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A critical step towards reducing the incidence of extinction is to identify and rank the species at highest risk, while implementing protective measures to reduce the risk of extinction to such species. Existing global processes provide a graded categorisation of extinction risk. Here we seek to extend and complement those processes to focus more narrowly on the likelihood of extinction of the most imperilled Australian birds and mammals. We considered an extension of existing IUCN and NatureServe criteria, and used expert elicitation to rank the extinction risk to the most imperilled species, assuming current management. On the basis of these assessments, and using two additional approaches, we estimated the number of extinctions likely to occur in the next 20 years. The estimates of extinction risk derived from our tighter IUCN categorisations, NatureServe assessments and expert elicitation were poorly correlated, with little agreement among methods for which species were most in danger – highlighting the importance of integrating multiple approaches when considering extinction risk. Mapped distributions of the 20 most imperilled birds reveal that most are endemic to islands or occur in southern Australia. The 20 most imperilled mammals occur mostly in northern and central Australia. While there were some differences in the forecasted number of extinctions in the next 20 years among methods, all three approaches predict further species loss. Overall, we estimate that another seven Australian mammals and 10 Australian birds will be extinct by 2038 unless management improves.
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Quantifying extinction risk and forecasting the number
of impending Australian bird and mammal extinctions
Hayley M. Geyle
A
,
T
,John C. Z. Woinarski
A
,G. Barry Baker
B
,
Chris R. Dickman
C
,Guy Dutson
D
,Diana O. Fisher
E
,Hugh Ford
F
,
Mark Holdsworth
G
,Menna E. Jones
H
,Alex Kutt
I
,
J
,
K
,Sarah Legge
A
,
L
,Ian Leiper
A
,
Richard Loyn
M
,
N
,
O
,Brett P. Murphy
A
,Peter Menkhorst
P
,April E. Reside
L
,
Euan G. Ritchie
Q
,Finley E. Roberts
R
,Reid Tingley
S
and Stephen T. Garnett
A
A
Threatened Species Recovery Hub, National Environmental Science Program, Research Institute
for the Environment and Livelihoods, Charles Darwin University, NT 0909, Australia.
B
Institute for Marineand Antarctic Studies, The University of Tasmania, Hobart, Tas. 7005, Australia.
C
Threatened Species Recovery Hub, National Environmental Science Program, Desert Ecology
Research Group, School of Life and Environmental Sciences A08, The University of Sydney,
NSW 2006, Australia.
D
Yellow Gum Drive, Ocean Grove, Vic. 3226, Australia.
E
School of Biological Sciences, The University of Queensland, St Lucia, Qld 4072, Australia.
F
School of Environmental and Rural Sciences, The University of New England, Armidale,
NSW 2351, Australia.
G
Forest Hill Wildlife Consultants, Sandford, Tas. 7020, Australia.
H
School of Natural Resources (Biological Sciences), The University of Tasmania, Hobart,
Tas. 7005, Australia.
I
School of BioSciences, The University of Melbourne, Parkville, Vic. 3010, Australia.
J
Green Fire Science, School of Earth and Environmental Science, The University of Queensland,
St Lucia, Qld 4072, Australia.
K
Bush Heritage Australia, Melbourne, Vic. 3000, Australia.
L
Threatened Species Recovery Hub, National Environmental Science Program,
Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia,
Qld 4072, Australia.
M
The Murray–Darling Freshwater Research Centre, School of Life Sciences, La Trobe University,
Wodonga, Vic. 3690, Australia.
N
Institute for Land, Water and Society, Charles Sturt University, Albury, NSW 2640, Australia.
O
Eco Insights, Beechworth, Vic. 3747, Australia.
P
Arthur Rylah Institute for Environmental Research, Department of Environment, Land,
Water and Planning, Heidelberg, Vic. 3084, Australia.
Q
Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University,
Burwood, Vic. 3125, Australia.
R
Forest Fire and Regions, Department of Environment, Land, Water and Planning, East Melbourne,
Vic. 3002, Australia.
S
Quantitative and Applied Ecology Group, School of BioSciences, The University of Melbourne,
Parkville, Vic. 3010, Australia.
T
Corresponding author. Email: hayley.geyle@cdu.edu.au
Abstract. A critical step towards reducing the incidence of extinction is to identify and rank the species at highest risk,
while implementing protective measures to reduce the risk of extinction to such species. Existing global processes provide
a graded categorisation of extinction risk. Here we seek to extend and complement those processes to focus more narrowly
on the likelihood of extinction of the most imperilled Australian birds and mammals. We considered an extension of
existing IUCN and NatureServe criteria, and used expert elicitation to rank the extinction risk to the most imperilled
species, assuming current management. On the basis of these assessments, and using two additional approaches, we
CSIRO PUBLISHING
Pacific Conservation Biology, 2018, 24, 157–167
https://doi.org/10.1071/PC18006
Journal compilation ÓCSIRO 2018 Open Access CC BY-NC-ND www.publish.csiro.au/journals/pcb
estimated the number of extinctions likely to occur in the next 20 years. The estimates of extinction risk derived from our
tighter IUCN categorisations, NatureServe assessments and expert elicitation were poorly correlated, with little agreement
among methods for which species were most in danger highlighting the importance of integrating multiple approaches
when considering extinction risk. Mapped distributions of the 20 most imperilled birds reveal that most are endemic to
islands or occur in southern Australia. The 20 most imperilled mammals occur mostly in northern and central Australia.
While there were some differences in the forecasted number of extinctions in the next 20 years among methods, all three
approaches predict further species loss. Overall, we estimate that another seven Australian mammals and 10 Australian
birds will be extinct by 2038 unless management improves.
Additional keywords Anthropocene mass extinction crisis, biodiversity conservation, threatened species
Received 17 January 2018, accepted 4 March 2018, published online 20 April 2018
Introduction
Although extinctions occur naturally, the rate of extinction is
currently ,1000 times the background rate (Pimm et al. 2014).
At least three endemic vertebrate species were rendered extinct
in Australia in the last decade (Woinarski et al. 2017), con-
tinuing an ongoing pattern of high rates of extinction for at least
some segments of our fauna. This is most evident in the loss of an
average of one to two mammals per decade since the 1850s,
amounting to a total loss of 30 endemic species (Woinarski et al.
2015). Twenty-nine Australian birds have also become extinct
over the last 200 years (Szabo et al. 2012). At least some of these
extinctions may well have been prevented with adequate fore-
warning followed by appropriate management responses
(Woinarski et al. 2017).
Extinction risk is broadly captured in the International Union
for the Conservation of Nature (IUCN) Red List categories and
criteria (IUCN 2012). The category ‘Critically Endangered is
applied to those species at greatest risk, suggesting that action
needs to be taken immediately to prevent their loss. However,
some species can be Critically Endangered for many decades
while others move rapidly through categories to Extinct, meeting
the criteria for Critically Endangered only briefly before the last
individual dies, thus allowing little time for management action.
Also, even recently, some species have not been assessed until it
was too late to act. For example, the forest skink (Emoia
nativitatis), which was endemic to Christmas Island, remained
unassessed by the IUCN until 2010 when it was listed as Critically
Endangered. This was evidently too late, as the last wild reporting
of this species took place in 2009 (Woinarski et al. 2017). The last
captive individual died in 2014, marking the species’ extinction
(Woinarski et al. 2017).
General models capable of forecasting which species are at
imminent risk of extinction do not yet exist. Population viability
models can be useful, but require detailed data that are not
available for most species, especially those most threatened with
extinction, and those from groups for which there is generally a
high proportion of species lacking extensive background data (i.e.
invertebrates: Schultz and Hammond 2003). One alternative is to
apply and extend existing systems conventionally used to assess
extinction risk. Additional to the IUCN Red List categories and
criteria, NatureServe provides a system for assessing extinction
risk, using broadly analogous criteria to the IUCN (Master et al.
2009). Both systems lend themselves to tailored modification for
more precisely predicting the likelihood of imminent extinction.
Extinction risk can also be assessed using expert elicitation.
Experts are able to synthesise multiple risks and probabilities in
ways that may be intractable for numerical models. Furthermore,
variation in experience and risk perception among experts allows
the development of multiple mental models from the same raw
empirical data. Thus, integrating the opinions of multiple experts
is essentially an exercise in model averaging (Symonds and
Moussalli 2011) and produces better results than can be obtained
from a single expert (Martin et al. 2012). Expert elicitation
techniques are becoming increasingly sophisticated as inherent
biases in judgement are better understood (Martin et al. 2012).
In this paper, we aim to predict which Australian bird and
mammal taxa (encompassing species and subspecies) are most
likely to be lost in the next 20 years under current management.
The rationale for this assessment is that such forecasting may
improve prioritisation, direction and resourcing of management
aimed at averting losses. We combine three approaches to identify
the taxa in most immediate danger: (1) a nominal tightening of the
IUCN Red List criteria; (2) application of the NatureServe proto-
col; and(3) expert elicitation. We compare each method to identify
overlaps and limitations, recognising that each may miss some
highly imperilled taxa or exaggerate extinction risk in others.
We then map the distributions of the 20 most imperilled birds
(using data provided by BirdLife Australia) and mammals (using
data compiled for Woinarski et al. 2014) to allow identification of
the regions in which prioritisation of extinction prevention should
be focussed. Finally, we aggregate and model our estimated
extinction risks for individual taxa to derive estimates of the
number of Australian birds and mammals likely to become extinct
in the next two decades unless management is enhanced or
directed more appropriately. We compare these outputs with
two other approaches used to forecast the number of extinctions:
(1) probability of extinction thresholds under IUCN Red List
Criterion E, and (2) projectionof the rate of change through IUCN
conservation status categories based on rates of change observed
over the past two decades.
Materials and methods
Identifying the taxa most at risk of extinction
Initial selection
All birds listed as Vulnerable, Endangered or Critically
Endangered under relevant Australian legislation (Environment
Protection and Biodiversity Conservation Act 1999) or in the
158 Pacific Conservation Biology H. M. Geyle et al.
2010 Action Plan for Australian Birds (Garnett et al. 2011)
were considered in this study. Because mammals were recently
assessed against the IUCN Red List criteria for the 2012
Action Plan for Australian Mammals (Woinarski et al.
2014), terrestrial taxa listed as Endangered or Critically
Endangered in the Action Plan wereconsideredinthisstudy,
along with subsequent assessments for a small set of taxa
described since then, and updated assessments for two subspe-
cies of nabarlek (Petrogale concinna) based on more recent
information. We excluded four birds and two mammals
flagged as ‘Possibly Extinct’ as the available evidence indi-
cates that each of these taxa had already been lost (Table S1,
available as Supplementary Material to this paper). In total, 235
birds and 39 mammals were assessed.
IUCN ‘Extinction Imminent’ assessments
To be threatened under the IUCN Red List, a species must
meet defined criteria (Table S2, see Supplementary Material;
IUCN 2012). Here, we nominally tighten those categories and
criteria to further highlight the most imperilled species by
subdividing the existing Critically Endangered category. The
more extreme of these subdivisions we consider to be Extinction
Imminent, with the definition of this class based on a logical
extrapolation of the existing Critically Endangered thresholds
(Table S2). We assessed all birds and mammals (identified
above) against these new thresholds, using information on
population size, geographic range and trends (obtained from
Garnett et al. 2011 and Woinarski et al. 2014).
NatureServe assessments
The NatureServe protocol uses point scoring and logical
rules with a mixture of quantitative, qualitative, and subjective
criteria to assess extinction risk (Master et al. 2009, 2012). This
method has five categories of threat, ranging from G1 (Criti-
cally Imperilled) to G5 (Secure and Abundant). While similar
data inputs are used for allocating a threat category under both
IUCN and NatureServe protocols (Tables S2 and S3, see
Supplementary Material), the latter system categorises and
assigns number codes (which may be positive or negative,
depending on the parameter), which are then weighted and
summed to give an overall conservation status score (Regan
et al. 2005) (See Table S3 for details on the data inputs and
weights). All birds and mammals identified above were evalu-
ated against the NatureServe criteria using the conservation
statusfactorsoutlinedinTableS3andthenrankedaccordingto
conservation status score. Two scores were derived for each
taxon: the pessimistic score (calculated using the lower bound
of the conservation status factors) and the optimistic score
(calculated using the upper bound of the conservation status
factors) (Table S3). Lower and upper data bounds, derived
from Garnett et al. (2011) and Woinarski et al. (2014),reflect
the uncertainty of data input estimates.
Expert elicitation
We used expert elicitation to assess extinction risk in all 39
mammal taxa selected using the procedures described above.
Due to the large number of threatened birds considered, we
reduced the number of birds to be assessed to 34 by choosing
only taxa that (1) were assessed as Extinction Imminent under
our extension of the IUCN protocol, and/or (2) ranked in the top
20 most at risk of extinction under the NatureServe protocol (for
both pessimistic and optimistic assessments).
We then asked 13 experts for each of the mammal and bird
lists to make a judgement about the likelihood of extinction (in
the wild) of each taxon (scaled from 0 to 100%) in the next
20 years, assuming current levels and character of management.
Experts were selected on the basis of their contributions to
Garnett et al. (2011) and Woinarski et al. (2014). We also
obtained a level of confidence for each of their estimates (very
low, low, moderate, high, or very high). Some experts decided to
score taxa only if confident in their ability to ascribe extinction
risk. We then asked experts to determine whether there were any
taxa missing from the lists that they also considered to be at high
risk of imminent extinction; this resulted in the inclusion of six
additional birds for assessment (Gawler Range short-tailed
grasswren, Amytornis merrotsyi pedleri; western bristlebird,
Dasyornis longirostris; mallee emu-wren, Stipiturus mallee;
Gulf St Vincent slender-billed thornbill, Acanthiza iredalei
rosinae; Norfolk Island scarlet robin, Petroica multicolor;
western partridge pigeon, Geophaps smithii blaauwi) and two
additional mammals (bridled nailtail wallaby, Onychogalea
fraenata; New Holland mouse, Pseudomys novaehollandiae).
Following the initial round of expert elicitation, feedback was
provided, email discussions took place, and some experts
adjusted their judgement (as per the Delphi process, see
McBride et al. 2012).
Statistical analysis
We controlled for individual experts consistently underesti-
mating or overestimating likelihood of extinction by analysing
each expert’s estimates (logit-transformed before analysis)
using a linear mixed-effects model (‘lme’ in package ‘nlme’)
in R 3.2.1 (R Core Team 2015), with the identity of the
individual experts specified as random intercepts. We specified
a variance structure in which variance increased with the level of
uncertainty associated with each estimate of likelihood of
extinction. Confidence classes of ‘very low’, ‘low’, ‘moderate’,
‘high’ and ‘very high’ were converted to uncertainty scores of
90%, 70%, 50%, 30%, and 10%, respectively. We used the
linear mixed-effects model to predict the probability of extinc-
tion (with 95% confidence intervals) for each taxon.
The set of experts involved in evaluating extinction risk were
largely different for birds compared with mammals. If a major
difference in attitude to risk evaluation was evident between
these two taxonomic groups, then a comparison of extinction
risk may be inappropriate. To test for such an artefactual result,
we compared the extinction risk ratings for the 20 birds and 20
mammals ranked most in danger of extinction (using Mann–
Whitney U tests) for each of three experts who provided scores
for both taxonomic groups.
We used Pearson’s correlation coefficient to test for corre-
lation between NatureServe scores and expert elicitation
extinction probabilities (log-transformed). To test for concor-
dance with Extinction Imminent status, we ran linear regres-
sion models where NatureServe score or expert extinction
probabilities were modelled as response variables and Extinc-
tion Imminent status was modelled as a binary predictor.
Forecasting extinction of threatened taxa Pacific Conservation Biology 159
We report the P-values (considered significant if P,0.05) of
these models for inference.
Estimating the number of taxa likely to become
extinct in the next 20 years
Expert elicitation
The predicted probabilities of extinction for each of the 40
birds and 41 mammals (assessed by the experts) were summed to
estimate the number of taxa (from this subset of birds and
mammals) likely to become extinct in the next 20 years.
We also estimated the likely number of extinctions, in the
next 20 years, of taxa not in this subset, i.e. those lower-
extinction-risk taxa not assessed by the experts. To do this, we
first established that there was no significant difference between
the distributions of predicted probabilities of extinction for the
subset of 40 birds and 41 mammals, using a non-parametric
Kolmogorov–Smirnov test (P.0.05). We then modelled the
linear relationship between the logarithm of predicted probabil-
ity of extinction for each taxon and rank order of likelihood of
extinction (based on expert elicitation in both cases) for birds
and mammals combined (R
2
¼0.99).
To estimate the probability of extinction of the 1199 birds
and 380 mammals not included in the subset of taxa assessed by
the experts, we summed predicted probabilities of extinction
for each rank to approximate the total number of taxa not
assessedbyexpertsthatarelikelytobecomeextinctinthenext
20 years.
IUCN Red List Criterion E
The number of taxa expected to become extinct in the next 20
years can also be estimated on the basis of assumptions under-
lying IUCN Criterion E extinction probability thresholds, which
are based on population viability analyses. Under the IUCN Red
List categories and criteria, Critically Endangered taxa are
considered to have at least a 50% probability of extinction
within 10 years or three generations (whichever is longer);
Endangered taxa are considered to have .20% probability of
extinction within 20 years or five generations; and Vulnerable
taxa are considered to have .10% probability of extinction
within 100 years. Following Brooke et al. (2008), we assumed
that taxa listed in a threatened Red List category (Vulnerable,
Endangered or Critically Endangered) under any criterion other
than E will have comparable extinction risk to taxa listed within
that status under Criterion E.
On the basis of this assumption, we calculated the minimum
number of bird and mammal taxa expected to become extinct
(N
ex
) in the next 20 years as:
Nex ¼Nth 1ð1EX Þ1
T
ðÞ
t

Where N
th
refers to the number of taxa in each threatened
category (hereby referred to as N
cr
,N
en
and N
vu
for respective
categories), EX is the probability of extinction (i.e. 50%, 20%
10% for Critically Endangered, Endangered, and Vulnerable
respectively), Tis the time corresponding to the minimum period
for each of the extinction probabilities (i.e. 10, 20 and 100 for
CriticallyEndangered, Endangered and Vulnerable respectively),
and tis the period of interest (i.e. 20 years). We were thus able to
calculate the number of expected extinctions as:
Nex ¼Ncr 1ð150Þ1
10
ðÞ
20

þNen 1ð120Þ1
20
ðÞ
20

þNvu 1ð110Þ1
100
ðÞ
20

Trajectories in IUCN Red List categories
over the last 20 years
Using Garnett et al. (2011) and Woinarski et al. (2014),we
assessed changes in the conservation status of all Australian birds
and all terrestrial Australian mammals from 1990 to 2010 and
from 1992 to 2012, respectively. We identified the number of taxa
moving between different conservation status categories owing to
genuine improvement or deterioration in status (as in Brooke et al.
2008) to estimate how many could move into the Extinct category
based on historical trends. We analysed these data using propor-
tional odds logistic regression models (‘polr’ in package ‘MASS’)
in R, whereby the response is an ordered multinomial. In our case,
the response was the most recent (2010 for birds, 2014 for
mammals) IUCN Red List category for each taxon (i.e. Least
Concern ,Near Threatened ,Vulnerable ,Endangered ,
Critically Endangered ,Extinct). We modelled these as a
function of the IUCN category for each taxon 20 years earlier
(1990 for birds, 1992 for mammals). To approximate the total
number of taxa likely to become extinct in the next 20 years, we
multiplied the proportion of taxa in each category moving into
the Extinct category over a 20-year period predicted using the
proportional odds logistic regression model by the number of taxa
currently in each category. This analysis assumes that the histori-
cal rate (i.e. over the last 20 years) of movement of individual taxa
across Red List conservation status categories will continue over
the next 20 years.
Results
Taxa most likely to become extinct
IUCN ‘Extinction Imminent’ category
Of the 40 birds assessed, 23 (,58%) triggered Extinction
Imminent status under our nominally tighter IUCN thresholds,
with most triggering either Criteria A1–4 (population size
reduction), Criteria B1 (extent of occurrence and accompanying
subcriteria) or B2 (area of occupancy and accompanying sub-
criteria) (Table S2). Of the 41 mammals assessed, nine taxa
(,22%) triggered Extinction Imminent status all based on
Criteria A1–4 or B1–2 (and accompanying subcriteria) (Table
S2). Taxa with Extinction Imminent status are listed in Tables 1
and S4 (see Supplementary Material).
NatureServe assessments
Of the birds assessed by the experts, NatureServe scores
ranged from 1.2 (for the Critically Imperilled orange-bellied
parrot, Neophema chrysogaster) to 2.7 (for the western bristle-
bird, Dasyornis longirostris) based on pessimistic estimates, and
from 0.7 to 3.5 based on optimistic assessments (Tables 1 and
S4). Most of the top 20 ranked pessimistic NatureServe scores
(85%) were ,1.5, corresponding to allocation to the highest
160 Pacific Conservation Biology H. M. Geyle et al.
Table 1. The likelihood of extinction (EX) in the next 20 years for the 20 birds and 20 mammals considered most imperilled
Likelihoods of extinction are based on expert elicitation (with lower/upper confidence intervals) and are ranked from highest to lowest probability of extinction.
Also shown: whether they met intensified IUCN Red List Criteria (EI), their pessimistic (pes) and optimistic (opt) NatureServe (NS) scores (i.e. scores
calculated using the lower and upper bound of NatureServe conservation status factors see Table S3) and their pessimistic (pes) and optimistic (opt)
NatureServe ranks respective to the total number of birds (n=235) and mammals (n=41) assessed. CI, confidence interval
Rank Taxon EX Lower
95% CI
Upper
95% CI
IUCN
(EI)
NS score
(pes)
NS rank
(pes)
NS score
(opt)
NS rank
(opt)
Birds
1 King Island brown thornbill, Acanthiza pusilla archibaldi 0.94 0.84 0.98 Yes 0.9
B
12 1.2
B
7
2 Orange-bellied parrot, Neophema chrysogaster
A
0.87 0.76 0.94 Yes 1.2
B
10.7
B
1
3 King Island scrubtit, Acanthornis magna greeniana 0.83 0.66 0.93 Yes 0.3
B
5 0.6
B
3
4 Western ground parrot, Pezoporus wallicus flaviventris
A
0.75 0.56 0.87 Yes 0.5
B
2 0.3
B
2
5 Houtman Abrolhos painted buttonquail, Turnix varius
scintillans
0.71 0.42 0.90 No 0.6
B
8 1.1
B
5
6 Plains-wanderer, Pedionomus torquatus
A
0.64 0.40 0.82 Yes 0.1
B
3 1.7 12
7 Regent honeyeater, Anthochaera phrygia
A
0.57 0.37 0.75 Yes 0.6
B
6 1.8 14
8 Grey range thick-billed grasswren, Amytornis modestus
obscurior
0.53 0.27 0.78 Yes 0.9
B
12 1.2
B
6
9 Herald petrel, Pterodroma heraldica
C
0.52 0.27 0.76 Yes 2.0 73 2.1 22
10 Black-eared miner, Manorina melanotis 0.47 0.05 0.93 No 0.9
B
16 2.2 27
11 Northern eastern bristlebird, Dasyornis brachypterus
monoides
A
0.39 0.17 0.67 No 1.2
B
19 1.7 13
12 Mallee emu-wren, Stipiturus mallee
A
0.34 0.11 0.67 No 1.3
B
21 2.8 66
13 Swift parrot, Lathamus discolor
A
0.31 0.16 0.50 Yes 0.8
B
10 2.2 24
14 Norfolk Island boobook, Ninox novaeseelandiae undulata
A
0.27 0.13 0.46 Yes 0.9
B
12 1.4 11
15 Mount Lofty Ranges chestnut-rumped heathwren, Cala-
manthus pyrrhopygia parkeri
0.24 0.08 0.51 No 0.6
B
7 1.9 18
16 Fleurieu Peninsula southern emu-wren, Stipiturus mala-
churus intermedius
0.17 0.05 0.44 No 1.3
B
20 1.9 15
17 Helmeted honeyeater, Lichenostomus melanops cassidix
A
0.17 0.08 0.32 Yes 1.0
B
17 1.1 4
18 Cocos buff-banded rail, Hypotaenidia philippensis andrewsi 0.17 0.07 0.34 Yes 1.9 62 2.2 25
19 Western bristlebird, Dasyornis longirostris 0.16 0.05 0.40 No 2.7 149 3.5 142
20 Alligator Rivers yellow chat, Epthianura crocea tunneyi
A
0.15 0.04 0.40 No 0.7
B
9 1.9 16
Mammals
1 Central rock-rat, Zyzomys pedunculatus
A
0.65 0.48 0.79 Yes 0.58
B
10.58
B
1
2 Northern hopping-mouse, Notomys aquilo
A
0.48 0.30 0.67 No 0.39
B
6 0.55
B
7
3 Carpentarian rock-rat, Zyzomys palatalis 0.44 0.24 0.66 No 0.84
B
15 1.0
B
15
4 Christmas Island flying-fox, Pteropus natalis
A
0.41 0.23 0.62 Yes 0.26
B
4 0.26
B
3
5 Black-footed tree-rat (Kimberley and mainland NT),
Mesembriomys gouldii gouldii
0.39 0.22 0.59 No 1.10
B
18 1.27
B
18
6 Gilbert’s potoroo, Potorous gilbertii
A
0.36 0.21 0.58 Yes 0.52
B
2 0.36
B
2
7 Leadbeater’s possum, Gymnobelideus leadbeateri
A
0.29 0.15 0.52 Yes 0.42
B
7 1.27
B
4
8 Nabarlek (Top End), Petrogale concinna canescens 0.29 0.13 0.51 No 0.49
B
9 0.65 10
9 Brush-tailed phascogale (Kimberley), Phascogale tapoatafa
kimberleyensis
0.28 0.13 0.49 No 1.58 31 1.7 31
10 Brush-tailed rabbit-rat (Kimberley, Top End), Conilurus
penicillatus penicillatus
A
0.25 0.11 0.47 No 0.92
B
16 1.37
B
22
11 Western ringtail possum, Pseudocheirus occidentalis
A
0.25 0.11 0.46 Yes 0.26
B
3 0.45
B
5
12 Northern brush-tailed phascogale, Phascogale pirata 0.23 0.10 0.44 No 1.59 32 1.88 32
13 Mountain pygmy-possum, Burramys parvus
A
0.22 0.09 0.42 No 1.28
B
23 1.43
B
24
14 Kangaroo Island dunnart, Sminthopsis griseoventer aitkeni
A
0.22 0.09 0.44 No 1.33
B
26 1.48
B
26
15 Brush-tailed rabbit-rat (Tiwi Islands), Conilurus penicillatus
melibius
A
0.21 0.09 0.41 No 0.06
B
11 1.06
B
17
16 Silver-headed antechinus, Antechinus argentus 0.20 0.08 0.42 No 1.71 33 3.17 39
17 Southern bent-winged bat, Miniopterus orianae bassanii 0.18 0.07 0.37 No 1.14
B
20 1.31
B
20
18 Black-tailed antechinus, Antechinus arktos 0.17 0.06 0.37 No 2.3 39 4.89 41
19 Northern bettong, Bettongia tropica 0.14 0.05 0.31 No 1.48
B
29 1.63 28
20 Tasman Peninsula dusky antechinus, Antechinus vandycki 0.14 0.05 0.31 No 2.23 38 4.75 40
A
Included in the priority list of 20 birds and 20 mammals under the National Threatened Species Strategy (Department of the Environment and Energy 2016).
B
Critically Imperilled based on NatureServe criteria.
C
Refers to Australian breeding population.
Forecasting extinction of threatened taxa Pacific Conservation Biology 161
category afforded by the NatureServe protocol, Critically Imper-
illed (Table 2). Less than half of the top 20 ranked optimistic
scores (30%) were categorised as Critically Imperilled, while the
remaining scores corresponded to an Imperilled or Vulnerable
status (i.e. scores ranging from 1.6 to 3.5: Table 2).
Of the mammals assessed, NatureServe pessimistic scores
ranged from 0.58 (for the Critically Imperilled central rock rat,
Zyzomys pedunculatus) to 3.34 (the vulnerable yellow-bellied
glider (wet tropics), Petaurus australis undescribed subspecies).
Optimistic scores ranged from 0.58 to 4.89 (Critically Imper-
illed to Secure and Abundant) (Tables 1 and S4).
Expert elicitation and extinction probabilities
Table 1 presents the probability of extinction and 95%
confidence intervals for the 20 birds and mammals at greatest
risk of extinction based on the expert elicitation, and application
of the linear mixed-effects model. Collation and analysis of
expert opinion indicated that nine birds (see Table 1) and one
mammal (the central rock-rat, Zyzomys pedunculatus) were
more likely than not to become extinct in the next 20 years.
This result may reflect real differences between these two
groups in likelihood of extinction or attitudinal difference in
the experts who assessed birds relative to those who assessed
mammals. The former is more likely, as all three experts who
assessed both birds and mammals rated extinction-risk higher
for bird taxa than mammal taxa, with this difference highly
significant in two out of three cases (Table 3).
Concordance among the three approaches
in ranking the taxa at highest extinction risk
Of the 20 birds and mammals listed in Table 1, just over half
(60%) of the birds and one-quarter (25%) of the mammals were
also categorised as Extinction Imminent in our nominal tighten-
ing of IUCN criteria. More than three-quarters of the birds
(80%) and just over half of the mammals (60%) had NatureServe
scores ranking in the top 20 (based on pessimistic calculations).
A greater proportion (85% of birds and 75% of mammals)
obtained NatureServe scores ,1.5, corresponding to allocation
of Critically Imperilled status.
For the remaining mammals, Extinction Imminent birds, and
those birds with high-ranking NatureServe scores, the experts
considered the probability of extinction in the next 20 years to be
relatively low (#12%, Table S4). The overall probability of
extinction for the entire subset of taxa was loosely correlated
with whether a taxon had a high-ranking NatureServe score
(r
80
¼0.5, P,0.01) (Fig. 1). There was no significant effect
of Extinction Imminent status on the probability of extinction
(P¼0.72), but Extinction Imminent taxa were more likely to
have lower NatureServe scores (P¼0.028) (Fig. 1).
Geographical distribution of the taxa at highest extinction
risk
Four of the 20 birds with highest extinction risk breed only on
small islands (,40 km
2
), with a further two from King Island, a
large island (1098 km
2
) in Bass Strait, and two others in
Tasmania, a larger island again (64 519 km
2
). The latter two
are both migratory parrots (Neophema chrysogaster and Latha-
mus discolor) that spend the non-breeding season in mainland
Australia. All of the other birds with mainland distributions
occur in southern Australia, mostly in intensively modified
regions (Fig. 2a).
Five of the 20 most imperilled mammals occur only on
islands (ranging in size from 137 to 5786 km
2
), but none of
these islands also support a highly threatened bird (i.e. ranking
Table 2. NatureServe scores and associated status descriptions
NS score range NS status description
#1.5 G1: Critically Imperilled
1.6–2.5 G2: Imperilled
2.6–3.5 G3: Vulnerable
3.6–4.5 G4: Apparently Secure
$4.6 G5: Secure
Table 3. Comparison of the average scores derived from three indi-
vidual experts’ estimated likelihoods of extinction (±standard error) for
the 20 birds and 20 mammals most in danger of extinction
All three experts provided assessments for most of the bird and mammal taxa
considered as part of this study. Z-scores and associated P-values (consid-
ered significant if P,0.05) are provided for comparisons between the
individual expert’s scores, based on Mann–Whitney U tests
Expert 1 Expert 2 Expert 3
Birds 0.46 (0.08) 0.49 (0.06) 0.52 (0.11)
Mammals 0.31 (0.06) 0.17 (0.03) 0.17 (0.04)
Comparison: Z (P) 1.22 (0.22) 3.47 (0.0005) 2.53 (0.0011)
0
1.5 1.0 1.0
NatureServe score
Probability of extinction (%)
0.5 0.5 2.01.5 3.02.5 3.50
10
20
30
40
50
60
70
80
90
G1 G2 G3
100
Birds
Mammals
Fig. 1. The relationship between expert elicitation probabilities of extinc-
tion, NatureServe pessimistic scores (i.e. those calculated using the lower
bound of NatureServe parameters see Table S3) and whether bird and
mammal taxa met the intensified IUCN Red List ‘Extinction Imminent’
criteria (dark shaded symbols). G1, Critically Imperilled; G2, Imperilled;
G3, Vulnerable (see Table 2).
162 Pacific Conservation Biology H. M. Geyle et al.
in the top 20) (Table 1). In contrast to the birds, half of the most
imperilled mammals occur mostly or only in northern or central
Australia (Fig. 2b).
Number of taxa likely to become extinct in the
next 20 years
From extinction-risk values assigned by experts to the 40 bird
and 41 mammal taxa assessed, we estimate that 9.9 birds and 7.2
mammals will become extinct in the next 20 years. On the basis
of the extrapolation of the distribution of scores for likelihood of
extinction (from expert opinion) of these taxa, we estimate that a
further 0.02 birds and 0.02 mammals, not assessed by experts,
will become extinct over this period, bringing the total to
,10 birds (0.82% of 1239 extant taxa) and ,7 mammals
(1.76% of 421 extant taxa) (Table 4).
Application of IUCN Red List Criterion E to all extant taxa
suggests that ,27 birds (2.2% of extant taxa) and ,15 mammals
(3.5% of extant taxa) can be expected to become extinct in the
next 20 years (Table 4).
Projection of the rate of movement of taxa between conserva-
tion status categories during the last 20 years indicates that 0.27%
of birds (i.e. ,3 taxa) and 1.01% of mammals (i.e. ,4 taxa) are
likely to become extinct by 2038 (Tables 4,5,6).
Discussion
Conservation status assessments aim to identify the extinction
risk of species (Mace et al. 2008). Accurate characterisation of
extinction risk is crucial, given ambitions of national govern-
ments and non-government organisations to prevent further
0
CK Cl Nl
0
No. of taxa
1
2
3
4
450
Scalebar for mainland Australia
900 1800
km
015
Scalebar for offshore islands and territories
30 60
km
0
CK Cl Nl
0
No. of taxa
1
2
3
4
450
Scalebar for mainland Australia
900 1800
km
015
Scalebar for offshore islands and territories
30 60
km
N
N
(a)
(b)
Fig. 2. The number of (a) bird and (b) mammal taxa occurring in each
Interim Biogeographic Regionalisation for Australia (IBRA) subregion (SA
Department of Environment Water and Natural Resources 2015). Data are
presented for the 20 most imperilled birds and the 20 most imperilled
mammals (obtained from expert elicitation). CK, Cocos (Keeling) Islands;
CI, Christmas Island; NI, Norfolk Island.
Table 4. The number and percentage of Australian bird and terrestri-
al mammals expected to become extinct in the next 20 years, if current
levels of management are assumed
Numbers are estimated using three methods: (1) expert elicitation (selected
high-risk taxa directly assessed by experts, and additional taxa not assessed);
(2) IUCN Red List Criterion E extinction probability thresholds; and (3)
trends and trajectories in IUCN statuses observed during recent 20-year
periods (1990–2010 for birds and 1992–2012 for mammals)
Estimation method Birds Mammals
Extant taxa 1239 421
Proportion extinct in next 20 years
Experts 0.82% 1.76%
Directly estimated 0.80% 1.71%
Additional taxa 0.02% 0.05%
Red List Criterion E 2.20% 3.50%
Trajectories over last 20 years 0.27% 1.01%
Absolute number extinct in next 20 years
Experts 10.16 7.41
Directly estimated 9.91 7.20
Additional taxa 0.25 0.21
Red List Criterion E 27.26 14.74
Trajectories over last 20 years 3.35 4.25
Table 5. The number of birds in each IUCN Red List category in 1990,
on the basis of current knowledge regarding population parameters (see
Brooke et al. 2008) and the number of taxa changing category by 2010
owing to genuine improvement (below diagonal ,) or deterioration
(above diagonal ,) in status
LC, Least Concern; NT,Near Threatened; VU, Vulnerable; EN, Endan-
gered; CR, Critically Endangered; EX, Extinct
1990 category No. of spp. 2010 category
LC NT VU EN CR EX
LC 1063 ,16 7 7 1
NT 56 ,561
VU 60 1 ,11
EN 47 1 1 3 ,1
CR 16 1 ,3
EX 1 ,
Forecasting extinction of threatened taxa Pacific Conservation Biology 163
species loss (United Nations 2015;Department of the Envi-
ronment and Energy 2016). Here, we apply and extend two
global protocols that assess conservation status and extinction
risk, and use expert elicitation, to forecast which, and how many,
Australian birds and mammals are in imminent danger of
extinction.
Typically, extinction probabilities are calculated by formu-
lating mathematical models based on life-history parameters
and population growth rates. For example, population viability
analysis estimates the future risk of extinction (Coulson et al.
2001). However, for most threatened taxa, the extensive and
high-quality data required to ensure reliable outputs from this
approach are not available. For taxa requiring urgent interven-
tion, managers can rarely afford delays until appropriate data
become available (O’Grady et al. 2004b;Martin et al. 2012). An
alternative approach is to use expert judgements obtained via
elicitation processes (e.g. McBride et al. 2012). While expert
judgements tend to overestimate risks, can show considerable
bias, and are sometimes not considered scientifically rigorous
(Morgan 2014), expert predictions can be of comparable quality
to those of modelled predictions, particularly when the data and
outputs relate to a short timeframe such as 20 years (McCarthy
et al. 2004). Compared with population modelling, expert
elicitation is cost-effective, requiring far less time and resources,
and can be conducted with limited ecological data (McCarthy
et al. 2004); the latter aspect is important when dealing with taxa
at imminent risk of extinction, and threatened taxa more
generally, particularly when considering the biases associated
with allocation of conservation resources. Fleming and Bateman
(2016) found that most Australian mammalian research is
focussed on larger, widely distributed taxa, or on managing
the threat caused by introduced eutherian mammals. As a result,
many native species (particularly those generally considered to
be the least charismatic, i.e. rodents and bats) have attracted
little research effort, recognition and funding.
For such taxa where high-quality data are lacking, there is a
temptation to use rubrics based on whatever data are available.
In such cases it may be useful to combine multiple approaches
for forecasting extinction risk, particularly given that experts are
able to add knowledge on some aspects that are not explicitly
considered by risk-ranking protocols (for example dispersal
ability, susceptibility to fire and low reproductive success).
Our study supports this suggestion, evident by the overall poor
correlation between extinction risk determined using IUCN and
NatureServe thresholds compared with expert elicitation. The
NatureServe scores were loosely correlated with expert esti-
mates of extinction risk, but we found no significant association
between the likelihood of species extinction derived from expert
elicitation and whether or not a species was categorised as
Extinction Imminent. Extinction Imminent taxa were, however,
more likely to be accorded higher extinction-risk (i.e. lower
scores) under our assessment against NatureServe criteria; this
concordance is consistent with a previous study that found a
significant correlation between IUCN and NatureServe status
assessments (O’Grady et al. 2004a).
The differences in how data are combined and weighted, and
the thresholds that delineate categories, make consistent assess-
ment among protocols difficult (Regan et al. 2005). For exam-
ple, the Australian breeding population of herald petrel
(Pterodroma heraldica), which nests on just 32 ha of Raine
Island, meets Extinction Imminent status based on IUCN Red
List Criteria B2 (area of occupancy ,10 km
2
and accompanying
subcriteria) (Table S2), yet does not rank highly based on
NatureServe assessments due to the taxon’s large non-breeding
extent of occurrence (,1 500 000 km
2
), the apparent lack of
high-impact threats (leading to allocation of a ‘low’ score), and
the subsequent weight afforded to each of these parameters in
the final calculation of status. The experts ranked the Australian
breeding population of herald petrel as having the 9th highest
probability of extinction of the bird taxa considered (with
likelihood of extinction in the next 20 years of 52%), thus
suggesting that the IUCN Red List assessment is more likely to
reflect the true extinction risk to this species when compared
with the NatureServe assessment.
Geographic range is a key criterion for both IUCN and
NatureServe protocols, with taxa occupying a greater geographic
range generally considered to be more secure than those with
restrictedranges (although this can mask population declines:see
Ceballos et al. 2017). The relationship between distribution and
extinction risk is not always straightforward (Runge et al. 2015).
Nomadic taxa (e.g. regent honeyeaters) often occupy a small
part of their maximum distribution in response to fluctuating
resources. In contrast, sedentary taxa with a restricted range may
be locally common (Williams et al. 2006) and face no immediate
threats, yet be allocated to a higher threat category due to their
limited extent of occurrence or area of occupancy. Furthermore,
the restricted distribution of such taxa may lead to more tractable
and effective management responsesand outcomes. For example,
noxious weeds, introduced predators and fire can be readily
controlled on small islands, an outcome much harder to achieve
on mainland Australia. In this study, several locally common and
stable populations of birds were classified as Critically Imperilled
or Extinction Imminent (e.g. the Lord Howe Island subspecies of
pied currawong, Strepera graculina crissalis; golden whistler,
Pachycephala pectoralis contempt; and silvereye, Zosterops
lateralis tephropleurus). In each of these examples expert elicita-
tion readily justified a lower extinction risk.
The fundamental difference among the protocols lies in the
structure of each method; thus, combining multiple approaches
Table 6. The number of mammals in each IUCN Red List category in
1992, on the basis of current knowledge regarding population para-
meters (see Brooke et al. 2008) and the number of taxa changing
category by 2012 owing to genuine improvement (below diagonal ,)
or deterioration (above diagonal ,) in status
LC, Least Concern; NT,Near Threatened; VU, Vulnerable; EN, Endan-
gered; CR, Critically Endangered; EX, Extinct
1992 category No. of spp. 2012 category
LC NT VU EN CR EX
LC 260 ,13 2 1 2
NT 90 4 ,27 2 1
VU 41 7 ,4
EN 19 1 ,31
CR 12 1 2 ,3
EX 35 ,
164 Pacific Conservation Biology H. M. Geyle et al.
provides anopportunity to overcomeinstances where one method
may be performing better than another. Regan et al. (2005) found
that a rule-based approach (i.e. the IUCN criteria) typically
performed better when data are scarce, as rule-based approaches
have more robust strategies for dealing with unknown data than a
point-scoring system (i.e. NatureServe). Furthermore, parameter
weightings that are implicit in particular protocols may suit some
purposes more than others (Regan et al. 2004). The importance of
knowledge of related taxa and experience of experts is valuable in
such cases, where subjective decisions are made using a combi-
nation of logic, common sense, skill, experience and judgement
(Regan et al. 2004). While the known biases in elicitation
methods can only partially be overcome (Morgan 2014;
Montibeller and Winterfeldt 2015), using multiple experts to
assess the probability of extinction independently, discussing
discrepancies among assessors, and reconciling inconsistencies
and differences in interpretation can produce robust estimates of
extinction probability, particularly whenused in conjunction with
the outputs of different risk-ranking protocols.
A notable feature of our results is the generally higher risk of
extinction predicted for the most at-risk birds relative to the most
at-risk mammals (Table 1). This appears to be a real result rather
than an artefact of largely different sets of individual experts
rating these groups (Table 3). We consider that this may be
because there has been substantial recent success by managers in
stabilising and recovering many of the most imperilled mammal
species through the use of predator exclosures and transloca-
tions (Kanowski et al. 2018;Moseby et al. 2018), thus giving
assessors relative confidence that the most imperilled mammals
can be at least secured and unlikely to become extinct over the
predictive timeframe considered in this study. In contrast,
although with some notable exceptions (e.g. Harley et al.
2018), there has been less success in recent management efforts
for highly imperilled birds. This may be because the most
successful approach for securing threatened mammals (i.e.
predator exclusion) is less relevant for the threats affecting the
most imperilled birds, or alternatively is far less tractable.
We predict that substantial numbers of Australian birds and
mammals are likely to become extinct in the next two decades
unless current management effort and approaches are greatly
enhanced. Our three independent approaches all predict further
extinctions of birds and mammals in the next 20 years, with the
highest predicted number of extinctions derived solely from the
application of Criterion E threshold probabilities of extinction
for Vulnerable, Endangered, and Critically Endangered catego-
ries. The lowest estimates of predicted extinctions follow
trajectories of conservation status changes reported in recent
decades, and reflect the efforts made over that time to prevent
extinctions. More taxa would almost certainly have gone extinct
in the last few decades had there not been concerted efforts to
prevent this (Garnett et al. 2011; Woinarski et al. 2014).
Nevertheless, there have been some notable failures (Martin
et al. 2012; Woinarski et al. 2017), and more can be expected in
the next two decades without substantial increase in the effort
and commitment by governments and society more broadly
(Visconti et al. 2016) and unless urgent attention is directed to
those taxa identified to be at greatest risk. While there is some
overlap in the distributions of the most imperilled birds and
mammals, most taxa will require individual attention. Without
interventions, future Australian bird extinctions are likely to
occur in island endemics, or in taxa that occupy the more
developed parts of southern Australia. In contrast, we can expect
future mammal extinctions to occur in the less developed parts
of central and northern Australia.
The predicted numbers of extinct taxa derived from the expert
elicitation fell between the estimates obtained using Criterion E
and trajectories through time, further suggesting that the expert
elicitation process was a reasonable approach. Experts expect the
rate of extinction to increase over the next 20 years comparedwith
20-year periods in the recent past. This may be attributed to the
fact that all experts were conservation biologists, and thus may
have been subject to the known bias of overestimating extinction
risk (Montibeller and Winterfeldt 2015), but this estimate is lower
than that obtained using Criterion E thresholds and thus should not
be ignored. The average of their estimates is that 10 birds and
seven mammals will become extinct in the next 20 years without
purposeful intervention. This estimate is about five times higher
than the 1–2 taxa per decade that has been occurring historically
for the Australian mammal fauna (Woinarski et al. 2015).
However, an increase in extinction rate is not unreasonable given
the increase in intensity of many threats, augmented by the novel
threat of climate change.
We recognise that each of the approaches used in this study
has inherent limitations. While previous studies have shown that
risk-ranking protocols are useful for forecasting extinction (Keith
et al. 2004), they are prone to some errors, and can sometimes fail
to acknowledge the extent to which taxa are in danger or,
conversely, overestimate extinction risk. Furthermore, the differ-
ences in the way that parameters are weighted and combined can
lead to inconsistent assessments between protocols (Regan et al.
2005). Experts may be subject to biases that vary somewhat
unpredictably depending on their interests in the outcome, but
increasing the number of participants can increase confidence in
predictions. We thus highlight the importance of integrating
multiple approaches in an attempt to overcome some of the
challenges associated with forecasting species extinction in the
face of data and resource constraints, presenting a simple and
transferable framework that may be applied to different taxo-
nomic groups and regions globally.
Regardless of these methodological constraints, our forecast-
ing of high (and increased) numbers of extinctions of Australian
bird and mammal taxa over the next 20 years is consistent across
three different approaches. If such a high rate of extinctions is to
be averted, then a more resolute, strategic and better-resourced
conservation response is required than that now prevailing.
Conflicts of interest
The authors declare no conflicts of interest.
Acknowledgements
We are most grateful to the following experts who contributed to the expert
elicitation process: Andrew Burbidge, Graham Carpenter, Peter Copley,
Alaric Fisher, Chris Johnson, Penny Olsen, Chris Pavey and David Watson.
This paper was also improved based on comments from Tracey Regan. The
preparation of this paper, including data collation and analysis was sup-
ported by the Australian Government’s National Environmental Science
Program (Threatened Species Recovery Hub).
Forecasting extinction of threatened taxa Pacific Conservation Biology 165
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Forecasting extinction of threatened taxa Pacific Conservation Biology 167
... The security of Australia's unique vertebrate biodiversity is of growing concern (Bradshaw 2012, Bilney 2014, Hanna and Cardillo 2014, Woinarski et al. 2015, Geyle et al. 2018. Australia has experienced a native mammal extinction crisis since European colonisation, with terrestrial mammal losses accounting for >10% of species lost over the last 200 years (Woinarski et al. 2015). ...
... Mammalian losses have also impacted various ecosystem services, such as bioturbation by small burrowing mammals (Fleming et al. 2014) and predation by marsupials (Moseby et al. 2021). Australia's bird fauna is also considered to be in decline, with multiple extinctions having occurred since European colonisation (Berryman et al. 2024, Woinarski et al. 2024, and more likely to occur over the next two decades (Campbell et al. 2024, Geyle et al. 2018. Whilst the extent to which Australia's reptile fauna is similarly imperilled is not as well-known due to data deficiency (Geyle et al. 2021, Tingley et al. 2019, there is growing concern that extinction events will increase in frequency over the coming century (Geyle et al. 2021, Tingley et al. 2019. ...
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Freshwater ecosystems are in decline globally. In Australia, threatening processes include invasive species, increasing drought frequency, climate change and changes to land use, all of which have been associated with declining vertebrate diversity, particularly in Australia's arid interior. Efficient monitoring tools are required to effectively monitor and conserve freshwater ecosystems and their associated vertebrate communities. Environmental DNA (eDNA) metabarcoding is one tool that shows promise for monitoring these systems, but knowledge of how eDNA data compares to more established ecological assessment techniques is limited. To address this knowledge gap, we sampled vertebrate eDNA from seven freshwater water bodies of proposed conservation importance in the Australian arid-lands, at three timepoints to measure visitation and compare our findings to camera trapping data at the same locations. Using eDNA we detected 19 species of vertebrates, including native species (such as macropods, wombats and emus) and invasive species (such as feral goats, cats and foxes). In contrast, camera traps detected 32 species, and was much more successful at detecting bird visitation than eDNA. These communities varied both spatially between rock-holes, and temporally, with summer collection periods being distinct from winter-spring. Our results demonstrate the success of eDNA metabarcoding as a tool for monitoring vertebrate visitation to arid-lands freshwater ecosystems that is complementary to more traditional survey methods such as wildlife camera trapping. Finally, we provide conservation recommendations for these vertebrate communities and discuss the efficacy of eDNA for monitoring freshwater resources in arid-lands environments.
... Approximately 20% of all vertebrate species on Earth are threatened with extinction in the wild (Pereira et al., 2010), and it is estimated that one million species are at risk of extinction in the coming decades globally (Toussaint et al., 2021), including 558 mammal species by 2100 (Andermann et al., 2020) and seven mammal species in Australia by 2038 (Geyle et al., 2018). ...
... Since European settlement in 1788, Australia's terrestrial mammal fauna has suffered severe declines and extinctions (Burbidge et al., 2009;Geyle et al., 2018). Leading causes of these declines include the arrival and spread of introduced predators such as feral domestic cats (Felis catus) and the European red fox (Vulpes vulpes), habitat loss, impacts by livestock and feral herbivores and diseases (Woinarski et al., 2015). ...
Article
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Globally, hundreds of mammal species face the threat of extinction in the coming decades, and in many cases, their ecology remains poorly understood. Fundamental ecological knowledge is crucial for effective conservation management of these species, but it is particularly lacking for small, cryptic mammals. The Julia Creek dunnart (Sminthopsis douglasi), a threatened, cryptic carnivorous marsupial that occurs in scattered populations in the central west of Queensland, Australia, was once so poorly studied that it was believed extinct. Sporadic research since its rediscovery in the early 1990s has revealed that S. douglasi is distributed across land at risk from many threats. Fundamental knowledge of S. douglasi population density is urgently required to inform conservation management at key sites, yet the species has historically proven hard to detect. Indeed, the status of the largest known population of S. douglasi, in Bladensburg National Park, is unknown. Here, we conducted a population study on S. douglasi at two sites within Bladensburg National Park via live mark–recapture surveys during 2022 and 2023. From likelihood‐based spatially explicit capture–recapture (SECR) modelling we provide the first estimates of density and population size for S. douglasi. Live trapping resulted in captures of 49 individual S. douglasi (with 83 captures total, including recaptures). We estimated S. douglasi to occur at a density of 0.38 individuals ha⁻¹ (0.25–0.58) at one site and 0.16 individuals ha⁻¹ (0.09–0.27) at another site, with an estimated mean population size in suitable habitat at Bladensburg National Park of 1211 individuals (776–1646). Our S. douglasi density estimates were similar to that reported for other threatened small mammals in Australia. We also found evidence of extreme S. douglasi population fluctuations over time at Bladensburg National Park, which is of concern for its future conservation. Our study has provided the first estimate of density for S. douglasi, a threatened dasyurid species from the Mitchell Grass Downs of central western Queensland, Australia. Our research provides crucial population data to assist the management of this poorly studied species. We demonstrate a method that can be applied to species with low detection probability to ultimately help address the mammal extinction crisis faced by Australia and the rest of the world.
... Knowledge of abundance and range changes of reptiles is more limited than for more readily sampled rodents and birds (Geyle et al. 2018); hence, confirmation of assemblage changes or individual reptile species threatened by cat predation is more challenging cat-selected member of its genus may also have been attributable to it being the most readily identifiable species in cat guts, being the only skink with regularly spaced stripes found through any cross-section or prey fragment, and hence least likely to be pooled into the unidentifiable skink category. The sandswimmer, Eremiascincus richardsonii, also apparently selected by cats, is frequently associated with rabbit warrens (Read et al. 2008), which represent both shelter sites and hunting foci for cats (Moseby and McGregor 2022). ...
Article
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Context Predators typically select prey on the basis of their availability and traits such as body size, speed, camouflage and behaviour that influence ease of capture. Such selectivity, particularly by invasive predators, can disproportionately affect the conservation status of prey. Control of top-order predators can also trigger trophic cascades if subordinate predators have different prey preference. Aims We aimed to document prey selectivity of feral cats by comparing their diet with prey availability over a 27-year study in an Australian desert. Methods Stomach-content and demographic data were recorded from 2293 feral cats, showing 3939 vertebrate prey. These were compared with vertebrate-prey availability estimated from 224,472 pitfall-trap nights, 9791 Elliott-trap nights and opportunistic sampling that accumulated 9247 small mammal and 32,053 herptile records. Potential bird availability was assessed through 2072 quantitative counts amounting to 29,832 bird records. We compared cat selectivity among species, guilds, and physical and behavioural traits of potential prey. Key results Prey guild selectivity from two quantitative subsets of these data indicated that cats preferentially selected medium-sized rodents, snakes and ground-nesting birds over other prey guilds, and also preyed extensively on rabbits, for which selectivity could not be assessed. Species that froze or responded defensively to predators were less favoured than were prey that fled, including fast-evading species. Species inhabiting dunes were hunted more frequently relative to their abundance than were closely related species on stony plains. Conclusions The size, habitat preference and response to predators of potential prey species affect their targeting by feral cats. Implications Our results assist assessment of risk to wildlife species from cat predation and suggest that cat control will trigger changes in the relative abundance of prey species depending on their size, habitat use and behaviour.
... These challenges stem not only from inherent species differences but also from the limited knowledge in relation to wildlife health care, along with the possible demanding requirements associated with rehabilitation. At the same time, many species have already gone extinct, and the rate of extinction is increasing for birds and mammals in Australia [1]. Wildlife injuries are often caused by humans, both directly and indirectly from human causes [2][3][4][5][6]. ...
Article
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Human activities in Australia frequently harm wildlife in their natural environments. Veterinary hospitals play an important role in treating individual animals and safeguarding threatened species. The primary objective of this study was to investigate the demographic and clinical characteristics of wildlife patients admitted to veterinary hospitals in Australia. Data from two wildlife hospitals situated in the southeast region of Australia was used to analyse the characteristics of wildlife patients. Avian species constitute the predominant category of wildlife patients admitted to these hospitals (54% and 60%, respectively). However, a large seasonal variation was observed for all types of animals. Traumatic injuries represent the foremost cause for admission for all types of animals; however, reptiles (62%) and birds (56%) were overrepresented in the category. Car collisions emerging as the most frequently encountered source of trauma. Moreover, the study reveals a notable mortality rate in admitted patients, approximately 50%, with an unfavourable prognosis for patients admitted due to trauma or disease. In conclusion, wildlife rehabilitation clearly presents a number of challenges. We recommend limiting rehabilitation patients, especially orphans and those not needing veterinary care, to focus resources on animals in real need. This could improve care quality, conserve resources, and enhance survival and release rates.
... Two genetically distinct conservation management units of Leadbeater's possum are recognized: highland populations that occupy montane ash forest and subalpine woodland between elevations of 600-1500 meters above sea level, and the genetically-distinct lowland population, now represented by a single wild population containing fewer than forty individuals, which inhabits swamp forest at 110 m above sea level (Hansen & Taylor, 2008;Hansen et al., 2009;Harley, 2023). Both highland and lowland populations are at high risk of extinction (Blair et al., 2018;Geyle et al., 2018;Zilko et al., 2021). The availability of high-quality habitat remains the most critical requirement to ensure the persistence of both populations (Harley, 2023). ...
Article
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Leadbeater's possums (Gymnobelideus leadbeateri) are a critically endangered marsupial found in a restricted area of cold, wet forest in South‐Eastern Australia. The majority of Leadbeater's possums inhabit highland forest, with one outlying lowland population. In 2012, a breeding program was established for the lowland Leadbeater's possums when this genetically distinct population faced imminent extinction. Successful reproduction by highland Leadbeater's possums in the international zoo‐based population between 1970 and 2010 led to the widespread belief that the species bred readily in captivity. Lowland possums have not bred in the 2012–2021 contemporary captive conservation breeding program. This study reviewed the historic captive‐breeding data and found that of the 84% (162/194) that reached reproductive maturity; 37% of males (n = 30) and 39.5% of females (n = 32) bred, and this success was highly skewed towards a subset of highly fecund individuals (14% of females and 15% of males produced 75% and 80% of all offspring). Although lack of reproductive output in the captive lowland animals could be explained if age at mortality was lower than that of highlands possums, comparison of the longevity of highland and lowland animals had no significant difference. Conservation objectives that specify how captive breeding may support in situ recovery of wild populations are integral to the success of captive programs. A lack of reflective analysis of past husbandry records allowed misconceptions of success and approaches implemented in the management of the breeding program, reducing the benefits for the conservation of this high profile threatened species. This case study provides a lesson for the management of conservation breeding programs and illustrates the importance of well‐defined conservation objectives, integration of in situ and ex situ strategies, and the importance of objective, systematic and timely analysis of available evidence to inform management objectives and improve conservation outcomes in real time.
... Despite the above limitations, it is clear that Bathurst Island remains as a nationally significant refuge for critical weight range mammals, including for the brush-tailed rabbitrat, which is included in the list of Australia's 20 mammals most likely to go extinct by 2038 (Geyle et al. 2018). We detected this species at 50% of sites in 2020, making it likely to be Australia's largest remaining stable population. ...
Article
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Context Native mammals continue to suffer widespread and severe declines across northern Australia’s tropical savannas. There is an increasing body of evidence that the primary driver of these declines is predation by feral cats (Felis catus) and that this is exacerbated by high-severity disturbance regimes (frequent high-intensity fires, and grazing and trampling by exotic megaherbivores) that simplify habitat, thereby increasing hunting efficiency. The large islands off the northern Australian coast – where some threats are either reduced or absent – provide a means of testing the conceptual model’s predictions. Aims To compare the trajectory and distribution of native mammal populations on two large, adjacent islands with markedly different disturbance regimes. Methods In 2020 and 2021, we resurveyed 111 historical sites across the two largest of the Tiwi Islands, Bathurst Island (42 sites) and Melville Island (69 sites) that were previously surveyed between 2000 and 2002. The Melville Island sites had also been resurveyed in 2015. We used the same live trapping method used in 2000–2002, supplemented with camera trapping. Key results On Bathurst Island, feral cats are rare, and we found no significant decrease in native mammal trap success or species richness, and the threatened brush-tailed rabbit-rat (Conilurus penicillatus melibius) appears stable. Conversely, cats occurred at relatively high abundance on Melville Island, and there was a 52% decline in trap success, a 47% reduction in species richness, and a 93% decline in trap success for the brush-tailed rabbit-rat over the 20-year period. The highest decreases in native mammal abundance and richness were in areas that were frequently burnt and had higher activity of feral cats. In contrast, in the absence of cats on Bathurst Island, native mammal abundance increased in frequently burnt areas. Conclusions While Bathurst Island remains one of Australia’s most important refuges for native mammals, neighbouring Melville Island is experiencing severe and ongoing mammal decline. We contend that this pattern primarily reflects the high abundance of cats on Melville Island compared to Bathurst Island. Implications Native mammal decline in northern Australian savannas is associated with abundant feral cats, but the relative contribution of disturbances in driving cat abundance remains less clear. An improved understanding of the constraints to feral cat populations in tropical savannas could enhance conservation management.
... A second response is preventing highly imperiled species from further declining and conserving at-risk species before they decline to the point where recovery becomes extremely difficult, improbable, or impossible. A similar process in Australia has been successfully used to identify those listed species for which imminent extinction is most likely and hence should be priorities for urgent conservation resource allocation (Geyle et al., 2018). In the past, the USFWS allocated some of its recovery funds to projects designed specifically to prevent extinction, but the agency has not been funded adequately enough in recent years to resurrect this program. ...
Article
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Currently 1677 species are listed under the U.S. Endangered Species Act (ESA), yet only a small percentage have been delisted due to recovery. In the fall of 2021, the U.S. Fish and Wildlife Service proposed delisting 23 species due to extinction. Tracking changes in species ‘recovery status over time is critical to understanding species’ statuses, informing adaptive management strategies, and assessing the performance of the ESA to prevent further species loss. In this paper, we describe four key obstacles in tracking species recovery status under the ESA. First, ESA 5‐year reviews lack a standardized format and clear documentation. Second, despite having been listed for decades, many species still suffer major data gaps in their biology and threats, rendering it difficult if not impossible to track progress towards recovery. Third, many species have continued declining after listing, yet given the above (1 & 2), understanding potential causes (proximate and/or ultimate) can be difficult. Fourth, many species currently have no path to clear recovery, which represents a potential failing of the process. We conclude with a discussion of potential policy responses that could be addressed to enhance the efficacy of the ESA.
... Furthermore, evaluations of the Act have revealed that it is failing to fulfill its objectives regarding the protection of threatened species (Auditor General, 2020;Samuel, 2020), as it has not prevented recent extinctions (Woinarski et al., 2017). More species are likely to become extinct without urgent recovery actions (Geyle et al., 2018), and decisions are still being made that detrimentally affect species, even those with recovery plans (Reside et al., 2019). ...
Article
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The rate of extinction is increasing with little reversal of negative trends, prompting a need for conservation scientists and practitioners to rethink approaches to aid the recovery of threatened species. Many extinctions could be prevented if impediments to protecting these species were addressed effectively. This article considers how current policies and practices are failing an endangered species and how biodiversity conservation is fraught with barriers such as rhetorical adoption, policy dismantling, circumvention of legislative obligations, and the deliberate disregard of scientific evidence. These issues became evident while researching the endangered Spectacled Flying‐fox (Pteropus conspicillatus Gould 1850), which, despite over a decade of recognized decline, received little attention from authorities who could have acted to stabilize or recover its populations. Recovery plans are often the primary means used by many countries to help threatened species recover and typically fall under government responsibility for implementation. For these plans to be effective, they should be mandatory, well‐funded, and subject to stringent monitoring and reporting requirements. However, the implementation of such plans is often inconsistent, with many not meeting these criteria. The scientific basis for recovery actions is usually well‐researched, although uncertainties around outcomes remain since these actions are experimental and success is not guaranteed. The failure to implement recovery plans can be highly frustrating for conservation scientists and practitioners, often stemming from policy failures. For those involved in conservation research and practice, learning how to identify and overcome policy impediments would help to ensure the successful implementation of recovery plans. Vigilance is required to ensure that recovery teams function effectively, that recovery actions are executed, that decision‐makers are held accountable for endangering species, and that legislation includes merits review provisions to challenge poor decision‐making. Conservation scientists who monitor species of concern are often best placed to track the progress of recovery actions. When they detect insufficient action, they have a responsibility to intervene or to notify the responsible authorities. Ultimately, government policies should prioritize the protection of threatened species over economic and political interests, recognizing that extinction is irreversible and the stakes are high for biodiversity conservation.
Article
Many terrestrial vertebrates require microhabitat shelter structures for survival. Where anthropogenic or environmental disturbances have degraded or depleted shelter, artificial shelters are increasingly used to provide supplementary habitat for various taxa. However, their application to medium‐sized ground‐dwelling mammals (MGMs) remains largely unexplored. We installed rudimentary artificial shelters in a conservation reserve to emulate the vegetative cover used as refuge by three Australian MGMs: the long‐nosed ( Perameles nasuta ) and northern brown bandicoots ( Isoodon macrourus ), and the vulnerable long‐nosed potoroo ( Potorous tridactylus ). We used multi‐method occupancy modeling and behavioral analysis to compare the detections and behaviors of the target species with those of four non‐target species. Our study design included three plot types (treatments)—artificial shelter, baited lure, and disturbance control—enabling unambiguous evaluation of responses to the shelters. The bandicoots showed no difference in detection among treatments, whereas detection of the potoroo was highest at control plots. Detection of non‐target species was generally highest at baited plots. The target species demonstrated a much higher willingness to enter the shelters compared to the non‐target species. The use of the structures appeared to be exploratory, with no evidence that individuals remained in shelters during the day. There was limited evidence that the shelters reduced the target species' perceptions of predation risk and no evidence that predators were attracted to the shelters. The high availability of natural shelter and our small sample size likely influenced these findings. Nevertheless, they lay the foundation for research and refinement into more effective shelter designs.
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Significance The strong focus on species extinctions, a critical aspect of the contemporary pulse of biological extinction, leads to a common misimpression that Earth’s biota is not immediately threatened, just slowly entering an episode of major biodiversity loss. This view overlooks the current trends of population declines and extinctions. Using a sample of 27,600 terrestrial vertebrate species, and a more detailed analysis of 177 mammal species, we show the extremely high degree of population decay in vertebrates, even in common “species of low concern.” Dwindling population sizes and range shrinkages amount to a massive anthropogenic erosion of biodiversity and of the ecosystem services essential to civilization. This “biological annihilation” underlines the seriousness for humanity of Earth’s ongoing sixth mass extinction event.
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The Australian mammalian fauna is marked by high endemism and evolutionary distinctiveness and comprises monotreme, marsupial, and eutherian (‘placental’) native species. It has suffered the highest extinction rate of any mammalian fauna in any global region; surviving species are threatened by competition and predation from a range of introduced mammal species, and receive low levels of conservation‐oriented funding compared with species in many other countries. We investigated research foci on this unique fauna by using species h ‐indices ( SHI ), and identified both taxonomic bias and subject bias in research effort and research impact for 331 Australian terrestrial mammal species. Species broadly fell into categories we labelled as the ‘good’, the ‘bad’, and the ‘ugly’. The majority of studies on monotremes and marsupials (the ‘good’) are directed towards their physiology and anatomy, with a smaller ecological focus. By contrast, introduced eutherians (the ‘bad’) have attracted greater attention in terms of ecological research, with greater emphasis on methods and technique studies for population control. Despite making up 45% of the 331 species studied, native rodents and bats (the ‘ugly’) have attracted disproportionately little study. While research on invasive species is directed towards problem solving, many Australian native species of conservation significance have attracted little research effort, little recognition, and little funding. Current global and national conservation funding largely overlooks non‐charismatic species, and yet these species may arguably be most in need of scientific and management research effort.
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Geographic range size is often conceptualized as a fixed attribute of a species and treated as such for the purposes of quantification of extinction risk; species occupying smaller geographic ranges are assumed to have a higher risk of extinction, all else being equal. However many species are mobile, and their movements range from relatively predictable to-and-fro migrations to complex irregular movements shown by nomadic species. These movements can lead to substantial temporary expansion and contraction of geographic ranges, potentially to levels which may pose an extinction risk. By linking occurrence data with environmental conditions at the time of observations of nomadic species, we modeled the dynamic distributions of 43 arid-zone nomadic bird species across the Australian continent for each month over 11 years and calculated minimum range size and extent of fluctuation in geographic range size from these models. There was enormous variability in predicted spatial distribution over time; 10 species varied in estimated geographic range size by more than an order of magnitude, and 2 species varied by >2 orders of magnitude. During times of poor environmental conditions, several species not currently classified as globally threatened contracted their ranges to very small areas, despite their normally large geographic range size. This finding raises questions about the adequacy of conventional assessments of extinction risk based on static geographic range size (e.g., IUCN Red Listing). Climate change is predicted to affect the pattern of resource fluctuations across much of the southern hemisphere, where nomadism is the dominant form of animal movement, so it is critical we begin to understand the consequences of this for accurate threat assessment of nomadic species. Our approach provides a tool for discovering spatial dynamics in highly mobile species and can be used to unlock valuable information for improved extinction risk assessment and conservation planning. © 2014 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of the Society for Conservation Biology.
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Significance The island continent of Australia harbors much of the world’s most distinctive biodiversity, but this review describes an extent of recent and ongoing loss of its mammal fauna that is exceptionally high and appreciably greater than previously recognized. The causes of loss are dissimilar to those responsible for most biodiversity decline elsewhere in the world.
Book
The Action Plan for Australian Mammals 2012 is the first review to assess the conservation status of all Australian mammals. It complements The Action Plan for Australian Birds 2010 (Garnett et al. 2011, CSIRO Publishing), and although the number of Australian mammal taxa is marginally fewer than for birds, the proportion of endemic, extinct and threatened mammal taxa is far greater. These authoritative reviews represent an important foundation for understanding the current status, fate and future of the nature of Australia. This book considers all species and subspecies of Australian mammals, including those of external territories and territorial seas. For all the mammal taxa (about 300 species and subspecies) considered Extinct, Threatened, Near Threatened or Data Deficient, the size and trend of their population is presented along with information on geographic range and trend, and relevant biological and ecological data. The book also presents the current conservation status of each taxon under Australian legislation, what additional information is needed for managers, and the required management actions. Recovery plans, where they exist, are evaluated. The voluntary participation of more than 200 mammal experts has ensured that the conservation status and information are as accurate as possible, and allowed considerable unpublished data to be included. All accounts include maps based on the latest data from Australian state and territory agencies, from published scientific literature and other sources. The Action Plan concludes that 29 Australian mammal species have become extinct and 63 species are threatened and require urgent conservation action. However, it also shows that, where guided by sound knowledge, management capability and resourcing, and longer-term commitment, there have been some notable conservation success stories, and the conservation status of some species has greatly improved over the past few decades. The Action Plan for Australian Mammals 2012 makes a major contribution to the conservation of a wonderful legacy that is a significant part of Australia’s heritage. For such a legacy to endure, our society must be more aware of and empathetic with our distinctively Australian environment, and particularly its marvellous mammal fauna; relevant information must be readily accessible; environmental policy and law must be based on sound evidence; those with responsibility for environmental management must be aware of what priority actions they should take; the urgency for action (and consequences of inaction) must be clear; and the opportunity for hope and success must be recognised. It is in this spirit that this account is offered. Winner of a 2015 Whitley Awards Certificate of Commendation for Zoological Resource.
Article
Extinctions typically have ecological drivers, such as habitat loss. However, extinction events are also influenced by policy and management settings that may be antithetical to biodiversity conservation, inadequate to prevent extinction, insufficiently resourced, or poorly implemented. Three endemic Australian vertebrate species – the Christmas Island pipistrelle (Pipistrellus murrayi), Bramble Cay melomys (Melomys rubicola), and Christmas Island forest skink (Emoia nativitatis) – became extinct from 2009 to 2014. All 3 extinctions were predictable and probably preventable. We sought to identify the policy, management, research, and other shortcomings that contributed their extinctions or failed to prevent them. Factors that contributed to these extinctions included a lack within national environmental legislation and policy of explicit commitment to the prevention of avoidable extinctions, lack of explicit accountability, inadequate resources for conservation (particularly for species not considered charismatic or not of high taxonomic distinctiveness), inadequate biosecurity, a slow and inadequate process for listing species as threatened, recovery planning that failed to consider the need for emergency response, inability of researchers to identify major threatening factors, lack of public engagement and involvement in conservation decisions, and limited advocacy. From these 3 cases, we recommend environmental policy explicitly seek to prevent extinction of any species and provide a clear chain of accountability and an explicit requirement for public inquiry following any extinction; implementation of a timely and comprehensive process for listing species as threatened and for recovery planning; reservation alone not be assumed sufficient to maintain species; enhancement of biosecurity measures; allocation of sufficient resources to undertake actions necessary to prevent extinction; monitoring be considered a pivotal component of the conservation response; research provide timely identification of factors responsible for decline and of the risk of extinction; effective dissemination of research results; and advocacy by an informed public for the recovery of threatened species; and public involvement in governance of the recovery process. These recommendations should be applicable broadly to reduce the likelihood and incidence of extinctions. This article is protected by copyright. All rights reserved