Shifting from effect- towards cause-oriented and systemic approaches in sustainable climate change adaptation requires a solid understanding of the climate-related and societal causes behind climate risks. Thus, capturing, systemizing, and prioritizing factors contributing to climate risks are essential for developing cause-oriented climate risk and vulnerability assessments (CRVA). Impact Chains (IC) are conceptual models used to capture hazard, vulnerability and exposure factors that lead to a specific risk. IC modeling includes a participatory stakeholder phase and an operational quantification phase. While ICs are widely implemented to systematically capture risk processes, they still show methodological gaps concerning, e.g., the integration of dynamic feedback or balanced stakeholder involvement. Such gaps usually only become apparent in practical applications, and there is currently no systematic perspective on common challenges and methodological needs. Therefore, we reviewed 47 articles applying IC and similar CRVA methods that consider the cause-effect dynamics governing risk. We provide an overview of common challenges and opportunities as a roadmap for future improvements. We conclude that IC should move from a linear-, to an impact web-like representation of risk to integrate cause-effect dynamics. Qualitative approaches are based on significant stakeholder involvement to capture expert-, place-, and context-specific knowledge. The integration of IC into quantifiable, executable models is still highly underexplored due to a limited understanding of systems, data, evaluation options, and other uncertainties. Ultimately, using IC to capture the underlying, complex processes behind risk supports effective, long-term, and sustainable climate change adaptation.

Millions of people fall ill with malaria every year—most of them are located in sub-Saharan Africa. The weight of the burden of malaria on a society is determined by a complex interplay of environmental and social factors, including poverty, awareness and education, among others. A substantial share of the affected population is characterized by a general lack of anticipation and coping capacities, which renders them particularly vulnerable to the disease and its adverse side effects. This work aims at identifying interdependencies and feedback mechanisms in the malaria social vulnerability system and their variations in space by combining concepts, methods and tools from Climate Change Adaptation, Spatial Analysis, and Statistics and System Dynamics. The developed workflow is applied to a selected set of social, economic and biological vulnerability indicators covering five East-African Nations. As the study areas’ local conditions vary in a multitude of aspects, the social vulnerability system is assumed to vary accordingly throughout space. The study areas’ spatial entities were therefore aggregated into three system-regions using correlation-based clustering. Their respective correlation structures are displayed as Causal Loop Diagrams (CLDs). While the three resulting CLDs do not necessarily display causal relations (as the set of social vulnerability indicators are likely linked through third variables and parts of the data are proxies), they give a good overview of the data, can be used as basis for discussions in participatory settings and can potentially enhance the understanding the malaria vulnerability system.

<p>Climate-related sudden-onset events (e.g., floods, cyclones) and slow-onset processes (e.g., sea level rise and heat waves) pose a major risk to communities all over the world. With intensifying climate change in combination with unequal socioeconomic development, climate-related risks are expected to escalate in the future, potentially leading to critical losses and damages. This calls for efficient and achievable risk management strategies. Climate Risk Management (CRM) is a leading approach to identify, assess and reduce risks, through an integration of Disaster Risk Reduction, Climate Change Adaptation, and sustainable development. CRM aims at comprehensively managing risks and increasing resilience and adaptive capacity. To date, several conceptual CRM frameworks have been developed, which have, however, rarely been applied to real-world cases.</p><p>Based on this conceptual literature, we further develop a comprehensive CRM framework, comprising both the risk assessment as well as the implementation and monitoring domains of CRM, and test it on three real-world risk cases in Peru, India and Austria. The cases have distinct spatial scales, from local level in Peru, to district level in India, to nationwide in Austria. The risks covered in these cases are linked to different hazards, ranging from glacier lake outburst floods (Peru), sea level rise, salinization and cyclones (India), to riverine flooding and agricultural droughts (Austria).</p><p>The aim of this complementary case study approach is to validate the overall structure and individual steps of the CRM framework against actual risk management practices in the three case studies. Based on the specific results and common insights from the three cases, we are able to (1) evaluate the applicability of the proposed conceptual CRM framework in real world circumstances, (2) present evidence on the extent to which comprehensive management of climate-related risks has been achieved in the three cases, and (3) synthesize policy recommendations towards an achievable comprehensive CRM in practice, acknowledging specific local contexts and characteristics.</p>

Current scientific discourse on the assessment of loss and damage from climate change focuses primarily on what is straightforwardly quantifiable, such as monetary value, numbers of casualties, or destroyed homes. However, the range of possible harms induced by climate change is much broader, particularly as regards residual risks that occur beyond limits to adaptation. In international climate policy, this has been institutionalized within the Loss and Damage discourse, which emphasizes the importance of non-economic loss and damage (NELD). Nevertheless, NELDs are often neglected in loss and damage assessments, being intangible and difficult to quantify. As a consequence, to date, no systematic concept or indicator framework exists that integrates market-based and non-market-based loss and damage. In this perspective, we suggest assessing risk of loss and damage using a climate change risk and vulnerability assessment (CRVA) framework: the Impact Chain method. This highly adaptable method has proven successful in unraveling complex risks in socio-ecological systems through a combination of engaging (political) stakeholders and performing quantitative data analysis. We suggest expanding the framework's logic to include not only the sources but also the consequences of risk by conceptualizing loss and damage as harm to nine domains of human well-being. Our approach is consistent with the risk conceptualization by the Intergovernmental Panel on Climate Change (IPCC). Conceptualization and systematic assessment of the full spectrum of imminent loss and damage allows a more comprehensive anticipation of potential impacts on human well-being, identifying vulnerable groups and providing essential evidence for transformative and comprehensive climate risk management.