United States

Department of

Agriculture

Forest Service

Pacific Northwest

Research Station

General Technical

Report

PNW-GTR-508

June 2001

In cooperation with:

Oregon State

University

Colorado State

University

MC1: A Dynamic Vegetation Model

for Estimating the Distribution of

Vegetation and Associated Ecosystem

Fluxes of Carbon, Nutrients, and Water

Technical Documentation. Version 1.0

Dominique Bachelet, James M. Lenihan, Christopher Daly,

Ronald P. Neilson, Dennis S. Ojima, and William J. Parton

lifeform mixture

live biomass

fire

occurrence

lifeform

mixture

carbon pools

soil moisture

biomass mortality

and consumption

nutrient loss

and release

lifeform

gradient

model

modified

CENTURY

model

MCFIRE

model
Dominique Bachelet is an associate professor of bioresource engineering, James M.

Lenihan is a research associate of botany and plant pathology, and Christopher Daly

is an assistant professor of geosciences, Oregon State University, Corvallis, OR 97331;

Ronald P. Neilson is a bioclimatologist, U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331; and

Dennis S. Ojima is a research scientist and William J. Parton is a senior research

scientist, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins,

CO 80523.

Cover: Links and feedbacks among the three modules of the dynamic vegetation model MC.

Authors
Abstract Bachelet, Dominique; Lenihan, James M.; Daly, Christopher; Neilson, Ronald P.;

Ojima, Dennis S.; Parton, William J. 2001. MC1: a dynamic vegetation model for

estimating the distribution of vegetation and associated carbon, nutrients, and

water—technical documentation. Version 1.0. Gen. Tech. Rep. PNW-GTR-508.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 95 p.

Assessments of vegetation response to climate change have generally been made only

by equilibrium vegetation models that predict vegetation composition under steady-state

conditions. These models do not simulate either ecosystem biogeochemical processes

or changes in ecosystem structure that may, in turn, act as feedbacks in determining

the dynamics of vegetation change. MC1 is a new dynamic global vegetation model

created to assess potential impacts of global climate change on ecosystem structure

and function at a wide range of spatial scales from landscape to global. This new tool

allows us to incorporate transient dynamics and make real time predictions about the

patterns of ecological change. MC1 was created by combining physiologically based

biogeographic rules defined in the MAPSS model with a modified version of the

biogeochemical model, CENTURY. MC1 also includes a fire module, MCFIRE, that

mechanistically simulates the occurrence and impacts of fire events.

Keywords: MC1, model documentation, vegetation response, climate change, MAPSS,

CENTURY, dynamic global vegetation model.
Contents 1 1. Introduction

3 2. Model Environment

3 2.1 Mode of Operation

3 2.1.1 Equilibrium mode

3 2.1.2 Transient mode

5 2.2 Spatial Scales

6 2.3 Input Data

6 2.3.1 Climate

7 2.3.2 Soil

7 3. Model Description

7 3.1 Biogeography

7 3.1.1 Delayed response

9 3.1.2 Lifeform interpreter

11 3.1.3 Vegetation classification rule base

13 3.2 Biogeochemistry

13 3.2.1 Net primary production

16 3.2.2 Decomposition

16 3.2.3 Hydrology

17 3.2.4 Competition for resources

17 3.2.5 Changes to CENTURY code

19 3.3 Fire

20 3.3.1 Fuel moisture and loading

21 3.3.2 Fire occurrence

22 3.3.3 Fire behavior and effects
24 3.3.4 Fire feedbacks to biogeochemistry

25 3.3.5 Fire feedbacks to biogeography

33 4. Parameters and Variables

33 4.1 Generalization of Input Parameters

33 4.2 Biogeographic Parameters and Variables

33 4.2.1 Equilibrium conditions

34 4.2.2 Transient conditions

34 4.3 Biogeochemical Parameters and Variables

34 4.3.1 Parameter and initial condition files

42 4.3.2 Biogeochemical parameters and variables

60 4.4 Fire Parameters and Variables

60 4.4.1 Fire parameters and descriptions

66 4.4.2 Fire parameter values

67 4.5 Output Variables

67 Acknowledgments

68 References

71 Appendix 1: List of Subroutines

81 Appendix 2: Routine Calling Sequence

93 Appendix 3: Abstracts
MC1 is a new dynamic vegetation model created to assess the impacts of global climate

change on ecosystem structure and function at a wide range of spatial scales from

landscape to global. MC1 was conceived at the beginning of the second phase of the

Vegetation/Ecosystem Modeling and Analysis Project (VEMAP). The first phase of

VEMAP consisted of a comparison of three biogeographic models (BIOME2 [Haxeltine

and others 1996, Prentice and others 1992], DOLY [Woodward and others 1995]), and

MAPSS ([Neilson 1995]) and three biogeochemical models (CENTURY [Parton and others

1987], BIOME-BGC [Running and Coughlan 1988, Running and Gower 1991], and TEM

[McGuire and others 1995]) to determine their responses to climate and carbon dioxide

(CO2) change (VEMAP Members 1995). The goal was to identify areas of uncertainty in

the six models and to increase our knowledge of ecological responses to altered forcing.

The objectives of the second phase included comparing the same biogeochemical models

and newly created coupled biogeographic-biogeochemical models, such as MC1.

1. Introduction

Figure 1—Simplified diagram of MC1. The biogeographic module includes a lifeform

“interpreter” that defines four tree lifeforms: deciduous needleleaf (DN), evergreen

needleleaf (EN), deciduous broadleaf (DB), and evergreen broadleaf (EB). Two

grass lifeforms are included as a function of climate. When the minimum monthly

(coldest month) mean temperature (MMT) drops below -15 °C, trees are assumed

to be needleleaved; when it is above 18 °C, trees are assumed to be evergreen

broadleaved. The relative mixture of tree lifeform also depends on precipitation

during the growing season (GSP). The biogeographic module also includes

vegetation classification rules that use thresholds of maximum monthly tree and

grass LAI (numbers on arrows) to distinguish forest, savanna, shrubland and

grassland classes. Specific classes are then determined by the lifeform mixes

provided by the lifeform interpreter and a few climatic indices. The biogeochemical

module is based on CENTURY (Parton and others 1987) and includes grass and

tree live compartments. It includes litter pools and soil organic matter pools.

Nitrogen and water fluxes are calculated to modify potential production. Information

from the vegetation classifier is used to determine which parameter values are

appropriate. The fire module uses information from the biogeochemical module to

calculate fuel loading and climatic information to calculate fuel moisture. It uses

information from the lifeform interpreter to choose allometric relations for

calculating crown and surface fire behavior. Postfire mortality information is used

by the biogeochemical module to reduce live plant pools.

1
Table 1—Interactions among the 3 modules in MC1 and information passed to and

from each module

Passed to:

Passed from: Biogeography Biogeochemistry Fire

Biogeography Position along lifeform Lifeforms (tree leaf

gradients (which determines type and used in

the phenology), interpolation allometric equations)

between lifeform-specific

standard CENTURY

parameters

Biogeochemistry Tree and grass leaf Aboveground carbon

carbon pools

Turnover and

decomposition rates

from the carbon pools

The value of the index

that modifies primary

production as a

function of available

soil moisture

Fire LAI and climate Consumption of dead

smoothing period is aboveground carbon,

reset to 0 after the associated with losses

occurrence of a fire by gaseous emissions

Nutrient return, calculated

as a fraction of the

biomass consumed

MC1 was produced by combining physiologically based biogeographic rules, originally

defined in the MAPSS model (Neilson 1995), with biogeochemical processes packaged in

a modified version of CENTURY (Parton and others 1987) and a new fire disturbance model,

MCFIRE (Lenihan and others 1998). The three linked modules simulating biogeography

(lifeform interpreter and vegetation classifier), biogeochemistry, and fire disturbance are

represented in figure 1 and their interactions are described in table 1.

The main functions of the biogeographic module (section 3.1) are to (1) predict lifeforms,

that is, the composition of deciduous-evergreen tree and C3-C4 grass lifeform mixtures;

and (2) classify those lifeforms and their associated biomass into different vegetation

classes using a climatologic rule base.

The biogeochemical module (section 3.2) simulates monthly carbon (C) and nutrient

dynamics for a given ecosystem. Aboveground and belowground processes are modeled

in detail and include plant production, soil organic matter decomposition, and water and

nutrient cycling. Parameterization of this module is based on the lifeform composition of

the ecosystems, which is updated annually by the biogeographic module.

The fire module (section 3.3) simulates the occurrence, behavior, and effects of severe

fire. Allometric equations, keyed to the lifeform composition supplied by the biogeographic module, are used to convert aboveground biomass to fuel classes. Fire effects

(plant mortality and live and dead biomass consumption) are estimated as a function of

2
simulated fire behavior (fire spread and fire line intensity) and vegetation structure. Fire

effects feed back to the biogeochemical module to adjust levels of various C and nutrient

pools and alter vegetation structure (e.g., leaf area index [LAI] levels and woody vs.

grass-dominated vegetation; table 1).

2.1.1 Equilibrium mode—MC1 is operated in two successive modes: equilibrium and

transient (fig. 2). First, the biogeochemical module requires an initial vegetation class for

parameterization. This initial vegetation map is provided by MAPSS, an equilibrium

model with full water balance simulation and a detailed biogeographical rule base

(Neilson 1995). MAPSS is run on long-term mean climate, which consists of 1 year of

monthly climate data. MAPSS requires two parameter files: site, which includes the

soil characteristic thresholds used in the water balance module; and parameter, which

includes climatic thresholds used in the biogeographic rules. (Parameter files are

reviewed in detail in section 4.)

For each vegetation type, the biogeochemical module selects the respective parameters

and initial condition files. These consists of (1) the schedule files (vvegTypex.sch)

where grass and tree types are defined and where fire events are scheduled; (2) the site

files (xfix.100), which include most of the site characteristics, such as the rates of

nitrogen (N) loss, and (3) the parameter files (vvegTypex.100), which include initial

conditions for soil organic matter and mineral content. The biogeochemical module also

reads the files tree.100 and crop.100, which include the physiological parameters

used in the C, N, and water cycles. The biogeochemical module runs on the same mean

climate until the slow soil C pool (see section 3.2.2.) reaches a steady state. This takes

200 to 3,000 simulation years, depending on the ecosystem being simulated. Because

the fire module cannot be run effectively on a mean climate, fire events are scheduled

at regular intervals that differ with vegetation type. Grasslands and savannas are assigned

5- to 30-year intervals, and certain forests have fire intervals exceeding 400 years.

2.1.2 Transient mode—Once the vegetation type has been defined and the slow soil C

pool has equilibrated, MC1 is run in transient mode on a monthly time step for a userdefined number of years to read the transient climatic data and produce estimates of C

and nutrient pools for each simulated vegetation type.

Every year the biogeographic module uses climatic data (MC1 biogeographic thresholds

are defined in the file thres.dat) and maximum tree and grass LAIs, which are derived

from the biogeochemical module’s standing biomass data and have been smoothed to

reduce interannual variability. When a fire has occurred, the LAI smoothing period (defined

in section 3.1.1) is set to zero, thus allowing the lifeform interpreter to predict a period of

low cover vegetation following the fire. The appropriate lifeform composition is determined

each year to start the next simulation year. The lifeform mixture is used by the fire module

for allometric calculations and by the biogeochemical module to determine lifeformdependent parameter values that are read from the files tree.100 and crop.100.

The biogeochemical module uses climatic data and the vegetation type as defined by

the biogeographic module to calculate C and N pools for each vegetation type and for

soil water content. It reads tree and grass types from the transient schedule files

(Mapss-Cenx.sch), soil characteristics from vvegTypex.100, physiological

parameters from the files tree.100 and crop.100, and some initial conditions from

xfix.100 files.

2. Model Environment

2.1 Mode of Operation

3
Figure 2—Operational flow of the MC1 model. MC1 is operated in two successive

modes: equilibrium and transient. In equilibrium mode, the biogeochemistry module

requires an initial vegetation class for parameterization. MAPSS (Neilson 1995) is

run on long-term mean climate, which consists of one average year of monthly

climate data (usually representing the most recent 30 years of record). The

biogeochemistry module is then run on the MAPSS vegetation class by using the

same mean climate until the slow soil carbon pool reaches a steady state. This

takes 200 to 3000 years, depending on the ecosystem being simulated. Because

the fire module cannot be run meaningfully on a mean climate, fire events are

scheduled at regular intervals that differ with vegetation type. Grasslands and

savannas are assigned 30-year intervals, and certain forests types have fire

intervals exceeding 400 years. In transient mode, the biogeochemistry module

operates on a monthly time step for a period of years, reading the transient climate

data and producing estimates of monthly carbon and nutrient pools. The fire

module accesses the same climate data and the biogeochemical carbon pools to

estimate fuel load and fuel moisture, and maintains a running probability of fire

occurrence. If that probability exceeds a certain threshold, a fire is simulated. The

fire module then calculates changes to carbon and nutrient pools, which are

passed back to the biogeochemistry module for use in the following month of

operation. Emissions from the simulated fire also are calculated. Every year, the

biogeography module uses climate data and maximum monthly tree and grass LAI

(derived from standing biomass data from the biogeochemistry module) that have

been smoothed to reduce interannual variability. When a fire has occurred, the LAI

smoothing period is reset to zero, thus allowing the vegetation classifier to simulate

a period of low cover vegetation after the fire. Vegetation classification is thus

allowed to proceed through a series of successional stages, for example from

grassland, to savanna to forest. The appropriate lifeform composition is determined

each year to start the next simulation year. The lifeform mixture is used by the fire

module for allometric calculations, and by the biogeochemistry module to determine

lifeform-dependent parameter values.

4
The fire module accesses the same climatic data and the biogeochemical C pools to

estimate fuel load and fuel moisture, and it maintains a running probability of fire

occurrence. A fire is simulated when thresholds defined in fire_param.dat are

exceeded. The fire module then calculates changes to C and nutrient pools. These are

passed back to the biogeochemical module, which uses them in the following month of

operation. Carbon emissions from the simulated fire also are calculated.

To date, MC1 has been run at three different spatial scales (local, national, and global)

based on the availability of climatic and soil data at these scales. Table 2 summarizes

the resolution and extent of the three different scales. The model was first used at Wind

Cave National Park, South Dakota, to study the potential impacts of climate change on

the forest-grassland ecotone in the park. It was then run on a global scale in an international comparison effort. Finally, it was run over the conterminous United States for

VEMAP. Figure 3 shows the location of the Wind Cave study area. Input data for each

of these runs are discussed in the following section.

2.2 Spatial Scales

5

Figure 3—Location of the study site at Wind Cave National Park, South Dakota.

Table 2-Resolution and extent of the 3 different spatial scales

Item Wind Cave United States Global

No. of rows,

 columns 50, 100 48, 115 56, 96

Resolution 50 meters 0.5 lat. x long. 2.75 x 3.5 lat. x long.

Number of cells 5,000 3,261 1,631

Headquarters Area

Wind Cave

National Park

Study Area

Custer

Rapid City

Hot Springs

South Dakota
2.3 Input Data MC1 requires a gridded, monthly climatic dataset of precipitation (millimeters), mean

minimum and maximum temperature (°C), vapor pressure (Pascals), wind speed (ms-1),

and solar radiation (K J m-2 day-1). It also requires gridded maps of soil texture (percentage of sand, silt, and clay), rock fraction (percentage), and depth to bedrock

(millimeters). Methods used to develop these datasets incorporated the effects of

elevation and topographic exposure on local climate and the relations among landform

type, soil depth, and texture.

2.3.1 Climate—Detailed information on the climatic datasets used for each of the three

spatial scales is presented in table 3.

Preparation of climatic input data for the Wind Cave study area is discussed in detail in

Daly and others (2000) and Bachelet and others (2001).

Historical climatic data and future climate change scenarios for the conterminous United

States were produced by the VEMAP Data Analysis Group for the VEMAP project. An

overview of the dataset can be found in http://www.cgd.ucar.edu/vemap and in

Kittel and others (1995, 1997).

The global climate dataset was provided by Wolfgang Cramer from the Potsdam Institute

for Climate Impact Research in Potsdam, Germany. This database was developed from

the Leemans and Cramer database (Leemans and Cramer 1991) and contains monthly

averages of mean temperature, temperature range, precipitation, rain days, and

sunshine hours for the land surface of Earth. More detail concerning this database can

be found in http://www.pik-potsdam.de/~cramer/climate.htm. Wind and

Table 3—Information on the climate datasets and atmospheric CO2

 concentrations

used at each of the 3 spatial scales

6

 Item Wind Cave United States Global

Equilibrium model Long-term average 1895-1994 average Long–term average

[CO2

]

a = 294.8 ppm [CO2

] = 288.75 ppm

Transient mode:

 Spinupb 100 years 1895-1993 8 x (1931-1960)

detrended until NEP = 0

[CO2] = 294.8 ppm constant [CO2] = 288.75 ppm

 Historical 1895-1994 1895-1993 1861-1995

variable [CO2

] variable [CO2]

 Future Hadley 1995-2094 HADCM2SUL HADCM2SUL

(uses 200 years 1994-2099 1861-2199

for spinup) variable [CO2

] variable [CO2]

CGCM1

1994-2100

variable [CO2

]

a [CO2] = atmospheric carbon dioxide concentration. b Spinup = time it takes for the model to reach reasonable fire frequencies in transient mode.
vapor pressure datasets were created by Ray Drapek from 0.5 global data (from

International Institute for Applied Systems Analysis data, http//www.iiasa.ac.at)

and were rescaled for the global grid.

In addition to climatic data, the fire module requires the vegetation class provided by the

biogeographic rule base, and the aboveground live and dead biomass and soil moisture

provided by the biogeochemical module. Fuel moisture and fire behavior are modeled at

a daily time step in the fire module, so the monthly values of the climatic data are used

to generate pseudo-daily data. For temperature and relative humidity, daily data are

generated by simple linear interpolation between monthly values. For precipitation, the

monthly totals are divided by the number of rainfall events in each month, and these

pseudo-daily values are randomly assigned to days within each month. The number of

rainfall events in each month is estimated using a regression function derived from weather

station data archived by the National Climate Data Center (WeatherDisc Associates 1995).

2.3.2 Soil—Preparation of soils input data for the Wind Cave study area is discussed in

greater detail in Daly and others (2000) and Bachelet and others (2001).

Soils data at the national scale came from national soil geographic (NATSGO) datasets

(Kern 1995), which are composed of information collected every 5 years as part of the

National Resources Inventory conducted by USDA Natural Resource Conservation

Service (NRCS) (Soil Conservation Service 1987). A review of these data can be found

in Bachelet and others (1998). The data were later modified for VEMAP (Kittel and others

1995). For global simulations, soil data were obtained from the soil map of the world

(Food and Agricultural Organization 1974-79).

The biogeographic module predicts spatial and temporal shifts in the relative dominance

of individual lifeforms and changes in vegetation classification. The method used was

originally derived from the physiologically based biogeographic rules defined in the

MAPSS model (Neilson 1995). However, the biogeography module in MC1 has evolved

to more explicitly represent lifeform mixtures along dynamic environmental gradients

using site production information. The heart of the biogeographic module is a lifeform

interpreter (figs. 4 and 5), which delineates continuous gradients of deciduous-evergreen

trees and C3-C4 grass lifeform mixtures as a function of climate. Information from the

lifeform interpreter (1) forms the basis for categorizing model output vegetation into 21

classes as defined by the VEMAP (VEMAP Members 1995) and (2) allows for dynamic

parameterization of the biogeochemistry module (fig. 5). The lifeform interpreter and

vegetation classification rule base are presented in this section. Dynamic parameterization

is discussed in section 4.2.

3.1.1 Delayed response—The lifeform interpreter distinguishes four tree lifeforms

(deciduous needleleaf [DN], evergreen needleleaf [EN], deciduous broadleaf [DB], and

evergreen broadleaf [EB]) and two grass lifeforms (C3 and C4) as a function of climate.

Shrubs are not explicitly simulated but are considered short-stature trees. Monthly

temperature and precipitation data drive the annual lifeform simulations, which are made

on an annual time step. Climatic data are smoothed before they are used by the

interpreter to reduce interannual variability in lifeform changes and to reflect the

3. Model Description

3.1 Biogeography

7
Figure 4—Determination of tree lifeform composition. Trees are assumed to be

needleleaved when the minimum (coldest month) monthly mean temperature (MMT)

drops below -15 °C, which generally corresponds to daily temperatures at which most

temperate broadleaf trees exhibit supercooled intracellular freezing (-41 °C to -47 °C) as

calculated by Prentice et al. (1992) and used by Lenihan and Neilson (1993) and Neilson

(1995). Within the needleleaved zone, the relative dominance of DN vs EN lifeforms is

determined by the value of a continentality index defined as the difference between the

minimum and maximum MMT. When the minimum MMT is above 18 °C, trees are

assumed to be EB. This corresponds to an area of no seasonal frost, following Neilson

(1995). Between the minimum MMTs of -15 °C and 18 °C, the relative mixture of the EN,

DB, and EB lifeforms is determined by both the growing season precipitation (GSP) and

the minimum MMT. The GSP is calculated as the mean monthly precipitation for the three

warmest months of the year (month of warmest temperature of the year, averaged with

the month before and the month after). This index was originally used by Lenihan and

Neilson (1993) and Neilson (1995) to separate broadleaf forests from needleleaf forests,

the latter being favored by dry summers. Above a GSP threshold of 95 mm (e.g., Eastern

United States) the relative mixture of lifeforms is defined by the value of a “wet” minimum

MMT index. A pure DB lifeform occurs at a minimum MMT of 1.5 °C. A mixture of

lifeforms is linearly interpolated at minimum MMTs between 1.5 °C and -15 °C (EN-DB

mix) and between 1.5 °C and 18 °C (DB-EB mix). When the GSP is below 75 mm (e.g,

Western United States), there is no transition through DB lifeforms and the relative

mixture of the EN and EB lifeforms is interpolated along a “dry” minimum MMT gradient.

When the GSP falls between 75 and 95 mm, a linearly interpolated mixture of both wet

and dry lifeform gradients is calculated.

physiological lags inherent to plant population dynamics. Each monthly temperature and

precipitation value is smoothed by calculating a running mean of an exponential response

curve of the form:

 yt = xt (e-1 τ) + y t-1 [1 - ( e-1 τ)] , (1)

where xt and yt are the current month’s unsmoothed and smoothed climate data values,

respectively, yt-1 is that month’s smoothed value calculated for the previous year, and τ

8
is the smoothing period in years. With each simulated fire event, τ is reset to zero, then

raised incrementally each year (equally for all lifeforms) until the next fire event occurs.

This procedure mimics the sensitivity of lifeform establishment to climate soon after

disturbance and the increase in inertia of lifeform composition with greater stand

maturity.

3.1.2 Lifeform interpreter—Tree lifeforms are distinguished by leaf phenology

(evergreen versus deciduous) and leaf shape (needleleaf versus broadleaf) (fig. 4). An

environmental gradient algorithm was developed to predict the relative dominance of tree

lifeforms and is based on the observed distribution of lifeform mixtures along temperature

and precipitation gradients across North America.

Figure 5—Schematic of the biogeographic module. Monthly temperature and

precipitation data drive the lifeform simulations, which are made on an annual time

step. The climatic data are smoothed before they are used by the interpreter to

reduce interannual variability in lifeform changes and reflect the lags inherent to

plant population dynamics. Thresholds of maximum monthly tree and grass LAI are

used to distinguish forest, savanna, shrubland, and grassland vegetation classes.

The LAI is calculated from leaf carbon in the biogeochemistry module using the

standard CENTURY equations. Once the vegetation has been assigned an LAIbased class, specific classes are determined by the lifeform mixes calculated by

the lifeform interpreter and other rules. The fire module calculates changes to

carbon and nutrient pools. Fire-caused changes in carbon affect the LAI values,

which are passed to the biogeography module to help determine vegetation type.

The LAI values are smoothed using the same function used for smoothing the

climatic values. The occurrence of a fire resets the smoothing period to zero, which

allows the biogeography rules to predict an open canopy vegetation type for a few

years after a simulated fire.

9
At high latitudes, heat-limited lifeforms are determined through a total annual growingdegree-day (GDD) index base (base 0 °C). Thresholds are GDD < 50 for permanent ice,

50 < GDD < 735 for tundra, and 735 < GDD < 1330 for taiga.

Trees are assumed to be needleleaved when the minimum (coldest month) monthly

mean temperature (MMT) drops below -15 oC (fig. 4). This generally corresponds to daily

temperatures at which most temperate broadleaf trees exhibit supercooled intracellular

freezing (-47 oC to -41 oC) as calculated by Prentice and others (1992) and used by

Lenihan and Neilson (1993) and Neilson (1995) (table 4). Within the needleleaved zone,

the relative dominance of the deciduous versus evergreen needleleaf lifeforms is

determined by the value of a “continentality” index (CI), defined as the difference

between the minimum and maximum MMT (table 4).

When the minimum MMT is above 18 °C, trees are assumed to be broadleaf evergreen.

This corresponds to an area of no seasonal frost, which follows the logic of Neilson

(1995) for identifying a broadleaf evergreen zone. Between the minimum MMT of -15 and

18 °C, the relative mixture of the EN, DB, and EB lifeforms is determined by both the

growing season precipitation (GSP) and the minimum MMT (fig. 4, table 4). The GSP is

calculated as the mean monthly precipitation for the three warmest months of the year

(month of warmest temperature of the year, averaged with the month before and the

month after). This index was originally used by Lenihan and Neilson (1993) and Neilson

(1995) to separate broadleaf forests from needleleaf forests, which grow better in dry

summers. Above a GSP threshold of 55 millimeters (such as in the Eastern United

States), the relative mixture of the lifeforms is defined by the value of a “wet” minimum

MMT index. The EN lifeforms dominate below a minimum MMT of -15 °C, DB lifeforms

dominate around 1.5 °C, and EB lifeforms dominate above 18 °C. A mixture of lifeforms

is linearly interpolated at minimum MMTs between -15 and 1.5 °C (EN-DB mix) and

between 1.5 and 18 °C (DB-EB mix) (table 4). When the GSP is below 55 mm (such

as in the Western United States), there is no transition through DB lifeforms, and the

relative mixture of the EN and EB lifeforms is interpolated along a “dry” minimum MMT

gradient (table 4). When the GSP falls to between 50 and 55 millimeters, a linearly

interpolated mixture of both wet and dry lifeform gradients is calculated.

10

Table 4—Lifeform classes used in the biogeographical modulea

Item Lifeform mixture Threshold variable Value

Boreal gradient, trees DN-DN/EN Max. - Min. MMTb (°C) 60

DN/EN-EN Max. - Min. MMT (°C) 55

Temperate and wet gradient,

 trees EN-EN/DB Minimum MMT (°C) -15

Pure DB Minimum MMT (°C) 1.5

DB/EB- EB Minimum MMT (°C) 18

Temperate and dry gradient,

 trees EN - EN/EB Minimum MMT (°C) 1.5

EN/EB - EB Minimum MMT (°C) 18

C3-C4 gradient, grasses C3 - C3/C4 Percentage C3 dominance 66

C3/C4 - C4 Percentage C3 dominance 33

a DN = deciduous needleleaf, EN = evergreen needleleaf, DB = deciduous broadleaf,

EB = evergreen broadleaf.

b MMT = mean monthly temperature.
The relative dominance of C3 and C4 grasses is predicted by using functions extracted

from CENTURY (Parton and others 1987, 1994) that simulate the potential production of

pure C3 and pure C4 grass stands from July soil temperature. Soil temperature is estimated from a running average of daily air temperatures interpolated from the monthly

mean temperature values. The ratio of C3 potential production to the sum of C3 and C4

potential production (calculated independently of each other) for the site is used to

determine the relative dominance of C3 grasses (table 4).

3.1.3 Vegetation classification rule base—MC1 uses a rule-based approach to

simulate the distribution of the 21 different vegetation classes (table 5) defined by

VEMAP (VEMAP Members 1995). Thresholds of maximum monthly tree and grass LAI

(one sided) are used to distinguish the forest, savanna, shrubland, and grassland

classes (fig. 6). LAI is calculated from leaf carbon in the biogeochemical module by

using the standard CENTURY equations (Parton and others 1987, 1994). Vegetation is

considered forest at tree LAI > 3.75 and savanna at tree LAI of 2 to 3.75. At tree LAI of 1

to 2, vegetation is classified as shrubland if grass LAI < 1, and as grassland if grass LAI

> 1 (fig. 6). Vegetation is considered grassland if tree LAI < 1. Shrubs are not explicitly

simulated but are considered short-stature trees.

Once the vegetation has been assigned an LAI-based class, specific classes are

determined by the lifeform mixes calculated from the lifeform interpreter and other rules.

For example, a savanna with an EN lifeform is classified as a temperate coniferous

savanna (TCS) (fig. 6). A continentality index threshold of 15 is used to distinguish

maritime temperate coniferous forest (MTCF) from continental temperate coniferous

forest (CTCF), when the lifeform mixture is EN, DN, or an EN-DN mixture and the

11

Table 5—VEMAP vegetation classes in MC1

Number Class

1 Tundra

2 Boreal coniferous forest

3 Maritime temperate coniferous forest

4 Continental temperate coniferous forest

5 Cool temperate mixed forest

6 Warm temperate mixed forest

7 Temperate deciduous forest

8 Tropical deciduous forest

9 Tropical evergreen forest

10 Temperate mixed xeromorphic woodland

11 Temperate conifer xeromorphic woodland

12 Tropical thorn woodland

13 Temperate subtropical deciduous savanna

14 Warm temperate subtropical mixed savanna

15 Temperate conifer savanna

16 Tropical deciduous savanna

17 C3 grasslands

18 C4 grasslands

19 Mediterranean shrubland

20 Temperate arid shrubland

21 Subtropical arid shrubland

22 Taiga (not VEMAP but MC1 specific)

23 Boreal larch forest (not VEMAP but MC1 specific)
minimum MMT > 16 °C (fig. 6). A minimum MMT < 16 °C puts the forest into the boreal

coniferous forest (BCF) class.

The percentage of C3 grasses determines several vegetation classes. Within the

shrubland LAI class, the vegetation is classed as temperate arid shrubland (TAS) if the

relative composition of C3 grasses is greater than 55 percent. A relative C3 composition

of 33 to 55 percent is classified as temperate conifer zeromorphic woodland (TCXW), and

< 33 percent C3 becomes subtropical arid shrubland (SAS). Within the grassland LAI

class, a relative composition of C3 grasses > 55 percent is classed as C3 grasslands

(C3G); 55 percent is classified as C4 grasslands (C4G).

In VEMAP phase 2, vegetation classes were aggregated to facilitate the comparison

between model output. Table 6 summarizes the criteria used to define the aggregated

classes.

Figure 6—Schematic of the vegetation classification rule base. Thresholds of

maximum monthly tree LAI separate shrublands (1 < LAI < 2), savannas (2 < LAI

< 3.75), and forests (LAI > 3.75). Climatic thresholds are used to determine the

lifeform associated with each LAI range. Below a tree LAI of 1, the vegetation is

restricted to grasslands. Tmin = minimum MMT; CI = continentality index (difference between the minimum and maximum MMT); E = evergreen; D = deciduous;

N = needleleaf; B = broadleaf; LAI = leaf area index; % C3 = relative dominance of

C3 grasses; C4G = C4 grasslands; C3G = C3 grasslands; TCXW = temperate

conifer xeromorphic woodland; SAS = subtropical arid shrubland; TAS = temperate

arid shrubland; CTMF = cool temperate mixed forest; TDF = temperate deciduous

forest; WTSMF = warm temperate subtropical mixed forest; TEF = tropical

evergreen forest; BCF = boreal coniferous forest; MTCF = maritime coniferous

forest; CTCF = continental temperate coniferous forest; TCS = temperate conifer

savanna; TSDS = temperate subtropical deciduous savanna; WTSMS = warm

temperate subtropical mixed savanna; TMXW = temperate mixed xeromorphic

woodland; and TTW = tropical thorn woodland.

12
The biogeochemical module consists of a modified version of CENTURY (Parton and

others 1987). It simulates monthly carbon and nutrient dynamics for a combined grass

and tree ecosystem (CENTURY’s savanna mode only). The model includes live shoots

(leaves, branches, stems), roots (fine and coarse), and standing dead material (fig. 7). It

includes perhaps the most detailed representation of soil processes among current

regional and global biogeochemical models and has been tested extensively across the

globe for terrestrial systems (Parton and others 1994). Modifications made to CENTURY

to build MC1 include a Beer’s Law tree and grass shading algorithm, changes to tree and

grass vertical root distributions, and the generalization of input parameter sets. These

changes are discussed in greater detail in section 3.2.5.

3.2.1 Net primary production—Tree production and grass production are functions of a

maximum potential rate modified by scalars representing the effect of soil temperature

and soil moisture on growth. For forests, total production, Pt

, is calculated as:

Pt = Ptg * kt * km* kl , (2)

where Ptg is gross tree production (lifeform specific input), kt 

and km are coefficients that

represent the effect of soil temperature and moisture, respectively, on growth, and kl is a

coefficient relating aboveground wood production to leaf area index.

For grasses, total production Pg is calculated as:

Pg = Pgg * kt * km * kb * ks , (3)

where Pgg is gross grass production (lifeform specific input), kb

 is a coefficient that

represents the effect of the live-to-dead biomass ratio on growth, and ks is a coefficient

that represents the effect of shading by trees. We have replaced CENTURY’s original

light competition function by the Beer’s Law formulation in the calculation of ks (Jarvis

and Leverenz 1983).

VEMAP aggregated vegetation types Criteria for defininga

Coniferous forests Tree types 1 (EN), 7 (DN) and 8 (DN-EN)

Winter deciduous forests Tree type 3 (DB)

Mixed conifer-broadleaved forests Tree types (EN-DB, EB, DB-EB and EN-DB)

Broadleaved evergreen drought-deciduous

 forests Zone 3 (tropical)

Savannas and woodlands Tree LAI >= savanna threshold (3.75)

Grasslands and shrublands

Deserts Live vegetation C < 600 g

Table 6—Aggregated VEMAP phase 2 vegetation classes with criteria for defining

a EN = evergreen needleleaf, DN = deciduous needleleaf, DB = deciduous

broadleaf, EB = evergreen broadleaf.

3.2 Biogeochemistry

13
The model also includes the effects of documented changes in atmospheric CO2

(Metherall and others 1993: 3-38). For both trees and grasses, total potential production

is enhanced by a coefficient (kCO2) of atmospheric CO2 concentration, which equals 1.25

when CO2 concentration reaches 700 ppm. A similar coefficient used on potential

transpiration rate equals 0.75 when CO2 concentration reaches 700 ppm. The effect of

elevated CO2 on C:N ratios is similarly modeled with a kCO2 =1.25. We assume a linear

relation between CO2 concentration and its effect on plants.

The production coefficient for soil moisture, km is defined as:

km = (Ms + Mp) / PET , (4)

where Ms

 is the water available in the soil profile, Mp is monthly precipitation, and PET is

potential evapotranspiration.

The number of soil layers (nlaypg) assumed to contain the water necessary for plant

growth (Ms

) differs among vegetation types (fig. 8). The total number of soil layers

Figure 7—Schematic of the biogeochemical module for a woody lifeform (adapted

from Gilmanov and others 1997). Potential plant production is calculated for each

lifeform as a function of temperature (T), soil water (P), and nitrogen availability.

Live biomass includes leaves, branches (fine and trunk), and roots (fine and

coarse). Grasses are represented only by leaf and root carbon pools. Aboveground

and belowground plant parts become senescent as a function of time, drought, and

cold stress. Dead leaves and branches accumulate in a surface litter pool, where

they are transformed into more slowly decomposing organic carbon. Dead roots

accumulate in a belowground litter pool that constitutes the active soil organic

matter pool. Decomposition transforms active soil carbon into slow and finally

passive carbon material. The various soil organic matter pools differ by their

turnover times.

14

Leaves

Fine Roots

Branches

Large Wood

Large Roots

Dead

Plant

Material

Structural

Metabolic

M,S

DEFAC

Nitrogen

DEFAC

P,T

Potential

Plant

Production

Soil Moisture

+

Temperature

Soil

Organic

Matter

Active

(.5 to 1y)

Slow

(10 - 50y)

Passive

(1000 - 5000y)

T = Temperature

P = Precipitation

M = Moisture stress

S = Plant senesence

DEFAC = Abiotic decomposition rate

Information flow

Mass flows
(nlayer) differs as a function of soil depth and is one of the site-specific model inputs.

Available soil water is accumulated in the surface soil layers (nlaypg) for grasses and in

the entire soil profile (nlayer) for trees (fig. 8). The difference in available soil water

between grasses and trees corresponds to deep soil water reserves assumed to be

accessible only to deep tree roots. This is a modification of the CENTURY configuration,

Figure 8—Hydrologic structure in the biogeochemistry module. Rainfall is intercepted

by the lifeform canopy. Interception and bare soil evaporation are calculated as a

function of leaf biomass, litter, and standing dead material. Runoff is calculated as a

fraction of precipitation. Water infiltrates the soil by saturated flow only. Soil depth

(nlayer) is an input to the model. The rooted soil layers are identified as nlaypg, and

their depth depends on the vegetation type. Transpiration is calculated for each

rooted soil layer as a function of potential evapotranspiration, leaf biomass, and

rainfall. Stormflow is calculated as 60 percent of the amount of water present in the

bottom soil layer. An extra compartment holds the water that does not leave by

stormflow or transpiration and is identified as baseflow.

15

tr1

tr2

tr3

tr10

Transpiration

Precipitation

Swowmelt

Evaporation

rleavc aglivc

Interception Saturated Flow

avh2o(1)

avh2o(2)

1

2

3

4

5

6 nlaypg

7

8

9

10 nlayer

Runoff

Base Flow

Storm Flow
which limited tree water access to the surface soil layers only. The sensitivity of the

model to a change in the accessibility of soil moisture was tested by varying the soil

layers available to trees and grasses for water uptake.

Finally, production is modified by yet another scalar that is a function of leaf N

concentration. In MC1, we assumed no N limitation, such that the calculated N demand

is always met (via the symbiotic N fixation flux). Atmospheric N input is a function of

annual precipitation. Abiotic soil N fixation is a function of actual evapotranspiration and

volatilization is a function of gross mineralization. The leaching rate is a constant read

from the xfix.100 files (see section 4.3.1.).

Further details, such as the shape of the k coefficients, can be found in the CENTURY

documentation (Metherall and others 1993).

3.2.2 Decomposition—Shoot and root lifeform-specific maximum death rates are

modified by functions of available soil water in the whole profile and the plant root zone,

respectively. During senescence, shoot death rate is a fixed fraction of live biomass.

Standing dead material is transferred to surface litter at a lifeform-specific fall rate. The

structural fraction of surface litter and that of belowground litter are further separated

into lignin and nonlignin (cellulose, nitrogen-rich compounds) compartments. Lignin-rich

compounds decompose directly into the slow organic matter pool, and cellulose-rich

compounds migrate through the surface or soil microbe (active soil organic matter pool)

compartments first. Soil organic matter is divided into three major components: active,

slow, and passive (fig. 7).

Active soil organic matter includes live soil microbes and their products and is assumed

to turn over in a few months or years. The slow pool includes resistant plant material

such as lignin and soil-stabilized plant and microbial material passed from the active

pool. It is assumed to have a turnover time of 10 to 50 years. Passive soil C includes

chemically and physically stabilized soil organic matter highly resistant to decomposition

and with a turnover time of 1,000 to 5,000 years. Soil organic matter pools have C-to-N

ratios that are functions of the mineral N pools. Soil texture affects the turnover rate of

the active pool and the size of the flows from either active or slow pools entering the

passive compartment. Decomposition of plant residues and soil organic matter is

assumed to be performed by the microbiological flora and thus includes a calculation of

the associated microbial respiration. Each soil C pool is characterized by a different

maximum decomposition rate. That potential rate is then reduced by multiplicative

functions of soil moisture (equation 4) and soil temperature.

3.2.3 Hydrology—Potential evapotranspiration (PET) is calculated as a function of

average monthly maximum and minimum temperatures from the equations of Linacre

(1977). Bare soil water evaporation and interception by the canopy are functions of

aboveground biomass, rainfall, and PET. Surface runoff is calculated as 55 percent of

monthly rainfall when rainfall exceeds 50 millimeters and 0 when rainfall falls below 50

millimeters. This is based on empirical analyses in Queensland, Australia (Probert and

others 1995).

Canopy interception, bare soil water evaporation, and surface runoff are subtracted from

monthly precipitation and snowmelt before being added to the top soil layer. Water is

16
then distributed to the different layers by draining water above field capacity from the top

layer to the next layer (fig. 8). Unsaturated flow is not simulated in version 1. Soil layers

are 0.15 meter thick to a depth of 0.6 meter and 0.3 meter thick below it. The number of

soil layers does not exceed 10. Field capacity and wilting point for the different soil

layers are calculated as a function of bulk density, soil texture (inputs to the model), and

organic matter content from Gupta and Larson’s (1979) equations. Water leaching below

this soil layer is accumulated and lost to base flow.

Potential transpiration (PT) is calculated last as a function of live leaf biomass, PET,

and atmospheric CO2 concentration. Surface evaporation is later subtracted from PT.

 Tr = PT * (Ms[layer] * TDDF) / Ms , (5)

where Tr is actual transpiration per layer, Ms[layer] is water available per soil layer, and

TDDF is the transpiration depth distribution factor (variable name=awtl).

The sum of water losses to the atmosphere (evaporation, interception, transpiration)

does not exceed the PET rate.

3.2.4 Competition for resources—Grasses and trees compete for light, water, and

nitrogen. When tree biomass becomes large because of the abundance of available soil

water (for example, high rainfall period with low evaporation potential), the model

reduces grass growth by assuming a shading effect, which represents the competition

for light between the tree canopy and the grass understory. In the hydrology submodel,

the amount of water transpired by plants is calculated as a function of the total plant

biomass. There is no lifeform-specific calculation of transpiration. Thus, competition for

water between trees and grasses occurs through the indirect effect of soil water content

on productivity. The production modifier increases for a given lifeform if deep soil water

resources are available and if the roots of that lifeform are present at depth. If deep soil

water resources are not available (dry soil profile) or both lifeforms are shallowly rooted,

the growth modifier of both lifeforms is identical and proportional to the soil water

content.

3.2.5 Changes to CENTURY code—Several subroutines not found in CENTURY

(Parton and others 1987, 1994) were added to the biogeochemical module. Table 7 lists

the new routines and descriptions of the operations they perform.

Some CENTURY subroutines were modified to create the MC1 biogeochemical module.

Major modifications (detailed in table 8) include the formulation of drought deciduousness,

the modification of the water effect on production (which separates trees from grasses),

the equilibration of soil C at the start of the transient mode, the modification of fire

effects with the fire module, the removal of N limitation, and the addition of Beer’s Law.

17
Subroutines Description

cen_init_climate Changes the units of precipitation from millimeter to centimeter; associates

new names with temperature

cen_init_lat Takes the absolute value of latitude

cen_init_soils Transforms sand and clay content into percentages; depth changed from

millimeter to centimeter; nlayer is calculated here; calculates adep (soil

depth of each layer modified by rock fragments)

cen_step Retrieves climate and soils data from MAPSS; updates schedule file;

calculates biogeography indices; includes what is left of readblk; updates

fire index; year’s end - changes in vegetation type, determines whether

fires should happen

cropmix Modifies CENTURY lifeform-dependent parameter values based on

C3/C4 index

eq_test Checks when som2c (the slow soil organic matter pool) reaches equilibrium

lacalc1 Calculates LAI as a function of leaves; original lacalc subroutine split into

lacalc1 and lacalc2

lacalc2 Calculates LAI as a function of wood; also averages with lacalc1 LAI

scale Finds an average between lifeform-dependent parameters

scale4 Finds an average between lifeform-dependent parameters (with 4 values)

stand_step Standard CENTURY new file name

statein Routine disburses CENTURY state variables into proper global variables

stateinit Initializes all state variables to 0 and then calls statein()

stateout Collects CENTURY state variables for pass to MAPSS

store_event Stores scheduled events for use during 1-step operation

treemix Calculates evergreen/deciduous and needleleaf/broadleaf indices and

modifies CENTURY lifeform-dependent parameters

update_event Overwrites existing events or adds new ones

update_sched Moves this year’s scheduled events from storage arrays into the working

arrays

varsin Distributes CENTURY output variables after pass from MAPSS

varsinit Initializes CENTURY output variables, call varsin() to distribute 0s to global

output variables

varsout Collects CENTURY output variables for pass to MAPSS

veg_change Subroutine called on January of 1st year or December of fire years

vetocen Translates VEMAP vegetation classes into MAPSS vegetation classes

vetofix Translates VEMAP vegetation classes into CENTURY fixed file names

Table 7—New subroutines in the biogeochemical module (not found in CENTURY)

Other modifications were minor adjustments to prevent mathematical errors that the

compiler could not handle (such as negative C or N flows). Some modifications were

required because MC1 is also run in transient mode (i.e., CO2 is read only in transient;

original site-specific parameters are not reread in transient mode). Some variable names

were modified to adapt the fire module variables to CENTURY variables. Input and

output (I/O) were required in subroutines that read in climate and soils data; these data

first are read on the biogeography side in MC1 and then are used to create indices

passed to the biogeochemical module. Finally, other I/O adjustments were necessary to

handle the biogeographic indices now used to modify parameters that were site specific

in CENTURY. Table 9 lists files that had minor modifications.

18
The fire disturbance module (Lenihan and others 1998) simulates fire occurrence,

behavior, and effects (fig. 9). The module dynamically simulates fuel moisture as a

function of the temperature, relative humidity, and precipitation data. Carbon stocks in

the aboveground pools, supplied by the biogeochemical module, are used to dynamically

simulate fuel loading, with the aid of allometric functions keyed to the current mixture of

lifeforms predicted by the biogeographic module. The simulated fuel characteristics and

climatic data are used to predict the behavior of surface fire, crown fire, and fire effects,

the last including vegetation mortality, fuel consumption, nutrient loss, and fire emissions.

Fire occurrence is simulated from thresholds of drought and the rate of fire spread. Fire

occurrence influences the determination of the lifeform mixture by the biogeographic

module, and fire behavior and effects impact biomass and nutrient levels in the

biogeochemical module.

Subroutine Modification description

eachyr Saturates the soil with N by using N-deposition (option 2)

extend Creates new MC1 variables

frem Fire module adaptation (defines fraction of trees removed by fire)

grem Fire module adaptation (defines fraction of grasses removed by fire)

nutrlm Saturates the soil with N using N-fixation (option 1)

potcrp Uses Beer’s Law to calculate shading modifier (sliding extinction coefficient k)

potcrp Modifies the original curve for low tree LAI (savannas and shrublands);

used to calculate the effect of water

potcrp, potfor Zeros out production below temperature threshold; Tests sensitivity of the

 model to water availability between grasses and trees

potfor Splits lacalc into lacalc1 and lacalc2, uses the mix index calculated on

biogeographic side

pprdwc Calibrates entire curve differently for trees vs. grasses to separate

availability of water to the two lifeforms

stand_step Equilibrium threshold when slow pool organic matter reaches equilibrium

treein New parameter file structure

treein Adds call to mix(), which determines if tree type should change to a mixed

type

trees Changes function (similar to LAI calculation in lacalc1)

wdeath Phenology: deciduous tree leaf drop, no longer includes day length, modifies

phenology for drought deciduousness, occurs only in tropical zones

Table 8—Major revisions to CENTURY subroutines

3.3 Fire

Modification Subtroutines affected

Transient vs. equilibrium cen_init, detiv, readblk

Fire variable names potcrop, potfor, wdeath

Climate input/output cen_init, detiv

Soils input/output sitein, cen_init, fixin

Biogeography input/output cen_init

Miscellaneous input/output cen_init, detiv, readblk, schedl, treein

Math errors cutrtn, cycle, dedrem, dshoot, grem, growth, h2olos, killrt, leach,

livrem, potcrp, potfor, savarp, simsom, wdeath

Table 9—Minor modifications to CENTURY subroutines

19
Figure 9—Flow diagram of the fire module. MCFIRE uses climatic (temperature,

precipitation, relative humidity), biogeographic (vegetation classes) and biogeochemical (carbon pools and soil moisture) inputs to calculate fuel loading and fuel

moisture. A set of lifeform-specific allometric equations is used to estimate average

stand dimensions (i.e., height and bole diameter) from aboveground biomass. The

stand dimensions are used in another set of allometric functions to allocate biomass

into fuel load categories. Live fuel moisture is estimated from an index of plant water

stress (Howard 1978). The index is a function of the percentage of soil moisture

simulated by the hydrology algorithms in the biogeochemical module. The moisture

contents of the four dead fuel classes are estimated by using the time-lag moisture

calculations developed by Fosberg and others (Fosberg 1971, Fosberg and

Deeming 1971, Fosberg and others 1981). Crown and surface fire behavior is

simulated in MCFIRE as a function of fuel load, fuel moisture, and stand structure.

Indices of fire behavior (e.g., fireline intensity, rate of spread, and the residence time

of flaming and smoldering combustion) are used in the simulation of fire effects in

terms of plant mortality and fuel consumption.

3.3.1 Fuel moisture and loading—Calculations of percentage of moisture are made for

tree leaves and fine branches, grass leaves, and four size classes of dead fuel (e.g., 1-,

10-, 100-, and 1,000-hour fuels) (fig. 10). The moisture contents of the four classes of

dead fuels are estimated from the time-lag moisture calculations developed by Fosberg

and others (Fosberg 1972, Fosberg and Deeming 1971, Fosberg and others 1981). For

example, a 100-hour dead fuel category corresponds to a particular size class of wood

(diameter between 3 and 10 centimeters) that takes 100 hours to come two-thirds of the

way toward equilibrium with standard conditions of ambient moisture. Live fuel moisture

is estimated from an index of plant water stress (Howard 1978). The index is a function

of the percentage of soil moisture simulated by the hydrology in the biogeochemical

module.

The fire module estimates loading in the different fuel classes from C in the live and

dead aboveground pools simulated by the biogeochemical module. The live grass shoot

and live tree leaf pools are summed to estimate the live fine fuel class load, and the

standing dead grass shoot and aboveground tree litter pools are summed to estimate

the dead 1-hour fuel class load (fig. 11). A set of lifeform-specific allometric equations is

used to estimate average stand dimensions (height and bole diameter) from aboveground

biomass (fig. 11). The stand dimensions are used in another set of allometric functions

20
to allocate the woody biomass into three different structural components (fine branches,

medium branches, and large branches plus boles) that correspond to the three live fuel

classes (the 10-, 100-, and 1,000-hour live fuels, respectively) (Means and others 1994,

Stanek and State 1978). These three live components, together with live biomass turnover

rates and dead biomass decomposition rates from the biogeochemical module, are used

to partition the two dead wood C pools into the three dead fuel classes (the 10-, 100-,

and 1,000-hour dead fuels).

3.3.2 Fire occurrence—For fire to occur in the model, three different conditions must be

met: (1) fuels must be exposed to extended drought, (2) fine dead fuels must be highly

flammable, and (3) fire spread must reach a critical rate. Our intent is not to simulate

every fire that potentially could occur on a landscape, but rather to simulate only the

more extensive fires with more significant effects on the vegetation. The moisture

Figure 10—Flow diagram for simulation of fuel loading. MCFIRE estimates the loading

in the different fuel classes from carbon in the live and dead aboveground pools

simulated by the biogeochemical module. The live grass shoot and live tree leaf

pools are summed to estimate the live fine fuel class load, and the standing dead

grass shoot and aboveground grass and tree leaf litter are summed to estimate the

dead 1-hour fuel class load. A set of lifeform-specific allometric equations is used

to estimate average stand dimensions (i.e., height and bole diameter) from aboveground biomass. The stand dimensions are used in another set of allometric functions

to allocate the woody biomass into three different structural components (i.e., fine

branches, medium branches, and large branches plus boles) (Means and others

1994, Stanek and State 1978). These three live components together with live

biomass turnover rates and dead biomass decomposition rates from the biogeochemical module are used to partition the two dead wood carbon pools into the

three dead fuel classes (i.e., the 10-, 100-, and 1,000-hr dead fuels).

21
content of the dead 1,000-hour fuel class is used as an indicator of extended drought.

Large, dead fuels are very slow to absorb and release moisture (Fosberg and others

1981), so their percentage of moisture content is a good index of extended periods of

either dry or wet conditions.

When the 1,000-hour fuel moisture drops below a calibrated drought threshold, the model

will simulate a fire if there is also a sufficient fine fuel flammability and fire spread. We

used a function from the National Fire Danger Rating system (Bradshaw and others

1984) to calculate a probability of flammability and spread. Flammability is a function of

fine fuel moisture and air temperature. The critical rate of spread is a function of the rate

of spread estimated by the Rothermal algorithm and a minimum rate of spread for

reportable fires (Bradshaw and others 1984). We used a 50-percent threshold value of

the National Fire Danger Rating system function to determine fire occurrence in our

model. Ignition sources (such as lightning) are assumed to be always available in this

version of the model.

If a simulated fire is triggered in a cell, the fire effects are applied uniformly to the entire

cell when the resolution of the climate input is high. In VEMAP where resolution is

coarse (0.5 lat x lon), the model calculates the fraction of the cell that burns. Currently,

there is no provision in the fire module for spatially explicit fire spread within and among

cells.

3.3.3 Fire behavior and effects—Both surface fire behavior and crown fire behavior are

simulated in the fire module (fig. 12) as a function of fuel load, fuel moisture, and stand

structure. Surface fire behavior is modeled with the Rothermel (1972) fire spread

equations as implemented in the National Fire Danger Rating System (Bradshaw and

others 1984) (fig. 13). Crown fire initiation is simulated with van Wagner’s formulation

(1993). Indices of fire behavior (such as fireline intensity, rate of spread, and the

Figure 11—Flow diagram for simulation of stand structure and live fuel classes. A

set of lifeform-specific allometric equations is used to estimate average stand

dimensions (i.e., height and bole diameter) and lifeform specific parameters from

aboveground biomass.

22
residence time of flaming and smoldering combustion) are used to simulate the effects of

fire on plant mortality and fuel consumption.

Crown kill—In a simulated crown fire, postfire mortality of aboveground live biomass is

assumed to be complete. Otherwise, the percentage of mortality for crown biomass is

estimated as a function of crown scorch and cambial kill (Peterson and Ryan 1986).

Crown scorch is a function (Peterson and Ryan 1986) of lethal scorch height (van

Wagner 1973) and the average crown height and length as determined by the allometric

functions of biomass. Cambial kill is a function of (1) the duration of lethal heat and (2)

the bark thickness estimated from average bole diameter (Peterson and Ryan 1986).

Root kill—In a simulated fire, the depth of lethal heating is used to estimate mortality of

live tree roots and is modeled as a function of the duration of flaming and glowing combustion at the surface (Peterson and Ryan 1986). The depth-versus-duration relation was

derived from empirical data presented by Steward and others (1990).

Fuel consumption—The consumption of dead fuel by fire is modeled as a function of

the moisture content of the different dead fuel size classes (Peterson and Ryan 1986).

Emissions from fuel consumption are modeled for CO2, carbon monoxide (CO), methane

(CH4), and particulate matter as the product of the mass of fuel consumed and emission

factors for the different emission gases (Keane and Long 1998).

Figure 12—Flow diagram for simulation of fire effects. If a crown fire is initiated in

the model, postfire mortality of aboveground live biomass is assumed to be

complete. Otherwise, crown mortality is a combined effect of crown scorch and

cambial kill simulated in MCFIRE. Crown scorch is a function (Peterson and Ryan

1986) of lethal scorch height (van Wagner 1973) and the average crown height

and length as determined by the allometric functions of biomass. Cambial kill is a

function of the duration of lethal heat and the bark thickness estimated from

average bole diameter (Peterson and Ryan 1986). The percentage of mortality of

crown biomass is estimated as a function of crown scorch and cambial kill

(Peterson and Ryan 1986). Dead fuel consumption by fire is simulated as a

function of the moisture content of the different dead fuel size classes (Peterson

and Ryan 1986). Emissions from fuel consumption are simulated for CO2, CO, CH4,

and particulate matter as the product of the mass of fuel consumed and emission

factors for the different emission gases (Keane and others 1997).

23
Figure 13—Flow diagram for simulation of fire behavior. Surface and crown fire

behavior are simulated in MCFIRE as a function of fuel load, fuel moisture, and

stand structure. Surface fire behavior is modeled by using the Rothermel (1972)

fire spread equations as implemented in the National Fire Danger Rating System

(Bradshaw and others 1983). Crown fire initiation is simulated by using van

Wagner’s (1993) formulation. Indices of fire behavior (e.g., fireline intensity, rate of

spread, and the residence time of flaming and smoldering combustion) are used in

the simulation of fire effects in terms of plant mortality and fuel consumption.

3.3.4 Fire feedbacks to biogeochemistry—The standard version of CENTURY (Parton

and others 1987) simulates fire as a scheduled series of fires at one of three levels of

intensity. The effects of different levels of fire intensity are defined by parameters that

set fractions of the live and dead C pools consumed by fire, and fractions of N and other

nutrients returned to the soil. In the initialization phase, MC1 uses the same fire schedule

as standard CENTURY. But in transient mode, the values of these parameters in the

biogeochemical module are set equal to the rates of live and dead fuel consumption

simulated by the fire module in MC1 (table 1).

Unlike the standard version of CENTURY, MC1 also simulates live-to-dead C pool

turnover caused by postfire mortality. These equations are included in the biogeochemical

module. In the case of a simulated crown fire, the model assumes that live leaves and

branches are completely consumed. Otherwise, live leaves are consumed and live

branches are transferred to the appropriate dead C pool in proportion to the percentage

of mortality for the crown. The bole biomass of killed trees or shrubs and the biomass of

killed roots also are transferred to dead C pools.

24
3.3.5 Fire feedbacks to biogeography—The fire module calculates changes to C and

nutrient pools. Fire-caused changes in C affect the LAI values, which are passed to the

biogeographic module to help determine vegetation type. The LAI values are smoothed

by using the same function used for smoothing the climatic values (see equation 1). The

occurrence of a fire resets the smoothing period to zero, which allows the biogeographic

rules to predict an open canopy vegetation type for a few years after a simulated fire

(table 1).

Parameter Units Value

WhichSoilsa:

 No soils data 0

 FAO soil data 1

 SCS soil data** 2

Thickness[SURFACE]b millimeters 500.0

Thickness[INTERMEDIATE] millimeters 1000.0

Thickness[DEEP] millimeters 1500.0

Rock_frag_max [SURFACE][INTERMEDIATE][DEEP] fraction 0.50

IgnoreRockFragments:

 Use rock fragment data 0

 Ignore rock fragment data 1

Field_potential pascal -0.033

#Saturated water holding capacities:

 swhc[SURFACE] millimeters 210.0

 swhc[INTERMEDIATE] millimeters 420.0

 swhc[DEEP] millimeters 750.0

Field capacity (fraction of swhc),

whc [SURFACE][INTERMEDIATE][DEEP] pascal 0.6

Matrix potential (MPa), used to derive awc, all layers,

matrix_pot pascal -1.5

Coefficient of soil water potential model:

 a_swp [SURFACE][INTERMEDIATE][DEEP] -61466.84

 c_swp [SURFACE][INTERMEDIATE][DEEP] 4.359

 theta_s [SURFACE][INTERMEDIATE][DEEP] 47.7

Exp of saturated percolation (1), increase to reduce percolation:

 exp_perc[SATURATED][SURFACE] 1.0

 exp_perc[SATURATED][INTERMEDIATE] 2.5

 exp_perc[SATURATED][DEEP] 10.0

Exp of unsaturated percolation (1), increase to reduce percolation:

 exp_perc[UNSATURATED][SURFACE] 2.5

 exp_perc[UNSATURATED][INTERMEDIATE] 3.0

 exp_perc[UNSATURATED][DEEP] 10.0

Saturated drainage:

 KK[SATURATED][SURFACE] fraction 0.5

 KK[SATURATED][INTERMEDIATE][DEEP] fraction 0.8

Unsaturated drainage:

 KK[UNSATURATED][SURFACE] fraction 0.8

 KK[UNSATURATED][INTERMEDIATE] fraction 0.5

 KK[UNSATURATED][DEEP] fraction 0.2

Table 10—Parameters and their values in the MAPSS parameter file, site

25
Parameter Units Value

Texture, text [SURFACE][INTERMEDIATE][DEEP] 1.0

Soil surface condition 1.0

ConductanceEq:

 Old conductance equations 0

 New conductance equations 1

Soil constants:

 SoilsConstraints[SURFACE] 0

 SoilsConstraints[INTERMEDIATE] 1

 SoilsConstraints[DEEP] 2

Variable soil layer constants:

 pp[SURFACE] [INTERMEDIATE] 21.012

 pp[DEEP] 19.012

 qq[SURFACE] [INTERMEDIATE][DEEP] -8.0e-2

 rr[SURFACE][INTERMEDIATE] -3.895

 rr[DEEP] -4.3

 tt[SURFACE] 4.55e-2

 tt[INTERMEDIATE] 3.92e-2

 tt[DEEP] 3.42e-2

 uu[SURFACE] -0.03

 uu[INTERMEDIATE] -0.04

 uu[DEEP] -0.05

 vv[SURFACE][INTERMEDIATE][DEEP] 8.76e-5

a FAO soil data used for global runs; SCS soil data used for US runs. 0 corresponds to sandy

loam conditions.

b [SURFACE] = soil layer 1: upper 0.5 m of soil.

[INTERMEDIATE] = soil layer 2: 0.5-1.5 m depth.

[DEEP] = soil layer 3: below 1.5 m.

26

Table 10—Parameters and their values in the MAPSS parameter file, site
Parameter Value

snow0 temp (°C) above which snow fraction equals 05.0

snow1 temp (°C) below which snow fraction equals 1 -7.0

frost threshold (°C) for beginning, end of growing season 13.0

Tree productivity for growing season used for evergreen/deciduous decision

evergreen_productivity_tree 10.0

evergreen_productivity_shrub 10.0

evergreen_productivity_tree_lad 10.0

evergreen_productivity_shrub_lad 10.0

evergreen_gdd growing degree days for evergreen (frost based) 600.0

evergreen_events 40.0

evergreen_events_grow 26.0

evergreen_events_avg 11.0

evergreen_events_grow_avg (6.0 to 7.5) 7.5

evergreen_events_grow_min 5.00

evergreen_events_grow_std (1.5 to 2.0) 2.00

evergreen_events_grow_cov 0.30

evergreen_events_grow_rng 4.00

evergreen_gdd_north 250.0

evergreen_gdd_south 600.0

evergreen_gdd_ratio 100.0

evergreen_selection1 12

evergreen_selection2 4

Stage 1 options

# 12 => EvergreenDrySummerGddRatio

Stage 2 options

# 4 => EvergreenAetGdd

no_melt temp (C) below which no snow melt occurs -14.0

melt_slope temp coefficient for snow melt rate (mm) 4.0

event_ppt rainfall coefficient for number of events 0.1

event_pet pet threshold (mm/mo) for max_events determination 50.0

max_events[0] maximum number of events at pet <= event_pet 5.0

max_events[1] maximum number of events at pet > event_pet 10.0

interc_lai maximum ppt interception per event (mm) 3.0

LaiUpperBoundsEnergy[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] 6.0

LaiUpperBoundsEnergy[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsEnergy[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 3.50

LaiUpperBoundsEnergy[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 6.0

LaiUpperBoundsEnergy[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsEnergy[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 3.50

LaiUpperBoundsEnergy[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 6.0

LaiUpperBoundsEnergy SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsEnergy[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 3.50

LaiUpperBoundsEnergy[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 6.0

LaiUpperBoundsEnergy[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsEnergy[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 3.50

LaiUpperBoundsEnergy[ICE][GRASS][NEEDLELEAF][BROADLEAF] 0.0

LaiUpperBoundsEnergy[ICE][TREE][NEEDLELEAF][BROADLEAF] 0.0

LaiUpperBoundsEnergy[ICE][SHRUB][NEEDLELEAF][BROADLEAF] 0.0

LaiUpperBoundsEnergy[TUNDRA][GRASS][NEEDLELEAF][BROADLEAF] 2.0

LaiUpperBoundsEnergy[TUNDRA][TREE][NEEDLELEAF][BROADLEAF] 0.0

LaiUpperBoundsEnergy[TUNDRA][SHRUB][NEEDLELEAF][BROADLEAF] 1.5

LaiUpperBoundsEnergy[TAIGA_TUNDRA][GRASS][NEEDLELEAF][BROADLEAF] 3.0

LaiUpperBoundsEnergy[TAIGA_TUNDRA][TREE][NEEDLELEAF][BROADLEAF] 0.0

Table 11—Parameters and their values in the MAPSS parameter file, parameters

27
28

Table 11—Parameters and their values in the MAPSS parameter file, parameters

(continued)

Parameter Value

LaiUpperBoundsEnergy[TAIGA_TUNDRA][SHRUB][NEEDLELEAF][BROADLEAF] 2.5

LaiUpperBoundsLifeform[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[ICE][GRASS][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[ICE][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[ICE][SHRUB][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TUNDRA][GRASS][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TUNDRA][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TUNDRA][SHRUB][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TAIGA_TUNDRA][GRASS][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TAIGA_TUNDRA][TREE][NEEDLELEAF][BROADLEAF] 15.0

LaiUpperBoundsLifeform[TAIGA_TUNDRA][SHRUB][NEEDLELEAF][BROADLEAF] 15.0

Maximum grass LAI in first month of growing season

spring_grass[BOREAL] [TEMPERATE][SUBTROPICAL][TROPICAL] 1.5

LAI at which shrub becomes chaparral

chaparral_lai[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL] 1.2

LAI below which forest -> savanna

forest_threshold[BOREAL][NEEDLELEAF][BROADLEAF] 3.75

forest_threshold[TEMPERATE][NEEDLELEAF][BROADLEAF] 3.75

forest_threshold[SUBTROPICAL][NEEDLELEAF][BROADLEAF] 3.75

forest_threshold[TROPICAL][NEEDLELEAF][BROADLEAF] 3.75

min_tree_lai[BOREAL][NEEDLELEAF][BROADLEAF] 1.85

min_tree_lai[TEMPERATE][NEEDLELEAF][BROADLEAF] 1.85

min_tree_lai[SUBTROPICAL][NEEDLELEAF][BROADLEAF] 1.85

min_tree_lai[TROPICAL][NEEDLELEAF][BROADLEAF] 0.65

tree_pet_factor[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL] 2.55

tallgrass_pet_factor[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL] 1.22

Woody LAI threshold for light attenuation

no_attenuation_lai

[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL] [NEEDLELEAF] 0.0

[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][BROADLEAF] 0.0

full_attenuation_lai

[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][NEEDLELEAF] 5.0

[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][BROADLEAF] 5.0

a_surf y-intercept (mm), detention as function of soil surface 0.0

b_surf slope (mm), detention as function of soil surface 0.0

Maximum conductance in tropical forests (mm/sec)

normal_cond_max[BOREAL][TEMPERATE][SUBTROPICAL] 3.5

normal_cond_max[TROPICAL] 7.6

wue[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] 1.00

wue[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 1.00

wue[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 1.00
29

Table 11—Parameters and their values in the MAPSS parameter file, parameters

(continued)

Parameter Value

wue[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 1.00

wue[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 1.00

wue[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 1.00

wue[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 1.00

wue[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 1.00

wue[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 1.00

wue[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 1.00

wue[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 1.00

wue[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 1.00

Maximum conductance (mm/sec)

cond_max[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] 3.50

cond_max[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 2.50

cond_max[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 1.5

cond_max[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 3.50

cond_max[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 2.50

cond_max[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 1.5

cond_max[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 5.50

cond_max[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 2.50

cond_max[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 1.5

cond_max[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 5.50

cond_max[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 7.6

cond_max[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 1.5

Minimum conductance (mm/sec)

cond_min[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] 1.0

cond_min[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 1.5

cond_min[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.8

cond_min[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 1.0

cond_min[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 1.5

cond_min[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 0.8

cond_min[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 0.2

cond_min[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 1.5

cond_min[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.8

cond_min[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 0.2

cond_min[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 1.5

cond_min[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.8

Maximum conductance (mm/sec)

cond_surface_max[BOREAL][GRASS][NEEDLELEAF] [BROADLEAF] 5.00

cond_surface_max[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 20.6

cond_surface_max[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 9.4

cond_surface_max[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 23.0

cond_surface_max[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 20.6

cond_surface_max[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 9.4

cond_surface_max[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 17.1

cond_surface_max[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 12.1

cond_surface_max[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 9.4

cond_surface_max[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 17.1

cond_surface_max[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 16.1

cond_surface_max[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 9.4

Allowed months of below minimum conductance

cond_min_months[GRASS][NEEDLELEAF][BROADLEAF] 0.0

cond_min_months[TREE][NEEDLELEAF][BROADLEAF] 1.0

cond_min_months[SHRUB][NEEDLELEAF][BROADLEAF] 1.0
30

Table 11—Parameters and their values in the MAPSS parameter file, parameters

(continued)

Parameter Value

Maximum LAI/at ratio below at threshold

max_lai2at[GRASS][NEEDLELEAF][BROADLEAF] 15.0

max_lai2at[TREE][NEEDLELEAF][BROADLEAF] 0.25

max_lai2at[SHRUB][NEEDLELEAF][BROADLEAF] 10.0

Apply max LAI/at ratio below this value

at_thresh[GRASS][NEEDLELEAF][BROADLEAF] 1000.0

at_thresh[TREE][NEEDLELEAF][BROADLEAF] 1000.0

at_thresh[SHRUB][NEEDLELEAF][BROADLEAF] 250.0

Permanent wilting point (MPa)

wp[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] -1.5

wp[BOREAL][TREE][NEEDLELEAF][BROADLEAF] -1.5

wp[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] -6.0

wp[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] -1.5

wp[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] -1.5

wp[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] -6.0

wp[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] -1.5

wp[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] -1.5

wp[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] -6.0

wp[TROPICAL][GRASS][NEEDLELEAF] [BROADLEAF] -1.5

wp[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] -1.5

wp[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] -6.0

k_trans_addend[GRASS][NEEDLELEAF][BROADLEAF] 0.00

k_trans_addend[TREE][NEEDLELEAF][BROADLEAF] 0.00

k_trans_addend[SHRUB][NEEDLELEAF][BROADLEAF] 0.00

Coefficient of transpiration ratio model

k_transp[BOREAL][GRASS][0][NEEDLELEAF][BROADLEAF] 4.00

k_transp[BOREAL][TREE][0][NEEDLELEAF] 1.50

k_transp[BOREAL][TREE][0][BROADLEAF] 1.95

k_transp[BOREAL][SHRUB][0][NEEDLELEAF][BROADLEAF] 8.75

k_transp[TEMPERATE][GRASS][0][NEEDLELEAF][BROADLEAF] 4.00

k_transp[TEMPERATE][TREE][0][NEEDLELEAF] 2.50

k_transp[TEMPERATE][TREE][0][BROADLEAF] 2.95

k_transp[TEMPERATE][SHRUB][0][NEEDLELEAF][BROADLEAF] 8.75

k_transp[SUBTROPICAL][GRASS][0][NEEDLELEAF][BROADLEAF] 4.00

k_transp[SUBTROPICAL][TREE][0][NEEDLELEAF] 2.25

k_transp[SUBTROPICAL][TREE][0][BROADLEAF] 2.70

k_transp[SUBTROPICAL][SHRUB][0][NEEDLELEAF][BROADLEAF] 8.75

k_transp[TROPICAL][GRASS][0][NEEDLELEAF][BROADLEAF] 4.00

k_transp[TROPICAL][TREE][0][NEEDLELEAF][BROADLEAF] 2.70

k_transp[TROPICAL][SHRUB][0][NEEDLELEAF][BROADLEAF] 6.75

This determines which of the AT formulae are to be used

at_flag Grouped constants 3

Coefficient of PET effects coefficient of conductance

a_slope[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] 0.002

a_slope[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 0.1

a_slope[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.030

a_slope[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 0.002

a_slope[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 0.1

a_slope[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 0.030

a_slope[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 0.002

a_slope[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 0.1

a_slope[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.030

a_slope[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 0.002
31

Table 11—Parameters and their values in the MAPSS parameter file, parameters

(continued)

Parameter Value

a_slope[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 0.100

a_slope[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.030

pet_int[BOREAL][GRASS][NEEDLELEAF][BROADLEAF] 0.00

pet_int[BOREAL][TREE][NEEDLELEAF][BROADLEAF] 0.0

pet_int[BOREAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.0

pet_int[TEMPERATE][GRASS][NEEDLELEAF][BROADLEAF] 0.00

pet_int[TEMPERATE][TREE][NEEDLELEAF][BROADLEAF] 0.0

pet_int[TEMPERATE][SHRUB][NEEDLELEAF][BROADLEAF] 0.0

pet_int[SUBTROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 0.00

pet_int[SUBTROPICAL][TREE][NEEDLELEAF][BROADLEAF] 0.0

pet_int[SUBTROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.0

pet_int[TROPICAL][GRASS][NEEDLELEAF][BROADLEAF] 0.00

pet_int[TROPICAL][TREE][NEEDLELEAF][BROADLEAF] 0.0

pet_int[TROPICAL][SHRUB][NEEDLELEAF][BROADLEAF] 0.0

_surfrun coeff of surface runoff (increase to reduce runoff) 1.7

max_infilt coefficient relating soil texture to maximum infiltration rate 0.0

infilt_thresh threshold melt plus throughfall attains max infiltration 0.0

broad_ppt_mo[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL] -1

broad_ppt_min minimum monthly ppt for broadleaf, growing season 40.0

s_decid_bound southern temp threshold of coldest month, deciduous (1.25) 2.25

n_decid_bound northern temp threshold, deciduous -16.0

ice_boundary[BOREAL] 0.0

tundra_boundary[BOREAL] 735.0

taiga_tundra_boundary[BOREAL] 1330.0

tundra_boundary[BOREAL] 367.5

taiga_tundra_boundary[BOREAL] 665.0

ice_boundary[TEMPERATE] 0.0

tundra_boundary[TEMPERATE] 615.0

taiga_tundra_boundary[TEMPERATE] 1165.0

tundra_boundary[TEMPERATE] 307.5

taiga_tundra_boundary[TEMPERATE] 582.5

closed_forest_at annual wood at prohibiting grass fire (mm) (n/a) 480.0

fire_min_at frost free mean monthly grass at for fire (mm) (n/a) 1000.0

desert_wood_at annual wood at desert threshold (mm) 200.0

desert_wood_lai maximum woody lai at < desert_wood_at 3.00

DoFire 5 => the VEMAP fire rule. 5

1 MaxBurnCycles

fire_threshold_1 threshold for Grass Sum LAI 2.0

fire_threshold_2 threshold for Shrub LAI 2.50

fire_threshold_3 threshold for Tree LAI 3.0

fire_threshold_4 threshold for surface soil moisture 0.0

fire_threshold_5 threshold for pet 100.0

fire_threshold_6 threshold for Precip in High Month 50.0

Hammer woody LAI down before entry into grass/woody competition

hammer 0

do not hammer 1

k_factor_slope[BOREAL][NEEDLELEAF][BROADLEAF] -2.50

k_factor_contstraint[BOREAL][NEEDLELEAF][BROADLEAF] 170.0

k_factor_pet_boundary[BOREAL][NEEDLELEAF][BROADLEAF] default (< 0) -1325.0

k_factor_slope[TEMPERATE][NEEDLELEAF][BROADLEAF] -2.50

k_factor_contstraint[TEMPERATE][NEEDLELEAF][BROADLEAF] 170.0

k_factor_pet_boundary[TEMPERATE][NEEDLELEAF][BROADLEAF] default (< 0) -1325.0

k_factor_slope[SUBTROPICAL][NEEDLELEAF][BROADLEAF] -2.50
32

Table 11—Parameters and their values in the MAPSS parameter file, parameters

(continued)

Parameter Value

k_factor_contstraint[SUBTROPICAL][NEEDLELEAF][BROADLEAF] 170.0

k_factor_pet_boundary[SUBTROPICAL][NEEDLELEAF][BROADLEAF] default (< 0) -1325.0

k_factor_slope[TROPICAL][NEEDLELEAF][BROADLEAF] -2.50

k_factor_contstraint[TROPICAL][NEEDLELEAF][BROADLEAF] 170.0

k_factor_pet_boundary[TROPICAL][NEEDLELEAF][BROADLEAF] default (< 0) -1325.0

k_factor_winter_boundary_upper 8

k_factor_winter_boundary_lower 4

Temperature between maritime and continental types

maritime_boundary[BOREAL][SUBTROPICAL][TROPICAL] 20.0

maritime_boundary[TEMPERATE] 18.0

xeric_savanna_threshold 0.50

mediterranean_savanna_threshold 0.75

temperate_conifer_threshold 1.6

temperate_xeromorphic_conifer_threshold 1.2

dry_trop_threshold 2.00

semi_desert_threshold 0.45

short_grass_threshold # was 0.8 1.15

tall_grass_threshold 2.00

desert_grass_sum_threshold 1.20

desert_shrub_threshold 0.175

desert_grass_threshold 0.10

north_hard_threshold # was 11.0 9.00

tsg_threshold 0.60

tsg_threshold 0.50

pj_max_lai_continental 2.10

pj_max_lai_maritime 2.10

pj_xeric_threshold 2.00

max_grass_threshold 1.50

max_grass_shrub_threshold 0.70

cool_grass_threshold 3.00

C3C4 Option 4

# 4 => C3C4CenturyNew

c3c4_jim_thresh 0.20

c3c4_century_thresh 0.48

# These are the parameters for the internal PET calculations.

Upper heights

z[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][GRASS] 10.00

z[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][TREE] 10.00

z[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][SHRUB] 10.00

Roughness lengths

z0[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][GRASS] 0.0005

z0[BOREAL][TEMPERATE][SUBTROPICAL][TREE] 0.01

z0[TROPICAL][TREE] 0.02

z0[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL][SHRUB] 0.001

Uniform across all terrain all seasons

wind_speed[BOREAL][TEMPERATE][SUBTROPICAL][TROPICAL] -5.0

(A negative value means use actual wind values from input files.)

elevation (A negative value means use actual elevation value from an input file.) -500.0

grass_snowpack Max depth of snow under which grass will grow (mm of rain). 10.0

Note that this is not a measure of snow depth. It is an amount of water.

fractional_gcm Fractional GCM 1.0

fractional_wue Fractional WUE 1.0
4. Parameters and

Variables

4.1 Generalization of

Input Parameters

4.2 Biogeographic

Parameters and Variables

CENTURY (Parton and others 1987, 1994) was designed primarily for site-specific

application to individual ecosystems. It uses a parameter set containing values of tree

and grass maximum potential production, temperature growth limits, C:N ratios, leaf

turnover rate, soil nutrient concentrations, and other related parameters. The parameter

set is selected through an externally supplied ecosystem type, such as a VEMAP

vegetation class (VEMAP Members 1995). In MC1, however, the ecosystem type may

change over time in response to climatic and successional factors. Early applications of

MC1 with step changes in ecosystem types, and thus step changes in parameter sets,

produced unacceptable discontinuities in predicted C pools when the ecosystem type

changed. In the modified version of CENTURY used in MC1, a method therefore was

developed to reduce the number of parameter sets and to smoothly transition from one

set to another.

As discussed previously, the biogeographic module calculates climatic indices that

describe the lifeform composition of an ecosystem as mixtures of deciduous needleleaf

(DN), evergreen needleleaf (EN), deciduous broadleaf (DB), evergreen broadleaf (EB)

trees, and C3 and C4 grasses. Parameter values appropriate for pure stands of the four

tree lifeforms and the two grass lifeforms were extracted from parameter files previously

used with CENTURY. We linearly interpolated between these pure stand values to

estimate the biogeochemical module’s parameter values appropriate for the lifeform

mixture predicted by the biogeographic model. Transforming CENTURY’s static input

structure to a smoothly varying and dynamic system resulted in more realistic and

natural transitions of model predictions.

4.2.1 Equilibrium conditions—

Running equilibrium MAPSS—Running MAPSS requires input from two parameter

files: site and parameters. The site file includes site-specific inputs, such as field

capacity, saturated drainage, and texture for the three soil layers. The parameters file

includes other information necessary to set the parameters of the MAPSS model, such

as LAI, PET, and water use efficiency for the various vegetation classes. Tables 10 and

11 show the values of the most important parameters included in those two files.

33
Running equilibrium CENTURY—The biogeochemical module of MC1 (a modified

version of CENTURY) is run independently of the fire module and of the MC1

biogeographic module. Fire events are prescribed in Veg.type specific files

(vvegTypex.sch). The module is run until som2c (the slow organic matter pool)

becomes stable. At this point, simulated values of all C and N pools are saved and can

serve as initial conditions for the transient run.

4.2.2 Transient conditions—A set of biogeographic rules (different from those used in

MAPSS) was developed for the MC1 biogeographic module. The MC1 rules use LAI

thresholds from CENTURY and climatic indices to identify vegetation types. Table 12

lists thresholds from the biogeography parameter file: thres.dat.

4.3.1 Parameter and initial condition files—For each vegetation type, the

biogeochemical module selects respective parameters and initial condition files.

Parameter files consist of (1) schedule files (vvegTypex.sch), where grass and tree

types are defined and where fire events are scheduled for the equilibrium run; (2) the

“fixed” files (xfix.100), which are separated into seven vegetation types and include

most of the site characteristics, such as the rates of nitrogen loss; and (3) the

parameter files (vvegTypex.100), which include initial conditions for soil organic

matter and mineral content. The biogeochemistry module also reads the files tree.100

and crop.100, which include the physiological parameters specific to MC1 that differ

from one lifeform to another.

Tables 13 through 15 list some examples of the parameter files required by the

biogeochemistry module. Tables 16 and 17 are the tree.100 and crop.100 files.

4.3 Biogeochemical

Parameters and Variables

Name Description Value

forest_thres LAI threshold for forest vs. savanna 3.75

savanna_thres LAI threshold for savanna vs. shrubland 2.0

shrub_thres LAI threshold for shrubland vs. grassland 1.0

C3_thres c3_c4 index threshold for c3 vs. c4 grassland 55.0

maritime_thres Continental index threshold for maritime vs. continental 15.0

 coniferous forests

tundra_thres Degree-day threshold for tundra vs. taiga 735.0

taiga_thres Degree-day threshold for taiga vs. boreal forest 1330.0

Table 12—Thresholds from the biogeographic parameter file, thres.dat

34
Table 13—An example of a schedule file, MapssCenx.sch, required by the

biogeochemical modulea

Value Description

1 Starting year

1 Last year

vvegType3.100 Site file name

0 Labeling type

-1 Labeling year

-1.00 Microcosm

0 CO2

 systems [effect of CO2 on/off switch]

3 Initial system [savanna mode]

SUPRG Initial crop [MC1 definition of tree and grass types]

SUPRT Initial tree

Year Month Option:

1 Block number temperate mixed

1 Last year

1 Repeats number of years

1 Output starting year

1 Output month

0.08333 Output interval (1month)

M: Weather choice

 1 1 TFST [first month of growth - trees]

 1 1 FRST [first month of growth - grasses]

 1 12 LAST [last month of growth - grasses]

 1 11 SENM [senescence month - grasses]

 1 12 TLST [last month of growth - trees]

-999 -999 X

a These files were created for transient mode, and original .sch files from CENTURY are used only in

equilibrium mode.

35
Table 14—An example of an MC1 parameter file, ffix.100, required by the biogeochemical modulea

Variable Value

ADEP(1) 15.0

ADEP(2) 15.0

ADEP(3) 15.0

ADEP(4) 15.0

ADEP(5) 30.0

ADEP(6) 30.0

ADEP(7) 30.0

ADEP(8) 30.0

ADEP(9) 30.0

ADEP(10) 30.0

AGPPA -40.0

AGPPB 7.70

ANEREF(1) 1.50

ANEREF(2) 3.0

ANEREF(3) 0.30

ANIMPT 5.0

AWTL(1) 0.8

AWTL(2) 0.6

AWTL(3) 0.4

AWTL(4) 0.3

AWTL(5) 0.2

AWTL(6) 0.2

AWTL(7) 0.2

AWTL(8) 0.2

AWTL(9) 0.0

AWTL(10) 0.0

BGPPA 100.0

BGPPB 7.0

CO2PPM(1) 350.0

CO2PPM(2) 700.0

CO2RMP 1.0

DAMR(1,1) 0.0

DAMR(2,1) 0.02

DAMRMN(1) 15.0

DAMRMN(2) 150.0

DAMRMN(3) 150.0

DEC1(1) 3.9

DEC1(2) 4.9

DEC2(1) 14.8

DEC2(2) 18.5

DEC3(1) 6.0

DEC3(2) 7.3

a See list of parameters in section 4.3.2 for definitions.

36

Variable Value

DEC4 0.0045

DEC5 0.20

DECK5 5.0

DLIGDF -4.0

DRESP 0.999

EDEPTH 0.2

ELITST 0.4

ENRICH 2.0

FAVAIL(1) 0.90

FAVAIL(3) 0.5

FAVAIL(4) 0.2

FAVAIL(5) 0.4

FAVAIL(6) 2.0

FLEACH(1) 0.2

FLEACH(2) 0.7

FLEACH(3) 1.0

FLEACH(4) 0.0

FLEACH(5) 0.1

FWLOSS(1) 0.8

FWLOSS(2) 0.8

FWLOSS(3) 0.65

FWLOSS(4) 0.7

FXMCA -0.125

FXMCB 0.005

FXMXS 0.35

FXNPB 7.0

GREMB 0.0

IDEF 2.0

LHZF(1) 0.20

LHZF(2) 0.40

LHZF(3) 0.80

MINLCH 18.0

NSNFIX 0.0

NTSPM 4.0

OMLECH(1) 0.03

OMLECH(2) 0.12

OMLECH(3) 60.0

P1CO2A(1) 0.60

P1CO2A(2) 0.17

P1CO2B(1) 0.0

P1CO2B(2) 0.68

P2CO2 0.55

Variable Value

P3CO2 0.55

PABRES 100.0

PCEMIC(1,1) 16.0

PCEMIC(2,1) 10.0

PCEMIC(3,1) 0.02

PEFTXA 0.25

PEFTXB 0.75

PHESP(1) 6.0

PHESP(2) 0.0008

PHESP(3) 7.6

PHESP(4) 0.015

PLIGST(1) 3.0

PLIGST(2) 3.0

PMCO2(1) 0.55

PMCO2(2) 0.55

PMNSEC(1) 0.0

PMNSEC(2) 0.0

PMNSEC(3) 2.0

PMNTMP 0.004

PMXBIO 600.0

PMXTMP 0.0035

PPARMN(1) 0.0

PPARMN(2) 0.0001

PPARMN(3) 0.0005

PPRPTS(1) 0.0

PPRPTS(2) 1.0

PPRPTS(3) 0.80

PS1CO2(1) 0.45

PS1CO2(2) 0.55

PS1S3(1) 0.003

PS1S3(2) 0.032

PS2S3(1) 0.003

PS2S3(2) 0.009

PSECMN(1) 0.0

PSECMN(2) 0.0022

PSECMN(3) 0.20

PSECOC 0.0

RAD1P(1,1) 12.0

RAD1P(2,1) 3.0

RAD1P(3,1) 5.0

RCESTR(1) 200.0

RCESTR(2) 500.0

Variable Value

RCESTR(3) 500.0

RICTRL 0.015

RINNT 0.80

RSPLIG 0.30

SEED -1.00

SPL(1) 0.85

SPL(2) 0.013

STRMAX(1) 5000

STRMAX(2) 5000

TEXEPP(1) 1.0

TEXEPP(2) 0.7

TEXEPP(3) 0.0001

TEXEPP(4) 0.00016

TEXEPP(5) 2.0

TEXESP(1) 1.0

TEXESP(3) 0.004

TEFF(1) 0.0

TEFF(2) 0.125

TEFF(3) 0.07

TMELT(1) -6.0

TMELT(2) 2.0

VARAT1(1,1) *

VARAT1(2,1) *

VARAT1(3,1) 2.0

VARAT2(1,1) 40.0

VARAT2(2,1) 12.0

VARAT2(3,1) 2.0

VARAT3(1,1) 20.0

VARAT3(2,1) 6.0

VARAT3(3,1) 2.0

VLOSSE **

VLOSSG **

VARAT(1,1) 14

 (dryg, drytrp, g, trp)

VARAT(1,1) 18

arc, bor, f

VLOSSE/VLOSSG 0.02

arc, bor, f, g, trp

VLOSSE/VLOSSG 0.05
Climate parameters

Value Parameter

29.61000 PRECIP(1)

30.85000 PRECIP(2)

25.93000 PRECIP(3)

15.09000 PRECIP(4)

10.40000 PRECIP(5)

7.36000 PRECIP(6)

1.76000 PRECIP(7)

4.28000 PRECIP(8)

7.64000 PRECIP(9)

16.65000 PRECIP(10)

35.62000 PRECIP(11)

42.65000 PRECIP(12)

14.83000 PRCSTD(1)

11.14000 PRCSTD(2)

10.12000 PRCSTD(3)

5.41000 PRCSTD(4)

5.21000 PRCSTD(5)

5.24000 PRCSTD(6)

1.63000 PRCSTD(7)

3.59000 PRCSTD(8)

5.64000 PRCSTD(9)

10.66000 PRCSTD(10)

17.69000 PRCSTD(11)

17.39000 PRCSTD(12)

0.00000 PRCSKW(1)

0.00000 PRCSKW(2)

0.00000 PRCSKW(3)

0.00000 PRCSKW(4)

0.00000 PRCSKW(5)

0.00000 PRCSKW(6)

0.00000 PRCSKW(7)

0.00000 PRCSKW(8)

0.00000 PRCSKW(9)

0.00000 PRCSKW(10)

0.00000 PRCSKW(11)

0.00000 PRCSKW(12)

-1.80000 TMN2M(1)

-0.30000 TMN2M(2)

0.50000 TMN2M(3)

1.60000 TMN2M(4)

4.20000 TMN2M(5)

7.20000 TMN2M(6)

9.00000 TMN2M(7)

8.80000 TMN2M(8)

6.10000 TMN2M(9)

3.00000 TMN2M(10)

0.60000 TMN2M(11)

-1.10000 TMN2M(12)

4.00000 TMX2M(1)

6.90000 TMX2M(2)

10.20000 TMX2M(3)

Climate parameters (cont.)

Value Parameter

14.00000 TMX2M(4)

18.70000 TMX2M(5)

22.80000 TMX2M(6)

28.00000 TMX2M(7)

27.70000 TMX2M(8)

23.80000 TMX2M(9)

16.10000 TMX2M(10)

7.10000 TMX2M(11)

3.30000 TMX2M(12)

External nutrient input

 parameters

Value Parameter

0.05000 EPNFA(1)

0.00700 EPNFA(2)

0.00000 EPNFS(1)

0.00000 EPNFS(2)

0.00000 SATMOS(1)

0.00000 SATMOS(2)

0.00000 SIRRI

Water initial parameters

Value Parameter

0.00000 RWCF(1)

0.00000 RWCF(2)

0.00000 RWCF(3)

0.00000 RWCF(4)

0.00000 RWCF(5)

0.00000 RWCF(6)

0.00000 RWCF(7)

0.00000 RWCF(8)

0.00000 RWCF(9)

0.00000 RWCF(10)

0.00000 SNLQ

0.00000 SNOW

Site and control parameters

Value Parameter

0.00000 IVAUTO

1.00000 NELEM

44.25000 SITLAT

122.17000 SITLNG

0.25000 SAND

0.50000 SILT

0.25000 CLAY

1.00000 BULKD

8.00000 NLAYER

5.00000 NLAYPG

1.00000 DRAIN

0.30000 BASEF

0.60000 STORMF

1.00000 SWFLAG

0.20000 AWILT(1)

Site and control parameters

 (cont.)

Value Parameter

0.20000 AWILT(2)

0.20000 AWILT(3)

0.20000 AWILT(4)

0.20000 AWILT(5)

0.20000 AWILT(6)

0.20000 AWILT(7)

0.20000 AWILT(8)

0.20000 AWILT(9)

0.30000 AWILT(10)

0.30000 AFIEL(1)

0.30000 AFIEL(2)

0.30000 AFIEL(3)

0.30000 AFIEL(4)

0.30000 AFIEL(5)

0.30000 AFIEL(6)

0.30000 AFIEL(7)

0.30000 AFIEL(8)

0.30000 AFIEL(9)

0.00000 AFIEL(10)

6.00000 PH

1.00000 PSLSRB

5.00000 SORPMX

Organic matter initial values

Value Parameter

60.00000 SOM1CI(1,1)

0.00000 SOM1CI(1,2)

130.0000 SOM1CI(2,1)

0.00000 SOM1CI(2,2)

2570.0000 SOM2CI(1)

0.00000 SOM2CI(2)

1596.0000 SOM3CI(1)

0.00000 SOM3CI(2)

15.00000 RCES1(1,1)

50.00000 RCES1(1,2)

50.00000 RCES1(1,3)

15.50000 RCES1(2,1)

50.00000 RCES1(2,2)

50.00000 RCES1(2,3)

32.00000 RCES2(1)

117.0000 RCES2(2)

117.0000 RCES2(3)

18.00000 RCES3(1)

62.00000 RCES3(2)

62.00000 RCES3(3)

260.0000 CLITTR(1,1)

0.00000 CLITTR(1,2)

165.0000 CLITTR(2,1)

0.00000 CLITTR(2,2)

165.0000 RCELIT(1,1)

Table 15—An example of an MC1 parameter file, vvegTypex.100, required by the

biogeochemical module

37
Organic matter initial

 values (cont.)

Value Parameter

0.00000 RCELIT(1,2)

0.00000 RCELIT(1,3)

66.00000 RCELIT(2,1)

300.0000 RCELIT(2,2)

300.0000 RCELIT(2,3)

0.00000 AGLCIS(1)

0.00000 AGLCIS(2)

0.00000 AGLIVE(1)

0.00000 AGLIVE(2)

0.00000 AGLIVE(3)

0.00000 BGLCIS(1)

0.00000 BGLCIS(2)

0.00000 BGLIVE(1)

0.00000 BGLIVE(2)

0.00000 BGLIVE(3)

0.00000 STDCIS(1)

0.00000 STDCIS(2)

0.00000 STDEDE(1)

0.00000 STDEDE(2)

0.00000 STDEDE(3)

Forest organic matter initial

Value Parameter

685.0000 RLVCIS(1)

0.00000 RLVCIS(2)

7.70000 RLEAVE(1)

0.00000 RLEAVE(2)

0.00000 RLEAVE(3)

2630.0000 FBRCIS(1)

0.00000 FBRCIS(2)

15.90000 FBRCHE(1)

0.00000 FBRCHE(2)

0.00000 FBRCHE(3)

Forest organic matter initial

 (cont.)

Value Parameter

32300.000 RLWCIS(1)

0.00000 RLWCIS(2)

36.20000 RLWODE(1)

0.00000 RLWODE(2)

0.00000 RLWODE(3)

89.00000 FRTCIS(1)

0.00000 FRTCIS(2)

1.10000 FROOTE(1)

0.00000 FROOTE(2)

0.00000 FROOTE(3)

2475.0000 CRTCIS(1)

0.00000 CRTCIS(2)

4.45000 CROOTE(1)

0.00000 CROOTE(2)

0.00000 CROOTE(3)

500.0000 WD1CIS(1)

0.00000 WD1CIS(2)

9500.000 WD2CIS(1)

0.00000 WD2CIS(2)

1900.000 WD3CIS(1)

0.00000 WD3CIS(2)

0.26000 W1LIG

0.26000 W2LIG

0.26000 W3LIG

Mineral initial parameters

Value Parameter

0.00770 MINERL(1,1)

0.00500 MINERL(2,1)

0.00320 MINERL(3,1)

0.00210 MINERL(4,1)

0.00130 MINERL(5,1)

0.00085 MINERL(6,1)

38

Table 15—An example of an MC1 parameter file, vvegTypex.100, required by the

biogeochemical module

Mineral initial parameters

 (cont.)

Value Parameter

0.00054 MINERL(7,1)

0.00035 MINERL(8,1)

0.00004 MINERL(9,1)

0.00000 MINERL(10,1)

0.00000 MINERL(1,2)

0.00000 MINERL(2,2)

0.00000 MINERL(3,2)

0.00000 MINERL(4,2)

0.00000 MINERL(5,2)

0.00000 MINERL(6,2)

0.00000 MINERL(7,2)

0.00000 MINERL(8,2)

0.00000 MINERL(9,2)

0.00000 MINERL(10,2)

0.00000 MINERL(1,3)

0.00000 MINERL(2,3)

0.00000 MINERL(3,3)

0.00000 MINERL(4,3)

0.00000 MINERL(5,3)

0.00000 MINERL(6,3)

0.00000 MINERL(7,3)

0.00000 MINERL(8,3)

0.00000 MINERL(9,3)

0.00000 MINERL(10,3)

500.0000 PARENT(1)

0.00000 PARENT(2)

0.00000 PARENT(3)

0.00000 SECNDY(1)

15.00000 SECNDY(2)

2.00000 SECNDY(3)

0.00000 OCCLUD
Parameter DN EN DB EB

BASFC2 1.0 1.0 1.0 1.0

BASFCT 400.0 400.0 400.0 400.0

BTOLAI 0.012 0.004 0.012 0.007

CERFOR(1,5,1) 600 600 83 150.

CERFOR(1,4,1) 900.0 900.0 140.0 150.0

CERFOR(1,1,1) 100.0 100.0 20.0 20.0

CERFOR(1,2,1) 50.0 50.0 35.0 35.0

CERFOR(1,3,1) 310. 310 80.0 120.0

CERFOR(2,5,1) 80. 80. 500. 300.

CERFOR(2,4,1) 800.0 800.0 140.0 300.0

CERFOR(2,1,1) 100.0 100.0 40.0 40.0

CERFOR(2,2,1) 81.0 81.0 50.0 60.0

CERFOR(2,3,1) 310. 310. 99. 180.

CERFOR(3,5,1) 550. 550. 80.0 155.0

CERFOR(3,4,1) 900.0 900.0 140.0 155.0

CERFOR(3,1,1) 90.0 90.0 40.0 40.0

CERFOR(3,2,1) 80.0 80.0 50.0 76.0

CERFOR(3,3,1) 300. 300. 80. 84.

CO2ICE(1,2,1) 1.25 1.25 1.25 1.25

CO2ICE(1,2,2) 1.0 1.0 1.0 1.0

CO2ICE(1,1,3) 1.0 1.0 1.0 1.0

CO2ICE(1,1,2) 1.0 1.0 1.0 1.0

CO2ICE(1,1,1) 1.25 1.25 1.25 1.25

CO2ICE(1,2,3) 1.0 1.0 1.0 1.0

CO2IPR 1.25 1.25 1.25 1.25

CO2IRS 1.0 1.0 1.0 1.0

CO2ITR 0.75 0.75 0.75 0.75

DECID 1.0 1.0 1.0 1.0

DECW1 0.9 0.9 0.9 0.9

DECW2 0.4 0.4 0.4 0.4

DECW3 0.4 0.4 0.4 0.4

DEL13C 0.0 0.0 0.0 0.0

FCFRAC(1,2) 0.37 0.37 0.34 0.34

FCFRAC(1,1) 0.37 0.37 0.34 0.25

FCFRAC(2,2) 0.34 0.34 0.40 0.25

FCFRAC(2,1) 0.34 0.34 0.40 0.25

FCFRAC(3,2) 0.10 0.10 0.09 0.11

FCFRAC(3,1) 0.10 0.10 0.09 0.10

FCFRAC(4,2) 0.18 0.18 0.15 0.22

FCFRAC(5,2) 0.01 0.01 0.02 0.08

FORRTF 0.450 0.450 0.450 0.450

FCFRAC(4,1) 0.18 0.18 0.15 0.30

FCFRAC(5,1) 0.01 0.01 0.02 0.10

FORRTF(2) 0.0 0.0 0.0 0.0

FORRTF(3) 0.0 0.0 0.0 0.0

KLAI 2000.0 2000.0 1000.0 1000.0

LAITOP -0.470 -0.470 -0.470 -0.470

Table 16—MC1 parameter file, tree.100a

39
Parameter DN EN DB EB

LEAFDR(1) 0.00 0.03 0.00 0.07

LEAFDR(10) 0.00 0.03 0.00 0.07

LEAFDR(11) 0.00 0.03 0.00 0.07

LEAFDR(12) 0.00 0.10 0.00 0.07

LEAFDR(2) 0.00 0.03 0.00 0.07

LEAFDR(3) 0.00 0.03 0.00 0.07

LEAFDR(4) 0.00 0.03 0.00 0.07

LEAFDR(5) 0.00 0.03 0.00 0.07

LEAFDR(6) 0.00 0.03 0.00 0.07

LEAFDR(7) 0.00 0.03 0.00 0.07

LEAFDR(8) 0.00 0.03 0.00 0.07

LEAFDR(9) 0.00 0.03 0.00 0.07

MAXLAI 10. 10. 10. 10.

MAXLDR 1.0 1.0 1.0 1.0

PPDF(1) 15. 15. 25. 30.

PPDF(2) 30. 30. 35. 45.

PPDF(3) 1.0 1.0 1.0 1.0

PPDF(4) 5.0 5.0 3.5 2.5

PRDX(3) 10000 10000 10000 10000

PRDX(4) 250. 250. 250. 250.

SAPK 1500.0 1500.0 1500.0 1500.0

SITPOT 4800.0 4800.0 2400.0 2400.0

SNFXMX(2) 0.0 0.0 0.0 0.0

SWOLD 0.0 0.0 0.0 0.0

WDLIG (1) 0.2100 0.2100 0.2100 0.2100

WDLIG (2) 0.2200 0.2200 0.2200 0.2200

WDLIG (4) 0.3000 0.3000 0.3000 0.3000

WDLIG (5) 0.3000 0.3000 0.3000 0.3000

WDLIG (3) 0.2500 0.2500 0.2500 0.2500

WOODDR(1) 1.0 0.0 1.0 0.0

WOODDR(2) 0.05 0.05 0.04 0.03

WOODDR(3) 0.01 0.01 0.01 0.01

WOODDR(4) 0.0008 0.0008 0.002 0.002

WOODDR(5) 0.001 0.001 0.004 0.004

a See parameter list for definitions; DN = deciduous needleleaf, EN = evergreen needleleaf, DB =

deciduous broadleaf, EB = evergreen broadleaf.

40

Table 16—MC1 parameter file, tree.100a (continued)
Parameter C3 C4

BIOFLG 1 1

BIOK5 60 60

BIOMAX 400 400

CO2ICE(1,2,1) 1.25 1.25

CO2ICE(1,1,1) 1.25 1.25

CO2IPR 1.25 1.25

CO2IRS 1 1

CO2ITR 0.75 0.75

CRPRTF(1) 0.5 0.5

DEL13C 0 0

EFRGRN(1) 0.5 0.5

FALLRT .2 .2

FLIGNI(1,1) 0.02 0.02

FLIGNI(1,2) 0.26 0.26

FLIGNI(2,1) 0.0012 0.0012

FLIGNI(2,2) -0.0015 -0.0015

FRTC(1) 0 0

FRTC(2) 0 0

FRTC(3) 0 0

FSDETH(1) 0.2 0.2

FSDETH(2) 0.95 0.95

FSDETH(3) 0.2 0.2

FSDETH(4) 150 150

FULCAN 100 100

HIMAX 0 0

HIMON(1) 0 0

HIMON(2) 0 0

HIWSF 0 0

PLTMRF 1 1

PPDF(1) 18 30

PPDF(2) 32 45

PPDF(3) 1.2 1.0

PPDF(4) 3.0 3.0

PRAMN(1,1) 20 20

PRAMN(1,2) 30 30

PRAMX(1,1) 30 30

PRAMX(1,2) 40 80

PRBMN(1,1) 40 60

PRBMN(1,2) 0 0

PRBMX(1,1) 50 80

PRBMX(1,2) 0 0

PRDX(1) 300. 400.

RDR 0.05 0.05

RTDTMP 2 2

SNFXMX(1) 0 0

VLOSSP 0.04 0.04

Table 17—MC1 parameter file, crop.100a

a See list of parameters for definitions.

41
4.3.2 Biogeochemical parameters and variables—

accrst accumulator of C in straw removed for grass or crop (g·m-2)

acrcis(1) growing season accumulator for unlabeled C production by isotope in

forest system coarse root component (g·m-2·year-1

)

acrcis(2) growing season accumulator for labeled C production by isotope in forest

system coarse root component (g·m-2·year-1)

adefac average annual value of defac, the decomposition factor that combines

the effects of temperature and moisture

adep(1,2...) depth of soil layer 1,2... (only nlayer + 1 values used) (cm)

afbcis(1) growing season accumulator for unlabeled C production by isotope in

forest system fine branch component (g·m-2·year-1)

afbcis(2) growing season accumulator for labeled C production by isotope in forest

system fine branch component (g·m-2·year-1)

afiel(1,2...) the field capacity of soil layer 1,2... (fraction); used only if swflag = 0

afrcis(1) growing season accumulator for unlabeled C production by isotope in

forest system fine root component (g·m-2·year-1

)

afrcis(2) growing season accumulator for labeled C production by isotope in forest

system fine root component (g·m-2·year-1)

agcacc growing season accumulator for aboveground C production (g·m-2·year-1)

agcisa(2) growing season accumulator for aboveground labeled C production for

grass or crop (g·m-2)

aglcis(1) aboveground unlabeled C by isotope for grass or crop (g·m-2)

aglcis(2) aboveground labeled C by isotope for grass or crop (g·m-2)

aglcn aboveground live C:N ratio = -999 if either component = 0 for grass or crop

aglivc C in aboveground live for grass or crop (g·m-2)

aglive(1) N in aboveground live for grass or crop (g·m-2)

aglrem fraction of aboveground live that will not be affected by harvest

operations, 0 to 1

agppa intercept parameter in the equation estimating potential aboveground

biomass production for calculation of root-to-shoot ratio (used only if

frtc(1) = 0) (g·m-2·year-1)

agppb slope parameter in the equation estimating potential aboveground

biomass production calculation of root-to-shoot ratio (used only if

frtc(1) = 0)

(g·m-2·year-1) Note: agppb is multiplied by annual precipitation (cm)

alvcis(1) growing season accumulator for unlabeled C production in forest system

leaf component

alvcis(2) growing season accumulator for labeled C production in forest system

leaf component (g·m-2·year-1

)

alwcis(1) growing season accumulator for unlabeled C production in forest system

large wood component (g·m-2·year-1)

alwcis(2) growing season accumulator for labeled C production in forest system

large wood component (g·m-2·year-1)

aminrl(1) mineral N in layer 1 before uptake by plants

amt1c2 annual accumulator for surface CO

2

 loss due to microbial respiration

during litter decomposition

amt2c2 annual accumulator for soil CO

2

 loss due to microbial respiration during

litter decomposition

anerb the effect of soil anaerobic conditions on decomposition; used as a

multiplier on all belowground decomposition flows

42
aneref(1) ratio of rain to potential evapotranspiration below which there is no

negative impact of soil anaerobic conditions on decomposition

aneref(2) ratio of rain to potential evapotranspiration above which there is

maximum negative impact of soil anaerobic conditions on

decomposition

aneref(3) minimum value of the impact of soil anaerobic conditions on

decomposition; functions as a multiplier for the maximum

decomposition rate

animpt slope term used to vary the impact of soil anaerobic conditions on

decomposition flows to the passive soil organic matter pool

as11c2 annual accumulator for CO2 loss due to microbial respiration during soil

organic matter decomposition of surface som1 to som2

as21c2 annual accumulator for CO2 loss due to microbial respiration during soil

organic matter decomposition of soil som1 to som2 and som3

as2c2 annual accumulator for CO2 loss due to microbial respiration during soil

organic matter decomposition of som2 to soil som1 and som3

as3c2 annual accumulator for CO2 loss due to microbial respiration during soil

organic matter decomposition of som3 to soil som1

asmos(1,2...) soil water content of layer 1,2...(cm)

asmos

 (nlayer+1) soil water content in deep storage layer (cm)

ast1c2 annual accumulator for CO2 loss due to microbial respiration during litter

decomposition of surface structural into som1 and som2

ast2c2 annual accumulator for CO2 loss due to microbial respiration during litter

decomposition of soil structural into som1 and som2

astgc grams of C added with the addition of organic matter (g·m-2)

astlbl fraction of added C that is labeled, when C is added as a result of the

addition of organic matter, range 0 to 1

astlig lignin fraction content of organic matter, range 0 to 1

astrec(1) C:N ratio of added organic matter

avh2o(1) water available to grass or crop or tree for growth in soil profile (sum of

layers 1 through nlaypg)(cm water)

avh2o(2) water available to grass or crop or tree for survival in soil profile (sum of

all layers in profile, 1 through nlayer) (cm water)

avh2o(3) water in the first two soil layers (cm water)

awilt(1,2...) the wilting point of soil layer 1,2... (fraction); used only if swflag = 0, 5, or 6

awtl(1,2...) weighting factor for transpiration loss for layer 1,2... (only nlayer+1

values used); indicates which fraction of the availability water can be

extracted by the roots

basef the fraction of the soil water content of layer nlayer +1 lost via base flow,

0 to 1

basfc2 (savanna only) a basal factor used to calculate the N reaction; if not

running savanna, 1

basfct (savanna only) a constant used to calculate the tree basal area; equal to

(form factor * wood density * tree height); if not running savanna, set

to 1.0

bgcacc growing season accumulator for belowground C production for grass or

crop (g·m-2)

bgcisa(1) growing season accumulator for belowground unlabeled C production for

grass or crop (g·m-2)

43
bgcisa(2) growing season accumulator for belowground labeled C production for

grass or crop (g·m-2)

bglcis(1) belowground live unlabeled C for grass or crop (g·m-2)

bglcis(2) belowground live labeled C for grass or crop (g·m-2)

bglcis(2) initial value for belowground live labeled C; used only if ivauto = 0 or 2

(gC·m-2)

bglcn belowground live C:N ratio; = -999 if either component = 0 for grass or crop

bglivc C in belowground live for grass or crop (g·m-2)

bglive(1) N in belowground live for grass or crop (g·m-2)

bglrem fraction of belowground live that will not be affected by harvest

operations, 0 to 1

bgppa intercept parameter in the equation estimating potential belowground

biomass production for calculation of root-to-shoot ratio (used only if

frtc(1) = 0) (g·m-2·year-1)

bgppb slope parameter in the equation estimating potential belowground

biomass production for calculation of root-to-shoot ratio (used only if

frtc(1) = 0) (g·m-2·year-1) Note: bgppb is multiplied by annual

precipitation (cm)

bioflg flag indicating whether production should be reduced by physical

obstruction (= 0 production should not be reduced; = 1 production

should be reduced)

biok5 level of aboveground standing dead + 10 percent strucc(1) C at which

production is reduced to half maximum due to physical obstruction by

the dead material, used only when bioflg = 1 (gC·m-2)

biomax biomass level above which the minimum and maximum C:N ratios of the

new shoot increments equal pramn(*,2) and pramx(*,2) respiration (g

biomass·m-2)

bulkd bulk density of soil used to compute soil loss by erosion, wilting point,

and field capacity (kg·liter-1)

cerfor(1,2,1) minimum C:N ratio for fine roots

cerfor(1,1,1) minimum C:N ratio for leaves

cerfor(1,5,1) minimum C:N ratio for coarse roots

cerfor(1,3,1) minimum C:N ratio for fine branches

cerfor(1,4,1) minimum C:N ratio for large wood

cerfor(2,3,1) maximum C:N ratio for fine branches

cerfor(2,2,1) maximum C:N ratio for fine roots

cerfor(2,1,1) maximum C:N ratio for leaves

cerfor(2,5,1) maximum C:N ratio for coarse roots

cerfor(2,4,1) maximum C:N ratio for large wood

cerfor(3,1,1) initial C:N ratio for leaves

cerfor(3,5,1) initial C:N ratio for coarse roots

cerfor(3,2,1) initial C:N ratio for fine roots

cerfor(3,3,1) initial C:N ratio for fine branches

cerfor(3,4,1) initial C:N ratio for large wood

cgracc accumulator for grain and tuber production for grass or crop (g·m-2)

cgrain economic yield of C in grain + tubers for grass or crop (g·m-2)

cinput annual C inputs

cisgra(1) unlabeled C in grain (g·m-2) for grass or crop

cisgra(2) labeled C in grain (g·m-2) for grass or crop

clay fraction of clay in soil, range 0 to 1

44
clittr(1,2) initial value for surface labeled plant residue; used only if ivauto = 0 (g·m-2)

clittr(1,1) initial value for surface unlabeled plant residue; used only if ivauto = 0

(g·m-2)

clittr(1,1) surface unlabeled residue (g·m-2)

clittr(1,2) surface labeled residue (g·m-2)

clittr(2,1) initial value for soil unlabeled plant residue; used only if ivauto = 0 (g·m-2)

clittr(2,2) initial value for soil labeled plant residue; used only if ivauto = 0 (g·m-2)

clittr(2,1) soil unlabeled residue (g·m-2)

clittr(2,2) soil labeled residue (g·m-2)

co2cce(1,1,1) in a grass or crop system, the calculated effect on minimum C:N ratios

of doubling the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2cce(1,2,1) in a grass or crop system, the calculated effect on maximum C:N ratios of

doubling the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2cce(2,1,1) in a forest system, the calculated effect on minimum C:N ratios of

doubling the atmospheric CO2

 concentration from 350 ppm to 700 ppm

co2cce(2,2,1) in a forest system, the calculated effect on maximum C:N ratios of

doubling the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2cpr(1) in a grass or crop system, the calculated effect on production of doubling

the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2cpr(2) in a forest system, the calculated effect on production of doubling the

atmospheric CO2 concentration from 350 ppm to 700 ppm

co2crs(1) in a grass or crop system, the calculated effect on root-to-shoot ratio of

doubling the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2crs(2) in a forest system, the calculated effect on root-to-shoot ratio of doubling

the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2ctr(1) in a grass or crop system, the calculated effect on transpiration rate of

doubling the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2ctr(2) in a forest system, the calculated effect on transpiration rate of doubling

the atmospheric CO2 concentration from 350 ppm to 700 ppm.

co2ice(1,1,1) in a grass or crop system, the effect on minimum C:N ratio of doubling

the atmospheric CO2 concentration from 350 ppm to 700 ppm

co2ice(1,2,1) in a grass or crop system, the effect on maximum C:N ratio of doubling

the atmospheric CO2

co2ice(2,2,1) in a forest system, the effect on maximum C:N ratio of doubling the

atmospheric CO2

co2ice(2,1,1) in a forest system, the effect on minimum C:N ratio of doubling the

atmospheric CO2

co2ipr(1) in a grass or crop system, the effect on plant production of doubling the

atmospheric CO2 concentration from 350 ppm to 700 ppm

co2ipr(2) in a forest system, the effect on plant production of doubling the

atmospheric CO2 concentration

co2irs(1) in a grass or crop system, the effect on root-to-shoot ratio of doubling the

atmospheric CO2

co2irs(2) in a forest system, the effect on root-to-shoot ratio of doubling the

atmospheric CO2 concentration

co2itr(1) in a grass or crop system, the effect on transpiration rate of doubling the

atmospheric CO2 concentration

co2itr(2) in a forest system, the effect on transpiration rate of doubling the

atmospheric CO2 concentration

co2rmp flag indicating whether CO2 effect should be 0 or 1 (= 0 step function; = 1

ramp function)

45
cproda annual accumulator of C production in grass or crop + forest = NPP (net

primary production; g·m-2·year-1)

cprodc total monthly C production for grass or crop (g·m-2·month-1)

cprodf total monthly C production for forest (g·m-2·month-1)

creta annual accumulator of C returned to system during grazing/fire for grass

or crop (g·m-2·year-1)

crmvst amount of C removed through straw during harvest for grass or crop

(g·m-2·month-1)

crootc C in forest system coarse root component (g·m-2)

croote(1) N in forest system coarse root component (g·m-2)

croote(1) initial value for N in a forest system coarse root component (gN·m-2)

crprtf(1) fraction of N retranslocated from grass or crop leaves at death, range 0

to 1

crpstg(1) retranslocation N storage pool for grass or crop (g·m-2)

crpval a numerical representation of the current crop

crtacc growing season accumulator for C production in forest system coarse

root component (g·m-2·year-1)

crtcis(1) initial value for unlabeled C in forest system coarse root component

(gC·m-2)

crtcis(1) unlabeled C in forest system coarse root component (g·m-2)

crtcis(2) labeled C in forest system coarse root component (g·m-2)

crtcis(2) initial value for labeled C in forest system coarse root component (gC·m-2)

csrsnk(1) unlabeled C source/sink (g·m-2)

csrsnk(2) labeled C source/sink (g·m-2)

cultra(1) fraction of aboveground live transferred to standing dead, range 0 to 1

cultra(2) fraction of aboveground live transferred to surface litter, range 0 to 1

cultra(3) fraction of aboveground live transferred to the top soil layer, range 0 to 1

cultra(4) fraction of standing dead transferred to surface litter, range 0 to 1

cultra(5) fraction of standing dead transferred to top soil layer, range 0 to 1

cultra(6) fraction of surface litter transferred to top soil layer, range 0 to 1

cultra(7) fraction of roots transferred to top soil layer, range 0 to 1

damr(1,1) fraction of surface N absorbed by residue, range 0 to 1

damr(2,1) fraction of soil N absorbed by residue, range 0 to 1

damrmn(1) minimum C:N ratio allowed in residue after direct absorption

dblit delta 13C value for belowground litter for stable isotope labeling

dec1(1) maximum surface structural decomposition rate

dec1(2) maximum soil structural decomposition rate

dec2(1) maximum surface metabolic decomposition rate

dec2(2) maximum soil metabolic decomposition rate

dec3(1) maximum decomposition rate of surface organic matter with active

turnover

dec3(2) maximum decomposition rate of soil organic matter with active turnover

dec4 maximum decomposition rate of soil organic matter with slow turnover

dec5 maximum decomposition rate of soil organic matter with intermediate

turnover

decid = 0 if forest is coniferous; = 1 if forest is deciduous

deck5 available soil water content at which shoot and root death rates are half

maximum (cm)

decw1 decomposition rate for wood1 (dead fine branch) (/year)

decw2 decomposition rate for wood2 (dead large wood) (/year)

46
decw3 decomposition rate for wood3 (dead coarse root) (/year)

defac decomposition factor based on temperature and moisture

drain the fraction of excess water lost by drainage; indicates whether a soil is

sensitive for anaerobiosis

edepth depth of the single soil layer where C, N dynamics are calculated (only

affects C, N loss by erosion)

efrgrn(1) fraction of the aboveground N which goes to grain, range 0 to 1

egracc(1) accumulator of N in grain + tuber production for grass or crop (g·m-2)

egrain(1) economic yield of N in grain + tubers for grass or crop (g·m-2)

elimit indicator of the limiting element (= 1 if N is the limiting element)

elitst effect of litter on soil temperature relative to live and standing dead

biomass

enrich the enrichment factor for soil organic matter (SOM) losses

epnfa(1) intercept value for determining the effect of annual precipitation on

atmospheric N-fixation (wet and dry deposition) (g·m-2·year-1)

epnfa(2) slope value for determining the effect of annual precipitation on

atmospheric N-fixation (wet and dry deposition) (g·m-2·year-1·cm

precipitation-1)

epnfs(1) intercept value for determining the effect of annual precipitation on

nonsymbiotic soil N-fixation; not used if nsnfix = 1 (g·m-2·year-1)

epnfs(2) slope value for determining the effect of annual precipitation on

nonsymbiotic soil N-fixation; not used if nsnfix = 1 (g·m-2·year-1·

precipitation-1)

eprodc(1) actual monthly N uptake for grass or crop (g·m-2·month-1)

eprodf(1) actual monthly N uptake in forest system (g·m-2·month-1)

ereta(1) annual accumulator of N returned to system during grazing or fire for

grass or crop (g·m-2·year-1)

ermvst(1) amount of N removed as straw during harvest for grass or crop

(g·m-2·month-1)

esrsnk(1) N source or sink (g·m-2)

eupacc(1) growing season accumulator for N uptake by grass, crop, or tree (g·m-2)

eupaga(1) aboveground growing season accumulator for N uptake by plants for

grass or crop (g·m-2)

eupbga(1) belowground growing season accumulator for N uptake by plants for

grass or crop (g·m-2)

eupprt(1,1) growing season accumulator for N uptake by forest leaf component (g·m-2)

eupprt(2,1) growing season accumulator for N uptake by forest fine roots component

(g·m-2)

eupprt(3,1) growing season accumulator for N uptake by forest fine branches

component (g·m-2)

eupprt(4,1) growing season accumulator for N uptake by forest large wood

component (g·m-2)

eupprt(5,1) growing season accumulator for N uptake by forest coarse roots

component (g·m-2)

evap monthly evaporation (cm)

evntyp = 0 for cutting event; = 1 for fire event

fallrt fall rate (fraction of standing dead that falls each month), range 0 to 1

favail(1) fraction of N available per month to plants, range 0 to 1

fbracc growing season accumulator for C production in forest system fine branch

component (g·m-2·year-1)

47
fbrchc C in forest system fine branch component (g·m-2

)

fbrche(1) initial value for N in a forest system fine branch component (gN·m-2)

fbrche(1) N in forest system fine branch component (g·m-2

)

fbrcis(1) initial value for unlabeled C in forest system fine branch component

(gC·m-2)

fbrcis(2) initial value for labeled C in forest system fine branch component (gC·m-2)

fbrcis(1) unlabeled C in forest system fine branch component (g·m-2)

fbrcis(2) labeled C in forest system fine branch component (g·m-2)

fcacc growing season accumulator for C production in forest system

(g·m-2·year-1)

fcfrac(1,1) C allocation fraction of new leaves for juvenile forest, range 0 to 1

fcfrac(1,2) C allocation fraction of old leaves for mature forest, range 0 to 1

fcfrac(2,2) C allocation fraction of old fine roots for mature forest, range 0 to 1

fcfrac(2,1) C allocation fraction of new fine roots for juvenile forest, range 0 to 1

fcfrac(3,1) C allocation fraction of new fine branches for juvenile forest, range 0 to 1

fcfrac(3,2) C allocation fraction of old fine branches for mature forest, range 0 to 1

fcfrac(4,2) C allocation fraction of old large wood for mature forest, range 0 to 1

fcfrac(4,1) C allocation fraction of new large wood for juvenile forest, range 0 to 1

fcfrac(5,2) C allocation fraction of old coarse roots for mature forest, range 0 to 1

fcfrac(5,1) C allocation fraction of new coarse roots for juvenile forest, range 0 to 1

fd(1) fraction of fine root component that dies, range 0 to 1

fd(2) fraction of coarse root component that dies, range 0 to 1

fdfrem(2) fraction of surface litter removed by a fire event, range 0 to 1

fdgrem fraction of standing dead removed by a grazing event, range 0 to 1

feramt(1) amount of N to be added (gN·m-2

)

fertot(1) accumulator for N fertilizer

ffcret fraction of C in the burned aboveground material that is moved to surface

litter by a fire event

fleach(1) intercept value for a normal month to compute the fraction of mineral N

that will leach to the next layer when there is a saturated water flow;

normal leaching is a function of sand content

fleach(2) slope value for a normal month to compute the fraction of mineral N that

will leach to the next layer when there is a saturated water flow;

normal leaching is a function of sand content

fleach(3) leaching fraction multiplier for N to compute the fraction of mineral N that

will leach to the next layer when there is a saturated water flow;

normal leaching is a function of sand content, range 0 to 1

flfrem fraction of live shoots removed by a fire event, range 0 to 1

fdfrem(1) fraction of standing dead plant material removed by a fire event, range 0

to 1

flghrv = 1 if the grain is to be harvested; = 0 otherwise

flgrem fraction of live shoots removed by a grazing event, range 0 to 1

fligni(1,2) intercept for equation to predict lignin content fraction based on annual

rainfall for belowground material, range 0 to 1

fligni(1,1) intercept for equation to predict lignin content fraction based on annual

rainfall for aboveground material, range 0 to 1

fligni(2,2) slope for equation to predict lignin content fraction based on annual

rainfall for belowground material, range 0 to 1

fligni(2,1) slope for equation to predict lignin content fraction based on annual

rainfall for aboveground material, range 0 to 1

fnue(1) effect of fire on increase in maximum C:N ratio of shoots

48
fnue(2) effect of fire on increase in maximum C:N ratio of roots

forrtf(1) fraction of N retranslocated from green forest leaves at death, range 0 to 1

forstg(1) retranslocation N storage pool for forest

fret(1) fraction of N in the burned aboveground material removed by a fire vent,

0 to 1

frootc C in forest system fine root component (g·m-2)

froote(1) initial value for N in a forest system fine root component (gN·m-2)

froote(1) N in forest system fine root component (g·m-2)

frstc sum of C in forest system live components (g·m-2) (rleavc + frootc +

fbrchc + rlwodc + crootc)

frste(1) sum of N in forest system live components (g·m-2) [rleave(1) + froote(1)

+ fbrche(1) + rlwode(1) + croote(1)]

frtacc growing season accumulator for C production in forest system fine root

component (g·m-2)

frtc(1) initial fraction of C allocated to roots; Great Plains equation based on

precipitation, set to 0, range 0 to 1

frtc(2) final fraction of C allocated to roots, range 0 to 1

frtc(3) time after planting (months with soil temperature greater than rtdtmp)

when the final value is reached; must not equal 0

frtcis(1) initial value for unlabeled C in forest system fine root component (gC·m-2)

frtcis(1) unlabeled C in forest system fine root component (g·m-2)

frtcis(2) initial value for labeled C in forest system fine root component (gC·m-2)

frtcis(2) labeled C in forest system fine root component (g·m-2)

frtsh additive effect of burning on root to shoot ratio

fsdeth(1) maximum shoot death rate at very dry soil conditions (fraction/month);

for getting the monthly shoot death rate, this fraction is multiplied by a

reduction factor, depending on the soil water status, range 0 to 1

fsdeth(2) fraction of shoots that die during senescence month; must be greater

than or equal to 0.4, range 0 to 1

fsdeth(3) additional fraction of shoots that die when aboveground live C is greater

than fsdeth(4), range 0 to 1

fsdeth(4) the level of aboveground C above which shading occurs and shoot

senescence increases

fsysc total C in forest system: sum of soil organic matter, trees, dead wood,

forest litter

fsyse(1) total N in forest system: sum of soil organic matter, trees, dead wood,

forest litter

fulcan value of aglivc at full canopy cover, above which potential production is

not reduced

fwloss(1) scaling factor for interception and evaporation of precipitation by live and

standing dead biomass, range 0 to 1

fwloss(2) scaling factor for bare soil evaporation of precipitation, range 0 to 1

fwloss(3) scaling factor for transpiration water loss

fwloss(4) scaling factor for potential evapotranspiration

fxmca intercept for effect of biomass on nonsymbiotic soil N-fixation; used only

when nsnfix = 1

fxmcb slope control for eff. of biomass on nonsymbiotic soil N-fixation; used

only when nsnfix= 1

fxmxs maximum monthly nonsymbiotic soil N-fixation rate (reduced by effect of

N:P ratio, used when nsnfix = 1)

49
fxnpb N/P control for N-fixation based on availability of top soil layer (used when

nsnfix = 1)

gfcret fraction of consumed C that is excreted in faeces and urine, range 0 to 1

gremb grazing effect multiplier for grzeff types 4, 5, and 6

gromin(1) gross mineralization of N

grzeff effect of grazing on production (= 0 grazing has no direct effect on

production; = 1 linear impact on agp (agppa+agppb); = 2 quadratic

impact on agp and root-to-shoot ratio; = 3 quadratic impact on root-toshoot ratio; = 4 linear impact on root-to-shoot ratio; = 5 quadratic

impact on agp and linear impact on root-to-shoot ratio; = 6 linear

impact on agb and root-to-shoot ratio)

harmth = 0 in nonharvest months; = 1 in a harvest month

hi harvest index (cgrain/aglivc at harvest) for grass or crop

hibg fraction of roots that will be harvested, range 0 to 1

himax harvest index maximum (fraction of aboveground live C in grain), range 0

to 1

himon(1) number of months before harvest in which to begin accumulating water

stress effect on harvest index

himon(2) number of months before harvest in which to stop accumulating water

stress effect on harvest index, range 0 to 12

hiwsf harvest index water stress factor (= 0 no effect of water stress; = 1 no

grain yield with maximum water stress)

idef flag for method of computing water effect on decomposition (= 1 option

using the relative water content of soil [0-15 cm]; = 2 ratio option

[rainfall/potential evaporation rate])

irract actual amount of irrigation (cm water/month)

irramt amount of water to apply regardless of soil water status (cm)

irraut amount of water to apply automatically when auirri = 2 (cm)

irrtot accumulator for irrigation (cm water)

ivauto use Burke’s equations to initialize soil C pools (= 0 the user has supplied

the initial values; = 1 initialize using the grassland soil parameters; = 2

initialize using the crop soil parameters)

klai large wood mass (gC·m-2) at which half of the theoretical maximum leaf

area (maxlai) is achieved

laitop parameter determining relation between LAI and forest production

leafdr

 (1,2,...,12) monthly death rate fraction for leaves, range 0 to 1

lhzcac accumulator for C inputs to 0-20 cm layer from the lower horizon pools

associated with soil erosion (g·m-2)

lhzeac(1) accumulator for N inputs to 0-20 cm layer from the lower horizon pools

associated with soil erosion (g·m-2)

lhzf(1) lower horizon factor for active pool; = fraction of active pool (som1cI(2,*))

used in computation of lower horizon pool sizes for soil erosion

routines

lhzf(2) lower horizon factor for slow pool; = fraction of slow pool (som2cI(*)) used

in computation of lower horizon pool sizes for soil erosion routines

lhzf(3) lower horizon factor for passive pool; = fraction of passive pool

(som3cI(*)) used in computation of lower horizon pool sizes for soil

erosion routines

maxlai theoretical maximum leaf area index achieved in mature forest

50
maxldr multiplier for effect of N availability on leaf death rates (continuously

growing forest systems only); a ratio between death rate at unlimited

vs. severely limited N status, range 0-1

metabc(1) metabolic C in surface litter (g·m-2)

metabc(2) metabolic C in belowground litter (g·m-2)

metabe(1,1) metabolic N in surface litter (g·m-2)

metabe(2,1) metabolic N in belowground litter (g·m-2)

metcis(1,1) metabolic surface litter unlabeled C (g·m-2)

metcis(1,2) metabolic surface litter labeled C (g·m-2)

metcis(2,2) metabolic belowground litter labeled C (g·m-2)

metcis(2,1) metabolic belowground litter unlabeled C (g·m-2)

metmnr(1,1) net mineralization for N for aboveground metabolic litter

metmnr(2,1) net mineralization for N for belowground metabolic litter

minerl(1,...1) initial value for mineral N for layer 1,... (gN·m-2)

minerl(1,...1) mineral N content for layer 1,... (g·m-2)

minerl(nlayer

 +1,1) deep storage layer for leached N

minlch critical water flow for leaching of minerals (cm of water leached below

30 cm soil depth)

mt1c2(1) accumulator for unlabeled surface CO2 loss due to microbial respiration

during litter decomposition

mt1c2(2) accumulator for labeled surface CO2 loss due to microbial respiration

during litter decomposition

mt2c2(1) accumulator for unlabeled soil CO2 loss due to respiration

mt2c2(2) accumulator for labeled soil CO2 loss due to respiration

nfix amount of symbiotic N-fixation (g·m-2/month)

nfixac accumulator for amount of symbiotic N-fixation (g·m-2/month)

nlayer number of soil layers in water model (max 9); used only to calculate the

amount of water available for survival of the plant

nlaypg number of soil layers in the top level of the water model; determines

avh2o(1), used for growth and root death, range 1 to 10

nsnfix =1 if nonsymbiotic N-fixation should be based on N:P ratio in mineral

pool; otherwise nonsymbiotic N-fixation is based on annual

precipitation

ntspm number of time steps per month for the decomposition submodel

omlech(1) intercept for the effect of sand on leaching of organic compounds

omlech(2) slope for the effect of sand on leaching of organic compounds

omlech(3) the amount of water (cm) that needs to flow out of water layer 2 to

produce leaching of organics

p1co2a(1) intercept parameter that controls flow from surface organic matter with

fast turnover to CO2

 (fraction of C lost to CO2 when there is no sand in

the soil)

p1co2a(2) intercept parameter that controls flow from soil organic matter with fast

turnover to CO2 (fraction of C lost to CO2 when there is no sand in the

soil)

p1co2b(1) slope parameter that controls flow from surface organic matter with fast

turnover to CO2 (slope is multiplied by the fraction of sand content in

the soil)

p1co2b(2) slope parameter that controls flow from soil organic matter with fast

turnover to CO2 (slope is multiplied by the fraction of sand content in

the soil)

51
p2co2 controls flow from soil organic matter with intermediate turnover to CO

2

(fraction of C lost as CO

2

 during decomposition)

p3co2 controls flow from soil organic matter with slow turnover rate to CO

2

(fraction of C lost as CO

2

 during decomposition)

pabres amount of residue that will give maximum direct absorption of N (gC·m-2)

parent(1) initial N value for parent material (gN·m-2)

parent(1) parent material N (g·m-2)

pcemic(1,1) maximum C:N ratio for surface microbial pool

pcemic(2,1) minimum C:N ratio for surface microbial pool

pcemic(3,1) minimum N content of decomposed aboveground material, above which

the C:N ratio of the surface microbes equals pcemic(2,*)

peftxa intercept parameter for regression equation to compute the effect of soil

texture on the microbe decomposition rate (the effect of texture when

there is no sand in the soil)

peftxb slope parameter for the regression equation to compute the effect of soil

texture on the microbe decomposition rate; the slope is multiplied by

the sand content fraction

pet monthly potential evapotranspiration (cm)

petann annual potential evapotranspiration (cm)

pligst(1) effect of lignin on surface structural or fine branch and large wood

decomposition

pligst(2) effect of lignin on soil structural or coarse root decomposition

pltmrf planting month reduction factor to limit seedling growth; should be 1.0 for

grass, range 0-1

pmco2(1) surface; controls flow from surface metabolic to CO

2

 (fraction of C lost as

CO

2

 during decomposition)

pmco2(2) soil; controls flow from soil metabolic to CO

2

 (fraction of C lost as CO

2

during decomposition)

pmnsec(1) slope for N; controls the flow from mineral to secondary N (yr-1)

pmntmp effect of biomass on minimum surface temperature

pmxbio maximum dead biomass (standing dead + 10 percent litter) level for soil

temperature calculation and for calculation of the potential negative

effect on plant growth of physical obstruction by standing dead and litter

pmxtmp effect of biomass on maximum surface temperature

pparmn(1) N; controls the flow from parent material to mineral compartment (fraction

of parent material flowing to mineral N, P, and S)

ppdf(1) optimum temperature for production for parameterization of a Poisson

density function curve to simulate temperature effect on growth

ppdf(2) maximum temperature for production for parameterization of a Poisson

density function curve to simulate temperature effect on growth

ppdf(1) optimum temperature for production for parameterization of a Poisson

density function curve to simulate temperature effect on growth

ppdf(2) maximum temperature for production for parameterization of a Poisson

density function curve to simulate temperature effect on growth

ppdf(3) left curve shape for parameterization of a Poisson density function curve

to simulate temperature effect on growth

ppdf(3) left curve shape for parameterization of a Poisson density function curve

to simulate temperature effect on growth

ppdf(4) right curve shape for parameterization of a Poisson density function curve

to simulate temperature effect on growth

52
ppdf(4) right curve shape for parameterization of a Poisson density function curve

to simulate temperature effect on growth

pprpts(1) the minimum ratio of available water to PET that would completely limit

production, assuming water content = 0, range 0 to 1

pprpts(2) the effect of water content on the intercept; allows the user to increase

the value of the intercept and thereby increase the slope of the line

pprpts(3) the lowest ratio of available water to PET at which there is no restriction

on production, range 0 to 1

pramn(1,1) minimum C:N ratio with 0 biomass

pramn(1,2) minimum C:N ratio with biomass = biomax

pramx(1,1) maximum C:N ratio with 0 biomass

pramx(1,2) maximum C:N ratio with biomass = biomax

prbmn(1,1) intercept parameter for computing minimum C:N ratio for belowground

matter as a linear function of annual precipitation

prbmn(1,2) slope parameter for computing minimum C:N ratio for belowground matter

as a linear function of annual precipitation

prbmx(1,1) intercept parameter for computing maximum C:N ratios for belowground

matter as a linear function of annual precipitation

prbmx(1,2) slope parameter for computing maximum C:N ratios for belowground

matter as a linear function of annual precipitation

prcann annual precipitation (cm)

prcfal fallow period precipitation; the amount of rain that falls during the months

after harvest until the month before the next planting (cm)

prcskw

 (1,2...,12) skewness value for January, February,..., December precipitation

prcstd

 (1, 2,...,12) standard deviations for January, February,..., December precipitation

value (cm·month-1)

prdx(1) potential aboveground monthly production for crops (gC·m-2)

prdx(2) gross forest production

prdx(3) maximum forest production excluding respiration

precip

 (1,2,...,12) precipitation for January, February,..., December (cm/month)

ps1co2(1) surface; controls amount of CO2 loss when structural decomposes to

som1c

ps1co2(2) soil; controls amount of CO2

 loss when structural decomposes to som1c

ps1s3(1) intercept for flow from soil organic matter with fast turnover to som with

slow turnover (fraction of C from som1c to som3c)

ps1s3(2) slope for the effect of clay on the control of the flow from soil organic

matter with fast turnover to som with slow turnover (fraction of C from

som1c to som3c)

ps2s3(1) slope value that controls flow from soil organic matter with intermediate

turnover to soil organic matter with slow turnover (fraction of C from

som2c to som3c)

ps2s3(2) intercept value that controls flow from soil organic matter with

intermediate turnover to soil organic matter with slow turnover (fraction

of C from som2c to som3c)

psecmn(1) N; controls the flow from secondary to mineral N

ptagc growing season accumulator for potential aboveground C production for

grass or crop (g·m-2·y-1)

53
ptbgc growing season accumulator for potential belowground C production for

grass or crop (g·m-2·y-1)

pttr potential transpiration water loss for the month

rad1p(1,1) intercept used to calculate addition term for C:N ratio of slow som formed

from surface active pool

rad1p(2,1) slope used to calculate addition term for C:N ratio of slow som formed

from surface active pool

rad1p(3,1) minimum allowable C:N used to calculate addition term for C:N ratio of

slow som formed from surface active pool

rain monthly precipitation (cm)

rcelit(1,1) initial C:N ratio for surface litter

rcelit(2,1) initial C:N ratio for soil litter

rces1(1,1) initial C:N ratio in surface organic matter with fast turnover (active som)

rces1(2,1) initial C:N ratio in soil organic matter with fast turnover (active som)

rces2(1) initial C:N ratio in soil organic matter with intermediate turnover (slow som)

rces3(1) initial C:N ratio in soil organic matter with slow turnover (passive som)

rcestr(1) C:N ratio for structural material (fixed parameter value)

rdr maximum root death rate at very dry soil conditions (fraction/month); for

getting the monthly root death rate, this fraction is multiplied by a

reduction factor, depending on the soil water status, range 0 to 1

rtdtmp physiological shutdown temperature for root death and change in shootto-root ratio

relyld relative yield for grass, crop, or tree production

remf(1) fraction of leaf live component returned, range 0 to 1

remf(2) fraction of fine branch live component returned, range 0 to 1

remf(3) fraction of large wood live component returned, range 0 to 1

remf(4) fraction of fine branch dead component returned, range 0 to 1

remf(5) fraction of large wood dead component returned, range 0 to 1

remwsd fraction of the remaining residue that will be left standing, range 0 to 1

resp(1) annual unlabeled CO

2 respiration from decomposition (g·m-2

)

resp(2) annual labeled CO

2 respiration from decomposition (g·m-2

)

retf(1,1) fraction of C returned in the live leaf component, range 0 to 1

retf(1,2) fraction of N returned in the live leaf component, range 0 to 1

retf(2,1) fraction of C returned in the fine branch component, range 0 to 1

retf(2,2) fraction of N returned in the fine branch component, range 0 to 1

retf(3,2) fraction of N returned in the large wood component, range 0 to 1

retf(3,1) fraction of C returned in the large wood component, range 0 to 1

rictrl root impact control term used by rtimp; used for calculating the impact of

root biomass on nutrient availability

riint root impact intercept used by rtimp; used for calculating the impact of

root biomass on nutrient availability

rleavc C in forest system leaf component (g·m-2)

rleave(1) N in forest system leaf component (g·m-2)

rlvacc growing season accumulator for C production in forest

rlvcis(1) unlabeled C in forest system leaf component (g·m-2)

rlwacc growing season accumulator for C production in forest system large

wood component (g·m-2·y-1)

rlwcis(1) unlabeled C in forest system large wood component (g·m-2)

rlwodc C in forest system large wood component (g·m-2)

rlwode(1) N in forest system large wood component (g·m-2)

rmvstr fraction of the aboveground residue that will be removed, range 0 to 1

54
rsplig fraction of lignin flow (in structural decomposition) lost as CO2

, range 0 to 1

rwcf(1,2...) relative water content for layer 1,2...

rwcf(1,2...) initial relative water content for layer 1,2...

s11c2(1) accumulator for unlabeled CO2 loss due to microbial respiration during

soil organic matter decomposition of surface som1c to som2c

s11c2(2) accumulator for labeled CO2 loss due to microbial respiration during soil

organic matter decomposition of surface som1c to som2c

s1mnr(1,1) net mineralization for N for surface microbes som1e(1,1)

s1mnr(2,1) net mineralization for N for active pool som1e(2,1)

s21c2(1) accumulator for unlabeled CO2 loss due to microbial respiration during

soil organic matter decomposition of soil som1c to som2c and som3c

s21c2(2) accumulator for labeled CO2 loss due to microbial respiration during soil

organic matter decomposition of soil som1c to som2c and som3c

s2c2(1) accumulator for unlabeled CO2 loss due to microbial respiration during

soil organic matter decomposition of som2c to soil som1c and som3c

s2c2(2) accumulator for labeled CO2 loss due to microbial respiration during soil

organic matter decomposition of som2c to soil som1c and som3c

s2mnr(1) net mineralization for N for slow pool som2e(1)

s3c2(1) accumulator for unlabeled CO2 loss due to microbial respiration during

soil organic matter decomposition of som3c to soil som1c

s3c2(2) accumulator for labeled CO2 loss due to microbial respiration during soil

organic matter decomposition of som3c to soil som1c

s3mnr(1) net mineralization for N for passive pool som3e(1)

sand fraction of sand in soil, range 0 to 1

sapk parameter controlling ratio of sapwood to total stem wood, expressed as

gC·m-2; equal to both the large wood mass (rlwodc) at which half of

large wood is sapwood, and the theoretical maximum sapwood mass

achieved in mature forest

sclosa accumulated C lost from soil organic matter by erosion (total C for entire

simulation) (g·m-2)

scloss total C loss from soil organic matter by erosion for current month (g·m-2)

sdrema annual accumulator of C removed from standing dead during grazing or

fire for grass or crop (g·m-2)

sdrmae(1) annual accumulator of N removed from standing dead during grazing or

fire for grass or crop (g·m-2)

sdrmai(1) annual accumulator of unlabeled C removed from standing dead during

grazing or fire for grass or crop (g·m-2)

sdrmai(2) annual accumulator of labeled C removed from standing dead during

grazing or fire for grass or crop (g·m-2)

secndy(1) initial N value for secondary N (gN·m-2)

secndy(1) secondary N (g·m-2)

seed random number generator seed value

shrema annual accumulator of C removed from shoots during grazing or fire for

grass or crop (g·m-2)

shrmae(1) annual accumulator of N removed from shoots during grazing or fire for

grass or crop (g·m-2)

shrmai(2) annual accumulator of labeled C removed from shoots during grazing or

fire for grass or crop (g·m-2)

silt fraction of silt in soil, range 0 to 1

sitlat latitude of model site (deg) (for reference only)

55
sitlng longitude of model site (deg) (for reference only)

sitpot (savanna only) site potential; the N fraction

snfxac(1) annual accumulator for symbiotic N-fixation for crop system

snfxac(2) annual accumulator for symbiotic N-fixation for forest system

snfxmx(1) symbiotic N-fixation maximum for grass or crop (gN fixed/gC new growth)

snfxmx(2) symbiotic N-fixation maximum for forest (gN fixed/gC new growth)

snlq liquid water in the snow pack (cm of water)

snow snow pack water content (cm of water) output.def

soilnm(1) annual accumulator for net mineralization of N in soil compartments (soil

organic matter + belowground litter + dead coarse roots) (g·m-2

)

som1c(1) C in surface microbe pool (g·m-2)

som1c(2) C in active soil organic matter (g·m-2)

som1ci(1,2) initial value for labeled C in surface organic matter with fast turnover;

used only if ivauto = 0 (gC·m-2

)

som1ci(1,1) initial value for unlabeled C in surface organic matter with fast turnover;

used only if ivauto = 0 (gC·m-2)

som1ci(1,2) labeled C in surface microbe pool (g·m-2)

som1ci(1,1) unlabeled C in surface microbe pool (g·m-2)

som1ci(2,2) initial value for labeled C in soil organic matter with fast turnover; used

only if ivauto = 0 (gC·m-2)

som2ci(1) initial value for unlabeled C in soil organic matter with intermediate

turnover; used only if ivauto = 0 (gC·m-2)

som2ci(2) initial value for labeled C in soil organic matter with intermediate turnover;

used only if ivauto = 0 (gC·m-2)

som1ci(2,1) initial value for unlabeled C in soil organic matter with fast turnover; used

only if ivauto = 0 (gC·m-2)

som1ci(2,1) unlabeled C in active soil organic matter (g·m-2)

som1ci(2,2) labeled C in active soil organic matter with fast turnover rate (g·m-2)

som1e(1,1) N in surface microbe pool (g·m-2)

som1e(2,1) N in active soil organic matter (g·m-2)

som2c C in slow pool soil organic matter (g·m-2)

som2ci(1) unlabeled C in slow pool soil organic matter (g·m-2)

som2ci(2) labeled C in slow pool soil organic matter (g·m-2)

som2e(1) N in slow pool soil organic matter (g·m-2)

som3c C in passive soil organic matter (g·m-2)

som3ci(2) initial value for labeled C in soil organic matter with slow turnover; used

only if ivauto = 0 (gC·m-2

)

som3ci(2) labeled C in passive soil organic matter (g·m-2)

som3e(1) N in passive soil organic matter (g·m-2)

somsc sum of labeled and unlabeled C from som1c, som2c, and som3c (g·m-2)

somsci(1) sum of unlabeled C in som1c, som2c, and som3c

somsci(2) sum of labeled C in som1c, som2c, som3c

somse(1) sum of N in som1e, som2e, and som3e (g·m-2)

somtc total soil C including belowground structural and metabolic (g·m-2)

somtci(1) total unlabeled C in soil including belowground structural + metabolic

somtci(2) total labeled C in soil including belowground structural + metabolic

somte(1) total N in soil organic matter including belowground structural + metabolic

spl(1) intercept parameter for metabolic (vs. structural) split, range 0 to 1

spl(2) slope parameter for metabolic split (fraction metabolic is a function of

lignin to N ratio), range 0 to 1

56
st1c2(1) accumulator for unlabeled CO2

 loss due to microbial respiration during

litter decomposition of surface structural into som1c and som2c

st2c2(1) accumulator for unlabeled CO2 loss due to microbial respiration during

litter decomposition of soil structural into som1c and som2c

stdcis(1) initial value for standing dead unlabeled C; used only if ivauto = 0 (gC·m-2)

stdcis(1) unlabeled C in standing dead for grass or crop (g·m-2)

stdedc C in standing dead material for grass or crop (g·m-2)

stdede(1) initial value for N in standing dead; used only if ivauto = 0 (gN·m-2)

stdede(1) N in standing dead for grass or crop (g·m-2)

stemp average soil temperature (°C)

stormf the fraction of flow from NLAYER to NLAYER+1 which goes into storm

flow, 0-1

strcis(1,1) unlabeled surface litter structural C (g·m-2)

strcis(2,1) unlabeled belowground litter structural C (g·m-2)

stream(1) cm water of stream flow (base flow + storm flow)

stream(2) N from mineral leaching of stream flow (base flow + storm flow) (g·m-2)

stream(5) C from organic leaching of stream flow (base flow + storm flow) (g·m-2)

stream(6) N from organic leaching of stream flow (base flow + storm flow) (g·m-2)

strlig(1) lignin content of surface structural residue

strlig(2) lignin content of soil structural residue

strmax(1) maximum amount of structural material in surface layer that will

decompose (gC·m-2)

strmax(2) maximum amount of structural material belowground that will decompose

(gC·m-2)

strmnr(1,1) net mineralization for N for surface structural litter

strmnr(2,1) net mineralization for N for belowground structural litter

strucc(1) surface litter structural C (g·m-2)

strucc(2) belowground litter structural C (g·m-2)

struce(1,1) surface litter structural N (g·m-2)

struce(2,1) belowground litter structural N (g·m-2)

sumnrs(1) annual accumulator for net mineralization of N from all compartments

except structural and wood (g·m-2·y-1)

sumrsp monthly maintenance respiration in the forest system (g·m-2)

swflag flag indicating the source of the values for awilt and afield, either from

actual data from the site.100 file or from equationsfrom Gupta and

Larson (1979) or Rawls and others (1982).

 swflag = 0 use actual data from the site.100 file

 swflag = 1 use G & L for both awilt (-15 bar) and afiel (-0.33 bar)

 swflag = 2 use G & L for both awilt (-15 bar) and afiel (-0.10 bar)

 swflag = 3 use Rawls for both awilt (-15 bar) and afiel (-0.33 bar)

 swflag = 4 use Rawls for both awilt (-15 bar) and afiel (-0.10 bar)

 swflag = 5 use Rawls for afiel (-0.33 bar) with actual data for awilt

 swflag = 6 use Rawls for afiel (-0.10 bar) with actual data for awilt

swold labeled C value for forest system fine root component (g·m-2)

tave average air temperature (°C)

tcnpro total C:N ratio for grass, crop, or tree production

tcrem total C removed during forest removal events (g·m-2)

terem(1) total N removed during forest removal events (g·m-2)

tmax maximum temperature for decomposition (°C)

tmelt(1) minimum temperature above which at least some snow will melt

tmelt(2) ratio between degrees above the minimum and cm of snow that will melt

57
tminrl(1) total mineral N summed across layers (g·m-2

)

tmn2m

 (1,2,.,12) January, February,..., December minimum temperature at 2 meters (°C)

tmx2m

 (1,2,.,12) January, February,..., December maximum temperature at 2 meters (°C)

tnetmn(1) annual accumulator of net mineralization for N from all compartments

(g·m-2·y-1

)

tomres(1) total unlabeled C in soil, belowground, and aboveground litter

tomres(2) total labeled C in soil, belowground, and aboveground litter

topt optimum temperature for decomposition (°C)

totalc total C including source or sink

totale(1) total N including source or sink

totc minimum annual total nonliving C, where total is som1c(SOIL) +

som1c(SRFC) + som2c + som3c + strucc(SOIL) + strucc(SRFC)

+ metabc(SOIL) + metabc(SRFC)

tran monthly transpiration (cm)

tshl shape parameter to left of the optimum temperature (for decomposition)

tshr shape parameter to right of the optimum temperature

varat1(1,1) maximum C:N ratio for material entering som1c

varat1(2,1) minimum C:N ratio for material entering som1c

varat1(3,1) amount N present when minimum ratio applies

varat2(1,1) maximum C:N ratio for material entering som2c

varat2(2,1) minimum C:N ratio for material entering som2c

varat2(3,1) amount N present when minimum ratio applies

varat3(1,1) maximum C:N ratio for material entering som3c

varat3(2,1) minimum C:N ratio for material entering som3c

varat3(3,1) amount N present when minimum ratio applies

vlosse fraction per month of excess N (N left in the soil after nutrient uptake by

the plant) that is volatilized, range 0 to 1

vlossg fraction per month of gross mineralization that is volatilized, range 0 to 1

vlossp fraction of aboveground plant N that is volatilized (occurs only at

harvest), range 0 to 1

volex volatilization loss as a function of mineral N remaining after uptake by

grass, crop, or tree (g·m-2

)

volexa accumulator for N volatilization as a function of N remaining after uptake

by grass, crop, or tree (total N for entire simulation) (g·m-2

)

volgm volatilization loss of N as a function of gross mineralization

volgma accumulator for N volatilized as a function of gross mineralization (g·m-2)

(total N for entire simulation)

volpl volatilization of N from plants during harvest for grass or crop

volpla accumulator for N volatilized from plant at harvest for grass or crop (total

N for entire simulation) (g·m-2)

w1lig initial lignin content of dead fine branches (fraction of lignin in wood1c),

range 0 to 1

w1lig lignin content of dead fine branches of forest system (fraction lignin in

wood1c)

w1mnr(1) N mineralized from the wood1c (dead fine branch) component of a forest

system (g·m-2)

w2lig initial lignin content of dead large wood (fraction of lignin in wood2c),

range 0 to 1

58
w2lig lignin content of dead large wood of forest system (fraction lignin in

wood2c)

w2mnr(1) N mineralized from the wood2c (dead large wood) component of a forest

system (g·m-2)

w3lig lignin content of dead coarse roots of forest system (fraction lignin in

wood3c)

w3lig initial lignin content of dead coarse roots (fraction of lignin in wood3c),

range 0 to 1

w3mnr(1) N mineralized from the wood3c (dead coarse root) component of a forest

system (g·m-2)

wd1cis(1) unlabeled C in forest system wood1c (dead fine branch) material (g·m-2)

wd2cis(1) unlabeled C in forest system wood2c (dead large wood) material (g·m-2)

wd3cis(2) labeled C in forest system wood3c (dead coarse root) material (g·m-2)

wdfx annual atmospheric and nonsymbiotic soil N-fixation based on annual

precipitation (wet and dry deposition) (g·m-2)

wdfxa annual N-fixation in atmosphere (wet and dry deposition) (g·m-2)

wdfxaa annual accumulator for atmospheric N inputs (g·m-2·y-1)

wdfxas annual accumulator for soil N-fixation inputs (g·m-2·y-1)

wdfxma monthly N-fixation in atmosphere (g·m-2)

wdfxms monthly nonsymbiotic soil N-fixation (g·m-2)

wdfxs annual nonsymbiotic soil N-fixation based on precipitation rather than soil

N:P ratio (g·m-2)

wdlig(1) lignin fraction for forest system leaf production, range 0 to 1

wdlig(2) lignin fraction for forest system fine root production, range 0 to 1

wdlig(3) lignin fraction for forest system fine branch production, range 0 to 1

wdlig(4) lignin fraction for forest system large wood production, range 0 to 1

wdlig(5) lignin fraction for forest system coarse root production, range 0 to 1

wood1c C in wood1c (dead fine branch) component of forest system (g·m-2)

wood1e(1) N in wood1c (dead fine branch) component of forest system (g·m-2)

wood2c C in wood2c (dead large wood) component of forest system (g·m-2)

wood2e(1) N in wood2c (dead large wood) component of forest system (g·m-2)

wood3c C in wood3c (dead coarse roots) component of forest system (g·m-2)

wood3e(1) N in wood3c (dead coarse roots) component of forest system (g·m-2)

woodc sum of C in wood components of forest system (g·m-2)

wooddr(1) fraction of forest that is deciduous; the fraction of leaves that fall during

senescence month or at the end of the growing season, range 0 to 1

wooddr(2) monthly death rate fraction for fine root component, range 0 to 1

wooddr(3) monthly death rate fraction for fine branch component, range 0 to 1

wooddr(4) monthly death rate fraction for large wood component, range 0 to 1

wooddr(5) monthly death rate fraction for coarse root component, range 0 to 1

woode(1) sum of N in wood components of forest system (g·m-2)

59
4.4.1 Fire parameters and descriptions—

Name Files Description

ad fire, fire_beh exponent in optimum reaction

velocity equation

ade fire, fire_beh exponent in optimum reaction

velocity equation (energy release)

adec1 fuel_load maximum annual decomposition rate

for fine fuels

adec100 fuel_load maximum annual decomposition rate

for coarse fuels

adj_lai fire_sta post-fire woody LAI

aet_ann fire_sta annual actual evapotranspiration

b_eff fire, fire_beh wind effect exponent in phiwnd

equation

bark_fac_c ratio of bark thickness to dbh for

conifers

bark_fac_h ratio of bark thickness to dbh for

hardwoods

bed_dep fuel_load depth of fuel bed

betbar fire, fire_beh packing ratio

betop fire, fire_beh optimum packing ratio

betope fire, fire_beh optimum packing ratio (energy

release)

c_tree_lai fuel_load tree LAI estimated from leaf biomass

c_var fire, fire_beh intermediate variable in ufact

equation

ch[365] fire, fire_beh crown height (m)

ck fire, fire_beh fraction of crown volume killed

cl[365] fire, fire_beh crown length (m)

cl_rat_c ratio of length to tree height for

conifers

cl_rat_h ratio of crown length to tree height for

hardwoods

d_1000hr fuel_load dead 1,000-hour fuel load

d_100hr fuel_load dead 100-hour fuel load

d_10hr fuel_load dead 10-hour fuel load

d_1hr fuel_load dead 1-hour fuel load

dbh fuel_load tree diameter at breast height

dead fire_sta dead grass accumulation

dead_accum fire_sta dead herb load

dedrt fire, fire_beh ratio in calculation of etamd

dedrte fire, fire_beh ratio in calculation of etamd (energy

release)

defac fuel_load decomposition factor

depth fire, fire_beh effective fuel bed depth

dstnd fuel_load standing dead grass (from

CENTURY)

dwod1 fuel_load dead fine wood (from CENTURY)

dwod100 fuel_load dead coarse wood (from CENTURY)

dwood fuel_load dead wood (dwod1 + dewod2)

4.4 Fire Parameters and

Variables

60
Name Files Description

e_eff fire, fire_beh wind effect exponent in ufact equation

end fire, fire_beh Julian date for end of current month

end_gs fire_sta Julian date for end of growing season

etamd fire, fire_beh moisture damping coefficient of dead

fuels

etamde fire, fire_beh moisture damping coefficient of dead

fuels (energy release)

etaml fire, fire_beh moisture damping coefficient of live

fuels

etamle fire, fire_beh moisture damping coefficent of live

fuels (energy release)

etasd fire, fire_beh mineral damping coefficient of dead

fuels

etasl fire, fire_beh mineral damping coefficient of live

fuels

f1 fire, fire_beh 1-hour weighting factor

f10 fire, fire_beh 10-hour weighting factor

f100 fire, fire_beh 100-hour weighting factor

f1000e fire, fire_beh 1,000-hour weighting factor (energy

release)

f100e fire, fire_beh 100-hour weighting factor (energy

release)

f10e fire, fire_beh 10-hour weighting factor (energy

release)

f1e fire, fire_beh 1-hour weighting factor (energy

release)

fd fire, fire_beh flame depth

fdead fire, fire_beh dead fuel weighting factor

fdeade fire, fire_beh dead fuel weighting factor (energy

release)

fherb fire, fire_beh live herb weighting factor

fherbe fire, fire_beh live herb weighting factor (energy

release)

fi[days_per_year] fire, fire_beh Byram’s fire line intensity

fl[days_per_year R] fire, fire_beh flame length

flamm_thres fire_sta flammability threshold

flive fire, fire_beh live fuel weighting factor

flivee fire, fire_beh live fuel weighting factor (energy

release)

fwood fire, fire_beh live wood weighting factor

fwoode fire, fire_beh live wood weighting factor (energy

release)

gmamx fire, fire_beh maximum reaction velocity

gmamxe fire, fire_beh maximum reaction velocity (energy

release)

gmaop fire, fire_beh optimum reaction velocity

gmaope[365] fire, fire_beh optimum reaction velocity (energy

release)

grass lfuel_mc live grass moisture content

61
Name Files Description

grass_decay fire_sta d dead grass decay rate

grass_stress[days_per_year] fire_sta soil moisture available to grass roots

hd fire, fire_beh dead fuel heat of combustion

hl fire live fuel heat of combustion

hn1 fire, fire_beh 1-hour heating number

hn10 fire, fire_beh 10-hour heating number

hn100 fire, fire_beh 100-hour heating number

hnherb fire, fire_beh live herb heating number

hnwood fire, fire_beh live wood heating number

ht fire, fire_beh tree height (m)

ht fuel_load tree height

htsink fire, fire_beh heat sink

ic[365] fire, fire_beh National Fire Danger Rating System

(NFDRS) ignition component

ir fire, fire_beh reaction intensity

ire[365] fire, fire_beh reaction intensity (energy release)

k_coeff Beer’s Law coefficient

l_1000hr fuel_load live fuel load - 1,000 hour (g·m-2)

l_100hr fuel_load live fuel load - 100 hour (g·m-2)

l_10hr fuel_load live fuel load - 10 hour (g·m-2)

l_1hr fuel_load live fuel load - 1 hour (g·m-2)

last_yr_snw fire_dat snowpack at end of previous year

lat d_fuel latitude of cell

lgras fuel_load grass carbon (g·m-2

)

lig1 fuel_load lignin content of fine dead wood

lig100 fuel_load lignin content of coarse dead wood

lightn[DAYS_PER_YEAR] fire_sta lightning probability

lit_accum fire_sta litter load

lit_bd fire_sta bulk density (gm/m

3) of horizontal

fine fuels

litfall fire_sta litterfall

littr fuel_load litter biomass (g·m-2)

livrt fire, fire_beh ratio in calculation of etaml

livrte fire, fire_beh ratio in calculation of etaml (energy

release)

lleaf fuel_load leaf biomass (g·m-2

)

ltree fuel_load tree biomass (g·m-2)

lwod1 fuel_load live fine wood biomass (g·m-2)

lwod100 fuel_load live coarse wood biomass (g·m-2)

lwood fuel_load live wood biomass (g·m-2)

m_grass_stress[YEAR] fire_sta, lfuel_mc soil moisture available to grass roots

m_pet[12] fire_dat, fire_sta monthly potential

evaporatranspiration (mm)

m_ppt[12] fire_dat, fire_sta monthly precipitation (mm)

m_ppt_rat[12] fire_dat rate of monthly precipitation (in·hour-1

)

m_rad[12] fire_dat monthly radiation

m_rh[12] fire_dat, fire_sta monthly relative humidity

m_tmp[12] fire_dat, fire_sta monthly temperature (°C)

m_tree_stress lfuel_mc soil moisture available to tree roots

62
Name Files Description

m_ws[12] fire_dat monthly wind speed (m·min-1)

mc_1[DAYS_PER_YEAR] fire, fire_beh dead fuel moisture: 1-hour fuels

mc_10[DAYS_PER_YEAR] fire, fire_beh dead fuel moisture: 10-hour fuels

mc_100[DAYS_PER_YEAR] fire, fire_beh dead fuel moisture: 100-hour fuels

mc_1000[DAYS_PER_YEAR] fire, fire_beh dead fuel moisture: 1,000-hour fuels

mc_1000hr[365] d_fuel dead fuel moisture: 1,000-hour fuels

mc_100hr[365] d_fuel dead fuel moisture: 100-hour fuels

mc_10hr[365] d_fuel dead fuel moisture: 10-hour fuels

mc_1hr[365] d_fuel dead fuel moisture: 1-hour fuels

mc_ext fuel_load level of fuel moisture above which a

fire is not possible

mc_grass[DAYS_PER_YEAR] fire, fire_beh live grass moisture content

mc_grass_max fire_sta maximum live grass moisture

content

mc_grass_min fire_sta minimum live grass moisture content

mc_thres 1,000-hour fuel moisture content

threshold for fire events

mc_tree[365] fire, fire_beh live tree foliage moisture content

mc_tree_max max live tree moisture content

mc_tree_min min live tree moisture content

mclfe fire, fire_beh dead_fuel moisture for live-fuel

extinction moisture

melt_b fire_sta snowmelt coefficient

mlittr fuel_load metabolic litter carbon (g·m-2)

mixed_bd bulk density vertical and horizontal

fine fuels mix

mxd fire moisture extinction of dead fuels

mxd[365] fire_beh moisture extinction of dead fuels

mxday fire_sta Julian day of maximum lethal scorch

height

mxl fire, fire_beh moisture extinction of live fuels

mxlsh fire_sta maximum lethal scorch height

no_mlt fire_sta snowmelt coefficient

p_flamm[DAYS_PER_YEAR] d_fuel probability of fire start

p_lightn[12] fire_dat probability of lightning

partial cell burn switch to turn partial burning of grid

cells on (1) or off (0)

pet[365] fire_dat daily potential evapotranspiration

phislp fire, fire_beh slope effect multiplier

phiwnd fire, fire_beh wind effect multiplier

pligst fuel_load lignin effect on decomposition

ppt[365] d_fuel, fire_dat daily precipitation (mm)

ppt_ann fire_sta annual precipitation (mm)

ppt_events[12] fire_dat number of ppt events per month

ppt_rat[365] d_fuel, fire_dat daily rate of ppt (in·hour-1)

prf[365] fire, fire_beh probability of reportable fire

propr_rat[365] fire, fire_beh compaction of fuel

propr_rate[365] fire, fire_beh compaction of fuel

rad[365] d_fuel, fire_dat daily radiation

63
Name Files Description

rh[365] d_fuel, fire_dat daily relative humidity (percent)

rh_corr[365] d_fuel relative humidity shade correction

rhobar fire, fire_beh weighted fuel density

rhobed fire, fire_beh bulk density of fuel bed

rhod fire, fire_beh dead fuel particle density

rhol fire, fire_beh live fuel particle density

ros[DAYS_PER_YEAR] fire, fire_beh rate of spread

ros_thres threshold of rate of fire spread

sa1 fire, fire_beh 1-hour surface area

sa10 fire, fire_beh 10-hour surface area

sa100 fire, fire_beh 100-hour surface area

sadead fire, fire_beh total surface area of dead fuels

saherb fire, fire_beh live herb surface area

salive fire, fire_beh total surface area of live fuels

sawood fire, fire_beh live wood surface area

scn[365] fire, fire_beh normalized ros

sd fire, fire_beh silica-free mineral fraction of dead

fuels

sg1 fire, fire_beh ratio of 1-hour surface area to volume

sg10 fire, fire_beh ratio of 10-hour surface area to

volume

sg100 fire, fire_beh ratio of 100-hour surface area to

volume

sg1000 fire, fire_beh ratio of 1,000-hour surface area to

volume

sgbrd fire, fire_beh ratio of dead fuel characteristic

surface area to volume

sgbrde fire, fire_beh ratio of dead fuel characteristic surface

area to volume (energy release)

sgbrl fire, fire_beh ratio of live fuel characteristic

surface area to volume

sgbrle fire, fire_beh ratio of live fuel characteristic surface

area to volume (energy release)

sgbrt fire, fire_beh ratio of characteristic surface area to

volume

sgbrte fire, fire_beh ratio of characteristic surface area to

volume (energy release)

sgherb fire, fire_beh ratio of live herb surface area to

volume

sgwood fire, fire_beh ratio of live wood surface area to

volume

sh[DAYS_PER_YEAR] fire, fire_beh van Wagner’s maximum height of

lethal scorch

shrub_bio fire_sta shrub biomass estimated from LAI

shrub_ht fire_sta height estimated from LAI

sl fire, fire_beh silica-free mineral fraction of live fuels

slittr fuel_load structural litter carbon (g·m-2)

slp fire, fire_beh slope

slpfct fire, fire_beh slope effect multiplier coefficient

64
Name Files Description

snow[365] d_fuel, fire_dat daily snowpack (mm)

snowfall[365] d_fuel, fire_dat daily snowfall (mm)

snowmelt[365] d_fuel, fire_dat daily snowmelt (mm)

snw0 fire_sta snowmelt coefficient

snw1 fire_sta snowmelt coefficient

start fire, fire_beh first Julian day of current month

start_gs fire_sta Julian date for start of growing

season

std fire, fire_beh mineral fraction of dead fuels

stems fuel_load number of stems per square meter

stl fire, fire_beh mineral fraction of live fuels

tau fire, fire_beh residence time of the flaming front

temp_corr[365] d_fuel temperature shade correction

temp_corr[DAYS_PER_YEAR] fire_sta temperature shade correction

tmp[365] d_fuel, fire, fire_dat daily temperature (°C)

total_accum fire_sta dead herb load + litter load

tovr1 fuel_load fine live wood turnover rate

tovr100 fuel_load coarse live wood turnover rate

tree lfuel_mc live tree foliage moisture content

tree_bio fire_sta tree biomass estimated from LAI

tree_ht fire_sta height estimated from LAI

tree_lai fire_sta tree leaf area index (m2

·m-2)

ufact fire, fire_beh wind effect multiplier in phiwnd

equation

upright_bd bulk density (g·m-3) of vertical fine

fuels

w10[365] fire_beh 10-hour dead fuel load

w100[365] fire_beh 100-hour load

w1000[365] fire_beh 1,000-hour load

w100n fire, fire_beh combustible 100-hour load

w10n fire, fire_beh combustible 10-hour load

w1n fire, fire_beh combustible 1-hour load

w1p[DAYS_PER_YEAR] fire, fire_beh 1-hour load (dead_accum + lit_accum)

wdeadn fire, fire_beh weighted net loading of dead fuels

wdedne[365] fire, fire_beh weighted net loading of dead fuels

(energy release)

wherb rothermal live grass fuel load (g·m-2)

wherbn fire, fire_beh combustible live herb load

wherbp[DAYS_PER_YEAR] fire, fire_beh live herb load

wliven fire, fire_beh weighted net loading of live fuels

wlivne[365] fire, fire_beh weighted net loading of live fuels

(energy release)

wndfac rothermal wind reduction factor

wndfac[365] fire_beh daily wind reduction factor

wndfac_for fire_sta forest wind reduction factor

wndfac_grass fire_sta grassland wind reduction factor

wndfac_sav fire_sta savanna wind reduction factor

wndfc fire, fire_sta wind reduction factor

woody_decay fire_sta litter decay rate

65
Name Files Description

wrat fire, fire_beh ratio of dead to live heating numbers

(heating numbers are specified for

each fuel class [lb·ft-3] and

correspond to what must be heated

to ignition temperature before

flaming combustion begins)

ws[365] fire, fire_da, d_fuel daily wind speed (m·min-1)

wtmcd fire, fire_beh weighted moisture content of dead

fuels

wtmcde[365] fire, fire_beh weighted moisture content of dead

fuels

wtmcl fire, fire_beh weighted moisture content of live

fuels

wtmcle[365] fire, fire_beh weighted moisture content of live

fuels

wtot fire, fire_beh total load

wtotd fire, fire_beh total dead load

wtotl fire, fire_beh total live load

wwood fire, fire_beh live shrub load

wwoodn fire, fire_beh combustible live wood load

zeta fire, fire_beh no wind propagating flux ratio (amount

of heat energy moving from burning

fuels into adjacent unburning fuels

(Btu·ft-2·min-1); the no-wind

calculation of the propagating flux

assumes no flame kill due to wind)

66

Table 18—Parameters and values in MC1 parameter

file, fire_param.dat

Parameter Value

bark_fac_c 0.07

bark_fac_h 0.001

cl_rat_c 0.4

cl_rat_h 0.99

hd 8000

hl 8000

k_coeff .50

lit_bd 4440

Parameter Value

mc_grass_max 120

mc_grass_min 30

mc_thres 15.0

mc_tree_max 130

mc_tree_min 80

melt_b 1.5

mixed_bd 4440

no_mlt 1.0

4.4.2 Fire parameter values—Tables 18 and 19 list the parameters and values in the

MC1 files fire_param.dat and thres.dat.
4.5 Output Variables

 Acknowledgments

Table 19—Parameters and values in the MC1 parameter file, thres.dat

Parameter Value

partial cell burn 0

ros_thres 60.0

sg1 2500

sg10 109

sg100 30

sg1000 8

sgherb 2500

sgwood 1500

Parameter Value

slp 12.67

snw0 3.0

snw1 0.0

upright_bd 1000

wndfac_for 0.4

wndfac_grass 0.6

wndfac_sav 0.5

Table 20 includes a selected set of output variables for VEMAP.

Table 20—Selected set of output variables for VEMAP

Module Variable name Variable definition

Biogeography vclass VEMAP vegetation class (22)

agg_vclass Aggregated VEMAP vegetation class (7)

Biogeochemistry max_tree Maximum LAI value for trees

max_grass Maximum LAI value for grasses

aglivc Live grass leaf carbon

bglivc Live grass root carbon

frstc Total tree live carbon

rleafc Live tree leaf carbon

fcacc Total tree net primary production

bgcacc Grass root net primary production

agcacc Grass aboveground net primary production

mxnfix Nitrogen-fixation

nppx Net primary production (tree + grass)

nepx Net ecosystem production (tree + grass + soil)

aetx Actual evapotranspiration

rnfx Runoff

vegc Live vegetation carbon (tree + grass)

soilc Soil carbon

minx Mineralization

Fire bio_consume Biomass consumed

part_burn Fraction of grid cell burned

GIS assistance was provided by Ray Drapek of the College of Forestry, Oregon State

University, Corvallis, Oregon. Documentation of this model was compiled by Lisa Balduman

of the USDA Forest Service, Pacific Northwest Research Station, Corvallis, Oregon.

Funding was provided by the USDA Forest Service, U.S. Department of Energy -

NIGEC, and the USGS Biological Resources Division.

67
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Bachelet, D.; Daly, C.; Lenihan, J.M. [and others]. 2001. Interactions between fire,

grazing, and climate change at Wind Cave National Park, SD. Ecological Modelling.

134: 229-244

Bradshaw, L.S.; Deeming, J.E.; Burgan, R.E.; Cohen, J.D. 1984. The 1978 national

fire danger rating system: a technical documentation. Gen. Tech. Rep. INT-169.

Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and

Range Experiment Station. 44 p.

Daly, C.; Bachelet, D.; Lenihan, J.M. [and others]. 2000. Dynamic simulation of treegrass interactions for global change studies. Ecological Applications. 10(2): 449-469.

Food and Agriculture Organization. 1974-79. Soil map of the world. Paris, France:

United Nations Educational, Scientific and Cultural Organization. Vol. I-X.

Fosberg, M.A. 1972. Moisture content calculations for the 100-hour timelag fuel in fire

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Fosberg, M.A.; Deeming, J.E. 1971. Derivation of the 1- and 10-hour timelag fuel

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Fosberg, M.A.; Rothermal, R.C.; Andrews, P.A. 1981. Moisture content calculations for

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Gilmanov, T.G.; Parton, W.J.; Ojima, D.S. 1997. Testing the ‘CENTURY’ ecosystem

level model on data sets from eight grassland sites in the former USSR representing

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Gupta, S.C.; Larson, W.E. 1979. Estimating soil water retention characteristics from

particle size distribution, organic matter content and bulk density. Water Resources

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Rothermel, R.E. 1972. A mathematical model for predicting fire spread in wildland fuels.

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Forest Service, Intermountain Forest and Range Experiment Station. 40 p.

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Running, S.W.; Gower, S.T. 1991. FOREST-BGC, a general model of forest ecosystem

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70
Appendix 1: List of

Subroutines

Subroutine File Called from Input/output

access_file bfuncs.c read_inputs file, filename, status

AccumulateTranspiration transpire TranspireStep curr_mo, pot_transp, water, soil

add_mapssvars mapss_1t century_eq_1d, mapss_1d cen_outvars, year, data_point

AddAttributes_nc nc_output AddAttributes_nc_bgc, fileid, cmdline

 AddAttributes_nc_All

AddAttributes_nc_All nc_output init_io cmdline

AddAttributes_nc_bgc nc_out_bgc init_io cmdline

adjilig adjilig.F cultiv, partit oldc, frnew, addc, fract1

adjust_parameters read_site_parm load_globals

AdjustMaxlai grasses_equil GrassWoodyEquilibrium excess, site, tmp, lai, maxlai, grass_lai, deciduous,

 data_point, curr_mo

Aet2LaiProductivity grasses_equil CheckEvergreen state, tmp, maxlai, at2lai, lifeform

alloc_bgc_buffer io_general mapss_2tt, century_equilibrium_2d data_point, bgc_data, bgc_length

alloc_input_data io_general mapss_equilibrium_2d, mapss_2tt, input_data, data_size, var_list

 century_equilibrium_2d

alloc_nc_globals nc_input OpenAllNCFFiles max_climate_len

alloc_output_data io_general mapss_2tt mapss_output, years_to_run

annacc annacc.F eachyr, prelim

annual_budget wbcalc classic_water_balance budget, capacity, row, col

ApplyLifeformRules lifeform_rules climate_prep data_point

ArgFileInit mapss_main.c process_command_line files

assign fire_behav fire_behav, fire data_point, i

at_assess bfuncs ReiterateLaiCycle site

Biogeog biogeog mapss_1d data_point

BroadDecid lifeform_rules CheckEvergreen, ApplyLifeformRules cats, productivity, IsTree, SecondTime, data_point

buffer_bgc_data mapss_1t century_eq_1d, add_mapssvars, bgc_outvars, data_point, bgc_data, year, mo

 mapss_1d

burn_index dfuel_mc DFuelMC

calc_fc_wp swp set_drainage_constants sand, clay, eff_thickness, matrix_pot_a, field_cap, wilt_pt,

 Theta_m, layer

calc_hycon swp saturated_drainage sand, clay, h2o , layer

calc_swhc swp set_drainage_constants sand clay, eff_thickness, layer

calc_swp swp transpire sand, clay, pct_soil_h2o, layer

calciv calciv.F detiv

CalcPenmon pet_calc CalcPet data_point, lifeform

71
Subroutine File Called from Input/output

CalcPet pet_calc GrassAlone, pet_adjust, InitPet data_point, lifeform, PetCalc

CalcSatvp pet_calc InitPet data_point

CalcTrbxfr pet_calc CalcPet

calculate_budget wbcalc process_data prev_mo, curr_mo, change, capacity

cen_end csa_main.F MAPSS_1T

cen_init csa_main.F MAPSS_1T yr, vveg, diag_flag, os_flag, state, outvars, path, mx,

 c3c4, initflag, fm, zn, tmpi, ppti

cen_init_climate init_climate.F MAPSS_1T ppt, tmax, tmin

cen_init_lat init_lat.F MAPSS_1T lat, elev

cen_init_soils init_soils.F MAPSS_1T bd, sand, cly, depth, rock, ws

cen_step csa_main.F MAPSS_1d vveg_in, wbegin, wend, cbegin, cend, csene, wfire, cfire,

 treec, cropc, state, outvars, mx, mx_out, c3c4, c3c4_out,

 tname, cname, diag_flag, os_flag, burn_out,

 burn_count, tmpi, tmpi_out, ppti, ppti_out

century_equilibrium_1d mapss_1t century_equilibrium_2d data_point, input_data, cen_data

century_equilibrium_2d mapss_main.c mapss data_point

CenturyFCarbToMapssLai mapss_1t mapss_1d carbon

CenturyFCarbToMapssLaiSLA mapss_1t mapss_1d grass_carbon, woody_carbon, index, grass_lai,

 woody_lai

check_at_flag at_flag pre_mapss_initialize

check_param_values read_site_parm read_site_specific, read_parameters

CheckEvergreen grasses_equil GrassWoody data_point, site, lai, grass_lai, maxlai, site_begin,

 offset_begin, lai_values, c3c4_ratio, canopy_type,

 mapss_output

CheckStateValues grasses_equil GrassWoodyEquilibrium, curr_mo, lastyear, threshold, mo, base

 GrassAloneEquilibrium,

 LaiCycleEquilibrium

ckdata ckdata.F cultin, fertin, firein, grazin, harvin, routin, expect, found

 irrgin, omadin, tremin, cropin,

 sitein, treein

classic_water_balance wbcalc GrassWoody ppt, pet, row, col, budget, capacity

ClassifyStation classification GrassWoody, CheckEvergreen dat_point, lai_values, c3c4_ratio, canopy_type

climate_prep mapss_equil mapss_equilibrium_1d, mapss_1t data_point

close_io io_general main_finalize var_list

CloseAllNCFiles nc_input close_io var_list

CloseNCFile nc_input CloseAllNCFiles data_file

CloseOutputNC_All nc_output close_io

cmplig cmplig.F eachyr, cropin cursys, fligni, wdlig, pltlig

cnvrt_units dfuel_mc DFuelMC

co2eff co2eff.F eachyr, schedl time

command_line_defaults mapss_main.c process_command_line data_point

consump fire_eff fire_eff, fire data_point, day

CreateOutputNC nc_output CreateOutputNC_bgc, nc_idvals, interval, filename, row_begin,

 CreateOutputNC_All row_end, col_begin, col_end, f, filter_length

CreateOutputNC_All nc_output init_io filename, row_begin, row_end, col_begin, col_end

CreateOutputNC_bgc nc_out_bgc init_io filename, row_begin, row_end, col_begin, col_end

72
Subroutine File Called from Input/output

crop crop.F simsom time, wfunc

cropin cropin.F schedl tomatchcropmix cropmix.F cropin, veg_changecrown_fire fire_behav fire_behav, fire data_point, mo, daycrown_kill fire_eff fire_eff, fire data_point, mo, daycsched csched.F cultiv, declig, dshoot, harvst, litburn, cflow, protop, probot, froma1, tob1, froma2, tob2,

 litdec, partit, respir, soilos, somdec, frac, accum cutrtn, dedrem, grem, growth, killrt, livrem, trees, wdeath

cultin cultin.F schedl tomatch, curcultcultiv cultiv.F crop pltligcutrtn cutrtn.F frem accumcycle cycle.F simsom month, cancvr, wfuncdaily_dat fire_data fire_datadaily_ppt fire_data fire_data data_pointdaylen_ daylen.c simsom month, sitlatdead_wood fuel_load fuel_load data_point, mo, yr

declig declig.F litdec, woodec aminrl, ligcon, lyr, nelem, nlr, ps1co2, rnew, rsplig, tcflow,

 tcstva, csrsnk, cstatv, elstva, gromin, minerl, netmnr, resp, som1ci, som1e, som2ci, som2e

decomp decomp.F simsom dtm, decsysdedrem dedrem.F frem accumDesertRules classification ClassifyStation zonedetiv csa_detiv.F cen_initDFuelMC dfuel_mc mapss_1d data_point, yearDistributePpt distrib GrassWoody, LaiCycle curr_mo, data_point, lai, modroot droot.F crop pltligDrySoilCheck transpire transpiration curr_mo, SoilDatadshoot dshoot.F crop wfunceachyr eachyr.F stand_step, cen_step, standardefold mapss_1t efold_climate, efold_climate_init, efold_t, current, previous

 efold_lai, efold_biogeog

efold_biogeog mapss_1t mapss_1d, efold_lai years, data_pointefold_climate mapss_1t mapss_1t year, data_point, input_dataefold_climate_init mapss_1t mapss_init data_point, input_dataefold_lai mapss_1t years, data_point, lai_values, laiemissions fire_eff fire_eff data_point, month, dayeq_test eq_test.F stand_step, standard eq_flag, min_years, final_growtherosn erosn.F simsom psloss, bulkd, edepth, enrich, lhzci, lhze, nelemesched esched.F declig, litdec, somdec cflow, tca, rcetob, anps, bnps, labile, mnrfloEvaluateSite grasses_equil GrassWoody state, data_point, laiexcess_at_events_count transpire main_finalize

extend extend.F detiv in, dowrite

FallFreeze lifeform_rules TempZone data_point

falstd falstd.F crop, wthini pltlig

faterr faterr.F weathr itell1, itell2fertin fertin.F schedl tomatch, curfert, savedfert

73
Subroutine File Called from Input/output

final_pet wbcalc GrassWoody pet, pet_adjfind_param_value read_site_parm read_site_param var_nameFindIIndex lifeform_rules ApplyLifeformRules fddFindMaxLai mapss_1t lai_allocate lai, lfFindMeanLai grasses_equil GrassWoody, CheckEvergreen, lai, total_lai, lifeform

 lai_allocate

FindRatio lifeform_rules ApplyLifeformRules x,slope, y_interceptFindSlopeYIntercept lifeform_rules pre_mapss_initialize X1, Y1, X2, Y2, slope, y_interceptFindStartPosition nc_input InputNCValues row, colFire fire data_point, yr, mo, cen_statefire_condition bfuncs.c GrassWoody grass_sum_lai, shrub_lai, pet, pptFireBehavior fire_behav mapss_1d data_point, moFireData fire_data mapss_1d data_point, yr, cen_state, woody_fire, grass_fireFireEffect fire_eff mapss_1d data_point, mo, cen_statefirein firein.F schedl tomatch, curfireFireOccur fire_occur mapss_1d data_point, yr, moFireSched fire_sched mapss_1d data_point, mo, yr, woody_fire, grass_fire, cen_statefirrtn firrtn.F fremfixin fixin.F detivflammability dfuel_mc DFuelMCfloclr floclr.F prelimfloclr_ floclr.c prelim iflow flow.F csched, cultiv, dshoot, erosn, esched, var1, var2, when, howmch

 firrtn, harvst, litburn, partit, pschem, respir, soilos, cutrtn, dedrem, grem, growth, killrt, livrem, simsom, trees, wdeath

flow_ flow.c flow.F from, to, when, howmuchflow_err ferr.c flowl.c, flow.c error_num, whenflowl_ flowl.c flowl.F from, to, when, howmuchflowup flowup.F calciv, crop, cultiv, harvst, simsom, time

 trees

flowup_ flowup.c flowup.F timeForestRules classification ClassifyStation data_point, lai_values, zonefree_bgc_buffer io_general mapss_2tt, century_equilibrium_2d data_point, bgc_datafree_input_data io_general mapss_equilibrium_2d, mapss_2tt, input_data, var_list

 century_equilibrium_2d, mapss_equilibrium_2d

frem frem.F simsom, treesfuel_depth fuel_load fuel_load data_point

fuel_mc dfuel_mc DfuelMC data_point, year

FuelLoad fuel_load mapss_1d cen_outvars, cen_state, data_point, yr, moget_command_line mapss_main.c process_command_line argc, argvget_daily fire_behav fire_behav, fire data_point, moget_input io_general mapss_equilibrium_2d, mapss_2tt input_data, data_size, var_listget_jul fire_behav fire_behav, fire data_point, mo

74
Subroutine File Called from Input/output

get_var_len nc_input OpenAllNCFFiles data_fileGetCheckRowCol mapss_main.c process_command_line arg, name, beg, end

GetFilePath mapss_main.c process_command_line user_path, model, include_path, default_name,

 default_path

GrassAlone grasses_equil GrassWoody site, lai, conductance, data_pointGrassAloneEquilibrium grasses_equil GrassAlone site, mo, lai, months, row, col

GrassPotAtSatisfied transpire TranspireStep pot_at, curr_mo, conductance, lai, grass_lai,

 begin_h2o,pot_transp, data_point, mo, curr_canopy_cond_max

GrassRules classification ClassifyStation lai_values, zone, c3c4_ratio, canopy_typeGrassWoody grasses_equil LaiCycle conductance, lai, grass_lai, maxlai, curr_year, prev_year,

 data_point, site_begin, offset_begin, mapss_output

GrassWoodyEquilibrium grasses_equil GrassWoody site, mo, tmp, lai, maxlai, grass_lai, pet_adj, months,

 shrubs, deficit, deciduous, data_point, curr_mo

grazin grazin.F schedl tomatch, curgrazgrem grem.F simsomGrowingDegreeDays lifeform_rules ApplyLifeformRules tmp, degreegrowth growth.F crop cisofrH2oCompetition transpire TranspireStep lai, h2o_fraction, conductance, data_pointh2olos h2olos.F cycle months, aliv, alit, adead, co2valharvin harvin.F schedl tomatch, curharvharvst harvst.F simsom month, pltligHeatLimitedRules classification ClassifyStation data_point, zoneignition fire fire data_point, yr, iinfiltrate drain transpiration site, SoilDatainit_data_point mapss_equil mapss_equilibrium_1d, mapss_1t data_point

init_data_size io_general mapss_equilibrium_2d, mapss_2tt, data_size, row, col, years

 century_equilibrium_2d

init_io io_general main_initialize data_point, all_files, cmdlinesinit1 fire_data fire_data data_point, yrinit2 dfuel_mc DfuelMC data_pointInit3 fire_behav fire_behav, fire data_pointinit4 fire_eff fire_eff data_point, start, endInitConductance woody_equil GrassWoody, LaiCycle conductance, grass, woody

InitOutputFilter io_general init_io filename, f, filter_lengthInitPet misc_init climate_prep, mapss_1t data_pointInitPoint misc_init init_data_point data_pointInitSnow drain LaiCycle, GrassWoody, GrassAlone data_point, curr_yearInitSoilWater drain LaiCycle,GrassWoody, GrassAlone curr_year, SoilDatainprac inprac.F prelim, cycleinput_leaf_root_areas mapss_equil CheckEvergreen, lai_limit lai, tmp, offset, grasslai, deciduous, tree_upperboundInputNCValues nc_input get_input input_data, data_size, var_listintensity fire_behav fire_behav, fire data_point, iirrgin irrgin.F schedl tomatch, curirrikillrt killrt.F frem accumlacalc1 lacalc1.F potfor lai, rleavc

75
Subroutine File Called from Input/output

lacalc2 lacalc2.F potfor lai, rlwodc, maxlai, klailai_allocate mapss_1t mapss_1d lai_values, lai, data_pointlai_at_adequate transpire ReiterateLaiCycle state, lai, lifeform, tmp, row, col, broadleaflai_limit mapss_equil mapss_equilibrium_1d data_point, lai, grass_lai, maxlai, offsetLaiCycle woody_equil CheckEvergreen, maxlai, lai, grass_lai, offset, data_point, site_begin,

 mapss_equilibrium_1d offset_begin, mapss_output

LaiCycleEquilibrium woody_equil LaiCycle curr_mo, mo, months, equilibrium_factorleach leach.F simsom amov, nelem, nlayer, minerl, minlch, frlech, stream, basef,

 stormf

LFuelMC lfuel_mc mapss_1d cen_state, data_point, yr, moLifeform lifeform mapss_1d data_point, laiLightAttenuate grasses_equil GrassWoody, tmp, maxlai, grass_lai, lai, deciduous, data_point, site

 GrassWoodyEquilibrium, AdjustMaxlai, GrassAlone, AdjustMaxLai

lightning fire_data fire_datalitburn litburn.F firrtn, grem, frem litrme

litdec litdec.F decomp dtmlive_mc lfuel_mc LfuelMC data_pointlive_wood fuel_load fuel_load data_point, mo, yrlivrem livrem.F frem accumload_arg_file mapss_main.c process_command_line argc, argvload_globals mapss_main.c main_initialize data_point, all_filesload_init_bgc nc_out_bgc mapss_2tt filename, row, col, datLoadOutputFilter io_general show_avail_outvars, init_io f, filter_lengthLoadOutputFilter_bgc io_general show_avail_outvars, init_io f, filter_lengthmain mapss_main.c *** THIS IS THE START OF IT ALL rgc, argvmain_finalize mapss_main.c mapss data_pointmain_initialize mapss_main.c mapss data_point, all_files, cmdlinemapss mapss_main.c main argc, argvmapss_1d mapss_1t mapss_1t data_point, mapss_output, state_mapss_1d, cen_data,

 year, cen_state

mapss_1t mapss_1t mapss_2tt data_point, mapss_output, input_data, cen_data

mapss_2tt mapss_main.c mapss data_pointmapss_equilibrium_1d mapss_equil mapss_equilibrium_2d, mapss_2tt, data_point, mapss_output

 century_equilibrium_2d

mapss_equilibrium_2d mapss_main.c mapss data_pointmapss_init mapss_1t mapss_1t initflag, data_point, cen_outvars, input_dataMapssToVemapConvert classification_bgc process_command_line, mapss_2tt, class

 century_equilibrium_2d

minimum_reserve drain ReiterateLaiCycle site, lai, maxlai, SoilData

MinMaxTemp lifeform_rules TempZone data_point

MixIndex lifeform_rules ApplyLifeformRules data_point

mnracc mnracc.F declig, litdec, somdec mnrflo, gross, netMonthMin lifeform_rules ProcessSeason current, next, prior, min, periodmortality fire_eff fire_eff, fire data_point, mo, day

76
Subroutine File Called from Input/output

nc_output_bgc nc_out_bgc store_output_bgc mask, data_point, bgc_datanc_output_month nc_output store_output data_point, mapss_outputnc_output_year nc_output store_output data_point, mapss_outputNewFireCondition bfuncs.c rassWoody grass_sum_lai, tree_lai, shrub_lai, site, zone,

 SoilData,broadleaf

NewMonthlyLai woody_equil LightAttenuate, LaiCycle, GrassWoody maxlai, grass_lai, tmp, lai, deciduous, zone, gdd, siteNewProcessSeason lifeform_rules BroadDecid data_pointno_deficit wbcalc annual_budget budget, capacity, row, col

no_excess wbcalc annual_budget budget, row, col

NoDeficits grasses_equil GrassWoodyEquilibrium deficitNorthernHemiSet misc_init climate_prep, century_eq_1d,

 mapss_1t

nutrlm nutrlm.F restrp nelem, nparts, cprodl, eprodl, maxec, maxeci, mineci,

 cfrac, eavail, nfix, sngxmx, snfxzc, elimit, eup

omadin omadin.F schedl tomatch, curomadOneThreshold lifeform_rules TimeInterval curr_tmp, next_tmp, frost_lineOpenAllNCFiles nc_input init_io data_root, data_set, data_dir, var_listOpenNCFile nc_input OpenAllNCFFiles data_root, data_set, data_dir, data_filepad_data io_general get_input input_data, data_size, var_listpart_burn fire_sched FireSched data_point, yrpartit partit.F calciv, crop, cultiv, droot, falstd, harvst, cpart, recres, lyr, cdonor, edonor, frlign, friso

 cutrtn, grem, killrt, trees, wdeath

pet_adjust transpire GrassWoody, GrassWoodyEquilibrium, lai, data_point

 GrassAlone

potcrp potcrp.F cycle month, cancvrPotential transpire H2OCompetition lai, conductance, zone, LaiUpperBoundWater, lifeform,

 broadleaf

PotentialAt transpire TranspireStep pot_transp, lai, conduct, k0, k1, data_point, lifeformPotentialAtPenmon transpire TranspireStep curr_canopy_cond_max, lai, stomatal_conduct, k0,

 data_point, lifeform, mo

PotentialLai transpire GrassPotAtSatisfied k0, k1, transp, pot_transp, conduct, data_point, lifeform

PotentialLaiPenmon transpire GrassPotAtSatisfied k0, k1, transp, stomatal_conduct, data_point, lifeform, mo,

 curr_canopy_cond_max

potfor potfor.F cycle monthprcgrw prcgrw.F cycle imnthpre_mapss_initialize mapss_equil main_initialize data_pointpredec predec.F prelim, cen_step, readblk sandprelim prelim.F detivprelim fire_behav fire_behav, fire iprocess_command_line mapss_main.c mapss argc, argv, all_files, data_pointprocess_data wbcalc annual_budget prev_mo, curr_mo, capacityProcessSeason lifeform_rules BroadDecid data_point, frost_line, ppt_ptrPS_Century c3c4_functions ApplyLifeformRules meantemp, ratio, canopypschem pschem.F simsom dtmRainfallEvents lifeform_rules ApplyLifeformRules data_point

77
Subroutine File Called from Input/output

read_inputs read_site_parm read_site_specific, read_parameters file, maxread_parameters read_site_parm load_globals fileread_scale nc_input ReadSite, ReadClimate varid, start, count, dat

read_site_specific read_site_parm load_globals file, SoilDatareadblk readblk.F detiv, stand_step, standard years_to_runReadClimate nc_input InputNCValues input_data, var_list, start, countREADCLIN readblk.F readblkReadFireParams fire_param mapss_1t, load_globals data_pointReadGeoHeader nc_input init_io geo_headerReadNCValues nc_input read_scale, ReadSoilsData data_file, start, count, values

ReadSite nc_input InputNCValues input_data, var_list, start, count, full_startReadSoilsData nc_input ReadSite start, count, soil_dataReiterateLaiCycle woody_equil LaiCycle curr_year, prev_year, lai, maxlai, inc_mode, offset,

 data_point, lifeform

release fire_behav fire_behav, fire irespir respir.F declig, somdec co2los, nlr, lyr, tcstva, cstatv, csrsnk, resp, estatv, minerl,

 gromin, netmnr

restrp restrp.F growth, trees nelem, nparts, avefrc, cerat, cfrac, potenc, rimpct,

 storage, snfxmx, cprodl, eprodl, eup, uptake, elimit, nfix, relyld, snfxac, svuptk

root_kill fire fire data_point, yr, day, cen_staterow_col_init io_general init_io data_point, geo_headesaturated_drainage drain transpiration site, layer, destination, SoilDatasatvp satvp CalcSatvp d_pointsavarp savarp.F prelim, simsom

scale scale.F cropmix f, val1, val2, resultscale4 scale4.F treemix f, ic, val1, val2, val3, val4, resultschedl schedl.F cycleSecondEvergreen lifeform_rules BroadDecid data_point, productivity, IsTreeset_drainage_constants drain soil_prep SoilDataset_hemisphere mapss_equil mapss_equilibrium_1d, mapss_1t row_cur, equator_rowset_initial_bgc_vars mapss_1t mapss_1t data_pointset_lai_bounds mapss_equil lai_limit data_point

set_pm_globals pm InitPet ts_yr, ta_yr, ea_yr, u_yrset_transpire_constants transpire pre_mapss_initializeset_var_list io_general main_initialize var_list, run_mode

SetCurrPrev woody_equil GrassWoody, LaiCycle months, site, curr_mo, prev_mo, lai, currlaiSetEffectiveThickness drain set_drainage_constants SoilDataSetOutputElsePoint station_out store_output data_point, class, mapss_outputSetOutputMaskPoint station_out store_output data_point, class, mapss_outputSetUpNCFiles nc_input OpenAllNCFFiles var_listshade_rad dfuel_mc fuel_mc data_point, year, monthshade_rh dfuel_mc fuel_mc data_point, year, monthshade_temp dfuel_mc fuel_mc data_point, year, monthshow_avail_outvars io_general process_command_lineshow_version_info station_out process_command_line prog_name, revision, file

78
Subroutine File Called from Input/output

ShrubRules classification ClassifyStation data_point, lai_values, zone

simsom simsom.F stand_step, cen_step, standardsitein sitein.F detiv ivoptSnarfInitialLai one_step process_command_line lai, lai_strsnow_cond fire_data fire_data data_pointSnowAndMelt lifeform_rules ApplyLifeformRules data_pointsoil_prep mapss_equil mapss_equilibrium_1d, mapss_1t data_point

soilos soilos.F erosn time, nelem, nlr, flost, somc, somci, csrsnk, some, esrsnk

somdec somdec.F decomp dtmSouthernHemiSwap misc_init climate_prep, century_eq_1d, data_point

 apss_1t

spread fire_behav fire_behav, fire data_point, iSpringThaw lifeform_rules TempZone data_point

stand_step csa_main.F MAPSS_1T state, outvars, eq_flag, final_growth, diag_flag, os_flag

statein passvars.F cen_step statestateinit passvars.F cen_init statestateout passvars.F cen_init, stand_step, cen_step stateStomatal Conductance transpire TranspireStep site, pet, lifeform, conductance, mo, shrubs, zone,

 broadleaf

store_event store_event.F readblkstore_output io_general mapss_equilibrium_2d, mapss_2tt input_result, mapss_result, mapss_output, data_point

store_output_bgc io_general mapss_2tt, century_equilibrium_2d input_result, bgc_data, data_pointsumcar sumcar.F calciv, crop, cultiv, harvst, detiv,

 simsom, trees

surface_runoff drain transpiration site, SoilData

SwapYears woody_equil ReiterateLaiCycle, GrassWoody curr_year, prev_year

TempZone lifeform_rules climate_prep data_pointTimeInterval lifeform_rules ProcessSeason curr_tmp, next_tmp, frost_line, period

transpiration transpire GrassWoody, GrassAlone, LaiCycle curr_mo, pet, conductance, lai, grass_lai, mo, data_pointTranspireStep transpire transpiration curr_mo, conductance, lai, grass_lai, pet, mo, data_pointtree_dim fuel_load fuel_load data_point, mo, yrtreein treein.F schedl tomatchtreemix treemix.F treein, veg_change

trees trees.F simsom month, cisotf, wfunc

TreeSavannaRules classification ClassifyStation data_point, lai_values, zonetremin treminimumF schedl tomatch, curtrmunsaturated drainage drain transpiration site, layer, destination, SoilDataupdate_event update_event.F cen_stepupdate_sched update_sched.F cen_stepvarsin passvars.F cen_init outvarsvarsinit passvars.F cen_init outvarsvarsout passvars.F cen_init, stand_step, cen_step outvars

veg_change veg_change.F cen_stepVemap2Mon vemap2_mo mapss_1d data_point, mo, cen_statevetocen vetocen.c cen_stepvetofix vetofix.c cen_init vclass, fixname

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Subroutine File Called from Input/output

WaterBalance transpire transpiration site, excess_pot_atwdeath wdeath.F trees tave, wfuncweathr weathr.F eachyr precip, prcstd, prcskw, mintmp, maxtmpwoodec woodec.F decomp dtmwrtbin wrtbin.F stand_step, cen_step, standard timewthini wthini.F readblk precip, prcstd, prcskw, mintmp, maxtmpxfer_climate_year io_general century_eq_1d, mapss_1t, input_data, data_point, year, var_list

 efold_climate_init, mapss_equilibrium_2d, mapss_2tt, century_equilibrium_2d

xfer_site io_general mapss_1t, mapss_equilibrium_2d, input_data, data_point

 mapss_2tt, century_equilibrium_2d

xfer_to_output mapss_1t mapss_1d data_point, mapss_output, lai_values, lai, burn_year

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MC1 is run in two successive modes: equilibrium and transient. First, MAPSS is run to produce an initial vegetation class corresponding to the climax

vegetation for the equilibrium climate (case I stops there). This vegetation map is read by the biogeochemical module, which runs for up to 3,000years—until the slow pool of soil organic matter reaches equilibrium—and generates the initial conditions for the transient run (case II stops here).Finally, transient climate and the initial condition file are read by MC1, which calculates monthly pools of carbon and nitrogen for each lifeform. Thesepools are interpreted by the biogeographic module to determine if the vegetation types should be changing or not. Pool sizes also are read by the firemodule, which can trigger a fire (case III).CASE I:MAPSS_EQUILIBRIUM1) Initialization:main (mapss_main)

mapss (mapss_main)

process_command_line (mapss_main) - i/omain_initialize (mapss_main) - opens files, initializes variables

2) EQ MAPSS is first run to give CENTURY an initial vegetation grid.

mapss_equilibrium_2d (mapss_main)

Miscellaneous data input and initialization subroutinesmapss_equilibrium_1d (mapss_equil)

init_data_point (mapss_equil) - sets various parts of data_point to initial dummy valuesset_hemisphere (mapss_equil) - checks if current row is above or below equator, or set on command line

soil_prep (mapss_equil) - returns error if missing soils data, checks valid soil data, checks/adjusts soil composition variablesclimate_prep (mapss_equil) - does Southern Hemisphere adjustments to climate, sets temperature zone, snow fall and melt, rain

events, growing degree days, vapor pressure deficit with ApplyLifeformRules. Calculates PET (InitPet), checks precipitation limits.

lai_limit (mapss_equil) - calls set_lai_bounds to set LaiUpperBoundEnergy, calls input_leaf_root_areas to set maxlaiLaiCycle (woody_equil)

InitConductance (woody_equil)InitSoilWater (drain)InitSnow (woody_equil)SetCurrPrev (woody_equil)DistributePpt (distrib)

Appendix 2: Routine

Calling Sequence

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transpiration (transpire)

LaiCycleEquilibrium (woody_equil)ReiterateLaiCycle (woody_equil)GrassWoody (grasses_equil)SwapYears (woody_equil)

NewMonthlyLai (woody_equil)

store_output (io_general)free_input_data (io_general)

CASE IICENTURY_EQUILIBRIUM(1) Initialization:main (mapss_main)

mapss (mapss_main)

process_command_line (mapss_main) - input/outputmain_initialize (mapss_main) - opens files, initializes variables

(2) EQ MAPSS is first run to give CENTURY an initial vegetation grid.

century_equilibrium_2d (mapss_main)

Miscellaneous data input and initialization subroutinesmapss_equilibrium_1d (mapss_equil)

See Case I.

MapssToVemapConvert (classification_bgc)

(3) EQ CENTURY takes the vegetation type output by EQ-MAPSS and calculates associated C and N pools corresponding to equilibrium conditions by

using long term climate data input (1 year repeated). This runs until slow soil C is stabilized (up to 3,000 years for forest types).

century_equilibrium_1d (mapss_1t)

Miscellaneous data input and initilization subroutines.cen_init (csa_main) - steps through standard CENTURY to get output and state, until EQ

vetofix - translates VEMAP vegetation classes into CENTURY fix file namesstateinit (passvars) – initializes all state variables to zero. After, calls statein() to disburse zeros to global state variablesdetiv (csa_detiv) - CENTURY initialization: determines name of schedule file which contains the name of site file, values of |

timing variables, and order of events

fixin - sets values of fixed parameters and initial values (xfix.100 files)sitein - reads the parameter file (.100 files)

extend - reads from binary file until EOF

cropin - obtains the new crop or forest system values

cmplig - recalculates plant lignin; returns the fraction of residuecropmix - calculates intermediate values of selected crop.100 parameters based on a C3/C4 index

treein - reads in the new forest type

treemix - calculates an index (function of temperature) and calculates all the lifeform dependent parameters

(tree.100 files)

calciv - calculates initial values for temperature, water, and live root carbon variablessumcar - sums carbon to get annual totals

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prelim - preliminary initialization and calculation of variables and parameters

annacc - resets annual accumulatorsinprac - initializes annual production accumulatorspredec - preliminary set-up (once at the start of each run) for comp. related to decomposition of soil organic mattersavarp - computes variables for printing or plottingflowclr - clears the C and N flow stack

readblk - reads the next block of events from the schedule file

wthini - determines which weather data will be used

varsin (passvars) - distributes CENTURY output variables after pass from MAPSS

Reports back to MAPSS with new outvars and state.stateout (passvars) - collects CENTURY state variables for pass to MAPSS

varsout (passvars) - collects CENTURY output variables for pass to MAPSS

xfer_climate_year - copies climate variables from input_data to data_point for a single year. Assumes monthly data in input_data.

SouthernHemiSwap or NorthernHemiSet - sets up climate data for CENTURY

cen_init_climate (init_climate) - initializes climate data

Monthly loop:stand_step (csa_main) - runs CENTURY in standard mode once model has been initialized. Broken out from csa_main

readblk - reads the next block of events from the schedule file

wthini - determines what weather data will be used

eachyr - performs tasks that only need to be done once a year (annual loop)

annacc - resets annual accumulatorsweathr - determines current year values for precipitation, temperature and next year’s values for predicting production

potential

co2eff - computes the effect of atmospheric CO2 concentration

cmplig - computes plant lignin; returns the fraction of residue

simsom - simulates flow of carbon and nitrogen (main driver for the model)

cycle - determines relative water content, available water, and decomposition factor related to temperature and water

schedl - determines the next set of scheduling options from .sch file

cropin - reads in the new crop type

cmplig - computes plant lignincropmix - calculates intermediate values of selected crop.100 parameters

co2eff - computes the effect of atmospheric CO2 concentration

omadin - reads in the new omad typegrazin - reads in the new graze typefirein - reads in the new fire typetreein - reads in the new forest type (Read in as default, DN, EN, DB, EB)

treemix - calculates an index (function of temp) and all the lifeform dependent parameters

co2eff - computes the effect of atmospheric CO2 conc.

tremin - reads in the new tree removal type

inprac - initializes annual production accumulatorsprcgrw - computes a growing season precipitation

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------PRODUCTION SUBMODEL

Crop system potcrp - computes monthly production potential based on monthly precipitation

lacalc1 - calculates LAI as a function of leaf C

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Forest system potfor - computes monthly potential production for a forest

lacalc1 - calculates LAI as a function of leaf Clacalc2 - calculates LAI as a function of wood; also averages with lacalc1 LAI

Hydrology h2olos - determines co2 effect on transpiration, calculates all hydrological flows

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------DECOMPOSITION SUBMODEL

decomp - decomposes structural and metabolic components for surface and soil

Litter litdec - litter decomposition

Computes total C flow out of structural, metabolic in layers: SRFC/SOIL

declig - decomposes stuff containing lignin (structural and wood)

respir - computes flows associated with microbial respirationcsched - schedules C flows for decompositionesched - schedules N flow and associated mineralization or immobilizationmnracc - updates mineralization accumulatorscsched - schedules C flows for decompositionesched - schedules N flow and associated mineralization or immobilization

mnracc - updates mineralization accumulators

Wood woodec - wood decomposition routine

Computes total C flow out of fine branches, large wood, coarse rootsdeclig - decomposes stuff containing lignin (structural and wood)

respir - computes flows associated with microbial respirationcsched - schedules C flows for decompositionesched - schedules N flow and assoc mineralization or immobilizationmnracc - updates mineralization accumulators

Soil organic matter somdec - soil organic matter decomposition: SOM1 (surface and soil), SOM2, and SOM3. (som1 to som2, som1 to

som3, som 2 to som 3, som 2 to som1,som3 to som1)

respir - computes flows associated with microbial respirationcsched - schedules C flows for decompositionesched - schedules N flow and associated mineralization or immobilizationmnracc - updates mineralization accumulators

Final Calculations Updates decomposition and nitrogen flows:

flowup - completes the flows that were scheduled to occur at or before “time”

sumcar - sums carbon to get totalserosn - erosion routine

soilos - computes soil loss for som1, som2, or som3

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------DEATH SUBMODEL

Grassland crop - driver for calling all of crop code

falstd - simulates fall of standing dead for the month

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droot - simulates death of roots for the month

dshoot - simulates death of shoots for the monthflowup - completes the flows that were scheduled to occur at or before ‘time’sumcar - sums carbon to get totalsgrowth - simulates production for the month

restrp - restricts actual production based on C:N ratios. Calculates minimum, maximum whole plant nutrient

concentrationnutrlm - ‘nutrient limitation for plants is based on demand’

grem - simulates removal of crop or grass by fire or grazing for the month

Forest trees - simulates forest production for the month

wdeath - death of leaves, fine branches, large wood, fine roots, and coarse rootsflowup - completes the flows that were scheduled to occur at or before “time”sumcar - sums carbon to get totalsfrem - forest removal - fire or cutting (includes storms and litter burning in forest)

livrem - removal of live biomass from cutting or fire in a forestdedrem - removal of dead wood from cutting or fire in a forestkillrt - death of roots from cutting or fire in a forestcutrtn - elemental return from a cutting event

firrtn - elemental return from a fire event

litburn - simulates removal of litter by fire for the month

Final calculations Updates state variables and accumulators and sum carbon isotopes:

flowupsumcar

harvst - harvests the crop

leach - computes the leaching of nitrogen, phosphorus, and sulfur

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Updates state variables and accumulators and sums carbon isotopes:

Updates time.wrtbin - writes all output values to the binary fileWrites output variables and state to MAPSS for each time step:stateoutvarsout

*** For standard CENTURY runs, runs model only until slow pool organic matter achieves relative equilibrium

eq_test - sets EQ threshhold for SOM2C change in fraction per year

add_mapssvars (mapss_1t)Saves only last month for seeding transient run.buffer_bgc_data (mapss_1t) - buffers bgc_outvars array from currnet bgc run into bgc_data for later save to disk store.cen_end (csa_main) - CENTURY closes file.

store_output_bgc (io_general) - stores data in mapss_output to external file or other storefree_input_data (io_general) - de-allocates space for input variable arrays in input_data structurefree_bgc_buffer (io_general)

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III CENTURY_TRANSIENT

(1) Initialization:main (mapss_main)

mapss (mapss_main)

process_command_line (mapss_main) - input/outputmain_initialize (mapss_main) - opens files, initializes variablesmapss_2tt (mapss_main)

alloc_input_data (io_general) - allocates space for input data variable arrays in input_data structurealloc_bgc_buffer (io_generalinit_data_size (io_general) - sets data_size structure to describe extent of data requested

alloc_input_data (io_general) - allocates space for input data variable arrays in input_data structure

get_input (io_general) - reads climate data in from external file and maybe other location

InputNCValues (nc_input) - read block of data defined in data_size and var_list. Loads into input_data.

FindStartPosition (nc_input) - filters background points. Determines start position.

ReadClimate (nc_input) - loads climate variables in var_list. Sets input_data.len to length of each variable arrayReadSite (nc_input)

xfer_site (io_general) - copies site variables from input_data to data_point, elevation and soil data nowxfer_climate_year (io_general) - copies climate variables from input_data to data_point for single year, assumes mo data in input_data

(2) EQ MAPSS is first run to give CENTURY an initial vegetation grid. This was also done in case II (CENTURY_EQUILIBRIUM) but is done here to

initialize some variables that are not included in the seed file (that is, zone).

mapss_equilibrium_1d (mapss_equil) - returns GOOD_POINT_RETURN if MAPSS was able to run this point.

See case I.

MapssToVemapConvert (classification_bgc) sets initial tree and crop mix

load_init_bgc (nc_out_bgc) - loads data from netCDF file for seeding transient runxfer_climate_year (io_general) - copies climate variables from input_data to data_point for a single year

(3) Transient CENTURY (OneStep CENTURY) - Values of C and N output in EQ CENTURY are used as initialization values for the transient run.

Transient climate data are 100 years.

mapss_1t (mapss_1t)

init_data_point (mapss_equil) - sets various parts of data_point to initial dummy values (should be from seed file)set_hemisphere (mapss_equil) - checks if current row is above or below equator, or set on command lineset_initial_bgc_vars (mapss_1t) - basic biogeocehmical variable initialization (should be read from seed)xfer_site (io_general) - copies site variables from input_data to data_pointsoil_prep (mapss_equil) - returns error if missing soils data, check valid soil data, checks or adjusts soil composition variables

set_drainage_constants (drain)

xfer_climate_year (io_general) -copies climate variables from input_data to data_point for a single year

SouthernHemiSwap or NorthernHemiSet (misc_init) - sets up climate data for CENTURY

Start of CENTURY-----------------------cen_init_climate (init_climate) - passes soils info and latitude to CENTURY assignment for output in xfer_to_output

initialization

cen_init_soils (init_soils) - transforms sand, clay content into percentage; depth changed from mm to cm; nlayer is calculated here;

calculates adep

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cen_init_lat (init_lat) - takes the absolute value of latitude

mapss_init (mapss_1t) - initializes MAPSS parameters at start of a run (should read seed file)

efold_climate_init (mapss_1t) - seeds efold data with first year’s values

cen_init (csa_main) - simulates C and N cycling, steps through standard CENTURY to get output and state, until EQ

vetofix - translates VEMAP veg classes into CENTURY fix file namesstateinit (passvars) - initializes all state variables to 0. After, calls statein() to disburse zeros to global state variables

detiv (csa_detiv) - CENTURY initialization: determines name of schedule file that contains the name of the site file, values of

timing variables, order of events

fixin - sets values of fixed parameters and initial valuessitein - reads starting values from site-specific parameter fileextend - reads from binary file until EOFcropin - obtains the new crop or forest system values

cmplig - recalculates plant lignincropmix - calculates intermediate values of selected crop.100 parameters based on a C3/C4 index

treein - reads in the new forest type

treemix - calculates an index (function of temp) and calculates all the lifeform dependent parameters

calciv - calculates initial values for temperature, water, and live root carbon variablessumcar - sums carbon to get totals for use in partit

partit - partitions N into structural and metabolic compartments

csched - schedules C flows for decomposition (to go to metabolic and structural)

flowup - completes the flows scheduled to occur at or before “time”sumcar - sums carbon to get totals

sumcar - sums carbon to get totals

Sums som1 surface and soil isotopes separately

prelim - preliminary initialization and calculation of variables and parameters

annacc - resets annual accumulators

inprac - initializes annual production accumulatorspredec - preliminary set-up (once at the begininning of each run); computations related to decomposition of SOMsavarp - computes variables for printing or plottingflowclr - clears C and N the flow stack

Reads the first block of events:readblk - reads the next block of events from the schedule file

wthini - determines which weather data will be used

predec - preliminary set-up (once at begininning of each run) for Soil Organic Matter Submodel

varsin (passvars) - distributes CENTURY output variables after pass from MAPSS

stateout (passvars) - collects CENTURY state variables for pass to MAPSSvarsout (passvars) - collects CENTURY output variables for pass to MAPSS

if fire, then:

ReadFireParams (fire_param) - reads fire model parameters from data file

fire_param.dat

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

START YEAR LOOP

xfer_climate_year (io_general) - copies climate variables from input_data to data_point for a single yearSouthernHemiSwap or NorthernHemiSet (misc_init) - sets up climate data for CENTURYcen_init_climate (init_climate) - passes soils information and latitude to CENTURY assignment for output in xfer_to_output

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If petcalc,

InitPet (misc_init)

CalcSatVP (pet_calc)

CalcPet (pet_calc)

EFOLDING--------efold_climate (mapss_1t) - applies efolding to data_point.ppt and .tmp|------------------------------efold (mapss_1t) - does a single value efold

xfer_climate_year (io_general) - copies climate variables from input_data to data_point for a single year

End of CENTURY climate_prep (mapss_equil) - does Southern Hemisphere adjustments to climate, sets temperature zone, snow fall and melt, rainINITIALIZATION------------------events, growing degree days, vapor pressure deficits w/ApplyLifeformRules, calc PET (InitPet), check precipitation limits...

START MONTHLY LOOP mapss_1d (mapss_1t) - monthly loop to call BGC model monthly time routine, calls MAPSS classification routine, saves

BGC output to cen_data array, saves other output to mapss_output structure

FIRE MODULE---------------------------FireData (fire_data) - estimates daily values of temperature, RH, wind speed, solar radiation, precipitation

(first part) intensity, precipitation, snowfall, snowpack, snowmelt

init1 (fire_data) - initializes daily data array variablesdaily_ppt (fire_data) - precipitation daily data generatordaily_dat (fire_data) - daily data generatorsnow_cond (fire_data) - calculates snowpack and snowmeltlightning (fire_data) - lightning function

DfuelMC (dfuel_mc) - estimates percentage moisture content of dead fuels in the 1;10;100; and 1,000-hour time

lag classes and flammabilityinit2 (dfuel_mc) - initializes data point variablescnvrt_units (dfuel_mc) - converts climatic variables to required unitsfuel_mc (dfuel_mc) - calculates dead fuel moistureshade_temp (dfuel_mc) - corrects temperature for canopy shadeshade_rh (dfuel_mc) - corrects relative humidity for canopy shadeshade_rad (dfuel_mc) - corrects radiation for canopy shade

------------------------------------------------------------------flammability (dfuel_mc) - estimates fine fuel flammability

cen_step (csa_main) - calls statein (obtains climate, soils data from MAPSS); updates schedule file; calculates all

biogeographic indices; includes whatever is left of readblk; updates fire index; at year’s end - changes vegtype,determines whether fires should happenstatein (passvars) - routine disburses CENTURY state variables into proper global variablesupdate_sched - moves this year’s scheduled events from storage arrays into the working arrayveg_change - calls treemix, cropmix after passing biogeography indices to MAPSS

treemix - calculates an index (a function of temperature), calculates all the lifeform dependent parameterscropmix - calculates intermediate values of selected crop.100 parameters based on a C3/C4 index

vetocen - translates VEMAP vegetation classes into MAPSS vegetation classesupdate_event - overwrites existing events or add new onespredec - preliminary set-up (once at the begininning of each run) for Soil Organic Matter Submodeleachyr - performs tasks that need to be done only once a year

annacc - resets annual accumulatorsweathr - determines current year values for precipitation and temperature and next year’s values for

predicting production potential

co2eff - computes the effect of atmospheric CO2 concentration

cmplig - computes plant lignin

simsom - simulates flow of C and N (main driver for model)

cycle - determines relative water content, available water, and decomposition factor related to

temperature and water

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schedl - determines the next set of scheduling options from the sch file

begins event loopcropin - reads in the new crop type

cmplig - computes plant lignincropmix - calculates intermediate values of selected crop.100 params

co2eff - computes the effect of atmospheric CO2 concentration

omadin - reads in the new omad typegrazin - reads in the new graze type

firein - reads in the new fire typetreein - reads in the new forest type (as default, DN, EN, DB, EB)

treemix - calculates an index (function of temperature) and all lifeform dependent parameters

co2eff - computes the effect of atmospheric CO2 concentration

tremin - reads in the new tree removal type

inprac - initializes annual production accumulators

prcgrw - computes a growing season precipitation

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------PRODUCTION SUBMODEL

Crop system potcrp - computes monthly production potential based on monthly precipitation

lacalc1 -calculates LAI as function of leaf C

Forest system potfor computes monthly potential production (forest)

lacalc1 -calculates LAI as function of leaf Clacalc2 - calculates LAI as a function of wood; averages with lacalc1 LAI

Hydrology h2olos - determines CO2 effect on transpiration, calculates all hydrological flows

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------DECOMPOSITION SUBMODEL

decomp - decomposes structural and metabolic components for surface or soil layer

Litter litdec - litter decomposition

Computes total C flow out of structural and metabolic in layers: SRFC and SOILdeclig - decomposes stuff containing lignin (structural and wood)

respir - computes flows assoc. with microbial respirationcsched - schedules C flows for decompositionesched - schedules N flow and associated mineralization or immobilizationmnracc - updates mineralization accumulatorscsched - schedules C flows for decompositionesched - schedules N flow and associated mineralization or immobilizationmnracc - updates mineralization accumulators

Wood woodec - wood decomposition routine

computes total C flow out of fine branches, large wood, coarse rootsdeclig - decomposes material containing lignin (structural and wood)

89
respir - computes flows assoc. with microbial respiration

csched - schedules C flows for decompositionesched - schedules N flow and associated mineralization or immobilizationmnracc - updates mineralization accumulators

Soil Organic Matter somdec - soil organic matter decomposition: SOM1 (surface, soil), SOM2, and SOM3 (som1-som2, som1 - som3, som

2-som 3, som 2-som1,som-som1)

respir - computes flows associated with microbial respirationcsched - schedules C flows for decompositionesched - schedules N flow and associated mineralization or immobilizationmnracc - updates mineralization accumulators

Final Calculations Updates decomposition and nitrogen flows:

flowup - completes the flows scheduled to occur at or before ‘time’sumcar - sums carbon to get totalserosn - erosion routine

soilos - computes soil loss for som1, som2, or som3

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------DEATH SUBMODEL

Grassland crop - driver for calling crop code

falstd - simulates fall of standing dead for the monthdroot - simulates death of roots for the monthdshoot - simulates death of shoots for the monthflowup - completes the flows scheduled to occur at or before “time”sumcar - sums C to get totalsgrowth - simulates production for the month

restrp - restricts actual production based on C:N ratios. Calculates minimum and maximum whole plant

nutrient concentration

nutrlm - ‘nutrient limitation for plants is based on demand’

grem - simulates removal of crop or grass by fire or grazing for the month

Forest trees - simulates forest production for the month

wdeath - death of leaves, fine branches, large wood, fine roots, coarse rootsflowup - completes the flows scheduled to occur at or before ”time”sumcar - sums C to get totalsfrem - forest removal - fire or cutting (includes storms and litter burning in forest)

livrem - removal of live biomass from cutting or firededrem - removal of dead wood from cutting or firekillrt - death of roots from cutting or fire in a forestcutrtn - elemental return from a cutting eventfirrtn - elemental return from a fire event

litburn simulates removal of litter by fire for the month

Final Calculations Updates state variables and accumulators and sum carbon isotopes:

flowupsumcarharvst - harvests the cropleach - computes the leaching of nitrogen

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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Updates time.wrtbin - writes all output values to the binary filestateoutvarsout

Vemap2Mon - captures monthly value of VEMAP2 output variablesCenturyFCarbToMapssLaiSLA (mapss_1t) - redoes old biomass-LAI translator, uses published SLAs

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------FIRE MODULE (second part)

Inputs LfuelMC (lfuel_mc) - estimates percentage moisture content for live herbaceous and tree fuel classes from CENTURY soil

moisture indices and water stress vs. moisture content functionlive_mc (lfuel_mc)

FuelLoad (fuel_load) - estimates loading in all live and dead fuel classes from the biogeochemical module of carbon pools and

various allometric functions chosen with information from the biogeographic moduletree_dim (fuel_load) - estimates dbh and heightlive_wood (fuel_load) - estimates branch portion of live wood biomass

dead_wood (fuel_load) - estimates loads of live branch and stem wood classesfuel_depth (fuel_load) - estimates fuel bed depth

Process FireBehavior (fire_behav)

get_jul (fire_behav) - gets Julian days for beginning and end of current monthinit3 (fire_behav) - initializes some data_point structure membersget_daily (fire_behav) - creates pseudo daily values for fuel moisture, loadingassign (fire_behav) - makes local variable assignments from data_point structure, some metric to English conversionprelim (fire_behav) - makes some preliminary calculations of spread model input variablesspread (fire_behav) - rate of spreadrelease (fire_behav) - energy releaseintensity (fire_behav) - fireline intensity and related measures

crown_fire (fire_behav) - crown fire start

Outputs FireEffect (fire_eff)

init4 (fire_eff) - initializes members of datapoint structurecrown_kill (fire_eff)mortality (fire_eff)consump (fire_eff)emissions (fire_eff)

FireOccur (fire_occur)FireSched (fire_sched) - sets CENTURY fire variable values for fires that occurred in current month

part_burn (fire_sched)

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

add_mapssvars (mapss_1t)buffer_bgc_data (mapss_1t) - buffers bgc_outvars from current bgc run into bgc_data for later save to disklai_allocate (mapss_1t) - allocates month LAI to lai_values, based on MAPSS vegetation class

FindMeanLai (grasses_equil)FindMaxLai (mapss_1t) - returns the average LAI for the growing season

-------------------------------efold_biogeog (mapss_1t) - applies efolding to some biogeographic function inputs

Biogeography Module efold (mapss_1t)) - does a single value efold

 Biogeog (mapss_1d) - rules to determine vegetation categories

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-------------------------------------Lifeform (lifeform) - rules to determine lifeforms

xfer_to_output (mapss_1t) - loads mapss_output structure from various variablesadd_mapssvars (mapss_1t)buffer_bgc_data (mapss_1t) - buffers bgc_outvars from current bgc run into bgc_data for later save to disk

END of MONTH cen_end (csa_main) - does a little clean up and ends this CENTURY sessionand YEAR LOOPS Else: No CENTURY run here so call it a background point-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

store_output_bgc (io_general)store_output (io_general)free_input_data (io_general) - deallocates space for input variabe arrays in input_data structurefree_bgc_buffer (io_general)

main_finalize (mapss_main)

close_io (io_general) - closes files (netCDF only now) at end of runexcess_at_events_count (transpire)

92
Lenihan, James M.; Daly, Christopher; Bachelet, Dominique; Neilson, Ronald P.

1998. Simulating broad-scale fire severity in a dynamic global vegetation model.

Northwest Science. 72: 91-103.

Simulating the impact of fire in a broad-scale dynamic global vegetation model (DGVM)

used for global change impact assessments requires components and concepts not part

of existing fire modeling systems. The focus shifts from fire behavior and danger at the

small scale to the system-specific impacts of fire at the broad scale (i.e., fire severity).

MCFIRE, a broad-scale fire severity model we currently are developing as part of our

MAPSS-CENTURY DGVM, simulates the occurrence and impacts (i.e., vegetation

mortality and fuel consumption) of relatively infrequent and extreme events historically

responsible for the majority of fire disturbance to ecosystems. The occurrence of severe

fire is strongly related to synoptic-scale climatic conditions producing extended drought,

which is indicated in MCFIRE by the low moisture content of large dead fuels. Due to

constraints posed by currently available datasets, we have been developing our DGVM

model on a relatively fine-scale data grid at a landscape scale, but we will implement the

model at regional to global scales on much coarser data grids. Constraints on the broadscale impact of severe fire imposed by the fine-scale heterogeneity of fuel properties

will be represented in our coarse-scale simulations by subgrid parameterizations of the

fire behavior and effects algorithms for distinct land surface types. Ecosystem structure

and function often are constrained by disturbance, so it is critical to include disturbance

processes in dynamic vegetation models used to assess the potential broad-scale

impact of global change. The ability to simulate the impact of changes in fire severity on

vegetation and the atmosphere has been a central focus in the development of the

MAPSS-CENTURY DGVM.

Keywords: Fire, simulation, broad-scale, fire severity model, DGVM (dynamic global

vegetation model), disturbance.

Daly, Christopher; Bachelet, Dominique; Lenihan, James M.; Neilson, Ronald P.;

Parton, William; Ojima, Dennis. 2000. Dynamic simulation of tree-grass interactions

for global change studies. Ecological Appplications. 10(2): 449-469.

The objective of this study was to dynamically simulate the response of a complex

landscape, containing forests, savannas, and grasslands, to potential climate change. It

thus was essential to accurately simulate the competition for light and water between

trees and grasses. Accurate representation of water competition requires simulating the

appropriate vertical root distribution and soil water content. The importance of differential

rooting depths in structuring savannas has long been debated. In simulating this

complex landscape, we examined alternative hypotheses of tree and grass vertical root

distribution and the importance of fire as a disturbance, as they influence savanna

dynamics under historical and changing climates. MC1, a new dynamic vegetation

model, was used to estimate the distribution of vegetation and associated carbon and

nutrient fluxes for Wind Cave National Park, SD. MC1 consists of three linked modules

simulating biogeography, biogeochemistry, and fire disturbance. This new tool allows us

to document how changes in rooting patterns may affect production, fire frequency, and

whether or not current vegetation types and lifeform mixtures can be sustained at the

same location or would be replaced by others. Because climate change may intensify

resource deficiencies, it will likely affect allocation of resources to roots and their

distribution through the soil profile. We manipulated the rooting depth of two lifeforms–

Appendix 3:

Abstracts

93
trees and grasses–competing for water. We then assessed the importance of variable

rooting depth on ecosystem processes and vegetation distribution by running MC1 for

historical climate (1895-1994) and a global climate model (GCM)-simulated future scenario

(1995-2094). Deeply rooted trees caused higher tree productivity, lower grass productivity,

and longer fire return intervals. When trees were shallowly rooted, grass productivity

exceeded that of trees even if total grass biomass was only a third to a fourth that of

trees. Deeply rooted grasses developed extensive root systems that increased nitrogen

uptake and the input of litter into soil organic matter pools. Shallow–rooted grasses

produced smaller soil carbon pools. Under the climate change scenario, NPP (net

primary production) and live biomass increased for grasses and decreased for trees, and

total soil organic matter decreased. Changes in the size of biogeochemical pools

produced by the climate change scenario were overwhelmed by the range of responses

across the four rooting configurations. Deeply rooted grasses grew larger than shallowly

rooted ones and deeply rooted trees outcompeted grasses for resources. In both

historical and future scenarios, fire was required for the coexistence of trees and grasses

when deep soil water was available to trees. Consistent changes in fire frequency and

intensity were simulated during the climate change scenario: More fires occurred

because higher temperatures resulted in decreased fuel moisture. Fire also increased in

the deeply rooted grass configurations because grass biomass, which serves as a fine

fuel source, was relatively high.

Keywords: Dynamic vegetation model, MC1, global change, climate change, tree-grass

competition, belowground resources, root distribution, water availability, savanna, fire,

Wind Cave National Park, grassland, landscape.

Key phrases: MC1 dynamic vegetation model, simulation of tree-grass interactions,

model sensitivity to allocation of deep water resources, role of root distribution in

maintenance of savannas, effect of climate change on tree-grass competition, role of

fire in maintenance of savannas, impact of climate change on fire frequency and

intensity, effect of root distribution on simulated fire frequency and intensity.

94
Bachelet, Dominique; Lenihan, James M.; Daly, Christopher; Neilson, Ronald P.

[2001]. Interactions between fire, grazing, and climate change at Wind Cave National

Park, SD. Ecological Modelling. 134: 229-244.

Climatically, Wind Cave National Park is at the ecotone between grassland and forest

where small climatic variations can lead to dominance by either system. Natural fires

promoted by productive grassy areas and moderate grazing by native herbivores have

maintained a system where trees and grasses coexist. It is a fragile equilibrium, however,

that can be greatly affected by management practices, such as fire suppression or

livestock grazing, and also by climatic changes. We used a dynamic vegetation model,

MC1, that simulates vegetation distribution, associated biogeochemical cycles, and

natural fire occurrence to test the sensitivity of the system. Simulated fire suppression

enhances the expansion of forests. Fire, promoted by healthy grasslands, acts as a

negative feedback on tree development, because it consumes seedlings and live foliage

and thus reduces tree growth and survival. Simulated grazing reduces grass biomass

and fuel load thus indirectly reducing fire frequency and enhancing the expansion of

forests or woodlands. Future climate projections simulate warmer and drier weather by

the end of the next century. This would constrain the growth of trees that rely on the

availability of deep water resources and favor shrub and grass development and a shift

from forests to savannas. The loss of trees might then be inevitable. To prevent shrub

encroachment over grassland areas and to conserve a source of forage for herbivores,

park managers will need to restrict the grazing pressure and maintain a frequent fire

regime that can prevent establishment of woody seedlings.

Keywords: Management, ponderosa pine, grasslands, simulation model, biogeography,

biogeochemistry, carbon, nitrogen, water.

95
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