Evaluation of safety treatments at roadwork zones

A major 3-year research project to improve safety at roadworks has recently been completed by the Centre for Accident Research and Road Safety – Queensland (CARRS-Q) and industry partners. This project involved developing strategies to mitigate roadwork hazards including speeding. This paper presents three on-road evaluation studies on the effectiveness of some current and new safety treatments: use of pilot vehicles, variable message signage (VMS), police enforcement with and without VMS, and remote-controlled traffic control devices. The speed reduction potential of pilot vehicles was evaluated at a highway site. Results showed that pilot vehicles reduced average speeds within the work area, but not at a downstream location. Combinations of VMS and police enforcement were evaluated at a motorway site and results showed that police enforcement accompanied with VMS had greater effects on reducing speeds than either of these treatments alone. Three new remote-controlled traffic control devices—red and amber lights, red light and amber arrow, and a robotic stop/slow sign—were evaluated at a highway site. Results showed that the red light and amber arrow option produced consistent effects on the speeds at the approach to traffic controls and at a location inside the work area. This paper presents the first rigorous evaluations of these roadwork safety treatments in Queensland.

Sustainability at the Australian local government level: Is there room for Strategic Environmental Assessment (SEA)?

Recent calls in Australia have addressed the need for better integration of planning processes. The consequent effort made by government has been, and still is, reshaping the way urban and regional planning and sustainability are managed. Focusing on planning practices at the local and regional levels, we investigate how environmental sustainability is pursued from an institutional perspective. Specifically, we analyse the way that planning in Australian cities aims to achieve sustainable strategies and reflect on the relationship with ‘Strategic Environmental Assessment’. This paper has four goals. First, sustainable planning practices at the local and regional levels are analysed considering the legislative and organizational frameworks of each state. The goal is to identify through an analysis of planning documents how much discretion is given to local councils to address sustainable strategies. Second, we focus on two regional and four cities in Queensland, to outline strengths and weaknesses of current legislative and practical frameworks. We use analytical criteria from the SEA literature to investigate these plans in more detail. Third, we examine the relationship between strategic and statutory plans, to see how sustainability is actually implemented. Finally we compare emerging issues about sustainable planning in Australia with countries overseas with different planning and SEA traditions. Considering that SEA is evolving and there are considerable international experiences, we offer recommendations on how Australia might achieve a more integrated and sustainable approach to planning.

Compact features for birdcall retrieval from environmental acoustic recordings

Bioacoustic data can be used for monitoring animal species diversity. The deployment of acoustic sensors enables acoustic monitoring at large temporal and spatial scales. We describe a content-based birdcall retrieval algorithm for the exploration of large data bases of acoustic recordings. In the algorithm, an event-based searching scheme and compact features are developed. In detail, ridge events are detected from audio files using event detection on spectral ridges. Then event alignment is used to search through audio files to locate candidate instances. A similarity measure is then applied to dimension-reduced spectral ridge feature vectors. The event-based searching method processes a smaller list of instances for faster retrieval. The experimental results demonstrate that our features achieve better success rate than existing methods and the feature dimension is greatly reduced.

Assessing environmental inequalities in ambient air pollution across urban Australia

Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO2) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO2 levels was small and may not translate into substantive differences in health.

Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

Do stakeholders or social obligations drive corporate social and environmental responsibility reporting? Managerial views from a developing country

Purpose – The purpose of this study is to explore senior managers’ perception and motivations of corporate social and environmental responsibility (CSER) reporting in the context of a developing country, Bangladesh. Design/methodology/approach – In-depth semi-structured interviews were conducted with 25 senior managers of companies listed on the Dhaka Stock Exchange. Publicly available annual reports of these companies were also analysed. Findings – The results indicate that senior managers perceive CSER reporting as a social obligation. The study finds that the managers focus mostly on child labour, human resources/rights, responsible products/services, health education, sports and community engagement activities as part of the social obligations. Interviewees identify a lack of a regulatory framework along with socio-cultural and religious factors as contributing to the low level of disclosures. These findings suggest that CSER reporting is not merely stakeholder-driven, but rather country-specific social and environmental issues play an important role in relation to CSER reporting practices. Research limitations/implications – This paper contributes to engagement-based studies by focussing on CSER reporting practices in developing countries and are useful for academics, practitioners and policymakers in understanding the reasons behind CSER reporting in developing countries. Originality/value – This paper addresses a literature “gap” in the empirical study of CSER reporting in a developing country, such as Bangladesh. This study fills a gap in the existing literature to understand managers’ motivations for CSER reporting in a developing country context. Managerial perceptions on CSER issues are largely unexplored in developing countries.

Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade

Tephritid fruit flies (Diptera: Tephritidae) are considered by far the most important group of horticultural pests worldwide. Female fruit flies lay eggs directly into ripening fruit, where the maggots feed causing fruit loss. Each and every continent is plagued by a number of fruit fly pests, both indigenous as well as invasive ones, causing tremendous economic losses. In addition to the direct losses through damage, they can negatively impact commodity trade through restrictions to market access. The quarantine and regulatory controls put in place to manage them are expensive, while the on-farm control costs and loss of crop affect the general well-being of growers. These constraints can have huge implications on loss in revenues and limitations to developing fruit and vegetable-based agroindustries in developing, emergent and developed nations. Because fruit flies are a global problem, the study of their biology and management requires significant international attention to overcome the hurdles they pose. The Joint Food and Agriculture Organisation / International Atomic Energy Agency (FAO/IAEA) Programme on Nuclear Techniques in Food and Agriculture has been on the foreground in assisting Member States in developing and validating environment-friendly fruit fly suppression systems to support viable fresh fruit and vegetable production and export industries. Such international attention has resulted in the successful development and validation of a Sterile Insect Technique (SIT) package for the Mediterranean fruit fly. Although demands for R&D support with respect to Mediterranean fruit fly are diminishing due to successful integration of this package into sustainable control programmes against this pest in many countries, there were increasing demands from Member States in Africa, Asia and Latin America, to address other major fruit fly pests and a related, but sometimes neglected issue of tephritid species complexes of economic importance. Any research, whether it is basic or applied, requires a taxonomic framework that provides reliable and universally recognized entities and names. Among the currently recognized major fruit fly pests, there are groups of species whose morphology is very similar or identical, but biologically they are distinct species. As such, some insect populations that are grouped taxonomically within the same pest species, display different biological and genetic traits and show reproductive isolation which suggest that they are different species. On the other hand, different species may have been taxonomically described, but there may be doubt as to whether they actually represent distinct biological species or merely geographical variants of the same species. This uncertain taxonomic status has practical implications on the effective development and use of the SIT against such complexes, particularly at the time of determining which species to mass-rear, and significantly affects international movement of fruit and vegetables through the establishment of trade barriers to important agricultural commodities which are hosts to these pest tephritid species...

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

The navigation and visualisation of environmental audio using zooming spectrograms

Acoustic recordings play an increasingly important role in monitoring terrestrial and aquatic environments. However, rapid advances in technology make it possible to accumulate thousands of hours of recordings, more than ecologists can ever listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from minutes, hours, days to years. The visualization should facilitate navigation and yield ecologically meaningful information prior to listening to the audio. To construct images, we calculate acoustic indices, statistics that describe the distribution of acoustic energy and reflect content of ecological interest. We combine various indices to produce false-color spectrogram images that reveal acoustic content and facilitate navigation. The technical challenge we investigate in this work is how to navigate recordings that are days or even months in duration. We introduce a method of zooming through multiple temporal scales, analogous to Google Maps. However, the “landscape” to be navigated is not geographical and not therefore intrinsically visual, but rather a graphical representation of the underlying audio. We describe solutions to navigating spectrograms that range over three orders of magnitude of temporal scale. We make three sets of observations: 1. We determine that at least ten intermediate scale steps are required to zoom over three orders of magnitude of temporal scale; 2. We determine that three different visual representations are required to cover the range of temporal scales; 3. We present a solution to the problem of maintaining visual continuity when stepping between different visual representations. Finally, we demonstrate the utility of the approach with four case studies.

Genome-wide association study of major depressive disorder: New results, meta-analysis, and lessons learned

Major depressive disorder (MDD) is a common complex disorder with a partly genetic etiology. We conducted a genome-wide association study of the MDD2000+ sample (2431 cases, 3673 screened controls and >1 M imputed single-nucleotide polymorphisms (SNPs)). No SNPs achieved genome-wide significance either in the MDD2000+ study, or in meta-analysis with two other studies totaling 5763 cases and 6901 controls. These results imply that common variants of intermediate or large effect do not have main effects in the genetic architecture of MDD. Suggestive but notable results were: (a) gene-based tests suggesting roles for adenylate cyclase 3 (ADCY3, 2p23.3) and galanin (GAL, 11q13.3); published functional evidence relates both of these to MDD and serotonergic signaling; (b) support for the bipolar disorder risk variant SNP rs1006737 in CACNA1C (P=0.020, odds ratio=1.10), and; (c) lack of support for rs2251219, a SNP identified in a meta-analysis of affective disorder studies (P=0.51). We estimate that sample sizes 1.8- to 2.4-fold greater are needed for association studies of MDD compared with those for schizophrenia to detect variants that explain the same proportion of total variance in liability. Larger study cohorts characterized for genetic and environmental risk factors accumulated prospectively are likely to be needed to dissect more fully the etiology of MDD.

Genome-wide meta-analysis of common variant differences between men and women

The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 x 10(-8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ~115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.

Common variation in the CYP17A1 and IFIT1 genes on chromosome 10 does not contribute to the risk of endometriosis

Endometriosis is a complex disease involving multiple susceptibility genes and environmental factors. Our previous studies on endometriosis identified a region of significant linkage on chromosome 10q. Two biological candidate genes (CYP17A1 and IFIT1) located on chromosome 10q, have previously been implicated in endometriosis and/or uterine function. We hypothesized that variation in CYP17A1 and/or IFIT1 could contribute to the risk of endometriosis and may account for some of the linkage signal on chromosome 10q. We genotyped 17 single nucleotide polymorphisms (SNPs) in the CYP17A1 and IFIT1 genes including SNP rs743572 previously associated with endometriosis in 768 endometriosis cases and 768 unrelated controls. We found no evidence for association between endometriosis and individual SNPs or SNP haplotypes in CYP17A1 and IFIT1. Common variation in these genes does not appear to be a major contributor to endometriosis susceptibility in our Australian sample.

Within-family outliers: Segregating alleles or environmental effects? A linkage analysis of height from 5815 sibling pairs

Most information in linkage analysis for quantitative traits comes from pairs of relatives that are phenotypically most discordant or concordant. Confounding this, within-family outliers from non-genetic causes may create false positives and negatives. We investigated the influence of within-family outliers empirically, using one of the largest genome-wide linkage scans for height. The subjects were drawn from Australian twin cohorts consisting of 8447 individuals in 2861 families, providing a total of 5815 possible pairs of siblings in sibships. A variance component linkage analysis was performed, either including or excluding the within-family outliers. Using the entire dataset, the largest LOD scores were on chromosome 15q (LOD 2.3) and 11q (1.5). Excluding within-family outliers increased the LOD score for most regions, but the LOD score on chromosome 15 decreased from 2.3 to 1.2, suggesting that the outliers may create false negatives and false positives, although rare alleles of large effect may also be an explanation. Several regions suggestive of linkage to height were found after removing the outliers, including 1q23.1 (2.0), 3q22.1 (1.9) and 5q32 (2.3). We conclude that the investigation of the effect of within-family outliers, which is usually neglected, should be a standard quality control measure in linkage analysis for complex traits and may reduce the noise for the search of common variants of modest effect size as well as help identify rare variants of large effect and clinical significance. We suggest that the effect of within-family outliers deserves further investigation via theoretical and simulation studies.