110 citations as recorded by crossref.

1. Progress in DGVMs: a comment on "Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis" by Verheijen et al. (2013) S. Higgins et al. https://doi.org/10.5194/bg-11-4357-2014
2. The Tree of Life in ecosystems: evolution of plant effects on carbon and nutrient cycling J. Cornelissen et al. https://doi.org/10.1111/1365-2745.12217
3. Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework E. Weng et al. https://doi.org/10.1111/gcb.13542
4. TRY plant trait database – enhanced coverage and open access J. Kattge et al. https://doi.org/10.1111/gcb.14904
5. Functional trait variation related to gap dynamics in tropical moist forests: A vegetation modelling perspective H. Togashi et al. https://doi.org/10.1016/j.ppees.2018.10.004
6. Remote sensing of young leaf photosynthetic capacity in tropical and subtropical evergreen broadleaved forests X. Yang et al. https://doi.org/10.5194/essd-17-3293-2025
7. Understanding global change impacts on South African biomes using Dynamic Vegetation Models G. Moncrieff et al. https://doi.org/10.1016/j.sajb.2015.02.004
8. CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model M. Drüke et al. https://doi.org/10.5194/gmd-14-4117-2021
9. A fully traits-based approach to modeling global vegetation distribution P. van Bodegom et al. https://doi.org/10.1073/pnas.1304551110
10. Future global productivity will be affected by plant trait response to climate N. Madani et al. https://doi.org/10.1038/s41598-018-21172-9
11. Climate change promotes transitions to tall evergreen vegetation in tropical Asia S. Scheiter et al. https://doi.org/10.1111/gcb.15217
12. Traits link drought resistance with herbivore defence and plant economics in semi‐arid grasslands: The central roles of phenology and leaf dry matter content D. Blumenthal et al. https://doi.org/10.1111/1365-2745.13454
13. A global scale mechanistic model of photosynthetic capacity (LUNA V1.0) A. Ali et al. https://doi.org/10.5194/gmd-9-587-2016
14. Trait-based representation of hydrological functional properties of plants in weather and ecosystem models A. Matheny et al. https://doi.org/10.1016/j.pld.2016.10.001
15. Seasonal Variations in Leaf Maximum Photosynthetic Capacity and Its Dependence on Climate Factors Across Global FLUXNET Sites X. Wang et al. https://doi.org/10.1029/2021JG006709
16. Drivers and mechanisms of tree mortality in moist tropical forests N. McDowell et al. https://doi.org/10.1111/nph.15027
17. Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model B. Sakschewski et al. https://doi.org/10.1111/gcb.12870
18. Intraspecific trait variation across scales: implications for understanding global change responses E. Moran et al. https://doi.org/10.1111/gcb.13000
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20. Reshaping Plant Biology: Qualitative and Quantitative Descriptors for Plant Morphology M. Balduzzi et al. https://doi.org/10.3389/fpls.2017.00117
21. Herb hydraulics: Variation and correlation for traits governing drought tolerance and efficiency of water transport R. Huang et al. https://doi.org/10.1016/j.scitotenv.2023.168095
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23. Intra- and inter-specific responses of plant functional traits to environmental variables: implications for community ecology in the tropical monsoonal dwarf forest on Hainan Island M. Yaseen et al. https://doi.org/10.3389/ffgc.2023.1198626
24. The new plant functional diversity model JeDi-BACH (version 1.0) in the ICON Earth System Model (version 1.0) P. Hu et al. https://doi.org/10.5194/gmd-19-6357-2026
25. The validity of optimal leaf traits modelled on environmental conditions K. Bloomfield et al. https://doi.org/10.1111/nph.15495
26. Trait-Based Climate Change Predictions of Vegetation Sensitivity and Distribution in China Y. Yang et al. https://doi.org/10.3389/fpls.2019.00908
27. Microanatomical traits track climate gradients for a dominant C4 grass species across the Great Plains, USA S. Bachle & J. Nippert https://doi.org/10.1093/aob/mcaa146
28. Including leaf trait information helps empirical estimation of jmax from vcmax in cool-temperate deciduous forests G. Song et al. https://doi.org/10.1016/j.plaphy.2021.06.055
29. Mesophyll conductance does not contribute to greater photosynthetic rate per unit nitrogen in temperate compared with tropical evergreen wet‐forest tree leaves N. Bahar et al. https://doi.org/10.1111/nph.15031
30. Plant functional diversity affects climate–vegetation interaction V. Groner et al. https://doi.org/10.5194/bg-15-1947-2018
31. Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information A. Harper et al. https://doi.org/10.5194/gmd-9-2415-2016
32. Do we (need to) care about canopy radiation schemes in DGVMs? Caveats and potential impacts A. Loew et al. https://doi.org/10.5194/bg-11-1873-2014
33. Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model D. Zhu et al. https://doi.org/10.5194/gmd-8-2263-2015
34. Leaf respiration (GlobResp) – global trait database supports Earth System Models S. Wullschleger et al. https://doi.org/10.1111/nph.13364
35. A data-conditioned stochastic parameterization of temporal plant trait variability in an ecohydrological model and the potential for plasticity S. Liu & G. Ng https://doi.org/10.1016/j.agrformet.2019.05.005
36. A simple CO2 exchange model simulates the seasonal leaf area development of peatland sedges M. Raivonen et al. https://doi.org/10.1016/j.ecolmodel.2015.07.008
37. Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management J. Chang et al. https://doi.org/10.5194/bg-13-3757-2016
38. The role of spatiotemporal plant trait variability in model predictions of ecohydrological responses to climate change in a desert shrubland S. Liu & G. Ng https://doi.org/10.1016/j.jhydrol.2020.125088
39. Using traits to uncover tropical forest function N. McDowell & C. Xu https://doi.org/10.1111/nph.14576
40. Leaf Trait Acclimation Amplifies Simulated Climate Warming in Response to Elevated Carbon Dioxide M. Kovenock & A. Swann https://doi.org/10.1029/2018GB005883
41. Imaging spectrometry-derived estimates of regional ecosystem composition for the Sierra Nevada, California S. Bogan et al. https://doi.org/10.1016/j.rse.2019.03.031
42. Variation in trait trade‐offs allows differentiation among predefined plant functional types: implications for predictive ecology L. Verheijen et al. https://doi.org/10.1111/nph.13623
43. The importance of species‐specific and temperature‐sensitive parameterisation of A/Ci models: A case study using cotton (Gossypium hirsutum L.) and the automated ‘OptiFitACi’ R‐package D. Sargent et al. https://doi.org/10.1111/pce.14800
44. A new approach to optimal discretization of plant functional types in a process‐based ecosystem model with forest management: a case study for temperate conifers M. Peaucelle et al. https://doi.org/10.1111/geb.12557
45. Root structural and functional dynamics in terrestrial biosphere models – evaluation and recommendations J. Warren et al. https://doi.org/10.1111/nph.13034
46. Modeling terrestrial carbon and water dynamics across climatic gradients: does plant trait diversity matter? C. Pappas et al. https://doi.org/10.1111/nph.13590
47. A test of the ‘one‐point method’ for estimating maximum carboxylation capacity from field‐measured, light‐saturated photosynthesis M. De Kauwe et al. https://doi.org/10.1111/nph.13815
48. Optimal model complexity for terrestrial carbon cycle prediction C. Famiglietti et al. https://doi.org/10.5194/bg-18-2727-2021
49. Re-evaluating the role of plant traits in cross-scale vegetation simulations: evidence from coastal dwarf forests B. Liu et al. https://doi.org/10.1080/15481603.2026.2620147
50. Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region E. Cui et al. https://doi.org/10.1029/2018GB005909
51. The future distribution of the savannah biome: model-based and biogeographic contingency G. Moncrieff et al. https://doi.org/10.1098/rstb.2015.0311
52. The impact of alternative trait‐scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production A. Walker et al. https://doi.org/10.1111/nph.14623
53. Increases in heat-induced tree mortality could drive reductions of biomass resources in Canada’s managed boreal forest E. Chaste et al. https://doi.org/10.1007/s10980-019-00780-4
54. Representation of Plant Hydraulics in the Noah‐MP Land Surface Model: Model Development and Multiscale Evaluation L. Li et al. https://doi.org/10.1029/2020MS002214
55. Maximum Carboxylation Rate Estimation With Chlorophyll Content as a Proxy of Rubisco Content X. Lu et al. https://doi.org/10.1029/2020JG005748
56. A novel way to understand plant species preferences in relation to groundwater discharge conditions using a trait‐based approach Y. van der Knaap et al. https://doi.org/10.1002/eco.1655
57. From plant functional types to plant functional traits Y. Yang et al. https://doi.org/10.1177/0309133315582018
58. Climate, soil and plant functional types as drivers of global fine‐root trait variation G. Freschet et al. https://doi.org/10.1111/1365-2745.12769
59. Active layer depth and soil properties impact specific leaf area variation and ecosystem productivity in a boreal forest C. Anderson et al. https://doi.org/10.1371/journal.pone.0232506
60. A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: demonstration with photosynthesis simulations D. Aboelyazeed et al. https://doi.org/10.5194/bg-20-2671-2023
61. Plant community structure and nitrogen inputs modulate the climate signal on leaf traits B. Borgy et al. https://doi.org/10.1111/geb.12623
62. In situ temperature response of photosynthesis of 42 tree and liana species in the canopy of two Panamanian lowland tropical forests with contrasting rainfall regimes M. Slot & K. Winter https://doi.org/10.1111/nph.14469
63. Are litter decomposition and fire linked through plant species traits? J. Cornelissen et al. https://doi.org/10.1111/nph.14766
64. Inter- and intra-specific trait shifts among sites differing in drought conditions at the north western edge of the Mediterranean Region E. Garnier et al. https://doi.org/10.1016/j.flora.2018.07.009
65. Higher functional diversity improves modeling of Amazon forest carbon storage B. Rius et al. https://doi.org/10.1016/j.ecolmodel.2023.110323
66. Inverse Determination of the Influence of Fire on Vegetation Carbon Turnover in the Pantropics J. Exbrayat et al. https://doi.org/10.1029/2018GB005925
67. Tradeoff in the supply and demand for CO2dominates the divergence of net photosynthesis rates of functional plants in alpine ecosystems H. Yao et al. https://doi.org/10.1002/eco.2487
68. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales C. Qiu et al. https://doi.org/10.5194/gmd-11-497-2018
69. Linking Leaf Functional Traits with Soil and Climate Factors in Forest Ecosystems in China X. Zhou et al. https://doi.org/10.3390/plants11243545
70. Inclusion of ecologically based trait variation in plant functional types reduces the projected land carbon sink in an earth system model L. Verheijen et al. https://doi.org/10.1111/gcb.12871
71. Simulating the effects of water limitation on plant biomass using a 3D functional–structural plant model of shoot and root driven by soil hydraulics R. Braghiere et al. https://doi.org/10.1093/aob/mcaa059
72. The imprint of plants on ecosystem functioning: A data-driven approach T. Musavi et al. https://doi.org/10.1016/j.jag.2015.05.009
73. Global variability in leaf respiration in relation to climate, plant functional types and leaf traits O. Atkin et al. https://doi.org/10.1111/nph.13253
74. Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1) N. Fyllas et al. https://doi.org/10.5194/gmd-7-1251-2014
75. The emergence and promise of functional biogeography C. Violle et al. https://doi.org/10.1073/pnas.1415442111
76. A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China Y. Yang et al. https://doi.org/10.1038/srep24110
77. Coordination of photosynthetic traits across soil and climate gradients A. Westerband et al. https://doi.org/10.1111/gcb.16501
78. Trait-based modelling in ecology: A review of two decades of research L. Zakharova et al. https://doi.org/10.1016/j.ecolmodel.2019.05.008
79. Biogeographic patterns of multi-element stoichiometry of Quercus variabilis leaves across China X. Sun et al. https://doi.org/10.1139/cjfr-2015-0110
80. Genetic diversity and morphological variability of Iranian Silene aucheriana populations inferred from nrDNA ITS sequences and morphological analysis M. Safaeishakib et al. https://doi.org/10.2478/hacq-2023-0001
81. Vegetation ecology meets ecosystem science: Permanent grasslands as a functional biogeography case study C. Violle et al. https://doi.org/10.1016/j.scitotenv.2015.03.141
82. Leaf chlorophyll constraint on model simulated gross primary productivity in agricultural systems R. Houborg et al. https://doi.org/10.1016/j.jag.2015.03.016
83. Simulating Global Dynamic Surface Reflectances for Imaging Spectroscopy Spaceborne Missions: LPJ‐PROSAIL B. Poulter et al. https://doi.org/10.1029/2022JG006935
84. Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED) R. Fisher et al. https://doi.org/10.5194/gmd-8-3593-2015
85. Plant functional trait uncertainty can outweigh climate scenario uncertainty in tundra ecosystem productivity K. Jay et al. https://doi.org/10.1111/nph.70740
86. BHPMF – a hierarchical Bayesian approach to gap‐filling and trait prediction for macroecology and functional biogeography F. Schrodt et al. https://doi.org/10.1111/geb.12335
87. Differential ecophysiological responses and resilience to heat wave events in four co-occurring temperate tree species A. Guha et al. https://doi.org/10.1088/1748-9326/aabcd8
88. Decomposing leaf mass into metabolic and structural components explains divergent patterns of trait variation within and among plant species M. Katabuchi et al. https://doi.org/10.1007/s00442-025-05714-3
89. The effect of using the plant functional type paradigm on a data-constrained global phenology model S. Caldararu et al. https://doi.org/10.5194/bg-13-925-2016
90. Variation in bulk‐leaf 13C discrimination, leaf traits and water‐use efficiency–trait relationships along a continental‐scale climate gradient in Australia R. Rumman et al. https://doi.org/10.1111/gcb.13911
91. Is there a species spectrum within the world‐wide leaf economics spectrum? Major variations in leaf functional traits in the Mediterranean sclerophyll Quercus ilex Ü. Niinemets https://doi.org/10.1111/nph.13001
92. Seasonal Variation in the Capacity for Plant Trait Measures to Predict Grassland Carbon and Water Fluxes G. Everwand et al. https://doi.org/10.1007/s10021-014-9779-z
93. The multi-assumption architecture and testbed (MAAT v1.0): R code for generating ensembles with dynamic model structure and analysis of epistemic uncertainty from multiple sources A. Walker et al. https://doi.org/10.5194/gmd-11-3159-2018
94. Impacts of climate timescale on the stability of trait–environment relationships C. Famiglietti et al. https://doi.org/10.1111/nph.19416
95. Integrating correlation between traits improves spatial predictions of plant functional composition R. Wüest et al. https://doi.org/10.1111/oik.04420
96. MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales M. De Cáceres et al. https://doi.org/10.5194/gmd-16-3165-2023
97. Using hyperspectral leaf reflectance to estimate photosynthetic capacity and nitrogen content across eastern cottonwood and hybrid poplar taxa T. Kyaw et al. https://doi.org/10.1371/journal.pone.0264780
98. Independent evolutionary changes in fine‐root traits among main clades during the diversification of seed plants O. Valverde‐Barrantes et al. https://doi.org/10.1111/nph.16729
99. Robust hydraulic traits correlation in woody species despite large trait variation along natural and experimental environmental gradients R. Huang et al. https://doi.org/10.1111/1365-2435.14591
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101. An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data T. Majasalmi et al. https://doi.org/10.5194/bg-15-399-2018
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107. Plant Nutrient Contents Rather Than Physical Traits Are Coordinated Between Leaves and Roots in a Desert Shrubland X. Jiang et al. https://doi.org/10.3389/fpls.2021.734775
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109. Global ecosystem-scale plant hydraulic traits retrieved using model–data fusion Y. Liu et al. https://doi.org/10.5194/hess-25-2399-2021
110. Evaluation of the Community Land Model-Simulated Specific Leaf Area with Observations over China: Impacts on Modeled Gross Primary Productivity Y. Zheng et al. https://doi.org/10.3390/f14010164