Richness patterns in vertebrates are robust to the Linnean and Wallacean shortfalls
Data files
Feb 28, 2025 version files 381 KB
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README.md
2.59 KB
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Table_A1.csv
27.09 KB
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Table_A2.csv
351.32 KB
Abstract
Nearly all research has to rely on imprecise data. This poses a challenge of knowing which conclusions are reliable despite potential data quality issues. One field fundamentally affected by this is macroecology. Can we understand drivers of biodiversity patterns without having fully reliable distributional data? In this paper, we investigated the reliability of biodiversity patterns focused on three groups of terrestrial vertebrates ranging from very well-known (birds and mammals) to relatively poorly known (amphibians). We compared two expert-derived sets of range maps generated more than 10 years apart. We found that the overall spatial diversity patterns between the two sets were extraordinarily similar for all three groups but that nearly half of all species had changes in taxonomy and or distribution. We further found that the minute changes in richness we did see were nearly exclusively driven by changes in the mapped ranges of already known species rather than the discovery of new species, even though up to 18% of new species were added between assessments. Since the patterns were highly similar between the asessments it suggests that, at least for vertebrates, data quality does not affect analyses of biodiversity patterns. This further implies that results based on older and less precise input data remains reliable, even though more precise input data has become available.
https://doi.org/10.5061/dryad.v15dv4270
Description of the data and file structure
All codes used to process the data in the paper have been uploaded as Software.
Codes are found in a total of 21 files, names in order they are processed. Code_11 to Code_18 deals with initial data processing. Code_21 to Code_26 performs statistical tests, Code_31 to Code_37 creates all figures.
We have also uploaded two files from the appendix in csv files.
Table_A1 contains all species deleted between two time points
Table_A1 contains all species added between two time points
Files and variables
File: Table_A1.csv
Description: contains all species deleted between two time points
Variables
- Group: If the species is a mammal, a bird or an amphibian
- Order: Taxonomic order
- Family: Taxonomic family
- Name_2023: The binomial name of the species the taxon is assigned to in the 2023 dataset
- Name_2012: The binomial name of the species the taxon is assigned to in the 2012 dataset
- Change: The type of change between the two datasets
- Source: The taxonomic source we used to asses the type of change
File: Table_A2.csv
Description:: contains all species added between two time points
Variables
- Group: If the species is a mammal, a bird or an amphibian
- Order: Taxonomic order
- Family: Taxonomic family
- Name_2023: The binomial name of the species the taxon is assigned to in the 2023 dataset
- Name_2012: The binomial name of the species the taxon is assigned to in the 2012 dataset
- Change: The type of change between the two datasets
- Source: The taxonomic source we used to asses the type of change
Code/software
All analyses were conducted in R 4.1.2 (R Core Team 2021) and relied on functions from the libraries Dplyr (Wickham et al 2022), fasterize (Ross 2020), ggcorrplot (Kassambara 2023), ggplot2 (Wickham 2016), grid (R Core Team 2021), geosphere (Hijmans 2021), maptools (Bivand and Lewin-Koh 2022), ncf (Bjornstad 2022), pdist(Wong 2022), proj4 (Urbanek 2022), rphylopic (Gearty et al 2023), raster (Hijmans 2022a), rgeos (Bivand and Colin Rundel 2021), spdep (Bivand 2022), sf (Pebesma and Bivand 2023), patialreg (Bivand et al 2013), stars (Pebesma & Bivand 2023) and terra (Hijmans 2022b)
Access information
Other publicly accessible locations of the data:
- n/a
Data was derived from the following sources:
- The analyses rely on primary data gathered by IUCN and birdlife.