Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Ecological networks reveal resilience of agro-ecosystems to changes in farming management


Sustainable management of ecosystems and growth in agricultural productivity is at the heart of the United Nations’ Sustainable Development Goals for 2030. New management regimes could revolutionize agricultural production, but require an evaluation of the risks and opportunities. Replacing existing conventional weed management with genetically modified, herbicide-tolerant (GMHT) crops, for example, might reduce herbicide applications and increase crop yields, but remains controversial owing to concerns about potential impacts on biodiversity. Until now, such new regimes have been assessed at the species or assemblage level, whereas higher-level ecological network effects remain largely unconsidered. Here, we conduct a large-scale network analysis of invertebrate communities across 502 UK farm sites to GMHT management in different crop types. We find that network-level properties were overwhelmingly shaped by crop type, whereas network structure and robustness were apparently unaltered by GMHT management. This suggests that taxon-specific effects reported previously did not escalate into higher-level systemic structural change in the wider agricultural ecosystem. Our study highlights current limitations of autecological assessments of effect in agriculture in which species interactions and potential compensatory effects are overlooked. We advocate adopting the more holistic system-level evaluations that we explore here, which complement existing assessments for meeting our future agricultural needs.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Variations in taxonomic composition.
Fig. 2: Core/periphery substructures in food webs.
Fig. 3: Food web properties varied significantly between crop types.

Data availability

The raw FSE data are free from intellectual property rights. The data can be requested by enquiry to the Environmental Information Data Centre of the Centre for Ecology and Hydrology ( Archived information about the FSEs are available from the National Archives of The Government of the United Kingdom (


  1. 1.

    Tilman, D. et al. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011).

    CAS  PubMed  Google Scholar 

  2. 2.

    Flohre, A. et al. Agricultural intensification and biodiversity partitioning in European landscapes comparing plants, carabids, and birds. Ecol. Appl. 21, 1772–1781 (2011).

    PubMed  Google Scholar 

  3. 3.

    Rockström, J. et al. A safe operating space for humanity. Nature 461, 472–475 (2009).

    PubMed  Google Scholar 

  4. 4.

    Geiger, F. et al. Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland. Basic Appl. Ecol. 11, 97–105 (2010).

    CAS  Google Scholar 

  5. 5.

    Butler, S. J. et al. Farmland biodiversity and the footprint of agriculture. Science 315, 381–384 (2007).

    CAS  PubMed  Google Scholar 

  6. 6.

    Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011).

    CAS  PubMed  Google Scholar 

  7. 7.

    Firbank, L. G. et al. Assessing the impacts of agricultural intensification on biodiversity: a British perspective. Phil. Trans. R. Soc. B 363, 777–787 (2008).

    PubMed  Google Scholar 

  8. 8.

    Brooks, D. R. et al. The implications of genetically modified herbicide-tolerant crops for uk farmland biodiversity : a summary of the results of the farm scale evaluations project. In Proc. Cultiv. Genet. Modif. Crop. Eval. Ecol. Eff. 29–52 (2007).

  9. 9.

    Phalan, B. et al. Minimising the harm to biodiversity of producing more food globally. Food Policy 36, S62–S71 (2011).

    Google Scholar 

  10. 10.

    Bohan, D. A. et al. Networking our way to better ecosystem service provision. Trends Ecol. Evol. 31, 105–115 (2016).

    Google Scholar 

  11. 11.

    Bohan, D. A. et al. Next-generation global biomonitoring: large-scale, automated reconstruction of ecological networks. Trends Ecol. Evol. 32, 477–487 (2017).

    PubMed  Google Scholar 

  12. 12.

    Thompson, R. M. et al. Food webs: reconciling the structure and function of biodiversity. Trends Ecol. Evol. 27, 689–697 (2012).

    PubMed  Google Scholar 

  13. 13.

    Hautier, Y. et al. Eutrophication weakens stabilizing effects of diversity in natural grasslands. Nature 508, 521–525 (2014).

    CAS  PubMed  Google Scholar 

  14. 14.

    Bohan, D. A. et al. Automated discovery of food webs from ecological data using logic-based machine learning. PLoS ONE 6, e29028 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Firbank, L. G. et al. An introduction to the farm-scale evaluations of genetically modified herbicide-tolerant crops. J. Appl. Ecol. 40, 2–16 (2003).

    Google Scholar 

  16. 16.

    Chamberlain, D. E. et al. Changes in the abundance of farmland birds in relation to the timing of agricultural intensification in England and Wales. J. Appl. Ecol. 37, 771–788 (2000).

    Google Scholar 

  17. 17.

    Hawes, C. et al. Functional approaches for assessing plant and invertebrate abundance patterns in arable systems. Basic Appl. Ecol. 10, 34–42 (2009).

    Google Scholar 

  18. 18.

    Haughton, A. J. et al. Invertebrate responses to the management of genetically modified herbicide-tolerant and conventional spring crops. II. Within-field epigeal and aerial arthropods. Phil. Trans. R. Soc. Lond. B 358, 1863–1877 (2003).

    CAS  Google Scholar 

  19. 19.

    Jordán, F. Keystone species and food webs. Phil. Trans. R. Soc. Lond. B 364, 1733–1741 (2009).

    Google Scholar 

  20. 20.

    Lu, X. et al. Drought rewires the cores of food webs. Nat. Clim. Change 6, 875–878 (2016).

    Google Scholar 

  21. 21.

    McCann, K. et al. Weak trophic interactions and the balance of nature. Nature 395, 794–798 (1998).

    CAS  Google Scholar 

  22. 22.

    Jacquet, C. et al. No complexity–stability relationship in empirical ecosystems. Nat. Commun. 7, 12573 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Ma, A. & Mondragón, R. J. Rich-cores in networks. PLoS ONE 10, e0119678 (2015).

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Gaston, K. J. Valuing common species. Science 327, 154–155 (2010).

    CAS  PubMed  Google Scholar 

  25. 25.

    Liu, Y.-Y. et al. Controllability of complex networks. Nature 473, 167–173 (2011).

    CAS  PubMed  Google Scholar 

  26. 26.

    Brede, M. Coordinated and uncoordinated optimization of networks. Phys. Rev. E 81, 66104 (2010).

    Google Scholar 

  27. 27.

    Dunne, J. A. et al. Network structure and biodiversity loss in food webs: robustness increases with connectance. Ecol. Lett. 5, 558–567 (2002).

    Google Scholar 

  28. 28.

    Brookes, G. & Barfoot, P. Environmental impacts of genetically modified (GM) crop use 1996–2015: impacts on pesticide use and carbon emissions. GM Crops Food 8, 117–147 (2017).

    PubMed  PubMed Central  Google Scholar 

  29. 29.

    Raybould, A. & Poppy, G. M. Commercializing genetically modified crops under EU regulations. GM Crops Food 3, 9–20 (2012).

    PubMed  Google Scholar 

  30. 30.

    The Millennium Development Goals Report 2012 (United Nations Development Programme, 2012).

  31. 31.

    Bairey, E., Kelsic, E. D. & Kishony, R. High-order species interactions shape ecosystem diversity. Nat Commun. 7, 12285 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Levine, J. M., Bascompte, J., Adler, P. B. & Allesina, S. Beyond pairwise mechanisms of species coexistence in complex communities. Nature 546, 56–64 (2017).

    CAS  PubMed  Google Scholar 

  33. 33.

    Kaiser-Bunbury, C. N. & Bluthgen, N. Integrating network ecology with applied conservation: a synthesis and guide to implementation. AoB Plants 7, plv076 (2015).

    PubMed  PubMed Central  Google Scholar 

  34. 34.

    Dormann, C. F., Fründ, J. & Schaefer, H. M. Identifying causes of patterns in ecological networks: opportunities and limitations. Annu. Rev. Ecol. Evol. Syst. 48, 559–584 (2017).

    Google Scholar 

  35. 35.

    Rothery, P. et al. Design of the farm-scale evaluations of genetically modified herbicide-tolerant crops. Environmetrics 14, 711–717 (2003).

    Google Scholar 

  36. 36.

    Tamaddoni-Nezhad, A. et al. Construction and validation of food webs using logic-based machine learning and text mining. Adv. Ecol. Res. 49, 225–289 (2013).

    Google Scholar 

  37. 37.

    Tamaddoni-Nezhad, A et al. Machine learning a probabilistic network of ecological interactions. in Proc. 21st International Conference on Inductive Logic Programming (ILP’11) (Springer, 2012).

  38. 38.

    Davey, J. S. et al. Intraguild predation in winter wheat: prey choice by a common epigeal carabid consuming spiders. J. Appl. Ecol. 50, 271–279 (2013).

    Google Scholar 

  39. 39.

    Bray, J. R. & Curtis, J. T. An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr. 27, 325–349 (1957).

    Google Scholar 

  40. 40.

    Borgatti, S. P. & Everett, M. G. Models of core/periphery structures. Soc. Networks 21, 375–395 (1999).

    Google Scholar 

  41. 41.

    Csermely, P. et al. Structure and dynamics of core/periphery networks. J. Complex Networks 1, 93–123 (2013).

    Google Scholar 

  42. 42.

    Csete, M. & Doyle, J. Bow ties, metabolism and disease. Trends Biotechnol. 22, 446–450 (2004).

    CAS  PubMed  Google Scholar 

  43. 43.

    Zhou, S. & Mondragon, R. J. The rich-club phenomenon in the internet topology. IEEE Commun. Lett. 8, 180–182 (2004).

    Google Scholar 

  44. 44.

    Woodward, G. et al. Climate Change impacts in multispecies systems: drought alters food web size structure in a field experiment. Phil. Trans. R. Soc. Lond. B 367, 2990–2997 (2012).

    Google Scholar 

  45. 45.

    Memmott, J. et al. Tolerance of pollination networks to species extinctions. Proc. R. Soc. Lond. B 271, 2605–2611 (2004).

Download references


We thank J. Bigham, P. Curtis, P. Kratina, B. Parker and R. Bailey for their comments and discussion. X.L. and C.G. were supported by Queen Mary University of London. X.L. was additionally supported by the Chinese Scholarship Council and C.G. was additionally supported by the Freshwater Biological Association. D.A.B. acknowledges the support of the FACCE SURPLUS PREAR and ANR (ANR-17-CE32-011) NGB projects.

Author information




A.M. and D.A.B. designed the research. D.A.B. and A.T.-N. contributed materials and datasets. X.L. implemented the analysis. X.L. and C.G. analysed the data. A.M., X.L., C.G., A.R., G.W. and D.A.B. discussed the results. A.M. and D.A.B. led the paper writing with input from all authors.

Corresponding author

Correspondence to David A. Bohan.

Ethics declarations

Competing interests

A.R. is employed by Syngenta, which develops and markets genetically modified seed products.

Additional information

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

Supplementary information

Supplementary Information

Supplementary Methods 1–2, Supplementary Figures 1–6 and Supplementary Tables 1–3

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ma, A., Lu, X., Gray, C. et al. Ecological networks reveal resilience of agro-ecosystems to changes in farming management. Nat Ecol Evol 3, 260–264 (2019).

Download citation


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing