Identifying priority landscapes and
ecosystems for nature conservation in the
Kangaroo Island NRM region
Phil Pisanu, Dan Rogers, Jody O’Connor, David Thompson and Darcy Peters
Department of Environment, Water and Natural Resources
April 2014
DEWNR Technical Report 2013/14
i
Department of Environment, Water and Natural Resources
GPO Box 1047, Adelaide SA 5001
Telephone
National (08) 8463 6946
International+61 8 8463 6946
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www.environment.sa.gov.au
Disclaimer
The Department of Environment, Water and Natural Resources and its employees do not warrant or make any
representation regarding the use, or results of the use, of the information contained herein as regards to its
correctness, accuracy, reliability, currency or otherwise. The Department of Environment, Water and Natural
Resources and its employees expressly disclaims all liability or responsibility to any person using the information
or advice. Information contained in this document is correct at the time of writing.
© Crown in right of the State of South Australia, through the Department of Environment, Water and Natural
Resources 2013
This work is Copyright. Apart from any use permitted under the Copyright Act 1968 (Cwlth), no part may be
reproduced by any process without prior written permission obtained from the Department of Environment,
Water and Natural Resources. Requests and enquiries concerning reproduction and rights should be directed to
the Chief Executive, Department of Environment, Water and Natural Resources, GPO Box 1047, Adelaide SA
5001.
Preferred way to cite this publication
Pisanu, P, Rogers, D, O’Connor, J, Thompson, D and Peters, D, 2013, Identifying priority landscapes and
ecosystems for nature conservation in the Kangaroo Island NRM region, DEWNR Technical Report 2013,
Government of South Australia, through Department of Environment, Water and Natural Resources, Adelaide
ii
Acknowledgements
We received valuable feedback on an early draft of this report from Martine Kinloch, Phillipa Holden and David
Taylor. Chris Butcher provided assistance with production of figures and maps. The final draft of the report was
reviewed by Kane Aldridge, SMK.
iii
Table of Contents
1
INTRODUCTION
1.1
Project Description and Objectives
1.1.1 Linking Landscape Assessment and NatureLinks Planning
1.1.2 Structure of theReport
2
BACKGROUND
6
6
7
9
10
2.1
Conservation Planning Concepts
2.1.1 Landscape Drivers and Resilience
2.1.2 The Landscape State and Transition Model (LSTM)
2.1.3 Ecosystem Definition
10
11
13
13
2.2
14
3
Kangaroo Island Land Use History and Impacts on Natural Systems
METHODS
17
3.1
Approach
3.2
Landscapes
3.2.1 Landscape Description
3.2.2 Landscape Analysis
17
18
18
18
3.3
Ecosystems
3.3.1 Ecosystem Assessment
19
19
4
22
RESULTS
4.1
Landscape Identification and Description
4.2
Key Ecological Drivers on Kangaroo Island
4.2.1 Fire Regimes
4.2.2 Landscape level patterns of clearance of native vegetation
4.2.3 Other drivers
4.2.4 Landscape Analysis – Summary
22
24
24
29
29
31
4.3
Ecosystem Assessment
4.3.1 Ecosystem Descriptions
4.3.2 Ecosystem level patterns of native vegetation clearance
4.3.3 Avifauna Decline
32
32
33
34
4.4
Eucalyptus cneorifolia Case Study
4.4.1 The Eucalyptus cneorifolia Ecological Community
4.4.2 Conceptual Model of Mallee Ecological Dynamics
34
34
35
5
37
DISCUSSION
5.1
Understanding Drivers of Ecological Change
5.2
The Potential Role of Corridors
5.3
Improving Knowledge
5.3.1 Fire Regimes
5.3.2 Other Threats and Drivers of Change
37
39
40
41
42
6
44
RECOMMENDATIONS
6.1.1
6.1.2
Priority landscapes and ecosystems for conservation activity
Additional knowledge building
44
44
7
CONCLUSION
46
8
REFERENCES
47
9
APPENDICES
53
iv
Summary
The Kangaroo Island NatureLinks project presents the conceptual framework, analysis methods and results for identification of priority
landscapes and ecosystems (ecological communities) for conservation on Kangaroo Island using a whole of island ‘landscape assessment’
approach. The report includes analysis of all major landscapes to identify broad scale landscape units that can be used in management,
evaluates key drivers of change at the landscape scale, identifies a number of key ecosystem types, and presents a detailed case study of
a Kangaroo Island ecosystem to demonstrate how the broad approach can be extended, in cases where sufficient high quality information
is available, to identify fine scale priorities for conservation management and investment.
The project addresses a key aim of the NatureLinks program for Kangaroo Island - 1) Identifying priority landscapes and corridors. The
project addresses two key objectives to achieve this aim:
1.
Identification of priority landscapes for conservation activity; and
2.
For priority landscapes, identification of priority ecosystems for conservation activity.
The ‘Landscape Assessment’ uses a nested approach to setting conservation goals, referred to as the ‘coarse-filter/fine-filter’ approach.
This has been used successfully to identify priority ecosystems for restoration in South Australian agricultural landscapes by identifying
those ecosystems whose dependent biota are at risk of local extinction, where these risks are associated with system-level changes in
function. This type of information has then been used to identify priorities that provide a basis for developing conservation delivery
programs in these regions.
For Kangaroo Island, the landscape assessment essentially comprised four analytical components:
1.
Define and spatially represent the landscapes of Kangaroo Island;
2.
Identify island-wide drivers of landscape change with respect to biodiversity;
3.
Identify where each landscape “sits” relative to these landscape-scale drivers, in order to identify the relative resilience of
different landscapes; and
4.
Target ecosystem-level analyses toward those landscapes that appear to be approaching or have crossed critical thresholds
with respect to landscape-scale drivers.
For the purposes of this assessment, three landscapes were defined for Kangaroo Island: 1) West and South Coast, 2) Central Plateau and
North Coast, and 3) Eastern Plains and Dudley. The analysis identified 12 ecosystems within the three landscapes. Consideration of broad
patterns of historical land use change and interpretation of empirical data where it was available indicates that a number of key drivers
appear to operate at the landscape scale, and/or at the scale of individual patches of remnant vegetation. The key drivers identified were
-fire regime, conversion of native vegetation cover for agricultural production; and species population processes (particularly metapopulation dynamics). In addition, a number of key drivers were identified that specifically relate to the dynamics of patches of remnant
vegetation - grazing of remnant patches; and changes to physico-chemical processes (particularly dryland salinity).
Of the three landscapes, the West and South Coast is the most intact and there is no evidence to suggest major declines at the ecosystem
level are occurring. A dominance of young fire age classes following the large-scale 2007 fires is apparent, reinforcing the need for fire
managers to encourage the reinstatement of older age classes over time.
The terrestrial bird analysis presented here, as well as existing knowledge and new analysis that highlights less than optimal fire regimes,
reinforces the need to keep addressing management issues in the most altered parts of Kangaroo Island, in particular the Eastern Plains
and Dudley landscape. This landscape is essentially fragmented and has a number of highly altered ecosystems, such as associated with
the Narrow-leaved Mallee community complex. Continued management efforts to address issues such as fire regime, grazing pressure,
weeds and salinity will be needed to ensure that resilience in this landscape is maintained and improved over time.
The second key landscape to focus on is the Central Plateau and North Coast. The fire regime for this landscape appears to be operating,
at least in part, outside of optimal limits in terms of age classes, and the eastern section of the landscape is highly altered by clearing. At
an ecosystem scale the terrestrial bird analysis did not flag any major declines in ecological resilience at this time, however, anecdotal
evidence suggests that some changes may be occurring that could lead to losses of ecosystem function in the future. Preferential
historical clearing of woodlands on ironstone soils makes these areas a logical priority for future management and restoration efforts.
The study does not specifically identify corridors but discusses the relevance of corridors as a management option in the context of other
management interventions that could be applied to improve ecological function in the agricultural matrix.
The report makes a number of recommendations about how to improve the knowledge base for Kangaroo Island biodiversity and how to
apply this in an adaptive management framework.
5
1 INTRODUCTION
The Kangaroo Island NatureLinks project presents the conceptual framework, analysis methods and
results for identification of priority landscapes and ecosystems (ecological communities) for
conservation on Kangaroo Island using a whole of island ‘landscape assessment’ approach. The
report includes analysis of all major landscapes to identify broad scale landscape units that can be
used in management, evaluates key drivers of change at the landscape scale, identifies a number of
key ecosystem types, and presents a detailed case study of a Kangaroo Island ecosystem to
demonstrate how the broad approach can be extended, in cases where sufficient high quality
information is available, to identify fine scale priorities for conservation management and
investment.
A key requirement of successful conservation is the clear articulation of goals (Wilson et al. 2006;
Bottrill et al. 2008). These goals should describe the desired outcomes of the conservation activity,
with regard to what components of biodiversity to target for investment in management actions. In
order to achieve nature conservation for a region, particularly in situations where resources for
undertaking action are limited, it is logical that the goals focus on the requirements of the
biodiversity that is most at risk of being irreversibly lost (Diamond et al. 1976; Bottrill et al. 2008;
Gibbons 2010). To put this into context for NRM, this means that investing in the restoration or
management of ecosystems that are demonstrably in decline now is a priority. Any delay in this
investment will lead to greater future costs and higher likelihood that intervention will fail.
Practically, we recognize that NRM invests in biodiversity for a range of outcomes (or to meet a
range of stakeholder expectations) so there are real challenges around making decisions when
resources are limited, which is almost always the case in NRM.
Biodiversity occurs at a range of interacting levels (such as landscape, ecosystem, species), and
conservation goals need to reflect these levels. One way of approaching this challenge is to
understand the state and trend of biodiversity at each of these levels, and the extent to which
meeting the conservation requirements at higher levels will meet the requirements of biota at lower
levels. For example, if we can identify and address the conservation requirements of those
ecosystems that are at risk of irreversible deleterious change, we are likely to meet the
requirements of most species that depend on those ecosystems functioning in a particular way.
This nested approach to setting conservation goals has been termed the ‘coarse-filter/fine-filter’
approach (Noss 1987; Hunter et al. 1988). At the ecosystem level, this approach has been used
successfully to identify priority ecosystems for restoration in South Australian agricultural landscapes
(Rogers 2010; Willoughby 2010; Rogers 2011a; b; 2012a; Rogers 2012d; c; b; Rogers et al. 2012) by
identifying those ecosystems whose dependent biota are at risk of local extinction, where these risks
are associated with system-level changes in function. The information produced has then been used
to identify priorities that provide a basis for developing conservation delivery programs in these
regions.
1.1
Project Description and Objectives
Natural Resources Kangaroo Island, along with DEWNR Policy, has identified five broad aims for the
delivery of NatureLinks on Kangaroo Island:
1.
Identify priority landscapes and corridors across Kangaroo Island
2.
Facilitate stakeholder understanding of the importance of biodiversity corridors
6
3.
New corridor projects identified, assessed and planned
4.
KI NRM Plan reviewed and new actions/targets provided for the next plan
5.
Facilitate NatureLinks delivery
These aims focus on a range of planning requirements, some of which are beyond the scope of the
project presented here. Following discussions with Kangaroo Island regional staff, a decision was
made that SMK would primarily focus on aim 1) Identifying priority landscapes and corridors.
The project addresses two key objectives to achieve this aim:
1.
Identification of priority landscapes for conservation activity; and
2.
Identification of priority ecosystems for conservation activity.
The project identifies priorities for conservation activity on Kangaroo Island by identifying landscapes
and ecosystems within landscapes, that appear to be in decline and thus requiring targeted
conservation management. The issue of corridors is not assessed directly in this report. There are
sound reasons to be cautious about implementing a corridor focused program (see discussion
section) so the recommended approach is that regional staff consult with SMK to evaluate how the
results of the landscape analysis could be used to spatially define parts of landscapes that could be
the focus of on-ground restoration activities.
The project does not provide a review of NRM targets and actions (aim 4) but the types of analysis
used here can produce information useful for review processes. This could be achieved using an
adaptive planning/management framework (see below).
The project also highlights key knowledge gaps that currently limit conservation planning efforts.
Finally, the landscape analysis will be useful as the basis for assessing some of the risks to
biodiversity posed by global climate change. The landscape assessment provides new information on
the current status and trajectory of key ecosystems, which could be combined with additional
information on climate exposure to assess potential climate impacts under different change
scenarios.
1.1.1
Linking Landscape Assessment and NatureLinks Planning
New knowledge built through landscape assessment would be utilized most effectively for the NRM
planning process if an adaptive management approach is adopted. Adaptive management is explicit
about knowledge building as a key part of planning, and as such provides a structure for assimilating
and testing new knowledge, as well as applying knowledge at crucial decision points in the planning
process.
Ecological and social systems are complex and as a result, whole-system responses cannot be easily
predicted from the sum of individual components’ responses (Harris 2007). For example, how a
system responds to a combination of human pressures, management interventions and the variation
linked to natural cycles (e.g. such as drought), strongly depends on context (both historical and
spatial). Moreover, is difficult to predict system responses with certainty based on previous
experiences (simply because the world keeps changing) so expecting predictive certainty in natural
resource management can often be counterproductive (Holling 1978).
The landscape assessment for Kangaroo Island will produce a series of working hypotheses about
processes (or drivers of change) and how different biotas are expected to respond to them. Because
the adaptive management method treats management as a hypothesis, with alternative approaches
7
to natural resource management designed to test this hypothesis (Walker and Salt 2012), it would
be ideal if regional NRM staff work with SMK to develop a set of actions for addressing key
conservation priorities identified by the project.
The adaptive management cycle includes up to seven critical steps, including specification of
management objectives (1), modelling of existing knowledge (2), identification of goals and related
assessment criteria (3), models of alternative management options (4), identification of how to
structure decision-making (5), implementation of management actions (6), and monitoring and
evaluation (7) (Figure 1). There are key feedback loops in adaptive management, particularly in
relation to how models influence objectives and goals, and how management results influence
objectives for new management cycles (Sabine et al. 2004).
Figure 1. The adaptive management cycle (from Sabine et al. 2004).
The adaptive management cycle is not linear, and we recognise that knowledge, management
objectives and specified actions already exist for Kangaroo Island landscapes. Thus the new
information generated by the landscape assessment project will essentially provide synthesis and
models of existing knowledge which can be used to review or refine management objectives, or in
some cases develop new goals.
This process is a way of linking knowledge generation and priority or goal setting. Designing science
to monitor outcomes is outside of the scope of this project but the types of analysis presented here
can provide a foundation for monitoring design, or at least demonstrate how the scientific
foundation or evidence base can be constructed. Overall, this approach should ultimately reduce
(but not necessarily eliminate) uncertainty and provide evidence for sound management practice.
If implemented these adaptive steps will contribute towards meeting NatureLinks objectives 4) KI
NRM Plan reviewed and new actions/targets provided for the next plan, and 5) Facilitate NatureLinks
delivery.
8
1.1.2
Structure of theReport
The report is presented as seven sections, described below:
1. Introduction (project description, objectives, and conceptual background, NRM planning
and adaptive management framework)
2. Methods (landscape and ecosystem analysis methodology)
3. Results (landscape analysis, ecosystem analysis and a fine scale case study)
4. Discussion (significant of key results, identification of knowledge gaps)
5. Recommendations (priority landscapes and ecosystems, future knowledge building)
6. Conclusion
7. References
9
2 BACKGROUND
2.1
Conservation Planning Concepts
A number of different tools can potentially be used for setting conservation goals. These include the
focal species (Lambeck 1997), coarse- and fine-filter ecosystem approaches (Poiani et al. 2000;
Groves et al. 2002) and, more recently, resilience (Walker and Salt 2006). One of the key
requirements of a successfully implemented conservation plan is the development of clearly
articulated conservation goals that are designed to meet the conservation requirements of the
landscape for which they have been designed. The complexity of biological diversity makes this a
challenging task.
The approach presented here for Kangaroo Island is based on identifying and addressing both the
systemic conservation requirements of a landscape (coarse filter), along with the idiosyncratic
conservation requirements of those species and populations whose needs aren’t met by the coarse
filter (fine filter) (Noss 1987; Hunter et al. 1988; Hunter 1991; 2005).
The coarse-fine filter concept rests on the assumption that biodiversity is hierarchical, where the
ecological requirements of many components of the lower levels in a hierarchy (e.g. species) are
nested within the ecological requirements of higher levels in a hierarchy (e.g. ecosystems). The
‘coarse-filter/fine-filter’ approach has received criticism because the spatial distribution of the
coarse-filter surrogate (ecosystem) does not necessarily reflect the distribution of lower levels of
biodiversity (Januchowski-Hartley et al. 2011), and surrogates have been criticised as not being
representative of the wide range of biota in particular systems (Andelman and Fagan 2000;
Saetersdal and Gjerde 2011), however, this assumes there is only interest in patterns of biodiversity,
and not the processes that underpin these patterns (Bennett et al. 2009). In fact addressing
processes should meet the requirements of biota that depend on these systems and this can be
done by assessing the relatively transient biotic components of systems in the context of the more
enduring abiotic elements of a system in which the biotic elements interact (Hunter et al. 1988).
Thus in the landscape assessment framework presented here, birds are used to represent landscapescale processes and interactions under the assumption that they are effective coarse-filter
surrogates.
The decision to use avifauna for Kangaroo Island is based on previous applications of the landscape
assessment approach. It is difficult to obtain useful information for most fauna that is informative
about the state and trajectory of ecological communities. Birds, on the other hand, are a visible and
relatively well-studied type of fauna in most agricultural settings. Also, in many landscapes, the
spatial scale over which terrestrial bird populations operate are comparable to the scale over which
human activities operate; thus the scale at which we define our landscapes may be comparable
between terrestrial birds and human impacts (e.g. Major 2010).
The fine filter analogy refers to those species with specific ecological requirements that cannot be
conserved by addressing systemic landscape scale issues alone. These species are commonplace in
conservation, typically being addressed through threatened species recovery programs. An example
is the very small population, for which secondary threats associated with small population sizes are
critical (Gilpin and Soúle 1986). Species that have been reduced to very small populations are
susceptible to a range of threats linked to their population size and demographic processes (such as
inbreeding depression, demographic stochasticity and genetic drift (Gilpin and Soúle 1986).
10
The external factors that influence the decline of a population are likely to vary on a case-by-case
basis but for agricultural settings they tend to be processes associated with the alteration and
fragmentation of landscapes that leads to habitat loss (Akçakaya 2001). In practice, uncommon
species need to be managed as meta-population which persist in a balance between local extinction
and colonisation (Harrison 1991). This balance is influenced by the colonisation ability of individual
species, habitat patch size and isolation, compensation effects between colonisation and extinction
rates, the effect of immigration on local dynamics (rescue effect), and heterogeneity among habitat
patches (Hanski 1991). Threatened species sometimes require specific and targeted management
interventions.
On Kangaroo Island, the Glossy-Black Cockatoo and the nationally threatened plants found on the
Eastern Plains are examples of these types of species. A key difference being that the work being
undertaken by the Eastern Plains Fire Trial (EPFT 2008) is beginning to demonstrate that the
conservation requirements of these plant species can be addressed at ecosystem and landscape
scales (coarse-filter) because of the important influence of fire regime, whereas, the Glossy-Black
Cockatoo is an idiosyncratic species with species -specific (fine filter) conservation management
needs (Mooney and Pedler 2005). Thus from a practical perspective, one of the main aims of
undertaking landscape assessment is to be able to reliably identify those small populations that have
passed through the coarse filter, so that it is possible to clearly articulate specific conservation
management requirements that cannot be addressed by management of systemic landscape level
issues alone.
2.1.1
Landscape Drivers and Resilience
In agricultural regions, such as Kangaroo Island, land use dictates the degree of removal and
modification of native vegetation, a process that is typically not homogenous across different
elements of a landscape and at regional scales (Paton et al. 1999). While the reasons for these
patterns are complex, heterogeneous modification is typically driven by variation in the nature of
the physical environment, which largely determines patterns of agricultural production in a given
landscape. As a result, particular elements of the landscape are likely to be impacted more by
human activity than other elements. Understanding these differences is an important step for
understanding which landscape attributes are associated with components of biodiversity at risk
that require conservation intervention, and what the drivers of these relationships are (Rogers et al.
2012).
Thus one of the key underlying objectives of landscape assessment is to identify key drivers of
change. Concepts about how ecosystems change in response to disturbance, external changes, or
other forms of perturbation have developed over the last 100 years but there is still no agreed upon
general conceptual framework concerning the controls on species turnover and ecosystem
development. However, over past decades there has been a noticeable shift in ecological thinking
from a focus on models based on gradual continuum dynamics to models that incorporate
trajectories, thresholds and stochasticity (or chance events) (Suding and Hobbs 2009). These ideas
are at the core of resilience theory. Resilience thinking can be applied at different levels of a
biological hierarchy but application at a landscape level can be particularly useful for identifying and
describing which landscapes are important for different reasons. The idea is to focus on describing
and evaluating the characteristics of desirable states and how information on changes in species
composition, habitat structure and ecological processes should be interpreted as evidence for
transformation to undesirable ecosystem states (at landscape scales). This then becomes a first step
towards prioritising which conversation assets need immediate attention.
11
Models that include alternative stable states are useful for predicting threshold dynamics, where a
small change in environmental conditions can cause an abrupt change in ecosystem function and/or
community structure. Being clear about feedback processes is also important because multiple
states can exist under similar environmental conditions, feedbacks influence whether a system is
maintained in a particular state, and there is no guarantee that a disturbed system will to return to
its original state once a pressure has been removed. In fact it is possible that some changes can lead
to irreversible collapse (Suding and Hobbs 2009). Thresholds are a breakpoint between two states of
a system, and a characteristic feature of a threshold is a change in system feedbacks. Resilience is a
property of systems that defines the capacity of a system to absorb disturbance and reorganise so to
retain essentially the same function, structure, identity and feedbacks. As the resilience of an
ecosystem declines, the amount of disturbance needed to cross the threshold declines (Suding and
Hobbs 2009).
King and Hobbs (2006) developed a conceptual model of ecosystem resilience (Figure 2) that
incorporates the concept of abiotic and biotic thresholds. The model shows three stages of change
(degradation), with thresholds between them that represent barriers to ecosystem recovery. As time
goes on and degradation continues it becomes increasingly difficult to restore ecosystems back to
their original state or starting point because functional thresholds have been crossed.
Figure 2. Concept of biotic and abiotic thresholds indicating breakpoints in ecosystem redevelopment from a
degraded state. In the first stage, biotic function is degraded but the system still has the capacity for
autogenic recovery if the cause of degradation is removed. If degradation continues, the first threshold of
recovery potential is crossed. This results in damage to biotic function. If the ecosystem has crossed over
this threshold and is in the second stage, some manipulation of biotic components beyond removal of
disturbance will be required for autogenic recovery to take place. Although abiotic functions may have been
degraded in the second stage they still maintain some resilience in terms of their capacity to recover
without direct manipulation. Beyond the second threshold, biotic processes are severely dysfunctional and
abiotic function has been degraded beyond its resilience. In this final stage of degradation, abiotic
components require manipulation in order to make autogenic recovery possible (from King and Hobbs
2006).
12
The application of resilience concepts is implicit in landscape assessment and is particularly
important for developing conceptual models of how landscapes and ecosystems are structured.
Resilience thinking is used throughout but was particularly important for development of the stateand-transition model (STM) presented in this study to describe Narrow-leaved mallee dynamics.
2.1.2
The Landscape State and Transition Model (LSTM)
The Landscape State and Transition Model (LSTM) framework (Cale 2007; Cale and Willoughby 2009)
is applied in this study as an analysis tool for describing broad scale drivers of change in key
landscapes. The LSTM and the matrix threshold model of McIntyre and Hobbs (1999) are
conceptually similar models of landscape change that describe relationships between remnant
vegetation and the status of landscapes. The matrix threshold model describes a simple relationship
between remnancy of native vegetation and the “state” of a landscape, with regard to its
biodiversity (McIntyre and Hobbs 1999), and includes conservation management guidelines
(McIntyre et al. 2000). It is applied in this study to describe landscape-scale patterns of vegetation
remnancy.
A limitation of the matrix threshold model is that it assumes that clearance of native vegetation for
agriculture is the only driver of state change at the landscape scale, and that the biodiversity of
landscapes within each vegetation remnant class is at equilibrium with the level of clearance impact
(i.e. it doesn’t account for the temporal nature of clearance). The LSTM approach (Cale 2007)
attempts to account for at least the former assumption, by explicitly describing the range of
important drivers that determine the state of an ecological landscape (such as fire, grazing,
hydrology and nutrient cycling, as well as clearance), and attempts to apply this reasoning at both
the scale of the landscape, and to the patch. This approach has been applied in a case study of the
South Australian Murray-Darling Basin NRM region (Cale and Willoughby 2009). While it does
provide a description of the dynamics of ecological landscapes (and their response to modification)
more explicitly, it is still based on general principles, such as those regarding remnancy. Thus further
conservation planning is still required to increase understanding of the state and drivers of specific
conservation assets (i.e. ecosystems and species) within landscapes. The LSTM is applied in this
study to describe broad differences in key Kangaroo Island landscapes at a regional scale.
2.1.3
Ecosystem Definition
An important biological unit assessed in this study of Kangaroo Island is the ecosystem (synonymous
with the ecological community). In practice, the terms ecosystem and ecological community are
often used interchangeably and the scientific literature includes different definitions of ecosystems.
Despite some nuances, a key concept applicable to ecosystems is to explicitly recognise the link
between biotic and abiotic components (Keith 2009). In South Australia, recent consultation with a
range of ecologists and land managers interested in the management of threatened ecological
communities has led to the following description of an ecosystem that can be broadly applied to the
work presented here - a geographically distinct assemblage of interacting native species and their
associated abiotic environment (Bonifacio and Pisanu 2013).
Classifying ecosystems can be done on the basis of characteristic native biota, associated physical
environment, processes and interactions between components and spatial extent. Characteristic
native biota are also commonly used when describing ecological communities, along with structure
and or habitat, whereas relatively few community descriptions address species interactions or other
ecological processes and functions (Keith 2009; 2012). Descriptions of ecosystems are scaledependent in terms of spatial, temporal and thematic scales, and they can vary greatly. Thematic
scale refers to the similarity of features within and between ecosystems, and their degree of
13
uniqueness in composition and processes. An ecosystem can appear stable at some temporal scales,
while undergoing trends and fluctuations at others (Keith et al. 2013).
South Australian ecological communities have previously been described largely on the basis of
floristic and vegetation structural features, with limited explicit focus on the inherent physical
environments that drive much of ecological variation. An example is the floristic classification used
as the basis for mapping vegetation on Kangaroo Island (Robinson and Armstrong 1999), which still
forms a base layer for many management decisions. This approach reflects widely applied
conventions for classification, naming and mapping of vegetation types, which focus strongly on the
description of structural or physiognomic attributes of vegetation and vascular plant species
composition(e.g. Benson 2006). The focus on ecosystems presented here does represent a
departure from conventional vegetation identification and mapping to some degree, but it is still
possible to make clear linkages between the vegetation types typically used in NRM for management
and the important underlying abiotic conditions and biological processes that drive change used to
define ecosystems.
2.2
Kangaroo Island Land Use History and Impacts on Natural Systems
An important aim of landscape assessment is to develop an understanding of how historical land use
has influenced, and continues to influence the composition, structure and function of ecosystems
within particular landscapes. Finding accurate, detailed and spatially-explicit data on land use is
challenging, as it is often general, specific to particular enterprises or issues, or has simply not been
recorded. Thus the overview presented here is meant to provide context for interpreting more
detailed data where it exists, and as background for interpreting current observed patterns in
landscapes.
European discovery and early exploration of Kangaroo Island by Matthew Flinders (Investigator) and
circumnavigation by Nicholas Baudin (Le Geographe) resulted in mapping and naming of a number of
coastal locations. Sealing was the first industry on KI, established by an American expedition in the
Union at American River. By 1880 the last major shipment of fur-seal skins occurred due to
widespread depletion of seal numbers (Robinson 1999). A number of key historical events have since
driven land use change on Kangaroo Island (Figure 3). These mainly relate to land clearing for
agricultural production. Today, approximately 60% (or 230,370 ha) of Kangaroo Island is utilised for
agriculture, with dryland agriculture the predominant land use, principally sheep grazing for wool
and meat. Cropping and beef cattle are the next most significant industries and new industries have
emerged since the mid- 1990s – primarily farm forestry, viticulture, horticulture (including seed
potatoes), apiary and other minor livestock enterprises (Dohle 2007). In 2002/03 the value of major
industries to the Kangaroo Island economy were $54.6 million (grazing), $10.8 million (cropping),
$7.6 million (commercial fishing) and $53 million (tourism) (Gellard 2005).
Cropping increased substantially from 8,000 ha in 1991 to 19,000 ha in 2011/12 (Dohle 2013). The
key crops grown on the island are cereals (mainly wheat, barley and oats), canola and pulses (broad
beans, lupins and peas), and cropping includes continuous cropping and mixed livestock/cropping
enterprises. Cropping has the potential to increase the risk of a number of adverse land degradation
impacts, such as soil erosion, soil acidity, water logging, salinity, fire risk (due to stubble burning) and
fertiliser spray drift, which may have secondary impacts on remnant native vegetation (Dohle 2013).
Land clearing associated with cropping tends to target isolated paddock trees which may reduce
connectivity (e.g. stepping stones) between more substantive vegetation remnants for some native
species (Lindenmayer and Fischer 2006).
14
1802
Early exploration of KI coastline (Matthew
Flinders Investigator; Nicholas Baudin Le
Geographe)
Sealing – sea lion & fur seal
1836
KI settlement at Kingscote
Most settlers return to mainland by 1840
1880
Sealing ceases
Clearing of Eastern Plains commences
Land clearance, changed fire regime
1919
Flinders Chase National Park proclaimed
Soil deficiencies limit sheep and crop
production – cobalt, copper
1923-25
18 koalas introduced to the island
1930s
CSIRO solves ‘coast disease’
1950s
Post WW2 land improvement and soldier
settlement schemes
KI population doubles; agricultural
production trebles
1969
Present broad acre clearance pattern
established island-wide
1971
Cape Gantheaume Conservation Park
proclaimed
1985
Native Vegetation Act 1985 gazetted
1991
Cereal cropping = 8,000 ha
Soil enrichment and superphosphate fertiliser
application increases
Major clearing of land – Central Plateau
Native Vegetation Act 1991 gazetted
Large-scale land clearing ceases
Dryland(secondary) salinity estimated at
5,600 ha
Salinity impacts mainly on drainage lines and
flats of Eastern Plains
Phytophthora cinnamomi plant pathogen
detected on KI
Potential impacts on Eucalyptus,
Xanthorrhoea, Banksia and Grevillea.
1997
Koala population estimated at 5000
Widespread defoliation of KI Stringybark
woodlands
2001
Koala population estimate revised to 27,000
Koala control program commences
2008
Eastern Plains Fire Trial commences
2011-12
Cereal cropping = 19,000 ha
1993
Cropping increases risks of salinity, fertiliser
drift, soil acidification & erosion
Figure 3. Timeline of major historical events linked to land use change on Kangaroo Island.
15
Other factors that have significantly influenced the status of biodiversity on Kangaroo Island include
proclamation of large protected area reserves such as Flinders Chase National Park in 1919, the
introduction of koalas to the island in 1923-25, and the establishment of the South Australian Native
Vegetation Act 1991, which saw the cessation of broad scale land clearance (Figure 3).
The history of change for the early settlement period (yellow band: 1802 to late 1940s) is incomplete
but it assumed that ecosystems on the island began to change gradually as agriculture expanded.
The red zone between the late 1940s to the early 1990s represents a period of intensive change in
natural systems associated with improved technologies, increased settlement and higher rates of
agricultural production. A key limitation prior to this period was the constraint on agricultural
production posed by soil deficiencies. CSIRO ultimately found a remedy for ‘coast disease’ in the
1930s.
The subsequent introduction of superphosphate fertilisers, subterranean clover and minerals to
address soil deficiencies (cobalt, zinc and some trace elements)(Robinson 1999) boosted agriculture.
A further renewed push for settlement occurred after Second World War due to incentives for rural
subdivision from government sponsored land improvement and soldier settlement schemes (1947
onwards) (Mooney and Grinter 2000; Dooley et al. 2002). The 1930s-40s resulted in increased
primary production and agricultural development, including intensive clearing of the Central Plateau
around Parndana. By the 1950s Kangaroo Island’s population had doubled and agricultural
production had tripled (Robinson 1999).
Native vegetation remained relatively intact until 1945 but by 1969 the clearance pattern across the
island resembled what it does today (Robinson 1999). The consequences for native vegetation has
been a progressive change in cover and in the most extreme cases, such as found on the eastern
part of the island, fragmentation of large areas. Broad-scale land clearing has ceased since the
introduction of South Australian clearance legislation (Native Vegetation Management Act 1985)
and subsequent amendments resulting in the Native Vegetation Act 1991 (Figure 3).
16
3 METHODS
3.1
Approach
The key concept in ‘landscape assessment’ is that particular ecosystems have been subjected to
particular historic processes and these processes, coupled with the abiotic context or setting in
which they occur, shape how ecosystems function. It is assumed that where a group of species that
are commonly associated with a particular ecosystem are undergoing similar rates of decline, these
declines can be attributed to a systemic issue (or set of issues) affecting the ecosystem itself. Thus by
identifying the systemic issues commonly impacting on declining species (identified by measuring
their trajectory of change), conservation goals can be designed to explicitly address the systemic
issue.
In practice, landscape assessment relies on the synthesis of landscape-specific information regarding
the nature of ecosystems in the landscape; status and trend of species in the landscape; and
environmental (and particularly land-use) history of the landscape. The integration of this
information allows for identification of patterns of association between the ecological (and
particularly ecosystem) requirements of species and their state and historic trajectory (Rogers et al.
2012).
For Kangaroo Island, the landscape assessment essentially comprised four analytical components:
5. Define and spatially represent the landscapes of Kangaroo Island;
6. Identify island-wide drivers of landscape change with respect to biodiversity;
7. Identify where each landscape “sits” relative to these landscape-scale drivers, in order to
identify the relative resilience of different landscapes; and
8. Target ecosystem-level analyses toward those landscapes that appear to be approaching or
have crossed critical thresholds with respect to landscape-scale drivers (as these landscapes
appear to be those that require some of kind of intervention to achieve island-wide nature
conservation outcomes).
The landscape assessment utilized a range of spatial data and survey data sources. The main GIS
layers (SA EGIS data) included geology, topography, soils, rainfall, fire mapping and native vegetation
cover. The biotic components of landscapes and ecosystems were analysed using two key survey
datasets from the Biological Survey Databases of South Australia (BDBSA). Floristic survey data that
have been collected using the standard survey design employed by the SA Biological Survey (Heard
and Channon 1997) formed the basis for assessing ecosystem types. This dataset included all flora
records that were collected on Kangaroo Island and stored in BDBSA. Variation in floristic
composition was analysed using cluster analysis. Kangaroo Island bird data was obtained from the
BDBSA in September 2013, and included all bird records that were collected on Kangaroo Island and
stored in BDBSA between 1901 and 2013.
All statistical analyses were performed using R-project for statistical computing for windows version
2.15.1 for windows (R Development Core Team 2008).
17
3.2
Landscapes
3.2.1
Landscape Description
For the purposes of this analysis, landscapes were defined as contiguous areas with common
biophysical and ecological features, whereby the relationship between the physical and ecological
features was consistent, and where the response to key drivers was relatively consistent. The
analysis largely precluded the differential impacts of post-colonial land-use history on landscape
definition because of insufficient detailed and spatially explicit historical information.
In order to create a common set of spatial boundaries, landscapes were spatially described by
attributing each polygon in the soil landscape layer with the following additional information:

Slope Class. Derived from the average slope across the polygon, which was calculated using
the NASA SR-DEM (30m horizontal resolution). This average slope was then classified
according to Australian Soil and Land Survey classification (National Committee on Soil and
Terrain 2009).

Relief Class. Derived from the minimum and maximum elevation across the polygon, which
was calculated using the NASA SR-DEM (30m horizontal resolution). The difference between
the minimum and maximum elevation (the relief) was then classified according to the relief
classification of the Australian Soil and Land Survey(National Committee on Soil and Terrain
2009).

Surface Geology. Derived from the Surface Geology layer. The existing geological
classification was reclassified (based on geological age and description) to produce
ecologically relevant surface geology.

Rainfall. Derived from the Mean Annual Rainfall (MAR) model generated by ANUCLIM, using
the NASA SR-DEM (30m horizontal resolution). The modelled MAR for each pixel was
averaged across each soil polygon, and this average value was then classified to one of three
rainfall classes: <600mm (Low), 600-750mm (Medium), and >750mm (High).
Based on these four environmental features, polygons were attributed to the same landscape based
on common patterns of geology, topography and rainfall. The landscape definitions that came from
this did not necessarily have uniform physical features; rather, the patterns of variation within
landscapes (environmentally equivalent to β-diversity (Anderson et al. 2011) were consistent relative
to patterns of variation between landscapes.
For practical reasons, the final landscapes used in this analysis were also required to be spatially
contiguous, and be large enough in extent to warrant further within-landscape analyses, should it be
required.
3.2.2
Landscape Analysis
Following the definition of landscapes for Kangaroo Island, an assessment of each landscape was
undertaken to determine if they are operating within acceptable limits in terms of their capacity to
support dependent native biota. The application of the LSTM framework to Kangaroo Island was
based on the following steps to assess landscape state and key ecological thresholds for each
landscape:
1. Identify region-wide ecological drivers considered to be of primary importance to how
landscapes function;
18
2. Identify the “position” of each landscape relative to key thresholds for each of these drivers
(e.g. where a landscape sits relative to generally-derived remnancy thresholds);
3. Describe management recommendations for each landscape, including where more detailed
analysis (at ecosystem level) is required.
The outcome of step 3 informed the prioritisation of subsequent within-landscape analyses (that
typically comprise the Landscape Assessment process). The information sources used to identify key
thresholds for important drivers were dependent on the nature of these drivers.
3.2.2.1
Fire Regime
A landscape-level evaluation of fire regime was undertaken based on thresholds for the upper and
lower limits of the “acceptable “ fire regime, outlined in the Ecological Fire Management Guidelines
for South Australian native vegetation (DENR 2012). These guidelines were applied to the Major
Vegetation Sub-groups (MVS) found in each landscape (Table 1.). However, because the guidelines
are based on a relatively small set of fire sensitive plant species there is little variation in the upper
and lower thresholds for fire frequency across major vegetation types. Thus we have used a
consistent upper threshold of 50 years, and lower threshold of 20 years, for all landscapes across the
island.
3.2.2.2
Landscape level patterns of clearance of native vegetation
For each landscape, an assessment of the proportion of the landscape that was mapped as remnant
native vegetation was undertaken. This assessment was initially evaluated in the context of existing,
generic thresholds for native vegetation of landscapes, particularly focussing on the 30% cover
threshold. A number of authors have suggested that if native vegetation cover in a landscape falls
below 30%, critical habitat functions for dependent flora and fauna are compromised (McIntyre and
Hobbs 1999; Radford et al. 2005). However, the actual threshold for cover will depend on the
requirements of the particular biota that depend on a system, and how different drivers (e.g. fire
and fragmentation) interact to impact on these requirements (Cale 2007).
3.3
Ecosystems
For landscapes that appear to approaching or have crossed critical ecological thresholds (as
identified in the assessment of landscapes described above), an assessment of the state and
trajectory of ecosystems within these landscapes was undertaken. This assessment was designed to
determine if the systemic issues associated with landscapes at risk are related to drivers and impacts
that are associated with particular ecosystems.
3.3.1
Ecosystem Assessment
3.3.1.1
Defining ecosystem types
The description of Kangaroo Island ecosystems combines key physical drivers that are the primary
determinant of an ecosystem’s distribution, and a description of the “typical” or “best remaining”
floristic community that occurs in association with those key physical drivers. As with the definition
of landscapes, the key physical drivers that determine the distribution of ecosystems on Kangaroo
Island are geology, soil type, and rainfall. Topography also plays a minor role in some cases, such as
for alluvial and drainage systems.
19
An analysis of existing floristic survey data was undertaken to quantitatively describe the different
ecosystems of Kangaroo Island. This analysis investigated variation in floristic species composition
among survey sites using hierarchical cluster analysis, using the “Jaccard” dissimilarity index and the
“mcquitty” agglomeration method. This analysis was populated with an estimate of percent cover
for each species at each site (taken from the survey dataset). Cluster analysis was implemented
using ‘R’ statistical software, within the ‘vegan’ package.
Based on the outputs of this analysis, ecosystems were defined based on the common physical
attributes of the patches that occurred within clusters. The relationship between floristic similarity
and physical attributes was done visually using the cluster outputs, with each patch attributed with
its physical features. The physical features that were used to define ecosystems were soil type
(taken from the DSM model), geology (1:50k mapping), rainfall, slope, relief and landscape (defined
above).
3.3.1.2
Ecosystem level patterns of native vegetation clearance
As with the analysis of vegetation clearance at the landscape level, an analysis of vegetation
clearance patterns in relation to the ecosystems of landscapes at risk was undertaken. This was done
on the basis of the spatial information for the key physical drivers identified for the ecosystem
definition (see above), overlayed with the mapped remnant native vegetation. The results of this
analysis then provided insight regarding the drivers of change to biodiversity at the ecosystem level,
that was used in combination with other indicators (in particular, changes in the status of terrestrial
birds and their association with different ecosystems).
3.3.1.3
Trends for Terrestrial Birds
A key step in ‘landscape assessment’ is to determine the relative state and trajectory of different
landscapes and ecosystems. In the past, this has been achieved by relating the state and trajectory
of different terrestrial bird species, with their common ecological requirements, to determine the
most parsimonious solution to patterns of state and trajectory among birds. They key assumption
here is that if species that are commonly associated with a particular ecosystem also share
similarities in their current state and historic trajectory, we can infer that this common state and
trajectory is in some way related to the dynamics of the ecological requirements (particularly
habitats or ecosystems) that they are commonly associated with (Rogers et al. 2012).
In order to determine the status and trajectory of terrestrial bird species within the landscapes of
Kangaroo Island, three analyses based on the historic and recent bird records of Kangaroo Island
were applied. These analyses were constrained by the available records from the BDBSA and
availability of expert knowledge and the outcomes of these analyses may be improved should
additional datasets become available. The three analyses were:
a. Difference in distribution between all-time, and “current” records, where current
included all records that were collected after 1994 (method adapted from Franklin
(1999)).
i. The occurrence of bird species in each 100 ha polygon on Kangaroo Island
was denoted for the period 1995-2013 (the recent period), or 1901-2013
(all-time). The degree of change between recent trends and all-time trends
was then calculated as the proportion of hexagons in which a species was
recently recorded (≥1995), compared to the number of times it had been
recorded over the entire survey period (1901-2013). This analysis excluded
20
species with <10 records and/or those that had been recorded in <5
hexagons.
b. Change in relative distribution through time, using linear regression between Year
and Proportion of cells occupied.
i. Linear regression was performed on the proportion of GIS mapping cells
(hexagons) that were occupied by each species per year. Species were
identified as declining in this analysis if the results of the regression
indicated p values of <0.1, and a negative slope value.
c. Expert Model (species status assessment)
i. Expert scores of KI species ‘status’ and ‘trend’ (Gillam and Urban in prep.)
were used to identify declining birds. Species were given the following
‘status scores’ based on their assigned conservation status: Extinct=6,
Critically Endangered=5, Endangered=4, Vulnerable=3, Rare=2, Near
Threatened=1, Least Concern or Data Deficient=0. Species trends were
scored as: definite decline=-2, probable decline=-1, stable=0, probable
increase=+1, or definite increase=+2.
ii. Status and trend scores were combined to calculate an overall threat score:
0-1 = Least Concern, 2 = Rare but Stable, 3 = Widespread but Declining, 4 =
Rare and Declining, 5 = Extinct (locally). Species that were assigned a threat
score of 3 or 4 were identified as declining in this analysis.
The results of these three analyses were used to calculate an overall ‘threat category’ for each
species based on the number of analyses in which they were identified as declining (or not
declining):
1. Threat Categories:
0. not identified as declining in any analyses
1. identified as declining in one analysis
2. identified as declining in two analyses
3. identified as declining in all three analyses.
Species were assigned an overall ‘declining’ status if they were identified as declining in at least two
of the three analyses.
In addition to analysing state and trajectory of terrestrial bird species, a qualitative assessment of
the requirements of terrestrial bird species, in the context of the ecosystem analysis, was also
undertaken. This was done by using ornithological expertise and literature (e.g. Handbook of
Australian, New Zealand and Antarctic Birds series). This allowed species to be assigned to “response
groups” (Rogers et al. 2012), where species were assigned to groups based on their common
ecological requirements.
21
4 RESULTS
4.1
Landscape Identification and Description
For the purposes of this assessment, three landscapes were defined for Kangaroo Island: 1) West
and South Coast, 2) Central Plateau and North Coast, and 3) Eastern Plains and Dudley (Figure 4).
The primary discriminating features of these landscapes are their underlying geological patterns,
together with rainfall and topography. Geological features are a primary determinant of soil
properties, and soils can have a strong influence on the distribution and composition of ecological
communities.
The West and South Coast landscape is comprised of a coastal band that runs south from Cape
Borda, along the entire south coast, almost as far as Cape Willoughby (a total area of 965 km2). The
West and South Coast landscape also incorporates the entire ismuth between the Dudley Peninsula
and main body of the Island. This landscape is dominated by Pleistocene calcrete that was formed as
marine sediments during periods of high sea level. Along with this calcrete, recently deposited (and
often active) Holocene marine sands are prominent. These near coastal environments largely
support a range of coastal mallee and shrublands that are typical of these environments in other
areas of the state (e.g. Eyre Peninsula and Yorke Peninsula).
The Central Plateau and North Coast landscape is comprised of the higher elevation plateau of
Kangaroo Island, and includes the entire north coast between Cape Borda and west of Emu Bay (a
total area of 2,011 km2). This landscape is dominated by ironstone soils derived from Tertiary
weathered materials. These Tertiary materials overlay Cambrian sedimentary materials that are
expressed at the surface along areas adjacent to the north coast. Due to the erosional nature of
these higher rainfall elevated environments, the Central Plateau and North Coast landscape is
dissected by a number of drainage lines and narrow depositional areas that fan out to form the
deeper depositional soils onto adjacent areas of the Eastern Plains and Dudley Peninsula.
The Eastern Plains and Dudley landscape is comprised of the lower elevation depositional areas of
Kangaroo Island. The geology and soils of this landscape are complex relative to the other
landscapes of Kangaroo Island, but are largely dominated by the deposition of eroded soils from the
Central Plateau (in the western parts of the landscape), along with a large number of lacustrine
environments. The northern Dudley Peninsula contains Tertiary ironstone that is similar to the
Central Plateau environment, although with lower rainfall. Other notable environments of the
Eastern Plains and Dudley landscape include the igneous rises west of Kingscote that form the
Wisanger Hills.
22
Figure 4. Map of Kangaroo Island highlighting the boundaries of the ecological landscapes used in this assessment. Blue= West and South Coast; Red = Central Plateau
and North Coast; Green = Eastern Plains and Dudley.
23
4.2
Key Ecological Drivers on Kangaroo Island
Consideration of broad patterns of historical land use change and interpretation of empirical data where it was
available indicates that a number of key drivers appear to operate at the landscape scale, and/or at the scale of
individual patches of remnant vegetation. These probably determine the state and trajectory of the majority of
biota at these two scales. At the landscape scale, the key drivers identified were:

fire regime;

conversion of native vegetation cover for agricultural production; and

population processes (particularly meta-population dynamics).
In addition, a number of key drivers were identified that specifically relate to the dynamics of patches of
remnant vegetation (noting that these drivers in turn can be derived from landscape-scale processes):

grazing of remnant patches; and

changes to physico-chemical processes (particularly dryland salinity).
The logic framework of the Landscape State and Transition model (LSTM) is described above. Using this logic
framework, critical ecological thresholds for the key drivers identified above were described, and the current
state of the landscapes of Kangaroo Island, relative to these thresholds, was determined. The relationship
between these thresholds and the current state of Kangaroo Island’s landscapes is presented graphically in
Figure 8. The justification for this pattern is described below for each key driver.
4.2.1
Fire Regimes
The pattern of fire across Kangaroo Island (equivalent to the current mosaic) for each landscape varies across
the island and between different landscapes (Figure 5). This pattern shows that at a coarse level fire is a
relatively infrequent occurrence in the Eastern Plains Dudley landscape, manifests as a gradient from relatively
frequent fires in the west to fewer fires in the east of the Central Plateau and North Coast landscape, but is
relatively common and close to evenly spread within the West and South Coast landscape.
For each landscape, the average and current area within each decadal fire-age class was calculated, and
compared with the critical thresholds identified for the dominant ‘Major Vegetation Subgroup’ MVS in each
landscape (Table 1). The distribution of landscape area among these fire interval classes varied depending on
whether the average fire interval or the current fire interval (i.e. time since last fire) is used as a measure of fire
regime.
West and South Coast
The current fire interval for the West and South Coast (Figure 6) is skewed toward early fire-age classes, with
58% of native vegetation in the landscape having burnt in the last 20 years (<TPC1 for the dominant MVS in this
landscape (Table 1). This skewness is driven by the recent large-scale wildfires across the intact, western end of
Kangaroo Island. About 23% of native vegetation is currently within the acceptable fire interval range for the
dominant MVS. However, given the requirement for ~30% of the MVS to have fire intervals less than the upper
threshold, means the West and South Coast does not appear to contain enough area of older habitats (18%).
This suggests that the requirements of plant species dependent on older seral stages (fire age classes) may be at
risk.
The average fire interval (based on the number of fires recorded since 1931) for the West and South Coast is
dominated by older fire-interval classes, with 68% falling within the ‘acceptable’ thresholds for fire interval (2050 years), and another 30% having fire intervals greater than the upper threshold (TPC2, 40 years). Across the
24
landscape, only 1% of native vegetation has an average fire interval threshold of less than 20 years, suggesting
that, while the recent (e.g. 2007) wildfires have placed large areas of the landscape in a young seral age class,
over the past 81 years the average fire frequency is generally not higher than the acceptable thresholds for the
dominant vegetation communities.
Central Plateau and North Coast
As with the West and South Coast landscape, the current fire interval for the Central Plateau and North Coast
landscape is skewed toward early fire-age classes (58% burnt in the past 20 years, Figure 6), again with this
pattern driven by recent large-scale wildfires across the intact, western end of the landscape. In addition, 33% of
the native vegetation of the landscape currently occurs in fire interval classes greater than the upper threshold,
again suggesting that the requirements of species dependent on older seral ages are currently being met. Only a
small proportion of native vegetation (9%) is currently within the acceptable thresholds for fire interval (20-50
years). Furthermore, the distribution of fire interval classes is currently distributed non-randomly across the
landscape, with older seral classes dominating the eastern end of the landscape, while younger seral classes
dominate the western end of the landscape.
Eastern Plains and Dudley
The current distribution of seral classes in the Eastern Plains and Dudley landscape is heavily skewed toward
older age classes. While 25% of native vegetation in the landscape has burnt in the last 20 years (i.e. is younger
than the recommended lower threshold), 66% was last burnt more than 50 years ago (older than the
recommended upper threshold). Thus just 7% of the native vegetation of the landscape current exists within the
acceptable thresholds (Figure 6). This pattern of dominance by long fire interval classes in the landscape is
further demonstrated when looking at average fire interval over the last 81 years. Across the 81 year period for
which fire history data are available, 76% of native vegetation has an average fire interval greater than the
recommended upper threshold (i.e. an average fire interval of >50 years; Figure 7). Only 23% of native
vegetation has an average fire interval within the acceptable thresholds.
25
Figure 5. Distribution of current fire interval across the native vegetation of Kangaroo Island. The ecological landscape boundaries used for the purpose of this analysis
are presented in relation to this fire regime.
26
MVS
Name
Area
Central Plateau
Eastern Plains
TPC1: Lower threshold in
years
TPC2: Upper threshold in
years
Inter-fire intervals within
TPC1 & TPC2 cross more
than X% of the extent of
of the
MVS
Percentage
the
this MVS within
stay > TPC2
to
area
planning
Avoid more than 2 fires
within a period of X
years
Avoid more than 2
successive
fires of low intensity
(Yes/No)
Some medium to high
intensity fire needed to
regenerate some species
(Yes/No)
Interval
Spatial
Criteria
Frequen
cy
Intensity
Season
8
Shrubby
Eucalypt
woodlands
1,529
39,086
6,868
20
50
40
30
40
Y
Y
Spring or
during
&
following
drought
26
Casuarina
woodlands
-
1,002
-
20
50
40
30
60
N
N
During &
following
drought
29
Mallee
shrublands
76,01
3
49,472
15,49
2
20
40
40
30
40
Y
Y
Spring or
during
&
following
drought
47
Shrubby
open
Eucalypt
woodlands
-
13,045
1,017
20
50
40
30
60
N
N
During &
following
drought
49
Melaleuca
shrublands
-
-
2,037
20
60
40
30
70
N
N
Spring
Avoid more than 1
successive
fires in season
MVS
West & South Coast
Table 1. Ecological Fire Management Guidelines for fire-prone Major Vegetation Sub-groups (MVS) on Kangaroo Island.
Fire-prone MVS were included in this list if >1,000 ha occurred in any one landscape. Two MVS (Chenopod shrublands,
and Other shrublands), both of which are found on Kangaroo Island, were excluded from this table as they are not
considered fire-prone, and therefore do not have acceptable fire regimes presented in the EFMG (DENR 2012).
27
Current Fire Interval
Average Fire Interval
Figure 6. Distribution of native vegetation by fire age classes (seral stages) for the three ecological landscapes of
Kangaroo Island. Proportion (y-axis) of the area of native vegetation in different fire interval classes (x-axis). The current
fire interval (years since last fire) are presented in the left column, the average fire interval (average years/fire, for period
since 1931) are presented in the right column. The data for each landscape are colour coded: West and South Coast =
green; Central Plateau and North Coast = blue; Eastern Plains and Dudley = red. Recommended acceptable limits for fire
interval are bounded by red boxes for each chart.
28
4.2.2
Landscape level patterns of clearance of native vegetation
West and South Coast
The West and South Coast landscape can be considered Variegated-Intact (McIntyre and Hobbs 1999) (Figure 8),
with 85% of the landscape mapped as native vegetation. The low level of fragmentation in this landscape is due
to the dominant soil types, which are highly calcareous calcrete or sand, being unsuitable for agriculture (Hall et
al. 2009).
Central Plateau and North Coast
Across the Central Plateau and North Coast landscape 54% of the landscape is mapped as native vegetation, and
is considered Fragmented-Variegated (McIntyre and Hobbs 1999) (Figure 8). However, vegetation clearance is
not evenly distributed across the landscape, with the majority of remnant vegetation being distributed at the
western end. This uneven distribution of vegetation clearance is largely historical. The ironstone soils of the
Plateau were considered unsuitable for agriculture until the end of the Second World War, and were only
cleared for agriculture from that period. However, the Flinders Chase National Park was proclaimed in 1919,
prior to the large wave of post-war vegetation clearance, and was thus protected from this period of clearance.
Eastern Plains and Dudley
The remnant vegetation of the Eastern Plains and Dudley landscape is fragmented (McIntyre and Hobbs 1999)
(Figure 8) with only 27% of the landscape mapped as native vegetation. The remaining vegetation typically
occurs as small isolated remnants, although a significant proportion of this mapped vegetation occurs on
roadsides.
4.2.3
Other drivers
The remaining key drivers particularly relate to the dynamics of remnant vegetation patches (particularly
grazing, and physico-chemical changes). These were considered to be particularly relevant in discriminating the
current state of the Eastern Plains landscape from the Central Plateau and West and South Coast landscapes.
The key physico-chemical driver for the Eastern Plains is dryland salinisation, which in turn is driven by
catchment-scale historic clearance of native vegetation (Robinson 1999). Soil salinisation within some remnants
on the Eastern Plains is leading to the transformation of historic vegetation communities (e.g. mallee
woodlands) to saline-tolerant communities (e.g. those dominated by samphire species and cutting-grass).
Patches that cross thresholds relating to the nature of the physico-chemical environment (particularly in relation
to dryland salinisation) are often considered irreversible, and as such management is often considered in
relation to facilitated transformation based on these new physical conditions, rather than restoration of
previously existing conditions and biotic communities (Standish et al. 2009).
As with dryland salinisation, grazing impacts within remnant vegetation are particularly prevalent in the Eastern
Plains and Dudley landscape.
29
Figure 7. Current distribution of remnant native vegetation on Kangaroo Island (Source: DEWNR EGIS Dataset).
30
Figure 8. Conceptual model of the three landscapes of Kangaroo Island, relative to key thresholds associated with
landscape-scale and patch-scale drivers of ecological change.
4.2.4
Landscape Analysis – Summary
The West and South Coast landscape appears to be largely operating within acceptable limits with regard to the
key ecological drivers identified (Figure 8), although the recent large-scale wildfires suggest that consideration
should be given to develop a more diverse fire age distribution across this landscape. The Central Plateau
landscape is operating across a range of alternate states with regard to landscape-scale drivers, reflecting the
variable land-use history of this landscape. While much of the landscape appears to be operating outside of
acceptable limits with regard to fire regime, the interaction between fragmentation and land tenure (i.e. native
vegetation on public versus private land) suggests that the fire regime in parts of the landscape may involve too
frequent fire, while the fragmented eastern areas of the landscape appear to currently have a fire regime that is
less frequent than desired (DENR 2012). The Eastern Plains and Dudley landscape appears to have crossed both
the fire regime and fragmentation thresholds at the landscape scale, suggesting that the current regimes will
lead to species decline and local extinction if not addressed. However, recent evidence from the Eastern Plains
Fire Trial suggest that, due to the persistence of soil seed banks, population processes for many species have not
yet broken down, as there appears in many cases to be adequate propagule banks to facilitate recovery, should
these other processes be restored (Davies et al. 2013).
31
4.3
Ecosystem Assessment
4.3.1
Ecosystem Descriptions
Based on the outcomes of the landscape-level assessment described above, the ecosystem-level assessments
subsequently undertaken focused primarily on the Central Plateau and Eastern Plains landscapes. However, an
initial analysis to describe the ecosystems of Kangaroo Island (with respect to both their physical and biotic
components) was undertaken for the entire island.
This analysis identified 12 broad ecosystems for Kangaroo Island. The key physical determinants of ecosystems
were the landscape within which the ecosystem was typically found (which, in turn reflects the broad geology
and climate drivers of the ecosystem – see landscape descriptions above), and, within landscapes, the soil types
upon which the ecosystem was typically found. The 12 ecosystems used in subsequent assessments are listed
below. The estimated distribution of soil types associated with the ecosystems listed in this document is shown
in a series of maps in Appendix 1. The detailed descriptions of soil subgroups can be found in Hall et al. (2009).
For each map, the shade of blue indicates the proportion of a soil landscape unit (SLU) polygon that is made up
of the soil types of interest (light blue = <30%; med. blue = 30-60%; dark blue = >60%), and lists the vegetation
types typically associated with the soil type. The mapping provides a general representation of the distribution
of environmental settings that have the potential to support different ecosystems. As such it is analogous to a
prediction of potential habitats at landscape scale. There may be finer scale drivers that override the predictions
based on soil types, thus field data could be used to identify finer scale relationships between vegetation
communities, soils types and landforms to improve the resolution of the mapping.
West and South Coast
1. Eucalyptus diversifolia ± E. rugosa over Melaleuca lanceolata / Orthoxanthus multiflorus, on Shallow Soils
over Calcrete.
2. Near coastal shrubland (Olearia axillaris, Leucopogon parviflorus, Carpobrotus rossii) ± E. diversifolia, on
Deep Carbonate Coastal Sands and/or Shallow Soils on Calcrete near high energy coastlines.
Central Plateau and North Coast
1. Allocasuarina verticillata open woodland, on Shallow Soil over Rock and/or occasionally Acidic Sandy Loams
over Rock.
2. Eucalyptus cladocalyx over shrubland on Acidic Sandy Loams over Rock.
3. Eucalyptus baxteri ± E. cosmophylla over closed shrubland on Ironstone and/or Acidic Sandy Loams over
Rock.
4. Mixed closed shrubland on Ironstone and/or Acidic Sandy Loams over Rock.
5. Riparian shrublands (Melaleuca gibbosa, Leptospermum continentale) and woodlands (Eucalyptus viminalis)
along drainage lines.
Eastern Plains and Dudley
1. Eucalyptus cneorifolia over mixed shrubland (Melaleuca uncinata) on a variety of soil types (predominantly
Acidic Sandy Loams over clay).
2. Riparian shrublands along drainage lines.
3. Fringing vegetation of freshwater wetlands (Juncus pallidus, Melaleuca gibbosa, Callistemon rugulosus),
4. Low shrublands (Sarcocornia spp., Melaleuca oppositifolia) associated with Saline wetlands.
32
This analysis also identified some data gaps, particularly with respect to the relationship between soil type and
vegetation type on the Eastern Plains. While a diversity of soil types occurs on the Eastern Plains, the floristic
data suggest low diversity with respect to terrestrial ecosystems (in this broad analysis, one terrestrial
ecosystem was identified for this landscape). However, observations suggest soil variation can promote floristic
differences. This may require further analysis to broaden our understanding and guide restoration.
4.3.2
Ecosystem level patterns of native vegetation clearance
As our descriptions of ecosystems were closely related to soil type, our analysis of vegetation clearance at the
ecosystem level was done using the proportion of a mapped soil type that was mapped as native vegetation
within each of the priority landscapes (i.e. excluding the West and South Coast landscape). The results of this
analysis are presented in Table 2.
Table 2. Area and proportion of remnant native vegetation for the dominant soil types in the priority
landscapes of Kangaroo Island.
Central Plateau and North Coast
Soil Type
Total Area (hectares)
Vegetation Remnancy (%)
Ironstone
83,041
38.9
Acidic Sandy Loam over Rock
76,594
62.4
Drainage Lines
15,745
82.6
Shallow Soil On Rock
5,127
79.4
Soil Type
Total Area (hectares)
Vegetation Remnancy (%)
Ironstone
45,084
15.8
Acidic Sandy Loam over Rock
26,052
38.0
Drainage Lines
16,061
20.7
Deep Siliceous Sands Over Clay
12,193
26.4
Wet Saline Soils
7,315
46.4
Eastern Plains and Dudley
For the Central Plateau, a pattern of preferential clearance appears to have focused on those ecosystems
associated with Ironstone Soils, where remnancy is 38.9%. This compares with the remnancy of the shallower
terrestrial soils (Acidic Sandy Loam over Rock – 62.4%, Shallow Soils over Rock – 79.4%), and the riparian
systems (82.6%). This preferential removal of vegetation is strongly associated with the Eucalyptus baxteri
/closed shrubland systems that are concentrated more in the east of the landscape. However, significant
remnant patches of this ecosystem still occur within the protected areas of the western end of the landscape.
For the dominant soil types of the Eastern Plains, the most heavily cleared soil type is Ironstone soils (15.8%).
Riparian soils are also heavily cleared in this landscape (20.7%), while Acidic Soil over Rock has higher remnancy
(38.0%). As expected, saline wetlands have the highest remnancy of the dominant types (46.4%). However,
33
compared with the rest of Kangaroo Island, even those ecosystems with higher remnancy have still been heavily
impacted by historic vegetation clearance.
4.3.3
Avifauna Decline
Of the three landscapes, a strong signal linking avian decline to particular ecosystems could only be found for
the Eastern Plains landscape. Six species were considered declining by both data-driven analyses, with a further
six species considered declining by one analysis. The six species that were considered declining in both analyses
are Tawny-crowned Honeyeater Gliciphila melanops, Horsfield’s Bronze Cuckoo Chrysococcyx basalis, Golden
Whistler, Pachycephala pectoralis, Brush Bronzewing, Phaps elegans, Bassian Thrush, Zoothera lunulata and
Beautiful Firetail Stagonopleura bella. The strong relationship between shrub-dependent species and avian
decline in the Eastern Plains is congruent with the decline in extent of Eucalyptus cneorifolia mallee woodlands,
and changes in the condition of the understorey of remnants for this ecosystem. However, the mixed patterns of
decline and lack of association between decline and particular ecosystems for the Central Plateau suggests
inadequate information to guide restoration priority setting for this landscape. While the remnancy statistics
presented above provide some guidance to focus on E. baxteri woodlands and closed shrublands on Ironstone,
further analysis is required to determine the expected conservation outcomes of this restoration focus.
A full list of species and predictions of their status in the three Kangaroo Island landscapes is presented in
Appendix 2.
4.4
Eucalyptus cneorifolia Case Study
The Eucalyptus cneorifolia community is arguably the most well studied ecological community on Kangaroo
Island at present. This makes it ideal for demonstrating how detailed information can be used to develop fine
scale analysis for conservation planning. The results that follow are based on work conducted as part of the
Kangaroo Island Threatened Plants Project (Taylor 2003b) and the related Eastern Plains Fire Trial (EPFT 2008).
The synthesis of these results in conceptual model format is relatively new, although some of the ideas for the
patch scale state and transmission model (STM) were initially conceived in a study of KI mallee dynamics for the
KI Biodiversity Monitoring Project (Pisanu 2007), and subsequently used for the recent EPBC Act nomination of
the E. cneorifolia community complex.
4.4.1
The Eucalyptus cneorifolia Ecological Community
Eucalyptus cneorifolia (Narrow-leaved) Mallee is critical habitat for five nationally threatened plant species
(listed under the Environment Protection and Biodiversity Conservation (EPBC) Act 1999), four of which are
endemic to KI and found only in the Eastern Plains area. Listed threatened plants are Beyeria subtecta (Vu),
Caladenia ovate (Vu), Leionema equestre (En), Olearia microdisca (En), Pomaderris halmaturina ssp. halmaturina
(Vu), Pultenaea insularis (En), and Spyridium eriocephalum var. glabrisepalum (Vu)(Taylor 2003b). Another 25
plant species are of conservation concern in the region (State or regionally listed) and the Eucalyptus cneorifolia
Mallee community, that is almost entirely restricted to KI, has recently been nominated as a threatened
ecological community complex under the EPBC Act.
Key drivers of continued decline of the Eucalyptus cneorifolia community are habitat loss, habitat fragmentation
and fire exclusion. Mallee was extensively cleared in eastern Kangaroo Island with the intensification of
agriculture post Second World War. Native vegetation on has been progressively subdivided into smaller and
more isolated fragments with 16% (15,198 ha) of the 95,205 ha cover now remaining in the Eastern Plains study
area. One outcome of this fragmentation has been the effective restriction of wildfire spread. This has
contributed to a situation where most E. cneorifolia patches have not been burnt for c35-70+ years. The
exclusion of fire has created a senescent landscape where long lived overstorey species have become dominant
at the expense of shorter lived understorey plants. Many remnants, including roadside strips, support as few as
3-8 perennial species, and vegetation structure is a canopy of mallee trees with a few shrub species and very
34
little ground layer diversity or cover in the understorey. Thus this landscape is currently dominated by senescent
mallee remnants (EPFT 2008).
Two projects have specifically addressed the impacts of habitat loss and fragmentation on E. cneorifolia
communities. The Eastern Plains Fire Trial (2008-2013) implemented 42 prescribed burns to test fire as a means
of stimulating the regeneration of senescent mallee and improve understanding of the role of fire in maintaining
ecosystem health. The Kangaroo Island Nationally Threatened Plants project also directly addressed the causes
of fragmentation by reinstating habitat to strategically buffer, enlarge and connect important E. cneorifolia
remnants. Under this program 400,000 tubestock were planted over 212 ha to create highly diverse and selfsustaining habitats supporting threatened plant species.
4.4.2
Conceptual Model of Mallee Ecological Dynamics
The conceptual model developed for Eucalyptus cneorifolia (Narrow-leaved Mallee) can broadly be described as
a state-and-transition model (STM) in that it attempts to capture key vegetation states, describe different
successional and disturbance pathways, and define where ecological thresholds are likely to occur (Figure 9).
The model includes four gradients/drivers of change – landscape modification, fire, grazing pressure and dryland
salinity. These all occur in this landscape to varying degrees and can influence the status of individual mallee
patches.
The model summarises a number of observations about the dynamics of Narrow-leaved Mallee and potential
pathways of change as follows:
1. Landscape modification is a primary driver of change (Figure 9). The process involves change from intact
vegetation cover to small remnants, through a process of patch scale change (Forman 1995) and
ultimately results in alteration of the configuration of remnants at a landscape scale (McIntyre and
Hobbs 1999). Patch (remnant) size is an important determinant of resilience because smaller patches are
generally more susceptible to threatening processes than larger ones (States 1a-1d). Observations
indicate a threshold exists between very small patches that still maintain some elements of native
diversity (State 1d) and circumstances where small clumps of trees, or isolated individuals, remain in
paddocks (1e). The most degraded state in the continuum in terms of biodiversity is 1f, which is
effectively cleared pasture consisting of a mix of native and exotic grasses and forbs.
2. Fire is a second primary driver of change, shown in the STM as a time-dependent process, depicted as
time from a point after a fire event (Figure 9). Narrow-leaved Mallee relies on fire for periodic
regeneration of a diverse shrubby understorey, achieving a maximum level of diversity within a defined
age range (estimated to be between 8-25 years) that coincides with an optimal regeneration time of
c17-40 years (defined through vital attribute analysis)(Dowie 2006). The upper time limit for burning
requires verification, therefore the STM places it conservatively at about 25 years based on observations
that at 35+ years the transition to a community dominated by a mallee overstorey and a few shrubs
tends to occur. It is assumed that in the absence of other major forms of landscape disturbance fire can
be applied to restore the E. cneorifolia community at a patch scale but fire probably interacts with patch
size. Therefore the STM shows this as being less important for intact areas and large patches (2a and
2b), under the assumption that they can become senescent but will respond positively to fire in terms of
a transition back to high levels of understorey diversity. In contrast, we hypothesise that medium-small
patches can cross thresholds to more highly degraded states (3c and 3d), where a combination of
threatening processes may limit the influence of fire on restoring diversity.
3. A secondary driver of change (or threat) is grazing pressure. Grazing can impact on the native plant
seedbank, resulting in lower rates of germination, establishment of fewer native species, or increased
germination of exotic species following fire events (Davies et al. 2013). Also, grazing by stock and native
herbivores can impact directly on above-ground regeneration post-fire. Thus while the STM shows this
35
pressure as being highest for medium-small patches (3c and 3d) where there is less resilience, it is
plausible that secondary grazing impacts could occur in larger patches (2a and 2b).
4. The fourth driver of change is salinity that produces impacts associated with rising saline groundwater.
In the STM the threshold for a transition to salt scalded terrain is shown in relation to its impact on
cleared land (States 1f and 1g) but small salt scalds have been observed within some Narrow-leaved
Mallee remnants. The resulting change in soil chemistry represents a substantial change in abiotic
conditions and is considered to be a uni-directional transition to a different (degraded) vegetation type.
As a result fire is assumed to have limited positive biodiversity benefits under these circumstances.
Weeds are not shown in the STM but they can pose a significant threat to the Eucalyptus cneorifolia community,
e.g. limiting post-fire regeneration of native species. Bridal Creeper (Asparagus asparagoides) and Bridal Veil (A.
declinatus) are two of around 11 high impact weed species that occur in the study area. Bridal Creeper has been
present on eastern KI for around 100 years, with the heaviest and most established populations occurring on
roadsides (Ball 1996; Willoughby et al. 2001). Bridal Veil was first recorded on KI in 1984 (SA Herbarium record)
and now infests an area of approximately 234 km2 in the east (Taylor 2004; 2005). Both species are highly
competitive perennial climbers that, once established, can completely smother native vegetation. They are
known to be sensitive to the direct impacts of high intensity fire but Bridal Creeper is an early post fire
emergent. Plants such as Perennial Veldt Grass (Erharta calycina) are also fire sensitive but capable of invading
burnt areas from adjacent sites (Willoughby et al. 2001).
Figure 9. Conceptual model – Eucalyptus cneorifolia Mallee fire response in a fragmented landscape.
36
5 DISCUSSION
5.1
Understanding Drivers of Ecological Change
Fire is clearly a key driver of change for terrestrial ecosystems on Kangaroo Island and its
management currently involves a substantial commitment of resources, expended for both life and
property protection and to promote various ecological values. This project has provided an
opportunity to synthesise existing information on fire regimes at a landscape scale, and for the
Eucalyptus cneorifolia ecological community, consider the role of fire on the basis of a more detailed
dataset. Native vegetation fragmentation is also an important driver of change in natural systems
and interacts with other drivers to shape ecosystems.
The analysis of fire history for the West and South Coast landscape suggests that the fire regime, on
average, is operating largely within acceptable limits (based on the current Ecological Fire
Management Guideline, EFMG). Although, it is also clear that the recent large wildfires in 2007 that
burnt over 90,000 ha have produced a dominance of early age classes. It is worth noting that fire
ignitions in this landscape are largely lightning driven, with some deliberate fire based management
interventions to protect specific assets, create buffers designed to limit the propagation of large fire
events, and to mitigate fire impacts during emergencies (DEH 2009). This suggests that given the
current dominance of young age classes, management should continue to facilitate an appropriate
distribution of native vegetation in different seral classes by reinstatement of larger areas of older
age classes through maintaining less frequent, large scale fires.
The fact that the West and South Coast landscape is largely intact is a positive for conservation
management but where vegetation has become variegated, management actions that actively
promote habitat restoration and/or actions that promote maintenance of ecological function in the
vegetation matrix should be considered. The bird analysis does not signal any significant declines in
species or bird functional groups at this point. While beyond the scope of this project to comment
on in any detail, continuing to build specific knowledge about species with specialist requirements,
such as linked to fire regime, is a clear priority for conservation planning.
With regard to average fire interval over the past 81 years, the Central Plateau and North Coast
landscape has a fire history that suggests a higher than appropriate fire regime (with reference to
the EFMG) has historically been in place. Since 1931, 25% of the landscape’s native vegetation has
been exposed to fire intervals that, on average are lower than the recommended lower threshold
(20 years). Fire ignition in this landscape is also lightning driven but where there is dense human
settlement accidental ignitions do occur. Overall, 40% of the native vegetation of this landscape falls
within the acceptable fire interval thresholds, while 35% of the landscape has fire intervals that are
higher than the upper threshold. This pattern suggests that the requirements of biota that depend
on older fire-age classes are largely being met in this landscape.
At present 54% of the Central Plateau landscape is mapped as native vegetation, and this is either
fragmented or variegated (McIntyre and Hobbs 1999). However, the distribution of vegetation
clearance is not even across the landscape, with the majority of remnant vegetation being
distributed at the western end. This uneven distribution of vegetation clearance is largely historical
because the ironstone soils of the Plateau were considered unsuitable for agriculture until the end of
the Second World War, and were only cleared for agriculture from that period. The Flinders Chase
National Park had been proclaimed in 1919, prior to the large wave of post-war vegetation
clearance, and was thus protected from this period of clearance.
37
Most ecosystems remain relatively intact with between 62.4% to 82.6% vegetation remnancy.
However, in relative terms, ecological communities on ironstone soils (e.g. Eucalyptus baxteri ± E.
cosmophylla over closed shrubland) appear to have been preferentially cleared in this landscape,
suggesting that these could be a priority for management intervention such as restoration.
Analysis of the pattern of disturbance on the Central Plateau indicates that more conservation effort
should be focused on the eastern part where the combined effects of less than optimal fire regime
and fragmentation signal that systemic alteration of landscape processes is taking place. The bird
analysis presented here did not indicate any major declines in habitat quality but expert
observations of the avifauna (not currently documented in detail) indicate that birds dependent on a
shrubby understorey in woodland habitats have in fact declined historically since land clearing
intensified (C. Baxter pers. comm. 2013). This suggests it would be advantageous to further elicit
expert knowledge and collate local records more systematically to improve the bird dataset for this
part of the island. A renewed focus on lessons learnt from existing habitat restoration and onground works programs to design conservation management for the Central Plains and North Coast
landscape is also recommended.
Something that land managers need to consider is the deliberate application of fire in fragmented
areas where fire has been absent for long periods, however, this should be done with deliberate
biodiversity objectives in mind to avoid adverse ecological outcomes. In practice, this will require
consideration of the trade-offs for fire management around asset protection, particularly where
large-scale buffers are to be implemented to prevent fire spread. In some cases buffer burns may
include ecological benefits but in others cases, such as requirements to establish low fuel loads over
the long-term, frequent burning is likely to bring dis-benefits for conservation. Thus NRM should be
explicit about this in order to, for example, identify potential actions for positive outcomes in other
areas
The current distribution of fire classes in the Eastern Plains landscape is heavily skewed toward older
age classes and only 7% of the native vegetation of the landscape current exists within the
acceptable thresholds. This pattern of dominance by long fire interval classes in the landscape is
further demonstrated when looking at average fire interval over the last 81 years, with only 23% of
native vegetation having an average fire interval within acceptable thresholds. Based on the EFMG,
the Eastern Plains landscape is currently operating outside of acceptable limits for biodiversity
conservation with regard to fire regime. This is not surprising given the relatively long history of
close settlement and intensive land use on this part of the island.
The remnant vegetation of the Eastern Plains landscape is fragmented (McIntyre and Hobbs 1999)
with only 27% of the landscape mapped as native vegetation. The remaining vegetation typically
occurs as small isolated remnants, although a significant proportion of this mapped vegetation
occurs on roadsides. All environments support low native vegetation remnancy and interestingly the
small area of ironstone soils on the Dudley Peninsula has been heavily cleared (15.8% remnancy).
Close to half of wet saline soils are also cleared, although this pattern probably includes soils that
have become affected by dryland salinity. Managing these environments is challenging and lessons
from studies of salt affected eucalypt woodlands in the WA wheatbelt suggest considerable
investment is required to rehabilitate these landscapes to a productive state (Standish et al. 2009).
Six species bird species also appear to be in decline in the Eastern Plains and Dudley landscape.
Tawny-crowned Honeyeater Gliciphila melanops, Horsfield’s Bronze Cuckoo Chrysococcyx basalis,
Golden Whistler Pachycephala pectoralis, Brush Bronzewing Phaps elegans, Bassian Thrush Zoothera
lunulata and Beautiful Firetail Stagonopleura bella are all, to a greater or lesser extent, dependent
on or have a preference for woodland habitats with a shrubby/heathy understorey. When coupled
with the research on the ecology of threatened plants in the Eucalyptus cneorifolia community,
38
which has been identified as critical habitat for seven nationally threatened species and another 25
plant species that are rare in the region, it is obvious that the current prioritisation of the Eastern
Plains and Dudley landscape as a high priority for conservation actions is a sound strategy.
There are other lessons to be learnt from the Eastern Plains. Patch-scale data and observations
strongly indicate that physico-chemical alterations to habitat conditions (e.g. dryland salinity),
grazing pressure from both native and introduced herbivores and weeds can combine to
substantially degrade ecological resilience. However, this assessment recognises that there is still a
lack of detailed data (or synthesis of existing knowledge) on the impacts of many of these threats on
both ecological communities and species. Some of this work is currently being done for Narrowleaved Mallee but there are still scientific and management challenges to address. A key overarching
challenge is to gain a better understanding of how processes at different scales interact, an example
being changes in landscape-scale fire regime that impact on biodiversity at the scale of individual
patches of remnant vegetation, and a second relates to understanding how the drivers of change
themselves interact. An example of the latter is that fire regime can be driven by the fragmentation
of remnant vegetation (through conversion for agriculture) because small, isolated patches tend to
burn less often than large, intact patches (see further discussion of fire regimes and knowledge
building below).
The STM presented for the Narrow-leaved Mallee community is an example of a useful tool for
defining interactions, and developing hypotheses about processes and thresholds that signal
ecosystem decline. For key ecological drivers, thresholds have been identified that once crossed it is
predicted that ecosystem will operate in an inherently different way that no longer supports the full
suite of biodiversity found historically or currently. At a regional scale, some information is available
to suggest where landscapes sit in relation to grazing regime, physico-chemical processes and
population processes, but quantitative thresholds have only identified for the landscape-scale
drivers of fragmentation and fire regime. This highlights a general limitation related to a lack of high
resolution time series data for many drivers of change in Kangaroo Island landscapes.
From a management perspective, similar conceptual models for KI ecosystems could be developed
relatively easily, particularly for situations where good data exists for some biota or biological
processes and/or there is a good level of expert understanding. The decline of Stringybark
woodlands due to koala browsing pressure is a good example, as there is sufficient knowledge
available to develop a fine-scale management model for regional woodland recovery. These models
can also ultimately have a practical application as a guide for target setting and investment in onground actions. While beyond the scope of this report, it would be possible to identify a range of
priorities for conceptual model building in a workshop setting with regional experts.
5.2
The Potential Role of Corridors
A key objective of this project is to “Identify priority landscapes and corridors across Kangaroo
Island”. The project goes some way to identifying priority landscapes but has deliberately avoided
explicit consideration of corridors as a means for achieving conservation outcomes. The reasons for
this are discussed below.
Corridors have long been a subject of interest in restoration ecology and they are promoted as part
of programs both nationally, National Wildlife Corridors Plan (DSEWPC 2012), and within SA, through
NatureLinks planning (DEH 2006). Substantial research effort has produced an impressive body of
theoretical work on the importance of corridors for biological conservation, yet generalisations
regarding how to implement them remain elusive (Schmiegelow 2007) and significant controversy
still surrounds the design and efficacy of corridors for meeting conservation objectives (Rouget et al.
2006).
39
The use of corridors as a conservation approach stemmed from the theoretical ideas originating with
the equilibrium theory of island biogeography (MacArthur and Wilson 1967) and the assertion that
habitat fragments linked by corridors are likely to have greater conservation value than isolated
fragments (all else being equal) (Diamond et al. 1976). Many large-scale processes such as biota
movement, geographic speciation and responses to climate change are associated with
environmental gradients at landscape scales, and large-scale corridors (or landscape linkages) could
potentially capture environmental gradients and facilitate these sorts of biotic interactions and
processes both spatially and temporally (Rouget et al. 2006). A common goal for establishing
corridors cited in the conservation literature is to use them to enhance or maintain the viability of
populations in heterogeneous landscapes, particularly animal population, under assumptions that
corridors increase potential for immigration, reduce inbreeding depression and demographic
stochasticity, increase accessibility to resources for far-ranging species and provide additional
habitat (Schmiegelow 2007). Indeed, corridors have proven beneficial for some Australian species,
such as facilitating the movement of Rufous Bristlebirds in Victoria (Du Guesclin, Smith et al. 1995).
The literature on corridors highlights some disadvantages, such as potential for transmission of
disease, fire and other catastrophes, conduits for invasive species and increased road kill
(Schmiegelow 2007). The issue of whether road kill is strongly associated with native vegetation on
roadsides (a form of corridor) on Kangaroo Island has been the subject of some debate.
Thus current views about corridors tend to conclude that they are valuable for some species and
landscapes and establishing physical corridors is one approach to facilitating movement and
reducing isolation (Gilbert-Norton et al. 2010). However, it is recognised that other actions that are
alternative or complimentary to corridor establishment, such as improving management of the
agricultural matrix to increase landscape permeability, also deserve attention (see examples below).
Ultimately, determining the best strategy to address connectivity involves careful consideration of
the life-history characteristics of target species, the state and condition and dynamics of the
landscapes they occupy, and spatial and temporal scales of concern (Schmiegelow 2007).
When it comes to climate change, it is generally assumed that facilitating the maintenance of larger
populations as well as shifts in species distributions, should help native species adjust to changing
climates, however, it remains unclear exactly how to design landscapes to best achieve these goals.
Part of the complexity is that a range of possible changes in land uses and shifts in species
distributions are expected under climate change and these could interact with landscape design
approaches for biodiversity (Doerr et al. 2013).
Given the uncertainties surrounding the establishment of corridors for conservation, it is perhaps
best to view the NatureLinks concept of corridors as representing a desire to increase ecological
connectivity at a regional scale. This recognises corridors as one potential management response to
restoring degraded or declining landscapes, while understanding that corridors are not a panacea for
solving all conservation problems. Practically, it will be possible to use results from the landscape
assessment to inform whether implementation of corridors is appropriate for landscapes of interest,
and how other management actions may be used instead of or in conjunction with corridor
restoration. This could potentially include establishment of corridors (both small and large-scale),
buffers, understory plantings in degraded patches, new patches and/or implementation of other
types of maintenance actions (fire, pest and weed control, and fencing) in cleared landscapes to
achieve specified conservation objectives.
5.3
Improving Knowledge
Comprehensive and spatially-explicit quantitative data are not available for many drivers of
landscape change on Kangaroo Island, making it difficult to accurately estimate the magnitude of
40
impacts and rates of change, and reliably identify thresholds that determine ecosystem resilience.
Knowledge building is a key part of adaptive management under the assumption that science and
management can work together to produce evidence and refine conservation practice over time,
and in a structured way. The knowledge gaps discussed here are based on an overview of evidence
used for the purposes of this project, recognising that some knowledge may exist that has not be
utilised fully or simply could not be used effectively within the time constraints of the project.
5.3.1
Fire Regimes
Fire is recognised as a key driver of change on Kangaroo Island and considerable scientific and
practical knowledge is available for fire management. However, understanding fire regimes is
complex and remains challenging worldwide. The two most important factors for determining fire
regimes are vegetation type (or ecosystem) and weather and climate patterns. At a site scale, fire
regime is determined by intervals between fires, burn season, fire intensity and whether the fire
burns surface fuels or below ground (Gill 2012). Two of these, fire season and fire intensity, are
being investigated experimentally in Narrow-leaved Mallee by the EPFT (EPFT 2008). When scaled up
to landscapes, fire regimes tend to be expressed as dynamic mosaics because landscapes are not
uniform and fires do not burn evenly across them. Topography, rockiness, discontinuities in fuel and
chance events (stochasticity) can all influence how fire occurs in landscapes (Keith 2012), as can the
deliberate application of fire to manage fuel loads and/or biodiversity (prescribed burning) (Gill
2012).
There is a reasonable body of empirical evidence that diversity in biological composition and
structure at a range of spatial scales contributes to different aspects of landscape resilience. This
includes diversity in relation to the age structure of a landscape (in terms of time since fire), fire
intervals, intensity and season of occurrence (McCarthy 2012). Despite this general understanding of
fire regimes, many assumptions about fire remain untested. There are particular gaps in knowledge
about how fire influences fauna populations (Clarke 2008), including a widely held assumption that
animals respond to fires as discrete events in time and space, primarily in terms of fire intensity and
interval (Bradstock et al. 2005), and a lack of certainty around the importance of factors such as
quantity (area) and configuration of patches of differing burn or fire interval status, particularly in
relation to species that may require long-unburnt and infrequently burnt habitat (Bradstock et al.
2012).
There is no detailed history of the management of bushfire on Kangaroo Island for the early postEuropean settlement period but it is likely that fire was used as part of the process for clearing
vegetation such as mallee (Dowie 2005). Following the establishment of agriculture, fire appears to
have been excluded from the landscape where possible to protect built assets and land used for
agricultural production. Evaluation of historically recent data indicates that a number of ecological
communities located in areas of intensive agricultural activity, such as Eucalyptus cneorifolia Mallee,
currently fall outside of the recommended fire free interval of between c17-40 years defined
through vital attribute analysis (Dowie 2006), and additional evidence presented here tends to
reinforce that large parts of Kangaroo Island are in states outside of optimal in terms of fire age.
There has been limited research and synthesis regarding fauna responses to fire on the island,
although current work as part of the EPFT is addressing some gaps (e.g. J. March unpublished) and a
limited baseline focusing on birds from the EPFT could be used to increase knowledge of fauna
responses and fire requirements.
A major practical management challenge is to implement a well thought out program for burning in
a fragmented landscape where wildfire is largely absent and is routinely suppressed to protect life
and property. One way forward is to more clearly articulate a‘ landscape ecology fire model’ and use
41
prescribed burning to test the veracity of the model over time, in much the same way as is being
done at a patch-scale by the EPFT. This should help to increase certainly about the role of fire over
time. Precedents for this type of adaptive management do exist in the conservation planning
literature (e.g. McCarthy 2012).
5.3.2
Other Threats and Drivers of Change
Large areas of remnant native vegetation remain unfenced, so stock probably negatively impacts on
tree, shrub and groundcover recruitment and vegetation health, and stock also contribute nutrients
to soils. However, there is a lack of detailed information on stocking rates and associated impacts,
and while there is some evidence that fencing protects native vegetation we are not aware of a
systematic evaluation of how stock management contributes to conservation outcomes across the
island.
Soil enrichment is a consequence of direct addition of nutrients to improve pasture and crop
production that has clear production benefits (Dohle 2007). The secondary impacts of nutrients on
remnant native vegetation, such as toxicity to native plants and promotion of weeds, would have
increased following the establishment of widespread application of superphosphate, minerals and
elements for conditioning of agricultural soils (Mooney and Grinter 2000) but these impacts remain
unquantified at present.
Salinity is recognised as a priority natural resource management issue on Kangaroo Island, affecting
both land and water resources. The major type of salinity is groundwater driven salinity, or salinity
associated with a saline watertable. An evaluation in 2002 identified large areas of primary (natural)
salinity, estimated at 4100 ha, and secondary (human-induced) salinity, estimated at 5600 ha in
2002, and secondary salinity is predicted to increase to 8000 ha by the year 2050 (Dooley et al.
2002). Salt mostly affects areas with flat and low lying terrain and poorly drained soils, but also
impacts on gullies, river courses and lagoons (Mooney and Grinter 2000). Salt scalding in native
vegetation results in altered abiotic (soil and groundwater) conditions and replacement of dryland
trees, shrubs and groundcover with salt tolerant plants such as reeds, sedges and grasses. This level
of change in ecological conditions represents a major, largely irreversible state shift (see Narrowleaved Mallee case study). We are not aware of a systematic evaluation of salinity impacts on native
vegetation at the ecosystem scale on Kangaroo Island.
High population densities of native animals can have negative impacts on native vegetation and
agricultural production. Land clearance and changed water availability seem to have favoured
Tammar Wallaby (Macropus eugenii), Western Grey Kangaroo (Macropus fulignosus) and Common
Brushtail Possum (Trichosurus vulpecular) (Willoughby et al. 2001). Herbivores can restrict the
rehabilitation of fragmented native vegetation by reducing rates of plant recruitment, and significant
investment in new or improved infrastructure (such as fencing) is required to ensure long term
management outcomes are achieved. Some anecdotal evidence is available from the KI Threatened
Plants Project to support the idea that restricting native herbivory has positive conservation benefits
and it is being tested experimentally as part of the EPFT.
Another native animal that has impacted substantially on native vegetation is the koala
(Phascolarctos cinereus). In less than a century koalas shifted from a threatened species introduced
to KI for conservation purposes to one of pest status. The original population of 18 animals in 192325 spread progressively across Kangaroo Island and by 1994 the population was estimated at ~5000.
There were significant impacts on Eucalyptus viminalis ssp cygnetensis recorded at this time, with
over 50% of the canopy of most trees defoliated. The South Australian Government (DEH)
implemented a control program in 1997, and a more detailed census and analysis in 2001 revealed
that the koala population was much larger at ~27,000 than previously thought (Masters et al. 2004).
42
After intensive management the population is estimated to currently be approximately 14,000 and
tree health has shown significant improvement. As discussed earlier in this document it would be
possible to undertake a synthesis of existing knowledge to better define restoration goals for E.
vimanalis woodland.
Weeds risks have been evaluated at a regional scale to determine biosecurity goals and to guide
investment in control programs (e.g. Gellard and Pisanu 2005) but a further synthesis of weed
impacts at an ecosystem scale would be beneficial for conservation management. Many questions
also remain about how weeds interact with other drivers of change such as fire regime and soil
nutrient enrichment. The EPFT will provide information about some of these processes once trial
data is analysed.
The plant pathogen Phytophthora cinnamomi was first detected on Kangaroo Island in the early
1990s but positive confirmation of its presence in many areas has been difficult (Taylor 2003a). It is
known to have the potential to impact on Eucalyptus, Xanthorrhoea, Banksia and Grevillea, but it
has proven to be difficult to study, both on Kangaroo Island and Australia-wide, and a number of
questions remain about how it impacts on vegetation health in different ecological settings (Mooney
and Macphee 2007).
43
6 RECOMMENDATIONS
6.1.1
Priority landscapes and ecosystems for conservation activity
1. The terrestrial bird analysis presented here, as well as existing knowledge and new analysis
that highlights less than optimal fire regimes, reinforces the need to keep addressing
management issues in the most altered landscapes of Kangaroo Island. The most obvious is
the Eastern Plains and Dudley landscape which is essentially fragmented and has a number
of highly altered ecosystems, such as associated with the Narrow-leaved Mallee community
complex. Continued management efforts to address issues such as fire regime, grazing
pressure, weeds and salinity will be needed to ensure that resilience in this landscape is
maintained and improved over time.
2. The second key landscape to focus on is the Central Plateau and North Coast. The fire regime
for this landscape appears to be operating, at least in parts, outside of optimal limits in
terms of age classes. At an ecosystem scale the terrestrial bird analysis did not flag any
major declines in ecological resilience at this time, however, anecdotal evidence suggests
that some changes may be occurring that could lead to losses of ecosystem function in the
future. However, preferential clearing of woodlands on ironstone makes these a logical
priority for future management effort.
6.1.2
Additional knowledge building
3. For the Eastern Plains, better use could be made of existing knowledge by further testing the
hypotheses presented in the STM that identify potential thresholds and highlight the
potential synergistic impacts of different drivers and threats. We are also aware of existing
thinking about management interventions arising from the EPFT that could be integrated
with the science foundation from the Trial and the work presented here to develop an
adaptive management framework. This would provide the advantage of making more
explicit inks between on-ground works and ecological outcomes. This type of knowledge can
then be used to review NRM management targets and determine the cost-effectiveness of
investments. Extension of this type of approach could then form a model for a management
framework for other ecosystems of concern.
4. Scaling up patch-scale results from the EPFT would be beneficial in terms of shaping a
landscape-scale management program, but will require applying new analytical methods not
previously used on KI. The lessons learnt from doing this would translate to fire management
more generally and allow for better use of fire for achieving ecological outcomes. This is a
general issue for the whole island and, indeed, a challenge Australia-wide that reflects
limited understanding about how fire regimes manifest at landscape scales, including how
fire shapes species meta-populations, particularly fauna.
5. Using bird species as indicators of landscape and ecosystem function is an effective way of
evaluating ecological resilience but it does require good quality monitoring data. We
recommend that KI considers further investment in bird monitoring in a targeted way to
track changes in ecosystems of concern, such as fragmented parts of the Central Plateau. It
is likely that local bird data is available for some ecosystems and this could be included in
DEWNR databases to improve coverage for Kangaroo Island.
6. There are opportunities to make better use of existing data and expert knowledge in a
structured way. The focus of this should be on evaluating how different threats impact on
44
ecosystems, and how these threats combine or manifest synergistically, and how
management currently responds to these challenges.
7. While not a primary focus of this report, we recognise that climate change planning could be
informed by the work presented here. The landscape scale analysis provides a baseline that
when combined with information on potential exposure of biodiversity to future climates
will allow for development of a biodiversity risk analysis for the terrestrial systems of the
island.
8. We recommend continuing the partnership between SMK and the Kangaroo Island region to
take advantage of existing science capability and the extensive local knowledge within the
region.
45
7 CONCLUSION
This study addresses a key objective of the NatureLinks program for Kangaroo Island – to identify
priority landscapes (for biodiversity management). It has achieved this by focusing at a landscape
scale to develop a regional (island wide) analysis and to further evaluate the finer scale of
ecosystems nested within landscapes.
Of the three broad landscapes identified for Kangaroo Island, one, the West and South Coast, is
currently relatively intact with coastal mallee and shrublands having a high degree of ecological
function and resilience overall. The fire regime is, on average, operating within acceptable limits but
care will need in future to ensure that older age classes are reinstated in areas of the west and south
coasts affected by the December 2007 fires.
The Central Plateau and North Coast landscape is divided into variegated and fragmented sections
from west to east, and the fire regime in more disturbed areas is dominated by older age classes . No
major declines in ecological function were detected by the bird analysis but fragmented areas should
be the focus of further assessment and management effort to prevent future declines. Where
ecosystems have been cleared preferentially, such as on ironstone soils, further evaluation of the
need for maintenance and restoration should be undertaken.
The Eastern Plains and Dudley has had the most prolonged and intensive land use history on
Kangaroo Island and it is now largely fragmented. This coupled with alteration of the natural fire
regime has resulted in widespread senescence of remnant mallee communities. The bird analysis
indicates that at least six species are declining, a further signal of changed ecological conditions on
this part of the island. Other threats associated with intensive land use, such as salinity, weeds,
changed soil conditions and grazing pressure, are also apparent. The recent interest by NRM in
threatened plant species and the community they occur in has prompted knowledge building and
the testing of management interventions such as fire. There is an opportunity to build this effort into
a working adaptive management approach and use this as a model for ecosystem management on
the island more widely.
The work presented here does not explicitly identify corridors but recognises that corridor
restoration may be one option to use in conjunction with others to improve the quality of
biodiversity in the agricultural matrix.
A number of opportunities for building new knowledge and future collaboration between SMK and
regional NRM managers have been identified.
46
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52
9 Appendices
Appendix 1. Estimated Distribution of Soil Types Associated with Ecosystems within Kangaroo Island
Landscapes
Estimated distribution of soil types associated with the ecosystems listed in this document based on
Hall et al. (2009): The Soils of Southern South Australia. For each map, the shade of blue indicates
the proportion of a soil landscape unit (SLU) polygon that is made up of the soil types of interest
(light blue = <30%; med. blue = 30-60%; dark blue = >60%).
Figure A1.1. Distribution of shallow soils on calcrete (soil subgroups B1, B2 and B3) within the West
and South Coast landscape. In this landscape, these soil types are typically associated with
coastal/subcoastal mallee (Eucalyptus diversifolia and E. rugosa over Melaleuca lanceolata,
Orthoxanthus multiflorus- ecosystems 1, 3 and 11).
Figure A1.2. Distribution of carbonate sands (soil subgroup H1) within the West and South Coast
landscape. In this landscape, this soil type is typically associated with coastal shrublands (e.g.
Leucopogon parviflorus, Olearia axillaris - ecosystems 2 and 4).
53
Figure A1.3. Distribution of shallow soils over Pre-Cambrian sedimentary rocks (soil subgroup L1) in
the Central Plateau landscape. In this landscape, this soil type is typically associated with she-oak
(Allocasuarina verticillata) woodlands (ecosystem 5), although sclerophyllous woodlands dominated
by Eucalyptus cladocalyx (ecosystem 7; ) can also occur.
Figure A1.4. Distribution of acidic sandy loams over brown or grey clay over rock (soil subgroup K4)
in the Central Plateau landscape. In this landscape, this soil type is typically associated with
sclerophyllous woodlands dominated by Eucalyptus cladocalyx (ecosystem 7), although
sclerophyllous woodlands dominated by Eucalyptus baxteri and E. cosmophylla (ecosystem 9; ) can
also occur.
54
Figure A1.5. Distribution of ironstone soils (soil subgroup J2) in the Central Plateau landscape. In this
landscape, this soil type is typically associated with sclerophyllous woodlands and shrublands
dominated by Eucalyptus baxteri and E. cosmophylla (ecosystem 9).
Figure A1.6. Distribution of wet saline soils (soil subgroup N2) in the Eastern Plains and Dudley
landscape. In this landscape, this soil type is typically associated with low samphire shrublands and
Melaleuca halmaturorum woodlands (ecosystem 6).
55
Figure A1.7. Distribution of soils associated with narrow-leaved mallee communities in the Eastern
Plains and Dudley landscape. In this landscape, a range of communities exist with Eucalyptus
cneorifolia as an overstorey dominant, on a range of soil types that are less susceptible to
waterlogging and inundation. Other mallee, such as Kingscote mallee may occur where conditions
are suitable.
56
Appendix 2. Trend analysis for terrestrial bird species within landscapes of Kangaroo Island
Landscapes
Trend analysis for terrestrial bird species within each of the three defined landscapes of Kangaroo
Island. Change refers to the proportion of hexagonal cells (cell size = 100 ha) where a species was
recorded after 1995, compared with those cells where the species was recorded all time (e.g. a value
of 0.5 refers to the fact that the species was recorded in one half of cells in which it was recorded alltime, after 1995). Species were considered declining for this metric if dChange was less than 0.7. r2
refers to the r2 value for the linear regression between Year and the proportion of cells (within
which any bird was recorded) that the species was recorded. Direction refers to the trend analysis
direction; - refers to a significant (p<0.1) negative trend with time, + refers to a significant positive
trend. Direction is left blank if the relationship between Year and proportion of cells occupied was
not significant (p>0.1). Species were considered declining if Direction was negative and the
regression analysis was significant (p<0.1). # analyses refers to the number of analyses (max=2)
where a species was considered declining within a landscape
Table A2.1. Eastern Plains and Dudley Landscape
Species
Bassian Thrush
Beautiful Firetail
Brush Bronzewing
Golden Whistler
Horsfield's Bronze-cuckoo
Shining Bronze-Cuckoo
Tawny-crowned Honeyeater
Fan-tailed Cuckoo
Change
0.63
0.67
0.6
0.69
0.53
0.57
0.57
0.6
r2
Direction
# analyses
0.57
0.31
0.55
0.5
0.96
0.84
0.48
0.05
-
2
2
2
2
2
2
2
1
-
1
1
1
1
1
1
0
Grey Shrike-thrush
Little Wattlebird
Western Whipbird
White-browed Scrubwren
White-fronted Chat
White-naped Honeyeater
Australasian Pipit
0.72
0.71
0.83
0.83
0.76
0.91
0.95
0.73
0.51
0.9
0.35
0.33
0.33
0.36
Australian Magpie
0.88
0.01
Australian Raven
Black-faced Cuckoo-shrike
0.92
0.82
0.36
0.001
1
0.04
0
Brown Falcon
0.71
0.06
0
Brown Goshawk
0.92
0.3
0
Brown Thornbill
0.87
0.08
0
Brown-headed Honeyeater
0.86
0.02
0
Bush Stone-curlew
Collared Sparrowhawk
0.84
0.78
0.47
0.18
Common Bronzewing
0.82
0.03
Black-shouldered Kite
0
+
+
0
0
0
0
0
57
Species
Crescent Honeyeater
Change
0.87
r2
Direction
# analyses
0.04
0
Crimson Rosella
0.93
0.04
0
Dusky Woodswallow
0.85
0.2
0
Eastern Spinebill
0.82
0.11
0
Galah
0.86
0.04
0
Grey Currawong
0.78
0.05
0
0.9
0.19
0
Laughing Kookaburra
0.87
0.01
0
Little Corella
Little Raven
Magpie-lark
0.91
0.86
0.89
0.44
0.66
0.05
Nankeen Kestrel
0.93
0.001
0
New Holland Honeyeater
0.81
0.13
0
Peregrine Falcon
0.92
0.16
0
Purple-crowned Lorikeet
0.77
0.005
0
Purple-gaped Honeyeater
0.7
0.07
0
Rainbow Lorikeet
0.83
0.0004
0
Red Wattlebird
0.83
0.06
0
Red-browed Finch
0.92
0.24
0
Restless Flycatcher
0.79
0.29
0
0.8
0.59
0
Scarlet Robin
0.82
0.19
0
Shy Heathwren
0.71
0.07
0
Silvereye
0.81
0.08
0
Southern Boobook
0.8
0.01
0
Spotted Pardalote
0.87
0.11
0
Striated Pardalote
0.78
0.002
0
Striated Thornbill
0.86
0.01
0
Superb Fairy-wren
Swamp Harrier
Tree Martin
0.83
0.93
0.86
0.37
0.61
0.03
Wedge-tailed Eagle
0.94
0.04
0
Welcome Swallow
0.89
0.15
0
White-eared Honeyeater
0.84
0.01
0
Willie Wagtail
Yellow-tailed Black-Cockatoo
0.89
0.88
0.31
0.05
Grey Fantail
Rock Parrot
+
+
+
+
+
0
0
0
0
0
0
0
0
58
Table A2.2. Central Plateau and North Coast Landscape
Species
Black-faced Cuckoo-shrike
Australasian Pipit
Brown Falcon
Change
0.69
0.5
r2
0.31
0.03
Direction
-
# analyses
2
1
0.5
0.07
Crimson Rosella
Fan-tailed Cuckoo
0.84
0.53
0.17
0.14
Horsfield's Bronze-cuckoo
0.38
0.03
Silvereye
Southern Boobook
0.76
0.6
0.41
0.07
-
1
1
Western Whipbird
White-browed Scrubwren
White-fronted Chat
0.95
0.76
0.62
0.83
0.22
0.006
-
1
1
1
Yellow-tailed Black-Cockatoo
Australian Magpie
0.8
0.91
0.33
0.02
-
1
0
Australian Raven
0.88
0.16
0
0.9
0.11
0
0.76
0.01
0
1
0.55
0
Brown Thornbill
0.85
0.05
0
Brown-headed Honeyeater
0.84
0.01
0
Brush Bronzewing
0.78
0.09
0
Bush Stone-curlew
0.7
0.12
0
Common Bronzewing
0.81
0.13
0
Crescent Honeyeater
0.86
0.07
0
Dusky Woodswallow
0.73
0.03
0
0.8
0.08
0
Elegant Parrot
0.71
0.17
0
Galah
0.78
0.006
0
Golden Whistler
0.7
0.16
0
Grey Currawong
0.87
0.05
0
Grey Fantail
0.87
0.07
0
Grey Shrike-thrush
Laughing Kookaburra
0.74
0.9
0.22
0.45
+
0
0
Little Corella
Little Raven
0.85
0.83
0.71
0.01
+
0
0
Little Wattlebird
0.78
0.23
0
Magpie-lark
0.88
0.01
0
Nankeen Kestrel
0.73
0.03
0
New Holland Honeyeater
0.81
0.09
0
Bassian Thrush
Beautiful Firetail
Black-shouldered Kite
Eastern Spinebill
1
-
1
1
1
59
Species
Painted Button-quail
Change
0.83
r2
Direction
# analyses
0.11
0
Peregrine Falcon
0.71
0.01
0
Purple-crowned Lorikeet
0.83
0.001
0
Purple-gaped Honeyeater
0.79
0.02
0
Rainbow Lorikeet
0.89
0.01
0
Red Wattlebird
0.86
0.06
0
Red-browed Finch
0.93
0.11
0
Restless Flycatcher
Scarlet Robin
1
0.84
0.85
0.006
Shy Heathwren
0.72
0.08
0
Southern Emu-wren
0.98
0.03
0
Spotted Pardalote
0.92
0.01
0
Striated Pardalote
0.77
0.16
0
Striated Thornbill
0.84
0.03
0
Superb Fairy-wren
0.84
0.02
0
Swamp Harrier
0.83
0.29
0
Tawny-crowned Honeyeater
0.71
0.04
0
Tree Martin
0.74
0.02
0
Wedge-tailed Eagle
0.91
0.04
0
Welcome Swallow
0.81
0.03
0
White-eared Honeyeater
0.86
0.02
0
White-naped Honeyeater
1
0.33
0
0.89
0.05
0
Willie Wagtail
+
0
0
60
Table A2.3. West and South Coast Landscape
Fan-tailed Cuckoo
Golden Whistler
Grey Shrike-thrush
Rainbow Lorikeet
Red Wattlebird
Southern Boobook
Australasian Pipit
Change
0.42
0.57
0.65
0.69
0.61
0.5
0.5
Bassian Thrush
Brush Bronzewing
0.89
0.53
Common Bronzewing
0.56
Crimson Rosella
Dusky Woodswallow
Fairy Martin
0.82
0.83
0.57
Species
slope
r2
#analyses
-
0.42
0.53
0.43
0.28
0.41
0.42
0.38
2
2
2
2
2
2
1
-
0.55
0.29
1
1
0.37
1
0.34
0.73
0.09
1
1
1
0.6
0.27
1
Grey Currawong
0.68
0.0004
1
Grey Fantail
Horsfield's Bronze-cuckoo
0.78
0.27
0.37
0.4
1
1
Little Wattlebird
0.68
0.09
1
Nankeen Kestrel
Peregrine Falcon
0.76
0.6
0.3
0.23
1
1
Purple-crowned Lorikeet
0.68
0.2
1
Purple-gaped Honeyeater
0.64
0.2
1
Rock Parrot
0.57
0.48
1
Silvereye
Striated Thornbill
0.71
0.69
-
0.25
0.08
1
1
Wedge-tailed Eagle
Welcome Swallow
Western Whipbird
White-browed Scrubwren
0.84
0.75
0.94
0.69
-
0.25
0.44
0.93
0.2
1
1
1
1
White-fronted Chat
0.27
0.39
1
Yellow-tailed Black-Cockatoo
0.69
0.18
1
Australian Magpie
0.85
0.005
0
Australian Raven
0.8
0.04
0
Beautiful Firetail
0.83
0.12
0
Black-faced Cuckoo-shrike
0.76
0.02
0
Brown Thornbill
0.72
0.18
0
Brown-headed Honeyeater
0.73
0.03
0
Bush Stone-curlew
0.87
0.29
0
Galah
-
-
-
61
Species
Crescent Honeyeater
Change
0.82
slope
r2
#analyses
0.02
0
Eastern Spinebill
0.83
0.0008
0
Little Raven
0.88
0.12
0
Magpie-lark
0.88
0.36
0
New Holland Honeyeater
0.71
0.07
0
0.9
0.03
0
Scarlet Robin
0.73
0.02
0
Shy Heathwren
0.71
0.01
0
1
0.04
0
Spotted Pardalote
0.74
0.09
0
Striated Pardalote
0.76
0.07
0
Superb Fairy-wren
0.75
0.03
0
Tawny-crowned Honeyeater
0.71
0.09
0
Tree Martin
0.73
0.09
0
White-eared Honeyeater
0.75
0.07
0
Willie Wagtail
0.86
0.02
0
Red-browed Finch
Southern Emu-wren
62