Sarah Hülsen

Weather and climate extremes are transforming ecosystems in ways that threaten society through the disruption of nature’s contributions to people (NCP) from food and water security to disaster mitigation and mental well-being. While scientists and policy makers increasingly recognize the need to account for nature-related losses from climate-driven weather extremes, major research gaps remain, particularly in how climate-altered disturbance regimes will impact NCP and associated human well-being. Addressing this gap is critical for climate mitigation and adaptation planning, because the loss of NCP amplifies social-ecological vulnerability and exacerbates climate risks. However, this cross-systems dynamic remains underrepresented in most climate risk models. Climate risk modeling offers a probabilistic view of evolving hazard regimes under climate change, while ecological research provides mechanistic insight into ecosystem responses to disturbance. We argue that bridging these fields is essential to increasing societal resilience to climate change and propose an interdisciplinary research agenda to integrate social-ecological dynamics with a climate risk perspective. Advancing this agenda is critical to project, anticipate, and plan for ecosystem-related impacts of weather and climate extremes on society.

Climate risks are increasing globally due to climate change and socio-economic development. Societies must implement adaptation measures today despite deep uncertainty regarding future climate trajectories, socio-economic pathways, and intervention effectiveness. Because no single strategy performs equally well across all impacts, for instance, protecting infrastructure versus saving lives, decisions depend on which outcomes are prioritized.Most assessments focus on a single criterion, most often the cost to benefit ratio of measures, overlooking other trade-offs and risking maladaptation. Multi-criteria decision analysis (MCDA) addresses this by explicitly evaluating and weighting multiple objectives. When coupled with probabilistic risk modeling and uncertainty quantification, MCDA can identify strategies that are robust across various futures and stakeholder priorities.In this project, we develop and test an integrated framework by coupling the new MCDA module of the open-source platform CLIMADA with its uncertainty and sensitivity quantification engine. Using a stylized case study from the Economics of Climate Adaptation (ECA), we explore how methodological and normative choices shape adaptation outcomes through three primary research questions:How do different impact units influence the prioritization of adaptation measures? We systematically compare rankings derived from multiple types of impact (e.g., population affected, economic losses, infrastructure exposure) to identify measures that perform consistently well across criteria versus those that are context-specific.How does the choice of risk metric affect the evaluation of adaptation measures? We quantify how rankings vary when using expected annual impact versus tail-risk metrics (high-impact, low-likelihood events), clarifying the normative implications of how "risk" is formulated.How sensitive and robust are MCDA-derived rankings to the weighting of decision criteria? We explore how results shift when assigning equal weights versus emphasizing specific priorities, making explicit how the assignment of preferences affects evaluations.Across these questions, we perform an uncertainty and sensitivity analysis that propagates uncertainty through all model components. This allows for a quantitative assessment of decision robustness and identifies the assumptions to which results are most sensitive.The key contributions of this work include the integration of MCDA with uncertainty analysis in a global modeling platform (CLIMADA); a systematic exploration of how normative modeling choices affect adaptation prioritizations; and a transparent, reproducible workflow for more integrated and value-aware climate-adaptation assessments.

Natural disturbances shape ecosystems by redistributing biomass, resources, and mortality across space and time. While the ecological effects of individual disturbance types (e.g. fire, floods, storms) are well studied, a globally consistent assessment of how multiple disturbance types combine into long-term disturbance regimes, and how these regimes relate to biodiversity patterns, is still lacking at the macroecological scale.Previous work (Kropf et al. in prep) presented 'hazomes,' a novel classification system of the earth based on hazard profiles, which is distinct from existing frameworks such as climate zones that categorize earth according to average conditions. Building up on this, we utilize a disturbance score based on eight different natural hazards (including heavy precipitation, earth quakes, tropical cyclones, cold spells, heat stress, coastal and river floods, water deficit, and wildfires), and their frequency of occurrence at different intensities. Unlike other commonly used climate descriptors such as mean temperature and precipitation, this approach captures the historical disturbance regimes ecosystems have been exposed to, providing a complementary perspective on the environmental drivers of biodiversity.By correlating the disturbance index with biodiversity indicators, such as species richness across taxa, we find biome-specific disturbance-biodiversity relationships. While climate is understood to be a key driver of global biodiversity patterns, our research implies disturbance regimes may be key to understanding biodiversity patterns within areas of similar climatic conditions. These findings highlight disturbance regimes as an underexplored dimension of biogeography and suggest that biodiversity patterns reflect long-term exposure to disturbance, not only to climate. As climate change increasingly alters the frequency and intensity of natural hazards, understanding how ecosystems have been shaped by historical disturbance regimes is critical for anticipating future biodiversity responses. Kropf, C. M., Hülsen, S., Stalhandske, Z., Hantson, S., Ward, P. J., Wens, M., Peleg, N., Bresch, D. N., & Steinmann, C. B. (in prep). Hazomes: Earth’s natural multi-hazard terrestrial disturbance regimes. EarthArXiv. https://eartharxiv.org/repository/view/10580/

An increasing number of countries and stakeholders now require large companies to disclose physical climate-related risks. However, the lack of standardization has led to the use of varied risk metrics from different data sources, making it difficult to compare physical risks across companies and preventing investors from aggregating risks at the portfolio level. To address this, we develop an approach using standardized, event-based probabilistic natural catastrophe risk assessments to improve global risk data aggregation and enable customized risk metrics. Integrating these methods into climate physical risk reporting would help investors align portfolios with a risk-return efficient frontier that accounts for physical risks, directing capital toward companies better equipped to manage climate impacts and promoting strategic adaptation. We propose a transparent, replicable, open-source methodology using event-loss tables to present per-event impact data. This approach is illustrated with two fictional companies exposed to tropical cyclone risk under current and future climate scenarios, highlighting the potential for company comparison, and portfolio risk assessment and optimization. Finally, we call on the scientific community and regulators to establish standardized hazard sets and financial loss functions to support transparent comparison and risk aggregation.

An increasing number of countries and stakeholders now require large companies to disclose physical climate-related risks. However, the lack of standardization has led to the use of varied risk metrics from different data sources, making it difficult to compare physical risks across companies and preventing investors from aggregating risks at the portfolio level. To address this, we develop an approach using standardized, event-based probabilistic natural catastrophe risk assessments to improve global risk data aggregation and enable customized risk metrics. Integrating these methods into climate physical risk reporting would help investors align portfolios with a risk-return efficient frontier that accounts for physical risks, directing capital toward companies better equipped to manage climate impacts and promoting strategic adaptation. We propose a transparent, replicable, open-source methodology using event-loss tables to present per-event impact data. This approach is illustrated with two fictional companies exposed to tropical cyclone risk under current and future climate scenarios, highlighting the potential for company comparison, and portfolio risk assessment and optimization. Finally, we call on the scientific community and regulators to establish standardized hazard sets and financial loss functions to support transparent comparison and risk aggregation.

Climate change is expected to alter the frequency and intensity of extreme events, modifying the natural disturbance regimes to which ecosystems are adapted. Here, we present a spatially explicit risk index for mangroves and associated biodiversity and ecosystem services based on projected frequency changes of tropical cyclone wind speeds and rates of relative sea level rise under SSPs 245, 370 and 585 by 2100. Globally, approximately half of the total mangrove area (40–56% depending on the SSP) will be at high to severe levels of risk due to climate-modified tropical cyclone disturbance regimes. Further, we find mangrove areas with high levels of biodiversity and ecosystem services provision, including coastal protection for people and assets, carbon sequestration, and fishery benefits, are at proportionally higher levels of risk. Our findings emphasize the need to anticipate changes in natural disturbance regimes and adapt ecosystem management to sustain mangroves and their services in the future.

The combination of natural hazards, along with their frequency and intensity, defines local disturbance regimes that fundamentally shape ecosystems and human societies. We propose 'hazomes,' a novel classification system of the earth based on these specific hazard profiles. Unlike other classification systems such as climatic zones that categorize the earth according to average conditions, 'hazomes' are defined by distinct profiles of extreme natural hazards. We integrate data from multiple open sources and develop methodologies to systematically identify and categorize 'hazomes' across the globe, based on two return periods and two intensities for each hazard type (among others earthquakes, floods, wildfires, and tropical cyclones). This approach reveals thousands of distinct 'hazomes,' reflecting a diverse range of natural disturbance regimes. Our analysis shows that 'hazomes' provide insights that complement traditional classifications such as Köppen–Geiger climatic zones, biomes, and ecoregions.For enhanced usability and broader application, we also develop two streamlined versions of the classification. The reduced version classifies geographic points based solely on the binary presence or absence of each hazard type. The simplified version distills the framework into less than a hundred principal categories by focusing on the most significant hazard characteristics. These versions balance the richness of detailed data with practical applicability in risk management and planning. This framework aims to deepen insights into ecosystem and societal resilience by highlighting how both ecological and human systems may adapt to or depend upon specific natural disturbance regimes. Among its various potential applications, this approach is particularly useful for facilitating multi-hazard risk assessments and supporting the development of adaptive strategies by transferring knowledge between areas with similar disturbance profiles.

Climate change is expected to alter the frequency and intensity of extreme events, modifying the natural disturbance regimes to which ecosystems are currently adapted. Here, we present a spatially explicit risk index for mangroves and their associated biodiversity and ecosystem services based on projected frequency changes of tropical cyclone wind speeds and rates of relative sea level rise under SSPs 245, 370 and 585 by 2100.To compute the risk index, we calculate the relative change of tropical cyclone frequency across different wind speed intensity categories based on probabilistic tropical cyclone tracks downscaled from 3 different CMIP6 models of varying climate sensitivity. This data is then combined with thresholds of sea level rise which are estimated to exceed mangrove adaptive capacity and mapped onto global mangrove extents.Globally, approximately half of the total mangrove area (40-56% depending on the SSP) will be at high to severe levels of risk due to climate-modified tropical cyclone disturbance regimes. Further, we find mangrove areas with high levels of biodiversity and ecosystem services provision, including coastal protection for people and assets, carbon sequestration, and fishery benefits, are at proportionally higher levels of risk than mangrove forests generally. We also identify mangrove areas which are projected to experience non-analog tropical cyclone disturbances in the future. Our findings emphasize the need to anticipate changes in natural disturbance regimes to adapt ecosystem management, sustain ecosystem services in the future, and fully realize mangroves’ potential as nature-based solutions (NBS).

Coastal ecosystems, such as mangroves, coral reefs, salt marsh, seagrass, and kelp forests, provide crucial regulating, provisioning, and cultural services to human societies. Previous research has demonstrated the various ways in which these ecosystems can reduce disaster risk and contribute to climate change adaptation. Simultaneously, the potential effects of climate extremes and extreme weather events on ecosystem composition and functioning are increasingly gaining attention.While it is apparent that these ecosystems are subject to changing disturbance regimes under climate change, assessments of what these future disturbance regimes are likely to look like in the future have rarely been attempted and are often limited to single ecosystem and hazard pairs.Therefore, we propose a global multi-layer hazard assessment for coastal ecosystems to assess i) the changing disturbance regimes coastal ecosystems are exposed to with regards to tropical cyclones, storm surge, sea level rise, and marine heatwaves, ii) potential ecological responses to these changes, and iii) implications for ecosystem service provision. We will present preliminary results as a starting point for further discussion.

Climate change is expected to alter the frequency and intensity of extreme events, modifying the natural disturbance regimes to which ecosystems are currently adapted. Here, we present a spatially explicit risk index for mangroves and their associated biodiversity and ecosystem services based on projected frequency changes of tropical cyclone wind speeds and rates of relative sea level rise under SSPs 245, 370 and 585 by 2100. Globally, approximately half of the total mangrove area (40-56% depending on the SSP) will be at high to severe levels of risk due to climate-modified tropical cyclone disturbance regimes. Further, we find mangrove areas with high levels of biodiversity and ecosystem services provision, including coastal protection for people and assets, carbon sequestration, and fishery benefits, are at proportionally higher levels of risk than mangrove forests generally. Our findings emphasize the need to anticipate changes in natural disturbance regimes and to adapt ecosystem management to sustain ecosystem services in the future.