Biology subjects

Colli-Silva, M.

Publications and source records attributed to Colli-Silva, M..

2 recordsLinked to original sources

bioRxiv2025

How much can reticulate evolution entangle plant systematics? Revisiting subfamilial classification of the Malvatheca clade (Malvaceae) on the basis of phylogenomics

Reticulate evolution (RE), involving hybridization and related processes, generates network-like rather than strictly bifurcating relationships among lineages and can obscure phylogenetic relationships. Detecting ancient hybridization is particularly challenging, as genomic signals may erode over time. The Malvatheca clade (Malvaceae), marked by multiple paleopolyploidy events since its estimated origin 66 my, offers a useful model for examining RE. Its three subfamilies--Bombacoideae (with high chromosome numbers, mostly trees), Malvoideae (lower chromosome numbers, mostly herbs), and the recently described Matisioideae--show unresolved relationships, with several taxa of uncertain placement. We conducted a phylogenomic analysis of 62 Malvatheca species via complete plastomes, 35S rDNA cistrons, and comparative repeatome data. All datasets consistently resolved three main clades: (i) Bombacoideae, (ii) Malvoideae, and (iii) a heterogeneous assemblage including most of the recently assigned Matisioideae and several incertae sedis taxa, suggesting a more complex evolutionary history and circumscription than previously recognized. Chromosome numbers were negatively correlated with repeatome diversity: Bombacoideae presented higher counts but lower repeat diversity, possibly reflecting slower repeat evolution associated with woody growth forms. In contrast, clade III showed marked heterogeneity in both chromosome number and repeat composition, which is consistent with a reticulate origin. Overall, our results show evidence of ancient hybridization and polyploidy, predominantly allopolyploidy, in shaping Malvatheca evolution. These results highlight that reticulation and genome dynamics, rather than taxonomic boundaries alone, are central to understanding the diversification of Malvatheca.

genomics↗

bioRxiv2020

No one-size-fits-all solution to clean GBIF

Species occurrence records provide the basis for many biodiversity studies. They derive from georeferenced specimens deposited in natural history collections and visual observations, such as those obtained through various mobile applications. Given the rapid increase in availability of such data, the control of quality and accuracy constitutes a particular concern. Automatic filtering is a scalable and reproducible means to identify potentially problematic records and tailor datasets from public databases such as the Global Biodiversity Information Facility (GBIF; www.gbif.org), for biodiversity analyses. However, it is unclear how much data may be lost by filtering, whether the same filters should be applied across all taxonomic groups, and what the effect of filtering is on common downstream analyses. Here, we evaluate the effect of 13 recently proposed filters on the inference of species richness patterns and automated conservation assessments for 18 Neotropical taxa, including terrestrial and marine animals, fungi, and plants downloaded from GBIF. We find that a total of 44.3% of the records are potentially problematic, with large variation across taxonomic groups (25 - 90%). A small fraction of records was identified as erroneous in the strict sense (4.2%), and a much larger proportion as unfit for most downstream analyses (41.7%). Filters of duplicated information, collection year, and basis of record, as well as coordinates in urban areas, or for terrestrial taxa in the sea or marine taxa on land, have the greatest effect. Automated filtering can help in identifying problematic records, but requires customization of which tests and thresholds should be applied to the taxonomic group and geographic area under focus. Our results stress the importance of thorough recording and exploration of the meta-data associated with species records for biodiversity research.

ecology↗