Stochastic community assembly of abundant taxa maintains the relationship of soil biodiversity-multifunctionality under mercury stress

Shuai Du, Xin-Qi Li, Li Bi, Dong Zhu, Hang-Wei Hu, Xiuli Hao, Jiao Feng, Qiaoyun Huang, Yu-Rong Liu

Soil Ecology Letters ›› 2024, Vol. 6 ›› Issue (2) : 230197.

PDF(1158 KB)
PDF(1158 KB)
Soil Ecology Letters ›› 2024, Vol. 6 ›› Issue (2) : 230197. DOI: 10.1007/s42832-023-0197-z
RESEARCH ARTICLE
RESEARCH ARTICLE

Stochastic community assembly of abundant taxa maintains the relationship of soil biodiversity-multifunctionality under mercury stress

Author information +
History +

Highlights

● Soil abundant taxa diversity positively related to multifunctionality under Hg stress.

● Microbial network complexity of soil abundant taxa supported the strength of SBF.

● Stochastic assembly of soil abundant subcommunity supported the strength of SBF.

● Stochastic ratio was the most important predictor for the strength of SBF.

Abstract

It is known that soil microbial communities are intricately linked to multiple ecosystem functions and can maintain the relationship between soil biodiversity and multifunctionality (SBF) under environmental stresses. However, the relative contributions and driving forces of abundant and rare taxa within the communities in maintaining soil biodiversity-multifunctionality relationship under pollution stresses are still unclear. Here, we conducted microcosm experiments to estimate the importance of soil abundant and rare taxa in predicting these relationships under heavy metal mercury (Hg) stress in paired paddy and upland fields. The results revealed that the diversity of abundant taxa, rather than rare taxa, was positively related to multifunctionality, with the abundant subcommunity tending to maintain a larger proportion of soil functions including chitin degradation, protein degradation, and phosphorus mineralization. Soil multitrophic network complexity consisting of abundant species showed positive correlations with biodiversity and multifunctionality, and supported the strength of SBF within a network complexity range. Stochastic assembly processes of the abundant subcommunity were positively correlated with the strength of SBF, although stochastic processes decreased the biodiversity and the multifunctionality, respectively. After simultaneously accounting for multiple factors on the strength of SBF, we found that the stochastic community assembly ratio of abundant taxa was the most important predictor for SBF strength under Hg stress. Our results highlight the importance of abundant taxa in supporting soil multifunctionality, and elucidate the linkages between community assembly, network complexity and SBF relationship under environmental stresses.

Graphical abstract

Keywords

abundant taxa / biodiversity-multifunctionality relationship / community assembly / network complexity / environmental stresses

Cite this article

Download citation ▾
Shuai Du, Xin-Qi Li, Li Bi, Dong Zhu, Hang-Wei Hu, Xiuli Hao, Jiao Feng, Qiaoyun Huang, Yu-Rong Liu. Stochastic community assembly of abundant taxa maintains the relationship of soil biodiversity-multifunctionality under mercury stress. Soil Ecology Letters, 2024, 6(2): 230197 https://doi.org/10.1007/s42832-023-0197-z

References

[1]
Adler, P.B., HilleRisLambers, J., Levine, J.M., 2007. A niche for neutrality. Ecology Letters10, 95–104.
CrossRef Google scholar
[2]
Archer, E., 2016. rfPermute: estimate permutation p-values for random forest importance metrics. R package version 1
[3]
Balvanera, P., Pfisterer, A.B., Buchmann, N., He, J.S., Nakashizuka, T., Raffaelli, D., Schmid, B., 2006. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecology Letters9, 1146–1156.
CrossRef Google scholar
[4]
Balvanera, P., Siddique, I., Dee, L., Paquette, A., Isbell, F., Gonzalez, A., Byrnes, J., O’Connor, M.I., Hungate, B.A., Griffin, J.N., 2014. Linking biodiversity and ecosystem services: current uncertainties and the necessary next steps. Bioscience64, 49–57.
CrossRef Google scholar
[5]
Barberán, A., Bates, S.T., Casamayor, E.O., Fierer, N., 2012. Using network analysis to explore co-occurrence patterns in soil microbial communities. ISME Journal6, 343–351.
CrossRef Google scholar
[6]
Barberán, A., Ramirez, K.S., Leff, J.W., Bradford, M.A., Wall, D.H., Fierer, N., 2014. Why are some microbes more ubiquitous than others? Predicting the habitat breadth of soil bacteria.. Ecology Letters17, 794–802.
CrossRef Google scholar
[7]
Bardgett, R.D., Van Der Putten, W.H., 2014. Belowground biodiversity and ecosystem functioning. Nature515, 505–511.
CrossRef Google scholar
[8]
Bastian, M., Heymann, S., Jacomy, M., 2009. Gephi: an open source software for exploring and manipulating networks. Proceedings of the International AAAI Conference on Web and Social Media3, 361–362.
CrossRef Google scholar
[9]
Bell, C.W., Fricks, B.E., Rocca, J.D., Steinweg, J.M., McMahon, S.K., Wallenstein, M.D., 2013. High-throughput fluorometric measurement of potential soil extracellular enzyme activities. Journal of Visualized Experiments81, e50961.
[10]
Bender, S.F., Wagg, C., van der Heijden, M.G., 2016. An underground revolution: biodiversity and soil ecological engineering for agricultural sustainability. Trends in Ecology & Evolution31, 440–452.
CrossRef Google scholar
[11]
Breiman, L., 2001. Random forests. Machine Learning45, 5–32.
CrossRef Google scholar
[12]
Byrnes, J.E., Gamfeldt, L., Isbell, F., Lefcheck, J.S., Griffin, J.N., Hector, A., Cardinale, B.J., Hooper, D.U., Dee, L.E., Emmett Duffy, J., 2014. Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions. Methods in Ecology and Evolution5, 111–124.
CrossRef Google scholar
[13]
Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Pena, A.G., Goodrich, J.K., Gordon, J.I., Huttley, G.A., Kelley, S.T., Knights, D., Koenig, J.E., Ley, R.E., Lozupone, C.A., McDonald, D., Muegge, B.D., Pirrung, M., Reeder, J., Sevinsky, J.R., Tumbaugh, P.J., Walters, W.A., Widmann, J., Yatsunenko, T., Zaneveld, J., Knight, R., 2010. QIIME allows analysis of high-throughput community sequencing data. Nature Methods7, 335–336.
CrossRef Google scholar
[14]
Cardinale, B.J., 2011. Biodiversity improves water quality through niche partitioning. Nature472, 86–89.
CrossRef Google scholar
[15]
Carlson, M.L., Flagstad, L.A., Gillet, F., Mitchell, E.A., 2010. Community development along a proglacial chronosequence: are above-ground and below-ground community structure controlled more by biotic than abiotic factors? Journal of Ecology 98, 1084–1095
[16]
Chase, J.M., Myers, J.A., 2011. Disentangling the importance of ecological niches from stochastic processes across scales. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences366, 2351–2363.
CrossRef Google scholar
[17]
Csardi, G., Nepusz, T., 2006. The igraph software package for complex network research. InterJournal, Complex Systems1695, 1–9.
[18]
De Vries, F.T., Thébault, E., Liiri, M., Birkhofer, K., Tsiafouli, M.A., Bjørnlund, L., Bracht Jørgensen, H., Brady, M.V., Christensen, S., De Ruiter, P.C., d’Hertefeldt, T., Frouz, J., Hedlund, K., Hemerik, L., Hol, W.H.G., Hotes, S., Mortimer, S.R., Setälä, H., Sgardelis, S.P., Uteseny, K., van der Putten, W.H., Wolters, V., Bardgett, R.D., 2013. Soil food web properties explain ecosystem services across European land use systems. Proceedings of the National Academy of Sciences of the United States of America110, 14296–14301.
CrossRef Google scholar
[19]
Delgado-Baquerizo, M., Maestre, F.T., Reich, P.B., Jeffries, T.C., Gaitan, J.J., Encinar, D., Berdugo, M., Campbell, C.D., Singh, B.K., 2016. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nature Communications7, 1–8.
CrossRef Google scholar
[20]
Delgado-Baquerizo, M., Reich, P.B., Trivedi, C., Eldridge, D.J., Abades, S., Alfaro, F.D., Bastida, F., Berhe, A.A., Cutler, N.A., Gallardo, A., Garcia-Velazquez, L., Hart, S.C., Hayes, P.E., He, J.Z., Hseu, Z.Y., Hu, H.W., Kirchmair, M., Neuhauser, S., Perez, C.A., Reed, S.C., Santos, F., Sullivan, B.W., Trivedi, P., Wang, J.T., Weber-Grullon, L., Williams, M.A., Singh, B.K., 2020. Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nature Ecology & Evolution4, 210–220.
CrossRef Google scholar
[21]
Du, S., Li, X.Q., Feng, J., Huang, Q., Liu, Y.R., 2023. Soil core microbiota drive community resistance to mercury stress and maintain functional stability. Science of the Total Environment894, 165056.
CrossRef Google scholar
[22]
Du, S., Li, X.Q., Hao, X., Hu, H.W., Feng, J., Huang, Q., Liu, Y.R., 2022. Stronger responses of soil protistan communities to legacy mercury pollution than bacterial and fungal communities in agricultural systems. ISME Communications2, 1–12.
CrossRef Google scholar
[23]
Duffy, J.E., Cardinale, B.J., France, K.E., McIntyre, P.B., Thébault, E., Loreau, M., 2007. The functional role of biodiversity in ecosystems: incorporating trophic complexity. Ecology Letters10, 522–538.
CrossRef Google scholar
[24]
Edgar, R.C., 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods10, 996–998.
CrossRef Google scholar
[25]
Fajardo, C., Costa, G., Nande, M., Botías, P., García-Cantalejo, J., Martín, M., 2019. Pb, Cd, and Zn soil contamination: monitoring functional and structural impacts on the microbiome. Applied Soil Ecology135, 56–64.
CrossRef Google scholar
[26]
Fortmann-Roe, S., 2015. Consistent and clear reporting of results from diverse modeling techniques: the A3 method. Journal of Statistical Software66, 1–23.
CrossRef Google scholar
[27]
Gamfeldt, L., Hillebrand, H., Jonsson, P.R., 2008. Multiple functions increase the importance of biodiversity for overall ecosystem functioning. Ecology89, 1223–1231.
CrossRef Google scholar
[28]
Gardes, M., Bruns, T.D., 1993. ITS primers with enhanced specificity for basidiomycetes-application to the identification of mycorrhizae and rusts. Molecular Ecology2, 113–118.
CrossRef Google scholar
[29]
Gaston, K.J., Fuller, R.A., 2007. Biodiversity and extinction: losing the common and the widespread. Progress in Physical Geography31, 213–225.
CrossRef Google scholar
[30]
Guillou, L., Bachar, D., Audic, S., Bass, D., Berney, C., Bittner, L., Boutte, C., Burgaud, G., de Vargas, C., Decelle, J., Del Campo, J., Dolan, J.R., Dunthorn, M., Edvardsen, B., Holzmann, M., Kooistra, W.H., Lara, E., Le Bescot, N., Logares, R., Mahe, F., Massana, R., Montresor, M., Morard, R., Not, F., Pawlowski, J., Probert, I., Sauvadet, A.L., Siano, R., Stoeck, T., Vaulot, D., Zimmermann, P., Christen, R., 2013. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote small sub-unit rRNA sequences with curated taxonomy. Nucleic Acids Research41, D597–D604.
CrossRef Google scholar
[31]
Hao, X., Zhu, J., Rensing, C., Liu, Y., Gao, S., Chen, W., Huang, Q., Liu, Y.R., 2021. Recent advances in exploring the heavy metal (loid) resistant microbiome. Computational and Structural Biotechnology Journal19, 94–109.
CrossRef Google scholar
[32]
Hughes, J.B., Daily, G.C., Ehrlich, P.R., 1997. Population diversity: its extent and extinction. Science278, 689–692.
CrossRef Google scholar
[33]
Isbell, F., Craven, D., Connolly, J., Loreau, M., Schmid, B., Beierkuhnlein, C., Bezemer, T.M., Bonin, C., Bruelheide, H., De Luca, E., Ebeling, A., Griffin, J.N., Guo, Q., Hautier, Y., Hector, A., Jentsch, A., Kreyling, J., Lanta, V., Manning, P., Meyer, S.T., Mori, A.S., Naeem, S., Niklaus, P.A., Polley, H.W., Reich, P.B., Roscher, C., Seabloom, E.W., Smith, M.D., Thakur, M.P., Tilman, D., Tracy, B.F., van der Putten, W.H., van Ruijven, J., Weigelt, A., Weisser, W.W., Wilsey, B., Eisenhauer, N., 2015. Biodiversity increases the resistance of ecosystem productivity to climate extremes. Nature526, 574–577.
CrossRef Google scholar
[34]
Jassey, V.E., Lamentowicz, Ł., Robroek, B.J., Gąbka, M., Rusińska, A., Lamentowicz, M., 2014. Plant functional diversity drives niche‐size‐structure of dominant microbial consumers along a poor to extremely rich fen gradient. Journal of Ecology102, 1150–1162.
CrossRef Google scholar
[35]
Jiao, S., Chen, W., Wei, G., 2017. Biogeography and ecological diversity patterns of rare and abundant bacteria in oil-contaminated soils. Molecular Ecology26, 5305–5317.
CrossRef Google scholar
[36]
Jiao, S., Lu, Y., 2020. Abundant fungi adapt to broader environmental gradients than rare fungi in agricultural fields. Global Change Biology26, 4506–4520.
CrossRef Google scholar
[37]
Jiao, S., Lu, Y., Wei, G., 2021. Soil multitrophic network complexity enhances the link between biodiversity and multifunctionality in agricultural systems. Global Change Biology28, 140–153.
CrossRef Google scholar
[38]
Jiao, S., Wang, J., Wei, G., Chen, W., Lu, Y., 2019. Dominant role of abundant rather than rare bacterial taxa in maintaining agro-soil microbiomes under environmental disturbances. Chemosphere235, 248–259.
CrossRef Google scholar
[39]
Jiao, S., Yang, Y., Xu, Y., Zhang, J., Lu, Y., 2020. Balance between community assembly processes mediates species coexistence in agricultural soil microbiomes across eastern China. ISME Journal14, 202–216.
CrossRef Google scholar
[40]
Jousset, A., Bienhold, C., Chatzinotas, A., Gallien, L., Gobet, A., Kurm, V., Küsel, K., Rillig, M.C., Rivett, D.W., Salles, J.F., van der Heijden, M.G.A., Youssef, N.H., Zhang, X., Wei, Z., Hol, W.H.G., 2017. Where less may be more: how the rare biosphere pulls ecosystems strings. ISME Journal11, 853–862.
CrossRef Google scholar
[41]
Kardol, P., Wardle, D.A., 2010. How understanding aboveground-belowground linkages can assist restoration ecology. Trends in Ecology & Evolution25, 670–679.
CrossRef Google scholar
[42]
Knelman, J.E., Nemergut, D.R., 2014. Changes in community assembly may shift the relationship between biodiversity and ecosystem function. Frontiers Media SA, p. 424
[43]
Kraft, N.J., Adler, P.B., Godoy, O., James, E.C., Fuller, S., Levine, J.M., 2015. Community assembly, coexistence and the environmental filtering metaphor. Functional Ecology29, 592–599.
CrossRef Google scholar
[44]
Langfelder, P., Horvath, S., 2012. Fast R functions for robust correlations and hierarchical clustering. Journal of Statistical Software46, 1–17.
CrossRef Google scholar
[45]
Leibold, M.A., Holyoak, M., Mouquet, N., Amarasekare, P., Chase, J.M., Hoopes, M.F., Holt, R.D., Shurin, J.B., Law, R., Tilman, D., Loreau, M., Gonzalez, A., 2004. The metacommunity concept: a framework for multi-scale community ecology. Ecology Letters7, 601–613.
CrossRef Google scholar
[46]
Lennon, J.T., Jones, S.E., 2011. Microbial seed banks: the ecological and evolutionary implications of dormancy. Nature Reviews Microbiology9, 119–130.
CrossRef Google scholar
[47]
Li, H.Z., Zhu, D., Lindhardt, J.H., Lin, S.M., Ke, X., Cui, L., 2021. Long-term fertilization history alters effects of microplastics on soil properties, microbial communities, and functions in diverse farmland ecosystem. Environmental Science & Technology55, 4658–4668.
CrossRef Google scholar
[48]
Li, M., Wei, Z., Wang, J., Jousset, A., Friman, V.P., Xu, Y., Shen, Q., Pommier, T., 2019a. Facilitation promotes invasions in plant-associated microbial communities. Ecology Letters22, 149–158.
CrossRef Google scholar
[49]
Li, P., Liu, J., Jiang, C., Wu, M., Liu, M., Li, Z., 2019b. Distinct Successions of common and rare bacteria in soil under humic acid amendment – a microcosm study. Frontiers in Microbiology10, 2271.
CrossRef Google scholar
[50]
Liu, L., Yang, J., Yu, Z., Wilkinson, D.M., 2015. The biogeography of abundant and rare bacterioplankton in the lakes and reservoirs of China. ISME Journal9, 2068–2077.
CrossRef Google scholar
[51]
Liu, Y.R., Delgado-Baquerizo, M., Bi, L., Zhu, J., He, J.Z., 2018. Consistent responses of soil microbial taxonomic and functional attributes to mercury pollution across China. Microbiome6, 183.
CrossRef Google scholar
[52]
Liu, Y.R., van der Heijden, M.G., Riedo, J., Sanz-Lazaro, C., Eldridge, D.J., Bastida, F., Moreno-Jiménez, E., Zhou, X.Q., Hu, H.W., He, J.Z., Moreno, J.L., Abades, S., Alfaro, F., Bamigboye, A.R., Berdugo, M., Blanco-Pastor, J.L., de los Ríos, A., Duran, J., Grebenc, T., Illán, J.G., Makhalanyane, T.P., Molina-Montenegro, M.A., Nahberger, T.U., Peñaloza-Bojacá, G.F., Plaza, C., Rey, A., Rodríguez, A., Siebe, C., Teixido, A.L., Casado-Coy, N., Trivedi, P., Torres-Díaz, C., Verma, J.P., Mukherjee, A., Zeng, X.M., Wang, L., Wang, J., Zaady, E., Zhou, X., Huang, Q., Tan, W., Zhu, Y.G., Rillig, M.C., Delgado-Baquerizo, M., 2023. Soil contamination in nearby natural areas mirrors that in urban greenspaces worldwide. Nature Communications14, 1706.
CrossRef Google scholar
[53]
Lu, T., Xu, N., Lei, C., Zhang, Q., Zhang, Z., Sun, L., He, F., Zhou, N.Y., Peñuelas, J., Zhu, Y.G., Qian, H., 2023. Bacterial biogeography in China and its association to land use and soil organic carbon. Soil Ecology Letters5, .
CrossRef Google scholar
[54]
Lynch, M.D., Neufeld, J.D., 2015. Ecology and exploration of the rare biosphere. Nature Reviews Microbiology13, 217–229.
CrossRef Google scholar
[55]
Ma, B., Wang, H., Dsouza, M., Lou, J., He, Y., Dai, Z., Brookes, P.C., Xu, J., Gilbert, J.A., 2016. Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China. ISME Journal10, 1891–1901.
CrossRef Google scholar
[56]
Maestre, F.T., Quero, J.L., Gotelli, N.J., Escudero, A., Ochoa, V., Delgado-Baquerizo, M., García-Gómez, M., Bowker, M.A., Soliveres, S., Escolar, C., García-Palacios, P., Berdugo, M., Valencia, E., Gozalo, B., Gallardo, A., Aguilera, L., Arredondo, T., Blones, J., Boeken, B., Bran, D., Conceição, A.A., Cabrera, O., Chaieb, M., Derak, M., Eldridge, D.J., Espinosa, C.I., Florentino, A., Gaitán, J., Gatica, M.G., Ghiloufi, W., Gómez-González, S., Gutiérrez, J.R., Hernández, R.M., Huang, X., Huber-Sannwald, E., Jankju, M., Miriti, M., Monerris, J., Mau, R.L., Morici, E., Naseri, K., Ospina, A., Polo, V., Prina, A., Pucheta, E., Ramírez-Collantes, D.A., Romão, R., Tighe, M., Torres-Díaz, C., Val, J., Veiga, J.P., Wang, D., Zaady, E., 2012. Plant species richness and ecosystem multifunctionality in global drylands. Science335, 214–218.
CrossRef Google scholar
[57]
Mahbub, K.R., Krishnan, K., Naidu, R., Andrews, S., Megharaj, M., 2017. Mercury toxicity to terrestrial biota. Ecological Indicators74, 451–462.
CrossRef Google scholar
[58]
Meyer, S.T., Ptacnik, R., Hillebrand, H., Bessler, H., Buchmann, N., Ebeling, A., Eisenhauer, N., Engels, C., Fischer, M., Halle, S., Klein, A.M., Oelmann, Y., Roscher, C., Rottstock, T., Scherber, C., Scheu, S., Schmid, B., Schulze, E.D., Temperton, V.M., Tscharntke, T., Voigt, W., Weigelt, A., Wilcke, W., Weisser, W.W., 2018. Biodiversity–multifunctionality relationships depend on identity and number of measured functions. Nature Ecology & Evolution2, 44–49.
CrossRef Google scholar
[59]
Mokany, K., Burley, H.M., Paini, D.R., 2013. β Diversity contributes to ecosystem processes more than by simply summing the parts. Proceedings of the National Academy of Sciences of the United States of America110, E4057–E4057.
CrossRef Google scholar
[60]
Mori, A.S., Isbell, F., Seidl, R., 2018. β-diversity, community assembly, and ecosystem functioning. Trends in Ecology & Evolution33, 549–564.
CrossRef Google scholar
[61]
Mouillot, D., Graham, N.A., Villéger, S., Mason, N.W., Bellwood, D.R., 2013. A functional approach reveals community responses to disturbances. Trends in Ecology & Evolution28, 167–177.
CrossRef Google scholar
[62]
Newman, M.E., 2003. The structure and function of complex networks. SIAM Review45, 167–256.
CrossRef Google scholar
[63]
Newman, M.E., 2006. Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America103, 8577–8582.
CrossRef Google scholar
[64]
Nilsson, R.H., Larsson, K.H., Taylor, A.F.S., Bengtsson-Palme, J., Jeppesen, T.S., Schigel, D., Kennedy, P., Picard, K., Glöckner, F.O., Tedersoo, L., Saar, I., Kõljalg, U., Abarenkov, K., 2019. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research47, D259–D264.
CrossRef Google scholar
[65]
Ning, D., Deng, Y., Tiedje, J.M., Zhou, J., 2019. A general framework for quantitatively assessing ecological stochasticity. Proceedings of the National Academy of Sciences of the United States of America116, 16892–16898.
CrossRef Google scholar
[66]
Pedrós-Alió, C., 2012. The rare bacterial biosphere. Annual Review of Marine Science4, 449–466.
CrossRef Google scholar
[67]
Pocock, M.J., Evans, D.M., Memmott, J., 2012. The robustness and restoration of a network of ecological networks. Science335, 973–977.
CrossRef Google scholar
[68]
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., Glockner, F.O., 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research41, D590–D596.
CrossRef Google scholar
[69]
Rillig, M.C., Ryo, M., Lehmann, A., 2021. Classifying human influences on terrestrial ecosystems. Global Change Biology27, 2273–2278.
CrossRef Google scholar
[70]
Rillig, M.C., Ryo, M., Lehmann, A., Aguilar-Trigueros, C.A., Buchert, S., Wulf, A., Iwasaki, A., Roy, J., Yang, G., 2019. The role of multiple global change factors in driving soil functions and microbial biodiversity. Science366, 886–890.
CrossRef Google scholar
[71]
Rivett, D.W., Bell, T., 2018. Abundance determines the functional role of bacterial phylotypes in complex communities. Nature Microbiology3, 767–772.
CrossRef Google scholar
[72]
Schermelleh-Engel, K., Moosbrugger, H., Müller, H., 2003. Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online8, 23–74.
[73]
Soliveres, S., Manning, P., Prati, D., Gossner, M.M., Alt, F., Arndt, H., Baumgartner, V., Binkenstein, J., Birkhofer, K., Blaser, S., Blüthgen, N., Boch, S., Böhm, S., Börschig, C., Buscot, F., Diekötter, T., Heinze, J., Hölzel, N., Jung, K., Klaus, V.H., Klein, A.M., Kleinebecker, T., Klemmer, S., Krauss, J., Lange, M., Morris, E.K., Müller, J., Oelmann, Y., Overmann, J., Pašalić, E., Renner, S.C., Rillig, M.C., Schaefer, H.M., Schloter, M., Schmitt, B., Schöning, I., Schrumpf, M., Sikorski, J., Socher, S.A., Solly, E.F., Sonnemann, I., Sorkau, E., Steckel, J., Steffan-Dewenter, I., Stempfhuber, B., Tschapka, M., Türke, M., Venter, P., Weiner, C.N., Weisser, W.W., Werner, M., Westphal, C., Wilcke, W., Wolters, V., Wubet, T., Wurst, S., Fischer, M., Allan, E., 2016. Locally rare species influence grassland ecosystem multifunctionality. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences371, 20150269.
CrossRef Google scholar
[74]
Stegen, J.C., Lin, X., Fredrickson, J.K., Chen, X., Kennedy, D.W., Murray, C.J., Rockhold, M.L., Konopka, A., 2013. Quantifying community assembly processes and identifying features that impose them. ISME Journal7, 2069–2079.
CrossRef Google scholar
[75]
Stoeck, T., Bass, D., Nebel, M., Christen, R., Jones, M.D., Breiner, H.W., Richards, T.A., 2010. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Molecular Ecology19, 21–31.
CrossRef Google scholar
[76]
Trivedi, P., Delgado-Baquerizo, M., Trivedi, C., Hu, H., Anderson, I.C., Jeffries, T.C., Zhou, J., Singh, B.K., 2016. Microbial regulation of the soil carbon cycle: evidence from gene–enzyme relationships. ISME Journal10, 2593–2604.
CrossRef Google scholar
[77]
Tsiafouli, M.A., Thébault, E., Sgardelis, S.P., De Ruiter, P.C., Van Der Putten, W.H., Birkhofer, K., Hemerik, L., De Vries, F.T., Bardgett, R.D., Brady, M.V., Bjornlund, L., Jørgensen, H.B., Christensen, S., Hertefeldt, T.D., Hotes, S., Gera Hol, W.H., Frouz, J., Liiri, M., Mortimer, S.R., Setälä, H., Tzanopoulos, J., Uteseny, K., Pižl, V., Stary, J., Wolters, V., Hedlund, K., 2015. Intensive agriculture reduces soil biodiversity across Europe. Global Change Biology21, 973–985.
CrossRef Google scholar
[78]
Van Elsas, J.D., Chiurazzi, M., Mallon, C.A., Elhottovā, D., Krištůfek, V., Salles, J.F., 2012. Microbial diversity determines the invasion of soil by a bacterial pathogen. Proceedings of the National Academy of Sciences of the United States of America109, 1159–1164.
CrossRef Google scholar
[79]
Vellend, M., 2010. Conceptual synthesis in community ecology. Quarterly Review of Biology85, 183–206.
CrossRef Google scholar
[80]
Wagg, C., Bender, S.F., Widmer, F., Van Der Heijden, M.G., 2014. Soil biodiversity and soil community composition determine ecosystem multifunctionality. Proceedings of the National Academy of Sciences of the United States of America111, 5266–5270.
CrossRef Google scholar
[81]
Wagg, C., Schlaeppi, K., Banerjee, S., Kuramae, E.E., van der Heijden, M.G., 2019. Fungal-bacterial diversity and microbiome complexity predict ecosystem functioning. Nature Communications10, 4841.
CrossRef Google scholar
[82]
Walkley, A., Black, I.A., 1934. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Science37, 29–38.
CrossRef Google scholar
[83]
Wang, Y.F., Chen, P., Wang, F.H., Han, W.X., Qiao, M., Dong, W.X., Hu, C.S., Zhu, D., Chu, H.Y., Zhu, Y.G., 2022b. The ecological clusters of soil organisms drive the ecosystem multifunctionality under long-term fertilization. Environment International161, 107133.
CrossRef Google scholar
[84]
Wu, W., Logares, R., Huang, B., Hsieh, C., 2017. Abundant and rare picoeukaryotic sub-communities present contrasting patterns in the epipelagic waters of marginal seas in the northwestern Pacific Ocean. Environmental Microbiology19, 287–300.
CrossRef Google scholar
[85]
Xun, W., Li, W., Xiong, W., Ren, Y., Liu, Y., Miao, Y., Xu, Z., Zhang, N., Shen, Q., Zhang, R., 2019. Diversity-triggered deterministic bacterial assembly constrains community functions. Nature Communications10, 3833.
CrossRef Google scholar
[86]
Xun, W., Liu, Y., Li, W., Ren, Y., Xiong, W., Xu, Z., Zhang, N., Miao, Y., Shen, Q., Zhang, R., 2021. Specialized metabolic functions of keystone taxa sustain soil microbiome stability. Microbiome9, 35.
CrossRef Google scholar
[87]
Yu, X., Polz, M.F., Alm, E.J., 2019. Interactions in self-assembled microbial communities saturate with diversity. ISME Journal13, 1602–1617.
CrossRef Google scholar
[88]
Zhang, Z., Lu, Y., Wei, G., Jiao, S., Zambrano, M.M., 2022. Rare species-driven diversity-ecosystem multifunctionality relationships are promoted by stochastic community assembly. mBio0, e00449–e00422.
CrossRef Google scholar
[89]
Zhao, J., Duan, G., Zhu, Y., Zhu, D., 2023. Gut microbiota and transcriptome response of earthworms (Metaphire guillelmi) to polymyxin B exposure. Journal of Environmental Sciences133, 37–47.
CrossRef Google scholar
[90]
Zhao, Z.B., He, J.Z., Geisen, S., Han, L.L., Wang, J.T., Shen, J.P., Wei, W.X., Fang, Y.T., Li, P.P., Zhang, L.M., 2019. Protist communities are more sensitive to nitrogen fertilization than other microorganisms in diverse agricultural soils. Microbiome7, 33.
CrossRef Google scholar

Data availability

The raw bacterial, fungal, and protistan sequencing data reported in this paper are available in the NCBI Sequence Read Archive under BioProject PRJNA914639, PRJNA803336, and PRJNA803337, respectively.

Acknowledgments

This research was financially supported by the National Natural Science Foundation of China (42177022 and 41877120) and Natural Science Foundation of Hubei Province, China (2020CFA013). We thank Dr. Xiao-Min Zeng from Huazhong Agricultural University for her helpful suggestions in manuscript writing.

Author contributions

Shuai Du: Conceptualization, Methodology, Software, Formal analysis, Investigation, Writing-original draft, Writing-review and editing, Visualization. Xin-Qi Li: Data curation, Software, Formal analysis, Writing-review and editing, Visualization. Li Bi: Data curation, Software, Formal analysis, Writing-review and editing, Visualization. Dong Zhu: Formal analysis, Investigation, Writing-review and editing, Visualization. Hang-Wei Hu: Formal analysis, Investigation, Writing-review and editing, Visualization. Xiuli Hao: Formal analysis, Investigation, Writing-review and editing, Visualization. Jiao Feng: Formal analysis, Investigation, Writing-review and editing, Visualization. Qiaoyun Huang: Formal analysis, Investigation, Writing-review and editing, Visualization. Yu-Rong Liu: Conceptualization, Investigation, Writing-review and editing, Supervision, Resources, Funding acquisition.

Ethics declarations

The authors declare that they have no competing interests.

Electronic supplementary material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s42832-023-0197-z and is accessible for authorized users.

RIGHTS & PERMISSIONS

2023 Higher Education Press
AI Summary AI Mindmap
PDF(1158 KB)

Accesses

Citations

Detail

Sections
Recommended

/