Microrefugia and microclimate: Unraveling decoupling potential and resistance to heatwaves

Microrefugia, defined as small areas maintaining populations of species outside their range margins during environmental extremes, are increasingly recognized for their role in conserving species in the face of climate change. Understanding their microclimatic dynamics becomes crucial with global warming leading to severe temperature and precipitation changes. This study investigates the phenomenon of short-term climatic decoupling within microrefugia and its implications for plant persistence in the Mediterranean region of southeastern France. We focus on microrefugia's ability to climatically disconnect from macroclimatic trends, examining temperature and Vapor Pressure Deficit (VPD) dynamics in microrefugia, adjacent control plots, and weather stations. Our study encompasses both "normal" conditions and heatwave episodes to explore the role of microrefugia as thermal and moisture insulators during extreme events. Landscape attributes such as relative elevation, solar radiation, distance to streams, and vegetation height are investigated for their contribution to short-term decoupling. Our results demonstrate that microrefugia exhibit notable decoupling from macroclimatic trends. This effect is maintained during heatwaves, underscoring microrefugia's vital role in responding to climatic extremes. Importantly, microrefugia maintain lower VPD levels than their surroundings outside and during heatwaves, potentially mitigating water stress for plants. This study advances our understanding of microclimate dynamics within microrefugia and underscores their ecological importance for plant persistence in a changing climate. As heatwaves become more frequent and severe, our findings provide insights into the role of microrefugia in buffering but also decoupling against extreme climatic events and, more generally, against climate warming. This knowledge emphasizes the need to detect and protect existing microrefugia, as they can be integrated into conservation strategies and climate change adaptation plans.

Assessing combined effects of long-term exposure to copper and marine heatwaves on the reef-forming serpulid Ficopomatus enigmaticus through a biomarker approach

Sessile benthic organisms can be affected by global changes and local pressures, such as metal pollution, that can lead to damages at different levels of biological organization. Effects of exposure to marine heatwaves (MHWs) alone and in combination with environmentally relevant concentration of copper (Cu) were evaluated in the reef-forming tubeworm Ficopomatus enigmaticus using a multi-biomarker approach. Biomarkers of cell membrane damage, enzymatic antioxidant defences, metabolic activity, neurotoxicity, and DNA integrity were analyzed. The exposure to Cu alone did not produce any significant effect. Exposure to MHWs alone produced effects only on metabolic activity (increase of glutathione S-transferase) and energy reserves (decrease in protein content). MHWs in combination with copper was the condition that most influenced the status of cell homeostasis of exposed F. enigmaticus. The combination of MHWs plus Cu exposure induced increase of protein carbonylation and glutathione S-transferase activity, decrease in protein/carbohydrate content and carboxylesterase activity. This study on a reef-forming organism highlighted the additive effect of a climate change-related stressor to metals pollution of marine and brackish waters.

Long-term study of phytoplankton dynamics in a supply reservoir reveals signs of trophic state shift linked to changes in hydrodynamics associated with flow management and extreme events

This study analyses over a decade (2009-2022) of monitoring data to understand the impact of hydrological characteristics on water quality and phytoplankton dynamics in Prospect Reservoir, a critical water supply for Greater Sydney, Australia, known for its excellent water quality. Water quality and phytoplankton dynamics were related to hydrodynamics, linked to flow management and the water quality of inflows. Phytoplankton biovolume increased after a prolonged drawdown and subsequent refill event, mainly driven by dinoflagellates, and corresponded to increases in total phosphorus and water temperature. The hydrological period following the 2019/2020 summer bushfires (post-bushfire) that impacted connected reservoirs, was marked by increased flow activity and nutrient loading, leading to significant shifts in the phytoplankton community. Functional group classification and ordination analysis indicated a transition from taxa typically dominant in oligotrophic conditions to meso‑eutrophic. This transition correlated with elevated nutrient levels and chlorophyll-a (Chl-a), and reduced Secchi depth and dissolved oxygen, providing evidence of eutrophication. Q index indicated good water quality post-bushfire, contrasting with a eutrophic status assessment using Chl-a. Our findings highlight the importance of analysing long-term datasets encompassing varied hydroclimatological conditions for a deeper understanding of reservoir behaviour. A comprehensive approach to water quality assessment is recommended, combining functional group classification, Q index and Chl-a measurements for effective reservoir health assessment. This research provides novel insights into the effects of disturbances such as bushfires, on water quality and phytoplankton dynamics in an underrepresented geographic region, offering valuable knowledge for managing water resources amidst growing climate variability.

Pluvial flood risk assessment for 2021-2050 under climate change scenarios in the Metropolitan City of Venice

Pluvial flood is a natural hazard occurring from extreme rainfall events that affect millions of people around the world, causing damages to their properties and lives. The magnitude of projected climate risks indicates the urgency of putting in place actions to increase climate resilience. Through this study, we develop a Machine Learning (ML) model to predict pluvial flood risk under Representative Concentration Pathways (RCP) 4.5 and 8.5 for future scenarios of precipitation for the period 2021-2050, considering different triggering factors and precipitation patterns. The analysis is focused on the case study area of the Metropolitan City of Venice (MCV) and considers 212 historical pluvial flood events occurred in the timeframe 1995-2020. The methodology developed implements spatio-temporal constraints in the ML model to improve pluvial flood risk prediction under future scenarios of climate change. Accordingly, a cross-validation approach was applied to frame a model able to predict pluvial flood at any time and space. This was complemented with historical pluvial flood data and the selection of nine triggering factors representative of territorial features that contribute to pluvial flood events. Logistic Regression was the most reliable model, with the highest AUC score, providing robust result both in the validation and test set. Maximum cumulative rainfall of 14 days was the most important feature contributing to pluvial flood occurrence. The final output is represented by a suite of risk maps of the flood-prone areas in the MCV for each quarter of the year for the period 1995-2020 based on historical data, and risk maps for each quarter of the period 2021-2050 under RCP4.5 and 8.5 of future precipitation scenarios. Overall, the results underline a consistent increase in extreme events (i.e., very high and extremely high risk of pluvial flooding) under the more catastrophic scenario RCP8.5 for future decades compared to the baseline.

Subtropical coastal microbiome variations due to massive river runoff after a cyclonic event

BACKGROUND

Coastal ecosystem variability at tropical latitudes is dependent on climatic conditions. During the wet, rainy season, extreme climatic events such as cyclones, precipitation, and winds can be intense over a short period and may have a significant impact on the entire land‒sea continuum. This study focused on the effect of river runoff across the southwest coral lagoon ecosystem of Grand Terre Island of New Caledonia (South Pacific) after a cyclonic event, which is considered a pulse disturbance at our study site. The variability of coastal microbiomes, studied by the metabarcoding of V4 18S (protists) and V4-V5 16S (bacteria) rDNA genes, after the cyclone passage was associated with key environmental parameters describing the runoff impact (salinity, organic matter proxies, terrestrial rock origin metals) and compared to community structures observed during the dry season.

RESULTS

Microbiome biodiversity patterns of the dry season were destructured because of the runoff impact, and land-origin taxa were observed in the coastal areas. After the rainy event, different daily community dynamics were observed locally, with specific microbial taxa explaining these variabilities. Plume dispersal modeling revealed the extent of low salinity areas up to the coral reef area (16 km offshore), but a rapid (< 6 days) recovery to typical steady conditions of the lagoon's hydrology was observed. Conversely, during the same time, some biological components (microbial communities, Chl a) and biogeochemical components (particulate nickel, terrigenous organic matter) of the ecosystem did not recover to values observed during the dry season conditions.

CONCLUSION

The ecosystem resilience of subtropical ecosystems must be evaluated from a multidisciplinary, holistic perspective and over the long term. This allows evaluating the risk associated with a potential continued and long-term disequilibrium of the ecosystem, triggered by the change in the frequency and intensity of extreme climatic events in the era of planetary climatic changes.

Evaluating the extent and impact of the extreme Storm Gloria on Posidonia oceanica seagrass meadows

Extreme storms can trigger abrupt and often lasting changes in ecosystems by affecting foundational (habitat-forming) species. While the frequency and intensity of extreme events are projected to increase under climate change, its impacts on seagrass ecosystems remain poorly documented. In January 2020, the Spanish Mediterranean coast was hit by Storm Gloria, one of the most devastating recent climate events in terms of intensity and duration. We conducted rapid surveys of 42 Posidonia oceanica meadows across the region to evaluate the extent and type of impact (burial, unburial and uprooting). We investigated the significance of oceanographic (wave impact model), geomorphological (latitude, depth, exposure), and structural (patchiness) factors in predicting impact extent and intensity. The predominant impact of Storm Gloria was shoot unburial. More than half of the surveyed sites revealed recent unburial, with up to 40 cm of sediment removed, affecting over 50 % of the meadow. Burial, although less extensive, was still significant, with 10-80 % of meadow cover being buried under 7 cm of sediment, which is considered a survival threshold for P. oceanica. In addition, we observed evident signs of recently dead matte in some meadows and large amounts of detached drifting shoots on the sea bottom or accumulated as debris on the beaches. Crucially, exposed and patchy meadows were much more vulnerable to the overall impact than sheltered or continuous meadows. Given how slow P. oceanica is able to recover after disturbances, we state that it could take from decades to centuries for it to recoup its losses. Seagrass ecosystems play a vital role as coastal ecological infrastructure. Protecting vulnerable meadows from anthropogenic fragmentation is crucial for ensuring the resilience of these ecosystems in the face of the climate crisis.

Avian responses to climate extremes: insights into abundance curves and species sensitivity using the UK Breeding Bird Survey

Climate change remains one of the most urgent challenges for biodiversity conservation. Recent studies have highlighted that climate extremes (CLEXs) can lead to widespread and negative effects across all taxa and ecological levels, but most of these studies are based on short-term periods and small spatial scales and lack a multi-species approach. Here, using generalised additive models (GAMs) and the UK Breeding Bird Survey (BBS), we described response curves for the abundance of 100 resident bird species over large spatial and temporal scales and identified the species showing a greater sensitivity to CLEXs. We used five climatic indices computed at 1-km spatial resolution as proxies of CLEXs during the winter or breeding season and considered both 1- and 2-year lagged effects. The results demonstrated widespread and significant effects of CLEXs on bird abundances at both time lags and in both seasons. Winter frost days (FD0), summer days (SU25) during the breeding season and simple precipitation intensity index (SDII) during the breeding season mainly showed negative effects. Daily temperature range (DTR) in both winter and breeding season and dry days (DD) during the breeding season led to diversified responses across the species, with a prevalence of positive effects. A large proportion of species showed a high sensitivity to CLEXs, highlighting that these species may deserve attention in future studies aimed at biodiversity conservation. We demonstrated that CLEXs can represent a significant driver affecting population abundances over large spatial and temporal scales, emphasising the need for understanding mechanistic processes at the basis of the observed effects.

Heat waves accelerate the spread of infectious diseases

COVID-19 pandemic appeared summer surge in 2022 worldwide and this contradicts its seasonal fluctuations. Even as high temperature and intense ultraviolet radiation can inhibit viral activity, the number of new cases worldwide has increased to >78% in only 1 month since the summer of 2022 under unchanged virus mutation influence and control policies. Using the attribution analysis based on the theoretical infectious diseases model simulation, we found the mechanism of the severe COVID-19 outbreak in the summer of 2022 and identified the amplification effect of heat wave events on its magnitude. The results suggest that approximately 69.3% of COVID-19 cases this summer could have been avoided if there is no heat waves. The collision between the pandemic and the heatwave is not an accident. Climate change is leading to more frequent extreme climate events and an increasing number of infectious diseases, posing an urgent threat to human health and life. Therefore, public health authorities must quickly develop coordinated management plans to deal with the simultaneous occurrence of extreme climate events and infectious diseases.

Forecasting crude oil prices in the COVID-19 era: Can machine learn better?

Since the onset of the COVID-19 pandemic, energy price predictability has worsened. We evaluate the effectiveness of the two machine learning methods of shrinkage and combination on the spot prices of crude oil before and during the COVID-19 epidemic. The results demonstrated that COVID-19 increased economic uncertainty and diminished the predictive capacity of numerous models. Shrinkage methods have always been regarded as having an excellent out-of-sample forecast performance. However, during the COVID period, the combination methods provide more accurate information than the shrinkage methods. The reason is that the outbreak of the epidemic has altered the correlation between specific predictors and crude oil prices, and shrinkage methods are incapable of identifying this change, resulting in the loss of information.

An extreme wind speed climatology - Atmospheric driver identification using neural networks

Extreme wind speeds are a significant climate risk, potentially endangering human lives, causing damage to infrastructure, affecting maritime and aviation activity, along with the optimal operation of wind energy conversion systems. In this context, accurate knowledge of return levels for various return periods of extreme wind speeds and their atmospheric circulation drivers is essential for effective risk management. In this paper, location-specific extreme wind speed thresholds are identified and return levels of extremes are estimated using the Peaks-Over-Threshold method of the Extreme Value Analysis framework. Furthermore, using an environment-to-circulation approach, the key atmospheric circulation patterns that cause extreme wind speeds are identified. The data used for this analysis are hourly wind speed data, mean sea level pressure and geopotential at 500 hPa from the ERA5 reanalysis dataset, at a horizontal resolution of 0.25° × 0.25°. The thresholds are selected utilizing the Mean Residual Life plots, while the exceedances are modeled with the General Pareto Distribution. The diagnostic metrics exhibit satisfactory goodness-of-fit and the maxima of extreme wind speed return levels are located over marine and coastal areas. The optimal Self-Organizing-Map (2 × 2) is selected using the Davies-Bouldin criterion, and the atmospheric circulation patterns are related to the cyclonic activity in the area. The proposed methodological framework can be applied to other areas, that are endangered by extreme phenomena or in need of accurately assessing the principal drivers of extremes.

Effects of the 2018 European heatwave and drought on coastal biogeochemistry in the German Bight

In 2018, Europe experienced an unprecedented heatwave and drought, especially in central and northern Europe, which caused decreased terrestrial production and affected ecosystem health. In this study, the effects of this event on the marine environment are investigate, with a focus on the biogeochemical response in the German Bight of the North Sea. Using time series data from FerryBoxes, research cruises, monitoring programs and remote sensing we compare conditions in 2018 to climatological values. We find that (1) the heatwave caused rapid warming of surface waters, (2) the drought reduced river discharge and nutrient loads to the coast, and (3) these combined effects altered coastal biogeochemistry and productivity. During 2018, both water discharge and nutrient loads from rivers discharging into the German Bight were below the seasonally variable 10th percentile from March onward. Throughout the study domain, water temperature was near or below that threshold in March 2018, but higher than in other years during May 2018, representing not only a heat wave, but also the fastest spring warming on record. This extreme warming period saw concurrent high peaks in chlorophyll a, dissolved oxygen and pH, consistent with the development of a strong spring bloom. It appears that productivity was above 75th percentile of the 21-year record in most of the nearshore region, while offshore it was widely below the 25th percentile in 2018. The drought-related low discharge limited nutrient supply from the rivers, but likely increased water residence time nearshore, where a surge in primary production with efficient nutrient utilization during the spring depleted nutrients available for transport offshore. There, the heatwave-related rapid warming of surface water resulted in the establishment of a stable thermal water column stratification, hindering vertical nutrient supply to the surface layer during the summer.

Diatom responses to warming, heavy rains and human impact in a Mediterranean lake since the preindustrial period

In the Mediterranean region, annual mean air temperature will continue to increase during the 21st century, while seasonal precipitation is expected to decrease and extreme events to be more frequent. Human-induced climate change will severely impact aquatic ecosystems. A subdecadal stratigraphic diatom record of Lake Montcortès (central Pyrenees) was investigated, focusing on the potential responses of diatoms to anthropogenic warming and catchment alteration. The study includes the end of the Little Ice Age (LIA), the transition to the industrial and postindustrial eras, and the recent global warming and its current acceleration. Sediment samples were treated and diatoms taxonomically identified. Relationships between diatom taxa abundances and climatic (temperature and precipitation) and environmental (land use, soil erosion, and eutrophication) variables were investigated using multivariate statistical methods. The results indicate that, from ca. 1716 to 1971 CE, the diatom community was dominated by Cyclotella cyclopuncta and showed small perturbations, despite the pressure of important stressors such as strong cooling episodes, droughts and an intense use of the lake for hemp retting during the 18th and 19th centuries. However, during the 20th century, other centric species gained relevance, and from the 1970s on, Cyclotella ocellata competed with C. cyclopuncta for dominance. These changes coincided with pulse-like disturbances in the form of extreme rainfall events along with the gradual 20th century increase in global temperature. These perturbations affected the planktonic diatom community and led to instability dynamics. The benthic diatom community did not reflect any comparable shifts under the effect of the same climatic and environmental variables. Because heavy rainfall episodes are likely to intensify with current climate change in the Mediterranean region, their importance as stressors of planktonic primary producers should be taken into account as potential disrupters of biogeochemical cycles and trophic networks of lakes and ponds.

Does water temperature influence in microcystin production? A case study of Billings Reservoir, São Paulo, Brazil

We investigated the relationship between some water quality parameters and microcystin, chlorophyll-a, and cyanobacteria in different conditions of water temperature. We also proposed to predict chlorophyll-a concentration in the Billings Reservoir using three machine learning techniques. Our results indicate that in the condition of higher water temperatures with high density of cyanobacteria, microcystin concentration can increase severely (>10² μg/L). Besides the magnitude observed in higher concentrations, in water temperatures above 25.3 °C (classified as high extreme event), higher frequencies of inadequate values of microcystin (87.5%), chlorophyll-a (70%), and cyanobacteria (82.5%) compared to cooler temperatures (<19.6 °C) were observed. The prediction of chlorophyll-a in Billings Reservoir presented good results (0.76 ≤ R² ≤ 0.82; 0.17 ≤ RMSE≤0.20) using water temperature, total phosphorus, and cyanobacteria as predictors, with the best result using Support Vector Machine.

Total and dissolved phosphorus losses from agricultural headwater streams during extreme runoff events

Eutrophication continues to be a concerning global water quality issue. Managing and mitigating harmful algal blooms demands clear information on the conditions promoting large phosphorus losses from contributing watersheds. Of particular concern is the amount and form of phosphorus loading to receiving water bodies during extreme runoff events, which are expected to increase in frequency due to climate change. Five years (2015 to 2020) of water quantity and quality data from 11 agricultural watersheds in the lower Great Lakes basin were analyzed and used to model total and dissolved phosphorus losses. This study aimed to assess temporal dynamics in phosphorus concentrations and losses over runoff events covering a wide range of hydrologic conditions and to quantify their relative importance on annual phosphorus losses. Event concentration-discharge relationships for total and dissolved phosphorus were hysteretic and had contrasting dominant patterns across watersheds. The proportion of annual phosphorus losses during events was highly variable between watersheds, accounting for 47-94 %. Extreme events were particularly impactful: as few as three events per year were found to be responsible for nearly half of total phosphorus (20-50 %) and total dissolved phosphorus (14-44 %) losses. Variability in total and dissolved phosphorus losses and concentrations over a wide range of flow conditions suggests that event magnitude is an important control on the relative mobility of particulate and dissolved phosphorus fractions. This study showed that insights into nutrient dynamics and phosphorus budgets in the lower Great Lakes basin and agriculture dominated environments more broadly can be gained by assessing event nutrient losses with respect to flow conditions and patterns in concentration-discharge relationships.

Increased chlorophyll-a concentration in Barra Bonita reservoir during extreme drought periods

Climate projections models indicate that longer periods of droughts are expected within the next 100 years in various parts of South America. To understand the effects of longer periods of droughts on aquatic environments, we investigated the response of chlorophyll-a (Chl-a) concentration to recent severe drought events in the Barra Bonita Hydroelectric Reservoir (BBHR) in São Paulo State, Brazil. We used satellite imagery to estimate the Chl-a concentration from 2014 to 2020 using the Slope Index (NRMSE of 18.92% and bias of -0.20 mg m^-3). Ancillary data such as precipitation, water level and air temperature from the same period were also used. Drought events were identified using the standardized precipitation index (SPI). In addition, we computed the probability of future drought events. Two periods showed extremely dry conditions: 1) January-February (2014) and 2) April-May (2020). Both periods were characterized by a recurrence probability of 1in every 50 years. The highest correlation was observed between Chl-a concentration and SPI (-0.97) in 2014, while Chl-a had had the highest correlation with water level (-0.59) in 2020. These results provide new insights into the influence of extreme drought events on the Chl-a concentration in the BBHR and their relationship with other climate variables and reservoir water levels. Drought events imply less rainfall, higher temperatures, and atmospheric dryness, and these factors affect evaporation and the water levels in the reservoir.

Increased burned area in the Pantanal over the past two decades

Wildfires are behaving differently now compared to other time in history in relation to frequency, intensity and affected ecosystems. In Brazil, unprecedented fires are being experienced in the last decade. Thus, to prevent and minimize similar disasters, we must better understand the natural and human drivers of such extreme events. The Brazilian Pantanal is the largest contiguous wetland in the world and a complex environmental system. In 2020, Pantanal experienced catastrophic wildfires due to the synergy between climate, inadequate fire management strategies and weak environmental regulations. In this study, we analyzed recent patterns and changes in fire behavior across the Pantanal based on land use and cover (LULC) classes. The inter-annual variability of the fire and land cover changes between 2000 and 2021 was assessed using BA from MCD64A1 V.6 product and LULC data from Landsat satellite. Our work reveals that fires in the Pantanal over the last two decades tended to occur more frequently in grassland than in others land cover types, but the 2020 fires have preferentially burned forest regions. Large fire patches are more frequent in forest and grasslands; in contrast, croplands exhibit small patches. The results highlight that a broad scale analysis does not reflect distinct localized patterns, thus stratified and refined studies are required. Our work contributes as a first step to disentangling the role of anthropogenic-related drivers, namely LULC changes, in shaping the fire regime in the Pantanal biome. This is crucial not only to predict future fire activity but also to guide appropriated fire management in the region.

An Investigation of the Factors that Influence Job Performance During Extreme Events: The Role of Information Security Policies

Diligent compliance with Information security Policies (ISP) can effectively deter threats but can also adversely impact organizational productivity, impeding organizational task completion during extreme events. This paper examines employees' job performance during extreme events. We use the conservation of resources (COR) theory to examine how psychological resources (individual resilience, job meaningfulness, self-efficacy) and organizational resources (incident command leadership, information availability, and perceived effectiveness of security and privacy controls) influence ISP compliance decisions and job performance during extreme events. The results show that a one-size-fits-all approach to ISP is not ideal during extreme events; ISP can distract employees from critical job tasks. We also observed that under certain conditions, psychological resources, such as individual resilience, are reserved for job performance, while others, such as self-efficacy, are reserved for ISP compliance. A post hoc analysis of data from respondents who experienced strain during a real extreme event while at work was conducted. Our discussion provides recommendations on how security and privacy policies can be designed to reflect disaster conditions by relaxing some policy provisions.

Post hurricane Harvey dataset: Portable free fall penetrometer and chirp sonar measurements of Texas rivers

This data article includes datasets collected at three sections of the Guadalupe River, Brazos River, and Colorado River in Texas, USA, almost ten months post Hurricane Harvey. Instruments used include a Portable Free Fall Penetrometer (PFFP), Chirp Sonar, Side Scan Sonar (SSS), Acoustic Doppler Current Profiler (ADCP) and sediment grab sampler. Measurements were collected from small vessels such as canoes and a 6-feet inflatable zodiac and were supported by long term hydrodynamic data from local river water level and discharge gages. Laboratory testing performed on samples collected included grain size analysis, Atterberg test, and erodibility testing using an Erosion Function Apparatus (EFA). Data collected were analyzed to estimate sediment strength derived from the PFFP, backscatter intensity recorded by the chirp sonar, and soil sample characteristics. The dataset includes raw and processed data for the measurements recorded by the instruments, location of measurements, and laboratory testing grouped for each river with a readme file which gives a potential for reuse by other researchers for further analysis if needed. This data article is representing supplementary data to the following research article published in Engineering Geology [1]:

Jaber, R., Stark, N., Jafari, N., & Ravichandran, N. “Combined Portable Free Fall Penetrometer and Chirp Sonar Measurements of three Texas River Sections Post Hurricane Harvey.”

Raw data was published [2]: Stark, N. Jafari, N. Ravichandran, R. Jaber, R. (2020). Combined Geotechnical and Geophysical Investigation of Texas Rivers Post Hurricane Harvey. in Combined Geotechnical and Geophysical Investigation of Texas Rivers Post Hurricane Harvey. DesignSafe-CI. https://doi.org/10.17603/ds2-835m-zp94

Anthropogenic pressures enhance the deleterious effects of extreme storms on rocky shore communities

Climate change is not only changing the mean values of environmental parameters that modulate ecosystems, but also the regime of disturbances. Among them, extreme events have a key role in structuring biological communities. Ecosystems are frequently suffering multiple anthropogenic pressures which can cause effects that are not additive. Thus, the effects of extreme events need to be studied in combination with other pressures to adequately evaluate their consequences. We performed a manipulative approach in two rocky shores in the Mediterranean with contrasting levels of anthropogenic pressure (mainly eutrophication) simulating storms with different disturbance regimes in the intertidal and subtidal zones. In the short-term, an extreme storm had a greater impact on the species assemblage than other disturbance regimes, being especially notable in the area suffering from a high anthropogenic pressure. In this area, the species assemblages that suffered from an extreme storm took a longer time to recover than the ones affected by other disturbance regimes and were generally more affected after the disturbance. The intertidal zone, having more variable environmental conditions than the subtidal zone, was more resistant and able to recover from extreme storms. Our results suggest that the effects of extreme events on biological communities could be strengthened when co-occurring with anthropogenic pressures, especially ecosystems adapted to less variable environmental conditions. Thus, limiting other anthropogenic pressures that ecosystems are suffering is crucial to maintain the natural resistance and recovery capacity of ecosystems towards extreme events such as storms.

Development of a catalogue of damage in Portuguese forest associated with extreme extratropical cyclones

In European forests, extreme wind events associated with severe extratropical cyclones are considered the main abiotic agent of forest vulnerability, leading to high economic losses in forests due to damage caused by the uprooting of trees and trunk breaks. Despite the importance recognized to severe cyclones and associated extreme phenomena, the impact on forest stocks is not always properly reported, leading to underestimation in the perception of losses, with direct consequences on forest governance decisions. This is particularly true in countries where other agents traditionally have a high impact, such as the countries under the influence of the Mediterranean, where wildfire is a recurrent menace with devastating effects. This work characterizes the situation observed in Portugal and presents the methodology followed to obtain information about forest damages and the procedure to identify the extreme extratropical cyclones responsible for those damages. As an example, available information and the recording of damage occurring in the Portuguese forest in winter 2017-2018 are presented and discussed. The study shows how difficult and demanding it is to obtain past information about the damage. In addition, there is high uncertainty about the precise identification of the event that caused the damage, as field records often occur several days or even weeks after the storm. To reduce the constraints, it is proposed to use a model whose skeleton of information has been designed to obtain useful information from traditional registries. The proposed model is useful for the characterization of losses and to support national policies to reduce the impact of damage associated with extreme wind events. The design of the catalogue can be used for recording information at the stand scale level by stakeholders and ensure compatibility with international databases for updating information purposes.

Nexus between climate change and oil palm production in Malaysia: a review

Climate change is believed to be caused by natural processes such as volcanic eruptions, which release ash into the atmosphere, and anthropogenic activities that increase the concentration of greenhouse gases (GHGs) in the atmosphere, such as carbon dioxide (CO₂), which trap energy and cause intense warming. This article conducts a comprehensive review of existing literature relating to climate change and its impact on oil palm production in Malaysia. To enable analysis, articles were arranged, sorted, and categorized into various themes and associations based on the title of the article, abstract, and later the content. The findings reveal that climate change causes variability in the intensity and duration of rainfall, which ultimately affects the production of oil palm fresh fruit bunches (FFB) and the quality of crude palm oil (CPO). The decline in FFB increased the price of crude palm oil. The impacts of climate change on oil palm vary and are felt differently in different regions. Climate change increases the vulnerability and exposure of oil palms to various diseases, exposes them to water stress, and disrupts metabolic activities. The surface temperature in Malaysia is anticipated to rise by 1.5 to 2 °C, worsening the adaptation plans. Oil palm growers explore possible ways to adapt to and withstand the impacts of climate change by adopting the use of an improved variety of oil palm seedlings, soil management and fertility preservation, silt pit, mulching, intercropping, livelihood diversification, buying insurance, and best water conservation practices.

The influence of extreme events such as Brexit and Covid-19 on equity markets

In this article first, we show that the result that the PIIGS group had the largest negative unadjusted and abnormal returns on the day following the Brexit Referendum is robust to taking into account jointly other extreme events such as the Covid-19. Second, we provide evidence that the impact of the declaration of Covid-19 to be a global pandemic by the WHO - when global markets fell by nearly 15% - had a total different reaction in the financial markets to the one following the Brexit Referendum, impacting more negatively in countries where quarantine lockdowns were announced that day (i.e. Austria, Belgium, Brazil, Canada, Italy and Spain), independently on their debt-to GDP ratio. We also show that the day after Covid-19 was declared as a global pandemic, China and Japan (countries that already implemented lockdowns in the previous months) were the only analyzed countries that did not experience any evidence of abnormal returns in their financial markets. Moreover, during the three following days, the US was the only analyzed country showing no evidence of negative abnormal returns due to the declaration of the national emergency. These results suggest that government policies must take into account and monitor specially health-related news at global level, since they can have enormous impacts on portfolio allocations on stock markets, in order to take more informed decisions.

Climate regime shifts and biodiversity redistribution in the Bay of Biscay

Global ocean warming, wave extreme events, and accelerating sea-level rise are challenges that coastal communities must address to anticipate damages in coming decades. The objective of this study is to undertake a time-series analysis of climate change (CC) indicators within the Bay of Biscay, including the Basque coast. We used an integrated and flexible methodology, based on Generalized Additive Mixed Models, to detect trends on 19 indicators (including marine physics, chemistry, atmosphere, hydrology, geomorphology, biodiversity, and commercial species). The results of 87 long-term time series analysed (~512,000 observations), in the last four decades, indicate four groups of climate regime shifts: 1) A gradual shift associated with CC starting in the 1980s, with a warming of the sea surface down to 100 m depth in the bay (0.10-0.25 °C per decade), increase in air temperature and insolation. This warming may have impacted on benthic community redistribution in the Basque coast, favouring warm-water species relative to cold-water species. Weight at age for anchovy and sardine decreased in the last two decades. 2) Deepening of the winter mixed layer depth in the south-eastern bay that probably led to increases in nutrients, surface oxygen, and chlorophyll concentration. Current increases on chlorophyll and zooplankton (i.e., copepods) biomass are contrary to those expected under CC scenarios in the region. 3) Sea-level rise (1.5-3.5 cm per decade since 1990s), associated with CC. 4) Increase of extreme wave height events of 16.8 cm per decade in the south-eastern bay, probably related to stormy conditions in the last decade, with impacts on beach erosion. Estimating accurate rates of sea warming, sea-level rise, extreme events, and foreseeing the future pathways of marine productivity, are key to define the best adaptation measures to minimize negative CC impacts in the region.

Retrospection of heatwave and heat index

The frequency and intensity of extreme events especially heat waves (HW) are growing all around the world which ultimately poses a serious threat to the health of individuals. To quantify the effects of extreme temperature, appropriate information, and the importance of HW and heat index (HI) are carefully discussed for different parts of the world. Varied definitions of the HW and HI formula proposed and used by different countries are carried out systematically continent-wise. Different studies highlighted the number of definitions of HW; however, mostly used Steadman's formulae, which was developed in the late 1970s, for the calculation of HI that uses surface air temperature and relative humidity as climatic fields. Since then, dramatic changes in climatic conditions have been observed as evident from the ERA5 datasets which need to be addressed; likewise, the definition of HW, which is modified by the researchers as per the geographic conditions. It is evident from the ERA5 data that the temperature has increased by 1-2 °C as compared to the 1980s. There is a threefold increase in the number of heatwave days over most of the continents in the last 40 years. This study will help the researcher community to understand the importance of HW and HI. Furthermore, it opens the scope to develop an equation based on the present scenario keeping in mind the basics of an index as considered by Steadman.

Facing up to climate change: Community composition varies with aspect and surface temperature in the rocky intertidal

Marine rocky intertidal organisms are amongst those most affected by climate change with regional distributional changes observed for many species. Although often ascribed to increased sea surface temperatures, precise assessment of the local habitat conditions underpinning observed and predicted changes in community assembly is lacking. Here we examine how aspect (i.e. north-south orientation) affects intertidal community composition and how rock surface temperatures and stress responses of two dominant grazer species (Patella spp.) elucidate emergent differences. We quantified year-round temperature variation and surveyed intertidal community composition on paired natural rock gullies with Equator- (EF) and Pole-facing (PF) surfaces. We also investigated variation in limpet (Patella spp.) reproductive phenology and osmotic stress. Average annual temperatures were 0.8 °C (1.6 °C at low tide) higher, with six-fold more frequent extremes (i.e. > 30 °C) on EF than PF surfaces. Intertidal community composition varied with aspect across trophic levels with greater overall species richness, abundance of primary producers and grazers on PF-surfaces, and greater barnacle abundance on EF-surfaces. Although species richness of organisms from different biogeographical origins ('Boreal' or 'Lusitanian') did not vary, the Lusitanian limpet Patella depressa exhibited earlier reproductive development on EF-surfaces and both limpet species exhibited greater thermal stress on EF-surfaces. We argue that our study system provides a good model for understanding how temperature variation at local scales can affect community composition, as well as ecophysiological and ecological responses to climate change and so better inform and predict regional range shifts over coming decades.

A multi-proxy record of hurricanes, tsunami, and post-disturbance ecosystem changes from coastal southern Baja California

Tsunamis and hurricanes are two earth surface processes that can dramatically impact coastal landforms and ecosystems. This study uses a combination of palynological, grain-size, X-ray fluorescence, and loss-on-ignition analyses, short-lived isotopic and radiocarbon dating, and statistical analysis to differentiate the tsunami and hurricane deposits, establish a Late-Holocene record of extreme events, and document the landscape and vegetation transformation in response to disturbance events and environmental changes from a small coastal lagoon in Baja California, Mexico. Prior to ~530 cal yr BP, Playa Los Cocos was occupied by a short-hydroperiod tidal marsh bounded by desert vegetation on the surrounding hillslopes. At ~530 cal yr BP, a tsunami created a backbarrier lagoon and introduced mangrove propagules from other coastal localities, and the lagoonal environment and substrates also provided suitable habitats for red mangroves to proliferate. Once established, red mangrove populations rapidly expanded until ~180 cal yr BP, when modern human activities diminished the mangrove forest in our study area. Overall, the multi-proxy dataset revealed four hurricane events at ~770, ~600, ~280, and ~0 cal yr BP, and one tsunami event at ~530 cal yr BP. The hurricane deposits were preserved in the form of fluvial and slope-wash deposits characterized by low organic and water contents, low concentration of marine elements, and high concentration of terrestrial elements. The tsunami run-up deposits are characterized by abundant broken and intact sea shells, high content of carbonate and marine elements, low concentration of terrestrial elements, and sharp basal contact with the underlying sediments. The tsunami backwash deposits are characterized by a mixed physical and chemical signature resembling both marine and terrestrial sediments. Results also suggest that both hurricanes and tsunamis can help propagule dispersal and create suitable coastal habitats favorable for the spread and proliferation of mangroves in a desert coastal environment.

The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China

Detecting the adverse effects of major emergencies on financial markets and real economy is of great importance not only for short-term policy reactions but also for economic and financial stability. This is the lesson we learnt from the COVID-19 pandemic. This paper focuses on the risk spillover effect of the COVID-19 on Chinese energy industry using a high-dimensional and time-varying factor-augmented VAR model. The results show that the net volatility spillovers of the pandemic remain positive to all underlying energy sectors during January to June of 2020 and February to April of 2021. For the former sub-period, the volatility spillover of the COVID-19 is not only the highest, but also lasts longest for oil exploitation sector, followed by the power and gas sectors. While for the latter sub-period, the COVID-19 has relatively higher volatility spillovers to the power, coal mining and petrochemical sectors. These findings suggest that the COVID-19 has significant risk spillover effects on Chinese energy sectors, and the effects vary among different energy sub-sectors and across different periods of time.

COVID-19 and financial market efficiency: Evidence from an entropy-based analysis

This study assesses the market efficiency of S&P 500 Index, gold, Bitcoin and US Dollar Index during the extreme event of COVID-19 pandemic. Market efficiency is estimated by a multiscale entropy-based method for the scales of hourly and 1 to 30 business days. At all scales, four markets' efficiency decreases sharply and persistently during February-March 2020. Market efficiency decreases the most in S&P 500 Index and the least in Bitcoin market. Bitcoin market efficiency is more resilient than others during the extreme event, which is an attractive feature to serve as a safe haven asset.

Governance in the Face of Extreme Events: Lessons from Evolutionary Processes for Structuring Interventions, and the Need to Go Beyond

The increasing frequency of extreme events, exogenous and endogenous, poses challenges for our societies. The current pandemic is a case in point; but "once-in-a-century" weather events are also becoming more common, leading to erosion, wildfire and even volcanic events that change ecosystems and disturbance regimes, threaten the sustainability of our life-support systems, and challenge the robustness and resilience of societies. Dealing with extremes will require new approaches and large-scale collective action. Preemptive measures can increase general resilience, a first line of protection, while more specific reactive responses are developed. Preemptive measures also can minimize the negative effects of events that cannot be avoided. In this paper, we first explore approaches to prevention, mitigation and adaptation, drawing inspiration from how evolutionary challenges have made biological systems robust and resilient, and from the general theory of complex adaptive systems. We argue further that proactive steps that go beyond will be necessary to reduce unacceptable consequences.

Large lake sluice operations during an extreme rainfall season greatly affect circulation and water quality dynamics of a shallow eutrophic lake

Large hydraulic infrastructures have been constructed globally to address water challenges. Past studies have well documented their effects on downstream aquatic ecosystems, which have included disrupting hydrological regimes as well as nutrient delivery, cycling and mediating processes that affect primary production. However, how these infrastructure operations affect lake ecosystems where the infrastructures are situated remains poorly understood. In the present study, we used a three-dimensional hydrodynamic-biogeochemical lake model to quantify the potential effects of large lake sluice operations under extreme high water levels on current structure and water quality parameters of Lake Chaohu in China. We designed and simulated multiple operation strategies based on actual operation curves during the 2016 extreme rainfall season. The model successfully captured the water quality dynamics of Lake Chaohu during both the calibration and validation phases. Our results indicate that higher lake water release rates led to overall accelerations of the current velocity; however, the deceleration of along-shore current velocity along the shorelines was also evident. Higher release rates also resulted in rapid rises ammonium nitrogen (NH₄-N), total nitrogen (TN) and total phosphorous (TP) concentrations in the eastern lake basin, as well as a lake-wide rise of chlorophyll-a (Chla) concentration. When the lake sluice was operated at its full capacity, mean concentrations of these four parameters increased by 5.21%, 5.58%, 9.6% and 7.46%, respectively. Modeling results demonstrate that the effects of lake sluice operations were still quite pronounced for four months after the operations. Modeling results also revealed that higher release rate during the operation phase may help decease TN and TP concentrations during the subsequent period. This study provides a useful perspective on how to support the planning and operation of large infrastructures in the face of climate change induced extreme events.

Association of retreating monsoon and extreme air pollution in a megacity

The world's top ranked mega city Delhi is known for deteriorated air quality. However, the analysis of air pollution data of 5 years (2014-2018) reveals that years 2016 and 2017, which were marked by an unusual delayed withdrawal of monsoon, witnessed an unprecedented extreme levels of toxic PM_2.5 particles (≤2.5 µm in diameter) touching a peak level of ∼760 µg/m³ (24 hr average), immediately after the monsoon retreat, surpassing WHO standards by ∼30 time and Indian national standards by ∼12 times, jeopardising lives of its citizens. However, the normal monsoon withdrawal years do not show such extreme levels of pollution. The high resolution WRF-Chem model along with meteorological data are used in this work to understand that how the delayed monsoon withdrawal and associated vagarious anti-cyclonic circulation resulted in trapping externally generated pollutants ceaselessly under colder conditions, leading to historic air quality crisis in landlocked mega city in these selected years. The sensitivity analysis confirmed that when WRF-chem model forced the climatology of normal monsoon year (2015) to simulate the pollution scenario of 2016 and 2017 for the above time period, the crisis subsided. Present findings suggest that such unusual monsoon patterns are on the hook to spur extreme pollution events in recent time.

Extreme Events, Entrepreneurial Start-Ups, and Innovation: Theoretical Conjectures

In light of the COVID-19 pandemic, we scrutinize what has been established in the literature on whether entrepreneurship can cause and resolve extreme events, the immediate and long-run impacts of extreme events on entrepreneurship, and whether extreme events can positively impact (some) entrepreneurship and innovation. Based on this, we utilize a partial equilibrium model to provide several conjectures on the impact of COVID-19 on entrepreneurship, and to derive policy recommendations for recovery. We illustrate that while entrepreneurship recovery will benefit from measures such as direct subsidies for start-ups, firms' revenue losses, and loan liabilities, it will also benefit from aggregate demand-side support and income redistribution measures, as well as from measures that facilitate the innovation-response to the Keynesian supply-shock caused by the pandemic, such as access to online retail and well-functioning global transportation and logistics.

Spatiotemporal nexus between vegetation change and extreme climatic indices and their possible causes of change

Climate extremes have a significant impact on vegetation. However, little is known about vegetation response to climatic extremes in Bangladesh. The association of Normalized Difference Vegetation Index (NDVI) with nine extreme precipitation and temperature indices was evaluated to identify the nexus between vegetation and climatic extremes and their associations in Bangladesh for the period 1986-2017. Moreover, detrended fluctuation analysis (DFA) and Morlet wavelet analysis (MWA) were employed to evaluate the possible future trends and decipher the existing periodic cycles, respectively in the time series of NDVI and climate extremes. Besides, atmospheric variables of ECMWF ERA5 were used to examine the casual circulation mechanism responsible for climatic extremes of Bangladesh. The results revealed that the monthly NDVI is positively associated with extreme rainfall with spatiotemporal heterogeneity. Warm temperature indices showed a significant negative association with NDVI on the seasonal scale, while precipitation and cold temperature extremes showed a positive association with yearly NDVI. The DEA revealed a continuous increase in temperature extreme in the future, while no change in precipitation extremes. NDVI also revealed a significant association with extreme temperature indices with a time lag of one month and with precipitation extreme without time lag. Spatial analysis indicated insensitivity of marshy vegetation type to climate extremes in winter. The study revealed that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and low solar radiation with higher humidity contributed to climatic extremes in Bangladesh. The nexus between NDVI and climatic extremes established in this study indicated that increasing warm temperature extremes due to global warming might have severe implications on Bangladesh's ecology and the environment in the future.

Extreme climate projections under representative concentration pathways in the Lower Songkhram River Basin, Thailand

This paper aims to assess changes in the extreme climate indices of the Lower Songkhram River Basin of Thailand under Representative Concentration Pathways (RCPs) scenarios. A linear scaling method was used to correct climate data bias in three Regional Climate Models (RCMs) under RCP 4.5 and RCP 8.5 scenarios. Thereafter, extreme climate indices related to temperature and rainfall were analysed for the wet and dry seasons in upstream and downstream areas of the basin. A total of 14 climate indices were analysed for three time periods: the 2030s (2020–2044), 2055s (2045–2069), and 2080s (2070–2094) and compared with the baseline climate from 1980‒2004. The results show that considerable variability is expected in the extreme climate of the basin in future. The average annual and monthly maximum and minimum temperature is projected to increase, with a lesser increase in the near future and higher in the far future. Heat events (TXx, TXn) are projected to increase while the cold events (TNx, TNn) are projected to decrease in both dry and wet seasons upstream and downstream of the basin. The future average annual rainfall in the basin is projected to decrease under RCP 4.5 and RCP 8.5 scenarios for all three periods. However, the variability in average monthly rainfall is expected to increase in the dry season (Jan–May) and decrease in the wet (Aug–Dec). The most intense rainfall in one day (RX1Day) and five consecutive days (RX5Day) in the wet season is observed to increase in future, with a higher increase in the near future and a lower increase in the far future. The very heavy rainfall days (R20) (the number of days receiving more than 20 mm/day in the basin) are observed to decrease in both wet and dry seasons under RCP 4.5 and RCP 8.5 scenarios in both locations. The results of this study will be helpful for the planning and management of natural resources as well as disaster risk reduction in the Lower Songkhram River Basin.

Ten questions concerning occupant health in buildings during normal operations and extreme events including the COVID-19 pandemic

Even before the COVID-19 pandemic, people spent on average around 90% of their time indoors. Now more than ever, with work-from-home orders in place, it is crucial that we radically rethink the design and operation of buildings. Indoor Environmental Quality (IEQ) directly affects the comfort and well-being of occupants. When IEQ is compromised, occupants are at increased risk for many diseases that are exacerbated by both social and economic forces. In the U.S. alone, the annual cost attributed to sick building syndrome in commercial workplaces is estimated to be between $10 billion to $70 billion. It is imperative to understand how parameters that drive IEQ can be designed properly and how buildings can be operated to provide ideal IEQ to safeguard health. While IEQ is a fertile area of scholarship, there is a pressing need for a systematic understanding of how IEQ factors impact occupant health. During extreme events, such as a global pandemic, designers, facility managers, and occupants need pragmatic guidance on reducing health risks in buildings. This paper answers ten questions that explore the effects of buildings on the health of occupants. The study establishes a foundation for future work and provides insights for new research directions and discoveries.

The dynamics of plastic pellets on sandy beaches: A new methodological approach

Plastic found in the coastal zone is a result of waste mismanagement. This material comes directly from offshore disposal or by fishing debris, other marine activities, and by marine currents and winds, as well as urban drainage systems and estuaries. Specifically, in the case of plastic pellets, which are spheres with 2-5 mm that constitute the raw material for the manufacture of plastic products, the Santos Port and the plastic factories in Cubatão city (Brazilian southeastern coast), are considered the main local sources for the São Paulo state coast. Consequently, the beaches most affected by this pollutant are those near Santos estuary, like Enseada do Guarujá beach. However, some questions are still open, such as: what are the mechanisms which control the pellets deposition, and which locations are most favorable for deposition on the beach? To answer these questions, a four-step research was carried out at Enseada beach: 1) Plastic pellets geodetic survey based on GNSS positioning; 2) Beach geomorphometric parameters (altitude, aspect, and slope) derived by Digital Elevation Model (DEM); 3) Strandline altitude estimated through wave climate and tide height; and, 4) Plastic pellets deposition Suitability Index (PSI). The joint analysis of the altimetric, geomorphometric and meteoceanographic aspects showed that the beach areas with altitudes higher than those calculated for the strandline (>2.06 m), slope ~ 3° and facing the same direction of the higher energy waves (157.5-202.5°) were more susceptible to pellet deposition. This indicates that the accumulation of this pollutant on the beach is controlled not only by its physical characteristics, but mainly by storm surge events. Besides, surveys with geodetic reference (fixed, univocal, and relatively stable on time) bring up altimetric information as a result of all interactions and can be compared with other beaches anywhere on the planet - thus contributing to a standardization of the survey methodology.

How do rural-urban linkages change after an extreme flood event? Empirical evidence from rural communities in Pakistan

Extreme flood events can lead to dramatic changes in societal processes, disrupt rural-urban linkages and affect rural vulnerabilities. Changes in rural-urban linkages due to extreme flooding have been theoretically discussed with limited empirical evidence. Therefore, this study investigates the impacts of a flood event on linkages between rural and urban areas of Pakistan. This study also examines socioeconomic and spatial factors that can influence changes in rural-urban linkages. Three case studies were selected from the Punjab province of Pakistan, and a total of 325 samples were collected through household surveys. Descriptive statistics, binary logistic regression and correlation analysis were conducted to analyse the data. The findings show that flooding has severely affected rural communities directly and indirectly. This paper details the many different ways in which floods can change rural linkages with cities-i.e., the flow of people, information, finance, goods and services between rural and urban areas. The results also reveal that the age of household head, education, income and farming occupation are influential factors that affect how rural-urban linkages change. Most importantly, the research highlights that extreme flooding can both increase and decrease the dependence of rural communities on cities in different ways. This indicates that linkages between rural and urban areas need to be strengthened in order to reduce flood-related vulnerabilities. This study paves the way for regional planners and disaster managers to establish synergies for developing integrated flood risk management and development strategies.

Object-Based Comparison of Data-Driven and Physics-Driven Satellite Estimates of Extreme Rainfall

The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conventional "grid-by-grid analysis," the object-based approach provides a promising way to diagnose spatial properties of storms, trace them through space and time, and connect their accuracy to storm types and input data sources. The evolution of two tropical cyclones are generally captured by IMERG and NU-WRF, while the less organized spatial patterns of two mesoscale convective systems pose challenges for both. NU-WRF rain rates are generally more accurate, while IMERG better captures storm location and shape. Both show higher skill in detecting large, intense storms compared to smaller, weaker storms. IMERG's accuracy depends on the input microwave and infrared data sources; NU-WRF does not appear to exhibit this dependence. Findings highlight that an object-oriented view can provide deeper insights into satellite precipitation performance and that the satellite precipitation community should further explore the potential for "hybrid" data-driven and physics-driven estimates in order to make optimal usage of satellite observations.

Extreme events and emergency scales

An event is extreme if its magnitude exceeds the threshold. A choice of a threshold is subject to uncertainty caused by a method, the size of available data, a hypothesis on statistics, etc. We assess the degree of uncertainty by the Shannon's entropy calculated on the probability that the threshold changes at any given time. If the amount of data is not sufficient, an observer is in the state of Lewis Carroll's Red Queen who said "When you say hill, I could show you hills, in comparison with which you'd call that a valley". If we have enough data, the uncertainty curve peaks at two values clearly separating the magnitudes of events into three emergency scales: subcritical, critical, and extreme. Our approach to defining the emergency scale is validated by 39 years of Standard and Poor's 500 (S&P500) historical data.

Semi-probabilistic coastal flood impact analysis: From deterministic hazards to multi-damage model impacts

Coastal flood impact assessments are important tools for risk management and are performed by combining the hazard component with the vulnerability of exposed assets, to quantify consequences (or impacts) in terms of relative or absolute (e.g. financial) damage. The process generates uncertainties that should be taken into account for the correct representation of the consequences of floods. This study presents a coastal flood impact application at the spatial level of the Stavanger municipality (Norway), based on a multi-damage model approach able to represent impacts, and their overall uncertainty. Hazard modelling was performed using the LISFLOOD-FP code, taking into account historical extreme water level events (1988-2017) and relative sea level rise scenarios. Direct impacts were calculated in the form of relative and financial damage for different building categories, using flood damage curves. The results showed that the expected impacts are fewer than 50 flooded receptors and less than €1 million in damage in the current sea level scenario. The impacts could double by the end of the century, considering the most optimistic relative sea level scenario. The results were discussed considering the limitations of the approach for both hazard and impact modelling, that will be improved in future implementations. The outcome of this study may be useful for cost-benefit analyses of mitigation actions and local-scale plans for adaptation.

Estimating resilience of crop production systems: From theory to practice

Agricultural production systems are sensitive to weather and climate anomalies and extremes as well as to other environmental and socio-economic adverse events. An adequate evaluation of the resilience of such systems helps to assess food security and the capacity of society to cope with the effects of global warming and the associated increase of climate extremes. Here, we propose and apply a simple indicator of resilience of annual crop production that can be estimated from crop production time series. First, we address the problem of quantifying resilience in a simplified theoretical framework, focusing on annual crops. This results in the proposal of an indicator, measured by the reciprocal of the squared coefficient of variance, which is proportional to the return period of the largest shocks that the crop production system can absorb, and which is consistent with the original ecological definition of resilience. Subsequently, we show the sensitivity of the crop resilience indicator to the level of management of the crop production system, to the frequency of extreme events as well as to simplified socio-economic impacts of the production losses. Finally, we demonstrate the practical applicability of the indicator using historical production data at national and sub-national levels for France. The results show that the value of the resilience indicator steeply increases with crop diversity until six crops are considered, and then levels off. The effect of diversity on production resilience is highest when crops are more diverse (i.e. as reflected in less well correlated production time series). In the case of France, the indicator reaches about 60% of the value that would be expected if all crop production time-series were uncorrelated.

Comparison of Local, Regional, and Scaling Models for Rainfall Intensity-Duration-Frequency Analysis

Intensity-duration-frequency (IDF) analyses of rainfall extremes provide critical information to mitigate, manage, and adapt to urban flooding. The accuracy and uncertainty of IDF analyses depend on the availability of historical rainfall records, which are more accessible at daily resolution and, quite often, are very sparse in developing countries. In this work, we quantify performances of different IDF models as a function of the number of available high-resolution (N _τ ) and daily (N _24h) rain gauges. For this aim, we apply a cross-validation framework that is based on Monte Carlo bootstrapping experiments on records of 223 high-resolution gauges in central Arizona. We test five IDF models based on (two) local, (one) regional, and (two) scaling frequency analyses of annual rainfall maxima from 30-min to 24-h durations with the generalized extreme value (GEV) distribution. All models exhibit similar performances in simulating observed quantiles associated with return periods up to 30 years. When N _τ >10, local and regional models have the best accuracy; bias correcting the GEV shape parameter for record length is recommended to estimate quantiles for large return periods. The uncertainty of all models, evaluated via Monte Carlo experiments, is very large when N _τ ≤ 5; however, if N _24h ≥ 10 additional daily gauges are available, the uncertainty is greatly reduced and accuracy is increased by applying simple scaling models, which infer estimates on subdaily rainfall statistics from information at daily scale. For all models, performances depend on the ability to capture the elevation control on their parameters. Although our work is site specific, its results provide insights to conduct future IDF analyses, especially in regions with sparse data.

Heat-related mortality at the beginning of the twenty-first century in Rio de Janeiro, Brazil

Temperature record-breaking events, such as the observed more intense, longer-lasting, and more frequent heat waves, pose a new global challenge to health sectors worldwide. These threats are of particular interest in low-income regions with limited investments in public health and a growing urban population, such as Brazil. Here, we apply a comprehensive interdisciplinary climate-health approach, including meteorological data and a daily mortality record from the Brazilian Health System from 2000 to 2015, covering 21 cities over the Metropolitan Region of Rio de Janeiro. The percentage of absolute mortality increase due to summer extreme temperatures is estimated using a negative binomial regression modeling approach and maximum/minimum temperature-derived indexes as covariates. Moreover, this study assesses the vulnerability to thermal stress for different age groups and both genders and thoroughly analyzes four extremely intense heat waves during 2010 and 2012 regarding their impacts on the population. Results showed that the highest absolute mortality values during heat-related events were linked to circulatory illnesses. However, the highest excess of mortality was related to diabetes, particularly for women within the elderly age groups. Moreover, results indicate that accumulated heat stress conditions during consecutive days preferentially preceded by persistent periods of moderate-temperature, lead to higher excess mortality rather than sporadic single hot days. This work may provide directions in human health policies related to extreme climate events in large tropical metropolitan areas from developing countries, contributing to altering the historically based purely reactive response.

Evaluating SWAT model performance, considering different soils data input, to quantify actual and future runoff susceptibility in a highly urbanized basin

The Soil and Water Assessment Tool (SWAT) is a physical model designed to predict the hydrological processes that could characterize natural and anthropized watersheds. The model can be forced using input data of climate prediction models, soil characteristics and land use scenarios to forecast their effect on hydrological processes. In this study, the SWAT model has been applied in the Aspio basin, a small watershed, highly anthropized and characterized by a short runoff generation. Three simulations setup, named SL1, SL2 and SL3, were investigated using different soil resolution to identify the best model performance. An increase of space requirement and calibration time has been registered in conjunction with the increasing soil resolution. Among all simulations, SL1 has been chosen as the best one in describing watershed streamflow, despite it was characterized by the lower soil resolution. A map of susceptibility to runoff for the entire basin was so created reclassifying the runoff amount of four years in five classes of susceptibility, from very low to very high. Eleven sub-basins, coinciding with the main urban settlements, were identified as highly susceptible to runoff generation. Considering future climate predictions, a slight increase of runoff has been forecasted during summer and autumn. The map of susceptibility successfully identified as highly prone to runoff those sub-basins where extreme flood events were yet recorded in the past, remarking the reliability of the proposed assessment and suggesting that this methodology could represent a useful tool in flood managing plan.

Heat wave intensity can vary the cumulative effects of multiple environmental stressors on Posidonia oceanica seedlings

Climate change is introducing new stressors into already stressed ecosystems. Among these, extreme events such as heat waves play a crucial role in determining the structure of ecosystems. We tested single and combined effects of overgrazing, burial and heat waves on the seedlings of the habitat-forming species Posidonia oceanica. At current heat wave temperatures, overgrazing in isolation had more deleterious effects than seed burial, and effects were synergistic and additive when both factors co-occurred. The combined effect of overgrazing and seed burial with current heat waves could hamper P. oceanica seedling development, with similar or even higher levels than the sole effect of heat waves in the near future (29 °C). The effects of overgrazing and seed burial are expected to be overridden if heat waves temperatures exceed 29 °C. These results suggest that co-occurring environmental stressors, in combination with current heat waves, could compromise the sexual recruitment of this seagrass.

Legacy effects of drought on nitrate leaching in a temperate mixed forest on karst

With climate change the occurrence of summer droughts is expected to increase in Central Europe. This could lead to increased nitrate (NO₃^-) leaching when water scarcity affects the N-uptake capacity of trees and increases soil N availability due to early leaf senescence and higher litter input. In the present study, we used 16 years of ecological monitoring data from the LTER research site "Zöbelboden" in Austria. The monitoring site is a mixed Spruce-Sycamore-Ash-Beech forest on karst, which is representative for many watersheds that supply drinking water in Austria. We found that in the year after a summer drought, NO₃^- leaching via soil water seepage was significantly elevated compared to the long-term mean. While in normal years, NO₃^- leaching was primarily affected by soil water seepage volume, after a summer drought these controls changed and NO₃^- leaching was controlled by NO₃^- input via precipitation, tree N uptake, and vapor-pressure deficit. Furthermore, higher aboveground litter input during dry years was correlated with increased NO₃^- leaching in the following year. Our findings show that NO₃^- leaching from temperate mountain forests on karst is susceptible to summer drought, which could affect drinking water quality in the Central European Alps in the future, especially in combination with forest disturbances like bark beetle outbreaks, which are often a direct consequence of drought damage to trees.

Adverse weather conditions for UK wheat production under climate change

Winter wheat is an important crop in the UK, suited to the typical weather conditions in the current climate. In a changing climate the increased frequency and severity of adverse weather events, which are often localised, are considered a major threat to wheat production. In the present study we assessed a range of adverse weather conditions, which can significantly affect yield, under current and future climates based on adverse weather indices. We analysed changes in the frequency, magnitude and spatial patterns of 10 adverse weather indices, at 25 sites across the UK, using climate scenarios from the CMIP5 ensemble of global climate models (GCMs) and two greenhouse gas emissions (RCP4.5 and RCP8.5). The future UK climate is expected to remain favourable for wheat production, with most adverse weather indicators reducing in magnitude by the mid-21st century. Hotter and drier summers would improve sowing and harvesting conditions and reduce the risk of lodging. The probability of late frosts and heat stress during reproductive and grain filling periods would likely remain small in 2050. Wetter winter and spring could cause issues with waterlogging. The severity of drought stress during reproduction would generally be lower in 2050, however localised differences suggest it is important to examine drought at a small spatial scale. Prolonged water stress does not increase considerably in the UK, as may be expected in other parts of Europe. Climate projections based on the CMIP5 ensemble reveal considerable uncertainty in the magnitude of adverse weather conditions including waterlogging, drought and water stress. The variation in adverse weather conditions due to GCMs was generally greater than between emissions scenarios. Accordingly, CMIP5 ensembles should be used in the assessment of adverse weather conditions for crop production to indicate the full range of possible impacts, which a limited number of GCMs may not provide.

Impact of extreme temperatures on ambulance dispatches in London, UK

BACKGROUND

Associations between extreme temperatures and health outcomes, such as mortality and morbidity, are often observed. However, relatively little research has investigated the role of extreme temperatures upon ambulance dispatches.

METHODS

A time series analysis using London Ambulance Service (LAS) incident data (2010-2014), consisting of 5,252,375 dispatches was conducted. A generalized linear model (GLM) with a quasi-likelihood Poisson regression was applied to analyse the associations between ambulance dispatches and temperature. The 99^th (22.8°C) and 1^st (0.0°C) percentiles of temperature were defined as extreme high and low temperature. Fourteen categories of ambulance dispatches were investigated, grouped into 'respiratory' (asthma, dyspnoea, respiratory chest infection, respiratory arrest and chronic obstructive pulmonary disease), 'cardiovascular' (cardiac arrest, chest pain, cardiac chest pain RCI, cardiac arrhythmia and other cardiac problems) and 'other' non-cardiorespiratory (dizzy, alcohol related, vomiting and 'generally unwell') categories. The effects of long-term trends, seasonality, day of the week, public holidays and air pollution were controlled for in the GLM. The lag effect of temperature was also investigated. The threshold temperatures for each category were identified and a distributed lag non-linear model (DLNM) was reported using relative risk (RR) values at 95% confidence intervals.

RESULTS

Many dispatch categories show significant associations with extreme temperature. Total calls from 999 dispatches and 'generally unwell' dispatch category show significant RRs at both low and high temperatures. Most respiratory categories (asthma, dyspnoea and RCI) have significant RRs at low temperatures represented by with estimated RRs ranging from 1.392 (95%CI: 1.161-1.699) for asthma to 2.075 (95%CI: 1.673-2.574) for RCI. The RRs for all other non-cardiorespiratory dispatches were often significant for high temperatures ranging from 1.280 (95% CI: 1.128-1.454) for 'generally unwell' to 1.985 (95%CI: 1.422-2.773) for alcohol-related. For the cardiovascular group, only chest pain dispatches reported a significant RR at high temperatures.

CONCLUSIONS

Ambulance dispatches can be associated with extreme temperatures, dependent on the dispatch category. It is recommended that meteorological factors are factored into ambulance forecast models and warning systems, allowing for improvements in ambulance and general health service efficiency.

Does Climate Change Communication Matter for Individual Engagement with Adaptation? Insights from Forest Owners in Sweden

Natural resource managers urgently need to adapt to climate change, and extension services are increasingly using targeted communication campaigns to promote individual engagement with adaptation. This study compares two groups of Swedish forest owners: 1493 who participated in two climate communication projects by the Swedish Forest Agency, and 909 who were randomly sampled. The study finds statistically significant differences between the two groups in terms of climate change awareness and concern, belief in the urgency to act and intentions to take adaptive measures. Results suggest that the primary effect of the climate chance communication seems to have been on forest owners' subjective risk perceptions and beliefs in their knowledge and ability, which make it more likely that individuals will take adaptive action in the future. The study also finds that experience with extreme events affects people's intentions to take adaptive measures independently from their beliefs that these extremes were caused by climate change. Furthermore, findings also highlight the need for communication research and practice to recognise the impeding role social norms and economic rationales can play for individual adaptation. Future research should make use of longitudinal and qualitative research to assess the effect of deliberation- and solution-orientated communication on people's intentions and actions to adapt to climate change.

Pelagic harmful algal blooms and climate change: Lessons from nature's experiments with extremes

Time series now have sufficient duration to determine harmful algal bloom (HAB) responses to changing climate conditions, including warming, stratification intensity, freshwater inputs and natural patterns of climate variability, such as the El Niño Southern Oscillation and Pacific Decadal Oscillation. Against the context of time series, such as those available from phytoplankton monitoring, dinoflagellate cyst records, the Continuous Plankton Recorder surveys, and shellfish toxin records, it is possible to identify extreme events that are significant departures from long-term means. Extreme weather events can mimic future climate conditions and provide a "dress rehearsal" for understanding future frequency, intensity and geographic extent of HABs. Three case studies of extreme HAB events are described in detail to explore the drivers and impacts of these oceanic outliers that may become more common in the future. One example is the chain-forming diatom of the genus Pseudo-nitzschia in the U.S. Pacific Northwest and its response to the 2014-16 northeast Pacific marine heat wave. The other two case studies are pelagic flagellates. Highly potent Alexandrium catenella group 1 dinoflagellate blooms (up to 150 mg/kg PST in mussels; 4 human poisonings) during 2012-17 created havoc for the seafood industry in Tasmania, south-eastern Australia, in a poorly monitored area where such problems were previously unknown. Early evidence suggests that changes in water column stratification during the cold winter-spring season are driving new blooms caused by a previously cryptic species. An expansion of Pseudochattonella cf. verruculosa to the south and A. catenella to the north over the past several years resulted in the convergence of both species to cause the most catastrophic event in the history of the Chilean aquaculture in the austral summer of 2016. Together, these two massive blooms were colloquially known as the "Godzilla-Red tide event", resulting in the largest fish farm mortality ever recorded worldwide, equivalent to an export loss of USD$800 million which when combined with shellfish toxicity, resulted in major social unrest and rioting. Both blooms were linked to the strong El Niño event and the positive phase of the Southern Annular Mode, the latter an indicator of anthropogenic climate change in the southeastern Pacific region. For each of these three examples, representing recent catastrophic events in geographically distinct regions, additional targeted monitoring was employed to improve the understanding of the climate drivers and mechanisms that gave rise to the event and to document the societal response. Scientists must be poised to study future extreme HAB events as these natural experiments provide unique opportunities to define and test multifactorial drivers of blooms.