Package 'LandR.CS'

Title: Climate-sensitive Growth and Mortality in LandR
Description: This package contains climate-sensitive growth and mortality function for LandR. Some flexibility exists in how climate-sensitivity is derived, however the simplest and most robust method is to use the SpaDES module 'gmcsDataPrep' and R package 'PSPclean'.
Authors: Ian Eddy [aut, cre] , Alex M Chubaty [ctb] , Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Ian Eddy <[email protected]>
License: GPL-3
Version: 0.0.3.9003
Built: 2024-10-17 06:34:52 UTC
Source: https://github.com/ianmseddy/LandR.CS

Help Index

LandR.CS package

Description

Utilities for 'LandR.CS' suite of landscape simulation models. These functions incorporate climate sensitivity into LandR processes.

Details

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Package options

LandR.CS packages use the following options to configure behaviour:

  • LandR.assertions: If TRUE, additional code checks are run during function calls. Default FALSE.

Author(s)

Maintainer: Ian Eddy [email protected] (ORCID)

Other contributors:

  • Alex M Chubaty [email protected] (ORCID) [contributor]

  • Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada [copyright holder]

See Also

Useful links:

Calculate climate effect

Description

Predict biomass change with climate variables

Usage

calculateClimateEffect(
  cohortData,
  pixelGroupMap,
  cceArgs,
  year,
  gmcsGrowthLimits,
  gmcsMortLimits,
  gmcsMinAge,
  cohortDefinitionCols = c("age", "speciesCode", "pixelGroup")
)

Arguments

cohortData

The LandR cohortData object
pixelGroupMap

the pixelGroupMap needed to match cohorts with raster values
cceArgs

a list of datasets used by the climate function
year

time of simulation - used to select from list of projected climate rasters
gmcsGrowthLimits

lower and upper limits to the effect of climate on growth
gmcsMortLimits

lower and upper limits to the effect of climate on mortality
gmcsMinAge

minimum age for which to predict full effect of growth/mortality - younger ages are weighted toward a null effect with decreasing age
cohortDefinitionCols

cohortData columns that determine individual cohorts

gamlss.own

Description

the definition of the backfitting additive function

Usage

gamlss.own(x, y, w, xeval = NULL)

Arguments

x

description missing
y

description missing
w

description missing
xeval

description missing

Author(s)

Mikis Stasinopoulos and Marco Enea

own

Description

for predicting from gamlss with no random effect

Usage

own(
  fixed = ~1,
  random = NULL,
  correlation = NULL,
  method = "ML",
  level = NULL,
  ...
)

Arguments

fixed

the fixed terms
random

the random terms
correlation

this is the correlation structure?
method

TODO: Description needed
level

the marginal or conditional predictor
...

additional arguments passed to lmeCcontrol