1. Species occurrence records from online databases are an indispensable resource in ecological, biogeographical and palaeontological research. However, issues with data quality, especially incorrect geo-referencing or dating, can diminish their usefulness. Manual cleaning is time-consuming, error prone, difficult to reproduce and limited to known geographical areas and taxonomic groups, making it impractical for datasets with thousands or millions of records.2. Here, we present CoordinateCleaner, an r-package to scan datasets of species occurrence records for geo-referencing and dating imprecisions and data entry errors in a standardized and reproducible way. CoordinateCleaner is tailored to problems common in biological and palaeontological databases and can handle datasets with millions of records. The software includes (a) functions to flag potentially problematic coordinate records based on geographical gazetteers, (b) a global database of 9,691 geo-referenced biodiversity institutions to identify records that are likely from horticulture or captivity, (c) novel algorithms to identify datasets with rasterized data, conversion errors and strong decimal rounding and (d) spatio-temporal tests for fossils.3. We describe the individual functions available in CoordinateCleaner and demonstrate them on more than 90 million occurrences of flowering plants from the Global Biodiversity Information Facility (GBIF) and 19,000 fossil occurrences from the Palaeobiology Database (PBDB). We find that in GBIF more than 3.4 million records (3.7%) are potentially problematic and that 179 of the tested contributing This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

The unparalleled biodiversity found in the American tropics (the Neotropics) has attracted the attention of naturalists for centuries. Despite major advances in recent years in our understanding of the origin and diversification of many Neotropical taxa and biotic regions, many questions remain to be answered. Additional biological and geological data are still needed, as well as methodological advances that are capable of bridging these research fields. In this review, aimed primarily at advanced students and early-career scientists, we introduce the concept of “trans-disciplinary biogeography,” which refers to the integration of data from multiple areas of research in biology (e.g., community ecology, phylogeography, systematics, historical biogeography) and Earth and the physical sciences (e.g., geology, climatology, palaeontology), as a means to reconstruct the giant puzzle of Neotropical biodiversity and evolution in space and time. We caution against extrapolating results derived from the study of one or a few taxa to convey general scenarios of Neotropical evolution and landscape formation. We urge more coordination and integration of data and ideas among disciplines, transcending their traditional boundaries, as a basis for advancing tomorrow’s ground-breaking research. Our review highlights the great opportunities for studying the Neotropical biota to understand the evolution of life.

26PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.3074v1 | CC BY 4.0 Open Access | rec: 6 Jul 2017, publ: 6 Jul 2017 Abstract: The outstanding biodiversity found in the American tropics (the Neotropics) has attracted the 45 attention of naturalists for centuries. Despite major advances in the generation of biodiversity data, many 46 questions remain to be answered. In this review, we first summarize some of the knowns and unknowns 47 about Neotropical biodiversity, and discuss how human impact may have drastically affected some of the 48 patterns observed today. We then link biodiversity to landscape, and outline major advances in 49 biogeographical research. In particular, we argue that it is crucial to test the effect of landscape and 50 climatic evolution to biotic diversification and distribution in order to achieve a comprehensive 51 understanding of current patterns. In this context, it is also important to consider extant and extinct taxa, 52 as well as to use probabilistic and parametric methods that explicitly include landscape evolution models.