33 citations as recorded by crossref.

1. A long-term time series of global and diffuse photosynthetically active radiation in the Mediterranean: interannual variability and cloud effects P. Trisolino et al. https://doi.org/10.5194/acp-18-7985-2018
2. Coupling of Phosphorus Processes With Carbon and Nitrogen Cycles in the Dynamic Land Ecosystem Model: Model Structure, Parameterization, and Evaluation in Tropical Forests Z. Wang et al. https://doi.org/10.1029/2020MS002123
3. Improving the ISBACC land surface model simulation of water and carbon fluxes and stocks over the Amazon forest E. Joetzjer et al. https://doi.org/10.5194/gmd-8-1709-2015
4. Studying the impact of biomass burning aerosol radiative and climate effects on the Amazon rainforest productivity with an Earth system model F. Malavelle et al. https://doi.org/10.5194/acp-19-1301-2019
5. Towards a comprehensive approach to parameter estimation in land surface parameterization schemes R. Rosolem et al. https://doi.org/10.1002/hyp.9362
6. Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters A. Castanho et al. https://doi.org/10.5194/bg-10-2255-2013
7. TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description I. Maréchaux et al. https://doi.org/10.5194/gmd-18-5143-2025
8. Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia L. Anderson et al. https://doi.org/10.5194/bg-6-1883-2009
9. Development of a high-resolution dataset of future monthly surface solar radiation by combining CMIP6 projections and satellite-based retrievals J. He et al. https://doi.org/10.1016/j.accre.2025.02.007
10. Diel ecosystem conductance response to vapor pressure deficit is suboptimal and independent of soil moisture C. Lin et al. https://doi.org/10.1016/j.agrformet.2017.12.078
11. Transferability of an individual- and trait-based forest dynamics model: A test case across the tropics E. Rau et al. https://doi.org/10.1016/j.ecolmodel.2021.109801
12. Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees J. Lloyd et al. https://doi.org/10.5194/bg-7-1833-2010
13. Accounting for the impact of genotype and environment on variation in leaf respiration of wheat in Mexico and Australia O. Gaju et al. https://doi.org/10.1093/jxb/erae449
14. Impact of PM2.5 on cardiorespiratory mortality: A study in the capitals of Brazilian amazon rainforest G. de Oliveira Silveira et al. https://doi.org/10.1016/j.tox.2026.154401
15. Application of a coupled model of photosynthesis and stomatal conductance for estimating plant physiological response to pollution by fine particulate matter (PM2.5) W. Yu et al. https://doi.org/10.1007/s11356-018-2128-6
16. Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data G. Bonan et al. https://doi.org/10.1029/2010JG001593
17. Variations in Amazon forest productivity correlated with foliar nutrients and modelled rates of photosynthetic carbon supply L. Mercado et al. https://doi.org/10.1098/rstb.2011.0045
18. An individual‐based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications I. Maréchaux & J. Chave https://doi.org/10.1002/ecm.1271
19. Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data M. Groenendijk et al. https://doi.org/10.1016/j.agrformet.2010.08.013
20. Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses L. Rowland et al. https://doi.org/10.5194/gmd-8-1097-2015
21. Nutritional status of Abies pinsapo forests along a nitrogen deposition gradient: do C/N/P stoichiometric shifts modify photosynthetic nutrient use efficiency? M. Blanes et al. https://doi.org/10.1007/s00442-012-2454-1
22. Simulating forest productivity along a neotropical elevational transect: temperature variation and carbon use efficiency T. Marthews et al. https://doi.org/10.1111/j.1365-2486.2012.02728.x
23. Reconciling the optimal and empirical approaches to modelling stomatal conductance B. MEDLYN et al. https://doi.org/10.1111/j.1365-2486.2010.02375.x
24. Triggering Deep Convection with a Probabilistic Plume Model F. D’Andrea et al. https://doi.org/10.1175/JAS-D-13-0340.1
25. Determining Spatial Variation in Soil Properties in Teak and Native Tropical Forest Plots Using Electromagnetic Induction L. Bréchet et al. https://doi.org/10.2136/vzj2011.0102
26. Photosynthetic temperature responses in leaves and canopies: why temperature optima may disagree at different scales D. Kumarathunge et al. https://doi.org/10.1093/treephys/tpae135
27. Estimating aerosol characteristics from solar irradiance measurements at an urban location in southeastern Spain I. Foyo-Moreno et al. https://doi.org/10.1002/2013JD020599
28. Effects of leaf age and canopy structure on gross ecosystem production in a subtropical evergreen Chinese fir forest Q. Wu et al. https://doi.org/10.1016/j.agrformet.2021.108618
29. Deriving Plant Functional Types for Amazonian forests for use in vegetation dynamics models N. Fyllas et al. https://doi.org/10.1016/j.ppees.2011.11.001
30. Representation of the phosphorus cycle in the Joint UK Land Environment Simulator (vn5.5_JULES-CNP) M. Nakhavali et al. https://doi.org/10.5194/gmd-15-5241-2022
31. Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin K. Mallick et al. https://doi.org/10.5194/hess-20-4237-2016
32. A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA J. Iiames et al. https://doi.org/10.3390/f9010026
33. The Global Land Carbon Cycle Simulated With ISBA‐CTRIP: Improvements Over the Last Decade C. Delire et al. https://doi.org/10.1029/2019MS001886