Global human land alteration poses an immense threat to natural ecosystems with consequences to wildlife populations on numerous scales. Land is altered for agricultural supply of the human population, the gain of resources, and industrial production as well as for providing living space. The sprawl of urban agglomerations around the world creates novel ecosystems for wildlife species that remained in natural remnants enclosed by urbanization processes or actively colonized urban areas. These novel habitats provide high food abundances and diverse breeding opportunities but are also characterized by a high degree of human-induced disturbance, land- and light pollution and habitat fragmentation. The capacity to adjust to these novel environmental conditions depends on the behavioural plasticity or ecological flexibility of species (and individuals), or on rapid evolutionary processes that provide the genetic base for adaptive trait changes. The red fox (Vulpes vulpes) as a generalist predator of medium size and a broad geographic distribution, managed to successfully inhabit cities around the globe. Due to their ubiquitous presence in human dominated landscapes, ranging from agricultural land to densely built-up areas, it is commonly assumed that red foxes cope well with human presence. Although the fox’s inherent behavioural plasticity obviously enables the species to populate those areas, living in close proximity to humans may come with some downsides too. High mortality rates, low average life spans and elusive behaviours indicate a trade-off for this naturally shy generalist that is poorly addressed. Do we thus draw wrong conclusions about the actual boundaries of the behavioural plasticity of red foxes, based on shallow observations?
To address this issue we (i) looked at genetic patterns on the population level by analysing red fox samples across a rural to urban continuum. We investigated how the urban matrix affected gene flow in foxes and how the urban environment potentially shaped the red fox population genetics beyond the effects of single landscape elements. We then (ii) researched space use of foxes on an individual level by radio-collaring individuals across the Berlin area. We examined how foxes adjust their habitat use within the city depending on landscape - including manmade structures such as built-up areas and traffic infrastructure - as well as on human presence and activity.
The results of the first chapter revealed that gene flow between urban and rural fox population of Berlin and Brandenburg was limited, resulting in two genetically separable populations. Landscape did effect gene flow through the urban matrix to a certain extent but seemed to play a minor role for fox dispersal. For instance, while built-up areas had only weak impeding effects on gene flow despite their high degree of urbanization, urban green spaces like city parks and forests did not serve as gene flow enhancement either. Foxes avoided crossing the city border and predominantly dispersed along urban transport infrastructure such as larger streets and railways, despite the inherent mortality risk. This indicates that also human-induced fear drives dispersal behaviour in the studied red fox population.
The second chapter reports on movement and space use of the foxes based on the comparison of used to available habitat. The results show that foxes did not avoid built-up areas or high degrees of imperviousness (ground sealing), while high human population densities were avoided. The foxes further did not preferentially select green spaces like public parks or urban forests. Wasteland areas - including verges along railways - and gardens of residential houses were predominantly used by the studied individuals, providing sites inaccessible to humans or with low human presence. Finally avoidance of humans was more distinct during times of human activity. The results pinpoint that the foxes’ space use was partly driven by avoidance behaviour towards humans.
Our study showed that although foxes cope well with the urban landscape as a species, human presence has consequences on a population level and on an individual scale. Human local and temporal activities pushed the foxes into an adjustment of movement patters and their use of the urban habitat. The results also revealed the limits of this adjustment even in a flexible species like the red fox. We hope that our findings enhance the consideration of multiple factors beyond landscape for future studies on the ecology of wildlife.
For studying space use behaviour, we used radio collars that include a tri-axial accelerometer that measures deflections of the unit within the three-dimensional space. As recorded acceleration data hold an understudied potential to analyse animal behaviour using remote tracking, we also included a methodological work into our project (third chapter). We radio collared captive foxes and documented the behaviours they displayed during measurement, to train different machine learning programs in the inference of behaviours from the acceleration data. We showed that neural networks may provide an improved ability for the classification of animal behaviours from acceleration data using machine learning compared to established approaches.
The presence of foxes in urban areas also concerns people. In addition to the possible transmission of diseases, foxes cause damage on private property and in public spaces and induce disturbances (e.g. due to odours or noises). Short fleeing distances and unfamiliar approaches of the animals (in gardens and sometimes even houses) stir up fears in the population, but can also create annoyance and calls for control of the urban fox population. We therefore conducted a representative survey to look more closely into the factors affecting wildlife perception (fourth chapter). We found that attitude towards and risk perception of foxes mainly influenced the participants’ preferences on whether and how to deal with the fox population, while factual knowledge did not influence their positions. Risk perception and attitude mainly depended on education, age, gender and living environment of the participants.