Retrieving biodiversity data from multiple sources: making secondary data standardised and accessible.

Biodiversity data, particularly species occurrence and abundance, are indispensable for testing empirical hypothesis in natural sciences. However, datasets built for research programmes do not often meet FAIR (findable, accessible, interoperable and reusable) principles, which raises questions about data quality, accuracy and availability. The 21 century has markedly been a new era for data science and analytics and every effort to aggregate, standardise, filter and share biodiversity data from multiple sources have become increasingly necessary.

Bacteria and Archaea Communities in Cerrado Natural Pond Sediments.

Natural ponds in the Brazilian Cerrado harbor high biodiversity but are still poorly studied, especially their microbial assemblage. The characterization of the microbial community in aquatic environments is fundamental for understanding its functioning, particularly under the increasing pressure posed by land conversion and climate change. Here, we aim to characterize the structure (abundance, richness, and diversity) and composition of the Bacteria and Archaea in the sediment of two natural ponds belonging to different basins that primarily differ in size and depth in the Cerrado.

Cryptic diversity in Brazilian endemic monkey frogs (Hylidae, Phyllomedusinae, Pithecopus) revealed by multispecies coalescent and integrative approaches.

Even though Brazil is the world leader in amphibian diversity, a significant part of its richness remains unknown or hidden under cryptic taxa. Here, we used model-based species delimitation in an integrative taxonomic approach, by gathering molecular and morphometric data to assess cryptic taxa within the monkey frogs Pithecopus rohdei, from the Atlantic Forest, and P. megacephalus, from campos rupestres ecosystem.