Next Article in Journal
Improved Faraday Rotation Estimation in Spaceborne PolSAR Data Using Total Variation Denoising
Previous Article in Journal
Spatial and Temporal Variations of Particulate Organic Carbon Sinking Flux in Global Ocean from 2003 to 2018
Open AccessArticle

Spectral Diversity Successfully Estimates the α-Diversity of Biocrust-Forming Lichens

1
Remote Sensing of Environmental Dynamics Lab, University of Milano – Bicocca, 20126 Milan, Italy
2
Universidad Rey Juan Carlos, 28933 Móstoles, Spain
3
Centre for Ecological Research and Forestry Applications, CREAF-CSIC-UAB, 08193 Barcelona, Spain
4
Department of Ecology, University of Alicante, 03690 San Vicente del Raspeig, Alicante, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(24), 2942; https://doi.org/10.3390/rs11242942
Received: 18 September 2019 / Revised: 5 December 2019 / Accepted: 6 December 2019 / Published: 9 December 2019
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. View Full-Text
Keywords: biocrusts; biological soil crust; spectral diversity; chlorophyll; continuum removal; biodiversity; α-diversity; support vector machine; remote sensing biocrusts; biological soil crust; spectral diversity; chlorophyll; continuum removal; biodiversity; α-diversity; support vector machine; remote sensing
Show Figures

Figure 1

MDPI and ACS Style

Blanco-Sacristán, J.; Panigada, C.; Tagliabue, G.; Gentili, R.; Colombo, R.; Ladrón de Guevara, M.; Maestre, F.T.; Rossini, M. Spectral Diversity Successfully Estimates the α-Diversity of Biocrust-Forming Lichens. Remote Sens. 2019, 11, 2942.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop