Measuring alpha and beta diversity by field and Remote-Sensing data: a challenge for coastal dunes biodiversity monitoring

Combining field and remotely sensed (RS) data represents a promising approach for an extensive and up-to-date ecosystem assessment. We investigated the potential of the “Spectral Variability Hypothesis” (SVH) in linking field collected and remote sensed data in Mediterranean coastal dunes and explored if spectral diversity provides reliable information to monitor floristic diversity, as well as the consistency of such information in altered ecosystems due to plant invasions. We analyzed alpha diversity and beta diversity of herbaceous coastal vegetation in well-preserved (EUNIS category N14: Mobile coastal sand ridges including embryonic dunes and semi-permanent dunes and N16: Fixed dune grasslands including chamaephytic communities of the inland dunes and annual species-rich communities colonizing dry interdunal depressions) and in invaded Mediterranean coastal dunes with Carpobrotus spp. at the Tyrrhenian coast (Central Italy). We integrated the floristic field data, conformed by 163 random 2 m x 2 m vegetation plots sampled during the growing season (April – May) lately collected (years 2017 – 2020), and the Remote Sensing data derived from PlanetScope images, consisting of four spectral bands (blue, green, red. near infrared) and two spectral indices MSAVI2 (Modified Soil-Adjusted Vegetation Index 2, a proxy of biomass and CI (Coloration Index depicting soil conditions). We explored the relationship among alpha field floristic diversity (Species Richness, Shannon index, Inverse Simpson index) and remote sensed spectral variability (Distance from the Spectral Centroid index) through linear regressions. For beta diversity, we implemented a Distance Decay Model (DDM) relating floristic pairwise (Jaccard similarity index, Bray-Curtis similarity index) and spectral pairwise (Euclidean Distance) measures. Among the analyzed alpha diversity indices, Species Richness scored the highest goodness-of-fit (R2= 0.383), followed by Inverse Simpson index (R2 = 0.342) and Shannon index (R2 = 0.322). In all regressions, the regression line of the N14 EUNIS category resulted below the other categories. The regression line of the N16 EUNIS category and of the invaded areas showed similar trends. As for DDM, we found negative and significant relationships in all categories between Euclidean spectral distance and the two floristic similarities analyzed. The DDM based on Bray-Curtis floristic similarity showed most intense decay rates compared with the other DDM. We provided a first assessment of the relationship between floristic and spectral RS diversity in Mediterranean coastal dune habitats (i.e., natural or invaded). SVH provided evidence about the potential of RS for estimating diversity in complex and dynamic landscapes. The observed relationship between spectral and floristic diversity in natural and invaded dune vegetation is certainly a good applied outcome of the SVH suggesting its potential as an early warning system for preventing biodiversity loss.