Influence Of Climatic Factors Research Articles

Dynamics of Scutellaria tuvensis (Lamiaceae) coenopopulations

The dynamics of density, abundance, ontogenetic structure and spatial organization of Scutellaria tuvensis coenopopulations under the influence of climatic factors in different habitat conditions has been studied. The decrease in the climate aridity in the basins of the Republic of Tuva in the last 10 years has a positive effect on the condition of the coenopopulations of S. tuvensis, occurring in dry and deseritied steppes. The coenopopulations of S. tuvensis are normal, stable, and in balance with the ecotope. The dynamics of the number, ecological density, spatial distribution of individuals in the coenopopulations, and the type of ontogenetic spectrum are influenced by climatic factors, while the values of demographic indicators in the coenopopulations are determined by the peculiarities of development of individuals in different habitats. Under a mildening climate (early warm spring and non-dry summer), optimal conditions are created for seed germination and further development of young plants. Recently, an increase in the number of young plants has been found in all habitats, a left-sided type of the ontogenetic spectrum is being formed, and coenopopulations are rejuvenating.

Influence of Climatic Factors on Rust Severity in Sorghum in Dharwad, Karnataka, India

Sorghum rust, caused by Puccinia purpurea, significantly reduces crop yield, affecting plant growth and grain quality. Understanding the impact of weather parameters on disease incidence is crucial for timely disease management, to enhance crop resilience and yield stability. This study aims to identify and quantify the relationship between weather parameters and the incidence of sorghum rust, to inform decision-making on disease management strategies. A comprehensive analysis was conducted utilizing 17 years of secondary data (2006-2022) sourced from the All India Coordinated Research Project (AICRP) on Sorghum and the Department of Agrometeorology at the Climate Model Intercomparison Project (CMIP), University of Agricultural Sciences (UAS), Dharwad. The study employed statistical methods, including Multiple Linear Regression (MLR) and Step-wise Regression, to model the dependence of rust disease incidence on independent variables such as precipitation, temperature, relative humidity, wind speed, radiation, and heat flux. The results revealed the MLR model explains 65.45% of the variation and the Step-wise Regression model identifies four critical parameters- relative humidity, heat flux, wind speed, and radiation that together accounted for 65.09% of the variation without exhibiting multicollinearity (Variance Inflation Factor values below 10). These findings enhance the understanding of environmental impacts on sorghum rust and can inform future agricultural management strategies for disease prediction and control.

Generalized Partially Functional Linear Model with Interaction between Functional Predictors

This paper proposes a generalized partially functional linear model with interaction terms. It is suitable for cases where the response variable is scalar, and the predictor variables include a mix of functional and scalar types, while considering the correlations among functional predictor variables. The model uses principal component analysis for dimensionality reduction, employs maximum likelihood estimation to obtain parameter values, proves the asymptotic properties of the estimates, and validates the model’s accuracy through data simulation experiments. Finally, the proposed model was applied to investigate the influence of air quality, climate factors, and medical and social indicators, along with their interactions, on cancer incidence, which is a binary response.

The application of haplotypes instead of species-level ranks modifies the interpretation of ecological preferences in lichen symbiont interactions in Parmelia

The analysis of the interaction between main bionts (mycobiont and photobiont) in the lichen symbiosis delivers substantial information about their preferences in the selection of symbiotic partners, and their ecological preferences. The selectivity in the Parmelia genus has been defined as strong so far. However, data on this lichen genus, which includes several widely distributed species, are biogeographically limited. Therefore, using specialization indicators and extended sampling, in this study, we estimated the interactions between the main bionts of selected Parmelia spp., using two levels of estimation (species/OTU and haplotype). A comparison of mycobiont-photobiont interactions at different levels showed that considering only mycobiont species and Trebouxia OTUs, greater specialization is found, while Parmelia species studied in this work present a more generalistic strategy in photobiont choice when haplotypes are considered. Despite the uneven sampling of Parmelia species, the interpretation of specialization within species and individuals of the genus leads to a more precise and accurate interpretation of their adaptation strategies. Furthermore, the data from P. sulcata indicate the existence of a different pool of compatible haplotypes in some geographical regions compared to neighboring areas. This observation suggests the potential influence of climatic factors.

Evaluating seasonal variation in macronutrient levels and their impact on water quality in urban coastal waters: A case study in nutrient management along the North Colombo coast of Sri Lanka

Macronutrients are vital for sustaining marine food webs and primary production. However, their overabundance through riverine inflows and untreated wastewater discharges causes adverse ecological changes, especially in developing countries, necessitating effective nutrient management for ecosystem preservation. We assessed macronutrient enrichment and dispersion patterns in the north Colombo coast of Sri Lanka, an urban estuary stressed by untreated wastewater discharge from sewer channels and macronutrients from the Kelani River. Maximum concentrations of NO3−−N, total dissolved nitrogen, PO43−−P and total dissolved phosphorus were 0.085, 0.74, 0.70, and 0.79 mg/L, respectively, while the dissolved oxygen levels and temperature ranged from 6.42 to 8.62 mg/L and from 28.1 to 30.8 0C during January 2023. The estuary was a nitrogen-limited ecosystem, with the Kelani River being the primary source of NO3−−N. Although nutrient levels were within water quality guidelines, understanding how pollutants disperse during a catastrophic discharge is crucial for risk management. Simulated dispersion patterns using Delft3D revealed that NO3−−N and other solutes introduced through the Kelani River accumulate near the breakwaters of the Colombo harbor complex during the Northeast monsoon, primarily due to seasonal wave and wind conditions. The accumulation of the limiting nutrient increased the risk of eutrophication and harmful algal blooms by non-indigenous toxic algae species introduced by untreated ballast water disposal. The findings elucidate the critical role of breakwaters in retaining solutes and emphasize the influence of morphological, climatic, and topographical factors on dispersion patterns in coastal ecosystems. The study provides an example for developing countries to integrate cost-effective monitoring technologies and numerical modelling into coastal management, facilitating data-driven decision making for effective environmental management.

Duration of exposure to compound daytime-nighttime high temperatures and changes in population exposure in China under global warming

Global warming has led to the enhancement of diurnal (daytime-nighttime) compound heat waves, which can severely affect the population’s physical health and productive life; this is particularly the case for vulnerable populations that are more susceptible to psychological and physiological harm with the future normalization of heatwave scenarios. In this study, we attributed the changes in population exposure under diurnal compound high temperatures (HTs) and extremely high temperatures (EHTs) to the influence of climatic (exposure duration) and population factors and their combined influence to determine the relationship between exposure duration and the changes in exposure of vulnerable populations. Diurnal compound HT and EHT covered a land area of 4,016,800 and 1,984,200 km2, respectively. The heat-exposed area spread step-like in all directions, centering on the 24-h high-exposure area with a strong gradient effect. The area of prolonged exposure shifted from the Yellow-Huai-Huai Plain across the geographical boundary between the south and the north to the middle and lower reaches of the Yangtze River Plain. Meanwhile, the average maximum value of vulnerable population exposure reached 186,800 and 93,100 person-h, with high values in Zhengzhou, Chongqing, Wuhan, Chengdu, Beijing, and other cities. Changes in vulnerable population exposure were dominated first by demographic factors and then by climatic factors, with the dominance of climatic factors evident in areas of prolonged exposure. Under prolonged exposure to daytime-nighttime compound EHT, changes in the exposure of child and older populations were dominated by climatic factors with a contribution rate of 87.16% and 87.43%, respectively. Therefore, suitable cooling measures should be proposed for vulnerable populations under prolonged exposure, focusing more on the physical and mental health of children and older adults exposed to compound EHT.

Predicting rice phenology across China by integrating crop phenology model and machine learning

This study explores the integration of crop phenology models and machine learning approaches for predicting rice phenology across China, to gain a deeper understanding of rice phenology prediction. Multiple approaches were used to predict heading and maturity dates at 337 locations across the main rice growing regions of China from 1981 to 2020, including crop phenology model, machine learning and hybrid model that integrate both approaches. Furthermore, an interpretable machine learning (IML) using SHapley Additive exPlanation (SHAP) was employed to elucidate influence of climatic and varietal factors on uncertainty in crop phenology model predictions. Overall, the hybrid model demonstrated a high accuracy in predicting rice phenology, followed by machine learning and crop phenology models. The best hybrid model, based on a serial structure and the eXtreme Gradient Boosting (XGBoost) algorithm, achieved a root mean square error (RMSE) of 4.65 and 5.72 days and coefficient of determination (R2) values of 0.93 and 0.9 for heading and maturity predictions, respectively. SHAP analysis revealed temperature to be the most influential climate variable affecting phenology predictions, particularly under extreme temperature conditions, while rainfall and solar radiation were found to be less influential. The analysis also highlighted the variable importance of climate across different phenological stages, rice cultivation patterns, and geographic regions, underscoring the notable regionality. The study proposed that a hybrid model using an IML approach would not only improve the accuracy of prediction but also offer a robust framework for leveraging data-driven in crop modeling, providing a valuable tool for refining and advancing the modeling process in rice.

MIDDLE PLEISTOCENE NEOTECTONIC ACTIVATION OF THE MOUNTAIN BORDERING THE MUYA-KUANDA RIFT VALLEY (BAIKAL RIFT ZONE)

Geological and geomorphological studies of the northeastern branch of the Baikal rift zone have revealed structural features of sedimentary strata, as well as the features of lithology and interaction of heterochronous loose sedimentary complexes, block structure of rift valley bottoms and their mountain border, fault network, and activated Cenozoic faults. The Middle Pleistocene neotectonic uplift was identified on the southern slopes of the North Muya and the Kodar ranges and in the mountains bordering the Muya-Kuanda and Parama rift valleys. The authors have studied the parameters of this uplift, determined neotectonic movement amplitudes in the uplift areas, traced the marginal disjunctives and the kinematics of their movements, and identified homochromous sedimentary strata and determined their formation age.The activation of tectonic processes, during which the neotectonic uplift was formed, occurred in the early Middle Pleistocene, before the onset of glaciation. The formation of a dammed lake in the system of Muya-Kuanda rift valleys is associated with the tectonic damming of the Vitim River. During the Middle Pleistocene glaciation, the Kodar Range glaciers have twice formed the ice dams in the area of Lake Oron, which led to the emergence of dammed lakes in the Vitim valley connected with lakes in the Muya-Kuanda troughs. The shoreline of these lakes is preserved as a high rock terrace with an absolute height of 860±10 m along the perimeter of the rift valleys.In the Late Pleistocene, the terrace complex in the Muya-Kuanda rift valleys was mainly formed under the influence of climatic factor.

Global analysis of soil bacterial genera and diversity in response to pH

Soil pH stands as a decisive factor in shaping bacterial diversity and community composition, yet predicting the pH preferences and traits of individual bacterial taxa is still incomplete. We surveyed 942 samples from seven biomes worldwide to unravel the responses of individual bacterial genus to soil pH. Our findings indicate that soil pH surpasses the influences of spatial and climatic factors (biomes) in affecting bacterial composition and diversity. We observed that a comparable proportion of genera had low pH optima (21%), high pH optima (18%), and neutral pH optima (18%). However, apart from genera with optima groups, only a small percentage of genera were low pH tolerant (0.8%) compared to those that were high pH tolerant (21%). This suggests that a greater number of non-extremophiles genera can tolerate alkaline conditions compared to acidic conditions. Bacterial richness forms unimodal relationship with soil pH, consistently increasing from acidic levels to neutral across all biomes. However, the decline in richness when pH rises beyond neutral was less pronounced. This can be attributed to the higher number of alkaline-tolerant genera compared to acidic-tolerant genera. As expected, genera with acidic optima are more prevalent in humid climates, such as tropical forests, arctic tundra, and boreal forests, whereas genera with alkaline optima are generally dominant in arid grasslands and drylands. Collectively, our results indicate that the probability of existence of at least 75% of genera in specific soil pH conditions can be predicted, irrespective of biome. The identification of the actual niche spaces occupied by individual soil bacterial genera forms the foundation for developing comprehensive hypotheses regarding the response of soil communities to changing soil conditions worldwide.

Investigating the impact of climate variables on the organic honey yield in Turkey using XGBoost machine learning.

The Turkish organic honey industry, a major player in the global market, faces challenges due to climate fluctuations. Understanding the influence of climate factors on honey production is vital for sustainable farming and economic stability. This study uses a machine learning approach with the XGBoost algorithm to analyze temperature, wind, humidity, precipitation and surface pressure over a 20-year period from 2004 to 2023. The results show that these factors significantly impact organic honey production, with temperature, wind, humidity, precipitation and surface pressure having effects of 41.20%, 26.50%, 12.47%, 11.42% and 8.41%, respectively. Sensitivity analysis reveals the model's sensitivity to even minor fluctuations in these variables. The results of this research underscore the necessity of integrating climate change mitigation and adaptation measures into agricultural policies and beekeeping practices. This study showcases the practical application of machine learning in deciphering the intricate relationship between climate change and the production of crops, emphasizing the importance of data-driven decision-making to guarantee long-term sustainability and financial stability in the sector. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Islands of ice: Glacier‐dwelling metazoans form regionally distinct populations despite extensive periods of deglaciation

AbstractAimGlaciers cover considerable portion of land and host diverse life forms from single‐celled organisms to invertebrates. However, the determinants of diversity and community composition of these organisms remain underexplored. This study addresses the biogeography, population connectivity and dispersal of these organisms, especially critical in understanding during the rapid recession of glaciers and increased extinction risk for isolated populations. By reconstructing the Quaternary biogeographic history of Fontourion glacialis, a widespread in Northern Hemisphere glacier obligate species of Tardigrada, we aim to understand how populations of glacier‐dwelling metazoans receive immigrants, respond to disappearing glaciers and to what extent remaining glaciers can serve as refugia.LocationGlaciers across Svalbard, Scandinavia, Greenland and Iceland.MethodsWe analysed mtDNA (COI gene) variability of 263 F. glacialis specimens collected across the distribution range. Phylogeographic and coalescent‐based approaches were used to detect population differentiation patterns, investigate most likely models of gene flow and test the influences of geographical and climatic factors on the distribution of F. glacialis genetic variants.ResultsOur findings indicate that the distribution of F. glacialis genetic variants is primarily influenced by geographical rather than climatic factors. Populations exhibit a dispersal‐limited distribution pattern, influenced by geographical distance and local barriers, even between neighbouring glaciers. Significantly, the genetic structure within Scandinavia suggests the existence of “southern” glacial or low‐temperature refugia, where F. glacialis may have survived a period of extensive deglaciation during the Holocene climatic optimum (8–5 kyr ago).Main ConclusionThe study uncovers complex metapopulation structures in F. glacialis, with impacts of local barriers, population bottlenecks as well as historical ice sheet fluctuations. It suggests that such populations can endure extended periods of deglaciation, highlighting the resilience of glacial refugia. The study highlights the necessity of understanding the diversity and population structure of ice‐dwelling fauna in both spatial and temporal contexts.

The Influence of Climatic and Anthropogenic Factors on the Productivity of Forest Stands in the Ecotone of the Northern Treeline on the Yamal Peninsula

The Influence of Climatic and Anthropogenic Factors on the Productivity of Forest Stands in the Ecotone of the Northern Treeline on the Yamal Peninsula

Modelling the Influence of Climate and Vector Control Interventions on Arbovirus Transmission.

Most mathematical models that assess the vectorial capacity of disease-transmitting insects typically focus on the influence of climatic factors to predict variations across different times and locations, or examine the impact of vector control interventions to forecast their potential effectiveness. We combine features of existing models to develop a novel model for vectorial capacity that considers both climate and vector control. This model considers how vector control tools affect vectors at each stage of their feeding cycle, and incorporates host availability and preference. Applying this model to arboviruses of veterinary importance in Europe, we show that African horse sickness virus (AHSV) has a higher peak predicted vectorial capacity than bluetongue virus (BTV), Schmallenberg virus (SBV), and epizootic haemorrhagic disease virus (EHDV). However, AHSV has a shorter average infectious period due to high mortality; therefore, the overall basic reproduction number of AHSV is similar to BTV. A comparable relationship exists between SBV and EHDV, with both viruses showing similar basic reproduction numbers. Focusing on AHSV transmission in the UK, insecticide-treated stable netting is shown to significantly reduce vectorial capacity of Culicoides, even at low coverage levels. However, untreated stable netting is likely to have limited impact. Overall, this model can be used to consider both climate and vector control interventions either currently utilised or for potential use in an outbreak, and could help guide policy makers seeking to mitigate the impact of climate change on disease control.

Beta diversity patterns and driving mechanisms of stream bacteria and fungi on Mt. Kilimanjaro

Aquatic microbes, which are highly diverse in freshwater biofilms, play a vital role in shaping the structure and functioning of ecosystems. Nevertheless, the influence of environmental factors on aquatic microbes in different biogeographic ecosystems, especially in tropical mountains, is relatively unexplored. Here, we examined the relative influence of climate and physicochemical factors on beta diversity of stream bacteria and fungi using 16S rRNA amplicon sequencing at 40 sites on Mt. Kilimanjaro. Towards larger elevational distance, the total beta diversity and turnover of bacteria and fungi increased significantly, while nestedness decreased. The beta diversity of fungi showed greater spatial variation than that of bacteria, while the local contribution to beta diversity (LCBD) showed U-shaped elevational pattern for both taxa. Bacteria and fungi had strong positive relationships regarding the total beta diversity, LCBD and their components, except for nestedness, indicating similar environmental preferences and resource overlap. Among environmental variables, mean annual temperature, water depth and elevation predicted microbial beta diversity, while water depth, mean annual temperature and precipitation primarily affected LCBD. Overall, climate-related variables were the dominant factors for beta diversity and their effects were more pronounced for fungi than bacteria. The contrasting patterns of bacterial and fungal beta diversity and their ecological interactions in tropical aquatic ecosystems provide a rare dataset for assessing ecological functions in understudied aquatic ecosystems and predicting the impact of global change on microorganisms.

Progress in analytical methods for pesticide detection in palm oil and palm kernel oil matrices, and pesticide fate studies in oil palm plantations

AbstractThis review presents a comprehensive overview of instrumental analyses for both single‐component and multicomponent pesticide detection within palm oil matrices. It meticulously examines the analytical attributes of these methods across various pesticide categories, including insecticides, herbicides, and fungicides. The discussion extends to sample preparation methodologies tailored for palm oil, encompassing techniques such as low‐temperature precipitation followed by solid‐phase extraction, liquid–liquid extraction, and variations of the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method. Additionally, it explores the QuEChERS method employing different sorbent combinations to optimize extraction efficiency. The second part of the review focuses on the fate study of pesticides within oil palm plantations which covers laboratory‐scale simulations elucidating pesticide behavior, comparative analysis of field studies with predictive programs, and investigations into the influence of climatic and microbiological factors on pesticide persistence within the oil palm agroenvironment system.

Investigating the temporal lag and accumulation effect of climatic factors on vegetation photosynthetic activity over subtropical China

Monitoring vegetation photosynthesis in China’s subtropical regions using remote sensing is challenging because of the complex ecosystems and climate variability. Previous studies often pay less attention on the influence of multiple climatic factors on the temporal effects (lag and accumulation) of vegetation photosynthesis, thereby underestimating their impact. This study utilizes a dataset comprising Solar-induced chlorophyll fluorescence (SIF) data (GOSIF product), MODIS Land Cover product (MCD12C1), and various climatic variables. Analytical methods including Theil-Sen Median trend analysis, the Mann-Kendall test, partial correlation analysis, and the optimal parameter-based geographical detector (OPGD) model were employed to explore the temporal dynamics of subtropical vegetation SIF responses to climatic factors and to identify their climate drivers in subtropical China. The study findings indicate that (1) vegetation photosynthesis, as indicated by SIF, exhibited an increasing trend in the majority of Chinese subtropical regions, which constitute over 80 % of the study area, with particularly pronounced enhancements in the southern and central western parts of the Chinese subtropics. (2) Soil moisture primarily exhibits lag effects on SIF, particularly in evergreen needleleaf forests, deciduous broadleaf forests, and mixed forests, whereas temperature does not exhibit significant temporal effects. Solar radiation and vapor pressure deficits impact SIF through both lag and accumulation effects. Under the lag and accumulation effects, the proportion of significant correlations between climatic factors and vegetation SIF increases by 36.71 % ∼ 43.8 %, excluding temperature. (3) Temperature is the dominant factor affecting vegetation SIF, particularly in the evergreen needleleaf forest. Interactions between climatic factors have a significantly stronger influence on SIF than individual factors. Notably, the explanatory power of the vapor pressure deficit increases substantially when it interacts with other factors. Studying the lag and accumulation effects of climatic factors on photosynthesis aids in accurately predicting vegetation responses to climate change, thereby improving the accuracy of global carbon cycle models and guiding the development of carbon sequestration management strategies.

The influence of climatic and human-induced factors on the spatial distribution of invasive plant species richness across the Loess Plateau

Biological invasion poses a critical global issue, leading to substantial detrimental impacts on biodiversity, the environment, and the economy. The objective of the study is to offer a thorough understanding of how both climatic and human-induced elements impact the geographic richness of invasive plant species across the Loess Plateau. We evaluate the distribution of invasive plant species at the county level across the Loess Plateau by examining herbarium records from China. We incorporate 16 climatic and anthropogenic variables to depict the local environmental settings. Furthermore, we apply a classification and regression tree approach to investigate the correlation between the richness of invasive plant species and the identified factors. Our study demonstrates that a total of 401 invasive plant species are identified, which are spread across 249 genera and 61 families. Among these, the Asteraceae family stands out as the most prevalent, trailed by Poaceae and Fabaceae. The spatial distribution of invasive plant species richness reveals a notable trend, with the highest frequencies found in the southeastern parts of the region and the lowest in the northwestern areas. It is noteworthy that regions with higher levels of economic advancement tend to harbor a more significant abundance of invasive plant species. The richness of invasive plant species on the Loess Plateau is predominantly shaped by a combination of climatic and human variables, such as annual precipitation, gross domestic product, maximum temperature of warmest month, and minimum temperature of coldest month. To fully comprehend the ecological and biological mechanisms underlying the diversity of invasive plant species on the Loess Plateau, a pioneering conceptual framework has been established. Our study suggests that achieving a harmonious equilibrium among development, conservation, and invasion mitigation is essential for recognizing emerging risks associated with habitat alterations, climate change, and socio-economic advancements in arid regions.

Research on improving the efficiency of electricity transmission

A study of ways to modernize the current-carrying part of overhead lines to improve the efficiency of electricity transmission through the use of innovative types of wires was conducted. The technical and economic characteristics of AC, ACCR, and AERO-Z wires were analyzed. The results of the analysis revealed that further improvement of the design of AC wires should be based on new progressive developments that would meet such technical requirements as reliability, survivability and durability; corrosion resistance; high adhesion ability; resistance to vibration during operation under the influence of adverse climatic factors; resistance to environmental temperature effects. As an innovative solution to this issue, high-temperature (ACCR) and specially designed (AERO-Z) wires have been developed in foreign countries. A comparative analysis of the types of wires used in Ukrainian power grids with innovative types of wires used in power grids of foreign countries was performed. The results of the comparison of AC, ACCR, and AERO-Z wires show that the factor that limits the scope of application of ACCR wire, even for spans with extremely high requirements for power transmission characteristics, is its extremely high cost. This is because the technical characteristics of this wire are better than those of AC wire and it has a relatively low cost compared to ACCR wire, and its special design is adapted to adverse climatic conditions that affect the characteristics of electricity transmission.

Statistical investigation of climate and landfill age impacts on Kupferberg landfill leachate composition: one-way ANOVA analysis

This study investigated seasonal variations in the physico-chemical properties of leachate from the Kupferberg landfill site, examining the influence of landfill age and climatic factors. Data provided by the Windhoek Municipality during the years 2017 to 2022 facilitated the exploration of critical concerns related to groundwater protection and human health. Guided by two research questions and anchored in hypotheses tested at a 95% confidence level, the study employed Statistical Packages for Social Scientists (SPSS) for analysis.Significant temperature variations were observed across years [F (5, 21) = 4.493, p < 0.05], indicating a substantial relationship between landfill age and seasonal variations in leachate physico-chemical properties. Further ANOVA tests revealed temperature trends impacting leachate parameters, such as organic content and pH. While COD displayed a declining trend with landfill age, inorganic components like Cl- and alkalinity exhibited no distinct age-related pattern.Wet seasons demonstrated higher EC and Cl--mean values than dry seasons, correlating with elevated COD levels. The study underscored the incremental rise in parameter values over time and during the rainy season, attributed to solid waste degradation and rainwater percolation. Notably, climatic conditions significantly influenced seasonal variations in leachate physico-chemical properties (p < 0.05). Based on this outcome, null hypothesis 1 was rejected. The second null hypothesis was also rejected because climatic conditions do influence the seasonal variations in physico-chemical properties. These findings are crucial for emphasizing the need for effective leachate management strategies and providing valuable insights for arid regions. Future research can expand on a national scale, employing one-way ANOVA tests on other landfills in Namibia, and engaging local communities for comprehensive data collection on cross-contamination.

Temporal and spatial evolution of net primary productivity in the Three-River Headwaters Region under phenological changes and anthropogenic influence.

Understanding the spatiotemporal changes in net primary productivity (NPP) and the driving factors behind these changes in climate-vulnerable regions is crucial for ecological conservation. This study simulates the actual NPP (NPPA) and climate potential NPP (NPPC) in the Three-River Headwaters Region from 2000 to 2020. The Theil-Sen Median method and Mann-Kendall mutation analyses are employed to explore their spatiotemporal variation patterns, while geographic weighted regression and machine learning are used to investigate the influence of anthropogenic activities and climatic factors on NPPA, the results indicate that the average NPPA across the entire region over multiple years is 382.506 , which is 0.132 times the average annual NPPC over the past 21years, showing an overall distribution pattern of low in the northwest and high in the southeast. The annual increase in NPPA from 2000 to 2020 is approximately 1.034 . The source region of the Yangtze River shows the largest improvement in vegetation, with 74.1% of the area showing improvement. Between 2002 and 2003, the annual NPPA in the Three-River Headwaters Region experienced a sudden change, lagging behind the NPPC change by 1year, and after 2005, the upward trend in NPPA became more pronounced. The impact of anthropogenic activities on NPPA shifted from positive to negative to positive from 2000 to 2020, with significant impact areas mainly concentrated in the northeast and a few areas in the central and southern parts. The proportion of areas with extremely significant impact increased from 1.9% in 2000 to 3.7% in 2020. Over the past 21years, the main factors influencing NPPA changes in the Three-River Headwaters Region have been soil moisture and precipitation, with the influence of different climate factors on NPP changing over time. Additionally, NPP is more sensitive to changes in altitude in low-altitude areas. This study can provide more accurate theoretical support for ecological environment assessment and subsequent protection efforts in the Three-River Headwaters Region.