Great Basin Integrated Landscape Monitoring Project

Conceptual Ecological Models to Guide 

Integrated Landscape Monitoring of the Great Basin

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2010–5133

Nevada

Great Basin 

National Park

Utah
Cover: Satellite image is a Landsat scene acquired from U.S. Geological Survey’s Earth 

Resources Observation and Science (EROS) Center. Photographs are from the files of 

the U.S. Geological Survey.
Conceptual Ecological Models to Guide 

Integrated Landscape Monitoring of the 

Great Basin

Great Basin Integrated Landscape Monitoring Project

By D.M. Miller, S.P. Finn, Andrea Woodward, Alicia Torregrosa, 

M.E. Miller, D.R. Bedford, and A.M. Brasher

Scientific Investigations Report 2010-5133

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2010

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Suggested citation:

Miller, D.M., Finn, S.P., Woodward, Andrea, Torregrosa, Alicia, Miller, M.E., Bedford, D.R., and Brasher, A.M., 2010, 

Conceptual ecological models to guide integrated landscape monitoring of the Great Basin: U.S. Geological Survey 

Scientific Investigations Report 2010-5133, 134 p.
iii

Contents

Chapter 1. Conceptual Models for Landscape Monitoring

By D.M. Miller, S.P. Finn, Andrea Woodward, and Alicia Torregrosa ...................................................1

Introduction............................................................................................................................................1

Our Approach .......................................................................................................................................2

GBILM Project Area ............................................................................................................................3

Common Language...............................................................................................................................5

Definitions .....................................................................................................................................6

Ecosystem Drivers................................................................................................................................6

Wet Systems Drivers...................................................................................................................6

Dry Systems Drivers....................................................................................................................7

Cumulative Effects of Ecosystem Drivers.........................................................................................7

Structure of Conceptual Models........................................................................................................8

Chapter 2: Framework and System Models

By D.M. Miller, S.P. Finn, Andrea Woodward, Alicia Torregrosa, M.E. Miller, D.R. Bedford, and 

A.M. Brasher...................................................................................................................................13

Framework Model...............................................................................................................................13

Atmospheric System Model By D.M. Miller and M.E. Miller.......................................................14

Atmospheric System .................................................................................................................14

Climate Patterns in the Great Basin .......................................................................................15

Climate Change and Forecasts................................................................................................17

Ecosystem Effects .....................................................................................................................18

Summary Points .........................................................................................................................19

Human-Social System Model By Alicia Torregrosa......................................................................19

Introduction.................................................................................................................................19

Human Presence in the Great Basin ......................................................................................20

Modeling Approach...................................................................................................................27

Summary Points .........................................................................................................................27

Dry System Model By M.E. Miller and D.M. Miller .......................................................................28

Climate and the Physical Template.........................................................................................28

Soil Resources, Functions, and Quality..................................................................................28

Vegetation Resources and Functions.....................................................................................30

Wildlife and Habitat Quality .....................................................................................................31

Wet System Model By D.M. Miller, D.R. Bedford, and A.M. Brasher ........................................32

Subsystem Models .............................................................................................................................33
iv

Chapter 3: Subsystem Models for the Dry System

By M.E. Miller, S.P. Finn, and D.M. Miller.................................................................................................35

Salt Desert Scrub ...............................................................................................................................35

Sagebrush Steppe and Pinyon-Juniper Ecosystems By M.E. Miller ........................................35

Distribution and Management Significance .........................................................................35

Ecosystem Components and Processes................................................................................36

Drivers of Ecosystem Change..................................................................................................42

Ecosystem Dynamics ................................................................................................................44

Summary Points .........................................................................................................................55

Aspen Forests......................................................................................................................................55

Mixed Conifer Forest Model By S.P. Finn........................................................................................55

Distribution and Management Significance .........................................................................55

Components and Processes ....................................................................................................56

Drivers of Ecosystem Change..................................................................................................60

Ecosystem Dynamics ................................................................................................................62

Summary Points .........................................................................................................................68

Alpine Tundra Models By D.M. Miller .............................................................................................69

Distribution and Management Significance .........................................................................69

Ecosystem Components ...........................................................................................................69

Drivers of Ecosystem Change..................................................................................................70

Ecosystem Dynamics ................................................................................................................73

Summary Points .........................................................................................................................74

Chapter 4: Subsystem Models for the Wet System

By D.R. Bedford and D.M. Miller...............................................................................................................75

Groundwater Model By D.M. Miller and D.R. Bedford.................................................................75

Distribution and Management Significance .........................................................................75

Ecosystem Components and Processes................................................................................75

Drivers of Ecosystem Change..................................................................................................78

Ecosystem Dynamics ................................................................................................................78

Summary Points .........................................................................................................................78

Wetland and Spring Models By D.R. Bedford and D.M. Miller...................................................78

Distribution and Management Significance .........................................................................78

Ecosystem Components and Processes................................................................................79

Drivers of Ecosystem Change..................................................................................................84

Ecosystem Dynamics ................................................................................................................85

Summary Points .........................................................................................................................87

Stream and Riparian Models By D.R. Bedford...............................................................................87

Distribution and Management Significance .........................................................................87

Ecosystem Components and Processes................................................................................88

Drivers of Ecosystem Change..................................................................................................94

Ecosystem Dynamics ................................................................................................................95

Summary Points .........................................................................................................................95

Freshwater Lakes Model...................................................................................................................95

Saline Lakes and Marshes Model ...................................................................................................95
v

Chapter 5: Integration Models 

By Alicia Torregrosa and Andrea Woodward.........................................................................................97

Introduction..........................................................................................................................................97

Integrated Ecosystem Framework...................................................................................................97

Models for Monitoring Landscape Change..................................................................................104

Summary Points ................................................................................................................................108

Chapter 6: Summary and Conclusions

By Andrea Woodward, S.P. Finn, and D.M. Miller................................................................................109

Acknowledgments.....................................................................................................................................111

References Cited........................................................................................................................................111

Glossary.......................................................................................................................................................129

Appendix A. Ratings of System Drivers .................................................................................................133

Conversion Factors and Datums

Inch/Pound to SI

Multiply By To obtain

foot (ft) 0.3048 meter (m)

SI to Inch/Pound

Multiply By To obtain

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

hectare (ha) 0.003861 square mile (mi2)

square kilometer (km2) 0.3861 square mile (mi2)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8.

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).

Datums

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88)

Horizontal coordinate information is referenced to North American Datum of 1983 (NAD 83).

Altitude, as used in this report, refers to distance above the vertical datum.
vi

Acronyms and Abbreviations

AMO Atlantic Multidecadal Oscillation 

BSCs biological soil crusts

CO2 carbon dioxide 

ENSO the El Niño – Southern Oscillation

GBILM Great Basin Integrated Landscape Monitoring Project

GIS geographic information system

ILM Integrated Landscape Monitoring

NRCS Natural Resource Conservation Service

PDO Pacific Decadal Oscillation 

SSTs sea-surface temperatures 

TDS total dissolved solids

USDA U.S. Department of Agriculture

USGS U.S. Geological Survey

UNFCCC United Nations Framework Convention on Climate Change

UV ultraviolet
Introduction

The Integrated Landscape Monitoring Pilot Project (ILM) 

was developed by the U.S. Geological Survey (USGS) in 

response to the need of its partner agencies for a monitoring 

and predictive capability that addresses changes in broad 

landscapes and waterscapes. Human communities and needs 

are nested within landscapes formed by interactions among 

the hydrosphere, geosphere, and biosphere. Understanding the 

complex processes that shape landscapes and deriving ways to 

manage them sustainably while meeting human needs require 

sophisticated modeling and monitoring. The long-term goals 

of the ILM are to 

1. Identify, evaluate, and validate system components 

that are indicators of landscape change; 

2. Provide feedback to land managers on the results 

of management actions in the context of ecosystem 

change through synthesis of data, models, and other 

decision support tools; 

3. Define the unique ability of USGS to respond to 

customer needs in the area of landscape monitoring; 

and 

4. Lay out a vision for the future that will make use 

of USGS’ capabilities to design and implement 

monitoring networks, understand and model 

ecosystem change, and forecast landscape change. 

The Great Basin was selected as one of four national pilot 

landscape areas for integrated landscape monitoring effort 

because (1) there is a well-defined need by Federal, State, 

and local community groups for monitoring and ecosystem 

understanding at the landscape scale; and (2) USGS has 

significant capability, ongoing work, robust partnerships, 

and regional datasets in place. In response to the national 

directive, the Great Basin Integrated Landscape Monitoring 

Project (GBILM) was formed with participation from the five 

USGS disciplines and several Department of Interior partner 

agencies.

Conceptual Ecological Models to Guide Integrated 

Landscape Monitoring of the Great Basin

By D.M. Miller, S.P. Finn, Andrea Woodward, Alicia Torregrosa, M.E. Miller, D.R. Bedford, and A.M. Brasher

Chapter 1. Conceptual Models for Landscape Monitoring

By D.M. Miller, S.P. Finn, Andrea Woodward, and Alicia Torregrosa

In this document, we summarize and organize current 

understanding of ecosystem structure and function in the 

Great Basin using conceptual models. Communicating this 

understanding is fundamental to developing monitoring 

programs and can be done with clarity using the pictorial 

format of conceptual models. Conceptual models are not 

ends in themselves but are helpful organizers of thought, 

information, and ideas, and represent tools for communication 

and inquiry among scientists, managers, and the interested 

public. Consequently, the conceptual models in this report 

can be thought of as maps or flowcharts that help navigate a 

progression of scientific thought that starts with determining 

key ecological components and ends with a summary 

of mechanisms for the causal influences and relations 

among them. Eventually, conceptual models can provide a 

structure for designing monitoring programs, interpreting 

monitoring and other data, and assessing the accuracy of 

our understanding of ecosystem functions and processes. 

Additionally, the models can guide the identification of a few 

important attributes that provide information about multiple 

aspects of ecosystem status (Noon, 2003) and are efficient 

indicators to monitor.

In summary, conceptual models inform monitoring 

programs in the following ways (Maddox and others, 1999):

1. Models summarize the most important ecosystem 

descriptors, spatial and temporal scales of major 

biological processes, and current and potential 

threats to the system. They provide feedback to, 

and help formulate, goals, objectives, indicators, 

management strategies, results, and research 

needs. A model should not be expected to be 

complete and all-encompassing; rather, it should 

illuminate components of the ecosystem that relate 

to management and its impacts. Models facilitate 

discussion and debate about the nature of the system 

and important management issues and questions.
2 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

2. Ecological models play an important role in 

determining indicators for monitoring. The model 

is a statement of important biological and physical 

components and processes. It therefore identifies 

aspects of the ecosystem that should be measured. 

3. Ecological models can provide useful tools to help 

interpret monitoring results and explore alternative 

courses of management. Monitoring results should 

be used to update and improve the ecological model, 

which is the summary statement or framework of the 

system. Monitoring results may support or conflict 

with current understanding, thereby contributing 

to evolution of knowledge and understanding. 

Models are expected to evolve over time as they are 

developed, tested, and informed by new data and 

knowledge.

There is no single model that adequately describes 

an entire system or even a part of a system, because it is 

impossible to achieve both model generality and model 

realism. Model generality is needed to characterize broadscale influences and relationships among resources. In 

contrast, model realism is needed to identify specific potential 

expressions of change that could be effective monitoring 

indicators, which requires considerable detail. Consequently, 

integrative general models and more detailed specific models 

are needed to represent systems of the spatial extent and 

ecologic complexity of the Great Basin. Models that have 

the generality to describe an entire region will include few 

details about individual ecosystem components and will 

instead provide a broad overview of how those components 

interact. Achieving model realism necessary for understanding 

local-scale processes can be likened to moving a magnifying 

glass around to focus on individual ecological systems or 

management issues. With each change in position, some 

elements are brought into sharp focus while others become 

less distinct.

Recognizing that a group of related models is needed to 

describe the complexity of the Great Basin at different levels 

of detail, the GBILM project developed a set of conceptual 

ecosystem models to: identify key ecological functions and 

services; develop an overarching model of landscape function; 

inform regional monitoring strategy development that 

integrates existing capabilities; and identify critical gaps in our 

knowledge of ecosystem function. This report is a first step in 

the process; it: 

• Describes the process that the Conceptual Modeling 

Team used to develop the conceptual models, 

• Develops the framework for ecosystem models, 

• Identifies the most important ecosystem drivers, 

• Presents and describes our set of conceptual models, 

and 

• Illustrates our approach of scaling from a framework 

model to system-specific models and integrating the 

component pieces. 

This document provides a conceptual framework for 

many of the unique ecosystems within the Great Basin and 

includes conceptual models of ‘reference-states’ and the 

drivers and stressors particular to each biophysical system. 

The document develops models at different levels of 

specificity to illustrate our approach. A conceptual model also 

has been developed to address landscape integration, such 

as interactions among ecosystems and cumulative impacts 

of multiple drivers, and approaches for scaling from local 

to landscape-level understandings. Fine-scale models for 

several biophysical subsystems are not developed, but will 

be developed pending future focus of project staff on these 

subsystems. This document is presented to help develop a 

broad-scope monitoring strategy that, when implemented, 

will provide data to help answer the resource management 

questions that catalyzed the creation of the GBILM. 

The indicators developed through this effort function as 

measurement points that can be used to test the validity of the 

models and refine research paths needed to better understand 

change within the Great Basin.

The GBILM models are intended to help identify the 

natural and anthropogenic drivers/stressors of a system, serve 

as a structure to interpret data and assess the accuracy of our 

understanding of ecosystem functions and processes, and 

facilitate communication with partners about how decisions 

for indicators, priorities, and protocols in monitoring programs 

are determined. In response to Department of the Interior 

agency and partner needs, the GBILM models will place 

strong emphasis on management relevance and societal values.

Our Approach 

Models in this document were developed using a 

systematic process that defined our goals and limitations; 

identified key systems, subsystems, and system drivers; and 

characterized primary linkages among systems in the Great 

Basin. We loosely followed a set of tasks for developing 

conceptual models described by Gross (2003). These tasks are:

1. Determine the goals of the conceptual models.

2. Identify bounds of the system of interest.

3. Define a common language.

4. Identify key model components, subsystems, and 

interactions.

5. Develop control models of key systems and 

subsystems.

6. Identify natural and anthropogenic stressors.

7. Describe relationships of stressors, ecological 

factors, and responses.

8. Articulate key questions or alternative approaches.

9. Identify inclusive list of indicators.

10. Prioritize indicators.

11. Review, revise, and refine models.
Chapter 1. Conceptual Models for Landscape Monitoring 3

The process was initiated through a series of conference 

calls leading to a 2-day workshop held in June 2006, 

during which team members provided expert knowledge 

on systems and linkages and identified knowledge gaps 

amongst the team members. The workshop was followed 

by regular communication among several subteams, each 

focused on ecosystem-specific models. Subteams continued 

to communicate when using and refining the models with 

the intention of keeping the models relevant and updated. 

In this conceptual modeling phase, the group did not stress 

the systematic identification and prioritization of indicators, 

although many are identified in the model narratives.

The Conceptual Modeling Team articulated the following 

goal: 

We will develop conceptual ecosystem models 

that describe ecosystem components, external 

drivers, and interactions of the components, drivers, 

and processes in such a way that components 

and processes can be prioritized with regard to 

importance for monitoring.

We identified the relevant spatial, systemic, and 

temporal bounds of the Great Basin by iterative review and 

discussion within the interdisciplinary team in consultation 

with agency partners. We reviewed 11 existing descriptions 

of the Great Basin’s spatial extent, mapped these descriptions, 

and explored and described which geographic boundaries 

best encompassed the potential critical components for 

which managers most need monitoring information. Next 

we constructed a two-way matrix of subsystems versus key 

ecosystem components, stressors, drivers, and potential 

monitoring attributes to make initial predictions regarding 

which subsystems were significantly impacted by multiple 

(or intense) stressors and therefore were good candidate focal 

systems for conceptual models. We identified a 50-year future 

time span of consideration for the ensuing models based on 

this matrix, our knowledge of Great Basin landscape change, 

and resource manager needs. We later considered the legacy 

of land-use impacts (200-year bound) and pre-historic impacts 

by people and climate changes (2–5 millennia) as important 

precursor time windows. We maintained a common language 

throughout the process by agreeing to specific definitions for 

all terms and concepts used during the process (see sections 

“Common Language” and “Glossary”).

Team members identified key model components, 

subsystems, and interactions by reviewing existing models 

describing arid and aquatic ecosystems in the Western United 

States and cross-referencing them to our system-driver matrix. 

As part of the iterative process, we reevaluated potential 

model components, subsystems, and interactions in an expert 

roundtable discussion at the 2-day workshop.

An overall model structure was developed using a 

hierarchical approach. Based on the system-driver matrix 

we drafted a ‘Framework Model’ that coarsely describes 

systems and interactions operating in the Great Basin. One 

important principle that emerged during discussions was the 

significance of water to systems throughout the Great Basin 

and the distinction between precipitation-event-driven systems 

(‘dry’ systems) and surface- and groundwater systems (‘wet’ 

systems, which respond to precipitation at long time scales). 

We reviewed the prevalence and importance of key dry and 

wet subsystems at local and regional scales and identified 

where system-specific models would be most useful to 

managers. The team agreed that key models for an integrated 

understanding of landscape level functioning of the Great 

Basin are: stream and riparian areas, groundwater dominated 

wetlands and springs, freshwater lakes and marshes, saline 

lakes and marshes, salt desert scrub, sagebrush steppe, pinyonjuniper woodlands, aspen forests, conifer forests, and alpine 

tundra. This list excludes several systems such as dry and wet 

playas, sand dunes, caves, hot springs, and badlands, all of 

which play important ecological roles but have smaller spatial 

footprints.

During the expert roundtable discussion, the team 

identified a suite of 30 natural and anthropogenic drivers and 

stressors (appendix A). We selected a subset of nine stressors 

as being critical to Great Basin ecosystem functioning and as 

being top priorities for further monitoring. These nine stressors 

are: water extraction, flow regime, livestock grazing, invasive 

exotic species, fire regime, invasive plant-fire interactions, 

land treatments, motor vehicle use, and climate change and 

variability. Next, we described the relationships of the top 

stressors to each of the 10 subsystems independent of the 

previous system-driver matrix to validate our assumptions and 

identify draft components of the subsystem models.

Finally, we identified teams to develop subsystem models 

for six focal subsystems: sagebrush steppe/pinyon-juniper 

woodlands; mixed conifer forest; alpine tundra; groundwater; 

stream and riparian; and wetlands and springs. These models: 

(1) serve as stand-alone models for the respective subsystems, 

(2) provide ‘straw men’ for further iterative critique and 

review of our process, and (3) are representative examples for 

modeling the other key subsystems.

GBILM Project Area 

The Great Basin forms a wedge between the Sierra 

Nevada and Rocky Mountains (fig. 1.1). Bounded to the 

north by the Columbia Plateau and Snake River Plain and 

to the south by the Mojave Desert, the defining feature of 

the region is its internally draining surface hydrology. This 

closed hydrographic system exceeds 500,000 km2 in area and 

includes nearly all of Nevada, and parts of eastern California, 

western Utah, southeastern Oregon, and southern Idaho. The 

Great Basin may be spatially defined by hydrologic, geologic, 

biologic, or cultural definitions which all vary slightly. 

Anthropologists define the region by cultural attributes of 

the aboriginal inhabitants (d’Azavedo, 1986), botanists by 

species composition of the vegetation (Billings, 1951; Vasek 

and Barbour, 1977), geologists by the structure of the land 
4 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig01-01

Reno

Salt Lake

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Bend

Boise

Pocatello

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Las Vegas

Bishop

Sacramento

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Twin Falls

Ontario

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Pyramid

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UTAH

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Colu

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Columbia Plateau

Blue MountainsBlue Mountains

Snake River PlainSnake River Plain

Colorado Plateaus Colorado Plateaus

Wasatch Range Wasatch Range

Wyoming Bas ni Wyoming Bas ni

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Uinta Mountains Uinta Mountains

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Owyhee

Plateau

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Bonneville

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Meadow Valley Wash

Death Valley

Northern Basin and Range

Central Basin and Range

Fish Lake

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Ash

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SIERRA

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SIERRA

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GREAT BASIN

110°

112°

112°

114°

114°

118°

118°

120°

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122°

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116°

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44° 44°

42° 42°

40° 40°

38° 38°

36° 36°

0 50 100 150 200 MILES

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Washington

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California

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Arizona

Utah

Colorado

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PACIFIC

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CANADA

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GBILM

EXPLANATION

Omernik's ecoregions

Great Basin Integrated Landscape Monitoring 

Project (GBILM) Area-of-Interest

Figure 1.1. Map showing GBILM Area-of-Interest including the Great Basin and the floristically similar Snake River Plain. Area 

was delineated by overlapping Omernik’s northern and central Basin and Range provinces (Omernik, 1987) with the Bureau of Land 

Management’s (BLM) Great Basin Restoration Initiative focal area. 
Chapter 1. Conceptual Models for Landscape Monitoring 5

(Hunt, 1967), and hydrologists by the position of aquifers and 

surface-water flow. For regional monitoring, GBILM defines 

an area-of-interest that includes an overlay of Omernik’s 

(1987) northern and central Basin and Range Provinces and 

the Great Basin Restoration Initiative’s focal area [http://www.

blm.gov/id/st/en/prog/gbri/map.html] (fig. 1.1). GBILM’s 

boundary includes areas outside of but adjacent to the 

hydrologic Great Basin that are floristically and ecologically 

similar to the interior basins. Throughout this document, 

we will refer to the area depicted in figure 1.1 as the ‘Great 

Basin.’

Topographic relief in the Great Basin creates elevation 

gradients and associated gradients in air density, solar 

radiation, and precipitation. The interaction of these factors 

creates many temperature and moisture regimes, which 

significantly affects plant distribution (Billings, 1970) and 

animals that depend on them (Hall, 1946). The high, cold 

(relative to other American deserts) Great Basin desert 

historically has received most of its moisture as snow 

(McMahon, 1988; see Chapter 2, section “Atmospheric 

System Model” for more climate details).

The mountainous terrain, paleo-history, varied climate, 

and human settlement in the Great Basin provides many 

opportunities and challenges for a multitude of organisms with 

diverse life strategies. The composition of biota in the region 

is a blend of species in common with surrounding regions 

and a suite of endemic species specifically adapted to life in 

this cold desert. This combination produces high biological 

diversity but poses threats to some species’ existence. For 

example, the Great Basin contains more than 130 endemic 

plant species or subspecies, 95 of which are imperiled. A 

driver of this high endemism is the patchy nature of many 

habitat types and the fluidity of patch connectivity across 

the landscape over geological time. Within 20 km, a single 

basin-range unit can host environments that range from 

treeless alpine bogs and rocky slopes to montane coniferous 

forests, diverse mountain shrublands, woodlands of pinyon 

pine (Pinus edulis) or juniper (Juniperus spp.), lower slopes 

of sagebrush (Artemisia spp.) and grasses, lake shores that 

support an entirely different array of shrubs and flowers, 

barren sand dunes, and playas. Dozens of montane habitat 

islands in the region now are separated from each other by 

arid lowlands. Major metropolitan areas are connected by 

transportation and utility arteries, which contrast with the 

sparse ranch and farm land uses in much of the Great Basin.

Common Language

The degree of interdisciplinary cross-fertilization 

used by groups as they meet multidisciplinary challenges 

has been shown to affect the type of product that results 

(Westly and Miller, 2003; Lawrence and Despres, 2004; 

Hinkel, 2008; Klein, 2008). Teams that strongly adhere to 

disciplinary boundaries tend to merge their results into an 

overarching model after the individual disciplinary results 

are finalized. An example is the traditional approach to flood 

control which first engineers a flood-control (dam/reservoir) 

structure based on watershed drainage and subsequently 

mitigates the negative effects on salmonids using measures 

such as fish ladders. Teams that encourage more flexibility 

between disciplinary structures tend to use whole-systems 

approaches that take into account seemingly disparate causal 

relationships. A well documented example is the recent 

tobacco research that investigates the effects of smoking from 

genetic, neurobiological, social, and economic perspectives 

to conclude that previous understanding of addiction was 

inadequate to address the problem of tobacco usage by 

informing effective public policy (Stokols and others, 2003). 

The group challenge of developing a common language 

is especially acute for teams with disciplines that use terms 

(or jargon) in incompatible ways and where the terms have 

a long or strong theoretical disciplinary basis that is at odds. 

For example, the term ‘scale’ to a geographer refers to the 

ratio between a map and the landscape it represents. To a 

geographer, a map at 1: 24,000 scale is at a much larger scale 

than a map at 1:1,000,000 scale. For scientists in many other 

disciplines, a large-scale map refers to a map that shows a 

large area, necessitating a small map scale. These two opposed 

uses of the term ‘scale’ illustrate the potential difficulty in 

thinking across disciplines and foreshadows the shifts in 

perspective that can make way for new and different types of 

conceptualization.

The interdisciplinary nature of the GBILM team required 

that we agree to a common language drawn from a monitoring 

literature that is replete with terms and distinctions that vary 

among users. Consequently, we explicitly defined a vocabulary 

for this report and in the process we became more discerning 

in our use of terms such as ‘stressor’ and ‘driver’.
6 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Definitions

We define landscape change to be changes in the 

types, relative proportions, and ‘condition’ (health, integrity, 

resiliency, functioning) of Great Basin biophysical systems, 

particularly as these changes relate to mandates and/or 

management objectives of land managers. Landscape changes 

include changes to soils, geomorphic processes, hydrologic 

systems, and atmosphere as they pertain to ecosystems.

We define ecosystem (system) drivers, both natural 

and anthropogenic, as the events and processes that are 

most responsible for ecosystem change in the Great Basin. 

These may be related to global or regional climate, natural 

disturbance regimes, nutrient cycling, or human activities. 

Control models describe our present understanding of how 

ecosystems and their subsystems respond to the drivers. At the 

point that drivers exceed the range of variation beyond which 

the current biological communities can survive (commonly 

taken as exceeding the long-term or reference range of 

variation), the drivers become stressors to the system. 

Examples include extreme climate change (driver) that results 

in the conversion of shrub lands to grasslands or polluting 

levels of nitrogen fertilizers (driver) in streams that results in 

oxygen deprivation of the aquatic subsystems. Although we 

do not define precise thresholds beyond which drivers become 

stressors, we use stressor models to hypothesize what kind 

of ecosystem changes we expect the driver to cause. The 

predictions from stressor models and the critical processes, 

components, and drivers described in control models can 

inform the choice of monitoring indicators.

We define drivers as ‘natural’ when the ecosystem 

has evolved with their effects. Natural drivers commonly 

are quasi-cyclical and in a state of dynamic equilibrium 

in the absence of excessive human pressures. In contrast, 

‘anthropogenic’ is used when we wish to highlight that the 

driver is a result of human activities. Although anthropogenic 

activities are in many cases accompanied by losses in 

biodiversity or functional integrity, they also can have positive 

effects, for example restoration and mitigation. Making 

a distinction between natural and anthropogenic drivers 

is fraught with the potential for disagreement and good 

arguments can be made that any human action is natural. We 

make the distinction to allow us to make simpler models with 

better explanatory power.

Implicit in the ‘natural’ aspect of these definitions is 

the need to identify ecosystem-specific reference conditions 

that are framed with respect to a particular time period and 

place (White and Walker, 1997; Landres and others, 1999). In 

addition to these temporal and spatial bounds, it is desirable 

to explicitly identify associated goals, assumptions, and 

value judgments when adopting a particular set of reference 

conditions as the “natural” standard for management and 

monitoring (Truett, 1996; Landres and others, 1999). LateHolocene, pre-European conditions often are identified as the 

standard for defining natural disturbance regimes, although it 

is important to recognize the potentially important role of preEuropean human populations in shaping disturbance regimes 

and ecosystem conditions before European contact (Anderson 

and Moratto, 1996; White and others, 1999). In addition, 

periods of climate variability during the late Holocene such 

as the Medieval Warm Period (ca. 800–1350 AD) and Little 

Ice Age (ca. 1350–1850 AD) caused significant changes in 

hydrological systems (for example, lake levels and river flow) 

and human adaptations to the environment (for example, shifts 

in subsistence mechanisms and locus of habitation) (Benson 

and others, 1990). The dynamic nature of ecosystems is a vital 

concept for understanding the Great Basin.

Ecosystem Drivers

We listed and prioritized system drivers based on expert 

opinion in order to focus our conceptual models on those 

parts of Great Basin ecosystems most subject to change 

(appendix A). We rated every driver according to its scope or 

magnitude as a factor contributing to management relevant 

landscape change across the Great Basin. The final list of 

high priority drivers (five for wet systems, six for dry) is 

given below along with justifications. We recognize that 

this prioritized list may be too ambitious, and that further 

stakeholder input and changing societal conditions may 

change the priorities. Nevertheless, this list provides focus for 

developing the current subsystem models.

Wet Systems Drivers

Water Extraction. Withdrawal of groundwater is 

widespread in the Great Basin in agricultural settings and for 

municipal use. Groundwater withdrawal lowers water tables 

because recharge rates generally are very low, and the lowered 

water table can lead to loss of springs and wetlands. The 

possibility of accelerated groundwater withdrawal associated 

with urban development highlights this driver as one of special 

concern.

Flow Regime. Diversion of streams for irrigation, 

disruption of streamflow by roads and levees, channel changes 

for flood control or other reasons, and climate change resulting 

in changing precipitation and altered snowmelt patterns all 

contribute to altered flow regime. Flow Regime describes 

stream function and therefore biotic habitat condition.

Livestock Grazing. Livestock trample streambanks and 

wetlands, altering habitat in these critical riparian zones and 

changing hydrologic function. In addition, livestock may alter 

species composition and water quality by nutrient loading. 

Most of the Great Basin is subject to livestock grazing and 

large areas host feral horses.

Invasive Exotics. Introduction of invasive aquatic 

species has altered most water systems in the Great Basin. 

Specifically, sport fish have been introduced to nearly every 

stream. Invasive plants have altered the structure, function, 

and habitat value of many riparian and wetland systems.
Chapter 1. Conceptual Models for Landscape Monitoring 7

Climate Change and Variability. Global warming 

and accompanying increased climate variability has altered 

snowmelt periods, reducing water available for stream flow 

and lakes, and increasing impacts from intense storms, such as 

floods.

Dry Systems Drivers

Fire Regime. Altered fire regimes attributable to past 

livestock grazing (fuel removal) and fire-suppression efforts 

have caused significant changes in vegetation structure and 

the function of associated ecosystem processes. Mediated by 

changes in vegetation structure, ecosystem-level consequences 

of altered fire regimes can include diminished hydrologic 

functioning and increased erosion rates, as well as increased 

ecosystem susceptibility to drought (Miller, 2005).

Invasive-Fire Interaction. Introduction of 

Mediterranean annual grasses has led to infilling of intershrub 

spaces with highly combustible grass, increasing intensity and 

frequency of fire in shrublands of the Great Basin. Increased 

fire frequency alters natural fire cycles, promoting invasive 

grasslands over native shrubs, impacting soil properties, and 

altering wildlife habitat.

Livestock Grazing. Grazing alters species composition, 

vegetation structure, and animal habitat through many 

mechanisms. Trampling by livestock destabilizes soils, alters 

hydrologic processes and nutrient cycling, and facilitates the 

establishment of invasive exotic plants.

Land Treatments. This driver ranges widely in type 

and scope but all treatments are meant to improve land utility. 

Examples of land treatments are roads and trails, agriculture, 

crested wheatgrass and other introduced grass plantings, 

chained shrublands and woodlands, timber harvested forests, 

and even flood-control basins. All treatments cause vegetation 

change, alter wildlife habitat, and alter soils and nutrient 

cycling.

Motor Vehicle Use. Motor vehicles, used on road 

and off, are potential vectors for invasive species and toxic 

contaminants, and effectively introduce refuse and accelerated 

human visitation in all but the most remote mountain areas. 

Off-road vehicle use promotes soil compaction, plant 

mortality, soil erosion, increased carbon dioxide (CO2) and 

dust emissions, and reduced air quality.

Climate Change and Variability. Global atmospheric 

changes attributable to anthropogenic emissions of CO2

and other greenhouse gases are expected to have significant 

environmental consequences during this century (Houghton 

and others, 2001). Increasing levels of atmospheric CO2, 

increasing soil and air temperatures, and altered precipitation 

patterns (including a potential increase in the frequency of 

extreme events) are likely to affect physiological processes 

and competitive relationships of vascular plants, nutrient 

cycles, hydrologic processes, and disturbance regimes. All 

these changes have the potential to greatly alter the structure 

and functioning of dryland ecosystems and the sensitivity of 

these systems to other anthropogenic stressors (Miller, 2005).

Cumulative Effects of Ecosystem Drivers

Developing a predictive understanding of the effects of 

ecosystem drivers in the Great Basin requires the realization 

that drivers typically have effects that interact and accumulate 

in space and time. Depending on the temporal and spatial 

circumstances, these cumulative effects can appear as a 

stressor accumulating over space (for example, low levels 

of a water pollutant in tributaries accumulating in a river), a 

stressor accumulating over time (for example, repeated land 

treatments of the same area), and combinations of single and 

multiple stressors (fig. 1.2) accumulating over time and space. 

Interactions also can occur between natural and anthropogenic 

drivers or disturbances (White and others, 1999; Archer 

and Stokes, 2000). Because disturbance cycles play such 

an important role in shaping the structure and functioning 

of ecosystems (for example, by strongly interacting with 

soil resources and vegetation structure), disturbance-regime 

alteration is one of the most significant ways by which human 

activities affect ecosystems (Chapin and others, 1996).

The climate change/variability driver interacts with 

nearly all other key drivers, mostly by influencing how they 

operate on the landscape (fig. 1.2). For example, long-term 

changes in precipitation in the region, as well as changes in 

timing of snowmelt and intensity of storms, are likely to affect 

base streamflow rates causing changes in flow regimes and in 

the volume of water available to extract. Similarly, changing 

air temperatures influence evapotranspiration rates causing 

changes in soil and fuel moisture, and potentially influencing 

fire return intervals. Climate change also may create favorable 

conditions for the proliferation of disruptive species that 

previously were limited by water or air temperature. In 

general, relatively persistent shifts among ecosystem states 

commonly are triggered by synergistic interactions between 

two or more drivers of ecosystem change (Paine and others, 

1998; Scheffer and others, 2001; Folke and others, 2004). 

Characteristically, one driver acts to decrease system tolerance 

of another driver and thus enables subsequent changes (for 

example, soil disturbance can reduce ecosystem resistance to 

the establishment of invasive exotic grasses).

Interactions among stressors and drivers are scale 

dependent and may accumulate to affect multiple systems. 

Fine scale (site-specific) drivers, generally anthropogenic, 

also are likely to interact, and the results accumulate to 

potentially significant consequences at the landscape-scale 

and in systems other than those in which they occur. For 

example, livestock grazing in sagebrush-steppe may alter 

plant species composition, potentially increasing vulnerability 

to invasion by exotic species and, perhaps, altering fire and 

flow regimes. The altered fire and flow regimes in turn impact 

other systems, such as pinyon-juniper, riparian, and salt desert 

scrub communities. Some widespread effects (for example, 

climate change) also may have differing impacts in different 

systems depending on the dynamics of cumulative effects 

within or among subsystems. Therefore, we need to consider 

the relative scale at which stressors and processes work, 
8 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig01-02

I

access for fire suppression

gnition source; increased Ignition source; increased 

Decreased fuel moisture

Wetland conversion

Altered fuel loads/distributions

Partial driver of management actions

Seed source/increase disturbance

Drive land management strategies

Altered plant composition and 

distribution

Altered forage quality/availability

Seed source/increase 

disturbance and 

fragmentation Altered forage quality/availability

Altered plant composition/seed source

Shifting niche parameters

Changing E-T rates

Changing precipitation patterns

Changing precipitation patterns/ 

Altered groundwater levels Changing demands Reduced availability / reduced 

Increased fine fuels

Requires increased access Requires increased access

Large-scale disturbance

Varying 

temperatures/moisture

Increased particulates / 

Altered microclimates

Climate Change/Variation

Flow Regime

Water Extraction

Fire Regime Invasives

Land Treatments

Ultimate

Energy

Source

Motor Vehicle

Use

Livestock

Grazing

Ecological

Processes

Human

Activities

Figure 1.2. Diagram of principal interactions among ecosystem drivers in the Great Basin.

and their functional relationships (for example, non-linear, 

exponential, etc.). For example, fine-scale stressors such as 

land treatments could affect fire regime and invasion dynamics 

leading to changes in vegetation structure and composition in 

the surrounding landscape.

Our stylized conceptual model of stressor and driver 

interactions (fig. 1.2) identifies potential interactions among 

systems to better understand how to efficiently approach 

monitoring the changing landscape, to stimulate hypothesis 

development, and to identify gaps in our knowledge of 

ecosystem processes. We acknowledge the incompleteness 

of this diagram, which is due to the limitations of graphically 

portraying interactions of such complexity, and more 

significantly, a lack of current knowledge of the relevant 

interactions among many drivers. Two urgent questions 

require investigation. First, will Great Basin ecosystems 

be able to respond to increasing CO2 concentrations, 

temperature, and changing precipitation regimes without 

irreversible change? Second, will the response of Great Basin 

ecosystems to changing climatic and atmospheric conditions 

be excessively compromised by the multiple drivers associated 

with human land-use activities?

Structure of Conceptual Models

Multiple conceptual models are required to describe the 

Great Basin in enough detail to suggest and justify monitoring 

indicators. Consequently, we divided the Great Basin into 

hierarchical units that we described with sufficient detail 

to model the effects of the priority drivers. The hierarchy 

includes four levels (fig. 1.3).

Framework Model. The highest level of the hierarchy 

is the overall model, which we termed the Framework Model. 

It identifies the major biotic and abiotic systems of the Great 

Basin and how they are related.

System Models. We created a system-level model for 

each of the four systems described in the Framework Model. 

These are graphic and narrative models that describe how the 

system operates at the broad landscape scales and how it is 

divided into subsystems by major abiotic gradients, such as 

elevation and precipitation.

Subsystem Models. These models describe our 

understanding of the important components and drivers of 

each subsystem and present our current understanding of 

the processes that shape the subsystem. In some respects, 

these models are aspatial in that they ignore interactions 
Chapter 1. Conceptual Models for Landscape Monitoring 9

among adjacent systems and may de-emphasize aspects of 

geographic distribution that are important for understanding 

the subsystem. Each subsystem is modeled using some or 

all the following model structures: structural control model, 

state-and-transition model, and mechanistic stressor model 

(fig. 1.4).

Control Model. Different drivers predominate in each 

subsystem and each subsystem responds to different suites 

of drivers in different ways. Control Models describe our 

understanding of how the subsystems work in response to 

the inherent variation of drivers by depicting the principal 

components and processes of the subsystem. These models 

were built with a focus on the priority drivers. 

State-and-Transition Model. Ecological systems are 

naturally dynamic as they respond to effects of stressors and 

drivers and to inherent cycles. Ecosystem changes occur 

along a continuum of time and space, but for the purposes of 

quantitative modeling, it is helpful to categorize the changes 

in terms of discrete potential states. Subsystem categories 

essentially do this for ecosystems in space; state-and-transition 

models make it possible to illustrate these changes in time. 

Mechanisms for switching between ecosystem states are 

provided by the control and stressor models. 

Stressor Model. For most Control Models, there is at 

least one Stressor Model describing how the subsystem is 

expected to respond to changes induced by drivers that are 

out of the reference range of variation (stressors). The number 

of models for each subsystem will depend on how well we 

understand the subsystem and how adequately one model can 

describe all relevant stressors (fig. 1.3).

Figure 1.3. Hierarchy of conceptual models used to explain and justify the choice of monitoring questions and indicators. The 

hierarchy consists of one framework model, four system models, ten subsystems, and one model that integrates the others. Models

developed in this report are shown in bold.

tac09-0397_fig01-03

Subsystem Models

Aspatial descriptive models 

of subsystem components 

drivers and dynamics.

Framework Model

Atmosphere

Wet Systems Dry Systems

Human System

Integration Model

System Models

Groundwater

Stream and Riparian

Wetlands and Springs

Freshwater Lakes

Saline Lakes

Alpine Tundra

Subsystem Models

Aspen Forest

Salt Desert Shrub

Mixed Conifer Forest

Sagebrush Steppe/ PinyonJuniper Woodlands

System Models

Graphic and narrative 

models that describe the 

landscape and relationships 

among subsystems. 

Integration Model

Spatial model enabling 

accumulation of drivers and 

stressors, and transfer of 

information across spatial 

and temporal scales.
10 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Figure 1.4. Diagrams illustrating relations among control, stressor, and integration models used to describe the structure and 

dynamics of sagebrush steppe and pinyon-juniper ecosystems in this report. 

tac09-0397_fig01-04

NATURAL

DISTURBANCE

CLIMATE

WILDLIFE

& HABITAT

VEGETATION

&

SOIL

ANTHROPOGENIC

DRIVERS

ANTHROPOGENIC

DRIVERS

PHYSICAL

TEMPLATE LANDSCAPE

A. Control Model

REFERENCE CONDITION,

SAGEBRUSH STEPPE

EXOTIC

DOMINATED

INTRODUCED

SEEDING

RESTORED

CONDITION

DEGRADED

SAGE-STEPPE

TREE

DOMINATED

SEVERELY

ERODED

B. State-and-Transition Model

CLIMATE

EXCESSIVE GRAZING Cover / vigor

of perennial grasses

ATMOSPHERIC

CO2

Frequency of

surface fire

FIRE

SUPPRESSION ?

?

C. Mechanistic Stressor Model

TREE RECRUITMENT

& DOMINANCE
Chapter 1. Conceptual Models for Landscape Monitoring 11

Integration Model. We recognize the need to accumulate 

and integrate the effects of multiple stressors and drivers 

through time and space. Without doing so, we will miss such 

effects as those of patch dynamics on wildlife, including the 

proportional amount and distribution of habitat types, and the 

soil and climate constraints on ecosystem potential. Integration 

includes scaling, such as transferring data across the range of 

spatial scales, between the scales at which data are collected 

and then applied, and scaling to the appropriate level to 

address the management questions being asked. Integration 

provides templates for addressing the multiple temporal scales 

at which ecosystem processes, drivers, and stressors operate. 

In Chapter 5, we provide a conceptual model for how we 

intend to accomplish these integration steps.

One of the modeling challenges faced by the GBILM 

team was to conceptualize the human dimension. Chapter 2

describes the human dimension at the System Model level 

along with the other three models (atmosphere, dry systems, 

and wet systems) that are relevant at this level. Although 

subsystem models within the dry and wet systems are 

developed in greater detail, models of the atmospheric and 

human dimension are not developed in comparable detail. 

This is not to imply that atmospheric or human-induced 

effects are not included within control and stressor models; 

to the contrary, anthropogenic activities and climate are 

acknowledged as important factors in all Great Basin 

ecosystems and in all subsystem models. Nevertheless, we 

recognize that, especially for the human dimension, more 

needs to be done to effectively integrate an understanding of 

anthropogenic drivers into the conceptual models to guide the 

GBILM effort.

This document includes the framework model, system 

models, several subsystem models for parts of the Dry and 

Wet Systems, and the Integration Model. With this hierarchical 

approach, we aim to focus on the effects of our high priority 

drivers in an efficient manner while acknowledging those 

parts of the Great Basin we will not be addressing. This model 

structure forms the basis for quantitative models that can be 

developed in order to create local, landscape, and regional 

predictions of ecological change. Similarly, the conceptual 

and quantitative models can be used to identify, justify, and 

explain monitoring indicators.

Dividing the landscape into discrete units based on water 

sources and outlets, dominant plant species, or elevational 

bands is convenient for conceptual modeling. However, 

we recognize this approach also can be misleading because 

systems and their shared ecotones are interdependent at 

multiple spatial and temporal scales. Thus, the Great Basin 

more accurately may be characterized as a continuum with 

constant exchange of materials and energy among systems 

and subsystems where each species responds uniquely to 

underlying environmental gradients (Austin and Smith, 1989; 

Shugart, 1998; Euliss and others, 2004). By using discrete, 

system-based models, we do not imply that systems lack 

interaction, nor do we wish to blur important connections 

within or among systems. Rather our deconstructions in 

Chapters 2 to 4 attempt to simplify our conceptualization 

of the ecological continuum and focus system-specific 

management and monitoring targets. More incisive analyses 

and holistic reconstructions of Great Basin ecosystems are 

presented in Chapter 5.
12 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

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Chapter 2: Framework and System Models 13

Framework Model

As an organizational tool, we have adopted a simple 

conceptual framework describing systems and domains of 

integration encompassed by the GBILM project (fig. 2.1). We 

represent the patterns and processes of landscape change in 

the Great Basin as they are reflected by complex interactions 

and feedbacks among four systems – the atmospheric 

system, dry and wet ecosystems, and human social systems. 

To effectively meet science-information needs of Great 

Basin decision makers during a period of rapid social and 

environmental change, landscape-level monitoring requires 

integration across all these systems and the multiple spatial 

and temporal scales that span their interactions. This challenge 

can best be met through the collaborative integration of all 

USGS disciplines. This conceptual framework model provides 

a foundation for organizing ideas and communicating with 

diverse stakeholders. More detailed scale- and processspecific conceptual models at subsystem levels, presented in 

Chapters 3 and 4, are used to identify monitoring indicators 

and their ecological underpinnings (Noon, 2003).

Chapter 2: Framework and System Models

By D.M. Miller, S.P. Finn, Andrea Woodward, Alicia Torregrosa, M.E. Miller, D.R. Bedford, and A.M. Brasher

Figure 2.1. Framework model diagram illustrating the overall conceptual framework for the Great Basin project.

Alpine

Coniferous

Forests

Coniferous

Woodlands

Sagesteppe

Dry

Playas

Aspen

Salt Desert

Scrub

Saline / Alkaline

Lakes

Upland

Local

Regional

Wetlands

Wet

Playas

Fresh Lakes

Springs

& Seeps Elevation / Effective-Moisture Regime

Riparian (streams)

HUMAN SOCIAL SYSTEMS

Societal values and institutional 

mandates; socioeconomic, demographic, 

and land-use patterns; quality of life

ATMOSPHERIC SYSTEM

Precipitation, temperature, and 

wind regimes; air quality, CO2

concentrations

DRY ECOSYSTEMS

Biotic functional groups, 

disturbance regimes, 

soil quality, habitat

WET ECOSYSTEMS

Biotic functional groups, 

flow / hydrologic regimes,

water quality, habitat
14 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Ecosystems of the Great Basin can be described 

effectively by the interactions between climate and geology, 

which creates a template of water availability for biota. 

The framework model describes the fundamental division 

of ecosystems based on the fate of climatic resource inputs 

(precipitation) as runoff and recharge (wet systems) or as 

infiltrated soil moisture (dry systems). Similar partitioning 

of water affects surface sediment fluxes, and thus surface 

stability. The model therefore identifies the amount, 

persistence, and state (saturated versus unsaturated) of water 

as a basic structuring driver for Great Basin ecosystems. The 

ecosystems structured on a broad scale by water are modified 

in many ways by climatic, orographic, pedeologic, human, and 

biotic factors that combine with water to control the flow of 

energy and resources in Great Basin ecosystems.

Within each of these “wet system” and “dry system” 

divisions, a range of amount and quality of water, including 

the timing of when it is available, serve to subdivide them into 

finer categories. We describe the system models in this section 

and the critical subsystem models in Chapters 3 and 4. A few 

submodels are developed more fully to illustrate how the 

models can be used to develop monitoring goals. Remaining 

subsystem models will be developed in the future.

Figure 2.2. Sketch of the atmosphere system, depicting major components and processes, and some of the major changes 

in the atmospheric system that drive climate variability and change.

Atmosphere-ocean coupling

Wind stress

Heat

exchange GREAT BASIN

Westerlies

air flow

Orographic precipitation

effects at landscape scale

Evaporation

Evaporation, 

transpiration

Changes in N2, O2, CO2, O3, etc

Changes in airborne pathogens, 

harmful chemicals

Changes in land use: 

vegetation, albedo

Changes in solar radiation

PACIFIC OCEAN

ATMOSPHERE

Incoming solar

radiation

Ocean

circulation

NORTH AMERICA

Changed particulate load

Atmospheric System Model

By D.M. Miller and M.E. Miller

Atmospheric System

The atmospheric system drives weather, whose longterm behavior is described as climate, and it is the system 

that conducts most mass and energy, including pollution, to 

and from the Great Basin (fig. 2.2). The atmospheric system 

therefore is a fundamental driver for the ecosystems of the 

Great Basin, but it is also highly dynamic at all temporal and 

spatial scales, making prediction (forecasting) a challenge. 

The atmosphere receives solar radiation (insolation), a process 

which is mediated by reflective aerosols and absorbent trace 

gases before reaching Earth’s surface. It also receives water 

vapor from evaporation at the surface of oceans and the land, 

where heat exchange influences the vertical temperature 

gradient in the atmosphere (Bradley, 1985; Monin and 

Shishkov, 2000). Heat trapped by trace gases further modifies 

the temperature gradient. Although the atmosphere has low 

heat capacity, it couples with water bodies of much higher 

heat capacity, resulting in atmospheric energy being driven 

primarily by oceans and their circulation patterns. Interactions 
Chapter 2: Framework and System Models 15

between the atmosphere and land include evaporation, 

reflected radiation, precipitation, wind, and heat exchange; 

albedo, plant cover and soil moisture are each important 

factors that interact with atmospheric systems. 

The climate of the Earth as a whole depends on factors 

that influence the radiation balance, such as atmospheric 

composition, solar radiation, and volcanic eruptions. 

Insolation varies with orbital mechanics of many periods, from 

the familiar daily and annual cycles to millennial and longer 

periods. Because insolation is greater at the tropics than the 

poles, latitudinal zones exist within the atmosphere. Vertical 

zones, defined by temperature, moisture, trace gases, and 

dynamic properties, also exist. The atmosphere has low inertia, 

so it quickly responds to changes in ocean temperature. It also 

stirs the near-surface ocean and deposits evaporated water as 

rain and snow on land. 

A number of trace gases, such as CO2, methane (CH4), 

nitrous oxide (N2O), ozone (O3), and chlorofluorocarbons, 

absorb and emit infrared radiation. These so-called greenhouse 

gases, along with water vapor, play an essential role in the 

Earth’s energy budget. Because these greenhouse gases absorb 

the infrared radiation emitted by the Earth and emit infrared 

radiation upward and downward, they tend to raise the 

temperature near the Earth’s surface. 

Components of the atmospheric system described in 

figure 2.2 and in above paragraphs are linked, and feedback 

among the components can dampen or amplify perturbations 

(that is, negative or positive feedbacks). Increased CO2 and 

other trace gases induce a positive feedback by increasing 

absorption of terrestrial radiation, which increases atmosphere 

temperature. Increasing temperature in turn increases release 

of CO2 by increasing ocean water temperature, creating 

positive feedback sometimes referred to as the “runaway 

greenhouse effect.” Oceans can dampen perturbations because 

of their enormous heat capacity. The energy balance in the 

atmosphere results from a complex interplay of insolation 

(its reflection by clouds and water, ice, and land surfaces; its 

absorption by gases, dust, water vapor, and Earth’s surface) 

and radiated heat from the Earth and its absorption by water 

vapor and gases. The complexity provides many opportunities 

for non-linear feedback processes, which makes it difficult to 

simulate atmospheric condition.

Climate Patterns in the Great Basin

Desert conditions prevail across the Great Basin because 

the region lies in a rainshadow created by the Sierra Nevada 

and the Cascade Range of California and Oregon. As air 

masses leaving the coast meet the mountain ranges they 

rise and cool, causing atmospheric moisture to condense 

and precipitate (fig. 2.2). East of the mountains, moisturedeficient air masses descend and warm. The rain and snow 

that precipitates on the Sierra and Cascades partly enters 

watersheds that drain into the Great Basin; the Truckee, 

Walker, and Owens Rivers are examples. Valley bottoms of the 

Great Basin receive as little as 100 mm of annual precipitation 

on average, whereas a few of the tallest mountains receive 

more than 1,000 mm.

Climate is influenced at the landscape and local scales 

by topography. The rainshadow created by Sierra Nevada and 

Cascade Range, in combination with other regional factors, 

creates a moisture gradient with drier conditions prevailing in 

the western part of the Great Basin grading toward somewhat 

greater total annual precipitation to the east. To the west, 

precipitation mostly results from regional winter storms 

originating over the North Pacific Ocean (fig. 2.3). Toward the 

east, there is increasing likelihood of summer precipitation 

resulting from localized convective storms originating in 

subtropical seas (fig. 2.3). During winter, several gradients 

related to freezing temperatures also are strong determinants 

of ecosystem condition. In general, winter temperatures 

decrease with increasing elevation and increasing latitude; 

average temperature decreases about 6 oC for every 1,000 

m increase in elevation (Rickleffs, 1990). Thus, effective 

moisture varies with elevation, producing patterns of plant 

distributions that were described in a conceptual model more 

than 100 years ago (Merriam, 1890). The result is a regional 

mosaic of temperature, precipitation, and seasonality of 

precipitation that drives plant community patterns (vegetation 

zones). 

Temporal variability in precipitation is attributable to 

at least three different factors. First among these is random 

fluctuation (Baldwin, 2003). Random, interannual variability 

in precipitation tends to increase with decreasing mean annual 

precipitation; arid environments typically have the greatest 

relative degree of variability (Noy-Meir, 1973; Ehleringer and 

others, 1999). A second source of precipitation variability is 

the El Niño – Southern Oscillation (ENSO) phenomenon that 

is driven by variations in sea-surface temperatures (SSTs) in 

the eastern tropical Pacific Ocean (Cayan and others, 1999). 

ENSO influences the latitudinal position of winter storm tracks 

across western North America; thus, ENSO effects on winter 

precipitation in the Great Basin tend to vary latitudinally 

(Baldwin, 2003). The warm ENSO phase (El Niño) tends to 

result in relatively warm, dry winters in the northern Great 

Basin and relatively wet winters in the southern Great Basin. 

The opposite pattern occurs during the cold ENSO phase (La 

Nina), although ENSO effects in the Great Basin generally are 

much weaker than in the Pacific Northwest and the Southwest 

(Baldwin, 2003). There is some evidence that warm-season 

(April-October) precipitation is above average in the Great 

Basin during El Niño episodes (Ropelewski and Halpert, 

1986). ENSO periodicity ranges from 2 to 7 years (Baldwin, 

2003). The third source of variability operates over decadalscale time periods, creating spatial and temporal patterns in 

precipitation across the conterminous United States related to 

phenomena known as the Pacific Decadal Oscillation (PDO) 

and the Atlantic Multidecadal Oscillation (AMO; Mantua 

and Hare, 2002; McCabe and others, 2004). The AMO is 
16 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig02-03

Reno

Salt Lake

City

Bend

Boise

Pocatello

Carson

City

Las Vegas

Bishop

Sacramento

Susanville

Klamath Falls

Ely

Elko

Tonopah

Winnemucca

Twin Falls

Ontario

Walker RWalker R

Pyramid

Lake

Truckee RTruckee R

Humboldt River

Snake RiverSnake River

Great

Salt

Lake

Owens R

Lake

Tahoe

PACIFIC

OCEAN

PACIFIC

OCEAN

Colorado Colorado River

OREGON

CALIFORNIA

NEVADA

UTAH

ARIZONA

WYOMING

IDAHO

Colu

MONTANA mbia Plateau

Columbia Plateau

Blue MountainsBlue Mountains

Snake River PlainSnake River Plain

Colorado Plateaus Colorado Plateaus

Wasatch Range Wasatch Range

Wyoming Bas ni Wyoming Bas ni

RO

C

KY

M

O

U

N

T

A

NI S

RO

C

KY

M

O

U

N

T

A

NI S

Mojave Desert ojave Desert

Uinta Mountains Uinta Mountains

CAS

CAD

E

RAN

G

E

CAS

CAD

E

RAN

G

E

Owyhee

Plateau

Steens

Mountains

Bonneville

Salt

Flats

Great

Basin

NP

Meadow Valley Wash

Death Valley

Northern Basin and Range

Central Basin and Range

Fish Lake

Valley

Ash

Meadows

SIERRA

NEVADA

SIERRA

NEVADA

GREAT BASIN

110°

112°

112°

114°

114°

118°

118°

120°

120°

122°

122°

116°

116°

44° 44°

42° 42°

40° 40°

38° 38°

36° 36°

0 50 100 150 200 MILES

0 50 100 150 200 KILOMETERS

Washington

Oregon

California

Nevada

Arizona

Utah

Colorado

Idaho

Montana

PACIFIC

OCEAN

CANADA

MEXICO

GBILM

EXPLANATION

Great Basin Integrated Landscape Monitoring 

Project (GBILM) Area-of-Interest

Winter flow of northern 

frontal storms

Winter flow of southern 

frontal storms

Summer flow of 

convective storms

Figure 2.3. Major weather patterns of the Great Basin, showing the distinction between winter storms derived from the Pacific 

Northwest and those from the southwest, and the locus of enhanced summer convective storm precipitation in the eastern Great Basin.
Chapter 2: Framework and System Models 17

an index of SST variations over the North Atlantic Ocean, 

whereas the PDO reflects SST variations over the North 

Pacific Ocean (Mantua and Hare, 2002; McCabe and others, 

2004). The PDO and AMO are quasiperiodic and may be 

caused by internal variations in oceanic circulation patterns 

and associated patterns of heat transport (McCabe and others, 

2004). In their analyses of 20th-century data, McCabe and 

others (2004) determined that 52 percent of the spatial and 

temporal variance in multidecadal drought frequency across 

the conterminous United States was attributable to variations 

in these two SST indexes.

In addition, closed basins such as the Basin and Range 

physiographic province cause temperature inversions. During 

nighttime, cold air descends from the surrounding mountains 

and accumulates in valleys, creating an atmospheric inversion 

of cold air under warmer air. As a result, nighttime low 

temperatures commonly increase with increasing elevation 

above valleys, then decrease toward the tops of mountain 

ranges. This temperature inversion can affect the elevational 

distribution of plants, but may disappear toward the northern 

Great Basin due to strong winter storms that mix the air more 

thoroughly and disrupt the inversions (Grayson, 1993).

Atmosphere dynamics also control patterns for air 

quality. Regional storm and air flow from coastal areas 

partition much of the pollution, haze, and particulate matter 

from central California, Reno, and Salt Lake City into patterns 

of wet and dry deposition, reduced visibility, and pollutants 

that can be monitored on the regional scale. Local variations 

in these air quality indexes must be monitored with local 

topography and atmosphere dynamics in mind.

Climate Change and Forecasts

Climate and weather vary with time scale, for example 

from changing wind direction in minutes, brief intense storms 

in hours, to wet winters, to multi-year drought, to multi-decade 

wet periods, and Little Ice Age cool periods. This climatic 

variability creates a complex framework for understanding 

past, current, and future climate-dependent features in the 

Great Basin, such as plant viability, plant-animal interactions, 

soil moisture availability, groundwater levels, and persistence 

of ephemeral and perennial streams. Additionally, short- and 

long-term human effects of climate change are superimposed 

on the background of natural climate variability. Examples 

include heat islands in and near cities, insulating effects 

of increased CO2 and other gases, and decreased solar 

radiation by haze. We follow the United Nations Framework 

Convention on Climate Change by defining climate change as: 

“a change of climate which is attributed directly 

or indirectly to human activity that alters the 

composition of the global atmosphere and which is 

in addition to natural climate variability observed 

over comparable time periods.”

 “Climate change” thus is attributable to human 

activities altering the atmospheric composition, and “climate 

variability” is attributable to natural causes. Climate 

variability refers to variations in the mean state and other 

statistics (such as standard deviations, the occurrence of 

extremes, etc.) of the climate on all temporal and spatial scales 

beyond that of individual weather events (fig. 2.4). Isolating 

the effects of climate change from climate variability is an 

essential, but daunting, requirement for managing Great 

Basin ecosystems. In addition to climate variability and 

change, singular events such as volcanic eruptions can cause 

short-term cooling by adding particulates and gases to the 

atmosphere, which reflect solar radiation.

Variability and change in climate have effects that we 

can measure locally, and these effects multiply and combine 

in complex patterns that potentially affect entire populations, 

species, and ecosystems at the regional level. Great Basin 

plant and animal communities can provide useful insight into 

long-term variations in climate variability. Plants in these 

communities are adapted to the short-term variability in 

climate but community composition is, in part, driven by longterm changes. Historical ecology is a particularly important 

approach to understanding climate variability to which plant 

communities respond (Swetnam and others, 1999) over time 

scales of centuries to a few millennia. Climate change has 

potential to drive many ecosystem processes outside the 

reference range of variability and Great Basin biota can serve 

as indicators for such change.

The net effect of human-caused climate change has 

become quite clear: global warming at an unprecedented 

rate (Giorgi and others, 2001). Many climate models 

predict increased temperatures and drier conditions for 

the Southwestern United States, but the various modeling 

approaches yield some variation in results. Three categories 

of models are used: analogs with past conditions, processbased models of climatic conditions with variable inputs 

of greenhouse gases, and models of the effects of land-use 

change.

Studies that are based on past analogs and on regional 

climate models using increased atmospheric CO2 predict that 

dry conditions will prevail during the next couple of decades. 

Some predictions stem from observations that the PDO 

recently appeared to change phase (see http://topex-www.jpl.

nasa.gov/science/pdo.html). The previous similar phase of the 

PDO was accompanied by prolonged dry conditions in the 

Southwest during the middle 20th century. By extrapolation, 

some climatologists predict future drought in the Southwest 

(Swetnam and Betancourt, 1998; Cole and others, 2002). 

Frequency of flooding, particularly in larger river systems, 

may decrease, and eolian activity in the Southwest may 

increase (Schmidt and Webb, 2001). Dynamic models of 

future climate that simulate physical oceanic and atmospheric 

systems can link global models with regional climate models 

to better address topographic complexity of areas such as 

the Great Basin. Most of these studies evaluated the effect of 

increased CO2 in the atmosphere, and generally predicted that 
18 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

dry conditions will prevail. These models are calibrated by 

running “hindcasts” to evaluate how well they simulate past 

climate changes and by comparing them among themselves. 

The hindcasts tend to show good fidelity for temperature 

predictions and less fidelity for precipitation predictions. 

The models provide insight into possible future changes in 

climate driven by greenhouse gases. A summary of the results 

indicated by both kinds of models includes:

• More intense, more frequent, and longer heat waves 

(Meehl and Tebaldi, 2004).

• Increased temperature of stream water (Thompson 

and others, 1998).

• Increased temperature and decreased precipitation 

in all seasons (Giorgi and others, 1998b; Thompson 

and others, 1998).

• Some simulations predicted increased temperature 

and precipitation (http://www.gcrio.org/

NationalAssessment/index.htm, accessed June 22, 

2009).

• Winter warming, reduced snowpack, more extreme 

winter storms (Leung and others, 2004).

• Winter warming, no change in precipitation, reduced 

snowpack (Snyder and Sloan, 2005).

• Increased storm intensity (Groisman and others, 

2004).

Another approach for examining future climate is to 

model the effects of land cover change, such as expanded 

woodlands and decreased urban vegetation cover. One study 

predicted increased temperature due to modeled changes in 

land cover (Goddard Space Flight Center, 2004). 

Although future climate trends are imperfectly predicted 

because climate systems are exceedingly complex and future 

scenarios are speculative, the model studies tend to agree 

on trends during the future 50 years toward climate that is 

warmer and probably drier, accompanied by increased storm 

intensity, increased precipitation variability, less snowpack, 

and earlier spring melting and runoff. The implications for 

ecological systems are considerable, underscoring the need for 

monitoring meteorological conditions as one way to evaluate 

and anticipate changes in the ecosystem.

Ecosystem Effects

Climate variability is the primary natural factor driving 

ecosystem patterns in the Great Basin (fig. 2.1). Precipitation 

regime is of particular significance because of the importance 

of precipitation inputs for driving water-limited ecological 

processes such as primary production, nutrient cycling, 

and plant reproduction (Noy-Meir, 1973; Comstock and 

Ehleringer, 1992; Whitford, 2002). Precipitation seasonality 

Figure 2.4. Representation of the concepts of variability and mean climate conditions. Climate forecasting 

models indicate that increases in mean temperature and increases in variability of many climate parameters 

are likely to occur as a result of anthropogenic alteration of the atmosphere. (Adapted from Bradley, 1985.)

tac09-0397_fig02-04

Increasing variability, stable mean

Increasing mean, stable variability
Chapter 2: Framework and System Models 19

(that is, timing in relation to the annual cycle of potential 

evapotranspiration) and form (that is, snow versus rain) are 

key attributes because they strongly control the partitioning of 

precipitation among various compartments of the hydrologic 

budget – evaporation, transpiration, runoff, recharge, and 

soil-water storage. Because of their effects on hydrologic 

partitioning, precipitation seasonality and form are major 

determinants of ecosystem dominance by different vegetative 

life forms and functional groups (Comstock and Ehleringer, 

1992). The prevalence of cool-season precipitation results 

in effective soil-moisture recharge and relatively reliable 

growing conditions during spring (Caldwell, 1985; Comstock 

and Ehleringer, 1992; West and Young, 2000). 

Despite being remarkably adapted to the harsh and 

variable climate conditions of the Great Basin, biota 

nevertheless are limited by temperature extremes and 

precipitation timing (that is, seasonality and lengths of 

drought). Changes in climate created by anthropogenic 

increases in CO2, particulates, aerosols, and other pollution 

have the potential to drive many ecosystem processes outside 

the reference range of variability (the range of variation 

during a reference period of consideration; see discussion in 

Chapter 1). If climatic conditions persist outside the reference 

range, novel ecosystem trajectories can be expected.

Plant and animal population distributions reflect recent 

climate, dispersal patterns, and a complex integration of past 

climate changes and disturbances. As a result, time scales 

of decades to millennia of past conditions are relevant to 

addressing modern threats to biota.

Summary Points

The relationship between climate, topography, and Great 

Basin landscape configuration is relatively well understood 

within the context of historic ranges of variation. However, 

many aspects of climatic effects on Great Basin systems 

are unknown despite a growing understanding of regional 

climate-change patterns. Global climate models generally are 

too coarse for local or regional analysis and ‘downscaling’ 

techniques (for example, Murphy, 1999) to regionalize climate 

models are partially limited by the scarcity of climate stations 

in the Great Basin. Data for many climate stations is of 

short duration, limiting knowledge over long climate cycles. 

Additional weather stations would enable more accurate 

regional and local models and, in turn, improve regional 

models. Establishing relations between local climate and soil 

moisture-runoff-recharge balances would significantly advance 

modeling capabilities for Great Basin ecosystems.

Human-Social System Model

By Alicia Torregrosa

Introduction

Humans (Homo sapiens sapiens) comprise a 

complex agent of change in the Great Basin (fig. 2.5) over 

multiple spatial and temporal scales. Unlike most other 

dominant ecosystem species, humans have extensive social 

constructions that use symbolic language, abstract thinking, 

and cultural inheritance. These constructs give rise to 

things such as money, property boundaries, institutions, 

and conceptual paradigms that in turn produce enduring 

physical infrastructure such as fences, irrigation canals, farms, 

factories, cities, roads, power grids, and telecommunication 

networks.

Human-induced landscape change is a sociocultural 

phenomenon (fig. 2.6). The way we think about the land 

governs our interactions with our environment and is 

shaped by our cultural, socioeconomic, and political 

systems. Evolving conceptual paradigms, social agreements, 

institutions, and regulations abet and constrain land ownership 

and land uses. For example, a social construct of the early 

20th century was that fire destroys forests, which generated 

an institutional policy of fire suppression. The ecosystem 

response was a shift in vegetation composition and biomass 

which in many cases led later to uncontrollable fires. As 

managers and scientists investigated the response, a new 

understanding of the relationship between fires and forests led 

to a paradigm shift that fire is a part of healthy ecosystems. 

This new understanding has translated into management 

activities that include prescribed burns, thinning of trees 

within forests to mimic the effects of fire, and legislation such 

as the 2003 Healthy Forests Restoration Act (fig. 2.7).

From a biophysical perspective, the niche space occupied 

by humans is unusual compared to other species. Individual 

humans have the ability to harness the technological capacity 

built by extensive social systems and alter any ecological 

niche of the Great Basin. The importance of human impacts 

to the reproductive success of other species led Alberti and 

others (2003) to propose a reconceptualization of niche theory 

that explicitly integrates human effects into a species’ realized 

niche (fig. 2.8). 
20 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

 The human impact on the realized niche of species in 

the Great Basin is a function of the density of the human 

population and the intensity of anthropogenic impact from 

activities, such as agriculture, irrigation, infrastructure 

construction, and resource extraction. In addition to changing 

the available niche space for locally occurring species, 

anthropogenic introductions of species from regions outside 

the Great Basin has resulted in the emergence of new 

combinations of species. These novel ecosystems (Hobbs 

and others, 2006) have no known analogs. Understanding 

the persistence and dynamics of these novel ecosystems is 

a challenge and deciding how to manage them is even more 

challenging. 

Human Presence in the Great Basin

People have lived in the Great Basin for millennia but 

what effect have they had on ecosystems? Evidence exists 

that aboriginal populations made extensive use of fire to 

manipulate landscape conditions for resource management 

(Miller and others, 1995; Vale, 2002; Anderson, 2005). The 

statistical analysis of lightning fires by Kay (2007) indicates 

that there were far too few natural incendiary events to 

account for documented fire frequencies. This information 

is relevant for understanding dynamics between sage brush 

steppe and juniper woodlands especially in the context of 

restoration efforts. 

tac09-0397_fig02-05

EARTH

ENERGY

ATMOSPHERE

WET DRY

IMPACT, MANAGEMENT, RESTORATION

ECOSYSTEM GOODS AND SERVICES

LAND COVER

Human System

BIOTA

Co-evolving 

Co-adapted

Self-organizing

INFRASTRUCTURE

Dwellings

Technology

Work Places

Transportation

Communication

Defense

SOCIAL CONSTRUCTIONS

Social, political,

 institutional intellectual

Figure 2.5. Human Systems model. The box on the left represents the Great Basin system at the framework model level (fig. 2.1), 

conceptualized by the team as an open system driven by solar energy and structured through Earth processes with four main 

conceptual components: atmosphere, wet and dry systems, and the human system. Homo sapiens sapiens is one of many biological 

species in the biota of the Great Basin, a system of biogeophysical interactions. An expanded view of the human social system is 

enclosed by the dashed line. Ecosystems goods and services (top block arrow) stem from social constructions that assign value to the 

natural capital of the Great Basin used by the human system including minerals, soil fertility, water, water purification, and biomass. 

Changes on the landscape are driven by social constructions (top oval) and its resultant anthropogenic activities such as the creation 

of infrastructure (box on the right of diagram), resource management and restoration activities (bottom block arrow). Only some landcover change is a direct result of the human system; therefore, the dashed line does not cover the entire oval on the bottom of the figure 

representing landcover.
Chapter 2: Framework and System Models 21

Figure 2.6. Illustrations of landscape change. Human social 

constructions within culturally defined norms govern interactions 

with the environment, leading to common landscape modifying 

activities such as (A) agriculture, (B) livestock production, 

(C) irrigation, (D) urbanization, (E) oil and gas production, (F) 

recreational vehicle use, (G) defense training exercises, and (H) 

energy distribution. These activities can be mapped to quantify 

the human footprint on the landscape, shown in the third panel by 

major highways and utility corridors connecting urban centers. 

tac09-0397_fig02-06

A

B

C

G

H

D

E

F

SOCIAL

CONSTRUCTIONS

LANDSCAPE MODIFYING

ACTIVITIES

Values

Attitudes

Lifestyles

Affiliations

Visions

Goals

Knowledge

RESULTING HUMAN FOOTPRINT 

ON THE LANDSCAPE

0 100 200 MILES

0 100 200 KILOMETERS

Washington

Oregon

California

Nevada

Arizona

Utah

Wyoming Idaho

Montana

PACIFIC

OCEAN

CANADA

MEXICO

GBILM

EXPLANATION

GBILM with 50-kilometer buffer

Urban areas

Major roads

Powerlines

Great Basin Integrated Landscape 

Monitoring Project (GBILM) 

Area-of-Interest

Reno

Salt Lake

City

Bend

Las Vegas

Sacramento

Boise
22 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig02-07

EARTH

ENERGY

ATMOSPHERE

WET DRY

IMPACT, MANAGEMENT, RESTORATION

NEW POLICY

ECOSYSTEM GOODS AND SERVICES

Human System

BIOTA

Co-evolving 

Co-adapted

Self-organizing

INFRASTRUCTURE

Dwellings

Technology

Work Places

Transportation

Communication

Defense

SOCIAL CONSTRUCTIONS

Fire is Bad for Forests

LANDCOVER CHANGE

System responds

Uncontrollable fires

Institutional Policy  Stop Forest Fires

New understanding

 Paradigm Shift

T0+i+R

Time0

Timei

TimeR

LANDCOVER

SOCIAL CONSTRUCTIONS

Social, political,

 institutional intellectual

Figure 2.7. Social construction as a Great Basin ecosystem driver. An example of the linkage between social constructions and land 

cover (highlighted in the upper left box representing fig. 2.5) is the understanding of fire. The temporal dimension of this social model 

is especially important for forecasting landscape change in the Great Basin. Time0 (at the top of the left time arrow) represents the 

emergence of the social construction. Timei

 represents the time interval for (1) managers to implement the first social construction, 

(2) the ecosystem to respond, and (3) an understanding of the results of fire suppression. TimeR represents how long it takes for new 

understandings to effect change on the initial policy of forest suppression. Exploring cycles of paradigm shifts can lead to calculations 

of the total time required to change policy or social thinking (T0 + I + R) . This would provide insights on how to realistically calculate 

TimeR, which could potentially improve adaptive management efforts.
Chapter 2: Framework and System Models 23

tac09-0397_fig02-08

(Reproduced by permission, BioScience, December 2003, v. 53, no. 12, p. 1174, figure 5.)

A. Fundamental niche

Niche dimension 1 (e.g., temperature)

Niche dimension 2 

(e.g., suite of gradients 

indicative of standing 

water)

Species A

B. Realized niche (without people)

Niche dimension 2

Niche dimension 1

Species A

Species C Species B

C. Realized niche (with people)

Niche dimension 2

Niche dimension 1

Dense human 

population

Sparse human 

population

Species A

Species D

Species Species C

B

Figure 2.8. The fundamental niche of a species is n-dimensional, 

with each environmental gradient relevant to a species 

represented by one dimension (Hutchinson, 1957). (A) A twodimensional view for species A. (B) The Hutchinsonian realized 

niche is that part of the fundamental niche not preempted by 

competitors, shown here for three species in the absence of 

people. (C) A realized niche with human involvement, in which 

Species A expands to fill its fundamental niche in the presence 

of people. Species B has a restricted distribution because 

the human-subsidized species A out-competes it. Species C 

is intolerant of humans and is confined to a small part of its 

fundamental niche where people do not exist. Species D is 

imported by humans into the geographic niche space. 

Estimates of Native American populations in the Great 

Basin prior to the 18th century range from 26,000 (Kroeber, 

1937) to almost three times that number (Snipp, 1989). 

The current (2008) Great Basin population is estimated at 

4.5 million and population is expected to increase 50 percent 

in the next 10 to 30 years (Population Profile of the United 

States, accessed June 22, 2009, at http://www.census.gov/

population/www/pop-profile/natproj.html).

This massive population influx of the 20th century 

(fig. 2.9) was an outgrowth of two pivotal social constructions 

that strongly shaped land and water patterns in the Great 

Basin: the 1862 Homestead Act and the 1902 Reclamation 

Act. The Homestead Act framed modern American views of 

private and public property and continues to have a major 

impact on land management, land use, and urban planning. 

The Reclamation Act facilitated large irrigation and water 

reclamation projects and represented Congress’ rejection of 

John Wesley Powell’s recommendation to develop the arid 

lands of the West based on a local watershed stewardship 

model (Stegner, 1992). Water law is critical to the ecosystems 

of the Great Basin and the precedent-setting act of 1902 

continues to dictate the boundaries of water law (Worster, 

1985). A recent Supreme Court ruling (Hage versus United 

States, 2003) reaffirmed Congress’ intent for States to define 

water rights irrespective of greater public benefit. The 

extraction of water, accomplished through precedent-setting 

laws, for human needs including agricultural irrigation, is a 

significant anthropogenic driver within the Great Basin and 

can be seen as land-cover change at the landscape level 

(fig. 2.10). 

Historical events can be used as markers for the direction 

and timing associated with the anthropogenic drivers that 

result in ecosystem change. To better conceptualize these 

events, we developed timelines that relate to land use patterns 

and commodity production and water resources (fig. 2.11) 

with a focus on the Great Basin’s wet and dry systems. 

Although these timelines describe separate historical events, 

many are interrelated and cumulative. The historic ecological 

perspective can be important for assessing the cumulative 

impacts of these events over time as well as to help to shape 

the dialogue for restoration efforts. 

The extent to which human activity alters ecosystem 

function is not completely understood. For example, urban 

development alters ecosystem function by eliminating and 

altering habitats but what effect does exurban development 

have? Exurban expansion, characterized by large lots of 

5–40 acres with a single dwelling per lot, is positively 

correlated with habitat fragmentation, but the direct and 

indirect impact of this expansion on biological communities is 

still a matter of controversy (Hansen and others, 2005; Bock 

and others, 2008; Milder and others, 2008). 

Many anthropogenic impacts have a long temporal 

footprint, both physically and culturally. Roads and trails 

last a long time in the arid environments of the Great Basin, 

affecting drainage and erosion, encouraging off-road use, 

and facilitating development. Landscape alterations, such as 

riparian areas altered by livestock grazing, affect the additional 

ecosystem services that can be expected, which in turn impacts 

land values. A conceptual model that includes humans as an 

agent of change can better explore the effects of these changes 

on ecosystem sustainability. Models can generate exploratory 

scenarios of the future even in the absence of sufficient data 

for numerical computational approaches.
24 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Figure 2.9. Maps showing population change in the Great Basin from 1850 to 2050 by county or territory. The Great Basin study area is 

shown as a black boundary in each pane. In 1850, most of the Great Basin did not have statehood and comprised portions of the Oregon, 

Utah, and New Mexico territories. Some county boundaries changed between time periods. Population totals for the study area are: 

1850—42,374; 1900—333,867; 1950—275,000; 2000—3.6 million; 2008, 4.5 million. (Historical source data from the Minnesota Population 

Center, 2004. Recent population data from the U.S. Census Bureau, Population Division.)

EXPLANATION

Less than 1

1 to 2

3 to 10

11 to 100

Population by county, in 

persons per square 

kilometer (km2)

Greater than 100

Source: Yohe and others (2006). 

0 100

0 10 200 KILOMETERS

200 MILES

1850 1900

1950

2000 2050
Chapter 2: Framework and System Models

25

95

95

49

400

49

789

80

80

Winnemucca

0 5 10 15 20 MILES0 5 10 15 20 KILOMETERS

Winnemucca

Nevada EXPLANATION

Irrigated agriculture (circular patches of bright green fields)Dryland farms (light to dark brown squares)

Crisscrossing roads (larger roads are highlighted in yellow)Deep blue reservoir behind Rye Patch Dam (lower left)

Image courtesy of WikiMapia.com

Figure 2.10. Map showing footprints of anthropogenic drivers on the landscape. Aerial view (110 km wide) near Winnemucca, Nevada, shows many large round circles of irrigated agriculture, dryland farms with characteristic square angles, crisscrossing roads, and deep reservoir of water impounded behind Rye Patch Dam.
26 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig02-11

1845

1862

1868

1869

1872

1889

1890

1906

1914

1934

1951

1953

1986

1998

To

present

LAND USE AND COMMODITY TIMELINE

Virginia City silver mines

Fremont maps and names the Great Basin

Tribal Reservations established 1859-1939

U.S. Homestead Act of 1862

U.S. General Mining Act of 1872

White Pine tungsten mines

Transcontinental Railroad finished

Cattle decimated by winter kill

Sheep introduced to Great Basin

National Forests in Nevada

World War I

Taylor Grazing Act

Atomic bomb testing

Reese River uranium mining

Great Basin National Park

Southern Nevada Public Lands 

Management Act (SNPLMA)

SNPLMA Land auctions

SNPLMA Conservation activities

1822

1847

1840s

1859

1866

1870

1886

1885-

1890

1894

1902

1923

1935

1969

1973

1989

1990

1991

2000

2004

WATER USE TIMELINE

Stockmen drive cattle into Great Basin

1822-23 Droughts

First colonial farmers in GB (Mormon)

Virginia City silver mines

GB Census estimate 87,000

300,000 miners follow Humboldt River to fields

Transcontinental Railroad finished

Deseret Irrigation and Canal Company

1880-1890s Droughts

NV Senator Stewarts chairs irrigation committee

John Wesley Powell resigns USGS directorship

Cary Act grants states rights to sell irrigated land

Newland National Reclamation Act

Bureau of Reclamation instituted

1934 Drought

Hoover Dam completed

1953-55 Drought

National Environmental Policy Act

Endangered Species Act

SNWA files for White Pine water rights

Pyramid Lake - Paiute Shosone Water Rights Act

National Water-Quality Assessment Program

GB Census estimate 2,742,716

BARCASS legislated

Local and 

regional events

National events

Severe droughts

Figure 2.11. Diagrams showing timeline of events that shaped land-use patterns, commodity production, and water use in the Great 

Basin over the last two centuries. Most events are interwoven. For instance, the severe droughts of the 1880–1890s that led to the 

introduction of sheep and cheatgrass are pivotal events with increasing impacts on vegetation community structure a century later. 

Water related needs at the local and regional level resulted in national scale events that continue to affect Great Basin wet systems and 

water use (Lamm and McCarthy, 1982; Worster, 1985; United States, Western Water Policy Review Advisory Commission, 1998).
Chapter 2: Framework and System Models 27

Modeling Approach

There are several approaches for including human 

activities within ecosystem models. Early Urban-Long Term 

Ecological Research approaches modeled ecosystem processes 

without an explicit human social systems component, adding 

anthropogenic activities as modifiers to the flows or processes 

between major components (Grimm and Redman, 2004). 

This modifier approach is useful for studies that focus on 

biogeochemical flows or changes in the rates and sources of 

nutrients, water, pollution, and other materials (Grimm and 

others, 2004). An alternative approach is to separate human 

activities into a submodel within the modeling diagram 

(fig. 2.5). This approach is especially useful for applying a 

systems science approach to human activities, framing humans 

as a component of the biotic community interacting with other 

ecosystem components (Plotkin, 2003; Robbins, 2004), and 

for modeling social mechanisms that impact ecosystems such 

as institutional directives and paradigm shifts. The GBILM 

team advocates this latter approach because of the need to 

address scientifically and politically difficult issues that are 

more tractable if framed through explicit attention on human 

activities. 

Conceptualizing a human dimension to ecosystems by 

using a human systems approach also is useful for scaling 

between the spatial hierarchy of site → region → nation and 

the hierarchical parallel with human social units of individual 

→ group → institution. All these levels need to be considered 

if one accepts the premise that understanding regional scale 

processes must include an understanding of the next larger and 

next smaller hierarchical system levels (Allen and Starr, 1982; 

Giampietro, 2003).

Information exchange and collaboration is an important 

human activity rarely integrated into models of ecosystem 

management. Collaborative environmental problem solving is 

increasingly being incorporated into monitoring and adaptive 

management activities. Collaboration and communication can 

be measured as an indicator of social capacity and approached 

as a social driver for problem-solving and decision-making 

processes. The social structures that are built over time, 

such as networks, organizations, and institutions (important 

components of social capital), and the ecosystem impacting 

processes these structures mediate, are important elements for 

a model of human social system.

Social capacity is an element in several models such as 

the Sustainable Rangeland Roundtable (Hamilton and others, 

2003; Tanaka and others, 2003; Maczko and others, 2004). 

Recent examples of collaboration on Great Basin management 

issues include the Bureau of Land Management (BLM) Final 

Grazing Rule (http://edocket.access.gpo.gov/2006/pdf/06-

5788.pdf), which improved relations between BLM and permit 

or lease holders, and the U.S. Fish and Wildlife Service’s 

Protocol for Evaluating Conservation Effort (http://www.

fws.gov/endangered/pdfs/FR/PECE-final.pdf), an important 

driver for local involvement in sage grouse conservation. 

The challenge in these examples of social capacity is to 

conceptualize the links among the social constructions, 

management objectives, and ecosystem responses.

Summary Points

The social systems model seeks to link the biophysical 

environment and the human dimension guided by four 

principles: (1) humans are part of the Great Basin ecosystem; 

(2) anthropogenic activities result from social constructions—

which can be changed; (3) models should include only as 

much as is needed to understand the drivers and forecast 

landscape change; and (4) building upon existing research 

and knowledge best creates a model that is useful to the 

monitoring community. 

Unlike the “wet” and “dry” system models that have 

considerable pre-existing modeling material to draw on, social 

system research and modeling to forecast ecosystem change 

at the landscape level is in its infancy. High priority objectives 

for further model development would include:

• Define and expand on the social system components 

that link to ecosystem functioning and integrate 

these with the model.

• Geographically map social structures that are drivers 

for models.

• Develop an approach to incorporate processes acting 

at different spatial and temporal rates, extents, or 

domains into models.

• Explore how a better understanding of social 

processes could improve a monitoring framework 

that tracks ecosystem change, such as by tracking 

policy measures.

Distinguishing direct and indirect human impacts on the 

Great Basin landscape from those caused by other drivers 

is one of the greatest challenges, despite improved systems 

science models (Gunderson, 1999; Warfield, 2006). Progress 

is being made to integrate social system processes into global 

systems to generate climate change scenarios, plan sustainable 

agriculture, and conduct natural hazard vulnerability research 

(deGroot and others, 2003). Scaling these models down to 

the region still needs considerable work. Creating a model 

of ecosystem drivers in the Great Basin also will require 

addressing non-resolvable uncertainties (Ritchey, 2002) and 

“complex judgments about the level of abstraction at which to 

define the problem” (Buckingham Shum, 1997).

Models that can meet these challenges will help resource 

managers better understand the leverage points within the 

whole system and perhaps discover unsuspected links between 

social constructions and ecosystem functioning for improved 

decision making.
28 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Dry System Model 

By M.E. Miller and D.M. Miller

We define dryland ecosystems as those ecosystems 

that are not dependent on the availability of groundwater or 

surface water, in contrast with wetland, riparian, and aquatic 

ecosystems. As a communication tool and to guide the 

development of more detailed conceptual models, we have 

adopted a general model for dry ecosystems (fig. 2.12A) that 

is patterned after the dryland ecosystem model developed 

by Miller (2005). A premise of this model is that regional 

climatic and atmospheric conditions, biotic functional groups, 

disturbance regimes, and soil resources are key factors that 

interactively control ecosystem structure, function, and 

sustainability in relation to human use and other drivers of 

ecosystem change (Chapin and others, 1996). At the center of 

the model are soil (including biotic and abiotic components) 

and vegetation, which are tightly coupled through interactive 

effects on hydrologic (soil moisture) and biogeochemical 

(nutrient cycling) processes. Soil, vegetation, and landscape 

configuration (the spatial arrangement of vegetation patches 

or ecosystem types) influence habitat quality for wildlife 

(vertebrates and invertebrates), and wildlife in turn affect 

soil and vegetation in many ways (fig. 2.12A), including 

seed dispersal, herbivory, pollination, soil disturbance, and 

excavation. Elevation and soil-geomorphic setting (including 

topographic position and soil-profile characteristics) provide 

the physical template for landscape-level spatial variations in 

ecosystem structure and function through effects on soil water 

and nutrient regimes experienced by soil biota and vegetation 

(Monger and Bestelmeyer, 2006), as well as by temperature 

controls.

Climate and the Physical Template

The extreme topographic relief of Great Basin landscapes 

creates diverse ecosystem patterns and processes due to 

greater precipitation, lower temperatures, and lower potential 

evapotranspiration rates at high elevations compared to low 

elevations. These elevation-dependent factors are responsible 

for the predictable sequence of dryland ecosystems that is 

repeated along elevational-moisture gradients from lowland 

environments to tops of mountains. Along this gradient, 

major types of upland ecosystems include salt desert scrub, 

sagebrush steppe, pinyon-juniper woodlands, aspen and 

conifer forests, and alpine meadows and tundra (figs. 2.12B, 

2.13). Within each of these systems, climate (for example, 

interannual and decadal variations in precipitation and 

temperature) and disturbance (for example, fire and insect 

outbreaks) are major natural drivers of change and temporal 

variability. The model reflects the fact that vegetation structure 

and landscape configuration affect and are affected by most 

types of natural disturbances.

Abiotic factors including regional climate, elevation, and 

soil-geomorphic setting determine the potential distribution, 

biotic structure, and dynamics of terrestrial ecosystems 

through their combined effects on environmental conditions 

and resources (Jenny, 1980; Stephenson, 1990; Monger 

and Bestelmeyer, 2006; fig. 2.12). Climate encompasses a 

dynamic suite of variables that drives temporal patterns of 

ecosystem change and variability (Bonan, 2002; see Chapter 

2, section “Atmospheric System Model” and fig. 2.2). In 

contrast, the physical template is a relatively static (or 

inherent) determinant of potential ecosystem and landscape 

structure and thus provides a useful spatial framework for 

ecosystem assessment, monitoring, and management (Rowe, 

1997; Herrick and others, 2005; Pellant and Lysne, 2005; 

Herrick and others, 2006). The concept of the physical 

template encompasses elevation, topography, and soil physical 

and mineralogical properties controlled by parent material, 

geomorphic processes, and pedogenic processes (Monger 

and Bestelmeyer, 2006). Together, these abiotic factors exert 

strong control over biogeochemical and hydrologic processes 

that structure ecosystems through effects on soil water and 

nutrient regimes experienced by soil biota and vegetation. As 

determinants of potential ecosystem structure and landscape 

configuration, climate and the physical template are the basis 

for the ecological site land-type classification system of the 

U.S. Department of Agriculture (USDA) Natural Resource 

Conservation Service (NRCS; accessed June 22, 2009, at 

http://esis.sc.egov.usda.gov/) that serves as a powerful method 

for describing the landscape.

Soil Resources, Functions, and Quality

Soils (including soil organic matter and biota) are 

responsible for the regulation of hydrologic processes and 

the cycling of mineral nutrients in dryland ecosystems. As 

the primary medium for storage and delivery of water and 

nutrients, soils are essential for sustaining the existence and 

productivity of plant and animal populations. The capacity 

of a specific kind of soil to perform these functions is 

described by the concept of soil quality (Karlen and others, 

1997; Herrick and others, 2002; Norfleet and others, 2003). 

Soil functioning and soil quality are determined in part by 

inherent soil properties such as texture, depth, mineralogy, 

and profile development that are determined by parent 
Chapter 2: Framework and System Models 29

Figure 2.12. Diagrams showing general conceptual model of dry ecosystems. Panel (A) illustrates key structural 

components (rectangles), major drivers of ecosystem change and temporal variability (ovals), and functional 

relationships (arrows) (adapted from Miller, 2005). Structural components and drivers are ecological factors that 

are relatively dynamic at the centennial time scale, thus representing potential foci for long-term monitoring. 

Elevation and soil-geomorphic setting provide the underlying physical template that determines the potential 

structure, functioning, and spatial configuration of dry ecosystems in the Great Basin. Panel (B) examines the 

elevation-vegetation relationship, illustrating the typical zonation of dry ecosystems in the Great Basin along 

gradients of elevation and effective-moisture regimes.

tac09-0397_fig02-12

REGIONAL CLIMATIC &

ATMOSPHERIC CONDITIONS

WILDLIFE

HABITAT

QUALITY

LANDSCAPE

CONFIGURATION

ELEVATION AND

SOIL-GEOMORPHIC

SETTING

NATURAL

DISTURBANCE

REGIMES

ELEVATION

Alpine

Coniferous

forests

Coniferous

woodlands

Sagesteppe

Dry

playas

Elevation/Effective-moisture regime

Aspen

Salt desert

scrub

VEGETATION

Biogeochemical

and hydrologic

processes

SOIL

VEGETATION

Biogeochemical

and hydrologic

processes

SOIL

A.

B.
30 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig02-13

Pinyon-Juniper

Pinyon-Juniper

Shrub-steppe

Timberline

Bristlecone Pine

Spruce-Fir

LATITUDE

Low Elevation Scrub Coniferous

Woodland

Sub-alpine

Forest

EFFECTIVE MOISTURE

ELEVATION

EFFECTIVE MOISTURE

South North

Alpine

tundra

Salt Desert Scrub

Ponderosa Pine

G. B. Sagebrush

Dry Playa

Spruce-Fir

Salt Desert Scrub

Alpine tundra

Blackbrush Scrub

Sagebrush-steppe

Figure 2.13. Diagram showing vegetation zones in the Great Basin. As latitude increases, vegetation zones descend in elevation due to 

decreasing temperature and increasing available moisture. Total vegetative cover is generally greater northward and upward, except at 

very high elevations.

materials, geomorphic processes, and soil formation (elements 

of the physical template, described above). For example, 

due to differences in geologic parent materials and past 

patterns of landscape evolution, Great Basin soils generally 

are characterized by finer soil texture and higher inherent 

fertility than soils of adjoining areas such as the Colorado 

Plateau (Comstock and Ehleringer, 1992). These differences 

in inherent soil properties have important implications for 

soil functioning and ecosystem dynamics, and may contribute 

to the high susceptibility of Great Basin ecosystems to 

invasion by exotic annual grasses such as Cheatgrass (Bromus 

tectorum) and Medusahead (Taeniatherum caput-medusae) 

(Blank and Sforza, 2007; Norton and others, 2007). Although 

inherent soil properties are considered to be relatively static, 

soil texture and depth can change and influence ecosystem 

structure and dynamics over relatively short time scales in 

response to land uses and management activities that reduce 

erosion resistance (for example, Neff and others, 2005). 

Soil functioning and soil quality also are determined 

by dynamic soil properties that respond to land use, natural 

disturbances, and climatic fluctuations. For purposes of 

ecosystem management and monitoring, dynamic soil 

properties are particularly important because they represent 

a key pathway by which land use and management affect 

the condition of rangeland ecosystems (Seybold and others, 

1999; Herrick, 2000; Herrick and others, 2002). Dynamic 

soil properties that are particularly important for sustaining 

hydrologic processes, nutrient cycling, plant growth, and 

erosion resistance include organic matter content, aggregate 

stability, surface roughness, and structure.

Vegetation Resources and Functions

Vascular plants perform important functional roles in 

dryland ecosystems (fig. 2.12). In addition to conducting 

photosynthesis, aboveground structures of plants protect soils 

from erosive raindrops, obstruct erosive wind and overland 

water flow, and thus enhance the capture and retention of 

soil resources. Litter from plants further reduces the erosive 

impacts of rainfall on soil surfaces and provides inputs to 

soil organic matter for soil stabilization and nutrient cycling. 

Roots stabilize soils, are conduits for resource acquisition 

and redistribution, and provide organic-matter inputs to soil 

food webs. Vegetation also provides fuel for fire, as well 
Chapter 2: Framework and System Models 31

as resources and habitat structure for below-ground and 

above-ground organisms ranging from fungi and bacteria to 

birds and large mammals (Wardle, 2002; Whitford, 2002). 

Carbon storage and the mediation of earth-atmosphere energy 

and water balances are additional vegetation functions that 

are increasingly emphasized by researchers investigating 

processes of global climate change (Breshears and Allen, 

2002; Asner and others, 2003). Plants and litter also 

intercept solar radiation and precipitation, thereby altering 

microclimatic conditions, mediating spatial and temporal 

patterns of soil water content and temperature (Breshears and 

others, 1997), and strongly affecting soil-resource conditions 

experienced by other organisms. Interspecific competition 

often is emphasized as an important factor shaping the 

composition and structure of plant communities (Goldberg, 

1990). But facilitation also can be an important process in 

dryland ecosystems due to ameliorating effects of overstory 

plants on environmental conditions or herbivory experienced 

by understory plants (Callaway, 1995; Archer and Bowman, 

2002; Brooker and others, 2008).

Wildlife and Habitat Quality

Vertebrates and invertebrates perform numerous 

functions in Great Basin dryland ecosystems. Activities related 

to granivory and herbivory are among those that have the 

greatest ecosystem-level consequences in dryland ecosystems 

because of their many effects on vegetation structure and 

soil processes. Through selective harvesting, consumption, 

and dispersal by caching and defecation, granivores can 

have considerable effects on the abundance, composition, 

and spatial distribution of the seed bank (Whitford, 2002). 

Over time, these seed-bank effects can be reflected in the 

composition and spatial structure of plant communities. 

For example, seed caching by birds and rodents is the 

primary mechanism of seed dispersal for pinyon pine and 

thus contributes to the dynamics and distributional patterns 

of pinyon populations in the Great Basin and elsewhere 

(Chambers and others, 1999; Chambers, 2001). Seed 

ingestion and defecation by frugivorous birds and mammals 

are important for the dynamics and distributional patterns of 

juniper populations (Chambers and others, 1999). 

Large herbivores can affect individual plants directly and 

indirectly through various mechanisms. Direct impacts include 

altered physiological function and morphology attributable to 

defoliation and trampling (Briske, 1991; Briske and Richards, 

1994). Defoliation and trampling by large herbivores may 

indirectly influence plant performance as a consequence 

of altered microenvironmental conditions, soil properties 

(Thurow, 1991), mycorrhizal relations (Bethlenfalvay 

and Dakessian, 1984), competitive relations, and through 

effects on ecosystem processes such as nutrient cycling and 

hydrology. Over time, combined direct and indirect impacts 

can result in altered plant population dynamics (for example, 

altered rates of reproduction, recruitment, and mortality) 

and consequent changes in plant community composition, 

structure, and distribution (Crawley, 1983; Archer and Smeins, 

1991; Archer, 1994; Miller and others, 1994; Bich and others, 

1995). Because of strong interactions of vegetation with 

nutrient cycling, hydrologic processes, disturbance regimes, 

and geomorphic processes, herbivore-driven changes in 

vegetation structure can have cascading effects on multiple 

ecosystem processes and properties. 

The alteration of competitive relations among defoliated 

or differentially defoliated plants is one of the most significant 

ways in which herbivory affects the structure of plant 

populations and communities (Archer and Smeins, 1991; 

Briske, 1991; Briske and Richards, 1994; Crawley, 1997). 

Plants that possess a greater capacity for regrowth following 

defoliation experience a competitive advantage over defoliated 

competitors that possess a lesser capacity for regrowth. 

Similarly, plants that are defoliated less frequently or less 

intensively experience a competitive advantage relative to 

plants that are defoliated more frequently or more intensively 

due to relative differences in accessibility or palatability. For 

an individual plant, the most significant benefit arising from 

herbivory is the relative advantage gained when a neighboring 

plant has been reduced in size and competitive ability by an 

herbivore (for example, Caldwell and others, 1987). Through 

time, altered competitive relations eventually can be expressed 

in population dynamics and plant community structure 

(Briske, 1991).

Some workers have hypothesized that trampling by large 

herbivores has beneficial impacts on infiltration (Savory and 

Parsons, 1980; Savory, 1988). However, hydrologic research 

has failed to support this hypothesis (Spaeth and others, 1996; 

Holechek and others, 2000), indicating instead that trampling 

tends to result in lower infiltration rates, which leads to a 

deterioration of soil structure (Thurow, 1991). Hydrologic 

impacts of trampling by large herbivores vary with soil type, 

soil water content, seasonal climatic conditions, vegetation 

type, and the magnitude of trampling (Thurow, 1991).
32 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Wet System Model 

By D.M. Miller, D.R. Bedford, and A.M. Brasher

The wet systems of the Great Basin include springs, 

wetlands, streams, wet playas, and lakes (fig. 2.14). These 

components have in common the presence of “free” water 

on or near the ground surface. Despite their relatively small 

size and scarce distribution, aquatic and riparian systems 

play a critical role in the semi-arid Great Basin. As a result 

of abundant water, these locations constitute biological 

“hotspots” where biological diversity and abundance are 

concentrated into relatively small areas. Many drivers of 

Great Basin ecosystems relate to the wet components of the 

deserts, indicating their importance. Nearly all aspects of the 

wet systems are intimately interconnected to the groundwater 

regime, and groundwater systems control the behavior of 

wet features including the temporal and spatial availability 

of surface water and water chemistry. Thus, we feature 

groundwater systems in the model (fig. 2.15) as a basis for 

understanding the responses of aquatic and riparian habitat to 

hydrologic drivers and stressors.

Groundwater systems can be classified as one of three 

types based on their size: upland, local, and regional 

(figs. 2.14 and 2.15). Each occupies characteristic parts of 

the landscape and its underlying geology and these systems 

interact with each other as well as with surface-water systems. 

Surface water can result from point discharge of groundwater, 

such as springs, or broader areas of discharge such as gaining 

streams, wetlands and wet (discharging) playas. Gradients in 

groundwater systems often govern many characteristics of 

surface-water systems, and all are tied to climate parameters, 

land topography, geology, and human consumptive uses 

(fig. 2.15). Lakes are relatively rare in the Great Basin, but 

occur in alpine settings where they are fed by local snowmelt 

and runoff, and as terminal lakes fed by stream runoff. 

Groundwater recharge, transport and storage, and discharge 

are the key characteristics needed for understanding many wet 

systems features, as well as for predicting impacts.

Stream and streambank (riparian) ecosystems have 

attributes such as floodplain, channel bank, channel bed, and 

channel, the composition of which are important to vegetation, 

aquatic fauna, and wildlife. The function and distribution 

of these ecosystem components are driven by temporal and 

spatial variations in water flow discharge over time, commonly 

summarized as flow regime. These variations occur on many 

scales, from general longitudinal and lateral changes in 

discharge, flow, and streambed form, to temporal variations in 

discharge (for example, floods). Large streams and rivers are 

also complex networks in which the organization of channels 

and their tributaries uniquely shape flow characteristics 

(Benda and others, 2004). The flow regime shapes habitats 

through bed friction and sediment transport, temperature 

and light variations, and water chemistry (including nutrient 

concentrations) (Scott and others, 2005). Streams and riparian 

zones commonly are used by narrowly endemic and wideranging wildlife (such as mule deer and a wide variety of 

birds) and can act as corridors for invasive species such as 

tamarisk.

Springs and seeps can be classified according to a 

gradient in flow persistence, which is related to groundwater 

characteristics such as discharge and response time (fig. 2.15). 

Great Basin spring-fed systems can be broadly characterized 

as pools, streams, wetlands, wet meadows, and muddy or 

boggy areas. Extensive wetlands and multiple spring pools 

form where a regional aquifer system discharges, such as 

the carbonate aquifer discharging in the southern Great 

Basin. Springs tend to have smaller pools or marshy areas 

where associated with local aquifers. Upland aquifers most 

commonly exhibit wet meadows and small springs. Due in 

part to their isolation, springs are habitat for rare and endemic 

species, such as species of springsnails, frogs, and fish. Wet 

playas and alkaline seeps may occur low in desert basins. 

Orographic precipitation and snowmelt feed streams that flow 

off high peaks, forming small alpine lakes, disappearing into 

fissures in carbonate rocks and valley fill sediments along the 

outflowing streams. 

Spring-fed wetlands form a wide variety of important 

riparian and aquatic habitat (Stevens and Springer, 2004). 

Biological diversity generally is correlated with the size of 

the wet area—brook length for flowing streams and size 

of pools—which are in turn a function of spring discharge. 

Groundwater discharge at springs is thus a key indicator of 

riparian biologic health and integrity. The factors influencing 

groundwater discharge at landscape levels primarily are 

climate and partitioning between recharge and runoff. More 

locally, discharge is affected by groundwater extraction, 

distribution of contaminants, and disturbance—especially 

paving and diversion—of recharge zones. Because streams 

in arid lands are intimately connected to groundwater, they 

are affected by the same drivers and stressors, but also are 

susceptible to surface diversions and contamination. Springfed wetlands and stream systems are affected by invasive 

plants [for example, tamarisk (Tamarix ramosissima)] and 

animals [for example, mosquitofish (Gambusia affinis)

and Asian tapeworm (Bothriocephalus acheilognathi)], as 

well as by direct human disturbance and fire. Many of the 

drivers for wet systems are important for endemic and at-risk 

populations of fish, amphibians, and riparian bird and aquatic 

macroinvertebrate communities.
Chapter 2: Framework and System Models 33

tac09-0397_fig02-14

Regional springs

discharging in valley bottom

along mid-basin fault

Local springs; topographically controlled

discharge at range front

Upland springs discharging in mountain 

upland, controlled by local geology 

Vegetation/ET at playa margin

Permeable

consolidated 

rock

Mountain block recharge

in uplands

Impermeable

consolidated 

rock

Terminal lake

Alluvial fans

Alluvial fans

Discharging

 playa

Regional flow path

Upland

flow path Local

flow path

Regional flow path

Flow toward

ultimate sink

Long spring brook

Subalpine lake

Perennial large stream

Figure 2.14. Block diagram showing flow systems associated with groundwater and surface water parts of the wet systems, 

illustrating how the systems are connected between ground and surface in some cases and compartmentalized in other cases between 

basins and parts of the highlands.

Subsystem Models

Control models present mechanistic views of the 

operation of subsystems within the wet and dry systems that 

are useful for developing monitoring methods for the key 

drivers. The models describe the linkages among system 

components and how processes will change with influence 

by drivers, and provide a basis for developing stressor 

models. Chapters 3 and 4 present control and stressor models 

for highest priority ecosystems and those with the greatest 

knowledge levels. For clarity of communication and for 

eventual quantitative models of these systems, it is helpful 

to include state-and-transition models, as exemplified by the 

sagebrush steppe and pinyon-juniper models. Subsystem 

models presented in Chapters 3 and 4 vary widely in level 

of detail, which reflects a combination of: (1) resources with 

GBILM for developing the model, (2) status of knowledge, 

and (3) importance of the subsystem for Great Basin land 

managers.
34 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac090397fig0215

ET

ET

ET

ET

Discharge

Discharge

Discharge

Upland

Regional

Local

CLIMATIC and ATMOSPHERIC

 CONDITIONS

Runoff

Precipitation,

snowmelt

Deep infiltration 

and recharge

Downstream

flow

Discharge

NATURAL DISTURBANCE

REGIMES

GEOLOGICAL

SETTING

SUBALPINE LAKES

AND MARSHES

(primarily freshwater)

Water quality;

landscape position

STREAMS AND

RIPARIAN SYSTEMS

Stream size and 

persistence; fluvial 

processes; water quality; 

watershed characteristics

TERMINAL LAKES AND 

MARSHES

(more saline)

Salinity; landscape

position; temperature;

SPRINGS AND SEEPS

ET rates

Flow persistence, response time

Upland springs, seeps,

and wet meadows

Local springs, wetlands,

and wet playas

Regional large,

warm springs

AQUIFER SIZE

Small

Large

GROUNDWATER SYSTEMS

ELEVATION

Figure 2.15. Diagram showing wet systems model. Groundwater is a major driver for many wet systems of the Great Basin, thus 

recharge for upland, local, and regional aquifers is a key process. Important variables to monitor are noted for main surface-water 

systems.
Chapter 3: Subsystem Models for the Dry System 35

As described in the Dry System model, we partitioned 

the Great Basin dry system into vegetation zones for the 

creation of subsystem models to capture the importance of 

plant communities for ecosystem function. The subsystem 

models are ordered from low elevation, relatively dry zones to 

high elevation zones that are colder and have more moisture 

(figs. 1.3 and 2.13). We acknowledge that the following 

subsystem models are uneven in level of detail. We did not 

undertake a Salt Desert Scrub model due to time constraints 

and lesser management concern regarding this system. Models 

for Sagebrush Steppe and Pinyon-Juniper ecosystems are 

fairly detailed due to the broad extent of these biomes in 

the Great Basin and implications for many landscape-level 

land-management issues. The Conifer Forest models are less 

detailed partly because of lack of information. Aspen forests, 

although decreasing rapidly in parts of the Great Basin, were 

not modeled at this time. The alpine tundra has received 

relatively little study in the Great Basin, and the model is 

correspondingly brief.

Salt Desert Scrub 

Salt desert scrub, or alkali desert scrub, vegetation 

consists of xerophytic and halophytic species such 

as shadscale (Atriplex confertifolia) and winterfat 

(Krascheninnikovia lanata), most of which are members of 

the Chenopodiaceae (West and Young, 2000). It is widespread 

on desert floors of Great Basin valleys, where it commonly 

grades downslope into phreatophytic communities dominated 

by species such as greasewood (Sarcobatus vermiculatus) or 

to dry playas, and upslope into sagebrush steppe ecosystems 

dominated by varieties of big sagebrush (Artemisia tridentata). 

Developing a specific set of conceptual models for this system 

is beyond the scope of this study.

Sagebrush Steppe and Pinyon-Juniper 

Ecosystems 

By M.E. Miller 

This section provides an overview of the structure, function, 

and dynamics of sagebrush steppe and pinyon-juniper 

ecosystems in the Great Basin. Many of the following 

generalizations about dryland structure and function also 

apply to salt desert scrub as well as to dryland ecosystems 

characteristic of the nearby Colorado Plateau (Miller, 2005) 

and Mojave Desert (Belnap and others, 2008). However, 

specific patterns of ecosystem dynamics vary widely among 

dryland ecosystems within and among the dryland regions of 

North America due to differences in environmental setting 

(climate and soil-geomorphic properties), structural and 

functional attributes of component species, and types and 

degrees of human land-use activities.

Distribution and Management Significance

As defined for this project, the Great Basin covers a 

spatial extent of about 61.7 million ha. Within this region, the 

three dominant types of low-elevation dryland ecosystems 

are salt desert scrub (10.4 million ha, or 17.0 percent of the 

region), sagebrush steppe (28.2 million ha, or 46.1 percent), 

and pinyon-juniper (coniferous) woodlands (8.1 million 

ha, or 13.2 percent). (Estimated spatial coverages are based 

on revisions to Küchler’s [1970] map of potential natural 

vegetation types [U.S. Department of Agriculture, Forest 

Service, 2001] and do not consider land-cover alterations 

attributable to human land use.) In Great Basin landscapes, 

these three ecosystems typically are arrayed sequentially along 

a gradient of increasing soil moisture availability as controlled 

by soil properties, elevation, and geomorphic setting (see 

figs. 2.1 and 2.13; West and Young, 2000). Typical elevations 

for these systems range from 1,200 m in basins to 2,100 m on 

piedmont alluvial fans and mountain slopes. Pinyon-juniper 

and sagebrush steppe ecosystems occur as high as 2,500 m on 

south-facing slopes. These are the two primary types of upland 

ecosystems managed by the Bureau of Land Management 

(BLM) throughout the Great Basin; extensive areas dominated 

by pinyon-juniper woodlands also are managed by the U.S. 

Department of Agriculture (USDA) Forest Service. These 

dryland ecosystems support a tremendous diversity of plants, 

animals, and other organisms (for example, Rosentreter 

and Belnap, 2003; Welch, 2005). In addition, they provide 

livestock forage, watershed services, and wildland recreational 

opportunities. Pinyon-juniper ecosystems also provide 

substantial fuel-wood resources to local communities. Because 

of their spatial extent and the breadth of ecosystem services 

they provide, they have great significance for management and 

society. 

Chapter 3: Subsystem Models for the Dry System 

By M.E. Miller, S.P. Finn, and D.M. Miller
36 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Ecosystem Components and Processes

Climate and the Physical Template – Determinants of Site 

Potential

Dynamic and relatively static abiotic factors including 

regional climate, elevation, and soil-geomorphic setting 

determine the potential distribution, biotic structure, and 

dynamics of terrestrial ecosystems through their combined 

effects on environmental conditions and resources (Jenny, 

1980; Stephenson, 1990; Monger and Bestelmeyer, 2006; 

fig. 3.1). Climate was described in Chapter 2. Great Basin 

landscapes are characterized by a diversity of parent materials, 

landforms, and soils that contribute to the physical template 

and thus the characteristics of sagebrush steppe and pinyonjuniper ecosystems. Geologic parent materials range from 

Tertiary basalt and andesite on volcanic plateaus to Mesozoic 

and Paleozoic igneous rocks and marine and continental 

sedimentary rocks in uplifted fault-block mountain ranges 

(Hunt, 1974; U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2006). Piedmont slopes are 

Microclimatic modification; 

soil stabilization; resource

capture, retention, & uptake

VEGETATION

Trees, shrubs, perennial

grasses, forbs

Competition and facilitation

REGIONAL CLIMATIC &

ATMOSPHERIC CONDITIONS

Winter-dominated precipitation

with interannual, decadal

and spatial variability

BIOLOGICAL 

SOIL CRUSTS

Mosses, lichens,

cyanobacteria

SOIL RESOURCES

Mineral nutrients, water,

organic matter, soil biota

LANDSCAPE

CONFIGURATION

Spatial configuration

of ecosystem patches

HABITAT QUALITY

Patch level:

Vegetation composition

and structure

Landscape level:

Habitat dimensions,

arrangement, and 

connectivity

WILDLIFE

Obligate and

facultative associates

Competition and

predation

PHYSICAL TEMPLATE

Elevation and

soil-geomorphic

setting

NATURAL

DISTURBANCES

Climatic episodes,

insects, and fire

Determines site potential 

and provides 

resource inputs

Evapotranspiration

and energy balance

Determines

site potential

Resource availability

Safe-site availability

Microclimatic modification

Climatic episodes, fire weather, and 

antecedent environmental conditions 

Pollination, herbivory,

granivory, seed dispersal

Habitat dimensions,

arrangement, 

and connectivity

Effects on composition, structure, and spatial configuration of ecosystem patches

Effects on fire behavior

Determines potential

landscape configuration

Vegetation composition

and structure

Effects on 

vegetation composition,

structure, and productivity

Resource

transformation

and redistribution

Resource availability

Soil stabilization,

resource capture

& retention

Fuel structure and flammability

Figure 3.1. Diagram showing control model illustrating key components (rectangles), natural drivers of temporal change and variability 

(ovals), and functional relations (arrows) of Great Basin sagebrush steppe and pinyon-juniper ecosystems, excluding major human 

influences. The dashed box bounding vegetation, soil resources, and biological soil crusts emphasizes strong feedbacks among these 

three components that together form the foundation of dryland ecosystems. (Adapted from Miller, 2005.)
Chapter 3: Subsystem Models for the Dry System 37

mantled and intermontane basins are filled with Quaternary 

alluvium and other deposits with physical and mineralogical 

properties inherited from these parent materials and modified 

by geomorphic processes and soil formation. In basins 

formerly occupied by pluvial lakes, basin-floor soils are 

formed in lacustrine sediments as well as alluvium. Deposits 

and resultant soils generally become progressively deeper 

and finer in texture downslope from mountain fronts to basin 

floors. Although these are useful generalizations, spatial 

patterning of key soil properties such as depth, particle-size 

distribution, and degree of profile development are far more 

complex in actual Great Basin landscapes (Peterson, 1981). 

This spatial complexity is attributable to differences in the 

origins and ages of major types of landforms (for example, 

mountain-valley fans, alluvial fans, fan piedmonts, alluvial 

flats, and alluvial plains) that comprise piedmont slopes 

and basin floors (Peterson, 1981). In the Great Basin, these 

landforms developed primarily during or before the late 

Pleistocene, and since that time have been repeatedly modified 

during recurrent periods of erosion and deposition as well 

as by soil formation during periods of greater landscape 

stability (Peterson, 1981). As a consequence, different types 

of soils (that is, in terms of depth, particle size, and degree of 

development) and ecosystems (that is, in terms of structure 

and dynamics) tend to be associated with different landforms 

as well as with finer-scale components and elements of 

landforms (Peterson, 1981; Monger and Bestelmeyer, 2006). 

Aridisols, Mollisols, and Entisols generally are the dominant 

soil orders associated with sagebrush steppe and pinyonjuniper ecosystems in the Great Basin (U.S. Department of 

Agriculture Natural Resources Conservation Service, 2006).

Vegetation, Biological Soil Crusts, and Soil Resources—

The Foundation for Sagebrush Steppe and Pinyon-Juniper 

Ecosystems

Vegetation.—Vegetation, biological soil crusts, and 

soil resources are tightly coupled components of dryland 

ecosystems in the Great Basin (fig. 3.1; Whitford, 2002)—

including those dominated by big sagebrush, pinyon, and 

juniper. Big sagebrush is widely distributed across the Great 

Basin (fig. 3.2; Little, 1976) and is perhaps the single plant 

species that best characterizes the region. Three of five 

known varieties of big sagebrush are prevalent throughout 

the region (West and Young, 2000). These three taxa—

Wyoming big sagebrush (A. t. var. wyomingensis), basin 

big sagebrush (A. t. var. tridentata), and mountain big 

sagebrush (A. t. var. vaseyana)—generally shift in relative 

abundance along gradients of decreasing soil temperature 

and increasing soil moisture (West and Young, 2000). Of 

these three, Wyoming big sagebrush has the most extensive 

distribution as a shrubsteppe dominant in deep, salt-free soils 

below the elevation of pinyon-juniper woodlands. Basin big 

sagebrush commonly is restricted to deep alluvial soils along 

stream courses, although it is a shrubsteppe dominant in 

some settings. Mountain big sagebrush typically occurs as a 

shrubsteppe dominant in forest clearings and meadows above 

or in more mesic topographic settings than pinyon-juniper 

woodlands. In their treatment of vegetation communities of 

the Intermountain West, West and Young (2000) differentiated 

sagebrush steppe from Great Basin sagebrush—with the 

former type having a greater proportion of perennial grass 

cover and a more northerly distribution in the sagebrush 

biome relative to the latter type. In this report, we do not 

retain this coarse-scale distinction because community 

composition and especially the shrub:grass ratio also varies 

widely with soil—geomorphic properties, climatic conditions, 

and disturbance history at finer spatial scales. These factors 

as well as regional biogeographical patterns together result 

in considerable variability in the composition, structure, and 

dynamics of sagebrush steppe ecosystems across the Great 

Basin. Depending on these many factors, a large variety of 

shrubs (for example, Ericameria nauseosa, Ephedra viridis, 

Krascheninnikovia lanata, and Purshia tridentata), perennial 

bunchgrasses (for example, Pseudoroegneria spicata, 

Pascopyrum smithii, Poa secunda, and Festuca idahoensis), 

perennial forbs (for example, Astragalus spp., Balsamorhiza 

sagittata, Eriogonum spp., and Phlox spp.), and annuals can 

be important components of sagebrush steppe (Holmgren, 

1972). The issue of variability is a particularly important one 

for monitoring and management, and it is addressed later in 

this section.

Like sagebrush steppe, pinyon-juniper woodlands are 

extremely variable across the broad range of this general 

vegetation type. In the Great Basin, singleleaf pinyon (Pinus 

monophylla) and Utah juniper (Juniperus osteosperma) are 

the most widely distributed woodland species (fig. 3.2B and 

3.2D). Western juniper (Juniperus occidentalis) occurs along 

the western margin and particularly in the northwestern corner 

of the Great Basin (fig. 3.2E), whereas Colorado pinyon 

(P. edulis) is restricted to the southeastern corner of the region 

(fig. 3.2C). In large areas of the region, junipers occur in the 

absence of pinyon. In landscapes where they co-occur, juniper 

tends to dominate at lower and upper ends of elevational 

gradients, whereas pinyon dominates middle elevation due 

to lesser tolerance for dry (low elevation) and cold (high 

elevation) conditions (West, 1999). As with sagebrush steppe 

ecosystems, the composition and structure of understory shrub 

and herbaceous communities varies greatly in relation to 

woodland structure and successional stage, soil-geomorphic 

setting, climatic conditions, and disturbance history (West, 

1999). 

Interspecific competition and facilitation are important 

types of plant interactions in dryland ecosystems (Archer 

and Bowman, 2002). Much research has focused on 

the importance of competition as a process affecting 

plant community structure in drylands (Fowler, 1986; 

Reichenberger and Pyke, 1990; Booth and others, 2003), 
38 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig03-02

122° 118° 114° 110°

44°

40°

36°

122° 118° 114° 110°

44°

40°

36°

122° 118° 114° 110°

44°

40°

36°

122° 118° 114° 110°

44°

40°

36°

122° 118° 114° 110°

44°

40°

36°

0 100 200 MILES

0 100 200 KILOMETERS

A. Artemisia tridentata

C. Pinus edulis

B. Pinus monophylla

 D. Juniperus osteosperma

E. Juniperus occidentalis

Washington

Oregon

California

Nevada

Arizona

Utah

Wyoming Idaho

Montana

PACIFIC

OCEAN

CANADA

MEXICO

GBILM

Figure 3.2. Distribution of (A) Artemisia tridentata, (B) Pinus monophylla, (C) Pinus edulis, (D) Juniperus osteosperma, 

and (E) Juniperus occidentalis in the Great Basin (derived from Little, 1971,1976; U.S. Geological Survey, 1999). 
Chapter 3: Subsystem Models for the Dry System 39

with particular emphasis on interactions between woody 

plants and perennial grasses (Archer, 1994; West and Young, 

2000). But there is increasing recognition that facilitation also 

can be an important process in drylands due to ameliorating 

effects of overstory plants on environmental conditions or 

herbivory experienced by understory plants (Callaway, 1995; 

Archer and Bowman, 2002; Brooker and others, 2008). 

For example, sagebrush has been determined to facilitate 

establishment and persistence of perennial grasses under 

some conditions (Davies and others, 2007). The tendency 

for pinyons to establish beneath junipers (Chambers, 2001) 

also indicates an important role for facilitation in woodlands. 

The relative importance of competition versus facilitation 

can vary depending on characteristics of interacting species, 

environmental conditions such as aridity, and other factors 

such as grazing intensity (Brooker and others, 2008). Recent 

work also indicates that greater consideration of facilitative 

interactions between plants could enhance restoration success 

in the context of harsh environmental conditions (Pueyo and 

others, 2008). 

Biological Soil Crusts.—Biological soil crusts (BSCs) 

play important functional roles in sagebrush and pinyonjuniper ecosystems of the Great Basin (fig. 3.1). BSCs are 

biotic communities composed of cyanobacteria, algae, 

microfungi, mosses, and lichens that occur on and within 

a few millimeters of the soil surface (Belnap and Lange, 

2003). These diverse communities are characteristic biotic 

components of ecosystems where environmental conditions 

limit the development of closed-canopy vascular plant 

communities or thick layers of surface litter (Belnap and 

Lange, 2003; Rosentreter and Belnap, 2003). In addition to 

their contributions to biological diversity, BSCs are major 

contributors to soil stability because they aggregate soil 

particles, thereby reducing the susceptibility of soil to erosion 

by wind and water (Williams and others, 1995a, 1995b). BSCs 

also roughen the soil surface, thereby facilitating the capture 

and retention of wind-blown dust that can be a significant 

source of mineral nutrients in dryland ecosystems (Reynolds 

and others, 2001; Belnap and Lange, 2003). BSCs similarly 

can capture and enhance ecosystem retention of windborne 

and waterborne organic matter and seeds (Belnap and Lange, 

2003). 

Hydrologic effects of BSCs are complex. Regardless 

of crust or soil type, BSCs stabilize soils and reduce water 

erosion by reducing the detachment of soil particles by 

erosive raindrops and overland water flow. In this function, 

cyanobacteria and algae are less effective than mosses and 

lichens. However, BSC organisms also can clog soil pores 

and inhibit infiltration. In undisturbed settings of the Great 

Basin, BSCs typically are characterized by a rolling surface 

morphology (Rosentreter and Belnap, 2003). Where BSCs 

roughen the soil surface in this way, they increase the 

residence time of runoff on hillslopes, thereby increasing 

infiltration and offsetting the inhibitive effects of BSCs on 

infiltration (Belnap, 2006). Organic carbon produced by BSC 

organisms also contributes to the formation of stable soil 

aggregates that increase the ratio of macropores to micropores 

and thus enhance infiltration. The presence of heavy, shrinkswell clays overrides the local hydrologic effects of BSCs.

In addition to enhancing soil stability and nutrient 

retention, BSCs contribute to dryland nutrient cycles in other 

ways. Mosses, cyanobacteria, green algae, and lichens are 

photosynthetic and thus are significant sources of carbon 

in dryland ecosystems, particularly in interspaces among 

vascular plants where soil crusts can attain 100 percent cover 

(Lange, 2003). Cyanobacteria (for example, Nostoc and 

Scytonema spp.) and cyanolichens (for example, Collema spp.) 

also are capable of fixing atmospheric nitrogen into a mineral 

form that can be used by vascular plants (Evans and Lange, 

2003). Consequently, BSCs can be the dominant source of 

nitrogen in many dryland regions (Evans and Ehleringer, 

1993; Belnap, 2002). BSC organisms are significant sources 

of carbon for other soil biota, which are more abundant and 

diverse beneath BSCs than beneath bare soils (Belnap, 2003). 

BSCs also increase nutrient cycling rates of soil food webs 

through their effects on near-surface moisture availability, soil 

structure, soil aeration, and soil temperature, thus increasing 

soil nutrient availability (Belnap, 2003). 

BSCs have numerous effects on vascular plants. Where 

their presence results in roughened soil surfaces, BSCs 

generally enhance seed catchment and retention. Following 

seed catchment, BSC effects on plant establishment are 

dependent on crust composition and morphology, plant species 

(propagule morphology and germination requirements), 

and site conditions (Belnap and others, 2003; Escudero and 

others, 2007). Serpe and others (2006) determined that short 

mosses characteristic of the Great Basin reduced germination 

of four grasses (Festuca idahoensis, Festuca ovina, Elymus 

wawawaiensis, and Bromus tectorum) relative to bare soil. In 

contrast, tall mosses increased time to germination relative 

to bare soil but did not have an effect on final germination 

percentages for these same species. In a similar experiment, 

a lichen crust dominated by Diploschistes muscorum reduced 

germination of the exotic annual grass Bromus tectorum and 

the native annual grass Vulpia microstachys by two-thirds 

relative to bare soil (Deines and others, 2007). A mixed 

lichen-moss crust had no effects on germination relative to 

bare soil, with similar results for both grass species. Following 

the establishment phase, plants growing in soils with BSCs 

generally have greater biomass and lower root:shoot ratios 

than comparable plants growing in soils without BSCs, 

indicating greater availability of soil resources in the presence 

of BSCs (Belnap and others, 2003). Relative to plants growing 

in soils without BSCs, plants growing in association with 

nitrogen-fixing cyanobacteria and cyanolichens consistently 

have high nitrogen concentrations in tissues and usually have 

high concentrations of the plant-essential nutrients potassium, 

magnesium, copper, and zinc (Harper and Belnap, 2001). 
40 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

In contrast, plants growing in soils with BSCs commonly 

have low concentrations of phosphorus and iron than plants 

growing in soils without BSCs, indicating that plants and 

BSCs may compete for these elements. Nutritional differences 

between plants grown in soils with and without BSCs are 

greatest in shallow-rooted herbaceous species, probably 

because the plants are rooted in near-surface soils that are 

most directly influenced by BSCs (Harper and Belnap, 2001). 

Soil Resources and Functions.—Soils are the third 

element constituting the foundation of dryland ecosystems 

because they are important for sustaining hydrologic 

processes, nutrient cycling, and plant establishment and 

growth, and erosion resistance in sagebrush steppe and 

pinyon-juniper. Key dynamic properties affecting these 

processes include organic matter content, aggregate stability, 

surface roughness, and structure. General soil characteristics 

and their importance to dryland ecosystems are discussed in 

Chapter 2. 

Because soils and their geomorphic, elevation, and 

climatic setting are fundamental to determining potential 

ecosystem structure and function, including many aspects 

of ecosystem resistance and resilience to drivers of change 

(Monger and Bestelmeyer, 2006), they can provide a basis for 

subdividing and classifying upland ecosystems into ecological 

land units for purposes of ecosystem management, assessment 

and monitoring, and associated research. One such system that 

has been widely applied in the Great Basin is the ecological 

site system developed and managed by NRCS. Ecological 

sites are land units that are delineated on the basis of soil 

properties (soil texture and mineralogy through the profile), 

climate (latitude, elevation, and aspect), and geomorphic 

setting (landform association and topographic / hillslope 

position; fig. 3.3; table 3.1). These units have potential to 

produce specific kinds and amounts of vegetation and distinct 

responses to management, climate, and other drivers of change 

(Society for Range Management Task Group on Unity in 

Table 3.1. Dominant soil, ecological site, and generalized type of upland ecosystem associated with soil map units. 

[Map units are ordered as they are encountered along a cross-valley transect from west to east (see fig. 3.3). Soil and ecological site information were compiled 

from U.S. Department of Agriculture Natural Resource Conservations Service, Soil Survey of Box Elder County, Western Part. Dominant ecological site: 

Descriptions of these ecological sites are available online at http://www.ut.nrcs.usda.gov/technical/technology/range/ecosites.html]

Soil map 

unit

Dominant soil Dominant ecological site

Generalized type

Taxonomic class Landform Name No.

68 Loamy-skeletal, 

mixed, frigid Lithic 

Haploxerolls

Hills Upland Shallow Loam 

(Utah Juniper)

R025XY324UT Pinyon-juniper

11 Loamy-skeletal, mixed, 

mesic Haploxerollic 

Durargids

Fan remnants Semidesert Gravelly 

Loam (Wyoming Big 

Sagebrush) North

R028AY215UT Sagebrush steppe

45 Coarse-loamy, mixed, 

mesic Durixerollic 

Calciorthids

Fan remnants Semidesert Alkali Loam 

(Black Greasewood)

R028AY202UT Salt desert scrub

82 Coarse-silty, mixed 

(calcareous), mesic 

Typic Torriorthents

Lake plains and terraces Desert Loam (Shadscale) R028AY124UT Salt desert scrub

47 Coarse-loamy, mixed, 

superactive, mesic 

Xeric Argidurids

Fan remnants Semidesert Loam 

(Wyoming Big 

Sagebrush)

R028AY220UT Sagebrush steppe

64 Loamy, mixed 

(calcareous), mesic, 

shallow Xeric 

Torriorthents

Ridges on hillslopes Semidesert Shallow 

Hardpan (8-10 “ 

precip.) 

R028AY231UT Sagebrush steppe

23 Coarse-loamy, mixed, 

frigid Haploxerollic 

Durorthids

Hillslopes Upland Juniper Savanna 

(Utah Juniper)

R025XY322UT Pinyon-juniper

59 Loamy-skeletal, 

mixed Argic Pachic 

Cryoborolls

Mountain slopes Mountain Gravelly 

Loam (Mountain Big 

Sagebrush)

R025XY4122UT Sagebrush steppe
Chapter 3: Subsystem Models for the Dry System 41

Reno

Salt Lake

City

Pocatello

Las Vegas

Klamath Falls

Elko

Boise

Walker RWalker R Pyramid

Lake

Truckee RTruckee R

Humboldt River

Snake RiverSnake River

Great

Salt

Lake

Owens R

Lake

Tahoe

PACIFIC OCEANPACIFIC OCEAN

Colorado Colorado River

OREGON

CALIFORNIA

NEVADA

UTAH

ARIZONA

WYOMING

IDAHO

Colu

MONTANA mbia Plateau

Columbia Plateau

Blue Mountains Blue Mountains

Snake River PlainSnake River Plain

Wasatch Range Wasatch Range

ROCKY

MOUNTA NI S

ROCKY

MOUNTA NI S

Mojave Desert ojave Desert

CASCADE RAN

GE CASCADE RANGE

Steens

Mountains

Bonneville Salt

Flats

Meadow Valley Wash

SIERRA

NEVADA

SIERRA

NEVADA

GREAT BASIN

110°

114°

114°

118°

118°

122°

122°

44° 44°

40° 40°

36°

0 100 200 MILES

0 100 200 KILOMETERS

36°

EXPLANATION

Great Basin Integrated 

Landscape Monitoring Project 

(GBILM) Area-of-Interest

68

11

45 82

47

64 23 59

0 5 MILES

0 5 KILOMETERS

Grouse Creek Valley, Utah

Soil map units from U.S. Department of Agriculture Natural Resource 

Conservation Service, Soil Survey of Box Elder County, Western Part, survey 

area UT601, accessed June 23, 2009, at http://websoilsurvey.nrcs.usda.gov/app

Figure 3.3. Soil map units in Grouse Creek Valley, Utah. A description of the eight numbered map units that occur along a cross-valley 

transect from west to east is shown in table 3.1. 

Concepts and Terminology, 1995). In some cases, naming 

conventions for ecological sites include reference to one or 

more plant species that characterize the potential vegetation 

for the site (see table 3.1). Upland subsystems referred to in 

this report (for example, salt desert scrub, sagebrush steppe, 

and pinyon-juniper woodlands) represent coarse groupings 

of ecological sites, which incorporate considerable variation 

in classification factors and ecosystem responses. A map 

of actual vegetation differs from a map of ecological sites 

because the former reflects disturbance and fire history rather 

than the potential to respond to climate or land-use activities.
42 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Wildlife and Habitat Quality

Wildlife (including vertebrates and invertebrates) 

are significant contributors to the biological diversity and 

functioning of sagebrush steppe and pinyon-juniper woodlands 

of the Great Basin. Bird species that have obligate habitat 

associations with sagebrush steppe include greater sage-grouse 

(Centrocercus urophasianus), sage thrasher (Oreoscoptes 

montanus), sage sparrow (Amphispiza belli), and Brewer’s 

sparrow (Spizella breweri) (Knick and others, 2003; Welch, 

2005). Welch (2005), citing a long list of other researchers, 

identified 91 additional bird species that are facultative 

associates of sagebrush steppe. Mammals considered to be 

sagebrush obligates include the pygmy rabbit (Brachylagus 

idahoensis) and the sagebrush vole (Lagurus curtatus) 

(Welch, 2005). At least 88 mammal taxa have been identified 

as facultative sagebrush associates, including pronghorn 

(Antilocapra americana), mule deer (Odocoileus hemionus), 

elk (Cervus elaphus), and bighorn sheep (Ovis canadensis) 

(Welch, 2005). Depending on local habitat conditions, these 

same four species also have been determined to use pinyonjuniper woodlands on a facultative basis—with mule deer 

being the most important in terms of degree of woodland use 

for thermal cover and food (Frischknecht, 1975). In their study 

of pinyon-juniper woodlands in northeastern Utah (outside our 

Great Basin boundary), Paulin and others (1999) identified 

six bird species that they considered to be pinyon-juniper 

obligates—ash-throated flycatcher (Myiarchus cinerascens), 

blue-gray gnatcatcher (Polioptila caerulea), Bullock’s oriole 

(Icterus bullockii), pinyon jay (Gymnorhinus cyanocephalus), 

western scrub-jay (Aphelocoma coerulescens), and Virginia’s 

warbler (Vermivora virginiae). Periodic mast crops of pinyon 

and juniper seeds are particularly important resources for a 

wide range of birds and mammals (Frischknecht, 1975). Miller 

and others (2005) summarized the current understanding of 

habitat-use patterns of selected bird and mammal species 

in sagebrush steppe and western juniper woodlands in the 

northwestern Great Basin.

 Vertebrates and invertebrates perform numerous 

functions (see Chapter 2, section “Wildlife and Habitat 

Quality”) in sagebrush steppe and pinyon-juniper ecosystems, 

the most important of which is herbivory. Native herbivores in 

sagebrush steppe and pinyon-juniper ecosystems of the region 

include insects (grasshoppers, moth and butterfly larvae, bark 

beetles, and many others) and mammals such as woodrats 

(Neotoma spp.), desert cottontails (Sylvilagus audubonii), 

black-tailed jackrabbits (Lepus californicus), bighorn sheep, 

pronghorn, mule deer, and elk. Herbivorous insects and small 

to medium-size mammals can have significant effects on 

vegetation structure and ecosystem processes such as nutrient 

cycling. With the exception of infrequent insect outbreaks 

(discussed below in section “Insect Outbreaks”), the greatest 

ecosystem-level consequences of herbivory are those that 

can be caused by high densities of large-bodied browsers 

and grazers such as mule deer, elk, and domestic livestock. 

Herbivorous animals influence plant community composition 

and vigor through selective defoliation, transport of plant 

materials and seeds, caching, defecation, and trampling. 

Through time, these effects can lead to altered competitive 

relations among plants which then are expressed in population 

dynamics and plant community structure (Briske, 1991).

Drivers of Ecosystem Change

Natural Drivers

Climate Variability.—Climate variability and 

disturbance processes are the two natural factors that are 

most responsible for driving temporal patterns of change 

and variability in sagebrush steppe and pinyon juniper 

systems. With respect to climate, precipitation seasonality 

(that is, timing in relation to the annual cycle of potential 

evapotranspiration) and form (that is, snow versus rain) are 

major determinants of ecosystem dominance by different 

vegetative life forms and functional groups because these 

climatic attributes strongly control the partitioning of 

precipitation among various compartments of the hydrologic 

budget—evaporation, transpiration, runoff, drainage 

(recharge), and soil-water storage (Comstock and Ehleringer, 

1992). In the Great Basin, winter precipitation is predominant, 

with greater summer precipitation in the east (see Chapter 2, 

section “Climate Patterns in the Great Basin”). The prevalence 

of cool-season precipitation results in effective soil-moisture 

recharge and relatively reliable growing conditions in spring 

(Caldwell, 1985; Comstock and Ehleringer, 1992; West and 

Young, 2000). Annual temperature extremes also influence 

plant species distributions and therefore contribute to 

landscape configuration; for example, the upper elevational 

limit of pinyon pine appears to be defined by minimum annual 

temperatures (West, 1999). Pinyon pine and the other plant 

species defining the sagebrush steppe and pinyon-juniper 

zones exhibit adaptations to climate conditions that promote 

their local dominance.

Natural Disturbance Regimes.—

Extreme Climatic Events.—Episodic severe climatic 

events are major disturbances in dryland ecosystems (Walker, 

1993; Whitford, 2002). Drought, extreme precipitation events 

and floods, and wind storms can induce long-term changes 

in ecosystem structure and function by causing widespread 

mortality or enabling establishment of long-lived plants that 

are structural dominants. The erosive energy of extreme 

precipitation and wind events also can result in ecologically 

significant transport and redistribution of soil resources, 

potentially inducing geomorphic changes that fundamentally 

alter site conditions. Event sequencing (for example, timing 

of flooding in relation to drought) is an important factor that 

can affect ecosystem resistance and resilience to episodic 

climatic events. Episodic, event-driven change is an important 
Chapter 3: Subsystem Models for the Dry System 43

feature of many ecosystems (Holling, 1996; Scheffer and 

others, 2001), and is particularly characteristic of dryland 

ecosystems (Whitford, 2002). West and Young (2000) note 

that the occurrence of extremely wet springtime conditions 

or very cold winters without snow cover are climatic events 

that trigger sagebrush mortality and affect the ratio of shrubs 

to herbaceous species in sagebrush steppe ecosystems of 

the Great Basin. Climatic conditions and events can affect 

ecosystem susceptibility to other disturbances such as fire and 

insect outbreaks (Swetnam and Betancourt, 1998), as well as 

affect ecosystem resistance and resilience to anthropogenic 

drivers of change (Archer and Stokes, 2000; Scheffer and 

others, 2001). 

Fire.—Wildfire is another type of natural disturbance 

that can have many direct and indirect effects on ecosystem 

structure and function, although there is considerable 

variability among dryland ecosystems in the specific 

characteristics of natural fire regimes. One of the most 

significant direct effects of fire is the alteration of vegetation 

composition and structure due to the selective reduction 

or elimination of fire-intolerant life forms or age classes 

(Whelan, 1995). Specific effects of fire on vegetation structure 

vary in relation to fire-regime characteristics (for example, 

frequency, intensity, seasonality, and spatial patterning) 

and fire responses of dominant vegetative life forms. Fireregime characteristics are strongly influenced by vegetation 

composition and structure, as well as by preceding and 

coincident weather conditions that affect fuel availability, fuel 

flammability, and fire behavior. In describing fire regimes, fire 

intensity refers to how hot a fire burns (energy output; Whelan, 

1995) whereas fire severity refers to the degree of mortality 

in overstory woody plants (Baker and Shinneman, 2004). 

High-severity fires in woodlands and forests result in nearcomplete mortality of overstory trees, whereas low-severity 

fires consume primarily herbaceous surface fuels, litter, 

fire-sensitive understory trees, and shrubs. Mixed-severity 

fires result in a mosaic of high-severity and low-severity 

patches that can be caused by changes in weather during the 

fire, topographic heterogeneity, the relative abundance and 

distribution of fuels, and legacies of past fire (Noss and others, 

2006).

 Effects of fire on vegetation structure have multiple 

ecosystem-level consequences because of strong vegetation 

interactions with soil, hydrology, and geomorphic processes. 

Fire-caused reductions in ground cover and vegetation 

structure can result in significant erosional losses of soils, 

nutrients and organic matter by water and wind (Johansen and 

others, 2001; Whicker and others, 2002). Soil hydrophobicity 

caused by fire is another factor that can result in accelerated 

water-driven erosion because of decreased infiltration and 

increased runoff (Johansen and others, 2001; MacDonald and 

Huffman, 2004). 

Fire also has significant ecosystem-level consequences 

due to effects on nutrient cycles (Raison, 1979; Blank and 

others, 1994a, 1994b). Depending on the type and intensity 

of fire events, fire can (1) increase nutrient bioavailability

on a short-term basis due to ash deposition and accelerated 

rates of nutrient cycling, and (2) deplete total nutrient stocks

due to gaseous losses (particularly nitrogen) and off-site 

transfers of ash (Raison, 1979). Nutrient losses in gases and 

ash generally are proportional to heat generated and organicmatter consumed by fire (Raison, 1979; Schlesinger, 1997). 

Depending on fire intensity, other soil characteristics can be 

affected by fire, including pH (typically increased by ash 

deposition), cation exchange capacity and infiltration capacity 

(both typically decreased by organic-matter losses and 

transformations; Raison, 1979), and erodibility (Whicker and 

others, 2002). Fire extent and spatial patterning affect and are 

affected by topography, wind, fuel moisture, and the spatial 

configuration of different fuel (vegetation) types across the 

landscape (fig. 3.1). 

There is uncertainty regarding the characteristic 

frequency of fire in Great Basin sagebrush steppe prior to the 

time of Euro-American settlement. Some researchers have 

estimated that pre-settlement natural fire-return intervals 

in sagebrush steppe were 15–25 years in mountain big 

sagebrush ecosystems and 50–100 years in Wyoming big 

sagebrush ecosystems (Miller and others, 1994; Miller and 

Tausch, 2001). Following a critique of methodological issues 

associated with previous estimates, Baker (2006) concluded 

that these fire rotations (the time required for fire to burn 

once through a sagebrush landscape) may have been 70–200 

years or more in mountain big sagebrush and 100–240 

years in Wyoming big sagebrush. When fire does occur, all 

varieties and age classes of big sagebrush typically are killed 

irrespective of fire intensity (Welch, 2005). As a consequence, 

fire in sagebrush steppe tends to create a mosaic of burned and 

unburned patches rather than thinning the density of shrubs 

within patches (Baker, 2006). Fire frequency, size, and spatial 

patterning affect the spatial mosaic of vegetation patches and 

landscape-level habitat attributes for broad-ranging wildlife 

such as birds (fig. 3.1). 

There is a similar degree of uncertainty regarding 

characteristics of pre-settlement fire regimes in pinyonjuniper ecosystems of the Great Basin. West and Young 

(2000) suggest that many intermountain pinyon-juniper 

ecosystems likely were characterized by low-severity surfacefire regimes that maintained savanna-like vegetation structure 

prior to Euro-American settlement. In contrast, Baker and 

Shinneman (2004) concluded from their systematic review of 

fire research in pinyon-juniper ecosystems that low-severity 

surface fires probably were uncommon in such ecosystems 

prior to Euro-American settlement. They also concluded that 

much additional area-specific research is needed to provide 

a foundation for science-based management and restoration 

of pinyon-juniper ecosystems. They are in agreement with 

other workers who have warned ecosystem managers not to 

rely uncritically on fire-regime generalizations derived from 

studies conducted elsewhere (for example, Romme and others, 

2003; Veblen, 2003).
44 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

 In an effort to clarify issues associated with pinyonjuniper fire regimes, Romme and others (2007) compared 

two general types of pinyon-juniper ecosystems with areas 

of potential tree expansion and contraction based on canopy 

structure, understory characteristics, and historical disturbance 

regimes (table 3.2). Although there is a great deal of variability 

within each of these types as well (for example, variability 

corresponding with the large number of different pinyonjuniper ecological sites in the Great Basin), this general 

classification scheme provides a useful framework for future 

research regarding management, dynamics, and restoration of 

systems in which pinyon and juniper species occur. Following 

this scheme, pinyon-juniper ecosystems discussed in this 

report are considered to be classified as persistent woodlands. 

Sagebrush steppe ecosystems subject to tree encroachment 

are classified as areas of potential expansion and contraction

following the scheme described in table 3.2.

Insect Outbreaks.—Insect outbreaks can represent 

significant natural disturbances in sagebrush steppe and 

pinyon-juniper ecosystems of the Great Basin (Bentz and 

others, 2008). For example, Gates (1964) reported that 4,000–

6,000 ha of sagebrush in eastern Oregon were killed through 

defoliation by the Aroga moth (Aroga websteri) in 1962, and 

more than 4.5 million ha of sagebrush steppe was infested by 

the moth to some degree by 1963. More recently, an Aroga 

moth outbreak was reported in northern and central Nevada 

during 2004–06 (Bentz and others, 2008). Recent outbreaks 

of grasshoppers and Mormon crickets (Orthoptera) also have 

occurred in portions of Utah and Nevada (Bentz and others, 

2008). Factors controlling the frequency and magnitude of 

such outbreaks are poorly understood, but climate likely is 

a major driver. Hsiao (1986) reported that declines of Aroga 

moth populations were caused by high summer temperatures 

and host-plant desiccation during a 5-year study in Curlew 

Valley, Idaho. Climatic conditions can affect the occurrence of 

insect outbreaks directly through effects on insect metabolic 

processes and indirectly through effects on predation and food 

quality (Bentz and others, 2008).

The occurrence of insect outbreaks in tree-dominated 

ecosystems has been attributed to climatic conditions that 

diminish the vigor and insect resistance of host plants and/or 

affect life cycles and dispersal patterns of insect herbivores 

(Swetnam and Betancourt, 1998; Logan and others, 2003). 

In pinyon-juniper ecosystems, outbreaks of the bark beetle 

Ips confusus (pinyon ips) can be triggered by drought 

conditions that weaken host-tree populations (Leatherman and 

Kondratieff, 2003).

Anthropogenic Drivers

In addition to natural drivers, scoping for this project 

identified six high-priority anthropogenic drivers that currently 

affect sagebrush steppe and pinyon-juniper ecosystems in 

the Great Basin:. (1) fire-regime alteration, (2) invasive-fire 

interactions, (3) livestock grazing, (4) land treatments, (5) 

off-highway vehicle activity, and (6) climate change. These 

factors interact with one another and with natural drivers 

to affect change and temporal variability in Great Basin 

ecosystems (fig. 3.4). These interactive effects and their 

implications for ecosystem dynamics are discussed below.

Ecosystem Dynamics

General patterns of ecosystem dynamics are illustrated 

here with state-and-transition models (Westoby and others, 

1989; Bestelmeyer and others, 2003; Stringham and others, 

2003; Bestelmeyer and others, 2004; Briske and others, 2005, 

2008). State-and-transition models are management-oriented 

tools for describing and classifying ecosystem conditions 

(or states) and posing hypotheses about ecological factors 

responsible for persistent changes (or transitions) among 

different states (Bestelmeyer and others, 2004). Such models 

increasingly are being developed and used by managers and 

researchers to organize information about the dynamics of 

rangeland ecosystems, qualitatively compare and evaluate the 

relative benefits and risks of different management actions, 

and consider the effects of other drivers such as climate, 

natural disturbances, and invasive exotic plants (Bestelmeyer 

and others, 2004). For maximum utility, such models are 

developed for and applied to specific ecological land units (for 

example, specific ecological sites) because of the importance 

of site-specific factors such as local climatic conditions, 

soil-geomorphic properties, and landscape configuration for 

determining ecosystem responses to management actions 

and other drivers of change. The general models presented 

here do not account for these site-specific factors and require 

modification for application to a specific type of land unit.

To further elaborate on hypothesized mechanisms 

of ecosystem change, state-and-transition models are 

supplemented with mechanistic stressor models. These 

conceptual models illustrate how various natural and 

anthropogenic drivers interact to cause particular types (or 

pathways) of change in sagebrush steppe and pinyon-juniper 

ecosystems. To facilitate the consideration of indicators for 

long-term ecological monitoring, these models emphasize 

pathways and processes of ecosystem change that typically are 

considered undesirable with respect to agency management 

objectives. Relations among control models, state-andtransition models, and mechanistic stressor models are 

depicted in figure 1.4. 

Sagebrush Steppe

Figure 3.5 illustrates a general state-and-transition model 

for sagebrush steppe ecosystems of the Great Basin. (For other 

general models depicting state-and-transition dynamics of 

sagebrush steppe ecosystems, see Laycock, 1991; Miller and 

others, 1994; West and Young, 2000; Miller and Tausch, 2001; 

and Connelly and others, 2004). The model depicts seven 
Chapter 3: Subsystem Models for the Dry System 45

Table 3.2. Selected attributes of two general types of pinyon-juniper ecosystems compared with areas of potential tree expansion and 

contraction (derived from Romme and others, 2007).

Attributes

General type of pinyon-juniper ecosystem Areas of potential expansion 

and contraction Persistent woodland Pinyon-juniper savanna

Site conditions Soil and climate inherently 

favorable for pinyon and/

or juniper—typically 

shallow, coarse-textured 

soils.

Usually on gentle upland and transitional 

valley locations, where soil conditions 

favor graminoids but can support some 

tree cover—typically moderately deep, 

coarse to fine-textured soils with a large 

percentage of annual precipitation in 

summer.

Only intermittently suitable for pinyon 

and/or juniper, with increased tree 

establishment during moist climatic 

periods or long disturbance-free intervals, 

with subsequent die-back triggered by 

drought, insect outbreaks, or fire—found 

on a wide variety of substrates and 

climatic conditions.

Characteristic 

canopy 

structure

Highly variable, from sparse 

stands of small trees 

on poor substrates to 

relatively dense stands of 

large trees on productive 

sites.

Variable from sparse tree cover limited 

by soil and climate conditions; to 

sparse tree cover limited by herbaceous 

competition, recurrent fire, drought, 

or other disturbances; to denser 

woodlands where tree recruitment has 

increased historically due to release 

from competition, favorable climatic 

conditions, and/or lack of fire.

Fluctuates between shrubland or grassland 

structure and tree dominance.

Characteristic 

understory

Sparse herbaceous cover 

even in absence of 

livestock grazing.

Variety of growth forms including grasses 

and shrubs

Typically shrub dominated.

Disturbance 

regimes and 

dynamics

Typical fire regimes 

characterized by highseverity fire with very long 

rotations (for example, 2 to 

6 centuries); low-severity 

surface fires very rare; 

woodlands often stable for 

many hundreds of years 

with stand dynamics often 

driven more by drought 

and insect outbreaks than 

by fire.

Some savannas may have been maintained 

by relatively frequent low-severity 

surface fires. Livestock grazing and fire 

exclusion are important mechanisms 

responsible for driving the postsettlement conversion of savanna to 

woodland structure in some but not all 

areas. Climatic conditions also have 

played a role in driving vegetation 

changes in at least some areas. 

Interactions and spatial variability in 

these factors are poorly understood.

Livestock grazing and fire exclusion 

probably are important mechanisms 

responsible for driving the postsettlement expansion of trees into some 

grasslands and shrublands, but not all. 

Climate probably has played a role in 

driving these changes in some areas. 

Interactions and spatial variability in 

these factors are poorly understood. 

Tree expansion also occurred in some 

areas prior to Euro-American settlement 

and the phenomenon is not necessarily 

attributable to past land use or fire 

exclusion. Some drought-triggered tree 

mortality has recently occurred on some 

marginal sites.

Distribution Throughout the West, 

but particularly on the 

Colorado Plateau.

Especially prevalent in basins and foothills 

of southern New Mexico, but relatively 

rare in the Rocky Mountains, northern 

Colorado Plateau, and the Great Basin.

Throughout the West, but particularly in the 

Great Basin.

Research needs Develop a better 

understanding of the 

geographic distribution 

of this type in relation to 

environmental factors.

Develop a better understanding of the 

geographic distribution of this type 

in relation to environmental factors; 

disentangle mechanisms driving 

tree expansions in former grasslands 

and savannas (including geographic 

variability).

Develop a better understanding of the 

geographic distribution of this type 

in relation to environmental factors; 

disentangle mechanisms driving tree 

expansions in former grasslands and 

shrublands (including geographic 

variability).
46 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig03-04

Microclimatic modification; 

soil stabilization; resource

capture, retention, & uptake

VEGETATION

Trees, shrubs, perennial

grasses, forbs

Competition and facilitation

REGIONAL CLIMATIC &

ATMOSPHERIC CONDITIONS

Winter-dominated precipitation

with interannual, decadal

and spatial variability

BIOLOGICAL 

SOIL CRUSTS

Mosses, lichens,

cyanobacteria

SOIL RESOURCES

Mineral nutrients, water,

organic matter, soil biota

LANDSCAPE

CONFIGURATION

Spatial configuration

of ecosystem patches

HABITAT QUALITY

Patch level:

Vegetation composition

and structure

Landscape level:

Habitat dimensions,

arrangement, and 

connectivity

WILDLIFE

Obligate and

facultative associates

Competition and

predation

PHYSICAL TEMPLATE

Elevation and

soil-geomorphic

setting

CLIMATIC &

ATMOSPHERIC

CHANGES

FIRE

SUPPRESSION

INVASIVE PLANTS

LIVESTOCK GRAZING

OHV* ACTIVITY

LAND TREATMENTS

NATURAL

DISTURBANCES

Climatic episodes,

insects, and fire

Determines site potential 

and provides 

resource inputs

Evapotranspiration

and energy balance

Determines

site potential

Resource availability

Safe-site availability

Microclimatic modification

Climatic episodes, fire weather, and 

antecedent environmental conditions 

Pollination, herbivory,

granivory, seed dispersal

Habitat dimensions,

arrangement, 

and connectivity

Effects on composition, structure, and spatial configuration of ecosystem patches

Effects on fire behavior

Determines potential

landscape configuration

Vegetation composition

and structure

Effects on 

vegetation composition,

structure, and productivity

Resource

transformation

and redistribution

Resource availability

Soil stabilization,

resource capture

& retention

Soil and vegetation

impacts

Temperatures, CO2 and 

precipitation patterns

Fuel structure and flammability

*OHV = off-highway vehicle

Figure 3.4. Diagram showing control model illustrating key components (rectangles), drivers (ovals), and functional relations 

(arrows) of Great Basin sagebrush steppe and pinyon-juniper ecosystems, including high-priority anthropogenic drivers of ecosystem 

change and variability.

major states or persistent types of ecosystem condition, each 

of which is dynamic (rather than static) with temporal changes 

driven by climatic fluctuations, interactions among natural and 

anthropogenic drivers, and internal processes of change such 

as succession. In the Reference Condition (figure 3.5, Box A—

ideally defined on a site-specific basis according to climate 

and soil-geomorphic setting), biotic and abiotic ecosystem 

components and processes are present and functioning within 

their natural range of variability. These include processes and 

structures that confer resistance and resilience to natural and 

anthropogenic drivers of change, specifically soil structure and 

biological crusts; vegetative structure, species composition and 

competitive interactions; and the natural fire regime defined by 

frequency, intensity and severity. These are discussed in detail 

in the model descriptions below.
Chapter 3: Subsystem Models for the Dry System 47

As suggested above, the concept of “natural” commonly 

is defined on the basis of pre-settlement conditions. But it is 

important to recognize that changes in climate, atmospheric 

CO2 concentrations, and landscape structure will cause future 

ecosystem characteristics to drift away from historic patterns 

of variability even in the absence of local land-use effects, 

leading to the emergence of novel ecosystems characterized 

by new combinations of species and associated changes in 

ecosystem patterns and processes (Hobbs and others, 2006; 

Dukes, 2007; Seastedt and others, 2008). Thus, the concept of 

reference conditions must be sufficiently flexible to account 

for uncertain future environmental trajectories.

Despite uncertainties associated with current and future 

trajectories of change, six additional persistent conditions of 

sagebrush steppe ecosystems are pertinent for purposes of 

management and monitoring (fig. 3.5; table 3.3). Relative to 

reference conditions, five of these (conditions B-F) represent 

differing degrees of alteration attributable to effects of landtype conversions, invasive exotic plants, altered fire regimes, 

and land uses such as livestock grazing and off-road vehicle 

travel. Due to the extent to which sagebrush steppe ecosystems 

have been altered, the integrity of these systems and the 

long-term viability of several associated wildlife species are 

imperiled on a regional basis (Leopold, 1941; Billings, 1990; 

Miller and others, 1994; Noss and others, 1995; Miller and 

Rose, 1999; Beck and Mitchell, 2000; Knick and others, 

2003; Connelly and others, 2004; Thines and others, 2004; 

Welch, 2005; Chambers, 2008). Depending on site-specific 

ecosystem properties and histories (for example, specific 

ecological sites), there may be numerous expressions and 

intergradations of these five basic types of altered sagebrush 

steppe ecosystems. Moreover, it may prove impossible for 

managers to perfectly restore ecosystems once they have been 

changed from the reference conditions, particularly in the 

context of climate change. Condition G (fig. 3.5) represents a 

restored condition that has resistance and resilience but differs 

from the reference condition.

Transition to Dominance by Exotic Annual Grasses.—

Figure 3.6 illustrates multiple drivers and processes that may 

lead to increasing dominance of exotic annual grasses such 

as cheatgrass (Bromus tectorum), red brome (B. rubens) 

and medusahead (Taenatherum caput-medusa) in sagebrush 

steppe and other types of dryland ecosystems. In addition to 

propagule availability (not depicted in the model), safe sites 

(Harper, 1977) and soil resources (water and mineral nutrients) 

are critical factors enabling the establishment and proliferation 

of invasive exotic grasses. Soil disturbance is a primary 

mechanism that increases the availability of safe sites for the 

establishment of exotic annual grasses in sagebrush steppe 

by damaging the functional integrity of biological soil crusts 

(Mack and Thompson, 1982).

Davis and others (2000) proposed a simple conceptual 

model illustrating their hypothesis that an ecosystem becomes 

more susceptible to invasion when there is an increase in the 

amount of resources that otherwise limit invasion. According 

to this model, factors that cause a pulse in resource supply 

(for example, precipitation events or fire) or a reduction 

in resource uptake (for example, episodic mortality of 

community dominants) may enable the rapid population 

expansion of responsive invaders that previously existed in the 

ecosystem at low levels. Other workers also have emphasized 

the importance of temporal and spatial patterns of resource 

availability as factors affecting ecosystem susceptibility to 

invasion and dominance by exotic species (Johnstone, 1986; 

With, 2002), including patterns of cheatgrass invasion in 

sagebrush steppe ecosystems of the Great Basin (Chambers 

and others, 2007; Norton and others, 2007). 

Transition to Dominance by Trees.—“Encroachment” 

and increasing dominance of trees and/or shrubs in grasslands, 

savannas, and shrubsteppe vegetation is one of the most 

widely documented patterns of vegetation change in dryland 

ecosystems around the world (Archer, 1994; Miller and Rose, 

1999; Archer and Stokes, 2000). Factors proposed most 

commonly as explanatory mechanisms include excessive 

grazing by domestic livestock, fire-suppression efforts, and 

climate (fig. 3.7). Elevated atmospheric CO2 also has been 

suggested as a factor (Polley and others, 1996, 1997), although 

Archer and others (1995) argued that CO2 enrichment is an 

insufficient explanation for observed patterns of vegetation 

dynamics. Climate plays an important role due to effects on 

population dynamics and competitive relations of herbaceous 

versus woody plants, but persistent excessive grazing by 

domestic livestock generally has been implicated as the most 

important driver of transitions involving increasing dominance 

of unpalatable woody plants (Archer and others, 1995). 

Selective herbivory can affect the competitive relationships of 

plants, favoring the establishment and growth of unpalatable 

plants over those of palatable plants (Briske and Richards, 

1994). The reduction of aboveground herbaceous biomass 

and litter by grazing also can reduce the availability of fine 

fuels required to support a regime of frequent surface fires. 

Where such a fire regime is important for constraining the 

dominance of fire-intolerant woody vegetation, the removal 

of fine fuels by grazing may be more important than reduced 

herbaceous competition or fire-suppression efforts as a driver 

of ecosystem change (Archer, 1994; Archer and others, 1995). 

These same factors have been proposed as mechanisms 

enabling increases in tree establishment in sagebrush steppe 

ecosystems of the Great Basin (Miller and Tausch, 2001; 

Miller and others, 2005). In shrubsteppe ecosystems, tree 

establishment also can be facilitated by shrubs that ameliorate 

environmental conditions experienced by tree seedlings 

(Chambers, 2001). Fire-regime alteration has been suggested 

as a major driver of tree encroachment in the Great Basin 

(Miller and Tausch, 2001; Miller and others, 2005), but spatial 

variability in the relative importance of this factor is poorly 

understood (Baker, 2006; Romme and others, 2007).
48 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig03-05

Succession

Drought, insects

Fire/drought,

insects

Succession

Fire/drought,

insects

D. EXOTIC-DOMINATED

CONDITION

Degraded habitat quality; 

degraded resistance/resilience to fire,

drought, and other disturbances;

accelerated erosion

High-frequency

FIRE

Exotic

annual grasses

A. REFERENCE CONDITION: SAGE-STEPPE

Dynamic landscape mosaic; resilient to fire, drought, and other

disturbances; resistant to erosion; provides high-quality habitat

C. INTRODUCED SEEDING

Degraded habitat quality; depleted native

seedbank; degraded soil stability and 

hydrologic function?

Degraded resistance/resilience

to drought, & other disturbances?

Introduced

pasture grasses

F. SEVERELY ERODED

CONDITION

Significant loss/redistribution

of soil resources; site potential

degraded beyond repair

Diverse & productive plant community

composed of sagebrush, native 

perennial grasses, forbs, and 

biological soil crusts

Fluctuating composition in 

G. RESTORED CONDITION

relation to climate and land use

Resistant and resilient to fire, drought, 

and other disturbances; stable soil and 

proper hydrologic function; provides 

high-quality habitat

Pinyon/Juniper

Sagebrush

Exotic grasses/forbs

Thickening woodland

Exotic grasses/forbs

Succession

E. TREE-DOMINATED

CONDITION

Degraded habitat quality;

degraded resistance/ 

resilience to fire, drought, 

and other disturbances;

accelerated erosion 

Fluctuating relative abundance

in relation to climate and land use

Sagebrush

Exotic annual grasses

Sparse native grasses/forbs

Scattered trees

B. DEGRADED SAGE-STEPPE

Depleted native seedbank; degraded 

habitat quality; high frequency/abundance 

of exotic annual grasses; degraded soil 

stability and hydrologic function; degraded 

resistance/ resilience to fire, drought, and 

other disturbances

Native annual and perennial herbs

Biological soil crusts

Sagebrush

Perennial grasses and forbs

Biological soil crusts

Sagebrush

Biological soil crusts

Climate

change 

?

Designer ecosystems?

Climate

change 

Drought and

continuous erosion

Continuous erosion and

catastrophic fire/drought

Continued tree recruitment,

soil-surface disturbances,

herbivory, and

long-term absence of fire

Catastrophic overstory mortality

due to fire, drought, insects

OR unsuccessful

land treatment?

Soil-surface disturbances,

continuous erosion, and

catastrophic shrub/tree mortality

OR unsuccessful

land treatment?

Soil-surface disturbance, exotic species introduction,

excessive herbivory, tree establishment

Land

treatment

Catastrophic fire

and / or drought

Land treatment

Land treatmentLand treatmentLand treatment

Land treatment

Excessive herbivory and soil impacts;

grass mortality, continuous erosion

Excessive herbivory,

perennial grass mortality

OR unsuccessful

land treatment?

OR unsuccessful

land treatment?

OR unsuccessful

land treatment?

ExplanationManager’s concepts of reference conditions and restoration targets will need to be increasingly flexible  due to uncertain future environmental conditions attributable to changes in climate and atmospheric  CO2 concentrations.

Conditions that typically are most desirable from a management perspectiveIntermediate conditions that may continue to meet some but not all management objectivesConditions that are least desirable

Figure 3.5. General state-and-transition model for sagebrush steppe ecosystems of the Great Basin. 
Chapter 3: Subsystem Models for the Dry System 49

Table 3.3. Characteristics of six general persistent conditions of sagebrush steppe ecosystems in the Great Basin. 

[Letters B-G refer to boxes depicted in figure 3.5]

State General characteristics

B. Degraded sage-brush steppe Dominated vegetatively by sagebrush with an understory of exotic annual grasses. Native understory plants 

and the associated soil seed bank have been depleted by excessive herbivory. Biological soil crusts and 

associated ecosystem functions (soil stabilization, nutrient cycling, hydrologic processes, resistance to 

exotic annual grass establishment) have been degraded due to soil-surface disturbances. As a consequence, 

resilience to natural disturbances and anthropogenic drivers is degraded—thereby increasing risks of 

further degradation.

C. Introduced seeding Dominated by nonnative forage grasses such as crested wheatgrass (Agropyron cristatum), resulting from 

previous efforts to increase livestock forage or otherwise improve degraded rangeland conditions (Pellant 

and Lysne, 2005). Native plant diversity and habitat quality for native wildlife species typically are low 

relative to reference conditions for sagebrush steppe.

D. Exotic dominated Dominated by exotic annual grasses such as cheatgrass and typically perpetuated by a positive feedback 

between annual grass dominance and the occurrence of high-frequency surface fires (for example, 

D’Antonio and Vitousek, 1992; Brooks and others, 2004). Habitat quality and native biodiversity are low 

relative to reference conditions, and the potential for accelerated erosion may be high if ground cover 

provided by annual grass populations fluctuates strongly in relation to climate.

E. Tree dominated Represents a transition from shrubsteppe vegetation structure to woodland vegetation structure. Associated 

with this major structural change, habitat conditions and the functioning of key ecosystem processes (for 

example, disturbance regimes, rates of geomorphic and biogeochemical processes) also are significantly 

altered relative to reference conditions. Resistance to drought and high-severity wildfire may be reduced, 

potentially resulting in increased risk of severe erosion or conversion to dominance by exotic annual 

grasses (West, 1999).

F. Severely eroded Characterized by an extreme loss or alteration of soil resources and biogeochemical / hydrologic processes. 

Site conditions have been altered to the degree that characteristic species can no longer be supported on 

the site. 

G. Restored Results from successful ecological restoration of key ecosystem components and processes that are required 

for long-term sustainability of an ecosystem that is structurally and functionally similar to the reference 

condition. Depending on site history (for example, legacies of past land-use activities), as well as on 

ecological and socioeconomic constraints to restoration, it may not be possible to fully restore the 

damaged ecosystem to reference conditions. But a successfully restored ecosystem should be able to 

sustain a wide range of valued ecosystem services without further management intervention. As with the 

reference condition, the prospects of changing climatic and atmospheric conditions indicate the need for a 

flexible notion of restoration targets. Legacies of past land-use activities, multiple management objectives, 

and shifting concepts of reference conditions and restoration targets suggest that managers and restoration 

practitioners will increasingly be developing “designer ecosystems” as they seek to restore native diversity 

and resilience to damaged ecosystems (Pimm, 1996; Palmer and others, 2006; Seastedt and others, 2008).
50 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig03-06

Biological

soil crusts

Resource availability/

enrichment

Safe-site

availability

Exotic annual grass

recruitment, growth

and reproduction

Fine surface

fuels

Frequency of

surface fire

DOMINANCE BY

EXOTIC ANNUAL GRASSES

LIVESTOCK

CONCENTRATIONS

(Excretion)

CLIMATE VARIABILITY

AND CHANGE

WILDFIRE AND/OR

MANAGEMENTPRESCRIBED FIRE

EXCESSIVE GRAZING

(Herbivory)

MECHANICAL LAND

TREATMENTS

OHV ACTIVITY,

TRAMPLING AND OTHER

SOIL-SURFACE

DISTURBANCES

SOIL-RESOURCE TRANSFERS

FROM ADJACENT SITES

(Soil, nutrients, water)

CATASTROPHIC OVERSTORY

MORTALITY DUE TO FIRE,

INSECTS, OR DROUGHT

ATMOSPHERIC

NITROGEN DEPOSITION

AND CO2 ENRICHMENT

Dry Wet

?

Competition

Compaction

Soil aggregate

stability

Cover/vigor

of perennial grasses Litter

accumulation

Figure 3.6. Stressor model illustrating multiple drivers and processes that may lead to increasing dominance of dryland ecosystems by exotic annual grasses. Question marks 

indicate uncertainty regarding the relative importance of particular factors.
Chapter 3: Subsystem Models for the Dry System 

51

tac09-0397_fig03-07

TREE RECRUITMENT

AND DOMINANCE

CLIMATE VARIABILITY

AND CHANGE EXCESSIVE GRAZING

FIRE

SUPPRESSION

ATMOSPHERIC CO2

ENRICHMENT

Frequency of

surface fire

Fine surface

fuels

Cover/vigor of

perennial grasses

?

?

Seed production

and dispersal

Shrub recruitment

and dominance

?

?

Facilitation?

Competition? Competition? Wet

Dry

Figure 3.7. Stressor model illustrating multiple drivers and processes that may lead to increasing tree recruitment and dominance in sagebrush steppe ecosystems. Question 

marks indicate uncertainty regarding the relative importance of particular factors.
52 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Soil Erosion and Loss of Site Potential.—Figure 3.8

illustrates multiple drivers and processes that may lead to 

increasing rates of soil loss and redistribution in sagebrush 

steppe and other types of dryland ecosystems. Soil resources 

can be eroded and redistributed by wind and water. The 

relative importance of wind- versus water-driven erosion 

depends on soil properties, topography, vegetation structure, 

and the relative frequency and magnitude of erosive wind 

versus precipitation events (Breshears and others, 2003). Wind 

erosion has been determined to greatly exceed water erosion 

in some shrubland ecosystems (Breshears and others, 2003), 

although such comparisons have not been conducted for 

sagebrush steppe.

Whether wind or water is the driving force, factors 

leading to accelerated rates of soil erosion and redistribution 

are similar. Trampling and other soil-surface disturbances 

reduce soil stability by disrupting biological soil crusts that 

protect and retain soils against erosive forces of wind, rain, 

and runoff (Williams and others, 1995a; Belnap and Gillette, 

1998; Okin and others, 2001). Soil-surface disturbances 

also disrupt stable soil aggregates that enhance soil stability 

and soil infiltration capacity (Thurow, 1991). By reducing 

herbaceous cover and organic-matter inputs from litter and 

roots, excessive grazing can diminish soil protection and soil 

aggregate stability (Thurow, 1991). Decreases in vegetative 

ground cover and biological soil crusts also can result in 

accelerated erosion due to diminished capacity to obstruct 

erosive wind and overland flow of water (Davenport and 

others, 1998; Reid and others, 1999; Ludwig and Tongway, 

2000). Yeo (2005) examined vegetation and soil-surface 

properties inside and outside 19 long-term grazing exclosures 

in sagebrush steppe and salt desert scrub in east central Idaho 

and determined that erosional features (for example, pedestals 

and evidence of soil movement and overland water flow) were 

more pronounced outside the exclosures—indicating greater 

soil stability and hydrologic functioning inside exclosures 

where interspaces were no longer subject to trampling by 

livestock. Increasing dominance of shrubs and trees may result 

in accelerated rates of runoff and erosion due to competitive 

reductions in herbaceous ground cover and its capacity to 

stabilize soils, obstruct overland flow, and capture sediment in 

interspaces among woody plants (Wilcox and others, 1996). 

This process may be accelerated further where intercanopy 

soil-surface disturbances increase the connectivity of flow 

paths on hillslopes and reduce the capacity of shrub or tree 

mounds to capture overland flow (Spaeth and others, 1996; 

Eldridge and Rosentreter, 2004). In some settings, relatively 

small reductions in herbaceous ground cover may trigger 

large increases in runoff and erosion (Davenport and others, 

1998). Factors contributing to the occurrence of such erosion 

thresholds include soil structure, texture and rock content; 

slope length and gradient; and the spatial distribution of 

vegetation patches, biological soil crusts, and other features 

that control the connectivity of flow paths (Davenport and 

others, 1998).

Increasing dominance of exotic annual grasses, 

mechanical land treatments, and fire also may result in 

accelerated soil loss. Relative to perennial plants and 

biological soil crusts, annual plants are likely to experience 

greater climate-driven fluctuations in cover. Thus, dominance 

by annuals may result in greater exposure of bare ground to 

erosive forces of wind and water during drought periods if 

annuals fail to germinate. Mechanical land treatments, such as 

use of an anchor chain or pipe harrow (Stevens and Monsen, 

2004), can have multiple effects on erosional processes. Where 

such treatments are conducted to remove intact vegetation, 

reductions in vegetation structure and associated soil 

disturbance may result in significant short-term increases in 

soil erosion by wind. Treatments may reduce erosion by water 

where they disrupt existing flow paths, enhance soil-surface 

roughness, and thus facilitate retention of overland water flow. 

However, net effects of treatments on soil loss will depend on 

factors that determine the relative magnitude of water- versus 

wind-driven erosion as well as long-term treatment effects on 

vegetation cover and soil stability. Although most treatments 

are undertaken with the intent of reducing soil loss through 

long-term increases in cover of perennial grasses, monitoring 

efforts rarely are adequate for evaluating short- versus longterm treatment effects. Similarly, removal of vegetation by fire 

can generate large increases in soil erosion by wind (Whicker 

and others, 2002) and water (Johansen and others, 2001), 

but net effects on soil loss will depend on rates of post-fire 

vegetation recovery, soil properties, and topographic setting. 

Finally, climate plays a key role in erosion due to effects on 

vegetation cover (for example, rates of post-treatment and 

post-fire vegetation responses) and the frequency of erosive 

wind and precipitation events. As soil resources are lost due 

to erosional processes, declining resource availability may 

generate a positive feedback that facilitates further decreases 

in vegetative ground cover and further increases in erosion 

(for example, Friedel and others, 2003; Sparrow and others, 

2003; Tongway and others, 2003).

Pinyon-Juniper Woodlands

Figure 3.9 illustrates a general state-and-transition model 

for pinyon-juniper ecosystems (persistent-woodland types) of 

the Great Basin. The structure of the model is similar to that 

depicted for sagebrush steppe ecosystems, with the Reference 

Condition (fig. 3.9, Box A) characterized by biotic and abiotic 

ecosystem components and processes present and functioning 

within their natural range of variability, but potentially 

drifting away from historic conditions due to effects of 

changing climate and atmospheric CO2 concentrations. 

The model depicts four additional persistent conditions of 

pinyon-juniper ecosystems. Key characteristics of a degraded 

woodland (fig. 3.9, Box B) are altered understory plant 

community composition (shift in relative dominance from 

native perennial grasses and shrubs to dominance by exotic 

annual grasses), a depleted native seedbank, and loss of soil 
Chapter 3: Subsystem Models for the Dry System 

53

tac09-0397_fig03-08

Compaction Infiltration

Fluctuations in herbaceous

production and ground

cover due to climate

Soil detachment

and transport

Runoff

Bare

ground

Vegetative

cover

Biological soil

crust cover

Resource

availability

Soil protection

from raindrop

impact

Soil aggregate

stability

Sediment capture

and retention

Wind/water

obstruction

CLIMATE VARIABILITY

AND CHANGE

Reduced water availability: Conifer Forest Fragmentation and Loss

Short-term versus

long-term effects?

Wind

Water

Perennial grasses

in interspaces

Drought Perennial grasses in interspaces Erosive wind and precipitation events

EROSION AND

REDISTRIBUTION OF

SOIL RESOURCES

DOMINANCE BY

SHRUBS AND TREES

DOMINANCE BY

EXOTIC ANNUAL

GRASSES

WILDFIRE AND/OR

MANAGEMENTPRESCRIBED FIRE

EXCESSIVE GRAZING

MECHANICAL LAND

TREATMENTS

OHV ACTIVITY,

TRAMPLING AND OTHER

SOIL-SURFACE

DISTURBANCES

Figure 3.8. Stressor model illustrating multiple drivers and processes that may lead to increasing erosion and redistribution of soil resources in dryland ecosystems.
54 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig03-09

Succession

Drought, insects

Fire/drought,

insects

Succession

Fire/drought,

insects

C. EXOTIC-DOMINATED

CONDITION

Degraded habitat quality; 

degraded resistance/resilience to fire,

drought, and other disturbances;

accelerated erosion

High-frequency

FIRE

Exotic

annual grasses A. REFERENCE CONDITION: PERSISTENT WOODLAND

Resilient to fire, drought, and other disturbances; 

resistant to erosion

D. SEVERELY ERODED

CONDITION

Significant loss/redistribution

of soil resources

Site potential degraded

beyond repair

Sparse woodland;

diverse/productive native understory,

biological soil crusts

Fluctuating composition in 

E. RESTORED CONDITION

relation to climate and land use

Resistant and resilient to fire, drought, 

and other disturbances; stable soil and 

proper hydrologic function

Successional trend toward increasing

Dense woodland

tree dominance

Exotic annual grasses

Sparse native understory

B. DEGRADED WOODLAND

Depleted native seedbank; declining 

understory vegetation; degraded soil 

stability and hydrologic function; diminished 

resistance/resilience to fire, drought, and 

other disturbances

Native annual and perennial herbs

Biological soil crusts

Mixed shrubs, sparse trees

Perennial grasses and forbs

Biological soil crusts

Dense woodland

Biological soil crusts

Climate

change 

?

Designer ecosystems?

Climate

change 

ExplanationManager’s concepts of reference conditions and restoration targets will need to be increasingly flexible  due to uncertain future environmental conditions attributable to changes in climate and atmospheric  CO2 concentrations.

Conditions that typically are most desirable from a management perspectiveIntermediate conditions that may continue to meet some but not all management objectivesConditions that are least desirable

Drought and

continuous erosion

Catastrophic overstory mortality

due to fire, drought, insects

OR unsuccessful

land treatment?

Soil-surface disturbances,

continuous erosion, and

catastrophic overstory mortality

OR unsuccessful

land treatment?

Soil-surface disturbance, exotic species introduction,

excessive herbivory, increasing tree dominance

Land

treatment

Land treatment

Figure 3.9. General state-and-transition model for pinyon-juniper (persistent woodland) ecosystems of the Great Basin. Dashed boxes associated with the reference (

A) 

and restored (

D) condition indicate that managers’ concepts of reference conditions and restoration targets will need to be increasingly flexible due to uncertain future 

environmental conditions attributable to changes in climate and atmospheric CO2 concentrations.
Chapter 3: Subsystem Models for the Dry System 55

stability due to soil-surface disturbances. As a consequence 

of altered understory composition, resilience to drivers such 

as high-severity fire is reduced and the risk of conversion 

to dominance by exotic annual grasses is increased relative 

to the reference condition (West, 1999; Romme and others, 

2003)—even if high-severity fire is considered to be “natural” 

for pinyon-juniper ecosystems. Processes leading to increasing 

dominance by exotic annual grasses (fig. 3.6) and to soil 

erosion and redistribution (fig. 3.8) are similar to those 

described for sagebrush steppe ecosystems. Depending on sitespecific ecosystem properties (for example, specific pinyonjuniper ecological sites), there may be numerous expressions 

and intergradations of these basic types of altered or degraded 

pinyon-juniper ecosystems.

Summary Points

Sagebrush steppe and pinyon-juniper woodlands 

together account for about 60 percent of the land area in the 

Great Basin. These ecosystems are dominated by varying 

proportions of shrubs, perennial grasses, and other herbaceous 

plants, trees, and biological soil crusts, and they provide 

numerous benefits to society including habitat for valued 

wildlife species, livestock forage, fuel wood, watershed 

services, and recreational opportunities. The capacity of 

these systems to provide this suite of benefits is threatened 

by numerous processes that can lead to persistent alterations 

in vegetation composition and structure, soil resources, 

and patterns of ecosystem dynamics. In sagebrush steppe, 

dominance by invasive exotic grasses and dominance by 

encroaching tree populations are the two most persistent 

and pervasive vegetation changes that have had widespread 

implications for ecosystem dynamics and management. 

In pinyon-juniper woodlands, increasing dominance by 

invasive exotic plants likewise has significant management 

implications through potential effects on risks attributable 

to wildland fire. Some of the most important anthropogenic 

stressors that contribute to the occurrence of these persistent 

changes include excessive herbivory by livestock, altered fire 

regimes, and soil-surface disturbances by livestock trampling 

and off-highway vehicle use. Ecosystem responses to these 

and other anthropogenic factors commonly depend on climatic 

conditions and natural disturbance regimes. Projecting the 

future dynamics and condition of these ecosystems over the 

next 50 years is hampered by the need to better understand 

effects of changing climatic conditions and atmospheric CO2

concentrations on soil resources, competitive relations among 

plants, and fire regimes. Future dynamics and condition of 

these ecosystems also are hampered by a need to understand 

how ecosystems responses to the interactive effects of climate 

and land use vary spatially in relation to soil-geomorphic 

properties, landscape configuration, and patterns of human 

growth and infrastructural development. 

Aspen Forests

In the Great Basin, aspen forests grow in relatively 

pure stands associated with upland riparian corridors and in 

‘snow pockets’ where delayed snowmelt results in mesic soil 

conditions later into the growing season. In both situations 

aspen forest stands tend to be small (≤ 8 ha) and individual 

trees often do not meet their growth potential due to 

environmental limitations. Nevertheless, aspen groves provide 

valuable habitat for a range of species, most notably cavity 

nesting birds and bats (DeByle and Winokur, 1985; Dobkin 

and others, 1995; Parsons and others, 2003) and also provide 

valuable forage. Aspen most commonly regenerates by 

means of vegetative sprouting from the root system following 

disturbances, such as a fire that kills the mature trees. 

However, rare episodes of seedling recruitment occur (Jelinski 

and Cheliak, 1992). Aspen stands appear to be decreasing 

across the west (for example, Beever and others, 2005). 

Fire suppression has been identified as the most widespread 

proximal factor, but elk browsing and domestic cattle grazing 

also have been recognized (Rogers, 2002; Larsen and Ripple, 

2003). Developing a specific set of conceptual models for this 

system is beyond the scope of this study.

Mixed Conifer Forest Model 

By S.P. Finn

Distribution and Management Significance

Coniferous forests (excluding pinyon-juniper woodlands) 

cover 4.4 percent of the Great Basin landscape (derived 

from Kuchler, 1970), typically at high elevations on many 

of the 300+ interior mountain ranges and in the Sierra, 

Cascade, Wasatch, and other ranges that form the west, 

north, and east margins. Interior forest stands are patchily 

distributed at the coarse-scale whereas peripheral stands 

are more continuous and grade into other forest-types in 

adjacent ecoregions (Cronquist and others, 1972). In spite 

of their limited distribution, Great Basin forests contribute 

significantly to the biodiversity of the ecoregion; a host of 

plants, animals, and fungi closely linked with coniferous 

forest structure and microclimate are not found in other 

Great Basin systems. In the arid Great Basin, the distribution 

of vegetative communities primarily is determined by soil 

moisture, which is a function of the amount and timing of 

precipitation, insolation, geomorphic setting, elevation, 

and local soil properties. Coniferous forest replaces lowerelevation woodland and shrubland cover-types only where 

water is abundant enough in the soil-root zone during the 

growing season such that the balance between soil moisture, 

groundwater, and transpiration favors evergreen trees (Charlet, 

1996). Forests are limited at their upper elevational bound 

by the extreme weather (strong winds, blowing ice, winter 

drought) and late season snow cover of the alpine tundra 

(Stevens and Fox, 1991; Sveinbjornsson, 2000).
56 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Across the region, conifer forest stands are isolated 

by arid, shrub-dominated basins. Their present location is 

the result of either long-term climate trends that favored 

shrubland and grassland cover types at low elevations (Martin 

and Mehringer, 1965), or bird-aided conifer seed dispersal to 

suitable high-elevation growing locations that were (and are) 

separated by inhospitable interstices (Wells and Berger, 1967). 

Currently, the position of interior conifer forest patches on the 

Great Basin landscape is not unlike an archipelago of oceanic 

islands. The arrangement presents an ideal backdrop for 

natural experiments in continental island biogeography (Wells, 

1983; Brown, 1978), as well as potential dispersal barriers for 

the many low-vagility plant and animal species that inhabit 

forest patches. The literature suggests that some borealassociated trees are capable of direct or bird-aided dispersal 

among mountain ranges (Wells, 1983). More vagile species of 

birds (Behle, 1978), mammals (Skaggs and Boecklen, 1996; 

Lawlor, 1998), and butterflies (Wilcox and others, 1986) 

also are capable of dispersal among isolated forest patches 

(Brown, 1971). However, individuals of many less-mobile 

taxa, including some birds and butterflies, are not likely to 

cross the vast shrubland matrix surrounding montane forest 

patches. Some of these disjunct or isolated populations may be 

particularly vulnerable to extirpation because they are unlikely 

to receive immigrants from nearby patches (Brown, 1971; 

Johnson, 1975; Wilcox and others, 1986; Beever and others, 

2003; Grayson, 2005). Thus, changes in the rates or intensities 

of ecosystem drivers, like climate change or fire regime, that 

influence the location or continuity of Great Basin coniferous 

forests may have significant effects on the composition and 

diversity of associated biota.

Nearly all Great Basin forests are managed by the U.S. 

Forest Service (USFS) or BLM for multiple uses. Great Basin 

National Park is managed to conserve its natural and historic 

value and provide for visitor enjoyment. Historically, most 

forests in the region were heavily logged between 1860

–1890 when nearly all merchantable timber was harvested for 

mining and homesteading (M. Hampton, U.S. Forest Service, 

oral commun., 2008). Commercial timber harvest continues 

only in forests along the boundary and a few interior forests 

in southeast Oregon. Great Basin forests also produce wood 

for fuel and other local uses, livestock forage, watershed and 

ecosystem services, and a variety of recreational opportunities. 

Forests positioned on or near other desirable resources (for 

example, mineral deposits or wind energy potential) may 

be altered as a consequence of commodity production and 

transport.

Components and Processes

Climate and the Physical Template – Determinants of Site 

Potential

Interactions among a suite of abiotic factors (climate, 

elevation, landform, geology, and soils) determine the 

potential vegetative structure of a given site (Jenny, 1980; 

Long, 2003) and form integral portions of our conifer forest 

subsystem model (fig. 3.10). 

Conifer forests in the Great Basin typically are found on 

sedimentary (limestone, dolomite, sandstone, siltstone) and 

igneous (rhyolite, andesite, basalt, granite) parent materials 

that mostly arose from continental rock uplifted in fault-block 

mountain ranges (Hunt, 1974). Those formations tend to be 

highly stable through human time scales, but forests also can 

develop locally on alluvium and colluvium, which are more 

prone to short-term geomorphic change and disturbances. 

In the Basin and Range Province, these landforms have 

been repeatedly modified during recurrent periods of active 

erosion and deposition as well as by soil formation during 

periods of greater landscape stability (Peterson, 1981). Spatial 

patterning of soil properties such as depth, particle size, and 

degree of profile development are highly complex across the 

landscape (Peterson, 1981). Coniferous forests are supported 

by a diversity of parent materials, landforms, and soils that 

complicate generalizations made about their physical and 

biotic characteristics. Different types of soils and plant 

communities tend to be associated with different landforms 

as well as with finer-scale elements of landforms (Peterson, 

1981; Monger and Bestelmeyer, 2006).

Climatic factors are dynamic over much shorter temporal 

scales than topography and geology and therefore exert more 

proximate influences on the location and composition of Great 

Basin coniferous forest. Timing of precipitation is important 

to vegetative cover because it influences the annual hydrologic 

budget that determines factors such as soil moisture and 

evapotranspiration rates. Precipitation arrives primarily as 

winter snow throughout much of the region (Bailey, 1995) but 

the eastern part of the Great Basin often receives monsoon 

rainfall concentrated in late summer (Tyler and others, 1996). 

In the Great Basin, coniferous forests generally are found only 

on sites where average annual precipitation exceeds about 25 

cm on south-facing slopes and about 17 cm on north-facing 

slopes (fig. 3.11). Climate effects, however, are mediated by 

elevation and landform. Increasing elevation generally leads 

to an increase in precipitation, solar radiation, and wind and a 

decrease in temperature (Peet, 2000). Temperature and solar 

radiation, among other climate variables, also are influenced 

by slope-aspect. For example, south-facing slopes tend to 

be drier and conifer forests there lie at higher elevations 

(fig. 2.13). Climate trends and climatic contributions to trends 

in other drivers (for example, fire regime) over the next 

50+ years are likely to exert the most significant influence on 

Great Basin coniferous forest ecology. 
Chapter 3: Subsystem Models for the Dry System 57

FOREST VEGETATION

Trees, shrubs, grasses, forbs

(Primary productivity,

species composition,

competition, turnover,

mutualism

SOIL RESOURCES

Mineral nutrients, water,

organic matter, soil biota

LANDSCAPE

CONFIGURATION

Spatial configuration

of ecosystem patches;

patch isolation

HABITAT QUALITY

Vegetation composition,

configuration, structure,

function

PHYSICAL TEMPLATE

Elevation, slope, aspect,

soil-geomorphic

setting

CLIMATIC &

ATMOSPHERIC

CHANGES

FIRE

SUPPRESSION

INSECT OUTBREAKS

LIVESTOCK GRAZING

MOTOR VEHICLE USE

INVASIVE PLANTS

WILDLIFE

Mammals, birds, reptiles, 

amphibians, fish, 

invertebrates

(Genetic diversity, species 

richness, breeding success, 

energetics) 

ATMOSPHERIC &

CLIMATIC CONDITIONS

Cyclonic, orographic, and monsoonal

systems with interanual, decadal

variation and site-specific

patterns

NATURAL

DISTURBANCES

Climatic Episodes

(Lightning, high winds, drought)

Wildfire

(Frequency, severity, fuel loads)

Insects and Disease

Determines site potential 

and provides 

resource inputs

Resource availability

Climatic episodes, fire weather, and 

antecedent environmental conditions 

Fuel structure and flammability

Modify composition,

structure, and productivity

Habitat dimensions,

arrangement, 

and connectivity

Affects fire behavior

Determines potential

landscape configuration

Vegetation composition

and structure

Resource transformation

and redistribution

Soil and vegetation

impacts

Temperatures, CO2 and 

precipitation patterns

Soil stabilization; resource

capture and retention,

Determines site potential;

Topographic-moisture gradient,

Parent material geochemistry

Seed dispersal routes & barriers, 

gene flowgenetic drift, extirpation

Pollination, herbivory,

granivory, seed dispersal

Modifies landscape configuration through effects on vegetation composition and structure

Figure 3.10. Conifer Forest Control Model illustrating key structural components (green rectangles), primary natural (blue oval) and 

anthropogenic (orange ovals) drivers, and functional relations (arrows) of Great Basin forest ecosystems. Heavy arrows indicate more 

important functional relations. Hypothetical alternate states that emphasize mountain sagebrush, mountain mahogany, aspen, or several 

conifer mixes, are indicated by the multiple dashed boxes for Forest Vegetation. States may change due to disturbances, climate 

variation, pest outbreaks, etc.
58 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Figure 3.11. Coniferous and aspen forest distribution in the Great Basin is highly correlated with precipitation as shown here in the 

Schell Creek Range of eastern Nevada. Precipitation data from PRISM Group (2004).

tac09-0397_fig03-11

114°50' 114°45' 114°40' 114°35' 114°30'

39°

30'

39°

25'

39°

20'

39°

15'

39°

10'

8

10

12

14

16

10

10

12

14

14

12

10

16

18

20

22

12

24

26 28 30 32

34

34

36

Precipitation zones, in centimeters per year (10 = contour value)

Forest cover

Evergreen forest Rocky Mountain

aspen forest

Less than 11 11.1 to 17 17.1 to 23 23.1 to 31 31.1 to 47

Nevada

0 2 4 MILES

0 2 4 KILOMETERS

EXPLANATION

Great

Basin

NP

Ely
Chapter 3: Subsystem Models for the Dry System 59

Vegetation, Soil, and Wildlife Resources

Vegetation.—Great Basin coniferous forest overstories 

are composed of a mix of tree species originating from Rocky 

Mountain or Sierra Nevada floras. In some places, relatively 

monotypic stands occur (Burns and Honkala, 1990; Charlet, 

1996). Tree species richness generally decreases as distance 

from the western Rocky Mountains increases (Hamrick and 

others, 1994). Of the 15 species of Pinaceae in the Great 

Basin, ponderosa pine (Pinus ponderosa), limber pine (Pinus 

flexilis), and white fir (Abies concolor) are the most widely 

distributed (Pase and Brown, 1994; Charlet, 1996). In some 

places, fire adapted stands (that is, mature ponderosa pine) 

are being replaced by shade-tolerant species (that is, white 

fir) in part as a result of aggressive fire suppression. Douglas 

fir (Pseudotsuga menziesii) and Engelmann spruce (Picea 

engelmannii) are important components in some areas, for 

example Great Basin National Park. Bristlecone pine (Pinus 

longaeva), a species noted for its longevity, is an important 

constituent of the conifer community in many southern Great 

Basin mountain ranges. Bristlecone pine trees usually exist in 

open stands between 2,700 and 3,500 m elevation on exposed 

rocky sites above more densely stocked forest. At lower 

elevations and in mesic snow pockets, mixed conifer forests 

commonly include patches of deciduous trees dominated by 

quaking aspen (Populus tremuloides). Understory vegetation 

is an important part of the forest ecosystem although the 

composition and density varies with overstory species 

composition and closure and site disturbance regimes. 

Understories generally are composed of conifer seedlings, 

grasses (Poa spp., Pseudoroegneria spicata), forbs (Lupinus 

spp., Voila spp.), and shrubs (Ribes spp., Symphoricarpos 

spp.) growing most densely in canopy gaps. Shade intolerant 

shrubs such as mountain big sagebrush (Artemisia tridentata 

vaseyana) and mountain mahogany (Cercocarpus ledifolius) 

may play successional roles in forest development or arise 

as alternate stable states in place of conifer forest (fig. 3.10). 

Other shrubby trees include dwarf maple (Acer glabrum), 

which grows in moist shady areas with broken canopy 

between 1,500 and 2,400 m, and serviceberry (Amelanchier

spp.) most commonly found on shaded north-facing slopes.

Vascular plants perform many important functions in 

Great Basin forests. Their presence forestalls erosive effects 

of wind and precipitation; enhances the capture of nutrients, 

seeds and surface water; provides copious amounts of organic 

matter to the soil; and generates oxygen during photosynthesis. 

Additional functions performed by forest vegetation include 

sequestration of carbon, mediation of microclimates, and 

functions within the hydrological cycle. Large woody plants 

also provide coarse fuel which, in the arid Great Basin, 

retain relatively little moisture and are characterized by slow 

decomposition rates. Conifer trees and other forest vegetation 

provide food and shelter to a broad range of consumers and 

detritivores.

Soils.—Soils and soil development are intricately tied 

to the vegetation community they support. Extant vegetation 

often is a critical contributor to the upper soil horizon where 

most biological activity in soils occurs. Ultimately, however, 

soils are a product of the underlying parent material that 

largely determines the chemical and physical properties of 

the soil. Soils supporting Great Basin coniferous forests tend 

to be gravelly to very gravelly loams and silt loams that have 

moderate to high permeability, and range from very shallow 

to deep. Mollisols, in the form of Xerolls and Ustolls, are 

dominant on Great Basin mountain slopes (U.S. Department 

of Agriculture, 1998). Xerolls are freely drained Mollisols 

found in parts of California, Idaho, Nevada, and western 

Utah. Xerolls tend to be dry for extended periods in summer, 

but moisture moves through most of the soils in winter and 

is stored above the deep layers or above bedrock in normal 

years. Ustolls (also known as Borolls) are Mollisols of the 

cold-winter semi-arid plains and steppes; they are associated 

with monsoonal precipitation patterns in the eastern part of the 

region. Xerolls and Ustolls tend to have a xeric, aridic, or ustic 

moisture regime, meaning limited amounts of soil water may 

be present but they generally experience moisture stress during 

much of the growing season. Xerolls and Ustolls typically 

have a frigid or cryic temperature regime.

Soils provide nearly all mineral nutrients used by the 

plant communities they support. In a healthy state, they are the 

site of most decomposition of organic material, retain water 

and facilitate infiltration, provide a stable substrate for plant 

roots, and harbor a diverse community of micro- and macroorganisms that contribute to stability and diversity to the biotic 

community.

Wildlife and Habitat Quality.—Great Basin 

coniferous forests host a diverse complement of vertebrate 

and invertebrate animals. Across the region, species such as 

silver-haired bat (Lasionycteris noctivagans), ermine (Mustela 

erminea), Nuttall’s cottontail (Sylvilagus nuttallii), and an 

abundance of birds including band-tailed pigeon (Patagioenas 

fasciata), dusky grouse (Dendragapus obscurus), 

Williamson’s sapsucker (Sphyrapicus thyroideus), and 

flammulated owl (Otus flammeolus) are associated with Great 

Basin coniferous forests. Because dispersal rates vary among 

species, some forest-associated wildlife populations exhibit a 

metapopulation structure whereas less-vagile species persist 

largely as isolated populations with little if any exchange of 

individuals or genes (Brown, 1978; Cutler, 1991).

Animals perform significant functional roles in Great 

Basin forest ecosystems. Acts of herbivory, granivory, and 

digging contribute to enhanced seed dispersal, altered plant 

distributions, and soil-nutrient turnover. An example is the 

Clark’s nutcrackers (Nucifraga columbiana) role as dispersers 

of whitebark (Pinus albicaulis; Tomback, 1982) and limber 

pine (Tomback and Kramer, 1980) seeds.
60 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Ungulate herbivores, native and introduced, generally 

are not abundant in the upper elevation Great Basin conifer 

forests; therefore, their current influence on these systems 

probably is less than on low elevation shrub and grasslands 

(see Sagebrush Steppe Model). However, the legacy effects 

of historical livestock grazing in western coniferous forests 

is still not fully understood (Fleischner, 1994). Domestic 

herbivores tend to concentrate under the canopy of forest 

edges for shade. Effects on vegetation structure and 

composition and on soil and hydrologic processes from 

large ungulates in upland forest-types usually are greatest 

near lower treeline edges, access roads, and water sources 

(Fleischner, 1994; also see Chapter 4, Stream and Riparian 

Models).

We know very little about functional contributions of 

most vertebrates; however, we know even less about many 

aspects of invertebrate life-histories and their influence on 

Great Basin forests. Bark beetles (Coleoptera: Scolytidae) are 

one invertebrate group that is relatively well-studied and their 

influence on conifer forest health and function can be quite 

significant (Powers and others, 1999). The potential effect 

of insect outbreaks is addressed in the section, “Drivers of 

Ecosystem Change.”

Drivers of Ecosystem Change

Climate Variability and Change

Climate, including variations across all spatial and 

temporal scales, is the overriding driver of landscape 

condition. Increasing temperature and CO2 concentrations in 

recent decades appear to be of an unprecedented magnitude 

and rate (Intergovernmental Panel on Climate Change 

Working Group I, 2001; Connely, 2003) prompting our 

scoping efforts to identify climate change as a key ecosystem 

driver in the Great Basin. From the perspective of ecosystem 

responses, the causes of climate changes are somewhat 

irrelevant; it is more important to understand the rate and 

directionality of climate-induced landscape change so we rely 

on appropriate models to evaluate future climate scenarios. 

As described in the atmospheric model, existing climate 

models generally lack details necessary to understand climatic 

influences on the topographically diverse Great Basin. Nearly 

all climate models predict that warmer conditions will prevail 

in the Great Basin during the next few decades, but the same 

models disagree over the amount and timing of precipitation 

over the next 50–90 years. A decrease in precipitation would 

indicate that forest systems in the region may shrink, move 

upslope, or disappear from the landscape (for example, 

Diffenbaugh and others, 2003; Parmisan and Yohe, 2003). 

Indeed, resampled plots at Great Basin National Park 

demonstrate that Engelmann spruce is declining in permanent 

plots within riparian forest habitat at all but the highest 

elevations, and that the minimum elevation of the species’ 

distribution rose 175–200 m from 1992 to 2001 in three of 

four drainages studied (Beever and others, 2005). Recent 

mortalities in some pinyon-juniper stands (Shaw and others, 

2005) also might indicate changes in Great Basin vegetation 

due to climate change (Rehfeldt and others, 2006). Loss of 

forest would impact plant and wildlife communities associated 

with forest cover types.

Increased precipitation, especially that falling in winter 

and remaining as snowpack, may favor conifer forest cover 

at the expense of xeric shrubland (Thompson and others, 

1998; National Assessment Synthesis Team, 2000). Still other 

models predict that Great Basin conifer forest distributions 

will remain relatively unaffected by climate shifts over the 

next century (Rehfeldt and others, 2006).

Because plants will respond to climate changes 

individualistically (Smith and others, 2000) communitylevel responses remain open to interpretation. Furthermore, 

forest cover changes resulting from increasing greenhouse 

gasses and consequent climate change likely will be mediated 

by many additional factors including nutrient cycling 

feedbacks, age-dependent responses, and species interactions 

(Diffenbaugh and others, 2003). Moreover, invasive species 

that disperse rapidly are likely to find opportunities in newly 

forming communities (Dukes and Mooney, 1999; National 

Assessment Synthesis Team, 2000). Thus, the species 

composition of future communities may differ substantially 

from those occupying similar habitats today.

Wildfire

As is the case throughout most of the intermountain 

west, upland forests of the Great Basin are disturbance-driven 

ecosystems. Wildfire is the most widespread and significant 

disturbance agent in the region (Peet, 2000). A direct effect of 

fire is the alteration of vegetation composition and structure 

due to the selective damaging or elimination of fire-intolerant 

life forms or age classes (Whelan, 1995). High-severity fires 

in woodlands and forests result in near-complete mortality 

of overstory trees, whereas low-severity fires consume 

primarily herbaceous surface fuels, litter, and fire-sensitive 

understory vegetation including seedling and sapling trees. 

Mixed-severity fires result in a mosaic of patches that can be 

caused by variations in topography, weather, fuel loading, 

and previous fire or other disturbance history (Noss and 

others, 2006). Effects of fire on vegetation structure have 

many ecosystem-level consequences. Reduction in vegetation 

cover reduces or eliminates food and cover for most forestdependent wildlife although post-fire vegetation recovery 

typically increases forage for some herbivores. Erosion of 

soils, nutrients, and organic matter by water and wind may 

be exacerbated by fire-caused reduction of vegetative cover 

and forest floor litter. Soils may become hydrophobic as a 

result of severe burns leading to accelerated water runoff and 

decreased infiltration. Fires also may positively or negatively 

affect nutrient cycles and other soil functions and properties 

on short- or long- time scales (Raison, 1979; Whicker and 

others, 2002).
Chapter 3: Subsystem Models for the Dry System 61

Natural fire return intervals are estimated to be between 

7–30 years in Great Basin conifer forests (Miller and others, 

2005; Stevens and others, 2007). Pre-settlement wildfires 

within conifers probably were low-severity and reduced fine 

fuels while having minimal effect on mature trees. However, 

fires impacting conifer patches are affected by adjacent cover 

types. Thus, severity of a specific fire is influenced by adjacent 

cover-types and the fire history of those patches as well as 

their topographic relationships. Because many lower elevation 

patches are now degraded sagebrush, pinyon-juniper, or 

annual grass-dominated sites, fire frequencies and intensities 

generally have increased in upslope conifer stands. Wildfires 

spreading from adjacent habitats are correspondingly expected 

to occur more frequently or more intensely, thereby affecting 

coniferous forest structure, composition, and location. 

Livestock Grazing

Livestock management is arguably the most profound 

post-settlement human legacy on the Great Basin landscape. 

Introduction of cattle, sheep, and horses to a landscape nearly 

devoid of large herbivores in the late 1800s quickly resulted 

in the decline and eradication of many native grass species 

and other environmental consequences (Young, 1994). The 

vast majority of grazing effects were focused in low elevation 

shrublands, but forests were not spared from damage. 

Theodore Rixon was quoted by P.H. Roberts (1963) as stating:

“At the beginning [of livestock grazing in the 

southwestern US] the mountains and heavily 

timbered areas were used but little, but as the 

situation grew more acute in the more accessible 

regions the use of these areas became more general 

and in course of time conditions within them 

were more grave than elsewhere... The mountains 

were denuded of their vegetative cover, forest 

reproduction was damaged or destroyed, the slopes 

were seamed with deep erosion gullies, and the 

water-conserving power of the drainage basins 

became seriously impaired.” 

The high elevation, slightly wetter pastures available in 

the Great Basin were useful to herders because they generally 

provided better summer forage than the more xeric basins. As 

rangeland resources declined due to overstocking, sometimes 

coupled with drought, forage in the conifer forest understory 

began to be heavily impacted. Although stocking rates have 

declined from the early years of livestock management and 

the sheep industry all but collapsed in the middle of the 20th 

century, livestock grazing management continues to be an 

important driver in Great Basin conifer forests and the effects 

of historic and current disturbance are priority considerations 

when evaluating landscape change.

Invasive Plants

Like many Great Basin ecosystem drivers, the effects of 

exotic, invasive plant infestations are better understood for 

lower-elevation shrublands and woodlands even though they 

are a significant forest management concern. Within the last 

decade, cheatgrass has expanded its range in the pine forests 

of the southern Sierra Nevada and central Great Basin. The 

ecological consequences of cheatgrass invasion into forested 

habitats are not as well documented as in shrub-dominated 

landscapes (for example: D’Antonio and Vitousek, 1992) 

although USGS scientists are beginning to assess its effects 

(M. Brooks, U.S. Geological Survey, oral commun., 2008). 

Other invasive species recorded in Great Basin forests include 

Dalmatian toadflax (Linaria dalmatica), diffuse knapweed 

(Centaurea diffusa), hoary cress (Cardaria draba), and 

Canada thistle (Cirsium arvense). However, very little specific 

information exists on the landscape-scale effects associated 

with these invasions.

Motor Vehicle Use

Motorized vehicle use is a relatively recent phenomenon 

in the Great Basin and, consequently, little information 

exists on its effects on ecosystem components and processes. 

Motor vehicle use is known to accelerate erosion, potentially 

increasing silt loads in spring pools and streams (Trombulak 

and Frissell, 2000). It also contributes to fragmentation of 

formerly contiguous land cover patches. Resource agencies 

expend significant time and money managing roads and 

vehicle access; however, enforcement of transportation 

policies in such a huge area can be cost-prohibitive. Thus, 

much of the landscape alteration that is occurring is not 

well regulated or documented. The quantitative effects of 

this disturbance across the ecoregion are virtually unknown 

and, although the effects on the spatially-restricted conifer 

forest may be less significant that the broader shrubland 

systems, forest cover is typically identified as a destination 

by recreationists, hunters, and firewood collectors. Therefore, 

conifer stands may be disproportionally impacted by motor 

vehicle use.

Insect Outbreaks

Native bark beetles (Coleoptera: Scolytidae and 

Curculionidae) were not initially identified as a priority 

ecosystem driver of coniferous forests but we include them 

here because future insect outbreaks may be closely linked 

with future climates and disturbance regime trends. At least 

five species of beetles cause natural, cyclical disturbances to 

conifer species found in the Great Basin. Beetle population 

abundances and distributions are likely to covary with climate 

change and historical land-use management practices (Bentz 
62 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

and others, 2008). For example, mountain pine beetle and 

spruce beetle activity is believed to have increased in direct 

response to warming temperatures (Hansen and others, 

2001; Logan and Powell, 2001). Drought-driven moisture 

stress can increase tree susceptibility to insect colonization. 

Drought periods also increase the activity of the fir engraver 

(Scolytus ventralis) in fir stands throughout the Great Basin 

(Bentz and others, 2008). Bark beetles affect trees directly 

through their subcutaneous boring action and by facilitating 

fungal infestations that interrupt the tree’s water transport 

system. Mortality or dieback resulting from insects is likely to 

interact with changing fire regimes and influence forest health 

and persistence. Recent concerns also have focused on the 

introduction of exotic tree pests (Lee and others, 2007).

Ecosystem Dynamics

The following section describes conceptual models of 

Great Basin coniferous forests. As hypotheses, these models 

will be iteratively refined on the basis of new knowledge. 

These simple models are unlikely to capture all possible 

ecological processes and outcomes. By themselves, the models 

do not provide any quantification or predictive framework that 

will enable managers to anticipate and mitigate change on a 

site-specific basis. However, they do provide a starting point 

for a framework. Our general models do not account for sitespecific factors and may require modification for application to 

a specific type of land unit. Some of the conceptualizations we 

present (figs. 3.11–3.14) are modified from work done for the 

National Park Service’s Upper Columbia Basin and Northern 

Colorado Plateau Inventory and Monitoring Networks (Garrett 

and others, 2004; O’Dell and others, 2005). The models are 

best viewed as working hypotheses that can be improved with 

carefully designed monitoring and subsequent analyses.

The Reference Condition

Because a valid accurate conceptual model accounts 

for all important ecological states and processes it should 

accurately describe ecosystem-wide reference conditions. 

The significant system drivers and interactions are partially 

a function of a given site’s history. Conversely, identifying 

an ecological reference point has temporal and spatial 

complications that are especially difficult for Great Basin 

forests. Indications are that conifers stands were nearly 

continuous in the early-Holocene Great Basin (Grayson, 

1993). Grayson (1993) suggests that the Great Basin ‘came 

to look as it looks today’ during the middle Holocene, around 

4,500 years before present, although he cautions that reference 

conditions will differ in different areas. A more practical 

reference point for conifer forests may be defined as the 

condition that existed when Europeans arrived in the region 

in the early 1800s because timber removal to support mining 

and livestock introductions began in earnest by about 1860. 

Before that time Native Americans set landscape-altering fires 

in the Great Basin (Vale, 2002) and although the frequency 

and extent of ecosystem management and alteration caused by 

Native Americans is hotly debated (for example, Swetnam and 

Baisan, 1994; Anderson and Moratto, 1996), it is relatively 

certain that aboriginal influences on Great Basin forests had 

less impact than those of Euro-Americans (Fule and others, 

1997).

The concept of the reference state, however, must be 

sufficiently flexible to account for uncertain future trajectories 

in environmental conditions because, given enough time, even 

the most identifiable reference conditions are subject to ‘drift’

based on millennial-scale trends in climate and landscape 

structure.

State-and-Transition Model

General patterns of ecosystem dynamics can be 

effectively illustrated using state-and-transition models 

(Westoby and others, 1989; Bestelmeyer and others, 2003). 

State-and-transition models are management-oriented 

tools for describing and classifying ecosystem conditions 

(or states) and posing hypotheses about ecological factors 

responsible for changes (or transitions) among different states 

(Bestelmeyer and others, 2004). Such models have been very 

effectively used by managers and researchers in shrubland 

and other systems but the modeling exercise rarely has been 

applied to forested systems of the Great Basin. We developed 

a generalized state-and-transition model for Great Basin 

coniferous forests (fig. 3.12), borrowing from work presented 

by Miller (Sagebrush Steppe models NRCS Ecological Site 

Descriptions, accessed June 23, 2009, at http://esis.sc.egov.

usda.gov/Welcome/pgESDWelcome.aspx this volume; fig. 3.5, 

p. 82) and models being developed by NRCS (accessed June 

23, 2009, at http://esis.sc.egov.usda.gov/esis_report/fsReport.

aspx?id=F030XC279NV&rptLevel=communities&approve

d=yes) for their Ecological Site Description process. In this 

model, we depict three general states: the Reference Condition 

describing a healthy conifer forest experiencing cyclical, 

successional processes; a degraded forest impacted by some 

combination of system stressors; and a severely degraded 

condition, possibly leading to a permanent change in plant 

community (fig. 3.12; table 3.4). Factors driving transition 

from one state to another are analogous to the key drivers 

identified during our scoping effort and include: climate 

change, wildfire, livestock grazing, exotic plant invasions, 

motor vehicle use, and insect outbreak. We use our definitions 

of ‘driver’ and ‘stressor’ (see Glossary) to identify drivers 

within the reference condition when they are operating under 

natural ranges of variation and stressors in the transition 

portion of the model when individual or combined effects 

move the system outside natural successional processes.
Chapter 3: Subsystem Models for the Dry System 63

9-0397_fig03-12

REFERENCE CONDITION: Healthy Coniferous Forest

IMPACTED FOREST

A. MATURE FOREST

Tree age: 125–500+ years

Canopy closure: 30–45%

E. MID-LATE SERAL: YOUNG FOREST

Tree age: < 80–200 years

Canopy closure: < 10–30%

D. MID SERAL: SAPLING/POLE

Tree age: < 10–100 years

Canopy closure: < 5–20%

F. LATE SERAL: DECADENT FOREST

Tree age: 250+ years

Canopy closure: 35–45%

B. EARLY SERAL: HERBACEOUS

Tree age: < 5 years

Canopy closure: < 1%

C. EARLY SERAL: SHRUB/SEEDLING

Tree age: 5–10 years

Canopy closure: < 10%

H. HIGHLY DEGRADED OR

EXTRAMURAL COMMUNITY?

Stressors interact to severely disrupt 

ecosystem processes, soil functions 

and microclimates; vegetation 

community shifts; site potentially 

G. DEGRADED FOREST

degraded beyond repair

Tree age: variable

canopy closure: reduced,

variable

Increased edge effects, soil erosion, 

tree mortality; reduced soil moisture, 

biodiversity, wildlife habitat quality

Operating within range of natural variation; at or near dynamic equilibrium; resilient to exotic plant invasions, natural 

levels of herbivory, acute extreme weather events; resistant to soil erosion; provides high-quality wildlife habitat Processes moving outside range of natural 

variation; resilience and habitat quality 

degraded 

Climate

change 

4b. High-severity Fire

3a. Growth, Succession

5b. Thinning

9a. Restoration?

1a. Low Severity (surface) Fire, 

Partial Mortality Insect Outbreak 

1d. Succession, Select Harvest, 

Partial Mortality Insect Outbreak 1b. High-severity Fire, 

Clearcut Harvest, 

Windthrow 5a. Growth, Succession 1c. Thinning, Partial Mortality Insect Outbreak

6b. Thinning, 

Partial Mortality 

Insect Outbreak, 

Mid-severity Fire 6a. High-severity Fire, Clearcut Harvest, Windthrow

5b. High-severity Fire, 

Clearcut Harvest

4a. Growth, 

Succession

2a. Growth, 

Succession

3b. High-severity 

Fire

7a. Interactive effects of climate change, 

motor vehicle access, excessive 

herbivory, exotic plant invasion, insect 

outbreaks, wildfire

8b. Interactive effects 

of climate change, 

motor vehicle access, 

excessive herbivory, 

exotic plant invasion, 

insect outbreaks, 

wildfire

8a. Rest from 

Stressors; 

Restoration

9b. Restoration?; 

‘Designer’ landscape?

Figure 3.12. Generalized state-and-transition model for interior Great Basin Coniferous forests. This model will be refined and further developed as GBILM and partners generate further discussion and information.
64 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

State-and-transition models are best applied to specific 

land units (for example, specific ecological sites) because of 

the importance of site-specific factors such as local climatic 

conditions, soil-geomorphic properties, and landscape 

configuration for determining ecosystem responses to 

management actions and other drivers of change. Our general 

model does not account for these site-specific factors or the 

broad diversity found in Great Basin coniferous forests. They 

will require modification for application to specific forest 

types and adjustments as our understanding of forest processes 

improve.

Stressor Models

Ecosystem drivers become system stressors when their 

effects move the system outside the range of natural variability 

that we characterize as the reference state. Hypothetical 

processes by which drivers/stressors singly or interactively 

cause persistent changes in the structure and functioning of 

coniferous ecosystems are depicted in figures 3.13–3.15. 

These mechanistic models illustrate potential landscape 

changes that alter conifer forest systems and are of concern 

with respect to management objectives. These Stressor Models 

were developed based on information found in Shafer and 

Table 3.4. Characteristics of three general states of coniferous forest systems in the Great Basin. 

[Letters A-H refer to boxes depicted in figure 3.12]

State General characteristics

A-F. Reference Condition Climate and physical template within natural ranges of variation. Most of region dominated by mature or 

maturing conifer trees but portions in earlier successional stages and dominated by forbs, shrubs and/or 

sapling conifers. Soils, litter, and seed banks mostly intact though some erosion evident, especially on steep 

slopes in disturbance zones. Resilience to anthropogenic disturbances generally high. Native flora and fauna 

predominate. Predicted climate change likely to favor upslope movement of the entire community (for 

example, Parmesan and Yohe, 2003; Beever and others, 2005).

G. Degraded Forest Dominant vegetation shifts in terms of species composition, overstory structure, and vigor. Edge effect increase 

due to driver impact on periphery of stand. Soil moisture and plant biomass reduced. Increased susceptibility 

to wildfire, plant invasions, herbivore effects, and extreme weather events. Resilience degraded; soil stability 

and hydrologic functions altered. Wildlife habitat quality reduced. System is likely restorable with rest from 

certain stressors and/or active restoration.

H. Highly Degraded Characterized by depauperate vegetation community with increasing invasive species. Soil moisture severely 

reduced such that coniferous trees no longer favored. Overstory structure disrupted by interactive effects 

of insect damage, wildfire, motor vehicle use, invasives, and climate change. Wildlife habitat altered to the 

degree that assemblages change, with potential cascading effects. Some species extirpated. Highly degraded 

systems may not be restorable to reference condition due to ecological or financial limitations and novel, 

extramural communities may develop. Managers may need to consider targeting ‘designer ecosystems’ (for 

example, Pimm, 1996).

others (2001), Diffenbaugh and others (2003), Kupfer and 

others (2005), Vankat (2005), Rehfeldt and others (2006) and 

Millar and others (2007). Arrows and boxes in these models 

are potential monitoring targets. We hypothesize two possible 

outcomes of driver-stressor interactions that primarily are 

driven by water availability, the most limiting abiotic factor in 

these systems except near upper timberline. In one scenario, 

reduced water availability leads to decreasing forest patch 

size and potential extirpation of the entire stand (fig. 3.13). 

A second possible outcome is significant alteration of tree 

species composition, which may threaten individual species of 

plants and animals. This outcome could hypothetically result 

from a decrease (fig. 3.14) or increase (fig. 3.15) in water 

availability. Climate models generally agree that temperatures 

will increase, which will effectively reduce soil moisture. As 

a result, reduced water availability may represent the model 

needing the most study. Additional trajectories are likely and 

will be the subject of subsequent quantitative models.

Anthropogenic drivers include directional global climate 

change, the feedback loop generated by the combination 

of exotic plant invasions and fires, selective grazing and 

trampling by livestock, and motor vehicle use (primarily off 

highway vehicles). Natural drivers, which also may become 

stressors when compounded by other natural or anthropogenic 

drivers, include climate variability, lightning-caused wildfire, 

and insect outbreaks.
Chapter 3: Subsystem Models for the Dry System 

65

tac09-0397_fig03-13

Stress, mortality,

insects, diseases

Precipitation

Soil

erosion

Slumping

Snowpack

Catastrophic

fires

Plant vigor

and growth;

fuel moisture

Average annual

temperature (3°C)

Windthrow

Elevational

shift Root

exposure

Patch

fragmentation

Seedling

recruitment

Water

availability

Soil

compaction

Plant seed manipulations

(animal caching, bird-aided

dispersal)

Altered niche

parameters

WILDFIRE DECREASING PATCH SIZE; PATCH EXTIRPATION

CLIMATE VARIABILITY

AND CHANGE

EXCESSIVE GRAZING

MOTOR VEHICLE USE

DISPERSED OHV

Reduced water availability: Conifer Forest Fragmentation and Loss

Figure 3.13. Stressor Model illustrating processes by which multiple drivers (ovals) can lead to decreased coniferous forest patch size or complete replacement of a forest patch in the Great Basin. Decreasing patch size or patch extirpation primarily would be driven by reduced precipitation and soil moisture.
66 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Figure 3.14. Stressor Model illustrating processes by which multiple drivers (ovals) can lead to altered coniferous forest stand composition in the Great Basin. In this case, ‘forest composition’ includes all taxa (plants, animals, fungi, and microbes). Altered stand composition may result in significant changes in functional groups and consequent changes in nutrient storage and cycling, soil moisture characteristics, biodiversity, and ecosystem services. 

tac09-0397_fig03-14

Susceptability

to infestation

Physiological

stress on trees

Fine

fuels

Precipitation/

Snowpack

Fire

suppression

Vigor; seed

production

Average annual

temperature (3°C)

Fire return

interval

Tree

density

Lightning

strikes

Palatable

plant species

Snag density; large

downed wood

Mortality

Fire

severity

Successional

setback

Unpalatable and

invasive plants

FIRE REGIME

ALTERED FOREST

COMPOSITION

CLIMATE VARIABILITY

AND CHANGE

EXCESSIVE GRAZING

INSECT/DISEASE

INVASION

Reduced water availability: Altered Forest Composition
Chapter 3: Subsystem Models for the Dry System 

67

Figure 3.15. Stressor Model illustrating processes by which multiple drivers (ovals) can lead to altered species composition in Great Basin coniferous forests in the face of a climate-change induced increase in precipitation. Altered species composition may result in significant changes in functional groups and consequent changes in nutrient storage and cycling, soil moisture characteristics, biodiversity, and ecosystem services.

tac09-0397_fig03-15

Tree stress,

mortality Precipitation

Snowpack

Catastrophic

fires

Plant vigor

and growth;

fuel moisture

Average annual

temperature (3°C)

Seedling

recruitment

Fuel loading

Opportunity for

early successional

plants

Water

availability

Soil

compaction

Altered niche

parameters

EXCESSIVE

GRAZINE

INVASIVE

SPECIES

DEVELOPMENT OF

EXTRAMURAL/INVASIVE

COMMUNITIES?

CHANGES IN PLANT/

ANIMAL SPECIES

COMPOSITION

CLIMATE VARIABILITY

AND CHANGE

WILDFIRE

?

Increased water availability: Conifer Forests Increase
68 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

The landscape altering fire-invasive annual grass cycle 

has been thoroughly documented for low-elevation shrubland 

systems in the western U.S. (Mack, 1981) and current research 

is exploring the effects of exotic annual grass invasions in 

conifer forests (M. Brooks, U.S. Geological Survey, oral 

commun., 2009). Because impacted and at-risk shrublands 

abut conifer forest throughout the Great Basin, forest types 

may be threatened even if annual grass invasions are not 

altering fire return intervals within the forest cover types 

(for example, Swetnam and Betancourt, 1998). Fires ignited 

in shrubland may spread upslope and into conifer forest. 

However, fires driven by fine-fuel annual grasses tend to be 

lower in severity and, ignoring potential interactions, are 

likely to proliferate as ground fires in the forest. Although 

this may present significant alterations to understory plant 

communities and animals associated with them, forest cover is 

more devastatingly impacted by high-severity fires, especially 

if the fire extends to tree crowns. Fuel moisture in Great Basin 

conifer forests tends to be very low throughout most of the 

fire season, rendering a higher susceptibility to stand-altering 

fires. Records of forest patches being totally removed by 

catastrophic fire can be found, although total stand removal 

appears to be historically quite rare. Future scenarios that 

couple climate change and insect outbreaks with exotic plant 

invasions and fire indicate that conifer forest—especially 

smaller isolated stands—may be increasing in susceptibility.

Grazing effects, although not well documented in many 

coniferous forest types of the Great Basin, generally include 

alteration of ecosystem processes by decreasing the cover 

of herbaceous plants and litter, disturbing and compacting 

soils, decreasing water infiltration rates, and increasing soil 

erosion (Belsky and Blumenthal, 1997; Beever and Pyke, 

2004). Long-term browsing of aspen saplings by wild and 

domestic ungulates probably accelerates the process of 

conifer expansion and leads to their eventual dominance 

over aspen communities (Miller and others, 2001). We 

hypothesize that grazing will continue to alter forage plant 

species composition and dominance and affect natural soil 

functions and movements. We hypothesize that grazing alone 

would have negligible effects on conifer forest integrity but 

when interacting with other drivers, these effects contribute to 

system alteration.

The effects of increased motor vehicle use in Great 

Basin forests have not been addressed in the ecological 

literature. However, accounts from other areas indicate that 

motor vehicle use can lead to increases in soil compaction 

and erosion (Helvey and Kochenderfer, 1990), opportunities 

for invasive species (Tyser and Worley, 1992; Gelbard and 

Belknap, 2003), high incidence of human-caused fire, and a 

reduction in habitat quality due to increasing fragmentation 

(Trombulak and Frissell, 2000).

The influence of human-induced climate change on Great 

Basin forests is more difficult to forecast. Numerous efforts 

have attempted to forecast potential climate-change induced 

shifts of western plant communities (Thompson and others, 

1998; National Assessment Synthesis Team, 2000; Shafer 

and others, 2001; Diffenbaugh and others, 2003; Rehfeldt 

and others, 2006). Global and regional climate models 

generally agree that air temperatures will increase 3–5 °C 

over the next century primarily due to a two-fold increase 

in atmospheric CO2 (Intergovernmental Panel on Climate 

Change Working Group I, 2001). Some models predict an 

increase in moisture (National Assessment Synthesis Team, 

2000) whereas others forecast decreased precipitation (Giorgi 

and others, 1998a; Thompson and others, 1998) or relatively 

constant precipitation (Diffenbaugh and others, 2003) in some 

or all seasons over the next century. Increased precipitation, 

especially that falling in winter and remaining as snowpack, 

likely would promote an increase in forest cover at the 

expense of shrub and woodland habitats (National Assessment 

Synthesis Team, 2000). If alternate models are correct and 

precipitation decreases couples with increased temperatures, 

forests are likely to migrate uphill, replace alpine habitat, and 

become reduced in size. We elected to conceptualize both 

possibilities (figs. 3.13–3.15). Long-term climate change also 

may increase storm intensity (Groisman and others, 2004) and 

increase climate variability overall (for example, Meehl and 

Tebaldi, 2004), which likely would increase lightning strikes 

and tree windthrow, potentially increasing fragmentation 

within forest patches.

Summary Points

Coniferous forest landcover is found on many of the 

high-elevation mountain ranges of the interior Great Basin and 

on the mountains forming the west, north, and east boundaries. 

Forests are usually positioned high on the slope between 

lower-elevation shrubland or pinyon-juniper woodland and 

upper elevational alpine tundra. Coniferous forests contribute 

a distinct flora and fauna to the region’s biodiversity, perform 

important hydrological functions, sequester and store carbon, 

and provide a variety of other ecosystem services (air quality, 

recreation) and goods (fuel wood, forage), many of which are 

largely unquantified.

Our understanding of the function of Great Basin 

mixed conifer forests remains incomplete. Some common 

assumptions about forest ecosystem processes, including 

those presented here, need to be tested rigorously. The 

models of Vankat (2005) for Colorado Plateau montane 

forests contain additional submodels that may be applied to 

the Great Basin when sufficient data becomes available. If 

current climate predictions hold true, shifts in the location, 
Chapter 3: Subsystem Models for the Dry System 69

extent, and composition of forests likely will occur. However, 

the magnitude and direction of change remains uncertain 

because climate models depicting local-scale effects, 

particularly models forecasting the amount and timing 

of precipitation, forecast a broad spectrum of potentials. 

Therefore, one primary need is improved weather monitoring 

to provide baseline data, understand the interactive effects 

of microclimate, topography, and soil moisture on species 

persistence, and validate downscaled global climate models. 

We also need data for predicting how fire severity and 

frequency, insect outbreaks, and plant and animal distributions 

will interact with future climates to influence forest-patch 

distribution and associated fauna. For example, although 

recent biogeographical analyses indicate that small mammals 

may use lowland riparian corridors as dispersal routes (for 

example, Lawlor, 1998), it is unclear whether these avenues 

will remain available under some climate change scenarios. 

Understanding the dispersal ability of a whole suite of plants 

and animal species will aid in predicting future persistence and 

composition of forest patches in the region.

Forest patches in the Great Basin are highly variable 

both within a mountain range and among similar forest-types 

on adjacent ranges. We need to improve our understanding 

of spatial variability to better elucidate the potential for 

dispersal and recolonization of depauperate patches and 

recovery of disturbed sites. What spatial factors facilitate or 

inhibit movement of individuals, seeds, and genes? Which 

plant and animal populations are truly isolated and which 

function as part of metapopulations? Rigorous, quantitative, 

spatially explicit models are needed to begin making testable 

predictions based on our qualitative conceptual models. 

We also need better understanding of specific plant and 

animal habitat relationships in order to understand potential 

threats to species persistence and to prioritize management 

activities. Very few forest-associated species currently are 

understood well enough to integrate into our stressor models 

and generate species-response hypotheses. Information that is 

available needs to be cataloged and evaluated before initiation 

of specific modeling exercises that begin identifying vital 

monitoring indicators.

Limited empirical data (Shaw and others, 2005; Rehfeldt 

and others, 2006) support our hypothesized threats to 

coniferous forest persistence, vigor, and integrity. Researchers, 

modelers, and land managers should coordinate their efforts to 

monitor, understand, and respond to these trends.

Alpine Tundra Models 

By D.M. Miller

Distribution and Management Significance

Alpine tundra occurs in only 0.3 percent of the Great 

Basin landscape. Specifically, it occupies patches on 

mountain tops at elevations ranging from 10,000 to 13,000 ft 

and above sagebrush or tree communities. Alpine tundra 

is present in the Great Basin’s highest peaks including the 

Snake (home of Great Basin National Park), White, Ruby, 

East Humboldt, Jarbidge, Sweetwater, Toiyabe, and Toquima 

Ranges and Steens Mountain. The alpine zone is subject to 

harsh climatic extremes that limit plants and animals to those 

specially adapted to narrow tolerances. As a result, the alpine 

is a fragile zone that is easily disrupted and also difficult to 

manage because of its remoteness. It includes transitional 

upper treeline species of concern such as the bristlecone pine 

(the State tree of Nevada) and the American pika (Ochotona 

princeps), a mammal threatened with extirpation.

Ecosystem Components

The alpine tundra environment generally is characterized 

by thin, weakly developed rocky soils and prostrate vegetative 

growth forms (Patten, 2005). The short, cold-restricted 

growing season, intense radiation, wide daily and annual 

temperature variations, extreme winds, thin air, and longlasting snow create a short and harsh growing season that 

greatly limits the flora and fauna (Scott and Billings, 1964). 

Short-stemmed perennial herbs, lichens, and mosses are 

common, as are prostrate forms of woody shrubs (Pase, 1994). 

At the transitional zone between timberline and alpine tundra, 

krummholz tree growth forms are common. Bristlecone pine 

and limber pine are typical species in this transitional zone 

in the southern Great Basin. Although this transitional zone 

supports larger woody vegetation, we treat it in our alpine 

models because of the predominant influence of harsh climatic 

and geomorphic processes. 

The floras of the Great Basin alpine tundra total about 

600 species, reflecting species in common with alpine zones 

of the Sierra to the west and the Rocky Mountains to the 

east. In fact, this diversity rivals that of the alpine zones 

found in these larger and more continuous mountain masses. 

Ground-dwelling animals that commonly inhabit the alpine 

tundra include yellow-bellied marmot (Marmota flaviventris), 

mountain pocket gopher (Thomomys monticola), alpine 

chipmunk (Tamias alpinus), Palmer’s chipmunk (Tamias 
70 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

palmeri), western heather vole (Phenacomys intermedius), 

Inyo shrew (Sorex tenellus), long-legged myotis (Myotis 

volans), and the pika. Common nesting birds are the whitecrowned sparrow (Zonotrichia leucophrys), black rosy-finch 

(Leucosticte atrata), American pipit (Anthus rubescens), and 

horned lark (Eremophila alpestris). 

Abiotic factors, especially climate, tend to overwhelm 

biotic factors in structuring the alpine tundra (Cannone 

and others, 2007). The plant and animal communities of 

the alpine tundra are subject to natural disturbances from 

geologic processes, making these environments potentially 

very sensitive to climate changes. Current response to the 

last 50 years of increasing temperatures includes uphill shifts 

of many species distributions (Kullman, 2002; Beever and 

others, 2005) and associated changes in plant community 

composition. The delicate balance between persistence and 

extirpation in these extreme conditions could be altered with 

additional disruptions from climate change.

Drivers of Ecosystem Change

Natural Drivers

Natural drivers in the alpine tundra primarily are climatic 

and geologic processes (fig. 3.16), which combine with 

limitations of plant and animal physiological processes to 

limit growth and diversity of the biota. Climatic influences 

chiefly are extreme cold, short growing season, fierce, 

abrasive winds carrying ice and snow particles, and large 

temperature variations on all times scales from daily to annual. 

High-intensity solar radiation, particularly ultraviolet (UV) 

radiation, forces plant adaptations such as epidermal reflection. 

Lower partial pressure of CO2 reduces photosynthetic rates 

and requires adaptations by alpine tundra plants (Richalet, 

2007). Geologic processes include a wide range of effects 

of freeze-thaw cycles, such as soil disturbance on a daily to 

annual basis and movement of rocks. Steep slopes may have 

little plant stabilization, resulting in repeated movement of 

talus and scree. Geologic effects in a few places may include 

glacial activity (for example, possible rock glaciers in Great 

Basin National Park).

Anthropogenic Drivers

Anthropogenic drivers include climate change, direct 

trampling and contamination by humans and livestock, wet 

and dry deposition of air pollution, introduced fire, road 

effects, and plant harvesting (fig. 3.17). Climate change, the 

single most pervasive driver, is causing increased temperatures 

that may limit environments suitable for many alpine species 

due to limitations to upward migration. Climate change is 

likely to increase storm intensity by increasing the variability 

of climate overall, leading to increased intensity and frequency 

of wind related impacts. Increased solar radiation from 

reduced atmospheric ozone will slowly increase incident 

UV radiation. High CO2 concentrations may reduce the 

competitive advantage of photosynthetically efficient plants 

thereby changing the ratio of C3 to C4 plants, decreasing 

resistance to exotic plant invaders, and altering species 

composition. High temperatures probably will reduce the total 

area of tundra by upward migration of timberline (Kullman, 

2002) through differential upward migration of specific tree 

species (Beever and others, 2005), and through alteration of 

freeze-thaw activity and intensity. A change from snow to 

rain precipitation may increase erosion, particularly in plantdiminished patches previously disturbed by trampling, or by 

late-summer drought caused by reduced snowmelt. Cannone 

and others (2007) inferred that soil instability and disturbance 

creates migration barriers inhibiting upward movement of 

plants, altering the plant community toward disturbanceadapted species. As a result, it may be particularly productive 

to monitor the plant and bare-ground mosaic in those alpine 

zones most sensitive to climate change effects.

Reduced snow cover from shorter winters also may affect 

plant species composition, in particular the plant species that 

occupy snowbank margins such as Eschscholtz’s buttercup 

(Ranunculus eschscholtzii; Charlet, 1991). Human trampling 

and harvesting of plants disturbs soil crusts and surface 

horizons as well as plant mats, increasing wind and water 

erosion. Deposition of anthropogenic nitrogen may result in 

fast transmission downslope to streams without any biofiltering due to the high cover of rock and snow (Seastedt and 

others, 2004; Ashton and others, 2008). Impacts from nitrogen 

may aggregate at timberline, aggravating climate change 

effects where the bristlecone pine focal species is common.

American pikas have high energetic requirements and 

a disinclination for long-distance (>300 m) movements 

or dispersal making them especially sensitive to high 

temperatures (MacArthur and Wang, 1974; Smith, 1974; 

Peacock, 1997; Morrison and others, 2008). They are still 

widely distributed, and are locally common where they occur. 

Collectively, these traits make them valuable early-warning 

indicators of change in Great Basin alpine ecosystems. 

Numerous extirpations of historically recorded pika 

populations have occurred recently in the Great Basin (Beever 

and others 2003), and the rates of population loss and upslope 

migration of pika distributions have increased markedly in the 

last decade (Beever and others, unpub. data, 2008). Because 

pikas harvest, store, and process herbaceous vegetation and 

are important to seed dispersal and banking, their extirpation 

may significantly impact tundra plant communities. Pikas 

also redistribute nitrogen and other minerals and act as prey 

for alpine carnivores, and thus may be considered keystone 

species.
Chapter 3: Subsystem Models for the Dry System 71

Figure 3.16. Control model showing major components, drivers, and processes in the alpine tundra system. Ovals represent drivers 

and rectangles represent major functional components of the ecosystem. Note that, unlike other dry systems, the physical template is 

shown as a participating component for the timescales of interest because geomorphic processes can rapidly change the template in 

the alpine tundra. Plant pattern, species composition, and mortality rates might all be useful attributes to monitor, as well as mammal 

populations and ecotone movement such as upward movement of timberline.

tac09-0397_fig03-16

Microclimatic modification

Safe-site availability

VEGETATION

Plant pattern, mortality

and growth; asexual

plant recruitment

SOIL RESOURCES

Mineral nutrients, water,

organic matter, soil biota

LANDSCAPE

CONFIGURATION

Spatial configuration

of ecosystem microsites

HABITAT QUALITY

Plant patch pattern, plant

species composition

and structure

PHYSICAL TEMPLATE

Elevation, landforms,

soil-geomorphic

setting

WILDLIFE

Species richness, breeding

success, genetic diversity,

invertebrate populations

ATMOSPHERIC &

CLIMATIC CONDITIONS

Regional-, local-, and site-scale climate

patterns; winter precipitation regime;

extreme wind, snow, cold; low CO2

high UV levels; high summer 

temperature

NATURAL

DISTURBANCES

Climatic Episodes

Wind, wet/dry events, snowpack;

freeze-thaw actions (solifluction);

avalanche

Zoogeomorphic agents

Burrowing

Geomorphic processes

Rockfall, glacial activity

Determines site potential 

and provides 

resource inputs

Resource availability

Climatic episodes, weather events, and 

antecedent environmental conditions 

Plant pattern and erosion

Modify composition,

structure, and productivity

Habitat dimensions,

arrangement, 

and connectivity

Determines potential

landscape configuration

Resource transformation

and redistribution

Soil stabilization; resource

capture and retention,

Determines site potential

Pollination, herbivory,

granivory, seed dispersal

Vegetation composition

and structure

Modify landscape configuration through effects

on vegetation composition and structure
72 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Microclimatic modification

Safe-site availability

VEGETATION

Plant pattern, mortality

and growth; asexual

plant recruitment

SOIL RESOURCES

Mineral nutrients, water,

organic matter, soil biota

LANDSCAPE

CONFIGURATION

Spatial configuration

of ecosystem microsites

HABITAT QUALITY

Plant patch pattern, plant

species composition

and structure

PHYSICAL TEMPLATE

Elevation, landforms,

soil-geomorphic

setting

WILDLIFE

Species richness, breeding

success, genetic diversity,

invertebrate populations

ATMOSPHERIC &

CLIMATIC CONDITIONS

Regional-, local-, and site-scale climate

patterns; winter precipitation regime;

extreme wind, snow, cold; low CO2

high UV levels; high summer 

temperature

NATURAL

DISTURBANCES

Climatic Episodes

Wind, wet/dry events, snowpack;

freeze-thaw actions (solifluction);

avalanche

Zoogeomorphic agents

Burrowing

Geomorphic processes

Rockfall, glacial activity

Determines site potential 

and provides 

resource inputs

Resource availability

Climatic episodes, weather events, and 

antecedent environmental conditions 

Plant pattern and erosion

Modify composition,

structure, and productivity

Habitat dimensions,

arrangement, 

and connectivity

Determines potential

landscape configuration

Resource transformation

and redistribution

Soil stabilization; resource

capture and retention,

Determines site potential

Pollination, herbivory,

granivory, seed dispersal

Vegetation composition

and structure

Modify landscape configuration through effects

on vegetation composition and structure

CLIMATIC &

ATMOSPHERIC

CHANGES

LIVESTOCK GRAZING

MOTER VEHICLE USE

PLANT HARVESTING

Soil and vegetation impacts

Temperatures, UV, CO2

and precipitation patterns

Figure 3.17. Major anthropogenic stressors for the alpine tundra system (ovals).
Chapter 3: Subsystem Models for the Dry System 73

Ecosystem Dynamics

The control model (fig. 3.16) illustrates several 

components and processes important to the alpine tundra 

environment, many of which are common to the previously 

described dry systems models. Extreme climatic conditions 

and steep topographic gradients produce large variations from 

site to site in terms of microclimate, soils, and hydrology. 

Physical characteristics such as rocky talus slopes are crucial 

shelter sites for animals. As a result, the alpine tundra consists 

of small patches of different soil types, plant communities, 

and habitat. This fine scale patch interaction links several 

components within the control model: landscape configuration, 

soil configuration, and microsite potential are components that 

vary on the scale of meters in many cases and differs from the 

presumably coarser scale variation in low-elevation dryland 

systems. 

Geomorphic processes change the landscape of alpine 

tundra more rapidly than communities in low elevations. 

Geomorphic processes include freeze-thaw of rock and 

soil, as well as rockfall to create talus, creep of colluvium, 

landsliding, creeping of solifluction lobes, and even glacial 

activity. Snowpack is a critical feature of the alpine zone and 

illustrates the connection between biotic and abiotic features. 

The combination of snowfall and wind creates patterns of 

snow accumulation on lee sides of ridge crests (fig. 3.18). 

Snowbanks that persist into summer gradually melt back and 

successively foster plant communities that vary in accordance 

with—and are dependent on—the timing of snow retreat. 

Changes in timing and amount of snowfall, temperature 

and associated timing of snowmelt, and winds associated 

with snow deposition can all alter the snowbank processes. 

Over long periods of time, nivation hollows develop linear 

depressions formed below and parallel to ridgelines. Nivation 

hollows form by sub-snowpack processes of sediment 

transport by meltwater as snowbanks recede. The hollows 

enhance future snow capture and thus feed back into the 

snowpack-driven processes. Long-term effects include more 

mesic or hydric soils in downslope positions in meltwater 

meadows. Relatively dry rocky crests, snowdrifts, and areas 

below the drifts have characteristic plant communities and 

soils governed by water availability and timing of snowmelt 

and subsequent drying. The snowfield and associated plant 

community patterns may shift rapidly with climate change 

as historical geomorphic-climate combinations spatially 

decouple.

Zoogeomorphic agents including grazing, trampling, and 

burrowing are prominent as well (Hall and Lamont, 2003); 

these are dependent on soil depth and soil moisture, which 

vary by climate factors, topography, and plant cover, and 

therefore are linked to patch-scale processes described above 

(fig. 3.19). 

One monitoring objective in Great Basin alpine 

environs is to identify reliable monitoring cues. Vegetation 

composition and cover, including spatial patterns, are 

fundamental indicators of environmental stress (Kammer 

and Mohl, 2002). Along with climate factors (including 

snowcover and atmospheric pollutant deposition) and visitor 

use, monitoring plant communities should signal alterations 

to the tundra environment. Identifying reliably responding 

plants for monitoring should be a primary goal of future 

research. Animals well adapted to alpine conditions may be 

strongly affected by altered conditions mediated by climate 

change. Mammalian and invertebrate responses to changing 

Prevailing wind

Windward

slope

Ridgecrest

Snowfield

Meltwater

meadow

Progressive

retreat of snowfield

Nivation hollow

Increasing soil depth

Figure 3.18. Simplified illustration of topographic and climatic effects in the alpine tundra zone. Plant communities vary with 

position from the meltwater meadow upward, because they are tuned to the timing of snowfield retreat and the long-term 

accumulation of soil, which is unevenly distributed.
74 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig03-19

DISTURBANCE-ADAPTED

SPECIES

Late summer

 soil moisture

Migration

Plant cover barriers

Erosion

Upward migration

CLIMATE

CHANGE:

Snowfall

Rainfall

Temperature

OHV ACTIVITY,

TRAMPLING AND OTHER

PLANT AND SOIL

DISTURBANCES

Figure 3.19. Stressor model showing climatic and other effects in the alpine-tundra zone. Plant communities are impacted by 

changing climate conditions directly and by inhibited upward migration caused by increased eroded and disturbed ground. Both 

contribute to an increase in disturbance-adapted species. 

temperature regimes such as acute or chronic metabolic 

stress from excessive heat or cold, or increased mortality due 

to alterations of food supply, could be tracked as changes 

in population dynamics making them excellent monitoring 

targets. Some animals also play important functional roles as 

described previously for the pika. 

 Loss of the tundra ecosystem due to climate change 

most likely will result in a large loss of gamma diversity with 

loss of populations and genotypes (McDonald and Brown, 

1992; Hunter, 2002). The high mountains of the Great Basin 

will not recover quickly from loss of tundra because they 

lack connectivity with other tundra environments. Evidence 

from mammals in paleoecologic and recent time indicates 

that species differ in their vagility and their degree of obligate 

relationship to alpine habitats (Grayson and Livingston, 

1993; Lawlor, 1998; Grayson and Madsen, 2000). As a result, 

changes in alpine habitat may have ripple effects in broader 

mammal communities.

Summary Points

It is probable that warming temperatures and other 

climatic factors associated with climate change will impact 

tundra environments by shifting plant and animal community 

distributions, as well as by altering geomorphic processes, 

but little research is available to allow projections to be 

made. It is an important topic for study, because transitions to 

new plant community states may make recovery of existing 

habitat difficult (Laycock, 1991; Stringham and others, 2001). 

Knowledge of the processes that link components of the alpine 

ecosystem generally are poorly understood in comparison with 

some low-elevation Great Basin biomes. As a result, nearly 

all aspects of the alpine ecosystems in the Great Basin are in 

need of further study. Paleoecological studies may shed light 

on which plant and animal populations survived past climate 

changes, and inform hypotheses for survival and extirpation in 

the future when characteristics of past climate is well known.
Chapter 4: Subsystem Models for the Wet System 75

As described in the Wet Systems model, subsystem 

models can be built along many schemes, such as gradients 

between fresh and hypersaline water, between flowing and 

standing water, and between groundwater-controlled systems 

and runoff systems such as streams. In the Great Basin, most 

streams and lakes are interconnected with groundwater, 

which indicates that an approach using groundwater flow 

regime is best for a primary classification system. Secondary 

classifications we use are flowing versus standing water and 

salinity.

Groundwater Model 

By D.M. Miller and D.R. Bedford

The following treatment of groundwater systems is based 

in large part on a report for the National Park Service Mojave 

Network (Miller and others, 2006), which included part of the 

Great Basin.

Distribution and Management Significance

By definition, groundwater systems occur wherever 

there is water in a porous medium (that is, rock and soil) 

beneath the Earth’s surface. We restrict most of our discussion 

of groundwater systems to those that are saturated with 

respect to water. Most groundwater occurs in valley/basin 

sediments, and to a lesser degree, in bedrock in mountains. 

Surface expressions of groundwater occur in springs and seeps 

and a variety of ecosystems broadly categorized as “spring 

ecosystems” here. Groundwater systems often are connected 

to streams and rivers, and can be a source for streams (a 

gaining stream) or a net loss for streams (a losing stream).

The Great Basin region adopted by the GBILM project 

includes much of the northern Basin and Range physiographic 

province and parts of the Snake River Plain and adjacent 

plateaus; these provinces have distinctive hydrologic 

characteristics driven by distinctive geology. The Basin and 

Range province is marked by north-trending fault-block 

mountain ranges separated by wide valleys that have thick 

permeable valley-fill sequences. In the eastern part of the 

province, limestone and dolomite capable of transmitting 

and storing large quantities of water underlie the mountain 

blocks and valleys, creating an interconnected system 

generally known as the regional carbonate aquifer system. A 

consequence is that recharge in one mountain block aquifer 

may discharge in another area as a result of interbasin flow. On 

the scale of the entire Great Basin province, deep groundwater 

flow in the regional carbonate aquifer system generally is 

thought to be from the recharge area of eastern Nevada near 

and in Great Basin National Park; discharge occurs at low 

elevations such as Ash Meadows and Death Valley (Mifflin, 

1968; Winograd and Thordarson, 1975) and the Bonneville 

Salt Flats. The Snake River Plain and adjacent plateaus 

primarily are underlain by volcanic rock that rapidly transmits 

water, and the region is drained externally by Snake River 

surface flow.

Groundwater maintains springs, wetlands, lakes, and 

many streams of the Great Basin, and thus is of primary 

importance for aquatic and riparian plants and animals. 

Many upland animals also depend on water supplied by these 

sources, as do migrating waterfowl.

Ecosystem Components and Processes

Very little is known about ecosystems in Great Basin 

groundwater systems. They likely support a wide array of 

microorganisms and potentially other life forms. Because the 

biology of surface ecosystems dependent on groundwater 

(springs and streams) is better understood, we focus the 

groundwater conceptual model on the physics and chemistry 

of groundwater systems, and describe how they may drive 

many of the spring and stream ecosystems, which are 

elaborated on as separate models.

As described in the wet systems conceptual model 

(figs. 2.14 and 2.15), water flows into an aquifer system 

primarily through mountain recharge, flows out at springs 

and playas, and is transpired by phreatophytic vegetation. 

Flow through porous media can be modeled with the use of 

a linear gradient law in hydrogeological models. This makes 

groundwater systems amenable to analytical techniques unlike 

biological systems, which are more commonly analyzed 

statistically. Uncertainty enters hydrogeological models due 

to the heterogeneity of geological materials, lack of data (for 

example, measurements of subsurface rock properties), and 

natural variability of some conditions, such as infiltration. A 

conceptual model of the hydrogeologic framework including 

recharge and discharge conditions is fundamental to any 

site-specific groundwater flow model. Hydraulic properties 

of rocks and sediment, and faults and other perturbations 

to groundwater flow comprise a hydrogeologic framework 

conceptual model. Subsurface properties can be interpreted 

Chapter 4: Subsystem Models for the Wet System

By D.R. Bedford and D.M. Miller
76 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

remotely through geophysical techniques, well logs, surface 

maps, and pumping tests. Spring discharge can be measured 

with weirs and flumes, although discharge from combined 

plant and soil evapotranspiration is studied using heat and 

vapor flow methods. These measurements, combined with a 

hydrogeologic framework model and physical laws, can be 

used to model the response of a groundwater flow system. 

The most fundamental law of groundwater flow is that 

mass must be conserved (that is, the sum of all flows into an 

aquifer, minus the sum of all flows out, must equal the change 

in aquifer storage; fig. 4.1). If the change in storage is negative 

then flow out of an aquifer is greater than flow in, groundwater 

levels are dropping, and the aquifer is being depleted. When 

groundwater levels and storage are static, it implies that flow 

into the aquifer (recharge) is equivalent to flow out of the 

aquifer (discharge). A steady state condition results when 

recharge is balanced by discharge over a sufficiently long time 

period. 

A common conceptualization of an aquifer (fig. 4.2) 

presumes that recharge to the underlying formation is confined 

by the overlying impermeable layer so that the water level 

in a well penetrating the confining unit rises under pressure, 

perhaps even flowing to the ground surface in an artesian well. 

Water flows downhill from high elevations to low elevations 

and from high pressure to low pressure. Flow through a given 

cross-sectional area of a porous medium is proportional to the 

hydraulic gradient (difference in water-table elevation divided 

by the distance), where the constant of proportionality is called 

hydraulic conductivity—Darcy’s Law (Darcy, 1856). A storage 

coefficient (either specific yield or storativity) and hydraulic 

conductivity are the core parameters of the groundwater 

flow conceptual model. Another useful parameter is aquifer 

transmissivity, which is the product of hydraulic conductivity 

and thickness of saturated material. 

When an aquifer is perturbed from an equilibrium 

state by, for example, climatic variability or initiation of 

groundwater pumping, it responds at a rate controlled by 

its physical characteristics. The most important physical 

characteristic of an aquifer is its size, such that larger aquifers, 

both in area and volume, respond more slowly. Another 

important feature is whether the aquifer is confined by an 

impermeable layer and is under artesian pressure, or is an 

unconfined aquifer (fig. 4.2). Confined aquifers respond 

quickly—pulses of pressure are transmitted rapidly through 

the system; unconfined aquifers strongly dampen such 

pulses. Finally, there are the physical characteristics of the 

saturated thickness of the aquifer and the integrated hydraulic 

conductivity of its sediments, matrix, or fractures. Coarse 

gravel and fractured limestone more easily transmit water, 

whereas silt and clay layers and unfractured limestone do not. 

A larger transmissivity corresponds to a more rapid response. 

Estimating how quickly groundwater levels in an aquifer 

respond to perturbations requires information about the aquifer 

size, presence of a confining layer, depth to water, depth to 

bedrock, and hydraulic conductivity. 

Figure 4.1. Conservation of mass implies that the difference between inflow (recharge) and outflow (discharge) is 

balanced by a change in aquifer storage.

Unsaturated zone

Saturated zone

Inflow

∆ Storage

Outflow
Chapter 4: Subsystem Models for the Wet System 77

Groundwater Chemistry and Contamination

Evaporative moisture in the atmosphere, as well as 

transpiration from plants, is relatively pure water with little 

dissolved minerals. Condensation into raindrops, hail, snow, 

and sleet tends to form around dust particles, and precipitation 

delivers somewhat less pure water. Water is an effective 

solvent, reacting with most substances, and changes chemistry 

along its flowpath through the hydrologic cycle as it reacts 

with rock and sediment. Acidic precipitation facilitates 

dissolution of carbonate rocks, leading to enlarged solution 

cavities such as Lehman Cave in Great Basin National 

Park. Rock–water reactions dissolve mineral components 

so that the number of chemical species in solution and total 

concentration increases along a flowpath, usually measured 

in total dissolved solids (TDS). Groundwater in proximity 

to the zone of recharge at mountain fronts (usually high 

elevations) is generally low TDS (300–400 mg/L or less). 

Closer to discharge areas in valleys, TDS is usually greater 

than 1,000 mg/L. Groundwater flowing through the Great 

Basin regional carbonate aquifer system becomes saturated in 

carbonate and bicarbonate in isolation from the atmosphere. At 

groundwater discharge areas, such as Ash Meadows in Death 

Valley National Park, carbonate minerals are precipitated 

when groundwater comes into contact with the atmosphere, 

degasses, and evaporates. Evaporation from wet playas such 

as Devils Golf Course in Death Valley also leaves behind 

near-surface concentrated brine with TDS in excess of 50,000 

mg/L, along with salt deposits and other evaporite minerals. 

Ions in solution in groundwater reflect the geologic materials 

through which groundwater has passed. 

Groundwater quality is affected by natural and 

anthropogenic compounds, such as arsenic, nitrates, iron, 

manganese, hexavalent chromium, petroleum hydrocarbons 

and volatile organic compounds, as well as radon. Arsenic is 

a common naturally occurring groundwater contaminant in 

the desert, associated with sedimentary rocks derived from 

volcanic areas and geothermal systems. Arsenic contamination 

can be exacerbated by mining waste piles and by changes in 

oxidation-reduction conditions in the aquifer. Major sources 

of nitrates are fertilizer, animal wastes, and domestic sewage. 

Oxygen reacts with iron and manganese to form precipitates, 

so groundwater high in dissolved oxygen tends to be low 

in iron and manganese. Deep circulating groundwater, not 

exposed to the atmosphere for a long time, becomes depleted 

in dissolved oxygen and readily dissolves iron and manganese 

carbonates. A common indicator of overall groundwater 

quality is TDS, usually expressed in milligrams per liter or the 

equivalent parts per million. 

Figure 4.2. Illustration of confined and unconfined aquifers and associated potential water levels. 

tac09-0397_fig04-02

Bedrock

Confined aquifer

under pressure

Confining layer

Unconfined aquifer

Water table

Water rises

in well to

water table

Water flows from

artesian well

Potential

water level

Recharge

Unsaturated sediments
78 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Drivers of Ecosystem Change

Natural Drivers

Natural drivers of groundwater systems will vary 

in their significance depending on the aquifer type. For 

instance, regional groundwater systems are not likely to 

be affected by many biotic drivers, with the exception of 

evapotranspiration losses by phreatophytic vegetation. Smaller 

aquifers, particularly upland aquifers, are sensitive to climatic 

variations and biotic and physical losses in the form of 

evapotranspiration. Changes in discharge, water temperature, 

and water chemistry can be expected as a consequence of 

climate change.

Anthropogenic Drivers

Groundwater pumping has significant impacts on 

groundwater in the Great Basin. In addition to the direct 

effect on streams, diversion of streams that recharge aquifers 

also can affect groundwater systems. Pumping and diversion 

that reduce water tables can result in spring- and streamflow 

declines. Even when pumped at a rate that maintains water 

table levels, a pumped aquifer can alter the natural system 

by reducing water formerly available for plants and aquatic 

organisms, instead using the water for transpiring crops, for 

example.

Anthropogenic water contamination often is categorized 

as being derived from either a “point source” or a “non-point 

source.” Point sources are leaking underground tanks, spills, 

landfills, mining spoils, and septic systems, whereas non-point 

sources are atmospheric nitrogen deposition, pesticides, and 

fertilizers sprayed on agricultural fields. Shallow, unconfined 

aquifers are most susceptible to contamination, especially near 

urban areas, farmland, and roads. Deep aquifers and confined 

aquifers are less susceptible, especially over the time span 

of a few decades. However, once large aquifer systems are 

contaminated they can remain contaminated for long periods.

Ecosystem Dynamics

Most aspects of ecosystem change are dealt with 

in ensuing aquatic models. As described above, changes 

in recharge can drive immediate or gradual changes in 

discharge, depending on aquifer characteristics. Likewise, 

contamination of aquifers can have immediate or gradual 

effects. Key to understanding the dynamics of groundwater is 

an understanding of the relevant aquifer system.

Summary Points

Knowledge of aquifer characteristics and climate is 

sparse in the Great Basin, save for a few areas with dense 

wells, large populations, and dense climate stations. Increased 

density of hydrologic and climate data will improve our ability 

to model aquifers. Improved modeling will increase our ability 

to respond to disasters such as contamination events and 

to anticipate effects of drivers, such as climate change and 

increased groundwater pumping.

Wetland and Spring Models 

By D.R. Bedford and D.M. Miller

Spring systems in the Great Basin are found in settings 

ranging from alpine to desert valley floors and vary widely, 

and generally are poorly investigated and understood. The 

following treatment of spring systems is based in large part 

on a treatment of springs and wetlands for the National Park 

Service Mojave Network (Miller and others, 2006), which 

included part of the Great Basin.

Distribution and Management Significance

Spring systems in the most general sense are ecosystems 

formed where groundwater discharges at the Earth’s surface. 

Here, we include a wide variety of discharging systems 

from seeps and wet meadows to springs and spring-marsh 

complexes. We exclude from this model (1) those marshes 

along the edges of lakes because those systems interact closely 

with lakes and are better described in lake models, and (2) wet 

(discharging) playas, which typically have no surface water 

or have extremely saline surface water, and support a unique 

ecosystem. 

Spring systems vary widely, and can be described by 

a few fundamental variables that in general are related to 

aquifers. Aquifer characteristics (residence time, recharge 

source, lithology, chemistry) impart strong controls on 

groundwater discharge characteristics such as temperature, 

chemistry, and rates (Freeze and Cherry, 1979; Domenico and 

Schwartz, 1990; Fetter, 1994), as described in the groundwater 

model. In the Great Basin, springs often are the primary 

sources of water for small streams and riparian zones, and thus 

interact with surface-water systems.
Chapter 4: Subsystem Models for the Wet System 79

Three types of aquifers described in the wet model serve 

to differentiate springs: (1) small, upland aquifers; (2) local

valley aquifers; and (3) regional aquifers. The characteristics 

of these aquifer types as they relate to springs are summarized 

in table 4.1. Springs fed by upland aquifers tend to have cool 

water (<10 oC) and commonly go dry during droughts. Springs 

fed from local aquifers also may change seasonally and go dry 

during extended droughts. Springs fed by regional aquifers 

tend to be warmer (>20 oC), and high in solutes due to the 

depth and length of flow paths, and tend to have discharge 

rates that remain fairly constant over time intervals exceeding 

50,000 years (Winograd and others, 1992). Size of spring 

ecosystems is a strong function of groundwater discharge. At 

the low end of discharge, seeps tend to support upland and 

facultative wetland species adapted to drier conditions. At the 

high end of spring discharge, permanent ponds and riparian 

corridors are common and may support many endemic and 

endangered species.

From the perspective of aquatic and riparian ecology of 

spring systems, the position in the landscape, discharge rates 

and persistence, and water chemistry are determinants of the 

spring ecosystems. However, the ecology in combination with 

hydrologic characteristics dictates many of the characteristics 

such as morphology of the spring system. For instance, 

ephemeral seeps and wet meadows occur in and near 

mountains as a result of the very low and variable discharge 

from upland aquifers; water is fresh and cold, and plants in 

that environment include luxuriant xerophytic growth and 

in some cases phreatophytes. In contrast, springs with local 

aquifer sources typically occur in piedmont settings and range 

from low, fluctuating discharge with salty water, which may 

create salt grass systems that tend to trap fine materials and 

create spring mounds, to moderate discharge spring complexes 

with diverse phreatophytes, wildlife, and spring geometries. 

Regional aquifers form one end-member of the range of spring 

systems, for which large marsh complexes with open pools, 

situated in valley bottoms, are common. A general diagram of 

aquifers, flow paths, spring discharge types, and their typical 

locations in the landscape and associated hydrologic systems 

is shown in figure 2.14.

Challenging issues regarding Great Basin spring 

ecosystems are important for nearly all land managers in 

the region. Because of their importance for surface and 

groundwater availability, springs often are managed under 

long-standing water rights legislation. They also tend to 

support species of interest, rare, threatened, and endangered 

species (for example, Devil’s Hole pupfish [Cyprinodon

diabolis] and redband trout [Oncorhynchus mykiss]) due to 

their isolation and endemism. Invasive species are common in 

springs, difficult to manage, and commonly alter habitat and 

lead to local extinction of native species.

Springs in arid regions may serve as keystone 

ecosystems, commonly providing the only available water 

and habitat for many plant and animal species. Steep 

gradients of moisture, soil types, biodiversity, competition, 

and productivity create abrupt ecotone boundaries. Springs 

also may serve as paleo-refugia and as habitats in which the 

evolutionary processes of natural selection, isolation, and 

adaptation are coupled to assemblage composition through 

island biogeographic and historical community development 

processes (Stevens and Springer, 2004).

Ecosystem Components and Processes

Spring systems are largely driven by spring morphology, 

and the persistence and physiochemistry of water discharge. 

Springs exhibit many morphologies and a single spring may 

change morphology with time. Common types range from 

lush open pools to seeps that exhibit damp earth with no open 

water; between these end members is a wide variety of wet 

meadows, marshes, permanently wet short stream segments in 

canyons, spring mounds, and saline springs with few vascular 

plants. 

Aquatic organisms, riparian vegetation, and associated 

fauna all vary with spring type (Sada and others, 2005), 

but an anthropogenic influence is ubiquitous, complex, and 

severe. As a result, human modification of springs must be 

considered in classifications. For instance, a marsh that is 

cleared and dredged to provide open water for livestock may 

be functionally distinct from less-disturbed open-pool springs.

Table 4.1. Characteristics of springs related to three types of aquifers common in the Great Basin.

Characteristics

Aquifer type

Upland Local Regional

Aquifer size Very small Small Large 

Water temperature Cold Cool Warm

Solute concentration Very low Low to moderate Moderate to high

Total discharge Very low Low Moderate to high

Discharge persistence Highly ephemeral Ephemeral Invariant

Discharge site Mountain Piedmont Valley bottom

Typical discharge morphology Wet meadow, seep, pothole Small spring, seep, spring mound Spring-marsh complex, wet playa
80 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Groundwater Flow Regime

Despite the human influence, groundwater characteristics 

are a primary determinant of many biotic characteristics of 

springs, providing a multi-dimensional space in which springs 

of various types lie. Figure 4.3 shows some of the primary 

dimensions that tend to structure biota, with biodiversity 

portrayed as one metric of biotic structuring. Springs and other 

discharge types also can be plotted in discharge-biodiversity 

space (fig. 4.4) with the observation that spring brook length 

and spring pool size correlate positively with biodiversity and 

negatively with spring salinity (Sada and Nachlinger, unpub. 

data, 2009).

Spring systems are dynamic systems with inherent and 

anthropogenic disturbance regimes. Excluding anthropogenic 

disturbance, spring variability mimics hydrologically 

determined environmental conditions, each of which can 

be mapped into biotic response. Variability of biota tends 

to be determined by aquifer size, gradients in microclimate 

(temperature and precipitation), variability in hydrologic 

regime, and size and length of runout spring brook, which is 

correlated with groundwater discharge. Figure 4.5 shows an 

idealized example of a spring system with associated runout 

stream, showing typical trends in environmental and biotic 

factors. 

Mineral precipitation, which is driven by physiochemistry 

of water, flow rate, and evapotranspiration, may be 

important in springs. Precipitation of calcite (calcareous 

muds and travertine) or silica (opal or sinter) is especially 

pronounced in thermal springs but also occurs in cold water 

springs. Precipitation and sedimentation modifies discharge 

geomorphology, changing aquatic and riparian habitat.

Figure 4.3. Illustration of five gradients in spring discharge environment and effects on 

biodiversity. Each gradient can be related to aquifer characteristics, as shown qualitatively with 

colors.

Discharge rate

Low biodiversity High biodiversity

Discharge area

EXPLANATION

Environmental context

Discharge variability

Fresh Solute concentration

Persistent Variable

Small (seep) Large (meadow or playa)

Low biodiversity High biodiversity

Low biodiversity High biodiversity

High biodiversity Low biodiversity

High biotic density Low biotic density

Low High

Saline

DIMENSIONS OF VARIABILITY THAT STRUCTURE BIOTA

Low elevation, no stream 

connections

High elevation, 

stream connections

Regional aquifer Local aquifer Upland aquifer
Chapter 4: Subsystem Models for the Wet System 81

Spring Vegetation

With the exception of species that 

tolerate extremes in spring physiochemistry, 

such as geothermal, saline, alkaline, and 

anoxic conditions, spring vegetation is 

similar to stream-side riparian vegetation 

communities, particularly the presence 

of grasses and sedges. Large springs with 

associated streams may support riparian 

trees, as discussed in the stream and riparian 

model. In addition to emergent vegetation, 

spring systems typically include subaquatic 

macrophytes and planktonic and benthic 

algae.

Primary productivity in springs and 

wetlands primarily is determined by the 

amount and quality of flowing water. 

Stagnant or deep-water wetlands tend to 

have low productivity, while slowly flowing 

springs have high productivity (Mitsch and 

Gosselink, 2000).

Spring vegetation interacts with 

geomorphic processes by capturing fluvial 

and eolian sediment, causing infilling of 

open water. This alteration of habitat is 

counteracted by natural disturbance events 

such as scour by floods and digging by 

animals. In addition, algae-mediated calcite 

deposition as tufa or calcareous muds causes 

infilling.

Figure 4.4. Illustration of spring types and how they vary with 

discharge and total biodiversity. 

Figure 4.5. Illustration of typical components and gradients in open-pool springs and associated runout stream/riparian 

zone.

tac09-0397_fig04-04

TOTAL BIODIVERSITY

DISCHARGE

Open-pool spring

with long

spring brook

Spring marsh with

short spring brook

Wetland and wet meadow

Seep

Pothole

Freshwater discharge

Saline water

discharge

Spring mound

Wet playa

Explanation

Low solute concentrations

High solute concentrations

Increasing environmental variabiltiy

Increasing organic material

Decreasing riparian vegetation

Decreasing environmental variability

Decreasing organic material

Increasing riparian vegetation

Discharge Area

Spring substrate

Spring soil

Aquifer Type

Upland

Local (shown)

Regional

Floodplain soil

Stream substrate

SPRING RIPARIAN

Recharge

(important for

upland aquifers)

Groundwater table
82 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Geomorphic Processes

The geomorphic setting of springs as well as processes 

dictated by the setting (for example, slope, substrate 

characteristics, soils) and discharge all affect spring orifice and 

stream runout characteristics. The geomorphic setting affects 

streams in numerous ways. Lithology and soil characteristics 

can determine how discharge is manifested spatially, for 

example, as point sources, seeps, and discharge lineaments. 

Surface slope determines the flow rates away from discharge 

locations, and aspect has strong effects on evaporation rates.

Geomorphic processes acting in or near spring 

systems can maintain and modify orifice and stream 

runout characteristics. Processes affecting springs include 

flooding, scouring, and filling. External processes include 

erosion/deposition of sediments, rockfall, and freeze-thaw 

disturbances. Little is known about potential feedbacks of 

springs on the surrounding landscape (Stevens and Springer, 

2004).

Spring Invertebrates and Vertebrates

Spring invertebrates are important consumers, shredders, 

and detritovores whose life cycles are tied to hydrology, 

vegetation floristics, and physiognomy (Mitsch and Gosselink, 

2000). Sada and others (2005) determined that species 

richness of aquatic macroinvertebrates may be greatest at 

intermediate levels of natural and anthropogenic disturbance, 

and that general macroinvertebrate characteristics could 

not be predicted from simple metrics of environment, such 

as elevation, and disturbance (that is, springs are highly 

individualistic, as are their macroinvertebrate characteristics at 

a large scale).

Fishes are important consumers in springs, and are 

affected by water level, spring “openness” (a function of 

hydrology, geomorphology, and vegetation), chemistry, and 

temperature (Mitsch and Gosselink, 2000; Andersen and 

Deacon, 2001). Birds are abundant at springs, including 

obligate and migratory species (Mitsch and Gosselink, 2000). 

Birds act as secondary consumers, can maintain moderate 

levels of disturbance through bottom feeding activities, 

and can be important vectors for transmittal of seeds and 

organisms into and out of spring systems. Little is known 

about the characteristics of springs that determine bird 

community characteristics. Mammals (for example, beaver 

and muskrat) probably are unevenly distributed among Great 

Basin springs. However, mammals of all types extensively use 

springs, and act as consumers, ecosystem engineers, and seed 

and organism vectors.

The relative degree of isolation of spring systems either 

leads to endemism or development of dispersal mechanisms. 

Dispersal mechanisms vary with organism type, and include 

passive or active dispersal. Passive dispersal includes dispersal 

by wind, water, gravity, or other organisms. Active dispersal is 

exhibited in strong-flying invertebrates, birds, bats, and larger 

mammals including humans (Stevens and Springer, 2004).

General Spring Model

Figure 4.6 presents a general spring system control model 

incorporating key system components, processes, and drivers. 

Springs are driven predominantly by groundwater discharge, 

which determines the amounts and basic physiochemistry of 

water emerging from an aquifer. The orifice type determines 

the general shape of a spring, which is in part determined 

by the landscape template (not shown). Orifices with large 

discharges and appropriate configurations will have outflow in 

pools, marshes, and streams that are important parts of spring 

habitat.

Water physiochemistry and the configuration (geometry, 

soils, etc) of the orifice and outflow channels determine 

habitat characteristics of spring systems because vegetation 

communities are dependent on spring water physiochemical 

conditions, as well as community dynamics. Spring systems 

often support aquatic and terrestrial organisms, which sets up 

interspecific and intraspecific competition, facilitation, and 

food webs. A more detailed treatment of aquatic terrestrial 

dynamics is provided in the “Aquatic Ecology Control Model” 

section.

Geomorphic processes in springs with sufficient 

discharge create a dynamic system. Fluvial erosion or 

deposition and dust trapping (not shown in conceptual model) 

is enhanced by vegetation and the presence of moisture at the 

surface. Dust-trapping and vegetation expansion compete with 

orifice flow and scour to maintain a dynamic spring pool and 

spring brook system.

Geothermal Springs

The Great Basin is home to dozens of thermal springs 

that have many characteristics that set them apart from cool 

springs. Although temperatures range widely, springs that 

are warm (~20°C) to hot (>38°C) [70; >100°F] are generated 

from regional, deep aquifers that encounter hot rocks at great 

depth. Most occur in valley bottoms. They exhibit persistent 

flow but may have several spring pools and brooks with 

different temperatures and discharge. Edifices typically are 

large tufa mounds, although siliceous sinter complexes (for 

example, Fish Lake Valley) occur as well. Mineral deposition 

by precipitation and algal-mediated processes strongly shape 

edifices of many thermal springs. Complex ecosystems of 

thermophilic organisms may be present. However, these hot 

spring systems have been widely targeted for development by 

humans, and nearly all probably are highly disturbed. Water 

in runout brooks commonly is sufficiently cool to support 

cool spring aquatic communities and to be used by humans. 

However, some geothermal springs have unusually high 

concentrations of trace metals, minerals, or salts that make the 

waters toxic to many life forms.
Chapter 4: Subsystem Models for the Wet System 83

Figure 4.6. Control model of spring ecosystems including key processes (arrows), components (boxes), and drivers (ellipses).

tac09-0397_fig04-06

VEGETATION

COMMUNITY

REGIONAL CLIMATE

Precipitation, temperature

seasonality

GEOMORPHIC

PROCESSES

Scour, channel

change

ORIFICE/POOL/

BROOK

Physiochemical gradients

gradients and mixing

flow rates

GROUNDWATER

Aquifer type,

discharge

ORIFICE

Discharge dynamics

Linking process

Driver

Component

Key component

EXPLANATION

Key linking process

GROUNDWATER

EXTRACTION WATER DIVERSION INVASIVE SPECIES

LIVESTOCK GRAZING

AQUATIC ORGANISMS

Production, food webs,

decomposition, disturbances

TERRESTRIAL ORGANISMS

Production, food webs,

decomposition, disturbances

Recharge, evapotranspiration

Discharge, physiochemistry

Precipitation, evapotranspiration

Erosion deposition

Herbivory, predation

Herbivory, predation

Competition, herbivory, predation

Competition, herbivory, predation

Discharge

Erosion, deposition,

abrasion, stability,

encroachment

Habitat structure, disturbance

Fluvial disturbance

resource transfer,

dispersal

Fluvial disturbance

resource transfer,

dispersal
84 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Drivers of Ecosystem Change

Natural Drivers

The primary determinates of spring ecosystem form 

and function are aquifer type/discharge characteristics, 

environmental gradients away from discharge site, and 

anthropogenic modifications. Springs, by definition, are where 

the groundwater table intersects the ground surface, thus 

groundwater is the primary determinate of the physiochemistry 

of water delivered to springs. Changes in discharge rates or 

physiochemistry can dramatically alter spring characteristics 

and function, as well as cause them to dry out. However, due 

to the nearly ubiquitous modification of springs in the Great 

Basin by human activities, land use disturbance clearly is an 

important anthropogenic driver.

Anthropogenic Drivers

Pre-historic and historic use of large flowing springs is 

important to understand for assessments of modern spring 

biotic conditions. Seeps, spring mounds, and wet meadows 

have been widely developed as local water supplies that 

are not robust enough for irrigation. Nearly all springs and 

wetlands in arid environments have been severely impacted 

by human activity (Sada and Pohlmann, 2006). A survey 

of 505 springs in northern Nevada (Sada and others, 1992) 

determined that more than 85 percent of these springs were 

moderately or highly disturbed by diversion and livestock. 

Less than 5 percent of the springs in this study were unaffected 

by human activity. Shepard (1993) noted that human activities 

have altered the physical and biological condition of most 

springs in western North America. Anthropogenic stress 

factors include diversion (groundwater pumping, spring 

box capture and piping to troughs, channelization, etc.), 

impoundment, nutrient pollution, introduction of non-native 

plants and animals, and trampling by humans and non-native 

ungulates (Sada and Pohlmann, 2006). Water diversions, 

predation by exotic species, grazing, pollution, urbanization, 

and recreation have caused extinctions of spring populations 

since the late 1800s. Across the Great Basin, there is a loss 

exhibited by 60 percent of the endemic species (virtually all 

fishes, insects, and amphibians), of which all but 2 percent 

have had major declines, and 8 percent have been extirpated. 

Spring habitat and population loss peaked after each world 

war and was static during wars, indicating a tight connection 

to economic conditions (Sada and Vinyard, 2002).

Historical ecology has many potentially large applications 

for springs and wetlands. Paleoclimate and paleobotanical 

records describe the sediments under springs and marshes, 

and faunal records, though limited, typically are available as 

well. Study of past hydrologic and ecologic conditions can 

be valuable for establishing reference conditions with which 

modern conditions can be compared (Swetnam and others, 

1999) and future conditions projected.

Decreased discharge increases the variability of the 

spring environment and shortens spring runout length, 

which alters aquatic species composition. Native Americans 

and early settlers commonly increased access to water by 

excavating the pools and digging shallow wells. It is difficult 

to determine original characteristics for these modified 

springs. Some of the anthropogenic modification likely 

involved removal of phreatophytic vegetation to enhance 

water availability.

Introduction of non-native species also has been a 

consequence of historical activities. Sport fish, aquarium 

fish, and mosquitofish introductions were widespread. 

Trampling by non-native ungulates such as livestock, wild 

horse, and burro populations has impacted springs in ways 

similar to excessive grazing in riparian systems by increasing 

temperature, fine substrate sediments, and nutrient loading 

(Kauffman and Krueger, 1984; Fleischner, 1994). More 

recently, groundwater contamination by pollution, increased 

nutrient concentrations, and refuse disposal from mine 

stockpiles and tailings, landfills, sewage treatment ponds, 

fertilizers and pesticides, hazardous waste disposal, and 

accidental spills of hazardous chemicals and waste have 

become significant problems.

Modern increases in groundwater extraction is likely the 

single greatest threat to springs by reducing or eliminating 

discharge. Paving over or otherwise disturbing groundwater 

recharge zones, especially in mountainous areas and along 

mountain fronts, may significantly impact groundwater flow 

systems. The effects of groundwater extraction may take 

decades to centuries to manifest. Effects of water diversions 

and pumping are similar to the consequences of drought. 

Reduced discharge results in loss of endemic species and 

reduction of biodiversity. Drought-intolerant aquatic species 

(for example, mayflies, caddisflies, and crenobiontics) are 

replaced by drought tolerant taxa (for example, midges, 

beetles, corixids, etc.) and non-native and upland vegetation 

may become dominant members of the riparian community 

following reduction or elimination of surface discharge (Sada 

and Pohlmann, 2006).

Changes in climate can stress all aquifers but effects will 

be most immediate in upland and local aquifers with short 

flow paths. Alterations in watershed budgets through increased 

aridity (that is, little recharge occurs) or altered amounts 

and timing of snowmelt can decrease discharge or otherwise 

disturb spring ecosystems. Springs in deserts are highly likely 

to respond to climate changes and such changes can have 

cascading effects on wildlife dependent on the water sources.

Invasive species threaten nearly all water sources in 

the Great Basin, and include invasive plants (for example, 

saltcedar and annual grasses), invertebrates, fish, and 

mammals.
Chapter 4: Subsystem Models for the Wet System 85

Ecosystem Dynamics

Spring ecology in arid regions generally remains 

unsynthesized and relatively poorly studied. Studies have 

focused on characteristics of springs (for example, flow and 

water quality), individual taxa or biota, or on selected topics 

at local, or rarely, regional scales. High demands for water in 

arid lands and the inherent complexity of springs likely have 

retarded development of comprehensive understandings of 

spring ecosystem (Stevens and Springer, 2004). As a result, 

much is known about biotic composition of Great Basin spring 

systems, and little is known about the processes and dynamics 

that act in them. Consequently, we develop our conceptual 

model primarily around studies from other regions that have 

applicability to Great Basin springs.

Benthic macroinvertebrates, aquatic insects, reptiles, 

amphibians, and (mostly endemic) fish species in springs 

and seeps in the Great Basin have been identified as a high 

priority by land management agencies, highlighting a need 

for integrated eco-hydrologic models for these systems. 

Rather than attempt over-simplified, and probably incorrect, 

conceptual models on the basis of inadequate data, the 

approach taken here is to present conceptual models of what is 

known about spring-fed ecosystems and highlight information 

gaps. This approach emphasizes springs with pools and 

outflow streams, about which most is known.

Despite the unique characteristics of individual desert 

springs, some aspects of their ecological relationships may be 

generalized. Small springs tend to be autotrophic, with little 

dependence on allochothonous carbon sources (Minshall, 

1978; Cushing and Wolf, 1984). Within large spring systems, 

environmental variation tends to be lowest near the source, 

where conditions are more stable, and higher downgradient 

where variability in temperature, discharge, and dissolved 

oxygen concentration is greater (Deacon and Minckley, 

1974). Abundance of plant and animal populations may vary 

seasonally as a function of food availability, temperature, 

reproduction, and migration of species along a spring brook 

(Sada and Pohlmann, 2006), although spring morphology 

influences the types of species present. Habitats may be 

partitioned based on factors such as water depth and velocity, 

and substrate (Deacon and Deacon, 1979; Sada and Herbst, 

unpub. data, 1999). Aquatic organisms in thermally and 

geochemically stressed springs, where osmoregulation and 

respiration are difficult (Brock, 1994; McCabe, 1998), tend to 

be tolerant of harsh conditions; some flies and cyanobacteria 

are examples. 

Most springs in the Great Basin host saltgrass (Distichlis

spicata) and many host sedges (Carex sp.). Deeper waters 

commonly have bulrushes (Scirpus sp.) and lizardtail, 

and larger marshes and riparian zones may have mesquite 

(Prosopis sp.), willow (Salix sp.), or salt cedar (Tamarix 

ramosissima). Marsh birds and waterfowl use springs during 

migration, and nesting by blue-winged teal (Anas discors), 

cinnamon teal (A. cyanoptera), and ruddy ducks (Oxyura 

jamaicensis) is common. There are many aquatic amphibians 

such as toads and salamanders. Spring ecosystems also 

support enhanced populations of mammals such as rodents, 

bats, rabbits and ungulates (Minckley and Brown, 1994).

The biota of arid land spring systems show characteristics 

attributed to the colonization and extirpation dynamics of 

small, isolated habitats (Sada and Pohlmann, 2006). Isolation 

of springs and relatively small habitat patch size may promote 

aspects of island biogeography, including endemism and 

rarity. Both the occurrence and geographic sparseness of 

Great Basin springs certainly has significant effects on birds, 

reptiles, amphibians, and mammals. Ephemeral springs, 

and springs with harsh thermal and geochemical conditions, 

tend to have low species richness whereas perennial springs 

typically include more species and larger populations (Erman 

and Erman, 1995). Compared to perennial springs, ephemeral 

springs tend to harbor more upland and drought resistant plant 

species and include more vagile aquatic organisms capable of 

rapid colonization and recolonization. Spring ecosystems also 

are influenced by elevation-determined climatic gradients and 

by natural and anthropogenic disturbance stressors. 

Groundwater Orifice and Discharge Dynamics

Discharge is determined by groundwater characteristics 

and orifice type, and may be augmented by stream runoff 

(fig. 4.7). Local slope and microtopography may allow 

runout (that is draining of springs), which creates (commonly 

short-length) streams and associated riparian features. Flow 

conditions (depth, velocity) and local soils (texture, structure) 

determine sediment transport rates, which can result in 

erosion or deposition in runout channels or the spring orifice. 

Organisms are sensitive to water depth; for instance, the 

Devils Hole pupfish is extremely sensitive to small changes 

in water levels and other environmental factors (Chernoff, 

1985; Andersen and Deacon, 2001). Vegetation communities 

and associated invertebrates (not shown) respond to water 

physiochemical conditions (temperature, chemistry, flow rates) 

depending on their adaptations to those types of environments 

and disturbances. As stated previously, vegetation (possibly 

facilitated by dust deposition) may encroach into runout or 

orifice features given appropriate (that is low velocity, aerobic) 

water conditions.
86 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Figure 4.7. Control model emphasizing interactions between discharge dynamics and geomorphology. Bold outline indicates key 

components.

tac09-0397_fig04-07

VEGETATION COMMUNITY

Composition, structure

density, cover

REGIONAL CLIMATE

Precipitation, amount,

intensity, duraion

LANDSCAPE TEMPLATE

Topography (slope),

soil (texture, structure)

ORIFICE MORPHOLOGY

Width, depth, discharge

amount

DISCHARGE

Amounts, physiochemistry

RUNOUT

Channel width and depth,

substrate

SEDIMENT TRANSPORT

Erosion, deposition

GROUNDWATER

Aquifer type,

discharge

Linking process

Driver

Key component

EXPLANATION

Key linking process

Recharge

Pool dimensions, physiochemistry

Channel scour, filling

Drainage

Flow velocity

Stream channel/

riparian

characteristics

Abrasion, erosion, burial

Spring Vegetation Dynamics

A more detailed model of emergent vegetation 

dynamics in spring systems (fig. 4.8) is based on Stevens and 

Springer (2004) and Plumb and others (2005). The structure, 

composition, density, and cover of vegetation communities 

are determined by discharge/flow dynamics, which may 

be modified by trampling, other natural causes, or through 

anthropogenic mechanisms. The model considers how 

ungulates and other mammals interact with predators, and 

how both affect the local environment through trampling, 

seed dispersal, and as consumers. Riparian overstory and 

understory plants tend to be denser near spring brook channel 

heads, where flow is most consistent, and less dense and 

spread more widely farther down the spring brook. Plant 

diversity tends to increase with distance from the spring as 

well. Wildlife habitat varies with these plant patterns. Invasive 

species may create new disturbances or may out-compete 

native species.
Chapter 4: Subsystem Models for the Wet System 87

Spring Fauna

Variability in physiochemical properties is small near 

spring mouths and increases farther downstream, leading 

to variations in fauna according to their tolerance for 

environmental variability. Aquatic communities structured 

by variability are further modified by availability of organic 

material, which typically is limited near the spring source but 

increases downstream (Thorup, 1974). As a result of these 

environmental factors, aquatic communities tend to be low 

diversity in and near spring sources. Species richness also is 

correlated with variable substrate composition and current 

velocity (Sada and Nachlinger, unpub. data, 2009). Greater 

amphibian density is found downstream in open and varied 

vegetation than near springs (Bradford and others, 2003).

Summary Points

Wetland and spring ecosystems involve complex 

interactions of groundwater systems, discharge regime, orifice 

geometries, vegetation, and faunal use. They are very sensitive 

to physical and chemical disturbances as well as groundwater 

withdrawals and diversions. Nearly all spring and wetlands in 

the Great Basin have experienced anthropogenic impacts for 

as much as several thousands of years. There is much research 

needed to understand the ecology of Great Basin spring 

ecosystems because they commonly are isolated and contain 

endemic organisms that may make many systems unique. 

More information also is needed to assess the resilience of 

spring systems to climate change, increased water pumping 

and diversion, invasive species, fire regimes, and pollution.

Stream and Riparian Models

By D.R. Bedford

Distribution and Management Significance

Streams and their adjacent riparian zones are widespread 

in the Great Basin, and yet encompass less than 3 percent of 

the area. Several alluvial-valley rivers lie within the Great 

Basin area: Humboldt, Snake, and White Rivers, and Meadow 

Valley Wash. In addition, lower reaches of several rivers that 

head in the Sierra Nevada, Uinta Mountains, and the Owyhee 

and Colorado Plateaus also lie within the Great Basin. 

Countless small streams lie in mountain blocks, the larger of 

which have lower reaches that extend onto adjacent alluvial 

piedmonts. More ephemeral, intermittent streams exist; these 

flow only in response to seasonal snowmelt or rainfall-induced 

flooding.

The widespread distribution of countless perennial and 

ephemeral streams in the Great Basin has been a resource 

for ranchers, farmers, miners, and many others in need of 

water. As a consequence, most of these streams have been 

significantly modified in historic and prehistoric times.

Stream and streambank (riparian) systems consist of 

flowing water and associated channel bed and floodplain 

environments. Two aspects of stream and riparian zones 

separate them from other systems in semi-arid regions. The 

presence of (1) perennially or intermittently flowing water 

that typically spans multiple environmental zones creates, (2) 

unique mosaics of heterogeneous flow and bank environments tac09-0397_fig04-08

WETLAND VEGETATION

Composition, structure, density, cover

Driver

Component

EXPLANATION

Linking process

ALTERED FLOW

Impoundment,

diversion

INVASIVE SPECIES

Competition, disturbance

PREDATORS

UNGULATES Herbivory

Trampling

Seed Dispersal

Figure 4.8. Stressor model of emergent vegetation in spring systems showing structural components (rectangles), 

anthropogenic (ovals) drivers, and functional relations (arrows).
88 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

that support a high degree of biodiversity. However, 

because all streams and rivers are dynamic and adjust their 

characteristics to climate, geology, topography, base level, 

and vegetation (Fitzpatrick, 2001), they often share common 

processes, features, and interactions across a wide range 

of environments (Patten, 1998). Streams with intermittent 

flow generally lack riparian zones and aquatic species, 

although enhanced xerophytic growth adjacent to channels is 

common in these areas. Ephemeral streamflow provides some 

geomorphic and hydrologic spanning across environmental 

zones, similar to perennial streams. The following model 

development does not consider the poorly studied intermittent 

streams further.

Stream and riparian areas of semi-arid landscapes, 

despite their small total cover, are among the biologically most 

diverse and important ecosystem components in the Great 

Basin (Naiman and Decamps, 1997; Patten, 1998). In addition 

to obligate aquatic species, up to 80 percent of all vertebrates 

depend on stream and riparian areas for at least one-half 

of their life cycles, and more than one-half are completely 

dependent on these habitats (Chaney and others, 1993). Stream 

and riparian areas also serve as important connectors for 

energy and materials among nearly all Great Basin ecosystem 

components. They integrate effects from upstream and 

downstream regions, and in essence affect and are affected by 

all ecosystems.

The primary distinction in Great Basin riparian systems is 

between alluvial rivers and mountain streams. Most perennial 

streams in the Great Basin are mountain streams. Mountain 

streams tend to have distinct channel morphology because 

they are constrained by bedrock. Habitat in mountain streams 

varies relatively systematically with position in the watershed 

(Montgomery and Buffington, 1997). Mountain streams 

respond more quickly to precipitation and snowmelt and tend 

to be connected to small (and thus more climatically sensitive) 

aquifers. In contrast, alluvial rivers occupy wide, low relief 

valleys, and tend to have relatively high and mobile sediment 

concentrations. The course of alluvial rivers in wide valleys 

vary with dynamics of channel form determined through 

interactions with water and sediment supply, and riparian 

vegetation (Montgomery and Buffington, 1997; Murray and 

Paola, 2003), and these systems largely are driven by longterm groundwater and climate characteristics. In this section, 

we focus on the majority of riparian systems: mountain 

streams. 

Ecosystem Components and Processes

Stream and riparian systems are best described by the 

interactions among precipitation, flow, and geomorphic 

dynamics through the channel and floodplain, and aquatic 

and riparian biota. These systems commonly transect large 

areas with significant altitude ranges and thus interact with 

diverse dryland systems in the watershed. Because stream and 

riparian systems integrate processes in the watershed, we use 

upland watersheds models and theory as part of our modeling 

construct. The complex interactions among the upland systems 

are not treated here, and much more work is needed in order to 

better understand stream riparian connections with each other.

Figure 4.9 presents our conceptual model for riparian 

systems, which is modified from models for adjacent 

ecosystems (Miller and others, 2006). The top-level 

driver is regional climate, which affects riparian systems 

by adding water through precipitation and determining 

environmental gradients in wind, radiation, and temperature. 

This, in turn, affects water and energy budgets (for example 

evapotranspiration, snowmelt). Precipitation is partitioned 

into soil moisture, streamflow, and recharge to groundwater as 

represented in the model by “Upland Watershed Hydrology.” 

The upland watershed configuration also controls sediment 

delivery and flux of organic matter and nutrients to stream 

channels. Depending on upland watershed characteristics, 

groundwater may significantly affect stream levels. The flow 

regime determines magnitudes and temporal characteristics 

of streamflow, which interacts dynamically with the 

stream channel and sediment load to determine channel 

geometry. The channel and its flow interact with vegetation

and floodplain soils, determining the water, chemical, and 

sediment budgets for each. The vegetation community and 

fauna experience facilitation and competition among various 

species and functional types. 

Anthropogenic drivers (orange ovals) also are shown in 

figure 4.9 to illustrate where each has its greatest effects on the 

stream-riparian system. The drivers are discussed in section, 

“Drivers of Ecosystem Change.”

Upland Watershed Hydrology

Most water in any section of stream and riparian zones 

has sources in the upland watershed. Water entering the 

watershed as precipitation or snowmelt must make its way to 

stream channels by surface or subsurface (groundwater) flow. 

The partitioning of precipitation into surface and groundwater 

will be determined by the type of precipitation, other climate 

parameters such as temperature, as well as the spatial 

configuration of watershed characteristics, which integrates 

its long-term geomorphic history. An example of the effects 

of upland watershed characteristics and processes on riparian 

form and function is through long- and short-term effects 

on basin shape and interactions with groundwater. Steep, 

narrow basins tend to have narrow riparian zones with plant 

communities dominated by alder (Alnus sp.), and gentle, wider 

basins tend to have wide riparian zones with complex riparian 

vegetation and aquatic community structure (Patten, 1998; see 

fig. 4.10). 
Chapter 4: Subsystem Models for the Wet System 89 Figure 4.9. Control model of stream and riparian systems, illustrating dynamic coupling of climate, watershed characteristics, streamflow and sediment transport, and vegetation and faunal communities. Double arrows between stream channel, floodplain soil, vegetation, and faunal community boxes include numerous feedbacks. Drivers such as fire, land use, stream diversion and groundwater extraction enter into the model in several places (not all shown), with complex effects. Heavy line weight and boxes with color represent key components.

tac09-0397_fig04-09

FLOW REGIME

Flow regime characteristics:

variability, magnitude

duration, timing

STREAM CHANNEL

Channel geometry, substratum

Sediment transport, erosion and deposition

FLOODPLAIN SOILS AND RESOURCES

Water, soil, soil organism, organic matter

minerals

Water and nutrients storage and cycling,

stability, decomposition

UPLAND WATERSHED HYDROLOGY

Water and sediment delivery

GROUNDWATER

Aquifer type, 

physiochemistry

VEGETATION COMMUNITY

Trees, shrubs, herbs, grass,

below-ground organisms, woody debris

Production, life cycles facilitation,

competition, structure

FAUNAL COMMUNITY

Vertebrates, invertebrates, algae

Production, competition,

predation

REGIONAL CLIMATE

Precipitation, wind, radiation, snowmelt,

ozone

INVASIVE EXOTICS

FIRE REGIME

WATER EXTRACTION

STREAM DIVERSION

LIVESTOCK GRAZING

ComponentDriverKey linking process

EXPLANATION

Linking process

Flow:

overland, channel

Dispersal, succession, disturbance,

 Water and nutrient flux

Water and energy balance

Resource, habitat

decomposition,

bioturbation

Energy, sediment

transport cap.

Recharge

Channel stability

Discharge,

transmission loss

Precipitation,

snowmelt

Feeding, habitat

Water, sediment,

nutrient flux baseflow

Channel modification,

erosion, deposition

Draw-down

Flow reduction

Trampling, nutrient loading

Feeding, trampling

Competition,

predation

Competition, predation

PHYSICAL CHARACTERISTICS | BIOTIC CHARACTERISTICS
90 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

tac09-0397_fig04-10

Bedrock

Bedrock

Upland Upland Riparian

flood plain

Upland Upland Riparian

terrace

Riparian

flood plain

Riparian

terrace

A.

B.

Water table

Water table

Figure 4.10. Influence of upland watersheds through basin geometry on the structure of 

riparian system components. (A) wide valley with a losing stream, (B) narrow valley with a 

gaining stream. (From Scott and others, 2005, which is modified from Goodwin and others, 1997.)
Chapter 4: Subsystem Models for the Wet System 91

The delivery of materials from upland watersheds 

also is determined by the dry upland ecosystems. Stream 

channel networks act as a template for organizing vegetation 

and hydrological (ecosystem) dynamics within the upland 

watershed through processes such as incision and aggradation 

(Caylor and others, 2005). In turn, the timing, amounts, and 

quality of water, organic material, nutrients, and sediments 

delivered to channels from upland watersheds exerts strong 

controls on riparian systems (Frissell and others, 1986) as well 

as helping to shape the long-term evolution of drainage basins 

(Collins and others, 2004).

Flow Regime

The streamflow regime describes magnitude and timing 

of flowing water and varies greatly depending on the spatial 

and temporal scales. Modern theory of streams and rivers 

recognizes that they are complex networks that include 

distinct zones where hydrogeomorphological processes and 

ecology are very similar (Poole, 2002; Benda and others, 

2004; Thorp and others, 2006). These zones form in response 

to long-term geomorphic processes and, barring anthropogenic 

modification, set the inherent scale in determining a flow 

regime. In short, determining the flow regime for monitoring 

goals depends on the location and time scale of interest and 

the geomorphic history.

The flow regime is one of the primary determinates of 

ecosystem form and function in stream and riparian systems 

(Chambers and others, 2004). Ecologically important aspects 

of flow regime include the magnitude, frequency, duration, 

predictability, and rate of change of flow conditions (Poff 

and others, 1997; Lytle and Poff, 2004). Morphological, 

behavioral, and life history adaptations of numerous aquatic 

and riparian organisms appear to have evolved in response 

to different components of the flow regime (Lytle and Poff, 

2004) and are discussed in subsequent sections. Flood-related 

disturbances are important ecological processes, contributing 

to temporary loss of vegetation, but also expanding riparian 

habitats and allowing establishment of riparian vegetation 

(Naiman and Decamps, 1997; Friedman and Lee, 2002).

Stream Channel

Interactions between flowing water (defined by the flow 

regime) and stream channel geometry dictate most of the 

characteristics of stream and riparian ecosystems. Fluvial 

geomorphic processes are responsible for the entrainment, 

transport, and deposition of sediments in streams and rivers, 

and determine stream channel geometry, stability, and water 

physiochemistry. Stream channels adjust their geometry, bed 

substrate characteristics, and sediment loads to variations in 

water discharge and size and amount of sediment delivered 

to channels from upland watersheds. Channel geometry 

plays a significant ecological role by structuring flow width, 

depth, and velocity conditions. These stream conditions are 

crucial for stream and streambank communities because 

they determine disturbance (shear stress) on the channel bed, 

stability of channel walls, and light and temperature regimes 

(Allan, 1995). Over the long term, geomorphic processes 

shape drainage basins, and over short terms, they structure 

ecological processes, habitat characteristics, and their 

interactions (Frissell and others, 1986; Montgomery, 2001). 

Fluvial geomorphic processes are affected by streambed 

and bank vegetation through stability provided by roots and 

algae and decreases in flow velocity by vegetation. Riparian 

vegetation is implicated in providing channel stability in wide 

valley alluvial rivers (for example, Murray and Paola, 2003), 

and degradation of vegetation commonly precedes gully 

formation (Prosser and Slade, 1994).

Floodplain Soils and Resources

Floodplain soils are those immediately adjacent to 

streams that are continuously or periodically inundated by 

shallow stream-related groundwater or by overtopping of 

streambanks. Floodplain soils and resources provide many 

important ecosystem services. Repeated flooding of floodplain 

soils commonly limits their nutrient and water holding 

capacity (Scott and others, 2005). Recently flooded or scoured 

floodplain soils commonly are occupied by early colonizing 

vegetation, which is replaced by later succession vegetation as 

soil resources develop (Allan, 1995).

Water-table depth in floodplains is critical for riparian 

vegetation, and fluctuations can create lethal moisture stress 

(Busch and Smith, 1995; Shafroth and others, 2000; Snyder 

and Williams, 2000). Typically, depth to water is less than 

4 m and needs to be 1–2 m deep for riparian vegetation 

recruitment (Stromberg and others, 1996; Horton and others, 

2001). Floodplain microorganisms play important roles in 

watershed-wide nutrient dynamics. Organic matter from 

riparian vegetation is converted to particulate and dissolved 

organic matter for use by floodplain and stream organisms 

(Naiman and Decamps, 1997). Nitrogen uptake by riparian 

vegetation and microbes may render riparian zones as sites of 

net accumulation, which may help remediate nitrogen loading 

in upper watersheds (Naiman and Decamps, 1997).
92 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Vegetation Community

Stream and riparian vegetation communities serve 

several ecosystem functions. Aquatic plants serve as filters 

for water, sediment, and nutrients, and can help control 

non-point sources of pollution. Aquatic and riparian plants 

provide detritus as a raw material for nutrient cycles on which 

riparian vegetation and aquatic communities rely (Naiman and 

Decamps, 1997). Aquatic plants provide microclimate control 

on extreme temperature and water-level fluctuations and 

stabilize streambanks (Naiman and Decamps, 1997; Patten, 

1998). The many physiological and structural adaptations of 

riparian plants to their environments facilitate the utilization 

and conservation of resource flushes. Habitat for many 

vertebrates, such as birds and mammals, is linked to canopy 

structure (physiognomy) and structure variability (Mac Nally 

and others, 2002), which are maximized in riparian habitat.

Native riparian tree species are early successional, 

colonizing bare wet surfaces, and are tolerant of nutrient-poor 

soils and burial. Their life cycles are intimately tied to flow 

regime dynamics: release of seeds and dispersal occurs during 

periods of high flood flows, and recruitment occurs during 

intervening low flow periods (Bagstad and others, 2005; 

Scott and others, 2005). The invasive Eurasian species salt 

cedar and Russian-olive (Elaeagnus angustifolia) reproduce 

opportunistically, are tolerant of stress, high salinity, drought, 

and repeated burning (Stromberg, 2001), and particularly for 

saltcedar, have expanded rapidly throughout the Southwest 

(Webb and Leake, 2006). Recruitment of saltcedar is similar 

to cottonwood and willows, although saltcedar appears to be 

able to actively recruit on floodplains without being flooded 

(Birken and Cooper, 2006). Saltcedar appears to tolerate low 

water tables by using unsaturated zone moisture, which can 

lead to complete replacement of native trees; replacement in 

some cases increases total vegetative cover (Busch and others, 

1992; Birken and Cooper, 2006; Webb and Leake, 2006), but 

reduces biodiversity.

Faunal Community

Insects and other invertebrates play important roles in 

food webs of stream and riparian ecosystems as secondary 

consumers and as prey for fish, other insects, birds, and 

mammals (Power and Dietrich, 2002; Paetzold and Tockner, 

2005). Aquatic species commonly respond to pulses in stream 

water or chemistry, which leads to similar pulses in aquatic 

and streambank predator populations (Paetzold and others, 

2006). Fish act as consumers for many ecosystem components 

(algae, benthic invertebrates, insects, vertebrates), and as 

prey for other vertebrates. Fish and other aquatic fauna are 

structured by flow regimes, as well as water quality and 

temperature. Geomorphic processes determine channel form 

and in conjunction with flow regime influence habitat features, 

such as bed substrate characteristics (Biggs and others, 2005).

Riparian vegetation is an important determinant of bird 

communities. Birds are widely used as targets for management 

strategies, ecological assessments, and monitoring programs 

because they are scientifically and socially well known, and 

responsive to natural and anthropogenic environmental change 

(Fleishman and Mac Nally, 2006). Studies of desert bird 

species show that they are sensitive to total vegetation volume, 

and that the spatial structure of vegetation composition is 

reflected by bird assemblages, rather than metrics such as 

vegetation structure or primary productivity (Fleishman and 

others, 2003, 2004; Fleishman and Mac Nally, 2006). Birds 

also serve in nearly all trophic roles and as vectors for seed 

and organism dispersal from isolated habitats.

Aquatic Ecology Control Model

The conceptual model for aquatic ecosystems portrayed 

in figure 4.11 is modified from Scott and others (2005). The 

model expands the stream and riparian model (fig. 4.9) to 

emphasize aquatic biota. Stream physiochemistry represents 

physical characteristics such as bed and bank characteristics 

(grain-size distributions and roughness, temperature and 

velocity profiles), as well as chemical properties such as 

pH, conductivity, dissolved and suspended organic material, 

and potential contaminants. Stream physiochemistry plays a 

key role in aquatic ecosystems and is a dynamic function of 

climate, streamflow, riparian and floodplain vegetation, and 

fluvial geomorphic processes. Stream physiochemistry sets the 

habitat and resource template for aquatic biota. Streamflow 

directly affects aquatic biota by fluvial disturbances affecting 

flow and sediment transport and indirectly through its 

influence on temperature. Streamflow characteristics such as 

timing of flooding can influence behavioral characteristics, 

such as dispersal mechanisms and developmental cues 

(Stevens and Springer, 2004; Scott and others, 2005). Fluvial 

disturbance is technically a function of bed characteristics (and 

thus stream physiochemistry in the aquatic model) because 

bed geometry determines velocity profiles; we show it as 

directly affecting aquatic biota for simplicity. 
Chapter 4: Subsystem Models for the Wet System 93

tac09-0397_fig04-11

See Riparian Model

for Details

UPLAND WATERSHED

HYDROLOGY

FLOW REGIME

STREAM CHANNEL

Fluvial geomorphic

processes

RIPARIAN VEGETATION

AND FLOODPLAIN

FISH

Carnivores, herbivores,

omnivores, detrivores

Secondary production,

competition, predation

STREAM

PHYSIOCHEMISTRY

Mixing, disturbance

ALGAE

Primary productivity

RIPARIAN

INVERTEBRATES

AND VERTEBRATES

BENTHIC

MACROINVERTEBRATES

Secondary production,

competition, predation

GROUNDWATER

REGIONAL CLIMATE

Precipitation, wind, radiation, snowmelt,

ozone

INVASIVE EXOTICS

LIVESTOCK GRAZING

ComponentDriverLinking process

EXPLANATION

Key linking process

Feeding

Habitat structure

Chemical, sediment,

nutrient fluxes

Water flux

Resource and

habitat availability

Resource and

habitat availability

Fluvial disturbance, dispersal,

developmental cues

Herbivory

predation

Feeding

Feeding

Resource and habitat availability

Competition, disturbance

(affects all components)

Nitrogen loading

Feeding

Energy and water balance

Figure 4.11. Control model describing components and relations for aquatic stream ecology showing drivers (orange ellipses), key systems (colored rectangles), and linking processes (arrows). Modified from Scott and others (2005).
94 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Algae serve as primary producers in riparian aquatic 

systems and are consumed by benthic macroinvertebrates, 

fish, and riparian invertebrates and vertebrates. Benthic 

macroinvertebrates play key roles in aquatic ecosystems 

as secondary producers; functional behavior includes 

shredders, grazers, omnivores, detritovores, filter feeders, 

and decomposers. Fish functional types include carnivores, 

herbivores, omnivores, and detritovores; thus, all other biotic 

components impact and are impacted by fish.

Drivers of Ecosystem Change

Natural Drivers

Climate is a key driver of stream and riparian ecosystems 

at all temporal scales. Great Basin riparian areas are strongly 

affected by past and present climatic characteristics, largely 

through climatic effects on the coupling of geomorphic 

processes and vegetation (Chambers and others, 2004). 

Magnitude and timing of precipitation and snowmelt drive 

many ecosystem processes (Loik and others, 2004), and 

despite inherent high variability of precipitation, semi-arid 

ecosystems are adapted to an envelope or reference range of 

climatic variability.

Groundwater levels generally determine water levels in 

stream and riparian systems and vice versa in losing reaches. 

The aquifer type for a given system determines sensitivity 

to drivers such as climate and land use. Stream and riparian 

zones fed by regional aquifers may be relatively insensitive to 

precipitation over the short term (but not necessarily climatic 

affects on other ecosystem processes and drivers) because 

regional aquifers have slow response to changes in climate.

Stream and riparian zones are inherently dynamic, 

interrelated systems encompassing external and internal 

processes and their feedbacks. However, the primary 

characteristic in arid stream and riparian zones for 

describing ecosystem function (including biotic and abiotic 

characteristics) is that of the hydrologic flow regime (Naiman 

and Decamps, 1997; Poff and others, 1997; Patten, 1998; 

Ward and Tockner, 2001; Friedman and Lee, 2002; Power 

and Dietrich, 2002; Carsey and others, 2003; Benda and 

others, 2004; Bagstad and others, 2005; Biggs and others, 

2005; Thorp and others, 2006). The flow regime determines, 

and is determined by, hillslope hydrology and ecology of 

the watershed (including climatic processes), geomorphic 

processes, vegetation communities, fire regimes, and macro 

and micro invertebrates and vertebrate dynamics. Conceptual 

frameworks for riparian ecosystems and how they function in 

landscapes are remarkably similar across semi-arid regions. 

Anthropogenic Drivers

Land uses that act as drivers in stream and riparian 

systems include stream diversion, livestock grazing, 

groundwater extraction, logging and other land treatments, 

irrigated agriculture, urbanization, and mining activities. Each 

of these can affect stream and riparian zones directly through 

physical disruptions to streams and floodplains, vegetation, 

and other biota. Indirectly, these land uses can impact riparian 

ecosystems through effects in adjacent dryland systems that 

may modify water or sediment budgets (Chaney and others, 

1993; Naiman and Decamps, 1997; Patten, 1998).

Future climate change may include increased variability 

in timing and amount of precipitation, and warm water 

temperatures (see Chapter 2, section “Climate Change and 

Forecasts”). Perched and local aquifers likely will be affected 

strongly by climate change because residence times for water 

in these aquifers generally is short. Riparian trees are sensitive 

to groundwater depth, and invasive species may be more 

tolerant of low groundwater levels (Horton and others, 2001), 

high CO2, and high air temperatures.

Riparian vegetation is particularly susceptible to impacts 

from livestock grazing because livestock tend to congregate 

in riparian areas due to the presence of water, nutrient-rich 

forage, and shade (Beever and others, 2005). Livestock 

foraging and trampling can alter vegetation characteristics 

such as height, density, connectedness, complexity, and 

composition, as well as alter soils by compaction and other 

disturbances (Fleischner, 1994; Belnap, 1995; Beever and 

others, 2005). These effects can cascade into destabilizing 

stream banks causing increased erosion.

Fire regime plays an important role in riparian 

ecosystems, with potential feedback mechanisms between 

riparian zones and upland dry ecosystems. Fire may affect 

riparian ecosystems more than xeric systems because of the 

greater density of connected fuels than in xeric systems, 

but this effect is balanced by greater moisture content of 

riparian plants. Erosion may be increased following fires 

due to reduced riparian vegetation, and may lead to altered 

channel geometry and flow regime, causing significant 

changes to stream and riparian processes such as incision of 

channels. Fire regimes in adjacent dry ecosystems may alter 

the sediment budget to streams and riparian zones, affecting 

geomorphic processes, flow regime, and aquatic and riparian 

ecosystems.

Invasive species can out-compete native biota and 

introduce new disturbance regimes. If invasive species alter 

the structure of ecosystems (for example, monospecific stands 

of riparian trees with simple canopy structure), the effects may 
Chapter 4: Subsystem Models for the Wet System 95

be expressed in other biota that rely on structural diversity 

such as birds (Fleishman and others, 2003). Saltcedar and 

Russian olive are present, if not dominant, in most Great Basin 

riparian areas (Friedman and others, 2005; Webb and Leake, 

2006). Saltcedar is associated with modification of vegetation 

structure, reduced groundwater depths, and has been causally 

linked to floodplain development and channel narrowing 

(Busch and Smith, 1995; Stromberg and others, 1996; Birken 

and Cooper, 2006). Exotic fish and snails are prevalent in 

many streams and rivers, and often out-compete natives, 

lowering gene pool diversity. Hybridization of fish can lead to 

extirpation of native species.

Other drivers include non-point source pollution 

introduced through overland flow and groundwater, animal 

harvesting, and nutrient loading (particularly nitrogen). 

Increased nitrogen deposition occurs through anthropogenic 

airborne sources as well as local pollution.

Ecosystem Dynamics

Streams and riparian areas are highly dynamic systems. 

Although described in detail in the section, “Drivers 

of Ecosystem Change,” they involve interactions with 

groundwater systems, climate, the landscape configuration and 

natural and anthropogenic drivers, such as climate, grazing, 

and fire.

Summary Points

Great Basin riparian systems involve complex 

interactions between groundwater, surface water, vegetation, 

and climate. Because of this, they are sensitive to all natural 

and anthropogenic impacts that affect the interacting systems. 

They are particularly sensitive due to the high demand from 

the availability of water in this desert landscape. Historical 

ecology and paleoclimate are not well studied, but can provide 

a reference range of conditions to compare with current and 

future conditions. This is particularly important for wetland 

ecosystems in which human modification occurred prior 

to scientific and most historical records. Invasive riparian 

plants, such as saltcedar, potentially change habitat and 

affect local and migratory species, but studies are inadequate 

to fully document these effects. Improved understanding 

of the ecology and drivers of ephemeral streams is needed. 

Do they function similar to dryland or wetland ecosystems, 

or as a hybrid? What changes to stream flow regime will 

cause transitions in vegetation from riparian assemblages 

to xeric assemblages and vice versa? Little is known about 

nitrogen deposition in Western riparian ecosystems. Because 

most streams are in the alpine, subalpine, and forest biomes, 

nitrogen deposition and other pollutants may be rapidly 

transferred to streams and their biota. Improved understanding 

of the buffering capacity of alpine streams is needed in order 

to predict the effects of wet and dry deposition.

Freshwater Lakes Model

Freshwater lakes of the Great Basin can be divided into 

three types: (1) manmade reservoirs and ponds, (2) valleybottom natural terminal lakes that are fed by perennial streams 

and springs, and (3) high-mountain small lakes, commonly 

restricted to glacial cirque basins. Reservoirs are managed 

systems that are not conducive to ecological modeling. 

Valley-bottom lakes such as Pyramid Lake fluctuate markedly 

in depth and water quality with climatic episodes, and thus 

tend to have sparsely vegetated shores. Mountain lakes are 

small and range from deep, perennial rocky lakes with lush 

lake-edge vegetation to shallow, seasonally variable lakes in 

moraines that have sparsely vegetated shores. Developing a 

specific set of conceptual models for this system is beyond the 

scope of this study.

Saline Lakes and Marshes Model

Saline and hypersaline lakes are common in valley 

bottoms of the Great Basin. Great Salt Lake, the most famous 

of these lakes, is a terminal lake fed by major streams and 

springs. Hypersaline waters in these lakes support a limited 

flora and fauna, but brackish marshes bordering them often 

teem with wildlife and support a diverse flora. Developing a 

specific set of conceptual models for this system is beyond the 

scope of this study.
96 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

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Chapter 5: Integration Models 97

Introduction

Federal lands cover about 78 percent of the Great Basin 

region, and are managed to provide for multiple societal 

values including potentially conflicting goals such as 

supporting cattle grazing and protecting habitat for endangered 

species. Many decisions required to achieve these goals, 

such as when to remove cattle from an allotment, require 

that local managers evaluate information from a larger 

spatial and longer temporal context than what is directly 

under local control. In particular, habitat quality over large 

spatial extents is important for some species of concern. For 

example, home ranges for the Greater Sage-grouse commonly 

encompass multiple management units and several seasonally 

variable habitat needs such as meadows for chick rearing and 

sagebrush for nesting (Connelly and others, 2000). A broad 

landscape-level perspective also is necessary for evaluating 

processes such as disturbance, fragmentation, and connectivity 

that affect the local extent but are detectable only from an 

extensive view. Temporal extents are important because 

landscape patterns are created by the time-dependent transport 

of energy, matter, and organisms (Farina, 2000). Consequently, 

decisions made by local managers are improved with 

knowledge about management actions in adjacent or similar 

areas beyond their local jurisdiction and by observations over 

time frames longer than individual growing seasons or annual 

budget cycles. Local decisions also are affected by policy 

changes that impose additional constraints on allotments, for 

example by allowing higher ORV use levels. Hence, landmanagement agencies also must understand how multiple 

management activities and decisions covering various spatial 

extents will be impacted by events happening at other spatial 

extents and over various timeframes.

In addition to improving decisions with knowledge from 

spatial and temporal contexts larger than the typical individual 

management unit, managers also must consider the concurrent 

effects of multiple drivers. For example, the local manager’s 

decision regarding a grazing allotment depends not only on the 

effects of cattle, but also on an evaluation of other stressors 

and drivers that impact the condition of the allotment. The 

capacity for the allotment to maintain an expected level of 

productivity following a given level of grazing depends on 

soil properties, local precipitation, disturbance regimes, prior 

conditions, and human activities, among other factors. This 

complicated estimate may become more difficult to make 

in the face of unpredictable climate or other environmental 

change, which may invalidate previously understood 

relationships. Conceptual models assist in developing a 

capacity to anticipate future management opportunities and 

constraints by identifying the most important relationships 

among multiple drivers of ecosystem function. This document 

has described these relationships for subsystems; now the goal 

is to describe how to combine subsystems and to scale up to 

the region.

A major challenge to scaling is the mismatch between 

ecosystem structure and function and the human institutions 

that are available to manage and study them. The spatial scales 

at which habitat features are perceived and used typically 

differ among organisms in relation to body size and mobility, 

and they often do not correspond to the scales at which 

researchers and land managers focus their efforts (fig. 5.1; 

Wiens and others, 2002). A diagram similar to figure 5.1 could 

be produced for temporal scales because ecologists commonly 

sample and describe the environment at spatial and temporal 

scales that are not directly relevant to most organisms and 

management decisions. This document attempts to bridge 

these gaps by providing a regional or landscape view to 

help inform the decisions that are required at multiple scales 

across the Great Basin. A region-wide understanding of 

the interacting ecosystems of the Great Basin derived from 

conceptual modeling helps us develop a predictive capability 

to evaluate the cumulative effects of multiple stressors on 

target resources. Predictions, in the form of landscape change 

hypotheses, become the basis for a monitoring strategy to 

detect the predicted changes. Accomplishing this goal for the 

Great Basin involves linking the stressor and control models, 

described in chapters 3 and 4, with analytical models to 

facilitate the compilation of data from multiple scales and to 

simulate landscape change. 

Integrated Ecosystem Framework

Spatial Structure

In previous chapters, the Great Basin ecoregion 

was deconstructed into 10 subsystems (fig. 1.3), each of 

which represents groups of related ecological elements. 

Discrete, generalized conceptual models were presented of 

the significant interactions among environmental drivers, 

stressors, and biotic components and processes within

these subsystems (Chapters 3 and 4). The next step in 

integration is to recognize that subsystems are distributed 

across the landscape in predictable patterns based on 

biophysical conditions and previous management actions, 

Chapter 5: Integration Models 

By Alicia Torregrosa and Andrea Woodward
98 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

and that multi-scale, multiple-driver linkages exist among

subsystems. Supporting effective management decisions by 

predicting ecosystem responses requires developing tools that 

address these patterns and model these linkages. The spatial 

foundation for such a model is a digital representation of the 

subsystems in their mosaic arrangement across the Great Basin 

(figs. 5.2 and 5.3; see fig. 2.1).

Hierarchical Structure

Ecologists recognize that ecological systems can 

be viewed as being organized hierarchically, with larger 

slower-changing units composed of smaller units with faster 

process cycles (Allen and Hoekstra, 1992; Holling, 2001). 

Examples of commonly useful hierarchies include individual 

→ population → community → biome, and site → drainage 

→ watershed → basin → region. Each hierarchical level has 

novel emergent properties that arise from the combination of 

its subunits. For example, erosion-driven changes to small 

drainages occur frequently during a season and affect the 

establishment of individual plants. Over several seasons, these 

changes can accumulate and lead to changes at a larger extent 

such as mass wasting, which alters not only topography and 

soil quality, but also land cover with consequent changes in 

movement patterns of migratory species or new opportunities 

for invasive colonizers. This example shows how the smaller 

scale can be viewed as providing the mechanism for changes 

at the next larger scale (Allen and Starr, 1982; Giampietro, 

2003) and shows how temporal and spatial scales are 

hierarchical. These properties of hierarchical structure can be 

used as a framework for the integrative model.

Figure 5.1. Diagram illustrating how scaling windows differ among species that use, investigate, or have management 

responsibilities for sagebrush steppe ecosystems. A scaling window is defined by the minimum resolution at which organisms 

perceive spatial variation and the maximum spatial domain experienced by organisms over a fixed period of time (after Wiens and 

others, 2002).

tac09-0397_fig05-01

Politician

Resource administrator

Resource manager

Field ecologist

Experimental ecologist

Migrant songbird

Pronghorn

Livestock

Resident songbird

Prairie dog

Vole

Butterfly

Beetle

Aphid

SPATIAL SCALE

M2 Hectare Km2 Km2 × 10 Km2 × 102 Km2 × 103
Chapter 5: Integration Models 99

Figure 5.2. Map of dry subsystems described in Chapter 3 (see fig. 2.1) and also salt desert scrub. 

tac09-0397_fig05-02

Reno

Salt Lake

City

Bend

Pocatello

Carson

City

Las Vegas

Bishop

Sacramento

Susanville

Klamath Falls

Ely

Elko

Tonopah

Winnemucca

Twin Falls

OREGON Boise

CALIFORNIA

NEVADA

UTAH

ARIZONA

WYOMING

IDAHO

MONTANA

110°

112°

112°

114°

114°

118°

118°

120°

120°

122°

122°

116°

116°

44° 44°

42° 42°

40° 40°

38° 38°

36° 36°

0 50 100 150 200 MILES

0 50 100 150 200 KILOMETERS

EXPLANATION

Dry subsystems—described in Chapter 3

Alpine tundra

Pinyon-juniper

Salt desert scrub

Sagebrush steppe

Mixed conifer

Great Basin Integrated Landscape Monitoring 

Project (GBILM) Area-of-Interest

PACIFIC

OCEAN

PACIFIC

OCEAN

Note: Gray represents areas either outside the GBILM 

study boundary or other subsystems.
100 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

PACIFIC

OCEAN

PACIFIC

OCEAN

OREGON

CALIFORNIA

NEVADA

UTAH

ARIZONA

WYOMING

IDAHO

MONTANA

Reno

Salt Lake

City

Bend

Pocatello

Carson

City

Las Vegas

Bishop

Sacramento

Susanville

Klamath Falls

Ely

Elko

Tonopah

Winnemucca

Twin Falls

Boise

110°

112°

112°

114°

114°

118°

118°

120°

120°

122°

122°

116°

116°

44° 44°

42° 42°

40° 40°

38° 38°

36° 36°

0 50 100 150 200 MILES

0 50 100 150 200 KILOMETERS

EXPLANATION

Wet subsystems—described in Chapter 3

Streams, riparian

Springs, wetlands

Groundwater—only groundwater in Carbonate, 

Basin and Volcanic Aquifers is shown 

Great Basin Integrated Landscape Monitoring 

Project (GBILM) Area-of-Interest

Note: Gray represents areas either outside the GBILM 

study boundary or other wet subsystems.

Figure 5.3. Map of subsystems described in Chapter 4 (see fig. 2.1) and also lakes and discharging (wet) playas. 
Chapter 5: Integration Models 101

Different hierarchical systems can be used to describe the 

same set of resources and spatial extents depending on 

the process of interest and the management or research 

question. When describing the generic scaling process linked 

to the GBILM hierarchy of system models (fig. 1.2), a threetiered hierarchy (fig. 5.4) is used: sites within each subsystem 

→ mosaic of site classes within subsystem → mosaic of 

subsystems (or landscapes). The smallest hierarchical unit 

in this system is a site, which can be viewed as a study plot, 

transect, or an allotment. The next hierarchical unit, the 

site mosaic, is used to describe the aggregation of different 

site conditions for areas with similar vegetation potential 

(a function of the underlying ecological conditions of soil, 

geomorphology, and climate). For example, sites with the 

same ecological potential for Wyoming big sagebrush may 

have different site conditions. due to different disturbance 

regimes acting at the site over time. Sites that are within their 

ecological resilience capacity can be found as Wyoming big 

sagebrush with a high percent cover of perennial and annual 

native understory—this is the reference condition. Sites 

that have been stressed by excessive grazing and subject to 

exotic plant exposure may become Wyoming big sagebrush 

with a cheatgrass understory. Sites that have experienced 

an extremely hot fire may have no Wyoming big sagebrush, 

just herbaceous cover, but they still have the ecological 

potential for Wyoming big sagebrush, in the absence of further 

disturbance. Site classes are a result of both the ecological 

potential of the site and the stressors the site is subject to 

over time. A mosaic of site classes is aggregated to describe 

the sagebrush steppe subsystem; the mosaic of subsystems 

is aggregated to form the landscape level of the three-tier 

hierarchy. The approach that is taken is to scale across 

hierarchical levels—either upscaling, going from the site to 

subsystem to landscape, or downscaling—depends on the 

management question(s) and data availability. For example, 

when satellite data such as Landsat are the best available 

data, or the goal is to conduct a stratified random sampling 

design across a landscape, a downscaling approach is called 

for. Figure 5.4 uses an example of a three-tier spatially and 

temporally defined hierarchical structure to illustrate the 

model. Specific management questions may require more 

hierarchical levels depending on the temporal and spatial 

scales of the driving variable(s).

Interactions Within and Among Subsystems

Interactions within major subsystems of the Great 

Basin are described by their control models (Chapters 3

and 4). The dominant processes illustrated in the control 

models are those that contribute strongly to the biophysical 

structure of each subsystem. The responses of subsystems 

to stressors are outlined in the stressor models. Just as the 

entire ecoregion was deconstructed into subsystems to more 

easily understand and articulate the dominant controlling 

processes, the control and stressor models can be further 

disassembled, using spatial hierarchical levels (or scales), to 

describe the dominant processes occurring within subsystems. 

An illustration of the cross-scale approach for understanding 

subsystem controls and stressors will be described, from 

an upscaling perspective, using the sagebrush steppe and 

stream/riparian subsystems and the processes of overland 

flow and erosion across hierarchical scales. Factors relating 

to the specific example of soil hydrology, runoff, and erosion 

in the sagebrush steppe subsystem can be organized using 

domains of scale (fig. 5.5). At the site level, one can measure 

the number and depth of rills caused by erosion, which will 

depend primarily on soil characteristics, vegetation, and 

weather patterns. These site-based data describe the results 

of overland flow and erosion at specific places with a specific 

combination of variables, and can be statistically used to 

quantify relationships among them. At the next higher spatial 

domain, the sagebrush steppe subsystem consists of a mosaic 

Figure 5.4. Domains of scale from site to landscape including 

properties and processes especially relevant to determining the 

effects of erosion from sagebrush steppe on adjacent riparian 

areas. Examples at the site level include differential infiltration, 

runoff, and erosion because individual plant, animal, and microbial 

species affect site-specific soil conditions. At the level of the 

mosaic of site classes within the sagebrush steppe subsystem, 

mass wasting and other geomorphic changes in drainage areas 

are important. At the mosaic of subsystems, or landscape, level, 

differential precipitation and infiltration due to land cover and 

topography affect regional drainage patterns.

Spatial distribution of 

sagebrush steppe 

relative to stream/ 

riparian areas

Spatial distribution 

of drivers, stressors, 

physical and 

biological 

conditions within 

subsystems

Erosion and 

overland flow 

at site

Site within 

Subsystem

Mosaic of Site 

Classes within 

Subsystem

Mosaic of 

Subsystems = 

Landscape

SPATIAL EXTENT 

TEMPORAL EXTENT 
102 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

of vegetation community states (site classes), whose pattern 

depends on broader environmental factors, such as soil 

patterns and topographic features, as well as relict impacts of 

anthropogenic stressors, all of which determine the pattern of 

erosion among the mosaic of site class units. At the landscape 

scale, the aggregated patterns of erosion within the sagebrush 

steppe subsystem can be quantified as they interact with other 

subsystems (for example, riparian and aquatic), depending 

on the spatial pattern of subsystems as well as the pattern of 

erosion within the sagebrush steppe subsystem. As is shown in 

figure 5.6, cross-scale interactions occur within subsystems, as 

this example describes, or across subsystems.

A model of interactions among subsystems begins to 

address the complexity of an integrated landscape approach 

to monitoring because patterns and processes at spatial scales 

larger and smaller than the area of interest are relevant. The 

comparable statement with respect to temporal scales also 

holds. An important step in this conceptual approach is to 

select the appropriate spatial and temporal domains for the 

processes represented by the control and stressor models 

(fig. 5.5). Cross-scale interactions then can be categorized, 

as illustrated using the sagebrush steppe and stream/riparian 

subsystems for the processes of runoff as overland flow and 

erosion. For graphing purposes, space and time are combined 

on the vertical axis reflecting increases with each higher 

domain of scale (fig. 5.6). In this way, multiple subsystems can 

be displayed on the horizontal axis. 

To keep this example simple, only uni-directional 

water flow from sagebrush steppe to stream/riparian areas is 

considered, but we recognize that other relationships exist 

Figure 5.5. Context for example in text explaining how site-based data and conceptual models (control and stressor) from two 

subsystems are spatially and temporally identified within the appropriate hierarchical scale for analysis.

tac09-0397_fig05-05

Framework Model

Atmosphere

Wet Systems Dry Systems

Human System

Integration Model

System Models

Groundwater

Stream & Riparian

Wetland & Spring

Freshwater Lakes

Saline Lakes

Alpine Tundra

Subsystem Models

Aspen Forest

Salt Desert Shrub

Mixed Conifer Forest

Sagebrush Steppe/ 

P-J Woodland

Interactions from control and 

stressor models related to 

erosion and overland flow 

from two subsystems

Identify scale of process.

Domains of scale
Chapter 5: Integration Models 103

Figure 5.6. Example of interactions between two Great Basin subsystems regarding erosion and overland flow.

tac09-0397_fig05-06

SUBSYSTEMS

TIME AND SPACE INCREASING

• Topographic position

• Climate cells

• Cumulative disturbance and 

climate determine spatial 

distribution of vegetation site 

classes relative to riparian 

areas

• Spatial distribution and intensity 

of fire, livestock grazing, land 

treatments

• ORV use

• Distribution of soil properties

• Climate patterns 

Erosion and overland

flow as functions of:

• Vegetation community

• Soil properties

• Precipitation

Climate cells

Basin physical 

characteristics

Spatial distribution and 

intensity of livestock 

grazing, water 

extraction, flooding

Streamflow as function of:

• Stream channel 

characteristics

• Vegetation

• Precipitation

Transport of water 

and sediments

Site within 

Subsystem

Mosaic of Site 

Classes within 

Subsystem

Mosaic of 

Subsystems =

Landscape

SAGEBRUSH STEPPE RIPARIAN/STREAM

LANDSCAPE

PATTERN

(for example, flow from stream-riparian to sagebrush steppe 

due to flooding). For a given rainfall event, vegetation cover, 

topography, and soil structure determine rate of overland flow, 

and streamflow rate determines residence time of sediment 

for the stream/riparian subsystem. The spatial pattern of site 

characteristics that influence overland flow can be overlaid 

with data about the occurrences of stressors and drivers (for 

example, fire, invasive species, local disturbance). The result is 

a spatial representation of patches having different properties 

relative to erosion and overland flow. A spatial model (see 

section “Models for Monitoring Landscape Change”) then can 

be used to predict how this specific configuration of patches 

will respond, for example, to a given rainfall event or changes 

in climate pattern, depending on the specific management 

concern. 

Changes at the landscape level in response to system 

drivers are described in terms of changes to the spatial 

distribution of sagebrush steppe relative to stream/riparian 

areas. These changes will, in turn, affect the processes of 

erosion and overland flow at all other scales (fig. 5.7) and 

feedback loops within and across scales likely will need to be 

addressed. 

Many processes and management issues in the Great 

Basin involve more than two subsystems (fig. 5.8). Some 

interact more directly than others and interactions can involve 

various combinations of hierarchical levels. A comprehensive 

model of the Great Basin would include all subsystems. 

However, many priority management questions likely can be 

answered by focusing on the details of a few key subsystems.

By integrating the effects of multiple stressors and 

drivers across multiple subsystems, the integrated spatial 

modeling should improve decision-support for land managers. 

Predicting the consequences of changes in particular system 

drivers and stressors, including management actions, will 

help managers direct resource management decisions in the 

context of a large spatial extent, potentially as large as the 

entire Great Basin. In addition, assumptions and hypotheses 

about change will help identify the most effective indicators 

in which to invest monitoring efforts. Monitoring results can 

alert managers to changes resulting from changes in global, 

regional, and local drivers. As changes develop, they also can 

be used to improve model parameterization, and therefore the 

predictive ability, of the models.
104 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Models for Monitoring Landscape Change

Converting the knowledge embodied in the conceptual 

models of the Great Basin subsystems into a form that is 

useful to management decisions is the key to the landscape 

monitoring challenge (fig. 5.9). One useful approach, which 

we expand upon below, is to use frame-based simulation 

models (Starfield and others, 1994) to integrate plot-level data 

collected by local managers along with expert knowledge and 

measures of uncertainty to provide alternative predictions of 

the effects of multiple stressors over time. Predictions (results) 

from the simulation models provide a means for selecting 

indicators that track ecosystem responses over time and that 

serve as early warnings of possible altered ecosystem function. 

The results of the simulation model can be used to extrapolate 

the knowledge gained with site-specific conditions to explore management options across a landscape (fig. 5.10). An 

advantage of using spatially explicit frame-based simulations 

to inform indicator selection is that they map the conceptual 

model results to expected changes at actual locations on the 

ground. Identifying indicators using status and trends analysis 

of ecosystem elements or control and stressor models is an important first step, but indicators developed without addressing 

geography are likely to overlook significant aspects. Surprising relationships arise as a direct result of processes that are 

spatially and temporally cross-scale dependent. To increase the 

possibility of uncovering these surprises, and to do so before 

significant time and resources have been invested in indicator 

sampling design and implementation, the GBILM team proposes the use of landscape level simulation models to explore 

spatially and temporally explicit conceptual model results. The 

simulation models can facilitate an iterative planning—or at 

least increased dialogue—to ensure common purpose among 

the stakeholders responsible for funding and implementing an 

integrated landscape-level monitoring effort. tac09-0397_fig05-07

SUBSYSTEMS

TIME AND SPACE INCREASING

• Topographic position

• Climate cells

• Cumulative disturbance and 

climate determine spatial 

distribution of vegetation site 

classes relative to riparian 

areas

• Spatial distribution and intensity 

of fire, livestock grazing, land 

treatments

• ORV use

• Distribution of soil properties

• Climate patterns 

Erosion and overland

flow as functions of:

• Vegetation community

• Soil properties

• Precipitation

Climate cells

Basin physical 

characteristics

Spatial distribution and 

intensity of livestock 

grazing, water 

extraction, flooding

Streamflow as function of:

• Stream channel 

characteristics

• Vegetation

• Precipitation

Transport of water 

and sediments

Site within 

Subsystem

Mosaic of Site 

Classes within 

Subsystem

Mosaic of 

Subsystems =

Landscape

1

2

SAGEBRUSH STEPPE RIPARIAN/STREAM

LANDSCAPE

PATTERN

Figure 5.7. Landscape-level processes will have effects at other hierarchical levels. Arrow 1 could indicate 

the role of water and sediment transport to alter the spatial distribution of riparian and stream site classes, for 

example, by changing the spatial distribution of new surfaces for colonization by vegetation. Arrow 2 could 

indicate the effect of sediment transport to scour riparian vegetation and change the stability of a particular 

streambank.
Chapter 5: Integration Models 105

tac09-0397_fig05-08

SUBSYSTEMS

TIME AND SPACE INCREASING

Alpine

Springs

1

2

3

4

Sagebrush

Steppe

Pinyon-Juniper

Riparian/Streams

Groundwater LANDSCAPE

SCALE

Figure 5.8. Multiple subsystems interacting on the landscape. Arrows indicate that a hierarchical level of one subsystem 

may interact with one or more levels of another system. Arrow 1 represents the landscape level interaction where 

groundwater levels control spring discharge. Arrow 2 represents how spring discharge at a particular site depends on 

the spatial pattern of groundwater level (which may be altered by urban withdrawal). Arrow 3 represents the site-to-site 

interaction between sagebrush steppe and pinyon juniper because they are usually adjacent on the landscape, and spread 

of pinyon-juniper into sagebrush steppe. Processes represented at the local scale are plant dispersal mechanisms and 

effects of recent fire. Arrow 4 shows that a pattern of vegetation within the pinyon-juniper subsystem can affect site level 

sagebrush steppe vegetation. These arrows are just a few examples of the important interactions.

Frame-based models are dynamic versions of statetransition models, such as those described in Chapter 3, 

section “Ecosystem Dynamics.” They are based on the 

same idea that a site’s state is maintained by a number of 

interacting processes until a threshold of change is reached, 

which precipitates a switch to a different system state. 

For example, a sagebrush steppe-bunch grass site can be 

converted to sagebrush steppe-cheatgrass with the frequent 

occurrence of fire (fig. 3.6). Frame-based models incorporate 

site-specific ecological accounting, which means that these 

models keep track of and account for the prior or existing 

condition, the causative factors altering these conditions, 

and, if the conditions cumulatively cross a threshold, the 

subsequent changed condition. This ecological accounting 

is conducted at regular time steps (frames) defined by the 

management decision (question) that structures the model 

itself. The management questions also define which states 

and drivers must be tracked. Spatially explicit frame-based 

models use geographic information systems (GIS) to include 

measures of the site’s geographic relationships that affect the 

ecological processes such as landscape patterns and measures 

of adjacency, proximity, diffusion, and fragmentation. Until 
106 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Figure 5.9. Overview of the relationship between outcomes from subsystem models, the integration model, and specific management 

needs. The diagram provides context for the example in the text explaining how site-based data and conceptual models (control, 

stressor, and integration) are identified spatially and temporally within the appropriate hierarchical scale for analysis.

tac09-0397_fig05-09

Framework Model

Atmosphere

Wet Systems Dry Systems

Human System

Integration Model

System Models

Groundwater

Stream & Riparian

Wetland & Spring

Freshwater Lakes

Saline Lakes

Alpine Tundra

Subsystem Models

Aspen Forest

Salt Desert Shrub

Mixed Conifer Forest

Sagebrush Steppe/ 

P-J Woodland

Site-based data, conceptual

models from two subsystems

Spatial model enabling 

accumulation of drivers and 

stressors, and transfer of 

information across spatial 

and temporal scales

Predicted response to 

multiple stressors at multiple 

spatial and temporal scales

Effective monitoring 

indicators for detecting 

predicted changes

recently, compiling an ecological accounting framework for 

an area the size of the GBILM was unrealistic. However, with 

advances in GIS, remote sensing, digital archiving, computer 

technology, and networking, it is feasible to develop the 

required framework.

A necessary step for ecological accounting is to distill 

the information embodied in the control and stressor models. 

Model relationships must be compiled into a library of 

probabilities that can be used for the frame-based model in the 

form of parameters. The parameters represent the probability 

of occurrence of the agents of landscape change. For the 

example used in this chapter, the most common agents of 

change are fire return intervals, rates of invasion of exotic 

species, relative intensity of biological pests, anthropogenic 

aquifer drawdown, and climate parameters used to model 

the probability of droughts and floods. Within frame-based 

models, these probability parameters are the switches from 

one state to another. When the probability of an occurrence 

is high enough that a tipping point is reached, the system 

switches to an alternative state (fig. 5.11).

Each land unit has its own particular set of conditions 

that is part of its legacy within the landscape. Prior conditions 

that led to a degraded current condition can hold for 

parcels occurring adjacent to parcels with healthy reference 
Chapter 5: Integration Models 107

Figure 5.10. Overview of Integration Model. Depending on the objectives defined by resource managers, a 

subset of conceptual models is selected that provides a mechanistic understanding of the social, hydrologic, 

and ecological processes relevant for understanding management options. The conceptual models inform the 

development of a geographic information service (GIS) database to “map” the mechanisms onto a spatially explicit 

multi-scale framework. Using information from the mechanistic models and, if lacking, from sensitivity analysis or 

other techniques, probabilities are derived and used in frame-based state-transition models to begin to explore 

the effects of stressors on the focus areas. The outputs from the frame-based state-transition models are mapped 

back into the GIS to provide spatially explicit predictions to be tested as hypotheses. Results from the hypothesis 

testing provide information for management consideration for issues such as selecting indicators. 

tac09-0397_fig05-10

System Switches (as probabilities)

Conceptual Models

Resource 

Management 

Objectives 

Indicators and 

Monitoring Design

Output maps and Simulations

State-transition Model

Present

condition

Predicted 

condition(s)

Multiscale GeoSpatial 

Database

Sage Grouse

Vegetation

Restoration

Threats

conditions. The frame-based model predicts the changes 

for one land unit area in a specific initial condition given 

differing scenarios of probable occurrences. Frame-based 

models are made spatially explicit by merging them with GIS 

geodatabases where each polygon (or pixel) on a map can be 

categorized with the condition of its vegetation community 

and other attributes. In addition to the drivers/stressors 

shown in figure 5.11, other probabilities of occurrences 

associated with spatial patterns are included such as distance 

to a neighboring polygon with cheatgrass, distance to road 

features, relative topographic position, and measures of 

fragmentation or connectivity. The model is run on each 

individual land unit to produce landscape level change 

predictions. 

Running the simulation over time and across space can 

provide a systematic framework to explore the responses of 

various sagebrush steppe sites to drivers and stressors. Using 

regionwide site-based data will help to quantify the relative 

influence of site conditions and drivers to expected changes in 

climate and other anthropogenic impacts. 
108 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Figure 5.11. Frame-based model for simplified sagebrush steppe example. The single box on the left represents the state 

of one specific area of the map that was classified (for example, in year one, the initial condition) as “Sagebrush with 

perennial grasses and forbs.” The five boxes on the right represent the condition of the site after five yearly time steps 

(frames) under five scenarios each represented by a different driver. For simplicity, each driver is assumed to operate for 

the full 5 years and the transition result (for example, Frame YR 5) for each scenario is the result of a single driver. 

tac09-0397_fig05-11

Sagebrush with 

perennial grasses 

and forbs

Sagebrush with exotic 

annual grasses and 

scattered trees

Native annual 

grasses and 

perennial herbs

Exotic annual

grasses

Pinyon/juniper 

dominated

Sagebrush with 

perennial grasses 

and forbs

Excessive herbivory

Drought

High-frequency fire

Fire supression

No disturbance

Frame Year 1 Frame Year 5

Summary Points

The integration model described in this section seeks to 

link the components of the Great Basin within a multi-scale 

framework to provide insights for management decisions. 

A three-tiered hierarchical structure in which the ecological 

systems and the associated processes that structure these 

systems—described through control and stressor models—

forms the spatial and temporal skeleton of the integration 

model. The model is intended to improve understanding of 

cross-scale interactions and cumulative effects.

The model approach assumes that simulation model 

results from frame-based state-transition models (or other 

kinds of models) are hypotheses that summarize the current 

state of scientific knowledge and project these into the 

areas of management interest. These hypotheses then must 

be evaluated to validate the model. Evaluating hypotheses 

requires access to monitoring data, which in turn requires 

resources to extract and convert these data into the parameters 

that drive the model. Archived data such as remotely sensed 

imagery or land treatment data, for example, could be useful 

for generating and testing the hypotheses. 

Many issues related to data development will continue to 

challenge model integration. Data compilation, aggregation, 

and transformation are being advanced through informatic, 

geostatistical, and mathematical research. Keeping abreast of 

and incorporating innovative methods to integrate data from 

different sources will be important. 

As ecosystems continue to respond to anthropogenic 

pressures, novel conditions may arise that our current model 

categories have not captured. Maintaining flexibility in our 

ecological accounting framework will be an important design 

element so that new categories can be added as needed. 

Unexpected synergistic effects, either between stressors or as 

feedback loops between drivers and ecosystem responses, also 

are a category of surprise that a flexible accounting structure 

can accommodate.

Much research effort from many organizations is pointed 

toward creating model-based applications to work more 

effectively with changing geographic units over time. Given 

the resources, the challenge will be to communicate among 

land managers, scientists, modelers, computer application 

designers, and database designers to create systems that 

provide results and then develop visualization tools to share 

the results with society. 
Chapter 6: Summary and Conclusions 109

The goal of GBILM is to develop landscape monitoring 

approaches, including methods for monitoring environmental 

stressors and responses at the landscape level, and methods 

for scaling from plot-level data collected by land managers 

to larger spatial extents to describe cumulative effects. The 

need for a landscape approach primarily stems from the 

increasing impact from regional and global stressors (such 

as climate change, water withdrawal, invasive plant species, 

and air pollution), which affects areas larger than those 

under the authority of individual land managers. In addition, 

anthropogenic stressors (such as urbanization, off highway 

vehicle use, land treatments, and wildfire) that often are 

considered to be local are becoming more numerous and 

pervasive such that their aggregated impacts affect broad 

regions. Stressor effects accumulate and interact with each 

other in complex fashions that require understanding and 

assessment at the landscape level. For example, responses of 

biota to environmental change depend on inherent biophysical 

potential, in addition to past and current conditions of the 

individual sites and surroundings, and the responses may 

be directly and indirectly related to stressors. Streamflow, 

soil erosion, and water temperature in springs also respond 

to local and regional stressors and in turn drive changes in 

biota. In particular, changes in the Great Basin are threatening 

extinction of species whose habitat requirements span multiple 

management jurisdictions and require a landscape perspective 

for effective protection. The highly varied topography, strong 

climate gradients, and effective isolation of many biotic zones 

in the Great Basin compound these challenges and make the 

design of monitoring systems difficult.

Land managers often are charged with conserving 

environments within well-defined spatial and temporal 

bounds even though natural processes and disturbance 

regimes extend beyond those boundaries. Jurisdictional 

boundaries and duration-specific resource management plans 

place somewhat arbitrary hindrances on fully understanding 

and managing resources experiencing multiple interactions 

ranging from short-term and site-specific to long-term and 

regional. Our landscape perspective provides managers with 

perspectives and conceptual tools for evaluating external and 

antecedent inputs into their system of interest and applying 

landscape-context management principles to local resources. 

Furthermore, the conceptual models in this report can help 

land managers understand how individual management actions 

interact with one another and how these interactions may lead 

to the emergence of impacts unlike those of single actions. 

Conceptual models should be the foundation for 

all products GBILM aims to provide to land managers. 

Fundamentally, conceptual models describe the most salient 

components of ecosystems and the interactions among them. 

They express current understanding and hypotheses regarding 

system function, by integrating information from disparate 

sources including research results and expert opinion and 

experience. They facilitate communication to create agreement 

on, and common vision of, the system in question. Having a 

common perception insures that land managers, researchers, 

and other interested parties agree on the important components 

and processes related to the issue being addressed. A 

compilation of information sources insures that mechanistic 

models are as accurate as possible. The conceptual models 

can illustrate the relevant interactions and functions for any 

given problem or situation. The models provide a foundation 

for developing quantitative spatial models that will enable the 

integration of multiple stressors acting at various spatial scales 

to give managers a landscape context.

In this document we presented a hierarchy of conceptual 

models, beginning with a framework model that describes 

the relationships among the major biotic and abiotic systems 

in the Great Basin: the atmospheric system, the human 

social system, and the dry and wet ecosystems. Each of 

these systems is described in more detail in separate general 

system models. The atmospheric system model describes how 

atmospheric processes are fundamental drivers of Great Basin 

ecosystems, hydrology, and geomorphology; the human-social 

system model describes social and cultural factors resulting 

in patterns of land and water use and their evolution; the 

dry and wet system models describe the broad landscape 

patterns and relationships among the subsystems. For the 

dry and wet systems, we developed more detailed models 

for high-priority subsystems that describe components, their 

functional relationships, and potential effects of key stressors. 

Dry subsystem models are differentiated by biophysical 

potential on the landscape (biomes) and include sagebrush 

steppe, pinyon-juniper woodlands, mixed conifer forest, and 

alpine tundra. Wet subsystem models distinguish fundamental 

hydrologic entities, and include the groundwater system, 

stream and riparian systems, and wetland and spring systems. 

Chapter 6: Summary and Conclusions 

By Andrea Woodward, S.P. Finn, and D.M. Miller
110 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

We have not yet developed subsystem models for salt desert 

scrub, aspen forests, freshwater lakes and saline lakes and 

marshes, as well as for specialized environments such as 

dry playas and sand dunes, but these models are needed for 

complete evaluation of the Great Basin. Descriptions of each 

subsystem model identify knowledge gaps and research needs 

to acknowledge what is not understood and provide direction 

to future work.

In addition to the models in this report, GBILM is 

creating information products and analytical techniques that 

will assist with reinterpretation of the models in conjunction 

with the development of a long-term regional monitoring 

strategy. For example, we are creating a regional map of 

phreatophytic vegetation communities to identify areas that 

might be most responsive to groundwater development. Such 

products will have multiple applications, which our conceptual 

models will help scientists and managers to visualize. In this 

case, a manager interested in the effects of overland flow 

and erosion might use the phreatophytic vegetation layer 

to evaluate the combined effects of water withdrawal and 

erosion (for example, fig. 5.8). We believe these and other 

data products can be used effectively with our conceptual 

models to increase a manager’s ability to evaluate multiple 

actions and better understand the broader context within which 

management decisions are made.

Ultimately, this group of conceptual models will 

contribute to GBILM’s goal of developing a comprehensive 

landscape-level monitoring strategy for the Great Basin. 

Initially, conceptual models will identify elements of 

ecosystems that are predicted to respond to stressors based on 

our current understanding of system function. These elements 

are potentially valuable to monitor. Eventually, predictive 

spatial models, built according to the concepts presented in 

Chapter 5, can focus attention on ecosystem components and 

processes that will manifest the effects of multiple stressors 

and drivers. Predictive models also can combine conceptual 

models with empirical data to explore predicted stressor 

impacts. This modeling effort helps to visualize ecosystem 

responses and interactions, which can lead to identification of 

efficient or sensitive monitoring indicators. 

Our Great Basin conceptual models remain incomplete 

because we focused our limited resources on high priority 

subsystems and we lacked the expertise to fully develop some 

models. Furthermore, the models we present here are subject 

to modification in an adaptive management context. Because 

management priorities change and scientific understanding 

increases, all models are expected to undergo episodic 

development and increased scrutiny, particularly as new 

threats emerge. To have maximum effect, these models require 

data for validation and testing by targeted field studies. A 

logical step is to mine historical data to validate the models, 

an effort that GBILM has begun with promising early results 

(Land Treatments Digital Library project, accessed June 24, 

2009, at http://www.usgs.gov/features/greatbasin/projects/

treatments.html). After assembling and cataloging the data, 

analysis can follow. Analyses will feed back to the appropriate 

conceptual models for validation and application, help to 

identify data gaps and research needs, and help parameterize 

integrative predictive models. 

We expect the conceptual models in this report to 

stimulate and inform efforts to build efficient, comprehensive 

monitoring plans. When combined with programs that collect 

a body of data for trend evaluation, collect needed baseline 

data, and conduct field studies to investigate knowledge gaps, 

the conceptual models provide the basis for a comprehensive 

investigation of Great Basin landscape threats, on which 

comprehensive monitoring programs can be constructed. 

GBILM investigations provide long-term value over large 

extents, yielding benefits to society but only through sustained 

commitments from the U.S. Geological Survey and its landmanagement partners.
References Cited 111

Acknowledgments

This report is large, wide-ranging, was long in the 

making, and was developed as part of an interdisciplinary 

group project. As a consequence, its authors have benefited 

from interactions with a large group of scientists, land 

managers, and decision-makers; a group too large to 

acknowledge individually.

The initial conceptual models workshop members who 

contributed to developing the approach and the eventual 

design of the report deserve credit: Matt Brooks, Marie Denn, 

Nora Devoe, Kimball Goddard, Tom Owens, Mike Pellant, 

and Dave Pyke. These members continued in several roles, 

including providing informal reviews of early drafts of parts 

of the report. Contributions to water system models came 

from Debra Hughson and Kimball Goddard. Later meetings 

designed to develop specific models benefited greatly from 

contributions from Kimball Goddard, Debra Hughson, Steve 

Knick, Mike Casazza, and Don Sada. In addition, Eric Beever, 

Victor Heilweil, and Erika Fleishman provided informal 

reviews of draft models. Technical assistance from Linda 

Rogers, Janet Erickson, Ruth Jacobs, and Susan Powell is 

gratefully acknowledged.

The unwavering support and encouragement from project 

leaders Carol Schuler and Kate Kitchell played a vital role in 

seeing this document to completion. However, the technical 

reviews of the report by Dave Busch and Debra Hughson 

possibly required the largest individual commitments and had 

the largest impact. This report is more complete and much 

stronger as a result of their insightful questions and comments. 

We only wish it were within the scope of the report to carry 

out all of their recommendations.

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Glossary

Adaptive management A systematic process for continually 

improving management policies and practices by learning 

from the outcomes of operational programs. Its most effective 

form— “active” adaptive management—employs management 

programs that are designed to experimentally compare 

selected policies or practices by implementing management 

actions explicitly designed to generate information useful 

for evaluating alternative hypotheses about the system being 

managed (http://science.nature.nps.gov/im/monitor/Glossary.

cfm).

Attributes Any living or nonliving feature or process of 

the environment that can be measured or estimated and 

that provides insights into the state of the ecosystem. The 

term Indicator is reserved for a subset of attributes that is 

particularly information-rich in the sense that their values are 

somehow indicative of the quality, health, or integrity of the 

larger ecological system to which they belong (Noon, 2003; 

http://science.nature.nps.gov/im/monitor/Glossary.cfm). Also 

see Indicator.

Climate change (Also called climatic change) a change of 

climate which is attributed directly or indirectly to human 

activity that alters the composition of the global atmosphere 

and which is in addition to natural climate variability observed 

over comparable time periods (United Nations Framework 

Convention on Climate Change, accessed June 24, 2009, at 

http://unfccc.int/2860.php).

Climate variability (Also called climatic variability) The 

temporal variations of the atmosphere– ocean system around 

a mean state. Typically, this term is used for timescales longer 

than those associated with synoptic weather events (that is, 

months to millennia and longer; Glossary of Meteorology, 

accessed June 24, 2009, at http://amsglossary.allenpress.com/

glossary/). 

Community “All of the populations occupying a given area” 

(Odum 1959, 6); Odum’s definition was adapted by the Risk 

Assessment Forum to read: “an assemblage of populations of 

different species within a specified location in space and time” 

(Environmental Protection Agency Risk Assessment Forum 

1992, p. 37). “In ecology, a group of interacting populations 

in time and space. Sometimes, a particular subgrouping may 

be specified, such as the fish community in a lake or the soil 

arthropod community in a forest,” (EPA, 1992, p. 6). 

Composition The identity and variety of elements within 

an ecosystem, including species present and their population 

structure, abundance, and genetic diversity (Noss, 1990).

Conceptual Models Purposeful representations of reality 

that provide a mental picture of how something works to 

communicate that explanation to others (NPS I&M glossary). 

A “conceptual model describes a series of working hypotheses 

of how a stressor(s) might affect an ecological component(s). 

The conceptual model also describes the ecosystem 

potentially at risk, the relationship between measurement 

endpoints and assessment endpoints, and exposure scenarios,” 

(Environmental Protection Agency Risk Assessment Forum 

1992, p. 37).

Control model Describe our understanding of how the 

systems work in response to the natural variation of drivers 

by depicting the principal components and processes of the 

subsystem. These models focus on the priority drivers for 

specific subsystems.

Cumulative effects Can appear as a stressor accumulating 

over space (for example, low levels of a water pollutant 

in tributaries accumulating in a river), time (for example, 

multiple land treatments of the same patch), or combinations 

of single and multiple stressors accumulating over time and 

space.

Disturbance “...any relatively discrete event in time that 

disrupts ecosystem, community, or population structure and 

changes resources, substrate availability, or the physical 

environment” (White and Pickett, 1985, p. 7). In relation 

to monitoring, disturbances are considered to be ecological 

factors that are within the evolutionary history of the 

ecosystem (for example, drought). These are differentiated 

from anthropogenic factors (stressors, below) that are outside 

the range of disturbances naturally experienced by the 

ecosystem (Whitford, 2002).

Disturbance regime Consists of the timing, predictability, 

frequency, and severity of a specified source of disturbance, or 

combination of disturbances, in a specific area.

Drivers and Stressors Physical, chemical, or biological 

perturbations to a system that are either (a) foreign to that 

system or (b) natural to the system but applied at an excessive 

(or deficient) level (Barrett and others, 1976, p. 192). Stressors 

cause significant changes in the ecological components, 

patterns and processes in natural systems.

Dry system For the purposes of these models, a dry system is 

wholly dependent on precipitation for its source of water. Dry 

systems have no dependence or association with groundwater 

or free surface water. 
130 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Ecological integrity A concept that expresses the degree 

to which the physical, chemical, and biological components 

(including composition, structure, and process) of an 

ecosystem and their relations are present, functioning, and 

capable of self-renewal. Ecological integrity implies the 

presence of appropriate species, populations and communities 

and the occurrence of ecological processes at appropriate rates 

and scales as well as the environmental conditions that support 

these taxa and processes (http://science.nature.nps.gov/im/

monitor/Glossary.cfm). 

Ecoregion A relatively homogeneous geographic area 

“perceived by simultaneously analyzing a combination of 

causal and integrative factors including land surface form, 

soils, land uses, and potential natural vegetation (Omernik, 

1987, p. 123). Ecoregions “was coined by J.M. Crowley 

(1967) and popularized by R.G. Bailey (1978) to define a 

mapped classification of ecosystem regions of the U.S....

Ecoregions are generally considered to be the regions of 

relative homogeneity in ecological systems or in relationships 

between organisms and their environments”.

Ecosystem A spatially explicit unit of the Earth that includes 

all of the organisms, along with all components of the abiotic 

environment within its boundaries (Likens 1992, cited by 

Christensen and others, 1996, p. 670). 

Ecosystem functioning The flow of energy and materials 

through the arrangement of biotic and abiotic components of 

an ecosystem. Includes many ecosystem processes such as 

primary production, trophic transfer from plants to animals, 

nutrient cycling, water dynamics and heat transfer. In a broad 

sense, ecosystem functioning includes two components: 

ecosystem resource dynamics and ecosystem stability (Díaz 

and Cabido, 2001).

Ecosystem health A metaphor pertaining to the assessment 

and monitoring of ecosystem structure, function, and resilience 

in relation to the notion of ecosystem “sustainability” 

(following Rapport, 1998, and Costanza and others, 1998). A 

healthy ecosystem is sustainable (see Sustainable ecosystem, 

below). 

Extent, Spatial The total length, area, or volume that exists 

or is observed or analyzed; or the duration of time under 

consideration.

Focal ecosystems Ecosystems that play significant 

functional roles in landscapes by their disproportionate 

contribution to the transfer of matter and energy, or by their 

disproportionate contribution to landscape-level biodiversity.

Framework Model The highest level of our model hierarchy; 

identifies the major biotic and abiotic systems of the Great 

Basin and how they are related.

Grain The size of the elementary sampling units. It may be 

expressed as the diameter, surface, or volume of the matter 

supporting the measurements (Legendre and Legendre, 1998).

Hierarchical model A construct in which component 

variables and systems of ecological entities are defined to have 

the smallest unit of spatial and temporal detail in the lowest 

level; each higher level reflects processes and interactions 

occurring at ever larger spatial and temporal scales. Behaviors 

of a particular level in the hierarchical model are determined 

by constraints imposed by the levels above and filtered or 

averaged behaviors of components and subsystems of levels 

below (Environmental Protection Agency e-map, accessed 

June 24, 2009, at http://www.epa.gov/emap/html/pubs/docs/

resdocs/mglossary.html).

Hydrologic function (upland systems) Capacity of a site to 

capture, store, and safely release water from rainfall, run-on, 

and snowmelt, to resist a reduction in this capacity, and to 

recover this capacity following degradation (Pellant and 

others, 2005). Soil hydrologic function is the ability of the 

soil to absorb, store, and transmit water, both vertically and 

horizontally. Changes in soil properties and ground cover can 

alter the hydrologic function of the soil.

Hydrologic function (lotic and lentic systems) Capacity of 

an area to: dissipate energies associated with (1) high stream 

flow (lotic); or (2) wind action, wave action, and overland 

flow (lentic); thereby reducing erosion and improving water 

quality; filter sediment, capture bedload, and aid floodplain 

development; improve flood-water retention and groundwater 

recharge; develop root masses that stabilize streambanks 

against cutting action; develop diverse ponding and channel 

characteristics to provide the habitat and the water depth, 

duration, and temperature necessary for fish production, 

waterfowl breeding, and other uses; support greater 

biodiversity (from Prichard and others, 1998).

Indicator (general use of term) A term reserved for a subset 

of environmental attributes that is particularly information-rich 

in the sense that their values somehow indicate the quality, 

health, or integrity of the larger ecological system to which 

they belong (Noon, 2003; http://science.nature.nps.gov/im/

monitor/Glossary.cfm). Indicators are a selected subset of the 

physical, chemical, and biological elements and processes of 

natural systems that are selected to represent the overall health 

or condition of the system.

Indicators of ecosystem health (specific use of 

term) Measurable attributes of the environment (biotic or 

abiotic) that provide insights regarding (1) the functional 

status of one or more key ecosystem processes, (2) the status 

of ecosystem properties that are clearly related to these 

ecosystem processes, and/or (3) the capacity of ecosystem 

processes or properties to resist or recover from natural 

disturbances and/or anthropogenic stressors (modified from 

Whitford, 1998). In the context of ecosystem health, key 

ecosystem processes and properties are those that are most 

closely associated with the capacity of the ecosystem to 

maintain its characteristic structural and functional attributes 

over time (including natural variability). 
Glossary 131

Integration Model Summary model(s) addressing cumulative 

effects and integration of multiple stressors and drivers 

through time and space. Integration requires transferring 

data across the range of spatial scales between the scale at 

which data are collected and the scale at which management 

questions are asked. Integration provides templates for 

addressing the multiple temporal scales at which ecosystem 

processes, drivers, and stressors operate (see Chapter 5). 

Interactions Synergistic results of multiple stressors on a 

focal system and the mathematical expression that specifies 

the nature and strength of this effect.

Landscape A spatially structured mosaic of different types 

of ecosystems functionally interconnected by ecological flows 

of materials (for example, water and sediments) energy, and 

organisms.

Landscape change Changes in the types, relative 

proportions, and ‘condition’ (health, integrity, resiliency, and 

functioning) of ecosystems – particularly as these relate to 

mandates/management objectives of DOI land managers and 

other partner agencies.

Modeling A representation of a physical system or process 

intended to enhance our ability to understand, predict, or 

control its behavior. A conceptual model consists of a 

system’s initial and boundary conditions and hypotheses and 

observations made about the system.

Monitoring Collection and analysis of repeated observations 

or measurements to evaluate changes in condition and 

progress toward meeting a management objective (Elzinga 

and others, 2001). Detection of a change or trend may trigger 

a management action, or it may generate a new line of inquiry. 

Monitoring is often done by sampling the same sites over 

time, and these sites may be a subset of the sites sampled for 

the initial inventory.

Nutrient cycling The circulation of chemical elements 

such as nitrogen, oxygen, carbon, and phosphorus in specific 

pathways from the abiotic (not involving or produced 

by organisms) portions of the environment into organic 

substances in plants and animals and then back into abiotic 

forms.

Reference state Or reference condition ideally is defined on 

a site-specific basis according to climate and soil-geomorphic 

setting framed with respect to a particular time period and 

place. A reference state can be thought of as the “natural” 

standard for management and monitoring; it explicitly 

identifies associated goals, assumptions, and value judgments 

(White and Walker, 1997; Landres and others, 1999).

Resolution The smallest object that can be reliably detected; 

the precision of a measurement.

Scale A general term with multiple, sometimes contradictory 

meanings. In this document, scale is defined by one of the 

following, depending on qualifying words that place ‘scale’ in 

context: A. the spatial or temporal dimension of an object or 

process, characterized by both grain and extent; B. the actual 

distance, direction, shape, and geometry; C. the cartographic 

ratio between a map and the ground it represents. For 

somewhat analogous, but distinct terms see: Grain, Extent, 

Resolution, and Support.

Social capacity “and economic capital state is comprised 

of the “traditional” economic notion of capital – all assets 

and liabilities present in the economy. Also included are the 

concepts of social capital or capacity representing the potential 

opportunities afforded by the way society exists” (Sustainable 

Rangelands Roundtable, 2006).

State-and-Transition Model A non-linear approach to 

describe ecological systems and processes often presented as 

an alternate to the traditional Clementsian (Clements, 1916) 

succession-climax community concept. State-and-transition 

models are management-oriented tools for describing and 

classifying ecosystem conditions (or states) and posing 

hypotheses about ecological factors responsible for changes 

(or transitions) among different states. 

Stressor See Drivers and Stressors.

Stressor model An abstraction of a particular system or part 

of a system focused on the links between stressors, ecosystem 

responses, effects, and in some cases indicators. A stressor 

model does not necessarily incorporate all relevant system 

components, feedbacks, or interactions.

Subsystem In this document subsystem refers to a definable 

biophysical component of the wet or dry system and the 

specific subject of a Subsystem Model. A subsystem has a 

common suite of biota adapted to highly discernable climate 

and physical template properties. 

Subsystem Model Aspatial descriptive models of subsystem 

components, drivers & dynamics.

Support An N-dimensional volume, including its geometrical 

shape, size and orientation, within which average values of a 

variable may be computed (Dungan and others, 2002).

Sustainable ecosystem An ecosystem “...that, over the 

normal cycle of disturbance events, maintains its characteristic 

diversity of major functional groups, productivity, and rates of 

biogeochemical cycling” (Chapin and others, 1996, p. 1016). 

System The complete set of components and their 

interactions of interest. A system could be a forest, a desert, 

a manufacturing plant, or a town. In our case, the system 

of interest usually encompasses terrestrial, atmospheric, 

hydrological, and human-dominated components. 

System Model Graphic and narrative models that describe 

the landscape and relations among subsystems.
132 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

Threshold As applied to state-and-transition models, a 

threshold is a point “...in space and time at which one or 

more of the primary ecological processes responsible for 

maintaining the sustained [dynamic] equilibrium of the state 

degrades beyond the point of self-repair. These processes must 

be actively restored before the return to the previous state is 

possible. In the absence of active restoration, a new state ... 

is formed” (Stringham and others, 2003, p. 109). Thresholds 

are defined in terms of the functional status of key ecosystem 

processes and are crossed when capacities for resistance and 

resilience are exceeded. Also see State-and-Transition Model. 

Transition As applied to state-and-transition models, a 

transition is a trajectory of change that is precipitated by 

natural events and/or management actions which change the 

integrity of one or more of the primary ecological processes 

responsible for maintaining the dynamic equilibrium of the 

state. Transitions are vectors of system change that will lead 

to a new state without abatement of the stressor(s) and/or 

disturbance(s) prior to exceeding the system’s capacities for 

resistance and resilience (adapted from Stringham and others, 

2003). Also see state and threshold.

Water quality The chemical, physical, and biological 

characteristics of water, usually in respect to its suitability for 

a particular purpose.

Wet System For the purposes of these models, a wet system 

is an ecosystem or community that has direct input of free 

water sourcing from an underground aquifer (groundwater) 

or above-surface lotic or lentic system. Example wet systems 

include, springs, seeps, riparian systems, and lakes.
Appendix A 133

Appendix A. Ratings of System Drivers

Complete list of drivers considered for use in wet and dry subsystem models. Highest priority drivers are listed at the top; 

those in bold type are identified as top priority drivers for constructing models. Some drivers ranked high but were not listed as 

top priority because they are part of the Human-Social Systems model. Models of the Atmospheric/Climate and Human/Social 

systems are already driver-specific models describing how their top drivers interact with other drivers to impact the entire Great 

Basin region.

System System Driver

Wet Flow Regime

Water Extraction & Irrigation

Water Impoundment

Altered Flow Regime

Economic and Political Factors

Climate Variability

Land Use & Land Cover

Invasive Exotics

Livestock Grazing

Agriculture

Urban-Exurban Development

Channelization

Water Pollution

Legal Mandates

Resource Extraction

Climate Change

Recreation

Erosion

Motorized Vehicle Use

Fire Acceleration

Linear Infrastructure

Pathogens

Fire Suppression

Livestock Grazing

Atmospheric Pollution/Deposition

Insects and Disease

Fire Regime

Particulates (Airborne & Deposited)

Military Land Use

Light Pollution

Sound Pollution

System System Driver

Dry Fire Regime

Climate Variability (for example, drought)

Invasive Exotics

Land Use & Land Cover

Livestock Grazing

Fire Acceleration

Economic and Political Factors

Motor Vehicle Use

Urban-Exurban Development

Fire Suppression
134 Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin

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http://fresc.usgs.gov
Miller and others— Conceptual Ecological Models to Guide Integrated Landscape Monitoring of the Great Basin—Scientific Investigations Report 2010–5133