Over the last 100 years, urban populations have increased dramatically (Cox et al. 2018 ).
Indeed, urbanisation is predicted to increase further with an estimated 60% of the world's 48 population living in towns and cities by 2030 (Hake et Biodiversity loss is a global megatrend, with current species extinction rates estimated to be 58 1,000 times higher than historical background rates, and future rates likely to increase to 59 10,000 times higher (Haahtela et al. 2013; De Vos et al. 2015) . This is driven in part by 60 urbanisation, and associated processes including unsustainable land use, resource 61 exploitation, pollution and climate change (Sol et Hooks and guy ropes were also installed, ensuring stability in the field. Steel brackets were 176 installed to secure petri dishes, which we used to passively sample the aerobiome as per 177 9 179
The level of stability was tested in two phases -Phase 1: during windy conditions (~Beaufort 180 scale No. 5) in a yard environment, and Phase 2: in situ, prior to the sampling phase. 
We installed temperature and relative humidity data loggers at each sampling station. Each 188 logger was programmed to record data at 8-second intervals for the entire sampling period. 189
The dataloggers were calibrated using a mercury thermometer and a sling psychrometer. 190 191
The sampling stations were placed into position between 0600-0800hrs on 4th, 5th and 6th 193 November 2019. This ensured sufficient time was allocated to travel between the sampling 194 locations. From 0800hrs onwards and prior to installing the petri dishes for passive sampling, 195 the sampling stations were decontaminated using a 5% Decon 90 solution. The microclimate 196 data loggers were then decontaminated and installed on the sampling stations. The sampling procedure involved collecting soil samples (actively) and airborne microbiota 202 (passively). Environmental metadata were also collected (e.g., windspeed, temperature and 203 relative humidity). Soil pH at each site was measured using a digital pH meter (Alotpower). 204
The probe of the pH meter was inserted into the soil and left for a period of 1-minute prior to 205 taking a reading, as per manufacturer's instructions. Topsoil samples were collected using a small shovel and stored in 50 mL sterile falcon tubes. 214
The shovel was decontaminated using the 5% Decon 90 solution prior to use. Wearing gloves, 215 we sampled five topsoil samples (depth: 5-7cm) at equidistant sampling points, 20-30 cm 216 12 or an adult lying on the floor. The steel petri dish sampling plates were also decontaminated 241 using the 5% Decon 90 solution prior to use. 242
The petri dishes were secured to the sampling stations ( Figure 2) and were left open for 6-8 244 hours (Mhuireach et al. 2016) . At the end of the sampling period, we closed the petri dishes. 245
A new set of gloves was worn for the handling of petri dishes at each vertical sampling point 246 to reduce contamination. The petri dishes were then sealed using Parafilm, labelled, 247 immediately placed on ice, and transported to the laboratory for storage at -80˚C prior to 248 Museum. The order of processing samples was randomised using a digital number 256 randomiser, including the soil samples (higher biomass), which were processed after the low 257 biomass, aerobiome samples to minimise cross-contamination. 
Paired-end reads were assembled by aligning the forward and reverse reads using PEAR 279 (version 0.9.5). Primers were identified and trimmed. Trimmed reads were processed using 280
Quantitative Insights into Microbial Ecology (QIIME 1.8.4), USEARCH (version 8.0.1623), 281 and UPARSE software. Using USEARCH tools, reads were quality filtered, full length 282 duplicate reads were removed and sorted by abundance. Singletons or unique reads in the data 283 set were discarded. Reads were clustered and chimeric reads were filtered using the 284 "rdp_gold" database as a reference. To obtain the number of reads in each operational 285 taxonomic unit (OTU), reads were mapped back to OTUs with a minimum identity of 97%. 286
Taxonomy was assigned using QIIME. Spearman's rank correlation tests were used to examine correlations between sampling height 308 and alpha diversity scores. A Mann-Whitney Wilcoxon test was used to examine differences 309 in alpha diversity between merged air sampling heights (0.0 -0.5 m and 1.0-2.0 m) and a 310
Kruskal Wallace chi-squared test to explore differences in correlations between sites and 311 dates. We also calculated OTU relative abundances using the phyloseq package in R to 312 examine the distribution of taxa that have potential implications for public health. Results
We observed a significant negative correlation between alpha diversity (air and soil for all 319 sites/dates) and sampling height (r = -0.58, df = 38, P = <0.01; Figure 3A ; Table 1 ). 320
Alpha diversity ranged from 1 to 6 and was highest at soil level followed by the lower air 321 
Here we show that vertical stratification of aerobiome alpha diversity occurred. This 416 transpired as a significant association in the reduction of bacterial alpha diversity as height 417 increased (i.e., between the ground surface level and two vertical meters of the air column). 418
When considering all sampling heights, alpha diversity reduced with greater height. This 419 vertical stratification in alpha diversity was neither spatially (i.e., site specific) or temporally 420 dependent. The strength of the negative relationship between alpha diversity and height 421 increased when we merged lower sampling heights (0.0m with 0.5m) and the upper sampling 
We also showed vertical stratification of aerobiome beta diversity, where sampling height 455 explained 22% of the variation in environmental microbiota when all sampling heights were 456
included. This was corroborated by the analysis of equality of taxonomic proportions between 457 the air and the soil samples. As mentioned, the proportion of bacterial taxa from the air 458 samples that were also present in the soil decreased as altitude increased. This provides 459 preliminary evidence that soil has a stronger influence on aerobiome composition at lower 460 heights and allochthonous sources make a key contribution to the aerobiome higher up. Generally not considered to be pathogenic to humans. Spatial distribution suggests potential allochthonous deposition. Conclusions 522 We provide support for the presence of aerobiome vertical stratification in bacterial diversity 523 (alpha and beta), and demonstrate that significant spatial differences in known pathogenic and 524 beneficial bacterial taxa occur. Although the need to promote healthy ecosystems and 525 understand environmental microbial exposures has always been important, in light of the 526 COVID-19 pandemic, it is now justifiably at the forefront of many public health agendas 527 worldwide. As discussed, there is growing evidence to suggest that exposure to the 528 microbiome in biodiverse green spaces contributes towards 'educating' the immune system 529 We acknowledge and pay our respects to the Kaurna people, the traditional custodians whose 571 ancestral lands we conducted the research on for this study. We also acknowledge the City of 572
Adelaide who helped to facilitate this study through time and resources. 573