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China’s extensive planted forests play a crucial role in carbon storage, vital for climate change mitigation. However, the complex spatiotemporal dynamics of China’s planted forest area and its carbon storage remain uncaptured. Here we reveal such changes in China’s planted forests from 1990 to 2020 using satellite and field data. Results show a doubling of planted forest area, a trend that intensified post-2000. These changes lead to China’s planted forest carbon storage increasing from 675.6 ± 12.5 Tg C in 1990 to 1,873.1 ± 16.2 Tg C in 2020, with an average rate of ~ 40 Tg C yr −1 . The area expansion of planted forests contributed ~ 53% (637.2 ± 5.4 Tg C) of the total above increased carbon storage in planted forests compared with planted forest growth. This proactive policy-driven expansion of planted forests has catalyzed a swift increase in carbon storage, aligning with China’s Carbon Neutrality Target for 2060. The dynamics of planted forests in China over the past three decades have contributed ~1198tg of above-ground carbon storage.

Forest canopy height is an important indicator of forest biomass, species diversity, and other ecosystem functions; however, the climatic determinants that underlie its global patterns have not been fully explored. Using satellite LiDAR-derived forest canopy heights and field measurements of the world's giant trees, combined with climate indices, we evaluated the global patterns and determinants of forest canopy height. The mean canopy height was highest in tropical regions, but tall forests (>50 m) occur at various latitudes. Water availability, quantified by the difference between annual precipitation and annual potential evapotranspiration (P-PET), was the best predictor of global forest canopy height, which supports the hydraulic limitation hypothesis. However, in striking contrast with previous studies, the canopy height exhibited a hump-shaped curve along a gradient of P-PET: it initially increased, then peaked at approximately 680 mm of P-PET, and finally declined, which suggests that excessive water supply negatively affects the canopy height. This trend held true across continents and forest types, and it was also validated using forest inventory data from China and the United States. Our findings provide new insights into the climatic controls of the world's giant trees and have important implications for forest management and improvement of forest growth models.

Significance The Mongolian Plateau, composed mainly of Inner Mongolia in China and the Republic of Mongolia, has been experiencing remarkable lake shrinkage during the recent decades because of intensive human activities and climate changes. This study provides a comprehensive satellite-based evaluation of lake shrinkage across the plateau, and finds a greater decreasing rate of the number of lakes in Inner Mongolia than in Mongolia (34.0% vs. 17.6%) between the late 1980s and 2010, due mainly to an unsustainable mining boom and agricultural irrigation in the former. Disastrous damages to the natural systems are threatening the livelihood of local people, and we thus call for an urgent action to prevent further deterioration. Lakes are widely distributed on the Mongolian Plateau and, as critical water sources, have sustained Mongolian pastures for hundreds of years. However, the plateau has experienced significant lake shrinkage and grassland degradation during the past several decades. To quantify the changes in all of the lakes on the plateau and the associated driving factors, we performed a satellite-based survey using multitemporal Landsat images from the 1970s to 2000s, combined with ground-based censuses. Our results document a rapid loss of lakes on the plateau in the past decades: the number of lakes with a water surface area >1 km ² decreased from 785 in the late 1980s to 577 in 2010, with a greater rate of decrease (34.0%) in Inner Mongolia of China than in Mongolia (17.6%). This decrease has been particularly pronounced since the late 1990s in Inner Mongolia and the number of lakes >10 km ² has declined by 30.0%. The statistical analyses suggested that in Mongolia precipitation was the dominant driver for the lake changes, and in Inner Mongolia coal mining was most important in its grassland area and irrigation was the leading factor in its cultivated area. The deterioration of lakes is expected to continue in the following decades not only because of changing climate but also increasing exploitation of underground mineral and groundwater resources on the plateau. To protect grasslands and the indigenous nomads, effective action is urgently required to save these valuable lakes from further deterioration.

Forests play an important role in global carbon cycles. However, the lack of available information on carbon stocks in dead organic matter, including woody debris and litter, reduces the reliability of assessing the carbon cycles in entire forest ecosystems. Here we estimate that the national DOM carbon stock in the period of 2004–2008 is 925 ± 54 Tg, with an average density of 5.95 ± 0.35 Mg C ha −1 . Over the past two decades from periods of 1984−1988 to 2004−2008, the national dead organic matter carbon stock has increased by 6.7 ± 2.2 Tg carbon per year, primarily due to increasing forest area. Temperature and precipitation increase the carbon density of woody debris, but decrease that of litter. Additionally, the woody debris increases significantly with above ground biomass and forest age. Our results can improve estimates of the carbon budget in China's forests and for better understanding of effects of climate and stand characteristics on dead organic matter distribution. Reliable estimates of the total forest carbon (C) pool are lacking due to insufficient information on dead organic matter (DOM). Here, the authors estimate that the current DOM C stock in China is 925 ± 54 Tg and that it grew by 6.7 ± 2.2 Tg C/yr over the past two decades primarily due to increasing forest area

Individual tree segmentation (ITS) is essential for forest inventory, health assessment, carbon accounting, and evaluating restoration efforts. Populus euphratica, a widely distributed desert riparian tree species found along the inland rivers of Central Asia, presents challenges for accurately identifying individual trees and conducting forest inventories due to its complex stand structure and overlapping crowns. To determine the most effective ITS approach for P. euphratica, we benchmarked six commonly used tree segmentation approaches for terrestrial laser scanning (TLS) data: canopy height model segmentation (CHMS), point cloud segmentation (PCS), comparative shortest-path algorithm (CSP), stem location seed point segmentation (SPS), deep-learning trunk-based segmentation (TBS), and leaf–wood separation-based segmentation (LWS). All methods followed a unified preprocessing and tuning protocol. We evaluated these methods based on tree-count accuracy, crown delineation, and structural attributes such as tree height (H), diameter at breast height (DBH), and crown diameter (CD). The results indicated that the TBS and LWS methods performed the best, achieving a mean tree-count accuracy of 98%, while the CHMS method averaged only 46%. These two methods provide the basic branch structure within the tree crown, reducing the likelihood of incorrect segmentation. Validation against field-measured values for H, DBH, and CD showed that both the TBS and LWS methods achieved accuracies exceeding 80% (RMSE = 0.8 m), 86% (RMSE = 0.02 m), and 73% (RMSE = 0.7 m), respectively. For TLS data in P. euphratica desert riparian forests, these two methods provide the most reliable results, facilitating rapid plot-scale inventory and monitoring. These findings establish a practical basis for conducting high-accuracy inventories of Euphrates poplar desert riparian forests.

Simulating realistic three‐dimensional (3D) forest scenes is useful in understanding the links between forest structure and ecosystem functions (e.g. radiative transfer). Light detection and ranging (LiDAR) technology provides useful 3D data for forest reconstructions since it can characterise 3D structures of individual trees and canopies. High‐density terrestrial LiDAR (terrestrial laser scanning, TLS) is suitable for fine‐scale reconstructions but is limited to smaller forest plots; low‐density airborne LiDAR (airborne laser scanning, ALS) can cover larger areas but is only suitable for coarse‐scale reconstructions. How to take advantage of TLS and ALS to enable fine‐scale forest simulations in large areas needs to be studied. We propose a new voxel‐based method for forest simulations using the integration of TLS and ALS data. TLS data of representative reference trees are used to approximate the detailed architectures of the whole forest scene, with structural information on each individual tree extracted from ALS data. The high‐density point cloud data derived from TLS and ALS data are voxelised using high resolution solid voxels for scene representation. We tested the proposed method using two virtual forests (108 m × 108 m) and a real forest (300 m × 300 m) with conifer and broadleaf species. The physically based ray tracer (PBRT) was used to visualise the true virtual forest scenes, whereas voxel‐based radiative transfer (VBRT) was used to visualise the modelled forest scenes from LiDAR data. For the real forest scene, simulated and real ALS data were compared. Our results demonstrate that the images simulated by VBRT and PBRT are similar in the virtual forest scenes, with average radiance values of 1.02 and 1.72, respectively. In the real forest scene, the distributions of points and individual tree attributes (tree height, crown radius, and tree volume) derived from real and simulated ALS also match well, with Kullback–Leibler divergence ranging from 0.006 to 0.06. We conclude that the new method is capable of modelling fine‐scale 3D forests in large areas (over 1 ha) when TLS and ALS data are available, and it has good potential in studying the process of radiative transfer in conifer and broadleaf forests.

Resistance and resilience are widely used to characterize ecosystem drought stability. Tradeoff between resistance and resilience have been reported, but its long‐term trends remain uncertain at global scale. Based on remotely sensed vegetation indices, we assessed the spatiotemporal dynamics of drought resistance and resilience. Result revealed that there was a significant decline in the tradeoff between resistance and resilience, corresponding to a substantial increase in the proportion of areas with high resistance‐high resilience or low resistance‐low resilience. In the South Sahel, South Africa and Central China, the increased precipitation and vegetation coverage contribute to enhanced drought stability constructed by resistance and resilience; while rising temperature, decreased water availability and deforestation lead to declined stability in northeastern North America, South America and the Congo region. Increases in the areas with low resistance‐low resilience resulting from declining tradeoffs warn of increased regional ecosystem vulnerability. Plain Language Summary Drought resistance and resilience describe the two aspects of stability, and the tradeoff between the two describes the drought response patterns of ecosystems with high resistance‐low resilience or low resistance‐high resilience. Under global change, the tradeoff has declined significantly over the past few decades, corresponding to substantial increases in the proportion of areas with low resistance‐low resilience, implying a decrease in drought stability. Here we innovatively assess the changes in the tradeoff between resistance and resilience, highlighting the negative impact of rising temperature, decreasing water availability and deforestation on drought stability. Key Points The tradeoff between resistance and resilience has declined significantly over the past three decades Increases in the proportion of areas with low resistance ‐low resilience reflected the reduced stability of ecosystem to droughts Attribution analysis showed that rising temperature, decreasing water availability and deforestation led to the decreases in stability

The spatial scaling of stability is key to understanding ecological sustainability across scales and the sensitivity of ecosystems to habitat destruction. Here we propose the invariability–area relationship (IAR) as a novel approach to investigate the spatial scaling of stability. The shape and slope of IAR are largely determined by patterns of spatial synchrony across scales. When synchrony decays exponentially with distance, IARs exhibit three phases, characterized by steeper increases in invariability at both small and large scales. Such triphasic IARs are observed for primary productivity from plot to continental scales. When synchrony decays as a power law with distance, IARs are quasilinear on a log–log scale. Such quasilinear IARs are observed for North American bird biomass at both species and community levels. The IAR provides a quantitative tool to predict the effects of habitat loss on population and ecosystem stability and to detect regime shifts in spatial ecological systems, which are goals of relevance to conservation and policy. Just as species distribution patterns scale with area, so might the degree of variability in ecological properties. Here, Wang et al . develop a model invariability–area relationship and demonstrate the application of this theory to empirical data on plant primary production and bird biomass.

Northern ecosystems (≥ 30° N) have been accumulating vegetation biomass carbon in recent decades, but increasing droughts and wildfires threaten this carbon sink. Here, we analyse annual changes in live vegetation biomass in northern ecosystems using low-frequency microwave satellite observations at 25 km spatial resolution from 2010 to 2022. We find that live biomass carbon stocks have undergone a reversal from a positive to a negative trend during the study period with 2016 marking the turning point. During 2016–2022, live biomass carbon stocks decreased at a rate of − 0.20 − 0.26 − 0.11 PgC yr −1 across northern ecosystems, primarily in temperate biomes ( − 0.26 − 0.33 − 0.17 PgC yr −1 ). The annual mean gross loss of 4% of live biomass carbon in this region during 2016-2022 reflects high interannual variability, with significant losses associated with droughts and a further drop of − 0.60 − 0.75 − 0.47 PgC in the very dry year of 2022. Our findings highlight the vulnerability of live biomass carbon stocks to emerging climate-induced disturbances in northern ecosystems, challenging the sustainability of the current large terrestrial carbon sink in this key region for the global carbon balance. Drought, fires, and human activities have reversed the accumulation of live biomass carbon in the Northern Hemisphere, with total biomass shifting from a positive to a negative trend around 2016.