chillR (version 0.75)

make_pheno_trend_plot: 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"
)

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

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'.

Author

Eike Luedeling

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.

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")