This podcast provides some deeper insights into our new publication by Solovyeva et al. (2021) dealing with Arctic Geese in the Eastern Russian Arctic. It provides a showcase for the 'New Digital Arctic' as the myriad changes in the Arctic land-, sea- and coastal-scape are unfolding so fast with devastating outcomes (Krupnik and Crowell 2020).

This research shows a more nuanced range and distribution pattern for these two species - Tundra Bean Geese & Greater White-fronted Geese - during moult and brood-rearing than previously known for flyway delineations, nesting and summer range maps etc. This was possible by using Machine Learning and many Open Access GIS data ("Big Data"). Based on the first-time online release of 24 years of field data in very remote areas like rivers of Yakutia, Chaun research station, Chukotka and Northern Kamchatka it presents the best-available public and digital information on the topic, added by GBIF.org data as well as compiled and geo-referenced (Russian) literature data for a good model assessment.

This podcast emphasizes the experience and suggestions for data sharing in polar regions and elsehere, as stated by D. Carlson for the International Polar Year (IPY; Carlson 2011) making open access approaches a best-professional practice, if not already mandatory by many funders, e.g.Huettmann et al. (2011), Huettmann and Ickert-Bod (2017) for examples. An application is provided how it can affect better management and protection, e.g. for Climate Change forecast and conservation (Spiridonov et al. 2012).

This research raises the question why so many data repositories are either empty, locked behind passwords, or underused, and it shows that Open Access and Open Source in 'The Cloud' can provide a generic progress tfor everybody. Here we provide a workflow and baseline across international researchers to achieve such outcomes with ISO-complian metadata to actually understand the data sets, model inference and outcome. 

References and background readings

Carlson, D. A (2011) Lesson in sharing. Nature 469: 293. https://doi.org/10.1038/469293a

Huettmann, F. (ed) (2012) Protection of the Three Poles, Springer Tokyo, Japan, p. 337

Huettmann F, Yu Artukhin, O. Gilg, and G. Humphries (2011) Predictions of 27 Arctic pelagic seabird distributions using public environmental variables, assessed with colony data: a first digital IPY and GBIF open access synthesis platform. Marine Biodiversity 41: 141-179 DOI 10.1007/s12526-011-0083-2

Huettmann F and S. Ickert-Bond (2017). On Open Access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North Arctic Science. http://www. nrcresearchpress.com/toc/as/0/ja

Krupnik I. and A. L. Crowell (2020) Arctic Crashes: People and Animals in the Changing North. Smithsonian Institutional Press. Washington D.C.

Solovyeva D. I. Bysykatova-Harmey. S L. Vartanyan, A. Kondratyev F. Huettmann (2021) Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic. Scientific Reports.https://www.nature.com/articles/s41598-021-01595-7

Spiridonov V., M. Gavrilo, Y. Krasnov, A. Makarov, N. Nikolaeva, L. Sergienko, A. Popov and E. Krasnova (2012). Chapter 8 Toward the New Role of Marine and Coastal Protected Areas in the Arctic: The Russian Case. in F. Huettrmann (ed) Protection of the Three Poles. Springer New York. pp. 171 – 201.