Abstract
Pesticides are widely distributed in soils1,2,3, yet their effects on soil biodiversity remain poorly understood4,5,6,7. Here we examined the effects of 63 pesticides on soil archaea, bacteria, fungi, protists, nematodes, arthropods and key functional gene groups across 373 sites spanning woodlands, grasslands and croplands in 26 European countries. Pesticide residues were detected in 70% of sites and emerged as the second strongest driver of soil biodiversity patterns after soil properties. Our analysis further revealed organism- and function-specific patterns, emphasizing complex and widespread non-target effects on soil biodiversity. Pesticides altered microbial functions, including phosphorus and nitrogen cycling, and suppressed beneficial taxa, including arbuscular mycorrhizal fungi and bacterivore nematodes. Our findings highlight the need to integrate functional and taxonomic characteristics into future risk assessment methodology to safeguard soil biodiversity, a cornerstone of ecosystem functioning.
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Global variation in plant-beneficial bacteria in soil under pesticide stress
The soil microbiome as an indicator of ecosystem multifunctionality in European soils
Soil biodiversity effects on ecosystems
Data availability
Pesticide data supporting this study are available from European Soil Data Centre (ESDAC) (https://esdac.jrc.ec.europa.eu/content/pesticides-and-soil-biodiversity), subject to registration and a data sharing agreement, owing to the confidential nature of the measurements. The Pesticide Properties Database is accessible at https://sitem.herts.ac.uk/aeru/ppdb/. The database from the Herbicide Resistance Action Committee (HRAC) is accessible at https://hracglobal.com/files/2024-HRAC-GLOBAL-HERBICIDE-MOA-CLASSIFICATION-POSTERold.pdf, the database from the Fungicide Resistance Action Committee (FRAC) is accessible at https://www.frac.info/fungicide-resistance-management/by-frac-mode-of-action-group/#open-tour, and the one from Insecticide Resistance Action Committee (IRAC) is accessible at https://irac-online.org/mode-of-action/. The raw data (DNA sequences) generated in this study have been deposited in the Sequence Read Archive (SRA) database under BioProject ID PRJNA1118194 for archaeal 16S data, BioProject ID PRJNA952168 for bacterial 16S and fungal ITS data, BioProject ID PRJNA985135 for eukaryotic 18S data and BioProject ID PRJNA1032917 for metagenomic data. The Global database of soil nematodes is available at https://github.com/hooge104/2020_global_nematode_dataset/blob/master/data/nematode_full_dataset_wBiome.csv. The sampling site environmental metadata used in this study are available from ESDAC (https://esdac.jrc.ec.europa.eu/content/soil-biodiversity-dna-eukaryotes).
Code availability
All R scripts relating pesticide analysis to soil biodiversity are available from ESDAC (https://esdac.jrc.ec.europa.eu/content/pesticides-and-soil-biodiversity).
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Acknowledgements
The LUCAS Survey is coordinated by Unit E4 of the Statistical Office of the European Union (EUROSTAT). The LUCAS Soil sample collection and laboratory analysis are supported by the Directorate-General Environment (DG-ENV), Directorate-General Agriculture and Rural Development (DG-AGRI), Directorate-General Climate Action (DG-CLIMA) and Directorate-General for Health and Food Safety (DG-SANTE) of the European Commission. We also thank EFSA for supportive advice. M.G.A.v.d.H. and F.R. acknowledge funding of the Swiss National Science Foundation (grant 310030_188799). M.B. was funded by the Swedish Research Councils Formas (grant 2020–00807). This work was realized in collaboration with the European Commission’s Joint Research Centre under the Collaborative Doctoral Partnership Agreements no. 35533 with the Universidade de Vigo (UVIGO) and no. 35594 with the University of Zurich (UZH).
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M.G.A.v.d.H., M.J.I.B. and A.O. conceptualized the study. J.K., M.L., C.B., M.G.A.v.d.H., M.J.I.B. and A.O. undertook the design and methodology. J.K., M.L., C.B., O.D. and V.M. were involved in data analysis. J.K., M.L, C.B., O.D., V.M., A.F. and M.B. were involved in data interpretation. F.R., P.P., A.J., L.T., A.O., M.G.A.v.d.H. and M.J.I.B supervised the work. J.K. and M.L. wrote the original draft. All authors contributed to reviewing and editing the final manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Sampling sites.
Maps showing locations where soil biodiversity and pesticide residues were measured across five ecosystem types for (a) annual croplands (AC; n = 210), (b) permanent croplands (PC; n = 34), (c) former croplands recently converted to grasslands (FC; n = 19), (d) extensive grasslands (EG; n = 97) and (e) woodlands (WL; n = 13) respectively. Twenty-six countries in darker shades include sampling sites among the 373 investigated sites. Map from Natural Earth (Creative Commons CC0).
Extended Data Fig. 2 Maps of pesticide distribution per ecosystem type.
Maps showing (a) the number of pesticides and (b) cumulative concentration of pesticide residues (in mg/kg) per ecosystem type across Europe (n = 373 sites): annual croplands (AC), permanent croplands (PC), former croplands recently converted to grasslands (FC), extensive grasslands (EG) and woodlands (WL). For each location, the height of the bar is proportional to the number of pesticide residues (or cumulative concentration) detected per site, respectively. For better visualisation, the pesticide number bars were divided by two, while the concentration bars multiplied by 20. Map from Natural Earth (Creative Commons CC0).
Extended Data Fig. 3 Pesticide cumulative concentration and regression with number of pesticides.
At n = 373 sites: (a) Boxplots (individual data points together with the median and its associated variation (1.5 x interquartile)) of pesticide cumulative concentration (in mg/kg) across ecosystem types. Different letters indicate significant differences (two-sided pairwise Wilcoxon multiple comparison test (with a Benjamini & Hochberg’s correction)) between ecosystem types (for p-values, AC-PC = 0.069, AC-FC = 0.051, AC-EG<2e-16, AC-WL = 4.9e-06, PC-FC = 0.681, PC-EG = 0.005, PC-WL = 0.005, FC-EG = 0.069, FC-WL = 0.017, EG-WL = 0.054). (b) Regression models between the pesticide cumulative concentration and the number of pesticides detected per site. R-squared (R²) and p-value (p) are derived from a linear model (grey zone indicates the 95% confidence interval).
Extended Data Fig. 4 Pesticide distribution boxplot per ecosystem type.
Number of sites in which each pesticide was detected (summed values per pesticide) per ecosystem type (annual croplands (AC), permanent croplands (PC), former croplands recently converted to grasslands (FC), extensive grasslands (EG) and woodlands (WL); n = 373 sites).
Extended Data Fig. 5 Soil biodiversity responses to pesticides in croplands.
For croplands only (n = 244 sites), soil biodiversity (assessed by metabarcoding) responses to pesticide concentrations (herbicides H, metabolite of a herbicide MH, fungicides F or insecticides I). Positive or negative relationship of each pesticide concentration retained in the models with each (a) soil organism observed richness, (b) Shannon diversity, (c) functional group relative abundance and (d) multidiversity. Horizontal bars correspond to the variable importance (VIP) coloured in green (positive relationship) or pink (negative), according to the coefficient sign of each pesticide in the associated generalised linear model (GLM). Variable importance was calculated on the feature-selected GLM including pesticide concentrations, soil properties, climate and ecosystem type information. A correlation matrix for initial environmental and predictors is available in Extended Data Fig. 7 below. These analyses focus on croplands only (n = 244 sites), while analyses for all ecosystem types (n = 373 sites) are presented in Supplementary Data 3, Fig. 1).
Extended Data Fig. 6 Soil C, N, P functional gene responses to pesticides in croplands.
For croplands only (n = 234 sites), soil C, N, P functional gene groups responses to pesticide concentrations (herbicides H, metabolite of a herbicide MH, fungicides F or insecticides I). Positive or negative relationship of concentration of pesticides retained in the GLMs with the diversity of each functional gene involved in the C, N, and P cycles. Horizontal bars correspond to the variable importance (VIP) coloured in green (positive relationship) or pink (negative), according to the coefficient sign of each pesticide in the associated GLM. Variable importance was calculated based on the feature-selected GLM, including pesticide concentrations, soil properties, climate, and ecosystem type information. These analyses focus on croplands only (n = 234 sites), while analyses including croplands and grasslands (n = 349 sites) are presented in Supplementary Data 3, Fig. 2.
Extended Data Fig. 7 Correlation matrix of initial predictors for croplands.
For croplands only (n = 244 sites), Pearson (linear) correlation matrix between the initial set of predictors (i.e., before feature-selection) used in the generalised linear models, i.e., all environmental variables next to the most occurring pesticides across croplands (28 pesticides out of 63, all other pesticides with near-zero variance are not kept).
Extended Data Fig. 8 Explained variance of Shannon diversity in croplands.
For croplands only (n = 244 sites), explained variance (in %) of Shannon diversity by selected variables: pesticide residue concentrations (red), soil properties (brown), climate (blue), ecosystem type (green) together with the shared variance (yellow). See Extended Data Fig. 5 for the detailed pesticide concentrations and Supplementary Data 2, Table 7 for the selected soil properties and climatic variables retained per GLM. This figure shows the results when the data of croplands only are analysed (n = 244 sites) while the results in Supplementary Data 3, Fig. 4 are based on all ecosystem types (n = 373 sites for metabarcoding analyses).
Supplementary information
Supplementary Information
This file contains Supplementary Table 1, Supplementary Results 1–4, Supplementary Figs. 1–5, Supplementary Discussion, additional information about Supplementary Data 1–8 and references.
Reporting Summary
Supplementary Data 1
Classification table for all pesticides and metabolites. See main Supplementary Information file for further description.
Supplementary Data 2
Tables 1–16 for croplands only. See main Supplementary Information file for further description.
Supplementary Data 3
Figures for all ecosystem types. See main Supplementary Information file for further description.
Supplementary Data 4
Tables 1–20 for all ecosystem types. See main Supplementary Information file for further description.
Supplementary Data 5
Partial plots of the GLMs for croplands only. See main Supplementary Information file for further description.
Supplementary Data 6
Partial plots of the GLM for all ecosystem types. See main Supplementary Information file for further description.
Supplementary Data7
Supplementary tables for environmental variable differences for pesticide detection in croplands only. See main Supplementary Information file for further description.
Supplementary Data 8
Supplementary tables for environmental variable differences for pesticide detection in all ecosystem types. See main Supplementary Information file for further description.
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Köninger, J., Labouyrie, M., Ballabio, C. et al. Pesticide residues alter taxonomic and functional biodiversity in soils.
Nature (2026). https://doi.org/10.1038/s41586-025-09991-z
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DOI: https://doi.org/10.1038/s41586-025-09991-z
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