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This paper was to develop a prediction framework for obtaining the rheological properties of extracted and recovered asphalt binders utilizing mixture performance and other factors such as in-place air voids, pavement structure, traffic level, and aging duration. A total of 21 field projects consisting of 66 pavement sections were included in the analysis, which were located in different climatic zones with various RAP contents, traffic levels, pavement structures, pavement age, and material properties. Results indicate that the neural network can be successfully adopted to predict cracking-related binder properties consisting of effective asphalt binder, G*sin(δ) and binder fracture energy, and rutting-related binder properties including high temperature performance grade (PG), MSCR Jnr3.2, and R3.2. Both prediction and validation models worked well for pavement sections with varied contents of RAP when new data was introduced. [ABSTRACT FROM AUTHOR]

Summary: Angiosperms with large genomes experience nuclear‐, cellular‐, and organism‐level constraints that may limit their phenotypic plasticity and ecological niche, which could increase their risk of extinction. Therefore, we test the hypotheses that large‐genomed species are more likely to be threatened with extinction than those with small genomes, and that the effect of genome size varies across three selected covariates: life form, endemism, and climatic zone.We collated genome size and extinction risk information for a representative sample of angiosperms comprising 3250 species, which we analyzed alongside life form, endemism, and climatic zone variables using a phylogenetic framework.Genome size is positively correlated with extinction risk, a pattern driven by a signal in herbaceous but not woody species, regardless of climate and endemism. The influence of genome size is stronger in endemic herbaceous species, but is relatively homogenous across different climates. Beyond its indirect link via endemism and climate, genome size is associated with extinction risk directly and significantly.Genome size may serve as a proxy for difficult‐to‐measure parameters associated with resilience and vulnerability in herbaceous angiosperms. Therefore, it merits further exploration as a useful biological attribute for understanding intrinsic extinction risk and augmenting plant conservation efforts. [ABSTRACT FROM AUTHOR]

Climate change and invasive species represent two intertwined global environmental challenges profoundly affecting freshwater ecosystems. This study uses Ecological Niche Modeling along with risk screening to delve into the preferences and potential distribution of Potamopyrgus antipodarum, an invasive species, in relation to climate zones and habitat types, shedding light on the critical importance of coastal wetlands and high soil organic carbon content in shaping habitat suitability. Our findings underscore that P. antipodarum exhibits a distinct affinity for cool temperate, moist climates, as well as temperate floodplain rivers, wetlands, and coastal areas. Notably, coastal wetlands, endowed with elevated soil organic carbon levels, emerged as pivotal habitats for this species. Projections indicated a significant expansion in North America, potentially extending into South America. Türkiye reveals an intriguing alignment between its habitat and the natural distribution areas of P. antipodarum, presenting potential for habitat contraction while still retaining a broader range compared to other regions. These potential expansions were predominantly driven by climate suitability, playing a pivotal role in the invasiveness of P. antipodarum, with anticipated future climate regimes exerting substantial influence on its dispersal capabilities. [ABSTRACT FROM AUTHOR]

Net radiation (Rn), a critical component in land surface energy cycling, is calculated as the difference between net shortwave radiation and longwave radiation at the Earth's surface and holds significant importance in crop models for precision agriculture management. In this study, we examined the performance of four machine learning models, including extreme learning machine (ELM), hybrid artificial neural networks with genetic algorithm models (GANN), generalized regression neural networks (GRNN), and random forests (RF), in estimating daily Rn at four representative sites across different climatic zones of China. The input variables included common meteorological factors such as minimum and maximum temperature, relative humidity, sunshine duration, and shortwave solar radiation. Model performance was assessed and compared using statistical parameters such as the correlation coefficient (R2), root mean square errors (RMSE), mean absolute errors (MAE), and Nash–Sutcliffe coefficient (NS). The results indicated that all models slightly underestimated actual Rn, with linear regression slopes ranging from 0.810 to 0.870 across different zones. The estimated Rn was found to be comparable to observed values in terms of data distribution characteristics. Among the models, the ELM and GANN demonstrated higher consistency with observed values, exhibiting R2 values ranging from 0.838 to 0.963 and 0.836 to 0.963, respectively, across varying climatic zones. These values surpassed those of the RF (0.809–0.959) and GRNN (0.812–0.949) models. Additionally, the ELM and GANN models showed smaller simulation errors in terms of RMSE, MAE, and NS across the four climatic zones compared to the RF and GRNN models. Overall, the ELM and GANN models outperformed the RF and GRNN models. Notably, the ELM model's faster computational speed makes it a strong recommendation for Rn estimates across different climatic zones of China. [ABSTRACT FROM AUTHOR]

Sodium batteries are considered a promising candidate for large‐scale grid storage at tropical climate zone, and solid‐state sodium metal batteries have a strong proposition as high energy density battery. The main challenge is to develop ultra‐pure solid‐state ceramic electrolyte and compatible metal interface. Here, a scalable and energy‐efficient synthesis strategy of sodium (Na) Super Ionic CONductor, Na1+xZr2SixP3‐xO12 (x = 2, NZSP) solid electrolyte, has been introduced with the complete removal of unreacted zirconium oxide (ZrO2) impurities. Additionally, the reaction mechanism for the formation of pure phase NZSP is reported for the first time. The NZSP prepared by utilizing the Zr precursor, i.e., tetragonal zirconium oxide (t‐ZrO2) derived from the Zr(OH)4 gets quickly and completely consumed in the synthesis process leaving no unreacted monoclinic ZrO2 impurities. The synthesis process only needs a minimum stay of 4 h, which is three times less than the conventional synthesis method. The elimination of ZrO2 impurities results in a 2.5‐fold reduction in grain boundary resistivity, showcasing a total ionic conductivity of 1.75 mS cm−1 at room temperature and a relative density of 98%. The prepared electrolyte demonstrates remarkable resistance to dendrite formation, as evidenced by a high critical current density value of 1.4 mA cm−2. [ABSTRACT FROM AUTHOR]

BACKGROUND RESULTS CONCLUSIONS Coffee (Coffea arabica L.) is one of the most important commodities today, with a high economic value worldwide. Coffee leaf rust (Hemileia vastatrix Berk. et Br.) has been showing a high impact on Brazilian coffee trees among the various diseases that attack coffee. The climate has a great influence on the development of diseases, especially when fungi are the causal agents. This study aimed to carry out the zoning of climate favorability for coffee leaf rust in the traditional and main coffee‐producing regions of Brazil. The study was conducted in 13 locations in the states of Paraná, São Paulo, Rio de Janeiro, Espírito Santo, Minas Gerais, Goiás and Bahia. Air temperature and daily precipitation data for the current scenario were collected using the WorldClim version 2.1 platform for the last climatological normal and future climate change data. The ideal climate conditions for coffee leaf rust consist of a mean air temperature ranging from 21 to 25 °C and precipitation >30 mm per month. The Coupled Model Intercomparison Projects scenarios associated with the Intergovernmental Panel on Climate Change reports consisted of the Shared Socio‐Economic Pathways SSP‐1 2.6, SSP‐2 4.5, SSP‐3 7.0 and SSP‐5 8.5, the latter being considered one of the most catastrophic. All steps to carry out the suitability zoning were performed in a tool using the QGIS geographic information system software.Zoning for coffee leaf rust had three classes: favorable, relatively favorable and unfavorable. Currently, the largest coffee‐producing region in Brazil has 49.1% of its analyzed area classified as favorable, 39.2% as relatively favorable and 11.7% as unfavorable. In the current scenario, Patrocínio and Três Pontas are locations with high coffee production in which the favorable class is predominant. The state of Minas Gerais has an annual mean of 55.3% of its entire territory apt for the disease, with the highest occurrence between September and March.Climate change has a negative impact on the development of coffee leaf rust, mainly in the long term, as in the period of 2081–2100, in which the SSP‐5 8.5 scenario led to a decrease in the favorable and unfavorable areas and an increase in the relatively favorable areas of 9.8%, 18.6% and 71.5% for the Brazilian territory, respectively. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Flash droughts, characterized by rapid onset and development, present significant challenges to agriculture and climate mitigation strategies. Operational drought monitoring systems, based on precipitation, soil moisture deficits, or temperature anomalies, often fall short in timely detection of these events, underscoring the need for customized identification and monitoring indices that account for the rapidity of flash drought onset. Recognizing this need, this paper introduces a global flash drought inventory from 1990 to 2021 derived using the Soil Moisture Volatility Index (SMVI). Our work expands the application of the SMVI methodology, previously focused on the United States, to a global scale, providing a tool for understanding and predicting these rapidly developing phenomena. The dataset encompasses detailed event characteristics, including onset, duration, and severity, across diverse climate zones. By integrating atmospheric variables through their impact on soil moisture, the inventory offers a platform for analyzing the drivers and impacts of flash droughts, and serves as a large, consistent dataset for use in training and evaluating flash drought prediction models. [ABSTRACT FROM AUTHOR]

Background: Achieving zero-energy targets in residential buildings is challenging due to improper energy design and the selection of energy-related systems. Moreover, the absence of benchmarks for zero-energy residential buildings, along with the scarcity of studies tailored to diverse climates and building characteristics, highlights the urgent need for further research. This study aimed to address these gaps by designing zero-energy buildings to suit diverse climate zones in Jordan, acting as benchmarks to enhance energy efficiency and promote renewable energy use in the residential sector. Methods: Energy simulation tools were employed to design and verify zero-energy systems. The energy use intensity (EUI) results from the IDA ICE tool were compared with the reported targets and OpenStudio tool outcomes, ensuring that deviations among the proposed designs within the same climate zone consistently remained within acceptable limits, averaging 2, 1, and 1 kWh/m2 year in 1B (very hot dry), 2B (hot dry), and 3B (warm dry), respectively. Additionally, an economic evaluation was conducted by comparing the cost estimates of a Jordanian code-compliant house and the most acceptable proposed zero-energy design. Results: The proposed designs exhibited average EUI values of 64.4, 64, and 60 kWh/m2 in diverse climate zones. Outperforming typical Jordanian houses by 56%, 55%, and 60% in 1B, 2B, and 3B, respectively, these designs surpassed national and international benchmarks by at least 35%. Notably, the proposed zero-energy designs achieved substantial cost savings of 1938 USD, equivalent to 11 USD per square meter, throughout the construction phase. Conclusions: Considering Jordan's ambitious energy strategy for 2030 and the significant energy consumption in the residential sector, the proposed zero-energy building designs play a crucial role in advancing the national transition towards zero-energy buildings. This study provides valuable insights by presenting precise designs, benchmarks, and a comprehensive guide tailored to Jordan's distinctive building and climate characteristics with potential applications beyond its immediate context. [ABSTRACT FROM AUTHOR]

Physical and/or chemical changes in various module components frequently cause the electrical performance of PV modules to degrade, preventing them from operating at their peak potential. When PV producers choose the technology for their PV modules, reliability estimation of the modules is a key consideration. We never get actual PV power output as per the manufacturer's datasheet. It is simply because of degradation and some climatological parameters. So, reliability estimation is always an important task for PV scientists. In this research paper, the authors have performed a reliability analysis based on some figures of merits such as Fill Factor (FF), Efficiency, and regression analysis of different parameters. We usually do not get the actual PV power as per the manufacturer's specification, this happens the change in electrical parameters and external climatologically parameters degradation, which is a function of the internal electrical parameters or figures of merit. As a result, reliability estimation becomes a crucial duty for scientists to complete the data that may be provided to users. Since poly-Si technology for PV modules has been proven to be reliable in the eastern region, a study has been conducted in this work to evaluate the degradation by analyzing the values of various electrical parameters. The unique contribution of this research work has been that instead of other loading techniques in this research work authors have used the supercapacitor-based loading mechanisms. The primary focus of this research is on the performance assessment of poly-Si PV modules that were deployed in the Eastern Indian Climatic Zone under various environmental circumstances. [ABSTRACT FROM AUTHOR]

Warming-induced carbon loss via ecosystem respiration (Re) is probably intensifying in the alpine grassland ecosystem of the Tibetan Plateau owing to more accelerated warming and the higher temperature sensitivity of Re (Q10). However-little is known about the patterns and controlling factors of Q10 on the plateau, impeding the comprehension of the intensity of terrestrial carbon–climate feedbacks for these sensitive and vulnerable ecosystems. Here, we synthesized and analyzed multiyear observations from 14 sites to systematically compare the spatiotemporal variations of Q10 values in diverse climate zones and ecosystems, and further explore the relationships between Q10 and environmental factors. Moreover, structural equation modeling was utilized to identify the direct and indirect factors predicting Q10 values during the annual, growing, and non-growing seasons. The results indicated that the estimated Q10 values were strongly dependent on temperature, generally, with the average Q10 during different time periods increasing with air temperature and soil temperature at different measurement depths (5 cm, 10 cm, 20 cm). The Q10 values differentiated among ecosystems and climatic zones, with warming-induced Q10 declines being stronger in colder regions than elsewhere based on spatial patterns. NDVI was the most cardinal factor in predicting annual Q10 values, significantly and positively correlated with Q10. Soil temperature (Ts) was identified as the other powerful predictor for Q10, and the negative Q10–Ts relationship demonstrates a larger terrestrial carbon loss potentiality in colder than in warmer regions in response to global warming. Note that the interpretations of the effect of soil moisture on Q10 were complicated, reflected in a significant positive relationship between Q10 and soil moisture during the growing season and a strong quadratic correlation between the two during the annual and non-growing season. These findings are conducive to improving our understanding of alpine grassland ecosystem carbon–climate feedbacks under warming climates. [ABSTRACT FROM AUTHOR]

In recent decades, the annual mean temperature has increased, with unusual alternations of hot and cold years. In addition, the changes in temporal precipitation patterns are caused by complex interactions between temperature change, the global water cycle, and other components of the Earth's systems. To construct a statistical model of these temporal patterns in terms of temperature and precipitation, we propose a logistic mixture of spatial multivariate penalized regression splines for temporal profiles and apply this model to the contiguous United States climate data over 123 years (1900 to 2022) at 252 weather stations. The results reveal that the proposed model identifies climatologically meaningful clusters of weather stations in the contiguous United States with two important meteorological variables, temperature and precipitation, identifying the climate change patterns of each climate zone. The surface air temperature increased in the Northeast and West (Mountain and Pacific) regions, where the climate is affected by the continental Arctic air. A notable increment of precipitation also occurred in the Northeast. In contrast, the South region, where the climate is affected by the tropical Atlantic Ocean, is more stable than other regions in terms of year-to-year variations in temperature and precipitation. [ABSTRACT FROM AUTHOR]

The performance and durability of wood-frame building envelopes is affected by long-term moisture transport and its impact. Despite considerable progress in deterministic and prescriptive methodologies aimed at estimating moisture deposition and the consequent risk of mold growth, a consensus in methodology applicable to the analysis of moisture risk in building enclosures is an unfinished agenda. This might partly be caused by uncertainties that exist due to variations in input parameters, model structure, and data scarcity. To address this issue, this study presents a probabilistic risk assessment of building envelope deterioration from moisture accumulation. The proposed methodology integrates the development of meta-models, a full-factorial response surface methodology, and Bayesian analysis. The effectiveness of the proposed approach is demonstrated through a parametric analysis of typical wall assemblies featuring diverse layers and boundary conditions. The findings highlight the influence of input variables and their relative significance on moisture accumulation in the selected climate zones. Additionally, a sensitivity analysis of model parameters and the application of Bayesian analysis in specific contexts are presented, facilitating comparative evaluation of moisture-related risk of building envelopes. [ABSTRACT FROM AUTHOR]

Energy efficiency in the context of building design is a significant concern in Morocco. This paper offers a comprehensive analysis of how various design variables can impact both energy consumption and thermal comfort in the Moroccan context. Rather than isolating individual design variables, we investigate synergistic combinations of these variables. To achieve this, we develop multiple building design scenarios, each employing different combinations of design options, focusing on building orientation, window-to-wall ratio, building envelope construction, and window shading. We use EnergyPlus to conduct energy simulations for all scenarios under the hypothesis of air-conditioned houses and free-running houses with and without natural ventilation. Our results reveal that building design has the potential to significantly enhance energy efficiency and thermal comfort, but not for the same design strategies. In comparison to the most energy-efficient design scenario, the least favorable design scenario can lead to an increase in energy consumption between 237% in Agadir and 130% in Ifrane. Meanwhile, design scenarios favoring comfort can increase the number of comfortable hours by 85% in Agadir and 59% in Ifrane. We identify optimal building design scenarios that simultaneously offer the highest comfort levels with the lowest energy requirements. The findings provide valuable guidance for architects, allowing them to design high-performance buildings in all climate zones in Morocco. [ABSTRACT FROM AUTHOR]

Adaptive differentiation of traits and underlying loci can occur at a small geographical scale if natural selection is stronger than countervailing gene flow and drift. We investigated this hypothesis using coupled quantitative genetic and genomic approaches for a wind‐pollinated tree species, Quercus rubra, along the steep, narrow gradient of the Lake Superior coast that encompasses four USDA Hardiness Zones within 100 km. For the quantitative genetic component of this study, we examined phenotypic differentiation among eight populations in a common garden, measuring seed mass, germination, height, stem diameter, leaf number, specific leaf area and survival. For the genomic component, we quantified genetic differentiation for 26 populations from the same region using RAD‐seq. Because hybridisation with Quercus ellipsoidalis occurs in other parts of the species' range, we included two populations of this congener for comparison. In the common garden study, we found a strong signal of population differentiation that was significantly associated with at least one climate factor for nine of 10 measured traits. In contrast, we found no evidence of genomic differentiation among populations based on FST or any other measures. However, both distance‐based and genotype–environment association analyses identified loci showing the signature of selection, with one locus in common across five analyses. This locus was associated with the minimum temperature of the coldest month, a factor that defines the climate zones and was also significant in the common garden analyses. In addition, we documented introgression from Q. ellipsoidalis into Q. rubra, with rates of introgression correlated with the climate gradient. In sum, this study reveals signatures of selection at the quantitative trait and genomic level consistent with climate adaptation, a pattern that is more often documented at a much broader geographical scale, especially in long‐lived wind‐pollinated species. [ABSTRACT FROM AUTHOR]

This paper addresses the research gap concerning the impact of thermal diffusivity on cooling energy consumption in buildings, specifically in the context of Saudi Arabia's hot climate. The objective is to determine the optimal thermal diffusivity of building walls for different climate conditions in Saudi Arabia to minimize the cooling energy consumption of residential buildings. The study analyzes four locations in Saudi Arabia, namely, Riyadh, Jeddah, Abha, and Tabuk, to understand the correlation between optimal thermal diffusivity and cooling degree days. The study includes numerical modeling using the finite-difference method and developing a calibrated building energy model of an existing residential building. Sensitivity analysis is conducted to evaluate the influence of thermal conductivity and heat capacity on cooling energy consumption. Correlation analysis is performed to assess the relationship between optimal thermal diffusivity and cooling degree days. The results highlight the importance of finding a balance between thermal insulation and thermal mass for energy-efficient buildings, considering the unique climate conditions in Saudi Arabia. Finally, this study considered the development of the Saudi Energy Conservation Code (SBC-602), which provides guidelines and regulations for energy-efficient building design in Saudi Arabia by recommending the selection criteria for the optimal thermal properties of building walls while considering the outdoor climate conditions. By aligning the findings of this study with the requirements and recommendations of the SBC-602, the study aims to contribute to the effective implementation of energy-efficient strategies in building design. [ABSTRACT FROM AUTHOR]

We present a seasonal classification system to improve the temporal framing of comparative scientific analysis. Research often uses yearly aggregates to understand inherently seasonal phenomena like harvests, monsoons, and droughts. This obscures important trends across time and differences through space by including redundant data. Our classification system allows for a more targeted approach. We split global land into four principal climate zones: desert, arctic and high montane, tropical, and temperate. A cluster analysis with zone-specific variables and weighting splits each month of the year into discrete seasons based on the monthly climate. We expect the data will be able to answer global comparative analysis questions like: are global winters less icy than before? Are wildfires more frequent now in the dry season? How severe are monsoon season flooding events? This is a natural extension of the historical concept of biomes, made possible by recent advances in climate data availability and artificial intelligence. [ABSTRACT FROM AUTHOR]

The identification of aviation hazardous winds is crucial and challenging in air traffic management for assuring flight safety, particularly during the take-off and landing phases. Existing criteria are typically tailored for special wind types, and whether there exists a universal feature that can effectively detect diverse types of hazardous winds from radar/lidar observations remains as an open question. Here we propose an interpretable semi-supervised clustering paradigm to solve this problem, where the prior knowledge and probabilistic models of winds are integrated to overcome the bottleneck of scarce labels (pilot reports). Based on this paradigm, a set of high-dimensional hazard features is constructed to effectively identify the occurrence of diverse hazardous winds and assess the intensity metrics. Verification of the paradigm across various scenarios has highlighted its high adaptability to diverse input data and good generalizability to diverse geographical and climate zones. The identification of aviation hazardous winds is crucial for flight safety, especially during take-off and landing. Here, authors propose an interpretable semi-supervised clustering method to detect diverse hazardous winds from radar/lidar observations, integrating prior knowledge and probabilistic models. [ABSTRACT FROM AUTHOR]

Water vapor scale height reflects the vertical distribution of water vapor in the atmosphere, which is a vital parameter in tropospheric zenith wet delay (ZWD) modeling and GNSS meteorology. This study accurately calculated the long-term water vapor scale height using 89 radiosonde stations in China, analyzed the characteristics in temporal and spatial variations and explored the impact factors of the water vapor scale height from the perspective of the climate zones. The numerical results indicate that the water vapor scale height in China exhibits annual and semiannual variations with a rising-then-decreasing trend across the four seasons. A relatively larger value for the water vapor scale height were observed in the subtropical monsoon climate and the temperate continental climate zone, in which the values are greater than 2.35 km, while the values in temperate monsoon climate and the alpine plateau climate zone are relatively small. In addition, the water vapor scale height in different climate zones shows different trends, with a downward trend appeared in the subtropical monsoon climate and the alpine plateau climate zone, while an upward trend was observed in the temperate monsoon climate and the temperate continental climate zone. Furthermore, a positive correlation between water vapor scale height and temperature, pressure, and atmospheric precipitable water was found in China, with a varied degree of correlation in different climate zones. [ABSTRACT FROM AUTHOR]

This research addresses the issue of the heritage preventive conservation in the perspective of energy sustainability, for contributing to the achievement of the Sustainable Development Goals (SDGs) and towards the EU Green Deal. The study analyses and compares four cases associated with different microclimate thresholds as suggested by the standard EN 16893:2018 (Cases 1–3) and as derived from the outputs of three degradation models for preserving paper, wood, and canvas paintings (Case 4). Weather-based indices (degree and gram days) were calculated to estimate trends in the potential energy demand of collection facilities in three European cities belonging to different Köppen-Geiger climate zones (Cfb, Csa, and Dfb), under recent past (1981–2010) and near/far future climate scenarios (2021–2050 and 2071–2100) from two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). The findings suggest that adapting facilities' management strategies to focus on collections preservation can facilitate the achievement of 5 out of 17 SDGs, offering a viable alternative to costly energy retrofits and encouraging the development of shared solutions for similar facilities in the same climate zone. The results can contribute to inform the revision of EN 16893 and to face major challenges such as the preservation of paper collections in southern latitudes. [ABSTRACT FROM AUTHOR]

We introduce University of Texas - GLObal Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200 city or locales worldwide. UT-GLOBUS combines open-source spaceborne altimetry (ICESat-2 and GEDI) and coarse-resolution urban canopy elevation data with a machine-learning model to estimate building-level information. Validation using LiDAR data from six U.S. cities showed UT-GLOBUS-derived building heights had a root mean squared error (RMSE) of 9.1 meters. Validation of mean building heights within 1-km2 grid cells, including data from Hamburg and Sydney, resulted in an RMSE of 7.8 meters. Testing the UCPs in the urban Weather Research and Forecasting (WRF-Urban) model resulted in a significant improvement (55% in RMSE) in intra-urban air temperature representation compared to the existing table-based local climate zone approach in Houston, TX. Additionally, we demonstrated the dataset's utility for simulating heat mitigation strategies and building energy consumption using WRF-Urban, with test cases in Chicago, IL, and Austin, TX. Street-scale mean radiant temperature simulations using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, incorporating UT-GLOBUS and LiDAR-derived building heights, confirmed the dataset's effectiveness in modeling human thermal comfort in Baltimore, MD (daytime RMSE = 2.85°C). Thus, UT-GLOBUS can be used for modeling urban hazards with significant socioeconomic and biometeorological risks, enabling finer scale urban climate simulations and overcoming previous limitations due to the lack of building information. [ABSTRACT FROM AUTHOR]

Climate change and global warming in the Sahelian region cause dramatic drought and advancing of the desert. This phenomenon could affect the plant survival and community composition, but even for surviving plants, it could affect their phenology and the insect community associated with them. In a space‐for‐time approach, we studied the case of Annona senegalensis Pers. (Annonaceae), a common shrub in tropical areas, to determine the impact of climate change on its phenology and the insects associated with its flowers and fruits. We determined the phenology phases of Annona senegalensis during a 1‐year period and assessed the abundance and diversity of insects in the Sudanian and the Sudano‐Sahelian climatic zones of Burkina Faso. Temperature, rainfall and relative humidity were recorded during 12 months in two sites per zone. Leafing of Annona senegalensis lasted 10 months in the Sudanian zone, flowering and fruiting were 3 months long. In the Sudano‐Sahelian zone, leafing lasted 8 months while flowering and fruiting were 3 and 4 months long, respectively. A total of 10,040 insects belonging to 48 species were collected in the two climatic zones. Forty‐six species were found in the Sudanian zone while 25 species were recorded in the Sudano‐Sahelian one. The variations in the plant phenology and the insect community were mainly due to the variation in rainfall across both climatic zones. Our results emphasize that advancing of the desert due to climate change could not only affect the survival of plants but for resistant species it also affect their interactions with insects and the whole insect community associated. [ABSTRACT FROM AUTHOR]

Accurate streamflow prediction is significant for water resources management. However, due to the impact of climate change and human activities, accurately identifying the input factors of the streamflow prediction model and achieving high-precision results presents a significant challenge. In this study, past streamflow, meteorological, and climate factors were utilized as inputs to develop a predictive scenario for the bi-decomposition of input factors and streamflow series, i.e. Scenario 3 (S3). Mutual information (MI) was applied to recognize the input factors prediction potential. Based on the predictive potentials, factors were progressively incorporated into the kernel extreme learning machine (KELM) and hybrid kernel extreme learning machine (HKELM) models optimized by the gazelle optimization algorithm (GOA) to ascertain the optimal input configuration for each sub-series. The prediction results of S3-KELM and S3-HKELM models were obtained by reconstructing the optimal prediction results of each sub-series. The monthly streamflow of the upper Fenhe River Basin, which is in the semi-humid and semi-arid climate zone, was selected as a case study. The results indicate that in comparison to both undecomposed and singly decomposed scenarios, the input–output bi-decomposed scenario more accurately identifies the input factors and constructs high-precision prediction models. The Nash–Sutcliffe efficiency (NSE) of both the S3-KELM and S3-HKELM models exceeds 0.85. Specifically, the S3-HKELM model demonstrates superior performance, capable of handling more complex inputs, with its NSE reaching up to 0.93. Importantly, meteorological and climate factors contribute to the accuracy of streamflow predictions across different scenarios. [ABSTRACT FROM AUTHOR]

Precise estimation of daily reference crop evapotranspiration (ET0) is critical for water resource management and agricultural irrigation optimization worldwide. In China, diverse climatic zones pose challenges for accurate ET0 prediction. Here, we evaluate the performance of a support vector machine (SVM) and its hybrid models, PSO-SVM and WOA-SVM, utilizing meteorological data spanning 1960–2020. Our study aims to identify a high-precision, low-input ET0 estimation tool. The findings indicate that the hybrid models, particularly WOA-SVM, demonstrated superior accuracy with R2 values ranging from 0.973 to 0.999 and RMSE values between 0.123 and 0.863 mm/d, outperforming the standalone SVM model with R2 values of 0.955 to 0.989 and RMSE values of 0.168 to 0.982 mm/d. The standalone SVM model showed relatively lower accuracy with R2 values of 0.822 to 0.887 and RMSE values of 0.381 to 1.951 mm/d. Notably, the WOA-SVM model, with R2 values of 0.990 to 0.992 and RMSE values of 0.092 to 0.160 mm/d, emerged as the top performer, showcasing the benefits of the whale optimization algorithm in enhancing SVM's predictive capabilities. The PSO-SVM model also presented improved performance, especially in the temperate continental zone (TCZ), subtropical monsoon region (SMZ), and temperate monsoon zone (TMZ), when using limited meteorological data as the input. The study concludes that the WOA-SVM model is a promising tool for high-precision daily ET0 estimation with fewer meteorological parameters across the different climatic zones of China. [ABSTRACT FROM AUTHOR]

The Huaihe River basin (HRB) of China located in the climate transition zone between warm temperate and subtropical areas is highly sensitive to climatic change. However, the changes in future climate extreme events under anthropogenic warming and the population exposure to these climate extremes in HRB remain unexplored. Here, using the eight commonly used extreme climate indices and based on the bias‐corrections of 16 global climate models (GCMs) in CMIP6, we present a projection and uncertainty analysis of extreme events and investigate the corresponding population exposure risk in HRB under three shared socioeconomic pathways (SSP1‐2.6, SSP2‐4.5, SSP5‐8.5). The 16‐GCM ensemble mean projects an evident warming trend under all three scenarios with a total increase of 25.6–68.0 days in summer days (>25°C) by the end of the century in HRB. Larger increases (decreases) in maximum and minimum temperatures (frost days) are projected in the western HRB. Very heavy rain days (R20mm), maximum 5‐day precipitation (RX5day) and simple daily intensity index (SDII) will experience intensification across most of HRB (especially in southern and western HRB). The consecutive dry days is projected to decrease in northwestern HRB and increase in southern HRB. However, there is a large spatial variability in GCM uncertainty with a higher SSP scenario generally having higher uncertainty. Increases in summer days and R20mm exacerbate population exposure in HRB in near future (2030–2059), but in far future (2070–2099) although summer days (R20mm) continues to rise, population exposure is expected to decrease due to the rapid decline in population density. [ABSTRACT FROM AUTHOR]

Assessing anthropogenic climate change in a regional context is challenging due to the spatial heterogeneity of climatic variables and is more complicated than at the global scale. Especially in the Tropics, such spatial variations are expected to increase, warranting the identification of homogeneous climatic zones for assessing regional climate change. The present study explores the ability of bioclimatic variables in defining regional climatic zones, and the detection of climate change therein. We hypothesize that the identification of homogeneous climatic zones based on bioclimatic variables could be an effective approach rather than the conventional extreme climate‐based indices to identify climate change signals. To demonstrate the hypothesis, bioclimatic variables representing the generalized climatic characteristics of a tropical river basin were derived from observed gridded datasets of rainfall and temperature. Clusters of homogeneous climatic zones were identified, and their temporal variations were analysed to examine the existence of climate change. The results indicate that despite the spatial heterogeneity in extreme climate‐based indices, the bioclimatic variables‐based approach renders a meaningful representation of the regional climatic pattern. Investigation of bioclimatic zones of the study area helped to identify a shift in its climatic zones with a slant towards drier conditions. Further, future changes in climatic zones were identified from 13 different GCMs that participated in the CMIP6, projecting drier conditions over the basin, with varying spatial extend based on future emission scenarios. The study significantly contributes towards the identification of climatologically fragile regions in changing climate, which is an essential component in developing any regional climate change adaptation and mitigation strategy. [ABSTRACT FROM AUTHOR]

Greenhouse agriculture is expected to play a critical role in sustainable crop production in the coming decades, opening new markets in climate zones that have been traditionally unproductive for agriculture. Extreme hot and humid conditions, prevalent in rapidly growing economies including the Arabian Peninsula, present unique design and operational challenges to effective greenhouse climate control. These challenges are often poorly understood by local operators and inadequately researched in the literature. This study addresses this knowledge gap by presenting, for the first time, a comprehensive set of benchmarks for water and energy usage, CO 2 emissions (CO 2 e) contribution, and economic performance for low-, mid-, and high-tech greenhouse designs in such climates. Utilising a practical and adaptable model-based framework, the analysis reveals the high-tech design generated the best results for economic return, achieving a 4.9-year payback period with superior water efficiency compared to 5.8 years for low-tech and 7.0 years for mid-tech; however, the high-tech design used significantly more energy to operate its mechanical cooling system, corresponding with higher CO 2 e per unit area (8.3 and 4.0 times higher than the low- and mid-tech, respectively). These benchmarks provide new insights for greenhouse operators, researchers, and other stakeholders, facilitating the development of effective greenhouse design and operational strategies tailored to meet the challenges of hot and humid climates. • First comprehensive benchmarks for greenhouse performance in hot humid climates. • Practical model-based framework assesses greenhouses of various tech-levels. • Existing greenhouse tech with optimisations is economically viable in coastal Arabia. • Inefficient evaporative cooling and high CAPEX make mid-tech worst investment. • High-tech shows best payback period and water efficiency but worst CO 2 impact. [ABSTRACT FROM AUTHOR]

How species thrive in a wide range of environments is a major focus of evolutionary biology. For many species, limited genetic diversity or gene flow among habitats means that phenotypic plasticity must play an important role in their capacity to tolerate environmental heterogeneity and to colonize new habitats. However, we have a limited understanding of the molecular components that govern plasticity in ecologically relevant phenotypes. We examined this hypothesis in a spider species (Stegodyphus dumicola) with extremely low species-wide genetic diversity that nevertheless occupies a broad range of thermal environments. We determined phenotypic responses to temperature stress in individuals from four climatic zones using common garden acclimation experiments to disentangle phenotypic plasticity from genetic adaptations. Simultaneously, we created data sets on multiple molecular modalities: the genome, the transcriptome, the methylome, the metabolome, and the bacterial microbiome to determine associations with phenotypic responses. Analyses of phenotypic and molecular associations reveal that acclimation responses in the transcriptome and metabolome correlate with patterns of phenotypic plasticity in temperature tolerance. Surprisingly, genes whose expression seemed to be involved in plasticity in temperature tolerance were generally highly methylated contradicting the idea that DNA methylation stabilizes gene expression. This suggests that the function of DNA methylation in invertebrates varies not only among species but also among genes. The bacterial microbiome was stable across the acclimation period; combined with our previous demonstrations that the microbiome is temporally stable in wild populations, this is convincing evidence that the microbiome does not facilitate plasticity in temperature tolerance. Our results suggest that population-specific variation in temperature tolerance among acclimation temperatures appears to result from the evolution of plasticity in mainly gene expression. [ABSTRACT FROM AUTHOR]

Climate change leads to changes in climatic variables, with rainfall being one of them. Changes in rainfall influence rainfall erosivity and subsequently erosion rates. This study analysed rainfall data from 1901 to 2017 in Odisha, focusing on different agro-climatic zones to discern annual rainfall pattern, its spatial variation, and trend, particularly concerning the rainfall erosivity factor and its impact on soil erosion and agricultural productivity. Notably, the Eastern Ghats Highland region received the highest average annual rainfall of 1578.5 mm, while the Western Undulating Zone received the lowest (1308.4 mm). The rainfall distribution showed spatial variability largely influenced by topography, with areas experiencing orographic lifting receiving higher rainfall. The study observed significant trend in annual rainfall, noting a maximum decline of 1.2 mm yr−1 in the North Western Plateau, Western Central Table Land, and Western Undulating Zone, whereas the East and South Eastern Plain, Mid Central Table Land, North Eastern Coastal Plain, North Eastern Ghats, and South Eastern Ghats exhibited a noteworthy increase in annual rainfall (0 to 3.9 mm yr−1). The decline in rainfall can result in the drying up of water bodies and reduced soil water availability to crop, thereby influencing agricultural production. On the other hand, areas with increased rainfall, may face extreme events which can aggravate soil erosion and thereby loss of soil fertility. Considering the scarcity of pluviographic data in countries like India, Modified Fournier Index (MFI) may be considered as one of the useful methods to capture rainfall's aggressiveness towards soil erosion through rainfall erosivity (R-factor). Therefore, to evaluate potential soil erosion levels, the Modified Fournier Index method was employed, revealing varying degrees of soil erosiveness across different regions. The Eastern Ghats Highlands exhibited the highest erosion potential. The R-factor, aligned with these spatial patterns, with the Eastern Ghats Highland (12,965.4 MJ mm ha−1 h−1 yr−1) and South Eastern Ghats (12,242.3 MJ mm ha−1 h−1 yr−1) regions displaying the highest R-factor values. Furthermore, the research identified areas prone to soil erosion by overlaying R-factor, slope, and land use maps, highlighting vulnerable regions such as Eastern Ghats Highlands, North Eastern Ghats, South Eastern Ghats, and Western Undulating Zone. This comprehensive analysis allows for informed prioritization of conservation efforts and the implementation of appropriate measures like strip cropping of finger millet with groundnut, intercropping finger millet with hedgerows of Gliricidia and Leucaena, bio-engineering measures such as earthen or stone bunds with broom grass in arable land and growing of aromatic grasses like lemon and citronella grass, construction of staggered trenches in non-arable land to mitigate erosion in these susceptible areas. [ABSTRACT FROM AUTHOR]

An updated phylogenomic tree of the Nudiviridae is presented, including 49 species, proposing two genera associated with ectoparasitic insects. Evolution of the family Nudiviridae is estimated to have occurred in the mid-Devonian, matching the timeline of the insect's evolution. All the crustacean-infecting nudiviruses have likely emerged from a single common ancestor (~143 million years ago), perhaps transmitted to Jurassic crustaceans by an insect host. The Nudiviridae have a proclivity for ectoparasitic arthropods (i.e., lice and fleas), linked to multiple diversification events in the Triassic (early Betanudivirinae split), Jurassic (involving ectoparasitic hosts of alphanudiviruses), and Cretaceous periods (Zeta/Etanudivirus diversification). Nudiviruses inhabit various geographical and climatic zones, including members from subpolar habitats. The nudiviruses (family: Nudiviridae) are large double-stranded DNA (dsDNA) viruses that infect insects and crustaceans, and have most recently been identified from ectoparasitic members (fleas and lice). This virus family was created in 2014 and has since been expanded via the discovery of multiple novel viral candidates or accepted members, sparking the need for a new taxonomic and evolutionary overview. Using current information (including data from public databases), we construct a new comprehensive phylogeny, encompassing 49 different nudiviruses. We use this novel phylogeny to propose a new taxonomic structure of the Nudiviridae by suggesting two new viral genera (Zetanudivirus and Etanudivirus), from ectoparasitic lice. We detail novel emerging relationships between nudiviruses and their hosts, considering their evolutionary history and ecological role. [ABSTRACT FROM AUTHOR]

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

This document discusses the importance of conserving and managing marine benthic ecosystems, which provide essential resources and services. It emphasizes the need for ecosystem-based strategies in the face of challenges like global warming and invasive species. The document presents several studies that deepen our understanding of the ecology and biogeography of marine benthos, including investigations into specific regions and the effects of different factors on benthic communities. The document also highlights the importance of identifying species within these ecosystems and the use of DNA barcoding for ecological research and conservation efforts. The special issue includes a variety of research articles and reports that cover different marine ecosystems and utilize various research methods. The findings contribute to our understanding of marine ecology and biogeography, supporting conservation and management efforts. The summary also emphasizes the need for future studies to be more cost-effective and innovative in data collection and analysis. [Extracted from the article]

Numerous new records of Ferganiella, Podozamites, and Schidolepium, including a new species, Ferganiella ivantsovii sp. nov., are described from the Early Jurassic (Toarcian) Middle Subformation of the Prisayan Formation from the Euro‐Sinian paleofloristic region in the Irkutsk Basin, Eastern Siberia, Russia. An analysis of the paleogeographic distribution of Ferganiella and Podozamites shows that both genera were the most diverse and numerous in the East Asian province of the Euro‐Sinian region and in the Northern Chinese province of the Siberian region during the Early and Middle Jurassic. These phytochoria were located in the subtropical and temperate subtropical climate zones, which allows us to consider Ferganiella and Podozamites as thermophilic plants, which are important indicators of the Early Toarcian climatic optimum. Their abundance in the Irkutsk Basin thus may indicate Early Toarcian warming; further abundant Schidolepium cones, which produced Araucariacites pollen, typical for Euro‐Sinian flora complement the scenario. Thus, the new finds are the first macrofloristic indicators of the Toarcian climatic optimum in the Irkutsk Basin. [ABSTRACT FROM AUTHOR]

Urbanization is an important process in China's urban development, significantly contributing to resource allocation and the cooperative development of neighboring cities. In recent years, remote-sensing technology has emerged as a powerful tool in urbanization research. However, the disparity in development between urban and rural areas poses challenges in evaluating the degree of urbanization within a region. This paper addresses this issue by using LCZ (Local Climate Zone) data to provide a unified framework for analyzing a human settlement environmental geographic dataset. This study focuses on the spatial development and transformation of the Guangzhou–Foshan urbanization from 2000 to 2020. The LCZ data offer a suitable framework for examining urban–rural gradients, facilitating the analysis of spatial characteristics under varying development conditions. This unified framework enables a comprehensive analysis of the spatiotemporal characteristics of urban spatial integration. The results show that the analysis of the Guangzhou–Foshan metropolitan area reveals that the region has maintained a "core–edge" spatial structure over the past 20 years. The development rate has decelerated following policy changes in 2010, with the adjacent area experiencing significantly slower development compared to the overall study area. LCZ data are effective for comparative analysis of internal spatial development within urban areas, offering a novel approach to studying spatial integration amid urban development. [ABSTRACT FROM AUTHOR]

Stauroneis (Naviculales, Bacillariaceae) are widespread, mostly in fresh-water habitats, and account for 343 species. They are described mainly on the basis of morphology and morphometric traits. These characteristics vary during life cycles and may overlap between species, making their identification difficult. We isolated two strains of naviculoid diatoms and examined them using an integrative approach (phylogenetic, morphological, ultrastructural data, and life cycle). Phylogenetic analyses based on chloroplast rbcL gene data showed affinity of the new strains to the genus Stauroneis. Our algae share morphological features typical of Stauroneis but differ from similar species in minimal valve length measurements, valve apex shape, and minimal number of striae in 10 μm. Two strains are distinct from each other in maximal valve length and width, partially valve shape, the number of areolae in 10 μm, and cingulum structure. It was revealed that the strains reproduce via isogamy. Three species delimitation methods (ASAP, PTP, and GMYC) also confirmed that the two closely related new strains represent distinct species. Based on molecular data and phenotypic traits examined within the framework of an integrative approach, we describe two new isolates as Stauroneis urbani sp. nov. and Stauroneis edaphica sp. nov. [ABSTRACT FROM AUTHOR]

Assessing the daily water requirements of crops and understanding the severity of drought necessitates precise estimation of potential evapotranspiration (PET), particularly in regions with arid climates such as Egypt. In the present study, the RegCM4 regional climate model was used to investigate the sensitivity of the PET of Egypt to two land surface schemes and boundary layer parameterizations. The land surface schemes are the Biosphere Atmosphere Transfer System (BATS) and the Community Land Model version 4.5 (CLM45). The boundary layer schemes considered are the HOLTSLAG (HOLT) and University of Washington (UW). To accomplish this task, four 32-year simulations were conducted spanning from 1979 to 2010, with the first two years considered as spin up. The ERA-Interim reanalysis was used to downscale the RegCM4 model. The simulated PET was evaluated with respect to the high-resolution ERA5-land PET-based product (hPET). The results showed that the BATS showed a bias of −0.8 to −1.8 mm day−1, while the CLM45 showed a bias of −0.8 to −3 mm day−1. Also, fine-tuning the coefficient of the daily mean air temperature succeeded in reducing the PET bias. Additionally, the UW had a lower PET bias than that noted in HOLT. To further reduce the PET bias, the linear-scaling (LS) bias-correction method was used. The LS showed its potential skills in reducing the mean bias of the PET from −2.2 to +0.4 mm day−1 in the evaluation period and to ±0.2 mm day−1 in the validation period. Furthermore, the added value of the LS was confirmed concerning the climatological annual cycle in different locations representing different climate zones of Egypt. In conclusion, accurate estimation of the PET can be ensured using the BATS, the UW schemes, and the LS technique in the present climate or under different warming scenarios. [ABSTRACT FROM AUTHOR]

The Huaihe River basin is located in eastern and central China and in a climate transition zone. Its unique geographical location and climatic conditions have led to increases in flood waterlogging damage in the basin. The impact of climate change on water resources in the basin and the adaptability of these resources to these changes deserve attention. To achieve the objectives of climate resilient development, society and ecosystems must transform into a more resilient state. This dynamic process includes two stages: adaptation and resilience. In this study, elements of social resilience were integrated into adaptability analyses. Three aspects of the adaptation mechanism of water resource system are discussed: natural resilience, artificial adaptation, and social resilience. An index system that conforms to the process mechanism of water resource system adaptability was constructed. The fuzzy analytic hierarchy process was used to identify and analyse indexes of natural resilience, artificial adaptation and social resilience. Based on the adaptation mechanism of the water resource system and the original two-dimensional risk matrix, a method combining the connection number and three-dimensional risk matrix was established. In addition, a risk element combination table of a three-dimensional risk matrix and its chromatograms was obtained. Finally, an empirical study was conducted using the Huaihe River basin in Anhui Province, China, as an example. The results indicated that the adaptability level of the upper region of the Huaihe River basin in Anhui is higher than that of the lower region, and the adaptability level of the southern part is higher than that of the northern part. To improve the adaptability of water resource system in the lower and northern regions, targeted, evidence-based measures for strengthening water resource management in the Huaihe River basin are needed. [ABSTRACT FROM AUTHOR]

Temperature and water stress are important factors limiting the gross primary productivity (GPP) in terrestrial ecosystems, yet the extent of their influence across ecosystems remains uncertain. This study examines how surface air temperature, soil water availability (SWA) and vapor pressure deficit (VPD) influence ecosystem light use efficiency (LUE), a critical metric for assessing GPP, across different ecosystems and climatic zones at 80 flux tower sites based on in situ measurements and data assimilation products. Results indicate that LUE increases with temperature in spring, with higher correlation coefficients in colder regions (0.79–0.82) than in warmer regions (0.68–0.78). LUE reaches a plateau earlier in the season in warmer regions. LUE variations in summer are mainly driven by SWA, exhibiting a positive correlation indicative of a water‐limited regime. The relationship between the daily LUE and daytime temperature shows a clear seasonal hysteresis at many sites, with a higher LUE in spring than in fall under the same temperature, likely resulting from younger leaves being more efficient in photosynthesis. Drought stress influences LUE through SWA in all ranges of water availability; VPD variation under moderate conditions does not have a clear influence on LUE, but extremely high VPD (exceeding the threshold of 1.6 kPa, often observed during extreme drought‐heat events) causes a dramatic reduction of LUE. Our findings provide insight into how ecosystem productivities respond to climate variability and how they may change under the influence of more frequent and severe heat and drought events projected for the future. Plain Language Summary: The terrestrial ecosystem assimilates carbon through photosynthesis, and its ability to convert sunlight energy to primary production during photosynthesis is commonly measured by light use efficiency (LUE). To understand how temperature, water in the soil, and atmospheric aridity impact carbon assimilation through photosynthesis, we analyzed the drivers of LUE at 80 sites across different ecosystems and different climate regimes in the United States. We found that temperature is the main factor influencing LUE of grassland and forest in spring, and has a greater influence on LUE in colder regions than in warmer regions. Under the same temperature, LUE in the spring is higher than in the autumn season, likely because of new leaves. In summer, deep soil water availability is the primary driver of LUE variations. In addition, extreme aridity of the atmosphere contributes to a dramatic decrease in LUE during compound heat‐drought events. Our findings contribute to advancing our understanding of how climatic factors influence LUE across different ecosystems in a changing climate. Key Points: Light use efficiency (LUE) variation is generally driven by temperature in spring and by water stress in summerSoil water availability dominates the LUE response to moderate droughts, but vapor pressure deficit becomes important under extreme droughtThe primary drivers of LUE variation also depend on background climate and vegetation types [ABSTRACT FROM AUTHOR]

Wheat and barley yields in Japan are considerably lower than those in the UK, even where similar Climate Zones (CZs) of relatively cold and humid nature are shared. In order to understand this difference, it is first necessary to find out if any common climate–yield relationship exists between the two countries. The Climate Zonation Scheme (CZS) developed in the Global Yield Gap Atlas (GYGA) was used to analyse actual yield (Ya) with three climatic factors of the GYGA-CZS, i.e., growing degree days (GDD), aridity index (AI) and temperature seasonality (TS). A significant relationship was found between AI scores and Ya values across the two countries. Ya values decreased with an increase in AI scores; in other words, lower yields are associated with higher AI scores. In addition, the degree of yield reduction with the rise in AI scores was greater in Japan than in the UK. The present study also proposed a novel method to link CZs of the GYGA-CZS to regional classification units, especially for countries where statistical crop yield data are available only at a coarse scale. [ABSTRACT FROM AUTHOR]

The ice phenomena are an inherent component of rivers in temperate, continental, and polar climate zones. Evident progress in global warming leads to a decrease in snow cover on land and ice phenomena in water bodies, disrupting the stability of the hydrological cycle and aquatic ecosystems. Although common observations indicate the disappearance of ice phenomena in rivers over recent decades, detailed quantitative research is lacking in many regions, especially in the temperate zone. In this paper, ice phenomena were analyzed on the rivers of southern Poland, located in the upland and mountain areas of the country, as no such studies have been conducted so far. The temporal changes in the annual number of days with ice (NDI) phenomena were studied in locations where ice phenomena were observed every year for at least 30 years between 1951 and 2021. Using straightforward but commonly accepted procedures, such as the Mann-Kendall test, statistically significant decreasing trends in the annual NDI were revealed for the majority of gauging stations. The Theil-Sen (TS) slope mean values were -1.66 (ranging from -3.72 to -0.56), -1.41 (from -3.22 to -0.29), and -1.33 (from -2.85 to -0.29) for the datasets representing the periods 1992–2020, 1987–2020, and 1982–2020, respectively. The results for the annual NDI were additionally presented within the context of meteorological characteristics such as annual and winter (Nov-Apr) air temperature, precipitation, and water temperature. Correlation and regression analyses revealed that the main factor triggering the decrease in NDI is the increase in the average winter air temperature. An increase in temperature by 1°C results in a decrease in NDI by up to twenty days. If these negative trends continue, ice phenomena may disappear completely from southern Polish rivers within few decades. [ABSTRACT FROM AUTHOR]

Background: Southeast Asia is regarded as a hotspot for the diversity of ixodid ticks. In this geographical region, Vietnam extends through both temperate and tropical climate zones and therefore has a broad range of tick habitats. However, molecular-phylogenetic studies on ixodid tick species have not been reported from this country. Methods: In this study, 1788 ixodid ticks were collected from cattle, buffalos and a dog at 10 locations in three provinces of northern Vietnam. Tick species were identified morphologically, and representative specimens were molecularly analyzed based on the cytochrome c oxidase subunit I (cox1) and 16S rRNA genes. Fifty-nine tick species that are indigenous in Vietnam were also reviewed in the context of their typical hosts in the region. Results: Most ticks removed from cattle and buffalos were identified as Rhipicephalus microplus, including all developmental stages. Larvae and nymphs were found between January and July but adults until December. Further species identified from cattle were Rhipicephalus linnaei, Rhipicephalus haemaphysaloides, Amblyomma integrum and Haemaphysalis cornigera. Interestingly, the latter three species were represented only by adults, collected in one province: Son La. The dog was infested with nymphs and adults of R. linnaei in July. Phylogenetically, R. microplus from Vietnam belonged to clade A of this species, and R. haemaphysaloides clustered separately from ticks identified under this name in China, Taiwan and Pakistan. Amblyomma integrum from Vietnam belonged to the phylogenetic group of haplotypes of an Amblyomma sp. reported from Myanmar. The separate clustering of H. cornigera from Haemaphysalis shimoga received moderate support. Conclusions: Three tick species (R. linnaei, A. integrum and H. cornigera) are reported here for the first time in Vietnam, thus increasing the number of indigenous tick species to 62. Clade A of R. microplus and at least R. linnaei from the group of Rhipicephalus sanguineus sensu lato occur in the country. There is multiple phylogenetic evidence that different species might exist among the ticks that are reported under the name R. haemaphysaloides in South and East Asia. This is the first report of A. integrum in Southeastern Asia. [ABSTRACT FROM AUTHOR]

Ventilation significantly impacts energy consumption in ultra-low-energy buildings (ULEBs). However, in Chinese residential kitchens, the influence of mechanical ventilation formed by range hoods and make-up air systems on energy consumption has received limited attention. This study assesses the heating and cooling demands in ULEBs resulting from kitchen make-up air across different climate zones in China. The results reveal that in natural make-up air mode, there is a substantial rise in annual heating demand in cold and severe cold zones and a notable increase in annual cooling demand in hot summer and warm winter as well as hot summer and cold winter zones. Additionally, the natural make-up air mode often poses challenges in maintaining a satisfactory thermal environment in kitchens during both heating and cooling seasons. Conversely, the mechanical make-up air mode, especially with pretreatment of outdoor air to ensure thermal comfort in kitchens, significantly elevates both annual heating and cooling demands, making it hard for the building to meet the ULEB specifications, particularly in cold and severe cold zones. Furthermore, despite a generally small increase in annual cooling demand, the percentage rise in heating demand often exceeds the ULEB limits, ranging from 12.0% to 36.0%, depending on the climate zone. [ABSTRACT FROM AUTHOR]

Tsunami deposits provide evidence of historical and prehistorical events. However, their preservation in tropical regions is generally poor. The reasons behind this poor preservation are often linked to a number of environmental and anthropogenic factors. This study is focused on analyzing the environmental factors that impact the preservation and availability of tsunami deposits specifically in tropical regions. These factors predominantly encompass climate-related elements such as consistently high temperatures, rainfall, humidity, as well as specific soil processes, oceanic conditions, and vegetation. We compiled a comprehensive database of scientific publications on tsunami deposits, identifying the geomorphic environments where such deposits are typically preserved, as well as the commonly utilized proxies in studying tsunami deposits across different climatic zones. We propose a model that outlines the environmental factors, processes, and their interrelationships that contribute to the preservation and availability of tsunami deposits in tropical regions. This model may prove valuable in the future identification of tsunami deposits in tropical areas. [ABSTRACT FROM AUTHOR]

The Asian tiger mosquito, Aedes albopictus (Skuse) (Diptera: Culicidae), is a global vector of dengue, chikungunya and zika viruses. With extreme adaptability of survival as diapause eggs, this mosquito has invaded and established in temperate climatic zones. The diapause eggs are specially programmed to overcome the harsh winter conditions in temperate habitats. In the laboratory, diapausing females are reared from early larval instars under short‐day conditions (21°C and 16D:8 L photoperiods). Aedes albopictus is normally fed on Guinea pigs for the rearing of diapause mosquitoes which requires ethical approval from the animal use committee and costly arrangements. Therefore, the present study was conducted to find whether bovine serum albumin protein (10%) with sucrose (5%) solution (SAP‐10) offered through a membrane‐free feeding system would result in an alternative diet for the production of diapause eggs in comparison to blood‐feeding. This feeding system shows a considerable rate of engorgement of diapausing females under short‐day conditions and produced 30.8 diapause eggs/female in comparison to blood‐feeding on a guinea pig (40.9 eggs/female). The diapause rate of viable eggs for the SAP‐10 diet (95.28%) was similar to the blood‐feeding (96.32%). The findings suggest that the present diet feeding system is a promising tool for the rearing of diapause Ae. albopictus mosquitoes under short‐day conditions. Further studies are suggested to evaluate the physiological and developmental aspects of mosquitoes reared on the diet. [ABSTRACT FROM AUTHOR]

The aim of the experiment was to determine the yield of Miscanthus × giganteus M 19 in the first three years of cultivation and its bioaccumulation of Zn and Ni in aboveground and underground parts in response to different doses of sewage sludge and substrate left after the production of white mushrooms. Miscanthus × giganteus is a grass species that adapts to different environmental conditions and can be grown in various climatic zones of Europe and North America. In April 2018 the experiment was established in a randomized block design and with four replications in central-eastern Poland. Waste organic materials (municipal sewage sludge and mushroom substrate) were applied to the soil in 2018 in the spring before the rhizomes of giant miscanthus were planted. Each year (from 2018 to 2020) biomass was harvested in December. The yield of fresh and dry matter and the total content of Zn and Ni, after wet mineralization of plant samples, were determined by optical emission spectrometry (ICP-OES). After the third year of cultivation, the content of Zn and Ni in rhizomes and in the soil was determined again. In relation to control, an increase in the yield of miscanthus biomass in response to organic waste materials was noted. Plants responded to mushroom substrate (SMS) with the highest average yield (16.89 Mgha−1DM), while on the control plot it was 13.86 Mg ha−1DM. After the third year of cultivation, rhizomes of Miscanthus x giganteus contained higher amounts of Zn (63.3 mg kg−1) and Ni (7.54 mg kg−1) than aboveground parts (40.52 and 2.07 mg kg–1), which indicated that heavy metals were retained in underground parts. [ABSTRACT FROM AUTHOR]

We present a methodology designed to study the spatial heterogeneity of climate change. Our approach involves decomposing the observed changes in temperature patterns into multiple trend, cycle, and seasonal components within a spatio-temporal model. We apply this method to test the hypothesis of a global long-term temperature trend against multiple trends in distinct biomes. Applying this methodology, we delve into the examination of heterogeneity of climate change in Brazil—a country characterized by a spectrum of climate zones. The findings challenge the notion of a global trend, revealing the presence of distinct trends in warming effects, and more accelerated trends for the Amazon and Cerrado biomes, indicating a composition between global warming and deforestation in determining changes in permanent temperature patterns. [ABSTRACT FROM AUTHOR]

To address the United Nation's sustainable development goal of clean energy, new concepts are required to utilize renewable energy efficiently in buildings. One of the barriers against building-integrated solar thermal systems is the diluted outlet temperatures in winter, corresponding to large demand magnitudes. This study proposes a new design of an integrated and double-insulated active heating wall system, comprising an unglazed solar collector and a low-temperature radiant heating terminal. A hybrid resolution quasi-dynamic finite element model is developed, validated, and then used to test the system performance in a typical cold climate zone. The results suggest achievable daylight average heating capacities up to 60.82 W m−2 and demonstrate a passive heating effect during nighttime hours when the water circulation is disabled. At low flow rates of ~ 0.03 kg s−1, the pumping power is discardable, and the energy performance index reaches 3.1 × 105. The performance of the system is especially enhanced during days with mildly cold temperatures and partially cloudy skies, as well as when the indoor setpoint temperature is reduced. Besides, the integrated wall remarkably reverses the heat transfer direction and offsets thermal losses (up to ~ 21.2 W m−2) during nighttime hours, compared to a plain wall. The cost savings of the system are approximately 16.97 EUR m−2, with a payback period of 5.53 years. [ABSTRACT FROM AUTHOR]

The evaluation of natural ventilation potential for effective sustainable options and innovative green building design strategies is of great interest to architects, researchers and governments. From a retrospective review, we found that the potential evaluation of natural ventilation (NV) cooling effectiveness in the same category based on similar meteorological uncertainty, research objectives and objects showed significant differences. Uncertainties added and uncertainty propagation (both model form uncertainties and parameter uncertainties) could result in large discrepancies between simulation outcomes and real scenarios, especially in the design performance modeling (DPM) phase. In this conceptual design stage, a few parameters are available and therefore decisive. It is necessary to review and identify the key performance indicators and explore the extent to which deviations are caused by inconsistencies or biases in model information. As a basis for more concrete research, we propose statistical tests based on quantitative evaluations to explore the rule of natural ventilation potential volatility and identify whether there is a significant potential improvement resulting from the critical parameter enhancement with the optimal relationship. The showcase is applied in China, where there has been a significant amount of criticism regarding the current building climate zoning due to the perceived coarseness of the system and where there has been an active exploration into the possibility of redefining building climate zoning with a view toward improving its accuracy and effectiveness. [ABSTRACT FROM AUTHOR]

Understanding drought occurrence and evolution is important in minimizing the impacts associated with it. This work assesses the performance of 10 commonly used meteorological indices to measure drought in Morocco. The studied indices are Deciles Index (DI), Percent of Normal Index (PNI), Z‐Score Index (ZSI), China‐Z Index (CZI), Rainfall Anomaly Index (RAI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), its self‐calibrated variant (scPDSI) and Palmer Z Index (PZI). Rainfall and temperature gridded data is sourced from PERSIANN‐CDR and ERA5, respectively, for the period 1983–2021. The study area exhibits three main climatic regimes; subhumid, semi‐arid and arid, with a drying and warming climate, as depicted by the rainfall and temperature trends analysis. Results show that most rainfall‐based indices perform relatively poorly in drought monitoring in the study area. DI and PNI appear to be inconsistent and abnormally responsive to rainfall. RAI reports droughts 56.5% more frequently and slightly underestimate drought intensity compared to other indices. Similarly, ZSI and CZI largely underestimate drought intensity. PDSI and scPDSI are computationally demanding, often underestimate drought intensity and overestimate drought duration by at least 115% compared to SPI and SPEI. Conversely, PZI can be used for drought onset detection as it reported droughts early compared to the other indices. SPI and SPEI perform overall better regarding their consistent drought identification and severity assessment. However, SPEI is found to be more suitable than SPI in the arid and semi‐arid regions and performed better considering the warming climate of the country. [ABSTRACT FROM AUTHOR]