Mapping the spatial distribution of plant diversity indices in a tropical forest using multi-spectral satellite image classification and field measurements

Abstract

The relationships among alpha and beta diversity indices, computed from 141 randomly sampled quadrats, and the vegetation classes obtained by multi-spectral satellite image classification, were used as a strategy for mapping plant diversity in a tropical landscape mosaic. A relatively high accuracy of the land cover map was revealed by the overall accuracy assessment and the Cohen's Kappa statistic. Species accumulation models were used to evaluate how representative the sample size was of the different vegetation types. A standard one-way, between-subjects ANOVA confirmed a significant reduction of the within-class variance of plant diversity with respect to their total variance across the landscape. Computed uniformity indices, to assess the internal uniformity of vegetation classes on the diversity indices, confirmed the goodness of the mapped classes in stratifying variability of plant di- versity. This allowed for the use of the mapped classes as spatial interpolators of plant diversity values for estimation and up-scaling purposes. Finally, it was revealed that the plant diversity of the landscape depends, to a large extent, on the diversity contained in the most mature forest class, which is also the most diverse community in the studied area. High and moderate beta diversity values between mature forests and both the secondary associations and the first stages of succession, respectively, indicated that there is a significant contribution to the diversity of the landscape by those vegetation classes.