400 citations as recorded by crossref.

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14. Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century T. Smallman et al. 10.5194/esd-12-1191-2021
15. NIRVP: A robust structural proxy for sun-induced chlorophyll fluorescence and photosynthesis across scales B. Dechant et al. 10.1016/j.rse.2021.112763
16. Exploring neuro-symbolic AI applications in geoscience: implications and future directions for mineral prediction W. Chen et al. 10.1007/s12145-024-01278-7
17. Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe C. Poppe Terán et al. 10.5194/gmd-18-287-2025
18. Science to Commerce: A Commercial-Scale Protocol for Carbon Trading Applied to a 28-Year Record of Forest Carbon Monitoring at the Harvard Forest N. Bautista et al. 10.3390/land10020163
19. Distinct response of gross primary productivity in five terrestrial biomes to precipitation variability F. Ritter et al. 10.1038/s43247-020-00034-1
20. Impacts of benchmarking choices on inferred model skill of the Arctic–Boreal terrestrial carbon cycle J. Poe et al. 10.1088/2752-664X/adacee
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25. Leaf-scale quantification of the effect of photosynthetic gas exchange on Δ17O of atmospheric CO2 G. Adnew et al. 10.5194/bg-17-3903-2020
26. Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement A. Agustí-Panareda et al. 10.1038/s41597-022-01228-2
27. Evaluating the Performance of the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) Tailored to the Pan‐Canadian Domain S. Curasi et al. 10.1029/2022MS003480
28. Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model E. Kyker‐Snowman et al. 10.1111/gcb.15894
29. Environment-sensitivity functions for gross primary productivity in light use efficiency models S. Bao et al. 10.1016/j.agrformet.2021.108708
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31. New Drought Projections Over East Asia Using Evapotranspiration Deficits From the CMIP6 Warming Scenarios D. Kim et al. 10.1029/2020EF001697
32. Learning extreme vegetation response to climate drivers with recurrent neural networks F. Martinuzzi et al. 10.5194/npg-31-535-2024
33. Incorporation of needleleaf traits improves estimation of light absorption and gross primary production of evergreen needleleaf forests B. Pan et al. 10.1016/j.agrformet.2025.110526
34. Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality Y. Yang et al. 10.1007/s11427-021-2045-5
35. Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global‐scale models J. Jian et al. 10.1111/gcb.15795
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38. How long does carbon stay in a near-pristine central Amazon forest? An empirical estimate with radiocarbon I. Chanca et al. 10.5194/bg-22-455-2025
39. A long-term reconstruction of a global photosynthesis proxy over 1982–2023 J. Fang et al. 10.1038/s41597-025-04686-6
40. Capturing the spatiotemporal variations in the gross primary productivity in coastal wetlands by integrating eddy covariance, Landsat, and MODIS satellite data: A case study in the Yangtze Estuary, China Z. Yang et al. 10.1016/j.ecolind.2023.110154
41. Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration C. Zhao & W. Zhu 10.1038/s43247-025-02240-1
42. Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0 X. Yue et al. 10.5194/gmd-17-4621-2024
43. Causal hybrid modeling with double machine learning—applications in carbon flux modeling K. Cohrs et al. 10.1088/2632-2153/ad5a60
44. Carbon dynamics and soil greenhouse fluxes in a Florida's native rangeland before and after fire R. Bracho et al. 10.1016/j.agrformet.2021.108682
45. Evaluation of earth system model and atmospheric inversion using total column CO2 observations from GOSAT and OCO-2 P. Patra et al. 10.1186/s40645-021-00420-z
46. Improving regional climate simulations based on a hybrid data assimilation and machine learning method X. He et al. 10.5194/hess-27-1583-2023
47. Physics-constrained machine learning for satellite-derived evapotranspiration in China C. Zhang et al. 10.1016/j.jhydrol.2025.133512
48. Dryland Ecosystems of the Sudano-Sahel: A Vegetation Model Perspective W. Verbruggen 10.1163/2031356X-35010012
49. A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band X. Liu et al. 10.1016/j.rse.2022.113341
50. Global trends in land-atmosphere CO<SUB>2</SUB> exchange fluxes: an analysis of a flux measurement dataset and comparison with terrestrial model simulations A. ITO 10.2480/agrmet.D-21-00015
51. Estimating Global GPP From the Plant Functional Type Perspective Using a Machine Learning Approach R. Guo et al. 10.1029/2022JG007100
52. A global terrestrial ecosystem respiration dataset (2001-2010) estimated with MODIS land surface temperature and vegetation indices J. Ai et al. 10.1080/20964471.2020.1768001
53. Soil respiration–driven CO 2 pulses dominate Australia’s flux variability E. Metz et al. 10.1126/science.add7833
54. Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes W. Sun et al. 10.1029/2020AV000310
55. Spatial variations in terrestrial net ecosystem productivity and its local indicators E. Cui et al. 10.5194/bg-17-6237-2020
56. Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake J. Lai et al. 10.1038/s41586-024-08050-3
57. MetaFlux: Meta-learning global carbon fluxes from sparse spatiotemporal observations J. Nathaniel et al. 10.1038/s41597-023-02349-y
58. Causal inference reveals the dominant role of interannual variability of carbon sinks in complicated environmental-terrestrial ecosystems C. Dang et al. 10.1016/j.rse.2024.114300
59. Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations J. Leng et al. 10.5194/essd-16-1283-2024
60. Representation of Leaf‐to‐Canopy Radiative Transfer Processes Improves Simulation of Far‐Red Solar‐Induced Chlorophyll Fluorescence in the Community Land Model Version 5 R. Li et al. 10.1029/2021MS002747
61. Machine learning methods for assessing photosynthetic activity: environmental monitoring applications S. Khruschev et al. 10.1007/s12551-022-00982-2
62. Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning X. Zhu et al. 10.1016/j.scitotenv.2022.159390
63. The CO2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter‐annual scales S. Botía et al. 10.1111/gcb.15905
64. 中国陆地生态系统碳汇稳定性的空间分布特征及驱动机制 锴. 王 et al. 10.1360/N072021-0345
65. Vegetation Photosynthesis Model v3.0: Improved Estimates of Terrestrial Gross Primary Production from Individual Eddy Flux Tower Sites to the Globe L. Pan et al. 10.34133/remotesensing.0471
66. Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO2 T. Thum et al. 10.5194/bg-17-5721-2020
67. Testing stomatal models at the stand level in deciduous angiosperm and evergreen gymnosperm forests using CliMA Land (v0.1) Y. Wang et al. 10.5194/gmd-14-6741-2021
68. Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling A. van der Woude et al. 10.5194/essd-15-579-2023
69. Emergent Climatic Controls on Soil Carbon Turnover and Its Variability in Warm Climates H. Huang et al. 10.1029/2023GL105291
70. A 2001–2022 global gross primary productivity dataset using an ensemble model based on the random forest method X. Chen et al. 10.5194/bg-21-4285-2024
71. Elevation-dependent pattern of net CO2 uptake across China D. Wei et al. 10.1038/s41467-024-46930-4
72. Machine learning algorithms improve MODIS GPP estimates in United States croplands D. Menefee et al. 10.3389/frsen.2023.1240895
73. Global Carbon Fluxes Using Multioutput Gaussian Processes Regression and MODIS Products M. Campos-Taberner et al. 10.1109/JSTARS.2024.3413184
74. Improved GPP upscaling from instantaneous measurements to daily sums using the light-use-efficiency-based model R. Chen et al. 10.1016/j.agrformet.2025.110529
75. The Diurnal Dynamics of Gross Primary Productivity Using Observations From the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite‐R Series at an Oak Savanna Ecosystem A. Khan et al. 10.1029/2021JG006701
76. Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity W. Liu et al. 10.1016/j.ecolind.2025.113558
77. Apparent ecosystem carbon turnover time: uncertainties and robust features N. Fan et al. 10.5194/essd-12-2517-2020
78. Modeled Surface‐Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks D. Reed et al. 10.1029/2021JG006363
79. Bridging Satellite Productivity and Global Biodiversity: Unveiling Insights through Dynamic Habitat Indices K. Liu et al. 10.34133/remotesensing.0624
80. Potential for equation discovery with AI in the climate sciences C. Huntingford et al. 10.5194/esd-16-475-2025
81. CO2 fertilization is spatially distinct from stomatal conductance reduction in controlling ecosystem water-use efficiency increase X. Zhang et al. 10.1088/1748-9326/ac6c9c
82. Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions Q. Zhu et al. 10.1088/1748-9326/adad02
83. Artificial intelligence for geoscience: Progress, challenges, and perspectives T. Zhao et al. 10.1016/j.xinn.2024.100691
84. Remote Sensing‐Based Assessment of Carbon and Water Ecosystem Services in Response to Climate and Vegetation Cover Changes Across Global Major River Basins Y. Wang & J. Jin 10.1002/ldr.70025
85. WetCH4: a machine-learning-based upscaling of methane fluxes of northern wetlands during 2016–2022 Q. Ying et al. 10.5194/essd-17-2507-2025
86. Preface: Advancing deep learning for remote sensing time series data analysis H. Zhang et al. 10.1016/j.rse.2025.114711
87. Aircraft Measurements of Tropospheric CO2 in the North China Plain in Autumn and Winter of 2018–2019 H. Zhang et al. 10.3390/atmos14121835
88. Benchmarking large-scale evapotranspiration estimates: A perspective from a calibration-free complementary relationship approach and FLUXCOM N. Ma et al. 10.1016/j.jhydrol.2020.125221
89. Observed increasing light-use efficiency of terrestrial gross primary productivity Z. Liu et al. 10.1016/j.agrformet.2024.110269
90. Siberian 2020 heatwave increased spring CO2 uptake but not annual CO2 uptake M. Kwon et al. 10.1088/1748-9326/ac358b
91. MODIS-based modeling of evapotranspiration from woody vegetation supported by root-zone water storage G. Cui et al. 10.1016/j.rse.2024.114000
92. Emergent constraints on historical and future global gross primary productivity X. Chen et al. 10.1111/gcb.17479
93. Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks G. Tramontana et al. 10.1111/gcb.15203
94. The spatial heterogeneity of the relationship between gross primary production and sun-induced chlorophyll fluorescence regulated by climate conditions during 2007–2018 Y. Wang et al. 10.1016/j.gecco.2021.e01721
95. Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. 10.3389/frwa.2021.789352
96. Functionally Assembled Terrestrial Ecosystem Simulator (FATES) for Hurricane Disturbance and Recovery M. Shi et al. 10.1029/2023MS003679
97. Assimilation of Global Satellite Leaf Area Estimates Reduces Modeled Global Carbon Uptake and Energy Loss by Terrestrial Ecosystems A. Fox et al. 10.1029/2022JG006830
98. The ASK-16 motorized glider: an airborne eddy covariance platform to measure turbulence, energy, and matter fluxes I. Wiekenkamp et al. 10.5194/amt-18-749-2025
99. Technical note: A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set S. Walther et al. 10.5194/bg-19-2805-2022
100. A Spatially Downscaled TROPOMI SIF Product at 0.005° Resolution With Bias Correction J. Hu et al. 10.1109/JSTARS.2024.3433371
101. A consistent budgeting of terrestrial carbon fluxes L. Dorgeist et al. 10.1038/s41467-024-51126-x
102. Cross-biome synthesis of source versus sink limits to tree growth A. Cabon et al. 10.1126/science.abm4875
103. Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East‐West Divide of Temperate North America B. Byrne et al. 10.1029/2020GB006598
104. Climate drivers of the variations of vegetation productivity in India A. Verma et al. 10.1088/1748-9326/ac7c7f
105. Assessing Model Predictions of Carbon Dynamics in Global Drylands D. Fawcett et al. 10.3389/fenvs.2022.790200
106. How the CMIP6 climate models project the historical terrestrial GPP in China C. Zhang et al. 10.1002/joc.7834
107. Ideas and perspectives: Beyond model evaluation – combining experiments and models to advance terrestrial ecosystem science S. Caldararu et al. 10.5194/bg-20-3637-2023
108. Widespread temporal and spatial variability in net ecosystem productivity under climate change H. Huang et al. 10.1016/j.oneear.2024.01.008
109. Do State‐Of‐The‐Art Atmospheric CO2 Inverse Models Capture Drought Impacts on the European Land Carbon Uptake? W. He et al. 10.1029/2022MS003150
110. Demands and possibilities for field-scale estimation of agricultural greenhouse gas balances T. Palosuo et al. 10.1016/j.catena.2024.108649
111. CO2 exchange of the ecosystem–atmosphere in a mountain forest ecosystem: Combining stable carbon isotope (δ13C) and soil respiration measurements H. Li et al. 10.1016/j.ecolind.2022.108947
112. Emerging signals of declining forest resilience under climate change G. Forzieri et al. 10.1038/s41586-022-04959-9
113. Paddy rice methane emissions across Monsoon Asia Z. Ouyang et al. 10.1016/j.rse.2022.113335
114. The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2) E. Sinha et al. 10.1029/2022JG007187
115. Non-growing season carbon emissions in a northern peatland are projected to increase under global warming A. Rafat et al. 10.1038/s43247-021-00184-w
116. Kernel methods and their derivatives: Concept and perspectives for the earth system sciences J. Johnson et al. 10.1371/journal.pone.0235885
117. Observed impacts of large wind farms on grassland carbon cycling D. Wu et al. 10.1016/j.scib.2023.10.016
118. Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling A. Chen et al. 10.1029/2022MS003135
119. Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity L. Kooistra et al. 10.5194/bg-21-473-2024
120. Bridging the gap in carbon cycle studies: Meteorological station-based carbon flux dataset as a complement to EC towers W. Zhang et al. 10.1016/j.agrformet.2025.110397
121. Quantifying the impacts of land cover change on gross primary productivity globally A. Krause et al. 10.1038/s41598-022-23120-0
122. Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment E. Başakın et al. 10.3390/rs16111994
123. How Well Do We Understand the Land‐Ocean‐Atmosphere Carbon Cycle? D. Crisp et al. 10.1029/2021RG000736
124. Increased photosynthesis during spring drought in energy-limited ecosystems D. Miller et al. 10.1038/s41467-023-43430-9
125. Global synchronous increase in light-saturated and peak vegetation productivity K. Huang & J. Xia 10.1016/j.fmre.2024.09.001
126. Global apparent temperature sensitivity of terrestrial carbon turnover modulated by hydrometeorological factors N. Fan et al. 10.1038/s41561-022-01074-2
127. Random Forest Development and Modeling of Gross Primary Productivity in the Hudson Bay Lowlands J. Beaver et al. 10.1080/07038992.2024.2355937
128. Ecological restoration and rising CO2enhance the carbon sink, counteracting climate change in northeastern China B. Huang et al. 10.1088/1748-9326/ac3871
129. Analysis of Influencing Factors of Terrestrial Carbon Sinks in China Based on LightGBM Model and Bayesian Optimization Algorithm Y. Zou & X. Wang 10.3390/su17114836
130. Do forests store more water? A comparative analysis of water storage between multiple land cover types Q. Wu et al. 10.1016/j.jhydrol.2025.133752
131. Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2) W. Wieder et al. 10.1029/2021GB007034
132. Multi-year observations reveal a larger than expected autumn respiration signal across northeast Eurasia B. Byrne et al. 10.5194/bg-19-4779-2022
133. Solar-Induced Chlorophyll Fluorescence (SIF): Towards a Better Understanding of Vegetation Dynamics and Carbon Uptake in Arctic-Boreal Ecosystems R. Cheng 10.1007/s40641-024-00194-8
134. The potential of urban irrigation for counteracting carbon-climate feedback P. Li et al. 10.1038/s41467-024-46826-3
135. The fate and transit time of carbon in a tropical forest C. Sierra et al. 10.1111/1365-2745.13723
136. The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback S. Kou-Giesbrecht et al. 10.5194/bg-21-3339-2024
137. A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research D. Montero et al. 10.1038/s41597-023-02096-0
138. Increase in gross primary production of boreal forests balanced out by increase in ecosystem respiration J. Pulliainen et al. 10.1016/j.rse.2024.114376
139. Projected Rainfall‐Driven Expansion of Woody Cover in African Drylands W. Zhang et al. 10.1029/2023GL103932
140. Cascading environmental, phenological, and physiological influences on spatial variability of annual gross primary productivity in the Northern Hemisphere L. Han et al. 10.1016/j.scitotenv.2025.179290
141. A Radiation-Regulated Dynamic Maximum Light Use Efficiency for Improving Gross Primary Productivity Estimation Z. Xie et al. 10.3390/rs15051176
142. Multiscale analysis of existing actual evapotranspiration products over agropastoral Sahel J. Etchanchu et al. 10.1016/j.jhydrol.2024.132585
143. Spatio-temporal variability of gross primary productivity in moist and dry deciduous plant functional types of Northwest Himalayan foothills of India using temperature-greenness model R. Srinet et al. 10.1080/10106049.2020.1801855
144. Tracking Global Patterns of Drought‐Induced Productivity Loss Along Severity Gradient Y. Wang et al. 10.1029/2021JG006753
145. Impact of leaf area index assimilation and gauge-corrected precipitation on land surface variables in LDAS-Monde: a case study over China E. Liu et al. 10.1016/j.jhydrol.2025.133304
146. Ideas and perspectives: Allocation of carbon from net primary production in models is inconsistent with observations of the age of respired carbon C. Sierra et al. 10.5194/bg-19-3727-2022
147. Wildfires offset the increasing but spatially heterogeneous Arctic–boreal CO2 uptake A. Virkkala et al. 10.1038/s41558-024-02234-5
148. Prediction of Gross Primary Productivity Change in Central Asia Under Climate Change Using Deep Learning W. Shao et al. 10.1109/JSTARS.2025.3556678
149. Addressing biases in Arctic–boreal carbon cycling in the Community Land Model Version 5 L. Birch et al. 10.5194/gmd-14-3361-2021
150. Evidence and attribution of the enhanced land carbon sink S. Ruehr et al. 10.1038/s43017-023-00456-3
151. Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation R. Oliver et al. 10.5194/gmd-15-5567-2022
152. Impacts of climate extremes on variations in evergreen forest ecosystem carbon–water fluxes across Southern China W. Xing et al. 10.1016/j.gloplacha.2025.104867
153. Temperature, Moisture, Hyperspectral Vegetation Indexes, and Leaf Traits Regulated Soil Respiration in Different Crop Planting Fields X. Yao et al. 10.1007/s42729-021-00600-2
154. Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability K. Wang et al. 10.1038/s41467-022-31175-w
155. Climate‐Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products M. O'Sullivan et al. 10.1029/2020GB006613
156. Extrapolability improvement of machine learning-based evapotranspiration models via domain-adversarial neural networks H. Shi & X. Cai 10.1016/j.envsoft.2025.106383
157. Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask? S. Gallup et al. 10.1029/2021MS002555
158. Effects of Land Cover Change on Vegetation Carbon Source/Sink in Arid Terrestrial Ecosystems of Northwest China, 2001–2018 H. Tu et al. 10.3390/rs15092471
159. Constraining biospheric carbon dioxide fluxes by combined top-down and bottom-up approaches S. Upton et al. 10.5194/acp-24-2555-2024
160. Investigating the temporal lag and accumulation effect of climatic factors on vegetation photosynthetic activity over subtropical China J. Liang et al. 10.1016/j.ecolind.2024.112406
161. Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations V. Arora et al. 10.5194/bg-20-1313-2023
162. UFLUX-GPP: A Cost-Effective Framework for Quantifying Daily Terrestrial Ecosystem Carbon Uptake Using Satellite Data S. Zhu et al. 10.1109/TGRS.2024.3439333
163. Mapping turnover of dissolved organic carbon in global topsoil Z. Guo et al. 10.1016/j.scitotenv.2023.167621
164. Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods W. Zhu et al. 10.1080/15481603.2024.2318846
165. Net ecosystem exchange (NEE) estimates 2006–2019 over Europe from a pre-operational ensemble-inversion system S. Munassar et al. 10.5194/acp-22-7875-2022
166. Using automated machine learning for the upscaling of gross primary productivity M. Gaber et al. 10.5194/bg-21-2447-2024
167. Assessing the effectiveness of a central flux tower in representing the spatial variations in gross primary productivity in a semi-arid pine forest H. Wang et al. 10.1016/j.agrformet.2023.109415
168. Contrasting responses of vegetation productivity to intraseasonal rainfall in Earth system models B. Harris et al. 10.5194/esd-15-1019-2024
169. Divergent historical GPP trends among state-of-the-art multi-model simulations and satellite-based products R. Yang et al. 10.5194/esd-13-833-2022
170. Interannual Variability of Summer Net Ecosystem CO2 Exchange in High Arctic Tundra C. Braybrook et al. 10.1029/2020JG006094
171. Inland Water Greenhouse Gas Budgets for RECCAP2: 2. Regionalization and Homogenization of Estimates R. Lauerwald et al. 10.1029/2022GB007658
172. Overcoming barriers to enable convergence research by integrating ecological and climate sciences: the NCAR–NEON system Version 1 D. Lombardozzi et al. 10.5194/gmd-16-5979-2023
173. A Data-Driven Method for Direct Estimation of Global 8-Day 500-m Ecosystem Water Use Efficiency L. Huang et al. 10.1109/TGRS.2024.3501411
174. Estimating the Net Ecosystem Exchange at Global FLUXNET Sites Using a Random Forest Model N. Huang et al. 10.1109/JSTARS.2021.3114190
175. The biological basis for using optical signals to track evergreen needleleaf photosynthesis Z. Pierrat et al. 10.1093/biosci/biad116
176. Inferring causal relations from observational long-term carbon and water fluxes records E. Díaz et al. 10.1038/s41598-022-05377-7
177. Reply to: Autumn cooling paused increased net CO2 release in central Eurasia R. Tang & B. He 10.1038/s41558-023-01626-3
178. The climate benefit of carbon sequestration C. Sierra et al. 10.5194/bg-18-1029-2021
179. Mapping global forest age from forest inventories, biomass and climate data S. Besnard et al. 10.5194/essd-13-4881-2021
180. Serious underestimation of reduced carbon uptake due to vegetation compound droughts J. Song et al. 10.1038/s41612-024-00571-y
181. Harmonizing and Comparing Divergent Estimates of China’s Forest Carbon Sinks Q. Han et al. 10.1016/j.ecolind.2025.113250
182. Towards neural Earth system modelling by integrating artificial intelligence in Earth system science C. Irrgang et al. 10.1038/s42256-021-00374-3
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