Search Results (2,447)

Flood events, intensified by climate change, pose significant threats to both human settlements and ecological systems. This study presents an integrated approach to evaluate flood impacts on ecosystem carbon dynamics using remote sensing and machine learning techniques. The case of the Emilia-Romagna region in Italy is presented, which experienced intense flooding in 2023. To understand flood-induced changes in the short term, we quantified the differences in net primary productivity (NPP) and above-ground biomass (AGB) before and after flood events. Short-term analysis of NPP and AGB revealed substantial localized losses within flood-affected areas. NPP showed a net deficit of 7.0 × 10³ g C yr⁻¹, and AGB a net deficit of 0.5 × 10³ Mg C. While the wider region gained NPP (6.7 × 10⁵ g C yr⁻¹), it suffered a major AGB loss (3.3 × 10⁵ Mg C), indicating widespread biomass decline beyond the flood zone. Long-term ecological assessment using the Remote Sensing Ecological Index (RSEI) showed accelerating degradation, with the “Fair” ecological class shrinking from 90% in 2014 to just over 50% in 2024, and the “Poor” class expanding. “Good” and “Very Good” classes nearly disappeared after 2019. High-hazard flood zones were found to contain 9.0 × 10⁶ Mg C in AGB and 1.1 × 10⁷ Mg C in soil organic carbon, highlighting the vulnerability of carbon stocks. This study underscores the importance of integrating flood modeling with ecosystem monitoring to inform climate-adaptive land management and carbon conservation strategies. It represents a clear, quantifiable carbon loss that should be factored into regional carbon budgets and post-flood ecosystem assessments. Full article

Enhanced Rock Weathering (ERW) is a promising carbon dioxide removal (CDR) strategy that accelerates mineral dissolution, sequestering atmospheric CO₂ while improving soil health. This study builds on prior applications of soil calcimetry by investigating its ability to resolve short-term carbonate fluxes and rainfall-modulated weathering dynamics in wollastonite-amended croplands. Conducted over a single growing season (May–October 2024) in temperate row-crop fields near Port Colborne, Ontario—characterized by fibric mesisol soils (Histosols, FAO-WRB)—this study tests whether calcimetry can distinguish between dissolution and precipitation phases and serve as a proxy for weathering flux within the upper soil horizon, under the assumption that rapid pedogenic carbonate cycling dominates alkalinity retention in this soil–mineral system. Monthly measurements of soil pH (Milli-Q and CaCl₂) and calcium carbonate equivalent (CCE) were conducted across 10 plots, totaling 180 composite samples. Results show significant alkalinization (p < 0.001), with average pH increases of ~+1.0 unit in both Milli-Q and CaCl₂ extracts over the timeline. In contrast, CCE values showed high spatiotemporal variability (−2.5 to +6.4%) without consistent seasonal trends. The calcimetry-derived weathering proxy, log (Σ ΔCCE/Δt), correlated positively with pH (r = 0.652), capturing net carbonate accumulation, while the kinetic dissolution rate model correlated strongly and negatively with pH (r ≈ −1), reflecting acid-promoted dissolution. This divergence confirms that the two metrics capture complementary stages of the weathering–precipitation continuum. Rainfall strongly modulated short-term carbonate formation, with cumulative precipitation over the previous 7–10 days enhancing formation rates up to a saturation point (~30 mm), beyond which additional rainfall yielded diminishing returns. In contrast, dissolution fluxes remained largely independent of rainfall. These results highlight calcimetry as a direct, scalable, and dynamic tool not only for monitoring solid-phase carbonate formation, but also for inferring carbonate migration and dissolution dynamics. In systems dominated by rapid pedogenic carbonate cycling, this approach captures the majority of alkalinity fluxes, offering a conservative yet comprehensive proxy for CO₂ sequestration. Full article

Soil organic matter (SOM) is a key component of nutrient cycling and soil fertility in terrestrial ecosystems. SOM is of great significance to the stability of terrestrial ecosystems and the improvement of soil productivity; to further exert its role, it is first necessary to clarify its actual distribution and occurrence status in specific regions. Under the combined impacts of intensive agriculture, unreasonable farming practices, and climate change, the SOM content in the Songnen Plain is showing a degradation trend, posing multiple stresses on its soil ecosystem functions. This study aims to systematically track the dynamic changes of SOM in the Songnen Plain, assess its spatiotemporal evolution characteristics, and reveal its driving mechanisms. A total of 113 representative soil profiles were selected in 2023; standardized excavation and sampling procedures were employed in the Songnen Plain. Soil pH, SOM, total nitrogen (TN), total phosphorus (TP), total potassium (TK), particle size (PSD), texture, and Munsell soil colors of samples were determined. Temporal variation characteristics, as well as horizontal and vertical spatial distribution patterns, in SOM content in the Songnen Plain were assayed. Structural equation modeling (SEM), together with freeze–thaw of soil and soil color mechanism analyses, was applied to reveal the spatiotemporal dynamics and driving mechanisms of SOM. The result indicated that the distribution pattern of SOM content in horizontal space shows higher levels in the northeastern region and lower levels in the southwestern region, and decreased with increasing soil depth. SEM analysis indicated that TN and PSD were the main positive factors, whereas bulk density exerted a dominant negative effect. The ranking of contribution rates is TN > TK > TP > PSD > annual average temperature > annual precipitation > bulk density. Mechanistic analysis revealed a significant negative correlation between SOM content and R, G, B values, with soil color intensity serving as a visual indicator of SOM content. Freeze–thaw thickness of soil was positively correlated with SOM content. These findings provide a scientific basis for soil fertility management and ecological conservation in cold regions. Full article

This study examines the landing performance of a four-legged lunar lander equipped with magnetorheological dampers when landing on discrete lunar soil. To capture the complex interaction between the lander and the soil, a coupled dynamic model is developed that integrates flexible multibody dynamics (FMBD), granular material modeling, and a semi-active fuzzy control strategy. The flexible structures of the lander are described using the floating frame of reference, while the lunar soil behavior is simulated using the discrete element method (DEM). A fuzzy controller is designed to achieve the adaptive MR damping force under varying landing conditions. The FMBD and DEM modules are coupled through a serial staggered approach to ensure stable and accurate data exchange between the two systems. The proposed model is validated through a lander impact experiment, demonstrating good agreement with experimental results. Based on the validated model, the influence of discrete lunar regolith properties on MR damping performance is analyzed. The results show that the MR-based landing leg system can effectively absorb impact energy and adapt well to the uneven, granular lunar surface. Full article

Phosphorus (P) is essential to life yet constrained by finite reserves, heterogeneous distribution, and strong chemical binding to soil minerals. Pedogenesis progressively alters the availability of P: in ‘young’ soils, P associated with Ca and Mg is relatively labile, while in ‘old’ soils, acidification and leaching deplete base cations, shifting P into organic matter and recalcitrant Al- and Fe-bound pools. Podzolized soils (Spodosols) provide a unique lens for studying this transition because podzolization vertically segregates these dynamics into distinct horizons. Organic cycling dominates the surface horizon, while downward translocation of Al, Fe, and humus creates a spodic horizon that immobilizes P through sorption and co-precipitation in amorphous organometal complexes. This spatial separation establishes two contrasting P pools—biologically dynamic surface P and mineral-stabilized deep P—that may be variably accessible to plants and microbes depending on depth, chemistry, and hydrology. We synthesize mechanisms of spodic P retention and liberation, including redox oscillations, ligand exchange, root exudation, and physical disturbance, and contrast these with strictly mineral-driven or biologically dominated systems. We further propose that podzols serve as natural experimental models for ecosystem aging, allowing researchers to explore how P cycling reorganizes as soils develop, how vertical stratification structures biotic strategies for nutrient acquisition, and how deep legacy P pools may be remobilized under environmental change. By framing podzols as a spatial analogue of long-term weathering, this paper identifies them as critical systems for advancing our understanding of nutrient limitation, biogeochemical cycling, and sustainable management of P in diverse ecosystems. Full article

The dynamic loads affecting earth-retaining structures may increase in seismically active regions. Therefore, studying the soil–structure interaction among the soil, shoring systems, and adjacent structures is crucial. However, there is limited research on this important topic. This study investigates the seismic performance of a deep braced excavation and a nearby 10-story building in sandy soil formation. The main focus of this study is the consideration of the influence of varying foundation depths of adjacent structures on the seismic response of the shoring system and the performance of the shoring system and adjacent structure under different earthquake records. PLAXIS 2D software (Version 22.02) was used to carry out the numerical analysis. Sandy soil was modeled using the Hardening Soil with small-strain stiffness model (HS-small). Back analysis of observation data extracted from a real case study of a deep braced excavation in the central district of Kaohsiung City, adjacent to the O₇ Station on the Orange Line of the Kaohsiung MRT system in Taiwan, was used to validate the numerical analysis. Beyond model validation, a parametric study was conducted to address the effect of the foundation level of the building adjacent to the excavation on both the seismic behavior of the shoring system and the structure itself, using the Loma-Prieta (1989) earthquake record. The parametric study was further extended to assess the responses of the shoring system and the adjacent structure under the influence of the earthquake records of Loma-Prieta (1989), Northridge (1994), and El-Centro (1940). The results show that the maximum lateral displacement of the diaphragm wall occurred at the top of the wall in all studied cases. The maximum dynamic bending moment in the retaining structure was more than three times the static one on average. In contrast, the dynamic shear force was more than 2.85 times the static one on average. In addition, the dynamic axial force of the first and second struts was 1.38 and 3.17 times the static forces, respectively. The results also reveal large differences in the behavior of the shoring system and the adjacent structure between the different earthquake records. Full article

Sediment erosion under turbulent wave action is a highly dynamic process shaped by the interaction between wave properties and sediment characteristics. Despite extensive empirical research, the underlying mechanisms of wave-induced erosion remain insufficiently understood, particularly regarding the threshold energy required for particle mobilization and the factors governing displacement patterns. This study employed a custom-built wave flume and a 3D-printed sampler to examine sediment behavior under controlled wave conditions. Rounded glass beads, chosen to eliminate the influence of particle shape, were used as sediment analogs with a similar specific gravity to natural sand. Ten experiments were conducted to systematically assess the effects of particle size, particle number, input voltage (wave power), and water depth on sediment response. The results revealed that (1) only a fraction of particles were mobilized, with the remainder forming stable interlocking structures; (2) the number of displaced particles increased with particle size, particle count, and water depth; (3) a threshold wave power is required to initiate erosion, though buoyancy under shallow conditions reduces this threshold; and (4) wave steepness, rather than voltage or wave height alone, provided the strongest predictor of sediment displacement. These findings highlight the central role of wave steepness in erosion modeling and call for its integration into predictive frameworks. The study concludes with methodological limitations and proposes future research directions, including expanded soil types, large-scale flume testing, and advanced flow field measurements. Full article

Forests play a pivotal role in the global carbon cycle, yet accurately simulating forest soil carbon dynamics remains a significant challenge for process-based models. This review systematically compares the mechanistic foundations of traditional models (e.g., Century, CLM5) with emerging microbial-explicit models (e.g., MEND), highlighting key differences in mathematical formulation (first-order kinetics vs. Michaelis–Menten kinetics), carbon pools partitioning (measurable vs. non-measurable experimentally), and the representation of soil carbon stabilization mechanisms (inherent recalcitrance, physical protection, and chemical protection). Despite advances in process-based models in predicting forest soil organic carbon (SOC), improving prediction accuracy, and assessing SOC response to climate change, current research still faces several challenges. These include difficulties in capturing depth-dependent variations in critical microbial parameters such as microbial carbon use efficiency (CUE), limited capacity to distinguish the relative contributions of aboveground and belowground litter inputs to SOC formation, and a general lack of long-term observational data across soil profiles. To address these limitations, this study emphasizes the importance of integrating remote sensing data and refining cross-scale simulation approaches. Such improvements are essential for enhancing model predictive accuracy and establishing a more robust theoretical basis for forest carbon management and climate change mitigation. Full article

Earthquakes are highly unpredictable and often lead to secondary disasters such as slope collapses, landslides, and debris flows, posing serious threats to human life and property. To explore how multi-stage loess slopes respond to seismic loading, improve both the efficiency and precision of seismic analysis, and better capture the random characteristics of earthquakes in reliability assessment, this research proposes a new analytical framework. The approach adopts the pseudo-dynamic method, divides the slope soil into layers through the lumped mass scheme, and applies the Newmark-β integration method to construct a displacement response model that incorporates seismic variability. By comparing and analyzing results from Geo-Studio finite element simulations, the study reveals the dynamic response behavior of multi-level loess slopes subjected to seismic loads. The key findings are as follows: (1) The formation of unloading platforms introduces a graded energy dissipation effect that significantly reduces stress concentration along potential sliding surfaces; (2) The combined influence of the additional vertical load from the overlying soil and the presence of double free faces has a notable effect on the stability of secondary slopes; (3) The peak displacement response exhibits a nonlinear relationship with slope height, initially increasing and then decreasing. The proposed improved analysis method demonstrates clear advantages over traditional approaches in terms of computational efficiency and accuracy, and provides a valuable theoretical basis for the seismic design of high loess slopes. Full article

Photosynthesis drives terrestrial carbon uptake, yet its diurnal dynamics remain poorly resolved due to the sparse availability of flux towers and the coarse spatial resolution of current satellite observations. Solar-induced chlorophyll fluorescence (SIF) provides a direct proxy of carbon uptake, but the existing global monthly mean diurnal total canopy SIF product is limited to 0.5° resolution. We developed a random forest-based downscaling framework to generate a global monthly mean hourly SIF dataset (SIF_{total_01}) at 0.1° resolution for 2000–2022. When validated against eddy-covariance-based gross primary productivity (GPP) data, SIF_{total_01} showed a strong correlation (R² = 0.81) and reduced root mean square error when compared with SIF_total (2.89→2.8 mW m⁻² nm⁻¹), providing notable gains in broadleaved forests (R²: 0.80→0.88 with a root mean square error of 2.32→1.81 mW m⁻² nm⁻¹). The SIF_{total_01} dataset revealed a distinct double-peak in the SIF_{total_01}–GPP slope, reflecting widespread afternoon depression of photosynthesis, with normalized slopes declining from 1.03 in the morning to 0.98 in the afternoon. Soil moisture modulated this depression pattern, as the afternoon–morning SIF_{total_01} difference increased from 0.02 to 0.10 mW m⁻² nm⁻¹ across dry to wet years. Under water stress, SIF yield was more sensitive than absorbed photosynthetic active radiation (APAR), with a doubling of the afternoon–morning SIF yield difference (0.5→1.1 10⁻³ nm⁻¹), while the afternoon–morning APAR difference showed a smaller change (−300→−180 kJ m⁻²). This study improves the potential for bridging observational gaps and constraining models offer valuable insights for fundamental and applied research in the analysis of ecosystem productivity, climate-carbon feedbacks, and vegetation stress. Full article

Reservoir landslides undergo saturated–unsaturated transitions under hydrological variations. Matric suction significantly influences slip-zone soil strength. Existing studies lack analysis of suction–rate–strength coupling, while Amontons’ model fails for cohesive soils. This study investigated Huangtupo landslide slip-zone soil in the upper reaches of the Yangtze River using pressure plate and saturated salt solution methods to determine the soil–water characteristic curve. Suction-controlled ring shear tests were conducted under three matric suction levels ($\Psi$ = 0, 200, and 700 kPa) across net normal stresses (${\sigma }_{net}$ = 100–800 kPa) and shear rates ($\dot{\gamma }$ = 0.05–200 mm/min). Key findings revealed the following: (1) significant suction–rate coupling effects were shown, with 700 kPa suction yielding 30% higher residual strength than saturated conditions, validating matric suction’s role in enhancing effective stress and particle contact strength; (2) residual cohesion showed strong logarithmic correlation with shear rate, with the fastest growth below 10 mm/min, while the residual friction angle varied minimally (0.68°), contributing little to overall strength; (3) a bivariate model relating residual cohesion to $\dot{\gamma }$ and $\Psi$ was established, overcoming traditional single-factor limitations. The study demonstrates that dual-parameter Coulomb modeling effectively captures multi-field coupling mechanisms in unsaturated slip-zone soils, providing theoretical foundations for landslide deformation prediction and engineering design under dynamic hydrological conditions. Full article

Biopolymers have recently been introduced as eco-friendly alternatives to other chemical cementitious additives for sandy soil stabilization, especially in pavement construction. The resilient modulus (M_R) is a key metric considered in the mechanistic design of pavement layers that ensures a safe and economic design based on guaranteed accurate values. This study investigated the effects of dehydration on the M_R of biopolymer-treated sand. Prepared specimens were subjected to two different curing conditions. The first set underwent closed-system curing (CSC) for periods of 7, 14, and 28 days. The second set of specimens was cured at different levels of suction by controlling relative humidity (RH) using different salt solutions (0.27, 1.0, 9.7, 21.0, 54.6, 113.7, and 294 MPa), referred to as dehydration curing (DC). The soil water retention curve (SWRC) was measured over the entire suction range to evaluate the dehydration curing and to link the results of suction levels and dehydration regime. M_R tests were conducted on both sets of specimens using a dynamic triaxial system to simulate different confining, traffic, and dynamic stresses. The results showed a significant increase in M_R (i.e., up to eight times) for specimens cured under DC conditions that was proportional to the suction level across different zones of the SWRC. Scanning electron microscopy revealed a phase change from hydrogel to film, which enhanced cementation and bonding between particles. in addition, CSC treatment resulted in a 10–30% reduction in M_R. A new regression model is proposed to predict the M_R of biopolymer-treated sand as a function of confining stresses, dynamic stresses, and suction. These findings will assist pavement engineers and designers in achieving safe, sustainable, and economic designs. Full article

Artificial neural networks (ANNs) offer considerable advantages in predicting evaporation (EVAP), particularly in handling nonlinear relationships and complex interactions among factors like soil surface temperature (SST) and wind speed (WS). In Al Medina, Saudi Arabia, the connections among WS, SST at 5 cm, SST at 10 cm, and EVAP have been modeled using an ANN. This study demonstrates the practical effectiveness and applicability of the approach in simulating complex nonlinear dynamics in real-life systems. The modeling process employs time series data for WS, SST at both 5 cm and 10 cm, and EVAP, gathered from January to December (2002–2010). Four ANNs labeled T1–T4 were developed and trained with the feedforward backpropagation (FFBP) algorithm using MATLAB routines, each featuring a distinct configuration. The networks were further refined through the enumeration technique, ultimately selecting the most efficient network for forecasting EVAP values. The results from the ANN model are compared with the actual measured EVAP values. The mean square error (MSE) values for the optimal network topology are 0.00343, 0.00394, 0.00309, and 0.00306 for T1, T2, T3, and T4, respectively. Full article

The expansion of conventional agricultural models in the Colombian Amazon has caused deforestation, biodiversity loss, and socio-environmental degradation. In response, agroecology and bioeconomy are emerging as key strategies to regenerate landscapes and foster sustainable production systems. We evaluated the agroecological performance of 25 farms in the Andean–Amazon transition zone of Colombia using FAO’s Tool for Agroecology Performance Evaluation (TAPE). The analysis included land cover dynamics (2002–2024), characterization of the agroecological transition based on the 10 Elements of Agroecology, and 23 economic, environmental, and social indicators. Four farm typologies were identified; among them, Mixed Family Farms (MFF) achieved the highest transition score (CAET = 60.5%) and excelled in crop diversity (64%), soil health (SHI = 4.24), productive autonomy (VA/GVP = 0.69), and household empowerment (FMEF= 85%). Correlation analyses showed strong links between agroecological practices, economic efficiency, and social cohesion. Land cover dynamics revealed a continuous decline in forest cover (12.9% in 2002 to 7.1% in 2024) and an increase in secondary vegetation, underscoring the urgent need for restorative approaches. Overall, farms further along the agroecological transition were more productive, autonomous, and socially cohesive, strengthening territorial resilience. The application of TAPE proved robust multidimensional evidence to support agroecological monitoring and decision-making, with direct implications for land use planning, rural development strategies, and sustainability policies in the Amazon. At the same time, its sensitivity to high baseline biodiversity and to the complex socio-ecological dynamics of the Colombian Amazon underscores the need to refine the methodology in future applications. By addressing these challenges, the study contributes to the broader international debate on agroecological transitions, offering insights relevant for other tropical frontiers and biodiversity-rich regions facing similar pressures. Full article

The fragile karst ecosystem in Southwest China faces severe water scarcity. Since 2000, large-scale ecological restoration programs (e.g., the “Grain for Green” Program) have substantially increased vegetation coverage. Concurrently, climate change has manifested as a distinct warming trend and heightened drought risk in recent decades. Therefore, understanding the synergistic and competing effects of climate change and vegetation restoration on regional evapotranspiration (ET) is critical for projecting water budgets and ensuring the sustainability of ecosystems and water resources within this vital ecological barrier region. This study employs a dual-scenario PT-JPL model (simulating natural vegetation dynamics versus constant coverage) integrated with Sen + MK trend analysis to quantify the spatiotemporal patterns of ET and its components—canopy transpiration (ETc), interception evaporation (ETi), and soil evaporation (ETs)—in Southwest China’s karst region (2000–2018). Furthermore, multiple regression analysis and SEM were utilized to investigate the driving mechanisms of vegetation and climatic factors (temperature, precipitation, radiation, and relative humidity) on changes in ET and its components. The key results demonstrate the following: (1) Vegetation restoration exerted a net positive effect on total ET (+0.44 mm/a) through enhanced ETi (+0.22 mm/a) and ETs (+0.37 mm/a), despite reducing ETc (−0.08 mm/a), revealing trade-offs in water allocation. (2) Radiation dominated ET variability (66.45% of the area exhibiting >50% contribution), while temperature exhibited the most extensive spatial dominance (44.02% of the region), and relative humidity exhibited drought-mediated dual effects (promoting ETi while suppressing ETc). (3) Precipitation exhibited minimal direct influence. Vegetation restoration and climate change collectively drive ET dynamics, with ETc declines indicating potential water stress. These findings elucidate the synergistic regulation of vegetation restoration and climate change on karst ecohydrology, providing critical insights for water resource management in fragile ecosystems globally. Full article