City life does not change a small mammal community composition

doi:10.21203/rs.3.rs-4848585/v1

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City life does not change a small mammal community composition

https://doi.org/10.21203/rs.3.rs-4848585/v1

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Urbanization is a known widespread phenomenon with profound forms of land use changes. Urban areas are characterized by habitat fragmentation and the replacement of natural habitat by human-made structures impacting various environmental conditions (e.g., natural resources, light and noise level, temperature) and transforming wildlife communities. The overall effect of urbanization on wildlife communities can differ between taxa, although most results suggest an overall decrease of species abundance and evenness in urbanized areas. In this study, we analyzed 25,982 photos from a camera trap survey in 33 gardens in the city of Münster, Germany. Our goal was to investigate if community composition, species diversity and evenness, and species co-occurrence patterns of terrestrial small mammals change as a function of impervious surface cover. Eight taxa were recorded and Apodemus spp. predominated (73.8%) the captured photos. We found that community composition, species diversity and evenness do not change along the urbanization gradient (i.e., impervious surface cover). In addition, we observed mainly neutral associations between species, although one trend for a positive association between Myodes glareolus and Crocidura spp., and two trends for negative associations between Apodemus spp. and Crocidura spp., and Rattus norvegicus and Sciurus vulgaris were discernable. Overall, our results suggest that this small mammal community is not impacted by urbanization. The small mammal species community of Münster is likely the result of generalist species expressing high phenotypic plasticity to bypass the urban filters explaining our overall neutral results. Further studies will be needed to address whether our findings for this small mammal species community are generalizable to multiple cities in Europe.

Urbanization

community ecology

camera traps

species co-occurrences

wildlife camera

Urbanization is one of the most profound and pervasive forms of land use change globally. As cities expand, natural habitats are increasingly fragmented, transformed, or replaced by human-made environments, and biodiversity has become seriously threatened by habitat loss and degradation of urban habitats [1–3]. Urban areas are characterized by a mosaic of habitats, ranging from highly developed city centers to peri-urban green spaces, each influencing the distribution and abundance of wildlife in distinct ways [4, 5]. Urbanization can alter community composition and reduce both species richness and evenness of biotic communities [5–8], although they remain unchanged in some locations [9, 10]. Differences in parameters such as the degree of urbanization, available vegetation and time since development can affect how animal communities respond to urbanization [3, 11–13]. Several factors have been hypothesized to determine community assembly, such as regional climatic and biogeographical factors, human facilitation, urban structure and development history, socioeconomic and cultural factors, species interactions together with a species’ life history and functional traits [14]. Within cities, biological communities often differ from surrounding communities because urbanization can exert a filtering effect on species, rearranging them into novel urban communities [15, 16]. An increasing biotic homogenization across urban landscapes has been reported, where well-adapted species with similar traits (e.g. degree of dietary or habitat specialization or mobility) or life histories become increasingly widespread geographically and locally abundant [17–20].

The manner in which animal communities change in response to urbanization can vary between taxonomic groups, but some common trends have been reported across taxa. For instance, globally, urban bird communities tend to shift towards more omnivorous, granivorous, and cavity-nesting species, with a concurrent decline in insectivorous species [21], and urban-associated bird species tend to have broader dietary and habitat niches and to have greater dispersal ability [22]. Beetle communities have been observed to shift towards species with a high thermal preference and better dispersal capacities [16]. Similarly, urban butterfly communities are dominated by habitat generalists and mobile species [23]. The number of butterfly, dragonfly and bird species decreases from more natural areas to more urbanized areas in Europe [20, 23–28]. The diversity and richness of native rodent species is found to decrease with increasing urbanization in Buenos Aires, Argentina [29]. Multi-city studies in North America have demonstrated that species richness consistently declines when housing density at a site exceeds the average housing density [11]. Furthermore, urbanization has been found to have a more detrimental impact on larger-bodied species compared to smaller-bodied species [30]. Additionally, the negative effects of urbanization on species richness and diversity have been observed to be more pronounced in warmer, less vegetated cities [11, 30].

Nevertheless, neutral or positive effects of urbanization on species diversity have also been reported. For instance, bird species richness and Shannon’s diversity index in Santa Clara County, California, have been found to be highest at an intermediate level of urbanization [31]. Similarly, developed areas of two eastern US cities (Washington, DC and Raleigh, NC) show similar or higher mammalian occupancy, relative abundance, species richness and diversity compared to wild areas [32]. These findings highlight the complex patterns of species diversity variations along rural-urban gradients, which are associated with non-random changes in community composition [8]. In addition, specialist and generalist species can show opposing responses to urbanization [26].

Studying urban mammal communities provides valuable insights into the ecological resilience and adaptability of vertebrate species in anthropogenically modified landscapes [19]. Across Europe, mammal species richness increases with human population density but shows no relationship with percentage of urban land cover [33]. However, how small mammal communities respond to urbanization has been studied less intensively. Small ground-dwelling mammal species richness, diversity and evenness decrease from more natural areas to more disturbed and urban areas in Italy and Poland [34–36]. Given the paucity of data and contradicting findings across taxa, we aimed to investigate the urban small mammal community within Münster, Germany by employing camera trap surveys. We determined community composition, different species diversity and evenness indices and species co-occurrence patterns of terrestrial small mammals across a gradient of urbanization. Our aim was to assess if the aforementioned measures change as a function of impervious surface cover. We expected that small mammal species richness and diversity would decrease with increasing impervious surface cover.

Study sites and camera setup

We used camera-trap data collected between September 2023 and March 2024 to assess small mammal species occupancy, richness and diversity in the city of Münster, Germany. In 2022, Münster had 320.946 inhabitants and the population projection predicts further increasing population growth in the city (http://statistik.stadt-muenster.de). Via the distribution of flyers, we recruited garden owners in Münster that were willing to allow us to set up a passive infrared-triggered wildlife camera (Wilsus Juxta, Wildlife Monitoring Solutions, Netherlands) in their garden. We placed cameras in areas with little human activities (e.g. under shrubs or trees or in flower beds, but not on terraces or lawn). This study focused on small-bodied mammals which are typically under-represented or not detected at all in camera trapping studies [37]. Thus, we mounted cameras with close-focus lenses (+ 1 diopters) on sticks 50 cm above ground and angled downward, focusing on the center of a food tray filled with earth (distance 60 cm between plate and camera). The cameras used in this study have a fast trigger speed (0.35s), suitable to capture small and fast-moving species. For five consecutive nights, garden owners baited the food tray with approximately the same quantity of sunflower seeds with husk (ca. 12g) and dried mealworms (ca. 5g), which they covered with some earth from the garden. Camera traps were set to be operative for 24h a day, to record a burst of two consecutive photos (rapid fire) at each activation, and with the minimum triggering interval between activations. The date and time of capture were automatically stamped onto each photo. We collected data at a total of 35 sites. Due to malfunctioning of the cameras, only 33 sites could be included into data analyses. Of these, 31 sites were private gardens and two sites were gardens belonging to the University of Münster. The study sites were spread throughout the city and its surroundings (Fig. 1A).

Photo evaluation

All photo identification was conducted by one trained person (KH) using the software Timelaps (version 2.3.0.0) (https://saul.cpsc.ucalgary.ca/timelapse/pmwiki.php?n=Main.HomePage). Only photos with sufficient quality to clearly identify animals to the genus or species level were included. Given the challenges in identifying them to the species level from camera trap images, we identified shrews to the genus level (Crocidura). Yellow-necked mice and wood mice (Apodemus flavicollis and A. sylvaticus, respectively) cannot be identified to the species level from photos alone. Therefore, we summarized them to the genus level Apodemus. We recorded a total of 35,606 photos, of which 28,428 captured animals. Of those, 2,442 were excluded from the analyses because they did not depict focal species but pets (cats or dogs) or birds (including birds of prey such barn owls), resulting in a final dataset of 25,982 photos.

Environmental sampling

We determined the intensity of urbanization as the percentage of impervious surface around each site calculated using the QGIS software (version 3.36). Percentage of imperviousness is a widely used indicator for urbanization intensity [39]. We calculated the percentage of impervious surface for three different buffer zones surrounding each study site: a buffer of 100 m, 500 m and 1000 m radius (Fig. 1B). We included three buffer sizes to include areas of different ranging activities of animals of different body sizes. The 100 m buffer corresponds to the daily movement distances of smaller animals and 500 m comprises the average dispersal distance of small mammals [40, 41]. The 1000 m buffer was included as a null model to ensure that the maximum dispersal distance is included. The largest buffer was also included to assess whether patterns on a larger scale would be visible. To calculate percentage of imperviousness, we imported the OpenStreetMap Plugin into QGIS, on which the map containing all study sites was created (Fig. 1A). “EPSG:5652” (EPSG:5652 - ETRS89 / UTM zone 32N (N-zE)) was the corresponding coordinate reference system for the map excerpt of Münster. The coordinates of all study sites were added as a single shape file layer. By creating vectors with distinct distances around each data point we added the three different buffers (Fig. 1B). To calculate the percent of impervious surface for each buffer size and study site, we used an open access data set with comprehensive land-use classification provided by the city of Münster [42].

Species diversity indices

Species diversity can be described using different measures and indices. Using species richness (S), the absolute number of species, as the sole measure of diversity can be problematic because this measure does not consider differences in species’ abundances. To account for the uneven occurrence of species, various diversity indices that include the relative abundance of species have been developed. The Shannon’s diversity index or Shannon-Weaver index (H’) is a commonly used diversity index and describes the uncertainty of the species affiliation of an unknown individual. Accordingly, the value of the index increases with a higher diversity of species [43]. H’ is calculated as follows [43–45]:

$$\:\text{H}{\prime\:}\:={\sum\:}_{i=1}^{S}{\text{p}}_{i}\text{\:}{log}_{b}\:{p}_{i}$$

where p_i is proportion of species i, S is the species richness (the number of species), b is the base of the logarithm. This index is influenced relatively more by species richness than species evenness. Pielou’s index of evenness (J), also called Shannon’s evenness, is commonly used to determine how evenly species are distributed in a community [46]. It is calculated as follows:

$$\:\text{J}\:=\:H{\prime\:}\:/\:log\left(S\right)$$

where H’ is the Shannon-Weaver index and S = species richness.

Statistical analyses

We analyzed all data in R v.4.2.3 [47]. We used the package vegan [48] to plot the species accumulation curve using the function ‘specaccum’. Using the vegan package, we determined several common and widely used species diversity indices: species richness (S) as the absolute number of species present, Shannon’s diversity Index (H) and Pielou’s index (J) for evenness [49, 50]. We assessed if the three measures of species diversity change with increasing impervious surface cover for each of the three buffer zones using linear models. To assess for potential non-linear relationships, we also included the quadratic term of impervious surface cover in the linear models. We tested if model assumptions were met using the performance package [51] and if required, transformed data to reach normally distributed residuals.

We tested the potential co-occurrence patterns between species pairs using the probabilistic model of species co-occurrence using the cooccur package [52]. This model allows the calculation of the probability that two species co-occur at a frequency either less than or greater than the observed frequency of co-occurrence. The model is based on calculating the probability (Pj) that two species co-occur at exactly j sites (sampled study sites). To ensure that positive and negative associations are not due to the influence of a few study sites, we randomly removed two gardens from the data set and ran the analysis again. We repeated this in a loop for 30 iterations.

We detected the following eight species/taxa: yellow-necked mouse (Apodemus flavicollis) and wood mouse (A. sylvaticus) (summarized to Apodemus spp.), European hedgehog (Erinaceus europaeus), European rabbit (Oryctolagus cuniculus), brown rat (Rattus norvegicus), white-toothed shrews (Crocidura spp.), Eurasian red squirrel (Sciurus vulgaris), stone marten (Martes foina) and bank vole (Myodes glareolus). The majority of photos (73.8%) depicted Apodemus spp., 8.0% bank voles, 7.2% brown rats, 6.3% white-toothed shrews, 3.9% European hedgehog, 0.7% red squirrels, 0.1% stone marten and less than 0.1% European rabbit. The species accumulation curve shows an asymptotic trend, suggesting that further sampling would yield diminishing returns in discovering new species (Fig. 2).

The included study sites covered a very broad range of impervious surface cover. For the 1000 m buffer, impervious surface cover was on average 40.9% (range: 8.2–71.7%), for the 500 m the average value was 43.0% (range: 2.9–76.6%) and for the 100 m buffer it was 46.9% (range: 4.2–89.3%). There is no clear taxonomic pattern in community composition along the urbanization gradient (Fig. 3). With the exception of the European rabbit, all species occurred at study sites covering the range of the urbanization gradient (Fig. 3). Species richness, Shannon diversity index and Pielou’s evenness index did not vary with impervious surface cover (LMs: all P ≥ 0.22; Fig. 4).

Species co-occurrence patterns

Most pairwise comparisons showed co-occurrences which were not different from the expected co-occurrence (Table 1). Positive associations were absent in the data, but there was a trend for a positive association between Crocidura spp. and Myodes glareolus. Two species pairs showed negative associations, Apodemus spp. and Crocidura spp., and Rattus norvegicus and Sciurus vulgaris (Table 1). These results were confirmed by looping through the data 30 times, each time randomly removing two study sites. No positive association was found in any of the 30 iterations. In two iterations, no negative association was found, in 23 iterations one negative association was found and in five iterations two negative association were found. In 19 iterations (57.6%) a negative association occurred between Apodemus spp. and Crocidura spp. and in 14 iterations (42.4%) a negative association between Rattus norvegicus and Sciurus vulgaris occurred.

Table 1

**Observed and expected frequencies of co-occurrence between species pairs.** For each pair, the probability indicates whether the value of co-occurrence is lower or greater than the expected value. Bold type indicates species co-occurrences significantly lower or greater than expected.
Species 1	Species 2	Number of sites that have species 1	Number of sites that have species 2	Observed number of sites having both species	Expected number of sites having both species	Probability of co-occurrence at a frequency lower than observed	Probability of co-occurrence at a frequency greater than observed
Apodemus spp.	Erinaceus europaeus	26	17	13	13.4	0.537	0.775
Apodemus spp.	Rattus norvegicus	26	5	5	3.9	1	0.277
Apodemus spp.	Crocidura spp.	26	11	6	8.7	0.027	0.998
Apodemus spp.	Sciurus vulgaris	26	15	11	11.8	0.391	0.870
Apodemus spp.	Martes foina	26	6	5	4.7	0.792	0.624
Apodemus spp.	Myodes glareolus	26	19	15	15	0.679	0.652
Erinaceus europaeus	Rattus norvegicus	17	5	2	2.6	0.470	0.851
Erinaceus europaeus	Crocidura spp.	17	11	5	5.7	0.451	0.805
Erinaceus europaeus	Sciurus vulgaris	17	15	8	7.7	0.705	0.563
Erinaceus europaeus	Martes foina	17	6	4	3.1	0.899	0.358
Erinaceus europaeus	Myodes glareolus	17	19	8	9.8	0.182	0.947
Rattus norvegicus	Crocidura spp.	5	11	0	1.7	0.111	1
Rattus norvegicus	Sciurus vulgaris	5	15	0	2.3	0.0361	1
Rattus norvegicus	Myodes glareolus	5	19	3	2.9	0.722	0.649
Crocidura spp.	Sciurus vulgaris	11	15	6	5	0.867	0.355
Crocidura spp.	Martes foina	11	6	3	2	0.922	0.308
Crocidura spp.	Myodes glareolus	11	19	9	6.3	0.993	0.051
Sciurus vulgaris	Martes foina	15	6	4	2.7	0.947	0.242
Sciurus vulgaris	Myodes glareolus	15	19	9	8.6	0.729	0.539
Martes foina	Myodes glareolus	6	19	4	3.5	0.829	0.490

This study offers insights into the composition, species diversity and evenness of a small mammal community across a gradient of urbanization. The community composition varied between study sites, yet no discernible pattern emerged regarding an increase or decrease in indices of diversity and evenness with impervious surface cover.

Our camera trap study revealed the presence of eight small ground-dwelling mammal species/taxa within the study area, with Apodemus spp. appearing in the majority (74%) of all captured photos. The predominance of Apodemus spp. aligns with their generalist behavior and ability to thrive in diverse habitats, especially A. sylvaticus [35, 53]. Similarly to our results, the probability of occurrence of different Apodemus species (A. agrarius, A. flavicollis, A. sylvaticus) has been found to be unaffected by human population density in Poland, while that of bank voles (M. glareolus) decreased with increasing human population density [35]. Contrary to our expectations and in contrast to other studies [29, 35, 53], we found no decrease in species richness, Shannon diversity index or Pielou’s evenness index with increasing impervious surface cover in any of the three different buffer zones of 100 m, 500 m and 1000 m. This result cannot be explained by a lack of either very urban or rural areas because impervious surface cover of the study sites covered large ranges at all buffer sizes (1000 m buffer: 8.2–71.7%; 500 m buffer: 2.9–76.6%; 100 m buffer: 4.2–89.3%). Moreover, the asymptotic trend observed in the species accumulation curve suggests that the majority of mammal species in our study area have been adequately sampled and additional sampling efforts at additional sites would have resulted in the discovery of very few additional species, if any at all. These results suggest that the small mammal community composition of Münster is relatively stable across the urbanization gradient examined.

The development of Münster into a city commenced in 1850 [54]. The extant small mammal community comprises species that managed to survive the drastic change of a more natural habitat into a high-density human settlement. These species were able to pass the urban filters, potentially via the expression of high phenotypic plasticity, which may have allowed them to adjust to urban conditions [55–57]. Urban areas can offer a greater continuity of natural food resources because urban areas can harbor a high plant diversity. In addition, the ‘urban heat island effect’, where temperatures in urban areas are elevated in comparison to their surrounding rural areas [58], can result in earlier flowering and extended growing seasons [4, 59, 60]. Moreover, in addition to natural resources (e.g., fruit and nut trees), urban habitats provide predictable food resources for wildlife, either directly (i.e. through bird feeders) or unintentionally via accidental feeding of wildlife (i.e. garbage or composts) [61–64]. Cities provide not only predictable food sources, but also reliable water resources and shelter in anthropogenic structures, which might contribute to the maintenance of small mammal populations and could be one explanation for the absence of patterns in species diversity along the urbanization gradient. Furthermore, Münster's long history may have provided wildlife with sufficient time to adapt to the novel urban conditions (e.g., altered dietary quality, human disturbance, and noise, light and chemical pollution), either via phenotypic plasticity or evolutionary change. Observable evolutionary change can occur in as little as two generations [65, 66]. It is also conceivable that differences in species richness and diversity may have existed in the past along the rural-urban gradient in Münster, and that these differences may have disappeared over time due to species adaptation or the displacement of non-adapted species.

The magnitude and the direction of species’ responses to urbanization can vary between cities and can be affected, for example, by housing density and green space availability. For example, a multi-city study showed that consistent decreases in mammal diversity occurred only above average housing densities [11], while another study reported similar or higher mammalian species richness and diversity in developed areas of two large cities compared to wild areas [32]. Here, we focused our study on small mammals, which are often under-represented or not detected at all in camera trapping studies [37]. Across North America, larger-bodied mammal species are more negatively affected by urbanization compared to smaller-bodied species [30]. It is unclear, if the same patterns are present in European mammals. If European smaller-bodied species are also less affected by urbanization than larger-bodied species, this may offer one explanation for the absence of the expected patterns in our data. Moreover, the extent to which wildlife communities use human-modified habitats can vary across and between years, depending on fluctuations in human land use, and changes in resource availability and human activity [67–69]. For example, anthropogenic food sources can reduce starvation risk and positively influence survival of wildlife, especially during the winter [61, 70]. Moreover, the ‘urban heat island effect’, where air temperatures in urban areas are elevated compared to rural surroundings [58], may alleviate some of the thermal challenges [71] and reduce energy expenditure during winter, allowing especially small bodied species, to remain active for prolonged periods in winter [72]. Consequently, studies encompassing multiple seasons and/or years might yield different results.

Species co-occurrence patterns

Our analysis of species co-occurrence patterns revealed predominantly neutral associations among the species. The results showed a trend for a positive association between Crocidura spp. and Myodes glareolus. Both taxa use the same aboveground runways and underground tunnel systems and favor habitats with dense ground cover, thus our finding may be a result of shared habitat requirements [73–75]. Otherwise, positive associations were notably absent, indicating a lack of preferential co-occurrence patterns among the studied species pairs. We observed consistent negative associations between two pairs: Apodemus spp. and Crocidura spp., and Rattus norvegicus and Sciurus vulgaris. These negative associations suggest potential competition or avoidance behaviors. However, the negative associations between both species’ pairs were present together in only 5 out of 30 iterations (17%) when looping through the data. Therefore, it is possible that these results were influenced strongly by patterns recorded in specific gardens and do not reflect general co-occurrence patterns of these species.

One limitation of our study is that we focused on a single urban area, the city of Münster, and a limited set of mammal species (e.g. bats were not included). Future research could expand the geographic scope by studying multiple cities to provide a more comprehensive understanding of urban mammal ecology. Long-term monitoring could further elucidate the mechanisms driving species interactions and community dynamics in response to ongoing urbanization and environmental change.

In conclusion, our study contributes to the growing body of literature on urban ecology by providing empirical insights into the composition, structure, and interactions of small mammal communities in an urban environment.

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and materials

Competing interests

The authors declare no competing interests.

Funding

This research was conducted as part of the CRC TRR 212 (NC3) – Project number 316099922 and 396777092 funded by the German Research Foundation (DFG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work was also supported by University of Münster.

Authors’ contributions

R.R., L.P., and J.P. collected all data. K.H. identified all photos. R.R. and M.D. designed the study and conducted the statistical analyses. R.R. conceptualized the manuscript and wrote the initial draft. All authors (R.R., K.H., L.P., J.P. and M.D.) assisted with drafting and editing the manuscript.

Acknowledgements

We are grateful to the garden owners and Botanical Garden of Münster University for granting us access to their property and for their help with the data collection. We also thank Anna-Maria Molls and Jörg Jäger for their help with camera set-up and collection.

Availability of data and material

All data generated or analyzed during this study are included in this article and its supplementary information files.

Ethics approval

Not applicable.

Supplementary information

Supplementary material 1. Data used for analysis.

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City life does not change a small mammal community composition

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Abstract

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Introduction

Methods

Study sites and camera setup

Photo evaluation

Environmental sampling

Species diversity indices

Statistical analyses

Results

Species co-occurrence patterns

Discussion

Species co-occurrence patterns

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References

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Supplementary Files

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