This is the organizer class for all disperse behaviors. More...
Inheritance diagram for sortie.tools.parfileupdater.DisperseBehaviors:
Public Member Functions | |
| DisperseBehaviors () | |
| Constructor. More... | |
 Public Member Functions inherited from sortie.tools.parfileupdater.GroupBase | |
| void | writeBehaviorsList (BufferedWriter jOut) throws IOException |
| void | writeDataToFile (BufferedWriter jOut) throws IOException |
| Writes all data to an XML file. More... | |
| ModelData | findObjectByXMLTag (String sXMLTag, String sXMLParentTag) |
| Finds an object based on its XML tag. More... | |
| boolean | setSingleValueByXMLTag (String sXMLTag, String sXMLParentTag, Attributes oAttributes, String sData) throws ModelException |
| Sets a data object's value. More... | |
| ArrayList< Behavior > | getBehaviorByXMLTag (String sXMLTag) |
| Finds a behavior by its XML tag. More... | |
| boolean | readXMLParentTag (String sXMLTag, Attributes oAttributes) throws ModelException |
| Accepts an XML parent tag (empty, no data) from the parser. More... | |
| void | endXMLParentTag (String sXMLTag) |
| boolean | parentTagOKForQueue (String sTag) |
| Some tags get everything messed up in a parsing queue. More... | |
Static Public Attributes | |
| static final int | WEIBULL = 0 |
| Weibull disperse function. More... | |
| static final int | LOGNORMAL = 1 |
| Lognormal disperse function. More... | |
| static final int | CANOPY = 0 |
| Canopy forest cover status for cells. More... | |
| static final int | GAP = 1 |
| Gap forest cover status for cells. More... | |
| static final int | NUMBER_OF_DISPERSE_FUNCTIONS = 2 |
| Total number of disperse functions. More... | |
| static final int | NUMBER_OF_FOREST_COVERS = 2 |
| Total number of forest cover statuses. More... | |
Protected Attributes | |
| ModelData [][] | mp_fSTR |
| STR for disperse function. More... | |
| ModelData [][] | mp_fBeta |
| Beta for disperse function. More... | |
| ModelData [][] | mp_fThetaOrXb |
| Theta (if weibull) or Xb (if lognormal) for disperse function. More... | |
| ModelData [][] | mp_fDispOrX0 |
| Dispersal (if weibull) or X0 (if lognormal) for disperse function. More... | |
| ModelData [] | mp_iWhichFunctionUsed |
| Which disperse function to use under each forest cover - valid values are WEIBULL and LOGNORMAL - this is a vector of ModelEnums. More... | |
| ModelData | mp_fSlopeOfLambda = new ModelData("di_nonSpatialSlopeOfLambda", "di_nssolVal") |
| Non-spatial disperse - slope of lambda for each species. More... | |
| ModelData | mp_fInterceptOfLambda = new ModelData("di_nonSpatialInterceptOfLambda", "di_nsiolVal") |
| Non-spatial disperse - intercept of lambda for each species. More... | |
| ModelData | mp_fMinDbhForReproduction = new ModelData("di_minDbhForReproduction", "di_mdfrVal") |
| Minimum DBH for reproduction for each species. More... | |
| ModelData | mp_fStumpSTR = new ModelData("di_suckerSTR", "di_ssVal") |
| STR for stump dispersal for each species. More... | |
| ModelData | mp_fStumpBeta = new ModelData("di_suckerBeta", "di_sbVal") |
| Beta for stump dispersal for each species. More... | |
| ModelData | mp_fStandardDeviation = new ModelData("di_standardDeviation", "di_sdVal") |
| Standard deviation if seed distribution method is normal or lognormal. More... | |
| ModelData | mp_fClumpingParameter = new ModelData("di_clumpingParameter", "di_cpVal") |
| Clumping parameter if seed distribution is negative binomial. More... | |
| ModelData | mp_fSpatialMastMastingA = new ModelData("di_mastCDFA", "di_mcdfaVal") |
| Masting spatial disperse - "a" for masting CDF. More... | |
| ModelData | mp_fSpatialMastMastingB = new ModelData("di_mastCDFB", "di_mcdfbVal") |
| Masting spatial disperse - "b" for masting CDF. More... | |
| ModelData | mp_iSpatialMastSTRDrawPDF = new ModelData("di_mastSTRPDF", "di_mstrpdfVal") |
| Masting spatial disperse - Probability distribution for STR draw. More... | |
| ModelData | mp_fSpatialMastNonMastSTRMean = new ModelData("di_spatialSTR", "di_sstrVal") |
| Masting spatial disperse - Non-mast STR mean. More... | |
| ModelData | mp_fSpatialMastNonMastSTRStdDev = new ModelData("di_spatialSTRStdDev", "di_sstrsdVal") |
| Masting spatial disperse - Non-mast STR draw standard deviation, if PDF = normal or lognormal. More... | |
| ModelData | mp_fSpatialMastMastSTRMean = new ModelData("di_mastingSTR", "di_mstrVal") |
| Masting spatial disperse - Masting STR mean. More... | |
| ModelData | mp_fSpatialMastMastSTRStdDev = new ModelData("di_mastingSTRStdDev", "di_mstrsdVal") |
| Masting spatial disperse - Masting STR draw standard deviation, if PDF = normal or lognormal. More... | |
| ModelData | mp_fSpatialMastNonMastBeta = new ModelData("di_spatialBeta", "di_sbVal") |
| Masting spatial disperse - Non-masting beta. More... | |
| ModelData | mp_fSpatialMastMastBeta = new ModelData("di_mastingBeta", "di_mbVal") |
| Masting spatial disperse - Masting beta. More... | |
| ModelData | mp_fSpatialMastMastWeibDisp = new ModelData("di_weibullMastingDispersal", "di_wmdVal") |
| Masting spatial disperse - Weibull masting dispersal. More... | |
| ModelData | mp_fSpatialMastMastWeibTheta = new ModelData("di_weibullMastingTheta", "di_wmtVal") |
| Masting spatial disperse - Weibull masting theta. More... | |
| ModelData | mp_fSpatialMastMastLognormalX0 = new ModelData("di_lognormalMastingX0", "di_lmx0Val") |
| Masting spatial disperse - Lognormal masting X0. More... | |
| ModelData | mp_fSpatialMastMastLognormalXb = new ModelData("di_lognormalMastingXb", "di_lmxbVal") |
| Masting spatial disperse - Lognormal masting Xb. More... | |
| ModelData | mp_iSpatialMastGroupID = new ModelData("di_mastGroup", "di_mgVal") |
| Masting spatial disperse - Group identification for each species. More... | |
| ModelData | mp_iSpatialMastDrawPerSpecies = new ModelData("di_mastDrawPerSpecies", "di_mdpsVal") |
| Masting spatial disperse - Whether to draw STR once per species (1) or once per tree (0) More... | |
| ModelData | mp_fSpatialMastMastPropParticipating = new ModelData("di_mastPropParticipating", "di_mppVal") |
| Masting spatial disperse - Proportion trees participating in disperse for mast event. More... | |
| ModelData | mp_fSpatialMastNonMastPropParticipating = new ModelData("di_spatialPropParticipating", "di_sppVal") |
| Masting spatial disperse - Proportion trees participating in disperse for non-mast event. More... | |
| ModelData | mp_iNonSpatialMastNonMastFunction = new ModelData("di_nonSpatialNonMastFunction", "di_nsnmfVal") |
| Masting non-spatial disperse - distribution function to pick seeds in non-mast conditions. More... | |
| ModelData | mp_fNonSpatialMastBinomialP = new ModelData("di_nonSpatialMastBinomialP", "di_nsmbpVal") |
| Masting non-spatial disperse - P parameter for binomial distribution for deciding whether to mast. More... | |
| ModelData | mp_iNonSpatialMastMastFunction = new ModelData("di_nonSpatialMastMastFunction", "di_nsmmfVal") |
| Masting non-spatial disperse - distribution function to pick seeds in mast conditions. More... | |
| ModelData | mp_fNonSpatialMastMastInvGaussMu = new ModelData("di_nonSpatialMastInvGaussMu", "di_nsmigmVal") |
| Masting non-spatial disperse - mu parameter for inverse gaussian distribution - mast conditions. More... | |
| ModelData | mp_fNonSpatialMastMastInvGaussLambda = new ModelData("di_nonSpatialMastInvGaussLambda", "di_nsmiglVal") |
| Masting non-spatial disperse - lambda parameter for inverse gaussian distribution - mast conditions. More... | |
| ModelData | mp_fNonSpatialMastNonMastInvGaussMu = new ModelData("di_nonSpatialNonMastInvGaussMu", "di_nsnmigmVal") |
| Masting non-spatial disperse - mu parameter for inverse gaussian distribution - non-mast conditions. More... | |
| ModelData | mp_fNonSpatialMastNonMastInvGaussLambda = new ModelData("di_nonSpatialNonMastInvGaussLambda", "di_nsnmiglVal") |
| Masting non-spatial disperse - lambda parameter for inverse gaussian distribution - non-mast conditions. More... | |
| ModelData | mp_fNonSpatialMastMastNormalMean = new ModelData("di_nonSpatialMastNormalMean", "di_nsmnmVal") |
| Masting non-spatial disperse - mean for normal distribution - mast conditions. More... | |
| ModelData | mp_fNonSpatialMastMastNormalStdDev = new ModelData("di_nonSpatialMastNormalStdDev", "di_nsmnsdVal") |
| Masting non-spatial disperse - standard deviation for normal distribution. More... | |
| ModelData | mp_fNonSpatialMastNonMastNormalMean = new ModelData("di_nonSpatialNonMastNormalMean", "di_nsnmnmVal") |
| Masting non-spatial disperse - mean for normal distribution - non-mast conditions. More... | |
| ModelData | mp_fNonSpatialMastNonMastNormalStdDev = new ModelData("di_nonSpatialNonMastNormalStdDev", "di_nsnmnsdVal") |
| Masting non-spatial disperse - standard deviation for normal distribution. More... | |
| ModelData | mp_iNonSpatialMastMastGroupID = new ModelData("di_nonSpatialMastGroup", "di_nsmgVal") |
| Masting non-spatial disperse - group identification for each species. More... | |
| ModelData | mp_fTempDepNeighM = new ModelData("di_tempDepNeighFecM", "di_tdnfmVal") |
| Temperature dependent neighborhood disperse - fecundity function M. More... | |
| ModelData | mp_fTempDepNeighN = new ModelData("di_tempDepNeighFecN", "di_tdnfnVal") |
| Temperature dependent neighborhood disperse - fecundity function N. More... | |
| ModelData | mp_fTempDepNeighPresM = new ModelData("di_tempDepNeighPresM", "di_tdnpmVal") |
| Temperature dependent neighborhood disperse - presence function M. More... | |
| ModelData | mp_fTempDepNeighPresB = new ModelData("di_tempDepNeighPresB", "di_tdnpbVal") |
| Temperature dependent neighborhood disperse - presence function B. More... | |
| ModelData | mp_fTempDepNeighPresThreshold = new ModelData("di_tempDepNeighPresThreshold", "di_tdnptVal") |
| Temperature dependent neighborhood disperse - presence threshold. More... | |
| ModelData | mp_fTempDepNeighA = new ModelData("di_tempDepNeighA", "di_tdnaVal") |
| Temperature dependent neighborhood disperse - A. More... | |
| ModelData | mp_fTempDepNeighB = new ModelData("di_tempDepNeighB", "di_tdnbVal") |
| Temperature dependent neighborhood disperse - B. More... | |
| ModelData | m_fTempDepNeighMaxRadius = new ModelData("di_tempDepNeighRadius") |
| Temperature dependent neighborhood disperse - maximum search radius, in meters, for neighbors. More... | |
| ModelData | m_iSeedDistributionMethod = new ModelData("di_seedDistributionMethod") |
| Seed distribution. More... | |
| ModelData | m_iMaxGapDensity = new ModelData("di_maxGapDensity") |
| Max number of parent trees that can be in a grid cell for it to still be marked as gap. More... | |
| Protected Attributes inherited from sortie.tools.parfileupdater.GroupBase | |
| ArrayList< ModelData > | mp_oAllData |
| All data for this object. More... | |
| String | m_sXMLTag |
| Highest-level XML tag for this object. More... | |
| Behavior [] | mp_oChildBehaviors |
Additional Inherited Members | |
| Protected Member Functions inherited from sortie.tools.parfileupdater.GroupBase | |
| void | loadDataMember (ModelData oData) |
| Takes some data and adds it to all applicable behaviors in their string buffer. More... | |
Detailed Description
This is the organizer class for all disperse behaviors.
Copyright: Copyright (c) Charles D. Canham 2003
Company: Institute of Ecosystem Studies
- Version
- 1.0
Edit history:
---------------—
April 28, 2004: Submitted in beta version (LEM)
April 24, 2007: Added masting spatial disperse (LEM)
August 19, 2008: Added masting non-spatial disperse (LEM)
Constructor & Destructor Documentation
◆ DisperseBehaviors()
| sortie.tools.parfileupdater.DisperseBehaviors.DisperseBehaviors | ( | ) |
Constructor.
Member Data Documentation
◆ CANOPY
|
static |
Canopy forest cover status for cells.
◆ GAP
|
static |
Gap forest cover status for cells.
◆ LOGNORMAL
|
static |
Lognormal disperse function.
◆ m_fTempDepNeighMaxRadius
|
protected |
Temperature dependent neighborhood disperse - maximum search radius, in meters, for neighbors.
◆ m_iMaxGapDensity
|
protected |
Max number of parent trees that can be in a grid cell for it to still be marked as gap.
◆ m_iSeedDistributionMethod
|
protected |
Seed distribution.
◆ mp_fBeta
|
protected |
Beta for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.
◆ mp_fClumpingParameter
|
protected |
Clumping parameter if seed distribution is negative binomial.
◆ mp_fDispOrX0
|
protected |
Dispersal (if weibull) or X0 (if lognormal) for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.
◆ mp_fInterceptOfLambda
|
protected |
Non-spatial disperse - intercept of lambda for each species.
◆ mp_fMinDbhForReproduction
|
protected |
Minimum DBH for reproduction for each species.
◆ mp_fNonSpatialMastBinomialP
|
protected |
Masting non-spatial disperse - P parameter for binomial distribution for deciding whether to mast.
◆ mp_fNonSpatialMastMastInvGaussLambda
|
protected |
Masting non-spatial disperse - lambda parameter for inverse gaussian distribution - mast conditions.
◆ mp_fNonSpatialMastMastInvGaussMu
|
protected |
Masting non-spatial disperse - mu parameter for inverse gaussian distribution - mast conditions.
◆ mp_fNonSpatialMastMastNormalMean
|
protected |
Masting non-spatial disperse - mean for normal distribution - mast conditions.
◆ mp_fNonSpatialMastMastNormalStdDev
|
protected |
Masting non-spatial disperse - standard deviation for normal distribution.
- mast conditions
◆ mp_fNonSpatialMastNonMastInvGaussLambda
|
protected |
Masting non-spatial disperse - lambda parameter for inverse gaussian distribution - non-mast conditions.
◆ mp_fNonSpatialMastNonMastInvGaussMu
|
protected |
Masting non-spatial disperse - mu parameter for inverse gaussian distribution - non-mast conditions.
◆ mp_fNonSpatialMastNonMastNormalMean
|
protected |
Masting non-spatial disperse - mean for normal distribution - non-mast conditions.
◆ mp_fNonSpatialMastNonMastNormalStdDev
|
protected |
Masting non-spatial disperse - standard deviation for normal distribution.
- non-mast conditions
◆ mp_fSlopeOfLambda
|
protected |
Non-spatial disperse - slope of lambda for each species.
◆ mp_fSpatialMastMastBeta
|
protected |
Masting spatial disperse - Masting beta.
◆ mp_fSpatialMastMastingA
|
protected |
Masting spatial disperse - "a" for masting CDF.
◆ mp_fSpatialMastMastingB
|
protected |
Masting spatial disperse - "b" for masting CDF.
◆ mp_fSpatialMastMastLognormalX0
|
protected |
Masting spatial disperse - Lognormal masting X0.
◆ mp_fSpatialMastMastLognormalXb
|
protected |
Masting spatial disperse - Lognormal masting Xb.
◆ mp_fSpatialMastMastPropParticipating
|
protected |
Masting spatial disperse - Proportion trees participating in disperse for mast event.
◆ mp_fSpatialMastMastSTRMean
|
protected |
Masting spatial disperse - Masting STR mean.
◆ mp_fSpatialMastMastSTRStdDev
|
protected |
Masting spatial disperse - Masting STR draw standard deviation, if PDF = normal or lognormal.
◆ mp_fSpatialMastMastWeibDisp
|
protected |
Masting spatial disperse - Weibull masting dispersal.
◆ mp_fSpatialMastMastWeibTheta
|
protected |
Masting spatial disperse - Weibull masting theta.
◆ mp_fSpatialMastNonMastBeta
|
protected |
Masting spatial disperse - Non-masting beta.
◆ mp_fSpatialMastNonMastPropParticipating
|
protected |
Masting spatial disperse - Proportion trees participating in disperse for non-mast event.
◆ mp_fSpatialMastNonMastSTRMean
|
protected |
Masting spatial disperse - Non-mast STR mean.
◆ mp_fSpatialMastNonMastSTRStdDev
|
protected |
Masting spatial disperse - Non-mast STR draw standard deviation, if PDF = normal or lognormal.
◆ mp_fStandardDeviation
|
protected |
Standard deviation if seed distribution method is normal or lognormal.
◆ mp_fSTR
|
protected |
STR for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.
◆ mp_fStumpBeta
|
protected |
Beta for stump dispersal for each species.
◆ mp_fStumpSTR
|
protected |
STR for stump dispersal for each species.
◆ mp_fTempDepNeighA
|
protected |
Temperature dependent neighborhood disperse - A.
◆ mp_fTempDepNeighB
|
protected |
Temperature dependent neighborhood disperse - B.
◆ mp_fTempDepNeighM
|
protected |
Temperature dependent neighborhood disperse - fecundity function M.
◆ mp_fTempDepNeighN
|
protected |
Temperature dependent neighborhood disperse - fecundity function N.
◆ mp_fTempDepNeighPresB
|
protected |
Temperature dependent neighborhood disperse - presence function B.
◆ mp_fTempDepNeighPresM
|
protected |
Temperature dependent neighborhood disperse - presence function M.
◆ mp_fTempDepNeighPresThreshold
|
protected |
Temperature dependent neighborhood disperse - presence threshold.
◆ mp_fThetaOrXb
|
protected |
Theta (if weibull) or Xb (if lognormal) for disperse function.
Array is 3D - first index is which disperse function is used - weibull or lognormal. The second index is cover - canopy or gap. The third index is species.
◆ mp_iNonSpatialMastMastFunction
|
protected |
Masting non-spatial disperse - distribution function to pick seeds in mast conditions.
◆ mp_iNonSpatialMastMastGroupID
|
protected |
Masting non-spatial disperse - group identification for each species.
◆ mp_iNonSpatialMastNonMastFunction
|
protected |
Masting non-spatial disperse - distribution function to pick seeds in non-mast conditions.
◆ mp_iSpatialMastDrawPerSpecies
|
protected |
Masting spatial disperse - Whether to draw STR once per species (1) or once per tree (0)
◆ mp_iSpatialMastGroupID
|
protected |
Masting spatial disperse - Group identification for each species.
◆ mp_iSpatialMastSTRDrawPDF
|
protected |
Masting spatial disperse - Probability distribution for STR draw.
◆ mp_iWhichFunctionUsed
|
protected |
Which disperse function to use under each forest cover - valid values are WEIBULL and LOGNORMAL - this is a vector of ModelEnums.
◆ NUMBER_OF_DISPERSE_FUNCTIONS
|
static |
Total number of disperse functions.
◆ NUMBER_OF_FOREST_COVERS
|
static |
Total number of forest cover statuses.
◆ WEIBULL
|
static |
Weibull disperse function.
The documentation for this class was generated from the following file:
