Journal cover Journal topic
Proceedings of the ICA
Journal topic
Volume 1
Proc. Int. Cartogr. Assoc., 1, 24, 2018
https://doi.org/10.5194/ica-proc-1-24-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Proc. Int. Cartogr. Assoc., 1, 24, 2018
https://doi.org/10.5194/ica-proc-1-24-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 May 2018

16 May 2018

Recent vegetation phenology variability and wild reindeer migration in Hardangervidda plateau (Norway)

Romain Courault1, Alexiane Franclet2, Kévin Bourrand3, Clélia Bilodeau3, Sonia Saïd4, and Marianne Cohen1 Romain Courault et al.
  • 1Sorbonne-Universités Paris IV, UMR 8185 Espaces, Nature et Culture, Paris, France
  • 2Museum National d’Histoire Naturelle, Pôle Image – Université Paris-Diderot, Paris, France
  • 3Université Paris-Diderot, UMR 7533 Ladyss, Pôle Image – Université Paris-Diderot, France
  • 4Centre national d’Etudes et de la Recherche Appliquée sur la Faune de Montagne et les Cervidés-Sanglier, Office National de la Chasse et de la Faune Sauvage, Le Perray-en-Yvelines, France

Keywords: Raster datasets compiling, biogeography, Rangifer tarandus L., home ranges, kernel densities estimation, ecological habitat, phenology

Abstract. More than others, arctic ecosystems are affected by consequences of global climate changes. The herbivorous plays numerous roles both in Scandinavian natural and cultural landscapes (Forbes et al., 2007). Wild reindeer (Rangifer tarandus L.) herds in Hardangervidda plateau (Norway) constitute one of the isolated populations along Fennoscandia mountain range. The study aims to understand temporal and spatial variability of intra- and inter-annual home ranges extent and geophysical properties. We then characterize phenological variability with Corine Land Cover ecological habitat assessment and bi-monthly NDVI index (MODIS 13Q1, 250m). Thirdly, we test relationships between reindeer’s estimated densities and geophysical factors. All along the study, a Python toolbox (“GRiD”) has been mounted and refined to fit with biogeographical expectancies. The toolbox let user’s choice of inputs and facilitate then the gathering of raster datasets with given spatial extent of clipping and resolution. The grid generation and cells extraction gives one tabular output, allowing then to easily compute complex geostatistical analysis with regular spreadsheets. Results are based on reindeer’s home ranges, associated extent (MODIS tile) and spatial resolution (250m). Spatial mismatch of 0.6% has been found between ecological habitat when comparing raw (100m2) and new dataset (250m2). Inter-annual home ranges analysis describes differences between inter-seasonal migrations (early spring, end of the summer) and calving or capitalizing times. For intra-annual home ranges, significant correlations have been found between reindeer’s estimated densities and both altitudes and phenology. GRiD performance and biogeographical results suggests 1) to enhance geometric accuracy 2) better examine links between estimated densities and NDVI.

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