Integration of genomic and ecological methods inform management of an undescribed, yet highly exploited, sardine species.

Assessing genetic diversity within species is key for conservation strategies in the context of human-induced biotic changes. This is important in marine systems, where many species remain undescribed while being overfished, and conflicts between resource-users and conservation agencies are common. Combining niche modelling with population genomics can contribute to resolving those conflicts by identifying management units and understanding how past climatic cycles resulted in current patterns of genetic diversity. We addressed these issues on an undescribed but already overexploited species of sardine of the genus Harengula. We find that the species distribution is determined by salinity and depth, with a continuous distribution along the Brazilian mainland and two disconnected oceanic archipelagos. Genomic data indicate that such biogeographic barriers are associated with two divergent intraspecific lineages. Changes in habitat availability during the last glacial cycle led to different demographic histories among stocks. One coastal population experienced a 3.6-fold expansion, whereas an island-associated population contracted 3-fold, relative to the size of the ancestral population. Our results indicate that the island population should be managed separately from the coastal population, and that a Marine Protected Area covering part of the island population distribution can support the viability of this lineage.

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; http://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.