Title: | Climate-sensitive Growth and Mortality in LandR |
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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: | 2024-11-25 23:23:06 UTC |
Source: | https://github.com/ianmseddy/LandR.CS |
LandR.CS
packageUtilities for 'LandR.CS' suite of landscape simulation models. These functions incorporate climate sensitivity into LandR processes.
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LandR.CS
packages use the following options
to configure behaviour:
LandR.assertions
: If TRUE
, additional code checks are run
during function calls. Default FALSE
.
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]
Useful links:
Predict biomass change with climate variables
calculateClimateEffect( cohortData, pixelGroupMap, cceArgs, year, gmcsGrowthLimits, gmcsMortLimits, gmcsMinAge, cohortDefinitionCols = c("age", "speciesCode", "pixelGroup") )
calculateClimateEffect( cohortData, pixelGroupMap, cceArgs, year, gmcsGrowthLimits, gmcsMortLimits, gmcsMinAge, cohortDefinitionCols = c("age", "speciesCode", "pixelGroup") )
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 |
the definition of the backfitting additive function
gamlss.own(x, y, w, xeval = NULL)
gamlss.own(x, y, w, xeval = NULL)
x |
description missing |
y |
description missing |
w |
description missing |
xeval |
description missing |
Mikis Stasinopoulos and Marco Enea
for predicting from gamlss with no random effect
own( fixed = ~1, random = NULL, correlation = NULL, method = "ML", level = NULL, ... )
own( fixed = ~1, random = NULL, correlation = NULL, method = "ML", level = NULL, ... )
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 |