Climate Change Factors Research Articles

Root and Leaf Traits of Alfalfa Exhibit Distinct Responses to Soil Microbial Communities and Environmental Stresses

ABSTRACTOngoing climate change is negatively impacting crop productivity globally. Past research has highlighted that a diverse soil microbial community and variation in plant traits for resource acquisition can mitigate the negative impacts of climate change factors on crop productivity. This study investigates the effects of two major environmental stressors—drought and salinity stress, on plant productivity, biomass allocation, and root and leaf trait responses under distinct soil microbial diversities. Our results showed that salinity stress had stronger negative impacts on plant productivity than drought stress. Shoot biomass decreased by 30% and 32.5% under drought and salinity stress, respectively, whereas the root biomass decreased by 32% only under salinity stress. Soil microbial diversity did not affect plant productivity. Next, root traits were mainly impacted by drought and salinity stress, whereas leaf traits were impacted by both environmental stresses and soil microbial diversity. Specific root length and specific root area decreased under drought, and root tissue density was minimal under salinity stress. Root traits were not affected by soil microbial communities. In contrast, the leaf nitrogen content increased, whereas pheophytin content (a breakdown product of chlorophyll) decreased when plants were grown in diverse microbial communities under environmental stresses, especially drought. These results highlight the importance of soil microbial diversity in impacting plant traits in response to environmental stresses. We showed that the soil microbial diversity influences both aboveground and belowground plant traits, indicating the need for better management practices to conserve and promote soil microbial diversity.

Effect of Rice Input Variables and Climate Change Factors on Total Factor Productivity of Rice in Nigeria

This study evaluated the effect of rice production input variables and climate change variables on rice total factor productivity (TFP) in Nigeria. The research utilizes various data sets obtained from reputable organizations to analyze the period from 1961 to 2020. Descriptive and inferential statistics were employed to analyze the data. The study findings indicate an upward trajectory in rice TFP in Nigeria over the examined period. Regression analysis reveals that labor and capital have a significant positive effect on rice TFP, indicating that increased labor and capital investments can enhance productivity. Rainfall and sunlight duration also show a significant positive relationship with rice TFP, emphasizing their crucial role in rice farming. The study highlights the importance of addressing labor scarcity and promoting access to capital for farmers. Moreover, it emphasizes the quest for optimal rainfall and sunlight conditions throughout the rice cultivation process. The model's diagnostic tests confirm its reliability, and the findings demonstrate the statistical significance of the independent variables in explaining rice TFP. Overall, this research gives insightful information on the factors influencing rice TFP in Nigeria. It offers recommendations for stakeholders and decision-makers to enhance productivity by addressing labor scarcity, promoting capital access, and optimizing climatic conditions for rice cultivation.

Uluslararası Göçlerin Hukuki ve Ekonomik Sonuçları

Migration is the movement of people from one place to another. This phenomenon occurs for various reasons, including war, climate change, drought, and economic and political factors. It encompasses more than just the movement of people; it also includes the seasonal movement of birds, fish, and other animals. This phenomenon has persisted throughout history, including the migration of tribes in the fourth century due to drought and climate change. The economic and social dimensions of international migration have come under scrutiny. The rise of globalization has contributed to an increase in international migration, with certain countries, such as the USA, Canada, and Australia, implementing legal immigration policies motivated by economic considerations. Illegal migration from underdeveloped countries has reached substantial levels due to factors such as wars, food shortages, and climate change. This study aims to examine the causes of international human migration, the various types of migration, and the migration systems. The discussion will cover migration processes, agreements between receiving and sending countries, and the legal and economic consequences of migration. It will also address the challenges experienced by our nation as a source and destination for immigration. Migration entails challenges, but it also generates benefits in nations with the right legal frameworks and social measures. This study will cover both sociological and liberal perspectives.

Influence of precipitation and temperature variability on anthropogenic nutrient inputs in a river watershed: Implications for environmental management.

Since the Industrial Revolution, anthropogenic activities have substantially increased the input of nitrogen (N) and phosphorus (P) into river watersheds, exacerbated by uncertainties stemming from climate change. This study provided a detailed analysis of N and P inputs within the Dawen River Watershed in China from 2000 to 2021. The Net Anthropogenic Nitrogen Input (NANI) and Net Anthropogenic Phosphorus Input (NAPI) methods were used in study, which aimed to investigate how they respond to various climate change factors. Our findings reveal a generally decreasing trend in NANI, with an average of 17,882.34kg/km2/yr. NAPI showed an initially increasing and then decreasing trend, with an average value of 5151.79kg/km2/yr. Fertilizer usage emerged as the primary sources of nutrient inputs, accounting for approximately 63.42% of N and 61.88% of P inputs. Precipitation positively impacted the NANI and NAPI while temperature exerted more influential but opposing effects. Lag effects were evident as demonstrated by the stronger impacts of temperature in preceding year on NANI and NAPI. Moreover, climate not only influenced the quantity of NANI and NAPI but also impacted their changes, as well as the inputs of their components. Through quantitative analyses, we unveiled key thresholds in the correlation between nutrient inputs and climate variables, with cutoffs of 14.1°C in temperature and 820mm in precipitation. Our study highlights the complex relationships between anthropogenic nutrient inputs and climate change, and identifies critical climate thresholds that underscore the importance of sustainable management practices in the Dawen River Watershed to mitigate negative environmental impacts.

Impact of physical climate risks on agricultural firms’ bankruptcy: evidence from France, Italy, Portugal and Spain from 2016 to 2019

Abstract Frequent and long-lasting extreme climate events can impact business-related natural capital, severely affecting production and resulting in losses for agricultural firms. Physical climate effects are material dependencies for agricultural businesses and may severely affect their performance and compromise their survival. This study’s aim is to analyze the comprehensive effect of climate change factors on agricultural firm bankruptcies in a European geographical area that is especially susceptible to climate change. Employing a panel of 15 036 agricultural firms, we analyze the effects of adverse climatic conditions in the firm’s headquarters area using logit regressions, an instrumental variable ordinary least squares model, and the gradient-boosting ensemble method. We find that bankruptcy is conditioned upon extreme weather events, indicating that climate change’s physical impacts on firm resources already materially affect the agricultural sector’s resilience and survival. Specifically, abnormally high temperatures, precipitation, and the incidence of fires are significant factors that contribute to bankruptcy or insolvency. Furthermore, a “fire weather” index comprising high temperatures, drought, and wind, combined with fire occurrence, intensifies the bankruptcy risk of agricultural businesses.

Factors affecting risk perception of COVID-19: differences by age and gender.

Addressing emerging infectious diseases is a major task in public health. This study investigated the factors influencing the perception of risk related to COVID-19. This study analyzed data from the 2020 Social Survey conducted nationwide in South Korea, targeting 34,909 individuals aged 13 years and older. Using an ordered logit regression model, we examined the relationship between COVID-19 risk perception and its predictors across age groups (20-44 years, 45-64 years, 65 years and older) and gender groups. The predictors included in the analysis model were demographic factors, socioeconomic factors, health and quality of life factors, levels of social trust, and climate change factors. The results demonstrated that COVID-19 risk perception was higher among older individuals and women compared with men. In the young population group (20-44 years), mental stress was related to COVID-19 risk perception, but this was not observed in other population groups. In the older adult population group (65 years and older), education level was related to COVID-19 risk perception, whereas this was not observed in the young population group. In the male group, economic variables such as income and employment status were related to COVID-19 risk perception, whereas in women, family-related variables such as marital status and housing type were related. In most subgroup analyses, lower income levels or lower life satisfaction were associated with higher COVID-19 risk perception. The findings of this study suggest that health authorities need to tailor their responses to COVID-19 risk perception based on different populations and social groups. For the older adult population with a high-risk perception, it is necessary to provide reliable information to reduce anxiety caused by excessive risk perception. For the young population, proactive responses from health authorities regarding mental health are needed.

Ensuring Africa's Food Security by 2050: The Role of Population Growth, Climate-Resilient Strategies, and Putative Pathways to Resilience.

Africa is grappling with severe food security challenges driven by population growth, climate change, land degradation, water scarcity, and socio-economic factors such as poverty and inequality. Climate variability and extreme weather events, including droughts, floods, and heatwaves, are intensifying food insecurity by reducing agricultural productivity, water availability, and livelihoods. This study examines the projected threats to food security in Africa, focusing on changes in temperature, precipitation patterns, and the frequency of extreme weather events. Using an Exponential Growth Model, we estimated the population from 2020 to 2050 across Africa's five sub-regions. The analysis assumes a 5% reduction in crop yields for every degree of warming above historical levels, with a minimum requirement of 225 kg of cereals per person per year. Climate change is a critical factor in Africa's food systems, with an average temperature increase of approximately +0.3 °C per decade. By 2050, the total food required to meet the 2100-kilocalorie per adult equivalent per day will rise to 558.7 million tons annually, up from 438.3 million tons in 2020. We conclude that Africa's current food systems are unsustainable, lacking resilience to climate shocks and relying heavily on rain-fed agriculture with inadequate infrastructure and technology. We call for a transformation in food systems through policy reform, technological and structural changes, solutions to land degradation, and proven methods of increasing crop yields that take the needs of communities into account.

Analysis of Regional Characteristics of Climate Change Factors Affecting Water Distribution Pipe Leakage

Understanding the factors behind urban water leakage is crucial for developing a sustainable climate and protecting civil infrastructure. Water leaks not only waste essential resources but also increase urban vulnerabilities to climate-induced disasters. This study investigates the teleconnection between leakage incidents and climate change indices to establish predictive insight for water management. It focuses on climate phenomena such as El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), which significantly influence global climate dynamics, affecting temperature and precipitation in South Korea. Using Pearson correlation analysis and Granger causality tests, this research examines climate indices and leakage data across South Korea’s inland regions from 2009 to 2022. The results indicate that ENSO indices exhibit a lead time of 6 to 30 months, with significant correlations in coastal areas, particularly Chungnam (west coast) and Gyeongnam (east coast). Inland regions such as Gimcheon and Chuncheon also showed notable correlations influenced by topographical factors. The findings highlight the importance of integrating climate teleconnection indices into risk management strategies. This approach allows for targeted monitoring and predictive modeling, enabling proactive responses to water leakage risks and contributing to sustainable urban development.

Aerosol Effects on the Atmosphere: Types, Mechanisms and Future Perspectives

Aerosols, composed of solid or liquid particles suspended in the atmosphere, with complex sources and mechanisms of action, are widely present in both natural environments and human activities. Aerosols directly affect the Earth’s energy balance by scattering and absorbing solar radiation and indirectly affect climate and precipitation patterns by acting as cloud condensation nuclei, altering cloud formation and microphysical properties. This paper discussed the different types of aerosols, including natural, anthropogenic, and hybrid aerosols, and analyzed their physical and chemical properties. This paper also analyzed the direct and indirect climate effects of aerosols in the atmosphere and explored future research directions, including technological innovations, interdisciplinary collaborations and international policy drivers. Future research on aerosols as an important factor in climate change will contribute to a better understanding of its complexity and to strategies to address global climate change.

Spatiotemporal modeling and projection framework of rainfall-induced landslide risk under climate change

Global warming is expected to exacerbate extreme rainfall events, potentially increasing the risk of landslides. While landslides have been extensively studied, much of the focus has been on developing static frameworks for landslide susceptibility, with relatively little exploration of spatiotemporal modeling. Furthermore, previous studies have often overlooked the spatiotemporal impacts of climate change and dynamic socio-economic factors on landslide susceptibility and risk. This has resulted in a lack of understanding of how landslide risk will evolve in the future. Consequently, this study proposes a modeling approach to simulate the dynamics of landslide susceptibility and exposure population over the next 80 years. The approach involves a series of novel modeling experiments using rainfall-induced landslide data collected over the past decade in Jiangxi Province, using a GAMs that considers the effects of spatial relationships and spatio-temporal cross-validation, with an AUC of 0.885 and an error rate of 15.32%, and combining with the CMIP6 precipitation data to the direct effect of climate change on landslide susceptibility. In addition, a dynamic risk prediction model combining static and dynamic populations was developed to provide a more comprehensive understanding of future landslide impacts. This research framework serves as a scientific foundation and valuable reference for comprehending the effects of climate change on landslide hazards and their management in urban planning and risk mitigation. It aims to inform the development of more effective strategies to mitigate potential losses from future landslide risks.

Forest carbon sink in North China increased in recent two decades, but decreased in extreme drought years

ABSTRACT North China is one of China’s most severely warming and drying regions, and understanding the dynamics of forest carbon sinks in North China is critical for forest management in response to climate change. This study examined the spatial and temporal dynamics of forest carbon sinks in North China from 2000 to 2020 using carbon cycle process and soil respiration data, and explored the relationship between the sinks’ spatial and temporal dynamics and changes in major climatic factors, particularly the effects of droughts on the forest sinks. The results showed that forest net ecosystem productivity (NEP) in North China increased significantly at 7.0 gC·m−2·yr−1 over the last 21 years, mainly concentrated along Yanshan (e.g. Hebei Province) and Qinling (e.g. south-central Shaanxi Province) area. Shaanxi had the fastest NEP growth rate, while Henan had the slowest. The spatial distribution of forest NEP in North China decreased with increasing latitude, and the increase in NEP from 2000 to 2010 attained 115 gC·m−2 was higher than that from 2010 to 2020. Moisture is the main climatic factor affecting forest carbon sinks in North China, but there is some spatial heterogeneity in the response patterns to precipitation, drought, and temperature in different regions. Drought levels have dramatically impacted forests in North China, and drought losses and post-drought recovery for NEP increased as drought levels increased. Extreme drought had the greatest impact on the forest NEP, with a loss of up to 93.46 gC m−2, but the recovery from drought was much greater than the loss from drought, the entire increase might be as high as 120 gC·m−2. Forest carbon sinks in North China have superior drought resistance, recovery, and resilience. This study illustrates the impact of conservation measures like afforestation in North China through the dynamic distribution of carbon sinks and also highlights the impacts of drought events with varying severity on forest carbon sinks.

Impacts of Climate-smart Agriculture on Crop Production: A Review

Climate change(CC) factors worldwide have negatively impacted crop production. Temperature, precipitation, and greenhouse gas emissions have influenced soil fertility, irrigation resources, plant physiology, and metabolic activities in crops. Afghanistan has also encountered climate change factors, such as drought, that decreased crop production. A technologically sophisticated solution to the problems facing agriculture due to CC is called Climate-smart Agriculture (CSA). Crop rotation, crop residue management, and soil and water conservation are called Climate-smart Agriculture Practices (CSAP). It is reported that CSAP increased water use efficiency and total water storage by 9–68% and 1–13%, respectively. Furthermore, implementation of CSAP increased wheat yield by 30-45%. Although the adaptability of CSA has been investigated, little is known about the impacts of CSA on crop production. Thus, it is necessary to describe the impacts of CC on crop production and investigate widely. The review was stated to provide some understanding and recommendations on earlier studies on the topic. The review's objective is to determine the optimal CSAP that decreases the adverse effects of CC on crop production. Researchers, consultants to farmers, and policymakers can benefit from synthesizing all this information as it may help provide favorable plans to boost crop production by selecting and using relevant CSAP.

Assessing the relative contribution of climate change and human activity factors to spatiotemporal distributions of sand fixation service in the Loess Plateau

ABSTRACT The Loess Plateau is one of the most severely eroded regions in China. Assessing the spatiotemporal changes in wind erosion control services is of significant importance for the ecological protection of the Loess Plateau. The dynamic changes in these services are primarily influenced by human activities and natural climate changes. However, existing studies lack a quantitative evaluation of the contributions of climate change and human activities to the spatiotemporal changes in wind erosion control services on the Loess Plateau. This study utilized a modified soil wind erosion equation and partial derivative method to investigate the response characteristics of wind erosion control service changes on the Loess Plateau to climatic factors and human activities and quantified the relative contributions of these two driving factors. Additionally, the key threshold points of precipitation and grazing affecting soil wind erosion were found by constraint-line method. The results indicated that the amount of the sand fixation per unit area on the Loess Plateau increased slowly at a rate of 0.05 t·hm−2·a−1 from 2000 to 2013 and then increased at a rate of 0.97 t·hm−2·a−1 from 2013 to 2020. Spatially, 47.55% of the area showed an increasing trend, while 41.32% of the area showed a decreasing trend. Overall, the contribution of climate change to the variation in sand fixation services on the Loess Plateau is greater than that of human activities, but their contributions exhibit spatial heterogeneity. In the A2, B1, and B2 subregions, the decrease in sand fixation services and the increase in the A2 subregion are primarily influenced by human activities. Between 2000 and 2020, the average contributions of wind speed and precipitation to SR (sand fixation per unit area) on the Loess Plateau were 0.243 t·hm-2·a-1 and 0.09 t·hm-2·a-1, respectively, making them the most significant climatic drivers of SR changes. In coal mining areas on the Loess Plateau, the amount of the sand fixation per unit area mainly showed a decreasing trend (52.30%), while the conversion of cropland and unused land to grassland significantly promoted an increase in the amount of sand fixation, accounting for 50.30% of the total increase. After grazing intensity reaches a threshold (around 13.51%–35.84%), SR declines rapidly with further increases in grazing intensity. Various major ecological projects have also significantly promoted the increase in wind erosion control. The study results can provide empirical support and a basis for formulating ecological restoration plans for different ecological zones on the Loess Plateau, as well as for soil wind erosion control in coal mining and grazing areas.

Urban Water-Energy consumption Prediction Influenced by Climate Change utilizing an innovative deep learning method

The growing global demand for water and energy has created an urgent necessity for precise forecasting and management of these resources, especially in urban regions where population growth and economic development are intensifying consumption. Shenzhen, a rapidly expanding megacity in China, exemplifies this trend, with its water and energy requirements anticipated to rise further in the upcoming years. This research proposes an innovative Convolutional Neural Network (CNN) technique for forecasting water and energy consumption in Shenzhen, considering the intricate interactions among climate, socio-economic, and demographic elements. The proposed approach integrates a CNN model with an Enhanced Gorilla Troops Optimization (EGTO) algorithm to demonstrate superior performance compared to other leading methods in terms of accuracy and reliability. The results show a strong correlation between the simulated and observed data, with a correlation coefficient of 0.87 for water consumption and 0.91 for energy consumption, indicating a high level of agreement between the simulated and real-world data. Also, it is indicated that the new technique can accurately forecast water and energy consumption, achieving a mean absolute error (MAE) of 0.63 and a root mean square error (RMSE) of 0.58, respectively. The research indicates that the suggested approach can promote policymakers and stakeholders in making well-informed decisions by delivering precise predictions of water and energy usage. This, in turn, can facilitate better resource distribution, minimize waste, and promote greater sustainability. The study emphasizes the necessity of incorporating climate change and socio-economic factors into the forecasting process and showcases the proposed method’s potential to aid decision-making in this domain.

Projecting temperature-related dengue burden in the Philippines under various socioeconomic pathway scenarios

IntroductionAs climate change advances, the looming threat of dengue fever, intricately tied to rising temperatures, intensifies, posing a substantial and enduring public health challenge in the Philippines. This study aims to investigate the historical and projected excess dengue disease burden attributable to temperature to help inform climate change policies, and guide resource allocation for strategic climate change and dengue disease interventions.MethodsThe study utilized established temperature-dengue risk functions to estimate the historical dengue burden attributable to increased temperatures. Future projections were derived using Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP) scenarios to estimate the excess dengue burden on a national scale. Current health burden estimates were calculated by charting the attributable fraction per epidemiological week against the exponential risk function.ResultsProjections indicate a substantial increase in temperature-related dengue incidence across all SSP climate scenarios by 2100. Between 2010-2019, 72.1% of reported dengue cases in the Philippines were attributable to temperature, demonstrating that temperature is a significant driver in dengue transmission. The highest attributable fractions were observed between the warm-dry season to early rainy season (Epi Weeks 15–25). Southern, periequatorial areas, particularly those undergoing rapid urbanization, had the highest temperature-related dengue incidence.DiscussionThe findings emphasize the critical interplay between climate change and socioeconomic factors in shaping future dengue risk. By incorporating future climate scenarios and provincial-level projections, this study provides valuable insights for policy planning, early warning systems, and public health programming. Strengthening health infrastructure, promoting sustainable urban development, and implementing effective vector control measures are crucial to mitigating the future dengue burden in the Philippines.

System for forecasting the lake dynamics in Russian Arctic using satellite images based on NextGIS Web

The article discusses the important geoecological problem of predicting the dynamics of thermokarst lakes in the Russian Arctic as intensive sources of natural greenhouse gas emissions, which is considered as one of the factors of current climate change. The purpose of the work is to consider the development of a system for forecasting the dynamics of lake areas using entropy-randomized machine learning algorithms and tools of the NextGIS Web geographic information system. The procedure for processing information to predict the dynamics of lakes is considered. Data from remote measurements of the areas of thermokarst lakes in the Arctic zone of Russia, obtained from Landsat satellite images over the past several decades, and climate data determined by reanalysis of meteorological data for the same period are used as retrospective information for forecasting. The system is implemented on the basis of the NextGIS Web geographic information system, which allows the inclusion of randomized modeling applications using the Python language.

METHODS AND TOOLS USED TO INVESTIGATE INTERACTION BETWEEN AEROSOLS AND CLOUDS

The interaction between aerosols and clouds is a relevant factor in global, regional and local climate change. The scientific community is trying to provide relevant theoretical and experimental benchmarks on aerosol loading, cloud formation patterns and trends. Aerosol–cloud interactions play a vital role in global climate change and are associated with one of the greatest uncertainties. In recent decades, due to its unique geographical location, the North Indian Ocean (NIO) has been gaining significant attention among scientific communities. Deep understanding of aerosols and their interaction with clouds in this region is very important both regionally and globally. The paper provides both an overview of the most used methods and tools used in experimental approaches in the field, as well as an analysis methodology regarding aerosol-cloud interaction scenarios.

Assessing the Impacts of Urbanization and Climate Change on NPP Under Different Habitat Quality Conditions over the Last Two Decades in the Tibetan Plateau, China

The processes of urbanization and climate change have exerted a marked influence on net primary productivity (NPP). However, the underlying mechanisms that drive these effects remain intricate and insufficiently understood. The processes of urbanization and climate change both have an adverse effect on habitat quality (HQ) and biodiversity loss. The HQ has a direct influence on the health and stability of ecosystems, which regulate the level of NPP. A higher HQ is associated with stronger NPP. Now, the quantification and assessment of the impacts of climate change and urbanization on NPP are still challenging because of the various driving factors and the intricate mechanisms influencing the production of terrestrial vegetation. Therefore, a new perspective was adopted to study the effects of urbanization and climate change on NPP in the Qinghai–Tibet Plateau in China during 2000–2020. The spatiotemporal analysis method was employed to investigate the impact of the night light urbanization index and climate factors on NPP in different HQ regions (the HQ is divided into five levels, with each area type corresponding to a specific HQ level). Then, the coupled coordination model (CCD) was used to analyze the coupling coordination relationship between NPP and HQ. Finally, the relative contribution of urbanization and climate change to NPP was studied using scenario simulation. The results showed that (1) NPP in the whole Tibetan Plateau increased very little, with an average growth rate of 0.42 g C m⁻2 per year. (2) It was surprising to find that NPP in urban areas did not decline significantly as a result of urbanization. However, there was a notable decline in NPP in higher HQ areas. (3) The mean contribution of urbanization to NPP change was found to be 17%, while the mean contribution of climate change and other factors to NPP change was 69% and 14%, respectively. These findings provide valuable insights into the interactions between human development and environmental factors, enhancing our comprehension of their role in the Tibetan Plateau’s carbon cycle.

Nanotechnology for sustainability of agriculture and environment: Green synthesis and application of nanoparticles – A review

Moreover, with the continuous population increase worldwide, there is more demand of food and other daily necessities, which require double agriculture production to provide adequate food for humanity from the same available natural resources. Therefore, looking for new techniques to combat various challenges is instantly needed to sustain crop production and provide enough food for humanity. The use of nano-technology in agriculture field represents an important tool for consistent production of agriculture crops and assists farmers with new practice management systems such as precision agriculture systems, the aim of which is to increase productivity and reduce expenses. Nanotechnology plays an important role in altering agriculture food production. The particles ranging from 1 to 100 nm are accounted as nanoparticles, which usually have high surface energy, big surface area and quantum quarantine. Most notably, nanoparticles increase crop yield by increasing the effectiveness of agricultural inputs to enable site-targeted, controlled nutrient delivery, assuring the least amounts of agro-inputs needed. Additionally, the main aim in agricultural production is to facilitate plants' faster adaptation to the increasingly severe climate change factors, such as high temperatures, low water availability, salinity, alkalinity and environmental pollution with heavy metals, without jeopardizing the delicate ecosystems that are currently in place. This review illustrates the effect of numerous nanoparticles on diverse plants of many concentrations, sizes and shapes. The molecular and genetic response to NPs, their method of action and their interactions with biomolecules should be the main areas of study in the future.

Water Discharge Change in the Rivers of the South of the Boreal Forest Zone of Eastern European Russia at the End of the Late Holocene and in the Anthropocene: The Vyatka River

Based on long-term observations of the water discharge (WD) from 1878 to 2018, the main trends and patterns of its change in the basin of one of the largest rivers in the east of the East European Plain, the Vyatka River, were revealed using a set of standard statistical procedures and a graphical analysis of the WD probability curves. Three main phases of the annual river WD were identified, corresponding to the periods 1878–1929, 1930–1977, and 1978–2018. The first and third periods were characterized by increased WD (by 22–23%) relative to the medium period, and the differences in the average annual WD characteristics between these periods were statistically significant. It is also noteworthy that the difference in the average annual WD between the first and last periods of increased WD was very small and statistically insignificant. A gradual increase in the share of the so-called normal annual WD and a decrease in the abnormal (including extreme) annual WD were noted from 1878–1929 to 1978–2018 in the predominantly northern half of the river basin. At the same time, in the predominantly southern half of the basin, according to the analysis of only the periods 1930–1977 and 1978–2018, the so-called normal and abnormal WD remained almost unchanged; only a slight increase in positive anomalies of the WD was noted. Increased intra-annual variability in the WD was characteristic of the period of its reduced average annual value. Between the three identified periods, a gradual reduction in the water runoff coefficient was observed during the warm (mainly summer) season in the Vyatka River basin. The specified long-term variability in the water discharge of the Vyatka River was chiefly due to long-term changes in climatic factors, primarily the ratio of the air temperature and precipitation, expressed as the De Martonne aridity index. The duration of the principal cycle of these changes was 82 years. An additional contribution could also have been made by the widespread reduction in cropland in the study region in recent decades. The obtained results can be preliminarily considered representative of the entire southern sector of the boreal forest zone (taiga zone) of the east of the East European Plain.