Ant elevational biodiversity gradient

This repositiory contains the code to run the case study example analysis from the manuscript by McGlinn et al. (2020).

Data

The case study is a reanalysis of ant community data collected in the Great Smokies National Park with seven additional sites (Sanders et al. 2007).

The raw data files (NOT MEANT FOR FUTURE ANALYSIS) were provided by Nathan Sanders:

./data/180926-AllRawData.xlsx

which contains the community matrix of ant abundances and the site attributes. Note that this raw file does have a few small mistakes that are corrected in the data processing and cleaning step described below. Therefore, future re-analysis of the data should used the cleaned data and not the raw data. Sanders also provided:

./data/smokies_species_list.xlsx

which contains the ant species list. Ant taxonomy follows Bolton and were updated on Sept 26, 2018

The cleaned datafiles have been also published on Dryad (Sanders et al. 2020):

Reproducing the results of McGlinn et al.

To run the data processing and data analysis R scripts the following packages must be installed

install.packages(c('devtools', 'mobr', 'readxl', 'janitor', 
                   'leaflet', 'mapview', 'tidyr',
                   'vegan', 'dplyr', 'ggplot2', 
                   'egg', 'broom'))

Data processing

The script to process the raw data files into cleaned data files that were then posted to Dryad (Sanders et al. 2021) and analyzed is:

./scripts/data_processing.R

The cleaned data file is located at

./data/dryad/smokies_all.csv

and the metadata for that file is given in

./data/dryad/smokies_all_metadata.csv

Data analysis

The script to carry out the analysis published in McGlinn et al. (accepted) is:

./scripts/univariate_gradients.R

References

McGlinn, D.J., T. Engel, S.A. Blowes, N.J. Gotelli, T.M. Knight, B.J. McGill, N.J. Sanders, and J.M. Chase. 2020. A multiscale framework for disentangling the roles of evenness, density and aggregation on diversity gradients. Ecology.

Sanders, N.J., J.-P. Lessard, M.C. Fitzpatrick, and R.R. Dunn. 2007. Temperature, but not productivity or geometry, predicts elevational diversity gradients in ants across spatial grains. Global Ecology and Biogeography 16:640–649. https://doi.org/10.1111/j.1466-8238.2007.00316.x

Sanders, N.J., J.-P. Lessard, R.R Dunn. 2020. Great smoky mountain ant community composition, v3, Dryad, Dataset, https://doi.org/10.5061/dryad.z8w9ghx7g

Licence

MIT License

Copyright (c) [2020] [Daniel McGlinn]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.