Spatial Analysis Data for 'Lines in the Sand: Quantifying the Cumulative Development Footprint in the World's Largest Remaining Temperate Woodland' 

These datasets provide the data underlying the publication on "Lines in the sand: quantifying the cumulative development footprint in the world’s largest remaining temperate woodland" https://link.springer.com/article/10.1007/s10980-017-0558-z. . The datasets are: (A) data in csv format: [1] development footprint by sample area: Information on the 24, ~490 km^2 sample areas assessed in the study, including the different infrastructure types (roads, railways, mapped tracks, un-mapped tracks which have been manually digitized in the study using aerial imagery and hub infrastructure such as mine pits and waste rock dumps, also manually digitized in the study). Also contains some key co-variables assessed as potential explanatory variables for development footprint. The region-wide modelling of development footprint found strong positive effects of mining project density and pastoralism, as well as a highly significant negative interaction between the two. At low mining project densities, development footprints are more extensive in pastoral areas, but at high mining project densities, pastoral areas are relatively less developed than non-pastoral areas, on average. [2] Great Western Woodlands (GWW) 20 km grid: The datasets provides data for the 20x20 km grid placed over the whole GWW and used for the regional estimation of development footprint, linear infrastructure density, and linear infrastructure type based on the region-wide analysis. Data is for each cell in the grid and provides the total length of roads in that grid cell, MINEDEX mining projects, pastoral status, etc. This dateset was used to project the data from the 24 study areas across the whole of the Great Western Woodlands and calculate region-wide estimates of development footprint and linear infrastructure lengths. [3] disturbance by patch: This dataset provides the data for each patch for the analysis of patch-level drivers of development footprint, which was performed to gain further insights into the effects of other landscape variables that what could be gleaned from the region-wide analysis. For this analysis, we divided sample areas into polygonal patch types, each with a unique combination of the following categorical co-variables: pastoral tenure, greenstone lithology, conservation tenure, ironstone formation, schedule-1 area clearing restrictions, environmentally sensitive area designation, vegetation formation, and sample area. For each patch type (n=261), we calculated the following attributes: a) number of mining projects, b) number of dead mineral tenements, c) sum of duration of all live and dead tenements, d) type of tenements (exploration/prospecting tenement, mining and related activities tenement, none), e) primary target commodity (gold, nickel, iron-ore, other), f) distance to wheatbelt, and g) distance to the nearest town. [4] mapped versus digitized tracks: This dataset provides mapped and un-mapped track widths, measured using high-resolution aerial imagery at at least 20 randomly-generated locations within each of 24 sample areas. Pastoral tenure and mining intensity for each sample area are included for analysis purposes. [5] edge effect scenarios: Hypothetical edge effect zones were created, based on effect zones gleaned from the literature and arranged under three scenarios, to reflect potential risks of offsite impacts in areas adjacent to development footprints observed (see appendix 3 of article). The calculated proportion of the entire GWW within edge effect zones varied from ~3% under the conservative scenario to ~35% under the maximal scenario. Within the range of development footprints observed in this study, the proportion of a landscape that lies within edge effect zones increases hyperbolically with the number of mining projects, and approaches 100% in the maximal scenario, 60% in the moderate scenario, and ~20% under the conservative scenario. shapefiles: [6] Great Western Woodlands boundary, [7] sample areas (layer file shows sample areas by category). 

We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging. Suzanne Prober, Richard Hobbs, and Hugh Possingham were co-authors to the paper which these datasets underly, and provided important guidance to the analysis. Gondwana Link and the Wilderness Society (and the Great Western Woodlands Collaboration) provided the Great Western Woodlands boundary and also provided immense support and guidance on the analysis and desired outcomes. The Department of Biodiversity, Conservation and Attractions (previously DPaW and DEC), Landgate, Geoscience Australia, Department of Mines, Industry Regulation and Safety (previously Department of Mines and Petroleum), all provided data which was used in this analysis. We gratefully acknowledge support from the Gledden Postgraduate Research Scholarship, the Australian Research Council Centre of Excellence for Environmental Decisions, The Wilderness Society, Gondwana Link, the Natural Environmental Research Program Environmental Decisions Hub, and the Great Western Woodlands Supersite, part of Australia's Terrestrial Ecosystem Research Network. We thank Ophir Levin, Julia Waite, Brad Desmond, and Rachel Omodei for assistance in digitising the unmapped development footprint. We also thank Fiona Westcott for her assistance in ground-truthing, Cliffs Natural Resources for in-kind 500 support in the field, and Amanda Keesing (Gondwana Link), Judith Harvey (DPaW) and Katherine Zdunic (DPaW) for their assistance in supplying spatial information. Ashley Sparrow, Richard Forman, Andrew Bennett, John Bissonette, and two anonymous reviewers provided valuable reviews that improved this manuscript. All fieldwork was carried out under Department of Parks and Wildlife Regulation 4 lawful authority CE003548. 

This dataset relates to Chapter 3 of the author's PhD thesis: Conservation of large, relatively intact landscapes in the face of widespread development such as resource extraction is a challenge of global conservation significance. Growing human populations and economies and increasing scarcity of natural resources are pushing the frontiers of rapidly proliferating development into areas that have remained relatively intact until recent times; diminishing or degrading those landscapes.In this thesis I present research that aims to provide approaches, information and insights that can be used to ameliorate these impacts, using the largest and most intact remaining temperate woodland on earth as a case study. The Great Western Woodlands (GWW) is a region of international ecological significance and also a highly productive mining province, with a rich history of gold, nickel, and iron ore mining evidenced by numerous exploration tracks, drilling remains, mine pits, and waste dumps. I investigated the following overarching questions in the context of mining in the GWW: 1. What is the scope of ecological impacts that require mitigation to successfully conserve intact landscapes? 2. How significant is linear infrastructure (e.g. roads, tracks, and railways) as a component of disturbance? 3. How does linear infrastructure affect key ecosystem processes, such as predation and water movement? I developed a conceptual framework (Chapter 2), used spatial analysis techniques (Chapter 3), and conducted extensive field work (Chapters 4 and 5) to address these questions. Chapter 2 proposes a framework for conceptualising enigmatic ecological impacts: impacts that are often overlooked or inadequately addressed in impact evaluations. Enigmatic impacts include those that are small but act cumulatively (cumulative impacts); those outside of the area directly considered (offsite impacts); those not detectable with the methods or spatiotemporal scales used (cryptic impacts); those facilitated, but not directly caused, by the development (secondary impacts); and synergistic impact interactions. Potential solutions to these enigmatic impacts include strategic broad-scale planning, improving professional practice and decision-making processes, and environmental insurance schemes. This framework sets the context for the following chapters which explore various enigmatic effects of development in the GWW. In Chapter 3 I characterised and quantified the cumulative development footprint in the GWW, with extensive digitisation from aerial imagery across a random stratified sample of the region. In contrast to common perceptions of mining impacts as primarily consisting of mine pits and associated hub infrastructure, I found that approximately 67% of the disturbance footprint consists of linear infrastructure. I estimated that 150,000 km of tracks, roads, and railways exist in the region and that beyond the ~690 km2 total disturbance footprint, a further 4,00055,000 km2 (335% of the GWW) lies within offsite risk zones. Moreover, the majority of linear infrastructure is unmapped, indicating that available data sources are not comprehensive and can lead to false conclusions about ecological impacts. To explore the effect of linear infrastructure on predator activity, I used a combination of motion-sensor cameras and spoor inspections to compare dingo, fox and cat activity on vehicle tracks and for three kilometres into the surrounding vegetation matrix (Chapter 4). I found strong effects of roads on activity for all species studied: on-road activity was generally far higher than off-road activity, and roads appeared to affect predator activity even up to 2.5 km away. I also explored the effects of extensive track, road, and rail networks on water movement (Chapter 5). I assessed over 1100 km of linear infrastructure and off-road transects and 300 stream crossings, and found strong associations between linear infrastructure and evidence of altered surface and near-surface hydrology. Ninety-eight percent of stream crossings showed evidence of flow impedance, flow concentration, flow diversion and/or channel initiation. A number of engineering and environmental factors influence the frequency and severity of these impacts, which I estimate number at least 335,000 across the region. This research indicates that pervasive ecological impacts exist but are commonly overlooked in conventional impact evaluations, and undermine the potential for successful impact mitigation. Linear infrastructure can be the elephant in the room with regard to such impacts, affecting both top-down (predation) and bottom-up (water availability) ecosystem regulation across substantial parts of the landscape. Nevertheless, there is substantial scope for mitigating these impacts and conserving large, relatively intact landscapes such as the Great Western Woodlands in perpetuity. 

Data not provided.