make_pheno_trend_plot: Make image showing phenology response to temperatures during...

In chillR: Statistical Methods for Phenology Analysis in Temperate Fruit Trees

Make image showing phenology response to temperatures during two phases

Description

The timing of many developmental stages of temperate plants is understood to depend on temperatures during two phases. This function seeks to illustrate this dependency by plotting phenological dates as colored surface, as a function of mean temperatures during both phases, which are indicated on the x and y axes.

Usage

make_pheno_trend_plot(
  weather_data_frame,
  split_month = 6,
  pheno,
  use_Tmean = FALSE,
  Start_JDay_chill,
  End_JDay_chill,
  Start_JDay_heat,
  End_JDay_heat,
  outpath,
  file_name,
  plot_title,
  ylabel = NA,
  xlabel = NA,
  legend_label = NA,
  image_type = "png",
  colorscheme = "normal",
  fonttype = "serif"
)

Arguments

weather_data_frame	a dataframe containing daily minimum and maximum temperature data (in columns called Tmin and Tmax, respectively), and/or mean daily temperature (in a column called Tmean). There also has to be a column for Year and one for JDay (the Julian date, or day of the year). Alternatively, the date can also be given in three columns (Year, Month and Day).
split_month	the procedure analyzes data by phenological year, which can start and end in any month during the calendar year (currently only at the beginning of a month). This variable indicates the last month (e.g. 5 for May) that should be included in the record for a given phenological year. All subsequent months are assigned to the following phenological year.
pheno	a data frame that contains information on the timing of phenological events by year. It should consist of two columns called Year and pheno. Data in the pheno column should be in Julian date (day of the year).
use_Tmean	boolean variable indicating whether or not the column Tmean from the weather_data_frame should be used as input for the PLS analysis. If this is set to FALSE, Tmean is calculated as the arithmetic mean of Tmin and Tmax.
Start_JDay_chill	the Julian date, on which the first relevant period (e.g. the chilling phase) starts
End_JDay_chill	the Julian date, on which the first relevant period (e.g. the chilling phase) ends
Start_JDay_heat	the Julian date, on which the second relevant period (e.g. the forcing phase) starts
End_JDay_heat	the Julian date, on which the second relevant period (e.g. the forcing phase) ends
outpath	the output path
file_name	the output file name
plot_title	the title of the plot
ylabel	the label for the y-axis. There is a default, but in many cases, it may be desirable to customize this
xlabel	the label for the x-axis. There is a default, but in many cases, it may be desirable to customize this
legend_label	the label for the legend (color scheme). There is a default, but in many cases, it may be desirable to customize this
image_type	the type of image to produce. This currently has only two options: "tiff" or anything else (the default). If this is not "tiff", a png image is produced. The "tiff" option was added to produce publishable figures that adhere to the requirements of most scientific journals.
colorscheme	the color scheme for the figure. This currently has only two options: "bw" or anythings else (the default). "bw" produces a grayscale image, otherwise the figure will be in color
fonttype	font style to be used for the figure. Can be 'serif' (default) or 'sans'.

Details

The generation of the color surface is based on the Kriging technique, which is typically used for interpolation of spatial data. The use for this particular purpose is a bit experimental. The function uses the Krig function from the fields package.

Value

pheno	data frame containing all data needed for reproducing the plot: Year (during which the phenological event occurred - the year in which the phenological season indicated by split_month ended), pheno (the date on which the phenological event occurred), Chill_Tmean (mean temperature during the first relevant phase), Heat_Tmean (mean temperature during the second relevant phase) and Year_Tmean (mean annual temperature - not actually used in the plot)
ylabel	character string used for labeling the y axis
xlabel	character string used for labeling the x axis

Author(s)

Eike Luedeling

References

Guo L, Dai J, Wang M, Xu J, Luedeling E, 2015. Responses of spring phenology in temperate zone trees to climate warming: a case study of apricot flowering in China. Agricultural and Forest Meteorology 201, 1-7.

Guo L, Dai J, Ranjitkar S, Xu J, Luedeling E, 2013. Response of chestnut phenology in China to climate variation and change. Agricultural and Forest Meteorology 180, 164-172.

Luedeling E, Guo L, Dai J, Leslie C, Blanke M, 2013. Differential responses of trees to temperature variation during the chilling and forcing phases. Agricultural and Forest Meteorology 181, 33-42.

the interpolation was done according to:

Furrer, R., Nychka, D. and Sain, S., 2012. Fields: Tools for spatial data. R package version 6.7.

Reference to the chillR package:

Luedeling E, Kunz A and Blanke M, 2013. Identification of chilling and heat requirements of cherry trees - a statistical approach. International Journal of Biometeorology 57,679-689.

Examples

weather<-fix_weather(KA_weather)

#the output of the PLS function (PLS_pheno, plotted with plot_PLS) can be used to select
#phases that are likely relevant for plant phase timing. See respective examples for running
#these functions.

file_path<-paste(getwd(),"/",sep="")

#mpt<-make_pheno_trend_plot(weather_data_frame = weather$weather, split_month = 6,
#      pheno = KA_bloom, use_Tmean = FALSE, Start_JDay_chill = 260, 
#      End_JDay_chill = 64, Start_JDay_heat = 44, End_JDay_heat = 103,
#      outpath = file_path, file_name = "pheno_trend_plot",
#      plot_title = "Impacts of chilling and forcing temperatures on cherry phenology",
#      ylabel = NA, xlabel = NA, legend_label = NA, image_type = "png", 
#      colorscheme = "normal")

chillR documentation built on Nov. 28, 2023, 1:09 a.m.