1. University of Queensland
CONS3017
Semester 1 2016
The Koala Coast of South East Queensland
Trends in Koala Population Dynamics and Future Management
Recommendations
Greg Forster
42853288
2. 42853288
1
Abstract
The Koala Coast of South East Queensland has experienced rapid declines in Koala (Phascolarctos
cinereus) populations due to land use change and urban development. In order to assess the trends and
drivers of this change, a subset of Koala population data was acquired from the South East Queensland
Koala Population Modelling Study (Rhodes et al. 2015). Data calculations revealed a number of trends in
population densities between 1996 and 2013, and generalised linear models indicated the strength of key
factors which influenced density patterns between 2009 and 2013. From 1996 to 2013, Koala Coast
populations declined by 66.3%. For the same period, mean densities were 0.15koalaHa for bushland, 0.4
koalaHa for remnant, and 0.15 koalaHa for urban landscapes. However, a 24.7% decline in bushland, a
98% decline in remnant, and 121.1% decline at urban locations caused mean 2013 densities of 0.11
koala/Ha, 0.09 koala/Ha, and 0.12 koala/Ha in bushland, remnant and urban habitats respectively. The
most rapid decline was observed at urban coastal habitats (Ormiston, Thorneside, Point Halloran, Redland
Bay) and inland remnant patches (Ney Road, Gravel reserve, Clarks Shed). In total, three urban and one
bushland site resulted in zero Koalas (Capalaba, Redland Bay, Victoria Point and Kindilan), and the
remnant JC Trotter habitat was the only site that increased. Univariate modelling involving nitrogen,
phosphorus, area and broad vegetation groups were the most important in predicting koala counts. While
multivariate modelling suggested the interaction between area/ phosphorus (Wi= 0.54) and area/nitrogen
(Wi=- 0.45) had the greatest influence. Results from this project indicate Koala Coast habitat must be
conserved, and connectivity between patches of high soil fertility and nutritious eucalypt species must be
established. Landscape ecology principles are required ahead of socio economic theory if sustainable
Koala Coast populations will be sustained into the future.
3. 42853288
2
Table of Contents
1.0 INTRODUCTION .................................................................................................................................................. 3
2.0 METHODS ........................................................................................................................................................... 4
2.1 STUDY REGION............................................................................................................................................................4
2.2 SITE SELECTION AND DATA ............................................................................................................................................5
2.3 TRENDS IN POPULATION DENSITIES .................................................................................................................................6
2.4 INFLUENCES TO POPULATION TRENDS..............................................................................................................................6
2.5 MODEL RESULTS AND 2013 DENSITIES............................................................................................................................7
3.0 RESULTS.............................................................................................................................................................. 7
3.1 TRENDS IN POPULATION DENSITIES .................................................................................................................................7
3.2 INFLUENCES TO SPATIAL DENSITY TRENDS ......................................................................................................................12
3.3 MODEL RESULTS AND 2013 DENSITIES..........................................................................................................................13
4.0 DISCUSSION ...................................................................................................................................................... 13
5.0 PROPOSED MANAGEMENT ACTIONS ................................................................................................................ 16
6.0 REFERENCES...................................................................................................................................................... 17
7.0 APPENDIX ......................................................................................................................................................... 19
4. 42853288
3
1.0 Introduction
Human population growth has influenced biotic and abiotic interactions worldwide, and declining
biodiversity is just one example of an earth system response to the human requirement of resources and
space. Due to extensive vegetation clearing and land use change, habitat loss and fragmentation has
become common, which in turn has influenced intra and interspecific interactions at patch and landscape
scales. In recent times, metapopulational models and landscape ecology have attempted to understand
trends and drivers within the dynamic instability of such ecological systems (McAlpine et al. 2008; Wu
2013). While at the same time, socio-economic theorems have predominantly influenced decision making
and future development. However, the importance of biodiversity has become a relatively popular
debate, and scientific research has continued to suggest that anthropogenic drivers of change are
significant factors in species population dynamics. In terms of biodiversity and conservation management,
this has provided some relatively detailed accounts of biotic communities declining in response to urban
development.
The Australian Koala (Phascolarctos cinereus) is just one species that has received increased attention in
recent times. This species is a specialised folivorous arboreal marsupial, endemic to the Australian
continent and tagged as an Australian icon (McAlpine et al. 2006; Rhodes 2009). Characterised by a
solitary lifestyle and 20hours of inactivity per day, they require sufficient foliar nutrients and moisture
from particular eucalypt species, which are often found in remnant and bushland landscapes targeted for
urban development (McAlpine et al. 2008; Thompson 2006). Koala home ranges vary according to habitat
quality, season, gender and existing population densities (Rhodes et al. 2015), however ranges of
between 1 and 50ha has been suggested by De Oliveira et al. (2014). Foraging or finding new territory
instigates ground movement, and sub adult males can cover distances of 3.5km to 10km between the
June to December mating period (Rhodes et al. 2015). Common traits are found within the nationwide
distribution of Koalas; however site specific evolution has caused genetic diversity in isolated populations
(Rhodes et al. 2008).
Australian Koala communities generally occur along the East Coast, with populations established in over
30 bioregions from tropical North Queensland to the temperate South East of South Australia (McAlpine
et al. 2008; Rhodes et al. 2015). In the past, inconsistent Koala regional population have caused variability
in conservation legislation across state boundaries (Melzer et al. 2000). However, the Koala is now
protected in all states and territories, and listed as a Threatened Species in Queensland, New South Wales
and the Australian Capital Territory (Rhodes et al. 2015). Even so, land clearance and urban development
has continued to assert pressure, and rapid population declines have been observed at certain locations.
5. 42853288
4
The Koala Coast of South East Queensland (SEQ) is a regional community of Koalas declining in response
to anthropogenic and environmental change. Dique et al. (2003) have described this site as a nationally
significant habitat due to its proximity to dense human populations. Historically, this region supported
large Koala communities, but observations of population decline have captured the attention of
academics and decision makers alike. Since this recognition, a number of studies have been funded in an
attempt to document the trends and patterns of change. This includes papers by Dique et al. (2003),
Oliveira et al. (2014) and McAlpine et al. (2006); and a recent modelling study conducted by Rhodes et al.
(2015) which suggested a 80% decline in Koala Coast populations between 1996 and 2014. Considering
the significance of this region to both conservationists and developers, empirical evidence sourced from
scientific enquiry can only be assumed to influence future direction.
This current paper will report on the spatial distribution of Koala populations within the Koala Coast
region of South East Queensland. Main objectives include the identification of Koala population trends
and potential drivers between 1996 and 2013; and an investigation into the key environmental, habitat
and landscape factors which influence population dynamics over time. Firstly, a methods section will be
provided to describe the region of interest and the specific data processing methods. This will be followed
by a report of project results, and a discussion regarding the trends and influential factors that were
revealed through this analysis. As a conclusion, recommendations for future management strategies will
be provided in reference to relevant academic literature.
2.0 Methods
2.1 Study Region
On the Australian East Coast, and approximately 20km south east of Brisbane City, the Koala Coast covers
approximately 375km2
of the Redlands, Logan and Brisbane City Shires (De Oliveira et al. 2014) (Figure 1).
Geographic boundaries include the eastern coastline of Moreton Bay, the southern Logan River, the
Gateway Motorway to the north, and the Pacific Highway in the west (Dique et al. 2003). The Department
of Environment and Heritage Protection (2016) have reported SEQ population growth of approximately
1000 people per week, which generally defines the extent of development within the outer urban suburbs
of the Koala Coast region. A recent project by Thompson (2006) classified land cover as 50% forest, 19%
urban, 24% pasture and 7% non-koala habitat (Figure 2). The majority of the forested landscape contains
tall and open forest with riparian zones, commonly classified under the Regional Ecosystem code 12.11.5
(Thompson 2006). The Bureau of Meteorology (2016) report mean temperatures of approximately
15.5degC to 26.5degC, and mean yearly precipitation of 1209.5mm. Figure 2 below illustrates the Koala
Coast mosaic, and project survey sites have been highlighted for future reference.
6. 42853288
5
2.2 Site Selection and Data
This project involved the analysis of survey data from the South East Queensland Koala Population
Modelling Study (Rhodes et al. 2015), originally prepared for the Department of Environment and
Heritage Protection. According to Rhodes et al. (2015), site selection was based on land cover
classification from satellite imagery, which designated a number of sites according to bushland, remnant
or urban habitat types. Between 1996 and 2013, Koala count data was acquired for each site by either
strip transects, total counts or line transects for the months of February and August (Rhodes et al. 2015).
Measurements of environmental and habitat factors were also sampled between 2009 and 2013.
From these original SEQ datasets, CONS3017 pre-processing provided two Excel files which included a 36
site Koala Coast subset. A number of issues were found regarding missing values and extremely low
sample sizes, and these sites were duly removed from the following analysis. After this data cleansing
procedure, a total of 29 sites remained. Table 1 below provides a summary of the included survey
locations aggregated according to habitat type, and a complete list of site details can be found Appendix
1.
Figure 1- Approximate location of the Koala Coast in Queensland’s
South East corner (Esri 2015)
Figure 2- The Koala Coast and survey site locations (Queensland
Government 2016)
7. 42853288
6
Table 1- Project sample sizes and mean patch area
2.3 Trends in Population Densities
The analysis of Koala density trends between 1996 and 2013 involved survey data and an ArcMap
shapefile. For each sample site, total koala counts and density results allowed the extraction of 2013
population indicators, and the calculation of mean densities and rates of change (ROC) between 1996 and
2013. Results from this first step were aggregated to represent bushland, remnant and urban landscapes;
and processed using RStudio to produce summary boxplots. Following this, the aggregated mean yearly
densities were graphed to illustrate temporal change between 1996/98 and 2013. Further density trends
were observed by comparing the change within connected and slightly detached sites. The latest 2013
densities and mean ROC results were also joined to the provided shapefile attribute table. This allowed
the categorization of Koala trends according to the natural jenks classification scheme, and an overlay
with the 2013 SLATS foliage projective cover raster image.
2.4 Influences to Population Trends
Key factors that may have influenced Koala density trends between 2009 and 2013 were analysed
according to statistical procedures recommended by McAlpine (2016). The provided dataset contained
measurements of 10 environmental, habitat and land use factors which potentially influence Koala
distributions. In addition to the predefined categories, the patch area of each surveyed site and land use
codes were also attached to provide variables representing habitat size and landscape type. This adjusted
dataset was standardised in preparation for further statistical processing in RStudio.
An Information-Theoretic statistical approach was utilised to investigate the strength of interaction
between Koala populations and potential drivers. This procedure ranked univariate and multivariate
models according to the fit of data within the models, which is considered an improvement to traditional
hypothesis testing and P values (Anderson and Burnham 2002). This ranking technique is also useful
because it captures model and parameter uncertainty, which is often high in statistical modelling of
ecological interactions (Dail and Madsen 2011; McAlpine et al. 2008). Due to normality assumptions and
the skewed distribution within the project data (Appendix 2), a general linear model (GLM) for Poisson
distributions was considered suitable. Such models assume errors from the exponential family, and
Region
Total
Sites
Bushland Remnant Urban Koalas
Counted
(1996-2013)
Sites
Average Site
Area (ha)
Sites
Average Site
Area (ha)
Sites
Area
(ha)
Koala
Coast
29 14 36.5 8 34.8 6 143.8 2982
8. 42853288
7
predicted values are calculated by discrete and continuous predictor variables involving a link function
(Bolker et al. 2009). Calculating the interaction strength between explanatory variables and the Koala
Coast count data involved a number of steps.
The first step required a spearman’s test for correlation between explanatory variables. McAlpine et al.
(2006) have reported that relationships between dependant and independent variables can cause
irregular modelling results, and therefore one variable within a correlated pair should be removed if R >
0.7. Univariate GLM’s were then developed for each remaining explanatory variable, and a table was
compiled detailing the Parameter Estimates, P values, Standard Errors and Akaike Information Criterion
(AIC). The AIC’s were then weighted to account for small sample sizes and ranked largest to smallest,
followed by a calculation of the Akaike Weighted Index (Wi) where the highest decimal values implied the
best model. This procedure reveals the likelihood of explanatory variable effectiveness in explaining the
response data when compared to all other models in the set (McAlpine et al. 2006).
To investigate the effect of two variables interacting, multivariate GLM’s were designed using the most
influential explanatory variables from the previous univariate results. The same procedure of ranking
AIC’s was used, however the best combination of models were finalised by summing the most influential
model Wi’s until the total was greater than 0.95. This implied a 95% confidence interval in the final
combination and accounted for model selection uncertainty (McAlpine 2016).
2.5 Model Results and 2013 Densities
Following the multivariate analysis, the most important explanatory variables from the final 0.95 model
set were joined to the supplied polygon shapefile in ArcMap. A value was calculated for each site using
Field Calculator to factor the explanatory variables. This value was considered a basic and unit less
indicator of the effect of all three variables at individual patches, and was therefore compared to the
spatial arrangement of 2013 Koala densities. A final map was created to present this comparison.
3.0 Results
3.1 Trends in Population Densities
The mean density of the Koala Coast population between 1996 and 2013 was 0.2 Koala/Ha, while the ROC
over the same spatial and temporal scale resulted in a regional 66.3% decline. The density and ROC
calculations for the aggregated habitat types also revealed a number of trends. For the period between
1996 and 2013, mean Koala density was 0.15koalaHa for bushland (SD=0.12), 0.4 koalaHa for remnant
(SD=0.67), and 0.15 koalaHa for urban (SD=0.13) (Figure 3). The ROC’s revealed a 24.7% decline in
9. 42853288
8
bushland (SD=32), a 98% decline for remnant (SD=68), and 121.1% decline at urban locations (SD=141)
(Figure 4).
Time series comparisons revealed distinct declines for bushland, remnant and urban locations. However,
the intensity and pattern of change varied significantly. As previously illustrated, remnant habitats depict
the greatest range of decline in population densities (Figure 5), however a sequence of maximum and
minimum fluctuations within the general declining trend can be observed. The bushland habitat decline
appears less sequential and characterised by a significant peak in densities between 1999 and 2005,
followed by a rapid decline to low levels (Figure 6). The urban habitat trend depicts increased population
densities up till 2006, followed by a major decline in populations (Figure 7). A common feature within all
habitats is significant population decline during 2005/2006. However, low and variable sample sizes and
mean calculations are acknowledged to have influenced results.
Figure 3- Koala Coast mean density by habitat type
Figure 4- Koala Coast density rate of change from 1996 to 2013
10. 42853288
9
Mean 2013 densities exemplify the population decline throughout all habitat types. Results indicate
means of 0.11 koala/Ha for bushland (SD=0.11 koala/Ha), 0.09 koala/Ha for remnant (SD=0.07 koala/Ha),
and 0.12 koala/Ha for urban (SD=0.14 koala/Ha) (Appendix 3). In total, three urban and one bushland site
resulted in zero Koalas observed (Capalaba, Redland Bay, Victoria Point and Kindilan). Standard deviations
illustrate the extent of patch scale variability in 2013. For example, coastal urban habitat varies from high
density (Ormiston) to low density (Victoria Point and Redland Bay). A similar range of variability is also
0
0.2
0.4
0.6
0.8
1
Koala/Ha
Year
Koala Population Mean Decline in Remnant Habitat 1996 to
2013
0
0.2
0.4
0.6
0.8
1
Koala/Ha
Year
Koala Population Mean Decline in Bushland Habitat 1996
to 2013
0
0.1
0.2
0.3
0.4
Koala/Ha
Year
Koala Population Mean Decline in Urban Habitat 1998 to
2013
Figure 5 Time series of Koala population decline in remnant habitat
Figure 6- me series of Koala population decline in bushland habitat
Figure 7- me series of Koala population decline in urban habitat
11. 42853288
10
found in remnant and bushland habitat. The spatial distribution of 2013 Koala densities by independent
patch are illustrated in Figure 8 below.
The spatial distribution of ROC’s also reveal a number of trends (Figure 9). The most rapid decline can be
observed at urban coastal habitats (Ormiston, Thorneside, Point Halloran, Redland Bay), and inland
remnant patches (Ney Road, Gravel reserve, Clarks Shed). Particular similarities are found within
connected habitats (Daisy Hill, Neville Lawrie Reserve, Venman Bushland), and other patches that are
slightly disconnected (Redland Bay, Kindilan, Bayview). The only increase in Koala densities was at JC
Trotter bushland, which happens to be within 2.5km of four patches that experienced significant declines
(Ney Road, Gravel reserve, Burbank, Prout Road). Once again, low and variable sample sizes are
acknowledged to have influenced results.
Figure 8- Spatial distribution of 2013 Koala densities on the Koala Coast
12. 42853288
11
After further analysis of the time series data at patch scale, trends were observed between sites that were
connected. The Venman, Neville Lawrie and Daisy Hill bushland locations were connected by adjoining
patch edges, and an interrelated sequence of density change can be observed over time (Figure 10).
Graphs depicting the trend relationships between the Kindilan, Bayview and Native Dog Creek sites; and
the Gravel Reserve, Ney Road and Chook Farm sites have also been included in Appendix 4.
0.00
0.10
0.20
0.30
0.40
0.50
Koala/Ha
Year
Koala Decline withn Connected Bushland Sites- 1996 to 2013
Venman NP (Bushland) Neville Lawrie (Bushland) Daisy Hill (Bushland)
Figure 9 Spatial distribution of Koala population decline rates on the Koala
Coast between 1996 and 2013
Figure 10- Density trends within connected bushland sites within the Koala Coast region
13. 42853288
12
3.2 Influences to Spatial Density Trends
The univariate GLM procedure revealed a number of potential drivers of Koala population variability. The
models which included the explanatory variables nitrogen, phosphorus, area and broad vegetation groups
(BVG) resulted in the lowest P values and highest parameter estimates. These particular models also
displayed the highest Wi, suggesting particular importance in predicting the Koala count of a location
compared to the other models in the set. Perhaps counter intuitively, negative parameter estimates were
found for area and BVG variables. Table 2 below provides a complete summary of the univariate
modelling.
Table 2 Univariate modelling results
Variable Parameter Estimate Standard Error P-value Weighted AIC Wi
Water 0.023 0.061 0.708 245.16 0.000
DEM -0.029 0.064 0.644 245.08 0.000
Site Type 0.04 0.078 0.611 245.04 0.000
Roads 0.054 0.062 0.385 244.55 0.000
FPC -0.082 0.063 0.197 243.62 0.000
Rain -0.081 0.062 0.191 243.6 0.000
Clay 0.079 0.059 0.182 243.58 0.000
Temp -0.111 0.062 0.0725 242.1 0.000
BVG -0.147 0.066 0.0256 * 240.15 0.001
Area -0.252 0.082 0.00199 ** 233.78 0.025
Phosphorus 0.242 0.06 5.53e-05 *** 229.32 0.236
Nitrogen 0.261 0.06 1.62e-05 *** 227.05 0.736
The Spearman’s correlation matrix suggested a number of relationships between explanatory variables
(Appendix 5). This included correlations between foliar projected coverage (FPC) and
roads/temperature/BVG; and also between site type and roads/FPC. Due to this, interactions between
these variables were not included in the multivariate models combinations. Two particular models
resulted in the most significant prediction of Koala counts- area and phosphorus (Wi= 0.54), followed by
area and nitrogen (Wi=- 0.45). When summed, the Wi total was greater than 0.95.
Table 3 Multivariate modelling results
Model Variable Parameter Estimate Standard Error P-value Weighted AIC Wi
BVG:Phos -155.332 74.08 0.036011 * 226.8 0.000
Clay:Phos 4.292 1.667 0.01004 * 226.28 0.001
Clay:Nitrogen -1.421 0.609 0.019685 * 225.29 0.001
FPC:Phos -5.958 2.032 0.00336 ** 224.52 0.001
Nit:Temp -146.633 79.428 0.065 224.02 0.002
Area:NItrogen -0.61 0.221 0.00578 ** 212.7 0.452
Area:Phos 0.862 0.304 0.00459 ** 212.33 0.543
14. 42853288
13
3.3 Model Results and 2013 Densities
According to the multivariate modelling results, an indicator representing habitat area, phosphorus and
nitrogen was calculated for each site in ArcMap. A number of sites with the highest 2013 densities
corresponded with the highest results of this habitat quality index. This included Ormiston, JC trotter and
Native Dog Creek. However, a number of sites which represented quality habitat were characterised by
mid-range to low 2013 population densities; such as Cleveland, Tingalpa Railway, Thorneside and Karingal.
This suggests progressive change within the landscape elements at different locations, or that certain
influences are not represented in the statistical model variables.
4.0 Discussion
A number of Koala Coast population trends have been revealed during this analysis. Overall, almost all
2013 populations persisted under a range of environmental and anthropogenic pressures, and rapid
declines characterise each study site except JC Trotter. Mean densities illustrate a general long-term Koala
preference for remnant habitat, followed by bushland and urban which supported low populations. An
Figure 11 Comparison of the 2013 population densities to nitrogen, phosphorus and
area indicator calculation
15. 42853288
14
effect of the development of once quality Koala habitat is illustrated by the Koala densities at urban sites,
even though urban covers the largest overall mean habitat area. Although the mean density and ROC
calculations imply other influential factors besides just habitat area, intensive development of the region
has still caused substantial habitat loss. However, population fluctuations also occur yearly, indicating the
dynamic nature of ecosystem functionality within all habitat types and influences.
Continued habitat loss from development within already designated urban patches is just one
consequence of human population expansion. This also provides a finer scaled example of the
consequences of habitat loss following the initial Koala Coast conversion from extensive remnant
bushland. Although Koalas have a high tolerance for partial clearing and fragmentation (Hrdina, Gordon
and Patterson 2006), the extent of habitat disturbance is site and population dependant, which relates to
the variable combinations of factors that influence the structure and functions within specific landscapes.
Generally however, habitat loss influences Koala reproduction and mortality rates through secondary
effects such as increased fragmentation, limitations to resources, and increases in external threats
(McAlpine et al. 2008). Considering the current momentum of development within the Koala Coast region,
declining Koala populations may continue in line with the extent of habitat loss and human presence.
The population variance between similar patches suggests influencing factors besides just habitat type
and size. Research has suggested that Koalas have a specific preference for key eucalypt species with
foliage that contains high nitrogen, potassium and phosphorus (Moore et al. 2004). Generally, such
nutritious foliage is found on trees that grow on fertile soils with high moisture holding capacities, and this
directly influences the population density of a given habitat (Rhodes et al. 2015). Therefore, although a
given patch may have a low overall area, increased nutrition quality can provide suitable habitat for larger
populations. This potential relationship between soil nutrients, vegetation type and Koala counts was
illustrated in the statistic modelling during this project. However, as remnant habitat is overwhelmed by
urban development, the area of undisturbed and quality habitat is reduced, and disconnection occurs
between remaining attractive patches.
In order to maintain Koala population structure, dispersal and migration is required to allow foliage and
territory selectivity, interspecies competition and mating. When combined with habitat loss,
fragmentation without suitable connectivity increases the risk of predation and vehicle collisions when
koalas traverse the matrix, which may be compounded by low energy stores from resource shortages
(Rhodes et al. 2008). Research from Port Stephens has suggested a 43% mortality rate from dog attacks
(Lunney et al. 2007), while road collisions cause approximately 300 deaths per year within the Koala Coast
(Dique et al. 2003). Considering this risk is persistent only while Koalas are on the ground, the
configuration of landscape elements is important in decreasing ground dwelling risks, especially as overall
16. 42853288
15
patch area declines and the distance between patches increases (McAlpine et al. 2006). The provision of
suitable corridors connecting habitat patches may minimise this mortality risk and decrease exposure to a
number of hazards
Naturally occurring environmental influences are further drivers of Koala population dynamics. Events
such as bushfires and droughts are relatively natural in occurrence, yet the effects to landscape structure
and function are extensive. The impact of fire is more prevalent in fragmented landscapes due to
increased ground predation following canopy damage (Lunney et al. 2007), and drought conditions
specifically influence Koala food resources due to tree defoliation (Melzer et al. 2000). During drought
conditions in 1979/80, a 63% mortality rate was documented due to malnutrition and dehydration in
South West Queensland (Gordon, Brown and Pulsford 1988). Considering Queensland was in drought
conditions between approximately 2000 and 2008 (Appendix 6), Koala Coast populations were facing
pressure from both natural and anthropogenic sources at the same time.
The spatial and statistical results from this report specify patch area, soil and vegetation factors as
significant indicators of Koala Coast populations. However, absolute causation is near impossible when
considering such a complicated and interrelated system of environmental and anthropogenic influences.
Although the statistical results implied soil factors as the most important, soil nutrient availability is
dependent on specific fauna adaptations and rates of soil nutrient cycling, and soil measurements have
therefore been considered poor indicators of population densities (Moore et al. 2004). The influence of
road density was also insignificant in the statistical analysis, even though past research has suggested
widespread impacts to Koala populations (Dique et al. 2003; McAlpine et al. 2008; Rhodes et al. 2015). It is
therefore clear that modelling involves satisfying a range of assumptions, which become more influential
as the complexity of interactions increase.
Although this analysis has revealed trends and potential drivers of change within the Koala Coast, a
number of limitations may have influenced results. Firstly, the solitary nature and low populations of the
Koala make absolute counts and density calculations unreliable, while nomad male koalas influence
population calculations because these counts may not actually be permanent (Thompson 2006). A general
small sample size, conflicting ranges of temporal coverage, and sampling bias during the initial site
selection may also have influenced results and interpretations (Rhodes et al. 2015). Although
information- theoretic modelling generally provides good statistical results, the use of AIC for less than 40
parameters is not recommended (Anderson and Burnham 2002). Overall, this research design has
revealed particular trends and drivers in Koala populations. However, future analysis should involve
improvement rather than repetition of this specific research design.
17. 42853288
16
5.0 Proposed Management Actions
The principles of landscape ecology may provide a foundation for future management and conservation of
the Koala Coast region. Although declines are often reported at the landscape scale for the ease of human
interpretation, many significant drivers are ingrained in site specific conditions. This concept can be
observed in the patch variability yet regional similarities of the Koala Coast region. According to McAlpine
et al. (2008), the complicated and dynamic relationships between landscape pattern, process and scale
define species and habitat relationships; which in turn are related to the landscape mosaic and spatial
configuration of patch quality, size and connectivity relationships. Although such a context for
management is not simple in design, a provision for variability in structure and function at landscape and
patch scales is necessary for effective management plans and the co-existence of human development
and future Koala populations.
A number of recommendations can be provided in relation to the current analysis and previous academic
research. Connectivity must be established between habitat locations, with particular focus on patches
that contain high soil fertility and nutritious eucalypt species. While overall available patch size should be
increased, this must be balanced with other influential factors such as habitat quality, connectivity, edge
effects and core densities. The restriction of future residential development within proximity to known
Koala habitats is also recommended, which may be the only way to reduce Koala mortality from domestic
dog predation and vehicle collision risks (Dique et al. 2003). Installations for the safe migration of Koalas
over road networks is also recommended, while further general community education may act to raise
road awareness during mating season (Dique et al. 2003). Unfortunately, as in all conservation proposals
within developing landscapes, a balance must be found between the motivations of opposing
perspectives.
This will require practical management designs that allow urban development and Koala population
conservation (Lunney et al. 2007). Although effective yet practical solutions are difficult for such complex
problems, further monitoring and research will increase available data and provide further insight to
regional characteristics. This may assist the design and implementation of conservation management
practices which allow sustainable Koala Coast populations into the future, with the potential to co-exist
with the expected rate of human development.
18. 42853288
17
6.0 References
Anderson, DR & Burnham, KP 2002, 'Avoiding Pitfalls When Using Information-Theoretic
Methods', The Journal of Wildlife Management, vol. 66, no. 3, pp. 912-8.
Bolker, BM, Brooks, ME, Clark, CJ, Geange, SW, Poulsen, JR, Stevens, MHH & White, J-SS 2009,
'Generalized Linear Mixed Models: A practical Guide for Ecology and Evolution', Trends in Ecology
& Evolution, vol. 24, no. 3, pp. 127-35.
Bureau of Meteorology 2016, Climate Change and Variability, viewed 15th of May 2016,
<http://www.bom.gov.au/climate/change>.
Dail, D & Madsen, L 2011, 'Models for Estimating Abundance from Repeated Counts of an Open
Metapopulation', Biometrics, vol. 67, no. 2, pp. 577-87.
De Oliveira, SM, Murray, PJ, L., DVD & Baxter, GS 2014, 'Ecology and Movement of Urban Koalas
Adjacent to Linear Infrastructure in Coastal South-East Queensland', Australian Mammal Society,
no. 36, pp. 45–54.
Department of Environment and Heritage Protection 2016, Koala Threats, viewed 31st of May
2016, <https://www.ehp.qld.gov.au/wildlife/koalas/koala-threats.html>.
Dique, DS, Thompson, J, Preece, HJ, Penfold, GC, Deidré, LdV & Leslie, RS 2003, 'Koala mortality
on roads in south-east Queensland: the koala speed-zone trial', Wildlife Research, vol. 30, no. 4,
pp. 419-26.
Esri 2015, ArcGIS Online, viewed 22 of December 22 of December 2015,
<https://doc.arcgis.com/en/arcgis-online/create-maps/choose-basemap.htm>.
Gordon, G, Brown, AS & Pulsford, T 1988, 'A koala (Phascolarctos cinereus Goldfuss) population
crash during drought and heatwave conditions in south-western Queensland', Austral Ecology,
vol. 13, no. 4, pp. 451-61.
Hrdina, F, Gordon, G & Patterson, R 2006, 'Decline in the distribution of the Koala Phascolarctos
cinereus in Queensland', Australian Zoologist, vol. 33, no. 3, pp. 345-58.
Lunney, D, Gresser, S, O'Neill, LE, Matthews, A & Rhodes, J 2007, 'The Impact of Fire and Dogs on
Koalas at Port Stephens, New South Wales, Using Population Viability Analysis', Pacific
Conservation Biology, vol. 13, no. 3, pp. 189-201.
McAlpine, CA 2016, CONS3017 Course Material, The University of Queensland, Brisbane.
McAlpine, CA, Rhodes, JR, Bowen, ME, Lunney, D, Callaghan, JG, Mitchell, DL & Possingham, HP
2008, 'Can Multiscale Models of Species' Distribution Be Generalized from Region to Region? A
Case Study of the Koala', Journal of Applied Ecology, vol. 45, no. 2, pp. 558-67.
McAlpine, CA, Rhodes, JR, Callaghan, JG, Bowen, ME, Lunney, D, Mitchell, DL, Pullar, DV &
Possingham, HP 2006, 'The importance of forest area and configuration relative to local habitat
factors for conserving forest mammals: A case study of koalas in Queensland, Australia',
Biological Conservation, vol. 132, no. 2, pp. 153-65.
19. 42853288
18
Melzer, A, Carrick, F, Menkhorst, P, Lunney, D & St. John, B 2000, 'Overview, Critical Assessment,
and Conservation Implications of Koala Distribution and Abundance', Conservation Biology, vol.
14, no. 3, pp. 619-28.
Moore, BD, Wallis, IR, Marsh, KJ & Foley, WJ 2004, The role of nutrition in the conservation of the
marsupial folivores of eucalypt forests, 2 edn, Conservation of Australia's Forest Fauna Royal
Zoological Society, NSW, Sydney Australia.
Queensland Government 2016, Queensland Spatial Catalogue- QSpatial, viewed 25th of May
2016, <http://qldspatial.information.qld.gov.au/catalogue/custom/index.page>.
Rhodes, J, Callaghan, J, McAlpine, C, De Jong, C, Bowen, M, Mitchell, D, Lunney, D & Possingham,
H 2008, 'Regional Variation in Habitat-Occupancy Thresholds: A Warning for Conservation
Planning', Journal of Applied Ecology, vol. 45, no. 2, pp. 549-57.
Rhodes, JR 2009, 'GLMM Applied on the Spatial Distribution of Koalas in a Fragmented
Landscape', in Springer New York, New York, NY, pp. 469-92, DOI 10.1007/978-0-387-87458-
6_21.
Rhodes, JR, Beyer, HL, Preece, HJ & McAlpine, CA 2015, South East Queensland Koala Population
Modelling Study, Brisbane, Queensland, viewed 20th of May 2016,
<https://www.ehp.qld.gov.au/wildlife/koalas/pdf/seq-koala-population-modelling-study.pdf>.
Thompson, J 2006, 'The Comparative Ecology and Population Dynamics of Koalas in the Koala
Coast Region of South-East Queensland', Dissertation/Thesis thesis, University of Queensland.
Wu, J 2013, 'Key concepts and research topics in landscape ecology revisited: 30 years after the
Allerton Park workshop', Landscape Ecology, vol. 28, no. 1, pp. 1-11.
20. 42853288
19
7.0 Appendix
1. Project Survey Site details
2. Skewed distribution of environmental, habitat and land use factor dataset.
Site Number Site Type Site Name LGA DD DD2
1 Bushland Daisy Hill Logan 153.170181 -27.624524
2 Remnant Point Halloran Redland 153.294963 -27.568968
3 Remnant Gravel Reserve Redland 153.216826 -27.540257
4 Remnant McDonald/McMillan Redland 153.231681 -27.521552
5 Bushland JC Trotter Brisbane 153.171964 -27.553428
6 Bushland Warren Street Redland 153.244753 -27.600830
7 Bushland Kindilan Redland 153.278029 -27.637685
8 Bushland Karingal Redland 153.219203 -27.605043
9 Bushland Venman Bushland NP Redland 153.202268 -27.633736
11 Remnant Commonwealth Land Redland 153.201971 -27.505215
13 Bushland Burbank Brisbane 153.174341 -27.572391
14 Remnant Sewage Works Redland 153.240000 -27.532881
15 Bushland Serpentine Creek Redland 153.288130 -27.678210
16 Bushland Tingalpa Railway Brisbane 153.186783 -27.480510
18 Bushland Tingalpa Creek Reserve Brisbane 153.179689 -27.504688
19 Bushland Native Dog Creek Logan 153.263174 -27.668475
22 Bushland Bayview Redland 153.273869 -27.649002
25 Bushland Neville Lawrie Reserve Logan 153.174638 -27.618732
27 Remnant Ney Rd Redland 153.209101 -27.550267
28 Bushland Prout Rd Brisbane 153.150276 -27.538677
29 Urban Thorneside Redland 153.203136 -27.483040
30 Urban Capalaba Redland 153.208804 -27.517599
31 Urban Cleveland Redland 153.278813 -27.534140
33 Remnant Chook Farm Redland 153.223659 -27.554218
34 Remnant Clark's Shed Redland ? ?
35 Urban Ormiston Redland 153.254855 -27.515228
38 Urban Victoria Point Redland 153.311304 -27.583715
39 Urban Redland Bay Redland 153.301202 -27.634526
21. 42853288
20
3. 2013 Koala Density distributions by habitat type
3. Time series comparisons of patches in close proximity
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Koala/Ha
Year
Koala Decline in aThree Adjacent Bushland Sites- 1996 to
2013
Kindilan (Bushland) Bayview (Bushland) Native Dog Creek (Bushland)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Koala/Ha
Year
Koala Density Decline in a Remnant and Bushland Connected
Location - 1996 to 2013
Gravel Reserve (Remnant) Ney Rd (Bushland) Chook Farm (Remnant)
