Fragkias, M., Güneralp, B., Seto, K. C. & Goodness, J. In Urbanization, Biodiversity and Ecosystem Services: Challenges and Opportunities: A Global Assessment (eds Thomas, E. et al.) 409–435 (Springer, 2013).
Seto, K. C., Woodcock, C. E. & Kaufmann, R. K. In Land Change Science: Observing, Monitoring and Understanding Trajectories of Change on the Earth’s Surface (eds Garik, G. et al.) 223–236 (Springer, 2004).
McKinney, M. L. Urbanization, biodiversity, and conservation: The impacts of urbanization on native species are poorly studied, but educating a highly urbanized human population about these impacts can greatly improve species conservation in all ecosystems. Bioscience 52, 883–890. https://doi.org/10.1641/0006-3568(2002)052[0883:Ubac]2.0.Co;2 (2002).
Google Scholar
Müller, N., Ignatieva, M., Nilon, C. H., Werner, P. & Zipperer, W. C. In Urbanization, Biodiversity and Ecosystem Services: Challenges and Opportunities: A Global Assessment (eds Thomas, E. et al.) 123–174 (Springer, 2013).
Kaufmann, R. K. et al. Climate response to rapid urban growth: Evidence of a human-induced precipitation deficit. J. Clim. 20, 2299–2306. https://doi.org/10.1175/jcli4109.1 (2007).
Google Scholar
Reisinger, A. J., Groffman, P. M. & Rosi-Marshall, E. J. Nitrogen-cycling process rates across urban ecosystems. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiw198 (2016).
Google Scholar
Kaye, J. P., Groffman, P. M., Grimm, N. B., Baker, L. A. & Pouyat, R. V. A distinct urban biogeochemistry?. Trends Ecol. Evol. 21, 192–199. https://doi.org/10.1016/j.tree.2005.12.006 (2006).
Google Scholar
Xu, H.-J. et al. Does urbanization shape bacterial community composition in urban park soils? A case study in 16 representative Chinese cities based on the pyrosequencing method. FEMS Microbiol. Ecol. 87, 182–192. https://doi.org/10.1111/1574-6941.12215 (2014).
Google Scholar
Godefroid, S. & Koedam, N. The impact of forest paths upon adjacent vegetation: Effects of the path surfacing material on the species composition and soil compaction. Biol. Cons. 119, 405–419. https://doi.org/10.1016/j.biocon.2004.01.003 (2004).
Google Scholar
Zhu, W.-X., Hope, D., Gries, C. & Grimm, N. B. Soil characteristics and the accumulation of inorganic nitrogen in an arid urban ecosystem. Ecosystems 9, 711–724. https://doi.org/10.1007/s10021-006-0078-1 (2006).
Google Scholar
Tenenbaum, D. E., Band, L. E., Kenworthy, S. T. & Tague, C. L. Analysis of soil moisture patterns in forested and suburban catchments in Baltimore, Maryland, using high-resolution photogrammetric and LIDAR digital elevation datasets. Hydrol. Process. 20, 219–240. https://doi.org/10.1002/hyp.5895 (2006).
Google Scholar
Chen, W., Lu, S., Pan, N., Wang, Y. & Wu, L. Impact of reclaimed water irrigation on soil health in urban green areas. Chemosphere 119, 654–661. https://doi.org/10.1016/j.chemosphere.2014.07.035 (2015).
Google Scholar
Mehmood, K., Ahmad, H. R., Abbas, R., Saifullah, A. & Murtaza, G. Heavy metals in urban and peri-urban soils of a heavily-populated and industrialized city: Assessment of ecological risks and human health repercussions. Hum. Ecol. Risk Assess. https://doi.org/10.1080/10807039.2019.1601004 (2019).
Google Scholar
Decina, S. M., Templer, P. H., Hutyra, L. R., Gately, C. K. & Rao, P. Variability, drivers, and effects of atmospheric nitrogen inputs across an urban area: Emerging patterns among human activities, the atmosphere, and soils. Sci. Total Environ. 609, 1524–1534. https://doi.org/10.1016/j.scitotenv.2017.07.166 (2017).
Google Scholar
Decina, S. M., Templer, P. H. & Hutyra, L. R. Atmospheric inputs of nitrogen, carbon, and phosphorus across an urban area: Unaccounted fluxes and canopy influences. Earth’s Fut. 6, 134–148. https://doi.org/10.1002/2017ef000653 (2018).
Google Scholar
Tresch, S. et al. Direct and indirect effects of urban gardening on aboveground and belowground diversity influencing soil multifunctionality. Sci. Rep. 9, 9769. https://doi.org/10.1038/s41598-019-46024-y (2019).
Google Scholar
Epp Schmidt, D. J. et al. Metagenomics reveals bacterial and archaeal adaptation to urban land-use: N catabolism, methanogenesis, and nutrient acquisition. Front. Microbiol. https://doi.org/10.3389/fmicb.2019.02330 (2019).
Google Scholar
Wang, H. et al. Soil bacterial diversity is associated with human population density in urban greenspaces. Environ. Sci. Technol. 52, 5115–5124. https://doi.org/10.1021/acs.est.7b06417 (2018).
Google Scholar
Wang, H. et al. Changes in land use driven by urbanization impact nitrogen cycling and the microbial community composition in soils. Sci. Rep. 7, 44049. https://doi.org/10.1038/srep44049 (2017).
Google Scholar
Pouyat, R. V. et al. A global comparison of surface soil characteristics across five cities: A test of the urban ecosystem convergence hypothesis. Soil Sci. 180, 136–145. https://doi.org/10.1097/ss.0000000000000125 (2015).
Google Scholar
Yan, B. et al. Urban-development-induced changes in the diversity and composition of the soil bacterial community in Beijing. Sci. Rep. 6, 38811. https://doi.org/10.1038/srep38811 (2016).
Google Scholar
Yan, Z. Z., Chen, Q. L., Zhang, Y. J., He, J. Z. & Hu, H. W. Industrial development as a key factor explaining variances in soil and grass phyllosphere microbiomes in urban green spaces. Environ. Pollut. 261, 114201. https://doi.org/10.1016/j.envpol.2020.114201 (2020).
Google Scholar
Joyner, J. L. et al. Green infrastructure design influences communities of urban soil bacteria. Front. Microbiol. https://doi.org/10.3389/fmicb.2019.00982 (2019).
Google Scholar
Deeb, M. et al. Soil and microbial properties of green infrastructure stormwater management systems. Ecol. Eng. 125, 68–75. https://doi.org/10.1016/j.ecoleng.2018.10.017 (2018).
Google Scholar
Ramirez, K. S. et al. Biogeographic patterns in below-ground diversity in New York City’s Central Park are similar to those observed globally. Proc. R. Soc. B Biol. Sci. 281, 20141988. https://doi.org/10.1098/rspb.2014.1988 (2014).
Google Scholar
Zissimos, A. M., Cohen, D. R. & Christoforou, I. C. Land use influences on soil geochemistry in Lefkosia (Nicosia) Cyprus. J. Geochem. Explor. 187, 6–20. https://doi.org/10.1016/j.gexplo.2017.03.005 (2018).
Google Scholar
Henry, S., Bru, D., Stres, B., Hallet, S. & Philippot, L. Quantitative detection of the nosZ gene, encoding nitrous oxide reductase, and comparison of the abundances of 16S rRNA, narGnirK and nosZ genes in soils. Appl. Environ. Microbiol. 72, 5181. https://doi.org/10.1128/AEM.00231-06 (2006).
Google Scholar
Bru, D., Sarr, A. & Philippot, L. Relative abundances of proteobacterial membrane-bound and periplasmic nitrate reductases in selected environments. Appl. Environ. Microbiol. 73, 5971. https://doi.org/10.1128/AEM.00643-07 (2007).
Google Scholar
Jones, C. M., Graf, D. R. H., Bru, D., Philippot, L. & Hallin, S. The unaccounted yet abundant nitrous oxide-reducing microbial community: a potential nitrous oxide sink. ISME J. 7, 417–426. https://doi.org/10.1038/ismej.2012.125 (2013).
Google Scholar
Bustin, S. A. et al. The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 55, 611–622. https://doi.org/10.1373/clinchem.2008.112797 (2009).
Google Scholar
Jalili, V. et al. The galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2020 update. Nucleic Acids Res. 48, W395–W402. https://doi.org/10.1093/nar/gkaa434 (2020).
Google Scholar
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583. https://doi.org/10.1038/nmeth.3869 (2016).
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 (2012).
Google Scholar
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree: Computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650. https://doi.org/10.1093/molbev/msp077 (2009).
Google Scholar
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30, 772–780. https://doi.org/10.1093/molbev/mst010 (2013).
Google Scholar
Roller, B. R. K., Stoddard, S. F. & Schmidt, T. M. Exploiting rRNA operon copy number to investigate bacterial reproductive strategies. Nat. Microbiol. 1, 16160. https://doi.org/10.1038/nmicrobiol.2016.160 (2016).
Google Scholar
Stoddard, S. F., Smith, B. J., Hein, R., Roller, B. R. K. & Schmidt, T. M. rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Res. 43, D593–D598. https://doi.org/10.1093/nar/gku1201 (2014).
Google Scholar
Starke, R., Pylro, V. S. & Morais, D. K. 16S rRNA gene copy number normalization does not provide more reliable conclusions in metataxonomic surveys. Microb. Ecol. 81, 535–539. https://doi.org/10.1007/s00248-020-01586-7 (2021).
Google Scholar
Cáceres, M. D. & Legendre, P. Associations between species and groups of sites: Indices and statistical inference. Ecology 90, 3566–3574. https://doi.org/10.1890/08-1823.1 (2009).
Google Scholar
Banerjee, S. et al. Agricultural intensification reduces microbial network complexity and the abundance of keystone taxa in roots. ISME J. 13, 1722–1736. https://doi.org/10.1038/s41396-019-0383-2 (2019).
Google Scholar
Oka, M. & Uchida, Y. Heavy metals in slag affect inorganic N dynamics and soil bacterial community structure and function. Environ. Pollut. 243, 713–722. https://doi.org/10.1016/j.envpol.2018.09.024 (2018).
Google Scholar
Guo, H., Nasir, M., Lv, J., Dai, Y. & Gao, J. Understanding the variation of microbial community in heavy metals contaminated soil using high throughput sequencing. Ecotoxicol. Environ. Saf. 144, 300–306. https://doi.org/10.1016/j.ecoenv.2017.06.048 (2017).
Google Scholar
Singh, B. K. et al. Loss of microbial diversity in soils is coincident with reductions in some specialized functions. Environ. Microbiol. 16, 2408–2420. https://doi.org/10.1111/1462-2920.12353 (2014).
Google Scholar
Haferburg, G. & Kothe, E. Microbes and metals: Interactions in the environment. J. Basic Microbiol. 47, 453–467. https://doi.org/10.1002/jobm.200700275 (2007).
Google Scholar
Normand, P., Daffonchio, D. & Gtari, M. In The Prokaryotes: Actinobacteria (eds Eugene, R. et al.) 361–379 (Springer, 2014).
Kelly, D. P., Rainey, F. A. & Wood, A. P. In The Prokaryotes: Volume 5: Proteobacteria: Alpha and Beta Subclasses (eds Martin, D. et al.) 232–249 (Springer, 2006).
Peters, M. K. et al. Climate–land-use interactions shape tropical mountain biodiversity and ecosystem functions. Nature 568, 88–92. https://doi.org/10.1038/s41586-019-1048-z (2019).
Google Scholar
Paula, F. S. et al. Land use change alters functional gene diversity, composition and abundance in Amazon forest soil microbial communities. Mol. Ecol. 23, 2988–2999. https://doi.org/10.1111/mec.12786 (2014).
Google Scholar
Zhang, X. et al. Effect of intermediate disturbance on soil microbial functional diversity depends on the amount of effective resources. Environ. Microbiol. 20, 3862–3875. https://doi.org/10.1111/1462-2920.14407 (2018).
Google Scholar
Szoboszlay, M., Dohrmann, A. B., Poeplau, C., Don, A. & Tebbe, C. C. Impact of land-use change and soil organic carbon quality on microbial diversity in soils across Europe. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fix146 (2017).
Google Scholar
Huot, H. et al. Characterizing urban soils in New York City: profile properties and bacterial communities. J. Soils Sediments 17, 393–407 (2017).
Google Scholar
Nehls, T., Rokia, S., Mekiffer, B., Schwartz, C. & Wessolek, G. Contribution of bricks to urban soil properties. J. Soils Sediments 13, 575–584 (2013).
Google Scholar
Hemmat-Jou, M. H., Safari-Sinegani, A. A., Mirzaie-Asl, A. & Tahmourespour, A. Analysis of microbial communities in heavy metals-contaminated soils using the metagenomic approach. Ecotoxicology 27, 1281–1291. https://doi.org/10.1007/s10646-018-1981-x (2018).
Google Scholar
Zaborowska, M., Kucharski, J. & Wyszkowska, J. Biological activity of soil contaminated with cobalt, tin, and molybdenum. Environ. Monit. Assess 188, 398–398. https://doi.org/10.1007/s10661-016-5399-8 (2016).
Google Scholar
Drenovsky, R., Vo, D., Graham, K. & Scow, K. Soil water content and organic carbon availability are major determinants of soil microbial community composition. Microb. Ecol. 48, 424–430 (2004).
Google Scholar
Fierer, N. & Jackson, R. B. The diversity and biogeography of soil bacterial communities. Proc. Natl. Acad. Sci. U.S.A. 103, 626. https://doi.org/10.1073/pnas.0507535103 (2006).
Google Scholar
Bru, D. et al. Determinants of the distribution of nitrogen-cycling microbial communities at the landscape scale. ISME J. 5, 532–542. https://doi.org/10.1038/ismej.2010.130 (2011).
Google Scholar
Vos, M., Wolf, A. B., Jennings, S. J. & Kowalchuk, G. A. Micro-scale determinants of bacterial diversity in soil. FEMS Microbiol. Rev. 37, 936–954. https://doi.org/10.1111/1574-6976.12023 (2013).
Google Scholar
Rath, K. M., Fierer, N., Murphy, D. V. & Rousk, J. Linking bacterial community composition to soil salinity along environmental gradients. ISME J. 13, 836–846. https://doi.org/10.1038/s41396-018-0313-8 (2019).
Google Scholar
Jones, C. M. & Hallin, S. Ecological and evolutionary factors underlying global and local assembly of denitrifier communities. ISME J. 4, 633–641. https://doi.org/10.1038/ismej.2009.152 (2010).
Google Scholar
Philippot, L. et al. Mapping field-scale spatial patterns of size and activity of the denitrifier community. Environ. Microbiol. 11, 1518–1526. https://doi.org/10.1111/j.1462-2920.2009.01879.x (2009).
Google Scholar
Graf, D. R. H., Jones, C. M. & Hallin, S. Intergenomic comparisons highlight modularity of the denitrification pathway and underpin the importance of community structure for N2O emissions. PLoS ONE 9, e114118. https://doi.org/10.1371/journal.pone.0114118 (2014).
Google Scholar
Domeignoz-Horta, L. et al. The diversity of the N2O reducers matters for the N2O:N2 denitrification end-product ratio across an annual and a perennial cropping system. Front. Microbiol. https://doi.org/10.3389/fmicb.2015.00971 (2015).
Google Scholar
Hallin, S., Philippot, L., Löffler, F. E., Sanford, R. A. & Jones, C. M. Genomics and ecology of novel N2O-reducing microorganisms. Trends Microbiol. 26, 43–55. https://doi.org/10.1016/j.tim.2017.07.003 (2018).
Google Scholar
Xu, X. et al. NosZ clade II rather than clade I determine in situ N2O emissions with different fertilizer types under simulated climate change and its legacy. Soil Biol. Biochem. 150, 107974. https://doi.org/10.1016/j.soilbio.2020.107974 (2020).
Google Scholar
Source: Ecology - nature.com
