Remote sensing of β‐diversity: Evidence from plant communities in a semi‐natural system

Abstract

AbstractQuestionDo remote sensing signals represent β‐diversity? Does β‐diversity agree with community types?LocationUNESCO Man and the Biosphere Reserve, La Palma, Canary Islands.MethodsWe recorded perennial, vascular plant species abundances in 69 plots (10 m × 10 m) in three pre‐defined community types along an elevational gradient of 2,400 m: succulent scrubland, Pinus canariensis forest and subalpine scrubland. The remote sensing data consists of structural variables from airborne Light Detection and Ranging (LiDAR) and multispectral variables from a time series of Sentinel‐2 (S2) images. Non‐metric Multidimensional Scaling was used to assess β‐diversity between plots. K‐means unsupervised clustering was applied to remote sensing variables to distinguish three community types. We subsequently quantified the explanatory power of S2 and LiDAR variables representing β‐diversity via the Mantel test, variation partitioning and multivariate analysis of variance. We also investigated the sensitivity of results to grain size of remote sensing data (20, 40, 60 m).ResultsThe β‐diversity between the succulent and pine community is high, whereas the β‐diversity between the pine and subalpine community is low. In the wet season, up to 85% of β‐diversity is reflected by remote sensing variables. The S2 variables account for more explanatory power than the LiDAR variables. The explanatory power of LiDAR variables increases with grain size, whereas the explanatory power of S2 variables decreases.ConclusionAt the lower ecotone, β‐diversity agrees with the pre‐defined community distinction, while at the upper ecotone the community types cannot be clearly separated by compositional dissimilarity alone. The high β‐diversity between the succulent scrub and pine forest results from positive feedback switches of P. canariensis, being a fire‐adapted, key tree species. In accordance with the spectral variation hypothesis, remote sensing signals can adequately represent β‐diversity for a large extent, in a short time and at low cost. However, in‐situ sampling is necessary to fully understand community composition. Nature conservation requires such interdisciplinary approaches.