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1.
Am J Bot ; 110(10): e16235, 2023 10.
Artigo em Inglês | MEDLINE | ID: mdl-37661935

RESUMO

PREMISE: Cacti are characteristic elements of the Neotropical flora and of major interest for biogeographic, evolutionary, and ecological studies. We tested global biogeographic boundaries for Neotropical Cactaceae using specimen-based occurrences, coupled with data from visual observations, as a means to tackle the known collection biases in the family. METHODS: Species richness and record density were assessed for preserved specimens and human observations, and a bioregional scheme tailored to Cactaceae was produced using the interactive web application Infomap Bioregions, based on data from 261,272 point records cleaned through automated and manual steps. RESULTS: We found that areas in Mexico and southwestern USA, in eastern Brazil, and along the Andean region have the greatest density of records and the highest species richness. Human observations complement information from preserved specimens substantially, especially along the Andes. We propose 24 cactus bioregions, among which the most species-rich are northern Mexico/southwestern USA, central Mexico, southern central Mexico, Central America, Mexican Pacific coast, central and southern Andes, northwestern Mexico/extreme southwestern USA, southwestern Bolivia, northeastern Brazil, and Mexico/Baja California. CONCLUSIONS: The bioregionalization proposed shows biogeographic boundaries specific to cacti and can thereby aid further evolutionary, biogeographic, and ecological studies by providing a validated framework for further analyses. This classification builds upon, and is distinctive from, other expert-derived regionalization schemes for other taxa. Our results showcase how observation data, including citizen-science records, can complement traditional specimen-based data for biogeographic research, particularly for taxa with specific specimen collection and preservation challenges and those that are threatened or internationally protected.


Assuntos
Cactaceae , Humanos , México , Evolução Biológica , Brasil , Bolívia
2.
PeerJ ; 8: e9916, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33062422

RESUMO

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.

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