Remote Sensing in Ecology and Conservation (Jun 2024)

Assessing plant trait diversity as an indicators of species α‐ and β‐diversity in a subalpine grassland of the Italian Alps

  • Hafiz Ali Imran,
  • Karolina Sakowska,
  • Damiano Gianelle,
  • Duccio Rocchini,
  • Michele Dalponte,
  • Michele Scotton,
  • Loris Vescovo

DOI
https://doi.org/10.1002/rse2.370
Journal volume & issue
Vol. 10, no. 3
pp. 328 – 342

Abstract

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Abstract As the need for ecosystem biodiversity assessment increases within the climate crisis framework, more and more studies using spectral variation hypothesis (SVH) are proposed to assess biodiversity at various scales. The SVH implies optical diversity (also called spectral diversity) is driven by light absorption dynamics associated with plant traits (PTs) variability (which is an indicator of functional diversity) which is, in turn, determined by biodiversity. In this study, we examined the relationship between PTs variability, optical diversity and α‐ and β‐diversity at different taxonomic ranks at the Monte Bondone grasslands, Trentino province, Italy. The results of the study showed that the PTs variability, at the α scale, was not correlated with biodiversity. On the other hand, the results observed at the community scale (β‐diversity) showed that the variation of some of the investigated biochemical and biophysical PTs was associated with the β‐diversity. We used the Mantel test to analyse the relationship between the PTs variability and species β‐diversity. The results showed a correlation coefficient of up to 0.50 between PTs variability and species β‐diversity. For higher taxonomic ranks such as family and functional groups, a slightly higher Spearman's correlation coefficient of up to 0.64 and 0.61 was observed, respectively. The SVH approach was also tested to estimate β‐diversity and we found that spectral diversity calculated by Spectral Angle Mapper showed to be a better proxy of biodiversity in the same ecosystem where the spectral diversity approach failed to estimate α‐diversity. These findings suggest that optical and PTs diversity approaches can be used to predict species diversity in the grasslands ecosystem where the species turnover is high.

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