82 citations as recorded by crossref.

1. Reversal of the sensitivity of vegetation productivity to precipitation in global terrestrial biomes over the recent decade W. Zhang et al. 10.1016/j.agrformet.2025.110598
2. Global distribution pattern in characteristics of gross primary productivity response to soil water availability S. Bao et al. 10.1016/j.agrformet.2025.110701
3. Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China N. An et al. 10.1016/j.scitotenv.2024.171412
4. China’s current forest age structure will lead to weakened carbon sinks in the near future R. Shang et al. 10.1016/j.xinn.2023.100515
5. Machine learning-based investigation of forest evapotranspiration, net ecosystem productivity, water use efficiency and their climate controls at meteorological station level H. Shi et al. 10.1016/j.jhydrol.2024.131811
6. Modeling fire hazards for the maintenance of long-term forest inventory plots in Alberta, Canada K. Xu et al. 10.1016/j.foreco.2022.120206
7. Mapping of secondary forest age in China using stacked generalization and Landsat time series S. Zhang et al. 10.1038/s41597-024-03133-2
8. Nitrogen deposition favors later leaf senescence in woody species J. Wang et al. 10.1038/s41467-025-59000-0
9. Informing forest carbon inventories under the Paris Agreement using ground‐based forest monitoring data K. Anderson‐Teixeira et al. 10.1002/ppp3.10587
10. Modeling Fire Hazards for the Maintenance of Long-Term Forest Inventory Plots in Alberta, Canada K. Xu et al. 10.2139/ssrn.4010378
11. Exploring the Individualized Effect of Climatic Drivers on MODIS Net Primary Productivity through an Explainable Machine Learning Framework L. Li et al. 10.3390/rs14174401
12. Revised and updated geospatial monitoring of 21st century forest carbon fluxes D. Gibbs et al. 10.5194/essd-17-1217-2025
13. Global increase in biomass carbon stock dominated by growth of northern young forests over past decade H. Yang et al. 10.1038/s41561-023-01274-4
14. Unmanaged naturally regenerating forests approach intact forest canopy structure but are susceptible to climate and human stress W. Li et al. 10.1016/j.oneear.2024.05.002
15. Drivers of aboveground biomass in Quercus wutaishanica Mayr forests based on random forest and structural equation modeling: A cross-scale analysis S. Ma et al. 10.1016/j.ecolmodel.2025.111113
16. Combining satellite images with national forest inventory measurements for monitoring post-disturbance forest height growth A. Pellissier-Tanon et al. 10.3389/frsen.2024.1432577
17. Mapping planted forest age using LandTrendr algorithm and Landsat 5–8 on the Loess Plateau, China P. Li et al. 10.1016/j.agrformet.2023.109795
18. Forest degradation contributes more to carbon loss than forest cover loss in North American boreal forests L. Yu et al. 10.1016/j.jag.2024.103729
19. Biophysical impact of forest age changes on land surface temperature in China Z. Zhang et al. 10.1016/j.scitotenv.2025.178445
20. Forest Structure Simulation of Eucalyptus Plantation Using Remote-Sensing-Based Forest Age Data and 3-PG Model Y. Zhang et al. 10.3390/rs15010183
21. Divergent responses of forest canopy height to environmental conditions across China X. Pan et al. 10.1016/j.ecolind.2024.112763
22. Cropland expansion drives vegetation greenness decline in Southeast Asia R. Zhao et al. 10.5194/bg-21-5393-2024
23. A 2020 forest age map for China with 30 m resolution K. Cheng et al. 10.5194/essd-16-803-2024
24. A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps A. Araza et al. 10.1016/j.rse.2022.112917
25. Estimating and mapping forest age across Canada's forested ecosystems J. Maltman et al. 10.1016/j.rse.2023.113529
26. Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years Y. Chen et al. 10.5194/essd-15-897-2023
27. The global distribution and drivers of wood density and their impact on forest carbon stocks L. Mo et al. 10.1038/s41559-024-02564-9
28. Simulating Potential Tree Height for Beech–Maple–Birch Forests in Northeastern United States on Google Earth Engine Z. Zuo et al. 10.34133/remotesensing.0084
29. Enhancing ecohydrological simulation with improved dynamic vegetation growth module in SWAT S. An et al. 10.1016/j.jhydrol.2024.132042
30. Coastal carbon sentinels: A decade of forest change along the eastern shore of the US signals complex climate change dynamics M. Ardón et al. 10.1371/journal.pclm.0000444
31. Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model T. Dinh et al. 10.5194/gmd-17-6725-2024
32. High-resolution forest age mapping based on forest height maps derived from GEDI and ICESat-2 space-borne lidar data X. Lin et al. 10.1016/j.agrformet.2023.109592
33. Can wood harvest followed by forest regrowth enhance carbon sequestration of the forest sector in China? M. Wang et al. 10.1016/j.gloplacha.2024.104626
34. Global water use efficiency saturation due to increased vapor pressure deficit F. Li et al. 10.1126/science.adf5041
35. An Algorithm of Forest Age Estimation Based on the Forest Disturbance and Recovery Detection Z. Huang et al. 10.1109/TGRS.2023.3322163
36. Impact of the EU biodiversity strategy for 2030 on the EU wood-based bioeconomy F. Fulvio et al. 10.1016/j.gloenvcha.2025.102986
37. Towards a roadmap for space-based observations of the land sector for the UNFCCC global stocktake O. Ochiai et al. 10.1016/j.isci.2023.106489
38. Native American geography shaped historical fire frequency in forests of eighteenth-century Pennsylvania, USA S. Tulowiecki et al. 10.1038/s41598-023-44692-5
39. Nitrogen addition delays the emergence of an aridity-induced threshold for plant biomass H. Li et al. 10.1093/nsr/nwad242
40. Spatial Pattern of Forest Age in China Estimated by the Fusion of Multiscale Information Y. Xu et al. 10.3390/f15081290
41. Reforestation policies around 2000 in southern China led to forest densification and expansion in the 2010s X. Tong et al. 10.1038/s43247-023-00923-1
42. Afforestation as a mitigation strategy: countering climate-induced risk of forest carbon sink in China Y. Cao et al. 10.1186/s13021-025-00308-1
43. Enhancing ecosystem productivity and stability with increasing canopy structural complexity in global forests X. Liu et al. 10.1126/sciadv.adl1947
44. Maximum tree lifespans derived from public-domain dendrochronological data F. Biondi et al. 10.1016/j.isci.2023.106138
45. Mapping Annual Global Forest Gain From 1983 to 2021 With Landsat Imagery Z. Du et al. 10.1109/JSTARS.2023.3267796
46. Carbon accumulation rate peaks at 1,000-m elevation in tropical planted and regrowth forests Y. Su et al. 10.1016/j.oneear.2024.11.001
47. Optimal spatiotemporal thinning schemes combined with wood vaulting could maximize the forest biomass carbon sink in China Y. Chen et al. 10.1038/s43247-025-02350-w
48. The significance of large old trees and tree cavities for forest carbon estimates M. Hauck et al. 10.1016/j.foreco.2023.121319
49. Soil geochemistry – and not topography – as a major driver of carbon allocation, stocks, and dynamics in forests and soils of African tropical montane ecosystems B. Bukombe et al. 10.1111/nph.18469
50. Global patterns of tree wood density H. Yang et al. 10.1111/gcb.17224
51. Forestation at the right time with the right species can generate persistent carbon benefits in China H. Xu et al. 10.1073/pnas.2304988120
52. Reconstructing Long‐Term Forest Age of China by Combining Forest Inventories, Satellite‐Based Forest Age and Forest Cover Data Sets J. Xia et al. 10.1029/2023JG007492
53. Thirty-meter map of young forest age in China Y. Xiao et al. 10.5194/essd-15-3365-2023
54. The key role of forest disturbance in reconciling estimates of the northern carbon sink M. O’Sullivan et al. 10.1038/s43247-024-01827-4
55. Separating Biomass Gains and Losses of Planted Forest and Natural Forest and Their Contributions to Forest Biomass Carbon Storage in China for 2005–2020 H. Yan et al. 10.3390/f16060884
56. Forest aging limits future carbon sink in China Y. Leng et al. 10.1016/j.oneear.2024.04.011
57. Spatial Distribution Changes and Factor Analysis of Topsoil Organic Carbon Across Different Forest Types on Hainan Island X. Zhang et al. 10.3390/f16030550
58. Development of national post-fire restoration system to assess net GHG impacts and salvage biomass availability C. Smyth et al. 10.1016/j.mex.2024.102932
59. Influence of climate zone shifts on forest ecosystems in northeastern United States and maritime Canada S. Roy et al. 10.1016/j.ecolind.2024.111921
60. The carbon sequestration potential of vegetation over the Tibetan Plateau W. Cai et al. 10.1016/j.rser.2024.114937
61. Indigenous and European‐American Land‐Use Legacies in Forest Composition, Fort Drum, Northern New York State: What Do Species Distribution Models Detect Across a Local Extent? S. Tulowiecki 10.1111/jbi.15180
62. Satellite-based evidence of recent decline in global forest recovery rate from tree mortality events Y. Yan et al. 10.1038/s41477-025-01948-4
63. Time-series forest age estimation in Xinjiang based on forest disturbance and recovery detection L. Zhai et al. 10.1016/j.ecolind.2024.113043
64. Protect young secondary forests for optimum carbon removal N. Robinson et al. 10.1038/s41558-025-02355-5
65. Divergent biophysical responses of western United States forests to wildfire driven by eco-climatic gradients S. Shrestha et al. 10.5194/bg-21-2207-2024
66. Canopy-Height and Stand-Age Estimation in Northeast China at Sub-Compartment Level Using Multi-Resource Remote Sensing Data X. Guan et al. 10.3390/rs15153738
67. Assessing the potential of remote sensing-based models to predict old-growth forests on large spatiotemporal scales E. Lalechère et al. 10.1016/j.jenvman.2023.119865
68. Large-scale remote sensing reveals that tree mortality in Germany appears to be greater than previously expected F. Schiefer et al. 10.1093/forestry/cpae062
69. Forest Age Mapping Using Landsat Time-Series Stacks Data Based on Forest Disturbance and Empirical Relationships between Age and Height L. Tian et al. 10.3390/rs15112862
70. Multi-Sensor Fusion and Machine Learning for Forest Age Mapping in Southeastern Tibet Z. Chi & K. Xu 10.3390/rs17111926
71. OpenForest: a data catalog for machine learning in forest monitoring A. Ouaknine et al. 10.1017/eds.2024.53
72. Current Forest Carbon Offset Buffer Pool Contributions Do Not Adequately Insure Against Disturbance‐Driven Carbon Losses W. Anderegg et al. 10.1111/gcb.70251
73. Boreal tree species diversity increases with global warming but is reversed by extremes Y. Xi et al. 10.1038/s41477-024-01794-w
74. Best practices for calibration of forest landscape models using fine-scaled reference information G. Reese et al. 10.1139/cjfr-2024-0085
75. Spatial database of planted forests in East Asia A. Abbasi et al. 10.1038/s41597-023-02383-w
76. Mapping Forest Tree Species Using Sentinel-2 Time Series by Taking into Account Tree Age B. Yang et al. 10.3390/f15030474
77. Biogeographic pattern of living vegetation carbon turnover time in mature forests across continents K. Yu et al. 10.1111/geb.13736
78. Land cover and management effects on ecosystem resistance to drought stress C. Xiao et al. 10.5194/esd-14-1211-2023
79. How forest age impacts on net primary productivity: Insights from future multi-scenarios L. Tian et al. 10.1016/j.fecs.2024.100228
80. Carbon Balance of China-Made Wood Products Assessed Using a Trade-Linked Approach X. Zhang et al. 10.1021/acs.est.4c09208
81. The Forest Resistance to Droughts Differentiated by Tree Height in Central Europe T. Li et al. 10.1029/2021JG006668
82. The Value of Forests to Pollinating Insects Varies with Forest Structure, Composition, and Age M. Ulyshen et al. 10.1007/s40725-024-00224-6