Data from: Quantifying and estimating ecological network diversity based on incomplete sampling data
Authors/Creators
- 1. National Tsing Hua University
- 2. National Taiwan University
- 3. Bavarian Environment Agency*
- 4. University of Würzburg
- 5. Hessian Agency for Nature Conservation, Environment and Geology
Description
An ecological network refers to the ecological interactions among sets of species. Quantification of ecological network diversity and related sampling/estimation challenges have explicit analogues in species diversity research. A unified framework based on Hill numbers and their generalizations was developed to quantify taxonomic, phylogenetic, and functional diversity. Drawing on this unified framework, we propose three dimensions of network diversity that incorporate the frequency (or strength) of interactions, species' phylogenies and traits. As with surveys in species inventories, nearly all network studies are based on sampling data and thus also suffer from under-sampling effects. Adapting the sampling/estimation theory and the iNEXT (interpolation/extrapolation) standardization developed for species diversity research, we propose the iNEXT.link method to analyze network sampling data. The proposed method integrates the following four inference procedures: (i) Assessment of sample completeness of networks, (ii) asymptotic analysis via estimating the true network diversity, (iii) non-asymptotic analysis based on standardizing sample completeness via rarefaction and extrapolation with network diversity, and (iv) estimation of the degree of unevenness or specialization in networks based on standardized diversity. Interaction data between European trees and saproxylic beetles are used for illustrating the proposed procedures. The software iNEXT.link is developed to facilitate all computations and graphics.
Notes
In this dataset, R code and data are provided for plotting all figures in the paper "Quantifying and estimating ecological network diversity based on incomplete sampling data". Before using the R code, you must download the packages "iNEXT.3D", "iNEXT.4steps", "iNEXT.beta3D", and "iNEXT.link" from Anne Chao's Github at https://github.com/AnneChao?tab=repositories
Part of the dataset is also avialable from the repository "PTB_iNEXT.link" on Anne Chao's Github at https://github.com/AnneChao/PTB_iNEXT.link
The data used for examples are based on tree-beetle interaction frequency data collected from 2016 to 2019 in six study sites (Plot A−F) located in the Steigerwald forest, Germany. Taxonomic data were adapted from Vogel et al. (2020); the phylogeny and trait-based functional distance for beetle species were based on Hagge et al. (2021) and Seibold et al. (2015) respectively.
This dataset includes the following files:
(1) Data Files:
(1a) "Data tree-beetle interaction frequency.csv" (for Figures 5 to 8 in the main text, and figures in Appendices S3 and S4): tree-beetle interaction frequencies.
(1b) "Data phylo_tree.txt" (for Figures 6 and 7, and figures in Appendix S3): phylogeny tree for beetle species.
(1c) "Data distance matrix.txt" (for Figures 6 and 7, and figures in Appendix S3): trait-based functional distance between any two beetle species.
(2) "R code.R": Main code for plotting all figures (Figures 1, 2, 5 to 8 in the main text, and figures in Appendices S3 and S4).
NOTE: Because this code runs a random bootstrapping process in the background, with default = 100 replications, to estimate standard error, the output (for s.e. and 95% confidence intervals) will vary very slightly each time you enter the same data. Also, the bootstrap procedure is very time-consuming; please change the argument nboot = 100 (default) in any function to nboot = 0 (to skip the bootstrap process) or nbbot = 20 (to roughly browse the resulting confidence intervals).
Funding provided by: Ministry of Science and Technology, Taiwan
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100004663
Award Number: 110-2118-M007-004
Files
Data_distance_matrix.txt
Additional details
Related works
- Is derived from
- 10.5281/zenodo.7789389 (DOI)