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Diameter correction

Source: R/DiameterCorrection.R
DiameterCorrection.Rd

Diameter correction

Usage

DiameterCorrection(
  Data,
  UseTaperCorrection = TRUE,
  DefaultHOM = 1.3,
  TaperParameter = function(DAB, HOM) 0.156 - 0.023 * log(DAB) - 0.021 * log(HOM),
  TaperFormula = function(DAB, HOM, TaperParameter, DefaultHOM) DAB/(exp(-TaperParameter
    * (HOM - DefaultHOM))),
  KeepMeas = c("MaxHOM", "MaxDate"),
  MinDBH = NULL,
  AddMissedRecruits = TRUE,
  AddMissedStems = TRUE,
  PositiveGrowthThreshold = 5,
  NegativeGrowthThreshold = -2,
  Pioneers = NULL,
  PioneersGrowthThreshold = 7.5,
  WhatToCorrect = c("POM change", "Abnormal growth"),
  CorrectionType = c("individual", "phylogenetic hierarchical"),
  DBHRange = 10,
  MinIndividualNbr = 5,
  DBHCorForDeadTrees = TRUE,
  coef = 0.9
)

Arguments

Data

Dataset (data.frame or data.table) The dataset must contain the columns:

  • IdTree or IdStem (character)

  • ScientificName_DataHarmonizationCor (character)

  • Diameter (numeric)

  • IdCensus (ordered factor)

  • POM (Point Of Measurement) (factor) or HOM (Height Of Measurement) (numeric) if you want to correct from the "POM change" If you want to apply the "phylogenetic hierarchical" correction, the dataset must also contain the columns:

  • Genus_DataHarmonizationCor (character)

  • Family_DataHarmonizationCor (character)

UseTaperCorrection

(logical) TRUE: transform the tree diameter measured at a given height into the diameter corresponding to the default measurement height (DefaultHOM), using an allometry. FALSE: do not apply a taper correction

DefaultHOM

Default Height Of Measurement in meter (Default: 1.3 m) (numeric, 1 value)

TaperParameter

Taper parameter (unitless) formula (function) Default: TaperParameter = 0.156 - 0.023 log(DAB) - 0.021 log(HOM) of Cushman et al.2021. With:

  • DAB: Diameter Above Buttress (in cm)

  • HOM: Height Of Measurement (in m)

TaperFormula

Taper formula (function) Default: DAB / (e^(- TaperParameter (HOM - DefaultHOM))) of Cushman et al.2021. With:

  • DAB: Diameter Above Buttress (in cm)

  • HOM: Height Of Measurement (in m)

  • DefaultHOM: Default Height Of Measurement (in m)

  • TaperParameter: Taper parameter (unitless)

KeepMeas

In case of multiple diameter measurements in the same census: Possible values: "MaxHOM", "MaxDate" (character).

  • "MaxHOM": apply the correction to the measurement taken at the highest POM

  • "MaxDate": apply the correction to the most recent measurement (same IdCensus but more recent date)

MinDBH

Minimum diameter of trees inventoried (in cm) (numeric, 1 value) or NULL (Default) if you wish to use the MinDBH indicated in your data, which may vary per plot

AddMissedRecruits

(logical) TRUE: adds rows for stem that were supposed to be recruited at a prior census, based on their estimated diameter (from linear regression) and MinDBH. FALSE: will only indicate in the comment that the stem was supposed to be recruited earlier.

AddMissedStems

(logical) if TRUE, adds rows for trees that were missed between two censuses, with their estimated diameter (based on linear regression)

PositiveGrowthThreshold

in cm/year: a tree widening by more than this value is considered abnormal (numeric, 1 value)

NegativeGrowthThreshold

in cm/census: the possible positive measurement error (+n) cannot be corrected until the growth appears abnormal, but a negative measurement error can be allowed until -n (a tree does not decrease). Thus the positive measurement error (+n) is "compensated". (numeric, 1 value)

Pioneers

Scientific names of the pioneer species of the site, as in the ScientificName_DataHarmonizationCor column (characters vector)

PioneersGrowthThreshold

in cm/year: a tree of a pioneer species that widens by more than this value is considered abnormal (numeric, 1 value)

WhatToCorrect

Possible values: "POM change", "Abnormal growth" (character). All are complementary and recommended.

  • "POM change": detect POM change in the column POM and correct the Diameter values from it. (Ignored if taper correction is applied)

  • "Abnormal growth": detect if the growth is greater than PositiveGrowthThreshold ('PioneersGrowthThreshold' if species belongs to 'Pioneers') or smaller than NegativeGrowthThreshold and correct it by CorrectionType

CorrectionType

Possible values: "individual", "phylogenetic hierarchical" (character, 1 value).

  • "individual": replace abnormal growth by interpolation from the individual values.

  • "phylogenetic hierarchical": replace abnormal growth with the average growth of other trees in the dataset, at the specific, genus, family or stand level, within a DBH range of x cm (DBHRange argument). If the number of these trees < n (MinIndividualNbr argument) at the specific level, we switch to the genus level etc.

DBHRange

DBH range in cm to take into account to select other trees in the dataset to apply "phylogenetic hierarchical" correction (Default: 10 cm) (numeric, 1 value)

MinIndividualNbr

Minimum number of individuals to take into account in "phylogenetic hierarchical" correction (Default: 5) (numeric, 1 value)

DBHCorForDeadTrees

(logical) TRUE: return DBHCor also for dead trees. FALSE: do not return DBHCor for dead trees. In this case it is advisable to have corrected the tree life status with the StatusCorrection() function.

coef

(numeric, 1 value) This is used in individual corrections, to calculate weight of the growths by temporal proximity

Value

Fill the Comment_DataHarmonization column with error type information and add columns:

  • Diameter_DataHarmonizationCor: corrected trees diameter at default HOM

  • DiameterCorrectionMeth_DataHarmonization = "local linear regression","weighted mean"/phylogenetic hierarchical("species"/"genus"/"family"/"stand")/ "shift realignment"/"Same value".

  • POM_DataHarmonizationCor (factor): POM value at which the corrected diameters are proposed. Corresponds to the 1st POM value at which the stem was measured.

  • HOM_DataHarmonizationCor (numeric): HOM value at which the corrected diameters are proposed. Corresponds to the 1st HOM value at which the stem was measured.

  • MissedStem_DataHarmonizationCor if AddMissedStems is TRUE (with value TRUE for new rows).

  • MissedRecruit_DataHarmonizationCor if AddMissedRecruits is TRUE (with value TRUE for new rows).

Details

When there is only 1 Diameter value for a tree/stem, Diameter_DataHarmonizationCor takes the original Diameter value. If this value is 0 or > MaxDBH, Diameter_DataHarmonizationCor takes NA. Diameters not linked to an IdTree/IdStem or to a Census IdCensus are not processed. Punctual error correction only with linear regression and not quadratic, because punctual errors are corrected from a local regression with the 2 framing values.

Examples

# library(data.table)
data(TestData)

TestData$HOM[1:3] <- c(0.5,1.5,NA)
TestData$Diameter[21:23] <- c(31,91,14)
TestData <- TestData[!(IdStem %in% "100658_1_auto" & IdCensus %in% 2017), ]

Rslt <- DiameterCorrection(
 TestData,
  WhatToCorrect = c("POM change", "Abnormal growth"),
    CorrectionType = c("phylo"),
    MinIndividualNbr = 1)
#> Warning: We added rows for trees that were supposed to be recruited earlier based on linear extrapolation of growth and MinDBH
#> We added rows for trees that were missed and estimated their missed DBH by linear interpolation

DiameterCorrectionPlot(Rslt, OnlyCorrected = TRUE)
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: The shape palette can deal with a maximum of 6 discrete values because more
#> than 6 becomes difficult to discriminate
#> ℹ you have requested 7 values. Consider specifying shapes manually if you need
#>   that many have them.
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_point()`).