Sámi traditional ecological knowledge as a guide to science: snow, ice and reindeer pasture facing climate change
2011 (English)In: Polar Record, ISSN 0032-2474, E-ISSN 1475-3057, Vol. 47, no 3, 202-217 p.Article in journal (Refereed) Published
Scientific studies of challenges of climate change could be improved by including other sources of knowledge, such as traditional ecological knowledge (TEK), in this case relating to the Sámi. This study focuses on local variations in snow and ice conditions, effects of the first durable snow, and long term changes in snow and ice conditions as pre-requisites for understanding potential future changes. Firstly, we characterised snow types and profiles based on Sámi categories and measured their density and hardness. Regression analysis showed that density can explain much of the variation in hardness, while snow depth was not significantly correlated with hardness. Secondly, we found that whether it is dry/cold or warm/wet around the fall of the first durable snow is, according to Sámi reindeer herders, crucial information for forecasting winter grazing conditions, but this has had limited focus within science. Thirdly, elderly herders’ observations of changes in snow and ice conditions by ‘reading nature’ can aid reinterpretation of meteorological data by introducing researchers to alternative perspectives. In conclusion we found remarkable agreement between scientific measurements and Sámi terminology.We also learnt that TEK/science cooperation has much potential for climate change studies, though time and resources are needed to bridge the gap between knowledge systems. In particular, TEK attention to shifts in nature can be a useful guide for science.
Place, publisher, year, edition, pages
Cambridge University Press , 2011. Vol. 47, no 3, 202-217 p.
Traditional ecological knowledge, TEK, snow, ice, reindeer, climate
Earth and Related Environmental Sciences
IdentifiersURN: urn:nbn:se:uu:diva-157922DOI: 10.1017/S0032247410000434ISI: 000292194200002OAI: oai:DiVA.org:uu-157922DiVA: diva2:437093
ProjectsInterpretation and evalutation of snow and ice from remote sensing using local and scientific expertice