public static List <InputModelState> ConvertModelStates(
Madingley.Common.ModelState modelState,
Madingley.Common.Configuration c,
Madingley.Common.Environment e)
{
var numLatCells = (UInt32)((e.TopLatitude - e.BottomLatitude) / e.CellSize);
var numLonCells = (UInt32)((e.RightmostLongitude - e.LeftmostLongitude) / e.CellSize);
// Set up a grid of grid cells
var gridCellCohorts = new GridCellCohortHandler[numLatCells, numLonCells];
var gridCellStocks = new GridCellStockHandler[numLatCells, numLonCells];
gridCellCohorts[0, 0] = new GridCellCohortHandler(c.CohortFunctionalGroupDefinitions.Data.Count());
var cellList = e.FocusCells.ToArray();
var gridCells = modelState.GridCells.ToArray();
for (var ii = 0; ii < cellList.Count(); ii++)
{
var gridCell = gridCells[ii];
gridCellCohorts[cellList[ii].Item1, cellList[ii].Item2] = ConvertCohorts(gridCell.Cohorts);
gridCellStocks[cellList[ii].Item1, cellList[ii].Item2] = ConvertStocks(gridCell.Stocks);
}
var inputModelState = new InputModelState(gridCellCohorts, gridCellStocks);
return(new List <InputModelState>()
{
inputModelState
});
}
/// <summary>
/// Run metabolism
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="trackProcesses">An instance of ProcessTracker to hold diagnostics for metabolism</param>
/// <param name="partial">Thread-locked variables</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="outputDetail">The level of output detail being used for the current model run</param>
/// <param name="currentMonth">The current model month</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
public void RunEcologicalProcess(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> > deltas,
FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, ProcessTracker trackProcesses, ref ThreadLockedParallelVariables partial,
Boolean specificLocations, string outputDetail, uint currentMonth, MadingleyModelInitialisation initialisation)
{
double Realm = cellEnvironment["Realm"][0];
if (madingleyCohortDefinitions.GetTraitNames("Heterotroph/Autotroph", gridCellCohorts[actingCohort].FunctionalGroupIndex) == "heterotroph")
{
if (madingleyCohortDefinitions.GetTraitNames("Endo/Ectotherm", gridCellCohorts[actingCohort].FunctionalGroupIndex) == "endotherm")
{
Implementations["basic endotherm"].RunMetabolism(gridCellCohorts, gridCellStocks, actingCohort, cellEnvironment, deltas, madingleyCohortDefinitions, madingleyStockDefinitions, currentTimestep, currentMonth);
}
else
{
Implementations["basic ectotherm"].RunMetabolism(gridCellCohorts, gridCellStocks, actingCohort, cellEnvironment, deltas, madingleyCohortDefinitions, madingleyStockDefinitions, currentTimestep, currentMonth);
}
}
// If the process tracker is on and output detail is set to high and this cohort has not been merged yet, then record
// the number of individuals that have died
if (trackProcesses.TrackProcesses && (outputDetail == "high"))
{
trackProcesses.TrackTimestepMetabolism((uint)cellEnvironment["LatIndex"][0],
(uint)cellEnvironment["LonIndex"][0],
currentTimestep,
gridCellCohorts[actingCohort].IndividualBodyMass,
actingCohort[0],
cellEnvironment["Temperature"][currentMonth],
deltas["biomass"]["metabolism"]);
}
}
/// <summary>
/// Run ecological processes that operate on stocks within a single grid cell
/// </summary>
///<param name="gridCellStocks">The stocks in the current grid cell</param>
///<param name="actingStock">The acting stock</param>
///<param name="cellEnvironment">The stocks in the current grid cell</param>
///<param name="environmentalDataUnits">List of units associated with the environmental variables</param>
///<param name="humanNPPScenario">The human appropriation of NPP scenario to apply</param>
///<param name="madingleyStockDefinitions">The functional group definitions for stocks in the model</param>
///<param name="currentTimeStep">The current model time step</param>
///<param name="burninSteps">The number of time steps to spin the model up for before applying human impacts</param>
///<param name="impactSteps">The number of time steps to apply human impacts for</param>
///<param name="globalModelTimeStepUnit">The time step unit used in the model</param>
///<param name="trackProcesses">Whether to track properties of ecological processes</param>
///<param name="tracker">An instance of the ecological process tracker</param>
///<param name="globalTracker">An instance of the global process tracker</param>
///<param name="currentMonth">The current model month</param>
///<param name="outputDetail">The level of detail to use in outputs</param>
///<param name="specificLocations">Whether to run the model for specific locations</param>
///<param name="impactCell">Whether this cell should have human impacts applied</param>
public void RunWithinCellEcology(GridCellStockHandler gridCellStocks, int[] actingStock, SortedList <string, double[]> cellEnvironment,
SortedList <string, string> environmentalDataUnits, Tuple <string, double, double> humanNPPScenario,
FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimeStep, uint burninSteps, uint impactSteps, uint recoverySteps, uint instantStep, uint numInstantSteps, string globalModelTimeStepUnit, Boolean trackProcesses,
ProcessTracker tracker,
GlobalProcessTracker globalTracker, uint currentMonth,
string outputDetail, bool specificLocations, Boolean impactCell)
{
int ScenarioYear;
if (currentTimeStep < burninSteps)
{
ScenarioYear = 0;
}
else
{
ScenarioYear = (int)Math.Floor((currentTimeStep - burninSteps) / 12.0);
}
if (madingleyStockDefinitions.GetTraitNames("Realm", actingStock[0]) == "marine")
{
// Run the autotroph processor
MarineNPPtoAutotrophStock.ConvertNPPToAutotroph(cellEnvironment, gridCellStocks, actingStock, environmentalDataUnits["LandNPP"],
environmentalDataUnits["OceanNPP"], currentTimeStep, globalModelTimeStepUnit, tracker, globalTracker, outputDetail, specificLocations, currentMonth);
}
else if (madingleyStockDefinitions.GetTraitNames("Realm", actingStock[0]) == "terrestrial")
{
// Run the dynamic plant model to update the leaf stock for this time step
double WetMatterNPP = DynamicPlantModel.UpdateLeafStock(cellEnvironment, gridCellStocks, actingStock, currentTimeStep, madingleyStockDefinitions.
GetTraitNames("leaf strategy", actingStock[0]).Equals("deciduous"), globalModelTimeStepUnit, tracker, globalTracker, currentMonth,
outputDetail, specificLocations);
double fhanpp = HANPP.RemoveHumanAppropriatedMatter(WetMatterNPP, cellEnvironment, humanNPPScenario, gridCellStocks, actingStock,
currentTimeStep, ScenarioYear, burninSteps, impactSteps, recoverySteps, instantStep, numInstantSteps, impactCell, globalModelTimeStepUnit);
// Apply human appropriation of NPP
gridCellStocks[actingStock].TotalBiomass += WetMatterNPP * (1.0 - fhanpp);
if (globalTracker.TrackProcesses)
{
globalTracker.RecordHANPP((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0], (uint)actingStock[0],
fhanpp);
}
if (gridCellStocks[actingStock].TotalBiomass < 0.0)
{
gridCellStocks[actingStock].TotalBiomass = 0.0;
}
}
else
{
Debug.Fail("Stock must be classified as belonging to either the marine or terrestrial realm");
}
}
public GridCell(
GridCellCohortHandler GridCellCohorts,
GridCellStockHandler GridCellStocks,
SortedList <string, double[]> CellEnvironment,
float Latitude,
float Longitude)
{
this.GridCellCohorts = GridCellCohorts;
this.GridCellStocks = GridCellStocks;
this.CellEnvironment = CellEnvironment;
this._Latitude = Latitude;
this._Longitude = Longitude;
}
/// <summary>
/// Run metabolism for the acting cohort
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for the stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="currentMonth">The current model month</param>
public void RunMetabolism(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> >
deltas, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, uint currentMonth)
{
// Calculate metabolic loss for an individual and add the value to the delta biomass for metabolism
deltas["biomass"]["metabolism"] = -CalculateIndividualMetabolicRate(gridCellCohorts[actingCohort].IndividualBodyMass,
cellEnvironment["Temperature"][currentMonth] + _TemperatureUnitsConvert) * _DeltaT;
// If metabolic loss is greater than individual body mass after herbivory and predation, then set equal to individual body mass
deltas["biomass"]["metabolism"] = Math.Max(deltas["biomass"]["metabolism"], -(gridCellCohorts[actingCohort].IndividualBodyMass + deltas["biomass"]["predation"] + deltas["biomass"]["herbivory"]));
// Add total metabolic loss for all individuals in the cohort to delta biomass for metabolism in the respiratory CO2 pool
deltas["respiratoryCO2pool"]["metabolism"] = -deltas["biomass"]["metabolism"] * gridCellCohorts[actingCohort].CohortAbundance;
}
/// <summary>
/// Run reproduction
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stock functional groups in the model</param>
/// <param name="currentTimeStep">The current model time step</param>
/// <param name="processTracker">An instance of ProcessTracker to hold diagnostics for eating</param>
/// <param name="partial">Thread-locked variables for the parallelised version</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="outputDetail">The level of output detail being used for this model run</param>
/// <param name="currentMonth">The current model month</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
public void RunEcologicalProcess(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> > deltas,
FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimeStep, ProcessTracker processTracker, ref ThreadLockedParallelVariables partial,
Boolean specificLocations, string outputDetail, uint currentMonth, MadingleyModelInitialisation initialisation)
{
// Holds the reproductive strategy of a cohort
bool _Iteroparous = madingleyCohortDefinitions.GetTraitNames("reproductive strategy", actingCohort[0]) == "iteroparity";
// Assign mass to reproductive potential
Implementations["reproduction basic"].RunReproductiveMassAssignment(gridCellCohorts, gridCellStocks, actingCohort, cellEnvironment, deltas,
madingleyCohortDefinitions, madingleyStockDefinitions, currentTimeStep, processTracker);
// Run reproductive events. Note that we can't skip juveniles here as they could conceivably grow to adulthood and get enough biomass to reproduce in a single time step
// due to other ecological processes
Implementations["reproduction basic"].RunReproductionEvents(gridCellCohorts, gridCellStocks, actingCohort, cellEnvironment,
deltas, madingleyCohortDefinitions, madingleyStockDefinitions, currentTimeStep, processTracker, ref partial, _Iteroparous, currentMonth);
}
/// <summary>
/// Calculate the potential biomass that could be gained through herbivory on each grid cell autotroph stock
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the grid cell</param>
/// <param name="gridCellStocks">The stocks in the grid cell</param>
/// <param name="actingCohort">The acting cohort</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The functional group definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The functional group definitions for stocks in the model</param>
public void GetEatingPotentialMarine(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, int[] actingCohort, SortedList <string, double[]> cellEnvironment, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions)
{
// Set the total biomass eaten by the acting cohort to zero
_TotalBiomassEatenByCohort = 0.0;
// Get the individual body mass of the acting cohort
_BodyMassHerbivore = gridCellCohorts[actingCohort].IndividualBodyMass;
// Set the total number of units to handle all potential biomass eaten to zero
_TimeUnitsToHandlePotentialFoodItems = 0.0;
// Initialise the jagged arrays to hold the potential and actual biomass eaten in each of the grid cell autotroph stocks
_BiomassesEaten = new double[gridCellStocks.Count][];
_PotentialBiomassesEaten = new double[gridCellStocks.Count][];
// Loop over rows in the jagged arrays and initialise each vector
for (int i = 0; i < gridCellStocks.Count; i++)
{
_BiomassesEaten[i] = new double[gridCellStocks[i].Count];
_PotentialBiomassesEaten[i] = new double[gridCellStocks[i].Count];
}
// Loop over functional groups that can be eaten
foreach (int FunctionalGroup in _FunctionalGroupIndicesToEat)
{
// Loop over stocks within the functional group
for (int i = 0; i < gridCellStocks[FunctionalGroup].Count; i++)
{
// Get the mass from this stock that is available for eating (assumes all marine autotrophic organisms are edible)
//EdibleMass = gridCellStocks[FunctionalGroup][i].TotalBiomass * 0.1;
EdibleMass = gridCellStocks[FunctionalGroup][i].TotalBiomass;
// Calculate the potential biomass eaten from this stock by the acting cohort
_PotentialBiomassesEaten[FunctionalGroup][i] = CalculatePotentialBiomassEatenMarine(EdibleMass, _BodyMassHerbivore);
// Add the time required to handle the potential biomass eaten from this stock to the cumulative total for all stocks
_TimeUnitsToHandlePotentialFoodItems += _PotentialBiomassesEaten[FunctionalGroup][i] *
CalculateHandlingTimeMarine(_BodyMassHerbivore);
}
}
}
/// <summary>
/// Generate new cohorts from reproductive potential mass
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment of the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions of cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions of stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="tracker">An instance of ProcessTracker to hold diagnostics for reproduction</param>
/// <param name="partial">Thread-locked variables</param>
public void RunReproduction(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> >
deltas, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, ProcessTracker tracker, ref ThreadLockedParallelVariables partial)
{
// Check that the abundance in the cohort to produce is greater than or equal to zero
Debug.Assert(_OffspringCohortAbundance >= 0.0, "Offspring abundance < 0");
// Get the adult and juvenile masses of the cohort to produce
double[] OffspringProperties = GetOffspringCohortProperties(gridCellCohorts, actingCohort,
madingleyCohortDefinitions);
// Update cohort abundance in case juvenile mass has been altered
_OffspringCohortAbundance = (_OffspringCohortAbundance * gridCellCohorts[actingCohort].JuvenileMass) /
OffspringProperties[0];
//Create the offspring cohort
Cohort OffspringCohort = new Cohort((byte)actingCohort[0],
OffspringProperties[0],
OffspringProperties[1],
OffspringProperties[0],
_OffspringCohortAbundance,
(ushort)currentTimestep, ref partial.NextCohortIDThreadLocked);
// Add the offspring cohort to the grid cell cohorts array
gridCellCohorts[actingCohort[0]].Add(OffspringCohort);
// If the cohort has never been merged with another cohort, then add it to the tracker for output as diagnostics
if ((!gridCellCohorts[actingCohort].Merged) && tracker.TrackProcesses)
{
tracker.RecordNewCohort((uint)cellEnvironment["LatIndex"][0],
(uint)cellEnvironment["LonIndex"][0], currentTimestep, _OffspringCohortAbundance,
gridCellCohorts[actingCohort].AdultMass, gridCellCohorts[actingCohort].FunctionalGroupIndex);
}
// Subtract all of the reproductive potential mass of the parent cohort, which has been used to generate the new
// cohort, from the delta reproductive potential mass
deltas["reproductivebiomass"]["reproduction"] -= (gridCellCohorts[actingCohort].IndividualReproductivePotentialMass);
}
/// <summary>
/// Calculate the potential number of prey that could be gained through predation on each cohort in the grid cell
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The acting cohort</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The functional group definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The functional group definitions for stocks in the model</param>
public void GetEatingPotentialTerrestrial(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, int[] actingCohort,
SortedList <string, double[]> cellEnvironment, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions
madingleyStockDefinitions)
{
BinnedPreyDensities = new double[gridCellCohorts.Count, NumberOfBins];
// Set the total eaten by the acting cohort to zero
_TotalBiomassEatenByCohort = 0.0;
// Set the total number of units to handle all potential prey individuals eaten to zero
_TimeUnitsToHandlePotentialFoodItems = 0.0;
// Get the individual body mass of the acting (predator) cohort
_BodyMassPredator = gridCellCohorts[actingCohort].IndividualBodyMass;
// Get the abundance of the acting (predator) cohort
_AbundancePredator = gridCellCohorts[actingCohort].CohortAbundance;
// Pre-calculate individual values for this predator
_SpecificPredatorKillRateConstant = _KillRateConstant * Math.Pow(_BodyMassPredator, (_KillRateConstantMassExponent));
_SpecificPredatorTimeUnitsEatingPerGlobalTimeStep = _DeltaT * _ProportionOfTimeEating;
_PredatorAssimilationEfficiency = _AssimilationEfficiency;
_PredatorNonAssimilation = (1 - _AssimilationEfficiency);
// When body sizes are less than one gram, we have a flat handling time relationship to stop small things have extraordinarily short handling times
// if (_BodyMassPredator > 1.0)
// {
_ReferenceMassRatioScalingTerrestrial = HandlingTimeScalarTerrestrial * Math.Pow(_ReferenceMass / _BodyMassPredator, _HandlingTimeExponentTerrestrial);
// }
// else
// {
// _ReferenceMassRatioScalingTerrestrial = HandlingTimeScalarTerrestrial * _ReferenceMass / _BodyMassPredator;
// }
_PredatorAbundanceMultipliedByTimeEating = _AbundancePredator * _SpecificPredatorTimeUnitsEatingPerGlobalTimeStep;
_PredatorLogOptimalPreyBodySizeRatio = gridCellCohorts[actingCohort[0]][actingCohort[1]].LogOptimalPreyBodySizeRatio;
LogPredatorMassPlusPredatorLogOptimalPreyBodySizeRatio = Math.Log(_BodyMassPredator) + _PredatorLogOptimalPreyBodySizeRatio;
// Calculate the abundance of prey in each of the prey mass bins
PopulateBinnedPreyAbundance(gridCellCohorts, actingCohort, FunctionalGroupIndicesToEat, LogPredatorMassPlusPredatorLogOptimalPreyBodySizeRatio);
// Loop over potential prey functional groups
foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
{
// Loop over cohorts within the functional group
for (int i = 0; i < NumberCohortsPerFunctionalGroupNoNewCohorts[FunctionalGroup]; i++)
{
// Get the body mass of individuals in this cohort
_BodyMassPrey = gridCellCohorts[FunctionalGroup][i].IndividualBodyMass;
// Get the bin number of this prey cohort
PreyMassBinNumber = GetBinNumber(_BodyMassPrey, LogPredatorMassPlusPredatorLogOptimalPreyBodySizeRatio);
// Check whether the prey cohort still exists in the model (i.e. body mass > 0)
if ((0 < PreyMassBinNumber) && (PreyMassBinNumber < NumberOfBins) && (_BodyMassPrey > 0))
{
// Calculate the potential abundance from this cohort eaten by the acting cohort
_PotentialAbundanceEaten[FunctionalGroup][i] = CalculateExpectedNumberKilledTerrestrial(
gridCellCohorts[FunctionalGroup][i].CohortAbundance, _BodyMassPrey, PreyMassBinNumber, FunctionalGroup,
_BodyMassPredator, _CarnivoreFunctionalGroups[FunctionalGroup], _OmnivoreFunctionalGroups[FunctionalGroup],
_OmnivoreFunctionalGroups[actingCohort[0]], _PredatorLogOptimalPreyBodySizeRatio);
// Add the time required to handle the potential abundance eaten from this cohort to the cumulative total for all cohorts
_TimeUnitsToHandlePotentialFoodItems += _PotentialAbundanceEaten[FunctionalGroup][i] *
CalculateHandlingTimeTerrestrial(_BodyMassPrey);
}
else
{
// Assign a potential abundance eaten of zero
_PotentialAbundanceEaten[FunctionalGroup][i] = 0.0;
}
}
}
// No cannibalism; do this outside the loop to speed up the calculations
_TimeUnitsToHandlePotentialFoodItems -= PotentialAbundanceEaten[actingCohort[0]][actingCohort[1]] *
CalculateHandlingTimeTerrestrial(_BodyMassPredator);
PotentialAbundanceEaten[actingCohort[0]][actingCohort[1]] = 0.0;
}
/// <summary>
/// Calculate the potential number of prey that could be gained through predation on each cohort in the grid cell
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The acting cohort</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The functional group definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The functional group definitions for stocks in the model</param>
public void GetEatingPotentialMarine(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, int[] actingCohort,
SortedList <string, double[]> cellEnvironment, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions
madingleyStockDefinitions)
{
BinnedPreyDensities = new double[gridCellCohorts.Count, NumberOfBins];
// Set the total eaten by the acting cohort to zero
_TotalBiomassEatenByCohort = 0.0;
// Set the total number of units to handle all potential prey individuals eaten to zero
_TimeUnitsToHandlePotentialFoodItems = 0.0;
// Get the individual body mass of the acting (predator) cohort
_BodyMassPredator = gridCellCohorts[actingCohort].IndividualBodyMass;
// Get the abundance of the acting (predator) cohort
_AbundancePredator = gridCellCohorts[actingCohort].CohortAbundance;
// Pre-calculate individual values for this predator to speed things up
_SpecificPredatorKillRateConstant = _KillRateConstant * Math.Pow(_BodyMassPredator, (_KillRateConstantMassExponent));
_SpecificPredatorTimeUnitsEatingPerGlobalTimeStep = _DeltaT * _ProportionOfTimeEating;
_PredatorAssimilationEfficiency = _AssimilationEfficiency;
_PredatorNonAssimilation = (1 - _AssimilationEfficiency);
_DietIsAllSpecial = madingleyCohortDefinitions.GetTraitNames("Diet", actingCohort[0]) == "allspecial";
_PredatorLogOptimalPreyBodySizeRatio = gridCellCohorts[actingCohort[0]][actingCohort[1]].LogOptimalPreyBodySizeRatio;
// If a filter feeder, then optimal body size is a value not a ratio: convert it to a ratio to ensure that all calculations work correctly
if (_DietIsAllSpecial)
{
// Optimal body size is actually a value, not a ratio, so convert it to a ratio based on the present body size
_PredatorLogOptimalPreyBodySizeRatio = Math.Log(
Math.Exp(gridCellCohorts[actingCohort[0]][actingCohort[1]].LogOptimalPreyBodySizeRatio) / gridCellCohorts[actingCohort[0]][actingCohort[1]].IndividualBodyMass);
}
// Calculate the reference mass scaling ratio
_ReferenceMassRatioScalingMarine = HandlingTimeScalarMarine * Math.Pow(_ReferenceMass / _BodyMassPredator, _HandlingTimeExponentMarine);
_PredatorAbundanceMultipliedByTimeEating = _AbundancePredator * _SpecificPredatorTimeUnitsEatingPerGlobalTimeStep;
LogPredatorMassPlusPredatorLogOptimalPreyBodySizeRatio = Math.Log(_BodyMassPredator) + _PredatorLogOptimalPreyBodySizeRatio;
// Calculate the abundance of prey in each of the prey mass bins
PopulateBinnedPreyAbundance(gridCellCohorts, actingCohort, FunctionalGroupIndicesToEat, LogPredatorMassPlusPredatorLogOptimalPreyBodySizeRatio);
// Loop over potential prey functional groups
foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
{
// Eating operates differently for planktivores
// This can certainly be sped up
if (_DietIsAllSpecial)
{
// Loop over cohorts within the functional group
for (int i = 0; i < NumberCohortsPerFunctionalGroupNoNewCohorts[FunctionalGroup]; i++)
{
// Get the body mass of individuals in this cohort
_BodyMassPrey = gridCellCohorts[FunctionalGroup][i].IndividualBodyMass;
// Get the bin number of this prey cohort
PreyMassBinNumber = GetBinNumber(_BodyMassPrey, LogPredatorMassPlusPredatorLogOptimalPreyBodySizeRatio);
// Check whether
// The prey cohort is within the feeding range of the predator
// the prey cohort still exists in the model (i.e. body mass > 0)
// Currently having whales etc eat everything, but preferentially feed on very small things (i.e. filter feeders)
if ((_PlanktonFunctionalGroups[FunctionalGroup]) && (0 < PreyMassBinNumber) &&
(PreyMassBinNumber < NumberOfBins) && (_BodyMassPrey > 0))
{
// Calculate the potential abundance from this cohort eaten by the acting cohort
_PotentialAbundanceEaten[FunctionalGroup][i] = CalculateExpectedNumberKilledMarine(
gridCellCohorts[FunctionalGroup][i].CohortAbundance, _BodyMassPrey, PreyMassBinNumber, FunctionalGroup,
_BodyMassPredator, _CarnivoreFunctionalGroups[FunctionalGroup], _OmnivoreFunctionalGroups[FunctionalGroup],
_OmnivoreFunctionalGroups[actingCohort[0]], _PredatorLogOptimalPreyBodySizeRatio);
// Add the time required to handle the potential abundance eaten from this cohort to the cumulative total for all cohorts
_TimeUnitsToHandlePotentialFoodItems += _PotentialAbundanceEaten[FunctionalGroup][i] *
CalculateHandlingTimeMarine(_BodyMassPrey);
}
else
{
// Assign a potential abundance eaten of zero
_PotentialAbundanceEaten[FunctionalGroup][i] = 0.0;
}
}
}
else
{
// Loop over cohorts within the functional group
for (int i = 0; i < NumberCohortsPerFunctionalGroupNoNewCohorts[FunctionalGroup]; i++)
{
// Get the body mass of individuals in this cohort
_BodyMassPrey = gridCellCohorts[FunctionalGroup][i].IndividualBodyMass;
// Get the bin number of this prey cohort
PreyMassBinNumber = GetBinNumber(_BodyMassPrey, LogPredatorMassPlusPredatorLogOptimalPreyBodySizeRatio);
// Check whether
// The prey cohort is within the feeding range of the predator
// the prey cohort still exists in the model (i.e. body mass > 0)
if ((0 < PreyMassBinNumber) && (PreyMassBinNumber < NumberOfBins) && (_BodyMassPrey > 0))
{
// Calculate the potential abundance from this cohort eaten by the acting cohort
_PotentialAbundanceEaten[FunctionalGroup][i] = CalculateExpectedNumberKilledMarine(
gridCellCohorts[FunctionalGroup][i].CohortAbundance, _BodyMassPrey, PreyMassBinNumber, FunctionalGroup,
_BodyMassPredator, _CarnivoreFunctionalGroups[FunctionalGroup], _OmnivoreFunctionalGroups[FunctionalGroup],
_OmnivoreFunctionalGroups[actingCohort[0]], _PredatorLogOptimalPreyBodySizeRatio);
// Add the time required to handle the potential abundance eaten from this cohort to the cumulative total for all cohorts
_TimeUnitsToHandlePotentialFoodItems += _PotentialAbundanceEaten[FunctionalGroup][i] *
CalculateHandlingTimeMarine(_BodyMassPrey);
}
else
{
// Assign a potential abundance eaten of zero
_PotentialAbundanceEaten[FunctionalGroup][i] = 0.0;
}
}
}
}
// No cannibalism; do this outside the loop to speed up the calculations
_TimeUnitsToHandlePotentialFoodItems -= PotentialAbundanceEaten[actingCohort[0]][actingCohort[1]] *
CalculateHandlingTimeMarine(_BodyMassPredator);
PotentialAbundanceEaten[actingCohort[0]][actingCohort[1]] = 0.0;
}
/// <summary>
/// Initialises predation implementation each time step
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stocks in the model</param>
/// <remarks>This only works if: a) predation is initialised in every grid cell; and b) if parallelisation is done by latitudinal strips
/// It is critical to run this every time step</remarks>
public void InitializeEatingPerTimeStep(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions)
{
// Get the functional group indices of all heterotroph cohorts (i.e. potential prey)
_FunctionalGroupIndicesToEat = madingleyCohortDefinitions.GetFunctionalGroupIndex("Heterotroph/Autotroph", "heterotroph", false);
// Initialise the vector to hold the number of cohorts in each functional group at the start of the time step
NumberCohortsPerFunctionalGroupNoNewCohorts = new int[gridCellCohorts.Count];
// Initialise the jagged arrays to hold the potential and actual numbers of prey eaten in each of the grid cell cohorts
_AbundancesEaten = new double[gridCellCohorts.Count][];
_PotentialAbundanceEaten = new double[gridCellCohorts.Count][];
// Initialise the vector to identify carnivore cohorts
_CarnivoreFunctionalGroups = new Boolean[_FunctionalGroupIndicesToEat.Length];
_OmnivoreFunctionalGroups = new Boolean[_FunctionalGroupIndicesToEat.Length];
_PlanktonFunctionalGroups = new Boolean[_FunctionalGroupIndicesToEat.Length];
// Loop over rows in the jagged arrays, initialise each vector within the jagged arrays, and calculate the current number of cohorts in
// each functional group
for (int i = 0; i < gridCellCohorts.Count; i++)
{
// Calculate the current number of cohorts in this functional group
int NumCohortsThisFG = gridCellCohorts[i].Count;
NumberCohortsPerFunctionalGroupNoNewCohorts[i] = NumCohortsThisFG;
// Initialise the jagged arrays
_AbundancesEaten[i] = new double[NumberCohortsPerFunctionalGroupNoNewCohorts[i]];
_PotentialAbundanceEaten[i] = new double[NumberCohortsPerFunctionalGroupNoNewCohorts[i]];
}
// Loop over functional groups that are potential prey and determine which are carnivores
foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
{
_CarnivoreFunctionalGroups[FunctionalGroup] = madingleyCohortDefinitions.GetTraitNames("Nutrition source", FunctionalGroup) == "carnivore";
}
foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
{
_OmnivoreFunctionalGroups[FunctionalGroup] = madingleyCohortDefinitions.GetTraitNames("Nutrition source", FunctionalGroup) == "omnivore";
}
foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
{
_PlanktonFunctionalGroups[FunctionalGroup] = madingleyCohortDefinitions.GetTraitNames("Mobility", FunctionalGroup) == "planktonic";
}
}
/// <summary>
/// Run eating
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="trackProcesses">An instance of ProcessTracker to hold diagnostics for eating</param>
/// <param name="partial">Thread-locked variables</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="outputDetail">The level of output detail being used for the current model run</param>
/// <param name="currentMonth">The current model month</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
public void RunEcologicalProcess(GridCellCohortHandler gridCellCohorts,
GridCellStockHandler gridCellStocks, int[] actingCohort,
SortedList <string, double[]> cellEnvironment,
Dictionary <string, Dictionary <string, double> > deltas,
FunctionalGroupDefinitions madingleyCohortDefinitions,
FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, ProcessTracker trackProcesses,
ref ThreadLockedParallelVariables partial, Boolean specificLocations,
string outputDetail, uint currentMonth, MadingleyModelInitialisation initialisation)
{
PreviousTrophicIndex = gridCellCohorts[actingCohort].TrophicIndex;
//Reset this cohort's trohic index ready for calculation across its feeding this timetsstep
gridCellCohorts[actingCohort].TrophicIndex = 0.0;
// Get the nutrition source (herbivory, carnivory or omnivory) of the acting cohort
string NutritionSource = madingleyCohortDefinitions.GetTraitNames("Nutrition source", gridCellCohorts[actingCohort].FunctionalGroupIndex);
// Switch to the appropriate eating process(es) given the cohort's nutrition source
switch (NutritionSource)
{
case "herbivore":
// Get the assimilation efficiency for herbivory for this cohort from the functional group definitions
Implementations["revised herbivory"].AssimilationEfficiency =
madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup
("herbivory assimilation", gridCellCohorts[actingCohort].FunctionalGroupIndex);
// Get the proportion of time spent eating for this cohort from the functional group definitions
Implementations["revised herbivory"].ProportionTimeEating = gridCellCohorts[actingCohort].ProportionTimeActive;
// Calculate the potential biomass available from herbivory
if (cellEnvironment["Realm"][0] == 2.0)
{
Implementations["revised herbivory"].GetEatingPotentialMarine
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions, madingleyStockDefinitions);
}
else
{
Implementations["revised herbivory"].GetEatingPotentialTerrestrial
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions, madingleyStockDefinitions);
}
// Run herbivory to apply changes in autotroph biomass from herbivory and add biomass eaten to the delta arrays
Implementations["revised herbivory"].RunEating
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, deltas, madingleyCohortDefinitions,
madingleyStockDefinitions, trackProcesses,
currentTimestep, specificLocations, outputDetail, initialisation);
break;
case "carnivore":
// Get the assimilation efficiency for predation for this cohort from the functional group definitions
Implementations["revised predation"].AssimilationEfficiency =
madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup
("carnivory assimilation", gridCellCohorts[actingCohort].FunctionalGroupIndex);
Implementations["revised predation"].ProportionTimeEating = gridCellCohorts[actingCohort].ProportionTimeActive;
// Calculate the potential biomass available from predation
if (cellEnvironment["Realm"][0] == 2.0)
{
Implementations["revised predation"].GetEatingPotentialMarine
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions, madingleyStockDefinitions);
}
else
{
Implementations["revised predation"].GetEatingPotentialTerrestrial
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions, madingleyStockDefinitions);
}
// Run predation to apply changes in prey biomass from predation and add biomass eaten to the delta arrays
Implementations["revised predation"].RunEating
(gridCellCohorts, gridCellStocks, actingCohort, cellEnvironment, deltas,
madingleyCohortDefinitions, madingleyStockDefinitions, trackProcesses,
currentTimestep, specificLocations, outputDetail, initialisation);
break;
case "omnivore":
// Get the assimilation efficiency for predation for this cohort from the functional group definitions
Implementations["revised predation"].AssimilationEfficiency =
madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup
("carnivory assimilation", gridCellCohorts[actingCohort].FunctionalGroupIndex);
// Get the assimilation efficiency for herbivory for this cohort from the functional group definitions
Implementations["revised herbivory"].AssimilationEfficiency =
madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup
("herbivory assimilation", gridCellCohorts[actingCohort].FunctionalGroupIndex);
// Get the proportion of time spent eating and assign to both the herbivory and predation implementations
double ProportionTimeEating = gridCellCohorts[actingCohort].ProportionTimeActive;
Implementations["revised predation"].ProportionTimeEating = ProportionTimeEating;
Implementations["revised herbivory"].ProportionTimeEating = ProportionTimeEating;
// Calculate the potential biomass available from herbivory
if (cellEnvironment["Realm"][0] == 2.0)
{
Implementations["revised herbivory"].GetEatingPotentialMarine
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions,
madingleyStockDefinitions);
}
else
{
Implementations["revised herbivory"].GetEatingPotentialTerrestrial
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions,
madingleyStockDefinitions);
}
// Calculate the potential biomass available from predation
if (cellEnvironment["Realm"][0] == 2.0)
{
Implementations["revised predation"].GetEatingPotentialMarine
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions,
madingleyStockDefinitions);
}
else
{
Implementations["revised predation"].GetEatingPotentialTerrestrial
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, madingleyCohortDefinitions,
madingleyStockDefinitions);
}
// Calculate the total handling time for all expected kills from predation and expected plant matter eaten in herbivory
TotalTimeToEatForOmnivores =
Implementations["revised herbivory"].TimeUnitsToHandlePotentialFoodItems +
Implementations["revised predation"].TimeUnitsToHandlePotentialFoodItems;
// Assign this total time to the relevant variables in both herbviory and predation, so that actual amounts eaten are calculated correctly
Implementations["revised herbivory"].TimeUnitsToHandlePotentialFoodItems = TotalTimeToEatForOmnivores;
Implementations["revised predation"].TimeUnitsToHandlePotentialFoodItems = TotalTimeToEatForOmnivores;
// Run predation to update prey cohorts and delta biomasses for the acting cohort
Implementations["revised predation"].RunEating
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, deltas, madingleyCohortDefinitions,
madingleyStockDefinitions, trackProcesses,
currentTimestep, specificLocations, outputDetail, initialisation);
// Run herbivory to update autotroph biomass and delta biomasses for the acting cohort
Implementations["revised herbivory"].RunEating
(gridCellCohorts, gridCellStocks, actingCohort,
cellEnvironment, deltas, madingleyCohortDefinitions,
madingleyStockDefinitions, trackProcesses,
currentTimestep, specificLocations, outputDetail, initialisation);
break;
default:
// For nutrition source that are not supported, throw an error
Debug.Fail("The model currently does not contain an eating model for nutrition source:" + NutritionSource);
break;
}
// Check that the biomasses from predation and herbivory in the deltas is a number
Debug.Assert(!double.IsNaN(deltas["biomass"]["predation"]), "BiomassFromEating is NaN");
Debug.Assert(!double.IsNaN(deltas["biomass"]["herbivory"]), "BiomassFromEating is NaN");
double biomassEaten = 0.0;
if (madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup("carnivory assimilation",
gridCellCohorts[actingCohort].FunctionalGroupIndex) > 0)
{
biomassEaten += (deltas["biomass"]["predation"] / madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup("carnivory assimilation",
gridCellCohorts[actingCohort].FunctionalGroupIndex));
}
if (madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup("herbivory assimilation",
gridCellCohorts[actingCohort].FunctionalGroupIndex) > 0)
{
biomassEaten += (deltas["biomass"]["herbivory"] / madingleyCohortDefinitions.GetBiologicalPropertyOneFunctionalGroup("herbivory assimilation",
gridCellCohorts[actingCohort].FunctionalGroupIndex));
}
if (biomassEaten > 0.0)
{
gridCellCohorts[actingCohort].TrophicIndex = 1 +
(gridCellCohorts[actingCohort].TrophicIndex / (biomassEaten * gridCellCohorts[actingCohort].CohortAbundance));
}
else
{
gridCellCohorts[actingCohort].TrophicIndex = PreviousTrophicIndex;
}
}
/// <summary>
/// Initializes an implementation of eating
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stock functional groups in the model</param>
/// <param name="implementationKey">The name of the implementation of eating to initialize</param>
/// <remarks>Eating needs to be initialized every time step</remarks>
public void InitializeEcologicalProcess(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
string implementationKey)
{
// Initialize the implementation of the eating process
Implementations[implementationKey].InitializeEatingPerTimeStep(gridCellCohorts, gridCellStocks,
madingleyCohortDefinitions, madingleyStockDefinitions);
}
/// <summary>
/// Run mortality
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="trackProcesses">An instance of ProcessTracker to hold diagnostics for mortality</param>
/// <param name="partial">Thread-locked variables</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="outputDetail">The level output detail being used for the current model run</param>
/// <param name="currentMonth">The current model month</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
public void RunEcologicalProcess(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> > deltas,
FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, ProcessTracker trackProcesses, ref ThreadLockedParallelVariables partial,
Boolean specificLocations, string outputDetail, uint currentMonth, MadingleyModelInitialisation initialisation)
{
// Variables to hold the mortality rates
double MortalityRateBackground;
double MortalityRateSenescence;
double MortalityRateStarvation;
// Variable to hold the total abundance lost to all forms of mortality
double MortalityTotal;
// Individual body mass including change this time step as a result of other ecological processes
double BodyMassIncludingChangeThisTimeStep;
// Individual reproductive mass including change this time step as a result of other ecological processes
double ReproductiveMassIncludingChangeThisTimeStep;
// Calculate the body mass of individuals in this cohort including mass gained through eating this time step, up to but not exceeding adult body mass for this cohort.
// Should be fine because these deductions are made in the reproduction implementation, but use Math.Min to double check.
BodyMassIncludingChangeThisTimeStep = 0.0;
// Loop over all items in the biomass deltas
foreach (var Biomass in deltas["biomass"])
{
// Add the delta biomass to net biomass
BodyMassIncludingChangeThisTimeStep += Biomass.Value;
}
BodyMassIncludingChangeThisTimeStep = Math.Min(gridCellCohorts[actingCohort].AdultMass, BodyMassIncludingChangeThisTimeStep + gridCellCohorts[actingCohort].IndividualBodyMass);
// Temporary variable to hold net reproductive biomass change of individuals in this cohort as a result of other ecological processes
ReproductiveMassIncludingChangeThisTimeStep = 0.0;
// Loop over all items in the biomass deltas
foreach (var Biomass in deltas["reproductivebiomass"])
{
// Add the delta biomass to net biomass
ReproductiveMassIncludingChangeThisTimeStep += Biomass.Value;
}
ReproductiveMassIncludingChangeThisTimeStep += gridCellCohorts[actingCohort].IndividualReproductivePotentialMass;
// Check to see if the cohort has already been killed by predation etc
if ((BodyMassIncludingChangeThisTimeStep).CompareTo(0.0) <= 0)
{
// If individual body mass is not greater than zero, then all individuals become extinct
MortalityTotal = gridCellCohorts[actingCohort].CohortAbundance;
}
else
{
// Calculate background mortality rate
MortalityRateBackground = Implementations["basic background mortality"].CalculateMortalityRate(gridCellCohorts,
actingCohort, BodyMassIncludingChangeThisTimeStep, deltas, currentTimestep);
// If the cohort has matured, then calculate senescence mortality rate, otherwise set rate to zero
if (gridCellCohorts[actingCohort].MaturityTimeStep != uint.MaxValue)
{
MortalityRateSenescence = Implementations["basic senescence mortality"].CalculateMortalityRate(gridCellCohorts,
actingCohort, BodyMassIncludingChangeThisTimeStep, deltas, currentTimestep);
}
else
{
MortalityRateSenescence = 0.0;
}
// Calculate the starvation mortality rate based on individual body mass and maximum body mass ever
// achieved by this cohort
MortalityRateStarvation = Implementations["basic starvation mortality"].CalculateMortalityRate(gridCellCohorts, actingCohort, BodyMassIncludingChangeThisTimeStep, deltas, currentTimestep);
// Calculate the number of individuals that suffer mortality this time step from all sources of mortality
MortalityTotal = (1 - Math.Exp(-MortalityRateBackground - MortalityRateSenescence -
MortalityRateStarvation)) * gridCellCohorts[actingCohort].CohortAbundance;
}
// If the process tracker is on and output detail is set to high and this cohort has not been merged yet, then record
// the number of individuals that have died
if (trackProcesses.TrackProcesses && (outputDetail == "high") && (!gridCellCohorts[actingCohort].Merged))
{
trackProcesses.RecordMortality((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0], gridCellCohorts[actingCohort].BirthTimeStep,
currentTimestep, gridCellCohorts[actingCohort].IndividualBodyMass, gridCellCohorts[actingCohort].AdultMass,
gridCellCohorts[actingCohort].FunctionalGroupIndex,
gridCellCohorts[actingCohort].CohortID[0], MortalityTotal, "sen/bg/starv");
}
// Remove individuals that have died from the delta abundance for this cohort
deltas["abundance"]["mortality"] = -MortalityTotal;
// Add the biomass of individuals that have died to the delta biomass in the organic pool (including reproductive
// potential mass, and mass gained through eating, and excluding mass lost through metabolism)
deltas["organicpool"]["mortality"] = MortalityTotal * (BodyMassIncludingChangeThisTimeStep + ReproductiveMassIncludingChangeThisTimeStep);
}
public InputModelState(string outputPath, string filename, ModelGrid ecosystemModelGrid, List <uint[]> cellList)
{
//Set the input state flag to be true
_InputState = true;
// Construct the string required to access the file using Scientific Dataset
string _ReadFileString = "msds:nc?file=input/ModelStates/" + filename + ".nc&openMode=readOnly";
// Open the data file using Scientific Dataset
DataSet StateDataSet = DataSet.Open(_ReadFileString);
float[] Latitude = StateDataSet.GetData <float[]>("Latitude");
float[] Longitude = StateDataSet.GetData <float[]>("Longitude");
float[] CohortFunctionalGroup = StateDataSet.GetData <float[]>("Cohort Functional Group");
float[] Cohort = StateDataSet.GetData <float[]>("Cohort");
float[] StockFunctionalGroup = StateDataSet.GetData <float[]>("Stock Functional Group");
float[] Stock = StateDataSet.GetData <float[]>("Stock");
// Check that the longitudes and latitudes in the input state match the cell environment
for (int la = 0; la < Latitude.Length; la++)
{
Debug.Assert(ecosystemModelGrid.GetCellEnvironment((uint)la, 0)["Latitude"][0] == Latitude[la],
"Error: input-state grid doesn't match current model grid");
}
for (int lo = 0; lo < Longitude.Length; lo++)
{
Debug.Assert(ecosystemModelGrid.GetCellEnvironment(0, (uint)lo)["Longitude"][0] == Longitude[lo],
"Error: input-state grid doesn't match current model grid");
}
List <double[, , ]> CohortJuvenileMass = new List <double[, , ]>();
List <double[, , ]> CohortAdultMass = new List <double[, , ]>();
List <double[, , ]> CohortIndividualBodyMass = new List <double[, , ]>();
List <double[, , ]> CohortCohortAbundance = new List <double[, , ]>();
List <double[, , ]> CohortLogOptimalPreyBodySizeRatio = new List <double[, , ]>();
List <double[, , ]> CohortBirthTimeStep = new List <double[, , ]>();
List <double[, , ]> CohortProportionTimeActive = new List <double[, , ]>();
List <double[, , ]> CohortTrophicIndex = new List <double[, , ]>();
double[,,,] tempData = new double[Latitude.Length, Longitude.Length,
CohortFunctionalGroup.Length, Cohort.Length];
tempData = StateDataSet.GetData <double[, , , ]>("CohortJuvenileMass");
for (int la = 0; la < Latitude.Length; la++)
{
CohortJuvenileMass.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortJuvenileMass[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
tempData = StateDataSet.GetData <double[, , , ]>("CohortAdultMass");
for (int la = 0; la < Latitude.Length; la++)
{
CohortAdultMass.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortAdultMass[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
tempData = StateDataSet.GetData <double[, , , ]>("CohortIndividualBodyMass");
for (int la = 0; la < Latitude.Length; la++)
{
CohortIndividualBodyMass.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortIndividualBodyMass[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
tempData = StateDataSet.GetData <double[, , , ]>("CohortCohortAbundance");
for (int la = 0; la < Latitude.Length; la++)
{
CohortCohortAbundance.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortCohortAbundance[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
tempData = StateDataSet.GetData <double[, , , ]>("CohortLogOptimalPreyBodySizeRatio");
for (int la = 0; la < Latitude.Length; la++)
{
CohortLogOptimalPreyBodySizeRatio.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortLogOptimalPreyBodySizeRatio[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
tempData = StateDataSet.GetData <double[, , , ]>("CohortBirthTimeStep");
for (int la = 0; la < Latitude.Length; la++)
{
CohortBirthTimeStep.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortBirthTimeStep[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
tempData = StateDataSet.GetData <double[, , , ]>("CohortProportionTimeActive");
for (int la = 0; la < Latitude.Length; la++)
{
CohortProportionTimeActive.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortProportionTimeActive[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
tempData = StateDataSet.GetData <double[, , , ]>("CohortTrophicIndex");
for (int la = 0; la < Latitude.Length; la++)
{
CohortTrophicIndex.Add(new double[Longitude.Length, CohortFunctionalGroup.Length, Cohort.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Cohort.Length; c++)
{
CohortTrophicIndex[(int)cell[0]][cell[1], fg, c] = tempData[
cell[0], cell[1], fg, c];
}
}
}
_GridCellCohorts = new GridCellCohortHandler[Latitude.Length, Longitude.Length];
long temp = 0;
for (int cell = 0; cell < cellList.Count; cell++)
{
_GridCellCohorts[cellList[cell][0], cellList[cell][1]] = new GridCellCohortHandler(CohortFunctionalGroup.Length);
for (int fg = 0; fg < CohortFunctionalGroup.Length; fg++)
{
_GridCellCohorts[cellList[cell][0], cellList[cell][1]][fg] = new List <Cohort>();
for (int c = 0; c < Cohort.Length; c++)
{
if (CohortCohortAbundance[(int)cellList[cell][0]][cellList[cell][1], fg, c] > 0.0)
{
Cohort TempCohort = new Cohort(
(byte)fg,
CohortJuvenileMass[(int)cellList[cell][0]][cellList[cell][1], fg, c],
CohortAdultMass[(int)cellList[cell][0]][cellList[cell][1], fg, c],
CohortIndividualBodyMass[(int)cellList[cell][0]][cellList[cell][1], fg, c],
CohortCohortAbundance[(int)cellList[cell][0]][cellList[cell][1], fg, c],
Math.Exp(CohortLogOptimalPreyBodySizeRatio[(int)cellList[cell][0]][cellList[cell][1], fg, c]),
Convert.ToUInt16(CohortBirthTimeStep[(int)cellList[cell][0]][cellList[cell][1], fg, c]),
CohortProportionTimeActive[(int)cellList[cell][0]][cellList[cell][1], fg, c], ref temp,
CohortTrophicIndex[(int)cellList[cell][0]][cellList[cell][1], fg, c],
false);
_GridCellCohorts[cellList[cell][0], cellList[cell][1]][fg].Add(TempCohort);
}
}
}
}
CohortJuvenileMass.RemoveRange(0, CohortJuvenileMass.Count);
CohortAdultMass.RemoveRange(0, CohortAdultMass.Count);
CohortIndividualBodyMass.RemoveRange(0, CohortIndividualBodyMass.Count);
CohortCohortAbundance.RemoveRange(0, CohortCohortAbundance.Count);
CohortLogOptimalPreyBodySizeRatio.RemoveRange(0, CohortLogOptimalPreyBodySizeRatio.Count);
CohortBirthTimeStep.RemoveRange(0, CohortBirthTimeStep.Count);
CohortProportionTimeActive.RemoveRange(0, CohortProportionTimeActive.Count);
CohortTrophicIndex.RemoveRange(0, CohortTrophicIndex.Count);
List <double[, , ]> StockIndividualBodyMass = new List <double[, , ]>();
List <double[, , ]> StockTotalBiomass = new List <double[, , ]>();
double[,,,] tempData2 = new double[Latitude.Length, Longitude.Length,
StockFunctionalGroup.Length, Stock.Length];
tempData2 = StateDataSet.GetData <double[, , , ]>("StockIndividualBodyMass");
for (int la = 0; la < Latitude.Length; la++)
{
StockIndividualBodyMass.Add(new double[Longitude.Length, StockFunctionalGroup.Length, Stock.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < StockFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Stock.Length; c++)
{
StockIndividualBodyMass[(int)cell[0]][cell[1], fg, c] = tempData2[
cell[0], cell[1], fg, c];
}
}
}
tempData2 = StateDataSet.GetData <double[, , , ]>("StockTotalBiomass");
for (int la = 0; la < Latitude.Length; la++)
{
StockTotalBiomass.Add(new double[Longitude.Length, StockFunctionalGroup.Length, Stock.Length]);
}
foreach (uint[] cell in cellList)
{
for (int fg = 0; fg < StockFunctionalGroup.Length; fg++)
{
for (int c = 0; c < Stock.Length; c++)
{
StockTotalBiomass[(int)cell[0]][cell[1], fg, c] = tempData2[
cell[0], cell[1], fg, c];
}
}
}
_GridCellStocks = new GridCellStockHandler[Latitude.Length, Longitude.Length];
for (int cell = 0; cell < cellList.Count; cell++)
{
_GridCellStocks[cellList[cell][0], cellList[cell][1]] = new GridCellStockHandler(StockFunctionalGroup.Length);
for (int fg = 0; fg < StockFunctionalGroup.Length; fg++)
{
_GridCellStocks[cellList[cell][0], cellList[cell][1]][fg] = new List <Stock>();
for (int c = 0; c < Stock.Length; c++)
{
if (StockTotalBiomass[(int)cellList[cell][0]][cellList[cell][1], fg, c] > 0.0)
{
Stock TempStock = new Stock(
(byte)fg,
StockIndividualBodyMass[(int)cellList[cell][0]][cellList[cell][1], fg, c],
StockTotalBiomass[(int)cellList[cell][0]][cellList[cell][1], fg, c]);
_GridCellStocks[cellList[cell][0], cellList[cell][1]][fg].Add(TempStock);
}
}
}
}
}
/// <summary>
/// Initialises herbivory implementation each time step
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stocks in the model</param>
/// <remarks>This only works if: a) herbivory is initialised in every grid cell; and b) if parallelisation is done by latitudinal strips
/// It is critical to run this every time step</remarks>
public void InitializeEatingPerTimeStep(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions)
{
// Get the functional group indices of all autotroph stocks
_FunctionalGroupIndicesToEat = madingleyStockDefinitions.GetFunctionalGroupIndex("Heterotroph/Autotroph", "Autotroph", false);
}
/// <summary>
/// Assigns ingested biomass from other ecological processes to reproductive potential mass
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions of cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions of stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="tracker">An instance of ProcessTracker to hold diagnostics for reproduction</param>
public void RunReproductiveMassAssignment(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> > deltas,
FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, ProcessTracker tracker)
{
// Biomass per individual in each cohort to be assigned to reproductive potential
double _BiomassToAssignToReproductivePotential;
// Net biomass change from other ecological functions this time step
double NetBiomassFromOtherEcologicalFunctionsThisTimeStep;
// Reset variable holding net biomass change of individuals in this cohort as a result of other ecological processes
NetBiomassFromOtherEcologicalFunctionsThisTimeStep = 0.0;
// Loop over all items in the biomass deltas
foreach (var Biomass in deltas["biomass"])
{
// Add the delta biomass to net biomass
NetBiomassFromOtherEcologicalFunctionsThisTimeStep += Biomass.Value;
}
// If individual body mass after the addition of the net biomass from processes this time step will yield a body mass
// greater than the adult body mass for this cohort, then assign the surplus to reproductive potential
if ((gridCellCohorts[actingCohort].IndividualBodyMass + NetBiomassFromOtherEcologicalFunctionsThisTimeStep) > gridCellCohorts[actingCohort].AdultMass)
{
// Calculate the biomass for each individual in this cohort to be assigned to reproductive potential
_BiomassToAssignToReproductivePotential = gridCellCohorts[actingCohort].IndividualBodyMass + NetBiomassFromOtherEcologicalFunctionsThisTimeStep -
gridCellCohorts[actingCohort].AdultMass;
// Check that a positive biomass is to be assigned to reproductive potential
Debug.Assert(_BiomassToAssignToReproductivePotential >= 0.0, "Assignment of negative reproductive potential mass");
// If this is the first time reproductive potential mass has been assigned for this cohort,
// then set the maturity time step for this cohort as the current model time step
if (gridCellCohorts[actingCohort].MaturityTimeStep == uint.MaxValue)
{
gridCellCohorts[actingCohort].MaturityTimeStep = currentTimestep;
// Track the generation length for this cohort
if (tracker.TrackProcesses && (!gridCellCohorts[actingCohort].Merged))
{
tracker.TrackMaturity((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0],
currentTimestep, gridCellCohorts[actingCohort].BirthTimeStep, gridCellCohorts[actingCohort].JuvenileMass,
gridCellCohorts[actingCohort].AdultMass, gridCellCohorts[actingCohort].FunctionalGroupIndex);
}
}
// Assign the specified mass to reproductive potential mass and remove it from individual biomass
deltas["reproductivebiomass"]["reproduction"] += _BiomassToAssignToReproductivePotential;
deltas["biomass"]["reproduction"] -= _BiomassToAssignToReproductivePotential;
}
else
{
// Cohort has not gained sufficient biomass to assign any to reproductive potential, so take no action
}
}
/// <summary>
/// Assigns biomass from body mass to reproductive potential mass
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions of cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions of stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="tracker">An instance of ProcessTracker to hold diagnostics for reproduction</param>
public void AssignMassToReproductivePotential(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> > deltas,
FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, ProcessTracker tracker)
{
// If this is the first time reproductive potential mass has been assigned for this cohort,
// then set the maturity time step for this cohort as the current model time step
if (gridCellCohorts[actingCohort].MaturityTimeStep == uint.MaxValue)
{
gridCellCohorts[actingCohort].MaturityTimeStep = currentTimestep;
// Track the generation length for this cohort
if ((!gridCellCohorts[actingCohort].Merged) && tracker.TrackProcesses)
{
tracker.TrackMaturity((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0],
currentTimestep, gridCellCohorts[actingCohort].BirthTimeStep, gridCellCohorts[actingCohort].JuvenileMass,
gridCellCohorts[actingCohort].AdultMass, gridCellCohorts[actingCohort].FunctionalGroupIndex);
}
}
// Assign the specified mass to reproductive potential mass and remove it from individual biomass
deltas["reproductivebiomass"]["reproduction"] += _BiomassToAssignToReproductivePotential;
deltas["biomass"]["reproduction"] -= _BiomassToAssignToReproductivePotential;
}
/// <summary>
/// Remove human appropriated matter from the grid cell autotroph stocks
/// </summary>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="humanNPPScenario">The type of NPP extraction to apply</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingStock">The position of the acting stock in the jagged array of grid cell stocks</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="burninSteps">The number of steps to run before impact is simulated</param>
/// <param name="impactSteps">The number of time steps to apply the impact for (for 'temporary' scenarios)</param>
/// <param name="impactCell">Whether this cell should have human impacts applied</param>
/// <remarks>Scenario types are: 'no' = no removal; 'hanpp' = appropriated NPP estimate from input map; constant = constant appropriation after burn-in;
/// temporary = constant after burn-in until specified time; value = proportion of plant biomass appropriated</remarks>
public double RemoveHumanAppropriatedMatter(double wetMatterNPP, SortedList <string, double[]> cellEnvironment,
Tuple <string, double, double> humanNPPScenario, GridCellStockHandler
gridCellStocks, int[] actingStock, uint currentTimestep, uint burninSteps,
uint impactSteps, uint recoverySteps, uint instantStep, uint numInstantStep, Boolean impactCell,
string globalModelTimestepUnits)
{
double RemovalRate = 0.0;
if (impactCell)
{
// Factor to convert NPP from units per m2 to units per km2
double m2Tokm2Conversion = 1000000.0;
if (humanNPPScenario.Item1 == "hanpp")
{
if (currentTimestep > burninSteps)
{
// Loop over stocks in the grid cell and calculate the total biomass of all stocks
double TotalAutotrophBiomass = 0.0;
foreach (var stockFunctionalGroup in gridCellStocks)
{
for (int i = 0; i < stockFunctionalGroup.Count; i++)
{
TotalAutotrophBiomass += stockFunctionalGroup[i].TotalBiomass;
}
}
// Get the total amount of NPP appropriated by humans from this cell
double HANPP = cellEnvironment["HANPP"][0];
// If HANPP value is missing, then assume zero
if (HANPP == cellEnvironment["Missing Value"][0])
{
HANPP = 0.0;
}
HANPP *= cellEnvironment["Seasonality"][currentTimestep % 12];
// Allocate HANPP for this stock according to the proportion of total autotroph biomass that the stock represents
if (TotalAutotrophBiomass == 0.0)
{
HANPP = 0.0;
}
else
{
HANPP *= (gridCellStocks[actingStock].TotalBiomass / TotalAutotrophBiomass);
}
// Convert gC/m2/month to gC/km2/month
HANPP *= m2Tokm2Conversion;
// Multiply by cell area (in km2) to get g/cell/day
HANPP *= cellEnvironment["Cell Area"][0];
// Convert from gC to g dry matter
double DryMatterAppropriated = HANPP * 2;
// Convert from g dry matter to g wet matter
double WetMatterAppropriated = DryMatterAppropriated * 2;
//Calculate the rate of HANPP offtake
if (wetMatterNPP.CompareTo(0.0) == 0)
{
RemovalRate = 0.0;
}
else
{
RemovalRate = Math.Min(1.0, WetMatterAppropriated / wetMatterNPP);
}
// Remove human appropriated autotroph biomass from total autotroph biomass
//gridCellStocks[actingStock].TotalBiomass -= WetMatterAppropriated;
//if (gridCellStocks[actingStock].TotalBiomass < 0.0) gridCellStocks[actingStock].TotalBiomass = 0.0;
}
}
else if (humanNPPScenario.Item1 == "no")
{
// Do not remove any autotroph biomass
}
else if (humanNPPScenario.Item1 == "constant")
{
// If the burn-in period has been completed, then remove the specified constant
// fraction from the acting autotroph stock
if (currentTimestep > burninSteps)
{
//gridCellStocks[actingStock].TotalBiomass -= (gridCellStocks[actingStock].TotalBiomass *
// humanNPPScenario.Item2);
RemovalRate = humanNPPScenario.Item2;
}
}
else if (humanNPPScenario.Item1 == "temporary")
{
// If the spin-up period has been completed and the period of impact has not elapsed,
// then remove the specified constant fraction from the acting autotroph stock
if ((currentTimestep > burninSteps) && (currentTimestep <= (burninSteps + impactSteps)))
{
//gridCellStocks[actingStock].TotalBiomass -= (gridCellStocks[actingStock].TotalBiomass *
// humanNPPScenario.Item2);
RemovalRate = humanNPPScenario.Item2;
}
}
else if (humanNPPScenario.Item1 == "escalating")
{
// If the spin-up period has been completed, then remove a proportion of plant matter
// according to the number of time-steps that have elapsed since the spin-up ended
if (currentTimestep > burninSteps)
{
//gridCellStocks[actingStock].TotalBiomass -= gridCellStocks[actingStock].TotalBiomass *
// (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
RemovalRate = (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
}
}
else if (humanNPPScenario.Item1 == "temp-escalating")
{
// If the spin-up period has been completed and the period of impact has not elapsed,
// then remove a proportion of plant matter
// according to the number of time-steps that have elapsed since the spin-up ended
if ((currentTimestep > burninSteps) && (currentTimestep <= (burninSteps + impactSteps)))
{
//gridCellStocks[actingStock].TotalBiomass -= gridCellStocks[actingStock].TotalBiomass *
// (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
RemovalRate = (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
}
}
else if (humanNPPScenario.Item1 == "temp-escalating-const-rate")
{
// If the spin-up period has been completed and the period of impact (specified by the third scenario element
// has not elapsed,
// then remove a proportion of plant matter
// according to the number of time-steps that have elapsed since the spin-up ended
int ConstImpactSteps = Convert.ToInt32(humanNPPScenario.Item3 * _Utilities.ConvertTimeUnits("year", globalModelTimestepUnits));
if ((currentTimestep > burninSteps) && (currentTimestep <= (burninSteps + ConstImpactSteps)))
{
//gridCellStocks[actingStock].TotalBiomass -= gridCellStocks[actingStock].TotalBiomass *
// (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
RemovalRate = (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
}
}
else if (humanNPPScenario.Item1 == "temp-escalating-const-rate-duration")
{
// If the spin-up period has been completed and the period of impact (specified by the third scenario element
// has not elapsed,
// then remove a proportion of plant matter
// according to the number of time-steps that have elapsed since the spin-up ended
int ConstImpactSteps = Convert.ToInt32(humanNPPScenario.Item3 * _Utilities.ConvertTimeUnits("year", globalModelTimestepUnits));
if ((currentTimestep > burninSteps) && (currentTimestep <= (burninSteps + impactSteps)))
{
//gridCellStocks[actingStock].TotalBiomass -= gridCellStocks[actingStock].TotalBiomass *
// (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
RemovalRate = (Math.Min(1.0,
Math.Min(((ConstImpactSteps / 12.0) * humanNPPScenario.Item2),
(((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2))));
}
}
else if (humanNPPScenario.Item1 == "temp-escalating-declining")
{
// If the spin-up period has been completed, then apply a level of harvesting
// according to the number of time-steps that have elapsed since the spin-up ended
if ((currentTimestep > burninSteps) && (currentTimestep <= (burninSteps + impactSteps)))
{
//gridCellStocks[actingStock].TotalBiomass -= gridCellStocks[actingStock].TotalBiomass *
// (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2)));
RemovalRate = Math.Max(0.0, (Math.Min(1.0, (((currentTimestep - burninSteps) / 12.0) * humanNPPScenario.Item2))));
}
else if ((currentTimestep > (burninSteps + impactSteps)) & (currentTimestep <= (burninSteps + impactSteps + recoverySteps)))
{
//gridCellStocks[actingStock].TotalBiomass -= gridCellStocks[actingStock].TotalBiomass *
// (Math.Min(1.0, (((burninSteps + impactSteps + recoverySteps - currentTimestep) / 12.0) * humanNPPScenario.Item2)));
//RemovalRate = (Math.Min(1.0, (((burninSteps + impactSteps + recoverySteps - currentTimestep) / 12.0) * humanNPPScenario.Item2)));
RemovalRate = Math.Max(0.0, Math.Min(1.0, ((int)((impactSteps) - (currentTimestep - (burninSteps + impactSteps))) / 12.0) * humanNPPScenario.Item2));
}
}
else
{
Debug.Fail("There is no method for the human extraction of NPP scenario specified");
}
}
return(RemovalRate);
}
/// <summary>
/// Apply the changes from predation to prey cohorts, and update deltas for the predator cohort
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The acting cohort</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The functional group definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The functional group definitions for stocks in the model</param>
/// <param name="trackProcesses">An instance of ProcessTracker to hold diagnostics for predation</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="outputDetail">The level of output detail used in this model run</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
public void RunEating(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, int[] actingCohort, SortedList <string, double[]>
cellEnvironment, Dictionary <string, Dictionary <string, double> > deltas, FunctionalGroupDefinitions madingleyCohortDefinitions,
FunctionalGroupDefinitions madingleyStockDefinitions, ProcessTracker trackProcesses, uint currentTimestep, Boolean specificLocations,
string outputDetail, MadingleyModelInitialisation initialisation)
{
if (trackProcesses.TrackProcesses)
{
Track = (RandomNumberGenerator.GetUniform() > 0.975) ? true : false;
}
TempDouble = 0.0;
// Temporary variable to hold the total time spent eating + 1. Saves an extra calculation in CalculateAbundanceEaten
double TotalTimeUnitsToHandlePlusOne = TimeUnitsToHandlePotentialFoodItems + 1;
// Loop over potential prey functional groups
foreach (int FunctionalGroup in _FunctionalGroupIndicesToEat)
{
// Loop over cohorts within the functional group
for (int i = 0; i < NumberCohortsPerFunctionalGroupNoNewCohorts[FunctionalGroup]; i++)
{
// Get the individual body mass of this cohort
_BodyMassPrey = gridCellCohorts[FunctionalGroup][i].IndividualBodyMass;
// Calculate the actual abundance of prey eaten from this cohort
if (gridCellCohorts[FunctionalGroup][i].CohortAbundance > 0)
{
// Calculate the actual abundance of prey eaten from this cohort
_AbundancesEaten[FunctionalGroup][i] = CalculateAbundanceEaten(_PotentialAbundanceEaten[FunctionalGroup][i], _PredatorAbundanceMultipliedByTimeEating,
TotalTimeUnitsToHandlePlusOne, gridCellCohorts[FunctionalGroup][i].CohortAbundance);
}
else
{
_AbundancesEaten[FunctionalGroup][i] = 0;
}
// Remove number of prey eaten from the prey cohort
gridCellCohorts[FunctionalGroup][i].CohortAbundance -= _AbundancesEaten[FunctionalGroup][i];
gridCellCohorts[actingCohort].TrophicIndex += (_BodyMassPrey + gridCellCohorts[FunctionalGroup][i].IndividualReproductivePotentialMass) * _AbundancesEaten[FunctionalGroup][i] * gridCellCohorts[FunctionalGroup][i].TrophicIndex;
// If the process tracker is set and output detail is set to high and the prey cohort has never been merged,
// then track its mortality owing to predation
if (trackProcesses.TrackProcesses)
{
if ((outputDetail == "high") && (gridCellCohorts[FunctionalGroup][i].CohortID.Count == 1) &&
AbundancesEaten[FunctionalGroup][i] > 0)
{
trackProcesses.RecordMortality((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0], gridCellCohorts
[FunctionalGroup][i].BirthTimeStep, currentTimestep, gridCellCohorts[FunctionalGroup][i].IndividualBodyMass,
gridCellCohorts[FunctionalGroup][i].AdultMass, gridCellCohorts[FunctionalGroup][i].FunctionalGroupIndex,
gridCellCohorts[FunctionalGroup][i].CohortID[0], AbundancesEaten[FunctionalGroup][i], "predation");
}
// If the model is being run for specific locations and if track processes has been specified, then track the mass flow between
// prey and predator
if (specificLocations)
{
trackProcesses.RecordPredationMassFlow(currentTimestep, _BodyMassPrey, _BodyMassPredator, _BodyMassPrey *
_AbundancesEaten[FunctionalGroup][i]);
if (outputDetail == "high")
{
trackProcesses.TrackPredationTrophicFlow((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0],
gridCellCohorts[FunctionalGroup][i].FunctionalGroupIndex, gridCellCohorts[actingCohort].FunctionalGroupIndex,
madingleyCohortDefinitions, (_AbundancesEaten[FunctionalGroup][i] * _BodyMassPrey), _BodyMassPredator, _BodyMassPrey,
initialisation, cellEnvironment["Realm"][0] == 2.0);
}
}
}
// Check that the abundance eaten from this cohort is not negative
// Commented out for the purposes of speed
//Debug.Assert( _AbundancesEaten[FunctionalGroup][i].CompareTo(0.0) >= 0,
// "Predation negative for this prey cohort" + actingCohort);
// Create a temporary value to speed up the predation function
// This is equivalent to the body mass of the prey cohort including reproductive potential mass, times the abundance eaten of the prey cohort,
// divided by the abundance of the predator
TempDouble += (_BodyMassPrey + gridCellCohorts[FunctionalGroup][i].IndividualReproductivePotentialMass) * _AbundancesEaten[FunctionalGroup][i] / _AbundancePredator;
}
}
// Add the biomass eaten and assimilated by an individual to the delta biomass for the acting (predator) cohort
deltas["biomass"]["predation"] = TempDouble * _PredatorAssimilationEfficiency;
// Move the biomass eaten but not assimilated by an individual into the organic matter pool
deltas["organicpool"]["predation"] = TempDouble * _PredatorNonAssimilation * _AbundancePredator;
// Check that the delta biomass from eating for the acting cohort is not negative
//Debug.Assert(deltas["biomass"]["predation"] >= 0, "Predation yields negative biomass");
// Calculate the total biomass eaten by the acting (predator) cohort
_TotalBiomassEatenByCohort = deltas["biomass"]["predation"] * _AbundancePredator;
}
/// <summary>
/// Convert NPP estimate into biomass of an autotroph stock
/// </summary>
/// <param name="cellEnvironment">The environment of the current grid cell</param>
/// <param name="gridCellStockHandler">The stock handler for the current stock</param>
/// <param name="actingStock">The location of the stock to add biomass to</param>
/// <param name="terrestrialNPPUnits">The units of the terrestrial NPP data</param>
/// <param name="oceanicNPPUnits">The units of the oceanic NPP data</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="GlobalModelTimeStepUnit">The time step unit used in the model</param>
/// <param name="trackProcesses">Whether to output data describing the ecological processes</param>
/// <param name="globalTracker">Whether to output data describing the global-scale environment</param>
/// <param name="outputDetail">The level of output detail to use for the outputs</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="currentMonth">The current month in the model run</param>
public void ConvertNPPToAutotroph(SortedList <string, double[]> cellEnvironment, GridCellStockHandler gridCellStockHandler, int[]
actingStock, string terrestrialNPPUnits, string oceanicNPPUnits, uint currentTimestep, string GlobalModelTimeStepUnit,
ProcessTracker trackProcesses, GlobalProcessTracker globalTracker, string outputDetail, bool specificLocations, uint currentMonth)
{
// Get NPP from the cell environment
double NPP = cellEnvironment["NPP"][currentMonth];
// If NPP is a mssing value then set to zero
if (NPP == cellEnvironment["Missing Value"][0])
{
NPP = 0.0;
}
// Check that this is an ocean cell
if (cellEnvironment["Realm"][0] == 2.0)
{
// Check that the units of oceanic NPP are gC per m2 per day
Debug.Assert(oceanicNPPUnits == "gC/m2/day", "Oceanic NPP data are not in the correct units for this formulation of the model");
// Convert to g/cell/month
NPP *= _MsqToKmSqConversion;
// Multiply by cell area to get g/cell/day
NPP *= cellEnvironment["Cell Area"][0];
// Convert to g wet matter, assuming carbon content of phytoplankton is 10% of wet matter
NPP *= _PhytoplanktonConversionRatio;
// Finally convert to g/cell/month and add to the stock totalbiomass
NPP *= Utilities.ConvertTimeUnits(GlobalModelTimeStepUnit, "day");
gridCellStockHandler[actingStock].TotalBiomass += NPP;
if (trackProcesses.TrackProcesses && (outputDetail == "high") && specificLocations)
{
trackProcesses.TrackPrimaryProductionTrophicFlow((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0],
NPP);
}
if (globalTracker.TrackProcesses)
{
globalTracker.RecordNPP((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0], (uint)actingStock[0],
NPP / cellEnvironment["Cell Area"][0]);
}
// If the biomass of the autotroph stock has been made less than zero (i.e. because of negative NPP) then reset to zero
if (gridCellStockHandler[actingStock].TotalBiomass < 0.0)
{
gridCellStockHandler[actingStock].TotalBiomass = 0.0;
}
}
// Else if neither on land or in the ocean
else
{
Debug.Fail("This is not a marine cell!");
// Set the autotroph biomass to zero
gridCellStockHandler[actingStock].TotalBiomass = 0.0;
}
Debug.Assert(gridCellStockHandler[actingStock].TotalBiomass >= 0.0, "stock negative");
}
/// <summary>
/// Gets a state variable density for specified functional groups of specified entity types in a specified grid cell
/// </summary>
/// <param name="variableName">The name of the variable to get: 'biomass' or 'abundance'</param>
/// <param name="traitValue">The functional group trait value to get data for</param>
/// <param name="functionalGroups">The functional group indices to get the state variable for</param>
/// <param name="latCellIndex">The latitudinal index of the cell</param>
/// <param name="lonCellIndex">The longitudinal index of the cell</param>
/// <param name="stateVariableType">The type of entity to return the state variable for: 'stock' or 'cohort'</param>
/// <param name="modelInitialisation">The Madingley Model initialisation</param>
/// <returns>The state variable density for specified functional groups of specified entity types in a specified grid cell</returns>
public double GetStateVariableDensity(string variableName, string traitValue, int[] functionalGroups, uint latCellIndex,
uint lonCellIndex, string stateVariableType, MadingleyModelInitialisation modelInitialisation)
{
double returnValue = 0.0;
switch (stateVariableType.ToLower())
{
case "cohort":
GridCellCohortHandler TempCohorts = InternalGrid[latCellIndex, lonCellIndex].GridCellCohorts;
switch (variableName.ToLower())
{
case "biomass":
if (traitValue != "Zooplankton (all)")
{
foreach (int f in functionalGroups)
{
foreach (var item in TempCohorts[f])
{
returnValue += ((item.IndividualBodyMass + item.IndividualReproductivePotentialMass) * item.CohortAbundance);
}
}
}
else
{
foreach (int f in functionalGroups)
{
foreach (var item in TempCohorts[f])
{
if (item.IndividualBodyMass <= modelInitialisation.PlanktonDispersalThreshold)
{
returnValue += ((item.IndividualBodyMass + item.IndividualReproductivePotentialMass) * item.CohortAbundance);
}
}
}
}
break;
case "abundance":
if (traitValue != "Zooplankton (all)")
{
foreach (int f in functionalGroups)
{
foreach (var item in TempCohorts[f])
{
returnValue += item.CohortAbundance;
}
}
}
else
{
foreach (int f in functionalGroups)
{
foreach (var item in TempCohorts[f])
{
if (item.IndividualBodyMass <= modelInitialisation.PlanktonDispersalThreshold)
{
returnValue += item.CohortAbundance;
}
}
}
}
break;
default:
Debug.Fail("For cohorts, state variable name must be either 'biomass' or 'abundance'");
break;
}
break;
case "stock":
GridCellStockHandler TempStocks = InternalGrid[latCellIndex, lonCellIndex].GridCellStocks;
switch (variableName.ToLower())
{
case "biomass":
foreach (int f in functionalGroups)
{
foreach (var item in TempStocks[f])
{
returnValue += item.TotalBiomass;
}
}
break;
default:
Debug.Fail("For stocks, state variable name must be 'biomass'");
break;
}
break;
default:
Debug.Fail("State variable type must be either 'cohort' or 'stock'");
break;
}
return(returnValue / (InternalGrid[latCellIndex, lonCellIndex].CellEnvironment["Cell Area"][0]));
}
/// <summary>
/// Generate new cohorts from reproductive potential mass
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingCohort">The position of the acting cohort in the jagged array of grid cell cohorts</param>
/// <param name="cellEnvironment">The environment of the current grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions of cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions of stock functional groups in the model</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="tracker">An instance of ProcessTracker to hold diagnostics for reproduction</param>
/// <param name="partial">Thread-locked variables</param>
/// <param name="iteroparous">Whether the acting cohort is iteroparous, as opposed to semelparous</param>
/// <param name="currentMonth">The current model month</param>
public void RunReproductionEvents(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
int[] actingCohort, SortedList <string, double[]> cellEnvironment, Dictionary <string, Dictionary <string, double> >
deltas, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
uint currentTimestep, ProcessTracker tracker, ref ThreadLockedParallelVariables partial, bool iteroparous, uint currentMonth)
{
// Adult non-reproductive biomass lost by semelparous organisms
double AdultMassLost;
// Offspring cohort abundance
double _OffspringCohortAbundance;
// Mass ratio of body mass + reproductive mass to adult body mass
double CurrentMassRatio;
// Individual body mass including change this time step as a result of other ecological processes
double BodyMassIncludingChangeThisTimeStep;
// Offspring juvenile and adult body masses
double[] OffspringJuvenileAndAdultBodyMasses = new double[2];
// Offspring cohort
Cohort OffspringCohort;
// Individual reproductive mass including change this time step as a result of other ecological processes
double ReproductiveMassIncludingChangeThisTimeStep;
// Calculate the biomass of an individual in this cohort including changes this time step from other ecological processes
BodyMassIncludingChangeThisTimeStep = 0.0;
foreach (var Biomass in deltas["biomass"])
{
// Add the delta biomass to net biomass
BodyMassIncludingChangeThisTimeStep += Biomass.Value;
}
BodyMassIncludingChangeThisTimeStep += gridCellCohorts[actingCohort].IndividualBodyMass;
// Calculate the reproductive biomass of an individual in this cohort including changes this time step from other ecological processes
ReproductiveMassIncludingChangeThisTimeStep = 0.0;
foreach (var ReproBiomass in deltas["reproductivebiomass"])
{
// Add the delta reproductive biomass to net biomass
ReproductiveMassIncludingChangeThisTimeStep += ReproBiomass.Value;
}
ReproductiveMassIncludingChangeThisTimeStep += gridCellCohorts[actingCohort].IndividualReproductivePotentialMass;
// Get the current ratio of total individual mass (including reproductive potential) to adult body mass
CurrentMassRatio = (BodyMassIncludingChangeThisTimeStep + ReproductiveMassIncludingChangeThisTimeStep) / gridCellCohorts[actingCohort].AdultMass;
// Must have enough mass to hit reproduction threshold criterion, and either (1) be in breeding season, or (2) be a marine cell (no breeding season in marine cells)
if ((CurrentMassRatio > _MassRatioThreshold) && ((cellEnvironment["Breeding Season"][currentMonth] == 1.0) || ((cellEnvironment["Realm"][0] == 2.0))))
{
// Iteroparous and semelparous organisms have different strategies
if (iteroparous)
{
// Iteroparous organisms do not allocate any of their current non-reproductive biomass to reproduction
AdultMassLost = 0.0;
// Calculate the number of offspring that could be produced given the reproductive potential mass of individuals
_OffspringCohortAbundance = gridCellCohorts[actingCohort].CohortAbundance * ReproductiveMassIncludingChangeThisTimeStep /
gridCellCohorts[actingCohort].JuvenileMass;
}
else
{
// Semelparous organisms allocate a proportion of their current non-reproductive biomass (including the effects of other ecological processes) to reproduction
AdultMassLost = _SemelparityAdultMassAllocation * BodyMassIncludingChangeThisTimeStep;
// Calculate the number of offspring that could be produced given the reproductive potential mass of individuals
_OffspringCohortAbundance = gridCellCohorts[actingCohort].CohortAbundance * (AdultMassLost + ReproductiveMassIncludingChangeThisTimeStep) /
gridCellCohorts[actingCohort].JuvenileMass;
}
// Check that the abundance in the cohort to produce is greater than or equal to zero
Debug.Assert(_OffspringCohortAbundance >= 0.0, "Offspring abundance < 0");
// Get the adult and juvenile masses of the offspring cohort
OffspringJuvenileAndAdultBodyMasses = GetOffspringCohortProperties(gridCellCohorts, actingCohort, madingleyCohortDefinitions);
// Update cohort abundance in case juvenile mass has been altered through 'evolution'
_OffspringCohortAbundance = (_OffspringCohortAbundance * gridCellCohorts[actingCohort].JuvenileMass) / OffspringJuvenileAndAdultBodyMasses[0];
double TrophicIndex;
switch (madingleyCohortDefinitions.GetTraitNames("nutrition source", actingCohort[0]))
{
case "herbivore":
TrophicIndex = 2;
break;
case "omnivore":
TrophicIndex = 2.5;
break;
case "carnivore":
TrophicIndex = 3;
break;
default:
Debug.Fail("Unexpected nutrition source trait value when assigning trophic index");
TrophicIndex = 0.0;
break;
}
// Create the offspring cohort
OffspringCohort = new Cohort((byte)actingCohort[0], OffspringJuvenileAndAdultBodyMasses[0], OffspringJuvenileAndAdultBodyMasses[1], OffspringJuvenileAndAdultBodyMasses[0],
_OffspringCohortAbundance, Math.Exp(gridCellCohorts[actingCohort].LogOptimalPreyBodySizeRatio),
(ushort)currentTimestep, gridCellCohorts[actingCohort].ProportionTimeActive, ref partial.NextCohortIDThreadLocked, TrophicIndex, tracker.TrackProcesses);
// Add the offspring cohort to the grid cell cohorts array
gridCellCohorts[actingCohort[0]].Add(OffspringCohort);
// If track processes has been specified then add the new cohort to the process tracker
if (tracker.TrackProcesses)
{
tracker.RecordNewCohort((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0],
currentTimestep, _OffspringCohortAbundance, gridCellCohorts[actingCohort].AdultMass, gridCellCohorts[actingCohort].FunctionalGroupIndex,
gridCellCohorts[actingCohort].CohortID, (uint)partial.NextCohortIDThreadLocked);
}
// Subtract all of the reproductive potential mass of the parent cohort, which has been used to generate the new
// cohort, from the delta reproductive potential mass and delta adult body mass
deltas["reproductivebiomass"]["reproduction"] -= ReproductiveMassIncludingChangeThisTimeStep;
deltas["biomass"]["reproduction"] -= AdultMassLost;
}
else
{
// Organism is not large enough, or it is not the breeding season, so take no action
}
}
/// <summary>
/// Update the leaf stock during a time step given the environmental conditions in the grid cell
/// </summary>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="actingStock">The position of the acting stock in the array of grid cell stocks</param>
/// <param name="currentTimeStep">The current model time step</param>
/// <param name="deciduous">Whether the acting stock consists of deciduous leaves</param>
/// <param name="GlobalModelTimeStepUnit">The time step unit used in the model</param>
/// <param name="tracker">Whether to track properties of the ecological processes</param>
/// <param name="globalTracker">Whether to output data describing the global environment</param>
/// <param name="currentMonth">The current model month</param>
/// <param name="outputDetail">The level of detail to use in model outputs</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
public double UpdateLeafStock(SortedList <string, double[]> cellEnvironment, GridCellStockHandler gridCellStocks, int[] actingStock,
uint currentTimeStep, bool deciduous, string GlobalModelTimeStepUnit, ProcessTracker tracker, GlobalProcessTracker globalTracker,
uint currentMonth, string outputDetail, bool specificLocations)
{
// ESTIMATE ANNUAL LEAF CARBON FIXATION ASSUMING ENVIRONMENT THROUGHOUT THE YEAR IS THE SAME AS IN THIS MONTH
// Calculate annual NPP
double NPP = this.CalculateMiamiNPP(cellEnvironment["Temperature"].Average(), cellEnvironment["Precipitation"].Sum());
// Calculate fractional allocation to structural tissue
double FracStruct = this.CalculateFracStruct(NPP);
// Estimate monthly NPP based on seasonality layer
NPP *= cellEnvironment["Seasonality"][currentMonth];
// Calculate leaf mortality rates
double AnnualLeafMortRate;
double MonthlyLeafMortRate;
double TimeStepLeafMortRate;
if (deciduous)
{
// Calculate annual deciduous leaf mortality
AnnualLeafMortRate = this.CalculateDeciduousAnnualLeafMortality(cellEnvironment["Temperature"].Average());
// For deciduous plants monthly leaf mortality is weighted by temperature deviance from the average, to capture seasonal patterns
double[] ExpTempDev = new double[12];
double SumExpTempDev = 0.0;
double[] TempDev = new double[12];
double Weight;
for (int i = 0; i < 12; i++)
{
TempDev[i] = cellEnvironment["Temperature"][i] - cellEnvironment["Temperature"].Average();
ExpTempDev[i] = Math.Exp(-TempDev[i] / 3);
SumExpTempDev += ExpTempDev[i];
}
Weight = ExpTempDev[currentMonth] / SumExpTempDev;
MonthlyLeafMortRate = AnnualLeafMortRate * Weight;
TimeStepLeafMortRate = MonthlyLeafMortRate * Utilities.ConvertTimeUnits(GlobalModelTimeStepUnit, "month");
}
else
{
// Calculate annual evergreen leaf mortality
AnnualLeafMortRate = this.CalculateEvergreenAnnualLeafMortality(cellEnvironment["Temperature"].Average());
// For evergreen plants, leaf mortality is assumed to be equal throughout the year
MonthlyLeafMortRate = AnnualLeafMortRate * (1.0 / 12.0);
TimeStepLeafMortRate = MonthlyLeafMortRate * Utilities.ConvertTimeUnits(GlobalModelTimeStepUnit, "month");
}
// Calculate fine root mortality rate
double AnnualFRootMort = this.CalculateFineRootMortalityRate(cellEnvironment["Temperature"][currentMonth]);
// Calculate the NPP allocated to non-structural tissues
double FracNonStruct = (1 - FracStruct);
// Calculate the fractional allocation to leaves
double FracLeaves = FracNonStruct * this.CalculateLeafFracAllocation(AnnualLeafMortRate, AnnualFRootMort);
// Calculate the fractional allocation of NPP to evergreen plant matter
double FracEvergreen = this.CalculateFracEvergreen(cellEnvironment["Fraction Year Frost"][0]);
// Update NPP depending on whether the acting stock is deciduous or evergreen
if (deciduous)
{
NPP *= (1 - FracEvergreen);
}
else
{
NPP *= FracEvergreen;
}
// Calculate the fire mortality rate
double FireMortRate = this.CalculateFireMortalityRate(NPP, cellEnvironment["Fraction Year Fire"][0]);
// Calculate the structural mortality rate
double StMort = this.CalculateStructuralMortality(cellEnvironment["AET"][currentMonth] * 12);
// Calculate leaf C fixation
double LeafCFixation = NPP * FracLeaves;
// Convert from carbon to leaf wet matter
double WetMatterIncrement = this.ConvertToLeafWetMass(LeafCFixation, cellEnvironment["Cell Area"][0]);
// Convert from the monthly time step used for this process to the global model time step unit
WetMatterIncrement *= Utilities.ConvertTimeUnits(GlobalModelTimeStepUnit, "month");
// Add the leaf wet matter to the acting stock
//gridCellStocks[actingStock].TotalBiomass += Math.Max(-gridCellStocks[actingStock].TotalBiomass, WetMatterIncrement);
double NPPWetMatter = Math.Max(-gridCellStocks[actingStock].TotalBiomass, WetMatterIncrement);
// If the processer tracker is enabled and output detail is high and the model is being run for specific locations, then track the biomass gained through primary production
if (tracker.TrackProcesses && (outputDetail == "high") && specificLocations)
{
tracker.TrackPrimaryProductionTrophicFlow((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0],
Math.Max(-gridCellStocks[actingStock].TotalBiomass, WetMatterIncrement));
}
if (globalTracker.TrackProcesses)
{
globalTracker.RecordNPP((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0], (uint)actingStock[0],
this.ConvertToLeafWetMass(NPP, cellEnvironment["Cell Area"][0]) *
Utilities.ConvertTimeUnits(GlobalModelTimeStepUnit, "month") / cellEnvironment["Cell Area"][0]);
}
// Calculate fractional leaf mortality
double LeafMortFrac = 1 - Math.Exp(-TimeStepLeafMortRate);
// Update the leaf stock biomass owing to the leaf mortality
gridCellStocks[actingStock].TotalBiomass *= (1 - LeafMortFrac);
NPPWetMatter *= (1 - LeafMortFrac);
return(NPPWetMatter);
}
/// <summary>
/// Initialize an implementation of reproduction. This is only in here to satisfy the requirements of IEcologicalProcessWithinGridCells
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stock functional groups in the model</param>
/// <param name="implementationKey">The name of the reproduction implementation to initialize</param>
public void InitializeEcologicalProcess(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions, string implementationKey)
{
}
/// <summary>
/// Initialises herbivory implementation each time step
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stocks in the model</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <remarks>This only works if: a) herbivory is initialised in every grid cell; and b) if parallelisation is done by latitudinal strips
/// It is critical to run this every time step</remarks>
public void InitializeEatingPerTimeStep(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions, SortedList <string, double[]>
cellEnvironment)
{
// Get the functional group indices of all autotroph stocks
_FunctionalGroupIndicesToEat = madingleyStockDefinitions.GetFunctionalGroupIndex("Heterotroph/Autotroph", "Autotroph", false);
string[] realm = { "Terrestrial", "Marine" };
int realm_index = (int)cellEnvironment["Realm"][0] - 1;
string Current_realm = realm[realm_index];
}
/// <summary>
/// Initialize an implementation of mortality. This is only in here to satisfy the requirements of IEcologicalProcessAcrossGridCells
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohort functional groups in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stock functional groups in the model</param>
/// <param name="implementationKey">The name of the implementation of mortality to initialize</param>
public void InitializeEcologicalProcess(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks,
FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions,
string implementationKey, SortedList <string, double[]> cellEnvironmen)
{
}
/// <summary>
/// Calculate the actual amount eaten in herbivory, apply the changes to the eaten autotroph stocks, and update deltas for the herbivore cohort
/// </summary>
/// <param name="gridCellCohorts">The cohorts in this grid cell</param>
/// <param name="gridCellStocks">The stocks in this grid cell</param>
/// <param name="actingCohort">The acting cohort</param>
/// <param name="cellEnvironment">The environmental conditions in this grid cell</param>
/// <param name="deltas">The sorted list to track changes in biomass and abundance of the acting cohort in this grid cell</param>
/// <param name="madingleyCohortDefinitions">The functional group definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The functional group definitions for stocks in the model</param>
/// <param name="trackProcesses">An instance of ProcessTracker to hold diagnostics for herbivory</param>
/// <param name="currentTimestep">The current model time step</param>
/// <param name="specificLocations">Whether the model is being run for specific locations</param>
/// <param name="outputDetail">The level of output detail being used in this model run</param>
/// <param name="initialisation">The Madingley Model initialisation</param>
public void RunEating(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, int[] actingCohort, SortedList <string, double[]>
cellEnvironment, Dictionary <string, Dictionary <string, double> > deltas, FunctionalGroupDefinitions madingleyCohortDefinitions,
FunctionalGroupDefinitions madingleyStockDefinitions, ProcessTracker trackProcesses, uint currentTimestep, Boolean specificLocations,
string outputDetail, MadingleyModelInitialisation initialisation)
{
EdibleScaling = 1.0;
if (cellEnvironment["Realm"][0] == 1.0)
{
EdibleScaling = 0.1;
}
// Loop over autotroph functional groups that can be eaten
foreach (int FunctionalGroup in _FunctionalGroupIndicesToEat)
{
// Loop over stocks within the functional groups
for (int i = 0; i < gridCellStocks[FunctionalGroup].Count; i++)
{
// Get the mass from this stock that is available for eating (assumes only 10% is edible in the terrestrial realm)
EdibleMass = gridCellStocks[FunctionalGroup][i].TotalBiomass * EdibleScaling;
// Calculate the biomass actually eaten from this stock by the acting cohort
_BiomassesEaten[FunctionalGroup][i] = CalculateBiomassesEaten(_PotentialBiomassesEaten[FunctionalGroup][i],
_TimeUnitsToHandlePotentialFoodItems, gridCellCohorts[actingCohort].CohortAbundance, EdibleMass);
gridCellCohorts[actingCohort].TrophicIndex += _BiomassesEaten[FunctionalGroup][i];
// Remove the biomass eaten from the autotroph stock
gridCellStocks[FunctionalGroup][i].TotalBiomass -= _BiomassesEaten[FunctionalGroup][i];
// If the model is being run for specific locations and if track processes has been specified, then track the mass flow between
// primary producer and herbivore
if (specificLocations && trackProcesses.TrackProcesses)
{
trackProcesses.RecordHerbivoryMassFlow(currentTimestep, _BodyMassHerbivore, _BiomassesEaten[FunctionalGroup][i]);
}
// If track processes has been specified and the output detail level is set to high and the model is being run for specific locations,
// then track the flow of mass between trophic levels
if (trackProcesses.TrackProcesses && (outputDetail == "high") && specificLocations)
{
trackProcesses.TrackHerbivoryTrophicFlow((uint)cellEnvironment["LatIndex"][0], (uint)cellEnvironment["LonIndex"][0],
gridCellCohorts[actingCohort].FunctionalGroupIndex, madingleyCohortDefinitions, _BiomassesEaten[FunctionalGroup][i], _BodyMassHerbivore, initialisation, cellEnvironment["Realm"][0] == 2.0);
}
// Check that the biomass eaten is not a negative value
// Commented out for purposes of speed
//Debug.Assert(_BiomassesEaten[FunctionalGroup][i] >= 0,
// "Herbivory negative for this herbivore cohort" + actingCohort);
// Add the biomass eaten and assimilated by an individual to the delta biomass for the acting cohort
deltas["biomass"]["herbivory"] += _BiomassesEaten[FunctionalGroup][i] * AssimilationEfficiency / gridCellCohorts[actingCohort].CohortAbundance;
// Move the biomass eaten but not assimilated by an individual into the organic matter pool
deltas["organicpool"]["herbivory"] += _BiomassesEaten[FunctionalGroup][i] * (1 - AssimilationEfficiency);
}
// Check that the delta biomass from eating for the acting cohort is not negative
// Commented out for the purposes of speed
//Debug.Assert(deltas["biomass"]["herbivory"] >= 0, "Delta biomass from herbviory is negative");
// Calculate the total biomass eaten by the acting (herbivore) cohort
_TotalBiomassEatenByCohort = deltas["biomass"]["herbivory"] * gridCellCohorts[actingCohort].CohortAbundance;
}
}
/// <summary>
/// Initialises predation implementation each time step
/// </summary>
/// <param name="gridCellCohorts">The cohorts in the current grid cell</param>
/// <param name="gridCellStocks">The stocks in the current grid cell</param>
/// <param name="madingleyCohortDefinitions">The definitions for cohorts in the model</param>
/// <param name="madingleyStockDefinitions">The definitions for stocks in the model</param>
/// <param name="cellEnvironment">The environment in the current grid cell</param>
/// <remarks>This only works if: a) predation is initialised in every grid cell; and b) if parallelisation is done by latitudinal strips
/// It is critical to run this every time step</remarks>
public void InitializeEatingPerTimeStep(GridCellCohortHandler gridCellCohorts, GridCellStockHandler gridCellStocks, FunctionalGroupDefinitions madingleyCohortDefinitions, FunctionalGroupDefinitions madingleyStockDefinitions, SortedList <string, double[]>
cellEnvironment)
{
// Get the functional group indices of all heterotroph cohorts (i.e. potential prey)
// _FunctionalGroupIndicesToEat = madingleyCohortDefinitions.GetFunctionalGroupIndex("Heterotroph/Autotroph", "heterotroph", false);
string [] realm = { "Terrestrial", "Marine" };
int realm_index = (int)cellEnvironment["Realm"][0] - 1;
string Current_realm = realm[realm_index];
_FunctionalGroupIndicesToEat = madingleyCohortDefinitions.GetFunctionalGroupIndex("realm", Current_realm, false);
// Initialise the vector to hold the number of cohorts in each functional group at the start of the time step
NumberCohortsPerFunctionalGroupNoNewCohorts = new int[gridCellCohorts.Count];
// Initialise the jagged arrays to hold the potential and actual numbers of prey eaten in each of the grid cell cohorts
_AbundancesEaten = new double[gridCellCohorts.Count][];
_PotentialAbundanceEaten = new double[gridCellCohorts.Count][];
// Initialise the vector to identify carnivore cohorts
_CarnivoreFunctionalGroups = new Boolean[_FunctionalGroupIndicesToEat.Length];
_OmnivoreFunctionalGroups = new Boolean[_FunctionalGroupIndicesToEat.Length];
_PlanktonFunctionalGroups = new Boolean[_FunctionalGroupIndicesToEat.Length];
// Loop over rows in the jagged arrays, initialise each vector within the jagged arrays, and calculate the current number of cohorts in
// each functional group
for (int i = 0; i < gridCellCohorts.Count; i++)
{
// Calculate the current number of cohorts in this functional group
int NumCohortsThisFG = gridCellCohorts[i].Count;
NumberCohortsPerFunctionalGroupNoNewCohorts[i] = NumCohortsThisFG;
// Initialise the jagged arrays
_AbundancesEaten[i] = new double[NumberCohortsPerFunctionalGroupNoNewCohorts[i]];
_PotentialAbundanceEaten[i] = new double[NumberCohortsPerFunctionalGroupNoNewCohorts[i]];
}
// Loop over functional groups that are potential prey and determine which are carnivores THIS IS COMMENTED OUT AS IT'S NOT USED
//foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
// _CarnivoreFunctionalGroups[FunctionalGroup] = madingleyCohortDefinitions.GetTraitNames("Nutrition source", FunctionalGroup) == "carnivore";
//foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
// _OmnivoreFunctionalGroups[FunctionalGroup] = madingleyCohortDefinitions.GetTraitNames("Nutrition source", FunctionalGroup) == "omnivore";
//foreach (int FunctionalGroup in FunctionalGroupIndicesToEat)
// _PlanktonFunctionalGroups[FunctionalGroup] = madingleyCohortDefinitions.GetTraitNames("Mobility", FunctionalGroup) == "planktonic";
}