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Ecological prediction at macroscales using big data: Does sampling design matter?

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Code and data for:

Soranno, P.A., Cheruvelil, K.S., Liu, B., Wang, Q., Tan, P.N., Zhou, J., King, K.B.S., McCullough, I.M., Stachelek, J., Bartley, M., Filstrup, C.T., Hanks, E.M., Lapierre, J.F., Lottig, N.R., Schliep, E.M., Wagner, T., Webster, K.E. 2020. Ecological prediction at macroscales using big data: Does sampling design matter? Ecological Applications. doi:10.1002/eap.2123

Contents

├── data
│   └── bar_plot_data
├── graphics
│   ├── density_plots
│   └── lake_clusters
├── README.md
├── scripts
│   ├── 01_prep-data.R
│   ├── 02_exploratory-analysis.R
│   ├── 06_clustering_ecocontext_lakes.R
│   ├── 07_ident_cluster_holdouts.R
│   ├── 08_bar_plots.R
│   ├── 95_maps.R
│   ├── 96_tp_histograms.R
│   └── 97_big_density_plot.R
└── wq-prediction.Rproj

Dependencies

R packages

LAGOSNE, tibble, dplyr, tmap, USAboundaries, sf, ggplot2, raster, cowplot, janitor

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Ecological prediction at macroscales using big data: Does sampling design matter?

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