How did dispersal and habitat changes over 20,000 years shape the genetic structure of alpine species? We investigated by simulating the spatial dynamics of populations since the glaciation in combination with a large genomic data set on northern chamois.
Above: Northern chamois (Rupicapra rupicapra) inhabit steep terrain slopes. They can escape predators in steep slopes with their outstanding climbing abilities.
Alpine glaciers melted at unprecedent rates this summer, as a striking sign of the profound effects of climate change on alpine ecosystems. The alpine landscape is changing at a fast pace and these modifications may even accelerate over coming decades impacting the suitability for mountain species. Understanding how species reacted to past climate changes and habitat fragmentation is paramount to predicting and mitigating the effects of the current global changes. The dramatic changes since the last glaciation in the Alps (20,000 years ago) offer a particularly well-suited opportunity to study the dispersal and impact of landscape features on population structure.
Most alpine species were forced to live in the periphery of the Alps during the last glaciation. Alike many species, Northern chamois (Rupicapra rupicapra) recolonized the alpine range after the glacial retreat. They were able to colonize high-alpine areas due to their adaption to harsh weather conditions and outstanding climbing abilities. Chamois are not only charismatic mammals, but also well suited to study population genetic structure due to their widespread distribution nowadays throughout the Alps. We were interested in the long-term drivers of the population structure. What are obstacles to the master climbers? How far do they disperse and how did they probably recolonize the Alps?
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Leugger, F., Broquet, T., Karger, D. N., Rioux, D., Buzan, E., Corlatti, L., Crestanello, B., Curt-Grand-Gaudin, N., Hauffe, H. C., Rolečková, B., Šprem, N., Tissot, N., Tissot, S., Valterová, R., Yannic, G.& Pellissier, L. (2022). Dispersal and habitat dynamics shape the genetic structure of the Northern chamois in the Alps. Journal of Biogeography, 49, 1848– 1861. https://doi.org/10.1111/jbi.14363.
To answer those questions, we combined a newly generated genomic data set and paleo-environmental reconstructions with process-based modelling of population movements. The genetic data had to be sampled across the entire alpine range, spanning over five different countries. Collecting samples over such a large spatial scale and several countries can be difficult. Thanks to the efforts undertaken by many collaborators – involving interactions with several hunting departments or organizations – we were able to assemble samples for DNA sequencing from the entire massif of the Alps. The subsequent genetic analysis revealed that the chamois fall into two main groups separated by one of the main alpine valleys, the Rhone Valley (CH).
We modelled the species habitat suitability from the last glacial maximum (21ky) to the present before we could simulate dispersal events and population connectivity from the glaciation forwards in time. The habitat suitability models required occurrence data over the entire Alps. Citizen science projects, such as ornitho, collect the observations of thousands of contributors and offer a data synthesis at high resolution. We showed with the habitat suitability models that chamois inhabited areas not only at the periphery of the massif, but also far from the Alps during the glaciation which matched evidence from the fossil records. Maps of suitable habitats from the last glaciation to the present allowed to simulate dispersal and population connectivity over time. We explored a wide range of dispersal and landscape features and their effect on population connectivity with over 1,000 simulations.
Northern chamois reside nowadays in most parts of the Alps, the Jura mountains, Black Forest and Vosges (bluish background). Each pie chart represents a sample and is colored according to the ancestry proportions from the four populations. The eastern population expands nearly over half of the Alps and is closely related to the population living in Switzerland (central Alps). Interestingly, the Rhone valley in Switzerland forms the barrier between two populations.
Compared to the complex structure of the genomic data based on thousands of small genomic markers, the representation of genetic distances in the model was simple: we tracked population connectivity over time. We used a combined metric of the group assignment and Procrustes analysis to have a robust comparison combining the strengths of both metrics.
The likeness of the simulations tracking population connectivity since the last glaciation and the empirical data was striking! Our analysis revealed that the dispersal distance of chamois is short, i.e. most chamois’ home range is very close to their place of birth. Additionally, large valleys or rivers form considerable obstacles for the master climbers which results in a strong genetic structure across the Alps. Chamois likely avoid them, as they rely on steep terrain slopes to shelter from predators such as wolves and lynx. These results indicate that isolated populations of chamois might be at risk, e.g., if they are intensively hunted and/or additional anthropogenic barriers are built.
We showed how combining process-based modelling and genomics can inform about the formation of population structure in complex and dynamic landscapes: limited dispersal ability and habitat dynamics determined the genetic structure of Northern chamois. Applying this workflow to various taxa and ecosystems could enhance our understanding of the intraspecific diversity dynamics. Additionally, the models could be used to predict future changes, due to land use or climate change, and provide valuable information for conservation measures. For example, we could simulate to which extent anthropogenic barriers or strongly increasing temperatures decrease population connectivity and therefore intraspecific diversity. We hope that our study stimulates further projects combining modelling with genomic data to investigate species-landscape interactions.
Flurin Leugger & Loïc Pellissier
Ecosystems and Landscape Evolution, WSL / ETH Zürich
Close-up of a two-year-old Northern chamois.