Extreme Climate Research Articles

Variability increased underneath growth enhancement of Mongolian pine natural forests in northeastern China in response to climate change

Clarifying tree growth variability in response to long-term climate change and short-term climate extremes is crucial for predicting future trends of forest performances. With climate change accompanied by more frequent climate extremes, tree mortality has been recently observed in the natural distribution areas of Mongolian pine (Pinus sylvestris var. mongolica), an important species used for afforestation in water-limited environments of northern China. However, the growth dynamics of the naturally grown pine trees and their associations with climate change are not well understood. We combined tree-ring and remote sensing approaches to investigate long-term growth performances and their responses to climate change from tree individual to landscape scales of Mongolian pine natural forests in a water-limited region in northeastern China. We found that the tree-ring width index (RWI) was highly correlated (r = 0.927, P < 0.0001) with satellite-derived normalized difference vegetation index (NDVI) during growing season (May-September) and both metrics consistently showed an obvious increasing trend in recent two decades, indicating enhancements of growth and their strong associations at both individual tree and landscape scales. However, long RWI time series also revealed obviously greater variations in radial growth (reflected by increased coefficient of variation) and lower resilience to potential disturbances (higher first-order antocorrelation) underneath such enhanced growth during the past two decades than earlier periods. RWI was found to be positively influenced by water-related climate factors (i.e., precipitation, relative humidity and drought index-SPEI) and negatively affected by temperature during growing season, which were further corroborated by similar relationship patterns between these climate variables and NDVI. Such impacts seemed to have strengthened over time, particularly at short time scales, which likely contribute to the increased growth variability with increasing climate extremes. Comprehensive examinations on growth performances of Mongolian pine natural forests through integrating multiple approaches imply that such forests would suffer from increasing growth instability and risks of die-off under climate change.

HSP mRNA sequences and theirexpression under different thermal oscillation patterns and heat stress in two populations of Nodipecten subnodosus.

Understanding the molecular mechanisms underlying thermal acclimation and heat shock responsesin marine ectotherms is critical for assessing their adaptive capacity in the context of climate change and climate extremes. This study examines the expression dynamics of heat shock proteins (HSPs) in the scallop Nodipecten subnodosus, shedding light on their role in thermal adaptation. Our analysis revealed the presence of several conserved functional signatures in N. subnodosus HSPs deduced amino acid sequences. Comparative gene expression profiling between two populations of N. subnodosus, maintained for 15 days under constant and oscillatory thermal regimes and then exposed to acute heat stress, revealed conserved adaptive traits. The heat-inducible nature of N. subnodosus HSP70 (HSPA8) gene expression highlights its potential as a stress marker, in contrast to its human homolog, which is constitutively expressed. Furthermore, the identification of HSP90 (HSPC3) and its overexpression during acute heat stress underscores its critical role in initiating a protective stress response. Population-specific responses in the magnitude of gene expression were observed; however, both populations exhibited similar overall patterns of HSP induction, suggesting a shared adaptive response mechanism. This study also elucidated the diversity and expansion of members of the HSP70 family members, specifically the HSPA12 subfamily, in N. subnodosus. This characteristic, previously observed in other bivalves, underscores the role of HSPA12 in environmental adaptation, providing molecular plasticity to withstand varying environmental pressures. These findings offer valuable insights into the molecular basis of thermal adaptation in N. subnodosus, highlighting the importance of HSPs in coping with environmental stochasticity under climate change scenarios.

The melatonin synthase-encoding gene ASMT mediates poplar resistance to drought stress and fungi Dothiorella gregaria.

In recent years, the increase in extreme climates, such as persistent high temperatures and drought, has adversely affected the growth and development of fast-growing trees. Melatonin (MT) plays an important role in plant responses to biotic and abiotic stresses, yet there is a lack of research on the specific role of limiting enzyme genes for MT biosynthesis in fast-growing woody plants. In this study, we investigated the function of PtoASMT, a key rate-limiting enzyme encoding gene for MT biosynthesis, which can be induced by drought, salt, and the phytohormones ABA, SA and JA. Our results show that: (1) PtoASMT was widely expressed in all tissues of poplar, but was highly expressed in petioles, moderately expressed in roots, stems, shoots and young leaves, exhibiting a typical diurnal expression rhythm in leaves, with the encoded protein localized on chloroplasts; (2) the content of MT was significantly promoted in overexpressing PtoASMT transgenic poplar plants, but there were no obvious differences in their growth and development; (3) overexpressing PtoASMT plants exhibited stronger drought tolerance, accumulating less reactive oxygen species (ROS) under drought stress relative to wild-type plants, whereas knockout PtoASMT plants were more sensitive and accumulated more ROS; (4) overexpressing PtoASMT plants were more resistant to fungi Dothiorella gregaria than WT plants, while knockout plants showed higher sensitivity; meanwhile, the expression of disease resistance-related genes (PRs and JAZ10) was significantly altered. We conclude that PtoASMT enhances the resistance of poplar to drought and Dothiorella gregaria by mediating MT biosynthesis in poplar. These findings contribute to a better understanding the role of ASMT gene in MT accumulation and stress resistance in poplar.

Impact of dual-carbon attention competition from local government on regional carbon emissions in China.

Extreme climate change induced by carbon emissions has received extensive attention from governments worldwide. Strong competition in local governments' dual-carbon attention (GCA) produces an effective influence on the reduction of regional carbon emissions, confirming crucial policy implications. In this study, textual content analysis is employed to measure the GCA level and GCA competition, and the mechanism by which GCA competition reduces regional carbon emissions in China is explored from the perspective of competition behaviors. The findings demonstrate that the increase of GCA competition positively influences the reduction of regional carbon emissions. Influence mechanism analyses verify that increasing GCA competition primarily stimulates the greater reduction of regional carbon emissions by intensifying competition in energy consumption reduction and the optimization of the energy consumption structure. The influence of GCA competition on reduced regional carbon emissions is significantly related to industrial structure upgrading, the energy consumption structure, and environmental governance investment, as well as inter-government competition in these areas. The detailed findings of this research can provide economic and environmental benefits for policymakers, and can provide corporations with more targeted policy recommendations related to dual-carbon attention and carbon emission reduction.

The projected impacts of climate change and fishing pressure on a tropical marine food web.

Small-scale fisheries, especially those from developing countries, are vital for millions. Understanding the impact of environmental and human factors on fish stocks and yields and how they might change is crucial to ensure the sustainable use of aquatic resources. We developed an ecosystem model using Ecopath and Ecosim (EwE) to investigate changes in target species biomass and ecosystem attributes over 83 years (2017-2100) caused by different scenarios of fishing pressure and ocean warming in the Brazilian Northeastern continental shelf. The simulations considered three IPCC climate change scenarios (RCP2.6 [0.42°C], RCP4.5 [1.53°C], and RCP8.5 [4.02°C]) and four fishing pressure scenarios: two with increased pressure (10% and 30%) and two with decreased pressure (-10% and -30%). The Ecopath model indicated that the Brazilian Northeastern continental shelf ecosystem is a grazing-based system with high biomass in macroalgae and detritus compartments, supporting a diverse community of consumers. Our simulations projected overall reductions in the biomass of target species, mainly under extreme climate change. Increasing temperatures and fishing efforts reduced the biomass of large predatory species and the food web length in several scenarios. Although projected changes in ecological network and information metrics were of lower magnitude, results predicted declines in production/respiration ratio, material cycling, and ascendency (variable related to trophic specialization, internalization, and material cycling) with climate change. These declines were likely linked to increased respiration rates, metabolic costs, and lower trophic efficiency with elevated temperatures. Together, our results show how climate change and fishing pressure can change the structure of coastal ecosystems, potentially leading to undesirable alternative states for fisheries. Our approach demonstrates the effectiveness of ecosystem-based modeling in projecting likely trajectories of change, which can be especially useful for resource management in data-limited conditions.

Climate Crisis on Energy Bills: Who Bears the Greater Burden of Extreme Weather Events?

The increasing frequency of extreme weather events driven by global climate change poses a critical threat to energy system vulnerability and household energy security. Using meteorological data from NOAA and Chinese weather stations (2012-2022), this study examines the impact of extreme climate risks on household energy poverty. Our findings reveal two significant transmission channels: infrastructure disruption and price fluctuation. Extreme weather events compromise energy infrastructure stability and cause supply interruptions, while temperature extremes trigger energy price volatility and increase household expenditure burdens. We further find that regions with weak infrastructure, areas prone to natural disasters, and low-income households are particularly vulnerable to these impacts. These findings suggest that climate change may exacerbate social inequality through energy poverty channels.

On-farm diversity and production challenges in Ethiopian tef [Eragrostis tef ((Zuccagni) Trotter)] landraces from Arsi zone, Ethiopia: Implications for breeding and conservation.

Tef [Eragrostis tef ((Zucc.) Trotter)] is a remarkable indigenous crop, highly adaptive and resilient to erratic and extreme climatic and soil conditions. It is a major staple food in Ethiopia and is usually cultivated for household consumption and the generation of income. However, nowadays, the crop particularly, the landraces are exposed to genetic erosion owing to biotic and abiotic factors. Thus, detecting the current status and production bottlenecks of the crop is key to enhance its production and conservation. The main objectives of this study were to assess the extent of on-farm diversity, genetic erosion and current production challenges of Tef landraces in Arsi Zone, Oromia region, Ethiopia. The study was conducted in the Arsi zone, Southeast Ethiopia using 400 selected farmers. Data were collected using a semi-structured questionnaire and analyzed using Minitab version 19. The respondent farmers included the different sex groups, age groups, educational status, marital status, and religious outlooks. S: A total of 26 Tef landraces have been identified to be cultivated over the last 2 to 3 decades and/or still in production in the study areas. The respondents indicated differences in the landraces with regard to morphological features which along with the naming's could suggest their genetic distinctiveness. Patterns of on-farm diversity in the landraces showed a varied abundance in the area where eleven landraces showed a relatively higher estimate (D=0.75 in Sergegna to D=0.58 in Bulga). With the exception of Aruso Tef (D=0.47), all the remaining landraces showed minimal or no (D=0.00) genetic abundance. The extent of the Sorenson similarity index revealed a higher similarity (0.69 in Enkelo Wabe vs Arsi Robe to 0.77 in Shirka vs Arsi Robe) and the areas revealed a higher landrace richness (R) and evenness index (E). However, patterns of temporal genetic diversity and extent of genetic erosion revealed that only 10 are grown currently (combined genetic erosion of 61.54%). In general, biotic and abiotic factors are challenging the current production of the crop in the area. Hence, researchers and all stakeholders should pay attention to conserving and breeding this important food crop. Understanding the extents of on-farm diversity and possible production challenges of the crop could facilitate and enhance its breeding, conservation and utilizations and hence, contribute to the food security of the country.

Unveiling climate extremes: A bibliometric odyssey through resilience, adaptation, and sustainable development goal synergies

Unveiling climate extremes: A bibliometric odyssey through resilience, adaptation, and sustainable development goal synergies

Land sharing, land sparing, and Triad forestry: modeling forest composition, diversity, and carbon storage under climate change and natural disturbances

ContextForests are vital renewable resources for timber, while also serving as carbon reservoirs and habitats for many terrestrial species. However, there are tradeoffs between timber production and other ecosystem services, such as carbon storage and biodiversity, highlighting the need for new management strategies that more effectively balance these tradeoffs. This case study models the effectiveness of four such strategies, based on a newly proposed management plan for a state forest in coastal Oregon.ObjectivesWe tested the effectiveness of four landscape-scale forest management strategies designed to minimize tradeoffs between timber production, carbon storage, and biodiversity. These strategies include land sparing (spatially separating timber production from conservation), land sharing (integrating timber production with conservation), and two variants of Triad management (dividing forests into intensive, extensive, and reserve areas). This study assesses the long-term impacts of these strategies on timber production, tree and shrub diversity, and carbon storage, while also evaluating how natural disturbances (i.e. wind and fire) and climate change could affect their relative benefits.MethodsWe used the spatially interactive, raster-based forest landscape model, LANDIS-II, to simulate forest succession, management, windthrow, and wildfire under a range of potential climate futures from 2016 until 2100.ResultsOur results demonstrate that while all management strategies ensured sustainable timber production, land sharing promoted the highest occupancy, Shannon diversity index, and biomass of key early and mid-successional tree and shrub species identified by managers for their conservation value. In contrast, Triad management and land sparing tended to maximize carbon storage. Under extreme climate projections, carbon storage was equally compromised across all management strategies and there was a further shift towards Douglas-fir dominance.ConclusionTo our knowledge, this study represents the first modelled comparison of land sharing, land sparing, and Triad management under climate change and natural disturbance regimes. Management strategies differed in their provisioning of carbon, diversity, and plant biomass, and while the relative differences between these benefits remained consistent, all outcomes were negatively affected by climate change. We demonstrate the use of LANDIS-II in strategic forest planning and highlight the necessity of using spatial models for informed decision-making to simultaneously achieve multiple forest management objectives under climate change and disturbances.

Growing environments and cultivar selection limits wheat growth and yield potential in Punjab

Selecting a suitable sowing time and cultivar can play a pivotal role in sustaining wheat productivity in north India while mitigating the influence of climate extremes. Field experiments were conducted in two distinct climatic regions (Ludhiana and Gurdaspur), of Punjab, India to assess the influence of different sowing environments and cultivars on wheat growth and yield. The crop was sown on three dates (early-5 November, mid-20 November and late-5 December) with two popularly grown wheat cultivars (PBW725 and PBW677). The results indicated that mid and late sowing significantly shortened phenological phases compared to early sowing at both study sites. Wheat sown on 5 November accumulated more thermal time, exhibited a greater leaf area index (LAI), intercepted more photosynthetically active radiation (IPAR), and demonstrated superior radiation use efficiency (RUE). Early-sown wheat also produced higher biological yield (BY), grain yield (GY), irrigation water use efficiency and heat use efficiency compared to delayed sowing at both sites. The wheat cultivar PBW725 outperformed PBW677 in terms of phenological duration, yield, thermal time accumulation, IPAR, LAI and RUE at both sites. IPAR and RUE exhibited a strong positive correlation and regression with the periodic dry matter accumulation of wheat. Linear regression revealed that LAImax (maximum LAI) and ?LAI (accumulated LAI) were the best determinants of BY of wheat. These findings highlight the significance of optimizing growing environments and cultivar selection in mitigating climate extremes and sustaining wheat production in the diverse agro-climatic conditions of Punjab.

HYDROLOGY IN PAKISTAN: A REVIEW OF RUNOFF, FLOODS, DROUGHTS AND THEIR IMPACTS

This review explores the complex relationship between climate change and hydrology in Pakistan, which is leading to significant weather extremes such as rainfall, temperature, floods, droughts and variable runoff patterns. It highlights the significant challenges posed by these water-related issues and the adaptive strategies needed for sustainable water resource management in the face of climate change and human activities. This study observes the major hydrological challenges in Pakistan focusing on repetitive floods and droughts that have deep impacts on the country’s economy, agriculture and environment. According to the Global Climate Risk Index, Pakistan is ranked as the fifth most vulnerable country as it experiences extreme weather events since the last few decades. Pakistan has faced many worst floods due to the changes in climate and hydrological extremes. The recurring occurrence of extreme rainfall events can be challenging to alleviate the flood hazards. This study will be helpful for our understanding on water management strategies to safeguard water resources and diminish the impacts of climate change on the country.

Extreme Weather Patterns in Ethiopia: Analyzing Extreme Temperature and Precipitation Variability

Climate change is significantly altering Ethiopia’s weather patterns, causing substantial shifts in temperature and precipitation extremes. This study examines historical trends and changes in extreme rainfall and temperature, as well as seasonal rainfall variability across Ethiopia. In this study, we employed the Mann–Kendall test, Sen’s slope estimator, and empirical orthogonal function (EOF), with data from 103 stations (1994–2023). The findings provide insights into 16 climate extremes of temperature and precipitation by utilizing the climpact2.GUI tool in R software (v1.2). The study found statistical increases were observed in 59.22% of the annual maximum value of daily maximum temperature (TXx) and 77.67% of the annual maximum value of daily minimum temperature (TNx). Conversely, decreasing trends were found in 51.46% of the annual maximum daily maximum temperature (TXn) and 85.44% of the diurnal temperature range (DTR). The results of extreme precipitation found that 72.82% of yearly total precipitation (PRCPTOT), 73.79% of consecutive wet days (CWD), and 54.37% of the number of heavy precipitation days (R10mm) showed increasing trends. In contrast, at most selected stations, 61.17% of consecutive dry days (CDD), 55.34% of maximum 1-day precipitation (RX1day), 56.31% of maximum 5-day precipitation (RX5day), 66.02% of precipitation from very wet days (R95p), and 52.43% of precipitation from extremely wet days (R99p) were decreasing. The results of seasonal precipitation variability during Ethiopia’s JJAS (Kiremt) season found that the first three EOF modes accounted for 59.78% of the variability. Notably, EOF1, which accounted for 35.84% of this variability, showed declining rainfall patterns, particularly in northwestern and central-western Ethiopia. The findings of this study will help policymakers and stakeholders understand these changes and take necessary action, as well as build effective adaptation and mitigation measures in the face of climate change impacts.

Browning events in Arctic ecosystems: Diverse causes with common consequences

Arctic ecosystems are experiencing extreme climatic, biotic and physical disturbance events that can cause substantial loss of plant biomass and productivity, sometimes at scales of &gt;1000 km2. Collectively known as browning events, these are key contributors to the spatial and temporal complexity of Arctic greening and vegetation dynamics. If we are to properly understand the future of Arctic terrestrial ecosystems, their productivity, and their feedbacks to climate, understanding browning events is essential. Here we bring together understanding of browning events in Arctic ecosystems to compare their impacts and rates of recovery, and likely future changes in frequency and distribution. We also seek commonalities in impacts across these contrasting event types. We find that while browning events can cause high levels of plant damage (up to 100% mortality), ecosystems have substantial capacity for recovery, with biomass largely re-established within five years for many events. We also find that despite the substantial loss of leaf area of dominant species, compensatory mechanisms such as increased productivity of undamaged subordinate species lessen the impacts on carbon sequestration. These commonalities hold true for most climatic and biotic events, but less so for physical events such as fire and abrupt permafrost thaw, due to the greater removal of vegetation. Counterintuitively, some events also provide conditions for greater productivity (greening) in the longer-term, particularly where the disturbance exposes ground for plant colonisation. Finally, we find that projected changes in the causes of browning events currently suggest many types of events will become more frequent, with events of tundra fire and abrupt permafrost thaw expected to be the greatest contributors to future browning due to their severe impacts and occurrence in many Arctic regions. Overall, browning events will have increasingly important consequences for ecosystem structure and function, and for feedback to climate.

Assessment and driving factor analysis of eco-environmental security for the Qinghai‒Tibet Plateau

ABSTRACT Eco-environmental security reflects a region’s capacity to mitigate threats posed by ecological degradation and resource scarcity, thereby sustaining its environmental support for economic development. Monitoring and evaluating changes in eco-environmental security are essential for promoting regional sustainability. However, existing ecological security indices predominantly focus on vegetation resources and often overlook critical factors, such as water and soil resources. This study develops an integrated eco-environmental security index that encompasses water, soil, life, and air components. Using the Qinghai‒Tibet Plateau as a case study, we assess changes in eco-environmental security between 2000 and 2020. The results show that (1) the eco-environmental security situation in the Qinghai‒Tibet Plateau region decreases from southeast to northwest, with climate and terrain being the dominant factors shaping this spatial pattern. (2) Influenced by the warming and humidification of the climate, the interannual trend is gradually improving, but extreme climate events have caused certain disturbances. (3) The Hurst index indicates that the eco-environmental security conditions in the Qinghai‒Tibet Plateau region are expected to improve in the future. The index developed in this study accounts for the unique geographical and climatic conditions of the plateau, offering both methodological and theoretical insights for assessing ecological security in ecologically vulnerable areas and supporting regional sustainable development.

DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts

With climate extremes’ rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models. Despite recent progress in deep learning to ecosystem monitoring, there is a need for datasets specifically designed to analyse compound heatwave and drought extreme impact. Here, we introduce the DeepExtremeCubes database, tailored to map around these extremes, focusing on persistent natural vegetation. It comprises over 40,000 globally sampled small data cubes (i.e. minicubes), with a spatial coverage of 2.5 by 2.5 km. Each minicube includes (i) Sentinel-2 L2A images, (ii) ERA5-Land variables and generated extreme event cube covering 2016 to 2022, and (iii) ancillary land cover and topography maps. The paper aims to (1) streamline data accessibility, structuring, pre-processing, and enhance scientific reproducibility, and (2) facilitate biosphere dynamics forecasting in response to compound extremes.

GRAiCE: reconstructing terrestrial water storage anomalies with recurrent neural networks

The Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) missions have provided estimates of Terrestrial Water Storage Anomalies (TWSA) since 2002, enabling the monitoring of global hydrological changes. However, temporal gaps within these datasets and the lack of TWSA observations prior to 2002 limit our understanding of long-term freshwater variability. In this study, we develop GRAiCE, a set of four global monthly TWSA reconstructions from 1984 to 2021 at 0.5° spatial resolution, using Long Short-Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) neural networks. Our models accurately reproduce GRACE/GRACE-FO observations at the global scale and effectively capture the impacts of climate extremes. Overall, GRAiCE outperforms a previous reference TWSA reconstruction in predicting observed TWSA and provides reliable water budget estimates at the river basin scale. By generating long-term continuous TWSA time series, GRAiCE will offer valuable insights into the impacts of climate variability and change on freshwater resources.

Influence of Extreme Climate events on wind and Solar Energy over the Gobi Desert Region of China in the future

Influence of Extreme Climate events on wind and Solar Energy over the Gobi Desert Region of China in the future

Mixed responses among closely related Neotropical butterflies under extreme climate and land cover changes

Abstract Although the Neotropics harbour almost half of the world's butterfly species, there are few assessments regarding the potential future suitability of habitats for this important bioindicator in the region. Here, we test if butterfly species restricted to the Amazonia rainforest will be more affected by environmental change than closely related, more widespread species. We compiled 1149 individually checked observation records of three closely related species pairs with distinct distribution patterns (Amazonian‐restricted and widely distributed in the Neotropics). Using MaxEnt species distribution models, we projected the future habitat suitability (2050 and 2100) under low (SSP126) and high (SSP585) greenhouse gas emission scenarios and also considering reduced forested cover. Estimated models showed that in the low‐emission scenario, most species will potentially expand their suitable habitats and distributions by 3.7%–11.4% in 2100. Contrastingly, in the high‐emission scenario, most species will potentially lose habitat and distribution ranges by 9.6%–49.7% in 2100, regardless of their original range extent or phylogenetic relatedness. Only one widespread generalist species might benefit from this scenario in 2100, increasing its suitable habitat area by 30%. Both Amazonian range‐restricted and more widely distributed Neotropical butterflies may be equally negatively affected by global change in high‐emission scenarios. The fact that only one generalist species might expand its suitable habitat suggests a butterfly fauna homogenisation in the Neotropics. This prospect requires further testing to consider whether global change will affect not only restricted but generalist species as well.

An optimal path threshold method for rigorously identifying extreme climate events

Abstract The frequent occurrence of extreme hydroclimate events has a significant impact on ecosystems and socio-economic systems. However, intercomparisons of extreme events are often hampered by inconsistent definitions and standardizations for different types of events. Here we introduce the OPT method, a dynamic programming-based approach that adaptively determines the optimal thresholds for defining extreme events at specific severity levels. Two case studies demonstrate its applicability. The first case study presents a long-term comparison of air heatwaves and lake heatwaves in Lake Mead. The algorithm adaptively selects thresholds to identify a comparable number of events at various severity levels. The second case study examines compound hot, dry, and windy events in California, exploring threshold selection for multivariable extremes and investigating their potential relationship with wildfires. The OPT method proves effective for adaptably and objectively analyzing complex and multifactorial extreme events.&amp;#xD;

Impact of physical climate risks on agricultural firms’ bankruptcy: evidence from France, Italy, Portugal and Spain from 2016 to 2019

Abstract Frequent and long-lasting extreme climate events can impact business-related natural capital, severely affecting production and resulting in losses for agricultural firms. Physical climate effects are material dependencies for agricultural businesses and may severely affect their performance and compromise their survival. This study’s aim is to analyze the comprehensive effect of climate change factors on agricultural firm bankruptcies in a European geographical area that is especially susceptible to climate change. Employing a panel of 15 036 agricultural firms, we analyze the effects of adverse climatic conditions in the firm’s headquarters area using logit regressions, an instrumental variable ordinary least squares model, and the gradient-boosting ensemble method. We find that bankruptcy is conditioned upon extreme weather events, indicating that climate change’s physical impacts on firm resources already materially affect the agricultural sector’s resilience and survival. Specifically, abnormally high temperatures, precipitation, and the incidence of fires are significant factors that contribute to bankruptcy or insolvency. Furthermore, a “fire weather” index comprising high temperatures, drought, and wind, combined with fire occurrence, intensifies the bankruptcy risk of agricultural businesses.