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

Roccini, Duccio and Luque, Sandra and Pettorelli, Nathalie and Bastin, Lucy and Doktor, Daniel and Faedi, Nicolò and Feilhauer, Hannes and Feret, Jean-Baptist and Foody, Giles M. and Gavish, Yoni and Godinho, Sergio and Kunin, William and Lausch, Angela and Leitao, P.J. and Marcantonio, Matteo and Neteler, Markus and Ricotta, Carlo and Schmidtlein, Sebastian and Vihervaara, Petteri and Wegmann, Martin and Nagendra, Harini (2017) Measuring ß-diversity by remote sensing: A challenge for biodiversity monitoring. Methods in Ecology and Evolution, 9 (8), pp. 1787-1798. Wiley. DOI: 10.1111/2041-210X.12941 ISSN 2041-210X

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Official URL: https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.12941

Abstract

1. 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. 2. 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. 3. 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.

Item URL in elib:https://elib.dlr.de/124486/
Document Type:Article
Title:Measuring ß-diversity by remote sensing: A challenge for biodiversity monitoring
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Roccini, DuccioUNSPECIFIEDUNSPECIFIED
Luque, SandraUNSPECIFIEDUNSPECIFIED
Pettorelli, NathalieInstitute of Zoology, Zoological Society of London UKUNSPECIFIED
Bastin, LucyUNSPECIFIEDUNSPECIFIED
Doktor, DanielUFZUNSPECIFIED
Faedi, NicolòUNSPECIFIEDUNSPECIFIED
Feilhauer, Hanneshannes.feilhauer (at) fau.deUNSPECIFIED
Feret, Jean-BaptistUNSPECIFIEDUNSPECIFIED
Foody, Giles M.UNSPECIFIEDUNSPECIFIED
Gavish, YoniUNSPECIFIEDUNSPECIFIED
Godinho, SergioUNSPECIFIEDUNSPECIFIED
Kunin, WilliamUNSPECIFIEDUNSPECIFIED
Lausch, AngelaUFZ LeipzigUNSPECIFIED
Leitao, P.J.Humboldt Universität zu Berlin, Museum für Naturkunde, Abteilung Forschung, Bereich Mineralogie, Berlin, GermanyUNSPECIFIED
Marcantonio, MatteoUNSPECIFIEDUNSPECIFIED
Neteler, Markusneteler (at) mundialis.deUNSPECIFIED
Ricotta, CarloUNSPECIFIEDUNSPECIFIED
Schmidtlein, Sebastianschmidtlein (at) kit.eduUNSPECIFIED
Vihervaara, PetteriUNSPECIFIEDUNSPECIFIED
Wegmann, Martinmartin.wegmann (at) uni-wuerzburg.deUNSPECIFIED
Nagendra, HariniUNSPECIFIEDUNSPECIFIED
Date:August 2017
Journal or Publication Title:Methods in Ecology and Evolution
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:9
DOI :10.1111/2041-210X.12941
Page Range:pp. 1787-1798
Publisher:Wiley
ISSN:2041-210X
Status:Published
Keywords:β-diversity, Kohonen self-organizing feature maps, Rao's Q diversity index, remote sensing, satellite imagery, sparse generalized dissimilarity model, spectral species concept
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Wöhrl, Monika
Deposited On:06 Dec 2018 13:38
Last Modified:06 Dec 2018 13:38

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