chillR (version 0.75)

plot_phenology_trends: Visualizing phenology responses to temperatures during two phases

Description

The timing of many development stages of temperate trees may depend on temperatures during two phases (e.g. bloom dates depend on the temperature during both the chilling and forcing phase of dormancy). plot_phenology_trends() illustrates this dependency as a colored surface with contour lines by applying an interpolating procedure with functions in the fields package. The plot is implemented through functions in the ggplot2 package.

Usage

plot_phenology_trends(
  pheno_data,
  weather_data,
  split_month = 6,
  chilling_phase,
  forcing_phase,
  Krig_warn = TRUE,
  x_axis_name = NULL,
  y_axis_name = NULL,
  legend_name = NULL,
  contour_line_color = "black",
  point_color = "black",
  point_shape = 19,
  legend_colors = NULL,
  base_size = 11,
  ...
)

Value

plot_phenology_trends() is expected to return an object of class gg and ggplot. This means that the plot can be later modified by using the syntax '+' from the ggplot2 package (see examples). The plot returned in the function should look as the following:

Arguments

pheno_data

is a data frame that contains information on the timing of phenology 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).

weather_data

is a data frame containing daily minimum and maximum temperature data (in columns called Tmin and Tmax, respectively). There also has to be a column for Year, one for Month and one for Day. It can also contain a column for JDay (the Julian date, or day of the year).

split_month

is an integer representing the last month of the growing season. This procedure analyzes data by phenology 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 phenology year. All subsequent months are assigned to the following phenology year.

chilling_phase

is a vector of integers representing the start and end for the chilling period in temperate trees. Numbers must be provided in Julian date (day of the year).

forcing_phase

is a vector of integers representing the start and end for the forcing period in temperate trees. Numbers must be provided in Julian date (day of the year).

Krig_warn

is a boolean parameter passed to the Krig function. Default is set to TRUE following the recommendation of the authors of the package. For detailed information, please see the documentation of the function.

x_axis_name

is a character string that allows the user modifying the default label used in the x axis.

y_axis_name

is a character string that allows the user modifying the default label used in the y axis.

legend_name

is a character string that allows the user modifying the default label used in the legend.

contour_line_color

is a character string representing the color used to draw the contour lines. Default is set to black. If NA is used, the function will remove the contour lines with a warning.

point_color

is a character string representing the color used to draw the points for actual observations. Default is set to black. If NA is used, the function will remove the points with a warning.

point_shape

is a numeric input representing the point shape used to draw the points for actual observations. Default is set to 19 (filled point). If NA is used, the function will remove the points with a warning.

legend_colors

is a character string representing the color scale used in the surface plot. Default is set to NULL to let the function use the rainbow colors.

base_size

is a numeric input representing the relative size of the elements in plot. base_size is passed to ggplot2::theme_bw as well as used to determine the size of the points and contour lines.

...

accepts arguments passed to ggplot2::theme

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.

Examples

# Run a simple plot
# Code is commented out, so that it passes the CRAN incoming checks.
# Please uncomment to run the code.

# plot_phenology_trends(pheno_data = chillR::KA_bloom,
#                       weather_data = chillR::KA_weather,
#                       chilling_phase = c(306, 350),
#                       forcing_phase = c(355, 60))
             
# Customize the aspects of the plot and save it as 'plot'

# plot <- plot_phenology_trends(pheno_data = chillR::KA_bloom,
#                               weather_data = chillR::KA_weather,
#                               chilling_phase = c(306, 350),
#                               forcing_phase = c(355, 60),
#                               x_axis_name = "Temperatura en el periodo de frio (Celsius)",
#                               y_axis_name = "Temperatura en el periodo de forzado (Celsius)",
#                               legend_name = "Fecha de floracion\n(dia juliano)",
#                               contour_line_color = "white",
#                               point_color = "blue4",
#                               point_shape = 4,
#                               legend_colors = NULL,
#                               base_size = 14,
#                               legend.position = "bottom",
#                               axis.title = ggplot2::element_text(family = "serif"))

# plot

# Modify the plot object with the syntax from ggplot2.
# Be aware that the following code overrides the modifications
# done by the argument '...' in the main function

# plot + ggplot2::theme_classic(base_size = 14)