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EDCanopyStructureMod.F90
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EDCanopyStructureMod.F90
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module EDCanopyStructureMod
! =====================================================================================
! Code to determine whether the canopy is closed, and which plants are either in the
! understorey or overstorey. This is obviosuly far too complicated for it's own good
! =====================================================================================
use FatesConstantsMod , only : r8 => fates_r8
use FatesConstantsMod , only : itrue, ifalse
use FatesConstantsMod , only : tinyr8
use FatesConstantsMod , only : nearzero, area_error_1
use FatesConstantsMod , only : rsnbl_math_prec
use FatesConstantsMod , only : nocomp_bareground
use FatesConstantsMod, only : i_term_mort_type_canlev
use FatesGlobals , only : fates_log
use EDPftvarcon , only : EDPftvarcon_inst
use PRTParametersMod , only : prt_params
use FatesAllometryMod , only : carea_allom
use EDCohortDynamicsMod , only : terminate_cohorts, terminate_cohort, fuse_cohorts
use EDCohortDynamicsMod , only : InitPRTObject
use FatesAllometryMod , only : tree_lai
use FatesAllometryMod , only : tree_sai
use EDTypesMod , only : ed_site_type
use FatesAllometryMod , only : VegAreaLayer
use FatesAllometryMod , only : CrownDepth
use FatesPatchMod, only : fates_patch_type
use FatesCohortMod, only : fates_cohort_type
use EDParamsMod , only : nclmax
use EDParamsMod , only : nlevleaf
use EDParamsMod , only : radiation_model
use EDtypesMod , only : AREA
use EDLoggingMortalityMod , only : UpdateHarvestC
use FatesGlobals , only : endrun => fates_endrun
use FatesInterfaceTypesMod , only : hlm_days_per_year
use FatesInterfaceTypesMod , only : hlm_use_planthydro
use FatesInterfaceTypesMod , only : hlm_use_cohort_age_tracking
use FatesInterfaceTypesMod , only : hlm_use_sp
use FatesInterfaceTypesMod , only : numpft
use FatesInterfaceTypesMod, only : bc_in_type
use FatesPlantHydraulicsMod, only : UpdateH2OVeg,InitHydrCohort, RecruitWaterStorage
use PRTGenericMod, only : leaf_organ
use PRTGenericMod, only : leaf_organ
use PRTGenericMod, only : fnrt_organ
use PRTGenericMod, only : sapw_organ
use PRTGenericMod, only : store_organ
use PRTGenericMod, only : repro_organ
use PRTGenericMod, only : struct_organ
use PRTGenericMod, only : SetState
use PRTGenericMod, only : carbon12_element
use FatesTwoStreamUtilsMod, only : FatesConstructRadElements
use FatesRadiationMemMod , only : twostr_solver
use FatesRadiationMemMod , only : num_rad_stream_types
! CIME Globals
use shr_log_mod , only : errMsg => shr_log_errMsg
implicit none
private
public :: canopy_structure
public :: canopy_spread
public :: calc_areaindex
public :: canopy_summarization
public :: update_hlm_dynamics
public :: UpdateFatesAvgSnowDepth
public :: UpdatePatchLAI
public :: UpdateCohortLAI
logical, parameter :: debug=.false.
character(len=*), parameter, private :: sourcefile = &
__FILE__
integer :: istat ! return status code
character(len=255) :: smsg ! Message string for deallocation errors
real(r8), parameter :: area_target_precision = 1.0E-11_r8 ! Area conservation
! will attempt to reduce errors
! below this level
real(r8), parameter :: area_check_precision = 1.0E-7_r8 ! Area conservation checks must
! be within this absolute tolerance
real(r8), parameter :: area_check_rel_precision = 1.0E-4_r8 ! Area conservation checks must
! be within this relative tolerance
real(r8), parameter :: similar_height_tol = 1.0E-3_r8 ! I think trees that differ by 1mm
! can be roughly considered the same right?
logical, parameter :: preserve_b4b = .true.
! 10/30/09: Created by Rosie Fisher
! 2017/2018: Modifications and updates by Ryan Knox
! ============================================================================
contains
! ============================================================================
subroutine canopy_structure( currentSite , bc_in )
!
! !DESCRIPTION:
! create cohort instance
!
! This routine allocates the 'canopy_layer' attribute to each cohort
! All top leaves in the same canopy layer get the same light resources.
! The first canopy layer is the 'canopy' or 'overstorey'. The second is the 'understorey'.
! More than two layers is not permitted at the moment
! Seeds germinating into the 3rd or higher layers are automatically removed.
!
! ------Perfect Plasticity-----
! The idea of these canopy layers derives originally from Purves et al. 2009
! Their concept is that, given enoughplasticity in canopy position, size, shape and depth
! all of the gound area will be filled perfectly by leaves, and additional leaves will have
! to exist in the understorey.
! Purves et al. use the concept of 'Z*' to assume that the height required to attain a place in the
! canopy is spatially uniform. In this implementation, described in Fisher et al. (2010, New Phyt) we
! extent that concept to assume that position in the canopy has some random element, and that BOTH height
! and chance combine to determine whether trees get into the canopy.
! Thus, when the canopy is closed and there is excess area, some of it must be demoted
! If we demote -all- the trees less than a given height, there is a massive advantage in being the cohort that is
! the biggest when the canopy is closed.
! In this implementation, the amount demoted, ('weight') is a function of the height weighted by the competitive exclusion
! parameter (ED_val_comp_excln).
! Complexity in this routine results from a few things.
! Firstly, the complication of the demotion amount sometimes being larger than the cohort area (for a very small, short cohort)
! Second, occasionaly, disturbance (specifically fire) can cause the canopy layer to become less than closed,
! without changing the area of the patch. If this happens, then some of the plants in the lower layer need to be 'promoted' so
! all of the routine has to happen in both the downwards and upwards directions.
!
! The order of events here is therefore:
! (The entire subroutine has a single outer 'patch' loop.
! Section 1: figure out the total area, and whether there are >1 canopy layers at all.
!
! Sorts out cohorts into canopy and understorey layers...
!
! !USES:
use EDParamsMod, only : ED_val_comp_excln
use EDTypesMod , only : min_patch_area
!
! !ARGUMENTS
type(ed_site_type) , intent(inout), target :: currentSite
type(bc_in_type), intent(in) :: bc_in
!
! !LOCAL VARIABLES:
type(fates_patch_type) , pointer :: currentPatch
type(fates_cohort_type), pointer :: currentCohort
integer :: i_lyr ! current layer index
integer :: z ! Current number of canopy layers. (1= canopy, 2 = understorey)
integer :: ipft
real(r8) :: arealayer(nclmax+2) ! Amount of plant area currently in each canopy layer
integer :: patch_area_counter ! count iterations used to solve canopy areas
logical :: area_not_balanced ! logical controlling if the patch layer areas
! have successfully been redistributed
integer :: return_code ! math checks on variables will return>0 if problems exist
! We only iterate because of possible imprecisions generated by the cohort
! termination process. These should be super small, so at the most
! try to re-balance 3 times. If that doesn't give layer areas
! within tolerance of canopy area, there is something wrong
integer, parameter :: max_patch_iterations = 10
!----------------------------------------------------------------------
currentPatch => currentSite%oldest_patch
!
! zero site-level demotion / promotion tracking info
currentSite%demotion_rate(:) = 0._r8
currentSite%promotion_rate(:) = 0._r8
currentSite%demotion_carbonflux = 0._r8
currentSite%promotion_carbonflux = 0._r8
!
! Section 1: Check total canopy area.
!
do while (associated(currentPatch)) ! Patch loop
! ------------------------------------------------------------------------------
! Perform numerical checks on some cohort and patch structures
! ------------------------------------------------------------------------------
! canopy layer has a special bounds check
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
if( currentCohort%canopy_layer < 1 .or. currentCohort%canopy_layer > nclmax+1 ) then
write(fates_log(),*) 'lat:',currentSite%lat
write(fates_log(),*) 'lon:',currentSite%lon
write(fates_log(),*) 'BOGUS CANOPY LAYER: ',currentCohort%canopy_layer
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
currentCohort => currentCohort%shorter
enddo
! Does any layer have excess area in it? Keep going until it does not...
patch_area_counter = 0
area_not_balanced = .true.
do while(area_not_balanced)
! ---------------------------------------------------------------------------
! Demotion Phase: Identify upper layers that are too full, and demote them to
! the layers below.
! ---------------------------------------------------------------------------
! Its possible that before we even enter this scheme
! some cohort numbers are very low. Terminate them.
call terminate_cohorts(currentSite, currentPatch, 1, 12, bc_in)
! Calculate how many layers we have in this canopy
! This also checks the understory to see if its crown
! area is large enough to warrant a temporary sub-understory layer
z = NumPotentialCanopyLayers(currentPatch,currentSite%spread,include_substory=.false.)
do i_lyr = 1,z ! Loop around the currently occupied canopy layers.
call DemoteFromLayer(currentSite, currentPatch, i_lyr, bc_in)
end do
! After demotions, we may then again have cohorts that are very very
! very sparse, remove them
call terminate_cohorts(currentSite, currentPatch, 1,13,bc_in)
call fuse_cohorts(currentSite, currentPatch, bc_in)
! Remove cohorts for various other reasons
call terminate_cohorts(currentSite, currentPatch, 2,13,bc_in)
! ---------------------------------------------------------------------------------------
! Promotion Phase: Identify if any upper-layers are underful and layers below them
! have cohorts that can be split and promoted to the layer above.
! ---------------------------------------------------------------------------------------
! Re-calculate Number of layers without the false substory
z = NumPotentialCanopyLayers(currentPatch,currentSite%spread,include_substory=.false.)
! We only promote if we have at least two layers
if (z>1) then
do i_lyr=1,z-1
call PromoteIntoLayer(currentSite, currentPatch, i_lyr)
end do
! Remove cohorts that are incredibly sparse
call terminate_cohorts(currentSite, currentPatch, 1,14,bc_in)
call fuse_cohorts(currentSite, currentPatch, bc_in)
! Remove cohorts for various other reasons
call terminate_cohorts(currentSite, currentPatch, 2,14,bc_in)
end if
! ---------------------------------------------------------------------------------------
! Check on Layer Area (if the layer differences are not small
! Continue trying to demote/promote. Its possible on the first pass through,
! that cohort fusion has nudged the areas a little bit.
! ---------------------------------------------------------------------------------------
z = NumPotentialCanopyLayers(currentPatch,currentSite%spread,include_substory=.false.)
area_not_balanced = .false.
do i_lyr = 1,z
call CanopyLayerArea(currentPatch,currentSite%spread,i_lyr,arealayer(i_lyr))
if( ((arealayer(i_lyr)-currentPatch%area)/currentPatch%area > area_check_rel_precision) .or. &
((arealayer(i_lyr)-currentPatch%area) > area_check_precision ) ) then
area_not_balanced = .true.
endif
enddo
! ---------------------------------------------------------------------------------------
! Gracefully exit if too many iterations have gone by
! ---------------------------------------------------------------------------------------
patch_area_counter = patch_area_counter + 1
if(patch_area_counter > max_patch_iterations .and. area_not_balanced) then
write(fates_log(),*) 'PATCH AREA CHECK NOT CLOSING'
write(fates_log(),*) 'patch area:',currentpatch%area
do i_lyr = 1,z
write(fates_log(),*) 'layer: ',i_lyr,' area: ',arealayer(i_lyr)
write(fates_log(),*) 'rel error: ',(arealayer(i_lyr)-currentPatch%area)/currentPatch%area
write(fates_log(),*) 'abs error: ',arealayer(i_lyr)-currentPatch%area
enddo
write(fates_log(),*) 'lat:',currentSite%lat
write(fates_log(),*) 'lon:',currentSite%lon
write(fates_log(),*) 'spread:',currentSite%spread
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
write(fates_log(),*) 'coh ilayer:',currentCohort%canopy_layer
write(fates_log(),*) 'coh dbh:',currentCohort%dbh
write(fates_log(),*) 'coh pft:',currentCohort%pft
write(fates_log(),*) 'coh n:',currentCohort%n
write(fates_log(),*) 'coh carea:',currentCohort%c_area
ipft=currentCohort%pft
write(fates_log(),*) 'maxh:',prt_params%allom_dbh_maxheight(ipft)
write(fates_log(),*) 'lmode: ',prt_params%allom_lmode(ipft)
write(fates_log(),*) 'd2bl2: ',prt_params%allom_d2bl2(ipft)
write(fates_log(),*) 'd2bl_ediff: ',prt_params%allom_blca_expnt_diff(ipft)
write(fates_log(),*) 'd2ca_min: ',prt_params%allom_d2ca_coefficient_min(ipft)
write(fates_log(),*) 'd2ca_max: ',prt_params%allom_d2ca_coefficient_max(ipft)
currentCohort => currentCohort%shorter
enddo
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
enddo ! do while(area_not_balanced)
! Save number of canopy layers to the patch structure
if(z > nclmax) then
write(fates_log(),*) 'Termination should have ensured number of canopy layers was not larger than nclmax'
write(fates_log(),*) 'Predicted: ',z
write(fates_log(),*) 'nclmax: ',nclmax
write(fates_log(),*) 'Consider increasing nclmax if this value is to low'
write(fates_log(),*) 'and you think this number of canopy layers is reasonable.'
call endrun(msg=errMsg(sourcefile, __LINE__))
else
currentPatch%NCL_p = z
end if
! -------------------------------------------------------------------------------------------
! if we are using "strict PPA", then calculate a z_star value as
! the height of the smallest tree in the canopy
! loop from top to bottom and locate the shortest cohort in level 1 whose shorter
! neighbor is in level 2 set zstar as the ehight of that shortest level 1 cohort
! -------------------------------------------------------------------------------------------
if ( ED_val_comp_excln .lt. 0.0_r8) then
currentPatch%zstar = 0._r8
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
if(currentCohort%canopy_layer .eq. 2)then
if (associated(currentCohort%taller)) then
if (currentCohort%taller%canopy_layer .eq. 1 ) then
currentPatch%zstar = currentCohort%taller%height
endif
endif
endif
currentCohort => currentCohort%shorter
enddo
endif
currentPatch => currentPatch%younger
enddo !patch
return
end subroutine canopy_structure
! ==============================================================================================
subroutine DemoteFromLayer(currentSite,currentPatch,i_lyr,bc_in)
use EDParamsMod, only : ED_val_comp_excln
! !ARGUMENTS
type(ed_site_type), intent(inout) :: currentSite
type(fates_patch_type), intent(inout) :: currentPatch
integer, intent(in) :: i_lyr ! Current canopy layer of interest
type(bc_in_type), intent(in) :: bc_in
! !LOCAL VARIABLES:
type(fates_cohort_type), pointer :: currentCohort
type(fates_cohort_type), pointer :: copyc
type(fates_cohort_type), pointer :: nextc ! The next cohort in line
integer :: i_cwd ! Index for CWD pool
real(r8) :: cc_loss ! cohort crown area loss in demotion (m2)
real(r8) :: leaf_c ! leaf carbon [kg]
real(r8) :: fnrt_c ! fineroot carbon [kg]
real(r8) :: sapw_c ! sapwood carbon [kg]
real(r8) :: store_c ! storage carbon [kg]
real(r8) :: struct_c ! structure carbon [kg]
real(r8) :: scale_factor ! for prob. exclusion - scales weight to a fraction
real(r8) :: scale_factor_min ! "" minimum before exeedance of 1
real(r8) :: scale_factor_res ! "" applied to residual areas
real(r8) :: area_res ! residual area to demote after weakest cohort hits max
real(r8) :: newarea
real(r8) :: demote_area
real(r8) :: sumweights
real(r8) :: sumequal ! for rank-ordered same-size cohorts
! this tallies their excluded area
real(r8) :: arealayer ! the area of the current canopy layer
logical :: tied_size_with_neighbors
real(r8) :: total_crownarea_of_tied_cohorts
! First, determine how much total canopy area we have in this layer
call CanopyLayerArea(currentPatch,currentSite%spread,i_lyr,arealayer)
demote_area = arealayer - currentPatch%area
if ( demote_area > area_target_precision ) then
! Is this layer currently over-occupied?
! In that case, we need to work out which cohorts to demote.
! We go in order from shortest to tallest for ranked demotion
sumweights = 0.0_r8
currentCohort => currentPatch%shortest
do while (associated(currentCohort))
call carea_allom(currentCohort%dbh,currentCohort%n, &
currentSite%spread,currentCohort%pft, &
currentCohort%crowndamage, currentCohort%c_area)
if(debug) then
if(currentCohort%c_area<0._r8)then
write(fates_log(),*) 'negative c_area stage 1d: ',currentCohort%dbh,i_lyr,currentCohort%n, &
currentSite%spread,currentCohort%pft,currentCohort%c_area
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
end if
if( currentCohort%canopy_layer == i_lyr)then
if (ED_val_comp_excln .ge. 0.0_r8 ) then
! ----------------------------------------------------------
! Stochastic method.
! Weight cohort demotion by inverse size to a constant power.
! In this hypothesis, it is assumed that even the tallest
! cohorts have a chance (although smaller) of being forced
! to the understory.
! ----------------------------------------------------------
currentCohort%excl_weight = 1._r8 / (currentCohort%height**ED_val_comp_excln)
sumweights = sumweights + currentCohort%excl_weight
else
! -----------------------------------------------------------
! Rank ordered deterministic method
! -----------------------------------------------------------
! If there are cohorts that have the exact same height (which is possible, really)
! we don't want to unilaterally promote/demote one before the others.
! So we <>mote them as a unit
! now we need to go through and figure out how many equal-size cohorts there are.
! then we need to go through, add up the collective crown areas of all equal-sized
! and equal-canopy-layer cohorts,
! and then demote from each as if they were a single group
total_crownarea_of_tied_cohorts = currentCohort%c_area
tied_size_with_neighbors = .false.
nextc => currentCohort%taller
do while (associated(nextc))
if ( abs(nextc%height - currentCohort%height) < similar_height_tol ) then
if( nextc%canopy_layer .eq. currentCohort%canopy_layer ) then
tied_size_with_neighbors = .true.
total_crownarea_of_tied_cohorts = &
total_crownarea_of_tied_cohorts + nextc%c_area
end if
else
exit
endif
nextc => nextc%taller
end do
if ( tied_size_with_neighbors ) then
currentCohort%excl_weight = &
max(0.0_r8,min(currentCohort%c_area, &
(currentCohort%c_area/total_crownarea_of_tied_cohorts) * &
(demote_area - sumweights) ))
sumequal = currentCohort%excl_weight
nextc => currentCohort%taller
do while (associated(nextc))
if ( abs(nextc%height - currentCohort%height) < similar_height_tol ) then
if (nextc%canopy_layer .eq. currentCohort%canopy_layer ) then
! now we know the total crown area of all equal-sized,
! equal-canopy-layer cohorts
nextc%excl_weight = &
max(0.0_r8,min(nextc%c_area, &
(nextc%c_area/total_crownarea_of_tied_cohorts) * &
(demote_area - sumweights) ))
sumequal = sumequal + nextc%excl_weight
end if
else
exit
endif
nextc => nextc%taller
end do
! Update the current cohort pointer to the last similar cohort
! Its ok if this is not in the right layer
if(associated(nextc))then
currentCohort => nextc%shorter
else
currentCohort => currentPatch%tallest
end if
sumweights = sumweights + sumequal
else
currentCohort%excl_weight = &
max(min(currentCohort%c_area, demote_area - sumweights ), 0._r8)
sumweights = sumweights + currentCohort%excl_weight
end if
endif
endif
currentCohort => currentCohort%taller
enddo
! If this is probabalistic demotion, we need to do a round of normalization.
! And then a few rounds where we pre-calculate the demotion areas
! and adjust things if the demoted area wants to be greater than
! what is available. The math is too hard to explain here, see
! the tech note section on promotion/demotion.
if (ED_val_comp_excln .ge. 0.0_r8 ) then
scale_factor_min = 1.e10_r8
scale_factor = 0._r8
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
if(currentCohort%canopy_layer == i_lyr) then
currentCohort%excl_weight = currentCohort%excl_weight/sumweights
if( 1._r8/currentCohort%excl_weight < scale_factor_min ) &
scale_factor_min = 1._r8/currentCohort%excl_weight
scale_factor = scale_factor + currentCohort%excl_weight * currentCohort%c_area
endif
currentCohort => currentCohort%shorter
enddo
! This is the factor by which we need to multiply
! the demotion probabilities, so the sum result equals
! the total amount to demote
scale_factor = demote_area/scale_factor
if(scale_factor <= scale_factor_min) then
! Trivial case, all of the demotion fractions are less than 1.
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
if(currentCohort%canopy_layer == i_lyr) then
currentCohort%excl_weight = currentCohort%c_area * currentCohort%excl_weight * scale_factor
if(debug) then
if((currentCohort%excl_weight > (currentCohort%c_area+area_target_precision)) .or. &
(currentCohort%excl_weight < 0._r8) ) then
write(fates_log(),*) 'exclusion area too big (1)'
write(fates_log(),*) 'currentCohort%c_area: ',currentCohort%c_area
write(fates_log(),*) 'dbh: ',currentCohort%dbh
write(fates_log(),*) 'n: ',currentCohort%n
write(fates_log(),*) 'spread: ',currentSite%spread
write(fates_log(),*) 'pft: ',currentCohort%pft
write(fates_log(),*) 'currentCohort%excl_weight: ',currentCohort%excl_weight
write(fates_log(),*) 'excess: ',currentCohort%excl_weight - currentCohort%c_area
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
end if
endif
currentCohort => currentCohort%shorter
enddo
else
! Non-trivial case, at least 1 cohort's demotion
! rate would exceed its area, given the trivial scale factor
area_res = 0._r8
scale_factor_res = 0._r8
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
if(currentCohort%canopy_layer == i_lyr) then
area_res = area_res + &
currentCohort%c_area * currentCohort%excl_weight * &
scale_factor_min
scale_factor_res = scale_factor_res + &
currentCohort%c_area * &
(1._r8 - (currentCohort%excl_weight * scale_factor_min))
endif
currentCohort => currentCohort%shorter
enddo
area_res = demote_area - area_res
scale_factor_res = area_res / scale_factor_res
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
if(currentCohort%canopy_layer == i_lyr) then
currentCohort%excl_weight = currentCohort%c_area * &
(currentCohort%excl_weight * scale_factor_min + &
(1._r8 - (currentCohort%excl_weight*scale_factor_min) ) * scale_factor_res)
if(debug)then
if((currentCohort%excl_weight > &
(currentCohort%c_area+area_target_precision)) .or. &
(currentCohort%excl_weight < 0._r8) ) then
write(fates_log(),*) 'exclusion area error (2)'
write(fates_log(),*) 'currentCohort%c_area: ',currentCohort%c_area
write(fates_log(),*) 'currentCohort%excl_weight: ', &
currentCohort%excl_weight
write(fates_log(),*) 'excess: ', &
currentCohort%excl_weight - currentCohort%c_area
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
end if
endif
currentCohort => currentCohort%shorter
enddo
end if
end if
! perform a check and see if the demotions meet the demand
sumweights = 0._r8
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
if(currentCohort%canopy_layer == i_lyr) then
sumweights = sumweights + currentCohort%excl_weight
end if
currentCohort => currentCohort%shorter
end do
if (abs(sumweights - demote_area) > area_check_precision ) then
write(fates_log(),*) 'demotions dont add up'
write(fates_log(),*) 'sum demotions: ',sumweights
write(fates_log(),*) 'area needed to be demoted: ',demote_area
write(fates_log(),*) 'excess: ',sumweights - demote_area
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
! Weights have been calculated. Now move them to the lower layer
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
nextc => currentCohort%shorter
if(currentCohort%canopy_layer == i_lyr )then
cc_loss = currentCohort%excl_weight
leaf_c = currentCohort%prt%GetState(leaf_organ,carbon12_element)
store_c = currentCohort%prt%GetState(store_organ,carbon12_element)
fnrt_c = currentCohort%prt%GetState(fnrt_organ,carbon12_element)
sapw_c = currentCohort%prt%GetState(sapw_organ,carbon12_element)
struct_c = currentCohort%prt%GetState(struct_organ,carbon12_element)
if ( (cc_loss-currentCohort%c_area) > -nearzero .and. &
(cc_loss-currentCohort%c_area) < area_target_precision ) then
! If the whole cohort is being demoted, just change its
! layer index
currentCohort%canopy_layer = i_lyr+1
! keep track of number and biomass of demoted cohort
currentSite%demotion_rate(currentCohort%size_class) = &
currentSite%demotion_rate(currentCohort%size_class) + currentCohort%n
currentSite%demotion_carbonflux = currentSite%demotion_carbonflux + &
(leaf_c + store_c + fnrt_c + sapw_c + struct_c) * currentCohort%n
elseif( (cc_loss < currentCohort%c_area) .and. &
(cc_loss > area_target_precision) ) then
! If only part of the cohort is demoted
! then it must be split (little more complicated)
! Make a copy of the current cohort. The copy and the original
! conserve total number density of the original. The copy
! remains in the upper-story. The original is the one
! demoted to the understory
allocate(copyc)
! (keep as an example)
! Initialize running means
!allocate(copyc%tveg_lpa)
!!allocate(copyc%l2fr_ema)
! Note, no need to give a starter value here,
! that will be taken care of in copy()
!!call copyc%l2fr_ema%InitRMean(ema_60day)
! Initialize the PARTEH object and point to the
! correct boundary condition fields
copyc%prt => null()
call InitPRTObject(copyc%prt)
if( hlm_use_planthydro.eq.itrue ) then
call InitHydrCohort(currentSite,copyc)
endif
call currentCohort%Copy(copyc)
call copyc%InitPRTBoundaryConditions()
newarea = currentCohort%c_area - cc_loss
copyc%n = currentCohort%n*newarea/currentCohort%c_area
currentCohort%n = currentCohort%n - copyc%n
copyc%canopy_layer = i_lyr !the taller cohort is the copy
! Demote the current cohort to the understory.
currentCohort%canopy_layer = i_lyr + 1
! keep track of number and biomass of demoted cohort
currentSite%demotion_rate(currentCohort%size_class) = &
currentSite%demotion_rate(currentCohort%size_class) + currentCohort%n
currentSite%demotion_carbonflux = currentSite%demotion_carbonflux + &
(leaf_c + store_c + fnrt_c + sapw_c + struct_c) * currentCohort%n
call carea_allom(copyc%dbh,copyc%n,currentSite%spread,copyc%pft, &
copyc%crowndamage, copyc%c_area)
call carea_allom(currentCohort%dbh,currentCohort%n,currentSite%spread, &
currentCohort%pft,currentCohort%crowndamage, currentCohort%c_area)
!----------- Insert copy into linked list ------------------------!
copyc%shorter => currentCohort
if(associated(currentCohort%taller))then
copyc%taller => currentCohort%taller
currentCohort%taller%shorter => copyc
else
currentPatch%tallest => copyc
copyc%taller => null()
endif
currentCohort%taller => copyc
elseif(cc_loss > currentCohort%c_area)then
write(fates_log(),*) 'more area than the cohort has is being demoted'
write(fates_log(),*) 'loss:',cc_loss
write(fates_log(),*) 'existing area:',currentCohort%c_area
write(fates_log(),*) 'excess: ',cc_loss - currentCohort%c_area
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
! kill the ones which go into canopy layers that are not allowed
! USE THIS OVERRIDE IF YOU ARE FORCING A ONE COHORT SIMULATION
! (also make sure to turn off germination, external seed rain,
! (use only one PFT, and make sure disturb_frac is 0)
! (RGK-0822)
!if(currentCohort%canopy_layer>1) then
if(currentCohort%canopy_layer>nclmax )then
! put the litter from the terminated cohorts
! straight into the fragmenting pools
call terminate_cohort(currentSite,currentPatch,currentCohort,bc_in,i_term_mort_type_canlev)
deallocate(currentCohort, stat=istat, errmsg=smsg)
if (istat/=0) then
write(fates_log(),*) 'dealloc012: fail on deallocate(currentCohort):'//trim(smsg)
call endrun(msg=errMsg(sourcefile, __LINE__))
endif
else
call carea_allom(currentCohort%dbh,currentCohort%n, &
currentSite%spread,currentCohort%pft,currentCohort%crowndamage, &
currentCohort%c_area)
end if
endif !canopy layer = i_ly
! We dont use our typical (point to smaller)
! here, because, we may had deallocated the existing
! currentCohort
currentCohort => nextc
enddo !currentCohort
! Update the area calculations of the current layer
! And the layer below that may or may not had recieved
! Demotions
call CanopyLayerArea(currentPatch,currentSite%spread,i_lyr,arealayer)
if ( (abs(arealayer - currentPatch%area)/arealayer > area_check_rel_precision ) .or. &
(abs(arealayer - currentPatch%area) > area_check_precision) ) then
write(fates_log(),*) 'demotion did not trim area within tolerance'
write(fates_log(),*) 'arealayer:',arealayer
write(fates_log(),*) 'patch%area:',currentPatch%area
write(fates_log(),*) 'ilayer: ',i_lyr
write(fates_log(),*) 'bias:',arealayer - currentPatch%area
write(fates_log(),*) 'rel bias:',(arealayer - currentPatch%area)/arealayer
write(fates_log(),*) 'demote_area:',demote_area
call endrun(msg=errMsg(sourcefile, __LINE__))
end if
end if
return
end subroutine DemoteFromLayer
! ==============================================================================================
subroutine PromoteIntoLayer(currentSite,currentPatch,i_lyr)
! -------------------------------------------------------------------------------------------
! Check whether the intended 'full' layers are actually filling all the space.
! If not, promote some fraction of cohorts upwards.
! THIS SECTION MIGHT BE TRIGGERED BY A FIRE OR MORTALITY EVENT, FOLLOWED BY A PATCH FUSION,
! SO THE TOP LAYER IS NO LONGER FULL.
! -------------------------------------------------------------------------------------------
use EDParamsMod, only : ED_val_comp_excln
! !ARGUMENTS
type(ed_site_type), intent(inout), target :: currentSite
type(fates_patch_type), intent(inout), target :: currentPatch
integer, intent(in) :: i_lyr ! Current canopy layer of interest
! !LOCAL VARIABLES:
type(fates_cohort_type), pointer :: currentCohort
type(fates_cohort_type), pointer :: copyc
type(fates_cohort_type), pointer :: nextc ! the next cohort, or used for looping
! cohorts against the current
real(r8) :: scale_factor ! for prob. exclusion - scales weight to a fraction
real(r8) :: scale_factor_min ! "" minimum before exeedance of 1
real(r8) :: scale_factor_res ! "" applied to residual areas
real(r8) :: area_res ! residual area to demote after weakest cohort hits max
real(r8) :: promote_area
real(r8) :: newarea
real(r8) :: sumweights
real(r8) :: sumequal ! for tied cohorts, the sum of weights in
! their group
real(r8) :: cc_gain ! cohort crown area gain in promotion (m2)
real(r8) :: arealayer_current ! area (m2) of the current canopy layer
real(r8) :: arealayer_below ! area (m2) of the layer below the current layer
real(r8) :: leaf_c ! leaf carbon [kg]
real(r8) :: fnrt_c ! fineroot carbon [kg]
real(r8) :: sapw_c ! sapwood carbon [kg]
real(r8) :: store_c ! storage carbon [kg]
real(r8) :: struct_c ! structure carbon [kg]
logical :: tied_size_with_neighbors
real(r8) :: total_crownarea_of_tied_cohorts
call CanopyLayerArea(currentPatch,currentSite%spread,i_lyr,arealayer_current)
call CanopyLayerArea(currentPatch,currentSite%spread,i_lyr+1,arealayer_below)
! how much do we need to gain?
promote_area = currentPatch%area - arealayer_current
if( promote_area > area_target_precision ) then
if(arealayer_below <= promote_area ) then
! ---------------------------------------------------------------------------
! Promote all cohorts from layer below if that whole layer has area smaller
! than the tolerance on the gains needed into current layer
! ---------------------------------------------------------------------------
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
!look at the cohorts in the canopy layer below...
if(currentCohort%canopy_layer == i_lyr+1)then
leaf_c = currentCohort%prt%GetState(leaf_organ,carbon12_element)
store_c = currentCohort%prt%GetState(store_organ,carbon12_element)
fnrt_c = currentCohort%prt%GetState(fnrt_organ,carbon12_element)
sapw_c = currentCohort%prt%GetState(sapw_organ,carbon12_element)
struct_c = currentCohort%prt%GetState(struct_organ,carbon12_element)
currentCohort%canopy_layer = i_lyr
call carea_allom(currentCohort%dbh,currentCohort%n,currentSite%spread, &
currentCohort%pft,currentCohort%crowndamage, currentCohort%c_area)
! keep track of number and biomass of promoted cohort
currentSite%promotion_rate(currentCohort%size_class) = &
currentSite%promotion_rate(currentCohort%size_class) + currentCohort%n
currentSite%promotion_carbonflux = currentSite%promotion_carbonflux + &
(leaf_c + fnrt_c + store_c + sapw_c + struct_c) * currentCohort%n
endif
currentCohort => currentCohort%shorter
enddo
else
! ---------------------------------------------------------------------------
! This is the non-trivial case where the lower layer can accomodate
! more than what is necessary.
! ---------------------------------------------------------------------------
! figure out with what weighting we need to promote cohorts.
! This is the opposite of the demotion weighting...
sumweights = 0.0_r8
currentCohort => currentPatch%tallest
do while (associated(currentCohort))
call carea_allom(currentCohort%dbh,currentCohort%n,currentSite%spread, &
currentCohort%pft,currentCohort%crowndamage,currentCohort%c_area)
if(currentCohort%canopy_layer == i_lyr+1)then !look at the cohorts in the canopy layer below...
if (ED_val_comp_excln .ge. 0.0_r8 ) then
! ------------------------------------------------------------------
! Stochastic case, as above (in demotion portion of code)
! ------------------------------------------------------------------
currentCohort%prom_weight = currentCohort%height**ED_val_comp_excln
sumweights = sumweights + currentCohort%prom_weight
else
! ------------------------------------------------------------------
! Rank ordered deterministic method
! If there are cohorts that have the exact same height (which is possible, really)
! we don't want to unilaterally promote/demote one before the others.
! So we <>mote them as a unit
! now we need to go through and figure out how many equal-size cohorts there are.
! then we need to go through, add up the collective crown areas of all equal-sized
! and equal-canopy-layer cohorts,
! and then demote from each as if they were a single group
! ------------------------------------------------------------------
total_crownarea_of_tied_cohorts = currentCohort%c_area
tied_size_with_neighbors = .false.
nextc => currentCohort%shorter
do while (associated(nextc))
if ( abs(nextc%height - currentCohort%height) < similar_height_tol ) then
if( nextc%canopy_layer .eq. currentCohort%canopy_layer ) then
tied_size_with_neighbors = .true.
total_crownarea_of_tied_cohorts = &
total_crownarea_of_tied_cohorts + nextc%c_area
end if
else
exit
endif
nextc => nextc%shorter
end do
if ( tied_size_with_neighbors ) then
currentCohort%prom_weight = &
max(0.0_r8,min(currentCohort%c_area, &
(currentCohort%c_area/total_crownarea_of_tied_cohorts) * &
(promote_area - sumweights) ))
sumequal = currentCohort%prom_weight
nextc => currentCohort%shorter
do while (associated(nextc))
if ( abs(nextc%height - currentCohort%height) < similar_height_tol ) then
if (nextc%canopy_layer .eq. currentCohort%canopy_layer ) then
! now we know the total crown area of all equal-sized,
! equal-canopy-layer cohorts
nextc%prom_weight = &
max(0.0_r8,min(nextc%c_area, &
(nextc%c_area/total_crownarea_of_tied_cohorts) * &
(promote_area - sumweights) ))
sumequal = sumequal + nextc%prom_weight
end if
else
exit
endif
nextc => nextc%shorter
end do
! Update the current cohort pointer to the last similar cohort
! Its ok if this is not in the right layer
if(associated(nextc))then
currentCohort => nextc%taller
else
currentCohort => currentPatch%shortest
end if
sumweights = sumweights + sumequal
else
currentCohort%prom_weight = &
max(min(currentCohort%c_area, promote_area - sumweights ), 0._r8)
sumweights = sumweights + currentCohort%prom_weight
end if
endif
endif
currentCohort => currentCohort%shorter
enddo !currentCohort
! If this is probabalistic promotion, we need to do a round of normalization.
! And then a few rounds where we pre-calculate the promotion areas
! and adjust things if the promoted area wants to be greater than
! what is available.
if (ED_val_comp_excln .ge. 0.0_r8 ) then
scale_factor_min = 1.e10_r8
scale_factor = 0._r8
currentCohort => currentPatch%tallest