118 citations as recorded by crossref.

1. Global distribution pattern in characteristics of gross primary productivity response to soil water availability S. Bao et al.
2. Internal stem decay is not a major source of error for carbon stock estimates in managed temperate forests of Central Europe M. Hauck et al.
3. China’s current forest age structure will lead to weakened carbon sinks in the near future R. Shang et al.
4. Modeling fire hazards for the maintenance of long-term forest inventory plots in Alberta, Canada K. Xu et al.
5. Nitrogen deposition favors later leaf senescence in woody species J. Wang et al.
6. Revised and updated geospatial monitoring of 21st century forest carbon fluxes D. Gibbs et al.
7. Uncovering evapotranspiration patterns in the Murray Darling Basin over two decades A. Shadmehri Toosi et al.
8. Global increase in biomass carbon stock dominated by growth of northern young forests over past decade H. Yang et al.
9. Unmanaged naturally regenerating forests approach intact forest canopy structure but are susceptible to climate and human stress W. Li et al.
10. 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.
11. Predicting Forest Age up to 250 Years in Old-Growth Boreal Mixedwoods of Western Quebec, Canada, Using Airborne Laser Scanning Data and Modelled Tree Species Composition R. Rafieijahed et al.
12. A 2020 forest age map for China with 30 m resolution K. Cheng et al.
13. Biophysical factors and management practices are key to shaping forest resilience Y. Yan et al.
14. A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps A. Araza et al.
15. Temperature and Moisture Variability Drive Resilience Shifts in Canada’s Undisturbed Forests During 2001–2018 C. Yang et al.
16. Estimating and mapping forest age across Canada's forested ecosystems J. Maltman et al.
17. A Level-Cascaded Framework for Multiscale Forest Aboveground Biomass Estimation Using UAV-LiDAR and Public Data L. Yao et al.
18. Current and future carbon stocks of a dominant forest plantation species, Cryptomeria japonica, throughout Japan R. Nakahata et al.
19. Simulating Potential Tree Height for Beech–Maple–Birch Forests in Northeastern United States on Google Earth Engine Z. Zuo et al.
20. Coastal carbon sentinels: A decade of forest change along the eastern shore of the US signals complex climate change dynamics M. Ardón et al.
21. A dual-pathway framework for mapping forest age in complex mining landscapes by multi-source remote sensing data and tree growth patterns T. Ma et al.
22. Greater climate sensitivity of older forests than younger forests in the Extratropical Northern Hemisphere T. Jin et al.
23. Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model T. Dinh et al.
24. High-resolution forest age mapping based on forest height maps derived from GEDI and ICESat-2 space-borne lidar data X. Lin et al.
25. Can wood harvest followed by forest regrowth enhance carbon sequestration of the forest sector in China? M. Wang et al.
26. An Algorithm of Forest Age Estimation Based on the Forest Disturbance and Recovery Detection Z. Huang et al.
27. Impact of the EU biodiversity strategy for 2030 on the EU wood-based bioeconomy F. Fulvio et al.
28. Nitrogen addition delays the emergence of an aridity-induced threshold for plant biomass H. Li et al.
29. Spatial Pattern of Forest Age in China Estimated by the Fusion of Multiscale Information Y. Xu et al.
30. Contrasting age-dependent leaf acclimation strategies drive vegetation greening across deciduous broadleaf forests in mid- to high latitudes F. Wang et al.
31. Biodiversity regulates the asymmetric influence of forest cover gain and loss on land surface temperature Z. Liao et al.
32. Enhancing ecosystem productivity and stability with increasing canopy structural complexity in global forests X. Liu et al.
33. Mapping Annual Global Forest Gain From 1983 to 2021 With Landsat Imagery Z. Du et al.
34. Optimal spatiotemporal thinning schemes combined with wood vaulting could maximize the forest biomass carbon sink in China Y. Chen et al.
35. 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.
36. Thirty-meter map of young forest age in China Y. Xiao et al.
37. Extraction of eucalyptus age and estimation of its aboveground biomass in China with the integration of empirical model and machine learning algorithm C. Tang et al.
38. Newly established forests dominated global carbon sequestration change induced by land cover conversions D. Peng et al.
39. Ecosystem engineering and global changes are increasingly enhancing China’s terrestrial carbon sinks M. Zhang et al.
40. Spatial Distribution Changes and Factor Analysis of Topsoil Organic Carbon Across Different Forest Types on Hainan Island X. Zhang et al.
41. Development of national post-fire restoration system to assess net GHG impacts and salvage biomass availability C. Smyth et al.
42. Global covariation of forest age transitions with the net carbon balance S. Besnard et al.
43. Influence of climate zone shifts on forest ecosystems in northeastern United States and maritime Canada S. Roy et al.
44. Time-series forest age estimation in Xinjiang based on forest disturbance and recovery detection L. Zhai et al.
45. Divergent biophysical responses of western United States forests to wildfire driven by eco-climatic gradients S. Shrestha et al.
46. Canopy-Height and Stand-Age Estimation in Northeast China at Sub-Compartment Level Using Multi-Resource Remote Sensing Data X. Guan et al.
47. Large-scale remote sensing reveals that tree mortality in Germany appears to be greater than previously expected F. Schiefer et al.
48. Multi-Sensor Fusion and Machine Learning for Forest Age Mapping in Southeastern Tibet Z. Chi & K. Xu
49. OpenForest: a data catalog for machine learning in forest monitoring A. Ouaknine et al.
50. Current Forest Carbon Offset Buffer Pool Contributions Do Not Adequately Insure Against Disturbance‐Driven Carbon Losses W. Anderegg et al.
51. New evidence for age-related decline in carbon sinks in intact boreal forests N. Huang et al.
52. Boreal tree species diversity increases with global warming but is reversed by extremes Y. Xi et al.
53. Best practices for calibration of forest landscape models using fine-scaled reference information G. Reese et al.
54. Lagged precipitation effects on plant production across terrestrial biomes L. He et al.
55. Spatial database of planted forests in East Asia A. Abbasi et al.
56. Differences and uncertainties in land-use CO2 flux estimates W. Obermeier et al.
57. Multi-Resolution Mapping of Aboveground Biomass and Change in Puerto Rico’s Forests with Remote Sensing and Machine Learning N. Haghtalab et al.
58. Recent widespread forest expansion and densification in Southwest China D. Ma et al.
59. Demography, dynamics and data: building confidence for simulating changes in the world's forests A. Eckes‐Shephard et al.
60. Mapping Forest Tree Species Using Sentinel-2 Time Series by Taking into Account Tree Age B. Yang et al.
61. Carbon Balance of China-Made Wood Products Assessed Using a Trade-Linked Approach X. Zhang et al.
62. The Forest Resistance to Droughts Differentiated by Tree Height in Central Europe T. Li et al.
63. The Value of Forests to Pollinating Insects Varies with Forest Structure, Composition, and Age M. Ulyshen et al.
64. Reversal of the sensitivity of vegetation productivity to precipitation in global terrestrial biomes over the recent decade W. Zhang et al.
65. Combining Random Forest and Monte Carlo Method to Determine the Driving Factors and Uncertainty of Forest Age Prediction in Northwest China J. Zeng et al.
66. Carbon module: An open-source python package for global forest carbon accounting T. Honkomp
67. Carbon stock dynamics along a cork oak stand chronosequence: implications for climate-smart forest management H. Zaher et al.
68. Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China N. An et al.
69. Flash droughts threaten global managed forests J. Pang et al.
70. 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.
71. Global evidence for a positive relationship between tree species richness and ecosystem photosynthesis R. Cao et al.
72. Mapping of secondary forest age in China using stacked generalization and Landsat time series S. Zhang et al.
73. Informing forest carbon inventories under the Paris Agreement using ground‐based forest monitoring data K. Anderson‐Teixeira et al.
74. Modeling Fire Hazards for the Maintenance of Long-Term Forest Inventory Plots in Alberta, Canada K. Xu et al.
75. Exploring the Individualized Effect of Climatic Drivers on MODIS Net Primary Productivity through an Explainable Machine Learning Framework L. Li et al.
76. Combining satellite images with national forest inventory measurements for monitoring post-disturbance forest height growth A. Pellissier-Tanon et al.
77. Global dependency of canopy height on vapour pressure deficit and its projections under climate change W. Zhang et al.
78. Mapping planted forest age using LandTrendr algorithm and Landsat 5–8 on the Loess Plateau, China P. Li et al.
79. Forest degradation contributes more to carbon loss than forest cover loss in North American boreal forests L. Yu et al.
80. Biophysical impact of forest age changes on land surface temperature in China Z. Zhang et al.
81. Forest Structure Simulation of Eucalyptus Plantation Using Remote-Sensing-Based Forest Age Data and 3-PG Model Y. Zhang et al.
82. Divergent responses of forest canopy height to environmental conditions across China X. Pan et al.
83. Cropland expansion drives vegetation greenness decline in Southeast Asia R. Zhao et al.
84. China's annual forest age dataset at a 30 m spatial resolution from 1986 to 2022 R. Shang et al.
85. 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.
86. The global distribution and drivers of wood density and their impact on forest carbon stocks L. Mo et al.
87. Enhancing ecohydrological simulation with improved dynamic vegetation growth module in SWAT S. An et al.
88. Wildfires and Climate Change as Key Drivers of Forest Carbon Flux Variations in Africa over the Past Two Decades L. Zhang & Z. Zhang
89. Global water use efficiency saturation due to increased vapor pressure deficit F. Li et al.
90. Towards a roadmap for space-based observations of the land sector for the UNFCCC global stocktake O. Ochiai et al.
91. Native American geography shaped historical fire frequency in forests of eighteenth-century Pennsylvania, USA S. Tulowiecki et al.
92. Reforestation policies around 2000 in southern China led to forest densification and expansion in the 2010s X. Tong et al.
93. Afforestation as a mitigation strategy: countering climate-induced risk of forest carbon sink in China Y. Cao et al.
94. Maximum tree lifespans derived from public-domain dendrochronological data F. Biondi et al.
95. Carbon accumulation rate peaks at 1,000-m elevation in tropical planted and regrowth forests Y. Su et al.
96. Carbon sink conservation: Cost-effective spatial priorities and feasible management policies for China J. Liu et al.
97. Securing the forest carbon sink for the European Union’s climate ambition M. Migliavacca et al.
98. The significance of large old trees and tree cavities for forest carbon estimates M. Hauck et al.
99. Global patterns of tree wood density H. Yang et al.
100. Simultaneous Reductions in Forest Resilience and Greening Trends in Southwest China H. Wu et al.
101. Forestation at the right time with the right species can generate persistent carbon benefits in China H. Xu et al.
102. Simulating Central-European forests in the 21st century. Effects of climate change, disturbances and management on stocks, productivity and harvests M. Lexer et al.
103. Reconstructing Long‐Term Forest Age of China by Combining Forest Inventories, Satellite‐Based Forest Age and Forest Cover Data Sets J. Xia et al.
104. The key role of forest disturbance in reconciling estimates of the northern carbon sink M. O’Sullivan et al.
105. 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.
106. Forest aging limits future carbon sink in China Y. Leng et al.
107. Classification of old-growth beech forest across Europe using Sentinel-2 and airborne laser scanning M. Hirschmugl et al.
108. The carbon sequestration potential of vegetation over the Tibetan Plateau W. Cai et al.
109. 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
110. Satellite-based evidence of recent decline in global forest recovery rate from tree mortality events Y. Yan et al.
111. Protect young secondary forests for optimum carbon removal N. Robinson et al.
112. Assessing the potential of remote sensing-based models to predict old-growth forests on large spatiotemporal scales E. Lalechère et al.
113. Forest Age Mapping Using Landsat Time-Series Stacks Data Based on Forest Disturbance and Empirical Relationships between Age and Height L. Tian et al.
114. A framework for maximizing the benefit from retaining regrowth on private land H. Thomas et al.
115. Initial condition uncertainty exerts a large and persistent influence on model simulations of ecosystem carbon dynamics in California P. Selmants et al.
116. Biogeographic pattern of living vegetation carbon turnover time in mature forests across continents K. Yu et al.
117. Land cover and management effects on ecosystem resistance to drought stress C. Xiao et al.
118. How forest age impacts on net primary productivity: Insights from future multi-scenarios L. Tian et al.