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Drought-driven change in wildlife distribution and numbers: A case study of koalas in south west Queensland

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Context. Global climate change will lead to increased climate variability, including more frequent drought and heatwaves, in many areas of the world. This will affect the distribution and numbers of wildlife populations. In south-west Queensland, anecdotal reports indicated that a low density but significant koala population had been impacted by drought from 2001–2009, in accord with the predicted effects of climate change. Aims. The study aimed to compare koala distribution and numbers in south-west Queensland in 2009 with pre-drought estimates from 1995–1997. Methods. Community surveys and faecal pellet surveys were used to assess koala distribution. Population densities were estimated using the Faecal Standing Crop Method. From these densities, koala abundance in 10 habitat units was interpolated across the study region. Bootstrapping was used to estimate standard error. Climate data and land clearing were examined as possible explanations for changes in koala distribution and numbers between the two time periods. Key results. Although there was only a minor change in distribution, there was an80%decline in koala numbers across the study region, from a mean population of 59 000 in 1995 to 11 600 in 2009. Most summers between 2002 and 2007 were hotter and drier than average. Vegetation clearance was greatest in the eastern third of the study region, with the majority of clearing being in mixed eucalypt/acacia ecosystems and vegetation on elevated residuals. Conclusions. Changes in the area of occupancy and numbers of koalas allowed us to conclude that drought significantly reduced koala populations and that they contracted to critical riparian habitats. Land clearing in the eastern part of the region may reduce the ability of koalas to move between habitats. Implications. The increase in hotter and drier conditions expected with climate change will adversely affect koala populations in south-west Queensland and may be similar in other wildlife species in arid and semiarid regions. The effect of climate change on trailing edge populations may interact with habitat loss and fragmentation to increase extinction risks. Monitoring wildlife population dynamics at the margins of their geographic ranges will help to manage the impacts of climate change.
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Drought-driven change in wildlife distribution and numbers:
a case study of koalas in south west Queensland
Leonie Seabrook
A,E
, Clive McAlpine
A,B
, Greg Baxter
A,B
, Jonathan Rhodes
A,B
,
Adrian Bradley
C
and Daniel Lunney
D
A
The University of Queensland, Landscape Ecology and Conservation Group, School of Geography,
Planning & Environmental Management, Brisbane, Queensland 4072, Australia.
B
The University of Queensland, The Ecology Centre, Brisbane, Queensland 4072, Australia.
C
The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland 4072, Australia.
D
Ofce of Environment and Heritage NSW, PO Box 1967, Hurstville, New South Wales 2220, Australia and School
of Biological Sciences and Biotechnology, Murdoch University, Murdoch, Western Australia 6150, Australia.
E
Corresponding author. Email: l.seabrook@uq.edu.au
Abstract
Context. Global climate change will lead to increased climate variability, including more frequent drought and heatwaves,
in many areas of the world. This will affect the distribution and numbers of wildlife populations. In south-west Queensland,
anecdotal reports indicated that a low density but signicant koala population had been impacted by drought from
20012009, in accord with the predicted effects of climate change.
Aims. The study aimed to compare koala distribution and numbers in south-west Queensland in 2009 with pre-drought
estimates from 19951997.
Methods. Community surveys and faecal pellet surveys were used to assess koala distribution. Population densities were
estimated using the Faecal Standing Crop Method. From these densities, koala abundance in 10 habitat units was interpolated
across the study region. Bootstrapping was used to estimate standard error. Climate data and land clearing were examined as
possible explanations for changes in koala distribution and numbers between the two time periods.
Key results. Although there was only a minor change in distribution, there was an 80% decline in koala numbers across the
study region, from a mean population of 59 000 in 1995 to 11 600 in 2009. Most summers between 2002 and 2007 were hotter
and drier than average. Vegetation clearance was greatest in the eastern third of the study region, with the majority of clearing
being in mixed eucalypt/acacia ecosystems and vegetation on elevated residuals.
Conclusions. Changes in the area of occupancy and numbers of koalas allowed us to conclude that drought signicantly
reduced koala populations and that they contracted to critical riparian habitats. Land clearing in the eastern part of the region
may reduce the ability of koalas to move between habitats.
Implications. The increase in hotter and drier conditions expected with climate change will adversely affect koala
populations in south-west Queensland and may be similar in other wildlife species in arid and semiarid regions. The effect of
climate change on trailing edge populations may interact with habitat loss and fragmentation to increase extinction risks.
Monitoring wildlife population dynamics at the margins of their geographic ranges will help to manage the impacts of climate
change.
Additional keywords: climate variability, distribution, faecal standing crop method, habitat loss, Phascolarctos cinereus.
Received 1 April 2011, accepted 16 August 2011, published online 11 November 2011
Introduction
The geographic range of a species is broadly governed by the
presence of environmental conditions suitable for that species and
its ability to disperse to new areas (Gaston 2009). However,
within a geographic range, there is a complex internal structure of
distribution, often termed the area of occupancy, which reects
ner scale variations in habitat suitability, local and meta-
population dynamics and legacies of past events (Brown et al.
1996; Gaston and Fuller 2009). This ne scale structure leads
to considerable variations in the density and numbers of
local populations within the area of occupancy (Gaston and
Fuller 2009). Changes in environmental conditions, such as
climate variability and loss of habitat, affect population
dynamics, including dispersal ability, breeding success and
mortality rates, and alter population density either temporarily
or permanently (Fahrig 2003; Hughes 2003; Parmesan 2006).
CSIRO PUBLISHING
Wildlife Research,2011, 38, 509524
http://dx.doi.org/10.1071/WR11064
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These changes can occur cyclically, with populations expanding
or contracting as environmental conditions uctuate, but if
conditions alter too much, there may be more permanent
effects on populations (Thomas et al.2006; Piessens et al.2009).
Climate is one of the major determinants of the distribution
of species (Caughley et al.1988). Climate change is affecting
species distributions, leading to range shifts and changes in
density and numbers within geographic ranges (Parmesan
and Yohe 2003; Wilson et al.2004; Thomas et al.2006).
Species will survive climate change either by adapting or
moving to remain within suitable environmental conditions.
The physiological capacity of a species to adapt is based on
its phenotypic plasticity (the ability of an individual to change
its physiological properties or behaviour in response to
environmental conditions) or microevolutionary changes over
short time spans (Fuller et al.2010). There is evidence that
evolutionary and physiological adaptations are occurring in
several species in response to climate change, although there is
little evidence that these adaptations will occur rapidly enough
to allow occupation of previously unsuitable climatic regions
(Parmesan 2006). During the process of climate-induced range
shifts, trailing edge populations become increasingly fragmented,
while leading edge populations tend to expand along a broad
front (Thomas 2010). Some trailing edge populations will
survive in refugia where local and regional variations in
climate provide favourable conditions (Hampe and Petit 2005).
However, many will be vulnerable to local declines arising from
climate variability and weather extremes, particularly drought
and heatwaves, which may affect a fauna species directly or
change habitat quality and resource availability (Adams 2010;
Albright et al.2010). Monitoring changes in distribution and
numbers at the limit of a speciesrange during conditions that
mimic those predicted under climate change scenarios will help
identify and manage the effects of climate change (Adams 2010).
Habitat loss and fragmentation are also important drivers
of changes in species distribution and numbers (Fahrig 2003;
Wiegand et al.2005). Habitat fragmentation has a range of effects
on forest-dependent mammals, including: decreases in habitat
amount and quality; lower breeding and dispersal success; and
increased risk of mortality due to predation or collisions with
motor vehicles (Andrén 1994; Cogger et al.2003; Fahrig 2003;
McAlpine et al.2006a). Changes in distribution and numbers
may lag behind habitat clearance, resulting in an extinction debt
(Tilman et al.1994; Mouquet et al.2011). The 2006 State
of the Environment report for Australia identied that loss of
native vegetation continues to be one of the greatest threats to
biodiversity (Beeton et al.2006). The combination of climate
change and habitat fragmentation may affect the long-term
viability of many species (Travis 2003).
Koalas (Phascolarctos cinereus) are tree-dwelling marsupial
folivores, endemic to Australia, which feed almost exclusively
on a limited variety of Eucalyptus,Corymbia and Angophora
species. They are found across a broad geographic range in
eastern and south-east Australia, occurring in the states of
Queensland, New South Wales, Victoria and South Australia
(Martin and Handasyde 1999). The distribution of the koala is
limited by climatic factors, the presence of suitable habitat and
the ability to colonise new areas (Martin and Handasyde 1999;
Adams-Hosking et al.2011). Since the European settlement of
Australia, changes in distribution have occurred mainly from
broad-scale habitat loss, but historical events such as pelt hunting,
bushres and disease have also contributed to local and regional
population extinctions over time (Melzer et al.2000; Phillips
2000). In Queensland, a series of state-wide community surveys
indicate that, between 1928 and 1987 when the rst and last state-
wide surveys were conducted, the range of the koala has
progressively contracted to the south and east, with a reduction
of ~27% in their extent of occurrence and 31% in the area of
occupancy (Gordon et al.2006). The survey results also show
changes in the densities of local koala populations.
The rst koala survey in Queensland was carried out in 1928
by the Nature Lovers League to assess the impact of an open
hunting season in 1927 for koala pelts (Gordon et al.2006).
Nearly all replies from local councils and Dingo Boards
contained the same message, namely that koalas had become
scarce or absent in their districts since the open season. In 1967,
the Wildlife Preservation Society of Queensland carried out
a survey through primary schools across Queensland, asking
about current and historic sightings of koalas (Kikkawa and
Walter 1968). Results pointed to a range contraction from the
north and west. Koala deaths were attributed mainly to bushres
and disease, with some mention of past hunting (Kikkawa and
Walter 1968). Campbell et al.(1979) reported on a second
survey carried out in 1977 by the Wildlife Preservation
Society of Queensland. This survey found that although the
distribution did not appear to have changed signicantly since
1967, many districts reported lower numbers of koalas. Patterson
(1996) compared koala distribution from a 19861988 survey
with the 1967 and 1977 surveys. Koala sightings showed a
marked range contraction from the west in the southern half of
Queensland and some contraction to the south (Patterson 1996).
The contraction was attributed primarily to habitat loss,
fragmentation and the associated decline in habitat quality.
Within the koalasbroad range, their area of occupation and
densities are patchy and depend on the presence of favoured tree
species and fertile soils with higher levels of soil nutrients and
soil moisture (Bryan 1997; Sullivan et al.2003a). Population
densities vary from 9 per ha in parts of Victoria to less than 0.001
per ha in inland Queensland (Melzer et al.2000). In Queensland,
densities vary from 0.022 koalas per ha in Springsure (Gordon
et al.1990; Melzer and Lamb 1994), to 0.61.6 per ha in Oakey
(Gordon et al.1990), and 0.4 koala per ha in coastal Redlands
Shire (White and Kunst 1990).
Local koala populations face several threats, including loss
and fragmentation of habitat (Melzer et al.2000; McAlpine et al.
2006a; McAlpine et al.2006b), car strikes and dog attacks (Dique
et al.2003; Lunney et al.2007), and disease, which can lead either
to death or infertility (Gordon et al.1990; Hanger and Loader
2009). Koalas are susceptible to climatic extremes, particularly
heatwaves and droughts, which also affect the quality of nutrients
and moisture available in their diet (Cork and Braithwaite 1996;
Moore and Foley 2000). There is evidence that koalas can modify
their behaviour and physiology to increase water intake if
necessary (Krockenberger 2003; Ellis et al.2010), but climatic
stress on trees can lead to widespread leaf fall and subsequent
crashes in koala populations (Gordon et al.1988; Gordon et al.
1990). For example, Gordon et al.(1990) found, in northern and
western Queensland, that the variability in rainfall and its effect on
510 Wildlife Research L. Seabrook et al.
food sources was probably the most important factor affecting
koala populations, although in the eastern region it was high
infertility and prevalence of cystitis.
In the mid 1990s, Sullivan et al.(2003a,2004) conducted
the rst broad-scale study of koala distribution and abundance
in the Mulgalands bioregion of south-west Queensland.
They estimated that the total population ranged from 44 593
to 77 567. Densities varied across the region from 0.0007 to
2.5 per ha, with the highest densities occurring in riverine and
residual habitats in the eastern Mulgalands. Since that study
was completed, south-west Queensland suffered a severe and
prolonged drought (Hughes 2003; Beeton et al.2006) and
anecdotal evidence suggested that regional koala numbers
had declined.
This study aimed to update our understanding of the
distribution and numbers of koalas in south-west Queensland
and compare the results with those of the study by Sullivan et al.
(2003a,2004) Several years of severe drought provided
conditions similar to those predicted by climate change
scenarios, and an opportunity to assess the likely impacts of
future climate change on koala populations. We identied koala
distribution using a community survey and faecal pellet survey. A
Faecal Standing Crop Method was used to estimate population
densities. From these densities, the numbers of koalas in 10
habitat units were interpolated across the study region. We
examined climate data and the area of vegetation clearing as
possible explanations for changes in koala distribution and
numbers between the two studies.
Materials and methods
Study area
The study area was the South West Natural Resource
Management (SWNRM) region, covering 187 000 km
2
of
southern inland Queensland, Australia (Fig. 1a). Average
annual rainfall ranges between 250 mm in the south-west and
550 mm in the north-east (Fig. 1b). The mean daily maximum and
minimum temperatures for Charleville, the regions largest town,
are 28C and 13.5C respectively. Elevation varies from 580 m
above sea level in the north-east to 100 m above sea level in the
south. Regional drainage patterns are from north to south, with the
Warrego and Paroo Rivers along with the Nebine, Wallam and
Mungallala Creeks forming part of the MurrayDarling Basin
(Sattler and Williams 1999). The Bulloo River in the west of the
region has an internal drainage basin. The dominant landforms are
plains with generally sandy, infertile soils. The major plains
vegetation communities comprise mulga (Acacia aneura) with
poplar box (Eucalyptus populnea) and other eucalypt species co-
dominant in the higher rainfall areas to the east and north (Sattler
and Williams 1999). Separating the plains are low residual ranges
and plateaus, with shallow red earth soils. Residual vegetation has
some eucalypt communities of Thozets box (E. thozetiana)or
grey box (E. microcarpa), but it is dominated by Acacia species
(Table 1). There are signicant oodplains, dominated by poplar
box and coolabah (E. coolabah). Riparian vegetation, comprising
river red gum (E. camaldulensis) and coolabah occurs as narrow
strips along waterways. Land use in the region is predominantly
cattle grazing. Although the SWNRM region does not correspond
exactly with the Mulgalands bioregion used in Sullivans study
(Sullivan et al.2002), the area common to both (the overlap
zone) covers 145 537 km
2
, or 78% of the Mulgalands bioregion
(Fig. 1a).
Koala distribution
We used a combination of two independent survey designs a
community survey and faecal pellet survey to assess the
distribution and numbers of koalas in south-west Queensland.
Community surveys
Community surveys are an effective way to obtain presence or
absence data relatively cheaply and to provide access to private
land (Lunney et al.2009). Community surveys have been used to
obtain locations across wide areas for several easily recognisable
species, including spotted-tailed quolls (Dasyurus maculatus)
(Lunney and Matthews 2001), platypus (Ornithorhynchus
anatinus) (Otley 2001), and bandicoots (Isoodon macrourus)
(FitzGibbon and Jones 2006). National and state-wide
assessments of koala distribution have all used surveys
targeting sections of the community (Kikkawa and Walter
1968; Campbell et al.1979; Phillips 1990; Reed et al.1990;
Patterson 1996; Lunney et al.2009). Surveys are useful at
identifying outlying records where animals are found on a
transient basis (Lunney and Matthews 2001). Koalas are
difcult to spot in the wild, but there is no confusion with
other species, and koalas are popular with people in the local
community, making community surveys a valuable and
repeatable source of information about this iconic species.
A community survey was distributed as unaddressed mail to
680 rural landholders in the SWNRM region. Respondents were
asked whether koalas occurred in their area, when koalas had last
been sighted, and whether they thought koala numbers were
changing. They were provided with a map of the region and asked
to mark their sightings. Questions were also included on other
species including common brushtail possums (Trichosurus
vulpecula) which use similar habitat, dingos or wild dogs
(Canis lupus) and foxes (Vulpes vulpes). Commonly sighted
species have been used in previous surveys to assess where
koalas were either genuinely not present or were not noticed
(Lunney et al.2009). We did not follow up the mail survey to
increase the rate of return. Although the survey was not sent to
people living in towns, there was media coverage of the research
project including contact details of the research team.
Faecal pellet surveys
Identifying species presence can be done through direct
observation, but in many cases indirect signs such as scats or
tracks are used (Wilson and Delahay 2001; Telfer et al.2006).
Surveys that count koalas through direct observation take many
person hours and, although they are used in the more densely
populated east coast koala populations and in smaller study areas
(Gordon et al.1990; Melzer and Lamb 1996; Dique et al.2004),
they are not practical for large areas with low-density populations
(Sullivan et al.2002). Faecal pellet surveys are a well-established
method of determining koala presence, and thus distribution and
habitat selection (Phillips and Callaghan 2000; McAlpine et al.
2006b). Koala faecal pellets are relatively long-lasting and easily
Drought-driven change in distribution and numbers Wildlife Research 511
distinguishable from the pellets of other mammals in the region,
such as goats (Capra hircus) or common brushtail possums, either
by external and internal appearance, or smell. There are
consequences in using indirect signs for detecting species
occupancy of sites, including false absences if signs decay
rapidly or false positives if pellets last many months (Rhodes
et al.2011). The issue of false absences was addressed through
eld-ageing trials of pellets during the survey period. The issue of
false positives could not be determined during one-off surveys,
but in many survey sites there had been a signicant rain and
ooding event at the start of 2009 (ve months before the start of
eld surveys), which would have washed away older pellets. We
acknowledge that the absence of pellets does not necessarily
equate to the absence of koalas. However, both Sullivan (2000)
and Munks et al.(1996) found that direct observation was not
practical for the low-density and patchily distributed koalas of
western Queensland because of the length of time needed to carry
out reliable counts. In addition, Sullivan (2000) found that there
(a)
(b)
Fig. 1. (a) the Mulgalands Bioregion (white), South West Natural Resource Management (SWNRM) region
(grey), and the overlap zone between the SWNRM and Mulgalands (hatched); (b) sample zones (SZ), stratied by
latitude and rainfall zones (RFZ).
512 Wildlife Research L. Seabrook et al.
was only a slight underestimate of koala density when using
faecal pellet surveys rather than direct observation.
The presence of fresh faecal pellets allowed an estimate to
be made of koala densities and numbers using a Faecal Standing
Crop Method (FSCM) (Sullivan et al.2002; Sullivan et al.
2004). FSCM has been used widely for estimating the density
and numbers of species such as deer (Cervus elephus and
Capreolus capreolus), elephant (Loxodonta africana) and
kangaroos (Macropodid spp.) (Johnson and Jarman 1987;
Latham et al.1996; Mayle 1996; Barnes 2001; Bennett et al.
2005). It was adapted for use with koalas in the Mulgalands
by Sullivan et al.(2002). Provided that pellets can be reliably
aged, and the daily production rate is known, the FSCM is a useful
tool for assessing the density of a cryptic and wide spread
species, such as the koala (Sullivan et al.2004).
We followed a similar sampling strategy to Sullivan et al.
(2002,2003a,2003b). Vegetation communities were classied
into 10 habitat units based on landform and dominant vegetation
(Table 1). We used the Regional Ecosystem mapping Version 5
supplied by the Queensland Herbarium (2005). The region was
also stratied into eight sampling zones based on differences
in rainfall on an eastwest gradient, and in latitude on the north
south gradient, following Sullivan et al.(2003b) (Fig. 1b). The
difference in study regions between this work and that of Sullivan
meant that none of Sullivans sample zone 1 overlapped with the
SWNRM region. We did not survey sites in the extreme south-
west of the region because both Sullivan et al.(2004) and the
community survey indicated that no koalas had been present for
many decades. In addition, surveys in the southern part of Sample
Zone 8 (SZ 8) (Fig. 1b), close to the New South Wales border,
were prevented by heatwaves in December 2009 followed by
ooding in JanuaryMarch 2010. Evidence from the community
survey and personal communication with Queensland Parks and
Wildlife rangers in Charleville and Culgoa Flood Plain National
Park indicate that koalas are seldom present in this area, and
the lack of faecal pellet surveys did not, in our view, make a
signicant difference to the population estimates.
Based on the ndings of Gordon et al.(1988) and Munks et al.
(1996), koalas in semiarid regions are more commonly found in
riverine habitat (habitat unit 1), although they do utilise other
habitat for both feeding and resting (Witt and Pahl 1994; Melzer
and Lamb 1996; Ellis et al.2002). In the Mulgalands, Sullivan
et al.(2004) found the highest densities to be in riverine habitats,
although residual landforms also formed important habitat in the
north (Sullivan et al.2003a; Sullivan et al.2003b). Furthermore,
Rhodes et al.(2006) recommended surveying in high-quality
habitat if declines in population are suspected because the higher
densities of individuals living there allow a greater chance of
detecting declines. For these reasons, we sampled more sites in
riverine than in other habitats. Within each habitat unit, between
30 and 50 eld sites, at least 3 km apart, were randomly generated
using Hawths Analysis Tools 3.26 (http://www.spatialecology.
com/htools/) in ArcGIS 9.3 (www.esri.com). In habitat unit 1
(riverine habitat with river red gums present), 100 sites were
generated. The distribution of sites was examined and where
possible two to three sites were chosen in a locality or on a single
property to maximise the efciency of the time taken on eld
surveys. In total, we surveyed 200 sites in the SWNRM region in
south-west Queensland for faecal pellets between May and
November 2009.
The faecal-pellet survey method incorporated elements from
the spot-assessment technique of Phillips and Callaghan (2000)
and from Sullivan et al.(2002). A central tree closest to the GIS-
generated point was agged and it, plus the closest 29 Eucalyptus,
Corymbia or Angophora trees with a DBH (diameter at breast
height over bark) greater than 10 cm, formed a site. Site
characteristics, including tree species, height and DBH were
recorded. The area of the site was calculated by measuring the
radius of the circle of trees forming the site. Following the
experience of Sullivan et al.(2002), searches for faecal pellets
were carried out using two methods. First, under all species except
river red gums, a basal search in a radius of 1 m around the trunk of
the tree was conducted. If koala pellets were detected in the basal
search, then a second extended search using 1 m quadrats was
Table 1. Regional habitat units based on landforms and dominant vegetation species (modied from Sullivan 2000)
Landform Habitat
Unit
Dominant tree species Percentage
of region
A
Riverine
Eucalypt dominated 1 Eucalyptus camaldulensis, E. coolabah, E. populnea 2.5
Floodplain
Eucalypt dominated 2 E. coolabah,E. ochrophloia,E. largiorens,E. populnea,E. melanophloia 5.4
Acacia dominated 3 Acacia cambagei,E. ochrophloia,E. coolabah 3.2
Plains
Eucalypt dominated 4 E. melanophloia,E. populnea 1.4
5E. populnea,E. melanophloia,E. intertexta 5.6
Acacia dominated 6 A. aneura,E. populnea,E. melanophloia,E. intertexta,Corymbia terminalis 24.6
7A. harpophylla,A. aneura,E. cambageana,C. terminalis,C. papuana 4.3
Angophora dominated 8 Angophora melanoxylon,Callitris columellaris,E. melanophloia,E. populnea,C. tesselaris,C. polycarpa 1.6
Residual/High Plains
Eucalypt dominated 9 E. thozetiana,E. cambageana,E. microcarpa 1.3
Acacia dominated 10 A. catenulata,A. stowardii,E. exserta,E. populnea,E. melanophloia,E. thozetiana,C. terminalis,
E. cambageana
10.7
A
Remaining area (39.4%) is either not potential habitat or has been cleared.
Drought-driven change in distribution and numbers Wildlife Research 513
carried out under the canopy in order that a density could be
calculated. During quadrat searches, the area of one-quarter of the
canopy was searched, using up to six quadrats. For example, if
one-quarter of the canopy was estimated at 3 m
2
, then three
quadrats were randomly placed under the canopy. For river red
gums, all pellet searches were done using quadrats. The growth
form of riverine trees, particularly river red gum, was often
multi-stemmed with spreading branches and an asymmetrical
canopy, and there was a greater chance of false absences under
these trees if only a basal search was used (Sullivan et al.2002).
Since riverine habitats support the greatest densities of koalas, it
was important to reduce the possibility of under-estimating
densities in these habitats by falsely recording pellets as absent
under a tree.
Koala density calculations
For the calculation of density, and hence koala abundance, we
used the Faecal Standing Crop Method (Sullivan et al.2002;
Sullivan et al.2004). The FSCM requires three types of data: the
number of pellets present, how many pellets are produced daily,
and the age of the pellets. The number of pellets was estimated by
counting the fresh pellets found in the quadrat search, adjusting
this by a visibility correction factor taken from Sullivan et al.
(2004), which was based on the percentage of ground cover in the
quadrats, and multiplying the adjusted number of pellets by the
canopy area of the tree to give an estimated total pellet count.
Daily pellet production was based on the ndings of Sullivan
et al.(2004), and ranged from 138.2163.3 pellets. The maximum
pellet age was estimated from eld trials and was based
on external appearance and internal odour. Fresh koala pellets
have a characteristic sheen and a greenish colour, which
disappears after 13 days depending on weather conditions.
They also have a strong smell of eucalyptus oils when broken
open. Over a period of days or weeks, depending on weather
conditions, the characteristic eucalyptus smell fades. To assess
the age at which pellets lost their internal odour of eucalyptus oils,
fresh pellets were stored in a domestic refrigerator and three to
four were placed outside at the base of a eucalypt trunk at 3-day
intervals by an employee of SWNRM in Charleville (Sullivan
et al.2002). The age at which the smell faded was used to assign an
age range to the fresh pellets found in eld surveys. This included
a margin for error of 45 days, so a pellet that lost its internal
odour at 10 days might be allocated a minimum age of 7 days and
a maximum age of 12 days.
Koala density was calculated for each tree at a site by applying
the equation:
Density ¼P=da
Where P = estimated total pellet count, d = daily pellet
production and a = maximum pellet age (Sullivan et al.2004).
Site densities were calculated by summing the pellet count under
all trees in the site.
Estimating koala numbers
The number of koalas was calculated for each habitat unit within
each of the eight sampling zones where sites with fresh pellets
were located, using an area weighted average interpolated from
the site densities. To enable a more accurate comparison with the
population estimates of Sullivan et al.(2004), the calculation of
koala numbers was limited to the area of the overlap zone between
the SWNRM region and the Mulgalands Bioregion (Fig. 1a).
Following Sullivan et al.(2004), we used an inverse weighted
distance (IWD) method in the ArcGIS Spatial Analyst tool to
interpolate a density surface from the sites, using a power of 2,
which gives greater weight to nearby sites. If only one site in a
habitat unit and sample zone contained fresh pellets, then the IWD
surface was generated for a distance of 50 km around that site.
We generated a minimum, mean and maximum IDW surface for
the habitat units in each sample zone. The density surfaces were
then reclassied into 20 classes using Jenks Natural Breaks
option to give an attribute table that could be multiplied by the
area of the habitat units (Sullivan et al.2004). Each habitat unit
was converted from polygons into a raster grid, with a cell size of
50 m, based on the percentage cover of the different regional
ecosystems making up the habitat unit. This step gave the
most accurate measure of the area covered by each habitat unit
because one regional ecosystem could contain a mixture of two
to three different habitat units. We then calculated the area of
each reclassied density surface in the habitat unit in which the
sites occurred. Finally, the reclassied IDW surface was then
converted back to density classes and multiplied by the tabulated
area of the habitat unit to estimate the number of koalas for that
habitat unit within a particular sample zone.
To obtain a measure of the accuracy of our parameter
estimates, we used a bootstrap method to estimate a standard
error of koala abundance (Efron and Tibshirani 1986; Sullivan
et al.2004). For each site with fresh pellets, 500 bootstrap
estimates were generated for the total pellet count after
adjusting for visibility. Fifty estimates were selected at random
for each site and the equation to calculate site densities
shown above was applied. Minimum, mean and maximum
IWD surfaces were generated, values reclassied, and areas
tabulated as described above and in Sullivan et al.(2004). In
two habitat units, our estimate of koala numbers was less than 100
koalas, so we did not generate bootstrap estimates because the
difference in total numbers would have been minimal. Once
numbers had been calculated for the 50 bootstrap estimates,
the standard error of the means were calculated together with
the 95% condence interval.
Weather conditions and land clearing
We examined historical climate data for the region and estimated
the area of land clearing to assess whether either or both of these
factors might have contributed to a change in koala populations
between 1995 and 2009. Although we cannot unequivocally link
climatic conditions or land clearing with changes in koala
populations, there is evidence from previous work that allows
us to assign their effects to our ndings (Gordon et al.1988;
Cogger et al.2003; McAlpine et al.2006b; Ellis et al.2010).
Anecdotal evidence from several landholders mentioned
the local disappearance of koalas during the severe drought of
20022007, with 2002 and 2006 being mentioned in particular.
Evidence from previous studies indicates that hot days and low
rainfall can have severe impacts upon koala populations, either
directly by causing physiological stress or indirectly by affecting
the nutrient and water content in eucalypt leaves (Gordon et al.
514 Wildlife Research L. Seabrook et al.
1988; Clifton et al.2007; Ellis et al.2010). We examined climate
data from the Bureau of Meteorology for the major towns across
the region from 1990 to 2009 to see if there had been signicant
changes in climatic conditions. We totalled the amount of summer
rainfall in the six hottest months (1 October to 31 March), and
counted the number of days over 40C over the same period. This
temperature threshold was chosen for several reasons. In their
study of koala metabolism and heat balance, Degabriele and
Dawson (1979) stated that the body temperature, respiratory
rate and evaporative water loss of koalas rose rapidly when
air temperatures were above 30C. Bioclimatic modelling
conducted by Adams-Hosking et al.(2011) identied that
koalas occur in areas with maximum summer temperatures of
under 37.7C. However, Ellis et al.(2010) found that, in central
Queensland, the temperatures in trees used by koalas for shelter
in the summer could be around 2C cooler than ambient air
temperature, thereby moderating the effect on thermoregulation.
We accordingly picked 40C as an air temperature that would
result in signicant physiological stress for koalas.
Another major cause of koala population decline is land
clearing and habitat fragmentation (Cogger et al.2003;
Sullivan et al.2003b; McAlpine et al.2006b). The Statewide
Landcover and Trees Study (SLATS) uses Landsat Thematic
Mapper satellite images to assess changes in woody vegetation
over a given time period (for methods see DNRW 2008). We used
data from SLATS for the years from 19952008 to quantify
woody vegetation clearance in the different habitat units. The data
were in the form of a GIS point le, with each point showing
the rate of clearing per annum for the 25 m
2
Landsat pixel where
woody vegetation had been cleared during the relevant time
period. A spatial join was used to combine data from the
SLATS point les with the habitat unit polygons derived from
remnant regional ecosystem mapping (Queensland Herbarium
2005). Where SLATS points occurred in areas that were classied
as cleared in the remnant regional ecosystem mapping, the pre-
clearing regional ecosystem data were used to assign a habitat
unit to that point. The area cleared in hectares was multiplied
by the percentage of each habitat unit of that point, and the totals
were summed to get the total area of clearing by habitat unit
since 1995.
Results
Distribution of koalas from community surveys
and eld surveys
A total of 63 community surveys were returned (9.2%). The
distribution of records of koala occurrence was evenly spread
across the study area (Fig. 2a) and broadly agreed with the results
of the faecal pellet surveys. Due to the low number of returns, the
community survey was used only to map distribution according to
the reported sightings, but not analysed further.
The distribution of koalas shown by the eld survey was
similar to the community survey (Fig. 2b). The most densely
occupied area was between Charleville and Tambo, where all the
sites had some signs of koala presence. There was a patchier
occurrence elsewhere in the north and eastern sections of the
region. Koala pellets were found at only one site in the south-west
of the region (Fig. 2b).
Nearly half of the eld sites in habitat units 1, 2 and 9 had faecal
pellets present, with fresh pellets present at 70% of these sites
(Table 2). No pellets were found in habitat units 3, 4, and 8,
although the number of sites surveyed in these habitat units were
limited due to difculties accessing them in the eld or because
there were not enough trees of the genera Eucalyptus,Corymbia
or Angophora present at the site. The difference between the
number of sites with fresh pellets in the SWNRM region (48) and
those in the overlap region (27) (Table 2) was due to the densely
occupied sites between Charleville and Tambo on the Ward River
falling outside the overlap zone with the Mulgalands Bioregion
(Fig. 2b).
Estimated koala density and numbers
In 2009, koala density estimates varied from 0.002 to 1.85 koalas
per ha. Average densities in 2009 in Rainfall Zone 3 in the north-
eastern part of the region were 1.3 0.03 and in Rainfall Zone 2
were 0.04 0.02 (see Fig. 1bfor Rainfall Zone locations).
Sullivan et al.(2004) found that koala densities varied across
the region from 0.00072.5 per ha with average densities in
Rainfall Zone 3 being 1.8 0.06 and in Rainfall Zone 2 being
0.02 0.01
The bootstrap estimates of total koala numbers in the overlap
zone ranged from 9843 to 13 430 (95% condence interval),
with the mean of 11 634 (904 standard error) (Table 3). The
overall decline compared with the numbers estimated by Sullivan
et al.(2004) in 1995 was 80% (Table 3).
Weather conditions and area of land cleared
Weather records collected by the Bureau of Meteorology
show that, between 1989 and 2009, the average number
of days over 40C over the summer months (OctoberMarch)
was only slightly higher than the long-term average since 1950.
However, between 2002 and 2007, Charleville, Bollon and
Tambo had more than double the average number of hot days,
with a peak across most of the region in 2006 (Fig. 3). There was
also a much lower-than-average annual rainfall, particularly in
20022003 (Fig. 3). The combination of an above-average
number of hot days and low summer rainfall was most evident
in Charleville and Bollon between 2002 and 2006 (see Fig. 1afor
locations). In Quilpie and Cunnamulla, the climate is both hotter
and drier than further east (Fig. 3). These conditions are probably
close to the climatic limits of the koala, and would contribute to
determining the western boundary of its range. Koalas were
uncommon near these towns, although there was one site with
old faecal pellets south-west of Quilpie (Fig. 2b).
The greatest amount of clearing had occurred in the eastern
third of the region, with a trend of increasing clearing towards the
south. Across all habitat units, 11.72% of clearing was in SZ 3,
18.17% in SZ 6 and 22.6% in SZ 9 (Table 4and see Fig. 1for zone
locations). The habitat units with the greatest percentage of
clearing were HU 5 (20.2%) (poplar box and silver-leaved
ironbark: E. melanophloia) and HU 9 (16%) (Thozets box
and Dawson gum: E. cambageana). Sullivan et al.(2003a)
found Thozets box and poplar box formed an important part
of the diet of koalas in south-west Queensland, and these levels of
clearing may have contributed to the decline in koala population
Drought-driven change in distribution and numbers Wildlife Research 515
size between 1995 and 2009 (Table 3) through loss of habitat and
by limiting the ability of koalas to disperse safely away from creek
lines.
Discussion
The effect of climate change on the trailing edge of species
distribution is predicted to lead to increasingly fragmented
(a)
(b)
Fig. 2. Distribution of koalas across the South West Natural Resource Management (SWNRM) region in 2009 from (a)
the community survey; and (b) the faecal pellet survey.
516 Wildlife Research L. Seabrook et al.
populations, some of which may survive in small refugia due to
local and regional variations in climate but many of which will
face local extinction from extreme events (Parmesan 2006;
Thomas et al.2006; Gaston and Fuller 2009). Trailing-edge
populations have been shown to be critical to the long-term
survival of species because they may contain individuals that
can adapt to changing climatic conditions (Wilson et al.
2004; Hampe and Petit 2005; Thomas et al.2006). This
project assessed the distribution and numbers of koalas in
south-west Queensland following a severe drought from 2001
to 2007 and compared the results with a previous study carried
out in the mid 1990s. Koalas in this region are at the western
limits of their geographic range, and form a trailing-edge
population. There was a marked decline in the area of
occupancy and in population size since the mid 1990s,
although their extent of occurrence, e.g. the geographic range,
contracted only slightly. Their area of occupancy contracted
mainly to the most optimal habitat along creeks and rivers,
with little use of habitat away from water courses. The decline
coincided with a period of 45 years where there was a
combination of low summer rainfall and an above average
number of very hot days, which mimic the predicted direction
of climate change in the region and are known to affect koala
survival (Gordon et al.1988; Gordon et al.1990; Ellis et al.2010).
The changes in distribution (both the extent of occurrence and
the area of occupancy) reect the koalasresponse to alterations
in their environment and ability to disperse in south-west
Queensland.
Extreme events, such as drought and increased temperature,
can affect mortality rates, breeding success and dispersal of
Table 2. Number of sites with koala faecal pellets surveyed within
each habitat unit in the South West Natural Resource Management
(SWNRM) region and the overlap zone with the Mulgalands bioregion
(the overlap zone)
Habitat
unit
Number
of sites
Number of
sites with
any pellets
Number of
sites in SWNRM
with fresh pellets
Number of sites
in overlap zone
with fresh pellets
17336 24 20
25023 17 5
340 0 0
410 0 0
5154 3 0
6365 2 1
700 0 0
820 0 0
973 2 1
10 12 1 0 0
Total 200 72 48 27
Table 3. Comparison of bootstrap estimates of koala numbers by rainfall zone, sample zone and habitat unit
Minimum and maximum gures are the mean 95% condence interval
Abundance estimate 1995
A
Abundance estimate 2009
Minimum Mean Maximum Minimum Mean Maximum
Rainfall zone Rainfall zone
1zr
B
zr zr 1zr zr zr
214 530 18 490 22 930 22308 3152 3999
330 060 41 050 52 700 37535 8482 9431
Sample zone Sample zone
1zr zr zr 1Not sampled Not sampled Not sampled
210 849 13 822 17 234 2620 836 1052
34990 6823 8422 32597 3116 3635
4zr zr zr 4zr zr zr
53648 4633 5650 5442 896 1351
623 997 32 258 41 257 64511 5030 5303
7zr zr zr 7zr zr zr
833 42 48 81212 1377 1541
91076 1977 3026 9438 459 481
Habitat Unit Habitat Unit
120 312 26 980 34 260 16391 7459 8528
2597 682 850 22692 3230 3773
3714 819 1080 3zr zr zr
4zr zr zr 4zr zr zr
5635 1295 2269 5zr zr zr
6zr zr zr 6280 383 486
7353 456 543 7zr zr zr
861 99 130 8zr zr zr
96949 9998 13 447 9481 562 644
10 15 298 18 769 22 358 10 zr zr zr
Total 44 953 59 555 77 567 9843 11 634 13 430
A
Taken from Sullivan et al.(2004).
B
zr = no fresh pellets were found so koala numbers could not be estimated.
Drought-driven change in distribution and numbers Wildlife Research 517
50
40
30
20
10
0
50
40
30
20
10
0
50
40
30
20
10
0
50
40
30
20
10
0
50
Summer days >40°C Summer days >40°C Summer days >40°C Summer days >40°C Summer days >40°C
Summer rain (mm)Summer rain (mm)
Summer rain (mm)
Summer rain (mm)Summer rain (mm)
700
600
500
400
300
200
100
0
700
600
500
400
300
200
100
0
700
600
500
400
300
200
100
0
700
600
500
400
300
200
100
0
800
600
400
200
0
40
30
20
10
0
89...
90...
91...
92...
93...
94...
95...
96...
97...
98...
99...
00...
01...
02...
03...
04...
05...
06...
07...
08...
Fig. 3. The number of days over 40C (black, left axis) and total rainfall (grey, right axis) over the hottest months
(OctoberMarch) in major towns in south-west Queensland between 1990 and 2009 (see Fig. 1for town locations).
The black brackets mark the period of interest in summer weather conditions. The black dotted line is the average
number of days over 40C since 1950, and the grey dashed line is the average summer rainfall since 1950.
518 Wildlife Research L. Seabrook et al.
wildlife. For example, Adams (2010) found that higher
temperatures, and particularly severe drought, signicantly
reduced reproductive output in bats in western North America.
In Australia, one day over 42C killed thousands of ying foxes
(Pteropus spp), with greater mortality among young and adult
females (Welbergen et al.2008). Bolger et al.(2005) found that
drought years resulted in low food availability for insectivorous
passerine birds in California, leading to very low breeding success
rates. Albright et al.(2010) modelled the impacts of drought on
North American birds and found that abundance, richness and
species composition of avian communities were affected in
different ways and at different magnitudes, with the greatest
negative impacts on species in the semiarid Great Plains. They
also suggested that there could be stronger effects for prolonged
or more frequent droughts (Albright et al.2010). Our study
supports these effects. We found the most likely causes of the
decline in numbers and area of occupancy of the koala in
south-west Queensland were climate extremes, particularly the
combination of low summer rainfall and very hot days, i.e.
heatwaves. Reports from landholders, based on the community
survey and subsequent discussions, allowed the view to be formed
that local disappearances of koalas occurred around 20022003
across most of the region, and around 2006 in the north-east of the
region. Although we cannot unequivocally state that the drought
caused the koala population declines, increased mortality due to
low rainfall and/or heatwaves has been found in other koala
research. In the very hot, dry summer of 19791980, 63% of
koalas died along on the Mungallala Creek in the eastern part
of the Mulgalands (Gordon et al.1988). Over this period, the
nearby town of Bollon recorded 31 days over 40C and summer
rainfall of 154 mm (see Fig. 3for comparison with recent weather
records). A resurvey of sites in Springsure, central Queensland, in
2009 found that, since 1995, koalas had disappeared at two out of
four sites, and densities were much decreased in the other two
(Ellis et al.2010). Similarly, Lunney et al. (in press) estimated that
~25% of koala population around Gunnedah in north-west New
South Wales perished in NovemberDecember 2009 during the
heatwaves in a long-running drought. At a larger scale, Gordon
et al.(1990) found that in northern and western Queensland
variability in rainfall, and its effect on food sources, was probably
the most important factor affecting koala populations. Adams-
Hosking et al.(2011) modelled a signicant eastward contraction
in the koalas distribution in Queensland and New South Wales
under projected climate change scenarios. They concluded that in
arid and semiarid regions, such as south-west Queensland,
climate change is likely to compound the impacts of habitat
loss, resulting in signicant contractions in the distribution of
this species. Our study provides empirical evidence supporting
this prediction.
Understanding the impacts of climate change on species
will be of great importance in biodiversity conservation over
the coming decades (Parmesan 2006). The ability of species to
adapt to climate change will depend on several factors, including:
(i) dispersal ability; (ii) phenotypic plasticity; (iii) evolutionary
adaptability; and (iv) physiological tolerance (Williams et al.
2008). Range shifts in response to higher temperatures have
been seen in several species, generally either polewards or to
higher elevations (Tidemann 1999; Hughes 2003; Thomas et al.
2006; Thuiller et al.2008; Gibson et al.2009; Thomas 2010).
Some species are showing signs of physiological adaptation
to climate change, either through phenotypic plasticity or
behavioural change (Parmesan 2006; Fuller et al.2010). For
example, migratory species are changing their departure and
arrival times (Green and Pickering 2002; Gordo et al.2005)
and breeding seasons are commencing earlier (Crick et al.1997).
Thermal tolerance has been identied as one of the key
limitations for physiological adaptation to climate change
(Fuller et al.2010). There is evidence that koalas can adapt
their behaviour and physiology to deal with heat to some extent
(Krockenberger 2003; Ellis et al.2010). However, Clifton et al.
(2007) found that in coastal communities, the physiological
tolerance of koalas seemed be affected by hot night-time
temperatures and humidity, which reduced evaporative heat
loss. Bioclimatic modelling carried out by Adams-Hosking
et al.(2011) indicates that the maximum summer temperatures
that are physiologically acceptable for koalas are ~37.7C. This is
supported by Degabriele and Dawson (1979) who found that
evaporative water loss in koalas more than doubled and the
respiratory rate rose from a mean of 25.9 to 231.3 breaths per
minute when air temperatures increased from 30Cto40
C. If
these temperatures are exceeded on a regular basis, physiological
stress will lead to increased koala mortality. Thus, this study raises
signicant implications for the effect of climate change for koalas
in south-west Queensland, and for other wildlife in the region. In
Table 4. Percentage of land cleared as a proportion of the pre-clearing extent in each sample zone (SZ) and each habitat unit
(HU) between 1995 and 2008
The column and row of totals show the percentage of all clearing within the SZ or HU (Source: SLATS)
HU1 HU2 HU3 HU4 HU5 HU6 HU7 HU8 HU9 HU10 Clearing
by SZ
all zones
SZ2 0.00 0.11 0.63 0.00 0.00 2.59 2.62 0.00 0.00 0.58 2.81
SZ3 3.12 1.20 22.28 9.98 10.15 17.93 17.33 0.00 11.76 6.07 11.72
SZ5 0.42 5.71 4.27 0.00 4.91 3.86 8.80 0.00 10.89 2.00 3.47
SZ6 7.19 8.02 13.84 0.04 21.50 23.00 5.45 14.43 18.61 10.71 18.17
SZ8 0.47 1.66 2.17 0.00 12.54 6.66 2.97 4.19 35.20 4.09 4.23
SZ9 15.40 12.64 13.18 4.30 24.66 24.24 13.30 22.59 0.00 0.00 22.60
Clearing by HU all zones 3.4 2.9 5.3 2.5 20.2 13.1 5.8 10.5 16.0 4.1
Drought-driven change in distribution and numbers Wildlife Research 519
Australia, the mean annual temperature has increased by 0.9C
since 1901 (Hennessy et al.2008). Since 1950, Queensland has
the greatest rise in mean annual temperature in Australia (1.2C)
and the greatest decline in total annual rainfall (107 mm). By
2040, exceptionally hot years are predicted to occur every
2 years, affecting 60% of the state (Hennessy et al.2008).
Climate change predictions from the Queensland Government
report that, in Charleville, the number of days over 35C will
nearly double to 130 days per annum by 2070, and while there is
not a consensus on whether average annual rainfall will increase
or decrease, the majority of predictions point to a decrease in
rainfall, with increased variability and the likelihood of more
frequent droughts (DERM 2009). The drought and exceptionally
hot years that occurred between 2001 and 2007 mimicked these
climate change predictions.
Climate change will also affect terrestrial vegetation and
thus habitat quality and resource availability for many species
(Hughes 2003). Changes in foliar chemistry due to elevated CO
2
are predicted to signicantly affect arboreal folivores, including
koalas (Kanowski 2001; Hughes 2003; Moore et al.2004;
Lunney et al. in press). For example, DeGabriel et al.(2009)
found that the reproductive success of common brushtail
possums was reduced when leaves contained a high tannin
content, which lowers the nitrogen available to folivores.
Lawler et al.(1997) found higher CO
2
levels affected the
carbon : nitrogen ratio in forest red gum (Eucalyptus
tereticornis), which in turn increased levels of plant secondary
metabolites (PSMs). Herbivorous beetle larvae feeding on these
leaves showed increased mortality rates and reduced body
size. Higher CO
2
levels also decreased the amount of nitrogen
allocated to leaf protein and increased that allocated to the
production of toxic plant defences, reducing the nutritional
quality of leaves (Gleadow et al.1998). Both studies found the
effects enhanced when nitrogen availability was limited. In
addition to changes in leaf chemistry, if drought conditions
are severe enough, particularly when combined with extremely
hot days, leaf fall and tree die back can lead to population crashes,
such as those seen at Mungallala Creek and Springsure (Gordon
et al.1988; Ellis et al.2010).
Habitat loss and fragmentation are also important drivers
of changes in species distribution and numbers (Fahrig 2003;
Wiegand et al.2005). Habitat loss and fragmentation were
identied as one of the main causes of extinction of woodland
birds in Australia, related to poor dispersal to isolated patches,
increasing nest predation, changes in habitat quality and
resource availability, and increasing interspecic completion
from aggressive bird species (Ford 2011). Brown et al.(2008)
found that reptiles in Victoria, Australia, had declined
signicantly with loss of habitat and changes in woodland
structure, with declines in species richness even in remaining
large patches. For howler monkeys in the Central and South
American Neotropics, loss of habitat was more important than
fragmentation on distribution and abundance, probably because
howler monkeys are highly mobile and resistant to initial
habitat disturbance (Arroyo-Rodriguez and Dias 2010). Loss
of habitat has been identied as one of the most signicant
threats to koalas in New South Wales (Reed and Lunney
1990) and south-east Queensland (Seabrook et al.2003;
McAlpine et al.2006b). Although in Queensland, broad-scale
clearing of remnant vegetation has been regulated since 2006,
some clearing is still permitted for drought fodder, infrastructure
and urban development, and non-remnant vegetation continues
to be cleared (McGrath 2004;/2005). In a study of koalas in
south-east Queensland, the total area of forest, larger forest
patches and smaller distances between patches were important
predictors of koala presence (McAlpine et al.2006b). Land
clearance and habitat fragmentation are likely to have affected
koala distribution and numbers, particularly in Sample Zone (SZ)
6 and 9 in the east of the region (Table 3and see Fig. 1for
locations). Between 1995 and 2008, SZ 9 lost 28% of high quality
river red gum and coolabah habitats to clearing, and nearly
25% of poplar box habitat, while SZ 6 lost 15% of riverine
and coolabah vegetation and 21% of poplar box habitat. The
contraction of koalas across the region to riverine habitats
suggests that animals had vacated less-favourable poplar box
habitats over the drought, but the clearing of key riverine habitat
would almost certainly have affected the number of koalas.
Management of trailing-edge populations during climate
change will be challenging because, even if greenhouse gases
are signicantly reduced, there are likely to be lag effects on
species. There are already delays between habitat clearance and
loss of species, leading to an extinction debt (Tilman et al.1994;
Mouquet et al.2011), and the extinction debt may contribute to
the nding of Anderson et al.(2009) that changes in trailing-edge
populations happen more slowly than those in leading-edge
expansion. The interaction of habitat loss, fragmentation, and
climate extremes will increase pressure on some populations and
species, particularly in isolated trailing-edge populations where
dispersal ability is limited (Travis 2003; Thomas et al.2004). For
instance, Piessens et al.(2009) found that for populations of
Cupido minimus, a specialist herbivore buttery, extinction
probabilities were signicantly higher for small populations in
fragmented habitat during and after the hot summer in 2003 in
Europe. Williams et al.(2008) suggested that the rst step towards
conserving species in a changing climate is to understand the
relative vulnerability of the species and implement known
conservation techniques in potential refuge areas, including
increasing habitat amount and connectivity. However, we also
need to adopt a dynamic and proactive approach to conservation
to deal with spatial changes in species distribution and ecosystem
components (Williams et al.2008). For many trailing-edge
populations, variations in local microclimates may make the
difference between survival and extinction (Fuller et al.2010).
For example, research on European mussels indicates that
populations with low genetic diversity at the southern or
trailing edge of their range are less adapted to heat stress than
central populations (Pearson et al.2009). However, cold
upwelling explained the presence of relict populations of
barnacles in Europe, indicating that microclimatic inuences
can override broad climate change (Wethey and Woodin
2008). Local microclimatic variations may explain occasional
koala sightings in the Grey Ranges in the south-west of the study
area. Here, the local climate and habitat could be sufciently
different from those along the Bulloo River to allow koalas to
persist. Further surveys would be required in this region to offer
a more denitive explanation.
For koalas in south-west Queensland, the identication of
potential refugia through continued monitoring of population
520 Wildlife Research L. Seabrook et al.
change at the edges of the range will allow us to assess which local
populations are resilient to climate change, and therefore where to
concentrate management actions. In 2009, koalas were found
almost exclusively along creek lines where river red gum and
coolabah were present. There was little evidence of koalas at high
densities in residual landscapes, as found by Sullivan et al.(2004)
in the mid 1990s. This demonstrates that riverine habitats are
critical refugia in the region and their role as core habitat will
become more important as climate change leads to a greater
incidence of hot, dry conditions. This nding agrees with other
research in semiarid western Queensland. Along Mungallala
Creek in the south-east of the SWNRM region, Gordon et al.
(1988) found that koalas survived in riparian vegetation and
died in more marginal habitats away from the creek during a
very hot dry summer. In the Desert Uplands bioregion north of
our study area, Munks et al.(1996) found that the greatest
densities of koalas were along creeks, with strong relationships
with proximity to water and leaf moisture. However, in
Springsure, in central Queensland, the areas worst affected by
drought were along creeks, where forest red gums and carbeen
(Corymbia tessellaris) suffered extensive tree death, while
koalas survived off creeks (Ellis et al.2010). Ellis et al.
(2010) reported similar results at Blair Athol in central
Queensland, where plains vegetation comprising popular box
and narrow-leaved ironbark (E. crebra) have continued to support
koala populations and are the preferred food trees at the site. It
appears that the key refuge habitats where koalas survive in
times of environmental stress vary among locations, and this is
provisionally linked to both moisture availability and soil
nutrients, which in turn affect the balance between leaf
nutrients and leaf toxins (Creagh 1992; Cork and Braithwaite
1996; Bryan 1997; Moore and Foley 2000; Moore et al.2004).
Although there will continue to be years when numbers will
expand and koalas will disperse into less optimal habitat, in south-
west Queensland the maintenance of core habitat along creek
lines with permanent waterholes will become increasingly critical
in the coming decades.
Approach and limitations
There are some differences between this study and that by
Sullivan that affect direct comparison in some sample zones
and in habitat units 9 and 10. First, the region surveyed by
Sullivan and the region of this study are not identical and
although estimates of koala abundance in 2009 are limited to
the overlap zone, Sullivans koala estimates are for a larger area.
The area covered by SZ 2 in 2009 is smaller than in 1995, and
did not include the region around Idalia National Park, where
Sullivan et al.(2004) found koalas in HU9 and HU10 vegetation.
We found no fresh pellets in HU9 or HU10 in SZ 2, but we
sampled a much smaller area of these two habitat units and this
reduced our chances of nding fresh pellets. Overall, we had
proportionally fewer sites in HU9 and 10 than in Sullivan et al.
(2004). This may affect the comparison between the two studies,
as their population estimates were high for these two habitats
(Table 3). We found no fresh pellets in HU10, so no density
estimates could be calculated, and we estimated low densities
from fresh pellets in HU9. Our conclusion is that the koala
population in these habitats markedly decreased during the
drought, despite the difference in sampling effort. The area
covered by SZ 6 and SZ 9 was slightly larger in Sullivans
study (Fig. 1). Fresh pellets were found by Sullivan at two
sites on one property in SZ 6 that was not in the overlap zone.
The sites with fresh pellets in SZ 8 were close to the boundary with
SZ 9 and the different estimates in these two zones may reect a
slightly different boundary position between the two survey
periods, rather than a signicant change in numbers. Finally,
there appears to be a discrepancy in koala abundances in HU1
and HU2 between the 1995 and 2009 gures, with our HU2
showing higher numbers. This may reect a difference in the
habitat unit assigned to each site. Notwithstanding these minor
differences in the two survey methods, the eld data and analysis
reect a real decline in koala numbers since 1995 in south-west
Queensland. Our results show that climate change and land
clearing are key concerns for the long-term survival of koalas
in this region.
Acknowledgements
This project is funded by the Australian Research Council, the Australian
Koala Foundation and South West NRM through LP0882090. Data on land
clearing were supplied by the Remote Sensing Centre of the Queensland
Department of Environment and Resource Management. Field surveys were
carried out by Rebecca Condon, Virginia Seymour and Nicole Davies, with
help from Leonie Seabrook and several volunteers. We would like to thank
the staff of South West NRM and all landholders who participated in the
community survey and who allow us to carry out faecal pellet surveys on
their land. Their knowledge, help and hospitality were much appreciated.
The approved protocol for this project was obtained from the Animal
Ethics Committee at The University of Queensland (GPA/603/08/ARC)
and the Scientic Purposes Permit WISP05343008 was obtained from the
Environmental Protection Agency (now the Department of Environment and
Resource Management).
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Spatial patterns in species distributions reveal biodiversity change. Nature
432, 393396. doi:10.1038/nature03031
Witt, G. B., and Pahl, L. (1994) Mulgaland communities of south-west
Queensland as habitat for koalas. In Ecological Research and
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pp. 9195. (Lawes, Qld: Dept of Management Studies, The University
of Queensland.)
524 Wildlife Research L. Seabrook et al.
www.publish.csiro.au/journals/wr
... Koala populations occupying the hot semi-arid regions of southwest Queensland are on the front line of koala range shifts due to climate change (Adams-Hosking et al. 2011). Land clearing and climate change are directly affecting the habitats and dynamics of these western populations (Sullivan et al. 2004, Seabrook et al. 2011. Bioclimatic models predict that western koala habitats may become uninhabitable in the next 50 years under the more extreme climate change scenarios (Adams-Hosking et al. 2011). ...
... The koala populations of southwest Queensland form a significant regional population (Sullivan et al. 2004, Seabrook et al. 2011. The nutritional quality of their habitat has at times been degraded by severe droughts and heatwaves which are increasing in frequency and severity with climate change (NRMMC 2009). ...
... In 1980, a heatwave and drought in southwest Queensland caused food tree defoliation/dieback and a dramatic decline in koala populations from malnutrition and dehydration (Gordon et al. 1988). More recent research found that drought and heat-waves resulted in a decline in the koala population in southwest Queensland of 80% from 1995 to 2009 (Seabrook et al. 2011). There were also significant relationships between spatial and temporal patterns of tree use, distribution and habitat use by koalas and rainfall variability and surface water availability (Davies et al. 2013a, Smith et al. 2013b, Smith et al. 2013c). ...
Thesis
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Protecting high quality habitat is an important wildlife conservation action. Spatial and temporal variation in habitat quality in heterogeneous landscapes influences habitat use and population persistence. Populations living at the margins of species’ geographic ranges are particularly sensitive to fluctuations in habitat quality, especially if species occupy narrow ecological niches. For arboreal folivores, foliar chemical composition is a key factor influencing habitat quality. To understand the spatial and temporal dynamics of foliar chemistry and hence the habitat quality for an arboreal folivore species, I applied theories and methods from chemical ecology, nutritional ecology and landscape ecology to understand foliar chemical/folivore interactions in a seasonally changing environment. I used populations of koalas (Phascolarctos cinereus) in two semi-arid regions of Qeensland, Australia, as a case study. Koalas are specialist folivores with complex feeding behaviour from Eucalyptus species. My aim was to identify the influence of foliar chemicals (moisture content, digestible nitrogen (DigN) and a toxin formylated hloroglucinol compounds (FPC) concentrations) and associated environmental factors on koala habitat use and diet across three rainfall seasons. I addressed three specific questions: 1) How do tree characteristics and environmental factors influence on spatial and temporal variation in leaf chemistry composition of koala food tree species? 2) What are relative influences of leaf chemistry, tree characteristics and environmental factors on koala habitat use and diet? and 3) Can we use the WorldView-3 satellite imagery to accurately map foliar nutrition at high resolution in koala habitats in semi-arid regions? The research was conducted in the Mulga Lands and Brigalow Belt South bioregions of southwest Queensland. Eucalyptus leaf chemicals, koala habitat use and diet were examined. A hierarchical sampling design was applied to select 34 sites (6-10 trees in each) from ten landscapes (each 10×10 km) across the 62,500 km2 area. Leaf samples were collected from 261 trees and repeated over three seasons with contrasting rainfall. Leaf moisture content, DigN and FPC concentrations were analysed in the laboratory. Koala habitat use was indicated by the presence of fresh faecal pellets at the tree scale. Koala diet composition was assessed by histological analysis of leaf cuticles from fresh faecal pellets collected from sites and the adjacent transects along creeks. Generalised mixed effects modelling was applied to analyse the influence of tree characteristics and environmental factors on foliar chemistry and the presence/absence of koala pellets. The relationship between foliar chemical composition and temporal variation in koala diet composition was also investigated. Two satellite images captured by WorldView-3 were used to extract tree spectral reflectance for eight sites from two landscapes. Spectral indices were calculated from the tree spectra. The correlations between spectral indices and foliar DigN concentrations were examined. Rainfall within the previous six-months and surface water availability were the primary determinants of leaf moisture and secondary determinants of foliar DigN and FPC. All foliar chemicals varied among the four eucalypt species sampled. The riparian species E. camaldulensis had higher leaf moisture content, DigN and FPC concentrations than the floodplain species E. populnea. Koala presence was positively influenced by foliar DigN concentration, tree size and long-term (three years) soil moisture. Koalas used taller E. camaldulensis in riparian areas and the long-term soil moisture in the Brigalow Belt South was positively associated with koala presence. More than 50% of the koala diet was from E. camaldulensis. E. coolabah was eaten more than E. populnea and E. melanophloia where it occurred. Koalas increased consumption of E. melanophloia in the dry season, probably to increase moisture intake but ate more E. populnea in wet seasons in response to higher DigN levels. Leaf moisture was lower in the dry season whereas DigN and FPC were more stable across seasons. The normalised difference index using bands ‘Coastal’ and ‘NIR1’ extracted from WorldView-3 satellite images was best correlated with DigN concentrations. The index was used to map foliar DigN at landscape scale. The significance of this research lies in demonstrating the importance of leaf moisture and DigN for semi-arid koala populations, especially in E. camaldulensis as the koala primary food tree species. Leaf moisture decreased in dry seasons and was a key factor limiting foliar nutrition for koalas. The high variation and concentration of foliar FPC in E. camaldulensis indicated koalas could cope with FPC through physiological tolerance and using trees with comparatively lower FPC. The temporal variation in diet of E. populnea and E. melanophloia revealed the supplementary function of secondary koala habitats. Therefore, preserving riparian habitats and surface water bodies is essential for the survival of western koala populations under a hotter and drier climate. Protecting secondary floodplain habitats is important for their long-term persistence. Because foliar DigN did not show strong and unique absorption features, the relationship between the best spectral index and DigN is indirect. The applicability of this index for mapping DigN in other areas needs to be verified.
... Gordon et al. (1988) documented the mortality of up to 63% of a koala population in south-west Queensland (Qld) following a heat wave during a drought, which included a 12-day period when the temperature exceeded 40°C each day. Seabrook et al. (2011) estimated an 80% decline in koala abundance in south-west Qld over a 12-year period that encompassed the Millennium drought of 2002. Lunney et al. (2012 estimated that heatwaves during a drought killed 25% of the Gunnedah population in north-west New South Wales (NSW). ...
... This estimate is much higher than the naïve occupancy (0.16) recorded by spotlighting at 178 sites located at <800 m elevation by Kavanagh et al. (1995) An important finding in our study was that occupancy showed little variation, and appeared to increase as the confidence interval decreased, across the 8-year study period despite a very severe drought. We predicted that koala occupancy would decline and recovery would be slow, given declines have been observed in koala populations elsewhere during earlier droughts (Gordon et al., 1988;Lunney et al., 2012;Seabrook et al., 2011). We observed no decline and this was not a sampling artifact. ...
Article
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Abstract Multiyear investigations of population dynamics are fundamental to threatened species conservation. We used multiseason occupancy based on spotlight surveys to investigate dynamic occupancy of the koala and the greater glider over an 8‐year period that encompassed a severe drought in year 6. We combined our occupancy estimates with literature estimates of density to estimate the population sizes of these species within the focal conservation reserve. Both species showed substantial yearly variation in the probability of detection (koala: 0.13–0.24; greater glider: 0.12–0.36). Detection of the koala did not follow any obvious pattern. Low detection of the greater glider coincided with the drought and two subsequent years. We suggest the low detection reflected a decline in abundance. The probability of occupancy of the koala was estimated to be 0.88 (95% CI: 0.75–1.0) in year 8. Autonomous recording units were also used in year 8, enabling an independent occupancy estimate of 0.80 (0.64–0.90). We found no evidence of a drought‐induced decline in the koala. Habitat variables had a weak influence on koala occupancy probabilities. The probability of occupancy of the greater glider changed little over time, from 0.52 (95% CI: 0.24–0.81) to 0.63 (0.42–0.85) in year 8. Modeling suggested that the probability of colonization was positively influenced by the percentage cover of rainforest. Increased cover of these nonbrowse trees may reflect thermal buffering, site productivity, or soil moisture. We estimate that our study reserve is likely to contain >900 adult koalas and >2400 adult greater gliders. These are among some of the first reserve‐wide estimates for these species. Our study reserve can play an important role in the conservation of both species.
... Forest die-off events due to climatic extremes have the potential to influence fauna directly and indirectly, as a result of alterations in availability of food resources, loss of suitable refuges, and more extreme temperatures for fauna to endure. For example, following the millennium drought in Eastern Australia (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009), koala (Phascolarctos cinereus) populations declined by 80% (Seabrook et al., 2011). These declines were linked to low summer rainfall and an above average number of hot days, with surviving koalas retreating to riparian areas (Seabrook et al., 2011). ...
... For example, following the millennium drought in Eastern Australia (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009), koala (Phascolarctos cinereus) populations declined by 80% (Seabrook et al., 2011). These declines were linked to low summer rainfall and an above average number of hot days, with surviving koalas retreating to riparian areas (Seabrook et al., 2011). Droughts in the early 1980s were associated with koalas dying of malnutrition and dehydration as the result of extensive leaf fall and browning of foliage following drought and heatwave events (Gordon et al., 1988). ...
Article
Vegetation changes as a direct result of climatic shifts changes are likely to influence reptile communities reliant on forest habitat structure and health. Extreme heat and drought over the summer of 2010/11 caused canopy collapse and decline in a Mediterranean-type forest, southwest Western Australia. The loss of canopy and altered abiotic and biotic conditions changed habitat availability for fauna. A survey of reptile assemblages and vegetation was carried out over the summer of 2013/14, three years after the drought event. Reptiles were captured using camera traps and pitfall traps. Surveys were carried out at four independent locations, where trap stations were set up across drought-affected and adjacent healthy (not visibly affected) sites (total 32 trap stations). Habitat variables likely to influence reptile assemblages (leaf litter, coarse woody debris) were measured, and iButtons were used to capture temperatures within microhabitats likely to be used by reptiles. Reptile assemblages observed at drought-affected sites differed to assemblages observed at healthy sites. These differences could be related to warmer and colder temperature extremes in drought-affected sites compared with healthy sites. Coarse woody debris was readily available in drought-affected sites but leaf litter accumulation was significantly less in drought-affected sites compared to healthy sites. Drought events are becoming more commonplace and it is important to understand the repercussions of forest decline on reptile assemblages. More proactive approaches for maintaining native habitat, such as shelter structures, may be required to protect species in affected sites to ensure that ecosystem processes are not lost.
... We do know that severe population declines have also occurred in the sparsely populated southwest mulga lands due to drought and tree-clearing. 47 In rural central Queensland, one study documented at least 62 koalas killed on roads from 2009-2011. 48 ...
Technical Report
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Over 120 Australian vertebrate species have ended up on the national threatened species list due in large part to bulldozing of their bushland habitats. But behind this conservation crisis lies a largely unacknowledged crisis of animal welfare. Tens of millions of wild animals each year suffer injuries, deprivation and death due to the bulldozing of their forest and woodland habitats, also known as tree- clearing, land clearing or deforestation. This report shines a light on this hidden crisis of animal welfare in Queensland – by presenting information about the likely numbers and fates of wild animals afflicted by tree-clearing, identifying law and policy gaps that allow their welfare to be disregarded, and recommending policy to alleviate the crisis. Bushland destruction has recently resurged in Queensland due to weakening of the Vegetation Management Act 1999 by the former Newman state government. Tree- clearing rates have more than tripled, with nearly 300,000 hectares of forests and woodlands, both mature and immature, bulldozed in 2014-15, the latest year for which data are available. This has led to Eastern Australia being recognised as one of 11 global deforestation fronts, the areas which on current trends will account for 80% of all global forest losses up to 2030. WWF-Australia estimates clearing in Queensland kills about 34 million native mammals, birds and reptiles every year, comprising 900,000 mammals, 2.6 million birds and 30.6 million reptiles. But this underestimates true numbers of animals affected. In particular, the legacy impacts of clearing due to fragmentation and degradation of the remaining habitat are likely to be even more severe because they are ongoing and affect subsequent generations. This is exemplified by koalas, of which more than 10,000 were admitted to the four wildlife hospitals in southeast Queensland from 2009 to 2014, mainly due to dog attacks and vehicle collisions, more than 10 times the numbers directly affected by clearing. The enormous extent of suffering and death caused makes tree-clearing the single greatest animal welfare crisis in Queensland. Yet it is largely unmonitored and unstudied, and neglected in wildlife policy and law. Although we can be confident that animals losing their habitat to destruction likely all die, we know little about their specific fates. Many die on the site of clearing – some quickly if they are crushed by machinery or falling trees, for example, and others more slowly from injuries, starvation or exposure. Others die as they flee from clearing – in collisions with cars, fences or powerlines, killed by predators or due to injuries or deprivation. Larger and more mobile animals like birds and kangaroos may make it to remaining habitat but their chances of survival are low because it is more than likely that remaining habitat is already fully occupied. Overcrowding leads to elevated conflict, stress, hunger and disease risks for immigrants and residents. In very few instances, animals are removed prior to or during clearing by fauna salvage services (known as spotter/catchers in Queensland) or rescued if they happen to be found injured or sick nearby. RSPCA Queensland records show that rescues of forest-dependent wildlife more than tripled from 2011 to 2016, a rise attributed in part to higher clearing rates. Relocated or released wildlife also face the problem that the habitat into which they are relocated likely does not have sufficient resources to support immigrants. Although fauna salvage could save many more wild animals, most tree-clearing operations proceed without any requirement for it, and salvage services are not bound by adequate training and practice requirements. There is no law requiring those who bulldoze bushland in Queensland to reduce their impacts on animal welfare. Tree-clearing and conservation laws are silent on animal welfare impacts of habitat destruction. Queensland’s animal welfare law does not regulate actions not directed at the wild animals themselves, such as habitat destruction. Perversely, someone bulldozing trees can injure and kill thousands of wild animals with impunity, but if they step out of the bulldozer and intentionally shoot a native animal without a permit, they could be prosecuted.
... As an iconic Australian species, the koala (Phascolarctos cinereus) has received considerable attention from both the general public and scientists over the past century. Despite this, there is an ongoing decline of koala populations [1,2]. In 2012, the koala was listed as "Vulnerable to extinction" in Queensland and also by the International Union for Conservation of Nature (IUCN) Red List in 2016 [3]. ...
Article
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Koalas are facing many threats and have now been officially listed as endangered. Recently, concerns were raised in anecdotal reports of koalas being killed by livestock, especially cattle. We investigated the significance of cattle as a threat to koala survival via two koala–cattle interaction experiments, from both the koala and cattle perspectives. In the first experiment, we recorded the ranging behaviour of free-ranging, radio-collared koalas prior to, during and after cattle grazed within their usual home range. Koalas decreased their distance travelled and the size of their home range when they shared space with cattle, compared with the period before cattle started grazing within their home range. In the second experiment, we recorded the reactions of cattle towards koalas that they encountered on the ground, using motorised animal models: a model koala mounted on a remote-controlled vehicle and a model dog mounted on the same vehicle, and the vehicle alone. The koala model elicited aggression and fear in cattle, similar to the dog model, whereas their reaction to the vehicle was significantly less aggressive. No actual attacks by the cattle were observed. The results provide experimental evidence that negative koala–livestock interactions occur and indicate that cattle and koalas may see each other as a disturbance.
... Increasing temperature is also suspected to increase mortality rates, for example in moose, because of increased spread of diseases and parasites when temperature regimes change and a global body deterioration in moose with heat stress (Murray et al. 2006, Lenarz et al. 2009). Occupancy and population range may also decrease because of higher frequencies of droughts, as has been the case for a population of koala in Queensland, Australia (Seabrook et al. 2011). Climate change may also lead to changes in phenology in many species, but some may not succeed in shifting their phenology simultaneously with climate change and also with the community they live with, and thus individuals may incur reduced fitness (Visser and Holleman 2001, Edwards and Richardson 2004, Visser and Both 2005. ...
Thesis
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Natal dispersal is a process by which individuals move from their natal to reproductive ranges which is fundamental for population dynamics and persistence. Through for example the limitation of inbreeding or the capacity it provides to reach and colonize new habitats containing resources or mates, it can be highly beneficial to dispersing individuals. However, dispersal can also be costly for the individuals, through increased mortality or attrition, energy expenditure, or lost habitat opportunities and time. Its expression at the population level thus depends on the balance between costs and benefits, and theory states that dispersal may become counter-selected if costs outweigh benefits. In the current context of global change, we may expect (1) dispersal costs to increase with the degradation of environments and (2) increased dispersal costs to decrease dispersal success and geographical reach through evolutionary mechanisms. Moreover, because dispersal costs may vary with actual dispersal movement, we may wonder what are the discrete alternative tactics roe deer may use in contrasting environments (3). In this PhD, I aimed to address these three perspectives using two roe deer datasets from two geographically distinct populations (GPS data in Haute-Garonne and Capture-Mark-Recapture data in Deux-Sèvres, France), as well as a modelling approach. First, I show that, despite having a good body condition, dispersers incur costs in terms of mortality, reproduction and growth, and that climate change may increase mortality costs. Concomitant to these variations in costs, I also found that realised dispersal has diminished over the past 30 years by more than 30% in both sexes. Second, I identified at least six alternative dispersal tactics in roe deer, characterised by different movement timing, amplitude and duration, which may imply different outcomes in terms of costs and population dynamics. Lastly, my analyses suggest that dispersal might evolve towards tortuous and short distance movements when mortality costs increase, limiting the geographical reach of dispersal. Overall, these results highlight the concerning effects global changes may have on dispersal costs and dispersal evolution. Because dispersal is a species and context dependent process, more studies addressing the impacts of global changes on dispersal costs, ideally incorporating alternative dispersal tactics, will provide valuable information to better predict how species may cope with environmental changes.
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Abrupt environmental changes can affect the population structures of living species and cause habitat loss and fragmentations in the ecosystem. During August–October 2020, remarkably high mortality events of avian species were reported across the western and central United States, likely resulting from winter storms and wildfires. However, the differences of mortality events among various species responding to the abrupt environmental changes remain poorly understood. In this study, we focused on three species, Wilson’s Warbler, Barn Owl, and Common Murre, with the highest mortality events that had been recorded by citizen scientists. We leveraged the citizen science data and multiple remotely sensed earth observations and employed the ensemble random forest models to disentangle the species responses to winter storm and wildfire. We found that the mortality events of Wilson’s Warbler were primarily impacted by early winter storms, with more deaths identified in areas with a higher average daily snow cover. The Barn Owl’s mortalities were more identified in places with severe wildfire-induced air pollution. Both winter storms and wildfire had relatively mild effects on the mortality of Common Murre, which might be more related to anomalously warm water. Our findings highlight the species-specific responses to environmental changes, which can provide significant insights into the resilience of ecosystems to environmental change and avian conservations. Additionally, the study emphasized the efficiency and effectiveness of monitoring large-scale abrupt environmental changes and conservation using remotely sensed and citizen science data.
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Extreme climatic events such as droughts and floods are expected to become more intense and severe under climate change, especially in the southern and eastern parts of Australia. We aimed to quantify the relationship between body condition scores (BCS), demography, activity rate, and parasitic infections of eastern grey kangaroos on a large conservation property under different climate extremes by employing camera traps established at artificial water points (AWPs). The survey period included a severe drought, broken by a significant flooding event. Climatic and environmental conditions were documented using remotely sensed indices of moisture availability and vegetation productivity. These conditions were found to affect all health and population parameters measured. BCS, juvenile proportions, and sex ratios were most correlated with 6-month lags in climatic conditions, while the activity rate of kangaroos at AWPs was most correlated with vegetation productivity. Ticks were mostly found on individuals with a poorer BCS, while the concentration of parasitic eggs in feces was higher in autumn than in spring. Our study offers a glimpse into some of the environmental drivers of eastern grey kangaroo populations and their health, information that may become increasingly important in today’s climate. It further emphasizes the importance of this knowledge for wildlife conservation efforts appropriate to managing the impact of climate change alongside other threats.
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Koala populations in Australia are declining due to threats such as chlamydiosis, wild dog predation and vehicle collision. In the last decade, grazing livestock emerged anecdotally as a threat to koala survival in areas where koala habitat and livestock grazing land overlap. This is the first study investigating the significance of livestock-inflicted injuries and deaths in koala populations over a large spatial and temporal scale. We investigated the outcome, scale, and frequency of livestock–koala incidents via an online survey and analysed koala admission records in Queensland wildlife hospitals and a wildlife rescue group (Wildlife Victoria) in Victoria. The results provide evidence of both livestock-inflicted injuries and deaths to koalas, especially as these have been confirmed by witness statements. The outcomes for the koala victims of the incidents were severe with a 75% mortality rate. The reported frequency of livestock–koala incidents was low but increasing, with 72 cases (0.14% out of 50,873 admissions) in Queensland wildlife hospitals during 1997–2019, and 59 cases (0.8% of 7017 rescue records) in Wildlife Victoria during 2007–2019. These incidents were likely to be under-reported due to the remoteness of the incident location, possible mis-diagnoses by veterinarians and the possible reluctance of farmers to report them. Future research is encouraged to explore the mechanics and causes of livestock–koala incidents and to develop management strategies to minimise the livestock threat to koalas.
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The Koala (Phascolarctos cinereus) is an endemic marsupial inhabiting four states of Australia. Urbanisation, declining habitat, drought and fires are threatening the survival of this flagship species. These threats may cause acute and chronic stress in koalas, which might also be associated with occurrence of infectious diseases in koala populations. Stress may induce an increase in cortisol reflected in increased faecal cortisol metabolite (FCM) values. To be able to use faecal cortisol metabolites to measure stress levels in this species, our aim was to determine baseline values for males and females during breeding and non-breeding season. A total of 351 defecations were collected fortnightly, twice a day, for 12 months from koalas at a wildlife facility in South East Queensland. Samples were analysed with three different enzyme immunoassays (EIAs): a cortisol, 5α-pregnane-3β,11β,21-triol-20-one (37e) and tetrahydrocorticosterone (50c) EIA. The latter, which also reacts with tetrahydrocortisol, the main metabolite in koala faeces, was found to have the highest biological sensitivity and, therefore, is the most suitable EIA to measure stress levels in koalas. Utilising this EIA, we found significant differences (p < 0.05) in FCM values between males and females, breeding and non-breeding season, and between morning and evening samples. Values of faecal cortisol metabolites established in stress-free koalas in this study can serve as a reference for future studies in koalas.
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A survey of the diet and habitat condition of koalas was undertaken on a grazing property (Tyrone) located in the mulgalands of south west Queensland. The research was undertaken using faecal analysis from transects throughout various communities, and information collected on vegetation structure. Koalas were found to be present in a number of habitats not previously reported in the literature. Although riparian areas were known to be important to koalas, this study indicated the extent to which koalas use vegetation of dissected residual, and other landsystems. Some conclusions are drawn on possible distributions throughout this region.
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Context: The impacts of climate change on the climate envelopes, and hence, distributions of species, are of ongoing concern for biodiversity worldwide. Knowing where climate refuge habitats will occur in the future is essential to conservation planning. The koala (Phascolarctos cinereus) is recognised by the International Union for Conservation of Nature (IUCN) as a species highly vulnerable to climate change. However, the impact of climate change on its distribution is poorly understood.
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We assessed decline in the distribution of P. cinereus in Queensland over the last century using historical data from P. cinereus surveys and the Queensland State Archives to measure change in extent of occurrence and area of occupancy. Broad distribution (extent of occurrence, measured with a minimum convex polygon) has contracted by about 27% and area of occupancy (measured with a 30 minute grid) by about 31 %.The degree of contraction in area of occupancy correlates with the estimated extent of habitat loss, supporting suggestions that habitat loss has been, and may still be, the major threat to koalas in Queensland. Contraction in the overall range has occurred on the northern and western margins of the distribution (the Wet Tropics, Gulf Plains, Mitchell Grass Downs, and Mulga Lands Bioregions). Distribution showed a latitudinal change during the harvest period in the early 20th century, with an increase in area of occupancy in central Queensland and a decrease in southern and northern Queensland.This correlates with corresponding changes in population size. Analysis of distribution does not provide support for listing P. cinereus as vulnerable in Queensland or the South East Queensland Bioregion. Problems in measurement of area of occupancy and extent of occurrence are discussed. It is difficult to measure the areas accurately due to difficulty in meeting the underlying assumptions of the techniques.
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(1) We suggest a theoretical framework for considering limits to relatively stable distributions and illustrate some of the points raised with information on the distribution of two species of kangaroos. (2) If an attribute such as density or condition is low at the periphery but rises progressively towards the core of the distribution, its trend is described as a `ramp'. If the level of the attribute differs little between the periphery and the core of the distribution its trend forms a `step' at the range boundary. (3) Should density form a ramp inwards from the boundary whereas the mean well-being of the animals (e.g. body condition, growth, weight, recruitment) forms a step, the factor limiting distribution is likely to be a resource that is utilized consumptively or pre-emptively. (4) Should both density and well-being form a ramp, the implicated factor is a component of climate, an unmodifiable resource, or a facultative predator, parasite or pathogen. (5) Should both density and well-being step at the range boundary, the factor controlling the position of the boundary is likely to be the substrate (e.g. a rock type). (6) Two kangaroo populations were sampled at the core and periphery of their respective ranges. The southern (=`western') grey kangaroo Macropus fuliginosus (Desmarest) exhibited a ramp of both density and well-being which, in combination with ecological information on this species, suggested that the edge of the range was positioned by a component of climate perhaps interacting with an unmodifiable resource. (7) The eastern grey kangaroo Macropus giganteus Shaw exhibited a ramp of density but a step of well-being, implicating a renewable resource as the factor determining the inland boundary of distribution. (8) Density and distribution are likely to be different aspects of the same thing except where the limiting factor or combination of factors is or includes a renewable resource consumed by the animals.
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This paper reviews field methods for estimating and monitoring the abundance of terrestrial carnivores that do not involve capture. Effective methods of monitoring abundance are important tools for the management and conservation of many species. The development of methods for carnivores presents particular challenges, as they are often secretive and widely dispersed. Nevertheless, a variety of approaches based on direct observations and quantification of field signs have been employed. These techniques are described in relation to carnivore ecology and resource implications, and the advantages and deficiencies of each are discussed with reference to case studies.
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Community-based wildlife postal surveys, which included the spotted-tailed quoll, were undertaken in Eden, Port Stephens, Bellingen and Iluka. This resulted in 68 records for spotted-tailed quolls for Eden, 40 for Port Stephens, 39 for Bellingen and 7 for Iluka. Such a high number of records from coastal New South Wales, with many on private lands, identifies postal surveys as a major source of previously overlooked sightings. Spotted-tailed quolls have declined in range by as much as 50–90% since European settlement, which has seen them listed as a nationally vulnerable species. There have been few surveys of spotted-tailed quolls in New South Wales due to their difficulty of detection using standard field survey techniques, such as cage trapping and hair tube sampling. Their unique appearance makes them an ideal species to include in community-based surveys. Future use of these surveys has the potential to contribute significantly to conservation programs of spotted-tailed quolls that involve private lands and local support.