ADD3: Function for Implementing the Accumulated Degree Days Method...

In spphpr: Spring Phenological Prediction

Function for Implementing the Accumulated Degree Days Method Using Mean Daily Temperatures for the Combinations of the Starting Date and Base Temperature

Description

Estimates the starting date (S, in day-of-year) and base temperature (T_{0}, in {}^{\circ}C) in the accumulated degree days (ADD) method using mean daily air temperatures (Konno and Sugihara, 1986; Aono, 1993; Shi et al., 2017a, b).

Usage

ADD3( S.arr, T0.arr, Year1, Time, Year2, DOY, Temp, DOY.ul = 120, 
      fig.opt = TRUE, verbose = TRUE )

Arguments

S.arr	the candidate starting dates for thermal accumulation (in day-of-year)
T0.arr	the candidate base temperatures (in {}^{\circ}C)
Year1	the vector of the years in which a particular phenological event was recorded
Time	the vector of the occurrence times (in day-of-year) of a particular phenological event across many years
Year2	the vector of the years recording the climate data corresponding to the occurrence times
DOY	the vector of the dates (in day-of-year) for which climate data exist
Temp	the mean daily air temperature data (in {}^{\circ}C) corresponding to DOY
DOY.ul	the upper limit of DOY used to predict the occurrence time
fig.opt	an optional argument to draw the figures associated with the determination of the combination the starting date and base temperature, and a comparison between the predicted and observed occurrence times
verbose	an optional argument allowing users to suppress the printing of computation progress

Details

When fig.opt is equal to TRUE, it will show the contours of the root-mean-square errors (RMSEs) based on different combinations of S and T_{0}.

\qquadThe function does not require that Year1 is the same as unique(Year2), and the intersection of the two vectors of years will be kept. The unused years that have phenological records but lack climate data will be showed in unused.years in the returned list.

\qquadThe numerical value of DOY.ul should be greater than or equal to the maximum Time.

Value

mAADD.mat	a matrix consisting of the means of the annual accumulated degree days (AADD) values from the combinations of S and T_{0}
RMSE.mat	the matrix consisting of the RMSEs (in days) from different combinations of S and T_{0}
AADD.arr	the AADD values in different years associated with the smallest value in RMSE.mat
Year	The overlapping years between Year1 and Year2
Time	The observed occurrence times (day-of-year) in the overlapping years between Year1 and Year2
Time.pred	the predicted occurrence times in different years
S	the determined starting date (day-of-year)
T0	the determined base temperature (in {}^{\circ}C)
AADD	the expected AADD
RMSE	the smallest RMSE (in days) in RMSE.mat from different combinations of S and T_{0}
unused.years	the years that have phenological records but lack climate data

Note

The entire mean daily temperature data set for the spring of each year should be provided. AADD is represented by the mean of AADD.arr in the output.

Author(s)

Peijian Shi [e-mail], Zhenghong Chen [e-mail], Jing Tan [e-mail], Brady K. Quinn [e-mail].

References

Aono, Y. (1993) Climatological studies on blooming of cherry tree (Prunus yedoensis) by means of DTS method. Bulletin of the University of Osaka Prefecture. Ser. B, Agriculture and life sciences 45, 155-192 (in Japanese with English abstract).

Konno, T., Sugihara, S. (1986) Temperature index for characterizing biological activity in soil and its application to decomposition of soil organic matter. Bulletin of National Institute for Agro-Environmental Sciences 1, 51-68 (in Japanese with English abstract).

Shi, P., Chen, Z., Reddy, G.V.P., Hui, C., Huang, J., Xiao, M. (2017a) Timing of cherry tree blooming: Contrasting effects of rising winter low temperatures and early spring temperatures. Agricultural and Forest Meteorology 240-241, 78-89. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.agrformet.2017.04.001")}

Shi, P., Fan, M., Reddy, G.V.P. (2017b) Comparison of thermal performance equations in describing temperature-dependent developmental rates of insects: (III) Phenological applications. Annals of the Entomological Society of America 110, 558-564. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/aesa/sax063")}

See Also

predADD

Examples

data(apricotFFD)
data(BJDAT)
X1 <- apricotFFD
X2 <- BJDAT

Year1.val  <- X1$Year
Time.val   <- X1$Time
Year2.val  <- X2$Year
DOY.val    <- X2$DOY
Temp.val   <- X2$MDT
DOY.ul.val <- 120
S.arr0     <- seq(60, 70, by = 1)
T0.arr0    <- seq(-2, 5, by = 1)


  RES1 <- ADD3( S.arr = S.arr0, T0.arr = T0.arr0, Year1 = Year1.val, Time = Time.val, 
                Year2 = Year2.val, DOY = DOY.val, Temp = Temp.val, DOY.ul = DOY.ul.val, 
                fig.opt = TRUE, verbose = TRUE)
  RES1

  RMSE.mat0  <- RES1$RMSE.mat
  RMSE.range <- range(RMSE.mat0)

  dev.new()
  par1 <- par(family="serif")
  par2 <- par(mar=c(5, 5, 2, 2))
  par3 <- par(mgp=c(3, 1, 0))
  image( S.arr0, T0.arr0, RMSE.mat0, col = terrain.colors(200), axes = TRUE, 
         cex.axis = 1.5, cex.lab = 1.5, xlab = "Starting date (day-of-year)", 
         ylab = expression(paste("Base temperature (", degree, "C)", sep = "")))
  points( RES1$S, RES1$T0, cex = 1.5, pch = 16, col = 2 )
  contour( S.arr0, T0.arr0, RMSE.mat0, levels = round(seq(RMSE.range[1], 
           RMSE.range[2], len = 20), 4), add = TRUE, cex = 1.5, col = "#696969", labcex = 1.5)
  par(par1)
  par(par2)
  par(par3)

  # graphics.off()

spphpr documentation built on June 20, 2025, 5:07 p.m.