```CENTURY Parameterization Workbook
<site>.100 file
Most of the parameters in the <site>.100 file will have to be adjusted
to account for the unique properties of your particular system.
However, some sets of parameters are more important than others. For
example, climate and soil physical are very important but the initial
organic matter and water parameters are not important if you include
an equilibrium block in your schedule file. See Appendix 2.12 in the
Century User’s Manual for definitions of the parameters in this file.
SITE INFORMATION CENTURY PARAMERERIZATION
Site Name:_______________________________________________________
Latitude :______________________ Longitude:______________________
Elevation:_______________________________________________________
System simulated:
Modeler:_________________________________ Date:__________________
1.
PHYSICAL ENVIRONMENT
1.a.
CLMATE PARAMETERS
Enter below the mean climate for the site. These are averages for
each calendar month of daily maximum and minimum air temperatures and
monthly total precipitation. Standard deviation and skewness of
monthly precipitation totals are needed only if the stochastic
precipitation option is to be used and can be generated by using the
FILE100 utility.
MONTH
TEMPERATURES (oC)
MINIMUM
MAXIMUM
MEAN
PRECIPITATION (cm)
S.D.
SKEWNESS
1
2
3
4
5
6
7
8
9
10
11
12
VARIABLE
tmn2m
tmx2m
precip
prcstd
prcskw
Source for climate data:_________________________________________
1.b.
SITE AND CONTROL PARAMTERS
ivauto controls how SOM
ivauto=0 the initial
ivauto=1 an equation
ivauto=2 an equation
pools
pools are initialized.
SOM values in your <site>.100 file are used
for native grass soil initializes SOM pools
for cropped/disturbed soils initializes SOM
nelem controls the number of elements you want to model. For example,
nelem=1 means that P and S will not limit C flows.
C, N
C, N, P
C, N, P, S
nelem = 1
nelem = 2
nelem = 3
sitlat (lat.) ______ deg. N
sitlng (long.)______ deg. E (for reference only)
Enter the soil texture, pH, and bulk density for the top 20 cm of
mineral soil (for organic soils use top 20 cm; enter actual mass
fractions of sand, silt, and clay, these need not total to 1):
PROPERTY
VALUE
VARIABLE
SAND (fraction 0-1)
sand
SILT (fraction 0-1)
silt
CLAY (fraction 0-1)
clay
3
BULK DENSITY (g/cm )
bulkd
PH
ph
Check the appropriate soil drainage class below and circle the
corresponding value for the variable DRAIN:
_____
_____
_____
_____
_____
Excessively to moderately well drained
Somewhat poorly drained
Poorly drained
Very poorly drained
No drainage from solum
1.c.
SOIL LAYERS
drain
drain
drain
drain
drain
=
=
=
=
=
1.0
0.75
0.5
0.25
0.0
Enter the rooting zone depth (depth above which the large majority of
fine roots are found):___________________ cm
Enter the soil thickness to be used for the soil water model:
--- For soils on deep saprolite or unconsolidated material,
enter the greater of rooting zone depth or depth to base of
Bt.
--- For shallow soils enter depth to lithic contact.
--- For permafrost soils enter depth of summer thaw.
Soil thickness = __________________ cm
Convert rooting zone depth and soil thickness to numbers of soil
layers using the tables below. Circle the corresponding values for
nlaypg (layers available for plant growth) and nlayer (total layers in
solum):
Rooting zone
Total
DEPTH
nlaypg
nlayer
0-22 cm
1
1
23-37 cm
2
2
38-52 cm
3
3
53-74 cm
4
4
75-104 cm
5
5
105-134 cm
6
6
135-164 cm
7
7
165-194 cm
8
8
195 cm or more
9
9
Sources for soils data:__________________________________________
1.d.
STREAM FLOW CALBRATION
If you want, you can calibrate stream flow (stream(1)) by adjusting
the parameters stormf and basef. These parameters control monthly
distribution of streamflow, but they have no effect on water balance,
decomposition, or production. stormf is the fraction of excess water
that runs off immediately in the current month; the remainder goes to
the baseflow storage pool in asmos(nlayer+1). basef gives the
fraction of this storage pool that runs off each month. These
parameters can be calibrated iteratively by comparing an observed time
sequence of streamflow to the model predictions. Note that to do this
you must drive the model with the actual climate for the period, not
simply with the mean climate.
1.e.
FIELD CAPACITY AND WILTING POINT
Soil water contents at field capacity (FC) and wilting point (WP) for
each soil layer can be set by the user or can be calculated based on
different equations. If you want to use you own FC and WP values set
swflag=1 and enter appropriate WP and FC values for awilt(1..10) and
afiel(1..10). If you want to use an equation consult the Century
User’s Manual for the interpretation of different values of swflag, we
usually recommend swflag=2.
1.f.
CONTROLS ON PHOSPHORUS SORPTION
Set the value for sorpmx to the maximum P sorption
capacity for the
soil (0-20 cm) expressed as g P sorbed / m2 (extreme values are 1-3 for
sands and 10-20 for high sorption capacity clays):
sorpmx = _____________________
Set the value for pslsrb to the ratio between sorbed P and total
(sorbed + labile) P (extreme values are .5 for sands to .95 for highly
sorbing clays):
pslsrb = _____________________
Source for P sorption data:______________________________________
1.g.
EXTERNAL NUTRIENT INPUT PARAMETERS
The <site>.100 file includes parameters for atmosphereic N and S
deposition described below. Parameters controlling P and S inputs
from weathering are in the fix.100 file.
1.h.
NITROGEN
Enter your best estimates for rates of nitrogen input
Atmospheric deposition (wet + dry): ____________
Non-symbiotic biological N fixation:____________
Symbiotic biological N fixation:
____________
below:
g N m-2
yr-1
-2
g N m yr-1
g N m-2 yr-1
For deposition and
each input:
1) Have input
epnfa(1)
epnfa(2)
epnfs(1)
epnfs(2)
non-symbiotic fixation, you have two choices for
be fixed, constant amount each year:
= deposition ___________________
= 0.0
= fixation
___________________
= 0.0
2) Have input vary linearly with annual precipitation
epnfa(2) = ______________ * ___________ / _____________
dependence on
average
average
precipitation
annual
annual
(fraction, 0-1)
deposition -2 precipitation
= _______________________ g N m (cm H2O)-1
epnfa(1) = ______________ - ___________ * _____________
average
EPNFA(2)
average
annual
annual
deposition
precipitation
= _______________________ g N m-2 yr-1
epnfs(2) = ______________ * ___________ / _____________
dependence on
average
average
precipitation
annual
annual
(fraction, 0-1)
fixation
precipitation
= _______________________ g N m-2(cm H2O)-1
epnfs(1) = ______________ - ___________ * __________
average annual
EPNFS(2)
average annual
fixation
precipitation
= _______________________ g N m-2 yr-1
1.i.
SULFUR
Atmospheric deposition of S is simulated in the same manner as for N
deposition (above), with a slope and intercept based on annual
precipitation. You can choose fixed or variable S inputs:
Average atmospheric deposition (wet+dry) = _________(g S m-2 yr-1)
--- Input as a fixed, constant amount each year:
satmos(1): Average deposition = _______________________
satmos(2) = 0.0
--- Have input vary linearly with annual precipitation:
satmos(2) = ______________ * ___________ / ____________
dependence on
average
average
precipitation
annual
annual
(fraction, 0-1)
deposition
precipitation
= _______________________ g S m-2(cm H2O)-1
satmos(1) = ______________ - ___________ * ____________
average
satmos(2)
average
annual
annual
deposition
precipitation
= _______________________ g S m-2 yr-1
S can also be added in irrigation water. If you are irrigating set
sirri equal to the S concentration (mg S/l) of the water, oherwise set
sirri=0.
2.
SOIL BIOGEOCHEMISTRY
2.a.
INITIAL SOIL CARBON POOLS
This parameterization is necessary only if ivauto=0. Two procedures
are described, one for grassland/cropped soils and one for forest
soils. Choose the appropriate procedure but note that precise
initialization of these pools is not necessary if your schedule file
includes an equilibrium block.
Grassland/cropped soils:
Enter the initial litter and soil carbon storages. Enter total in top
20 cm. Subdivisions by pedogenic horizons are not required but may
help set apportioning to CENTURY SOM pools.
Observed soil carbon storages:
_________g C/m2
a.
Litter
b.
Mineral soil_________g C/m2
c.
TOTAL (a+b)__________g C m
2
Calculate apportioning of SOM into CENTURY pools:
I.
Horizon
a:
b:
TOTAL
:
Based on simple horizons:
som1ci(1,1)
som1ci(2,1)
som2ci(1)
som3ci(1)
clittr(1,1)
a*.12 =
a*.03=
a*.40=
a*.02=
a*.43=
b*.03=
b*.44
b*.53
0.0
0.0
Forest soils:
Enter the initial forest floor and soil carbon storages. For mineral
soil enter total in top 20 cm (for organic soils enter 0-20 cm totals
as forest floor, divided by horizons). Forest floor excludes woody
debris. This parameterization can be done using simple horizons or
subhorizons.
Observed soil carbon storages:
Simple Horizons
Sub Horizons
a.
Forest floor_________g C/m2;
a1. L+F layer/01_________
a2. H layer/02 _________
b.
Mineral soil_________g C/m2;
b1. A, Ap
_____________
b2. B, Bt, E_____________
b3. Bh
_____________
c.
TOTAL (a+b)__________g C m2
Calculate apportioning of SOM into CENTURY pools:
I.
Horizon
a:
Based on simple horizons:
som1ci(1,1)
som1ci(2,1)
som2ci(1)
som3ci(1)
clittr(1,1)
a*.12 =
a*.03=
a*.40=
a*.02=
a*.43=
b*.03=
b*.65
b*.32
som2ci(1)
som3ci(1)
0.0
0.0
0.0
b:
TOTAL
:
II.
0.0
Based on subhorizons:
Horizon
a1:
som1ci(1,1)
a2:
a2*.08=
a1*.20=
som1ci(2,1)
0.0
a2*.03=
a2*.55=
a2*.04=
clittr(1,1)
a1*.80=
a2*.30=
b1:
0.0
b1*.04=
b1*.70=
b1*.26=
0.0
b2:
0.0
b2*.02=
b2*.55=
b2*.43=
0.0
b3:
TOTAL
:
0.0
b3*0.2=
b3*.80=
b3*.18=
0.0
The values calculated from simple horizons generally indicate the
"steady state" proportions of the soil pools around which the model
will tend to settle over 1000’s of years. Those based on horizons
suggest non-steady state values for younger or disturbed soils.
Usually they differ little except in organic, very young, or highly
disturbed soils.
Examine the estimates for the initial pools on the previous page and
enter values chosen below:
som1ci(1,1):_______________________
som1ci(2,1):_______________________
som2ci(1): _______________________
som3ci(1): _______________________
clittr(1,1):_______________________
g
g
g
g
g
C/m22
C/m
C/m22
C/m2
C/m
Unless you want to simulate isotope labeling, all som*ci(*,2) and
clittr(*,2) parameters should be set to zero.
Sources for soil carbon data:____________________________________
2.b.
INITIAL SOM C/N, C/P, C/S RATIOS
Enter bulk C/N, C/P, C/S ratios for SOM below (make these calculations
only for those elements you intend to simulate; enter zeros for other
elements):
a. Litter or Forest floor_______C/N, _______C/P, ________C/S
b. Mineral soil
_______C/N, _______C/P, ________C/S
c. TOTAL
_______C/N, _______C/P, ________C/S
Calculate ratios for CENTURY pool:
VARIABLE
rces1(1,i)
EXPRESSION
a / 2.0
rces1(2,i)
b * 0.7
rces2(i)
c * 1.35
rces3(i)
rcelit(1,i)
rcelit(2,i)
c * 0.7
C/N (i=1)
C/P (i=2)
C/S (i=3)
a * 3.0
Sources for soil nutrient data:__________________________________
3.
BIOMASS INITIAL PARAMETERS
This parameterization is not necessary for annual grasses or crops and
is only necessary for perennial grasses and crops if ivauto=0. If you
are simulating a forest or perennial grass or crop, proper
initialization of these pools is not essential if you include an
equilibrium block in your schedule file. If you have biomass and
nutrient concentration estimates and want to set initial conditions
calculate as indicated below.
3.a.
GRASS/CROP ORGANIC MATTER INITIAL PARAMETERS
Carbon pools (if you have actual carbon data rather than just biomass,
use them):
BIOMASS FRACTION
EXPRESSION
VARIABLE
aboveground
biomass * 0.50
aglcis(1)
belowground
biomass * 0.50
bglcis(1)
biomass * 0.50
stdcis(1)
VALUE
Set all the corresponding *cis(2) pools to 0.0 if you are not
simulating isotope labeling.
Nutrient pools P (and S calculations are necessary only if
nelem = 2 (or 3):
Calculate each as (biomass)*(concentration)
FRACTION
aboveground
VARIABLE
agliv(i)
belowground
bgliv(i)
stdede(i)
3.b.
N
i=1
P
i=2
S
i=3
FOREST ORGANIC MATTER INITIAL PARAMETERS
Carbon pools (if you have actual carbon data rather than just biomass,
use them):
BIOMASS FRACTION
EXPRESSION
VARIABLE
LEAVES
biomass * 0.50
rlvcis(1)
FINE ROOT
biomass * 0.50
frtcis(1)
FINE BRANCH
biomass * 0.50
frbcis(1)
LARGE WOOD
biomass * 0.50
rlwcis(1)
COARSE ROOT
biomass * 0.50
crtcis(1)
VALUE
Set all the corresponding *cis(2) pools to 0.0 if you are not
simulating isotope labeling.
Nutrient pools(P and S calculations are necessary only if
nelem = 2 (or 3):
Calculate each as (biomass)*(concentration)
N
P
FRACTION
VARIABLE
i=1
i=2
LEAVES
rleave(i)
FINE ROOT
froote(i)
FINE BRANCH
fbrche(i)
LARGE WOOD
rlwode(i)
COARSE ROOT
croote(i)
3.c.
S
i=3
INITIAL WOODY DEBRIS AND ROOT LITTER POOLS
This parameterization is only necessary for forest systems. Enter the
woody debris and belowground litter pools below. Small woody debris
is the "wood litter" typically measured in forest floor sampling.
Large woody debris is highly clumped spatially hence measures of its
mass usually only come from deliberate efforts to quantify it
specifically. Data for belowground woody debris are rarely available;
a rough estimate can be made by assuming the ratio of
belowground:aboveground large woody debris is equal to the ratio of
coarse root:large wood live biomass. In the absence of any woody
debris estimates, these values can be crudely estimated as anywhere
from 10-30% of their corresponding live pools. "Belowground litter"
is approximately the mass of dead fine roots; in the absence of data
it can be estimated as of the same order of magnitude as live fine
roots. If there is no data from which to initialize these pools, they
may be set to zero and will gradually equilibrate during the model
run. Calculate the initial pools:
Initial woody debris and root litter pools:
Pool
Mass, g/m2
Variable
Small woody
wd1cis(1)
debris
Large woody
wd2cis(1)
debris
Coarse root
wd3cis(1)
debris
Fine root
clittr(2)
litter
Set all the corresponding *cis(2) pools
simulating isotope labeling.
Expression
VALUE, g/m2
small wood
* 0.50
large wood
* 0.50
root * 0.50
root * 0.40
to 0.0 if you are not
Source for woody debris data:____________________________________
4.
MINERAL INITIAL PARAMETERS
-2
minerl(1..n,1) These set the initial N (g m ) in each soil layer. If
you have no data or estimates for this use 1 for the layers that
include the top 20 cm of soil.
minerl(1..n,2) These set the initial P (g m-2) in each soil layer. If
you have no data or estimates for this use 1 for the layers that
include the top 20 cm of soil.
minerl(1..n,3) These set the initial S (g m-2) in each soil layer. If
you have no data or estimates for this use 1 for the layers that
include the top 20 cm of soil.
5.
WATER INITIAL PARAMETERS
This is not necessary if you include an equilibrium block in your
schedule file. But if you want to include precise initial conditions
then enter measured or estimated values for:
rwcf(1..n) These parameters set the initial relative water content
(RWC) for each soil layer.
RWC = (W - WP)/(FC – WP)
where W is the measured soil water content, WP is the soil water
content at wilting point and FC is the soil water content at field
capacity.
snlq is the liquid water in the snowpack (cm H2O)
snow is the snowpack water content (cm H2O)
6.
OTHER PARAMETERS
Check the parameters listed below and be sure they are set to the
indicated values:
w1lig = 0.0
w2lig = 0.0
w3lig = 0.0
crop.100 file
The crop 100 file is used to represent cropped and grassland systems.
The CENTURY installation package contains a crop.100 file for many
common crops (corn, wheat, etc.) and grasses (C3, C4, etc.) that have
been used in the past. Most of the grasses were parameterized with
data from LTER sites while many of the crop parameterizations use data
from VEMAP sites. We suggest that you use one of these existing
parameterizations as a starting point and use the following
suggestions to modify the parameters as needed to represent the
vegetation in your particular system. Do not hesitate to change the
recommended values of parameters to better represent your vegetation,
especially if you have data. See Appendix 2.1 in the Century User’s
Manual for definitions of the parameters in this file.
1.
MAXIMUM PRODUCTION
Maximum production is rarely directly observed in either the model or
reality and must be inferred. Maximum net production is expressed as
the theoretical maximum net biomass production per month in terms of
total mass, not C. Values of 200-300 for grasses and
slow growing
crops (e.g. winter wheat) and up to 600 g biomass m-2 mo-1 for fast
growing crops (corn) have been used.
prdx(1) = __________________________
2.
TEMPERATURE RESPONSES
The effect of temperature on production is controlled by the parameter
ppdf. Typical values for vegetation types are listed below. For
temperate crops, ppdf(1) is approximately equal to the mean
temperature of the warmest month. ppdf(2) is ~15 degrees higher.
ppdf(3) and ppdf(4) affect production mostly at the extremes; values
near 1.0 and 3.0 will serve adequately in most cases.
PARAMETER
ppdf(1)
Optimum
temp.
18
ppdf(2)
Maximum
temp.
35
Corn
30
45
1.0
2.5
Soy bean
27
40
1.0
2.5
C4 grass
30
45
1.0
2.5
C3 grass
15
32
1.0
3.5
Alfalfa
22
35
0.8
3.5
MEANING
Winter wheat/ barley
VALUE CHOSEN
ppdf(3)
Left
shape
0.7
ppdf(4)
Right
shape
5.0
3.
REDUCTION FACTORS
CENTURY allows for growth to be restricted due to physical obstruction
of above ground live and standing dead material. Growth may also be
reduced during the planting month. Values for these parameters that
we have used include:
0 for crop, 1 for grass
1800 for crops, 60-200 for grass
0.4-0.5 for annual crops, 1 for annual grass, and 0 for
perennial grass or crops (see Fig. 3-10 in the Century
User’s Manual)
100-150 (see Fig. 3-10 in the Century User’s Manual)
bioflg
biok5
pltmrf
fulcan
4.
C ALLOCATION
CENTURY accounts for variable allocation of C as plants mature. The
user specifies the initial allocation, final allocation, and the
number of months after the planting month when the final value is
reached. These parameters only apply to crops and annual grasses (see
Fig. 3.11 in the Century User’s Manual).
frtc(1)
frtc(2)
frtc(3)
5.
0.4-0.6 for crops, 0 for grass
0.1 for most crops, 0 for grass
3 for most crops, 0 for grass
C/E RATIOS
CENURY allows for flexibility in the ranges of C/E ratios as above
ground biomass increases. The following parameters (pramn(i,j) and
pramx(i,j)) control the maximum and minimum C/E ratios (E = N, P, or
S) for shoots when plant biomass is above and below biomax. The
following table shows values that we have used for pramn and pramx.
biomax=400 for most grasses and crops. (See Fig. 3-13 in the Century
User’s Manual).
pramn(1,1)
Tall
grass
20
Winter
wheat
12
Short
grass
30
8.5
Soy
bean
7.55
10
pramn(2,1)
390
100
390
100
150
150
pramn(1,2)
30
40
90
8.5
30
40
pramn(2,2)
390
160
390
100
150
150
pramx(1,1)
30
25
35
15
10
20
pramx(2,1)
440
200
440
133
230
230
pramx(1,2)
80
100
95
15
40
60
pramx(2,2)
440
260
440
133
230
230
Alfalfa
Corn
prbmn(i,j) and prbmx(i,j) control the minimum and maximum C/E (E = N,
P, or S) of roots. We believe these parameters are mainly a function
of plant type and commonly use a slope of 0.0. However, users have
the option of making C/N of roots vary with precipitation (see
parameter definitions).
prbmn(1,1)
Tall
grass
60
Winter
wheat
45
Short
grass
50
17
Soy
bean
24
34
prbmn(2,1)
390
390
390
100
390
390
prbmn(1,2)
0
0
0
0
0
0
prbmn(2,2)
0
0
0
0
0
0
prbmx(1,1)
80
60
55
22
28
60
prbmx(2,1)
420
420
420
133
420
420
prbmx(1,2)
0
0
0
0
0
0
prbmx(2,2)
0
0
0
0
0
0
6.
Alfalfa
Corn
LIGNIN CONTENTS
The lignin content of above and below ground material can be constant
or made a function of annual rainfall. See parameter definitions.
This table shows values we have used.
fligni(1,1)
Tall
grass
0.02
Winter
wheat
0.15
Short
grass
0.02
0.04
Soy
bean
0.12
0.12
fligni(2,1)
0.012
0.0
0.012
0.0
0.06
0
fligni(1,2)
0.26
0.06
0.26
0.12
0
0.06
fligni(2,2)
-0.0015
0
-0.0015
0.4
0
0
Alfalfa
Corn
7.
HARVEST/SENESCENCE PARAMETERS
The user controls the amount of C and nutrients allocated to grain,
effects of water stress on harvest, and N volatilized at harvest or
senescence through the following parameters. See parameter
definitions and Fig. 3-15 the Century User’s Manual.
himax
Tall
grass
0
Winter
wheat
0.5
Short
grass
0
0
Soy
bean
0.4
0.6
hiwsf
0
0.42
0
0
0
0
himon(1)
0
1
0
2
2
2
himon(2)
0
1
0
1
1
1
efgrn(1)
0.5
0.75
0
0
0.67
0.75
efgrn(2)
0.5
0.6
0
0
0.6
0.6
vlossp
0.04
0.04
0.15
0.02
0.04
0.04
8.
Alfalfa
Corn
SHOOT AND ROOT DEATH RATES AND NUTRIENT RETRANSLOCATION PARAMETERS
The user controls the maximum monthly shoot death rate, senescence
month shoot death rate, the influence of shading on death rate, shoot
fall rate, maximum root death rate, and the fraction of nutrients
retranslocated from leaves at death. See Fig. 3-16 the Century
Users’s Manual.
fsdeth(1)
Tall
grass
0.2
Winter
wheat
0
Short
grass
0.2
0.3
Soy
bean
0
0
fsdeth(2)
0.95
0
0.95
0.4
0
0
fsdeth(3)
0.2
0
0.2
0.1
0
0
fsdeth(4)
150
200
150
500
500
500
fallrt
0.15
0.12
0.15
0.5
0.1
0.1
rdr
0.07
0.05
0.05
0.2
0.05
0.05
rtdtmp
2
2
2
2
2
2
crprtf(1)
0.5
0
0
0
0
0
crprtf(2)
0
0
0
0
0
0
Alfalfa
Corn
9.
SYMBIOTIC BIOLOGICAL N FIXATION
N fixation is parameterized as snfxmx(2) = maximum g N fixed per g C
NPP. This can be approximated as (symbiotic N fixation)/(annual NPP g
C). Remember to set this to the maximum value; it will be reduced if
nitrogen availability is high enough. Enter the value used below
snfxmx(2) = _______________________ (g N fixed)/(g C NPP)
10.
DOUBLED CO2 PARAMETERS
CENTURY allows simulations to be conducted assuming a doubling of
atmospheric CO2 concentration from 350 ppm to 700 ppm. The following
parameters control the effects of doubled CO2 on NPP, transpiration,
C/E ratios, and root/shoot ratios.
co2ipr(1) is the multiplier that represents the effect of doubled CO2
on NPP.
co2ipr(1) = 1 for C4 and ~1.3 for C3
co2itr(1) is the multiplier that represents the effect of doubled CO2
on transpiration rate.
co2itr(1) = ~0.6
co2ice(1,i,j) is the multiplier that represents the effect of doubled
CO2 on minimum and maximum C/E ratios.
co2ice(1,i,j) = ~1.0
co2irs(1) is the multiplier that represents the effect of doubled CO2
on root/shoot ratio.
co2irs(1) <= ~1.3
tree.100
The CENTURY installation package contains tree.100 parameterizations
for deciduous, coniferous, and tropical systems that have been used in
the past. We suggest that you use one of those files as a starting
point and use the following procedure to modify parameters as needed
to represent the trees in your particular system. See Appendix 2.10
in the Century User’s Manual for definitions of the parameters in this
file.
1.
FOREST TYPE
Decide whether to simulate your forest as evergreen, deciduous, or
drought deciduous. In evergreen systems, allocation is fixed through
the year and leaf fall is calculated each month. In deciduous
forests, 80% of first month production goes to leaves and a given
percentage of leaves senesce and fall at the end of the growing season
which occurs when the days are shortening and temperatures are
dropping into the fall seasonal range. In a drought deciduous forest,
allocation is fixed throughout the year and a given percentage of
leaves senesce and fall at the end of the growing season which is
marked when the soil moisture reaches wilting point. In general, if
the large majority of the canopy is deciduous (say 80% or greater) one
of the deciduous system options will be adequate; otherwise use the
evergreen option.
For evergreen or semi-evergreen systems:
decid = 0
For deciduous systems:
decid = 1
For drought deciduous systems:
decid = 2
2.
MAXIMUM PRODUCTION
There are two maximum production values, one for gross production and
the other for net production. Either of these can be disabled by
setting it to a very high value (e.g. 10000) and allowing the other to
control production. Maximum production is rarely directly observed in
either the model or reality and must be inferred.
--- Maximum gross production
This is expressed as the theoretical maximum gross production per
month in terms of total organic matter produced, NOT in terms of
carbon. Common values are 1200-1500 g m-2 mo-1.
prdx(2) = __________________________
--- Maximum net production
This is expressed as the theoretical maximum net biomass production
per month in terms of carbon, NOT total mass. Common values are 300400 g C m-2 mo-1.
prdx(3) = __________________________
3.
CONTROLS ON PRODUCTION
3.a.
TEMPERATURE RESPONSES
The effect of temperature on production is controlled by the parameter
ppdf. Typical values for generalized forest types are listed below
(the example genera listed are heavily northamericano biased and are
general guidelines only). For temperate forests, ppdf(1) is
approximately equal to the mean temperature of the warmest month.
ppdf(2) is at least 15 degrees higher. ppdf(3) and ppdf(4) affect
production mostly at the extremes; 1.0 and 3.0 will serve adequately
in most cases.
Select values for ppdf:
PARAMETER
MEANING
Arctic/alpine shrub
(Ledum, Betula, Salix)
Boreal/subalpine conifer
(Picea, Abies, Pinus)
Northern hardwoods
(Betula, Populus, Acer)
Temperate conifer
(Pinus, Juniperus)
Temperate hardwood
(Quercus, Carya, etc.)
Tropical and subtropical
hardwood and conifer
VALUE CHOSEN
ppdf(1)
Optimum
temp.
ppdf(2)
Maximum
temp.
ppdf(3)
Left
shape
ppdf(4)
Right
shape
10
25
1.0
3.5
18
35
1.0
3.0
22
42
1.0
3.5
27
45
1.0
3.0
25
45
1.0
3.0
30
45
1.0
2.5
3.b.
BIOMASS CHEMISTRY
You have three options for calculating the biomass C/E. If you have
actual carbon data instead of just biomass, then use C data instead of
the generalized carbon percentages listed below. Select which option
you prefer, mark it with a check, calculate the C/E ratios and
retranslocation controls, and fill in the table with the values for
cerfor.
__1. Simulate tissue chemistry as fixed, with no retranslocation
or response to nutrient availability:
Record the values for cerfor below:
C/N
C/P
C/S
VARIABLE
EXPRESSION
i=1
i=2
i=3
cerfor
55%/leaf
litter conc
(*,1,i)
cerfor
50%/fine
root conc
(*,2,i)
cerfor
50%/fine
(*,3,i)
branch conc
cerfor
50%/large
wood conc.
(*,4,i)
cerfor
50%/coarse
(*,5,i)
root conc.
Set all values for forrtf equal to 0.
__2. Use fixed tissue chemistry (no response to nutrient
availability) but simulate retranslocation of nutrients from
senescent leaves before litterfall:
Record the values for cerfor below:
C/N
C/P
C/S
VARIABLE
EXPRESSION
i=1
i=2
i=3
cerfor
45%/green
(*,1,i)
leaf conc
cerfor
50%/fine
(*,2,i)
root conc
cerfor
50%/fine
branch conc
(*,3,i)
cerfor
50%/large
(*,4,i)
wood conc.
cerfor
50%/coarse
(*,5,i)
root conc.
Set values for forrtf as
forrtf(1): 1-(leaf litter %N)/(green leaf %N) = _____
forrtf(2): 1-(leaf litter %P)/(green leaf %P) = _____
forrtf(3): 1-(leaf litter %S)/(green leaf %S) = _____
__3. Use both variable tissue chemistry and retranslocation:
Based on data from fertilization trials, site
comparisons, literature, and/or educated guesses widen
the allowable range for one or more of the biomass
fractions. Foliar N content has the most extensive
data, but this option can be implemented for any or all
biomass pool(s) and nutrient(s). Assign the minimum
C/E ratio (maximum nutrient content) to cerfor(1,*,*),
the maximum C/E ratio (minimum nutrient content) to
cerfor(2,*,*) and the initial C/E ratio to
cerfor(3,*,*). Note that the maximum C/E ratio will
never actually be achieved in practice, so it must be
set higher than the observed highest value.
Record the values for cerfor below:
C/N
C/P
C/S
VARIABLE
i=1
i=2
i=3
cerfor(1,1,i)
cerfor(2,1,i)
cerfor(3,1,i)
cerfor(1,2,i)
cerfor(2,2,i)
cerfor(3,2,i)
cerfor(1,3,i)
cerfor(2,3,i)
cerfor(3,3,i)
cerfor(1,4,i)
cerfor(2,4,i)
cerfor(3,4,i)
cerfor(1,5,i)
cerfor(2,5,i)
cerfor(3,5,i)
Set values for forrtf as in option 2 above.
4.
WOOD DECOMPOSITION RATES
No good general scheme exists for estimating wood decomposition rates
from chemical or physical properties of the wood; therefore CENTURY
sets wood decomposition as a system-specific parameter. To set this,
first estimate the mean turnover times of each wood pool, then
calculate the values for decw. Mean turnover times can be estimated
as the half-life (in terms of mass loss) of an average piece of woody
debris, or assuming steady state (questionable for large wood) as
(standing stock)/(input rate). Again, for belowground woody debris
there is often very little data; a value similar to that for large
wood can be used in the absence of other information.
Calculate values for decw:
Perform a 3 year simulation using default parameters and mean weather
for your system. Output and calculate average values of defac and
anerb for the third year and complete the table:
DEBRIS COMPONENT
FINE BRANCH
LARGE WOOD
BELOWGROUND
5.
TURNOVER TIME, yr
EXPRESSION
2.5/(turnover*
defac)
2.5/(turnover*
defac)
2.5/(turnover*
defac*anerb)
decw
decw1=
decw2=
decw3=
BIOMASS AND WOODY DEBRIS
5.a.
BIOMASS AND NPP DATA
Enter below your best estimates for biomass pool sizes, chemistry,
annual production, and turnover (comments on estimating values
follow):
BIOMASS
NPP
LITTER
-2
-1
-2
-1
FRACTION
g/m2
g m yr g m yr
GREEN
XXXXXXX
LEAF
XXXXXXX
LEAF
XXXXXXX
XXXXXXX
XXXXXXX
XXXXXXX
LITTER
FINE
BRANCH*
LARGE
WOOD*
COARSE
ROOT**
FINE
ROOT**
TOTALS
%N
XXXXXXX
%P
XXXXXXX
%S
XXXXXXX
* Large wood is branch and stem wood > 10 cm diameter
**Fine roots are < 2 mm diameter
Measured "wood litterfall" collected in traps usually indicates fine
branch litterfall, and can be used as an estimate of fine branch
production in older forests. Large wood litterfall is rarely measured
and must be estimated from guesses about turnover time and tree
longevity. Coarse root production is likewise rarely measured; often
even biomass data are lacking. Educated guesses as to biomass and
turnover rates must be used in these cases.
Sources for biomass and production data:________________________
5.b.
PRODUCTION ALLOCATION PATTERN
CENTURY allows for different C allocation patterns for juvenile and
mature forests. Age indicator, i, is 1 for early forest, 2 for late
forest. If you are simulating only 1 types of forest set swold = 0.0
and fcfrac the same for i = 1 and 2. Otherwise, perform the following
calculations for each forest type and set swold = number of years
after beginning of simulation when the forest changes from juvenile to
mature:
fcfrac(1,i):(leaf production)/(total NPP)=
fcfrac(2,i):(fine root production)/(total NPP)=
fcfrac(3,i):(fine branch production)/(total NPP)=
fcfrac(4,i):(large wood production)/(total NPP)=
fcfrac(5,i):(coarse root production)/(total NPP)=
6.
__________
__________
__________
__________
__________
BIOMASS TURNOVER RATES
6.a.
SET LEAF DEATH RATES
Monthly leaf turnover is set in leafdr. In a deciduous or drought
deciduous system, the values of leafdr indicate mortality during the
growing season from causes such as herbivory, physical damage, or
early senescence. The leaf mortality at the end of the growing season
for deciduous or drought deciduous trees is determined by the value
entered for wooddr(1). In an evergreen or semievergreen system,
leafdr indicates all leaf turnover including seasonal senescence and
litterfall. In any case, these values are the fraction of leaves that
are transferred to litter each month. These values should be
estimated from observed rates of litterfall in comparison to observed
or estimated leaf biomass.
In deciduous and drought deciduous systems wooddr(1) is the fraction
of leaves that are lost during the month of leaf drop. For
temperature deciduous systems the months of leaf out and leaf drop are
controlled by temperature and day length while for drought deciduous
systems leaf drop occurs when monthly soil water content is below the
wilting point. Typical values for wooddr(1) for are ~0.95 for
temperature deciduous and ~0.3 for drought deciduous but use estimates
All forest systems:
leafdr(1)
leafdr(2)
leafdr(3)
leafdr(4)
leafdr(5)
leafdr(6)
=
=
=
=
=
=
_______________
_______________
_______________
_______________
_______________
_______________
leafdr(7)
leafdr(8)
leafdr(9)
leafdr(10)
leafdr(11)
leafdr(12)
=
=
=
=
=
=
_______________
_______________
_______________
_______________
_______________
_______________
Sources for litterfall/seasonality information:_______________________
______________________________________________________________________
6.b
ROOT AND WOOD DEATH RATES
Turnover of other pools is constant through the year and is in the
parameter wooddr.
Monthly fine root death rate, wooddr(2), is equal to
(annual fine root production)/(fine root biomass) = ________
12
Monthly fine branch death rate, wooddr(3), is equal to
(annual f. branch litterfall)/(f. branch biomass) = ________
12
Monthly large wood death rate, wooddr(4), is equal to
(annual l. wood litterfall)/(l. wood biomass) =
_______;
12
It may also be estimated as approximately the rate of whole tree
mortality per month.
Monthly coarse root death rate, wooddr(5), is very difficult to
estimate directly. It is typically similar in magnitude to large wood
death, wooddr(3). Enter the value used here:_______________
Sources:_________________________________________________________
6.c.
LEAF AREA CONTROLS
Set the leaf area to biomass ratio (based on biomass, not carbon):
btolai = (leaf area, m2 projected)/(leaf
dry mass, g)
= ___________________________ m2/g
Set the allometric controls on LAI as follows:
maxlai: maximum allowable LAI =
___________________ m2/m2
2
klai:
large wood mass (g C/m ) at which half of the
maximum LAI is achieved = ___________________ g C/m2
Source for LAI data:_____________________________________________
6.d.
SAPWOOD ALLOMETRIES
Set the relationship between sapwood and total wood as:
sapk: Maximum sapwood mass in mature stand; can be
approximately estimated as 10 years worth of wood
production = __________________________________ g C/m2
Symbiotic biological N fixation is parameterized as snfxmx(2) =
maximum g N fixed per g C NPP. This can be approximated as (symbiotic
N fixation)/(annual NPP g C). Remember to set this to the maximum
value; it will be reduced if nitrogen availability is high enough.
Enter the value used below:
snfxmx(2) = _______________________ (g N fixed)/(g C NPP)
Sources for N input data:________________________________________
7.
LIGNIN FRACTION OF FOREST COMPONENTS
The lignin content of tree components is system specific.
following table shows ranges of values we have used:
The
tree component
parameter
leaves
wdlig(1)
0.14 – 0.18
fine roots
wdlig(2)
0.09 – 0.28
fine branches
wdlig(3)
0.20 – 0.35
large wood
wdlig(4)
0.20 - 0.35
coarse roots
wdlig(5)
0.20 – 0.35
8.
lignin fraction
DOUBLED CO2 PARAMETERS
CENTURY allows simulations to be conducted assuming a doubling of
atmospheric CO2 concentration from 350 ppm to 700 ppm. The following
parameters control the effects of doubled CO2 on NPP, transpiration,
C/E ratios, and root/shoot ratios.
co2ipr(2) is the multiplier that represent the effect of doubled CO2 on
NPP.
co2ipr(2) = ~1.3
co2itr(2) is the multiplier that represent the effect of doubled CO2 on
transpiration rate.
co2itr(2) = ~0.75 for deciduous and ~0.9-0.95 for coniferous
co2ice(2,i,j) is the multiplier that represent the effect of doubled
CO2 on minimum and maximum C/E ratios.
co2ice(2,i,j) = ~1.2
co2irs(2) is the multiplier that represent the effect of doubled CO2 on
root/shoot ratio.
co2irs(2) <= ~1.3
9.
SAVANNA MODEL PARAMETERS
CENTURY allows the user to simulate competition between trees and
grasses. If you are not simulating a savanna (i.e. are only growing
trees) set the following 3 parameters to 1.
basfc2 relates tree basal area to grass N fraction.
basfc2 = ~ 0.5
basfct ratio between basal area and wood biomass.
basfct = ~400
sitpot relates grass N fraction to N availability. This represents
the above ground peak standing grass biomass without tree competition.
Units are pounds/acre and values range from 1000-4000.
sitpot = ~2400
10. OTHER PARAMETERS
Check the parameters listed below and be sure they are set to the
indicated values:
laitop = -0.5
del13c = -15 to –28
fix.100
If you want to simulate the effects of changes in atmospheric CO2
concentration you must specify the initial parts per million
(co2ppm(1)) and final parts per million (co2ppm(2)) of CO2
concentration and set co2rmp to specify a step (=0) or ramp (=1)
function. Most of the other parameters in the fix.100 should not be
changed. However, some parameters may need to be adjusted to
represent differences in C/N ratios of SOM inputs for grasslands and
forests and differences in P and S availability among various systems.
No other parameters in the fix.100 should be changed unless the user
has strong experimental evidence to justify the change. See Appendix
2.5 in the Century User’s Manual for definitions of parameters in the
fix.100 file.
1.
FLOATING C/N RATIOS IN SOM POOLS
The parameters controlling the C/N ratios may need to be adjusted from
the default values, particularly for temperate forest soils. The
default values listed in the table below are for grass/crop soils and
forest soils with a bulk C/N < 15. In most cases you will use the
default values from the table. If, however, your soil has a bulk C/N
> ~15 use the alternate values from the table.
Parameter
pcemic(1,1)
pcemic(2,1)
varat1(1,1)
varat1(2,1)
varat2(1,1)
varat2(2,1)
varat3(1,1)
varat3(2,1)
Default
16
10
14
3
20
12
8
6
Bulk soil C/N > 15
16
10
16
8
40
12
20
8
2.
C/E OF NEWLY FORMED SOM
The parameter rad1p is used to adjust the C/E ratio of newly formed
slow SOM produced from surface active SOM. This value is calculated
from the parameter rad1p as a function of C/E ratios of the surface
active SOM pool. You can either set it up as fixed values or let it
float. When using fixed values for rad1p it is a prescribed value
that is generally higher when leaf litter is of lower initial quality.
Typical fixed values for different systems are:
Grass/
crops
5
Conifers
forest
14
Temperate
hardwood
12
Tropical
hardwood
5
0
0
0
0
5
5
5
5
220
300
100
200
0
0
0
0
100
100
100
100
220
300
200
200
0
0
0
0
100
100
100
100
Typical floating values for different systems are:
Grass/
crops
12
Conifers
forest
-6
Temperate
hardwood
-5
Tropical
hardwood
0
3
3
3
3
5
5
5
5
220
-200
-200
-200
5
5
5
5
100
200
200
200
220
-200
-200
-200
5
5
5
5
100
100
100
100
3.
PHOSPHORUS (AND SULFUR)
If you are only modeling N (see nelem in your <site>.100 file) then
these parameters are irrelevant. If you do want to model P (and S)
then there are 2 ways to supply P inputs and 3 ways to supply S
inputs. P (and S) can be supplied by weathering of parent material in
which case you should appropriately adjust parent(2) (and parent(3))
in your <site>.100 file and pparm(2) (and pparm(3)) in the fix.100
file. parent(i) controls the amount of P (or S) in parent material
and pparm(i) controls the weathering rate in units of the fraction of
parent material weathered to mineral form per year. P (and S) can be
supplied as fertilizer inputs in which case you should make an
appropriate option in the fert.100 file. Atmospheric S inputs are
accounted for in your <site>.100 file.
If you have estimates of parent material P (and S) and atmospheric
deposition of S you can use the following table to parameterize
parent(i) and pparm(i) (this scheme is not necessarily appropriate for
detailed examination of long-term P dynamics and pedogenesis).
First, run the model for 3 years using mean weather and monthly
output. Calculate the average value of defac then complete:
Phosphorus
i = 2
Sulfur
i = 3
a. Atmospheric
deposition, wet +
dry (g m-2 yr-1)
Literature source:
b. Weathering
inputs that occur
within the rooting
zone (g m-2 yr-1)
Literature source:
c. TOTAL INPUTS =
a + b
d. defac (avg.)
e. parent(i)
{<site>.100}
pparm(i)=c/(d*e)
{fix.100}
Set the flag for texture effect on parent P mineralization for no
effect:
TEXEPP(1) = 0.0
Sources for P (and S) input data:________________________________
```