Search Results (1,169)

The ecosystem water use efficiency (WUE) plays a critical role in many aspects of the global carbon cycle, water management, and ecological services. However, the response mechanisms and driving processes of WUE need to be further studied. This research was conducted based on Gross Primary Productivity (GPP), Evapotranspiration (ET), meteorological station data, and land use/cover data, and the methods of Ensemble Empirical Mode Decomposition (EEMD), trend variation analysis, the Mann–Kendall Significant Test (M-K test), and Partial Correlation Analysis (PCA) methods. Our study revealed the spatio-temporal trend of WUE and its influencing mechanism in the Yellow River Basin (YRB) and compared the differences in WUE change before and after the implementation of the Returned Farmland to Forestry and Grassland Project in 2000. The results show that (1) the WUE of the YRB showed a significant increase trend at a rate of 0.56 × 10⁻² gC·kg⁻¹·H₂O·a⁻¹ (p < 0.05) from 1982 to 2018. The area showing a significant increase in WUE (47.07%, Slope > 0, p < 0.05) was higher than the area with a significant decrease (14.64%, Slope < 0, p < 0.05). The region of significant increase in WUE in 2000–2018 (45.35%, Slope > 0, p < 0.05) was higher than that of 1982–2000 (8.23%, Slope > 0, p < 0.05), which was 37.12% higher in comparison. (2) Forest WUE (1.267 gC·kg⁻¹·H₂O) > Cropland WUE (0.972 gC·kg⁻¹·H₂O) > Grassland WUE (0.805 gC·kg⁻¹·H₂O) under different land cover types. Forest ecosystem WUE has the highest rate of increase (0.79 × 10⁻² gC·kg⁻¹·H₂O·a⁻¹) from 2000 to 2018. Forest ecosystem WUE increased by 0.082 gC·kg⁻¹·H₂O after 2000. (3) precipitation (37.98%, R > 0, p < 0.05) and SM (10.30%, R > 0, p < 0.05) are the main climatic factors affecting WUE in the YRB. A total of 70.39% of the WUE exhibited an increasing trend, which is mainly attributed to the simultaneous increase in GPP and ET, and the rate of increasing GPP is higher than the rate of increasing ET. This study could provide a scientific reference for policy decision-making on the terrestrial carbon cycle and biodiversity conservation. Full article

Fractional vegetation cover (FVC) is an important indicator of regional ecological environment change, and quantitative research on the spatial and temporal distribution of FVC and the trend of change is of great significance to the monitoring, evaluation, protection, and restoration of regional ecology. This study estimates the FVC of the eastern Tibetan Plateau margin from 2000 to 2020 using the image element dichotomous model based on the Google Earth Engine platform using MODIS-NDVI images. It also investigates the temporal and spatial changes of the FVC in this region and its drivers using the Theil–Sen and Mann–Kendall trend tests, spatial autocorrelation analysis, geodetector, and machine learning approaches impact. The results of this study indicated a generally erratic rising tendency, with the Min River Basin (MRB) near the eastern tip of the Tibetan Plateau having an annual average FVC of 0.67 and an annual growth rate of 0.16%. The percentage of places with better vegetation reached 60.37%. The regional FVC showed significant positive spatial autocorrelation and was clustered. Driver analyses showed that soil type, DEM, temperature, potential evapotranspiration, and land use type were the main drivers influencing FVC on the eastern margin of the Tibetan Plateau. In addition, the random forest (RF) model outperformed the support vector machine (SVM), backpropagation neural network (BP), and long short-term memory network (LSTM) in FVC regression fitting. In summary, this study shows that the overall FVC in the eastern margin of the Tibetan Plateau is on an upward trend, and the regional ecological environment has improved significantly over the past two decades. Full article

Maize, regarded as a staple economic crop, attracts special global attention with the aim to enhance its production. Foliar fertilisation offers a complementary method to traditional soil fertilisation amongst resource-limited agricultural systems, providing a more efficient solution to nutrient deficiencies, especially in suboptimal soil conditions. This study aimed to analyse foliar fertiliser formulation research directions and their application in maize production. A literature search was conducted in the Web of Science (WoS) database. Bibliometric analyses were performed using the VOSviewer software (version 1.6.17). The changes in the publication trends of documents were tested using the Mann–Kendall test. The production effects of foliar fertilisation were independently synthesised. The results showed a strong positive increase in publication trends regarding maize foliar fertilisation (R² = 0.7842). The predominant nutrients that affected maize production were nitrogen, phosphorous, potassium, zinc, iron, and manganese. The timely foliar application of nutrients corrected deficiencies and/or sustained nutrient supply under several abiotic stresses. Foliar application at critical growth stages like flowering and grain filling boosted carbohydrate and protein content, lipid levels, kernel size, mineral content, and the weight of the maize grain. This review identified important research gaps, namely genotype-specific responses, interactions with other agronomic practices, and long-term environmental effects. Full article

Climate change is reshaping water systems and trends in hydro-climatic variables, such as temperature, precipitation, and river runoff, providing critical insights into the hydrological shifts influenced by climate change. However, the impact of climate variability on these variables varies by geographic location, making it necessary to study hydro-climatic variations in the Mediterranean’s changing climate to determine its impacts. This study analyzed the hydro-climatic trends in the Aterno-Pescara River watershed in central Italy from 1936 to 2013. We employed linear regression, Mann–Kendall, Sen’s slope, and Spearman correlation tests to estimate annual and seasonal trends. The results showed a significant warming trend on annual (0.037 °C/year) and seasonal time scales. Precipitation trends exhibited significant reductions annually, specifically during the autumn season, with a decrease of −0.68 mm/year; while showing a decline, other seasons were statistically insignificant. River runoff revealed drying trends annually and seasonally, decreasing by −0.29 m³ s⁻¹/year over the study period. Furthermore, linear regression and Spearman correlation coefficients suggested a significant relationship between hydro-climatic variables with varying strengths (at 95% and 99% confidence levels) annually and seasonally. This decrease in precipitation and river runoff trends with the continuous rate points towards potential meteorological and hydrological droughts occurring in the future in this watershed. This study’s findings provide scientific grounds that could help develop sustainable strategies in the watershed. Full article

Background: disordered eating (DE) and eating disorders (ED) can negatively impact athletes’ health, wellbeing, and athletic performance. Objective: this cross-sectional study aims to assess DE risk, body composition, and nutrition knowledge among elite Hungarian athletes. Methods: DE risk was assessed using DESA-6H and EAT-26 scales, nutrition knowledge through the Abridged Nutrition for Sport Knowledge Questionnaire (A-NSKQ), and body composition with the OMRON BF511 device. The data were analyzed using Kendall’s tau correlations, Mann–Whitney U tests, and ROC analysis. Results: a total of 71 athletes participated (39.4% males, mean age = 24.8 years, SD = 4.8 years and 60.6% females, mean age = 24.3 years, SD = 4.3 years). At-risk scores on the DESA-6H scale were recorded for nine athletes (12.7%), while 32.4% scored in the risk zone on the EAT-26, with female athletes in aesthetic, endurance and weight-dependent sports being most affected. Low BF was observed in four males and four females. Nutrition knowledge (49.1%) was below the acceptable threshold. DESA-6H significantly correlated with EAT-26 scores, BMI, sports nutrition knowledge, and A-NSKQ total scores. A statistically significant difference by gender was found in the EAT-26 total score (p = 0.019, d = 0.65). Risk groups significantly differed in A-NSKQ scores (p = 0.026, d = 0.511) and sport nutrition knowledge, specifically (p = 0.016, d = 0.491). Using EAT-26 to identify at-risk athletes and the DESA-6H recommended cut-off, the ROC analysis showed a sensitivity of 29.1% and a specificity of 95.7%. Conclusions: insufficient nutrition knowledge plays a role in being at-risk for DE and ED. These results underscore the need for early detection, early sport nutrition education across all elite athletes, with particular attention to female athletes in aesthetic, endurance and weight-dependent sports, and for monitoring these athletes to prevent DE. Further work is warranted to optimize screening tools such as EAT-26 and DESA-6H for elite athletes. Full article

Severe hydroclimatic events affect ecosystems and human livelihoods, creating significant challenges for managing water resources. This study analyzed the rainfall and river flow trends in the Bani River Basin (BRB) from 1991 to 2020. Using indices such as the maximum rainfall over a one-day period (RX1DAY), maximum rainfall over a five-day period (RX5DAY), rainfall exceeding the 95th percentile (R95P), simple daily precipitation intensity (SDII), and peak discharge (Qmax), the modified Mann–Kendall test and Pettitt’s test were applied to assess the trends and identify potential breakpoints. The results revealed spatial variability, with southern regions showing reduced rainfall, while northeastern areas exhibit increasing extreme rainfall and river flow. The RX5DAY declined significantly after 2000, reflecting reductions in prolonged rainfall events, followed by the RX1DAY, which declined significantly after 2012, indicating a reduction in short-duration extremes. In contrast, the R99P, SDII, and Qmax exhibited positive trends, indicating intensifying rainfall intensity and extremes in discharge. A notable breakpoint was detected in 1993, marking a transition to increased extreme flows. The highest values of the rainfall indices (R95P, R99P, RX1DAY, RX5DAY, SDII) were concentrated in the southern part of the basin, while the north recorded lower values. These results highlight the basin’s vulnerability to climate variability and provide insights into hydroclimatic changes, serving as a basis for informed decision-making and future research. Full article

The objective of this study was to analyze the climate change experienced in Spain between 1971 and 2022 and to estimate the future climate (2050). The main objectives were as follows: (1) to analyze the temporal evolution of temperature from 1971 to the present, to quantify the warming process experienced in the case study and to evaluate the increase in extreme heat events (heatwaves); (2) to study the evolution of the precipitation regime to determine whether there is a statistically representative trend towards a drier climate and an increase in extreme precipitation; (3) to investigate the interaction between annual precipitation and the continuous increase in temperature; and (4) to estimate the future climate scenario for mainland Spain and the Balearic Islands towards 2050, analyzing the trends in land aridity and predicting a possible change from a Mediterranean climate to a warm steppe climate, according to the Köppen classification. The aim of this study was to test the hypothesis that the increase in temperature resulting from the global warming process implies a tendency towards progressive drought. Given the extreme annual variability of the climate, in addition to the ordinary least squares methodology, the techniques mainly used in this study were the Mann–Kendall test and the Kendall–Theil–Sen (KTS) regression. The Mann–Kendall test confirmed the very high statistical significance of the relationship between precipitation (RR) and maximum temperature (TX). If the warming trend experienced in recent years (1971–2022) continues, it is foreseeable that, by 2050, there will be a reduction in precipitation in Spain of between 14% and 23% with respect to the precipitation of the reference period (understood as the average between 1971 and 2000). Spain’s climate is likely to change from Mediterranean to warm steppe in the Köppen classification system (from “C” to “B”). Full article

This study utilizes NASA’s Normalized Difference Vegetation Index (NDVI) data from the Google Earth Engine (GEE) platform and employs methods such as mean analysis, trend analysis, and the Hurst index to assess NDVI dynamics in Xinjiang, with a particular focus on desert, meadow, and grassland vegetation. Furthermore, multiple linear regression, random forest, support vector machines, and XGBoost models are applied to construct and evaluate the NDVI prediction models. The key driving forces are identified and ranked based on the results of the optimal model. Changes in the vegetation cover in response to these driving forces are analyzed using the Mann–Kendall test and partial correlation analysis. The results indicate the following: (1) From 2000 to 2023, the annual variation in NDVI in Xinjian fluctuates at a rate of 0.0012 per year. The intra-annual trend follows an inverted U shape, with meadow vegetation exhibiting the highest monthly NDVI fluctuations. (2) During this period, the annual average NDVI in Xinjiang ranges from 0 to 0.3, covering 74.74% of the region. Spatially, higher NDVI values are observed in the north and northwest, while lower values are concentrated in the south and southeast. (3) The overall slope of the variation in NDVI in Xinjiang between 2000 and 2023 ranges between −0.034 and 0.047, indicating no significant upward trend. According to the Hurst index, future projections suggest a shift from vegetation improvement to potential degradation. (4) Machine learning models are developed to predict NDVI, with random forest and XGBoost showing the highest precision. Soil moisture, runoff, and potential evaporation are identified as key drivers. In the last 24 years, the temperatures in Xinjiang have generally increased, while precipitation, soil moisture, and runoff have declined. There is a significant negative correlation between NDVI and both temperature and potential evaporation, while the correlation between NDVI and precipitation, soil moisture, and runoff is positive and significant, with distinct spatial variations throughout the region. The overall trend of vegetation cover in Xinjiang has been increasing, but the future outlook is less promising. Enhanced environmental monitoring and protective measures are essential moving forward. Full article

Drought presents significant challenges in arid regions, influencing local climate and environmental dynamics. While the large-scale climatic phenomena in Xinjiang, northwest China, are well-documented, the finer-scale climatic variability in subregions such as the Ili River Valley (IRV) remains insufficiently studied. This knowledge gap impedes effective regional planning and environmental management in this ecologically sensitive area. In this study, we analyze the spatiotemporal evolution of drought in the IRV from 1961 to 2023, using data from ten meteorological stations. The SPEI drought index, along with Sen’s trend analysis, the Mann–Kendall test, the cumulative departure method, and wavelet analysis, were employed to assess drought patterns. Results show a significant drying trend in the IRV, starting in 1995, with frequent drought events from 2018 onwards, and no notable transition year observed from wet to dry conditions. The overall drought rate was −0.09 per decade, indicating milder drought severity in the IRV compared to broader Xinjiang. Seasonally, the IRV experiences drier summers and wetter winters compared to regional averages, with negligible changes in autumn and milder drought conditions in spring. Abrupt changes in the drying seasons occurred later in the IRV than in Xinjiang, with delays of 21 years for summer, and over 17 and 35 years for spring and autumn, respectively, indicating a lagged response. Spatially, the western plains are more prone to aridification than the central and eastern mountainous regions. The study also reveals significant differences in drought cycles, which are longer than those in Xinjiang, with distinct wet–dry phases observed across multiple time scales and seasons, emphasizing the complexity of drought variability in the IRV. In conclusion, the valley exhibits unique drought characteristics, including milder intensity, pronounced seasonal variation, spatial heterogeneity, and notable resilience to climate change. These findings underscore the need for region-specific drought management strategies, as broader approaches may not be effective at the subregional scale. Full article

The accurate assessment of water availability throughout the cassava cropping season (the initial, developmental, mid-season, and late stages) is crucial for mitigating the impacts of climate change on crop production. Using the Mann–Kendall Test, we investigated the trends in rainfall and cassava crop evapotranspiration (ETc) within the Cross River basin in Nigeria. Reference evapotranspiration (ETo) was based on two approaches, namely Artificial Neural Network (ANN) modelling and three established empirical models—the Penman–Monteith (considered the standard method), Blaney–Morin–Nigeria (BMN), and Hargreaves–Samani (HAG) models. ANN predictions were performed by using inputs from BMN and HAG parameters, denoted as BMN-ANN and HAG-ANN, respectively. The results from the ANN models were compared to those obtained from the Penman–Monteith method. Remotely sensed meteorological data spanning 39 years (1979–2017) were acquired from the Climatic Research Unit (CRU) to estimate ETc, while cassava yield data were acquired from the International Institute of Tropical Agriculture (IITA), Ibadan. The study revealed a significant upward trend in cassava crop ETc over the study period. Additionally, the ANN models outperformed the empirical models in terms of prediction accuracy. The BMN-ANN model with a Tansig activation function and a 3-3-1 architecture (number of input neurons, hidden layers, and output neurons) achieved the highest performance, with a coefficient of determination (R²) of 0.9890, a root mean square error (RMSE) of 0.000056 mm/day, and a Willmott’s index of agreement (d) of 0.9960. There is a decreasing trend in cassava yield in the region and further analysis indicated potential average daily water deficits of approximately −1.1 mm/day during the developmental stage. These deficits could potentially hinder root biomass, yield, and overall cassava yield in the Cross River basin. Our findings highlight the effectiveness of ANN modelling for irrigation planning, especially in the face of a worsening climate change scenario. Full article

Analyzing the spatial and temporal changes in the carbon budget and its influencing factors is the basis for formulating effective measures to reduce emissions and increase sinks. This study establishes a carbon budget assessment model for forest enterprises, calculating forest carbon stocks and enterprise emissions using volume-derived biomass and emission factor methods. The spatiotemporal evolution characteristics of carbon budgets for forest enterprises in the key state-owned forest area (2017–2021) were analyzed using various methods, including the Mann-Kendall (MK) test and hotspot analysis. Influencing factors are identified through correlation analysis and the optimal parameter geographical detector (OPGD), while their spatial-temporal variations and causal relationships are analyzed using the geographical and temporal weighted regression model (GTWR) and structural equation modeling (SEM). The carbon budget in the Greater Khingan Range state-owned forest area averaged 10.16 × 10⁶ t CO₂-eq from 2017 to 2021, showing a gradual upward trend. The average annual carbon budget of forest enterprises was 1.02 × 10⁶ t CO₂-eq, which was highest in the central regions and lowest in the periphery. Soil pH, forest area, and elevation are the primary factors. The interaction between paired factors enhances the explanatory power of their impact, and the effects of different influencing factors exhibit both positive and negative variations across forest enterprises. In addition, the middle-aged forest tending area and average annual precipitation positively influenced forest area and soil pH, indirectly enhancing the carbon budget through multifactor interactions. This research can enhance the understanding of the carbon budget in forest enterprises, providing scientific support for the ecological protection of state-owned forests and contributing to the development of sustainable forestry practices that indirectly benefit societal well-being and economic resilience. Full article

With environmental changes, sustaining watershed ecosystem services requires understanding community perceptions and preferences. Integrated approaches considering community perceptions, climate change, and land use cover change are crucial. We address a study gap by combining climate change and land use cover change data with an analysis of community perceptions to evaluate the watershed ecosystem services situation in Nepal’s Khageri Khola Watershed. Data from in-depth stakeholder interviews (n = 16), household perception surveys (n = 440), and participant observations (n = 5) were supplemented by meteorological and land use cover change data. Descriptive analysis, index value calculation, Spearman’s Rho correlation, and chi-square statistics were used to understand linkages between socio-demographics, climate change perceptions, watershed ecosystem services importance, and changes in watershed ecosystem services supply. The Mann–Kendall test, Sen’s slope calculation, and land use cover change analysis considered temperature, precipitation, and land use. Among watershed ecosystem services, communities prioritized drinking water as the most important and biodiversity support as the least important. Watershed ecosystem services exhibited decreasing trends, with soil fertility and productivity notably high (89%) and natural hazard control low (41%). Significant alignment existed between community perceptions and local climate indicators, unlike the incongruity found with land use cover changes, especially regarding water bodies. Socio-demographic factors influenced community perceptions. Policy recommendations include analyzing watershed-level community demand and preferences, integrating community perceptions with climate change and land use cover change data in decision making, engaging communities, equitable sharing of the benefits generated by watershed ecosystem services, and considering socio-demographic and topographic diversity in tailoring management strategies. Full article

This study was conducted in Sawena district, located in the Eastern Bale Zone of Ethiopia, with the aim of analyzing climate variability and identifying adaptation strategies. Secondary data covering the period from 1984 to 2023 were utilized, along with structured and unstructured questionnaires. Primary data were gathered from 350 pastoralist households across six kebeles through a household survey. This study used the Mann–Kendall test, Sen’s slope estimator, the coefficient of variation, descriptive statistics, and a multivariate probit model to analyze climate variability and adaptation strategies. The Mann–Kendall test, Sen’s slope estimator, and coefficient of variation analysis results showed significant rainfall increases in September, October, and November, with high winter variability and an upward autumn trend. Temperature analysis revealed consistent warming, with the greatest increases in September (0.049 °C/year) and summer (0.038 °C/year), and an annual mean rise of 0.034 °C per year, indicating climate shifts affecting pastoralist and agro-pastoral livelihood strategies and water resources that lead the area toward vulnerability. The descriptive results indicated that pastoralist households have adopted various adaptation strategies: 45.1% participate in seasonal livestock migration, 26.3% rely on productive safety net programs, 19% pursue livelihood diversification, and 9.7% engage in agroforestry. Multivariate analysis indicates that education, age, credit access, livestock ownership, asset value, and media exposure influence these strategies. The findings highlight the importance of policies to enhance climate resilience through diversification, sustainable land management, and improved access to resources like credit and markets, alongside strengthened education and targeted extension services. Full article

The impacts of climate change and human activities on water resources are a complex and integrated process and a key factor for effective water resource management in semi-arid regions, especially in relation to the Jinghe River basin (JRB), a major tributary of the Yellow River basin. The Sen’s slope estimator and the Mann–Kendall test (M–K test) are implemented to examine the spatial and temporal trends of the hydrological factors, while the elasticity coefficient method based on Budyko’s theory of hydrothermal coupling is employed to quantify the degree of runoff response to the various influencing factors, from 1971 to 2020. The results reveal that the runoff at Pingliang (PL), Jingchuan (JC), and Yangjiaping (YJP) hydrological stations shows an obvious and gradual decreasing trend during the study period, with a sudden change in about 1986, while precipitation shows a fluctuating and increasing trend alongside a potential evapotranspiration-induced fluctuating and decreasing trend. Compared to the previous period, a change of −29%, in relative terms, in the runoff at the YJP hydrological station is observed. The interaction of human activities and climate change in the watershed contributes to the sharp decrease in runoff, with precipitation, potential evapotranspiration, and human activities accounting for −14.3%, −15.1%, and 70.6% of the causes of the change in runoff, respectively. Human activities (e.g., construction of water conservancy projects), precipitation, and potential evapotranspiration are the main factors contributing to the change in runoff. Full article

Globally, there has been a lot of focus on climate variability, especially variability in annual precipitation and temperatures. Depending on the area, different climate variables have different degrees of variation. Therefore, analyzing the temporal and spatial changes or dynamics of meteorological or climatic variables in light of climate change is crucial to identifying the changes induced by climate and providing workable adaptation solutions. This study examined how climate variability affects tea production in Darjeeling, West Bengal, India. It also looked at trends in temperature and rainfall between 1991 and 2023. In order to identify significant trends in these climatic factors and their relationship to tea productivity, the study used a variety of statistical tests, including the Sen’s Slope Estimator test, the Mann–Kendall’s test, and regression tests. The study revealed a positive growth trend in rainfall (Sen’s slope = 0.25, p = 0.001, R² = 0.032), maximum temperature (Sen’s slope = 1.02, p = 0.026, R² = 0.095), and minimum temperature (Sen’s slope = 4.38, p = 0.006, R² = 0.556). Even with the rise in rainfall, there has been a decline in tea productivity, as seen by the sharp decline in both the tea cultivated area and the production of tea. The results obtained from the regression analysis showed an inverse relationship between temperature anomalies and tea yield (R = −0.45, p = 0.02, R² = 0.49), indicating that the growing temperatures were not favorable for the production of tea. Rainfall anomalies, on the other hand, positively correlated with tea yield (R = 0.56, p = 0.01, R² = 0.68), demonstrating that fluctuations in rainfall have the potential to affect production but not enough to offset the detrimental effects of rising temperatures. These results underline how susceptible the tea sector in Darjeeling is to climate change adversities and the necessity of adopting adaptive methods to lessen these negative consequences. The results carry significance not only for regional stakeholders but also for the global tea industry, which encounters comparable obstacles in other areas. Full article