Biological Conservation

Biological Conservation 160 (2013) 97–104

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Biological Conservation

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Predicting post-release establishment using data from multiple reintroductions

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⇑ Corresponding author. Tel.: +64 6 3569099; fax: +64 6 3505623. E-mail address: E.Parlato@massey.ac.nz (E.H. Parlato).

Elizabeth H. Parlato ⇑, Doug P. Armstrong Wildlife Ecology Group, Institute of Natural Resources, Massey University, Palmerston North, Private Bag 11 222, New Zealand

a r t i c l e i n f o

Article history: Received 22 October 2012 Received in revised form 17 January 2013 Accepted 20 January 2013 Available online 28 February 2013

Keywords: Establishment probability Return rate Bayesian modeling Post-release Survival Dispersal

a b s t r a c t

For any reintroduction it is important to maximise the probability of released individuals establishing in the target area (settling and surviving to breed). Factors influencing establishment have typically been studied at single sites, making it impossible to assess factors that vary at the site level (e.g. connectivity) or quantify unpredictable variation among sites. Using data from 14 reintroductions of the North Island robin (Petroica longipes) to native forest reserves, we show how Bayesian modelling can be used to iden- tify general drivers of establishment and to account for site-to-site variation when making predictions for new sites. High landscape connectivity and high rat tracking rates (a density index) at reintroduction sites were key factors associated with lower individual establishment probabilities. Habitat similarity between source and release sites was also important, as robins sourced from native forest had higher establishment than those from exotic pine forest. Previous predator experience appeared to affect estab- lishment in sites with mammalian predators, as founders sourced from sites with these predators had higher establishment than those from other sites. Our approach can be applied to a wide range of species that are being reintroduced to multiple sites, providing guidance on source and release site selection, effi- cacy of management interventions, and the numbers of individuals to release to achieve desired initial population sizes. The results are not only applicable to these particular species, but can be used to predict site suitability for reintroductions of species with similar dispersal behaviour or other ecological characteristics.

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1. Introduction

Reintroduction is increasingly used to re-establish populations of threatened species within their historical ranges (Sarrazin and Barbault, 1996; Seddon et al., 2007). However, many reintroduc- tion attempts are unsuccessful (Griffith et al., 1989; Sarrazin, 2007; Wolf et al., 1996) and the underlying causes of failure are rarely well understood (Dickens et al., 2010; Fischer and Linden- mayer, 2000; Letty et al., 2007). Analysis of factors influencing reintroduction outcomes is therefore important to improve the success of future reintroduction programmes (Ewen and Arm- strong, 2007; Le Gouar et al., 2012; Sarrazin and Barbault, 1996; Sutherland et al., 2010).

The two key phases affecting the dynamics of reintroduced pop- ulations are establishment and persistence (Armstrong and Sed- don, 2008). While the ultimate goal of any reintroduction is population persistence (Seddon, 1999), this is only achievable if the population survives the establishment phase. There is often elevated mortality (e.g. Calenge et al., 2005; Kreger et al., 2006) and dispersal (e.g. Moehrenschlager and Macdonald, 2003; Tweed

et al., 2003) immediately after release, meaning that reintroduc- tions can fail during the establishment phase even if conditions at the new site would enable persistence once established (Arm- strong and Seddon, 2008). Dispersal and mortality can have similar costs because individuals who disperse and settle away from the reintroduction area will not contribute demographically or genet- ically to the population (Le Gouar et al., 2012).

Because individuals are lost soon after release, the effective ini- tial population size, commonly defined as the number of individu- als that survive to the breeding season, is often much lower than the number of individuals released (Armstrong and Seddon, 2008; Armstrong and Wittmer, 2011). This in turn can exacerbate problems faced by small populations, including demographic sto- chasticity, environmental stochasticity, Allee effects and loss of heterozygosity. Maximising initial population size is therefore an important consideration for any reintroduction.

The most obvious approach to increase the initial population size is to release more individuals. The benefit of larger release groups is widely cited in the literature (e.g. Deredec and Cour- champ, 2007; Griffith et al., 1989; Wolf et al., 1998). However, releasing more individuals has a trade-off with impact on the source population (Armstrong and Wittmer, 2011) and can also have financial and logistical repercussions. There may also be a

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trade-off at an individual and ethical level, as larger founder groups can result in more individuals being lost due to post-release dis- persal or mortality.

An alternative to releasing more individuals is taking measures to reduce post-release mortality or dispersal, thereby increasing the probability of founders settling in the reintroduction area. Pop- ulation establishment is dependent on the probability of reintro- duced individuals establishing at the new site, so understanding the key determinants of individual establishment is important for reintroduction success. Post-release survival and dispersal can be affected by various aspects of a reintroduction; including the trans- location process (e.g. release strategy, Devineau et al., 2011), char- acteristics of the individuals involved (e.g. age or sex, Masuda and Jamieson, 2012; Moehrenschlager and Macdonald, 2003), condi- tions at the reintroduction site (e.g. predator levels, Moorhouse et al., 2009), similarity between release and source sites (Lawrence and Kaye, 2011; Roe et al., 2010; Stamps and Swaisgood, 2007), and the habitat matrix surrounding the reintroduction site (La Morgia et al., 2011). Establishment of reintroduced individuals can therefore be facilitated at various levels; although the most appropriate and effective measures will depend on the species in question. For example, riparian brush rabbits (Sylvilagus bachmani riparius) held longer in enclosures before release had higher post- release survival (Hamilton et al., 2010), whereas delayed release of stitchbirds (Notiomystis cincta) lowered survival compared to birds released immediately (Castro et al., 1995).

Analysis of data collected after reintroduction can provide cru- cial information about factors affecting establishment of individu- als post-release. Importantly, modelled relationships can then be used to make predictions before new reintroductions take place, providing guidance to managers about site suitability and appro- priate measures to improve reintroduction success. However, iden- tification of factors influencing post-release establishment is often based on data from single sites (e.g. Bernardo et al., 2011; Jõgar and Moora, 2008; Roe et al., 2010; Tweed et al., 2003). While these studies can provide valuable insights for the site in question, fac- tors influencing success throughout a species’ range may not be apparent in results from a single site (Jachowski et al., 2011). Using data from reintroduction attempts at multiple sites provides more certainty that identified relationships are general (Johnson, 2002) and therefore applicable to other sites. Analyses of data from single sites are also limited to factors that can be manipulated within that site (for example, release techniques or supplementary feeding). Potentially more important factors, such as habitat quality or con- nectivity, only vary among sites so analysing data from multiple sites is necessary to evaluate their influence on reintroduction outcomes.

There are numerous examples where single species have been released into multiple sites for conservation purposes. In New Zea- land and Australia, more than 40 vertebrate species have each been translocated to at least five different sites (e.g. http://rsg-ocea- nia.squarespace.com/nz/; Short, 2009). In southern Africa, most large herbivores (e.g. Linklater et al., 2011; Van Houtan et al., 2009) and carnivores (e.g. Hayward et al., 2007) have been reintro- duced to multiple sites. There are also examples from other parts of the world, including Griffon vultures (Gyps fulvus) in France (Le Gouar et al., 2008) and black-footed ferrets (Mustela nigripes) in North America (Jachowski et al., 2011). These multiple releases create a unique opportunity to integrate data among sites to iden- tify the key influences on reintroduction outcomes, while also accounting for any unexplained site-to-site variation in population parameters. The results obtained would not only be applicable to the species that have already been reintroduced to multiple sites, but could be used to predict site suitability for reintroductions of species with similar dispersal behaviour or other ecological characteristics.

We present an approach whereby data from multiple reintro- duced populations are integrated into a Bayesian hierarchical mod- el to identify important factors influencing post-release establishment. We model establishment data for North Island rob- ins (Petroica longipes) reintroduced to 14 sites, and show how the resulting model can be used to make predictions for a candidate reintroduction site under alternative management scenarios. The strength of our approach is the ability to model the general influ- ences on establishment while accounting for site-to-site variation, thereby enhancing predictive capability and enabling targeted management to improve reintroduction success.

2. Methods

2.1. Species and reintroductions

The North Island robin is a small (26–32 g) insectivorous forest passerine endemic to New Zealand. The species was historically found over the entire North Island, but is now restricted to native forest remnants and exotic plantations in the central North Island, as well as some offshore islands (Higgins and Peter, 2002). Robins are susceptible to predation, primarily by exotic ship rats (Rattus rattus) (Brown, 1997; Powlesland et al., 1999), but also other exotic mammals such as stoats (Mustela erminea) and native avian preda- tors such as morepork owls (Ninox novaeseelandiae). Their breeding season is generally from early September to February, and juve- niles become sexually mature by the start of the breeding season after that in which they fledge.

North Island robins were reintroduced to 15 different sites (31– 1100 ha forested area) between 1997 and 2007 and analysable data were available for 14 of these (Table 1). Thirteen of the sites were on the North Island and two (Glenfern, Windy Hill) were on Great Barrier Island, a ca. 28,500 ha island off the north-east of the North Island. Reintroductions always occurred between March and August. Pre-release monitoring was conducted at all sites prior to reintroduction and no robins were found. Birds were caught from the wild and were released immediately on arrival at the re- lease site. Robins typically undergo a period of dispersal post-re- lease, and become sedentary once pairs and territories are established in the breeding season. All sites, including the pro- posed site, were managed to control exotic mammalian predators. At the time of reintroduction, two sites were fenced to exclude mammalian predators, which were eradicated after fencing, hence those species were expected to be absent. Another site was fenced but had openings for vehicle access, so mammalian predators re- mained present. All reintroductions were to areas of native forest, and birds could potentially disperse into unmanaged forest in the surrounding landscape. One site also had an exotic pine forest plantation within its boundary.

2.2. Data collection

We compiled data to assess the probability of released individ- uals establishing at each reintroduction site, where ‘‘establish- ment’’ is defined as surviving and remaining at the site until the start of the breeding season (late August). We specifically modelled return rates, which are the proportions of released individuals that remain at the site and are detected (Cam et al., 2005; Martin et al., 1995), as it was impossible to separately estimate establishment and detection probabilities from the data available for some sites. We included data on return rates from initial reintroduction at- tempts only, so any supplementary translocations in subsequent years were excluded from our analysis. All birds were individually colour banded prior to release, and data on the number of birds re- leased and post-release sightings of individuals were available

http://rsg-oceania.squarespace.com/nz/
http://rsg-oceania.squarespace.com/nz/
Table 1 Characteristics of 14 North Island robin reintroduction sites and one proposed reintroduction site.

Site Month and year reintroduced

Number of robins released

Forested predator- control area (ha)a

Peninsula Rat tracking rate (95% CI)b

Standardised habitat ratioc

Connectivity index

Mammalian predators present

Ark in the park April 2005 53 1100 No 0.05 (0.02–0.11) 0.34 97 Yes Boundary stream April 1998 28 800 No 0.01 (0–0.04) �0.48 68 Yes Bushy park August 2001 28 87 No 0.13 (0.01–0.52) �1.08 15 Yes Cape kidnappers May 2007 35 280 Yes 0.10 (0.07–0.15) �0.98 10 Yes Glenfern April 2005 27 230 Yes 0.16 (0.10–0.23) �0.51 54 Yes Hunua May 2001 30 600 No 0.34 (0.23–0.48) 1.79 99 Yes Kakepuku June 1999 30 198 No 0.68 (0.18–0.98) �1.33 33 Yes Paengaroa March 1999 40 101 No 0.27 (0.20–0.34) �0.32 50 Yes Tawharanui March 2007 25 240 Yes 0 (0–0) �0.60 17 No Trounson April 1997 21 445 No 0.01 (0–0.04) 0.15 71 Yes Waotu May 2001 30 31 No 0.54 (0.10–0.93) 1.55 40 Yes Wenderholm March 1999 21 60 Yes 0.37 (0.05–0.85) 0.93 25 Yes Windy hill April 2004 30 267 No 0.27 (0.20–0.35) 1.68 64 Yes Zealandia May 2001 40 225 No 0 (0–0) 0.08 91 No Pukaha (proposed) NA NA 942 No NA NA 60 Yes

a Area of forest managed to control exotic mammalian predators at time of reintroduction. b Tracking tunnel rates estimated from observed data. Imputed values are shown in italics for sites where data were missing (estimated from the modelled relationship

between return rates and tracking tunnel rates for the other sites). c Standardised (mean 0, variance 1) area of accessible forest habitat within 2 km of perimeter of reintroduction site divided by the forested predator-control area.

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from site managers, reports, field notebooks or theses (Pattemore, 2003; Small, 2004). Nine of the sites were systematically searched in September using robin lure tapes at regular distances to identify individuals present at the start of the breeding season. Less tar- geted monitoring was undertaken at 5 sites, where field staff re- corded birds sighted as they carried out other work in the site. Intensity of post-release monitoring is likely to influence the prob- ability of detecting individuals that establish, so we took this into account in our analysis. We expected detection probability to be close to 1 at intensively monitored sites, meaning return rates are equivalent to establishment probabilities, and test this by esti- mating detection probabilities at sites where this is possible.

We also compiled data on variables that were potentially useful predictors of return rates based on our knowledge of the species. These fell into three main categories: (1) Reintroduction site char- acteristics, which included the size of forested predator control area, presence/absence of mammalian predators (ship rats and stoats), rat tracking rate (an index of rat density), and three land- scape variables potentially influencing robin emigration post-re- lease; (2) Translocation process, which included monitoring intensity (moderate or hig