Spectral diversity successfully estimates the α-diversity of biocrust-forming lichens
Blanco-Sacristán, Javier (Università degli Studi di Milano. Laboratorio di Telerilevamento delle Dinamiche Ambientali (Italy))
Panigada, Cinzia (Università degli Studi di Milano. Laboratorio di Telerilevamento delle Dinamiche Ambientali (Italy))
Tagliabue, Giulia (Università degli Studi di Milano. Laboratorio di Telerilevamento delle Dinamiche Ambientali (Italy))
Gentili, Rodolfo (Università degli Studi di Milano. Laboratorio di Telerilevamento delle Dinamiche Ambientali (Italy))
Colombo, Roberto (Università degli Studi di Milano. Laboratorio di Telerilevamento delle Dinamiche Ambientali (Italy))
Ladrón de Guevara, Mónica (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Maestre, Fernando T. (Universitat d'Alacant. Departament d'Ecologia)
Rossini, Micol (Università degli Studi di Milano. Laboratorio di Telerilevamento delle Dinamiche Ambientali (Italy))

Data:	2019
Resum:	Biocrusts, topsoil communities formed by mosses, lichens, liverworts, algae, and cyanobacteria, are a key biotic component of dryland ecosystems worldwide. Experiments carried out with lichen- and moss-dominated biocrusts indicate that climate change may dramatically reduce their cover and diversity. Therefore, the development of reproducible methods to monitor changes in biocrust diversity and abundance across multiple spatio-temporal scales is key for evaluating how climate change may impact biocrust communities and the myriad of ecosystem functions and services that rely on them. In this study, we collected lichen-dominated biocrust samples from a semi-arid ecosystem in central Spain. Their α-diversity was then evaluated using very high spatial resolution hyperspectral images (pixel size of 0. 091 mm) measured in laboratory under controlled conditions. Support vector machines were used to map the biocrust composition. Traditional α-diversity metrics (i. e. , species richness, Shannon's, Simpson's, and Pielou's indices) were calculated using lichen fractional cover data derived from their classifications in the hyperspectral imagery. Spectral diversity was calculated at different wavelength ranges as the coefficient of variation of different regions of the reflectance spectra of lichens and as the standard deviation of the continuum removal algorithm (SD_CR). The accuracy of the classifications of the images obtained was close to 100%. The results showed the best coefficient of determination (r2 = 0. 47) between SD_CR calculated at 680 nm and the α-diversity calculated as the Simpson's index, which includes species richness and their evenness. These findings indicate that this spectral diversity index could be used to track spatio-temporal changes in lichen-dominated biocrust communities. Thus, they are the first step to monitor α-diversity of biocrust-forming lichens at the ecosystem and regional levels, a key task for any program aiming to evaluate changes in biodiversity and associated ecosystem services in drylands.
Ajuts:	European Commission 721995 European Commission 647038
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Biocrusts ; Biological soil crust ; Spectral diversity ; Chlorophyll ; Continuum removal ; Biodiversity ; α-diversity ; Remote sensing ; Support vector machine
Publicat a:	Remote sensing (Basel), Vol. 11, Issue 24 (December 2019) , art. 2942, ISSN 2072-4292

DOI: 10.3390/rs11242942

16 p, 4.2 MB

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