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.

Rocchini, D.; Luque, S.; Pettorelli, N.; Bastin, L.; Doktor, D.; Faedi, N.; Feilhauer, H.; Féret, J.B.; Foody, G.M.; Gavish, Y.; Godinho, S.; Kunin, W.E.; Lausch, A.; Leitão, P.J.; Marcantonio, M.; Neteler, M.; Ricotta, C.; Schmidtlein, S.; Vihervaara, P.; Wegmann, M.; Nagendra, H. (2018). Measuring β-diversity by remote sensing: a challenge for biodiversity monitoring. METHODS IN ECOLOGY AND EVOLUTION, 9 (8): 1787-1798. doi: 10.1111/2041-210X.12941 handle: http://hdl.handle.net/10449/54456

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

Rocchini, D.
Primo
;
Faedi, N.;
2018-01-01

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.
Beta-diversity
Kohonen self-organizing feature maps
Rao's Q diversity index
Remote sensing
Satellite imagery
Sparse generalized dissimilarity model
Spectral species concept
Settore BIO/03 - BOTANICA AMBIENTALE E APPLICATA
2018
Rocchini, D.; Luque, S.; Pettorelli, N.; Bastin, L.; Doktor, D.; Faedi, N.; Feilhauer, H.; Féret, J.B.; Foody, G.M.; Gavish, Y.; Godinho, S.; Kunin, W.E.; Lausch, A.; Leitão, P.J.; Marcantonio, M.; Neteler, M.; Ricotta, C.; Schmidtlein, S.; Vihervaara, P.; Wegmann, M.; Nagendra, H. (2018). Measuring β-diversity by remote sensing: a challenge for biodiversity monitoring. METHODS IN ECOLOGY AND EVOLUTION, 9 (8): 1787-1798. doi: 10.1111/2041-210X.12941 handle: http://hdl.handle.net/10449/54456
File in questo prodotto:
File Dimensione Formato  
MEE_2018.pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.78 MB
Formato Adobe PDF
1.78 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10449/54456
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 90
  • ???jsp.display-item.citation.isi??? 74
social impact