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Although invasive alien species have long been recognized as a major threat to nature and people, until now there has been no comprehensive global review of the status, trends, drivers, impacts, management and governance challenges of biological invasions. The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) Thematic Assessment Report on Invasive Alien Species and Their Control (hereafter 'IPBES invasive alien species assessment') drew on more than 13,000 scientific publications and reports in 15 languages as well as Indigenous and local knowledge on all taxa, ecosystems and regions across the globe. Therefore, it provides unequivocal evidence of the major and growing threat of invasive alien species alongside ambitious but realistic approaches to manage biological invasions. The extent of the threat and impacts has been recognized by the 143 member states of IPBES who approved the summary for policymakers of this assessment. Here, the authors of the IPBES assessment outline the main findings of the IPBES invasive alien species assessment and highlight the urgency to act now.

Species introduced through human-related activities beyond their native range, termed alien species, have various impacts worldwide. The IUCN Environmental Impact Classification for Alien Taxa (EICAT) is a global standard to assess negative impacts of alien species on native biodiversity. Alien species can also positively affect biodiversity (for instance, through food and habitat provisioning or dispersal facilitation) but there is currently no standardized and evidence-based system to classify positive impacts. We fill this gap by proposing EICAT+, which uses 5 semiquantitative scenarios to categorize the magnitude of positive impacts, and describes underlying mechanisms. EICAT+ can be applied to all alien taxa at different spatial and organizational scales. The application of EICAT+ expands our understanding of the consequences of biological invasions and can inform conservation decisions.

Species introduced through human-related activities beyond their native range, termed alien species, have various impacts worldwide. The IUCN Environmental Impact Classification for Alien Taxa (EICAT) is a global standard to assess negative impacts of alien species on native biodiversity. Alien species can also positively affect biodiversity (for instance, through food and habitat provisioning or dispersal facilitation) but there is currently no standardized and evidence-based system to classify positive impacts. We fill this gap by proposing EICAT+, which uses 5 semiquantitative scenarios to categorize the magnitude of positive impacts, and describes underlying mechanisms. EICAT+ can be applied to all alien taxa at different spatial and organizational scales. The application of EICAT+ expands our understanding of the consequences of biological invasions and can inform conservation decisions.

Macroecology is the study of patterns, and the processes that determine those patterns, in the distribution and abundance of organisms at large scales, whether they be spatial (from hundreds of kilometres to global), temporal (from decades to centuries), and organismal (numbers of species or higher taxa). In the context of invasion ecology, macroecological studies include, for example, analyses of the richness, diversity, distribution, and abundance of alien species in regional floras and faunas, spatio-temporal dynamics of alien species across regions, and cross- taxonomic analyses of species traits among comparable native and alien species pools. However, macroecological studies aiming to explain and predict plant and animal naturalisations and invasions, and the resulting impacts, have, to date, rarely considered the joint effects of species traits, environment, and socioeconomic characteristics. To address this, we present the MAcroecological Framework for Invasive Aliens (MAFIA). The MAFIA explains the invasion phenomenon using three interacting classes of factors – alien species traits, location characteristics, and factors related to introduction events – and explicitly maps these interactions onto the invasion sequence from transport to naturalisation to invasion. The framework therefore helps both to identify how anthropogenic effects interact with species traits and environmental characteristics to determine observed patterns in alien distribution, abundance, and richness; and to clarify why neglecting anthropogenic effects can generate spurious conclusions. Event-related factors include propagule pressure, colonisation pressure, and residence time that are important for mediating the outcome of invasion processes. However, because of context dependence, they can bias analyses, for example those that seek to elucidate the role of alien species traits. In the same vein, failure to recognise and explicitly incorporate interactions among the main factors impe

The family Cactaceae Juss. contains some of the most widespread and damaging invasive alien plant species in the world, with Australia (39 species), South Africa (35) and Spain (24) being the main hotspots of invasion. The Global Cactus Working Group (IOBC GCWG) was launched in 2015 to improve international collaboration and identify key actions that can be taken to limit the impacts caused by cactus invasions worldwide. Based on the results of an on-line survey, information collated from a review of the scientific and grey literature, expertise of the authors, and because invasiveness appears to vary predictably across the family, we (the IOBC GCWG): (1) recommend that invasive and potentially invasive cacti are regulated, and to assist with this, propose five risk categories; (2) recommend that cactus invasions are treated physically or chemically before they become widespread; (3) advocate the use of biological control to manage widespread invasive species; and (4) encourage the development of public awareness and engagement initiatives to integrate all available knowledge and perspectives in the development and implementation of management actions, and address conflicts of interest, especially with the agricultural and ornamental sectors. Implementing these recommendations will require global co-operation. The IOBC GCWG aims to assist with this process through the dissemination of information and experience

Alien species can have major ecological and socioeconomic impacts in their novel ranges and so effective management actions are needed. However, management can be contentious and create conflicts, especially when stakeholders who benefit from alien species are different from those who incur costs. Such conflicts of interests mean that management strategies can often not be implemented. There is, therefore, increasing interest in engaging stakeholders affected by alien species or by their management. Through a facilitated workshop and consultation process including academics and managers working on a variety of organisms and in different areas (urban and rural) and ecosystems (terrestrial and aquatic), we developed a framework for engaging stakeholders in the management of alien species. The proposed framework for stakeholder engagement consists of 12 steps: (1) identify stakeholders; (2) select key stakeholders for engagement; (3) explore key stakeholders' perceptions and develop initial aims for management; (4) engage key stakeholders in the development of a draft management strategy; (5) re-explore key stakeholders' perceptions and revise the aims of the strategy; (6) co-design general aims, management objectives and time frames with key stakeholders; (7) co-design a management strategy; (8) facilitate stakeholders' ownership of the strategy and adapt as required; and (9) implement the strategy and monitor management actions to evaluate the need for additional or future actions. In case additional management is needed after these actions take place, some extra steps should be taken: (10) identify any new stakeholders, benefits, and costs; (11) monitor engagement; and (12) revise management strategy. Overall, we believe that our framework provides an effective approach to minimize the impact of conflicts created by alien species management.

Human activities such as the transport of species to new regions and modifications of the environment are increasingly reshaping the distribution of biota. Accordingly, developing robust, repeatable, and consistent definitions of alien species that serve scientific and policy purposes has become of prime importance. We provide a set of classification criteria that are widely applicable across taxa and realms and offer guidance on their use in practice. The criteria focus on (a) acknowledging the role of assessment uncertainty, (b) incorporating time since introduction, (c) considering infraspecific taxonomic ranks, and (d) differentiating between alien species whose survival depends on explicit human assistance from those that survive without such assistance. Furthermore, we make recommendations for reducing assessment uncertainty, suggest thresholds for species assessment, and develop an assessment scheme. We illustrate the application of the assessment criteria with case studies. Finally, the implications for alien species management, policy, and research are discussed.

Human activities such as the transport of species to new regions and modifications of the environment are increasingly reshaping the distribution of biota. Accordingly, developing robust, repeatable, and consistent definitions of alien species that serve scientific and policy purposes has become of prime importance. We provide a set of classification criteria that are widely applicable across taxa and realms and offer guidance on their use in practice. The criteria focus on (a) acknowledging the role of assessment uncertainty, (b) incorporating time since introduction, (c) considering infraspecific taxonomic ranks, and (d) differentiating between alien species whose survival depends on explicit human assistance from those that survive without such assistance. Furthermore, we make recommendations for reducing assessment uncertainty, suggest thresholds for species assessment, and develop an assessment scheme. We illustrate the application of the assessment criteria with case studies. Finally, the implications for alien species management, policy, and research are discussed.

The global shipping network facilitates the transportation and introduction of marine and terrestrial organisms to regions where they are not native, and some of these organisms become invasive. South Africa was used as a case study to evaluate the potential for shipping to contribute to the introduction and establishment of marine and terrestrial alien species (i.e. establishment debt) and to assess how this varies across shipping routes and seasons. As a proxy for the number of species introduced (i.e. 'colonisation pressure') shipping movement data were used to determine, for each season, the number of ships that visited South African ports from foreign ports and the number of days travelled between ports. Seasonal marine and terrestrial environmental similarity between South African and foreign ports was then used to estimate the likelihood that introduced species would establish. These data were used to determine the seasonal relative contribution of shipping routes to South Africa's marine and terrestrial establishment debt. Additionally, distribution data were used to identify marine and terrestrial species that are known to be invasive elsewhere and which might be introduced to each South African port through shipping routes that have a high relative contribution to establishment debt. Shipping routes from Asian ports, especially Singapore, have a particularly high relative contribution to South Africa's establishment debt, while among South African ports, Durban has the highest risk of being invaded. There was seasonal variation in the shipping routes that have a high relative contribution to the establishment debt of the South African ports. The presented method provides a simple way to prioritise surveillance effort and our results indicate that, for South Africa, port-specific prevention strategies should be developed, a large portion of the available resources should be allocated to Durban, and seasonal variations and their consequences for prevention s

Many alien taxa are known to cause socio-economic impacts by affecting the different constituents of human well-being (security; material and non-material assets; health; social, spiritual and cultural relations; freedom of choice and action). Attempts to quantify socio-economic impacts in monetary terms are unlikely to provide a useful basis for evaluating and comparing impacts of alien taxa because they are notoriously difficult to measure and important aspects of human well-being are ignored.Here, we propose a novel standardised method for classifying alien taxa in terms of the magnitude of their impacts on human well-being, based on the capability approach from welfare economics. The core characteristic of this approach is that it uses changes in peoples' activities as a common metric for evaluating impacts on well-being.Impacts are assigned to one of five levels, from Minimal Concern to Massive, according to semi-quantitative scenarios that describe the severity of the impacts. Taxa are then classified according to the highest level of deleterious impact that they have been recorded to cause on any constituent of human well-being. The scheme also includes categories for taxa that are not evaluated, have no alien population, or are data deficient, and a method for assigning uncertainty to all the classifications. To demonstrate the utility of the system, we classified impacts of amphibians globally. These showed a variety of impacts on human well-being, with the cane toad (Rhinella marina) scoring Major impacts. For most species, however, no studies reporting impacts on human well-being were found, i.e. these species were data deficient.The classification provides a consistent procedure for translating the broad range of measures and types of impact into ranked levels of socio-economic impact, assigns alien taxa on the basis of the best available evidence of their documented deleterious impacts, and is applicable across taxa and at a range of spatial scales. The

Many recent studies in invasion science have identified species traits that determine either invasiveness or impact. Such analyses underpin risk assessments and attempts to prioritise management actions. However, the factors that mediate the capacity of an introduced species to establish and spread (i.e. its invasiveness) can differ from those that affect the nature and severity of impacts. Here we compare those traits correlated with invasiveness with those correlated with impact for Cactaceae (“cacti”) in South Africa. To assess impact magnitude, we scored 70 cacti (35 invasive and 35 non-invasive species) using the Generic Impact Scoring System (GISS) and identified traits correlated with impact using a decision tree approach. We then compared the traits correlated with impact with those identified in a recent study as correlated with invasiveness (i.e. native range size and growth form). We found that there is a significant correlation between native range size and both invasiveness and impact. Cacti with larger native ranges were more likely to become invasive (p=0.001) and cause substantial impacts (p=0.01). These results are important for prioritising efforts on the management of cactus species. Understanding when and why impact and invasiveness are correlated (as they appear to be for Cactaceae) is likely to be an important area of future research in risk assessment.

In a recent Discussion Paper, Hoffmann and Courchamp (2016) posed the question: are biological invasions and natural colonisations that different? This apparently simple question resonates at the core of the biological study of human-induced global change, and we strongly believe that the answer is yes: biological invasions and natural colonisations differ in processes and mechanisms in ways that are crucial for science, management, and policy. Invasion biology has, over time, developed into the broader transdisciplinary field of invasion science. At the heart of invasion science is the realisation that biological invasions are not just a biological phenomenon: the human dimension of invasions is a fundamental component in the social-ecological systems in which invasions need to be understood and managed.

Substantial progress has been made in understanding how pathways underlie and mediate biological invasions. However, key features of their role in invasions remain poorly understood, available knowledge is widely scattered, and major frontiers in research and management are insufficiently characterized. We review the state of the art, highlight recent advances, identify pitfalls and constraints, and discuss major challenges in four broad fields of pathway research and management: pathway classification, application of pathway information, management response, and management impact. We present approaches to describe and quantify pathway attributes (e.g., spatiotemporal changes, proxies of introduction effort, environmental and socioeconomic contexts) and how they interact with species traits and regional characteristics. We also provide recommendations for a research agenda with particular focus on emerging (or neglected) research questions and present new analytical tools in the context of pathway research and management.

Species moved by human activities beyond the limits of their native geographic ranges into areas in which they do not naturally occur (termed aliens) can cause a broad range of significant changes to recipient ecosystems; however, their impacts vary greatly across species and the ecosystems into which they are introduced. There is therefore a critical need for a standardised method to evaluate, compare, and eventually predict the magnitudes of these different impacts. Here, we propose a straightforward system for classifying alien species according to the magnitude of their environmental impacts, based on the mechanisms of impact used to code species in the International Union for Conservation of Nature (IUCN) Global Invasive Species Database, which are presented here for the first time. The classification system uses five semi-quantitative scenarios describing impacts under each mechanism to assign species to different levels of impact—ranging from Minimal to Massive—with assignment corresponding to the highest level of deleterious impact associated with any of the mechanisms. The scheme also includes categories for species that are Not Evaluated, have No Alien Population, or are Data Deficient, and a method for assigning uncertainty to all the classifications. We show how this classification system is applicable at different levels of ecological complexity and different spatial and temporal scales, and embraces existing impact metrics. In fact, the scheme is analogous to the already widely adopted and accepted Red List approach to categorising extinction risk, and so could conceivably be readily integrated with existing practices and policies in many regions

Aim? Many Australian Acacia species have been planted around the world, some are highly valued, some are invasive, and some are both highly valued and invasive. We review global efforts to minimize the risk and limit the impact of invasions in this widely used plant group. Location? Global. Methods? Using information from literature sources, knowledge and experience of the authors, and the responses from a questionnaire sent to experts around the world, we reviewed: (1) a generalized life cycle of Australian acacias and how to control each life stage, (2) different management approaches and (3) what is required to help limit or prevent invasions. Results? Relatively few Australian acacias have been introduced in large numbers, but all species with a long and extensive history of planting have become invasive somewhere. Australian acacias, as a group, have a high risk of becoming invasive and causing significant impacts as determined by existing assessment schemes. Moreover, in most situations, long-lived seed banks mean it is very difficult to control established infestations. Control has focused almost exclusively on widespread invaders, and eradication has rarely been attempted. Classical biological control is being used in South Africa with increasing success. Main conclusions? A greater emphasis on pro-active rather than reactive management is required given the difficulties managing established invasions of Australian acacias. Adverse effects of proposed new introductions can be minimized by conducting detailed risk assessments in advance, planning for on-going monitoring and management, and ensuring resources are in place for long-term mitigation. Benign alternatives (e.g. sterile hybrids) could be developed to replace existing utilized taxa. Eradication should be set as a management goal more often to reduce the invasion debt. Introducing classical biological control agents that have a successful track-record in South Africa to other regions and identifying n

Achieving data interoperability is a necessary element of realizing the United States Government's vision of interoperability across all the services. This paper describes an Extensible Markup Language (XML) approach that was invented to capture data structure, content, and semantics in a targeted military domain of space surveillance. The resulting Space Surveillance Ontology could become a standard, shared space surveillance vocabulary as a step toward achieving data interoperability for military space data across domains. The ontology was created using the World Wide Web Consortium (W3C) emerging standard called XML Schema., The original document contains color images. Project No. 03014000.

Objective: This paper aims to explore the role of factors pertaining to trust in real-world automation systems through the application of observational methods in a case study from the railway sector. Background: Trust in automation is widely acknowledged as an important mediator of automation use, but the majority of the research on automation trust is based on laboratory work. In contrast, this work explored trust in a real-world setting. Method: Experienced rail operators in four signalling centers were observed for 90 min, and their activities were coded into five mutually exclusive categories. Their observed activities were analyzed in relation to their reported trust levels, collected via a questionnaire. Results: The results showed clear differences in activity, even when circumstances on the workstations were very similar, and significant differences in some trust dimensions were found between groups exhibiting different levels of intervention and time not involved with signaling. Conclusion: Although the empirical, lab-based studies in the literature have consistently found that reliability and competence of the automation are the most important aspects of trust development, understanding of the automation emerged as the strongest dimension in this study. The implications are that development and maintenance of trust in real-world, safety-critical automation systems may be distinct from artificial laboratory automation. Application: The findings have important implications for emerging automation concepts in diverse industries including highly automated vehicles and Internet of things.

Alarm management is a key component of the successful operation of a prognostic or health-monitoring technology. Although alarms can alert the operator to critical information, false alarms and alarm flooding can cause major difficulties for successfully diagnosing and acting upon infrastructure faults. Human factors approaches seek to design more-effective alarm systems through a deep understanding of the contextual factors that influence alarm response, including strategies and heuristics used by operators. This paper presents an extensive analysis of alarm-handling activity in the setting of an Electrical Control Room on the rail network. The analysis is based on contextual observation, and the application of a time-stamped observation checklist. Functions, performance requirements, and general operating conditions that influence alarm handling are presented, delineating the typical operational constraints that need to be considered in the design and deployment of asset-based alarm systems. The analysis of specific alarm-handling incidents reveals the use of specific strategies that may bias operator performance. Implications for the design of health-monitoring systems are discussed.

The supervision of engineering work on the railways has received relatively little examination despite being both safety-critical in its own right and having wider implications for the successful running of the railways. The present paper is concerned with understanding the factors that make different engineering works perceived as easier or harder to manage. We describe an approach building on notions of ‘span of control’, through which we developed the TOECAP inventory (Team, Organisation, Environment, Communication, Activity and Personal). This tool was validated through both interviews and questionnaires. As well as identifying the physical factors involved, the work also emphasised the importance of collaborative and attitudinal factors. We conclude by discussing limitations of the present work and future directions for development.

This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity.

Objective: This paper aims to explore the role of factors pertaining to trust in real-world automation systems through the application of observational methods in a case study from the railway sector. Background: Trust in automation is widely acknowledged as an important mediator of automation use, but the majority of the research on automation trust is based on laboratory work. In contrast, this work explored trust in a real-world setting. Method: Experienced rail operators in four signalling centers were observed for 90 min, and their activities were coded into five mutually exclusive categories. Their observed activities were analyzed in relation to their reported trust levels, collected via a questionnaire. Results: The results showed clear differences in activity, even when circumstances on the workstations were very similar, and significant differences in some trust dimensions were found between groups exhibiting different levels of intervention and time not involved with signaling. Conclusion: Although the empirical, lab-based studies in the literature have consistently found that reliability and competence of the automation are the most important aspects of trust development, understanding of the automation emerged as the strongest dimension in this study. The implications are that development and maintenance of trust in real-world, safety-critical automation systems may be distinct from artificial laboratory automation. Application: The findings have important implications for emerging automation concepts in diverse industries including highly automated vehicles and Internet of things.

Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications.

Alarm management is a key component of the successful operation of a prognostic or health-monitoring technology. Although alarms can alert the operator to critical information, false alarms and alarm flooding can cause major difficulties for successfully diagnosing and acting upon infrastructure faults. Human factors approaches seek to design more-effective alarm systems through a deep understanding of the contextual factors that influence alarm response, including strategies and heuristics used by operators. This paper presents an extensive analysis of alarm-handling activity in the setting of an Electrical Control Room on the rail network. The analysis is based on contextual observation, and the application of a time-stamped observation checklist. Functions, performance requirements, and general operating conditions that influence alarm handling are presented, delineating the typical operational constraints that need to be considered in the design and deployment of asset-based alarm systems. The analysis of specific alarm-handling incidents reveals the use of specific strategies that may bias operator performance. Implications for the design of health-monitoring systems are discussed.

Objective: This paper aims to explore the role of factors pertaining to trust in real-world automation systems through the application of observational methods in a case study from the railway sector. Background: Trust in automation is widely acknowledged as an important mediator of automation use, but the majority of the research on automation trust is based on laboratory work. In contrast, this work explored trust in a real-world setting. Method: Experienced rail operators in four signalling centers were observed for 90 min, and their activities were coded into five mutually exclusive categories. Their observed activities were analyzed in relation to their reported trust levels, collected via a questionnaire. Results: The results showed clear differences in activity, even when circumstances on the workstations were very similar, and significant differences in some trust dimensions were found between groups exhibiting different levels of intervention and time not involved with signaling. Conclusion: Although the empirical, lab-based studies in the literature have consistently found that reliability and competence of the automation are the most important aspects of trust development, understanding of the automation emerged as the strongest dimension in this study. The implications are that development and maintenance of trust in real-world, safety-critical automation systems may be distinct from artificial laboratory automation. Application: The findings have important implications for emerging automation concepts in diverse industries including highly automated vehicles and Internet of things.

The supervision of engineering work on the railways has received relatively little examination despite being both safety-critical in its own right and having wider implications for the successful running of the railways. The present paper is concerned with understanding the factors that make different engineering works perceived as easier or harder to manage. We describe an approach building on notions of ‘span of control’, through which we developed the TOECAP inventory (Team, Organisation, Environment, Communication, Activity and Personal). This tool was validated through both interviews and questionnaires. As well as identifying the physical factors involved, the work also emphasised the importance of collaborative and attitudinal factors. We conclude by discussing limitations of the present work and future directions for development.

This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity.

This is a legal document dated March 15, 1849, in which John R. Wilson is donating some land to be used for a school and church, named the Washington Institute. He adds the condition that he be allowed water access for his livestock and that he be given free tuition for one student each session. He also adds another stipulation--that he be able to appoint his successor to the board of trustees.

This is a legal document dated March 15, 1849, in which John R. Wilson is donating some land to be used for a school and church, named the Washington Institute. He adds the condition that he be allowed water access for his livestock and that he be given free tuition for one student each session. He also adds another stipulation--that he be able to appoint his successor to the board of trustees.

Objective: This paper aims to explore the role of factors pertaining to trust in real-world automation systems through the application of observational methods in a case study from the railway sector. Background: Trust in automation is widely acknowledged as an important mediator of automation use, but the majority of the research on automation trust is based on laboratory work. In contrast, this work explored trust in a real-world setting. Method: Experienced rail operators in four signalling centers were observed for 90 min, and their activities were coded into five mutually exclusive categories. Their observed activities were analyzed in relation to their reported trust levels, collected via a questionnaire. Results: The results showed clear differences in activity, even when circumstances on the workstations were very similar, and significant differences in some trust dimensions were found between groups exhibiting different levels of intervention and time not involved with signaling. Conclusion: Although the empirical, lab-based studies in the literature have consistently found that reliability and competence of the automation are the most important aspects of trust development, understanding of the automation emerged as the strongest dimension in this study. The implications are that development and maintenance of trust in real-world, safety-critical automation systems may be distinct from artificial laboratory automation. Application: The findings have important implications for emerging automation concepts in diverse industries including highly automated vehicles and Internet of things.

Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications.

Alarm management is a key component of the successful operation of a prognostic or health-monitoring technology. Although alarms can alert the operator to critical information, false alarms and alarm flooding can cause major difficulties for successfully diagnosing and acting upon infrastructure faults. Human factors approaches seek to design more-effective alarm systems through a deep understanding of the contextual factors that influence alarm response, including strategies and heuristics used by operators. This paper presents an extensive analysis of alarm-handling activity in the setting of an Electrical Control Room on the rail network. The analysis is based on contextual observation, and the application of a time-stamped observation checklist. Functions, performance requirements, and general operating conditions that influence alarm handling are presented, delineating the typical operational constraints that need to be considered in the design and deployment of asset-based alarm systems. The analysis of specific alarm-handling incidents reveals the use of specific strategies that may bias operator performance. Implications for the design of health-monitoring systems are discussed.

The supervision of engineering work on the railways has received relatively little examination despite being both safety-critical in its own right and having wider implications for the successful running of the railways. The present paper is concerned with understanding the factors that make different engineering works perceived as easier or harder to manage. We describe an approach building on notions of ‘span of control’, through which we developed the TOECAP inventory (Team, Organisation, Environment, Communication, Activity and Personal). This tool was validated through both interviews and questionnaires. As well as identifying the physical factors involved, the work also emphasised the importance of collaborative and attitudinal factors. We conclude by discussing limitations of the present work and future directions for development.

This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity.

Objective: This paper aims to explore the role of factors pertaining to trust in real-world automation systems through the application of observational methods in a case study from the railway sector. Background: Trust in automation is widely acknowledged as an important mediator of automation use, but the majority of the research on automation trust is based on laboratory work. In contrast, this work explored trust in a real-world setting. Method: Experienced rail operators in four signalling centers were observed for 90 min, and their activities were coded into five mutually exclusive categories. Their observed activities were analyzed in relation to their reported trust levels, collected via a questionnaire. Results: The results showed clear differences in activity, even when circumstances on the workstations were very similar, and significant differences in some trust dimensions were found between groups exhibiting different levels of intervention and time not involved with signaling. Conclusion: Although the empirical, lab-based studies in the literature have consistently found that reliability and competence of the automation are the most important aspects of trust development, understanding of the automation emerged as the strongest dimension in this study. The implications are that development and maintenance of trust in real-world, safety-critical automation systems may be distinct from artificial laboratory automation. Application: The findings have important implications for emerging automation concepts in diverse industries including highly automated vehicles and Internet of things.

Macroecology is the study of patterns, and the processes that determine those patterns, in the distribution and abundance of organisms at large scales, whether they be spatial (from hundreds of kilometres to global), temporal (from decades to centuries), and organismal (numbers of species or higher taxa). In the context of invasion ecology, macroecological studies include, for example, analyses of the richness, diversity, distribution, and abundance of alien species in regional floras and faunas, spatio-temporal dynamics of alien species across regions, and cross- taxonomic analyses of species traits among comparable native and alien species pools. However, macroecological studies aiming to explain and predict plant and animal naturalisations and invasions, and the resulting impacts, have, to date, rarely considered the joint effects of species traits, environment, and socioeconomic characteristics. To address this, we present the MAcroecological Framework for Invasive Aliens (MAFIA). The MAFIA explains the invasion phenomenon using three interacting classes of factors – alien species traits, location characteristics, and factors related to introduction events – and explicitly maps these interactions onto the invasion sequence from transport to naturalisation to invasion. The framework therefore helps both to identify how anthropogenic effects interact with species traits and environmental characteristics to determine observed patterns in alien distribution, abundance, and richness; and to clarify why neglecting anthropogenic effects can generate spurious conclusions. Event-related factors include propagule pressure, colonisation pressure, and residence time that are important for mediating the outcome of invasion processes. However, because of context dependence, they can bias analyses, for example those that seek to elucidate the role of alien species traits. In the same vein, failure to recognise and explicitly incorporate interactions among the main factors impe

Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications.

Objective: This paper aims to explore the role of factors pertaining to trust in real-world automation systems through the application of observational methods in a case study from the railway sector. Background: Trust in automation is widely acknowledged as an important mediator of automation use, but the majority of the research on automation trust is based on laboratory work. In contrast, this work explored trust in a real-world setting. Method: Experienced rail operators in four signalling centers were observed for 90 min, and their activities were coded into five mutually exclusive categories. Their observed activities were analyzed in relation to their reported trust levels, collected via a questionnaire. Results: The results showed clear differences in activity, even when circumstances on the workstations were very similar, and significant differences in some trust dimensions were found between groups exhibiting different levels of intervention and time not involved with signaling. Conclusion: Although the empirical, lab-based studies in the literature have consistently found that reliability and competence of the automation are the most important aspects of trust development, understanding of the automation emerged as the strongest dimension in this study. The implications are that development and maintenance of trust in real-world, safety-critical automation systems may be distinct from artificial laboratory automation. Application: The findings have important implications for emerging automation concepts in diverse industries including highly automated vehicles and Internet of things.

Alarm management is a key component of the successful operation of a prognostic or health-monitoring technology. Although alarms can alert the operator to critical information, false alarms and alarm flooding can cause major difficulties for successfully diagnosing and acting upon infrastructure faults. Human factors approaches seek to design more-effective alarm systems through a deep understanding of the contextual factors that influence alarm response, including strategies and heuristics used by operators. This paper presents an extensive analysis of alarm-handling activity in the setting of an Electrical Control Room on the rail network. The analysis is based on contextual observation, and the application of a time-stamped observation checklist. Functions, performance requirements, and general operating conditions that influence alarm handling are presented, delineating the typical operational constraints that need to be considered in the design and deployment of asset-based alarm systems. The analysis of specific alarm-handling incidents reveals the use of specific strategies that may bias operator performance. Implications for the design of health-monitoring systems are discussed.

The supervision of engineering work on the railways has received relatively little examination despite being both safety-critical in its own right and having wider implications for the successful running of the railways. The present paper is concerned with understanding the factors that make different engineering works perceived as easier or harder to manage. We describe an approach building on notions of ‘span of control’, through which we developed the TOECAP inventory (Team, Organisation, Environment, Communication, Activity and Personal). This tool was validated through both interviews and questionnaires. As well as identifying the physical factors involved, the work also emphasised the importance of collaborative and attitudinal factors. We conclude by discussing limitations of the present work and future directions for development.

Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications.

This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity.

Alarm management is a key component of the successful operation of a prognostic or health-monitoring technology. Although alarms can alert the operator to critical information, false alarms and alarm flooding can cause major difficulties for successfully diagnosing and acting upon infrastructure faults. Human factors approaches seek to design more-effective alarm systems through a deep understanding of the contextual factors that influence alarm response, including strategies and heuristics used by operators. This paper presents an extensive analysis of alarm-handling activity in the setting of an Electrical Control Room on the rail network. The analysis is based on contextual observation, and the application of a time-stamped observation checklist. Functions, performance requirements, and general operating conditions that influence alarm handling are presented, delineating the typical operational constraints that need to be considered in the design and deployment of asset-based alarm systems. The analysis of specific alarm-handling incidents reveals the use of specific strategies that may bias operator performance. Implications for the design of health-monitoring systems are discussed.

The supervision of engineering work on the railways has received relatively little examination despite being both safety-critical in its own right and having wider implications for the successful running of the railways. The present paper is concerned with understanding the factors that make different engineering works perceived as easier or harder to manage. We describe an approach building on notions of ‘span of control’, through which we developed the TOECAP inventory (Team, Organisation, Environment, Communication, Activity and Personal). This tool was validated through both interviews and questionnaires. As well as identifying the physical factors involved, the work also emphasised the importance of collaborative and attitudinal factors. We conclude by discussing limitations of the present work and future directions for development.

This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity.