Augmenting the conservation value of rehabilitated wildlife by integrating genetics and population modeling in the post-rehabilitation decision process

Augmenting the conservation value of rehabilitated wildlife by integrating genetics and... Insular populations are particularly vulnerable to the effects of stochastic events, epidemics, and loss of genetic diversity due to inbreeding and genetic drift. The development of successful man- agement options will require accurate baseline data, establishment of clear objectives, and finally monitoring and implementation of corrective measures, if and when required. This study assessed management options for the genetic rehabilitation of highly inbred woylies obtained from wildlife rehabilitation centers. The study generated genetic data for the woylie Bettongia penicillata from a conservation reserve and calculated measures of genetic diversity and individual relatedness. These data were fed into a population viability analysis (PVA) to test genetic outcomes in relation to different management actions. We demonstrated that a careful selection of the founder cohort produced a population with an expected heterozygosity of 70% for a window of approximately 10 years. A proposal to increase the size of the reserve available to the colony was shown to almost double the time at which the colony would retain heterozygosity levels of  70%. Additionally, developing a regular program of supplementation of unrelated woylies would result in a further improvement in their genetic value. This study demonstrated how the application of molecular techniques in combination with PVA can be beneficial for the management of rehabilitated wildlife otherwise considered of little conservation value. This approach can be applied to the management of breeding programs, but also to small, closed populations such as those found on islands, fenced enclosures, insurance populations, and in zoological collections. Key words: Bettongia penicillata, conservation genetics, microsatellite loci, rescue centres, Vortex, vortexR. The ultimate goal of the wildlife rehabilitation is to release individu- difficult to identify a suitable recipient population for their release. als back into the wild in order to mitigate the effects of declining Specific local adaptations can be advantageous for resident animals wild populations (Conway 2011). There are a number of factors (Edmands 1999; Tallmon et al. 2004), while rehabilitated, intro- that contribute to preventing successful reintroductions, including duced individuals from different locations may lack these specific concerns about the genetic suitability of the rehabilitated individu- physical or physiological characteristics that would increase their als. For example, when the origin of animals is unknown, it may be chances of survival or successful breeding at the relocation site. In V C The Author (2017). Published by Oxford University Press. 1 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 2 Current Zoology, 2017, Vol. 0, No. 0 other instances, when a small number of rehabilitated animals inter- wildlife sanctuary near Perth, Dwellingup, in the northern Jarrah breed within the rehabilitation center facilities, the concern may be forest, and Batalling, in the Batalling state forest, 70 km east of related to the level of inbreeding. Inbred animals can have a reduced Bunbury. Karakamia and Dwellingup were established using indi- fitness and deleterious alleles are expressed in homozygous form viduals from Dryandra, while Batalling founders were sourced from (Frankham 1995). The situation may be further compromised when Perup (Pacioni et al. 2013). proper records are unavailable. In this case, identifying wild-caught In 2010, a decision was made to establish a woylie colony at a feral individuals from inbred offspring may be a challenge. While alterna- predator-free enclosed area at Whiteman Park, a conservation reserve tive post-rehabilitation pathways do exist (e.g. display for education north-east of Perth, Western Australia. In this study we focused on iden- purposes only) these are suboptimal, especially when the species in tifying the best management actions for this newly established woylie question is a critically endangered taxon. colony at Whiteman Park that received rehabilitated woylies from Population genetic tools, in combination with population viabil- Chidlow Marsupial Hospital (Chidlow, Western Australia) and from a ity analysis (PVA), can provide the means to redirect these wildlife carer in Wellard (Western Australia). The woylies at the “genetically compromised” animals toward immediate wildlife con- Chidlow Marsupial Hospital were believed to have been sourced from servation actions. An additional situation where the post- Karakamia Sanctuary, while the origin of the animals from the wildlife rehabilitation decision process can be helped by these techniques is carer in Wellard were of unclear origin, but were likely from when rehabilitated animals cannot be moved back into the wild Dwellingup (a translocated population from Dryandra) or Batalling (a because of logistical or other conservation-related reasons, for translocated population from Perup) stock (Figure 2). example, when a disease outbreak has caused a total halt of animal Small populations are exposed to a higher rate of genetic drift movements (Hollings et al. 2013). In these situations, the individuals and therefore, genetic diversity of enclosed (small) populations that are in rehabilitation facilities need to be managed in order to should be closely monitored and managed. Management actions maximize their chances (or their offspring’s chances) of being should ideally aim to maintain genetic diversity at similar levels to released back into the wild when the opportunity presents itself. As wild populations. This aim was going to be a challenge for opposed to captive breeding facilities, where breeding individuals Whiteman Park managers given the highly inbred cohort they had are carefully selected and reproduction is closely monitored and available to establish the woylie colony. However, not meeting this managed, rehabilitation centers typically have no or little control target would mean that this colony would have very little (if any) over which animals are admitted and often lack the facilities and conservation value other than serving as education display. expertise to manage breeding to maintain or increase the genetic Therefore, restoring genetic diversity to the newly established colony value of their offspring. In this study, we demonstrate how the application of population was deemed to be a high management priority. The specific aims of genetics in combination with PVA has enabled the management of this study were to: rehabilitated woylies Bettongia penicillata, to maximize the conser- 1. assess the genetic diversity and relatedness between individual vation outcome of individuals otherwise considered of little conser- pairs of the population established at Whiteman Park and quan- vation value. While there are examples in the literature using similar tify their difference from naturally occurring populations; tools (e.g. Russello et al. 2007; Ivy et al. 2009; Ottewell et al. 2014), 2. identify founders’ populations of origin (if wild caught) or their this study is unique because we show how in highly inbred individu- ancestors (if bred in captivity); als from unknown locations and over time augment genetic diversity 3. evaluate long-term effect of different management actions aimed of previously unmanaged captive populations. to maintain or improve current levels of genetic diversity and The woylie is a small Australian marsupial that has undergone a limit genetic drift. dramatic decline. It is currently classified as Critically Endangered (Wayne et al. 2008; Wayne et al. 2013) because the species went from more than 200,000 individuals in 1999 to around 15,000 in Materials and Methods 2010 (Wayne et al. 2013). Although never identified, a disease out- break was suspected to be either directly or indirectly responsible Individuals from the rehabilitation center and the wildlife carer for the decline (Wayne et al. 2015). As a result of a perceived pan- (Chidlow and Wellard) were managed in Whiteman Park as 2 differ- demic, all woylie translocations were halted for several years, ent stocks: animals from Chidlow (n ¼ 21) were housed in a “soft- including the release of rehabilitated animals into the wild. During release” enclosure (1 ha) and animals from Wellard (n ¼ 11) in a this time, animals held in rehabilitation facilities (either within reha- Woodland Reserve (52 ha). We conducted an assessment of the bilitation centers or with single, licensed wildlife rehabilitators) pro- colony’s genetic diversity, identified the source population through duced offspring. In most cases, there were no good records of the assignment tests, estimated the relatedness between individuals and parental contributors (e.g. identification of founders and offspring). conducted a simulation study to evaluate management options as Government authorities deemed these captive colonies unsuitable described below. Individuals were identified using a microchip for release due to the high likelihood of inbreeding. implant and ear tags. Blood samples from 30 animals were collected Previous genetic work identified four genetically distinct wild in commercial EDTA tubes as part of a health screening. DNA was woylie populations in Western Australia: Dryandra, Perup, extracted using QIAGEN kit following manufacturer’s instructions, Kingston, and Tutanning (Figure 1)(Pacioni et al. 2011). However, using 100 mL of whole blood. Woylies were genotyped at 12 micro- the separation of these populations is likely to be the result of recent satellite loci (summarized in Supplementary Appendix 1) following habitat fragmentation. In fact, analysis of historical samples con- protocols described in Pacioni and Spencer (2010). Reference sam- firmed that all current Australian wild woylie populations belong to ples from previously genotyped wild populations (Pacioni et al. the same evolutionarily significant unit (Pacioni et al. 2015). During 2011; Pacioni et al. 2013) were included to ensure consistency of the late 1990s several translocated populations were established as part of the woylie management plan, including Karakamia, a fenced allele scoring. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Pacioni et al.  Augmenting the conservation value of rehabilitated wildlife 3 1000 0 1000 2000 3000 4000 5000 6000 km Figure 1. Map of woylie population locations. In cyan, the Woodland Reserve at Whiteman Park. In green, the Chidlow Marsupial Hospital and Wellard. In purple other woylie populations. Figure 2. Origin of the woylies (Bettongia penicillata) relocated to Whiteman Park. Dashed arrows indicate unconfirmed origins as reported by the rehabilitation center(later to be confirmed as Dwellingup by the genetic analysis). GENALEX 6.4 (Peakall and Smouse 2006) using 1,000 permutations Genetic diversity Descriptive measures of population genetic diversity were all calcu- to test significant difference from zero. We also reported Nei’s F ST lated using GENALEX 6.4 (Peakall and Smouse 2006) and included (Nei, 1973), calculated under the AMOVA (analysis of molecular var- estimates of genetic diversity within populations: observed (H ) and o iance) framework for comparative purposes as recommended by expected heterozygosity (H ); and mean number of observed (N ), E A Meirmans and Hedrick (2011). expected (N ) and private alleles (PA). In order to further enable the comparison of the genetic variability among populations, we calcu- Parentage and relatedness analyses lated the mean allelic richness (N ) based on 14 diploid individuals AR Two independent analyses were undertaken in order to examine woy- using the rarefaction method implemented in HP-RARE lie relatedness at Whiteman Park. First, Queller and Goodnight’s (Kalinowski, 2005), which compensated for differences in sample (1989) pairwise relatedness (r) was calculated for each pair. The size producing unbiased estimates of allelic richness. within-group mean (QGM) was then calculated along with 95% con- fidence interval via bootstrapping (1,000 iterations) and compared Population assignment tests with the null hypothesis of no relatedness among individuals within Data for indigenous and translocated populations were obtained from groups by testing 1,000 random permutation of the dataset. As a Pacioni et al. (2013; 2011) and used to identify the source populations number of offspring from the colony established in the soft-release of the Chidlow and Wellard stock by performing a Bayesian assign- enclosure were already sampled, parentage testing was only carried ment test using the program STRUCTURE 2.2 (Pritchard et al. 2000). out for this colony, using CERVUS (Kalinowski et al. 2007). Allele Analysis of the data was carried out with the admixture model with frequencies for analysis were calculated and adjusted for null allele, correlated allele frequencies (Pritchard et al. 2000). Information on after merging the dataset of the soft-release enclosure genotypes with the geographic origin was included for the reference data in the prior the data of the source population (as identified by STRUCTURE). probability (i.e. potential source populations), while it was ignored for Additional details of CERVUS analysis are reported in Appendix 2. the individuals that had to be tested (i.e. woylies at Whiteman Park). STRUCTURE results were based on 10 independent runs, using a Population modeling “burn-in” period of 10,000 iterations followed by 100,000 iterations A modification of the baseline PVA model developed by Pacioni of a Markov Chain MonteCarlo. Population differentiation was esti- mated by calculating G’’ (Meirmans and Hedrick 2011)in (2017b) was implemented in VORTEX v9.99 b and used to test ST Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 4 Current Zoology, 2017, Vol. 0, No. 0 possible management actions. Based on expert opinion (Chris of alleles found in the wild populations (proportionally to their fre- Rafferty and Manda Page, pers. comm.), carrying capacity was set quencies). These conditions may not be met. However, it is not pos- to 15 woylies for the soft-release enclosure (note that Whiteman sible to predict in advance what genetic stock will be in care of Park supplements food to woylies in this enclosure) and 70 woylies rehabilitation centers in the future and this scenario has to be con- for Woodland Reserve. Whiteman Park plans to expand the sidered for demonstrative purpose only. Additionally, the model Woodland Reserve by a further 108 ha (giving a total of 160 ha also assumes that supplement survival is not reduced compared to with an estimated carrying capacity of 200 woylies). Allele frequen- “resident” woylies and they will successfully integrate in the breed- cies data for the first 9 of the 12 neutral microsatellite loci described ing pool. above were monitored during the simulations. Two possible man- Projections of two genetic parameters, H and N , were eval- E A agement scenarios that would have been implemented without the uated. Pairwise statistical comparisons between scenarios of similar supportive information generated from this genetic study were conditions (e.g. same carrying capacity) were carried out calculating investigated with this PVA model. A third scenario represents possi- the strictly standardized mean difference (SSMD, Zhang, 2007) ble management actions that make use of the genetic data available between two scenarios considering 2 time horizons: 5 years and from this study. 100 years since the beginning of the simulations. To evaluate Scenario 1. The two sub-units (Chidlow, n ¼ 17, and Wellard, whether a general trend was detectable, we ranked each scenario n ¼ 11) are managed as separate colonies, i.e. the soft-release and based on its strictly standardized mean difference for each genetic Woodland enclosure, respectively. For Wellard stock only, the effect parameters and each time horizon using the non-action scenario of changes in carrying capacity (K) to reflect the hypothesis that (Scenario 1) as a reference and then tested for concordance of rank- woylies may use the whole reserve after the first year (i.e. the area ing using the Kendall’s coefficient of concordance W. The probabil- would increase from 52 ha to 160 ha) is also included in the model. ity of extinction was calculated as the proportion of iterations where Scenario 2. Surplus from Chidlow (i.e. the proportion of the pop- the population went extinct over the total number of iterations run. ulation above the carrying capacity of the soft-release enclosure) is All statistical analysis and plots were conducted using vortexR moved, once a year, into the Woodland Reserve colony. More specif- (Pacioni and Mayer 2017a) in R 3.1.0 (R Core Team, 2016). ically, based on previous trapping data, we predict that 6 woylies a year (with a male sex bias of 3:2) would be relocated to Woodland Results Reserve from the soft-release enclosure once the size of the colony reaches 15 individuals. Genetic assessment Scenario 3. In order to include all individuals with the highest Each enclosure had a relatively low genetic variability (Table 1). heterozygosity (n ¼ 16) and limit the co-presence of highly related Individual heterozygosity ranged from 27.3% to 91.7% individuals the founding cohort in the Woodland Reserve colony is (Supplementary Appendix 3), suggesting a high level of inbreeding selected using genetic data. The effect of changes in K to reflect the in some individuals. The selection of breeders based on the genetic hypothesis that woylies may use the whole reserve after the first year data generated from this study (Scenario 3) proved to be an advanta- (i.e. the area would increase from 52 ha to 160 ha) is also taken into geous strategy. The starting expected heterozygosity and average consideration. numbers of alleles of this colony would be around 73.4% (95% con- We also investigated whether implementing seasonal breeding— fidence interval 73.1–73.7%) and 6 (95% confidence interval 5.96– as observed in Karakamia Sanctuary (Ward et al. 2008) as opposed 6.04), respectively. An improvement of 20% and 50% of the to continuous breeding implemented in Pacioni’s et al. (2017b) base- two parameters (H and N ) compared with either of the existing E A line model—in Scenario 3 would cause any significant difference in colonies (P  0.001). the projected trajectories. This was achieved by using the following The source populations were identified with high level of confi- formula as reproductive rate: dence (Supplementary Appendix 3). In fact, the minimum probabil- 8hi  9 ity at which an individual was assigned to a population was 94%. N N < = 89:3 ðÞ 89:3  57   4 K 0:1þN All woylies from Chidlow (soft release) were identified as sourced þ 4 : 2 ; from Karakamia (Dryandra stock), while all individuals from hi Wellard (Woodland Reserve) were sourced from Dryandra. It N N 89:3 ðÞ 89:3  57   4 K 0:1þN sinðÞ p  Y should be noted that the genetic profile of the population at 2 2 Dwellingup was not available for analysis. However, since woylies in the northern Jarrah forest (Dwellingup) were originally sourced where 83.9 and 57 represent the breeding rate at low and high den- sity, respectively (see Pacioni et al. 2017b for details); from Dryandra, it would be expected that the latter is the most N¼ population size; K¼ carrying capacity; 4 is the maximum per- similar population to the source population of Wellard stock (if centage of breeding females in the non-breeding season (Ward et al. actually from Dwellingup rather than Batalling). Therefore, it is 2008); sin ¼sine and Y is the time-unit of the simulation. Note that inferred that “Wellard” individuals were actually sourced in Pacioni et al. (2017b) model, the reproductive rate is density from Dwellingup, but the analysis assigned them to the most simi- dependent. This feature was maintained in the present study. lar (available) population. The Bayesian assignment results were Lastly, we also modeled the supplementation of the colony in also supported by the overall low differentiation (calculated as Woodland Reserve with 10 woylies (6 males and 4 females, ran- G’’ ) of Whiteman Park woylies from the two source populations ST domly chosen) from wild populations (either indigenous or translo- (Table 2). cated) in Scenarios 2 and 3 to reflect the hypothesis that the colony On average, the relatedness of woylies within each colony was would receive additional individuals from other rehabilitation cen- equivalent of half-sibs or above (i.e. QGM 0.25), confirming the ters. It has to be stressed that the so obtained scenario is a particu- expected high level of inbreeding (P  0.001, Figure 3). In the soft larly optimistic situation. The model assumes that supplemented release enclosure, the paternity analysis identified, with 95% confi- animals are unrelated, and they can have any possible combination dence, the father of 12 of the 14 woylies that were born at Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Pacioni et al.  Augmenting the conservation value of rehabilitated wildlife 5 Table 1. Genetic diversity parameters from this study (bold) and natural or translocated woylie populations Sampling locations nN (SE) N (SE) N (SD) H (SE) % H (SE) % PA (SE) A E AR E o Whiteman Park 28 6.5 (6 0.8) 4 (6 0.5) 5.8 (6 2.2) 70.5 (6 4) 68.4 (6 4) 0.1 (6 0.1) Chidlow MH 17 4.3 (6 0.5) 2.9 (6 0.3) 3 (6 0.8) 61.8 (6 4) 71.1 (6 6) na Wellard 11 3.8 (6 0.4) 2.8 (6 0.2) 2.9 (6 0.8) 58.9 (6 6) 62.2 (6 7) na a,n Dryandra 28 8.9 (6 0.9) 5.8 (6 0.7) 7.8 (6 2.3) 79.6 (6 3) 73.1 (6 5) 0.3 (6 0.2) b, t Karakamia 29 7.5 (6 0.8) 4.9 (6 0.7) 6.7 (6 2.3) 74.5 (6 4) 66.1 (6 7) 0.2 (6 0.1) a, n Tutanning 32 5.5 (6 0.6) 3.2 (6 0.3) 4.8 (6 1.5) 64 (6 5) 64.5 (6 8) 0.6 (6 0.3) a, n Kingston 69 12.1 (6 1.4) 5.9 (6 0.6) 8.2 (6 2.5) 78.8 (6 4) 70.6 (6 6) 1.1 (6 0.4) a, n Perup 102 15 (6 1.8) 7.6 (6 0.9) 9.7 (6 2.7) 83.6 (6 3) 74.6 (6 4) 1.7 (6 0.7) b, t Batalling 35 7.3 (6 0.6) 4.1 (6 0.4) 6.4 (6 1.6) 72.1 (6 4) 71.7 (6 5) 0.2 (6 0.1) n ¼ number of individuals genotyped at microsatellite loci. N ¼average number of alleles. N ¼average effective number of alleles. N ¼average allelic richness. A E AR a b H ¼observed heterozygosity. PA ¼ average private alleles . SE ¼ standard error. SD ¼ standard deviation., (Pacioni et al. 2011)., (Pacioni et al. 2013)., n r t Natural population., Rehabilitation center., Translocated population. Table 2. Pairwise G’’ (above diagonal) and F (below diagonal) values (all P values ¼ 0.001) between this study (bold) and natural or ST ST translocated woylie populations Batalling Dryandra Karakamia Tutanning Perup Kingston Whiteman Park Batalling – 0.530 0.578 0.642 0.318 0.429 0.482 Dryandra 0.111 – 0.213 0.606 0.385 0.482 0.321 Karakamia 0.130 0.046 – 0.651 0.506 0.518 0.311 Tutanning 0.183 0.152 0.175 – 0.620 0.665 0.721 Perup 0.065 0.061 0.096 0.137 – 0.316 0.475 Kingston 0.096 0.089 0.109 0.164 0.056 – 0.463 Whiteman Park 0.131 0.074 0.084 0.214 0.094 0.104 – n t Natural population., Translocated population. (a) (b) Figure 3. Mean pairwise Queller and Goodnight (with 95% confidence interval bars in black) within each Whiteman Park woylie colony and respective source pop- ulations. Red marks represent 95% confidence interval of the null hypothesis of no relatedness between two randomly chosen individuals calculated by perform- ing 1,000 permutations. Whiteman Park (Table 3). Of the 3 genotyped adult males, the data Population modeling indicates that 1 male, supposedly dominant, sired 64% of the off- None of the genetic diversity indices were statistically different spring, with the other two candidates successfully siring 21% and (P > 0.05) when modeling the reproduction as seasonal or continu- 7% of the offspring as expected given the polygamous mating sys- ous (see Table 4 for a brief scenario summary). Therefore, these sim- tem of this species. ulations are not discussed further. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 6 Current Zoology, 2017, Vol. 0, No. 0 Scenario 3 (the “genetic management” strategy) had higher H We ranked all scenarios using the strictly standardized mean dif- and N than Scenario 1 (the 2 colonies in Whiteman Park are man- ference against Wellard projections from Scenario 1, with or with- out increase of the carrying capacity. A significant concordance aged separately).When the genetic management (Scenario 3) was associated with the planned expansion of the Woodland Reserve, between ranking was found (P ¼ 0.0001 and P ¼ 0.001, respec- tively). Simulations from Scenario 3 ranked higher than relative this strategy was significantly more efficient in improving genetic counterparts and simulations that included supplementation ranked diversity than Scenario 1 both in the short term (i.e. Year 5) and the consistently as the top four. None of the analysed scenarios had a long term (i.e. Year 100) (Figure 4, Supplementary Appendix 4). probability of extinction (P ) of more than 2%, except the soft- When compared with Scenario 2, Scenario 3 had overall higher E release colony under the Scenario 1 and Scenario 2 where P was mean values. However, only the heterozygosity at Year 5 was signif- E equal or more than 50%. icantly improved when the selection of founders was associated with an extension of the reserve without implementing any supplementa- tions (Figure 4, Supplementary Appendix 4). Discussion When comparing the effect of an increased carrying capacity In this study, we evaluated how the use of population genetics in asso- (i.e. reserve expansion) on genetic diversity parameters, increasing ciation with PVA can assist in the management of rehabilitated wild- the carrying capacity generally resulted in a higher N and, depend- life. We provided evidence that rehabilitated wildlife that is not ing on the scenario, in a higher H (Figure 4, Supplementary immediately releasable due to genetic concerns can be part of a wider Appendix 4). Simulations that included supplementation had signifi- species conservation plan with adequate long-term management. cantly higher H and N compared to simulations without supple- E A The 2 Whiteman Park colonies established from woylies that mentation. However, there were no significant differences between bred unmanaged in rehabilitation settings had, as expected, low Scenario 3 and Scenario 2 when the supplementation program was genetic diversity, since only few animals were wild-caught and some implemented, except for the heterozygosity at Year 5 when carrying of the founders of the colonies were offspring born in captivity. An capacity was increased (Figure 4, Supplementary Appendix 4). H of 70% is generally considered the minimum acceptable level in macropods (Pope et al. 2000) and the only modeled scenario Table 3. Paternity analysis of offspring in the soft-release enclosure where a woylie colony at Whiteman Park was above this threshold Offspring First parent non-exclusion Candidate Pair from early on in the simulations was in the Scenario 3. This demon- ID probability (%) father ID confidence strates the value and the need for the genetic management of this colony. The identified levels of H were comparable to the lower 6B3C6A2 0.7 6B3E96C * end of those found in other wild populations (e.g. Tutanning or 6B3DA2B 0.7 6B3B6F4 * Batalling) and, broadly speaking, comparable to what is commonly 6B3A0AF 0.2 6B3E4B4 * found in other macropods (Pope et al. 2000). It should be stressed 6B3A0AF 0.2 6B3E96C 6B3D2E3 0.1 6B3E96C * that previous translocations indicated that woylie mortality rates are 6B39FF3 0.7 6B3E96C * extremely low when moved to fenced, predator-free areas. 6B39264 0.3 6B3B6F4 * Consequently, the risk of losing genetically valuable individuals 6B3A317 0.1 6B3E96C * when creating the founding stock in Scenario 3 was considered mini- 6B3A6B0 0.1 6B3E96C * mal. Additionally, there was no interest in managing the genetic var- 6B3B485 0.2 6B3E96C * iability in the soft release enclosure, as the holding area was too 6B3BBBA 0.5 6B3B6F4 * small to maintain high genetic variability in the long term. 6B3E554 0.0 In the long term, the planned reserve expansion would slow 6B3AF33 3.5 6B3E96C * down the rate at which genetic diversity is lost due to genetic drift, 6B39AD7 0.1 6B3E96C * making it a very effective conservation strategy. N is the genetic *indicates 95% confidence interval. index that is mostly influenced by this option. Most importantly, the Table 4. Abbreviations of PVA scenarios and their brief description Scenario Description Chidlow MH Scenario 1 Chidlow stock Wellard K70 Scenario 1 Wellard stock Wellard incK(200) Scenario 1 Wellard stock and K increases to 200 after the first year Chid_Well_disp Scenario 2 Chid_Well_disp incK(200) Scenario 2 and K increases to 200 after the first year Chid_Well_disp Suppl Scenario 2 plus the supplementation of 10 individuals once a year Chid_Well_disp Suppl incK(200) Scenario 2 plus K increases to 200 after the first year and the supplementation of ten individuals once a year Woodland Sel Scenario 3 Selection of breeders in the Woodland Reserve Woodland Sel incK(200) Scenario 3 Selection of breeders in the Woodland Reserve. K increases to 200 after the first year Woodland Sel Seas As for Woodland Sel, but reproduction is seasonal Woodland Sel Seas incK(200) As for Woodland Sel, but reproduction is seasonal and K increases to 200 after the first year Woodland Sel Suppl As for Woodland Sel, but the colony is supplemented with 10 individuals once a year Woodland Sel Suppl incK(200) As for Woodland Sel, but the colony is supplemented with 10 individuals once a year and K increases to 200 after the first year Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Pacioni et al.  Augmenting the conservation value of rehabilitated wildlife 7 Figure 4. Dot plot showing mean and SD of genetic diversity of the woylie colony in the Woodland Reserve at Whiteman Park at year five (left plots) and Year 100 (right plots) in different PVA scenarios. In blue scenarios where supplementation is implemented. Scenarios with increase in the carrying capacity of the reserve are indicated with circles. Scenario names are listed in Table 4. simulations demonstrated that supplementing 10 animals once a will be related to the supplementation with genetically valuable indi- year is the management action that would substantially improve the viduals, as well as on their successful settlement in the colony. genetic profile of the colony and counteract the effect of genetic drift Scenario 2 offers similar benefits to Scenario 3, but the obtained in both short term (5 years) and long term (100 years). A combina- information on the genetic makeup of the founding colony will tion of supplementation and increased carrying capacity would allow managers to make informed, and therefore more targeted, boost the genetic diversity of the Whiteman Park woylie colony to a decisions when supplementing animals from other sites. Without level comparable to that of large wild populations (e.g. Perup). In genetic management (Scenario 2) individuals with lower genetic and this case, the role of the woylie colony at Whiteman Park would conservation value could utilize resources that could be made avail- change from being an education display colony to a potential source able to more valuable individuals (including possible external sup- population for other translocations, either to establish new popula- plementations), while in Scenario 3 every supplementation is tions or supplement existing wild and captive populations. Of directed toward an increase in genetic variability. Additionally, course, the conservation value of the Whiteman Park woylie colony although the difference was not statistically significant, Scenario 3 Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 8 Current Zoology, 2017, Vol. 0, No. 0 options ranked better than the Scenario 2 counterparts. Considering depression. Additionally, adaptation to captivity (Frankham 2007) the lowering costs of genetic analyses and the clear advantages when is a serious issue that needs to be considered and when possible the managing inbred populations of unknown sources, we recommend use of wild-caught individuals has been recommended as the pre- Scenario 3 as optimal management action, and ideally in association ferred option when carrying out translocations (Pacioni et al. 2013). with the supplementation of woylies from other sources. In our cases, most individuals have been kept in captivity for only 2– Additionally, we recommend ongoing genetic monitoring to ver- 3 generations prior to being released in Woodland Reserve, while ify the modeled changes in the population. Possible concerns may most of the concerns related to captivity adaptation are associated arise if a small number of males dominate the reproductive output, with long-term captive breeding (Frankham 2007). the projected genetic diversity and fitness of the colony may be nega- Our recommendations rely on the assumption that the projected tively affected. While logistic reasons prevent Whiteman Park from trajectories of our simulations are accurate and effectively predict directly managing family groups (equalizing family sizes), other the population responses to different management options. Future management options (e.g. removal of dominant males) can help research will need to evaluate how reliable these conclusions are and achieve the targeted conservation goals. inform management on possible needed adjustments in order to The PVA model did not incorporate any stochastic events such as meet the established targets. The focus of future studies should aim fire, introduced predators (fox or cat incursions), or epidemics. to monitor genetic diversity over time, quantify uncertain simulation Consequently, genetic trends and the probability of extinction gener- parameters, like supplement survival rates, to further improve accu- ated by the analyses depend only on the “natural” fluctuation of the racy of the models, and, critically, compare predictions with actual survival, reproductive rates, and environmental variability of the car- data to verify the appropriateness of the developed models for mak- rying capacity (which were all generally modeled with a standard ing management decisions. deviation of 10% of the mean value, see Pacioni et al. 2017b). To conclude, while wildlife captive breeding should always be Increased genetic variability, in association with a large population planned and coordinated in consultation with conservation agencies size, is considered protective toward stochastic events (Maschinski and relevant authorities, and be accompanied by as accurate records et al. 2013) and it is possible to formally test the effect of these sto- as possible, we demonstrated that by using a combination of popula- chastic incidents within a PVA should this be required. Regardless, tion genetic tools and population modeling rehabilitated animals adequate steps toward prevention from these events should be under- can be used to achieve targeted genetic variability goals over time taken given the potential impact on the viability of the colony, due to even with suboptimal founders. Our approach has wide application their relatively small population size and captive environment. for different species and in widely differing demographic and man- We argue that our approach and methodology have general applicability when evaluating possible destinations for any species agement contexts, where ultimately, the goal is to maximize the of rehabilitated wildlife. This information, in combination with potential conservation outcome of any rehabilitation process. already available frameworks (Frankham et al. 2011; Weeks et al. 2011) would be of great help to make informed management deci- Acknowledgments sions. Similarly, our approach is suitable for the development of management plans for captive breeding colonies or zoological col- We are very grateful to Malcolm Kennedy for comments on early draft of this lections, where founders are generally assumed to be unrelated. manuscript and to Craig Thompson for providing DNA extractions for this However, we warn the readers that a number of factors played in study. We would also like to thank two anonymous reviewers whose com- “favour” of the woylie and would like to stress that by presenting ments have greatly improved this manuscript. the possible applications of genetic and population modeling techni- ques described in this article for rehabilitated wildlife, we by no Supplementary Material means intend to promote uncontrolled breeding of wildlife in care. Previous studies had confirmed that all current Australian wild woy- Supplementary material can be found at https://academic.oup.com/cz. lie populations belong to the same evolutionarily significant unit (Pacioni et al. 2011; Pacioni et al. 2015) and admixing of individuals References from different sources would not be expected to pose an outbreeding depression risk for the colony. Historically woylies have had a wide Conway WG, 2011. Buying time for wild animals with zoos. Zoo Biol 30:1–8. distribution and therefore assumed to be highly adapted to different Edmands S, 1999. Heterosis and outbreeding depression in interpopulation environments (from arid and semi-arid coastal and inland habitats crosses spanning a wide range of divergence. Evolution 53:1757–1768. Finlayson GR, Finlayson ST, Dickman CR, 2010. 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Assessing the benefits and risks of translocations in changing environments: Pacioni C, Williams M, Lacy RC, Spencer PBS, Wayne AF. 2017b. Predators a genetic perspective. Evol Appl 4:709–725. and genetic fitness: key threatening factors for the conservation of bettong Zhang XD, 2007. A pair of new statistical parameters for quality control in species. Pacific Conservation Biology, 23:200–212. RNA interference high-through put screening assays. Genomics 89:552–561. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Current Zoology Oxford University Press

Augmenting the conservation value of rehabilitated wildlife by integrating genetics and population modeling in the post-rehabilitation decision process

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Abstract

Insular populations are particularly vulnerable to the effects of stochastic events, epidemics, and loss of genetic diversity due to inbreeding and genetic drift. The development of successful man- agement options will require accurate baseline data, establishment of clear objectives, and finally monitoring and implementation of corrective measures, if and when required. This study assessed management options for the genetic rehabilitation of highly inbred woylies obtained from wildlife rehabilitation centers. The study generated genetic data for the woylie Bettongia penicillata from a conservation reserve and calculated measures of genetic diversity and individual relatedness. These data were fed into a population viability analysis (PVA) to test genetic outcomes in relation to different management actions. We demonstrated that a careful selection of the founder cohort produced a population with an expected heterozygosity of 70% for a window of approximately 10 years. A proposal to increase the size of the reserve available to the colony was shown to almost double the time at which the colony would retain heterozygosity levels of  70%. Additionally, developing a regular program of supplementation of unrelated woylies would result in a further improvement in their genetic value. This study demonstrated how the application of molecular techniques in combination with PVA can be beneficial for the management of rehabilitated wildlife otherwise considered of little conservation value. This approach can be applied to the management of breeding programs, but also to small, closed populations such as those found on islands, fenced enclosures, insurance populations, and in zoological collections. Key words: Bettongia penicillata, conservation genetics, microsatellite loci, rescue centres, Vortex, vortexR. The ultimate goal of the wildlife rehabilitation is to release individu- difficult to identify a suitable recipient population for their release. als back into the wild in order to mitigate the effects of declining Specific local adaptations can be advantageous for resident animals wild populations (Conway 2011). There are a number of factors (Edmands 1999; Tallmon et al. 2004), while rehabilitated, intro- that contribute to preventing successful reintroductions, including duced individuals from different locations may lack these specific concerns about the genetic suitability of the rehabilitated individu- physical or physiological characteristics that would increase their als. For example, when the origin of animals is unknown, it may be chances of survival or successful breeding at the relocation site. In V C The Author (2017). Published by Oxford University Press. 1 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 2 Current Zoology, 2017, Vol. 0, No. 0 other instances, when a small number of rehabilitated animals inter- wildlife sanctuary near Perth, Dwellingup, in the northern Jarrah breed within the rehabilitation center facilities, the concern may be forest, and Batalling, in the Batalling state forest, 70 km east of related to the level of inbreeding. Inbred animals can have a reduced Bunbury. Karakamia and Dwellingup were established using indi- fitness and deleterious alleles are expressed in homozygous form viduals from Dryandra, while Batalling founders were sourced from (Frankham 1995). The situation may be further compromised when Perup (Pacioni et al. 2013). proper records are unavailable. In this case, identifying wild-caught In 2010, a decision was made to establish a woylie colony at a feral individuals from inbred offspring may be a challenge. While alterna- predator-free enclosed area at Whiteman Park, a conservation reserve tive post-rehabilitation pathways do exist (e.g. display for education north-east of Perth, Western Australia. In this study we focused on iden- purposes only) these are suboptimal, especially when the species in tifying the best management actions for this newly established woylie question is a critically endangered taxon. colony at Whiteman Park that received rehabilitated woylies from Population genetic tools, in combination with population viabil- Chidlow Marsupial Hospital (Chidlow, Western Australia) and from a ity analysis (PVA), can provide the means to redirect these wildlife carer in Wellard (Western Australia). The woylies at the “genetically compromised” animals toward immediate wildlife con- Chidlow Marsupial Hospital were believed to have been sourced from servation actions. An additional situation where the post- Karakamia Sanctuary, while the origin of the animals from the wildlife rehabilitation decision process can be helped by these techniques is carer in Wellard were of unclear origin, but were likely from when rehabilitated animals cannot be moved back into the wild Dwellingup (a translocated population from Dryandra) or Batalling (a because of logistical or other conservation-related reasons, for translocated population from Perup) stock (Figure 2). example, when a disease outbreak has caused a total halt of animal Small populations are exposed to a higher rate of genetic drift movements (Hollings et al. 2013). In these situations, the individuals and therefore, genetic diversity of enclosed (small) populations that are in rehabilitation facilities need to be managed in order to should be closely monitored and managed. Management actions maximize their chances (or their offspring’s chances) of being should ideally aim to maintain genetic diversity at similar levels to released back into the wild when the opportunity presents itself. As wild populations. This aim was going to be a challenge for opposed to captive breeding facilities, where breeding individuals Whiteman Park managers given the highly inbred cohort they had are carefully selected and reproduction is closely monitored and available to establish the woylie colony. However, not meeting this managed, rehabilitation centers typically have no or little control target would mean that this colony would have very little (if any) over which animals are admitted and often lack the facilities and conservation value other than serving as education display. expertise to manage breeding to maintain or increase the genetic Therefore, restoring genetic diversity to the newly established colony value of their offspring. In this study, we demonstrate how the application of population was deemed to be a high management priority. The specific aims of genetics in combination with PVA has enabled the management of this study were to: rehabilitated woylies Bettongia penicillata, to maximize the conser- 1. assess the genetic diversity and relatedness between individual vation outcome of individuals otherwise considered of little conser- pairs of the population established at Whiteman Park and quan- vation value. While there are examples in the literature using similar tify their difference from naturally occurring populations; tools (e.g. Russello et al. 2007; Ivy et al. 2009; Ottewell et al. 2014), 2. identify founders’ populations of origin (if wild caught) or their this study is unique because we show how in highly inbred individu- ancestors (if bred in captivity); als from unknown locations and over time augment genetic diversity 3. evaluate long-term effect of different management actions aimed of previously unmanaged captive populations. to maintain or improve current levels of genetic diversity and The woylie is a small Australian marsupial that has undergone a limit genetic drift. dramatic decline. It is currently classified as Critically Endangered (Wayne et al. 2008; Wayne et al. 2013) because the species went from more than 200,000 individuals in 1999 to around 15,000 in Materials and Methods 2010 (Wayne et al. 2013). Although never identified, a disease out- break was suspected to be either directly or indirectly responsible Individuals from the rehabilitation center and the wildlife carer for the decline (Wayne et al. 2015). As a result of a perceived pan- (Chidlow and Wellard) were managed in Whiteman Park as 2 differ- demic, all woylie translocations were halted for several years, ent stocks: animals from Chidlow (n ¼ 21) were housed in a “soft- including the release of rehabilitated animals into the wild. During release” enclosure (1 ha) and animals from Wellard (n ¼ 11) in a this time, animals held in rehabilitation facilities (either within reha- Woodland Reserve (52 ha). We conducted an assessment of the bilitation centers or with single, licensed wildlife rehabilitators) pro- colony’s genetic diversity, identified the source population through duced offspring. In most cases, there were no good records of the assignment tests, estimated the relatedness between individuals and parental contributors (e.g. identification of founders and offspring). conducted a simulation study to evaluate management options as Government authorities deemed these captive colonies unsuitable described below. Individuals were identified using a microchip for release due to the high likelihood of inbreeding. implant and ear tags. Blood samples from 30 animals were collected Previous genetic work identified four genetically distinct wild in commercial EDTA tubes as part of a health screening. DNA was woylie populations in Western Australia: Dryandra, Perup, extracted using QIAGEN kit following manufacturer’s instructions, Kingston, and Tutanning (Figure 1)(Pacioni et al. 2011). However, using 100 mL of whole blood. Woylies were genotyped at 12 micro- the separation of these populations is likely to be the result of recent satellite loci (summarized in Supplementary Appendix 1) following habitat fragmentation. In fact, analysis of historical samples con- protocols described in Pacioni and Spencer (2010). Reference sam- firmed that all current Australian wild woylie populations belong to ples from previously genotyped wild populations (Pacioni et al. the same evolutionarily significant unit (Pacioni et al. 2015). During 2011; Pacioni et al. 2013) were included to ensure consistency of the late 1990s several translocated populations were established as part of the woylie management plan, including Karakamia, a fenced allele scoring. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Pacioni et al.  Augmenting the conservation value of rehabilitated wildlife 3 1000 0 1000 2000 3000 4000 5000 6000 km Figure 1. Map of woylie population locations. In cyan, the Woodland Reserve at Whiteman Park. In green, the Chidlow Marsupial Hospital and Wellard. In purple other woylie populations. Figure 2. Origin of the woylies (Bettongia penicillata) relocated to Whiteman Park. Dashed arrows indicate unconfirmed origins as reported by the rehabilitation center(later to be confirmed as Dwellingup by the genetic analysis). GENALEX 6.4 (Peakall and Smouse 2006) using 1,000 permutations Genetic diversity Descriptive measures of population genetic diversity were all calcu- to test significant difference from zero. We also reported Nei’s F ST lated using GENALEX 6.4 (Peakall and Smouse 2006) and included (Nei, 1973), calculated under the AMOVA (analysis of molecular var- estimates of genetic diversity within populations: observed (H ) and o iance) framework for comparative purposes as recommended by expected heterozygosity (H ); and mean number of observed (N ), E A Meirmans and Hedrick (2011). expected (N ) and private alleles (PA). In order to further enable the comparison of the genetic variability among populations, we calcu- Parentage and relatedness analyses lated the mean allelic richness (N ) based on 14 diploid individuals AR Two independent analyses were undertaken in order to examine woy- using the rarefaction method implemented in HP-RARE lie relatedness at Whiteman Park. First, Queller and Goodnight’s (Kalinowski, 2005), which compensated for differences in sample (1989) pairwise relatedness (r) was calculated for each pair. The size producing unbiased estimates of allelic richness. within-group mean (QGM) was then calculated along with 95% con- fidence interval via bootstrapping (1,000 iterations) and compared Population assignment tests with the null hypothesis of no relatedness among individuals within Data for indigenous and translocated populations were obtained from groups by testing 1,000 random permutation of the dataset. As a Pacioni et al. (2013; 2011) and used to identify the source populations number of offspring from the colony established in the soft-release of the Chidlow and Wellard stock by performing a Bayesian assign- enclosure were already sampled, parentage testing was only carried ment test using the program STRUCTURE 2.2 (Pritchard et al. 2000). out for this colony, using CERVUS (Kalinowski et al. 2007). Allele Analysis of the data was carried out with the admixture model with frequencies for analysis were calculated and adjusted for null allele, correlated allele frequencies (Pritchard et al. 2000). Information on after merging the dataset of the soft-release enclosure genotypes with the geographic origin was included for the reference data in the prior the data of the source population (as identified by STRUCTURE). probability (i.e. potential source populations), while it was ignored for Additional details of CERVUS analysis are reported in Appendix 2. the individuals that had to be tested (i.e. woylies at Whiteman Park). STRUCTURE results were based on 10 independent runs, using a Population modeling “burn-in” period of 10,000 iterations followed by 100,000 iterations A modification of the baseline PVA model developed by Pacioni of a Markov Chain MonteCarlo. Population differentiation was esti- mated by calculating G’’ (Meirmans and Hedrick 2011)in (2017b) was implemented in VORTEX v9.99 b and used to test ST Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 4 Current Zoology, 2017, Vol. 0, No. 0 possible management actions. Based on expert opinion (Chris of alleles found in the wild populations (proportionally to their fre- Rafferty and Manda Page, pers. comm.), carrying capacity was set quencies). These conditions may not be met. However, it is not pos- to 15 woylies for the soft-release enclosure (note that Whiteman sible to predict in advance what genetic stock will be in care of Park supplements food to woylies in this enclosure) and 70 woylies rehabilitation centers in the future and this scenario has to be con- for Woodland Reserve. Whiteman Park plans to expand the sidered for demonstrative purpose only. Additionally, the model Woodland Reserve by a further 108 ha (giving a total of 160 ha also assumes that supplement survival is not reduced compared to with an estimated carrying capacity of 200 woylies). Allele frequen- “resident” woylies and they will successfully integrate in the breed- cies data for the first 9 of the 12 neutral microsatellite loci described ing pool. above were monitored during the simulations. Two possible man- Projections of two genetic parameters, H and N , were eval- E A agement scenarios that would have been implemented without the uated. Pairwise statistical comparisons between scenarios of similar supportive information generated from this genetic study were conditions (e.g. same carrying capacity) were carried out calculating investigated with this PVA model. A third scenario represents possi- the strictly standardized mean difference (SSMD, Zhang, 2007) ble management actions that make use of the genetic data available between two scenarios considering 2 time horizons: 5 years and from this study. 100 years since the beginning of the simulations. To evaluate Scenario 1. The two sub-units (Chidlow, n ¼ 17, and Wellard, whether a general trend was detectable, we ranked each scenario n ¼ 11) are managed as separate colonies, i.e. the soft-release and based on its strictly standardized mean difference for each genetic Woodland enclosure, respectively. For Wellard stock only, the effect parameters and each time horizon using the non-action scenario of changes in carrying capacity (K) to reflect the hypothesis that (Scenario 1) as a reference and then tested for concordance of rank- woylies may use the whole reserve after the first year (i.e. the area ing using the Kendall’s coefficient of concordance W. The probabil- would increase from 52 ha to 160 ha) is also included in the model. ity of extinction was calculated as the proportion of iterations where Scenario 2. Surplus from Chidlow (i.e. the proportion of the pop- the population went extinct over the total number of iterations run. ulation above the carrying capacity of the soft-release enclosure) is All statistical analysis and plots were conducted using vortexR moved, once a year, into the Woodland Reserve colony. More specif- (Pacioni and Mayer 2017a) in R 3.1.0 (R Core Team, 2016). ically, based on previous trapping data, we predict that 6 woylies a year (with a male sex bias of 3:2) would be relocated to Woodland Results Reserve from the soft-release enclosure once the size of the colony reaches 15 individuals. Genetic assessment Scenario 3. In order to include all individuals with the highest Each enclosure had a relatively low genetic variability (Table 1). heterozygosity (n ¼ 16) and limit the co-presence of highly related Individual heterozygosity ranged from 27.3% to 91.7% individuals the founding cohort in the Woodland Reserve colony is (Supplementary Appendix 3), suggesting a high level of inbreeding selected using genetic data. The effect of changes in K to reflect the in some individuals. The selection of breeders based on the genetic hypothesis that woylies may use the whole reserve after the first year data generated from this study (Scenario 3) proved to be an advanta- (i.e. the area would increase from 52 ha to 160 ha) is also taken into geous strategy. The starting expected heterozygosity and average consideration. numbers of alleles of this colony would be around 73.4% (95% con- We also investigated whether implementing seasonal breeding— fidence interval 73.1–73.7%) and 6 (95% confidence interval 5.96– as observed in Karakamia Sanctuary (Ward et al. 2008) as opposed 6.04), respectively. An improvement of 20% and 50% of the to continuous breeding implemented in Pacioni’s et al. (2017b) base- two parameters (H and N ) compared with either of the existing E A line model—in Scenario 3 would cause any significant difference in colonies (P  0.001). the projected trajectories. This was achieved by using the following The source populations were identified with high level of confi- formula as reproductive rate: dence (Supplementary Appendix 3). In fact, the minimum probabil- 8hi  9 ity at which an individual was assigned to a population was 94%. N N < = 89:3 ðÞ 89:3  57   4 K 0:1þN All woylies from Chidlow (soft release) were identified as sourced þ 4 : 2 ; from Karakamia (Dryandra stock), while all individuals from hi Wellard (Woodland Reserve) were sourced from Dryandra. It N N 89:3 ðÞ 89:3  57   4 K 0:1þN sinðÞ p  Y should be noted that the genetic profile of the population at 2 2 Dwellingup was not available for analysis. However, since woylies in the northern Jarrah forest (Dwellingup) were originally sourced where 83.9 and 57 represent the breeding rate at low and high den- sity, respectively (see Pacioni et al. 2017b for details); from Dryandra, it would be expected that the latter is the most N¼ population size; K¼ carrying capacity; 4 is the maximum per- similar population to the source population of Wellard stock (if centage of breeding females in the non-breeding season (Ward et al. actually from Dwellingup rather than Batalling). Therefore, it is 2008); sin ¼sine and Y is the time-unit of the simulation. Note that inferred that “Wellard” individuals were actually sourced in Pacioni et al. (2017b) model, the reproductive rate is density from Dwellingup, but the analysis assigned them to the most simi- dependent. This feature was maintained in the present study. lar (available) population. The Bayesian assignment results were Lastly, we also modeled the supplementation of the colony in also supported by the overall low differentiation (calculated as Woodland Reserve with 10 woylies (6 males and 4 females, ran- G’’ ) of Whiteman Park woylies from the two source populations ST domly chosen) from wild populations (either indigenous or translo- (Table 2). cated) in Scenarios 2 and 3 to reflect the hypothesis that the colony On average, the relatedness of woylies within each colony was would receive additional individuals from other rehabilitation cen- equivalent of half-sibs or above (i.e. QGM 0.25), confirming the ters. It has to be stressed that the so obtained scenario is a particu- expected high level of inbreeding (P  0.001, Figure 3). In the soft larly optimistic situation. The model assumes that supplemented release enclosure, the paternity analysis identified, with 95% confi- animals are unrelated, and they can have any possible combination dence, the father of 12 of the 14 woylies that were born at Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Pacioni et al.  Augmenting the conservation value of rehabilitated wildlife 5 Table 1. Genetic diversity parameters from this study (bold) and natural or translocated woylie populations Sampling locations nN (SE) N (SE) N (SD) H (SE) % H (SE) % PA (SE) A E AR E o Whiteman Park 28 6.5 (6 0.8) 4 (6 0.5) 5.8 (6 2.2) 70.5 (6 4) 68.4 (6 4) 0.1 (6 0.1) Chidlow MH 17 4.3 (6 0.5) 2.9 (6 0.3) 3 (6 0.8) 61.8 (6 4) 71.1 (6 6) na Wellard 11 3.8 (6 0.4) 2.8 (6 0.2) 2.9 (6 0.8) 58.9 (6 6) 62.2 (6 7) na a,n Dryandra 28 8.9 (6 0.9) 5.8 (6 0.7) 7.8 (6 2.3) 79.6 (6 3) 73.1 (6 5) 0.3 (6 0.2) b, t Karakamia 29 7.5 (6 0.8) 4.9 (6 0.7) 6.7 (6 2.3) 74.5 (6 4) 66.1 (6 7) 0.2 (6 0.1) a, n Tutanning 32 5.5 (6 0.6) 3.2 (6 0.3) 4.8 (6 1.5) 64 (6 5) 64.5 (6 8) 0.6 (6 0.3) a, n Kingston 69 12.1 (6 1.4) 5.9 (6 0.6) 8.2 (6 2.5) 78.8 (6 4) 70.6 (6 6) 1.1 (6 0.4) a, n Perup 102 15 (6 1.8) 7.6 (6 0.9) 9.7 (6 2.7) 83.6 (6 3) 74.6 (6 4) 1.7 (6 0.7) b, t Batalling 35 7.3 (6 0.6) 4.1 (6 0.4) 6.4 (6 1.6) 72.1 (6 4) 71.7 (6 5) 0.2 (6 0.1) n ¼ number of individuals genotyped at microsatellite loci. N ¼average number of alleles. N ¼average effective number of alleles. N ¼average allelic richness. A E AR a b H ¼observed heterozygosity. PA ¼ average private alleles . SE ¼ standard error. SD ¼ standard deviation., (Pacioni et al. 2011)., (Pacioni et al. 2013)., n r t Natural population., Rehabilitation center., Translocated population. Table 2. Pairwise G’’ (above diagonal) and F (below diagonal) values (all P values ¼ 0.001) between this study (bold) and natural or ST ST translocated woylie populations Batalling Dryandra Karakamia Tutanning Perup Kingston Whiteman Park Batalling – 0.530 0.578 0.642 0.318 0.429 0.482 Dryandra 0.111 – 0.213 0.606 0.385 0.482 0.321 Karakamia 0.130 0.046 – 0.651 0.506 0.518 0.311 Tutanning 0.183 0.152 0.175 – 0.620 0.665 0.721 Perup 0.065 0.061 0.096 0.137 – 0.316 0.475 Kingston 0.096 0.089 0.109 0.164 0.056 – 0.463 Whiteman Park 0.131 0.074 0.084 0.214 0.094 0.104 – n t Natural population., Translocated population. (a) (b) Figure 3. Mean pairwise Queller and Goodnight (with 95% confidence interval bars in black) within each Whiteman Park woylie colony and respective source pop- ulations. Red marks represent 95% confidence interval of the null hypothesis of no relatedness between two randomly chosen individuals calculated by perform- ing 1,000 permutations. Whiteman Park (Table 3). Of the 3 genotyped adult males, the data Population modeling indicates that 1 male, supposedly dominant, sired 64% of the off- None of the genetic diversity indices were statistically different spring, with the other two candidates successfully siring 21% and (P > 0.05) when modeling the reproduction as seasonal or continu- 7% of the offspring as expected given the polygamous mating sys- ous (see Table 4 for a brief scenario summary). Therefore, these sim- tem of this species. ulations are not discussed further. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 6 Current Zoology, 2017, Vol. 0, No. 0 Scenario 3 (the “genetic management” strategy) had higher H We ranked all scenarios using the strictly standardized mean dif- and N than Scenario 1 (the 2 colonies in Whiteman Park are man- ference against Wellard projections from Scenario 1, with or with- out increase of the carrying capacity. A significant concordance aged separately).When the genetic management (Scenario 3) was associated with the planned expansion of the Woodland Reserve, between ranking was found (P ¼ 0.0001 and P ¼ 0.001, respec- tively). Simulations from Scenario 3 ranked higher than relative this strategy was significantly more efficient in improving genetic counterparts and simulations that included supplementation ranked diversity than Scenario 1 both in the short term (i.e. Year 5) and the consistently as the top four. None of the analysed scenarios had a long term (i.e. Year 100) (Figure 4, Supplementary Appendix 4). probability of extinction (P ) of more than 2%, except the soft- When compared with Scenario 2, Scenario 3 had overall higher E release colony under the Scenario 1 and Scenario 2 where P was mean values. However, only the heterozygosity at Year 5 was signif- E equal or more than 50%. icantly improved when the selection of founders was associated with an extension of the reserve without implementing any supplementa- tions (Figure 4, Supplementary Appendix 4). Discussion When comparing the effect of an increased carrying capacity In this study, we evaluated how the use of population genetics in asso- (i.e. reserve expansion) on genetic diversity parameters, increasing ciation with PVA can assist in the management of rehabilitated wild- the carrying capacity generally resulted in a higher N and, depend- life. We provided evidence that rehabilitated wildlife that is not ing on the scenario, in a higher H (Figure 4, Supplementary immediately releasable due to genetic concerns can be part of a wider Appendix 4). Simulations that included supplementation had signifi- species conservation plan with adequate long-term management. cantly higher H and N compared to simulations without supple- E A The 2 Whiteman Park colonies established from woylies that mentation. However, there were no significant differences between bred unmanaged in rehabilitation settings had, as expected, low Scenario 3 and Scenario 2 when the supplementation program was genetic diversity, since only few animals were wild-caught and some implemented, except for the heterozygosity at Year 5 when carrying of the founders of the colonies were offspring born in captivity. An capacity was increased (Figure 4, Supplementary Appendix 4). H of 70% is generally considered the minimum acceptable level in macropods (Pope et al. 2000) and the only modeled scenario Table 3. Paternity analysis of offspring in the soft-release enclosure where a woylie colony at Whiteman Park was above this threshold Offspring First parent non-exclusion Candidate Pair from early on in the simulations was in the Scenario 3. This demon- ID probability (%) father ID confidence strates the value and the need for the genetic management of this colony. The identified levels of H were comparable to the lower 6B3C6A2 0.7 6B3E96C * end of those found in other wild populations (e.g. Tutanning or 6B3DA2B 0.7 6B3B6F4 * Batalling) and, broadly speaking, comparable to what is commonly 6B3A0AF 0.2 6B3E4B4 * found in other macropods (Pope et al. 2000). It should be stressed 6B3A0AF 0.2 6B3E96C 6B3D2E3 0.1 6B3E96C * that previous translocations indicated that woylie mortality rates are 6B39FF3 0.7 6B3E96C * extremely low when moved to fenced, predator-free areas. 6B39264 0.3 6B3B6F4 * Consequently, the risk of losing genetically valuable individuals 6B3A317 0.1 6B3E96C * when creating the founding stock in Scenario 3 was considered mini- 6B3A6B0 0.1 6B3E96C * mal. Additionally, there was no interest in managing the genetic var- 6B3B485 0.2 6B3E96C * iability in the soft release enclosure, as the holding area was too 6B3BBBA 0.5 6B3B6F4 * small to maintain high genetic variability in the long term. 6B3E554 0.0 In the long term, the planned reserve expansion would slow 6B3AF33 3.5 6B3E96C * down the rate at which genetic diversity is lost due to genetic drift, 6B39AD7 0.1 6B3E96C * making it a very effective conservation strategy. N is the genetic *indicates 95% confidence interval. index that is mostly influenced by this option. Most importantly, the Table 4. Abbreviations of PVA scenarios and their brief description Scenario Description Chidlow MH Scenario 1 Chidlow stock Wellard K70 Scenario 1 Wellard stock Wellard incK(200) Scenario 1 Wellard stock and K increases to 200 after the first year Chid_Well_disp Scenario 2 Chid_Well_disp incK(200) Scenario 2 and K increases to 200 after the first year Chid_Well_disp Suppl Scenario 2 plus the supplementation of 10 individuals once a year Chid_Well_disp Suppl incK(200) Scenario 2 plus K increases to 200 after the first year and the supplementation of ten individuals once a year Woodland Sel Scenario 3 Selection of breeders in the Woodland Reserve Woodland Sel incK(200) Scenario 3 Selection of breeders in the Woodland Reserve. K increases to 200 after the first year Woodland Sel Seas As for Woodland Sel, but reproduction is seasonal Woodland Sel Seas incK(200) As for Woodland Sel, but reproduction is seasonal and K increases to 200 after the first year Woodland Sel Suppl As for Woodland Sel, but the colony is supplemented with 10 individuals once a year Woodland Sel Suppl incK(200) As for Woodland Sel, but the colony is supplemented with 10 individuals once a year and K increases to 200 after the first year Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Pacioni et al.  Augmenting the conservation value of rehabilitated wildlife 7 Figure 4. Dot plot showing mean and SD of genetic diversity of the woylie colony in the Woodland Reserve at Whiteman Park at year five (left plots) and Year 100 (right plots) in different PVA scenarios. In blue scenarios where supplementation is implemented. Scenarios with increase in the carrying capacity of the reserve are indicated with circles. Scenario names are listed in Table 4. simulations demonstrated that supplementing 10 animals once a will be related to the supplementation with genetically valuable indi- year is the management action that would substantially improve the viduals, as well as on their successful settlement in the colony. genetic profile of the colony and counteract the effect of genetic drift Scenario 2 offers similar benefits to Scenario 3, but the obtained in both short term (5 years) and long term (100 years). A combina- information on the genetic makeup of the founding colony will tion of supplementation and increased carrying capacity would allow managers to make informed, and therefore more targeted, boost the genetic diversity of the Whiteman Park woylie colony to a decisions when supplementing animals from other sites. Without level comparable to that of large wild populations (e.g. Perup). In genetic management (Scenario 2) individuals with lower genetic and this case, the role of the woylie colony at Whiteman Park would conservation value could utilize resources that could be made avail- change from being an education display colony to a potential source able to more valuable individuals (including possible external sup- population for other translocations, either to establish new popula- plementations), while in Scenario 3 every supplementation is tions or supplement existing wild and captive populations. Of directed toward an increase in genetic variability. Additionally, course, the conservation value of the Whiteman Park woylie colony although the difference was not statistically significant, Scenario 3 Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zox065/4604560 by Ed 'DeepDyve' Gillespie user on 08 June 2018 8 Current Zoology, 2017, Vol. 0, No. 0 options ranked better than the Scenario 2 counterparts. Considering depression. Additionally, adaptation to captivity (Frankham 2007) the lowering costs of genetic analyses and the clear advantages when is a serious issue that needs to be considered and when possible the managing inbred populations of unknown sources, we recommend use of wild-caught individuals has been recommended as the pre- Scenario 3 as optimal management action, and ideally in association ferred option when carrying out translocations (Pacioni et al. 2013). with the supplementation of woylies from other sources. In our cases, most individuals have been kept in captivity for only 2– Additionally, we recommend ongoing genetic monitoring to ver- 3 generations prior to being released in Woodland Reserve, while ify the modeled changes in the population. Possible concerns may most of the concerns related to captivity adaptation are associated arise if a small number of males dominate the reproductive output, with long-term captive breeding (Frankham 2007). the projected genetic diversity and fitness of the colony may be nega- Our recommendations rely on the assumption that the projected tively affected. While logistic reasons prevent Whiteman Park from trajectories of our simulations are accurate and effectively predict directly managing family groups (equalizing family sizes), other the population responses to different management options. Future management options (e.g. removal of dominant males) can help research will need to evaluate how reliable these conclusions are and achieve the targeted conservation goals. inform management on possible needed adjustments in order to The PVA model did not incorporate any stochastic events such as meet the established targets. The focus of future studies should aim fire, introduced predators (fox or cat incursions), or epidemics. to monitor genetic diversity over time, quantify uncertain simulation Consequently, genetic trends and the probability of extinction gener- parameters, like supplement survival rates, to further improve accu- ated by the analyses depend only on the “natural” fluctuation of the racy of the models, and, critically, compare predictions with actual survival, reproductive rates, and environmental variability of the car- data to verify the appropriateness of the developed models for mak- rying capacity (which were all generally modeled with a standard ing management decisions. deviation of 10% of the mean value, see Pacioni et al. 2017b). To conclude, while wildlife captive breeding should always be Increased genetic variability, in association with a large population planned and coordinated in consultation with conservation agencies size, is considered protective toward stochastic events (Maschinski and relevant authorities, and be accompanied by as accurate records et al. 2013) and it is possible to formally test the effect of these sto- as possible, we demonstrated that by using a combination of popula- chastic incidents within a PVA should this be required. Regardless, tion genetic tools and population modeling rehabilitated animals adequate steps toward prevention from these events should be under- can be used to achieve targeted genetic variability goals over time taken given the potential impact on the viability of the colony, due to even with suboptimal founders. Our approach has wide application their relatively small population size and captive environment. for different species and in widely differing demographic and man- We argue that our approach and methodology have general applicability when evaluating possible destinations for any species agement contexts, where ultimately, the goal is to maximize the of rehabilitated wildlife. This information, in combination with potential conservation outcome of any rehabilitation process. already available frameworks (Frankham et al. 2011; Weeks et al. 2011) would be of great help to make informed management deci- Acknowledgments sions. Similarly, our approach is suitable for the development of management plans for captive breeding colonies or zoological col- We are very grateful to Malcolm Kennedy for comments on early draft of this lections, where founders are generally assumed to be unrelated. manuscript and to Craig Thompson for providing DNA extractions for this However, we warn the readers that a number of factors played in study. We would also like to thank two anonymous reviewers whose com- “favour” of the woylie and would like to stress that by presenting ments have greatly improved this manuscript. the possible applications of genetic and population modeling techni- ques described in this article for rehabilitated wildlife, we by no Supplementary Material means intend to promote uncontrolled breeding of wildlife in care. 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Current ZoologyOxford University Press

Published: Nov 8, 2017

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