Search Results (10,259)

Future climate change poses unprecedented challenges to agricultural production worldwide. Therefore, designing region-specific rotation patterns is crucial for achieving synergies among multiple objectives, including agricultural productivity and ecological conservation. Based on a long-term field experiment in the Northern Agro-pastoral Ecotone of China, we calibrated and validated the Agricultural Production Systems Simulator (APSIM) and simulated rotation patterns involving four representative crops under eight climate scenarios, including warming, extreme precipitation, and combined temperature–precipitation changes. Analysis combined with carbon footprint assessment was employed to quantitatively evaluate the productivity, ecological benefits, and economic returns of different rotation patterns. The results showed that warming generally reduced crop productivity and economic returns, weakened soil carbon sequestration, and increased net carbon emissions across rotation patterns. Increasing intensity of extreme precipitation further constrained the capacity of rotation patterns to enhance yields, improve incomes, and reduce carbon emissions. Under scenarios of warming and extreme precipitation, the faba bean–oat rotation pattern was found to be the most effective for increasing crop yields, while the faba bean–potato rotation is beneficial for enhancing the incomes from local agriculture. The potato–faba bean rotation pattern was most effective for environmental sustainability due to low net carbon emissions. The findings provide a scientific basis for developing diversified planting strategies with synergistic multi-objectives in the Northern Agro-pastoral Ecotone of China, contributing to food security and sustainable agricultural development under a changing climate focused on changes in temperature and precipitation. Nevertheless, the potential effects of rising atmospheric CO₂ concentrations may be incorporated in future studies. Full article

In on-site rapid detection, the electrochemical method boasts high sensitivity and rapid response capabilities, while the colorimetric method can provide intuitive visual readings suitable for on-site screening. Therefore, this study developed an innovative dual-mode electrochemical/colorimetric aptasensor for the accurate detection of malathion (MAL) in vegetables. The sensor combines magnetic Fe₃O₄@ZIF-8-DNA composites and CuZr-MOF-cDNA probes, enabling simultaneous detection of the target through electrochemical reactions and colorimetric changes. The introduction of CuZr-MOF not only enhances the sensor’s conductivity but also significantly amplifies the electrochemical signal through its catalytic properties. The magnetic Fe₃O₄@ZIF-8-DNA composite facilitates solid–liquid separation under an external magnetic field. When the target MAL is present, the aptamer binds to the target, causing the CuZr-MOF-cDNA probes to release from the composite, altering the number of free probes in the supernatant and generating varying intensities of colorimetric signals. Meanwhile, the MAL captured in the precipitate by the aptamer is quantitatively detected through electrochemical methods. Experimental results demonstrate that as the target concentration increases, the colorimetric signal intensifies while the electrochemical signal weakens, showing a good linear relationship between the two. The aptasensor’s limit of detection (LOD) for colorimetric and electrochemical modes was 1.57 × 10⁻¹¹ M and 4.76 × 10⁻¹¹ M, respectively, with recoveries ranging from 87.71% to 107.68% and relative standard deviations between 3.23% and 10.75%. This method exhibits high sensitivity, excellent selectivity, and strong reliability, providing a novel technique for the accurate quantification of MAL in vegetables, particularly suited for on-site rapid detection. Full article

Aridity represents a fundamental climatic constraint governing water resources, ecosystem functioning, and agricultural systems in transitional climate zones. This study examines the spatial organization and temporal variability of aridity and thermal continentality in North Macedonia using observational records from 13 meteorological stations distributed across contrasting altitudinal and physiographic settings. The analysis is based on homogenized monthly and annual air temperature and precipitation series covering the period 1991–2020. Aridity and continentality were quantified using the Johansson Continentality Index (JCI), the De Martonne Aridity Index (I_DM), and the Pinna Combinative Index (I_P). Temporal consistency and trend behavior were evaluated using Pettitt’s nonparametric change-point test, linear regression, the Mann–Kendall test, and Sen’s slope estimator. Links between aridity variability and large-scale atmospheric circulation were examined using correlations with the North Atlantic Oscillation (NAO) and the Southern Oscillation Index (SOI). The results show a spatially consistent and statistically significant increase in mean annual air temperature, with a common change point around 2006, while precipitation displays strong spatial variability and limited temporal coherence. Aridity patterns display a strong altitudinal control, with extremely humid to very humid conditions prevailing in mountainous western regions and semi-humid to semi-dry conditions dominating lowland and southeastern areas, particularly during summer. Trend analyses do not reveal statistically significant long-term changes in aridity or continentality over the study period, although low-elevation stations exhibit weak drying tendencies. A moderate positive association between I_DM and I_P (r = 0.66) confirms internal consistency among aridity indices, while summer aridity shows a statistically significant relationship with the NAO. These results provide a robust climatic reference for North Macedonia, establishing a first climatological baseline of aridity conditions based on multiple indices applied to homogenized observations, and contributing to regional assessments of hydroclimatic variability relevant to climate adaptation planning. Full article

Weather modification has gained significant and growing interest in the United States (US) in recent years. The trend can be largely attributed to the changing climate, persistent droughts, and other extreme weather events that have been experienced across various regions of the US. This paper provides a critical review of weather modification program costs, benefits, policy, and governance to help shed light on policymaking and program management associated with the growing interest in adopting weather modification as a local climate management strategy in the US. Additionally, to deepen our understanding of the widely concerning issues, such as the financial burden on taxpayers and potential environmental risks, the paper explored the local implementation challenges and common environmental and public health concerns related to weather modification activities. A synthesis of the literature and policy debates reached four general conclusions: (1) The need for weather modification programs is expected to keep growing, though regional variations may exist due to regulatory and other local factors; (2) weather modification can bring significant local benefits, ranging from enhanced agricultural yield and recreational economy to extreme weather management and public environmental health benefits; (3) state-level and local support, including financial resources, will be essential for program development in the foreseeable future; and (4) technological advancements will be critical for addressing many of the project operation efficiency challenges and environmental and public health concerns related to weather modification programs. More specifically for program governance and local implementation, aspects such as project planning (including resource pooling), risk and liability management, communication and reporting, outcome measurability, and stakeholder engagement are indispensable for addressing issues related to program legality and oversight, public acceptance, and sustainability. Full article

The Tibetan Plateau is highly sensitive to global climate change and characterized by pronounced ecological fragility, making vegetation net primary productivity (NPP) a key indicator for assessing ecosystem functioning and regional ecological security. This study aims to characterize the spatiotemporal dynamics of NPP and to disentangle the multiple natural and land-use drivers shaping its variability across the Tibetan Plateau. MODIS-derived NPP data for the period 2001–2022 are integrated with multi-source datasets on climate, topography, normalized difference vegetation index (NDVI), and land use (CLCD), and analyzed using trend and correlation analyses, land-use transfer matrices, an optimal-parameter geographical detector, and partial least squares structural equation modeling (PLS-SEM). The results indicate that NPP exhibits a significant but fluctuating upward trend (0.52 gC·m⁻²·a⁻¹, p < 0.01), with higher values in the southeast and lower values in the northwest, the Yunnan Plateau evergreen broadleaf and pine forest region (VA5) and the southern Himalayan montane forest region (VA6) function as high-value centers, and regions such as the Kunlun high-cold desert region (HID1) represent low-value centers. The mutual conversion between forestland and grassland and bare land constitutes a key process driving regional NPP changes, with the net expansion of forestland making a substantial contribution to NPP increases (net gain of 2606.88 TgC). Geographic detector analysis indicates that NDVI (q = 0.741) and land use type (q = 0.741) are the primary factors governing the spatial differentiation of NPP, followed by precipitation, slope, and temperature. Moreover, interactions between any two factors enhance their explanatory power, with the interaction between aspect and land use type exhibiting the strongest effect (q approaching 1). PLS-SEM path analysis further quantifies the driving pathways, revealing that mean annual precipitation and land use type are the most direct drivers of NPP, while climatic and topographic factors influence NPP indirectly through their effects on vegetation cover and land use type. This study advances the understanding of the multifactorial driving mechanisms of ecosystem productivity on the Tibetan Plateau and provides a scientific basis for zoned and differentiated ecological restoration and climate adaptation strategies. Full article

The balance between gross primary productivity (GPP) and ecosystem respiration (ER) defines an ecosystem’s carbon sink-source status. Under global warming, hydrothermal conditions critically shape carbon fluxes, yet their differential impacts on GPP and ER remain insufficiently understood, especially across biomes. Elucidating these differences is essential for reducing uncertainties in terrestrial carbon cycle projections under ongoing climate change. Here, based on flux observations from global terrestrial sites with a focus on forest ecosystems, we selected mean annual temperature (MAT), latent heat flux (LH), vapor pressure deficit (VPD), soil water content (SWC), and annual precipitation as representative indicators of hydrothermal conditions, and employed mixed-effects models to examine how these key environmental drivers influence GPP and ER. After analyzing the fixed effects, LH and MAT promoted GPP more strongly than ER (slope = 0.5 > 0.253, slope = 0.595 > 0.392, respectively), whereas VPD suppressed GPP more than ER (slope = −0.658 < −0.499), yet accounted for a greater proportion of variance in ER than in GPP (R² = 0.14 > 0.07). Although SWC had a significant (p < 0.001) positive effect on GPP, the effect size was minimal, and its impact on ER was insignificant. R² decomposition showed that marginal R² values were similar for the GPP and ER models (0.43 and 0.44), whereas the GPP model exhibited a substantially higher conditional R² (0.82 vs. 0.63), indicating that MAT exerted a stronger influence on GPP than on ER across ecosystem types. The combined analysis of fixed and random effects indicated that MAT affected GPP more variably than ER across ecosystem types, with the strongest responses in mixed forests and savannas, intermediate responses in evergreen needleleaf forests, and the weakest responses in evergreen broadleaf forests. Overall, this study advances our understanding of how environmental factors differently influence GPP and ER, and incorporating these differences can improve predictions of forest carbon fluxes and climate-carbon feedbacks. Full article

Thallium is one of the most toxic elements on the planet, and one alternative method for its precipitation is through jarosite-type compounds. Therefore, in this work, the kinetics of thallium jarosite were evaluated in an alkaline medium (NaOH and Ca(OH)₂). Experiments were conducted to assess the effect of medium concentration from 0.03 M to 5.5 × 10⁻⁴ M and the effect of temperature from 20 °C to 60 °C. The sigmoidal curves showed an induction period, during which there was no release of sulfur or thallium ions into the solution, nor the formation of solid byproducts, according to the X ray diffraction (XRD) results. Similarly, a progressive conversion period was observed, evidenced by the release of sulfur and thallium ions into the solution and the formation of amorphous solids. Finally, a stability zone is reached, indicating that the decomposition reaction has ended, as there are no changes in the concentration of sulfur and thallium ions in the solution. The reaction was monitored by determining S using Inductively Coupled Plasma (ICP). The experimental results for the progressive conversion period show a better fit to the chemically controlled shrinking core kinetic model. The reaction order for the kinetics in NaOH medium is 1.09 for the induction period and 0.89 for the progressive conversion period, while for Ca(OH)₂ medium it is 0.78 for the induction period and 0.47 for the progressive conversion period. The activation energies for the progressive conversion period in the two proposed media are 91.87 kJ mol⁻¹ in NaOH and 71.14 kJ mol⁻¹ in Ca(OH)₂, indicating that the controlling mechanism in both systems is the chemical reaction. For the induction period, the activation energies are 101.52 kJ mol⁻¹ and 79.45 kJ mol⁻¹, respectively, indicating that the chemical reaction also controls the initiation of the reactions. The high activation energy in both reaction media suggests that high concentrations of OH⁻ and high temperatures are required to initiate the decomposition reaction. Thallium jarosite precipitates a large amount of thallium and requires high energy to decompose, so it could be a viable alternative in thallium retention. Full article

As a pivotal component of the global carbon cycle, the spatial variation in soil respiration (Rs) is crucial for forecasting climate change trajectories. Despite extensive research on the spatial patterns of total Rs, the distinct drivers of its two components, heterotrophic respiration (Rh) and autotrophic respiration (Ra), are still not well defined. We compiled a global dataset from studies published between 2007 and 2023 to investigate the drivers of spatial variations in Rs, Ra, and Rh. This dataset comprises 308 annual flux measurements from 172 sites. The results showed that Rh contributed 63% and 60% to Rs in forest and grassland ecosystems, respectively. Further analyses using structural equation modelling (SEM) showed that the spatial variation in Rh and Ra exhibited divergent responses to climatic factors and plant community structure (mostly driven by gross primary production, GPP). Rh was more affected by mean annual temperature (MAT) than by mean annual precipitation (MAP), with standardized total effects of 0.17 (forests) and 0.57 (grasslands) for MAT versus 0.10 and 0.07 for MAP, respectively. In contrast, Ra exhibited greater sensitivity to MAP (0.08 and 0.18) than to MAT (−0.01 and 0.04). GPP exerted biome-specific effects: in forests, high GPP enhanced Rh (0.18) more substantially than Ra (0.08), while in grasslands, elevated GPP significantly increased Ra (0.34) but suppressed Rh (−0.30). Moreover, these variables incorporated into the SEMs accounted for a greater proportion of the variation in Rh and Ra in grasslands (R² = 0.73 for Rh, 0.48 for Ra) as compared to forests (R² = 0.21 for Rh, 0.22 for Ra), suggesting the greater complexity in forest soil C dynamics. By using the whole yearly measured soil respiration data around the world, this study highlights the differential environmental regulation of Rh and Ra, providing critical insights into the mechanisms governing Rs variations under climate change. Full article

To effectively manage and conserve ecosystems, it is crucial to understand how vegetation changes over time and space and what drives these changes. The Normalized Difference Vegetation Index (NDVI) is a key measure of plant growth that is highly sensitive to climate variations. Despite its importance, there has been limited research on vegetation changes in the upper sections of the Irtysh River. In our study, we combined various datasets, including NDVI, temperature, precipitation, soil moisture, elevation, and land cover. We conducted several analyses, such as Theil–Sen median trend analysis, Mann–Kendall trend and mutation tests, partial correlation analysis, the geographical detector model, and wavelet analysis, to reveal the region’s pronounced warming and moistening trend in recent years, the response relationship between NDVI and the climate, and the primary drivers influencing NDVI variations. We also delved into the spatiotemporal evolution of NDVI and identified key factors driving these changes by analyzing atmospheric circulation patterns. Our main findings are as follows: (1) Between 1901 and 2022, the area’s temperature rose by 0.018 °C/a, with a noticeable increase in the rate of warming around 1990; precipitation increased by 0.292 mm/a. From 1950 to 2022, soil moisture exhibited a steady increase of 0.0002 m³ m⁻³/a. Spatial trend distributions indicated that increasing trends in temperature and precipitation were evident across the entire region, while trends in soil moisture showed significant spatial variation. (2) During 1982 to 2022, the vegetation greening trend was 0.002/10a, indicating a gradual improvement in vegetation growth in the study area. The spatial distribution of monthly average NDVI values revealed that the main growing season of vegetation spanned April to November, with peak NDVI values occurring in June–August. Combined with serial partial correlation and spatial partial correlation analysis, temperatures during April to May effectively promoted the germination and growth of vegetation, while soil moisture accumulation from June to August (or January to August) effectively met the water demand of vegetation during its growth process, with a significant promoting effect. Geographical detector results demonstrate that temperature exhibits the strongest explanatory power for NDVI variation, whereas land cover has the weakest. The synergistic promotional effect of multiple climatic factors is highly pronounced. (3) Wavelet analysis revealed that the periodic characteristics of NDVI and climate variables over a 2–15-year timescale may have been associated with the impacts of atmospheric circulation. Taking NDVI and climatic factors from June to August as an example, before 2000, temperature was the dominant influencing factor, followed by precipitation and soil moisture; after 2000, precipitation and soil moisture became the primary drivers. The North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were the primary atmospheric circulation patterns influencing vegetation variability in the region. Their effects were reflected in the inverse relationship observed between NAO/AO indices and NDVI, with typical phases of high and low NDVI closely corresponding to shifts in NAO and AO activity. This study helps us to understand how plants have been changing in the upper parts of the Irtysh River. These insights are critical for guiding efforts to develop the area in a way that is sustainable and beneficial for the environment. Full article

African vegetation responses to extreme drought represent a key challenge for global change research and sustainable water–land resource management. Satellite remote sensing provides long-term observations of vegetation dynamics, yet conventional analyses focus on vegetation structural, greenness, or productivity changes, lacking of understanding on physiological adaptation. This study applies a multi-model framework integrating high-temporal-resolution (4-day) and multi-spectral satellite data with machine learning to disentangle structural and physiological responses across Central and Western Africa. Three key indicators were used: evapotranspiration (ET), relative solar-induced chlorophyll fluorescence (SIF_rel), and the ratio of midday to midnight vegetation optical depth (VOD_ratio), which respectively, represent water flux, photosynthetic activity, and water regulation. A random forest model, combined with SHapley Additive exPlanations (SHAP) analysis, was used to separate vegetation anomaly signals and identify key climatic controls. The results reveal pronounced differences in vegetation responses between arid and humid climatic regions. In arid regions, near-infrared reflectance of vegetation (NIRv) and solar-induced chlorophyll fluorescence (SIF) exhibited clear negative anomalies and significant pre-drought declines, accompanied by marked changes in vegetation optical depth (VOD), indicating canopy structural damage and reduced photosynthetic activity. In contrast, trend analysis revealed that although SIF and NIRv in humid regions showed relatively strong responses during the pre-drought phase, they did not exhibit significant trends after the drought peak, and changes in VOD were comparatively small, suggesting that higher water availability partially buffered the prolonged impacts of drought on vegetation structure and function. Process analysis showed that three months before and after drought peaks, physiological indicators exhibited strong anomalies that closely tracked drought duration. SIF_rel, ET signals peaked earlier than water-content anomalies (VOD_ratio), suggesting a two-phase regulation strategy: early stomatal closure followed by delayed deep-root water uptake. Physiological anomalies accounted for over 88% of total vegetation anomalies during drought peaks, highlighting their dominant role in early-stage drought response. Precipitation and temperature emerged as primary drivers, explaining 76.8% of photosynthetic variation, 60.3% of ET variation, and 53.9% of water-content variation in the development. The recovery is influenced by the duration of drought and the regrowth of vegetation. By explicitly decoupling physiological and structural vegetation responses, this study provides refined, process-based insights into African ecosystem adaptation to water stress. These findings contribute to more accurate drought monitoring, water availability assessment, and climate adaptation strategies, directly supporting sustainable water and land management goals. Full article

Understanding how environmental conditions, functional composition, and species richness jointly relate to phylogenetic community structure is important for sustainable forest management under environmental change. Using 2858 plots from the 7th National Forest Inventory of South Korea, phylogenetic community structure as the standardized effect size of mean pairwise phylogenetic distance (SES.MPD) was quantified for broadleaved, conifer, and mixed stands. Associations between SES.MPD and abiotic factors such as elevation, mean annual precipitation, stand age, as well as biotic factors such as species richness and community-weighted means of specific leaf area and maximum height were assessed using multi-model inference and piecewise structural equation models (pSEM). Across stand types, SES.MPD values in most plots were not significantly different from the null-model baseline under the chosen randomization procedure, indicating weak net departures from null-model-relative phylogenetic dispersion at the national scale; meanwhile, mean SES.MPD tended to be slightly negative in broadleaved stands and positive in conifer and mixed stands. In multi-model inference analysis, the strongest associations with SES.MPD differed among stand types: trait composition—especially community-weighted specific leaf area—showed the strongest association in total stands and broadleaved stands, whereas species richness was the dominant correlate in mixed stands and precipitation showed the strongest association in conifer stands. The pSEM revealed that elevation, precipitation, and stand age were linked to SES.MPD largely through indirect pathways via trait composition and species richness, consistent with trait- and richness-mediated environmental filtering. These results highlight stand-type-specific linkages among environment, traits, richness, and phylogenetic structure and support trait- and phylogeny-informed forest management and restoration to enhance resilience under ongoing environmental change. Full article

Understanding long-term snow cover dynamics is essential in mountain regions with limited meteorological or in situ observations. This study examines seasonal snow cover evolution across the Romanian Carpathians (2000–2025) using daily MODIS/Terra MOD10A1 Cloud-Gap-Filled data at 500 m resolution. Snow-covered pixels were identified using an NDSI ≥ 40 threshold, and snow cover duration (SCD), snow onset date (SOD), and snow end date (SED) were analyzed in relation to elevation and aspect from the FABDEM, complemented by snow-covered area (SCA) and snowline elevation (SLE) metrics. Across the entire range, the snow season shortens mainly due to later onset (+0.28 days/year) and earlier melt (−0.78 days/year), resulting in an SCD decrease of −1.14 days/year. High-elevation (>2000 m) areas show only small changes (SCD: −0.13 days/year; SOD: +0.46 days/year; SED: +0.32 days/year), while the strongest reductions occur at low and mid elevations, where snow persistence is most sensitive to warming; consistent declines in seasonal SCA and a pronounced monthly SLE cycle further document the spatial expression of this variability. Uncertainty was assessed by comparison with station-based snow cover duration (n = 230 station-years), indicating strong agreement (r = 0.95) with a modest negative bias (median: −8 days) and a mean absolute error (MAE) of 16.7 days. Climate correlations highlight air temperature as the dominant covariate of interannual snow-phenology variability, whereas precipitation associations are weaker. Overall, these shifts in snow phenology highlight increasing instability of the Carpathian snow regime and emphasize the value of long-term MODIS observations for tracking cryospheric change in a warming southeastern European mountain system. Full article

Land use change driven by accelerated urbanization in Mongolia has precipitated significant degradation of urban riverine ecosystems over the past two decades. This study investigates hydrological transformations in the Selbe River Catchment of Ulaanbaatar, a cold semi-arid urban system undergoing intensive densification. Using the Site-scale Urban Water Mass Balance Assessment (SUWMBA) framework, we quantified water cycle dynamics across four temporal intervals (2008, 2010, 2018, and 2023), capturing shifts in surface runoff, infiltration, and evapotranspiration associated with land use transitions. Calibration and validation employed discharge records from the Selbe-Dambadarjaa gauging station. Results show that total inflows increased from 223 to 312 mm between 2008 and 2023, driven by a more than twentyfold rise in imported water (from 1 to 22 mm). Evapotranspiration declined by roughly one-third, while infiltration displayed a threshold-type non-linear response—rising sharply between 2010 and 2018 before decreasing again in 2023 as imperviousness intensified. Model performance weakened after 2018, underscoring the limitations of conventional hydrological frameworks in rapidly urbanizing contexts. A redevelopment scenario for the Selbe Sub-Center, aligned with the Ulaanbaatar City Master Plan 2040, projected substantially reduced evapotranspiration (132 mm) and markedly increased stormwater runoff (270 mm), reflecting expanded impervious cover and diminished vegetation. Imported water and wastewater flows (each 386 mm) also increased due to full connection to centralized supply and sewerage infrastructure, indicating a shift toward engineered water pathways and reduced hydrological connectivity to the Selbe River. These findings highlight the urgency of water-sensitive urban design and provide evidence directly informing Mongolia’s 2040 Urban Master Plan and decentralization strategy. The study establishes methodological precedent for applying SUWMBA to cold, semi-arid catchments and contributes quantitative insights for integrated land–water management policies. Full article

The increasing frequency of extreme rainfall events that cause severe damage is considered a clear sign of climate change. Therefore, analyzing these events and gaining a better understanding of the circulation patterns that form precipitation regimes and trigger torrential rainfall are crucial for developing adaptation strategies. This study aims to present a comprehensive picture of precipitation regimes in Bulgaria under contemporary climate conditions, investigate the connections between precipitation and atmospheric circulation patterns, and propose a regionalization of torrential rainfall. We used daily precipitation data collected in the period 1991–2020, along with data on hazardous rainfall warnings issued by the National Institute of Meteorology and Hydrology. To identify the circulation patterns associated with both rainy days and hazardous rainfall in Bulgaria, we applied the automated Jenkinson–Collison classification. To identify precipitation patterns, we conducted a principal component analysis in T-mode with varimax rotation and k-means clustering of component scores on both monthly normals and a dataset of 166 selected torrential rainfall days. The results, examined in the context of the existing regionalization of precipitation, highlight the climatic diversity of precipitation regimes in Bulgaria. Our findings indicate that torrential rainfall is associated with low-pressure systems and airflows mainly from the east or northeast, as well as with weak-gradient pressure fields. Full article