Accurate individual tree segmentation (ITS) is fundamental to forest management and to the studies of forest ecosystem. Unmanned Aerial Vehicle Light Detection and Ranging (UAV-LiDAR) shows advantages for ITS and tree height estimation at stand and landscape scale. However, dense deciduous forests with tightly interlocked tree crowns challenge the performance for ITS. Available LiDAR points through tree crown and appropriate algorithm are expected to attack the problem. In this study, a new UAV-LiDAR dataset that fused leaf-off and leaf-on point cloud (FULD) was introduced to assess the synergetic benefits for ITS and tree height estimation by comparing different types of segmentation algorithms (i.e., watershed segmentation, point cloud segmentation and layer stacking segmentation) in the dense deciduous forests of Northeast China. Field validation was conducted in the four typical stands, including mixed broadleaved forest (MBF), Mongolian oak forest (MOF), mixed broadleaf-conifer forest (MBCF) and larch plantation forest (LPF). The results showed that the combination of FULD and the layer stacking segmentation (LSS) algorithm produced the highest accuracies across all forest types (F-score: 0.70 to 0.85). The FULD also showed a better performance on tree height estimation, with a root mean square error (RMSE) of 1.54 m at individual level. Compared with using the leaf-on dataset solely, the RMSE of tree height estimation was reduced by 0.22 to 0.27 m, and 12.3% more trees were correctly segmented by the FULD, which are mainly contributed by improved detection rate at nearly all DBH levels and by improved detection accuracy at low DBH levels. The improvements are attributed to abundant points from the bole to the treetop of FULD, as well as each layer point being included for segmentation by LSS algorithm. These findings provide useful insights to guide the application of FULD when more multi-temporal LiDAR data are available in future.

The effects of forest restoration on ecosystem services and their trade-offs are increasingly discussed by environmental managers and ecologists, but few demonstrations have analyzed ecosystem service trade-offs with a view to informing afforestation choices. Here, we examined how the Grain for Green Program (GGP), an ambitious reforestation program in China, affected ecosystem services. We quantified regulating services and provisioning service in the potential scenarios, which were developed to improve ecosystem services better. The results indicated the GGP drove 14.5% of land-use/land-cover from 2000 to 2015, and all the regulating services increased. Prioritizing reforestations in steep-sloped and riparian farmlands can promote flood mitigation, water purification, and soil retention services by 62.7%, 25.5%, and 216.1% as compared with 2015 levels, respectively, suggesting that the improvements strongly depend on afforestation locations. Driven by the new GGP policy, a high proportion of economic forest increased provisioning service (272.2%), but at the expense of decreases in soil retention (−25.1%), flood mitigation (−11.4%), water purification (−36.6%), and carbon storage (−48.5%). We identified a suitable scenario that would reduce the trade-offs, which associated with afforestation types and their spatial allocation. Identifying priority areas of afforestation types can inform the GGP policy to assure sustainable and broader benefits.

Quantitative assessment of ecological vulnerability is of great significance for ecological protection and restoration in ecologically vulnerable regions. Here, the ecological vulnerability of the northern sand prevention belt (NSPB) of China was assessed using an ecological pressure–sensibility–resilience model from 2000 to 2015. Results showed that the ecological vulnerability index (EVI) displayed low values in the eastern part and high values in the western part of the study region. The EVI ranged from 0.29 to 1.32 in 2000, with the mean value of 0.88, whereas it averaged 0.78 in 2015, ranging from 0.21 to 1.26. Decreasing EVI from 2000 to 2015 indicated that the ecological status has been improved. Moreover, the area proportion of moderately, heavily, and extremely ecological vulnerability levels occupied approximately 87% in both 2000 and 2015, indicating a high ecological vulnerability level. Furthermore, the change in area proportion of different ecological vulnerability levels were associated with the change in the spatial distribution of vegetation coverage, indicating that eco-environmental protection projects were indeed effective. These findings indicated that differential strategies in different restoration zones should be adopted, especially in the western parts of the study region, and eco-environmental protection projects should be reinforced to improve the ecological restoration.

Understanding how trees coordinate carbon acquisition and allocation under warming is essential for predicting forest–carbon dynamics; however, whether warming induces common or species-specific source–sink regulation strategies remains unresolved. We conducted a field warming experiment (+2 °C and +4 °C above ambient) to investigate photosynthetic responses, organ-specific non-structural carbohydrate (NSC) dynamics, and carbon allocation strategies in two temperate tree species, Fraxinus mandschurica and Juglans mandshurica. Moderate warming (+2 °C) initially enhanced carbon assimilation in both species, whereas severe warming (+4 °C) progressively inhibited photosynthetic performance during the later growing season. In F. mandschurica, +2 °C warming promoted carbon storage by increasing starch accumulation across leaves, stems, and roots, with starch concentrations 2.5–38.0% higher than those in control plants from July to September. These enhanced NSC reserves were positively associated with photosynthetic performance and survival, indicating an effective source-driven carbon storage strategy. In contrast, J. mandshurica exhibited a distinct carbon allocation pattern under warming, characterized by preferential soluble sugar accumulation in leaves and reduced carbon investment in storage tissues. Specifically, leaf soluble sugar-to-starch ratios increased by 6.0–162.3%, whereas root soluble sugar content decreased by up to 55.7% under warming, suggesting a shift toward short-term carbon regulation rather than long-term storage. Structural equation modeling further demonstrated that photosynthetic performance and leaf NSC pools were central regulators of warming responses, but their effects on downstream carbon allocation differed between species. Our results reveal that warming does not induce a uniform carbon response among temperate trees; instead, species-specific source–sink regulation strategies determine carbon resilience under elevated temperatures. These findings improve understanding of how coexisting tree species may diverge in their adaptive capacity under future climate warming.

As an important agricultural product in China’s Xinjiang, geographical indication rice holds significant value for the development of regional specialty agriculture and contributes to the growth of farmer income. Using the MaxEnt model, this study simulated its suitable cultivation areas. Results showed high model accuracy (mean AUC = 0.954) and identified precipitation factors—especially in the driest quarter and month—as dominant influences, with a combined contribution of 75.6% (bio_15 + bio_17 + bio_14 + bio_19). Historically, suitable areas were mainly in mid-western Northern Xinjiang and southwestern Tianshan, covering 43.23 × 10⁴ km². Under future climates, these areas are projected to expand significantly to 47.35–50.50 × 10⁴ km² by 2050, with moderate suitability zones growing most, based on projections from the BCC-CSM2-MR model. By 2070, moderate and high suitability areas increase further, extending toward mid-western Northern Xinjiang and northwestern Southern Xinjiang. The cultivation centroid showed phased shifts—moving northeast by 2050, then southwest by 2070 under SSP1-2.6. These findings support optimized rice cultivation planning in Xinjiang under climate change.