Multidisciplinary representativeness maps across the Arctic
datasetposted on 07.08.2019 by Anna-Maria Virkkala, Abdulhakim M Abdi, Miska Luoto, Daniel Metcalfe
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
We provide detailed maps of potential new terrestrial sampling locations for nine environmental disciplines (Botany, Zoology, Microbiology, Soil Science, Biogeochemistry, Meteorology, Geosciences, Paleosciences, and Geographic Information Systems (GIS) / Remote Sensing (RS) / Modeling) derived with statistical modeling. The resultant high-resolution maps that consider multiple environmental conditions simultaneously help prioritize future research efforts.