Forests

Environmental regulations serve as a critical determinant of industrial competitiveness in the global market. Recent policy shifts have driven a gradual convergence of rural environmental standards with urban norms, fostering a dynamic landscape of “top-down competition” between urban and rural regulatory frameworks. While the economic consequences of regional regulatory disparities are well-documented, the specific impacts of this regulatory convergence remain insufficiently explored. To address this gap, this study constructs a novel index to measure the convergence of environmental regulations between urban districts and rural counties at the prefecture level. Utilizing an unbalanced panel dataset of 5600 county-level timber processing enterprises, the Heckman two-stage model is employed for empirical analysis. The results demonstrate that the convergence of urban and rural environmental regulations significantly enhances both the export probability and export intensity of county-level firms, with these effects exhibiting persistence and cumulative growth over time. These findings remain robust across a series of validation tests, including instrumental variable estimation, double machine learning, and alternative model specifications. Mechanism analysis reveals that regulatory convergence promotes exports primarily by improving access to green credit and enhancing peer quality within the industry. Furthermore, heterogeneity tests indicate that the positive effects are most pronounced for start-ups and firms in the decline stage, as well as for enterprises located in eastern China, those outside the Yangtze River Economic Belt, and those subject to minimal government intervention. This study provides critical micro-level evidence that helps enterprises navigate the evolving policy landscape and supports the formulation of strategies to boost export trade amidst the integration of environmental regulations.

Graphene oxide (GO) is a carbon-based nanomaterial explored for agricultural and forestry uses, but plant responses are strongly subject to both the dose and the route of exposure. We summarized recent studies with defined graphene oxide (GO) exposures by seed priming, foliar delivery, and root or soil exposure, while comparing annual crops with woody forest plants. Mechanistic progress points to a shared physicochemical basis: surface oxygen groups and sheet geometry reshape water and ion microenvironments at the soil–seed and soil–rhizosphere interfaces, and many reported shifts in antioxidant enzymes and hormone pathways likely represent downstream stress responses. In crops, low-to-moderate doses most consistently improve germination, root architecture, and tolerance to salinity or drought stress, whereas high doses or prolonged root exposure can cause root surface coating, oxidative injury, and photosynthetic inhibition. In forest plants, evidence remains limited and often relies on seedlings or tissue culture. For forest plants with long life cycles, processes such as soil persistence, aging, and multi-seasonal carry-over become key factors, especially in nurseries and restoration substrates. The available data indicate predominant root retention with generally limited root-to-shoot translocation, so residues in edible and medicinal organs remain insufficiently quantified under realistic-use patterns. This review provides a scenario-based framework for crop- and forestry-specific safe-dose windows and proposes standardized endpoints for long-term fate and ecological risk assessment.

Forest ecosystems, as vital natural resources, are increasingly endangered by wildfires. Effective forest fire management relies on the accurate and early detection of small–scale flames and smoke. However, the complex and dynamic forest environment, along with the small size and irregular shape of early fire indicators, poses significant challenges to reliable early warning systems. To address these issues, this paper introduces SER–YOLOv8, an enhanced detection model based on the YOLOv8 architecture. The model incorporates the RepNCSPELAN4 module and an SPPELAN structure to strengthen multi-scale feature representation. Furthermore, to improve small target localization, the Normalized Wasserstein Distance (NWD) loss is adopted, providing a more robust similarity measure than traditional IoU–based losses. The newly designed SERDet module deeply integrates a multi–scale feature extraction mechanism with a multi-path fused attention mechanism, significantly enhancing the recognition capability for flame targets under complex backgrounds. Depthwise separable convolution (DWConv) is utilized to reduce parameters and boost inference efficiency. Experiments on the M4SFWD dataset show that the proposed method improves mAP50 by 1.2% for flames and 2.4% for smoke, with a 1.5% overall gain in mAP50–95 over the baseline YOLOv8, outperforming existing mainstream models and offering a reliable solution for forest fire prevention.

Plant phenology is a sensitive indicator of ecosystem responses to climate change, yet its dynamics and drivers in subtropical montane forests remain poorly understood. Based on the continuous phenological monitoring of 12 dominant tree species from 2008 to 2022 in a mid-subtropical evergreen broad-leaved forest on Ailao Mountains, China, this study analyzed phenological shifts and their climatic drivers. The results show that, (1) unlike the widely reported trends in northern mid-to-high latitudes, spring phenophases (budburst and leaf-out) did not exhibit significant advancing trends, while autumn phenophases (leaf coloration and fall) remained stable; (2) water availability played a dominant role in regulating spring phenology, with both budburst and leaf-out showing significant negative correlations with winter-spring precipitation, and responses varied significantly across hydrological year types; and (3) the life form strongly influenced phenological strategies, with evergreen species exhibiting earlier spring phenology than deciduous species. This study highlights that in seasonally humid subtropical montane forests, water availability exerts a stronger control on phenology than temperature. Our findings underscore the necessity of incorporating precipitation variability and functional trait differences into assessments of forest phenology and ecosystem functioning under future climate change, providing a scientific basis for the conservation and adaptive management of subtropical forests.