phen_model_forecast: Multi-Year Forecast Based on the Phenology Model

Description

A forecast based on the phenology model for multiple years, based on daily temperatures.

Usage

phen_model_forecast(Tmean, thermal_units, chill_days, day_length,
                    bud_pars, weib_pars, lactin_pars,
                    max_day_length = 14.92, pop_quantile, year, data)

Arguments

Tmean

name of the column in the data representing the mean temperature

thermal_units

name of the column in the data representing the thermal units

chill_days

name of the column in the data representing the number of chill days

day_length

name of the column in the data representing the day length

bud_pars

vector of parameters for the budburst model

weib_pars

matrix of parameters for the Weibull model for each developmental stage

lactin_pars

matrix of parameters for the lactin model for each developmental stage

max_day_length

critical day length threshold

pop_quantile

quantile of the population to be evaluated by the phenology model

year

a vector of indices representing each yearly cycle (usually the output from get_cycle)

data

a data.frame

Value

A data.frame with the number of rows equal to the total number of yearly cycles, and each column representing the developmental stage of the insect.

Details

See phen_model

Examples

Run this code

# NOT RUN {
data(valentia)

valentia$cycle <- get_cycle(data = valentia, day = "day", month = "month",
                            day.end = 31, month.end = 10)
valentia_split <- split(valentia, valentia$cycle)
valentia_split <- lapply(valentia_split,
                         function(x) data.frame(x,
                                                with(x, get_total_info(Tmax = x$max_temp,
                                                                       Tmin = x$min_temp,
                                                                       Tbase = 7,
                                                                       lat = x$Lat,
                                                                       x$day_of_year))))
valentia <- do.call("rbind", valentia_split)

data(pvulg_budburst_parameters)
data(pvulg_weibull_parameters)
data(pvulg_lactin_parameters)

phen_forecast <- phen_model_forecast(Tmean = "Tmean",
                                     thermal_units = "thermal_units",
                                     chill_days = "chill_days",
                                     day_length = "day_length",
                                     bud_pars = pvulg_budburst_parameters,
                                     weib_pars = pvulg_weibull_parameters,
                                     lactin_pars = pvulg_lactin_parameters,
                                     pop_quantile = .5,
                                     year = "cycle",
                                     data = valentia)
# }