Forest fires present a significant threat to both ecosystems and socio-economic systems, making accurate risk assessment essential for effective prevention and control. However, conventional assessment approaches are often limited by subjective bias, incomplete indicator frameworks, or a reliance on static analysis, which hinders a comprehensive understanding of the multidimensional drivers and spatiotemporal evolution of fire risk. To address these gaps, this study proposes an integrated forest fire risk assessment model that incorporates natural, social, and economic dimensions. An improved G1–CRITIC combined weighting method is applied to determine indicator weights, effectively balancing expert judgment with objective data metrics. The model was implemented using multi-source data from 2013 to 2022–including remote sensing imagery, government statistics, and field survey data–in Huangu Town, Ankang City, Shaanxi Province. The results show that the model reliably assesses regional forest fire risk levels and successfully delineates their spatiotemporal dynamics. Correlation analyses further confirm the robustness of the model. The study reveals that forest fire risk is co-driven by natural and socio-economic systems: natural factors predominantly influence short-term fluctuations, whereas socio-economic factors shape long-term trends. By overcoming several limitations of traditional methods, the proposed model enables a dynamic and multi-factor driven analysis of forest fire risk. These findings offer a scientific foundation for phased, zoned, and graded precision management of forest fire prevention, as well as for the optimized allocation of firefighting resources.

Net Ecosystem Productivity (NEP) serves as a critical metric for evaluating the carbon sequestration capability of forest ecosystems. As a vast territory forming a vital ecological shield in northern China, Xinjiang possesses notably complex and varied forest environments, making an assessment of its ecosystem carbon cycle's spatial patterns and climatic responses highly significant. This study employed the Integrated Terrestrial Ecosystem Carbon-budget (InTEC) model, driven by multi-source remote sensing and reanalysis datasets for meteorology, vegetation, soil, and topography, to simulate the spatiotemporal dynamics of Xinjiang's forest NEP from 1901 to 2060. Using trend and partial correlation analyses, this study examined the spatiotemporal evolution of forest NEP and its response to changing climatic factors under three representative concentration pathways from the Coupled Model Intercomparison Project Phase 6 (CMIP6): SSP126, SSP245, and SSP585. The results indicate that: (1) For the 1901-2022 period, the average forest NEP in Xinjiang was 47.81 g C·m −2 ·yr −1 , demonstrating a fluctuating upward trend at an average rate of 0.52 g C·m −2 ·yr −1 . The overall spatial pattern showed higher values in the east and north compared to the west and south. (2) The carbon fixation potential of Xinjiang's forests under the SSP126 scenario is projected to be considerably higher than under other scenarios. The mean annual NEP values for 2023-2060 are estimated to be 122.88, 114.28, and 108.54 g C·m −2 ·yr −1 for the three respective scenarios. While NEP is expected to increase with fluctuations until around 2035 in all pathways, a decline may occur after 2045 under high-emission scenarios, potentially due to elevated temperatures, drought, frequent extreme events, and substantial increases in nitrogen deposition. This decrease is anticipated to be concentrated in the piedmont plains of the Tianshan Mountains and the areas surrounding the Tarim Basin. (3) The positive control of precipitation on Xinjiang's forest NEP is stronger than that of temperature. The partial correlation between temperature and NEP shows significant geographical differentiation, being positive in cool, humid montane forests and negative in hot, arid regions. Solar radiation and vapor pressure exhibit a distinct positive relationship with forest NEP, affecting 76.23% and 63.83% of the study area, respectively. These findings reveal the centennial-scale spatiotemporal dynamics of forest NEP in Xinjiang and its future carbon uptake potential, providing a valuable reference for assessing the region's carbon sequestration capacity.

In the Amazon, shifting cultivation has historically shaped the landscape and remains a key land-use system practiced by traditional communities. The ecological sustainability of this system depends on the regeneration capacity of forests between cultivation cycles. In this study, we investigated mechanisms regulating the recovery of soil macrofauna during natural regeneration of areas previously managed via slash-and-burn agriculture, evaluating the effects of fallow age, environmental variables, and trophic interactions on macrofauna diversity and community composition. We sampled 40 plots along a successional gradient from 1 to >80 years and collected soil and vegetation data. We used structural equation modeling, generalized additive models, and multivariate analysis to understand observed patterns. Fallow age did not directly affect macrofauna but exerted an indirect effect through vegetation. We also observed a top-down effect of predators on herbivores, detritivores, and geophages, highlighting the role of trophic interactions in structuring soil communities. These findings reinforce that sustainability of shifting cultivation should not be assessed solely on fallow age or vegetation cover but on the capacity of the regenerated system to sustain ecological functions. Given effective vegetation regeneration and a landscape favoring ecosystem resilience, this traditional land-use system can contribute to biodiversity and soil functionality restoration.

Future forests will have to face compound climate events such as hotter droughts as climate keeps warming. A better understanding of tree growth resilience to such extreme droughts is key to better inform future forests capacity to provide ecosystem services. Arboreta provide a suitable setting to assess the capacity of tree species from different origins to respond to drought under similar climatic conditions. However, the comparison of growth trajectories and growth resilience to drought of arboretum trees are still scarce, particularly for temperate oaks, a major group of trees with remarkable ecological and economical values across the northern Hemisphere. We propose that the comparison of the post-drought growth resilience of oaks co-occurring in an arboretum along with bioclimatic variables, and functional (wood and leaf) traits can help to identify vulnerable species in sight of climate change. To this end, we studied 20 oak species originating from different regions around the world, planted in the Iturrarán botanical garden located in Northern Spain. Dendrochronology was used to calculate growth statistics and resilience indices during the exceptionally hot 2022 drought. These indices were related to: bioclimatic variables, tree diameter, leaf (leaf area, leaf mass per area) and xylem traits (wood density, hydraulic diameter, conductive area, Huber value). Additionally, we compared resilience and drought legacies for eight oak species sampled in the arboretum and in the field, respectively. All oak species showed marked growth reductions in the year 2022. Diameter and mean ring width covaried with leaf traits and wood density since wider rings were observed in species with lower leaf mass per area. Resilience to the 2022 drought was related to the precipitation of origin of each species. The resilience data of the eight oak species sampled in the arboretum and in the field showed a weak positive, but not significant relationship. Among-tested variables, precipitation-of-origin explains the largest share of the variation in resilience to drought. Tree-ring data from arboreta trees provide relevant information which can be used to better preserve and manage temperate forests subjected to more arid conditions.

Soil scarification, which involves the disruption of the top layer of soil, is a common method utilized to promote the regeneration of tree species on clear-cut and calamity areas. In the context of adapting forests to become climate-resilient mixed species forests, this method could also be used to promote tree regeneration under intact canopies, either exclusively or in combination with direct seeding. However, evidence on the impact of this method on the composition of forest floor vegetation, including bryophytes, is lacking and needs to be investigated. This is of importance because the forest floor vegetation significantly contributes to species richness in temperate forests. To address how and to what extent soil scarification affects the forest floor species composition, we conducted a space-for-time-substitution study, creating a chronosequence spanning a 13-year period, to investigate the effect of soil scarification on forest floor vegetation in Norway spruce ( Picea abies ) stands in a lower montane forest in central Germany. Our results showed that soil scarifications were quickly recolonized by bryophyte species, whereas herbaceous species cover took around a decade to reach a similar level of establishment as the undisturbed forest floor. Species composition initially shifted in favor of early successional species. In the long term, however, the species composition converged back to the undisturbed state. Tree regeneration diversity especially benefitted from scarification, making it a viable method for intact forest stands, particularly given that it does not appear to exert any adverse effect on forest floor vegetation.

Introduction Maintaining the stability of forest ecosystem functions and mitigating climate-driven declines in ecosystem multifunctionality (EMF) are central objectives of contemporary forest management. Methods We evaluated the spatial stability of 11 forest ecosystem functions and overall multifunctionality using data from 2,859 natural forest plots in South Korea’s 7th National Forest Inventory. Specifically, we investigated how biotic factors (species, functional, and structural diversity), abiotic factors (elevation and aridity), and stand age influence the spatial stability of EMF and individual functions. Variance partitioning and regression analyses were conducted to determine the relative contributions of these factors. Results Biodiversity-related biotic factors—particularly species richness and structural diversity—were the main determinants of spatial stability for most individual functions and multifunctionality, generally showing positive effects. However, these relationships varied among different functions. Among abiotic variables, higher elevations and lower water stress (i.e., a higher aridity index) were associated with greater stability. In addition, community-weighted means of functional traits influenced EMF, with maximum tree height showing a particularly strong link to multifunctionality and its stability. Discussion Overall, our findings underscore the importance of developing targeted management strategies to enhance EMF and individual ecosystem functions. They further suggest that biodiversity alone does not guarantee stability across all ecosystem functions, highlighting the need to consider both biotic and abiotic contexts in forest management planning.

Greenhouse gas emissions have contributed to climate change, resulting in significant environmental and socioeconomic consequences, including rising sea levels and more frequent extreme weather events. The urgency to mitigate these effects has motivated governments and industries to seek innovative solutions that reduce carbon footprints and promote sustainability. Sustainable forest management practices, which aim to maximize carbon storage in both forests and forest products, offer a powerful strategy to reduce atmospheric CO₂. This study explores how market-based mechanisms, such as forest carbon programs, can help meet greenhouse gas reduction targets in accordance with international agreements, including the Kyoto Protocol. By examining corporate timber companies’ participation in carbon markets, the study highlights how sustainable forestry practices align with economic goals while reducing atmospheric CO₂ levels. Through a strategic assessment of literature and interviews with decision-makers in corporate forestry, this research study examines the motivations, barriers, and opportunities for carbon market integration, climate policy priorities, and the potential to scale up corporate involvement in carbon projects.

Introduction Urban trees are essential for mitigating elevated temperatures in cities worldwide, with many municipalities implementing large-scale urban tree planting initiatives. However, the cooling potential of tree canopy coverage is often estimated as a constant value across study areas, despite evidence that temperature reductions depend on local characteristics, including tree traits and urban geometry. Methods We evaluated the ability of Bayesian Spatially Varying Coefficient (SVC) models to capture local variability in the cooling potential of urban trees. The model, implemented in R-INLA, integrated Landsat 8 and 9 Land Surface Temperature (LST) data with aerial LiDAR data. Model performance was assessed using validation metrics obtained through 10-fold spatial cross-validation. Results Although the SVC did not outperform simpler spatio-temporal approaches according to validation metrics, the spatial distribution of local canopy cooling capacity revealed substantial spatial variability. Average estimated values of canopy cooling capacity on LST (defined as the change in LST associated with a 10% increase in tree canopy cover) were −0.28 °C in vacant lands and −0.09 °C in wooded areas. Discussion By providing local estimates, our model underscores how the cooling capacity of tree canopy in built-up environments varies substantially across space. This finding demonstrates the importance of accounting for local environmental characteristics in urban planning and serves as an example of a modeling approach that integrates both local-scale variability in canopy cooling capacity and spatial extent. These results encourage policymakers to adopt context-specific strategies for urban tree planting initiatives rather than applying uniform approaches.

Tropical uplands provide essential ecological functions and socio-economic benefits, but they are rapidly degrading due to deforestation and unsustainable agriculture. This leads directly to severe soil erosion and biodiversity loss. Critically, current restoration efforts are often small-scale, ecologically inefficient, and poorly integrated with local socio-economic needs, resulting in fragmented and ultimately unsustainable outcomes. Conventional reforestation efforts often fall short due to high costs, low seedling survival, and limited community involvement. This perspective presents an integrated framework for upland restoration that combines cutting-edge technology, nature-based solutions, and circular bioeconomy principles. Unmanned aerial vehicles (UAVs) or drones offer a scalable and precise method for distributing seedballs and monitoring ecological progress in challenging terrain, greatly reducing labor and time. Complementary to this, the use of arbuscular mycorrhizal fungi (AMF) improves plant establishment by enhancing nutrient uptake, water absorption, and microbial diversity, particularly in degraded soils. These innovations are unified under a circular bioeconomy model, which promotes the use of biodegradable inputs, local biomass, and species with ecological and economic value. The synergy of these elements results in a modular, adaptive, and community-based system that enhances ecological function while generating rural employment and reducing dependence on external inputs. The model is applicable across diverse restoration contexts and aligns with broader sustainability goals. Through integrating technology, biology, and circular systems thinking, this framework offer adaptive and innovative approaches to restoration for supporting global agendas such as the UN Decade on Ecosystem Restoration and the Sustainable Development Goals.