Simulation Strategies Used for Evaluation of Alternatives

The basic platform we used for simulating the

vegetation composition and structure and its associated disturbance for the preliminary draft EIS

alternatives was a spatial and temporal model

called the Columbia River Basin SUccession

Model (CRBSUM) (Keane 1996), along with the

Columbia River Basin Landscape Analysis Data

Base System (CRBLAD) (Gravenmier and others,

in press) and other associated models and data

(Hann and others 1997). CRBSUM predicts disturbance dynamics and vegetation response

through time at a landscape level. Differences in

alternatives were simulated by using various combinations of types, rates, and spatial allocations to

subbasin clusters, of disturbances. The data system, called CRBLAD, predicts many other attributes that aid in landscape, aquatic, terrestrial,

social, and economic assessment.

Management disturbances assessed included livestock grazing, timber harvest and thinning, range

improvements, prescribed fire, and fire suppression emphasis; other disturbances included wildfire, insect and disease mortality, and drought.

The simulations of the various alternatives showed

how different types of disturbance interact to produce various temporal and spatial mixes of vegetation types and associated attributes. The response

for a given spatial location varied depending on

the current and potential vegetation types, the

type of management assigned to the area in the

alternative, and the kinds of disturbances projected in the simulation period.

Prescription Models

The types and rates of disturbances varied among

the different potential vegetation types and pre-

••^•^•••••••••Illlll I i I •

scription models (Hann and others, in press;

Long and others 1996). While each prescription

represented a specific type of management, they

generally fell into one of five broad categories of

management:

• Traditional management of vegetation for production of commodities using traditional treatments and suppression of wildfires.

• No management of vegetation in reserves (roadless areas), and suppression of wildfires within

the National and Regional Interagency fire policy requirement.

• Traditional protection for visual quality or habitat objectives and suppression of wildfires while

producing minimal commodities.

• Ecological approach to conserving a balance of

ecosystem integrity and native diversity while

meeting human resource objectives, and integrating wildfire management with prescribed fire

management in roaded areas.

• Ecological approach to restoration of landscapes

to achieve a balance between ecosystem integrity

and native diversity while meeting human

resource objectives, and integrating wildfire

management with prescribed fire management

in roadless areas.

There were 18 prescriptions: the historical regime

and 17 simulations representing various types of

management (table 2.4). The historical regime was

simulated once for a 100-year period and a second

time for a 400-year period. These simulations

used the historical (circa 1850s) map as a starting

input layer and modeled a 100-year historical

range of variability (HRV) and a 400-year HRV.1

'The HRV (Morgan and others 1994) provides a means of understanding succession/disturbance and the biodiversity relationships

of paleoecological and historic systems. It incorporates the relationships between the energy of the system in terms of processes of

biomass accumulation and the processes of disturbance that convert or physically transport biomass. HRV can serve as a tool for

understanding the causes and consequences of change in ecosystem characteristics over time as well as serve as a benchmark for

understanding the effects of human-induced changes of biophysical systems. We simulated the HRV by developing pre-EuroAmerican settlement succession/disturbance models for each potential vegetation type and simulating change over a 100- or 400-

year period from the historical vegetation map (Long and others 1996).

Landscape Ecology 47
The management regimes were simulated for a

100-year period from current. All prescriptions

were simulated for all lands in the Basin and data

were stored in a prescription database (Hann and

others, in press; Hann and others 1997).

Each prescription had a different response used to

simulate the application of management activities

and associated effects. The historical prescription

set was used to define the historical range of variability (HRV) for the Basin, and also for each EIS

area, management class, potential vegetation

group (PVG), and subbasin. The historical prescription set was not appropriate for current management due either to differences in objectives

and current conditions, or to a change in the

response of the potential vegetation (Hann and

others, in press).

Table 2.4 — Landscape management prescription (Rx) map symbol legend names.

Prescription Type Rx Legend Name

Ecological

HI Prescription set to model 100-year and 400-year simulations of HRV.

A1 Restoration1 with PNF/P2

A2 Roaded Land High Restoration with Production'

A3 Roaded Land High Restoration with Production and Area or PVG Emphasis

N1 Conservation1

N4 Roaded Land Moderate Restoration with Production

C1 Roadless Land with Moderate Fire Suppression

N6 Roadless Land with Moderate Fire Suppression and PNF/U3

P1 Roadless Land Reserve with Moderate Fire Suppression

Traditional Reserve

Traditional Commodity

C2 Roaded Land High Commodity with Low Ecological Mitigation

C3 Roaded Land High Commodity with No Ecological Mitigation

* N3 Roaded Land Moderate Commodity with Low Ecological Mitigation

* N5 Roaded Land Moderate Commodity with High Exotic Weeds

N8 Roaded Land Moderate Commodity with Moderate Ecological Mitigation

* P3 Roaded Land Very High Commodity with No Ecological Mitigation

Traditional Commodity in Sensitive Areas

* N2 Sensitive Visual4 Area with Moderate Harvest & Livestock

* N7 Sensitive Visual Area with Moderate Harvest & Low Livestock

P2 Sensitive Visual Area with Low Commodity & High Wildfire

'Management Emphasis definitions:

1) Conservation — Emphasis provides for the protection of rare native elements and systems while maintaining proper functioning systems and

restoring systems where there is low risk to rare elements or systems. Some human commodities may be produced but the emphasis is on

human values related to protection of native diversity, aesthetics, and recreation.

2) Restoration — Emphasis provides for subsidizing ecological and landscape processes and functions to shift the transition toward proper functioning systems. Considerable human commodities may be produced that are compatible with restoration, as well as conservation of inclusions

of rare elements and systems, but the emphasis is on shifting landscapes that are in high departure from the native regime toward proper functioning ecological relationships.

3) Production — Emphasis provides for production of human needs and values by managing in concert with native ecological and landscape

processes to maintain or shift to proper functioning systems. This will typically require subsidies to represent native ecological cause-and-effect

relationships at landscape levels, along with some restoration and conservation, but the emphasis is on design of system responses that produce

commodities and other values.

4) Traditional — Emphasis on the independent management model for producing commodity values, protecting visually or environmentally

sensitive areas, or managing reserves to protect semi-primitive characteristics.

'Prescribed natural fire program with planned ignition.

'Prescribed natural fire program with unplanned ignition.

'Traditional sensitive visual area management similar to traditional reserve.

48 Landscape Ecology
Table 2.5 — General management activity levels' by prescription set (Rx).

2

Q.

en

o

03

TD

CD

Forest Management

Rx Road

Rx Harvest Thin Fire Density

H N

Ecological

A1 N

A2 M

A3 H

N1 N

N4 L

Traditional

C1 N

N6 N

P1 N

Traditional

C2 H

C3 H

N3 H

N5 M

N8 H

P3 H

Traditional

N2 M

N7 M

P2 L

N N N

Prescriptions

N H N

H H L-M

H H L-M

N L N

L L L

Reserve Prescriptions

N L N

N L N

N N N

Commodity Prescriptions

M L M-H

H L H-V

H L M-V

M L L-M

H L M-V

M L H-V

Commodity in Sensitive Areas

M L L-M

M L L-M

N N L

Range Management

Grazing

Effects

L

L

L

L

L

L

L

L

L

M

M

M

L

L

H

M

L

L

Upland

N

N

H

M

L

L

N

L

N

M

M

L

L

L

L

L

L

N

Riparian

N

N

H

M

L

L

N

N

N

M

L

L

L

L

N

L

L

N

Woodland

N

N

H

H

N

M

N

N

N

M

M

M

M

M

M

M

M

L

Rx

Fire

N

M

H

M

L

L

L

L

N

M

M

L

L

L

L

L

L

N

Road

Density

N

N

L

L

N

L

N

N

N

M

L

L

L

L

L

L

L

N

Wildfire

Hazard

H

L

L

L

M

M

M

M

H

M

M

H

M

M

M

M

M

H

Exotics

Hazard

N

L

L

L

L

M

M

L

M

H

H

H

H

H

H

H

M

H

Pres

Trad

NA

NA

NA

NA

NA

NA

1-7

1-7

1-7

1-7

1-7

1-7

1-7

1-7

1-7

1-7

1-7

1-7

'Levels: L = low; M = moderate; H = high; V = very high; N = none.

3

 As simulated by Columbia River Basin Succession Model.

'Rx = prescription; Trad. = traditional prescription; Ecol. = ecological prescription.
Table 2.6 — Management prescriptions (Rx) sorted by conservation, restoration, and production emphasis.

Rx Emphasis

Conserve

Conserve -

Produce

Produce

Restore

Restore -

Conserve

Restore -

Produce

Rx Ability

to Achieve

Emphasis

High

Moderate

Low

High

Moderate

Low

High

Moderate

Low

High

Moderate

Low

High

Moderate

Low

High

Moderate

Low

Management

of Forest

Non-Wilderness/

Roaded

N1

N4

P1

N2, N7

N4 > N52

P2i

P3 > C3> C2

N8, N3

N7 > N5 > N4

A1

A1

N4

A1

N1

N4

A3

A2

N2 > N4 > N5

Management

of Range

Non-Wilderness/

Roaded

• *• Prescription

N1

N4, C1

P1

N4

N1

C3

N2, N3

A2

A3

N1

A2

N1

N4

A3

A2

N1

Wilderness/

Non-Roaded

Management

N61

C1.P1

C1

N1

N6

C1

N6

A1

N1

A2

N1

A1

N1

'Model not commonly used in simulations.

2

 > = greater than; Rx has a greater emphasis than the next Rx.

The general characteristics of the 17 management

prescriptions are described in tables 2.5 and 2.6.

General responses of all 18 prescriptions are documented by Hann and others (in press) and Long

and others (1996). Documentation of the detailed

model probability and associated response data is

provided in the landscape assessment data record

(Hann and others 1997). Levels of disturbance

were identified by management prescription type

in relation to management emphasis: conserve,

restore, restore-produce, conserve-produce,

restore-conserve, or produce (table 2.6). These

categories correspond with emphasis categories in

the alternatives of the preliminary draft EISs.

Also identified for simulation purposes were relative rankings of fine-scale attributes associated

with the prescription (table 2.7). These attributes

had substantial fine- and mid-scale differences

within a broad-scale disturbance or vegetation

type. In the assessment of current and historical

conditions, for example, there were substantial

differences within a given broad-scale type in:

• Composition and structure of such components

as vegetation species and density; snags; down

wood; and bare soil.

• Disturbances, such as: fire behavior, grazing

effects, insect/disease mortality; and their patterns including patch size and shape, and position relative to biophysical relationships.

In general, these differences were correlated with:

• Roaded areas disturbed by management

activities.

• Roadless areas substantially affected by fire

exclusion.

SO Landscape Ecology
Table 2.7 — General attribute response to emphasis of management prescriptions in forest for dead

standing/down material conservation and soil exposed to erosion.

Rx'

N4

N5

N6

N7

N8

A2

C2

N2

P2

A3

C3

N3

P3

A1

C1

N1

P1

Large Snag

Conservation

Moderate

Moderate

High

Low

None

High

Low

Low

Low

Moderate

None

None

None

High

High

High

Low

(lost to wildfire)

Large Down

Wood Conservation

Moderate

Moderate

High

Low

None

High

Low

Low

Low

Moderate

None

None

None

High

High

High

Low

(lost to wildfire)

Duff/Litter Cover

Moderate

Moderate

High

Moderate

Low

High

Moderate

Moderate

High

High

Low

Low

Low

High

High

High

Low

(lost to wildfire)

Bare Soil

Low

Moderate

Low

Moderate

High

Low

High

Moderate

Low

Low

High

High

High

Low

Low

Low

High

(exposed to wildfire)

'Rx = prescription.

• Roadless areas with minimal or no effect by fire

exclusion.

We used the response differences between management prescriptions to characterize disturbance

probabilities and associated response. Our interpretations of the broad-, mid-, and fine-scale data

were done, either quantitatively or qualitatively,

based on our hierarchical knowledge of the broadscale patterns of vegetation and disturbance type

and its associated composition, structure, or landscape patterns at mid- and fine-scales.

Alternative Emphasis and

Prescription Assignments

Management classes represented areas of different ownership and management emphasis within

an EIS area. The BLM- and FS-administered

lands included the following five management

classes:

• Roadless, natural process dominated areas

(wilderness and wilderness-like).

• Roadless, human/natural process dominated

areas (typically visually sensitive or semiprimitive areas).

• Roadless, human process dominated areas (typically roadless areas managed for commodities or

dispersed recreation or visuals).

• Roaded, human/natural process dominated areas.

• Roaded human process dominated areas.

Spatial and temporal prescription assignments differed by alternative, with prescriptions assigned

systematically to stratifications by:

• Subbasin [4th-field hydrologic unit code

(HUG)]

• EIS area

• Management class

• Potential Vegetation Group.

To develop an integrated map of management

prescriptions for each alternative, we developed a

Landscape Ecology 51
data file stratified to the subbasin, EIS area, management class, and potential vegetation group

that had management emphasis codes from the

preliminary draft EISs for forest and range by

alternative. We then used the information from

the preliminary draft EIS on alternative activity

levels, theme, DFCs, and standards to correlate

with the "best fit" or management prescription

model.

Prescriptions were assigned a management emphasis based on the following factors, in successive

order:

• Emphasis maps (preliminary draft EISs, Ch. 3)

• Activity level descriptions

• Desired future conditions (DFCs)

• Theme of the alternative

• Standards of the alternative.

Using this data, we developed a rule set to assign a

management prescription code for each map stratification (table 2.6). The rule set was applied and

then adjusted for "best fit" based on:

• Our assumptions for the alternatives, as discussed in the "Introduction" section of this

chapter.

• Management emphasis and activity levels from

the preliminary draft EIS, Chapter 3.

• Themes and desired future conditions of the

alternatives.

• Standards from Chapter 3 of the preliminary

draft EIS.

• An iterative process for assigning prescriptions

and summarizing estimated effects levels to

achieve the standards (see appendix I, Vol. II of

this document).

• Qualitative review of Chapter 3 of the preliminary draft EISs to check for logical mapping of

prescription codes.

• Knowledge of ecological integrity, socioeconomic resiliency, forest and range clusters,

and the desired response as written in the preliminary draft EIS, Chapter 3 (see appendix I).

• Correction of errors in management class with

the appropriate prescriptions.

Management emphasis maps for forest and range

were based on the integrity clusters and preliminary draft EISs. Management emphases are shown

on maps 2.1 through 2.14. Descriptions of each

kind of management emphasis are provided in

appendix 2-C. The prescription assignments for

each alternative are shown on maps 2.15 through

2.21. Tables 2B.1 through 2B.28 in appendix 2-B

summarize prescription model characteristics for

forest and range areas for each EIS area by alternative, based on the prescription assignment and

other appropriate information.

Preliminary Draft EIS Alternative

Disturbances and Simulated

Disturbances

The simulation of alternatives had three objectives

for evaluating vegetation and disturbance response

at the broad-scale assessment level:

Objective 1. Prescription maps and associated

simulation data were adequate to determine the

relative differences in trends among the responses

for different landscape variables of Alternatives 1

through 7.

Objective 2. Understand the dynamics and variability of the responses of each alternative, based

on their ability to be successfully implemented.

For this objective, it was important that the simulation would quantify the dynamic cause and

effect relationships of management activities,

alternative standards, disturbances, and landscape

variables through time.

Objective 3. Quantify general levels of differences

among activity levels and other disturbances for

comparison purposes. For this objective, it was

also important to generally quantify any differLandscape Ecology
ences in the management activities specified in

Chapter 3 of the preliminary draft EISs and compare them to the simulated levels. This provided a

base for assessing if differences were related to

actual spatial and disturbance factors or if the prescription map was in error.

The simulations of alternatives met Objective 1.

Figures 2.3 through 2.6 provide comparisons of

the simulated responses during the first decade to

the preliminary draft EISs' minimum and maximum levels of activities. Tables 2.8 and 2.9 show

values of forest and range activities. Additional

information on the simulated responses is included in other sections of this evaluation.

The second objective was met to a moderate

degree with Alternatives 3 through 6, but only

partially met with Alternatives 1, 2, and 7. The

themes, desired future conditions, and standards

of Alternatives 3 through 6 provided a base for

predicting landscape dynamics in response to

management. Alternatives 1 and 2, which emphasize traditional management, were difficult to

model into the future with predictability because

treatment assumptions were not consistent with

the inherent disturbance processes and limitations

of the biophysical template. This difficulty led to

a response that has relatively poor reliability.

Alternative 7 also presented modeling difficulty

due to its large and frequently narrow reserves,

and an associated unpredictability of wildfire.

This response is indicative of the poor predictability and resiliency of systems managed with traditional commodity or reserve patterns, as compared to ecologically based management (Hann

and others, in press).

Some discussion points relative to Objective 3 are

listed below:

• For both EIS areas, the simulated levels of harvest in forests were relatively close to the preliminary draft EIS levels. Alternative 2 was slightly

high, but the difference was not substantial for

this spatial and temporal scale. However,

because of the transition time necessary to

change from from traditional management to

ecological management in Alternatives 3

through 7 we are not highly confident that the

harvest levels can be implemented.

1

 For both EIS areas, the simulated thinning levels

in forests were generally low compared to the

preliminary draft EIS levels. In contrast, the prescribed fire levels in forests were high for both

EIS areas. Given that simulated thinning also

assumed some prescribed fire or treatment of

fuels, and that prescribed fire assumed some pretreatment thinning, these two activities could be

grouped or interchanged to some degree. The

prescribed fire levels were high because the simulated levels included prescribed natural fire in

wilderness and roadless areas, that was not quantified in the prescribed fire levels in the preliminary draft EISs.

1

 The simulated prescribed fire in rangeland was

generally low in Alternatives 1 and 2, and high

in Alternatives 3 through 7. These differences

did not affect our ability to evaluate Objective 1,

but did affect our ability to evaluate Objective 3.

We discuss these differences qualitatively.

1

 The level of simulated rangeland improvements

was low compared to the levels in the preliminary draft EIS, which included more than just

vegetation improvements. When we included an

estimate of other range improvements to

improve livestock distribution, the level was

comparable.

1

 The preliminary draft EIS used "livestock management acres" as a measure of implementation

by permittees. We used a comparable estimate of

range plan revision and implementation levels

that combined the responsibilities of both the

Bureau of Land Management and the Forest

Service for rangeland plan revision within the

context of the alternatives and associated implementation of grazing operating plans by

permittees.

Landscape Ecology 53
Map 2.1 - Alternative 1 management emphasis for forest clusters on BLM- and FS-administered lands only. 

Landscape Ecology 
Map 2.2 - Alternative 2 management emphasis for forest clusters on BLM- and FS-administered lands only. 

Landscape Ecology 
Map 2.3 - Alternative 3 management emphasis for forest clusters on BLM- and FS-administered lands only. 

Landscape Ecology 
Map 2.4 - Alternative 4 management emphasis for forest clusters on BLM- and FS-administered lands only. 

Landscape Ecology 
Map 2.5 - Alternative 5 management emphasis for forest clusters on BLM- and FS-administered lands only. 

Landscape Ecology 
Map 2.6 - Alternative 6 management emphasis for forest clusters on BLM- and FS-administered lands only. 

Landscape Ecology