Canadell, J. G. & Schulze, E. D. Global potential of biospheric carbon management for climate mitigation. Nat. Commun. 5, 5282 (2014).
Google Scholar
Paine, C. E. T. et al. Globally, functional traits are weak predictors of juvenile tree growth, and we do not know why. J. Ecol. 103, 978–989 (2015).
Google Scholar
IPCC Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Pörtner, H.-O. et al. (eds)) (2022).
Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).
Google Scholar
Tagesson, T. et al. Recent divergence in the contributions of tropical and boreal forests to the terrestrial carbon sink. Nat. Ecol. Evol. 4, 202–209 (2020).
Google Scholar
Seidl, R., Schelhaas, M.-J., Rammer, W. & Verkerk, P. J. Increasing forest disturbances in Europe and their impact on carbon storage. Nat. Clim. Change 4, 806–810 (2014).
Google Scholar
Alkama, R. et al. Vegetation-based climate mitigation in a warmer and greener world. Nat. Commun. 13, 606 (2022).
Google Scholar
Lambers, H. & Poorter, H. Inherent variation in growth rate between higher plants: a search for physiological causes and ecological consequences. Adv. Ecol. Res. 23, 187–261 (1992).
Google Scholar
Grime, J. et al. Integrated screening validates primary axes of specialisation in plants. Oikos 79, 259–281 (1997).
Google Scholar
Herms, D. A. & Mattson, W. J. The dilemma of plants: to grow or defend. Q. Rev. Biol. 67, 283–335 (1992).
Google Scholar
Laughlin, D. C. et al. Intraspecific trait variation can weaken interspecific trait correlations when assessing the whole-plant economic spectrum. Ecol. Evol. 7, 8936–8949 (2017).
Google Scholar
Bongers, F. J. et al. Growth-trait relationships in subtropical forest are stronger at higher diversity. J. Ecol. 108, 256–266 (2020).
Google Scholar
Wright, S. J. et al. Functional traits and the growth–mortality trade-off in tropical trees. Ecology 91, 3664–3674 (2010).
Google Scholar
Herault, B. et al. Functional traits shape ontogenetic growth trajectories of rain forest tree species. J. Ecol. 99, 1431–1440 (2011).
Google Scholar
Yang, J., Cao, M. & Swenson, N. G. Why functional traits do not predict tree demographic rates. Trends Ecol. Evol. 33, 326–336 (2018).
Google Scholar
Gibert, A., Gray, E. F., Westoby, M., Wright, I. J. & Falster, D. S. On the link between functional traits and growth rate: meta-analysis shows effects change with plant size, as predicted. J. Ecol. 104, 1488–1503 (2016).
Google Scholar
Weemstra, M., Zambrano, J., Allen, D. & Umaña, M. N. Tree growth increases through opposing above-ground and below-ground resource strategies. J. Ecol. 109, 3502–3512 (2021).
Google Scholar
Augusto, L., Achat, D. L., Jonard, M., Vidal, D. & Ringeval, B. Soil parent material – a major driver of plant nutrient limitations in terrestrial ecosystems. Glob. Change Biol. 23, 3808–3824 (2017).
Google Scholar
Nemani, R. R. et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300, 1560–1563 (2003).
Google Scholar
Fisher, J. B., Badgley, G. & Blyth, E. Global nutrient limitation in terrestrial vegetation. Glob. Biogeochem. Cycles 26, GB3007 (2012).
Google Scholar
Jonard, M. et al. Tree mineral nutrition is deteriorating in Europe. Glob. Change Biol. 21, 418–430 (2015).
Google Scholar
Aerts, R. & Chapin, F. S. The mineral nutrition of wild plants revisited: a re-evaluation of processes and patterns. Adv. Ecol. Res. 30, 1–67 (2000).
Google Scholar
Chapin, F. S., Autumn, K. & Pugnaire, F. Evolution of suites of traits in response to environmental-stress. Am. Nat. 142, S78–S92 (1993).
Google Scholar
Reich, P. B. The world-wide ‘fast-slow’ plant economics spectrum: a traits manifesto. J. Ecol. 102, 275–301 (2014).
Google Scholar
Song, C. et al. Differential tree demography mediated by water stress and functional traits in a moist tropical forest. Funct. Ecol. 37, 2927–2939 (2023).
Google Scholar
Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).
Google Scholar
Poorter, H., Lambers, H. & Evans, J. R. Trait correlation networks: a whole-plant perspective on the recently criticized leaf economic spectrum. N. Phytol. 201, 378–382 (2014).
Google Scholar
Hunter, I. & Schuck, A. Increasing forest growth in Europe—possible causes and implications for sustainable forest management. Plant Biosyst. 136, 133–141 (2002).
Google Scholar
Hoffmann, N., Heinrichs, S., Schall, P. & Vor, T. Climatic factors controlling stem growth of alien tree species at a mesic forest site: a multispecies approach. Eur. J. For. Res. 139, 915–934 (2020).
Google Scholar
Van Sundert, K. et al. Towards comparable assessment of the soil nutrient status across scales—review and development of nutrient metrics. Glob. Change Biol. 26, 392–409 (2020).
Google Scholar
Makoto, K., Kitagawa, R. & Blume-Werry, G. How do leaf functional traits and age influence the maximum rooting depth of trees? Eur. J. For. Res. 142, 1197–1206 (2023).
Google Scholar
Koehler, K., Center, A. & Cavender-Bares, J. Evidence for a freezing tolerance-growth rate trade-off in the live oaks (Quercus series Virentes) across the tropical-temperate divide. N. Phytol. 193, 730–744 (2012).
Google Scholar
Rueda, M., Godoy, O. & Hawkins, B. A. Trait syndromes among North American trees are evolutionarily conserved and show adaptive value over broad geographic scales. Ecography 41, 450–550 (2018).
Google Scholar
Pierce, S. et al. A global method for calculating plant CSR ecological strategies applied across biomes world-wide. Funct. Ecol. 31, 444–457 (2017).
Google Scholar
Mirabel, A. et al. A whole-plant functional scheme predicting the early growth of tropical tree species: evidence from 15 tree species in Central Africa. Trees Struct. Funct. 33, 491–505 (2019).
Google Scholar
Baez, S. & Homeier, J. Functional traits determine tree growth and ecosystem productivity of a tropical montane forest: insights from a long-term nutrient manipulation experiment. Glob. Change Biol. 24, 399–409 (2018).
Google Scholar
Salgado-Luarte, C. & Gianoli, E. Shade tolerance and herbivory are associated with RGR of tree species via different functional traits. Plant Biol. 19, 413–419 (2017).
Google Scholar
Bauman, D. et al. Tropical tree growth sensitivity to climate is driven by species intrinsic growth rate and leaf traits. Glob. Change Biol. 28, 1414–1432 (2022).
Google Scholar
Serra-Maluquer, X. et al. Wood density and hydraulic traits influence species’ growth response to drought across biomes. Glob. Change Biol. 28, 3871–3882 (2022).
Google Scholar
Salguero-Gomez, R. et al. Fast-slow continuum and reproductive strategies structure plant life-history variation worldwide. Proc. Natl Acad. Sci. USA 113, 230–235 (2016).
Google Scholar
Francis, E. J. et al. Quantifying the role of wood density in explaining interspecific variation in growth of tropical trees. Glob. Ecol. Biogeogr. 26, 1078–1087 (2017).
Google Scholar
Rodríguez-Alarcón, S., González-M, R., Carmona, C. P. & Tordoni, E. Trait-growth relationships in Colombian tropical dry forests: incorporating intraspecific variation and trait interactions. J. Veg. Sci. 35, e13233 (2024).
Google Scholar
Huston, M. A. Precipitation, soils, NPP, and biodiversity: resurrection of Albrecht’s curve. Ecol. Monogr. 82, 277–296 (2012).
Google Scholar
Townsend, A. R., Cleveland, C. C., Asner, G. P. & Bustamante, M. M. C. Controls over foliar N:P ratios in tropical rain forests. Ecology 88, 107–118 (2007).
Google Scholar
Qin, Y. et al. Interactions between leaf traits and environmental factors help explain the growth of evergreen and deciduous species in a subtropical forest. For. Ecol. Manage. 560, 121854 (2024).
Google Scholar
Prado-Junior, J. A. et al. Conservative species drive biomass productivity in tropical dry forests. J. Ecol. 104, 817–827 (2016).
Felipe-Lucia, M. R. et al. Multiple forest attributes underpin the supply of multiple ecosystem services. Nat. Commun. 9, 4839 (2018).
Google Scholar
Warner, E. et al. Young mixed planted forests store more carbon than monocultures—a meta-analysis. Front. For. Glob. Change 6, 1226514 (2023).
Google Scholar
Baeten, L. et al. Identifying the tree species compositions that maximize ecosystem functioning in European forests. J. Appl. Ecol. 56, 733–744 (2019).
Google Scholar
Yang, H. et al. Global increase in biomass carbon stock dominated by growth of northern young forests over past decade. Nat. Geosci. 16, 886–892 (2023).
Google Scholar
Schwinning, S., Lortie, C. J., Esque, T. C. & DeFalco, L. A. What common-garden experiments tell us about climate responses in plants. J. Ecol. 110, 986–996 (2022).
Google Scholar
Correia, A. H. et al. Early survival and growth plasticity of 33 species planted in 38 arboreta across the European Atlantic area. Forests 9, 630 (2018).
Google Scholar
Manohan, B. et al. Use of functional traits to distinguish successional guilds of tree species for restoring forest ecosystems. Forests 14, 1075 (2023).
Google Scholar
Paquette, A. et al. A million and more trees for science. Nat. Ecol. Evol. 2, 763–766 (2018).
Google Scholar
Verheyen, K. et al. Contributions of a global network of tree diversity experiments to sustainable forest plantations. Ambio 45, 29–41 (2016).
Google Scholar
Augusto, L. & Boča, A. Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon. Nat. Commun. 13, 1097 (2022).
Google Scholar
Falster, D. S., Duursma, R. A. & FitzJohn, R. G. How functional traits influence plant growth and shade tolerance across the life cycle. Proc. Natl Acad. Sci. USA 115, E6789–E6798 (2018).
Google Scholar
Oktavia, D., Park, J. W. & Jin, G. Life stages and habitat types alter the relationships of tree growth with leaf traits and soils in an old-growth temperate forest. Flora 293, 152104 (2022).
Google Scholar
Chen, G., Hobbie, S. E., Reich, P. B., Yang, Y. & Robinson, D. Allometry of fine roots in forest ecosystems. Ecol. Lett. 22, 322–331 (2019).
Google Scholar
Enquist, B. J., Brown, J. H. & West, G. B. Allometric scaling of plant energetics and population density. Nature 395, 163–165 (1999).
Google Scholar
Mokany, K., Raison, R. J. & Prokushkin, A. S. Critical analysis of root: shoot ratios in terrestrial biomes. Glob. Change Biol. 12, 84–96 (2006).
Google Scholar
Ma, H. et al. The global distribution and environmental drivers of aboveground versus belowground plant biomass. Nat. Ecol. Evol. 5, 1110–1122 (2021).
Google Scholar
Niklas, K. J. & Spatz, H.-C. Growth and hydraulic (not mechanical) constraints govern the scaling of tree height and mass. Proc. Natl Acad. Sci. USA 101, 15661–15663 (2004).
Google Scholar
Chiba, Y. Architectural analysis of relationship between biomass and basal area based on pipe model theory. Ecol. Modell. 108, 219–225 (1998).
Google Scholar
Diaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).
Google Scholar
Kunstler, G. et al. Plant functional traits have globally consistent effects on competition. Nature 529, 204–209 (2016).
Google Scholar
Wright, I. J. et al. Assessing the generality of global leaf trait relationships. N. Phytol. 166, 485–496 (2005).
Google Scholar
Gomarasca, U. et al. Leaf-level coordination principles propagate to the ecosystem scale. Nat. Commun. 14, 3948 (2023).
Google Scholar
Poorter, H., Remkes, C. & Lambers, H. Carbon and nitrogen economy of 24 wild species differing in relative growth rate. Plant Physiol. 94, 621–627 (1990).
Google Scholar
Reich, P. B., Tjoelker, M., Walters, M., Vanderklein, D. & Buschena, C. Close association of RGR, leaf and root morphology, seed mass and shade tolerance in seedlings of nine boreal tree species grown in high and low light. Funct. Ecol. 12, 327–338 (1998).
Google Scholar
Doraisami, M. et al. A global database of woody tissue carbon concentrations. Sci. Data 9, 284 (2022).
Google Scholar
Garnier, E., Shipley, B., Roumet, C. & Laurent, G. A standardized protocol for the determination of specific leaf area and leaf dry matter content. Funct. Ecol. 15, 688–695 (2001).
Google Scholar
Perez-Harguindeguy, N. et al. New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 61, 167–234 (2013).
Google Scholar
Bruelheide, H. et al. Global trait-environment relationships of plant communities. Nat. Ecol. Evol. 2, 1906–1917 (2018).
Google Scholar
Caminha-Paiva, D., Negreiros, D., Barbosa, M. & Fernandes, G. W. Functional trait coordination in the ancient and nutrient-impoverished campo rupestre: soil properties drive stem, leaf and architectural traits. Biol. J. Linn. Soc. 133, 531–545 (2021).
Google Scholar
Eviner, V. T. & Chapin, F. S. III Functional matrix: a conceptual framework for predicting multiple plant effects on ecosystem processes. Ann. Rev. Ecol. Evol. Syst. 34, 455–485 (2003).
Google Scholar
Flores-Moreno, H. et al. Robustness of trait connections across environmental gradients and growth forms. Glob. Ecol. Biogeogr. 28, 1806–1826 (2019).
Google Scholar
Osnas, J. L. D., Lichstein, J. W., Reich, P. B. & Pacala, S. W. Global leaf trait relationships: mass, area, and the leaf economics spectrum. Science 340, 741–744 (2013).
Google Scholar
Reich, P. B. et al. The evolution of plant functional variation: traits, spectra, and strategies. Int. J. Plant Sci. 164, S143–S164 (2003).
Google Scholar
de la Riva, E. G. et al. Root traits across environmental gradients in Mediterranean woody communities: are they aligned along the root economics spectrum? Plant Soil 424, 35–48 (2018).
Google Scholar
Vet, R. et al. A global assessment of precipitation chemistry and deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus. Atmos. Environ. 93, 3–100 (2014).
Google Scholar
Hengl, T. et al. SoilGrids250m: global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).
Google Scholar
Shangguan, W., Dai, Y., Duan, Q., Liu, B. & Yuan, H. A global soil data set for earth system modeling. J. Adv. Model. Earth Syst. 6, 249–263 (2014).
Google Scholar
Lu, J. et al. Remarkable effects of microbial factors on soil phosphorus bioavailability: a country-scale study. Glob. Change Biol. 28, 4459–4471 (2022).
Google Scholar
Toloşi, L. & Lengauer, T. Classification with correlated features: unreliability of feature ranking and solutions. Bioinformatics 27, 1986–1994 (2011).
Google Scholar
Brienen, R. J. et al. Forest carbon sink neutralized by pervasive growth-lifespan trade-offs. Nat. Commun. 11, 4241 (2020).
Google Scholar
Charru, M., Seynave, I., Hervé, J. C., Bertrand, R. & Bontemps, J. D. Recent growth changes in Western European forests are driven by climate warming and structured across tree species climatic habitats. Ann. For. Sci. 74, 33 (2017).
Google Scholar
Harvey, J. E. et al. Tree growth influenced by warming winter climate and summer moisture availability in northern temperate forests. Glob. Change Biol. 26, 2505–2518 (2020).
Google Scholar
Ols, C., Hervé, J.-C. & Bontemps, J.-D. Recent growth trends of conifers across Western Europe are controlled by thermal and water constraints and favored by forest heterogeneity. Sci. Total Environ. 742, 140453 (2020).
Google Scholar
Lloyd, J. & Taylor, J. A. On the temperature-dependence of soil respiration. Funct. Ecol. 8, 315–323 (1994).
Google Scholar
Adair, E. C. et al. Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates. Glob. Change Biol. 14, 2636–2660 (2008).
Google Scholar
Chen, S. et al. National estimation of soil organic carbon storage potential for arable soils: a data-driven approach coupled with carbon-landscape zones. Sci. Total Environ. 666, 355–367 (2019).
Google Scholar
Kottek, M., Grieser, J., Beck, C., Rudolf, B. & Rubel, F. World map of the Koppen-Geiger climate classification updated. Meteorol. Z. 15, 259–263 (2006).
Google Scholar
Chini, L. et al. LUH2-GCB2019: Land-Use Harmonization 2 Update For The Global Carbon Budget, 850-2019 (ORNL DAAC, 2021).
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Google Scholar
Hebbali, A. Olsrr: tools for building OLS regression models (2020); cran.r-project.org/package=olsrr.
Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).
Google Scholar
Díaz-Uriarte, R. & Alvarez de Andrés, S. Gene selection and classification of microarray data using random forest. BMC Bioinform. 7, 3 (2006).
Google Scholar
Shao, Z., Zhang, L. & Wang, L. Stacked sparse autoencoder modeling using the synergy of airborne LiDAR and satellite optical and SAR data to map forest above-ground biomass. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 10, 5569–5582 (2017).
Google Scholar
Trefflich, I., Dietrich, S., Braune, A., Abraham, K. & Weikert, C. Short-and branched-chain fatty acids as fecal markers for microbiota activity in vegans and omnivores. Nutrients 13, 1808 (2021).
Google Scholar
Babst, F. et al. Site- and species-specific responses of forest growth to climate across the European continent. Glob. Ecol. Biogeogr. 22, 706–717 (2013).
Google Scholar
Poorter, L. et al. Biodiversity and climate determine the functioning of Neotropical forests. Glob. Ecol. Biogeogr. 26, 1423–1434 (2017).
Google Scholar
Soong, J. L. et al. Soil properties explain tree growth and mortality, but not biomass, across phosphorus-depleted tropical forests. Sci. Rep. 10, 2302 (2020).
Google Scholar
van der Sande, M. T. et al. Soil fertility and species traits, but not diversity, drive productivity and biomass stocks in a Guyanese tropical rainforest. Funct. Ecol. 32, 461–474 (2018).
Google Scholar
Noy-Meir, I., Walker, D. & Williams, W. Data transformations in ecological ordination: II. On the meaning of data standardization. J. Ecol. 63, 779–800 (1975).
Razali, N. M., Wah, Y. B. & others. Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. J. Stat. Model. Anal. 2, 21–33 (2011).
Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).
Google Scholar
Malyjurek, Z., de Beer, D., Joubert, E. & Walczak, B. Working with log-ratios. Anal. Chim. Acta 1059, 16–27 (2019).
Google Scholar
Voelkl, B., Würbel, H., Krzywinski, M. & Altman, N. The standardization fallacy. Nat. Methods 18, 5–7 (2021).
Google Scholar
Reich, P. B., Walters, M. B. & Ellsworth, D. S. From tropics to tundra: global convergence in plant functioning. Proc. Natl Acad. Sci. USA 94, 13730–13734 (1997).
Google Scholar
Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).
Google Scholar
Ellsworth, D. S. et al. Convergence in phosphorus constraints to photosynthesis in forests around the world. Nat. Commun. 13, 5005 (2022).
Google Scholar
Grime, J. P. & Hunt, R. Relative growth-rate: its range and adaptive significance in a local flora. J. Ecol. 63, 393–422 (1975).
Google Scholar
Thomas, F. M. & Vesk, P. A. Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits. PLoS ONE 12, e0176959 (2017).
Google Scholar
Bujang, M. A. & Baharum, N. Sample size guideline for correlation analysis. World J. Soc. Sci. Res. 3, 37–46 (2016).
Google Scholar
Altman, N. & Krzywinski, M. Points of significance: association, correlation and causation. Nat. Methods 12, 899–900 (2015).
Google Scholar
Altman, N. & Krzywinski, M. Analyzing outliers: influential or nuisance? Nat. Methods 13, 281–283 (2016).
Google Scholar
West, P. A review of the growth behaviour of stands and trees in even-aged, monospecific forest. Ann. For. Sci. 81, 34 (2024).
Google Scholar
Mayer, D. G. & Butler, D. G. Statistical validation. Ecol. Model. 68, 21–32 (1993).
Google Scholar
Isaac, M. E. et al. Intraspecific trait variation and coordination: root and leaf economics spectra in coffee across environmental gradients. Front. Plant Sci. 8, 1196 (2017).
Google Scholar
Kazakou, E. et al. Are trait-based species rankings consistent across data sets and spatial scales? J. Veg. Sci. 25, 235–247 (2014).
Google Scholar
Treurnicht, M. et al. Functional traits explain the Hutchinsonian niches of plant species. Glob. Ecol. Biogeogr. 29, 534–545 (2020).
Google Scholar
Ma, Z. et al. Evolutionary history resolves global organization of root functional traits. Nature 555, 94–97 (2018).
Google Scholar
Pietsch, K. A. et al. Global relationship of wood and leaf litter decomposability: the role of functional traits within and across plant organs. Glob. Ecol. Biogeogr. 23, 1046–1057 (2014).
Google Scholar
Joswig, J. S. et al. Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation. Nat. Ecol. Evol. 6, 36–50 (2022).
Google Scholar
Fajardo, A. Insights into intraspecific wood density variation and its relationship to growth, height and elevation in a treeline species. Plant Biol. 20, 456–464 (2018).
Google Scholar
Li, T. et al. Intraspecific functional trait variability across different spatial scales: a case study of two dominant trees in Korean pine broadleaved forest. Plant Ecol. 219, 875–886 (2018).
Google Scholar
Pompa-García, M. et al. Tree-ring wood density reveals differentiated hydroclimatic interactions in species along a bioclimatic gradient. Dendrochronologia 85, 126208 (2024).
Google Scholar
Ji, M., Jin, G. & Liu, Z. Effects of ontogenetic stage and leaf age on leaf functional traits and the relationships between traits in Pinus koraiensis. J. For. Res. 32, 2459–2471 (2021).
Google Scholar
Kattge, J. et al. TRY plant trait database—enhanced coverage and open access. Glob. Change Biol. 26, 119–188 (2020).
Google Scholar
Boehnke, M. & Bruelheide, H. How do evergreen and deciduous species respond to shade? Tolerance and plasticity of subtropical tree and shrub species of South-East China. Environ. Exp. Bot. 87, 179–190 (2013).
Google Scholar
Cornelissen, J. A triangular relationship between leaf size and seed size among woody species: allometry, ontogeny, ecology and taxonomy. Oecologia 118, 248–255 (1999).
Google Scholar
Unterholzner, L., Stolz, J., van der Maaten-Theunissen, M., Liepe, K. & van der Maaten, E. Site conditions rather than provenance drive tree growth, climate sensitivity and drought responses in European beech in Germany. For. Ecol. Manage. 572, 122308 (2024).
Google Scholar
Ovenden, T. S., Jinks, R. L., Mason, W. L., Kerr, G. & Reynolds, C. A comparison of the early growth and survival of lesser-known tree species for climate change adaptation in Britain. For. Ecol. Manage. 572, 122340 (2024).
Google Scholar
Albert, C. H., Grassein, F., Schurr, F. M., Vieilledent, G. & Violle, C. When and how should intraspecific variability be considered in trait-based plant ecology? Perspect. Plant Ecol. Evol. Syst. 13, 217–225 (2011).
Google Scholar
Wooliver, R. C. et al. Phylogeny is a powerful tool for predicting plant biomass responses to nitrogen enrichment. Ecology 98, 2120–2132 (2017).
Google Scholar
Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89–92 (2014).
Google Scholar
Lu, Y., Ran, J.-H., Guo, D.-M., Yang, Z.-Y. & Wang, X.-Q. Phylogeny and divergence times of gymnosperms inferred from single-copy nuclear genes. PLoS ONE 9, e107679 (2014).
Google Scholar
Magallón, S., Gómez-Acevedo, S., Sánchez-Reyes, L. L. & Hernández-Hernández, T. A metacalibrated time-tree documents the early rise of flowering plant phylogenetic diversity. N. Phytol. 207, 437–453 (2015).
Google Scholar
Saladin, B. et al. Fossils matter: improved estimates of divergence times in Pinus reveal older diversification. BMC Evol. Biol. 17, 95 (2017).
Google Scholar
Hipp, A. L. et al. Genomic landscape of the global oak phylogeny. N. Phytol. 226, 1198–1212 (2020).
Google Scholar
Jiang, L. et al. Phylogeny and biogeography of Fagus (Fagaceae) based on 28 nuclear single/low-copy loci. J. Syst. Evol. 60, 759–772 (2022).
Google Scholar
Liese, R., Alings, K. & Meier, I. C. Root branching is a leading root trait of the plant economics spectrum in temperate trees. Front. Plant Sci. 8, 315 (2017).
Google Scholar
Cadotte, M. W., Davies, T. J. & Peres-Neto, P. R. Why phylogenies do not always predict ecological differences. Ecol. Monogr. 87, 535–551 (2017).
Google Scholar
Augusto, L., Davies, T. J., Delzon, S. & de Schrijver, A. The enigma of the rise of angiosperms: can we untie the knot? Ecol. Lett. 17, 1326–1338 (2014).
Google Scholar
Augusto, L. et al. Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests. Biol. Rev. 90, 444–466 (2015).
Google Scholar
Bond, W. The tortoise and the hare: ecology of angiosperm dominance and gymnosperm persistence. Biol. J. Linn. Soc. 36, 227–249 (1989).
Google Scholar
Brodribb, T. J. & Feild, T. S. Leaf hydraulic evolution led a surge in leaf photosynthetic capacity during early angiosperm diversification. Ecol. Lett. 13, 175–183 (2010).
Google Scholar
Brodribb, T. J., Pittermann, J. & Coomes, D. A. Elegance versus speed: examining the competition between conifer and angiosperm trees. Int. J. Plant Sci. 173, 673–694 (2012).
Google Scholar
Martin, A. R., Doraisami, M. & Thomas, S. C. Global patterns in wood carbon concentration across the world’s trees and forests. Nat. Geosci. 11, 915–920 (2018).
Google Scholar
Reich, P. B. et al. Evidence of a general 2/3-power law of scaling leaf nitrogen to phosphorus among major plant groups and biomes. Proc. R. Soc. B 277, 877–883 (2010).
Google Scholar
Zheng, J. et al. A trait-based root acquisition-defence-decomposition framework in angiosperm tree species. Nat. Commun. 15, 5311 (2024).
Google Scholar