Article | Published:

A plant biodiversity effect resolved to a single chromosomal region


Despite extensive evidence that biodiversity promotes plant community productivity, progress towards understanding the mechanistic basis of this effect remains slow, impeding the development of predictive ecological theory and agricultural applications. Here, we analysed non-additive interactions between genetically divergent Arabidopsis accessions in experimental plant communities. By combining methods from ecology and quantitative genetics, we identify a major effect locus at which allelic differences between individuals increase the above-ground productivity of communities. In experiments with near-isogenic lines, we show that this diversity effect acts independently of other genomic regions and can be resolved to a single region representing less than 0.3% of the genome. Using plant–soil feedback experiments, we also demonstrate that allelic diversity causes genotype-specific soil legacy responses in a consecutive growing period, even after the original community has disappeared. Our work thus suggests that positive diversity effects can be linked to single Mendelian factors, and that a range of complex community properties can have a simple cause. This may pave the way to novel breeding strategies, focusing on phenotypic properties that manifest themselves beyond isolated individuals; that is, at a higher level of biological organization.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Data availability

The datasets described in this paper and a functional annotation of the 86 genes within the fine-mapped diversity QTL are available through the Zenodo data repository ( Sequencing data are deposited in the NCBI Sequence Read Archive (accession SRP149077). Analysis scripts are available from the authors on request.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


  1. 1.

    Cardinale, B. J. et al. The functional role of producer diversity in ecosystems. Am. J. Bot. 98, 572–592 (2011).

  2. 2.

    O’Connor, M. I. et al. A general biodiversity–function relationship is mediated by trophic level. Oikos 126, 18–31 (2017).

  3. 3.

    Cardinale, B. J., Palmer, M. A. & Collins, S. L. Species diversity enhances ecosystem functioning through interspecific facilitation. Nature 415, 426–429 (2002).

  4. 4.

    Schnitzer, S. A. et al. Soil microbes drive the classic plant diversity–productivity pattern. Ecology 92, 296–303 (2011).

  5. 5.

    Maron, J. L., Marler, M., Klironomos, J. N. & Cleveland, C. C. Soil fungal pathogens and the relationship between plant diversity and productivity. Ecol. Lett. 14, 36–41 (2011).

  6. 6.

    Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).

  7. 7.

    Ratcliffe, S. et al. Biodiversity and ecosystem functioning relations in European forests depend on environmental context. Ecol. Lett. 20, 1414–1426 (2017).

  8. 8.

    Tylianakis, J. M. et al. Resource heterogeneity moderates the biodiversity–function relationship in real world ecosystems. PLoS Biol. 6, 947–956 (2008).

  9. 9.

    Flynn, D. F. B., Mirotchnick, N., Jain, M., Palmer, M. I. & Naeem, S. Functional and phylogenetic diversity as predictors of biodiversity—ecosystem–function relationships. Ecology 92, 1573–1581 (2011).

  10. 10.

    Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).

  11. 11.

    Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2015).

  12. 12.

    Cadotte, M. W., Cardinale, B. J. & Oakley, T. H. Evolutionary history and the effect of biodiversity on plant productivity. Proc. Natl Acad. Sci. USA 105, 17012–17017 (2008).

  13. 13.

    Crutsinger, G. M. et al. Plant genotypic diversity predicts community structure and governs an ecosystem process. Science 313, 966–968 (2006).

  14. 14.

    Wang, S. & Loreau, M. Ecosystem stability in space: α, β and γ variability. Ecol. Lett. 17, 891–901 (2014).

  15. 15.

    Oehri, J., Schmid, B., Schaepman-Strub, G. & Niklaus, P. A. Biodiversity promotes primary productivity and growing season lengthening at the landscape scale. Proc. Natl Acad. Sci. USA 38, 10160–10165 (2017).

  16. 16.

    Siefert, A. et al. A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. Ecol. Lett. 18, 1406–1419 (2015).

  17. 17.

    Crutsinger, G. M., Souza, L. & Sanders, N. J. Intraspecific diversity and dominant genotypes resist plant invasions. Ecol. Lett. 11, 16–23 (2008).

  18. 18.

    Prieto, I. et al. Complementary effects of species and genetic diversity on productivity and stability of sown grasslands. Nat. Plants 1, 15033 (2015).

  19. 19.

    Mendel, G. Versuche über Pflanzenhybriden. Verhandlungen des Naturforschenden Vereines Brünn IV, 3–47 (1865).

  20. 20.

    Loudet, O., Chaillou, S., Camilleri, C., Bouchez, D. & Daniel-Vedele, F. Bay-0 × Shahdara recombinant inbred line population: a powerful tool for the genetic dissection of complex traits in Arabidopsis. Theor. Appl. Genet. 104, 1173–1184 (2002).

  21. 21.

    Griffing, B. Concept of general and specific combining ability in relation to diallel crossing systems. Aust. J. Biol. Sci. 9, 463–493 (1956).

  22. 22.

    Griffing, B. Genetic analysis of plant mixtures. Genetics 122, 943–956 (1989).

  23. 23.

    Zak, D. R., Holmes, W. E., White, D. C., Peacock, A. D. & Tilman, D. Plant diversity, soil microbial communities, and ecosystem function: are there any links? Ecology 84, 2042–2050 (2003).

  24. 24.

    Bukowski, A. R. & Petermann, J. S. Intraspecific plant–soil feedback and intraspecific overyielding in Arabidopsis thaliana. Ecol. Evol. 4, 2533–2545 (2014).

  25. 25.

    Meyer, S. T. et al. Effects of biodiversity strengthen over time as ecosystem functioning declines at low and increases at high biodiversity. Ecosphere 7, e01619 (2016).

  26. 26.

    Clements, F. E. & Goldsmith, G. W. The Phytometer Method in Ecology (Carnegie Institution of Washington, Washington DC, 1924).

  27. 27.

    Dawkins, R. The Extended Phenotype (Oxford Univ. Press, Oxford, 1982).

  28. 28.

    MacKay, T. F. C., Stone, E. A. & Ayroles, J. F. The genetics of quantitative traits: challenges and prospects. Nat. Rev. Genet. 10, 565–577 (2009).

  29. 29.

    Boyle, E. A., Li, Y. I. & Pritchard, J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017).

  30. 30.

    Wilfert, L. & Schmid-Hempel, P. The genetic architecture of susceptibility to parasites. BMC Evol. Biol. 8, 187 (2008).

  31. 31.

    Wittwer, R. A., Dorn, B., Jossi, W. & Van Der Heijden, M. G. A. Cover crops support ecological intensification of arable cropping systems. Sci. Rep. 7, 41911 (2017).

  32. 32.

    Finckh, M. R. et al. Cereal variety and species mixtures in practice, with emphasis on disease resistance. Agronomie 20, 813–837 (2000).

  33. 33.

    Zhu, Y. et al. Genetic diversity and disease control in rice. Nature 406, 718–722 (2000).

  34. 34.

    Litrico, I. & Violle, C. Diversity in plant breeding: a new conceptual framework. Trends Plant Sci. 20, 604–613 (2015).

  35. 35.

    Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).

  36. 36.

    Edgerton, M. D. Increasing crop productivity to meet global needs for feed, food, and fuel. Plant Physiol. 149, 7–13 (2009).

  37. 37.

    Lippman, Z. B. & Zamir, D. Heterosis: revisiting the magic. Trends Genet. 23, 60–66 (2007).

  38. 38.

    Weiner, J., Du, Y. L., Zhang, C., Qin, X. L. & Li, F. M. Evolutionary agroecology: individual fitness and population yield in wheat (Triticum aestivum). Ecology 98, 2261–2266 (2017).

  39. 39.

    Easlon, H. M. & Bloom, A. J. Easy leaf area: automated digital image analysis for rapid and accurate measurement of leaf area. Appl. Plant Sci. 2, apps.1400033 (2014).

  40. 40.

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

  41. 41.

    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

  42. 42.

    R Core Development Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2017).

  43. 43.

    Xie, W. et al. Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing. Proc. Natl Acad. Sci. USA 107, 10578–10583 (2010).

Download references


We thank B. Schmid and U. Grossniklaus for helpful discussions and sharing infrastructure. We thank J. Bacompte and J. Weiner for helpful comments on the manuscript. We further acknowledge M. Philipp for technical support, E. De Luca and N. Ponta for help with plant measurements, and M. Furler and D. Topalovic for technical greenhouse support. This work was supported by an Ambizione Fellowship (PZ00P3_148223) of the Swiss National Science Foundation (to S.E.W.). P.A.N. acknowledges support from the University of Zurich Priority Program ‘Global Change and Biodiversity’. S.E.W. was also financially supported by funds from the University of Zurich and European Research Council (to U. Grossniklaus).

Author information

S.E.W. conceptualized and designed the research (with input from P.A.N.), and performed the experiments. Both authors performed the analyses and wrote the manuscript. Both authors revised and approved the final version of the manuscript.

Competing interests

The authors declare no competing interests.

Correspondence to Samuel E. Wuest.

Supplementary information

Supplementary Information

Supplementary Tables 1–2, Supplementary Figures 1–6, Supplementary Discussion and Supplementary References

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Further reading

Fig. 1: Combining ecological concepts and genetic methods.
Fig. 2: Allelic diversity at a major effect locus increases community productivity.
Fig. 3: Resolving soil × allelic diversity interactions to a single Mendelian factor.
Fig. 4: Allelic diversity effects persist across a generation through their soil legacy.