Abstract
This systematic review aims to investigate how urban living influences the microbiome of wildlife. We included all studies that compared the bacterial communities of non-human vertebrate wildlife living inside vs outside cities, and/or across an urbanisation gradient. We found that the effect of urban living on bacterial diversity and community composition was not unidirectional: some studies found a positive association, others found a negative association, and some found no relationship. The definition of ‘urban’ was not specified in more than half of the studies, and when included, was not consistent across studies; paired with limited site replication in many studies, these features could have obscured the impacts of urban living. Most studies also focused on urban-adapted wildlife species. Future studies that include clear definitions for ‘urban’ environments and good replication of land uses within contrasting environments would help clarify the impact of urban living on wildlife microbiomes and wildlife health.
Introduction
Urban areas currently represent the fastest-growing ecosystem on Earth (Levy et al. 2014). Cities are expanding into wildlife’s natural habitats, and animal species increasingly venture into these concrete jungles in search of resources (Williams et al. 2006), with some having become well adapted to urban life (Lewis et al. 2019). Thus, the urban environment is taking on an increasingly important role as a new habitat and foraging ground for wildlife.
The urban ecosystem is complex, comprising many different kinds of landscapes – both built and natural (Alizadeh & Hitchmough 2019). There is a need for city designs that are beneficial for the health of city dwellers, non-human animals included. However, at present, wildlife remains little considered in urban designs, the majority of which usually incorporate ecological theories and considerations regarding vegetation (Kay et al. 2022). Furthermore, much of the research on urban animals has been directed to the topic of human–wildlife conflict and risk management, rather than wildlife health (Soulsbury & White 2015).
There is a small but growing body of literature on how cities affect wildlife community assemblages and wildlife health. Urbanisation is usually attributed to the decrease in wildlife species richness. However, some studies have found that this trend is not consistent, with varying relationships between urbanisation and diversity observed depending on wildlife taxonomy and the intensity of urbanisation. For example, a notable number of studies on invertebrates, and some on vertebrate species, have found an increase in species richness at moderate intensities of urbanisation, potentially due to an increase in habitat diversity with mosaic patterns of land use (McKinney 2008, Mbiba et al. 2021).
The bacterial communities of urban animals have been gathering interest due to their importance for host health and the potential for these communities to be influenced by the surrounding environment. In humans, microbiomes directly impact host health in many ways through immune and brain function, as well as energy storage and use (Clemente et al. 2012, Nicholson et al. 2012). Presumably, microbiomes have similarly strong influences on wildlife health, but the impacts of cities on wildlife bacterial assemblages, and any associated impacts on health, are unclear (Bernardo-Cravo et al. 2020, Clarke et al. 2020)
There is evidence demonstrating the impact of living environments on animal microbiomes. The gut microbial diversity of mice responded rapidly to changes in living environment and was higher in mice that came into contact with non-sterile soil compared to sterile soil (Zhou et al. 2018). The gut microbiota of baboons was more reliably predicted by the surrounding soil microbiome than by their genetics (Grieneisen et al. 2019). For urban living, the limited evidence seems to vary. For example, in one study, faecal microbiomes of domestic dogs growing up in large cities were found to be more diverse than microbiomes from dogs growing up in small cities and the countryside (Vilson et al. 2018). In contrast, another found that skin microbiomes of domestic dogs were overall more homogeneous in cities, and urban dogs were more susceptible to allergic diseases than their rural counterparts (Lehtimäki et al. 2018). The mechanisms behind these differences are not clear.
For wildlife, living in cities might affect their bacterial communities directly by exposing them to different environmental microbial communities or indirectly by altering their foraging activities, stress hormone levels, and immune function (Francis & Barber 2013, Birnie-Gauvin et al. 2016). To date, there has been no synthesis of the literature on urban environment–terrestrial vertebrate wildlife microbiome interactions. In this context, our goal is to understand how urban living might affect the microbiomes of wildlife. We do this by reviewing the literature that compares the microbiomes of animals living in urban vs non-urban habitats, or along urbanisation gradients.
Specifically, this systematic review aims to:
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Investigate whether and how urban living affects the bacterial communities of terrestrial vertebrate wildlife.
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Explore the factors influencing the relationship between urban living and bacterial communities, such as level of urbanisation, land use, and/or wildlife species.
The review identifies current gaps in the literature, as well as potential directions for future research to better understand the impact of urbanisation on wildlife microbial communities.
Methods
Search strategy
PRISMA-P was used as a guideline for collecting, extracting, and synthesising results from peer-reviewed studies. The purpose was to critically assess articles that explored the changes in terrestrial wildlife microbiomes in relation to urban living. A thorough literature search was accomplished, then data were extracted from vetted articles and analysed.
In September 2022, articles were searched for using the databases Web of Science and Scopus without time limitation. Our search strategy combined keywords related to three components: wildlife, microbiome, and urban vs non-urban habitat. Terrestrial vertebrate wildlife species were targeted for this review; hence, we included specific terms to capture key wildlife to class level such as bird, avian, animal, and mammal. For the bacterial microbiomes, we used different synonyms of the term, as well as combinations of the word ‘community’ and other relevant terms (e.g. ‘microbiot*’ and ‘bacterial community’). For habitat, we used terms that denoted urban living and urbanisation, combined with terms to capture the types of comparisons we were aiming for: ‘urban’, ‘city’, vs non-urban, and urbanisation gradients. The searches used Boolean logic (‘and’, ‘or’) to locate the appropriate articles in the two databases (Supplementary Table 1, see section on supplementary materials given at the end of this article).
Study selection
Our inclusion criteria were as follows:
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Studies must compare animal bacterial communities in urban vs non-urban areas, or across an urbanisation gradient/scale.
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Studies must target unconfined terrestrial vertebrate wildlife, not domesticated, lab-raised, or captive animals. Invertebrates were excluded as the relationship between invertebrates and urban soil microbiomes has been more extensively explored and reviewed previously (Bray & Wickings 2019); aquatic vertebrates were excluded as the gut microbiota of aquatic animals are more susceptible to change than that of terrestrial vertebrates, especially dietary changes, and thus are more appropriate for a separate review (Ringø et al. 2016)
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Studies must examine the microbiome as a community (i.e. not specific species or antimicrobial-resistant genes).
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Only peer-reviewed journal articles in English were included. Book chapters, conference abstracts, dissertations, editorials, case studies, and opinion pieces were excluded.
Duplicates were removed from all retrieved data. One reviewer (HN) screened all titles and abstracts and excluded studies that did not meet the inclusion criteria. Studies that were included in this step then had their full text reviewed.
In the initial search, 870 records were identified from the two databases, and 654 remained after duplicates were removed. Following this step, the number of articles eligible from the title/abstract review process and selected for full-text screening was 41. One further article was excluded for not being written in English; therefore, 40 papers proceeded to the full-text screening process. At this stage, 23 studies were eliminated for not meeting the criteria for the review, because they did not compare the targeted community(s) across urbanisation levels, did not focus on terrestrial vertebrate wildlife, and/or did not analyse the microbiome. The remaining 13 studies proceeded to the data extraction phase (Fig. 1).
PRISMA flow diagram of study selection.
Citation: Microbiota and Host 2, 1; 10.1530/MAH-24-0003
The profile of studies
The 13 studies were conducted in eight individual countries in Europe and the Americas (Table 1). All studies took place in the northern hemisphere. The USA had the largest number of studies (5/13, 38.5%), followed by Canada (4/13, 30.8%). All articles were published in the past 4 years.
Key characteristics of studies included in this systematic review.
| Study | Species | Wildlife | Tissue sampled | Sequenced region | Bacterial units | Country |
|---|---|---|---|---|---|---|
| Gadau et al. (2019) | House sparrows (Passer domesticus) | Bird | Faeces | V4 region (515f/806f) | Phylum | USA |
| Stephens et al. (2021) | Mountain chickadees (Poecile gambeli) | Bird | Nest and feathers | Noted as V4 region (341f/806r) – seem mistaken as this is the V3–V4 region | OTUs | Canada |
| Maraci et al. (2022) | Great tits (Parus major) | Bird | Faeces | V3–V4 region | OTUs | Poland |
| Teyssier et al. (2020) | House sparrows (Passer domesticus) | Bird | Cloacal wipe | V5–V6 region | OTUs | France |
| Berlow et al. (2021) | White-crowned sparrow (Zonotrichia leucophrys) | Bird | Cloacal wipe | V4 region (515F/806R) | OTUs, ASVs | USA |
| Fuirst et al. (2018) | Larus gulls (Larus argentatus) | Bird | Cloacal wipe | V3–V4 region (515F/806R) | ASVs | USA |
| Murray et al. (2020) | White ibises (Eudocimus albus) | Bird | Faeces | V3–V4 region (341F/805R) | OTUs | USA |
| Teyssier et al. (2018) | House sparrows (Passer domesticus) | Bird | Cloacal wipe | V5–V6 region (BACTB-F/BACTB-R) | OTUs | Belgium |
| Phillips et al. (2018) | Nuttall’s white-crowned sparrow (Zonotrichia leucophrys nuttalli) | Bird | Cloacal wipe | V4 region (515F/806R) | OTUs | USA |
| Stothart et al. (2019) | Eastern grey squirrel (Sciurus carolinensis) | Mammal | Faeces | V4 region (515F/806R) | OTUs | Canada |
| Gurbanov et al. (2022) | Rat (Rattus rattus) | Mammal | Faeces | V3–V4 regions (341F/805R) | OTUs | Turkey |
| Stothart & Newman (2021) | Eastern grey squirrel (Sciurus carolinensis) | Mammal | Faeces | V4 region (515F/806R) | OTUs | Canada |
| Sugden et al. (2020) | Coyotes (Canis latrans) | Mammal | Faeces | V4 region (515f/806R) | ASVs | Canada |
Birds (class: Aves) were the focus of nine studies (69%), among which seven targeted passerine birds (five sparrows, two tits). The remaining studies were on mammals (class: Mammalia). For full details, see Table 1.
Faecal sampling was the most common method for studying wildlife’s bacterial assemblages (7/13, 53.8%), followed by cloacal swabs (4/13, 30.8%). Outer-layer body tissues such as skin and feathers were the next most common (Table 1).
Assessment of urbanisation
Most studies investigated the influence of urban living on wildlife bacterial communities by juxtaposing samples from one or more urban locations with samples from non-urban or ‘rural’ areas (n = 11) (Table 2). Only two studies examined animal bacterial communities across an urban gradient.
Summary of key findings regarding associations between degree of urbanisation and microbial communities of wildlife.
| Study | Diversity | Comparison | Sites (total) | Urban sites | Non-urban sites | Urban definition and/or metric | Results |
|---|---|---|---|---|---|---|---|
| Gadau et al. (2019) | Not available | Urban vs rural | Not stated | Urban yards around university campus | Rural ranch properties | Not given | No significant differences in the relative abundance of gut microbial taxa. |
| Stephens et al. (2021) | Alpha and beta diversity | Urban vs rural | 2 | Kamloops neighbourhoods | A nature park | Not given | No significant differences in the relative abundance of dominant phyla. Urbanisation was related to a slight increase in community richness, but not alpha diversity. |
| Maraci et al. (2022) | Alpha and beta diversity | Urban mosaic | 9 | An office area, two residential areas, an urban forest, an urban park, and two urban woodlands. | A natural forest and a peri-urban village | Administrative limits ISA |
Phylogenetic diversity was lower in highly urbanised areas. Other alpha diversity metrics did not significantly differ, while composition significantly differed. |
| Teyssier et al. (2020) | Alpha and beta diversity | Urban vs rural | 6 | 3 | 3 | BUA: urban sites had 100% urbanisation ratio (BUA: average home range) | Alpha diversity of juvenile birds showed no significant difference Alpha diversity of urban adult birds was significantly lower than rural. Community OTU composition was most explained by the level of urbanisation. |
| Berlow et al. (2021) | Alpha and beta diversity | Noise gradient transect | 10 | Seven noise transects | Three noise transects | Impervious surface area: increased percentages of impervious surface area and noise level in urban areas, more open areas in rural areas. Each transect was approximately 2 km long. | Bacterial richness higher in urban birds. Beta diversity of community membership differed more between urban and rural birds than beta diversity of community structure. |
| Fuirst et al. (2018) | Alpha and beta diversity | Urban vs other habitats | 3 | One highly urbanised, one intermediate | One least urbanised | Human population density (people/square mile) | Evenness was the highest at the least urbanised colony. No significant difference for other diversity metrics |
| Murray et al. (2020) | Alpha diversity | Urban land cover gradient | 15 | % of urban land cover. Five wetlands ranging 15–92%, two wildlife rehabilitation centres, a landfill, a zoo, and six urban parks all <12% | Genus diversity did not correlate with urban land cover. Microbiome community composition was strongly associated with urban land cover. | ||
| Teyssier et al. (2018) | Alpha and beta diversity | 18 | Six urban Six suburban |
Six rurals | Percentage of BUA: 0–5% for ‘rural’ plots, 5–10% for ‘suburban’ plots, and >10% for ‘urban’ plots | Landscape urbanisation did not significantly affect gut OTU richness, while the contrary was true for local urbanisation. Sparrows from more urbanised locations hosted fewer bacterial species. Strong influence of urbanisation × season on beta diversity. | |
| Phillips et al. (2018) | Alpha and beta diversity | Urban vs rural | 10 | 7 | 3 | Administrative limits ISA |
Urban birds had more diverse gut microbiomes than rural birds. Composition differed in urban and rural individuals. Beta diversity was most explained by interaction between habitat and territory impervious cover |
| Stothart et al. (2019) | Beta diversity | Forest vs urban | 2 | University campus | Small forest | Not given | OTU differences could be explained by rural vs urban, but the relationship was weak to non-existent when taken into account with other factors. |
| Gurbanov et al. (2022) | Alpha and beta diversity | Urban vs rural | 2 | Urban industrial areas | Cow farms | Not given | Urban group had a larger bacterial richness and evenness. Composition was significantly different between groups. |
| Stothart & Newman (2021) | Alpha and beta diversity | Urban vs forest, intra urban | 6 | Urban university campuses | Forests | Definition of urban not given. Sampling was divided among three site pairs throughout southern Ontario. Site pairs were comprised of one within city limits and one nearby rural deciduous forest outside of city limits. | Urban squirrels had a greater abundance of a few genera and families. There was a colour phenotype x environment (urban/rural) effect on alpha diversity. |
| Sugden et al. (2020) | Alpha and beta diversity | Urban vs surrounding peri-urban/rural | Opportunistic collection | Edmonton | Surrounding areas | Definition of urban not given. Samples were collected as roadkill, obtained from local fur trappers, or lethally managed. Coyotes were classified based on their location of death as either ‘urban’ or ‘rural’. | Urban coyotes carried more diverse bacterial communities with higher ASV richness. The nearest taxon index (NTI) was significantly lower in urban coyotes. Urban and rural coyote bacterial communities also significantly differed in overall community composition |
Half the articles in this review (n = 6) clearly defined how they had classified sites as ‘urban’ vs ‘non-urban’ for analysis. As shown in Table 2, the metric used to delineate urban and rural areas for comparison was not consistent. Three studies used percent impervious surface area, two used percent built-up area (BUA), one used percent urban land cover, and one used human population density (Table 2) to define areas considered urban and rural, respectively. As impervious surface area and built-up area are sometimes defined differently (Zhao & Zhu 2022), they were counted as separate categories for this review. Some studies used impervious surface area in combination with administrative boundaries to classify study sites into urban and rural categories. Maraci et al. (2022) and Phillips et al. (2018) used administrative limits as their main definition but also included impervious surface area in their analysis.
The remaining studies did not specify how they classified ‘urban’ vs ‘non-urban’ for their sampling and did not use a quantitative urbanisation metric for analysis.
Given the potential for inter-site variability in multiple factors that can influence bacterial communities, including land use type, soil type, and vegetation type (Grierson et al. 2023), replication of sampling within urban and rural localities is an important component in a robust urban–rural comparison. However, amongst most studies included in this review, replication of sampling location was absent or poor. A number of studies did not provide details on how their sampling sites were selected to provide an optimum representation of the designated urban and non-urban areas, they only mentioned that they sampled at different spots within urban/rural categories (Gadau et al. 2019, Stothart et al. 2019, Stephens et al. 2021, Nieto-Claudin et al. 2021, Gurbanov et al. 2022). One collected samples opportunistically, and then assigned urban or rural labels to them based on the location of animal death (Sugden et al. 2020).
Interestingly, a few studies compared bacterial communities across multiple land-use types along the urbanisation gradient; however, not all land-use types were assessed at all points of the gradient, hence they did not represent true replication. For example, Murray et al. (2020)’s chosen ‘park’ sites were mostly highly urbanised landscapes (5/6 with >60% urban land cover), and their ‘wetland’ sites were mostly more ‘natural’ landscapes (5/6 with <30% urban land cover), thus making theirs a possible wetland vs parks comparison, rather than urbanisation. Other examples of studies using different habitats to represent urban vs rural included Maraci et al. (2022) (Table 2). The inconsistency makes it more difficult to separate the effect of urbanisation on the microbiomes, vs the effect of living in different types of habitats.
The outcome of studies
The studies included in this review returned inconsistent findings with respect to the effect of urbanisation on wildlife bacterial community composition and diversity. All studies employed 16S rRNA gene sequence analysis for the identification of bacteria. The outcomes of all studies are summarised in Table 2. The key cross-study trends with respect to diversity and composition are summarised below.
Diversity
Most studies investigated how urban living was associated with both alpha (within-site) and beta (inter-site, within landscape unit) diversity of the microbiome (Table 2). Exceptions were Murray et al. (2020), which considered alpha diversity alone, and Stothart et al. (2019), which compared only beta diversity across urban and rural locations.
The studies included in this review measured alpha diversity using one or multiple metrics, ranging from total species richness (i.e. number of OTUs and ASVs) to indices combining richness and evenness. Alpha diversity measurements in microbiome studies must be interpreted with an understanding of the potential for biases to occur in the sequencing process, particularly with respect to measurements of relative abundance; for example, the read capacity of sequencers can impact the number of reads returned for a particular OTU or ASV for a given sample (Joos et al. 2020).
With this caveat, seven studies (53.8%) found a significant association between urban living and the diversity of wildlife microbiomes. The direction of the association was not consistent, with some finding an increase in diversity associated with urbanisation, some finding the opposite, and some not finding any difference (Table 2).
Some studies examined the relationship in finer detail. Stothart & Newman (2021) found an interaction effect of colour phenotype × environment on the diversity of the eastern grey squirrel bacterial community. Teyssier et al. (2020) found alpha diversity to be the same between urban and non-urban juvenile sparrows, but urban adult birds hosted less diverse communities than rural birds. Teyssier et al. (2018) found the local landscape had a stronger effect on the bacterial community, with birds living in ‘green patches’ within urbanised landscapes having significantly higher alpha diversity than birds living in ‘highly urbanised local habitat surrounded by a rural landscape’.
Community composition
Six studies reported significant differences in community composition associated with the degree of urbanisation, while three found no significant difference (Table 2). In some studies, differences in relative abundance were only detected at certain taxonomic levels (e.g. phylum, family, or genus) (Table 2). For example, at the phylum level, Murray et al. (2020) found urban land cover was associated with a significantly lower relative abundance of Firmicutes and Cyanobacteria, and increased abundance of Proteobacteria, TM7, Bacteroidetes, OP11, and TM6, but no significant differences were observed at the genus level. In another example, some genera and families within the phylum Proteobacteria (Pseudomonadaceae, Pseudomonadales, Williamsiaceae, Williamsia, Pseudomonas) were more enriched in urban house sparrows; however, no significant differences were observed at the phylum level (Gadau et al. 2019).
Notably, some OTUs belonging to potentially pathogenic microbial taxa were found to be more abundant in urban wildlife. For example, urban hosts exhibited higher abundances of OTUs belonging to the families Enterobacteriaceae (Berlow et al. 2021, Maraci et al. 2022) and Campylobacteraceae (Phillips et al. 2018, Berlow et al. 2021). The genus Clostridium was found to be less abundant in urban coyotes (Sugden et al. 2020), but more abundant in urban squirrels (Stothart & Newman 2021) compared to their rural counterparts.
Urban wildlife was sometimes found to have higher abundances of some taxa that promote lipid metabolism and are beneficial to digestion, such as Lachnospiraceae (Sugden et al. 2020, Stothart & Newman 2021, Gurbanov et al. 2022), Lactobacillaceae (Teyssier et al. 2020, Berlow et al. 2021, Gurbanov et al. 2022), and Sutterella and Parasutterella (Stothart & Newman 2021).
Discussion
Overall, our review found evidence suggesting that in some contexts, urbanisation may be impacting wildlife bacterial communities, both at phylum and lower taxonomic levels. However, the nature, degree, and direction of the effect were not consistent among studies, and the number of studies systematically investigating this topic remains small, increasing the difficulty of elucidating clear patterns and trends. In addition to the complexity of the influence of urbanisation on wildlife bacterial communities, our synthesis revealed several key findings with implications for ongoing wildlife microbiome research.
First, our synthesis suggests that specific bacterial taxa show varied responses to urbanisation that are associated with their ecological characteristics. For example, the literature reviewed here suggests an emerging pattern of urban wildlife having higher abundances of bacterial taxa associated with digestion and specific nutrient absorption needs. Specifically, taxa belonging to the phylum Firmicutes such as Lachnospiraceae and Lactobacillaceae are generally associated with diets that are high-fat and high-carbohydrate in humans and mice (Beam et al. 2021). Lactobacillaceae is a group of beneficial gut bacteria that aid in the digestion of polysaccharides (Huynh & Zastrow 2023), but a high concentration of some bacteria in this taxa has been linked to obesity in adult humans (Chakraborti 2015). Lachnospiraceae is also a beneficial group of bacteria, but high abundances of this taxa are positively correlated with glucose and/or lipid metabolism and are associated with a high-fat diet in mice and humans (Vacca et al. 2020, Companys et al. 2021). Similarly, Parasutterella and Sutterella of the phylum Proteobacteria were observed to be a strong feature of the microbiome of wild red squirrels supplemented with food with higher sugar and fat contents than their natural diet (Dill-McFarland et al. 2014), which might be the case with the urban squirrels in the study by Stothart et al. (2019). It could be hypothesised that the higher abundances of bacteria from these groups are linked to urban wildlife having diets higher in fat and sugar, for example, via consumption of human food waste, and this hypothesis could warrant further investigation.
Our synthesis also reveals that bacterial taxa, including potential pathogens, were sometimes found to be more abundant in urban wildlife. For example, families such as Enterobacteriaceae, which includes Salmonella and Escherichia coli. In birds, taxa within Enterobacteriaceae have been associated with dysbiosis, higher mortality and hatching failure in ostriches (Knöbl et al. 2012, Videvall et al. 2020), and the health burden of Enterobacteriaceae pathogens in humans remains high (Lee et al. 2021). Taxa from Campylobacteraceae were also found to be elevated in some urban wildlife; this group includes Campylobacter sp. and feather-degrading bacteria. Campylobacter sp. is one of the most important contributors to the burden of foodborne disease in humans in high-income countries (Devleesschauwer et al. 2017). However, Clostridium, which includes several pathogens including botulism and tetanus agents, was found to be both less abundant (Sugden et al. 2020) and more abundant (Stothart & Newman 2021) in urban wildlife compared to their rural counterparts. If urban wildlife does indeed harbour more pathogens, it may present concerns with respect to both wildlife health and disease transmission to humans. While noting that this pattern was not uniform across all studies included in this review, which suggests a complex relationship potentially dependent on wildlife species and environmental context, we suggest a need for further systematic work to clarify patterns of pathogens in urban wildlife bacterial communities, which would have implications for human health.
There was also a slight inconsistency in the sequencing method. Both OTU and ASV-based methods are commonly used to classify sequences in microbiome studies: OTUs are usually defined as clusters that share at least 97% similarity in their genetic sequence (Nguyen et al. 2016), whereas ASV methods focus on detecting single-nucleotide variants. This makes ASV taxonomic groupings more comparable across studies (Maruyama et al. 2020); however, ASV methods are more complex and computationally intensive. The advantages of ASV over OTU approaches may depend on the context of the study: some studies have found ASV methods to be more sensitive in detecting bacterial strain differences, and OTU methods to inflate alpha diversity (Chiarello et al. 2022), while other studies have found consistent results between both methods (Moossavi et al. 2020). Regardless, the classification method can affect the comparability of results across studies.
Another key finding of our synthesis was the need for greater rigour and consistency in urbanisation metrics. Defining and measuring urbanisation has been a long-running issue within the field of urban ecology; and ambiguity and inconsistency with definitions of urban spaces and gradients can lead to biases in our understanding (Kendal et al. 2020). Similar to McIntyre et al. (2000), we found that many studies simply assumed what is ‘urban’, without clearly specifying why or how they had defined urban (and non-urban) landscapes, and few used a quantitative measure of urbanisation for analysis. Urban landscapes are complex mosaics with widely varying environmental variables (Hahs & McDonnell 2006); using only administrative boundaries to define cities is often insufficient to capture the socio-ecological characteristics of these places. Frameworks to define urbanisation with quantitative metrics have been proposed to increase comparability among independent studies (Theobald 2004); however, only a small number of studies in this review utilised such approaches. Where quantification was used, the studies reviewed here used approaches based mainly on (i) physical geography: city boundaries, percentages of impervious surface area, or built-up area and (ii) demography: by human population in the areas.
The inconsistency in how urban areas were defined across the studies in this review may partly explain the inconsistent findings regarding the impacts of urbanisation on wildlife bacterial communities. We suggest that for this field of research, greater rigour and consistency in urban metrics would be beneficial. An additional factor underlying the inconsistency of trends may be the tendency for urban areas to comprise a mosaic of heterogeneous environments, making it difficult to quantify urban effects. One study concluded that homogeneous environments (urbanised habitat in urban landscapes or rural habitat in rural landscapes) often harboured higher bacterial diversity compared to heterogeneous environments (Teyssier et al. 2018). Some studies in this review found that urbanisation explained some variations in the composition of bacterial communities, but the relationship became weak or insignificant when other environmental factors were included in the models (Stothart et al. 2019, Stothart & Newman 2021). We suggest that greater consideration of both local and landscape habitat factors would benefit this field of research, given clear evidence that both local and landscape habitats have been found to influence bacterial diversity (Bergman et al. 2008, Callaghan et al. 2018, Cely-Santos & Philpott 2019, Han et al. 2021). An example of this is Teyssier et al. (2018)’s study, where birds living in very urbanised patches within rural landscapes had significantly lower bacterial diversity than birds from ‘green patches’ within urbanised landscapes. Future work should ensure local habitat variation is considered in study design.
With respect to administrative boundaries as a means of delineating urban from rural areas, it is generally considered that administrative boundaries are insufficient to capture the complexity and multitude of urban habitats (Maraci et al. 2022). Administrative boundaries can also create ecological boundaries due to management differences between regions, but this may be context-dependent and hard to generalise across studies (Aslan et al. 2021). Interestingly, one study in this review found that habitat type as defined by administrative limits was more influential on the bacterial community than percentages of impervious surface area (Phillips et al. 2018). This further demonstrates the complexity of the structure and management of urban ecosystems, and the need for researchers to carefully consider how to define urban living and urbanisation for their research.
We also identified a need for greater rigour in replication in the sampling of urban (and non-urban) habitats. Given the mosaic nature of urban (and rural) landscapes, sampling replication across land uses in each landscape category is key to support systematic examination of patterns and adequate consideration of local landscape variation. Loosely defined replicates, or lack thereof, reduce the ability of studies to draw conclusions about the cause of any differences found between landscapes. Thoughtful sampling design that incorporates robust, independent replication, and which controls for key confounding factors, is important to support stronger conclusions about the cause of observed patterns. Many of the studies in this review did not have replicates within each of their urban and non-urban categories (Fuirst et al. 2018, Stephens et al. 2021, Gurbanov et al. 2022) and/or did not incorporate systematic sampling of multiple land-use types and habitats in each landscape type. We suggest that replication and adequate consideration of local landscape heterogeneity should be key considerations for study design going forward.
In this review, most studies focused on species known to be well adapted to urban environments, being either urban adapters (which make use of urban resources and habitats but remain largely dependent on natural resources), or urban exploiters, which are well-versed in navigating cities for food and shelter and can attain higher population density in urban spaces (McKinney 2006, Winarni et al. 2022). There was a noticeable focus in studies of urban wildlife microbiome on avian species, especially passerine birds. Birds have often been used to study effects of environmental changes such as urbanisation, especially passerines due to their omnipresence and small home range (Ding et al. 2023). Small passerines featured in this review, such as great tit Parus major, chickadees Poecile sp., and house finch Haemorhous mexicanus, are urban adapters and are often the subjects of research examining how city living affects wildlife biology (Donselaar et al. 2018, Isaksson 2018). House sparrows (Passer domesticus) were the most represented species, likely due to their ubiquitous appearance in cities as urban exploiters (Mohring et al. 2021). The other non-passerine birds (gulls and ibises) are also known to be well able to utilise human resources in cities. Similarly, mammalian subjects of research such as rats, squirrels, and coyotes were those that do well in urban settings and are able to coexist with humans (Bateman & Fleming 2012, Blasdell et al. 2022, Rimbach et al. 2022). All species are readily abundant in their local range. Urban avoiders were generally missing from studies. This is a trend across much ecological research, where common species are often targeted, as one risks lower data collecting availability and thus not being able to achieve rigorous statistical analysis (Fancourt 2014, Koertner et al. 2015). However, the consequence of wildlife microbiome research being driven by feasibility and convenience is that there is a knowledge gap on how the microbiome of urban avoiding species is affected by urban living and urbanisation, and if they play any role in their host’s avoidance behaviour.
Beside the overall lack of clear definitions and sampling in urban areas, our review also suggests a gap in understanding how urban living impacts microbiomes over time. Previously, a study found that, over a period of 18 days, the community composition and abundance of magpie eggs and nests in urban vs rural populations exhibited different trends (Lee et al. 2017). Among the studies included in this review, only Teyssier et al. (2018) examined time intervals, identifying an interaction between season and urbanisation on the microbiome.
The findings of our review are limited by our use of only two literature databases, although our approach complies with the minimum requirements set by the PRISMA guidelines. Secondly, the review only aimed for studies published in English. On this basis, we may not have identified the full range of literature in this field. And finally, the current relatively understudied state of this field of research limited what conclusions could be drawn with certainty. However, our study also has important strengths, being the first to examine the available literature on how urban living influenced the bacterial communities of wild animals, revealing some noticeable directions for expanding knowledge in this emerging field.
This review focused on the bacterial components of wildlife microbiomes. Other components that have also been found to be influenced by urban living but are beyond the scope of this review are as fungi/yeast, viruses, and protozoa (Lee et al. 2017, Fisher et al. 2023). Many wildlife species carry fungal, viral, and protozoan species that can infect humans, increasing the burden of disease (Akritidis 2011). Previously, antifungal-resistant yeast species have been found in the gut microbiome of urban birds (Al-Yasiri et al. 2017), holding implications for both human health, as antifungal genes can be transferred to the urban environment and then human, and animal health, as antifungal genes could have been transferred to them from living in urban environments. Loss of biodiversity, which urbanisation has been known to cause (Kondratyeva et al. 2020), also increases the risk of zoonotic infection (Glidden et al. 2021). Thus, it is important to investigate the impact of urbanisation on all components of wildlife microbiomes for both human and animals’ health. Future reviews and studies can expand upon this aspect.
Conclusion
This review suggests that urban areas are complex habitats with many heterogeneities, which create complicated relationships between urban environments, wildlife hosts, and wildlife microbiomes. The research identified by this review reveals a number of differences between the microbiomes of animals habituating urban vs non-urban areas. However, patterns are complex, environment- and taxon-dependent. Our review also identified a range of improvements that could be made by future studies to generate more comprehensive results that are more comparable between studies. We suggest that, in addition to greater replication and consideration of landscape heterogeneity, more rigour in definitions and metrics of urbanisation is key, with ecologically relevant metrics adopted such as human population, or percentage of built-up or impervious surface areas. There may also be a benefit in expanding the range of species targeted for wildlife microbiome studies to include urban avoiders and exploring microbial taxa beyond bacteria. Greater clarity on the impacts of urban living on wildlife microbiomes, and how this impacts wildlife health, could improve urban design and the conservation of urban-dwelling wildlife.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/MAH-24-0003.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the study reported. This article was prepared as part of a PhD degree at the University of Tasmania.
Funding
This study did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector.
Author contribution statement
All authors took part in study conceptualisation and design. Literature search and data analysis were performed by HKDN. The first draught of the manuscript was written by HKDN, and all authors commented on and revised all versions of the manuscript. All authors read and approved the final version of the manuscript.
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