RESUMEN
The recent availability of open-access repositories of functional traits has revolutionized trait-based approaches in ecology and evolution. Nevertheless, the underrepresentation of tropical regions and lineages remains a pervasive bias in plant functional trait databases, which constrains large-scale assessments of plant ecology, evolution, and biogeography. Here, we present MelastomaTRAITs 1.0, a comprehensive and updatable database of functional traits for the pantropical Melastomataceae, the ninth-largest angiosperm family with 177 genera and more than 5800 species. Melastomataceae encompass species with a wide diversity of growth forms (herbs, shrubs, trees, epiphytes, and woody climbers), habitats (including tropical forests, savannas, grasslands, and wetlands from sea level to montane areas above the treeline), ecological strategies (from pioneer, edge-adapted and invasive species to shade-tolerant understory species), geographic distribution (from microendemic to continental-wide distribution), reproductive, pollination, and seed dispersal systems. MelastomaTRAITs builds on 581 references, such as taxonomic monographs, ecological research, and unpublished data, and includes four whole-plant traits, six leaf traits, 11 flower traits, 18 fruit traits, and 27 seed traits for 2520 species distributed in 144 genera across all 21 tribes. Most data come from the Neotropics where the family is most species-rich. Miconieae (the largest tribe) contains the highest number of trait records (49.6%) and species (41.1%) records. The trait types with the most information in the database were whole-plant traits, flowers, and leaf traits. With the breadth of functional traits recorded, our database helps to fill a gap in information for tropical plants and will significantly improve our capacity for large-scale trait-based syntheses across levels of organization, plant-animal interactions, regeneration ecology, and thereby support conservation and restoration programs. There are no copyright restrictions on the dataset; please cite this data paper when reusing the data.
RESUMEN
Shifts among functional pollinator groups are commonly regarded as sources of floral morphological diversity (disparity) through the formation of distinct pollination syndromes. While pollination syndromes may be used for predicting pollinators, their predictive accuracy remains debated, and they are rarely used to test whether floral disparity is indeed associated with pollinator shifts. We apply classification models trained and validated on 44 functional floral traits across 252 species with empirical pollinator observations and then use the validated models to predict pollinators for 159 species lacking observations. In addition, we employ multivariate statistics and phylogenetic comparative analyses to test whether pollinator shifts are the main source of floral disparity in Melastomataceae. We find strong support for four well-differentiated pollination syndromes ('buzz-bee', 'nectar-foraging vertebrate', 'food-body-foraging vertebrate', 'generalist'). While pollinator shifts add significantly to floral disparity, we find that the most species-rich 'buzz-bee' pollination syndrome is most disparate, indicating that high floral disparity may evolve without pollinator shifts. Also, relatively species-poor clades and geographic areas contributed substantially to total disparity. Finally, our results show that machine-learning approaches are a powerful tool for evaluating the predictive accuracy of the pollination syndrome concept as well as for predicting pollinators where observations are missing.
