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

被引:17
作者
Blanco-Sacristan, Javier [1 ]
Panigada, Cinzia [1 ]
Tagliabue, Giulia [1 ]
Gentili, Rodolfo [1 ]
Colombo, Roberto [1 ]
Ladron de Guevara, Monica [2 ,3 ]
Maestre, Fernando T. [4 ]
Rossini, Micol [1 ]
机构
[1] Univ Milano Bicocca, Remote Sensing Environm Dynam Lab, I-20126 Milan, Italy
[2] Univ Rey Juan Carlos, Mostoles 28933, Spain
[3] CREAF CSIC UAB, Ctr Ecol Res & Forestry Applicat, Barcelona 08193, Spain
[4] Univ Alicante, Dept Ecol, Alicante 03690, Spain
基金
欧洲研究理事会; 欧盟地平线“2020”;
关键词
biocrusts; biological soil crust; spectral diversity; chlorophyll; continuum removal; biodiversity; alpha-diversity; support vector machine; remote sensing; BIOLOGICAL SOIL CRUSTS; REFLECTANCE SPECTRA; SPECIES-DIVERSITY; NATIONAL-PARK; BIODIVERSITY; CYANOBACTERIA; SPECTROSCOPY; RICHNESS; INDEX; AREA;
D O I
10.3390/rs11242942
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 alpha-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 alpha-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 (r(2) = 0.47) between SD_CR calculated at 680 nm and the alpha-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 alpha-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.
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页数:16
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共 77 条
  • [1] Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows
    Aasen, Helge
    Honkavaara, Eija
    Lucieer, Arko
    Zarco-Tejada, Pablo J.
    [J]. REMOTE SENSING, 2018, 10 (07)
  • [2] Lightweight unmanned aerial vehicles will revolutionize spatial ecology
    Anderson, Karen
    Gaston, Kevin J.
    [J]. FRONTIERS IN ECOLOGY AND THE ENVIRONMENT, 2013, 11 (03) : 138 - 146
  • [3] Correlating species and spectral diversities using hyperspectral remote sensing in early-successional fields
    Aneece, Itiya P.
    Epstein, Howard
    Lerdau, Manuel
    [J]. ECOLOGY AND EVOLUTION, 2017, 7 (10): : 3475 - 3488
  • [4] Belnap J., 2003, BIOL SOIL CRUSTS STR, P150
  • [5] Diversity and Patch-Size Distributions of Biological Soil Crusts Regulate Dryland Ecosystem Multifunctionality
    Bowker, Matthew A.
    Maestre, Fernando T.
    Mau, Rebecca L.
    [J]. ECOSYSTEMS, 2013, 16 (06) : 923 - 933
  • [6] Hydrology in a patterned landscape is co-engineered by soil-disturbing animals and biological crusts
    Bowker, Matthew A.
    Eldridge, David J.
    Val, James
    Soliveres, Santiago
    [J]. SOIL BIOLOGY & BIOCHEMISTRY, 2013, 61 : 14 - 22
  • [7] Functional profiles reveal unique ecological roles of various biological soil crust organisms
    Bowker, Matthew A.
    Mau, Rebecca L.
    Maestre, Fernando T.
    Escolar, Cristina
    Castillo-Monroy, Andrea P.
    [J]. FUNCTIONAL ECOLOGY, 2011, 25 (04) : 787 - 795
  • [8] Biological crusts as a model system for examining the biodiversity-ecosystem function relationship in soils
    Bowker, Matthew A.
    Maestre, Fernando T.
    Escolar, Cristina
    [J]. SOIL BIOLOGY & BIOCHEMISTRY, 2010, 42 (03) : 405 - 417
  • [9] The use of the area under the roc curve in the evaluation of machine learning algorithms
    Bradley, AP
    [J]. PATTERN RECOGNITION, 1997, 30 (07) : 1145 - 1159
  • [10] Diversity of biocrust-forming cyanobacteria in a semiarid gypsiferous site from Central Spain
    Cano-Diaz, Concha
    Mateo, Pilar
    Angeles Munoz-Martin, M.
    Maestre, Fernando T.
    [J]. JOURNAL OF ARID ENVIRONMENTS, 2018, 151 : 83 - 89