This file was created by scanning the printed publication. Text errors identified 

by the software have been corrected; however, some errors may remain.

Weyermann, Dale L.; Fight. Roger D.; Garrett, Lawrence D. 1991. A users guide

for SAMM: a prototype southeast Alaska multiresource model. Gen. Tech. Rep.

PNW-GTR-274. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 49 p.

This paper instructs resource analysts on using the southeast Alaska multiresource

model (SAMM). SAMM is an interactive microcomputer program that allows users to

explore relations among several resources in southeast Alaska (timber, anadromous

fish. deer, and hydrology) and the effects of timber management activities (logging,

thinning, and road building) on those relations and resources. This guide assists

users in installing SAMM on a microcomputer, developing input data files, making

simulation runs, and storing output data for external analysis and graphic display.

Keywords: Multiresource, forest management, software, microcomputer, users guide,

models, timber, hydrology, fisheries, deer.

1 Introduction

1 General Information About the SAMM Data Files

3 Watershed Description

5 Installation

5 Minimum System Requirements

5 Step-by-Step Installation

5 Starting a SAMM Simulation

6 Changing Run Options

6 Run Parameters

6 Data File Names

8 Run-Time Graphs

11 Quitting the Program and Saving Output

12 Input Requirements for SAMM (Data Files)

13 Default Values

14 Geographic Description of Watershed

18 Hydrologic Data

23 Data for Deer Submodel

27 Description of Management Plan

30 Economic Data

32 Advanced Topics

32 Initializer Run

32 Saving Run Parameters

33 Output File Names

Abstract

Introduction

General Information

About the SAMM

Data Files

The southeast Alaska multiresource model (SAMM) is an interactive computer program simulating the links among several natural resources in southeast Alaska and

the effects of typical management schemes on those resources over time (Fight and

others 1990).

Management options are specified for a certain year in the simulation period, and the

effects of those options are reflected in the succeeding years. Simulation length is

user specified and ranges from 1 to 150 years.

The program is spatially oriented; the user must define the spatial relations between

all land areas in the watershed and the stream system draining the watershed. Management options are specified for discrete land units, and their spatial orientation to

the stream system is important. The program simulates a single watershed, with the

stream system having only one outlet to salt water. Deer herds are confined to the

watershed (they cannot leave the watershed for other ranges), and resources are not

shared among herds (that is, each herd has an exclusive, user-defined range within

the watershed).

All forest area is assumed to be in the old-growth state at the beginning of the simulation and to require 250 years to return to old growth after harvest (logging). Simulations with SAMM are limited to 150 years, however, so logged areas will not

return to old growth in SAMM.

The sample data files in the appendices are actual data that can be used to run

SAMM. These, files are provided on the SAMM distribution diskette (containing the

full SAMM model) under the following names:

VCUDATA.TST

HYDRODAT.TST

DEERDATA.TST

PLANDET.TST

ECON.DAT

SAMM data files are text files that can be modified by using any word processor or

text editor. If modified, files should be saved as flat, ASCII, or DOS text files or in

any format that does not include special word processing control characters (such as

tabs, indents, word wrap at the end of lines, and so forth). Files should have hard

carriage returns at the end of each line.

SAMM data files are read as unformatted data in the input part of the program.

This means that any nonnumeric data must be delimited by single quotation marks.

SAMM data files make liberal use of text delimited by single quotation marks as

guides for the user in modifying the data; for instance, nearly every data item in file

HYDRODAT.TST is preceded by a line of text that is delimited with single quotation

marks. These lines of text must not be deleted from the data file. (The line of descriptive text often includes the name of the variable in the program that will read the data

item. This variable name is usually in capital letters or in parentheses and is useful

only to programmers.)

1
Unformatted files use blank spaces to separate all data items. Any number of continuous blank spaces are treated as a single blank space. This allows flexibility in

lining up data items to make them easier to read (for instance, to justify columns at

the right edge.) For this reason, any data item that is zero must have a 0 entered in

the file as a place holder. The following two lines of data, for example, would be read

identically by the program:

1 35.6 0.0 45.2 73

1 35.6 0.0 45.2 73

These two lines would yield different results because the data item that has the value

0.0 has been omitted in the second line:

1 35.6 0.0 45.2 73

1 35.6 45.2 73

In some situations, multiple records of data are read in until an end-data marker is

reached. In SAMM, the end-data marker is -99, because this is a value unlikely to be

encountered in data. The use of an end-data marker means that the user need not

count the number of entries of a certain data item and enter that number into the

data file. In VCUDATA.TST, for example, the user need not count the number of

spatial units ahead of time, but can simply use the end-data marker to indicate that

the last spatial unit has been entered. Refer to VCUDATA.TST for examples of using

the end-data marker (appendix 3).

The geographic description of the watershed is input by the user; it can represent

data from an actual watershed (geographical information system [GIS] output data,

for example) or data from an artificial watershed designed to test management

scenarios in a controlled environment. 

The model allows only a single simulation per run; that is, the user may wish to run a

150-year simulation with logging and contrast that with a 150-year simulation without

logging. This would require two runs of SAMM, and the outputs from each would

have to be compared externally to SAMM.

The model allows the user to monitor four resource indicators as the simulation

progresses; for example, deer numbers, fish spawners, miles of road built, and

deepest snow at sea level. When the simulation period is complete, the user can

choose from a menu of 37 graphs (see appendices 1 and 2) and, if desired, replace

or overlay graphs showing different variables. Graphs can be printed on a dot-matrix

printer.

Once the program is exited, all on-screen graphs are lost, although the data to

produce them can be saved on disk files. Disk files can be exported to commercial

software, such as Lotus 1-2-3, to produce and print graphs.1

1

 The use of trade, firm, or corporation names in this publication is for the information and convenience of the reader.

Such use does not constitute an official endorsement or

approval by the U.S. Department of Agriculture of any

product or service to the exclusion of others that may be

suitable.

2
Watershed

Description

The SAMM model is designed to simulate resource interactions over time in a single

watershed. The watershed is not bound by acreage limitations, although the model is

limited by the number of discrete land units the watershed can be divided into (currently 30 spatial units with up to five site classes each). Spatial units are sections of

the watershed defined by stream reaches and elevation. Each spatial unit is further

subdivided into one to five site classes, which reflect timber productivity and forest

characteristics. Site classes are defined with standard timber classification methods.

The program treats each site class of each spatial unit as a separate land unit. Management actions (timber harvest and road building) are specified for a particular

spatial unit in a particular year.

Care must be taken in defining the spatial unit boundaries to ensure that runoff

from each spatial unit goes to a single stream reach, that each stream reach passes

through only one spatial unit. and that the area in a spatial unit can be described by

a single, average elevation. Land areas draining to different stream reaches, or land

areas crossing a wide elevation gradient, must be subdivided into separate spatial

units.

The stream system in the watershed is assumed to have a single outlet to the ocean,

with the other streams forming a network feeding that stream. To track sediment flows

through the system, streams must be consecutively numbered by the user such that

each stream feeds into a successive stream through the network, finally ending at

salt water.

Input data files must be edited externally to SAMM, but text comments in each file

make them self-explanatory. Input files can be edited with any word processor or

text editor.

An example of how a simulation is made is shown in figures 1, 2, and 3.

Figure 1—System requirements for running SAMM.

3
Figure 2—Files that are required to use SAMM.

Figure 3—Commands to enter to start a

SAMM simulation.

4
Installation

Minimum System

Requirements

The minimum hardware system requirements for using SAMM are:

• IBM-AT or true compatible (model will run on an IBM-PC or IBM-XT class

machine, but will require a long time to run a typical simulation)

Math coprocessor strongly advised (separate version required for machines with

no coprocessor)

CGA, EGA, VGA, or Hercules video card (either monochrome or color)

• 500K bytes RAM available (other RAM resident programs installed at the same

time may limit the amount of available RAM memory and may have to be

removed before SAMM is run)

Epson MX or FX series dot-matrix printer or IBM Proprinter to print graphs

directly from the screen

Hard disk strongly advised (program produces a large number of output files)

Step-by-Step Installation Follow these steps to install SAMM on a computer:

Starting a SAMM

Simulation

Place the SAMM diskette number 1 into drive A

Make sure the screen shows the A> prompt (if not, enter A:)

To copy to a floppy disk, put a blank, formatted diskette in drive B: and enter

COPY *.* B:

To copy to a hard disk, create a subdirectory on the hard disk called SAMM by

entering:

C:

CD\

MD SAMM

CD SAMM

COPY A:\*.4

This will copy the entire diskette to the new subdirectory.

If there is a second SAMM diskette, copy it either to a floppy disk or to the same

subdirectory on the hard disk. Backup copies of diskettes should be made by using

the DOS COPY command.

SAMM produces output files in a subdirectory called GRAFS. This subdirectory must

be created before SAMM is run. If SAMM is run on a floppy disk machine, a formatted

floppy disk with subdirectory GRAFS must be available for output (put the floppy disk

in drive B:, and enter MD GRAFS). If SAMM is run on a hard disk machine, make

sure the prompt is C:SAMM and enter MD GRAFS.

At this point, SAMM should be properly installed on the computer. Change directories

until the computer is in the SAMM directory, or change to drive A if using a floppy

disk machine.

Enter METAWNDO to load the RAM resident graphics driver, which produces graphs

on the screen (required). This needs to be loaded only once for each SAMM session.

Enter PRTSCRN to load the RAM resident printer driver, which makes hard copies of

the graphs on a dot-matrix printer as the simulation progresses (optional). This also

needs to be loaded only once each session.

5
Changing Run

Options

Run Parameters

Data File Names

Enter SAMM to start the program.

A SAMM title screen will appear. Press ENTER to access the first menu.

The first menu that will appear is the main menu, which allows the choice of options

for this simulation (fig. 4). The parameters for the previous runs are the defaults for

the current run.

The option 'ACCEPT PARAMETERS AND NAMES' will be highlighted; to accept the

default parameters, simply press ENTER and the simulation will start.

Three things can be changed for each SAMM run:

RUN PARAMETERS

DATA FILE NAMES

RUN-TIME GRAPHS

To change the run parameters, scroll down to the choice 'CHANGE RUN PARAMETERS' and press ENTER. The program will pause briefly and the screen shown in

figure 5 will appear. To change any of the parameters, scroll until the desired

parameter is highlighted and press the SPACE BAR. For each parameter except

NUMBER OF YEARS TO RUN, the space bar will toggle between YES (parameter

chosen) and NO (parameter not chosen). To change the number of years to run the

model, highlight that option and press the SPACE BAR; a small window will open,

which allows a new number of years to be entered. (If a mistake is made in entering

the new number, simply press ENTER and then the SPACE BAR to choose NUMBER OF YEARS TO RUN, and reenter the correct number.)

One of the parameters, 'INITIALIZER RUN', is provided as an automatic method for

initializing new or changed data sets and is of importance only if the fisheries model

is being run. See the section "Advanced Topics" for more information on the initializer

run.

The initializer run takes as long as a 100-year simulation, so be judicious in using it.

To change the data file names, scroll to the choice 'CHANGE DATA FILE NAMES'

and press ENTER; the screen shown in figure 6 will appear. As before, scroll to the

file name to be changed, press the SPACE BAR, and a window will open to allow

the new file name to be entered. Some error checking is performed, and error messages are displayed if necessary.

The new file name should correspond with an already created file. The new file typically is an edited version of the default file that has been given a new name; for

example, to change the number of acres logged in a given year. load PLANDET.TST

into a word processing program (externally to SAMM) and make the appropriate

changes. The edited file would be saved with a new name, for example PLAN2.TST.

(Be sure that the file is saved without any control characters that are added by some

editors. The file should be a flat file [also called a DOS-file, or ASCII file], and should

be saved by using export or DOS-save commands.)

6
Figure 4—Screen showing main SAMM menu.

Figure 5—How to change run parameters in SAMM.

Path names are not supported. All input data files must be in the same subdirectory

with the SAMM executable code. Input file names must be valid DOS names. File

names must start with a letter and have at most eight letters or numbers, followed by

a period, followed by an optional three-letter or three-number extension. SAMM does

not expect any specific file names or extension. The naming scheme is entirely up to

the user. The file names used in this guide and provided on the SAMM diskette are

examples only. To correct an error, press ENTER, then the SPACE BAR, and reenter

the name correctly.

7
Run-Time Graphs

Figure 6—How to change the names of input data files.

As a SAMM simulation proceeds, graphs showing the changes in four resources are

shown on the screen. The graphs change dynamically as values for each year are

computed, which allows the user to monitor the progress of the simulation. These

four graphs are called run-time graphs.

To change the run-time graphs, scroll to the option 'CHANGE RUN-TIME GRAPHS',

and press ENTER. The screen shown in figure 7 will appear. The arrows pointing

to four of the graph names are the defaults from the previous run; press ENTER to

accept these or scroll to any graph name and press the SPACE BAR to select a

graph (the SPACE BAR toggles between selected and not selected). Only four

graphs are allowed, and the first four with arrows will be the run-time graphs.

Any graph can be selected as a run-time graph except PRES NET WORTH

(TIMBER). This graph can be displayed, however, after the simulation is complete,

because all graphs are automatically scaled to the largest and smallest values at

that time.

Once all parameters, file names, and run-time graphs have been chosen, select the

option 'ACCEPT PARAMETERS AND NAMES', and press ENTER to begin the simulation. If the initializer-run is not run, the four chosen run-time graphs will soon be

displayed, and the year counter at the bottom of the screen will count the completed

years of the simulation (fig. 8). A SAMM simulation cannot be interrupted before the

entire period is complete without a loss of intermediate results. If the simulation is

interrupted (by pressing CONTROL-BREAK), all data generated to that point are lost.

Press ENTER when the simulation has finished to bring up the large menu shown

in figure 9. Scroll with the arrow keys to choose a graph to display; select it with the

ENTER key. This will call the menu shown in figure 10.

8
IF 'CHANGE RUN-TIME GRAPHS' WAS CHOSEN

ON SCREEN 1, THEN THIS SCREEN WILL APPEAR:

ARROWS PaNT TO RUN-TIME GRAPHS OF PREVIOUS SIMULATIONS.

TO CHANGE. SCROLL TO GRAPH WITH ARROW KEYS, AND PRFSS

SPACE BAH TO SELECT OR DE-SELECT.

REMEMBER THAT ONLY 4 GRAPHS CAN BE CHOSEN

SELECT THESE

TO QUIT PROGRAM

Figure 7—How to choose run-time graphs for display during simulation.

FRY (BY SPECIES)

Figure 8—Typical screen during simulation.

The chosen graph can either overlay an existing graph or replace an existing graph.

Any number of graphs can be overlaid on the same set of axes, although the result

may become confusing. Graphs can be either drawn in a chosen quarter of the

screen or scaled to fill the entire screen.

Graphs are automatically scaled to the largest value encountered during the simulation. If graphs are overlaid, each will be scaled to its own largest value, and the

y-axis scale values and title will be shown only for the last graph drawn.

9
THE MAM GRAPH MENU WLL OVERLAY GRAPHS. AND

ALLOW A NEW GRAPH TO BE CHOSEN FOR DISPLAY

(SCROLL WITH ARROW KEYS, CHOOSE WITH 'ENTER' KEY).

GRAPHS UNDERNEATH WLL NOT BE DISTURBED.

Figure 9—Menu showing available graphs.

Figure 10—Menu to place graph in different parts of screen.

10
Quitting the

Program and

Saving Output

If the optional command PRTSCRN was entered before program execution and a

suitable dot-matrix printer is connected to the computer, then graphs can be printed

by pressing the SHIFT and PRTSCRN keys together. This method of printing graphs

will .work any time the program is executing (even during a simulation with only partial

run-time graphs), thereby causing the program to pause temporarily until the graph is

printed. This will produce draft-quality graphs. For presentation quality output, the data

must be saved in a file and graphed with a commercial software graphics package

(see below).

To quit the program, choose one of the last two options in the right column of the

graph menu:

'SAVE OUTPUT, THEN QUIT' or

'QUIT WITHOUT SAVING'.

The first option allows the data for any of the graphs to be saved on disk files, and

allows data analysis or graphing externally to SAMM (fig. 11). Scroll through the list

of graphs and select or eliminate as many as desired with the SPACE BAR; the

program will prompt for a three-letter file name extension. This extension will be

appended to all output files chosen for this simulation. Output files will be named as

follows (EXT is the example user-supplied extension):

GRAFS\GRAPH01 .EXT , the first graph in the menu. WATERSHED VOL (MMBF)

and GRAFS\GRAPH11.EXT . the eleventh graph in the menu, PERCENT FINE

SEDIMENT.

Figure 11—Menu that allows graphs to be chosen for saving to disk.

11
All output graphs will be placed in subdirectory GRAFS. This subdirectory must be

created before SAMM is run. Be sure that enough disk space is available for all

anticipated output files before making a SAMM run; no provision exists for suspending the program and exiting to DOS to delete some files, then restarting the

program. SAMM output files will differ in size depending on the complexity of the

watershed (how many spatial units, stream reaches, deer herds, and so forth) and

the number of years the simulation includes. Typically, each graph will produce a

file between 3K and 50K bytes.

The output file for a particular graph will always have the same root name (for

instance, WATERSHED VOL (MMBF) will always be named GRAPH01) with the

user-specified extension appended. This allows several runs to be made, with each

run having a run-specific extension (such as 001, 002, or 003). Output files for a

particular graph from all runs can later be accessed by using, for example.

DIR GRAPH11.*.

This will list output files for the PERCENT FINE SEDIMENT graph from all runs.

Output data files are written as ASCII text files; that is, they have no control characters or graphics characters included. They can be read by most commercial word

processing, spreadsheet, or graphics software.

Only those graphs with an arrow next to them will be saved on disk files. If ENTER is

pressed without first choosing graphs with the SPACE BAR, no output files will be

created.

The program allows changes to the file extension and to the choices of which graphs

to save.

WARNING: THE PROGRAM WILL REPLACE WITHOUT WARNING FILES

HAVING THE SAME NAME. Be sure of the extension before keying it!

Input Requirements

for SAMM (Data Files)

Choosing 'QUIT WITHOUT SAVING' will terminate the program, and all output data

files from the current simulation will be lost.

SAMM requires five input files to run a simulation. These files contain information

about the following submodels:

Geographic description of watershed

Data on hydrology (description of stream system, individual stream

characteristics, fish populations, fishing pressure, and weather data)

Data on deer (description of deer energetics and hunting pressure)

Description of timber management plan (logging, road building, and so forth)

• Economic values for summarizing some economic results

12
Default Values

No file-naming conventions are required by SAMM (either root name or extension),

although a system of naming data files should be established by each user so that

separate scenarios and data sets are recognizable. The program prompts the user

for input file names, and any legal DOS file names are allowed. Path names are not

supported, so input files should reside in the same subdirectory as the SAMM

executable code.

Because SAMM tracks several resources in the watershed, considerable care must

be taken to assure that the five data files are describing the same watershed. If, for

instance, the geographic description of the watershed specifies only one spatial unit

with a stream reach running through it, then the hydrologic file must not contain any

references to stream reach number 3. The program does some error checking to

uncover inconsistencies in the input data. Most errors found will stop the program

with an ERROR statement on the screen that requires the user to modify the input

data as necessary. ERROR statements are designed to locate problem data, and in

most cases the user will be informed which data item is causing the problem. Some

nonfatal errors are ignored, although a warning is reported on the screen, and the

program is allowed to proceed. These errors must be checked, however, as they

may affect results.

There is a set of maximum limits for watershed size for SAMM input files. These

limits may be changed-by a programmer if necessary, but will require a complete

recompiling and linking of all FORTRAN source code and, if increased, may exceed

the available memory of the computer. Watersheds smaller than these limits are

totally acceptable without a modification to the program.

The default values supplied with SAMM are:

Maximum number of spatial units in the watershed = 30,

Maximum number of stream reaches in the watershed = 10.

Maximum number of logging entries during simulation = 100,

Maximum number of thinning entries during simulation = 50.

Maximum number of road building entries = 100 (each road entry

can specify both main

road and spur road

mileage), and

Maximum number of deer herds in watershed = 5.

All input data files for SAMM can be modified by using a word processor or any text

editor. They are stored as text files. Care must be exercised, however, to maintain

the descriptive headers that precede each data field. These headers are read as

data by the program; if they are removed, the program will not execute properly.

The following sections give detailed descriptions of the major data files needed to

execute SAMM.

13
Geographic Description

of Watershed2

Figure 12—Map of typical watershed.

The geographic description of a watershed is the basis of a SAMM run. Care must

be taken to define the relations between all spatial units and all stream reaches to

ensure a successful simulation. Before the geographic data file is constructed, a map

of the watershed to be simulated is consulted or drawn (fig. 12). The land area characteristics, stream system morphology, and management plan for the watershed are

carefully analyzed, and a plan for dividing the watershed into meaningful spatial units

is devised. The watershed must be divided carefully so that spatial units are somewhat homogeneous in elevation and site characteristics and individual stream reaches

consist of a single dominant stem (so that stream flow down the system will be adequately modeled). The stream reach that flows into salt water can be braided, however, as is typical in southeast Alaska. Discrete land areas and stream reaches are

then delimited and numbered (as described below and as illustrated in fig. 13). This

map is consulted as the data file is constructed to help visualize the geographic

relations between land areas and stream reaches.

The geographic description data file has two parts: the first describes the spatial units

in the watershed, and the second describes the site classes comprising each spatial

unit, as described below.

The watershed is divided into a series of spatial units: each drains to a single stream

reach and each is described by a single elevation (the elevation is an average for the

spatial unit, and the spatial unit may in fact cover a range of elevations) (see fig. 13).

Each spatial unit is then further divided into site classes, with an acreage associated

with each site class. The sum of acreages for all site classes in a spatial unit is the

2

 The sample data file supplied on the SAMM diskettes is

VCUDATA.TST (see appendix 3).

14
Figure 13—How to set up spatial unit and stream reach boundaries.

total acreage for the spatial unit; that is, no part of the spatial unit exists unless categorized by the site class definitions. There cannot be two acreages of the same site

class in a single spatial unit; for example, all acreage of site class 90 in spatial unit 3

is treated as a continuous block (see fig. 14).

Data fields describing spatial units—Following are the data fields describing the

spatial units.

Descriptive label of spatial unit—The descriptive label of the spatial unit is used

only for identification, (for instance, a map reference number or a GIS cross-reference

code) and is not used internally by SAMM. It is 10 characters long and must be set

apart with single quotation marks.

15
Figure 14—How to set up the geographic data file.

Site class bordering each stream reach— the spatial unit has a stream reach

running through it, the site class bordering the stream is entered next. This must be

a valid site class for the spatial unit (70-130). If a site class of 0 is entered, the program will assign the highest site class in the spatial unit to bound the stream. If there

is no stream through the spatial unit, this entry should be 0.

Presence or absence of a stream reach—An indicator is needed to specify

whether a stream reach flows through the spatial unit: '1' indicates a stream flows

through the spatial unit, and '0' indicates no stream flows through the spatial unit.

The program counts the number of spatial units with streams flowing through them,

and this becomes the number of streams in the watershed. The hydrologic data file

must not specify more than this number of streams. (If the watershed has three

streams, the ocean is entered as number four.)

Stream reach receiving runoff—The number of the stream reach that will receive

the runoff from a spatial unit must correspond to the stream reach number in the

hydrologic data file. If a stream flows through the spatial unit (see previous data

entry), then that stream receives all runoff from the spatial unit.

Distance to terminal transfer facility—The total distance in miles from the center of

the spatial unit to the terminal transfer facility (typically the mouth of the watershed)

is used to calculate hauling costs. The program does not calculate hauling costs

based on actual miles of roads in the watershed, but instead uses this typical hauling

distance to compute hauling costs. This value should be representative of the anticipated hauling distance, not distance as the crow flies.

16
Sediment entering a stream reach—The proportion of sediment (from runoff, logging, or road construction) that will reach the stream from each spatial unit is used to

calculate stream sedimentation. If the spatial unit has a reach flowing through it, then

this could be 1.0. If the spatial unit is separated from a stream reach by a large

amount of land. then this could be set lower. As defaults, all spatial units are set to

1.0.

Elevation of the spatial unit—-The elevation of the spatial unit, expressed in feet, is

a single representative elevation for the entire spatial unit. Elevations should be at

least 1 foot.

Hunter accessibility—Accessibility of the spatial unit to hunters at the beginning of

the simulation (those spatial units within 2 miles of salt water, or having preexisting

access for hunters) is used to calculate the hunting pressure on deer. A '1' indicates

the spatial: unit is accessible to hunters; '0' indicates the spatial unit is not accessible

to hunters.

The second part of the geographic data file contains one line of data for each site

class in each of the spatial units listed above (fig. 14). There will be one to five lines

for each spatial unit in the watershed (each spatial unit must have at least one but

not more that five site classes associated with it). The lines of site class information

need not be in any special order; the first field will associate each line with a particular spatial unit. A line of end-data items will follow the last line of site class information. See "General Information About the SAMM Data Files" for more information

on end-data.

Data fields describing site classes—Following are the data fields for each line of

data describing site classes.

Spatial unit number—The spatial unit number corresponds to the order in which the

spatial unit is listed in the data file; the first line of spatial unit data becomes spatial

unit 1 and must. be referenced as spatial unit 1 in all corresponding entries describing

site classes.

Site class—Valid entries for site class are 70, 90.100, 110, and 130.

Acres In each site class—Acres in each site class must be greater than 0.

Random number seed—If an integer between 1 and 32000 is entered, that integer

will be used as the random seed. This allows the same seed to be used for several

simulations, which will result in the same weather pattern each simulation. If a 0 is

entered, the program will use the current time and date (based on the computer's

clock and calendar) to derive a pseudorandom seed, which will vary from simulation

to simulation.

It is very important that the lines of text (delimited by single quotation marks) found in

the data file be maintained when the data file is modified. These lines of text are to

help the user understand the various fields in the data file and are read as data by

the program. If these lines are deleted or moved, the program will not run.

17
Hydrologic Data3 The hydrologic data file describes the hydrologic system in the watershed, including

all stream, weather, and fisheries data. There is a line of text (delimited with single

quotation marks) preceding each data field to help the user understand the data

requirements. These allow the user to modify the data file with any text editor. These

lines of text must not be deleted or moved, because they are read as data by the

program.

The geographic description data file determines the number of stream reaches in the

watershed and denotes the relation of spatial units to stream reaches (fig. 13). The

data in the hydrologic data file describe each stream reach in detail.

 Description of hydrologic data fields—Following are the data fields in the

hydrologic data file.

Stream reach length-—Length of each stream reach is expressed in meters.

Cross-sectional area—The average cross-sectional area for each stream reach is

expressed in square meters. Data for each reach are separated by a blank space

(or spaces).

Stream width—-The average width of each stream reach is expressed in meters.

Side channel surface area—The side channel surface area serves as an additional

protected area for coho salmon (Oncorhynchus kisutch (Walbaum)) and is not included in stream flow or temperature calculations. It is expressed in square meters.

Rubble area—Rubble area in each stream reach is expressed in square meters.

Stream reach pointers—Stream reach pointers are the stream reach numbers

arranged with the headwaters stream reach number listed first and the succeeding

numbers following the stream flow to the ocean (fig. 15). The program calculates

stream flow, sediment transport, and water temperature by following the stream

system from the headwaters to the ocean and allowing the outflow from each reach

to affect the next reach downstream. For this reason, the user must delineate the

order of stream reaches in the stream system, starting at the headwaters and going

downstream until a branch is encountered, and then starting at the headwaters of

the other fork of the branch. In this way, all inflow to a stream from all branches

upstream will be accounted for when each stream reach is considered. If a stream

system had the following relations (as shown in fig. 15):

Reach 1 flows into the ocean,

Reach 2 flows into reach 1,

Reach 3 is a headwater stream and flows into reach 2,

Reach 4 also flows into reach 1 but is not a headwater stream, and

Reach 5 is a headwater stream and flows into reach 4;

3

 The sample data file supplied on the SAMM diskettes is

HYDRODAT.TST (see appendix 4).

18
Figure 15—Assignment of stream reach numbers.

then the order of consideration of the streams would be:

5 4 3 2 1 .

Because reaches 5 and 3 are both headwater (first order) streams, the order also

could be:

3 2 5 4 1 .

Downstream reach—-The next data item is the stream reach number of the downstream reach, from the current reach (fig.. 15). The current stream reach is determined

from the order given in the preceding data, which was 5 4 3 2 1 , so the downstream

reaches would be:

4 1 2 1 6; 

that is, 5 flows into 4, 4 flows into 1, 3 flows into 2, 2 flows into 1, and 1 flows into

the ocean. If the order of streams in the previous data item was 3 2 5 4 1 , this data

field then would be:

214 1 6.

The ocean is numbered as a stream reach; it is given a number that is one greater

than the number of streams in the system.

Complex stream networks can be described with this method. With a map of the

watershed showing numbered stream reaches, the user traces the sediment flow

down the system to determine the numbering for the data file.

19
Care must be taken to avoid having, for instance, stream 3 flow into stream 2, if the

geographic description of the watershed shows only two spatial units with reaches

passing through them. This will result in an error, and the program will stop.

The stream numbers used in this and the previous fields are the same numbers used

in the geographic description data file to denote the destination of runoff sediments

from a spatial unit.

Gravel area—Gravel area for spawning is expressed in square meters. There are

three lines of data, each representing a fish species (pink salmon [Oncorhynchus

gorbuscha (Walbaum)], chum salmon [0. keta (Walbaum)], and coho salmon). Each

column corresponds to a stream reach.

Water capacity—Available water capacity of the soil for each spatial unit is expressed in inches.

Depth of undercut banks —Natural mean depth of undercut banks for each stream

reach is expressed in meters. This is multiplied by the stream reach length to compute the protected area of undercut bank. This is an average depth for the entire

length of the stream reach (both undercut and nonundercut banks) and does not

represent the depth of a single, typical undercut bank.

Large organic debris Input—This is the amount of large organic debris that is added

to the stream at the time of logging and is expressed in cubic meters of debris per

meter of streambank logged. This value will be input only during the year of logging,

it is a one-time pulse of debris occurring during logging.

The old-growth, or natural, input value is 0.01 cubic meters of debris per meter of

streambank. If the user enters 0.02 for this data item, then each meter of streambank

cut during logging will initially contribute twice the natural, old-growth amount of large

organic debris. If the user inputs 0.005, then each meter of streambank cut during

logging will contribute half the natural, old-growth amount. A value of 0.0 will indicate

that there is no pulse of debris input at time of fogging. If the user enters a negative

value, then debris will actually be removed from the stream during logging. A better

way to simulate the removal of debris during logging is to activate the stream cleaning switch (see below), which will automatically remove 50 percent of the debris

during logging.

Equilibrium value for large organic debris—-The equilibrium value for large organic

debris is the amount of large organic debris in each stream in the absence of any

management activities (in the natural, undisturbed state). This is expressed in cubic

meters of large organic debris per square meter of stream surface area for each

stream reach.

Equilibrium value for sediments—-The equilibrium value for sediments is the

proportion of fine sediments in each stream reach in the absence of any

management activities (in the natural, undisturbed state).

20
Fine sediments that move out each year—This is the proportion of fine sediments

moving out of each stream reach each year; it affects the ratio of fine and large sediments in the stream reach. The sediments pass to the next reach downstream. The

values of coarse sediments and large organic debris that move out each year are

calculated in the program.

Maximum bedload shift —This is the maximum percentage of bedload shift that can

occur during extreme storm events for each stream reach. A value of 0.5 would indicate that in a severe storm, a maximum of 50 percent of the stream bed would

overturn (resulting in a 50-percent loss of protected area for coho and a reduction of

50 percent in fry survivability).

Edge effect of banks on stream velocity—This is the reduction in stream velocity

due to the edge effect of streambanks. This will reduce the maximum stream velocity

by the factor entered, thereby resulting in less bedload shift.

Stream cleaning—Stream cleaning is defined as removing 50 percent of the large

organic debris in the affected stream reach at the time of logging. This value is

tempered by the amount of bank cut during logging. If, for instance, 25 percent of the

bank is cut and the stream-cleaning switch is set, then half of 25 percent of the large

organic debris (or 12.5 percent) will be removed from the debris inventory in that

stream reach. A value of 0 indicates that no stream cleaning will occur; a value of 1

indicates stream cleaning will occur at the time of logging.

First-order stream Indicator—This indicator is used to indicate all first-order stream

reaches (headwater reaches) to predict debris torrents. Debris torrents occur only in

first-order streams. The program does not check this indicator against the stream

reach pointers (above).

Solar angle—The solar angle for the region being modeled is used to determine

stream shading; it is given by month, in degrees.

Airtemperature—Average sea level air temperature by month during a typical year

for the region being simulated is given in °F.

Monthly precipitation—Average monthly precipitation in a typical year for the region

being simulated is given in inches.

Streambank vegetation—-The proportion of streambank with vegetation describes

the amount of gaps in the streamside overstory vegetation. Exposed, streams in valley bottoms have more gaps in the streamside vegetation and thus have less stream

shading and higher water temperatures. A value of 0.85 indicates that 15 percent of

the streambank is not forested. There is one value for each stream reach.

Coho in first two age classes in fresh water—The numbers of coho in the first

two age classes are used to start the program with a stable coho population. These

values can be derived by using the initializer run of SAMM. The values are read from

a matrix with rows being age classes and columns being stream reaches.

21
Number of fry—The total numbers of fry in the stream system at the beginning of

the simulation are used to start the program with stable populations and are given by

species (pink, chum, and coho). These values can be derived by using the initializer

run of SAMM.

Ocean resident fish—The numbers of ocean resident fish at the beginning of the

simulation are used to start the program with stable populations and are given by

species (pink, chum, and coho). There is one age class for pinks, four age classes

for chum, and one age class for coho. These values can be derived by using the

initializer run of SAMM.

Precipitation-to-snow conversion factor —The number of inches of snow that is

equivalent to 1 inch of precipitation is the precipitation-to-snow factor.

Temperature lapse rate—The temperature lapse rate is the decrease in temperature

. as a result of elevation, expressed in °F per foot of elevation above sea level.

Snow melt rate—The rate at which snow melts is expressed as the inches of water

equivalent per degree-day (°F).

Standard deviation of temperature—The standard deviation of temperature sets

the degree of variation in the random weather patterns. Values are for both summer

and winter.

 Daily temperature spread—The daily spread of temperatures in summer and winter

is expressed in °F. The daily range of temperatures around the mean will be plus or

minus this value.

 Daylight period—The proportion of daylight in a 24-hour period must be set to 0.5

for the current program.

Commercial harvest rate—The commercial harvest rate by species (pink, chum,

anc coho) is the proportion of each entire spawning stock that is taken by the

commercial fishery in salt water.

Ocean survival rate—The ocean survival rate is the proportion of ocean resident

fish in an age class that survive each year. Values are by species (pink, chum, and

coho).

Subsistence harvest—-The proportion of spawning stock taken by subsistence users

in fresh water is the subsistence harvest. If a logging camp is present, this number

will be modified by the program.

Sport harvest—The proportion of fish removed by sport anglers in the ocean is the

sport harvest. Values are by species (pink. chum, and coho).

Vulnerability to sport catch—Fish vulnerability to sport catch is dependant on the

miles of roads in the watershed (indicating sport angler access). See Fight and

others (1990) for a description of this variable.

22
Average summer stream flows-—Summer stream flows for a 100-year period are

averaged to produce a typical average summer stream flow. Annual summer flows

during the simulation are then compared to this average flow to calculate annual

variation. Flows are calculated by stream reach and are in cubic feet per second.

This variable can be calculated by using the initializer run.

Average winter stream flows—Winter stream flows for a 100-year period are averaged to produce a typical average winter stream flow. Annual winter flows during the

simulation are then compared to this average flow to calculate annual variation. Flows

are calculated by stream reach and are in cubic feet per second. This variable can

be calculated by using the initializer run.

Freshwater fishery harvest strategy—The freshwater fishery can be regulated with

two different strategies: use a 0 to indicate the mixed fishery regulations and a 1 to

indicate a terminal fishery. See Fight and others (1990) for a complete description of

the different strategies. This variable will not affect the saltwater component of the

fishery.

Most of the variables in the hydrology data file can be entered for more stream

reaches than actually exist; for instance, in a watershed with three stream reaches,

the correct data for length of stream reaches might be:

1500 275-417.

But a data file having data for five reaches would work as shown in this example:

1500 275 417 500 265,

because the program will read only the first three data items. This can be useful in

editing data files, because the program will read only the data for the number of

reaches specified in the geographic description data file. The extra data can be

stored without the program execution being affected. If, for instance, the mean

depth of undercut banks for stream reaches was:

0.5 0.2 0.3 ,

then a simulation with no undercut banks could be made by changing the data to:

0.0 0.0 0.0 0.5 0.2 0.3 .

The original data are not lost and can be reconstructed easily by deleting the 0.0's.

Data for Deer Submodel4

 The data for the deer submodel are included in a separate data file. The model allows

several deer herds to occupy the same watershed, although the ranges of the various

herds may not overlap. For the purposes of SAMM, each spatial unit is assigned to

the range of a deer herd and must be in the range of only one deer herd. A watershed might have only one deer herd.

4

 The sample data file supplied on the SAMM diskette is

DEERDATA.TST (see appendix 5).

23
Because deer survival is modeled by using energetics, care must be taken to ensure

each herd has a winter range. Snow not only increases energetic costs but also

decreases the amount of available forage. Snow depth and duration are directly

related to elevation, so a herd that is not allowed a low-elevation winter range may

not survive.

The user is cautioned that the deer model has several interactions among the energetics, variables listed in the deer data file. Changing certain of these variables can

cause unanticipated side effects in another part of the deer model. A firm understanding of deer energetics is strongly suggested before any of these variables are altered

(see Fight and others 1990).

There is a line of text (delimited with single quotation marks) preceding each data

field to help the user understand the data requirements. These allow the user to

modify the data file with any editor. These lines of text must not be deleted or moved,

because they are read as data by the program.

Data fields in deer data file—Following are the data fields in the deer data file.

Number of deer herds In the watershed—The number of deer herds in the watershed must be matched with the mapping of deer herds to spatial units (below) for

the program to run correctly.

Initial deer density—-The initial deer density in the watershed is expressed in deer

per square mile. This value is the initial value for all herds in the watershed.

Mapping of deer herds to spatial units—The mapping of deer herds to spatial units

is specified by assigning a deer herd number to each spatial unit. There will be one

entry in this data record for each spatial unit in the watershed. For instance, if deer

herd number 1 ranges over spatial units 1, 2, and 5, and deer herd number 2 ranges

over spatial units 3, 4, and 6. then the data would be:

112212 .

Care must be taken that the herd numbers assigned to the spatial units are not

greater than the number of herds in the watershed (above).

Local population of hunters—The local population of hunters is the number of

full-time residents of the local area; it does not include short-duration employees,

such as loggers or road builders. (The number of loggers and road builders is

calculated by the program.)

Hunting days by local residents—The hunting days by local residents are specified

as the average number of hunting days per year per local resident hunter. The local

population of hunters (above) is multiplied by this number to calculate total local

hunting pressure, excluding loggers and road builders.

24
Proportion of loggers and road builders that —The hunt proportion of loggers and

road builders that hunt is used to determine the added hunting pressure resulting

from logging or road building in the watershed. Logging and road building employment levels are calculated by the program, and this proportion reduces the total

number of employees to account for the proportion that do not hunt.

Hunting days by loggers or road builders that hunt —The hunting days by loggers

and road builders that hunt are specified as the average number of hunting days per

year per employee that hunts. The total number of employees (hunters and road

builders) that hunt is multiplied by this variable to determine total hunting pressure

from loggers and road builders.

Maximum hunter days from outside the watershed—The maximum hunter days

from outside the watershed is the maximum possible hunting pressure from nonlocal

residents and is measured in total hunter days. This level of hunting pressure is

achieved only when hunting success is the highest.

Gross energy equivalents for forage —The gross energy equivalent is the gross

energy in each forage class in each season, measured in kilocalories per kilogram

of forage. The values are read from a matrix with rows being summer and winter

and columns being forbs, shrubs, and lichens.

Digestibility factor—-The digestibility factor accounts for the variation in forage

quality between open and forested sites for each forage class in each season, as

measured in the percentage of gross energy (above). The values are read from a

matrix with rows being summer and winter and columns being forbs, shrubs, and

lichens. The digestibility factor reduces the gross energy to yield digestible energy.

Metabolizable energy factor —The metabolizable energy factor accounts for the

amount of digestible energy lost to urine production and thus is not available for

deer maintenance and growth. This adjustment is a percentage of total digestable

energy and apply's to all forage classes and seasons.

Body weight of deer —The body weight of deer is measured in kilograms. The

values are read from a matrix with rows being fawns and adults and columns being

summer and winter.

Energy per kilogram of body weight—The energy per kilogram of body weight is

the average kilocalories of energy found in each kilogram of protein and fat, weighted

by the percentage occurrence of protein and fat in deer. This value is measured in

kilocalories of energy per kilogram of body weight and is used to calculate energy

reserves.

Net energy coefficient—The net energy coefficient adjusts the energy available to

deer to account for the energy loss from heat of nutrient metabolism. This value is

measured as the percentage of available digestible energy after adjustment for

energy loss. \

25
Active metabolic rate factor—-The active metabolic rate factor is an adjustment to

the basal metabolic rate for deer to account for the higher metabolic rates resulting

from deer activity; it generally is in the range of 1.25 to 2.00. The value is read from

a matrix with rows being summer and winter and columns being fawns and adults.

Handling times modifier—The handling times modifier is a global adjustment for

handling times (below). This variable was used for model calibration and should not

be changed.

Handling time—Handling time is the reciprocal of forage intake rate, and is measured in days per kilogram of forage by forage class, season, and deer group (fawns

and adults). The values are read from a matrix formatted as shown by the sample

data in the following tabulation:

Forage class

Deer group Season Forbs Shrubs Lichens

Fawns Summer 0.40 0.60 0.40

Winter .45 .80 .50

Adults Summer .30 .50 .30

Winter .40 .60 .40

Forage class preference factor—Vine forage class preference factor is-based on

subjective observations of deer feeding behavior. The values are read from a matrix

with rows being summer and winter and columns being forbs, shrubs, and lichens.

This is a highly sensitive variable and should not be changed from the preset values.

Search rate—The rate at which deer search for forage is expressed in days per

hectare searched, with values for both fawns and adults.

Survival rates—Maximum survival rates are expressed as a percentage for fawns

and adults.

Fawning rate—The fawning rate is the number of fawns per adult deer. This is given

per deer; for example, a value of 0.75 fawns per deer would be equivalent to 1.5

fawns per doe.

Metabolic costs for snow—The added metabolic costs for moving through snow

are given by snow depth classes (under 2 inches, 2-20 inches, over 20 inches). The

values are read from a matrix, with rows being fawns and adults, and columns being

depth classes.

Forb carrying capacities—Maximum forb carrying capacities are given for site

classes 70 and 130; the program will calculate forb carrying capacities for the

intermediate site classes.

Shrub carrying capacities—Maximum shrub carrying capacities are given for site

classes 70 and 130; the program will calculate shrub carrying capacities for the

intermediate site classes.

26
Net energy gain —The maximum net energy gain is not currently used by the

program; it is for a deer allocation scheme that is under development. A dummy

value (0.00) must be given, however, for the program to execute properly.

Output level for printouts—The output level is used for debugging the model and

should not be set under 10.

Description of The SAMM management plan is specified in four separate parts:

Management Plan5

1. Logging harvest (clearcut of old growth).

2. Road building.

3. Precommercial and commercial thinning.

4. Site preparation and planting.

The first three management scenarios affect the other parts of the model through

canopy cover, sedimentation of streams, and so forth. The fourth scenario includes

associated costs for site preparation and planting and is for economic analysis only.

Site preparation and planting will not affect the growth rates of timber or the later

value of timber or any other resource. The first three scenarios also have associated

economic implications. The program does not allow for subsequent harvest of secondgrowth timber.

Management data in SAMM is delimited with the end-data value to indicate to the

program that a certain type of data is complete. End-data in SAMM is value -99; it

must be placed in each data field and be read as data. The use of end-data eliminates the need to count data records in an input file. See "General Information About

the SAMM Data Files" for more information on end data.

Specifying SAMM logging data—The data required to carry out the simulated

timber harvest must be specified as shown below.

Two types of logging plans can be used in SAMM. The first allocates the harvest

acreage proportionally to occurrence of site classes in the spatial unit. If, for instance,

25 percent of the spatial unit is site 90 and 75 percent is site 110. then 25 percent of

the logging acreage will be taken from site 90 and 75 percent from site 110. This

allows for a simple data file but is not descriptive of a typical logging plan.

The second method allocates harvest acreage site by site, with the user entering

the actual acres for each site in the spatial unit for each logging entry. This requires

a more detailed data file than the first method but is more descriptive of a typical

logging plan.

Both plans allow for entering a percentage of the streambank to be cut and specification of the harvest method used.

5

 The sample data file supplied with the SAMM diskettes is

PLANDET.TST (see appendix 6).

27
Following is a description of each field in the SAMM logging data:

Harvest acreage allocation switch—The harvest acreage allocation switch indicates

which scheme will be used in allocating acreage for harvest; 0 is the proportional

acreage allocation, 1 is the hard acreage allocation. This item is followed on the

same line by a character variable (set off with single quotation marks) that helps to

describe the following six data items below, which are included for each logging entry.

A separate line of data is included in the data file for each logging entry that will be

carried out in the management plan. After all logging entries are entered, end-data

items are listed for each field.

1. Year of logging entry. The year of logging entry is the number of years since the

beginning of the simulation within which an entry is to occur; for instance, a value

of 35 would indicate that the logging entry would occur after SAMM has simulated

34 years in the current run. Use 999 (or any other year beyond the duration of the

simulation) to ignore a line of data during the current simulation.

2. Spatial unit in which the logging entry occurs. If a management plan will specify

logging in several spatial units in the same year, a separate line must be entered for

each spatial unit.

3. Harvest acreage for proportional allocation. This value is the total number of acres

to be harvested if the proportional allocation scheme is selected (see above). The

acreage specified here will be proportionately allocated for harvest based on the

relative acreage in each site class in the spatial unit. If the hard acreage allocation

scheme is chosen (see above), this field will be read and then ignored. Even with

hard acreage allocation, a data item must be entered for this field (for example, 0).

4. Harvest method to be used in this logging entry. Each harvest method has associated costs (see "Economic Data") that will affect total harvest costs depending on

the site class being harvested. Harvest methods will not affect any other variables.

The harvest method specified corresponds to a column of data in the economics data

file.

5. Percentage of streambank that will be cut in this logging entry. The percentage of

streambank to cut is based on the total streambank length for the stream reach, including both banks of the stream. For instance, if a stream reach is 1000 meters long

and this variable specifies a 30-percent bank cut, then 30-percent of 2000 meters will

be cut. The program will check for cut streambanks specified in spatial units having

no streams running through them and for cut streambanks specified in site classes

not adjacent to the stream. Either condition will stop the program.

6. Harvest acreage for hard acreage allocation scheme. The next five fields are the

acres by site class that will be harvested in this logging entry if the hard acreage

allocation scheme is chosen (see above). The first field is the acres to cut in site 70,

next is the acres to cut in site 90, and so on through sites 100,110, and 130. Site 70

28
is noncommercial forest type and typically always will be zero. The program checks

to make sure acreage exists in a specified site class in the spatial unit and checks

that the acreage allocated to harvest is not greater than the existing acreage. Either

condition will stop the program with an error statement.

If the hard acreage allocation scheme is chosen, all five fields (one for each site

class) must have a value for each logging entry in the management plan. To harvest,

for example, 30 acres of site class 100 and 50 acres of site class 130. the five fields

would be entered as 0.0 0.0 30.0 0.0 50.0 . Fractional acreage is allowed, and the

minimum specified harvest in any site class is 0.1 acre. Even if the spatial unit has

no acreage in sites 70, 90, and 110, a 0.0 must be entered. If the proportional acreage allocation scheme is chosen, these fields are ignored by the program (and can

be left blank).

Both allocation schemes will use the same year, spatial unit, harvest method, and

amount of bank cut.

Specifying SAMM road building date—The data necessary to carry out the

simulated road building in SAMM must be specified as shown below.

There are two types of roads in SAMM: main haul roads and spur roads. The construction of roads is not required for timber harvest simulation, so the user is expected

to track that the necessary roads are scheduled as timely. Road building can occur in

years without timber harvest, and timber harvest can occur in years without road

building. Main haul roads can be constructed in years without construction of spur

roads, and spur roads can be constructed in years without main haul roads. After all

road building entries are entered, end-data markers must be placed in each field.

Descriptions of the data fields in the road building plan follow.

Year—The year in which road building is to take place is entered. If roads are to be

built in several spatial units in the same year, each spatial unit will require a separate

line. Main haul roads and spur roads built in the same spatial unit in the same year

can be specified with a single line of data.

Spatial unit—The spatial unit in which the road building is to take place is specified.

If a road is built through several spatial units, each spatial unit is entered on a separate line.

Miles of main road—The miles of main road is the total number of miles of main

road built in the specified spatial unit in the specified year.

Miles of spur road—Miles of spur road is the total number of miles of spur road built

in the specified spatial unit in the specified year.

Note the line of end-data markers at the end of the road specifications.

29
Specifying SAMM precommerclal and commercial thinning data—The data necessary to carry out the simulated timber thinning in SAMM must be specified as

shown below.

Thinning occurs across site classes and is based on the age class of the stand. A

thinning could specify, for example, that all timber of age class 4 (31 to 40 years old)

in spatial unit 3 will be thinned. All site classes from the spatial unit that was logged

31 to 40 years earlier in the simulation will be thinned as one entry.

Description of the data fields in the thinning plan follows.

Year—The year when the thinning entry is to take place is entered. If thinning is to

occur in several spatial units in the same year, each spatial unit will require a separate line. Similarly, if several age classes are to be thinned in the same spatial unit in

a certain year, each age class will require a separate line.

Residual basal area—The residual basal area to be left after thinning is expressed

in square feet (at breast height) per acre. If the basal area at the time of thinning is

less than the residual basal area to be left after thinning, the program will ignore the

thinning entry without any error statement.

Spatial unit—The spatial unit number in which the thinning is to occur is specified.

Age class—The age class of timber to be thinned during this entry is specified as

the number of years from the time of original harvest, with age class 1 equal to 1 to

10 years, age class 2 equal to 11 to 20 years, and so forth. ,lf none of the stand is of

the proper age class, the thinning entry will be ignored without a warning statement.

Because there is no warning, care must be taken in designing the input data so that

the age classes are entered correctly for the desired thinning to occur. All stands in

the spatial unit with timber in the specified age class will be thinned.

Harvest method—Each harvest method has associated costs (see "Economic Data")

that will affect total harvest costs depending on the site class being harvested. Harvest methods will not affect any other variables. The harvest method specified corresponds to a column of data in the economics data file.

Economic Data6

 The economic data file includes the data required for the economic calculations in

SAMM.

Discount rates—The user can enter three different discount rates. Some of the

graphs will use all three rates in comparison, but the first rate of the three is used

exclusively for most outputs. Rates range from 0.0 to 1.0.

Site preparation costs—Site preparation costs include costs for site preparation,

planting, and any precommercial thinnings not covered by the thinning plan and are

expressed in dollars per acre. Costs for commercial thinnings are calculated in the

harvest routines.

6

 The sample data file supplied with the SAMM diskettes is

ECON.DAT (see appendix 7).

30
Associated harvest costs—Associated costs of harvest include sale layout and

planning, sale administration, environmental protection, hauling from terminal transfer

facility to the sawmill, and any other costs not included in specific data items. Costs

are expressed in dollars per thousand board feet harvested.

Wood hauling costs—Wood hauling costs are the costs per mile for transport of

harvested material from the logging site to the terminal transfer facility. The mileage

from each spatial unit to the terminal transfer facility is entered in the geographic

data file; it is not based on the number of miles of road built in the watershed. Costs

are expressed in dollars per thousand board feet of harvested material per mile

hauled.

Road maintenance costs—Road maintenance costs are expressed in dollars per

thousand board feet of harvested material per mile of road. This cost is based on the

total number of miles of road in the spatial unit being logged.

Mainline road construction costs—The costs per mile for mainline road construction are expressed in dollars per mile of main line road built in the current year.

Spurline road construction costs—The costs per mile for spur road construction

are expressed in dollars per mile of spur road built in the current year.

Value of cedar—The value of cedar is given in dollars per thousand board feet.

Even though cedar is not presently modeled in SAMM, a value (for example, 0.0)

must be entered in this field.

Value of wood by volume class—The value of wood by volume class is given in

dollars per thousand board feet: The volume classes are 0-8, 8-20, 20-30, 30-50,

and greater than 50 (volume class values are in thousands of board feet per acre).

Value of commercially thinned material—The value of commercially thinned

material is given in dollars per thousand board feet harvested. This value applies

to all commercially thinned material regardless of diameter.

Harvest costs—Harvest costs are given in dollars per thousand board feet of

harvested material and vary by site class harvested and harvest method used.

Typical costs for various harvest methods are listed in Fight and others (1990).

Harvest costs are listed in the data file with rows being site classes and columns

being harvest methods.

Acres harvested per mile of road for each harvest type—These values are not

used currently but must be present in the data file.

Employment rate—The employment rate is given for each of the following employment catagories: timber harvesting (expressed in person years per thousand board

feet harvested), road building (expressed in person years per mile of road built),

timber thinning (expressed in person years per thousand board feet thinned), and

site preparation (expressed in person years per acre treated with site preparation).

31
Advanced Topics

Initializer Run

Saving Run Parameters

Employment during hunting season—The proportion of total annual employment

that takes place during the hunting season is specified for the following employment

catagories: timber harvesting, road building, timber thinning, and site preparation.

The fisheries model requires long-term average values for fish populations and

stream temperature that are based on the stream morphology described in the data

set. The only way to derive these values; is to run SAMM for 100 years, average the

populations and temperatures, and put the averages into the data file for subsequent

runs. The initializer run makes a 100-year simulation from the estimated values for

fish populations and long-term stream temperatures found in the input file. The

initializer run calculates the correct initial values for these variables for subsequent

runs, and writes those values in a file named 'GRAFS\RUNSPECS'. These values

must be moved into the hydrology input data file by the user before subsequent

simulations are done.

The importance of the initializer run is that it allows the fish population and stream

temperature to stabilize in the stream system for 100 years and then uses those

stable values as initial values for subsequent runs. Any time the stream morphology

as described in the input data is changed, the initializer run should be used and the

data file edited. Changes in any of the following stream characteristics will affect

either fish populations or stream temperatures and will indicate use of the initializer

run:

• Stream length, width, or cross section

• Site class of streamside spatial units

• Amount of openings along streambank

• Solar angles

• Depth of undercut banks

• Amount of gravel, rubble, and side channel area

The initializer run takes as long as a 100-year simulation, so be judicious in using it.

If the initializer run has been used and the fish populations still are not stable (or are

nonexistent), further runs of the initializer run may be necessary. The first time it is

run, new long-term stream flows are calculated. Use these values at the beginning

of the next initializer run. In some cases, stream morphology will not be adequate to

sustain viable fish populations.

The run parameters, including input data file names, management options (whether or

not logging is allowed, whether or not deer hunting is allowed, and so forth), and the

choices for run-time graphs are stored by SAMM in a tile named DEFAULTS. This

file is updated each run and contains the default values for the next run.

The DEFAULTS file can be used to manage multiple data sets in the following way.

If SAMM is run with a large data set (for instance, the data from a large, complex

watershed in southeast Alaska) and several hypothetical data sets for looking at

variables in a controlled environment, then the DEFAULTS file for each data set can

be copied to a file with a different name and saved for later. To run the data from the

32
Output File Names

Correlation of Graphs

to Data

Two Simulations From

One SAMM Run

actual watershed, delete the current DEFAULTS file, copy the saved data file for the

watershed (for example, DEFAULTS.SEA) to DEFAULTS, and run the program. The

data file names will be loaded as defaults into the program, along with the run parameters used the last time a simulation was run from the watershed data. This saves

having to edit the file names in the program.

A system for naming output files should be designed that will keep track of the run

parameters used to generate each file. Output files from SAMM are named with the

graph number and a user-specified extension; either the file can be renamed externally to SAMM, or a file extension of three numbers or three letters can be used.

Output from several runs then can be compared on a single graph by using a package such as Lotus 1-2-3 (to get the output files into Lotus, enter the following Lotus

commands: / File Import Numbers [enter the file name including path and extension]).

Several files can be imported to the same worksheet and plotted on the same graph.

Some of the output data files contain several columns of data, which can lead to

confusion when columns of data with specific variables are correlated. Columns of

output data are correlated to variables as follows.

Deer herd numbers—The number of deer herds in the watershed determines the

number of columns in deer data output files. The columns of data correspond to

the herd numbers entered by the user in the deer input data (where the herds are

mapped to spatial units). The first column corresponds to the herd numbered 1, the

second column to the herd numbered 2, and so forth.

Stream reach numbers —Stream reach numbers correspond to the reach numbers

entered in the geographic data file. The first column corresponds to the stream reach

numbered 1, the second column to the stream reach numbered 2, and so forth.

Species of fish—The first column of output data corresponds to pink salmon, the

second column corresponds to chum salmon, and the third column corresponds to

coho salmon.

Data files can be set up to simulate two runs with a single SAMM simulation. If, for

example, the effects of logging on deer for a 5-spatial-unit watershed are being

studied, then a geographic description data file with 10 spatial units should be

designed, with the second 5 being identical to the first 5. Also define the site class

information similarly. Design the logging plan data file to harvest timber only in spatial

units 1-5. Map deer herd 1 to spatial units 1-5 and deer herd 2 to spatial units 6-10.

When the logging plan is activated, deer herd 1 will show the effects of logging, and

deer herd 2 will show the control or no-logging scenario. Both herds will be printed

on the same graph as the program runs. This method can be used to run five herds

on ranges that differ only by site class or that differ with elevation.

Because there is only a single fish population for the watershed, this method cannot

be used for fishery simulations.

33
Changing Data

File Names

Running SAMM From

a RAM Disk

Possible Errors

It is usually easier to edit the DEFAULTS file with a text editor or word processor

than with the interactive CHANGE FILE NAMES part of the program. The program is

admittedly weak on editing facilities for file names, and a recurring error sometimes

makes it impossible to change the file names. Simply edit the DEFAULTS file the

same as a data file, put in the new data file names, change the parameters if necessary, and even choose different run-time graphs. Be sure to preserve the single

quotation marks that surround the file names in DEFAULTS:

The program creates a temporary file during each simulation that is used to store

intermediate results of several variables for each year of the simulation. This slows

the program considerably, particularly if the computer has a slow hard disk or if the

program is being run from a floppy disk.

A RAM disk can be employed effectively to circumvent this problem. The following

command needs to be added to the CONFIG.SYS file used by the computer:

DEVICE=VDISK.SYS 135 .

This will create a 135K byte RAM disk (also called a virtual disk) that should be

adequate to run SAMM. The computer will need to be turned off and back on after

the above command is added to the CONFIG.SYS file. Every time the computer is

turned on after the command is added, the RAM disk will be activated and will be

available for SAMM simulations or any other software that can make use of a RAM

disk. A file named VDISK.SYS, supplied with the computer operating system, must

be in the boot directory for the computer to use a RAM disk (the boot directory is the

directory containing the COMMAND.COM file, whether on a hard disk or a floppy

disk system). See operating system documentation supplied with the computer for

more information on RAM disks.

If the computer has one floppy disk and a hard disk with two partitions (C and D),

then the RAM disk will be labeled as drive E. Simply copy the following files to drive

E (or whichever drive letter is the RAM disk):

DEFAULTS

ALL INPUT DATA FILES NEEDED

ROMANSIM.FNT

Create a subdirectory on drive E named GRAFS. Start SAMM by entering the full

MS-DOS path to the SAMM files; for instance, D:\SAMMDIR\SAMM . SAMM will

execute normally (be sure to run METAWNDO the first time), and all output will be

saved into the subdirectory E:\GRAFS. These output data files will be lost when the

computer is shut off, so be sure to copy them from the RAM disk to the hard disk

before shutting off the computer.

A listing follows of several problems that may be encountered when using SAMM,

and possible solutions to each problem.

Error: Pressing SHIFT-PRTSCRN does not result in a graph being printed.

34
Solutions:

Make sure that the printer is connected to the computer and that it is turned on.

Be sure to enter PRTSCRN before running SAMM to invoke the screen print driver.

Enter MODE LPT1 before running SAMM to make sure that the printer is connected

to the default printer port.

Turn the printer off and then back on to reset it to default settings. Only Epson FX

series and the IBM Proprinter are supported. Many other dot-matrix printers emulate

the Epson standard and should work.

Error: Printed graphs are compressed to only half a page.

Solutions:

The printer is not fully emulating Epson FX series printers.

The printer is configured for compressed print; turn the printer off and then back on

to set it to default settings.

The screen print facility does not use the full width of the paper even with an Epson

printer. This is a limitation of the screen dump facility being used. To get high-quality

printed copies of graphs, save the data needed to draw the graphs, and print the

graphs with a commercial graphics package.

Error: After SAMM is entered, the following message is received: 'ERROR

METAWNDO not installed'.

Solution:

Enter METAWNDO before running SAMM. METAWNDO is supplied with the

SAMM diskette. It must be in the SAMM subdirectory or in a subdirectory that

can be reached with a path command.

Error: After SAMM runs, the computer is in 40-column text mode.

Solutions:

Make sure that all the font files (files with an extension of .fnt) are in the SAMM

subdirectory; they are needed to restore the system screen font.

If the computer is in 40-column text mode, or 80-column graphics mode after SAMM

execution, enter MODE BW80, MODE C080, or MODE MONO to return to 80

columns.

Error: An error stops SAMM, and keyboarded commands are overwriting the graphs

on the screen.

Solutions:

There is probably no way to save the on-screen graphs. To remove the graphics

clutter from the screen, enter CLS. Follow with one of the MODE commands (see

above) if necessary.

35
Some error messages may be written to the screen as text during a simulation, and

will scroll the graphs out of view from the screen. Often these messages are warnings

and will only cause a pause in the simulation. In this case, make a note of the error

message and press ENTER to resume the SAMM simulation. The run-time graphs

will be ruined, but once the simulation is finished any of the graphs can be recalled

for inspection. If the error message is fatal, the program will stop, and all data will be

lost. Correct the data file per the suggestions in the error message before rerunning

SAMM.

Error: Arrow keys do not move the highlighted box on the screen.

Solution:

Some computers with dedicated cursor (arrow) keys will require the use of the arrow

keys on the numeric key pad. Be sure that NUM LOCK is off in order to use the

arrow keys.

Error: Mouse device does not move the highlighted box on the screen.

Solution:

Mouse devices are not supported by SAMM at present.

Error: Colors are not displayed on color monitor.

Solution:

SAMM uses a graphics package that senses the type of graphics card in use in

each computer. Most graphics cards are supported; however, if the software does

not recognize the graphics card in use, it may default to monochrome mode.

Error: Colors used in graphs are hard to tell apart or are the same as the

background color,

Solution:

SAMM is distributed with a separate program called SETCOLOR. Run this program

and choose the desired colors for background and lines from those available.

Error: Program runs up to the main graph menu, then locks up.

Solution:

Some very high resolution monitors may require more memory to store the background image than has been allowed for in the program. Try to reconfigure the

graphics card to emulate EGA or Hercules graphics.

Error: 'ERROR 1008' message scrolls up screen continually.

36
Solutions:

This is a run-time FORTRAN error message indicating that an argument to an EXP

function has gone out of range or is undefined. This is usually caused by specifying

fewer deer herds in the DEER DATA file than have been assigned to spatial units.

For instance, if there are five spatial units, and two herds have been specified at the

beginning of the deer data, then when the following assignment of herds to spatial

units is done:

12231,

deer herd 3 will be undefined, and ERROR 1008 will scroll up the screen. Enter

CONTROL-BREAK at the same time to stop SAMM, edit the deer data, and restart

the program. If CONTROL-BREAK does not work, press the CONTROL, ALT, and

DELETE keys simultaneously to restart the computer.

Error: 'ERROR 3012' is printed on the screen and the program stops.

Solutions:

This is a FORTRAN error message, indicating that the program was unable to find

file DEFAULTS, or the specified data file names, or subdirectory GRAFS. Be sure

that all files necessary to run SAMM are in the proper directory and that a subdirectory named GRAFS has been created.

This message also will be encountered when there is an error in an input data file

and SAMM tries to read past the end of the file.

Other '3000' series error messages usually will be caused by MS-DOS being unable

to find a file name or by an error in writing to or reading from a file. Be sure there is

enough room on the disk for output files, because there is no error message to indicate that no more space is available. Once the disk is full, the program will display

a '3000' series message indicating a formatted write error.

The distribution version of SAMM is compiled with the Ryan-McFarland FORTRAN

compiler, and any FORTRAN error messages can be found in the Ryan-McFarland

manual.

For other errors or to make suggestions, call, write, or send a message on the Forest

Service communications network to:

Dale Weyermann

Forestry Sciences Laboratory

Pacific Northwest Research Station

P.O. Box 3890

Portland, OR 97208-3890

(503)321-5903

Data General address: D.WEYERMANN:S26L07A

37
Literature Cited Fight, Roger D.; Garrett, Lawrence D.; Weyermann, Dale L., tech. eds. 1990.

SAMM: a prototype southeast Alaska multiresource model. Gen. Tech. Rep.

PNW-GTR-255. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 109 p.

Appendix 1

A List of Graphs With

Associated File Names

No. Filename1 Graph menu title

1 GRAPH0I.xxx

2 GRAPH02.xxx

3 GRAPH03.xxx

4 GRAPH04.xxx

5 GRAPH05.xxx

6 GRAPH06.XXX

7 GRAPH07.XXX

8 GRAPHO8.XXX

9 GRAPH09.XXX

10 GRAPHI0.xxx

11 GRAPHH.XXX

12 GRAPH12.XXX

13 GRAPH13.XXX

14 GRAPH 14.XXX

15 GRAPH15.xxx

16 GRAPH 16-xxx

17 GRAPH 17.XXX

18 GRAPH18.xxx

19 GRAPH19.xxx

20 GRAPH20.XXX

21 GRAPH21.XXX

22 GRAPH22.XXX

23 GRAPH23.XXX

24 GRAPH24.XXX

25 GRAPH25.XXX

26 GRAPH26.XXX

27 GRAPH27.XXX

28 GRAPH28.XXX

29 GRAPH29.XXX

30 GRAPH30.XXX

31 GRAPH31.XXX

32 GRAPH32.XXX

33 GRAPH33.XXX

34 GRAPH34.XXX

35 GRAPH35.XXX

36 GRAPH36.XXX

37 GRAPH37.XXX

38 GRAPH38.XXX

39 GRAPH39.XXX

40 GRAPH40.XXX

WATERSHED VOL(MMBF)

OLD GROWTH ACRES

VOLUME CUT

MAIN:SPUR ROAD Ml

EMPLOYMENT

SPAWNERS

FRY (BY SPECIES)

COMMERCIAL CATCH

SPORT CATCH (CPUE)

PERSONAL USE CATCH

PERCENT FINE SEDIMENT

LARGE ORG DEBRIS INV

STREAM TEMP (SUMMER)

EFF BANK CANOPY

PERCENT PROTECTED

DEER DENSITY BY HERD

HUNTING HARVEST

SURVIVAL RATE ADULTS

SURVIVAL RATE FAWNS

TOTAL YEARLY SNOWFALL

DEEPEST SNOW

UNDERCUT BANK AREA

PRES NET WORTH(TIMBER)

(available)

HARVEST BY SITE CLASS

PINK COMM:PERSONAL USE

CHUM COMM:PERSONAL USE

COHO COMM:PERS:SPORT

STREAM VELOCITY(M/SEC)

HUNTING EFFORT

KILL PER EFFORT

COHO/SQ-M BY YEAR CLASS

SMOLT BY YEAR CLASS

BEDLOAD SHIFT PROBABIL

SUMMER LOW FLOW FACTOR

WINTER LOW FLOW FACTOR

(available)

(available)

SAVE OUTPUT, THEN QUIT

QUIT WITHOUT SAVING

1

 The file extension .xxx is user-specified and should conform

to an overall user-designed file-naming convention.

38
Appendix 2

Brief Description of

Each Graph

1. WATERSHED VOL(MMBF)—This graph has three lines showing volume of oldgrowth timber in the watershed/volume of young-growth timber in the watershed,

and total timber volume in watershed (sum of the other two values). Volumes are

shown in millions of board feet.

2. OLD GROWTH ACRES—This graph shows the number of acres in the watershed

remaining as old growth.

3. VOLUME CUT—This graph shows the total volume of timber harvested in the

watershed in each year in thousands of board feet. This is not cumulative from year

to year.

4. MAIN: SPUR ROAD Ml—This graph has two lines showing total miles of main road

and total miles of spur road in the watershed. Spur roads are not retired in this model.

5. EMPLOYMENT—This graph shows total employment in the watershed from

loggers and road builders in person years.

6. SPAWN ERS—This graph has three lines showing the total number of returning

pink, chum. and coho salmon. Because the number of pink and chum is much

greater than the number of coho in a typical watershed, the coho line may appear to

be zero. Several other graphs allow the coho population dynamics to be studied

without this scaling problem.

7. FRY (BY SPECIES)—This graph has three lines showing the total number of fry

produced for pink, chum, and coho salmon. Because the number of pink and chum

is much greater than the number of coho in a typical watershed, the coho line may

appear to be zero. Several other graphs allow the coho population dynamics to be

studied without this scaling problem.

8. COMMERCIAL CATCH—This graph has three lines showing the total number of

pink, chum, and coho salmon that are commercially harvested. Because the number

of pink and chum are much greater than the number of coho in a typical watershed,

the coho line may appear to be zero. Several other graphs allow the coho population

dynamics to be studied without this scaling problem.

9. SPORT CATCH (CPUE)-This graph has a single line showing the sport fishing

success in terms of catch per unit of effort (one unit of effort is equal to one angler

day). Coho is the only species harvested by sport fishermen.

10. PERSONAL USE CATCH—This graph has three lines showing the total number

of pink, chum, and coho salmon taken by personal-use harvest. Personal-use harvest

is the allowable harvest taken by local Native populations. Because the number of

pink and chum is much greater than the number of coho in a typical watershed, the

coho line may appear to be zero. Several other graphs allow the coho population

dynamics to be studied without this scaling problem.

39
11. PERCENT FINE SEDIMENT—This graph will have a separate line for each

stream in the watershed. The value graphed is the percentage of sediment that is

fines (less than 3 millimeters in greatest dimension). This is NOT the inventory of

fine sediment in each stream reach.

12. LARGE ORG DEBRIS INV—This graph will have a separate line for each stream

in the watershed. The value graphed is the inventory of large debris found in each

stream reach in cubic meters of debris per square meter of stream surface area.

13. STREAM TEMP (SUMMER)—This graph will have a separate line for each

stream in the watershed. The value graphed is the maximum summer stream

temperature for each stream reach in °C.

14. EFF BANK CANOPY—This graph will have a separate line for each stream in

the watershed. The value graphed is the percentage of streambank that has canopy

closure along it. Each line represents an average for the entire stream reach.

15. PERCENT PROTECTED—This graph will have a separate line for each stream

in the watershed. The value graphed is the percentage of total stream area that is

considered protected area for fish (undercut banks, rubble areas, pools, or side

channels).

16. DEER DENSITY BY HERD—This graph will have one line for each deer herd

in the watershed. The value graphed is the number of deer per square mile in each

herd.

17. HUNTING HARVEST—This graph will have one line showing the total hunting

harvest of deer in the watershed.

18. SURVIVAL RATE ADULTS—This graph will have one line for each deer herd in

the watershed. The value graphed is the survival rate of adult deer in each herd.

19. SURVIVAL RATE FAWNS—This graph will have one line for each deer herd in

the watershed. The value graphed is the survival rate of fawns in each herd.

20. TOTAL YEARLY SNOWFALL—This graph has one line that is the total number

of inches of snow that fall each year in a forest opening (not intercepted by canopy)

in spatial unit number 1. The value graphed will be the snowfall at the elevation of

spatial unit 1.

21. DEEPEST SNOW—This graph has one line that is the deepest accumulation of

snow (in inches) in a forest opening (not intercepted by canopy) in spatial unit number

1 each year. The value graphed will be the deepest accumulation of snow at the

elevation of spatial unit 1.

22. UNDERCUT BANK AREA—This graph will have one line for each stream reach

in the watershed. The value graphed is the total area of undercut banks along the

stream reach in square meters.

40
23. PRES NET WORTH(TIMBER)—This graph has three lines showing the present

net worth of timber harvest and road building in the watershed at three different

discount rates (user input). This graph is not available for viewing as the simulation

proceeds. It can be called up only after the entire simulation period is complete.

24. (available)—This graph currently is not being used.

25. HARVEST BY SITE CLASS—This graph will have five lines showing the cumulative acres of each site class that have been harvested.

26. PINK COMM: PERSONAL USE—This graph has two lines showing the commercial harvest and personal-use harvest of pink salmon. The personal-use values are

typically very small compared to the commercial harvest and may appear as zero.

27. CHUM COMM: PERSONAL USE—This graph has two lines showing the commercial harvest and personal-use harvest of chum salmon. The personal-use values are

typically very small compared to the commercial harvest and may appear as zero.

28. COHO COMM:PERS:SPORT—This graph has three lines showing the commercial harvest, sport harvest, and personal-use harvest of coho salmon. The personaluse values are typically very small compared to the commercial harvest and may

appear as zero.

29. STREAM VELOCITY(M/SEC)—This graph will have a line for every stream reach

in the watershed. The value graphed is the stream velocity in meters per second that

is used to compute probability of bedload shift.

30. HUNTING EFFORT—This graph will have one line showing the hunting effort in

hunter days that is being expended in the watershed.

31. KILL PER EFFORT—This graph will have one line showing the kill per unit of

effort (one unit of effort equals one hunter day) in the current year in the watershed.

This value is used to determine the nonlocal hunting effort in the next year.

32. COHO/SQ-M BY YEAR CLASS—This graph has two lines showing the number

of coho per square meter in the entire stream system by coho age class.

33. SMOLT BY YEAR CLASS—This graph has two lines showing the number of

coho smolt per square meter in the entire stream system by age class.

34. BEDLOAD SHIFT PROBABLE—This graph will have one line for each stream

reach in the watershed. The value graphed is the probability of a bedload shift occurring in the stream reach during the year.

35. SUMMER LOW FLOW FACTOR—This graph will have one line for each stream

reach in the watershed. The value graphed is the reduced survival of coho in a reach

due to reduced summer stream flow. A value of 0.95 would indicate that 5 percent of

the coho die as a result of reduced summer stream flow.

41
Appendix 3

Sample Data File for

Geographic Description

Input

36. WINTER LOW FLOW FACTOR—This graph will have one line for each stream

reach in the watershed. The value graphed is the reduced survival of coho in a reach

due to reduced winter stream flow. A value of 0.95 would indicate that 5 percent of

the coho die as a result of reduced winter stream flow.

37. (available)—This graph currently is not being used.

38. (available)—This graph currently is not being used.

39. SAVE OUTPUT, THEN QUIT—This option calls another menu that allows the

user to save output on disk files before quitting the program.

40. QUIT WITHOUT SAVING—This option ends the SAMM run and returns the

computer to DOS.

VCUDATA.TST—Note that information in single quotation marks is included in the

data file and is read as data by the program; it must not be deleted;

label

sp unit

end data'

1'

2'

3'

4'

5'

6'

slope

0

0

0

0

0

0

-99

inear ptrdrn

1

1

1

0

1

1

-99

1

2

4

2

3

5

-99

dfid

1.

4.

4.

6.

6.

5.

-99

0

5

5

2

5

8

ptrsip

1.

1.

1.

0.6

1.

1.

-99

allude ace'

10.

25.

150.

650.

575.

600.

-99

1

1

1

0

0

0

-99

spatial unit information'

' (one line per spatial-unit/site-class combination)'

' sp-ptr site acres '

1

1

2

2

2

2

3

3

3

4

4

4

110

130

90

100

110

130

100

110

130

70

90

100

1500

990

210

300

420

1800

840

522

474

132

360

432

42

vcu information'

(one line per spatial unit in the vcu)'
5

5

5

6

6

-99

100

110

130

90

100

-99

390

468

480

312

498

-99

'initial random seed (range=l-32000) use 0 to let program choose'

741 0

Appendix 4

Sample Data File

for Hydrologic Input

HYDRODAT.TST—Note that information in single quotation marks is included in the

data file and is read as data by the program; it must not be deleted.

Cleveland 717

XXX.

'stream reach length (reachlen)'

2500 2000 1118 2093 500

'cross secional area(crossarea)'

50. 23. 4. 17. 5.

'ave width (reachwid)'

20.3 15.4 6.0 9.3 4.0

'side channel surface area (areasidach)'

3000 2000 0 1000 0

'area of stream bed in rubble (rubblearea)'

10000 5000 6775 548 0

'pointer to order reaches will be considered (iorder)f

54321

'downstream reach from current one (idown)'

4 12 1 6 :

'gravel area for,spawning by species (gravelarea) ROW=SP,COL=RCH'

24053 5951 556 4050 500

24053 5951 556 4050 500

12500 6000 556 4050 500

'available water capacity per spatial unit ,inches (soilh2ocap)'

5555555555

'natural mean depth of undercut banks (ucutdepth)'

0.5 0.5 0.5 0.5 0.5 0.5

'debris input at time of logging (debris input(1)'

0.1

'equilib value for large debris m3/m2 (equilldeb)'

43
0.01 0.01 0.007 0.01 0.007

' equilib prop fox fine sediments (equilfsed)'

0.15 0.15 .15 .15 .15

'prop of fine sed move out each year (propmove)'

0.5 0.5 0.9 0.5 .9

'max % bedload shift (bedshiftmax)'

0.4 0.4 0.9 0.4 0.7

'adjust stream velocity for edge effect (veladjust)'

0.4 0.3 0.5 0.3 0.5

' switch for stream cleaning, l=stream cleaning (istrmcin)'

0

'flag for torrents 1-1st order stream (itorrent)'

00000

'solar angle by month (solarangle)'

13.2 21.83 32.15 44.09 53.18 57.88 56.05 48.79 37.79 26.06 16.06 11.15

'standard deviation of temperature (stemp)'

32.85 31.8 33.6 36.5 41.8 49.2 55.2 58.6 58.7 53.1 45.8 38.4 33.9 32.85

'standard deviation of precipitation (sprec)'

8.845 8.36 6.3 6.44 6.08 4.8 4.1 4.3 5.39 8.02 12.61 10.67 9.33 8.845

'proportion of bank with streamside vegitation (propshaded)'

0.95 0.95 0.95 0.95 .95

'coho first two age classes, col=rch, row=age (fwaterres)'

29537. 18445. 2523. 10904. 1073.

6645. 4150. 568. 2453. 241.

'total fry by species (totalfry)'

9778840. 7909354. 88618.

'ocean residents at the beginning of the simulation'

'first row is pinks (1 age ciss) (oceanresidents)'

10136212.

'second row is chum ( 4 age classes)'

7909946. 1582053. 253129. 15187.

'third row is coho (1 age ciss)'

7359

'water to snow conversion factor (wscon)'

8

'temperature lapse rate (degrees/ft elev) (rtlaps)'

.0036

' snow melt rate (fmelt)'

.06 '.12 '

' std dev of temperature, summer winter (stdsum, stdwin)'

44
4.0 6.0

'spread of daily temps, summer, winter (sprsum, sprwin)'

7.0 6.0

'proportion of 24 hours that is day (daying)'

.50

'commercial harvest rate by species (commharvprop)'

.5 .5 .40

'ocean survival rate by species (oceansurvrate)'

.02 .20 .10

'prop of fish that go to subsistence users (subsharvprop)'

0.01

'prop of fish that go to sport (ocean) sp (sportharvprop)'

0.0 0.0 0.10

' fish vulnerability to catch (fwvul)'

.000 .000 .001

'long term summer stream flow (sumlongterm)'

46.5 22.9 6.1 12.2 3.7

'long term winter stream flow (winlongterm)'

10.6 5.2 1.4 2.8 0.8

'switch for ocean or terminal fishery (iharv)'

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 101111111111111

'switch for printout options in hydro, (ihd)'

1

'switch to turn on the (1=) constant snow model (isncon)'

0

45
Appendix 5

Sample Data File

for Deer input

DEERDATA.TST—Note that information in single quotation marks is included in the

data file and is read as data by the program; it must not be deleted.

'number of deer herds (numherds)'

' initial deer per square mile (deerdensityinit)'

50.0

'map deer herds to spatial units, one entry per spatial unit

(mapherds)'

111111

'local population (residenthunters)'

25

'days/year each resident hunts (dayseachresidents)'

2

.5

2

10

'prop of loggers that hunt (prophunters)'

'days/year each logger hunts (dayseachloggers)'

'max hunter days/year from outside local area (maxdaysdistant)'

'gross energy equiv (grossenergy) forage class,season'

4500 4500 4500

4500 4500 4500

'digestability factor (digestability) for class, season'

.70 .60 .70

.60 .40 .70

'metabolizable energy factor (metabolizablefac)'

.80

'body weight (weight) deer grp'

15. 27.

50. 43.

'Kcal/kg of body weight (kcalkgbodywt)'

8400

'net energy coefficient (netenergycoeff)'

0.70

'active metabolic rate factor [amfsummer(f,a),axnfwinter(f,a)]

season'

2.00 2.00

1.70 1.70

'handling time modifier (dhmult)'

1.14 1.12

46

1
'handling times (dh) for els, deex grp, season'

'columns are forbs, shrubs, lichens, first line is

fawns,summer'

'second line fawns,winter, then adults,summer, and

adults,winter'

.40 .60 .40

.45 .80 .50

.30 .50 .30

.40 .60 .40

'preference factor (xpref) for cls, season .6 .2 .2'

.95 .16 .1

.95 .16 .1

'search rate (da) deer group'

1.00 1.00

'maximum survival rate, fawns, adults(survratemax)'

.75 .90

'fawning rate, adults (fawningrate)'

0.75

'metabolic costs for snow - fawns, by depth class

(snowcost)'

0 200 600

'metabolic costs for snow. - adults, by depth class

(snowcost)'

0 300 900

'max forb carrying capacities (forbmincapacity,

forbmaxcapacity)'

100. 300.

'max shrub carrying capacities (shrubmincapacity,

shrubmaxcapacity)'

15000. 50000.

'cutoff percent for net energy gain (cutoffpercent)'

0.00

'output level (for getting various intermediate print files)'

10

47
Appendix 6

Sample Data File

for Management

Plan Input

PLANDET.TST—Note that information in single quotation marks is included in the

data file and is read as data by the program; it must not be deleted.

1

19

20

21

23

24

20

21

25

27

22

26

26

29

28

'year spunit acres

20

21

22

23

24

22

23

24

25

26

27

28

24

25

26

27

28

27

28

29

30

29

30

-99

1

1

1

1

1 .

2

2

2

2

3

3

5

5

6

1

1

1

1

1

2

2

2

2

2

2

2

3

3

3

3

3

5

5

5

5

6

6

-99

1.00

1.00

1.00

0.00

0.00

1.00

1.00

1.00

0.00

1.00

0.00

1.00

0.00

1.00

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

20

-99

2.00

0.00

0.00

1.00

1.00

1.00

0.00

1.00

2.00

1.00

1.00

1.00

1.00

1.00

harvtype %bankcut

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

-99

40

0

40

0

10

10

0

20

0

20

0

10

10

10

10

0

0

10

10

10

10

10

10

-99

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

0.

-99

5x

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

acreage cut

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

-99

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

50.0

0.0

0.0

0.0

50.0

0.0

50.0

50.0

0.0

0.0

0.0

0.0

100.0

100.0

-99

each site'

50

50

0

50

0

50

0

0

50

40

40

50

0

50

0

35

35

40

75

50

50

0

0

-

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

.0

99

75.0

100.0

200.0

50.0

50.0

75.0

65.0

100.0

80.0

100.0

35.0

50.0

100.0

50.0

100.0

0.0

0.0

50.0

100.0

25.0

50.0

0.0

0.0

-99

48
Appendix 7

Sample Data File

for Economics Input

-99 -99 -99 -99

65 150 1 5 2 'year residba spunit agecis harvtyp'

65 150 242

65 150 2 5 2

65 150 342

65 150 352

ECON.DAT—This file contains all data necessary for economic analysis of a simulation. Note that information in single quotation marks is included in the data file and

is read as data by the program; it must not be deleted.

discount rates'

.05 .075 .1

'2nd grwth mgmt costs, site prep, planting, thinning'

40 480 350

'hauling costs/mile of road, CCMU'

60

'wood hauling cost, CHAUL'

1.50

'road maintenance costs, CMR'

.45

'xnailnline road building costs, CBMR/

175000

'spurline roadbuilding costs, CBRS'

120000

'value of cedar, VALC'

1000

'val of wood by vol class,0-8,8-20,20-30,30-50,50+mbf, VAL'

205.50 251.50 285.50 309.00 322.50

'value of commercially thinned material'

100

'harvest cost $/mbf by site, harvest method, CHT'

144 177 137 156 161 186 186 252 135 300 107

126 149 119 134 140 160 162 216 133 275 101

109 127 104 115 121 137 141 185 131 250 95

90 103 85 94 101 114 119 156 99 243 79

83 94 82 89 94 106 112 146 90 240 76

'ac harvested/mi road by harvest method, RPH'

160 160 160 160 240 240 320 320 80 600 80

'employment rate/mbf cut,/mi road,/mbf thin,/ac 2nd grth.ERATE'

.002 1 .002 .0056

'prop of employment in hunting season(see ERATE).PDH?^

.7 .7 .7 1

49

* U.S. GOVERNMENT PRINTING OFFICE: 1991 - 591 -001 / 40044
33 Correlation of Graphs to Data

33 Two Simulations From One SAMM Run

34 Changing Data File Names

34 Running SAMM From a RAM Disk

34 Possible Errors

38 Literature Cited

38 Appendix 1

A List of Graphs With Associated File Names

39 Appendix 2

Brief Description of Each Graph

42 Appendix 3

Sample Data File for Geographic Description Input

43 Appendix 4

Sample Data File for Hydrologic Input

46 Appendix 5

Sample Data File for Deer Input

48 Appendix 6

Sample Data File for Management Input

49 Appendix 7

Sample Data File for Economics Input