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)...

We estimated phylogenetic relationships of Polygala inferred from nrITS, matK-trnK, trnL intron, trnL-trnF intergenic spacer, and rbcL sequence data, with emphasis on the New World clade. Our results did not support the New World and Old World clades as sister groups in Polygala. Relationships among Polygala and allied genera are being discussed, with the recovered clades compared to those of the current taxonomic delimitations. A biogeographic analysis using an ultrametric phylogenetic tree and calibrated with the fossil Paleosecuridaca as well as a reconstruction of the ancestral area are also provided.

Epiphytes are hyper‐diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non‐vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer‐reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non‐vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non‐vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events.