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Spatiotemporal interactions of a novel mesocarnivore community in an urban environment before and during SARS‐CoV‐2 lockdown

Cite this dataset

Louvrier, Julie et al. (2022). Spatiotemporal interactions of a novel mesocarnivore community in an urban environment before and during SARS‐CoV‐2 lockdown [Dataset]. Dryad.


1. Studying species interactions and niche segregation under human pressure provides important insights into species adaptation, community functioning and ecosystem stability. Due to their high plasticity in behaviour and diet, urban mesocarnivores are ideal species for studying community assembly in novel communities.

2. We analysed the spatial and temporal species interactions of an urban mesocarnivore community composed of the red fox (Vulpes vulpes) and the marten (Martes sp.) as native species, the raccoon (Procyon lotor) as invasive species, and the cat (Felis catus) as a domestic species in combination with human disturbance modulated by the SARS-CoV-2 lockdown effect that happened while the study was conducted.

3. We analysed camera-trap data and applied a joint species distribution model to understand not only the environmental variables influencing the detection of mesocarnivores and their use intensity of environmental features but also the species’ co-occurrences while accounting for environmental variables. We then assessed whether they displayed temporal niche partitioning based on activity analyses, and finally analysed at a smaller temporal scale the time of delay after the detection of another focal species.

4. We found that species were more often detected and displayed a higher use intensity in gardens during the SARS-CoV-2 lockdown period, while showing a shorter temporal delay during the same period, meaning a high human-induced spatio-temporal overlap. All three wild species spatially co-occurred within the urban area, with a positive response of raccoons to cats in detection and use intensity, whereas foxes showed a negative trend towards cats. When assessing the temporal partitioning, we found that all wild species showed overlapping nocturnal activities. All species displayed temporal segregation based on temporal delay. According to the temporal delay analyses, cats were the species avoided the most by all wild species. To conclude, we found that although the wild species were positively associated in space, the avoidance occurred at a smaller temporal scale, and human pressure in addition led to high spatio-temporal overlap.

5. Our study sheds light to the complex patterns underlying the interactions in a mesocarnivore community both spatially and temporally, and the exacerbated effect of human pressure on community dynamics.


Data collection

The camera trap study of urban mammals ( is one of the scientific projects conducted by citizen scientists within the knowledge transfer project WTimpact ( We divided the area of Berlin into a regular grid of 287 2 x 2 km and accepted around 200 Berlin citizens per sampling phase with private gardens (either adjunct to their residential area or within an allotment), trying to get at least one participant per each 2 x 2 km grid per sampling phase to ensure spatial independence of the data. For each new sampling phase, we selected new citizen scientists while respecting this spatial grid. The camera traps took three consecutive pictures when triggered. We repeated this study for five sampling phases: first; October 7th - November 4th 2018, second; April 1st - April 28th 2019, third; September 30th - October 27th 2019, fourth; from March 30th - April 26th 2020 and fifth; September 28th - October 26th 2020.

The mesocarnivore community was composed of the native red fox (Vulpes vulpes) and native martens (Martes foina and Martes martes), the invasive raccoon (Procyon lotor) and the feral/domestic cat (Felis catus), directly associated with human activities. We excluded badgers (Meles meles) as their presence was rare. 

Species’ spatial analyses

We first checked for spatial overlap of mesocarnivore species by modelling mesocarnivore community assemblage in response to environmental covariates as well as the species associations using Joint Species Distribution Models (JSDM) in a hierarchical Bayesian framework using the R package Hmsc. JSDMs are a multivariate method that analyse the response of multiple species to environmental drivers and allow to assess species associations in the residual variance after accounting for the environmental effects. We analysed the urban mesocarnivore community spatial patterns using three complementary approaches: (i) a binary detection-non detection model (‘detection’ hereafter) based on the detection of each species at least once at a camera trap location during a sampling phase, (ii) a relative use intensity model (‘use intensity’ hereafter) based on the number of independent pictures (i.e. filtered with a time difference of 30 minutes) of each species at a camera-trap location during each sampling phase, and (iii) a nocturnality model (‘nocturnality’ hereafter) based on the proportion of independent pictures taken at night over the total number of independent pictures taken at a camera-trap location, per species and sampling phase. Only for the nocturnality model did we restrict the data set to the night time between 6 pm and 6 am, corresponding to when wild species were mostly active, according to the activity pattern analyses.

In all three models, we included as fixed effects environmental variables related to four main groups: sampling phase, garden characteristics, local urban environmental variables, and the effects of cats. Given that cats are attached to the households they belong to (with the exception of stray cats), we considered them as explanatory variable associated with the environmental conditions. We therefore included cat presence (detection model), cat use intensity (use intensity model) or cat nocturnality (nocturnality model) as explanatory variable in the respective models. Finally, season was included to account for variability of mesocarnivores’ activity within the year, as a binary categorical variable spring/fall. During our study, the epidemic of the Novel Coronavirus SARS-CoV-2 reached Berlin. The Berlin Senate established several contingency measures, resulting in lockdowns during spring and fall 2020. Consequently, human activities drastically decreased during this global shutdown, leading to an increase in wildlife sightings, possibly representing a change of activity patterns of urban wildlife. To account for a possible change in urban mesocarnivores’ space use and activity pattern in Berlin gardens we created a binary variable of the SARS-CoV-2 lockdown, denoted covid/ no_covid, referring to low (covid)/ high (no_covid) human disturbance, respectively. 

Temporal analyses

To test for temporal partitioning between the mesocarnivores of Berlin, we first filtered the pictures of the same species with a minimum time difference of 30 minutes to consider independent presence events. Using the R package camtrapR, we compared the activity patterns of all four species by assessing the temporal overlap D1 between each species. The coefficient ranges from 0 (no overlap) to 1 (complete overlap) and refers to the area under both density curves resulting from the activity patterns of each species.

To test for avoidance or attraction we measured the time interval between the last picture of a species and the first picture of the focal species, hereafter called ‘time of delay’, for gardens where both species were detected. For the temporal analyses, we restricted the pictures to when wild species were mostly active, according to the activity pattern analyses, i.e. between 6 pm and 6 am. The time of delay for the red fox, as focal species, for instance, would be the time difference between the last picture of a raccoon, a cat or a marten, and the first picture of a fox. In our study we then considered that the focal species would avoid another species if the time of delay was significantly greater than for its own species. In this case, we also analysed the time of delay of cats as a response variable, in contrast to the spatial analyses. Finally, to account for differences of probability of presences in gardens, we ran pair-wise regression of time of delay: we restrained the data to gardens where only the two species occurred and ran a similar regression with only one variable; the species after which the focal species was detected.


Federal Ministry of Education and Research, Award: 01IO1725

Federal Ministry of Education and Research, Award: 01LC1501

German Academic Exchange Service, Award: 57423756