Ecology

An, Z., Guo, F., Chen, Y., Bai, G. & Chen, Z. Rhizosphere bacterial and fungal communities during the growth of Angelica sinensis seedlings cultivated in an Alpine uncultivated meadow soil. PeerJ 8, e8541. https://doi.org/10.7717/peerj.8541 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Munkholm, L. J., Heck, R. J. & Deen, B. Long-term rotation and tillage effects on soil structure and crop yield. Soil Tillage Res. 127, 85–91. https://doi.org/10.1016/j.still.2012.02.007 (2013).Article 

Google Scholar 
Jiao, X. L. et al. Effects of maize rotation on the physicochemical properties and microbial communities of American ginseng cultivated soil. Sci. Rep. 9, 8615. https://doi.org/10.1038/s41598-019-44530-7 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wang, X., Chen, Y., Guo, F., Yuan, H. & Guo, Y. Effects of medicinal crop stubbles on physiological and biochemical characteristics of Angelica sinensis seedings. J. Chin. Med. Mater. 40, 2002–2006 (2017).
Google Scholar 
Jin, Y. et al. Effect of various crop residues on growth and disease resisitance of Angelica sinensis seedlings in Min County. Acta Pratacul. Sin. 27, 69–78 (2018).MathSciNet 

Google Scholar 
Bai, G., Guo, F., Chen, Y., Yuan, H. & Xiao, W. Differences in physiological resistance traits of Angelica sinensis seedlings from uncultivated and cultivated fields in Min County. Acta Pratacul. Sin. 28, 86–95 (2019).
Google Scholar 
Bai, G. et al. Regulated effects of preceding crop on soil property and cultivating seedlings for Angelica sinensis on cultivated farmland. Chin. J. Eco-Agric. 28, 701–712. https://doi.org/10.13930/j.cnki.cjea.190719 (2020).Article 
CAS 

Google Scholar 
Mendes, R., Garbeva, P. & Raaijmakers, J. M. The rhizosphere microbiome: Significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiol. Rev. 37, 634–663 (2013).Article 
CAS 
PubMed 

Google Scholar 
Tkacz, A., Cheema, J., Chandra, G., Grant, A. & Poole, P. S. Stability and succession of the rhizosphere microbiota depends upon plant type and soil composition. Int. Soc. Microb. Ecol. 9, 2349–2359. https://doi.org/10.1038/ismej.2015.41 (2015).Article 
CAS 

Google Scholar 
Berg, G. et al. Microbiome definition re-visited: Old concepts and new challenges. Microbiome 8, 103. https://doi.org/10.1186/s40168-020-00875-0 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Chaparro, J. M., Badri, D. V. & Vivanco, J. M. Rhizosphere microbiome assemblage is affected by plant development. ISME J. 8, 790–803. https://doi.org/10.1038/ismej.2013.196 (2014).Article 
CAS 
PubMed 

Google Scholar 
Uroz, S. et al. Specific impacts of beech and Norway spruce on the structure and diversity of the rhizosphere and soil microbial communities. Sci. Rep. 6, 27756. https://doi.org/10.1038/srep27756 (2016).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chamberlain, L. A. et al. Crop rotation, but not cover crops, influenced soil bacterial community composition in a corn-soybean system in southern Wisconsin. Appl. Soil Ecol. 154, 103603. https://doi.org/10.1016/j.apsoil.2020.103603 (2020).Article 

Google Scholar 
Classen, A. T. et al. Direct and indirect effects of climate change on soil microbial and soil microbial-plant interactions: What lies ahead?. Ecosphere 6, 130. https://doi.org/10.1890/es15-00217.1 (2015).Article 

Google Scholar 
Tiemann, L. K. et al. Crop rotational diversity enhances belowground communities and functions in an agroecosystem. Ecol. Lett. 18, 761–771. https://doi.org/10.1111/ele.12453 (2015).Article 
CAS 
PubMed 

Google Scholar 
Maldonado, S. et al. Enhanced crop productivity and sustainability by using native phosphate solubilizing rhizobacteria in the agriculture of arid zones. Front. Sustain. Food Syst. 4, 607355. https://doi.org/10.3389/fsufs.2020.607355 (2020).Article 

Google Scholar 
Gómez Expósito, R., de Bruijn, I., Postma, J. & Raaijmakers, J. M. Current insights into the role of rhizosphere bacteria in disease suppressive soils. Front. Microbiol.y 8, 2529. https://doi.org/10.3389/fmicb.2017.02529 (2017).Article 

Google Scholar 
Li, X., Rui, J., Mao, Y., Yannarell, A. & Mackie, R. Dynamics of the bacterial community structure in the rhizosphere of a maize cultivar. Soil Biol. Biochem. 68, 392–401. https://doi.org/10.1016/j.soilbio.2013.10.017 (2014).Article 
CAS 

Google Scholar 
Fierer, N. et al. Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients. Int. Soc. Microb. Ecol. 6, 1007–1017. https://doi.org/10.1038/ismej.2011.159 (2012).Article 
CAS 

Google Scholar 
Kuffner, M. et al. Culturable bacteria from Zn- and Cd-accumulating Salix caprea with differential effects on plant growth and heavy metal availability. J. Appl. Microbiol. 108, 1471–1484. https://doi.org/10.1111/j.1365-2672.2010.04670.x (2010).Article 
CAS 
PubMed 

Google Scholar 
De Corato, U. Disease-suppressive compost enhances natural soil suppressiveness against soil-borne plant pathogens: A critical review. Rhizosphere 13, 100192. https://doi.org/10.1016/j.rhisph.2020.100192 (2020).Article 

Google Scholar 
Brookes, P. C., Landman, A., Pruden, G. & Jenkinson, D. S. Chloroform fumigation chloroform fumigation and the release of soil nitrogen: a rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol. Biochem. 17, 837–842 (1985).Article 
CAS 

Google Scholar 
Arnebrant, K. & Schnürer, J. Changes in atp content during and after chloroform fumigation. Soil Biol. Biochem. 22, 875–877 (1990).Article 
CAS 

Google Scholar 
Toju, H. et al. Community composition of root-associated fungi in a Quercus-dominated temperate forest: “codominance” of mycorrhizal and root-endophytic fungi. Ecol. Evol. 3, 1281–1293. https://doi.org/10.1002/ece3.546 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Magoč, T. & Salzberg, S. L. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57–59. https://doi.org/10.1038/nmeth.2276 (2013).Article 
CAS 
PubMed 

Google Scholar 
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Haas, B. J. et al. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res. 21, 494–504. https://doi.org/10.1101/gr.112730.110 (2011).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Edgar, R. C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998. https://doi.org/10.1038/nmeth.2604 (2013).Article 
CAS 
PubMed 

Google Scholar 
Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267. https://doi.org/10.1128/AEM.00062-07 (2007).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596. https://doi.org/10.1093/nar/gks1219 (2013).Article 
CAS 
PubMed 

Google Scholar 
Edgar, R. C. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Louca, S., Parfrey, L. W. & Doebeli, M. Decoupling function and taxonomy in the global ocean microbiome. Science 353, 1272 (2016).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Nguyen, N. H. et al. FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248. https://doi.org/10.1016/j.funeco.2015.06.006 (2016).Article 

Google Scholar 
Sisk-Hackworth, L., Ortiz-Velez, A., Reed, M. B. & Kelley, S. T. Compositional data analysis of periodontal disease microbial communities. Front. Microbiol. 12, 617949. https://doi.org/10.3389/fmicb.2021.617949 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Khan, M. A. W. et al. Deforestation impacts network co-occurrence patterns of microbial communities in Amazon soils. FEMS Microbiol. Ecol. 95, fiy230. https://doi.org/10.1093/femsec/fiy230 (2019).Article 
CAS 
PubMed 

Google Scholar 
Zhang, B., Zhang, J., Liu, Y., Shi, P. & Wei, G. Co-occurrence patterns of soybean rhizosphere microbiome at a continental scale. Soil Biol. Biochem. 118, 178–186. https://doi.org/10.1016/j.soilbio.2017.12.011 (2018).Article 
CAS 

Google Scholar 
Huang, M., Jiang, L., Zou, Y., Xu, S. & Deng, G. Changes in soil microbial properties with no-tillage in Chinese cropping systems. Biol. Fertil. Soils 49, 373–377. https://doi.org/10.1007/s00374-013-0778-6 (2013).Article 

Google Scholar 
Unger, P. W. & Cassel, D. K. Tillage implement disturbance effects on soil properties related to soil and water conservation: A literature review. Soil Tillage Res. 19, 363–382 (1991).Article 

Google Scholar 
Alvarez, R. & Steinbach, H. S. A review of the effects of tillage systems on some soil physical properties, water content, nitrate availability and crops yield in the Argentine Pampas. Soil Tillage Res. 104, 1–15. https://doi.org/10.1016/j.still.2009.02.005 (2009).Article 

Google Scholar 
Essel, E. et al. Bacterial and fungal diversity in rhizosphere and bulk soil under different long-term tillage and cereal/legume rotation. Soil Tillage Res. 194, 104302. https://doi.org/10.1016/j.still.2019.104302 (2019).Article 

Google Scholar 
Zhu, Q., Wang, N., Duan, B., Wang, Q. & Wang, Y. Rhizosphere bacterial and fungal communities succession patterns related to growth of poplar fine roots. Sci. Total Environ. 756, 143839. https://doi.org/10.1016/j.scitotenv.2020.143839 (2021).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Guseva, K. et al. From diversity to complexity: Microbial networks in soils. Soil Biol. Biochem. 169, 108604. https://doi.org/10.1016/j.soilbio.2022.108604 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Jiang, B. et al. Analysis of microbial community structure and diversity in surrounding rock soil of different waste dump sites in fushun western opencast mine. Chemosphere 269, 128777. https://doi.org/10.1016/j.chemosphere.2020.128777 (2020).Article 
ADS 
MathSciNet 
CAS 
PubMed 

Google Scholar 
Liu, J. et al. Pecan plantation age influences the structures, ecological networks, and functions of soil microbial communities. Land Degrad. Dev. 33, 3294–3309. https://doi.org/10.1002/ldr.4389 (2022).Article 

Google Scholar 
Lv, X. et al. Strengthening insights in microbial ecological networks from theory to applications. mSystems 4, e00124-19. https://doi.org/10.1128/mSystems.00124-19 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Toju, H., Kishida, O., Katayama, N. & Takagi, K. Networks depicting the fine-scale co-occurrences of fungi in soil Horizons. PLoS ONE 11, e0165987. https://doi.org/10.1371/journal.pone.0165987 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chun, S. J., Cui, Y., Baek, S. H., Ahn, C. Y. & Oh, H. M. Seasonal succession of microbes in different size-fractions and their modular structures determined by both macro- and micro-environmental filtering in dynamic coastal waters. Sci. Total Environ. 784, 147046. https://doi.org/10.1016/j.scitotenv.2021.147046 (2021).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Cardinale, M., Grube, M., Erlacher, A., Quehenberger, J. & Berg, G. Bacterial networks and co-occurrence relationships in the lettuce root microbiota. Environ. Microbiol. 17, 239–252. https://doi.org/10.1111/1462-2920.12686 (2015).Article 
CAS 
PubMed 

Google Scholar 
Zhou, Z. et al. Increases in bacterial community network complexity induced by biochar-based fertilizer amendments to karst calcareous soil. Geoderma 337, 691–700. https://doi.org/10.1016/j.geoderma.2018.10.013 (2019).Article 
ADS 
CAS 

Google Scholar 
Olesen, J. M., Bascompte, J., Dupont, Y. L. & Jordano, P. The modularity of pollination networks. Proc. Natl. Acad. Sci. U.S.A. 104, 19891–19896. https://doi.org/10.1073/pnas.0706375104 (2007).Article 
ADS 
PubMed 
PubMed Central 
MATH 

Google Scholar 
Eisenhauer, N. et al. Root biomass and exudates link plant diversity with soil bacterial and fungal biomass. Sci. Rep. 7, 44641. https://doi.org/10.1038/srep44641 (2017).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hassan, M. K., McInroy, J. A. & Kloepper, J. W. The interactions of rhizodeposits with plant growth-promoting Rhizobacteria in the rhizosphere: A review. Agriculture 9, 142. https://doi.org/10.3390/agriculture9070142 (2019).Article 
CAS 

Google Scholar 
Sasse, J., Martinoia, E. & Northen, T. Feed your friends: Do plant exudates shape the root microbiome?. Trends Plant Sci. 23, 25–41. https://doi.org/10.1016/j.tplants.2017.09.003 (2018).Article 
CAS 
PubMed 

Google Scholar 
Zhang, F., Xu, X., Wang, G., Wu, B. & Xiao, Y. Medicago sativa and soil microbiome responses to Trichoderma as a biofertilizer in alkaline-saline soils. Appl. Soil Ecol. 153, 103573. https://doi.org/10.1016/j.apsoil.2020.103573 (2020).Article 

Google Scholar 
Woźniak, A. Chemical properties and enzyme activity of soil as affected by tillage system and previous crop. Agriculture 9, 262. https://doi.org/10.3390/agriculture9120262 (2019).Article 
CAS 

Google Scholar 
Choudhary, M. et al. Changes in soil biology under conservation agriculture based sustainable intensification of cereal systems in Indo-Gangetic Plains. Geoderma 313, 193–204. https://doi.org/10.1016/j.geoderma.2017.10.041 (2018).Article 
ADS 
CAS 

Google Scholar 
Ai, C. et al. Distinct responses of soil bacterial and fungal communities to changes in fertilization regime and crop rotation. Geoderma 319, 156–166. https://doi.org/10.1016/j.geoderma.2018.01.010 (2018).Article 
ADS 
CAS 

Google Scholar 
Gałązka, A., Gawyjołek, K., Perzyński, A., Gałązka, R. & Jerzy, K. Changes in enzymatic activities and microbial communities in soil under long-term maize monoculture and crop rotation. Pol. J. Environ. Stud. 26, 39–46. https://doi.org/10.15244/pjoes/64745 (2017).Article 
CAS 

Google Scholar 
Tremblay, C., Deslauriers, A., Lafond, J., Lajeunesse, J. & Paré, M. Effects of soil pH and fertilizers on haskap (Lonicera caerulea L) vegetative growth. Agriculture 9, 56. https://doi.org/10.3390/agriculture9030056 (2019).Article 
CAS 

Google Scholar 
Sirisuntornlak, N. et al. Interactive effects of silicon and soil pH on growth, yield and nutrient uptake of maize. SILICON 13, 289–299. https://doi.org/10.1007/s12633-020-00427-z (2021).Article 
CAS 

Google Scholar 
Xu, Y., Ge, Y., Song, J. & Rensing, C. Assembly of root-associated microbial community of typical rice cultivars in different soil types. Biol. Fertil. Soils 56, 249–260. https://doi.org/10.1007/s00374-019-01406-2 (2019).Article 
CAS 

Google Scholar 
Putranta, H., Permatasari, A. K., Sukma, T. A. & Dwandaru, W. S. B. The effect of pH, electrical conductivity, and nitrogen (N) in the soil at yogyakarta special region on tomato plant growth. TEM J.-Technol. Educ. Manag. Inform. 8, 860–865. https://doi.org/10.18421/TEM83-24 (2019).Article 

Google Scholar 
Wang, J. et al. Effects of alternate partial root-zone irrigation on soil microorganism and maize growth. Plant Soil 302, 45–52. https://doi.org/10.1007/s11104-007-9453-8 (2007).Article 
CAS 

Google Scholar 
Yang, X., Zhu, K., Loik, M. E. & Sun, W. Differential responses of soil bacteria and fungi to altered precipitation in a meadow steppe. Geoderma 384, 114812. https://doi.org/10.1016/j.geoderma.2020.114812 (2021).Article 
ADS 
CAS 

Google Scholar 
Balota, E. L., Colozzi Filho, A., Andrade, D. S. & Dick, R. P. Long-term tillage and crop rotation effects on microbial biomass and C and N mineralization in a Brazilian Oxisol. Soil Tillage Res. 77, 137–145. https://doi.org/10.1016/j.still.2003.12.003 (2004).Article 

Google Scholar 
Franchini, J., Crispino, C., Souza, R., Torres, E. & Hungria, M. Microbiological parameters as indicators of soil quality under various soil management and crop rotation systems in southern Brazil. Soil Tillage Res. 92, 18–29. https://doi.org/10.1016/j.still.2005.12.010 (2007).Article 

Google Scholar 
Li, X., Wang, T., Chang, S. X., Jiang, X. & Song, Y. Biochar increases soil microbial biomass but has variable effects on microbial diversity: A meta-analysis. Sci. Total Environ. 749, 141593. https://doi.org/10.1016/j.scitotenv.2020.141593 (2020).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Lynch, J. M. & Panting, L. M. Effects of season, cultivation and nitrogen fertiliser on the size of the soil microbial biomass. J. Sci. Food Agric. 33, 249–252 (1982).Article 
CAS 

Google Scholar 
Tan, G. et al. Effects of biochar application with fertilizer on soil microbial biomass and greenhouse gas emissions in a peanut cropping system. Environ. Technol. 42, 9–19. https://doi.org/10.1080/09593330.2019.1620344 (2021).Article 
CAS 
PubMed 

Google Scholar 
Liu, C. et al. Linkages between nutrient ratio and the microbial community in rhizosphere soil following fertilizer management. Environ. Res. 184, 109261. https://doi.org/10.1016/j.envres.2020.109261 (2020).Article 
CAS 
PubMed 

Google Scholar 
Li, H. et al. Film mulching, residue retention and N fertilization affect ammonia volatilization through soil labile N and C pools. Agric. Ecosyst. Environ. 308, 107272. https://doi.org/10.1016/j.agee.2020.107272 (2021).Article 
CAS 

Google Scholar 
Jiao, P. et al. Bacteria are more sensitive than fungi to moisture in eroded soil by natural grass vegetation restoration on the Loess Plateau. Sci. Total Environ. 756, 143899. https://doi.org/10.1016/j.scitotenv.2020.143899 (2021).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Sommer, J. et al. The tree species matters: Belowground carbon input and utilization in the myco-rhizosphere. Eur. J. Soil Biol. 81, 100–107. https://doi.org/10.1016/j.ejsobi.2017.07.001 (2017).Article 
CAS 

Google Scholar 
Yu, K., Pieterse, C. M. J., Bakker, P. A. H. M. & Berendsen, R. L. Beneficial microbes going underground of root immunity. Plant Cell Environ. 42, 2860–2870. https://doi.org/10.1111/pce.13632 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
de Varennes, A. & Goss, M. J. The tripartite symbiosis between legumes, rhizobia and indigenous mycorrhizal fungi is more efficient in undisturbed soil. Soil Biol. Biochem. 39, 2603–2607. https://doi.org/10.1016/j.soilbio.2007.05.007 (2007).Article 
CAS 

Google Scholar 
Wang, X. et al. Mycorrhizal symbiosis modulates the rhizosphere microbiota to promote rhizobia-legume symbiosis. Mol. Plant 14, 503–516. https://doi.org/10.1016/j.molp.2020.12.002 (2020).Article 
CAS 
PubMed 

Google Scholar 
Zhang, R., Vivanco, J. M. & Shen, Q. The unseen rhizosphere root-soil-microbe interactions for crop production. Curr. Opin. Microbiol. 37, 8–14. https://doi.org/10.1016/j.mib.2017.03.008 (2017).Article 
PubMed 

Google Scholar 
Berendsen, R. L., Pieterse, C. M. & Bakker, P. A. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486. https://doi.org/10.1016/j.tplants.2012.04.001 (2012).Article 
CAS 
PubMed 

Google Scholar  More

Forster D, Bittner L, Karkar S, Dunthorn M, Romac S, Audic S, et al. Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms. BMC Biol. 2015;13:16. http://bmcbiol.biomedcentral.com/articles/10.1186/s12915-015-0125-5.Article 
PubMed 
PubMed Central 

Google Scholar 
Galperin MY, Koonin EV. From complete genome sequence to ‘complete’ understanding? Trends Biotechnol. 2010;28:398–406. https://linkinghub.elsevier.com/retrieve/pii/S0167779910000892.Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Modha S, Robertson DL, Hughes J, Orton RJ. Quantifying and cataloguing unknown sequences within human microbiomes. mSystems. 2022;7:e01468–21. https://journals.asm.org/doi/10.1128/msystems.01468-21.Article 
PubMed 
PubMed Central 

Google Scholar 
Wyman SK, Avila-Herrera A, Nayfach S, Pollard KS. A most wanted list of conserved microbial protein families with no known domains. PLoS One. 2018;13:e0205749. https://dx.plos.org/10.1371/journal.pone.0205749.Bernard G, Pathmanathan JS, Lannes R, Lopez P, Bapteste E. Microbial dark matter investigations: how microbial studies transform biological knowledge and empirically sketch a logic of scientific discovery. Genome Biol Evol. 2018;10:707–15. https://academic.oup.com/gbe/article/10/3/707/4840377.Article 
PubMed 
PubMed Central 

Google Scholar 
Vanni C, Schechter MS, Acinas SG, Barberán A, Buttigieg PL, Casamayor EO, et al. Unifying the known and unknown microbial coding sequence space. eLife. 2022;11:e67667. https://elifesciences.org/articles/67667.Article 
PubMed 
PubMed Central 

Google Scholar 
Jaroszewski L, Li Z, Krishna SS, Bakolitsa C, Wooley J, Deacon AM, et al. Exploration of uncharted regions of the protein universe. PLoS Biol. 2009;7:e1000205. https://dx.plos.org/10.1371/journal.pbio.1000205.Meng A, Corre E, Probert I, Gutierrez-Rodriguez A, Siano R, Annamale A, et al. Analysis of the genomic basis of functional diversity in dinoflagellates using a transcriptome-based sequence similarity network. Mol Ecol. 2018;27:2365–80. https://onlinelibrary.wiley.com/doi/10.1111/mec.14579.Article 
CAS 
PubMed 

Google Scholar 
Meng A, Marchet C, Corre E, Peterlongo P, Alberti A, Da Silva C, et al. A de novo approach to disentangle partner identity and function in holobiont systems. Microbiome. 2018;6:105. https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-018-0481-9.Article 
PubMed 
PubMed Central 

Google Scholar 
Carradec Q, Pelletier E, Da Silva C, Alberti A, Seeleuthner Y, Tara Oceans Coordinators et al. A global ocean atlas of eukaryotic genes. Nat Commun. 2018;9:373. http://www.nature.com/articles/s41467-017-02342-1.Ramond P, Sourisseau M, Simon N, Romac S, Schmitt S, Rigaut-Jalabert F, et al. Coupling between taxonomic and functional diversity in protistan coastal communities: functional diversity of marine protists. Environ Microbiol. 2019;21:730–49. http://doi.wiley.com/10.1111/1462-2920.14537.Article 
CAS 
PubMed 

Google Scholar 
Zamkovaya T, Foster JS, de Crécy-Lagard V, Conesa A. A network approach to elucidate and prioritize microbial dark matter in microbial communities. ISME J. 2021;15:228–44. https://www.nature.com/articles/s41396-020-00777-x.Article 
PubMed 

Google Scholar 
Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, et al. Structure and function of the global ocean microbiome. Science. 2015;348:1261359–1261359. https://www.sciencemag.org/lookup/doi/10.1126/science.1261359.Article 
PubMed 

Google Scholar 
de Vargas C, Audic S, Henry N, Decelle J, Mahe F, Logares R, et al. Eukaryotic plankton diversity in the sunlit ocean. Science. 2015;348:1261605–1261605. https://www.sciencemag.org/lookup/doi/10.1126/science.1261605.Article 
PubMed 

Google Scholar 
Strassert JFH, Karnkowska A, Hehenberger E, del Campo J, Kolisko M, Okamoto N, et al. Single cell genomics of uncultured marine alveolates shows paraphyly of basal dinoflagellates. ISME J. 2018;12:304–8. http://www.nature.com/articles/ismej2017167.Article 
CAS 
PubMed 

Google Scholar 
Burki F, Sandin MM, Jamy M. Diversity and ecology of protists revealed by metabarcoding. Curr Biol. 2021;31:R1267–80. https://linkinghub.elsevier.com/retrieve/pii/S0960982221010563.Article 
CAS 
PubMed 

Google Scholar 
Cai R, Kayal E, Alves-de-Souza C, Bigeard E, Corre E, Jeanthon C, et al. Cryptic species in the parasitic Amoebophrya species complex revealed by a polyphasic approach. Sci Rep. 2020;10:2531. http://www.nature.com/articles/s41598-020-59524-z.Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Singer D, Seppey CVW, Lentendu G, Dunthorn M, Bass D, Belbahri L, et al. Protist taxonomic and functional diversity in soil, freshwater and marine ecosystems. Environ Int. 2021;146:106262. https://linkinghub.elsevier.com/retrieve/pii/S0160412020322170.Article 
CAS 
PubMed 

Google Scholar 
Guillou L, Viprey M, Chambouvet A, Welsh RM, Kirkham AR, Massana R, et al. Widespread occurrence and genetic diversity of marine parasitoids belonging to Syndiniales (Alveolata). Environ Microbiol. 2008;10:3349–65. https://onlinelibrary.wiley.com/doi/10.1111/j.1462-2920.2008.01731.x.Article 
CAS 
PubMed 

Google Scholar 
Clarke LJ, Bestley S, Bissett A, Deagle BE. A globally distributed Syndiniales parasite dominates the Southern Ocean micro-eukaryote community near the sea-ice edge. ISME J. 2019;13:734–7. http://www.nature.com/articles/s41396-018-0306-7.Article 
CAS 
PubMed 

Google Scholar 
Cleary AC, Durbin EG. Unexpected prevalence of parasite 18S rDNA sequences in winter among Antarctic marine protists. J Plankton Res. 2016;38:401–17. https://academic.oup.com/plankt/article-lookup/doi/10.1093/plankt/fbw005.Article 
CAS 

Google Scholar 
Anderson SR, Harvey EL. Temporal variability and ecological interactions of parasitic marine syndiniales in coastal protist communities. mSphere. 2020;5. https://journals.asm.org/doi/10.1128/mSphere.00209-20.Käse L, Metfies K, Neuhaus S, Boersma M, Wiltshire KH, Kraberg AC. Host-parasitoid associations in marine planktonic time series: can metabarcoding help reveal them? Amato A, editor. PLoS One. 2021;16:e0244817. https://dx.plos.org/10.1371/journal.pone.0244817.Jephcott TG, Alves-de-Souza C, Gleason FH, van Ogtrop FF, Sime-Ngando T, Karpov SA, et al. Ecological impacts of parasitic chytrids, syndiniales and perkinsids on populations of marine photosynthetic dinoflagellates. Fungal Ecology. 2016; https://linkinghub.elsevier.com/retrieve/pii/S175450481500032X.Siano R, Alves-de-Souza C, Foulon E, Bendif EM, Simon N, Guillou L, et al. Distribution and host diversity of Amoebophryidae parasites across oligotrophic waters of the Mediterranean Sea. Biogeosciences. 2011;8:267–78. https://bg.copernicus.org/articles/8/267/2011/.Article 

Google Scholar 
Moran MA, Ferrer‐González FX, Fu H, Nowinski B, Olofsson M, Powers MA, et al. The Ocean’s labile DOCsupply chain. Limnol Oceanogr. 2022;lno.12053. https://onlinelibrary.wiley.com/doi/10.1002/lno.12053.Chambouvet A, Morin P, Marie D, Guillou L. Control of toxic marine dinoflagellate blooms by serial parasitic killers. Science. 2008;322:1254–7. https://www.science.org/doi/10.1126/science.1164387.Article 
CAS 
PubMed 

Google Scholar 
Shadrin AM, Kholodova MV, Pavlov DS. Geographic distribution and molecular genetic identification of the parasite of the genus Ichthyodinium causing mass mortality of fish eggs and larvae in coastal waters of Vietnam. Dokl Biol Sci. 2010;432:220–3. http://link.springer.com/10.1134/S0012496610030154.Article 
CAS 
PubMed 

Google Scholar 
Farhat S, Le P, Kayal E, Noel B, Bigeard E, Corre E, et al. Rapid protein evolution, organellar reductions, and invasive intronic elements in the marine aerobic parasite dinoflagellate Amoebophrya spp. BMC Biol. 2021;19:1. https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-020-00927-9.Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chambouvet A, Alves-de-Souza C, Cueff V, Marie D, Karpov S, Guillou L. Interplay between the parasite Amoebophrya sp. (Alveolata) and the cyst formation of the red tide Dinoflagellate Scrippsiella trochoidea. Protist. 2011;162:637–49. https://linkinghub.elsevier.com/retrieve/pii/S1434461011000022.Article 
PubMed 

Google Scholar 
Okamura B, Hartigan A, Naldoni J. Extensive uncharted biodiversity: the parasite dimension. integrative and comparative biology. 2018. https://academic.oup.com/icb/advance-article/doi/10.1093/icb/icy039/5026008.Rohde K. Ecology and Biogeography, Future Perspectives: Example Marine Parasites. Geoinfor Geostat Overview. 2016;4; http://www.scitechnol.com/peer-review/ecology-and-biogeography-future-perspectives-example-marine-parasites-wRny.php?article_id=4869.Pawlowski J, Audic S, Adl S, Bass D, Belbahri L, Berney C, et al. CBOL Protist Working Group: barcoding eukaryotic richness beyond the animal, plant, and fungal kingdoms. PLoS Biol. 2012;10:e1001419. https://dx.plos.org/10.1371/journal.pbio.1001419.Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
del Campo J, Sieracki ME, Molestina R, Keeling P, Massana R, Ruiz-Trillo I. The others: our biased perspective of eukaryotic genomes. Trends Ecol Evol. 2014;29:252–9. https://linkinghub.elsevier.com/retrieve/pii/S0169534714000640.Article 
PubMed 
PubMed Central 

Google Scholar 
Sibbald SJ, Archibald JM. More protist genomes needed. Nat Ecol Evol. 2017;1:0145. http://www.nature.com/articles/s41559-017-0145.Article 

Google Scholar 
Egge E, Elferink S, Vaulot D, John U, Bratbak G, Larsen A, et al. An 18S V4 rRNA metabarcoding dataset of protist diversity in the Atlantic inflow to the Arctic Ocean, through the year and down to 1000 m depth. Earth Syst Sci Data. 2021;13:4913–28. https://essd.copernicus.org/articles/13/4913/2021/.Article 

Google Scholar 
Mugnai F, Meglécz E, Abbiati M, Bavestrello G, Bertasi F, Bo M, et al. Are well-studied marine biodiversity hotspots still blackspots for animal barcoding? Global Ecol Conserv. 2021;32:e01909. https://linkinghub.elsevier.com/retrieve/pii/S2351989421004595.Article 

Google Scholar 
Bittner L, Gobet A, Audic S, Romac S, Egge ES, Santini S, et al. Diversity patterns of uncultured Haptophytes unravelled by pyrosequencing in Naples Bay. Mol Ecol. 2013;22:87–101. https://onlinelibrary.wiley.com/doi/10.1111/mec.12108.Article 
CAS 
PubMed 

Google Scholar 
Malviya S, Scalco E, Audic S, Vincent F, Veluchamy A, Poulain J, et al. Insights into global diatom distribution and diversity in the world’s ocean. Proc Natl Acad Sci USA. 2016;113. https://pnas.org/doi/full/10.1073/pnas.1509523113.Kochin BF, Bull JJ, Antia R. Parasite evolution and life history theory. PLoS Biol. 2010;8:e1000524. https://dx.plos.org/10.1371/journal.pbio.1000524.Article 
PubMed 
PubMed Central 

Google Scholar 
Sheath DJ, Dick JTA, Dickey JWE, Guo Z, Andreou D, Britton JR. Winning the arms race: host–parasite shared evolutionary history reduces infection risks in fish final hosts. Biol Lett. 2018;14:20180363. https://royalsocietypublishing.org/doi/10.1098/rsbl.2018.0363.Article 
PubMed 
PubMed Central 

Google Scholar 
Mahé F, de Vargas C, Bass D, Czech L, Stamatakis A, Lara E, et al. Parasites dominate hyperdiverse soil protist communities in Neotropical rainforests. Nat Ecol Evol. 2017;1:0091. http://www.nature.com/articles/s41559-017-0091.Article 

Google Scholar 
Blanco-Bercial L, Parsons R, Bolaños L, Johnson R, Giovannoni S, Curry R. The protist community mirrors seasonality and mesoscale hydrographic features in the oligotrophic Sargasso Sea. 2022. https://www.authorea.com/users/453879/articles/551657-the-protist-community-mirrors-seasonality-and-mesoscale-hydrographic-features-in-the-oligotrophic-sargasso-sea?commit=ba32b47ec0dffb4865eb448dd0b5dd27d5f8cd15.Lepère C, Domaizon I, Debroas D. Unexpected importance of potential parasites in the composition of the freshwater small-eukaryote community. Appl Environ Microbiol. 2008;74:2940–9. https://journals.asm.org/doi/10.1128/AEM.01156-07.Article 
PubMed 
PubMed Central 

Google Scholar 
Decelle J, Martin P, Paborstava K, Pond DW, Tarling G, Mahé F, et al. Diversity, ecology and biogeochemistry of cyst-forming acantharia (radiolaria) in the Oceans. PLoS One. 2013;8:e53598. https://dx.plos.org/10.1371/journal.pone.0053598.Stern RF, Horak A, Andrew RL, Coffroth MA, Andersen RA, Küpper FC, et al. Environmental barcoding reveals massive dinoflagellate diversity in marine environments. PLoS One. 2010;5:e13991. https://dx.plos.org/10.1371/journal.pone.0013991.Stoeck T, Bass D, Nebel M, Christen R, Jones MDM, Breiner HW, et al. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol Eco. 2010;19:21–31. http://doi.wiley.com/10.1111/j.1365-294X.2009.04480.x.Article 
CAS 

Google Scholar 
Chambouvet A, Gower DJ, Jirků M, Yabsley MJ, Davis AK, Leonard G, et al. Cryptic infection of a broad taxonomic and geographic diversity of tadpoles by Perkinsea protists. Proc Natl Acad Sci USA. 2015;112. https://pnas.org/doi/full/10.1073/pnas.1500163112.Chauvet M, Debroas D, Moné A, Dubuffet A, Lepère C. Temporal variations of Microsporidia diversity and discovery of new host–parasite interactions in a lake ecosystem. Environ Microbiol. 2022;1462-2920.15950. https://onlinelibrary.wiley.com/doi/10.1111/1462-2920.15950.Bjorbækmo MFM, Evenstad A, Røsæg LL, Krabberød AK, Logares R. The planktonic protist interactome: where do we stand after a century of research? ISME J. 2020;14:544–59. http://www.nature.com/articles/s41396-019-0542-5.Article 
PubMed 

Google Scholar 
Dallas TA, Han BA, Nunn CL, Park AW, Stephens PR, Drake JM. Host traits associated with species roles in parasite sharing networks. Oikos. 2019;128:23–32. https://onlinelibrary.wiley.com/doi/10.1111/oik.05602.Article 

Google Scholar 
Lima-Mendez G, Faust K, Henry N, Decelle J, Colin S, Carcillo F, et al. Determinants of community structure in the global plankton interactome. Science. 2015;348:1262073. https://www.science.org/doi/10.1126/science.1262073.Article 
PubMed 

Google Scholar 
Hayashi A, Crombie A, Lacey E, Richardson A, Vuong D, Piggott A, et al. Aspergillus Sydowii marine fungal bloom in Australian coastal waters, its metabolites and potential impact on symbiodinium dinoflagellates. Marine Drugs. 2016;14:59. http://www.mdpi.com/1660-3397/14/3/59.Article 
PubMed 
PubMed Central 

Google Scholar 
Drew GC, Stevens EJ, King KC. Microbial evolution and transitions along the parasite–mutualist continuum. Nat Rev Microbiol. 2021;19:623–38. https://www.nature.com/articles/s41579-021-00550-7.Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hehenberger E, Tikhonenkov D, Cooney E, Jacko-Reynolds V, Irwin N, Keeling P. Free-living relatives of highly abundant unicellular marine parasites elucidate plastid loss. 2022. https://www.researchsquare.com/article/rs-1472581/v1.Sures B, Nachev M, Selbach C, Marcogliese DJ. Parasite responses to pollution: what we know and where we go in ‘Environmental Parasitology’. Parasites Vectors. 2017;10:65. http://parasitesandvectors.biomedcentral.com/articles/10.1186/s13071-017-2001-3.Article 
PubMed 
PubMed Central 

Google Scholar 
Payne RJ. Seven reasons why protists make useful bioindicators. Acta Protozoologica. 2013;52:105–13. https://doi.org/10.4467/16890027AP.13.0011.1108Article 

Google Scholar 
Vaulot D, Sim CWH, Ong D, Teo B, Biwer C, Jamy M, et al. metaPR 2: a database of eukaryotic 18S rRNAmetabarcodes with an emphasis on protists. Mol Ecol Resour. 2022;1755-0998.13674. https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13674.Vernette C, Henry N, Lecubin J, Vargas C, Hingamp P, Lescot M. The Ocean barcode atlas: a web service to explore the biodiversity and biogeography of marine organisms. Mol Ecol Resour. 2021;21:1347–58. https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13322.Article 
CAS 
PubMed 

Google Scholar 
Chust G, Vogt M, Benedetti F, Nakov T, Villéger S, Aubert A, et al. Mare incognitum: a glimpse into future plankton diversity and ecology research. Front Mar Sci. 2017;4. http://journal.frontiersin.org/article/10.3389/fmars.2017.00068/full.Guillou L, Bachar D, Audic S, Bass D, Berney C, Bittner L, et al. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucl Acids Res. 2012;41:D597–604. http://academic.oup.com/nar/article/41/D1/D597/1064851/The-Protist-Ribosomal-Reference-database-PR2-a.Article 
PubMed 
PubMed Central 

Google Scholar 
Coppola L, Raimbault P, Mortier L, Testor P. Monitoring the Environment in the Northwestern Mediterranean Sea. Eos 2019;100. https://doi.org/10.1029/2019EO125951.Callahan BJ, McMurdie PJ, Holmes SP. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 2017;11:2639–43;. http://www.nature.com/articles/ismej2017119.Article 
PubMed 
PubMed Central 

Google Scholar 
RStudio Team. RStudio: integrated development for R. Boston, MA: RStudio, PBC; 2020. http://www.rstudio.com/.Caracciolo M, Rigaut‐Jalabert F, Romac S, Mahé F, Forsans S, Gac J, et al. Seasonal dynamics of marine protist communities in tidally mixed coastal waters. Mol Ecol. 2022;31:3761–83. https://onlinelibrary.wiley.com/doi/10.1111/mec.16539.Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Giner CR, Balagué V, Krabberød AK, Ferrera I, Reñé A, Garcés E, et al. Quantifying long‐term recurrence in planktonic microbial eukaryotes. Mol Ecol. 2019;28:923–35. https://onlinelibrary.wiley.com/doi/10.1111/mec.14929.Article 
PubMed 

Google Scholar 
Giner CR, Pernice MC, Balagué V, Duarte CM, Gasol JM, Logares R, et al. Marked changes in diversity and relative activity of picoeukaryotes with depth in the world ocean. ISME J. 2020;14:437–49. http://www.nature.com/articles/s41396-019-0506-9.Article 
PubMed 

Google Scholar 
Lambert S, Tragin M, Lozano JC, Ghiglione JF, Vaulot D, Bouget FY, et al. Rhythmicity of coastal marine picoeukaryotes, bacteria and archaea despite irregular environmental perturbations. ISME J. 2019;13:388–401. http://www.nature.com/articles/s41396-018-0281-z.Article 
PubMed 

Google Scholar 
Logares R, Deutschmann IM, Junger PC, Giner CR, Krabberød AK, Schmidt TSB, et al. Disentangling the mechanisms shaping the surface ocean microbiota. Microbiome. 2020;8:55. https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-020-00827-8.Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Pernice MC, Giner CR, Logares R, Perera-Bel J, Acinas SG, Duarte CM, et al. Large variability of bathypelagic microbial eukaryotic communities across the world’s oceans. ISME J. 2016;10:945–58. http://www.nature.com/articles/ismej2015170.Article 
PubMed 

Google Scholar 
Massana R, Gobet A, Audic S, Bass D, Bittner L, Boutte C, et al. Marine protist diversity in European coastal waters and sediments as revealed by high-throughput sequencing: protist diversity in European coastal areas. Environ Microbiol. 2015;17:4035–49. http://doi.wiley.com/10.1111/1462-2920.12955.Article 
CAS 
PubMed 

Google Scholar 
Csardi G, Nepusz T. The igraph software package for complex network research. InterJ Complex Syst. 2006;1695:1–9.
Google Scholar 
Bray JR, Curtis JT. An ordination of the upland forest communities of Southern Wisconsin. Ecol Monographs. 1957;27:325–49. https://onlinelibrary.wiley.com/doi/10.2307/1942268.Article 

Google Scholar 
Robert P, Escoufier Y. A unifying tool for linear multivariate statistical methods: the RV- coefficient. J R Stat Soc Ser C Appl Stat. 1976;25:257–65. https://doi.org/10.2307/2347233Article 

Google Scholar 
Ruf T. The lomb-scargle periodogram in biological rhythm research: analysis of incomplete and unequally spaced time-series. Biol Rhythm Res. 1999;30:178–201. https://www.tandfonline.com/doi/full/10.1076/brhm.30.2.178.1422.Article 

Google Scholar  More

Campbell, J. L. & Laudon, H. Carbon response to changing winter conditions in northern regions: current understanding and emerging research needs. Environ. Rev. 27, 545–566 (2019).Article 

Google Scholar 
Groffman, P. M. et al. Effects of mild winter freezing on soil nitrogen and carbon dynamics in a northern hardwood forest. Biogeochemistry 56, 191–213 (2001).Article 
CAS 

Google Scholar 
Song, C. et al. Large methane emission upon spring thaw from natural wetlands in the northern permafrost region. Environ. Res. Lett. 7, 034009 (2012).Article 

Google Scholar 
Chen, H. et al. Methane emissions during different freezing-thawing periods from a fen on the Qinghai-Tibetan Plateau: Four years of measurements. Agric. Ecosyst. Environ. 297, 108279 (2021).
Google Scholar 
Bao, T., Xu, X., Jia, G., Billesbach, D. P. & Sullivan, R. C. Much stronger tundra methane emissions during autumn freeze than spring thaw. Glob. Chang. Biol. 27, 376–387 (2021).Article 
CAS 

Google Scholar 
Yu, J. et al. Enhanced net formations of nitrous oxide and methane underneath the frozen soil in Sanjiang wetland, northeastern China. J. Geophys. Res 112, D07111 (2007).Article 

Google Scholar 
Kreyling, J., Peršoh, D., Werner, S., Benzenberg, M. & Wöllecke, J. Short-term impacts of soil freeze-thaw cycles on roots and root-associated fungi of Holcus lanatus and Calluna vulgaris. Plant Soil 353, 19–31 (2012).Article 
CAS 

Google Scholar 
Min, K., Chen, K. & Arora, R. Effect of short-term versus prolonged freezing on freeze–thaw injury and post-thaw recovery in spinach: Importance in laboratory freeze–thaw protocols. Environ. Exp. Bot. 106, 124–131 (2014).Article 
CAS 

Google Scholar 
Kennedy, A. Photosynthetic response of the Antarctic moss Polytrichum alpestre Hoppe to low temperatures and freeze-thaw stress. Polar Biol. 13, 271–279 (1993).Article 

Google Scholar 
Sanders-DeMott, R., Sorensen, P. O., Reinmann, A. B. & Templer, P. H. Growing season warming and winter freeze–thaw cycles reduce root nitrogen uptake capacity and increase soil solution nitrogen in a northern forest ecosystem. Biogeochemistry 137, 337–349 (2018).Article 
CAS 

Google Scholar 
Vankoughnett, M. R. & Henry, H. A. L. Soil freezing and N deposition: transient vs. multi-year effects on extractable C and N, potential trace gas losses and microbial biomass. Soil Biol. Biochem. 77, 170–178 (2014).Article 
CAS 

Google Scholar 
Kreyling, J., Beierkuhnlein, C., Pritsch, K., Schloter, M. & Jentsch, A. Recurrent soil freeze-thaw cycles enhance grassland productivity. New Phytol. 177, 938–945 (2008).Article 

Google Scholar 
Song, Y., Zou, Y., Wang, G. & Yu, X. Altered soil carbon and nitrogen cycles due to the freeze-thaw effect: a meta-analysis. Soil Biol. Biochem. 109, 35–49 (2017).Article 
CAS 

Google Scholar 
Vankoughnett, M. R. & Henry, H. A. L. Soil freezing and N deposition: transient vs multi-year effects on plant productivity and relative species abundance. New Phytol. 202, 1277–1285 (2014).Article 
CAS 

Google Scholar 
Luan, Z. & Cao, H. Response of fine root growth and nitrogen and phosphorus contents to soil freezing in Calamagrostis angustifolia wetland, Sanjiang Plain, Northeast China. J. Food Agric. Environ. 10, 1495–1499 (2012).
Google Scholar 
Garcia, M. O. et al. Soil microbes trade-off biogeochemical cycling for stress tolerance traits in response to year-round climate change. Front. Microbiol. 11, 616 (2020).Article 

Google Scholar 
Tang, H., Bai, J., Chen, F., Liu, Y. & Lou, Y. Effects of salinity and temperature on tuber sprouting and growth of Schoenoplectus nipponicus. Ecosphere 12, e03448 (2021).Article 

Google Scholar 
Satyanti, A., Guja, L. K. & Nicotra, A. B. Temperature variability drives within-species variation in germination strategy and establishment characteristics of an alpine herb. Oecologia 189, 407–419 (2019).Article 

Google Scholar 
Harrison, J. L., Schultz, K., Blagden, M., Sanders-DeMott, R. & Templer, P. H. Growing season soil warming may counteract trend of nitrogen oligotrophication in a northern hardwood forest. Biogeochemistry 151, 139–152 (2020).Article 
CAS 

Google Scholar 
Semenchuk, P. R. et al. Deeper snow alters soil nutrient availability and leaf nutrient status in high Arctic tundra. Biogeochemistry 124, 81–94 (2015).Article 

Google Scholar 
Song, Y., Zou, Y., Wang, G. & Yu, X. Stimulation of nitrogen turnover due to nutrients release from aggregates affected by freeze-thaw in wetland soils. Phys. Chem. Earth 97, 3–11 (2017).Article 

Google Scholar 
Keith, D. A., Rodoreda, S. & Bedward, M. Decadal change in wetland-woodland boundaries during the late 20th century reflects climatic trends. Glob. Chang. Biol. 16, 2300–2306 (2010).Article 

Google Scholar 
Wang, J., Song, C., Hou, A. & Xi, F. Methane emission potential from freshwater marsh soils of Northeast China: response to simulated freezing-thawing cycles. Wetlands 37, 437–445 (2017).Article 

Google Scholar 
Yu, X. et al. Wetland plant litter decomposition occurring during the freeze season under disparate flooded conditions. Sci. Total Environ. 706, 136091 (2020).Article 
CAS 

Google Scholar 
Dong, X. et al. Variations in active layer soil hydrothermal dynamics of typical wetlands in permafrost region in the Great Hing’an Mountains, northeast China. Ecol. Indic. 129, 107880 (2021).Article 

Google Scholar 
Li, Y. et al. Freeze-thaw cycles increase the mobility of phosphorus fractions based on soil aggregate in restored wetlands. CATENA 209, 105846 (2022).Article 
CAS 

Google Scholar 
Song, C., Zhang, J., Wang, Y., Wang, Y. & Zhao, Z. Emission of CO2, CH4 and N2O from freshwater marsh in northeast of China. J. Environ. Manage. 88, 428–436 (2008).Article 
CAS 

Google Scholar 
Wang, G., Liu, J., Zhao, H., Wang, J. & Yu, J. Phosphorus sorption by freeze–thaw treated wetland soils derived from a winter-cold zone (Sanjiang Plain, Northeast China). Geoderma 138, 153–161 (2007).Article 
CAS 

Google Scholar 
Ji, X., Liu, M., Yang, J. & Feng, F. Meta-analysis of the impact of freeze–thaw cycles on soil microbial diversity and C and N dynamics. Soil Biol. Biochem. 168, 108608 (2022).Article 
CAS 

Google Scholar 
Ren, J. et al. Shifts in soil bacterial and archaeal communities during freeze-thaw cycles in a seasonal frozen marsh, Northeast China. Sci. Total. Environ. 625, 782–791 (2018).Article 
CAS 

Google Scholar 
Mitsch, W. J. & Gosselink, J. G. Wetlands. 5th edn (Wiley, Hoboken, New Jersey, 2015).Yu, X., Zou, Y., Jiang, M., Lu, X. & Wang, G. Response of soil constituents to freeze–thaw cycles in wetland soil solution. Soil Biol. Biochem. 43, 1308–1320 (2011).Article 
CAS 

Google Scholar 
Sawicka, J. E., Robador, A., Hubert, C., Jørgensen, B. B. & Bruchert, V. Effects of freeze-thaw cycles on anaerobic microbial processes in an Arctic intertidal mud flat. ISME J 4, 585–594 (2010).Article 
CAS 

Google Scholar 
Song, Y. The Freeze-thaw Effect On Soil Mineralization Between Various Moisture States Of Wetlands. Master of Natural Science thesis (Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 2017).Mason, R. E. et al. Evidence, causes, and consequences of declining nitrogen availability in terrestrial ecosystems. Science 376, eabh3767 (2022).Article 
CAS 

Google Scholar 
Koerselman, W. & Meuleman, A. F. M. The vegetation N:P ratio: a new tool to detect the nature of nutrient limitation. J. Appl. Ecol. 33, 1441–1450 (1996).Article 

Google Scholar 
Yang, K. et al. Immediate and carry-over effects of increased soil frost on soil respiration and microbial activity in a spruce forest. Soil Biol. Biochem. 135, 51–59 (2019).Article 
CAS 

Google Scholar 
Lambers, H., Chapin, F. S. I. & Pons, T. L. Plant Physiological Ecology. 2nd edn (Springer, 2008).Ott, J. P., Klimešová, J. & Hartnett, D. C. The ecology and significance of below-ground bud banks in plants. Ann. Bot. 123, 1099–1118 (2019).Article 

Google Scholar 
Pedersen, E. P., Elberling, B. & Michelsen, A. Foraging deeply: depth‐specific plant nitrogen uptake in response to climate‐induced N‐release and permafrost thaw in the High Arctic. Glob. Chang. Biol. 26, 6523–6536 (2020).Article 

Google Scholar 
Dyer, A.R. Maternal and sibling factors induce dormancy in dimorphic seed pairs of Aegilops triuncialis. Plant Ecol. 172, 211–218 (2004).Article 

Google Scholar 
Renne, I. J. et al. Eavesdropping in plants: delayed germination via biochemical recognition. J. Ecol. 102, 86–94 (2014).Article 

Google Scholar 
Li, H. Eco-physiological Responding Characteristics of Scirpus Planiculmis on Coupling of Water Table Depths and Salinity in Momoge Wetland. Master Dissertation thesis, University of Chinese Academy of Sciences (Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 2013).Yu, D. Responses of Sprouting and Growth to Environmental Factors in Bolboschoenus Planiculmis. Master Dissertation thesis (Harbin Normal University, 2022).Zhang, C., Willis, C. G., Donohue, K., Ma, Z. & Du, G. Effects of environment, life-history and phylogeny on germination strategy of 789 angiosperms species on the eastern Tibetan Plateau. Ecol. Indic. 129, 107974 (2021).Article 

Google Scholar 
Hoyle, G. L. et al. Seed germination strategies: an evolutionary trajectory independent of vegetative functional traits. Front. Plant Sci. 6, 731 (2015).Article 

Google Scholar 
Mercer, K. L., Alexander, H. M. & Snow, A. A. Selection on seedling emergence timing and size in an annual plant, Helianthus annuus (common sunflower, Asteraceae). Am. J. Bot. 98, 975–985 (2011).Article 

Google Scholar 
Cui, Y. et al. Ecoenzymatic stoichiometry reveals microbial phosphorus limitation decreases the nitrogen cycling potential of soils in semi-arid agricultural ecosystems. Soil Tillage. Res. 197, 104463 (2020).Article 

Google Scholar 
Ye, Z. et al. Ecoenzymatic stoichiometry reflects the regulation of microbial carbon and nitrogen limitation on soil nitrogen cycling potential in arid agriculture ecosystems. J. Soils Sediments 22, 1228–1241 (2022).Article 
CAS 

Google Scholar 
Pan, Y. et al. Drivers of plant traits that allow survival in wetlands. Funct. Ecol. 34, 956–967 (2020).Article 

Google Scholar 
Pezeshki, S. R. Wetland plant responses to soil flooding. Environ. Exp. Bot. 46, 299–312 (2001).Article 

Google Scholar 
Zheng, S. Soil Water-heat Process and Nitrogen Transformation During Freezing and Thawing Period in Wetland of Momoge. Master Dissertation thesis (Jilin Agricultural University, 2019).An, Y., Gao, Y., Zhang, Y., Tong, S. & Liu, X. Early establishment of Suaeda salsa population as affected by soil moisture and salinity: implications for pioneer species introduction in saline-sodic wetlands in Songnen Plain, China. Ecol. Indic. 107, 105654 (2019).Article 
CAS 

Google Scholar 
FAO/IIASA/ISRIC/ISS-CAS/JRC. Harmonized World Soil Database (version 1.2). (FAO, Rome, Italy and IIASA, Laxenburg, Austria, 2012).Jiang, M., Lu, X., Xu, L. & Yang, Q. Estimation on benefit of latent soil nutrient in melmeg reserve wetlands. J. Nat. Resour 20, 279–285 (2005).
Google Scholar 
Wang, Y. & Zhang, S. The pH distribution and soil nutrient characteristic at different habitats-a case study of Momoge Wetland. J. Anhui Agric. Sci. 50, 135–139 (2022).
Google Scholar 
Hao, M. The Ecological Restoration Research on Momoge Scripus Planiculmis Wetland. Master Dissertation thesis, University of Chinese Academy of Sciences (Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 2016).Ma, H. et al. Effect of nitrate supply on the facilitation between two salt-marsh plants (Suaeda salsa and Scirpus planiculmis). J. Plant. Ecol. 13, 204–212 (2020).Article 

Google Scholar 
Liu, B. et al. Effects of burial depth and water depth on seedling emergence and early growth of Scirpus planiculmis Fr. Schmidt. Ecol. Eng. 87, 30–33 (2016).Article 

Google Scholar 
Zhang, L., Zhang, G., Li, H. & Sun, G. Eco-physiological responses of Scirpus planiculmis to different water-salt conditions in Momoge wetland. Pol. J. Environ. Stud. 23, 1813–1820 (2014).
Google Scholar 
Sosnová, M., van Diggelen, R. & Klimešová, J. Distribution of clonal growth forms in wetlands. Aquat. Bot. 92, 33–39 (2010).Article 

Google Scholar 
Lu, R. Analytical Methods of Soil Agrochemistry (China Agricultural Science and Technology Press, 2000).Bao, S. Soil and Agricultural Chemistry Analysis. 3 edn. (China Agriculture Press, 2000).Magoc, T. & Salzberg, S. L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).Article 
CAS 

Google Scholar 
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).Article 
CAS 

Google Scholar 
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).Article 
CAS 

Google Scholar 
Edgar, R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).Article 
CAS 

Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).Article 
CAS 

Google Scholar 
Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).Article 
CAS 

Google Scholar 
Li, D., Liu, C. M., Luo, R., Sadakane, K. & Lam, T. W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).Article 
CAS 

Google Scholar 
Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).Article 
CAS 

Google Scholar 
Zhu, W., Lomsadze, A. & Borodovsky, M. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res. 38, e132 (2010).Article 

Google Scholar 
Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150–3152 (2012).Article 
CAS 

Google Scholar 
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).Article 
CAS 

Google Scholar 
Lauro, F. M. et al. An integrative study of a meromictic lake ecosystem in Antarctica. ISME J 5, 879–895 (2011).Article 
CAS 

Google Scholar 
Shen, M. et al. Trophic status is associated with community structure and metabolic potential of planktonic microbiota in Plateau lakes. Front. Microbiol. 10, 2560 (2019).Article 

Google Scholar 
Kieft, B. et al. Microbial community structure-function relationships in Yaquina Bay estuary reveal spatially distinct carbon and nitrogen cycling capacities. Front. Microbiol. 9, 1282 (2018).Article 

Google Scholar 
Kay, M. Effect Sizes with ART (2021).Mangiafico, S. S. Summary and Analysis of Extension Program Evaluation in R, version 1.18.8 https://rcompanion.org/handbook/ (2016).R Core Team R: A Language and Environment for Statistical Computing (2020).Fox, J. & Weisberg, S. An R Companion to Applied Regression. 3rd edn (Thousand Oaks, Sage, CA, 2019).Kay, M., Elkin, L. A., Higgins, J. J. & Wobbrock, J. O. ARTool: Aligned Rank Transform for Nonparametric Factorial ANOVAs. R package version 0.11.1. https://doi.org/10.5281/zenodo.594511 (2021).Wobbrock, J. O., Findlate, L., Gergle, D. & Higgins, J. J. The aligned rank transform for nonparametric factorial analyses using only anova procedures. 29th Annual Chi Conference on Human Factors in Computing Systems (CHI 2011), p. 143-146. https://doi.org/10.1145/1978942.1978963 (2011).Elkin, L. A., Kay, M., Higgins, J. J. & Wobbrock, J. O. An aligned rank transform procedure for multifactor contrast Tests. Proceedings of the ACM Symposium on User Interface Software and Technology (UIST 2021), p. 754-768. https://doi.org/10.1145/3472749.3474784 (2021).Lenth, R. V. emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.6.3. (2021).Wickham, H. ggplot2: Elegant Graphics for Data Analysis (2016).Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-7 (2020).Revelle, W. psych: Procedures for Psychological, Psychometric, and Personality Research, Northwestern University, Evanston, Illinois, USA, R package version 2.2.9 (2022).Wei, T. & Simko, V. R package ‘corrplot’: Visualization of a Correlation Matrix (Version 0.90) (2021). More

Department of Ecology and Evolutionary Biology and Eversource Energy Center, University of Connecticut, Storrs, CT, USACory MerowDepartment of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USABrad Boyle & Brian J. EnquistDepartment of Geography, Florida State University, Tallahassee, FL, USAXiao FengBiodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Graduate University, Onna, JapanJamie M. KassDepartment of Geography, University at Buffalo, Buffalo, NY, USABrian S. Maitner & Adam M. WilsonSchool of Biology and Ecology, University of Maine, Orono, ME, USABrian McGillMitchell Center for Sustainability Solutions, University of Maine, Orono, ME, USABrian McGillCenter for Macroecology, Evolution and Climate, Globe Institute, University of Copenhagen, Copenhagen, DenmarkHannah OwensFlorida Museum of Natural History, University of Florida, Gainesville, FL, USAHannah OwensDepartment of Biological Sciences, Purdue University, West Lafayette, IN, USADaniel S. ParkPurdue Center for Plant Biology, Purdue University, West Lafayette, IN, USADaniel S. ParkDepartment of Environmental Systems Science, Institute of Integrative Biology, ETH Zürich, Zurich, SwitzerlandAndrea PazDepartment of Biology, City College of the City University of New York, New York, NY, USAGonzalo E. Pinilla-BuitragoPhD Program in Biology, Graduate Center of the City University of New York, New York, NY, USAGonzalo E. Pinilla-BuitragoDepartment of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USAMark C. UrbanCenter of Biological Risk, University of Connecticut, Storrs, CT, USAMark C. UrbanDepartamento de Ecoloxía e Bioloxía Animal, Universidade de Vigo, Vigo, SpainSara Varela More

Abrahms, B. Human–wildlife conflict under climate change. Science 373, 484–485 (2021).Article 
CAS 

Google Scholar 
Nyhus, P. J. Human–wildlife conflict and coexistence. Annu. Rev. Environ. Resour. 41, 143–171 (2016).Article 

Google Scholar 
Ripple, W. J. et al. Extinction risk is most acute for the world’s largest and smallest vertebrates. Proc. Natl Acad. Sci. USA 114, 10678–10683 (2017).Article 
CAS 

Google Scholar 
Estes, J. A. et al. Trophic downgrading of planet Earth. Science 333, 301–306 (2011).Article 
CAS 

Google Scholar 
Abrahms, B. et al. Data from: Climate change as an amplifier of human–wildlife conflict. Github https://github.com/Abrahms-Lab/Climate-Conflict-Review (2022).IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Sydeman, W. J., Santora, J. A., Thompson, S. A., Marinovic, B. & Lorenzo, E. D. Increasing variance in North Pacific climate relates to unprecedented ecosystem variability off California. Glob. Change Biol. 19, 1662–1675 (2013).Article 

Google Scholar 
Wang, G. et al. Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization. Nat. Clim. Change 7, 568–572 (2017).Article 

Google Scholar 
Filazzola, A., Blagrave, K., Imrit, M. A. & Sharma, S. Climate change drives increases in extreme events for lake ice in the Northern Hemisphere. Geophys. Res. Lett. 47, e2020GL089608 (2020).Marzeion, B., Cogley, J. G., Richter, K. & Parkes, D. Attribution of global glacier mass loss to anthropogenic and natural causes. Science 345, 919–921 (2014).Article 
CAS 

Google Scholar 
Martin, J. T. et al. Increased drought severity tracks warming in the United States’ largest river basin. Proc. Natl Acad. Sci. USA 117, 11328–11336 (2020).Article 
CAS 

Google Scholar 
Laufkötter, C., Zscheischler, J. & Frölicher, T. L. High-impact marine heatwaves attributable to human-induced global warming. Science 369, 1621–1625 (2020).Article 

Google Scholar 
Donat, M. G., Lowry, A. L., Alexander, L. V., O’Gorman, P. A. & Maher, N. More extreme precipitation in the world’s dry and wet regions. Nat. Clim. Change 6, 508–513 (2016).Article 

Google Scholar 
Walther, G.-R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002).Article 
CAS 

Google Scholar 
Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).Article 

Google Scholar 
Lin, D., Xia, J. & Wan, S. Climate warming and biomass accumulation of terrestrial plants: a meta‐analysis. New Phytol. 188, 187–198 (2010).Article 

Google Scholar 
Kharouba, H. M. & Wolkovich, E. M. Disconnects between ecological theory and data in phenological mismatch research. Nat. Clim. Change 10, 406–415 (2020).Article 

Google Scholar 
Marinovic, B. B., Croll, D. A., Gong, N., Benson, S. R. & Chavez, F. P. Effects of the 1997–1999 El Niño and La Niña events on zooplankton abundance and euphausiid community composition within the Monterey Bay coastal upwelling system. Prog. Oceanogr. 54, 265–277 (2002).Article 

Google Scholar 
Kardol, P. et al. Climate change effects on plant biomass alter dominance patterns and community evenness in an experimental old‐field ecosystem. Glob. Change Biol. 16, 2676–2687 (2010).Article 

Google Scholar 
Prugh, L. R. et al. Ecological winners and losers of extreme drought in California. Nat. Clim. Change 8, 819–824 (2018).Article 

Google Scholar 
Sorte, C. J. B., Williams, S. L. & Zerebecki, R. A. Ocean warming increases threat of invasive species in a marine fouling community. Ecology 91, 2198–2204 (2010).Article 

Google Scholar 
Muehlenbein, M. P. Human–environment interactions, current and future directions. Hum. Environ. Interact. 1, 79–94 (2012).
Google Scholar 
Sinervo, B. et al. Erosion of lizard diversity by climate change and altered thermal niches. Science 328, 894–899 (2010).Article 
CAS 

Google Scholar 
Mason, T. H. E., Keane, A., Redpath, S. M. & Bunnefeld, N. The changing environment of conservation conflict: geese and farming in Scotland. J. Appl. Ecol. 55, 651–662 (2018).Article 

Google Scholar 
Pérez-Flores, J., Mardero, S., López-Cen, A., Contreras-Moreno, F. M. & Pérez-Flores, J. Human–wildlife conflicts and drought in the greater Calakmul Region, Mexico: implications for tapir conservation. Neotrop. Biol. Conserv. 16, 539–563 (2021).Article 

Google Scholar 
Mariki, S. B., Svarstad, H. & Benjaminsen, T. A. Elephants over the cliff: explaining wildlife killings in Tanzania. Land Use Policy 44, 19–30 (2015).Article 

Google Scholar 
Mukeka, J. M., Ogutu, J. O., Kanga, E. & Roskaft, E. Spatial and temporal dynamics of human–wildlife conflicts in the Kenya Greater Tsavo Ecosystem. Hum. Wildl. Interact. 14, 255–272 (2020).
Google Scholar 
Popp, J. N., Hamr, J., Chan, C. & Mallory, F. F. Elk (Cervus elaphus) railway mortality in Ontario. Can. J. Zool. 96, 1066–1070 (2018).Article 

Google Scholar 
Olson, D. D. et al. How does variation in winter weather affect deer–vehicle collision rates? Wildl. Biol. 21, 80–87 (2015).Article 

Google Scholar 
Nyhus, P. & Tilson, R. Agroforestry, elephants, and tigers: balancing conservation theory and practice in human-dominated landscapes of Southeast Asia. Agric. Ecosyst. Environ. 104, 87–97 (2004).Article 

Google Scholar 
Laufenberg, J. S., Johnson, H. E., Doherty, P. F. & Breck, S. W. Compounding effects of human development and a natural food shortage on a black bear population along a human development–wildland interface. Biol. Conserv 224, 188–198 (2018).Article 

Google Scholar 
Blondin, H., Abrahms, B., Crowder, L. B. & Hazen, E. L. Combining high temporal resolution whale distribution and vessel tracking data improves estimates of ship strike risk. Biol. Conserv. 250, 108757 (2020).Article 

Google Scholar 
Abrahms, B. et al. Dynamic ensemble models to predict distributions and anthropogenic risk exposure for highly mobile species. Divers. Distrib. 25, 1182–1193 (2019).Article 

Google Scholar 
Gaynor, K. M., Hojnowski, C. E., Carter, N. H. & Brashares, J. S. The influence of human disturbance on wildlife nocturnality. Science 360, 1232–1235 (2018).Article 
CAS 

Google Scholar 
Kabir, M., Ghoddousi, A., Awan, M. S. & Awan, M. N. Assessment of human–leopard conflict in Machiara National Park, Azad Jammu and Kashmir, Pakistan. Eur. J. Wildl. Res. 60, 291–296 (2014).Article 

Google Scholar 
Soto, J. R. Patterns and Determinants of Human–Carnivore Conflicts in the Tropical Lowlands of Guatemala (Univ. of Florida, 2008).Honda, T. & Kozakai, C. Mechanisms of human–black bear conflicts in Japan: in preparation for climate change. Sci. Total Environ. 739, 140028 (2020).Article 
CAS 

Google Scholar 
Mukeka, J. M., Ogutu, J. O., Kanga, E. & Røskaft, E. Human–wildlife conflicts and their correlates in Narok County, Kenya. Glob. Ecol. Conserv. 18, e00620 (2019).Article 

Google Scholar 
Kuiper, T. R. et al. Seasonal herding practices influence predation on domestic stock by African lions along a protected area boundary. Biol. Conserv. 191, 546–554 (2015).Article 

Google Scholar 
Funston, P. J., Mills, M. G. L. & Biggs, H. C. Factors affecting the hunting success of male and female lions in the Kruger National Park. J. Zool. 253, 419–431 (2001).Article 

Google Scholar 
Schiess-Meier, M., Ramsauer, S., Gabanapelo, T. & Konig, B. Livestock predation—insights from problem animal control registers in Botswana. J. Wildl. Manag. 71, 1267–1274 (2007).Article 

Google Scholar 
Wilder, J. M. et al. Polar bear attacks on humans: implications of a changing climate. Wildl. Soc. B 41, 537–547 (2017).Article 

Google Scholar 
Towns, L., Derocher, A. E., Stirling, I., Lunn, N. J. & Hedman, D. Spatial and temporal patterns of problem polar bears in Churchill, Manitoba. Polar Biol. 32, 1529–1537 (2009).Article 

Google Scholar 
Schmidt, A. & Clark, D. ‘It’s just a matter of time:’ lessons from agency and community responses to polar bear-inflicted human injury. Conserv. Soc. 16, 64 (2018).Article 

Google Scholar 
Koenig, J., Shine, R. & Shea, G. The dangers of life in the city: patterns of activity, injury and mortality in suburban lizards (Tiliqua scincoides). J. Herpetol. 36, 62–68 (2002).Article 

Google Scholar 
Whitaker, P. B. & Shine, R. Responses of free-ranging brownsnakes (Pseudonaja textilis: Elapidae) to encounters with humans. Wildl. Res. 26, 689–704 (1999).Article 

Google Scholar 
Saberwal, V., Gibbs, J., Chellam, R. & Johnsingh, A. Lion–human conflict in the Gir Forest, India. Conserv. Biol. 8, 501–507 (1994).Article 

Google Scholar 
Ferreira, S. M. & Viljoen, P. African large carnivore population changes in response to a drought. Afr. J. Wildl. Res. https://hdl.handle.net/10520/ejc-wild2-v52-n1-a1 (2022).Masiaine, S. et al. Landscape-level changes to large mammal space use in response to a pastoralist incursion. Ecol. Indic. 121, 107091 (2021).Article 

Google Scholar 
Kiria, E. A Spatial Multi-criteria Analysis of Land Use, Land Cover and Climate Changes on Wildlife Ecosystems Planning and Management in Meru Conservation Area (Chuka Univ., 2018).Benansio, J., Demaya, G., Dendi, D. & Luiselli, L. Attacks by Nile crocodiles (Crocodylus nilotticus) on humans and livestock in the Sudd wetlands, South Sudan. Russ. J. Herpetol. https://doi.org/10.30906/1026-2296-2022-29-4-199-205 (2022).Melia, N., Haines, K. & Hawkins, E. Sea ice decline and 21st century trans‐Arctic shipping routes. Geophys. Res. Lett. 43, 9720–9728 (2016).Article 

Google Scholar 
Ivanova, S. V. et al. Shipping alters the movement and behavior of Arctic cod (Boreogadus saida), a keystone fish in Arctic marine ecosystems. Ecol. Appl. 30, e02050 (2020).Article 

Google Scholar 
Hauser, D. D. W., Laidre, K. L. & Stern, H. L. Vulnerability of Arctic marine mammals to vessel traffic in the increasingly ice-free Northwest Passage and Northern Sea Route. Proc. Natl Acad. Sci. USA 5, 201803543–201803546 (2018).
Google Scholar 
Hovelsrud, G. K., McKenna, M. & Huntington, H. P. Marine mammal harvests and other interactions with humans. Ecol. Appl. 18, S135–S147 (2008).Article 

Google Scholar 
Santora, J. A. et al. Habitat compression and ecosystem shifts as potential links between marine heatwave and record whale entanglements. Nat. Commun. 11, 536 (2020).Samhouri, J. F. et al. Marine heatwave challenges solutions to human–wildlife conflict. Proc. R. Soc. B 288, 20211607 (2021).Article 

Google Scholar 
Chapman, B. K. & McPhee, D. Global shark attack hotspots: identifying underlying factors behind increased unprovoked shark bite incidence. Ocean Coast. Manag. 133, 72–84 (2016).Article 

Google Scholar 
Burgess, G., Buch, R., Carvalho, F., Garner, B. & Walker, C. in Sharks and Their Relatives II: Biodiversity, Adaptive Physiology, and Conservation (eds Carrier, J. C. et al.) 541–565 (CRC Press, 2010).Woodward, A. R., Leone, E. H., Dutton, H. J., Waller, J. E. & Hord, L. Characteristics of American alligator bites on people in Florida. J. Wildl. Manag. 83, 1437–1453 (2019).Article 

Google Scholar 
Khorozyan, I., Soofi, M., Ghoddousi, A., Hamidi, A. K. & Waltert, M. The relationship between climate, diseases of domestic animals and human–carnivore conflicts. Basic Appl. Ecol. 16, 703–713 (2015).Article 

Google Scholar 
Treves, A. & Bruskotter, J. Tolerance for predatory wildlife. Science 344, 476–477 (2014).Article 
CAS 

Google Scholar 
Carpenter, S. Exploring the impact of climate change on the future of community‐based wildlife conservation. Conserv. Sci. Pract. 4, e585 (2022).Nisi, A. Cryptic Neighbors: Connecting Movement Ecology and Population Dynamics for a Large Carnivore in a Human-dominated Landscape (Univ. California, 2021). .Asiyanbi, A. P. A political ecology of REDD+: property rights, militarised protectionism, and carbonised exclusion in Cross River. Geoforum 77, 146–156 (2016).Article 

Google Scholar 
Dawson, N. M. et al. Barriers to equity in REDD+: deficiencies in national interpretation processes constrain adaptation to context. Environ. Sci. Policy 88, 1–9 (2018).Article 

Google Scholar 
Rabaiotti, D. et al. High temperatures and human pressures interact to influence mortality in an African carnivore. Ecol. Evol. 11, 8495–8506 (2021).Article 

Google Scholar 
Vargas, S. P., Castro-Carrasco, P. J., Rust, N. A. & F, J. L. R. Climate change contributing to conflicts between livestock farming and guanaco conservation in central Chile: a subjective theories approach. Oryx 55, 275–283 (2021).Article 

Google Scholar 
Heemskerk, S. et al. Temporal dynamics of human–polar bear conflicts in Churchill, Manitoba. Glob. Ecol. Conserv. 24, e01320 (2020).Article 

Google Scholar 
Schell, C. J. et al. The evolutionary consequences of human–wildlife conflict in cities. Evol. Appl. 14, 178–197 (2021).Article 

Google Scholar 
Clark, J. A. & May, R. M. Taxonomic bias in conservation research. Science 297, 191–192 (2002).Article 
CAS 

Google Scholar 
Ravenelle, J. & Nyhus, P. J. Global patterns and trends in human–wildlife conflict compensation. Conserv. Biol. 31, 1247–1256 (2017).Article 

Google Scholar 
Zack, C. S., Milne, B. T. & Dunn, W. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildl. Soc. Bull. 31, 517–520 (2003).
Google Scholar 
Acosta-Jamett, G., Gutiérrez, J. R., Kelt, D. A., Meserve, P. L. & Previtali, M. A. El Niño Southern Oscillation drives conflict between wild carnivores and livestock farmers in a semiarid area in Chile. J. Arid. Environ. 126, 76–80 (2016).Article 

Google Scholar 
Timmermann, A. et al. El Niño–Southern Oscillation complexity. Nature 559, 535–545 (2018).Article 
CAS 

Google Scholar 
Wittemyer, G., Elsen, P., Bean, W. T., Burton, A. C. O. & Brashares, J. S. Accelerated human population growth at protected area edges. Science 321, 123–126 (2008).Article 
CAS 

Google Scholar 
Powell, G., Versluys, T. M. M., Williams, J. J., Tiedt, S. & Pooley, S. Using environmental niche modelling to investigate abiotic predictors of crocodilian attacks on people. Oryx 54, 639–647 (2020).Article 

Google Scholar 
Maxwell, S. M. et al. Dynamic ocean management: defining and conceptualizing real-time management of the ocean. Mar. Policy 58, 42–50 (2015).Article 

Google Scholar 
Maxwell, S. M., Gjerde, K. M., Conners, M. G. & Crowder, L. B. Mobile protected areas for biodiversity on the high seas. Science 367, 252–254 (2020).Article 
CAS 

Google Scholar 
Pons, M. et al. Trade-offs between bycatch and target catches in static versus dynamic fishery closures. Proc. Natl Acad. Sci. USA 119, e2114508119 (2022).Article 

Google Scholar 
Oestreich, W. K., Chapman, M. S. & Crowder, L. B. A comparative analysis of dynamic management in marine and terrestrial systems. Front. Ecol. Environ. 18, 496–504 (2020).Article 

Google Scholar 
Mason, N., Ward, M., Watson, J. E. M., Venter, O. & Runting, R. K. Global opportunities and challenges for transboundary conservation. Nat. Ecol. Evol. 4, 694–701 (2020).Article 

Google Scholar 
Dickman, A. J., Macdonald, E. A. & Macdonald, D. W. A review of financial instruments to pay for predator conservation and encourage human–carnivore coexistence. Proc. Natl Acad. Sci. USA 108, 13937–13944 (2011).Article 
CAS 

Google Scholar 
Ej, N. G. et al. A Future for All: The Need for Human–Wildlife Coexistence (UNEP, 2021).Lankford, A. J., Svancara, L. K., Lawler, J. J. & Vierling, K. Comparison of climate change vulnerability assessments for wildlife. Wildl. Soc. Bull. 38, 386–394 (2014).Article 

Google Scholar 
Syombua, M. An Analysis of Human–Wildlife Conflicts in Tsavo West-Amboseli Agro-Ecosystem Using an Integrated Geospatial Approach: A Case Study of Taveta District (Univ. of Nairobi, 2013).Malhi, Y. et al. The role of large wild animals in climate change mitigation and adaptation. Curr. Biol. 32, R181–R196 (2022).Article 
CAS 

Google Scholar 
Aryal, A., Brunton, D. & Raubenheimer, D. Impact of climate change on human–wildlife–ecosystem interactions in the Trans-Himalaya region of Nepal. Theor. Appl. Climatol. 115, 517–529 (2013).Article 

Google Scholar 
Aryal, A., Brunton, D., Ji, W., Barraclough, R. K. & Raubenheimer, D. Human–carnivore conflict: ecological and economical sustainability of predation on livestock by snow leopard and other carnivores in the Himalaya. Sustain. Sci. 9, 321–329 (2014).Article 

Google Scholar 
Aryal, A. et al. Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya. Ecol. Evol. 6, 4065–4075 (2016).Article 

Google Scholar 
Nowell, K., Li, J., Paltsyn, M. & Sharma, R. An Ounce of Prevention: Snow Leopard Crime Revisited (Traffic Report, 2016). More

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

Google Scholar 
Tilman, D. et al. Forecasting agriculturally driven global environmental change. Science 292, 281–284 (2001).Article 
CAS 
PubMed 

Google Scholar 
IPBES: Summary for Policymakers. In The Assessment Report on Pollinators, Pollination and Food Production (eds Potts, S. G. et al.) (IPBES, 2016).Potts, S. G. et al. Safeguarding pollinators and their values to human well-being. Nature 540, 220–229 (2016).Article 
CAS 
PubMed 

Google Scholar 
Sgolastra, F. et al. Synergistic mortality between a neonicotinoid insecticide and an ergosterol-biosynthesis-inhibiting fungicide in three bee species. Pest Manag Sci. 73, 1236–1243 (2016).Article 
PubMed 

Google Scholar 
Whitehorn, P. R., O’Connor, S., Wackers, F. L. & Goulson, D. Neonicotinoid pesticide reduces bumble bee colony growth and queen production. Science 336, 351–352 (2012).Article 
CAS 
PubMed 

Google Scholar 
Rundlöf, M. et al. Seed coating with a neonicotinoid insecticide negatively affects wild bees. Nature 521, 77–80 (2015).Article 
PubMed 

Google Scholar 
Woodcock, B. et al. Impacts of neonicotinoid use on long-term population changes in wild bees in England. Nat. Commun. 7, 12459 (2016).Stuligross, C. & Williams, N. Past insecticide exposure reduces bee reproduction and population growth rate. Proc. Natl Acad. Sci. USA 118, e2109909118 (2021).Stanley, D. A. et al. Neonicotinoid pesticide exposure impairs crop pollination services provided by bumblebees. Nature 528, 548–550 (2015).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Tamburini, G. et al. Fungicide and insecticide exposure adversely impacts bumblebees and pollination services under semi-field conditions. Environ. Int. 157, 106813 (2021).Article 
CAS 
PubMed 

Google Scholar 
Sponsler, D. B. et al. Pesticides and pollinators: a socioecological synthesis. Sci. Total Environ. 662, 1012–1027 (2019).Article 
CAS 
PubMed 

Google Scholar 
Meehan, T. D., Werling, B. P., Landis, D. A. & Gratton, C. Agricultural landscape simplification and insecticide use in the Midwestern United States. Proc. Natl Acad. Sci. USA 108, 11500–11505 (2011).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Nicholson, C. C. & Williams, N. M. Cropland heterogeneity drives frequency and intensity of pesticide use. Environ. Res. 16, 074008 (2021).CAS 

Google Scholar 
Böhme, F., Bischoff, G., Zebitz, C. P. W., Rosenkranz, P. & Wallner, K. Pesticide residue survey of pollen loads collected by honeybees (Apis mellifera) in daily intervals at three agricultural sites in South Germany. PLoS ONE 13, e0199995 (2018).Larsen, A. E. & Noack, F. Impact of local and landscape complexity on the stability of field-level pest control. Nat. Sustain. 4, 120–128 (2021).Article 

Google Scholar 
Botías, C. et al. Neonicotinoid residues in wildflowers, a potential route of chronic exposure for bees. Environ. Sci. Technol. 49, 12731–12740 (2015).Article 
PubMed 

Google Scholar 
Krupke, C. H., Holland, J. D., Long, E. Y. & Eitzer, B. D. Planting of neonicotinoid-treated maize poses risks for honey bees and other non-target organisms over a wide area without consistent crop yield benefit. J. Appl. Ecol. 54, 1449–1458 (2017).Article 
CAS 

Google Scholar 
Wintermantel, D. et al. Neonicotinoid-induced mortality risk for bees foraging on oilseed rape nectar persists despite EU moratorium. Sci. Total Environ. 704, 135400 (2020).Article 
CAS 
PubMed 

Google Scholar 
Krupke, C. H., Hunt, G. J., Eitzer, B. D., Andino, G. & Given, K. Multiple routes of pesticide exposure for honey bees living near agricultural fields. PLoS ONE 7, e29268 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Long, E. Y. & Krupke, C. H. Non-cultivated plants present a season-long route of pesticide exposure for honey bees. Nat. Commun. 7, 11629 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
David, A. et al. Widespread contamination of wildflower and bee-collected pollen with complex mixtures of neonicotinoids and fungicides commonly applied to crops. Environ. Int. 88, 169–178 (2016).Article 
CAS 
PubMed 

Google Scholar 
Heinrich, B. The foraging specializations of individual bumblebees. Ecol. Monogr. 46, 105–128 (1976).Article 

Google Scholar 
Bolin, A., Smith, H. G., Lonsdorf, E. V. & Olsson, O. Scale-dependent foraging tradeoff allows competitive coexistence. Oikos 127, 1575–1585 (2018).Article 

Google Scholar 
Cresswell, J. E., Osborne, J. L. & Goulson, D. An economic model of the limits to foraging range in central place foragers with numerical solutions for bumblebees. Ecol. Entomol. 25, 249–255 (2000).Article 

Google Scholar 
Rundlöf, M. et al. Flower plantings support wild bee reproduction and may also mitigate pesticide exposure effects. J. Appl. Ecol. 59, 2117–2127 (2022).Article 

Google Scholar 
Graham, K. K. et al. Identities, concentrations, and sources of pesticide exposure in pollen collected by managed bees during blueberry pollination. Sci. Rep. 11, 16857 (2021).Centrella, M. et al. Diet diversity and pesticide risk mediate the negative effects of land use change on solitary bee offspring production. J. Appl. Ecol. 57, 1031–1042 (2020).Article 
CAS 

Google Scholar 
De Palma, A. et al. Ecological traits affect the sensitivity of bees to land-use pressures in European agricultural landscapes. J. Appl. Ecol. 52, 1567–1577 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Sponsler, D. B. & Johnson, R. M. Mechanistic modeling of pesticide exposure: the missing keystone of honey bee toxicology. Environ. Toxicol. Chem. 36, 871–881 (2017).Article 
CAS 
PubMed 

Google Scholar 
Holzschuh, A., Dormann, C. F., Tscharntke, T. & Steffan-Dewenter, I. Mass-flowering crops enhance wild bee abundance. Oecologia 172, 477–484 (2013).Article 
PubMed 

Google Scholar 
McArt, S. H., Fersch, A. A., Milano, N. J., Truitt, L. L. & Böröczky, K. High pesticide risk to honey bees despite low focal crop pollen collection during pollination of a mass blooming crop. Sci. Rep. 7, 46554 (2017).Sanchez-Bayo, F. & Goka, K. Pesticide residues and bees—a risk assessment. PLoS ONE 9, e94482 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Zioga, E., Kelly, R., White, B. & Stout, J. C. Plant protection product residues in plant pollen and nectar: a review of current knowledge. Environ. Res. 189, 109873 (2020).Article 
CAS 
PubMed 

Google Scholar 
The European Green Deal (European Commission, 2019).More, S. J., Auteri, D., Rortais, A. & Pagani, S. EFSA is working to protect bees and shape the future of environmental risk assessment. EFSA J. 19, e190101 (2021).Schmolke, A. et al. Assessment of the vulnerability to pesticide exposures across bee species. Environ. Toxicol. Chem. 40, 2640–2651 (2021).Article 
CAS 
PubMed 

Google Scholar 
Rollin, O. et al. Differences of floral resource use between honey bees and wild bees in an intensive farming system. Agric. Ecosyst. Environ. 179, 78–86 (2013).Article 

Google Scholar 
Persson, A. S. & Smith, H. G. Seasonal persistence of bumblebee populations is affected by landscape context. Agric. Ecosyst. Environ. 165, 201–209 (2013).Article 

Google Scholar 
Samuelson, A. E., Schürch, R. & Leadbeater, E. Dancing bees evaluate central urban forage resources as superior to agricultural land. J. Appl. Ecol. 59, 79–88 (2022).Article 

Google Scholar 
Milner, A. M. & Boyd, I. L. Toward pesticidovigilance. Science 357, 1232–1234 https://doi.org/10.1126/science.aan2683 (2017).Nowell, L. H., Norman, J. E., Moran, P. W., Martin, J. D. & Stone, W. W. Pesticide toxicity index—a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms. Sci. Total Environ. 476–477, 144–157 (2014).Article 
PubMed 

Google Scholar 
Mullin, C. A., Frazier, M., Frazier, J. L., Ashcraft, S. & Simonds, R. High levels of miticides and agrochemicals in North American apiaries: implications for honey bee health. PLoS ONE 5, 9754 (2010).Article 

Google Scholar 
Pettis, J. S. et al. Crop pollination exposes honey bees to pesticides which alters their susceptibility to the gut pathogen Nosema ceranae. PLoS ONE 8, e70182 (2013).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Végh, R., Sörös, C., Majercsik, N. & Sipos, L. Determination of pesticides in bee pollen: validation of a multiresidue high-performance liquid chromatography-mass spectrometry/mass spectrometry method and testing pollen samples of selected botanical origin. J. Agric. Food Chem. 70, 1507–1515 (2022).Article 
PubMed 

Google Scholar 
Park, M. G., Blitzer, E. J., Gibbs, J., Losey, J. E. & Danforth, B. N. Negative effects of pesticides on wild bee communities can be buffered by landscape context. Proc. R. Soc. B 282, 20150299 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Graham, K. K. et al. Pesticide risk to managed bees during blueberry pollination is primarily driven by off-farm exposures. Sci. Rep. 12, 7189 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Yourstone, J., Karlsson, M., Klatt, B. K., Olsson, O. & Smith, H. G. Effects of crop and non-crop resources and competition: high importance of trees and oilseed rape for solitary bee reproduction. Biol. Conserv. 261, 109249 (2021).Persson, A. S., Mazier, F. & Smith, H. G. When beggars are choosers—how nesting of a solitary bee is affected by temporal dynamics of pollen plants in the landscape. Ecol. Evol. 8, 5777–5791 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Wood, T. J., Holland, J. M. & Goulson, D. Providing foraging resources for solitary bees on farmland: current schemes for pollinators benefit a limited suite of species. J. Appl. Ecol. 54, 323–333 (2016).Garthwaite, D. et al. Collection of Pesticide Application Data in View of Performing Environmental Risk Assessments for Pesticides (EFSA, 2017).de Oliveira, R. C., Nascimento Queiroz, S. C., Pinto da Luz, C. F., Silveira Porto, R. & Rath, S. Bee pollen as a bioindicator of environmental pesticide contamination. Chemosphere 163, 525–534 (2016).Article 
PubMed 

Google Scholar 
Arena, M. & Sgolastra, F. A meta-analysis comparing the sensitivity of bees to pesticides. Ecotoxicology 23, 324–334 (2014).Article 
CAS 
PubMed 

Google Scholar 
Douglas, M. R., Sponsler, D. B., Lonsdorf, E. V. & Grozinger, C. M. County-level analysis reveals a rapidly shifting landscape of insecticide hazard to honey bees (Apis mellifera) on US farmland. Sci. Rep. 10, 797 (2020).Commission Implementing Regulation (EU) 2021/2081 of 26 November 2021 concerning the non-renewal of approval of the active substance indoxacarb, in accordance with Regulation (EC) No 1107/2009 of the European Parliament and of the Council concerning the placing of plant protection products on the market, and amending Commission Implementing Regulation (EU) No 540/2011 (EUR-Lex, 2021); http://data.europa.eu/eli/reg_impl/2021/2081/ojCommission Implementing Regulation (EU) 2020/23 of 13 January 2020 concerning the non-renewal of the approval of the active substance thiacloprid, in accordance with Regulation (EC) No. 1107/2009 of the European Parliament and of the Council concerning the placing of plant protection products on the market, and amending the Annex to Commission Implementing Regulation (EU) No 540/2011 (EUR-Lex, 2020); http://data.europa.eu/eli/reg_impl/2020/23/ojCommission Implementing Regulation (EU) 2018/783 of 29 May 2018 amending Implementing Regulation (EU) No 540/2011 as regards the conditions of approval of the active substance imidacloprid (EUR-Lex, 2018); http://data.europa.eu/eli/reg_impl/2018/783/ojHerbertsson, L., Jonsson, O., Kreuger, J., Smith, H. G. & Rundlöf, M. Scientific note: imidacloprid found in wild plants downstream permanent greenhouses in Sweden. Apidologie 52, 946–949 (2021).Article 

Google Scholar 
Tosi, S. et al. Long-term field-realistic exposure to a next-generation pesticide, flupyradifurone, impairs honey bee behaviour and survival. Commun. Biol. 4, 805 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Siviter, H. & Muth, F. Do novel insecticides pose a threat to beneficial insects?: novel insecticides harm insects. Proc. R. Soc. B 287, 20201265 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
EFSA. Guidance on the risk assessment of plant protection products on bees (Apis mellifera, Bombus spp. and solitary bees). EFSA J. 11, 3295 (2013).Guidance for Assessing Pesticide Risks to Bees (US EPA, 2014).Boyle, N. K. et al. Workshop on pesticide exposure assessment paradigm for non-apis bees: foundation and summaries. Environ. Entomol. 48, 4–11 (2019).Article 
PubMed 

Google Scholar 
EFSA. Analysis of the evidence to support the definition of specific protection goals for bumble bees and solitary bees. EFSA J. 19, EN-7125 (2022).Garibaldi, L. A. et al. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 339, 1608–1611 (2013).Article 
CAS 
PubMed 

Google Scholar 
Tscharntke, T., Grass, I., Wanger, T. C. & Westphal, C. Restoring biodiversity needs more than reducing pesticides. Trends Ecol. Evol. 37, 115–116 (2022).Article 
PubMed 

Google Scholar 
Topping, C. J. et al. Holistic environmental risk assessment for bees. Science 37, 897 (2021).Article 

Google Scholar 
Tsvetkov, N. et al. Chronic exposure to neonicotinoids reduces honey bee health near corn crops. Science 356, 1395–1397 (2017).Article 
CAS 
PubMed 

Google Scholar 
Jonsson, O., Fries, I. & Kreuger, J. Utveckling av Analysmetoder och Screening av Växtskyddsmedel i bin och Pollen (CKB, 2013).Sawyer, R. Pollen Identification for Beekeepers (Univ. Cardiff Press, 1981).IUPAC Pesticide Properties Data Base (Univ. of Hertfordshire, 2022).EFSA Scientific Committee & More, S.J. et al. Guidance on harmonised methodologies for human health, animal health and ecological risk assessment of combined exposure to multiple chemicals. EFSA J. 17, e05634 (2019).Martin, O. et al. Ten years of research on synergisms and antagonisms in chemical mixtures: a systematic review and quantitative reappraisal of mixture studies. Environ. Int. 146, 106206 (2021).Article 
CAS 
PubMed 

Google Scholar 
DiBartolomeis, M., Kegley, S., Mineau, P., Radford, R. & Klein, K. An assessment of acute insecticide toxicity loading (AITL) of chemical pesticides used on agricultural land in the United States. PLoS ONE 14, e0220029 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Test No. 213: Honeybees, Acute Oral Toxicity Test (OECD, 1998); https://doi.org/10.1787/9789264070165-enPrice, P. S. & Han, X. Maximum cumulative ratio (MCR) as a tool for assessing the value of performing a cumulative risk assessment. Int. J. Environ. Res. Public Health 8, 2212–2225 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Oksanen, J. et al. vegan community ecology package version 2.6-2 (2022).Lenth, R. emmeans: Estimated marginal means, aka least-squares means (2022).Lüdecke, D., Ben-shachar, M. S., Patil, I. & Makowski, D. performance: an R package for assessment, comparison and testing of statistical models statement of need. J. Open Source Softw. 6, 3139 (2021).Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).Article 

Google Scholar 
Kendall, L. K. et al. The potential and realized foraging movements of bees are differentially determined by body size and sociality. Ecology 103, e3809 (2022).Parreño, M. A. et al. Critical links between biodiversity and health in wild bee conservation. Trends Ecol. Evol. 37, 309–321 (2022).Article 
PubMed 

Google Scholar  More

Finkelman, S., Navarro, S., Rindner, M. & Dias, R. Effect of low pressure on the survival of Trogoderma granarium Everts, Lasioderma serricorne (F.) and Oryzaephilus surinamensis (L.) at 30°C. J. Stored. Prod. Res. 42, 23–30 (2006).Article 

Google Scholar 
Hosseininaveh, V., Bandani, A., Azmayeshfard, P., Hosseinkhani, S. & Kazzazi, M. Digestive proteolytic and amylolytic activities in Trogoderma granarium Everts (Dermestidae: Coleoptera). J. Stored. Prod. Res. 43, 515–522 (2007).Article 
CAS 

Google Scholar 
Burges, H. D. Development of the khapra beetle, Trogoderma granarium, in the lower part of its temperature range. J. Stored. Prod. Res. 44, 32–35 (2008).Article 

Google Scholar 
Hagstrum, D. W. & Subramanyam, B. Stored-Product Insect Resource 1–518 (AACC International Inc, 2009).Book 

Google Scholar 
Beal, R. S. Synopsis of the economic species of Trogoderma occurring in the United States with description of a new species (Coleoptera: Dermestidae). Ann. Entomol. Soc. Am. 49, 559–566 (1956).Article 

Google Scholar 
Day, C. & White, B. Khapra beetle, Trogoderma granarium interceptions and eradications in Australia and around the world. Crawley, School of Agricultural and Resource Economics, University of Western Australia, SARE Working paper 1609, (2016).Kerr, J. A. Khapra beetle returns. Pest Control 49, 24–25 (1981).
Google Scholar 
Stibick, J.N. New pest response guidelines: khapra beetle. US Department of Agriculture, Marketing and Regulatory Programs, Animal and Plant Health Inspection Service, Riverdale, pp. 114 (2009).Myers, S. W. & Hagstrum, D. W. Quarantine. In Stored Product Protection (eds Hagstrum, D. W. et al.) 297–304 (Kansas State University Agricultural Experiment Station and Cooperative Extension Service, 2012).
Google Scholar 
Athanassiou, C. G., Phillips, T. W. & Wakil, W. Biology and control of the khapra beetle, Trogoderma granarium, a major quarantine threat to global food security. Annu. Rev. Entomol. 64, 131–148 (2019).Article 
CAS 
PubMed 

Google Scholar 
Barak, A. V. Development of a new trap to detect and monitor khapra beetle (Coleoptera: Dermestidae). J. Econ. Entom. 82, 1470–1477 (1989).Article 

Google Scholar 
Gerken, A. R. & Campbell, J. F. Life history changes in Trogoderma variabile and T. inclusum due to mating delay with implications for mating disruption as a management tactic. Ecol. Evol. 8, 2428–2439 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Partida, G. J. & Strong, R. G. Comparative studies on the biologies of six species of Trogoderma: T variabile. Ann. Entomol. Soc. Am. 68, 115–125 (1975).Article 

Google Scholar 
Strong, R. G. Comparative studies on the biologies of six species of Trogoderma: T inclusum. Ann. Entomol. Soc. Am. 68, 91–104 (1975).Article 

Google Scholar 
Phillips, T. W., Pfannenstiel, L. & Hagstrum, D. Survey of Trogoderma species (Coleoptera: Dermestidae) associated with international trade of dried distiller’s grains and solubles in the USA. Julius Kühn Archiv. 463, 233–238 (2008).
Google Scholar 
Hadaway, A. The biology of the beetles, Trogoderma granarium Everts and Trogoderma versicolor (Creutz). Bull. Entomol. Res. 46, 781–796 (1956).Article 
CAS 

Google Scholar 
Phillips, T.W., Pfannenstiel, L. & Hagstrum, D. Survey of Trogoderma species (Coleoptera: Dermestidae) associated with international trade of dried distiller’s grains and solubles in the USA. In: Adler CS, Opit G, Fürstenau B, Müller-Blenkle C, Kern P, Arthur FH et al., editors. Proceedings of the 12th International Working Conference on Stored Product Protection; Vol. 1, Quedlinburg, Julius-Kühn-Archiv, pp. 233–238 (2018).Gorham, J.R. Insect and Mite Pests in Food: An Illustrated Key. Vol. 1 and 2. US Department of Agriculture, Agricultural Research Service (1991).Olson, R. L. O., Farris, R. E., Barr, N. B. & Cognato, A. I. Molecular identification of Trogoderma granarium (Coleoptera: Dermestidae) using the 16S gene. J. Pest Sci. 87, 701–710 (2014).Article 

Google Scholar 
Furui, S., Miyanoshita, A., Imamura, T., Minegishi, Y. & Kokutani, R. Qualitative real-time PCR identification of the khapra beetle, Trogoderma granarium (Coleoptera: Dermestidae). Appl. Entomol. Zool. 54, 101–107 (2019).Article 
CAS 

Google Scholar 
Rako, L. et al. A LAMP (loop-mediated isothermal amplification) test for rapid identification of Khapra beetle (Trogoderma granarium). Pest Manag. Sci. 77, 5509–5521 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Castañé, C., Agustí, N., del Estal, P. & Riudavets, J. Survey of Trogoderma spp. in Spanish mills and warehouses. J. Stored. Prod. Res. 88, 101661 (2020).Article 

Google Scholar 
Trujillo-González, et al. Detection of khapra beetle environmental DNA using portable technologies in Australian biosecurity. Front. Insect Sci. 2, e795379 (2022).Article 

Google Scholar 
Svec, D., Tichopad, A., Novosadova, V., Pfaffl, M. W. & Kubista, M. How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments. Biomol. Detect. Quantif. 3, 9–16 (2015).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Taylor, S. C. et al. The Ultimate qPCR experiment: Producing publication quality, reproducible data the first time. Trends Biotechnol. 37, 761–774 (2019).Article 
CAS 
PubMed 

Google Scholar 
Van Holm, W. et al. A viability quantitative PCR dilemma: Are longer amplicons better?. Appl. Environ. Microbiol. 87, e0265320 (2021).Article 
PubMed 

Google Scholar 
Ratnasingham, S. & Hebert, P. D. N. BOLD: The barcode of life data system (wwwbarcodinglifeorg). Mol. Ecol. Notes 7, 355–364 (2007).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wittwer, C. T. & Kusakawa, N. Real-time PCR. In Molecular microbiology: Diagnostic principles and practice (eds Persing, D. H. et al.) 71–84 (ASM Press, 2004).
Google Scholar 
Stewart, D. et al. A needle in a haystack: A multigene TaqMan assay for the detection of Asian gypsy moths in bulk pheromone trap samples. Biol. Invasions 21, 1843–1856 (2019).Article 

Google Scholar 
Butterwort, V. et al. A DNA extraction method for insects from sticky traps: Targeting a low abundance pest, Phthorimaea absoluta (Lepidoptera: Gelechiidae), in mixed species communities. J. Econ. Entom. 115, 844–851 (2022).Article 
CAS 
PubMed 

Google Scholar 
Carew, M. E., Coleman, R. A. & Hoffmann, A. A. Can non-destructive DNA extraction of bulk invertebrate samples be used for metabarcoding?. PeerJ 6, e4980 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Domingue, M.J. et al. Outcome of direct competition between Trogoderma granarium and Trogoderma inclusum over varying commodities, temperatures, and experimental duration. In Submission to Scientific Reports.Zieritz, A. et al. Development and evaluation of hotshot protocols for cost- and time-effective extraction of PCR-ready DNA from single freshwater mussel larvae (Bivalvia: Unionida). J. Molluscan Stud. 84, 198–201 (2018).Article 

Google Scholar 
Djoumad, A. et al. Development of a qPCR-based method for counting overwintering spruce budworm (Choristoneura fumiferana) larvae collected during fall surveys and for assessing their natural enemy load: A proof-of-concept study. Pest Manag. Sci. 78, 336–343 (2022).Article 
CAS 
PubMed 

Google Scholar 
Chen, H., Rangasamy, M., Tan, S. Y., Wang, H. & Siegfried, B. D. Evaluation of five methods for total DNA extraction from western corn rootworm beetles. PLoS ONE 5, e11963 (2010).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Beckmann, J. S. & Soller, M. Restriction fragment length polymorphisms in genetic improvement: Methodologies, mapping and costs. Theor. Appl. Genet. 67, 35–43 (1983).Article 
CAS 
PubMed 

Google Scholar 
Arimoto, M., Satoh, M., Uesugi, R. & Osakabe, M. PCR-RFLP analysis for identification of Tetranychus spider mite species (Acari: Tetranychidae). J. Econ. Entom. 106, 661–668 (2013).Article 
CAS 
PubMed 

Google Scholar 
Vezenegho, S. B. et al. Discrimination of 15 Amazonian anopheline mosquito species by polymerase chain reaction—Restriction fragment length polymorphism. J. Med. Entomol. 59, 1060–1064 (2022).Article 
CAS 
PubMed 

Google Scholar 
Beal, R. S. Annotated checklist of Nearctic Dermestidae with revised key to the genera. Coleopt. Bull. 57, 391–404 (2003).Article 

Google Scholar 
Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 3, 294–299 (1994).CAS 
PubMed 

Google Scholar 
Liu, H. & Mottern, J. An old remedy for a new problem? Identification of Ooencyrtus kuvanae (Hymenoptera: Encyrtidae), an egg parasitoid of Lycorma delicatula (Hemiptera: Fulgoridae) in North America. J. Insect Sci. 17, 18 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Simon, C. et al. Evolution, weighing, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Ann. Entomol. Soc. Am. 87, 651–701 (1994).Article 
CAS 

Google Scholar 
Dowton, M. & Austin, A. D. Evidence for AT-transversion bias in wasp (Hymenoptera: Symphyta) mitochondrial genes and its implications for the origin of parasitism. J. Mol. Evol. 44, 398–405 (1997).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Untergasser, A. et al. Primer3—New capabilities and interfaces. Nucleic Acids Res. 40, e115 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ye, J. et al. Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction. BMC Bioinform. 13, 134 (2012).Article 
CAS 

Google Scholar 
Süss, B., Flekna, G., Wagner, M. & Hein, I. Studying the effect of single mismatches in primer and probe binding regions on amplification curves and quantification in real-time PCR. J. Microbiol. Methods 76, 316–319 (2009).Article 
PubMed 

Google Scholar 
Stadhouders, R. et al. The effect of primer-template mismatches on the detection and quantification of nucleic acids using the 5’ nuclease assay. J. Mol. Diagn. 12, 109–117 (2010).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Stewart, D. et al. A multi-species TaqMan PCR assay for the identification of Asian gypsy moths (Lymantria spp.) and other invasive Lymantriines of biosecurity concern to North America. PLoS ONE 11, e0160878 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Bustin, S. A. et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 55, 1–12 (2009).Article 

Google Scholar  More

Breed differences in animal feed conversion and economic trait performanceThroughout the feed intake measurement period, summary statistics shows animals on test had an average DMI of 1.11 kg/d (SD = 0.18), ADG of 0.27 kg/d (SD = 0.1), FCR of 4.04 kg of DMI/ Kg of ADG (SD = 0.1), start weight of 29.60 kg (SD = 3.7), final live weight of 46.00 kg (SD = 2.9), carcass weight of 20.20 kg (SD = 1.6), and a KO% of 44.1% (SD = 2.3). Average daily gain (P = 0.005), FCR (P = 0.035), CW (P  More