Published October 20, 2016
| Version v1
Dataset
Open
Data from: A combined field survey and molecular identification protocol for comparing forest arthropod biodiversity across spatial scales
Authors/Creators
- 1. University of East Anglia
- 2. French National Centre for Scientific Research
- 3. Laboratory Evolution and Biological Diversity
- 4. University of Helsinki
- 5. University of La Laguna
- 6. National Museum of Natural History
- 7. University of La Réunion
Description
Obtaining fundamental biodiversity metrics such as alpha, beta and gamma diversity for arthropods is often complicated by a lack of prior taxonomic information and/or taxonomic expertise, which can result in unreliable morphologically based estimates. We provide a set of standardized ecological and molecular sampling protocols that can be employed by researchers whose taxonomic skills may be limited, and where there may be a lack of robust a priori information regarding the regional pool of species. These protocols combine mass sampling of arthropods, classification of samples into parataxonomic units (PUs) and selective sampling of individuals for mtDNA sequencing to infer biological species. We sampled ten lowland rainforest plots located on the volcanic oceanic island of Réunion (Mascarene archipelago) for spiders, a group with limited taxonomic and distributional data for this region. We classified adults and juveniles into PUs and then demonstrated the reconciliation of these units with presumed biological species using mtDNA sequence data, ecological data and distributional data. Because our species assignment protocol is not reliant upon prior taxonomic information, or taxonomic expertise, it minimizes the problem of the Linnean shortfall to yield diversity estimates that can be directly compared across independent studies. Field sampling can be extended to other arthropod groups and habitats by adapting our field sampling protocol accordingly.
Notes
Files
GL alignments.zip
Files
(372.0 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:310212ff0159a2a4fa3d6122466dfb8f
|
372.0 kB | Preview Download |
Additional details
Related works
- Is cited by
- 10.1111/1755-0998.12617 (DOI)