README (original) (raw)

The goal of barrks (bark beetleraster kit forseasonal development) is to calculate the phenological development of bark beetles. Rather than implementing one specific model, the package provides a collection of different models that can be chosen. Additionally, the models can be customized and combined to create an individual model. The calculations can be done spatially explicit by using raster inputs, or based on station inputs that are available as data frames. Even though most of the implemented models describe the phenology of Ips typographus, the package is not limited to particular bark beetle species. For instance, CHAPY models the phenology of Pityogenes chalcographus and the package may be extended by models for additional bark beetle species. The full documentation of barrks can be found here.

The following table lists the models that are implemented in the package.

barrks comes with sample data that will be used below. The phenology is calculated with phenology() which takes all necessary inputs as arguments. Subsequently, the rasters of emerged generations by date can be retrieved withget_generations_rst(). terra::plot() can be used to visualize these rasters.

library(barrks)
library(tidyverse)
library(terra)


# calculate phenology
pheno <- phenology('phenips-clim', barrks_data())

# plot number of prevailing generations on 4 different dates
dates <- c('2015-04-15', '2015-06-15', '2015-08-15', '2015-10-15')
get_generations_rst(pheno, dates) %>% plot(mar = c(0.2, 0.1, 2, 5),
                                           axes = FALSE, box = TRUE, nr = 1,
                                           cex.main = 1.9, plg = list(cex = 1.8))

barrks makes it easy to plot the development of the individual generations. To illustrate that, a “shaded” variant of the phenology above is calculated and the development diagram for a specific cell (called “station” in barrks) is plotted for both phenology variants.

pheno_shaded <- phenology('phenips-clim', barrks_data(), exposure = 'shaded')

plot_development_diagram(list(sunny = pheno, shaded = pheno_shaded),
                         stations_create('Example', 234),
                         .lty = c(1, 2),
                         xlim = as.Date(c('2015-04-01', '2015-12-31')))

Baier, Peter, Josef Pennerstorfer, and Axel Schopf. 2007. “PHENIPS—A comprehensive phenology model of Ips typographus (L.)(Col., Scolytinae) as a tool for hazard rating of bark beetle infestation.” _Forest Ecology and Management_249 (3): 171–86. https://doi.org/10.1016/j.foreco.2007.05.020.

Jakoby, Oliver, Heike Lischke, and Beat Wermelinger. 2019. “Climate change alters elevational phenology patterns of the European spruce bark beetle (Ips typographus).”Global Change Biology 25 (12): 4048–63. https://doi.org/10.1111/gcb.14766.

Jönsson, Anna Maria, Susanne Harding, Paal Krokene, Holger Lange, Ake Åke Lindelöw, Bjørn Økland, Hans Peter Ravn, and Leif Martin Schroeder. 2011. “Modelling the potential impact of global warming on Ips typographus voltinism and reproductive diapause.” Climatic Change 109: 695–718. https://doi.org/10.1007/s10584-011-0038-4.

Lange, Holger, Bjørn Økland, and Paal Krokene. 2008. “To Be or Twice to Be? The Life Cycle Development of the Spruce Bark Beetle Under Climate Change.” In Unifying Themes in Complex Systems: Proceedings of the Sixth International Conference on Complex Systems, 251–58. Springer. https://doi.org/10.1007/978-3-540-85081-6_32.

Ogris, Nikica, Mitja Ferlan, Tine Hauptman, Roman Pavlin, Andreja Kavčič, Maja Jurc, and Maarten De Groot. 2019. “RITY–A phenology model of Ips typographus as a tool for optimization of its monitoring.” _Ecological Modelling_410: 108775. https://doi.org/10.1016/j.ecolmodel.2019.108775.

Ogris, Nikica, Mitja Ferlan, Tine Hauptman, Roman Pavlin, Andreja Kavčič, Maja Jurc, and Maarten de Groot. 2020. “Sensitivity analysis, calibration and validation of a phenology model for Pityogenes chalcographus (CHAPY).”Ecological Modelling 430: 109137. https://doi.org/10.1016/j.ecolmodel.2020.109137.