The wildland–urban interface (WUI) refers to zones where buildings intersect with undeveloped wildland vegetation, and identifying its ecological effects is crucial for understanding human–environment conflicts in relation to landscapes. Current WUI assessments have focused primarily on areas with high-density human activity in developed countries, with limited evidence of vegetation degradation in ecologically vulnerable regions with rapid increases in human activity, e.g., the Qinghai-Tibetan Plateau (QTP). We mapped the WUI at a 100-m resolution from 2000 to 2020 on the QTP and quantified vegetation greenness degradation within WUI expansion areas based on the normalized difference vegetation index (NDVI), leaf area index (LAI) and solar-induced chlorophyll fluorescence (SIF), using propensity score matching (PSM) to control for environmental covariate bias and a difference-in-differences (DiD) approach to eliminate background temporal trends, thereby quantifying the net suppressive effect of WUI expansion on vegetation.The results revealed that the WUI area expanded by 48% over the 20-year period, and the expansion was concentrated mainly at the western, southern, southeastern, and eastern margins of the QTP. Urban expansion had a mean total contribution of 89.6% to WUI expansion, approximately 9 times that of wildland. LAI degradation was 11.57%, NDVI degradation was 2.48%, and SIF degradation was 2.06%; all three indicators exhibited consistent degradation directions, confirming that the impact of WUI expansion on vegetation is dominated by leaf area loss and canopy structural simplification. Direct land conversion is the primary driver of LAI degradation, which proceeds through multiple pathways including direct clearing, landscape reorganisation with fragmentation amplification, and the concentration of grazing pressure.

The asynchronous changes in vegetation greenness and resilience (the capacity of ecosystems to absorb disturbances and maintain their functions) may threaten the long-term sustainability of ecological restoration. However, their coupling mechanisms and responses to climate change and human activities in desertification areas remain poorly understood. Here, we used the kernelized Normalized Difference Vegetation Index (kNDVI) and its temporal autocorrelation to characterize vegetation greenness and resilience from 2000 to 2020 in Yellow River Basin in Inner Mongolia, China. Random forest (RF) models were employed to quantify the dominant drivers of vegetation resilience. Results indicate a persistent greening trend across the study region, 96.62% of pixels experienced kNDVI increases. Meanwhile, resilience exhibits a pronounced turning point around 2011, transitioning from an increasing to a declining trajectory, while the proportion of resilience-declining areas increased from 18.09% in 2000–2010 to 45.85% in 2011–2020. The greenness–resilience relationship transitioned from synchronous increases to systematic decoupling, resulting in a high-greenness–low-resilience regime. The dominant drivers of vegetation resilience shifted from climate factors during 2000–2010 (contributing 51.57%) to grazing pressure during 2011–2020 (contributing 32.12%). Threshold analysis further revealed that vegetation resilience decline in the later decade resulted from the combined effects of intensified hydrological constraints and grazing pressure. Therefore, we recommend incorporating ecosystem resilience into restoration frameworks and coordinating the regulation of water availability and grazing pressure to promote the synergistic enhancement of greenness and resilience, thereby ensuring long-term ecosystem stability.

Drylands, among Earth's most vulnerable and climate-sensitive regions, face growing challenges in sustainable landscape management due to combined pressures from climate change and agricultural expansion and intensification. Existing evidence, however, is limited by short temporal coverage, insufficient spatial explicitness, and incomplete characterization of environmental pressures in these systems. This study integrates newly released multi-source long-term datasets to provide the first spatially explicit assessment of relationships between agricultural landscape dynamics, grazing intensity, and water-related environmental pressures across global drylands over a continuous 60-year period (1960-2019). The key findings include: global dryland cropland expanded by approximately 6.1×10⁵ km², primarily replacing grasslands; pastureland increased by about 5.1×10⁵ km², with over half originating from previously sparse land; dryland cropland fragmentation increased globally, though decreasing trends occurred in South America, Africa, and Oceania; Spatial correlation analyses show roughly equal proportions of positive and negative relationships between terrestrial water storage (TWS) and cropland area, while positive correlations between TWS and pasture area slightly exceeded negative ones; regionally, concurrent TWS decline and cropland expansion dominated in Europe, Asia, and South America, while Europe showed pronounced TWS decline alongside shrinking pastureland; in areas with significant changes in both livestock numbers and pasture area, simultaneous increases in both accounted for 27.5% globally, with Asia showing the highest proportion (35.2%). This 60-year assessment underscores the urgent need to prioritize sustainable landscape management in Asian and African drylands by curbing excessive cropland expansion and overgrazing, strengthening water security, and regulating grazing intensity.

Resilience plays a crucial role in maintaining desirable ecosystem states and is a key objective of sustainable ecosystem management. This study synthesizes the concepts and measurement approaches of terrestrial ecosystem resilience and expounded on its spatio-temporal changes and influencing factors based on the literature over the past 50 years. Arid regions exhibited the lowest levels of spatial resilience, and the global ecosystem resilience showed a downward trend. In the focal regions, ecological resilience in Amazonian and Southeast Asian rainforest regions declined primarily driven by human activities such as deforestation and cropland expansion. Precipitation and temperature exerted bidirectional influences the resilience of ecosystems, indicating that ecosystem responses to climatic factors were non-monotonic. Evidence concerning anthropogenic factors such as land management and deforestation on ecosystem resilience were predominantly negative. Overall, this study provides a comprehensive synthesis of large scale terrestrial ecosystem resilience assessments, offering valuable insights for ecosystem protection and restoration policy development.

Managing grazing regimes is a key strategy for promoting the sustainable use of grasslands. The Qinghai-Xizang Plateau, dominated by alpine grasslands, is subjected to extensive grazing by livestock. Apart from some control experiments, the regional impact of livestock species on alpine grassland has been overlooked, mostly due to the spatial mismatch between statistical livestock data and grassland biomass data. Using cross-scale feature extraction and random forest models, we developed a 1 km & times; 1 km gridded long-term grazing intensity data set distinguishing between herbivore types between cattle and sheep from 2000 to 2019. We used the propensity score matching method to identify the impact of grazing intensity and herbivore types on aboveground biomass on the Qinghai-Xizang Plateau. The data set demonstrated strong spatio-temporal consistency with county-level statistics, with R2 values above 0.9 and Nash-Sutcliffe efficiency (NSE) ranging from 0.93 to 0.98. The interannual trends of sheep (mainly Tibetan sheep) and cattle (mainly yaks) were largely opposite, with a significant decline in the sheep-to-cattle ratio in 42% of areas. At high grazing intensity, the aboveground biomass increase rate was slower, and aboveground biomass decreased more rapidly with an increasing sheep-to-cattle ratio. These findings advance our understanding of the spatio-temporal dynamics of grazing intensity on the Qinghai-Xizang Plateau and provide new insights into how grazing intensity and herbivore composition jointly shape alpine grassland productivity at the landscape scale.

International trade serves as a crucial pathway for enhancing global food security and equality amid severe food crises worldwide. Under globalization, economic development has profoundly influenced food trade, while disparities in food purchasing power among different economic development groups have led to uneven food security outcomes. However, the varying contributions of international trade to food security across these groups remain to be quantitatively elucidated. This study categorized countries into four economic development groups—high, high-medium, medium-low, and low—and examined changes in their food security scores from 2010 to 2019. The cross-group contributions of international trade to food security across these groups were compared. The results revealed that the food security score of the high economic development group was 9.22 times higher than that of the low economic development group. From 2010 to 2019, the high economic development group exhibited a significant upward trend in food security scores, whereas the low economic development group showed a significant decline. Moreover, international trade contributed significantly to both cross-group and within-group food security in the high economic development group, while its contribution to the low economic development group remained negligible. These findings demonstrated that international trade has further widened the food security gap between the high and low economic development groups, and its limited contribution to the low economic development group has failed to reverse the declining trend in their food security scores. This study quantified the divergent impacts of international trade on food security across economic development groups, providing valuable insights for optimizing global food trade policies—particularly in addressing the food security challenges faced by low econominc development group.

The environmentalist's paradox refers to the pattern where increases in human well-being accompany decreases in ecosystem services (ES). IPBES has introduced the concept of Nature's Contributions to People (NCP), which provides a more pluralistic and inclusive framework than traditional ES. However, it remains unclear whether the NCP context supports the environmentalist's paradox or offers new insights. We used linear mixed-effects models (LMM) and network analysis to assess how changes in human well-being impact NCPs, both quantitatively and structurally, using the Human Development Index (HDI) and NCP assessment data for 15,204 global basins. Quantitatively, our LMM analysis suggests that the validity of the paradox varies across NCP types. Along the HDI gradient, 66%-72% of NCPs showed either no significant change or even an increasing trend. Structurally, our network analysis shows that interactions among NCPs exhibited nonlinear variation, and the synergistic relationship network became highly coupled during periods of rapid HDI increase. This implies that the impact of a decrease in a single NCP could be amplified through the highly coupled network. Compared with drylands, humid areas exhibited more severe trends of NCP decrease and higher coupling of synergistic relationship networks. These findings deepen the understanding of the environmentalist's paradox on the relationship between NCPs and human well-being, and can assist in identifying priorities for sustainable action in countries at different stages of human well-being development.

The rapid urbanization has significantly accelerated the expansion of cities and led to a notable increase in urban land surface temperature (LST). Currently, most studies mainly examine the effects of two-dimensional (2D) landscape patterns on LST variations, and research investigating the relationship between three-dimensional (3D) urban landscape patterns and LST remains relatively scarce. Therefore, this study utilizes partial correlation analysis and piecewise linear regression to systematically investigate the impacts of gray landscape indicators on LST variations under both 2D and 3D urban patterns, aiming to elucidate the complex relationship between 3D urban landscape patterns and LST dynamics. The results demonstrate that specific 3D building characteristics, particularly the area of low-rise buildings, building aggregation degree, shape complexity, and patch density of mid-rise buildings, serve as effective indicators of urban thermal environment risk. The analysis reveals that increased area-related indicators for low-rise buildings significantly exacerbate the LST rise, whereas modifications to the landscape shape of middle and high-rise buildings contribute to thermal mitigation. Additionally, when gray landscape aggregation exceeds 80 %, the spatial concentration of mid-rise buildings exhibits a pronounced positive effect on moderating urban LST. These findings elucidate the mechanisms through which 3D landscape patterns influence urban thermal risks in Beijing, advancing the understanding of urban landscape-ecological processes interactions and providing crucial scientific support for landscape optimization and urban thermal environment risk mitigation strategies.

Forest resilience characterizes the capability of forest ecosystems to recover from perturbations. With the global increase in the occurrence of multi-year drought (MYD) events and anthropogenic pressures on terrestrial ecosystems, the resilience of forest ecosystems to extreme multi-year droughts and how it interferes with human pressures is, however, largely unexplored. On the basis of the temporal autocorrelation of the kernel-normalized difference vegetation index, we mapped the spatial patterns of resilience of global forests before and after MYDs. We found diminished resilience in over 70.9% of forests after the top-10 MYDs as compared to the prior situation. Species richness was the primary factor of the spatial variation of forest resilience, followed by vapour pressure deficit, temperature and soil moisture. Across different forest types, plant species richness showed distinct relationships with resilience, exhibiting both positive and negative associations. However, after accounting for human footprint, its contribution became consistently and strongly negative. Managed forests had lower resilience than undisturbed forests to MYDs, especially in the deciduous needle-leaved forest of the boreal regions. These findings underscore the importance of mitigating human pressure for maintaining forest resilience under extreme climatic disturbances.

Abstract Revegetation mitigates climate change through carbon sequestration but intensifies water conflicts between ecosystems and human demands in water-limited regions. This study quantified not only the revegetation potential but also the allowable vegetation conversions in China’s drylands under water constraints using a multidata ensemble approach. The ensemble estimate of available water resources (AWR) was 65.4 ± 13 mm [median ± standard deviation (SD)] in water surplus areas (covering 55% of the region) and −39.1 ± 7 mm in water deficit areas of China’s drylands averaged over 2003–18. The ensemble of nine precipitation and evapotranspiration data combinations effectively reduced estimation uncertainty compared with most single-dataset combinations. Under current water constraints, the median estimate of gross primary productivity gain associated with revegetation ranged from 4% to 7% across the drylands depending on vegetation types and 12%–17% in water surplus areas (forests: 14%, grasslands: 17%, both irrigated and rain-fed crops: 12%). Crucially, in water surplus areas, vegetation conversions toward higher water consumption types were feasible. In contrast, in most water deficit areas, the deficit cannot be fully offset by converting existing vegetation to less water-intensive types, suggesting a critical deficit under the current accounting framework. Future revegetation potential will increase with improved water use efficiency and rising AWR under the impacts of climate change. Our research highlights the importance of water constraints on revegetation and the vegetation-specific water costs and carbon benefits, which are critical to implementing natural climate solutions while ensuring water sustainability. Significance Statement Revegetation is a key natural climate solution but risks intensifying water stress in drylands. This study maps where and how much vegetation increase can be sustainably supported across China’s drylands under water constraints. Using a multidataset ensemble that effectively mitigates the high uncertainty of single-data approaches, we found that over half of the region retains a water surplus, allowing for vegetation growth that could increase carbon uptake by up to 17%. However, in water deficit areas, vegetation conversion alone cannot offset the deficit. Our findings provide a credible water budget for drylands, emphasizing that revegetation or vegetation conversion plans must align with water availability to secure carbon and water sustainability.

Ambitious conservation efforts are needed to curb biodiversity loss as drought severity intensifies globally. Here, we assess the exposure of resident terrestrial vertebrates within global biodiversity hotspots to drought severity surpassing the extremes experienced during their pre-industrial history. We show that 22.5% of threatened terrestrial vertebrates (especially reptiles and amphibians) have recently experienced drought severity exceeding their historical extremes across at least half of their current geographic range. Under an intermediate greenhouse gas emission scenario (Shared Socioeconomic Pathway 2-4.5), this proportion is projected to reach 36.5% by the latter half of the 21st century, with mid-latitude dryland biodiversity hotspots facing the most severe drought exposure. Importantly, a low-warming future (Shared Socioeconomic Pathway 1-2.6) will reduce exposure estimates of species by 8.5% compared to Shared Socioeconomic Pathway 2-4.5, highlighting the urgency of ambitious climate mitigation. However, as future drought exposure is projected to increase across most biodiversity hotspots, and many exposed regions face inadequate protection and substantial social burdens, expanding adaptive conservation without compromising local well-being is essential. Our findings offer spatial guidance for prioritizing conservation and adaptive strategies in biodiversity hotspots, contributing to global biodiversity targets.

Natural capital refers to the stock of natural resources that generates flows of goods and services benefiting human well-being. Over the past 30 years, increasing attention has been paid to natural capital valuation and mapping. However, notable differences remain in how natural capital valuation is conceptualized, and systematic summaries of the valuation methods used are still lacking. We propose a concise conceptual framework that aims to clarify natural capital valuation and its relationship with ecosystem service valuation. We subsequently conducted a literature search, screening, and mapping of data related to natural capital valuation, ultimately identifying 54 relevant publications. These publications were classified into three categories according to different methods: M1 emergy accounting; M2 ecosystem service valuation; and M3 other methods. Existing assessments show that the monetary value of natural capital varies across regions. For example, illustrative case studies show that the monetary value of natural capital is increasing in the temperate climatic regions of China but is decreasing in Europe, with relatively limited monetary valuation assessments in tropical climatic regions. Existing publications show that the valuation results derived via emergy accounting methods are higher on average than those obtained from ecosystem service valuation. Our systematic review of natural capital valuation highlights the recent research hotspots and the similarities and differences in the results of different valuation approaches. This study can provide a reference for the selection of study areas and methods for future natural capital valuation research and support regional and global natural capital valuation.

Armed conflict is closely associated with food insecurity, but its impact on interregional food movement remains insufficiently understood, especially in data-scarce regions. Here we develop a path-based framework to assess food system exposure to armed conflict in the Sahel and Lake Chad Region. We combine staple food supply and demand data, road networks, and armed conflict event records to simulate potential staple food calorie flows in 2022. A gravity model allocates surplus calories from supply areas to demand areas, and a minimum cost path algorithm identifies transport paths; conflict exposure is then assessed for supply areas, demand areas, and flow paths. The results show potential for internal calorie redistribution under idealized conditions, with 47.9% of staple food calories participating in interregional redistribution. Armed conflict-impact zones directly overlap with 3.9% of the region’s total cropland, but intersect 91.3% of the simulated flow paths. These findings suggest that regional food system vulnerability is shaped by the spatial alignment between transport corridors and conflict exposure. Even where foods are available, conflict often coincides with key routes, most essential flows traverse exposed networks, heightening food insecurity, according to a 2022 Sahel and Lake Chad Region network simulation using gravity models and road data.

The Three-North Shelterbelt Forest Program (TNSFP) is a key ecological initiative in China's arid and semi-arid regions, vital for wind prevention, sand fixation, and ecological restoration. However, long-term drought, extreme climate events, and human disturbances have threatened forest ecosystem stability. A systematic understanding of these disturbance and degradation patterns is lacking, hindering effective restoration strategies. This study aims to identify forest disturbances in the TNSFP from 1991 to 2021 and reveal their spatiotemporal patterns under varying climatic aridity gradients. Using annual Landsat imagery, four indices—NDVI, NBR, SWIR1, and SWIR2—were constructed. The LandTrendr algorithm was applied to extract multi-parameter degradation features, integrated with Hansen Forest Loss Data and the Random Forest model for disturbance classification (OA = 0.96, Kappa = 0.94). Results show that forest degradation peaked in the 1990s, with a decline in degraded areas over time. The high-density degradation zones were mainly in the Greater Khingan Mountains, Changbai Mountains, Loess Plateau, and Altay Mountains. Degradation characteristics such as duration, NDVI decline, and rate varied regionally. Northeastern areas of TNSFP showed slow degradation, while the Loess Plateau and northern Changbai Mountains experienced rapid degradation. Arid regions showed long-duration degradation but weak intensity, while humid regions showed high degradation rates. The findings provide technical support for understanding forest disturbance dynamics and degradation patterns.

Between 2023 and 2024, Amazonian rainforests experienced two consecutive, record-breaking droughts-each more intense than any previously observed-yet their impacts remain largely unquantified. Using newly developed monthly radar satellite observations (1992 to 2025) that track forest moisture and biomass dynamics, we analyzed the long-term responses of intact Amazonian rainforests to past major droughts-particularly the 2023-2024 event-and projected their post-drought recovery. We found a biome-wide sharp decline in radar signal during 2023-2024, marking the lowest level observed since 1992. Spatially, 26.8% of the forests reached their three-decade minima during this period, primarily in eastern Amazonia. This ratio is more than double that recorded during the 2005 drought, when 11.0% of the forests reached such minima. Moreover, projections based on both historical and future CMIP6 precipitation scenarios consistently indicated that, even 7 y after the 2023-2024 droughts, less than 50% of the affected areas are expected to recover to predrought conditions, and these forests are associated with lower soil cation concentrations, higher soil sand content, and lower canopy height-characteristics that lessen the risk of hydraulic failure. Given that severe droughts have occurred approximately every 7 y over the past three decades, Amazonian rainforests may face another drought before fully recovering from the 2023-2024 event. Our results therefore highlight the growing vulnerability of the Amazonian rainforests to intensifying climate extremes driven by El Niño events and ongoing anthropogenic climate change, providing evidence that these forests are approaching the limits of their preindustrial operating space.