45 citations as recorded by crossref.

1. Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0) H. Ninomiya et al. https://doi.org/10.5194/gmd-16-4155-2023
2. Underestimating global land greening: Future vegetation changes and their impacts on terrestrial water loss Y. Chai et al. https://doi.org/10.1016/j.oneear.2025.101176
3. Resilience of a subtropical rainforest to annual typhoon disturbance: Lessons from 25-year data of leaf area index C. Chang et al. https://doi.org/10.1016/j.foreco.2020.118210
4. Characterizing the Error and Bias of Remotely Sensed LAI Products: An Example for Tropical and Subtropical Evergreen Forests in South China Y. Zhao et al. https://doi.org/10.3390/rs12193122
5. Is the annual maximum leaf area index an important driver of water fluxes simulated by a land surface model in temperate forests? A. Maheu et al. https://doi.org/10.1139/cjfr-2020-0126
6. Estimation of Leaf Area Index in a Typical Northern Tropical Secondary Monsoon Rainforest by Different Indirect Methods X. Xie et al. https://doi.org/10.3390/rs15061621
7. Divergent future trends in global land greening and carbon sequestration under climate change scenarios C. Bian & J. Xia https://doi.org/10.1088/1748-9326/ad8508
8. Implementation of nitrogen cycle in the CLASSIC land model A. Asaadi & V. Arora https://doi.org/10.5194/bg-18-669-2021
9. Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change P. Li et al. https://doi.org/10.1016/j.agrformet.2021.108571
10. Impact of leaf area index from various sources on estimating gross primary production in temperate forests using the JULES land surface model H. Lee et al. https://doi.org/10.1016/j.agrformet.2019.107614
11. Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45 S. Curasi et al. https://doi.org/10.5194/gmd-17-2683-2024
12. Peak growing season patterns and climate extremes-driven responses of gross primary production estimated by satellite and process based models over North America W. He et al. https://doi.org/10.1016/j.agrformet.2020.108292
13. Global Carbon Budget 2023 P. Friedlingstein et al. https://doi.org/10.5194/essd-15-5301-2023
14. CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 2: Global benchmarking C. Seiler et al. https://doi.org/10.5194/gmd-14-2371-2021
15. Local-scale evaluation of the simulated interactions between energy, water and vegetation in ISBA, ORCHIDEE and a diagnostic model J. De Pue et al. https://doi.org/10.5194/bg-19-4361-2022
16. Compensatory Effects Between CO2, Nitrogen Deposition, and Nitrogen Fertilization in Terrestrial Biosphere Models Without Nitrogen Compromise Projections of the Future Terrestrial Carbon Sink S. Kou‐Giesbrecht & V. Arora https://doi.org/10.1029/2022GL102618
17. CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance J. Melton et al. https://doi.org/10.5194/gmd-13-2825-2020
18. Stand-Level Biomass and Leaf Trait Models for Young Naturally Regenerated Forests of European Hornbeam B. Konôpka et al. https://doi.org/10.3390/f14061084
19. Ammonia Cycling and Emerging Secondary Aerosols from Arable Agriculture: A European and Irish Perspective V. Pohl et al. https://doi.org/10.3390/air1010003
20. Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset H. Omidvar et al. https://doi.org/10.5194/gmd-15-3041-2022
21. Biomass Allocation into Woody Parts and Foliage in Young Common Aspen (Populus tremula L.)—Trees and a Stand-Level Study in the Western Carpathians B. Konôpka et al. https://doi.org/10.3390/f11040464
22. Improving the MODIS LAI compositing using prior time-series information J. Pu et al. https://doi.org/10.1016/j.rse.2023.113493
23. Responses of non-structural carbohydrate content to different stand densities and configurations in poplar plantations P. Cao et al. https://doi.org/10.1007/s11056-023-10005-x
24. Non‐Structural Carbohydrates Drive Vegetation Productivity: Global Insights From a Land Surface Model Z. Tu et al. https://doi.org/10.1111/geb.70185
25. Simulating the land carbon sink: Progresses and challenges of terrestrial ecosystem models W. Yuan et al. https://doi.org/10.1016/j.agrformet.2024.110264
26. Litter dynamics, leaf area index and forest floor respiration as indicators for understanding the role of Nepalese alder in white oak forests in central Himalaya, India R. Joshi & S. Garkoti https://doi.org/10.1016/j.ecolind.2020.106065
27. Changes in leaf and root carbon allocation of global vegetation simulated by the optimally integrated ecosystem models Z. Duanmu et al. https://doi.org/10.1016/j.agrformet.2024.110366
28. Global Carbon Budget 2024 P. Friedlingstein et al. https://doi.org/10.5194/essd-17-965-2025
29. Seasonal Effect of the Vegetation Clumping Index on Gross Primary Productivity Estimated by a Two-Leaf Light Use Efficiency Model Z. Li et al. https://doi.org/10.3390/rs15235537
30. Effect and suitability evaluation of vegetation restoration on carbon, water, and sand Z. Qiao et al. https://doi.org/10.1016/j.ejrh.2026.103223
31. Evaluating the Performance of the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) Tailored to the Pan‐Canadian Domain S. Curasi et al. https://doi.org/10.1029/2022MS003480
32. Divergent Responses of Leaf Area Index to Abiotic Drivers Across Abies Forest Types in China Z. Gao et al. https://doi.org/10.3390/f17010103
33. Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest B. Bahrami et al. https://doi.org/10.5194/gmd-15-6957-2022
34. Recent field findings and modeling on non-structural carbohydrates (NSCs): How to synthesize? N. Cho et al. https://doi.org/10.1016/j.ecoinf.2022.101695
35. Modeling temporal variations of non-structural carbohydrate (NSC) storages across biomes N. Cho et al. https://doi.org/10.1016/j.foreco.2022.120033
36. Global Carbon Budget 2021 P. Friedlingstein et al. https://doi.org/10.5194/essd-14-1917-2022
37. Pronounced inter-model uncertainties in TRENDY-simulated terrestrial carbon sink responses to hydroclimatic extremes Z. Wang et al. https://doi.org/10.1088/1748-9326/ae4b55
38. Global Patterns and Climate Controls of Terrestrial Ecosystem Light Use Efficiency S. Tang et al. https://doi.org/10.1029/2020JG005908
39. Representing the Dynamic Response of Vegetation to Nitrogen Limitation via Biological Nitrogen Fixation in the CLASSIC Land Model S. Kou‐Giesbrecht & V. Arora https://doi.org/10.1029/2022GB007341
40. Global Carbon Budget 2022 P. Friedlingstein et al. https://doi.org/10.5194/essd-14-4811-2022
41. Summary and synthesis of Changing Cold Regions Network (CCRN) research in the interior of western Canada – Part 2: Future change in cryosphere, vegetation, and hydrology C. DeBeer et al. https://doi.org/10.5194/hess-25-1849-2021
42. A better carbon-water flux simulation in multiple vegetation types by data assimilation Q. Liu et al. https://doi.org/10.1016/j.fecs.2022.100013
43. Seasonal decoupling of water supply and CO2 fluxes of urban greening shrubs is driven by leaf area index W. Huang et al. https://doi.org/10.1016/j.jenvman.2026.129289
44. Global climate change below 2 °C avoids large end century increases in burned area in Canada S. Curasi et al. https://doi.org/10.1038/s41612-024-00781-4
45. 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. https://doi.org/10.5194/bg-21-3339-2024