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.

28Species occurrence records provide the basis for many biodiversity studies. They derive from geo-referenced 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 flagging and filtering are a scalable and reproducible means to identify potentially problematic records in datasets from public databases such as the Global Biodiversity Information Facility (GBIF; www.gbif.org). However, it is unclear how much data may be lost by filtering, whether the same tests should be applied across all taxonomic groups, and what is the effect of filtering for 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 animals, fungi, and plants, terrestrial and marine, downloaded from GBIF. We find that 29-90% of the records are potentially erroneous, with large variation across taxonomic groups. Tests for duplicated information, collection year, basis of record as well as urban areas and coordinates for terrestrial taxa in the sea or marine taxa on land have the greatest effect. While many flagged records might not be de facto erroneous, they could be overly imprecise and increase uncertainty in downstream analyses. Automated flagging 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 exploration of the meta-data associated with species records for biodiversity research. 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44Publicly available species distribution data have become a crucial resource in biodiversity research, including studies in 46 ecology, biogeography, systematics and conservation biology. In particular, the availability of digitized collections from 47 museums and herbaria, and citizen science observations has increased drastically over the last few years. As of today, 48 the largest public aggregator for geo-referenced species occurrences data, the Global Biodiversity Information Facility 49 (www.gbif.org), provides access to more than 1.3 billion geo-referenced occurrence records for species from across the 50 globe and the tree of life. 51A central challenge to the use of these publicly available species occurrence data in research are erroneous geographic 52 coordinates (Anderson et al. 2016). Errors mostly arise because public databases integrate records collected with 53 different methodologies in different places, at different times; often without centralized curation and only rudimentary 54 meta-data. For instance, erroneous coordinates caused by data-entry errors or automated geo-referencing from vague 55 locality descriptions are common (Maldonado et al. 2015; Yesson et al. 2007)...

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Fishery statistics are mainly made by recording the popular fish names, which is later translated into scientific identification. However, these names often either refer to a species group and/or vary along their distribution, increasing identification uncertainty. Species that have cultural value for traditional communities are known as culturally important species (CIS). Herein, we assessed Fishers' Ecological Knowledge to investigate small-silvery herrings (ginga) used as part of a traditional dish "ginga com tapioca", that is recognized as a cultural heritage in the Brazilian northeastern. Through 103 interviews conducted in six communities in three states, we determined that ginga, although a name known elsewhere, is only traded as such in the metropolitan area of Natal. In this region, ginga is caught with drift net and deemed profitable by fishers. We identified both over-and under-differentiation, with ginga recognized by fishers as five, and sold as three main species, namely Opisthonema oglinum, Harengula sp., and Lile piquiting. The larger specimens of two of those species (O. oglinum and Harengula sp.) were also traded as sardines. We found that most individuals sold as ginga were juveniles, which might impact the recruitment of some fish species. Due to its unique cultural relevance to the local community of Natal, ginga could be considered a CIS, which could aid future management or conservation measures.

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