Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).
Google Scholar
Huang, Y. et al. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362, 80–83 (2018).
Google Scholar
Urgoiti, J. et al. No complementarity no gain—net diversity effects on tree productivity occur once complementarity emerges during early stand development. Ecol. Lett. 25, 851–862 (2022).
Google Scholar
Feng, Y. et al. Multispecies forest plantations outyield monocultures across a broad range of conditions. Science 376, 865–868 (2022).
Google Scholar
Reich, P. B. et al. Impacts of biodiversity loss escalate through time as redundancy fades. Science 336, 589–592 (2012).
Google Scholar
Wagg, C. et al. Biodiversity–stability relationships strengthen over time in a long-term grassland experiment. Nat. Commun. 13, 7752 (2022).
Google Scholar
Tilman, D., Isbell, F. & Cowles, J. M. Biodiversity and ecosystem functioning. Annu. Rev. Ecol. Evol. Syst. 45, 471–493 (2014).
Google Scholar
Barry, K. E. et al. The future of complementarity: disentangling causes from consequences. Trends Ecol. Evol. 34, 167–180 (2019).
Google Scholar
Cardinale, B. J. et al. The functional role of producer diversity in ecosystems. Am. J. Bot. 98, 572–592 (2011).
Google Scholar
Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).
Google Scholar
Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).
Google Scholar
Cadotte, M. W. Functional traits explain ecosystem function through opposing mechanisms. Ecol. Lett. 20, 989–996 (2017).
Google Scholar
Bongers, F. J. et al. Functional diversity effects on productivity increase with age in a forest biodiversity experiment. Nat. Ecol. Evol. 5, 1594–1603 (2021).
Google Scholar
Veryard, R. et al. Positive effects of tree diversity on tropical forest restoration in a field-scale experiment. Sci. Adv. 9, eadf0938 (2023).
Google Scholar
Dawson, J. O. in Nitrogen-fixing Actinorhizal Symbioses (eds Pawlowski, K. & Newton, W. E.) 199–234 (Springer, 2008).
Wright, A. J., Wardle, D. A., Callaway, R. & Gaxiola, A. The overlooked role of facilitation in biodiversity experiments. Trends Ecol. Evol. 32, 383–390 (2017).
Google Scholar
Ackerly, D. Conservatism and diversification of plant functional traits: evolutionary rates versus phylogenetic signal. Proc. Natl Acad. Sci. USA 106, 19699–19706 (2009).
Google Scholar
Grossman, J. J., Cavender-Bares, J., Reich, P. B., Montgomery, R. A. & Hobbie, S. E. Neighborhood diversity simultaneously increased and decreased susceptibility to contrasting herbivores in an early stage forest diversity experiment. J. Ecol. 107, 1492–1505 (2019).
Google Scholar
Jactel, H., Moreira, X. & Castagneyrol, B. Tree diversity and forest resistance to insect pests: patterns, mechanisms, and prospects. Annu. Rev. Entomol. 66, 277–296 (2021).
Google Scholar
Tobner, C. M. et al. Functional identity is the main driver of diversity effects in young tree communities. Ecol. Lett. 19, 638–647 (2016).
Google Scholar
Wang, S. et al. Towards mechanistic integration of the causes and consequences of biodiversity. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2024.02.008 (2024).
Weiner, J. Asymmetric competition in plant populations. Trends Ecol. Evol. 5, 360–364 (1990).
Google Scholar
Godoy, O., Gómez-Aparicio, L., Matías, L., Pérez-Ramos, I. M. & Allan, E. An excess of niche differences maximizes ecosystem functioning. Nat. Commun. 11, 4180 (2020).
Google Scholar
Roscher, C. et al. Using plant functional traits to explain diversity–productivity relationships. PLoS ONE 7, e36760 (2012).
Google Scholar
Hisano, M. & Chen, H. Y. H. Spatial variation in climate modifies effects of functional diversity on biomass dynamics in natural forests across Canada. Glob. Ecol. Biogeogr. 29, 682–695 (2020).
Google Scholar
Ruiz-Benito, P. et al. Diversity increases carbon storage and tree productivity in Spanish forests. Global Ecol. Biogeogr. 23, 311–322 (2014).
Google Scholar
Luo, Y.-H. et al. Greater than the sum of the parts: how the species composition in different forest strata influence ecosystem function. Ecol. Lett. 22, 1449–1461 (2019).
Google Scholar
Kahmen, A., Renker, C., Unsicker, S. B. & Buchmann, N. Niche complementarity for nitrogen: an explanation for the biodiversity and ecosystem functioning relationship? Ecology 87, 1244–1255 (2006).
Google Scholar
Ewel, J. J., Celis, G. & Schreeg, L. Steeply increasing growth differential between mixture and monocultures of tropical trees. Biotropica 47, 162–171 (2015).
Google Scholar
Guerrero-Ramírez, N. R. et al. Diversity-dependent temporal divergence of ecosystem functioning in experimental ecosystems. Nat. Ecol. Evol. 1, 1639–1642 (2017).
Google Scholar
Cardinale, B. J. et al. Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl Acad. Sci. USA 104, 18123–18128 (2007).
Google Scholar
Maestre, F. T., Callaway, R. M., Valladares, F. & Lortie, C. J. Refining the stress-gradient hypothesis for competition and facilitation in plant communities. J. Ecol. 97, 199–205 (2009).
Google Scholar
Jucker, T. et al. Climate modulates the effects of tree diversity on forest productivity. J. Ecol. 104, 388–398 (2016).
Google Scholar
Kattge, J. et al. TRY plant trait database—enhanced coverage and open access. Glob. Change Biol. 26, 119–188 (2020).
Google Scholar
Pyron, R. A., Costa, G. C., Patten, M. A. & Burbrink, F. T. Phylogenetic niche conservatism and the evolutionary basis of ecological speciation. Biol. Rev. 90, 1248–1262 (2015).
Google Scholar
Tucker, C. M., Davies, T. J., Cadotte, M. W. & Pearse, W. D. On the relationship between phylogenetic diversity and trait diversity. Ecology 99, 1473–1479 (2018).
Google Scholar
Parker, I. M. et al. Phylogenetic structure and host abundance drive disease pressure in communities. Nature 520, 542–544 (2015).
Google Scholar
Wright, A. J., Barry, K. E., Lortie, C. J. & Callaway, R. M. Biodiversity and ecosystem functioning: have our experiments and indices been underestimating the role of facilitation? J. Ecol. 109, 1962–1968 (2021).
Google Scholar
Cong, W.-F. et al. Plant species richness promotes soil carbon and nitrogen stocks in grasslands without legumes. J. Ecol. 102, 1163–1170 (2014).
Google Scholar
Furey, G. N. & Tilman, D. Plant chemical traits define functional and phylogenetic axes of plant biodiversity. Ecol. Lett. 26, 1394–1406 (2023).
Google Scholar
Xiao, W., Chen, C., Chen, X., Huang, Z. & Chen, H. Y. H. Functional and phylogenetic diversity promote litter decomposition across terrestrial ecosystems. Glob. Ecol. Biogeogr. 29, 2261–2272 (2020).
Google Scholar
Zhang, Y. & Chen, H. Y. H. Individual size inequality links forest diversity and above-ground biomass. J. Ecol. 103, 1245–1252 (2015).
Google Scholar
Williams, L. J., Paquette, A., Cavender-Bares, J., Messier, C. & Reich, P. B. Spatial complementarity in tree crowns explains overyielding in species mixtures. Nat. Ecol. Evol. 1, 0063 (2017).
Google Scholar
Finegan, B. et al. Does functional trait diversity predict above-ground biomass and productivity of tropical forests? Testing three alternative hypotheses. J. Ecol. 103, 191–201 (2015).
Google Scholar
van Moorsel, S. J. et al. Evidence for rapid evolution in a grassland biodiversity experiment. Mol. Ecol. 28, 4097–4117 (2019).
Google Scholar
Engelhardt, K. A. M. & Ritchie, M. E. The effect of aquatic plant species richness on wetland ecosystem processes. Ecology 83, 2911–2924 (2002).
Google Scholar
Dee, L. E. et al. Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference. Nat. Commun. 14, 2607 (2023).
Google Scholar
Duffy, J. E., Godwin, C. M. & Cardinale, B. J. Biodiversity effects in the wild are common and as strong as key drivers of productivity. Nature 549, 261–264 (2017).
Google Scholar
Fagan, M. E. et al. The expansion of tree plantations across tropical biomes. Nat. Sustain. 5, 681–688 (2022).
Google Scholar
O’Dea, R. E. et al. Preferred reporting items for systematic reviews and meta-analyses in ecology and evolutionary biology: a PRISMA extension. Biol. Rev. 96, 1695–1722 (2021).
Google Scholar
Page, M. J. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Br. Med. J. 372, n71 (2021).
Google Scholar
de Wit, C. T. On competition. Verslagen Landbouwkundige Onderzoekingen 66, 1–82 (1960).
Google Scholar
Chen, C., Xiao, W. & Chen, H. Y. H. Data and R codes for “Meta-analysis reveals global variations in plant diversity effects on productivity”. Figshare https://doi.org/10.6084/m9.figshare.27316062 (2024).
Keeling, H. C. & Phillips, O. L. The global relationship between forest productivity and biomass. Glob. Ecol. Biogeogr. 16, 618–631 (2007).
Google Scholar
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
Google Scholar
taxize: Taxonomic information from around the web. R package version 0.9.100 https://CRAN.R-project.org/package=taxize (2022).
Jin, Y. & Qian, H. V.PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).
Google Scholar
Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).
Google Scholar
Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61, 1–10 (1992).
Google Scholar
Su, G. et al. Human impacts on global freshwater fish biodiversity. Science 371, 835–838 (2021).
Google Scholar
Cox, N. et al. A global reptile assessment highlights shared conservation needs of tetrapods. Nature 605, 285–290 (2022).
Google Scholar
Botta-Dukát, Z. Rao’s quadratic entropy as a measure of functional diversity based on multiple traits. J. Veg. Sci. 16, 533–540 (2005).
Google Scholar
Rao, C. R. Diversity and dissimilarity coefficients: a unified approach. Theoret. Pop. Biol. 21, 24–43 (1982).
Google Scholar
FD: Measuring functional diversity (FD) from multiple traits, and other tools for functional ecology. R package version 1.0-12.3 https://CRAN.R-project.org/package=FD (2023).
Fanin, N. et al. Consistent effects of biodiversity loss on multifunctionality across contrasting ecosystems. Nat. Ecol. Evol. 2, 269–278 (2018).
Google Scholar
Viechtbauer, W. & Cheung, M. W.-L. Outlier and influence diagnostics for meta-analysis. Res. Synth. Methods 1, 112–125 (2010).
Google Scholar
Rousseeuw, P. J. & Leroy, A. M. in Robust Regression and Outlier Detection (eds Rousseeuw, P. J. & Leroy, A. M.) 216–247 (Wiley, 1987).
Gurevitch, J., Koricheva, J., Nakagawa, S. & Stewart, G. Meta-analysis and the science of research synthesis. Nature 555, 175 (2018).
Google Scholar
Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 36, 1–48 (2010).
Google Scholar
Nakagawa, S., Yang, Y., Macartney, E. L., Spake, R. & Lagisz, M. Quantitative evidence synthesis: a practical guide on meta-analysis, meta-regression, and publication bias tests for environmental sciences. Environ. Evid. 12, 8 (2023).
Google Scholar
Pittelkow, C. M. et al. Productivity limits and potentials of the principles of conservation agriculture. Nature 517, 365–368 (2015).
Google Scholar
Kröel-Dulay, G. et al. Field experiments underestimate aboveground biomass response to drought. Nat. Ecol. Evol. 6, 540–545 (2022).
Google Scholar
Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).
Google Scholar
Nakagawa, S. et al. A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations. Ecol. Lett. 26, 232–244 (2023).
Google Scholar
Deeks, J. J., Higgins, J. P. & Altman, D. G. in Cochrane Handbook for Systematic Reviews of Interventions (eds Higgins, J.P.T. et al.) 241–284 (Wiley, 2019).
Sterne, J. A. & Egger, M. Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments (Wiley, 2005).
Koricheva, J., Gurevitch, J. & Mengersen, K. Handbook of Meta-analysis in Ecology and Evolution (Princeton Univ. Press, 2013).
lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-35.5 https://CRAN.R-project.org/package=lme4 (2024).
Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. https://doi.org/10.18637/jss.v082.i13 (2017).
multcomp: Simultaneous inference in general parametric models. R package version 1.4-26 https://CRAN.R-project.org/package=multcomp (2024).
ggplot2: Create elegant data visualisations using the grammar of graphics. R package version 3.5.1 https://CRAN.R-project.org/package=ggplot2 (2024).
cowplot: Streamlined plot theme and plot annotations for ‘ggplot2’. R package version 1.1.3 https://CRAN.R-project.org/package=cowplot (2024).
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2023).
