gompertz_yield {decisionSupport}

Gompertz function yield prediction for perennials

Description

Yields of trees or other perennial plants have to be simulated in order to predict the outcomes of many interventions. Unlike annual crops, however, trees normally yield nothing for a few years after planting, following which yields gradually increase until they reach a tree-specific maximum. This is simulated with this function, which assumes that a Gompertz function is a good way to describe this (based on the general shape of the curve, not on extensive research...). The function assumes that yields remain at the maximum level, once this is reached. For long simulations, this may not be a valid assumption! The function parameters are estimated based on yield estimates for two points in time, which the user can specify. They are described by a year number and by a percentage of the maximum yield that is attained at that time.

Usage

gompertz_yield(
  max_harvest,
  time_to_first_yield_estimate,
  time_to_second_yield_estimate,
  first_yield_estimate_percent,
  second_yield_estimate_percent,
  n_years,
  var_CV = 0,
  no_yield_before_first_estimate = TRUE
)

Arguments

max_harvest

maximum harvest from the tree (in number of fruits, kg or other units)

time_to_first_yield_estimate

year (or other time unit) number, for which the first yield estimate is provided by first_yield_estimate_percent

time_to_second_yield_estimate

year (or other time unit) number, for which the second yield estimate is provided by second_yield_estimate_percent

first_yield_estimate_percent

percentage of the maximum yield that is attained in the year (or other time unit) given by time_to_first_yield_estimate

second_yield_estimate_percent

percentage of the maximum yield that is attained in the year (or other time unit) given by time_to_second_yield_estimate

n_years

number of years to run the simulation

var_CV

coefficient indicating how much variation should be introduced into the time series of n_targeted_per_year, annual_adoption_rate, perc_disadopt and spontaneous adoption. If this is one numeric value, then this value is used for all variables. If var_CV is a numeric vector with 4 elements, each of these is used to introduce variation in one of these variables (in the sequence: n_targeted_per_year, annual_adoption_rate, perc_disadopt and spontaneous adoption). The numbers correspond to the coefficient of variation that the resulting time series should have. The default is 0, for a time series with no artificially introduced variation. See description of the vv function for more details on this.

no_yield_before_first_estimate

boolean variable indicating whether yields before the time unit indicated by time_to_first_yield_estimate should be 0

Value

vector of n_years numeric values, describing the simulated yield of the perennial. This starts at 0 and, if the simulation runs for a sufficient number of years, approaches max_harvest. If var_CV>0, this time series includes artificial variation.

Author(s)

Eike Luedeling

Examples

gompertz_yield(max_harvest=1000,
               time_to_first_yield_estimate=5,
               time_to_second_yield_estimate=15,
               first_yield_estimate_percent=10,
               second_yield_estimate_percent=90,
               n_years=30,
               var_CV=5,
               no_yield_before_first_estimate=TRUE)