In an article published recently in the latest issue of Molecular Ecology, researchers from Researchers from the Leibniz Institute for Zoo and Wildlife Research and the Luxembourg National Museum of Natural History investigated differences between urban and rural red fox populations. They found that physical barriers in both habitats, such as a river or road, limited fox movement, and also that human activities influenced where foxes moved. This is important because it means that the interaction between human activity and other structures on the landscape may negatively alter the fox populations. For more information, please see the full article and the interview with lead author Sophia Kimmig below. 

What led to your interest in this topic / what was the motivation for this study? Human population growth and land use are altering ecosystems worldwide and although continuing urbanization results in dramatic environmental changes, some species seem to cope well with the anthropogenic pressure. Foxes are distributed over the entire metropolitan area of Berlin, therefore it is usually assumed that they cope well with human presence. However, city life can affect key aspects of wildlife ecology and have substantial impact on the movement ecology and dispersal ability of populations. Dispersal in urban areas may be influenced by physical barriers, but also by behavioural barriers that we cannot directly see. Thus species that are physically capable of crossing the urban matrix may nevertheless face behavioural barriers due to avoidance of man-made objects (with their artificial structure, scents etc.) as well as human presence per se. We therefore wanted to understand how the landscape influences gene flow patterns in red foxes across the urban-rural matrix.

What difficulties did you run into along the way? With an increasing number of population genetic clustering approaches and R packages that differ in their precise working mechanisms, it becomes more challenging to interpret diverging results and recognize biological patterns. Further, the promising and fascinating possibilities of modelling gene flow through the landscape also come with uncertainties in how to deal with certain circumstances or type of data. For example, we discuss the issue of dealing with overlapping landscape features in the studied environment i.e. linear landscape elements (such as roads or rivers) that cross a surface structured landscape element (e.g. a forest or park). Especially in urban areas, the habitat has such a high level of complexity that you could easily spend years modelling and testing different land use layers.

What is the biggest or most surprising innovation highlighted in this study? Regarding the fox in the Berlin Metropolitan area: Foxes are quite common in urban areas, so we presumed that there would be few dispersal barriers in the urban environment. Our results have nevertheless shown that foxes disperse preferentially along linear landscape elements such as motorways and railway lines despite the inherent mortality risk. We interpreted this to mean that even urban foxes avoid the presence of humans if possible. 
Regarding a broader, biological perspective: Although we have to further improve our methods (for our study, for example, by including data on population densities, road traffic or other proxies of human presence and activity), it is fascinating that molecular genetic methods may enable us to answer more questions in behavioural ecology in the future. 

Moving forward, what are the next steps in this area of research? Now that we have familiarised ourselves with the landscape genetic techniques, we are looking forward to applying the approaches to a broad range of taxa to better understand how animals move through the landscape. This is not just of academic interest, but may help to identify and protect dispersal corridors for endangered species in a scientifically robust way.
For the Berlin foxes we are going to analyse data from a radio tracking study and research their movement patterns and space use – it will be interesting to compare those results with the ones from landscape genetics. We are looking forward to hopefully adding some more pieces to the puzzle of the city as a wildlife habitat.

What would your message be for students about to start developing or using novel techniques in Molecular Ecology? From a beginners’ perspective: For our project, we greatly benefitted from the exchange with other researchers working in this field. For example, we contacted William Peterman, who created the ResistanceGA package that we used for our landscape resistance analysis, with some methodological questions and he provided very helpful advice. I would therefore recommend getting in touch with people who work with the same methods and discussing your ideas and obstacles. Also, our work greatly benefitted from the thorough review process that it underwent. Although the requested changes and suggestions sometimes may come with a lot of re-thinking and -working effort and we usually do not always agree with every single given comment, it is crucial to take constructive criticism to improve our scientific work.

What have you learned about methods and resources development over the course of this project? Molecular genetic methods and the inherent potential to study complex ecological contexts have been changing a lot in the last decades. This is a field of frequent on-going development and improvement. Especially regarding the analytical methods, for an ecologist it is difficult to keep on track with all the latest approaches. Also, due to big data involved in the landscape analysis and the resulting time for computational analysis, the computational effort for a model becomes a real issue in landscape genetics. It is really a pity when more thorough analysis are theoretically possible and even free data is available but the analysis can just not be conducted in a feasible amount of time.

Describe the significance of this research for the general scientific community in one sentence. Assessing the impact of the habitat on (urban) wildlife beyond the physical properties of the landscape may help us to more deeply understand dispersal, behaviour and population genetic structure of populations.

Describe the significance of this research for your scientific community in one sentence. Methodological advancement due to more in depth comparisons of different genetic measures used in resistance modelling.

Kimmig ES, Behinde J, Brandt M, Schleimer A, Kramer-Schadt S, Hofer H, Börner K, Schulze C, Wittstatt U, Heddergott M, Halczok T, Staubach C, Frantz A. 2020. Beyond the landscape: resistance modeling infers physical and behavioral gene flow barriers to a mobile carnivore across a metropolitan area. Molecular Ecology. https://doi.org/10.1111/mec.15345.