Abstract Background Using this dataset, we examined the global geographical distributions of Solenidae species in relation to their endemicity, species richness and latitudinal ranges and then predicted their distributions under future climate change using species distribution modelling techniques (Saeedi et al. 2016a, Saeedi et al. 2016b). We found that the global latitudinal species richness in Solenidae is bi-modal, dipping at the equator most likely derived by high sea surface temperature (Saeedi et al. 2016b). We also found that most of the Solenidae species will shift their distribution ranges polewards due to global warming (Saeedi et al. 2016a). We also provided a comprehensive review of the taxon to test whether the latitudinal gradient in species richness was uni-modal with a peak in the tropics or northern hemisphere or asymmetric and bimodal as proposed previously (Chaudhary et al. 2016). New information This paper presents an integrated global geographic distribution dataset for 77 Solenidae taxa, including 3,034 geographic distribution records. This dataset was compiled after a careful data-collection and cleaning procedure over four years. Data were collected using field sampling, literature and from open-access databases. Then all the records went through quality control procedures such as validating the taxonomy of the species by examining and re-identifying the specimens in museum collections and using taxonomic and geographic data quality control tools in the World Register of Marine Species (WoRMS) and the r-OBIS package (Provoost and Bosch 2017). This dataset can thus be further used for taxonomical and biogeographical studies of Solenidae.
A world dataset on the geographic distributions of Solenidae razor clams (Mollusca: Bivalvia)
Published 2019 in Biodiversity Data Journal
ABSTRACT
PUBLICATION RECORD
- Publication year
2019
- Venue
Biodiversity Data Journal
- Publication date
2019-01-31
- Fields of study
Biology, Geography, Medicine, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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