This thesis uses population viability analysis to assess the viability of the two remaining wild populations of Critically Endangered Western swamp tortoises under current and future climate conditions, and explores assisted colonization as a conservation strategy. Baseline models project a high risk of extinction for the Ellen Brook population and moderate risk for Twin Swamps. Sensitivity analysis shows adult mortality strongly impacts viability. Climate change is an emerging threat as declining rainfall shortens the hydroperiod needed by tortoises. Founder populations of larger sizes that include juveniles show greater growth in viability analysis of assisted colonization sites.

1. A population viability analysis of the Critically Endangered Western
Swamp Tortoise: the context for assisted colonization
This thesis is submitted in partial fulfillment of the requirements for a
Master of Biological Science
BIOL5520-23 Zoology Project
Faculty of Science
The University of Western Australia
November 2014
Written by: Alexandra Elizabeth Windsor, 21197547
Supervisors: Nicola Mitchell (University of Western Australia)
Professor Fred Allendorf (University of Montanna, USA),
and Dr. Gerald Kuchling (DPaW, WA)
Total Word Count: 9006
Journal formatting style: Biological Conservation

2. 2
Abstract
For the last fifty years, two small wild populations of the Critically Endangered Western
swamp tortoise, Pseudemydura umbrina, have been maintained through strong conservation and
captive breeding efforts. However declining winter rainfall threatens these populations by
severely reducing the length of time that standing water occurs in the wetland habitat. The
viability of the two populations was assessed using population viability analysis (PVA), after first
compiling and deriving demographic parameters based on 50 years of life-history data. A range
of scenarios based on these demographic parameters and on the estimated carrying capacity were
modeled using the PVA software VORTEX v.10.0. Sensitivity analyses were conducted to assess
the impact of age-specific mortality rates on population viability. Baseline scenarios for the wild
populations projected a 96% probability of extinction at Ellen Brook Nature Reserve, even under
optimistic mortality rates, and a 39% probability of extinction at Twin Swamps Nature Reserve,
assuming the continuing of the current supplementation of this population with captive-bred sub-
adults. Sensitivity testing showed that population viability is reduced substantially if adult
mortality rates were increased beyond current levels. To determine assisted colonization to sites
where lower mortality could be realized, founder populations of 6,12, or 20 individuals, at
different ages (juveniles versus adults), and sex ratios were simulated. Higher growth rates and
larger mean population sizes were achieved with larger founder populations that were
supplemented by juveniles. Taken together, population viability analysis demonstrates that
stochasticity in demographic variables can impact appreciably on population trajectories for P.
umbrina, and highlight the importance of funding suitable sites for future translocations to areas
where breeding success and survival can be enhanced.

3. 3
Table of Contents
Acknowledgements pg 4
1. Introduction pg 5
2. Materials and methods pg 8
2.1 Primary data sources pg 8
2.2 Estimation of juvenile and sub-adult mortality rates pg 8
2.3 Population estimation of mortality rates pg 10
2.4 Estimation of wild population sizes pg 11
2.5 Population viability analysis (PVA) pg 12
2.6 PVA on the Ellen Brook and Twin Swamps populations pg 13
2.7 Sensitivity analysis of demographic parameters pg 16
2.8 Climate change scenarios pg 16
2.9 VORTEX scenarios – Assisted Colonization pg 17
3. Results pg 18
3.1 Adult mortality pg 18
3.2 Baseline scenarios pg 18
3.3 Current conservation management tools pg 20
3.4 Sensitivity analyses pg 22
3.5 Climate change pg 24
3.6 Founder population pg 25
4. Discussion pg 27
4.1 Climate change pg 28
4.2 Sensitivity Analysis pg 29
4.3 Conservation methods pg 30
4.4 Assisted colonization pg 31
5. Conclusion pg 34
References pg 36
Appendices pg 36
Appendix A – Research proposal pg 39
Appendix B – Journal reference style pg 57
Appendix C – VORTEX scenario variables pg 59

4. 4
Acknowledgements
I am indebted to Dr. Gerald Kuchling (DPaW) and Dr. Andrew Burbidge for sharing data
and their insights into P. umbrina biology. I also thank Sophie Arnall for sharing unpublished
databases compiled from data collected by DPaW and Perth Zoo personnel. I am grateful to the
Perth Zoo for their research and logistical support. Mostly I would like to thank my supervisor
Prof. Nicola Mitchell for her wisdom, guidance and unlimited patience. This study was funded by
the Department of Animal Biology at the University of Western Australia.

5. 5
1. Introduction
Population viability analysis (PVA) is a critical tool in species conservation and has been
used in the research of many endangered species. These models are useful in assessing a species’
extinction risk, and incorporating PVA into a species management plan allows the assessment of
the relative importance of the risks that influence population viability. Few species recovery
programs have used PVA to direct their conservation methods (Beissinger and McCullogh 2002;
Beissinger and Westphal 1998; Burbidge 1967). Even fewer PVA have focused on reptilian
species, due to the large variety in life histories (Akcakaya et al. 2004). However the few
recovery plans that have used PVA, have seen great success. Notably, a PVA applied to the
conservation of the Desert tortoise (Gopherus agassizii) from North America, used sensitivity
analyses to determine that adult female mortality was highly influential to the survival of the
population (Akcakaya et al. 2004; Doak et al. 1994).
The Western swamp tortoise (Pseudemydura umbrina), is a freshwater tortoise endemic
to Western Australia, and is classified as Critically Endangered according to the International
Union for Conservation of Nature (IUCN 2011). P. umbrina is Australia's rarest reptile, with only
two wild populations that number around 50 breeding adults (Burbidge et al. 2010). With an
estimated life span of over 60 years, adult males can reach a carapace length of 155mm, while
adult females will average approximately 135mm (Kuchling et al. 1992). The species depends on
shallow winter swamp habitats, most of which have been modified or cleared for agricultural or
urban uses in the vicinity of the wild populations (Burbidge et al. 2010; Georges 1993; Kuchling
et al. 1992; Mitchell et al. 2013; Mitchell et al. 2012b). It has been estimated that wetlands within
the Swan Coastal Plain in Western Australia have been reduced by 70% as a result of land
alteration and draining (Finlayson 2000). However this value underestimates the loss of P.
umbrina habitat. Ephemeral wetlands are usually the first to be drained and cleared, or

6. 6
transformed into permanent ponds, and are often overlooked in wetland surveys. For example,
clay extraction still allows the wetland to exist, but makes them unviable as P. umbrina habitat.
Taking into account suitable areas for tortoise habitat, a more accurate and realistic estimate of
wetland habitat loss would be 99% (G. Kuchling, person. comm). The tortoises persist in two
Class A nature reserves: Ellen Brook and Twin Swamps, which were set aside for tortoise
conservation in 1962 and fenced to exclude exotic predators in 1990 (Burbidge et al. 2010).
The transient swamp habitat and Mediterranean climate in which P. umbrina occurs,
restricts their activities to the cooler, wetter months when their aquatic food sources are more
abundant (Kuchling et al. 1992). During the wet winter season, starting between June and July,
the swamps fill with water providing a rich food source of invertebrates and tadpoles. Swamps
dry in the late spring or early summer, after which, tortoises aestivate in clay burrows or under
leaf litter (Burbidge 1981; Kuchling et al. 1992). Mating occurs when the swamps are full in
winter and spring, with clutches of three to five eggs being laid between November and
December (Kuchling et al. 1992). Females lay one clutch per year, with hatching occurring the
following winter, triggered by the decreasing incubation temperature (Burbidge 1967; Kuchling
et al. 1992).
There are many factors that have resulted in the current threatened status of P. umbrina,
including loss and fragmentation of their habitat, low fecundity, slow growth rates, and the
introduction of exotic predators (Burbidge 1981; Burbidge et al. 2010). However it is climate
change that poses an emerging and great threat to their survival (Burbidge et al. 2011; Burbidge
et al. 2010; Mitchell et al. 2012a; Popescue and Hunter 2012). Escalating climactic conditions
result in declining winter rainfall (Smith et al. 2000; Zheng et al. 1998) and decreases the lengths
of the hydroperiod of the swamps, reducing the food and water sources, and shortening the length
of the tortoise’s breeding period (Kuchling et al. 1992; Mitchell et al. 2013; Mitchell et al.

7. 7
2012b). In order to survive desiccation during their first aestivation, it is imperative that
hatchlings achieve a body weight of approximately 18g within the first six months (Burbidge
1981; Mitchell et al. 2012b). However shortened hydroperiods limit hatchling growth and may
prevent them reaching this critical mass. Further, female P. umbrina are unable to reproduce in
years with below average rainfall (Burbidge 1967; Burbidge 1981). Therefore shorter
hydroperiods may lower the intrinsic growth rate for the population making it difficult for the
species to recover from a very low population base (Burbidge 1981; Kuchling et al. 1992).
Due to the threat climate change imposes on P. umbrina populations, locations in
southwestern Australia are currently being assessed as viable sites for assisted colonization.
Assisted colonization (AC) is a form of translocation that involves the planned introduction of a
population or entire species beyond its historic distribution, and is especially relevant when
climate change threatens the wild populations (Popescue and Hunter 2012). The overarching goal
is that populations will be moved to sites where they can persist under future climactic conditions
(Lunt et al. 2013; Popescue and Hunter 2012). However due to risks that translocations incur on
the population in a new environment, as well as the risks incurred upon the new location itself
being exposed to a new taxon, AC’s are often proposed as a last resort for species conservation,
implemented only when all in situ options have been exploited (Burbidge et al 2011l; Lunt et al
2013). The translocation of P. umbrina has been proposed to areas in southern and southwestern
Western Australia, where the impact of climate change is expected to be less severe (Burbidge et
al 2010).
Given the conservation concerns surrounding P. umbrina a PVA model is paramount in
assessing the risk of extinction. In particular, given the growing impact of climate change in
southwestern Australia, it is important to assess the affects of aridity and decreased rainfall on the
viability of tortoise populations. Hence, the objectives of this study were to (i) assess the

8. 8
extinction risk for Ellen Brook and Twin Swamps populations under current management
regimes, (ii) predict the extinction risk for these two populations under a range of future
demographic parameters that could feasibly change under a drier climate, and (iii) to assess the
viability of a founder population under the assumption of lower mortality rates.
2. Materials and methods
2.1 Primary data sources
Models of animal populations rely on estimates of demographic parameters, particularly
age-specific rates of mortality and fecundity. This type of data is often difficult to obtain for wild
animals, and as there are currently no published demographic studies for P. umbrina, I used
unpublished mark-recapture data collected by researchers from the Western Australian
Department of Parks and Wildlife (DPaW) (primarily by Dr. Gerald Kuchling) as well as
unpublished data on reproduction and hatchling mortality rates based on the captive breeding
program at the Perth Zoo. As the life span of P. umbrina, is unknown, it was estimated at 80
years, based on similarly long-lived turtle species (Cann 1998; Famelli et al. 2012), and took into
account the age of the oldest breeding pairs currently in the captive breeding program at Perth
Zoo (female CZ1 and CZ2 were acquired as adults in 1959; male 12 was acquired as an adult in
the 1950’s, and male 139 was taken into captivity from TSNR in 1981) (G. Kuchling, pers.
comm).
2.2 Estimation of juvenile and sub-adult mortality rates
Population viability analysis requires knowledge of the mortality rates in each age class
from egg to adulthood. As mortality rates are not known for wild P. umbrina, I calculated
mortality values up until age 5, based on data from the captive breeding program at the Perth Zoo

9. 9
(there were 529 samples collected between 1986-2014). To account for the influence of the
captive care on the mortality rates, the hatchling and juvenile mortality rates were doubled for the
wild populations, and adjusted where necessary based on advice from Dr. Gerald Kuchling.
Values from age 5 to adulthood were based on demographic data for similarly sized and long-
lived turtle and tortoise species (Doak et al. 1994; Enneson and Litzgus 2009; Famelli et al.
2012).
Repeated estimates of survival rates allow for the estimation of temporal variance within
these rates. However these variances also include variance due to demographic stochasticity and
measurement error (Akcakaya 2002; Kendall 1998). It is vital for accurate viability analyses, that
these variances be removed, in order to estimate the variance due to environmental stochasticity
By calculating the environmental variance (EV), these sampling variances can be removed from
the survival rate estimates (Akcakaya 2002). The equation I used to calculate EV was:
EV = pt (1-pt)/Nt (Akcakaya 2002)
In this equation pt is the survival rate at time t, and Nt is the number of individuals at time t. The
calculation used in Akcayaya (2002) was derived from the original calculation as described in
Kendal (1998).
EBNR and TSNR population scenarios were originally modeled with the same mortality
rates for the 0-1 and 1-2yr age classes. However, despite annual supplementation at TSNR by the
Perth Zoo’s captive breeding program, this population has remained exceptionally low,
suggesting either lower reproductive rates or higher mortality rates. Observations in the field
indicate that many females at TSNR are producing clutches, but that nest and hatchling survival
is low (G. Kuchling pers. comm). Therefore, the TSNR population was modeled with a 25%
higher mortality rate (G. Kuchling pers. comm) (Table 1).

10. 10
2.3 Estimation of adult mortality rates
The instantaneous adult mortality rate was calculated for P. umbrina using length-based
catch curves. Such methods are useful in estimating mortality rates in long-lived and slow
growing species (King 2007; Mitchell et al. 2010; Spencer 2002). Following the methods in King
(2007) I used the inverse of the von Bertalanffy equation:
t = (-1/K) ln(1-Lt/Linf) (King 2007)
In this equation t is the time at the relative age, L is the length of the carapace, and K is the
growth efficient. Converted catch curves plot ln(F/dt) against t, where F is the number of
individuals within each age class, and t is the relative age of the individual. The value dt is the
average length of time it takes for the species to growth through a particular age class (King
2007).
The data used in the frequency tables was unpublished mark and recapture data provided by
the Department of Parks and Wildlife, and compiled by Sophie Arnall for a related project.
Despite the large number of mark-recapture samples (132), only growth rates of wild individuals
that were recaptured over a 3-year time span, and who had not been removed for captive care by
the Perth Zoo then re-released, could be used (18 individuals). The sex of most of the samples
was unknown. The initial and final carapace lengths were used to determine the growth rate over
the particular recapture interval for each individual. A linear growth model was then generated,
relating growth rate to carapace length, to determine the instantaneous adult mortality rate (Z),
under the assumption that it was the same for both sexes. Growth was calculated from the initial
capture and the last re-capture for each sample. As the length of time in between recaptures
varied within the samples, time was factored into the growth calculations to estimate the average
growth per month. The equation used for these calculations was previously described by King

11. 11
(2007):
Age (t) = (1/b) ln(a + bCL) + c (King 2007)
In this equation, t is the time at the relative age, a and b are the intercept and slope of the linear
regression, and c is a constant of integration calculated if the age of an individual at any specific
size is known (Mitchell et al. 2010).
The Z value was converted into a mortality rate using the equation:
Mortality (%) = 100 (1-exp[-Z]). (King 2007).
2.4 Estimation of wild population sizes
The estimates for the initial population sizes for both EBNR and TSNR were obtained
from census data previously collected by DPaW from 1965-2012. VORTEX provides users with
the option of using a ‘stable age distribution’, used primarily when the precise age-class
distribution in the population is unknown, or ‘specified age distribution’. Since the age
distribution of both populations was unknown, I used the ‘stable age distribution’ created by
VORTEX, based on the mortality inputs, and carrying capacity I provided. However, census data
provided by DPaW only accounts for adult tortoises known-to-be-alive (KTBA). The value for
the initial population size that was used, was 126 for EBNR, as this value, when input in the
model provided an age distribution that had the same number of adults as the KTBA estimates.
However when this same method was applied for the TSNR population, the age distribution

12. 12
produced by VORTEX consisted of a large number of juveniles, which is not an accurate
depiction of the wild population. As a result, the size of each age class was entered manually to
allow for an adult majority (G. Kuchling pers. comm). Therefore the value for the initial
population size that was used for TSNR (54) was much closer to the original KTBA estimates for
that population.
2.5 Population viability analysis (PVA)
PVA determines the likelihood that a population or entire species will become extinct
within a specific time period and under specific conditions (Beissinger and Westphal 1998;
Miller and Lacey 2005). The PVA process incorporates known survival threats into a population
model. When applying a PVA to the management of endangered species, there are two main
objectives. The short-term objective is to minimize the probability that the target species or
population will become extinct. The long-term objective is to ensure that the species or
population being studied retains its potential for evolutionary change without continuous
management from a species recovery or management program (Beissinger and McCullogh 2002;
Morris et al. 2002). In this respect, the most important use of PVA is to assist in the management
of threatened species by estimating the extinction probability that is associated with different
conservation methods.
In this study PVA was used to assess the viability of management techniques currently
being used in the conservation of P. umbrina. The techniques examined included yearly
supplementation of captive-reared juveniles into the Twin Swamps nature reserve, as well as
various predator controls at both nature reserves. A PVA for P. umbrina was conducted using the
VORTEX v. 10.0 software (Miller and Lacey 2005), using the life-history parameters outlined in
Table 1. In all instances populations were simulated for 100 years and 100 iterations.

13. 13
Table 1
VORTEX input variables for the Ellen Brooke (EBNR) and Twin Swamps (TSNR) populations, with either low (left
column) or high (right column) mortality values imposed.
Parameter Value (EBNR) Value (TSNR) Reference
Reproductive system Polygynous Polygynous
Age of first offspring,
females
10 9 (Burbidge 1967)
Age of first offspring, males 10 9 (Burbidge 1967)
Maximum breeding age 80 80 (A. Burbidge, pers. comm)
Sex ratio 50% 50% (Burbidge 1967)
% adult females breeding 85% 75% (G. Kuchling, pers. comm)
% adult males in breeding
pool
100% 100% (G. Kuchling, pers. comm)
Mortality Rates (EV1
) (G. Kuchling, pers. comm.)
Mortality rates 0-1yr 40 (15) 60 (15) 75 (15) 90 (15) Refer to Section 2.2
Mortality rates 1-2yr 60 (20) 80 (20) 60 (20) 80 (20)
Mortality rates 2-3yr 7 (5) 9 (5) 7 (5) 9 (5)
Mortality rates 3-4yr 7 (5) 7 (5) 7 (5) 7 (5)
Mortality rates 4-5yr 5 (2) 5 (2) 5 (2) 5 (2)
Mortality rates 5-6yr 4 (2) 4 (2) 4 (2) 4 (2)
Mortality rates 6-7yr 4 (2) 4 (2) 4 (2) 4 (2)
Mortality rates 7-8yr 3 (1) 3 (1) 3 (1) 3 (1)
Mortality rates 8-9yr 1 (1) 1 (1) 1 (1) 1 (1)
Mortality rates 9-10yr 1 (1) 1 (1) 2 (1) 2 (1)
Mortality rates 10-11yr 2 (1) 2 (1) 8 (5) 8 (5) Refer to Section 2.3
Mortality rates 11+ yr 8 (5) 8 (5) -- --
Initial population size 126 54 Refer to Section 2.4
Carrying capacity (K) (EV) 180 (100) 120 (150) (A. Burbidge, per. comm)
Maximum age 80 80 (Burbidge 1981)
2.6 PVA on the Ellen Brook and Twin Swamps populations
The scenarios used as base models for the population simulations were referred to as the
Ellen Brook Nature Reserve (EBNR) and the Twin Swamps Nature Reserve (TSNR) scenarios.
Due to the high variability of annual rainfall in recent decades (Mitchell et al. 2012a; Mitchell et
al. 2012b) two scenarios were generated for each wild population by adjusting the hatchling and
juvenile mortality rates: a ‘low mortality’ scenario (EBNR-low and TSNR-low) and a ‘high
mortality’ scenario (EBNR-high and TSNR-low; Appendix C). However, since 1994, the TSNR
1
Environmental variance (EV) is the annual variation in the probabilities of survival that result from random
variation in environmental conditions. Sources of EV occur outside the population, such as weather, predation, and
food sources (Miller and Lacey 2005).

14. 14
population has been supplemented in many years by captive-bred juveniles (2-3 years old) from
the Perth Zoo (Burbidge et al. 2010). An average of 20-30 juveniles are supplemented annually as
long as there are adequate water levels in the swamps (ie. no tortoises were released in 2013 due
to a dry winter) (G. Kuchling pers. comm). Therefore, to account for this annual
supplementation, two additional scenarios were created for the TSNR population, a ‘low’ and
‘high mortality’ scenario with an annual supplementation of 30 juveniles (2-3 years old). These
two scenarios were the base-models used in all subsequent TSNR scenarios, as the annual
supplementation is ongoing. Both adult and juvenile tortoises are also more susceptible to
predation during aestivation at TSNR, due to the tendency of the tortoises to aestivate under leaf
litter rather than burrow. The higher hatchling mortality at TSNR is based on the naiveté of the
mature female tortoises, who often lay their eggs well away from water sources. This is assumed
to decrease the survival of hatchlings, as they have to travel greater distances to reach the water
(G. Kuchling, pers. comm).
PVA’s are useful for determining the effectiveness of current management actions
and hence one set of scenarios was devoted to evaluating a range of current management
practices employed by DPaW. Scenarios were based on i) yearly supplementation of captive-bred
juveniles, ii) baiting to reduce the numbers of black rats (Rattus rattus) and foxes (Vulpes vulpes),
and iii) fencing to exclude introduced exotic predators. In 1990 an electric fence was erected in
the Ellen Brook Nature Reserve, and extended to include the newly acquired adjoining areas in
1997 and in 2006, in an attempt to ward off larger predators such as foxes, and feral dogs and cats
(G. Kuchling pers. comm). Adult tortoises are most vulnerable to predation during aestivation in
the summer months. Most tortoises at EBNR will aestivate in clay burroww, but tortoises at the
TSNR are more often found aestivating under leaf litter, where they are particularly vulnerable to
predation and brush fire (Burbidge et al. 2010). Management of the Black rat (Rattus rattus)

15. 15
populations using poisoned bait began in 1999 at the Twin Swamps Nature Reserve, and in 2005
at the Ellen Brook Nature Reserve. Black rats (Rattus rattus), and Red foxes (Vulpes vulpes),
pose perhaps the largest threat to P. umbrina populations both at their two current locations, and
at any future location, as they not only prey upon hatchlings and juveniles, but tortoises of all
ages. Whereas the Southern Brown bandicoot (Isoodon obesulus) has a preference for eggs, and
young tortoises (Burbidge et al. 2010). For the supplementation models, data on current rates of
supplementation of juveniles at TSNR was used and replicated for EBNR scenarios. For the
baiting models, mortality rates were reduced across all age classes as baiting influences a variety
of predators, specifically Black rats (Rattus rattus) and Red foxes (Vulpes vulpes), which predate
upon all age groups. Finally, the scenarios regarding fencing to exclude predators involved
reducing the mortality rates to a lesser extent, as only a few predator species, such as the Black
rat (Rattus rattus), can traverse fences (Table 2) (Burbidge et al. 2010).
Table 2.
Description of the mortality variables changed for each management scenario. The 2nd
and 4th
columns represent the
original mortality values for the wild populations. The 3rd
and 5th
columns represent the value that the mortality rate
was changed to for that specific scenario.
Management
scenario
Baseline value
(EBNR)
New value
(EBNR)
Baseline value
(TSNR)
New value
(TSNR)
Fox-fencing 0-1 years: 40
1-2 years: 60
2-3 years: 7
3-4 years: 7
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 3
8-9 years: 1
9-10 years: 1
10-11 years: 2
11+ years: 8
0-1 years: 35
1-2 years: 50
2-3 years: 6
3-4 years: 6
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 3
8-9 years: 1
9-10 years: 1
10-11 years: 2
11+ years: 8
0-1 years: 75
1-2 years: 60
2-3 years: 7
3-4 years: 7
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 3
8-9 years: 1
9-10 years: 2
10+ years: 8
0-1 years: 70
1-2 years: 55
2-3 years: 6
3-4 years: 6
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 3
8-9 years: 1
9-10 years: 2
10+ years: 8
Baiting 0-1 years: 40
1-2 years: 60
2-3 years: 7
3-4 years: 7
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 3
0-1 years: 30
1-2 years: 50
2-3 years: 5
3-4 years: 5
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 2
0-1 years: 75
1-2 years: 60
2-3 years: 7
3-4 years: 7
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 3
0-1 years: 65
1-2 years: 55
2-3 years: 5
3-4 years: 5
4-5 years: 5
5-6 years: 4
6-7 years: 4
7-8 years: 2

16. 16
8-9 years: 1
9-10 years: 1
10-11 years: 2
11+ years: 8
8-9 years: 1
9-10 years: 1
10-11 years: 2
11+ years: 5
8-9 years: 1
9-10 years: 2
10+ years: 8
8-9 years: 1
9-10 years: 2
10+ years: 5
2.7 Sensitivity analysis of demographic parameters
In order to test the sensitivity of the mortality parameters at different age classes (adult 10
years, and juvenile 2-4 years), two sets of PVA models were created. In the first set, adult
mortality was kept at 8% (Table 1), while juvenile mortality rates were systematically increased
and decreased by 1% for each scenario, above and below the ‘low mortality’ baseline values
(Table 1). Conversely, in the second set of scenarios, the juvenile mortality rates were maintained
at the ‘low mortality’ baselines (Table 1), while adult mortality was adjusted by 1% increments
for each scenario, above and below the baseline value of 8%.
2.8 Climate change scenarios
Climate change is considered a significant threat to many species in southwestern
Australia as it may influence the dynamics of many animal populations, especially those that rely
on winter rainfall, such as the orange and white-bellied frog species, Geocrinia alba, and G.
vitellina (Conroy and Brook 2003). The impact of climate change on P. umbrina populations was
simulated by changing the reproductive and survival rates. Multiple scenarios were run in order
to properly assess the impact of climate change on the two wild populations. Two reproductive
variables were adjusted: the ‘percentage of breeding females’, and the ‘clutch size distribution’.
To account for the impact of climate change on the body condition of sexually mature females, I
reduced the percentage of females breeding by 10%, and redistributed the clutch frequencies; 1
egg (0%), 2 eggs, (12%), 3 eggs (55%), 4 eggs, (32%), and 5 eggs (1%). As a previous study has
shown that increased water temperatures can have a positive effect on growth rates of P. umbrina

17. 17
(Mitchell et al. 2012b), in some climate change scenarios the age of sexual maturity was reduced
by two years, for both EBNR and TSNR populations (Appendix C).
2.9 VORTEX Scenarios – Assisted Colonization
To determine the optimal structure of a founder population for future translocations of P.
umbrina, a number of scenarios were constructed, examining the importance of initial population
size, sex ratio, and age on population growth rates and viability. When the first two translocated
P. umbrina populations were established in Mogumber and Moore River Nature Reserves, 6-12
larger juveniles, (approximately 2-4 years of age) were released as a trial release. Once
monitoring was able to establish that these individuals survived and gained mass, yearly
supplementations of similarly aged juveniles were made over the following five years (Burbidge
et al. 2010; G. Kuchling, pers. comm). Hence I constructed scenarios in VORTEX that mirrored
these previous translocations, where I varied the founding population size as 6, 12, or 20
individuals. As P. umbrina is polygynous, a founding population might potentially benefit from a
higher female sex ratio (Grayson et al. 2014; Wedekind 2002). However P. umbrina males
generally grow faster than females, often reaching sexual maturity at a younger age, making it
difficult to accurately determine the sex of a juvenile animal (G. Kuchling, pers. comm.). As a
result, when individuals are chosen for translocation based on their size, there is often a male bias
amongst those released. Therefore I varied the founding sex ratio (males to females) as 70%,
50%, and 30%. Finally, I varied the age of the subsequent supplemented individual: either 30
older juveniles (3-5 years of age), or 30 adults (8+ years of age) with subsequent
supplementations of all juveniles or all adults. The sex ratio of the supplementation cohorts was
25%, 50% or 75%.

18. 18
3. Results
3.1 Adult mortality rate
Based on a length-based catch curve, the instantaneous adult mortality rate was 8% (Fig. 1). This
mortality rate was applied to all sexually mature adults (10+ years) in the VORTEX scenarios
(Table 2).
Fig. 1. Relationship between size (carapace length) and age for P. umbrina from mark/recapture samples collected
1997- 2010. The regression line was placed through the largest cluster of carapace length samples. Adjustments to
the data points produced similar Z values of 7.7% and 8.03%.
3.2 Baseline scenarios
All baseline scenarios from the two populations (EBNR and TSNR) had high mean
probabilities of extinction (PE) in a 100-year timeframe (Table 3). There was a slight difference
in the rate of decline in the number of animals in each population (Figure 2), however there were
y"="$0.0803x"+"3.9096"
0"
0.5"
1"
1.5"
2"
2.5"
20" 25" 30" 35" 40" 45"
Growth/month*(mm)*
Average*Length*

19. 19
large differences in the mean number of years until populations reached extinction depending on
the population, mortality rates, and on whether the population was supplemented (Table 3).
Table 3
VORTEX results of the four baseline scenarios and two supplementation scenarios, showing the mean final growth
rate, probability of extinction, population size, and year to extinction.
Baseline
Scenario
Population
growth rate
(SD)
Probability of
extinction (PE)
(SD)
Final mean
population (N)
(SD)
Mean years to extinction (SD)
EBNR low
mortality
0.055 (0.21) 0.96 (0.02) 2.44 (13.02) 24.01 (21.08)
EBNR high
mortality
-0.005 (0.27) 1.00 (0) 0.01 (0.1) 22.81 (19.01)
TSNR low
mortality
0.028 (0.24) 0.99 (0.04) 0 (0) 24.41 (4.23)
TSNR high
mortality
-0.055 (0.29) 1.0 (0) 0.01 (0.28) 14.77 (19.49)
TSNR low
mortality +
supplementation
0.199 (0.34) 0.39 (0.049) 13.98 (15.91) 64.84 (4.28)
TSNR high
mortality +
supplementation
0.2 (0.35) 0.46 (0.049) 14.76 (17.74) 64.32 (3.47)
The EBNR simulations were consistent with an average of 22-24 years until extinction for
both high and low mortality scenarios. Nonetheless there was a difference in the extinction time
for the TNSR models. Under low mortality rates, TSNR had an average of 24 years until
extinction, while under high mortality rates, there was an average of 15 years until extinction.

20. 20
Fig. 2. The mean number of animals surviving each year of the simulation: i) EBNR low mortality, ii) EBNR high
mortality, iii) TNSR low mortality including supplementation, iv) TSNR high mortality including supplementation.
3.3 Assessment of current management tools
Using the baseline low mortality (i.e more optimistic) scenarios, the affects of
supplementation and predator control (fencing and baiting) were analyzed. Accounting for
current conservation management practices by implementing supplementation in the TSNR
population, there is a significant improvement on the population size (N) of both high and low
mortality scenarios (Figure 3).
0"
20"
40"
60"
80"
100"
120"
140"
0" 10" 20" 30" 40" 50" 60" 70" 80" 90" 100"
Mean%Popula+on%(N)%
Years% i" ii" iii" iv"

21. 21
A)
B)
Fig. 3. The mean number of animals surviving each year of the simulation based on different management
strategies: ii) annual supplementation, iii) poisonous baits, iv) fox-proof fencing. Panel A shows EBNR simulations
and Panel B shows the TSNR simulations.
The annual addition of juvenile tortoises into the model had equally large impacts on both
the EBNR and TSNR populations. The EBNR extinction probability decreased to 11% for the
low mortality scenario (the high mortality scenario remained at 100% PE, data not presented),
while the extinction probabilities for the TSNR population decreased to 46% and 39% for the
high and low mortality scenarios, respectively. All subsequent models of the TNSR population
!20$
0$
20$
40$
60$
80$
100$
120$
140$
0$ 10$ 20$ 30$ 40$ 50$ 60$ 70$ 80$ 90$ 100$
Mean%Final%Popula-on%(N)%
Years% i$ ii$ iii$ iv$
0"
10"
20"
30"
40"
50"
60"
70"
0" 10" 20" 30" 40" 50" 60" 70" 80" 90" 100"
Mean%Final%Popula-on%(N)%
Years% i" ii" iii" iv"

22. 22
included annual supplementation to reflect the current practice of releasing captive bred juveniles
head-started at Perth Zoo.
Simulations of baiting and fencing management, and their associated improvements in
survival, was not as effective as supplementation in terms of maintaining a viable population. The
baiting simulations resulted in a probability extinction of 99% and 97% respectively for EBNR
and TSNR, while the fencing simulations resulted in a probability extinction of 97% for TSNR
and 100% for EBNR (Figure 3).
3.4 Sensitivity Analysis
With regards to adult versus juvenile mortality rates, there was a moderate difference in
the overall population size for both populations, however PE values were most influenced by
decreases in adult mortality. In order to achieve a PE of zero for EBNR, adult mortality needs to
be reduced to 4%, while juvenile mortality would have to be reduced to 27% (Figure 4). To attain
a PE of zero for TSNR, adult mortality would have to be reduced to 2%, and juvenile mortality
would have to be reduced to 18% (Figure 4).

23. 23
A)
B)
Fig. 4. Simulation of the mean probability of extinction rate for A) EBNR and B) TSNR. Each data point represents
a separate VORTEX scenario. The mortality rate increased in 1% increments for each scenario. The black data points
in each plot represent the baseline mortality value for that population. The difference in age of adults between the
two populations is the result of faster individual growth rates at TSNR.
0"
10"
20"
30"
40"
50"
60"
70"
80"
90"
100"
0" 10" 20" 30" 40" 50" 60"
Probability*of*Extnc0on*(%)*
Mortality*Rate* Juvenile"(144"years)" Adult"(11+"years)"
0"
5"
10"
15"
20"
25"
30"
35"
40"
0" 10" 20" 30" 40" 50" 60"
Probability*of*Ex.nc.on*(%)*
Mortality*Rate* Juvenile"(114"years)" Adult"(10+"years)"

24. 24
3.5 Climate Change
The addition of climate change (as represented by increased mortality rates, and reduced
reproductive rates) had significant impacts on both populations, specifically with regards to the
mean number of years to extinction (Table 4). All variables were most affected by the change in
clutch distribution (Table 4).
Table 4
VORTEX results from climate change scenarios. The 4th
column represents the change in PE from the baseline
scenario to the new model. The 7th
column represents the change in the mean time to extinction from the baseline
scenario to the new model.
Scenarios Growth
rate (SD)
Probability
of
Extinction
(PE) (SD)
PE Baseline
difference
Mean final
population
(SD)
Mean years to
extinction (SD)
Baseline difference
in extinction time
%
females
breeding
0-1yr
EBNR
-0.04
(0.2)
0.98
(0.014)
0.02 0.8
(6.5)
15.3
(13.3)
-8.7
0-1yr
TSNR
0.2
(0.3)
0.37
(0.05)
-0.02 17. 8
(13.0)
22.0
(21.8)
-0.8
1-2yr
EBNR
-0.04
(0.2)
0.98
(0.014)
0.02 0.64
(4.5)
15.5
(14.1)
-8.5
1-2yr
TSNR
0.21
(0.4)
0.4
(0.04)
0.01 16.6
(17.9)
21.2
(19.9)
-1.6
10+ yr
EBNR
-0.04
(0.22)
1.0
(0)
0.04 0
(0)
15.0
(18.5)
-9.0
9+ yr
TSNR
0.19
(0.35)
0.44
(0.05)
0.05 15.8
(11.8)
19.0
(16.8)
-3.8
All ages
EBNR
-0.0002
(0.25)
1.0
(0)
0.04 0
(0)
14.03
(16.8)
-10.0
All ages
TSNR
0.15
(0.08)
0.4
(0.05)
0.01 15.87
(18.8)
15.0
(14.3)
-7.9
Clutch
Distr.
0-1yr
EBNR
-0.04
(0.25)
0.96
(0.01)
0 0.56
(5.9)
15.3
(11.2)
-8.7
0-1yr
TSNR
0.19
(0.03)
0.37
(0.05)
-0.02 17.5
(17.3)
19.0
(18.3)
-3.8
1-2yr
EBNR
-0.04
(0.25)
0.97
(0.017)
0.01 0.63
(3.8)
15.3
(15.1)
-8.7
1-2yr
TSNR
0.2
(0.02)
0.43
(0.05)
0.04 13.87
(15.4)
16.9
(16.0)
-5.9
10+ yr
EBNR
-0.04
(0.21)
0.99
(0.02)
0.03 0.66
(2.0)
14.9
(14.8)
-9.6
9+ yr
TSNR
0.19
(0.35)
0.37
(0.05)
-0.02 18.45
(17.3)
16.4
(20.8)
-6.4
All ages
EBNR
-0.0004
(0.2)
1.0
(0)
0.04 0
(0)
13.4
(13.9)
-10.6

25. 25
All ages
TSNR
0.09
(0.35)
0.48
(0.05)
0.09 17.2
(17.7)
14.8
(17.7)
-8.0
3.6 Founder Populations
P. umbrina is currently in a severe genetic bottleneck, with only approximately 50
breeding adults for both wild populations (Burbidge et al. 2010). With so few breeding
individuals and small population sizes, P. umbrina is at risk of inbreeding. In larger populations
inbreeding can occur as a result of nonrandom mating because of a tendency for mating with
related individuals. But in smaller populations, substantial inbreeding occurs even with random
mating, because all or most individuals within small populations are related (Allendorf et al.
2012). Although it is unknown if inbreeding is currently occurring in P. umbrina populations, it
was accounted for in the founder population models.
The PE showed minor variation between founder groups of N=6 (16%), N=12 (14%), and
N=20 (0%). The sex ratio of 1:1 was the most favourable for both population survival and the
genetic diversity of the population. The mean growth rate for the founder population was higher
under a female biased sex ratio (25% male) compared with an equal or male biased population.
Table 5
Values of the population growth rate and mean population size for variants of age structures for the founding group
and yearly supplements (50% male sex ratio). The size of the founder group is 20 individuals, with annual
supplementation of 30 individuals.
Founder Population Juvenile Supplements 30 Adult Supplements 30
Population Growth Rate
(r) (SD)
Mean
Population (N)
(SD)
Population
Growth Rate
(r) (SD)
Mean
Population (N)
(SD)
20 Juveniles 0.12
(0.14)
232.16 (53.63) 0.11
(0.18)
160.61 (79.92)
20 Adults 0.081
(0.18)
146.21 (81.08) 0.082
(0.18)
166.81 (64.73)

26. 26
Fig. 5. Comparison of growth rates for an N=20 founder population with varying sex ratios and age classes. The size
of each box represents the size of the population for that variable. The yearly supplementation consists of 30
individuals.
N
=
20
r
=
0.08
Juv.
founders
r
=
0.08
Juv.
suppl.
r
=
0.12
75%
Males
r
=
0.08
50%
Males
r
-­‐
0.12
25%
Males
r
=
0.18
Adult.
suppl.
r
=
0.11
75%
Males
r
=
0.06
50%
Males
r
=
0.1
25%
Males
r
=
0.11
Adult
founders
r
=
0.06
Juv.
suppl.
r
=
0.08
75%
Males
r
=
0.06
50%
Males
r
=
0.08
25%
Males
r
=
0.1
Adult.
suppl.
r
=
0.08
75%
Males
r
=
0.06
50%
Males
r
=
0.08
25%
Males
r
=
0.09

27. 27
4. Discussion
Due to the scarcity of long-term demographic data for most chelonians, very few PVA’s
have been conducted on these long-lived species. Although the adult mortality rate appeared to be
high for sexually mature P. umbrina, similar rates have been estimated in other tortoise species.
Heppell’s (1998) study on the life history of long-lived turtle and tortoise species, suggests an
average adult mortality rate of 8.75% for freshwater turtles, and 10.2% for desert tortoises
(Heppell 1998).
This analysis of the viability of wild populations of P. umbrina, suggests a very high
probability of extinction (96% and 100%) within the next 100 years. According to the IUCN
criteria for Critically Endangered species, a species or population is considered demographically
unviable when “quantitative analysis showing the probability of extinction in the wild is at least
50% within 10 years or three generations, whichever is the longer (up to a maximum of 100
years)” (2011) . Based on this criterion, neither of the high or low mortality scenarios for either
wild population would remain viable without intensive conservation management. Current
management practices at both EBNR and TSNR involve predation control (ie. predator fences,
and poisonous baits), as well as the use of bore water to manually fill the swamps in dry years.
Equally as important as the probability of extinction the extinction time frame. The mean
number of years until extinction is considerably lower in the TSNR population, except in the
models that included population supplementation. Much of this is due to the difference in the
sensitivity of hatchling and juvenile mortality rates between the two populations, and the much
lower initial population size, for the TSNR population.

28. 28
4.1 Climate Change
The most immediate threat perceived from climate change on P. umbrina is the declining
amounts of winter rainfall. Since 2000, the annual rainfall totals in southwestern Western
Australia have continued to decline, and there has been a marked increase in the geographic
extent of this drying (Smith et al. 2000). Management strategies have been implemented since
1994 in TSNR to allow the manual filling of swamps to supplement winter and spring rainfall.
Without long hydroperiods during the winter, females are unable to breed sufficiently, and the
mortality rates of tortoises surviving their first year of aestivation drastically increase. Juvenile
tortoises are more vulnerable to desiccation. Experiments on the water loss of P. umbrina
indicate that a 50 gram juvenile tortoise has a desiccation rate 2.4 times higher than a 400 gram
adult (Burbidge 1967). The same studies have shown that hatchling tortoises weighing 17 grams
will lose water four times faster than adult tortoises, with a total weight loss of 24% (Burbidge
1967). By shortening the length of the hydroperiod and thus reducing the amount of foraging
time available to tortoises, the ability for these animals to reach an adequate body mass is
significantly reduced. The climate change scenarios conducted in VORTEX, assumed a
continuous gradual increase in juvenile mortality as the amount of yearly rainfall decreases over
the next 100 years. Despite the assumption that tortoises would reach sexual maturity earlier as a
result of warmer water temperatures, (Mitchell et al. 2012b) both wild populations had no
influence from the simulated impacts of climate change on their demographic parameters (Table
3). Similarly, a recent study of the long-lived Hermann’s tortoise, Testudo hermanni, used data
from long-term monitoring to determine the effects of an increasingly arid climate on tortoise
populations. The study found that decreased winter rainfall had severe impacts on population
demographics, with significant impacts on hatchling and juvenile survival rates (Fernandez-
Chacon et al. 2011). This study also examined the viability of populations of T. hermanni, under

29. 29
three different climactic conditions, and found that like P. umbrina, future populations would be
negatively affected by an arid climate (Fernandez-Chacon et al. 2011).
4.2 Sensitivity analyses
The sensitivity tests applied to the baseline models showed that adult mortality rates have
a greater influence on the risk of population extinction than juvenile (1-4 years) and sub-adult (5-
8 years) mortality rates at both locations. For both the EBNR and the TSNR populations, a
decrease in extinction probability was realized by reducing the adult mortality rates (individuals
8+ year) by 1% increments annually. Given the small population sizes at ESNR and TSNR, and
the low adult recruitment as a result of high levels of juvenile mortality, it was hypothesized that
populations would be more susceptible to changes in adult mortality. For example fewer breeding
females would significantly impede the growth rate of a population, especially in a long-lived
species with a relatively late age of sexual maturity (Crouse et al. 1987). Doak et al (1994)
modeled PVA for the desert tortoise, Gopherus agassizii, using a size-structured demographic
model. Sensitivity analysis of the population model indicated that the population was most
sensitive to variation in the survival of large adult females (Akcakaya et al. 2004; Doak et al.
1994). The same study argued that improving the annual survival of such females, could reverse
population decline, whereas improvements in other rates alone would not (Akcakaya et al. 2004;
Doak et al. 1994). In a similar analysis of Loggerhead turtles, Caretta caretta, it was suggested
that increasing the survival of sub-adults who have passed through the most vulnerable juvenile
stages, would produce much larger numbers of adult individuals (Crouse et al. 1987). Other
analyses on chelonian populations have also shown similar responses in sensitivity tests on
mortality rates. A study of snapping turtles, Chelydra serpentina, showed that variation in
hatchling and first-year survival had little effect on the mean population growth rate, whereas

30. 30
even small variations in sub-adult and adult survival rates, had a large impact on growth rates
(Congdon et al. 1994; Cunnington and Ronald 1996). Such results were also reflected in Heppell
et al (1998) study, where sensitivity analyses indicated that annual survival rates of adults and
sub-adult turtles affected population growth rates more than other rates for the Kemp’s Ridley sea
turtle, Lepidochelys kempi, and the non threatened Yellow mud turtle, Kinosternon flavescens
(Akcakaya et al. 2004; Heppell 1998). Cunnington and Ronald (1996) outlined the concept of
‘bet-hedging’ which suggests that a long reproductive life-span, a high rate of adult survival, and
a low fecundity, are all adaptations that maximize the probability of reproductive success during
periods of high or fluctuating hatchling and juvenile mortality (Cunnington and Ronald 1996).
The demographics of P. umbrina, (ie high rates of sub-adult and adult survival, and the long life-
span), allows this species to tolerate, to some extent, low and variable hatchling survival.
However it also means that these populations are highly susceptible to changes in adult mortality.
Thus, reduction of adult mortality should be a primary of management actions.
4.3 Other conservation methods
Despite the relatively high hatchling and juvenile mortality rates, P. umbrina is a species
with few biological threats. Once a tortoise has survived their first summer as an embryo, and
their second summer as a juvenile (for which the latter case, the length of the hydroperiod is
crucial), there is little that will cause gross mortality. The greatest threat to adult tortoises is
predation by Black rats, Rattus rattus, the Australian raven, Corvus coronoides, and the European
red fox, Vulpes vulpes (Burbidge et al. 2010). Despite the uncertainty in the estimates of some
model parameters, PVA studies can robustly rank alternative management strategies and
determine which would be highly likely to benefit threatened populations. Although efforts can
be made to reduce the impact of climate change on hatchling and juvenile mortality by extending

31. 31
the hydroperiods of swamps with bore water (Burbidge et al. 2010), defenses against invasive
predators are limited. In this study scenarios were modeled to represent the impact of predator
management (fences and baiting) on mortality rates. Although neither management method
enhanced the long-term survival of P. umbrina, (Figure 3) the annual population sizes were
considerably higher than the baseline scenarios, if fencing and baiting were used in conjunction
with each other.
4.4 Assisted colonization
Conservation agencies have been managing P. umbrina for over 50 years, yet this PVA
suggests extirpation of the wild populations within the next 20 years. Unfortunately long life
spans, slow reproductive rates, and presumed low levels of genetic diversity, suggest that P.
umbrina is unlikely to adapt quickly to a changing climate (Mitchell et al. 2013). Assisted
colonization has already been recommended as the next crucial step in conservation management
for P. umbrina (Burbidge et al. 2010). Earlier translocations of captive-bred juveniles to sites
north of their current habitat have proven to be successful. There are short and long term criteria
for a successful translocation. Survival of the released animals as well as consistent growth rate,
are both short-term criteria for successful translocations. Tortoises at both locations are surviving
the translocation and gaining adequate body mass. Although some recruitment has been observed
at Mogumber Nature Reserve, there is currently no evidence of recruitment at Moore River
Nature Reserve (G. Kuchling, pers. comm). However it is too early to determine if in the long-
term, viable populations can be established at these locations (G. Kuchling, pers. comm).
However, new translocation sites with suitable habitat now and under future climates are
required. The PVA of a population of tortoises showed good growth rates and low probabilities
of extinction (Table 4, Figure 5), despite the potential for a slight increase in the age of sexual

32. 32
maturity (Mitchell et al. 2012b). The current protocol for P. umbrina translocations over 5 years,
with an initial release of 6-12 juveniles (2-4 years) and additional annual supplementation of 30
juvenile tortoises (3-4 years) would appear to be sufficient to establish a population. There was
little difference in success of the new population with regards to the size of the founding
population (Figure 5). But as social behaviours, such as sharing aestivation burrows, have been
observed in P. umbrina (G. Kuchling, pers. comm), larger founder population sizes may be
beneficial in other respects.
Next to population size, the sex ratio of a founder group is considered to be one of the
most important factors in species translocation (Daleszyzyk 2009). The success of a translocation
should be measured not only by the survival of released animals, but also by the reproductive
output and growth of the population, which is largely influenced by the mating strategy and sex
ratio of the population (Sigg et al. 2005). Due to their polygynous nature, it was not surprising
that a 25% male sex ratio was more favourable for population growth and the retention of genetic
diversity (He), compared to an equal or male biased population (Figure 5). Sigg et al (2005)
asserted that females were a limiting resource which males competed for, and thus the best
management strategy for translocation programs for polygynous species, would be to release a
higher proportion of females, thereby increasing the reproductive output of the population.
Similar results were also seen in a study of polygynous European bison, Bison bonasus, which
had greater growth rates and He in populations founded with a large female bias (Daleszyzyk
2009).
To assess the most optimal age-structure for a founding population, the ages of the initial
founder population and the supplemented individuals were varied. Releasing older juvenile/ sub-
adult tortoises (3-7 years) instead of sexually mature adults did not have a significant impact on
the probability of success of the new population. However, populations that were both founded

33. 33
and supplemented with juveniles (3-7 years) did significantly increase the growth rate, and
retention of genetic diversity. Younger individuals may be more adaptable to new conditions and
environments relative to older individuals. For example, sexually mature female tortoises that
were released into TSNR from the Perth Zoo’s captive population were often found laying eggs
well away from water sources, significantly decreasing the chance of survival for the hatchlings
(G. Kuchling, pers. comm). By using older juveniles as founders, and supplementation stock,
there is an increase in the probability of survival and genetic diversity of the population. A study
on translocation demographics by Robert et al. (2004) suggested that the age of released
individuals can not only influence population dynamics demographically, but also has a
substantial impact on the extent of fitness heterogeneity. The results of this study indicated that
populations founded by adults may be generally more affected by the accumulation of genetic
mutations than those founded by juveniles (Roberts et al. 2004). Founding a population with
juveniles implies no reproduction for a certain number of years until they reach sexual maturity.
Roberts et al. (2004) suggest that during this time, the new population undergoes a purging period
as a result of contrasting mortality rates between the individuals of heterogeneous fitness.
Conversely, with adult releases, reproduction occurs immediately after release, rapidly decreasing
the fitness variance within the population (Roberts et al. 2004). When genetic factors were
included in general models for the Griffon vulture (Gyps fulvus), the juvenile release strategy led
to lower long-term extinction probabilities than the adult release strategy (Roberts et al. 2004;
Sarrazin and Legendre 2000). For all of these models, the release of juveniles was the optimal
strategy on a 100-300 year time scale (Sarrazin and Legendre 2000). Similar methods are used in
head-starting translocated populations, where young animals either captive bred or collected from
the wild, are temporarily reared in captivity prior to release (Alberts 2007). Head-starting was
initially applied to assist in the recovery of declining populations of marine turtles in the 1970’s,

34. 34
but has since been adopted as part of integrated recovery plans for a number of other reptiles,
including freshwater turtles, tortoises, and iguanas (Alberts 2007; Crouse et al. 1987). The
rationale for this conservation approach is that larger juveniles have a greater probability of
surviving the neonatal period than smaller ones. If juvenile tortoises can be reared in a captive
environment free from predators, and environmental stress, a greater proportion of animals will
reach sexual maturity and be recruited into the adult breeding population (Alberts 2007). Head-
starting has proven successful in other populations with severely reduced juvenile recruitment. In
2006, along the Texas-Oklahoma border, 16 captive-bred juvenile Alligator snapping turtles
(Macrochelys temminckii) were released. Over the course of the study the released juveniles
exhibited better body conditions compared to the wild-bred cohorts, and continued to grow
successfully (Moore et al. 2013). Similarly, a trial release of 5 juvenile ploughshare tortoises
(Geochelone yniphora), considered to be the rarest tortoise in the world, was deemed successful,
with all five juveniles surviving the fist year, and individual growth rates reflecting those of the
wild tortoises (Pedrono and Saraovy 2000). The results of the assisted colonization VORTEX
models proposes that founding a new population of P. umbrina, with head-started juveniles will
have a lower probability of extinction and higher genetic diversity, than a new population
founded by adult tortoises.
5. Conclusions
This study has presented numerous PVA models for P. umbrina. Firstly, modeling the
probability of extinction of two remaining wild populations, and then modeling the viability of
these same populations under the influence of a drier climate. The PVA indicated a high
probability of extinction for the Ellen Brook population, and a relatively high extinction
probability for the Twin Swamps population, due to the presumed impacts of climate change on

35. 35
mortality and reproductive rates. The most notable scenarios were those for populations
translocated to more southerly locations with reliable hydroperiods that promoted the recruitment
of juveniles into the adult population.
So close to extinction, and with fewer than 50 breeding adults remaining in the wild, P.
umbrina is an ideal candidate for assisted colonization. A significant shift to drier, more arid
conditions within the past few decades (Smith et al. 2000), has substantially reduced the length of
the swamp hydroperiods within the tortoise’s habitat (Mitchell et al. 2012b).
Despite the absence low rates of mortality due to biotic causes, populations at both relic
sites, especially at Ellen Brook Nature Reserve, are at risk of extinction due to their naturally low
reproductive rates, coupled with high mortality rates. The grim outlook for wild populations may
be improved if the focus of conservation turns to assisted colonization to habitats better able to
provide lengthy hydroperiods under future climates.

36. 36
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187.

39. 39
Appendix A: Research Proposal
Optimizing a Founder Population of
Western Swamp Tortoises
Alexandra Windsor
The University of Western Australia
Word Count: 6080

40. 1
Table of Contents
Introductory Statement pg 2
Background pg 3
What is Population Viability Analysis pg 3
The Western Swamp Tortoise pg 5
Impacts of Climate Change pg 6
Captive Breeding pg 7
Translocation Sites pg 8
Translocation as a Management Tool pg 11
Aims and Objectives pg 13
Significance and Outcomes pg 13
Methods pg 13
Study Site pg 13
Demographic Data pg 14
Genetic Data pg 15
PVA and Genetics Software pg 17
Population Viability Analysis pg 18
References pg 20
Budget pg 21
Timetable pg 23

41. 2
Optimizing a Founder Population of Western Swamp Tortoises
1.0 Introductory statement
For the last fifty years, two small wild populations of the Western Swamp Tortoise,
Pseudemydura umbrina, have been successfully maintained through strong conservation and
captive breeding efforts. In such efforts, two new populations have been established outside of
the historical range of the species, with captive bred tortoises translocated fro the Perth Zoo.
However decreasing rainfall within the swamp tortoise’s habitat now threatens these populations.
To ensure the long-term survival of this species, the viability of the wild and the two additional
translocated populations needs to be established. By understanding how decreased rainfall impact
on existing populations, the need and requirements to establish new populations can be assessed.
Removing tortoises from existing wild populations for the purpose of establishing
additional translocated populations will reduce their size and breeding individuals may be lost.
Can wild populations withstand the harvesting of individuals, while maintaining population
growth and sufficient genetic variation? The aim of this project is to examine the survival
probability of the current wild populations using a population viability analysis (PVA) driven by
current life-history and demographic parameters, and by a range of future parameters that could
feasibly change under a drier climate. My second aim is to determine what, if any, harvesting
pressure the wild populations could sustain in order to provide individuals for a new translocated
population. Finally, I will attempt to optimize the size, age-structure and genetic variation of a
new translocated population, within the constraints imposed by the small numbers and likely low
genetic variation in the surviving members of this species
2.0 Background
2.1 What is Population Viability Analysis?
Population Viability Analysis (PVA) is the process of determining the likelihood that a
population or entire species will become extinct within a specific time period and under specific
conditions (Beissinger & Westphal, 1998; Miller & Lacey, 2005). The PVA process incorporates
known survival threats into an extinction model. A population is considered ‘genetically viable’
if is able to maintain ≥90% of the initial heterozygosity, and ‘Critically Endangered’ if the
population size decreases by more than 80% over the course of 3 generations (Pertoldi et al,

42. 3
2013). Small populations in particular are vulnerable to stochastic processes such as genetic drift,
environmental change, natural catastrophes, and demographic stochasticity (Mills and Allendorf,
1996; Pertoldi et al, 2013).
The use of PVA offers a multitude of benefits for programs that are designed to ensure the
conservation of a threatened or endangered species. The application of a PVA can help to place a
quantitative value on the impact that proposed conservation methods have on the target species or
population (Possingham et al, 1993). When applying a PVA to the management of endangered
species, there are two main objectives. The short-term objective is to minimize the probability
that the target species or population will become extinct. The long-term objective is to ensure that
the species or population being studied retains its potential for evolutionary change without
continuous management from a species recovery or management program. In this respect, the
most important use of PVA is to assist in the management of threatened or endangered species by
estimating the extinction probability that is associated with different management methods.
PVA can be used to predict the response of a population or entire species to conservation
management techniques such as reintroduction, translocation, captive breeding, and habitat
alterations. For example during the recovery program for the Northern spotted owl (Strix
occidentalis caurina) a PVA model was used to determine the optimal size of habitat
conservation areas to ensure optimal viability of the population within the conservation area
(Possingham et al, 1993). The main advantage of incorporating PVA into a species management
plan is its ability to assess the relative importance of the risks that influence the survival of a
population. Notably, few species recovery programs have involved the use of PVA in assisting
with their conservation methods (Beissinger & Westphal, 1998; Wielgus, 2002). However many
recovery plans that have used PVA, have seen great success. A recent study on polar bear (Ursus
maritimus) populations in Nunavut, Canada, determined that local bear populations could
withstand a considerable yearly harvest of individuals. It was also concluded that in order for
these populations to continue to prosper, a harvest of three adult individuals per year was
required (Taylor et al, 2006). Similar methods were used in the management of grizzly bear
(Ursus arctos) populations in British Columbia, Canada. In this study, a PVA was used to
determine the population size needed for “benchmark” grizzly bear populations. “Benchmark”
grizzly bear management units are non-hunted, naturally regulated populations that serve as
source populations for surrounding hunted areas (Miller, 2003; Wielgus, 2002).

43. 4
Another good example of the application of PVA to threatened species conservation is a
the desert tortoise (Gopherus agassizii), an indigenous tortoise of the Mojave desert that is under
intensive management. Conservation studies of the desert tortoise have used PVA to analyze the
status of the remaining populations and evaluate the effectiveness of potential conservation
methods. The analyses were able to show that populations were declining rapidly and that road
expansion into the tortoise’s habitat was a significant threat to their survival (Doake et al, 1994).
In this study I will use similar techniques, and apply PVA to assess the viability of current
management techniques being used in the conservation of the Western Swamp Tortoise
(Pseudemydura umbrina). Using demographic data collected over more than 50 years of
intensive monitoring, and genetic data available through a Stud Book of the captive P. umbrina
population at the Perth Zoo, multiple analyses will be conducts to assess the viability of the two
wild populations. Knowing the viability of these populations, steps can taken to assess the need
and viability of new translocated population.
2.2 The Western Swamp Tortoise
The Western Swamp tortoise (Pseudemydura umbrina) is Australia's rarest chelonion, with only
two wild populations that number around 50 breeding adults. With a suggested life span of over
60 years, adult males can reach a carapace length of 155mm, while adult females will average
approximately 135mm (Burbidge & Kuchling, 1994). Out of concern for the specie’s survival,
they were first taken into captivity in 1959, when it was quickly realized that severe habitat loss
in the form of urbanization and agriculture, posed a significant threat to the few remaining
populations (Kuchling et al, 1992). The species depends on shallow winter swamp habitats, and
that land that was traditionally inhabited by these tortoise has a very small geographic range,
most of which has been converted for agricultural or urban uses (Kuchling et al, 1992). What
remaining land that is protected, is limited to two nature reserves: Ellen Brooke and Twin
Swamps Nature Reserves, which contains the only remaining wild populations (Burbidge &
Kuchling, 1994). The four sites currently being managed include the Twin Swamps nature
reserve, Ellen Brooke Nature Reserve, Mogumber Nature Reserve, and Moore River Nature
Reserve (Burbidge & Kuchling, 2004).
The Mediterranean climate in which these tortoises live, restricts their activities to the
cooler, wetter months when food sources are much more abundant (Kuchling et al, 1992). During

44. 5
the winter wet season, starting in June or July, the swamps fill with water and provides a rich
food source of invertebrates and tadpoles. During the hot summer months, the swamps dry up,
and the tortoises aestivate in clay burrows or under leaf litter (Burbidge & Kuchling, 1994).
Breeding occurs during spring, with clutches of three to five eggs being laid between November
and December (Kuchling et al, 1992). Females will lay one clutch per year, with hatching
occurring the following winter, triggered by the decreasing incubation temperature (Burbidge &
Kuchling, 1994).
2.3 Impact of Climate Change
There are many factors that have resulted in the current conservation status of P.
umbrina, including their small geographic range, low fecundity and slow growth rates, an
increasingly drying climate, exotic predators, and vulnerability during aestivation. Climate
change now poses as an emerging threat to their survival, and declining winter rainfall has
decreased the length of the hydroperiod of the swamps, reducing the food and water sources, and
shortening the length of the tortoise’s breeding period (Kuchling et al, 1992; Mitchel et al, 2012).
Studies of P. umbrina at Twin Swamps Nature Reserve show that hatchlings must achieve a body
weight of approximately 18g within the first six months in order to survive dessication the
following summer (Burbidge, 1981; Mitchel et al, 2012). Female tortoises are unable to
reproduce in years with below average rainfall (Burbidge, 1964; Burbidge 1981), and two
successive years of average or above average rainfall are necessary in order for successful
reproduction and recruitment to occur at the Twin Swamps Nature Reserve (Burbidge &
Kuchling, 1994).
As with many tortoise species, P. umbrina has a low fecundity and slow growth rates,
resulting in slow maturity. The age of the maturity depends on the specific individual, and is
based on size rather than age per se, and hence is strongly influenced by environmental
conditions. A recent study examined the affects that increased climate change has on juvenile
growth rates in Western Swamp tortoises. The study discovered that small increases in the water
temperate resulted in a large increase in juvenile growth rates in the early spring, provided that
there was an abundance of food. Researchers concluded that hatchlings ground under future
climactic conditions during a 5 month hydroperiod, were between 4.6 and 13.9g heavier when
compared to wild hatchlings grown under the present climate, and they these hatchlings were able

45. 6
to exceed the critical aestivation weight of 18g by mid-October, when there as an unlimited food
source (Mitchel et al, 2012). However wild hatchlings, who emerge early in the breeding season,
prior to the hydroperiod, when the swamps are empty, must rely heavily on their stored yolk in
order to survive until the hydroperiod (Mitchel et al, 2012). These wild hatchlings are also more
vulnerable to desiccation and predation, compared to hatchlings who emerge during the
hydroperiod. Shorter hydropperiod and reduced autumn/winter rainfall could increase the time
that hatchlings must survive on yolk reserves. Despite its findings, the study suggested that
juveniles may not reach sexual maturity earlier, if the hydroperiod and growth period is reduced
(Mitchel et al, 2012). This could result in an invariable or declining seasonal growth, despite
increased growth rates in juveniles. Ultimately decreased rainfall and shorter hydroperiods results
in a slower growth rate, which in turn results in low intrinsic growth rate for the population, and
it makes it difficult for the species to recover from extreme population decline (Burbidge &
Kuchling, 1994).
2.3 Captive Breeding
Captive breeding is a necessary part of the recovery program for P. umbrina due to the
small size of the overall population, and the continuous decline in the size and breeding success
of the wild populations (Burbidge & Kuchling, 2004). Captive or conservation breeding serves
three primary roles for species recovery and management (Allendorf et al, 2013).
i. It provides both demographic and genetic support for remaining wild populations,
ii. It establishes sources for founding new populations,
iii. It prevents species extinction when there is no present chance of survival in the wild
In 1959, 25 specimens were removed from wild populations in order to establish a captive
breeding colony. However this breeding colony was largely unsuccessful, and in 1988, a joint
project was started between researchers at The University of Western Australia, The Perth Zoo,
and the Department of Conservation and Land Management (Kuchling & DeJose, 1989). Since
1989, The Perth Zoo has successfully bred over 800 tortoises, 600 of which have been released at
translocation sites or used to supplement the wild population at Twin Swamps Nature Reserve
(Robertson, 2007). Currently there are 181 tortoises in the captive population at Perth Zoo,
including 39 breeding adults (Robertson, 2007).

46. 7
Once the incubated eggs have hatched, they are weighed and given identification dots on
their carapace. When the juveniles have reached a body weight of 100g, they are relocated to one
of the translocated habitats managed by the Western Australian Department of Parks and Wildlife
(DPaW, formerly DEC).
2.4 Translocation Sites
Despite the progress being made at the Ellen Brooke and Twin Swamps reserves, both
reserves are relatively small, and require continuous intensive habitat management. Both of these
sites are also located within the Perth metropolitan area, and while current precautions are being
taken to control the extent of land used and developed near the reserves, increasing human
populations within Perth will only escalate the demand for land development. It was therefore
rational to establish new translocation sites in more secure areas, that will be free from
urbanization pressures and resilient towards future climactic conditions, for the future success of
the species. Although the population inhabiting the Twin Swamps reserve is one of the remaining
original wild populations of swamp tortoises, continuous decline of the population has resulted in
the addition of captive bred tortoises, making it a translocated population. The release of captive
bred individuals into this population began in 1994 and continued until 2001. During this time a
total of 148 captive bred juvenile (body mass > 100g) and 20 hatchlings were released. The
oldest translocated tortoises, which hatched at the Perth Zoo in 1990, are now reaching sexual
maturity, yet despite ultra sound evidence of vitellogenic follicles in several females, no egg
production has yet been observed.
The two translocation sites currently being managed are at the Mogumber and Moore
River nature reserves. The Mogumber reserve contains 3 clay swampland is located nearly
150km north of Perth. At the time that this area of land was purchased for the translocation site,
the yearly recorded rainfall was well above average. Translocation of captive bred tortoises at
Mogumber reserve began in 2000 with 6 juvenile tortoises. An additional 20 tortoises were
released in 2001, nine of which were radio-collared. A severe wildfire in 2002 killed many
aestivating tortoises. Those that survived were temporarily moved to Perth Zoo, and were
returned to the reserve in 2003. From 2001-2005 a further 120 tortoises were released, and 25
more in 2007. No individuals were released in 2006, as the swamps did not experience a
hydroperiod that year. As a result many of the radio-tracked tortoises moved to nearby water

47. 8
sources on adjacent private property. The last juvenile release in Mogumber reserve was in 2008,
as many of the previously released tortoises had reached sexual maturity and oviducal eggs has
been observed in 2009.
Figure 1: Map displaying current wild and translocated populated sites (Dade et al, 2014)
The Moore River reserve is located nearby the Mogumber reserve. Tortoises were first
introduced into the Northwest swamp at Moore River reserve in 2007, with 10 juvenile tortoises
all equipped with radio collars. In 2008 an additional 17 tortoises were released, and 30 more in
2009. The spring of 2008 was very dry, and many of the radio tracked tortoises moved to the
Southeastern swamp in the reserve, which sits lower and receives drainage from the NW swamp.
To allow for longer hydroperiods at the NW swamp, an embankment was created to increase the
water depth. Additional alterations were conducted at Moore River reserve in 2009, with the
creation of more embankments. However with a consistent decline in the length of the
hydroperiods of these swamps, further habitat alterations might be necessary for the long-term
viability of this translocation site. The sites currently being used for translocation are relatively
small in habitat size, and are susceptible to predators such as the European Red Fox, Vulpes
vulpes, and increasing climate change. Therefore it is very likely that new populations of tortoises

48. 9
will need to be established in the future.
Currently new translocation sites farther south are being proposed. The land surrounding
the Perth International Airport has frequently been recommended as a new translocation site. It it
generally assumed that these swamps used to house a population of western swamp tortoises, and
sightings here were recorded into the mid 1970’s. The area is much further south than the current
translocation sites and contains many suitable swamps that require few land management
practices, mainly fox control. There are other less suitable swamps that could be made habitable
through landscape modifications. A recent intensive GIS study on suitable habitats for the
western swamp tortoise, concluded that the most ideal sites were located 150-250km south of the
current known range for this species (Dade et al, 2014). Southern sites would be less arid that
current translocation sites under future climactic conditions. The affects of future climate change
in these areas would be less severe than in northern Western Australia. For the purpose of this
study, Ellen Brooke and Twin Swamps Nature Reserves and their associated tortoise populations,
along with the captive population at the Perth Zoo, will be the populations be the focus of
population viability assessments.
2.5 Translocation as a Management Tool
Assisted colonization is the introduction of a single population or entire species, into an
area that is outside of its current distribution. Assisted colonization is used when the climate
surrounding the current habitat, is expected to become unsuitable. Animals are translocated into
new areas that are expected to persist under future climactic conditions (Lunt et al, 2013).
Assisted colonization has frequently been proposed as a conservation method to preserve
biodiversity under predicted climactic changes. This method could prove beneficial in the
conservation of endangered species, especially in situations where species are restricted to patchy
habitats, such as the western swamp tortoise. Assisted colonization could help prevent the
extinction of such species by intentionally moving them to an area outside of their current range,
but where they could survive under future climate conditions. Assisted colonization could be a
viable management option against habitat loss and fragmentation and rapid climate change.
Recent studies have used assisted colonization for two butterflies in the United Kingdom,
marbled white (Melanargia galathea) and small skipper (Thymelicus sylvestris), and have been
very successful. Both butterfly populations continue to survive 7 years after their initial

49. 10
introduction 65 km outside of their historic ranges (Willis et al. 2009).
However assisted colonization is highly controversial, and has generated strong debates
over the risks and benefits of moving species beyond their historical ranges. Although assisted
colonization can conserve species threatened by climate change, introduced populations into new,
previously uninhabited areas, can cause unexpected ecological and economic damage (Lunt et al,
2013). To ensure that a potential site for translocation is capable of supporting the target species,
the habitat must be carefully evaluated. With regards to the western swamp tortoise, this should
account for variables such as average amount of rainfall, average length of hydroperiods, and
abundance of prey species. Additionally, it must assured that the site in question can maintain its
ecological integrity under future climactic conditions (Dade et al, 2014). Most research to date,
has focused on the translocation of species within their current or historic range. Very few studies
have been conducted on the viability of assisted colonization as a conservation tool. Assisted
colonization has only occasionally been used as a method for combatting extinction due to
climate change, however it is increasingly being considered as a more assertive approach to
conservation practices.
3.0 Aims And Objectives
There are two main objectives to this project.
i. Firstly, to determine the extinction probability of the tortoise populations at Ellen Brook
and Twin Swamps Nature Reserves with respect to the impacts of declining rainfall on
life-history parameters.
ii. Secondly, to determine the optimal size, age-structure, sex ratio and genetic diversity of a
new population, translocated under the guise of an assisted colonization.
4.0 Significance and outcomes
By understanding how climate change (decreasing rainfall, increasing temperature) may
impact the wild populations of P. umbrina, appropriate steps can be taken to manage wild and
translocated populations. This may involve the translocating tortoises outside of their historical
range to sites where they are more suited to withstanding future climactic conditions. Similarly,
by understanding the harvesting limits that the wild populations can withstand, conservation

50. 11
managers will know how many individuals could be removed from existing populations to
increase the genetic diversity of new populations.
5.0 Methods
5.1 Study Site
Although once inhabiting a larger area, conversion of the swamplands and an increased
arid climate, have resulted in dwindling numbers, and only two true wild populations remain at
Ellen Brooke and Twin Swamps nature reserves. Although both populations continue do decline,
the individuals at the Ellen Brook site have been successfully breeding on their own, unlike the
population at the Twin Swamps site, where individuals must be supplemented into the population
from the Perth Zoo. The captive population at Perth Zoo, initially founded by individuals from
Ellen Brooke and Twin Swamps Nature Reserves, sources captive bred tortoises into four
different sites, including Ellen Brooke Nature Reserve, and Twin Swamps Nature Reserve. The
other two sites are composed entirely of captive-bred tortoises and are located at the Mogumber
nature reserve, and the Moore River nature reserve.
5.2 Demographic Data
In order to conduct the PVA on both the Ellen Brook and Twin Swamps populations, as well as
on the potential founder population, a variety of demographic data is needed. The follow list
outlines the data that will be used for the simulations. This data has been previously collected and
compiled by the Department of Parks and Wildlife (DPaW) and the Perth Zoo.
Table 1: Demographic Data required for PVA analysis
Previously Collected Data (DPaW/Perth Zoo) Data yet to be analyzed
Hatchling sex ratio Mortality rates
Age of first offspring Carrying Capacity
Maximum age of breeding
Maximum clutch size
Clutch size distribution
% Females breeding

51. 12
% Males breeding
Although much of the demographic data will be available through the Perth Zoo’s captive
breeding program, the mortality rates for the tortoises will still require analysis. A Catch-curve
analysis is a method applied to age-specific data in order to estimate the total mortality rate (Z)
(Thorson & Prager, 2011). The catch-curve analysis fits a linear regression to the log-transformed
age proportions of a population. The resulting slope from this regression analysis provides an
estimate of Z (Thorson & Prager, 2011). The analysis works best when multiple of years of
sampling on the same population have been conducted, to allow the catch-curve to follow that
age cohort through time. For this reason catch-curves are incredibly beneficial when working
with species with long life spans and slow growth rates such as the western swamp tortoise
(Mitchel et al, 2010).
A sensitivity analysis will be conducted on this data to determine the weighted strength of
each of the variables. When demographic data has been collected through sampling techniques
the resulting statistics are merely estimates, especially when the analysis are focused on
endangered species. Sensitivity testing enables researchers to record the uncertainty in the model.
Sensitivity testing can also determine which parameters have a stronger effect on population
dynamics (Miller & Lacey, 2005). Knowing which of the parameters strongly influence the
population dynamics can help in understanding what parameters might require further studies,
and what factors might be effective targets for management (Miller & Lacey, 2005).
5.3 Genetic Data
P. umbrina is in a severe genetic bottleneck. In 2001 there were approximately 50 animals
of breeding age for the whole species, both wild and captive (Kutchling et al, 1992). Current
genetic management of the species focuses on optimizing the genetic variability in the captive
breeding population as well as in the translocated populations. These management practices are
based on equalizing the founder contribution, or maximizing the allelic diversity, and produce the
most genetically diverse release populations (Burbidge & Kutchling, 2010; Kutchling et al,
1992). Each year a female is paired with a specific male and the resulting young, for the purposes
of the studbook, are assumed to be the result of that pairing (Kutchling et al, 1992). But the
ability of females to store sperm facilitates the possibility that the young could be the result of

52. 13
any number of the previous few years’ pairings. The possibility of sperm storage was not a
priority when the recovery program was first established, as the main objective was to initiate
breeding. However the captive population is now at an age where there are a significant number
of F1 generation tortoises approaching sexual maturity. Therefore it is now of great importance to
know the true parentage of these animals in order to continue to manage the genetic diversity of
the captive breeding population.
An ongoing study into the genetic management of the captive bred population at The Perth
Zoo, is examining the accuracy of the current studbook with regards to sperm storage. This study
is also generating an estimate of the genetic diversity of this population, and examining whether
there as been any historical gene exchange between the populations at the Twin Swamps and
Ellen Brook Nature Reserves. If this research becomes available, I hope to use the data to
examine the genetic diversity of the wild populations, and assess the potential genetic
contribution of individuals from either the wild populations or captive population, to a new
translocated population.
A lot of the data collected for the sperm storage study and used in regards to this study
study, was obtained from the studbook at The Perth Zoo. Studbooks are an important
management tool for ex situ populations, in ensuring their demographic stability and genetic
diversity. Studbooks contain the identification number of each individual, the sex, birth date,
identification numbers of its parents, original birthplace, and the transfer location (if it was
released). The data is used to determine potential mating partners to minimize inbreeding and
increase or maintain a sufficient level of genetic diversity within the population. It would be
beneficial for the recovery and genetic management of P. umbrina, to assess the genetic
variability of the captive population as well as of the last wild population. The reconstruction of
family lineages for captive-bred individuals would be further helpful in assessing the genetic
contribution of males, which may be indeterminate by the ability of females to store sperm.
5.4 PVA and Genetics Software
Vortex
VORTEX is a PVA software program that simulates the effect of deterministic forces,
stochastic demographic and environmental events, and genetic drift in small populations. The
population size is determined through a combination of user-specified distributions, and random

53. 14
variables (Miller & Lacey, 2005). The program is designed to model the viability in small
populations of long-lived, diploid sexually reproducing species with a low fecundity, such as
mammals, reptiles and birds (Miller & Lacey, 2005). The program uses variables such as
reproduction, mortality, carrying capacity (K), and migration, and has been used to evaluate
management strategies in many species such as the African wild dog (Lycaon pictus; Bach et al,
2010), the European Bison (Bison bonasus; Daleszczyk, 2009) and the American mink (Neovison
vison; Pertoldi et al., 2013).
VORTEX uses a pseudorandom number generator, to model demographic stochasticity,
using reproduction, litter size, and mortality as variables (Miller & Lacy, 2005). VORTEX was
chosen as the PVA software for this study as it has often been used for exploring different
management strategies for endangered and threatened populations, and the consequences of such
strategies. The program is also capable of conducting sensitivity testing, which is used to assess
how much the different variables and their interactions affect the probability of the survival of
that population (Miller & Lacey, 2005).
Allele Retain
With regards to the genetic conservation of a species, allelic diversity is particularly
important, as it provides the capacity for adaptation and therefore enables long-term population
viability. The more alleles present within a population, provides more alternatives for that
population to respond to natural selection (Weiser et al, 2012). These alleles can become lost in
small populations as the result of bottlenecks or genetic drift. The retention of alleles through a
population can be difficult to predict, especially in species with complex demographics and life-
history traits (Weiser et al, 2012; Allendorf, 2013). The AlleleRetain software is used as an
extension of the R statistical software program. The program simulates the probability of
retaining a rare allele within a specified amount of time. Unlike PVA it does not include
stochastic effects such as environmental stochasticity (Weiser et al, 2012). AlleleRetain can be
used to assess different management options for conserving allelic diversity within small
populations.
5.5 Population Viability Analysis
Phase 1a: Assessing extinction probability at EBNR and TSNR under a) the current climate, and

54. 15
b) a future drier climate
To determine the long-term viability of the populations at Both Ellen Brook Nature
Reserve and Twin Swamps Nature Reserve, a PVA will be conducted for both populations. The
first rounds of analyses will be conducted under current climactic conditions to determine the
possibility of extinction for these populations within the near future. The second round of
analyses will use inputs based on future climactic conditions (reduced rainfall, and increase
aridity), such as increased juvenile mortality rates, increased ages of sexual maturity, and
decreased reproduction rates. This will enable the PVA model to determine the future viability of
these populations.
Phase 1b: Harvesting Pressures
To determine each population’s harvesting limitations, each VORTEX simulation will use
different harvesting pressure inputs. This stage of simulations will be run with a stable age
distribution using data previously collected. These simulations will be run for both the Ellen
Brook and Twin Swamps populations. The demographics of each population will be used as the
input data for the VORTEX software.
Phase 2: Optimal A New Population for Assisted Colonization
To determine an optimal size and structure for a new population, each Vortex analysis
will assess the minimum number of founder individuals, the ages and sex ratio of this founder
group required for a low extinction probability. Additionally, the analysis will determine the
impacts that these attributes have on the genetic diversity of the population, and how often the
population should be supplemented with new individuals. The analysis will use decreased
reproduction values and increased juvenile mortality rates to represent future climactic
conditions.
Phase 3: Using AlleleRetain
Using the results previous phase (phase 2), I will run multiple simulations using the
AlleleRetain software to determine genetically, which individuals could contribute the most to
genetic diversity in a new translocated population. To this, the genetic diversity for both wild
populations (Ellen Brook and Twin Swamps Nature Reserves) and the captive population at The
Perth Zoo, will have to be assessed. Once it is understood which populations have suitable levels

55. 16
of genetic diversity, it can be determined which populations would, genetically, be ideal sources
for a new translocated population. The AlleleRetain program will also be used in conjunction
with the VORTEX software to determine the genetic viability of a new translocated population.
6.0 Reference list
Allendorf, F.W., Luikar, G., & Aitkent, S.N. (2013) Conservation and the genetics of
populations. Hoboken: John Wiley & Sons.
Beissinger, S. R., & Westphal, M. I. (1998). On the use of demographic models of population
viability in endangered species management. The Journal of wildlife management, 821-841.
Brook, B. W., O'Grady, J. J., Chapman, A. P., Burgman, M. A., Akçakaya, H. R., & Frankham,
R. (2000). Predictive accuracy of population viability analysis in conservation biology. Nature,
404(6776), 385-387.
Burbidge, A.A. (1967). The biology of south-western Australian tortoises. Ph.D. Thesis,
University of Western Australia, Nedlands.
Burbidge, A. A. (1981). The ecology of the western swamp tortoise Pseudemydura umbrina
(Testudines: Chelidae). Wildlife Research, 8(1), 203-223.
Burbidge, A. A., & Kuchling, G. (2010). Western swamp tortoise recovery plan. Department of
Conservation and Land Management.
Dade, M. C., Pauli, N., Mitchel, N. J. (2014). Mapping a new future: using spatial multiple
criteria analysis to identify novel habitats for endangered species *currently being revised*
Daleszczyk, K. (2009). Parameters of a founder group and long term viability of a newly created
European bison populations. European Bison Conservation Newsletter 35(2), 61-7
Doak, D., Kareiva, P., & Klepetka, B. (1994). Modeling population viability for the desert
tortoise in the western Mojave Desert. Ecological Applications, 4(3), 446-460.
Grayson, K.L, Mitchell, N.J., Monks, J.M., Keall, S.N., Wilson, J.N., & Nelson, N.J. Sex ratio
bias and extinction risk in an isolated population of tuatara (Sphenodon punctatus). PLOSONE
Kuchling, G., & Bradshaw, S. D. (1993). Ovarian cycle and egg production of the western
swamp tortoise Pseudemydura umbrina (Testudines: Chelidae) in the wild and in captivity.
Journal of Zoology, 229(3), 405-419.
Kuchling, G., Dejose, J. P., Burbidge, A. A., & Bradshaw, S. D. (1992). Beyond captive
breeding: the western swamp tortoise Pseudemydura umbrina recovery programme. International
Zoo Yearbook, 31(1), 37-41.

56. 17
Lunt, I. D., Byrne, M., Hellmann, J. J., Mitchell, N. J., Garnett, S. T., Hayward, M. W., ... &
Zander, K. K. (2013). Using assisted colonisation to conserve biodiversity and restore ecosystem
function under climate change. Biological conservation, 157, 172-177.
Mitchell, N., Hipsey, M. R., Arnall, S., McGrath, G., Tareque, H. B., Kuchling, G., ... &
Kearney, M. R. (2012). Linking Eco-Energetics and Eco-Hydrology to Select Sites for the
Assisted Colonization of Australia’s Rarest Reptile. Biology, 2(1), 1-25.
Mills, L. S., & Allendorf, F. W. (1996). The one‐migrant‐per‐generation rule in conservation and
management. Conservation Biology, 10(6), 1509-1518.
Miller, S. D. (2003). Grizzly bear. Wild mammals of North America: biology, management and
conservation. Second edition. The Johns Hopkins University Press, Baltimore, Maryland, USA,
556-586.
Miller, P. S., & Lacy, R. C. (2005). VORTEX: a stochastic simulation of the extinction process.
User’s manual, version, 9.5.
Robertson, H. M. (2007). Wildlife Conservation and Perth Zoo. In National Wildlife
Rehabilitation Conference.
Shirey, P. D., & Lamberti, G. A. (2010). Assisted colonization under the US Endangered Species
Act. Conservation Letters, 3(1), 45-52.
Taylor, M. K., Laake, J., McLoughlin, P. D., Cluff, H. D., & Messier, F. (2006). Demographic
parameters and harvest-explicit population viability analysis for polar bears in M'Clintock
Channel, Nunavut, Canada. Journal of Wildlife Management, 70(6), 1667-1673.
Thorson, J. T., & Prager, M. H. (2011). Better catch curves: incorporating age-specific natural
mortality and logistic selectivity. Transactions of the American Fisheries Society, 140(2), 356-
366.
Pertoldi, C., Rødjajn, S., Zalewski, A., Demontis, D., Loeschcke, V., & Kjærsgaard, A. (2013).
Population viability analysis of American mink (Neovison vison) escaped from Danish mink
farms. Journal of animal science, 91(6), 2530-2541.
Possingham, H. P., Lindenmayer, D. B., & Norton, T. W. (1993). A framework for the improved
management of threatened species based on population viability analysis (PVA). Pacific
Conservation Biology, 1(1), 39.
Wielgus, R. B. (2002). Minimum viable population and reserve sizes for naturally regulated
grizzly bears in British Columbia. Biological Conservation, 106(3), 381-388.
Weiser, E. L., Grueber, C. E., & Jamieson, I. G. (2012). AlleleRetain: a program to assess
management options for conserving allelic diversity in small, isolated populations. Molecular
ecology resources, 12(6), 1161-1167.

57. 18
Willis, S. G., Hill, J. K., Thomas, C. D., Roy, D. B., Fox, R., Blakeley, D. S., & Huntley, B.
(2009). Assisted colonization in a changing climate: a test‐study using two UK butterflies.
Conservation Letters, 2(1), 46-52.
7.0 Budget
Funds Available: $800
Expenditures Budget Breakdown of Costs
Travel $300 for a
UWA vehicle
a) Two trips to Perth Zoo (34.4km)
b)Trip to translocation sites (452.6km)
60¢/km for UWA vehicle
Printing $50 Thesis printing and binding (UniPrint)
External Hard
Drive
$100 Data storage, including simulation results and data
from The Perth Zoo’s Stud Book.
8.0 Time table
Tasks Time
Collection of Data • All data will be obtained by June 30th
,
2014
Demographic Data • The data will demographic data will be
compiled by May 30th
, 2014
• The mortality rates and carrying capacity
rates will be assessed by June 30th
, 2014
Vortex Simulations • PVA for EBNR and TSNR under current
climactic conditions will be completed by
July 20th
, 2014
• Values for ‘future climactic conditions’
will be determined by July 5th
, 2014
• PVA for EBNR and TSNR under future
climactic conditions will be completed by
July 20th
, 2014
• PVA for EBNR and TSNR for juvenile
harvesting will be completed by August
10th
, 2014
• Simulation outline for new population
parameters will be completed by August
10th
, 2014
• PVA for future translocated population
will be completed by August 31st
, 2014
AlleleRetain Simulations • Genetic analyses on EBNR and TSNR will
be completed by September 15th
, 2014
• Genetic analysis on new population will be
completed by September 20th
, 2014

58. 57
Appendix B Journal reference style
Present-day risk assessment would have predicted the extinction
of the passenger pigeon (Ectopistes migratorius)
Jessica C. Stanton 1
Ecology and Evolution, Stony Brook University, Stony Brook, NY, United States
a r t i c l e i n f o
Article history:
Received 29 June 2014
Received in revised form 2 September 2014
Accepted 7 September 2014
Keywords:
Habitat loss
Hunting
IUCN Red List
Population fluctuations
Population modeling
Threat assessment
Threat status
a b s t r a c t
The precipitous decline and extinction of the passenger pigeon one century ago helped galvanize imple-
mentation of national policies and international cooperation on wildlife management. Having a clear
understanding of past conservation failures will aid in preventing future unanticipated extinctions.
Simulations from a population model developed for this species indicate that while habitat loss contrib-
uted to decline, the main cause of the extinction was an unregulated commercial harvest. Hindcast appli-
cation of the IUCN’s Red Listing criteria to modeled population trajectories show that the species would
have been listed as threatened for decades prior to extinction had the data and risk-assessment methods
been available. Abundant populations can belie indicators of extinction-risk such as a high rate of
population decline. Listing species as threatened based solely on rates of decline remains controversial;
however this study demonstrates that this risk-indicator may have been the sole means by which the risk
to the passenger pigeon could have been detected early enough for effective conservation measures.
Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction
This year marks the 100 year anniversary of the passing of the
last known individual passenger pigeon (Ectopistes migratorius),
once the most abundant bird species in North America (Herman,
1948). For decades their relative abundance obscured the rapid
rate of their decline (Brewster, 1889). Whether rapid decline rates
ought to warrant threatened status for still-abundant species
remains a controversial topic in conservation biology, especially
when commercial harvest is a factor in management (Godfrey
and Godley, 2008; Hutchings, 2001; Punt, 2000). Having a clear
understanding of past conservation errors, and when and how they
might have been avoided, is a critical exercise for meeting current
obligations to slow the rate of biodiversity loss (Chandra and
Idrisova, 2011).
Historically, passenger pigeons were a source of protein and lip-
ids for both Native Americans and later European colonists
(Schorger, 1955). The birds were nomadic, and therefore spatially
and temporally variable as a food resource. However, when they
were encountered, passenger pigeons tended to be abundant and
relatively easy to harvest. In the mid-19th century a commercial
market for passenger pigeon meat and live birds for sport shooting
expanded rapidly (Blockstein and Tordoff, 1985; Schorger, 1955).
At the same time, human disturbance was also reducing and frag-
menting the hardwood forests which were the primary nesting
habitat (Brewster, 1889; Bucher, 1992). Population numbers plum-
meted so dramatically that it was only a few decades after
famously dense flocks were observed that cash rewards for evi-
dence of a single wild individual went uncollected (Hodge, 1912,
1911). The species was likely extinct in the wild by the beginning
of the 20th century, and the last known individual died in captivity
in 1914 at the Cincinnati zoo (Herman, 1948).
For the past century, analysis of this extinction event has mostly
concluded that overharvest combined with disturbance of the
nesting colony was the primary causal factor (Blockstein and
Tordoff, 1985). However, skepticism of that conclusion has been
expressed since persecution from professional hunters ought to
have eased as the population declined and colonies became harder
to find and the role of habitat loss was proposed as an alternative
(Bucher, 1992; but see Conrad, 2005). Recent work suggests that
the species’ reliance on tree mast made it prone to natural popula-
tion fluctuations and unusually sensitive to anthropogenic distur-
bance (Hung et al., 2014). However, a quantitative analysis of the
simultaneous impacts of anthropogenic impacts in conjunction
with possible intrinsic life-history characteristics has not been
done. I constructed a set of population models parameterized
across a range of plausible species traits and anthropogenic
impacts to find the driving factors and interactions that best
simulate the observed population trajectory. Specifically, the
anthropogenic impact factors I explored were direct mortality from
http://dx.doi.org/10.1016/j.biocon.2014.09.023
0006-3207/Ó 2014 Elsevier Ltd. All rights reserved.
1
Current address: US Geological Survey, Upper Midwest Environmental Sciences
Center, La Crosse, WI, United States.
E-mail address: jcstanton@usgs.gov
Biological Conservation 180 (2014) 11–20
Contents lists available at ScienceDirect
Biological Conservation
journal homepage: www.elsevier.com/locate/biocon

59. 58
The perception that passenger pigeon were still abundant masked
the immediacy of the threat.
This analysis is predicated on the assumption that that accurate
population data could have been collected for the passenger pigeon
with which to conduct the IUCN Red List assessment. Without this
data, a sense that flocks seem smaller, or nesting colonies do not
cover the area they once did, might not be obvious or alarming
until population sizes are extremely reduced. Reliance on casual
observation is not likely to be a suitable monitoring strategy for
many species, particularly while they are still relatively abundant.
Organized, long-term data collection and monitoring is an essential
mechanism for risk-assessment and should not be reserved for
only those species known to be in decline or already at low popu-
lation levels.
Presently in North America, avian populations are regularly
monitored and assessed through several long-standing and orga-
nized programs (DeSante and Saracco, 2009; Hochachka et al.,
2012; Sauer et al., 2013) making it unlikely that any future North
American avian extinctions would come without a high degree of
expectation or foreknowledge. However, globally most taxa are
not nearly as well monitored; with many species too data deficient
even for risk assessment. There is a great need for the expansion of
global wildlife population monitoring programs and risk assess-
ment based on population-level symptoms such as decline rates.
We already have the necessary tools, such as the IUCN Red List
assessment, for identifying species in need of protection before
they go the way of the passenger pigeon.
Acknowledgements
I thank H.R. Akçakaya, L. Ginzburg, C. Graham, W. Thogmartin
and three anonymous reviewers for providing useful and insightful
comments. I am grateful to D. McKenney and P. Papadopol from
Natural Resources Canada for providing historic gridded climate
layers. My appreciation also goes to M. Aiello-Lammens, K. Shoe-
maker, and B. Weinstein for analytical consultation.
Appendix A. Supplementary material
Supplementary data associated with this article can be found, in
the online version, at http://dx.doi.org/10.1016/j.biocon.2014.09.
023.
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60. 59
Appendix C: Supplementary Material – VORTEX output for all scenarios
Scenario Mean
Population
Growth Rate
(r) (SD)
Probability of
Extinction
(PE) (SD)
Mean Final
Population
Size (N) (SD)
Mean Years
to Extinction
(SD)
Final Expected
Heterozygosity
(He) (SD)
EBNR low
mortality
0.055 (0.2) 0.96 (0.02) 2.44 (13.02) 24.01 (21.1) 0.71 (0.17)
EBNR high
mortality
-0.0046 (0.27) 1.0 (0) 0.01 (0.1) 22.81 (19.0) --
EBNR+
10% juv.
mortality
-0.047 (0.25) 1.0 (0) 0 (0) 16.0 (21.6) --
EBNR -10% juv.
mortality
0.052 (0.2) 0.97 (0.02) 1.29 (8.8) 18.38 (17.9) 0.74 (0.14)
EBNR+ 10%
adult mortality
-0.042 (0.22) 1.0 (0) 0 (0) 17.0 (20.4) --
EBNR- 10%
adult mortality
0.066 (0.21) 0.99 (0.01) 1.88 (8.8) 26.02 (19.8) 0.83 (0)
EBNR+ 10% juv.
Mortality -10%
adult mortality
0.07 (0.12) 0.98 (0.014) 0.91 (9.07) 24.2 (22.33) 0.72 (0.12)
EBNR- 10% juv.
Mortality +10%
adult mortality
0.043 (0.22) 0.99 (0.01) 0.5 (4.71) 23.22 (22.1) 0.8 (0)
EBNR+
10% juv.
Mortality
(exponential)
-0.11 (0.13) 0.99 (0.01) 0.36 (2.26) 20.9 (19.0) 0.83 (0.029)
EBNR-
10% juv.
Mortality
(exponential)
0.071 (0.02) 0.96 (0.02) 1.96 (10.87) 26.79 (22.97) 0.78 (0.054)
EBNR+
10% adult
Mortality
(exponential)
-0.097 (0.2) 1.0 (0) 0 (0)
16 (20.0)
--
EBNR-
10% adult
Mortality
(exponential)
0.057 (0.21) 0.99 (0.01) 0.71 (7.1) 22.81 (18.92) 0.83 (0)
TSNR low
mortality
0.028 (0.24) 0.99 (0.04) 0 (0) 24.41 (4.23) --
TSNR high
mortality
-0.055 (0.29) 1.0 (0) 0.01 (0.28) 14.77 (19.49) 0.69 (0.17)
TSNR low mort +
suppl*
0.2 (0.34) 0.39 (0.05) 13.98 (15.91) 64.84 (4.28) 0.97 (0.03)
TSNR high mort
+ suppl
0.2 (0.35) 0.46 (0.05) 14.76 (17.74) 64.32 (3.47) 0.97 (0.02)
TSNR+10% juv.
mortality
-0.3 (0.26) 0.34 (0.05) 15.13 (4.0) 24.1 (13.67) 0.97 (0.02)
TSNR -10% juv.
mortality
0.54 (0.26) 0.38 (0.05) 24.81 (16.1) 25.1 (4.6) 0.97 (0.01)
TSNR+ 10%
adult mortality
-0.03 (0.2) 1.0 (0) 10.02 (11.7) 14.0 (3.19) --
TSNR- 10% adult 0.54 (0.27) 0.46 (0.05) 25.04 (17.4) 14.6 (3.9) 0.98 (0.01)

61. 60
mortality
TSNR+ 10% juv.
Mortality -10%
adult mortality
-0.049 (0.25) 1.0 (0) 0 (0) 4.23 (3.6) --
TSNR- 10% juv.
Mortality +10%
adult mortality
-0.008 (0.27) 1.0 (0) 0 (0) 4.49 (4.29) --
TSNR+
10% juv.
Mortality
(exponential)
-0.1 (0.17) 1.0 (0) 0 (0) 5.0 (4.27) --
TSNR-
10% juv.
Mortality
(exponential)
-0.02 (0.23) 1.0 (0) 0 (0) 4.0 (3.31) --
TSNR+
10% adult
Mortality
(exponential)
-0.1 (0.24) 1.0 (0) 0 (0) 4.8 (4.87) --
TSNR-
10% adult
Mortality
(exponential)
-0.008 (0.24) 1.0 (0) 0 (0) 5.09 (4.35) --
EBNR climate
change %
females breeding
0.02 (0.12) 0.95 (0.02) 5.51 (26.0) 19 (23.4) 0.78 (0.07)
EBNR climate
change clutch
distr.
0.017 (0.13) 0.99 (0.01) 2.14 (21.4) 19 (21.6) 0.67 (0)
TSNR climate
change %
females breeding
0.024 (0.4) 0.35 (0.05) 15.8 (16.7) 15.0 (4.47) 0.97 (0.01)
TSNR climate
change clutch
distr.
-0.02 (0.19) 1.0 (0) 10.66 (11.8) 14.8 (4.7) --
Juv. Founder
Adult suppl. 50%
males N6
0.1 (0.2) 0.1 (0.03) 154.75
(74.23)
49.38 (27.54) 0.91 (0.03)
Juv. Founder
Adult suppl. 50%
males N12
0.11 (0.19) 0.12 (0.02) 157.38
(77.38)
52.48 (30.01) 0.92 (0.035)
Juv. Founder
Adult suppl. 50%
males N20
0.11 (0.18) 0.09 (0.03) 160.6 (79.92) 57.22 (21.76) 0.92 (0.004)
Juv. Founder
Adult suppl. 30%
males N6
0.12 (0.24) 0.13 (0.033) 166.67
(85.56)
45.93 (32.45) 0.92 (0.04)
Juv. Founder
Adult suppl. 30%
males N12
0.12 (0.2) 0.16 (0.04) 161.6 (67.14) 54.25 (25.23) 0.92 (0.03)
Juv. Founder
Adult suppl. 30%
males N20
0.12 (0.03) 0.13 (0.033) 175.17
(87.21)
54.08 (18.68) 0.93 (0.03)
Juv. Founder
Adult suppl. 70%
males N6
0.11 (0.22) 0.16 (0.037) 140.24
(87.49)
51.25 (24.65) 0.93 (0.03)

62. 61
Juv. Founder
Adult suppl. 70%
males N12
0.1 (0.19) 0.22 (0.04) 143.05
(95.83)
42.0 (30.93) 0.93 (0.03)
Juv. Founder
Adult suppl. 70%
males N20
0.1 (0.2) 0.17 (0.04) 142.74
(88.85)
45.78 (34.12) 0.92 (0.07)
Adult founder
juv. Suppl. 50%
males N6
0.1 (0.3) 0.11 (0.03) 155.9 (80.83) 49.46 (35.68) 0.91 (0.06)
Adult founder
juv. Suppl. 50%
males N12
0.12 (0.2) 0.21 (0.05) 138.46
(86.74)
55.9 (25.74) 0.92 (0.03)
Adult founder
juv. Suppl. 50%
males N20
0.1 (0.17) 0.1 (0.03) 172.58
(69.38)
66.45 (38.23) 0.93 (0.004)
Adult founder
juv. Suppl. 30%
males N6
0.09 (0.1) 0.09 (0.03) 142.67
(73.58)
49.67 (30.2) 0.92 (0.003)
Adult founder
juv. Suppl. 30%
males N12
0.1 (0.021) 0.09 (0.03) 147.92
(71.96)
54.73 (28.75) 0.93 (0.002)
Adult founder
juv. Suppl. 30%
males N20
0.12 (0.02) 0.11 (0.033) 151.84
(73.86)
56.3 (27.7) 0.94 (0.005)
Adult founder
juv. Suppl. 70%
males N6
0.1 (0.001) 0.1 (0.02) 148.23
(68.34)
50.23 (21.85) 0.91 (0.002)
Adult founder
juv. Suppl. 70%
males N12
0.1 (0.02) 0.13 (0.03) 151.83
(70.41)
52.54 (28.38) 0.92 (0.002)
Adult founder
juv. Suppl. 70%
males N20
0.11 (0.18) 0.13 (0.033) 154.29 (83.1) 53.77 (29.67) 0.92 (0.002)
Juv. founder juv.
Suppl 50% males
N6
0.086 (0.04) 0.16 (0.037) 134.28 (79.9) 63.4 (25.88) 0.92 (0.004)
Juv. founder juv.
Suppl 50% males
N12
0.17 (0.001) 0.14 (0.03) 233.8 (58.35) 50.92 (31.94) 0.99 (0.001)
Juv. founder juv.
Suppl 50% males
N20
0.08 (0.19) 0 (0) 146.21 (61.7) 58.29 (25.15) 0.99 (0.005)
Juv. founder juv.
Suppl 30% males
N6
0.19 (0.21) 0 (0) 229.24
(68.55)
63.23 (28) 0.99 (0.001)
Juv. founder juv.
Suppl 30% males
N12
0.08 (0.22) 0.1 (0.03) 255.18
(75.17)
65.0 (21.4) 0.91 (0.05)
Juv. founder juv.
Suppl 30% males
N20
0.18 (0.14) 0 (0) 253.16
(56.63)
68.69 (28.9) 0.99 (0.002)
Juv. founder juv.
Suppl 70% males
N6
0.03 (0.27) 0.09 (0.03) 107.96
(60.66)
43.21 (22.32) 0.99 (0.004)
Juv. founder juv.
Suppl 70% males
0.03 (0.25) 0.03 (0.02) 107.7 (53.3) 42.17 (20.29) 0.99 (0.03)

63. 62
N12
Juv. founder juv.
Suppl 70% males
N20
0.03 (0.22) 0.08 (0.03) 11.35 (57.34) 44.18 (22.86) 0.92 (0.001)
EBNR fox fence 0.0698
(0.1915)
0.99
(0.00995)
0.38 (3.80) 27.75 (22.15) 0.8452 (0)
EBNR poison
baits
0.0888
(0.1827)
1.0 (0) 0 (0) 23.88 (21.43) --
TSNR fox fence 0.2164
(0.3394)
0.4 (0.04899) 17.58 (19.8) 3.79 (3.16) 0.9758 (0.0169)
TSNR poison
baits
0.2162
(0.3336)
0.37
(0.04828)
18.66 (19.88) 4.44 (3.89) 0.9758 (0.0168)