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Efficient Weight Ranking in Multi-Criteria Decision Support Systems
Get PDFThere are well-known issues in conjunction with eliciting probabilities, utilities, and criteria weights in real-life decision analysis. This article explores various computationally efficient methods for generating weights in multi-criteria decision support systems. Therefore, it constitutes an aid for MCDA modellers and tool designers in selecting surrogate methods for criteria weights. Given the challenges in eliciting precise criteria weights from decision-makers, this study evaluates a range of techniques for automatically generating surrogate weights, focusing on both ordinal and cardinal ranking approaches. With a thorough inquiry methodology never before used, we examine automatic multi-criteria weight-generating algorithms in this article. The methods tested include traditional rank-based models such as rank sum (RS), rank reciprocal (RR), and rank order centroid (ROC), alongside newer approaches like the sum reciprocal (SR) and cardinal sum reciprocal (CSR). The results show that the SR approach for the ordinal case and the CSR method for the cardinal case perform better in terms of robustness than other methods, even including the promising new geometric class of methods. It is also shown that linear programming (LP) performs poorly when compared to surrogate weight models. Additionally, as expected, the cardinal models perform better than the ordinal models. Unexpectedly, though, the well-established LP model’s performance is worse than previously thought
Measuring global migration flows using online data
Get PDFExisting estimates of human migration are limited in their scope, reliability, and timeliness, prompting the United Nations and the Global Compact on Migration to call for improved data collection. Using privacy protected records from three billion Facebook users, we estimate country-to-country migration flows at monthly granularity for 181 countries, accounting for selection into Facebook usage. Our estimates closely match high-quality measures of migration where available but can be produced nearly worldwide and with less delay than alternative methods. We estimate that 39.1 million people migrated internationally in 2022 (0.63% of the population of the countries in our sample). Migration flows significantly changed during the COVID-19 pandemic, decreasing by 64% before rebounding in 2022 to a pace 24% above the precrisis rate. We also find that migration from Ukraine increased tenfold in the wake of the Russian invasion. To support research and policy interventions, we release these estimates publicly through the Humanitarian Data Exchange
Policy Brief No.102: Inclusive Climate Adaptation in Central Asia: Strengthening Participatory Governance for Resilience
Get PDFCentral Asia’s climate adaptation strategies increasingly emphasize the need for inclusive participation, with national frameworks engaging government bodies, civil society, academic institutions, and local communities to enhance resilience against climate risks. While progress is evident in capacity-building and multi-level stakeholder involvement, the reliance on periodic consultations such as roundtables and workshops highlights a critical gap in establishing continuous, structured feedback loops. This shortfall limits the ability to systematically integrate local knowledge and address the unique challenges faced by vulnerable groups. Strengthening participatory governance through formalized feedback mechanisms and targeted outreach is therefore essential for improving transparency, responsiveness, and the overall effectiveness of adaptation measures across the region
Biodiversity citizen science with farmers and communities: Engagement activities and materials for Farmer Clusters
Get PDFAging and age selectivity: Exploring differences across time and space
No full textThis paper uses the methodology of the Characteristics Approach to the study of population aging to produce a framework in which population aging is consistently measured from both a cross-sectional and longitudinal perspective. To do this, it introduces the Retrospective Survival Age Threshold (RSAT) to complement the existing Prospective Old-Age Threshold (POAT). The Prospective Old-Age Threshold (POAT) is the forward-looking age at which remaining life expectancy is 15 years. The Retrospective Survival Age Threshold (RSAT) is a backward-looking age reflecting the age by which 79 % of adults (20 + ) have survived. These complementary thresholds, when used together, illuminate variations in trajectories of aging across different mortality regimes. Drawing on national and global data, we show that some countries exhibit parallel movement of POAT and RSAT (implying the expansion of the survival curve), while others display divergent trends linked to shifts in midlife mortality (often implying compression of the survival curve). Our results underscore how combining forward-looking and backward-looking ages can provide richer insights into aging processes than using chronological age alone
Effect of climate on traits of dominant and rare tree species in the world’s forests
Get PDFSpecies’ traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly
The nature-based solution implementation gap: A review of nature-based solution governance barriers and enablers
Get PDFNature-based solutions (NbS) represent a critical umbrella concept encompassing measures that employ nature's properties to systemically address societal challenges, potentially providing benefits for biodiversity, climate and people. NbS are accordingly emerging on an ever-expanding number of policy agendas, such as the Kunming-Montreal Global Biodiversity Framework and multiple European Union strategies. However, despite this increasing political traction, NbS implementation (that is, the design, planning, construction, monitoring and maintenance of NbS) remains fragmented and is often too context-specific for their wider upscaling and mainstreaming, creating an 'NbS implementation gap' between ambitions and on-the-ground operationalization. Based on a systematic review of grey- and peer-reviewed literature and workshop results (N = 34), we identify and discuss the institutional, legal, regulatory, social and economic enablers (N = 301) and barriers (N = 307) to NbS implementation. Our results highlight the governance factors that currently facilitate or limit NbS implementation and mainstreaming, which are often homologous. These include inclusive stakeholder engagement processes and true co-design; an evidence base on NbS performance and their co-benefits, including quantitative cost-benefit analyses; the existence of or lack of knowledge products and NbS-specific expertise; and available funds earmarked for NbS. We find that polycentric governance arrangements may act as a critical enabler for NbS implementation, yet path dependencies significantly limit NbS by still favouring grey alternatives. By providing an overview of NbS implementation enablers and barriers across literature and workshop findings, this analysis represents a first step towards understanding key pitfalls and leverage points for enhancing NbS implementation and mainstreaming
Integrated Modeling for Managing Catastrophic Risks: Vulnerability Analysis and Systemic Risks Management
No full textCatastrophic dependent systemic losses have analytically intractable multidimensional probability distributions dependent on exogenous shocks, interactions among goals and constraints of the involved actors and systems, activities of economic sectors, structural and environmental standards, critical infrastructure in place, feasible mitigation and adaptation structural and financial measures, investment potentials, etc. For the analysis of the systemic risks we argue for the design of proper Decision Support Systems (DSSs) and integrated catastrophe analysis and management modeling approaches similar to ISCRiMM model of IIASA. We discuss several important aspects and components of the ISCRiMM. This includes considerations of systemic risks, safety and security constraints, the necessity of robust ex-ante loss reduction and ex-post emergency response and BBB actions, structural and financial measures, the need for stochastic catastrophe models (scenario generators), and proper stochastic optimization solution procedures to enable the decision-support regarding coherent systemic ex-ante and ex-post preventing and coping solutions for dealing with catastrophes. The diversion of capital from ex-post measures to ex-ante investments into structural loss reduction measures can essentially reduce the dependencies among losses and, hence, decrease overall vulnerability, stabilize insurance mechanisms, reduce the demand for ex-post risk sharing and restoration efforts. One of the ISCRiMM submodels is Vulnerability assessment model. In the paper we discuss different methodologies and models for vulnerabilities analysis and modeling, and how they can be effectively integrated within ISCRiMM. In particular, vulnerability models can be based on AI, statistical and machine learning principles, which provide an effective means of incorporating them into ISCRiMM and designing optimal and robust interdependent ex-ate and ex-post measures decreasing vulnerabilities and increasing resilience and BBB capacities
Enhancing and stabilizing effects of low-carbon models on the synergistic benefits of wind and solar energy: Evidence from China
No full textWind and solar energy are seen as the most promising renewable energy sources for the future and will dominate future global renewable energy expansion. However, there is still a lack of sufficient research on the variation, especially the synergistic variation, of wind power (WP) and solar photovoltaic (PVPOT) generation under low-carbon modes. Here, we use bias-corrected Global Climate Models (GCMs) to analyse changes in WP and solar PVPOT by mid-century, providing a comprehensive assessment under two carbon-neutral scenarios. The results show that low-carbon modes significantly mitigate the continuous decline in China's wind energy resources, particularly in East and Central China. In the future, China's solar resources will shift southeastward, and under low-carbon modes, this growth trend becomes more significant, stable, and persistent. Beyond their individual effects on wind and solar energy, low-carbon modes notably improve the efficiency of wind and solar energy utilization, enhancing the synergistic benefits of renewable energy across the country. On this basis, further analysis of the drivers of WP and solar PVPOT changes in China reveals that changes in the frequency of cut-in wind speed (V < 3 m s−1) and ramp-up wind speed (3 ≤ V ≤ 11 m s−1) are the main contributors to the changes in 21st-century WP, whereas solar PVPOT changes are dominated by rsds, with a negligible effect of wind. Finally, we emphasise that global carbon neutral policies can effectively enhance the stability of China's WP and solar PVPOT especially their synergistic benefits across different time scales. The results of the study can provide a scientific basis for the development of long-term renewable energy planning in China
European Union needs large heat pump and targeted renovation subsidies to meet heating targets
No full textCurrent European Union policies are insufficient to achieve residential heating decarbonization targets. Substantial subsidies for heat pumps and carefully targeted incentives for home renovation are critical to efficiently and affordably meet climate goals. We emphasize the importance of adapting strategies to national contexts