Inheritance diagram for javawrapper::DisperseBehaviors:

Public Member Functions | |
| DisperseBehaviors (GUIManager oManager) | |
| Constructor. | |
| void | DoSetup (TreePopulation oPop) throws ModelException |
| Does setup. | |
| void | ValidateData (TreePopulation oPop) throws ModelException |
| Validates the data in preparation for parameter file writing or some such. | |
| void | ChangeOfSpeciesName (String sOldSpecies, String sNewSpecies) throws ModelException |
| Changes the names in the grids. | |
Static Public Attributes | |
| static final int | WEIBULL = 0 |
| static final int | LOGNORMAL = 1 |
| static final int | CANOPY = 0 |
| static final int | GAP = 1 |
| static final int | NUMBER_OF_DISPERSE_FUNCTIONS = 2 |
| static final int | NUMBER_OF_FOREST_COVERS = 2 |
Private Attributes | |
| ModelVector[][] | mp_fSTR |
| STR for disperse function. | |
| ModelVector[][] | mp_fBeta |
| Beta for disperse function. | |
| ModelVector[][] | mp_fThetaOrXb |
| Theta (if weibull) or Xb (if lognormal) for disperse function. | |
| ModelVector[][] | mp_fDispOrX0 |
| Dispersal (if weibull) or X0 (if lognormal) for disperse function. | |
| ModelVector[] | mp_iWhichFunctionUsed |
| Which disperse function to use under each forest cover - valid values are WEIBULL and LOGNORMAL - this is a vector of ModelEnums. | |
| ModelVector | mp_fSlopeOfLambda |
| Slope of lambda for non spatial dispersal for each species. | |
| ModelVector | mp_fInterceptOfLambda |
| Intercept of lambda for non spatial dispersal for each species. | |
| ModelVector | mp_fMinDbhForReproduction |
| Minimum DBH for reproduction for each species. | |
| ModelVector | mp_fStumpSTR |
| STR for stump dispersal for each species. | |
| ModelVector | mp_fStumpBeta |
| Beta for stump dispersal for each species. | |
| ModelVector | mp_fDirectionMaxDispersal |
| Azimuth direction of maximum dispersal distance, in radians. | |
| ModelVector | mp_fAnisotropicAmplitude |
| Amplitude of anisotropic effect. | |
| ModelVector | mp_fStandardDeviation |
| Standard deviation if seed distribution method is normal or lognormal. | |
| ModelVector | mp_fClumpingParameter |
| Clumping parameter if seed distribution is negative binomial. | |
| ModelEnum | m_iSeedDistributionMethod |
| Seed distribution. | |
| ModelFloat | m_fMaxSearchRadius |
| Maximum search radius, in meters, for neighbors for isotropic and anisotropic disperse. | |
| ModelInt | m_iMaxGapDensity |
| Max number of parent trees that can be in a grid cell for it to still be marked as gap. | |
Copyright: Copyright (c) Charles D. Canham 2003
Company: Institute of Ecosystem Studies
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Constructor.
Edit history: ------------------ April 28, 2004: Submitted in beta version (LEM) |
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Changes the names in the grids.
Reimplemented from javawrapper::WorkerBase. |
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Does setup. Sets up the substrate favorability grid.
Edit history: ------------------ April 28, 2004: Submitted in beta version (LEM) Implements javawrapper::WorkerBase. |
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Validates the data in preparation for parameter file writing or some such.
Edit history: ------------------ April 28, 2004: Submitted in beta version (LEM) Implements javawrapper::WorkerBase. |
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Initial value: new ModelFloat(0, "Maximum Search Distance for Neighbor Parents, in m", "di_maxSearchRadius")
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Initial value: new ModelInt(0, "Maximum Parent Trees Allowed in Gap Cell", "di_maxGapDensity")
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Initial value:
new ModelEnum(new int[] {0, 1, 2, 3, 4}
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new String[] {"Deterministic", "Poisson", "Lognormal",
"Normal", "Negative binomial"}
, "Seed Distribution", "di_seedDistributionMethod")
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Initial value: new ModelVector( "Amplitude of Anisotropic Effect", "di_anisotropicAmplitude", "di_aaVal", 0, ModelVector.FLOAT)
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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. |
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Initial value: new ModelVector( "Seed Dist. Clumping Parameter (Neg. Binomial)", "di_clumpingParameter", "di_cpVal", 0, ModelVector.FLOAT)
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Initial value: new ModelVector( "Azimuth Direction of Max Dispersal Distance, in rad", "di_directionMaxDispersal", "di_dmdVal", 0, ModelVector.FLOAT)
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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. |
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Initial value: new ModelVector( "Intercept of Mean Non-Spatial Seed Rain, seeds/m2/yr", "di_nonSpatialInterceptOfLambda", "di_nsiolVal", 0, ModelVector.FLOAT)
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Initial value: new ModelVector( "Slope Mean Non-Spatial Seed Rain, seeds/m2/ha of BA/yr", "di_nonSpatialSlopeOfLambda", "di_nssolVal", 0, ModelVector.FLOAT)
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Initial value: new ModelVector( "Seed Dist. Std. Deviation (Normal or Lognormal)", "di_standardDeviation", "di_sdVal", 0, ModelVector.FLOAT)
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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. |
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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. |
1.4.6-NO