Valuing adaptation under rapid change

AbstractThe methods used to plan adaptation to climate change have been heavily influenced by scientific narratives of gradual change and economic narratives of marginal adjustments to that change. An investigation of the theoretical aspects of how the climate changes suggests that scientific narratives of climate change are socially constructed, biasing scientific narratives to descriptions of gradual as opposed rapid, non-linear change. Evidence of widespread step changes in recent climate records and in model projections of future climate is being overlooked because of this. Step-wise climate change has the potential to produce rapid increases in extreme events that can cross institutional, geographical and sectoral domains.Likewise, orthodox economics is not well suited to the deep uncertainty faced under climate change, requiring a multi-faceted approach to adaptation. The presence of tangible and intangible values range across five adaptation clusters: goods; services; capital assets and infrastructure; social assets and infrastructure; and natural assets and infrastructure. Standard economic methods have difficulty in giving adequate weight to the different types of values across these clusters. They also do not account well for the inter-connectedness of impacts and subsequent responses between agents in the economy. As a result, many highly-valued aspects of human and environmental capital are being overlooked.Recent extreme events are already pressuring areas of public policy, and national strategies for emergency response and disaster risk reduction are being developed as a consequence. However, the potential for an escalation of total damage costs due to rapid change requires a coordinated approach at the institutional level, involving all levels of government, the private sector and civil society.One of the largest risks of maladaptation is the potential for un-owned risks, as risks propagate across domains and responsibility for their management is poorly allocated between public and private interests, and between the roles of the individual and civil society. Economic strategies developed by the disaster community for disaster response and risk reduction provide a base to work from, but many gaps remain.We have developed a framework for valuing adaptation that has the following aspects: the valuation of impacts thus estimating values at risk, the evaluation of different adaptation options and strategies based on cost, and the valuation of benefits expressed as a combination of the benefits of avoided damages and a range of institutional values such as equity, justice, sustainability and profit.The choice of economic methods and tools used to assess adaptation depends largely on the ability to constrain uncertainty around problems (predictive uncertainty) and solutions (outcome uncertainty). Orthodox methods can be used where both are constrained, portfolio methodologies where problems are constrained and robust methodologies where solutions are constrained. Where both are unconstrained, process-based methods utilising innovation methods and adaptive management are most suitable. All methods should involve stakeholders where possible.Innovative processes methods that enable transformation will be required in some circumstances, to allow institutions, sectors and communities to prepare for anticipated major change.Please cite this report as: Jones, RN, Young, CK, Handmer, J, Keating, A, Mekala, GD, Sheehan, P 2013 Valuing adaptation under rapid change, National Climate Change Adaptation Research Facility, Gold Coast, pp. 192.The methods used to plan adaptation to climate change have been heavily influenced by scientific narratives of gradual change and economic narratives of marginal adjustments to that change. An investigation of the theoretical aspects of how the climate changes suggests that scientific narratives of climate change are socially constructed, biasing scientific narratives to descriptions of gradual as opposed rapid, non-linear change. Evidence of widespread step changes in recent climate records and in model projections of future climate is being overlooked because of this. Step-wise climate change has the potential to produce rapid increases in extreme events that can cross institutional, geographical and sectoral domains.Likewise, orthodox economics is not well suited to the deep uncertainty faced under climate change, requiring a multi-faceted approach to adaptation. The presence of tangible and intangible values range across five adaptation clusters: goods; services; capital assets and infrastructure; social assets and infrastructure; and natural assets and infrastructure. Standard economic methods have difficulty in giving adequate weight to the different types of values across these clusters. They also do not account well for the inter-connectedness of impacts and subsequent responses between agents in the economy. As a result, many highly-valued aspects of human and environmental capital are being overlooked.Recent extreme events are already pressuring areas of public policy, and national strategies for emergency response and disaster risk reduction are being developed as a consequence. However, the potential for an escalation of total damage costs due to rapid change requires a coordinated approach at the institutional level, involving all levels of government, the private sector and civil society.One of the largest risks of maladaptation is the potential for un-owned risks, as risks propagate across domains and responsibility for their management is poorly allocated between public and private interests, and between the roles of the individual and civil society. Economic strategies developed by the disaster community for disaster response and risk reduction provide a base to work from, but many gaps remain.We have developed a framework for valuing adaptation that has the following aspects: the valuation of impacts thus estimating values at risk, the evaluation of different adaptation options and strategies based on cost, and the valuation of benefits expressed as a combination of the benefits of avoided damages and a range of institutional values such as equity, justice, sustainability and profit.The choice of economic methods and tools used to assess adaptation depends largely on the ability to constrain uncertainty around problems (predictive uncertainty) and solutions (outcome uncertainty). Orthodox methods can be used where both are constrained, portfolio methodologies where problems are constrained and robust methodologies where solutions are constrained. Where both are unconstrained, process-based methods utilising innovation methods and adaptive management are most suitable. All methods should involve stakeholders where possible.Innovative processes methods that enable transformation will be required in some circumstances, to allow institutions, sectors and communities to prepare for anticipated major change

Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System

Peer reviewedPublisher PD

Methods for anticipating governance breakdown and violent conflict

In this paper, authors Sarah Bressan, Håvard Mokleiv Nygård, and Dominic Seefeldt present the evolution and state of the art of both quantitative forecasting and scenario-based foresight methods that can be applied to help prevent governance breakdown and violent conflict in Europe’s neighbourhood. In the quantitative section, they describe the different phases of conflict forecasting in political science and outline which methodological gaps EU-LISTCO’s quantitative sub-national prediction tool will address to forecast tipping points for violent conflict and governance breakdown. The qualitative section explains EU-LISTCO’s scenario-based foresight methodology for identifying potential tipping points. After comparing both approaches, the authors discuss opportunities for methodological advancements across the boundaries of quantitative forecasting and scenario-based foresight, as well as how they can inform the design of strategic policy options

Extremely cold and hot temperatures increase the risk of ischaemic heart disease mortality: epidemiological evidence from China.

OBJECTIVE: To examine the effects of extremely cold and hot temperatures on ischaemic heart disease (IHD) mortality in five cities (Beijing, Tianjin, Shanghai, Wuhan and Guangzhou) in China; and to examine the time relationships between cold and hot temperatures and IHD mortality for each city. DESIGN: A negative binomial regression model combined with a distributed lag non-linear model was used to examine city-specific temperature effects on IHD mortality up to 20 lag days. A meta-analysis was used to pool the cold effects and hot effects across the five cities. PATIENTS: 16 559 IHD deaths were monitored by a sentinel surveillance system in five cities during 2004-2008. RESULTS: The relationships between temperature and IHD mortality were non-linear in all five cities. The minimum-mortality temperatures in northern cities were lower than in southern cities. In Beijing, Tianjin and Guangzhou, the effects of extremely cold temperatures were delayed, while Shanghai and Wuhan had immediate cold effects. The effects of extremely hot temperatures appeared immediately in all the cities except Wuhan. Meta-analysis showed that IHD mortality increased 48% at the 1st percentile of temperature (extremely cold temperature) compared with the 10th percentile, while IHD mortality increased 18% at the 99th percentile of temperature (extremely hot temperature) compared with the 90th percentile. CONCLUSIONS: Results indicate that both extremely cold and hot temperatures increase IHD mortality in China. Each city has its characteristics of heat effects on IHD mortality. The policy for response to climate change should consider local climate-IHD mortality relationships

Applying probabilistic temporal and multi-site data quality control methods to a public health mortality registry in Spain: A systematic approach to quality control of repositories

OBJECTIVE: To assess the variability in data distributions among data sources and over time through a case study of a large multisite repository as a systematic approach to data quality (DQ). MATERIALS AND METHODS: Novel probabilistic DQ control methods based on information theory and geometry are applied to the Public Health Mortality Registry of the Region of Valencia, Spain, with 512 143 entries from 2000 to 2012, disaggregated into 24 health departments. The methods provide DQ metrics and exploratory visualizations for (1) assessing the variability among multiple sources and (2) monitoring and exploring changes with time. The methods are suited to big data and multitype, multivariate, and multimodal data. RESULTS: The repository was partitioned into 2 probabilistically separated temporal subgroups following a change in the Spanish National Death Certificate in 2009. Punctual temporal anomalies were noticed due to a punctual increment in the missing data, along with outlying and clustered health departments due to differences in populations or in practices. DISCUSSION: Changes in protocols, differences in populations, biased practices, or other systematic DQ problems affected data variability. Even if semantic and integration aspects are addressed in data sharing infrastructures, probabilistic variability may still be present. Solutions include fixing or excluding data and analyzing different sites or time periods separately. A systematic approach to assessing temporal and multisite variability is proposed. CONCLUSION: Multisite and temporal variability in data distributions affects DQ, hindering data reuse, and an assessment of such variability should be a part of systematic DQ procedures.This work was supported by the Spanish Ministry of Economy and Competitiveness grant numbers RTC-2014-1530-1 and TIN-2013-43457-R, and by the Universitat Politecnica de Valencia grant number SP20141432.Sáez Silvestre, C.; Zurriaga, O.; Pérez-Panadés, J.; Melchor, I.; Robles Viejo, M.; García Gómez, JM. (2016). Applying probabilistic temporal and multi-site data quality control methods to a public health mortality registry in Spain: A systematic approach to quality control of repositories. Journal of the American Medical Informatics Association. 23(6):1085-1095. https://doi.org/10.1093/jamia/ocw010S1085109523

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope

Evolution of security engineering artifacts: a state of the art survey

Security is an important quality aspect of modern open software systems. However, it is challenging to keep such systems secure because of evolution. Security evolution can only be managed adequately if it is considered for all artifacts throughout the software development lifecycle. This article provides state of the art on the evolution of security engineering artifacts. The article covers the state of the art on evolution of security requirements, security architectures, secure code, security tests, security models, and security risks as well as security monitoring. For each of these artifacts the authors give an overview of evolution and security aspects and discuss the state of the art on its security evolution in detail. Based on this comprehensive survey, they summarize key issues and discuss directions of future research