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Nature sports include pursuits such as paragliding, white-water kayaking, free diving, mountaineering, and surfing. Participants in nature sports interact with geographical features (e.g. mountains, rivers, oceans, snow fields, ice sheets, caves, rock faces) as well as the dynamic forces that produce them (e.g. gravity, waves, thermal currents, flowing water, wind, rain, sun). In this article, I engage a representational approach to analyze how participants in nature sports interact with nature. Anthropocentric representations privilege participants' interests, wants, desires, and ends; they typically refer to claims of conquest/achievement in nature, or praise nature for its therapeutic qualities. In contradistinction, ecocentric representations recognize humankind as one entity in an interdependent world that comprises all living organisms and the geological processes and geomorphological features that sustain them. Ecocentric representations of nature sports highlight networks of participants and landforms that help preserve a balance between people and the environment. Yet, notwithstanding the allure of ecocentric representations, especially in the wake of evidence that human-induced greenhouse gases are predisposing environmental calamities, there is a substantial gap between the ontological concepts and categories of ecocentrism and lived sporting experiences and practices in nature. [ABSTRACT FROM AUTHOR]

Soil erosion is a serious threat to agriculture and environmental sustainability in the risk‐prone rainfed Himalayan ecosystem. Hence, runoff and soil loss mitigation ability of four maize‐based intensified systems; maize (Zea mays) + turmeric (Curcuma longa), maize + ginger (Zingiber officinale), maize + colocasia (Colocasia esculenta), and maize + sweet potato (Ipomoea batatas) were tested against the sole maize. The study recorded 41 erosive events during the 2020–2022 monsoon season. A principal component analysis (PCA) was performed to transform correlated rainfall parameters into orthogonal principal components. A two‐dimensional biplot analysis examined the relationship between PCs, rainfall events, and rainfall parameters. The rainfall events were divided into three regimes based on cluster analysis using PC. Rainfall regime 1 was characterized by low rainfall, I30, rainfall erosivity (E), and moderate rainfall duration (D), regime2 with moderate rainfall, short duration, high I30, and E, and regime3 with high D, I30, and rainfall erosivity. The soil loss of regime‐3 was 9.29 and 3.24 times higher than regime‐1 and regime‐2, respectively. Cover crops reduced runoff by 21.5%–69.3% and soil loss by 54.1%–77.0% over control. Redundancy analysis (RDA) showed that rainfall parameters (I30, I60, D, and E) had a significant direct influence across the systems, explaining 37.7%–54.9% of response variable variance, with E being the most influential (47.4%–54.9%), indicating varied impacts on runoff and soil loss. The sweet potato was best suited with maize as an intercrop to minimize soil erosion and maximize the system's profitability. [ABSTRACT FROM AUTHOR]

Numerous hydrological applications, such as soil erosion estimation, water resource management, and rain driven damage assessment, demand accurate and reliable rainfall erosivity data. However, the scarcity of gauge rainfall records and the inherent uncertainty in satellite and reanalysis-based rainfall datasets limit rainfall erosivity assessment globally. Here, we present a new global rainfall erosivity dataset (0.1° × 0.1° spatial resolution) integrating satellite (CMORPH and IMERG) and reanalysis (ERA5-Land) derived rainfall erosivity estimates with gauge rainfall erosivity observations collected from approximately 6,200 locations across the globe. We used a machine learning-based Gaussian Process Regression (GPR) model to assimilate multi-source rainfall erosivity estimates alongside geoclimatic covariates to prepare a unified high-resolution mean annual rainfall erosivity product. It has been shown that the proposed rainfall erosivity product performs well during cross-validation with gauge records and inter-comparison with the existing global rainfall erosivity datasets. Furthermore, this dataset offers a new global rainfall erosivity perspective, addressing the limitations of existing datasets and facilitating large-scale hydrological modelling and soil erosion assessments. [ABSTRACT FROM AUTHOR]

India represents 3% of the global malaria burden. Chhattisgarh is the second-most endemic region in India in terms of malaria transmission. The research related to the effect of weather variables on malaria transmission through dynamic modelling is at an early stage in India. We attempted to do it with the help of the VECtor borne disease community model of International Centre for Theoretical Physics, TRIeste model for the Chhattisgarh region during 2000–2019. The highest malaria transmission is found in August and September. We also found that the malaria transmissions are found to be more endemic in the districts, namely Baster, Dantewada, Sukma, Bijapur, Narayanpur, Kondagaon, Raigarh, Jashpur, Balrampur, Bemetara and BalodaBazar. [ABSTRACT FROM AUTHOR]

Previous studies have shown that aerosols invigorate deep convective systems (DCS). However, the magnitude or even the existence of aerosol invigoration of DCS remains controversial. Here, we aimed to observationally quantify the full aerosol effects on DCS by tracking their entire lifecycle and spatial extent in tropical regions. We found that fine aerosols (FA) can invigorate DCS, making them taller and longer lived, and resulting in up to ×5 increase in total area and rainfall amount. In contrast, added coarse sea salt aerosols (CSA) over the ocean can inhibit the vertical development of DCS through enhancing warm rain formation, yet resulting in longer lived and extensive DCSs. Notably, combining FA and CSA generates the strongest aerosol invigoration effect at the concentrations of ~5 and ~80 μg/m³, leading up to ×10 increase in rainfall amount. Our results indicate that aerosols significantly redistribute convective precipitation and climate effects, greatly underestimated in previous studies. [ABSTRACT FROM AUTHOR]

Membraneless coacervate microdroplets have long been proposed as model protocells as they can grow, divide, and concentrate RNA by natural partitioning. However, the rapid exchange of RNA between these compartments, along with their rapid fusion, both within minutes, means that individual droplets would be unable to maintain their separate genetic identities. Hence, Darwinian evolution would not be possible, and the population would be vulnerable to collapse due to the rapid spread of parasitic RNAs. In this study, we show that distilled water, mimicking rain/freshwater, leads to the formation of electrostatic crosslinks on the interface of coacervate droplets that not only suppress droplet fusion indefinitely but also allow the spatiotemporal compartmentalization of RNA on a timescale of days depending on the length and structure of RNA. We suggest that these nonfusing membraneless droplets could potentially act as protocells with the capacity to evolve compartmentalized ribozymes in prebiotic environments. [ABSTRACT FROM AUTHOR]

Eight spatial interpolation models were used to map the spatial distribution of precipitation in the southwestern sector of the Iberian Peninsula (22330 km2) over 40 years (1980/1981–2019/2020). Rainfall data from 103 meteorological stations were used to generate the interpolation models, namely inverse distance weight (IDW) with 6, 12 and 24 points, regression spline (RS), thin spline (TS), universal kriging with spherical and Gaussian variogram (UK_Sphe and UK_gauss, respectively) and multilinear regression (MR), based on physiographic and geographic variables. Furthermore, 32 rainfall stations were used to assess the performance of the previous methods through 7 statistical metrics Ordinary Least Squares (OLS), Root Mean Square Error (RMSE), Normalized root mean square error (NRMSE), Coefficient of determination (R2), Nash-Sutcliffe efficiency coefficient (NSE), Mean Absolute Error (Bias and MAE). Based on these metrics, UK_gauss and IDW_6 provided the best adjustments, whereas MR presented the highest errors. All methods were suitable to predict the spatial distribution of rainfall, but adjustments are conditioned by the features of the study area, gauge density and gauge spatial distribution. [ABSTRACT FROM AUTHOR]

Lead (Pb) halide perovskite solar cells (PSCs) exhibit impressive power conversion efficiencies close to those of their silicon counterparts. However, they suffer from moisture instability and Pb safety concerns. Previous studies have endeavoured to address these issues independently, yielding minimal advancements. Here, a general nanoencapsulation platform using natural polyphenols is reported for Pb‐halide PSCs that simultaneously addresses both challenges. The polyphenol‐based encapsulant is solution‐processable, inexpensive (≈1.6 USD m−2), and requires only 5 min for the entire process, highlighting its potential scalability. The encapsulated devices with a power conversion efficiency of 20.7% retained up to 80% of their peak performance for 2000 h and up to 70% for 7000 h. Under simulated rainfall conditions, the encapsulant rich in catechol groups captures the Pb ions released from the degraded perovskites via coordination, keeping the Pb levels within the safe drinking water threshold of 15 ppb. [ABSTRACT FROM AUTHOR]

AbstractWe present a stochastic programming model for informing the deployment of ad hoc flood mitigation measures to protect electrical substations prior to an imminent and uncertain hurricane. The first stage captures the deployment of a fixed number of mitigation resources, and the second stage captures grid operation in response to a contingency. The primary objective is to minimize expected load shed. We develop methods for simulating flooding induced by extreme rainfall and construct two geographically realistic case studies, one based on Tropical Storm Imelda and the other on Hurricane Harvey. Applying our model to those case studies, we investigate the effect of the mitigation budget on the optimal objective value and solutions. Our results highlight the sensitivity of the optimal mitigation to the budget, a consequence of those decisions being discrete. We additionally assess the value of having better mitigation options and the spatial features of the optimal mitigation. [ABSTRACT FROM AUTHOR]

Slope instability, driven by factors such as rainfall, seismic activity, and human influence, presents a pervasive hazard worldwide. Timely assessment of slope stability and accurate identification of its most critical slip surface are important for slope safety early warning and management. Currently, for the slope reliability analysis by the strength reduction method (SRM), the critical failure path is approximately determined through visualization techniques, which is not sufficiently precise. Therefore, this study proposes a critical failure search method based on SRM for slope reliability analysis, aiming to accurately identify the critical slip surface. The critical failure path is considered as the path with the maximum plastic dissipative energy density (PDED) and is searched in the constructed weighted graph based on the dissipated energy of the slope. This proposed method is further applied with an engineering slope to find the critical failure path and assess its reliability during and after construction. The searched critical failure path lies within the approximate range obtained through conventional visualization methods. Finally, a reliability prediction model consisting of time, rainfall, and deformation component is further constructed, which allows rapid estimation of the slope reliability through available monitor data. The results of reliability analysis indicate that construction disturbances have a significant impact on slope stability, along with other factors such as rainfall and creep. [ABSTRACT FROM AUTHOR]

In this study, the impact of change in land use and land cover (LULC) on runoff estimation in the Kidangoor watershed was assessed using the SCS-CN technique. Recent flood-like natural disasters in Kerala are thought to be driven by changes in rainfall patterns and LULC. The accurate calculation of runoff from watersheds is urgently needed. In ArcGIS 10.5, the supervised classification approach is used to classify satellite images from 2000, 2011, 2013, and 2017. Similarly, the Inverse Distance Weighted (IDW) technique is used to produce spatial distribution maps of rainfall for each antecedent moisture condition (AMC). The runoff maps were generated by superimposing the distributed rainfall, LULC, and Hydrological Soil Group (HSG) maps. It was observed that the built-up area expanded by 168% between 2000 and 2017, whereas other classes decreased by 10-23%. However, compared to 2000, both with and without a change in LULC, runoff generation increased by just 31%, and 27% in 2017. The SCS-CN technique for runoff estimation indicates that the change in LULC in the Kidangoor watershed is insignificant. Thus, this study will help land use planners and decision-makers in limiting the potential damage from flooding when it comes to flood management techniques. [ABSTRACT FROM AUTHOR]

On 8 June 2017, a heavy storm struck the parallel ridge-valley area of western Chongqing, resulting in serious urban waterlogging and landslides, which led to severe impacts on infrastructure and damage to private property. Based on high-resolution optical satellite images, this paper comprehensively identified the landslides triggered by this rainfall event, and established a corresponding landslide database. The database takes the landslide area density and landslide number density as the main indicators, and combines the lithology characteristics to analyze the spatial distribution of landslides. The results show that this event triggered 487 landslides in an area of 583 km2, involving an area of about 485,587 m2, accounting for about 0.083% of the study area. The average landslide number density is 0.84 num/km2, the highest value of landslide number density can reach 55.6 num/km2, and the maximum landslide area density is about 6.4%. These landslides are mainly distributed in the southern foothills of the Huaying Mountain, especially in the weak interlayer lithology area. The database provides scientific reference and data support for exploring the mechanism of landslides in western Chongqing and reducing the risk of landslide disasters under the background of rapid development of local society. [ABSTRACT FROM AUTHOR]

Objectives: The game between socio-economic development and ecological development has always been the core issue in coal areas, but the internal mechanism of tradeoff and cooperative dynamic change of ecosystem services in mining areas under long-term mineral resources development is still lacking in indepth research. Methods: Therefore, taking Shendong mining area as an example, this study used InVEST model to evaluate the changes of four major ecosystem service functions in Shendong mining area from 1990 to 2020, namely, water yield (WY), net primary productivity (NPP), soil conservation (SC) and habitat quality (HQ). Meanwhile, correlation analysis was used to explore the trade-off and synergistic relationship among these services. On this basis, the coupling effect between the four ecosystem services is further discussed by using the constraint line method. Finally, the key drivers of ecosystem service trade-offs/synergies in the region are explored by using geodetectors and the explanations of each influence factor for RMS errors are obtained. Results: The results show that 1) from 1990 to 2020, the water yield and soil retention in the mining area decrease first and then increase, and the net primary productivity and habitat quality increase slowly, mainly in the southeast of the mining area. 2) In terms of constraint relationship, all the four ecosystem services showed hump-like constraint relationship, that is, there was obvious constraint threshold effect. 3) In the Shendong mining area, the synergistic relationship is the dominant relationship between ecosystem services, and the tradeoff effect mainly occurs between water yield and habitat quality. 4) In terms of the driving mechanism of tradeoff/synergy, land use type, temperature, and rainfall are the main factors that cause the spatial differentiation of tradeoff synergy intensity among ecosystem services in Shendong mining area. Conclusions: The results of this study provide a scientific basis for the improvement of ecological environment and sustainable utilization of mineral resources under long-term exploitation. [ABSTRACT FROM AUTHOR]

Urbanization and climate change are contributing to severe flooding globally, damaging infrastructure, disrupting economies, and undermining human well-being. Approaches to make cities more resilient to floods are emerging, notably with the design of flood-resilient structures, but relatively little is known about the role of urban form and its complexity in the concentration of flooding. We leverage statistical mechanics to reduce the complexity of urban flooding and develop a mean-flow theory that relates flood hazards to urban form characterized by the ground slope, urban porosity, and the Mermin order parameter which measures symmetry in building arrangements. The mean-flow theory presents a dimensionless flood depth that scales linearly with the urban porosity and the order parameter, with different scaling for disordered square- and hexagon-like forms. A universal scaling is obtained by introducing an effective mean chord length representative of the unobstructed downslope travel distance for flood water, yielding an analytical model for neighborhood-scale flood hazards globally. The proposed mean-flow theory is applied to probe city-to-city variations in flood hazards, and shows promising results linking recorded flood losses to urban form and observed rainfall extremes. A statistical mechanics approach unveils how urban layout influences flood hazards linking flood risk to factors like ground slope, porosity, building arrangement symmetry, and chord length, offering a scalable model applicable worldwide. [ABSTRACT FROM AUTHOR]

Rainfall in East Asia is affected by two rain‐bearing systems: tropical cyclones and monsoon‐related frontal systems. Distinguishing typhoon rainfall (TR) and non‐typhoon rainfall (non‐TR) helps to understand the evolution process of regional rainfall at different timescales. Taking Fujian Province in the southeast coast of China as an example, based on the fixed box approach of separating TR, the method of determining the size of fixed box is explored. TR and non‐TR are separated in Fujian Province, and the spatial variations of TR and non‐TR at different timescales (annual, monthly, day of annual‐maximum‐rain) are analysed. The results showed that (1) according to the relationship between the sizes of fixed box and the rate of change of TR, the size of fixed box could be reasonably determined; thus, the expended size of fixed box suitable for separating TR in Fujian was 3.5°, namely the range of 20°–31.8°N and 112.3°–124.2°E. (2) The spatial variations of TR at different timescales in Fujian were similar: TR decreased from the coast to the inland, and the northeast coast of Fujian was the high‐value region. Due to the difference of water vapour sources, non‐TR in March–June increased from the coast to the inland, but the high value of non‐TR in July–September was distributed in the eastern coast. (3) The contribution rates of average TR to the total rainfall of the year, July–September and 1 day were 12.8%, 34.6% and 35.7%, respectively. In eastern coast, TR in July–September accounted for 1/3–1/2 of total rainfall, and the rainfall in a day was mainly affected by TR; while in western inland, rainfall was mainly non‐TR and the influence of TR was less than 1/4. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Time Period Major Taxa Studied Methods Results Main Conclusions Ongoing climate changes represent a major determinant of demographic processes in many organisms worldwide. Birds, and especially long‐distance migrants, are particularly sensitive to such changes. To better understand these impacts on long‐distance migrants' breeding productivity, we tested three hypotheses focused on (i) the shape of the relationships with different climate variables, including previously rarely tested quadratic responses, and on regional differences in these relationships predicted by (ii) mean climatic conditions and (iii) by the rate of climate change in respective regions ranging from Spain to Finland.Europe.2004–2021.Long‐distance migratory passerine birds.We calculated breeding productivity from constant effort ringing sites from 11 European countries covering 34° of latitude, and extracted temperature‐ and precipitation‐related climate variables from E‐OBS and NASA MODIS datasets. To test our hypotheses, we fitted GLMM and Bayesian meta‐analytic models.We revealed hump‐shaped responses of productivity to temperature, growing degree‐days, green‐up onset date, and precipitation anomaly, and negative responses to intense and prolonged rains across the regions. The effects of March temperature and April growing degree‐days were more negative in cold than in warm regions, except for the region with the highest accumulated heat, whereas increasing June precipitation anomalies were associated with higher productivity in both dry and wet regions. Productivity responses to climate were unrelated to the rate of climate warming.The influence of climate on bird productivity proved to be frequently nonlinear, as expected by ecological theory. The rate of climate change is less important than regional interannual variability in climate (which is predicted to increase), but this may change with the progression of climate change in the future. Productivity declines in long‐distance migratory songbirds are particularly expected if out‐of‐norm water excess increases in frequency or strength. [ABSTRACT FROM AUTHOR]

Forecasting warm‐sector rainfall (WR) remains a major challenge, primarily due to weak synoptic forcing. Through cloud‐permitting numerical simulations, in addition to direct triggering mechanism from low‐level jets, we identify the important role of gravity waves in a heavy WR event in South China via convective preconditioning. The preconditioning manifests as mid‐level moistening and destabilization with wave‐like variations. This process is driven by fast‐propagating (∼24 m s−1) n = 2 waves, associated with lower‐tropospheric ascents and upper‐tropospheric descents. Waves are generated during the evolution of northern frontal rainfall (FR). As FR intensifies, surges in low‐level diabatic cooling mainly resulting from microphysical processes, trigger n = 2 waves, which further precondition the environment along their path. In contrast, a sensitivity experiment involving stably developing FR fails to reproduce the preconditioning process by waves and the subsequent occurrence of WR. Overall, our study illuminates a new pathway through which FR significantly influences WR via gravity waves. Plain Language Summary: During the rainy season, the coastal regions of South China frequently experience heavy rainfall, leading to significant socio‐economic losses. Unfortunately, understanding the mechanisms underlying this heavy rainfall and accurately predicting it remains a great challenge, as it often occurs without evident synoptic influences such as fronts and low‐pressure vortex. Another rainband occasionally forms to the north of the coastal heavy rainfall through frontal lifting. The northern inland frontal rainfall could be considered a potential contributor to the initiation of coastal heavy rainfall, yet no concrete connection has been established until now. Our research reveals that this frontal rainband can generate low‐frequency gravity waves that have a substantial influence on coastal heavy rainfall. These waves primarily result from the sharp cooling associated with the frontal rainband, featuring lower‐tropospheric upward motions. They are capable to travel considerable distances ahead of the frontal rainband at high speeds. Along their journey, they moisten and destabilize the cloud environment ahead of the frontal rainband, thereby favoring the occurrence of coastal rainfall. Key Points: The initiation of warm‐sector heavy rainfall at the coast is related to the evolution of northern frontal rainfall that located 300 km awayVariations in latent cooling resulting from the frontal rainfall produce gravity waves featuring ascents over the lower troposphereThese gravity waves moisten and destabilize mid‐level environment along their paths, promoting warm‐sector rainfall [ABSTRACT FROM AUTHOR]

Sub6 GHz non‐line‐of‐sight signals are a potential opportunistic source of rainfall information that promises to improve the current urgent need regarding near‐surface rainfall detection, but the complex mechanisms in which these signals are impacted by rainfall have hindered further development in this area. In this study, we focus on four types of microwave propagation processes to explore the theoretical basis for Sub6 GHz signal sensitivity to rainfall. We also investigate how these signals change during rainy conditions using a cellphone signal recording experiment. The results demonstrate that the indirect effect of rainfall‐induced changes in the interfacial water film may significantly affect the Sub6 GHz signal, making it an opportunity to reflect rainfall information. Finally, we offer a comprehensive overview of the potential challenges, benefits, and drawbacks of low‐frequency non‐line‐of‐sight links in the context of rainfall inversion. Plain Language Summary: This study investigates Sub6 GHz non‐line‐of‐sight signals, which are widely available and cost‐effective tools that have the potential to enhance our ability to detect rainfall patterns near the Earth's surface. This combination of theory and experiments gives us a better understanding about the behavior of low‐frequency non‐line‐of‐sight signals in rainy conditions. This knowledge can guide the development of innovative and improved methods for rainfall monitoring in the future through opportunistic means. Key Points: The analysis provides insights into the physical mechanisms underlying this sensitivity of Sub6 GHz signals to rainfallThe experimental results support the theoretical analysis and enhance the understanding of Sub6 GHz signal behavior in rainy environmentsThis summary emphasizes the characteristics and challenges of low‐frequency non‐line‐of‐sight links in potential rainfall monitoring [ABSTRACT FROM AUTHOR]

Meghalaya is known for its complex environment due to its hilly terrain and heavy rains, which result in significant soil erosion challenges. The LS factor is the primary factor used to estimate soil loss. Acquiring accurate LS values has always been a significant challenge. The main aim of this research is to compute the LS factor in the Meghalaya region. Three methods are used to calculate the LS factor: (1) Wischmeier and Smith's (1978) method, (2) Moore and Wilson's (1992) method, and (3) Desmet and Gover's (1996) method. All three approaches used the digital elevation model (DEM) in the spatial domain to determine the LS factor. The results of this investigation demonstrated significant variation in LS factor in all three methods. Wischmeier and Smith's method yielded LS factor values ranging from 0 to 266.538, Moore and Wilson's method resulted in values ranging from 0 to 112.631, and Desmet and Gover's method resulted in values ranging from 0 to 683.679. This study concluded that Wischmeier and Smith's method resulted in LS factor values distributed uniformly across the spatial domain. In contrast, Moore and Wilson's method only yielded high values along the flow path and low values in other areas. Additionally, Desmet and Gover's method identified high LS factors in regions with steep slopes near rivers and streamlines. This study can be helpful in anticipating soil erosion well before time and also in developing a slope management plan in the study region. [ABSTRACT FROM AUTHOR]

Variations in southern African precipitation have a major impact on local communities, increasing climate‐related risks and affecting water and food security, as well as natural ecosystems. However, future changes in southern African precipitation are uncertain, with climate models showing a wide range of responses from near‐term projections (2020–2040) to the end of the 21st century (2080–2100). Here, we assess the uncertainty in southern African precipitation change using five Ocean‐Atmosphere General Circulation single model initial‐condition large ensembles (30–50 ensemble members) and four emissions scenarios. We show that the main source of uncertainty in 21st Century projections of southern African precipitation is the internal climate variability. In addition, we find that differences between ensemble members in simulating future changes in the location of the Angola Low explain a large proportion (∼60%) of the uncertainty in precipitation change. Together, the internal variations in the large‐scale circulation over the Pacific Ocean and the Angola Low explain ∼64% of the uncertainty in southern African precipitation change. We suggest that a better understanding of the future evolutions of the southern African precipitation may be achieved by understanding better the model's ability to simulate the Angola Low and its effects on precipitation. Plain Language Summary: The variability of precipitation in southern Africa has a strong impact on local communities, rain‐fed agriculture, food security and water demand, hydropower production, lake levels, ecosystems, and wildlife. Above‐average rainfall increases the risk of flooding, while below‐average rainfall increases the risk of drought. However, future changes in precipitation in southern Africa are poorly understood. Here, we examine the potential sources of uncertainty in southern African precipitation change using five ocean‐atmosphere general circulation single‐model initial‐condition large ensembles and four emissions scenarios. We show that the main source of uncertainty is the simulation of internal climate variability throughout the 21st century. Among potential drivers, we show that the main driver of uncertainty in southern African precipitation change is the future change in the location of the Angola low. A future northward (southward) shift of the Angola Low is associated with a future decrease (increase) in southern African precipitation. We suggest that a better understanding of future changes in southern African precipitation could be achieved by better understanding the impact of internal climate variability on the Angola Low. Key Points: Future changes in southern African precipitation are uncertainThe main source of uncertainty in simulating southern African precipitation change is internal climate variabilityFuture changes in southern African precipitation depend on internal variations in the meridional location of the Angola Low [ABSTRACT FROM AUTHOR]

In this study, we employ the Conformal Cubic Atmospheric Model (CCAM), a variable‐resolution global atmospheric model, driven by two distinct sea surface temperature (SST) data sets: the 0.25° Optimum Interpolation Sea Surface Temperature (CCAM_OISST) version 2.1 and the 2° Extended Reconstruction SSTs Version 5 (CCAM_ERSST5). Model performance is assessed using a benchmarking framework, revealing good agreement between both simulations and the climatological rainfall spatial pattern, seasonality, and annual trends obtained from the Australian Gridded Climate Data (AGCD). Notably, wet biases are identified in both simulations, with CCAM_OISST displaying a more pronounced bias. Furthermore, we have examined CCAM's ability to capture El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) correlations with rainfall during Austral spring (SON) utilizing a novel hit rate metric. Results indicate that only CCAM_OISST successfully replicates observed SON ENSO‐ and IOD‐rainfall correlations, achieving hit rates of 86.6% and 87.5%, respectively, compared to 52.7% and 41.8% for CCAM_ERSST5. Large SST differences are found surrounding the Australian coastline between OISST and ERSST5 (termed the "Coastal Effect"). Differences can be induced by the spatial interpolation error due to the discrepancy between model and driving SST. An additional CCAM experiment, employing OISST with SST masked by ERSST5 in 5° proximity to the Australian continent, underscores the "Coastal Effect" has a significant impact on IOD‐Australian rainfall simulations. In contrast, its influence on ENSO‐Australian rainfall is limited. Therefore, simulations of IOD‐Australian rainfall teleconnection are sensitive to local SST representation along coastlines, probably dependent on the spatial resolution of driving SST. Plain Language Summary: In this research, the Conformal Cubic Atmospheric Model (CCAM), a global atmospheric model, is used to study the impact of different driving sea surface temperature (SST) data sets on Australian rainfall simulations. Two SST data sets, one with high resolution (OISST) and another at lower resolution (ERSST5), are employed to drive CCAM (CCAM_OISST and CCAM_ERSST5). Model performance is evaluated using a benchmarking approach, indicating that both SST‐driven experiments are in good agreement with observed rainfall patterns in Australia. However, both simulations exhibit wet biases, with CCAM_OISST having a more noticeable bias. The study assesses CCAM's ability to capture the correlation between El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) with rainfall during Austral spring. Results reveal that CCAM_OISST performs better, replicating observed correlations more accurately than CCAM_ERSST5. The research identifies strong SST differences found between OISST and ERSST5 around the Australian coastline. An additional experiment underscores that this "Coastal Effect" plays an important role in simulating IOD‐Australian rainfall correlations, while its impact on ENSO‐Australian rainfall is limited. In conclusion, robust simulations of IOD‐Australian rainfall teleconnection require an accurate representation of local SST, which is related to the spatial resolution of SST products driving the model. Key Points: Novel hit rate metrics are proposed to evaluate El Niño‐Southern Oscillation and Indian Ocean Dipole‐rainfall teleconnectionsCCAM driven by different SST performs well in mean rainfall but ENSO and IOD related rainfall varies substantially over AustraliaResolution of the driving sea surface temperature is important to simulate IOD‐rainfall variability over Australia [ABSTRACT FROM AUTHOR]

Zonal extensions of the Western Pacific subtropical high (WPSH) strongly modulate extreme rainfall activity and tropical cyclone (TC) landfall over the Western North Pacific (WNP) region. These zonal extensions are primarily forced on seasonal timescales by inter‐basin zonal sea surface temperature (SST) gradients. However, despite the presence of large‐scale zonal SST gradients, the WPSH response to SSTs varies from year to year. In this study, we force the atmosphere‐only NCAR Community Earth System Model version 2 simulations with two real‐world SST patterns, both featuring the large‐scale zonal SST gradient characteristic of decaying El Niño‐developing La Niña summers. For each of these patterns, we performed four experimental sets that tested the relative contributions of the tropical Indian Ocean, Pacific, and Atlantic basin SSTs to simulated westward extensions over the WNP during June–August. Our results indicate that the subtle differences between the two SST anomaly patterns belie two different mechanisms forcing the WPSH's westward extensions. In one SST anomaly pattern, extratropical North Pacific SST forcing suppresses the tropical Pacific zonal SST gradient forcing, resulting in tropical Atlantic and Indian Ocean SSTs being the dominant driver. The second SST anomaly pattern drives a similar westward extension as the first pattern, but the underlying SST gradient driving the WPSH points to intra‐basin forcing mechanisms originating in the Pacific. The results of this study have implications for understanding and predicting the impact of the WPSH's zonal variability on tropical cyclones and extreme rainfall over the WNP. Plain Language Summary: Westward extensions of the Western North Pacific subtropical high (WPSH) drive rainfall extremes over the Western North Pacific basin, and is important for the prediction of summer rainfall, including monsoonal rainfall and tropical cyclone activity. Studies have previously highlighted the importance of tropical large‐scale zonal sea surface temperature (SST) gradient—warm tropical Indian Ocean in conjunction with cold equatorial eastern Pacific Ocean—in developing and maintaining the summer WPSH and westward extensions. Here, we further show that even with very similar SST patterns, the large‐scale zonal SST pattern may belie forcing from inter‐basin SSTs versus intra‐basin SSTs. We find that the net influence from the Pacific basin determines whether inter‐basin remote SST gradients versus intra‐basin Pacific SST gradients are the predominant driver of westward extensions. Key Points: Two similar SST patterns belie two different mechanisms forcing the subtropical high's westward extensionsTropical Pacific SST gradient forcing of westward extensions can be suppressed by its extratropical SST forcingRemote Atlantic SST forcing drives westward extensions when the local net Pacific forcing is weak [ABSTRACT FROM AUTHOR]

The Mediterranean region is experiencing pronounced aridification and in certain areas higher occurrence of intense precipitation. In this work, we analyze the evolution of the precipitation probability distribution in terms of precipitating days (or "wet‐days") and all‐days quantile trends, in Europe and the Mediterranean, using the ERA5 reanalysis. Looking at the form of wet‐days quantile trends curves, we identify four regimes. Two are predominant: in most of northern Europe the precipitation quantiles all intensify, while in the Mediterranean the low‐medium quantiles are mostly decreasing as extremes intensify or decrease. The wet‐days distribution is then modeled by a Weibull law with two parameters, whose changes capture the four regimes. Assessing the significance of the parameters' changes over 1950–2020 shows that a signal on wet‐days distribution has already emerged in northern Europe (where the distribution shifts to more intense precipitation), but not yet in the Mediterranean, where the natural variability is stronger. We extend the results by describing the all‐days distribution change as the wet‐days' change plus a contribution from the dry‐days frequency change, and study their relative contribution. In northern Europe, the wet‐days distribution change is the dominant driver, and the contribution of dry‐days frequency change can be neglected for wet‐days percentiles above about 50%. In the Mediterranean, however, the change of precipitation distribution comes from the significant increase of dry‐days frequency instead of an intensity change during wet‐days. Therefore, in the Mediterranean the increase of dry‐days frequency is crucial for all‐days trends, even for heavy precipitation. Plain Language Summary: The Mediterranean region is facing increased dryness alongside more intense rainfall in certain areas. We delved into the change of precipitation frequency and intensity across Europe and the Mediterranean using ERA5 reanalysis data from 1950 to 2020. Our analysis revealed four distinct patterns in how rainfall is evolving. In much of northern Europe, heavy rainfall events are becoming more frequent, while in the Mediterranean, lighter precipitation is decreasing while heavy rain is either increasing or decreasing. To understand these changes better, we used a mathematical model with two parameters. This model helped us track the types of changes in precipitation patterns. We found that in northern Europe, the increase in rainfall intensity is the primary driver of change, while in the Mediterranean, it's more about the increase of the dry‐days frequency. These findings underscore the importance of considering both the frequency and intensity of precipitation when studying climate change impacts. By understanding these shifts, we can better prepare for future weather extremes in these regions and adapt to the changing climate. Key Points: Four regimes of change for daily precipitation distribution are identified, and are captured by a two parameters analytical modelIn northern Europe, a signal of increasing mean and extreme precipitation has emergedIn the Mediterranean, the changes of precipitation appears dominated by changes in dry‐days frequency [ABSTRACT FROM AUTHOR]

The climate characteristics of remote rainfall events in Taiwan from September to February over 41 years (1980–2020) are studied. These events are induced by the interaction between the northeasterly flow and the typhoon's outer circulation. Our findings reveal that rainfall in northeastern Taiwan becomes more prominent when tropical cyclones move to the remote rainfall‐prone area, located in the north Philippine area to the northern South China Sea, and when the background northeasterly wind speed exceeds 7 m s−1. Under these criteria, the confluence of the typhoon's outer circulation and the northeasterly flow creates a convergence area that enhances rainfall in northeastern Taiwan, increasing the occurrence of moderate to extreme rainfall (ER) events. This leads to an average enhancement in rainfall amount of 80–220 mm per day. Additionally, when typhoons are in the remote rainfall‐prone area, there is a greater than 20% chance for events with maximum rainfall over 200 mm day−1 to occur, particularly in the region of 20°–22°N, 116°−124°E, and north to Luzon Island. In this area, the occurrence rate can exceed more than a 45% chance. The highest risk of ER events occurs between 20°–22°N and 118°−120°E, with a probability of over 90%. Notably, the convergence area for the Taiwan cases does not necessarily coincide with the baroclinic forcing as that associated with remote rainfall events observed in Japan, Korea, and North America. Plain Language Summary: We studied a particular pattern of rainfall in Taiwan that occurs between September and February over a 41‐year period (1980–2020). Our research found that when tropical cyclones (TCs) are far from Taiwan and there is a strong northeasterly wind, it causes more rainfall in northeastern Taiwan. This can lead to moderate to extreme rainfall, with an increase in rainfall of 80–220 mm per day. When tropical storms are in a specific area north of Luzon Island, there is a higher chance of heavy rain, with some places receiving more than 200 mm per day. The highest probability of extreme rain events occurs when TCs are in a specific area between 20°–22°N and 118°−120°E, where the chance of extreme rain in Taiwan is over 90%. It happens because the TC circulation meets with the northeasterly flow and creates a convergence area. It's important to note that the way remote rainfall events happen in Taiwan may not be the same as in Japan, Korea, and North America. Key Points: Northeastern Taiwan experiences heavy rainfall as tropical cyclone (TC) move toward North South China Sea while northeasterly flow >7 m/sTyphoons' outer flow and the northeasterly convergence enhanced remote rainfall events to 80–220 mm/dayAbove 45% of events with max daily rainfall over 200 mm occur when TCs are in the 20°–22°N, 116°–124°E area and north to Luzon Island [ABSTRACT FROM AUTHOR]

Rhegmatogenous retinal detachment (RRD) is a sight-threatening condition with rising global incidence. Identifying factors contributing to seasonal variations in RRD would allow a better understanding of RRD pathophysiology. We therefore performed a retrospective case series study investigating the relationship between RRD occurrence and meteorological factors throughout metropolitan France (the METEO-POC study), particularly the mean temperature over the preceding 10-day period (T-1). Adult patients having undergone RRD surgery and residing in one of the three most populated urban areas of each French region were included (January 2011–December 2018). The study involved 21,166 patients with idiopathic RRD (61.1% males, mean age 59.8–65.1 years). RRD incidence per 100,000 inhabitants increased from 7.79 to 11.81. RRD occurrence was not significantly associated with mean temperature over T-1 in the majority of urban areas (31/36). In a minority of areas (5/36) we observed correlations between RRD incidence and mean temperature over T-1, however these were extremely weak (r = 0.1–0.2; p < 0.05). No associations were found between RRD incidence and secondary outcomes: mean daily temperature over the 10 days prior T-1, minimum/maximum temperatures, rainfall, duration of sunshine, atmospheric pressure, overall radiation, relative humidity, wind speed. Overall, we found no relationships between meteorological parameters and RRD occurrence. [ABSTRACT FROM AUTHOR]

Recent research has shown that there is a projected increase in the frequency of strong positive Indian Ocean dipole (spIOD) events in terms of both sea surface temperature (SST) and precipitation. However, it is not clear whether the spIOD events defined by SST and precipitation, hereafter referred to as SST-spIOD and Pr-spIOD events, respectively, will increase at the same pace under greenhouse warming. Using climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and CMIP6 that can reasonably simulate the spIOD events, here we find that the occurrence of Pr-spIOD events increases much more than that of SST-spIOD events (+217% vs +77%) under the future high-emission scenario. The diverse response stems from a notably large increase in the spIOD events with strong rainfall but moderate SST anomalies (Pr-only spIOD), which is facilitated by a change in the local meridional Hadley circulation induced by land–sea thermal contrast in addition to the background mean-state SST warming. For the spIOD events with prominent anomalies in both rainfall and SST (concurrent spIOD), their occurrences are projected to increase, but their average SST amplitude is projected to weaken. The increased occurrence is associated with a westward-extended structural change induced by mean linear zonal advection feedbacks, while the weakened event-average SST amplitude results from a more stabilized atmosphere and coincides with the projected reduction in IOD SST skewness. Our results suggest that IOD-related mitigation strategies should consider the diverse responses of different kinds of spIOD events to greenhouse warming. [ABSTRACT FROM AUTHOR]

Fluopyram, a pyridyl ethyl benzamide broad-spectrum fungicide and nematicide, used for the management of plant parasitic nematodes and soil-borne fungi, is recommended for use in crops like tomato, potato and tobacco. Fluopyram being a pesticide used for drenching soil, there is every possibility of it getting leached down with water, ultimately leading to contamination of waterbodies. An experiment was conducted to study the downward movement of fluopyram in laterite and red loam soils in Kerala, India. Fluopyram and fluopyram benzamide, each at150 µg, were loaded separately on top of the respective soil column and were eluted separately with 20, 40, 80 and 160 mL each of water equivalent to 50, 100, 200 and 400 mm rainfall. It was observed that 76.84% and 74.85% of fluopyram and 73.48% and 64.24% of fluopyram benzamide were confined to the top 0–10 cm soil with application of 20 mL water in laterite and red loam soil, respectively. More than 50% of fluopyram and fluopyram benzamide were detected in the top 0–10 cm layer of soil with the application of 40 and 80 mL water. With the application of 160 mL water, considerable reduction in the concentration of both compounds was observed and the residues moved beyond 30 cm. Leaching of residues was more in laterite soil than in red loam soil, and they are in direct relation to the volume of water applied and the residues moved beyond 30 cm depth with 160 mL water. [ABSTRACT FROM AUTHOR]

Blackgram, a protein-rich pulse crop (24%), is crucial for combating food insecurity, particularly in malnourished and economically weak countries. Enhancing blackgram production requires improved, input-saving management practices. Given the challenges of climate change and population growth, efficient water management is vital for increasing pulse productivity and water use efficiency with minimal investment. This study aimed to identify cost-effective irrigation methods to optimise blackgram yields. Experiments were conducted at the National Pulses Research Centre in Vamban, Pudukkottai, and the Agricultural College and Research Institute in Kumulur, Tiruchirappalli, during the kharif season of 2021 and 2022. The study compared different treatments of irrigation methods, such as check basin, raised bed, drip, sprinkler and rain hose irrigation. Results showed that the rain hose system maintained the highest soil moisture (23.93% at 10 cm depth and 19.71% at 20 cm depth). Even though drip irrigation resulted in a higher seed yield (1363 kg ha−1), the rain hose system proved to be more cost-effective, saving 27.09% in costs and achieving a 15.23% higher benefit–cost ratio. These findings suggest that the rain hose method, combined with current agronomic practices, is a viable low-cost technique for sustainable blackgram cultivation, optimising water use and maximising profits. This research provides valuable insights into water-saving irrigation methods for pulse crops. [ABSTRACT FROM AUTHOR]

Synoptic forcings have traditionally played a pivotal role in extreme rainfall over North China. However, there are still large unexplained gaps in understanding the formation of extreme rainfalls over this region. The heavy rainfall event, lasting from 29 July to 2 August 2023 (referred to as "23·7" event), is characterized by long duration, widespread coverage, and high accumulated rainfall over North China. Overall, the persistent extreme rainfall is closely associated with the remnant vortex originating from typhoon Doksuri(2305), tropical storm Khanun(2306), and the unusual westward extended western Pacific subtropical high (WPSH), as well as quasi-stationary cold dry air masses surrounding North China on the west and north sides. Based on wind profiles and rainfall characteristics, the life history of the "23·7" event is divided into two stages. In the first stage, the western boundary of the western Pacific subtropical high (WPSH) was destroyed by the tropical storm Doksuri, appearing that the WPSH retreated eastward with decreasing height. As a result, an inclined vertical distribution on the western boundary was established below 500 hPa. Therefore, convections were limited by the tilted WPSH with warm-dry cover embedded in the low-to-middle troposphere. Meanwhile, the orography in the west of North China was controlled by cold air masses above nearly 3.0 km. Combining the orographic and cold air blockings, only a shallow southeasterly layer (between 1.3 and 3.0 km) can overpass mountains. Although the warm and moist southeasterly flows were lifted by orography, no convections were triggered because of the local capped cold and dry air masses overhead. Under this framework, equivalent potential temperature (θe) gradients were established between warm humid and dry cold air masses, similar to a warm front, causing warm air to lift and generate widespread rainfall but low intensity. However, the lifting was too weak to allow convection to be highly organized. In the second stage, the WPSH was further destroyed by enhanced Khanun, and thus the embedded warm-dry cover associated with the tilted WPSH was significantly thinned. Consequently, convections triggered by orographic blocking can move upward and consequently further develop, forming deep convections. Comparatively speaking, the convections in the second stage are much deeper than those in the first stage. The results gained herein may shed new light on better understanding and forecasting of long-lasting extreme rainfall. [ABSTRACT FROM AUTHOR]

Landslide disasters, due to their widespread distribution and clustered occurrences, pose a significant threat to human society. Rainfall is considered a primary triggering factor, and the frequent clustering of landslides underscores the importance of early warning systems for regional landslide disasters in preventing and mitigating rainfall-induced landslides. Research on early warning models is crucial for accurately predicting rainfall-induced landslides. However, traditional models face challenges such as the complexity of landslide causes, insufficient data, and limited analysis methods, resulting in low accuracy and inadequate precision. This study focuses on Fujian Province, China, proposing a four-step process for building a regional landslide early warning model based on machine learning. The process includes data integration and cleaning, sample set construction, model training and validation, and practical application. By integrating and cleaning the latest and most detailed data, a training sample set (15,589 samples) for the regional landslide disaster early warning model is established. Three machine learning algorithms--Random Forest, Multilayer Perceptron, and Convolutional Neural Network--are employed and compared, the evaluation results indicated that the RF-based warning model achieved an accuracy of 0.930-0.957 and an AUC value of 0.955. The CNNbased warning model demonstrated an accuracy of 0.945-0.948 with an AUC value of 0.940. The MLP-based warning model achieved an accuracy of 0.930-0.953 and an AUC value of 0.930. The results showed comparable accuracy metrics among the three models, with RF exhibiting a significant advantage in AUC values. Finally, the models are applied to the regional landslide disasters induced by heavy rainfall in Fujian Province on 5 August 2021. The results showed that in the binary classification warning strategy, the accuracy of the Random Forest and Convolutional Neural Network was 92.9%, while that of the Multilayer Perceptron was 85.8%, all performing well. In the multi-classification hierarchical warning strategy, the Random Forest excelled, while the performance of the Convolutional Neural Network and Multilayer Perceptron was relatively limited. The findings of this study Frontiers in Earth Science 01 frontiersin.org Liu et al. 10.3389/feart.2024.1419421 contribute to valuable attempts in landslide disaster warning model research, with anticipated further improvements through the gradual accumulation of samples and practical application verification. [ABSTRACT FROM AUTHOR]

This paper tests a multivariate statistical model to simulate rainfall dependent susceptibility scenarios of shallow landslides. To this end, extreme rainfall events spanning from 1977 to 2021 in the Orba basin (a study area of 505 km2 located in Piedmont, northern Italy), have been considered. First of all, the role of conditioning and triggering factors on the spatial pattern of shallow landslides in areas with complex geological conditions is analysed by comparing their spatial distribution and their influence within logistic regression models, with results showing that rainfall and specific lithological and geomorphological conditions exert the strongest control on the spatial pattern of landslide. Different rainfall-based scenarios were then modelled using logistic regression models trained on different combinations of past events and evaluated using an ensemble of performance metrics. Models calibrated on multi-events outperform the ones based on a single event, since they are capable of compensating for local misleading effects that can arise from the use of a single rainfall event. The best performing developed model considers all the landslide triggering rainfall scenarios and two non-triggering intense rainfall events, with a score of 0.90 out of 1 on the multi-criteria TOPSIS-based performance index. Finally, a new approach based on misclassification costs is proposed to account for false negatives and false positives in the predicted susceptibility maps. Overall, this approach based on a multi-event calibration and on a misclassification costs analysis shows promise in producing rainfall dependent shallow landslide susceptibility scenarios that could be used for hazard analyses, early warning systems and to assist decision-makers in developing risk mitigation strategies. [ABSTRACT FROM AUTHOR]

Medicinal macrofungi, like prized plants and animals, have dietary, therapeutic and commercial significance. This knowledge, anchored in the traditional healthcare system, warrants the identification of the most prominent species harbouring novel natural products. A traditional ethnobiological approach was adopted to collect ethnomycological data by interviewing 110 informants (95 men and 15 women) inhabiting 10 settlements in Bannu District, Pakistan. Visiting the remote nomadic sites revealed the most unique data of its type. This data was assessed and correlated with previous studies, comparing the standard numerical indices: informant consensus factor, fidelity level, use value, relative frequency of citation and Jaccard index. Tradition medicinal uses of 30 species of wild macrofungi (belonging to 19 genera and 12 families) are documented here. Podaxis pistillaris macrofungi was preference ranked with priority therapeutic uses, medicinally for stomach problems, as an antipyretic, for erotic uses, as an immune booster and as an antidiabetic; it is also nutritionally significant. Temperature and humidity are key factors for the growth of macrofungi generally in Pakistan (in spring and during the monsoon season), while the dynamic frequency of rain in the rainy season due to the impact of climate change cannot be neglected. Indigenous communities divided the ethnomycological potential of macrofungi into three main clusters: (a) edible macrofungi, for treating various disorders and as nutritional supplements; (b) non-edible macrofungi, medicinally important or just poisonous; (c) unknown or unused, without any known utility. Importantly, eight novel species with traditional uses are reported here, and the present work is the first ethnomycological study of macrofungi from Pakistan. This research aims to trace the traditional knowledge related to the naturally occurring medicinal macrofungi in the Bannu District, Khyber Pakhtunkhwa, Pakistan. Documentation of new medicinal species and novel uses of existing species reflect a healthy relationship between inhabitants of the Bannu District and wild medicinal macrofungi. [ABSTRACT FROM AUTHOR]

The latex of Ipomoea (Convolvulaceae) is a source of a special kind of acylsugars called resin glycosides, which are highly appreciated because of their biological activities (i.e. laxative, antimicrobial, cytotoxic etc.). Most research has been conducted in perennials with tuberous roots, where resin glycosides are stored. However, their content and variation are unknown in annual vines that lack this type of root, such as in the case of Ipomoea parasitica. This species contains research/biological and human value through its fast growth, survival in harsh environments, and employment in humans for mental/cognitive improvements. These qualities make I. parasitica an ideal system to profile resin glycosides and their variations in response to edaphoclimate. Topsoil samples (0–30 cm depth) and latex from petioles of I. parasitica were collected in two localities of central Mexico. The latex was analyzed through UHPLC-ESI-QTOF, and soil physico-chemical characteristics, the rainfall, minimum, average, and maximum temperatures were recorded. We also measured canopy (%), rockiness (%), and plant cover (%). A Principal Component Analysis was conducted to find associations between edaphoclimate and the resin glycosides. Forty-four resin glycosides were found in the latex of I. parasitica. Ten correlated significantly with three components (47.07%) and contained tetrasaccharide, pentasaccharide, and dimers of tetrasaccharide units. Five resin glycosides were considered constitutive because they were in all the plants. However, exclusive molecules to each locality were also present, which we hypothesize is in response to significant microhabitat conditions found in this study (temperature, clay content, pH, and potassium). Our results showed the presence of resin glycosides in I. parasitica latex and are the basis for experimentally testing the effect of the conditions above on these molecules. However, ecological, molecular, and biochemical factors should be considered in experiments designed to produce these complex molecules. [ABSTRACT FROM AUTHOR]

Climate models commonly overestimate warm rain frequency and underestimate its intensity over the ocean, primarily due to insufficient representation of the aerosol effects. This pertains to both fine aerosols (FA) and coarse sea spray aerosols (CSA), where the latter is mostly absent in the models. Here, our observations show that adding CSA enhances vertical warm rain structure, in contrast to the effect of FA. The magnitude of the effect of CSA is larger than the opposite effect of the FA. For rain with top heights of 2–3 km, the raindrop size, concentration, and rain rate can be increased by factors of 1.03, 1.47, and 1.60, respectively. These CSA-induced changes are larger for thicker clouds, reaching a maximum by factors of 1.12, 1.85, and 2.21, respectively. Therefore, the combined FA and CSA effects should be incorporated into climate models for accurately simulated precipitation microphysical processes. [ABSTRACT FROM AUTHOR]

In England, the Environment Agency (EA) estimates that over 3 million properties in England are at risk of surface water flooding. Heavy and prolonged rainfall that drives surface water flooding is projected to increase in the future due to climate change. This paper presents a quantitative secondary analysis of a cross-sectional household flood survey in a disadvantaged city in England heavily impacted by surface water flooding in 2007 and at severe risk of flooding in the future. The aim of this study was to examine how previous experience of flooding, demographic factors, and behaviours impact on feelings of protection against flooding and perceived ability to recover from flooding. Survey data were collected from residents in Hull in northern England in 2018, in areas impacted by major floods in 2007 when over 8,600 households were flooded. Valid responses were received from 453 households, of whom 37.3% were flooded or flooding damaged their house (n = 169), 14.6% had been disrupted by flooding (n = 66), 9.3% had been exposed to flooding (n = 42) and 176 (38.9%) had not experienced flooding. Over 22% felt they had very low protection against flooding, and over 25% would make a very slow recovery if they were flooded. Associations were found between gender and both low levels of protection against flooding. Females were less likely to feel confident in their recovery from flooding than males (OR 0.551). The findings support a need to focus on women's perceptions of flood vulnerability and capacity to cope and recover from flooding in flood and disaster management policy and practice, including providing effective support before, during and after flooding. [ABSTRACT FROM AUTHOR]

Background: Chickpea is a key pulse crop grown in the spring in dryland regions. The cold resistance potential of chickpeas allows for the development of genotypes with varying sowing dates to take advantage of autumn and winter rainfall, particularly in dryland regions. In this study, we assessed grain yield, plant height, 100-seed weight, days to maturity, and days to flowering of 17 chickpea genotypes in five autumn-sown dryland regions from 2019 to 2021. Additionally, the response of selected chickpea genotypes to cold stress was examined at temperatures of -4 °C, 4 °C, and 22 °C by analyzing biochemical enzymes. Results: Mixed linear model of ANOVA revealed a significant genotype × environment interaction for all traits measured, indicating varying reactions of genotypes across test environments. This study reported low estimates of broad-sense heritability for days to flowering (0.34), days to maturity (0.13), and grain yield (0.08). Plant height and seed weight exhibited the highest heritability, with genotypic selection accuracies of 0.73 and 0.92, respectively. Moreover, partial least square regression highlighted the impactful role of rainfall during all months except of October, November, and February on grain yield and its interaction with environments in autumn-planted chickpeas. Among the genotypes studied, G9, G10, and G17 emerged as superior based on stability parameters and grain yield. In particular, genotype G9 stood out as a promising genotype for dryland regions, considering both MTSI and genotype by yield*trait aproaches. The cold assay indicated that − 4 °C is crucial for distinguishing between susceptible and resistant genotypes. The results showed the important role of the enzymes CAT and GPX in contributing to the cold tolerance of genotype G9 in autumn-sown chickpeas. Conclusions: Significant G×E for agro-morphological traits of chickpea shows prerequisite for multi-trial analysis. Chickpea's direct root system cause that monthly rainfall during plant establishment has no critical role in its yield interaction with dryland environment. Considering the importance of agro-morphological traits and their direct and indirect effects on grain yield, the utilization of multiple-trait stability approches is propose. Evaluation of chickpea germplasm reaction against cold stress is necessary for autumn-sowing. Finally, autumn sowing of genotype FLIP 10–128 C in dryland conditions can led to significant crop performance. [ABSTRACT FROM AUTHOR]

Aim Location Taxa Time Period Methods Results Conclusions Shifting climates are reshaping ecosystems globally and are projected to intensify over the coming century. Understanding how biodiversity will respond to these shifts is crucial for developing effective climate adaptation measures. We generate predictive models built from long‐term data to hindcast historic fluctuations in small mammal abundances as they have responded to shifting rainfall and fire conditions. This data set serves as the basis for predicting historical variations (hindcasting) in small mammal abundances, allowing us to examine their responses to decadal changes in fire and rainfall conditions within our study landscape.Australia (Victoria).Small mammals (Mammalia).1970–2022.Small mammal abundance was surveyed at 36 long‐term trapping sites and modelled against coinciding fire history, vegetation productivity and rainfall using generalized additive mixed models. Six species were then used in predictive modelling against these variables for the decades preceding our monitoring programme (1970–2007).All species abundances increased with higher rainfall. Time since fire was also an important variable in all but one species model, with species displaying varying responses to time since fire. Hindcasting predictions for small mammal abundances varied with some species showing marked declines over time. Clear trends emerged, indicating more volatile population fluctuations in response to intensified fire and rainfall extremes in the 21st century. This suggests that periods of higher rainfall and less frequent fire events in the decades preceding our monitoring period supported higher and more stable small mammal abundances.Native species show distinct sensitivity to the combined effects of drought and fire, which has occurred in recent times. Intensification of these drivers has caused increased volatility in small mammal abundances with low abundance extremes occurring more frequently. [ABSTRACT FROM AUTHOR]

The present investigation breaks new ground by examining the Raniganj sediments in the Kendudihi section of the Ib‐River Coalfield, Odisha, India. The study identifies a megaflora consisting of 25 species of Glossopteris, Vertebraria indica, stem casts and equisetaceous stems. The microflora is predominantly composed of Striatopodocarpites spp., with a secondary presence of Densipollenites spp. The lithological signatures, including off‐white fine‐grained sandstone with thin bands of silty shale and grey shale, indicate that these sediments belong to the Late Permian succession of the Lower Gondwana sequence, specifically the Raniganj Formation. The macrofloral assemblage found in the lowermost grey shale can be attributed to the Wordian–Capitanian age, while the microfloral assemblage in the upper silty shale resembles that of the Wuchiapingian‐Changhsingian age. Well‐preserved palynomorphs and megafossils, along with the abundant occurrence of lath‐shaped translucent phytoclasts in the grey and silty shale of the Raniganj sediments exposed in the Kendudihi section, explicitly suggest that the sediments were deposited in proximal, low‐energy swampy settings. Additionally, the moderate occurrence of charcoal (20%), along with the existence of degraded organic matter (DOM: 7.6%) and amorphous organic matter (AOM: 16.4%), indicates that the sediments might have been deposited in oxic–dysoxic conditions. The palynological and megafloral studies reveal a warm‐temperate climate with low humidity and intermittent spells of hot and cold seasons, associated with abundant rainfall. The occurrence of phosphorite in the form of nodules and thin lenses, as well as biogenic structures at the juncture of the Raniganj and Barren Measures formations, suggests a marine incursion in the area during the deposition of the late Barren Measures and early Raniganj sediments. X‐ray diffraction (XRD) analysis identified fluorapatite (Ca5(PO4)3F) as the predominant phosphatic mineral phase in the phosphatic nodule, siltstone and claystone. The Post‐Archean Australian Shale composition, normalized rare earth element (REE) patterns of samples from this area, reveals slight positive La (average La anomaly: 1.02) and Gd (average Gd anomaly: 1.05) anomalies and heavy REE enrichment compared to light REE, explicitly indicating a marine environment. [ABSTRACT FROM AUTHOR]

Background: The government of Lao PDR has increased efforts to control malaria transmission in order to reach its national elimination goal by 2030. Weather can influence malaria transmission dynamics and should be considered when assessing the impact of elimination interventions but this relationship has not been well characterized in Lao PDR. This study examined the space–time association between climate variables and Plasmodium falciparum and Plasmodium vivax malaria incidence from 2010 to 2022. Methods: Spatiotemporal Bayesian modelling was used to investigate the monthly relationship, and model selection criteria were used to evaluate the performance of the models and weather variable specifications. As the malaria control and elimination situation was spatially and temporally dynamic during the study period, the association was examined annually at the provincial level. Results: Malaria incidence decreased from 2010 to 2022 and was concentrated in the southern regions for both P. falciparum and P. vivax. Rainfall and maximum humidity were identified as most strongly associated with malaria during the study period. Rainfall was associated with P. falciparum incidence in the north and central regions during 2010–2011, and with P. vivax incidence in the north and central regions during 2012–2015. Maximum humidity was persistently associated with P. falciparum and P. vivax incidence in the south. Conclusions: Malaria remains prevalent in Lao PDR, particularly in the south, and the relationship with weather varies between regions but was strongest for rainfall and maximum humidity for both species. During peak periods with suitable weather conditions, vector control activities and raising public health awareness on the proper usage of intervention measures, such as indoor residual spraying and personal protection, should be prioritized. [ABSTRACT FROM AUTHOR]

Instrumental variable (IV) analysis relies on the exclusion restriction—that the instrument only affects the dependent variable via its relationship with the independent variable and not via other causal routes. However, scholars generally justify the exclusion restriction based on its plausibility. I propose a method for searching for additional violations implied by existing social science studies. I show that the use of weather to instrument different independent variables represents strong prima facie evidence of exclusion‐restriction violations for all weather‐IV studies. A review of 289 studies reveals 194 variables previously linked to weather: all representing potential exclusion‐restriction violations. Using sensitivity analysis, I show that the magnitude of many of these violations is sufficient to overturn numerous existing IV results. I conclude with practical steps to systematically review existing literature to identify and quantify possible exclusion‐restriction violations when using IV designs. [ABSTRACT FROM AUTHOR]

The banana mealybug Pseudococcus elisae Borchsenius (Hemiptera: Coccomorpha: Pseudococcidae) is a pest of economic importance in Cameroon that requires effective control practices, especially after the routinely used chlorpyrifos insecticide was banned in 2019. For effective mealybug control, it is imperative to understand their ecology in relation to banana growth stages and climate‐induced seasonal variations. Therefore, the influence of climatic variables and banana growth stages on a spatio‐temporal distribution of mealybugs in Esuke and Benoe banana plantations of the Cameroon Development Corporation in Tiko was assessed. A 60‐ha area was mapped in each plantation and divided into 12 plots of 5 ha each, which were further sub‐divided into four quadrants of 1.25 ha. A total of 10 banana suckers, 10 pre‐flowering, 10 flowering and 10 bunchy plants were sampled per quadrant. Monthly mealybug population dynamics were assessed across 2 years in 2021 and 2022 on lower or upper pseudostem, leaves and banana bunches. Significant yearly and monthly mealybug population variation on banana plants were observed, with more mealybugs in 2022 than 2021, and two monthly mealybug peaks in February and November (p < 0.001). Mealybug population was higher on banana bunches and lower or upper pseudostem than on leaves (p < 0.001). Mealybugs preferred bunchy plants than suckers or pre‐flowering and flowering plants, and exhibited clumped distribution with Taylor aggregation index (b) greater than one (p < 0.001). A simple linear regression revealed strong positive effects of high temperature on mealybug population ecology, while relative humidity and rainfall had inverse effects on the population of mealybug. These highlight the dynamics of banana mealybug population ecology under variable climatic conditions and banana growth stages, which provides valuable baseline information to facilitate developing effective control strategies for mealybugs in banana plantations. [ABSTRACT FROM AUTHOR]