The forest plant production model (
Figure 3-17
) divides the tree into leaves, fine roots, fine branches, large wood, and coarse
roots with carbon and nutrients allocated to the different plant parts using
a fixed allocation scheme. Maximum monthly gross production is calculated as
the product of maximum gross production rate (PRDX(2), tree.100),
moisture, soil temperature and live leaf-area-index terms. The effect of moisture
and temperature on potential productions are the same functions used for the
monthly grassland model (
Figures 3-8a
and
3-9
), while the effect of live leaf-area-index on production is shown in
Figure 3-18
. Plant respiration is calculated as a function of wood N content and temperature
using an equation developed by Ryan (1991) and subtracted from the gross production
rate in order to get the net potential production rate. The net potential production
rate is not allowed to exceed the tree specific maximum net production rate (PRDX(3)
times the other limiting factors). The model assumes that only the sapwood part
of the tree respires C and the sapwood fraction of aboveground large wood biomass
is calculated using the relationship shown in
Figure 3-19
. The same sapwood fraction is used for coarse woody roots (Ryan, 1991). The
leaf biomass is not allowed to exceed a maximum value that is a function of the
live wood biomass (
Figure 3-20
). This function specifies the effect of tree allometry and structure on maximum
leaf area and is potentially different for different species. Some of the important
forest specific parameters include the maximum gross and net production rates
(PRDX(2), PRDX(3), tree.100), the leaf area index to wood biomass
relationship parameters (MAXLAI, KLAI, tree.100), the sapwood to
large wood C ratio parameter (SAPK, tree.100), and the allocation
of C into different plant parts (FCFRAC(1-5,1-2), tree.100).
The actual production is limited to that achievable with the currently available nutrient supply with plant nutrient concentrations constrained between upper and lower limits set separately for different tree parts. Invoking Liebig's Law of the Minimum, the most limiting nutrient (ELIMIT) constrains production. The limits of nutrient content for shoot growth are a function of plant biomass in order to reflect the changing nutrient content with plant age ( Figure 3-13 ). The user specifies the effect of live shoot biomass on maximum and minimum nutrient content ( BIOMAX, PRAMN(*,*), PRAMX(*,*)).
C:E minimum, maximum =
PRAMN(E,0) + (range of PRAMN) * conversion_factor * AGLIVC / BIOMAX
The conversion factor is equal to 2.5 for leaves and fine roots, and equals 2.0 for the remaining woody biomass. The upper limit on nutrient content is based on roots and shoots only.
The model has two carbon allocation patterns for young and mature forests and
can represent either deciduous forests or forests that grow continuously. With
a continuous growth or evergreen forest the death of the live leaves is specified
as a function of month (LEAFDR(1-12), tree.100), while with a
deciduous forest the leaf death rate is very high at the senescence month.
For deciduous forest the leaf growth rate is also much higher during the first
month of leaf growth. Dead leaves and fine roots are transferred to the surface
and root residue pools and are then allocated into structural and metabolic
pools. Dead fine branch, large wood, and coarse root pools receive dead wood
material from the live fine branch, large wood, and coarse root pools respectively.
Each dead wood pool has a specific decay rate. The dead wood pools decay in
the same way that the structural residue pool decomposes with lignin going
to the slow SOM pool and the non-lignin fraction going to surface microbes
or active SOM pool (above- or belowground material). The decay rates of the
dead wood pools are also reduced by the temperature and moisture decomposition
functions, and include CO2 losses.
A forest removal event, which is defined by
Tree Removal Parameters
in the trem.100 file,
can simulate the impact of different forest harvest practices, fires, and the
effect of large scale disturbances such as hurricanes. For each disturbance or
harvest event, the fraction of each live plant part lost and the fraction of
material that is returned to the soil system is specified. Death of fine and
coarse roots are also considered in the removal event along with the removal
of dead wood. Another feature is that the nutrient concentration of live leaves
that go into surface residue can be elevated above the dead leaf nutrient concentration
(e.g. simulating the effect of adding live leaves to surface residue as a result
of hurricane disturbance) by specifying the return nutrient fraction of the leaves
to be greater than one (
RETF(1,*)
,
trem.100
).
Calculation of the true leaf area index uses leaf biomass and a biomass-to-LAI conversion parameter which is the slope of a regression line derived from LAI vs foliar mass for slash pine. The theoretical LAI is calculated as a function of large wood mass ( Waring et al., 1981 ). There is no strong consensus on the true nature of the relationship between LAI and stemwood mass. Version 3.0 used a negative exponential relationship between leaf mass and large wood mass, which tended to break down in very large forests. Many studies have cited a "general" increase of LAI up to a maximum, then a decrease to a plateau value (e.g. Switzer et al. 1968 , Gholz and Fisher 1982 ). However, this response is not general, and seems to mostly be a feature of young pine plantations. Northern hardwoods have shown a monotonic increase to a plateau (e.g. Switzer et al. 1968 ). Pacific Northwest conifers have shown a steady increase in LAI with no plateau evident (e.g. Gholz 1982 ). In this version, we use a simple saturation fucntion in which LAI increases linearly against large wood mass initially, then approaches a plateau value. The plateau value can be set very large to give a response of steadily increasing LAI with stemwood.
Plant Production Submodels: Overview
Grassland/Crop Submodel
Savanna Submodel