Precipitation Temperature Research Articles

Modeling the impacts of extreme climate scenarios on soil acidity (pH and exchangeable aluminum) in Abbay River Basin, Ethiopia

The Abbay River Basin faces the looming threat of extreme climate events, including prolonged droughts and erratic rainfall patterns, which can significantly affect soil health and fertility. This study aimed to explore the influence of extreme climate conditions on soil pH and exchangeable aluminum, aiming to promote sustainable agricultural practices in Ethiopia. The Africa Soil Information Service (ASIS) provided datasets on soil pH and exchangeable aluminum. The European Copernicus Climate Change Data Store was used to download historical and future datasets of extreme climatic indices from 1980 to 2010 and 2015–2050, respectively. The Coupled Model Intercomparison Project Phase 6 model ensemble was used to predict future climate impacts under three shared socioeconomic scenarios: SSP1-2.6, SSP2-4.3, and SSP5-8.5. Data extraction, quality control, and clustering were conducted before analysis, and the model was validated for its accuracy and reliability in predicting soil parameter changes. An artificial neural network model was utilized to predict the effects of extreme climate indices on soil pH and exchangeable aluminum concentrations. The model was designed to accurately and reliably predict changes in soil parameters. This study compared the changes in soil pH and aluminum concentrations using paired t tests. The model's diagnostic results indicated a significant impact of extreme climate scenarios on soil pH and exchangeable aluminum. Extreme climate factors such as heavy precipitation and cooler night time temperatures significantly contribute to soil acidification and an increase in aluminum concentration. Under the SSP1-2.6 and SSP2-4.5 emission scenarios, soil pH levels are expected to increase by 8.38 % and 3.79 %, respectively. These changes in soil pH are expected to have significant impacts on the exchangeable aluminum content in the soil, with increases of 37 % and 5.38 %, respectively, under the same emission scenarios. However, the SSP5.8 scenario predicted a 45 % increase in exchangeable aluminum and a 9.36 % decrease in soil pH. Therefore, this study significantly enhances our understanding of the influence of climate change on soil health. The development of strategies to mitigate climate change impacts on agriculture in the region must consider the effects of extreme climate indices.

The relative importance of precipitation change and temperature sensitivity in determining the population viability of a threatened sub‐tropical rainforest endemic plant Triunia robusta (Proteaceae)

AbstractThreatened species in rainforests may be vulnerable to climate change, because of their potentially narrow thermal tolerances, small population sizes, restricted distributions and limited dispersal. We investigated the relative influence of potential climate change on the population viability of Triunia robusta (Proteaceae), an endangered rainforest shrub endemic to southeast Queensland, Australia. A spatially explicit, stochastic population model with seven stage classes was developed and linked with the species distribution model (SDM) to explore a variety of hypothetical climate change simulations over a 90‐year period from 2010 to 2100: (1) constant population dynamics, (2) changes in habitat distributions as trend in carrying capacity and (3) changes in habitat distributions, precipitation and temperature regime as relative change in seedling survival and fecundity. The results revealed high vulnerability of small populations to local extinction regardless of geographical location or climatic stressors, while some larger populations located in the southern end of the species distribution range showed persistence in‐situ. Triunia robusta was found to be sensitive to reduced precipitation and increased temperature, limiting the species reproductive activities and seedling establishment and reducing the overall abundance consequently. Integration of population models and SDM allowed for the evaluation of multiple climatic stressors that may affect habitat distributions and population dynamics of T. robusta and ultimately suggest potential implications for future conservation and management planning with respect to climate change.

Projection of extreme climate change in the Asian arid region and the Tibetan Plateau in the early and middle 21st century based on NEX-GDDP-CMIP6

In the context of global warming, it is anticipated that both the intensity and the frequency of future global extreme high precipitation (EHP) and extreme high temperature (EHT) events will increase. To evaluate the future extreme climate changes in the Asian arid region and Tibetan Plateau, this study applied the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) to assess the changes in EHP (Rx5d and R95pTOT) and EHT (TX90p and TXx) under different emission scenarios in the 21st century. Findings suggest that both the frequency and the intensity of the extreme indices will increase, exhibiting accelerated growth under higher emission scenarios, particularly under the SSP5-8.5 emission scenario. It is suggested that the growth of EHT and EHP in the early subperiod of the 21st century (2026–2045) will be relatively moderate, with small differences between different emission scenarios. However, by the middle subperiod of the 21st century (2041–2060), the differences between different emission scenarios will become larger than the 2035s and the growth will become more intense. In western central Asia, TX90p, TXx, Rx5d, and R95pTOT increase by 9.7%–14.2% (13.3%–24.7%), 1.3°C–1.7°C (1.6°C–2.7°C), 6.5%–8.9% (8.2%–8.8%), and 18.1%–27.0% (25.6%–30.0%) by the early (middle) subperiod; in eastern central Asia, TX90p, TXx, Rx5d, and R95pTOT increase 8.1%–12.0% (11.3%–21.1%), 1.4°C–1.8°C (1.9°C–2.9°C), 7.4%–9.7% (10.4%–13.8%), and 20.2%–29.3% (32.0%–40.8%) by the early (middle) subperiod; and over the Tibetan Plateau, TX90p, TXx, Rx5d, and R95pTOT increase 12.5%–17.4% (17.0%–31.0%), 1.2°C–1.5°C (1.6°C–2.5°C), 7.2%–10.0% (9.9%–15.0%), and 26.6%–33.1% (36.1%–55.3%) by the early (middle) subperiod.摘要近年来, 随着全球变暖, 大部分地区极端气候事件的风险都有所增加. 作为中国一带一路建设核心区域的亚洲干旱区和青藏高原区域面临着严峻的极端气候风险. 本文利用NEX-GDDP-CMIP6数据预估了未来21世纪早期 (2026–2045) 和中期 (2041–2060) 不同排放情景下亚洲干旱区和青藏高原相较气候参考期 (1995–2014) 极端高温指数和极端降水指数的变化. 预估结果显示, 在不同排放情景下极端高温指数和极端降水指数都有所上升, 且在SSP5-8.5情景下增长最多, 其中NEX-GDDP-CMIP6不同模式对极端高温指数的模拟一致性高于极端降水指数. 21世纪中期相比早期极端高温指数和极端降水指数的增长更加严重.

Potential impact of climate change on the distribution of Capricornis milneedwardsii, a vulnerable mammal in China.

Climate change significantly impacted on the survival, development, distribution, and abundance of living organisms. The Chinese serow Capricornis milneedwardsii, known as the "four unlike," is a Class II nationally protected species in China. In this study, we predicted the geographical suitability of C. milneedwardsii under current and future climatic conditions using MaxEnt. The model simulations resulted in area under the receiver operating characteristic curve (AUC) values above 0.9 for both current and future climate scenarios, indicating the excellent performance, high accuracy, and credibility of the MaxEnt model. The results also showed that annual precipitation (Bio12), slope, elevation, and mean temperature of wettest quarter (Bio8) were the key environmental variables affecting the distribution of C. milneedwardsii, with contributions of 31.2%, 26.4%, 11%, and 10.3%, respectively. The moderately and highly suitable habitats were mainly located in the moist area of China, with a total area of 34.56 × 104 and 16.61 × 104 km2, respectively. Under future climate change scenarios, the areas of suitability of C. milneedwardsii showed an increasing trend. The geometric center of the total suitable habitats of C. milneedwardsii would show the trend of northwest expansion and southeast contraction. These findings could provide a theoretical reference for the protection of C. milneedwardsii in the future.

Evaluating Performance of Multiple Machine Learning Models for Drought Monitoring: A Case Study of Typical Grassland in Inner Mongolia

Driven by continuously evolving precipitation shifts and temperature increases, the frequency and intensity of droughts have increased. There is an obvious need to accurately monitor drought. With the popularity of machine learning, many studies have attempted to use machine learning combined with multiple indicators to construct comprehensive drought monitoring models. This study tests four machine learning model frameworks, including random forest (RF), convolutional neural network (CNN), support vector regression (SVR), and BP neural network (BP), which were used to construct four comprehensive drought monitoring models. The accuracy and drought monitoring ability of the four models when simulating a well-documented Inner Mongolian grassland site were compared. The results show that the random forest model is the best among the four models. The R2 range of the test set is 0.44–0.79, the RMSE range is 0.44–0.72, and the fitting accuracy relationship could be described as RF > CNN > SVR ≈ BP. Correlation analysis between the fitting results of the four models and SPEI found that the correlation coefficient of RF from June to September was higher than that of the other three models, though we noted the correlation coefficient of CNN in May was slightly higher than that of RF (CNN = 0.79; RF = 0.78). Our results demonstrate that comprehensive drought monitoring indices developed from RF models are accurate, have high drought monitoring ability, and can achieve the same monitoring effect as SPEI. This study can provide new technical support for comprehensive regional drought monitoring.

Carbide Precipitation Behavior of High‐Alloy Steel During Solidification and Cooling Process

The precipitation, growth, and transformation of carbides rich in Cr and Mo during solidification and cooling process of high‐alloy steel for cold working dies are investigated. The Fe–C pseudobinary phase diagram of high‐alloy steel is calculated by Thermo‐Calc software to ascertain the critical phase transformation temperatures. The temperatures of phase transformation during the solidification process are determined by a differential scanning calorimeter. Then the microstructure of the samples at these characteristic temperatures is observed in situ by high‐temperature confocal microscope. The results show that the characteristic temperatures for phase transformation and carbide precipitation are 1380, 1315, 1140, and 980 °C, respectively. At 1315 °C, thick rod‐like or island‐like M7C3 carbides enriched in Cr and Fe are formed. At 1140 °C, secondary M7C3, adhering to the primary eutectic M7C3, grows rapidly in a rod‐like morphology and maintains a similar composition. The secondary M6C carbides of segregated Mo elements precipitate in fan‐shaped clusters near M7C3 through the dissolution of M7C3 and the conversion of M2C. Thermodynamic calculation further indicates that the eutectic Cr7C3 precipitates at 1213 °C, and secondary Cr7C3 remains under conditions favorable for precipitation below the solidus, preceding the precipitation of secondary carbides Cr23C6 and Mo2C.

Climate variability and change in Ecuador: dynamic downscaling of regional projections with RegCM4 and HadGEM2-ES for informed adaptation strategies

Ecuador, a country with distinct coastal (CO), highland (HL), and Amazon (AM) regions that are characterized by unique climatic, ecological, and socio-economic features is highly vulnerable to climate change. This study focuses on these three regions, highlighting their individual importance in the broader context of Ecuador's climate vulnerability. Utilizing dynamically downscaled data from the Regional Climate Model (RCM), we generated precipitation and air temperature projections for the period 2070–2099 under three different climate change scenarios. We indicate projected temperature increases across all three regions: mean temperature increases for the CO, HL and AM regions are of 1.35, 1.55, and 1.21°C, respectively. Each year, the largest temperature increases are predicted for the third quarter (June–August), with the smallest increases predicted for the last quarter (December–February). Precipitation patterns show varied changes, with CO exhibiting a positive mean daily change, in contrast to a mean negative change in the AM region. These region-specific projections underscore the differential impacts of climate change within Ecuador and highlight the necessity for tailored adaptation measures. The study's novel approach, focusing on distinct regional impacts within a single nation, offers valuable insights for policymakers, aiding in the development of effective, region-specific climate change mitigation and adaptation strategies. This targeted approach is crucial to address unique challenges faced by different regions, thereby supporting national resilience strategies.

The effect of local climatic conditions on household consumption: a case study of South Africa

The article explores the causal effect of local climate conditions on household consumption in South Africa. The climatic conditions are represented by monthly average temperature and precipitation. The study utilises the nationally representative 2017 National Income Dynamics Study (NIDS), wave 5 data and 2017 Climate Research Unit (CRU) climate data. The parsimonious quantile regression shows that climatic conditions (precipitation, temperature, wet days, and cloud cover) impact household per capita consumption. The quadratic quantile regression model analysis shows that household per capita consumption is convex in precipitation. Below the turning point, increased precipitation is associated with decreased household per capita consumption. Above the turning point, increased precipitation is related to increased household per capita consumption. Regions that receive very low precipitation or experience extreme temperatures (very cold or very hot) require tailor-made interventions to alleviate consumption. When we control for household characteristics, the impact of climatic conditions on household per capita consumption is weak. Providing inclusive development policies and programmes can mitigate the impact of climatic conditions on household per capita consumption.

Precipitation masks the effect of temperature on Birch airborne pollen start, and previous summer temperature affects pollen intensity; A 31-year study at its southwestern distribution boundary

We studied the relationship between the occurrence of airborne pollen of Betula spp. and climate, during the main pollination season, as well as before the pollen season and in the preceding year. Our aim was to understand how environmental conditions could influence the main pollen season and the intensity of airborne pollen presence at the meridional boundary of the Betula forest distribution in Europe.For this purpose, pollen monitoring was conducted using Lanzoni VPPS 2000 volumetric trap and weather data from the nearest meteorological station. The study area was located in the northwest of the Iberian Peninsula, specifically in three areas with diverse mesoclimate: Vigo (Atlantic), Ourense (Mediterranean) and Lugo (Cantabrian), which had a distinct oceanic influence. Aerobiological analysis was conducted based on the Spanish aerobiology network protocol. Data on precipitation, maximum, minimum and mean temperature were selected for three time windows: 1st the main pollen season period, 2nd from 5 to 90 days before the onset of pollen presence, with a cumulative five-day interval, and 3rd the average monthly climate of the previous year.Precipitation delays the onset of the main pollination season as well as the end of the season, increasing pollen counts in the post-peak interval at all three sites. Temperature during the pollen season affects duration and pollen integral differently among sites. The pollen integral shows an increasing trend over the last decade's at all three areas. The rise trend detected in the minimum temperature of the previous summer explains these increases in the three sites.In conclusion, the effect of climate prior to and during the main pollen season have varied effects on date-related data across mesoclimates, while temperature during bud floral primordia development can be considered as a timeframe for predicting pollen intensity in the following year through the entire area.

Using proxy data and vegetation modelling to predict past, current and future distributional shifts of Butea monosperma, a marker of land degradation in India

Extensive deviations in spatio-temporal social and environmental dynamics currently alter the health of ecosystems and the services they provide. Detecting the causes that contribute to the distribution of a natural forest species capable of restoring the lost ecosystem function and productivity will aid in determining better food security, livelihoods and provision of ecosystem goods and services. We modelled the spatial range of Butea monosperma (B. monosperma) under past, that is, Last Glacial Maximum (LGM), Middle Holocene (MH), current and future (2070) climatic scenarios with Maximum Entropy (MaxEnt) trained on present-day occurrences. We identified areas of suitable habitats for which the estimation of habitat stability is predicted in all the models at different times. To validate the inferred suitable habitat, we tested the model by the current occurrence and fossil pollen data of B. monosperma. Our distribution models agree with the fossil pollen records for the MH (4,500–7,000 yr BP) and predict the prevalence of B. monosperma covering 84.22% of the Indian subcontinent with maximum habitat stability in western and southwestern India (10.95%). The widespread potential distribution of the plant species during the LGM supports the presence of the last remnants of tropical dry deciduous forest in the region. However, a decline in habitat suitability (62.84%) is predicted under current and future climatic scenarios with maximum stability (0.90%–3.09%) along the Western Ghats, Nilgiri hills, Gir range in the western India and north-eastern region covering the Assam Valley and foothills of Tripura and Mizo hills. Temperature seasonality (33.6%) measured in terms of variable contribution in MaxEnt model significantly affects the distribution shift of B. monosperma, along with annual precipitation (22.8%) and annual mean temperature (16.2%). Model results provide evidence of habitat reduction and identify the stability hotspots for B. monosperma for its conservation and establishment of land management policies mainly for the dry tropics.

Modeling climate change impacts under future CCM3 scenario on sorghum (Sorghum bicolor) as an drought resilient crop in tropical arid Lombok Island, Indonesia

Abstract. Wibowo AA, Meylani V. 2024. Modeling climate change impacts under future CCM3 scenario on sorghum (Sorghum bicolor) as an drought resilient crop in tropical arid Lombok Island, Indonesia. Intl J Trop Drylands 8: 35-43. The arid ecosystems and drought conditions exacerbated by climate change and rising CO2 levels necessitate the identification of alternative drought-tolerant crops. Sorghum bicolor L. has emerged as a promising option due to its resilience to drought. However, there is dearth of information regarding its future potential distribution, particularly in arid regions like Lombok Island, Indonesia, where sorghum is being considered as a viable alternative to ensure food security. This study employs Maximum Entropy (MaxEnt) modeling, incorporating environmental and bioclimatic variables, along with the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) scenario reflecting doubled CO2 levels, to model the future potential distribution of S. bicolor. The model projects a total suitable habitat area of 1,875 km2, constituting 39.56% of Lombok Island’s land area. Notably, very high-suitability areas of 175 km2, and high-suitability areas of 200 km2 encompass 3.69% and 4.22% of the island’s territory, respectively, predominantly concentrated in the southern region of the island and characterized by low precipitation and high temperatures, particularly at altitudes ranging from 0 to 1,000 meters. The model's performance, evaluated using the Area Under the Curve (AUC), yields a score of 0.725, indicating a good level of accuracy. Key factors influencing sorghum distribution include annual precipitation (68.69%), isothermality (9.56%), temperature seasonality (9.56%), precipitation seasonality (8.69%), and annual mean temperature (3.47%). The CCM3 model forecasts an expansion of sorghum distribution toward the north, occupying approximately 6.25% of Lombok's total area. These findings highlight sorghum’s adaptability and resilience to future climate changes, positioning it as a valuable resource for sustainable agriculture in arid environments.

Robust hydraulic traits correlation in woody species despite large trait variation along natural and experimental environmental gradients

Abstract Hydraulic traits are major determinants of plant fitness, thus exerting control over vegetation structure, function and distribution. Yet it remains unclear whether and how hydraulic traits respond to environmental stimuli (i.e. phenotypic variation of hydraulic traits; PVHT) and if the coordination between different hydraulic traits and the trait–climate relationship are affected by PVHT. Here, we synthesized data of PVHT (maximum hydraulic conductivity and water potential inducing 50% loss of hydraulic conductivity) and potentially related morphological and anatomical traits (e.g. sapwood density, branch Huber value, mean and hydraulic weighted conduit diameter). We analysed the magnitude, direction and source of variation of the plastic response, as well as the influence of environmental factors on trait coordination. Additionally, we compared the intra‐ and inter‐specific variation between key hydraulic traits and climate metrics (mean annual precipitation and mean annual temperature) at the site of growth, as well as across the population range. PVHT was highly variable in both magnitude and direction, which was contingent on the environmental factor. The variation in PVHT mainly occurred at high taxonomic levels (i.e. family and genus), whereas phenology explained little variation for PVHT. Despite the high variability, trait correlation remained robust in the presence of environmental stimuli. Moreover, trait–climate relationships differed at inter‐specific and intra‐specific levels. The intra‐specific variation of hydraulic traits in most species showed no correlation with climate metrics compared with the high correlation of hydraulic traits with climate metrics across species. Our findings suggest that the high variability of PVHT does not affect the trait correlation which may be valuable in predicting vegetation dynamics under varying environments. The distinct trait–climate relationships highlight the need to unravel the driving force of PVHT, as well as the adaptive strategy across populations. Read the free Plain Language Summary for this article on the Journal blog.

Evaluation of the Activity of a Municipal Waste Landfill Site in the Operational and Non-Operational Sectors Based on Landfill Gas Productivity

This research identifies the productivity of landfill gas actively captured at a municipal waste landfill site with a waste mass exceeding 1 million Mg from sectors in the operational and non-operational phases, considering meteorological conditions. Based on the analysis of landfill gas, including emissions and composition (CH4, CO2, O2, and other gases), the processes occurring demonstrate the impact of the decomposition of deposited waste on the activity of the deposit. With average monthly gas emissions exceeding 960,000 m3, the average content of CH4 (30–63%) and CO2 (18–42%) and the varied content of O2 (0.3–9.8%) in individual sectors of the landfill site were significant. The statistically significant relationship between CH4, CO2, and landfill gas emissions exhibited a noticeable decrease in methane content. Despite the abandonment of waste storage, a high correlation is present between the emission level and methane content (0.59) and carbon dioxide (0.50). In the operational part of the landfill, this relationship is also statistically significant but to a lesser extent; Spearman’s R-value was 0.42 for methane and 0.36 for carbon dioxide. The operational and post-operational phases of the municipal waste landfill demonstrated a noticeable impact from the amount of precipitation, relative humidity, and air temperature, on landfill gas productivity. The generally progressive decline in the activity of the waste deposit, which reflects a decreasing trend in the methane content of approximately 2% annually in the total composition of landfill gas, as well as the share below 50%, indicates the need only to utilise landfill without producing energy.

Projection of mean and extreme precipitation and air temperature over India: a CMIP6 analysis

ABSTRACT This study used 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) models to analyze the mean and extreme projection precipitation during the Indian summer monsoon (ISM) season, i.e., June to September (JJAS). A continuous rise in precipitation and its associated unpredictability were predicted by global climate models using the CMIP6. The extreme values are estimated on the basis of generalized extreme value (GEV) distribution. Four socioeconomic paths are used as SSP126, SSP245, SSP370 and SSP585 to understand the impact of low-emission to high-emission scenarios. In all the scenarios, it is seen that all the models predict a significant rise in JJAS mean and extreme precipitation. Moreover, a strong correlation is obtained between the historical (1995–2014) and near-emission future simulation (2021–2040), mid-emission future simulation (2041–2060), high-emission future simulations (2081–2100) of air temperature and precipitation. In extreme emission scenarios, ensemble mean of CMIP6 models shows an increasing amplitude in surface air temperature and precipitation over India in the near future (2021–2040), mid future (2041–2060) and the end of the century (2081–2100). The CMIP6 simulations mainly support the results of all models, but they also demonstrate improved robustness across models.

Predicted range expansion of Prostephanus truncatus (Coleoptera: Bostrichidae) under projected climate change scenarios.

The larger grain borer (Prostephanus truncatus [Horn] [Coleoptera: Bostrichidae]) is a wood-boring insect native to Central America and adapted to stored maize and cassava. It was accidentally introduced to Tanzania and became a pest across central Africa. Unlike many grain pests, P. truncatus populations can establish and move within forests. Consequently, novel infestations can occur without human influence. The objectives of our study were to (i) develop an updated current suitability projection for P. truncatus, (ii) assess its potential future distribution under different climate change scenarios, and (iii) identify climate variables that best inform the model. We used WALLACE and MaxEnt to predict potential global distribution by incorporating bioclimatic variables and occurrence records. Future models were projected for 2050 and 2070 with Representative Concentration Pathways (RCPs) 2.6 (low change) and 8.5 (high change). Distribution was most limited by high precipitation and cold temperatures. Globally, highly suitable areas (> 75%) primarily occurred along coastal and equatorial regions with novel areas in northern South America, India, southeastern Asia, Indonesia, and the Philippines, totaling 7% under current conditions. Highly suitable areas at RCPs 2.6 and 8.5 are estimated to increase to 12% and 15%, respectively, by 2050 and increase to 19% in 2070 under RCP 8.5. Centroids of highly suitable areas show distribution centers moving more inshore and away from the equator. Notably, the result is a range expansion, not a shift. Results can be used to decrease biosecurity risks through more spatially explicit and timely surveillance programs for targeting the exclusion of this pest.

An Investigation of the Impact of Precipitation Temperature and Filter Cake Thickness on the Physical Stability of Amorphous Solids: A Case Study.

The purpose of this study was to resolve the issue of physical instability in amorphous solid drugs, which can result in unwanted crystallization, affecting solubility and dissolution rates. The focus was on precipitating physically stable amorphous forms of the nilotinib free base, an anticancer drug, by monitoring preparation conditions such as precipitation temperature and filter cake thickness. A comprehensive set of characterization techniques, including powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and focused beam reflectance measurement (FBRM), were used. These were supplemented by advanced data analysis methods that incorporated pair distribution function (PDF), reduced crystallization temperature (Rc), and principal component analysis (PCA) to evaluate the physical stability of the amorphous samples. Results emphasized that optimal physical stability was achieved when amorphous solids were prepared at a precipitation temperature of 10 °C and a filter cake thickness of 4 cm. Moreover, the integration of PDF analysis with Rc values was confirmed as an innovative approach for assessing physical stability, thus offering enhanced efficiency and accuracy over conventional accelerated stability testing methods.

Woody encroachment induced earlier and extended growing season in boreal wetland ecosystems.

Woody plant encroachment (WPE), a widespread ecological phenomenon globally, has significant impacts on ecosystem structure and functions. However, little is known about how WPE affects phenology in wetland ecosystems of middle and high latitudes. Here, we investigated the regional-scale effects of WPE on the start (SOS), peak (POS), end (EOS), and length (GSL) of the growing season in boreal wetland ecosystems, and their underlying mechanisms, using remote sensing dataset during 2001-2016. Our results showed that WPE advanced the annual SOS and POS, while delaying EOS and extending GSL in boreal wetlands with these impacts increasing over time. When boreal wetland ecosystems were fully encroached by woody plants, the SOS and POS were advanced by 12.17 and 5.65 days, respectively, the EOS was postponed by 2.74 days, and the GSL was extended by 15.21 days. We also found that the impacts of WPE on wetland SOS were predominantly attributed to the increased degree of WPE (α), while climatic factors played a more significant role in controlling the POS and EOS responses to WPE. Climate change not only directly influenced phenological responses of wetlands to WPE but also exerted indirect effects by regulating soil moisture and α. Winter precipitation and spring temperature primarily determined the effects of WPE on SOS, while its impacts on POS were mainly controlled by winter precipitation, summer temperature, and precipitation, and the effects on EOS were mainly determined by winter precipitation, summer temperature, and autumn temperature. Our findings offer new insights into the understanding of the interaction between WPE and wetland ecosystems, emphasizing the significance of considering WPE effects to ensure accurate assessments of phenology changes.

Effect of Ce2O3 content on structure, viscosity, and melting properties of CaO-Al2O3-MgO-SiO2-Ce2O3 slag

To ensure the reliable operation of high aluminum steel smelting, it is common practice to employ low-reactivity CaO-Al2O3-based slag. Various analytical methods, including scanning electron microscopy with energy-dispersive X-ray spectroscopy, X-ray diffraction, Raman spectroscopy, and so on, are employed to investigate the impact of Ce2O3 content on the crystalline phase and structure within the CaO-Al2O3-MgO-SiO2 slag. Concurrently, the slag properties of viscosity and melting temperature are assessed. The findings reveal that the principal crystalline phases in the CaO-Al2O3-MgO-SiO2 slag include Ca3Al4MgO10, Ca3Al2O6, and MgO. Additionally, the introduction of Ce2O3 leads to the formation of the high melting temperature CaCeAlO4 phase, whose abundance correlates positively with the Ce2O3 content. Ce2O3 demonstrates efficient bridging oxygen bond disruption, causing the transformation of network former [AlO4]-tetrahedron into network modifier [AlO6]-octahedron. Simultaneously, Q4Al shifts to Q2Al and Q3Al in [AlO4]-tetrahedron, resulting in a marked reduction in degree of polymerization of slag. This reduction is evident in decreased viscosity and melting temperature, reaching the minimum value of 0.153 Pa·s and 1331 °C, respectively. However, the Ce2O3 content is beyond 15 wt%, Q2Al and Q3Al transform into Q4Al, which lead to an upward trend in high-temperature viscosity. Furthermore, as the temperature decreases, the precipitation of the CaCeAlO4 phase from the slag occurs. The content and precipitation temperature of CaCeAlO4 increase with rising Ce2O3 content, representing the primary factor behind the elevation of low-temperature viscosity and melting temperature.

Role of (Al, Ti) alloying and annealing temperature in precipitation, recrystallization, and mechanical properties of ferrous multi-component alloys

L12-precipitate-strengthened multi-component alloys (MCAs) possess exceptional combination of strength and ductility. However, the high production costs of L12-containing MCAs impede their industrial application. This study introduces a novel approach for designing cost-effective L12-containing MCAs by microalloying Al and Ti with a base composition of Fe50Ni30Cr20 (at%). Three types of MCAs were investigated in this study: Fe50.13Ni28.84Cr18.56Al1.39Ti1.08 (1Ti alloy), Fe46.53Ni27.32Cr19.91Al3.44Ti2.80 (3Ti alloy), and Fe48.51Ni25.93Cr15.75Al5.10Ti4.71 (5Ti alloy) (at%). An increase in the (Al, Ti) content from 1 to 3 at% accelerates the formation of L12 particles, whereas an increase in the (Al, Ti) content from 3 to 5 at% leads to the activation of the brittle B2 and D024 phases. The rapid co-precipitation of the L12, B2, and D024 phases in the 5Ti alloys substantially hinders recrystallization during annealing, whereas the 3Ti alloys exhibit the highest rate of recrystallization upon annealing at 600 and 700 °C, mainly due to the reduction in the stacking fault energy of the matrix. The 5Ti alloys exhibit the highest hardness and the lowest plasticity owing to the presence of brittle B2 and D024 precipitates. By contrast, the 3Ti alloy annealed at 600 °C, in which dense and relatively fine L12 particles precipitated, exhibits a superior combination of hardness and plasticity. This study provides insights into the composition and annealing condition-dependent precipitation, recrystallization, and mechanical properties of ferrous MCAs.

Adaptive potential of winter common wheat varieties in the Penza region

The current paper has presented the results of long-term study (2014–2023) of productivity, adaptability parameters and correlation between a genotype and environment of winter common wheat varieties in the forest-steppe conditions of the Penza region. The purpose of the study was to determine the response of winter common wheat varieties in changing agroclimatic conditions according to productivity. The vegetation conditions during the years of study varied in temperature and amount of precipitation, which served as a good background for conducting research on the issue in question. The objects for the study were 9 zoned varieties approved for cultivation in the Middle Volga region and 5 winter common wheat varieties developed by the FSBRI CBFC. The zoned winter common wheat variety ‘Fotiniya’ was used as a standard. The years of the varieties’ study were divided into favorable, typical (mean) and unfavorable (dry, excessively wet). Winter common wheat productivity in favorable years averaged 5.68 t/ha, in typical years it was 4.32 t/ha and 2.19 t/ in unfavorable years. As a result of determining the response of winter common wheat varieties in changing agroclimatic conditions according to productivity, there was proven a strong effect of environmental conditions and genotype. There have been proposed for breeding use such valuable and stable genotypes of winter common wheat as ‘Biryuza’, ‘Skipetr’, ‘Don-eko’, ‘Alyonushka’, ‘Pamyati Krivobocheka’, ‘Surskaya Nika’, ‘Dargo’, which should be placed on a high and medium agricultural background. The varieties ‘Fotiniya’ and ‘Klavdiya 2’ are highly adaptable to unfavorable cultivation conditions and will have an advantage over other varieties in medium and low agricultural backgrounds.