Questions
Are topography‐based forest types floristically consistent between sites in central Amazonia? Do broad landform and geological features control site‐specific edaphic and floristic variation and therefore obfuscate the floristic classification based on local topographical classes? Is model‐based clustering a useful tool for floristic classification?
Location
Non‐inundated forest of central Amazonia, north of the Amazon River.
Methods
We analysed species presence–absence of a group of terrestrial monocot herbs (Zingiberales) in 123 plots (250 × 2 m) concentrated in three sites of non‐inundated forests. Distances between plots were 1–140 km. Floristic patterns were extracted by dimensionality reduction using geodesic floristic distance. We applied a model‐based cluster analysis (MC) coupled with the Bayesian information criterion to determine the best floristic classification. We used geometric and non‐geometric internal evaluators to compare the performance of MC to the agglomerative hierarchical clustering method UPGMA. The floristic clusters were tested for differences in edaphic and topographic features. Landform‐geological classes were defined based on geological maps and a digital elevation model. We used the Kappa index and ANOVA to evaluate the agreement between landform–geological classes, floristic clusters and environmental features.
Results
The best MC solution found four floristic clusters. Differences in soil chemical properties, which were linked with lithological classes and broad land‐form features, explained abrupt floristic changes and floristic differences between the same topographical habitats of different sites. Within poor soils, floristic classes defined by elevation along the soil catena (upland and valley forests) were fuzzy. Valley sandy forest was not floristically consistent across sites due to subtle edaphic variation. Using a non‐geometric internal evaluator, MC coupled with geodesic floristic distance estimation performed better overall than UPGMA.
Main conclusions
Geological classes defined by lithology and broad landform features control the major variation of edaphic and floristic patterns in central Amazonia. MC proved to be a useful method to classify and interpret floristic patterns. Revised vegetation maps that account for lithology, broad land‐form features and edaphic conditions would therefore be a better proxy for regional floristic variation than the presently used simple classes based on position along the catena.