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Extreme climate events can have significant consequences on ecosystems and by extension human populations. Over 50 million of the world's lakes typically freeze each winter, and the absence of winter ice cover, in lakes where ice has historically been present, can be characterized as an extreme event. We quantified the effects of extreme climate events on lake ice cover using 78‐year ice records from 122 lakes to show that (1) extreme ice‐free years are becoming more frequent and severe, (2) winter air temperature is a significant predictor of ice cover that was driven by large‐scale climate oscillations, (3) extremes in temperature are closely related to extremes in ice cover, and (4) ice‐free years are forecasted to result in significant loss of ice‐cover in the future. Without drastic reductions in carbon emissions, we can expect the widespread loss of lake ice cover could have significant socioeconomic and biological implications. Plain Language Summary: Climate change is expected to have a large impact on humans and our natural systems. Freshwater lakes are an important resource and each year, millions around the world freeze during the winter months. However, climate change is expected to threaten the freezing of some of these lakes. We explored 122 lakes that typically freeze over winter and that had records of freeze/thaw since 1939. We asked, do extremes in winter air temperature affect extremes in lake ice cover and what would that mean for the future? Winter air temperature was found to closely predict ice‐free years for lakes. Years with abnormally hot winters were also years where many lakes remained ice‐free. Projecting into the future, we predicted that lakes will continue to experience more ice‐free years. With a reduction in carbon emissions, there will be a modest increase in ice‐free years, but if carbon emissions continue as they are currently, there could be a large increase in ice‐free lakes. This study highlights lake ice as another victim of climate change. The loss of lake ice will have impacts to natural systems and also socioeconomic implications for human populations that are dependent on it. Key Points: Observed recent increases in ice‐free years for 122 lakes since 1939Extremes in winter air temperature were observed to closely relate to extremes in ice‐free cover for lakesUsing climate change scenarios, ice‐free years for lakes are predicted to increase significantly in the next decades [ABSTRACT FROM AUTHOR]

Extreme climate events such as hurricanes can influence the movement and distribution of fish and other aquatic vertebrates. However, our understanding of the scale of movement responses and how they vary across taxa and ecosystems remains incomplete. In this study, we used acoustic telemetry data to investigate the movement patterns of common snook (Centropomus undecimalis) in the Florida Coastal Everglades during Hurricane Irma, which made landfall on the southwest Florida coast as a Category 3 storm on 10 September 2017 after passing in close proximity to our study site. We hypothesized that the hurricane resulted in shifts in distribution and that these movements may have been driven by environmental cues stemming from changes in barometric pressure associated with hurricane conditions, fluctuations in water levels (stage) characterizing altered riverine conditions, or a combination of both hurricane and riverine drivers. The data revealed large-scale movements of common snook in the time period surrounding hurricane passage, with 73% of fish detected moving from the upper river into downriver habitats, and some individuals potentially exiting the river. Furthermore, regression model selection indicated that these movements were correlated to both hurricane and riverine conditions, showing increased common snook movement at higher river stage and lower barometric pressure, and stage explaining a larger proportion of model deviance. Animal movement has widespread and diverse ecological implications, and by better understanding the factors that drive movement, we may anticipate how future extreme climate events could affect fish populations in impact-prone regions. [ABSTRACT FROM AUTHOR]

Extreme climate events such as droughts, cold snaps, and hurricanes can be powerful agents of natural selection, producing acute selective pressures very different from the everyday pressures acting on organisms. However, it remains unknown whether these infrequent but severe disruptions are quickly erased by quotidian selective forces, or whether they have the potential to durably shape biodiversity patterns across regions and clades. Here, we show that hurricanes have enduring evolutionary impacts on the morphology of anoles, a diverse Neotropical lizard clade. We first demonstrate a transgenerational effect of extreme selection on toepad area for two populations struck by hurricanes in 2017. Given this short-term effect of hurricanes, we then asked whether populations and species that more frequently experienced hurricanes have larger toepads. Using 70 y of historical hurricane data, we demonstrate that, indeed, toepad area positively correlates with hurricane activity for both 12 island populations of Anolis sagrei and 188 Anolis species throughout the Neotropics. Extreme climate events are intensifying due to climate change and may represent overlooked drivers of biogeographic and large-scale biodiversity patterns. [ABSTRACT FROM AUTHOR]

Hurricanes are expected to increase in both frequency and intensity as a result of climate change, but the impacts of these disturbances on the evolutionary trajectories of the species they affect are not yet well understood. In this project, we investigated population-level changes in morphology in the lizard Anolis carolinensis after Hurricane Irma in 2017. We found that anole populations were morphologically distinct after the hurricane, exhibiting significantly longer forelimbs and hindlimbs compared with pre-hurricane measurements. These morphological changes were consistent across two replicate islands and between males and females. The observed morphological shifts were potentially driven by positive selection from Hurricane Irma on clinging capacity. In this opportunistic study, we documented post-hurricane changes in the morphology of island lizards and suggest the potential for increasingly frequent and intense hurricanes to play an important role in natural selection and anole evolution. [ABSTRACT FROM AUTHOR]

• Vegetation succession was abrupt, rather than gradual, in emerging coastal wetlands. • Phragmites might expand to areas where sedimentation lowered flooding frequency to below a threshold. • Abrupt Phragmites expansion, however, did not occur without extremely high precipitation. • Combining extreme climates with local hydro-conditions is critical for wetland vegetation management. Climate change is projected to increase extreme precipitation events in coming decades. Although extreme precipitation events have been reported to cause vegetation degradation, how they affect replacement of dominant species in vegetation succession remains poorly understood. By analyzing two decades' vegetation dynamics in emerging coastal wetlands on four fluvial islands, we investigate the roles of extreme precipitation events in the shifts of dominant vegetation. We found that shifts in the dominant vegetation from Suaeda salsa to Phragmites australis were abrupt, rather than gradual. Phragmites coverage varied in a nonlinear, threshold manner along flooding gradients across the islands, being very high where flooding frequency was below the threshold flooding frequency (18–40%, depending on island) and minimal elsewhere. Although with time sedimentation lowered flooding frequency to below these thresholds, abrupt shifts from Suaeda to Phragmites did not take place until extremely wet years occurred, likely because extreme precipitation was necessary to decrease salinity stress and to allow this relatively salt-intolerant plant to proliferate. Our findings reveal that extreme precipitation events may play a key role in triggering abrupt vegetation succession and provide a novel addition to previous views that vegetation succession in emerging coastal wetlands is driven primarily by sedimentation-mediated flooding changes and plant-plant interactions. Combining extreme climate events with local hydrological conditions is thus critical for vegetation management in coastal wetlands (including those under restoration) in an increasingly anthropogenic hydrosphere. [ABSTRACT FROM AUTHOR]

Based on the outputs from 21 CMIP5 (Coupled Model Intercomparison Project phase 5) models, future changes in the mean temperature, precipitation and four climate extreme indices (annual maximum of daily maximum temperature (TXx), minimum of daily minimum temperature (TNn), annual total precipitation when the daily amount exceeds the 95th percentile of wet-day precipitation (R95p), and maximum consecutive 5-day precipitation (RX5day)) over Hindu Kush Himalayan (HKH) region are investigated under the greenhouse gas concentration pathways of RCP4.5 and RCP8.5. Two periods of the 21st century, 2036–2065 and 2066–2095, are selected, with the reference period is considered as 1976–2005. Results show general increase of the mean temperature, TXx and TNn under both scenarios, with the largest increases found during 2066–2095 under RCP8.5. Future precipitation is projected to increase over most part of HKH, except for the northwestern part. Intensification of the precipitation extremes is projected over the region. The uncertainties of mean temperature, TXx and TNn over the HKH1 subregions are the largest compared to the other three subregions and the overall HKH. Besides RX5day during 2036–2065 over HKH1, the uncertainties of R95p and RX5day tend to be larger following the increase of greenhouse gas concentrations. The multimodel ensemble medians of temperature and four extreme indices under RCP8.5 are projected to be larger than those under RCP4.5 in each of the subregions.

Recent increases in the frequency of extreme climate events (ECEs) such as heatwaves and floods have been attributed to climate change, and could have pronounced ecosystem and evolutionary impacts because they provide little opportunity for organisms to acclimate or adapt. Here we synthesize information on a series of ECEs in Australia from 2011 to 2017 that led to well-documented, abrupt, and extensive mortality of key marine habitat-forming organisms – corals, kelps, seagrasses, and mangroves – along >45% of the continental coastline of Australia. Coral bleaching occurred across much of northern Australia due to marine heatwaves (MHWs) affecting different regions in 2011, 2013, 2016, and 2017, while seagrass was impacted by anomalously high rainfall events in 2011 on both east and west tropical coasts. A MHW off western Australia (WA) during the 2011 La Niña extended into temperate and subtropical regions, causing widespread mortality of kelp forests and seagrass communities at their northern distribution limits. Mangrove forests experienced high mortality during the 2016 El Niño across coastal areas of northern and north-WA due to severe water stress driven by drought and anomalously low mean sea levels. This series of ECEs reflects a variety of different events – MHWs, intense rainfall from tropical storms, and drought. Their repeated occurrence and wide extent are consistent with projections of increased frequency and intensity of ECEs and have broad implications elsewhere because similar trends are predicted globally. The unprecedented and widespread nature of these ECE impacts has likely produced substantial ecosystem-wide repercussions. Predictions from ecosystem models suggest that the widespread mortality of habitat-forming taxa will have long-term and in some cases irreversible consequences, especially if they continue to become more frequent or severe. The abrupt ecological changes that are caused by ECEs could have greater long-term impacts than slower warming that leads to gradual reorganization and possible evolution and adaptation. ECEs are an emerging threat to marine ecosystems, and will require better seasonal prediction and mitigation strategies.

A central question in contemporary ecology is how climate change will alter ecosystem structure and function across scales of space and time. Climate change has been shown to alter ecological patterns from individuals to ecosystems, often with negative implications for ecosystem functions and services. Furthermore, as climate change fuels more frequent and severe extreme climate events (ECEs) like marine heatwaves (MHWs), such acute events become increasingly important drivers of rapid ecosystem change. However, our understanding of ECE impacts is hampered by limited collection of broad scale in situ data where such events occur. In 2011, a MHW known as the Ningaloo Niño bathed the west coast of Australia in waters up to 4°C warmer than normal summer temperatures for almost 2 months over 1000s of kilometers of coastline. We revisit published and unpublished data on the effects of the Ningaloo Niño in the seagrass ecosystem of Shark Bay, Western Australia (24.6–26.6° S), at the transition zone between temperate and tropical seagrasses. Therein we focus on resilience, including resistance to and recovery from disturbance across local, regional and ecosystem-wide spatial scales and over the past 8 years. Thermal effects on temperate seagrass health were severe and exacerbated by simultaneous reduced light conditions associated with sediment inputs from record floods in the south-eastern embayment and from increased detrital loads and sediment destabilization. Initial extensive defoliation of Amphibolis antarctica, the dominant seagrass, was followed by rhizome death that occurred in 60–80% of the bay's meadows, equating to decline of over 1,000 km2 of meadows. This loss, driven by direct abiotic forcing, has persisted, while indirect biotic effects (e.g., dominant seagrass loss) have allowed colonization of some areas by small fast-growing tropical species (e.g., Halodule uninervis). Those biotic effects also impacted multiple consumer populations including turtles and dugongs, with implications for species dynamics, food web structure, and ecosystem recovery. We show multiple stressors can combine to evoke extreme ecological responses by pushing ecosystems beyond their tolerance. Finally, both direct abiotic and indirect biotic effects need to be explicitly considered when attempting to understand and predict how ECEs will alter marine ecosystem dynamics.

Global climate changes have led to ocean acidification, ice and snow melting, a continuous rise in temperature, and an increasing frequency of extreme weather events, with profound impacts on the social economic system. With the aggravation from climate changes, even the industrial fields with a relatively strong resistance to climatic changes have also suffered serious losses. At present, the vulnerability of the industrial field is growing, and the absolute economic losses are increasing. The quantitative evaluation of these industrial economic losses is therefore an important basis for formulating policies to tackle global climate change, and analyzing the current research progress can provide ideas and methods for the effective evaluation of the industrial economy. Therefore, in this paper, we summarized both the positive and negative effects of climate changes on the industrial fields and found that the influences of climatic changes on different industrial sectors are slightly variable. For example, while the mining industry, so far, has positively responded to the changing climate, severe weather events such as storms, drought, and rain could severely impede the normal production and business operation activities of the mining industry in the future. The manufacturing industry mostly involves indoor jobs, which are relatively resistant to extreme weather events, and some industries have complex response mechanisms. In terms of the construction industry, its losses are mainly indirect through increased electricity costs. The production and supply industries for electricity, heat, and water would suffer transmission supply losses in extreme weather events; and as the largest carbon emission industries, the costs of emission reduction would affect the economic growth of this sector in the short term. Overall, the industrial sectors pay relatively high costs for climate change mitigation and adaptation, and therefore, the quantitative evaluation of industrial economic losses through models is crucial for both the development of reasonable policies and ensuring a smooth and consistent growth of the industrial economy. [ABSTRACT FROM AUTHOR]

Quantifying the impact of urbanization on extreme climate events is significant for ecosystem responses, flood control, and urban planners. This study aimed to examine the urbanization effects on a suite of 36 extreme temperature and precipitation indices for the Beijing-Tianjin-Hebei (BTH) region by classifying the climate observations into three different urbanization levels. A total of 176 meteorological stations were used to identify large cities, small and medium-size cities and rural environments by applying K-means cluster analysis combined with spatial land use, nighttime light remote sensing, socio-economic data and Google Earth. The change trends of the extreme events during 1980–2015 were detected by using Mann-Kendall (MK) statistical test and Sen's slope estimator. Urbanization effects on those extreme events were calculated as well. Results indicated that the cool indices generally showed decreasing trends over the time period 1980–2015, while the warm indices tended to increase. Larger and more significant changes occurred with indices related to the daily minimum temperature. The different change rates of temperature extremes in urban, suburban and rural environments were mainly about the cool and warm night indices. Urbanization in medium-size cities tended to have a negative effect on cool indices, while the urbanization in large cities had a positive effect on warm indices. The significant difference of urbanization effect between large and medium-size cities lay in the daily maximum temperature. Results also demonstrated the scale effect of the urbanization on the extreme temperature events. However, the results showed little evidence of the urban effect on extreme precipitation events in the BTH region. This paper explored the changes in temperature and precipitation extremes and qualified the urbanization effects on those extreme events in the BTH region. The findings of this research can provide new insights into the future urban agglomeration development projects. Unlabelled Image • Urbanization effects on extreme climate events were estimated. • The scale effects of urbanization on extreme events were revealed. • Significant changes occurred with indices related to the daily minimum temperature. • Main difference between urban and suburban areas lay in daily maximum temperature. • Little evidence of the urbanization effect on precipitation extremes was found. [ABSTRACT FROM AUTHOR]

The possibility of an occurrence of adverse selection in the agricultural insurance market in Brazil is evaluated. Adverse selection occurs when insurances are primarily contracted by agents, at high risks. The hypothesis is that the phenomenon may be triggered by increase in value compensated in accidents derived from extreme climate changes that would cause increase in the premiums demanded by the insurance companies. The most expensive premiums cause portfolios to be primarily composed of high-risk insurance, increasing the occurrence of compensation for losses. Linear regression analyses were performed between losses, which occurred in one year, and contracts for the following year, between 2003 and 2013 for six Brazilian states: Mato Grosso do Sul (MS); Minas Gerais (MG); Paraná (PR); Santa Catarina (SC); Rio Grande do Sul (RS); and São Paulo (SP). The significance of data linear regressions was estimated by randomized statistical tests. The occurrence of adverse selection between 2003 and 2013 could be inferred in the case of the states of MS, RS and SP. Results contribute towards the characterization and identification of the adverse selection phenomenon that causes high loss rates in the Brazilian agricultural insurance market. [ABSTRACT FROM AUTHOR]

• A hybrid model was developed by integrating the APSIM model and the RF model • The hybrid model outperformed the APSIM model in predicting observed wheat yield • The APSIM model might underestimate future yield losses caused by climate extremes • Increasing heat events were identified to be the major factor causing future yield losses Accurately assessing the impacts of extreme climate events (ECEs) on crop yield can help develop effective agronomic practices to deal with climate change impacts. Process-based crop models are useful tools to evaluate climate change impacts on crop productivity but are usually limited in modelling the effects of ECEs due to over-simplification or vague description of certain process and uncertainties in parameterization. In this study, we firstly developed a hybrid model by incorporating the APSIM model outputs and growth stage-specific ECEs indicators (i.e. frost, drought and heat stress) into the Random Forest (RF) model, with the multiple linear regression (MLR) model as a benchmark. The results showed that the APSIM + RF hybrid model could explain 81% of the observed yield variations in the New South Wales wheat belt of south-eastern Australia, which had a 33% improvement in modelling accuracy compared to the APSIM model alone and 19% improvement compared to the APSIM + MLR hybrid model. Drought events during the grain-filling and vegetative stages and heat events immediately prior to anthesis were identified as the three most serious ECEs causing yield losses. We then compared the APSIM + RF hybrid model with the APSIM model to estimate the effects of future climate change on wheat yield. It was interesting to find that future yield projected from single APSIM model might have a 1–10% overestimation compared to the APSIM + RF hybrid model. The APSIM + RF hybrid model indicated that we were underestimating the effects of climate change and future yield might be lower than predicted using single APSIM informed modelling due to lack of adequately accounting for ECEs-induced yield losses. Increasing heat events around anthesis and grain-filling periods were identified to be major factors causing yield losses in the future. Therefore, we conclude that including the effects of ECEs on crop yield is necessary to accurately assess climate change impacts. We expect our proposed hybrid-modelling approach can be applied to other regions and crops and offer new insights of the effects of ECEs on crop yield. [ABSTRACT FROM AUTHOR]

Climate change has introduced a new social group called "Climate migrants'.' In 1995, approximately 25 million people worldwide were considered to be environment or climate refugees, it is anticipated that this number will have increased to 200 million by 2050. Bangladesh is one of the countries highly exposed to extreme "climate" and an appropriate place to study climate-induced migration. With an empirical field research through stratified sampling techniques amongst migrants, this article examines the drivers of migration, impacts on individual and family livelihoods of the explosion of climate migrants to analyse how consideration of this growing body of climate migrants fits with traditional migration theory. [ABSTRACT FROM AUTHOR]

In this study, the performance of the Beijing Climate Center (BCC) Climate System Model version 1.1 (BCC-CSM1.1) (280-km resolution) and the BCC-CSM1.1m (110-km resolution) in simulating extreme climate events over China in the last 40 years is compared. Both models capture the main spatial distribution features of heavy precipitation (R95T), the number of consecutive wet days (CWD), the annual count of days with precipitation mm (R1), the maximum consecutive 5-day precipitation (Rx5), and the numbers of frost days (FD) and summer days (SU). The BCC-CSM1.1m has a better ability to simulate the detailed distribution of extreme climate events than the BCC-CSM1.1, including R95T, CWD, R1, and the simple precipitation intensity index (SDII). However, the BCC-CSM1.1m does not show an improvement in simulating the number of days with extreme precipitation (R90N), the number of consecutive dry days (CDD), the heat wave duration index (HWDI), the warm day frequency (TX90P), and cold night frequency (TN10P). This indicates that the simulation of the R95T, CWD, R1, and SDII climate events is more sensitive to the resolution of the model. The improved BCC-CSM1.1m is used to explore the projection of extreme climate change in China during the 21st century under the RCP4.5 (Representative Concentration Pathways) and RCP8.5 scenarios. The results show that extreme precipitation will increase dramatically over North and Southwest China in the late 21st century. The CWD index will decrease on the Tibetan Plateau and in northeastern and central China and will increase in other parts of China; R1 will increase in northern China and decrease in southern China; Rx5 will increase dramatically in southern China; FD will decrease and SU will increase over China in the late 21st century under both emission scenarios, with larger amplitudes in RCP8.5. [ABSTRACT FROM AUTHOR]

The Wolonghu Wetlands is an essential ecological barrier to resist southward expansion of the Horqin Desert, also is an important stopover and energy supplement site for the global birds migrating in the route of East Asia to Australia. This paper aims to clarify the characteristics of Climate Change and adaptability assessment of migratory bird habitats in Wolonghu Wetlands. The study used the historical measured data of the past 60 years and the predicted results by CMIP5 climate model to analyze the variation and development trend of temperature and precipitation in history and future. The impacts of extreme weather events on migratory bird habitats have been analyzed as well. The results show that: (1) The water level is one of the important factors affecting the birds and their habitat in Wolonghu Wetlands. The water level dropped from 88.9 m to 87.83 m, and the number of birds raised by 2orders of magnitude. (2) The whole climate is getting warmer and wetter. (3) In the past 60 years, extreme precipitation accounted for 19% of total precipitation, and 7.7% in July. In the next 30 years, extreme precipitation accounts for 13.9% of the total precipitation in the RCP4.5 scenario, and 10.1% in July. Compared with history, extreme precipitation is more concentrated in July. (4) In the past 60 years, no severe drought and extraordinary drought occurred in summer. The occurrence probability of above extreme events in the next 30 years is 1.83%. This study can provide some references for relevant management departments of Wolonghu Wetlands to formulate wetland protection and restoration measures. [ABSTRACT FROM AUTHOR]

A catastrophic tailings dam failure disaster occurred in Brumadinho, Brazil on 25 January 2019, which resulted in over 270 casualties, 24,000 residents evacuated, and a huge economic loss. Environmental concerns were raised for the potential pollution of water due to tailings waste entering the Paraopeba River. In this paper, a detailed analysis has been carried out to investigate the disaster conditions of the Brumadinho dam failure using satellite images with different spatial resolutions. Our in-depth analysis reveals that the hazard chain caused by this failure contained three stages, namely dam failure, mudflow, and the hyperconcentrated flow in the Paraopeba River. The variation characteristics of turbidity of the Rio Paraopeba River after the disaster have also been investigated using high-resolution remote sensing images, followed by a qualitative analysis of the impacts on the downstream reservoir of the Retiro Baixo Plant that was over 300 km away from the dam failure origin. It is believed that, on the one hand, the lack of dam stability management at the maintenance stage was the main cause of this disaster. On the other hand, the abundant antecedent precipitation caused by extreme weather events should be a critical triggering factor. Furthermore, the spatiotemporal pattern mining of global tailings dam failures revealed that the Brumadinho dam disaster belonged to a Consecutive Hot Spot area, suggesting that the regular drainage inspection, risk assessment, monitoring, and early warning of tailings dam in Consecutive Hot Spot areas still need to be strengthened for disaster mitigation.

• The climate of the QTP has been wetter and warmer during the past decades. • Annual streamflow of twelve natural rivers had dominant periodicities of 2–7 years. • Long-term patterns of large-scale climate phenomena can affect regional climate change. • Annual streamflow variability is strongly influenced by extreme climate in the QTP. • Effect of SSN can be transferred to the hydrological cycle by modulating ENSO and PDO. Solar activity and large-scale climate phenomena have significant effects on extreme climate events and streamflow variability. As the roof of the world and the water tower of Asia, the Qinghai-Tibet Plateau (QTP) is highly sensitive to climate change. Therefore, it is of great significance to study the relationship between extreme hydrometeorological events of the QTP and climate change for global hydroclimate research. In this study, we analyzed the spatiotemporal variation and significant oscillation period of several hydrometeorological variables such as extreme precipitation indices (EPIs), extreme temperature indices (ETIs) and annual streamflow variability based on the observation data of hydrometeorological stations in the QTP during 1962–2019 using Sen's slope estimator, Mann-Kendall test and continuous wavelet analysis (CWT). And the teleconnection patterns and the lead-lag relationship between annual precipitation, extreme climate events, multiple nonstationary climate mode and annual streamflow were evaluated using wavelet coherence (WTC). The results show that the climate of the QTP has been wetter and warmer in the past 58 years. The annual streamflow of several natural rivers in the QTP mainly show an increasing trend over the last 60 years. The annual streamflow of natural river (except Yellow River) increases significantly in three-rivers headwater region, and the rivers in the northeast and northwest also show a significant increase trend, but there is no significant change in the natural river streamflow in the south of QTP. In addition, the annual streamflow of natural rivers had significant periodicities in the bands of 2–4 years, 4–7 years and 7–11 years. The significant coherence of WTC spectra between annual precipitation and streamflow indicate that precipitation is the main reason for annual streamflow variation in the QTP. The variation of extreme climate events significantly regulates the regional annual streamflow. All EPIs except consecutive dry days show an in-phase correlation with annual streamflow of most headwater. Annual streamflow of Naijin River is positively and negatively correlated with extreme warm and extreme cold, respectively, and has a clearer lead-lag relationship than that with EPIs. Annual streamflow of headwater has higher correlations with EI Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) than with sunspot number (SSN). Solar activity may first affect ENSO and PDO, and then this effect is transferred sequentially to the hydrological cycle of the QTP by SSN-modulated PDO and PDO-SSN co-modulated ENSO. It is of great significance to investigate the response of streamflow variation to annual precipitation, extreme climate events and large-scale climate phenomena for water resources management, flood control, ecosystem restoration, and the well-being of surrounding residents and sustainable development in the QTP. [ABSTRACT FROM AUTHOR]

This study addresses the occurrence of extreme values of chlorophyll-a concentrations in European seas, using the satellite's OBGP MODIS AQUA v2018 dataset, for the 2003–2021 period. Two novel and complementary statistical indices based on the combination of the overall period's and the monthly 90th percentiles (P90 and mP90, respectively) are proposed: (i) the Extreme Highest exceedances (EH) include the observations with highest chlorophyll-a magnitudes in each location (larger than P90 and mP90); (ii) the Extreme Anomalous exceedances (EA) address the observations larger than mP90 but lower than P90, thus representing relevant anomalies during low phytoplankton growing seasons. Given the important differences of available observations per pixel, the EH and EA exceedances are normalized and also presented in percentage units. Although the occurrence of these indices greatly varies in time and space, the aggregated statistics and maps reveal some clear patterns: EH and EA have very distinct (almost complementary) seasonal and spatial distribution, EH prevail in mesotrophic and euphotic waters during the main interannual bloom season whilst EA are more abundant in oligotrophic waters out of the main seasonal bloom in each area. Both significant (p < 0.05) increasing and decreasing annual trends have been found in different European Seas. Overall, these EH and EA trends are reflecting the climate-driven physical and ecological changes in European Seas. Although these results and the conceptual and computational simplicity of these indices are encouraging, further ground truth testing is required to account for their uncertainties, mostly related to data representativeness and the performance of the chlorophyll-a estimation algorithms. [Display omitted] • EH and EA combine the overall period's and the monthly 90th percentile thresholds. • Their patterns are linked with the phytoplankton blooms intensity and phenology. • The occurrence of these indices greatly varies interannually and regionally. • Increasing trends of EH and EA occupy bigger areas. • Decreasing trends are found in areas recovering from very altered past situations. [ABSTRACT FROM AUTHOR]

Extreme weather events are expected to increase worldwide, therefore, anticipating and calculating their effects on crop yields is important for topics ranging from food security to the economic viability of biomass products. Given the local nature of weather, particularly precipitation, effects are best measured at a local level. This paper analyzes weather events at the level of the farm for a specific crop, winter wheat. Once it has been established that extreme events are expected to continue occurring at historically high levels for farming locations throughout the Netherlands, the effects of those events on wheat yields are estimated while controlling for the other major input factors affecting yields. Econometric techniques are applied to an unbalanced panel data set of 334 farms for a period of up to 12 years. Analyzes show that the number of days with extreme high temperatures in Dutch wheat growing regions has significantly increased since the early 1900s, while the number of extreme low temperature events has fallen over that same period. The effects of weather events on wheat yields were found to be time specific in that the week in which an event occurred determined its effect on yields. High temperature events and precipitation events were found to significantly decrease yields.

The exceptional severity of recent climate extremes has raised the question of whether some events would have been impossible in the absence of global warming. This question is critical for climate adaptation, but is challenging to answer given the length and non-stationarity of the observational record. The large single-model ensemble climate simulations archived in the Coupled Model Intercomparison Project (CMIP6) offer a unique opportunity to explore whether the hottest temperatures of the current climate are more extreme than any that could have occurred in the absence of human forcings. We first analyze the one CMIP6 model that has daily data archived for large ensembles in both the historical all-forcings and historical natural forcings experiments. We find that, for large areas of the world, the maximum daily-, seasonal- and annual-scale thresholds of the large single-model ensemble with natural and human forcings (‘all-forcings’) are never reached in the large single-model ensemble with only natural forcings. However, we also identify widespread areas—notably in the northern hemisphere mid-latitudes—where the hottest thresholds of the all-forcings ensemble are frequently exceeded in the absence of human forcings. Further analysis suggests that human forcings other than greenhouse gases (GHGs) are a primary cause of this discrepancy. For example, when comparing the late and early periods of the CMIP6 historical all-forcings experiment, other large single-model ensembles exhibit similar muting of extremely warm years over northern-hemisphere mid-latitude regions. However, under GHG-only forcing, all years in the recent period are hotter than the hottest early-period year over most of the globe. These results suggest that, although the hottest possible events in the current climate may have been virtually impossible in the absence of historical GHG emissions, other non-GHG anthropogenic forcings have muted the emergence of previously impossible events.

Vegetation net primary production (NPP) is an essential index for determining the quality of terrestrial ecosystems and their potential carbon storage ability. The impacts of extreme climate events on vegetation NPP are different under different altitude gradients. However, the research on the impact of extreme climate events on the spatial variation in vegetation NPP and the coupling effects under different altitude conditions remain insufficient. Using the MOD17A3HGF remote sensing data set and RClimDex 1.9 software, the vegetation NPP and 10 extreme climate indices in the Songhua River Basin from 2001 to 2020 were calculated, respectively. The spatial and temporal evolution characteristics of vegetation NPP and its response mechanism to extreme climate events in the Songhua River Basin under different altitude gradients were analyzed by means of trend analysis, correlation analysis, regression analysis, GeoDetector, and relative importance analysis. The results showed that:① the vegetation NPP (calculated by C) in the Songhua River Basin increased significantly at the rate of 4.13 g·(m 2 ·a) -1 from 2001 to 2020 ( P &lt; 0.01), and the rates of 3.65, 4.04, 4.70, 5.09, and 4.57 g·(m 2 ·a) -1 at the altitude gradients of 29-255, 255-440, 440-658, 658-935, and 935-2 589 m, respectively ( P &lt; 0.01). ② The spatial distribution pattern of vegetation NPP presented "high around and low in the middle," and the fluctuation of vegetation NPP in high altitude areas was more obvious than that in low altitude areas; for example, the average value of vegetation NPP at an altitude gradient from 29 to 255 m had a lower value, whereas the other altitude gradients had higher mean values than the mean value of the basin. ③ The extreme precipitation events in the Songhua River Basin were the main influencing factors of vegetation NPP, i.e., the vegetation NPP in low-altitude areas was mainly affected by extreme precipitation events, whereas the values in high-altitude areas were affected by both extreme precipitation events and extreme temperature events. The results of this research can provide a scientific basis for improving the carbon cycle model of the terrestrial ecosystem in the Songhua River Basin, quantifying the ability of carbon storage of vegetation and formulating policies to deal with climate change.

Weakening of annual temperature cycle (ATC) on the Tibetan Plateau (TP) in the last decades has been identified, and there is a subsequent change in the frequency of the ATC magnitude extremes. These changes in the climate have a potential influence on biological and ecological systems. However, the frequency of occurrences of the ATC magnitude extremes in the recent decades compared to the preindustrial period, as well as the potential driving forces remains unclear. This can limit the robust predictions and risk assessments for extreme events of the ATC in the future. In this study, we analyzed the frequency of occurrence of the ATC magnitude extremes using both recent observations (1955-2011) and a tree-ring-based reconstruction covering the past three centuries over the TP. The results indicate that the ATC magnitude extremes in maximum obviously decrease and in minimum distinctly increase under climate warming, both for the instrumental period and the past three centuries. Moreover, the occurrence of the ATC magnitude extremes on the TP had a distinct regional characteristic and was mainly related to the winter temperature extremes triggered by the anomalous meridional gradient of geopotential height impelling cold air intrudes the TP. Although volcanic eruptions were expected to result in summer cooling and winter warming, and thus trigger the minimum ATC magnitude extremes, this effect only can be identified in event-specific eruptions (e.g., the 1835 Cosiguina eruption). Our study results provide an essential background for developing robust predictions and risk assessments for the ATC magnitude extremes on the TP. [ABSTRACT FROM AUTHOR]

Heat waves are an important type of extreme climate event and directly result in more than 130 deaths per year across the United States. Heat waves have been described by several attributes and combinations which constitute various event typologies. Attributes of heat waves from 10 cities are analyzed over the period 1950–2016 to understand how these attributes determine variability in local heat waves and how climate change affects heat waves across the United States. This study uses eight definitions to differentiate heat waves and tests for temporal trends in key properties of heat waves over the period 1950–2016. At least five harmful attributes of heat waves have increased simultaneously for Dallas, Miami, New York, Phoenix, and Portland.Miami showed the greatest change in heat wave season length, frequency, and timing over the study period. Surprisingly, the greatest mean heat wave intensities above daily thresholds were for Bismarck, ND (+8.2 °C) and Syracuse, NY (+6.5 °C). Similar results across Baltimore, MD, Colorado Springs, CO, Dallas, TX, Des Moines, IA, Miami, FL, New York, NY, Phoenix, AZ, and Portland, OR, are presented to clarify the many quantitative differences in heat wave attributes and variance in quantification approaches across climates. This work explores the nexus of quantitative description and social construction of heat waves through the lens of the various regional metrics to describe heat waves. Ultimately, this assessment will guide the development of various strategies to help communities understand and prepare for heat resilience based on local heat wave components. Plain Language Summary: Heat waves are a series of consecutive days and nights with very high temperatures. They impact human health and increase water and energy demands, particularly in the urban areas. Heat waves have different lengths, occur in various seasons, and have different ranges between daytime and nighttime temperatures. These variations create numerous types of heat waves. Although heat waves happen more frequently in hot regions, residents of cities in northern climates also experience various types of heat waves. Analysis of differences in heat wave occurrences from 1950 to 2016 in 10 cities with various climates across the United States shows how different types of heat waves are changing across the United States. We found that many descriptive characteristics are increasing in value through time. For example, heat wave duration has increased in Miami, FL. The findings of this study are intended to guide policy makers, urban managers, and first responders to better prepare for future changes in regional heat waves and mitigate negative impacts of heat waves on human health and the environment. Key Points: This study uses many different definitions for heat wave to make broad comparisonsRegional differences in heat wave components complicate uniform public health and urban management strategiesFrequency and intensity of extreme climate‐related urban heat wave events are increasing for the various climates of the United States [ABSTRACT FROM AUTHOR]

Abstract Extreme climate events occur more frequently and stronger in the future due to climate change. Maintaining the energy security during extreme conditions is essential to reduce the impacts of extreme climate and avoid disasters. Resilient design of the energy system to resist against extreme climate events are investigated considering four scenarios, namely, typical demand (TD), extreme demand (ED), extreme renewable energy generation (ER) and, extreme demand and renewable generation (EDR). A regional climate model is used to develop the four scenarios with the assistance of a building simulation model. Subsequently, multi-energy hub is optimized for each scenario considering net present value (NPV) and grid integration (GI) level as the objective functions. A significant difference in objective function values is observed when analyzing the four scenarios. Similarly, a significant difference in the energy system design is observed when moving from one scenario to another. The results of the study reveal that a energy system design is strongly influenced by extreme climate scenario considered which will make the energy system to be a sub-optimal when operating at a different climatic condition with a significant performance gap. Therefore, improving the climate flexibility of energy systems is an essential task which is challenging at the early design process. [ABSTRACT FROM AUTHOR]

Abstract Due to global warming, extreme climate events have become an important issue, and different geographical regions have different sensitivities to climate change. Therefore, temporal and spatial variations in extreme temperature and precipitation events in Inner Mongolia were analyzed based on the daily maximum temperature, minimum temperature, and precipitation data during the period of 1960–2017. The results showed that warm extreme indices, such as SU25, TX90p, TN90p, and WSDI, significantly increased, whereas the cold extreme indices, such as FD0, TX10p, TN10p, and CSDI, significantly decreased; all indices have obvious abrupt changes based on the Mann-Kendall test; nighttime warming was higher than daytime warming. Extreme precipitation indices slightly decreased overall. All of the extreme temperature and precipitation indices had long-range correlations based on detrended fluctuation analysis (a > 0.5), thereby indicating that the extreme climate indices will maintain their current trend directions in the future. ENSO, AO, and IOD had a strong positive influence on warm extremes and a strong negative influence on cold extremes in Inner Mongolia. NCEP/NCAR and ERA-20CM reanalysis showed that strengthening anticyclone circulation, increasing geopotential height, decreasing daytime cloudiness and increasing nightime cloudiness contributed to changes in climate extremes in Inner Mongolia. Graphical abstract Unlabelled Image Highlights • Warm extreme indices significantly increased, while cold extreme indices decreased. • Nighttime warming was higher than daytime warming in Inner Mongolia. • Extreme temperature and precipitation events had long-range correlation based on DFA. • ENSO, AO, and IOD had positive (or negative) impacts on warm (or cold) extremes. [ABSTRACT FROM AUTHOR]

We synthesize and summarize main findings from a special issue examining the origins, evolution, and resilience of diverse water quality responses to extreme climate events resulting from a Chapman Conference of the American Geophysical Union (AGU). Origins refer to sequences of interactive disturbances and antecedent conditions that influence diversification of water quality responses to extreme events. Evolution refers to the amplification, intensification, and persistence of water quality signals across space and time in watersheds. Resilience refers to strategies for managing and minimizing extreme water quality impacts and ecosystem recovery. The contributions of this special issue, taken together, highlight the following: (1) there is diversification in the origins of water quality responses to extreme climate events based on the intensity, duration, and magnitude of the event mediated by previous historical conditions; (2) interactions between climate variability and watershed disturbances (e.g., channelization of river networks, land use change, and deforestation) amplify water quality ‘pulses,’ which can manifest as large changes in chemical concentrations and fluxes over relatively short time periods. In the context of the evolution of water quality responses, results highlight: (3) there are high intensity and long-term climate events, which can generate unique sequences in water quality, which have differential impacts on persistence of water quality problems and ecosystem recovery rates; and (4) ‘chemical cocktails’ or novel mixtures of elements and compounds are transported and transformed during extreme climate events. The main findings regarding resilience to extreme climate events are that: (5) river restoration strategies for reducing pollution from extreme events can be improved by preserving and restoring floodplains, wetlands, and oxbow ponds, which enhance hydrologic and biogeochemical retention, and lengthen the distribution of hydrologic residence times; and (6) the biogeochemical capacity for stream and river ecosystems to retain and transform pollution from landscapes can become “saturated” during floods unless watershed pollution sources are reduced. Finally, the unpredictable occurrence of extreme climate events argues for wider deployment of high-frequency, in situ sensors for monitoring, managing, and modeling diverse water quality responses. These sensors can be used to develop robust proxies for chemical cocktails, detect water quality violations following extreme climate events, and effectively trace the trajectory of water quality recovery in response to managing ecosystem resilience. [ABSTRACT FROM AUTHOR]

Large runoff, sediment, and nutrient exports from watersheds could occur due to individual extreme climate events or a combination of multiple hydrologic and meteorological conditions. Using high-frequency hydrologic, sediment, and turbidity data we show that freeze-thaw episodes followed by intense winter (February) rainstorms can export very high concentrations and loads of suspended sediment and particulate organic carbon (POC) and nitrogen (PN) from mid-Atlantic watersheds in the US. Peak suspended sediment (> 5000 mg L−1), POC (> 250 mg L−1) and PN (> 15 mg L−1) concentrations at our 12 and 79 ha forested watersheds for the February rainfall-runoff events were highest on record and the fluxes were comparable to those measured for tropical storms. Similar responses were observed for turbidity values (> 400 FNU) at larger USGS-monitored watersheds. Much of the sediments and particulate nutrients likely originated from erosion of stream bank sediments and/or channel storage. Currently, there is considerable uncertainty about the contribution of these sources to nonpoint source pollution, particularly, in watersheds with large legacy sediment deposits. Future climate projections indicate increased intensification of storm events and increased variability of winter temperatures. Freeze-thaw cycles coupled with winter rain events could increase erosion and transport of streambank sediments with detrimental consequences for water quality and health of downstream aquatic ecosystems. [ABSTRACT FROM AUTHOR]

River beads refer to retention zones within a river network that typically occur within wider, lower gradient segments of the river valley. In lowland, floodplain rivers that have been channelized and leveed, beads can also be segments of the river in which engineering has not reduced lateral channel mobility and channel-floodplain connectivity. Decades of channel engineering and flow regulation have reduced the spatial heterogeneity and associated ecosystem functions of beads occurring throughout river networks from headwaters to large, lowland rivers. We discuss the processes that create and maintain spatial heterogeneity within river beads, including examples of beads along mountain streams of the Southern Rockies in which large wood and beaver dams are primary drivers of heterogeneity. We illustrate how spatial heterogeneity of channels and floodplains within beads facilitates storage of organic carbon; retention of water, solutes, sediment, and particulate organic matter; nutrient uptake; biomass and biodiversity; and resilience to disturbance. We conclude by discussing the implications of river beads for understanding solute and particulate organic matter dynamics within river networks and the implications for river management. We also highlight gaps in current understanding of river form and function related to river beads. River beads provide an example of how geomorphic understanding of river corridor form and process can be used to restore retention and resilience within human-altered river networks. [ABSTRACT FROM AUTHOR]

Understanding the consequences of biotic and abiotic variability on population dynamics is fundamental to assessing anthropogenic impacts, such as global climate disruption, on populations and species. Our understanding from studies to date is poor, although some long-term studies of small mammals in temperate ecosystems have elucidated the roles of climate and of interspecific interactions in their population dynamics. However, the lack of long-term studies in the tropics is a major impediment to understanding species and ecosystems in these regions. We analyzed the long-term population dynamics of seven species of small mammals from two adjacent tropical dry forests with contrasting phenology in a protected area of western Mexico. We modeled these dynamics using data from an 18-year live-trapping database, and we evaluated the effects of intra- and interspecific interactions, primary productivity, temperature, precipitation, and unusual climate events. Intraspecific interactions were the most common factors in every population, while interspecific interactions had only a mild positive interaction between few species. While we found that the effect of temperature was not relevant to population dynamics, precipitation caused positive effects on all species, either by directly enhancing the reproductive rate or, indirectly, by triggering changes in primary productivity. Extreme climate events created intense signals. Oryzomys melanotis , an invasive and opportunistic species, benefited from these events, and two populations were harmed by them: Peromyscus perfulvus and Liomys pictus , the small mammal with the most abundant population of the upland forest, which was extirpated for over 16 months. Our results suggest that sharp reductions in precipitation and more frequent extreme climate events—both predicted by global climate disruption regional models—would have dramatic effects, adding to the other anthropogenic pressures these forests are already suffering (habitat loss, excessive management). These results emphasize the importance of protected and unmanaged refugia, such as our study site, to provide sources for refaunation following local extinctions. [ABSTRACT FROM AUTHOR]

Abstract: Extreme climate events—such as hurricanes, droughts, extreme precipitation, and wildfires—have the potential to alter watershed processes and stream response. Yet due to the destructive and hazardous nature and unpredictability of such events, capturing their hydrochemical signal is challenging. A 5‐year postwildfire study of stream chemistry in the Fourmile Creek watershed, Colorado Front Range, USA, focused on high‐frequency storm sampling. During the study, the watershed was impacted by three additional extreme climate events—drought and two periods of extreme rainfall totals. These events altered concentration‐discharge relationships in ways that elucidate how hydrologic flow paths and source material availability affect stream water chemistry. Reduced infiltration after wildfire led to overland flow during thunderstorms, which conveyed ash and soil into streams. This resulted in elevated stream concentrations of constituents elevated in ash—Ca, K, Mg, alkalinity, and dissolved organic carbon—along with sediment and nitrate. Subsurface flow paths were bypassed, leading to low concentrations of Na and SiO2, which are bedrock derived and not elevated in ash. During drought conditions, when stream discharge was <20% of average, concentrations of sediment, dissolved organic carbon, and Ca fell below average concentrations, but SiO2 did not. Extreme rainfall totals saturated the subsurface and led to prolonged elevated stream discharge. Concentration‐discharge relationships for bedrock‐derived constituents, such as Ca and SiO2, were altered in that time period, while those for dissolved organic carbon were not. Previous disturbances, including historical mining, also affect stream chemistry, and water‐quality impairment can be exacerbated by extreme climate events. [ABSTRACT FROM AUTHOR]

Abstract: Extreme climate events affect sustainable development in many parts of the world. Although several studies of local extreme climate events exist, such events need more thorough investigation. Detailed studies of climatic variations that assess changes on both spatial and temporal scales are becoming increasingly necessary. In this study, 14 indices for extreme temperature and 12 indices for extreme precipitation were used to analyze the spatial distribution and temporal trends of extreme climate events in the three‐rivers headwater region (TRHR), China, over the past five decades. We found that the frequency of high temperature extremes has increased, whereas the frequency of dry extremes has decreased. Statistically significant upward trends emerged for the number of warm nights (TN90p) and the number of warm days (TX90p) in the TRHR, which increased at a rate of 11.75 and 6.79 days/10 years (p < 0.05), respectively. We also found a highly significant downward trend in the number of consecutive dry days with a rate of −4.05 days/10 years across the whole region. Overall, the TRHR has become warmer and wetter over the past 50 years and the frequency of extreme events has increased. Wavelet analysis indicated that there are significant relationships between extreme climate events in the TRHR and large‐scale ocean‐atmosphere circulation patterns, for example, the Pacific Decadal Oscillation and the El Niño–Southern Oscillation. Our findings will help local water managers and stakeholders ensure that there are effective measures in place to adapt to and mitigate the effects of potential future climate change in the TRHR. [ABSTRACT FROM AUTHOR]

River flooding is expected to increase in frequency and severity under climate change. However, the impact of extreme river flooding on the coastal carbon cycle has rarely been studied. A severe Changjiang flood occurred in the summer of 2020, which was the largest Changjiang flood in the last 20 years since 2000. This extreme flood resulted in the export of great amounts of nitrate (6.4 × 108 mol d−1), silicate (7.1 × 108 mol d−1), phosphate (5.1 × 106 mol d−1), dissolved organic carbon (DOC; 13.9 × 109 g C d−1), and inorganic carbon (DIC; 145.5 × 109 g C d−1) from Changjiang to the Changjiang Estuary, which were considerably higher (by ∼8–178%) compared to those observed in previous summers since 2006. The increase in nutrient loads, including a considerable increase in PO 4 3− concentrations due to the flood, has triggered the development of severe algal blooms in the East China Sea. Consequently, the production of DOC and removal of DIC were observed in the offshore region during the flood. Moreover, the increase in NH 4 + concentrations likely indicated enhanced organic material remineralization in flood-influenced coastal waters. The decrease in CO 2 fluxes across the air-sea interface (FCO 2) has been observed in the offshore region, while an increase in FCO 2 was found in the nearshore region during the flood compared to the non-flood condition in July 2018. These findings provide valuable references for assessing the impact of the extreme Changjiang flood on the coastal carbon cycle. • Considerable nutrients and carbon were transported during an extreme Changjiang flood. • Increased nutrient loads contributed to severe algal blooms during the flood. • An increase in CO 2 evasion was observed in flood-influenced nearshore waters. [ABSTRACT FROM AUTHOR]

• Extreme climate events are growing more common. • Some species or mutualisms may be more vulnerable to disruption by extreme events. • Mammalian fruit preference is altered asymmetrically by simulated extreme event. • Generalist species removed more exposed fruit while specialists removed less. • Extreme climate events may alter seed dispersal mutualisms over time. Anthropogenic climate change is contributing to an increase in the frequency of extreme weather events. These extreme events may affect interactions in mutualisms that provide key ecosystem functions, especially when the event is rare for a given system and participants are differentially affected. The tropical hardwood hammocks of Key Largo, Florida, USA are inhabited by a highly specialized endangered rodent, the Key Largo woodrat (Neotoma floridana smalli), which may be an important seed disperser of many native fleshy-fruited plant species. Other potential mammalian dispersers are generalist omnivores, northern raccoons (Procyon lotor) and Virginia opossums (Didelphis virginiana), that are less selective. We sought to demonstrate that extreme climate events could alter seed dispersal mutualisms by differentially affecting fruit preference of potential dispersers. We designed a replicated cafeteria-style experiment across the entire range of the Key Largo woodrat with fruit from sixteen native plant species and simulated an extreme climate event by exposing half of the fruits to sub-freezing temperatures. Freezing temperatures are rare in this tropical environment, but increased frequencies of these types of extreme events are predicted with climate change. Using camera traps, we monitored the removal of fruit and seeds by woodrats and the generalist consumers, predicting that changes in fruit quality resulting from exposure to sub-freezing temperatures would reduce preference by the more specialized woodrat relative to its generalist consumers. Indeed, exposure to subfreezing temperatures decreased the probability of fruit and seed removal by woodrats while generalist consumers preferentially removed more of the fruits and seeds exposed to sub-freezing temperatures. These data provide evidence that extreme climate events may affect species preferences for food asymmetrically, which may shift the dynamics of seed dispersal mutualisms. Over time, increasing frequencies of extreme weather events could indirectly affect communities and ecosystem services by shifting interactions between organisms. [ABSTRACT FROM AUTHOR]

Trend analysis of 27 indices related with extreme temperature and precipitation during 1961-2011 were conducted in Tabriz using the non-parametric Mann-Kendall test and Sen’s Estimator Slope methods. Furthermore Generalized Extreme Value distribution fitted to observational extreme events. Values of quantiles of the variables were estimated for different return periods. Results indicated that during the past half century, trends of indices for summer days, tropical nights and warm nights were upward and statistically significant. Trends of indices related to ice days and cool days were downward and significant. Minimum values of daily minimum and maximum temperature in year indicate significant increasing trends. Indices of number of days with precipitation greater or equal to 10 and 15 mm, consecutive wet days, total precipitation in wet days and total precipitation when rainfall is greater than 95 and 99 percentiles have experienced significant decreasing trends. After fitting GEV distribution to annual values of daily minimum and maximum temperature as well as daily maximum precipitation in Tabriz Growth curves and Q-Q plats were illustrated. Investigation of plots indicated that this distribution function has more capability in fitting of time series of extreme value even in tails of the distribution.

Abstract: Large storm events possess significant erosive energy capable of mobilizing large amounts of sediment and particulate organic matter (POM) into fluvial systems. This study investigated how stream POM composition varied as a function of the watershed POM source, particle size, storm event magnitude, and seasonal timing. POM composition was characterized for multiple watershed sources and for stream POM following storms in a second‐order forested stream. Carbon (C) and nitrogen (N) amount, C:N ratio and isotopic content (13C and 15N) were determined for solid phase POM, whereas dissolved organic C, total N concentrations, and fluorescence characteristics were determined for solution/extracted POM. Key findings from this study were the following: (1) Composition of POM varied greatly with watershed sources with forest floor litter being C and N rich and labile, while stream banks and bed were C and N poor and recalcitrant. (2) Summer storms mobilized more carbon and nitrogen‐rich labile sources, while winter events mobilized more carbon‐ and nitrogen‐poor refractory material from near‐stream sources. (3) POM composition varied by size class, with the coarse POM showing more C and N rich and labile properties, while the fine POM displayed more degraded and refractory properties. If climate variability increases the magnitude and intensity of large storm events, our observations suggest that this will not only increase the inputs of POM to aquatic systems but also result in the delivery of coarser, C and N rich, and more bioavailable POM to the stream drainage network. [ABSTRACT FROM AUTHOR]

Root mucilage modulates soil-plant-water dynamics, but its interactions with microbial community functioning remain poorly understood. The aims of this study were to estimate (I) the impacts of mucilage and soil water content on the microbial community composition and (II) the mucilage consumption by individual microbial groups. C4 root mucilage from maize (at 40 and 200 μg C per gram dry soil, corresponding to 10 and 50% of soil microbial biomass, respectively) was added in single pulses to a C3 soil at two moisture levels: optimum (80% of water-holding capacity (WHC)) and drought (30% of WHC). After 15 days of incubation, the microbial community composition was studied by phospholipid fatty acids (PLFA) analysis and incorporation of mucilage-derived C into individual microbial groups was determined by compound-specific isotope analysis. Microbial community composition remained largely unaffected by mucilage addition but was affected by moisture. Whereas an increase in water content reduced mucilage C recovery in PLFA for the low-dose mucilage amendment from 19 to 9%, it had no effect under the high-dose amendment (11-12%). This suggests that the role of mucilage for microbial functioning is especially pronounced under drought conditions. The fungal PLFA 18:2ω6,9 was present only under drought conditions, and fungi profited in their mucilage C utilisation from the lower competitiveness of many bacterial groups under drought. In this study, Gram-negatives (G−, characterised by PLFA 18:1ω9c, 18:1ω7c, 16:1ω7c and cy17:0) showed the highest mucilage-derived C in PLFA, especially at the high-dose amendment, suggesting them to be the major decomposers of mucilage, especially when the availability of this C source is high. Gram-positives (G+) included different sub-groups with distinct responses to moisture: G+ 1 (a15:0) were only competitive for mucilage C under drought, whereas G+ 3 (i17:0) were only able to utilise mucilage-derived C under optimal moisture conditions. During the 15-day incubation, they built up more than 40% of their membranes from mucilage-derived C, suggesting that in the case of high availability, mucilage can act as an important C source for this microbial group. However, under drought, G− 1 and fungi were incorporating the most mucilage C into their membranes (approx. 20% of PLFA-C). The observation that, for some groups, the high-dose mucilage amendments under drought led to higher C incorporation into PLFA than under optimum moisture suggests that mucilage can compensate drought effects for particular microbial groups. Thus, mucilage may not only act as a C source for microorganisms but may also mitigate drought effects for specific rhizosphere microbial groups. [ABSTRACT FROM AUTHOR]

Global climate forecasts predict changes in the frequency and intensity of extreme climate events ( ECEs). The capacity for specific habitat patches within a landscape to modulate stressors from extreme climate events, and animal distribution throughout habitat matrices during events, could influence the degree of population level effects following the passage of ECEs. Here, we ask (i) does the intensity of stressors of an ECE vary across a landscape? And (ii) Do habitat use patterns of a mobile species influence their vulnerability to ECEs? Specifically, we measured how extreme cold spells might interact with temporal variability in habitat use to affect populations of a tropical, estuarine-dependent large-bodied fish Common Snook , within Everglades National Park estuaries ( FL US). We examined temperature variation across the estuary during cold disturbances with different degrees of severity, including an extreme cold spell. Second, we quantified Snook distribution patterns when the passage of ECEs is most likely to occur from 2012 to 2016 using passive acoustic tracking. Our results revealed spatial heterogeneity in the intensity of temperature declines during cold disturbances, with some habitats being consistently 3-5°C colder than others. Surprisingly, Snook distributions during periods of greatest risk to experience an extreme cold event varied among years. During the winters of 2013-2014 and 2014-2015 a greater proportion of Snook occurred in the colder habitats, while the winters of 2012-2013 and 2015-2016 featured more Snook observed in the warmest habitats. This study shows that Snook habitat use patterns could influence vulnerability to extreme cold events, however, whether Snook habitat use increases or decreases their vulnerability to disturbance depends on the year, creating temporally dynamic vulnerability. Faunal global change research should address the spatially explicit nature of extreme climate events and animal habitat use patterns to identify potential mechanisms that may influence population effects following these disturbances. [ABSTRACT FROM AUTHOR]

How do disasters shape local government legitimacy in relation to managing climate- and disaster-related risks? This paper looks at how local authorities in Central Vietnam perceive their social contract for risk reduction, including the partial merging of responsibilities for disaster risk management with new plans for and investments in climate change adaptation and broader socioeconomic development. The findings indicate that extreme floods and storms constitute critical junctures that stimulate genuine institutional change. Local officials are proud of their strengthened role in disaster response and they are eager to boost investment in infrastructure. They have struggled to reinforce their legitimacy among their constituents, but given the shifting roles of the state, private sector, and civil society, and the undiminished emphasis on high-risk development models, their responsibilities for responding to emerging climate change scenarios are increasingly nebulous. The past basis for legitimacy is no longer valid, but tomorrow's social contract is not yet defined. [ABSTRACT FROM AUTHOR]

Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-toextinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local timeto- extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming. [ABSTRACT FROM AUTHOR]