67 citations as recorded by crossref.

1. Light use efficiency (LUE) based bimonthly gross primary productivity (GPP) for global grasslands at 30 m spatial resolution (2000–2022) M. Isik et al.
2. Development of a model framework for terrestrial carbon flux prediction: the Regional Carbon and Climate Analytics Tool (RCCAT) applied to non-tidal wetlands A. Brereton et al.
3. Spatializing Net Ecosystem Exchange in the Brazilian Amazon biome using the JULES model and vegetation properties A. Prudente Jr. et al.
4. Prithvi-EO-2.0: A Versatile Multitemporal Foundation Model for Earth Observation Applications D. Szwarcman et al.
5. Global Upscaling of Gross Primary Productivity Using a Simple and Robust Modeling Scheme C. Cao et al.
6. CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization Y. Kang et al.
7. OpenBench: a land model evaluation system Z. Wei et al.
8. Radiocarbon and the Transit Time of Carbon in Terrestrial Ecosystems C. Sierra & S. Trumbore
9. Tower-to-global upscaling of terrestrial carbon fluxes driven by MODIS-LAI, Sentinel-3-LAI and ERA5-Land data P. Reyes-Muñoz et al.
10. Hydroclimate shapes photosynthetic sensitivity to cloud cover across global terrestrial ecosystems H. Luo et al.
11. A novel memory-based deep learning framework for reliable joint estimation of daily vegetation carbon fluxes X. Chen et al.
12. Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale B. Cazorla et al.
13. A machine learning framework for modeling and upscaling mangrove carbon productivity (ML-MCP) K. Alsafadi et al.
14. Global assessment of terrestrial precipitation and evapotranspiration in CMIP6 simulations using observation-based estimates S. Sun et al.
15. Insights into terrestrial carbon and water cycling from the global eddy covariance network J. Xiao et al.
16. MCI GPP: ensembling a global model- and climate-independent gross primary productivity for 2001–2023 J. Pu et al.
17. Climate impact on mean annual cycle and interannual variability of CO2 fluxes in European deciduous broadleaf and evergreen needleleaf forests: insights from observations and state-of-the-art data-driven and process-based models A. Ullah et al.
18. Declining net carbon sequestration of west-central Indian ecosystem in response to frequently occurring drought: Inference from satellite measurements and modeling A. Ravi et al.
19. H2MV (v1.0): global physically constrained deep learning water cycle model with vegetation Z. Baghirov et al.
20. The UFLUX ensemble of multiple-scale carbon, water, and energy fluxes S. Zhu et al.
21. Fusing Enhanced Flux Measurements and Multi-Source Satellite Observations to Improve GPP Estimation for the Qinghai–Tibet Plateau Based on AutoML Techniques M. Zhao et al.
22. All-sky hourly estimation over East Asia using Himawari-8 AHI and multi-source data: investigating the main climatic drivers of afternoon depression and intraday variability in gross primary productivity S. Bae et al.
23. A process model-guided transfer learning framework for mapping global gross primary production X. Guan et al.
24. WOMBAT v2.S: A Bayesian Inversion Framework for Attributing Global CO2 Flux Components From Multiprocess Data J. Jacobson et al.
25. Remote sensing proxies underestimate fire-induced gross primary productivity loss and overestimate recovery in forests X. Fan et al.
26. Large gains in leaf scale photosynthetic rates of sparsely vegetated arid and semi-arid lands J. Pu et al.
27. Amazon dieback beyond the 21st century under high-emission scenarios by Earth System models I. Melnikova et al.
28. An Interpretable Machine Learning Approach to Remote Sensing-Based Estimation of Hourly Agricultural Evapotranspiration in Drylands Q. Zhuang et al.
29. Global 0.1-Degree Monthly Mean Hourly Total Canopy Solar-Induced Chlorophyll Fluorescence Dataset Derived from Random Forest Y. Liu et al.
30. To what extent does the CO2 diurnal cycle impact flux estimates derived from global and regional inversions? S. Munassar et al.
31. Integrating flux footprint, random forest, and SHAP for interpretable hourly carbon flux upscaling: Development and application in the Qilian mountains watershed J. An et al.
32. First global carbon dynamics from an observational and process-informed hybrid perspective: Oversimplified respiration representation likely drives divergence in terrestrial carbon sequestration across models S. Zhu et al.
33. Constraining a data-driven CO2 flux model by ecosystem and atmospheric observations using atmospheric transport S. Upton et al.
34. Unrecognised water limitation is a main source of uncertainty for models of terrestrial photosynthesis S. Biegel et al.
35. High-spatial-resolution gross primary production estimation from Sentinel-2 reflectance using hybrid Gaussian processes modeling E. De Clerck et al.
36. Assessing the suitability of global evapotranspiration products over irrigated areas P. Laluet et al.
37. Ecosystem carbon use efficiency at global scale from upscaling eddy-covariance data with machine learning and MODIS products M. Campos-Taberner et al.
38. Using point dendrometers to improve forest transpiration estimation accuracy at stand scales R. Bright et al.
39. Reviews and syntheses: Current perspectives on biosphere research 2024–2025 – eight findings from ecology, sociology, and economics F. Bohn et al.
40. Water tracer model-assessed contributions of source waters to changing circumpolar Arctic terrestrial evapotranspiration and river discharge H. Park et al.
41. Increase in plant reliance on past precipitation associated with greening and drying H. Zhang et al.
42. If the Yedoma thaws, will we notice? Quantifying detection limits of top-down methane monitoring infrastructures M. Pallandt et al.
43. Global variation in vegetation carbon use efficiency inferred from eddy covariance observations X. Luo et al.
44. Model and Observation for surface–atmosphere interactions over heterogeneous landscape: MOSAI project F. Lohou et al.
45. Variability and uncertainty in net ecosystem carbon exchange modeling: Systematic estimates at global flux sites via ensemble machine learning N. Wang et al.
46. Combined CO2 measurement record indicates Amazon forest carbon uptake is offset by savanna carbon release S. Botía et al.
47. Observed declining strength of vegetation-atmosphere coupling S. Li et al.
48. pyVPRM: a next-generation vegetation photosynthesis and respiration model for the post-MODIS era T. Glauch et al.
49. On the added value of sequential deep learning for the upscaling of evapotranspiration B. Kraft et al.
50. GPP-net: a robust high-resolution GPP estimation network for Sentinel-2 using only surface reflectance and photosynthetically active radiation S. Wang et al.
51. Global optimization of a water-constrained two-leaf light use efficiency model through multi-biome FLUXNET observations S. Zhang et al.
52. Climate Change Is Altering Ecosystem Water Use Efficiency in Water‐Limited Ecosystems T. Green et al.
53. The net ecosystem carbon balance (NECB) at catchment scales in the Arctic E. López-Blanco et al.
54. Carbon–Water Coupling in Forest Ecosystems Under Climate Change: Advances in Water Use Efficiency and Sustainability Perspectives X. Liang et al.
55. Modeling diurnal gross primary production in East Asia using Himawari-8/9 geostationary satellite data Y. Yamamoto et al.
56. Detecting anthropogenically induced changes in extreme and seasonal evapotranspiration observations M. Egli et al.
57. A U.S. scientific community review of carbon cycle science gaps and opportunities to better support earth system science and carbon management N. Parazoo et al.
58. Automated machine learning integrating multi-source satellite observations to predict gross and net CO2 fluxes of coastal wetlands in China N. Ngoc Tu et al.
59. Flux Footprints: A Critical Link to Bridge Eddy‐Covariance Measurements With Models, Remote Sensing, and Other Observations H. Chu et al.
60. Improved consistency in solar-induced fluorescence retrievals from GOME-2A with the SIFTER v3 algorithm J. Anema et al.
61. UFLUX v2.0: A Process-Informed Machine Learning Framework for Efficient and Explainable Modeling of Terrestrial Carbon Uptake W. Dong et al.
62. Spatiotemporal averaging resolution of high importance within Earth-observation-based light use efficiency models of gross primary production T. Tagesson et al.
63. Benchmarking and evaluating the NASA Land Information System (version 7.5.2) coupled with the refactored Noah-MP land surface model (version 5.0) C. He et al.
64. Large contribution of antecedent climate to ecosystem productivity anomalies during extreme events J. Qiu et al.
65. Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle R. Zhao et al.
66. An information-theoretic approach to obtain ensemble averages from Earth system models C. Sierra & E. Muñoz
67. Warming Reshapes Land-Atmosphere Coupling: The LST-SM-ET-GPP Framework R. Mi et al.