ABSTRACT Soil conservation is a key criterion for evaluating ecological restoration processes and governance effectiveness and is of great significance for socioeconomic development and regional sustainability. However, in karst regions, slow soil formation, poor soil fertility, and rapid soil loss lead to a marked deviation between theoretical potential erosion and actual soil loss. Therefore, traditional evaluation methods based on absolute erosion amounts cannot accurately characterize the actual effectiveness of soil and water conservation. In this study, the Revised Universal Soil Loss Equation (RUSLE) model was modified based on the rock exposure rate, and the soil conservation ratio was introduced to evaluate soil conservation effectiveness in the karst trough valley region of southern China from 2000 to 2023. The results showed that the soil erosion modulus in the karst trough valley region exhibited a continuous decreasing trend during the study period, with a change rate of −2.36 t ha −1 yr −1 , whereas the potential soil erosion modulus and soil conservation modulus increased at rates of 10.93 and 13.47 t ha −1 yr −1 , respectively. Compared with that in 2000, the soil conservation ratio increased by 4.83%. In terms of driving mechanisms, the contribution rates of the normalized difference vegetation index (NDVI) and precipitation to the soil conservation ratio were 72.27% and 6.48%, respectively. This study can provide a scientific basis for evaluating soil and water conservation effectiveness and optimizing rocky desertification control in karst.

ABSTRACT Eco‐geology studies interactions between Earth's surface multi‐sphere structures and their feedback mechanisms under natural and anthropogenic influences. Eco‐geological environment elements maintain organic interconnections and dynamic equilibrium, with stability being crucial for human–nature harmony in urban agglomerations. However, few studies have focused on the integrated and comprehensive assessment of regional eco‐geological environments. Therefore, quantitatively analyzing the evolution of the eco‐geological environment in urban agglomerations and its driving mechanisms is of great significance for long‐term urban planning. Taking the Beijing‐Tianjin‐Hebei region as an example, this study developed a comprehensive evaluation model integrating ecosystem services, ecosystem vulnerability, and geological environment sensitivity and established an Eco‐Geological Environmental Security Index. In addition, spatial statistical methods were employed to uncover the driving mechanisms of eco‐geological environment evolution under multi‐factor causal cascades and interactions. The self‐organizing map (SOM) algorithm was further applied for eco‐geological environment zoning. Results showed the BTH's eco‐geological environment exhibited a spatial pattern of lower values in the northwest and higher values in the southeast, with an overall improving trend. The eco‐geological environment in the northwestern desert, southwestern mountainous, and southeastern plains was predominantly influenced by natural factors, while the northeast was significantly affected by human activities. Furthermore, SOM‐based clustering identified four distinct zones: Northwestern Long‐term Consolidation Zone, Taihang‐Yanshan Key Conservation Zone, Southeastern Stable Development Zone, and Critical Fragile Zone of the Mountain‐Plain Transition Belt. This framework provides a novel methodology for eco‐geology research and supports sustainable development of eco‐geological environments in large urban agglomerations.

ABSTRACT Cultivated land ecological security (CLES) is fundamental to ensuring food security and supporting sustainable socioeconomic development. However, most existing assessments adopt static analytical approaches and treat counties as independent spatial units. This assumption overlooks the inherently interactive and path‐dependent nature of ecological processes across neighboring regions. To address this limitation, this study develops an integrated DPSIR–ESTDA framework that links structured evaluation of internal system conditions with the diagnosis of external spatial interactions. Using county‐level data from the middle and lower reaches of the Yellow River for 2005–2020, a CLES index is constructed through the entropy‐weighted TOPSIS method. The spatiotemporal interaction patterns are then examined through LISA time‐paths and spatiotemporal transition analysis. Results show that CLES exhibits pronounced spatial heterogeneity and stage‐based evolution characteristics, with the spatial gradient shifting from a high east–low west pattern during 2005–2015 to a high west–low east configuration after 2015. Although the system displays strong spatiotemporal dynamism, these fluctuations rarely translate into substantive structural transitions, leaving most counties trapped in their existing ecological levels. Although spatial interactions are widespread across the region, they remain at an early stage of development. Most counties follow trajectories of synergistic decline or positive fault type movements, indicating the absence of a strong, constructive synergistic mechanism. Regional transitions further differentiate into three spatial structural patterns: path lock‐in–endogenous transition, same‐direction transition–transmission resistance, and opposite‐direction transition. Overall, these findings clarify the spatiotemporal dynamics of CLES and provide evidence for spatially differentiated governance strategies.

ABSTRACT Land degradation and climate change are increasingly converging to threaten ecosystem stability, food security, and rural livelihoods in China, making land restoration a critical pathway for strengthening socio‐ecological resilience. However, many existing land restoration decision‐support studies still use simple linear methods, consider ecological, governance, and social factors separately, and do not properly include community resilience and local knowledge under uncertainty, which makes it difficult to select the most suitable restoration strategies. This study proposes an integrated decision‐support framework that combines the analytic network process (ANP), artificial neural networks (ANN), and fuzzy weighted aggregated sum product assessment (fuzzy WASPAS) to prioritize restoration strategies in China. Four main criteria and 16 sub‐criteria were developed in this study. ANP results indicate that ecological stabilization and climate resilience drivers dominate the weighting structure, with vegetation recovery and land‐cover stabilization, soil erosion control, drought tolerance, and long‐term ecosystem stability emerging as the most influential sub‐criteria, while policy alignment and institutional support represent key enabling conditions for implementation. ANN refinement improved the robustness of the ANP‐derived weights by optimizing the distribution of closely competing factors and reducing subjectivity‐driven variability, providing a more stable priority structure for the fuzzy WASPAS strategy evaluation. Using the final ANP–ANN weights, fuzzy WASPAS results rank the seven restoration strategies, showing that the hybrid co‐governance restoration model achieves the highest overall utility, followed by climate‐smart adaptive restoration and community‐led stewardship.

ABSTRACT Salt marsh soils store substantial organic carbon, yet the persistence of this carbon depends on microbial community composition that governs key transformation processes. Coastal reclamation buries former marshes, but how burial alters microbiomes and carbon‐relevant functions through time remains unclear. We investigated successional shifts in soil microbiomes across a reclamation chronosequence in the Yangtze River Estuary and compared buried (historically reclaimed) soils with modern marsh soils using 16S rRNA high‐throughput sequencing. Bacterial diversity declined significantly in buried soils, with Shannon index values decreasing from 7.07–7.24 in modern soils to 6.13–6.55, accompanied by a depth‐related shift from aerobic to anaerobic dominance. Burial duration was the strongest predictor of community composition ( r 2 = 0.6759, p = 0.001), indicating that prolonged burial after reclamation is associated with physicochemical changes that restructure microbiomes. Total organic carbon, total nitrogen, and pH were the main environmental correlates; total organic carbon decreased with depth, consistent with the expansion of anaerobes and intensified carbon and sulfur cycling. Redundancy analysis showed that variation in these soil properties explained 56.61% of community differences. By linking burial‐driven microbial reassembly to measurable soil properties, these findings elucidate the spatiotemporal dynamics of microbial communities in buried salt marshes induced by reclamation and their environmental constraints, providing a theoretical basis for assessing the stability of soil carbon sinks of salt marshes.

ABSTRACT Climate change is urgent and has multifaceted impacts on agricultural production and the national food security system, especially in climate‐vulnerable agricultural economies. The present study assesses the role of climate shocks and agricultural emissions in agricultural productivity and food dependency in China and the European Union (EU). Using the time series data, it adopted the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) methods in empirical estimation. The results show that climate shocks increase (decrease) food dependency (agricultural productivity) in China, whereas climate change decreases agricultural output and food dependency in the EU. On the one hand, agricultural carbon emissions boost (decline) agricultural productivity (food dependency) in China and stimulate it in the EU. In the robust analysis, the canonical cointegrating regression (CCR) confirms the results of the regression. Overall, the study provides comprehensive and cohesive climate policies for sustainable food supplies and agricultural production. From a policy suggestion, China and the EU need to accelerate the adoption of smart agriculture technologies—such as precision farming, digital monitoring systems, climate forecasting tools, and data‐driven irrigation—to enhance input efficiency, reduce environmental externalities, and stabilize production under climate uncertainty.

ABSTRACT Páramos are neotropical mountain ecosystems that regulate water and store large amounts of carbon, but are increasingly degraded by agriculture and grazing. Although native vegetation often recolonizes after abandonment, belowground recovery remains poorly understood. We tested whether natural regeneration over contrasting recovery times yields parallel recovery of soil properties, arbuscular mycorrhizal fungi (AMF) abundance, and root‐associated fungal community composition. We compared two naturally regenerating sites in the Cumbal páramo (Nariño, Colombia) representing 12 and 45 years since disturbance. We measured soil properties, quantified AMF root colonization and spore density, and profiled root‐associated fungi using ITS metabarcoding. Soil organic matter and organic carbon showed no significant differences between sites, reaching comparable levels after 12 years of recovery. In contrast, soil fertility indicators increased with recovery time, with cation exchange capacity rising by ~8% and available phosphorus by ~21% at the long‐recovery site. AMF colonization decreased with recovery time (51.2%–44.6%), whereas spore density did not differ between sites and was highly variable. Alpha diversity of the root‐associated fungal community did not differ between sites. However, PERMANOVA showed that community composition varied with host plant species, recovery site, and their interaction, and redundancy analysis identified cation exchange capacity as the main edaphic correlate of community structure. Overall, results reveal a temporal decoupling between rapid vegetation/carbon recovery and slower, sometimes incomplete, recovery of soil fertility, highlighting root‐associated fungi and AMF functional metrics as sensitive indicators of belowground recovery and supports their application in nature‐based restoration and monitoring of high‐mountain páramo ecosystems.

ABSTRACT Soil transport through uprooted trees represents a crucial soil disturbance agent in many forest ecosystems. In addition to tree species and forest structure, tree throw dynamics strongly depend on the character of wind flow and specifically on extreme wind events. The tracks of extra‐tropical cyclonic storms are typically west–east in Europe and the disturbances cause major pulses in forest slope dynamics. In the regime of rare but powerful winds alternating with long periods of low‐intensity wind flows, slope exposure can be a significant geomorphological driver. Slope orientation can hypothetically affect the frequency of uprooting events and the direction of tree falls. Tree orientation determines how much of the uprooted soil will return to the tree throw pit and how much will be eroded. These aspects were explored for the first time, using extensive repeated tree census data spanning from 1975 to 2007 collected in Žofínský Primeval Forest Reserve in Novohradské Mountains, Czech Republic. We analyzed differences between spatial configuration and biogeomorphic potential of uprootings under two scenarios—extreme windthrow related to a strong disturbance event and selective uprooting associated with forest gap dynamics. Wind observations (direction and speed) were used to define the relationship between uprooting intensity and spatiotemporal linkages of uprooted tree azimuths with wind and terrain properties (elevation and aspect). We found differences in tree stem azimuths of uprootings, in their spatial configuration against elevation contour lines, and terrain aspect. The differences were found for upslope and downslope uprooting categories, and two forest developmental trajectories—the first one dominated by gap‐dynamic treefall (associated with selective tree mortality), and the second one dominated by treefall caused by extreme storms such as the Kyrill storm in January 2007. Azimuths of uprootings followed prevailing wind directions, suggesting this metric can be used as a bioindicator of wind properties in places without standard meteorological measurements. Norway spruce ( Picea abies ) was the most commonly uprooted and broken tree species. Upslope uprooting was more common, potentially involving higher soil mass volume being subjected to mixing than erosion. Our results show that slope aspect is a terrain feature which modulates the developmental trajectory of an old‐growth forest and soil. The changes in the forest development happen during extreme wind events which act occasionally but with great force over the European land. It is important to underline the synergistic critical impact of such geomorphic features as slope aspect and strong wind events on soils and forests, especially in the context of the expected increase in the extremity of various climate parameters, including wind speed and frequency of strong winds. The study brings new results on soil mixing/transport and forest damage evaluation using high‐resolution and long‐term monitoring data with implications for changes in soils, and shifts in forest development trajectories.

ABSTRACT Sustainable land use in degraded ecosystems is increasingly constrained by climate pressure, yet the role of governance remains unevenly explained. This study examines whether economic governance and policy innovation improve sustainable land use efficiency (SLUE) under climate stress and whether these effects spill over across cities. Using a city‐year panel of 200 Chinese prefecture‐level cities from 2005 to 2020, SLUE is measured with a DEA framework and then analyzed with two‐way fixed effects and a spatial Durbin model under inverse‐distance and rook‐contiguity matrices. The local estimates show that economic governance and policy innovation are positively associated with SLUE, whereas climate pressure is negatively associated with it. In the fully controlled baseline model, a 1% increase in economic governance and policy innovation is associated with about a 0.0259% and 0.0184% increase in SLUE, while a 1% increase in climate pressure is associated with a 0.0292% decline. Spatial results show positive clustering in SLUE, negative climate spillovers from neighboring cities, and short‐run adverse neighbor effects of governance and policy upgrading under immediate contiguity. The findings indicate that land policy in degraded ecosystems should combine local implementation capacity, adaptive policy design, and cross‐city coordination under shared climate stress.