LWFBrook90R (version 0.6.3)

make_seasLAI: Construct the seasonal course of leaf area index from parameters

Description

A daily sequence of leaf area index is derived from maximum and minimum values, dates and shape parameters using different methods.

Usage

make_seasLAI(
  method = "b90",
  years,
  maxlai,
  winlaifrac = 0,
  budburst_doy = 121,
  leaffall_doy = 279,
  emerge_dur = 28,
  leaffall_dur = 58,
  shp_optdoy = budburst_doy + emerge_dur,
  shp_budburst = 0.5,
  shp_leaffall = 10,
  lai_doy_table = data.frame(lai_doy = c(1, 121, 150, 280, 320, 365), lai_frac = c(0, 0,
    0.5, 1, 0.5, 0))
)

Value

A vector of daily lai values covering the years specified.

Arguments

method

Name of method for generating the sequence. Must be one of "b90", "linear", "Coupmodel".

years

Vector of years to be returned.

maxlai

Maximum leaf are index.

winlaifrac

Fraction of maxlai during winter (ignored when method = 'linear').

budburst_doy

Budburst day of year (ignored when method = 'linear').

leaffall_doy

Day of year when leaf fall begins (ignored when method = 'linear').

emerge_dur

Number of days from budburst until maximum leaf area index is reached.

leaffall_dur

Number of days until minimum leaf are index is reached.

shp_optdoy

Day of year when optimum value is reached (required when method = "Coupmodel").

shp_budburst

Shape parameter for the growth phase (required when method = "Coupmodel").

shp_leaffall

Shape parameter growth cessation (required when method = "Coupmodel").

lai_doy_table

Data.frame with day of year ('doy') and LAI fraction values ('lai_frac'), required when method = "linear"). Can be provided as a single data.frame or a list of data.frames with one entry for each year of the simulation.

Examples

# Intraannual courses of leaf area index
lai_b90 <- make_seasLAI(method = "b90",
                       year = 2001,
                       maxlai = 5,
                       winlaifrac = 0,
                       budburst_doy = 121,
                       leaffall_doy = 280,
                       emerge_dur = 15,
                       leaffall_dur = 30)

lai_doy_table <- data.frame(lai_doy = c(1,110,117,135,175,220,250,290,365),
                            lai_frac = c(0.1,0.1,0.5,0.7,1.2,1.2,1.0,0.1,0.1))
lai_linear <- make_seasLAI(method = "linear",
                          year = 2001,
                          maxlai = 5,
                          lai_doy_table = lai_doy_table)

lai_coupmodel <- make_seasLAI(method = "Coupmodel",
                             year = 2001,
                             maxlai = 5,
                             winlaifrac = 0.05,
                             budburst_doy = 100,
                             leaffall_doy = 280,
                             shp_optdoy = 180,
                             shp_budburst = 0.5,
                             shp_leaffall = 5)

plot(lai_b90, type = "n", xlab = "doy", ylab = "lai [m²/m²]", ylim = c(0,6))
lines(lai_b90, col ="green",lwd = 2,)
lines(lai_linear, col ="red",lwd = 2)
lines(lai_coupmodel, col ="blue",lwd = 2)

# incorparating between-year variability
years <- 2002:2004
lai <- make_seasLAI(method = "Coupmodel",
                   year = years,
                   maxlai = c(4,6,5),
                   budburst_doy = c(100,135,121),
                   leaffall_doy = 280,
                   shp_budburst = c(3,1,0.3),
                   shp_leaffall = 3,
                   shp_optdoy =c(210,180,240) )

dates <- seq.Date(as.Date("2002-01-01"), as.Date("2004-12-31"), by = "day")
plot(dates,lai, col = "green", ylab = "lai [m²/m²]",
     type ="l", xlab = "", lwd = 2)

# doy/value-tables
lai_linear1 <- make_seasLAI(method = "linear",
                    year = years,
                    maxlai = c(4,6,5),
                    lai_doy_table = lai_doy_table)

plot(dates,lai_linear1, col = "green", ylab = "lai [m²/m²]",
     type ="l", xlab = "", lwd = 2)

# linear interpolation for lists of annual tables
lai_doy_table_l <- list("2002" = data.frame(lai_doy = c(1,90,97,115,155,200,230,270,365),
                                          lai_frac = c(0.1,0.1,0.5,0.7,1.2,1.2,1.0,0.1,0.1)),
                        "2003" = data.frame(lai_doy = c(1,100,107,125,165,210,240,280,365),
                                          lai_frac = c(0.1,0.1,0.5,0.7,1.2,1.2,1.0,0.1,0.1)),
                        "2004"= data.frame(lai_doy = c(1,110,117,135,175,220,250,290,365),
                                           lai_frac = c(0.1,0.1,0.5,0.7,1.2,1.2,1.0,0.1,0.1)))

lai_linear2 <- make_seasLAI(method = "linear",
                    year = years,
                    maxlai = c(4,6,5),
                    lai_doy_table = lai_doy_table_l)

lines(dates,lai_linear2, col = "darkgreen", ylab = "lai [m²/m²]",
     type ="l", xlab = "", lwd = 2)