Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m⁻²·a⁻¹) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China.

Introduction: China’s forests have sequestrated a significant amount of carbon over the past two decades. However, it is not clear whether China’s forests will be able to continue to have as much carbon sequestration potential capacity in the future.Methods: In order to research China’s forest carbon storage and carbon sequestration potential capacities at spatial and temporal scales, we built a digital forest model for each province of China using the data from The China Forest Resources Report (2014– 2018) and calculated the carbon storage capacity and sequestration potential capacity of each province with the current management practices without considering natural successions.Results: The results showed that the current forest carbon storage is 10.0 Pg C, and the carbon sequestration potential in the next 40 years (from year 2019 to 2058) will be 5.04 Pg C. Since immature forests account for the majority of current forests, the carbon sequestration capacity of the forest was also high (0.202 Pg C year−1). However, the forest carbon storage reached the maximum with the increase of stand maturity. At this time, if scenarios such as afforestation and reforestation, human and natural disturbances, and natural succession are not considered, the carbon sequestration capacity of forests will continue to decrease. After 90 years, all stands will develop into mature and over-mature forests, and the forest carbon sequestration capacity is 0.008 Pg year−1; and the carbon sequestration rate is ~4% of what it is nowadays. The change trend of forest carbon in each province is consistent with that of the country. In addition, considering the large forest coverage area in China, the differences in tree species and growing conditions, the forest carbon storage and carbon sequestration capacities among provinces were different. The growth rate of carbon density in high-latitude provinces (such as Heilongjiang, Jilin, and Inner Mongolia) was lower than that in the south (Guangdong, Guangxi, or Hunan), but the forest carbon potential was higher.Discussion: Planning and implementing targeted forest management strategies is the key to increasing forest carbon storage and extending the service time of forest carbon sinks in provinces. In order to reach the national carbon neutrality goals, we recommend that each province have an informative strategic forest management plan.

The rapid urbanization process and high-intensity construction mode have greatly changed the underlying surface structure and spatial distribution of the natural land surface, further amplified the possibility of urban floods, and made urban security face more serious threats. Urban forest could help to mitigate urban floods through water holding and interception by its unique structures, especially the litter layer. This paper compared the ability of different forest tree species on urban floods mitigation, through analyzing their litter accumulation, litter water holding characteristics, and water interception features of different decomposed layers. The results concluded that Quercus mongolica Fisch. ex Ledeb. (QM) forest, Betula platyphylla Sukaczev (BP) forest, Larix gmelinii (Rupr.) Kuzen. (LG) forest, and Picea koraiensis Nakai (PK) forest were the best choices for improving urban floods resistance in a high-urbanization winter city, for they had larger litter mass and higher maximum water holding and interception capacity. The corresponding results of this study could help environmental management departments worldwide in the selection of tree species in urban greening projects focusing on urban flood control.

Leaf area index (LAI) stands as a pivotal parameter for the quantitative assessment of vegetation growth dynamics, and the rapid acquisition of the effective leaf area index (LAIe) in different scales is crucial for forest ecological monitoring. In this study, forest structure parameters were derived from fusion point cloud data obtained through Airborne Laser Scanning and Terrestrial Laser Scanning in three coniferous forests. The influence of point diameter on the extraction of different forest structure parameters was examined, and an in-depth analysis of the correlations between these parameters and measured LAIe was undertaken. The LAIe inversion model was constructed, and its performance for different forest types was studied. The results show that the precision of the extracted forest structure parameters was highest when the point diameter was set to 0.1 cm. Among the 10 forest structure parameters, internal canopy structures such as canopy openness (CO), gap fraction (GF) and canopy closure (CC) were significantly correlated with measured LAIe (p < 0.01), and the correlations between different forest types were significantly different. In addition, the multiparameter LAIe inversion model was able to distinguish forest type and thus better stimulate measured LAIe; also, it appeared closer to the 1:1 relationship line than the voxel model. This study made up for the inefficiency of LAIe measurement with optical instruments and the inaccuracy of passive remote sensing measurement and proved the possibility of LAIe extraction at a large scale via LiDAR in the future.

Urban agroforestry ecosystems, formed by the intermixing of croplands and urban forests, play a crucial role in enhancing ecological resilience and supporting sustainable landscape management. However, how different proportions of forest and farmland contribute to ecosystem multifunctionality and modify interactions among ecosystem services (ESs) remains insufficiently understood, particularly within rapidly urbanizing environments. In this study, we quantified four keys-grain production, water conservation, soil retention, and carbon sequestration-across urban–rural agroforestry compositions in Changchun City, Northeast China. Using multisource satellite products and biophysical models, we assessed spatiotemporal changes in ES supply, evaluated multifunctionality across five agroforestry composition types, and examined trade-offs and synergies among ESs. The results show clear spatial differentiation driven by the urban-rural forest gradient. Among the five compositions, multifunctionality was lowest in the agricultural area (AA, farmland > 80%), while in mixed urban agroforestry zones-including agriculture-forest area (AFA, farmland > 60% and forest > 20%), agriculture–forest balance area (AFBA, farmland > 40% and forest > 40%), forest-agriculture area (FAA, farmland > 20% and forest > 60%), and forest area (FA, forest > 80%)-multifunctionality declined progressively as forest proportion increased. Strong synergy between grain production and water conservation was observed in AA, whereas in the other compositions, soil retention and water conservation formed the dominant synergistic pair, with synergy slightly strengthening as forest percentage increased. Notably, in FA, the relationship between grain production and soil retention shifted from synergy to trade-off, reflecting functional shifts along the urban forest gradient. These findings provide a scientific basis for optimizing the spatial configuration of urban forests and farmlands, and support nature-based solutions and integrated landscape planning aimed at balancing food security and ecological sustainability in urbanizing regions.