Influence of different data cleaning solutions of point-occurrence records on downstream macroecological diversity models.

ABSTRACT: Digital point-occurrence records from the Global Biodiversity Information Facility (GBIF) and other data providers enable a wide range of research in macroecology and biogeography. However, data errors may hamper immediate use. Manual data cleaning is time-consuming and often unfeasible, given that the databases may contain thousands or millions of records. Automated data cleaning pipelines are therefore of high importance. Taking North American Ephedra as a model, we examined how different data cleaning pipelines (using, e.g., the GBIF web application, and four different R packages) affect downstream species distribution models (SDMs). We also assessed how data differed from expert data. From 13,889 North American Ephedra observations in GBIF, the pipelines removed 31

SUBMITTER: Fuhrding-Potschkat P 

PROVIDER: S-EPMC9351331 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature