This session seeks to highlight research on the nexus of weather and climate-related extreme events and ecosystems. We encourage submissions on: 1) investigations into the key attributes and patterns of extreme weather events which affect ecosystem composition, structure and functioning, 2) studies on how ecosystems respond to and recover from extreme weather events across past, present, and future climates, 3) Implications of extreme weather impacts on ecosystems for biodiversity and ecosystem service provision. We welcome a diverse array of contributions, including theoretical analyses, modelling approaches, field studies, experimental designs, and remote sensing analysis.
Key topics include:
- Identification of extreme weather risk hotspots, and subsequent ecosystem responses (terrestrial, coastal, or marine) in past, present and future climates
- Role of extreme weather in shaping ecosystem composition, biodiversity, structure and functioning, and its impact on ecosystems service provisions across temporal and spatial scales
- Interactions of natural hazard, anthropogenic and biogenic disturbances with ecosystems (including compounding events)
- Ecosystem vulnerability, resilience and recovery dynamics under weather extremes, including regime shifts / tipping points in ecosystems
- Impact and efficacy of nature-based solutions under extreme conditions, risk of maladaptation or disservices
Orals: Fri, 8 May, 08:30–10:15 | Room 2.24
Extreme events can have severe impacts on ecosystems, their functioning and on the services they provide. For example, extended drought periods and heat waves are occuring more frequently and intensely in the recent past, with severe consequences for forests. My talk will give insights on the impacts of extended drought periods and heat waves on two different forest ecosystem types. First, I show how drought-impacts on forest ecosystems can be detected using the European Forest Condition Monitor and the Amazon Canopy Condition Monitor, which are based on remotely-sensed canopy greenness. Then I exemplify how the fusion of remotely-sensed canopy greenness and model simulation output helps to quantify tree-species specific drought-vulnerabilities. My talk also demonstrates how process-based models can help to assess impacts of extreme events on forest dynamics and composition, and on the carbon and water cycle. I present new developments from the process-based vegetation model LPJ-GUESS regarding the representation of drought-response strategies of different forest types and tree species. Finally, I will discuss how climate change and the impacts of extreme events can lead to different ecosystem recovery trajectories after disturbance.
How to cite: Rammig, A., Layritz, L., Meyer, B., Gregor, K., Ferreira, V., Wang, Y., and Buras, A.: Forest responses to extreme events: Insights from remote sensing and process-based modelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13977, https://doi.org/10.5194/egusphere-egu26-13977, 2026.
Forests are increasingly relied upon as climate mitigation assets, but their carbon sequestration capacity is vulnerable to intensifying disturbance regimes. This vulnerability is especially relevant in intensively managed production forests, where disturbance can disrupt harvest cycles and alter carbon trajectories. In Ireland, for instance, conifer forests, largely composed of Sitka spruce (Picea sitchensis (Bong.) Carr.), dominate the productive forest estate and are particularly exposed to wind damage (Gallagher, 1974, Ni Dhubhain, 1998), raising questions about the robustness of mitigation benefits under a “business-as-usual” management. In this context, this study quantifies how alternative management strategies influence the carbon resilience of Irish forests at national scale.
A windstorm disturbance scenario was implemented across the Irish conifer forest estate using the CBM-CFS3 framework (Kurz et al., 2009). Stands were initialised with attributes from the National Forest Inventory (DAFM, 2022) to represent the most up-to-date age structure and management context. The windstorm event was defined as a target affected area consistent with recent post-storm damage magnitudes in Ireland (McInerney et al., 2016, DAFM, 2025). Damage is allocated using exposure and stand structure eligibility rules informed by Ni Dhubhain et al. (2009), with susceptibility weighted by management state (e.g., recently thinned stands) and stratified by region and age class. A baseline management scenario followed standard practice in the country (thinnings and clearfell with replanting). Post-storm dynamics included a short period of on-site decomposition of downed biomass followed by static salvage prescriptions to isolate management effects.
Management was evaluated through two decision factors expected to affect both forest exposure and recovery to storm events: thinning strategy and rotation length. Results were summarised using mitigation-relevant indicators at national scale, including changes in ecosystem carbon pools (live biomass, dead organic matter, soils), the magnitude and duration of storm-induced carbon debt and the timing of recovery relative to pre-storm trajectories. This analysis was framed as a scenario-based sensitivity assessment rather than a forecast, providing an evidence base for national reporting discussions and for subsequent work extending to alternative management pathways and analyses considering the carbon stocks in harvested wood products.
Keywords: carbon dynamics, forest resilience, natural disturbance, storm damage, temperate forests.
References
DAFM 2022. National Forest Inventory of Ireland. Dublin: DAFM.
DAFM 2025. Minister Healy-Rae confirms that over 26,000 hectares of forests have suffered wind damage. DAFM. Government of Ireland.
GALLAGHER,G. 1974. Windthrown in state forests in the Republic of Ireland. Irish Forestry, 31, 14.
KURZ, W.A., DYMOND, C.C., WHITE, T.M., STINSON, G., SHAW, C.H., RAMPLEY, G.J., SMYTH,C., SIMPSON, B.N., NEILSON, E.T., TROFYMOW, J.A., METSARANTA, J. & APPS, M.J. 2009. CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecological Modelling, 220, 480-504.
MCINERNEY,D., BARRETT,F., LANDY, J. & MCDONAGH,M. 2016. A rapid assessment using remote sensing of windblow damage in Irish forests following Storm Darwin. Irish Forestry, 73, 19.
NI DHUBHAIN, A. 1998. The influence of wind on forestry in Ireland. Irish Forestry, 55, 105-113.
NI DHUBHAIN, A., BULFIN, M., KEANE, M., MILLS, P. & WALSHE, J. 2009. The development and validation of a windthrow probability model for Sitka spruce in Ireland. Irish Forestry, 66, 74-84.
How to cite: Longo, B. L. and Byrne, K. A.: Adapting management to wind disturbance: national-scale carbon trajectories under alternative silvicultural strategies in Ireland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20290, https://doi.org/10.5194/egusphere-egu26-20290, 2026.
Key Biodiversity Areas (KBAs) in South Asia are ecologically important, yet many are increasingly exposed to climate extremes and human pressures. Integrated assessments that combine climate extremes, species vulnerability, and anthropogenic pressures remain limited for the Key Biodiversity Areas of South Asia. This study develops a combined framework to evaluate climate hazards and multidimensional vulnerability across more than 800 KBAs.
Species vulnerability scores were calculated using IUCN distribution range maps for threatened birds, reptiles, amphibians, mammals, and plants, which were intersected with KBA boundaries to calculate species vulnerability based on the number of IUCN-threatened species present in each KBA. Anthropogenic vulnerability was calculated using the global human-pressure map, representing pressures from built environments, agricultural areas, population density, transportation networks, and night-time lights. The initial climate analysis includes temperature trends, precipitation trends, and the calculation of ETCCDI indices (such as TXx and WSDI) using ERA5 observational data (1951–2014) and CMIP6 model outputs.
The preliminary results indicate that warming patterns are most pronounced across the Himalayas, northeastern India, and parts of the Western Ghats. Several species-rich KBAs are in rapidly warming or strongly human-modified landscapes, suggesting heightened ecological sensitivity. Extended climate analysis includes precipitation-extreme indices to provide a more complete representation of hydro-climatic variability.
Biological, anthropogenic, and climatic components are combined to form a composite vulnerability index. This index is integrated with climate-extreme hazards to produce a Climate–Biodiversity Risk Index for each KBA. The framework provides a practical and data-driven basis for identifying KBAs where climate extremes and vulnerability factors overlap, supporting improved conservation and climate-adaptation planning across South Asia.
How to cite: Fatima, N.: Assessing Climate Extremes and Composite Vulnerability in South Asian Key Biodiversity Areas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-682, https://doi.org/10.5194/egusphere-egu26-682, 2026.
Climate change is projected to increase the frequency, intensity, and spatial extent of extreme climate events. Among these, extreme cold impacts on crop yield are often overlooked from historical and future analyses. To address this issue, a unique national dataset detailing 2,490 field-identified extreme cold days at 212 sites was assembled to quantify stage-specific crop responses to extreme cold. Results show that extreme cold affected 27% of China’s rice seasons during 1999-2012, resulting in an average yield reduction of 12.1±3.2%. This is mainly attributed to extreme cold during the transplanting-stem elongation and the heading-flowering stages, which reduces the total grain number per panicle and yield. In contrast, current global gridded crop models underestimate the cold sensitivity by 60% and a board range of model sensitivity. The constrained estimates show with >95% probability that rice yield would be reduced by extreme cold in stage of transplanting-stem elongation (−3.8±1.2% day−1), heading-flowering (−3.6±1.0% day−1), and milking grain-mature grain (−1.6±0.9% day−1). Uncertainties associated with modelled sensitivities were reduced by 36-44%. The national rice yield losses decrease by 9.1 ± 2.4% under the scenario of SSP1-2.6 by the end of this century, approximately twice as large as the unadjusted model estimates. This research highlights the underappreciated role of extreme cold in reducing crop yield under climate change.
How to cite: Fu, J., Tang, G., Qiao, F., Tong, X., and Zhou, F.: China’s Rice Yield Sensitivity to Extreme Cold is Underestimated, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2021, https://doi.org/10.5194/egusphere-egu26-2021, 2026.
Successions of drought and extreme precipitation events are frequent compound events that pose a wide range of threats to ecosystems, whether natural or managed, and to society as a whole. The severity of such impacts depends on the intensity of the cascading hazards, the exposure and vulnerability of the affected systems. In the project ARCEME (Adaptation and Resilience to Climate Extremes and Multi-hazard Events) funded by the European Space Agency, we propose a workflow to analyse compound events fingerprints, i.e. spatially aggregated time series of indices based on small data cubes of satellite remote sensing imagery, typically 10x10 km over two years. Here, we demonstrate the workflow in some agroecosystems across Europe, selected using the WOCAT database on sustainable land management, which experienced heavy precipitation following extremely dry conditions. The compound events are detected in ERA5-Land time series of precipitation and potential evapotranspiration. We stratify the Sentinel 2-based fingerprints using land management information from the Copernicus Land Monitoring Service High Resolution Layers. The results provide insight into the effect of land management on the resilience of European agroecosystems to the impacts of drought followed by heavy precipitation.
How to cite: Weynants, M., Teber, K., Mahecha, M. D., Kluczek, M., Bojanowski, J. S., and Gans, F.: Can Sentinel-2 help characterize the land management effect on the impact of drought followed by heavy precipitation in European agroecosystems?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13636, https://doi.org/10.5194/egusphere-egu26-13636, 2026.
Earthworms are adapted to resist extreme weather and soil flooding through a range of a physiological, behavioural and life-history strategies. During flooding, the oxygen content of soils reduces, representing a substantial risk to the survival of earthworms, which “breathe” oxygen across their skin. Therefore, changes in flood characteristics due to climate change are likely to pose significant challenges to earthworm populations. Given the importance of earthworms to several ecosystem services and provisions, understanding these risks is critical. Using historical (HadUK-Grid) data and future UKCP18 climate projections covering a 100-year period (1970-2080), we developed a rain-on-grid model for the whole of UK to model changing flood extent, frequency and duration due to changing climate conditions. The information was twinned with experimental data on earthworm survival under low oxygen conditions, including species-specific levels and oxygen affinities of their haemoglobins, mortality and cocoon viability to reveal a spatial understanding of hydrological extremes and its threats to earthworm under changing climate conditions.
Using the combined flood metrics, earthworm vulnerability and survival rate information, hazard maps reveal spatial and temporal hotspots of risk to earthworm populations and communities. These maps demonstrate critical thresholds beyond which earthworm populations experience mortality, threatening ecosystem resilience and ecosystem services. By linking hydrological extremes to earthworm response, this work provides an interdisciplinary workflow for predicting earthworm impacts due to changing flood characteristics under future climate.
The findings emphasise the need to integrate earthworms into flood risk management and ecosystem resilience planning, which can address potential ecosystem impacts that may be overlooked in climate adaptation strategies and promotion of nature-based solutions.
How to cite: Zhu, Q., Klaar, M., Daly, K., Berenbrink, M., Pile, B., and Hodson, M.: Mapping flood hazards and earthworm resilience under climate change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7022, https://doi.org/10.5194/egusphere-egu26-7022, 2026.
Earth's biomes are undergoing fundamental reorganisation under anthropogenic warming, yet it is unclear how they may be changing on multi-centennial timescales. We examine the co-evolution of land and ocean biome distributions under a high-CO2 emission scenario through the 23rd century using the Community Earth System Model version-2 Large Ensemble (CESM2-LE). We apply the Köppen-Geiger climate classification for land (15 classes) and a chlorophyll-based classification for ocean (7 classes). Our findings exhibit sharply decoupled trajectories of biome reorganization between land and ocean.
The response of terrestrial biomes to rising global temperatures appears to be approximately linear in time and with global mean surface temperature. Driven by rising aridity thresholds and decreased precipitation, arid deserts and steppe regions gradually expand, eventually extending to about 35% of the world's land surface in the extended future. On the other hand, marine biome responses are strongly non-linear. Despite rising temperatures and enhanced stratification, the expansion of oligotrophic “ocean deserts” is initially buffered until about 2100. Phytoplankton’s adaptive strategies such as N2 fixation, enhanced organic nutrient recycling, and stoichiometric plasticity support this resilience. However, these adaptive mechanisms break down when a warming threshold of about 2-6°C is exceeded, leading to a sudden increase in extreme oligotrophic areas that eventually cover almost 25% of the world's ocean surface.
We refer to this degradation in the extended future as “compound desertification”, in which terrestrial desert expansion is followed by the sudden acceleration of marine oligotrophication. In subtropical regions including the Mediterranean, Central America, and Southern Africa, this phenomenon is particularly noticeable and poses serious cross-domain risks to biodiversity and food security. Additionally, we pinpoint important land-ocean feedbacks, such as increased dust-driven iron deposition from growing terrestrial deserts, which influences marine productivity in High-Nutrient Low-Chlorophyll (HNLC) regions to some extent. Our results emphasise the need to account for distinct response timescales of land and ocean biomes and highlight the latent vulnerability of marine ecosystems under sustained greenhouse gas emissions.
How to cite: Paul, D., Park, E. J., Kwon, E. Y., Jahfer, S., Sharma, S., and Sreeush, M. G.: Compound Desertification from Land to Ocean under Multi-Centennial Climate Warming, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6419, https://doi.org/10.5194/egusphere-egu26-6419, 2026.
Sea turtles are among the marine life endangered by human activities that directly disturb their environment, such as fisheries bycatch, habitat degradation, and pollution. Additionally, the effects of ongoing global warming can also pose an extra threat since sea turtles are a species with temperature-dependent sex determination. Hence, with the increasing temperatures, they may experience a feminization phenomenon that can pose a risk to their extinction. Since the female sea turtles exhibit a great fidelity to beach sites where they were nested, a potential behavioral change to mitigate the effects of global warming is a nesting phenological shift to cooler periods of the year. Based on previous observations, the most optimistic phenological shift for sea turtles can be extrapolated to 27 days (about one month) per 1.5°C increase in the nesting sand temperature. Using this hypothesis, in this study, we aim to assess by when the sea turtles have to perform a one-month phenological shift in 48 sites around the world and the respective warming mitigation achieved by the phenological shift. We used two future climate scenarios (SSP2-4.5 and SSP5-8.5) from the simulations of 22 CMIP6 climate models. For SSP2-4.5 future scenario (a moderate scenario), it is projected that the middle of this century is the earliest date for phenological shift in sites located in the southeastern part of the USA and in the eastern Mediterranean sites. Sea turtles nesting in the equatorial sites have up to the end of the century or beyond to perform a phenological shift. However, the warming mitigation is greater in sites located further away from the equatorial region, whereas the sites in the equatorial region show a small mitigation effect from the phenological shift. Regarding the SSP5-8.5 future scenario (an extreme scenario), the phenological shift has to be performed in this century in all sites, with some sites in the Mediterranean with threshold dates sooner than mid-21th century. Moreover, compared with the SSP2-4.5 future scenario, there is some reduction in warming mitigation capacity, but it is not significantly different from the moderate scenario. Considering the uncertainty from the climate models' projections, our analysis shows that the models have lower uncertainty in sites projecting earlier threshold dates for phenological shifts.
How to cite: F. Veiga, S. and Yuan, H.: How many years do sea turtles have to shift their phenology due to global warming? , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16370, https://doi.org/10.5194/egusphere-egu26-16370, 2026.
Climate change increases the risk of passing tipping points, such as the Atlantic Meridional Overturning Circulation (AMOC), which would lead to additional changes in the climate system. Tipping of the AMOC significantly alters the heat distribution on Earth, as well as the mixing and advection of nutrients in the ocean. These changes impact marine ecosystems that support the Earth system and society, posing an additional threat to environments that are already under pressure. Here, we look at the effect of an AMOC weakening on marine ecosystems by forcing the Community Earth System Model v2 (CESM2) with low (SSP1-2.6) and high (SSP5-8.5) emission scenarios from 2015 to 2100. For each emission scenario we have two types of simulations: (1) a control simulation with emissions only; and (2) a hosing simulation in which an additional freshwater flux is added in the North Atlantic to induce an extra weakening of the AMOC. We use the temperature and phytoplankton fields of the CESM2 simulations to drive the marine ecosystem model EcoOcean. This model simulates 52 different functional groups that represent species on all trophic levels. EcoOcean allows us to get a good overview of the response of marine ecosystems to changes in the AMOC. Globally, marine ecosystems see a decrease in total biomass as a response to an AMOC weakening. However, the regional and functional group response can deviate from the global mean, meaning that in some regions and for some groups biomass actually increases. We present an overview of the winners and losers in marine ecosystems in response to an AMOC weakening with potential consequences for the fishery industry and society.
How to cite: Boot, A., Smolders, E., and Schuring, I.: Winners and losers in marine ecosystems: the response of functional groups to an AMOC weakening under future emission scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2774, https://doi.org/10.5194/egusphere-egu26-2774, 2026.
As the frequency and intensity of extreme events such as marine heatwaves, droughts and storms increases with climate change, so too do the efforts of researchers to understand the impacts of such extreme on marine and coastal ecosystems. In many coastal areas, communities and local industry depend on these ecosystems for income, protection, cultural heritage and sense of place, while at the same potentially influencing the strength of hazards through management decisions. It is therefore critical to understand the connection between hydro-dynamic extremes, marine and coastal ecosystems, and the services depended upon by different social and sectoral interests.
We combined mapping and modelling of marine and coastal ecosystems with stakeholder workshops in the Elbe / German Bight region from Hamburg to Helgoland, a region heavily connected with and impacted by human activities, to understand ecosystem risks due to extreme events and the ways in which these risks affect different local sectors and communities. Spatial data on local ecosystems was synthesised and mapped to identify key ecosystems of interest. Data was then gathered via literature review on thresholds for extreme event parameters and the ecosystem / individual level responses, supported by expert consultations and ecosystem-focused mini-workshops. We combined this with an impact web approach to create a conceptual risk web as a baseline for identifying and prioritising socio-ecological risks due to different extreme events experienced in the region. A series of stakeholder workshops were held to understand the key risks perceived by a diverse range of actors, and values were assigned to different regions of the study area by different sectors based on the IPBES Nature’s Contributions to People (NCP) framework. This framework puts more emphasis on non-monetary services, while allowing for diverse values and knowledge types to be integrated.
This work highlights the “black box” of linking empirical data on ecosystem impacts with how these impacts affect the provision of certain ecosystem services, which can be derived using qualitative and qualitative data. A mixed-methods approach is essential for assessing the cascading effects of ecosystem damage on society, especially in support of more effective, collaborative adaptation planning which enhances ecosystem resilience in oft-overlooked marine and coastal systems.
How to cite: O'Connor, J., Rackelmann, F., Amundsen, A., and Dekker, G.: The Black Box – A mixed-method approach linking extreme event impacts on ecosystems in coastal and marine areas to socio-ecological risks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20934, https://doi.org/10.5194/egusphere-egu26-20934, 2026.
Posters on site: Fri, 8 May, 14:00–15:45 | Hall X1
Climate change leads to soil drying in many regions via reduced precipitation and/or increased atmospheric water demand. This threatens the functioning of global vegetation, particularly forests, which currently absorb a substantial fraction of human carbon emissions. Analyses of forest responses to droughts typically focus on single events and span spatial scales ranging from individual sites to continents. A global analysis of drought impacts on forests and their evolution over time under ongoing climate change is lacking.
In this study, we quantify and analyse the evolution of the effects of soil moisture drought events on forests across the globe during 2001–2023. We identify dry events from a reanalysis soil-moisture dataset using percentile-based thresholds per grid pixel. Further, we evaluate forest responses using satellite-based vegetation indices, including NDVI and NIRv, and normalize anomalies by the pixel-based standard deviation to ensure comparability across regions. Using this approach, we find a steady increase in the global area exhibiting negative forest responses to soil dryness between 2001 and 2023. Additionally, regions with more negative forest responses tend to show faster increases over time than regions with mildly negative responses. We further hypothesize that this increased magnitude of severe vegetation responses to dryness may be related to three factors: increasing soil dryness and/or compound occurrence with atmospheric dryness, increased forest sensitivity to dryness, and changing spatial patterns of soil dryness occurrence. Understanding how these factors contribute to aggravated forest responses to dryness is essential for predicting the land carbon sink and implications for local water and energy cycling.
How to cite: Müller, P. M. and Orth, R.: Increasing impacts of soil dryness on forests across the globe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18103, https://doi.org/10.5194/egusphere-egu26-18103, 2026.
In the context of global warming, increasing frequency of extreme weather events has become a major challenge for humanity, especially for climate-sensitive and ecologically fragile area. However, the patterns and underlying mechanisms of extreme climate events, and its effects on vegetation are even less explored in arid and semi-arid regions in northwest China. In this study, we systematically examined historical changes, driving mechanisms, future projections of extreme climate events, and their impacts on vegetation dynamics in the Qilian Mountains, which is a key ecological security barrier in northwest China. We found that both extreme temperature and precipitation events in the Qilian Mountains have increased significantly in intensity, frequency, and duration over the past six decades, with pronounced spatial heterogeneity. Extreme low temperatures increased faster than extreme high temperatures, leading to a reduced diurnal temperature range, while heavy precipitation and wet-day precipitation contributed increasingly to annual totals. These changes are closely associated with intensified Eurasian anticyclonic circulation, enhanced geopotential heights, and increased moisture transport, modulated by phase shifts in the AMO, PDO, and AO. Future projections show continued intensification of extreme warming and precipitation, accompanied by a decline in cold and freezing days, especially under high-emission scenarios. From 1982 to 2015, NDVI in the Qilian Mountains exhibited an overall increasing trend, with 3.34% of the area showing a significant decreasing trend and 38.11% showing a significant increasing trend. Grasslands dominated the areas where vegetation significantly increased. Precipitation emerged as the main climatic factor limiting vegetation growth in the region, with the extreme precipitation intensity index contributing the most to NDVI, accounting for 17.1%. Both climate change and human activities jointly influenced vegetation dynamics, with differing dominant drivers between greening and browning areas. These findings improve understanding of climate–vegetation interactions in arid mountain systems and provide scientific support for ecosystem management and climate adaptation strategies in the Qilian Mountains.
How to cite: Gou, X., Liu, L., and Wang, X.: Extreme climate change and its impact on vegetation in the Qilian Mountains, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8662, https://doi.org/10.5194/egusphere-egu26-8662, 2026.
Climate warming is reshaping drought regimes and their impacts on terrestrial vegetation, yet most large-scale studies still describe drought–vegetation relationships using long-term mean states or trend metrics that integrate over many processes and do not reveal how ecosystems reorganize during individual drydowns. Here, we adopt an event-scale perspective by explicitly tracking vegetation responses along discrete drydown events. We identify droughts as periods of increasing cumulative water deficit (CWD), defined as the running imbalance between precipitation and actual evapotranspiration, and we quantify hydroclimatic forcing using the severity of the most extreme drydown in each year, expressed as the annual maximum absolute CWD (CWDmax, mm). Over 2000–2023, significant CWDmax trends occur in 16.51%of vegetated grid cells, corresponding to 18.71% of total vegetated land area (area-weighted). Significant increases in CWDmax account for 7.39% of vegetated grid cells (7.88% of vegetated land area) across much of the Northern Hemisphere, the Sahel and the Amazon, while significant decreases account for 9.12% of grid cells (10.58% of land area). Positive CWDmax trends indicate that the most severe annual drydowns are reaching larger absolute deficits over time, consistent with intensification of hydroclimatic water stress, whereas negative trends indicate a weakening of extreme deficits; with typical magnitudes of 24.5 mm per decade, and 50% of significant trends falling between 14.1 and 37.9 mm per decade (IQR). To characterise vegetation responses at the event scale, we track satellite-based surface greenness (Enhanced Vegetation Index, EVI) along each year’s most severe drydown and fit smooth EVI–CWD trajectories to locate productivity peaks and subsequent critical losses. We define EVIpeak as the fitted maximum greenness and its associated deficit (i.e., CWDcritical) along the event trajectory and EVIcritical as the greenness level at a standardized loss threshold (90% of EVIpeak). Across climates, the fractional decline from peak to critical states is relatively conserved (~10–24%), yet the cumulative deficit required to reach that decline spans a five-fold range (~40–200 mm), highlighting strong hydroclimatic modulation of event-scale greenness loss. We summarise long-term changes in these within-event thresholds into five threshold pathways : Stable (no trend), Greening and Browning (co-trending EVIpeak and EVIcritical), and two decoupled modes: Overshoot (EVIpeak↑, EVIcritical↓) and Compensatory (EVIpeak↓, EVIcritical↑). While ~80% of vegetated land area shows no detectable change (Stable), a latitudinal band (~50–65°N) exhibits a marked increase in non-stationary pathways, with Overshoot, Compensatory, and Browning over-represented; within 60–65°N, Browning reaches ~21.9%. Across regions where drought severity is intensifying in absolute terms (positive CWDmax trends), mid- to high-latitude systems more often shift toward Overshoot or Browning, whereas many dryland systems remain largely Greening. By uniting trends in absolute drought severity with within-event productivity thresholds, the framework provides state-dependent indicators of ecosystem pathways, highlighting where event-scale buffering appears stationary and where threshold dynamics indicate increasing vulnerability to greenness loss.
How to cite: Terristi, M.: Vegetation dynamics along drydowns under shifting drought regimes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13460, https://doi.org/10.5194/egusphere-egu26-13460, 2026.
The wealth of spa territories depends directly on their main resource: mineral and thermal groundwater. Their use has developed from Antiquity to the present day, through various applications, mainly medical and energy-related, enabling the growth of highly attractive local sectors. However, climate change is threatening their sustainability, impacting thermal resources and exploitation models. In the Interreg Southwest Europe region (SUDOE), this occurs by natural triggers such as a rainfall redistribution coupled to a long-term downward trend in its quantity, which may cause a deterioration in the current quality and quantity of water from thermal water points, and governance issues.
To minimize the impacts of climate change at the territorial level and increase their resilience, only an adaptation plan based on a clear strategy can be employed. However, the decisional processes needed to develop such a plan may generate conflicts among the relevant stakeholders and decision makers. To face these difficulties, the ThermEcoWat Project proposes a workflow and a methodology for the definition of adaptation strategies that include environmental, socio-economic, and regulatory aspects, based on participative approach structured around thematic workshops and a decision-aiding tool. This tool must be capable of managing the complexity of data and information requested for short-, medium-, and long-term strategies.
A consortium of geoscientists, city managers and entrepreneurs representing three thermal towns (Chaudes-Aigues - FR, Caldes de Montbui - ESP, and São Pedro do Sul - PT) are working together to (1) release a diagnostic of the current functioning of each pilot case and their link with thermal resource, (2) understand the current and futures constraints applied to the use of the resource, and (3) propose sustainable solutions that all relevant stakeholders agree on. These objectives need relevant amount of heterogeneous types of data, organized in a multidisciplinary knowledge base, which is the fundament of the decision-aiding tool. This tool, currently under development, leverages semantic data management technologies to enable an innovative approach to transdisciplinary data collection and a powerful knowledge extraction capability through inference.
This methodology is expected to be replicable across all European thermal sites in order to improve the durability of investments and build the essential prerequisite for adaptation to climate change.
How to cite: Klaba, V., Iasio, C., Aumar, C., Brunet, C., Arnó, G., Moreno, R. M., Ramalho, E., Carvalho, J., Ferreira Gomes, L. M., Ferreira, L., Jorge, A., Almeida, N., Diéguez, J., Madorell Batlle, Q., Pineda Moncusi, I., Martin Forns, J., Roussel, M., and Brut, E.: FOR A BETTER ADAPTATION OF THERMAL TERRITORIES TOWARD CLIMATE CHANGE - ThermEcoWat Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18673, https://doi.org/10.5194/egusphere-egu26-18673, 2026.
Forests in mountainous areas can lower the frequency, magnitude, and intensity of gravity-driven natural hazards, such as snow avalanches, rockfall and landslides. These so-called protective forests thus constitute a primary natural protection mechanism, which can be complemented by technical protective measures against natural hazards. Their protective effect depends on several factors, including forest structure and management, as well as site characteristics and hazard types.
With ongoing climate change, forests are increasingly exposed to stressors and natural disturbances. Environmental stressors create unfavourable conditions that can impair the physiology of trees. In contrast, natural disturbances are discrete events that cause tree mortality leading to a sudden change in the forest structure. Stressors and disturbances can be biotic, such as fungi or insects, or abiotic, such as drought or storms. For example, drought can act as a stressor affecting tree health, or as a disturbance causing tree death. Strong winds can put stress on trees, but they can also cause windthrow, where trees are uprooted or broken. Both phenomena lower forests’ resistance to future stressors and disturbances, as well as their capacity to recover from them.
Originating from climate research, compound events are commonly defined as situations where several climatic drivers or hazards co-occur, creating an increased risk to society or the environment. The impacts of compound events across spatial and temporal scales can be significantly greater than the sum of individual drivers or hazards alone. In this study, we transferred this concept to protective forests. Compound events in protective forests are defined as multiple, spatially and/or temporally, interacting climate-induced stressors and disturbances. These events lead to changes in forest structure and composition, which negatively impact the protective effect of forests against natural hazards and create compound risk for people and infrastructure. For example, windthrow and bark beetle infestations can cause large forest openings that create potential release areas for snow avalanches.
Compound risks pose novel challenges for pre- and post-disturbance protective forest and natural hazard management. Due to the high level of uncertainty and complexity involved, it is necessary to develop a shared understanding of compound risk. There is also a need to quantitatively assess compound risks to enable the implementation of effective strategies to address and mitigate them.
Based on a systematic literature review, we synthesized existing knowledge to develop a definition of compound risk resulting from compound events in protective forests. To assess compound risk for protective forest and natural hazard management, we proposed a methodological framework based on adaptive pathways. Adaptive pathways are a decision-focused approach in climate adaptation research and planning, allowing performance-threshold oriented decision-making under uncertainties. We applied this approach in two case studies and developed scenarios that included a variety of uncertainties regarding compounding stressors and disturbances in forests as well as regarding natural hazards. The method allows the consideration of different forest and natural hazard management strategies for risk-based interventions.
How to cite: Saxer, L., Moos, C., and Teich, M.: Compound risk in protective forest and natural hazard management, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12519, https://doi.org/10.5194/egusphere-egu26-12519, 2026.
Along the rivers March and Thaya in eastern Austria, 80 km of flood protection dikes have been constructed and rehabilitated since 2006. These structures are predominantly setback flood defenses that only interact directly with river discharge during flood events. Embedded within a Natura 2000 floodplain landscape, the dikes represent linear infrastructure elements that fulfil a dual function: they provide technical flood protection while simultaneously forming important ecosystems at the interface between riparian forests, agricultural land and settlement boundaries. Vegetation cover on flood protection dikes plays a key role in slope stabilization and erosion control, particularly under extreme hydrometeorological conditions. Beyond their protective function, dikes act as linear green corridors that enhance landscape connectivity and provide habitats for insects and small fauna. Biodiversity on these structures is therefore a crucial factor influencing ecosystem resilience, while degraded vegetation cover increases vulnerability to erosion, drought stress, and mechanical failure during extreme events and climate change poses increasing challenges for flood protection dikes. Prolonged drought periods weaken vegetation cover and reduce root cohesion, whereas more frequent intense precipitation and flood events impose additional stress through surface runoff, saturation, and erosion. Understanding how vegetation management affects ecosystem functioning under these compound stressors is therefore essential for assessing future vulnerability and resilience of flood defense infrastructure. Within the framework of the CLIMD research project, this study investigates how different management strategies, including mowing regimes, removal or retention of cut biomass, grazing by cattle and horses, and partial abandonment of maintenance, affect vegetation structure, biodiversity, biomass production, and soil water and nutrient dynamics across 20 dike sites along the March-Thaya system. The study sites span a broad gradient of environmental settings, ranging from floodplain forests to intensively managed agricultural landscapes. Data collection includes biomass assessments, biodiversity surveys, soil analyses, and high-resolution measurements of soil moisture and temperature in different depths. By integrating field observations, management scenarios, and climate projections into a biomass-based modeling framework, the study aims to quantify safety factors of dike sections and identify how biodiversity-driven vegetation complexity can enhance resilience while reducing vulnerability to extreme weather events.
How to cite: Dorfer, M., Rauch, H. P., Zehetner, F., Kager, T., and Ferchl, E.: Linking Biodiversity, Vegetation Structure, and Safety of Flood Protection Dikes under Compound Climate Stressors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17492, https://doi.org/10.5194/egusphere-egu26-17492, 2026.
How is tree vitality affected by conditions near railway tracks? Evapotranspiration can be higher, through increased sunlight exposure and wind, higher air temperature and lower air humidity than in a closed canopy. The extent, impact and occurrence frequency of more drought-prone conditions are investigated in the project “RailVitaliTree – Tree vitality monitoring and modelling of drought-related risks along railways with remote sensing and dendroecology”. The four most common tree species in Germany, pedunculate oak (Quercus robur), European beech (Fagus sylvatica), Norway spruce (Picea abies) and Scots pine (Pinus sylvestris), are examined.
The project follows a multidisciplinary approach, aspiring to develop a nation-wide tree vitality monitor along the German railway network to support early detection of potential damage to railway infrastructure and further ensure railway safety. Tree vitality is investigated through dendroecological methods, digital orthophotos and satellite imagery analysis, hydroclimatic measurements and a forest-focused climate analysis.
Herein we focus on the hydroclimatic investigations of the project, which consist of two parts: (1) Regional climate change effects on tree vitality are analysed via the plant-available water content computed by the forest water balance model LWFBrook90 from 1961 until the present. After applying a literature-based threshold for drought indication, the findings are compared with relative tree vitality changes computed from satellite data (https://forestwatch.lup-umwelt.de/) and dendroecological time series. As a further step, the lengths of continuous periods with a drought indication and their frequency over time are initially evaluated only for oak. An increase in period length and frequency (for the time period 1961 to 2020) can be observed so far.
(2) Additionally, instrumental measurements are carried out at selected, exemplary sites along the German railway network, to investigate microclimate conditions at forest edges. At a total of three sites, mobile weather stations measure standard meteorological parameters (air temperature, humidity, precipitation, wind, etc.) as well as soil moisture and matrix potential over one or two vegetation periods. These stations are installed as pairs, one station at the edge and one as a reference within the forest stand. The collected data is used to identify differences in the local water balance and compared to selected existing meteorological products of the German Meteorological Service. Preliminary results show small measurement differences between the reference and forest edge stations. Averaged over the meteorological summer months, the air temperature is highest and the humidity is lowest at the forest edge at midday.
How to cite: Billig, L., Kurtz, W., Bräuning, A., Gey, S., Hannak, N., Häusser, M., Herbst, M., Klinke, R., Rutte, D., Schmidt-Walter, P., Stöckigt, B., and Szymczak, S.: Investigating drought effects on forest edges along railway tracks within the project RailVitaliTree, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19349, https://doi.org/10.5194/egusphere-egu26-19349, 2026.
Extreme weather events pose severe challenges to the recovery of aquatic ecosystems, particularly for shallow lakes in critical stages of eutrophication restoration. Clarifying the tipping characteristics, mechanisms, and driving factors during ecosystem recovery is essential for improving sustainable management. Focusing on typical shallow lakes in eastern China at key governance stages, this study integrates sediment core analysis and historical monitoring records to reconstruct century‑scale eutrophication trajectories, identify regime shifts, and derive potential recovery pathways and restoration baselines. By combining short‑term observations with long‑term paleolimnological evidence, we develop and calibrate a PCLake dynamic model adapted to shallow lake ecosystems. Through scenario simulations that incorporate future extreme climate change and human‑induced stressors, we systematically analyze responses in ecosystem structure and function, and quantitatively assess vulnerability, resilience, and potential tipping points. This research aims to provide a scientific foundation for adaptive management of shallow lakes in regions during a critical restoration window under intensifying climate warming.
How to cite: Qin, B., Xu, M., Zhang, E., and Wang, R.: Restoration potential of eutrophic shallow lakes in eastern China under potential climate change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22350, https://doi.org/10.5194/egusphere-egu26-22350, 2026.
The Kunming-Montreal Global Biodiversity Framework (GBF) has established a global target to conserve 30% of the planet's land and seas by 2030. Nations worldwide, including South Korea, are actively committed to achieving this target. However, achieving this goal in South Korea is complicated by specific geographical and socio-economic constraints. While the nation is a critical stopover in the East Asian–Australasian Flyway (EAAF), its current Protected Area (PA) network is disproportionately skewed toward mountainous regions due to topographical characteristics. Consequently, critical habitats for threatened bird species—specifically in coasts, lowlands, farmlands, and islands—remain severely underrepresented, creating distinct conservation gaps. However, these biodiversity-rich areas are often privately owned and subject to high development pressure, making the designation of strict PAs legally and economically difficult. Therefore, identifying Other Effective area-based Conservation Measures (OECMs) that balance ecological needs with socio-economic realities is essential.
To systematically bridge the aforementioned conservation gaps, this study aims to identify feasible potential OECMs. To model nationwide habitat suitability, we employed the ensemble modeling framework of the biomod2 R package, utilizing machine learning algorithms such as Random Forest (RF), Generalized Boosting Model (GBM), and Artificial Neural Networks (ANN). For this analysis, we utilized occurrence data from the Global Biodiversity Information Facility (GBIF) for avian species classified as Critically Endangered (CR), Endangered (EN), and Vulnerable (VU) as input variables to accurately quantify the ecological value of unprotected areas. Crucially, unlike previous studies that focused solely on ecological metrics, this research integrated "Human Pressure Index (HPI)" and "proportion of private land" as explicit cost layers in a spatial optimization framework. This approach allows for the identification of areas offering high conservation value with manageable socio-economic trade-offs.
The analysis reveals that existing PAs fail to cover key lowland habitats essential for threatened birds. By incorporating cost variables, the optimization model derived potential OECMs that minimize land-use conflicts and acquisition costs while maximizing species protection. These findings suggest that a multi-criteria approach, considering both biological suitability and anthropogenic pressure, is vital for realistic conservation planning. The proposed potential OECMs provide a scientific basis for policy decisions and are expected to offer a practical pathway for South Korea to achieve the national 30 by 30 target by securing vulnerable avian habitats outside the traditional protected area network.
How to cite: Lim, S., Go, G., Kim, Y. I., Jang, T., and Jang, W. S.: Identifying Potential OECM Sites for Endangered Birds to Achieve the '30 by 30' Target in South Korea: Integrating Ecological Value and Socio-Economic Costs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10520, https://doi.org/10.5194/egusphere-egu26-10520, 2026.
We present the Surrogate Engine for Crop Simulations for Maize (SECS4M), a deep-learning emulator designed to replicate the process-based ECroPS crop growth model for grain maize in Europe while enabling computationally efficient, large-scale applications in climate services. SECS4M is built on a nested Long Short-Term Memory architecture capturing short- and long-term weather–crop interactions, while it ingests only three daily meteorological inputs, minimum and maximum temperature and total precipitation, thus minimizing the uncertainty that follows the use of a much wider input stream as in ECroPS. Trained on ERA5-forced yield outputs, SECS4M accurately reproduces crop growth trajectories, harvest timing, and yield distributions. Computational requirements are reduced from ~70s to ~0.008s per grid-cell–year, a four-order-of-magnitude speed-up that enables ensemble-scale, operational use.
Forced with bias-adjusted SEAS5.1 forecasts, SECS4M reproduces observed 2022 impacts and supports probabilistic identification of Areas of Concern (AoC) based on tercile-based yield anomalies. Under CMIP6 scenarios SSP3-7.0 and SSP5-8.5 to 2050, the emulator highlights specific regions as persistent hotspots of yield risk, while others exhibit mixed signals. SECS4M thus provides a scalable, digital twins enabled and data-efficient framework for seasonal forecasting, AoC mapping, and scenario analysis. Finally, the methodology can be extended to other crops and can be tested for its potential on other regions.
How to cite: Vlachopoulos, O., Luther, N., Ceglar, A., Toreti, A., and Xoplaki, E.: From climate hazards to yield losses: AI surrogate impact modelling , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17290, https://doi.org/10.5194/egusphere-egu26-17290, 2026.
Three gridded datasets (SAFRAN, ERA5-Land and EOBS) are compared to INRAE’s and Météo-France’s observed data from their respective weather stations networks. The Météo France network comprises 37 synoptic stations, while the INRAE network comprises 49 stations. This work analyses the bias between the gridded data and the stations’ ones. It aims to quantify the bias between those three datasets in terms of climatic parameters, as well as their repercussions on agroclimatic indicators and on the plant phenology cycle (in this case represented by wheat).
While historically studies of climate change and its impacts have relied on data from weather stations (located in a given place), in recent years we have observed more and more studies using gridded climatic data. Their value lies in the fact that these data enable the climate of a territory to be represented spatially (rather than at a single point), and they also ensure the continuity of all climatic variables. These two characteristics make them particularly useful for impact studies. Furthermore, this data is used to correct climate projections (e.g. CORDEX) at different scales. Many gridded datasets have been created with diverse characteristics and so equally diverse data values.
The datasets are, in the first instance, studied in regard to a set of weather parameters: minimal, mean and maximal temperatures and precipitations. The mean temperature is then incorporated in a phenology model to simulate the wheat’s phenology cycle. Simultaneously, the minimal and maximal temperatures are also used to calculate three agroclimatic indicators: number of frost days, number of days with maximal temperatures over 25°C (as an important threshold for wheat yield elaboration) and over 35°C (considered as a critical threshold for plant development and growth). In a second phase, the results are analysed to identify if the biases between the gridded data and the stations’ ones are changing seasonally, annually or depending on the value of the parameter.
We found that for the mean temperature and the phenology cycle the biases are not significative. The bias obtained for simulating phenology stages is in majority under the 5 days admissible error (which could be due to an observation error). For those two indicators, SAFRAN is showing the best results. In regard to the minimal and maximal temperature and the matching agroclimatic indicators, EOBS is showing lowest bias and ERA5-Land is showing the highest bias. We could also highlight a seasonality in the bias of the minimal temperature for SAFRAN and ERA5-Land, and a bias depending on the value of the parameter.
This work presents a method for identifying biases in a dataset, that can be applied to various parameters and impact studies. It quantifies the accuracy of the gridded data used in these studies and determines whether the biases are indicative. Furthermore, it illustrates the extent to which these biases shape the evaluation of indicators like phenology dates and climate-related risks to crop production. Finally, it helps users choose the most suitable dataset for their needs.
How to cite: Le Bihan, N., García de Cortázar-Atauri, I., Furusho-Percot, C., Launay, M., and Le-Roux, R.: Unveiling biases on agroclimatic indicators : assessment of gridded climate data SAFRAN, ERA5-Land, and EOBS, against station-based observations in France., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20300, https://doi.org/10.5194/egusphere-egu26-20300, 2026.
In Northern Europe, climate change lengthens the growing season and increases temperatures during this period, but it also raises exposure to adverse climatic events such as reduced timely precipitation, temperatures above the optimum, and frost damage. Nonetheless, the net effect of positive and negative changes of climatic conditions in Northern Europe is still unclear, and it remains underexplored whether future climatic conditions, particularly in winter, will be beneficial or detrimental for crop yields.
To assess future risks, we analyzed a regional Single Model Initial-Condition Large Ensemble (CRCM5-LE) over Northern Europe under the RCP8.5 scenario (1955–2099), focusing on agriculturally relevant climatic variables over winter. Projections showed increasing winter temperatures and precipitation, and a decrease in snow depth across most regions. Combined effects of these changes resulted in more frequent periods of snow depth <5 cm below 60°N, and an increased number of freeze-thaw cycles. Both of these conditions negatively affect autumn-sown crops during their winter dormant period, increasing susceptibility to frost damage. Trends toward these unfavorable winter conditions emerged as early as the first half of this century.
In parallel, by using statistical models we quantified past response of county-averaged spring- and autumn-sown cereal yields in Sweden (1965–2020) to a wide range of observed temperature- and precipitation-related indicators across physiologically relevant crop development stages. Average growing season climatic conditions explained 75–85% of yield variability and outperformed short-term extremes. Yield reductions were associated with low precipitation or prolonged dry spells combined with high temperatures, as well as excessive precipitation under cool conditions.
Together these results show that without targeted adaptation strategies, climate change is unlikely to benefit cereal yields in Northern Europe, as a result of changes in winter conditions, and reductions in growing season precipitation and increases in temperature.
How to cite: Tootoonchi, F., Lehner, F., Bergkvist, G., and Vico, G.: Changes in winter climatic conditions and growing-season precipitation-temperature interactions affect cereal yields in Northern Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10731, https://doi.org/10.5194/egusphere-egu26-10731, 2026.
Climate change manifests not only as changes in daily mean temperatures but also as shifts in the daily pattern of temperatures. We analyze historical analogues in the daily temperature cycle by comparing equivalent hourly temperatures since the 1980s. On a global average, temperatures characteristic of the morning warming period occur roughly 15 minutes earlier per decade, while those in the afternoon cooling period occur more than 20 minutes later per decade. For example, temperatures that occurred at 10 AM in the 1980s now occur at 9 AM, with even greater shifts in the afternoon. If sustained, the time of day at which equivalent temperatures occur would be displaced by more than three hours by 2100 relative to the 1980s, persisting under the ‘middle of the road’ pathway but slowing and eventually stopping under mitigation. The timing changes perturb ecological cues, increase human heat exposure, and displace energy demand in ways not captured by means or extremes, underscoring the value of time-of-day metrics for characterizing climate change impacts. Moreover, in more than half of mid-latitude regions, mean daily minima are projected to exceed the 1980s maxima, creating novel diurnal regimes with no recent historical analogues.
How to cite: Shmuel, A., Greenspoon, L., Mankin, J., and Milo, R.: The daily timing of a given temperature has shifted by over an hour since 1980, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16985, https://doi.org/10.5194/egusphere-egu26-16985, 2026.
The intensifying frequency and severity of compound moisture–temperature extremes pose a profound threat to ecosystem stability. This is especially the case for drylands, which are facing these compound events at rates increasing at least twice as much as they do for humid regions, both in terms of event frequency and intensity. Identifying “tipping” compound dry-hot thresholds at which vegetation survival is currently threatened is therefore critical to anticipate large-scale ecosystem collapse in water-scarce regions.
In this study, we built a copula-based probabilistic framework to investigate the responses of 132 grassland sites to compound dry-hot events of varying intensity between 2000–2022. The sites considered comprise 299 species and span an area of 6.6 million km2 in north China, with climates ranging from hyper-arid to dry sub-humid. At each site, our framework allowed us to examine the likelihood for dry-hot conditions to pose a threat to the vegetation. That is, we established site-specific “eco-risk probabilities” relating compound dry-hot intensity thresholds (defined by the standardized soil moisture and heatwaves index, CMHI) to significant impacts on vegetation structure. We further investigated the relationship between eco-risk probabilities, “tipping” dry-hot thresholds, and both longer-term ecosystem pedoclimatic conditions and underlying biotic factors like species richness.
We found >64% of the surveyed drylands area to have experienced an increase in eco-risk with intensifying compound dry-hot events between 2000-2022. “Tipping” thresholds for compound dry-hot events spanned the full breath of the CMHI index, from -2.84 (extremely severe dry-hot event) to -0.16 (very dry-hot event), indicating that different grassland ecosystems show very different levels of vulnerability. Among the multiple pedo-climatic and biotic factors considered as possible explainers for site-specific “tipping” dry-hot thresholds, continued warming emerges as the primary driver. Notably, a relatively higher species’ phylogenetic diversity greatly helps grasslands resist compound dry-hot extremes.
Our results confirm previous findings showing that dryland ecosystem stability is under an acute risk with rising temperatures; however, enhancing plant phylogenetic diversity may help mitigate the escalating threat faced by these ecosystems.
How to cite: Hu, Y. and Sabot, M.: Bioclimatic controls on compound dry-hot thresholds that govern dryland grassland ecosystem stability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11427, https://doi.org/10.5194/egusphere-egu26-11427, 2026.
How to cite: Piani, C., Ivimey-Cook, E., Glavan, S., Bricout, S., and Berg, E.: Evolution under exposure to heatwaves in the seed beetle, Callosobruchus maculatus., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2828, https://doi.org/10.5194/egusphere-egu26-2828, 2026.
The response of terrestrial vegetation to seasonal or extreme weather events is complex and dynamic. In recent decades, the increased frequency and intensity of extreme events, driven by global warming, have led to adaptive processes in the biosphere. These processes can also place additional stress on ecosystems, limiting their functionality.
Possible consequences of extreme weather events include shifts in the timing of seasonal vegetation activity, as well as changes in the strength of ecosystem functions such as carbon dioxide assimilation. These temporal characteristics include the start, peak, and end of the vegetation growing phase. Such shifts challenge the accuracy of traditional monitoring and modelling of ecosystem dynamics based on climatic thresholds or phenology, which have become less accurate over the past few decades. The existing methods also overlook the irregular vegetation responses under stress conditions caused by short-term impacts. New indices, parameters and methods are needed to better capture evolving vegetation responses, especially in the context of overall ecosystem functioning.
We propose that anomalies in seasonal photosynthetic activity, measured through near-real-time fluctuations in aboveground atmospheric CO₂ concentrations, could be used to qualitatively assess the impacts of extreme events on terrestrial ecosystems. When interpreted in conjunction with meteorological and remote sensing data, CO₂-based metrics could enhance our understanding of ecosystem functioning. We show preliminary results obtained with this approach, in combination with methods of correlation analysis of CO₂ trends and net ecosystem exchange index, We find good sensitivity and an adaptive response, which could be promising to advance ecological monitoring.
We expect that limitations of our approach, such as generalisation and behaviour-averaging, could be overcome with machine learning approaches. These could focus on the detection of vegetation functional periods, as well as in the qualitative assessment of functioning.
Our research results, based on a high-level carbon balance model, statistical methods, and time-series analysis, provide a preliminary non-phenological detection of vegetation activity periods and CO₂ uptake strength. We expect that our method can be applied in conjunction with existing approaches to aid identification of vegetation activity and ecosystem functioning, or as a standalone tool for their preliminary evaluation in near-real-time.
How to cite: Savytska, Y., Smolii, V., and Rehfeld, K.: Towards ML-based detection of terrestrial vegetation responses to seasonality and extreme weather events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10053, https://doi.org/10.5194/egusphere-egu26-10053, 2026.
Peatland greenhouse gas dynamics are affected by anthropogenic land-use but also climate change, and especially methane emissions are expected to increase due to warmer temperatures. We study peatland sites in Europe using process-based JSBACH-HIMMELI ecosystem model, which includes the peat-YASSO soil carbon model and HIMMELI methane production and transport model. The model is capable of simulating peatlands and peatlands drained for forestry with a separate forestry-growth model. We account for drainage by modifying the water table level.
Here we use CMIP 5 and CMIP 6 climate scenarios including IPSL, MPI and CNRM climate models and RCP 2.6, 4.5 and 8.5 pathways. We first simulate the peatland sites with their current land-use and set the model parameters according to in-situ measurements of GHGs and hydrology when available or otherwise use Sentinel 2 -based estimation and default set of parameters.
We also simulate different land use options for historical period the site being either pristine, drained for forestry, or drained for agriculture or peat extraction. For future scenarios, we simulate the site being pristine or restored by rewetting or afforestation. We study the temporal dynamics of soil carbon, water table level, carbon dioxide and methane fluxes due to changes in management and in alternative management scenarios. We also study the trends climate change possesses and how increasing drought events affect the peatlands.
Our results showed that the peatlands became more climate-warming in Radiative Forcing due to increased methane emissions, while the effect solely on water table level or Net Ecosystem Exchange was small. Drought events became more important on their contribution to annual GHG budget, but the intensity of emissions during droughts did not change notably. Peatland rewetting showed the return of carbon sink, and the methane emissions increased for a couple of decades depending on the water table level.
How to cite: Tuominen, V., Markkanen, T., Juutinen, S., Strötz, L., Aalto, T., Leppänen, A., Nevalainen, O., and Lohila, A.: Peatland CO2, CH4 and WT under climate change: process-based simulations of alternative land-uses , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5431, https://doi.org/10.5194/egusphere-egu26-5431, 2026.
Vegetation and water bodies play a crucial role in regulating the water and carbon cycles, however the climatic disturbances are impacting their functioning leading to the alterations in ecohydrological behavior of catchments. Therefore, it is crucial to identify the degraded ecosystems which are adversely affected under the influence of climate change. This study identifies degraded ecosystems in Peninsular India using remote sensing-based indicators, the Normalized Difference Vegetation Index (NDVI) for vegetation degradation and the Modified Normalized Difference Water Index (MNDWI) for waterbody changes. Sen’s slope trend analysis and Persistent change index (P-value) were applied to NDVI and surface water area (computed using MNDWI) for 90 catchments in Peninsular India to quantify the degradation levels. Results demonstrate that NDVI values range from 0.3 to 0.6 as majority of the Peninsular India is dominated by croplands. The spatial variation of surface water bodies indicates that larger waterbodies (>700 km2) are scattered in the central and north-western part of Peninsular India, while 59 out of 90 catchments have the lowest surface waterbody area (0.4-125 km2). Sen’s slope for NDVI varied from -0.03 year-1 to 0.03 year-1 observed across central, north western and north eastern regions of Peninsular India. Sen’s slope of water bodies computed catchment wise is varying from -8 km2yr-1 in southern part to 35 km2yr-1 in the Central and Northern Peninsular India. Persistent change analysis of NDVI and surface waterbody area reveals pockets of degradation in the northwest and southern regions of Peninsular India, with nearly 48 out of 90 catchments exhibiting low improvement in surface area of waterbodies. Comparison with climate and drought resilience indicates that resilient catchments experienced modest but stable gains in surface water area, while non-resilient catchments exhibited higher variability, including signs of both degradation and recovery. The findings provide a comprehensive understanding of vegetation and waterbody degradation, offering a scientific basis for prioritizing restoration and adaptation strategies in vulnerable catchments under climate change.
How to cite: Singh, A. and Sharma, A.: Assessment of Catchment Resilience Through Integrated Vegetation and Waterbody Degradation Analysis in Peninsular India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-847, https://doi.org/10.5194/egusphere-egu26-847, 2026.
Coastal wetlands are among the most productive ecosystems globally and play a crucial role in carbon sequestration. However, their carbon sequestration capacity has increasingly been affected by climate change and anthropogenic activities in recent decades. Revealing spatiotemporal changes in coastal wetland carbon sequestration capacity over extended time periods is crucial for understanding the long-term carbon dynamics. Our research constructed a global spatial dataset of accumulated carbon stocks in coastal wetlands at 1 km resolution for the period 2000–2020, capturing spatiotemporal variations in carbon stocks at both global and regional scales and identifying regional patterns of accumulated carbon stock losses. Our findings provide a solid basis for pinpointing vulnerable areas in need of restoration efforts and for supporting sustainable management of coastal wetland ecosystems.
How to cite: Xiong, S., Ge, Z., and Wu, X.: Mapping the accumulated carbon storage of global coastal wetlands from 2000 to 2020 at a 1km resolution , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15405, https://doi.org/10.5194/egusphere-egu26-15405, 2026.
