R code to fit Gaussian process models to white-nose syndrome/Pseudogymnoascus destructans monitoring data across North America from 2006-2022
Dates
Publication Date
2022-11-10
Start Date
2006-01-01
End Date
2021-12-31
Citation
Wiens, A.M., and Thogmartin, W.E., 2022, R code to fit Gaussian process models to white-nose syndrome/Pseudogymnoascus destructans monitoring data across North America from 2006-2022: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZD9GVZ.
Summary
This code supports the manuscript "Gaussian process forecasts Pseudogymnoascus destructans will cover coterminous United States by 2030." The code is used to fit Gaussian process models to publicly accessible monitoring data on the spread of white-nose syndrome in North America. These models are used to make predictions on a fine spatial grid, giving a forecast (and hindcast) of the spread of white-nose syndrome at any location. Also contained in the code is a retrospective cross validation experiment, producing parameter estimates and model scoring over time. The code also relies on the GRTS grid for model prediction, which is publicly accessible at https://doi.org/10.5066/p9o75ydv. Shapefiles such as administrative boundaries can [...]
Summary
This code supports the manuscript "Gaussian process forecasts Pseudogymnoascus destructans will cover coterminous United States by 2030." The code is used to fit Gaussian process models to publicly accessible monitoring data on the spread of white-nose syndrome in North America. These models are used to make predictions on a fine spatial grid, giving a forecast (and hindcast) of the spread of white-nose syndrome at any location. Also contained in the code is a retrospective cross validation experiment, producing parameter estimates and model scoring over time. The code also relies on the GRTS grid for model prediction, which is publicly accessible at https://doi.org/10.5066/p9o75ydv. Shapefiles such as administrative boundaries can be used to add to plots are not required for the analysis.
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wns_spread_manuscript_code.R
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wnsRcode_metadata.xml Original FGDC Metadata
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Related External Resources
Type: Related Primary Publication
Wiens, A.M., and Thogmartin, W.E., 2022, Gaussian process forecasts
Pseudogymnoascus destructans
will cover coterminous United States by 2030: Ecology and Evolution, v. 12, no. 11, https://doi.org/10.1002/ece3.9547.
The code was used to produce all results and figures for the manuscript. In addition, as more white-nose syndrome monitoring data are collected, this code can be used to re-fit models and make updated predictions.