Development by Design

Development by Design: Cooperative Mitigation Planning for Barrick Gold’s Kanowna Belle Operations in Western Australia

Acknowledgements We thank external independent members of the project Working Group for providing their time and expertise to this process: Keith Bradby, Neil Gibson, Ric How, Ian Kealley, Amanda Keesing, Peter Price, Suzanne Prober and Wayne O’Sullivan. Megan Evans and Mark Cowan, also provided important feedback and data. Melissa Barbanell, Allison Brown, Adrian Lally, Ben Wither, and Gail Ross from Barrick Gold are thanked for engaging in the process and providing data and feedback. All assumptions are ours and no do necessarily represent the views of the above mentioned people. Funding provided by Barrick Gold.

© The Nature Conservancy 2013 Kiesecker, J., M. Heiner, K. Sochi, B. McKenney, and J.Fitzsimons. 2013. Development by Design: Cooperative mitigation planning for Barrick Gold’s Kanowna Belle operations in Western Australia. The Nature Conservancy. Address questions to: Joseph Kiesecker ([email protected]) Mike Heiner ([email protected]) Kei Sochi ([email protected]) Bruce McKenney ([email protected]) The Nature Conservancy Global Conservation Lands

James Fitzsimons ([email protected]) The Nature Conservancy Australia Program Suite 2-01 60 Leicester Street Carlton VIC 3053 Phone: (+61) 3 8346 8604

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Development by Design: Cooperative Mitigation Planning for Barrick Gold’s Kanowna Belle Operations In Western Australia Table of Contents 1.0 Introduction ............................................................................................................................ 4 1.1 Overview of Development by Design ................................................................................... 4 1.2 Study Area ............................................................................................................................ 5 1.3 Steps used in the Kanowna Belle Mine Development by Design Project ............................ 6 2.0 Methods and Results: Offset site selection........................................................................... 8 2.1 Assembling a Working Group.............................................................................................. 8 2.2 Compiling a List of Representative Biological Elements .................................................... 8 2.3 Gathering Spatial Data ......................................................................................................... 9 2.4 Assess Development Footprint and Determine Impacts and Goals ................................... 14 3.0 Offset Accounting: Options for Achieving the No Net Loss Goal ................................... 24 3.1 Offset Accounting Principles .............................................................................................. 24 3.2 Portfolio of Potential Offset Sites and Conservation Actions ............................................. 25 3.3 Accounting Framework: Assumptions and Estimates ........................................................ 27 3.4 Offset Options for Achieving the No Net Loss Goal .......................................................... 28 4.0 Discussion of Proposed Offset Activities ............................................................................. 33 5.0 Additional Comments from Barrick ................................................................................... 35

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List of Tables Table 1:

Habitat elements: Source data and mapping method

Table 2:

Mine footprint components

Table 3:

Distribution of pastoral lease area by habitat type, condition and proposed offset action

Table 4:

Offset accounting: Assumptions and estimates

Table 5:

Project impacts and offset options

Table 6:

Proposed offset actions to achieve no net loss goal by management status

Table 7.

Offset actions and cost estimates

List of Figures Figure 1:

Study area

Figure 2:

Habitat types (NVIS Level 5, plant associations)

Figure 3:

Landform classification

Figure 4:

Surficial geology / Lithology

Figure 5:

Footprint of Barrick Kanowna Belle mining operations

Figure 6a: Infrastructure and land use Figure 6b: Disturbance index Figure 7:

Management unit classified by condition, summarized by roadless blocks

Figure 8:

Total project impacts vs. implementation of all proposed offset activities

Figure 9:

Comparison of current Barrick spending to proposed offset spending

List of Appendices Appendix A: Working group participants Appendix B: Summary of probability of success and timing to maturity for potential offset actions Appendix C: Mine footprint habitat composition C(i) NVIS plant associations C(ii) General lithology Appendix D: Reclass of surficial geology/lithology types to generalized surficial geology Appendix E: References for reviewing probability of success and timing to maturity of offset

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1.0 Introduction In January 2011 Barrick Gold (hereafter Barrick) and The Nature Conservancy (hereafter TNC) agreed to pilot TNC’s Development by Design conservation program at Barrick’s Kanowna Belle mine operations in Western Australia. The Development by Design analysis was intended to help inform and provide options as Barrick seeks to implement its biodiversity standard, which took effect in July of 2009 and requires that where significant biodiversity impacts around mining operations cannot be avoided, Barrick operations and projects are responsible to minimize, mitigate and compensate fairly for those impacts. This may include offsets which are specific conservation or enhancement activities that compensate to result in no net loss of biodiversity on a regional level. Below we give an overview of the Development by Design process and then discuss in detail the steps to implement the process at Barrick’s Kanowna Belle operations. The outcome of this implementation of the Development by Design process is a set of offset options to be considered by the operation. It is important to note that there may be some legal hurdles to implementing some of these offset activities given the land tenure system in Western Australia. Therefore, this process should be considered an exercise only at this point. Whilst recognizing the challenges associated with the offset options, this bundle appears to be the best opportunity to achieve a like for like set of biodiversity offsets. It is also important to note that our analysis did not attempt to assess impacts related to any emissions resulting from Barrick’s Kanowna Belle operations or impacts on cultural or recreational values, nor did we attempt to address cumulative impacts resulting from mining activities of other companies adjacent to the Kanowna Belle operations. 1.1 Overview of Development by Design Development by Design (DbD) is a science-based mitigation planning process that balances the needs of planned development, such as mining and infrastructure, with those of biodiversity conservation ((Kiesecker et al. 2009, 2010, 2011, McKenney and Kiesecker 2010). The aim is to bring efficiencies to development planning and impact mitigation, while achieving effective conservation that encourages “no net loss” of biodiversity values. DbD improves implementation of the “mitigation hierarchy” at each stage – avoid, minimize/restore, and offset – in a way that is transparent and transferable to industry and regulators, and complementary to the environmental assessment process. The Nature Conservancy has developed DbD as a landscape-level approach to mitigation that supports proactive thinking about how to avoid siting conflicts, maintain biodiversity, and determine suitable mitigation responses within a region (Kiesecker et al. 2010). Where impacts occur, DbD supports the identification of offsets (compensating conservation actions) as appropriate and feasible to deliver positive outcomes for nature (Kiesecker et al. 2009). Through this approach, DbD can benefit both business and conservation by reducing conflicts, increasing flexibility, transparency, and cost-effectiveness for mitigation, and delivering higher value conservation. As part of the Kanowna Belle mine offset project we focused on the following questions:

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

Identifying best options: Where impacts have occurred, how can compensating mitigation (i.e., offsets) best deliver values ecologically and functionally equivalent to those lost, be located at an acceptable proximity from the impact site, and contribute to regional conservation goals?

Our focus is on identifying the most effective options for addressing/mitigating impacts (restoration, management, and protection actions). One of the key deficiencies in mitigation planning is a failure to locate offset actions in places that contribute to broader landscape scale conservation priorities (McKenney and Kiesecker 2010). The establishment of goals for mitigation (i.e., what is necessary to offset impacts) first requires the expected direct and indirect impacts to be quantified. These impacts may be the anticipated impacts of a proposed new project or project expansion or, as with Barrick’s operational Kanowna Belle mine, existing impacts. In the case of Kanowna Belle, with over 100 years of mining history and limited baseline data, the starting point for the purpose of the exercise is not assumed as the disturbance footprint at the time Barrick took over operations in 2003 but mature Great Western Woodland habitat. The assessment process considers baseline environmental impact assessment information as well as information compiled as part of a landscape conservation plan (e.g,. list of representative biological elements and spatial data). Once impacts are quantified, mitigation goals can be established and an optimal portfolio of potential mitigation options can be developed. The aim is to select options that provide ecologically and/or functionally equivalent values to impacted areas, contribute to landscape conservation goals, and will persist at least as long as impacts. 

Measuring progress toward goals: To what extent will offsets compensate for impacts to achieve no net loss goal? Which offsets will provide the best conservation return on investment – highest conservation value at least cost and risk?

With a portfolio of the best mitigation options identified, we focus on measuring the extent to which implementation of mitigation actions will fully address impacts in a manner consistent with landscape-level conservation goals. Among several considerations for measuring progress, three important factors to take into account include: (a) “additionality” (an option’s new contribution to conservation, additional to existing values); (b) probability of success (the likelihood that an option will deliver expected conservation benefits); and (c) time-lag to conservation maturity (how long it will take for an option to deliver conservation at a maturity level similar to what was lost due to impacts). With an understanding of the conservation value of different mitigation actions, it is possible to compare these values to the cost of implementing the actions to estimate which actions will provide the highest conservation returns on investment. 1.2 Study Area The Great Western Woodlands is the largest remaining intact temperate or 'Mediterranean' woodland in the world. The area covers almost 16 million hectares, and is a continuous band of vegetation spanning the edge of the Western Australian ‘Wheatbelt’ to the Mulga country in north - the inland deserts to the northeast and the Nullarbor plain to the east. This significant area of eucalypt woodlands is intermixed with thicker eucalypt mallee, low shrublands, and grasslands. The very high plant diversity within these vegetation types (over 3000 species being recorded to date, with high rates of endemism), is one of the primary reasons for the region’s 5

conservation significance. Across the landscape, these species change rapidly, many occurring only in localised areas, creating a mosaic of ecological communities throughout the region (Watson et al. 2008). According to the Interim Biogeographic Regionalisation of Australia (IBRA), the Kanowna Belle operations lie at the northern edge of the Coolgardie bioregion, in the North-western corner of the East Goldfields sub-region, where the Coolgardie transitions northward into the Murchison bioregion (Australian Government 2004). The Coolgardie bioregion forms roughly the northern and western boundary of the Great Western Woodlands. See Figure 1 for a map of the region.

1.3 Steps Used in the Kanowna Belle Mine Development by Design Project Our objective is to design an approach ensuring that offset options are ecologically equivalent to impact sites and will persist at least as long as on-site impacts, and that they will achieve no net loss or positive outcomes. We undertook six steps for this approach: (1) assemble a working group; (2) compile a list of representative biological elements; (3) gather spatial data for biological elements; (4) assess development scenario/footprint analysis and determine impacts and goals; (5) identify potential offset sites; and (6) develop an offset valuation framework.

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2.0 Methods and Results: Offset site selection 2.1 Assembling a Working Group A mitigation-design working group was formed to guide the development of the mitigation planning analysis and integration of spatial data into the offset design and valuation process (Appendix A). Participants were selected because they had expertise and have been involved with management of the biological systems affected by the Kanowna Belle operations and included representatives from Barrick, state and federal agencies, universities, local and regional NGOs and the local community. This group helped secure the most current spatial data on biological elements, assessments of any predictive models utilized, and insights into the process being developed. We sought to apply rigorous, objective measures of conservation value whenever possible, recognizing that a quantitative assessment would have to be supplemented by expert opinion. 2.2 Compiling a List of Representative Biological Elements Biological diversity cannot easily be completely and directly measured. Thus, practitioners are forced to select a set of components of biological diversity that can be measured effectively given existing resources, adequately represent the range of biological phenomena in the project area and contribute the most to the overall biological diversity of a project area. Selecting a set of focal elements with sufficient breadth and depth is possible using what is referred to as “the coarse-filter/fine-filter approach”, as applied, for example, in ecoregional planning by The Nature Conservancy (Groves et al. 2002, Groves 2003). “Coarse filter” generally refers to ecosystems; in a more practical sense, it refers to mapped units of vegetation and underlying physical environmental patterns including landforms and soils. The basic idea is that conserving a sample of each distinct vegetation type, in sufficient abundance and distribution, is an efficient way to conserve the majority of biological phenomena in the target area. “Fine Filter” generally refers to species, usually rare and/or range-limited, whose distributions are not well-represented by the coarse filter. This coarse filter/fine filter approach has ecological advantages in that it considers multiple scales of organization, environmental patterns and processes that influence habitat structure and function. Choosing elements that represent the range of environmental gradients and settings is a way to address the dynamic nature of ecosystems and the uncertain impacts of climate change (Hunter et al. 1988, Halpin 1997, Groves 2003, Anderson and Ferree 2010, Beier and Brost 2010). This approach also has practical advantages in that it makes the best use of available data to represent the full range of representative biodiversity with a practical number of elements. Our knowledge regarding species ranges and habitat needs will always be incomplete. As coarse filter elements, ecosystems can often be mapped with available GIS data. This alone provides a basis for conservation planning and fills a significant information gap. Fine-filter species and natural community data are typically more limited and dependent on survey effort, and therefore vary in 8

geographic coverage. Thus, the coarse but geographically consistent ecosystem classification complements the locally accurate but uneven coverage of species data. Given the short time frame of this assessment and the lack of GIS data to comprehensively map the current range of species that are significant to the study area, we defined biodiversity elements following a coarse filter approach focused on terrestrial habitat and did not define or develop information for fine filter elements. To define and map coarse-filter biodiversity elements, we used an existing vegetation classification, the NVIS (ESCAVI 2003) and a map of surficial geology (Stewart et al. 2008). 2.3 Gathering Spatial Data Vegetation/Landforms The NVIS (ESCAVI 2003) is a mapped vegetation classification which for Western Australia is derived from maps of Pre-European vegetation (Beard & Webb, 1974, Figure 2). The classification is hierarchical, organized as 6 levels from vegetation class to plant sub-association. On the advice of the working group, we defined a set of biodiversity elements based on the NVIS Plant Associations (Level 5). The NVIS defines and maps 22 Plant Associations within the East Goldfields study area, of which 15 occur within the Kanowna Belle mine footprint. Several Plant Associations occupy a relatively large area in the East Goldfields. These broadlymapped vegetation types are usually a heterogeneous, patchy matrix of plant communities formed by topography, disturbance regimes and successional cycles. Patterns of plant species composition within these matrix-forming ecosystems generally follow topographic environmental gradients. To capture this ecological, environmental and genetic diversity, we stratified these widespread, broadly-mapped vegetation types by landforms (Figure 3). We defined and mapped landforms according to a cluster analysis of elevation, insolation (Rich et al. 1995) and a topographic index (Moore et al. 1991), as shown in Figure 3. We stratified 18 of the 22 Plant Associations by landforms to define 116 focal elements across the East Goldfields study area, of which 71 occur within the Kanowna Belle mine footprint (see Table 1 and Appendix C(i)). Soils/Lithology Patterns of surficial geology may capture and account for the habitat preferences of many animal species, in particular reptiles, which respond strongly to soils and physical habitat (pers comm Rick How, Mark Cowan; Morton and James 1988). Therefore, we also defined biodiversity elements based on a map of surficial geology (Stewart et al. 2008) that we re-classified to define and map 12 general lithology types across the East Goldfields IBRA sub-region, and 10 within the Kanowna Belle mine footprint (Figure 4). The original typology and the generalized reclassification are listed in Appendix D. See Table 1 below for a full listing of habitat elements, source data and mapping methods.

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Table 1: Habitat Elements: source data and mapping method

Vegetation Plant Associations (NVIS Level 5)

* Landforms

Mapping Method

Source Data

22 types mapped across E. Goldfields IBRA sub-region; 18 stratified by landforms*. Result: 116 unique types across E. Goldfields, of which 71 occur within Kanowa Belle mine footprint.

Beard’s pre-European vegetation (ESCAVI 2003) derived from (Beard & Webb, 1974).

1. map DEM-derived topographic indices:

SRTM DEM, 90m resolution (HydroSHEDs; Lehner et al. 2005)

 elevation  solar flux (Rich et al. 1995)  compound topographic index (CTI; (Moore et al. 1991)

2. define landforms by cluster analysis (ISOCLUSTER; n=8): North-facing slope South-facing, gentle slope South-facing, steep slope low(er) elevation lowland depression low(er) elevation upland and rolling hills valley bottom, wetland or waterbody high(er) elevation lowland depression high(er) elevation upland and rolling hills

Surficial Geology /Lithology

Re-classified into major lithology types: greenstone sand plain granite alluvium colluvium lacustrine sediment lateritic duricrust mafic intrusive sand other other

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Surface geology of Australia 1:1,000,000 scale, Western Australia (Stewart et al. 2008)

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12

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2.4 Assess Development Footprint and Determine Impacts and Goals We calculated estimates of the spatial area, or footprint, affected by the Kanowna Belle Mine and associated roads and activities. We estimated the development footprint with data provided by Barrick as well as data from Geoscience Australia and Western Australian Department of Mines and Petroleum. Our estimate separates the components of the mining footprint into three categories: 1) Mine pits and tailings (which are relatively permanent) 2) Connecting roads 3) Remaining area in mining tenements, summarized three ways: a) Leases/tenements owned by Barrick. b) Leases/tenements owned by joint venture managed by Barrick. c) Leases/tenements owned by joint venture but not managed by Barrick For 1) mine pits and tailings, and 2) the connecting roads, we mapped a 1 km buffer to represent a nominal area of impact. In a review of the impacts of roads associated with mining and energy development, Hebblewhite (2008) reported reduced habitat use by ungulates within 2.7- 3.7 km of infrastructure in the USA. Other studies found a larger area of impact (Copeland et al. 2009, Doherty et al. 2011). While these studies are based in the Western United States, they utilize observations that are likely to make them relevant to estimating impacts in Western Australia. For example, several of the studies reviewed by Hebblewhite (2008) use measures of dust spread and noise level to estimate indirect impacts associated with these activities. Changes in abiotic conditions (noise and dust) associated with these mining activities, may be similar in nature and scale in the arid environments of Western Australia and the Western United States. In light of these studies, a 1 km buffer was chosen as an estimate of the area affected; however it must be emphasized that much of the structural vegetation (such as trees) within the 1 km buffer zone is largely intact. The footprint and components are mapped in Figure 5, and Table 2 lists each component and area of impact.

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It is important to note that lease/tenements are areas under management by Barrick and other joint ventures. These areas are managed as part of pastoral leases and/or could be subject to exploration and potential development. These are not areas necessarily impacted by operations at this time. They were included in calculations for this report as a conservative estimate since development in this area could proceed at some point.

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Table 2: Mine Footprint components area (hectares) Tenements Feature

Total

Managed 100%

JV Manager

JV unmanaged

1

Mine site Pits & tailings

1,294

1,234

60

2

1 km buffer

8,124

6,685

1,425

13

Transport 3 Connecting Roads and 1 km buffer

20,992

17,061

2,545

1,386

4

Tenement (remaining area)

47,820

17,650

10,979

19,190

5

Total area of impact

78,230

42,630

15,010

20,589

Mapping Method

Source Data

Selected features occurring within Barrick mining tenements

GEODATA TOPO 1:250k (GeoScience Australia, 2006)

Mapped 1km buffer around mine site Selected roads connecting mine sites and occurring within Barrick mining tenements, mapped 1 km buffer.

GEODATA TOPO 1:250k (GeoScience Australia, 2006)

Tenements classified by management

Tenement boundaries: WA Dept. Mines & Petroleum; Management: Barrick

Note: the area amounts listed in this table differ from those in Figure 5 because Figure 5 classifies the footprint differently to distinguish an inactive mine site and associated connecting roads, road buffer and tenements. Table 2 and Figure 5 describe the same footprint area.

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We then measured the area of each habitat element identified in Section 2.3 affected by the mining footprint (see Appendix C). Based on developments of a similar nature, we assume that impacts will persist during development/production (e.g., Tongway and Ludwig 2010). When mining production activities are halted, we estimate that impacts will persist for at least a 20 year recovery period (Tongway and Ludwig 2010) during subsequent restoration actions. We assume restoration will deliver a return of 5% habitat recovery per year (Appendix B & C, Tables 2 and 4). The resulting calculation identifies 78,230 ha of potential impact. Of these impacts 1,060 ha (~9%) composed of the mine pits and tailing piles is considered to be permanent impact, subject to reclamation but unlikely to be fully restored during the time period we are considering. We are comfortable with our estimates of indirect impacts although we recognize they were derived from studies conducted in similar but geographically distinct biological systems and may not correspond to impacts in Western Australian systems. Future research should better define the nature of indirect effects in this system to improve environmental impact assessments and mitigation planning. For this reasons calculations have been broken out into direct and indirect impacts.

2.5 Identifying Potential Offset Sites To ensure that offsets would serve to mitigate on-site impact, we selected offset sites that contain similar habitat as the mining footprint and in configurations that would contribute to conservation goals across the region. After developing criteria (biodiversity elements and representation targets), we analyzed possible offset designs across two geographic extents (see map in Figure 1): 1. First, at the site level, across the Kanowna Pastoral leases currently under management control of Barrick Gold. 2. Second, at the landscape level, across a larger area defined roughly by the Coolgardie/ East Goldfields IBRA subregion. The main purpose of the second landscape-level analysis is to evaluate possible offset designs that contribute the most to conservation priorities across the region. We followed an approach developed for regional conservation planning, or "ecoregional assessments," that identifies conservation areas to meet explicit representation targets while optimizing for ecological condition and efficiency (minimal area), and involves the following steps: i. identity focal habitat types, as described in Section 2.3 18



vegetation: NVIS Plant Associations (ESCAVI 2003), stratified by landforms



generalized surface geology (Stewart et al. 2008)

ii. set representation targets, based on the amount of each habitat element occurring in the footprint, as described in Section 2.4 and listed in Appendix C. iii. evaluate ecological condition, based on an index of disturbance derived from GIS data for sources and types of current human disturbance. Source data included infrastructure and land use mapped by GeoScience Australia in GEODATA TOPO 250K Series 3 (2006), as listed below and shown in Figure 6a. Land Use: mine areas, built areas, homesteads, recreation areas, mine points, building points, yards Transport: airports, roads, railways, rail points, road crossing lines, railway crossing lines, railway stop points Water infrastructure: bores, water holes, wind points, canals, pondage areas Other infrastructure: fences, conveyors, pipe lines, power lines, water tanks, wind pumps The disturbance index is the cumulative density of all these features, calculated by a moving-window analysis (circular window of 5 km radius) and shown in Figure 6b. The index summarizes cumulative human impacts as an indirect measure of ecological integrity or departure from historic or natural conditions. In site selection, this index is the basis for maximizing selection of undisturbed ecosystem occurrences. Patterns of existing disturbance have historically played a significant role in the design and development of conservation priorities (Margules and Pressey 2000). Areas of high disturbance generally have lower value for biodiversity (e.g., Forman et al. 2002, Fletcher et al. 2011). Disturbance is also consistently associated with reduced biological integrity and increased probability of extirpation for many species (Johnson et al. 2005, Vors et al. 2007). Several types of human disturbance have been shown to reduce the value of natural areas for biodiversity and conservation. For example, human settlement, roads, and land use have significant impacts on biodiversity (Woolmer et al. 2008). Additionally, resource extraction associated with oil and gas wells and mining have demonstrated negative impacts to habitat and species (Sanderson et al. 2002, Sawyer et al. 2006).

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Conservation of large and intact landscapes that contain endemic biodiversity is essential to maintaining the full set of conservation targets in an ecoregion (Schneider 2001, Bottrill et al. 2008). Given the relationship between disturbance and biodiversity our index functions as a measure of ecological disturbance, and a generalized coarse-scale measure of relative cost of conservation effort as well as a proxy of potential habitat value1. The resulting disturbance surface is shown in Figure 6b. The disturbance index serves two purposes: first, for site selection in the landscape level analysis, as described here, and second, to classify potential offset areas according to ecological condition, as described in section 3.2. We recognize that our disturbance index does not account for investments in management activities or lands designated with formal conservation protection such as the Credo Station managed by DEC or the Rowles Lagoon Conservation Park. Nonetheless, we are comfortable with the use of the index as applied here since the primary use of the disturbance index was to classify offset areas within the Barrick pastoral leases where conservation investments of this nature are not of the same extent. iv. build an analysis framework. To create a GIS framework for the site selection analysis it is necessary to identify a set of discrete planning units (PUs) across the study area. For this analysis we defined PUs based on a combination of a) pastoral lease boundaries and b) roadless areas delineated by all roads and unsealed tracks ( GEODATA TOPO 1:250k; GeoScience Australia 2006). We then populated this PU framework as follows: 

measured the amount (area) of each habitat element type in each PU



calculated the average disturbance index values for each PU.

v. site selection Finally, we evaluated various scenarios, or sets of possible offset sites, that meet representation targets for habitat elements while optimizing for efficiency and condition (least disturbed, based on the disturbance index). We conducted this analysis using a software package called MARXAN (Ball & Possingham 2000, Possingham et al. 2000), which was designed for conservation planning and allows the integration of many available spatial data sets on land-use patterns and conservation status, and enables a rapid evaluation of alternative configurations. The site-level analysis found that all habitat types that occur in the Kanowna Belle Mining Footprint also occur in the Barrick Kanowna pastoral leases. For all of those habitat elements, the pastoral leases contain the same amount or more, meaning representation targets can be met within Barrick-owned pastoral leases. Results of the site-level analysis are listed in Appendix C.

1

It is recognised that the disturbance surface generated is based on available data and assumptions. It may be that there are some areas of high ecological integrity within areas mapped as poor quality. This would require ground truthing.

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The landscape-level analysis found that all of the optimal offset sites occur in the area near Kanowna Belle mine operations and pastoral leases. This is not surprising, since areas near the mine operations are more likely to contain similar habitat, but it indicates that offset actions in the Kanowna pastoral leases, in theory at least, are likely to contribute to conservation priorities across the region.

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3.0 Offset Accounting: Options for Achieving the No Net Loss Goal Policies to guide the design and implementation of biodiversity offsets are being established at an increasing rate. According to the 2011 State of the Biodiversity Markets study, there are “45 existing compensatory mitigation programs around the world, ranging from programs with active mitigation banking of biodiversity credits to programs channeling development impact fees to policies that drive one-off offsets. There are another 27 programs in various stages of development or investigation” (Madsen et al. 2011). Across these policies and programs, the stated goal is quite consistent: to achieve no net loss or a net gain for biodiversity (McKenney and Kiesecker 2010). Drawing on the guidance and experience of these approaches, the DbD offset accounting framework focuses on ensuring offsets provide benefits that are ecologically equivalent to those lost due to impacts, and that standard accounting principles are applied in assessing how much offset is enough to fully compensate for project impacts. 3.1 Offset Accounting Principles We begin by identifying a portfolio of possible offsets that, in comparison to the impact site, can provide ecological equivalency (here based on vegetation classification) and equivalent or better ecological quality as defined by condition as well as ensuring that offsets would contribute to landscape-level conservation (Section 2.5). This portfolio of offsets represents the best opportunities for taking protection, management, and/or restoration actions that can contribute toward achieving the no net loss goal. As noted above, our site-level and landscape-level analysis found that optimal offset sites (areas that best meet ecological equivalence targets and contribute to regional conservation priorities) occur within Barrick’s pastoral lease areas. After selection of an offset portfolio, the next question is which offset areas in that portfolio should be selected for implementation. The aim is to identify offsets within the portfolio that will deliver the greatest contribution toward achieving no net loss at the lowest cost and risk. To measure the potential contribution of offset options toward the no net loss goal, we consider several important factors, including: (a)

“Additionality” – an option’s new contribution to conservation, additional to existing values. When offsets restore degraded ecosystems, they provide a new contribution to conservation over time as the restoration supports improvements in those ecosystems. Offsets that preserve or improve management of habitat also deliver conservation value when, taking into account real-world conditions and threats, those offsets protect against an expected background rate of loss. For this analysis we consider the additional conservation values associated with management and restoration actions that include fire suppression in old growth areas, de-stocking of cattle, removal of artificial watering sources, and continued investment in ongoing management activities such as control of non-native species, and other actions which could occur within the pastoral leases.

(b)

Probability of success – the likelihood that an option will deliver expected conservation benefits. The success of conservation actions can vary greatly depending on the ecosystem, restoration and management techniques, and other factors. In some cases, approaches are known to be effective, but in other situations

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there may be great uncertainty due to a lack of experience. For example, we examine the effectiveness of restoring areas impacted as a result of potential cattle over-grazing (currently the dominate form of land use on the offset sites identified is grazing). Where cattle and watering sources are removed or decreased, problems of overgrazing diminish and ecological systems and species recover over time. Studies and experience indicate these actions have a high probability of success (See Appendix B). (c)

Timing and duration of project impacts and offset benefits – the need to account for temporal differences between project impacts and offset benefits. Project impacts and the restoration of impacted areas occur at different points in time. Likewise, an offset involving restoration actions will have a time-lag before conservation benefits mature. This time-lag, when weighed against an immediate project impact, represents a loss for biodiversity and should be accounted for in estimates of offset benefits. And for offsets focused on preserving habitat, while the delivery of conservation benefits begins at the moment of implementation, the level of benefits depends on the expected background rate of loss for the site over time. To address differences in timing of project impacts and offset benefits, we apply a discount rate – a commonly used method for estimating the present value of future values.

3.2 Portfolio of Potential Offset Sites and Conservation Actions Our assessment indicates Barrick’s pastoral lease areas could provide offset opportunities for protection, management, and restoration actions that would deliver ecologically equivalent values to what was lost due to project impacts at the lowest cost and risk (Section 2.5). We divide the pastoral lease areas into four broad categories based on habitat type and condition (Table 3): 

Old growth area (46,998 ha): remaining old growth forest, delineated by Ian Kealley (DEC, 2011), as shown in Figure 7. Old growth areas were identified given their high value for species, the limited amount of old growth woodland remaining in the Great Western Woodlands and the risk that fire poses to the remaining old growth woodland.

In the remaining area, excluding old growth: 

High condition area (158,447 ha): the least-disturbed 50% of the area, i.e., top 50th percentile, based on the disturbance index (described in Section 2.5) and summarized by analysis units defined by pastoral leases, land use zones and roadless blocks, as shown in Figure 7.



Medium condition area (142,331 ha): the area in the 10th to 40th percentile, based on the disturbance index and summarized by analysis units. When old growth and medium condition areas overlapped they were classified as old growth given their importance and rarity, but would need to be verified on the ground.



Low condition area (38,276 ha): the most-disturbed 10% of the area, or lowest 10th percentile, based on the disturbance index and summarized by analysis units. 25

We used expert opinion to estimate the potential distribution of old growth forest in our study area. The accuracy of these predictions has not been assessed in the field and are not intended to estimate old growth forest outside of the Barrick pastoral leases.

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Table 3. Distribution of pastoral lease area by habitat type (old growth) and condition (high/medium) and possible offset actions. High 158,447 ha Actions 1 Protect old growth through fire management 2 De-stocking pastoral leases 3 4

Removing artificial water sources (number*) Road closures or track closures Recapping drill holes (data: mines dept -> old mine shafts)

6

Control of invasive species (e.g., goats, donkeys, camels)

7 8 9 10

Control of invasive species (plants) Non-native predator control Supplementary faunal habitat Active restoration (e.g., reseeding)

Old growth 46,998 ha















(35)



5

Medium 142,331 ha



(64)





(18)



 





 

as needed



as needed



as needed



as needed

 as needed * possible artificial water sources include all water holes, bores, wind pumps and water tanks mapped in GEODATA TOPO 250k (GeoScience Australia, 2006)

A suite of offset actions for the old growth, high condition, and medium condition areas that includes de-stocking, removing artificial water sources, road/track closures, and recapping drill holes could be implemented towards achieving no net loss (Table 3). In addition to these actions, development of fire suppression/management plans for old growth areas to reduce risk of uncontrolled damaging fires would be beneficial, as well as a number of additional offset actions for medium condition areas (i.e., active reseeding or re-planting or other forms of active restoration) in order to improve the condition. A degree of uncertainty remains around the value of offset investments without some security that elevates the conservation value in the land use decision making process. For further discussion regarding security of offset investments see the offset options section below. Low quality sites should not be considered for offset actions as these are the least cost effective options given the high amount of disturbance and high risk to improve these areas2.

3.3 Accounting Framework: Assumptions and Estimates Assessing progress towards the no net loss goal requires comparison of project impacts and offsets benefits. Table 4 provides a summary of assumptions and estimates to support this comparison. Of particular importance for the accounting framework are: (a) the “currency,” 2

Given the precision of the data it is recognised that some high quality sites are likely to be present amongst areas modelled as low quality.

27

which allows for an “apples to apples” comparison of project impacts to the offset benefits, (b) discounting, which supports comparison of impacts and benefits occurring during different time periods, and (c) the probability of success and additionality estimates for offset actions. Note that in the case of Kanowna Belle the type of vegetation actually impacted is unknown, so preEuropean vegetation maps were consulted to compare project impacts to offset benefits. Habitat lost and gained is assumed comparable. For an accounting currency, we use hectare-years to reflect the spatial and temporal elements of impacts and benefits. For example, an impact of 100 hectares in Year 1 that continues through Year 2 represents 200 hectare-years of impact at the end of Year 2 (undiscounted). An offset that restores 100 hectares over five years at a rate of 20 ha/year (20 + 40 + 60 + 80 + 100) provides 300 hectare-years of benefit at the end of Year 5 (undiscounted). The hectare-years currency allows us to compare impacts and benefits for different spatial extents over different periods of time. Discounting is a widely used economic tool for weighing past and future benefits or costs so that they are comparable to present benefits and costs. For purposes here, discounting is necessary for calculating the present value of project impacts, on-site restoration of these impacts, and benefits of offset actions, all of which can occur over different periods of time. We apply a discount rate of three percent, which is the longstanding recommended rate for discounting losses and gains for compensatory actions (National Oceanic and Atmospheric Administration 1999).

3.4 Offset Options for Achieving the No Net Loss Goal To compare project impacts to offset benefits, we use a currency of hectare-years and apply the offset accounting assumptions and estimates in Table 4. We estimate hectare-years of project impact (total and by management status) and hectare-years of offset benefit for old growth, high condition, and medium condition options (Table 5). We calculate hectare-years of project impact as follows: the project impact of 78,230 ha exists for seven years, after which 91 percent of this footprint is restored over the following 20 years (five percent/year rate of recovery). Applying a discount rate of three percent, we estimate an impact of about 1.1 million hectareyears over a 27-year period. We then segment these hectare-years of impact in accordance with management status. The 7 year footprint was based on the time period when Barrick first released their biodiversity standard in 2009 until the estimated time to mine closure in 2016. We estimate the hectare-years of benefit provided by offset options in a similar manner. For example, for the old growth area of 46,998 ha, we expect protection, restoration, and management actions will have a 95 percent probability of success, the site will improve in conservation value by 40 percent compared to current conditions, and it will take 20 years to achieve conservation benefits (Table 4). Estimates of improved condition are based on restoration activities of mining sites in Western Australia that measure percent changes in biological condition (i.e., percent vegetation cover) and increases in ecological function (i.e., nutrient retention) (Tongway and Ludwig 2010, Appendix E). We assume that fire management targeted at preventing large scale fires will help protect the old growth area in the face of a 1.1 percent probability of fire. Applying a discount rate of three percent, we estimate offset benefits for the old growth area of 294,158 hectare-years over a 27-year period (equal to time of impacts).

28

Estimates of hectare-years of benefit for high and medium condition areas are calculated similarly, based on the actions proposed for these areas and assumptions and estimates in Table 4. We recognize that changes to the estimates of how much conservation actions improve conditions would result in changes to our estimates of additionality and in turn amount of offset needed. In particular we want to note that research is needed to improve understanding of fire regimes and fire intervals in the GWW. Obviously changes in the understanding of fire risk for the old growth systems would result in changes in the estimate of additionality fire prevention would deliver.

29

Table 4. Offset accounting: Assumptions and estimates Accounting elements

Assumptions & estimates

Explanation of basis for estimates and assumptions

“Currency” to compare project impacts to offset benefits

Hectare-years of impact compared to hectare-years of offset

A currency that incorporates spatial and temporal elements is necessary for comparing project impacts to offset benefits over time.

Discount rate for comparing impacts and benefits over time

3 percent

Longstanding recommended rate for discounting losses and gains for compensatory actions (National Oceanic and Atmospheric Administration 1999)

Total area of impact

78,230 ha

See Table 2.

Years of impact

7 years

Duration of impacts from Barrick operations, from time of establishing a new biodiversity standard in 2009 to estimated mine closure in 2016. If mining activities continue beyond 2016 then estimates offset amount will need to the revisited.

Years to restoration of impact

20 years

Estimate of how long it will take to restore impacted areas that can be restored (See Appendix B, Tongway and Ludwig. 2010). Based on 20 year estimate, restoration occurs at a rate of 5%/year.

Recoverable area of footprint

91 percent

Some areas of the footprint can be restored and others will be permanently impacted (i.e., pit, etc.). See Table 2.

347,776 ha

Area of potential offsets within pastoral leases. This includes potential Old Growth area, high condition, and medium condition areas. Low condition area is excluded due to poor opportunities for achieving offset benefits. See Section 3.2 and Table 6.

Potential Old Growth area

46,998 ha

Based on expert opinion about the location of Old Growth areas (Section 3.2 and Figure 7)

High condition

158,447 ha

Estimated from Disturbance Index. Section 2.5, 3.2, Figs. 6a & 6b, and Table 6.

Medium condition

142,331 ha

Estimated from Disturbance Index. Section 2.5, 3.2, Figs 6a & 6b, and Table 6.

Background rate of loss/yr (due to fire)

1.06 percent/year

Based on estimates of annual losses due to fire in the Great Western Woodlands (Barrett et al. 2009, Daniel 2010). We assume an effective fire suppression/management plan, as a protection measure, would reduce this rate of loss for areas where it is implemented.

Additionality of restoration actions (current condition to reference condition)

40 percent (old growth & high condition areas)

Based on the Disturbance Index and assumptions that restoration of less degraded areas provides less additionality (new contribution to conservation) than areas that are more degraded and require more intensive restoration actions.

Probability of success of conservation actions

95 percent (protection and restoration of old growth areas)

Impact/Footprint

Potential Offset Areas Total area of potential offsets

60 percent (medium condition areas)

50 percent (restoration of medium condition areas)

Based on a review of literature on the probability of success for protection, management, and restoration actions (Appendix C & D). Compared to high condition areas, we assume a lower probability of success for medium condition areas, which require more intensive actions. We also assume implementing a fire suppression/management plan will modestly increase the probability of successful outcomes for old growth areas (increasing to 95 percent from 80 percent)

Fire reduction is immediate upon implementation of management plan; Restoration will take 20 yrs.

We assume a fire management plan to suppress damaging fires can be developed and implemented immediately with the first offset actions. Full restoration is expected to require 20 years (Appendix C & D)

80 percent (restoration of high condition areas)

Timing (years to achieving conservation goals)

30

Table 5. Project impacts and offset options Project impacts Area Currency Offset-to-impact by management status (ha) (ha-yrs) ratio* 1. Barrick 100 percent owned and operated 42,630 600,284 2. Barrick joint venture managed by Barrick 15,010 211,363 3. Barrick joint venture not managed by Barrick 20,589 289,92 Total 78,230 1,101,569 Offset options Old growth areas 46,998 294,158 2.2 to 1 High condition areas 158,447 534,074 4.2 to 1 Medium condition areas 142,331 449,767 4.5 to 1 Total 347,776 1,277,999 3.8 to 1 *The offset-to-impact ratio reflects how many hectares of offset in each condition area should be fully implemented for each hectare of impact. The ratio is calculated using the hectare-year currency as follows. Consider the old growth areas offset: 46,998 ha offset providing 294,158 ha-yrs of benefit vs. 78,230 ha impact area resulting in 1,101,569 ha-yrs of impact. Solving for the offset-to-impact ratio (46,998/78,230=294,158/1,101,569) = 2.2 to 1.

Based on project impacts and potential offset actions, we provide a summary of offset options in Table 6. We estimate that through implementation of conservation actions on its pastoral leases Barrick could achieve ‘no net loss’ for habitat at the Kanowna Belle mining areas. To facilitate Barrick’s consideration of offset options for implementation, highest priority offset actions (i.e., old growth) where Barrick’s management status is strongest would be considered as first priority. However, to achieve no net loss addressing the full extent of Barrick’s impacts (1.1 mil ha-yrs); offset actions would need to be implemented for all areas – old growth, high condition, and medium condition (1.3 mil ha-yrs). By doing so, it is estimated Barrick would achieve a net positive result, providing 16 percent more benefit than loss (1.3 mil ha-yrs > 1.1 mil ha-yrs) (Figure 8). Table 6. Proposed offset actions to achieve no net loss goal, by management status Management Status 1. Barrick 100 percent owned and operated 2. Barrick joint venture managed by Barrick 3. Barrick joint venture not managed by Barrick Total

Impact (ha-yrs) 600,284

Offset (ha-yrs) Old growth = 294,158 High condition = 306,127

211,363

High condition = 211,363

289,922

High condition = 16,584 Medium condition = 273,338

1,101,569

All offsets = 1,277,999

31

Proposed offset actions Implement offset actions for all old growth & 57% of high condition Implement offset actions for 40% of remaining high condition areas Implement offset actions for remaining 3% percent of high condition areas and for 61% of medium condition areas Implement offset actions for all areas: old growth, high condition, and medium condition

Figure 8: Total project impacts compared to implementation of all proposed activities

Project Impacts vs. Offset Benefits 90000 80000

Hectare-Years

70000 60000 50000

Impact total = 1.1 mil ha-yrs

40000

Offset total = 1.3 mil ha-yrs

30000 20000 10000 0 -

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Time in years Offset Benefits

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Project Impacts

4.0 Discussion of Proposed Conservation Activities At a desktop level, Barrick’s pastoral leases appear to provide offset opportunities for management and restoration actions that could deliver a no-net-loss outcome with ecologically equivalent values to what was impacted by mining activities. Here we calculated no-net-loss based on impacts associated with the 7 year time period from when Barrick developed their biodiversity standard in July of 2009 until their current estimated mine closure date of 2016. Their standard requires that where significant biodiversity impacts around mining operations cannot be avoided, Barrick operations and projects are responsible to minimize, mitigate and compensate fairly for those impacts. However we recognized that the estimate of no-net-loss calculated for this time period would likely underestimate the impacts of the mine as a whole. For Barrick to claim no-net-loss of the entire mine site activities the time period would need to be extended to include all of the time mining was conducted at the Kanowna Belle sites. Moreover, if mining activities were to continue beyond the currently permitted area and projected mine closure was extended beyond 2016, the estimate of offsets needed to achieve nonet-loss will need to be revisited. Offsets that target key management issues for the pastoral lease areas with offset actions are most likely to deliver a high conservation return on investment. For this reason potential offset activities were based on habitat type and condition. Old Growth Woodlands (46,998 ha) were identified given their high value for species, the limited amount of old growth woodland remaining in the Great Western Woodlands and the risk that fire possess to the remaining old growth woodlands. Given the relative importance of old growth areas for the Great Western Woodlands, these areas would be given priority consideration for use as offset sites. While it is unlikely that old growth areas were lost as a result of mining activities on the Kanowna Belle sites during Barrick’s tenure, there is added value both from a conservation perspective as well as from an offset valuation perspective to favor these areas. A bundle of management activities (de-stocking, removing artificial water sources, closing roads/tracks where possible, and removing exploration drill holes) would improve the condition of vegetation and remove a major source of mortality for small- and medium-size animals in this area. Cumulatively, impacts from mining operations, infrastructure and land conversion in general often have a multiplicative effect on habitat quality and habitat use. For that reason, applying the full set of possible offset actions is necessary for habitat improvement. In high condition areas (158,447 ha) focusing on a similar bundle of offset actions (de-stocking, removing artificial water sources, closing roads/tracks where possible, and removing exploration drill holes) is also most likely to provide a high conservation return on investment. These areas with high quality habitat because of fewer anthropogenic disturbances and larger patch sizes investments have a higher probability of succeeding and should be given priority for offset investment second to Old Growth. The same suite of high-return bundle of management actions described above should be implemented in medium condition areas (142,331 ha). In addition, given that these areas are likely to be further degraded by human activities additional actions (i.e., re-seeding, invasive weed treatments) would be necessary to improve conditions. Offset actions within areas of low condition are considered high risk and not cost-effective. 33

For Barrick to achieve a no-net-loss outcome Barrick would need to address impacts associated with all of the management categories associated with its activities: Barrick 100 percent owned and operated; Barrick joint venture managed by Barrick; and Barrick joint venture not managed by Barrick. Although this desktop analysis demonstrates opportunities to achieve nonet-loss in theory within Barrick’s current pastoral lease system, pastoral lease obligations currently inhibit the potential for Kanowna Belle to fully leverage the offset opportunities to deliver no net environmental loss. Under the Lands Act, the primary legislation relevant to pastoral lease management, there are a number of stipulations regarding specific activities that must be undertaken (i.e., the commercial grazing of authorized stock). Many of these stipulations run counter to the conservation-minded management activities that would serve to offset the impacts associated with Barrick’s mining activities. Moreover, these stipulations make it difficult to legally secure conservation outcomes on pastoral leases making the long-term success of proposed actions uncertain at this time. However, the Western Australian Government is in the process of exploring new tenure options for rangelands as part of broader rangelands reform3. Included as part of the Rangelands Tenure Options Discussion Paper released in April 2011, a new lease type ‘Conservation Lease’ was proposed. While a conservation lease would not preclude mining and exploration, it would remove the requirement to manage a lease as a pastoral property and thus graze the lease with livestock (and provide infrastructure to enable this grazing) and it would recognize conservation as a primary purpose. If a conservation lease mechanism is established by the Western Australian Government, a conservation lease could be applied to the Barrick pastoral holdings in order to better secure offsets. The proposed ‘Conservation Lease mechanism’ in other words would provide greater opportunity to enhance biodiversity outcomes by removing the requirement to run stock, amongst other provisions. If opportunities present themselves to implement proposed actions, an implementation plan to review and operationalize the result of the DbD analyses presented here would be appropriate. A key component of the plan would be defining necessary monitoring to accompany implementation of activities. Monitoring would be implemented for a period of time relevant to capture biological responses and include a mechanism for making information publically available. 3

See: Department of Regional Development and Lands (2011). Rangelands Tenure Options Discussion Paper. April 2011. http://www.rdl.wa.gov.au/publications/Documents/Rangelands%20Tenure%20Options%20%20Discussion%20paper.pdf

34

5.0 Closing Remarks from Barrick The Cooperative Development by Design report for Kanowna Belle was put together at a time when Barrick’s 2009 Biodiversity Standard strived to achieve no net loss for significant impacts which could not be avoided, minimized or mitigated by operations from exploration to closure. The learning which has occurred through the first round of piloting this Standard, illustrates that baseline information at some existing operations was not collected in a way that would clearly determine what could be considered ‘significant’ or quantified to a point where no net loss could be clearly demonstrated. At Kanowna Belle, for example, given deforestation practices since the beginning of the century it is difficult to determine if impacts to standing Great Western Woodland species or already modified habitat occurred as a result of current day mining operations.

35

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Appendix A. Working group participants and kickoff meeting agenda Name Keith Bradby Neil Gibson Ric How Ian Kealley Amanda Keesing Peter Price Suzanne Prober Wayne O’Sullivan Melissa Barbanell Allison Brown Adrian Lally Ben Wither James Fitzsimons Mike Heiner Joseph Kiesecker Bruce McKenney Kei Sochi

Affiliation Gondwana Link Western Australian Department of Environment and Conservation Western Australian Museum Western Australian Department of Environment and Conservation Gondwana Link Gondwana Link CSIRO The Wilderness Society, Inc. Barrick Gold Corporation Barrick Australia Pacific Barrick Kanowna Belle Barrick Australia Pacific The Nature Conservancy The Nature Conservancy The Nature Conservancy The Nature Conservancy The Nature Conservancy

Appendix A. Working group participants and kickoff meeting agenda - 40

Agenda: The Nature Conservancy and Barrick Gold Corporation - Development by Design Date:

Thursday 10 March from 9:00 am - 5:00 pm & Friday 11 March from 9:00 am - 4:00 pm

Location:

Mining Hall of Fame, Goldfields Highway, Kalgoorlie

Participants:

Please see the full list of participants and affiliations attached

Goal:

To introduce Development by Design concepts, discuss project goals and deliverables, Identify team members, Discuss project boundaries and representative biodiversity, and discuss the work plan.

DAY 1

Thursday 10 March

9:00

Introductions

All

9:15

Welcome

Natalie Holland James Fitzsimons Joseph Kiesecker Bruce McKenney Melissa Barbanell

Overview of the day Project objectives 9:30

11.15 11.30

Overview of Development by Design: (1) Demonstrate how DbD can be used to offset impacts from the Kanowna Belle Mine (2) Steps of the DbD process (3) Discuss how DbD will blend with ongoing Conservation Planning. Goals: (1) Establish Working Group and introduce DbD; (2) Establish project boundaries; (3) Discuss biodiversity targets; (4) Provide overview of data needs to support DbD; (5) Discuss workplan for DbD and role of WG. Morning Tea

Joseph Kiesecker

Overview of Kanowna Belle Mine Impacts, Barrick Holdings in GWW and GIS data available for use in project  Overview of Kanowna Belle operation  Virtual tour using GIS applications of mine site and pastoral leases

Ben Wither, Adrian Lally



12:30 1:30

GIS data available for use in project  Environmental management and monitoring programs Lunch break State of Conservation Planning in The Great Western Woodlands: Discuss what work has already been done regarding conservation planning in the GWW.

Keith Bradby Wayne O’Sullivan

Appendix A. Working group participants and kickoff meeting agenda - 41

2:30

Mike Heiner & Kei Sochi

Provide overview of data needs to support DbD Deeper dive into data needs and analysis steps.

4:30

Break Discuss Next Steps

5:00

Adjourn

7:00

Group Dinner

DAY 2

Friday 11 March

9:00-3:00

Field Trip of Barrick Mine and Holdings in GWW  Mine public viewing areas  Pastoral lease area

Joseph Kiesecker Bruce McKenney

Discussion and wrap up

Participants Name Suzanne Prober Ric How Ian Kealley

Position Senior Research Scientist Senior Curator, Department of Terrestrial Zoology Regional Manager Goldfields

Organisation CSIRO Ecosystem Sciences Western Australian Museum

Keith Bradby James Fitzsimons Peter Price

Principal Research Scientist, Western Australian Conservation Science Centre Director Director of Conservation Corporate Relations Manager

Ben Wither Adrian Lally Natalie Holland Bruce McKenney Joe Kiesecker Melissa Barbanell

EMS & Compliance Manager Community Compliance Manager Conservation Projects Manager Senior Economic Advisor, Conservation Lands Lead Scientist Senior Counsel, Regulatory Policy

Department of Environment and Conservation Department of Environment and Conservation Gondwana Link Ltd The Nature Conservancy Great Western Woodlands Collaboration Barrick Gold of Australia Barrick Gold of Australia The Nature Conservancy The Nature Conservancy The Nature Conservancy Barrick Gold

Blyth Spraggins Mike Heiner Kei Sochi Wayne O'Sullivan

Intern Ecoregional Scientist, Conservation Lands GIS Manager, Conservation Lands Project Director, Great Western Woodlands Collaboration

Gondwana Link The Nature Conservancy The Nature Conservancy Great Western Woodlands Collaboration

Neil Gibson

Appendix A. Working group participants and kickoff meeting agenda - 42

Appendix B. Summary of probability of success and timing to maturity for potential offset actions Timing to maturity to reference conditions

Actions

Probability of success (H/M/L) + notes

1

Old Growth Fire management targeted to prevent damaging fires

The benefits of fire prevention are likely to be immediately recognized in old growth woodlands since fire intervals are long and any effort to prevent fires will contribute to maintaining that interval. Research indicates that fire intervals in mature woodland communities are relatively long and may exceed 400 years.

2

De-stocking pastoral leases

LOW: Fire agencies, hampered by limited resources and access routes, have little capacity to effectively suppress bushfires in the GWW. Fire management in the area therefore is focused on pre-suppression activities such as fuel modification through prescribed burning. Bushfires in the GWW are most likely to originate within large patches of long unburnt shrubland or mallee - fires that affect woodlands often begin in shrublands or mallee and burn into wooded areas. Research indicates that without deliberate fire management in the GWW, it is very unlikely that long inter-fire intervals for woodland types will be able to be maintained. HIGH: Relatively high degree of confidence that removing grazing pressure (non-native as well as reducing artificial density of natives) results in significant increase in condition.

3

Removing dams

HIGH: High degree of confidence that removing artificial water sources will both reduce numbers of native and non-native grazers as well as shift vegetation back towards reference conditions and result in positive (towards reference conditions) changes in small mammal, reptile and bird communities. Quite a few references indicating impacts, fewer studies on the positive benefits of removal. Indirect impacts from water likely large: For sheep the proposed threshold is 3 km, 6 km for cattle and 7 km for red kangaroos.

Timing to maturity varies dependent of starting condition but like de-stocking can be from 5-25 years. Estimates are based on observations of restoration activities after removal of watering sources. Studies compared removal areas to undisturbed reference sites and estimates time to bring conditions of the restoration sites back to comparable conditions (see for example James et al. 1999)

Time to maturity depends to a large degree on condition at time of destocking. References suggest return times can be anywhere from 525 years Studies compared recover after destocking events and estimated time to bring conditions of the restoration sites back to comparable reference conditions (see for examples Lunt et al 2007)

Appendix B. Summary of probability of success and timing to maturity for potential offset actions - 43

Timing to maturity to reference conditions

Actions

Probability of success (H/M/L) + notes

4

Road closures or track closures

HIGH: Good data to show removing roads and tracks eliminates impacts of road activity: dust spread & indirect habitat avoidance due to activity and increase access. Impacts of altered hydrology and direct habitat loss of the road surface may still need to be addressed in some situations.

Benefit is assumed to be instantaneous once road activity is removed.

5

Recapping drill holes

HIGH: High degree of confidence that capping has a highly positive impacts on small mammals and reptiles

Effect is assumed to be instantaneous although data on long-term recovery is limited; short-term studies show fast response for both small mammals and reptiles.

6

Control of invasive species (e.g., goats, donkeys, camels)

MEDIUM & MIXED: Mixed data on the success of control programs for non-plant invasive species. Where extensive effort is applied some studies show benefit but applications must be widespread and need to be re-implemented periodically.

7

Control of invasive species (plants)

8.

Non-native predator control

MEDIUM to LOW but MIXED: Mixed data on the success of control programs for plant invasive species. Where extensive effort is applied some studies show benefit but applications must be widespread and need to be re-implemented periodically. MEDIUM: Mixed data on the success predator control programs. Like control efforts for invasive animals where extensive effort is applied, some studies show reductions in numbers of target predators but applications must be widespread and needs to be re-implemented periodically. Many studies question whether the dingo should be lumped into the same category as non-native predators (i.e., foxes) as they may have positive impacts on reducing the density of herbivores (e.g., kangaroo) and predators (e.g., cats). Thus we do not consider them as part of the control program

Limited info on time to maturity although assume that once action is implemented i.e. baiting, shooting, if they are effective, recovery can occur immediately. Timing to recovery for overgrazing by non-native invasive animals is likely to be similar to destocking estimate. Limited info on time to maturity although assume that once action is implemented i.e., spraying, if they are effective, recovery can occur immediately. With seed banks it is likely that recovery will be difficult, requiring multiple treatments over extended periods. Limited info on time to maturity although we assume that once action is implemented i.e., baiting, shooting, if effective, recovery can occur immediately. Estimates on timing of prey recovery after predator removal are limited.

Appendix B. Summary of probability of success and timing to maturity for potential offset actions - 44

Actions

Probability of success (H/M/L) + notes

Timing to maturity to reference conditions

opportunities here.

9

Supplementary faunal habitat (nest boxes, additional coarse woody debris etc.)

10 Active restoration (e.g., reseeding, thinning of thick regrowth)

MIXED: very dependent of the target species and more importantly the quality of habitat for use by target species.

MEDIUM to HIGH: Generally the success of active restoration will depend on the nature and intensity of disturbance. Minor disturbances can be restored with high probability of success while significant impacts, likely those associated with mine pits and tailing piles can be reclaimed but it is unlikely that they will be restored.

Limited info on time to maturity although we assume that once action is implemented i.e., "habitat" is created, utilization can occur immediately. Although may be dependent on other restoration activities i.e., bird breeding boxes only become effective habitat when restoration of surrounding vegetation is completed. Time to maturity depends to a large degree on condition at time of restoration activities. References suggest return times can be anywhere from 5-35 + years. Estimates are based on observations of restoration activities associated with mine sites. Studies compared active restoration areas to undisturbed reference sites and estimates time to bring conditions of the restoration sites back to comparable conditions (see for examples Tongway and Ludwig 2010)

Appendix B. Summary of probability of success and timing to maturity for potential offset actions - 45

Appendix C(i) Plant associations (NVIS Level 5)* occurring in Kanowna Bell Mining footprint and pastoral leases** * list includes only those occurring in Barrick Mining footprint ** Black Flag, Mount Burgess and Mungari

NVIS Level 4: Vegetation Sub-formations

Bare areas; rock outcrops Bare areas; salt lakes Maireana open chenopod shrubland Casuarina mixed open woodland / Eremophila mixed sparse shrubland / Atriplex open chenopod shrubland Acacia woodland / Acacia mixed sparse shrubland / Maireana mixed open chenopod shrubland

Acacia closed shrubland

NVIS Level 5: Plant associations

Bare areas; rock outcrops Bare areas; salt lakes G^Maireana sp., Atriplex sp.\chenopod\2\i U Casuarina cristata, Myoporum platycarpum, Callitris columellaris\tree\6\r;M Eremophila miniata, Grevillea sarissa\shrub\4\r;G^Atriplex hymenotheca\chenopod\2\i U^Acacia aneura,^Callitris columellaris,^Eucalyptus oleosa\tree\6\i;M Acacia hemiteles, Senna artemisioides subsp. petiolaris, Eremophila decipiens\shrub\3\r;G Maireana sedifolia, Ptilotus obovatus\chenopod,forb\2\i U^Acacia quadrimarginea, Acacia acuminata, Allocasuarina campestris\shrub\4\d

Acacia shrubland Allocasuarina open woodland / Atriplex chenopod shrubland

U^Acacia quadrimarginea\shrub\4\c U^Allocasuarina sp.\tree\6\rG Atriplex sp.\chenopod\2\c

Eucalyptus woodland / Eremophila open shrubland

U^Eucalyptus le souefii, Eucalyptus salmonophloia, Eucalyptus transcontinentalis\tree\7\i;M Eremophila scoparia, Eremophila alternifolia, Eremophila decipiens\shrub\4\i U^Eucalyptus oleosa, Eucalyptus griffithsii, Eucalyptus gracilis\mallee\5\iG Triodia scariosa\hummock grass\2\i U^Eucalyptus oleosa, Eucalyptus transcontinentalis\tree\6\iG Cratystylis conocephala\shrub\2\i U^Eucalyptus salmonophloia, Eucalyptus dundasii\tree\7\i U^Eucalyptus salmonophloia, Eucalyptus lesouefii, Eucalyptus salubris\tree\7\i

Eucalyptus open mallee shrubland / Triodia open hummock grassland Eucalyptus woodland / Cratystylis mixed open heath Eucalyptus woodland Eucalyptus woodland Eucalyptus woodland Eucalyptus woodland / Eremophila sparse shrubland

U^Eucalyptus salmonophloia\tree\7\i U^Eucalyptus torquata,^Eucalyptus le souefii, Eucalyptus clelandii\tree\6\i;M Eremophila scoparia, Eremophila glabra, Eremophila oldfieldii\shrub,chenopod\4\r

MINE FOOTPRINT

Pastoral Leases

area (ha)

area (ha)

fraction

(c)

(d)

= (d)/(c)

22 6,065

2,611 11,967

117.9 2.0

606

3,723

6.1

17,906

36,868

2.1

16,083

14,135

0.9

128 176

19,807 2,192

154.3 12.5

5,178

5,156

1.0

11,900

19,906

1.7

3,580

6,234

1.7

408

7,104

17.4

14,004

89,748

6.4

415 175

3,281 13,984

7.9 80.0

1,586

20,540

12.9

Appendix C(i) Plant associations (NVIS Level 5) occurring in Kanowna Bell Mining footprint and pastoral leases - 46

Appendix C(ii) Surficial Geology/Lithology types* occurring in Kanowna Bell Mining footprint and pastoral leases** * list includes only those occurring in Barrick Mining footprint ** Black Flag, Mount Burgess and Mungari

Lithology Type

greenstone

MINE FOOTPRINT

Pastoral Leases

area (ha)

area (ha)

fraction

(d)

(e)

= (e)/(d)

19,916

91,990

965

15,880

2

14,422

lateritic duricrust

1,997

17,287

alluvium

5,434

13,532

sand other

19,776

43,500

colluvium

26,458

135,964

3,684

6,179

mafic intrusive Ag granite

lacustrine sediment

Total

4.6 16.5 6,515.0 8.7 2.5 2.2 5.1 1.7

78,232

Appendix C(ii) Surficial Geology/Lithology types occurring in Kanowna Bell Mining footprint and pastoral leases - 47

Appendix D: Reclassification of surficial geology/lithology types to generalized surficial geology MAP SYMBOL

UNITNAME / FORMATION

LITH_GROUP

LITH_TYPE

1

-Pd

mafic, ultramafic, intermediate intrusions 74431

igneous mafic intrusive, igneous ultramafic intrusive

2

-Pz

breccia 74357

fault / shear rock

3

-Pzf

Fraser Complex - flaser gneiss and migmatite

high-grade metamorphic rock

felsic gneiss, migmatite

4

Aae

intermediate volcanic and volcaniclastic rocks 74244

igneous intermediate volcanic, igneous volcanic

andesite, basaltic andesite, volcaniclastic rock

Flaser gneiss with lit-par-lit microgranite; migmatite with plagioclase-quartz and magnetite-epidote-clinopyroxenegarnet-hornblende layers; Fraser Complex Intermediate volcanic and volcaniclastic rocks, intermediate schist; basaltic andesite; andesite, metaandesite, commonly porphyritic, locally carbonatealtered

5

Ab

metamorphosed mafic igneous rocks 74246

meta-igneous mafic

greenstone

Metamorphosed mafic igneous rocks undivided

igneous mafic volcanic, igneous mafic intrusive

basalt, komatiitic (high-Mg) basalt, andesite, agglomerate, mafic schist

6

7

8

9

Reclassified

dolerite, gabbro, norite, pyroxenite,

LITH_DESC Dolerite, gabbro, norite, pyroxenite, peridotite, diorite, tonalite; locally metamorphosed; rare biotite rock, amphibolite

breccia - fault

Quartz or quartzite breccia in fault zones

other

Aby

mafic extrusive rocks 74255

igneous mafic volcanic

basalt, komatiitic (high-Mg) basalt, agglomerate, mafic schist, dolerite

Ace

banded iron formation, chert 74256

sedimentary non-carbonate chemical or biochemical, argillaceous detrital sediment

banded iron formation, chert, slate, shale, sandstone

Basalt, high-Mg basalt, minor mafic intrusive rocks; some andesite; agglomerate; mafic schist; amphibolite; dolerite; komatiitic basalt; carbonated basalt; basaltic andesite; mafic rock interleaved with minor granitic rock Metabasalt, high-Mg basalt, tholeiitic basalt, carbonated basalt, agglomerate, mafic schist, dolerite, amphibolite; porphyritic basalt and dolerite; komatiitic basalt; mafic pyroclastics; minor mafic schist with granite intercalations Banded quartz-magnetite rock, banded iron formation, ferruginous chert, chert, quartz-grunerite rock; minor jaspilite and silicified slate and shale, exhalite, phyllite, chert breccia, sandstone, siltstone, agglomerate, tuff, silicic volcanic rocks

chert, banded iron formation 74260

sedimentary non-carbonate chemical or biochemical, metaigneous mafic

banded iron formation, amphibolite, ultramafic schist

Banded iron formation, chert, ferruginous chert; locally with jaspilite. Hornblende-grunerite-hematite-magnetitequartz rock; schistose amphibolite and ultramafic schist; silicified and commonly lateritised

Abe

Acy

mafic extrusive rocks 74248

10

Ade

mafic intrusive rocks 74263

igneous mafic intrusive

dolerite, gabbro, peridotite, pyroxenite, granophyre

11

Ady

mafic intrusive rocks 74270

igneous mafic intrusive

dolerite, gabbro, granophyre

Mafic intrusive rocks, medium to coarse-grained; layered mafic to ultramafic intrusions - dolerite, gabbro, olivine gabbro, peridotite, pyroxenite, leucogabbro, quartz dolerite, quartz gabbro, gabbronorite Mafic intrusive rocks, medium to coarse-grained; layered mafic to ultramafic intrusions; metadolerite; Medium to coarse-grained metagabbro, dolerite and granophyre, local ultramafic bases

Appendix D: Reclassification of surficial geology/lithology types to generalized surficial geology - 48

other

other

greenstone greenstone

greenstone

greenstone

other

other

mafic intrusive

mafic intrusive

MAP SYMBOL

UNITNAME / FORMATION

LITH_GROUP

LITH_TYPE

12

Aee

ultramafic and meta-ultramafic rock 74281

meta-igneous ultramafic intrusive

serpentinite, ultramafic schist

13

Afe

felsic volcanic and volcaniclastic rocks 74288

igneous volcanic, igneous felsic volcanic

porphyry, rhyolite, dacite, rhyodacite, andesite

monzogranite, granodiorite, granite, tonalite, quartz monzonite syenogranite

14 15

Ag Agaa

felsic intrusives 74292 Fair Adelaide Syenogranite

igneous felsic intrusive, igneous intermediate intrusive igneous felsic intrusive

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Agh Agha Aghc Aghd Aghe Aghi Aghk Aghki Aghl Aghp Aghr Aght Aghu Aghw Agid

hi-Ca granite 74296 Bali Monzogranite Credo Granodiorite Goat Dam Monzogranite Dardie Monzogranite Calooli Monzogranite Karramindie Monzogranite Kiaki Monzogranite Lone Hand Monzogranite Pioneer Granitoid Complex Rowles Lagoon Monzogranite Theatre Rocks Monzogranite Buldania Granitoid Complex Cawse Monzogranite Silt Dam Monzogranite

igneous felsic intrusive, igneous intermediate intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive meta-igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive

31 2

Agl Agla

low-Ca granite 74297 Ularring Monzogranite

igneous felsic intrusive igneous felsic intrusive

monzogranite, granodiorite, tonalite, quartz monzonite, monzogranite granodiorite monzogranite monzogranite monzogranite monzogranite monzogranite monzogranite monzogranite monzogranite monzogranite, granodiorite granodiorite monzogranite monzogranite syenogranite, alkali feldspar granite, monzogranite, granodiorite, monzogranite

33 34 35 36 37

Aglb Aglm Agln Aglu Agmb

Bullabulling Monzogranite Mungari Monzogranite Lake Dundas Monzogranite Dunnsville Granodiorite Bonnie Vale Tonalite

igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive

monzogranite monzogranite monzogranite granodiorite tonalite

38

Agmd

Depot Granodiorite

igneous felsic intrusive

39 40 41 42

Agmh Agmk Agml Agmo

Red Hill Granitoid Complex Kintore Tonalite Liberty Granodiorite Doyle Dam Granodiorite

igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive igneous felsic intrusive

granodiorite, tonalite syenogranite, monzogranite, granodiorite tonalite granodiorite granodiorite

LITH_DESC Tremolite-actinolite-chlorite rock +/- carbonate, serpentinite, ultramafic schist, tremolite-chlorite schist, tremolite-chlorite-talc schist, talc-chlorite-tremolite rock, peridotite, talc carbonate chlorite serpentinite schist Quartz-feldspar (meta-) porphyry, porphyritic microgranite; rhyolite, dacite, rhyodacite, andesite; agglomerate, breccia tuff; felsic schist; felsic volcanic and volcaniclastic rocks; dacite and rhyodacite tuff; dacite porphyry; Undifferentiated felsic intrusive rocks, including monzogranite, granodiorite, granite, tonalite, quartz monzonite, syenogranite, diorite, monzodiorite, pegmatite. Locally metamorphosed, foliated, gneissic. Local abundant mafic and ultramafic inclusions Syenogranite Monzogranite, granodiorite, tonalite, quartz monzonite; in places recrystallised and foliated; some mixed granite and country rock assemblages; high-Ca granite Monzogranite; Hi-Ca granite Granodiorite; Hi-Ca granite Monzogranite; Hi-Ca granite Monzogranite; Hi-Ca granite Monzogranite; Hi-Ca granite Recrystallised biotite monzogranite; Hi-Ca granite Leucomonzogranite; Hi-Ca granite Monzogranite; Hi-Ca granite Monzogranite with orthogneiss enclaves; Hi-Ca granite Monzogranite; Hi-Ca granite Monzogranite, granodiorite; Hi-Ca granite Granodiorite; Hi-Ca granite Monzogranite; Hi-Ca granite Monzogranite Syenogranite, alkali-feldspar granite, monzogranite; in places recrystallised; some mixed granite and country rock assemblages; low-Ca granite Monzogranite; low-Ca granite Foliated, partly recrystallised monzogranite with scattered microcline phenocrysts; low-Ca granite Monzogranite; low-Ca granite Monzogranite; low-Ca granite Granodiorite; low-Ca granite Tonalite; mafic granite. Hornblende granodiorite and tonalite with scattered microcline phenocrysts; mafic granite Syenogranite, monzogranite, granodiorite; mafic granite Tonalite; mafic granite Granodiorite; mafic granite Hornblende-biotite granodiorite; low-Ca granite

Appendix D: Reclassification of surficial geology/lithology types to generalized surficial geology - 49

Reclassified

Greenstone

Greenstone

Ag granite Ag granite

Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite

Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite Ag granite

43 44

MAP SYMBOL Agmr Agmt

UNITNAME / FORMATION Lake Brazier Tonalite Two Gum Monzogranite

45

Ags

syenite, monzonite 74299

46

Agse

47

Erayinia Granite Complex

igneous intermediate intrusive, igneous felsic intrusive igneous felsic intrusive, igneous intermediate intrusive

LITH_TYPE tonalite, granodiorite monzogranite syenite, quartz syenite, quartz monzonite, syenogranite, monzogranite syenogranite, quartz syenite, syenite, quartz monzonite,

Ahe

hornfels 74301

metasedimentary siliciclastic

hornfels

48

Aje

volcaniclastic rocks 74303

igneous volcanic, igneous felsic volcanic

volcaniclastic rock, felsic volcanic, felsic schist

49

Ame

calc-silicate rocks 74306

metasedimentary carbonate

calc-silicate, marble, paraamphibolite

high-grade metamorphic rock

felsic gneiss, mafic granulite, felsic granulite, banded iron formation, migmatite

gneiss, granulite, migmatite 74310 granite gneiss - high-Ca type 74313

50

An

51

Anh

52

Anhf

53

Anl

Fifty Mile Tank Gneiss granitic gneiss - low-Ca type 74315

54

Are

55

56

LITH_GROUP igneous felsic intrusive igneous felsic intrusive

high-grade metamorphic rock, meta-igneous mafic

felsic gneiss, migmatite felsic gneiss, monzogranite,greenstone, pegmatite

high-grade metamorphic rock

migmatite

metamorphosed felsic igneous rocks 74318

igneous volcanic, igneous felsic volcanic

porphyry, felsic volcanic

Ase

sedimentary rocks 74322

argillaceous detrital sediment, sedimentary siliciclastic

phyllite, siltstone, sandstone, greywacke, conglomerate

Aty

amphibolite 74334

meta-igneous mafic

amphibolite

57

Aue

ultramafic and minor mafic rocks 74475

58

Ave

igneous ultramafic intrusive, meta-igneous ultramafic volcanic igneous felsic volcanic, igneous mafic volcanic

59

Awe

felsic and mafic volcanics 74395 undivided sedimentary and volcanic rocks 74481

high-grade metamorphic rock

sedimentary, igneous volcanic

LITH_DESC Tonalite, granodiorite; mafic granite Monzogranite; mafic granite Syenite, alkali-feldspar syenite, hornblende quartz monzonite, syenogranite, monzogranite; syenite group Syenogranite, quartz syenite, syenite, quartz monzonite; syenite group Hornfelsed psammitic and pelitic rocks with sillimanite, biotite, garnet; pyroxene hornfels Felsic (silicic or intermediate) volcaniclastic conglomerate, sandstone, tuff, breccia; metasedimentary rock derived from or with felsic volcanogenic provenance; minor volcanic rocks and quartz-feldspar schist. Banded two-feldspar-epidote-actinolite-quartz rock; metamorphosed carbonate-rich sedimentary rocks, mainly dolomite; para-amphibolite Banded granitic gneiss (monzogranitic to granodioritic), quartzofeldspathic gneiss with mafic bands, migmatite, granofels, mafic and felsic granulites, hyperstheneplagioclase-quartz granulite; schist, pelitic or mafic granofels Banded to agmatitic felsic and/or granitic gneiss, migmatite; high-Ca group Quartzofeldspathic gneiss, minor monzogranite, mafic to ultramafic enclaves and deformed pegmatite veins common; high-Ca group

Reclassified Ag granite Ag granite

Ag granite Ag granite other

greenstone

greenstone

other other

other other

ultramafic schist, metapyroxenite, peridotite, pyroxenite, serpentinite

Migmatite; low-Ca group Metamorphosed feldspar porphyry and undifferentiated felsic volcanic rocks; quartz-feldspar schist and quartzmuscovite schist derived from felsic volcanic rock or granite Phyllitic schist, siltstone, sandstone, greywacke, pelite, conglomerate, quartzite, phyllite, shale, slate, claystone, chert, minor felsic volcanic and volcaniclastic rocks; arkose, para- and orthoamphibolites; rare banded iron formation Amphibolite, mafic schist, mafic rock intercalated with granite, para-amphibolite; metabasalt, metagabbro, metapyroxenite and metadolerite; Youanmi Terrane Tremolite-chlorite-talc amphibolite, metapyroxenite, pyroxenite, peridotite, serpentinite, ultramafic schists, komatiite, high-Mg basalt; also chalcedony, silica, jasper, silcrete, silica cap rock on ultramafic rocks

felsic volcanic, mafic volcanic sedimentary rock, felsic volcanic, volcanic rock

Felsic and mafic volcanic rocks, some granite intercalations Undivided sedimentary (non-volcanic) and felsic volcanic rocks

greenstone

Appendix D: Reclassification of surficial geology/lithology types to generalized surficial geology - 50

other

greenstone

greenstone

greenstone

greenstone

60

MAP SYMBOL

UNITNAME / FORMATION

LITH_GROUP

Awy

volcanic and sedimentary rocks 74483

sedimentary, igneous volcanic

LITH_TYPE

LITH_DESC Rhyodacitic porphyry, volcaniclastic rocks, tuff, paraamphibolite, quartzite, mafic schist, amphibolite, felsic rhyolite, volcaniclastic rock, tuff, volcanic rocks, mafic volcanic rocks, banded iron formation, para-amphibolite, quartzite siliciclastic rocks, ultramafic rocks, chert

Reclassified

greenstone

61

Axe

undivided rocks 74484

metasedimentary, meta-igneous , igneous felsic intrusive, regolith

62

Aye

metapelitic and metapsammitic rocks 74439

metasedimentary siliciclastic, sedimentary siliciclastic

pelite, phyllite, psammite, quartzite, slate

Metagranite, granite, gneiss, migmatite, dolerite, gabbro, basalt, silicic volcanic rocks, chert, amphibolite, banded iron formation, quartz-rich metasedimentary rocks, calcsilicate rock, ultramafic rocks, schist; weathered Archean rock Metamorphosed sandstone, shale, siltstone, conglomerate, volcaniclastics; fuchsite-quartz rock; schist and metapsammite; quartzite, quartz-aluminosilicate rock, phyllite, slate, chert Undivided poorly consolidated sediments: colluvium, weathered rocks, alluvium, sand, silt, clay, lacustrine and swamp deposits; silcrete, ferricrete, calcrete; ?shallowmarine sediments

sed. noncarbonate

granite, felsic gneiss, migmatite, weathered material - unknown origin, dolerite

other

greenstone

63

Cz

undivided sediments 74488

sedimentary, regolith

sedimentary rock, colluvial sediment, weathered material unknown origin, sand - residual, silt - unknown origin

64

Czc

sandstone 74489

sedimentary siliciclastic, regolith

sandstone, silcrete, sand residual

Fossiliferous terrestrial sandstone; sandstone and silcrete; quartz-lithic-pebbly-gritty sand

sed. noncarbonate

65

Czceu

Eundynie Group

sedimentary carbonate, sedimentary siliciclastic

limestone, sandstone

Limestone, siliciclastic rocks (locally spongolitic, bituminous, calcareous, or bioclastic), sandstone

sed. carbonate

66

Czcpl

Plumridge Formation

sedimentary siliciclastic, argillaceous detrital sediment

sandstone, siltstone

Sandstone, siltstone, minor conglomeratic sandstone

sed. noncarbonate

spongolite, sandstone, siltstone, claystone,

Spongolite, sandstone, siltstone, claystone, locally silicified

67

Czcpr

Princess Royal Member

sedimentary non-carbonate chemical or biochemical, argillaceous detrital sediment

68

Cziab

Abrakurrie Limestone

sedimentary carbonate

calcirudite, calcarenite

Porous bryozoan calcirudite and calcarenite

69

Czico

Cowan Dolomite

sedimentary carbonate

dolostone

Massive, cryptocrystalline white or grey dolomite

70

Czin

Nullarbor Limestone

sedimentary carbonate

calcarenite

71

Czk

calcrete 38497

regolith

calcrete

Foraminiferal calcarenite Pisolitic, nodular or massive calcrete; ferruginous inclusions; calcareous cementing of bedrock and transported materials; locally with intercalated chalcedony; as low mounds, in playa lakes, or as valley calcrete; locally dissected and karstified

72

Czl

ferruginous duricrust 38498

regolith

lateritic duricrust

73

Czs

sand plain 38499

regolith

sand - residual

Pisolitic, nodular or vuggy ferruginous laterite; some lateritic soils; ferricrete; magnesite; ferruginous and siliceous duricrusts and reworked products, calcrete, kaolinised rock, gossan; residual ferruginous saprolite Sand or gravel plains; quartz sand sheets commonly with ferruginous pisoliths or pebbles, minor clay; local calcrete, laterite, silcrete, silt, clay, alluvium, colluvium, aeolian sand

Appendix D: Reclassification of surficial geology/lithology types to generalized surficial geology - 51

sed. noncarbonate sed. carbonate sed. carbonate sed. carbonate

other

lateritic duricrust

sand plain

MAP SYMBOL

UNITNAME / FORMATION

LITH_GROUP

LITH_TYPE

LITH_DESC

Reclassified

74

Czz

silcrete 42026

regolith

silcrete

Silcrete, siliceous duricrust, siliceous breccia; opaline silica, jasperoidal chalcedony, and local chrysoprase caprock over ultramafic rocks.

75

Ldj

Jimberlana Norite

igneous mafic intrusive, igneous ultramafic intrusive

norite, gabbro, pyroxenite, dolerite,

Norite, bronzitite, gabbro, pyroxenite, peridotite, dolerite

other

76

Lnbd

Dalyup Gneiss

high-grade metamorphic rock

felsic gneiss

Granitic augen gneiss and granitic gneiss

other

sandstone, conglomerate, mudstone, shale, breccia sedimentary

Sandstone, conglomerate, mudstone, shale, siltstone, breccia

other

serpentinite, metapyroxenite

Ultramafic intrusive rocks including serpentinite, tremolite rock and pyroxenite

other

granite, monzogranite, diorite, pegmatite,

Granite, metagranite, Equigranular to porphyritic granite; leucocratic granite; biotite granite with potassium feldspar phenocrysts in places; foliated adamellite; mixed granitic rocks; dioritic rocks

other

other

other

77

Lswo

Woodline Formation

sedimentary siliciclastic, argillaceous detrital sediment

78

Me

metamorphosed ultramafic rocks 74438

meta-igneous ultramafic intrusive

79

Mg

granite, pegmatite 74405

igneous felsic intrusive, igneous intermediate intrusive

other

80

Mn

high grade metamorphic rocks 74341

high-grade metamorphic rock, igneous felsic intrusive

gneiss, migmatite, dolerite, augen gneiss, felsic gneiss

Garnet-biotite-quartz-feldspar augen gneiss, migmatite, quartz-feldspar granofels, metadolerite; granitic gneiss; ultramafic, mafic, and felsic granulites; banded granulite; felsic gneiss, granite, banded gneiss

81

Mnf

Fraser Complex

high-grade metamorphic rock, meta-igneous mafic

felsic granulite, mafic granulite, felsic gneiss, gabbro, amphibolite

Felsic and mafic granulites, felsic gneiss, gabbro and metagabbro, amphibolite, microgranite, pegmatite

82

Mx

granite, gneiss, migmatite 74404

igneous felsic intrusive, highgrade metamorphic rock

granite, felsic gneiss

83

My

metasedimentary and metavolcanic rocks 74525

metasedimentary siliciclastic, meta-igneous felsic

quartzite, pelite, conglomerate, felsic schist, slate

Undivided granite, gneiss and migmatite; foliated felsic rock Quartzite, quartz-mica schist (some is deformed granitoid), quartz conglomerate, quartzite with kyanite, sillimanite, muscovite, or magnetite, phyllitic schist, quartz-mica-garnet schist, slate, phyllite, feldspar porphyry, basalt

Paterson Formation

sedimentary siliciclastic, feldspar- or lithic-rich arenite to rudite

sandstone, claystone, conglomerate, tillite, siltstone

Poorly sorted sandstone, claystone, conglomerate, tillite, siltstone, diamictite; varves and erratics in places glacigene, lacustrine, to fluvioglacial.

other

alluvial sediment

Channel and flood plain alluvium; gravel, sand, silt, clay, locally calcreted

alluvium

sand - aeolian, sand - residual

Dunes, sandplain with dunes and swales; may include numerous interdune claypans; residual and aeolian sand with minor silt and clay; aeolian red quartz sand, clay and silt, in places gypsiferous; yellow hummocky sand

sand other

84 85

86

Psp Qa

Qd

alluvium 38485

dunes 38496

regolith

regolith

Appendix D: Reclassification of surficial geology/lithology types to generalized surficial geology - 52

other

other

MAP SYMBOL

UNITNAME / FORMATION

LITH_GROUP

LITH_TYPE

87

Qdlu

lunette dunes 72955

regolith

sand - aeolian, lacustrine sediment

88

Qrc

colluvium 38491

regolith

colluvial sediment

89

Qrl

loam and kankar 72999

regolith

colluvial sediment, residual material

90

Qt

lake deposits 38492

regolith

lacustrine sediment

LITH_DESC Quartz and gypsum dunes and mounds (kopi); may include minor silt, sand, gravel, and clay flats adjacent to playas; locally includes some playa sediments Colluvium, sheetwash, talus; gravel piedmonts and aprons over and around bedrock; clay-silt-sand with sheet and nodular kankar; alluvial and aeolian sand-siltgravel in depressions and broad valleys in Canning Basin; local calcrete, reworked laterite Residual (eluvial) loam, clay, silt, sand with sheet and nodular kankar Lacustrine or residual mud, clay, silt and sand, commonly gypsiferous and/or saline; playa, claypan, and swamp deposits; peat; peaty sand and clay; halitic and gypsiferous evaporites

Appendix D: Reclassification of surficial geology/lithology types to generalized surficial geology - 53

Reclassified

sand other

colluvium colluvium

lacustrine sediment

Appendix E: References for reviewing probability of success and timing to maturity of offset actions Overview Ford, H. A., G. W. Barrett, D. A. Saunders, and H. F. Recher. 2001. Why have birds in the woodlands of Southern Australia declined? Biological Conservation 97:71–88. Lindenmayer, D., A. Bennett, and R. Hobbs. 2010. Temperate woodland conservation and management. CSIRO Publishing, Victoria, Australia. Prober, S. M., and F. P. Smith. 2009. Enhancing biodiversity persistence in intensively used agricultural landscapes: A synthesis of 30 years of research in the Western Australian wheatbelt. Agriculture, Ecosystems & Environment 132:173-191. Tongway, D. J., and J. A. Ludwig. 2010. Restoring disturbed landscapes: putting principles into practice. Island Press, Washington, D.C. Yates, C. J., and R. J. Hobbs. 1997. Temperate eucalypt woodlands: a review of their status, processes threatening their persistence and techniques for restoration. Australian Journal of Botany 45:949–973. Destocking pastoral leases (and manage as a conservation lease/covenant) Brandis, A. 2005. The establishment, management and evaluation of the conservation reserve system in the rangelands of western australia. University of Notre Dame Australia, Fremantle, WA. http://researchonline.nd.edu.au/cgi/viewcontent.cgi?article=1026&context=theses. Environmental Protection Authority, 2002. Environmental protection and sustainability of the rangelands in western australia, position statement no. 5. Available at: http://www.epa.wa.gov.au/epadoclib/1516_PS502.pdf. Knight, R. L., W. C. Gilgert, and E. Marston. 2002. Ranching west of the 100th meridian: culture, ecology, and economics. Island Press, Washington, D.C. Landsberg, J., C. D. James, J. Maconochie, A. O. Nicholls, J. Stol, and R. Tynan. 2002. Scale-related effects of grazing on native plant communities in an arid rangeland region of south australia. Journal of Applied Ecology 39:427-444. Lunt, I. D., D. J. Eldridge, J. W. Morgan, and G. B. Witt. 2007. Turner Review No. 13 A framework to predict the effects of livestock grazing and grazing exclusion on conservation values in natural ecosystems in Australia. Australian Journal of Botany 55:401-415. Yates, C. J., D. A. Norton, and R. J. Hobbs. 2000. Grazing effects on plant cover, soil and microclimate in fragmented woodlands in south‐western Australia: implications for restoration. Austral Ecology 25:36-47.

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Removing dams Fensham, R. J., and R. J. Fairfax. 2008. Water-remoteness for grazing relief in Australian arid-lands. Biological Conservation 141:1447-1460. Fukuda, Y., H. I. McCallum, G. C. Grigg, and A. R. Pople. 2009. Fencing artificial waterpoints failed to influence density and distribution of red kangaroos (Macropus rufus). Wildlife Research 36:457-465. Harrington, R. 2002. The effects of artificial watering points on the distribution and abundance of avifauna in an arid and semi-arid mallee environment. PhD thesis, University of Melbourne, Melbourne. James, C. D., J. R. Landsberg, and S. R. Morton. 1999. Provision of watering points in the Australian arid zone: a review of effects on biota. Journal of Arid Environments 41:87-121. Landsberg, J, James, C., Morton, S., Hobbs, T., Stol, A. Drew and H. Tongway 1997. The effects of artificial sources of water on rangeland biodiversity. Final report to the Biodiversity Convention and Strategy Section of Environment Australia, Canberra. Landsberg, J., C. D. James, S. R. Morton, W. J. Müller, and J. Stol. 2003. Abundance and composition of plant species along grazing gradients in Australian rangelands. Journal of Applied Ecology 40:10081024. Landsberg, J., and D. Gillieson. 1996. Looking beyond the piospheres to locate biodiversity reference areas in Australia’s rangelands. Proceedings of the Fifth International Rangelands Congress 1:304305. Montague-Drake, R., and D. Croft. 2004. Do kangaroos exhibit water-focused grazing patterns in arid New South Wales? A case study in Sturt National Park. Australian Mammalogy 26:87-100. Noy-Meir, I. 1996 The spatial dimensions in plant –herbivore interactions. Pages 152-154 in N.E. West, editor. Rangelands in a sustainable biosphere. Proceedings of the Fifth International Rangeland Congress, Volume 2. Society for Range Management, Denver, CO. Pringle, H. J. R., and J. Landsberg. 2004. Predicting the distribution of livestock grazing pressure in rangelands. Australian Ecology 29:31-39. Thrash, I. 1998. Impact of water provision on herbaceous vegetation in Kruger National Park, South Africa. Journal of Arid Environments 38:437-450. Westbrooke, M. E., F. J. Christie, S. Cook, S. K. Florentine, P. Gell, and P. Graz. 2010. Biodiversity impacts of ground tank closure in southeast Australian rangelands. Proceedings of the 16th Biennial Conference of the Australian Rangeland Society. Australian Rangeland Society, Perth. Wilson, M. E. 2010. Effects of artificial watering points on rangeland bird communities. Proceedings of the 16th Biennial Conference of the Australian Rangeland Society. Australian Rangeland Society, Perth.

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Road closures or track closures Donaldson, A., and A. Bennett. 2004. Ecological effects of roads: implications for the internal fragmentation of australian parks and reserves. Parks Victoria, Melbourne. Gager P.and A. Conacher. 2001. Erosion of access tracks in Kalamunda National Park, Western Australia: causes and management implications. Australian Geographer 32:343-357. Ree, R. van der, N. Gulle, K. Holland, E. van der Grift, C. Mata, and F. Suarez. 2007. Overcoming the barrier effect of roads-how effective are mitigation strategies? UC Davis: Road Ecology Center. Spellerberg, I. 1998. Ecological effects of roads and traffic: a literature review. Global Ecology and Biogeography 7:317-333. Trombulak, S. C., and C. A. Frissell. 2000. Review of ecological effects of roads on terrestrial and aquatic communities. Conservation Biology 14:18-30. Control of invasive species (e.g., goats, donkeys, camels) Agnew, D. C., G. B. J. Patrick, and S. Arnold. 2010. A framework for the management of feral goals in semi-arid South Australia. Page Biodiversity impacts of ground tank closure in southeast Australian rangelands. Australian Rangeland Society, Perth. Burbidge, A. A., and N. L. McKenzie. 1989. Patterns in the modern decline of Western Australia’s vertebrate fauna: causes and conservation implications. Biological Conservation 50:143-198. Edwards, G. P., K. Saalfeld, and B. Clifford. 2004. Population trend of feral camels in the Northern Territory, Australia. Wildlife Research 31:509-517. Environmental Protection Authority. 2002. Environmental Protection and Sustainability of the Rangelands in Western Australia. Retrieved from http://www.epa.wa.gov.au/epadoclib/1516_PS502.pdf. James, C. D., J. R. Landsberg, and S. R. Morton. 1999. Provision of watering points in the Australian arid zone: a review of effects on biota. Journal of Arid Environments 41:87-121. McLeod, S. R., and A. R. Pople. 2008. Modelling management options for management of feral camels in central Australia. DKRC Research Report 48. Desert Knowledge CRC, Alice Springs. Retrieved from http://www.desertknowledgecrc.com.au/resource/DKCRC-Report-48-Modelling-options-formanagement-of-feral-camels-in-central-Australia.pdf. Pimentel, D. 2002. Biological invasions: economic and environmental costs of alien plant, animal, and microbe species. CRC Press, Boca Raton, Florida. Saunders, G., J. Kinnear, B. Coman, and M. Braysher. 1995. Managing Vertebrate Pests: Foxes. Australian Government Publishing Service, Canberra. Retrieved from http://adl.brs.gov.au/data/warehouse/pe_brs90000003159/MVP_foxes1995_ap14.pdf. Woolnough, A. P., G. S. Gray, T. J. Lowe, W. E. Kirckpatrick, K. Rose, and G. R. Martin. 2011. Distribution and abundance of pest animals in Western Australia: a survey of institutional knowledge.

Appendix E: References for reviewing probability of success and timing to maturity of offset actions- 56

Vertebrate Pest Research Station, Department of Agriculture, Western Australia, Forrestfield, WA. Retrieved from http://www.agric.wa.gov.au/PC_93073.html. Control of invasive species (plants) Pimentel, D. 2002. Biological invasions: economic and environmental costs of alien plant, animal, and microbe species. CRC Press, Boca Raton, Florida. Reid, A. M., L. Morin, P. O. Downey, K. French, and J. G. Virtue. 2009. Does invasive plant management aid the restoration of natural ecosystems? Biological Conservation 142:2342-2349. Sinden, J., R. Jones, S. Hester, D. Odom, C. Kalisch, R. James, and O. Cacho. 2004. The Economic impact of Weeds in Australia. Cooperative Research Centre for Australian Weed Management, Adelaide, Australia. Non-native predator control (e.g., cats) Fleming, P. J. S., L. R. Allen, S. J. Lapidge, A. Robley, G. R. Saunders, and P. C. Thomson. 2006. A strategic approach to mitigating the impacts of wild canids: proposed activities of the Invasive Animals Cooperative Research Centre. Australian Journal of Experimental Agriculture 46:753-762. Fleming, P., L. Corbett, R. Harden, and P. Thomson. (n.d.). Managing the impacts of dingoes and other wild dogs. Bureau of Rural Sciences, Canberra. Retrieved from http://www.daff.gov.au/__data/assets/pdf_file/0013/1504111/dingoes-and-dogs.pdf. Glen, A. S., and C. R. Dickman. 2005. Complex interactions among mammalian carnivores in australia, and their implications for wildlife management. Biological Reviews 80:387-401. May, S. A., and T. W. Norton. 1996. Influence of fragmentation and disturbance on the potential impact of feral predators on native fauna in Australian forest ecosystems. Wildlife Research 23:387-400. Risbey, D. A., M. C. Calver, J. Short, J. S. Bradley, and I. W. Wright. 2000. The impact of cats and foxes on the small vertebrate fauna of Heirisson Prong, Western Australia. II. A field experiment. Wildlife Research 27:223-235. Wheeler, R., and D. Priddel. 2009. The impact of introduced predators on two threatened prey species: A case study from western New South Wales. Ecological Management & Restoration 10:S117-S123. Protect old-growth woodland Cunningham, R. B., D. B. Lindenmayer, M. Crane, D. Michael, and C. MacGregor. 2007. Reptile and arboreal marsupial response to replanted vegetation in agricultural landscapes. Ecological Applications 17:609-619. Lindenmayer, D., A. F. Bennett, and R. Hobbs. 2010. An overview of the ecology, management and conservation of Australia’s temperate woodlands. Ecological Management & Restoration 11:201-209. Williams, M. R., I. Abbott, G. L. Liddelow, C. Vellios, I. B. Wheeler, and A. E. Mellican. 2001. Recovery of bird populations after clearfelling of tall open eucalypt forest in Western Australia. Journal of Applied Ecology 38:910-920.

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Fire management Barrett, S., S. Comer, N. McQuoid, M. Porter, C. Tiller, and D. Utber. 2009. Identification and conservation of fire sensitive ecosystems and species of the South Coast Natural Resource Management Region. Department of Conservation and Land Management, South Coast Region, Western Australia. Clarke, M. F., S.C. Avitablue, L. Brown, K.E. Callister, A. Haslem, G. J. Holland, L.T. Kelley, S.A. Kenny, D. G. Nimmo, L.M. Spence-Bailey, R.S. Taylor, S.J. Watson, and A.F. Bennett. 2010. Ageing mallee eucalypt vegetation after fire: insights for successional trajectories in semi-arid mallee ecosystems. Australian Journal of Botany 58:363-372. Craig, M. D., R. J. Hobbs, A. H. Grigg, M. J. Garkaklis, C. D. Grant, P. A. Fleming, and G. E. S. J. Hardy. 2010. Do thinning and burning sites revegetated after bauxite mining improve habitat for terrestrial vertebrates? Restoration Ecology 18:300-310. Cruz, M. G., S. Matthews, J. Gould, P. Ellis, M. Henderson, I. Knight, and J. Watters. 2006. Fire dynamics in mallee-heath: fuel, weather and fire behaviour prediction in South Australian Semi-arid shrublands. Bushfire Cooperative Research Centre, CSIRO Sustainable Ecosystems, Canberra, ACT, Australia. Daniel, G. 2010. Bushfire threat analysis of the great western woodlands. Department of Environment and Conservation, Western Australia. Friend, G. R. 1993. Impact of fire on small vertebrates in mallee woodlands and heathlands of temperate Australia: A review. Biological Conservation 65:99-114. Goldingay, R. L. 2009. Characteristics of tree hollows used by Australian birds and bats. Wildlife Research. 36:394-409. Goldingay, R. L., and J. R. Stevens. 2009. Use of artificial tree hollows by Australian birds and bats. Wildlife Research 36:81-97. Gosper, C. R., S. M. Prober, and C. J. Yates. 2010. Chaining and burning modifies vegetation structure, fuel, and post-disturbance sprouting capacity. Rangeland Ecology & Management 63:588-592. Gosper, C. R., S. M. Prober, and C. J. Yates. 2010. Repeated disturbance through chaining and burning differentially affects recruitment among plant functional types in fire-prone heathlands. International Journal of Wildland Fire 19:52-62. Gosper, C. R., C. J. Yates, S. M. Prober, and B. C. Parsons. 2011. Contrasting changes in vegetation structure and diversity with time since fire in two Australian Mediterranean‐climate plant communities. Austral Ecology 37:164-174. Gosper, C. R., C. J. Yates, S. M. Prober, and M. R. Williams. 2010. Fire does not facilitate invasion by alien annual grasses in an infertile Australian agricultural landscape. Biological Invasions 13:533544. Haslem, A., L. T. Kelly, D. G. Nimmo, S. J. Watson, S. A. Kenny, R. S. Taylor, S. C. Avitabile, K. E. Callister, L. M. SpenceBailey, M.F. Clarke, and A.F. Bennett. 2011. Habitat or fuel? Implications of

Appendix E: References for reviewing probability of success and timing to maturity of offset actions- 58

long‐term, post‐fire dynamics for the development of key resources for fauna and fire. Journal of Applied Ecology 48:247-256. Herath, D. N., B. B. Lamont, N. J. Enright, and B. P. Miller. 2009. Impact of fire on plant-species persistence in post-mine restored and natural shrubland communities in southwestern Australia. Biological Conservation 142:2175-2180. Herford, I., R. Armstrong, and G. Daniel. 2011. DRAFT Fire management plan for the conservation of biodiversity and cultural heritage values in the Great Western Woodlands. Department of Environment and Conservation, Western Australia. Kelly, L. T., D. G. Nimmo, L. M. Spence-Bailey, M. F. Clarke, and A. F. Bennett. 2010. The short-term responses of small mammals to wildfire in semiarid mallee shrubland, Australia. Wildlife Research 37:293-300. Kelly, L. T., D. G. Nimmo, L. M. Spence‐Bailey, A. Haslem, S. J. Watson, M. F. Clarke, and A. F. Bennett. 2011. Influence of fire history on small mammal distributions: insights from a 100‐year post‐ fire chronosequence. Diversity and Distributions 17:462-473. O’Donnell, A. J., M. M. Boer, W. L. McCaw, and P. F. Grierson. 2011. Vegetation and landscape connectivity control wildfire intervals in unmanaged semi‐arid shrublands and woodlands in Australia. Journal of Biogeography 38:112-124. Parsons, B. C., and C. R. Gosper. 2011. Contemporary fire regimes in a fragmented and an unfragmented landscape: implications for vegetation structure and persistence of the fire-sensitive malleefowl. Int. J. Wildland Fire 20:184-194. Ross, K. A., J. E. Taylor, M. D. Fox, and B. J. Fox. 2004. Interaction of multiple disturbances: importance of disturbance interval in the effects of fire on rehabilitating mind areas. Austral 29:508529. Smith, B. M. A., W. A. Loneragan, C. D. Grant, and J. M. Koch. 2000. Effect of fire on the topsoil seed banks of rehabilitated bauxite mine sites in the jarrah forest of Western Australia. Ecological Management & Restoration 1:50-60. Smith, M. A., C. D. Grant, W. A. Loneragan, and J. M. Koch. 2004. Fire management implications of fuel loads and vegetation structure in jarrah forest restoration on bauxite mines in Western Australia. Forest Ecology and Management 187:247-266. Taylor, R. S., S. J. Watson, D. G. Nimmo, L. T. Kelly, A. F. Bennett, and M. F. Clarke. 2011. Landscape‐ scale effects of fire on bird assemblages: does pyrodiversity beget biodiversity? Diversity and Distributions 18:519-529. Watson, S. J., R. S. Taylor, D. G. Nimmo, L. T. Kelly, A. Haslem, M. F. Clarke, and A. F. Bennett. In press. Effects of time-since-fire on birds: how informative are generalized fire-response curves for conservation management? Ecological Applications.

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Restoration activities (specifically, reseeding, nest boxes, maintaining woody debris, thinning trees to promote growth) Batty, L. C., and K. B. Hallberg. 2010. Ecology of industrial pollution. Cambridge University Press, Cambridge, UK. Bell, L. C. 2001. Establishment of native ecosystems after mining — Australian experience across diverse biogeographic zones. Ecological Engineering 17:179-186. Brady, C. J., and R. A. Noske. 2010. Succession in bird and plant communities over a 24‐year chronosequence of mine rehabilitation in the Australian monsoon tropics. Restoration Ecology 18:855-864. Craig, M. D., A. M. Benkovic, A. H. Grigg, G. E. S. J. Hardy, P. A. Fleming, and R. J. Hobbs. 2011. How many mature microhabitats does a slow-recolonising reptile require? Implications for restoration of bauxite mine sites in south-western Australia. Australian Journal of Zoology 59:9-17. Gardner, J. H., and D. T. Bell. 2007. Bauxite mining restoration by Alcoa World Alumina Australia in Western Australia: social, political, historical, and environmental contexts. Restoration Ecology 15:S3-S10. George, S. J., R. N. Kelly, P. F. Greenwood, and M. Tibbett. 2010. Soil carbon and litter development along a reconstructed biodiverse forest chronosequence of South-Western Australia. Biogeochemistry 101:197-209. Goldingay, R.L., and Stevens, J.R. 2009. Use of artificial tree hollows by Australian birds and bats. Wildlife Research 36:81–97 Grant, C., and J. Koch. 2007. Decommissioning Western Australia’s first bauxite mine: co‐evolving vegetation restoration techniques and targets. Ecological Management & Restoration 8:92-105. Grant, C. D., S. C. Ward, and S. C. Morley. 2007. Return of ecosystem function to restored bauxite mines in Western Australia. Restoration Ecology 15:S94-S103. Jonson, J. 2010. Ecological restoration of cleared agricultural land in Gondwana Link: lifting the bar at ‘Peniup’. Ecological Management & Restoration 11: 16–26. Koch, J. M. 2007. Alcoa’s mining and restoration process in South Western Australia. Restoration Ecology 15:S11-S16. Koch, J. M. 2007. Restoring a jarrah forest understorey vegetation after bauxite mining in Western Australia. Restoration Ecology 15:S26-S39. Koch, J. M., and R. J. Hobbs. 2007. Synthesis: Is Alcoa successfully restoring a jarrah forest ecosystem after bauxite mining in western australia? Restoration Ecology 15:S137-S144. Koch, J. M., and G. P. Samsa. 2007. Restoring jarrah forest trees after bauxite mining in Western Australia. Restoration Ecology 15:S17-S25.

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Lin, D. S., P. F. Greenwood, S. George, P. J. Somerfield, and M. Tibbett. 2011. The development of soil organic matter in restored biodiverse jarrah forests of South-Western Australia as determined by ASE and GCMS. Environmental Science and Pollution Research 18:1070-1078. Munro, N. T., J. Fischer, G. Barrett, J. Wood, A. Leavesley, and D. B. Lindenmayer. 2011. Bird’s response to revegetation of different structure and floristics—are “restoration plantings” restoring bird communities? Restoration Ecology 19:223-235. Munro, N. T., D. B. Lindenmayer, and J. Fischer. 2007. Faunal response to revegetation in agricultural areas of Australia: A review. Ecological Management & Restoration 8:199-207. Nichols, O. G., and C. D. Grant. 2007. Vertebrate fauna recolonization of restored bauxite mines—key findings from almost 30 years of monitoring and research. Restoration Ecology 15:S116-S126. Nichols, O. G., and F. M. Nichols. 2003. Long‐term trends in faunal recolonization after bauxite mining in the jarrah forest of southwestern Australia. Restoration Ecology 11:261-272. Nichols, O. G., and D. Watkins. 1984. Bird utilisation of rehabilitated bauxite minesites in Western Australia. Biological Conservation 30:109-131. Norman, M. A., J. M. Koch, C. D. Grant, T. K. Morald, and S. C. Ward. 2006. Vegetation succession TN Orabi, G., M. L. Moir, and J. D. Majer. 2010. Assessing the success of mine restoration using Hemiptera as indicators. Australian Journal of Zoology 58:243-249. Rokich, D. P., K. A. Meney, K. W. Dixon, and K. Sivasithamparam. 2001. The impact of soil disturbance on root development in woodland communities in Western Australia. Aust. J. Bot. 49:169-183. Yates, C. J., D. A. Norton, and R. J. Hobbs. 2000. Grazing effects on plant cover, soil and microclimate in fragmented woodlands in south‐western Australia: implications for restoration. Austral Ecology 25:36-47. Recapping drill holes (old mine shafts) Osborne, J. M., and D. R. Brearley. 1998. Exploration disturbances in semi arid Western Australia: A cost effective and proactive approach to rehabilitation. Page 7th International Symposium on Mine Planning and Equipment Selection. Pedler, R. D. 2010. The impacts of abandoned mining shafts: Fauna entrapment in opal prospecting shafts at Coober Pedy, South Australia. Ecological Management & Restoration 11:36-42.

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