Current and projected heatwave-attributable occupational injuries, illnesses, and associated economic burden in Australia.

INTRODUCTION: The costs of global warming are substantial. These include expenses from occupational illnesses and injuries (OIIs), which have been associated with increases during heatwaves. This study estimated retrospective and projected future heatwave-attributable OIIs and their costs in Australia. MATERIALS AND METHODS: Climate and workers' compensation claims data were extracted from seven Australian capital cities representing OIIs from July 2005 to June 2018. Heatwaves were defined using the Excess Heat Factor. OIIs and associated costs were estimated separately per city and pooled to derive national estimates. Results were projected to 2030 (2016-2045) and 2050 (2036-2065). RESULTS: The risk of OIIs and associated costs increased during heatwaves, with the risk increasing during severe and particularly extreme heatwaves. Of all OIIs, 0.13% (95% empirical confidence interval [eCI]: 0.11-0.16%) were heatwave-attributable, equivalent to 120 (95%eCI:70-181) OIIs annually. 0.25% of costs were heatwave-attributable (95%eCI: 0.18-0.34%), equal to $AU4.3 (95%eCI: 1.4-7.4) million annually. Estimates of heatwave-attributable OIIs by 2050, under Representative Concentration Pathway [RCP]4.5 and RCP8.5, were 0.17% (95%eCI: 0.10-0.27%) and 0.23% (95%eCI: 0.13-0.37%), respectively. National costs estimates for 2030 under RCP4.5 and RCP8.5 were 0.13% (95%eCI: 0.27-0.46%) and 0.04% (95%eCI: 0.66-0.60), respectively. These estimates for extreme heatwaves were 0.04% (95%eCI: 0.02-0.06%) and 0.04% (95%eCI: 0.01-0.07), respectively. Cost-AFs in 2050 were, under RCP4.5, 0.127% (95%eCI: 0.27-0.46) for all heatwaves and 0.04% (95%eCI: 0.01-0.09%) for extreme heatwaves. Attributable fractions were approximately similar to baseline when assuming theoretical climate adaptation. DISCUSSION: Heatwaves represent notable and preventable portions of preventable OIIs and economic burden. OIIs are likely to increase in the future, and costs during extreme heatwaves in 2030. Workplace and public health policies aimed at heat adaptation can reduce heat-attributable morbidity and costs.

The utility of coded very high frequency telemetry for monitoring reintroduced mammal populations.

Very high frequency (VHF) radio tracking technology deployed on terrestrial vertebrates has been well utilized in ecology without much evolution since the 1960s. With the advent of multi-species rewilding projects, and the new field of reintroduction biology, there has been an increase in requirements for telemetry systems to monitor survival and mortality for many animals simultaneously. Common, pulsed VHF can only monitor one individual on each radio frequency, and the number of individuals monitored is constrained by the amount of time spent on each frequency to facilitate a detection and the number of receivers. Coded VHF largely removes these constraints by using a digital code that can simultaneously monitor up to 512 individuals on a single frequency. Incorporated into an autonomous monitoring system, the coded VHF system also greatly reduces time in the field to confirm the status of individuals. Here we demonstrate the utility of coded VHF technologies applied to monitoring a reintroduced population of brush-tailed bettong (Bettongia penicillata) on the Southern Yorke Peninsula in southern Australia. A system of autonomous monitoring towers was able to monitor 28 different individuals simultaneously without having to change frequency on any of the towers. During a single 24-h period, one individual was recorded 24,078 times. Key benefits of the high detection rate and autonomous recording are, a timely response to mortalities or a predation event, the detection of nocturnal, cryptic, or burrowing species whenever they are active, and the reduced need for personnel to be in the field.

Detecting Grapevine Virus Infections in Red and White Winegrape Canopies Using Proximal Hyperspectral Sensing.

Grapevine virus-associated disease such as grapevine leafroll disease (GLD) affects grapevine health worldwide. Current diagnostic methods are either highly costly (laboratory-based diagnostics) or can be unreliable (visual assessments). Hyperspectral sensing technology is capable of measuring leaf reflectance spectra that can be used for the non-destructive and rapid detection of plant diseases. The present study used proximal hyperspectral sensing to detect virus infection in Pinot Noir (red-berried winegrape cultivar) and Chardonnay (white-berried winegrape cultivar) grapevines. Spectral data were collected throughout the grape growing season at six timepoints per cultivar. Partial least squares-discriminant analysis (PLS-DA) was used to build a predictive model of the presence or absence of GLD. The temporal change of canopy spectral reflectance showed that the harvest timepoint had the best prediction result. Prediction accuracies of 96% and 76% were achieved for Pinot Noir and Chardonnay, respectively. Our results provide valuable information on the optimal time for GLD detection. This hyperspectral method can also be deployed on mobile platforms including ground-based vehicles and unmanned aerial vehicles (UAV) for large-scale disease surveillance in vineyards.

The behavioral responses of a nocturnal burrowing marsupial (Lasiorhinus latifrons) to drone flight.

The use of drones in wildlife research and management is increasing. Recent evidence has demonstrated the impact of drones on animal behavior, but the response of nocturnal animals to drone flight remains unknown. Utilizing a lightweight commercial drone, the behavioral response of southern hairy-nosed wombats (Lasiorhinus latifrons) to drone flights was observed at Kooloola Station, Swan Reach, South Australia. All wombats flown over during both day and night flights responded behaviorally to the presence of drones. The response differed based on time of day. The most common night-time behavior elicited by drone flight was retreat, compared to stationary alertness behavior observed for daytime drone flights. The behavioral response of the wombats increased as flight altitude decreased. The marked difference of behavior between day and night indicates that this has implications for studies using drones. The behavior observed during flights was altered due to the presence of the drone, and therefore, shrewd study design is important (i.e., acclimation period to drone flight). Considering the sensory adaptations of the target species and how this may impact its behavioral response when flying at night is essential.

Using satellite imagery to evaluate precontact Aboriginal foraging habitats in the Australian Western Desert.

Modern satellite imaging offers radical new insights of the challenges and opportunities confronting traditional Aboriginal ecology and land use in Australia's Western Desert. We model the likely dynamics of historic and precontact desert land use using Earth observation data to identify the distribution of suitable foraging habitats. Suitability was modelled for an ideal environmental scenario, based on satellite observations of maximal water abundance, vegetation greenness, and terrain ruggedness. Our model shows that the highest-ranked foraging habitats do not align with land systems or bioregions that have been used in previous reconstructions of Australian prehistory. We identify impoverished desert areas where unsuitable foraging conditions have likely persisted since early in the last glacial cycle, and in which occupation would always have been rare. These findings lead us to reconsider past patterns of land use and the predicted archaeological signature of earlier desert peoples.

Relationship Between Traffic Volume and Accident Frequency at Intersections.

Driven by the high social costs and emotional trauma that result from traffic accidents around the world, research into understanding the factors that influence accident occurrence is critical. There is a lack of consensus about how the management of congestion may affect traffic accidents. This paper aims to improve our understanding of this relationship by analysing accidents at 120 intersections in Adelaide, Australia. Data comprised of 1629 motor vehicle accidents with traffic volumes from a dataset of more than five million hourly measurements. The effect of rainfall was also examined. Results showed an approximately linear relationship between traffic volume and accident frequency at lower traffic volumes. In the highest traffic volumes, poisson and negative binomial models showed a significant quadratic explanatory term as accident frequency increases at a higher rate. This implies that focusing management efforts on avoiding these conditions would be most effective in reducing accident frequency. The relative risk of rainfall on accident frequency decreases with increasing congestion index. Accident risk is five times greater during rain at low congestion levels, successively decreasing to no elevated risk at the highest congestion level. No significant effect of congestion index on accident severity was detected.

Current Understanding of the Effects of Congestion on Traffic Accidents.

Traffic accidents impart both economic and social costs upon communities around the world, hence the desire for accident rates to be reduced. For this reduction to occur, the factors influencing the occurrence of accidents must be understood. The role of congestion in modifying accident risk has been widely studied, but consensus has not been reached, with conflicting results leaving open questions. An inverse relationship between accidents and congestion would imply a benefit of congested conditions for road safety, posing a difficult situation for traffic management. This paper assesses articles that reveal the shape of the relationship between traffic accidents and congestion. We find a positive linear response to dominate the literature. However, studies with higher numbers of statistical units tend to show a U-shaped relationship. This suggests an important role of high spatio-temporal traffic data in understanding factors causing accidents and identifying the combination of real-time conditions which may lead to increased accident risk. Modern advancements in traffic measurement systems provide the ability for real-time alleviation of accident-prone conditions before they can fully develop.

The Significance of Social Perceptions in Implementing Successful Feral Cat Management Strategies: A Global Review.

This review examines the social aspects that influence feral cat management. In particular, it examines definitions and perceptions of feral cats as a species in different countries and across cultures. Using case studies from around the world, we investigate the factors that can influence public perceptions and social acceptance of feral cats and management methods. The review then highlights the importance of social factors in management and suggests the best approach to use in the future to ease the process of gaining a social license for management campaigns. Implications of the influence of education and awareness on public perception and acceptance are further explained, and are suggested to be an essential tool in successfully engaging the community about management in the future.

Performance of Excess Heat Factor Severity as a Global Heatwave Health Impact Index.

The establishment of an effective policy response to rising heatwave impacts is most effective when the history of heatwaves, their current impacts and future risks, are mapped by a common metric. In response meteorological agencies aim to develop seamless climate, forecast, and warning heat impact services, spanning all temporal and spatial scales. The ability to diagnose heatwave severity using the Excess Heat Factor (EHF) has allowed the Australian Bureau of Meteorology (the Bureau) to publicly release 7-day heatwave severity maps since 2014. National meteorological agencies in the UK and the United States are evaluating global 7-day and multi-week EHF heatwave severity probability forecasts, whilst the Bureau contributes to a Copernicus project to supply the health sector with global EHF severity heatwave projection scenarios. In an evaluation of impact skill within global forecast systems, EHF intensity and severity is reviewed as a predictor of human health impact, and extended using climate observations and human health data for sites around the globe. Heatwave intensity, determined by short and long-term temperature anomalies at each locality, is normalized to permit spatial analysis and inter-site comparison. Dimensionless heatwave event moments of peak severity and accumulated severity are shown to correlate with noteworthy events around the globe, offering new insights into current and future heatwave variability and vulnerability. The EHF severity metric permits the comparison of international heatwave events and their impacts, and is readily implemented within international heatwave early warning systems.

A Comparison between Video and Still Imagery as a Methodology to Determine Southern Hairy-Nosed Wombat (Lasiorhinus latifrons) Burrow Occupancy Rates.

Broad-scale abundance estimates of the southern hairy-nosed wombat population use a proxy measure based on counting the number of active burrows, which is multiplied by an index of 'wombats/active burrow'. However, the extant indices were calculated in the 1980s, prior to the use of calicivirus to control rabbits, and used invasive monitoring methods which may have affected the results. We hypothesise that the use of video might provide a logistically simple, non-invasive means of calculating updated indices. To this end, motion-activated, infra-red still and video cameras were placed at various distances outside active wombat burrows in the South Australian Murraylands and Eyre Peninsula regions. The captured imagery was inspected to determine how often the burrow was occupied by one or more wombats, and how effective the cameras were at detecting wombat activity. Video data was clearly superior to the still imagery, with more than twice as many burrow occupancies being positively identified (still: 43%). The indices of wombats/active burrow calculated based on video imagery were: Murraylands: 0.43, Eyre Peninsula: 0.42. 1948 false positive videos were recorded, of which 1674 (86%) occurred between noon and sunset.

Climate change and the economics of biomass energy feedstocks in semi-arid agricultural landscapes: A spatially explicit real options analysis.

The economics of establishing perennial species as renewable energy feedstocks has been widely investigated as a climate change adapted diversification option for landholders, primarily using net present value (NPV) analysis. NPV does not account for key uncertainties likely to influence relevant landholder decision making. While real options analysis (ROA) is an alternative method that accounts for the uncertainty over future conditions and the large upfront irreversible investment involved in establishing perennials, there have been limited applications of ROA to evaluating land use change decision economics and even fewer applications considering climate change risks. Further, while the influence of spatially varying climate risk on biomass conversion economic has been widely evaluated using NPV methods, effects of spatial variability and climate on land use change have been scarcely assessed with ROA. In this study we applied a simulation-based ROA model to evaluate a landholder's decision to convert land from agriculture to biomass. This spatially explicit model considers price and yield risks under baseline climate and two climate change scenarios over a geographically diverse farming region. We found that underlying variability in primary productivity across the study area had a substantial effect on conversion thresholds required to trigger land use change when compared to results from NPV analysis. Areas traditionally thought of as being quite similar in average productive capacity can display large differences in response to the inclusion of production and price risks. The effects of climate change, broadly reduced returns required for land use change to biomass in low and medium rainfall zones and increased them in higher rainfall areas. Additionally, the risks posed by climate change can further exacerbate the tendency for NPV methods to underestimate true conversion thresholds. Our results show that even under severe drying and warming where crop yield variability is more affected than perennial biomass plantings, comparatively little of the study area is economically viable for conversion to biomass under $200/DM t, and it is not until prices exceed $200/DM t that significant areas become profitable for biomass plantings. We conclude that for biomass to become a valuable diversification option the synchronisation of products and services derived from biomass and the development of markets is vital.

Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2) area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural spatio-temporal variables such as rainfall, soil type, and vegetation community distributions, due to the nature of the cross-fence experimental design, and the spatially comprehensive data available in satellite imagery. This method provides a potential tool to aid land managers in decision making processes, particularly with regard to stocking rates.

Real options analysis for land use management: Methods, application, and implications for policy.

Discounted cash flow analysis, including net present value is an established way to value land use and management investments which accounts for the time-value of money. However, it provides a static view and assumes passive commitment to an investment strategy when real world land use and management investment decisions are characterised by uncertainty, irreversibility, change, and adaptation. Real options analysis has been proposed as a better valuation method under uncertainty and where the opportunity exists to delay investment decisions, pending more information. We briefly review the use of discounted cash flow methods in land use and management and discuss their benefits and limitations. We then provide an overview of real options analysis, describe the main analytical methods, and summarize its application to land use investment decisions. Real options analysis is largely underutilized in evaluating land use decisions, despite uncertainty in policy and economic drivers, the irreversibility and sunk costs involved. New simulation methods offer the potential for overcoming current technical challenges to implementation as demonstrated with a real options simulation model used to evaluate an agricultural land use decision in South Australia. We conclude that considering option values in future policy design will provide a more realistic assessment of landholder investment decision making and provide insights for improved policy performance.

Spatial distribution of diuron sorption affinity as affected by soil, terrain and management practices in an intensively managed apple orchard.

We investigated how the sorption affinity of diuron (3'-(3,4-dichlorophenyl)-1,1-dimenthyl-urea), a moderately hydrophobic herbicide, is affected by soil properties, topography and management practices in an intensively managed orchard system. Soil-landscape analysis was carried out in an apple orchard which had a strong texture contrast soil and a landform with relief difference of 50 m. Diuron sorption (K(d)) affinity was successfully predicted (R(2)=0.79; p<0.001) using a mid-infrared - partial least squares model and calibrated against measured data using a conventional batch sorption technique. Soil and terrain properties explained 75% of the variance of diuron K(d) with TOC, pH(w), slope and WI as key variables. Mean diuron K(d) values were also significantly different (p<0.05) between alley and tree line and between the different management zones. Soil in the tree line generally had lower sorption capacity for diuron than soil in the alleys. Younger stands, which were found to have lower TOC than in the older stands, also had lower diuron K(d) values. In intensively managed orchards, sorption affinity of pesticides to soils was not only affected by soil properties and terrain attributes but also by management regime.

Non-detection errors in a survey of persistent, highly-detectable vegetation species.

Rare, small or annual vegetation species are widely known to be imperfectly detected with single site surveys by most conventional vegetation survey methods. However, the detectability of common, persistent vegetation species is assumed to be high, but without supporting research. In this study, we evaluate the extent of false-negative errors of perennial vegetation species in a systematic vegetation survey in arid South Australia. Analysis was limited to the seven most easily detected persistent vegetation species and controlled for observer skill. By comparison of methodologies, we then predict the magnitude of non-detection error rates in a second survey. The analysis revealed that all but one highly detectable perennial vegetation species was imperfectly detected (detection probabilities ranged from 0.22 to 0.83). While focussed in the Australian rangelands, the implications of this study are far reaching. Inferences drawn from systematic vegetation surveys that fail to identify and account for non-detection errors should be considered potentially flawed. The identification of this problem in vegetation surveying is long overdue. By comparison, non-detection has been a widely acknowledged, and dealt with, problem in fauna surveying for decades. We recommend that, where necessary, vegetation survey methodology adopt the methods developed in fauna surveying to cope with non-detection errors.