Measuring β-diversity by remote sensing:A challenge for biodiversity monitoring

Rocchini, Duccio, Luque, Sandra, Pettorelli, Nathalie, Bastin, Lucy, Doktor, Daniel, Faedi, Nicolò, Feilhauer, Hannes, Féret, Jean Baptiste, Foody, Giles M., Gavish, Yoni, Godinho, Sergio, Kunin, William E., Lausch, Angela, Leitão, Pedro J., Marcantonio, Matteo, Neteler, Markus, Ricotta, Carlo, Schmidtlein, Sebastian, Vihervaara, Petteri, Wegmann, Martin and Nagendra, Harini (2018). Measuring β-diversity by remote sensing:A challenge for biodiversity monitoring. Methods in Ecology and Evolution, 9 (8), pp. 1787-1798.


Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, especially when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this context, airborne or satellite remote sensing allows information to be gathered over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (β-diversity) might add crucial information related to relative abundance of different species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript, we propose novel techniques to measure β-diversity from airborne or satellite remote sensing, mainly based on: (1) multivariate statistical analysis, (2) the spectral species concept, (3) self-organizing feature maps, (4) multidimensional distance matrices, and the (5) Rao's Q diversity. Each of these measures addresses one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating β-diversity from remotely sensed imagery and potentially relating them to species diversity in the field.

Publication DOI:
Divisions: Engineering & Applied Sciences
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Engineering & Applied Sciences > Sustainable environment research group
Engineering & Applied Sciences > Computer Science
Uncontrolled Keywords: Kohonen self-organizing feature maps,Rao's Q diversity index,remote sensing,satellite imagery,sparse generalized dissimilarity model,spectral species concept,β-diversity,Ecology, Evolution, Behavior and Systematics,Ecological Modelling
Full Text Link: http://eprints. ...
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://besjour ... 2041-210X.12941 (Publisher URL)
PURE Output Type: Article
Published Date: 2018-08-06
Accepted Date: 2017-11-11
Authors: Rocchini, Duccio
Luque, Sandra
Pettorelli, Nathalie
Bastin, Lucy ( 0000-0003-1321-0800)
Doktor, Daniel
Faedi, Nicolò
Feilhauer, Hannes
Féret, Jean Baptiste
Foody, Giles M.
Gavish, Yoni
Godinho, Sergio
Kunin, William E.
Lausch, Angela
Leitão, Pedro J.
Marcantonio, Matteo
Neteler, Markus
Ricotta, Carlo
Schmidtlein, Sebastian
Vihervaara, Petteri
Wegmann, Martin
Nagendra, Harini

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