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Stability of Surrogate MCDA Weights Under Different Assumptions on Value Distributions
No full textThis article studies the effects of sampling the alternative values from different distributions when studying the performance of surrogate weight methods in the additive model in multi-criteria decision analysis. The aim is to demonstrate surrogate weights' performance invariance regarding underlying actual distributions. Multiple distributions are characterised and examined through extensive simulation to evaluate their influence on the efficacy of surrogate weight approaches. It was found that employing the presently accepted standard distributions for alternative values led to outcomes from the surrogate weight methods that were remarkably consistent, barring a few notable deviations—-suggesting considerable robustness. In contrast, drawing samples from more extreme distributions resulted in greater divergence. Overall, the observed patterns of the surrogate weight approaches align, to a substantial degree, with findings reported in prior research. We conclude that the performance of the surrogate weight methods is generally stable under a wide variety of reasonable alternative value distributions and show a case when the distribution is too skewed
Climate change and health: the next challenge of ethical AI
Get PDFArtificial intelligence (AI) is one of the world's most resource-intensive digital technologies, but the environmental impact of AI on health remains largely unaddressed in both global health and bioethics. Effects on the environment have, thus far, been understood as a subsidiary consideration in AI ethics and rarely considered as a key ethical concern. AI technologies exacerbate climate change and sociopolitical instability due to their intensive use of natural resources and energy resources linked to the training and deployment of algorithmic systems. In global health, this intensive resource use is particularly concerning, given the explicit emphasis on improving health and advancing equity across the world. To address this, we interrogate how the inclusion of AI's environmental impact necessarily reshapes established ethical commitments in AI ethics frameworks and propose concrete strategies for accountability in the area of global health. This approach includes building a culture of intentional AI, for example through improved reporting, auditing, and intranational cooperation, in order to better align AI development and AI ethics with critical climate goals
Thermodynamic exploration of the adaptive cycle
No full textThe adaptive cycle was proposed by Holling in 1985 to explain macroscale patterns and processes of ecosystem dynamics. According to this qualitative model, ecological succession progresses through four stages: 1) exploitation, 2) conservation, 3) collapse, and 4) renewal. Since introducing the adaptive cycle, many efforts have been made to improve, quantify, and expand the application of this model. In this paper, we developed a new thermodynamic model aligned with the four stages of the adaptive cycle. However, in contrast to the classic adaptive cycle, the present model provides a clear, quantified, thermodynamic definition of each stage by specifically considering the rates of entropy and energy production, consumption, and exportation. According to this model, steady state occurs when the entropy production rate and energy consumption rate of living organisms are balanced with the entropy exportation rate and gross primary production of the ecosystem. The growth-oriented exploitation stage (1) requires a positive energy balance and a negative entropy balance. When both energy and entropy balances are negative, the ecosystem enters the conservation phase. If the energy balance is negative and the entropy balance is positive, then the system will collapse (3). Finally, when both entropy and energy balance are positive, new subsystems will emerge and adapt to continue a path of exploration and a new cycle of succession (4). Since this work is based on pure theoretical thermodynamics, these four stages of growth and development may apply to any complex adaptive system
An evolving Coupled Model Intercomparison Project phase 7 (CMIP7) and Fast Track in support of future climate assessment
No full textThe Coupled Model Intercomparison Project (CMIP) coordinates community-based efforts to answer key and timely climate science questions, facilitate delivery of relevant multi-model simulations through shared infrastructure, and support national and international climate assessments. Generations of CMIP have evolved through extensive community engagement from punctuated phasing into more continuous support for the design of experimental protocols, infrastructure for data publication and access, and public delivery of climate information. We identify four fundamental research questions motivating a seventh phase of coupled model intercomparison relating to patterns of sea surface temperature change, changing weather, the water–carbon–climate nexus, and tipping points. Key CMIP7 advances include an expansion of baseline experiments, a focus on CO2-emissions-driven experiments, sustained support for community MIPs, periodic updating of historical forcings and diagnostics requests, and a collection of prioritized experiments, or the “Assessment Fast Track”, drawn from community MIPs to support climate research, assessment, and service goals across prediction and projection, characterization, attribution, and process understanding
Just the two of us: presence of a second species of non-native gecko of the genus Hemidactylus Goldfuss, 1820 (Squamata: Gekkonidae) confirmed on Saint Helena
No full textHemidactylus mabouia (Moreau de Jonnès, 1818) is recorded for the first time from the remote island of Saint Helena, based on a specimen observed by one of the coauthors and several further photographic records verified from the citizen science platform iNaturalist. Comparison is made with the well-established and widespread Hemidactylus frenatus Duméril & Bibron, 1836 which was hitherto the only established gecko known from Saint Helena. Notes on reptiles on the neighbouring Ascension Island, especially its geckos, are provided
A toolbox to deal with misinformation in disaster risk management
No full textMisinformation significantly challenges disaster risk management by increasing risks and complicating response efforts. This technical note introduces a methodology toolbox designed to help policy makers, decision makers, practitioners, and scientists systematically assess, prevent, and mitigate the risks and impacts of misinformation in disaster scenarios. The methodology consists of eight steps, each offering specific tools and strategies to help address misinformation effectively. The process begins with defining the communication context using PESTEL analysis and Berlo’s communication model to assess external factors and information flow. It then focuses on identifying misinformation patterns through data collection and analysis using advanced AI methods. The impact of misinformation on risk perceptions is assessed through established theoretical frameworks, guiding the development of targeted strategies. The methodology includes practical measures for mitigating misinformation, such as implementing AI tools for prebunking and debunking false information. Evaluating the effectiveness of these measures is crucial, and continuous monitoring is recommended to adapt strategies in real-time. Ethical considerations are outlined to ensure compliance with international laws and data privacy regulations. The final step emphasizes managerial aspects, including clear communication and public education, to build trust and promote reliable information sources. This structured approach provides practical insights for enhancing disaster response and reducing the risks associated with misinformation
The 2025 report of the Lancet Countdown on health and climate change: climate change action offers a lifeline
No full textEducational differentials in cohort fertility rates across Indian macro-regions: A study of cohorts born between 1945–1949 and 1975–1979
No full textWomen’s education is among the significant factors contributing to the reduction in fertility rates in developing countries. India has experienced a rapid decline in total fertility rates and significant improvements in women’s educational attainment over the past several decades. However, little is known about the cohort-specific implications of educational expansion on fertility decline in India. Thus, this study aimed to elucidate the pattern of fertility differentials based on education level and assess the contribution of changes in women’s educational attainment to the fertility decline across different cohorts in India. Education-based differences in cohort fertility rates (CFRs) were analysed among the birth cohorts of 1945–1949 to 1975–1979, utilising data from five rounds of the Indian National Family Health Survey conducted between 1992–1993 and 2019–2021. Demographic decomposition methods were employed to examine the contribution of changes in women’s educational composition to fertility decline. The results suggest that the differences in fertility based on educational attainment have gradually declined over birth cohorts. The decomposition results show that the composition changes in women’s education contributed to approximately one-fifth of the decline in CFRs in India. However, within urban and rural areas of Indian macro-regions, the composition changes in women’s education were minimal. Uneducated women were the primary driver of CFR decline across social groups and macro-regions. Thus, the role of education in fertility decline lies more in the diffusion of reproductive behaviours, which has contributed to reducing fertility differentials across social strata
MERCURY: A Fast and Versatile Multi‐Resolution Based Global Emulator of Compound Climate Hazards
No full textHigh-impact climate damages are often driven by compounding conditions, such as elevated heat stress arising from combined high humidity and temperatures. To explore future changes in compounding hazards under several climate scenarios, climate emulators can provide light-weight, data-driven complements to Earth System Models (ESMs). Yet, only a few existing emulators jointly emulate multiple climate variables. We introduce MERCURY (Multi-resolution EmulatoR for CompoUnd climate Risk analYsis), a spatio-temporal, multi-resolution emulator designed for compound climate risk analysis. MERCURY employs image-compression-based techniques for memory-efficient emulation and consists of two main modules. The regional module represents the monthly, regional response of a given variable to yearly Global Mean Temperature using a probabilistic additive model, resolving regional cross-correlations. The resulting regional values are then jointly disaggregated to grid-cell level values using a lifting-scheme operator, founded on principles of Discrete Wavelet Transforms. We demonstrate MERCURY on the humid-heat metric, wet bulb globe temperature (WBGT), as derived from temperature and relative humidity emulations. The emulated WBGT spatial correlations correspond well to those of ESMs and the 95 and 97.5 quantiles of WBGT distributions are well captured, with an average of 5 deviation. MERCURY's setup allows for region-specific emulations from which one can efficiently "zoom" into the grid-cell level across multiple variables by means of the reverse lifting-scheme operator. This circumvents the traditional problem of having to emulate complete, global-fields of climate data and resulting storage requirements