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

Thouverai, Elisa;Marcantonio, Matteo;Bacaro, Giovanni;Da Re, Daniele;Rocchini, Duccio;et.al.
(2021) Community Ecology : an interdisciplinary journal reporting progress in community and population studies — Vol. 22, n° 1, p. 1-11 (2021)

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  • Thouverai, ElisaAlma Mater Studiorum University of Bologna
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  • Marcantonio, Matteoorcid-logoUCLouvain
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  • Bacaro, Giovanniorcid-logoUniversity of Trieste
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  • Da Re, Danieleorcid-logoUCLouvain
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  • Rocchini, Duccioorcid-logoAlma Mater Studiorum University of Bologna
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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 R package - rasterdiv - 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 rasterdiv package can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.
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Thouverai, E., Marcantonio, M., Bacaro, G., Da Re, D., Iannacito, M., Marchetto, E., Ricotta, C., Tattoni, C., Vicario, S., & Rocchini, D. (2021). Measuring diversity from space: a global view of the free and open source rasterdiv R package under a coding perspective. Community Ecology : an interdisciplinary journal reporting progress in community and population studies, 22(1), 1-11. https://doi.org/10.1007/s42974-021-00042-x (Original work published 2021)