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Matrix of confusion resulted from the species classification analysis applied to the morphological variables 'leaf area', 'number of secondary veins' and 'leaf-shape PCA axis', using a Support Vector Machine (SVM) classifier. P. gui m. tapajoensis refers to P. guianensis m. tapajoensis.

Matrix of confusion resulted from the species classification analysis applied to the morphological variables 'leaf area', 'number of secondary veins' and 'leaf-shape PCA axis', using a Support Vector Machine (SVM) classifier. P. gui m. tapajoensis refers to P. guianensis m. tapajoensis.

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Species complexes are common in the Neotropical flora, and the Pagamea guianensis complex is one of the most widespread groups of species in the Amazonian white-sand flora. Previous analyses suggested the occurrence of ten species in this group, but species limits remained unclear due to poor sampling, morphological overlap and low molecular variat...

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... o n g m o s t s p e c i e s (Fig. 3A). However, we found strong patterns of species clustering in the morphological space when clades were analysed separately ( Fig. 3B-D). Discriminant models correctly predicted 85 and 79% (SVM and NB models, respectively) of the samples into their respective species when analysing all species together (Table 2, Fig. 4). Although, on average, the SVM model performed better, the NB model yielded a considerably high value of species assignment for P. m. daviliana (the only taxon with low prediction in the SVM analysis) when compared to the SVM model (0.84 and 0.48%, respectively). We found even higher values of species assignment when applying the SVM ...
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... main variables explaining relative habitat suitability for the species were 'precipitation of coldest quarter' (for P. m. angustifolia, P. m. occulta, P. plicatiformis, P. puberula), 'precipitation seasonality' (for P. m. cryptica, P. m. daviliana, P. m. peruviana, P. m. resinosa and P. sessiliflora), 'podzols' (for P. m. solimoensis and P. spruceana), 'slope' (for P. dudleyi), 'precipitation of warmest quarter' (for P. pilosa) and 'count of the number of months with mean temperature > 10 °C' (for P. guianensis) (Table 3; Supporting Information, Fig. S4). Values of niche overlap calculated between species were in general low (< 0.5) and less equivalent/similar than random (P < 0.05; Fig. 6), thus indicating niche divergence. ...

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... This is due to the fact that the spectral behavior of a leaf is a function of its chemical composition, morphology and internal structure, data that help in the recognition of species [31][32][33]. Recent studies have shown the effectiveness of Fourier transform near-infrared (FT-NIR) spectroscopy in the identification of botanical species [20,21,30,34,35]. ...
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... Using multivariate analyses of morphological data may facilitate the identification and selection of diagnostic morphological characters (Henderson, 2006;Marhold, 2011). The further inclusion of molecular techniques can be used to assess whether morphological variants are genetically distinct, thereby contributing to quantification of reproductive isolation (Østbye et al., 2005;Lowry et al., 2008;Xu & Schlüter, 2015;Prata et al., 2018). Genetic data can provide additional insight into the evolutionary history and phylogenetic relationships (e.g. ...
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