The progressive rehabilitation of open-cut coal mines and the demonstration of a sustainable post-mining land use is required prior to mine closure in many parts of the world. There is a general belief that the risk of rehabilitation failure following mine closure due to disturbance events such as fire is minimal, based largely on the assumed resilience of rehabilitated pastures and the assumption that rehabilitated pastures will respond analogous to unmined pastures following fire. However, there is little scientific evidence to support this notion, and additional knowledge gaps on the resilience of rehabilitation age classes and appropriate methods for land managers to measure and demonstrate rehabilitation resilience. We used Sentinel-2 and Landsat-8 time-series and assessed the impact and vegetation response to eight fire events in rehabilitation and five fires in unmined analogues in central and southeast Queensland, Australia. Using the Soil Adjusted Vegetation Index (SAVI), we aimed to compare rehabilitated and unmined areas using three resilience metrics: i) percent impact, ii) recovery time and iii) recovery rate. Compared with unmined pastures, post-mine rehabilitation recorded higher mean impact (52-65 % vs 67-79 % respectively), longer recovery times (38-117 vs 144-245 days respectively) and a slower rate of recovery (2.5-5.7 % vs 0.9-1.7 % per day respectively). Younger age-classes (<10 y/o and 10-15 y/o) recorded reduced resilience compared to mature rehabilitation (>= 16 y/o). We compared three different baseline indices and showed that the choice of baseline index yielded significantly different results for the same fires, indicating the importance of standardised approaches to resilience monitoring.

Context Pasture dieback has emerged as a significant threat to the health and productivity of sown pastures in eastern Queensland and northern New South Wales, Australia. Aims We aimed to address knowledge gaps on spatial spread patterns, recovery trajectories and floristic changes using remote sensing and ground surveys. Methods We used a time series of high-resolution (12–25 cm) aerial imagery to quantify and compare pasture dieback spread over 7 years in three land-use areas: ungrazed pasture, grazed pasture and rehabilitation following mining. The green leaf index was applied using supervised random forest algorithms to classify areas affected between 2015 and 2021. Flora surveys were conducted to compare impacted and unimpacted areas for the three land uses and validate classifications. Key results The first emergence of pasture dieback was in ungrazed pasture, and these areas recorded the highest rate of dieback spread at 1.88 ha month−1, compared with 0.54 and 0.19 ha month−1 in rehabilitated and grazed pastures respectively. Field validation showed that dieback-impacted pastures shifted from buffel grass (Cenchrus ciliaris L.), to forb-dominated communities with significantly different species mix, biomass and cover conditions. An analysis of local climate data showed that winter night-time temperatures and rainfall were notably higher than long-term means in the year preceding the first detection of pasture dieback. Conclusions High resolution aerial imagery and ground surveys can be used to monitor pasture health by employing vegetation indices and random forest classifiers. Implications Ungrazed pastures and roadside areas should be managed to protect the region from further outbreaks.

Sustainable long-term use of land rehabilitated following mining is required to be resilient to fire and other disturbances. We analysed the vegetation responses to three fires in grassland pasture and open woodland on rehabilitated open-cut coal mine sites in Queensland, Australia. Two fires in central Queensland were controlled burns to manage fuel loads and test the vegetation and landform response, while the third fire, in southeastern Queensland, was an unintended wildfire. We monitored several ecological variables at the study sites for up to five years following the fires and found that vegetation cover, biomass and species richness recovered to pre-fire or unburnt control values within two years. However, one study site experienced lower than average rainfall during the three to five-year post-fire period, resulting in a significant reduction in vegetation cover of between 14 and 31 %, and biomass between 45 and 57 % compared to pre-fire values. Tree and shrub densities changed significantly at two of the sites, reflected in a 635 % increase in stem density of Acacia stenophylla (A.Cunn. ex Benth.) and 82 % mortality of Atriplex nummularia Lindl. subsp. nummularia individuals <2 m in height and 100 % mortality in the 2-5 m height class. The results suggest that rehabilitated pasture systems in central and southern Queensland are resilient to fire in the short-term but are vulnerable to long-term shifts in climate, particularly if a fire precedes a long period of drought. Further resilience work is needed to i) compare rehabilitation recovery with unmined vegetation communities to determine residual risk of future fire impacts, ii) account for seasonality in resilience assessments and iii) understand recovery traits of seed mix combinations sourced from disparate regions.

The commencement of the United Nations Decade on Ecosystem Restoration has highlighted the urgent need to improve restoration science and fast‐track ecological outcomes. The application of remote sensing for monitoring purposes has increased over the past two decades providing a variety of image datasets and derived products suitable to map and measure ecosystem properties (e.g. vegetation species, community composition, and structural dimensions such as height and cover). However, the operational use of remote sensing data and derived products for ecosystem restoration monitoring in research, industry, and government has been relatively limited and underutilized. In this paper, we use the Society for Ecological Restoration (SER) ecological recovery wheel (ERW) to assess the current capacity of drone‐airborne‐satellite remote sensing datasets to measure each of the SER's recommended attributes and sub‐attributes for terrestrial restoration projects. Based on our combined expertise in the areas of ecological monitoring and remote sensing, a total of 11 out of 18 sub‐attributes received the highest feasibility score and show strong potential for remote sensing assessments; while sub‐attributes such as gene flows, all trophic levels and chemical and physical substrates have a reduced capacity for monitoring. We argue that in the coming decade, ecologists can combine remote sensing with the ERW to monitor restoration recovery and reference ecosystems for improved restoration outcomes at the local, regional, and landscape scales. The ERW approach can be adapted as a monitoring framework for projects to utilize the benefits of remote sensing and inform management through scalable, operational, and meaningful outcomes.

Summary Landscape rehabilitation following mining is required to be resilient to disturbance impacts such as fire, drought and disease. As mining companies undergo the process of rehabilitation certification and mine closure, there are notable knowledge gaps on the ecological risks associated with mature rehabilitated landscapes, based largely on the assumption that rehabilitation is analogous to reference communities. However, the response to fire disturbance across a range of landscapes remains largely untested and in particular there is limited understanding of recovery traits of plant species that occur naturally or are commonly seeded into rehabilitation. In August 2018, a controlled fire was applied to 37 hectares of 12‐year‐old coal‐mine rehabilitation in central Queensland, Australia. We used a combination of (i) ground plot surveys and (ii) drone imagery to compare the vegetation response of burnt woody species to unburnt controls prior to, and for, two years following the fire. The survival of the most dominant shrub species found on the rehabilitation site was significantly impacted by the fire. Old Man Saltbush ( Atriplex nummularia Lindl. subsp. nummularia ) recorded significant post‐fire mortality, with ground surveys recording an average reduction of 89% of stems per hectare across the burnt site, while unburnt controls remained unchanged. The plot data analysis was supported with high spatial and temporal resolution drone imagery, classified using a Random Forest machine‐learning approach. Change analysis of these maps showed a significant decline of 82% in Old Man Saltbush plant density and 92% reduction in foliage cover following the fire. In addition, the mean canopy area of individual Old Man Saltbush shrubs reduced significantly from a pre‐fire mean of 11.3 to 4.8 m 2 two years following the fire. A spatial proximity analysis showed that those individuals that survived the fire were located significantly closer to unburnt areas and bare spoil, indicating that discontinuous ground fuel loads can greatly improve the survivability of individuals. This study provides new evidence on the contested fire sensitivity of Old Man Salt bush and demonstrates the risk that future climate‐driven extreme events may have on the resilience of novel ecosystems.

The mining industry has been operating across the globe for millennia, but it is only in the last 50 years that remote sensing technology has enabled the visualization, mapping and assessment of mining impacts and landscape recovery. Our review of published literature (1970–2019) found that the number of ecologically focused remote sensing studies conducted on mine site rehabilitation increased gradually, with the greatest proportion of studies published in the 2010–2019 period. Early studies were driven exclusively by Landsat sensors at the regional and landscape scales while in the last decade, multiple earth observation and drone-based sensors across a diverse range of study locations contributed to our increased understanding of vegetation development post-mining. The Normalized Differenced Vegetation Index (NDVI) was the most common index, and was used in 45% of papers; while research that employed image classification techniques typically used supervised (48%) and manual interpretation methods (37%). Of the 37 publications that conducted error assessments, the average overall mapping accuracy was 84%. In the last decade, new classification methods such as Geographic Object-Based Image Analysis (GEOBIA) have emerged (10% of studies within the last ten years), along with new platforms and sensors such as drones (15% of studies within the last ten years) and high spatial and/or temporal resolution earth observation satellites. We used the monitoring standards recommended by the International Society for Ecological Restoration (SER) to determine the ecological attributes measured by each study. Most studies (63%) focused on land cover mapping (spatial mosaic); while comparatively fewer studies addressed complex topics such as ecosystem function and resilience, species composition, and absence of threats, which are commonly the focus of field-based rehabilitation monitoring. We propose a new research agenda based on identified knowledge gaps and the ecological monitoring tool recommended by SER, to ensure that future remote sensing approaches are conducted with a greater focus on ecological perspectives, i.e., in terms of final targets and end land-use goals. In particular, given the key rehabilitation requirement of self-sustainability, the demonstration of ecosystem resilience to disturbance and climate change should be a key area for future research.

Ranger uranium mine, surrounded by Kakadu National Park in northern Australia, is about to undertake broad-scale restoration of the first of its two pits and cease all mining and processing activities. Over the mine's forty-year life information from two detailed vegetation maps and five significant reference site surveys has been used to assist with closure. All relevant and available data were reviewed and, as a result, biophysical, remote sensing and vegetation survey data, across an area known as the Georgetown analogue, were subsequently analysed in greater detail. Vegetation communities were assessed using cluster analysis, spatial analysis and regional scale fire mapping. Regional floristic patterns were reflected in vegetation survey data, but the frequency of fires in the assessed Georgetown analogue site was significantly lower to the landscape adjacent to most of the mine site. Indeed, reference ecosystems that capture the variability of fire regimes in the area surrounding the mine should be utilised in the future to provide further engineering and restoration guidance for the new landform, determine appropriate understory species and inform pathways for restoration success. Of the 44 over-storey species assessed in this study there is limited information on the propagation techniques for eighteen species, whilst the establishment of more than 40% of the species on unnatural, mine-created substrates is unknown. Therefore, a more complete list of plant species, knowledge of their propagation and establishment requirements, and appropriate spatial patterns are still needed to ensure that the restoration of Ranger Uranium mine will be successful.

The application of controlled fire on post-mine rehabilitation is currently underutilised as an ecological tool throughout fire prone landscapes such as eastern Australia. Despite widely accepted benefits of fuel management and ecological outcomes, mined land managers are generally reluctant to incorporate fire regimes on rehabilitated lands. We applied an experimental fire to 117 ha of 19- to 21-year-old coal mine rehabilitation in subtropical, semi-arid Central Queensland, Australia, and assessed the vegetation changes in five successive assessments for the two years following the burn. Vegetation metrics all showed trajectories towards pre-fire levels, or recovered to surpass pre-fire levels. Within two years of the burn, native species richness was significantly higher than pre-fire levels for both grassland and open woodland areas and vegetation cover had returned to pre-fire levels. Woody plant density ( < 2 m) increased from an average of 425-3,255 stems ha(-1) in open woodland areas reaching values higher than those recorded at unburnt historical transects (n = 145); while stems greater than 2 m in height declined from 585 to 220 ha(-1) due to the death of mature Acacia spp. The vegetative response following two wet seasons demonstrates short-term recovery following a range of fire impacts and demonstrates the potential to enhance the quality of the rehabilitation and increase the possibility of early relinquishment by reducing ecological, financial and reputational risks.

As open-cut coal mines progress towards closure, mining companies have an obligation to provide certainty to stakeholders that their rehabilitated landscapes have the capacity to withstand future disturbance impacts such as fire and drought. This paper describes the assessment of fire severity and recovery using WorldView-3 spectral indices following an experimental fire in a 19- to 21-year old coal mine rehabilitation in semi-arid Central Queensland, Australia. In a highly heterogeneous reconstructed environment, the differenced Normalized Difference Vegetation Index (dNDVI) outperformed the differenced Normalized Burn Ratio (dNBR) with an overall map accuracy of 65% and 58%, respectively. The combination of red and near infra-red multispectral bands proved more effective at classifying severity compared with the shortwave infra-red, particularly when pre-fire imagery was dominated by highly cured grasses (>70%) and post-fire imagery contained a high coverage of residual ash. Recovery trends using spectral indices demonstrate the trajectory towards vegetation recovery, with 62% of the burnt site demonstrating high regrowth in the first two years following fire. This is supported by in situ recovery trends of understory biomass suggesting that under the study conditions, the rehabilitated site has the capacity to withstand impacts from a wildfire and recover to pre-fire levels.

Rehabilitated lands created by open-cut coal mines are generally protected by land managers from fire and grazing disturbances. This practice is employed to reduce negative impacts, such as erosion, on the developing ecosystems. However, fire exclusion over long periods inadvertently contributes to increased fire risk on rehabilitated landforms, particularly when high biomass, mono-dominant grasses form a major component of these new ecosystems. In May 2015, an experimental fire burnt 117 ha of rehabilitation at a coal mine site in the Bowen Basin, Australia. Standing grass fuel loads, dominated by buffel grass (Cenchrus ciliaris L.), were up to 9.3 t/ha in grassland areas and 5.3 t/ha in areas of open woodland. Average litter fuel loads were 2.4 and 3.6 t/ha for grassland and open woodland, respectively. Calculated fire intensity was higher in grassland (4612 +/- 502 kW m(-1)) than open woodland areas (1977 +/- 804 kW m(-1)) indicating that rehabilitated landforms dominated by buffel grass may represent a higher fire risk to mine sites and regional areas in the Bowen Basin when compared to the original vegetation. Fire behaviour reflected the varying underlying terrain, fuel loads and surface soil or overburden conditions. Further research is recommended to investigate fire behaviour in buffel grasslands across a range of fuel load and curing conditions, with the aim to develop an invasive grass fire spread model that can be used inform both landscape reconstruction prescriptions for ecological engineers and more broadly in managing the fire risk across landscapes dominated by these vegetation types. (C) 2017 Elsevier B.V. All rights reserved.

Regional planning approaches to mining infrastructure aim to reduce the conflict associated with mining operations and existing land uses, such as urban areas and biodiversity conservation, as well as the cumulative impacts that occur offsite. In this paper, we describe a method for conducting Geographical Information System (GIS) least-cost path and least-cost corridor analysis for linear mining infrastructure, such as roads. Least-cost path analysis identifies the optimal pathways between two locations as a function of the cost of traveling through different land use/cover types. In a case study from South-East Sulawesi, Indonesia, we identify potential linear networks for road infrastructure connecting mines, smelters, and ports. The method used interview data from government officials to characterise their orientation (perceived importance and positive/negative attitude) toward the social and environmental factors associated with mining infrastructure. A cost-surface was constructed by integrating spatial layers representing the social and environmental factors to identify areas that should be avoided and areas that were compatible with linear infrastructure using the least-cost path analysis. We compared infrastructure scenario outputs from local and national government officials by the degree of spatial overlap and found broad spatial agreement for infrastructure corridors. We conclude by discussing this approach in relation to the wider social-ecological and mine planning literature and how quantitative approaches can reduce the conflict associated with infrastructure planning.

Remote-sensing methods for fire severity mapping have traditionally relied on multispectral imagery captured by satellite platforms carrying passive sensors such as Landsat Thematic Mapper /Enhanced Thematic Mapper Plus or Moderate Resolution Imaging Spectroradiometer. This article describes the analysis of high spatial resolution Unmanned Aerial Vehicle UAV imagery to assess fire severity on a 117 ha experimental fire conducted on coal mine rehabilitation in an open woodland environment in semi-arid Central Queensland, Australia. Three band indices, Excess Green Index, Excess Green Index Ratio, and Modified Excess Green Index, were used to derive differenced d fire severity maps from UAV data. Fire severity data sets derived from aerial photograph interpretation were used to assess the utility of employing UAV technology to determine fire severity impacts. The dEGI was able to separate high severity, low severity, and unburnt areas with an overall classification accuracy of 58% and Kappa statistic of 0.37; outperforming the dEGIR overall accuracy 55%, Kappa 0.31 and the dMEGI overall accuracy 38%, Kappa 0.06. Classification accuracy increased for all indices when canopy shadows were masked, with dEGI improving to an overall accuracy of 68% and 0.48 Kappa. The McNemar’s test indicated that there was no significant difference between the classification accuracies for dEGI and dEGIR p p 4m2–1 km2.

AimEffective vegetation conservation requires reasonable certainty regarding the distribution, extent and classification of plant communities and ecoregions for assessing rarity. In this paper we describe a multivariate clustering approach based on environmental data for objectively defining temperate treeless palustrine wetland communities.LocationNew South Wales (NSW), Australia.MethodsIn NSW no comprehensive state-wide map of wetland vegetation exists, with more than 200 vegetation maps produced by local and state governments at a range of spatial resolutions and extents. Using the available vegetation spatial data, we produced a composite map which identified 6323 wetlands >1ha. We then used the partitioning around medoids cluster analysis method for grouping wetlands based on 12 climate, topography, geology and soils spatial data layers and the wetland locations. We tested a range of cluster numbers from three to 20, and assessed the stability of the clustering by calculating mean silhouette widths. The derived classes were then characterized in terms of number of individual wetlands and their area, and also the number and area of individual wetlands found within protected areas such as national parks.ResultsWe found a peak in the mean silhouette width at 11 clusters, indicating that this was the optimal number of clusters for classifying the wetland data. We produced maps of wetland density for each of the 11 clusters and described the mean and mode environmental characteristics of each cluster. Each cluster represented a unique combination of environmental variables. For example, wetlands in cluster 2 are typically in the south, in areas of low evaporation and low average temperatures. An assessment of rarity found that wetlands in the largest cluster class had an areal extent of 14644ha, compared to 1414ha for the smallest cluster. All but one of the clusters had part of their range within protected areas.ConclusionsClustering environmental variables is an important but underutilized method for characterizing vegetation communities/ecoregions such as wetlands spatially. This approach can be used to produce objective, repeatable and defensible wetland community maps for assessing rarity.

Mongolia is an example of a nation where the rapidity of mining development is outpacing capacity to manage the potential land and water resources impacts. Further, Mongolia has a particular social and economic reliance on traditional uses of land and water, principally livestock herding. While some mining operations are setting high standards in protecting the natural resources surrounding the mine site, others have less incentive and capacity to do so and therefore are having adverse effects on surrounding communities. The paper describes a case study of the Sharyn Gol Soum in northern Mongolia where a range of mining types, from artisanal, small-scale mining to a large coal mine, operate alongside traditional herding lifestyles. A multi-disciplinary approach is taken to observe and attribute causes to the water resources impacts in the area. Surveys of the herding household community, land use mapping, and monitoring the spatial variations in water quality indicate deterioration of water resources. Collectively, the different sources of evidence suggest that the deterioration is mainly due to small-scale gold mining. The evidence included the perception of 78% of the interviewed herders that water quality had changed due to mining; a change in the footprint of small-scale gold mining from 2.8 to 15.2km(2) during the period 1999 to 2015; and pH and sulphate values in 2015 consistently outside the ranges observed at a baseline site in the same region. It is concluded that the lack of baseline data and effective governance mechanisms are fundamental challenges that need to be addressed if Mongolia's transition to a mining economy is to be managed alongside sustainability of herder lifestyles.

The aim of this project was to build on the traditional GIS-based prospectivity analysis for mineral deposits, and integrate data relevant to environmental, community, and infrastructure development, in order to produce "sustainable prospectivity maps". This allows target areas to be highlighted based on both geological and sustainability factors, which both have a significant impact on the ability of exploration and mining companies to operate. A pilot project was undertaken in South-East Sulawesi, Indonesia, which clearly highlighted areas that showed both geological potential for orogenic and placer gold mineralization, as well as favourable sustainability. This approach to sustainable exploration potentially de risks investment in exploration and mineral resource development.

Download Publication Part discussion, part handbook, this document aims to bridge the gap between the current understanding of the impact of mining on Mongolian herder communities, in particular the different impacts on women, men and their traditional livelihoods. It explores the interactions between herding and mining in Mongolia; the current and future socio-economic, institutional and ecological factors that influence this interaction; and how mining projects influence the current gender roles and responsibilities in traditionally herder communities. The handbook presents a discussion around six themes as separate chapters (local community development, water, pasture, dust, resettlement and displacement, and artisanal and small-scale mining); with gender and governance issues cutting across all chapters. It also offers several recommendations for how local government, national government, and mining companies and developers operating in Mongolia can translate these findings into actions that will support responsible minerals development in the future. The research was funded by the Australian Government Overseas Aid program through the Department of Foreign Affairs and Trade.