Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability

The integrated - environmental, economic and social - analysis of climate change calls for a paradigm shift as it is fundamentally a problem of complex, bottom-up and multi-agent human behaviour. There is a growing awareness that global environmental change dynamics and the related socio-economic implications involve a degree of complexity that requires an innovative modelling of combined social and ecological systems. Climate change policy can no longer be addressed separately from a broader context of adaptation and sustainability strategies. A vast body of literature on agent-based modelling (ABM) shows its potential to couple social and environmental models, to incorporate the influence of micro-level decision making in the system dynamics and to study the emergence of collective responses to policies. However, there are few publications which concretely apply this methodology to the study of climate change related issues. The analysis of the state of the art reported in this paper supports the idea that today ABM is an appropriate methodology for the bottom-up exploration of climate policies, especially because it can take into account adaptive behaviour and heterogeneity of the system's components.Review, Agent-Based Modelling, Socio-Ecosystems, Climate Change, Adaptation, Complexity.

A Spatial Agent-Based Model to Explore Scenarios of Adaptation to Climate Change in an Alpine Tourism Destination

A vast body of literature suggests that the European Alpine region may be one of the most sensitive to climate change impacts. Adaptation to climate change of Alpine socio-ecosystems is increasingly becoming an issue of interest for the scientific community while the people of the Alps are often unaware of or simply ignore the problem. ClimAlpTour is a European research project of the Alpine Space Programme, bringing together institutions and scholars from all countries of the Alpine arch, in view of dealing with the expected decrease in snow and ice cover, which may lead to a rethinking of tourism development beyond the traditional vision of winter sports. The research reported herein analyses the municipality of Auronzo di Cadore (22,000 ha) in the Dolomites under the famous peaks of the “Tre Cime di Lavaredo”. The local economy depends on tourism which is currently focused on the summer season, while the winter season is weak. As a whole, the destination receives approximately 65,000 guests per year with a resident population of 3,600 inhabitants. Since recently the Community Council is considering options on how to stimulate a further development of the winter tourism. This paper refers to a prototype agent-based model, called AuronzoWinSim, for the assessment of alternative scenarios of future local development strategies, taking into account complex spatial and social dynamics and interactions. Different typologies of winter tourists compose the set of human agents. Climate change scenarios are used to produce temperature and snow cover projections. The model is mainly informed by secondary sources, including demographic and economic time series, and biophysical data which feed-in its spatial dimension. Primary data from field surveys are used to calibrate the main parameters. AuronzoWinSim is planned for use in a participatory context with groups of local stakeholders.Alpine Winter Tourism, Spatial Agent-Based Model, Climate Change Adaptation

The economics of hydro-meteorological disasters: approaching the estimation of the total costs

21 p.Hydro-meteorological disasters have caused increasing losses in recent years. Efficient risk reduction policies require accurate assessment approaches, with careful consideration of costs, beyond direct tangible costs, which are commonly used in practice. Faced with possible risk reduction scenarios, limited financial resources require an improvement in the quality of cost estimation, thereby contributing to an efficient allocation of resources. This paper focuses on the concept of total costs of hydro-meteorological disasters, based on direct and indirect as well as tangible and intangible cost categories. These categories are defined and explained, supported by a comprehensive review of economic valuation methods. Based on this information, practice relevant suggestions are made concerning the most appropriate methods for different cases in terms of scale, availability of data and of technical resources. Our survey also provides critical insights to drawbacks of flood risk estimation, which need to be addressed and carefully dealt with in any future research in this area

Bacterial–viral load and the immune response in stable and exacerbated COPD: Significance and therapeutic prospects

Chronic obstructive pulmonary disease (COPD) is characterized by persistent airflow limitation and an abnormal inflammatory response of the lung. Bacteria and viruses are a major cause of COPD exacerbations and may contribute to COPD progression by perpetuating the inflammatory response in the airways. Bacterial variety diminishes with increasing COPD severity. Respiratory viruses can colonize the lower respiratory tract in stable COPD, altering the respiratory microbiome and facilitating secondary bacterial infections. In this review, we present the most updated information about the role of bacteria and viruses in stable and exacerbated COPD. In our opinion, to optimize therapeutic strategies, the dynamic events involving bacterial–viral infections and related immune response in COPD phenotypes need to be better clarified. Our paper would address these points that we consider of great importance for the clinical management of COPD

The economics of hydro-meteorological disasters: approaching the estimation of the total costs

21 p.Hydro-meteorological disasters have caused increasing losses in recent years. Efficient risk reduction policies require accurate assessment approaches, with careful consideration of costs, beyond direct tangible costs, which are commonly used in practice. Faced with possible risk reduction scenarios, limited financial resources require an improvement in the quality of cost estimation, thereby contributing to an efficient allocation of resources. This paper focuses on the concept of total costs of hydro-meteorological disasters, based on direct and indirect as well as tangible and intangible cost categories. These categories are defined and explained, supported by a comprehensive review of economic valuation methods. Based on this information, practice relevant suggestions are made concerning the most appropriate methods for different cases in terms of scale, availability of data and of technical resources. Our survey also provides critical insights to drawbacks of flood risk estimation, which need to be addressed and carefully dealt with in any future research in this area

Bayesian approach to SETI

The search for technosignatures from hypothetical galactic civilizations is going through a new phase of intense activity. For the first time, a significant fraction of the vast search space is expected to be sampled in the foreseeable future, potentially bringing informative data about the abundance of detectable extraterrestrial civilizations, or the lack thereof. Starting from the current state of ignorance about the galactic population of non-natural electromagnetic signals, we formulate a Bayesian statistical model to infer the mean number of radio signals crossing Earth, assuming either non-detection or the detection of signals in future surveys of the Galaxy. Under fairly noninformative priors, we find that not detecting signals within about $1$ kly from Earth, while suggesting the lack of galactic emitters or at best the scarcity thereof, is nonetheless still consistent with a probability exceeding $10$ \% that typically over $\sim 100$ signals could be crossing Earth, with radiated power analogous to that of the Arecibo radar, but coming from farther in the Milky Way. The existence in the Galaxy of potentially detectable Arecibo-like emitters can be reasonably ruled out only if all-sky surveys detect no such signals up to a radius of about $40$ kly, an endeavor requiring detector sensitivities thousands times higher than those of current telescopes. Conversely, finding even one Arecibo-like signal within $\sim 1000$ light years, a possibility within reach of current detectors, implies almost certainly that typically more than $\sim 100$ signals of comparable radiated power cross the Earth, yet to be discovered.Comment: Published in PNAS ahead of print October 1, 2018. Preprint has 13 pages, 7 figures + 7 pages of Supplementary Information with 5 figure

The global environmental agenda urgently needs a semantic web of knowledge

Progress in key social-ecological challenges of the global environmental agenda (e.g., climate change, biodiversity conservation, Sustainable Development Goals) is hampered by a lack of integration and synthesis of existing scientific evidence. Facing a fast-increasing volume of data, information remains compartmentalized to pre-defined scales and fields, rarely building its way up to collective knowledge. Today's distributed corpus of human intelligence, including the scientific publication system, cannot be exploited with the efficiency needed to meet current evidence synthesis challenges; computer-based intelligence could assist this task. Artificial Intelligence (AI)-based approaches underlain by semantics and machine reasoning offer a constructive way forward, but depend on greater understanding of these technologies by the science and policy communities and coordination of their use. By labelling web-based scientific information to become readable by both humans and computers, machines can search, organize, reuse, combine and synthesize information quickly and in novel ways. Modern open science infrastructure-i.e., public data and model repositories-is a useful starting point, but without shared semantics and common standards for machine actionable data and models, our collective ability to build, grow, and share a collective knowledge base will remain limited. The application of semantic and machine reasoning technologies by a broad community of scientists and decision makers will favour open synthesis to contribute and reuse knowledge and apply it toward decision making

Relationship between the night shift work and thyroid disorders: A systematic review and meta-analysis

AbstractObjectives. The night shift workers were reported to have health consequences, ranging from mild, as cluster headache, to severe, as heart attacks and hormonal irregularities. This study is aimed to perform a systematic review and meta-analyze of the association between the night shift work and the thyroid disorders.Methods. We comprehensively searched eight databases, including PubMed and Google Scholar for the relevant articles. This systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement.Results. We finally included six papers involving 4074 participants. Four papers were eligible for meta-analysis involving 1864 night shift workers and 2017 day shift workers. We against found that thyroid stimulating hormone (TSH) is significantly higher in the night shift group compared to the day shift group.Conclusions. The higher TSH among the night shift workers is attributed to disruption of the circadian rhythm and sleep/wake cycle, with subsequent eating disorders. We proposed that more attention should be paid to the working pattern and the related health consequences