Plant spectral diversity from high-resolution multispectral imagery detects functional diversity patterns in coastal dune communities

QuestionRemote sensing is a fundamental tool to monitor biodiversity and spectral diversity may represent a proxy for different biodiversity facets such as taxonomic (TD) and functional diversity (FD). We used fine-resolution multispectral imagery to explore spectral diversity (SD) patterns across spatial scales (i.e., plot, transect, area), and assess SD relationships with TD and FD along an environmental gradient.LocationCoastal sand dune, Viareggio, Italy ("Migliarino-San Rossore-Massaciuccoli" Regional Park, 43 degrees 83 ' N, 10 degrees 25 ' E).MethodsWe measured TD as species richness, while SD and FD were computed using probability density functions based on pixel and species position in multivariate spaces. We compared SD and FD patterns in space occupation, and we tested whether these patterns are coordinated along the sea-inland gradient. We also assessed univariate relationships between SD and biodiversity facets, and we tested how these facets were partitioned across scales.ResultsWe found a strong correspondence between functional and spectral patterns in space occupation and along the environmental gradient, with a lack of significance when considering TD. However, TD and SD showed higher variation at broader scale while most FD variation occurred at plot level.ConclusionBy measuring FD and SD with a common methodological framework, we demonstrate that SD approximates functional patterns in plant communities. Moreover, we show that SD retrieved using high-resolution images can capture different aspects of FD, and that the occupation of the spectral space is analogous to the occupation of the functional space. In this study, we estimated spectral and functional diversity in a common framework encompassing all their multivariate components. Our findings indicate that spectral diversity accurately captures the functional structure of plant communities and approximates species patterns in the functional space. Furthermore, we showed the efficient approximation of functional diversity patterns by spectral diversity across spatial scales and along ecological gradients.image