\textsubscript{W} and L\textsubscript{P} (which are
important for calculating this index) were unaffected by captivity. This
result reaffirms that detailed surveillance is crucial for detecting
subtle deviations from the wild phenotype. Ensuring that captive animals
are in optimal condition for life in the wild is especially crucial for
species that experience strong phenotypic selection from some component
of life history (Davis \emph{et al.} 2020; Crates \emph{et al.} 2022).
However, surveillance for altered captive phenotypes is negligible
despite the risks that these changes pose to the success of release
programs (Crates \emph{et al.} 2022). I argue captive breeding programs
should (i) clearly identify components of phenotype that could impose
strong selection (e.g. migration, traits associated with foraging such
as the ability to capture/subdue prey, exaggerated sexual signals), (ii)
establish baseline information about variation in wild phenotypes for
identified traits, (iii) surveil captive populations for extreme
variance in these traits, (iv) where changes are detected, identify the
mechanisms driving them, and (v) quantify the impacts of captive
phenotypes on release success. Rapid post-release mortality of
phenotypically maladapted animals is a waste of conservation resources,
may not benefit wild populations and is ethically problematic. This may
be overcome by focusing on the phenotypic quality (not quantity) of
animals produced so that the likelihood of post-release survival is
increased (Crates \emph{et al.} 2022). Given the wide diversity of taxa
held in zoological collections globally (Conde \emph{et al.} 2011), this
study is likely only the tip of an iceberg of subtle phenotypic changes
are overlooked among captive-bred animals. Implementing the five steps
above is a good start for identifying the scale and magnitude of this
conservation challenge, which is likely to become increasingly important
as the global extinction crisis forces more species into captive
breeding programs (IUCN Conservation planning specialist group 2020).



\textbf{References}

Berger-Tal, O., Blumstein, D.T. \& Swaisgood, R.R. (2020). Conservation
translocations: a review of common difficulties and promising
directions. \emph{Animal Conservation} , 23, 121-131.

Burnside, R.J., Collar, N.J. \& Dolman, P.M. (2017). Comparative
migration strategies of wild and captive-bred Asian
Houbara\emph{Chlamydotis macqueenii} . \emph{Ibis} , 159, 374-389.

Conde, D.A., Flesness, N., Colchero, F., Jones, O.R. \& Scheuerlein, A.
(2011). An emerging role of zoos to conserve biodiversity.\emph{Science}
, 331, 1390.

Crates, R., Stojanovic, D. \& Heinsohn, R. (2022). The phenotypic costs
of captivity. \emph{Biological Reviews} , In Press.

Davis, A.K., Smith, F.M. \& Ballew, A.M. (2020). A poor substitute for
the real thing: captive-reared Monarch Butterflies are weaker, paler and
have less elongated wings than wild migrants. \emph{Biology Letters} ,
16, 20190922.

Davis, C. (2010). A review of the success of major crane conservation
techniques. \emph{Bird Conservation International} , 8, 19-29.

Department of Environment Land Water and Planning (2016). National
Recovery Plan for the Orange-bellied Parrot \emph{Neophema chrysogaster}
. Australian Government Canberra.

Dingle, H. (2014). \emph{Migration: the biology of life on the move.
Second Edition} . Oxford University Press.

Franklin, D., Burbidge, A. \& Dostine, P.L. (2014). The harvest of wild
birds for aviculture: an historical perspective on finch trapping in the
Kimberley with special emphasis on the Gouldian Finch. \emph{Australian
Zoologist} , 31, 92-109.

Hadfield, J. (2010). MCMC Methods for multi-response Generalized Linear
Mixed Models: The MCMCglmm R Package. \emph{Journal of Statistical
Software} , 33, 1-22.

Hall, K.S.S. (2005). Do nine-primaried passerines have nine or ten
primary feathers? The evolution of a concept. \emph{J Ornithol} , 146,
121-126.

Hutchins, M., Marra, P.P., Diebold, E., Kreger, M.D., Sheppard, C.,
Hallager, S. \emph{et al.} (2018). The evolving role of zoological parks
and aquariums in migratory bird conservation. \emph{Zoo Biology} , 37,
360-368.

IUCN Conservation planning specialist group (2020). IUCN Red List
captive breeding recommendations.

Jenni, L. \& Winkler, R. (1989). The feather-length of small passerines:
a measurement for wing-length in live birds and museum skins. \emph{Bird
Study} , 36, 1-15.

Lenth, R. (2018). emmeans: Estimated Marginal Means, aka Least-Squares
Means. R package version 1.1.3.

Lockwood, R., Swaddle, J.P. \& Rayner, J.M.V. (1998). Avian wingtip
shape reconsidered: Wingtip shape indices and morphological adaptations
to migration. \emph{Journal of Avian Biology} , 29, 273-292.

Minias, P., Meissner, W., W\selectlanguage{polish}ł\selectlanguage{english}odarczyk, R., O\selectlanguage{polish}ż\selectlanguage{english}arowska, A., Piasecka, A.,
Kaczmarek, K. \emph{et al.} (2015). Wing shape and migration in
shorebirds: a comparative study. \emph{Ibis} , 157, 528-535.

Morrison, C.E., Johnson, R.N., Grueber, C.E. \& Hogg, C.J. (2020a).
Genetic impacts of conservation management actions in a critically
endangered parrot species. \emph{Conservation Genetics} , In Press.

Morrison, C.E., Johnson, R.N., Grueber, C.E. \& Hogg, C.J. (2020b).
Genetic impacts of conservation management actions in a critically
endangered parrot species. \emph{Conservation Genetics} , 21, 869-877.

Pritchard, R., Kelly, E., Biggs, J., Everaardt, A., Loyn, R., Magrath,
M. \emph{et al.} (In Prep). Identifying cost-effective recovery actions
for a critically endangered species.

Pritchard, R.A., Kelly, E.L., Biggs, J.R., Everaardt, A.N., Loyn, R.,
Magrath, M.J.L. \emph{et al.} (2022). Identifying cost-effective
recovery actions for a critically endangered species. \emph{Conservation
Science and Practice} , 4, e546.

R Development Core Team (2021). R: A language and environment for
statistical computing. \emph{R Foundation for Statistical Computing,
Vienna, Austria} .

Rotics, S., Kaatz, M., Resheff, Y.S., Turjeman, S.F., Zurell, D., Sapir,
N. \emph{et al.} (2016). The challenges of the first migration: movement
and behaviour of juvenile vs. adult White Storks with insights regarding
juvenile mortality. \emph{Journal of Animal Ecology} , 85, 938-947.

Sheard, C., Neate-Clegg, M.H.C., Alioravainen, N., Jones, S.E.I.,
Vincent, C., MacGregor, H.E.A. \emph{et al.} (2020). Ecological drivers
of global gradients in avian dispersal inferred from wing
morphology.\emph{Nature Communications} , 11, 2463.

Shier, D. (2016). Manipulating animal behavior to ensure reintroduction
success. In: \emph{Applying Behavioral Ecology to Wildlife Conservation
and Management} (eds. Berger-Tal, O \& Saltz, D). Cambrige University
Press United Kingdom, pp. 275--304.

Smales, I., Brown, P., Menkhorst, P., Holdsworth, M. \& Holz, P. (2000).
Contribution of captive management of Orange-bellied Parrots to the
recovery programme for the species in Australia. \emph{International Zoo
Yearbook} , 37, 171-178.

Stojanovic, D., Alves, F., Cook, H., Crates, R., Heinsohn, R., Peters,
A. \emph{et al.} (2018). Further knowledge and urgent action required to
save orange-bellied parrots from extinction. \emph{Emu - Austral
Ornithology} , 118, 126-134.

Stojanovic, D., Neeman, T., Crates, R., Troy, S. \& Heinsohn, R.
(2020a). Short-term impacts of prescribed burning on Orange-bellied
Parrot (\emph{Neophema chrysogaster} ) food plant
abundance.\emph{Ecological Management \& Restoration} , In Press.

Stojanovic, D., Neeman, T., Hogg, C.J., Everaardt, A., Wicker, L.,
Young, C.M. \emph{et al.} (2021). Differences in wing shape of captive,
critically endangered, migratory orange-bellied parrots \emph{Neophema
chrysogaster} relative to wild conspecifics. \emph{Emu - Austral
Ornithology} , 1-9.

Stojanovic, D., Neeman, T., Lacy, R., Farquharson, K.A., Hogg, C.J. \&
Heinsohn, R. (2022). Effects of non-random juvenile mortality on small,
inbred populations. \emph{Biological Conservation} , 268, 109504.

Stojanovic, D., Potts, J., Troy, S., Menkhorst, P., Loyn, R. \&
Heinsohn, R. (2020b). Spatial bias in implementation of recovery actions
has not improved survival of orange-bellied parrots \emph{Neophema
chrysogaster} . \emph{Emu} , 120, 263-268.

Stojanovic, D., Young, C.M., Hogg, C.J. \& Heinsohn, R. (2019). Body
mass is not a useful measure of adaptation to captivity in the
orange-bellied parrot \emph{Neophema chrysogaster} . \emph{Emu - Austral
Ornithology} , 120, 162 - 167.

Swaddle, J.P. \& Lockwood, R. (2003). Wingtip shape and flight
performance in the European Starling \emph{Sturnus vulgaris}
.\emph{Ibis} , 145, 457-464.

Taylor, G., Canessa, S., Clarke, R.H., Ingwersen, D., Armstrong, D.P.,
Seddon, P.J. \emph{et al.} (2017). Is Reintroduction Biology an
Effective Applied Science? \emph{Trends Ecol Evol} , 32, 873-880.

Tenger-Trolander, A., Lu, W., Noyes, M. \& Kronforst, M.R. (2019).
Contemporary loss of migration in monarch butterflies. \emph{Proc Natl
Acad Sci U S A} , 116, 14671-14676.

Tripovich, J.S., Popovic, G., Elphinstone, A., Ingwersen, D., Johnson,
G., Schmelitschek, E. \emph{et al.} (2021). Born to be wild: Evaluating
the zoo-based regent honeyeater breed for release program to optimise
individual success and conservation outcomes in the wild.\emph{Frontiers
in Conservation Science} , 2.

Troy, S. \& Lawrence, C. (2021). Report on the Melaleuca wild population
2020/21. Tasmanian Orange-bellied Parrot Program, Tasmanian Department
of Primary Industries, Parks, Water and the Environment.

Tucker, V.A. (1995). Drag reduction by wing tip slots in a gliding
Harris hawk, \emph{Parabuteo unicinctus} . \emph{The Journal of
Experimental Biology} , 198, 775.

Vall-llosera, M. \& Cassey, P. (2017). Physical attractiveness,
constraints to the trade and handling requirements drive the variation
in species availability in the Australian cagebird
trade.\emph{Ecological Economics} , 131, 407-413.

Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis.
Springer-Verlag New York. ISBN 978-3-319-24277-4,
https://ggplot2.tidyverse.org.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2}

\textbf{Figure Captions}

\textbf{Figure 1.} Z scores with 66\% and 95\% credible intervals (black
bars) computed with Bayesian mixed models showing captive-wild pairwise
contrasts of wing feather lengths of birds of 16 species. Primary flight
feathers are numbered in decreasing order counting inward from P10 on
the leading edge of the wing. LW = unflattened wing chord, LP = length
of the longest primary feather, LS = length of the most distal secondary
flight feather. High Z scores indicate that feathers of captive-born
individuals are longer, low Z scores indicate that feathers of wild-born
individuals are longer. Species with significant effects are highlighted
with illustrations (artwork by Julian Teh).

\textbf{Figure 2.} Wing phenotypes of captive- vs. wild-born
orange-bellied parrots. The captive phenotype involves a shorter
outermost flight feather (1mm\textsuperscript{2} grid), and results in
halving of juvenile survival of the first year of life relative to the
wild phenotype. Artwork by Julian Teh.

\textbf{Tables}

\textbf{Table 1.} Summary of fixed effects from Bayesian linear
regression of juvenile survival of orange-bellied parrots reared in
captivity. CI = credible interval, * indicates a significant effect at
0.01, ** indicates a significant effect at 0.1.\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\textbf{Fixed effect} & \textbf{Posterior mean} & \textbf{Lower 95\% CI}
& \textbf{Upper 95\% CI} & \textbf{Effective sample} &
\textbf{P}\tabularnewline
\midrule
\endhead
(Intercept) & -1.95 & -4.43 & 0.65 & 1047.90 & 0.09\tabularnewline
P10 & -1.08 & -1.97 & -0.20 & 690.30 & 0.01*\tabularnewline
P8 & 0.25 & -0.62 & 1.26 & 990.00 & 0.62\tabularnewline
P7 & -0.42 & -1.45 & 0.69 & 836.70 & 0.40\tabularnewline
P6 & 0.03 & -1.46 & 1.39 & 990.00 & 0.95\tabularnewline
P5 & 0.22 & -1.32 & 1.50 & 839.90 & 0.77\tabularnewline
L\textsubscript{W} & 0.32 & -0.54 & 1.30 & 990.00 & 0.52\tabularnewline
L\textsubscript{T} & -0.86 & -1.81 & 0.08 & 734.80 &
0.07\textsuperscript{**}\tabularnewline
Body mass & 0.39 & -0.62 & 1.45 & 787.20 & 0.45\tabularnewline
\bottomrule
\end{longtable}

\selectlanguage{english}
\FloatBarrier
\end{document}

