Intense Events Research Articles

Terrestrial Photogrammetry–GIS Methodology for Measuring Rill Erosion at the Sparacia Experimental Area, Sicily

Rill erosion is a major issue on a global scale, and predicting the presence, position, and development of erosive forms on hillslopes is a significant challenge for the scientific community. Several plot-scale investigations confirmed the reliability of the terrestrial photogrammetric (TP) technique for studying rill erosion and the reliability of a method for extracting the rill network from Digital Surface Models (DSMs) and measuring the corresponding volume. In this paper, for an intense erosive event that occurred at the Sparacia experimental area (Sicily, Southern Italy), TP surveys of three plots, with different length and steepness, incised by rills, were performed to reconstruct the DSMs. For each plot, the rill network was extracted from the DSMs, and the non-contributing network was distinguished from the contributing one, from which the soil loss and the consequent eroded volumes V were determined. The specific aims were to (i) establish the effect of plot steepness on rill depths and some morphometric characteristics of the drainage rill network; (ii) test and calibrate the relationship between V and the total rill length L, using all rill measurements available in the literature and those obtained in this study; and (iii) modify the V–L relationship by including climate forcing and assessing the related performance. The rill depths, h, the drainage frequency, and drainage density of the rill networks detected in the three plots were compared. The analysis demonstrated that h and the morphometric parameters of the contributing rill network increase with plot steepness s. In particular, the mean depth increases from 2.79 to 4.85 cm for slope increasing from 14.9 to 26%. Moreover, the drainage frequency of the contributing rill network varies from 0.16 m−2 for s = 14.9% to 0.47 m−2 for s = 26%, while the drainage density of the contributing rill network varies from 0.92 m−1 for s = 14.9% to 2.1 m−1 for s = 26%. Finally, using the data available in the literature and those obtained in this investigation, an empirical relationship between V and the total rill length L was firstly tested and then rearranged considering the event rainfall erosivity Re. Including Re in the rearranged equation guaranteed the best performance in V estimation.

Midge Paleo-Communities (Diptera Chironomidae) as Indicators of Flood Regime Variations in a High-Mountain Lake (Italian Western Alps): Implications for Global Change

Sediments of alpine lakes serve as crucial records that reveal the history of lacustrine basins, offering valuable insights into the effects of global changes. One significant effect is the variation in rainfall regimes, which can substantially influence nutrient loads and sedimentation rates in lacustrine ecosystems, thereby playing a pivotal role in shaping biotic communities. In this study, we analyze subfossil chironomid assemblages within a sediment core from an alpine lake (western Italian Alps) to investigate the effects of rainfall and flood regime variations over the past 1200 years. Sediment characterization results highlight changes in sediment textures and C/N ratio values, indicating phases of major material influx from the surrounding landscape into the lake basin. These influxes are likely associated with intense flooding events linked to heavy rainfall periods over time. Flooding events are reflected in changes in chironomid assemblages, which in our samples are primarily related to variations in sediment texture and nutrient loads from the surrounding landscape. Increased abundances of certain taxa (i.e., Brillia, Chaetocladius, Cricotopus, Psectrocladius, Cricotopus/Orthocladius Parorthocladius) may be linked to higher organic matter and vegetation inputs from the surrounding landscape. Biodiversity decreased during certain periods along the core profile due to intense flood regimes and extreme events. These results contribute to our understanding of alpine lake system dynamics, particularly those associated with intense flooding events, which are still understudied.

Local field potential-based brain-machine interface to inhibit epileptic seizures by spinal cord electrical stimulation.

This study proposes a closed-loop brain-machine interface (BMI) based on spinal cord stimulation to inhibit epileptic seizures, applying a semi-supervised machine learning approach that learns from Local Field Potential (LFP) patterns acquired on the pre-ictal (preceding the seizure) condition.
 
Approach. LFP epochs from the hippocampus and motor cortex are band-pass filtered from 1 to 13 Hz, to obtain the time-frequency representation using the continuous Wavelet transform, and successively calculate the phase lock values (PLV). As a novelty, the Z-score-based PLV normalization using both modified k-means and Davies-Bouldin's measure for clustering is proposed here. Consequently, a generic seizure's detector is calibrated for detecting seizures on the normalized PLV, and enables the spinal cord stimulation for periods of 30 s in a closed-loop, while the BMI system detects seizure events. To calibrate the proposed BMI, a dataset with LFP signals recorded on five Wistar rats during basal state and epileptic crisis was used. The epileptic crisis was induced by injecting pentylenetetrazol (PTZ). Afterwards, two experiments without/with our BMI were carried out, inducing epileptic crisis by PTZ in Wistar rats. 

Main Results. Stronger seizure events of high LFP amplitudes and long time periods were observed in the rat, when the BMI system was not used. In contrast, short-time seizure events of relative low intensity were observed in the rat, using the proposed BMI. The proposed system detected on unseen data the synchronized seizure activity in the hippocampus and motor cortex, provided stimulation appropriately, and consequently decreased seizure symptoms. 

Significance. Low-frequency LFP signals from the hippocampus and motor cortex, and cord spinal stimulation can be used to develop accurate closed-loop BMIs for early epileptic seizures inhibition, as an alternative treatment.

Real-time joint recognition of weather and ground surface conditions by a multi-task deep network

Climate change and the occurrence of intense and unexpected weather events highlighted the need for real-time weather warning systems, especially in smart roads and isolated scenarios like rural areas. In this work, we propose to jointly recognize the weather and the ground surface conditions using existing video surveillance systems. Previous works separately tackled these two tasks even if they are correlated to each other. We propose a convolutional neural network with shared weights in the lower layers and two separate classification branches on top to exploit the correlation between the tasks and, at the same time, learn diverse high-level features for each task. Moreover, the network architecture implements attention mechanisms allowing the classification branches to focus on diverse image regions. The method is versatile and allows us to train the network on partially labeled data. The experimental analysis on real data demonstrate the effectiveness of the proposed method on both tasks, confirmed by the accuracy comparison with existing methods for the recognition of weather and ground surface conditions. The multi-task solution improves the inference speed (50 frames per second) and reduces the required memory (less than 1 GB) with respect to a system with two different single-task approaches; these results confirm that the proposed solution is ready for video surveillance applications to support smart cities.

Differentiated growth of the most widely planted conifer in response to extreme droughts across semi-arid regions in Northern China

Global warming is leading to more frequent and intense drought events, exerting unprecedented pressure on forest growth. Although post-drought recovery in plantation growth has been studied enormously, the variation of planted populations across the whole distribution range of a species is not well understood. In this study, the growth suitability of the most widely planted conifer species in dry lands of northern China, Mongolian Scots pine (Pinus sylvestris var. mongolica), was estimated, based on tree-ring data sampled in 289 plots of afforestation across most of its planting range. According to changes in the hydrothermal condition during the last forty years (1980–2018), the distribution range was divided into three parts: warming, warming-wetting, and non-significant trends (NT) regions. Two severe droughts in 2000 and 2007 were identified using the Standardized Precipitation Evapotranspiration Index (SPEI). Then, the resistance (Rt), recovery (Rc), and resilience (Rs) growth indices were calculated and compared among these three parts. The growth of planted Mongolian Scots pine has overall significantly increased from 1980 to 2018 (p < 0.001). The pine plantations in warming regions were sensitive to annual precipitation, while warming-wetting regions were more influenced by the growing season climate. Pines reverted to pre-drought growth levels within 3 years after the drought event in 2000 but failed in 2007, and populations in the warming region showed significantly lower post-drought recovery. Furthermore, high pre-drought growth levels were linked to low Rs in both drought events (p < 0.001). Post-drought precipitation enhanced the Rc of plantations, compensating for the growth reduction caused by droughts. Soil moisture during the drought events enhanced Rt and Rs. The Rt and Rs indices decreased significantly with the age of plantations (p < 0.05). Overall, our results revealed that pre-drought growth and post-drought precipitation were key factors influencing the resilience of planted Mongolian Scots pine. Besides, the plantations experiencing wetting trends revealed favorable drought resilience and stable radial growth, which indicated promising potential for planted Mongolian Scots pine in those areas. Controlling the age of plantations seems to be crucial for maintaining drought resilience in large-scale plantations and maximizing ecological benefits.

China is suffering from fewer but more severe Drought to flood abrupt alternation events

Drought to flood abrupt alternation (DFAA) events, as a special category of compound extreme events that suddenly shift from drought to flood conditions, have significantly greater impacts than individual drought or flood events. In this paper, we have utilized a multifactorial drought index and flood index to identify daily DFAA events occurring in mainland China and in major impact areas during the period 1961-2022. Based on drought and flood index, we have used entropy weighting method to measure the intensity of DFAA events. Our findings indicate that China's DFAA events primarily occur in the hotspots of Huang-Huai-Hai River Basin, the middle and lower Yangtze River Basin, the southeastern coastal area, and the southwestern part of the country. The most frequent and intense DFAA events occur from June to September, with varying subseasonal patterns in the frequency and intensity of events in each hotspot. The frequency of DFAA events in mainland China shows a significant decreasing trend declining at a rate of 0.25 pre year in year-round. While DFAA events occurring in the warm season tend to decrease more significantly compared to the year-round at a rate of 0.26 per year. However, the intensity of DFAA events is increasing with a rate of 0.1 per decade in both the year-round and warm season. The evolution of DFAA events and their direct causes vary non-uniformly across regions and months. Subseasonally, frequency and intensity trends diverged monthly across regions, notably with the Huang-Huai-Hai Basin and southeast coast experiencing a July decline in frequency but a surge in intensity. Our research deepens the understanding of changes in DFAA events and provides practical reference for preventing and mitigating drought-to-flood disasters in mainland China.

Extreme weather impact on carbon-neutral power system operation schemes: A case study of 2060 Sichuan Province

The impact of increasingly frequent and intense climate change events on power supply and consumption has become a concern for many countries. This study evaluated the impact of extreme weather on the power system economy and security by conducting an empirical case study of the Sichuan power network to address uncertainty attributed to different extreme weather events under carbon neutrality scenarios. First, our paper proposed a CNPSSO model of four seasonal typical days by jointly considering the regional hourly disparities of load curves and renewable power output curves. Then, the model creatively introduced the effects of extreme weather on the power supply and demand curves based on various scenario analyses. The most cost-effective output strategy using various generation technologies was provided based on optimization models. Finally, Sichuan Province, a hydropower-dominated province was selected as an empirical case study. The results indicate that extreme weather significantly affects the hourly operational and dispatching schemes of Sichuan's power system. Compared to the "Normal weather scenario”, hydropower's share plummets from 83.3 % to 46.1 %, while pumped storage surges 7.1 billion kWh in summer in extremely hot and dry weather. Imported electricity rises by 24.4 %, 30.5 % and 24.8 % in dry scenario, extremely hot and dry scenario, and extremely cold scenario, respectively. Furthermore, extreme weather increases carbon emissions (mainly from thermal power and imported electricity) and costs. Specifically, when juxtaposed against normal weather, extreme drought, extreme heat drought and extremely cold lead to respective increases in carbon emissions by 32.9 %, 33.5 %, and 12.3 %. Regarding the levelized cost of electricity (LCOE), "Extremely dry scenario”, "Extremely hot and dry scenario”, and "Extremely cold scenario” drive up the LCOE by 7.2 %, 9.2 %, and 4.2 %, respectively.

Plant community composition and traits modulate the impacts of drought intensity on soil microbial community composition and function

Terrestrial ecosystems are increasingly threatened by extreme drought events. Soil microbial communities are central to terrestrial ecosystem function via their role in regulating biogeochemical cycling. Consequently, the impact of increasingly intense drought events on soil microbial communities will have knock-on effects for how ecosystems cope with climate change. In an outdoor grassland mesocosm experiment, we determined how increasing drought intensity affects bacterial and fungal community composition, and functioning, during and after drought. We also tested whether plant community resource acquisition strategy (fast- versus slow-strategy plant communities), plant community composition, and plant functional traits mediate soil microbial responses to increasing drought intensity. We found that increasing drought intensity markedly shifted bacterial and fungal community composition, and these effects persisted until the end of the experiment (two months after re-wetting). Bacterial and fungal communities that experienced severe droughts did not return to baseline composition, while those that experienced a mild drought did. Microbial community functioning (potential extracellular enzyme activity) was reduced at peak drought and shortly after re-wetting. While drought intensity effects on bacterial or fungal communities were insensitive to plant community resource acquisition strategy, functional group abundance (aboveground biomass of grass or forb plant species) composition (grass:forb ratio) and leaf traits (leaf dry matter content and leaf nitrogen concentration) explained significant variation in bacterial and fungal community composition during and after drought. Notably, plant community leaf dry matter content and soil nitrogen were the key factors mediating the effect of increasing drought intensity on microbial indicator taxa (ASVs). We conclude that increasing drought intensity affects grassland soil microbial communities during and after drought, and this impact is influenced by plant community composition and functional traits.

Urban Planning Strategies for Coastal Cities in China in Response to Climate Change

Global climate change has increasingly posed a serious threat to coastal cities, rendering them particularly vulnerable to the adverse effects of rising sea levels, more frequent and intense extreme weather events, and the shifting patterns of climate. Traditional urban planning methods, which had been the cornerstone of city development, were found to be inadequate in addressing these escalating challenges. The previous studies often failed to account for the critical importance of integrating climate factors into the planning process, leading to vulnerabilities in urban infrastructure and design. This study meticulously examined the limitations of these conventional urban planning approaches and explored the potential for adapting urban planning strategies in Chinas coastal cities to better respond to the looming threat of climate change. By conducting a thorough analysis of the impacts of high temperatures, floods, and other climate-related events, the study proposed a comprehensive series of response measures tailored to the specific conditions of the time. These measures included the integration of green policies into urban planning to enhance environmental sustainability, the strategic selection of building materials aimed at mitigating urban heat, and the enhancement of water resource management systems to alleviate the urban heat island effect. Moreover, the study closely investigated existing climate response measures through detailed case studies in Xiamen and Dalian, two prominent coastal cities in China. The primary objective was to significantly enhance the resilience of these cities, effectively reduce the risks associated with climate change, and promote a path towards sustainable development. Ultimately, the goal was to create more livable, safer, and sustainable urban environments that would be better equipped to face the challenges posed by an unpredictable climate future.

Solar cycle phase and occurrence of intense geomagnetic storms

Solar cycles have an asymmetrical shape with a fast rise and a slow decline, which varies from cycle to cycle. This makes it difficult to study the solar cycle phase dependence of the occurrence of intense solar-terrestrial events such as intense geomagnetic storms. In the previous works, differences in the rise and fall time lengths of each solar cycle were not fully considered. We normalized the asymmetric shape of each solar cycle using the rise and fall time lengths and showed the solar cycle phase dependence of occurrence of the intense geomagnetic storms selected using the Dst index for solar cycles 19−24 and using the aa index for solar cycles 12−24. The previous works noted that the occurrence of geomagnetic disturbances shows double peaks before and after solar maximum. Our results showed that the occurrence of the intense geomagnetic storms selected using the Dst and aa indices does not always show clear double peaks and increased more in the earlier half of the fall time than in the other time periods. The Dst and aa indices have been used to select geomagnetic storms in the previous studies. We pointed out that the solar cycle phase dependence of occurrence of the geomagnetic storms selected using the aa index is slightly different from those selected using the Dst index. We showed the geomagnetic storm on 4 August 1972 as an extreme case, which showed difference between Dst and aa. We also showed that intense geomagnetic storms associated with eruptive flares from the active sunspot groups occurred around the solar minima of cycles 17, 19, 20, and 21.Graphical

Evaluation of WRF model performance with different microphysics schemes for extreme rainfall prediction in Lagos, Nigeria: Implications for urban flood risk management

In Nigeria, particularly in urban areas like Lagos, flooding is a frequent natural hazard. In 2011, Lagos experienced one of its worst floods resulting in significant economic losses and displacement of people. In recent years, Lagos has continued to grapple with flooding challenges, with an equally significant flood episode occurring in 2021. This study focuses on predicting floods and forecasting extremely heavy rainfall in West Africa's equatorial zone using the Weather Research and Forecasting (WRF) model, particularly in humid tropical environments like Lagos. The study discusses the need to review existing flood models and adopt alternative flood models to address the limitations of flood prediction. As potential causes of these rainfall episodes, the interconnections between synoptic systems such as tropical easterly waves, southwesterly winds related to the West African Monsoon, and local topography and oceanic conditions are investigated. Three key metrics: root mean square error (RMSE), mean bias (MB), and mean absolute error (MAE) are used to assess the effectiveness of the computational model. Results indicate that the WRF model, specifically when using the Thompson parameterisation, can estimate the amount of rainfall accumulated over a 24-h period. This suggests that the model can predict the size of daily precipitation during intense rain events. The Thompson scheme shows better performance compared to the WSM6 scheme while evaluating the stations and episodes. During the rainfall episode on July 10, 2011, Thompson's spatial rainfall predictions were better than WSM6, resulting in a decrease in root mean square error (RMSE) of 15–31% depending on the area. Simulations of the July 2021 episode also show better performance, with a decrease in RMSE of 11–25% when comparing Thompson to WSM6 scheme. The Thompson scheme’s improved ability is directly linked to a more accurate depiction of the microphysical mechanisms that control the rainfall formation. By explicitly simulating the dynamics of ice crystals and graupel, it is possible to accurately replicate the processes of orographic lifting and moist convection that are responsible for driving intense monsoon precipitation. In addition, Thompson scheme shows a reduced degree of systemic bias in comparison to WSM6, with a 75% reduction in the average bias in rainfall accumulation over the research area. The combination of the advanced Thompson microphysics method and WRF's atmospheric dynamics shows a high level of accuracy in predicting intense rainfall and the risk of floods in this area with diverse tropical topography.

A Rapid Sequence of Solar Energetic Particle Events Associated with a Series of Extreme-ultraviolet Jets: Solar Orbiter, STEREO-A, and Near-Earth Spacecraft Observations

A series of solar energetic electron (SEE) events was observed from 2022 November 9 to November 15 by Solar Orbiter, STEREO-A, and near-Earth spacecraft. At least 32 SEE intensity enhancements at energies >10 keV were clearly distinguishable in Solar Orbiter particle data, with 13 of them occurring on November 11. Several of these events were accompanied by ≲10 MeV proton and ≲2 MeV nucleon−1 heavy-ion intensity enhancements. By combining remote-sensing and in situ data from the three viewpoints (Solar Orbiter and STEREO-A were ∼20° and ∼15° east of Earth, respectively), we determine that the origin of this rapid succession of events was a series of brightenings and jetlike eruptions detected in extreme ultraviolet (EUV) observations from the vicinity of two active regions. We find a close association between these EUV phenomena, the occurrence of hard X-ray flares, type III radio bursts, and the release of SEEs. For the most intense events, usually associated with extended EUV jets, the distance between the site of these solar eruptions and the estimated magnetic connectivity regions of each spacecraft with the Sun did not prevent the arrival of electrons at the three locations. The capability of jets to drive coronal fronts does not necessarily imply the observation of an SEE event. Two peculiar SEE events on November 9 and 14, observed only at electron energies ≲50 keV but rich in ≲1 MeV nucleon−1 heavy ions, originated from slow-rising confined EUV emissions, for which the process resulting in energetic particle release to interplanetary space is unclear.

Seasonal Characteristics of Air–Sea Exchanges over the South Coast of Matara, Sri Lanka

Air–sea exchanges play a crucial role in intense weather events over Sri Lanka, particularly by providing the heat and moisture that fuel heavy rainfall. We present a year-round dataset of meteorological observations from the southern shoreline of Sri Lanka in the equatorial Indian Ocean for 2017, aiming to investigate its seasonal characteristics and evaluate the performance of reanalysis data in this region. The observations reveal distinct diurnal and seasonal patterns. During the winter and spring, higher shortwave (646.2 W/m2) and longwave radiation (−86.9 W/m2) are coupled with higher temperatures (30.6 °C) and lower humidity (67.4% at noon). In contrast, the Indian summer monsoon period features reduced shortwave (579.8 W/m2) and longwave radiation (−58.6 W/m2), lower temperatures (29.2 °C), higher humidity (over 79.7%), and stronger winds (6.25 m/s). The observations were compared with the ERA5 reanalysis dataset to evaluate the regional performance. The reanalysis data correlated well with the observed data for the radiation, temperature, and sensible heat flux, although notable deviations occurred in terms of the wind speed and latent heat flux. During the impact of Tropical Cyclone Ockhi, the reanalysis data tended to underestimate both the wind speed and precipitation. This dataset will provide vital support for studies on monsoons and coastal atmospheric convection, as well as for model initialization and synergistic applications.

Development of Vertical Radar Reflectivity Profiles Based on Lightning Density Using the Geostationary Lightning Mapper Dataset in the Subtropical Region of Brazil

The study aims to develop vertical radar reflectivity profiles based on lightning density data from the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite in the subtropical region of Brazil. The primary objective is to improve the assimilation of lightning data in numerical weather prediction models. The methodology involves the analysis of polarimetric radar data from Chapecó-SC and Jaraguari-MS, spanning from January 2019 to December 2023, and their correlation with lightning data from the GLM. Radar reflectivity profiles were created for different lightning density classes, categorized into six classes based on geometric progression. Results show a significant relationship between lightning activity and radar reflectivity, with distinct profiles for convective and stratiform events. These findings demonstrate the potential of using GLM data to enhance short-term weather forecasting, particularly for severe weather events. The study concludes that the integration of GLM data into weather models can lead to more accurate predictions of intense precipitation events, contributing to better preparedness and response strategies.

Radiation exposure of astronauts following an intense solar particle event: analysis and comparison of doses in male and female voxel phantoms.

According to NASA's plans, a human travel to the Moon is planned by the end of 2025 with the Artemis II mission, and humans should land on the Moon again in 2026. Exposure to space radiation is one of the main risks for the crew members; while for these short missions the doses from galactic cosmic rays would be relatively low, the possible occurrence of an intense solar particle event (SPE) represents a major concern, especially considering that in 2025 the Sun activity will be at its peak. Quantifying the amount and the effects of such exposure is therefore crucial, to identify shielding conditions that allow respecting the dose limits established by the various space agencies. By exploiting an interface between the BIANCA biophysical model and the FLUKA Monte Carlo radiation transport code, in this work we implemented a male and a female voxel phantom and we calculated absorbed doses and Gy-Eq doses in the various tissues/organs, as well as effective doses, following exposure to the August 1972 SPE, the most intense event of the modern era. The calculations were performed respect the organ dose limits for 30 d missions. A detailed comparison between male and female doses was then carried out, also considering that the Artemis II crew will include a woman. The results showed that female doses tend to be higher than male doses, especially with light shielding. This should be taken into account in mission design, also considering that, in a typical lunar mission, up to 15% of time may be spent in extra-vehicular activities, and thus with light shielding. More generally, this work outlines the importance of performing separate calculations for male and female astronauts when dealing with radiation doses and effects.

Giant landslide, hidden caldera structure, magnetic anomalies and tectonics in southern Tyrrhenian Sea (Italy)

Phlegraean Fields and Ischia Island are large, densely populated, active volcanic structures located in the Campanian Tyrrhenian margin between the onshore and offshore sectors. While the emerged landforms provide significant insights into a series of intense volcano-tectonic events of the last 60 ka, our understanding of the sub-marine portion of these volcanoes remains limited due to its inaccessibility to direct exploration. In the last decades, the use of magnetic methods has proven to be useful in volcanic context, given the presence of large magnetization contrasts, whereas the implementation of a high-resolution Digital Elevation Model (DEM) has allowed the integration of detailed morphological analyses into the geophysical studies. In this work, we present two new high-resolution airborne and shipborne magnetic surveys, carried out by the National Institute of Geophysics and Volcanology (INGV) in the marine sector of the Phlegraean Fields caldera (Pozzuoli Bay) and surrounding sea sectors. Moreover, the new datasets have been integrated with older marine surveys carried out by the National Research Council (CNR) to extend the resulting magnetic anomaly map embracing the whole Campanian offshore volcanic structures, excluding Ischia Island. As a result, we present here three new magnetic anomaly maps used for an integrated interpretation of magnetic, morphological, and tectonic features. The study results provide valuable insights into the relationship between volcanic, magmatic, and tectonic activity, which may be useful for further investigations. Among the most notable findings are: the identification of the magnetic signatures of regional faults, previously unknown caldera structures, and a massive rock avalanche. Consequently, our research provides a significant contribution to seabed exploration aimed at identifying potential hazard factors in the study area.

Role of Squalene Epoxidase Gene (SQE1) in the Response of the Lichen Lobaria pulmonaria to Temperature Stress.

Currently, due to the increasing impact of anthropogenic factors and changes in solar activity, the temperature on Earth is rising, posing a threat to biodiversity. Lichens are among the most sensitive organisms to climate change. Elevated ambient temperatures can have a significant impact on lichens, resulting in more frequent and intense drying events that can impede metabolic activity. It has been suggested that the possession of a diverse sterol composition may contribute to the tolerance of lichens to adverse temperatures and other biotic and abiotic stresses. The major sterol found in lichens is ergosterol (ERG); however, the regulation of the ERG biosynthetic pathway, specifically the step of epoxidation of squalene to 2,3-oxidosqualene catalyzed by squalene epoxidase during stress, has not been extensively studied. In this study, we used lichen Lobaria pulmonaria as a model species that is well known to be sensitive to air pollution and habitat loss. Using in silico analysis, we identified cDNAs encoding squalene epoxidase from L. pulmonaria, designating them as LpSQE1 for the mycobiont and SrSQE1 for the photobiont Symbiochloris reticulata. Our results showed that compared with a control kept at room temperature (+20 °C), mild temperatures (+4 °C and +30 °C) did not affect the physiology of L. pulmonaria, assessed by changes in membrane integrity, respiration rates, and PSII activity. An extreme negative temperature (-20 °C) noticeably inhibited respiration but did not affect membrane stability. In contrast, treating lichen with a high positive temperature (+40 °C) significantly reduced all physiological parameters. Quantitative PCR analysis revealed that exposing thalli to -20 °C, +4 °C, +30 °C, and +40 °C stimulated the expression levels of LpSQE1 and SrSQE1 and led to a significant upregulation of Hsps. These data provide new information regarding the roles of sterols and Hsps in the response of lichens to climate change.

Hydro-geomorphological assessment of culvert vulnerability to flood-induced soil erosion using an ensemble modeling approach

Intense precipitation events pose growing threats to forest infrastructure causing flooding, and soil erosion and deposition, creating bottlenecks at road-stream crossing structures (RSCS). We describe a hillslope-scale ensemble hydro-geomorphological vulnerability assessment integrating geospatial Streambank Erosion Vulnerability Assessment (SBEVA), Modified Revised Soil Loss Equation (MRUSLE), and process-based Water Erosion Prediction Project (WEPP) model into an ensemble hydro-geomorphologic vulnerability index (EHVI) for USDA Forest Service (USFS) managed 194 road-culverts at the Hubbard Brook Experimental Forest (HBR-EF) in New Hampshire, USA. The results revealed that five and one culvert with diameters of 0.46m and 0.61m, respectively, have extreme EHVI values between 4 and 5, and fifteen and three culverts with diameters of 0.46m and 0.61m, respectively, have severe EHVI values between 3 and 4, some of which were previously identified as hydrologically vulnerable (undersized) to floods. This knowledge will inform USFS efforts to improve the resilience of the RSCS and protect aquatic habitats.

Petrogenesis of ultramafic rocks from the Neoproterozoic Bou Azzer Ophiolite (Morocco): new insights into a long-standing geodynamic question

ABSTRACT The Neoproterozoic Bou Azzer Ophiolite, located in the Pan-African orogen of the Anti-Atlas, Morocco, exposes a well-preserved mantle section of the ophiolitic sequence. Although ultramafic rocks are the most common rock types in the sequence, they have received less attention in previous studies. In this work, we investigate the petrogenesis of these ultramafic rocks in detail, including their petrology, mineralogy, and whole rock geochemistry. The mineral assemblages are mainly formed by antigorite with minor lizardite, chlorite, and accessory Cr-spinel. The only preserved primary mantle mineral is Cr-spinel, which shows unaltered cores with Cr# between 0.61 and 0.71 and alteration rims to ferrian chromite and magnetite. Whole rock analyses indicate almost total serpentinization and, locally, strong carbonation (mass loss of ignition between 11.94 and 22.20 wt%). The non-carbonated samples preserve protolith signatures, with decreased MgO/SiO2 suggesting metasomatic processes related to serpentinization. Immobile trace elements compare well with fore-arc peridotites, while melting modelling indicates intense and polyphasic melting events. We propose polyphase melting in a subduction-initiation setting, with a first stage of 14–23% anhydrous melting, forming fore-arc basalts, and a second stage of 15–25% melting with 1 wt% H2O, forming boninites. The Bou Azzer ultramafic rocks represent the fore-arc region of a supra-subduction zone, challenging previous interpretations that suggested a back-arc position.

Quercus acutissima exhibits more adaptable water uptake patterns in response to seasonal changes compared to Pinus massoniana

BackgroundSeasonal precipitation variability significantly affects water use in forests; however, whether water uptake is adapted to changes in precipitation, particularly whether it could affect the coexistence of tree species, has rarely been quantified in forest systems. MethodIn this study, dual stable isotopes and the Li-6400 portable photosynthesis system were used to determine the water sources of a mixed conifer (Pinus massoniana) and broadleaf (Quercus acutissima) forest and changes in hydraulic characteristics during the dry and wet seasons in a southern hilly region of China. ResultsAlthough the hydraulic characteristics of P. massoniana were lower than those of Q. acutissima, it maintained a stable water source from the deep soil layer and a higher stomatal conductance (Gs), leading to a higher transpiration rate (Tr) during the growing seasons. Q. acutissima mainly absorbed water from deeper soil layers in the dry season and took up from shallow soil layers in the wet season. Its Gs values exhibited sensitivity to precipitation, while it maintained a lower Tr value during the growing seasons. The excessive water-use strategy observed in P. massoniana may confer weak drought-tolerance during higher frequency and more intense extreme precipitation events, whereas Q. acutissima may exhibit better ecological adaption to precipitation changes. ConclusionsThe overlap of water niches in mixed forests did not appear to affect the coexistence of tree species. The present study provides insights into reforestation and water management in the southern hilly regions of China.