Species distribution modeling and remote sensing
Understanding the past and present distribution of species is important for many applications, including predictions of future biodiversity patterns and the development of sustainable management and conservation strategies. Species occurrence is commonly obtained from field data (e.g., collections, surveys, checklists, expert range maps) and increasingly provided by remote sensing. Species distribution models (SDMs) in turn relate occurrence data to spatial variables (e.g., climate, topography, land use).
Incorporating spatial information in SDMs raises a number of methodological issues. These issues are associated with the type of spatial variable (e.g., climate, topography, land use), their quality and associated error and uncertainties, their typical process length, and their context of use; with the quality and spatio-temporal resolution of the species data; and with the context in which SDMs are applied. This working group aims at exploring these challenges.
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|Article: Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models||Completed||Christophe Randin|
|Article: Climate data for ecological predictions in mountains*
* preliminary title
||University of Lausanne & Jardin Flore-Alp, Switzerland||GMBA Network|
|Nigel Yoccoz||The Arctic University of Tromsoe, Norway||GMBA SSC|
|Walter Jetz||Yale University, United States||GMBA SSC
|Xuefei Yang||Chinese Academy of Sciences, Kunming Institute of Botany, China|| GMBA SSC
|| GMBA office
Informing Species Distribution Models and Essential Biodiversity Variables using Remote Sensing
University of Zurich (Irchel Campus), Switzerland, 05-09.02.2018