Handling and updating uncertain information in bow-tie analysis

Bow-tie analysis is a fairly new concept in risk assessment that can describe the relationships among different risk control parameters, such as causes, hazards and consequences to mitigate the likelihood of occurrence of unwanted events in an industrial system. It also facilitates the performance of quantitative risk analysis for an unwanted event providing a detailed investigation starting from basic causes to final consequences. The credibility of quantitative evaluation of the bow-tie is still a major concern since uncertainty, due to limited or missing data, often restricts the performance of analysis. The utilization of expert knowledge often provides an alternative for such a situation. However, it comes at the cost of possible uncertainties related to incompleteness (partial ignorance), imprecision (subjectivity), and lack of consensus (if multiple expert judgments are used). Further, if the bow-tie analysis is not flexible enough to incorporate new knowledge or evidence, it may undermine the purpose of risk assessment.Fuzzy set and evidence theory are capable of characterizing the uncertainty associated with expert knowledge. To minimize the overall uncertainty, fusing the knowledge of multiple experts and updating prior knowledge with new evidence are equally important in addition to addressing the uncertainties in the knowledge. This paper proposes a methodology to characterize the uncertainties, aggregate knowledge and update prior knowledge or evidence, if new data become available for the bow-tie analysis. A case study comprising a bow-tie for a typical offshore process facility has also been developed to describe the utility of this methodology in an industrial environment.     

Prevalence-adjusted optimisation of fuzzy models for species distribution

Most performance criteria which have been applied to train ecological models focus on the accuracy of the model predictions. However, these criteria depend on the prevalence of the training set and often do not take into account ecological issues such as the distinction between omission and commission errors. Moreover, a previous study indicated that model training based on different performance criteria results in different optimised models. Therefore, model developers should train models based on different performance criteria and select the most appropriate model depending on the modelling objective. This paper presents a new approach to train fuzzy models based on an adjustable performance criterion, called the adjusted average deviation (aAD). This criterion was applied to develop a species distribution model for spawning grayling in the Aare River near Thun, Switzerland. To analyse the strengths and weaknesses of this approach, it was compared to model training based on other performance criteria. The results suggest that model training based on accuracy-based performance criteria may produce unrealistic models at extreme prevalences of the training set, whereas the aAD allows for the identification of more accurate and more reliable models. Moreover, the adjustable parameter in this criterion enables modellers to situate the optimised models in the search space and thus provides an indication of the ecological model relevance. Consequently, it may support modellers and river managers in the decision making process by improving model reliability and insight into the modelling process. Due to the universality and the flexibility of the approach, it could be applied to any other ecosystem or species, and may therefore be valuable to ecological modelling and ecosystem management in general.     

Modelling the outcrossing between genetically modified and conventional maize with equation discovery

Many studies explore the feasibility of co-existence between genetically modified (GM) and conventional (non-GM) crops. An important research topic in these studies is the process of outcrossing, i.e., the process of gene flow via pollen flow from GM to non-GM crops. In this paper, we address a new modelling approach to define the environmentally driven processes of outcrossing for maize from existing empirical datasets. In particular, we use equation discovery methodology that combines background knowledge and empirical data from several studies. We induce models that predict the degree of outcrossing rate between the donor (GM) and the recipient (non-GM) maize field from the distance between the fields and the local wind characteristics (speed, direction and duration). This results in highly accurate models, for which both variables (distance and wind) are essential and of roughly equal importance.     

Is current agronomy ready to promote sustainable agriculture? Identifying key skills and competencies needed

The quest for agricultural sustainability generates the need to develop functional support schemes aimed at supplying farmers with knowledge, information and appropriate solutions, thus smoothing the transition towards sustainable agriculture (SA). In this vein, it is expected that agronomists have to play a key role, plotting the course for a sustainable farming future. Nevertheless, a critical question is whether agronomists possess the skills and competencies needed to motivate and guide this transition process. Two studies were designed to examine which clusters of agronomists’ skills and competencies determine their ability to promote SA. Study 1, using data from a sample of farmers, revealed that agronomists’ level of knowledge on issues pertaining to SA, their networking capacities, facilitation competencies, and communication skills affect their ability to guide the transition towards sustainable farm production. Study 2, drawing on data from a sample of agronomists, confirmed the pivotal role of sustainability knowledge, facilitation skills and networking competencies on the aptitude to promote SA. Both studies uncovered that agronomists display low to moderate levels of these skills. Taken together, these results point out the need to reorganize agronomic (formal and lifelong) education in order to equip agronomists with new competencies and to enable them to effectively promote SA.     

基于文献计量学的“十三五”生态环境监测研究热点分析

利用科学计量与可视化相关工具,以《中文核心期刊要目总览(2017年版)》27种环境科学类核心期刊发表的2016—2020年生态环境监测论文数据为基础,从载文量分布、高被引论文、高产机构分布和技术主题分布等方面分析了"十三五"期间我国生态环境监测研究热点。结果表明:"十三五"期间生态环境监测论文数量有所增加,主要载文期刊分布于《环境科学》《中国环境监测》《环境科学与技术》;主要发文机构是中国环境科学研究院、中国环境监测总站、中国科学院大学;排名前10位的技术主题词分别是PM_(2.5)、重金属、土壤、污染特征、颗粒物、挥发性有机物、生态风险、臭氧、沉积物、多环芳烃,结合"十三五"前期和中后期热点主题词变化分析了生态环境监测研究关注点的变化趋势。     

Ecological literacy and psychographics: lifestyle contributors to ecological knowledge and understanding

Knowledge and understanding about how the ecological systems of the Earth support life form the foundation for ecological literacy, which, in turn, is of critical importance for sustainability. There is widespread concern that levels of ecological literacy within many contemporary human societies are too low to enable effective decision-making about how to live sustainably. This paper presents and discusses the findings of an ecological literacy assessment of South Australian adults. The assessment tested for knowledge and understanding of ecological systems and interconnections with human society. Analyses revealed significant relationships between assessment scores and a range of value-based and behavioural characteristics. Such characteristics included the value placed on nature, time spent outdoors and in nature, involvement in nature-based activities, and perceived sources of ecological knowledge and understanding. Higher average scores were correlated with higher values accorded to involvement in outdoor activities, importance of the outdoors to enjoyment of life, importance of nature in the household, volunteer environmental activity and growing food. Higher scores were also correlated with higher education, research activities, outdoor lifestyles, place-based experiences, volunteer activities, mentors and colleagues, and books and magazines. Lower scores were achieved by those who considered media, natural disasters and environmental marketing to be major contributors to their ecological knowledge. These findings contribute to a broader study of the relationships between ecological literacy and a range of both socio-demographic and psychographic characteristics. They invite serious consideration from any society that values the participation of an informed population with the capacity to make sustainable environmental decisions.     

How expert insight into alpine peatland conservation complements global scientific evidence

Experts can provide valuable information to fill knowledge gaps in published research on management effectiveness, particularly for threatened ecosystems, for which there is often limited evidence and the need for prompt intervention to ensure their persistence. One such ecosystem, alpine peatland, is threatened by climate change and other pressures, provides vital ecosystem services, and supports unique biodiversity. In a workshop, we gathered and synthesized into an accessible format information from experts on interventions used, threat context, and intervention effectiveness for Australian alpine peatland and used this knowledge to evaluate local relevance of the global literature for this threatened ecosystem. Experts identified 15 interventions used to conserve Australian peatlands, most of which enhanced or restored peatland condition and effectively addressed diverse threats. Experts’ perspectives and global studies were strongly aligned, suggesting that research on peatland management may be broadly relevant across contexts, despite the distinct characteristics of Australian systems. Our workshop-based expert elicitation approach provided insights into current management practices unavailable in the literature.     

Performance and microbial community analysis of bioaugmented activated sludge for nitrogen-containing organic pollutants removal

Nitrogen-containing organic pollutants (quinoline, pyridine and indole) are widely distributed in coking wastewater, and bioaugmentation with specific microorganisms may enhance the removal of these recalcitrant pollutants. The bioaugmented system (group B) was constructed through inoculation of two aromatics-degrading bacteria, Comamonas sp. Z1 (quinoline degrader) and Acinetobacter sp. JW (indole degrader), into the activated sludge for treatment of quinoline, indole and pyridine, and the non-bioaugmented activated sludge was used as the control (group C). Both groups maintained high efficiencies (> 94%) for removal of nitrogen-containing organic pollutants and chemical oxygen demand (COD) during the long-term operation, and group B was highly effective at the starting period and the operation stage fed with raw wastewater. High-throughput sequencing analysis indicated that nitrogen-containing organic pollutants could shape the microbial community structure, and communities of bioaugmented group B were clearly separated from those of non-bioaugmented group C as observed in non-metric multidimensional scaling (NMDS) plot. Although the inoculants did not remain their dominance in group B, bioaugmentation could induce the formation of effective microbial community, and the indigenous microbes might play the key role in removal of nitrogen-containing organic pollutants, including Dokdonella, Comamonas and Pseudoxanthomonas. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis suggested that bioaugmentation could facilitate the enrichment of functional genes related to xenobiotics biodegradation and metabolism, probably leading to the improved performance in group B. This study indicated that bioaugmentation could promote the removal of nitrogen-containing organic pollutants, which should be an effective strategy for wastewater treatment.     

A GIS-based protocol for the collection and use of local knowledge in fisheries management planning

Despite a heavy reliance on scientific knowledge as the primary source of information in resource management, many resources are in decline, particularly in fisheries. To try and combat this trend, researchers have drawn upon the knowledge of local resource users as an important supplement to scientific knowledge in designing and implementing management strategies. The integration of local knowledge with scientific knowledge for marine species management, however, is problematic stemming primarily from conflicting data types. This paper considers the use of spatial information technology as a medium to integrate and visualise spatial distributions of both quantitative scientific data and qualitative local knowledge for the purposes of producing valid and locally relevant fisheries management plans. In this context, the paper presents a detailed protocol for the collection and subsequent use of local knowledge in fisheries management planning using geographic information systems (GIS). Particular attention is paid to the use of local knowledge in resource management, accuracy issues associated with the incorporation of qualitative data into a quantitative environment, base map selection and construction, and map bias or errors associated with the accuracy of recording harvest locations on paper map sheets, given the complications of map scale.     

Social actors’ perceptions of wildlife: Insights for the conservation of species in Mediterranean protected areas

AbstractIn the current Anthropocene Era, with numerous escalating challenges for biodiversity conservation, the inclusion of the social dimension into management decisions regarding wildlife and protected areas is critical to their success. By conducting 354 questionnaires in a Mediterranean protected area (the Biosphere Reserve of Bardenas Reales, Northern Spain), we aim to determine sociodemographic factors influencing knowledge levels and perceptions of species and functional groups as, emblematic and threatened. We found that hunters and animal husbandry workers knew more species than other social actors. Additionally, the perception of functional groups as threatened or emblematic differed between social actor groups, with statistically significant associations between perceptions and the characteristics of respondents. Interestingly, we found that although elusive steppe species are globally considered as endangered, these species were the least known by all social actor groups and rarely perceived as emblematic. This research is a novel approach and provides a better understanding of how perceptions can facilitate conservation decisions, particularly regarding endangered speciesGraphic abstract Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01546-6.