Reindeer are hihgly sensitive to human development.

The cumulative impact of human activities causes habitat loss and fragmentation. As a consequence of the industrial revolution, the historically continuous ranges were fragmented into 24 isolated sub-populations, and virtually all major migration routes are now lost.

The work presented here results from decades of collaborations among reindeer experts, spatial ecologists, network scientists, land managers and stakeholders. We develop theories and approaches to quantify the cumulative impact of human activities and guide sustainable land planning, by producing high-resolution statistical maps, and by testing scenarios of changes in land use and climate

In a nutshell: where do these maps come from?

GPS tracking data

Millions of GPS position for more than 500 wild reindeer were modelled together with environmental data to understand which areas they need, how do they move and how do they respond to disturbance & infrastructure

Local knowledge

Local knowledge has been used to improve data on human activities in areas partnering the project. This is important and should be extended to all areas, to increase relevance for local managment

Environmental data

Data describing infrastructure, human activities, land cover, vegetation, climate and topography were modelled to quantify the cumulative effect of anthropogenic activities

Software & algorithms

New algorithms (Randomized Shortest Path), software (ConScape), R libraries (OneImpact) & models were developed to produce Nation-wide, high resolution maps quantifyig cumulative impacts, suitable areas, funcional areas, barriers & movement corridors

In a nutshell: where do these maps come from?

Is it possible to extend the approach to other species and ecosystems, using GPS data or otehr types of data? Yes, we apply this same framework and software to create connectivity maps for many species of mammals (so far: moose, red deer), insects (solitary bees), trees (14 species) and ecosystems (e.g. temperate deciduous forests. Connectivity is modelled with respect to individual movements - and in the case of trees with respect to range shift due to climatic changes. Take a look here ConnectivityMaps.nina.no

Acknowledgements

The analytical maps, theoretical frameworks and methodological approaches presented are the result of a decade of developments within several large projects supported by the Research Council of Norway, starting first and foremost with RenewableReindeer, and continuing with OneImpact and ProdChange. These projects built upon a series of local monitoring projects supported by a countless range of stakeholders, local experts, funding sources, and industries that provided essential reindeer GPS data, knowledge and expertise on reindeer and their areas. Last but not least, these innovations would not have been possible without a series of national and international collaborations with lead researchers in ecology, network- and computer science, including the work of several MSc students, PhD students and PostDocs.

It is challenging to name all funding sources and direct/indirect supporters through the years, but we can try: in addition to the Norwegian institute for Nature Research NINA and the Research Council of Norway, the main contriubtors include the Norwegian Environment Agency NVE, The Norwegian Water Resource and Energy Directorate, the Norwegian Wild Reindeer Centre, Wild Reindeer Council, Siri Bøthun naturforvaltning, the hydropower company SiraKvina, the Norwegian Trekking Association DNT, Consortium of stakeholders in Setesdal, Stakeholders boards in Dovre, the University of Louvain (Belgium), University of Alberta (Canada), University of Aalto (Finland), University of Stirling (UK), Basque Centre for Climate Change and many more. It would be impossible to acknolwedge all those that contributed, but a very special thanks goes to Olav Strand, Roy Andersen, Per Jordhøy, Vegard Gundersen, Torkild Tveraa, Audun Stien, Knut Langeland, Marco Særens, Ilkka Kivimaki, John Fryxell, Rebecca Vijou and many many more.