32. Allan, E. et al. Interannual variation in land-use intensity enhances grassland multidiversity. *Proc. Natl. Acad. Sci. USA* **111**, 308–313 (2014).

33. Le Provost, G. et al. Contrasting responses of above- and below-ground diversity to multiple components of land-use intensity. *Nat. Commun.* **12**, 3918 (2021).

34. Hairston, N. G., Smith, F. E. & Slobodkin, L. B. Community structure, population control, and competition. *Am. Nat.* **94**, 421–425 (1960).

35. Audusseau, H., Kolb, G. & Janz, N. Plant fertilization interacts with life history: variation in stoichiometry and performance in nettle-feeding butterflies. *PLoS ONE* **10**, e0124616 (2015).

36. Cadotte, M. W. Functional traits explain ecosystem function through opposing mechanisms. *Ecol. Lett.* **20**, 989–996 (2017).

37. Evans, R. et al. Defining the functional traits that drive bacterial decomposer community productivity. *ISME J.* **11**, 1680–1687 (2017).

38. Manning, P. et al. Redefining ecosystem multifunctionality. *Nat. Ecol. Evol.* **2**, 427–436 (2018).

39. Migliavacca, M. et al. The three major axes of terrestrial ecosystem function. *Nature* **598**, 468–472 (2021).

40. Eskelinen, A. et al. Resource-enhancing global changes drive a whole-ecosystem shift to faster cycling but decrease diversity. *Ecology* **101**, e03178 (2020).

41. Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. *Ecol. Lett.* **18**, 834–843 (2015).

42. Körösi, Á., Dolek, M., Nunner, A., Lang, A. & Theves, F. Pace of life and mobility as key factors to survive in farmland – Relationships between functional traits of diurnal Lepidoptera and landscape structure. *Agric. Ecosyst. Environ.* **334**, 107978 (2022).

43. Leff, J. W. et al. Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe. *Proc. Natl. Acad. Sci. USA* **112**, 10967–10972 (2015).

44. Gallagher, R. V. et al. Open Science principles for accelerating trait-based science across the Tree of Life. *Nat. Ecol. Evol.* **4**, 294–303 (2020).

45. Kattge, J. et al. TRY – a global database of plant traits. *Glob. Change Biol.* **17**, 2905–2935 (2011).

46. Madin, J. S. et al. A synthesis of bacterial and archaeal phenotypic trait data. *Sci. Data* **7**, 170 (2020).

47. Tobias, J. A. et al. AVONET: morphological, ecological and geographical data for all birds. *Ecol. Lett.* **25**, 581–597 (2022).

48. Bruelheide, H. et al. Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China. *Methods Ecol. Evol.* **5**, 74–89 (2014).

49. Fischer, M. et al. Implementing large-scale and long-term functional biodiversity research: the biodiversity exploratories. *Basic Appl. Ecol.* **11**, 473–485 (2010).

50. Li, D. et al. Standardized NEON organismal data for biodiversity research. *Ecosphere* **13**, e4141 (2022).

51. Blüthgen, N. et al. A quantitative index of land-use intensity in grasslands: integrating mowing, grazing and fertilization. *Basic Appl. Ecol.* **13**, 207–220 (2012).

52. Gossner, M. M. et al. A summary of eight traits of Coleoptera, Hemiptera, Orthoptera and Araneae, occurring in grasslands in Germany. *Sci. Data* **2**, 150013 (2015).

53. Börshig, C. & Krauss, J. Diversity and abundance of day active butterflies and day-active moths along a land use intensity gradient (2008). *v2. Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/12526 (2011).

54. Cook, P. M. et al. Traits data for the butterflies and macro-moths of Great Britain and Ireland. *NERC EDS Environ. Inf. Data Cent.* https://doi.org/10.5285/5b5a13b6-2304-47e3-9c9d-35237d1232c6 (2021).

55. Mangels, J., Fiedler, K., Schneider, F. D. & Blüthgen, N. Diversity and trait composition of moths respond to land-use intensification in grasslands: generalists replace specialists. *Biodivers. Conserv.* **26**, 3385–3405 (2017).

56. Middleton-Welling, J. et al. A new comprehensive trait database of European and Maghreb butterflies, Papilionoidea. *Sci. Data* **7**, 351 (2020).

57. Cavalier-Smith, T. r- and K-tactics in the evolution of protist developmental systems: Cell and genome size, phenotype diversifying selection, and cell cycle patterns. *Biosystems* **12**, 43–59 (1980).

58. Piton, G. et al. Using proxies of microbial community-weighted means traits to explain the cascading effect of management intensity, soil and plant traits on ecosystem resilience in mountain grasslands. *J. Ecol.* **108**, 876–893 (2020).

59. Endara, M.-J. & Coley, P. D. The resource availability hypothesis revisited: a meta-analysis. *Funct. Ecol.* **25**, 389–398 (2011).

60. Liu, X., Zhang, L., Huang, M. & Zhou, S. Plant diversity promotes soil fungal pathogen richness under fertilization in an alpine meadow. *J. Plant Ecol.* **14**, 323–336 (2021).

61. Fiore-Donno, A. M., Richter-Heitmann, M. & Bonkowski, T. Functional traits of two important protistan lineages (*Cercozoa* and *Endomyxa*) reveal contrasting distributions of plant parasites and phagotrophs in temperate grassland and forest soils. **14**, (2020).

62. Birkhofer, K. et al. Land-use type and intensity differentially filter traits in above- and below-ground arthropod communities. *J. Anim. Ecol.* **86**, 511–520 (2017).

63. Hanson, H. I., Palmu, E., Birkhofer, K., Smith, H. G. & Hedlund, K. Agricultural land use determines the trait composition of ground beetle communities. *PLoS ONE* **11**, e0146329 (2016).

64. Chisté, M. N. et al. Losers, winners, and opportunists: how grassland land-use intensity affects orthopteran communities. *Ecosphere* **7**, e01545 (2016).

65. Gámez-Virués, S. et al. Landscape simplification filters species traits and drives biotic homogenization. *Nat. Commun.* **6**, 8568 (2015).

66. Boch, S., Biurrun, I. & Rodwell, J. Grasslands of Western Europe. in *Encyclopedia of the World's Biomes* (eds. Goldstein, M. I. & DelaSala, D. A.) 678–688 (Elsevier, 2020). https://doi.org/10.1016/B978-0-12-409548-9.12095-0.

67. Socher, S. A. et al. Direct and productivity-mediated indirect effects of fertilization, mowing and grazing on grassland species richness. *J. Ecol.* **100**, 1391–1399 (2012).

68. Ali, J. G. & Agrawal, A. A. Specialist versus generalist insect herbivores and plant defense. *Trends Plant Sci.* **17**, 293–302 (2012).

69. Bielby, J. et al. The fast-slow continuum in mammalian life history: an empirical reevaluation. *Am. Nat.* **169**, 748–757 (2007).

70. Stearns, S. C. The influence of size and phylogeny on patterns of covariation among life-history traits in the mammals. *Oikos* **41**, 173–187 (1983).

71. Garibaldi, L. A. et al. Trait matching of flower visitors and crops predicts fruit set better than trait diversity. *J. Appl. Ecol.* **52**, 1436–1444 (2015).

72. Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. *Proc. Natl. Acad. Sci. USA* **115**, 6506–6511 (2018).

73. Chapin, F. S., Matson, P. A. & Vitousek, P. M. Principles of Terrestrial Ecosystem Ecology. (Springer, 2011). https://doi.org/10.1007/978-1-4419-9504-9.

74. Yvon-Durocher, G. & Allen, A. P. Linking community size structure and ecosystem functioning using metabolic theory. *Philos. Trans. R. Soc. B Biol. Sci.* **367**, 2998–3007 (2012).

75. Reich, P. B. The world-wide 'fast-slow' plant economics spectrum: a traits manifesto. *J. Ecol.* **102**, 275–301 (2014).
32. Allan, E. et al. Interannual variation in land-use intensity enhances grassland multidiversity. *Proc. Natl. Acad. Sci. USA* **111**, 308–313 (2014).

33. Le Provost, G. et al. Contrasting responses of above- and below-ground diversity to multiple components of land-use intensity. *Nat. Commun.* **12**, 3918 (2021).

34. Hairston, N. G., Smith, F. E. & Slobodkin, L. B. Community structure, population control, and competition. *Am. Nat.* **94**, 421–425 (1960).

35. Audusseau, H., Kolb, G. & Janz, N. Plant fertilization interacts with life history: variation in stoichiometry and performance in nettle-feeding butterflies. *PLoS ONE* **10**, e0124616 (2015).

36. Cadotte, M. W. Functional traits explain ecosystem function through opposing mechanisms. *Ecol. Lett.* **20**, 989–996 (2017).

37. Evans, R. et al. Defining the functional traits that drive bacterial decomposer community productivity. *ISME J.* **11**, 1680–1687 (2017).

38. Manning, P. et al. Redefining ecosystem multifunctionality. *Nat. Ecol. Evol.* **2**, 427–436 (2018).

39. Migliavacca, M. et al. The three major axes of terrestrial ecosystem function. *Nature* **598**, 468–472 (2021).

40. Eskelinen, A. et al. Resource-enhancing global changes drive a whole-ecosystem shift to faster cycling but decrease diversity. *Ecology* **101**, e03178 (2020).

41. Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. *Ecol. Lett.* **18**, 834–843 (2015).

42. Körösi, Á., Dolek, M., Nunner, A., Lang, A. & Theves, F. Pace of life and mobility as key factors to survive in farmland – Relationships between functional traits of diurnal Lepidoptera and landscape structure. *Agric. Ecosyst. Environ.* **334**, 107978 (2022).

43. Leff, J. W. et al. Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe. *Proc. Natl. Acad. Sci. USA* **112**, 10967–10972 (2015).

44. Gallagher, R. V. et al. Open Science principles for accelerating trait-based science across the Tree of Life. *Nat. Ecol. Evol.* **4**, 294–303 (2020).

45. Kattge, J. et al. TRY – a global database of plant traits. *Glob. Change Biol.* **17**, 2905–2935 (2011).

46. Madin, J. S. et al. A synthesis of bacterial and archaeal phenotypic trait data. *Sci. Data* **7**, 170 (2020).

47. Tobias, J. A. et al. AVONET: morphological, ecological and geographical data for all birds. *Ecol. Lett.* **25**, 581–597 (2022).

48. Bruelheide, H. et al. Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China. *Methods Ecol. Evol.* **5**, 74–89 (2014).

49. Fischer, M. et al. Implementing large-scale and long-term functional biodiversity research: the biodiversity exploratories. *Basic Appl. Ecol.* **11**, 473–485 (2010).

50. Li, D. et al. Standardized NEON organismal data for biodiversity research. *Ecosphere* **13**, e4141 (2022).

51. Blüthgen, N. et al. A quantitative index of land-use intensity in grasslands: integrating mowing, grazing and fertilization. *Basic Appl. Ecol.* **13**, 207–220 (2012).

52. Gossner, M. M. et al. A summary of eight traits of Coleoptera, Hemiptera, Orthoptera and Araneae, occurring in grasslands in Germany. *Sci. Data* **2**, 150013 (2015).

53. Börshig, C. & Krauss, J. Diversity and abundance of day active butterflies and day-active moths along a land use intensity gradient (2008). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/12526 (2011).

54. Cook, P. M. et al. Traits data for the butterflies and macro-moths of Great Britain and Ireland. *NERC EDS Environ. Inf. Data Cent.* https://doi.org/10.5285/5b5a13b6-2304-47e3-9c9d-35237d1232c6 (2021).

55. Mangels, J., Fiedler, K., Schneider, F. D. & Blüthgen, N. Diversity and trait composition of moths respond to land-use intensification in grasslands: generalists replace specialists. *Biodivers. Conserv.* **26**, 3385–3405 (2017).

56. Middleton-Welling, J. et al. A new comprehensive trait database of European and Maghreb butterflies, Papilionoidea. *Sci. Data* **7**, 351 (2020).

57. Cavalier-Smith, T. r- and K-tactics in the evolution of protist developmental systems: Cell and genome size, phenotype diversifying selection, and cell cycle patterns. *Biosystems* **12**, 43–59 (1980).

58. Piton, G. et al. Using proxies of microbial community-weighted means traits to explain the cascading effect of management intensity, soil and plant traits on ecosystem resilience in mountain grasslands. *J. Ecol.* **108**, 876–893 (2020).

59. Endara, M.-J. & Coley, P. D. The resource availability hypothesis revisited: a meta-analysis. *Funct. Ecol.* **25**, 389–398 (2011).

60. Liu, X., Zhang, L., Huang, M. & Zhou, S. Plant diversity promotes soil fungal pathogen richness under fertilization in an alpine meadow. *J. Plant Ecol.* **14**, 323–336 (2021).

61. Fiore-Donno, A. M., Richter-Heitmann, M. & Bonkowski, T. Functional traits of two important protistan lineages (*Cercozoa* and *Endomyxa*) reveal contrasting distributions of plant parasites and phagotrophs in temperate grassland and forest soils. **14**, (2020).

62. Birkhofer, K. et al. Land-use type and intensity differentially filter traits in above- and below-ground arthropod communities. *J. Anim. Ecol.* **86**, 511–520 (2017).

63. Hanson, H. I., Palmu, E., Birkhofer, K., Smith, H. G. & Hedlund, K. Agricultural land use determines the trait composition of ground beetle communities. *PLoS ONE* **11**, e0146329 (2016).

64. Chisté, M. N. et al. Losers, winners, and opportunists: how grassland land-use intensity affects orthopteran communities. *Ecosphere* **7**, e01545 (2016).

65. Gámez-Virués, S. et al. Landscape simplification filters species traits and drives biotic homogenization. *Nat. Commun.* **6**, 8568 (2015).

66. Boch, S., Biurrun, I. & Rodwell, J. Grasslands of Western Europe. in *Encyclopedia of the World's Biomes* (eds. Goldstein, M. I. & DelaSala, D. A.) 678–688 (Elsevier, 2020). https://doi.org/10.1016/B978-0-12-409548-9.12095-0.

67. Socher, S. A. et al. Direct and productivity-mediated indirect effects of fertilization, mowing and grazing on grassland species richness. *J. Ecol.* **100**, 1391–1399 (2012).

68. Ali, J. G. & Agrawal, A. A. Specialist versus generalist insect herbivores and plant defense. *Trends Plant Sci.* **17**, 293–302 (2012).

69. Bielby, J. et al. The fast-slow continuum in mammalian life history: an empirical reevaluation. *Am. Nat.* **169**, 748–757 (2007).

70. Stearns, S. C. The influence of size and phylogeny on patterns of covariation among life-history traits in the mammals. *Oikos* **41**, 173–187 (1983).

71. Garibaldi, L. A. et al. Trait matching of flower visitors and crops predicts fruit set better than trait diversity. *J. Appl. Ecol.* **52**, 1436–1444 (2015).

72. Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. *Proc. Natl. Acad. Sci. USA* **115**, 6506–6511 (2018).

73. Chapin, F. S., Matson, P. A. & Vitousek, P. M. *Principles of Terrestrial Ecosystem Ecology*. (Springer, 2011). https://doi.org/10.1007/978-1-4419-9504-9.

74. Yvon-Durocher, G. & Allen, A. P. Linking community size structure and ecosystem functioning using metabolic theory. *Philos. Trans. R. Soc. B Biol. Sci.* **367**, 2998–3007 (2012).

75. Reich, P. B. The world-wide 'fast-slow' plant economics spectrum: a traits manifesto. *J. Ecol.* **102**, 275–301 (2014).
76. Gibb, H. et al. Ecological strategies of (pl)ants: Towards a world-wide worker economic spectrum for ants. *Funct. Ecol.* **37**, 13–25 (2023).

77. DeMalach, N., Ron, R. & Kadmon, R. Mechanisms of seed mass variation along resource gradients. *Ecol. Lett.* **22**, 181–189 (2019).

78. Lamanna, C. et al. Functional trait space and the latitudinal diversity gradient. *Proc. Natl. Acad. Sci. USA* **111**, 13745–13750 (2014).

79. Scherber, C. et al. Bottom-up effects of plant diversity on multi-trophic interactions in a biodiversity experiment. *Nature* **468**, 553–556 (2010).

80. Walde, M. et al. Both diversity and functional composition affect productivity and water use efficiency in experimental temperate grasslands. *J. Ecol.* **109**, 3877–3891 (2021).

81. Allan, E. et al. More diverse plant communities have higher functioning over time due to turnover in complementary dominant species. *Proc. Natl. Acad. Sci. USA* **108**, 17034–17039 (2011).

82. Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. *Nature* **486**, 59 (2012).

83. Craven, D., Polley, H. W. & Wilsey, B. Multiple facets of biodiversity drive the diversity-stability relationship. *Nat. Ecol. Evol.* **2**, 1579 (2018).

84. Ricotta, C. & Moretti, M. CWM and Rao's quadratic diversity: a unified framework for functional ecology. *Oecologia* **167**, 181–188 (2011).

85. Zhu, J., Jiang, L. & Zhang, Y. Relationships between functional diversity and aboveground biomass production in the Northern Tibetan alpine grasslands. *Sci. Rep.* **6**, 34105 (2016).

86. Joswig, J. S. et al. Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation. *Nat. Ecol. Evol.* https://doi.org/10.1038/s41559-021-01616-8 (2021).

87. Bardgett, R. D. et al. Changes in soil fungal: bacterial biomass ratios following reductions in the intensity of management of an upland grassland. *Biol. Fertil. Soils* **22**, 261–264 (1996).

88. Gounand, I., Little, C. J., Harvey, E. & Altermatt, F. Global quantitative synthesis of ecosystem functioning across climatic zones and ecosystem types. *Glob. Ecol. Biogeogr.* **29**, 1139–1176 (2020).

89. Lindo, Z. Warming favours small-bodied organisms through enhanced reproduction and compositional shifts in belowground systems. *Soil Biol. Biochem.* **91**, 271–278 (2015).

90. Martins, I. S. et al. Widespread shifts in body size within populations and assemblages. *Science* **381**, 1067–1071 (2023).

91. Donoso, I. et al. Downsizing of animal communities triggers stronger functional than structural decay in seed-dispersal networks. *Nat. Commun.* **11**, 1582 (2020).

92. Ostrowski, A., Lorenzen, K., Petzold, E. & Schindler, S. Land use intensity index (LUI) calculation tool of the Biodiversity Exploratories project for grassland survey data from three different regions in Germany since 2006. BEXIS 2 module. https://doi.org/10.5281/zenodo.3865579 (2020).

93. Schöning, I., Solly, E., Klötzing, T., Schrumpf, M. & Trumbore, S. Mineral soil pH values of all experimental plots (EP) of the Biodiversity Exploratories project from 2011, Soil (core project). v8. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14447 (2015).

94. Schöning, I. et al. MinSoil 2014 - Soil pH. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19067 (2015).

95. Schöning, I., Heublein, J., Klötzing, T., Schrumpf, M. & Trumbore, S. MinSoil 2011 - Soil Texture. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14686 (2013).

96. Le Provost, G. et al. Aggregated environmental and land-use covariates of the 150 grassland EPs used in 'Contrasting responses of above- and belowground diversity to multiple components of land-use intensity'. v5. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/31018 (2021).

97. Hänsel, F., Forteva, S., Wöllauer, S. & Nauss, T. Öffentlich verfügbare Klimadaten der Exploratorien / Open Climate Data of the Exploratories Project. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/tcd/PublicClimateData/Index (2019).

98. Penone, C. et al. Assembled species information from grassland EPs (2008–2020) for multidiversity synthesis - November 2020. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/27706 (2021).

99. Penone, C. et al. Assembled RAW diversity from grassland EPs (2008–2020) for multidiversity synthesis - November 2020. v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/27707 (2021).

100. Bolliger, R., Prati, D. & Fischer, M. Vegetation Records for Grassland EPs, 2008–2020. v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/27386 (2021).

101. Buscot, F., Goldmann, K. & Wubet, T. Abundant soil fungi on all 150 grassland EPs (from Soil Sampling Campain 2011; Illumina MiSeq) - ASV abundances. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26470 (2021).

102. Buscot, F., Goldmann, K. & Wubet, T. Abundant soil fungi on all 150 grassland EPs (from Soil Sampling Campain 2014; Illumina MiSeq) - ASV abundances. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26471 (2020).

103. Overmann, J. & Sikorski, J. 16S rRNA gene (V3 region) RNA-based analysis of microbial soil communities at sequence variant level in 148 grassland EP plots, using QIIME2-based bioinformatics, 2011. v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/24866 (2019).

104. Kandeler, E., Marhan, S., Berner, D. & Boeddinghaus, R. S. Microbial soil properties of all grassland EPs, soil sampling campaign (SSC) 2011, SCALEMIC. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20250 (2017).

105. Kandeler, E., Marhan, S., Berner, D. & Boeddinghaus, R. S. Microbial soil properties of all grassland EPs, soil sampling campaign (SSC) 2014, SCALEMIC. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20251 (2017).

106. Sikorski, J., Overmann, J. & Marzini, C. 16S rRNA gene (V3 region) RNA-based analysis of microbial soil communities at sequence variant level in 150 grassland EP plots, using QIIME2-based bioinformatics, 2014. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/25066 (2019).

107. Fiore-Donno, A. M. & Bonkowski, M. Cercozoa and Endomyxa (Rhizaria, protists), Illumina Sequences, all EPs, grassland and forest, 2011. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/24426 (2019).

108. Fiore-Donno, A. M. & Bonkowski, M. Cercozoa and Endomyxa (Rhizaria, protists), Illumina Sequences, all EPs, grassland and forest, 2017. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/24466 (2019).

109. Baulechner, D., Wolters, V., John, K. & Zaytsev, A. Acari abundance (Oribatida to species level) on all 150 grassland EPs from 2019. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/27406.
76. Gibb, H. et al. Ecological strategies of (pl)ants: Towards a world-wide worker economic spectrum for ants. *Funct. Ecol.* **37**, 13–25 (2023).

77. DeMalach, N., Ron, R. & Kadmon, R. Mechanisms of seed mass variation along resource gradients. *Ecol. Lett.* **22**, 181–189 (2019).

78. Lamanna, C. et al. Functional trait space and the latitudinal diversity gradient. *Proc. Natl. Acad. Sci. USA* **111**, 13745–13750 (2014).

79. Scherber, C. et al. Bottom-up effects of plant diversity on multi-trophic interactions in a biodiversity experiment. *Nature* **468**, 553–556 (2010).

80. Walde, M. et al. Both diversity and functional composition affect productivity and water use efficiency in experimental temperate grasslands. *J. Ecol.* **109**, 3877–3891 (2021).

81. Allan, E. et al. More diverse plant communities have higher functioning over time due to turnover in complementary dominant species. *Proc. Natl. Acad. Sci. USA* **108**, 17034–17039 (2011).

82. Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. *Nature* **486**, 59 (2012).

83. Craven, D., Polley, H. W. & Wilsey, B. Multiple facets of biodiversity drive the diversity-stability relationship. *Nat. Ecol. Evol.* **2**, 1579 (2018).

84. Ricotta, C. & Moretti, M. CWM and Rao's quadratic diversity: a unified framework for functional ecology. *Oecologia* **167**, 181–188 (2011).

85. Zhu, J., Jiang, L. & Zhang, Y. Relationships between functional diversity and aboveground biomass production in the Northern Tibetan alpine grasslands. *Sci. Rep.* **6**, 34105 (2016).

86. Joswig, J. S. et al. Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation. *Nat. Ecol. Evol.* https://doi.org/10.1038/s41559-021-01616-8 (2021).

87. Bardgett, R. D. et al. Changes in soil fungal: bacterial biomass ratios following reductions in the intensity of management of an upland grassland. *Biol. Fertil. Soils* **22**, 261–264 (1996).

88. Gounand, I., Little, C. J., Harvey, E. & Altermatt, F. Global quantitative synthesis of ecosystem functioning across climatic zones and ecosystem types. *Glob. Ecol. Biogeogr.* **29**, 1139–1176 (2020).

89. Lindo, Z. Warming favours small-bodied organisms through enhanced reproduction and compositional shifts in belowground systems. *Soil Biol. Biochem.* **91**, 271–278 (2015).

90. Martins, I. S. et al. Widespread shifts in body size within populations and assemblages. *Science* **381**, 1067–1071 (2023).

91. Donoso, I. et al. Downsizing of animal communities triggers stronger functional than structural decay in seed-dispersal networks. *Nat. Commun.* **11**, 1582 (2020).

92. Ostrowski, A., Lorenzen, K., Petzold, E. & Schindler, S. Land use intensity index (LUI) calculation tool of the Biodiversity Exploratories project for grassland survey data from three different regions in Germany since 2006. BEXIS 2 module. https://doi.org/10.5281/zenodo.3865579 (2020).

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238. Frostegård, Å., Tunlid, A. & Bååth, E. Phospholipid fatty acid composition, biomass, and activity of microbial communities from two soil types experimentally exposed to different heavy metals. *Appl. Environ. Microbiol.* https://doi.org/10.1128/aem.59.11.3605-3617.1993 (1993).

239. Ruess, L. & Chamberlain, P. M. The fat that matters: soil food web analysis using fatty acids and their carbon stable isotope signature. *Soil Biol. Biochem.* **42**, 1898–1910 (2010).

240. Dumack, K., Fiore-Donno, A. M., Bass, D. & Bonkowski, M. Making sense of environmental sequencing data: ecologically important functional traits of the protistan groups Cercozoa and Endomyxa (Rhizaria). *Mol. Ecol. Resour.* **20**, 398–403 (2020).

241. Schenk, N. et al. Assembled ecosystem measures from grassland EPs. *Biodiversity Exploratories Information System* https://www.bexis.uni-jena.de/ddm/data/Showdata/27087 (2020).

242. Smith, M. S. & Tiedje, J. M. Phases of denitrification following oxygen depletion in soil. *Soil Biol. Biochem.* **11**, 261–267 (1979).

243. Keil, D. et al. Effects of warming and drought on potential N2O emissions and denitrifying bacteria abundance in grasslands with different land-use. *FEMS Microbiol. Ecol.* **91**, fiv066 (2015).

244. Schinner, F., Öhlinger, R., Kandeler, E. & Margesin, R. *Methods in Soil Biology* (Springer, 1996).

245. Ollivier, J. et al. Effects of repeated application of sulfadiazine-contaminated pig manure on the abundance and diversity of ammonia and nitrite oxidizers in the root-rhizosphere complex of pasture plants under field conditions. *Front. Microbiol.* **4**, 22 (2013).

246. Hoffmann, H., Schloter, M. & Wilke, B.-M. Microscale-scale measurement of potential nitrification rates of soil aggregates. *Biol. Fertil. Soils* **44**, 411–413 (2007).

247. Marx, M.-C., Wood, M. & Jarvis, S. C. A microplate fluorimetric assay for the study of enzyme diversity in soils. *Soil Biol. Biochem.* **33**, 1633–1640 (2001).

248. Berner, D. et al. Land-use intensity modifies spatial distribution and function of soil microorganisms in grasslands. *Pedobiologia* **54**, 341–351 (2011).

249. Kandeler, E., Berner, D., Marhan, S. & Boeddinghaus, R. S. Soil enzyme activities of all grassland EPs, soil sampling campaign (SSC) 2011, SCALEMIC. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20246 (2017).

250. Stempfhuber, B. & Schloter, M. Abundance of nitrogen fixing microbes and ammonia oxidizers in grassland. v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/13986 (2017).

251. Stempfhuber, B. & Schloter, M. Nitrogen pools and potential nitrification taken at soil sampling campaign 2014. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19847 (2016).

252. Kovacevic, V., Schultz, S. & Schloter, M. Nitrifiers abundances at grassland EPs. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21547 (2019).

253. Frank, K. & Blüthgen, N. Decomposition (dung removal in) on 300 EPs, season 2014/2015), Taxon: dung beetles (Invertebrates, Scarabaeoidea) - Dungwebs. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21206 (2017).

254. Solly, E. & Schöning, I. MinSoil 2011 root decomposition. v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/16666 (2013).

255. Fischer, M. & Grassein, F. Litter decomposition (2013, all grassland EPs). v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/18926 (2015).

256. Grogan, P. Co2 Flux measurement using soda lime: correction for water formed during co2 adsorption. *Ecology* **79**, 1467–1468 (1998).

257. Keith, H. & Wong, S. C. Measurement of soil CO2 efflux using soda lime absorption: both quantitative and reliable. *Soil Biol. Biochem.* **38**, 1121–1131 (2006).

258. Apostolakis, A., Schöning, I., Schrumpf, M., Klötzing, T. & Trumbore, S. MinSoil 2018-19: soil respiration in forests and grasslands. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26908 (2020).

259. Boch, S., Mueller, J., Socher, S., Prati, D. & Fischer, M. Measurement of biomass (2009, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/16209 (2017).

260. Fischer, M., Schäfer, D., Boch, S. & Prati, D. Vegetation records for 150 grassland EPs in 2016, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21187 (2017).

261. Prati, D., Fischer, M., Minker, J. & Schmitt, B. Measurement of biomass (2013, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/16786 (2013).

262. Schäfer, D., Prati, D. & Fischer, M. Vegetation records for 150 grassland EPs in 2017, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/23486 (2018).

263. Schäfer, D., Fischer, M., Klaus, V. & Busch, V. Vegetation records for 150 grassland EPs in 2014, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19807 (2016).

264. Schäfer, D., Fischer, M., Klaus, V. & Busch, V. Vegetation records for 150 grassland EPs in 2015, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19809 (2016).

265. Schmitt, B., Prati, D., Fischer, M. & Minker, J. Measurement of biomass (2011, all grassland EPs). v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/Showdata/14346 (2012).

266. Schmitt, B., Prati, D., Fischer, M. & Minker, J. Measurement of biomass (2012, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/13986 (2017).
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236. Baulechner D. et al. Collembola traits from all grassland plots (2023). v0. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/31481 (2023).

237. Frostegård, Å., Tunlid, A. & Bååth, E. Microbial biomass measured as total lipid phosphate in soils of different organic content. *J. Microbiol. Methods* **14**, 151–163 (1991).

238. Frostegård, Å., Tunlid, A. & Bååth, E. Phospholipid fatty acid composition, biomass, and activity of microbial communities from two soil types experimentally exposed to different heavy metals. *Appl. Environ. Microbiol.* https://doi.org/10.1128/aem.59.11.3605-3617.1993 (1993).

239. Ruess, L. & Chamberlain, P. M. The fat that matters: soil food web analysis using fatty acids and their carbon stable isotope signature. *Soil Biol. Biochem.* **42**, 1898–1910 (2010).

240. Dumack, K., Fiore-Donno, A. M., Bass, D. & Bonkowski, M. Making sense of environmental sequencing data: ecologically important functional traits of the protistan groups Cercozoa and Endomyxa (Rhizaria). *Mol. Ecol. Resour.* **20**, 398–403 (2020).

241. Schenk, N. et al. Assembled ecosystem measures from grassland EPs. *Biodiversity Exploratories Information System* https://www.bexis.uni-jena.de/ddm/data/Showdata/27087 (2020).

242. Smith, M. S. & Tiedje, J. M. Phases of denitrification following oxygen depletion in soil. *Soil Biol. Biochem.* **11**, 261–267 (1979).

243. Keil, D. et al. Effects of warming and drought on potential N2O emissions and denitrifying bacteria abundance in grasslands with different land-use. *FEMS Microbiol. Ecol.* **91**, fiv066 (2015).

244. Schinner, F., Öhlinger, R., Kandeler, E. & Margesin, R. *Methods in Soil Biology* (Springer, 1996).

245. Ollivier, J. et al. Effects of repeated application of sulfadiazine-contaminated pig manure on the abundance and diversity of ammonia and nitrite oxidizers in the root-rhizosphere complex of pasture plants under field conditions. *Front. Microbiol.* **4**, 22 (2013).

246. Hoffmann, H., Schloter, M. & Wilke, B.-M. Microscale-scale measurement of potential nitrification rates of soil aggregates. *Biol. Fertil. Soils* **44**, 411–413 (2007).

247. Marx, M.-C., Wood, M. & Jarvis, S. C. A microplate fluorimetric assay for the study of enzyme diversity in soils. *Soil Biol. Biochem.* **33**, 1633–1640 (2001).

248. Berner, D. et al. Land-use intensity modifies spatial distribution and function of soil microorganisms in grasslands. *Pedobiologia* **54**, 341–351 (2011).

249. Kandeler, E., Berner, D., Marhan, S. & Boeddinghaus, R. S. Soil enzyme activities of all grassland EPs, soil sampling campaign (SSC) 2011, SCALEMIC. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20246 (2017).

250. Stempfhuber, B. & Schloter, M. Abundance of nitrogen fixing microbes and ammonia oxidizers in grassland. v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/13986 (2017).

251. Stempfhuber, B. & Schloter, M. Nitrogen pools and potential nitrification taken at soil sampling campaign 2014. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19847 (2016).

252. Kovacevic, V., Schultz, S. & Schloter, M. Nitrifiers abundances at grassland EPs. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21547 (2019).

253. Frank, K. & Blüthgen, N. Decomposition (dung removal in) on 300 EPs, season 2014/2015), Taxon: dung beetles (Invertebrates, Scarabaeoidea) - Dungwebs. v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21206 (2017).

254. Solly, E. & Schöning, I. MinSoil 2011 root decomposition. v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/16666 (2013).

255. Fischer, M. & Grassein, F. Litter decomposition (2013, all grassland EPs). v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/18926 (2015).

256. Grogan, P. Co2 Flux measurement using soda lime: correction for water formed during co2 adsorption. *Ecology* **79**, 1467–1468 (1998).

257. Keith, H. & Wong, S. C. Measurement of soil CO2 efflux using soda lime absorption: both quantitative and reliable. *Soil Biol. Biochem.* **38**, 1121–1131 (2006).

258. Apostolakis, A., Schöning, I., Schrumpf, M., Klötzing, T. & Trumbore, S. MinSoil 2018-19: soil respiration in forests and grasslands. v4. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26908 (2020).

259. Boch, S., Mueller, J., Socher, S., Prati, D. & Fischer, M. Measurement of biomass (2009, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/16209 (2017).

260. Fischer, M., Schäfer, D., Boch, S. & Prati, D. Vegetation records for 150 grassland EPs in 2016, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21187 (2017).

261. Prati, D., Fischer, M., Minker, J. & Schmitt, B. Measurement of biomass (2013, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/16786 (2013).

262. Schäfer, D., Prati, D. & Fischer, M. Vegetation records for 150 grassland EPs in 2017, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/23486 (2018).

263. Schäfer, D., Fischer, M., Klaus, V. & Busch, V. Vegetation records for 150 grassland EPs in 2014, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19807 (2016).

264. Schäfer, D., Fischer, M., Klaus, V. & Busch, V. Vegetation records for 150 grassland EPs in 2015, header data without species identities (incl. biomass). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19809 (2016).

265. Schmitt, B., Prati, D., Fischer, M. & Minker, J. Measurement of biomass (2011, all grassland EPs). v3. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/Showdata/14346 (2012).

266. Schmitt, B., Prati, D., Fischer, M. & Minker, J. Measurement of biomass (2012, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/13986 (2017).
Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14986 (2012).

267. Schmitt, B., Prati, D. & Fischer, M. Measurement of biomass (2010, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/12706 (2011).

268. R Core Team. *R: A language and environment for statistical computing*. (R Foundation for Statistical Computing, Vienna, Austria 2023).

269. Lavorel, S. & Garnier, E. Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. *Funct. Ecol.* **16**, 545–556 (2002).

270. Suding, K. N. et al. Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants. *Glob. Change Biol.* **14**, 1125–1140 (2008).

271. Pollock, L. J. et al. Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model. *Methods Ecol. Evol.* **5**, 397–406 (2014).

272. Freckleton, R. P. On the misuse of residuals in ecology: regression of residuals vs. multiple regression. *J. Anim. Ecol.* **71**, 542–545 (2002).

273. Bécue-Bertaut, M. & Pagès, J. Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data. *Comput. Stat. Data Anal.* **52**, 3255–3268 (2008).

274. Escofier, B. & Pagès, J. Multiple factor analysis (AFMULT package). *Comput. Stat. Data Anal.* **18**, 121–140 (1994).

275. Kéfi, S. et al. More than a meal... integrating non-feeding interactions into food webs. *Ecol. Lett.* **15**, 291–300 (2012).

276. Rosseel, Y. lavaan: An R package for structural equation modeling. *J. Stat. Softw.* **48**, 1–36 (2012).

277. Wolfgang Wagner. *Europäische Schmetterlinge und ihre Ökologie*. http://www.pyrgus.de/.

## Acknowledgements

The work was partly funded by the DFG Priority Program 1374 'Infrastructure-Biodiversity-Exploratories', and by Senckenberg Biodiversity and Climate Research Center. The soil analyses (EK, SM) was funded by the DFG (KA 1590/8-5, MA 4436/1-5). DB, ASZ, KB, KJ and VW have received funding in the context of Resilience DFG project 413730012. ASZ was supported by the RSF 23-14-00201 grant. Fieldwork permits were issued by the state environmental offices of Baden-Württemberg, Thüringen, and Brandenburg. The authors thank Konstans Wells, Kirsten Reichel-Jung, Sonja Gockel, Kerstin Wiesner, Katrin Lorenzen, Andreas Hemp, Martin Gorke maintained the plot and project infrastructure; Simone Pfeiffer, Maren Gleisberg, Christiane Fischer, Jule Mangels and Victoria Grießmeier for administrative support, and Jens Nieschulze, Michael Owonibi and Andreas Ostrowski for database management. Eduard Linsenmair, Dominik Hessenmöller, Daniel Prati, Ernst-Detlef Schulze, Wolfgang W. Weisser and Elisabeth Kalko helped establish the Biodiversity Exploratories project. The administration of the Hainich National Park, the UNESCO Biosphere Reserves Swabian Alb and Schorfheide-Chorin and all land owners provided logistical support. Tom Lachaise, Jörg Overmann and Johannes Sikorski contributed data. Icons were acquired and adapted (colour, width-height ratio) from Phylopic.org. Lepidoptera, fungi, secondary consumer arthropods, bats, protists, Oribatid mites: public domain. Birds: Maxime Dahirel (CC BY 3.0 Deed). Collembola: Birgit Lang (CC BY 3.0 Deed). Bacteria: Matt Crook (CC BY-SA 3.0 Deed). Hare: Jan A. Venter, Herbert H. T. Prins, David A. Balfour & Rob Slotow (vectorised by T. Michael Keesey) (CC BY 3.0 Deed). Tortoise: Andrew A. Farke, shell lines added by Yan Wong (CC BY 3.0 Deed). Primary consumer arthropods: Gareth Monger (CC

BY 3.0 Deed). Link to the corresponding licences: CC BY 3.0 Deed: https://creativecommons.org/licenses/by/3.0/. CC BY-SA 3.0 Deed: https://creativecommons.org/licenses/by-sa/3.0/.

## Author contributions

M.N., F.D.S. and P.M. designed the study. M.N. and P.M. conducted the analyses with inputs from G.L.P. and A.L.B. M.N., P.M., G.L.P., D.B., F.T.d.V., J.B., A.M.F.D., S.G., K.G., A.M., R.A.S., N.K.S., J.A.T., A.S.Z. participated to workshops and expert discussions to define guild-specific trait lists and hypotheses. M.N. and P.M. wrote the manuscript with significant inputs from G.L.P., A.L.B., D.B., J.B., S.G., J.A.T., M.M.G., E.K., K.B., K. Jung, J. K., C.P., M.C.R., M. Schlöter, S. Schulz, M. Staab, M.v.K. and V.W. G.L.P., D.B., J.B., A.M.F.D., K.G., R.S., N.S., J.T., A.Z., M.G., K. John, K. Jung, E.K., J.K., C.P., M. Schloter, S. Schulz, M. Staab, V.W., A.A., S.B., R.S.B., R.B., M.B., F.B., K.D., H.Y.G., N.H., J.H., K.J., V.H.K, T.K., S.M., J.M., S.C.R., N.V.S., I.S., M.S., S. Seibold, S.A.S., E.S., M.T., M.v.K., T.W., M.F. and P.M. contributed data. All authors commented on the manuscript. Author order was determined as follow: main authors, workshop and discussion participants (alphabetical), other authors with significant input (alphabetical), other data contributors (alphabetical), senior author.

## Funding

Open access funding provided by University of Bergen.

## Competing interests

The authors declare no competing interests.

## Additional information

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s41467-024-45113-5.

**Correspondence** and requests for materials should be addressed to Margot Neyret or Peter Manning.

**Peer review information** *Nature Communications* thanks Bertrand Fournier and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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© The Author(s) 2024
Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14986 (2012).

267. Schmitt, B., Prati, D. & Fischer, M. Measurement of biomass (2010, all grassland EPs). v2. *Biodiversity Exploratories Information System*. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/12706 (2011).

268. R Core Team. *R: A language and environment for statistical computing*. (R Foundation for Statistical Computing, Vienna, Austria 2023).

269. Lavorel, S. & Garnier, E. Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. *Funct. Ecol.* **16**, 545–556 (2002).

270. Suding, K. N. et al. Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants. *Glob. Change Biol.* **14**, 1125–1140 (2008).

271. Pollock, L. J. et al. Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model. *Methods Ecol. Evol.* **5**, 397–406 (2014).

272. Freckleton, R. P. On the misuse of residuals in ecology: regression of residuals vs. multiple regression. *J. Anim. Ecol.* **71**, 542–545 (2002).

273. Bécue-Bertaut, M. & Pagès, J. Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data. *Comput. Stat. Data Anal.* **52**, 3255–3268 (2008).

274. Escofier, B. & Pagès, J. Multiple factor analysis (AFMULT package). *Comput. Stat. Data Anal.* **18**, 121–140 (1994).

275. Kéfi, S. et al. More than a meal... integrating non-feeding interactions into food webs. *Ecol. Lett.* **15**, 291–300 (2012).

276. Rosseel, Y. lavaan: An R package for structural equation modeling. *J. Stat. Softw.* **48**, 1–36 (2012).

277. Wolfgang Wagner. *Europäische Schmetterlinge und ihre Ökologie*. http://www.pyrgus.de/.

## Acknowledgements

The work was partly funded by the DFG Priority Program 1374 'Infrastructure-Biodiversity-Exploratories', and by Senckenberg Biodiversity and Climate Research Center. The soil analyses (EK, SM) was funded by the DFG (KA 1590/8-5, MA 4436/1-5). DB, ASZ, KB, KJ and VW have received funding in the context of Resilience DFG project 413730012. ASZ was supported by the RSF 23-14-00201 grant. Fieldwork permits were issued by the state environmental offices of Baden-Württemberg, Thüringen, and Brandenburg. The authors thank Konstans Wells, Kirsten Reichel-Jung, Sonja Gockel, Kerstin Wiesner, Katrin Lorenzen, Andreas Hemp, Martin Gorke maintained the plot and project infrastructure; Simone Pfeiffer, Maren Gleisberg, Christiane Fischer, Jule Mangels and Victoria Grießmeier for administrative support, and Jens Nieschulze, Michael Owonibi and Andreas Ostrowski for database management. Eduard Linsenmair, Dominik Hessenmöller, Daniel Prati, Ernst-Detlef Schulze, Wolfgang W. Weisser and Elisabeth Kalko helped establish the Biodiversity Exploratories project. The administration of the Hainich National Park, the UNESCO Biosphere Reserves Swabian Alb and Schorfheide-Chorin and all land owners provided logistical support. Tom Lachaise, Jörg Overmann and Johannes Sikorski contributed data. Icons were acquired and adapted (colour, width-height ratio) from Phylopic.org. Lepidoptera, fungi, secondary consumer arthropods, bats, protists, Oribatid mites: public domain. Birds: Maxime Dahirel (CC BY 3.0 Deed). Collembola: Birgit Lang (CC BY 3.0 Deed). Bacteria: Matt Crook (CC BY-SA 3.0 Deed). Hare: Jan A. Venter, Herbert H. T. Prins, David A. Balfour & Rob Slotow (vectorised by T. Michael Keesey) (CC BY 3.0 Deed). Tortoise: Andrew A. Farke, shell lines added by Yan Wong (CC BY 3.0 Deed). Primary consumer arthropods: Gareth Monger (CC

BY 3.0 Deed). Link to the corresponding licences: CC BY 3.0 Deed: https://creativecommons.org/licenses/by/3.0/. CC BY-SA 3.0 Deed: https://creativecommons.org/licenses/by-sa/3.0/.

## Author contributions

M.N., F.D.S. and P.M. designed the study. M.N. and P.M. conducted the analyses with inputs from G.L.P. and A.L.B. M.N., P.M., G.L.P., D.B., F.T.d.V., J.B., A.M.F.D., S.G., K.G., A.M., R.A.S., N.K.S., J.A.T., A.S.Z. participated to workshops and expert discussions to define guild-specific trait lists and hypotheses. M.N. and P.M. wrote the manuscript with significant inputs from G.L.P., A.L.B., D.B., J.B., S.G., J.A.T., M.M.G., E.K., K.B., K. Jung, J. K., C.P., M.C.R., M. Schlöter, S. Schulz, M. Staab, M.v.K. and V.W. G.L.P., D.B., J.B., A.M.F.D., K.G., R.S., N.S., J.T., A.Z., M.G., K. John, K. Jung, E.K., J.K., C.P., M. Schloter, S. Schulz, M. Staab, V.W., A.A., S.B., R.S.B., R.B., M.B., F.B., K.D., H.Y.G., N.H., J.H., K.J., V.H.K, T.K., S.M., J.M., S.C.R., N.V.S., I.S., M.S., S. Seibold, S.A.S., E.S., M.T., M.v.K., T.W., M.F. and P.M. contributed data. All authors commented on the manuscript. Author order was determined as follow: main authors, workshop and discussion participants (alphabetical), other authors with significant input (alphabetical), other data contributors (alphabetical), senior author.

## Funding

Open access funding provided by University of Bergen.

## Competing interests

The authors declare no competing interests.

## Additional information

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s41467-024-45113-5.

**Correspondence** and requests for materials should be addressed to Margot Neyret or Peter Manning.

**Peer review information** *Nature Communications* thanks Bertrand Fournier and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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© The Author(s) 2024
Margot Neyret Ⓓ1,2, Gaëtane Le Provost Ⓒ3, Andrea Larissa Boesing¹, Florian D. Schneider Ⓒ1,4, Dennis Baulechner Ⓒ5,
Joana Bergmann Ⓒ6, Franciska T. de Vries Ⓒ7, Anna Maria Fiore-Donno Ⓒ8, Stefan Geisen⁹, Kezia Goldmann Ⓒ10,
Anna Merges¹, Ruslan A. Saifutdinov¹¹, Nadja K. Simons¹²,¹³, Joseph A. Tobias Ⓒ14, Andrey S. Zaitsev Ⓒ5,¹¹,¹⁵,
Martin M. Gossner Ⓒ16,¹7, Kirsten Jung Ⓒ18, Ellen Kandeler¹⁹, Jochen Krauss Ⓒ20, Caterina Penone Ⓒ21,
Michael Schloter²²,²³, Stefanie Schulz Ⓒ22, Michael Staab Ⓒ12, Volkmar Wolters Ⓒ5, Antonios Apostolakis Ⓒ24,25,
Klaus Birkhofer²⁶, Steffen Boch Ⓒ27, Runa S. Boeddinghaus Ⓒ19,28, Ralph Bolliger Ⓒ21, Michael Bonkowski Ⓒ8,
François Buscot Ⓒ10,29, Kenneth Dumack Ⓒ8, Markus Fischer Ⓒ21, Huei Ying Gan³⁰, Johannes Heinze Ⓒ31,
Norbert Hölzel Ⓒ32, Katharina John⁵, Valentin H. Klaus Ⓒ33,34, Till Kleinebecker Ⓒ35,36, Sven Marhan¹⁹, Jörg Müller³⁷,
Swen C. Renner³⁸, Matthias C. Rillig Ⓒ39, Noëlle V. Schenk Ⓒ21, Ingo Schöning Ⓒ24, Marion Schrumpf Ⓒ24,
Sebastian Seibold Ⓒ40,41, Stephanie A. Socher Ⓒ42, Emily F. Solly Ⓒ43, Miriam Teuscher⁴⁴, Mark van Kleunen Ⓒ45,46,
Tesfaye Wubet Ⓒ29,47 & Peter Manning Ⓒ1,48 Ⓒ

¹Senckenberg Biodiversity and Climate Research Centre, Frankfurt, Germany. ²Laboratoire d'Écologie Alpine, Université Grenoble Alpes - CNRS - Université Savoie Mont Blanc, Grenoble, France. ³INRAE, Bordeaux Sciences Agro, ISVV, SAVE, Villenave d'Ornon, France. ⁴ISOE - Institute for social-ecological research, Frankfurt am Main, Germany. ⁵Justus Liebig University, Department of Animal Ecology, Giessen, Germany. ⁶Leibniz Center for Agricultural Landscape Research (ZALF), Müncheberg, Germany. ⁷Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands. ⁸Terrestrial Ecology, Institute of Zoology, University of Cologne, Köln, Germany. ⁹Laboratory of Nematology, Wageningen University and Research, Wageningen, The Netherlands. ¹⁰Helmholtz Centre for Environmental Research (UFZ), Soil Ecology Department, Halle/Saale, Germany. ¹¹A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, Russia. ¹²Ecological Networks, Technical University Darmstadt, Darmstadt, Germany. ¹³Applied Biodiversity Sciences, University of Würzburg, Würzburg, Germany. ¹⁴Department of Life Sciences, Imperial College London, Ascot, UK. ¹⁵Senckenberg Museum for Natural History Görlitz, Görlitz, Germany. ¹⁶Forest Entomology, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland. ¹⁷Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, Zürich, Switzerland. ¹⁸Institut of Evolutionary Ecology and Conservation Genomics, Ulm University, Ulm, Germany. ¹⁹Department of Soil Biology, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany. ²⁰Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Würzburg, Germany. ²¹Institute of Plant Sciences, University of Bern, Bern, Switzerland. ²²Helmholtz Zentrum Muenchen, Research Unit for Comparative Microbiome Analysis, Oberschleissheim, Germany. ²³Chair of Environmental Microbiology, Technical University of Munich, Freising, Germany. ²⁴Department of Biogeochemical Processes, Max-Planck-Institute for Biogeochemistry, Jena, Germany. ²⁵Department of Crop Sciences, University of Göttingen, Göttingen, Germany. ²⁶Department of Ecology, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany. ²⁷Swiss Federal Research Institute WSL, Birmensdorf, Switzerland. ²⁸Department Plant Production and Production Related Environmental Protection, Center for Agricultural Technology Augus-tenberg (LTZ), Karlsruhe, Germany. ²⁹German Centre for Integrative Biodiversity Research (iDiv) Halle - Jena-, Leipzig, Germany. ³⁰Senckenberg Centre for Human Evolution and Palaeoenvironments Tübingen (SHEP), Tübingen, Germany. ³¹Department of Biodiversity, Heinz Sielmann Foundation, Wustermark, Germany. ³²Institute of Landscape Ecology, University of Münster, Münster, Germany. ³³Institute of Agricultural Sciences, ETH Zürich, Zürich, Switzerland. ³⁴Forage Production and Grassland Systems, Agroscope, Zürich, Switzerland. ³⁵Institute for Landscape Ecology and Resources Man-agement (ILR), Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig University Giessen, Giessen, Germany. ³⁶Centre for International Development and Environmental Research (ZEU), Justus Liebig University Giessen, Giessen, Germany. ³⁷Department of Nature Conservation, Heinz Sielmann Foundation, Wustermark, Germany. ³⁸Ornithology, Natural History Museum Vienna, Vienna, Austria, Germany. ³⁹Freie Universität Berlin, Institute of Biology, Berlin, Germany. ⁴⁰Technical University of Munich, TUM School of Life Sciences, Freising, Germany. ⁴¹TUD Dresden University of Technology, Forest Zoology, Tharandt, Germany. ⁴²Paris Lodron University Salzburg, Department Environment and Biodiversity, Salzburg, Austria. ⁴³Helmholtz Centre for Environmental Research (UFZ), Computation Hydrosystems Department, Leipzig, Germany. ⁴⁴University of Göttingen, Centre of Biodiversity and Sustainable Land Use, Göttingen, Germany. ⁴⁵Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China. ⁴⁶Ecology, Department of Biology, University of Konstanz, Konstanz, Germany. ⁴⁷Helmholtz Centre for Environmental Research (UFZ), Community Ecology Department, Halle/Saale, Germany. ⁴⁸Department of Biological Sciences, University of Bergen, Bergen, Norway. e-mail: margot.neyret@univ-grenoble-alpes.fr; peter.manning@uib.no
Margot Neyret Ⓓ1,2, Gaëtane Le Provost Ⓒ3, Andrea Larissa Boesing¹, Florian D. Schneider Ⓒ1,4, Dennis Baulechner Ⓒ5, Joana Bergmann Ⓒ6, Franciska T. de Vries Ⓒ7, Anna Maria Fiore-Donno Ⓒ8, Stefan Geisen⁹, Kezia Goldmann Ⓒ10, Anna Merges¹, Ruslan A. Saifutdinov¹¹, Nadja K. Simons¹²,¹³, Joseph A. Tobias Ⓒ14, Andrey S. Zaitsev Ⓒ5,¹¹,¹⁵, Martin M. Gossner Ⓒ16,¹⁷, Kirsten Jung Ⓒ18, Ellen Kandeler¹⁹, Jochen Krauss Ⓒ20, Caterina Penone Ⓒ21, Michael Schloter²²,²³, Stefanie Schulz Ⓒ22, Michael Staab Ⓒ12, Volkmar Wolters Ⓒ5, Antonios Apostolakis Ⓒ24,25, Klaus Birkhofer²⁶, Steffen Boch Ⓒ27, Runa S. Boeddinghaus Ⓒ19,28, Ralph Bolliger Ⓒ21, Michael Bonkowski Ⓒ8, François Buscot Ⓒ10,29, Kenneth Dumack Ⓒ8, Markus Fischer Ⓒ21, Huei Ying Gan³⁰, Johannes Heinze Ⓒ31, Norbert Hölzel Ⓒ32, Katharina John⁵, Valentin H. Klaus Ⓒ33,34, Till Kleinebecker Ⓒ35,36, Sven Marhan¹⁹, Jörg Müller³⁷, Swen C. Renner³⁸, Matthias C. Rillig Ⓒ39, Noëlle V. Schenk Ⓒ21, Ingo Schöning Ⓒ24, Marion Schrumpf Ⓒ24, Sebastian Seibold Ⓒ40,41, Stephanie A. Socher Ⓒ42, Emily F. Solly Ⓒ43, Miriam Teuscher⁴⁴, Mark van Kleunen Ⓒ45,46, Tesfaye Wubet Ⓒ29,47 & Peter Manning Ⓒ1,48 Ⓒ

¹Senckenberg Biodiversity and Climate Research Centre, Frankfurt, Germany. ²Laboratoire d'Écologie Alpine, Université Grenoble Alpes - CNRS - Université Savoie Mont Blanc, Grenoble, France. ³INRAE, Bordeaux Sciences Agro, ISVV, SAVE, Villenave d'Ornon, France. ⁴ISOE - Institute for social-ecological research, Frankfurt am Main, Germany. ⁵Justus Liebig University, Department of Animal Ecology, Giessen, Germany. ⁶Leibniz Center for Agricultural Landscape Research (ZALF), Müncheberg, Germany. ⁷Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands. ⁸Terrestrial Ecology, Institute of Zoology, University of Cologne, Köln, Germany. ⁹Laboratory of Nematology, Wageningen University and Research, Wageningen, The Netherlands. ¹⁰Helmholtz Centre for Environmental Research (UFZ), Soil Ecology Department, Halle/Saale, Germany. ¹¹A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, Russia. ¹²Ecological Networks, Technical University Darmstadt, Darmstadt, Germany. ¹³Applied Biodiversity Sciences, University of Würzburg, Würzburg, Germany. ¹⁴Department of Life Sciences, Imperial College London, Ascot, UK. ¹⁵Senckenberg Museum for Natural History Görlitz, Görlitz, Germany. ¹⁶Forest Entomology, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland. ¹⁷Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, Zürich, Switzerland. ¹⁸Institut of Evolutionary Ecology and Conservation Genomics, Ulm University, Ulm, Germany. ¹⁹Department of Soil Biology, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany. ²⁰Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Würzburg, Germany. ²¹Institute of Plant Sciences, University of Bern, Bern, Switzerland. ²²Helmholtz Zentrum Muenchen, Research Unit for Comparative Microbiome Analysis, Oberschleissheim, Germany. ²³Chair of Environmental Microbiology, Technical University of Munich, Freising, Germany. ²⁴Department of Biogeochemical Processes, Max-Planck-Institute for Biogeochemistry, Jena, Germany. ²⁵Department of Crop Sciences, University of Göttingen, Göttingen, Germany. ²⁶Department of Ecology, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany. ²⁷Swiss Federal Research Institute WSL, Birmensdorf, Switzerland. ²⁸Department Plant Production and Production Related Environmental Protection, Center for Agricultural Technology Augus-tenberg (LTZ), Karlsruhe, Germany. ²⁹German Centre for Integrative Biodiversity Research (iDiv) Halle - Jena-, Leipzig, Germany. ³⁰Senckenberg Centre for Human Evolution and Palaeoenvironments Tübingen (SHEP), Tübingen, Germany. ³¹Department of Biodiversity, Heinz Sielmann Foundation, Wustermark, Germany. ³²Institute of Landscape Ecology, University of Münster, Münster, Germany. ³³Institute of Agricultural Sciences, ETH Zürich, Zürich, Switzerland. ³⁴Forage Production and Grassland Systems, Agroscope, Zürich, Switzerland. ³⁵Institute for Landscape Ecology and Resources Man-agement (ILR), Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig University Giessen, Giessen, Germany. ³⁶Centre for International Development and Environmental Research (ZEU), Justus Liebig University Giessen, Giessen, Germany. ³⁷Department of Nature Conservation, Heinz Sielmann Foundation, Wustermark, Germany. ³⁸Ornithology, Natural History Museum Vienna, Vienna, Austria, Germany. ³⁹Freie Universität Berlin, Institute of Biology, Berlin, Germany. ⁴⁰Technical University of Munich, TUM School of Life Sciences, Freising, Germany. ⁴¹TUD Dresden University of Technology, Forest Zoology, Tharandt, Germany. ⁴²Paris Lodron University Salzburg, Department Environment and Biodiversity, Salzburg, Austria. ⁴³Helmholtz Centre for Environmental Research (UFZ), Computation Hydrosystems Department, Leipzig, Germany. ⁴⁴University of Göttingen, Centre of Biodiversity and Sustainable Land Use, Göttingen, Germany. ⁴⁵Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China. ⁴⁶Ecology, Department of Biology, University of Konstanz, Konstanz, Germany. ⁴⁷Helmholtz Centre for Environmental Research (UFZ), Community Ecology Department, Halle/Saale, Germany. ⁴⁸Department of Biological Sciences, University of Bergen, Bergen, Norway. e-mail: margot.neyret@univ-grenoble-alpes.fr; peter.manning@uib.no