SCIENCE ADVANCES | RESEARCH ARTICLE ECOLOGY Copyright © 2021 The Authors, some Global homogenization of the structure and function rights reserved; exclusive licensee in the soil microbiome of urban greenspaces American Association for the Advancement of Science. No claim to Manuel Delgado-Baquerizo1*, David J. Eldridge2, Yu-Rong Liu3, Blessing Sokoya4, original U.S. Government Jun-Tao Wang5, Hang-Wei Hu6,7, Ji-Zheng He6,7, Felipe Bastida8, José L. Moreno8, Works. Distributed Adebola R. Bamigboye9, José L. Blanco-Pastor10, Concha Cano-Díaz11, Javier G. Illán12, under a Creative Thulani P. Makhalanyane13, Christina Siebe14, Pankaj Trivedi15, Eli Zaady16, Jay Prakash Verma17, Commons Attribution Ling Wang18, Jianyong Wang18, Tine Grebenc19, Gabriel F. Peñaloza-Bojacá20, NonCommercial License 4.0 (CC BY-NC). Tina U. Nahberger19, Alberto L. Teixido21, Xin-Quan Zhou3, Miguel Berdugo22,23, Jorge Duran24, Alexandra Rodríguez24, Xiaobing Zhou25, Fernando Alfaro26,27, Sebastian Abades27, Cesar Plaza28, Ana Rey29, Brajesh K. Singh5,30, Leho Tedersoo31, Noah Fierer4,32 The structure and function of the soil microbiome of urban greenspaces remain largely undetermined. We con- ducted a global field survey in urban greenspaces and neighboring natural ecosystems across 56 cities from six continents, and found that urban soils are important hotspots for soil bacterial, protist and functional gene diver- sity, but support highly homogenized microbial communities worldwide. Urban greenspaces had a greater proportion of fast-growing bacteria, algae, amoebae, and fungal pathogens, but a lower proportion of ectomy- corrhizal fungi than natural ecosystems. These urban ecosystems also showed higher proportions of genes associated with human pathogens, greenhouse gas emissions, faster nutrient cycling, and more intense abiotic stress than natural environments. City affluence, management practices, and climate were fundamental drivers of urban soil communities. Our work paves the way toward a more comprehensive global-scale perspective on urban greenspaces, which is integral to managing the health of these ecosystems and the well-being of human populations. INTRODUCTION (1–3). Urban greenspaces also provide habitat for a myriad of plants Urban greenspaces, such as parks and residential gardens, are criti- and animals including a wide range of bird species (e.g., pigeons), cally important for promoting mental and physical well-being and terrestrial and arboreal mammals (e.g., squirrels), and diverse above- for reducing morbidity and mortality (1). According to the United and below-ground invertebrates (3, 4). Similarly, soils in urban Nations, 68% of the global population will live in cities by 2050, in- greenspaces are also home to a diverse community of microbes, in- creasing the environmental and social stresses for the billions of cluding archaea, bacteria, fungi, and protists (4–6). This soil bio- humans living in urban areas (2). Urban greenspaces make up most diversity plays important roles in maintaining ecosystem services of the open spaces available for recreational activities in urban areas such as soil fertility, plant health, productivity, and waste decompo- such as sport and social engagement and play important roles in sition (7). Moreover, human exposure to soil microbes has been curbing pollution, reducing noise, and lowering air temperatures shown to be beneficial to human health by promoting effective 1 Departamento de Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, 41013 Sevilla, Spain. 2Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia. 3College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China. 4Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA. 5Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales 2751, Australia. 6Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria 3010, Australia. 7Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Science, Fujian Normal University, Fuzhou 350007, China. 8CEBAS-CSIC, Department of Soil and Water Conservation, Campus Universitario de Espinardo, 30100, Murcia, Spain. 9Natural History Museum (Botany Unit), Obafemi Awolowo University, Ile-Ife, Nigeria. 10INRAE, UR4 (URP3F), Centre Nouvelle-Aquitaine-Poitiers, 86600 Lusignan, France. 11Biología y Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, Móstoles 28933, Spain. 12Department of Entomology, Washington State University, Pullman, WA 99164, USA. 13Centre for Microbial Ecology and Genomics, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria 0028, South Africa. 14 Instituto de Geología, Universidad Nacional Autónoma de México, Ciudad Universitaria, México D.F. CP 04510, México. 15Microbiome Network and Department of Agri- cultural Biology, Colorado State University, Fort Collins, CO 80523, USA. 16Department of Natural Resources, Agricultural Research Organization, Institute of Plant Sciences, Gilat Research Center, Mobile Post Negev, Gilat 8531100, Israel. 17Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221005 Uttar Pradesh, India. 18Institute of Grassland Science/School of Life Science, Northeast Normal University, and Key Laboratory of Vegetation Ecology, Ministry of Education, Changchun, Jilin 130024, China. 19Department of Forest Physiology and Genetics, Slovenian Forestry Institute, Ljubljana, Slovenia. 20Laboratório de Sistemática Vegetal, Departamento de Botânica, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, Pampulha, Belo Horizonte, 31270-901 MG, Brazil. 21Departamento de Botância e Ecologia, Instituto de Biociências, Universidade Federal de Mato Grosso, Av. Fernando Corrêa, 2367, Boa Esperança, Cuiabá, 78060- 900 MT, Brazil. 22Institut de Biologia Evolutiva (UPF-CSIC), 08003 Barcelona, Spain. 23Institute of Integrative Biology, Department of Environment Systems Science, ETH Zurich, Univeritätstrasse 16, 8092 Zürich, Switzerland. 24Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, Portugal. 25 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China. 26GEMA Center for Genomics, Ecology and Environment, Faculty of Interdisciplinary Studies, Universidad Mayor, Santiago, Chile. 27Instituto de Ecología y Biodiversidad (IEB), CP 7800003 Santiago, Chile. 28Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Serrano 115 bis, 28006 Madrid, Spain. 29Museo Nacional de Ciencias Naturales, Consejo Superior de Investigaciones Científicas, Serrano 115 bis, 28006 Madrid, Spain. 30Global Centre for Land-Based Innovation, Western Sydney University, Penrith South DC, New South Wales 2751, Australia. 31Department of Mycology and Microbiology, University of Tartu, Ravila 14a, 50411 Tartu, Estonia. 32Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO 80309, USA. *Corresponding author. Email: m.delgadobaquerizo@gmail.com Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 1 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE immunoregulation functions and reducing allergies (8). However, small (population < 50,000; e.g., Alice Springs, Australia), medium some soil microbes (e.g., Mycobacterium, Listeria, and Fusarium (population, 50,000 to 1 million; e.g., Ljubljana, Slovenia), and large spp.) can also have substantial negative consequences for the sus- cities (population > 5 million; e.g., Beijing, China; table S1), and tainability of urban greenspaces and for animal, human, and plant spanned a large range in vegetation types (forests, grasslands, and health. For instance, some soil microbial taxa harbor antibiotic re- shrublands) and climatic regions (arid, temperate, tropical, and cold sistance genes and could potentially influence the health of people ecosystems; table S1). Our sampling was explicitly designed to and animals by reducing our ability to fight human diseases (9, 10). account for the spatial heterogeneity in our plots (fig. S1; Materials Unfortunately, unlike with urban birds, plants, and mammals, we and Methods). At each plot, we collected three composite soil sam- have a very limited understanding of the identity and function of ples (to 7.5 cm in depth) along with information on the dominant the soil organisms inhabiting our urban parks and gardens. Previ- vegetation type (e.g., forest), vegetation structure in three 30-m ous microbial studies in urban greenspaces have focused on specific transects (plant species richness, plant cover, and proportion of locations (e.g., New York’s Central Park) (4, 5), specific groups of locations with ectomycorrhizal dominant plant species; table S2 soil organisms (e.g., mycorrhizal fungi) (6), or specific microbial and fig. S1) and management practices (irrigation, fertilization, and functions (e.g., denitrification) (11). However, we currently lack a mowing). A total of 336 composite topsoil samples were analyzed global perspective on the soil microbiome of urban greenspaces and for this study as detailed in Materials and Methods. how these soil microbiomes compare to those found in nearby natural To achieve our first aim, we characterized the biodiversity [number ecosystems. A comprehensive evaluation must consider multiple of amplicon sequence variants (ASVs); taxa that share 100% se- cities with contrasting populations, vegetation, and climates and in- quence similarity in the targeted gene region] and community com- clude a wide range of functional and taxonomic groups of soil or- position (proportional abundances of ASVs, phyla/class, and functional ganisms. Improving our understanding of soil organisms associated groups) of bacteria, archaea, protists, and fungi in the soil samples with urban parks is a critical step toward building a better under- from 56 paired cities and natural vegetated areas using ribosomal standing of the role of these fundamental organisms in controlling RNA (rRNA) gene amplicon sequencing (Materials and Methods). the functioning and health of urban environments and toward Diversity within each group was calculated at an equivalent se- managing the sustainable development of urban greenspaces. quencing depth across all samples using plot-level ASVs based on Here, we report results of the first global field assessment of the three soil composite samples per plot (Materials and Methods). We soil microbiome in urban greenspaces, aiming to (i) compare the compared the diversity and proportion of soil organisms using two diversity and community composition of microbial taxonomic and statistical approaches that explicitly considered our sampling using functional groups of urban greenspaces with those of nearby “natural” a blocked design (paired urban and natural ecosystems): (i) re- ecosystems; (ii) identify the soil microbial taxa (bacteria, archaea, sponse ratios (i.e., changes in the values of microbial attributes from protists, and fungi) that are consistently found to be residents of natural to cities; see Materials and Methods for correlations with urban greenspaces across the globe; (iii) evaluate the socioeconomic other choices of response ratios) and (ii) nested permutational mul- and environmental factors linked to the structure of the soil micro- tivariate analysis of variance (PERMANOVA) comparing urban to biome of urban greenspaces; and (iv) assess the microbial functional natural ecosystems (56 paired locations; see Materials and Methods attributes characterizing soils in urban greenspaces including genes for details). associated with pathogenesis, greenhouse gas emissions, nutrient Our analyses show that urban greenspaces harbor soil microbi- cycling, and abiotic stress. omes that are distinct from adjacent natural ecosystems (Figs. 1 to 8 and figs. S3 to S10). Urban greenspaces harbored communities of soil protists and bacteria that were, on average, 12 and 17%, respec- RESULTS AND DISCUSSION tively, more diverse than the adjacent natural ecosystems, with no To achieve these goals, we carried out a field survey across 112 sites significant differences in the richness of fungi and archaea (Fig. 1B from 17 countries spanning six continents (Fig. 1A, table S1, and and fig. S3). However, our analyses also revealed that, at the global fig. S1). We used an experimental design that included paired urban scale, urban greenspaces tended to host more homogeneous micro- and nearby natural sites located across 56 globally distributed loca- bial communities across cities than those found across natural eco- tions (statistical “blocks”; Fig. 1A, table S1, and fig. S1). In each systems (Betadisper P < 0.001; Fig. 2, A and B, and figs. S4 to S6). location (e.g., Cape Town, South Africa; fig. S1), we established a Specifically, microbial communities were between 25% (protists) 30 m by 30 m plot in a representative urban greenspace (e.g., an and 101% (fungi) more homogeneous in urban greenspaces than in urban forest or lawn in a city park; fig. S1) and a nearby, relatively nearby natural ecosystems (+39% for bacteria and +83% for ar- undisturbed natural ecosystem resembling the original vegetation chaea; Fig. 2B). In other words, our analyses show a greater similar- representative of these locations (e.g., a natural grassland; fig. S1). ity in the community composition of archaea, bacteria, fungi, and Urban greenspaces were located mostly in public parks and large protists across the 56 globally distributed urban greenspaces than residential gardens and comprised a mixture of open areas with across the corresponding natural ecosystems (Fig. 2B). This result lawns, scattered trees, patches of shrubs, and associated flowerbeds. was maintained across contrasting geographic, climatic, and vege- We refer to these ecosystems as urban greenspaces hereafter (1). tation contexts (fig. S6). We further show that patterns in soil com- Natural areas near these cities were unmanaged or seminatural forests, munity similarity for different soil organisms (archaea, bacteria, shrublands, and grasslands, many of them relict ecosystems. Urban fungi, and protists) are highly correlated across communities, both greenspaces and natural ecosystems strongly differ in vegetation across cities and across natural ecosystems (Fig. 3). This finding structure and supported lower levels of plant species richness (fig. suggests that the homogenization effects of urban greenspaces and S2 and table S2). Agricultural lands were not included in this study. the potential environmental drivers of these effects are shared Our database comprises a wide range of urban areas including relatively across distinct groups of soil organisms. Human-induced land-use Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 2 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 1. The diversity and structure of the soil microbiome in urban greenspaces across the globe. (A) The locations of the 56 surveyed cities included in this study along with their respective human populations. The names of some of the largest cities are included in this figure (see table S1 for details on all cities). (B) The changes [site-level response ratios, mean ± 95% confidence interval (CI)] in microbial diversity and the proportional abundances of significant taxa, comparing urban greenspaces to nearby natural ecosystems (n = 56 response ratios). Points above the dashed line indicate that the diversity or relative abundances of those taxa are higher in urban greenspaces compared to the corresponding natural areas near each city. Complementary figures showing results for other groups of organisms can be found in figs. S7 to S10. Phylotypes, ASVs; MG-RAST, metagenomics rapid annotation using subsystem technology. changes such as the conversion of forests to pasture have been re- the soil microbiome of urban greenspaces, are consistent with the ported to result in the biotic homogenization of soil microbial com- effects of urbanization on bird (15), plant, and invertebrate com- munities (12). Moreover, the importance of land-use intensification munities (16). Together, our findings provide novel evidence that (e.g., livestock grazing) in generating cross-site multitrophic urban greenspaces are important hot spots for the local (alpha) homogenization has been previously reported at larger spatial scales diversity of some microbial groups such as bacteria and protists (13). Likewise, homogenization of bacterial communities has also worldwide. However, we also show that the geographic variation in been reported in dust samples collected from urban areas compared microbial community composition is typically lower across cities with more rural areas across the United States (14). Our results, em- worldwide than across natural ecosystems, suggesting a global phasizing a global convergence (reduced geographic variation) in homogenization in the soil microbiome of urban greenspaces. Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 3 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 2. Global homogenization in the soil microbiome of urban greenspaces. (A) The soil community composition heterogeneity of soil microorganisms in natural ecosystems and urban greenspaces. Boxes include median and 25th/75th percentile of the distances to the group centroid derived from betadisper (vegan R package). Asterisks indicate significant differences in compositional heterogeneity based on permutation test for homogeneity of multivariate dispersions (Materials and Methods). (B) Information on the within-group (urban or natural) community similarity for archaea, bacteria, fungi, protists, and metagenomics. Dots represent the average similar- ity (Bray-Curtis) in the soil community composition of each natural/urban site compared with the rest of natural/urban sites, respectively. In these panels, higher commu- nity similarity values indicate that the soils harbor communities that are more similar in composition, compared with the rest of the sites, across the 56 surveyed locations. The solid lines show mean values (n = 112 urban greenspaces and natural ecosystems). Asterisks indicate significant differences in nested PERMANOVA analyses using a block design as described in the Materials and Methods. (C) The relationship between soil pH and within-group (urban or natural) community similarity for archaea, bac- teria, fungi, and protists. **P < 0.01; *P < 0.05. Soils from urban greenspaces harbored communities of archaea, also supported a higher proportion of Chlorophyta, important photo- bacteria, fungi, and protists distinct from those found in natural synthetic organisms, which often colonize bare soils in urban green- ecosystems, with urban greenspaces consistently supporting a sig- spaces (Fig. 1D) (17). Our results further indicate that the soils in nificantly greater proportion of Gammaproteobacteria, Deltaproteo- urban greenspaces have a lower proportion of ectomycorrhizal and bacteria, Bacteroidetes, Gemmatimonadetes, Ascomycota, Chlorophyta, ericoid mycorrhizal fungi (but not arbuscular mycorrhizal fungi) and Amoebozoa (Fig. 1D and figs. S7 to S10). These phyla/classes compared with those from adjacent natural areas (Fig. 1D and figs. include multiple fast-growing organisms (e.g., members from Gamma­ S7 to S10). These results are consistent in plots dominated by both proteobacteria and Bacteroidetes) that could take advantage of the ectomycorrhizal (EcM) and no-EcM plants (table S2 and fig. S11). often fertilized and irrigated conditions found in urban ecosystems The negative impact of urban environments on ectomycorrhizal (Fig. 1D). The Amoebozoa group, for example, includes a wide variety fungi has been previously reported, at a local scale, in Southern Finland of species that feed on bacteria and could more likely thrive in urban (6). Our findings further indicate that urban greenspaces support a systems because of irrigation practices more often providing the water higher proportion of fungal parasites and plant pathogens that are films needed to sustain their activities (Fig. 1D). Urban greenspaces often economically important pests (Fig. 1D and figs. S8 and S10) (18). Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 4 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 3. Relationships between the within-group (urban or natural) community similarity of archaea, bacteria, fungi, and protists. (A to F) Dots represent the aver- age similarity in community composition of each natural/urban site compared with the rest of natural/urban sites, respectively. In these panels, higher community simi- larity values indicate that the soils harbor communities that are more similar in composition, compared with the rest of the sites, across the 56 surveyed locations (n = 56 urban greenspaces or natural ecosystems). **P < 0.01; *P < 0.05. Identifying the members of the soil microbiome that commonly To improve the sustainable management of urban greenspaces, reside in urban greenspaces is fundamental for the appropriate manage- we need to understand how environmental and socioeconomic changes ment of these habitats, as revealed by studies on macro-organisms will affect important structural and functional attributes of the soil (19). Here, we identified the indicative members of the soil micro- microbiome. Here, we identified the most important socioeconomic biome of urban greenspaces across the globe (urban greenspaces factors [in terms of per capita gross domestic product (GDP) and taxa hereafter). We focused on those microbial phylotypes (ASVs) population density], vegetation structure (plant diversity, plant cover, that (i) were relatively ubiquitous (>25% of all cities), (ii) were clas- and presence of ectomycorrhizal dominant plants), park manage- sified as “species indicators” of greenspaces using the algorithm of ment practices (irrigation, fertilization, and mowing), and environ- the “indicspecies” R package (see Materials and Methods), and (iii) mental factors (climate, solar radiation, total plant cover, and soil showed statistically significantly higher proportions in urban rather properties) associated with the soil microbiome of urban greenspaces than natural environments (see Materials and Methods for a more (n = 56 urban greenspaces). Socioeconomic and climatic factors detailed description of these analyses). On the basis of these three such as GDP per capita and high temperatures could influence the criteria, we identified a total of 539 phylotypes (i.e., 488 bacteria, soil microbiome of urban greenspaces by increasing environmental 47 protists, 2 archaea, and 2 fungi from a total of 142 genera) character- stress associated with disturbance, pollution, and climatic stress. As izing the soil microbiome of urban greenspaces (Fig. 4A and table expected, we found that soil properties and climate significantly in- S3). These patterns were consistent across geographical regions, cli- fluenced the soil microbiome across cities. For instance, we found a mates, and vegetation types (Fig. 4B). The urban greenspace taxa well-established association between soil pH and bacterial richness included important fungal and oomycete plant pathogens such as (20), a positive correlation between the proportion of Cercozoa and Fusarium intricans, Pythium rostratifingens, and Pythium uncinulatum, mean annual precipitation (21), and a positive relationship between fungal decomposers such as Mortierella elongata, archaeal nitrifiers such bacterial and protist richness (Figs. 5 and 6 and figs. S12 to S14) as Nitrososphaera sp., bacteria such as Streptomyces and Pseudomonas spp., (22). Likewise, soil pH was also the most important factor associated and multiple species of bacteria-feeding amoebae (table S3 for se- with the changes in the soil community similarity across cities, which quences). Our results suggest that, similar to what has been found mostly supported curvilinear relationships (Fig. 2C). Plant diversity for birds (e.g., pigeons) and plants (e.g., roses), many comparable was negatively related to bacterial and archaeal community similarity, microbial species thrive in urban ecosystems across the globe. as well as to the proportion of urban greenspace taxa (Fig. 6). Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 5 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 4. Microbial phylotypes comprising the urban greenspace soil microbiome. (A) Two phylogenetic trees showing the diversity of prokaryotic and eukaryotic or- ganisms identified as being characteristic of urban greenspaces. See table S3 for the complete list of taxa and their representative sequences. (B) The proportion (mean ± SE) of the microbial phylotypes comprising the urban greenspace microbiome across continents, climates, and vegetation types (mean ± SE; n in brackets). ns, not significant; **P < 0.01. P values are based on nested PERMANOVA analyses using a block design as described in the Materials and Methods. EcM, ectomycorrhizal. Our findings show that economic metrics, park management To gain a deeper understanding of the functional attributes of practices, and climate are important factors associated with the the urban greenspace soil microbiome, we obtained shotgun meta­ richness and community composition of the soil microbiome in urban genomic data from a subset of 54 soil samples (one of the soil com- greenspaces (figs. S12 and S13). Our results indicate that warmer posite samples from a selection of 27 cities and their corresponding and more irrigated cities supported a greater proportion of fungal natural ecosystems). This selection covered a wide range of cities plant pathogens (Figs. 5 and 6 and figs. S12 and S13) and revealed from contrasting climates and populations and 17 countries from that warmer and more densely populated cities also had a lower both hemispheres (table S1). Consistent with our results for bacte- proportion of symbiotic ectomycorrhizal fungi—a pattern that could rial richness, soils from urban greenspaces typically had greater also be influenced by a reduction in ectomycorrhizal hosts at lower functional gene richness than adjacent natural terrestrial ecosystems latitudes (23). Warming and disturbance have been shown to regu- (Fig. 1C and fig. S15). We found further evidence of global homo­ late the distribution of fungal pathogens and mycorrhizal organisms genization of the soil functional microbiome of urban greenspaces in natural terrestrial environments worldwide (24). In addition, more (Fig. 2), with functional gene profiles from urban greenspaces being affluent cities were characterized by soils with a greater proportion more homogeneous across cities worldwide than the variability of Nitrososphaeria (often involved in nitrification) and potentially among natural ecosystems (Fig. 2, B and C, and fig. S15)—a pattern rapid-growing Gammaproteobacteria (e.g., Pseudomonas sp.) (see likely associated with the higher soil pH in urban greenspaces com- other examples in Fig. 5 and figs. S12 and S13). These patterns are pared with natural ecosystems (Fig. 2 and figs. S12 and S14). likely the result of fertilizer applications to greenspace soils, given The microbial communities in urban greenspaces had distinct that similar taxonomic shifts have been observed in grasslands functional gene profiles (Figs. 1C and 7, A to C, and figs. S4 to S6 worldwide receiving elevated nutrient inputs (25). Thus, our find- and S15). We further investigated well-known functional genes as- ings suggest that changes in temperature, as well as differences in sociated with pathogenesis, greenhouse gas emissions, nutrient cy- important socioeconomic and management factors, are largely as- cling, and abiotic stress (Fig. 7) and found that urban greenspaces sociated with the soil microbiome of our greenspaces. had a higher proportion of plant and human pathogens (26–29), Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 6 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 5. Socioeconomic, management, and environmental drivers of the soil microbiome in urban greenspaces. (A to L) Selected relationships between the propor- tional abundances or diversity of soil organisms and site characteristics across urban areas (n = 56 urban greenspaces). USD, U.S. dollars; MAT, mean annual temperature; MAP, mean annual precipitation. Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 7 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 6. Spearman correlation analyses aiming to identify the most important socioeconomic factors, management practices, and environmental drivers of the taxonomic and functional properties of the soil microbiome of urban greenspaces (n = 56 urban greenspaces). Statistically nonsignificant correlations (P > 0.05) are shown in white. Total P and N = Soil total P and N. Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 8 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 7. The functional attributes of the soil microbiome in urban greenspaces across the globe. (A to C) The changes (site-level response ratios) in the proportion of selected functional genes associated with human diseases and antibiotic resistance (A), nutrient cycles (B), and abiotic stress (C) from natural to urban ecosystems (mean ± 95% CI; n = 56 response ratios). Points above the dashed line indicate a positive response ratio, with the selected gene category or soil property being relatively more abundant in urban greenspace soils compared with the corresponding “natural” sites. greenhouse gas emission, and nitrogen and phosphorus cycle genes. we do not know whether these particular genes detected may affect For instance, soils from urban greenspaces had a higher proportion human health outcomes. Therefore, extrapolating and linking the of genes associated with Mycobacterium virulence. This was espe- occurrence of particular soil microbial genes to human health needs cially important in the most alkaline soils [Figs. 6 to 8 and (15)] and to be further investigated in the future to better understand how is in agreement with our observation that one of the most abundant those microbes found in urban soils may affect human health. species in the soil microbiome of urban greenspaces is a member of Our results also indicate that soils from urban greenspaces in- the genus Mycobacterium (table S3). Although most soil mycobac- cluded a higher proportion of bacterial genes associated with N and teria are nonpathogenic (28), others are known to be important P cycling, likely associated with the fact that nitrogen and P are im- pathogens of humans and animals and can cause important respira- portant fertilizers in urban greenspaces (from atmospheric depo- tory infections (28, 29). Moreover, compared with natural ecosystems, sition and direct fertilizer application). We also found a greater urban greenspaces had a greater proportion of genes associated proportion of genes associated with archaeal methylotrophic meth- with Listeria and diphtheria toxins, Vibrio pathogenesis islands, anogenesis (30) and denitrification processes, especially in irrigated and key antibiotic resistance genes (e.g., -lactamases in Streptococ- and mowed greenspaces (Figs. 5 to 7B and fig. S15). This is impor­ cus, which includes penicillin) (Fig. 7A and fig. S15) (26, 27), which tant because it suggests that urban greenspaces could potentially be could all potentially influence human health. The proportion of important sources of greenhouse gas emissions (methane and ni- genes coding for Vibrio pathogenesis islands was higher in more trous oxide) to the atmosphere (11). However, direct measurements affluent cities and that of genes coding for -lactamases in Streptococcus of these soil processes are required to determine how these patterns in warmer, more densely populated cities (Fig. 4C and fig. S12). We in gene abundances might relate to actual process rates in urban also found higher proportions of viral genes in urban greenspaces than greenspaces. Last, we found a higher proportion of gene copies in natural ecosystems, particularly in fertilized greenspaces (Fig. 7A associated with bacterial tolerance to alkaline or saline conditions and fig. S15). We note that gene annotations are approximate, and (Figs. 5 to 7C and fig. S15), which are typical of many urban Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 9 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE Fig. 8. Selected relationships between socioeconomic, management, and environmental drivers and the proportional abundances or richness of selected func- tional genes across urban greenspaces (A to E) (n = 56 urban greenspaces). greenspaces (fig. S14). Together, these findings suggest that the within urban spaces. These natural ecosystems were selected to rep- soil microbiome of urban greenspaces supports a wide variety of resent the most common ecosystem type in each location in the potentially pathogenic organisms and microbes associated with absence of urbanization. Natural ecosystems were, on average, important soil biogeochemical conditions and processes. The po- 22.8 ± 3.3 km apart from urban greenspaces. Mean annual precipi- tential consequences of these relationships justify more detailed tation and temperature in the selected cities ranged from 210 to future investigations to better understand the functioning of ur- 1577 mm and 3.1° to 26.4°C, respectively. In each location, we sur- ban soils and their contributions to environmental and human veyed a 30 m by 30 m plot using three parallel transects of equal health. length, spaced 15 m down the part. We also collected information In summary, we found that urban greenspaces are important hot on the vegetation structure of each location based on the three 30-m spots of local soil microbial taxonomic and functional diversity but transects. This information includes plant species richness, plant also support a global homogenization in the structure and function cover, and proportion of locations with ectomycorrhizal dominant of the soil microbiome. More specifically, we show that urban soils plant species (table S2). across the globe harbor more similar microbiomes than would be Soils were collected from 56 paired urban greenspaces and nearby expected from comparable analyses of soils from adjacent natural natural ecosystems (Fig. 1A, table S1, and fig. S1) between 2017 ecosystems. Our analyses indicate that soils from urban greenspaces and 2019. Samples were over the three 30-m transects (fig. S1). To are characterized by higher proportions of fast-growing bacteria, account for spatial heterogeneity in our plots, three composite soil algae, nitrifiers, and important plant pathogens, which were partic- samples (from five soil cores, top 7.5-cm depth) were collected under ularly dominant in the warmer, more affluent, and more intensively the most common environments (vegetation and open areas be- managed greenspaces. Last, our results indicate that the urban tween plant canopies covered by bare soils and nonvascular plants) greenspace microbiome harbors a greater proportion of genes asso- found at each plot (fig. S1). A total of 336 composite soil samples ciated with greenhouse gas emissions (denitrification and methano- were collected for this study. After field collection, each composite genesis), as well as elevated proportions of genes associated with human soil sample was divided into two subsamples; one subsample was pathogens and antibiotic resistance (e.g., -lactamases), which may immediately frozen at −20°C for molecular analyses, while the other potentially have important implications for human health. Together, subsample was air-dried for chemical analyses. Soil pH had a simi- our study represents the first global assessment of the structure and lar range for natural (4.1 to 8.6) and urban greenspaces (5.1 to 8.8), functional attributes of the soil microbiome of urban greenspaces with urban greenspaces having slightly more alkaline soils (fig. S14). worldwide. Soil biodiversity sequencing Amplicon sequencing MATERIALS AND METHODS Soil DNA was extracted from each of the 336 composite soil Study sites samples using the DNeasy PowerSoil Kit (Qiagen, Hilden, Germa- A total of 112 ecosystems across 17 countries and six continents ny) according to the manufacturer’s instructions. The diversity of soil (table S1 and Fig. 1A) were included in this study. Our survey tar- archaea, bacteria, and protists was measured via amplicon sequenc- geted well-established urban parks and large residential gardens. ing using the Illumina MiSeq platform (Illumina Inc., CA, USA). We also targeted relatively undisturbed natural ecosystems includ- DNA was shipped to the University of Colorado Boulder where all ing seminatural forests, grasslands, and shrublands close to cities or samples were processed using the same standardized protocol. A relict forests maintaining their original vegetation and embedded total of 336 soil composite samples (three composite samples per Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 10 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE plot; fig. S1) were sequenced aiming to characterize the soil biodi- Isolation Kit (Qiagen Inc., USA) according to the manufacturer’s versity of urban greenspaces. To characterize the richness (number protocol. Sequencing was performed using an Illumina HiSeq (Illu- of phylotypes) and community composition (proportion of phylo- mina Inc., USA) at Majorbio in Shanghai, China. Raw reads {PE150 types; relative abundance; percentage) of archaea, bacteria, and fungi, [150–base pair (bp) paired-end reads]} were trimmed to remove a portion of the prokaryotic 16S and eukaryotic 18S rRNA genes low-­quality reads as follows. First, the SeqPrep software (https:// were sequenced using the 515F/806R and Euk1391f/EukBr primer github.com/jstjohn/SeqPrep) was used to remove the adapter sequences. sets (4, 22), respectively. Bioinformatic processing was performed Second, the library sickle (https://github.com/najoshi/sickle) was used using DADA2 (31). Phylotypes (i.e., ASVs) were identified at the to trim the reads from the 5′ end to the 3′ end using a sliding window 100% identity level. The ASV abundance tables were rarefied at 5000 (size, 50 bp; 1-bp step). If the mean quality of bases inside a window (bacteria via 16S rRNA gene), 100 (archaea via 16S rRNA gene), and dropped below 20, then the remainder of the read below the quality 1000 (protists via 18S rRNA gene) sequences per sample, respec- threshold was trimmed. Quality-trimmed reads that were shorter tively, to ensure even sampling depth within each belowground group than 50 bp or containing N (ambiguous bases) were discarded. of organisms. Protists are defined as all eukaryotic taxa, except fungi, The original sequences of the 54 samples were annotated using invertebrates (Metazoa), and vascular plants (Streptophyta). The Subsystem Technology [MG-RAST (metagenomics rapid annota- richness and community composition of fungi were determined via tion using subsystem technology); www.mg-rast.org)] (36) to per- full-length 18S ITS (internal transcribed spacer) amplicon sequencing form quality control and automated annotation as well as produce using the primers ITS9mun/ITS4ngsUni and the PacBio Sequel II taxonomic and functional assignments. MG-RAST generates taxo- platform in the University of Tartu (32). Bioinformatic processing nomic assignments based on the SEED subsystem database by was performed as explained above (ASVs at 100% similarity). The DIAMOND software (version 0.9.32) by best-hit classification with fungi ASV abundance table was rarefied at 1000 sequences per sam- a maximum E value of 1 × 10−5, a minimum identity of 60%, and a ple. See fig. S16 for rarefaction curves. Richness units are number of minimum alignment length of 25 amino acids for proteins and func- phylotypes (ASVs). Proportion of taxa units are percentages. tional categories. The resulting table was parsed at SEED subsystem Rarefaction cross-validation level 3 by software SUPER-FOCUS. The proportion of 1276 groups Before conducting further analyses, we ensured that our choice of of functional genes was determined from these analyses. This infor- rarefaction level, taken to maximize the number of samples in our mation was used to analyze patterns in the community composition study, was not obscuring our results. Thus, using the samples with and similarity of functional genes. Moreover, we investigated particu- the highest sequence per sample yield, we tested for the impact of lar groups of genes that are known to be associated with pathogenesis, different levels of rarefaction on soil biodiversity. We found highly greenhouse gas emissions, nutrient cycling, and abiotic stress (Fig. 7). statistically significant correlations between the diversities and The richness of functional genes was determined from a rarefied gene community compositions of soil archaea (rarefied at 100 versus 500 table including 5.8 million annotated reads per sample. sequences per sample), bacteria (rarefied at 5000 versus 12,500 se- quences per sample), fungi (rarefied at 1000 versus 5000 sequences Statistical analyses per sample), and protists (rarefied at 1000 versus 5000 sequences Comparing the soil microbiome of urban greenspaces and per sample), for a subset of samples wherein high numbers of se- natural ecosystems quences were available. These analyses provide evidence that our We compared the richness (number of ASVs) and community com- choice of rarefaction level did not affect our results or conclusions position (proportion of ASVs, phyla/classes, or functional genes and (fig. S17). guilds) of soil organisms using two complementary statistical ap- Plot-level estimations of soil biodiversity proaches aiming to explicitly consider our sampling using a block Before data and statistical analyses, within-plot information on all design (paired urban and natural ecosystems): soil (e.g., pH) and microbial variables (rarefied ASV tables), derived 1) Response ratios. We calculated the changes in the values in from three composite soil samples per plot, were averaged to obtain the proportion and richness of soil microbial taxonomic and func- plot-level estimates (33). This allowed us to relate the spatial hetero- tional variables from natural to cities as follows: Change variable geneity in our plots (fig. S1) to our metrics of soil biodiversity (number A = Value variable A urban − Value variable A natural. This ap- of ASVs) and community composition (proportion of taxa). This proach yielded similar results to other response ratios such as per- approach allowed us to obtain plot-level estimates of the proportion centage changes: (Value variable A urban − Value variable A natural) × and number of phylotypes at the 112 studied sites (56 urban and 56 100/Value variable A natural and lnRR: ln (Value variable A urban + 1) natural paired ecosystems) for bacteria, fungi, and protists based on − ln (Value variable A natural + 1). In these formulas, “variable A” 336 composite soil samples from five soil cores each. The only ex- represents any variable included in this study (e.g., richness of bacteria). ception was archaea, for which we only obtained high-resolution Thus, on average, the response ratio used in the main analyses in this information for 92 plots including 39 urban/natural paired ecosys- paper was highly correlated with that calculated from % changes tems. Using these averaged plot-level ASV abundance tables, we (average r = 0.84; P < 0.001) and lnRR (average r = 0.99; P < 0.001) calculated the richness (number of ASVs) of the most prevalent across all microbial variables included in this study. The response ratio prokaryotic and eukaryotic organisms in our soil samples. used in our paper has the advantage that it is easy to interpret (changes in the proportion of taxa or richness) compared with other indexes Microbial functional diversity such as lnRR that implies stronger data transformation (37). A composite sample per plot was sequenced for the entire metage- 2) Nested PERMANOVA analyses (38) using a block design (to nome in 27 paired urban/natural ecosystems (54 samples). More account for our paired natural/urban ecosystem design) testing for than 500 ng of DNA per soil sample was isolated for shotgun meta­ differences in the values associated with the richness and propor- genomic (34, 35) sequencing using the DNeasy PowerSoil DNA tions of microbial variables in urban greenspaces versus natural Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 11 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE ecosystems. We used the function “adonis” in the R package “Vegan” using the average standardized relative abundance of all urban (39) and the term “strata” (block) to conduct these analyses. This greenspaces taxa. It should be noted that this calculation yielded the approach is expected to yield similar results to the response ratio exact same result as when first obtaining the individual response approach and provided complementary statistical support to our study. ratios for the proportion of each urban phylotype and then averaging This study is designed to capture the global variability of soil them out (r = 1.00; P < 0.001). microbiomes in natural and urban greenspaces. In this respect, we Environmental drivers of the soil microbiome of have 56 natural and urban replicates globally distributed. We would urban greenspaces like to clarify that within-city replication would be considered pseudo-­ We first used random forest modeling to identify the major factors replication in this design. While within-plot replication is funda- associated with the diversity, proportion, and community similarity mental when comparing two factors at a local scale or in an experiment, of soil organisms in urban greenspaces (n = 56). The importance of including within-plot replicates could result in important pseudo-­ each variable is calculated as the percentage of increase in the mean replication issues when evaluating the relationship between envi- square error (MSE) from multiple regression trees. Put simply, ronmental factors (e.g., climate) and the diversity and proportions when an important environmental factor is missing from the model, of taxa and functional genes across locations. the MSE increases, indicating that this factor is an important pre- Soil community homogenization analyses dictor of a given response variable. We then used Spearman correla- We tested for a homogenization effect of urban greenspaces cf. nat- tions to test for the link between soil biodiversity and the proportion ural ecosystems on the soil microbiome (archaea, bacteria, fungi, of the urban park core microbiome with multiple socioeconomic protists, and metagenomics). To such an end, we used the betadisper and environmental factors in 56 urban greenspaces. We also used R function (39) to calculate the dispersion within each group (urban Spearman correlations to evaluate the socioeconomic and environ- greenspaces and natural ecosystems) based on a Bray-Curtis dis- mental drivers associated with functional microbial diversity and similarity matrix. Subsequently, the permutetest function (39) was the proportion of functional genes. Spearman rank correlations are used to compare dispersions between urban greenspaces and natural a nonparametric approach that does not require normality of data ecosystems. or homogeneity of variances and measures the strength and direc- To further explore these results, we determined the average tion of the association between two ranked variables. In addition, within-group (urban or natural) community similarity of each plot unlike Pearson correlations, Spearman rank correlations can be using a Bray-Curtis similarity matrix. Locations with higher com- used to associate two variables regardless of whether they are ordi- munity similarity values indicate that the soils harbor communities nal, interval, or ratio. that are more similar in composition across natural or urban eco- Soil radiation and climatic information were extracted from the systems. These analyses were done for archaea, bacteria, fungi, protists, WorldClim database (www.worldclim.org/data/index.html). Soil and metagenomics. Significant differences in community similarity pH was measured with a pH meter, in a 1:2.5 mass:volume soil and were further tested using nested PERMANOVA analyses with a water suspension. Total nitrogen (N) in the soil was analyzed using block design (site) as described above. an elemental analyzer (C/N Flash EA 112 Series-Leco Truspec). Total Identifying the soil microbiome of urban greenspaces soil P was determined, after nitric-perchloric acid digestion, using To assess the soil microbiome associated with urban greenspaces an inductively coupled plasma optical emission spectrometer (ICAP (urban greenspaces taxa), we followed the three steps. First, using 6500 DUO; Thermo-Scientific, Waltham, MA, USA). Population the information from the plot-level ASV abundance table, we kept density was determined using the latest available city censuses using those microbial phylotypes (bacterial, fungal, and protist ASVs) official national statistical sources. We used population density that were present in at least 25% of the studied cities (40). Second, rather than the total population because it is a more complete index we then used the function “multipatt” in the R package indicspecies of the human pressure on urban environments. Population density (41) to identify those microbial phylotypes that were significant in- was positively correlated to total population (Spearman  = 0.33; dicators of city greenspaces compared with natural ecosystems. In P = 0.010). Moreover, we collected information about mowing, irri- particular, this function studies the association between species gation, and fertilization treatments in the urban greenspaces. GDP patterns and combinations of groups of sites and identifies what per capita, which provides information on the monetary value of species are most likely to be indicators of a given group of sites final goods and services in the regions for the cities surveyed, was (here, urban greenspaces). Last, we conducted nested PERMANOVA extracted from that dataset in (43), to provide information on the tests, as explained above, to ensure that the proportion of the economic activity for each location. Plant structure data (plant selected phylotypes was significantly higher in urban than natural diversity and cover) were determined in the three 30-m transects ecosystems. We always used a P < 0.01 in these analyses to ensure within each plot (fig. S1) (44). The ectomycorrhizal preferences of that we retained only those microbial phylotypes strongly associat- the dominant plant species in each plot were determined in the field ed with the urban park-associated soil microbiome. We conducted using (table S2) (45). these analyses independently for archaea, bacteria, fungi, and pro- tists. The proportion of “urban greenspaces” taxa (i.e., urban clus- SUPPLEMENTARY MATERIALS ter; Fig. 3 and table S3) was calculated as the average of all taxa Supplementary material for this article is available at http://advances.sciencemag.org/cgi/ selected as archaea, bacteria, fungi, or protist phylotypes that were content/full/7/28/eabg5809/DC1 consistently common in urban greenspaces. Before conducting these analyses, the proportion of microbial taxa was previously standard- REFERENCES AND NOTES ized (0 to 1) (42). We also calculated the difference in the propor- 1. World Health Organization, Urban Green spaces: A Brief for Action (2017). tion of selected urban greenspaces taxa from natural to urban pairs 2. United Nations Department of Economic and Social Affairs Population Division, World using the response ratio explained above. We did this calculation Urbanization Prospects: The 2018 Revision (2018). Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 12 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE 3. E. Gómez-Baggethun, Å. Gren, D. N. Barton, J. Langemeyer, T. McPhearson, P. O’Farrell, 25. J. W. Leff, S. E. Jones, S. M. Prober, A. Barberán, E. T. Borer, J. L. Firn, W. S. Harpole, E. Andersson, Z. Hamstead, P. Kremer, Urban ecosystem services, in Urbanization, S. E. Hobbie, K. S. Hofmockel, J. M. H. Knops, R. L. McCulley, K. la Pierre, A. C. Risch, Biodiversity and Ecosystem Services: Challenges and Opportunities, T. Elmqvist, M. Fragkias, E. W. Seabloom, M. Schütz, C. Steenbock, C. J. Stevens, N. Fierer, Consistent responses J. Goodness, B. Güneralp, P. J. Marcotullio, R. I. McDonald, S. Parnell, M. Schewenius, of soil microbial communities to elevated nutrient inputs in grasslands across the globe. M. Sendstad, K. C. Seto, C. Wilkinson, Eds. (Springer, 2013). Proc. Natl. Acad. Sci. U.S.A. 112, 10967–10972 (2015). 4. K. S. Ramirez, J. W. Leff, A. Barberán, S. T. Bates, J. Betley, T. W. Crowther, E. F. Kelly, 26. M. Bahram, F. Hildebrand, S. K. Forslund, J. L. Anderson, N. A. Soudzilovskaia, E. E. Oldfield, E. A. Shaw, C. Steenbock, M. A. Bradford, D. H. Wall, N. Fierer, Biogeographic P. M. Bodegom, J. Bengtsson-Palme, S. Anslan, L. P. Coelho, H. Harend, J. Huerta-Cepas, patterns in below-ground diversity in New York City’s Central Park are similar to those M. H. Medema, M. R. Maltz, S. Mundra, P. A. Olsson, M. Pent, S. Põlme, S. Sunagawa, observed globally. Proc. R. Soc. B 281, 20141988 (2014). M. Ryberg, L. Tedersoo, P. Bork, Structure and function of the global topsoil microbiome. 5. Z. Charlop-Powers, C. C. Pregitzer, C. Lemetre, M. A. Ternei, J. Maniko, B. M. Hover, Nature 560, 233–237 (2018). P. Y. Calle, K. L. McGuire, J. Garbarino, H. M. Forgione, S. Charlop-Powers, S. F. Brady, 27. R. Bhatia, Antimicrobial Resistance in developing Asian countries: Burgeoning challenge Urban park soil microbiomes are a rich reservoir of natural product biosynthetic diversity. to global health security demanding innovative approaches. Glob. Biosecur. 1, 50–54 Proc. Natl. Acad. Sci. U.S.A. 113, 14811–14816 (2016). (2019). 6. N. Hui, X. Liu, D. J. Kotze, A. Jumpponen, G. Francini, H. Setälä, Ectomycorrhizal fungal 28. C. Walsh, M. J. Gebert, M. Delgado-Baquerizo, F. T. Maestre, N. Fierer, A global survey communities in urban parks are similar to those in natural forests but shaped by of mycobacterial diversity in soil. Appl. Environ. Microbiol. 85, e01180-19 (2019). vegetation and park age. Appl. Environ. Microbiol. 83, e01797-17 (2017). 29. M. J. Gebert, M. Delgado-Baquerizo, A. M. Oliverio, T. M. Webster, L. M. Nichols, 7. C. Wagg, S. F. Bender, F. Widmer, M. G. A. van der Heijden, Soil biodiversity and soil J. R. Honda, E. D. Chan, J. Adjemian, R. R. Dunn, N. Fierer, Ecological analyses community composition determine ecosystem multifunctionality. Proc. Natl. Acad. Sci. of mycobacteria in showerhead biofilms and their relevance to human health. mBio 9, U.S.A. 111, 5266–5270 (2014). e01614-18 (2018). 8. G. A. Rook, L. R. Brunetm, Microbes, immunoregulation, and the gut. Gut 54, 317–320 30. I. Vanwonterghem, P. N. Evans, D. H. Parks, P. D. Jensen, B. J. Woodcroft, P. Hugenholtz, (2005). G. W. Tyson, Methylotrophic methanogenesis discovered in the archaeal phylum 9. K. J. Forsberg, A. Reyes, B. Wang, E. M. Selleck, M. O. A. Sommer, G. Dantas, The shared Verstraetearchaeota. Nat. Microbiol. 1, 16170 (2016). antibiotic resistome of soil bacteria and human pathogens. Science 337, 1107–1111 31. B. J. Callahan, P. J. McMurdie, M. J. Rosen, A. W. Han, A. J. A. Johnson, S. P. Holmes, (2012). DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 7, 10. J. L. Martinez, Antibiotics and antibiotic resistance genes in natural environments. Science 581–583 (2016). 321, 365–367 (2008). 32. L. Tedersoo, S. Anslan, M. Bahram, R. Drenkhan, K. Pritsch, F. Buegger, A. Padari, 11. S. M. Raciti, A. J. Burgin, P. M. Groffman, D. N. Lewis, T. J. Fahey, Denitrification N. Hagh-Doust, V. Mikryukov, D. Gohar, R. Amiri, I. Hiiesalu, R. Lutter, R. Rosenvald, in suburban lawn soils. J. Environ. Qual. 40, 1932–1940 (2011). E. Rähn, K. Adamson, T. Drenkhan, H. Tullus, K. Jürimaa, I. Sibul, E. Otsing, S. Põlme, 12. J. L. M. Rodrigues, V. H. Pellizari, R. Mueller, K. Baek, E. C. Jesus, F. S. Paula, B. Mirza, M. Metslaid, K. Loit, A. Agan, R. Puusepp, I. Varik, U. Kõljalg, K. Abarenkov, Regional-scale G. S. Hamaoui, S. M. Tsai, B. Feigl, J. M. Tiedje, B. J. M. Bohannan, K. Nusslein, Conversion in-depth analysis of soil fungal diversity reveals strong pH and plant species effects of the Amazon rainforest to agriculture results in biotic homogenization of soil bacterial in Northern Europe. Front. Microbiol. 11, 1953 (2020). communities. Proc. Natl. Acad. Sci. U.S.A. 110, 988–993 (2013). 33. F. T. Maestre, M. Delgado-Baquerizo, T. C. Jeffries, D. J. Eldridge, V. Ochoa, B. Gozalo, 13. M. M. Gossner, T. M. Lewinsohn, T. Kahl, F. Grassein, S. Boch, D. Prati, K. Birkhofer, J. L. Quero, M. García-Gómez, A. Gallardo, W. Ulrich, M. A. Bowker, T. Arredondo, S. C. Renner, J. Sikorski, T. Wubet, H. Arndt, V. Baumgartner, S. Blaser, N. Blüthgen, C. Barraza-Zepeda, D. Bran, A. Florentino, J. Gaitán, J. R. Gutiérrez, E. Huber-Sannwald, C. Börschig, F. Buscot, T. Diekötter, L. R. Jorge, K. Jung, A. C. Keyel, A. M. Klein, S. Klemmer, M. Jankju, R. L. Mau, M. Miriti, K. Naseri, A. Ospina, I. Stavi, D. Wang, N. N. Woods, X. Yuan, J. Krauss, M. Lange, J. Müller, J. Overmann, E. Pašalić, C. Penone, D. J. Perović, O. Purschke, E. Zaady, B. K. Singh, Increasing aridity reduces soil microbial diversity and abundance P. Schall, S. A. Socher, I. Sonnemann, M. Tschapka, T. Tscharntke, M. Türke, P. C. Venter, in global drylands. Proc. Natl. Acad. Sci. U.S.A. 112, 15684–15689 (2012). C. N. Weiner, M. Werner, V. Wolters, S. Wurst, C. Westphal, M. Fischer, W. W. Weisser, 34. N. Fierer, J. W. Leff, B. J. Adams, U. N. Nielsen, S. T. Bates, C. L. Lauber, S. Owens, E. Allan, Land-use intensification causes multitrophic homogenization of grassland J. A. Gilbert, D. H. Wall, J. G. Caporaso, Cross-biome metagenomic analyses of soil communities. Nature 540, 266–269 (2016). microbial communities and their functional attributes. Proc. Natl. Acad. Sci. U.S.A. 109, 14. A. Barberán, J. Ladau, J. W. Leff, K. S. Pollard, H. L. Menninger, R. R. Dunn, N. Fierer, 21390–21395 (2012). Continental-scale distributions of dust-associated bacteria and fungi. Proc. Natl. Acad. Sci. 35. F. Fierer, J. Ladau, J. C. Clemente, J. W. Leff, S. M. Owens, K. S. Pollard, R. Knight, U.S.A. 112, 5756–5761 (2015). J. A. Gilbert, R. L. McCulley, Reconstructing the microbial diversity and function 15. A. C. Murthy, T. S. Fristoe, J. R. Burger, Homogenizing effects of cities on North American of pre-agricultural tallgrass prairie soils in the United States. Science 342, 621–624 (2013). winter bird diversity. Ecosphere 7, e01216 (2016). 36. R. Overbeek, R. Olson, G. D. Pusch, G. J. Olsen, J. J. Davis, T. Disz, R. A. Edwards, S. Gerdes, 16. M. L. McKinney, Effects of urbanization on species richness: A review of plants B. Parrello, M. Shukla, V. Vonstein, A. R. Wattam, F. Xia, R. Stevens, The SEED and the rapid and animals. Urban Ecosyst. 11, 161–176 (2008). annotation of microbial genomes using subsystems technology (RAST). Nucleic Acids Res. 17. B. A. Whitton, Diversity, ecology and taxonomy of the cyanobacteria, in Photosynthetic 42, D206–214 (2014). Prokaryotes, N. H. Mann, N. G. Carr, Eds. (Plenum Press, 1992). 37. J. Koricheva, J. Gurevitch, K. Mengersen, Handbook of Meta-analysis in Ecology and 18. E. Barford, Crop pests advancing with global warming. Nature 10.1038/ Evolution (Princeton Univ. Press, 2013). nature.2013.13644 , (2013). 38. M. J. Anderson, A new method for non-parametric multivariate analysis of variance. 19. J. Beninde, M. Veith, A. Hochkirch, Biodiversity in cities needs space: A meta-analysis Austral Ecol. 26, 32–46 (2001). of factors determining intra-urban biodiversity variation. Ecol. Lett. 18, 581–592 (2015). 39. J. Oksanen, F. Guillaume Blanchet, M. Friendly, R. Kindt, P. Legendre, D. M. Glinn, 20. N. Fierer, R. B. Jackson, The diversity and biogeography of soil bacterial communities. P. R. Minchin, R. B. O’Hara, G. L. Simpson, P. Solymos, M. Henry H. Stevens, E. Szoecs, Proc. Natl. Acad. Sci. U.S.A. 103, 626–631 (2006). H. Wagner, vegan: Community Ecology Package, R package (2019). 21. A. M. Oliverio, S. Geisen, M. Delgado-Baquerizo, F. T. Maestre, B. L. Turner, N. Fierer, The 40. M. Delgado-Baquerizo, P. B. Reich, C. Trivedi, D. J. Eldridge, S. Abades, F. D. Alfaro, global-scale distributions of soil protists and their contributions to belowground systems. F. Bastida, A. A. Berhe, N. A. Cutler, A. Gallardo, L. García-Velázquez, S. C. Hart, P. E. Hayes, Sci. Adv. 4, eaax8787 (2020). J. Z. He, Z. Y. Hseu, H. W. Hu, M. Kirchmair, S. Neuhauser, C. A. Pérez, S. C. Reed, F. Santos, 22. M. Delgado-Baquerizo, R. D. Bardgett, P. M. Vitousek, F. T. Maestre, M. A. Williams, B. W. Sullivan, P. Trivedi, J. T. Wang, L. Weber-Grullon, M. A. Williams, B. K. Singh, Multiple D. J. Eldridge, H. Lambers, S. Neuhauser, A. Gallardo, L. García-Velázquez, O. E. Sala, elements of soil biodiversity drive ecosystem functions across biomes. Nat. Ecol. Evol. 4, S. R. Abades, F. D. Alfaro, A. A. Berhe, M. A. Bowker, C. M. Currier, N. A. Cutler, S. C. Hart, 210–220 (2020). P. E. Hayes, Z. Y. Hseu, M. Kirchmair, V. M. Peña-Ramírez, C. A. Pérez, S. C. Reed, F. Santos, 41. M. deCaceres, F. Jansen, N. Dell, Indicspecies: Relationship between Species and Groups C. Siebe, B. W. Sullivan, L. Weber-Grullon, N. Fierer, Changes in belowground biodiversity of Sites, R package (2020). during ecosystem development. Proc. Natl. Acad. Sci. U.S.A. 116, 6891–6896 (2019). 42. L. Wang, M. Delgado-Baquerizo, D. Wang, F. Isbell, J. Liu, C. Feng, J. Liu, Z. Zhong, H. Zhu, 23. B. S. Steidinger, T. W. Crowther, J. Liang, M. E. Van Nuland, G. D. A. Werner, P. B. Reich, X. Yuan, Q. Chang, C. Liu, Diversifying livestock promotes multidiversity G. J. Nabuurs, S. De-Miguel, M. Zhou, N. Picard, B. Herault, X. Zhao, C. Zhang, D. Routh, and multifunctionality in managed grasslands. Proc. Natl. Acad. Sci. U.S.A. 116, 6187–6192 K. G. Peay; GFBI Consortium, Climatic controls of decomposition drive the global (2019). biogeography of forest-tree symbioses. Nature 569, 404–408 (2019). 43. M. Kummu, M. Taka, J. H. A. Guillaume, Gridded global datasets for Gross Domestic 24. M. Delgado-Baquerizo, C. A. Guerra, C. Cano-Díaz, E. Egidi, J. T. Wang, N. Eisenhauer, Product and Human Development Index over 1990-2015. Sci. Data 5, 180004 (2018). B. K. Singh, F. T. Maestre, The proportion of soil-borne pathogens increases with warming 44. F. T. Maestre, J. L. Quero, N. J. Gotelli, A. Escudero, V. Ochoa, M. Delgado-Baquerizo, at the global scale. Nat. Clim. Chang. 10, 550–554 (2020). M. Garcia-Gomez, M. A. Bowker, S. Soliveres, C. Escolar, P. Garcia-Palacios, M. Berdugo, Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 13 of 14 SCIENCE ADVANCES | RESEARCH ARTICLE E. Valencia, B. Gozalo, A. Gallardo, L. Aguilera, T. Arredondo, J. Blones, B. Boeken, D. Bran, truffles from their natural distribution areas” and the Research Program in Forest Biology, A. A. Conceicao, O. Cabrera, M. Chaieb, M. Derak, D. J. Eldridge, C. I. Espinosa, Ecology, and Technology (P4-0107) of the Slovenian Research Agency. J.D. and A. Rey A. Florentino, J. Gaitan, M. G. Gatica, W. Ghiloufi, S. Gomez-Gonzalez, J. R. Gutierrez, acknowledge support from the FCT (IF/00950/2014 and SFRH/BDP/108913/2015, respectively), R. M. Hernandez, X. Huang, E. Huber-Sannwald, M. Jankju, M. Miriti, J. Monerris, R. L. Mau, as well as from the MCTES, FSE, UE, and the CFE (UIDB/04004/2020) research unit financed by E. Morici, K. Naseri, A. Ospina, V. Polo, A. Prina, E. Pucheta, D. A. Ramirez-Collantes, FCT/MCTES through national funds (PIDDAC). J.P.V. acknowledges financial support from SERB R. Romao, M. Tighe, C. Torres-Diaz, J. Val, J. P. Veiga, D. Wang, E. Zaady, Plant species (Science and Engineering Research Board) (EEQ/2017/000775) India. J.-Z.H. and H.-W.H. are richness and ecosystem multifunctionality in global drylands. Science 335, 214–218 financially supported by Australian Research Council (DP170101628). The BBVA Foundation (2012). accepts no responsibility for the opinions, statements, and contents included in the project 45. N. A. Soudzilovskaia, S. Vaessen, M. Barcelo, J. He, S. Rahimlou, K. Abarenkov, and/or the results thereof, which are entirely the responsibility of the authors. Author M. C. Brundrett, S. I. F. Gomes, V. Merckx, L. Tedersoo, FungalRoot: Global online database contributions: M.D.-B. developed the original idea of the analyses presented in the of plant mycorrhizal associations. New Phytol. 227, 955–966 (2020). manuscript and coordinated all field and laboratory operations. Field data were collected by M.D.-B., D.J.E., Y.-R.L., A.R.B., J.L.B.-P., J.G.I., T.P.M., C.S., P.T., E.Z., J.P.V., L.W., J.W., T.G., M.B., Acknowledgments: We would like to thank C. Walsh and R. Ochoa-Hueso for advice on G.F.P.-B., T.U.N., A.L.T., X.-Q.Z., J.D., A. Rodriguez,, X.Z., F.A., S.A., C.P., and A. Rey. Laboratory bioinformatics and statistical analyses. We also thank M. Martin for revising the English of the analyses were done by M.D.-B., N.F., H.-W.H., J.-Z.H., F.B., J.L.M., and L.T. Bioinformatic analyses manuscript. In addition, we thank J. Owojori for connecting us with our sampling collaborator were done by N.F., B.S., J.-T.W., B.K.S., and C.C.-D. Statistical analyses were done by M.D.-B. The in Nigeria, A. R. Bamigboye. Funding: M.D.-B. and this project were supported by a 2019 manuscript was written by M.D.-B. and edited by N.F. and D.J.E., with contributions from all Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation (URBANFUN) and by coauthors. Competing interests: The authors declare that they have no competing interests. the BES grant agreement no. LRB17\1019 (MUSGONET). M.D.-B. is also supported by a Ramón Data and materials availability: All data needed to evaluate the conclusions in the paper are y Cajal grant from the Spanish Ministry of Science and Innovation (RYC2018-025483-I). N.F. present in the paper and/or the Supplementary Materials. The data associated with this study was supported by grants from the U.S. National Science Foundation (DEB1556090 and can be found in the following: https://figshare.com/s/529c98609cd88e78e1a3; DOI: 10.6084/ DEB1542653). L.T. acknowledges support from Norway-Baltic collaboration grant EMP442 and m9.figshare.12930986. Estonian Science Foundation grant PRG632. B.K.S. acknowledges a research award by the Humboldt Foundation and funding from the Australian Research Council (DP190103714). F.A. Submitted 15 January 2021 is supported by ANID FONDECYT 11180538 and 1170995. S.A. is funded by ANID FONDECYT Accepted 26 May 2021 1170995 and ANID ANILLO ACT192027. F.B. and J.L.M. acknowledge support from the Spanish Published 9 July 2021 Ministry and FEDER funds for the project AGL2017-85755-R, the i-LINK+ 2018 (LINKA20069) 10.1126/sciadv.abg5809 from CSIC, as well as funds from “Fundación Séneca” from Murcia Province (19896/GERM/15). C.P. acknowledges support from the Spanish State Plan for Scientific and Technical Research Citation: M. Delgado-Baquerizo, D. J. Eldridge, Y.-R. Liu, B. Sokoya, J.-T. Wang, H.-W. Hu, J.-Z. He, and Innovation (2013–2016), award reference AGL201675762-R (AEI/FEDER, UE). M.B. F. Bastida, J. L. Moreno, A. R. Bamigboye, J. L. Blanco-Pastor, C. Cano-Díaz, J. G. Illán, T. P. Makhalanyane, acknowledges support from a Juan de la Cierva Formación grant from the Spanish Ministry of C. Siebe, P. Trivedi, E. Zaady, J. P. Verma, L. Wang, J. Wang, T. Grebenc, G. F. Peñaloza-Bojacá, Economy and Competitiveness (FJCI-2018-036520-I). T.P.M. would like to acknowledge T. U. Nahberger, A. L. Teixido, X.-Q. Zhou, M. Berdugo, J. Duran, A. Rodríguez, X. Zhou, F. Alfaro, contributions from the National Research Foundation of South Africa and cities involved in the S. Abades, C. Plaza, A. Rey, B. K. Singh, L. Tedersoo, N. Fierer, Global homogenization of the South African survey. Slovenian coauthors were supported by the research project J4-1766 structure and function in the soil microbiome of urban greenspaces. Sci. Adv. 7, eabg5809 “Methodology approaches in genome-based diversity and ecological plasticity study of (2021). Delgado-Baquerizo et al., Sci. Adv. 2021; 7 : eabg5809 9 July 2021 14 of 14