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Measuring diversity from space: a global view of the free and open source rasterdiv R package under a coding perspective

Elisa Thouverai; Matteo Marcantonio; Giovanni Bacaro; Daniele Da Re; Martina Iannacito; Elisa Marchetto; Carlo Ricotta; Clara Tattoni; Saverio Vicario; Duccio Rocchini
Community Ecology · Vol. 22, Issue 1 · pp. 1-11 · 2021

Abstract

The variation of species diversity over space and time has been widely recognised as a key challenge in ecology. However, measuring species diversity over large areas might be difficult for logistic reasons related to both time and cost savings for sampling, as well as accessibility of remote ecosystems. In this paper, we present a new package - - to calculate diversity indices based on remotely sensed data, by discussing the theory behind the developed algorithms. Obviously, measures of diversity from space should not be viewed as a replacement of in situ data on biological diversity, but they are rather complementary to existing data and approaches. In practice, they integrate available information of Earth surface properties, including aspects of functional (structural, biophysical and biochemical), taxonomic, phylogenetic and genetic diversity. Making use of the package can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.

Bibliographic Information

JournalCommunity Ecology
PublisherSpringer
Publication Date2021-04-01
Publication Year2021
Volume22
Issue1
Pages1-11
Document TypeJournal Article
Print ISSN1585-8553
eISSN1588-2756
DOI10.1007/s42974-021-00042-x

Access Information

NARA Access Coverage2000-01-01~Current
Journal Homepagehttps://www.springer.com/journal/42974
Publisher PageOpen Publisher Page
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