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The warming climate and increasing extreme weather events are transforming ecological backgrounds, which is bringing new challenges to herders' livelihood in grassland areas. To understand the practical ecological risks and the current resilience situations of herders' behaviors and government correspondence measures, we built a conceptual framework of community resilience in pastoral areas, selected different kinds of steppes along the ecological gradient (desert steppe, typical steppe and meadow steppe) and took household surveys to recognize the difference in ecological risks and enhancing strategies in different grassland types. The results show that: (1) Herders in desert steppe, with the lowest precipitation and the worst grassland condition, turn out to have more experience in perceiving droughts and mitigating loss from disaster, but received the most attention from government assistance (28.0%) to getting through drought; (2) Typical steppe, with traditionally better pastural husbandry environment, suffered most broadly through droughts (85.7%) and have worst household livestock loss (26.7%) through snow storms; (3) Meadow steppe has the highest catastrophic snow storm ratio (65.0%) and affected ratio (95.0%), but the least assistance from the government (22.22%). The results revealed that originally high ecological vulnerability gradually encouraged herder's livelihood adaptive capability. However, the government assistance and attention are more inclined to the local original ecological vulnerability. In addition, the increasing extreme climate events are bringing new challenges to adaptive knowledge systems of indigenous herders under good ecological condition. There is a clear need to combine the efforts of local pastoralists, policymakers and scientific community together to construct a more resilient socio-ecological pastoral systems under the global climate change. This research provides an in-depth understanding of community resilience in pastoral areas along the ecological gradient while facing the slow-onset climate change impacts. Practical recommendations on climate risk management and adaptation in pastoral areas are discussed. [ABSTRACT FROM AUTHOR]

Countries face extreme climate-related adaptation challenges, but some countries are more vulnerable due to their geographic location and socioeconomic conditions. These differences in vulnerabilities between countries motivated us to examine the socioeconomic factors and climate change adaptation relationship. The objective is to capture the impact of the socioeconomic factors on the climate change adaptation index for selected developing countries that influence vulnerability or adaptation. Dynamic panel data from 1995 to 2019 are used for four developing countries. The results reveal that fossil fuel increases vulnerability in the long run. However, education, patents, and domestic credit to the private sector positively influence adaptation. Hence, the selected countries' governments must encourage renewable energy consumption with a special focus on municipal solid waste, which is abundant in selected developing countries. [ABSTRACT FROM AUTHOR]

The increasing frequency of extreme climate events may significantly alter the species composition, structure, and functionality of ecosystems, thereby diminishing their stability and resilience. This study draws on temperature and precipitation data from 53 meteorological stations across Mongolia, covering the period from 1983 to 2016, along with MODIS normalized difference vegetation index (NDVI) data from 2001 to 2016. The climate anomaly method and the curvature method of cumulative NDVI logistic curves were employed to identify years of extreme climate events and to extract the start of the growing season (SOS) in Mongolia. Furthermore, the study assessed the impact of extreme climate events on the SOS across different vegetation types and evaluated the sensitivity of the SOS to extreme climate indices. The study results show that, compared to the multi-year average green-up period from 2001 to 2016, extreme climate events significantly impact the SOS. Extreme dryness advanced the SOS by 6.9 days, extreme wetness by 2.5 days, and extreme warmth by 13.2 days, while extreme cold delayed the SOS by 1.2 days. During extreme drought events, the sensitivity of SOS to TN90p (warm nights) was the highest; in extremely wet years, the sensitivity of SOS to TX10p (cool days) was the strongest; in extreme warm events, SOS was most sensitive to TX90p (warm days); and during extreme cold events, SOS was most sensitive to TNx (maximum night temperature). Overall, the SOS was most sensitive to extreme temperature indices during extreme climate events, with a predominantly negative sensitivity. The response and sensitivity of SOS to extreme climate events varied across different vegetation types. This is crucial for understanding the dynamic changes of ecosystems and assessing potential ecological risks. [ABSTRACT FROM AUTHOR]

Under the global warming, the research on ecological effects caused by extreme climate events has received widespread attention. Based on a total of 913 literatures collected by the China National Knowledge Infrastructure (CNKI) and the Web of Science Core Collection database from 2000 to 2020, CiteSpace software was applied to visualize and analyze the current research status, progresses and trends of ecological effects caused by extreme climate events. The results showed that the number of publications in this field experienced three phases: slow growth, steady growth, and rapid growth. The number of publications in China was seriously insufficient and relatively scattered compared with that in foreign countries over the same period. The institutions and authors with the highest publications were the Chinese Academy of Sciences and Beierkuhnlein Carl, respectively. Keywords with high frequency of appearance included "climate change", "drought", "response", "temperature", and "extreme climate". Current research on the ecological effects of extreme climate events mainly tends to focus on the impacts of extreme drought, extreme precipitation and extreme temperature on terrestrial ecosystems. The carbon cycle, resistance and stability, sensitivity and dynamic evolution of ecosystems under extreme climate have been research hotspots in recent years. In the future, it is necessary to standardize the terminology related to extreme climate events and to carry out long-term ecological effects research on discrete and compound extreme climate eventsusing new techniques methods. [ABSTRACT FROM AUTHOR]

The small Mediterranean islands, unique geographical places where coastlines and mountains converge due to volcanic genesis, are among the most threatened environments on Earth. Their marginality, which has historically led to their use as places of detention and punishment, coupled with the extreme climate and rugged geomorphology shaped by terracing practices, has resulted in the loss of systematic land management. This loss stems from the abandonment of cropland in favor of alternative activities and migrations, impacting essential ecosystem services such as the water cycle, soil fertility, and the cultural landscape. The need to counteract the land degradation in these vulnerable areas has been acknowledged for some Mediterranean small islands, including the UNESCO heritage site of Stromboli in the Aeolian Islands, Sicily, Italy—an especially captivating location due to its active volcano. The agricultural abandonment on terraces, intensively cultivated with olives groves and vineyards until the mid-20th century, has rendered the area highly fragile and susceptible to risks such as fires and soil erosion, particularly as a consequence of extreme weather events, as proven in 2022, which saw a destructive fire followed by storms. To mitigate the negative effects of hydrogeological disruptions, the implementation of integrated landscape management—managing ecosystems at the landscape level—has been proposed. Specifically, an agroforestry intervention, coupled with the restoration of dry stone walls, the shaping of soil slopes by recovering the traditional ecological knowledge (TEK), and the design of water-collecting devices incorporated with the traditional hydraulic knowledge, may be proposed as a strategic approach to minimize the soil erosion risks, adapt to climate change, and extensively restore the use of traditional agrobiodiversity to support the local economy and tourism. A pilot intervention by local stakeholders based on these principles is described as an emblematic agrobiodiversity-based landscape design project in a vulnerable area, aiming at the preservation of the cultural landscapes of the small Mediterranean islands. [ABSTRACT FROM AUTHOR]

In addition to greater precipitation on extreme days of precipitation, preceding and succeeding precipitation (PSP) is often an objective component of flooding in the mid–lower reaches of the Yangtze River Basin (MLRYRB). In this study, focused on the temporal distribution pattern of precipitation, the concept of an extreme precipitation event (EPE), defined as a consecutive precipitation event having at least one daily precipitation extreme, is proposed to consider PSP in an extreme event. We analyzed the spatiotemporal variation of four types of EPEs based on daily data obtained from 130 monitoring stations covering 1960–2019. Extreme precipitation increased significantly over the last 60 years (p < 0.01). The frequency and precipitation amount of single-day EPEs accounted for only 13% and 21%, respectively, while multi-day continuous EPE types that are associated with PSP accounted for 87% and 79%, respectively, confirming the connotations of EPEs. The front and late EPEs under the 100-year return level reached 250 mm and 230 mm, respectively. Furthermore, climate warming could lead to significant increases in the frequency of single-day and late EPEs, particularly in the southern region. The EPE concept may be helpful in exploring disaster-causing processes under extreme weather, and it provides a theoretical basis for deriving the precipitation hazard chain, which is more applicable to basins with long precipitation durations. [ABSTRACT FROM AUTHOR]

The increased intensity and frequency of extreme climate events (ECEs) have significantly impacted vegetation phenology, further profoundly affecting the structure and functioning of terrestrial ecosystems. However, the mechanisms by which ECEs affect the end of the growing season (EOS), a crucial phenological phase, remain unclear. In this study, we first evaluated the temporal variations in the EOS anomalies in Northern China (NC) based on the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from 2001 to 2018. We then used event coincidence analysis (ECA) to assess the susceptibility of EOS to four ECEs (i.e., extreme heat, extreme cold, extreme wet and extreme dry events). Finally, we examined the dependence of the response of EOS to ECEs on background climate conditions. Our results indicated a slight decrease in the proportion of areas experiencing extreme heat and dry events (1.10% and 0.66% per year, respectively) and a slight increase in the proportion of areas experiencing extreme wet events (0.77% per year) during the preseason period. Additionally, EOS exhibited a delaying trend at a rate of 0.25 days/a during the study period. The susceptibility of EOS to ECEs was closely related to local hydrothermal conditions, with higher susceptibility to extreme dry and extreme hot events in drier and warmer areas and higher susceptibility to extreme cold and extreme wet events in wetter regions. Grasslands, in contrast to forests, were more sensitive to extreme dry, hot and cold events due to their weaker resistance to water deficits and cold stress. This study sheds light on how phenology responds to ECEs across various ecosystems and hydrothermal conditions. Our results could also provide a valuable guide for ecosystem management in arid regions. [ABSTRACT FROM AUTHOR]

Abstract Increases in the frequency, intensity, and duration of extreme climate events (ECEs) are already impacting ecosystems, with many of the strongest effects associated with high‐elevation areas. Most research on the ecological impacts of climate change has focused on climatic averages, which might differ from ECEs. Rhododendron, a diverse genus of alpine and subalpine woody plant, plays a crucial role in ecosystem stability and biodiversity in the biodiversity hotspots of the Himalayas and Hengduan Mountains. Here, we compared the predicted impacts of average climate with those including ECEs on 189 Rhododendron species in China for the historical period (1981–2010) and the future period (2071–2100) under two emissions scenarios (SSP2‐4.5 and SSP5‐8.5). We analyzed changes in suitable habitat and patterns of species richness, weighted endemism, and phylogenetic diversity, identifying areas of coinciding high‐risk as priority conservation areas. Inclusion of ECEs altered the projected areas of suitable habitat across all species from an increase of over 3% to a decrease exceeding 10%, with the distribution of most Rhododendron species strongly influenced by extremes of drought and high temperatures. We found fewer than 18% of high‐risk areas of diversity loss were currently protected, with priority conservation areas mainly located in the Daxue, Daliang, Wumeng, and Jade Dragon Snow Mountains, as well as in the Nyingchi. We suggest inclusion of ECEs is critical when projecting changes in alpine and subalpine species distributions for effective conservation planning for climate change.

Climate change leads to extreme climate events that result in frequent wildfires that cause numerous adverse societal impacts. Public Safety Power Shutoffs, adopted by utilities to minimize the risk of wildfires, pose many challenges to electricity consumers. Microgrids, have been proposed to improve the resilience of energy infrastructure during wildfire events for vulnerable communities. However, a comprehensive techno-economic and environmental assessment of the potential of such energy systems have not been performed. To address this research gap, the present study introduces a modeling framework, consisting of (1) clustering algorithms that identify the communities based on building footprint data, fire hazard severity, and renewable energy potential; (2) a building simulation model to quantify the energy demand; and (3) an energy system optimization model to assist the Microgrid design. A novel optimization tool was introduced to model Microgrids in wildland-urban interface, and subsequently, a comprehensive assessment was performed, focusing on seven localities from California, United States, with different climatic conditions. The study reveals that Microgrids can keep the average levelized energy cost and annual Public Safety Power Shutoffs below $0.3/kilowatt-hour (kWh) and 2%–3% (of the annual energy demand), respectively. Furthermore, renewable energy penetration levels can be maintained above 60% of the annual energy demand. Therefore, Microgrid may become an attractive solution to reduce the adverse impacts of wildfires and enhance the resilience of energy infrastructure. However, the study reveals that Microgrid cannot completely eliminate the Public Safety Power Shutoffs. The levelized cost and renewable energy generation curtailments (waste of renewable energy) become notably high when attempting to eliminate Public Safety Power Shutoffs completely. A notable reduction in energy storage cost is essential to achieve zero Public Safety Power Shutoffs, and this is expected with the evolution of energy storage technologies. The present study recommends Microgrids for communities affected by wildfires to enhance the resilience of energy infrastructure and protect the health and safety of residents. The modeling framework and optimization tool developed in this study can be used by stakeholders and their consultants to inform design and optimization of Microgrids for investment decision making.

This study examines the relationship between institutional trust from an individual and societal perspective and perceived corruption and climate attitudes of individuals in Latin America. To this end, multilevel modeling was used to test whether the attitudes of individuals from 285 regions of Latin America are influenced by these constructs. Based on the results, it was found that in contrast to studies in developed countries, where institutional trust is positively associated with pro-climate attitudes, in Latin America institutional trust acts as an inhibiting factor and is inversely related to climate attitudes. Furthermore, the perception of corruption in public institutions was also identified as a factor inhibiting collective action to combat climate change. Moderation analysis revealed that individuals' level of education significantly influences this relationship, with a notable difference in climate attitudes between individuals with low and high levels of trust, especially among those with less education. These findings highlight the importance of taking regional specificities into account when examining the relationship between institutional trust, perceptions of corruption, and climate attitudes, and underscore the need for public policies that promote transparency and accountability of institutions to foster effective collective action on climate change. [ABSTRACT FROM AUTHOR]

Climate change affects biodiversity in a variety of ways, necessitating the exploration of multiple climate dimensions using appropriate metrics. Despite the existence of several climate change metrics tools for comparing alternative climate change metrics on the same footing are lacking. To address this gap, we developed 'climetrics' which is an extensible and reproducible R package to spatially quantify and explore multiple dimensions of climate change through a unified procedure. Six widely used climate change metrics are implemented, including 1) standardized local anomalies; 2) changes in probabilities of local climate extremes; 3) changes in areas of analogous climates; 4) novel climates; 5) changes in distances to analogous climates; and 6) climate change velocity. For climate change velocity, three different algorithms are implemented in the package including; 1) distanced‐based velocity ('dVe'); 2) threshold‐based velocity ('ve'); and 3) gradient‐based velocity ('gVe'). The package also provides additional tools to calculate the monthly mean of climate variables over multiple years, to quantify and map the temporal trend (slope) of a given climate variable at the pixel level, and to classify and map Köppen‐Geiger (KG) climate zones. The 'climetrics' R package is integrated with the 'rts' package for efficient handling of raster time‐series data. The functions in 'climetrics' are designed to be user‐friendly, making them suitable for less‐experienced R users. Detailed descriptions in help pages and vignettes of the package facilitate further customization by advanced users. In summary, the 'climetrics' R package offers a unified framework for quantifying various climate change metrics, making it a useful tool for characterizing multiple dimensions of climate change and exploring their spatiotemporal patterns. [ABSTRACT FROM AUTHOR]

This paper examines the linear relationship between climate events in the La Plata Basin (LP) from 1980 to 2018 and atmospheric moisture transport from major sources using a Lagrangian approach. The standardized precipitation evapotranspiration index (SPEI-1) was utilized to assess climate events, as monthly water balance variations may be related to changes in atmospheric moisture transport. A total of 49 dry and 46 wet events were identified through sequences of negative and positive SPEI-1 values, respectively. Lagrangian analysis tracked changes in moisture uptake and supply from sources to the LP during these events. Simple linear regression analysis revealed a relationship between moisture transport from the Amazonas (AM), North Atlantic (NA), and Tocantins (TO) basins and the severity and duration of climate events. Increased moisture supply from the São Francisco basin (SF) and Eastern Brazil oceanic (EBO) sources intensified the duration and severity of wet events. Peak wet events were linked to increased moisture supply from the northern South America basins (AM, NA, and TO), while peak droughts were related to decreased moisture uptake from eastern sources (TO, SF, and EBO). Our findings highlight how the water balance in distant regions affects the LP via moisture transport, emphasizing the need for interconnected adaptive strategies. [ABSTRACT FROM AUTHOR]

Saline lakes contributions to the carbon cycle is crucial to the Qinghai‐Tibetan Plateau (QTP) carbon budget. Here, based on the 8‐year direct measurement of CO2 flux over the Qinghai Lake (QHL) and 83 collected CO2 flux data estimated by pCO2 sampling from 45 lakes over the QTP, we identified the interannual variations of CO2 flux and its response to the extreme climate events. Results showed: (a) the QHL CO2 absorption weakened in the spring, autumn and winter and turn to CO2 emissions in the summer during 2013–2020; (b) with higher Ts and less precipitation, coupling of positive Pacific Decadal Oscillation (PDO) and El Niño enhanced the summer CO2 emissions; and (c) the PDO and ENSO had obvious superposition effect on the decrease of CO2 absorption in autumn. Our results show the potential mechanism of lake CO2 flux responses to extreme climate and further defines the significance of the QTP carbon budget and cycling. Plain Language Summary: The CO2 flux at the water‐air interface is especially important since it directly affects the accurate evaluation of the global carbon budget. However, lacking of long‐term continuous observation data left an undeniable gap on the interannual variations of CO2 flux and its respond to extreme climate events (the El Niño‐Southern Oscillation and Pacific Decadal Oscillation: ENSO and PDO) in saline lakes, although they are globally significant. Here, based on the 8‐year direct measurement of CO2 flux by eddy covariance system over the QHL and 83 collected CO2 flux data estimated by pCO2 sampling from 45 lakes over the QTP. This study found a weakening of CO2 absorption in the spring, autumn and winter, and an enhancing of CO2 emissions in the summer in QHL during 2013–2020, and first reported a notable transformation of carbon sink to source of saline lakes for responding to the extreme climate events. Moreover, the enhancing of CO2 emissions may be stronger in saline lakes than that in fresh lakes over QTP. The results firstly show the potential mechanism of lake CO2 flux responses to extreme climate and further defines the significance of the QTP carbon budget and cycling. Key Points: The QHL CO2 absorption weakened in spring, autumn and winter, and even turn to CO2 emissions in summer during 2013–2020In‐phase PDO and El Niño events enhanced the summer CO2 emissions in saline lake over QTPRising in Ts and decreasing in precipitation dominated the CO2 variations [ABSTRACT FROM AUTHOR]

The escalating frequency and intensity of extreme climate events pose significant challenges in the context of the climate crisis, leading to substantial human and economic losses. This study aims to assess trends and disruptions in extreme climate indicators, focusing on precipitation and air temperature, within the watersheds of eastern Paraná state. Data from 1976 to 2015 were used, ensuring record failure rates below 5%. Trend analysis employed the extreme climate indicators developed by the Canadian Meteorological Service and the Mann-Kendall test, while discontinuities in the historical series were identified using normality tests (Pettitt, SNHT, and Buishand). Results revealed increasing trends in annual precipitation totals (PRCPTOT), the annual total of rainfall exceeding 95% of percentiles (R95p), and, notably, the index of daily rainfall concentration (SDII). The Upper Ribeira watershed displayed the highest frequency of trends associated with SDII. Moreover, widespread upward trends in air temperature were observed, particularly in Curitiba, where the average annual minimum temperature rose by 1.8 °C. Notably, many discontinuities in the historical climatic series were detected between the late 1980s and early 2000s. This research provides a comprehensive understanding of the modifications in extreme climate indicators in the study area, emphasizing significant trends of more heavy and concentrated rainfall and a robust increase in average air temperature. [ABSTRACT FROM AUTHOR]

[Objective] This study was aimed to understand the spatiotemporal changes in extreme climate and its influence on vegetation. [Methods] Based on daily meteorological data (1960—2020) from 115 weather stations in the Qinling-Daba mountains (QBMs) and surrounding areas and satellite-derived normalized difference vegetation index (NDVI), the spatiotemporal variation characteristics of the NDVI in the QBMs and its response to 19 extreme climate indices were analyzed. Geographic detector was used to identify the contribution rate of extreme climate indices and their influence on the NDVI. [Results] (1) The NDVI significantly increased in the majority of the QBMs (80.34%) and decreased in only a few regions (1.09%) from 2000 to 2020. The interannual change rate in the study area was approximately 0.03/10 a. (2) Noticeable warming was observed in the QBMs from 1960 to 2020, with the temperature increasing more at night than during the day, and regions with a larger change in extreme temperature events were mostly found in the Western Qinling Mountains (WQMs). During the study period, extreme precipitation events showed weak changes, extreme precipitation intensity increased in the southwestern QBMs, while in the eastern QBMs, extreme precipitation intensity decreased but extreme precipitation frequency increased. (3) Extreme precipitation events were the main factor affecting NDVI in the west Qinling region, while extreme temperature events were the main factor affecting NDVI in the Qinling and Daba mountain regions; the impact of extreme climate events on NDVI was not independent, and the interaction between extreme climate indices enhances the impact of a single factor on NDVI in a double-factor or nonlinear way. [Conclusion] The spatiotemporal changes in extreme climate and its influence on vegetation were clarified, which could establish scientific evidence for the protection and restoration of vegetation in the QBMs in response to global climate change.

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Background: Seagrass, a vital primary producer habitat, is crucial for maintaining high biodiversity and offers numerous ecosystem services globally. The increasing severity and frequency of marine heatwaves, exacerbated by climate change, pose significant risks to seagrass meadows. Aims: This study acknowledges the uncertainty and variability of marine heatwave scenarios and aims to aid managers and policymakers in understanding simulated responses of seagrass to different durations, frequencies and recurrence gaps of marine heatwaves. Materials and Methods: Using expert knowledge and observed data, we refined a global Dynamic Bayesian Network (DBN) model for a specific case study on Halophila ovalis in Leschenault Estuary, Australia. The model evaluates the potential impact of marine heatwaves on seagrass resilience, examining stress resistance, recovery and extinction risk. Results: Simulations of different marine heatwave scenarios reveal significant impacts on seagrass ecosystems. Scenarios ranged from 30‐ to 90‐day heatwaves, with longer durations causing more significant biomass decline, reduced resistance, higher extinction risk and prolonged recovery. For instance, recovery time may increase from 18 to 26 months with four 60‐day and from 24 to 47 months with four 90‐day marine heatwave events. Increasing the frequency of marine heatwaves from one to four annual events, with no gaps between occurrences, could raise extinction risk from 11% to 55% for 60‐day events and from 17% to 83% for 90‐day events. However, introducing gaps between heatwaves enhanced resilience, with spaced events showing lower extinction risks and quicker recovery than consecutive yearly events. Discussion: The study demonstrates the DBN model's utility in simulating the impact of marine heatwaves on seagrass, providing tools for risk‐informed assessment of management and restoration efforts. While these simulations align with existing research on temperature impacts on seagrass, they are not empirical. Conclusion: Further research is necessary to expand our understanding of climate change effects on seagrass ecosystems, guide policy and develop strategies to strengthen marine ecosystem resilience. [ABSTRACT FROM AUTHOR]

Forest ecosystems within national parks are threatened by various biotic and abiotic factors. To determine the causes of the desiccation and death of trees in mixed coniferous and deciduous forests of Tara National Park (TNP), Serbia, we monitored defoliation and mortality of individual trees in permanent experimental plots. Data on the desiccation of a large number of trees were gathered by determining the total volume of dry trees and areas of forests under drying stress. The two sets of data were combined to determine the impact of climatic events, primarily drought periods, on the desiccation of forests. Combining data from the International Co-operative Program on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) with TNP data helped relate forest desiccation to climate events. Key climate signals were identified by monitoring tree defoliation changes in two permanent experimental plots, and then assessed for their influence on tree desiccation in the entire national park. The standardized precipitation evapotranspiration index (SPEI) was used for a more detailed analysis of the drought period. Despite the lack of climate data for a certain period, the SPEI index revealed a link between climate variables and the defoliation and desiccation of forests. Furthermore, the desiccation of trees was preceded by a long drought period. Although mixed coniferous-deciduous forests are often considered less vulnerable to natural influences, this study suggests that forest ecosystems can become vulnerable regardless of tree species composition due to multi-year droughts. These findings contribute to a better understanding of important clues for predicting possible future desiccation of forests. Continuous monitoring of the state of forests and of more permanent experimental plots in national parks could provide better quality data and timely responses to stressful situations. [ABSTRACT FROM AUTHOR]

The small Mediterranean islands, unique geographical places where coastlines and mountains converge due to volcanic genesis, are among the most threatened environments on Earth. Their marginality, which has historically led to their use as places of detention and punishment, coupled with the extreme climate and rugged geomorphology shaped by terracing practices, has resulted in the loss of systematic land management. This loss stems from the abandonment of cropland in favor of alternative activities and migrations, impacting essential ecosystem services such as the water cycle, soil fertility, and the cultural landscape. The need to counteract the land degradation in these vulnerable areas has been acknowledged for some Mediterranean small islands, including the UNESCO heritage site of Stromboli in the Aeolian Islands, Sicily, Italy—an especially captivating location due to its active volcano. The agricultural abandonment on terraces, intensively cultivated with olives groves and vineyards until the mid-20th century, has rendered the area highly fragile and susceptible to risks such as fires and soil erosion, particularly as a consequence of extreme weather events, as proven in 2022, which saw a destructive fire followed by storms. To mitigate the negative effects of hydrogeological disruptions, the implementation of integrated landscape management—managing ecosystems at the landscape level—has been proposed. Specifically, an agroforestry intervention, coupled with the restoration of dry stone walls, the shaping of soil slopes by recovering the traditional ecological knowledge (TEK), and the design of water-collecting devices incorporated with the traditional hydraulic knowledge, may be proposed as a strategic approach to minimize the soil erosion risks, adapt to climate change, and extensively restore the use of traditional agrobiodiversity to support the local economy and tourism. A pilot intervention by local stakeholders based on these principles is described as an emblematic agrobiodiversity-based landscape design project in a vulnerable area, aiming at the preservation of the cultural landscapes of the small Mediterranean islands.

The increasing intensity and frequency of extreme climate events have made improving the adaptability to extreme climate events a strategic imperative for manufacturing companies. This paper investigates whether manufacturing enterprises increase green technology innovation affected by different extreme climate events. Based on panel data of Chinese listed manufacturing enterprises, we show that extreme precipitation events can positively promote green technology innovation, yet extreme temperature events do not. Heterogeneity analyses suggest that the effect of extreme precipitation events on green technology innovation is more significant for non-state-owned enterprises, poor performance enterprises, and high R&D intensity enterprises than other enterprises. Furthermore, the facilitating effect of extreme precipitation events on green technology innovation is merely temporary.

This study investigates, for the first time, the urbanization effect (UE) on local extreme climate events in Urumqi, China, based on 22 indices of climate extremes, which are calculated with daily observation data from 1976 to 2018. These analyses reveal a pronounced nocturnal urban heat island (UHI) effect and a daytime urban cold island (UCI) effect. Due to Urumqi's arid climate background, the UCI effect is considered a unique feature of the UE, which significantly differs from those in eastern and northern China. The UE on the TR20 index (number of days with minimum daily temperature exceeding 20 °C) reached 5.22 d/10a, indicating that urbanization has led to a fast increase in the number of hot nights in Urumqi. The absolute averaged UE on the indices measuring the frequency of warm events is about twice as large as that on the indices measuring the frequency of cold events, while that on the indices measuring the intensity of warm events is about one third of that on the indices measuring the intensity of cold events. The highest averaged urbanization contributions (UCs) to the extreme warm and cold events are represented by the frequency indices and the intensity indices, respectively, while those contributing to the extreme precipitation events are represented by the duration indices. Moreover, urbanization probably exacerbates the degree of wetting in the overall "warming and wetting" climate trend of the region. These findings can be seen as new evidence to provide scientific basis for further investigation of the UE on climate changes in arid regions. [ABSTRACT FROM AUTHOR]

The increasing intensity and frequency of extreme climate events have made improving the adaptability to extreme climate events a strategic imperative for manufacturing companies. This paper investigates whether manufacturing enterprises increase green technology innovation affected by different extreme climate events. Based on panel data of Chinese listed manufacturing enterprises, we show that extreme precipitation events can positively promote green technology innovation, yet extreme temperature events do not. Heterogeneity analyses suggest that the effect of extreme precipitation events on green technology innovation is more significant for non-state-owned enterprises, poor performance enterprises, and high R&D intensity enterprises than other enterprises. Furthermore, the facilitating effect of extreme precipitation events on green technology innovation is merely temporary. [ABSTRACT FROM AUTHOR]

Global warming and extreme climate events (ECEs) have grown more frequent, and it is essential to investigate the influences of ECEs on vegetation in the Yellow River Basin (YRB) and other environmentally fragile areas. This study was based on data from 86 meteorological stations in the YRB for the period 2000–2020. Twenty-five extreme climate indices (ECIs) were chosen, encompassing four dimensions: extreme value, intensity, duration, and frequency. The trend analysis approach was used to examine the spatiotemporal characteristics of extreme climate conditions. Additionally, geographical detectors and Pearson correlation analysis methods were employed to quantitatively assess the influence of ECEs on the Normalized Difference Vegetation Index (NDVI). The Multiscale Geographically Weighted Regression (MGWR) method was adopted to analyze the regression of twenty-five ECIs. The findings revealed the following: (1) Over the last 21 years, there has been a distinct rise in both the extreme precipitation indices (EPIs) and the extreme temperature indices (ETIs). (2) The spatial distribution of the NDVI throughout the year displayed the characteristic of being high in the south and low in the north. The annual NDVI demonstrated a noteworthy increase at a rate of 0.055/decade, with the enhancement encompassing an extensive area of 87.33%. (3) The investigation revealed that EPIs, including PRCPTOT, R10mm, CWD, R95p, and CDD, had explanatory values surpassing 0.4. This implied that the intensity, frequency, and duration of extreme precipitation played pivotal roles in steering vegetation alterations in the YRB. (4) The correlation between the EPIs and vegetation was greater than the ETIs. Grassland meadows exhibited greater sensitivity to precipitation than woody plants. The EPIs (excluding CDD and SDII) and the ETIs (TXn) displayed a substantial positive correlation with the NDVI in regions hosting grasslands, broadleaf forests, and shrubs. Desert vegetation and cultivated plants were less affected by ECEs. This study underscores the importance of the interplay between extreme climate and vegetation in the YRB. Additionally, it provides a scientific basis for formulating environmental safeguarding strategies. [ABSTRACT FROM AUTHOR]

The objective is to analyze in the period 1990 to 2019 the effects of climate and the tendency of individuals to leave a territory, measuring the weight of precipitation or lack thereof in the Central American Dry Corridor. To study this process, a stochastic frontier model was developed. As a primary result, it was found that there is a greater tendency to migrate when a drought occurs, understanding it as an extreme event for the environment and society. This tendency is evaluated with a system that includes series of controls such as other extreme weather events such as El Niño (ENSO) and hurricanes, vio lence levels, economy and exchange rate, which leads to the conclusion that drought above any other climatic event motivates the population to migrate. These findings contribute to the formulation of prevention, mitigation and resilience policies [ABSTRACT FROM AUTHOR]

Climate change has many negative effects on the viticulture sector, as it does in all sectors. In recent years, global climate change has also shown its effect in the form of sudden climatic events. There is an urgent need to develop preventive/protective activities for all plant species in order to prevent the increasing world population from being negatively affected by many negative consequences of climate change such as increasing temperatures, drought, floods, and sudden climatic events. Grape industry is among the sectors that feel the negative effects of climate change the most, and this effect is increasing every year. Along with global warming, there are also important problems in accessing water. Particularly, there is a need to develop cultivars that are more resistant to drought stress and to make applications that will protect grapevine plants from drought stress. One of the most important issues to be overcome is to develop new cultivars that can withstand different stress conditions and to use them more in production. In addition, environmental and human health awareness is increasing day by day. Adaptation strategies to be taken against the negative effects of climate change and the studies to be carried out, as well as the use of new environmentally friendly varieties (requiring less input costs) to be developed in accordance with the sustainable agriculture model, will make significant contributions to protecting both the environment and human health. [ABSTRACT FROM AUTHOR]

Despite the increased frequency of extreme climate events including their significance in Nepal's socio-economy, climate studies have seldom considered extremes, and even fewer have considered them in combination with temperature and precipitation. This study aimed at examining the trend of climate variables in Gandaki Province, Nepal. Daily temperature and precipitation data of five stations between 1990 and 2020 were analyzed. Modified Mann–Kendall and Sen's slope methods were used to detect trend and magnitude. The Mann–Whitney–Pettitt test was used to detect abrupt changes, and the Pearson correlation coefficient was used to find the correlation. The result showed an increasing trend and a significant abrupt change in the maximum temperature for all stations. A decreasing trend in the minimum temperature was observed in the Himalayas and the Hill region, whereas an increasing trend was seen in Siwalik and Terai regions. The Jomsom station, however, behaved differently by showing an increasing trend in precipitation and the number of rainy days. The majority of the temperature indices showed an increasing trend unlike precipitation indices, which showed a mixed result. The maximum five-day precipitation and consecutive dry days showed a significant positive correlation with altitude. The results indicate an increase in the frequency and intensity of extreme climate conditions in Gandaki Province. HIGHLIGHTS The paper analyzes the trend in the mean and the extreme value of temperature and precipitation.; High altitude region could experience an extreme climate condition with frequent heavy rainfall and drought periods, while Siwalik and Terai regions could experience frequent drought periods.; The results will help the relevant stakeholders to understand the change happening in the Gandaki Province.;

The resilience of rice production to floods is a crucial aspect of agricultural development in flood-prone regions. However, little is known about the farming practices and challenges of rice farmers in two river basins in Tanzania: Lower-Rufiji and Kilombero, where rice is the main crop grown. This study aimed to investigate the experiences of farmers in these two rice-growing floodplains regarding the impact of floods on lowland rice production and farmer livelihoods, and the strategies they use to cope with floods. The study used a mixed-methods approach that involved household surveys, key informant interviews, and transect walks to collect data from 180 rice farmers and 14 experts and community leaders. The data analysis revealed that floods were the dominant stressor affecting rice production, occurring mostly during the long rainy season and experienced by all farmers in both locations. Floods not only caused significant crop losses, especially in Lower- Rufiji where farmers reported losing between 75 and 100% of their yield in cases of extreme floods, but also made it difficult to establish and manage crops, leading to crop land abandonment. Floods also affected the livelihoods of rice farmers by forcing them to abandon, rent, or sell their farms. Coexistence of floods with other biotic and abiotic stresses such as crop diseases and droughts also limited the use of short maturing high yielding rice varieties. Farmers have adopted on-farm strategies such as adjusting planting schedules, using different varieties of rice, changing to other crops or activities after the floods to cope with floods, but these practices face numerous challenges. The study recommends the development of early warning systems, breeding for flood-tolerant rice varieties, introgression of tolerance traits to multiple stresses and improving crop establishment methods to enhance the resilience of farmers to floods and other extreme climate events. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to clarify the high incidence areas and time periods of extreme climate events within a continuous spatiotemporal range in the Chinese region, enhance understanding of the occurrence patterns of extreme climate events in China, and provide an important scientific basis for human society to mitigate and adapt to climate change. [Methods] We analyzed the spatiotemporal distribution characteristics of different types of extreme climate events in China from 1981 to 2015, using both the 1.5 times standard deviation and the continuous spatiotemporal extreme event analysis method based on the temperature and precipitation data of CRUNCEP. [Results] There were different regional patterns of extreme climate events in those years experiencing extreme annual precipitation and air temperature events for the whole country. For the years with extreme heavy annual precipitation in 1983, 1998 and 2012, extreme heavy annual precipitation events mainly occurred in the middle and lower reaches of the Yangtze River, the upper reaches of the Yangtze River and eastern Inner Mongolia, and the middle and lower reaches of the Yangtze River and Inner Mongolia, respectively. The national extreme drought event existed in 1986 and 2011. Most regions of the country were drier than that in normal years in 1986, while the extreme drought events mainly occurred in the subtropical and tropical monsoon climate region in 2011. The extreme high temperature and extreme low temperature events occurred in 1998 and 2012, respectively. The mean air temperature in most parts of the country was higher than usual in 1998. The extreme low temperature events in 2012 occurred frequently in the temperate continental climate region. During 1981—2015, 46% of extreme heavy precipitation events occurred in 2001—2015. There were 13% of extreme drought events which occurred in the subtropical tropical monsoon climate region from 2001 to 2015. Extreme high temperature events occurred frequently in 1991—2000（42%） and 2001—2015（43%）. There were 21% of extreme low temperature events which occurred in the temperate continental climate region from 2001 to 2015. The proportion of compound extreme climate events had a decadal increasing trend. The extreme low temperature and heavy precipitation events had the highest proportion（34%）, and concentrated in 2001—2015（23%）. [Conclusion] That single-factor extreme climate events and composite extreme climate events have strong differences in the four major climate zones in China. In the future, it is necessary to strengthen the analysis of the spatiotemporal distribution characteristics of extreme climate events on short time scales such as day and month in regions of China. [ABSTRACT FROM AUTHOR]

The Canadian Prairies are associated with high natural hydroclimatic variability including the frequent periodic occurrence of droughts and pluvials. These extremes carry various risks including significant damage to the economy, environment and society. The well-documented level of damage necessitates further risk assessment and planned reductions to vulnerability, particularly in light of a warming climate. A logical starting point involves awareness and information about the changing characteristics of such climate extremes. We focus on the compound occurrence of droughts and pluvials as the risks from this type of event are magnified compared to the hydroclimatic extremes in isolation. Compound droughts and pluvials (CDP) are drought and pluvial events that occur in close succession in time or in close proximity in area. Also, research on CDP is limited even for the worldwide literature. Therefore, the purposes of this paper are to synthesize recent literature concerning the risks of CDP, and to provide examples of past occurrences, with a focus on the Canadian Prairies. Since literature from the Prairies is limited, global work is also reviewed. That literature indicates increasing concern and interest in CDP. Relationships between drought and pluvials are also characterized using the SPEI Global Monitor for the Prairies, emphasizing the recent past. Research mostly considers drought and pluvials as separate events in the Prairies, but is integrated here to characterize the relationships of these extremes. The spatiotemporal patterns showed that several of the extreme to record pluvials were found to be closely associated with extreme droughts in the Prairies. The intensities of the extremes and their dry to wet boundaries were described. This is the first research to explore the concept of and to provide examples of CDP for the Prairies and for Canada. Examples of CDP provide insights into the regional hydroclimatic variability. Furthermore, most literature on future projections strongly suggests that this variability is likely to increase, mainly driven by anthropogenic climate change. Therefore, improved methods to characterize and to quantify CDP are required. These findings suggest means of decreasing vulnerability and associated damages. Although the study area is the Canadian Prairies, the work is relevant to other regions that are becoming more vulnerable to increasing risks of and vulnerabilities to such compound extremes. [ABSTRACT FROM AUTHOR]

Abstract Background Global climate change poses a significant challenge in contemporary society, particularly affecting vulnerable populations like small farmers residing in arid and semiarid regions. This study aims to investigate the perception of health risks and adaptive responses in the semiarid region of Northeast Brazil (NEB). Four questions were formulated: (1) How do socioeconomic factors influence the perception of health risks during extreme climate events? (2) How do socioeconomic factors impact the adoption of adaptive responses to mitigate health risks during extreme weather events? (3) How does the perceived risk level affect the utilization of adaptive responses? (4) What is the influence of extreme climate events on the perceived risks and the adoption of adaptive responses? Method The research was conducted in the rural community of Carão, situated in the Agreste region of the State of Pernambuco, NEB. Semi-structured interviews were conducted with 49 volunteers aged 18 and above. The interviews aimed to gather socioeconomic information, including sex, age, income, access to healthcare services, family size, and education level. Additionally, the interviews explored the perceived risks and responses employed during different extreme climate events such as droughts or heavy rainfall. The perceived risks and adaptive responses data were quantified to address the research questions. Generalized linear models were employed to analyze the data for the first three questions, while the nonparametric Mann–Whitney test was used for the fourth question. Results The study found no significant differences in the level of perceived risk and adaptive responses between the two climate extremes. However, the quantity of adaptive responses was found to be directly influenced by the perceived risks, regardless of the type of extreme climate event. Conclusion The study concludes that risk perception is influenced by various complex factors, including socioeconomic variables, and plays a critical role in the adoption of adaptive responses during extreme climate events. The findings suggest that specific socioeconomic variables have a more pronounced influence on how individuals perceive and adapt to risks. Furthermore, the results indicate a cause-and-effect relationship between perceived risks and the generation of adaptive responses. These findings contribute to a better understanding of the factors shaping risk perception and provide valuable insights for future studies in regions prone to extreme climate events.

The resilience of rice production to floods is a crucial aspect of agricultural development in flood-prone regions. However, little is known about the farming practices and challenges of rice farmers in two river basins in Tanzania: Lower-Rufiji and Kilombero, where rice is the main crop grown. This study aimed to investigate the experiences of farmers in these two rice-growing floodplains regarding the impact of floods on lowland rice production and farmer livelihoods, and the strategies they use to cope with floods. The study used a mixed-methods approach that involved household surveys, key informant interviews, and transect walks to collect data from 180 rice farmers and 14 experts and community leaders. The data analysis revealed that floods were the dominant stressor affecting rice production, occurring mostly during the long rainy season and experienced by all farmers in both locations. Floods not only caused significant crop losses, especially in Lower-Rufiji where farmers reported losing between 75 and 100% of their yield in cases of extreme floods, but also made it difficult to establish and manage crops, leading to crop land abandonment. Floods also affected the livelihoods of rice farmers by forcing them to abandon, rent, or sell their farms. Coexistence of floods with other biotic and abiotic stresses such as crop diseases and droughts also limited the use of short maturing high yielding rice varieties. Farmers have adopted on-farm strategies such as adjusting planting schedules, using different varieties of rice, changing to other crops or activities after the floods to cope with floods, but these practices face numerous challenges. The study recommends the development of early warning systems, breeding for flood-tolerant rice varieties, introgression of tolerance traits to multiple stresses and improving crop establishment methods to enhance the resilience of farmers to floods and other extreme climate events.

Understanding the response of vegetation to temperature extremes is crucial for investigating vegetation growth and guiding ecosystem conservation. North China is a vital hub for China's economy and food supplies, and its vegetation is highly vulnerable to complex heatwaves. In this study, based on remote sensing data, i.e., the normalized difference vegetation index (NDVI), spatio-temporal variations in vegetation and extreme high temperatures are investigated by using the methods of trend analysis, linear detrending, Pearson correlation and ridge regression. The impacts of extreme-high-temperature events on different vegetation types in North China from 1982 to 2015 are explored on multiple time scales. The results indicate that the NDVI in North China exhibits an overall increasing trend on both annual and monthly scales, with the highest values for forest vegetation and the fastest growth trend for cropland. Meanwhile, extreme-high-temperature events in North China also display an increasing trend. Before detrending, the correlations between the NDVI and certain extreme-high-temperature indices are not significant, while significant negative correlations are observed after detrending. On an annual scale, the NDVI is negatively correlated with extreme temperature indices, except for the number of warm nights, whereas, on a monthly scale, these negative correlations are only found from June to September. Grassland vegetation shows relatively strong correlations with all extreme temperature indices, while forests show nonsignificant correlations with the indices. This study offers new insight into vegetation dynamic variations and their responses to climate in North China. [ABSTRACT FROM AUTHOR]

Among several devastating natural hazards, flooding is a common and serious threat to society causing huge loss of lives, properties, and infrastructure throughout the world. The intensity and frequency of this extreme weather event are expected to increase due to significant changes in the present‐day climate and land use and land cover (LULC) pattern. India has a very systematic and organized structural program and policies but lacks proper implementations, and adverse effect of climate change and the extreme event goes on in society. This paper is an analysis of floods in India and hazards due to climate change and LULC change patterns. Three models, namely "Eco‐biogeography‐based optimization (EBO), Random forest (RF), and Support vector machine (SVM)" were used to obtain the final output to prepare a "Flood susceptibility map". The result was validated through the "Receiver operating characteristics (ROC)" with "Area under curve (AUC)" values. The future rainfall scenario has been estimated by considering the "General circulation models" through different "shared socioeconomic pathways (SSPs)". The values of AUC are 0.915 (EBO), 0.887 (RF), and 0.869 (SVM), respectively. After consideration of different SSPs, the result shows that there is an increasing tendency of flood hazards in the projected period. Among all the employed modelling approaches, the EBO model has notable potential in delineating the possible flood‐prone regions for effective flood planning and management. Decision‐makers can benefit from country‐specific information and regional planner to implement sustainable and long‐term measures to overcome this type of hazardous situation. [ABSTRACT FROM AUTHOR]

Much attention has been given to the change rule of a single extreme event, and there are few reports on comprehensive characteristics of multiple extreme events in a certain region. Based on the analyzes of annual frequency of extreme high temperature, extreme low temperature, extreme drought, extreme precipitation, and extreme typhoon events in China from 1961 to 2020, a multi extreme events composite risk grade index (MXCI) was constructed and applied to the comprehensive characteristics analyzes of multiple extreme events in China. The results show that the high value areas of MXCI were mainly located in southeast China and southwest China. Over the past 60 years, the MXCI has shown a decreasing trend in western China and most of southeastern China, and an increasing trend in the middle zone from southwest China to northeast China. Through comparative analysis, MXCI can objectively reflect the comprehensive characteristics of multiple extreme climate events in a region, which is helpful to understand regional extreme climate characteristics and effectively cope with extreme climate risks. [ABSTRACT FROM AUTHOR]

Quantifying the impacts of climate change on evapotranspiration (ET) and gross primary production (GPP) in the Dongting Lake Basin is essential for assessing water scarcity and implementing sustainable development strategies. Premised on actual measurements and remote sensing data from 47 stations, the impact of climate change on eco-hydrological parameters in the Dongting Lake Basin was analyzed in the present study using the BESS model (The Breathing Earth System Simulator), ridge regression analysis, stepwise regression model and time-lag analysis. The results reveal that: (1) the Dongting Lake Basin has been warm and arid over the last four decades, with the frequent occurrence of extreme climate events. Vegetation carbon sequestration capacity exhibited a slightly upward trend with 0.0081 g C m−2 d−1/year from 2000–2017. ET changed with rates of −3.309 mm/year, with possible risk conflicts between water demand and supply in the future. (2) The increasing temperature was the main driver of ET enhancement in the Dongting Lake Basin. Meanwhile, both temperature and precipitation were found to be the dominant drivers of GPP enhancement. The effect of temperature on GPP was found to be greater in the areas covered by crops and tree vegetation, and natural vegetation was more strongly influenced by precipitation than radiation. (3) Extreme temperature events have had a significant impact on evapotranspiration (ET) and gross primary production (GPP) in the Dongting Lake Basin. Specifically, the cold index in extreme temperature events was found to significantly affect ET, while the heat index in extreme temperature events significantly affected GPP. Additionally, both ET and GPP were found to respond to extreme precipitation events in the region. The results of the study established that vegetation is highly sensitive to temperature, especially temperature extremes, and that precipitation also has a stressful effect. Increasing temperatures and precipitation within a range benefit vegetation productivity. (4) In the Dongting Lake Basin, we found that different climatic factors produced different time lag effects on GPP and ET by time lag analysis. This study highlights the lag effects of climate factors and extreme climate events on eco-hydrological parameters. We suggest incorporating the effects into simulation models of eco-hydrological parameters. This will lead to a better understanding of the variation of eco-hydrological parameters under climate change. [ABSTRACT FROM AUTHOR]

The concept of the 'Capitalocene' draws attention to the origins of the climate crisis in capitalist dynamics, and specifically to the need for natural resources to be reproduced for less than their true cost if firms are to remain profitable. This insight suggests that the environmental crisis, manifested by extreme climate events, and the crisis in labour law, manifested by wage suppression and rising inequality, have the same root cause. Bringing production and reproduction back into balance will require changes of a structural kind to the global economy, and a rethinking of the law-nature nexus. [ABSTRACT FROM AUTHOR]

The roles of rainfall with various intensities in hydraulic erosion processes are obviously different. In-depth knowledge about the spatiotemporal variation in extreme rainfall erosivity is critical for soil erosion risk assessment and formulation of response measures. In the period of 1961–2020, more than 390,000 erosive rainfall data from 212 meteorological stations were collected to explore the erosion characteristics of different intensities of rainfall erosivity across southern China. The asymmetric characteristic of extreme rainfall erosion was analyzed and expressed by an asymmetric change index (ACI) defined in this study. Correlation analysis was applied to study the impact of global extreme climate events on the ACI. The results showed that different patterns of precipitation had evident asymmetric characteristics in rainfall erosivity, and fewer high-intensity precipitation events contributed to much higher total rainfall erosivity, particularly for rainstorms (≥100 mm). The ACI of the rainfall erosivity exhibited evident spatial heterogeneity; insignificant increasing trends were found in the ACIs for heavy rainfall, torrential, and rainstorm erosivities over the past 60 years. The change rate of ACI varied greatly on both monthly and interdecadal scales, and the ACI of rainstorms showed the maximum linear increasing trend on the long-time scale. There were significantly high correlations between the ACI and erosive rainfall days and the ACI and erosive rainfall (p < 0.01), and the correlation coefficients were relatively higher from May to October, where the precipitation was concentrated. Additionally, the El Niño-Southern Oscillation and tropical cyclones clearly influenced the spatiotemporal distribution of the ACI and rainfall erosivity but were limited to specific periods and regions. These results could provide a reference for extreme soil erosion event monitoring and control in southern China. [ABSTRACT FROM AUTHOR]

IntroductionThe rapid increase in sea-water temperatures and frequency of extreme thermal events have amplified the risk of functional extinction of Mediterranean species such as the endemic long-lived seagrass Posidonia oceanica. Because of the valuable ecological functions and ecosystem services the species provides, understanding the life-stage specific thermal vulnerability is crucial to accurately predict the consequences of current and future global climate change and to protect and conserve existing meadows.MethodsTo this end, here we report a study on the ontogeny-specific thermal sensitivity of important physiological functions (i.e. respiration and net production) of three different early life history stages of P. oceanica, namely seed, seedling (4-month-old individuals) and 16-month-old plantlet by measuring thermal performance curves (eleven temperatures treatments between 15-36°C with n=8).ResultsAll three stages examined showed photosynthetic activity during light exposure with similar optimal temperatures for both net and gross production. Gross photosynthesis increased with rising temperature up to 28-30°C, subsequently declining at higher temperatures until complete inhibition at 36°C. The metabolic response of seeds was found to be temperature-dependent up to 26°C, while respiration of seedlings and plantlets was almost stable up to 28-30°C, but increased markedly at higher temperatures, resulting in a negative whole-plant C balance at temperatures above 32°C. Overall, our results show that seedlings and plantlets tolerate a wider temperature range (15 - 32°C) than seeds, which experience metabolic and physiological dysfunction from 26-28°C onwards.DiscussionThese findings suggest that the impact of warming on recruitment in P. oceanica meadows may vary depending on the timing of marine heatwaves (i.e. mid-spring to mid-autumn) and provide useful knowledge to inform restoration programs using early life stages of the species. In conclusion, the study of physiological responses during the early life stages of species is key to identify life history stages that are particularly vulnerable to climate change, which is vital knowledge for ecosystem management and conservation.