Climate Change Vulnerability and Adaptation 

in the Intermountain Region

Part 1

Forest Rocky Mountain General Technical Report

Service Research Station RMRS-GTR-375 April 2018

United States Department of Agriculture
Halofsky, Jessica E.; Peterson, David L.; Ho, Joanne J.; Little, Natalie, J.; Joyce, Linda A., eds. 2018. Climate 

change vulnerability and adaptation in the Intermountain Region. Gen. Tech. Rep. RMRS-GTR-375. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. Part 1. pp. 1–197.

Abstract

The Intermountain Adaptation Partnership (IAP) identified climate change issues relevant to resource management 

on Federal lands in Nevada, Utah, southern Idaho, eastern California, and western Wyoming, and developed 

solutions intended to minimize negative effects of climate change and facilitate transition of diverse ecosystems 

to a warmer climate. U.S. Department of Agriculture Forest Service scientists, Federal resource managers, and 

stakeholders collaborated over a 2-year period to conduct a state-of-science climate change vulnerability assessment 

and develop adaptation options for Federal lands. The vulnerability assessment emphasized key resource areas—

water, fisheries, vegetation and disturbance, wildlife, recreation, infrastructure, cultural heritage, and ecosystem 

services—regarded as the most important for ecosystems and human communities.

The earliest and most profound effects of climate change are expected for water resources, the result of declining 

snowpacks causing higher peak winter streamflows, lower summer flows, and higher stream temperatures. These 

changes will in turn reduce fish habitat for cold-water fish species, negatively affect riparian vegetation and wildlife, 

damage roads and other infrastructure, and reduce reliable water supplies for communities. Increased frequency and 

magnitude of disturbances (drought, insect outbreaks, wildfire) will reduce the area of mature forest, affect wildlife 

populations (some positively, some negatively), damage infrastructure and cultural resources, degrade the quality of 

municipal water supplies, and reduce carbon sequestration. Climate change effects on recreation, a major economic 

driver in the IAP region, will be positive for warm-weather activities and negative for snow-based activities. IAP 

participants developed adaptation options that can be implemented in planning, project management, monitoring, and 

restoration as climate-smart responses to altered resource conditions.

Keywords: adaptation, climate change, ecological disturbance, Intermountain Adaptation Partnership, resilience, 

science-management partnership, vulnerability assessment

Front cover photo: Fall colors and reflection on a pond in Lamoille Canyon, Ruby Mountains District, Humboldt-Toiyabe National 

Forest, NV, photo by Susan Elliott, U.S. Forest Service.

All Rocky Mountain Research Station publications are published by U.S. Forest Service employees and are in the 

public domain and available at no cost. Even though U.S. Forest Service publications are not copyrighted, they 

are formatted according to U.S. Department of Agriculture standards and research findings and formatting cannot 

be altered in reprints. Altering content or formatting, including the cover and title page, is strictly prohibited.
Editors

Jessica E. Halofsky is a Research Ecologist with the University of Washington, College of the Environment, School 

of Environmental and Forest Sciences in Seattle, Washington.

David L. Peterson was a Senior Research Biologist Scientist with the U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station in Seattle, Washington.

Joanne J. Ho is a Research Environmental Economist with the University of Washington, College of the 

Environment, School of Environmental and Forest Sciences in Seattle, Washington.

Natalie J. Little is the Regional Sustainability and Climate Coordinator, U.S. Department of Agriculture, Forest 

Service, Intermountain Region in Ogden, Utah.

Linda A. Joyce is a Research Ecologist with the U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station, Human Dimensions Research Program in Fort Collins, Colorado.

Acknowledgments

We thank leadership and resource managers of the U.S. Forest Service Intermountain Region and National Park 

Service for their support of the Intermountain Adaptation Partnership. We greatly appreciate the enthusiasm and 

contributions of all participants in the vulnerability assessment and adaptation workshops. We appreciated the 

help of Gary Eickhorst, DuWayne Kimball, and Tosha Wixom in logistical assistance with the workshops, and the 

facilitation of the webinar series by Karen Dante-Wood. The following peer reviewers provided insightful comments 

that greatly improved this publication: Seth Arens, Robert Al-Chokhachy, Sarah Baker, Dale Blahna, Kristie Boatner, 

Michael Bowker, Polly Buotte, C. Alina Cansler, Caty Clifton, Molly Cross, Dan Dauwalter, Chris Fettig, Nick Glidden, 

Gordon Grant, Ed Grumbine, Sean Harwood, Justin Humble, Morris Johnson, Gordon Keller, Sarah Leahy, Susan 

Leslie, Maia London, Jeff Lukas, Danielle Malesky, Anne Marsh, John McCann, Toni Lyn Morelli, Nick Neverisky, 

Mary O’Brien, Andrew Orlemann, Troy Osborne, Kristen Pelz, Holly Prendeville, Ben Rasmussen, Bryce Richardson, 

Marcy Rockman, Rema Sadak, Steve Scheid, Nikola Smith, Casey Watson, Jim Winfrey, and Caleb Zurstadt. Paige 

Eagle provided valuable website design and support. Jeff Bruggink, Robert Norheim, and Teresa Rhoades provided 

support with geospatial analysis and cartography. Kit Mullen provided valuable input throughout the process. We 

thank Mark Bethke for his vision, solutions, and leadership. Funding was provided by the U.S. Forest Service Office 

of Sustainability and Climate, Intermountain Regional Office, and Pacific Northwest and Rocky Mountain Research 

Stations. Our hope is that the Intermountain Adaptation Partnership will maintain an ongoing dialogue about climate 

change in the years ahead, catalyzing activities that promote sustainability in the remarkable ecosystems of the 

Intermountain Adaptation Partnership region.

Summary

The Intermountain Adaptation Partnership (IAP) is a science-management partnership with a wide variety of participants 

across the U.S. Department of Agriculture, Forest Service Intermountain Region, which spans Nevada, Utah, southern 

Idaho, eastern California, and western Wyoming. The partnership includes the Forest Service Intermountain Region, 

and Pacific Northwest and Rocky Mountain Research Stations; National Park Service Climate Change Response 

Program; North Central Climate Science Center; Desert, Great Basin, Great Northern, and Southern Rockies 

Landscape Conservation Cooperatives; the University of Washington; Native American tribes; and dozens of other 

stakeholder organizations. These organizations and other IAP participants worked together over 2 years to identify 

climate change issues relevant to resource management on Forest Service and National Park Service lands in the 

IAP region, and to find solutions that could help to minimize the negative effects of climate change and facilitate the 

transition of ecosystems to a warmer climate. The IAP provided education, conducted a climate change vulnerability 

assessment, and developed adaptation options for managing resources of the 12 national forests (Ashley, Boise, 

Bridger-Teton, Caribou-Targhee, Dixie, Fishlake, Humboldt-Toiyabe, Manti-La Sal, Payette, Salmon-Challis, Sawtooth, 

Uinta-Wasatch-Cache [plus Curlew National Grassland]) and 22 National Park Service units in the IAP region.
ii

The IAP region is characterized by high ecological diversity. Vegetation types include mixed conifer forest, dry 

ponderosa pine forest, subalpine forest, sagebrush, grasslands, alpine tundra, and wetlands. Ecosystems in the IAP 

region produce water, fish, timber, wildlife, recreation opportunities, livestock grazing, and other ecosystem services, 

providing a socioeconomic foundation based on natural resources. The geographic and ecological diversity of the 

region, especially on Federal lands, contributes significantly to the economic sustainability of human communities, 

linking Federal resource management with local livelihoods.

The effects of climate change on each resource area in the IAP region are synthesized from the available scientific 

literature and analyses and are based on available climate change projections (Chapter 3). Highlights of the 

vulnerability assessment and adaptation options for each resource area are summarized next.

Water and Soil Resources

Climate Change Effects

Lower snowpack and increased drought will result in lower base flows, reduced soil moisture, wetland loss, riparian 

area reduction or loss, and more frequent and possibly more severe wildfire. April 1 snow water equivalent and mean 

snow residence time are sensitive to temperature and precipitation variations. Warmer (usually lower elevation) 

snowpacks are more sensitive to temperature variations, whereas colder (usually higher elevation) snowpacks are 

more sensitive to precipitation. Warmer locations will experience more runoff in winter months and early spring, 

whereas colder locations will experience more runoff in late spring and early summer. In both cases, future peakflows 

will be higher and more frequent.

Lower snowpacks will cause significantly lower streamflow in summer, and reduce the rate of recharge of water 

supply in some basins. Annual water yields, which are affected by annual precipitation totals (heavily influenced 

by winter and spring precipitation in the western part of the region) and summer evapotranspiration, will generally 

be lower. Although declining snowpacks will occur throughout the region, snowpacks at higher elevations (Uinta 

Mountains, Teton and Wind River Ranges, and some central Idaho ranges) may not change much through the late 

21st century. Carbon content in soils will decrease in areas where decomposition rate and wildfire frequency increase, 

and soil erosion will be accelerated by intense fires.

Adaptation Options

Primary adaptation strategies focus on expanding water conservation; increasing water storage, managing for 

highly functioning riparian areas, wetlands, and groundwater-dependent ecosystems; and developing policies 

for water rights. Adaptation tactics include: (1) using drought-tolerant plants for landscaping, managing livestock 

water improvements efficiently, and educating the public about water resource issues and conservation; (2) 

decommissioning and improving road systems, improving grazing management practices, and promoting and 

establishing American beaver populations; (3) managing vegetation to reduce forest density and hazardous fuels; 

(4) modifying dam and reservoir operation to improve water storage, and improving streamflow and runoff forecasts; 

and (5) maintaining and protecting soil cover and cryptobiotic crusts, using grazing management systems that 

promote healthy root systems in plants, and promoting native plant species diversity.

Fish and Other Aquatic Species

Climate Change Effects

A combination of higher stream temperature, low streamflow in summer, and higher peakflow at other times of the 

year will create a significant stress complex for cold-water fish species. Habitats that provide the restrictive thermal 

requirements of juvenile bull trout are rare, and little evidence exists for flexibility in habitat use. The length of 

connected habitat needed to support a bull trout population varies with local conditions, but current estimates suggest 

a minimum of 20 to 30 miles contingent on water temperature, nonnative species presence, and local geomorphic 

characteristics. Juvenile cutthroat trout occupy a broader thermal and stream size niche than bull trout. They also 

appear to persist in smaller habitat patches. Nonetheless, they require cold-water habitat patches exceeding 3 to 6 

miles. Increased frequency and extent of extreme events will be especially stressful for bull trout and cutthroat trout, 

except at higher elevations, where habitat will remain favorable. Both species may in some cases be able to adjust 
iii

their life histories to accommodate altered habitat, although the potential for this adaptive capacity is unknown. From 

the mid- to late-21st century, the vast majority of suitable cold-water fish habitat will be on Federal lands.

Rocky Mountain tailed frogs have long generation times and low fecundity, so increased summer droughts and 

wildfires, as well as extreme floods and postfire debris flows may threaten some populations. Sensitivities are 

similar for Idaho giant salamanders. Western pearlshell mussels have a broad geographic range, which reduces 

their vulnerability, although lower streamflow and higher stream temperatures are expected to be stressful in some 

locations. Springsnails are expected to be highly vulnerable because they require particular hydrological conditions, 

specific and stable temperature regimes, and perennial flows. Yosemite toads, already in decline, will be sensitive to 

reduced duration of ephemeral ponds for breeding in spring. Sierra Nevada yellow-legged frogs will be sensitive to 

less reliable availability of perennial water bodies needed for multiyear metamorphosis and maturation.

Adaptation Options

Primary adaptation strategies focus on increasing resilience of native fish species by restoring structure and function 

of streams, riparian areas, and wetlands; monitoring for invasive species and eliminating or controlling invasive 

populations; understanding and managing for community-level patterns and processes; and conducting biodiversity 

surveys to describe current baseline conditions and manage for changes in the distribution of fish and other aquatic 

species. Adaptation tactics include reconnecting floodplains and side channels to improve hyporheic and base 

flow conditions, ensuring that passage for aquatic organisms is effective, accelerating restoration in riparian areas, 

maintaining or restoring American beaver populations, managing livestock grazing to restore ecological function of 

riparian vegetation, removing nonnative fish species, maintaining or increasing habitat connectivity, and increasing 

the resilience of forests to wildfire.

Vegetation and Ecological Disturbances

Climate Change Effects

Increased temperature is expected to cause a gradual change in the distribution and abundance of dominant plant 

species. Increased ecological disturbance, driven by higher temperatures, is expected to cause near-term effects 

on vegetation structure and age classes, and will facilitate long-term changes in dominant vegetation. In forest 

ecosystems, native and non-native insects are expected to be significant stressors in a warmer climate; in fact, this 

appears to be already occurring. In all vegetation types, an increase in the frequency and extent of wildfire will be 

a significant stressor, especially where large fuel accumulations exist. Nonnative plant species will likely continue 

to expand in most vegetation types, especially in rangelands, potentially displacing native species and altering fire 

regimes. A combination of these and other stressors (stress complexes), exacerbated by climate, may accelerate the 

rate of change in vegetation assemblages, and reduce productivity and carbon storage in most systems. Riparian 

areas may be especially sensitive as a warming climate causes hydrological regimes to change, reducing the timing 

and amount of water available in summer. Climate change effects on specific forest types include:

• Subalpine pine forest—Most subalpine tree species will be moderately affected by a warmer climate, although 

bristlecone pine could undergo stress in the driest locations. Whitebark pine will be vulnerable because it is 

already stressed from white pine blister rust and mountain pine beetles. If wildfire increases, crown fires may 

quickly eliminate mature trees across the landscape.

• Subalpine spruce-fir forest—This forest type will be moderately vulnerable. Subalpine fir and Engelmann spruce 

may have increased growth in a longer growing season. Bark beetles will be a stressor for Engelmann spruce. If 

wildfire increases, crown fires may quickly eliminate mature trees across the landscape. Quaking aspen will be 

minimally affected by a warmer climate.

• Mesic mixed conifer forest—Late-seral forests will be susceptible to wildfire, especially where fuel loads are high. 

Douglas-fir, ponderosa pine, and Jeffrey pine, which have high fire tolerance, may become more common, and 

late-seral species less common. Growth rates of most species will decrease. Lodgepole pine and quaking aspen 

will persist, perhaps with increased stress from insects and pathogens.
iv

• Dry mixed conifer forest—Most species in mixed conifer forest (ponderosa pine, Gambel oak, quaking aspen) 

can cope with dry soils and wildfire. Growth of less drought-tolerant species (Douglas-fir, white fir) will decrease. 

With increased fire frequency, early-seral species will become more common, and late-seral species less 

common.

• Aspen mixed conifer forest—Increased wildfire frequency and extent will determine future composition and 

structure of this forest type. Conifers at higher elevations (mostly not fire resistant) will become less common, 

confined to northern slopes and valley bottoms. Quaking aspen and Gambel oak will attain increasing dominance 

because of their ability to sprout vigorously after fire, outcompeting species susceptible to drought and fire.

• Persistent aspen forest—Conifers at higher elevation (mostly not fire resistant) will become less common, 

confined to northern slopes and valley bottoms. Quaking aspen will attain increasing dominance because of its 

ability to sprout vigorously after fire, outcompeting species susceptible to drought and fire. Douglas-fir will persist 

in locations with sufficient soil moisture. Overall productivity will probably decrease.

• Montane pine forest—Ponderosa pine will persist in this forest type because it is drought tolerant and fire 

tolerant, outcompeting other species following wildfire, but will grow more slowly. Limber pine and bristlecone 

pine will probably persist at higher elevations where fuel loads are low. If insect outbreaks are more prevalent in 

a warmer climate, they could increase stress in pine species, especially during drought.

• Riparian forest—This is a highly vulnerable forest type because it depends on a reliable water supply. Vegetation 

dominance may shift to species that are more tolerant of seasonal drought, including ponderosa pine and other 

deep-rooted conifers. Hardwoods could become less common. Riparian forests associated with small or transient 

water sources will be especially vulnerable, especially at lower elevations.

Nonforest

In nonforest ecosystems, increasing frequency and duration of drought are expected to drive direct changes on 

soil moisture, which will reduce the vigor of some species, causing mortality or making (mostly woody species) 

more susceptible to insects and pathogens. Increasing frequency and extent of wildfire will be a major stressor for 

species that regenerate slowly following fire, especially non-sprouting vegetation (e.g., most sagebrush species). 

The dominance of nonnative plant species, especially annual grasses (e.g., cheatgrass), will be enhanced by 

increasing disturbance and will themselves encourage more frequent fire—a significant change in the ecology of most 

vegetation assemblages. Although productivity may increase in some grasslands, most other nonforest ecosystems 

will experience lower productivity. Most native species are expected to persist if they can move to favorable portions 

of the landscape and are sufficiently competitive. Climate change effects on specific nonforest vegetation include:

• Pinyon-juniper shrublands and woodlands—These woodlands are sensitive to chronic low soil moisture during 

prolonged droughts (to which pinyon pines are more sensitive than junipers), increased insect outbreaks that 

follow drought stress, and increased frequency and extent of wildfire. These species will persist across the 

landscape, although the distribution and abundance of species may change.

• Oak-maple woodlands—Gambel oak and bigtooth maple, the dominant species in these woodlands, are widely 

distributed and both sprout heavily following wildfire. As a result, their vulnerability is expected to be relatively 

low, and Gambel oak in particular may become more dominant as wildfire frequency and extent increase across 

the landscape.

• Mountain mahogany woodlands—These woodlands, which are dominated by curl-leaf mountain mahogany, 

are expected to be moderately vulnerable. This species is slow-growing and does not sprout following wildfire, 

so regeneration of disturbed sites may be slow, especially where nonnative species are common. However, 

mountain mahogany is capable of growing on low-fertility soils, so it will continue to be competitive with other 

species.

• Mountain big sagebrush shrublands—Vulnerability varies from moderate to high because of the broad elevation 

range at which mountain big sagebrush occurs, and because of the wide range in current conditions. Livestock 
v

grazing, expansion of pinyon pine and juniper species, altered wildfire regimes, and nonnative invasive species 

are significant stressors. These factors may be exacerbated by a warmer climate, especially in drier habitats.

• Dry big sagebrush shrublands—Vulnerability is high, as evidenced by significant mortality that occurred during 

recent drought. Conditions suitable for seedling establishment are infrequent under current climatic conditions 

and are likely to become less frequent in a warmer climate. Lower elevations of the Great Basin are especially 

vulnerable, whereas sagebrush in wetter locations may be able to persist.

• Sprouting sagebrush shrublands—Warmer, drier climate will negatively affect the vigor and abundance of 

sprouting sagebrush species, which are adapted to more mesic conditions. These species can sprout following 

wildfire, but seed viability is short and unreliability of spring soil moisture will make them susceptible to prolonged 

droughts. Overall vulnerability is moderate, and regeneration will be critical to long-term persistence across the 

landscape.

• Dwarf sagebrush shrublands—All low-growing sagebrush species are likely to be negatively affected by higher 

temperatures and increased periods of drought. Seed viability is short and their dependence on spring soil 

moisture will make them susceptible to prolonged droughts and to altered timing and amount of spring moisture. 

Increased wildfire frequency, coupled with drought, could inhibit regeneration on drier sites.

• Mountain, blackbrush, and salt desert shrublands—These shrublands have low to moderate vulnerability, 

depending on their location relative to soil moisture availability. Many of these shrublands have relatively high 

species diversity—some are well-adapted to periodic drought and some may be able to migrate to higher 

elevations. Salt desert communities at lower elevations may be vulnerable to drought and are intolerant of 

wildfire.

• Alpine communities—The composition and distribution of alpine ecosystems will be affected by decreasing 

snowpack, altering plant vigor and regeneration. Specific effects will depend on vulnerability thresholds of diverse 

species and the rate and magnitude of changes over time. Some species may be able to persist or migrate to 

suitable habitat, but the lower extent of some communities will be compromised by tree establishment. 

• Mountain grasslands—The vulnerability of cool-season grass-dominated communities is moderate to high. 

Warm-season grasses are favored by higher temperatures, providing an opportunity for spread into mountain 

grasslands from lower-elevation and more southern locations. Increased wildfire frequency will facilitate more 

nonnative invasive species, decreasing the dominance and vigor of natives.

• Subalpine forb communities—Higher temperatures and increasing drought make this vegetation type highly 

vulnerable in many locations. Although some subalpine forb communities may be able to move higher in 

elevation, shallow soil profiles may support only lower-growing species. Tall forb communities at the highest 

elevations on plateaus (e.g., Wasatch Plateau) are particularly vulnerable.

• Riparian and wetland communities—Most of these communities are highly vulnerable, especially those at lower 

elevations where soil conditions are already affected by periodic drought. Reduced summer streamflow and 

groundwater will create significant stress for some dominant plant species, although high species diversity in 

many locations ensures some long-term persistence, perhaps with lower functionality.

Adaptation Options

Primary adaptation strategies for forest vegetation focus on promoting disturbance-resilient species, maintaining 

low tree densities, promoting species and genetic diversity, promoting diversity of forest structure, and increasing 

knowledge about climate change effects for agency land managers and stakeholders. Tactics include conducting 

thinning treatments, favoring disturbance-resilient species in thinnings, planting potential microsites with a mixture of 

species, collecting seed for postfire reforestation, and reducing density through prescribed fire and managed wildfire. 

Maintaining and restoring stream channels, and protecting vegetation through appropriate livestock management can 

be applied in riparian areas.

Primary adaptation strategies for nonforest vegetation focus on restoring resilience to and maintaining healthy 

and intact woodlands, shrublands, and grasslands, increasing management actions to prevent invasive species, 
vi

and maintaining and restoring natural habitat. Tactics include using mechanical treatments, prescribed fire, using 

integrated weed management, implementing fuels reduction projects, using ecologically based invasive plant 

management, implementing livestock management that reduces damage to native perennial species, and maintaining 

or improving native plant cover, vigor, and species richness.

Terrestrial Animals

Climate Change Effects

The effects of climate change on terrestrial animal species are expected to be highly variable, depending on habitat 

conditions in specific locations and on the flexibility of animal life histories to accommodate altered conditions. 

Flammulated owl, wolverine, and greater sage-grouse are expected to be the most vulnerable to population declines, 

whereas Utah prairie dog and American three-toed woodpecker will be the least vulnerable. Most species will exhibit 

some sensitivity to altered phenology, habitat, and physiology. Species restricted to high elevations or surface water 

habitats will generally be vulnerable. Following are possible climate change effects on species of conservation 

concern.

• Black rosy finch—An alpine specialist, this species will suffer loss of habitat associated with shrinking snowfields 

and glaciers and possibly encroaching tree establishment, although it does have the capacity to migrate to other 

locations.

• Flammulated owl—Wildfire and insects will increase early-seral forest structure over time, conditions detrimental 

for this species, which prefers mature, open ponderosa pine and other semiarid forests with brushy understories.

• Greater sage-grouse—Degraded habitat caused by wildfire-induced mortality of mature sagebrush, in 

combination with increased dominance of pinyon-juniper woodlands, invasive annual species, and possible 

effects of West Nile virus will be significant challenges to this species.

• White-headed woodpecker—As long as sufficient mature coniferous forest habitat with pines as a seed source 

and dead trees for nesting remain, this species will be relatively resilient to a warmer climate because it can 

move readily to more favorable locations.

• American pika—This species will be vulnerable on isolated mountaintops and at low elevations where it is near 

its physiological tolerance. Populations in the southern Great Basin are the most vulnerable in the IAP region, but 

populations in other locations may be fairly resilient.

• Bighorn sheep—Different parts of the region, and thus different subspecies, will be subject to different population 

dynamics. Populations in the most arid, low-elevation locations and without access to dependable springs and 

forage will be most vulnerable.

• Canada lynx—This species will be vulnerable to reduced snowpack and prey availability (especially snowshoe 

hares), although interactions among climate, wildfire, and insect outbreaks may reduce late-seral forest habitat 

preferred for breeding.

• Fisher—The extent, quality, and connectivity of habitat for this species will probably decrease as increasing 

wildfire reduces late-seral forest habitat, although fishers can readily move from unfavorable to favorable habitat.

• Fringed myotis—This species could undergo some stress if water sources become less common or more 

transient, although its mobility and migratory nature allow it to respond to changing conditions.

• Northern Idaho ground squirrel—Increased vegetative productivity may benefit this species, although loss 

of snowpack, drought, disease, and nonclimatic factors (overgrazing, land development) may be significant 

stressors.
• Sierra Nevada red fox—With populations that are mostly small and isolated, this species may be affected by 

drought, wildfire, and insects that alter vegetation, and especially by reduced snowpack, which promotes higher 

populations of coyotes, a competitor for limited prey.

• Townsend’s big-eared bat—This species uses a variety of habitats, conferring some resilience, although 

increasing wildfires and nonnative grasses could degrade habitats and reduce prey availability. Declining 

snowpack may also reduce the number and duration of water sources.

• Utah prairie dog—This species may be fairly resilient to a warmer climate, although population declines have 

been observed during prolonged periods of drought, which affects food and water availability.

• Wolverine—This species, already low in numbers, could be significantly affected by declining snowpack in its 

preferred high-elevation forest and alpine habitats, and possibly by altered vegetation composition over time.

• Boreal toad—Subject to recent population declines, this species is sensitive to water balance, so altered timing 

and duration of water availability could be stressors. The harmful chytrid fungus may or may not be affected by 

climate change, and trampling of riparian areas by livestock is locally damaging.

• Columbia spotted frog—Historical declines of this species may be exacerbated by alteration and fragmentation 

of aquatic habitats. Drought, warmer temperatures, and reduced snowpack will potentially alter breeding habitat, 

although spotted frogs will probably be resilient in areas with reliable water sources.

• Great Basin spadefoot—This species may be fairly resilient to a warmer climate because it occurs in a variety of 

vegetation types, has a flexible breeding season, and has high reproductive rates. Populations in the southern 

portion of its range and where it relies on ephemeral ponds may be more vulnerable.

• Prairie rattlesnake—This species has low fecundity, long generation times, and low dispersal, making it 

vulnerable to additional climate stresses such as wildfires and flooding. It will probably be more resilient in areas 

with sufficient microhabitats and low habitat fragmentation.

Adaptation Options

Primary adaptation strategies focus on improving riparian habitat through restoration, encouraging healthy beaver 

populations, retaining mature forest structure where possible, reducing nonnative plant species, maintaining quaking 

aspen habitat, and maintaining connectivity of habitat patches across the landscape. Adaptation tactics include 

removing hazardous fuels to reduce wildfire intensities, minimizing impacts from livestock grazing, using prescribed 

fire and conifer removal to promote aspen stands, removing cheatgrass and other invasive species from sagebrush 

systems, and minimizing impacts of recreation on species sensitive to human disturbance.

Outdoor Recreation

Climate Change Effects

Summer recreation (hiking, camping, bicycling) will benefit from a longer period of suitable weather without snow, 

especially during the spring and fall shoulder seasons. Snow-based recreation (downhill skiing, cross-country skiing, 

snowmobiling) will be negatively affected by a warmer climate because of less snow and more transient snowpacks. 

Ski areas and other facilities at lower elevations will be especially vulnerable. Hunting and fishing may be affected 

somewhat by a warmer climate, depending on specific location and activity. Hunting will be sensitive to temperature 

during the allotted hunting season and timing and amount of snow. Fishing will be sensitive to streamflows and 

stream temperatures associated with target species; if summer flows are very low, some streams may be closed 

to fishing. Water-based recreation (swimming, boating, rafting) will be sensitive to lower water levels. Gathering 

forest products for recreational and personal use (e.g., huckleberries, mushrooms) will be somewhat sensitive to the 

climatic conditions that support the distribution and abundance of target species, and to extreme temperatures and 

increased occurrence of extreme events (e.g., flooding, landslides).

vii
Adaptation Options

Recreation participants are highly adaptable to changing conditions, although Federal agencies are not very flexible 

in modifying management. Primary adaptation strategies focus on transitioning management to shorter winter 

recreation seasons, providing sustainable recreation opportunities, increasing management flexibility and facilitating 

transitions to meet user demand and expectations, and managing recreation sites to mitigate risks to public safety 

and infrastructure. Adaptation tactics include collecting data on changing use patterns and demands, maintaining 

current infrastructure and expanding facilities in areas where concentrated use increases, educating the public about 

changing resource conditions, varying the permit season for rafting to adapt to changes in peak flow and duration, 

and determining which recreation sites are at risk from increased hazards.

Infrastructure

Climate Change Effects

Vulnerability of infrastructure can be assessed at three levels: (1) documentation of the type and quantity of 

infrastructure, (2) examination of infrastructure investments at the regional level, and (3) evaluation of infrastructure 

at local or smaller scales. Infrastructure risk can be proactively addressed by identifying assets that have a high 

likelihood of being affected by future climatic conditions and significant consequences if changes do occur. Roads 

and other infrastructure that are near or beyond their design life are at considerable risk to damage from flooding and 

geomorphic disturbance (e.g., debris slides). If road damage increases as expected, it will have a profound impact on 

access to Federal lands and on repair costs. Trails and developed recreation sites may also be sensitive to increased 

flooding and chronic surface flow, especially in floodplains. Buildings and dams represent large investments, and 

some may be at risk to an increased frequency of extreme events (wildfire, flooding).

Adaptation Options

Primary adaptation strategies focus on maintaining an accurate inventory of at-risk infrastructure components (e.g., 

buildings, roads), increasing resilience of the transportation system to increased disturbances (especially flooding), 

and ensuring that design standards are durable under the new conditions imposed by a warmer climate. Adaptation 

tactics include improving roads and drainage systems to survive higher peakflows and more flooding, conducting 

risk assessments of vulnerable roads and infrastructure, decommissioning roads where appropriate, documenting 

seasonal traffic patterns, emphasizing potential increases in extreme storm events when evaluating infrastructure 

inventory, fireproofing of buildings, and coordinating with partners whenever possible.

Cultural Resources

Climate Change Effects

Some aspects of climate change may exacerbate damage and loss of cultural resources, which are threatened by 

natural biophysical factors as well as human behaviors such as vandalism and illegal artifact digging. Increasing 

wildfire, flooding, melting of snowfields, and erosion can quickly displace or destroy artifacts before they have been 

identified and examined, potentially leading to the loss of thousands of items. In addition, large disturbances can 

change the condition of vegetation, streams, and other landscape features valued by Native Americans.

Adaptation Options

Adaptation strategies and tactics to protect cultural resources include improving inventories of the location of cultural 

resources, suppressing wildfires to protect specific sites, implementing fuels treatments in dry forests to reduce 

wildfire intensity, implementing protection strategies (e.g., stabilization, armoring, fireproofing) in areas prone to 

disturbances, monitoring areas affected by flooding and debris flows in mountain canyon and foothill areas, and 

applying vegetation management treatments designed to protect “first food” resources.

Ecosystem Services

Climate Change Effects

Ecosystem services provided to human communities from Federal lands will be affected by climate change in several 

ways:

viii
• Timber and related products and services—Reduced growth rates in primary timber species will have a minimal 

effect on harvestable wood volume, although increased wildfires and insect outbreaks can reduce harvestable 

timber supply. Economic forces and policies will continue to dominate the wood products industry and 

employment, regardless of climate change.

• Grazing forage for domestic livestock and wildlife—Productivity may increase in some rangelands and decrease 

in others, so effects will vary spatially. Increased dominance of nonnative species (e.g., cheatgrass) will reduce 

range quality and support more frequent wildfires. Local erosion and encroaching urbanization will reduce the 

amount of available forage, regardless of climate change.

• Water quantity and quality—Declining snowpack will alter hydrological regimes annually and seasonally. Water 

yield is expected to decrease significantly by the 2040s and considerably more by the 2080s. The most sensitive 

watersheds are those already impaired or at risk, based on vegetation and soil conditions. Water quality may be 

affected by algal blooms and by erosion following wildfires.

• Ecosystem carbon—Ecosystems will increasingly be affected by disturbances (drought, wildfires, insects) that 

will remove living and dead vegetation, and, in turn, reduce carbon sequestration. If fires are as frequent as 

expected, forests may rarely attain a mature stand structure at lower elevations, thus limiting potential carbon 

sequestration.

• Pollination—Altered temperature and precipitation may lead to variable flowering phenology, which could reduce 

pollination by native insects such as bumblebees, and reduce native plant reproduction. Increased drought and 

extreme temperatures may impact pollinators already under stress from insecticides and increased dominance 

by nonnative plants.

Adaptation Options

Adaptation strategies for ecosystem services focus on availability and quality of forage for livestock, availability 

and quality of water, and habitat for pollinators. Adaptation strategies for grazing focus on increasing resilience of 

rangeland vegetation, primarily through nonnative species control and prevention. Adaptation tactics include flexibility 

in timing, duration, and intensity of authorized grazing as a tactic to prevent ecosystem degradation under changing 

conditions, as well as a more collaborative approach to grazing management.

Adaptation strategies for water focus on timing of water availability and quality of water delivered beyond Federal 

lands, assessments of potential climate change effects on municipal water supplies, and identifying potential 

vulnerabilities to help facilitate adaptive actions. Adaptation tactics include reducing hazardous fuels in dry forests 

to reduce the risk of crown fires, reducing other types of disturbances (e.g., off-road vehicles, unregulated livestock 

grazing), and using road management practices that reduce erosion.

Adaptation strategies for pollinators focus on improving pollinator habitat by increasing native vegetation and by 

applying pollinator-friendly best management. Adaptation tactics include establishing a reserve of native seed 

mixes for pollinator-friendly plants, implementing revegetation with plants beneficial to both pollinators and wildlife, 

and creating guidelines that would help managers incorporate pollinator services in planning, project analysis, and 

decisionmaking.

Conclusions

The IAP facilitated the most comprehensive effort on climate change assessment and adaptation in the United States, 

including participants from stakeholder organizations interested in a broad range of resource issues. It achieved 

specific elements of national climate change strategies for the U.S. Forest Service and National Park Service, 

providing a scientific foundation for resource management, planning, and ecological restoration in the IAP region. The 

large number of adaptation strategies and tactics, many of which are a component of current management practice, 

provides a pathway for slowing the rate of deleterious change in resource conditions. Rapid implementation of 

adaptation as a component of sustainable resource management will help to maintain critical structure and function of 

terrestrial and aquatic ecosystems in the IAP region. Long-term monitoring will help to detect potential climate change 

effects on natural resources, and evaluate the effectiveness of adaptation options that have been implemented.

ix
Contents—Part 1

Summary................................................................................................................. unnumbered page i

Water and Soil Resources.................................................................................................................... ii

Fish and Other Aquatic Species........................................................................................................... ii

Vegetation and Ecological Disturbances............................................................................................. iii

Nonforest............................................................................................................................................iv

Terrestrial Animals...............................................................................................................................vi

Outdoor Recreation ...........................................................................................................................vii

Infrastructure.....................................................................................................................................viii

Cultural Resources ............................................................................................................................viii

Ecosystem Services............................................................................................................................viii

Conclusions........................................................................................................................................ix

Chapter 1: Introduction..........................................................................................................1

Joanne J. Ho

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

Climate Change Response in the Forest Service and National Park Service.......................................... 2

The Intermountain Adaptation Partnership Process .............................................................................. 5

Toward an All-Lands Approach to Climate Change Adaptation............................................................ 7

References .......................................................................................................................................... 7

Appendix 1—Author Affiliations.......................................................................................................... 9

Chapter 2: Biogeographic, Cultural, and Historical Setting.............................................12

Hanna K. Olson and Don W. Fallon

Introduction ...................................................................................................................................... 12

Descriptions of Subregions................................................................................................................ 13

Middle Rockies Subregion .................................................................................................................13

Southern Greater Yellowstone Subregion ...........................................................................................16

Uintas and Wasatch Front Subregion .................................................................................................19

Plateaus Subregion ............................................................................................................................21

Great Basin and Semi Desert Subregion.............................................................................................24

Intermountain Semi Desert Subregion................................................................................................27

References ........................................................................................................................................ 29

Chapter 3: Historical and Projected Climate......................................................................32

Linda A. Joyce and Marian Talbert

Introduction ...................................................................................................................................... 32

Assessing Climate Futures for Natural Resource Management............................................................32

Climatic Variability and Change in the Subregions ............................................................................ 37

Historical Climate..............................................................................................................................37

Projected Climate.............................................................................................................................. 40

Summary and Conclusions................................................................................................................ 43

Acknowledgments............................................................................................................................. 43

References ........................................................................................................................................ 56

Appendix 2—Models Included in the Climate Analysis for the Intermountain 

Adaptation Partnership Region ...................................................................................................... 58

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil.........60

Mark J. Muir, Charles H. Luce, Joseph T. Gurrieri, Marek Matyjasik, Jeffrey L. Bruggink, Stacey L. Weems, 

James C. Hurja, David B. Marr, and Sarah D. Leahy

Introduction ...................................................................................................................................... 60

x
Hydrological Processes ..................................................................................................................... 60

Climate and Hydrological Processes..................................................................................................60

Snowpack and Glaciers.....................................................................................................................63

Streamflow ........................................................................................................................................65

Streamflow Projections......................................................................................................................66

Drought.............................................................................................................................................69

Sediment Yield...................................................................................................................................69

Groundwater Resources.................................................................................................................... 69

Hydrogeologic Setting .......................................................................................................................70

Groundwater Systems in the Intermountain Adaptation Partnership Region........................................70

Dependence of Special Habitats on Different Water Sources.............................................................72

Current Resource Conditions.............................................................................................................73

Potential Climate Change Effects on Groundwater and Groundwater-Dependent Ecosystems ............74

Soil Resources................................................................................................................................... 75

Soil Temperature and Moisture...........................................................................................................75

Soil Carbon and Nitrogen ..................................................................................................................76

Soil Biological Activity.......................................................................................................................77

Soil Chemical Properties....................................................................................................................78

Regional-Scale Soil Vulnerability Ratings...........................................................................................78

Summary and Conclusions................................................................................................................ 83

Acknowledgments............................................................................................................................. 84

References ........................................................................................................................................ 84

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species........89

Daniel J. Isaak, Michael K. Young, Cynthia Tait, Daniel Duffield, Dona L. Horan, David E. Nagel, 

and Matthew C. Groce

Introduction ...................................................................................................................................... 89

Analysis Area Network and Stream Climate Scenarios....................................................................... 89

Focal Species Ecology and Climate Vulnerability............................................................................... 92

Rocky Mountain Tailed Frog...............................................................................................................92

Idaho Giant Salamander....................................................................................................................92

Western Pearlshell Mussel .................................................................................................................93

Springsnails .......................................................................................................................................93

Yosemite Toad....................................................................................................................................94

Sierra Nevada Yellow-Legged Frog .....................................................................................................94

Bull Trout...........................................................................................................................................94

Cutthroat Trout...................................................................................................................................96

Climate Vulnerability and Adaptive Capacity of Focal Species ...........................................................96

Climate Refugia for Native Trout........................................................................................................ 98

Trout Distribution Model and Scenarios.............................................................................................98

Cutthroat Trout Status and Projected Trends .......................................................................................99

Bull Trout Status and Projected Trends..............................................................................................100

Conclusions and Implications ......................................................................................................... 101

Climate Adaptation Options............................................................................................................ 105

Acknowledgments........................................................................................................................... 106

References ...................................................................................................................................... 106

Chapter 6: Effects of Climate Change on Forest Vegetation..........................................112

Patrick N. Behrens, Robert E. Keane, David L. Peterson, and Joanne J. Ho

Introduction .................................................................................................................................... 112

Climate Change Assessment Techniques ..........................................................................................112

Forest Vegetation Responses to Climate ........................................................................................... 115

xi
Individual Plant Effects.....................................................................................................................115

Genetics and Species Adaptation.....................................................................................................121

Stressors: Biotic and Abiotic Disturbances .......................................................................................123

Climate Change Assessment for Tree Species................................................................................... 125

Tree Species.....................................................................................................................................125

Climate Change Assessment for Forest Vegetation Types.................................................................. 147

Subalpine Pine Forest ......................................................................................................................147

Subalpine Spruce-Fir Forest..............................................................................................................148

Mesic Mixed Conifer Forest .............................................................................................................148

Dry Mixed Conifer Forest.................................................................................................................148

Aspen-Mixed Conifer Forest.............................................................................................................148

Persistent Aspen Forest.....................................................................................................................149

Montane Pine Forest ........................................................................................................................149

Riparian Forest.................................................................................................................................149

References ...................................................................................................................................... 149

Chapter 7: Effects of Climate Change on Nonforest Vegetation....................................165

Wayne G. Padgett, Matthew C. Reeves, Stanley G. Kitchen, David L. Tart, Jeanne C. Chambers, 

Cheri Howell, Mary E. Manning, and John G. Proctor

Introduction .................................................................................................................................... 165

Vulnerability Assessment Methods................................................................................................... 165

Vulnerability of Nonforest Ecosystems to Climate Change ............................................................... 165

Woodland Ecosystems.....................................................................................................................168

Shrubland Ecosystems .....................................................................................................................173

Alpine Forblands and Grasslands.....................................................................................................182

Riparian and Wetland Communities ................................................................................................186

References ...................................................................................................................................... 190

xii

Figure 1.1—Project area for the Intermountain Adaptation Partnership.
USDA Forest Service RMRS-GTR-375. 2018 1

Chapter 1: Introduction

Joanne J. Ho

Introduction

The Intermountain Adaptation Partnership (IAP) is a 

science-management partnership with a wide variety of 

participants across the U.S. Department of Agriculture 

Forest Service (USFS) Intermountain Region, which 

spans Nevada, Utah, southern Idaho, eastern California, 

and western Wyoming. This USFS region is the largest in 

the Nation, representing nearly 17 percent of all National 

Forest System lands. The partnership includes the USFS 

Intermountain Region and the USFS Pacific Northwest and 

Rocky Mountain Research Stations, National Park Service 

(NPS) Climate Change Response Program, U.S. Fish and 

Wildlife Service, North Central Climate Science Center, the 

Desert, Great Basin, Great Northern, and Southern Rockies 

Landscape Conservation Cooperatives, the University of 

Washington, Native American tribes, and dozens of other 

stakeholder organizations (fig. 1.1, box 1.1). Initiated in 

2015, the IAP is a collaborative project with the goals of 

increasing climate change awareness, assessing vulnerability, and developing science-based adaptation options 

to reduce adverse effects of climate change and ease the 

transition to new climate states and conditions (see http://

adaptationpartners.org/iap). Developed in response to proactive climate change strategies of the USFS (USDA FS 2008, 

Box 1.1—Intermountain Adaptation Partnership Participating Organizations

Backcountry Hunters and Anglers

Boise State University

Bureau of Land Management (BLM)

Colorado State University

Cooperative Institute for Research in Environmental 

Sciences

Deseret News

Desert Landscape Conservation Cooperative

Eastern Idaho Public Health

EcoAdapt

Grand Canyon Trust

Great Basin Landscape Conservation Cooperative

Great Northern Landscape Conservation Cooperative

Henry’s Fork Foundation

Idaho Army National Guard

Idaho Bureau of Homeland Security

Idaho Department of Fish and Game

Idaho National Guard

Idaho Power Company

Institute of Outdoor Recreation and Tourism

Inter-Tribal Council of Nevada

McGinnis and Associates

National Oceanic and Atmospheric Administration

National Park Service

National Weather Service

Natural Resources Conservation Service

Nevada Department of Wildlife

Nez Perce Tribe

North Central Climate Science Center

Northwest Watershed Research Center

Southern Rockies Landscape Conservation Cooperative

Trout Unlimited

U.S. Fish and Wildlife Service

U.S. Forest Service

U.S. Forest Service Intermountain Region

U.S. Forest Service Pacific Northwest and Rocky 

Mountain Research Stations

University of Nevada, Reno

University of Utah

University of Washington

Utah Division of Forestry, Fire and State Lands

Utah State University

Utah’s Hogle Zoo

Weber State University

Western Water Assessment

Wild Utah Project

Yerington Paiute Tribe

Yomba Shoshone Tribe
2 USDA Forest Service RMRS-GTR-375. 2018

Chapter 1: Introduction

2010a,b), and building on previous efforts in national forests 

(Halofsky and Peterson 2017; Halofsky et al. 2011, 2018, in 

press; Littell et al. 2012; Raymond et al. 2013, 2014; Rice 

et al. 2012; Swanston et al. 2011, 2016), the partnership 

brings together resource managers, research scientists, and 

stakeholders to plan for climate change in the Intermountain 

Region.

This effort directly addressed goals identified in the 

USFS Intermountain Region Strategic Framework for FY 

2017–2020 (USDA FS 2016) and the USFS Strategic Plan, 

FY 2015–2020 (USDA FS 2015). These main strategic goals 

are to: (1) sustain our Nation’s forests and grasslands, 

(2) deliver benefits to the public, (3) apply knowledge globally, and (4) excel as a high-performing agency. These goals 

aim the USFS toward success in the agency’s mission “to 

sustain the health, diversity, and productivity of the Nation’s 

forests and grasslands to meet the needs of present and 

future generations.” Finally, this assessment strives to provide options and solutions to a complex challenge in a way 

inspired by Gifford Pinchot, the first Chief of the USFS: for 

“the greatest good of the greatest number in the long run,” 

(USDA FS 2007).

Climate Change Response 

in the Forest Service and 

National Park Service

Climate change is an agency-wide priority for the USFS, 

which has issued direction to administrative units for responding to climate change (USDA FS 2008) (table 1.1). In 

2010, the USFS provided specific direction to the National 

Forest System in the form of the National Roadmap for 

Responding to Climate Change (USDA FS 2010a) and the 

Performance Scorecard for Implementing the USFS Climate 

Change Strategy (USDA FS 2010b). The goal of the USFS 

climate change strategy is to “ensure our national forests 

and private working lands are conserved, restored, and 

made more resilient to climate change, while enhancing our 

water resources,” (USDA FS 2010a, p. 2). To achieve this 

goal, starting in fiscal year (FY) 2011, each national forest 

and grassland began using a 10-point scorecard system to 

report accomplishments on 10 elements in 4 dimensions: (1) 

increasing organizational capacity, (2) partnerships, engagement, and education, (3) adaptation, and (4) mitigation and 

sustainable consumption. The scorecard elements can be 

found in box 1.2. From FY 2011 to FY 2016, progress toward accomplishing elements of the scorecard was required 

to be reported annually by each national forest and national 

grassland. All units were expected to accomplish 7 of 10 

criteria, with at least one “yes” in each dimension, and in FY 

2016, all units in the Intermountain Region were successful 

in this endeavor. As of FY 2017, the USFS is actively developing a new reporting model.

Similarly, the NPS Climate Change Response Strategy 

provides direction for addressing the impacts of climate 

change on NPS lands (NPS 2010) (table 1.2). The strategy has four components to guide NPS actions: science, 

adaptation, mitigation, and communication. The science 

component involves conducting and synthesizing research 

at various scales, monitoring trends and conditions, and 

delivering information to resource managers and partners. It 

also provides the scientific basis for adaptation, mitigation, 

and communication. Adaptation involves developing capacity within the agency to assess climate change scenarios and 

risks and implementing actions to better manage natural and 

cultural resources and infrastructure for a changing climate. 

Mitigation efforts focus on reducing the agency carbon 

footprint and enhancing carbon sequestration. Finally, the 

strategy requires the NPS to take advantage of agency 

capacity for education and interpretation to communicate 

the effects of climate change to NPS employees and to the 

public. Park rangers and other employees are encouraged to 

engage visitors about climate change because national parks 

are visible examples of how climate change can affect natural and cultural resources. The similarity of USFS and NPS 

climate response strategies facilitated coordination between 

the two agencies.

The IAP built on previous Adaptation Partners (www.

adaptationpartners.org) efforts in ecosystem-based management and ecological restoration to address climate change 

and put these efforts in a broader regional context in the 

Intermountain Region. Starting in 2008, Halofsky et al. 

(2011) conducted a climate change assessment for Olympic 

National Forest and Olympic National Park (1.55 million 

acres), a science-management collaboration initiated to 

develop climate adaptation strategies. In 2010, the North 

Cascadia Adaptation Partnership (Raymond et al. 2014) 

began a similar effort with an expanded geographic scope 

of two national forests and two national parks. These 

organizations worked with stakeholders over 2 years to 

identify climate change issues relevant to resource management in the North Cascades to assist in the transition 

of diverse ecosystems of the region to a warmer climate. 

The North Cascadia Adaptation Partnership provided 

education, conducted a climate change vulnerability assessment, and developed adaptation options for the Federal 

agencies that manage nearly 6 million acres in northcentral Washington. In 2013, the USFS Pacific Northwest 

Research Station, Pacific Northwest Region, and Malheur, 

Umatilla, and Wallowa-Whitman National Forests (5.29 

million acres in Oregon and Washington) initiated the 

Blue Mountains Adaptation Partnership (Halofsky and 

Peterson 2017). Formed in 2015, the South Central Oregon 

Adaptation Partnership (Halofsky et al. in press) brought 

together the Deschutes National Forest, Fremont-Winema 

National Forest, Ochoco National Forest, Crooked River 

National Grassland, the USFS Pacific Northwest Region, 

USFS Pacific Northwest and Rocky Mountain Research 

Stations, Crater Lake National Park, and the University of 

Washington to conduct a similar climate change assessment, 

covering 5 million acres. In the largest effort to date in the 

western United States, the Northern Rockies Adaptation 
USDA Forest Service RMRS-GTR-375. 2018 3

Chapter 1: Introduction

Table 1.1—U.S. Forest Service policies related to climate change.

Policy Description

Forest Service Strategic Framework for 

Responding to Climate Change

(USDA FS 2008)

Developed in 2008, the Strategic Framework is based on seven strategic goals 

in three broad categories: foundational, structural, and action. The seven goals 

are science, education, policy, alliances, adaptation, mitigation, and sustainable 

operations.

Like the challenges themselves, the goals are interconnected; actions that achieve 

one goal tend to help meet other goals. The key is to coordinate approaches to each 

goal as complementary parts of a coherent response to climate change. All seven 

goals are ultimately designed to achieve the same end (the USFS mission): to ensure 

that Americans continue to benefit from ecosystem services from national forests and 

grasslands. 

USDA 2010-2015 Strategic Plan

(USDA FS 2010c)

In June 2010, the U.S. Department of Agriculture released the Strategic Plan that 

guides its agencies toward achieving several goals including Strategic Goal 2—

Ensure our national forests and private working lands are conserved, restored, and 

made more resilient to climate change, while enhancing our water resources. This 

goal has several objectives. Objective 2.2 is to lead efforts to mitigate and adapt 

to climate change. The performance measures under this objective seek to reduce 

greenhouse gas emissions by the U.S. agricultural sector, increase the amount of 

carbon sequestered on U.S. lands, and bring all national forests into compliance with 

a climate change adaptation and mitigation strategy. The USFS response to this goal 

includes the National Roadmap for Responding to Climate Change and Performance 

Scorecard (Roadmap).

National Roadmap for Responding to 

Climate Change

(USDA FS 2010a)

Developed in 2011, the Roadmap integrates land management, outreach, and 

sustainable operations accounting. It focuses on three kinds of activities: assessing 

current risks, vulnerabilities, policies, and gaps in knowledge; engaging partners in 

seeking solutions and learning from as well as educating the public and employees 

on climate change issues; and managing for resilience in ecosystems and human 

communities through adaptation, mitigation, and sustainable consumption strategies.

Climate Change Performance 

Scorecard

(USDA FS 2010b)

To implement the Roadmap, starting in 2011, each national forest and grassland 

began using a 10-point scorecard to report accomplishments and plans for 

improvement on 10 questions in four dimensions: organizational capacity, 

engagement, adaptation, and mitigation. By 2015, each is expected to answer 

“yes” to at least seven of the scorecard questions, with at least one “yes” in each 

dimension. The goal is to create a balanced approach to climate change that includes 

managing forests and grasslands to adapt to changing conditions, mitigating climate 

change, building partnerships across boundaries, and preparing employees to 

understand and apply emerging science.

2012 Planning Rule

(USDA FS 2012)

The 2012 Planning Rule is based on a planning framework that will facilitate 

adaptation to changing conditions and improvement in management based on new 

information and monitoring. There are specific requirements for addressing climate 

change in each phase of the planning framework, including in the assessment 

and monitoring phases, and in developing, revising, or amending plans. The 2012 

Planning Rule emphasizes restoring the function, structure, composition, and 

connectivity of ecosystems and watersheds to adapt to the effects of a changing 

climate and other ecosystem drivers and stressors, such as wildfire and insect 

outbreaks. A baseline assessment of carbon stocks required in assessment and 

monitoring will check for measureable changes in the plan area related to climate 

change and other stressors.

Requirements of the Roadmap and Scorecard and requirements of the 2012 Planning 

Rule are mutually supportive and provide a framework for responding to changing 

conditions over time.
4 USDA Forest Service RMRS-GTR-375. 2018

Partnership developed a vulnerability assessment and adaptation options for 15 national forests and 3 national parks in 

Montana, northern Idaho, North Dakota, and parts of South 

Dakota and Wyoming, covering a total of 183 million acres 

(Halofsky et al. 2018). The IAP continues these efforts to 

develop science-based adaptation strategies.

Other efforts have also demonstrated the success of 

science-management partnerships for increasing climate 

change awareness among resource managers and adaptation 

planning on Federal lands. In addition to the Adaptation 

Partners assessments described earlier, Tahoe National 

Forest, Inyo National Forest, and Devils Postpile National 

Monument worked with the USFS Pacific Southwest 

Research Station to develop climate change vulnerability 

assessments (Littell et al. 2012) and the Climate Project 

Screening Tool (Morelli et al. 2012) in order to incorporate 

adaptation into project planning. In response to requests 

from Shoshone National Forest in northern Wyoming, the 

Rocky Mountain Research Station synthesized information 

on past climate, future climate projections, and potential 

effects of climate change on the multiple ecosystems within 

the forest (Rice et al. 2012).

In the largest effort to date in the eastern United States, 

the USFS Northern Research Station, in collaboration 

with Chequamegon-Nicolet National Forest in northern 

Wisconsin and numerous other partners, conducted a 

vulnerability assessment for natural resources (Swanston 

et al. 2011) and developed adaptation options (Swanston 

et al. 2016). Another USFS science-management partnership assessed the vulnerability of watersheds to climate 

change (Furniss et al. 2013). These watershed vulnerability 

assessments, conducted on 11 national forests throughout 

the United States, were locally focused (at a national forest 

scale) and included water resource values, hydrological reaction to climate change, watershed condition, and 

landscape sensitivity. The assessments were intended to help 

national forest managers identify where limited resources 

could be best invested to increase watershed resilience to 

climate change. More recently, Butler et al. (2015) conducted a climate change vulnerability assessment and synthesis 

for forest ecosystems of the Central Appalachians region.

The processes, products, and techniques used for several 

studies and other climate change efforts on national forests 

have been compiled in a guidebook for developing adaptation options for national forests (Peterson et al. 2011). The 

guidebook outlines four key steps to facilitate adaptation in 

national forests: (1) Become aware of basic climate change 

science and integrate that understanding with knowledge of 

local conditions and issues (review), (2) evaluate sensitivity 

of natural resources to climate change (rank), (3) develop 

and implement options for adapting resources to climate 

change (resolve), and (4) monitor the effectiveness of 

Box 1.2—The Forest Service Climate Change Performance Scorecard, 2011

1. Employee Education. Are all employees provided with training on the basics of climate change, impacts on 

forests and grasslands, and the Forest Service response? Are resource specialists made aware of the potential 

contribution of their own work to climate change response?

2. Designated Climate Change Coordinators. Is at least one employee assigned to coordinate climate change 

activities and be a resource for climate change questions and issues? Is this employee provided with the 

training, time, and resources to make his/her assignment successful?

3. Program Guidance. Does the Unit have written guidance for progressively integrating climate change 

considerations and activities into Unit-level operations?

4. Science and Management Partnerships. Does the Unit actively engage with scientists and scientific 

organizations to improve its ability to respond to climate change?

5. Other Partnerships. Have climate change related considerations and activities been incorporated into existing 

or new partnerships (other than science partnerships)?

6. Assessing Vulnerability. Has the Unit engaged in developing relevant information about the vulnerability of key 

resources, such as human communities and ecosystem elements, to the impacts of climate change?

7. Adaptation Actions. Does the Unit conduct management actions that reduce the vulnerability of resources and 

places to climate change?

8. Monitoring. Is monitoring being conducted to track climate change impacts and the effectiveness of adaptation 

activities?

9. Carbon Assessment and Stewardship. Does the Unit have a baseline assessment of carbon stocks and an 

assessment of the influence of disturbance and management activities on these stocks? Is the Unit integrating 

carbon stewardship with the management of other benefits being provided by the Unit?

10. Sustainable Operations. Is progress being made toward achieving sustainable operations requirements to 

reduce the environmental footprint and increase the resilience of agency operations and assets? 

Chapter 1: Introduction
USDA Forest Service RMRS-GTR-375. 2018 5

Table 1.2—National Park Service policies related to climate change.

Policy Description

National Park Service Climate Change 

Response Strategy

(NPS 2010)

Developed in 2010, the Climate Change Response Strategy is designed to guide 

management actions and collaboration, from the national to park levels, to address 

the effects of climate change. The Response Strategy is based on four components: 

science, mitigation, adaptation, and communication. These components provide 

a framework for consistent, legal, and appropriate management decisions. The 

Response Strategy calls for a scientific approach to updating interpretations of 

previous policy and mandates in order to uphold the mission of the NPS in the face 

of new conditions created by climate change.

A Call to Action: Preparing for a 

Second Century of Stewardship and 

Engagement

(NPS 2011)

The Call to Action outlines themes and goals for the second century of stewardship 

and engagement of the NPS. The plan provides actions for the achievement of each 

goal before the NPS centennial in 2016. Under the theme of preserving America’s 

special places, the plan sets the goal for management of resources to increase 

resilience to climate change stressors. Specific actions include revised management 

objectives, increases in sustainability, and changes in investments.

Green Parks Plan

(NPS 2012b)

The Green Parks Plan (GPP) outlines how the NPS will achieve the commitment 

set in A Call to Action, to “Go Green.” An overarching vision and strategy for 

sustainable management in the future, the GPP is based on nine strategic goals that 

focus on the effects of park operations on the environment and human welfare. 

The goals are to continually improve environmental performance; be climate 

friendly and climate ready; be energy smart; be water wise; develop a green NPS 

transportation system, buy green and reduce, reuse, and recycle; preserve outdoor 

values; adopt best practices; and foster sustainability beyond NPS boundaries.

Revisiting Leopold: Resource 

Stewardship in the National Parks

(NPS 2012c)

In August 2012, the NPS released the Revisiting Leopold, intended as an updated 

interpretation of the guiding document, The Leopold Report (Leopold et al. 1963). 

Members of the current NPS Science Committee were tasked with revisiting three 

questions: (1) What should be the goals of resource management in the National 

Parks? (2) Which policies for resource management are necessary to achieve these 

goals? (3) Which actions are required to implement these policies? The interpretation 

presents general principles and guidance for the enlarged scope of all natural and 

cultural resources of the NPS. The committee stresses that the NPS needs to act 

quickly on structural changes and long-term investments in management in order to 

preserve resources through the uncertainties of environmental change. 

Climate Change Action Plan 2012-2014

(NPS 2012a)

The 2012 Climate Change Action Plan builds on the 2010 NPS Climate Change 

Response Strategy to communicate how the NPS can respond to climate change at 

different geographic scales. The plan outlines parameters for introducing science, 

adaptation, mitigation, and communication actions to address climate change. 

The plan also identifies high-priority actions for addressing climate change in NPS 

operations, and describes how to anticipate and prepare for future changes.

on-the-ground management (observe) and adjust as needed. 

The IAP is focused on implementation of the principles and 

practices in the guidebook.

The Intermountain Adaptation 

Partnership Process

The IAP geographic area includes 12 national forests 

(table 1.3) and 22 NPS units across an ecologically and 

geographically complex area. The IAP process includes:

• A vulnerability assessment of the effects of climate 

change on water resources, fisheries, forest and 

nonforest vegetation, disturbance, wildlife, recreation, 

infrastructure, cultural resources, and ecosystem 

services. These resource sectors were selected 

based on their importance in the region and current 

management concerns and challenges.

• Development of adaptation options that will help to

reduce negative effects of climate change and assist 

the transition of biological systems and management 

to a warmer climate.

• Development of an enduring science-management

partnership to facilitate ongoing dialogue and 

activities related to climate change and to other 

natural resource management challenges and actions.

• Vulnerability assessments typically involve 

exposure, sensitivity, and adaptive capacity (Parry et 

al. 2007), where exposure is the degree to which the 

Chapter 1: Introduction
6 USDA Forest Service RMRS-GTR-375. 2018

system is exposed to changes in climate, sensitivity 

is an inherent quality of the system that indicates 

the degree to which it could be affected by climate 

change, and adaptive capacity is the ability of a 

system to respond and adjust to the exogenous 

influence of climate. Vulnerability assessments can 

be both qualitative and quantitative and focus on 

whole systems or individual species or resources 

(Glick et al. 2011). Several tools and databases are 

available for systematically assessing sensitivity 

of species (e.g., Case and Lawler 2016; Luce et al. 

2014; Potter and Crane 2010).

We used scientific literature and expert knowledge to 

assess exposure, sensitivity, and adaptive capacity to identify key vulnerabilities for the selected resource areas. The 

assessment process took place over 2 years and involved 

monthly phone meetings for each of the resource-specific 

assessment teams. Each assessment team refined key questions that the assessment needed to address, chose values 

and key ecosystem attributes to assess, and determined 

which climate change effects models best informed the 

assessment. In some cases, assessment teams conducted 

spatial analyses or ran and interpreted models, selected 

criteria by which to evaluate model outputs, and developed 

maps of model output and resource sensitivities. To the 

greatest extent possible, teams focused on effects and 

projections specific to the region and used the finest scale 

projections that are scientifically valid.

By working collaboratively with scientists and resource 

managers and focusing on a specific region, the goal of 

IAP was to provide the scientific foundation for integrating 

climate change in planning, ecological restoration, and 

project management (Peterson et al. 2011; Raymond et al. 

2013, 2014; Swanston et al. 2016). After identifying key 

vulnerabilities for each resource sector, scientists, land 

managers, and other stakeholders (box 1.1) convened five 

2-day workshops in May and early June 2016 in Ogden, 

Utah (Uinta and Wasatch Front subregion), Boise, Idaho 

(Middle Rockies subregion), Salt Lake City, Utah (Plateaus 

subregion), Reno, Nevada (Great Basin region), and Idaho 

Falls, Idaho (Southern Greater Yellowstone subregion) to 

present and discuss the vulnerability assessment, and to 

elicit adaptation options from resource managers.

During these workshops, scientists and resource specialists presented information on climate change effects and 

current management practices for each of the resources. 

Facilitated dialogue was used to identify key sensitivities 

and adaptation options. Participants identified strategies 

(general approaches) and tactics (on-the-ground actions) 

for adapting resources and management practices to 

climate change, as well as opportunities for implementing 

these adaptation actions in projects, management plans, 

partnerships, and policies. Participants generally focused 

on adaptation options that can be implemented given our 

current scientific understanding of climate change effects, 

but they also identified research and monitoring that would 

benefit future efforts to assess vulnerability and guide 

management practices. Information from the assessment 

was also downscaled to identify the most significant vulnerabilities to climate change for priority resources in each 

subregion where appropriate. Facilitators captured information generated during the workshops with worksheets 

adapted from Swanston et al. (2016). Initial results from 

the workshops were augmented with continued dialogue 

with Federal agency resource specialists.

This publication contains a chapter on expected climatological changes in the IAP region, and one chapter for 

each of the resource sectors covered in the vulnerability 

assessment (water resources, fisheries, forest and nonforest 

vegetation, disturbance, wildlife, recreation, infrastructure, 

cultural resources, and ecosystem services). Each of the 

resource chapters includes a review of climate change effects, sensitivities, and current management practices. An 

additional chapter summarizes adaptation strategies and 

tactics that were compiled at the workshops (see Appendix 

1 for author affiliations).

Resource managers and other decisionmakers can use 

this publication in several ways. First, the vulnerability 

assessment will provide information on climate change effects needed for national forest and national park planning, 

Table 1.3—Area of U.S. Forest Service units in the Forest Service Intermountain Region (from USDA FS 2016). The 

national forests and grassland in the Intermountain Region are organized into 12 administrative units discussed 

throughout this assessment. The Forest Service Rocky Mountain Research Station manages the Desert Range 

Experimental Station. The “Other” category refers to areas located within National Forest System boundaries that are 

not Federally owned or administered by the Forest Service.

Number of units

National Forest 

System Other Total

-----------------------------------------Acres------------------------------------------------

National forest 18 31,784,550 2,330,896 34,115,446

National grassland 1 47,544 27,240 74,784

Research and 

experimental area

1 55,510 0 55,510

 Regional totals 20 31,887,604 2,358,136 34,245,740

Chapter 1: Introduction
USDA Forest Service RMRS-GTR-375. 2018 7

projects, conservation strategies, restoration, monitoring, 

and environmental effects analyses. Second, climate 

change sensitivities and adaptation options developed at 

the broad scale provide the scientific foundation for finer 

scale assessments, adaptation planning, and resource monitoring. We expect that over time, and as needs and funding 

align, appropriate adaptation options will be incorporated 

into plans and programs of Federal management units. 

Third, we anticipate that resource specialists will apply 

this assessment to incorporate climate-smart resource 

management and planning in land management throughout 

the region.

Adaptation planning is an ongoing and iterative process. 

Implementation may occur at critical times in the planning 

process, such as when managers revise USFS land management plans and other planning documents, or after the 

occurrence of extreme events and ecological disturbances 

(e.g., wildfire). We focus on adaptation options for the USFS 

and NPS, but information in this publication can be used 

by other land management agencies as well. Just as the IAP 

process has been adapted from previous vulnerability assessments and adaptation planning, it can be further adapted 

by other national forests and organizations, thus propagating 

climate-smart management across larger landscapes.

Toward an All-Lands Approach 

to Climate Change Adaptation

The USFS and NPS climate change strategies identify 

the need to build partnerships and work across jurisdictional boundaries when planning for adaptation. This concept 

of responding to the challenge of climate change with an 

“all-lands” approach is frequently mentioned, but a process 

for doing so is rarely defined. In addition to representatives 

from the USFS and NPS, several other agencies and organizations participated in the resource sector workshops. 

This type of partnership enables a coordinated and complementary approach to adaptation that crosses jurisdictional 

boundaries. The IAP also provides a venue for agencies to 

learn from the practices of others so that the most effective 

adaptation strategies can be identified.

Risks and vulnerabilities resulting from climate change 

and gaps in scientific knowledge and policy need to be 

assessed on a continual basis. Adaptation is a prominent 

focus of the IAP, with emphasis on creating resilience 

in human and natural systems. Communicating climate 

change information and engaging employees, partners, and 

the public in productive discussions is also an integral part 

of successfully responding to climate change. The need for 

partnerships and collaborations on climate change issues 

was clearly identified in the IAP. Sharing climate change 

information, vulnerability assessments, and adaptation 

strategies across administrative boundaries will contribute 

to the success of climate change responses throughout the 

Intermountain West.

References

Butler, P.R.; Iverson, L.; Thompson, F.R., III; [et al.]. 2015. Central 

Appalachians forest ecosystem vulnerability assessment and 

synthesis: A report from the Central Appalachians Climate 

Change Response Framework project. Gen. Tech. Rep. NRS146. Newtown Square, PA: U.S. Department of Agriculture, 

Forest Service, Northern Research Station.

Case, M.J.; Lawler, J.J. 2016. Relative vulnerability to climate 

change of trees in western North America. Climatic Change. 

136: 367–379.

Furniss, M.J.; Roby, K.B.; Cenderelli, D.; [et al.]. 2013. Assessing 

the vulnerability of watersheds to climate change: Results of 

national forest watershed vulnerability pilot assessments. Gen. 

Tech. Rep. PNW-GTR-884. Portland, OR: U.S. Department 

of Agriculture, Forest Service, Pacific Northwest Research 

Station. 32 p.

Glick, P.; Stein, B.A.; Edelson, N.A., eds. 2011. Scanning the 

conservation horizon: A guide to climate change vulnerability 

assessment. Washington, DC: National Wildlife Federation. 5 p.

Halofsky, J.E.; Peterson, D.L., eds. 2017. Climate change 

vulnerability and adaptation in the Blue Mountains. Gen. 

Tech. Rep. PNW-GTR-939. Portland, OR: U.S. Department 

of Agriculture, Forest Service, Pacific Northwest Research 

Station. 331 p.

Halofsky, J.E.; Peterson, D.L.; Dante-Wood, S.K.; [et al.]. 2018. 

Climate change vulnerability and adaptation in the Northern 

Rocky Mountains. Gen. Tech. Rep. RMRS-GTR-374. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station.

Halofsky, J.E.; Peterson, D.L.; Ho, J.J., eds. In press. Vulnerability 

of natural resources to climate change in the South Central 

Oregon region. PNW-GTR-XXX. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific Northwest 

Research Station.

Halofsky, J.E.; Peterson, D.L.; O’Halloran, K.A.; Hoffman, C.H. 

2011. Adapting to climate change at Olympic National Forest 

and Olympic National Park. Gen. Tech. Rep. PNW-GTR-844. 

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

Pacific Northwest Research Station. 130 p.

Leopold, A.S.; Cain, S.A.; Cottam, C.M.; Gabrielson, I.N.; 

Kimball, T.L. 1963. Wildlife management in the National 

Parks: The Leopold Report. Washington, DC: U.S. National 

Park Service. 14 p.

Littell, J.S.; Peterson, D.L.; Millar, C.I.; O’Halloran, K.A. 2012. 

U.S. national forests adapt to climate change through sciencemanagement partnerships. Climatic Change. 110: 269–296.

Luce, C.; Lopez-Burgos, V.; Holden, Z. 2014. Sensitivity of 

snowpack storage to precipitation and temperature using spatial 

and temporal analog models. Water Resources Research. 50: 

9447–9462.

Morelli, T.L.; Yeh, S.; Smith, N.M.; [et al.]. 2012. Climate project 

screening tool: An aid for climate change adaptation. Res. Pap. 

PSW-RP-263. Albany, CA: U.S. Department of Agriculture, 

Forest Service, Pacific Southwest Research Station.

National Park Service [NPS]. 2010. National Park Service climate 

change response strategy. Fort Collins, CO: National Park 

Service Climate Change Response Program.

Chapter 1: Introduction
8 USDA Forest Service RMRS-GTR-375. 2018

National Park Service [NPS]. 2011. A call to action: Preparing for 

a second century of stewardship and engagement. http://www.

nps.gov/calltoaction/PDF/Directors_Call_to_Action_Report.pdf 

[Accessed February 9, 2017].

National Park Service [NPS]. 2012a. Climate Change Action Plan. 

2012–2014. National Park Service Climate Change Response 

Program, Fort Collins, Colorado. 36 p. http://www.nps.gov/

orgs/ccrp/upload/NPS_CCActionPlan.pdf. (21 July 2015).

National Park Service [NPS]. 2012b. Green parks plan. 15 p. http://

www.nps.gov/greenparksplan/downloads/NPS_2012_Green_

Parks_Plan.pdf [Accessed February 9, 2017].

National Park Service [NPS]. 2012c. Revisiting Leopold: Resource 

stewardship in the National Parks. National Park System 

Advisory Board Science Committee. 18 p. http://www.nps.gov/

calltoaction/PDF/LeopoldReport_2012.pdf [Accessed February 

9, 2017].

Parry, M.L.; Canzianai, O.F.; Palutikof, J.P.; [et al.], eds. 2007. 

Climate change 2007: Impacts, adaptation and vulnerability: A 

contribution of working group II to the fourth assessment report 

of the Intergovernmental Panel on Climate Change. Cambridge, 

United Kingdom: Cambridge University Press. 976 p.

Peterson, D.L.; Millar, C.I.; Joyce, L.A.; [et al.]. 2011. Responding 

to climate change in national forests: A guidebook for 

developing adaptation options. Gen. Tech. Rep. PNWGTR-855. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 109 p.

Potter, K.M.; Crane, B.S. 2010. Forest tree genetic risk assessment 

system: A tool for conservation decision-making in changing 

times. Version 1.2. Asheville, NC: U.S. Department of 

Agriculture, Forest Service, Eastern Forest Environmental 

Threat Assessment Center. http://www.forestthreats.org/currentprojects/project-summaries/genetic-risk-assessment-system 

[Accessed February 9, 2017].

Raymond, C.L.; Peterson, D.L.; Rochefort, R.M. 2013. The North 

Cascadia Adaptation Partnership: A science-management 

collaboration for responding to climate change. Sustainability. 

5: 136–159.

Raymond, C.L.; Peterson, D.L.; Rochefort, R.M., eds. 2014. 

Climate change vulnerability and adaptation in the North 

Cascades region, Washington. Gen. Tech. Rep. PNW-GTR-892. 

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

Pacific Northwest Research Station. 279 p.

Rice, J.; Tredennick, A.; Joyce, L.A. 2012. Climate change on 

the Shoshone National Forest, Wyoming: A synthesis of past 

climate, climate projections, and ecosystem implications. 

Gen. Tech. Rep. RMRS-GTR-264. Fort Collins, CO; U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station. 60 p.

Swanston, C.W.; Janowiak, M.K.; Brandt, L.A.; [et al.], eds. 

2016. Forest Adaptation Resources: Climate change tools and 

approaches for land managers, 2nd edition. Gen. Tech. Rep. 

NRS-GTR-87-2. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station. 161 p.

Swanston, C.; Janowiak, M.; Iverson, L.; [et al.]. 2011. Ecosystem 

vulnerability assessment and synthesis: A report from the 

Climate Change Response Framework project in northern 

Wisconsin. Gen. Tech. Rep. NRS-82. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, Northern 

Research Station. 142 p.

U.S. Department of Agriculture, Forest Service [USDA FS]. 2007. 

The greatest good: A Forest Service centennial film. https://

www.fs.fed.us/greatestgood/press/mediakit/facts/pinchot.shtml# 

[Accessed June 26, 2017].

U.S. Department of Agriculture, Forest Service [USDA FS]. 2008. 

Forest Service strategic framework for responding to climate 

change. Version 1.0. Washington, DC: U.S. Department of 

Agriculture, Forest Service, Climate Change Advisor’s Office. 

http://www.fs.fed.us/climatechange/documents/strategicframework-climate-change-1-0.pdf [Accessed February 9, 

2017].

U.S. Department of Agriculture, Forest Service [USDA FS]. 

2010a. National roadmap for responding to climate change. 

Washington, DC: U.S. Department of Agriculture, Forest 

Service, Climate Change Advisor’s Office. http://www.fs.fed.

us/climatechange/pdf/roadmap.pdf [Accessed June 6, 2015].

U.S. Department of Agriculture, Forest Service [USDA FS]. 

2010b. A performance scorecard for implementing the Forest 

Service climate change strategy. Washington, DC: U.S. 

Department of Agriculture, Forest Service, Climate Change 

Advisor’s Office. http://www.fs.fed.us/climatechange/pdf/

performance_scorecard_final.pdf [Accessed February 9, 2017].

U.S. Department of Agriculture, Forest Service [USDA FS]. 

2010c. Strategic plan 2010–2015 FY. Washington, DC: U.S. 

Department of Agriculture, Forest Service. http://www.ocfo.

usda.gov/usdasp/sp2010/sp2010.pdf [Accessed February 9, 

2017].

U.S. Department of Agriculture, Forest Service [USDA FS]. 

2012. 2012 planning rule. Washington, DC: U.S. Department 

of Agriculture, Forest Service. Federal Register. 77(68). 115 

p. http://www.fs.usda.gov/Internet/FSE_DOCUMENTS/

stelprdb5362536.pdf [Accessed February 9, 2017].

U.S Department of Agriculture, Forest Service [USDA FS]. 

2015. USDA Forest Service Strategic Plan: FY 2015–2020. 

Washington, DC: U.S. Department of Agriculture, Forest 

Service. 53 p. https://www.fs.fed.us/sites/default/files/

strategic-plan%5B2%5D-6_17_15_revised.pdf?utm_

medium=email&utm_source=govdelivery [Accessed June 26, 

2017].

U.S. Department of Agriculture, Forest Service [USDA FS]. 

2016. USDA Forest Service Intermountain Region Strategic 

Framework: FY 2017-2020. Washington, D.C.: U.S. 

Department of Agriculture, Forest Service. 18 p. https://www.

fs.usda.gov/Internet/FSE_DOCUMENTS/fseprd530247.

pdf?utm_medium=email&utm_source=govdelivery [Accessed 

June 26, 2017].

Chapter 1: Introduction
USDA Forest Service RMRS-GTR-375. 2018 9

Chapter 1

Joanne J. Ho is a Research Environmental Economist 

with the University of Washington, College of the 

Environment, School of Environmental and Forest 

Sciences in Seattle, Washington.

Chapter 2

Hanna K. Olson is an undergraduate student at the 

University of Washington in Seattle, Washington.

Don W. Fallon is the Regional Resource Information and 

Monitoring Coordinator with the U.S. Department of 

Agriculture, Forest Service, Intermountain Region in 

Ogden, Utah.

Chapter 3

Linda A. Joyce is a Research Ecologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station, Human Dimensions 

Research Program in Fort Collins, Colorado.

Marian Talbert is a Biostatistician with the U.S. 

Department of the Interior, North Central Climate 

Science Center in Fort Collins, Colorado.

Chapter 4

Mark J. Muir is a Hydrologist with the U.S. Department 

of Agriculture, Forest Service, Intermountain Region in 

Ogden, Utah.

Charles H. Luce is a Research Hydrologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Boise, Idaho.

Joseph T. Gurrieri is a Hydrogeologist with the U.S. 

Department of Agriculture, Forest Service, National 

Forest System in Golden, Colorado.

Marek Matyjasik is an Advisor in Applied Environmental 

Geosciences with Weber State University, College of 

Science in Ogden, Utah.

Jeffrey L. Bruggink is the Regional Soil Scientist with 

the U.S. Department of Agriculture, Forest Service, 

Intermountain Region in Ogden, Utah.

Stacey L. Weems is a Soil Scientist with the U.S. 

Department of Agriculture, Forest Service, WasatchCache National Forest in South Jordan, Utah.

James C. Hurja is a Soil Scientist with the U.S. 

Department of Agriculture, Forest Service, HumboldtToiyabe National Forest and Spring Mountains National 

Recreation Area in Sparks, Nevada.

David B. Marr is a Forest Soil Scientist and Soil and 

Air Program Manager with the U.S. Department of 

Agriculture, Forest Service, Caribou-Targhee National 

Forest in Idaho Falls, Idaho.

Sarah D. Leahy is a Forest Soil Scientist with the U.S. 

Department of Agriculture, Forest Service, Ashley 

National Forest in Vernal, Utah.

Chapter 5

Daniel J. Isaak is a Research Fish Biologist with the 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Boise, Idaho.

Michael K. Young is a Research Fisheries Biologist with 

the U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station in Missoula, Montana.

Cynthia Tait is the Regional Aquatic Ecologist with 

the U.S. Department of Agriculture, Forest Service, 

Intermountain Region in Ogden, Utah.

Daniel Duffield is a Fisheries Program Manager with 

the U.S. Department of Agriculture, Forest Service, 

Intermountain Region in Ogden, Utah.

Dona L. Horan is a Fisheries Biologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Boise, Idaho.

David E. Nagel is a Geographic Information Systems (GIS) 

Analyst with the U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station in Boise, 

Idaho.

Matthew C. Groce is a GIS Analyst with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Boise, Idaho.

Chapter 6

Patrick N. Behrens is a Silviculturist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Robert E. Keane is a Research Ecologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station, Missoula Fire Sciences 

Laboratory in Missoula, Montana.

David L. Peterson was a Senior Research Biologist 

Scientist with the U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station in Seattle, 

Washington.

Joanne J. Ho is a Research Environmental Economist 

with the University of Washington, College of the 

Environment, School of Environmental and Forest 

Sciences in Seattle, Washington.

Chapter 7

Wayne G. Padgett is a retired Ecologist, formerly with 

the U.S. Department of Agriculture, Forest Service, 

Washington Office in Washington, DC.

Matthew C. Reeves is a Research Ecologist with the 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Missoula, Montana.

Appendix 1—Author Affiliations

Chapter 1: Introduction
10 USDA Forest Service RMRS-GTR-375. 2018

Stanley G. Kitchen is a Research Botanist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Provo, Utah.

David L. Tart is a Regional Ecologist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Jeanne C. Chambers is a Research Ecologist with the 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Reno, Nevada.

Cheri Howell is an Ecologist with the U.S. Department of 

Agriculture, Forest Service, Humboldt-Toiyabe National 

Forest in Sparks, Nevada.

Mary E. Manning is a Regional Vegetation Ecologist with 

the U.S. Department of Agriculture, Forest Service, 

Northern Region in Missoula, Montana.

John G. Proctor is a Regional Botanist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Chapter 8

Danielle M. Malesky is an Entomologist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Barbara J. Bentz is a Research Entomologist with the 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Logan, Utah.

Gary R. Brown is a Regional Fire Specialist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Andrea R. Brunelle is a Professor with the University of 

Utah, Department of Geography in Salt Lake City, Utah.

John M. Buffington is a Research Geomorphologist with 

the U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station in Boise, Idaho.

Linda M. Chappell is a Fire Ecologist with the U.S. 

Department of Agriculture, Forest Service, Dixie and 

Fishlake National Forests in Richfield, Utah.

R. Justin DeRose is a Research Ecologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Ogden, Utah.

John C. Guyon, II, is a Plant Pathologist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Carl L. Jorgensen is an Entomologist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Rachel A. Loehman is a Research Landscape Ecologist, 

U.S. Geological Survey, Alaska Science Center in 

Anchorage, Alaska.

Laura L. Lowrey is a Forest Entomologist with the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Ann M. Lynch is a Research Entomologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Tucson, Arizona.

Marek Matyjasik is an Advisor in Applied Environmental 

Geosciences with Weber State University, College of 

Science in Ogden, Utah.

Joel D. McMillin is a Supervisory Entomologist with 

the U.S. Department of Agriculture, Forest Service, 

Intermountain Region in Ogden, Utah.

Javier E. Mercado is an Entomologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Fort Collins, Colorado.

Jesse L. Morris is a Research Assistant Professor with the 

University of Utah, Department of Geography in Salt 

Lake City, Utah.

Jose F. Negrón is a Research Entomologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Fort Collins, Colorado.

Wayne G. Padgett is a retired Ecologist, formerly with 

the U.S. Department of Agriculture, Forest Service, 

Washington Office in Washington, DC.

Robert A. Progar is a Research Entomologist with the 

U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station in La Grande, Oregon.

Carol B. Randall is a Forest Entomologist with the U.S. 

Department of Agriculture, Forest Service, Northern 

Region in Boise, Idaho.

Chapter 9

Megan M. Friggens is a Research Ecologist with the 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Albuquerque, New 

Mexico.

Mary I. Williams is a Postdoctoral Researcher with the 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Boise, Idaho.

Karen E. Bagne is a Wildlife Biologist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Albuquerque, New 

Mexico.

Tosha T. Wixom is a Regional Sustainability and Climate 

Intern with the U.S. Department of Agriculture, Forest 

Service, Intermountain Region in Ogden, Utah.

Samuel A. Cushman is a Research Landscape Ecologist 

with the U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station in Flagstaff, Arizona.

Chapter 10

Michael S. Hand is a Research Economist with the U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station in Missoula, Montana.

Jordan W. Smith is the Director of the Institute of Outdoor 

Recreation and Tourism and an Assistant Professor with 

Utah State University, College of Natural Resources, 

Department of Environment and Society in Logan, Utah.

David L. Peterson was a Senior Research Biologist 

Scientist with the U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station in Seattle, 

Washington.

Chapter 1: Introduction
USDA Forest Service RMRS-GTR-375. 2018 11

Nancy A. Brunswick is a Regional Landscape Architect 

with the U.S. Department of Agriculture, Intermountain 

Region in Ogden, Utah.

Carol P. Brown is the Forest Environmental Coordinator 

with the U.S. Department of Agriculture, Sawtooth 

National Forest in Twin Falls, Idaho.

Chapter 11

Michael J. Furniss is a retired Hydrologist, formerly with 

the U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station, Redwood Sciences 

Lab in Arcata, California.

Natalie J. Little is the Regional Sustainability and Climate 

Coordinator with the U.S. Department of Agriculture, 

Intermountain Region in Ogden, Utah.

David L. Peterson was a Senior Research Biologist 

Scientist with the U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station in Seattle, 

Washington.

Chapter 12

Tom H. Flanigan is an Archaeologist with the U.S. 

Department of Agriculture, Forest Service, WasatchCache National Forest in South Jordan, Utah.

Charmaine Thompson is the Heritage Program Leader 

with the U.S. Department of Agriculture, Forest Service, 

Uinta National Forest in Provo, Utah.

William G. Reed is the Regional Heritage Program Leader 

with the U.S. Department of Agriculture, Intermountain 

Region in Ogden, Utah.

Chapter 13

Travis W. Warziniack is a Research Economist with the 

U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station Human Dimensions Research 

Program in Fort Collins, Colorado.

Matthew J. Elmer is a graduate student at Colorado 

State University in Fort Collins, Colorado, where he is 

currently working on his Ph.D. in economics.

Chris J. Miller is an Economist with the U.S. Department 

of Agriculture, Forest Service, Washington Office 

Ecosystem Management Coordination in Ogden, Utah.

S. Karen Dante-Wood is a Natural Resource Specialist 

with the U.S. Department of Agriculture, Forest Service, 

Office of Sustainability and Climate in Washington, DC.

Christopher W. Woodall is a Project Leader for the U.S. 

Department of Agriculture, Forest Service, Northern 

Research Station in Durham, New Hampshire.

Michael C. Nichols is a Computer Systems Analyst for the 

U.S. Department of Agriculture, Forest Service, Northern 

Research Station in Durham, New Hampshire.

Grant M. Domke is a Team Leader and Research Forester 

for the U.S. Department of Agriculture, Forest Service, 

Northern Research Station in St. Paul, Minnesota.

Keith D. Stockmann is an Economist with the U.S. 

Department of Agriculture, Forest Service, Missoula 

Technology and Development Center in Missoula, 

Montana.

John G. Proctor is the Regional Botanist for the U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region in Ogden, Utah.

Allison M. Borchers is an Economist with the U.S. 

Department of Agriculture, Forest Service, Washington 

Office Enterprise Program, TEAMS in Washington, DC.

Chapter 14

Jessica E. Halofsky is a Research Ecologist with the 

University of Washington, College of the Environment, 

School of Environmental and Forest Sciences in Seattle, 

Washington.

Chapter 15

Joanne J. Ho is a Research Environmental Economist 

with the University of Washington, College of the 

Environment, School of Environmental and Forest 

Sciences in Seattle, Washington.

David L. Peterson was a Senior Research Biologist 

Scientist with the U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station in Seattle, 

Washington.

Natalie J. Little is the Regional Sustainability and Climate 

Coordinator with the U.S. Department of Agriculture, 

Intermountain Region in Ogden, Utah.

Chapter 1: Introduction
12 USDA Forest Service RMRS-GTR-375. 2018

Introduction

The Intermountain Adaptation Partnership (IAP) 

encompasses unique landscapes within the Intermountain 

Region of the U.S. Forest Service (USFS), from rugged 

mountains to deep canyons, from alpine snowfields to 

wild and scenic rivers (fig. 1.1). The area defined by the 

boundaries of the Intermountain Region contains both 

private and Federally owned lands, including 12 national 

forests and 22 national parks. Before Euro-Americans 

settled this area, Native American tribes occupied the land 

for thousands of years. With Euro-American settlement 

came timber extraction, mining, grazing, water extraction, 

and increased recreation to the region. Urban growth has 

increased significantly during recent decades, bringing new 

Chapter 2: Biogeographic, Cultural, and 

Historical Setting

Hanna K. Olson and Don W. Fallon

businesses and development that affect socioeconomic and 

natural environments.

Climate, biogeography, natural resource conditions, 

and management issues differ considerably from Idaho to 

Nevada, and from western Wyoming to the southern border 

of Utah. To capture how these differences influence potential climate change effects and adaptation strategies, the 

IAP region was divided into six subregions that are detailed 

in this assessment: the Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch Front, Plateaus Great 

Basin and Semi Desert, and Intermountain Semi Desert subregions (fig. 1.1, table 2.1). The Intermountain Semi Desert 

contains no national forests, but is identified as a discrete 

area that may be of interest to those outside the USFS. Each 

subregion is briefly characterized in the next section.

National forest Subregions

Number of 

subregions in a 

national forest

Ashley Uintas and Wasatch Front, Plateaus 2

Boise Middle Rockies 1

Bridger-Teton Southern Greater Yellowstone 1

Caribou-Targhee Middle Rockies, Southern Greater Yellowstone, Uintas and Wasatch Front 3

Dixie Plateaus, Great Basin and Semi Desert 2

Fishlake Plateaus, Great Basin and Semi Desert 2

Humboldt-Toiyabe Great Basin and Semi Desert 1

Manti-La Sal Uintas and Wasatch Front, Plateaus 2

Payette Middle Rockies 1

Salmon-Challis Middle Rockies 1

Sawtooth Middle Rockies, Uintas and Wasatch Front 2

Uinta-Wasatch-Cache Uintas and Wasatch Front, Plateaus, Great Basin and Semi Desert 3

Subregion National forest

Number of 

national forests 

in a subregion

Middle Rockies Boise, Caribou-Targhee, Payette, Salmon-Challis, Sawtooth 5

Southern Greater Yellowstone Bridger-Teton, Caribou-Targhee 2

Uintas and Wasatch Front Ashley, Caribou-Targhee, Manti-La Sal, Uinta-Wasatch-Cache, Sawtooth 5

Plateaus Ashley, Dixie, Fishlake, Manti-La Sal, Uinta-Wasatch-Cache 5

Great Basin and Semi Desert Dixie, Fishlake, Humboldt-Toiyabe, Uinta-Wasatch-Cache 4

Intermountain Semi Desert None 0

Table 2.1—Subregions within national forests and national forests within subregions of the Intermountain Adaptation Partnership 

region.
USDA Forest Service RMRS-GTR-375. 2018 13

Figure 2.1—National 

forests within the 

Middle Rockies 

subregion of the 

Intermountain 

Adaptation 

Partnership region.

Descriptions of Subregions

Middle Rockies Subregion

The Middle Rockies subregion is part of the Rocky 

Mountains and extends over 16 million acres of central 

Idaho (fig. 2.1). The subregion is characterized by rugged 

mountain ranges and intermontane valleys vegetated with 

coniferous forests, as well as sagebrush-steppe ecosystems 

in the lower elevations, particularly in the southern and eastern portions (fig. 2.2). The subregion includes the Payette, 

Salmon-Challis, Boise, and Sawtooth National Forests, and 

a small portion of the Caribou-Targhee National Forest. 

This area is bordered by the Centennial Mountains near 

the Montana-Idaho border, the Lemhi Mountains along the 

Continental Divide of the western Montana-Idaho border, 

the northeastern Beaverhead Mountains, and the Salmon 

River Mountains in the northern section of the subregion. 

The area extends southward to the Intermountain Semi 

Desert subregion, which is dominated by geographic features associated with the Snake River Plains volcanic fields. 

Designated wilderness areas encompass almost 1.5 million 

acres of this subregion.

Geologically, the area is relatively young with emplacement of Cretaceous igneous intrusions (batholiths) roughly 

120 million years BP, and younger Columbia basalts on the 

western boundary. During the Pleistocene (roughly 10,000 

to 130,000 years BP), mountain glaciers carved and gouged 

the bedrock while depositing glacial till and associated river 

deposits in the intermontane valleys. The modern mountain 

ranges are characterized by high elevation ridges and 

deeply incised river valleys, such as those associated with 

the Salmon River in the Frank Church River of No Return 

Wilderness (Demarchi 1994).

Numerous rivers run through the Middle Rockies subregion. The Salmon River, flowing westward and spanning 

Chapter 2: Biogeographic, Cultural, and Historical Setting
14 USDA Forest Service RMRS-GTR-375. 2018

Figure 2.2—Rugged mountain 

topography in the 

Salmon-Challis National 

Forest. Subalpine forest 

and montane shrubs 

characterize the higher 

elevations (photo: U.S. 

Forest Service).

Chapter 2: Biogeographic, Cultural, and Historical Setting

425 mi, divides northern Idaho from the remainder of the 

State. Major subbasins include the Little Salmon River, the 

Lemhi River, and the Big and Little Lost Rivers in eastcentral Idaho. Dry land farming occurs in valleys within the 

southeastern portion of central Idaho. The 1,000-mile-long 

Snake River enters the eastern edge of the subregion and 

is joined by the Salmon River near Riggins, Idaho, where 

river incision has created Hells Canyon, the deepest river 

gorge in North America. High flows of the merged rivers 

exceed those of the Colorado River (Idaho Department of 

Health and Welfare 1999). In the northwestern portion of 

the Middle Rockies subregion, the Boise River and Payette 

River are major tributaries of the Snake River. The Payette 

River leads to the popular recreation areas of Lake Cascade 

and Lake Payette. The Lemhi River is fed by the Bitterroot 

Range and the Big Lost River Range, and is a critical 

spawning habitat for Federally protected steelhead trout 

(Oncorhynchus mykiss) and Chinook salmon (Oncorhynchus 

tshawytscha) (Idaho Department of Health and Welfare 

1999). The Big Lost River and the Little Lost River Range 

are named for their disappearance underground as they leave 

their valleys and flow into the Intermountain Semi Desert 

subregion.

Climate varies along a gradient between the western 

and eastern areas of central Idaho. Maritime atmospheric 

patterns are prevalent near the northwestern border of the 

subregion, delivering high precipitation that allows coniferous forests to thrive. Toward the southeastern border, the 

climate creates an arid environment that supports sagebrush 

and grassland ecosystems at lower elevations. Eastern Idaho 

experiences large temperature variation during the year, and 

precipitation differs considerably from the western portions 

of the subregion, with monsoonal summer moisture and 

snowier winters. The abrupt elevation gradients associated 

with the steep mountain ranges of central Idaho creates 

an orographic (rain-shadow) effect in which condensed 

moisture is deposited on the western or windward mountain 

slopes, and reduced moisture falls on leeward valley sides of 

the mountains.

Mixed conifer and subalpine forests are the dominant vegetation in the Middle Rockies. Heavily forested areas are most 

common in the northern portion of the subregion, progressing 

to more arid lowlands in the southeast. Dominant species 

include Douglas-fir (Pseudotsuga menziesii), ponderosa pine 

(Pinus ponderosa), lodgepole pine (Pinus contorta var. latifolia), grand fir (Abies grandis), subalpine fir (A. lasiocarpa), 

Engelmann spruce (Picea engelmannii), and quaking aspen 

(Populus tremuloides) (Brown and Chojnacky 1991). Of 

these species, Douglas-fir, ponderosa pine, lodgepole pine, 

grand fir, subalpine fir, and Engelmann spruce are commercially harvested (USDA FS 2016). Since 1952, ponderosa 

pine cover has decreased by 40 percent because of its high 

timber value (O’Laughlin et al. 1993). Conifer species with 

high ecological value but no commercial value include whitebark pine (Pinus albicaulis Engelm.), limber pine (P. flexilis), 

alpine larch (Larix lyallii), and western juniper (Juniperus 

occidentalis) (Brown and Chojnacky 1991).

Among the abundant shrub species are serviceberry 

(Amelanchier alnifolia), Rocky Mountain maple (Acer glabrum), tall Oregon-grape (Berberis aquifolium), snowbrush 

ceanothus (Ceanothus velutinus), and multiple species of 

sagebrush (Artemisia spp.) (Pyke et al. 2015; Robson and 
USDA Forest Service RMRS-GTR-375. 2018 15

Kingery 2006). Idaho fescue (Festuca idahoensis) and bluebunch wheatgrass (Pseudoroegneria spicata) are common 

grassland species. Conservation of rare plant species in the 

subregion is an important management responsibility (Tilley 

et al. 2013).

Over 300 animal species live in the Middle Rockies. Large 

mammals include Canada lynx (Lynx canadensis), grizzly 

bear (Ursus arctos), elk (Cervus elaphus), gray wolf (Canis 

lupus), bighorn sheep (Ovis canadensis), and moose (Alces 

alces). Smaller vertebrates include American beaver (Castor 

canadensis), American pika (Ochotona princeps), snowshoe 

hare (Lepus americanus), yellow-bellied marmot (Marmota 

flaviventris), and Rocky Mountain tailed frog (Ascaphus 

montanus) (Link et al. 2000). The Middle Rockies are home 

to over 400 bird species, including bald eagle (Haliaeetus 

leucocephalus), golden eagle (Aquila chrysaetos), osprey 

(Pandion haliaetus), multiple owl species, trumpeter swan 

(Cygnus buccinator), greater sage-grouse (Centrocercus 

urophasianus), and white-headed woodpecker (Picoides 

albolarvatus).

Fish rearing and spawning sites of both native and nonnative fish species are common in the rivers, lakes, and ponds 

of the Middle Rockies. Steelhead trout, cutthroat trout (O. 

clarkii), and bull trout (Salvelinus confluentus) are sensitive 

species found throughout the subregion. Nonnative lake 

trout (S. namaycush) and brook trout (S. fontinalis) were 

introduced into Idaho’s lakes and streams during the 1900s 

and continue to thrive (Dillon and Grunder 2008). Since the 

1880s, dams and reservoirs have altered water flows and decreased water quality in some rivers, leading to declines in the 

white sturgeon (Acipenser transmontanus) population (Dillon 

and Grunder 2008).

Before the 1900s, wildfires in the Middle Rockies 

subregion maintained grasslands and open forests in lower 

elevation and drier portions of the landscape. Historical 

fire frequencies were 10 to 20 years for ponderosa pine and 

dry Douglas-fir forests in Boise National Forest (Crane and 

Fischer 1986). In recent decades, grand fir and Douglas-fir 

have increased in ponderosa pine stands in response to 

decreased fire frequency. The resulting dense, multistoried 

stands are more susceptible to crown fires, insects, and fungal 

pathogens. Sagebrush communities generally have lower 

wildfire frequencies, but are increasingly affected by cheatgrass (Bromus tectorum) and other nonnative species. These 

annual species create fine fuels that facilitate more frequent 

fire, mostly to the detriment of native species.

Lodgepole pine, whitebark pine, and limber pine have 

undergone high mortality from mountain pine beetle 

(Dendroctonus ponderosae) outbreaks in much of central 

Idaho. A warmer climate has encouraged higher reproductive 

rates in the beetles and allowed them to survive at higher 

elevations (Gibson et al. 2008). Western spruce budworm 

(Choristoneura occidentalis) attacks Douglas-fir, grand fir, 

and pine, causing mortality and low vigor in host stands 

(Fellin and Dewey 1982). Balsam woolly adelgid (Adelges 

piceae) causes subalpine fir mortality and lower growth in 

grand fir (Lowrey 2015).

Forest diseases are especially prominent in conifer forests 

in the Middle Rockies. The nonnative fungus white pine blister rust (Cronartium ribicola) has caused extensive mortality 

in western white pine (Pinus monticola), whitebark pine, and 

limber pine (Cairns 2015). The formerly abundant western 

white pine has been mostly replaced by Douglas-fir and 

grand fir, driving forest succession toward more susceptible 

stand composition. Although efforts to eradicate blister rust 

have been unsuccessful, decades of natural selection have 

increased rust resistance in remnant western white pines, 

providing a foundation for regeneration of this species in 

the future (Schwandt et al. 2013). Parasitic dwarf mistletoe 

(Arceuthobium spp.) is also fairly common in coniferous 

forests. The spread rate of mistletoe has accelerated in dense, 

multistoried Douglas-fir stands because of the abundance of 

susceptible hosts and ease of mistletoe dispersal and regeneration. Long-term effects include growth reduction of the host 

and reduced forest productivity (Giunta et al. 2016).

No Native American communities or reservations reside 

within the Middle Rockies, although portions of national 

forests are traditional use areas. Historically, riverbanks in 

the Salmon-Challis National Forest provided fishing and 

foraging grounds for the Sheepeater Indians, the Nez Perce 

Tribe, and the Flathead Tribe. After the Lewis and Clark expedition during the early 19th century, assistance from Indian 

tribes opened the way for fur trappers, explorers, miners, 

ranchers, and settlers to populate what is now Lemhi County. 

Previously, the Whitebird band of the Nez Perce Tribe occupied portions of Payette National Forest, and utilized summer 

hunting and fishing grounds along the Little Salmon River. 

Other bands camped along the Little Salmon and Salmon 

Rivers as a primary source for salmon throughout the harvesting season. A wide variety of plant species provided materials 

for food and construction (Reddy 1993). In the mid-1800s, 

the Federal Government gained control of the land in Idaho, 

restricting the Nez Perce to the northwestern part of the State.

Resource-dependent economic activities in the Middle 

Rockies include livestock grazing, logging, recreation, and 

tourism. The gold rush of the mid-19th century brought 

settlers to the mountainous areas of the IAP region. The 

initial boom quickly died out, leaving only ghost towns to 

mark the once-promising gold and copper mines. Several 

mineral exploration projects are still operating and more have 

been recently proposed. Between the 1860s and 1870s, the 

livestock industry grew within the South Boise, Atlanta, and 

Deadwood mining districts (Jones 1990). After the gold rush, 

summer grazing activity extended beyond the outskirts of 

mining towns, and became established along the Boise and 

Payette river valleys (Jones 1990). The economic viability 

of livestock grazing has declined in recent decades, although 

large areas of national forest and other Federal lands still have 

grazing allotments. Exposure of bighorn sheep to cattle-borne 

diseases is a concern for wildlife managers, and programs are 

aimed at renewing the viability of bighorn sheep populations 

on Federal lands (USDA FS 2011).

Timber operations came to the IAP region during 

the “great buying rush” between 1899 and 1908. These 

Chapter 2: Biogeographic, Cultural, and Historical Setting
16 USDA Forest Service RMRS-GTR-375. 2018

operations supported the expanding railroad system with 

railroad ties, as well as traditional building products. By 1902, 

the Payette Lumber and Manufacturing Company had been 

established, with ponderosa pine as the main commodity. 

The company continued to expand throughout the early 20th

century, resulting in more sawmills, higher lumber production, and a growing economy. However, timber production 

has declined significantly in the past 30 years. Counties south 

of the Salmon River currently contribute up to 11 percent of 

Idaho’s overall timber harvest and 45 percent of the State’s 

timber exports. Valley County provides the largest annual 

timber harvest in the State: 65 million board feet (Brandt et al. 

2012).

Travel and tourism support a significant portion of the 

subregional economy. A study conducted in the Sawtooth 

National Recreation Area found that 77 percent of visitors traveled to the forest for recreational purposes such as 

viewing natural features, hiking, and driving for pleasure 

(Headwaters Economics 2014). In 2012, 6.5 million visitors 

to Idaho national forests (including outside the subregion) 

spent over $300 million on recreation activities.

Southern Greater Yellowstone Subregion

The Southern Greater Yellowstone subregion covers 

6.5 million acres of eastern Idaho, and western Wyoming 

(fig. 2.3). Bridger-Teton National Forest and CaribouTarghee National Forests are the only national forests in this 

subregion. The Bridger-Teton spans the eastern portion of 

the Idaho-Wyoming border from Jackson Hole, Wyoming, 

eastward toward west-central Wyoming and contains 3.4 

million acres of watersheds and wildlands. Approximately 

2 million acres of wilderness land, as well as Grand Teton 

National Park, are contained within the subregion. There are 

several designated wilderness areas located on USFS lands 

in the subregion, including the Teton Wilderness and Wind 

Figure 2.3—National 

forests and national 

parks within the 

Southern Greater 

Yellowstone 

subregion of the 

Intermountain 

Adaptation 

Partnership region.

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 17

River Range Wilderness in Wyoming, and two smaller wildernesses in Idaho: the Jedediah Smith Wilderness, known 

for karst limestone formations and caves, and the Wineger 

Hole Wilderness, which was set aside to protect grizzly bear 

habitat.

Physiography of this area reflects a wide variety of 

geologic mountain-building events. The subregion is part 

of the Greater Yellowstone Area, which extends south 

from the Centennial Mountains and Yellowstone National 

Park, through Grand Teton National Park, and southward 

to include the Wind River Range and Wyoming Range in 

Wyoming. The Centennial Mountains are a result of uplift 

and faulting that form steep, high-relief mountain ranges 

with sharp alpine ridges and cirques at high elevation. 

Faulting in the Centennial Mountains is fairly recent, and 

young faults are also present along the western border of 

Wyoming in the Teton Range, where active block faulting continues today. In the southeastern portions of the 

subregion, deformation and faulting produced the Wind 

River Range, with over 2,500 lakes in alpine and piedmont 

settings. Intermontane valleys include alluvial terraces and 

floodplains on the valley floor, and glacial till and moraines 

along the mountain flanks. The Wyoming Range, Caribou 

Range, and other smaller mountains of southeastern Idaho 

and western Wyoming were formed from low-angle thrust 

faulting associated with overthrust belt mountain building. 

Some smaller areas of volcanic activity produced lava flows 

and basalt in southeastern Idaho. The volcanic hotspot that 

underlies present-day Yellowstone National Park created 

volcanic tuff and tephra deposits in the Absaroka Range, and 

giant volcanic craters in the Island Park area. Glaciers covered most mountain ranges at times during the Pleistocene, 

carrying till and debris from the mouths of drainages to produce moraines that were dissected and buried by subsequent 

erosion and sedimentation from rivers and streams.

As elevation increases in the Southern Greater 

Yellowstone subregion, average temperatures decrease, 

and annual precipitation increases (Knight et al. 2014). 

Mountain ecosystems tend to be cool and moist, although 

mountain slopes facing south may experience dry environments similar to lower elevations. Direct solar radiation and 

increased rates of evaporation allow higher elevations to 

support more arid vegetation, such as mountain big sagebrush (Artemisia tridentata ssp. vaseyana) and grassland 

species (Knight et al. 2014). Alpine ecosystems are found 

on the uppermost ridges and peaks, dominated by alpine 

vegetation and stunted conifers. Subalpine ecosystems are 

typically coniferous forests with wildflower meadows, 

lush wetlands, and arid shrublands along mountain flanks 

(fig. 2.4). Overall, the steep and rugged topography of the 

mountain ranges provides conditions with 60 to 80 inches of 

annual precipitation in higher elevations and as little as 15 

inches of precipitation at lower elevations. This translates to 

heavy snowfall at high elevations throughout the subregion, 

with prevailing winds dispersing snow accumulations on 

exposed ridges and slopes.

The largest river system in the subregion is the Snake 

River, including the North, South, and Henry’s forks. 

This system drains to the Columbia River through the 

Intermountain Semi Desert subregion. To the southeast, 

the Green River, Sandy River, and Newfork River drain 

southward to the Colorado River system and the Pacific 

Ocean, while a small area in the northeastern portion of the 

subregion drains to the Gulf of Mexico. Smaller rivers, such 

as the Greys River, Blackfoot River, Portneuf River, and 

Hoback River, emanate from surrounding mountains and 

join the larger rivers in the valleys. Numerous reservoirs 

and piedmont lakes are located along the river network, 

including Island Park Reservoir in eastern Idaho, Palisades 

Reservoir near the Idaho-Wyoming border, and several lakes 

at the base of the Wind River Range.

Vegetation in the Southern Greater Yellowstone subregion varies from high-elevation alpine grasslands and 

shrublands, through vast coniferous subalpine forests, to 

sagebrush shrublands and agricultural lands at the lowest 

Figure 2.4—Complex mountain topography, alpine meadows, 

and dense coniferous forests, typical of the Southern 

Greater Yellowstone subregion of the Intermountain 

Adaptation Partnership region (photo: U.S. Forest Service).

Chapter 2: Biogeographic, Cultural, and Historical Setting
18 USDA Forest Service RMRS-GTR-375. 2018

elevations. At the uppermost elevations, high precipitation 

(mostly as snow), short growing seasons, and cold temperatures create a harsh environment where only stunted trees 

and hardy plants survive. Middle elevations are dominated 

by coniferous forests, typically Douglas-fir, lodgepole 

pine, Engelmann spruce, and subalpine fir. These forests 

were historically logged to provide railroad ties for the 

expanding railroad system to the south. Low elevations are 

dominated by several species of sagebrush. These areas are 

used as rangelands for small communities in the winter, 

as cold weather moves livestock to their lower elevation 

winter ranges (Blackwell and Reese 2001). In some cases, 

hay from surrounding agricultural areas is delivered to 

feed grounds in winter to reduce wildlife mortality. Stands 

of quaking aspen are found throughout middle elevations, 

providing important habitat for wildlife and subalpine 

herbaceous species.

Wildfire plays an important role in maintaining the biodiversity of terrestrial ecosystems. Since the big northern 

Idaho wildfires in 1910, fire suppression has been implemented to protect urban communities and other resources 

(Caribou-Targhee National Forest 2005). As a result, many 

conifer forests are relatively mature, in some locations 

blending with aspen woodlands, riparian zones, mountain 

meadows, and sagebrush-grassland habitats. Biodiversity 

in these ecosystems has decreased, promoting highseverity fires, loss of habitat for bighorn sheep and greater 

sage-grouse, and western balsam bark beetle (Dryocoetes 

confusus) outbreaks in subalpine fir. Prescribed fire has 

been implemented in some locations to reduce fuels, improve wildlife habitat, and increase habitat heterogeneity 

(Caribou-Targhee National Forest 2005).

White pine blister rust and mountain pine beetle have 

reduced whitebark pine populations near the northern 

border of the subregion. Whitebark pine provides forage 

for grizzly bear and black bear (Ursus americanus) during 

the winter. Mountain pine beetle has affected lodgepole 

pine populations, causing increased mortality throughout 

the Intermountain West. Douglas-fir and Engelmann spruce 

stands have suffered stunted growth and mortality from the 

spread of western spruce budworm.

About 100 species of mammals live within the subregion. Common rangeland and forest species include black 

bear, Rocky Mountain elk (Cervus canadensis), moose, 

mule deer (Odocoileus hemionus), pronghorn (Antilocapra 

americana), and bighorn sheep. Areas near Yellowstone 

National Park provide protection for grizzly bear and gray 

wolf. Small vertebrates include American pika, American 

beaver, wolverine (Gulo gulo), and numerous amphibians. 

Grassland ecosystems support large areas for livestock 

grazing. The National Elk Refuge was established in 1912 

to provide feed, sanctuary, and habitat for one of the largest elk herds on Earth. In early fall, elk migrate from the 

surrounding uplands down to Jackson Hole, where hay 

from the surrounding communities is used as forage for the 

surviving elk.

Over 350 avian species reside within the subregion. 

Riparian and forest habitats provide nesting sites for bald 

eagle, golden eagle, peregrine falcon (Falco peregrinus), 

and other raptors. Greater sage-grouse occupies sagebrushgrassland ecosystems, and is a high-priority species for 

conservation. Trumpeter swan, sandhill crane (Grus 

canadensis), Canada geese (Branta canadensis), and many 

species of ducks are common in the wetlands of BridgerTeton National Forest.

World-class fishing is supported along all rivers in the 

Southern Greater Yellowstone subregion. Cutthroat trout 

and mountain whitefish (Prosopium williamsoni) are indigenous species, whereas brook trout, brown trout (Salmo 

trutta), lake trout, and golden trout (Oncorhynchus mykiss 

aguabonita) have been introduced in many lakes throughout 

the river system.

Beginning around 11,000 years BP, bands of Shoshone, 

Blackfoot, and Bannock Indians occupied western portions 

of the subregion (State of Wyoming 2013). Farther east, nomadic hunters and gatherers migrated throughout the valleys 

and mountains of the Wind River and Absaroka Ranges. 

At the beginning of the 19th century, trappers and explorers 

began to frequent western Wyoming and started trading with 

the Indian tribes of the area. Over time, Native American 

tribes were confined to smaller portions of the subregion.

After the Lewis and Clark expedition, John Colter 

traversed the Continental Divide and descended into 

Jackson Hole during the winter of 1807–1808 (State of 

Wyoming 2013). Other settlers soon followed, establishing 

trading posts along the Wind River, Gros Ventre, Teton, 

and Wyoming Ranges. Wyoming became the focus for 

Governmental expeditions, fur trapping, and hunting for 

the next 30 years. Independent trappers began to appear 

in the Jackson Hole Valley, changing the socioeconomic 

trajectory of the area. With increasing settlement of western 

Wyoming, forest reserves were established to protect water, 

wood, wildlife, recreation, and forage. These reserves would 

eventually become the Caribou-Targhee and Bridger-Teton 

National Forests. The Civilian Conservation Corps contributed to an increase in national forest infrastructure and 

expansion of the timber industry. Timber has remained an 

important component of local economies, although the volume of harvests has decreased greatly in the past 30 years. 

Thinning is now used to reduce stand densities and improve 

wildlife habitat.

The gold rush of 1870, when gold was found near 

Caribou Mountain, sparked a 20-year run of gold mining 

in eastern Idaho and western Wyoming, after which mining 

of phosphate deposits for fertilizers was conducted in the 

Caribou-Targhee National Forest for 50 years. Recently, 

exploration for oil and gas reserves has been conducted 

along the southern portion of the subregion, mostly in the 

surrounding basins.

Tourism is a vital industry in the area, with Jackson Hole 

serving as a major entrance for millions of visitors each year 

to Grand Teton and Yellowstone National Parks. The Grand 

Targhee and Jackson Hole resorts attract skiers from around 

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 19

the world. Other activities, such as camping, hunting, and 

fishing, are popular summer activities for visitors to the 

subregion.

Uintas and Wasatch Front Subregion

The northern portion of the Uintas and Wasatch Front 

subregion includes the Albion, Black Pine, Raft River, and 

Sublett Mountains along the Idaho-Utah border. Sagebrush 

and grasslands dominate the low to middle elevations that 

surround islands of higher elevation coniferous forests. 

Farther south, the rugged Wasatch Front is the western 

border of the subregion, with high ridges and an abrupt 

transition from high desert to alpine ecosystems (fig. 2.5). 

National forests in the subregion are the Uinta-WasatchCache National Forest, Ashley National Forest, and southern 

portions of the Sawtooth and Caribou-Targhee National 

Forests (fig. 2.6). Over 600,000 acres are dedicated to wilderness, including the Wellsville Mountain Wilderness. The 

Curlew National Grassland encompasses over 47,000 acres.

The complex topography of the subregion has resulted 

from millions of years of mountain building, sedimentation, 

and erosion. Warm, shallow water once covered the area of 

the Wasatch and Uinta Mountains, depositing thick layers 

of fossil-bearing gray sediment. Once compression of the 

North American Plate began, thrust faulting and buckling 

on the eastern half of the Wasatch Front created highly 

deformed mountain ranges that shed sediment into the lower 

valleys to create the sandstone and limestone valleys of 

the present day (Atwood 2012). Local and regional uplift 

brought the landscape to its current position, allowing rivers 

and glaciers to carve steep slopes and deposit high volumes 

of sediment within the surrounding basins and ranges. The 

Wasatch fault displays faulting along the base of the steep 

Wasatch Front where fault scarps have displaced beach deposits of ancient Lake Bonneville. This lake was the larger 

precursor to the present-day Great Salt Lake, forming from 

meltwaters during warming periods of the Pleistocene.

Near the southeastern corner of the subregion, the 

Green River flows into Flaming Gorge Reservoir, continuing southeastward and emerging near Vernal, Utah. 

Numerous tributaries that run through the Ashley and 

Uinta-Wasatch-Cache National Forests provide water for 

critical watersheds, including Strawberry Reservoir, where 

diversions and tunnels carry the water from the Uinta Basin 

and the Colorado River drainage to the Wasatch Front for 

agricultural and municipal use.

The northern portion of the subregion has hot summers with little precipitation and winters that receive high 

amounts of precipitation at higher elevations, but less at 

lower elevations. The southern portion experiences both 

dry summer and wet winter patterns, as well as wet summer 

and dry winter patterns (Shaw and Long 2007). The western 

portion of the subregion has average summer temperatures 

above 90 °F and average winter temperatures below 20 °F. 

The eastern portion typically experiences wet summers 

and dry winters, with annual precipitation as low as 7 to 10 

inches at lower elevations.

Coniferous forests are prominent in the southern portions of the subregion, especially in the Wasatch and Uinta 

Mountains. Scattered patches of coniferous forests occur 

along the middle to high slopes of the northern mountain 

ranges, which are surrounded by sage-steppe ecosystems in 

valleys. Dominant conifer species, including subalpine fir, 

Engelmann spruce, lodegepole pine, and Douglas-fir, account for a large proportion of the forest types (Heyerdahl et 

Figure 2.5—U-shaped valleys, rugged mountain ranges, scattered alpine lakes, and dense coniferous forests, which are common 

in the Uintas and Wasatch Front subregion of the Intermountain Adaptation Partnership region (photo: U.S. Forest Service).

Chapter 2: Biogeographic, Cultural, and Historical Setting
20 USDA Forest Service RMRS-GTR-375. 2018

al. 2011). Utah juniper (Juniperus osteosperma) and pinyon 

pine (Pinus edulis) occupy arid, shallow, and rocky soils at 

lower elevation. Lower elevations also provide habitat for 

Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) and mountain big sagebrush, as well as bluebunch 

wheatgrass, bottlebrush squirreltail (Elymus elymoides), 

Sandberg bluegrass (Poa sandbergii), and Thurber’s needlegrass (Achnatherum thurberuanum). These shrub-steppe 

systems provide habitat for small fauna, ungulates, and local 

populations of greater sage-grouse.

Wildfire regimes influence the overall health and biodiversity of all ecosystems, with most fires occurring during 

July through October (Morris 2006). Fire exclusion in the 

Wasatch Range and Uinta Mountains has mixed conifer 

forests that are relatively mature and dense with high fuel 

loadings, making them susceptible to crown fire. Low-vigor 

stands in Uinta-Wasatch-Cache National Forest provide 

suitable conditions for bark beetle outbreaks, such as the 

outbreak in 1980 when beetle populations were extremely 

high and conditions for beetle survival were optimum 

(Shaw and Long 2007). These forests have been subject to 

outbreaks by mountain pine beetle and other beetle species 

during the past 15 years.

Moose are common in wetlands of most intermontane 

valleys. Mountainous topography provides habitat for elk, 

black bear, bighorn sheep, mule deer, and small populations of mountain goats (Oreamnos americanus). Sensitive 

species within the Albion Range include mountain lion 

(Felis concolor) and Canada lynx. Small vertebrates include 

lizards, rattlesnakes, sagebrush vole (Lemmiscus curtatus), 

and muskrat (Ondatra zibethicus).

Rivers, streams, creeks, and reservoirs throughout the 

Uintas and Wasatch Front subregion support both native 

and nonnative fish. Colorado River cutthroat trout (O. 

clarkii pleuriticus) is native to the Green River watershed, 

and the Bonneville cutthroat trout (O. c. utah) is native to 

Figure 2.6—National 

forests within the 

Uintas and Wasatch 

Front subregion of 

the Intermountain 

Adaptation 

Partnership region.

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 21

other drainages. These species attract anglers from around 

the world for recreational fishing. Nonnative fish include 

numerous trout and bass species, kokanee salmon (O. 

nerka), walleye (Sander vitreus), and yellow perch (Perca 

flavescens).

Numerous avian species inhabit various ecosystems of 

the subregion. Olive-sided flycatcher (Contopus cooperi), 

chipping sparrow (Spizella passerina), and chickadees 

(Poecile spp.) are common in subalpine forests. Raptors, 

including red-tailed hawk (Buteo jamaicensis), golden 

eagle, and bald eagle, populate low rangelands that border 

the mountains. Along the Wasatch Front, hermit thrush 

(Catharus guttatus), fox sparrow (Passerella iliaca), 

mountain bluebird (Sialia currucoides), and sandhill crane 

are common near small reservoirs and streams. In the Uinta 

Mountains, alpine habitat is occupied by pine grosbeak 

(Pinicola enucleator), three-toed woodpecker (Picoides 

dorsalis), and gray jay (Perisoreus canadensis). Many species of shorebirds and waterfowl populate reservoirs across 

the subregion.

Native American tribes once lived throughout the area. 

In 1500, the Northern Utes occupied central Utah, western 

Colorado, southern Wyoming, and northern New Mexico. 

Utah Valley with its abundant supply of fish and other natural resources supported most of the population (Simmons 

2000). With the acquisition of horses in 1600, the Utes were 

able to extend their range and travel to the Great Plains to 

hunt American bison (Bison bison). The Uintah and Ouray 

Indian Reservation is now home to the Ute Tribe and is situated south of the Ashley National Forest.

Agriculture accounts for a large portion of the economy. 

The animal industry is the single largest sector of farm 

income in Utah. River valleys and cultivated fields provide 

fertile soils for the production of hay, corn, barley, and a 

variety of fruit. Orchards of apples, apricots, and peaches 

are scattered throughout the subregion and concentrated 

along the Wasatch Front. In the southeastern portion of 

the subregion, melons and other fruits provide economic 

benefits to smaller communities. Specialty products such as 

soap and honey also contribute agricultural income in some 

communities.

Watersheds throughout the subregion are an important 

source of water for municipal, industrial, and recreational 

use, and for hydroelectric power. Flaming Gorge National 

Recreation Area, Strawberry Reservoir, and other smaller 

reservoirs provide these water resources, as well as popular 

destinations for recreation. Watershed and groundwater 

management are a component of resource management for 

urban populations along the Wasatch Front; water supplies 

are decreasing with increasing urban populations, making 

water conservation a significant concern. The Bear River, 

Jordan River, Weber River, and Ogden River are sources 

for this water, relying on dams and diversions to create 

power and allocate water resources. Regulations restricting 

construction, wastewater, and livestock operations help 

ensure adequate water supplies and water quality, although 

overdraft has occurred in aquifers in northern Utah since 

1985 (Burden 2015).

Mining projects have been proposed throughout the 

subregion, including sites that are focused on hard rock such 

as gold or copper mining, and soft rock such as phosphate 

mining. Drilling for oil and gas has expanded, including 

proposed drilling of up to 400 new wells over a 20-year 

period in the Vernal Basin area. About 50 active oil and 

gas wells are currently in national forest lands within the 

subregion. Coal mining is a major industry, with coal fields 

scattered throughout the subregion. Tourism continues to 

provide economic stimulus to many mountainous areas 

along the Wasatch Front. Several world-class ski resorts 

such as Snowbird, Alta, and Park City serve local and international enthusiasts. Snowbasin and Park City hosted the 

2002 Olympic Games.

Plateaus Subregion

The Plateaus subregion covers the southern half of Utah 

and a small portion of western Colorado, including Ashley, 

Manti-La Sal, Fishlake, and Uinta-Wasatch-Cache, Dixie 

National Forests, as well as Zion, Bryce Canyon, Capitol 

Reef, Arches, and Canyonlands National Parks (fig. 2.7). 

Rugged mountain landscapes contrast with the red-rock 

desert of Utah badlands, where millions of years of erosion 

have carved steep canyons and intricate rock formations 

through the sandstone and carbonate composition of the 

Colorado Plateau. About 150,000 acres are devoted to 

wilderness. Mountain ranges, plateaus, cliffs, and canyons 

characterize the rugged landscape (fig. 2.8), providing recreational and economic benefits for surrounding communities.

In the northwestern portion of the Plateaus subregion, 

Manti-La Sal National Forest contains the La Sal, Manti, 

North Horn, and Abajo Mountains. Rugged topography, alpine meadows, and forests cover these north-south trending 

ranges. The Tushar Mountain Range in Fishlake National 

Forest provides the basin for Fish Lake, which is a popular 

location for summer activities. Dixie National Forest contains white cliffs, red canyons, and several mountain peaks 

covered by dense forests and desert shrublands. Sedimentary 

rocks are pronounced at Cedar Breaks National Monument 

and at adjacent national parks, Glenwood Canyon National 

Recreation Area, and Grand Staircase-Escalante National 

Monument.

The major river network in the Plateaus subregion 

belongs to the Green and Colorado River system. Major 

tributaries flow through the surrounding lowlands and empty 

into Lake Powell. The Dirty Devil, Virgin, and San Juan 

Rivers are smaller tributaries that are locally important. 

The north-to-south running Green River joins the Colorado 

River in Canyonlands National Park. The Colorado River 

then flows to the southwest, carving steep cliffs through 

sandstone bedrock and continuing into Arizona. Glen 

Canyon National Recreation Area contains the second largest reservoir in the United States, providing hydroelectric 

power, water resources, and recreation. The westerly 

Chapter 2: Biogeographic, Cultural, and Historical Setting
22 USDA Forest Service RMRS-GTR-375. 2018

Figure 2.7—National 

forests and national 

parks within the 

Plateaus subregion 

of the Intermountain 

Adaptation Partnership 

region.

Figure 2.8—A red-rock 

landscape in the 

Plateaus subregion 

of the Intermountain 

Adaptation Partnership 

region. Steep cliffs line 

canyons that have been 

powerfully eroded 

throughout geologic 

history (photo: U.S. 

Forest Service).

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 23

flowing San Juan River begins in southwestern Colorado, 

flowing southeast until it meets the Colorado River near the 

mouth of Glen Canyon.

The Colorado Plateau is the dominant physiographic 

feature of this area, characterized by isolated buttes, mesas, 

plateaus, steep escarpments and cliffs, and gently folded 

sedimentary rocks. Several small mountain ranges such as 

the La Sal Mountains and Henry Mountains provide higher 

elevations from the surrounding lowlands, supplying water 

to the tributaries. Millions of years of evaporate deposition, folding, wind and water erosion, and salt deformation 

formed the diverse landscape. Between 70 and 265 million 

years BP, a shallow marine depositional environment covered the Colorado Plateau, forming limestone, sandstone, 

shales, marine fossils, and salt deposits (Harris et al. 1997).

Erosion processes, such as by wind and rivers, shaped 

the bedrock and topography of this area. Stream incisions 

dissect this relatively flat area through down-cutting and 

headward erosion processes. Melting of Pleistocene glaciers 

provided large volumes of water to be carried throughout 

the Colorado River network, and incised drainages. As 

uplift continued, river incision further carved deep canyons 

throughout the flat landscape, creating landmarks that can 

be observed today (Harris et al. 1997). Strong winds have 

eroded the smooth arches and other geologic formations 

in Arches National Park and Natural Bridges National 

Monument (Harris et al. 1997).

Dominant ecosystems of the Plateaus subregion include 

coniferous and deciduous forests at higher elevations, and 

woodlands, mountain shrub communities, sagebrush shrublands, grasslands, and desert ecosystems at lower elevations. 

Other more isolated ecosystems are also important including 

riparian wetlands, and unique niches within the associated 

canyons, cliffs, and talus slopes. High mountain ranges 

support subalpine ecosystems of coniferous and deciduous 

forests throughout the western portion of the subregion and 

in the La Sal and Henry Mountains. Coniferous forests of 

ponderosa pine, Douglas-fir, white fir (Abies concolor), 

Engelmann spruce, and limber pine occupy mid- to upper 

slopes. Mountain shrub communities intermix with forests, 

and are dominated by understory layers of mountain big 

sagebrush, Wyoming big sagebrush (Artemisia tridentata 

ssp. wyomingensis), common snowberry (Symphoricarpos 

albus), and serviceberry (Amelanchier alnifolia). Deciduous 

woodlands of pinyon pine, Utah juniper, quaking aspen, and 

Gambel oak (Quercus gambelii) exist throughout the subregion and mix with the sagebrush shrublands and agricultural 

grassland ecosystems at lower elevations. These stands contain understory layers of black sagebrush (Artemisia nova), 

mountain big sagebrush, and curl-leaf mountain mahogany 

(Cercocarpus ledifolius) (Mohlenbrock 2006). Utah juniper 

has encroached into sagebrush areas, depleting habitat 

of greater sage-grouse. Riparian areas create hotspots of 

biodiversity for flora and fauna, and help moderate flooding, 

sediment deposition, and water temperature (Knight et al. 

2014). Riparian ecosystems are vulnerable to damage from 

livestock grazing and construction activities for roads and 

other infrastructure (Utah Division of Wildlife Resources 

1991).

Some 480 plant species are found in the subregion. 

Common shrubs include mountain big sagebrush, black 

sagebrush, greenleaf manzanita (Arctostaphylos patula), 

fourwing saltbush (Atriplex canescens), rubber rabbitbrush 

(Ericameria nauseosa), antelope bitterbrush (Purshia 

tridentata), Mormon tea (Ephedra viridis), and greasewood 

(Sarcobatus vermiculatus) (Mohlenbrock 2006). Grasses 

include Salina wildrye (Leymus salinus), galleta (Hilaria 

jamesii), and purple three-awn (Aristida purpurea) (West 

1983). Many of these species are tolerant of high salt concentration in low-elevation soils, especially ancient lake beds.

A particularly fragile feature of desert ecosystems is 

known as a “cryptobiotic crust.” Cyanobacteria and other 

organisms create these crusts on the soil surface where they 

live and retain carbon, fix nitrogen, and stabilize soil. These 

crusts thicken through time, providing nutrients to the dry 

soil below. The crust is vulnerable to disturbances (e.g., human footprints, vehicles) that disrupt its structure and reduce 

plant growth.

Large mammal species include mule deer, bighorn sheep, 

elk, mountain lion, black bear, and coyote (Canis latrans). 

Smaller vertebrates include red squirrel (Tamiasciurus 

hudsonicus), hoary bat (Lasiurus cinereus), pinyon mouse 

(Peromyscus truei), and desert cottontail (Sylvilagus 

audubonii). Bird species include red-tailed hawk, northern 

goshawk (Accipiter gentilis), Cooper’s hawk (A. cooperi), 

wild turkey (Meleagris gallopavo), boreal owl (Aegolius 

funereus), and numerous warblers. Amphibians and reptiles 

include tiger salamander (Ambystoma tigrinum) and milk 

snake (Lempropeltis triangulum) (West 1983).

The Plateaus subregion contains diverse fisheries in 

streams, lakes, and reservoirs. Common species of fish 

include rainbow trout (Oncorhynchus mykiss), cutthroat 

trout, lake trout, brook trout, speckled dace (Rhinichthys 

osculus), desert sucker (Catostomus clarki), and yellow 

perch. The Virgin River system provides habitat for the rare 

Virgin River chub (Gila seminude), Virgin River spinedace 

(Lepidomeda mollispinis), and woundfin (Plagopterus 

argentissimus). Nonnative fish, stream diversions, and poor 

water quality have reduced the abundance of these species.

Native Americans arrived in the Plateaus subregion 

around 12,500 years BP. Hunting of mammoths, giant 

sloths, and American bison sustained these peoples until the 

megafauna became extinct around 8,000 years BP, when 

the Puebloan people emerged and populated the entire 

region (Hatt 2014). Native Americans had diverse lifeways 

focused on hunting, fishing, food gathering, and eventually 

agriculture. Near the end of the 19th century, pioneers began 

to settle southeastern Utah for mineral extraction, farming, 

and ranching (Hatt 2014). Native American populations 

were greatly reduced following Euro-American contact. 

Currently, the Ute Indians and Navajo Nation have large 

reservations within the subregion.

Geologic evolution of the subregion created extensive 

deposits of coal, oil, gas, tar sands, oil shale, uranium, and 

Chapter 2: Biogeographic, Cultural, and Historical Setting
24 USDA Forest Service RMRS-GTR-375. 2018

potash (Hatt 2014). Coal beds have allowed the subregion to 

become a major contributor to U.S. energy production. On 

a local scale, coal, oil, and gas industries support economic 

development. Renewable energy sources include wind, 

hydroelectric, geothermal, and solar (Hatt 2014). In 2010, 

Ashley National Forest sold more than 1.3 million cubic 

feet of timber (Ashley National Forest 2010), representing a 

significant source of income for local communities.

National parks, national forests, and other lands contribute significantly to the tourism economy of the Plateaus 

subregion, attracting millions of visitors, of which twothirds are from out of state. Diverse landscapes from alpine 

forests to the red-rock deserts provide a wide range of attractions for recreation and tourism. Summer offers hunting, 

fishing, hiking, mountain biking, and off-road travel, and 

winter attracts skiers, snowmobilers, and other winter sport 

enthusiasts.

Great Basin and Semi Desert Subregion

The Great Basin and Semi Desert subregion is the largest 

subregion, occupying over 100 million acres, and covering 

most of Nevada, the western half of Utah, small sections 

of southern Idaho, and portions of east-central California 

(fig. 2.9). Sections of Humboldt-Toiyabe National Forest 

are distributed throughout Nevada and parts of east-central 

California. The western half of the Dixie National Forest 

and the northern tip of the Fishlake National Forest are 

included near the eastern border of the subregion.

Between 300 and 800 million years BP, deep oceans 

covered western Utah, depositing limestone and dolomite 

sediments. These deposits were buried by thick layers 

of shale, forming large coal beds that underlie much 

of the subregion. Between 18 and 40 million years BP, 

volcanism formed large calderas, cinder cones, and lava 

flows throughout Nevada and western Utah. Large areas 

of mineral deposits (silver, gold, molybdenum, zinc, beryllium, iron, and copper) were formed in hydrothermal veins 

and host rock. Around 65 million years BP, Utah began to 

Figure 2.9—National 

forests and national 

parks within the 

Great Basin and Semi 

Desert subregion of 

the Intermountain 

Adaptation Partnership 

region.

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 25

sink and extensional faulting produced the basin-and-range 

topography of the Great Basin (Black 2011). More than 150 

different mountain ranges are scattered throughout Nevada 

and Utah, including the Schell Creek Range, Toiyabe Range, 

Ruby Mountains, Shoshone Mountains, and Snake Range. 

These mountains are typically isolated and surrounded by 

intervening lowlands.

Around 10,000 years BP, melting glaciers of the Rocky 

Mountains and Sierra Nevada filled valleys of the Great 

Basin (Black 2011). Lake Bonneville and Lake Lahontan 

formed, covering most of western Utah. As climate warmed, 

both lakes evaporated and left remnant lakes (e.g., Sevier 

Lake and the Great Salt Lake from Lake Bonneville), as 

well as numerous dry playas.

Climate in the Great Basin and Semi Desert subregion is 

mostly desert and semiarid. The high Sierra Nevada traps 

moisture coming from the Pacific Ocean, creating a significant rain-shadow effect that makes Nevada the driest State 

in the United States. Average temperatures in northwestern 

Nevada are about 50 °F, with hot, dry summers and moderately cool winters (WRCC 2016). Farther south, average 

temperatures are about 65 °F; summers are long and hot, 

and winters are short and mild. Little precipitation falls in 

the southern part of the subregion, whereas the northwestern 

portion receives more precipitation because of proximity to 

the Sierra Nevada.

The Humboldt, Colorado, Sevier, and Truckee Rivers 

are the major river networks in the subregion. Smaller river 

networks include the Carson and Walker Rivers. Supplied 

with water from the Rocky Mountains to the north and east, 

the Colorado River flows in the southeastern portion of the 

subregion. The Humboldt River runs 290 miles through 

northern Nevada (the longest U.S. river that exists entirely 

within one State), and drains into the Humboldt Sink, a 

playa in western Nevada. The headwaters of the Humboldt 

River drain the East Humboldt and Jarbidge Ranges, and 

the river continues westward, gathering water from scattered tributaries along the way during the spring and losing 

surface water to groundwater during much of the rest of the 

year. The Sevier River is Utah’s longest river, flowing 279 

miles through western Utah and emptying into the nearly 

dry Sevier Lake (Seligman et al. 2008).

With elevations ranging from 4,100 to 13,065 feet, the 

Great Basin and Semi Desert subregion exhibits a broad 

spectrum of ecosystems. High elevations contain a mixture 

of alpine, subalpine, woodland, riparian, and shrub habitats. 

Subalpine ecosystems include quaking aspen woodlands, 

coniferous forests, pinyon-juniper woodlands, and mountain 

shrublands. Aspen woodlands dominate more than 250,000 

acres and are commonly found between 5,200 and 10,500 

feet, providing wildlife habitat, areas for livestock grazing, 

and recreation opportunities. Lower elevations are dominated by sagebrush-steppe ecosystems (fig. 2.10), which 

encompass most of the subregion, and include numerous 

small spring-fed riparian and wetland areas.

Mountain shrub communities of mountain big sagebrush, 

serviceberry, Gambel oak, and many other species occupy 

mountain slopes at 5,000 to 9,000 feet elevation. These are 

the most widespread communities in the subregion, providing nesting, food resources, and shelter for many vertebrate 

and invertebrate species. Riparian zones are common along 

the lower portions of the mountain ranges in HumboldtToiyabe National Forest. Springs, rivers, creeks, and lakes 

offer moist conditions for grasses and forbs and habitat for 

mammals, migratory songbirds, and wildflowers.

Coniferous forests, including bristlecone pine (Pinus 

longaeva), limber pine, whitebark pine, and ponderosa 

pine, occur at mid- to high elevations. In the eastern Sierra 

Nevada, coniferous forests also include Jeffrey pine (Pinus 

jeffreyi), lodgepole pine, western white pine, Douglas-fir, 

white fir, and Shasta red fir (Abies magnifica). Pinyonjuniper woodlands exist at middle elevations, dominated 

Figure 2.10—Sagebrush 

and desert shrub habitats 

characteristic of the 

Great Basin and Semi 

Desert subregion of the 

Intermountain Adaptation 

Partnership region (photo: 

U.S. Geological Survey).

Chapter 2: Biogeographic, Cultural, and Historical Setting
26 USDA Forest Service RMRS-GTR-375. 2018

by pinyon pine and Utah juniper. These woodlands provide habitat for mule deer, desert cottontail, pinyon jay 

(Gymnorhinus cyanocephalus), and Clark’s nutcracker 

(Nucifraga columbiana). Expansion of pinyon-juniper 

woodlands has displaced some shrub-steppe habitat, and 

cutting and mechanical treatments are used to control the 

extent of woodlands in some locations.

Sagebrush is common throughout the Great Basin and 

Semi Desert subregion, providing habitat for sage sparrow 

(Artemisiospiza belli), sage thrasher (Oreoscoptes montanus), loggerhead shrike (Lanius ludovicianus), burrowing 

owl (Athene cunicularia), and greater sage-grouse. Both 

large and small vertebrates, including pronghorn and mule 

deer, inhabit sagebrush ecosystems.

Other large mammals in this subregion include desert 

(Ovis canadensis nelsoni), California (O.c. californiana), 

Rocky Mountain (O.c. canadensis), and Sierra Nevada 

(O.c. sierra) bighorn sheep; elk; mountain goat; black bear; 

and mountain lion. Small mammals include several species 

of rabbits, Sierra Nevada red fox (Vulpes vulpes necator), 

coyote, bobcat (Lynx rufus), Palmer’s chipmunk (Tamias 

palmeri), American marten (Martes americana), and numerous bat species. Wild horses and burros are common across 

the entire State, competing with wildlife and livestock for 

scarce forage. Birds in the subregion include greater sagegrouse, goshawk, California spotted owl (Strix occidentalis 

occidentalis), great gray owl (Strix nebulosi), flammulated 

owl (Psiloscops flammeolus), burrowing owl (Athene 

cunicularia), red-tailed hawk, golden eagle, prairie falcon 

(Falco mexicanus), and Cooper’s hawk.

Many fish species occupy streams and major rivers 

in the subregion. Rivers and streams of eastern Nevada 

contain Bonneville cutthroat trout, interior redband trout 

(Oncohynchus mykiss gairdneri), and bull trout. The 

Sevier River contains primarily brown trout, rainbow trout, 

and cutthroat trout. Lahontan cutthroat trout (O. clarkii 

henshawi), a Federally listed threatened species, occurs in 

isolated mountain streams throughout much of Nevada. 

Silver King Creek in California contains the only population 

of Paiute cutthroat trout (O. clarkii seleniris).

Desert ecosystems support Pacific tree frog (Hyla 

regilla), Columbia spotted frog (Rana luteiventris), and 

red-spotted toad (Bufo punctatus). The mountain yellowlegged frog (R. muscosa) and Yosemite toad (B. canorus) 

occupy the higher elevations in the far western part of 

the subregion. Reptiles include side-blotched lizard (Uta 

stansburiana), zebra-tailed lizard (Callisaurus draconoides), Great Basin collared lizard (Crotaphytus bicinctores), 

coachwhip (Masticophis flagellum), speckled rattlesnake 

(Crotalus mitchellii), and Gilbert’s skink (Plestiodon gilberti) (Knight et al. 2014). Many species of hummingbirds 

and small songbirds populate both desert and mountain 

ecosystems (Knight et al. 2014).

Wildfire regimes in the subregion have been altered 

where nonnative species have proliferated following fire. At 

the end of the 19th century, cheatgrass was introduced to the 

shrublands. This species is highly flammable, increases the 

spread rate of wildfires, and regenerates quickly after fire, 

outcompeting sagebrush and other perennial species (Blank 

et al. 2008). Public policy has encouraged fire suppression 

throughout the subregion, which has resulted in single-age 

sagebrush habitats that lack herbaceous and perennial grass 

species (Blank et al. 2008). Some shrub cover is so dense 

that biodiversity is low within these habitats.

Before Euro-American settlement, Native American 

tribes claimed lands that are now in Humboldt-Toiyabe 

and Dixie National Forests. In the Nevada portion of the 

area, the ancestral land of the Southern Paiute, Northern 

Paiute, Western Shoshone, and Washoe Indians has been 

inhabited for over 4,500 years. The Fremont, Anasazi, and 

Paiute Indians inhabited what is now Dixie National Forest. 

Several Indian reservations occupy the area, including those 

for the Summit Lake Paiute Tribe, Pyramid Lake Paiute 

Tribe, Walker River Paiute Tribe, Moapa Band of Paiute 

Indians, Goshute Confederated Tribes, Te-Moak Tribe of 

Western Shoshone Indians-South Fork band, Skull Valley 

band of Goshute Indians, Paiute Indian Tribes-Shivwits 

band, and a portion of the Shoshone-Paiute Tribe.

The 19th-century California gold rush brought EuroAmerican settlers to the area. Emigrant roads and trails 

connected mining towns, logging sites, and stagecoach 

stops throughout the region. Industries and economic pressure grew with continued settlement of the American West 

throughout the 19th century. Nevada leads the country in 

production of gold, barite, diatomite, and mercury, and is the 

only State that produces magnesite, lithium, and specialty 

clays (Price 2004).

Oil and gas reserves lie below the eastern part of the 

subregion. The National Forest System evaluates lands for 

drilling potential in accordance with the Federal Onshore 

Oil and Gas Leasing Reform Act of 1987 (Dixie National 

Forest 2011). Drilling is allowed within some areas of Dixie 

National Forest and Humboldt-Toiyabe National Forest, 

excluding designated wilderness, although no drilling has 

been conducted on Dixie National Forest since 1987. Most 

expressions of interest in drilling have been processed by 

the Bureau of Land Management for its lands adjacent to 

national forests.

Several prominent conservation issues influence resource 

management in this subregion. Humboldt-Toiyabe National 

Forest is home to over 800 wild horses and burros. The Wild 

Free-Roaming Horses and Burros Act of 1971 (Public Law 

92-195) protects wild horses and burros of the American 

West, but competition for forage and water resources with 

domestic livestock is controversial. Fragmentation and loss 

of sagebrush habitat have made the Columbia spotted frog a 

candidate endangered species, susceptible to extirpation in 

some areas. Protection of the species has been implemented 

in the greater Humboldt River watershed of central and 

northeastern Nevada. Conservation of greater sage-grouse, 

one of the highest profile natural resource issues in the 

West, is influenced by the loss of sagebrush ecosystems, 

with declining populations of sage-grouse in Nevada and 

Utah. Methods to sustain both the habitat and population of 

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 27

sage-grouse include restoration of shrub-steppe ecosystems 

and control of nonnative species (Nevada Department of 

Wildlife 2013).

Intermountain Semi Desert Subregion

The Intermountain Semi Desert subregion covers 5.5 

million acres. No national forests are located here, although 

500,000 acres of wilderness area have been reserved, along 

with Craters of the Moon National Monument and Idaho 

National Laboratory in the north-central part of the subregion (fig. 2.11).

The western half of the subregion contains the Snake 

River Plain and Camas Plain. Uplands consist of the 

Owyhee Plateau located along the Idaho-Nevada border, and 

the Blackfoot Mountains. Flat plateaus and volcanic plains 

dotted with cinder cones and other volcanic remnants characterize the landscape. Deep river canyons, granite domes, 

and rugged peaks distinguish the Owyhee Mountains from 

the low-lying areas along the Snake River to the north, 

where basalt sheets underlie the irrigated plains. The eastern 

half of the subregion begins just north of the junction with 

Idaho, Utah, and Wyoming, extending west into the Great 

Basin. Desert habitats are uniformly distributed throughout 

the plains and plateaus.

The northwestern corner of the subregion typically 

has the same maritime climate trends as northern and 

central Idaho. Within the Snake River Plain, the climate is 

influenced by warm, dry Pacific air masses and cold, moist 

Arctic air masses that converge from western and northern 

directions, respectively. This interaction allows for freezing 

winter temperatures, summer thunderstorms, and hot, humid 

summers. The Snake River Plain and the area south to the 

Nevada/Idaho border receive an average of 10 to 15 inches 

of precipitation annually (Chandler 2003). However, the 

higher elevation Owyhee Mountains receive more precipitation and prolonged freezing temperatures during the winter. 

The Blackfoot Mountains have cool, dry winters and hot, 

dry summers.

The South Fork of the Boise River runs westward across 

the northwestern corner of the Intermountain Semi Desert 

subregion, joining the North and Central Forks of the Boise 

River at Arrow Rock Reservoir. Originating from the northeastern corner of the subregion, the Snake River cuts across 

the middle of the Snake River Plain from the Southern 

Greater Yellowstone subregion to the Oregon-Idaho border. 

Figure 2.11—Location of the Intermountain Semi Desert subregion of the Intermountain Adaptation Partnership region.

Chapter 2: Biogeographic, Cultural, and Historical Setting
28 USDA Forest Service RMRS-GTR-375. 2018

Impoundments to the Snake River, such as those at Lake 

Walcott and American Falls Reservoir, provide hydroelectricity and irrigation water for nearby agriculture. In the 

northeastern areas, the Big Lost River disappears from 

its central Idaho source, drains to the Snake River aquifer 

below the surface of the volcanic rocks, and re-emerges 

near Thousand Springs Creek. Incising through canyons of 

the Owyhee Mountains, the Owyhee River flows generally 

northward to the Snake River near the Oregon-Idaho border, 

forming one of the largest subbasins of the Columbia River 

system.

The Snake River Plain is believed to have originated 

16 to 17 million years BP as a hotspot of the Earth’s crust 

moved from west to east, producing lava flows and basalt 

throughout the subregion. Large basalt flows erupted onto 

the surface in volcanic rift zones. Between 12,000 and 

15,000 years BP, powerful floods cut through the Snake 

River basin from Lake Bonneville to the south, depositing 

alluvial sediments derived from adjacent mountain ranges. 

The Owyhee Plateau marks the highland portions of the 

subregion, characterized by warped volcanic deposits that 

eventually converge with the lower plains (Chandler 2003).

Sagebrush-steppe ecosystems are distributed throughout 

lower elevations in the subregion, giving way to mountain 

big sagebrush and other subalpine systems at higher elevations (fig. 2.12). The northern border of the western section 

of the subregion is dominated by subalpine ecosystems 

similar to those of the Middle Rockies subregion. Farther to 

the south, the high desert habitats of the Great Basin become 

more prevalent with more arid vegetation.

High desert habitats are dominated by open desert with 

low-lying sagebrush and grasslands. As the Snake River 

flows along the natural arc-shape of the plain, riparian 

zones are plentiful and contain habitat for willows (Salix

spp.), quaking aspen, narrowleaf cottonwood (Populus 

angustifolia), and chokecherry (Prunus virginiana). 

Sagebrush shrublands, including mountain big sagebrush, 

greasewood, and shadscale (Atriplex confertifolia), cover 

most of the central and southern portions of lower elevations (Chandler 2003). Nonnative Russian thistle (Salsola 

kali), cheatgrass, and other species have degraded the once 

productive grazing land that lies between Twin Falls and the 

Boise River.

Wildfire frequency in the subregion has increased since 

the early 1900s. Before European settlement, fire intervals 

were 60 to 110 years, allowing for productive native 

grasslands to thrive (Manier et al. 2011). Introduction of 

cheatgrass has reduced intervals to less than 5 years in some 

places. After fires occur, cheatgrass regenerates quickly, 

limiting the growth of native vegetation and providing fuel 

for subsequent fires. Addressing this change in ecology 

and disturbance regimes is a major challenge for resource 

management in the Snake River Plain. In addition, juniper 

woodlands have expanded into sagebrush and grasslands 

of the lower plains, reducing wildlife habitat, water quality, 

and forage for grazing.

The subregion is home to a wide range of mammals, including mule deer, whitetail deer (Odocoileus virginianus), 

black bear, Rocky Mountain elk, bighorn sheep, pronghorn, 

and American bison. Smaller mammals include badger 

(Taxidea taxus), coyote, yellow pine chipmunk (Tamias 

amoenus), Great Basin pocket mouse (Perognathus parvus), 

and bobcat (Chandler 2003).

Greater sage-grouse can be found throughout the 

sagebrush-steppe ecosystem, especially in the Owyhee 

Canyonlands. Steeper cliffs of the Canyonlands provide 

important nesting and foraging habitat for raptor species, 

such as red-tailed hawk, golden eagle, and peregrine falcon. These species also populate the eastern and western 

plains, which are home to osprey, American kestrel (Falco 

Figure 2.12—Highly 

incised river canyons, 

flat plateaus, and 

sagebrush-grasslands 

characteristic of the 

Intermountain Semi 

Desert subregion of 

the Intermountain 

Adaptation Partnership 

region, shown here 

in Birds of Prey 

National Conservation 

Area (photo: Natural 

Resources Conservation 

Service).

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 29

sparverius), bald eagle, and prairie falcon as well. In the 

juniper highlands and Blackfoot Mountains, iconic birds 

include common poorwill (Phalaenoptilus nuttallii), broadtailed hummingbird (Selasphorus platycercus), bushtit 

(Psaltriparus minimus), and green-tailed towhee (Pipilo 

chlorurus).

Within the Snake River system, anadromous fish, including steelhead trout and Chinook salmon, arrive in the spring. 

Interior redband trout, bull trout, mountain whitefish, and 

other fish species inhabit the Owyhee River and Bruneau 

River. The Owyhee River contains large populations of nonnative brown trout and rainbow trout.

The Fort Hall Reservation, located in southeastern Idaho, 

is home to the Shoshone-Bannock Indian Tribes. The Fort 

Bridger Treaty of 1868 and the Indian Reorganization Act of 

1934 granted self-governing rights to the tribes (ShoshoneBannock Tribes 2015). Historically, the tribes consisted of 

hunters and gatherers who traveled in spring and summer 

collecting winter supplies. Riparian zones along the Snake 

River provided a diversity of plant food sources. Abundant 

salmon in the river were harvested year round, along with 

mammals that inhabited the river banks. American bison 

was valued as a primary food and raw material for tribal 

communities. By 1864, bison had vanished from the area, 

and land ownership changed from ancestral tribal lands 

to the reservation system. Resource management and 

land ownership policies in the surrounding area of the 

current-day reservation are administered by U.S. and Tribal 

Governments.

References

Ashley National Forest. 2010. Ashley National Forest: 2012 year 

in review. Vernal, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Region, Ashley National Forest.

Atwood, G. 2012. Geology of Utah. In: Powell, A.K., ed. Utah 

History Encyclopedia. Utah Education Network. http://www.

uen.org/utah_history_encyclopedia/uheindex.html [Accessed 

June 19, 2016].

Black, D.V. 2011. The geologic history of Utah. Provo, UT: 

Walden School of Liberal Arts. 26 p. https://elementsunearthed.

files.wordpress.com/2010/12/utah_geology.pdf [Accessed July 

12, 2016].

Blackwell, J.; Reese, J. 2001. Draft environmental impact 

statement for the Caribou National Forest: Draft revised forest 

plan. Idaho Falls, ID: U.S. Department of Agriculture, Forest 

Service, Intermountain Region.

Blank, R.; Burkhardt, W.; Chatterton, W.; [et al.]. 2008. Great 

Basin wildfire forum: The search for solutions. Wildfire Forum 

for the Great Basin. Reno, NV: University of Nevada, Nevada 

Agricultural Experiment Station.

Brandt, J.P.; Morgan, T.A.; Keegan, C.E.; [et al.]. 2012. Idaho’s 

forest products industry and timber harvest, 2006. Res. 

Bull. RMRS-RB-12. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station.

Brown, M.J.; Chojnacky, D.C. 1991. Idaho’s Forests, 1991. Res. 

Bull. INT-RB-88. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Research Station.

Burden, C.B. 2015. Groundwater conditions in Utah, spring 

of 2015. Coop. Invest. Rep. 56. Salt Lake City, UT: U.S. 

Department of the Interior, U.S. Geological Survey; Utah 

Department of Natural Resources, Utah Department of 

Environmental Quality.

Cairns, C., ed. 2015. Rocky Mountain Research Station: 

Looking back on 2014. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 

4 p.

Caribou-Targhee National Forest. 2005. Fire management plan, 

2005. FMP-2005. Ashton, ID: U.S. Department of Agriculture, 

Forest Service, Caribou-Targhee National Forest. http://www.

fs.usda.gov/Internet/FSE_DOCUMENTS /stelprdb5238562.

pdf. [Accessed June 23, 2016].

Chandler, J.A., ed. 2003. Feasibility of reintroduction of 

anadromus fish above or within the Hells Canyon Complex. 

Gen. Tech. Rep. FERC-GTR-1971: E.3.1-2. Boise, ID: 

Idaho Power Company. https://www.idahopower.com/pdfs/

Relicensing/hellscanyon/hellspdfs/techappendices/Aquatic/

e31_02_ch03.pdf. [Accessed June 15, 2016].

Crane, M.F.; Fischer, W.C. 1986. Fire ecology of the forest 

habitat types of central Idaho. Gen. Tech. Rep. INT-GTR-218. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station.

Demarchi, D.A. 1994. Ecoprovinces of the central North American 

cordillera and adjacent plains. Gen. Tech. Rep. RM-GTR-254. 

Fort Collins, CO: U.S. Department of Agriculture, Rocky 

Mountain Forest and Range Experiment Station.

Dillon, J.; Grunder, S.A. 2008. Management plan for the 

conservation of Snake River white sturgeon in Idaho. Boise, 

ID: Idaho Department of Fish and Game. https://fishandgame.

idaho.gov/public/fish/planSnakeWhiteSturgeon.pdf. [Accessed 

June 15, 2016].

Dixie National Forest. 2011. Oil and gas leasing on the Dixie 

National Forest: Final Environmental Impact Statement. Cedar 

City, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Region, Dixie National Forest. http://www.

fs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb5325181.pdf 

[Accessed on June 20, 2016].

Fellin, D.G.; Dewey, J.F. 1982. Western spruce budworm. For. 

Insect Dis. Leafl. 53. Missoula, MT: U.S Department of 

Agriculture, Forest Service, Forest Health Protection.

Gibson, K.; Skov, K.; Kegley, S.; [et al.]. 2008. Mountain pine 

beetle impacts in high-elevation five-needle pines: current 

trends and challenges. R1-08-020. Missoula, MT: U.S. 

Department of Agriculture, Forest Service, Forest Health 

Protection.

Giunta, A.D.; Jenkins, M.J.; Hebertson, E.G.; [et al.]. 2016. 

Disturbance agents and their associated effects on the health 

of interior Douglas-fir forests in the Central Rocky Mountains. 

Forests. 7: 80.

Harris, A.G.; Tuttle, E.; Tuttle, S.D. 1997. Geology of national 

parks, 6th ed. Dubuque, ID: Kendall/Hunt Publishing Company.

Hatt, D.L. 2014. 2015–2019 Southeastern Utah economic 

development district comprehensive economic development 

strategy. Report prepared for the Southeastern Utah Economic 

Development District. Price, UT: U.S. Department of 

Commerce, Economic Development Administration. 150 p.

Chapter 2: Biogeographic, Cultural, and Historical Setting
30 USDA Forest Service RMRS-GTR-375. 2018

Headwaters Economics. 2014. High Divide region: Summary 

of recreation economy. Report written for the High Divide 

region. Bozeman, MT: Headwaters Economics. http://

headwaterseconomics.org/wphw/wp-content/uploads/High_

Divide_ Outdoor_Rec_Economy.pdf [Accessed June 20, 2016].

Heyerdahl, E.K.; Brown, P.M.; Kitchen, S.G.; [et al.]. 2011. 

Multicentury fire and forest histories at 19 sites in Utah and 

Eastern Nevada. Gen. Tech. Rep. RMRS-GTR-261WWW. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station. 192 p.

Idaho Department of Health and Welfare. 1999. Lemhi River 

Watershed TMDL: An allocation of nonpoint source pollutants 

in the water quality limited watersheds of the Lemhi River 

Valley. Boise, ID: Idaho Department of Health and Welfare, 

Division of Environmental Quality. http://www.deq.idaho.

gov/media/454821_water_data_reports_surface_water_tmdls_

lemhi_river_lelem_river_entire.pdf [Accessed June 14, 2016].

Jones, M. 1990. History of settlement and early livestock grazing 

in the area of the Boise National Forest. R4-1680-95-0001-14-

8. U.S. Department of Agriculture, Forest Service. http://www.

fs.usda.gov/Internet/FSE_DOCUMENTS/fsbdev3_042215.pdf 

[Accessed June 22, 2016].

Knight, D.H.; Jones, G.P.; Reiners, W.A.; [et al.]. 2014. Mountains 

and plains: The ecology of Wyoming landscapes, 2nd ed. 

Laramie, WY: University of Wyoming Biodiversity Institute.

Link, P.; Welhan, J.; Peterson, C.; [et al.]. 2000. Digital atlas of 

Idaho: Idaho’s natural history online. Boise, ID: State of Idaho, 

Board of Education. http://imnh.isu.edu/digitalatlas/aboutus/

about.htm. [Accessed June 15, 2016].

Lowrey, L.L. 2015. Evaluation of the extent of the non-native 

insect, balsam wooly adelgid, south of the Salmon River 

in Idaho from 2006–2014 by ground delimitation and 

aerial detection surveys. BFO-PR-2015-01. Boise, ID: 

U.S. Department of Agriculture, Forest Service, Forest 

Health Protection. http://www.fs.usda.gov/Internet/FSE_

DOCUMENTS/stelprd3834265.pdf. [Accessed June 9, 2016].

Manier, D.J.; Aldridge, C.; Anderson, P.; [et al.]. 2011. 

Land use and habitat conditions across the southwestern 

Wyoming sagebrush steppe: Development impacts, 

management effectiveness and the distribution of invasive 

plants. Natural Resources and Environmental Issues. 17: 

Article 4. http://digitalcommons.usu.edu/cgi/viewcontent.

cgi?article=1749&context=nrei. [Accessed July 13, 2016].

Mohlenbrock, R.H. 2006. This land: A guide to Western national 

forests. Berkeley, CA: University of California Press.

Morris, L.A. 2006. Fire history of the City of Rocks National 

Reserve from 1926 to 2005. Cooperative Agreement 

H8R07010001. Boise, ID: Idaho State Parks and Recreation.

Nevada Department of Wildlife. 2013. Sage-grouse conservation. 

Reno, NV: Nevada Department of Wildlife. http://www.ndow.

org/Nevada_Wildlife/Sage_Grouse [Accessed June 20, 2016].

O’Laughlin, J.; Adams, D.L.; Bunting, S.C.; [et al.]. 1993. Forest 

health conditions in Idaho. Rep. RP-11. Boise, ID: Idaho 

Forest, Wildlife and Range Policy Analysis Group. http://www.

idahoforests.org/health3.htm [Accessed June 17, 2016].

Price, J.G. 2004. Geology of Nevada. Proceedings, 39th forum on 

the geology of industrial minerals; 2003 May 19–21; Reno, NV. 

Proc. NBMG-P-33. Reno, NV: Nevada Bureau of Mines and 

Geology.

Pyke, D.A.; Chambers, J.C.; Pellant, M.; [et al.]. 2015. Restoration 

handbook for sagebrush steppe ecosystems with emphasis on 

greater sage-grouse habitat: Part 1, concepts for understanding 

and applying restoration. Circ. 1416: 44. Reston, VA: U.S 

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

Reddy, S.D. 1993. The empty land: The search for the Nez Perce 

on the Payette National Forest. McCall, ID: U.S. Department 

of Agriculture, Forest Service, Heritage Program. http:// http://

www.fs.usda.gov/detailfull/payette/learning/history-culture/?cid

=fsm9_031023&width=full [Accessed June 18, 2016].

Robson, S.; Kingery, J. 2006. Idaho native plants for roadside 

restoration and revegetation programs: A report for the 

Idaho Transportation Department. Moscow, ID: University 

of Idaho, Idaho Transportation Department. http://itd.idaho.

gov/highways/ops/maintenance/roadside/ documents/

RP171Roadside_RevegReveget.pdf [Accessed June 13, 2016].

Schwandt, J.; Kearns, H.; Byler, J. 2013. White pine blister rust: 

General ecology and management. Insect Dis. Manage. Ser. 

14.2. Boise, ID: U.S Department of Agriculture, Forest Service, 

Forest Health Protection. http://www.fs.usda.gov/Internet/

FSE_ DOCUMENTS /stelprdb5415080.pdf [Accessed June 18, 

2016].

Seligman, D.; Peterson, M.; Price, S.; [et al.]. 2008. World’s 

major rivers: An introduction to international water law with 

case studies. Las Vegas, NV: Colorado River Commission 

of Nevada. http://crc.nv.gov/docs/Worlds_Major_Rivers.pdf 

[Accessed June 18, 2016].

Shaw, J.D.; Long, J.N. 2007. Forest ecology and biogeography 

of the Uinta Mountains, U.S.A. Arctic, Antarctic, and Alpine 

Research. 39: 614–628.

Shoshone-Bannock Tribes. 2015. History of the ShoshoneBannock Tribes. Fort Hall, ID: Shoshone-Bannock Tribes of the 

Fort Hall Reservation. http://www.shoshonebannocktribes.com/

shoshone-bannock-history.html [Accessed June 18, 2016].

Simmons, V.M. 2000. The Ute Indians of Utah, Colorado, and New 

Mexico. Boulder, CO: University Press of Colorado.

State of Wyoming. 2013. Wyoming history. Cheyenne, WY: State 

of Wyoming. http://www.wyo.gov/about-wyoming/wyominghistory [Accessed June 24, 2016].

Tilley, D.; Ogle, D.; St. John, L.; [et al.]. 2013. Threatened, 

endangered, and candidate plant species of Idaho. Tech. Note 

TN-51. Boise, ID: U.S. Department of Agriculture, Natural 

Resources Conservation Service.

U.S. Department of Agriculture, Forest Service [USDA FS]. 2011. 

Payette National Forest land and resource and management 

plan: Five-year evaluation report 2004–2008. McCall, ID: 

U.S. Department of Agriculture, Forest Service, Intermountain 

Region. http://www.fs.usda.gov/Internet/FSE_DOCUMENTS/

stelprdb5292644.pdf [Accessed June 22, 2016].

U.S. Department of Agriculture, Forest Service [USDA FS]. 2016. 

Cut and sold (new). CUTS203F. Quarterly report prepared for 

the Forest Service. Quart. Rep., FY 2016, Q1. Washington, DC: 

U.S. Department of Agriculture, Forest Service.

Utah Division of Wildlife Resources. 1991. Utah’s wildlife 

habitats. Utah Nongame Leaflet 2(1). Salt Lake City, UT: Utah 

Department of Natural Resources. http://digitallibrary.utah.gov/

awweb/awarchive?type=file&item=29617 [Accessed June 22, 

2016].

Chapter 2: Biogeographic, Cultural, and Historical Setting
USDA Forest Service RMRS-GTR-375. 2018 31

West, N.E. 1983. Southeastern Utah galleta-threeawn shrub steppe. 

In: West, N.E., ed. Ecosystems of the world: Temperate deserts 

and semi-deserts. Amsterdam, The Netherlands: Elsevier: 

413–421.

Western Regional Climate Center [WRCC]. 2016. Climate of 

Nevada. Reno, NV: Western Regional Climate Center. http://

www.wrcc.dri.edu/narratives/NEVADA.htm [Accessed 

November 19, 2016].

Chapter 2: Biogeographic, Cultural, and Historical Setting
32 USDA Forest Service RMRS-GTR-375. 2018

Introduction

The Intermountain Adaptation Partnership (IAP) region 

is characterized by extreme temperatures and precipitation; it is home to some of the driest, hottest, and coldest 

locations in the conterminous United States. The region 

has numerous mountain ranges, high-elevation basins and 

valleys, and low-elevation mesas and canyons. Climate is 

influenced by this diverse and complex terrain. The IAP region is bounded on the eastern side by the Rocky Mountains 

and on the western side by the Sierra Nevada. For this 

region, moisture comes predominantly from the Pacific 

Ocean, and consequently much of the moisture occurs as 

orographic precipitation in the mountains.

This chapter provides a brief discussion of the current 

climate in each of the six subregions to set the context for 

projected changes in climate under two future scenarios. The 

Great Basin and Semi Desert, and the Intermountain Semi 

Desert subregions are warmer and drier than the Southern 

Greater Yellowstone and Middle Rockies subregions. The 

Plateaus, and Uintas and Wasatch Front subregions have intermediate amounts of precipitation. Within each subregion, 

climate influences the ecosystem services that forests and 

rangelands provide. Thus, an understanding of how climate 

may change in the future is vital for long-term planning and 

management.

This chapter focuses on the historical record of climate, 

primarily temperature and precipitation, and the projected 

changes in temperature and precipitation. Chapter 4 describes the effects of climate on hydrological processes, 

snowpack and glaciers, streamflow, sediment yield, and 

drought. The impacts of climate change on wildfire and 

geologic processes, such as mass wasting, are discussed in 

Chapter 8. Other chapters review literature on the effects of 

climate change on particular resources, such as individual 

species in Chapter 9.

Assessing Climate Futures for Natural 

Resource Management

Information on weather and climate are used to inform 

the decisionmaking process in natural resource management. Day-to-day resource management practices are 

implemented with information on real-time conditions of 

temperature, precipitation, wind, humidity, and other meteorological factors. These specific conditions over a relatively 

short time period and in a particular place are what we call 

weather. This information is used to make on-the-ground 

real-time decisions, such as the start of prescribed fire 

activities.

Long-term resource management strategies and plans 

are informed by the observed dynamics of precipitation, 

temperature, wind, snowfall, and other measures of weather 

over a long time period in a particular place. Climate is 

defined by this long-term meteorological information. 

Understanding the climate of an area assists managers in 

identifying both the general characteristics of the area and 

the risks associated with potential extremes of weather conditions, such as flooding, drought, wildfire, and extreme heat 

or cold events. Typically, the most recent three full decades 

(e.g., 1981–2010) are used to determine the normal climate, 

or the average conditions on an annual, monthly, or daily 

basis. Long-term records (>30 years) are also used to assess 

the risk of specific weather events and thresholds that have 

relevance to management, such as in the sizing of culverts 

and bridges.

Although long-term records of climate can help to 

establish the characteristics of the average climate or the 

probability of certain extreme events, future climate may be 

different than the past 30 to 60 years (Walsh et al. 2014). To 

understand how climate might change, scientists use global 

climate models (GCMs), which are supercomputer-based 

simulations that represent the key components, interactions, 

and feedback processes of the climate system, based on 

fundamental physical laws and decades of observations of 

the atmosphere, oceans, ice sheets, and biosphere. These 

models have been used to study the physical dynamics of 

the atmosphere and the interaction between the atmosphere 

and the surface of the Earth, as well as interactions with 

ocean currents moving heat around the globe. Information 

on future changes in climate provided by GCMs can be 

helpful in understanding how the environmental settings of 

plants, animals, and habitats may change in the future; how 

runoff and seasonal flows may vary with precipitation and 

timing of snowmelt; and how wildfire, insects and disease 

patterns may change.

Scenarios

Climate models have been an important part of the 

Intergovernmental Panel on Climate Change (IPCC) assessments since 1990. In 1995, atmospheric scientists came 

together to coordinate a standardized set of model runs 

(also called experiments) for evaluating changes to past and 

future global climate: the Coupled Model Intercomparison 

Project (CMIP) (Meehl et al. 2007). This project also 

developed a web portal where these GCM results could be 

archived and made available for use by other scientists. This 

Chapter 3: Historical and Projected Climate

Linda A. Joyce and Marian Talbert
USDA Forest Service RMRS-GTR-375. 2018 33

approach allows for a rigorous comparison of results across 

the models because the models have similar initial conditions and similar changes in atmospheric chemistry and land 

use cover over time. This approach improves our understanding of the range of possible future climate change.

Many of the model experiments focus on improving 

the ability of the model to describe climate; however, 

these models can also be used to look at the evolution of 

climate over time when a description of how the future may 

develop is constructed. A climate scenario is a simplified 

representation of future climate, based on climatological 

relationships constructed for investigating the potential 

consequences of human-caused climate change (Stocker et 

al. 2013). Climate dynamics are influenced by land surface 

changes, such as building cities or changing land use from 

forest to agriculture, by the chemical composition of the 

atmosphere, and by human contributions to the atmosphere 

through land management, energy sources, and industrial 

processes. Constructing a scenario requires describing how 

these forces may develop over time. The goal of working 

with scenarios is to understand uncertainties and alternative 

conditions associated with climate change, thus informing 

decisions or options for a range of possible futures (IPCC 

Data Distribution Center 2016).

Climate scenarios in the last three IPCC assessments 

have been constructed in two ways (table 3.1). In the 

third and fourth IPCC assessments, scenario development 

started with specific assumptions about population growth, 

economic growth, and policies related to alternative energy 

and conventional fossil fuel sources; then the resultant 

greenhouse gas emissions to the atmosphere were projected 

(Solomon et al. 2007). These scenarios were called SRES 

scenarios, named for the report that developed them, the 

Special Report on Emission Scenarios (Nakićenović et al. 

2000). These different combinations of population, economic growth, and energy policy resulted in scenarios that 

ranged from low emissions (B1) to high emissions (A1FI), 

with a range of scenarios in between.

For the IPCC Fifth Assessment Report (Stocker et al. 

2013), scenario development focused on radiative forcing 

in the atmosphere. Here the emphasis was on adding different amounts of energy to the climate system over time. 

Scientists reviewed current estimates on radiative forcing, 

the total amount of extra energy entering the climate system 

throughout the 21st century and beyond. They used this 

information to construct a set of scenarios that would bound 

these estimates, from lesser amounts of energy entering 

the climate system to greater amounts of energy. These 

Table 3.1—Scenarios used by climate models in the Special Report on Emission Scenarios (SRES) and representative 

concentration pathway (RCP) scenarios in the Intergovernmental Panel on Climate Change (IPCC) assessment reports.

SRES scenarios RCP scenarios

Definition A plausible representation of the future 

development of emissions of substances that are 

potentially radiatively active (e.g., greenhouse 

gases, aerosols) based on a coherent and 

internally consistent set of assumptions about 

driving forces (such as demographic and 

socioeconomic development, technological 

change) and their key relationships.

Concentration scenarios, derived from emissions 

scenarios, are used as input to a climate model to 

compute climate projections.

Scenarios that include time series of emissions and 

concentrations of the full suite of greenhouse gases 

and aerosols and chemically active gases, as well as 

land use/land cover (Moss et al. 2008).

The word “representative” signifies that each RCP 

provides only one of many possible scenarios 

that would lead to the specific radiative forcing 

characteristics.

The term “pathway” emphasizes that not only the 

long-term concentration levels, but also the trajectory 

taken over time to reach that outcome, are of interest 

(Moss et al. 2010).

Different scenarios Scenario family is a set of scenarios that have a 

similar demographic, societal, economic, and 

technical change storyline. Four scenario families 

compose the SRES scenario set: A1, A2, B1, and 

B2.

RCP 2.6: One pathway where radiative forcing peaks 

at approximately 3 W m-2 before 2100 and then 

declines.

RCP 4.5 and RCP 6.0: Two intermediate stabilization 

pathways in which radiative forcing is stabilized at 

approximately 4.5 W m-2 and 6.0 W m-2 after 2100.

RCP 8.5: One high pathway for which radiative 

forcing reaches greater than 8.5 W m-2 by 2100 and 

continues to rise for some amount of time. 

Use in models Used to drive climate models in CMIP3a Used to drive climate models in CMIP5.

Use in IPCC 

assessments

Houghton et al. (2001), Solomon et al. (2007). Stocker et al. (2013).

a

 CMIP = Coupled Model Intercomparison Project; versions 3 and 5 are cited here. 

Chapter 3: Historical and Projected Climate
34 USDA Forest Service RMRS-GTR-375. 2018

scenarios are called representative concentration pathways 

(RCPs) (van Vuuren et al. 2011) because these scenarios 

represent one of many possible ways in which population, 

economic growth, and energy policy would lead to the 

specific radiative forcing characteristics. Consequently, the 

scenarios are defined by the amount of energy that is added 

to the atmosphere. For example, RCP 2.6 assumes a total radiative forcing increase of 2.6 Watts per square meter (0.82 

British thermal units per square foot) by 2100, whereas RCP 

8.5 assumes a much larger increase in the radiative forcing 

(8.5 Watts per square meter [2.7 British thermal units per 

square foot]). Intermediate scenarios include RCP 4.5 and 

RCP 6.0.

The RCPs focused on the implications of energy added 

to the atmosphere and consequently were not designed to 

mimic particular SRES scenarios. But because the SRES 

scenarios have been used for many analyses of climate 

change effects on natural resources (Walsh et al. 2014), 

an understanding of how the RCP and the SRES scenarios 

compare is helpful in interpreting past analyses. The comparison by Rogelj et al. (2012) considers climate sensitivity 

uncertainty, synthesizes the understanding of climate system 

and carbon cycle behavior, and is constrained by observed 

historical warming. Rogelj et al. (2012) identify analogs 

between RCP 4.5 and SRES B1, RCP 6.0 and SRES B2, and 

RCP 8.5 and SRES A1FI (table 3.2). The SRES A1B has a 

greater range in temperature changes than RCP 6.0, and a 

warmer upper range. Rogelj et al. (2012) note that temporal 

patterns differ between the SRES and RCP scenarios.

Climate Projections for the Region

This report uses scenarios RCP 4.5 and RCP 8.5 to 

explore future climate in the IAP region. These scenarios 

capture a moderate and a high future warming. In addition, 

more GCMs have used these scenarios than RCP 2.6 or RCP 

6.0. The breadth of these scenarios and the availability of a 

larger set of projections enhance our understanding of the 

possible ranges in future climate. The term “climate projection” is used to describe the results of a climate model when 

forced by a particular scenario.

For an overview of projected future climate in the IAP 

region, we use the most recent climate change projections 

based on RCP 4.5 and RCP 8.5 scenarios (Stocker et al. 

2013). Output from GCMs is at a scale too coarse to represent climate patterns in subregions and management areas 

relevant for the IAP. Therefore, we drew on climate projections that had been downscaled using the bias-correction 

and spatial disaggregation (BCSD) method (Maurer et al. 

2007). We used projections from 36 climate models for RCP 

4.5 and 34 climate models for RCP 8.5 (see Appendix 2). 

The variables available for each BCSD climate projection 

include monthly precipitation and monthly surface air temperature for the 1950–2099 period. Spatial resolution of the 

data is 1/8 degree latitude-longitude (about 7 square miles), 

and data cover the entire IAP region. Climate projections 

were archived by CMIP; hereafter climate projections that 

used SRES scenarios are referred to as “CMIP3” and climate projections that used the RCP scenarios as “CMIP5.”

Historical mean annual temperature and precipitation 

vary across the IAP region (figs. 3.1, 3.2). We use a base 

period of 1979–2009 for the mean historical climate, and 

show mean temperatures and precipitation projected for two 

periods: 2030–2059 and 2070–2099. These time periods 

were selected to summarize climate that has influenced the 

current environmental conditions (base period) and two future periods that will be relevant to long-term management 

action (e.g., road construction, management of hydrological 

infrastructure, or vegetation planting). Historical mean 

Table 3.2—Probabilistic estimates of temperature increase above preindustrial levels based on 

representative equilibrium climate sensitivity distribution for six Special Report on Emission 

Scenarios (SRES) market scenarios and four representative concentration pathway (RCP) scenarios 

(Rogelj et al. 2012).

2090–2099 2100

Scenario Median 66% range Median 66% range

---------------------------------------------- o

F ---------------------------------------------

SRES B1 4.3 3.6–5.6 4.5 3.6–5.8

SRES A1T 5.2 4.5–6.7 5.4 4.5–6.8

SRES B2 5.2 4.3–6.3 5.4 4.7–6.7

SRES A1B 6.1 5.0–7.6 6.3 5.2–7.9

SRES A2 7.0 5.8–8.6 7.6 6.3–9.4

SRES A1F1 8.5 7.0–10.4 9.0 7.4–11.2

RCP 3-PD (2.6) 2.7 2.3–3.4 2.7 2.3–3.4

RCP 4.5 4.3 3.6–5.2 4.3 3.6–5.4

RCP 6.0 5.2 4.5–6.5 5.4 4.7–6.7

RCP 8.5 8.3 6.8–10.3 8.8 7.2–11.0

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 35

Figure 3.1—(a) Historical (1979–2009) and (b–e) projected (2030–2059 and 2070–2099) mean annual monthly temperature 

(

o

F) under RCP 4.5 and RCP 8.5 scenarios for the entire Intermountain Adaptation Partnership region. Projected climate is the 

36-model mean for RCP 4.5 and the 34-model mean for RCP 8.5. Spatial resolution of the data is 1/8th degree latitude-longitude.

Figure 3.2—(a) Historical (1979–2009) and (b–e) projected (2030–2059 and 2070–2099) total annual precipitation (inches) under 

RCP 4.5 and RCP 8.5 scenarios for the entire Intermountain Adaptation Partnership region. Projected climate is the 36-model 

mean for RCP 4.5 and the 34-model mean for RCP 8.5. Spatial resolution of the data is 1/8th degree latitude-longitude.

Chapter 3: Historical and Projected Climate
36 USDA Forest Service RMRS-GTR-375. 2018

annual temperatures can vary from nearly 20 oF to 75 oF 

within the IAP region. Historical total annual precipitation ranges from less than 3 inches to above 70 inches. All 

subregions of the IAP are expected to see increases in mean 

annual temperature. Temperatures are projected to increase 

more by the end-of-century period (2070–2099) and under 

the warmer scenario, RCP 8.5. Precipitation changes are less 

consistent; the northern parts of the IAP region may have 

precipitation increases.

Several resource chapters in this report have drawn on 

published literature about the effects of climate change on 

natural resources which used SRES scenarios and CMIP3 

models. The question arises as to the regional differences 

between the CMIP3 projections under SRES scenarios and 

the CMIP5 projections under RCP scenarios. Understanding 

these differences may be helpful in interpreting the different 

projections used across these studies. Here, we compare 

CMIP5 climate projections under RCP 4.5 and RCP 8.5 

scenarios from this study with CMIP3 models under the 

SRES scenario A1B, which has been used in several natural 

resource assessments, including the cold-water fisheries 

analysis in chapter 5.

To identify differences between these two sets of 

scenarios, we compare the projected changes in mean 

temperature with change in total annual precipitation over a 

common period for the IAP region. We obtained 10 CMIP3 

global climate projections for the A1B scenario (moderate 

emissions) from Littell’s group. We estimate the change in 

temperature and percentage change in precipitation between 

the future period (2040–2060) and the historical period 

(1979–2009) for the CMIP3 models that Littell et al. (2011) 

used and the CMIP5 models used in this study. In figure 3.3, 

the projected change in mean annual temperature is shown 

on the horizontal axis, and the percentage change in precipitation is shown on the vertical axis. Change is described 

as the difference in temperature and percentage change in 

precipitation between historical and projected future values. 

We show all CMIP5 models used in this study. We show 

only the mean (ensemble) of all 10 CMIP3 models and two 

individual models (pcm1 and miroc_3.2), as these projections from Littell et al. (2011) are used most often.

Across all CMIP5 models, projected change in temperature by the 2040–2060 period ranges from just under 2 o

F 

to nearly 8 oF (fig. 3.3). Generally, the projected change for 

CMIP5 models under the RCP 8.5 scenario (shown in red) is 

greater than the change projected under the RCP 4.5 scenario (shown in yellow), but not always. For example, the RCP 

8.5 projections for models FIO-ESM (number 15 in fig. 3.3) 

and MRI-CGCM3 (number 34 in fig. 3.3) show temperature 

changes that are less than the median changes for all RCP 

4.5 models. The projected change in precipitation ranges 

from a decrease of about 12 percent to an increase of nearly 

30 percent. However, 28 of the 36 projections under RCP 

4.5 and 29 of the 34 projections under RCP 8.5 indicate 

an increase in precipitation. Across the IAP region, mean 

temperatures are projected to warm by 3.5 o

F to almost 

5 o

F over the next 50 years, with precipitation projected to 

increase slightly, by 5 to 8 percent.

The CMIP3 projections for the A1B scenario are within 

the mean temperature range of the CMIP5 projections (fig. 

3.3). The A1B ensemble projection of a nearly 4 o

F increase 

in temperature is similar to the mean increase for the RCP 

4.5 scenario; both of these scenarios are considered moderate in terms of future warming. The two individual model 

projections under the A1B scenario span the temperature 

range of the individual model projections under RCP 4.5. 

For precipitation, the CMIP3 models under the A1B scenario project a slight increase (ensemble) and decreases in 

precipitation (pcm1 and miroc_3.2). We conclude that when 

this set of CMIP3 results are compared with CMIP5 results 

for the IAP region, future temperatures are projected to be 

similar. However, CMIP5 precipitation projections collectively show a greater likelihood of increases in precipitation 

than the CMIP3 projections (fig. 3.3). This slight increase 

in projected precipitation with the CMIP5 models might be 

considered when evaluating the impact of analyses using 

CMIP3 climate projections.

Figure 3.3—For the entire Intermountain Adaptation 

Partnership region, change in mean annual temperature 

(

o

F) and total annual precipitation (%) from the simulated 

historical climate (1979–2009) and the projected climate 

(2040–2060) using the CMIP5 RCP 4.5 and RCP 8.5 

scenarios and the CMIP3 A1B scenario. Each CMIP5 model 

result is labeled by a number with a key in the legend (e.g., 

29 is MIROC-ESM) in colors to indicate RCP 4.5 (yellow) 

and RCP 8.5 (red) (see table 3.2). The crosses in the middle 

represent the median and 25 to 75 percent of the RCP 4.5 

and the RCP 8.5 projections used in this study. The mean 

values for the CMIP5 changes are shown on the figure as 

colored diamonds. The CMIP3 results are labeled in black 

triangles (see table 3.2 and Littell et al. [2011]).

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 37

Climatic Variability and Change 

in the Subregions

Historical Climate

To understand historical climatic variability and trends 

at the subregional scale in the IAP region, we compared 

three gridded datasets: Parameter-elevation Regressions 

on Independent Slopes Model (PRISM) (PRISM Climate 

Group 2014), Maurer (Maurer et al. 2002), and TopoWx 

(Oyler et al. 2015a). These three datasets used observed 

point measurements of precipitation, temperature, and other 

climatic factors to produce continuous, digital grid estimates 

of monthly, yearly, and event-based climatic parameters. 

Because of differences in the station data used by these gridded products as well as the models and assumptions used 

to interpolate to a grid, these models do not always agree 

on the historical climate or trend for a region. For example, 

in the western mountains, PRISM has been shown to have 

an artificial amplification in warming trend (Oyler et al. 

2015b).

The Middle Rockies subregion encompasses central 

Idaho, an area known as the “Idaho Batholith,” and the 

Salmon River Mountains. Climate is strongly influenced by 

interactions with topography, elevation, and aspect. Westerly 

winds bring in moisture from the Pacific Ocean, but moisture is precipitated over the western blocking mountains. 

Elevations range from 3,000 to 10,000 feet, with the highest 

peaks in the Salmon River Mountains. The deep dissections of this subregion can be seen in the ridge patterns in 

temperature (fig. 3.1a) and large gradients in precipitation 

(fig. 3.2a).

Climate in the Middle Rockies is characterized by cold 

winters with moderate to heavy snow accumulations at 

higher elevations. Throughout the 1940–2009 period, mean 

minimum temperatures showed a distinct increasing trend 

(fig. 3.4). Mean maximum temperature ranged from 48 to 

54 o

F over this period (fig. 3.5). As with other subregions, 

no warming trend is evident across the entire time period. 

In the last 25 years, however, the Middle Rockies maximum 

temperatures showed a slight increasing trend (fig. 3.5); similar increasing trends in summer temperatures were noted 

by Isaak et al. (2010) for the Upper Boise River watershed. 

Annual precipitation over the historical period ranged from 

20 inches to greater than 35 inches per year. Precipitation 

patterns were highly variable, with a slight downward trend 

in the last 25 years (fig. 3.6).

Figure 3.4—Annual historical mean monthly minimum temperature from the monthly gridded PRISM, Maurer, and TopoWx 

datasets for 1949–2010 for all six subregions of the Intermountain Adaptation Partnership region. The heavy lines are the 

10-year rolling average from each dataset to show short-term trends.

Chapter 3: Historical and Projected Climate
38 USDA Forest Service RMRS-GTR-375. 2018

Figure 3.5—Annual historical mean monthly maximum temperature from the monthly gridded PRISM, Maurer, 

and TopoWx datasets for 1949–2010 for all six subregions of the Intermountain Adaptation Partnership region. 

The heavy lines are the 10-year rolling average from each dataset to show short-term trends.

Figure 3.6—Historical total annual precipitation from the monthly gridded PRISM and Maurer et al. (2007) 

datasets for 1949–2010 for all six subregions of the Intermountain Adaptation Partnership region. The heavy 

lines are the 10-year rolling average from each dataset to show short-term trends.

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 39

The Southern Greater Yellowstone subregion includes 

Grand Teton National Park, and the Targhee and BridgerTeton National Forests. This subregion and the Middle 

Rockies are the coldest subregions (figs. 3.4, 3.5). Mean 

minimum temperatures in the Southern Greater Yellowstone 

subregion showed an increasing trend over the last 50 years 

of the historical period (fig. 3.4). Monahan and Fisichelli 

(2014) reported that recent annual mean temperatures (last 

10-, 20-, or 30-year periods) for Grand Teton National Park 

were higher than 90 percent of the historical temperatures 

over the 1901–2012 period. They also found that recent 

minimum temperatures in the coldest month (last 10-, 20-, 

or 30-year periods) were greater than 95 percent of the historical record. In contrast, maximum temperatures showed 

an increasing trend only during the last 25 years (fig. 3.5).

Climate in the Southern Greater Yellowstone subregion, 

as in the Middle Rockies, is strongly influenced by the 

mountains and interactions among topography, elevation, 

and aspect. Few mountains block the western passage 

of moist air from the Pacific Ocean to the Teton Range; 

consequently, the Teton Range, along with portions of 

southwestern Yellowstone National Park, are among the 

wettest areas in the larger Greater Yellowstone Area. Annual 

precipitation on the west side of the Teton Range can 

exceed 70 inches, with most of this precipitation falling as 

snow. In contrast, precipitation on the east side of the Teton 

Range can be as little as 19 inches (Davey et al. 2006). 

The Southern Greater Yellowstone subregion is the wettest 

in the IAP region (fig. 3.6). No trend is found in annual 

precipitation over the last 50 years although distinct wet and 

dry periods occurred. Davey et al. (2006) describe a 6-year 

drought (1999–2005) as the longest drought in the Grand 

Teton National Park since the Dust Bowl drought of the 

1930s.

Climate in the Uintas and Wasatch Front can be characterized as humid continental, with warm to hot summers, 

cold winters with abundant snowfall, and no distinct dry period (Gillies and Ramsey 2009). As with the Middle Rockies 

and the Southern Greater Yellowstone subregions, climate 

in this subregion is strongly influenced by the terrain and 

interactions among topography, elevation, and aspect. The 

Wasatch Range generally runs north to south, and the Uinta 

Mountains extend east and west. These ranges crest above 

10,000 feet, with the highest point of 13,498 feet at Kings 

Peak in the Uinta Mountains. As in most of the subregions, 

minimum temperatures trended upward over the last 50 

years (fig. 3.4). Mean maximum temperatures were between 

about 53 and 57 o

F, with no clear trends over the historical 

period (fig. 3.5). Gillies et al. (2012) concluded that during 

the last half-century, the proportion of winter (January–

March) precipitation falling as snow across Utah has 

decreased by 9 percent, the result of a significant increase 

in rainfall combined with a minor decrease in snowfall. 

Although warming temperatures play a role, climate features 

such as circulation patterns also contribute to these changes.

Mean annual precipitation within the Uintas and Wasatch 

Front subregion ranged from 10 inches to more than 40 

inches (fig. 3.6). Over the last 50 years, precipitation 

exhibited no annual trend, although dry or wet periods are 

evident. Morrisette (1988) reported that the 1982–1986 

precipitation reached 134 percent of normal in the Salt 

Lake drainage area, resulting in historically high levels in 

the Great Salt Lake. Using tree-ring analyses, DeRose et al. 

(2015) concluded that 1986 was the fourth wettest year over 

the last 1,200 years in the Bear River watershed. They also 

reported that although the later part of the 20th century was 

the second wettest period (40 years), the first half was the 

fourth driest period in the past 1,200 years. Using tree rings 

to reconstruct streamflow for the Weber River, Bekker et 

al. (2014) reported that the 20th-century instrumental record 

includes the fewest extreme dry years in the 576-year, treering-based reconstruction. In the Uinta Mountains, severe 

droughts have occurred, on average, two to five times per 

century (MacDonald and Tingstad 2007). Strong decreases 

in winter precipitation characterized the major droughts 

in the Uinta Mountains: the 1930s Dust Bowl event, the 

1976–1977 event, and the 1987–1989 event. These later two 

droughts were related to decreases in eastern Pacific Ocean 

sea surface temperatures (MacDonald and Tingstad 2007). 

Droughts in the Wasatch Range occurred during the 1400s 

and 1500s; even though droughts were fewer in the 1700s 

and 1800s, they had longer duration (Bekker et al. 2014). 

The tree-ring studies consistently emphasize the importance 

of local conditions in understanding climate-vegetation 

relationships (Louderback et al. 2015).

The Plateaus subregion encompasses three ecological 

provinces of the Colorado Plateau. The Uinta Basin is a 

gently rolling plateau that the Green River and its tributaries have eroded into many spectacular canyons (Leydsman 

McGinty and McGinty 2009). In the High Plateaus 

province, north-south trending faults and valleys separate 

individual plateaus, such as the Awapa, Aquarius, and 

Paunsaugunt Plateaus (Leydsman McGinty and McGinty 

2009). The Uinta Basin and the High Plateaus are cooler 

than the Canyonlands province. The Colorado River has 

eroded the Canyonlands into many deep, sheer-walled 

canyons, plateaus, mesas, buttes, and badlands. In addition, 

the La Sal and Abajo Mountains rise above the Colorado 

Plateau in southeastern Utah. Precipitation in this subregion 

ranges from 14 to 35 inches, with the highest precipitation 

in the High Plateaus province.

Minimum temperatures in the Plateaus subregion 

showed an upward trend over the entire historical period 

(fig. 3.4). Mean maximum temperature in the subregion 

ranged between 59 and 65 o

F over the last 50 years, showing a slight upward trend after 1980 (fig. 3.5). No trend is 

seen in precipitation over the last 50 years, although higher 

precipitation occurred in the 1980s (fig. 3.6). Tree-ring 

reconstruction of precipitation from 1200–2001 in the Uinta 

Basin indicates significant precipitation variability at interannual to decadal scales, with more severe dry events prior 

to 1900 than after (Gray et al. 2004).

The Great Basin and Semi Desert subregion has great 

climatic diversity (Svejcar et al. 2016). The surrounding 

Chapter 3: Historical and Projected Climate
40 USDA Forest Service RMRS-GTR-375. 2018

mountains, as well as the mountains within, strongly influence the climate of this subregion. A series of north-south 

mountain ranges within the subregion are interspersed 

among low-elevation basins, resulting in wide local variations in temperature and precipitation (fig. 3.1). Elevation 

ranges from less than 1,500 feet to more than 10,000 feet. 

Extreme temperatures can range from -15 to 120 oF (WRCC 

2016b,c).

The Great Basin and Semi Desert subregion is the warmest of the subregions. For the larger Southwest region in the 

United States, Kunkel et al. (2013) reported an increase in 

mean annual temperature, with greater warming for minimum temperature than maximum temperature, over the last 

115 years. That pattern for minimum and maximum monthly 

temperature was also seen in this subregion; mean minimum 

temperatures ranged from 30 to 38 oF (fig. 3.4) and mean 

maximum temperatures from 60 to 66 oF (fig. 3.5).

The primary source of moisture for the Great Basin and 

Semi Desert subregion is the Pacific Ocean, with seasonal 

monsoonal influences from the Gulf of Mexico. Much of the 

moisture from the Pacific Ocean is lost through orographic 

precipitation as the moisture flows upward and then over the 

bordering Sierra Nevada and Cascade Range. Mean annual 

precipitation varied from less than 8 inches to more than 

15 inches over the last 50 years (fig. 3.6), with wet and dry 

years evident. Annual snowfall ranges from less than 1 inch 

to 124 inches (WRCC 2016b,c).

The Intermountain Semi Desert subregion includes 

two distinct areas: the large valley encompassing the 

Snake River plains in Idaho, and the southwestern area 

in Wyoming (Chapter 2). The long, large valley in Idaho 

gradually rises in elevation from 3,300 feet in the Magic 

Valley, through the Lower Snake River Plain, to the eastern 

end of the Upper Snake River Plain at 5,600 feet (Andretta 

and Geerts 2010). Swan Falls, on the Snake River in Idaho, 

has a mean annual temperature of 55 o

F (WRCC 2016a). 

The Central Mountains, where the Boise, Payette, SalmonChallis, and Sawtooth National Forests are located, bound 

this valley to the north. To the south and east of this subregion lies the Southern Highlands at elevations from 6,500 to 

8,200 feet, Eastern Highlands, and Upper Snake Highlands 

of Idaho. As with the Great Basin and Semi Desert subregion, topography plays a role in the climate; however, with 

fewer barriers to the west, this area of the subregion receives 

greater moisture (fig. 3.2).

The Wyoming portion of this subregion encompasses the 

Green River Basin, a valley bounded on the northern edges 

by the Gros Ventre Mountains to the west and the Wind 

River Mountains to the east. The nearly 4,000-square-mile 

area is high, dry sagebrush-steppe, basically a desert where 

winter brings wind and cold, and little snow (Ostlind 2011). 

Temperatures are cooler in the Wyoming section than in the 

Idaho valley (fig. 3.1); mean annual temperature for Big 

Piney in the northern part of Green River Basin is 36 o

F, 

making for a short growing season. Winter extremes can 

reach -50 oF as cold air settles in the Green River Basin.

Mean minimum temperatures for this subregion showed 

a slight warming trend over the 1949–2010 period (fig. 

3.4). Mean maximum temperatures during this time ranged 

from about 55 to 60 oF, with little trend (fig. 3.5). Hoekema 

and Sridhar (2011) reported regional warming in the Snake 

River Basin, particularly in spring, over the last 35 years. 

This subregion and the Great Basin and Semi Desert are the 

driest subregions. Annual precipitation in the Intermountain 

Semi Desert subregion is generally between 8 and 12 inches 

(fig. 3.6). Precipitation showed no trend over the historical 

period.

Projected Climate

Changes in annual and seasonal temperature and precipitation are summarized by subregion in table 3.3. Trends in 

annual and seasonal temperature and precipitation projections are shown as figures for each subregion (see box 3.1 

for more information on the format of these subregional 

figures): Middle Rockies (figs. 3.7–3.9), Southern Greater 

Yellowstone (figs. 3.10–3.12), Uintas and Wasatch Front 

(figs. 3.13–3.15), Plateaus (figs. 3.16–3.18), Great Basin 

and Semi Desert (figs. 3.19–3.21), and Intermountain Semi 

Desert (figs. 3.22–3.24).

In the future, all subregions in the IAP are projected 

to see increases in annual and seasonal minimum and 

maximum temperatures, with greater changes under the 

RCP 8.5 scenario by 2100 than under the RCP 4.5 scenario 

(table 3.3). Within each subregion, temperatures vary 

greatly across landscapes, the result of topography and 

aspect. In the Middle Rockies, the projected increase in 

minimum temperature under the RCP 8.5 scenario will 

bring the subregional median temperature above freezing 

(fig. 3.7a); this projected increase suggests that for some 

areas in the IAP region, a biologically meaningful threshold could be crossed. Similar patterns for an increase in 

median minimum temperature above freezing occur in the 

Southern Greater Yellowstone subregion under the RCP 

8.5 scenario only (fig. 3.10), and Uintas and Wasatch Front 

(fig. 3.13), the Plateaus (fig. 3.16), and the Intermountain 

Semi Desert subregions (fig. 3.22) under both scenarios. For 

most subregions, annual precipitation projections are highly 

variable with no discernible trend over time or between 

the two scenarios. However, slight increases in annual precipitation are projected under the RCP 8.5 scenario for the 

Middle Rockies, the Southern Greater Yellowstone, and the 

Intermountain Semi Desert subregions (figs. 3.7, 3.10, 3.22), 

which lie in the northern part of the IAP region.

Seasonal temperatures across the subregions are projected to increase and may cross biologically meaningful 

thresholds in particular seasons (table 3.3). Minimum 

seasonal temperatures are projected to rise in all seasons 

across all subregions under both the RCP 4.5 and RCP 

8.5 scenarios (figs. 3.8, 3.11, 3.14, 3.17, 3.20, 3.23). 

Maximum seasonal temperatures are also projected to rise 

in all seasons under both RCP 4.5 and RCP 8.5 across all 

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 41

Table 3.3—Summary of projected changes in annual and seasonal temperature, and precipitation for each Intermountain 

Adaptation Partnership subregion.

Subregion Temperature Precipitation Seasonality

Middle Rockies By 2100, median maximum 

temperature is projected to rise 

about 6 °F under RCP 4.5 and 

about 10 °F under RCP 8.5; 

the two ensemble projections 

begin to diverge after 2045.

Median minimum temperature 

is projected to rise about 5 °F 

under RCP 4.5 and about 10 °F 

under RCP 8.5.

Annual precipitation 

projections are highly 

variable with no discernible 

trend under RCP 4.5 and 

a slight increasing trend 

under RCP 8.5.

Maximum temperatures are projected to 

increase by 5 to 10 °F across the seasons. 

The greatest departure from historical 

seasonal minimum temperatures occurs 

in summer. Over the historical period, 

summer minimum temperatures ranged 

around the mid- to upper 30s. By 2040, 

the projected median is 40 °F and rises to 

nearly 50 °F under the RCP 8.5 scenario 

by 2100 (fig. 3.9). By 2100, the median 

projections for spring, summer, and fall 

under the RCP 8.5 scenario are outside of 

historical ranges.

Southern Greater 

Yellowstone

By 2100, median maximum 

temperature is projected to rise 

about 5 °F under RCP 4.5 and 

about 11 °F under RCP 8.5; 

projections for the two RCPs 

begin to diverge around 2040.

By 2100, median minimum 

temperature is projected to 

increase about 6 °F under RCP 

4.5 and about 12 °F under 

RCP 8.5. Median minimum 

temperatures are projected to 

remain below freezing under 

RCP 4.5. However, minimum 

temperatures are likely to rise 

to just under freezing by 2100 

under RCP 8.5.

Annual precipitation 

projections are highly 

variable with no discernible 

trend under RCP 4.5 and 

a slight increasing trend 

under RCP 8.5.

Maximum temperature is projected 

to increase in all seasons, with winter 

temperatures rising about 3 °F and all 

other seasons rising about 5 °F under 

RCP 4.5 by the end of the 21st century. 

Under the warmest scenario, seasonal 

temperatures increase about 10 °F in 

winter, spring, and fall, but by more than 

12 °F in summer by the end of the 21st

century. Median minimum temperatures 

for all seasons by the 2080s are projected 

to be outside of historical ranges in the 

warmest scenario. Median minimum 

spring and fall temperatures are projected 

to increase, such that some projections 

rise above freezing by the end of the 21st

century under the RCP 8.5 scenario.

Uintas and 

Wasatch Front

By 2100, median maximum 

temperature is projected to 

rise about 5 °F under RCP 4.5 

and about 11 °F under RCP 

8.5. Projections for the two 

scenarios begin to diverge 

around 2040. By 2100, median 

minimum temperature is 

projected to rise about 5 °F 

under RCP 4.5 and about 12 

°F under RCP 8.5. Median 

minimum temperatures are 

projected to rise above freezing 

in both scenarios (by 2050 

under RCP 8.5 and by 2075 

under RCP 4.5). 

Annual precipitation 

projections are highly 

variable with no discernible 

trends. 

Maximum temperatures are projected 

to increase in all seasons, with winter 

temperatures rising about 4 °F and all 

other seasons rising about 6 °F under 

RCP 4.5 by the end of the 21st century. 

Maximum median temperatures by the 

2080s are outside of the historical range 

of values for all seasons in the warmest 

scenario. Median minimum spring and fall 

temperatures are projected to rise above 

freezing by the 2080s in both scenarios. 

The greatest departure from historical 

seasonal minimum temperatures occurs in 

summer.

Chapter 3: Historical and Projected Climate
42 USDA Forest Service RMRS-GTR-375. 2018

subregions (figs. 3.9, 3.12, 3.15, 3.18, 3.21, 3.24). Thus, the 

frequency of days with extreme heat in summer is likely to 

increase. Winter precipitation is an important reservoir for 

mountain and surrounding lower elevation communities. 

Few subregional or site-specific projections for snowpack 

have been made for the IAP region. For the Wasatch Range 

and Uinta Mountains, Klos et al. (2014) used only RCP 

8.5 and 20 climate models (similar to the projections used 

in this chapter), and they report that these ranges will have 

fall-through-spring temperatures such that wintertime precipitation will begin to shift from strongly snow dominated 

to a mixed rain-snow regime by the mid-21st century. The 

shoulder months of November and March will shift to rain, 

with December through February retaining a snow-dominated system longer. For additional discussion of snowpack and 

climate change, see Chapter 4. Also see Rice et al. (2017) 

for a review of climate change literature for the Uintas and 

Wasatch Front area.

Subregion Temperature Precipitation Seasonality

Plateaus By 2100, median maximum 

temperature is projected to rise 

about 5 °F under RCP 4.5 and 

about 10 °F under RCP 8.5. 

By 2100, median minimum 

temperature is projected to rise 

about 5 °F under RCP 4.5 and 

about 12 °F under RCP 8.5; 

the two ensemble projections 

begin to diverge after 2050. 

By 2050, median minimum 

temperature is projected to 

rise above freezing in both 

scenarios. 

Precipitation projections 

are highly variable with 

no discernible trend over 

time or between the two 

scenarios.

Maximum temperature is projected to 

increase in all seasons by about 5 °F 

under RCP 4.5 and by about 10 °F under 

RCP 8.5 by the end of the 21st century. 

The greatest departure from historical 

temperatures by 2100 is projected 

to occur in summer, where median 

temperatures rise above 95 °F under 

the RCP 8.5 scenario. Projected median 

maximum temperatures for winter, spring 

and autumn are also outside of historical 

ranges by end of the 21st century. The 

greatest departure from historical seasonal 

minimum temperatures is projected to 

occur in summer. Minimum temperatures 

in summer are projected to rise about 6 

°F by 2100 under RCP 4.5 and over 10 

°F under RCP 8.5, with the variation well 

outside of the historical ranges.

Great Basin and 

Semi Desert

By 2100, median maximum 

temperature is projected to 

rise about 5 °F under the RCP 

4.5 scenario and about 10 °F 

under the RCP 8.5 scenario. 

Historically median minimum 

temperature has ranged around 

freezing; in the near future, 

it is projected to rise above 

freezing, and by end of century, 

is projected to increase by 6 

to 10 °F. The two ensemble 

projections begin to diverge 

after 2050. 

Precipitation projections 

are highly variable with 

no discernible trend over 

time or between the two 

scenarios.

Maximum temperature is projected to 

increase by 5 °F in winter and spring 

under the RCP 4.5 scenario and by 10 

°F under the RCP 8.5 scenario by the 

end of the 21st century. Summer and fall 

temperatures are projected to increase by 

12 °F by the end of the 21st century under 

the RCP 8.5 scenario. Median minimum 

spring temperatures rise above freezing 

for both scenarios by 2100 and for the 

RCP 8.5 scenario, temperatures approach 

40 °F. Median minimum and maximum 

projections for the both scenarios in 

all seasons by 2100 are outside of the 

historical range. 

Intermountain 

Semi Desert

By the mid-21st century, 

median maximum temperature 

is projected to rise about 5 °F 

under RCP 4.5 and about 10 °F 

under the RCP 8.5.

Median minimum temperature 

is projected to rise about 5 °F 

under RCP 4.5 and about 11 

°F under RCP 8.5. By 2100, 

the projected changes for 

minimum temperature rise 

above freezing. 

The highly variable 

precipitation projections 

show no discernible trend 

over time under the RCP 

4.5 and suggest a slight 

increase under the RCP 8.5 

scenario. 

Maximum temperature increases in all 

seasons to the end of the 21st century 

in both climate scenarios. The greatest 

departure from historical temperatures 

by 2100 occurs in summer under RCP 

8.5, when projected mean temperatures 

approach 95 °F, nearly 15 °F above 

historical temperature. Median minimum 

seasonal temperatures are projected to 

rise in all seasons. Median minimum and 

maximum values for all seasons under 

the RCP 8.5 scenario are outside of the 

historical ranges by 2100.

Table 3.3—Continued.

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 43

Box 3.1—Template for Projected Climate Change Figures

For each of the six subregions, a common template for figures has been used to describe the projected climate. 

The first figure for each subregion (figs. 3.7, 3.10, 3.13, 3.16, 3.19, 3.22) shows the historical simulations and 

projections for annual daily minimum and maximum mean temperatures (oF), and total annual precipitation (inches) 

under the RCP 4.5 and RCP 8.5 scenarios based on the CMIP5 BCSD data. These figures show the historical climate 

simulations by the CMIP5 models, which reflect the pre-2010 climate forcings. These historical simulations are bias 

corrected and downscaled in the same manner as model future projections. In these figures, we overlaid the gridded 

historical observation data (blue line) from Maurer et al. (2002). In most regions, the historical simulated minimum 

and maximum temperatures and annual precipitation are less variable than the historical observed gridded climate. 

The future projections are shown in colors: red for RCP 8.5 and yellow for RCP 4.5. The ensemble median from all 

20 models for each scenario is shown in the heavy line; the 5th- and 95th-percent quantiles for all models are shown 

by the shaded area. Typically, climate projections under the higher emissions scenario (RCP 8.5) will indicate a 

higher temperature by 2100 than climate projections under the RCP 4.5 scenario.

The second figure for each subregion (figs. 3.8, 3.11, 3.14, 3.17, 3.20, 3.23) shows the seasonal daily minimum 

temperature (o

F) for the historical and projected period 1950–2100. Winter is defined as the months of December, 

January, and February. Spring is defined as March, April, and May; summer as June, July, and August; and fall 

as September, October, and November. We use box plots here, where each box is an aggregation of 20 years of 

modeled historical or projected seasonal data. For example, the box labeled “1960” represents the seasonal average 

of 1950 to 1969. We used the 20-year period here to explore the temporal changes over this century. The modeled 

historical boxes are gray, and boxes for projections use the same colors as in other figures: yellow for RCP 4.5 and 

red for RCP 8.5. The central line in each box is the median, indicating the same number of modeled historical or 

projections above and below this line. The hinges or edges of the boxes are the first and third quartiles. Whiskers 

extend past the first and third quartile by 1.5 times the interquartile range. 

The third figure for each subregion (figs. 3.9, 3.12 3.15, 3.18, 3.21, 3.24) shows the seasonal daily maximum 

temperature (o

F) for the historical and projected period. These figures are set up in the same way as the second 

figures. There is large variability and no discernible trend in the seasonal precipitation projections, and hence, less 

confidence overall in the finer scale precipitation projections; these figures are not shown here.

Summary and Conclusions

For this overview, the projected climate was derived from 

climate models in the CMIP5 database, which was used in 

the most recent IPCC reports. We quantified changes in temperature and precipitation by the 2040 period (2030–2059) 

and 2080 period (2070–2099). Over the next 100 years, 

annual minimum and maximum temperatures are projected 

to rise by as much as 10 °F in the IAP region. Projections 

for annual precipitation are highly variable. For most 

subregions in the IAP area, precipitation remains variable; 

slight increases in total annual precipitation are projected 

for the Middle Rockies, Southern Greater Yellowstone, 

and Intermountain Semi Desert subregions under the RCP 

8.5 scenario. As with annual temperature, winter, spring, 

summer, and fall temperatures are projected to increase, 

with summer temperatures showing the greatest increases 

in several subregions. For many subregions, the seasonal 

temperatures by end of century are outside of the historical 

observed ranges. Many of the resource chapters draw from 

existing scientific literature that used climate projections 

from the 2007 IPCC reports (the CMIP3 database). In 

mid-century (2040–2060), CMIP3 and CMIP5 temperature 

projections are similar. However, CMIP5 precipitation projections appear to be slightly wetter than those in CMIP3.

Acknowledgments

We acknowledge the World Climate Research 

Programme’s Working Group on Coupled Modelling, 

which is responsible for CMIP, and we thank the climate 

modeling groups (listed in Appendix 2) for producing 

and making available their model output. For CMIP, the 

U.S. Department of Energy’s Program for Climate Model 

Diagnosis and Intercomparison provides coordinating 

support and led development of software infrastructure in 

partnership with the Global Organization for Earth System 

Science Portals. Contributions from Marian Talbert were 

supported by the Department of the Interior’s North Central 

Climate Science Center. We appreciate the contributions 

of Jeff Morisette to the development of the chapter and the 

workshop presentations.

Chapter 3: Historical and Projected Climate
44 USDA Forest Service RMRS-GTR-375. 2018

Figure 3.7—Historical modeled and projected annual mean monthly minimum temperature, 

annual mean monthly maximum temperature, and total annual precipitation for 1950–2100 

under RCP 4.5 and RCP 8.5 emissions scenarios based on CMIP5 data for the Middle Rockies 

subregion of the Intermountain Adaptation Partnership region. Historical annual data from the 

gridded Maurer et al. (2007) dataset are also shown. See box 3.1 for further explanation. 

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 45

Figure 3.9—Historical 

modeled and 

projected seasonal 

mean monthly 

maximum 

temperature for 

1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios 

for the Middle 

Rockies subregion 

of the Intermountain 

Adaptation 

Partnership region. 

See box 3.1 for 

further explanation.

Figure 3.8—Historical 

modeled and 

projected seasonal 

mean monthly 

minimum 

temperature for 

1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios 

for the Middle 

Rockies subregion 

of the Intermountain 

Adaptation 

Partnership region. 

See box 3.1 for 

further explanation.

Chapter 3: Historical and Projected Climate
46 USDA Forest Service RMRS-GTR-375. 2018

Figure 3.10—Historical modeled and projected annual mean monthly minimum temperature, annual 

mean monthly maximum temperature, and total annual precipitation for 1950–2100 under RCP 4.5 

and RCP 8.5 emissions scenarios based on CMIP5 data for the Southern Greater Yellowstone subregion 

of the Intermountain Adaptation Partnership region. Historical annual data from the gridded Maurer et 

al. (2007) dataset are also shown. See box 3.1 for further explanation.

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 47

Figure 3.11— Historical 

modeled and projected 

seasonal mean monthly 

minimum temperature 

for 1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios for 

the Southern Greater 

Yellowstone subregion 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Chapter 3: Historical and Projected Climate

Figure 3.12—Historical 

modeled and projected 

seasonal mean monthly 

maximum temperature 

for 1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios for 

the Southern Greater 

Yellowstone subregion 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.
48 USDA Forest Service RMRS-GTR-375. 2018

Figure 3.13—Historical modeled and projected annual mean monthly minimum temperature, annual 

mean monthly maximum temperature, and total annual precipitation for 1950–2100 under RCP 4.5 and 

RCP 8.5 emissions scenarios based on CMIP5 data for the Uintas and Wasatch Front subregion of the 

Intermountain Adaptation Partnership region. Historical annual data from the gridded Maurer et al. (2007) 

dataset are also shown. See box 3.1 for further explanation.

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 49

Figure 3.14— Historical 

modeled and projected 

seasonal mean 

monthly minimum 

temperature for 1950–

2100 under RCP 4.5 

and RCP 8.5 emissions 

scenarios for the 

Uintas and Wasatch 

Front subregion of 

the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Figure 3.15— Historical 

modeled and projected 

seasonal mean 

monthly maximum 

temperature for 1950–

2100 under RCP 4.5 

and RCP 8.5 emissions 

scenarios for the 

Uintas and Wasatch 

Front subregion of 

the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Chapter 3: Historical and Projected Climate
50 USDA Forest Service RMRS-GTR-375. 2018

Figure 3.16—Historical modeled and projected annual mean monthly maximum temperature, annual 

mean monthly minimum temperature, and total annual precipitation for 1950–2100 under RCP 

4.5 and RCP 8.5 emissions scenarios based on CMIP5 data for the Plateaus subregion of the 

Intermountain Adaptation Partnership region. Historical annual data from the gridded Maurer et al. 

(2007) dataset are also shown. See box 3.1 for further explanation.

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 51

Chapter 3: Historical and Projected Climate

Figure 3.18— Historical 

modeled and projected 

seasonal mean 

monthly maximum 

temperature for 1950– 

2100 under RCP 4.5 

and RCP 8.5 emissions 

scenarios for the 

Plateaus subregion 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Figure 3.17— Historical 

modeled and projected 

seasonal mean monthly 

minimum temperature 

for 1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios for 

the Plateaus subregion 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.
52 USDA Forest Service RMRS-GTR-375. 2018

Figure 3.19—Historical modeled and projected annual mean monthly minimum temperature, annual 

mean monthly maximum temperature, and total annual precipitation for 1950–2100 under RCP 

4.5 and RCP 8.5 emissions scenarios based on CMIP5 data for the Great Basin and Semi Desert 

subregion of the Intermountain Adaptation Partnership region. Historical annual data from the 

gridded Maurer et al. (2007) dataset are also shown. See box 3.1 for further explanation.

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 53

Figure 3.20—Historical 

modeled and projected 

seasonal mean monthly 

minimum temperature 

for 1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios for 

the Great Basin and 

Semi Desert region 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Figure 3.21—Historical 

modeled and projected 

seasonal mean monthly 

maximum temperature 

for 1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios for 

the Great Basin and 

Semi Desert subregion 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Chapter 3: Historical and Projected Climate
54 USDA Forest Service RMRS-GTR-375. 2018

Figure 3.22—Historical modeled and projected annual mean monthly minimum temperature, annual 

mean monthly maximum temperature, and total annual precipitation for 1950–2100 under RCP 4.5 

and RCP 8.5 emissions scenarios based on CMIP5 data for the Intermountain Semi Desert subregion of 

the Intermountain Adaptation Partnership region. Historical annual data from the gridded Maurer et al. 

(2007) dataset are also shown. See box 3.1 for further explanation.

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 55

Figure 3.23—Historical 

modeled and projected 

seasonal mean monthly 

minimum temperature 

for 1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios 

for the Intermountain 

Semi Desert subregion 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Figure 3.24— Historical 

modeled and projected 

seasonal mean monthly 

maximum temperature 

for 1950–2100 under 

RCP 4.5 and RCP 8.5 

emissions scenarios 

for the Intermountain 

Semi Desert subregion 

of the Intermountain 

Adaptation Partnership 

region. See box 3.1 for 

further explanation.

Chapter 3: Historical and Projected Climate
56 USDA Forest Service RMRS-GTR-375. 2018

References

Andretta, T.A.; Geerts, B. 2010. Heavy snowfall produced by 

topographically induced winds in the Snake River Plain of 

Eastern Idaho. Part I: Observational analysis. E-Journal of 

Severe Storms Meteorology. 5. http://www.ejssm.org/ojs/index.

php/ejssm/article/viewArticle/56/74 [Accessed July 13, 2017].

Bekker, M.F.; DeRose, R.J.; Buckley, B.M.; [et al.]. 2014. A 576-

year Weber River streamflow reconstruction from tree rings 

for water resource risk assessment in the Wasatch Front, Utah. 

Journal of the American Water Resources Association. 50: 

1338–1348.

Davey, C.A.; Redmond, K.T.; Simeral, D.B. 2006. Weather and 

climate inventory, National Park Service, Rocky Mountain 

Network. Natural Resource Technical Report NPS/GRYN/

NRTR—2006/001. Fort Collins, CO: National Park Service. 83 

p.

DeRose, R.J.; Bekker, J.F.; Wang, S.-Y.; [et al.]. 2015. A 

millennium-length reconstruction of Bear River stream flow, 

Utah. Journal of Hydrology. 529: 524–534.

Gillies, R.R.; Ramsey, R.D. 2009. Climate of Utah. In: Banner, 

R.E., Baldwin, B.D., Leydsman McGinty, E.K., project 

coordinators. Rangeland resources of Utah. Logan, UT: 

Utah State University, Cooperative Extension Service. http://

extension.usu.edu/rangelands/ou-files/RRU_Introduction.pdf

[Accessed December 5, 2016].

Gillies, R.R.; Wang, S-Y.; Booth, M.R. 2012. Observational and 

synoptic analyses of the winter precipitation regime change 

over Utah. Journal of Climate. 25: 4679–4698.

Gray, S.T.; Jackson, S.T.; Betancourt, J.L. 2004. Tree-ring based 

reconstructions of interannual to decadal scale precipitation 

variability for northeastern Utah since 1226 A.D. Journal of 

American Water Resources Association. 40: 947–960.

Hoekema, D.J.; Sridhar, V. 2011. Relating climatic attributes 

and water resources allocation: A study using surface 

water supply and soil moisture indices in the Snake River 

Basin, Idaho. Water Resources Research. 47: W07536. 

doi:10.1029/2010WR009697.

Houghton, J.T.; Ding, Y.; Griggs, D.J.; [et al.], eds. 2001. Climate 

change 2001: The scientific basis. Contribution of working 

group I to the third assessment report of the Intergovernmental 

Panel on Climate Change. Cambridge, United Kingdom and 

New York, NY: Cambridge University Press. 881 p.

Intergovernmental Panel on Climate Change Data Distribution 

Center [IPCC]. 2016. Scenario process of AR5. http://sedac.

ipcc-data.org/ddc/ar5_scenario_process/index.html [Accessed 

March 22, 2017].

Isaak, D.J.; Luce, C.H.; Rieman, B.E.; [et al.]. 2010. Effects 

of climate change and wildfire on stream temperatures 

and salmonid thermal habitat in a mountain river network. 

Ecological Applications. 20: 1350–1371.

Klos, P.Z.; Link, T.E.; Abatzoglou, J.T. 2014. Extent of the 

rain-snow transition zone in the western U.S. under historic 

and projected climate. Geophysical Research Letters. 41: 

4560–4568.

Kunkel, K.E.; Stevens, L.E.; Stevens, S.E.; [et al.]. 2013. 

Regional climate trends and scenarios for the U.S. National 

Climate Assessment: Part 5. Climate of the Southwest U.S. 

NOAA Technical Report NESDIS 142-5. Washington, DC: 

National Oceanic and Atmospheric Administration, National 

Environmental Satellite, Data, and Information Service. 87 p.

Leydsman McGinty, E.I.; McGinty, C.M. 2009. The physiography 

of Utah. In: Banner, R.E.; Baldwin, B.D.; Leydsman McGinty, 

E.K., project coordinators. Rangeland resources of Utah. 

Logan, Utah: Logan, UT: Utah State University, Cooperative 

Extension Service. http://extension.usu.edu/rangelands/ou-files/

RRU_Introduction.pdf [Accessed December 5, 2016].

Littell, J.S.; Elsner, M.M.; Mauger, G.S.; [et al.]. 2011. Regional 

climate and hydrologic change in the northern US Rockies and 

Pacific Northwest: internally consistent projections of future 

climate for resource management. Unpublished project report. 

http://cses.washington.edu/picea/USFS/pub/Littell_etal_2010 

[Accessed December 5, 2016].

Louderback, L.A.; Rhode, D.; Madsen, D.B.; Metcalf, M. 2015. 

Rapid vegetation shifts in the Uinta Mountains (Utah and 

Wyoming, USA) during the Late Pleistocene and Holocene. 

Palaeogeography, Palaeoclimatology, Palaeoecology. 438: 

327–343.

MacDonald, G.M.; Tingstad, A.H. 2007. Recent and 

multicentennial precipitation variability and drought occurrence 

in the Uinta Mountains region, Utah. Arctic, Antarctic, and 

Alpine Research. 39: 549–555.

Maurer, E.P.; Wood, A.W.; Adam, J.C.; [et al.]. 2002. A long-term 

hydrologically based dataset of land surface fluxes and states 

for the conterminous United States. Journal of Climate. 15: 

3237–3251.

Maurer, E.P.; Brekke, L.; Pruitt, T.; Duffy, P.B. 2007. Fineresolution climate projections enhance regional climate change 

impact studies. Eos Transactions of the American Geophysical 

Union. 88: 504.

Meehl, G.A.; Covey, C.; Delworth, T.; [et al.]. 2007. The WCRP 

CMIP3 multimodel data set. Bulletin of the American 

Meteorological Society. 88: 1383–1394.

Monahan, W.B.; Fisichelli, N.A. 2014. Climate exposure of US 

national parks in a new era of change. PloS One. 9: e101302. 

https://doi.org/10.1371/journal.pone.0101302

Moss, R.; Babiker, W.; Brinkman, S.; [et al.]. 2008. Towards 

new scenarios for the analysis of emissions, climate change, 

impacts and response strategies. IPCC Expert Meeting Report. 

Technical Summary. Geneva, Switzerland: Intergovernmental 

Panel on Climate Change. 25 p.

Moss, R.H.; Edmonds, J.A.; Hibbard, K.A.; [et al.]. 2010. The 

next generation of scenarios for climate change research and 

assessment. Nature. 463: 747.

Morrisette, P.M. 1988. The rising level of the Great Salt 

Lake: Impacts and adjustments. Bulletin of the American 

Meteorological Society. 69: 1034–1040.

Nakićenović, N.; Davidson, O.; Davis, G.; [et al.]. 2000. Special 

report on emissions scenarios: A special report of Working 

Group III of the Intergovernmental Panel on Climate Change. 

Cambridge, United Kingdom: Cambridge University Press. 

599 p.

Ostlind, E. 2011. The Green River Basin: A natural history. 

Wheatland, WY: Wyoming State Historical Society. http://

www.wyohistory.org/encyclopedia/green-river-basin-naturalhistory [Accessed December 5, 2016].

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 57

Oyler, J.W.; Ballantyne, A.; Jencso, K.; [et al.]. 2015a. Creating a 

topoclimatic daily air temperature dataset for the conterminous 

United States using homogenized station data and remotely 

sensed land skin temperature. International Journal of 

Climatology. 35: 2258–2279.

Oyler, J.W.; Dobrowski, S.Z.; Ballantyne, A.P.; [et al.]. 2015b. 

Artificial amplification of warming trends across the mountains 

of the western United States. Geophysical Research Letters. 42: 

153–161.

PRISM Climate Group. 2014. Oregon State University. PRISM 4 

km climate data, 2014. http://prism.oregonstate.edu/ [Accessed 

March 31, 2016].

Rice, J.; Bardsley, T.; Gomben, P.; [et al.]. 2017. Assessment 

of watershed vulnerability to climate change for the UintaWasatch-Cache and Ashley National Forests, Utah. Gen. Tech. 

Rep. RMRS-GTR-362. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 

111 p.

Rogelj, J.; Meinshausen, M.; Knutti, R. 2012. Global warming 

under old and new scenarios using IPCC climate sensitivity 

range estimates. Nature Climate Change. 2: 248–253.

Solomon, S.; Qin, D.; Manning, M.; [et al.], eds. 2007. Climate 

change 2007: The physical science basis. Contribution of 

Working Group I to the fourth assessment report of the 

Intergovernmental Panel on Climate Change. Cambridge, UK 

and New York, NY: Cambridge University Press. 996 p.

Stocker, T.F.; Qin, D.; Plattner, G.-K.; [et al.], eds. 2013. Climate 

change 2013: The physical science basis. Contribution 

of Working Group I to the fifth assessment report of the 

Intergovernmental Panel on Climate Change. Cambridge, UK 

and New York, NY: Cambridge University Press. 1,535 p.

Svejcar, T.; Angell, R.; James, J. 2016. Spatial and temporal 

variability in minimum temperature trends in the western U.S. 

sagebrush steppe. Journal of Arid Environments. 133: 125–133.

van Vuuren, D.P.; Edmonds, J.; Kainuma, M.; [et al.]. 2011. The 

representative concentration pathways: An overview. Climatic 

Change. 109: 5–31.

Walsh, J.; Wuebbles, D.; Hayhoe, K.; [et al.]. 2014. Our changing 

climate. In: Melillo, J.M.; Richmond, T.C.; Yohe, G.W., 

eds. Climate change impacts in the United States: The Third 

National Climate Assessment. Washington, DC: U.S. Global 

Change Research Program. p. 19–67.

Western Regional Climate Center [WRCC]. 2016a. Climate of 

Idaho. https://wrcc.dri.edu/Climate/narrative_id.php [Accessed 

November 19, 2016].

Western Regional Climate Center [WRCC]. 2016b. Climate 

of Nevada. https://wrcc.dri.edu/Climate/narrative_wy.php 

[Accessed November 19, 2016].

Western Regional Climate Center [WRCC]. 2016c. Climate of 

Utah. https://wrcc.dri.edu/Climate/narrative_ut.php [Accessed 

November 19, 2016].

Chapter 3: Historical and Projected Climate
58 USDA Forest Service RMRS-GTR-375. 2018

Appendix 2—Models Included in the Climate Analysis for 

the Intermountain Adaptation Partnership Region

Following are the climate models we used in the Intermountain Adaptation Partnership Region climate analysis, and 

the institutions that developed them. CMIP5 climate projections for RCP 4.5 and RCP 8.5 scenarios were obtained for 

these models using the downscaled CMIP3 and CMIP5 climate and hydrology projections archive at: http://gdo-dcp.ucllnl.

org/downscaled_cmip_projections. The first model run was selected for this analysis. Model runs were available for both 

RCP 4.5 and RCP 8.5 scenarios, except for the NASA Goddard Institute for Space Studies models GISS-E2-H-CC and 

GISS-E2-R-CC.

Institution Climate model

Commonwealth Scientific and Industrial Research Organization and Bureau of 

Meteorology, Australia

ACCESS1-0

ACCESS1-3

Beijing Climate Center, China Meteorological Administration bcc-csm1-1

Beijing Climate Center, China Meteorological Administration bcc-csm1-1-m

Canadian Centre for Climate Modelling and Analysis CanESM2

National Center for Atmospheric Research CCSM4

Community Earth System Model Contributors CESM1-BGC

CESM1-CAM5

Centro Euro-Mediterraneo per i Cambiamenti Climatici CMCC-CM

Centre National de Recherches Météorologiques/Centre Européen de Recherche et 

Formation Avancée en Calcul Scientifique

CNRM-CM5

Commonwealth Scientific and Industrial Research Organization, Queensland Climate 

Change Centre of Excellence

CSIRO-Mk3-6-0

EC-EARTH consortium EC-EARTH

Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid 

Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, and Center for 

Earth System Science, Tsinghua University

FGOALS-g2

Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid 

Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, and Center for 

Earth System Science, Tsinghua University

FGOALS-s2

The First Institute of Oceanography, State Oceanic Administration, China FIO-ESM

NOAA Geophysical Fluid Dynamics Laboratory GFDL-CM3

GFDL-ESM2G

GFDL-ESM2M

NASA Goddard Institute for Space Studies GISS-E2-H-CC

GISS-E2-R

GISS-E2-R-CC

Met Office Hadley Centre (additional HadGEM2-ES realizations contributed by Instituto 

Nacional de Pesquisas Espaciais)

HADGEM2-AO

Met Office Hadley Centre (additional HadGEM2-ES realizations contributed by Instituto 

Nacional de Pesquisas Espaciais)

HADGEM2-CC

Met Office Hadley Centre (additional HadGEM2-ES realizations contributed by Instituto 

Nacional de Pesquisas Espaciais)

HADGEM2-ES

Chapter 3: Historical and Projected Climate
USDA Forest Service RMRS-GTR-375. 2018 59

Institute for Numerical Mathematics INM-CM4

Institut Pierre-Simon Laplace IPSL-CM5A-LR

IPSL-CM5A-MR

IPSL-CM5B-LR

Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research 

Institute (The University of Tokyo), and National Institute for Environmental Studies

MIROC-ESM

MIROC-ESM-CHEM

Atmosphere and Ocean Research Institute (The University of Tokyo), National Institute for 

Environmental Studies, and Japan Agency for Marine-Earth Science and Technology

MIROC5

Max Planck Institute for Meteorology (MPI-M) MPI-ESM-LR

Max Planck Institute for Meteorology (MPI-M) MPI-ESM-MR

Meteorological Research Institute MRI-CGCM3

Norwegian Climate Centre NorESM1-M

Norwegian Climate Centre MorESM1-ME

Chapter 3: Historical and Projected Climate
60 USDA Forest Service RMRS-GTR-375. 2018

Introduction

Water is critical to life, and many of the effects of climate 

change on ecosystems are mediated through altered hydrology. Snow accumulation and melt are consistently cited as 

the most important changes to water in the western United 

States (Barnett et al. 2005; Service 2004), affecting when 

water will be available for forests, fish, and people. Changes 

in summer atmospheric circulation patterns may alter the 

ability of summer precipitation to provide a midsummer 

respite from seasonal drought and dampening of wildfire 

spread (IPCC 2013) (Chapter 8). Declining summer water 

contributions will challenge municipal and agricultural 

water supplies (Barnett and Pierce 2009; Dawadi and 

Ahmad 2012). Aquatic and terrestrial ecosystems—including riparian areas, wetlands, and groundwater-dependent 

ecosystems—will be affected by lower base flows (Kormos 

et al. 2016; Rood et al. 2008), earlier snowmelt (Luce et al. 

2014), increased periods of drought (Cayan et al. 2009), 

increased sediment delivery (Goode et al. 2012), and higher 

midwinter floods (Goode et al. 2013). Soils will likewise 

be affected by increased temperatures and shifts in precipitation and hydrological processes, with effects on physical 

and biological processes and attributes of soils.

This chapter describes potential changes to hydrological 

processes, groundwater resources, and soil attributes and 

processes in the Intermountain Adaptation Partnership (IAP) 

region with a changing climate. We specifically discuss 

potential changes in snowpack and glaciers, streamflow, 

drought, sediment yield, and groundwater recharge, and 

in soil temperature, moisture, carbon, nitrogen, biological 

activity, and chemical properties. The Soil Resources section 

concludes with an example vulnerability assessment method 

and application.

Hydrological Processes

Climate and Hydrological Processes

Warming temperatures are the most certain consequence 

of increased carbon dioxide in the atmosphere. The hydrological consequences of warmer temperatures include less 

Chapter 4: Effects of Climate Change on 

Hydrology, Water Resources, and Soil

Mark J. Muir, Charles H. Luce, Joseph T. Gurrieri, Marek Matyjasik, 

Jeffrey L. Bruggink, Stacey L. Weems, James C. Hurja, David B. Marr, 

and Sarah D. Leahy

snowpack and greater evaporative demand from the atmosphere. In general, snowpack depth, extent, and duration 

are expected to decrease, particularly at lower and middle 

elevations, because of a combination of less precipitation 

falling as snow (Pierce et al. 2008) and slightly earlier melt 

(Luce et al. 2014). The degree of change expected as a 

result of warming varies considerably over the landscape 

as a function of temperature (Luce et al. 2014). Places that 

are warm (near the melting point of snow) are expected to 

be more sensitive than places where temperatures remain 

subfreezing throughout much of the winter despite warming 

(Woods 2009).

The relationship of evapotranspiration (ET) to a warming 

climate is more complicated (Roderick et al. 2014). Warmer 

air can hold more water, which means that even if relative 

humidity stays constant, vapor pressure deficit—the difference between actual water content of the air and water 

content at saturation—increases. That difference between 

actual and saturation drives a water vapor gradient between 

leaves and the atmosphere that can draw more moisture out 

of the leaves. This is likely to cause more evaporation in a 

warmer climate (Cook et al. 2014; Dai 2013).

However, evaporation is an energy-intensive process, and 

there is only so much additional energy that will be available for evaporation. In addition, one needs to consider both 

the water balance and the energy balance when considering 

future warming (Roderick et al. 2015). The observation 

that temperatures are warmer during drought is related 

more generally to the lack of water to evaporate, leading to 

warmer temperatures, than to warmer temperatures causing 

faster evaporation (Yin et al. 2014). Unfortunately, when 

potential ET models based on air temperature (including 

Penman-Monteith) are applied as postprocessing to global 

climate model (GCM) calculations, an overestimate of increased ET is likely, because the energy balance is no longer 

tracked (Milly 1992; Milly and Dunne 2011). The reality is 

that most of the increased energy from increased longwave 

radiation will result in warming rather than increased evaporation (Roderick et al. 2015).

Precipitation has a direct effect on hydrological processes, although precipitation is less commonly discussed 

because climate change projections are uncertain (Blöschl 

and Montanari 2010; IPCC 2013). Figure 4.1 helps to illustrate how the IAP region is located in an area of high 
USDA Forest Service RMRS-GTR-375. 2018 61

uncertainty in regard to precipitation projections, slightly 

overlapping with projected increases to the north and 

drying to the south (Walsh et al. 2014). The bounds of 

uncertainty (-20 to +30 percent) are large, making it difficult to accurately project the effects of precipitation on 

many hydrological processes (e.g., floods, hydrological 

drought, snow accumulation, groundwater recharge). As 

a consequence, we use an ensemble average precipitation 

for streamflow projections here. In this assessment, we 

also discuss uncertainty surrounding the mean estimate to 

illustrate which processes or hydrological outcomes are 

most uncertain and where. Not all processes are sensitive 

to precipitation, and uncertainty in outcomes caused by 

uncertainty in precipitation is not the same everywhere for a 

given process.

Background information can help to clarify where and 

when some precipitation estimates may be more reliable 

than others. Two primary concepts are applied for precipitation change: dynamic (referring to changes in wind and 

atmospheric circulation) and thermodynamic (referring 

to how much water the air can hold) (Seager et al. 2010). 

Dynamic drivers of precipitation change include changes in 

global circulation patterns (e.g., the Hadley cell extent) and 

changes in mid-latitude storm tracks. Changes in teleconnection patterns (e.g., the North American Monsoon System 

[NAMS]) fall into this category and are very important for 

this region. Thermodynamic changes reflect the fact that the 

atmosphere can hold more water (Held and Soden 2006), 

leading to an expectation on the order of a 3.9 percent increase in precipitation per 1 °F of temperature change. There 

are, however, other physical limits on the disposition of 

energy driving the cycling of water in the atmosphere. These 

lead to estimates on the order of less than 1 percent per 1 °F 

of temperature change at the global scale, with individual 

grid cells being less or potentially negative, particularly over 

land (Roderick et al. 2014). Different approaches to scaling 

the thermodynamic contribution are a reason for differences 

among models, although the dynamic process modeling differences can be great as well.

One outcome of thermodynamically driven changes is 

that when precipitation occurs, the same total volume is 

expected to fall with greater intensity, leading to shorter 

events and longer dry periods between events. The number 

of consecutive dry days is projected to increase across the 

western United States, which will affect portions of the IAP 

region (fig. 4.1). In the Pacific Northwest, this projection 

is connected to an expected decrease in summer precipitation, but for the Southwest, it is more likely connected to a 

decrease in monsoonal moisture during the late spring (fig. 

4.2). In general, the NAMS is expected to weaken (IPCC 

2013), particularly in the early portion of the monsoon season (Cook and Seager 2013), which could have substantial 

effects across the southern portion of the IAP region. Late 

spring and early summer precipitation contributions can be 

an important determinant of the severity of summer drought 

and length of fire seasons (Abatzoglou and Kolden 2013). 

Pairing longer periods of precipitation deficit in summer 

with decreasing snowpack may be particularly challenging 

for vegetation and aquatic ecosystems.

Changes in orographic enhancement of precipitation over 

mountainous areas also have dynamic effects. Historical 

changes in westerly windflows have led to a decrease in 

the enhancement of winter precipitation by orographic 

lifting over mountain ranges (Luce et al. 2013), raising the 

question of whether such a pattern may continue into the 

future. There is general agreement among GCMs projecting 

further decreases in windspeed into the 21st century, but 

the correlation is applicable only to the northern portion 

of the IAP region. Westerly winds are strongly correlated 

with precipitation in mountainous areas (fig. 4.3), but valley 

precipitation is not, nor is precipitation in much of southern 

Idaho. The historical trend in westerlies was driven by pressure and temperature changes spatially consistent with those 

expected under a changing climate; however, the rapidity 

of the changes in the last 60 years may have been partly 

enhanced by normal climatic variability.

Dynamic downscaling using a regional climate model 

(RCM) with small (~8 mile) cells provides a means to 

estimate orographically induced precipitation, which cannot 

be simulated with the large cell size of GCMs. Although the 

GCM shows general moistening over most of the area, the 

RCM shows a pattern of drying or no change on the upwind 

side of major mountain ranges, with moistening limited to 

valleys in the lee. Because mountainous areas are where 

most of the precipitation falls (and streamflow originates), 

this is a potentially important aspect of future changes. The 

Variable Infiltration Capacity (VIC) model simulations 

Figure 4.1—Projected change in the number of consecutive 

dry days for 2071–2099 (compared to 1970–1999) for the 

RCP8.5 emissions scenario (from Walsh et al. [2014]).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
62 USDA Forest Service RMRS-GTR-375. 2018

variation will also differ from the northern to southern 

portions of the region. Fundamentally, topography is an 

important factor affecting seasonality, precipitation amount, 

and potential trends. Because most forests and generation 

of water supply are generally in mountainous areas, it is 

important to recognize how topography affects climate. 

Specific hydrological outcomes of interest are discussed in 

the following sections.

discussed later in this chapter do not include this effect, so 

for purposes of general discussion, it can be considered an 

additional source of uncertainty for precipitation.

The range of potential changes to climate is complex, 

particularly for such a varied landscape as the IAP region 

(fig. 4.2), and current climatological settings vary over 

the landscape at both large and small spatial scales. 

Precipitation seasonality and amount differ between mountain and valley locations. Trends and drivers for climatic 

Figure 4.2—Projected change in seasonal precipitation for 2071–2099 (compared to 1970–1999) under the 

RCP 8.5 emissions scenario (Walsh et al. 2014). Hatched lines indicate model agreement and nonhatched 

areas have the highest uncertainty. The Intermountain Adaptation Partnership region sits in an area of high 

uncertainty, between projected moistening to the north and drying to the south.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 63

Snowpack and Glaciers

Snowpack

Snowpack declines are among the most widely cited 

changes occurring with climate change, through the effect of 

warmer temperatures on the fraction of precipitation falling 

as snow (Barnett et al. 2008). About 70 percent of the water 

supply in the western United States is tied to mountain 

snowpacks (Service 2004), so changes in snowpack are 

highly relevant to municipal and agricultural water supplies 

and timing (Stewart et al. 2005).

Historical trends in snowpack accumulation have been 

negative across most of the western United States (Mote et 

al. 2005; Regonda et al. 2005). However, care must be taken 

when looking at individual sites, which can be influenced 

by site-specific effects such as vegetation changes, physical 

site changes, sensor changes, and measurement technique 

(Clayton and Julander 2015). Temperature sensitivity of 

the snowpack is highest in places that are already relatively 

warm (warm snowpacks), and warm snowpacks with high 

precipitation are likely to undergo some of the largest 

changes in snow storage as the climate warms (Luce et al. 

2014; Nolin and Daly 2006).

The most sensitive locations within the IAP region include the eastern Sierra Nevada and mid- to lower-elevation 

sites across Idaho, Utah, and Nevada (figs. 4.4–4.7). In 

contrast, many interior portions of the IAP region are cold 

enough to be relatively insensitive to warming and strongly 

sensitive to precipitation variation (Luce et al. 2014; Mote 

2006). At the coldest and highest elevations, in the Uinta, 

Teton, Wind River, and some central Idaho ranges, for 

instance, there could be increases in snow water equivalent 

(SWE) if precipitation increases (Rice et al. 2017). Despite 

warming temperatures, a large proportion of precipitation 

would still fall as snow in these areas. This means that 

the future of snow, and consequently hydrology in these 

regions, depends on one of the more uncertain parts of GCM 

projections: the precipitation.

Precipitation uncertainty can be substantial, but it does 

not translate into equal uncertainty in snowpack changes 

everywhere (fig. 4.8). We estimated sensitivity of April 1 

SWE using data from 524 snowpack telemetry (SNOTEL) 

stations across the western United States in a space-for-time 

model (Luce et al. 2014). This allowed us to determine 

where in the western United States snowpack was more 

sensitive to variability in precipitation or variability in 

temperature. We computed an index of uncertainty as the 

ratio (Ru

) of the effects on snow (ΔS) from the likely range 

of precipitation values (about ±7.5 percent for 1 standard 

deviation across models) in the numerator, to ΔS from the 

relatively certain temperature change in the denominator:

Ru

 = ΔS across precipitation uncertainty (+7.5%)

ΔS expected from warming

We found strong certainty of large changes in April 

1 SWE for the Cascade Range, Sierra Nevada, and the 

Southwest (Ru < 0.2). But we found substantial uncertainty 

(Ru > 0.6) in outcomes for interior locations such as the 

Greater Yellowstone Area and higher elevations in Idaho 

and Utah, where cold temperatures leave the snowpack 

more sensitive to precipitation than to temperature changes 

(fig. 4.8). The uncertainty ratio in these colder areas suggests that relatively large increases in precipitation could 

help counter the effects of warming on snowpack loss. 

These results are similar to those seen using a physically 

based model across the western United States (Gergel et al. 

2017).

Figure 4.3—Correlation 

of winter precipitation 

to winter westerly 

windspeed across the 

Pacific Northwest, 

showing snowpack 

telemetry (SNOTEL) 

and Historical Climate 

Network (HCN) 

stations (from Luce et 

al. [2013]).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
64 USDA Forest Service RMRS-GTR-375. 2018

Figure 4.4—Estimated April 1 snow water equivalent (SWE) 

sensitivity (percentage change) for a 5.5-°F increase in 

winter average temperature at each snowpack telemetry 

station (modified from Luce et al. [2014]).

Figure 4.5—Estimated April 1 snow water equivalent (SWE) 

sensitivity (absolute change in inches) for a 5.5-°F increase 

in winter average temperature at each snowpack telemetry 

station (modified from Luce et al. [2014]).

Figure 4.6—Estimated mean snow residence time sensitivity 

(percentage change) for a 5.5-°F increase in winter average 

temperature at each snowpack telemetry station (modified 

from Luce et al. [2014]).

Figure 4.7—Estimated mean snow residence time sensitivity 

(absolute change in days), for a 5.5-°F increase in winter 

average temperature at each snowpack telemetry station 

(modified from Luce et al. [2014]).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 65

Glaciers

Glaciers are limited throughout the IAP region but do occur in central Idaho, in western Wyoming, and in an isolated 

location at Wheeler Peak in Great Basin National Park (see 

maps at Portland State University 2009). Declines in the extent of glaciers in the Wind River Range have been observed 

over the 20th century (Marston et al. 1991).

Estimating future changes in glaciers is complex (Hall 

and Fagre 2003), but empirical relationships derived for 

glaciers indicate a brief future for them, with many glaciers becoming fragmented or disappearing by the 2030s. 

Increasing temperatures yield a rising equilibrium line 

altitude (ELA), decreasing the effective contributing area for 

each glacier as warming progresses. Warming of 5.5 °F can 

translate to an elevation rise of 1,000 to 1,600 feet in snowrain partitioning and summer temperatures. Those changes 

do not directly equate to a shift in ELA, which depends on 

the geometry and topography of the contributing cirque.

Temperate alpine glaciers are well known for being as, 

or more, sensitive to precipitation variations as they are 

to temperature variations (McCabe and Fountain 1995), 

which has very likely contributed to changes in glacial 

dynamics across the Pacific Northwest. Westerlies and their 

contribution to winter precipitation have changed over 

the northern part of the region since the 1940s (Luce et al. 

2013), and April 1 SWE at these elevations and latitudes 

is relatively insensitive to temperature. However, summer 

temperature is a strong predictor of glacial behavior, and 

changes in summer temperatures could affect the melt rate 

and additional snow contributions in glaciers because this 

area receives significant spring and summer precipitation 

(Hall and Fagre 2003).

Streamflow

Streamflow changes of significance for aquatic species, 

water supply, and infrastructure include annual yield, summer low flows (average, extreme), peakflows (scouring 

floods), peakflow seasonality, and center of runoff timing. 

Irrigation water for crops and urban landscapes is typically 

needed in summer months. Annual yield, summer low flows, 

and center of runoff timing are important metrics with 

respect to water supply, but they are most relevant to surface 

water supplies rather than groundwater supplies, although 

changes in long-term annual means could be informative for 

the latter. The mean summer yield (June through September) 

is used for summer low flows. Center of runoff timing is the 

date on which 50 percent of the annual runoff has flowed 

out of a basin and is an effective index for the timing of 

water availability in snowmelt-driven basins. Shifts to 

earlier runoff in the winter or spring disconnect streamflow 

timing from water supply needs such as agricultural irrigation. Center of timing can be redundant with other 

metrics that measure impact more directly, but with care in 

interpretation, it can help clarify different potential causal 

mechanisms, such as changing precipitation versus changing 

temperature.

Peakflows are important to fish and infrastructure. 

Scouring flows can damage eggs in fish redds if they occur 

while the eggs are in the gravel or alevins are emerging 

(Goode et al. 2013; Tonina et al. 2008). Winter peakflows 

can affect fall-spawning fish (chinook [Oncorhynchus 

tshawytscha], bull trout [Salvelinus confluentus], and brook 

trout [S. fontinalis]), whereas spring peakflows affect springspawning cutthroat trout (O. clarkii), resident rainbow trout 

(O. mykiss), and steelhead (O. m. gairdneri) (Wenger et 

al. 2011a,b). Spring peakflows associated with the annual 

snowmelt pulse are typically muted in magnitude compared 

to winter rain-on-snow events for two reasons. The rain-onsnow events can generate larger water input rates (rainfall 

precipitation plus high melt rate), and they tend to affect 

much larger fractions of a basin at a time, so scouring is 

less of a risk to spring-spawning fishes. Consequently, a 

shift to more midwinter events can yield higher peakflow 

magnitudes, which can also threaten infrastructure such 

as roads, recreation sites, and water management facilities 

(e.g., diversions, dams).

Historical changes in some of these streamflow metrics 

have been examined in northern portions of the IAP region, 

specifically earlier runoff timing (Cayan et al. 2001; Stewart 

Figure 4.8—Uncertainty ratio for April 1 snow water 

equivalent. Orange to dark red sites are strongly influenced 

by precipitation in contrast to temperature. Thus, 

temperature-based projections for snow water equivalent in 

those sites may be inaccurate if precipitation changes are 

large. At dark green (and white) sites, temperature effects 

will predominate, and precipitation changes in either 

direction are inconsequential.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
66 USDA Forest Service RMRS-GTR-375. 2018

et al. 2005) and declining annual streamflows (Clark 2010; 

Luce and Holden 2009). Declining low flows (7Q10) have 

also been observed in the western half of the Northern 

Rockies (Kormos et al. 2016), associated more with declining precipitation than warming temperature effects for the 

historical period. Low-flow changes and timing changes in 

projections are generally associated with expected changes 

in snowpack related to temperature (e.g., more melt or 

precipitation as rain in winter, yielding a longer summer dry 

period). Low-flow changes driven by these timing changes 

are strongly dependent on groundwater conditions in the 

basin (Tague and Grant 2009), which vary considerably 

across the IAP region as discussed later in the Groundwater 

Resources section.

Streamflow Projections

Streamflow projections for an ensemble of Coupled 

Model Intercomparison Project Phase 3 (CMIP3) models 

under the A1B scenario (Littell et al. 2011) were produced 

from the VIC model (Liang et al. 1994) for the western 

United States (University of Washington, Climate Impacts 

Group 2017)) (figs. 4.9–4.13). Differences between the climate described by CMIP3 projections and the more recently 

developed CMIP5 projections are minimal with respect to 

temperature (Chapter 3). The gridded VIC data were used 

to estimate streamflow by using area-weighted averages of 

runoff from each VIC grid cell within a given basin, following the methods of Wenger et al. (2010), to accumulate flow 

and validate. Streamflow metrics were calculated for stream 

segments in the National Hydrography Dataset Plus (version 

2) stream segments (USDA FS n.d.).

Figure 4.9—Percentage change in 

mean annual flow projections 

in the Intermountain Adaptation 

Partnership (IAP) region between a 

historical period (1970–1999) and 

the 2040s. Projections are from the 

Variable Infiltration Capacity model, 

following the methods of Wenger et 

al. (2010).

Figure 4.10—Percentage change in 

mean summer flow projections 

in the Intermountain Adaptation 

Partnership region between a 

historical period (1970–1999) and 

the 2040s. Projections are from the 

Variable Infiltration Capacity model, 

following the methods of Wenger et 

al. (2010).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 67

Figure 4.12—Projections of change 

(days) in the number of mid-winter 

floods (95th-percentile flow) in 

the Intermountain Adaptation 

Partnership region between a 

historical period (1970–1999) and 

the 2040s. Projections are from the 

Variable Infiltration Capacity model, 

following the methods of Wenger et 

al. (2010).

Figure 4.11—Change (days) in the 

center of flow mass projections 

in the Intermountain Adaptation 

Partnership region between a 

historical period (1970–1999) and 

the 2040s. Projections are from the 

Variable Infiltration Capacity model, 

following the methods of Wenger et 

al. (2010).

Figure 4.13—Percentage change 

in 1.5-year flood magnitude 

(approximate “bankfull” flow) 

in the Intermountain Adaptation 

Partnership region between a 

historical period (1970–1999) and 

the 2040s. Projections are from the 

Variable Infiltration Capacity model, 

following the methods of Wenger et 

al. (2010).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
68 USDA Forest Service RMRS-GTR-375. 2018

Uncertainty in climate model inputs can be a significant 

factor in uncertainty for outcomes related to natural resources (Wenger et al. 2013). Downscaling for these runs was 

done statistically, not dynamically, using an RCM to account 

for orographic enhancement changes, so GCM expectations 

for precipitation are implicit in the streamflow estimates. No 

effects of change in orographic enhancement are inherent 

in these images; thus, uncertainty may be higher (in a drier 

direction) on the windward side of mountain ranges.

Mean annual flow projections (fig. 4.9) suggest a slight 

increase across the northern portion of the IAP region, 

which ties back to the general moistening predicted by 

CMIP3 GCM runs (also illustrated in fig. 4.2). Minor 

changes are displayed through the central part of the region. 

The decreases shown in the southern part of the region 

are associated with changes in the Hadley cell circulation, 

which has also been described as an expansion of the midlatitude deserts.

Despite projections of slightly increased annual flow 

across much of the region, summer low flows are expected 

to decline (fig. 4.10), with relatively uniform changes 

in mountainous areas, particularly in wetter ranges. The 

primary mechanism expected to drive lower summer base 

flows is reduced snowpack in winter, leading to less stored 

water. The VIC model simulations do not include the effects 

of large groundwater reserves; thus, this effect could be 

moderated in systems where groundwater flow contributes 

a substantial volume of water to late summer flows (see 

more discussion in the Groundwater Resources section on 

where this may be important). Although such groundwater 

support could moderate the percentage declines as shown in 

figure 4.10, actual low-flow runoff rates could have greater 

declines in such places because the fractional decline is 

applied to a larger pre-change low-flow rate (e.g., Tague 

and Grant 2009). This is an important consideration when 

dealing with water rights, in which actual volumes or flows, 

rather than percentages, are allocated to individual rights.

Places where summer precipitation plays an important 

role, particularly the southern portion of the region, are 

more likely to see low flows affected by summer precipitation patterns. Shifts in circulation that affect how moisture 

flows from the Gulf of Mexico in summer are expected to 

negatively affect precipitation. Increased spacing between 

precipitation events (IPCC 2013; Luce et al. 2016) and 

decreased moisture in the early portion of the monsoon 

season (Cook and Seager 2013) are other likely occurrences. 

These summer wet areas are also more likely to have greater 

losses of precipitation with increased evaporation, but it 

is important to recognize energy balance constraints when 

estimating the degree of loss (Roderick et al. 2014). This is 

not done in the VIC modeling, which uses only the temperature outputs from GCMs without reevaluating the change in 

energy balance from a different hydrological formulation; 

loss by evapotranspiration may thus be overestimated (Milly 

and Dunne 2011).

Generally, areas showing a change in summer low flows 

also show a shift to earlier center of flow mass timing (2–4 

weeks) (fig. 4.11) and a shift to stronger changes in mountains dominated by snowmelt runoff. Changes in timing are 

related to snow residence time and earlier snowmelt runoff 

(figs. 4.6, 4.7).

Projected changes in the number of winter floods 

(95th percentile flow) show more of an effect in mid- and 

lower-elevation mountain ranges. Higher elevation and 

colder ranges, which will preserve more snowpack, show 

less change (fig. 4.12). The shift to more midwinter rain 

and more rain-on-snow flooding depends strongly on the 

elevational range of each basin. At middle elevations, temperatures are projected to increase enough that rain is likely 

on snowpacks, even in midwinter. Consequently, projected 

peakflow increases are generally stronger in these midelevation mountainous areas (fig. 4.13). Greater midwinter 

flooding could increase both the occurrence and magnitude 

of peakflows (fig. 4.14), as well as the potential for scour in 

gravel riverbeds (Goode et al. 2013).

Figure 4.14—Illustration of increased mid-winter flooding 

potential. Projected streamflows are from Variable 

Infiltration Capacity modeling for (a) current conditions, 

(b) 2040s, and (c) 2080s. The long, short, and gray dashed 

lines indicate the 2-year flood for each period (current, 

2040s, and 2080s, respectively) (from Goode et al. [2013]).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 69

Drought

Several studies help to provide a paleoclimatic context 

for evaluating drought in the IAP region. For example, both 

an early and an updated reconstruction of streamflow in the 

Colorado River Basin indicate that water allocation agreements were developed during one of the wettest periods in 

the last 500 years (Stockton and Jacoby 1976; Woodhouse et 

al. 2006), and that droughts were more severe before the 20th

century (Woodhouse et al. 2006). Similarly, DeRose et al. 

(2015) found that in the Bear River of the Great Basin, the 

latter half of the 20th century was the second wettest period 

in the last 1,200 years. Other studies have also demonstrated 

high variability and severe droughts in the Uinta Mountains 

(MacDonald and Tingstad 2007), Weber River (Bekker et al. 

2014), Logan River (Allen et al. 2013), and Great Salt Lake 

(Wang et al. 2012). Figure 4.15 illustrates a general correlation in wet and dry cycles between these basins over time, 

but also some unique differences based on onsite-specific 

factors (DeRose et al. 2015).

Understanding long-term climate dynamics is critical 

for sustainable management of environmental resources. In 

combination with projections for climate change, knowledge 

of past climatic conditions can help inform water and land 

management decisions. For a more extensive discussion of 

drought, paleoclimatic history, and effects on forests and 

streams, see Luce et al. 2016.

Sediment Yield

The delivery and transport of sediment through mountain 

rivers affect aquatic habitat and water resource infrastructure. Although climate change is expected to produce 

significant changes in hydrology and stream temperature, 

the effects of climate change on sediment yield have received less attention. Climate change is expected to increase 

sediment yield primarily through the effects of temperature 

and hydrology on vegetation disturbances (wildfire, insects, 

drought-related mortality) (Goode et al. 2012).

A conceptual model (fig. 4.16) of sediment yield (solid 

black line) relative to climate can help to illustrate the 

regulating role of vegetation. The dashed lines indicate the 

relative increase in resistance to erosion that vegetation 

provides as the driving force of precipitation increases. The 

biggest divergence in the lines occurs in semiarid climates 

where sufficient precipitation is available to drive erosion, 

but there is a limited amount of vegetation to stabilize hillslopes from erosion. The result is higher sediment yield in 

semiarid climates. The red arrow and circle on the plot depict the potential shift of current temperate forest climates to 

more semiarid climates, increasing overall erosion potential 

and sediment yield (Goode et al. 2012) (fig. 4.16).

Figure 4.15—Comparison between the Bear River and other 

Wasatch Front hydroclimate reconstructions, illustrating the 

cyclical nature of wet and dry periods in the Intermountain 

Adaptation Partnership region (from DeRose et al. [2015]).

Figure 4.16—Conceptual plot of sediment yield (solid black 

line) relative to hydroclimate and the regulating role of 

vegetation. The red arrow and circle illustrate the potential 

shift of current temperate forest climates, which under a 

warming climate could become more like semiarid climates, 

increasing erosion potential and sediment yield (from Goode 

et al. [2012]).

Groundwater Resources

Climate change is likely to have significant, long-term 

implications for groundwater resources in the IAP region. 

Climate change is expected to cause a transition from snow 

to rain, resulting in diminished snowpack, shifts in streamflow to earlier in the season (Leibowitz et al. 2014; Luce et 

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
70 USDA Forest Service RMRS-GTR-375. 2018

al. 2012), and changes in groundwater recharge to aquifers 

and groundwater discharge to groundwater-dependent 

ecosystems (GDEs). In this section, we synthesize existing 

information about occurrence of groundwater resources 

in five of the six subregions, describe potential effects of 

climate change, and describe how climate change can affect 

GDEs, including aquifers, streams, wetlands, and springs.

Groundwater is broadly defined as “all water below 

the ground surface, including water in the saturated and 

unsaturated zones” (USDA FS 2012). Groundwater resources include water residing in the subsurface, as well 

as ecosystems that depend on the presence or discharge of 

groundwater.

Groundwater-dependent ecosystems are “communities 

of plants, animals and other organisms whose extent and 

life processes are dependent on access to or discharge of 

groundwater” (USDA FS 2012). In the IAP region, GDEs 

include springs, springbrooks, groundwater-supported 

lakes, fens, streams, and rivers with base flow and riparian wetlands or phreatophytic vegetation along segments 

known as “gaining river reaches.” Fens are wetlands supported primarily by groundwater with a minimum depth 

(usually 12–16 inches) of accumulated peat (Chadde et al. 

1998; USDA FS 2012a). Springs are entirely supported by 

groundwater. These GDEs contribute significantly to local 

and regional biodiversity (Murray et al. 2006).

The fundamental hydrological processes that influence 

GDEs are: (1) amount, timing, and type of precipitation 

(rain or snow); (2) groundwater recharge; (3) groundwater 

quality; (4) groundwater discharge; and (5) evapotranspiration (Lins 1997). Along stream segments referred to as 

“gaining reaches,” groundwater enters the stream from the 

banks or the channel bed, and the volume of downstream 

streamflow is subsequently increased (Winter 2007; Winter 

et al. 1996). Groundwater can contribute substantially to late 

summer streamflow (Gannett 1984) and is the source for 

cool-water upwellings that serve as refugia for cold-water 

aquatic species (Lawrence et al. 2014; Torgersen et al. 1999, 

2012).

Hydrogeologic Setting

Hydrogeologic setting provides a context for assessing potential climate-induced changes to groundwater 

resources. Geologic units respond differently to changes 

in precipitation because of differences in hydraulic 

conductivity, transmissivity, primary versus secondary 

porosity, and fracture patterns. In a study that combined 

aerial photography (over 50–80 years) and climate analysis, 

Drexler et al. (2013) showed that five fens in the Sierra 

Nevada (California) decreased 10 to 16 percent in area. 

This decrease in area occurred over decades with high mean 

minimum air temperature and low SWE and snowpack longevity. However, two fens in the southern Cascade Range, 

underlain by different geology than the Sierra Nevada, did 

not change in area, suggesting that the hydrogeologic setting 

plays an important role in mediating GDE functionality.

Several different hydrogeologic settings have been 

delineated in the IAP region, including igneous/metamorphic, sedimentary, karst, and unconsolidated sediments. 

Igneous and metamorphic rocks with low permeability and 

porosity, with low-volume groundwater discharges, and that 

are recharged only during large infrequent precipitation or 

snowmelt events may not be vulnerable to changes in temperature and precipitation. However, aquifers in sedimentary 

formations, karst formations (fig. 4.17), and unconsolidated 

sediments may be more sensitive to climate change because 

they have high permeability, high porosity, and larger volume discharges to GDEs.

Groundwater Systems in the Intermountain Adaptation Partnership Region

Middle Rockies Subregion

Located in central Idaho, the Middle Rockies subregion 

is underlain with predominantly igneous and volcanic rocks 

with carbonate (fig. 4.17) and other sedimentary rocks in the 

southeast. Groundwater occurs in fractured and weathered 

crystalline rocks and sedimentary rocks (USGS 2000). Sand 

and gravel aquifers are found in floodplains and terraces in 

the valleys. Bedrock aquifers are the only source of groundwater across much of the subregion. Igneous, metamorphic, 

and sedimentary rocks that underlie the mountains generally 

yield little water to wells. Recharge to the basin aquifer system is by precipitation that falls directly on basin floors and 

by snowmelt that runs off the surrounding mountains and is 

transported into the basins by tributary streams.

Southern Greater Yellowstone Subregion

The Southern Greater Yellowstone subregion in western 

Wyoming and eastern Idaho consists primarily of sedimentary rocks but also contains igneous and metamorphic rocks 

(USGS 2000). Aquifers include sedimentary rocks, sand, 

and gravel along streams and basin-fill aquifers adjacent to 

the mountain blocks. Groundwater occurs in pore spaces, 

joints, fractures, faults, and solution openings in carbonate 

rocks. Many basins are bounded by mountain front faults. 

The most important aquifers are basin-fill aquifers, but they 

are recharged mainly from the mountain blocks. Deposits 

that fill the basins are mostly alluvium derived from the 

weathering and erosion of consolidated rocks that underlie 

the mountains bordering the basins. Primary recharge areas 

are generally located along the mountain fronts and extend 

into some mountain valleys. Groundwater is obtained 

principally from the basin-fill deposits. Basin margin faults 

are likely to influence flow from the bedrock aquifers to the 

basin-fill aquifers by forming barriers and highly permeable 

pathways, depending on the fault-zone geometry.

Uintas and Wasatch Front Subregion

Consolidated rocks of Precambrian to Tertiary age, which 

form the Wasatch Range and other mountain ranges in the 

Uintas and Wasatch Front subregion, yield water chiefly 

through complex systems of fractures, joints, solution 

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 71

cavities, fault zones, and vesicles (Price 1985). These waterbearing zones, which are not present at all locations, are 

difficult to find and delineate. Wells in consolidated rocks 

also have small yields, and the depth to the saturated zone 

can be great. Consequently, the consolidated rocks in the 

Wasatch Front area are not considered to be favorable sources of water for withdrawal from wells. As a unit, however, 

they do absorb, store, and transmit large volumes of water to 

downstream aquifers. This is particularly true for carbonate 

units (fig. 4.17). In Utah, the aquifers in Cache Valley, the 

lower Bear River area, and along the Wasatch Front provide 

water to 84 percent of the population of Utah.

Geologic conditions vary considerably throughout the 

Wasatch Front area, and thus, groundwater occurrence, 

Figure 4.17—Areas with cave and karst potential composed of carbonate and minor volcanic rocks in the U.S. 

Forest Service Intermountain Region (from Weary and Doctor [2014]).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
72 USDA Forest Service RMRS-GTR-375. 2018

movement, quality, and availability also vary. Most of the 

wells that obtain water from the consolidated rocks are used 

for domestic supply and produce only a few gallons of water 

per minute. However, some of the springs that discharge 

from these rocks (especially carbonate rocks) produce several hundred to more than 1,000 gallons per minute. Alluvial 

fans make up much of the valley fill near mountain fronts.

Plateaus Subregion

Colorado Plateau aquifers underlie the Plateaus subregion of eastern Utah. Principal aquifers in the Colorado 

Plateau include the Uinta-Animas, Mesaverde, DakotaGlen Canyon, and Coconino-De Chelly (USGS 2000). 

Distribution of aquifers on the Colorado Plateau is controlled in part by the structural deformation and erosion that 

have occurred since deposition of the sediments composing 

the aquifers. Much of the land is underlain by rocks that 

contain aquifers capable of yielding usable quantities of 

water of quality suitable for most agricultural or domestic 

use. In general, the aquifers in the Colorado Plateau area are 

composed of permeable, moderately to well-consolidated 

sedimentary rocks. These rocks range in age from Permian 

to Tertiary and vary greatly in thickness, lithology, and 

hydraulic characteristics.

Relatively impermeable confining units separate each 

of the four principal aquifers in the Colorado Plateau. 

The two thickest units are the Mancos (underlying the 

Mesaverde aquifer) and Chinle-Moenkopi (underlying the 

Dakota-Glen Canyon aquifer). Groundwater recharge to the 

Uinta-Animas aquifer generally occurs at higher elevations 

along the margins of each basin. The Mesaverde aquifer is 

at or near the land surface in extensive areas of the Colorado 

Plateau.

Great Basin and Semi Desert Subregion

The Great Basin and Semi Desert Subregion lies within 

the Basin and Range Physiographic Province, which 

contains three principal aquifer types: (1) volcanic-rock 

aquifers, which are primarily tuff, rhyolite, or basalt of 

Tertiary age; (2) carbonate-rock aquifers (fig. 4.17), which 

are primarily limestones and dolomites of Mesozoic and 

Paleozoic age; and (3) basin-fill aquifers, which are primarily unconsolidated sand and gravel of Quaternary and 

Tertiary age (USGS 2000). These aquifers underlie most of 

Nevada, western Utah, and southern Idaho. All the precipitation that falls in the area is returned to the atmosphere by 

ET, and streams do not carry water to the oceans.

Fracturing in carbonate rocks (limestone and dolomite) 

may enable groundwater to circulate through the fractures 

where the water can dissolve the slightly soluble rock and 

enlarge and increase the size and number of pathways 

for water movement through the rock. Such dissolution 

eventually can change a relatively impermeable carbonate 

rock into a permeable water-yielding unit. Carbonate rocks 

predominate in a 20,000- to 30,000-foot thick sequence of 

Paleozoic and Lower Mesozoic rocks in an extensive area of 

southern and eastern Nevada and are present on all National 

Forests in the region. The location of solution-altered zones 

of enhanced permeability within these carbonate rocks is 

poorly known. Although extrusive igneous rocks (primarily 

basalt) can be permeable in local areas, most other types of 

consolidated rock are not sufficiently permeable to transmit 

large volumes of water, and bedrock generally forms a 

relatively impermeable boundary to the Basin and Range 

aquifers.

The groundwater flow systems of the Basin and Range 

area are in individual isolated basins or in two or more 

hydraulically connected basins. The impermeable rocks are 

boundaries to the flow system, and most of the groundwater 

flows through basin-fill deposits. If carbonate rocks underlie 

the basins, substantial quantities of water can flow between 

basins through the carbonate rocks and into the basin-fill 

deposits. Most recharge to the basin-fill deposits originates 

in the mountains as snowmelt. Major faults that cut the alluvial deposits can act as partial barriers to the movement of 

groundwater.

Dependence of Special Habitats on 

Different Water Sources

Groundwater-dependent ecosystems occur in locations 

with abundant growing-season water. Because precipitation is the ultimate source of water and directly influences 

streamflow characteristics and groundwater dynamics, it is 

expected that climate-induced changes in precipitation will 

affect riparian areas, wetlands, and GDEs. Availability of 

water is also influenced by physical watershed characteristics that affect infiltration and surface and hillslope runoff, 

including lithology, soil depth, and topography (Jencso et al. 

2009).

Groundwater Recharge in Mountain 

Aquifers in the Western United States

Most aquifers in Western mountains are small compared 

to the major aquifer systems in the basins. Despite being 

small, these aquifers are essential in storing and transmitting 

groundwater that becomes recharge to the adjacent major 

aquifer systems. Altered recharge caused by climate change 

will translate into altered mountain aquifer storage and 

discharge, which will, in turn, directly influence recharge 

to downgradient aquifers and stream base flows. Between 

61 and 93 percent of diffuse mountain catchment recharge 

becomes streamflow available for downstream aquifer 

recharge by stream loss (Meixner et al. 2016).

Snowmelt is likely to contribute the majority of recharge 

in most mountainous regions of the western United States, 

either because most of the precipitation falls as snow, or 

snowmelt infiltrates below the root zone more effectively 

than rainwater (Earman et al. 2006). Snowmelt can compose 

a large fraction of recharge because much of the water 

released from the snowpack occurs over a prolonged period 

in early spring when ET is low (Ajami et al. 2012; Earman 

et al. 2006). Consequently, mountain recharge is sensitive 

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 73

to the climatic shifts that result in changes in SWE noted 

earlier in the chapter.

Recharge in many mountainous areas is permeability 

limited rather than recharge limited where thin soils overlie 

low-permeability crystalline bedrock (Flint et al. 2008). 

Lower maximum annual SWE in these areas may decrease 

overland flow of snowmelt to streams, but has little influence on recharge because spring snowmelt substantially 

exceeds the unsaturated zone storage capacity (Blankinship 

et al. 2014). Conversely, bedrock permeability in karst areas 

is so high that most snowmelt and rainfall infiltrates into 

the porous rock, flows in conduits, and is discharged to the 

surface as springs or discharges directly to fill aquifers.

Higher minimum temperatures will reduce the longevity of snowpack, and decrease the length of time aquifer 

recharge can occur, potentially leading to less groundwater 

recharge. Some watersheds will be shifting from snowdominated to rain-dominated, which may result in declines 

in groundwater recharge (Earman and Dettinger 2011; 

Safeeq et al. 2013, 2014). Recharge could also increase in 

these areas as a result of a more gradual release of water 

from snowpack from enhanced winter melting (Byrne et al. 

2014; Musselman et al. 2017). Projecting future mountain 

recharge requires knowledge of groundwater flow systems 

that is generally unavailable.

In summary, recharge is likely to decrease in the southern 

IAP region, but changes in other parts of the region are 

uncertain because of limited understanding of mountain 

recharge processes and groundwater flow in mountains 

(Meixner et al. 2016). However, there are existing approaches (e.g., Safeeq et al. 2014) that can be used to 

develop sensitivity maps from available information about 

geology, stream recession behavior, and other factors. These 

approaches could be used to evaluate sensitivities for future 

mountain recharge in the IAP.

Current Resource Conditions

Steep elevation gradients, varied bedrock, and glacial 

landforms influence the distribution, characteristics, and water chemistry of groundwater-dependent features. Existing 

information on the condition and distribution of GDEs in 

National Forests of the IAP region is limited. Here, we 

rely on data compiled by the Spring Stewardship Institute, 

the National Hydrography Dataset (USGS 2017), and the 

National Wetlands Inventory (NWI) (USFWS n.d.) to assess 

the current condition of springs, wetlands, and GDEs in the 

region.

Springs are usually small, averaging less than 0.5 acre, 

with few spring habitat patches larger than 2 acres (Kreamer 

et al. 2015). Thus, springs fall below the scale of most landscape mapping efforts and are therefore neglected in remote 

sensing, soil, and floristic mapping. Recently, National 

Forests in the U.S. Forest Service Intermountain Region and 

the Spring Stewardship Institute have begun to map springs 

and other GDEs, but the known occurrence of these are limited, and many more springs certainly exist (table 4.1).

Springs play a key role as groundwater discharge zones 

that deliver cool water to warming streams, support lateseason streamflows in summer, and deliver relatively warm 

water during winter months (Lawrence et al. 2014; Winter 

2007). Most streams and rivers in the region are at least partially groundwater dependent (Santhi et al. 2008). Locations 

of groundwater discharge to streams have been identified 

by using remote sensing (Torgersen et al. 1999) and field 

techniques (Torgersen et al. 2012), but have not been systematically mapped.

Wetlands can be identified by targeting palustrine/emergent wetlands with a saturated water regime (Cowardin 

et al. 1979) in the NWI database (table 4.1). To ascertain 

whether these wetlands are indeed fens, each wetland would 

require a field visit to determine if it is supported (at least 

in part) by groundwater and is peat-forming (Chadde et al. 

1998; USDA FS 2012a, b). Fens occupy a small portion of 

the landscape, but contribute substantially to biodiversity 

of plants and animals (Blevins and Aldous 2011). In an 

otherwise arid region, perennially saturated fens are critical 

habitat for invertebrate and amphibian species. Although 

not explicitly differentiated as fen vegetation, several 

herbaceous-dominated plant associations frequently occur 

in fens.

Since 2008, GDEs, mostly springs and fens, have been 

inventoried and documented in National Forests by using 

draft and final versions of the Groundwater-Dependent 

Ecosystems Level I and Level II inventory methods 

Table 4.1—Area of palustrine emergent wetlands with saturated 

water regime and number of mapped springs in the U.S. 

Forest Service Intermountain Region. Differences in wetland 

area reflect different mapping accuracy and limitation 

among national forests; wetlands less than 1 to 3 acres are 

generally not included (USFWS n.d.).

National Forest Wetland area Springs

Acres Number

Ashley 18,388 426

Boise 92 442

Bridger-Teton 3,397 140

Caribou-Targhee 262 1,467

Dixie 1,048 652

Fishlake 1,259 622

Humboldt-Toiyabe 1,275 4,286

Manti-La Sal 1,894 481

Payette 218 155

Salmon-Challis 205 692

Sawtooth 224 1,211

Uinta-Wasatch-Cache 19,269 917

 Total 47,530 11,491

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
74 USDA Forest Service RMRS-GTR-375. 2018

(USDA FS 2012a, b). The Level I guide (USDA FS 2012a) 

describes basic methods for assessment of GDEs within a 

given area (e.g., National Forest, ranger district, specific 

project area) and is intended to qualitatively document the 

location, size, and basic characteristics of each GDE site. 

The Level II guide presents more detailed inventory (USDA 

FS 2012b) in addition to protocols for more comprehensive 

characterization of the vegetation, hydrology, geology, and 

soils at a given site.

Inventories have been conducted in Ashley, CaribouTarghee, Dixie, Humboldt-Toiyabe, Manti-La Sal, and 

Sawtooth National Forests. Inventories in HumboldtToiyabe National Forest targeted springs with terrestrial and 

aquatic flora and fauna values. In the GDE Level I protocol 

(USDA FS 2012a), a series of 25 management indicator 

statements assist in identifying potential concerns and needs 

for management action based on observations recorded during field inventories. Three of the most important indicators 

are aquifer functionality, soil integrity, and vegetation composition. Most inventories targeted sites where proposals for 

water development could be damaging, or portions of grazing allotments and watersheds with specific management 

concerns. Findings of inventories commonly show notable 

resource impacts through water diversion, soil disturbance, 

and effects of livestock on vegetation.

Potential Climate Change Effects on 

Groundwater and Groundwater-Dependent 

Ecosystems

Groundwater recharge has been examined in only a 

few locations (Tague and Grant 2009), and little is known 

about groundwater recharge processes in many watersheds, 

including those that may be shifting from snow-dominated 

to more rain-dominated hydrological regimes (Safeeq et al. 

2013, 2014). Depending on elevation and hydrogeologic 

setting, slowly infiltrating precipitation that includes both 

rain and snow may recharge some groundwater aquifers as 

effectively as rapid, seasonal snowmelt runoff. Although 

rain-on-snow zones are expected to shift upwards in elevation, the influence of these shifts on groundwater recharge is 

unknown.

Small, unconfined aquifers (especially surficial and 

shallow aquifers) are more likely to have renewable 

groundwater on shorter time scales and may respond rapidly 

to changes in climate (Healy and Cook 2002; Lee et al. 

2006; Sophocleous 2002; Winter 1999). Larger, deeper, and 

confined aquifers are more likely to have nonrenewable 

groundwater, may be less sensitive to the direct effects of 

climate change, and are projected to have a slower response 

(Wada et al. 2012).

Groundwater storage can moderate surface water response to precipitation changes (Maxwell and Kollet 2008), 

and changes to groundwater levels can alter the interaction 

between groundwater and surface water systems (Hanson 

et al. 2012). Climate-induced changes in connectivity between groundwater and surface water could directly affect 

stream base flows and associated wetlands and other GDEs 

(Earman and Dettinger 2011; Kløve et al. 2012; Tujchneider 

et al. 2012). Short flow-path groundwater systems, including 

many that provide base flow to headwater streams, could 

change substantially in timing of discharge in response to 

changes in seasonality of recharge (Waibel et al. 2013). In 

contrast, regional-scale aquifer systems, with flow paths on 

the order of tens of miles, are much less affected by shifts 

in seasonality of recharge. These effects may be highly variable, depending on local hydrogeology.

Altered groundwater levels in wetlands can reduce 

groundwater inflow, leading to lower water table levels and 

altered wetland water balances. For local and intermediatescale systems, the spatial extent of some GDEs is likely to 

contract in response to decreasing surface water and groundwater and increasing temperatures. Changes in groundwater 

and surface water will also vary depending on location 

within the watershed, as well as future land use.

Effects of changing climate on the ecology of GDEs 

will depend on changes in groundwater levels and recharge 

rates, as influenced by the size and position of groundwater 

aquifers (Aldous et al. 2015). GDEs supported by small, 

local groundwater systems tend to exhibit more variation 

in temperature and nutrient concentrations than regional 

systems (Bertrand et al. 2012). It is likely that larger systems 

will be more resilient to climate change.

Freshwater springs depend on continuous discharge of 

groundwater, forming ecotones between subsurface-surface 

water and aquatic-terrestrial environments (Ward and 

Tockner 2001). Springs and springbrooks support locally 

unique biological communities (Barquin and Death 2006). 

However, climate-induced changes in recharge may cause 

decreased summer flows with possible drying, as well as 

increased winter flow and inundation of biological communities (Green et al. 2011).

Many biogeochemical processes are temperature 

dependent, so climate-induced changes in groundwater temperature may negatively affect the quality of groundwater, 

and, in turn, influence aquatic communities (Figura et al. 

2011). However, because the thermal regime of groundwater 

systems is less dependent on air temperature patterns than 

surface waters, the effects of rising air temperatures are 

likely to be less pronounced in springs and other GDEs.

Peat-accumulating processes in fens will be influenced 

by increasing temperatures and local and regional changes 

in hydrological regime. Reduced groundwater levels tend 

to promote soil aeration and organic matter oxidation. 

Generation and maintenance of peat soils over time depend 

on stable hydrological conditions. In recent studies of 

peatlands exposed to groundwater lowering, responses such 

as soil cracking, peat subsidence, and secondary changes 

in water flow and storage patterns have been observed 

(Kværner and Snilsberg 2011). Wetland plant species can 

respond to even slight changes in water table elevation 

(Magee and Kentula 2005; Shipley et al. 1991; Vitt and 

Slack 1984), and shifts in composition of vascular and bryophyte species could occur with lowered water tables.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 75

Some riparian ecosystems depend on the presence of 

flowing water, although streamflow may not be perennial 

along all stream segments and can vary considerably with 

season, physical features of the watershed, and water source. 

Depending on physical characteristics of a given stream 

segment, the volume of streamflow can also drive seasonal 

changes in water table elevation of the adjacent riparian area 

(Jencso et al. 2011). These hydrological and fluvial processes and resulting geomorphic surfaces are essential for 

the persistence of riparian vegetation (Naiman et al. 2005). 

According to long-term daily flow data, different streams in 

the region are supported by perennial runoff, snow plus rain, 

and stable groundwater levels (Poff 1996).

Changes in water table elevations and streamflow 

volumes may affect riparian areas and their plant communities (Jencso et al. 2009; Naiman et al. 2005). Examples of 

changes in flow systems are decreased summer base flows 

(see earlier Hydrological Processes section), lower riparian 

water table elevations, and reduced hydrological connectivity between uplands and riparian areas (Jencso et al. 2009, 

2011). Streamflow volume along gaining reaches increases 

with the inflow of groundwater to the channel. Stream 

water can also drain from the channel bed and banks to the 

groundwater system (losing reaches), resulting in a loss 

of downstream surface flow volume (Winter et al. 1996). 

Gaining and losing stream reaches result in different aquatic 

communities in the channels and different riparian plant 

communities on the floodplains. The extent to which gaining or losing characteristics of specific reaches may change 

in response to climate-induced changes in precipitation, 

streamflow characteristics, and groundwater discharge is 

unknown.

In wetlands and riparian ecosystems, hydrological 

variables are consistently the strongest predictors of plant 

species distributions (e.g., Cooper and Merritt 2012). 

Current understanding of the water sources used by riparian and wetland plants is limited to a few highly valued or 

highly invasive species (mostly woody). However, riparian 

and wetland plant species use water from multiple sources 

(surface water, soil water, groundwater), depending on life 

stage and season (Busch and Smith 1995; Cooper et al. 

1999; Goslee et al. 1997). In assessing the vulnerability of 

riparian and wetland species to climate-induced changes in 

streamflow or groundwater, the availability of water at all 

life stages must be considered, from plant recruitment and 

establishment, to reproducing adults, to persistence at later 

life stages (Cooper and Merritt 2012).

Climate-induced changes in precipitation, drought, and 

streamflow will influence the distribution of riparian vegetation via changes in local hydrological regimes, especially 

if summer base flows decrease. If water table elevation can 

be assumed to be in equilibrium with water levels in the 

stream, reduced base flows could result in lower riparian 

water table elevations and subsequent drying of streamside 

areas, particularly in wide valley bottoms. Wetland and 

riparian plant communities will respond to climate-induced 

changes in hydrological variables differently as a function 

of species composition (Merritt et al. 2010; Weltzin et al. 

2000).

Although ET is not expected to increase substantially 

from the landscape generally as outlined earlier in the 

chapter, water supplies around riparian areas and GDEs 

are consistently high. Riparian areas and GDEs compose a 

very small fraction of the landscape, so they affect the landsurface energy balance only very slightly. Consequently, the 

increased net radiation and atmospheric demand will induce 

higher ET rates in riparian areas and GDEs, and this higher 

ET rate will not substantially feed back into the regional 

energy balance. Higher ET will result in drying in these 

ecosystems, potentially stressing characteristic plant species 

and resulting in compositional shifts in vegetation. If plant 

cover is reduced in riparian areas, erosion may increase.

Soil Resources

The potential effects of climate change on soils are multifaceted; changes in soil physical, biological, and chemical 

processes can occur with changing climate, which may in 

turn affect other processes such as carbon cycling and vegetation growth. Soil responses to climate change will vary by 

geographic location and are determined by the interactions 

of soil, vegetation, and the degree of management intervention. The following sections provide a summary of potential 

effects of climate change on soils in the IAP region.

Soil Temperature and Moisture

Soil temperature and moisture are the primary drivers 

of change for all soil processes. Potential changes to these 

soil properties with climate change have been well studied, 

but where and when the changes may occur is difficult to 

predict. The magnitude of projected change is variable depending on existing soil resources and existing climate. The 

properties and processes of soils are not independent, and a 

change to one soil property will affect other soil properties 

and processes. For example, changes to soil temperature and 

moisture will affect carbon and nitrogen cycles, which can 

in turn affect soil properties such as water holding capacity, 

cation exchange capacity, soil nutrient content, and aggregate stability (Brevik 2013).

An increase in soil temperature will generally produce 

an increase in soil biological activity and soil respiration. 

However, the rate and magnitude of change are dependent 

on soil moisture (Kardol et al. 2010). In the current semiarid 

soils of the IAP region, an increase in soil temperature 

without an increase in soil moisture is likely to create soils 

that have reduced biological activity and less potential to 

store carbon. If soil moisture is limiting with increased soil 

temperatures, the soils may become a net source of carbon 

until equilibrium is reached. However, an increase in soil 

temperature could be offset by an increase in water available 

for biological activity and vegetation production, resulting 

in little change or a possible increase in carbon storage. In 

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
76 USDA Forest Service RMRS-GTR-375. 2018

the colder and wetter areas of the IAP region, an increase 

in soil temperature may lead to longer growing seasons if 

soil moisture is not limiting (Kurylyk et al. 2014). Thus, the 

timing and type of moisture will determine soil biological 

activity, respiration, and ultimately vegetation supported by 

the soil.

Changes to soils with climate change will not be uniform 

across the IAP region. Soil responses to temperature and 

moisture are highly dependent on the soil parent material. Soils derived from coarse-textured granitic soils will 

transfer heat more efficiently downward into the soil 

profile than fine-textured limestone soils. The heat transfer 

downward can affect soil processes and even groundwater 

temperatures, and it could ultimately affect surface water 

temperatures where groundwater is the source for surface 

water. Fine-textured soils, which are capable of storing 

water longer in the soil profile, will generally have a higher 

buffering capability to changes in soil temperature and 

moisture.

The timing of soil moisture can also affect soil erosional 

processes. A shift away from winter precipitation as snow 

to greater amounts of rain and more intense rain storms can 

generate a higher frequency of runoff and erosional process 

from disturbance events such as fire (Litschert et al. 2014). 

Runoff from extreme rain events could increase for shallow 

soils with little capacity to store water.

Soil Carbon and Nitrogen

Soils are a major component of carbon and nitrogen 

cycles. Changes in soil temperature and moisture will affect 

carbon and nitrogen cycles. Management of soil organic 

matter can affect both of these cycles at local and global 

scales. The greenhouse gases carbon dioxide, methane, 

and nitrous oxide are regulated to some extent by the soil 

organic matter. Soils provide both a source and sink for carbon and nitrogen and the greenhouse gases associated with 

carbon and nitrogen. Changes to the carbon and nitrogen 

cycles may include an increase or reduction in cycling rates 

or storage of carbon and nitrogen. Soil temperature and 

moisture drive the type of change that will occur as they affect microbial activity and plant composition.

Soil Carbon Pool

Soil organic carbon (SOC) is derived from soil organic 

matter (SOM). The SOM is composed of plant and animal 

residues, cells and tissues of soil organisms, and substances 

produced by decomposing organisms. The SOC is the 

carbon component of SOM. Generally, about 58 percent of 

SOM is SOC by weight. Most soil orders within the IAP 

region have a near-surface SOC content (by mass) of 0.5 

percent (for the hotter and drier areas) to 8 percent (for the 

cooler and wetter areas; Histosols excluded) (Brady 1999). 

Hereafter, we use SOC to represent both SOC and SOM, 

as these properties are likely to have similar response to 

climate change.

Soil organic carbon may be the best indicator and 

contributor to soil health because SOC supports many soil 

processes and functions. These include providing nutrients 

for plants, binding soil particles together and thereby maintaining structure, providing an energy source for microbes, 

increasing water infiltration and retention, and providing 

cation-anion exchange for retention of ions and nutrients. 

Climate change will affect SOC and ultimately the functions 

and processes supported by SOC.

Globally, SOC may contain more than three times as 

much carbon as is found in the atmosphere or terrestrial 

vegetation. In forest ecosystems, SOC may be as much as 

80 percent of the total terrestrial carbon pool, and in nonforest ecosystems, SOC may be as much as 95 percent of the 

total terrestrial carbon pool (Meyer 2012). Soils can store 

and release carbon at the same time. If soils store more 

carbon than they release back to the atmosphere, the soil is 

a carbon sink. If soils are releasing more carbon than what 

is being stored, they become a carbon source. Therefore, the 

management of SOC is critical to the management of atmospheric carbon concentrations (Woodall et al. 2015).

Carbon is stored in soils in organic or inorganic forms. 

Soil organic carbon originates from carbon fixation during 

photosynthesis and microbial decomposition (Thomey et 

al. 2014). Inorganic carbon (IC) is in rocks and minerals. 

An example of IC is limestone, or calcium carbonate. The 

stable IC is released slowly through weathering or anthropogenic manipulation, such as mining and conversion to 

other chemical compounds. Although IC is slow to change, 

it represents a large portion of stored carbon in many ecosystems, such as drier shrublands and grasslands. Many of 

the drier rangeland soils include carbonate horizons within 

the soil profile. Climatic changes may affect the release of 

IC. Higher atmospheric carbon dioxide concentrations and a 

warmer and wetter climate will increase weathering of rocks 

and acidification in the carbonate layers in the soil, which 

will release greater amounts of carbon into the active carbon 

cycle (USDOE 2014).

Different soils have different capacity to store carbon. 

The differences are related to parent material, existing 

climate, and terrestrial ecological community types. 

Shrublands have a higher percentage of SOC stored lower 

in the soil profile (below 3 feet). Forests have most of their 

SOC in the first 3 feet of the soil. Changes to vegetative 

composition can affect long-term carbon storage. A shift 

from shrublands to annual grasslands will eventually move 

the bulk of carbon from deep in the soil profile to the upper 8 inches (USDOE 2014). This may be happening with 

conversions of shrublands to cheatgrass (Bromus tectorum) 

in the IAP region. This process is very slow, however, and 

respiration of carbon deep in the soil profile is much slower 

than near the soil surface. A shift from shrublands to forest 

will increase near-surface carbon pools as a result of litter 

addition and deeper reserves being tapped by roots for the 

production of biomass (Nave et al. 2013).

Soils have SOC storage limits set by soil physical 

and chemical composition as well as microbial and plant 

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 77

community types, all of which are determined by soil 

moisture and temperature. Most soils in the IAP region are 

at SOC saturation for the existing climate (Woodall et al. 

2015). Soils that are degraded or furthest from potential 

SOC saturation have the greatest ability to sequester additional carbon. These are generally areas with vegetation 

that has been altered for long periods of time, such as 

agricultural fields. Most of the soils in the IAP region could 

sequester additional carbon if soil temperatures decrease 

and soil moisture increases. This is particularly true with 

the lower-elevation soils. However, soil moisture may not 

increase in a warming climate.

Soil Physical Properties Related to 

Carbon and Climate Change

Changes to SOC can alter several soil properties, including soil structure, bulk density, and soil porosity (Pal Singh 

et al. 2011). These soil properties affect water infiltration, 

rooting depth, soil erosional losses, and water holding 

capacity. A reduction in SOC will change soil structure 

through reducing the bonds between soil particles and the 

microbial “glue” that helps hold soil particles together. 

This can lead to less resistance of the soil to erosive forces 

of wind and water. A change in soil structure can also lead 

to changes in soil porosity and bulk density. Soil porosity and pore size distribution are important for soil water 

management and maintaining release rates of greenhouse 

gases (carbon dioxide, methane, and nitrous oxide) within 

the soil. A loss of macropores with reduction in SOC could 

lead to slower water infiltration rates, increased runoff, 

decreased nutrient cycling, reduced plant growth (above and 

below ground), and poor aeration of the soil, resulting in a 

decreased capacity to oxidize greenhouse gases, specifically 

methane. A reduction in SOC also leads to increased risk of 

surface compaction with management activities through an 

increase in surface bulk density of soils. Surface compaction 

restricts water infiltration and increases surface runoff.

Although the changes to soil physical properties with 

loss of SOC are highly variable across the landscape, they 

do provide potential indicators that can be used to prioritize 

management in a changing climate; the soil types where 

current management is already having negative effects on 

soil physical properties could be the soil types that are prioritized for climate change adaptation actions. For example, 

areas where excessive runoff and soil loss have occurred 

because of grazing management may be a priority. These 

areas would be expected to have a higher risk of soil quality 

loss under a warmer and drier climate with reduction in 

plant growth and SOC development.

Soil Nitrogen

SOM typically contains about 5 percent nitrogen; therefore, the distribution of soil nitrogen closely parallels that 

of SOM (Brady 1999). Nitrogen cycles are closely tied to 

carbon cycles, although they may respond differently to 

changes in climate. On average, nitrogen fixation occurs at 

a rate of about 9 pounds per acre for forested sites and 13 

pounds per acre for grasslands (Brady 1999). Forest soils 

may contain 15 times as much nitrogen as the standing 

vegetation, including roots (Brady 1999). About 29 to 56 

percent of the soil nitrogen pool is found in the upper 4 

inches (Page-Dumroese and Jurgensen 2006), making the 

soil nitrogen pool highly susceptible to loss from erosion.

Although most of the nitrogen in terrestrial systems 

is found within the soil, the mineralization of nitrogen is 

required to provide a form of nitrogen that plants can utilize. 

Nitrogen mineralization occurs through decomposition of 

organic material by soil micro-organisms. Warmer soil temperatures increase decomposition by microbial activity, thus 

increasing nitrogen mineralization. However, soil moisture 

may have a greater effect on net nitrogen mineralization 

through changes in the form of nitrogen (Emmett et al. 

2004).

Nitrogen could be limiting to plants in some soils of the 

IAP region even if conditions for plant growth improve with 

changes in climate. If plant growth increases with increased 

atmospheric carbon dioxide, then organisms that decompose 

residual plant material will need more nitrogen to survive. 

If nitrogen is tied up by soil microflora and microfauna, the 

nitrogen would be unavailable to plants. Thus, any positive 

effects of increased atmospheric carbon dioxide may be offset by the reduction in available soil nitrogen (Brevik 2013), 

particularly on nitrogen-limited soils. In the IAP region, 

those areas most susceptible to reduction in nitrogen are 

forested areas on soils with coarse-textured parent material.

Soil Biological Activity

Soil organisms perform many functions in the soil, 

including decomposition and nutrient cycling. As with other 

soil processes, the soil biology is affected by other soil processes and the inherent soil composition and climate. Thus, 

the effects of climate change on soil biology will be variable. Some models project that a warming of the soil will 

create greater microbial activity, resulting in more carbon 

being released to the atmosphere because of increased decomposition (Kardol et al. 2010). Other models suggest that 

a warming of the soil will result in lower microbial growth 

and less carbon released through respiration (Wieder et al. 

2013). In the warm and dry desert ecosystems, such as those 

in the Great Basin and Semi Desert and Intermountain Semi 

Desert subregions, the effects of soil warming are expected 

to increase microbial activity and carbon dioxide released to 

the atmosphere (Thomey et al. 2014). In cooler and wetter 

ecosystems, projections are mixed (Steinweg et al. 2013).

Vegetation composition can affect soil biology, soil 

processes, and soil response to climate change. Some soil 

organisms prefer specific plant types, and plant diversity 

increases soil biological diversity. Greater biodiversity in 

soils is likely to increase soil resilience to climate change 

(Kardol et al. 2010).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
78 USDA Forest Service RMRS-GTR-375. 2018

Soil Chemical Properties

Potential effects of climate change on soil chemical properties are linked to other biological and physical changes 

in the soil, all of which are driven by soil temperature and 

moisture. Soil pH is closely tied to organic matter, parent 

material, and soil moisture. A warming climate with additional or similar precipitation will lower soil pH (Pal Singh 

et al. 2011). A warming climate with less precipitation may 

increase pH on some higher-elevation soils and have little 

effect on existing lower-elevation high-pH soils (Pal Singh 

et al. 2011).

In areas that are expected to experience increased 

drought, such as drier shrubland and grassland systems, an 

increase in the accumulation of carbonates and salts in the 

soil profile is expected. This would result in a salinization of 

the soil and have significant effects on vegetation composition. In wetter areas of the IAP region, an increase in soil 

temperatures may cause an increase in acidification from the 

decomposition of organic matter. This could change species 

composition and diversity to favor species more adapted to 

acidic soils.

Cation exchange capacity (CEC) is the ability of the 

soil to retain nutrients such as calcium, potassium, and 

magnesium and make them available to the soil solution 

and plants. It also provides the capacity to retain and immobilize some cations that may be toxic to soil microbes and 

plants in high amounts, such as aluminum and manganese. 

The CEC is generally low in coarse-textured soils or soils 

with low amounts of SOC. Soils with a subsurface argillic 

horizon (higher CEC) are likely to be able to moderate a 

shift in nutrient exchange, specifically a loss of SOC and 

other major soil nutrients requiring cation exchange sites. 

An increase in soil temperatures could lead to a reduction of 

SOC and the CEC of soils. A reduction in CEC would result 

in loss of base cations in the soil that are released to groundwater and surface water (Pal Singh et al. 2011).

Managing soil resources for optimum SOC will limit 

the effects of climate change to the CEC. Areas with low 

SOC are the most susceptible to CEC changes in soils due 

to climate change, as they have poor buffering capabilities. In the IAP region, these are primarily drier rangeland 

soils, particularly those that have been vegetated for many 

decades with annual shallow-rooted grasses.

Weathering of rock and erosion of soil is a continuous 

process. Changes to rainfall and wind as well as changes to 

chemical, physical, and biological properties of soils can 

affect the type, amount, and rates of runoff and erosion of 

soil. More precipitation may not have any long-term effects 

on erosion and runoff, because vegetation will respond 

positively to increases in available soil moisture. However, 

an increase in the number of intense rain events may result 

in an increasing rate of erosion. A reduction in the amount 

of precipitation generally reduces the rate of erosion. 

However, lower vegetation cover in response to low soil 

moisture may result in increased rates of erosion from wind 

and water. Areas of the IAP region that are most susceptible 

to increased erosion are the lower-elevation shrublands and 

grasslands, where a warmer and drier climate will reduce 

the potential for vegetative cover.

Regional-Scale Soil Vulnerability Ratings

The potential magnitude of change to soil resources in a 

changing climate is extremely variable because of the heterogeneity of soil types and their potential response across 

the landscape. Identifying the degree of potential change 

and risk to soils spatially across a landscape is difficult, even 

with detailed soils data. However, general projections can 

be made across large landscapes by using different soil and 

landscape attributes, particularly vegetation composition and 

productivity. The following section provides a general rating 

of soil vulnerability to climate change across the IAP region. 

The rating is based on general soil characteristics and data 

from Natural Resources Conservation Service STATSGO 

datasets (NRCS 2017).

Several assumptions were used to develop a regionwide 

rating of soil vulnerability to climate change. These include:

• The existing climate will generally be warmer and 

drier in the future across all subregions in the IAP.

• Soils that are currently capable of holding water 

longer and deeper within the soil profile have a greater 

buffering capacity to change.

• Soils that are currently cooler and wetter, or have 

higher SOC, are less susceptible to climate change.

• Many soil properties will change in a changing 

climate.

• The ratings of soil vulnerability to climate change 

are based on general surrogates of landscape and soil 

conditions. Data on detailed soil properties, such as 

available water holding capacity, were not available 

across the region to make predictions.

• Soil properties used to derive a vulnerability map were 

soil temperature and moisture regimes (combined into 

subclasses), and SOC from depths of 0 to 12 inches.

• Soil polygons contain many soil components. The 

components were combined by dominant condition 

for soil temperature and moisture subclasses and by 

weighted averages for SOC.

A combined STATSGO soil map was made for all lands 

within the IAP region. Soil temperature and moisture classes 

were determined for each polygon based on the dominant 

condition within the polygon. The soil temperature and 

moisture classes were further combined according to 

soil taxonomy to create 44 different subclasses. These 

subclasses were combined qualitatively based on common 

soil temperature and moisture breaks to create four class 

ratings of low, moderate, high, and very high susceptibility 

to a warming and drying climate. The same STATSGO soil 

map was used to create a SOC map for the 0 to 4 inches soil 

depth (the database was poorly populated for depths deeper 

than 4 inches). Each polygon received a value for SOC. The 

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 79

polygon values were assigned to one of four classes (low, 

moderate, high, very high) of SOC such that all classes 

contained the same number of polygons in each class. This 

method of creating general SOC classes was chosen because 

threshold class values for SOC are not available.

The ratings for soil temperature and moisture were then 

combined with the ratings for SOC into a four-class rating 

of soil vulnerability to climate change. A simple matrix was 

used to determine the final rating (table 4.2). The final soil 

vulnerability rating was applied to each polygon, and a general soil vulnerability map to climate change was developed 

(fig. 4.18). The map represents soils that may or may not 

be capable of sustaining existing ecosystems in a changing 

climate. The map suggests that soils at higher elevations and 

deeper soils are not as susceptible to climate change as the 

soils in warmer and drier areas. But this does not mean soils 

will not change in wetter or cooler climates or in locations 

high in SOC.

The regional-scale soil vulnerability map is a coarse 

estimation of potential change to soils with climate change. 

Local data and information are needed to estimate vulnerability at a local scale. Other soil properties that should 

be considered in creating a local map include: available 

water holding capacity, soil depth, hydrological soil group, 

erodibility (K) factor, soil texture, parent material, SOC, 

and calcium carbonate content (inorganic carbon), as well 

as vegetation type, geology, slope, aspect, and elevation. 

An example of how to create a soil vulnerability rating at a 

forest-project scale is given next.

Example Project-Scale Assessment of 

Soil Vulnerability to Climate Change

At the individual forest level, local soils information 

could be utilized to create maps of soil vulnerability to 

climate change at the project, watershed, or landscape scale. 

The Uinta-Wasatch-Cache National Forest used available 

soil data and applied a soil vulnerability assessment to a 

watershed-scale project during the project planning stage. 

The assessment was used initially to identify potential 

projects that would help create more resilient ecosystems 

and then to stratify fieldwork. Vegetation manipulation is 

one example of a specific adaptive management strategy to 

maintain or enhance soil health. Quaking aspen (Populus 

tremuloides) and pinyon-juniper vegetative communities 

were examined for this example.

A soil map was created for two watersheds within a project boundary. Vegetation and geology layers were added, as 

well as a digital elevation model to create slope and aspect. 

Soil available water holding capacity, soil depth to a restrictive layer, hydrological group, parent material, and soil 

temperature and moisture regimes were included in a matrix 

and rated for each soil type to derive vulnerability to climate 

change. Using soil indicators, along with vegetation and 

geology layers, we can estimate nutrient content, SOM, and 

how well a soil retains moisture. These estimates were used 

to assign a rating for soil vulnerability to climate change 

(table 4.3). The higher the point value rating, the more 

resilient and resistant the soil resources are to the effects of 

a warmer and drier climate. This information was added to 

the soil attribute table in a geographic information system 

(GIS). Potential focus areas for fieldwork verification and 

for recommended vegetation projects to meet desired conditions were identified by creating intersects for vegetation 

attributes of interest. An example of an interpretive map is 

shown in figure 4.19.

The value ranges or ratings will be used to focus attention on soil resources that best meet vegetation management 

objectives. Soils that are more suitable or resistant to change 

(less vulnerable to climate change) are those expected to 

better maintain soil moisture and nutrient conditions favorable for the vegetative communities present. These soils will 

be areas of opportunity for vegetation management designed 

to sustain existing vegetation community types.

Conclusions from the soil vulnerability analysis include:

1. Sustaining aspen vegetative communities within 

the project area will be one of the objectives of the 

project. Vegetative treatments will be implemented 

to promote aspen retention and increase diversity 

of aspen age classes. The climate change soil 

vulnerability rating was determined for each of the 

aspen polygons in the treatment area. An examination 

of the rating criteria showed some aspen stands with 

Table 4.2—Final rating classes for soil vulnerability to climate change, based on a combination of soil temperature/

moisture rating and soil organic carbon rating.

Organic carbon 

rating = Low

Organic carbon 

rating = Moderate

Organic carbon 

rating = High

Organic carbon 

rating = Very high

Temperature/moisture 

rating = Low Low Low Moderate High

Temperature/moisture 

rating = Moderate Low Moderate Moderate High

Temperature/moisture 

rating = High Moderate Moderate High Very High

Temperature/moisture 

rating = Very high High High Very High Very High

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
80 USDA Forest Service RMRS-GTR-375. 2018

Figure 4.18—Soil vulnerability to climate change in the Intermountain Adaptation Partnership region, 

based on ratings in table 4.2 (combination of soil temperature/moisture and soil organic carbon).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 81 Table 4.3—Forest-level soil vulnerability indicators and ratings. Water holding capacity Soil depth Hydrological group Aspect Parent material Soil temperature/ moisture regime Point value range Suitability rating Vulnerability rating Valuea Pts b Inches Pts Group Pts Group Pts Texture Pts Valuea Pts VH 12 60+ 12 A 9 N 9 Fine 9 L 9 46–60 VH VL H 9 40–60 9 B 6 E 6 Medium 6 M 6 33–45

H L

M 6 20–40 6 C 3 W 3 Coarse 3 H 3 20–32

M

M

L 3 11–20 3 D 0 S 0 VH 0 7–19 L H

VL 0 0–10 0 0–6 VL VH

a VH = very high, H = high, M = moderate, L = low, VL = very low.b Pts = points.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
82 USDA Forest Service RMRS-GTR-375. 2018

Figure 4.19—Example of soil vulnerability to climate change at a small spatial scale, based on ratings in 

table 4.2 (combination of soil temperature/moisture and soil organic carbon). Numbers indicate soil 

series mapping units (not discussed here).

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 83

a very high to high vulnerability rating and some 

with a moderate vulnerability rating. Aspen stands 

with a moderate vulnerability rating will be areas 

for recommended project work to maintain aspen 

community types. The aspen stands located within 

the high and very high vulnerability areas will not 

be recommended for aspen regeneration treatments 

unless a site visit indicates available water could be 

sustained in a warmer, drier climate.

2. Pinyon-juniper encroachment into shrublands and 

grasslands is occurring because of a lack of fire. 

Removal of the pinyon and juniper is recommended 

in areas that currently have mountain big sagebrush 

in the understory, with the objective of increasing 

sagebrush cover. Removal would be accomplished 

through mechanical treatments (mastication) and lopand-scatter. Very high to low soil vulnerability ratings 

were found across the project area where pinyonjuniper exists. Soils that were rated as very high to 

high in vulnerability are areas with shallow soils 

and low available water holding capacity. Pinyonjuniper may decrease in dominance in these areas 

with a reduction in available soil water due to climate 

change. Removal of pinyon and juniper may make 

these areas more susceptible to invasion by nonnative 

species such as cheatgrass. In areas rated as having 

low to moderate vulnerability to climate change, the 

ability to manage for restoration of shrublands may 

be higher as soils are expected to retain soil moisture 

longer. Site visits will be used to verify potential for 

management.

Summary and Conclusions

Climate change will alter fundamental physical processes 

in the IAP region, including hydrological processes and soil 

processes. Changes in physical processes will in turn affect 

biological processes, including soil microbial processes and 

vegetation growth and development. These physical and 

biological effects of climate change are complex and will be 

highly variable across the IAP region.

Warming temperatures will reduce snowpack accumulation and advance snowmelt timing in the region. Despite 

mixed signals from precipitation and temperature changes 

in the historical record, future temperature changes are 

expected to be higher than historical temperature trends, 

and future precipitation declines are expected to be less 

pronounced—and increased precipitation is possible. Earlier 

streamflow center of timing is expected over much of the 

region, and summer low flows are expected to be lower. 

Total water yields may decrease due to increased ET, but 

precipitation amounts are uncertain. Increasing precipitation 

could outweigh ET effects on total water yields, but decreasing precipitation could substantially exacerbate declines 

in annual water yield and low flows. The frequency and 

extent of midwinter flooding are expected to increase. Flood 

magnitudes are also expected to increase because rain-onsnow-driven peakflows will become more common.

Places with seasonally intermittent snowpacks are 

likely to see snow more rarely. Some mid- to low-elevation 

seasonal snowpacks are likely to become intermittent. 

Higher-elevation snowpacks may or may not undergo 

substantial changes in April 1 SWE, snow residence time, or 

center of melt timing, depending on precipitation outcomes. 

In warmer locations, temperature-dependent changes are 

relatively robust even if precipitation increases. In colder 

locations, a precipitation increase within the range of projected possibilities could cancel or overwhelm the effects of 

even a relatively large temperature change. Alternatively, a 

precipitation decrease could exacerbate projected temperature-related declines.

Glacier accumulation zones are at some of the highest 

elevations of the region, so they may respond positively if 

precipitation increases. Annual dynamics of mass balance 

with respect to input and output suggest that the equilibrium 

line (demarcating places where annual snow does not 

completely melt each summer) will increase in elevation, 

regardless of precipitation; where that elevation falls on 

each glacier will influence glacier response. Most glaciers 

will be reduced in volume and area and may become small 

enough to prevent movement. If climate at higher elevations 

becomes both warmer and drier, glaciers are unlikely to 

persist.

Groundwater recharge is likely to decrease in the 

southern portion of the IAP region, but changes in recharge 

remain uncertain throughout the region given limited 

understanding of mountain recharge processes and groundwater flow in mountain blocks. Groundwater recharge has 

been examined in only a few locations, and little is known 

about groundwater recharge processes in many watersheds. 

Higher minimum temperatures will reduce the longevity of 

snowpack, and decrease the length of time aquifer recharge 

can occur, potentially leading to faster runoff and less 

groundwater recharge. Some watersheds will be shifting 

from snow-dominated to rain-dominated, which may result 

in declines in groundwater recharge. Because many biological processes are temperature dependent, climate-induced 

changes in groundwater temperature may negatively affect 

aquatic communities. But because the thermal regime of 

groundwater systems is less dependent on air temperature 

patterns than on surface waters, the effects of rising air temperatures are likely to be less pronounced in groundwater 

discharges. Plant species in GDEs can respond to even slight 

changes in water table elevation, and shifts in composition 

of both vascular and bryophyte species could occur with 

lowered water tables.

Soil temperature and moisture are the primary drivers of 

change for all soil processes. The magnitude of projected 

change in soils with climate change is variable and depends 

on existing soil resources and existing climate. An increase 

in soil temperature will generally produce an increase in soil 

biological activity and soil respiration. In the current semiarid soils of the IAP region, an increase in soil temperature 

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
84 USDA Forest Service RMRS-GTR-375. 2018

without an increase in soil moisture is likely to result in 

reduced biological activity, increased respiration, and 

decreased potential to store carbon. In the colder and wetter 

areas of the IAP region, an increase in soil temperature may 

lead to greater biological activity and to longer growing 

seasons if soil moisture is not limiting. Soils derived from 

coarse-textured parent material will transfer heat more efficiently down into the soil profile than will fine-textured 

soils. The heat transfer downward can affect soil processes 

and even groundwater temperatures. Fine-textured soils are 

capable of storing water longer in the soil profile, providing 

a buffer to warming and higher water demands by plants.

Changes in soil temperature and moisture will affect 

carbon and nitrogen cycles. Changes to carbon and nitrogen 

cycles may include an increase or reduction in cycling rates 

or storage of carbon and nitrogen. Soil organic carbon may 

contain more than three times as much carbon as is found 

in the atmosphere or terrestrial vegetation, and it supports 

many soil processes and functions. These include providing nutrients for plants, binding soil particles together and 

thereby maintaining structure, providing an energy source 

for microbes, increasing water infiltration and retention, and 

providing cation/anion exchange for retention of ions and 

nutrients. Climate change will affect SOC and ultimately the 

functions and processes supported by SOC. Most of the soils 

in the IAP region can sequester additional carbon if soil 

temperatures decrease and soil moisture increases. However, 

most climate models suggest warmer soil temperatures and 

various soil moisture changes. The warming temperatures 

without additional moisture may reduce SOC and capability 

of soils to store carbon.

Changes to SOC with climate change can cause changes 

to several soil properties that are directly tied to the amount 

of SOC. These include soil structure, bulk density, and soil 

porosity. These soil properties affect water infiltration, rooting depth, soil erosional losses, and water holding capacity. 

These properties are potential indicators that can be used to 

determine the effects of climate change and where management changes may be needed to adapt to a changing soil 

environment.

Soil organisms perform many functions including 

decomposition and nutrient cycling. The effects of climate 

change on soil biology are mixed. Warming of the soil may 

result in greater microbial activity, releasing more carbon to 

the atmosphere through increased decomposition. Warming 

of the soil may also result in slowed microbial growth and 

less carbon being released through respiration. Greater soil 

biodiversity is expected to increase soil resilience to changing climate.

Potential effects to soil chemical properties with climate 

change are linked to other biological and physical changes 

in the soil, all of which are driven by the soil temperature 

and moisture inputs. Salinization, acidification, pH, and 

cation exchange capacity are soil processes and properties 

that will change with changes to climate. In general, the 

lower-elevation, drier shrubland and grassland soils are 

more vulnerable to changes in soil chemical processes and 

properties.

There are many potential management actions to decrease vulnerabilities to climate change. The information 

in this chapter was used as the basis for development of 

climate change adaptation strategies and tactics for water 

use, GDEs, and soils (Appendix 4, Chapter 14).

Acknowledgments

Many thanks to Patrick Kormos and Abigail Lute for 

generating many of the figures in this report.

References

Abatzoglou, J.T.; Kolden, C.A. 2013. Relationships between 

climate and macroscale area burned in the western United 

States. International Journal of Wildland Fire. 22: 1003–1020.

Ajami, H.; Meixner, T.; Dominguez, F.; [et al.]. 2012. 

Seasonalizing mountain system recharge in semi-arid basins—

climate change impacts. Groundwater. 50: 585–597.

Aldous, A.R.; Gannett, M.W.; Keith, M.; O’Connor, J. 2015. 

Geologic and geomorphic controls on the occurrence of fens 

in the Oregon Cascades and implications for vulnerability and 

conservation. Wetlands. 35: 757–767.

Allen, E.F.; Rittenour, T.M.; DeRose, R.J.; [et al.]. 2013. A 

tree-ring based reconstruction of Logan River streamflow in 

northern Utah. Water Resources Research. 49: 1–10.

Barnett, T.P.; Adam, J.C.; Lettenmaier, D.P. 2005. Potential impacts 

of a warming climate on water availability in snow-dominated 

regions. Nature. 438: 303–309.

Barnett, T.P.; Pierce, D.W. 2009. Sustainable water deliveries from 

the Colorado River in a changing climate. Proceedings of the 

National Academy of Sciences. 106: 7334–7338.

Barnett, T.P.; Pierce, D.W.; Hidalgo, H.G.; [et al.]. 2008. Humaninduced changes in the hydrology of the western United States. 

Science. 319: 1080–1083.

Barquin, J.; Death, R.G. 2006. Spatial patterns of diversity in 

New Zealand springs and rhithral streams. Journal of the North 

American Benthological Society. 25: 768–786.

Bekker, M.F.; DeRose, R.J.; Buckley, B.M.; [et al.]. 2014. A 576-

year Weber River streamflow reconstruction from tree rings 

for water resource risk assessment in the Wasatch Front, Utah. 

Journal of the American Water Resources Association. 50: 

1338–1348.

Bertrand, G.; Goldscheider, N.; Gobat, J.M.; Hunkeler, D. 2012. 

Review: from multiscale conceptualization of groundwaterdependent ecosystems to a classification system for 

management purposes. Hydrogeology Journal. 20: 5–25.

Blankinship, J.C.; Meadows, M.W.; Lucas, R.G.; Hart, S.C. 2014. 

Snowmelt timing alters shallow but not deep soil moisture in 

the Sierra Nevada. Water Resources Research. 50: 1448–1456.

Blevins, E.; Aldous, A. 2011. Biodiversity value of groundwaterdependent ecosystems. Wetland Science and Practice. 1: 18–24.

Blöschl, G.; Montanari, A. 2010. Climate change impacts—

Throwing the dice? Hydrological Processes. 24: 374–381.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 85

Brady, N.C. 1999. Elements of the nature and properties of soils, 

12th edition. Upper Saddle River, NJ: Prentice-Hall.

Brevik, E.C. 2013. The potential impact of climate change on soil 

properties and processes and corresponding influence on food 

security. Agriculture. 3: 398–417.

Busch, D.E.; Smith, S.D. 1995. Mechanisms associated with 

decline of woody species in riparian ecosystems of the 

southwestern U.S. Ecological Monographs. 65: 347–370.

Byrne, J.M.; Fagre, D.; MacDonald, R. 2014. Climate change and 

the Rocky Mountains. In: Grover, V.I.; Borsdorf, A.; Breuste, J.; 

[et al.], eds. Impact of global changes on mountains: Responses 

and adaptation. Boca Raton: CRC Press: 432–463.

Cayan, D.R.; Das, T.; Pierce, D.W.; [et al.]. 2009. Future dryness 

in the southwest US and the hydrology of the early 21st century 

drought. Proceedings of the National Academy of Sciences 107: 

21271–21276.

Cayan, D.R.; Dettinger, M.D.; Kammerdiener, S.A.; [et al.]. 2001. 

Changes in the onset of spring in the Western United States. 

American Meteorological Society. 82: 399–415.

Chadde, S.W.; Shelly, J.S.; Bursik, R.J.; [et al.]. 1998. Peatlands 

on National Forests of the northern Rocky Mountains: Ecology 

and conservation. Gen. Tech. Rep. RMRS-GTR-11. Ogden, 

UT: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 75 p.

Clark, G.M. 2010. Changes in patterns of streamflow from 

unregulated watersheds in Idaho, Western Wyoming, and 

Northern Nevada. Journal of the American Water Resources 

Association. 46: 486–497.

Clayton, J.A.; Julander, R.P. 2015. Discussion of influences on 

snow water equivalent at Utah snow courses. Journal of Earth 

Science and Engineering. 5: 147–172.

Cook, B.I.; Seager, R. 2013. The response of the North American 

monsoon to increased greenhouse gas forcing. Journal of 

Geophysical Research, Atmospheres. 118: 1690–1699.

Cook, B.I.; Smerdon, J.E.; Seager, R.; Coats, S. 2014. Global 

warming and 21st century drying. Climate Dynamics. 43: 

2607–2627.

Cooper, D.J.; Merritt, D.M. 2012. Assessing the water needs of 

riparian and wetland vegetation in the western United States. 

Gen. Tech. Rep. RMRS-GTR-282. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station. 125 p.

Cooper, D.J; Merritt, D.M.; Anderson, D.C.; Chimner, R.A. 1999. 

Factors controlling the establishment of Fremont cottonwood 

seedlings on the upper Green River, U.S.A. Regulated Rivers: 

Research and Management. 15: 419–440.

Cowardin, L.M.; Carter, V.; Golet, F.C.; LaRoe, E.T. 1979. 

Classification of wetlands and deepwater habitats of the United 

States. FWS/OBS-79/31. Washington, DC: U.S. Department of 

the Interior, U.S. Fish and Wildlife Service. 132 p.

Dai, A. 2013. Increasing drought under global warming in 

observations and models. Nature Climate Change. 3: 52–58.

Dawadi, S.; Ahmad, S. 2012. Changing climatic conditions in 

the Colorado River Basin: Implications for water resources 

management. Journal of Hydrology. 430–431: 127–141.

DeRose, R.J.; Bekker, J.F.; Wang, S.-Y.; [et al.]. 2015. A 

millennium-length reconstruction of Bear River stream flow, 

Utah. Journal of Hydrology. 529: 524–534.

Drexler, J.A.; Knifong, D.; Tuil, J.; [et al.]. 2013. Fens as wholeecosystem gauges of groundwater recharge under climate 

change. Journal of Hydrology. 481: 22–34.

Earman, S.; Campbell, A.R.; Phillips, F.M.; Newman, B.D. 2006. 

Isotopic exchange between snow and atmospheric water 

vapor: Estimation of the snowmelt component of groundwater 

recharge in the southwestern United States. Journal of 

Geophysical Research Atmospheres. 111: D09302.

Earman, S.; Dettinger, M. 2011. Potential impacts of climate 

change on groundwater resources—A global review. Journal of 

Water and Climate Change. 2: 213–229.

Emmett, B.A.; Beier, C.; Estiarte, M.; [et al.]. 2004. The response 

of soil processes to climate change: results from manipulation 

studies of shrublands across an environmental gradient. 

Ecosystems. 7: 625–637.

Figura, S.; Livingstone, D.M.; Hoehn, E.; Kipfer, R. 2011. Regime 

shift in groundwater temperature triggered by the Arctic 

Oscillation. Geophysical Research Letters. 38: 1–5.

Flint, A.L.; Flint, L.E.; Dettinger, M.D. 2008. Modeling soil 

moisture processes and recharge under a melting snowpack. 

Vadose Zone Journal. 7: 350–357.

Gannett, M. 1984. Groundwater assessment of the John Day basin. 

Salem, OR: Oregon Water Resources Department. 99 p.

Gergel, D.R.; Nijssen, B.; Abatzoglou, J.T.; [et al.]. 2017. Effects 

of climate change on snowpack and fire potential in the western 

United States. Climatic Change. 141: 287–299.

Goode, J.R.; Buffington, J.M.; Tonina, D.; [et al.]. 2013. Potential 

effects of climate change on streambed scour and risks to 

salmonid survival in snow-dominated mountain basins. 

Hydrological Processes. 27: 750–765.

Goode, J.R.; Luce, C.H.; Buffington, J.M. 2012. Enhanced 

sediment delivery in a changing climate in semi-arid 

mountain basins: Implications for water resource management 

and aquatic habitat in the northern Rocky Mountains. 

Geomorphology. 139–140: 1–15.

Goslee, S.C.; Brooks, R.P.; Cole, C.A. 1997. Plants as indicators of 

wetland water source. Plant Ecology. 131: 199–206.

Green, T.R.; Taniguchi, M.; Kooi, H.; [et al.]. 2011. Beneath the 

surface: Impacts of climate change on groundwater. Journal of 

Hydrology. 405: 532–560.

Hall, M.H.; Fagre, D.B. 2003. Modeled climate-induced glacier 

change in Glacier National Park, 1850–2100. BioScience. 53: 

131–140.

Hanson, R.T.; Flint, L.E.; Flint, A.L.; [et al.]. 2012. A method for 

physically based model analysis of conjunctive use in response 

to potential climate changes. Water Resources Research. 48: 

W00L08.

Healy, R.W.; Cook, P.G. 2002. Using groundwater levels to 

estimate recharge. Hydrogeology Journal. 10: 91–109.

Held, I.M.; Soden, B.J. 2006. Robust responses of the hydrological 

cycle to global warming. Journal of Climate. 19: 5686–5699.

Intergovernmental Panel on Climate Change [IPCC]. 2013. 

Climate change 2013: The physical science basis. Contribution 

of working group I to the fifth assessment report of the 

Intergovernmental Panel on Climate Change. Cambridge, 

United Kingdom and New York, NY, USA: Cambridge 

University Press. 1535 p.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
86 USDA Forest Service RMRS-GTR-375. 2018

Jencso, K.G.; McGlynn, B.L. 2011. Hierarchical controls on runoff 

generation: Topographically driven hydrologic connectivity, 

geology, and vegetation. Water Resources Research. 47: 

W11527.

Jencso, K.G.; McGlynn, B.L.; Gooseff, M.N.; [et al.]. 2009. 

Hydrologic connectivity between landscapes and streams: 

Transferring reach-and-plot-scale understanding to the 

catchment scale. Water Resources Research. 45: W04428.

Kardol, P.; Cregger, M.A.; Campany, C.E.; Classen, A.T. 2010. 

Soil ecosystem functioning under climate change: Plant species 

and community effects. Ecology. 91: 767–781.

Kløve, B.; Ala-aho, P.; Okkonen, J.; Rossi, P. 2012. Possible effects 

of climate change on hydrogeological systems: Results from 

research on esker aquifers in northern Finland. In: Treidel, H.; 

Martin-Bordes, J.J.; Gurdak, J.J., eds. Climate change effects 

on groundwater resources: A global synthesis of findings and 

recommendations. New York, NY: Taylor & Francis Publishing, 

International Association of Hydrogeologists (IAH)–

International Contributions to Hydrogeology: 305–322.

Kormos, P.; Luce, C.; Wenger, S.J.; Berghuijs, W.R. 2016. Trends 

and sensitivities of low streamflow extremes to discharge 

timing and magnitude in Pacific Northwest mountain streams. 

Water Resources Research. 52: 4990–5007.

Kreamer, D.K.; Stevens, L.E.; Ledbetter, J.D. 2015. Groundwater 

dependent ecosystems—Science, challenges, and policy. 

In: Adelana, S.M., ed. Groundwater. Hauppauge, NY: Nova 

Science Publishers, Inc.: 205–230.

Kurylyk, B.L.; MacQuarrie, K.T.B; McKenzie, J.M. 2014. Climate 

change impacts on groundwater and soil temperatures in cold 

and temperate regions: Implications, mathematical theory, 

and emerging simulation tools. Earth-Science Reviews. 138: 

313–334.

Kværner, J.; Snilsberg, P. 2011. Groundwater hydrology of boreal 

peatlands above a bedrock tunnel—Drainage impacts and 

surface water groundwater interactions. Journal of Hydrology. 

403: 278–291.

Lawrence, D.J.; Stewart-Koster, B.; Olden, J.D.; [et al.]. 2014. The 

interactive effects of climate change, riparian management, 

and a nonnative predator on stream-rearing salmon. Ecological 

Applications. 24: 895–912.

Lee, L.J.E.; Lawrence, D.S.L.; Price, M. 2006. Analysis of 

water level response to rainfall and implications for recharge 

pathways in the Chalk aquifer, SE England. Journal of 

Hydrology. 330: 604–620.

Leibowitz, S.G.; Comoleo, R.L.; Wigington, P.J.; [et al.]. 2014. 

Hydrologic landscape classification assesses streamflow 

vulnerability to climate change in Oregon, USA. Hydrology 

and Earth System Sciences Discussions. 11: 2875–2931.

Liang, X.; Lettenmaier, D.P.; Wood, E.F.; Burges, S.J. 1994. 

A simple hydrologically based model of land surface water 

and energy fluxes for general circulation models. Journal of 

Geophysical Research. 99: 14415–14428.

Lins, H.F. 1997. Regional streamflow regimes and 

hydroclimatology. Water Resources Research. 33: 1655–1667.

Litschert, S.E.; Theobald, D.M.; Brown, T.C. 2014. Effects of 

climate change and wildfire on soil loss in the Southern Rockies 

ecoregion. Catena. 118: 206–219.

Littell, J.S.; Elsner, M.M.; Mauger, G.S.; [et al.]. 2011. Regional 

climate and hydrologic change in the northern US Rockies and 

Pacific Northwest: Internally consistent projections of future 

climate for resource management. Unpublished project report. 

http://cses.washington.edu/picea/USFS/pub/Littell_etal_2010 

[Accessed December 5, 2016].

Luce, C.H.; Abatzoglou, J.T.; Holden, Z.A. 2013. The missing 

mountain water: Slower westerlies decrease orographic 

enhancement in the Pacific Northwest USA. Science. 342: 

1360–1364.

Luce, C.H.; Holden, Z.A. 2009. Declining annual streamflow 

distributions in the Pacific Northwest United States, 1948-2006. 

Geophysical Research Letters 36: L16401.

Luce, C.H.; Lopez-Burgos, V.; Holden, Z. 2014. Sensitivity of 

snowpack storage to precipitation and temperature using spatial 

and temporal analog models. Water Resources Research. 50: 

9447–9462.

Luce, C.H.; Morgan, P.; Dwire, K.A.; [et al.]. 2012. Climate 

change, forests, fire, water, and fish: Building resilient 

landscapes, streams and managers. Gen. Tech. Rep. RMRSGTR-290. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station. 207 p.

Luce, C.H.; Pederson, N.; Campbell, J.; [et al.]. 2016. 

Characterizing drought for forested landscapes and streams. 

In: Vose, J.M.; Clark, J.S.; Luce, C.H.; Patel-Weynand, T., 

eds. Effects of drought on forests and rangelands in the United 

States: A comprehensive science synthesis. Gen. Tech. Rep. 

WO-93b. Washington, DC: U.S. Department of Agriculture, 

Forest Service, Washington Office: 13–48.

MacDonald, G.M.; Tingstad, A.H. 2007. Recent and 

multicentennial precipitation variability and drought occurrence 

in the Uinta Mountains region, Utah. Arctic, Antarctic, and 

Alpine Research. 39: 549–555.

Magee, T.K; Kentula, M.E. 2005. Response of wetland plant 

species to hydrologic conditions. Wetlands Ecology and 

Management. 13: 163–181.

Marston, R.A.; Pochop, L.O.; Kerr, G.L.; [et al.]. 1991. Recent 

glacier changes in the Wind River Range, Wyoming. Physical 

Geography. 12: 115–123.

Maxwell, R.M.; Kollet, S.J. 2008. Interdependence of groundwater 

dynamics and land-energy feedbacks under climate change. 

Nature Geoscience. 1: 665–669.

McCabe, G.J.; Fountain, A.G. 1995. Relations between 

atmospheric circulation and mass balance of South Cascade 

Glacier, Washington, USA. Arctic and Alpine Research. 27: 

226–233.

Meixner, T., Manning, A.H., Stonestrom, D.A.; [et al.]. 2016. 

Implications of projected climate change for groundwater 

recharge in the western United States. Journal of Hydrology. 

534: 124–138.

Merritt, D.M.; Scott, M.L.; Poff, N.L.; [et al.]. 2010. Theory, 

methods, and tools for determining environmental flows for 

riparian vegetation: Riparian-flow response guilds. Freshwater 

Biology. 55: 206–225.

Meyer, S.E. 2012. Restoring and managing cold desert shrublands 

for climate change mitigation. In: Finch, D.M., ed. Climate 

change in grasslands, shrublands, and deserts of the interior 

American West: A review and needs assessment. Gen. Tech. 

Rep. RMRS-GTR-285. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station: 

21–34.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 87

Milly, P.; Dunne, K.A. 2011. On the hydrologic adjustment of 

climate-model projections: The potential pitfall of potential 

evapotranspiration. Earth Interactions. 15: 1–14.

Milly, P.C.D. 1992. Potential evaporation and soil moisture in 

general circulation models. Journal of Climate. 5: 209–226.

Mote, P.W. 2006. Climate-driven variability and trends in mountain 

snowpack in western North America. Journal of Climate. 19: 

6209–6220.

Mote, P.W.; Hamlet, A.F.; Clark, M.P.; Lettenmaier, D.P. 2005. 

Declining mountain snowpack in western North America. 

Bulletin of the American Meteorological Society. 86: 39–49.

Murray, B.R.; Hose, G.C.; Eamus D.; Licari, D. 2006. Valuation of 

groundwater-dependent ecosystems: A functional methodology 

incorporating ecosystem services. Australian Journal of Botany. 

54: 221–229.

Musselman, K.N.; Clark, M.P.; Liu, C.; [et al.]. 2017. Slower 

snowmelt in a warmer world. Nature Climate Change. 7: 

214–219.

Naiman, R.J.; Dècamps, H.; McCalin, M.E. 2005. Riparia: 

Ecology, conservation, and management of streamside 

communities. Burlington, MA: Elsevier Academic Press. 430 p.

Natural Resources Conservation Service [NRCS]. 2017. Web Soil 

Survey. http://websoilsurvey.nrcs.usda.gov/ [Accessed March 

15, 2016].

Nave, L.E.; Swanston, C.W.; Mishra, U.; Nadelhoffer, K.J. 2013. 

Afforestation effects on soil carbon storage in the United States: 

A synthesis. Soil Science Society of America Journal. 77: 

1035–1047.

Nolin, A.W.; Daly, C. 2006. Mapping “at risk” snow in the Pacific 

Northwest. Journal of Hydrometeorology. 7: 1164–1171.

Page-Dumroese, D.S.; Jurgensen, M.F. 2006. Soil carbon and 

nitrogen pools in mid- to late-successional forest stands of the 

northwestern United States: Potential impact of fire. Canadian 

Journal of Forest Research. 36: 2270–2284.

Pal Singh, B.; Cowie, A.L.; Chan, K.Y. 2011. Soil health and 

climate change. Berlin: Springer-Verlag.

Pierce, D.W.; Barnett, T.P.; Hidalgo, H.G.; [et al.]. 2008. 

Attribution of declining western U.S. snowpack to human 

effects. Journal of Climate. 21: 6425–6444.

Poff, N.L. 1996. A hydrogeography of unregulated streams in the 

United States and an examination of scale-dependence in some 

hydrological descriptors. Freshwater Biology. 36: 71–91.

Portland State University. 2009. Glaciers of the American West. 

http://glaciers.research.pdx.edu/states- [Accessed April 21, 

2017].

Price, D. 1985. Ground water in Utah’s densely populated Wasatch 

Front area—The challenge and the choices. U.S. Geological 

Survey Water Supply Paper 2232. Washington, DC: U.S. 

Government Printing Office.

Regonda, S.; Rajagopalan, B.; Clark, M.; Pitlick, J. 2005. Seasonal 

cycle shifts in hydroclimatology over the western United States. 

Journal of Climate. 18: 372–384.

Rice, J.; Bardsley, T.; Gomben, P.; [et al.]. 2017. Assessment 

of watershed vulnerability to climate change for the UintaWasatch-Cache and Ashley National Forests, Utah. Gen. Tech. 

Rep. RMRS-GTR-362. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 

111 p.

Roderick, M.L.; Greve, P.; Farquhar, G.D. 2015. On the assessment 

of aridity with changes in atmospheric CO2

. Water Resources 

Research. 51: 5450–5463.

Roderick, M.L.; Sun, F.; Lim, W.H.; Farquhar, G.D. 2014. A 

general framework for understanding the response of the water 

cycle to global warming over land and ocean. Hydrology and 

Earth System Sciences. 18: 1575–1589.

Rood, S.B.; Pan, J.; Gill, K.M.; [et al.]. 2008. Declining summer 

flows of Rocky Mountain rivers: Changing seasonal hydrology 

and probable impacts on floodplain forests. Journal of 

Hydrology. 349: 397–410.

Safeeq, M.; Grant, G.E.; Lewis, S.L.; [et al.]. 2014. A 

hydrogeologic framework for characterizing summer 

streamflow sensitivity to climate warming in the Pacific 

Northwest, USA. Hydrology and Earth System Sciences. 18: 

3693–3710.

Safeeq, M.; Grant, G.E.; Lewis, S.L.; Tague, C.L. 2013. Coupling 

snowpack and groundwater dynamics to interpret historical 

streamflow trends in the western United States. Hydrological 

Processes. 27: 655–668.

Santhi, C.; Allen, P.M.; Muttiah, R.S.; [et al.]. 2008. Regional 

estimation of base flow for the conterminous United States 

by hydrologic landscape regions. Journal of Hydrology. 351: 

139–153.

Seager, R.; Naik, N.; Vecchi, G.A. 2010. Thermodynamic 

and dynamic mechanisms for large-scale changes in the 

hydrological cycle in response to global warming. Journal of 

Climate. 23: 4651–4668.

Service, R.F. 2004. As the West goes dry. Science. 303: 1124–1127.

Shipley, B.; Keddy, P.A.; Lefkovich, L.P. 1991. Mechanisms 

producing plant zonation along a water depth gradient: A 

comparison with the exposure gradient. Canadian Journal of 

Botany. 69: 1420–1424.

Sophocleous, M. 2002. Interaction between groundwater and 

surface water: the state of the science. Hydrogeology Journal. 

10: 52–67.

Steinweg, J.M.; Dukes, J.S.; Paul, E.A.; Wallenstein, M.D. 

2014. Microbial responses to multi-factor climate change: 

Effects on soil enzymes. The Microbial Regulation of Global 

Biogeochemical Cycles. 4: 105–118.

Stewart, I.T.; Cayan, D.R.; Dettinger, M.D. 2005. Changes toward 

earlier streamflow timing across western North America. 

Journal of Climate. 18: 1136–1155.

Stockton, C.W.; Jacoby, G.C. 1976. Long-term surface-water 

supply and streamflow trends in the Upper Colorado River 

Basin. Lake Powell Research Project Bulletin No. 18. 

Arlington, VA: National Science Foundation. 70 p.

Tague, C.; Grant, G.E. 2009. Groundwater dynamics mediate 

low-flow response to global warming in snow-dominated alpine 

regions. Water Resources Research. 45: W07421.

Thomey, M.L.; Ford, P.L.; Reeves, M.C.; [et al.]. 2014. Review 

of climate change impacts on future carbon stores and 

management of warm deserts of the United States. Gen. Tech. 

Rep. RMRS-GTR-316. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 

26 p.

Tonina, D.; Luce, C.H.; Rieman, B.; [et al.]. 2008. Hydrological 

response to timber harvest in northern Idaho: Implications 

for channel scour and persistence of salmonids. Hydrological 

Processes. 22: 3223–3235.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
88 USDA Forest Service RMRS-GTR-375. 2018

Torgersen, C.E.; Ebersole, J.L.; Keenan, D.M. 2012. Primer for 

identifying cold-water refuges to protect and restore thermal 

diversity in riverine landscapes. U.S. Environmental Protection 

Agency Report EPA 910-C-12-001. Seattle, WA: U.S. 

Environmental Protection Agency, Region 10. 78 p.

Torgersen, C.E.; Price, D.M.; Li, H.W.; McIntosh, B.A. 1999. 

Multiscale thermal refugia and stream habitat associations 

of Chinook salmon in northwestern Oregon. Ecological 

Applications. 9: 301–319.

Tujchneider, O.; Paris, M.; Perez, M.; D’Elia, M. 2012. Possible 

effects of climate change on groundwater resources in the 

central region of Santa Fe province, Argentina. In: Treidel, H.; 

Martin-Bordes, J.J.; Gurdak, J.J., eds. Climate change effects 

on groundwater resources: A global synthesis of findings and 

recommendations. New York, NY: Taylor & Francis Publishing, 

International Association of Hydrogeologists (IAH)–

International Contributions to Hydrogeology: 265–280.

U.S. Department of Agriculture, Forest Service [USDA FS]. 

2012a. Groundwater-dependent ecosystems: Level I inventory 

field guide; inventory methods for assessment and planning. 

Gen. Tech. Rep. WO-86a. Washington, DC: U.S. Department of 

Agriculture, Forest Service. 191 p.

U.S. Department of Agriculture, Forest Service [USDA FS]. 

2012b. Groundwater-dependent ecosystems: Level II inventory 

field guide; inventory methods for assessment and planning. 

Gen. Tech. Rep. WO-86b. Washington, DC: U.S. Department of 

Agriculture, Forest Service. 124 p.

U.S. Department of Agriculture, Forest Service [USDA FS]. 

[N.d.]. Western U.S. stream flow metrics. U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Air, Water, and Aquatic Environments Program. http://www.

fs.fed.us/rm/boise/AWAE/projects/modeled_stream_flow_

metrics.shtml [Accessed April 26, 2017].

U.S. Department of Energy [USDOE]. 2014. Overview of different 

aspects of climate change effects on soils. Richland, WA: U.S. 

Department of Energy, Pacific Northwest Laboratory. http://

www.pnnl.gov/main/publications/external/technical_reports/

PNNL-23483.pdf [Accessed January 24, 2017].

U.S. Fish and Wildlife Service [USFWS]. [n.d.]. National Wetlands 

Inventory. http://www.fws.gov/wetlands [Accessed September 

22, 2017].

U.S. Geological Survey [USGS]. 2000. Groundwater atlas of 

the United States. http://pubs.usgs.gov/ha/ha730/gwa.html 

[Accessed March 15, 2016].

U.S. Geological Survey [USGS]. 2017. Hydrography http://nhd.

usgs.gov [Accessed September 22, 2017].

University of Washington, Climate Impacts Group. 2017. CIG 

datasets. Western U.S. hydroclimate scenarios project. Seattle, 

WA: University of Washington, College of the Environment, 

Climate Impacts Group. https://cig.uw.edu/datasets/wus 

[Accessed September 22, 2017].

Vitt, D.H.; Slack, N.G. 1984. Niche diversification of Sphagnum 

relative to environmental factors in northern Minnesota 

peatlands. Canadian Journal of Botany. 62: 1409–1430.

Wada, Y.; van Beek, L.P.H.; Bierkens, M.F.P. 2012. Nonsustainable 

groundwater sustaining irrigation: A global assessment. Water 

Resources Research. 48: W00L06.

Waibel, M.S.; Gannett, M.W.; Chang, H.; Hulbe, C.L. 2013. 

Spatial variability of the response to climate change in regional 

groundwater systems—Examples from simulations in the 

Deschutes Basin, Oregon. Journal of Hydrology. 486: 187–201.

Walsh, J., D. Wuebbles, K. Hayhoe,; [et al.]. 2014. Our changing 

climate. Climate change impacts in the United States: The third 

National Climate Assessment. In: Melillo, J. M.; Richmond, 

T.; Yohe, G.W., eds. Washington, DC: U.S. Global Change 

Research Program: 19–67.

Wang, S.Y.; Gillies, R.R.; Reichler, T. 2012. Multi-decadal drought 

cycles in the Great Basin recorded by the Great Salt Lake: 

Modulation from a transition-phase teleconnection. Journal of 

Climate. 25: 1711–1721.

Ward, J.V.; Tockner, K. 2001. Biodiversity: Towards a unifying 

theme for river ecology. Freshwater Biology. 46: 807–819.

Weary, D.J.; Doctor, D.H. 2014. Karst in the United States: A 

digital map compilation and database. U.S. Geological Survey 

Open-File Report 2014–1156. Reston, VA: U.S Geological 

Survey.

Weltzin, J.F.; Pastor, J.; Harth, C.; [et al.]. 2000. Response of 

bog and fen plant communities to warming and water-table 

manipulations. Ecology. 81: 3464–3478.

Wenger, S.J.; Isaak, D.J.; Dunham, J.B.; [et al.]. 2011a. Role of 

climate and invasive species in structuring trout distributions in 

the interior Columbia River Basin, USA. Canadian Journal of 

Fisheries and Aquatic Sciences. 68: 988–1008.

Wenger, S.J.; Isaak, D.J.; Luce, C.H.; [et al.]. 2011b. Flow regime, 

temperature, and biotic interactions drive differential declines 

of trout species under climate change. Proceedings of the 

National Academy of Sciences, USA. 108: 14175–14180.

Wenger, S.J.; Luce, C.H.; Hamlet, A.F.; [et al.]. 2010. Macroscale 

hydrologic modeling of ecologically relevant flow metrics. 

Water Resources Research. 46: W09513.

Wenger, S.J.; Som, N.A.; Dauwalter, D.C.; [et al.]. 2013. 

Probabilistic accounting of uncertainty in forecasts of species 

distributions under climate change. Global Change Biology. 19: 

3343–3354.

Wieder, W.R.; Bonan, G.B.; Allison, S.D. 2013. Global soil carbon 

projections are improved by modelling microbial processes. 

Nature Climate Change. 3: 909-912.

Winter, T.C. 1999. Relation of streams, lakes, and wetlands to 

groundwater flow systems. Hydrogeology Journal. 7: 28–45.

Winter, T.C. 2007. The role of groundwater in generating 

streamflow in headwater areas and in maintaining baseflow. 

Journal of the American Water Resources Association. 43: 

15–25.

Winter, T.C.; Harvey, J.W.; Franke, O.L.: Alley, W.M. 1996. 

Ground water and surface water, a simple resource. USGS 

Circular 1139. Reston, VA: U.S. Geological Survey.

Woodall, C.W.; Coulston, J.W.; Domke, G.M.; [et al.]. 2015. The 

U.S. forest carbon accounting framework: stocks and stock 

change, 1990-2016. Gen. Tech. Rep. NRS-154. Newtown 

Square, PA: U.S. Department of Agriculture, Forest Service, 

Northern Research Station. 49 p.

Woodhouse, C.A.; Gray, S.T.; Meko, D.M. 2006. Updated 

streamflow reconstructions for the Upper Colorado River Basin. 

Water Resources Research. 42: W05415.

Woods, R.A. 2009. Analytical model of seasonal climate impacts 

on snow hydrology: Continuous snowpacks. Advances in Water 

Resources. 32: 1465–1481.

Yin, D.; Roderick, M.L.; Leech, G.; [et al.]. 2014. The contribution 

of reduction in evaporative cooling to higher surface air 

temperatures during drought. Geophysical Research Letters. 41: 

7891–7897.

Chapter 4: Effects of Climate Change on Hydrology, Water Resources, and Soil
USDA Forest Service RMRS-GTR-375. 2018 89

Introduction

The diverse landscapes of the Intermountain Adaptation 

Partnership (IAP) region contain a broad range of aquatic 

habitats and biological communities. A number of aquatic 

species are regional endemics, several are threatened or 

endangered under the U.S. Endangered Species Act (ESA), 

and many have declined because of the introduction of 

nonnative aquatic species, habitat fragmentation, and human development. Environmental trends associated with 

human-caused climate change have been altering the habitats of these species for several decades (Barnett et al. 2008; 

Hamlet and Lettenmaier 2007; Luce and Holden 2009; Mote 

et al. 2005), and more significant changes are expected 

during the 21st century (chapters 3, 4). For animals that live 

in or near aquatic environments such as fishes, amphibians, 

crayfish, mussels, and aquatic macroinvertebrates, changes 

in habitat and hydrological regimes are expected to shift 

their abundance and distribution (Ficke et al. 2007; Hauer et 

al. 1997; Poff et al. 2002; Rieman and Isaak 2010; Schindler 

et al. 2008). This is primarily because many of these species are ectothermic; thus, thermal conditions dictate their 

metabolic rates and most aspects of their life stages—how 

fast they grow and mature, whether and when they migrate, 

when and how often they reproduce, and when they die 

(Magnuson et al. 1979). Buffering these changes are the 

topographic diversity and steep environmental gradients of 

many landscapes throughout the IAP region, which contribute to slow climate velocities (sensu Loarie et al. 2009) 

and often create climate refugia where populations of many 

species can persist under all but the most extreme climatic 

changes (Isaak et al. 2016a; Morelli et al. 2016).

A large literature exists that describes the many interactions among climate change, aquatic environments, and 

cold-water fishes such as trout, salmon, and char (Hauer 

et al. 1997; Isaak et al. 2012a,b; ISAB 2007; Mantua and 

Raymond 2014; Mantua et al. 2010; Mote et al. 2003; 

Rieman and Isaak 2010; Young et al. 2018). Rather than 

revisiting those sources, we focus on providing information 

specific to the IAP region. First, we describe the ecology, 

status, and climate vulnerabilities of species of concern. 

Through discussions with scientists and U.S. Department 

of Agriculture Forest Service (USFS) Intermountain 

Region staff and national forest resource managers, species 

were chosen for their perceived vulnerability to climate 

Chapter 5: Effects of Climate Change on 

Native Fish and Other Aquatic Species

Daniel J. Isaak, Michael K. Young, Cynthia Tait, Daniel Duffield, Dona L. 

Horan, David E. Nagel, and Matthew C. Groce

change and their societal prominence as ESA-listed 

threatened and endangered species. The species are Rocky 

Mountain tailed frog (Ascaphus montanus), Idaho giant 

salamander (Dicamptodon aterrimus), western pearlshell 

mussel (Margaritifera falcata), springsnails (Pyrgulopsis

spp.), Yosemite toad (Anaxyrus canorus), Sierra Nevada 

yellow-legged frog (Rana sierrae), bull trout (Salvelinus 

confluentus), and cutthroat trout (Oncorhynchus clarkii). 

Second, we develop spatially explicit model projections 

and geospatial datasets showing where bull trout and cutthroat trout are most likely to occur in current and future 

climates. These projections are used to assess the potential 

and future distribution of suitable habitats for these species, 

but could also be used to design and implement long-term 

conservation strategies or monitoring programs. Although 

the availability of biological datasets and models for stream 

networks restricted our projections to trout in streams, 

the approach used here is easily extended to other aquatic 

species as more geographic data on these taxa are gathered 

and models are extended to standing waters. The preceding 

information was used to develop climate adaptation options 

for species of concern, including how new technologies and 

ongoing development of better information could enable 

strategic implementation of those options to maximize their 

effectiveness.

Analysis Area Network and 

Stream Climate Scenarios

This assessment encompasses all streams in the USFS 

Intermountain Region that flow through its 12 national 

forests and lands downstream of those forests. To delineate 

a network that represented streams within this area, geospatial data for the 1:100,000-scale National Hydrography 

Dataset (NHD)-Plus Version 2 were downloaded from the 

Horizons Systems website (Horizon Systems Corp. http://

ww.horizon-systems.com/nhdplus/; McKay et al. 2012) 

and filtered by minimum flow and maximum stream slope 

criteria. Summer flow values predicted by the Variable 

Infiltration Capacity (VIC) hydrological model (Wenger 

et al. 2010) were obtained from the Western U.S. Flow 

Metrics website (USDA FS https://www.fs.fed.us/rm/boise/

AWAE/projects/modeled_stream_flow_metrics.shtml) and 
90 USDA Forest Service RMRS-GTR-375. 2018

linked to NHDPlus stream reaches. Reaches with summer 

flows less than 0.2 cubic feet per second, approximating a 

wetted width of 3 feet (based on an empirical relationship 

developed in Peterson et al. 2013b), or with slopes greater 

than 15 percent were trimmed from the network because 

they are rarely occupied by fish or other aquatic vertebrates 

(Isaak et al. 2017b). The steepest headwater reaches are also 

prone to frequent large disturbances (e.g., postfire debris torrents) that may cause local extirpations of fish populations 

(Bozek and Young 1994; Miller et al. 2003). To exclude dry 

channels throughout much of the Great Basin, reaches that 

were coded as intermittent in the NHDPlus network were 

also trimmed. Application of these criteria resulted in a final 

network extent of 55,700 miles (fig. 5.1), which was almost 

evenly split between USFS (48 percent) and non-USFS (52 

percent) lands.

Scenarios representing mean August stream temperature 

were downloaded from the NorWeST website (USDA FS 

https://www.fs.fed.us/rm/boise/AWAE/projects/NorWeST.

html) and linked to reaches in the analysis network. 

NorWeST scenarios have a 0.6-mile resolution and were 

developed by applying spatial-stream network models 

(Isaak et al. 2016b, 2017b; Ver Hoef et al. 2006) to temperature records for 8,726 summers of measurement at 4,277 

unique stream sites within the IAP region. The predictive 

accuracy of the NorWeST model (cross-validated r2 = 0.91; 

cross-validated root mean square prediction error = 2.0 °F), 

combined with substantial empirical support, provided a 

consistent and spatially balanced rendering of temperature 

patterns and thermal habitat for all streams. To depict 

temperatures during a baseline period, we used the S1 scenario, which represented average conditions for 1993–2011 

(hereafter 2000s). The mean August stream temperature 

during this period was 57 °F for all streams, although 

temperatures were significantly colder in streams flowing 

through national forests, where the average was 52 °F (table 

5.1, fig. 5.2).

Future stream temperature scenarios were also downloaded from the NorWeST website (USDA FS n.d.b) and 

chosen for the same climate periods (2030–2059, hereafter 

2040s; 2070–2099, hereafter 2080s) and emissions scenario 

(A1B) as those used for the streamflow analysis in the 

IAP hydrological assessment (Chapter 4). With respect to 

scenarios used in other chapters of the IAP assessment, the 

A1B scenario is similar to the RCP 6.0 scenario associated 

with CMIP5 simulations (Chapter 3). The future NorWeST 

scenarios used were S30 (2040s) and S32 (2080s), which 

accounted for differential sensitivity and slower warming 

rates of the coldest streams (Luce et al. 2014). Future stream 

temperature increases were projected to range from 1.4 to 

2.3 °F by mid-21st century and from 2.3 to 4.0 °F by late 

century, with variation occurring within and among river basins (table 5.2, fig. 5.2). Future temperature increases imply 

warming rates similar to those observed in recent decades

(Isaak et al. 2012b, 2017a) and shifts of stream temperature 

isotherms upstream at 1,000 to 1,600 feet per decade (Isaak 

and Rieman 2013; Isaak et al. 2016a).

Changes in several ecologically relevant streamflow 

characteristics were discussed in the hydrological assessment (Chapter 3), indicating that future snowmelt and 

spring runoff will occur earlier, summer flows will decrease, 

stream intermittency may increase in marginal areas, and 

more high-flow events will occur during the winter in 

transitional watersheds where air temperatures are near 

freezing (Hamlet and Lettenmaier 2007). Those projections 

concur with historical trends that show streams now run off 

1 to 3 weeks earlier in the spring (Stewart et al. 2005), and 

that summer flows have decreased 10 to 30 percent in the 

last 50 years (Leppi et al. 2012; Luce and Holden 2009). 

Hydrological changes make it likely that mountain wetlands 

Figure 5.1—Stream network showing channels with perennial flows for (a) the baseline period and (b) 2080s based 

on the A1B emissions trajectory. Increasing prevalence of red stream reaches late in the century indicates a trend 

towards lower summer flows as winter snow accumulations decrease and melt earlier in the spring.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 91

Table 5.1—Projected changes in mean August air temperatures, streamflow, and stream temperatures for major river basins 

in the Intermountain Adaptation Partnership region. Projections are based on the A1B emissions scenario represented by 

an ensemble of 10 global climate models that best predicted historical climate conditions during the 20th century in the 

northwestern United States (Hamlet et al. 2013; Mote and Salathé 2010). Additional details about scenarios are provided 

elsewhere (Hamlet et al. 2013; Wenger et al. 2010). For more information on flow, see the western United States flow metrics 

website (USDA FS n.d.c) and the Pacific Northwest Hydroclimate Scenarios Project website (University of Washington, 

Climate Impacts Group 2010). For more information on stream temperatures, see Isaak et al. (2017b), Luce et al. (2014), and 

the NorWeST website (USDA FS n.d.b).

2040s (2030–2059) 2080s (2070–2099)

NorWeST unita

Air 

temperature 

changeb

Streamflow

 change

Stream 

temperature 

changec

Air 

temperature 

change

Streamflow 

change

Stream 

temperature 

change

°F Percent °F °F Percent °F

Salmon River basin 5.9 -22.3 2.3 9.9 -31.4 3.7

Upper Snake River, Bear River 

basins 5.8 -7.6 1.5 9.5 -9.5 2.4

Middle Snake River 5.8 -19.5 2.2 9.8 -26.7 3.7

Utah basins 4.7 +2.3 2.2 10.4 12.6 4.0

Lahontan basin 4.8 +2.6 1.4 10.7 +6.5 2.4

a Boundaries of NorWeST production units as described in USDA FS (n.d.c).

b Changes in air temperature and stream flow are expressed relative to the 1980s (1970–1999) baseline climate period.

c

 Changes in stream temperatures account for differential sensitivity to climate forcing within and among river basins as described in Luce et al. 

(2014) and USDA FS (n.d.c).

Figure 5.2—NorWeST August mean stream temperature maps interpolated from 8,726 summers of monitoring data at 4,277 

unique stream sites across the 55,700 miles of streams in the analysis area. Map panels show conditions for (a) the baseline 

period (2000s) and (b) late-century scenario (2080s). Networks were trimmed to represent potential fish-bearing streams by 

excluding intermittent reaches and those with slopes greater than 15 percent and summer flows less than 0.2 cubic feet per 

second. High-resolution digital images of these maps and ArcGIS databases with reach-scale predictions are available at the 

NorWeST website (USDA FS n.d.b).

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
92 USDA Forest Service RMRS-GTR-375. 2018

and moist areas near streams will become drier during future 

summer periods (Lee et al. 2015). Increased frequency or 

severity of wildfires in portions of the IAP region could also 

cause more extensive debris flows and channel disturbances 

in headwater streams with steep channels (Luce et al. 2012) 

(Chapter 3). Those combined changes suggest that stream 

environments and habitats for aquatic species will become 

more variable, subject to more disturbances, and gradually 

warmer throughout the rest of the 21st century.

Focal Species Ecology and 

Climate Vulnerability

Rocky Mountain Tailed Frog

The Rocky Mountain tailed frog occurs throughout 

central and northern Idaho, western Montana, and northeastern Oregon, but occurs within the IAP region only in 

Boise, Payette, Salmon-Challis, and Sawtooth National 

Forests. Populations inhabit steep, cold headwater streams, 

their distributions often extending upstream past waterfalls 

and cascades that limit fish distributions (Dunham et al. 

2007; Isaak et al. 2017b). After eggs hatch in late summer, 

tadpoles grow for 1 to 4 years before metamorphosing into 

adults, which reach sexual maturity after another 4 to 5 

years; local densities may be high (Hayes and Quinn 2015; 

Pilliod et al. 2013). Larval frogs are strictly aquatic, but 

adults often exploit cool, moist riparian zones to forage. 

Adult body size is 1 to 2 inches, and dispersal is limited, so 

floods and fire-related channel disturbances may suppress 

populations for some time after an event (Hossack and 

Pilliod 2011; Hossack et al. 2006). Populations are patchily 

distributed among headwater streams and show evidence of 

genetic divergence (Metzger et al. 2015).

The Rocky Mountain tailed frog is of conservation 

concern but does not appear on the sensitive species list of 

the Intermountain Region. Land use practices that warm 

streams, increase sedimentation, and reduce interstitial 

spaces in substrates or reduce habitat moisture (through loss 

of stream and terrestrial canopy cover) are thought to reduce 

habitat quality (Hayes and Quinn 2015). Nonnative fish 

predators may increase mortality where distributions overlap, as has been documented for other amphibians (Pilliod 

and Peterson 2001; Pilliod et al. 2010). Although existing 

data for tailed frogs suggest that the species occurs in many 

streams throughout its range (Isaak et al. 2017b), monitoring data are not available to describe temporal trends in 

abundance.

Rocky Mountain tailed frogs require cold water, so 

increasing temperatures may decrease the suitability of 

warmer downstream habitats (Isaak et al. 2017b). Their 

long generation times and relatively low fecundity cause 

populations to rebound slowly from disturbances; thus, extreme floods or postfire debris flows in steep channels may 

threaten persistence of some populations as climate change 

causes these events to become more common (Hossack and 

Pilliod 2011; Hossack et al. 2006). Tailed frog populations 

may also be negatively affected by more extreme summer 

droughts or wildfires that open riparian canopies, making 

areas adjacent to streams warmer and drier (Hossack and 

Pilliod 2011; Hossack et al. 2006).

Idaho Giant Salamander

The Idaho giant salamander occurs in northern and westcentral Idaho and a small portion of west-central Montana, 

but is found within the IAP region only in Boise and Payette 

National Forests. Populations are patchily distributed and 

often co-occur with native salmonids in headwater streams, 

although salamanders also occupy reaches farther upstream 

from which fish are excluded (Sepulveda and Lowe 2009). 

Table 5.2—Lengths of streams in the Intermountain Adaptation Partnership region (slope less than 15 percent and Variable Infiltration Capacity 

model-predicted summer flows greater than 0.2 cubic feet per second) categorized by mean August stream temperatures during the baseline 

and two future climate periods and by land administrative status. Values in parentheses are percentages of the total in the last column.

<46 °F 46–52 °F 52–57 °F 57–63 °F 63–68 °F >68 °F Totala

Forest Service 

lands Miles (%) Miles (%) Miles (%) Miles (%) Miles (%) Miles (%) Miles (%)

2000s 3,872 (14.4) 11,061 (39.5) 8,799 (32.7) 3,014 (11.2) 559 (2.1) 37 (0.1) 27,305

2040s 1,644 (6.3) 8,692 (33.1) 9,994 (38.0) 4,790 (18.2) 1,016 (3.9) 141 (0.5) 26,277 

2080s 835 (3.2) 6,752 (26.2) 10,371 (40.2) 6,058 (23.5) 1,424 (5.5) 343 (1.3) 25,783 

Non-Forest Service 

lands

 

2000s 48 (0.2) 924 (3.2) 4,655 (16.2) 11,490 (39.9) 8,027 (27.9) 3,639 (12.6) 28,783 

2040s 6 (0.0) 348 (1.2) 2,896 (10.2) 9,242 (32.5) 9,767 (34.3) 6,185 (21.7) 28,444 

2080s 3 (0.0) 173 (0.6) 1,990 (7.0) 7,853 (26.8) 10,552 (37.3) 7,966 (28.2) 28,537 

a

 Reductions in network extent in future scenarios result from projected decreases in summer flows as described in Chapter 4.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 93

Giant salamander may also use lakes and ponds. Neotony 

(maturation as a strictly aquatic form with larval characteristics) is common (Blaustein et al. 1995). Uncertainty 

exists about timing of reproduction, although some literature 

suggests both spring and fall spawning (Nussbaum 1969). 

Females guard egg masses until hatching occurs and larval 

stages last several years before metamorphosing into adults. 

Adults reach body sizes of 7 to 12 inches and prey on a 

variety of aquatic and terrestrial species, including tailed 

frog tadpoles, in and near streams (Blaustein et al. 1995). 

Dispersal is limited, and population genetic structure varies 

among basins (Mullen et al. 2010).

Idaho giant salamanders are of conservation concern but 

do not appear on the Intermoutain Region sensitive species 

list. There is some indication that land use practices may affect their occurrence, but their patchy distribution and sparse 

datasets limit inferences about habitat requirements. They 

are prey for both native and nonnative fish species, but fish 

species presence is not known to affect their population status (Sepulveda and Lowe 2011). Overall, their distribution 

is poorly described, and monitoring data are not available 

to evaluate temporal trends. Idaho giant salamander sensitivities are presumed to be similar to Rocky Mountain 

tailed frogs, although the salamander may be even more 

susceptible to disturbance of headwater natal areas, given 

nest guarding behavior by females and multiyear development of larval stages before maturity (Blaustein et al. 1995; 

Nussbaum 1969).

Western Pearlshell Mussel

The western pearlshell mussel is found throughout the 

Columbia River Basin, in a portion of the Missouri River 

headwaters in Montana, and in internally draining basins 

such as the Humboldt, Truckee, and Provo Rivers. It has 

been recorded in all national forests in the IAP region except 

the three southern Utah forests. This sedentary filter-feeder 

inhabits cool streams and rivers at depths of 1.5 to 3.0 feet, 

and tends to congregate in stable substrates amid boulders, 

gravel, and some sand, silt, and clay (Roscoe and Redelings 

1964). The species has limited mobility and will not tolerate 

accumulation of fine sediment. Western pearlshell larvae are 

obligate parasites of an array of salmonid species (Chinook 

salmon [O. tshawytscha], cutthroat trout, and rainbow trout 

[O. mykiss]; utilization of bull trout is unknown) and rely 

on these hosts for recruitment and dispersal (Karna and 

Milleman 1978; Meyers and Milleman 1977; Murphy 1942). 

Female mussels generally release larvae (or glochidia) in 

spring or early summer, depending on water temperature. 

Glochidia attach to fish gills and develop for a period of 

weeks to months. Once metamorphosed, juvenile mussels 

drop from their host fishes and burrow into the substrate 

(Murphy 1942).

The western pearlshell mussel ranges from Alaska and 

British Columbia south to California and east to Nevada, 

Wyoming, Utah, and Montana. Many examples exist of 

pearlshell decline or extirpation from streams and rivers 

across its range, especially in arid areas (Hovingh 2004; 

Stone et al. 2004). Threats include impoundments, loss of 

host fishes, channel modification, dredging and mining, pollution, sedimentation, nutrient enrichment, water diversion, 

degradation of native riparian vegetation, and introduction 

of nonnative fishes that outcompete host species. Many of 

these impacts, especially reduction in streamflow and increased stream temperatures, can be exacerbated by climate 

change.

The western pearlshell mussel occupies streams with 

broad ranges of thermal regimes, but nevertheless prefers 

cold water and perennial flows. Its habitat must also be suitable for its trout and salmon hosts, and mussel sensitivity to 

climatic variability will closely parallel that of salmonids. 

Although potentially vulnerable to climate change, the 

western pearlshell mussel does not face an immediate risk 

of extinction because it occupies such a broad geographic 

range.

Springsnails

Springsnails are hydrobiid snails that occur in freshwater 

habitats throughout much of western North America. About 

100 species inhabit the IAP region (Hershler et al. 2014). 

These tiny mollusks (shell length 0.04–0.31 inches) are 

widespread and locally abundant (often greater than 100 per 

square foot) in perennial, groundwater-dependent springs 

and brooks. Spring habitats may be either ambient temperature or thermal, and springsnails are often concentrated 

near sources of groundwater discharge with stable water 

chemistry (Mladenka and Minshall 2001). They typically 

live on emergent plants and hard substrates, grazing on 

attached algae and fungi (Hershler 1998; Mladenka and 

Minshall 2001). They are gill breathers and do not tolerate 

desiccation.

Distributed from southern Canada to northern Mexico, 

the springsnail exhibits habitat specificity and low dispersal 

ability, which contribute to a high degree of endemism; 

many species occurr only within a single spring or seep 

(Hershler et al. 2014). Springsnails have life history traits 

that make them vulnerable to extinction. First, they have 

specialized habitat requirements, typically occurring in 

pristine, cold-water or thermal springs close to the spring 

source, where dissolved carbon dioxide and calcium concentrations are high (Mladenka and Minshall 2001; O’Brien 

and Blinn 1999). Slight changes in water chemistry or 

warming temperatures could negatively affect local populations (Jyväsjärvi et al. 2015). Second, springsnails are poor 

dispersers, and suitable habitats are generally isolated from 

each other by arid uplands. Once a springsnail population 

has been extirpated, it is unlikely to be naturally refounded. 

Threats to springsnails include groundwater pumping and 

aquifer drawdown, surface flow diversion for agriculture, 

impoundments, channelization of outflows, springhead 

development, physical alteration of thermal springs for bathing, overgrazing, and nonnative species (e.g., New Zealand 

mudsnail [Potamopyrgus antipodarum]).

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
94 USDA Forest Service RMRS-GTR-375. 2018

The limited ability of springsnails to disperse and their 

narrow environmental tolerances make them vulnerable to 

emerging threats associated with climate change. Because 

they require particular hydrological conditions, specific 

and stable temperature regimes, and perennial flows, some 

taxa (e.g., eight Nevada springsnail species) have been 

rated as “extremely vulnerable” using the Climate Change 

Vulnerability Index (Young et al. 2012).

Yosemite Toad

The Yosemite toad occurs in the Sierra Nevada, restricted 

primarily to publicly managed lands at high elevations 

(3,000–12,000 feet) (Brown et al. 2015). It inhabits ponds 

and wet meadows as well as drier upland sites. Adult toads 

emerge from their overwintering refuges in rodent burrows 

or underground cover from late April to late June, depending 

on elevation and year (Brown et al. 2012). Females lay approximately 1,000 eggs per clutch in shallow standing water 

amid emergent vegetation. After hatching, tadpoles require 

4 to 6 weeks to reach metamorphosis and are not known to 

overwinter (Jennings and Hayes 1994; Kagarise Sherman 

1980; Karlstrom 1962). Adults spend most of their lives in 

upland habitats adjacent to breeding sites, and are capable 

of moving and dispersing several hundred feet through dry 

forests.

Yosemite toad populations are in decline. The Yosemite 

toad, once common in high-elevation aquatic ecosystems of 

the Sierra Nevada, had disappeared from half its historical 

range by the 1990s (Jennings 1996). More recent surveys 

indicate an 87-percent decline from watersheds occupied before 1990, with scattered remaining populations and fewer 

individuals per site (Brown et al. 2015). Toads were most 

recently recorded at 470 sites in 5 national forests (17 sites 

in Humboldt-Toiyabe National Forest) and about 100 more 

sites in national parks (Brown et al. 2015). Several factors, 

such as disease, drought, airborne contaminants, habitat 

alteration, water diversions, nonnative fishes, and wildfire, 

may have contributed to the declines, but there is no clear 

evidence targeting any particular threat (Brown et al. 2015).

The dependence of Yosemite toad on shallow, ephemeral 

breeding ponds filled by melting snow makes the species 

susceptible to risks of climate change (Kagarise Sherman 

and Morton 1993). Models project that climate change will 

lead to higher average temperatures in all seasons, higher 

precipitation, and decreased spring and summer runoff due 

to decreased snowpack (Smith and Tirpak 1989) (Chapter 

4). Less runoff could affect egg and tadpole survival by 

premature drying of breeding sites. Earlier snowmelt could 

lead to earlier breeding with possible positive effects on 

developmental time, but negative effects and mortality from 

uncertain weather patterns. For example, toads that emerge 

early risk starvation or death in late-spring snowstorms 

(Kagarise Sherman and Morton 1993).

Sierra Nevada Yellow-Legged Frog

The Sierra Nevada yellow-legged frog currently inhabits the Sierra Nevada, restricted primarily to publicly 

managed lands at high elevations (4,500–12,000 feet), 

including streams, lakes, ponds, and meadow wetlands in 

Humboldt-Toiyabe National Forest (CDFG 2011). The species is highly aquatic during all times of the year (Mullally 

and Cunningham 1956). At high elevation, both frogs and 

tadpoles overwinter under ice in lakes and streams, and 

because tadpoles require 1 to 4 years to metamorphose, 

successful breeding sites cannot dry out in summer and need 

to be deep enough to preclude complete freezing or deoxygenation (Bradford 1983). Although almost always found in 

or near water, the frog moves seasonally between breeding 

ponds, foraging, and overwintering habitats, usually along 

watercourses. However, individuals are capable of moving several hundred feet over dry land, which facilitates 

recolonization of sites that have lost populations (Pope and 

Matthews 2001).

The Sierra Nevada yellow-legged frog was listed as endangered under the ESA after populations declined severely 

during the 20th century due to chytridiomycosis disease 

(caused by the chytrid fungus [Batrachochytrium dendrobatidis]), predation from nonnative fishes, livestock grazing, 

habitat loss and fragmentation, and perhaps airborne 

contaminants from the Central Valley (CDFG 2011). The 

species was estimated to be extirpated from 220 of 318 historical occurrence localities and most remaining populations 

were thought to have fewer than 100 post-metamorphic individuals (CDFG 2011). During the last 20 years, however, 

yellow-legged frog populations have increased significantly 

in Yosemite (Knapp et al. 2016). The disappearance of 

nonnative fish from numerous water bodies after cessation 

of stocking, combined with reduced susceptibility to chytridiomycosis, are thought to have stimulated the recovery 

(Knapp et al. 2016).

Sierra Nevada yellow-legged frogs may be vulnerable 

to climate change because the species relies on perennial 

waterbodies and needs several years to metamorphose and 

mature (Mullally and Cunningham 1956). Climate change 

could result in greater interannual climatic variability or 

drier summers and cause lakes, ponds, and other standing 

waters fed by snowmelt or streams to dry more frequently, 

which would reduce available breeding habitat and lead to 

more frequent stranding and death of tadpoles (Lacan et 

al. 2008). On the other hand, projected earlier snowmelt is 

expected to cue breeding earlier in the year, which could 

allow additional time for tadpole growth and development. 

However, earlier breeding may also expose young tadpoles 

and eggs to mortality from early spring frosts (Corn 2005).

Bull Trout

Bull trout are broadly distributed across the northwestern 

United States but are restricted to the northwestern portion 

of the IAP region in Boise, Humboldt-Toiyabe, Payette, 

Salmon-Challis, and Sawtooth National Forests (Rieman et 

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 95

al. 1997) (fig. 5.3). Populations may exhibit migratory or 

resident life histories. Migratory fish travel long distances 

as subadults to more productive habitats and achieve larger 

sizes and greater fecundity as adults before returning to 

cold natal headwater habitats to spawn (Howell et al. 2010; 

Rieman and McIntyre 1993). Fish exhibiting resident life 

histories remain in natal habitats and mature at smaller sizes, 

though often at the same age as migratory adults. Adults 

spawn primarily in September, and eggs incubate throughout the winter before juveniles hatch and emerge from 

stream substrates in late winter or early spring (Dunham 

et al. 2008). Reproduction and juvenile growth for the first 

2 to 3 years is almost exclusively in streams with average 

August water temperatures less than 54 °F and flows greater 

than 1.2 cubic feet per second (Isaak et al. 2015). Bull trout 

populations are typically low density, even among strong 

populations in the best habitats (Isaak et al. 2017b; Rieman 

et al. 2006).

The bull trout is a sensitive species in the Intermountain 

Region and is ESA-listed as threatened (USFWS 2014). 

Their historical distribution has declined because of water 

development and habitat degradation (e.g., simplification of in-channel habitat complexity and fragmentation 

of some habitats), temperature increases, elimination of 

migratory life histories by anthropogenic barriers, harvest 

by anglers, and interactions with introduced nonnative fishes 

(Al-Chokhachy et al. 2010; Rieman et al. 1997, 2007). 

Encounters with nonnative fishes may involve wasted reproductive opportunities (e.g., interbreeding with brook trout 

[Salvelinus fontinalis]) (Kanda et al. 2002), competition, 

and predation (in streams, perhaps with brown trout [Salmo 

trutta]; in lakes, with lake trout [Salvelinus namaycush]) 

(Al-Chokhachy et al. 2016b; Martinez et al. 2009).

Bull trout evolved in western North America in interior 

and coastal streams that exhibit a wide array of flow characteristics and natural disturbance at scales from reaches to 

riverscapes (Dunham et al. 2003, 2008). Nevertheless, large 

habitats satisfying their restrictively cold thermal requirements for spawning and early juvenile rearing are relatively 

rare, and little evidence exists for flexibility in habitat use 

(Rieman et al. 2007). The length of connected cold-water 

habitats needed to support a bull trout population varies 

with local conditions, but current estimates suggest 10 to 

30 miles are needed to ensure a high probability (>0.9) of 

habitat occupancy, with specifics contingent on water temperature, prevalence of brook trout, and stream slope (Isaak 

et al. 2015). Migratory life histories probably conferred 

greater resistance to extirpation under historical conditions 

Figure 5.3—Native range distributions of (a) cutthroat trout and (b) bull trout in the Intermountain Adaptation 

Partnership region. The ranges of six cutthroat trout subspecies occur partly or wholly in this area.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
96 USDA Forest Service RMRS-GTR-375. 2018

(Dunham et al. 2008; Rieman and Dunham 2000), but may 

no longer do so in some areas. Bull trout may also be sensitive to larger or more frequent winter high flows because 

eggs incubate in stream substrates throughout the winter 

where they are susceptible to bed-scour (Goode et al. 2013; 

Wenger et al. 2011a).

Cutthroat Trout

Cutthroat trout are represented by six subspecies in the 

IAP region: westslope cutthroat trout (O. clarkii lewisi), 

Yellowstone cutthroat trout (O. c. bouvieri), Lahontan 

cutthroat trout (O. c. henshawi), Paiute cutthroat trout (O. 

c. seleniris), Bonneville cutthroat trout (O. c. utah), and 

Colorado River cutthroat trout (O. c. pleuriticus) (Behnke 

2002) (fig. 5.3). Although there was no historical overlap 

in the distribution of these subspecies, one or more were 

distributed throughout all national forests in the IAP region 

except where perennial streams are lacking (e.g., southern 

Nevada). These subspecies have a complex evolutionary 

history with two major clades (Crête-Lafrenière et al. 2012; 

Loxterman and Keeley 2012). One consists of westslope, 

Lahontan (including Paiute), and coastal cutthroat trout, 

and the other includes the rest of the interior subspecies. 

Phylogeographic structure in the latter group suggests that 

another one to four taxa may be present (Loxterman and 

Keeley 2012; Metcalf et al. 2012), but we confine our discussion to the prevailing taxonomy (Behnke 2002).

Cutthroat trout exhibit resident and migratory life history 

strategies similar to bull trout, but are spring spawners that 

reproduce in stream reaches where August temperatures 

are slightly warmer (up to 57 °F) (Isaak et al. 2015). Cold 

stream reaches where average August temperatures are less 

than 48 °F are suboptimal for cutthroat trout because of frequent recruitment failures associated with small numbers of 

growing degree days (Coleman and Fausch 2007). Cutthroat 

trout populations are generally found at higher densities 

than are bull trout (Isaak et al. 2017b).

Among cutthroat trout, all subspecies are either ESAlisted as threatened (Lahontan cutthroat trout [USFWS 

1995] and Paiute cutthroat trout [USFWS 1985]) or have 

been petitioned for listing and found not warranted. Those 

not listed are on the Intermountain Region sensitive species list (Bonneville, Colorado River, westslope, and 

Yellowstone cutthroat trout). Distributions of these subspecies have declined more than 50 percent in response to the 

same stressors affecting bull trout (Behnke 2002; Shepard et 

al. 2005). Declines in response to nonnative species can be 

more severe than in bull trout, probably because cutthroat 

trout historically used slightly warmer habitats and overlap 

with more nonnative species. Brook trout have replaced 

cutthroat trout in many waters in the IAP region (Benjamin 

and Baxter 2012; Dunham et al. 2002a). These invasions 

seem to be influenced by the distribution of low-gradient 

alluvial valleys that may serve as nurseries for brook trout 

(Benjamin et al. 2007; Wenger et al. 2011a). Introduced 

rainbow trout have introgressively hybridized with cutthroat 

trout at lower elevations and in warmer streams (>50 °F) 

across their historical ranges (McKelvey et al. 2016), 

although genetically pure populations often persist in cold 

headwaters where climatic conditions limit the expansion 

of hybrid zones from downstream areas (Young et al. 2016, 

2017).

Cutthroat trout occupy a broader thermal and stream 

size niche than do bull trout and can persist in small habitat 

patches for extended periods (Peterson et al. 2013a; Whitely 

et al. 2010). However, they still require cold-water natal 

habitat patches exceeding 2 to 6 miles to have a high probability of persistence (Isaak et al. 2015), with the habitat size 

depending on the prevalence of brook trout, water temperatures, and stream slope. Temperatures at the upstream extent 

of cutthroat trout populations in extremely cold streams will 

become more suitable from climate warming, but that trend 

may be countered by decreasing flows as snowmelt and 

runoff occur earlier (Chapter 3).

Climate Vulnerability and Adaptive 

Capacity of Focal Species

Warmer temperatures and declining summer streamflows 

will have broadly similar effects on aquatic species in 

the IAP region by reducing habitat volumes in perennial 

streams, fragmenting large habitat patches into smaller 

areas of suitable habitats (Isaak et al. 2012a; Rieman and 

Isaak 2010; Rieman et al. 2007), and shifting thermally 

suitable habitats upstream (Isaak et al. 2016a). Nonnative 

trout species more tolerant of warmer temperatures—brook 

trout, rainbow trout, and brown trout—will expand their 

distributions upstream and further constrain, replace, or prey 

on native trout and amphibians in some stream reaches. The 

relatively warm thermal niches of most nonnative species 

other than brook trout will restrict them from colonizing the 

coldest headwater streams, so refugial habitats, mostly at 

higher elevations, will continue to persist in some mountainous areas for the foreseeable future.

Wildfires may cause more extensive geomorphic disturbances and debris flows into streams, especially the smallest 

and steepest channels at the upstream extent of the drainage network (Miller et al. 2003; Sedell et al. 2015). Less 

water, more variable environments, and declining fluvial 

connectivity (e.g., from water development or interactions with road culverts) may favor resident life histories, 

as would greater separation between spawning and adult 

growth habitats. Smaller, more isolated populations will be 

more susceptible to extirpation from local environmental 

disturbances and during years of extreme drought and high 

summer water temperatures.

Species-specific vulnerabilities to these changes depend 

on the nexus among species ecological attributes, rates 

at which habitats are changing, and extent of current distributions (table 5.3). Bull trout and some cutthroat trout 

subspecies (e.g., westslope cutthroat trout, Yellowstone 

cutthroat trout) are moderately vulnerable because they 

are widely distributed, have good dispersal abilities, and 

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 97

occupy headwater habitats that are relatively resistant to 

thermal changes. Other subspecies of cutthroat (Bonneville, 

Lahontan, and Paiute cutthroat trout) are more vulnerable 

because distributions are limited to small numbers of isolated stream habitats.

Vulnerability of western pearlshell mussel will track that 

of their native trout hosts, but summer flow declines may be 

especially problematic because adult mollusks are immobile. Debris flows triggered by increased wildfire frequency 

could extirpate local mussel populations, although the 

species usually inhabits low-gradient stream reaches, where 

those events are rare (Stagliano 2005). However, fine sediments from debris flows could propagate downstream and 

smother mussel beds. Rocky Mountain tailed frog and Idaho 

giant salamanders are poor dispersers occupying headwater 

habitats and could be vulnerable to debris flows and more 

frequent disturbances.

Reduced aquifer recharge caused by altered seasonal 

precipitation and runoff could adversely affect groundwaterdependent and lake ecosystems that support endemic taxa 

such as springsnails, Yosemite toad, and Sierra Nevada 

yellow-legged frog (Burns et al. 2017; Hershler et al. 2014; 

Jyväsjärvi et al. 2015). The extreme endemism of springsnails means that the drying of individual springs could 

result in extirpation or extinction of a species. Arid land 

springs, which provide habitat for most springsnail species, 

are usually isolated, and dispersal of snails may be impossible without assistance by humans or other animal vectors. 

Recent and abrupt declines in the number and extent of 

Yosemite toad puts this species at high risk regardless of 

climate-induced environmental change. Altered aquatic 

habitat conditions, especially the greater environmental 

stochasticity that is expected, are predicted to exacerbate 

existing stressors and further degrade the resilience of remaining populations.

Niche conservatism suggests there is little capacity for 

rapid evolutionary or physiological adaptations to warmer 

water temperatures or desiccation within the aquatic species considered here (McCullough et al. 2009; Narum et 

al. 2013; Wiens et al. 2010). However, species with good 

dispersal abilities may track shifting habitats or recolonize 

previously disturbed habitats or those that have been 

Table 5.3—Summary of anticipated vulnerability of selected aquatic species to climate change in the Intermountain Adaptation 

Partnership (IAP) region.

Species or subspecies

Taxonomy and 

phylogeography Range extenta

Population 

trend

Climate 

vulnerability Comment

Bull trout Resolved

Locally common in north and 

elsewhere Stable Moderate ESA listedb

Cutthroat trout 

subspecies

 Paiute Resolved Narrow endemic in west Stable High ESA listed

 Yellowstone Resolved

Widespread in northeast and 

elsewhere Stable Moderate

 Westslope Resolved

Widespread in north and 

elsewhere Stable Moderate

 Colorado River Pending Widespread in east and elsewhere Stable Moderate

 Bonneville Pending Restricted distribution in east Stable Moderate

 Lahontan Resolved Restricted distribution in west Stable High ESA listed

Western pearlshell 

mussel Resolved

Widespread in north and 

elsewhere Unknown Moderate

Springsnails Partially resolved Widespread Unknown High

Idaho giant salamander Resolved

Restricted distribution in north and 

northern Idaho Unknown Moderate

Rocky Mountain tailed 

frog Resolved

Restricted distribution in north but 

more common elsewhere Unknown Moderate

Yosemite toad Resolved Restricted distribution in west Declining High

Warranted 

but 

precluded

Sierra Nevada yellowlegged frog Resolved Restricted distribution in west Increasing High ESA listed

a Geographic location (north, west, etc.) refers to IAP region only.

b ESA refers to U.S. Endangered Species Act.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
98 USDA Forest Service RMRS-GTR-375. 2018

recently restored as long as artificial barriers do not impede 

their movement (Fausch et al. 2009). Some species exhibit 

both migratory and resident life history strategies, and the 

relative frequencies of these strategies may evolve based on 

how climate change affects metabolic rates, water temperature, stream productivity, and connectivity. Development 

of disease resistance or other adaptive responses associated 

with phenology may also bolster population resilience in 

ways that allow species to persist in dynamic environments 

(Knapp et al. 2016; Kovach et al. 2012).

Climate Refugia for Native Trout

Trout Distribution Model and Scenarios

Species distribution models for bull trout and cutthroat 

trout were developed previously in the Coldwater Climate 

Shield (CS) project by compiling large species occurrence datasets (more than 4,000 sites in over 500 streams) 

from field biologists, peer-reviewed literature, and State 

and Federal agency reports (Isaak et al. 2015). The CS 

models use the high-resolution stream temperature and 

flow scenarios described earlier with stream slope and the 

prevalence of brook trout as predictor variables in logistic 

regression models that predict occurrence probabilities of 

juvenile bull trout and cutthroat trout in cold-water habitat 

(CWH) patches (fig. 5.4). Juvenile occurrence is used as an 

indicator of important natal habitat locations and serves as 

evidence of locally reproducing populations for salmonid 

fishes (Dunham et al. 2002b; Rieman and McIntyre 1995). 

The CS models are also designed to identify CWHs that are 

too cold (<52 °F mean August temperature) for invasions 

by most nonnative species other than brook trout and thus 

should require limited management interventions to support 

native trout populations.

Previously, Young et al. (2018) applied the CS models 

to describe bull trout and cutthroat trout distributions and 

refugia in the Northern Rockies Adaptation Partnership 

region (Halofsky et al. 2018). Here, we repeat that exercise and summarize CS model predictions for native 

trout populations across the IAP region. Information for 

these summaries was downloaded from the CS website 

(USDA FS https://www.fs.fed.us/rm/boise/AWAE/projects/

Figure 5.4—Relationships between predictor variables in the Climate Shield models and the probability 

of occupancy by juvenile native trout for (a–c) 512 bull trout and (d–f) 566 cutthroat trout streams 

characterized by cold-water habitats less than 52 °F (from Isaak et al. 2015). Relationships shown 

are conditioned on mean values of the two predictors not shown in a panel. An exception occurs for 

cutthroat trout with regard to stream slope (panel f), where brook trout values of 0 and 100 percent 

were used to highlight the interaction between these covariates. 

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 99

ClimateShield.html), which also provides extensive metadata descriptions, a user-friendly digital map archive (fig. 5.5), 

and geospatial databases showing stream-specific model 

predictions for all streams in the USFS Northern, Rocky 

Mountain, Intermountain, and Pacific Northwest Regions in 

the western United States.

Scenarios used to assess native trout distributions were 

based on the same climate periods (2040s and 2080s) and 

A1B trajectory already described earlier for the NorWeST 

stream temperature and VIC scenarios. To account for uncertainties in brook trout distributions across the IAP region, 

native trout occupancy probabilities were also summarized 

for a pristine scenario (no brook trout) and a broad invasion 

scenario that assumed brook trout would be present at half 

the sites within each CWH (50-percent brook trout). For the 

IAP region, we did not summarize a scenario in which brook 

trout were present at all sites because their prevalence rarely 

exceeded 50 percent in the largest cold-water habitats (>25 

miles), which are most likely to serve as strongholds for 

native trout (see Appendices S2 and S3 in Isaak et al. 2015), 

and because not all stream locations are suitable for brook 

trout (Isaak et al. 2017b; Wenger et al. 2011a). Brook trout 

prevalence may reach 100 percent in small, low-gradient 

streams, so native trout probabilities for a full range of invasion scenarios (0-, 25-, 50-, 75-, and 100-percent brook trout 

prevalence) have been calculated and integrated into the CS 

geospatial databases to facilitate stream-specific assessments 

(if local information is available on brook trout prevalence).

Cutthroat Trout Status and Projected 

Trends

Invasion-resistant streams with mean August temperatures less than 52 °F encompassed 15,000 miles of the 

56,000-mile network draining the IAP region during the 

baseline period; 94 percent of those cold streams are on 

national forests (table 5.2). The number of discrete CWHs 

that were potentially occupied by juvenile cutthroat trout 

during the baseline period was estimated to be 2,600 and encompassed nearly 13,000 stream miles across all subspecies 

(table 5.4, fig. 5.6). Three subspecies—Lahontan cutthroat 

trout, Bonneville cutthroat trout, and Paiute cutthroat 

trout—had restricted ranges and are summarized separately 

(table 5.5). Bonneville and Lahontan cutthroat had about 

620 miles of CWHs during the baseline period, whereas 

habitat for the Paiute cutthroat trout was less than 12 miles 

because it occurred in only a few streams.

Across all cutthroat trout subspecies, 89 percent of 

CWHs were predicted to have probabilities of occupancy 

exceeding 50 percent in the current period if brook trout 

Figure 5.5—Example of a detailed Climate Shield map that shows probabilities of juvenile cutthroat trout 

occupancy in cold-water stream habitats. Information is available for three climate periods and five 

brook trout invasion scenarios for bull trout and cutthroat trout streams in the Intermountain Adaptation 

Partnership region at the Climate Shield website (USDA FS n.d.a).

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
100 USDA Forest Service RMRS-GTR-375. 2018

were absent (table 5.4), largely because of the relatively 

small stream networks that a cutthroat trout population 

requires for persistence (e.g., 6 miles is associated with a 

90-percent probability of occupancy) (fig. 5.4). Nonetheless, 

the largest CWHs accounted for a disproportionate amount 

of the habitat most likely to be occupied; 35 percent of 

CWHs had probabilities greater than 90 percent, but these 

accounted for 68 percent of the length of CWHs. As expected, the number and extent of CWHs were predicted to 

decrease substantially (14–50 percent) in future periods, but 

1,845 potential habitats encompassing almost 6,500 miles 

were projected to remain in the extreme 2080 scenario.

Where headwater stream reaches are currently too cold 

for cutthroat trout, future warming may increase habitat suitability and the probability of occupancy in portions of the 

Uinta Mountains and other cold streams draining the upper 

Green, Salmon, and Snake Rivers. As expected, the brook 

trout invasion scenario did not affect the number or amount 

of CWHs because the habitats remained potentially suitable 

for cutthroat trout, but occupancy probabilities declined 

(table 5.4). The sensitivity of streams to brook trout invasions varies with local conditions, but impacts were most 

pronounced in small CWHs with low slopes (fig. 5.4).

Bull Trout Status and Projected Trends

The historical range of bull trout occupies a smaller portion of the IAP region than cutthroat trout, so the number 

of discrete CWHs for bull trout during the baseline climate 

period was estimated to be 984, encompassing 7,700 

miles (table 5.6, fig. 5.7). In contrast to cutthroat trout, 

most CWHs for bull trout had probabilities of occupancy 

less than 50 percent because of the relatively large stream 

networks that bull trout require (30 miles is associated with 

a 90-percent probability of occupancy) (fig. 5.4). Although 

only 8 percent of CWHs had probabilities greater than 90 

percent, they provided 36 percent of the total length of 

CWH, emphasizing the contribution of large CWHs to the 

amount of habitat predicted to be occupied. The requirement for larger CWHs caused projected decreases in the 

number (9–28 percent) and network extent (35–57 percent) 

of bull trout CWHs to be more substantial than those for 

cutthroat trout, particularly for the CWHs with the highest 

probabilities of occupancy. However, more than 700 CWHs 

representing 3,330 miles were projected to remain even in 

the extreme 2080 scenario.

Similar to the effect on cutthroat trout, the brook trout 

invasion scenario showed reduced bull trout occupancy 

rates (especially in CWHs with greater than 50-probability 

of occupancy), and as few as three to four CWHs with 

probabilities greater than 90 percent remained under the 

extreme warming scenario with a ubiquitous brook trout 

presence. However, many of the large bull trout habitats are 

less susceptible to broad-scale brook trout invasions given 

the preference by the latter species for small low-gradient 

streams (Dunham et al. 2002a; Isaak et al. 2015). Not 

surprisingly, CWHs with the highest bull trout occupancy 

probabilities in all scenarios coincided with river networks 

containing the largest number of cold streams (headwater 

portions of the Boise, Middle Fork Salmon, and Upper 

Salmon Rivers) (fig. 5.7).

Table 5.4—Number and length of cold-water habitats for all subspecies of juvenile cutthroat trout by probability of occurrence 

for three climate periods and two brook trout invasion scenarios in the Intermountain Adaptation Partnership region.

Probability of occurrence (percent) Total coldPeriod <25 25–50 50–75 75–90 >90 water habitats

Cold-water habitat number -------------------------------------Number-------------------------------------

 0% brook trout prevalence 2000s 73 206 540 872 909 2,600

2040s 49 170 544 791 680 2,234

2080s 66 252 479 572 476 1,845

 50% brook trout prevalence 2000s 80 261 1,296 736 227 2,600

2040s 50 193 1,152 606 233 2,234

2080s 66 260 975 440 104 1,845

Cold-water habitat length ---------------------------------------Miles----------------------------------------

 0% brook trout prevalence 2000s 215 388 1,272 2,322 8,794 12,776

2040s 68 288 951 1,858 5,871 9,036

2080s 93 398 931 1,402 3,665 6,489

 50% brook trout prevalence 2000s 578 864 2,894 4,447 4,208 12,991

2040s 140 386 2,202 3,047 3,260 9,035

2080s 93 454 2,008 2,290 1,643 6,488

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 101

Conclusions and Implications

A changing climate has significant implications for 

distributions of aquatic habitats and species dependent on 

them in the IAP region. Vulnerability to habitat shifts or 

losses this century may be high, especially for taxa that have 

either restricted habitats or limited dispersal abilities. Yet 

the symptoms of rapid climate change have been manifest 

throughout the western United States for several decades 

(Barnett et al. 2008; Hamlet and Lettenmaier 2007; Luce 

and Holden 2009; Mote et al. 2005) without widespread 

losses of aquatic populations or species. Three factors help 

explain this apparent paradox. First, the steep topography 

in parts of the IAP region translates to slow climate velocities, which may enable species to track gradual shifts in 

their habitats (Isaak et al. 2016a). Second, the thermal and 

hydrological changes that have accumulated to date are 

relatively small compared to changes expected throughout 

the remainder of the 21st century (Chapter 3). Third, existing 

monitoring programs and analyses of available datasets may 

be inadequate for detecting the subtle distribution shifts 

or extirpation of small populations that are expected with 

climate change (Isaak and Rieman 2013).

In one of the few attempts to rigorously measure how 

distributions of stream organisms are responding to climate 

change, site revisits over a 20-year period revealed that 

juvenile bull trout distributions were contracting upstream 

within the Bitterroot River basin of Montana (Eby et al. 

2014). In a larger study across western Montana, long-term 

monitoring indicated that brown trout populations were increasing in abundance and gradually expanding into streams 

Figure 5.6—Distribution of cold-water habitats with probabilities of occupancy greater than 0.1 for juvenile 

cutthroat trout for (a–b) the baseline period (2000s) and (c–d) late-century scenario (2080s). Panels a and 

c illustrate occupancy when brook trout are absent; panels b and d illustrate occupancy when brook trout 

prevalence is 50 percent.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
102 USDA Forest Service RMRS-GTR-375. 2018

Table 5.5—Number and length of cold-water habitats for three cutthroat trout subspecies by probability of occurrence for three 

climate periods, assuming the absence of brook trout. Reduced occurrence probabilities associated with brook trout invasions 

would be similar to declines described in table 5.4.

Cutthroat trout subspecies

Probability of occurrence (percent) Total 

cold-water 

Period <25 25–50 50–75 75–90 >90 habitats

Bonneville ----------------------------------------Number----------------------------------------------

 Cold-water habitat number 2000s 1 24 70 90 96 281

2040s 0 12 34 62 54 162

2080s 0 8 23 22 44 97

----------------------------------------Miles----------------------------------------------

 Cold-water habitat length 2000s 0 33 100 176 530 839

2040s 0 12 39 124 310 485

2080s 0 9 26 48 228 311

Lahontan ----------------------------------------Number----------------------------------------------

 Cold-water habitat number 2000s 3 25 39 63 29 159

2040s 2 16 40 50 25 133

2080s 1 10 40 31 11 93

----------------------------------------Miles----------------------------------------------

 Cold-water habitat length 2000s 5 48 86 175 227 541

2040s 3 31 78 137 150 399

2080s 2 17 85 93 58 255

Paiute ----------------------------------------Number----------------------------------------------

 Cold-water habitat number 2000s 0 0 0 1 2 3

2040s 1 0 1 3 0 5

2080s 1 0 0 2 0 3

----------------------------------------Miles----------------------------------------------

 Cold-water habitat length 2000s 0 0 0 4 8 12

2040s 1 0 1 6 0 7

2080s 1 0 0 5 0 6

that were previously too cold (Al-Chokhachy et al. 2016b). 

Similar monitoring efforts and site resurveys are needed 

at broad scales for many species to document the effects 

of climate change on aquatic life and to provide the basis 

for strategic planning and proactive conservation actions 

(Comte and Grenouillet 2013; Craine et al. 2007).

The first step in promulgating an informative aquatic 

biodiversity census is the aggregation and organization 

of historical datasets into functional databases, allowing species occurrence information to be linked with 

environmental covariates, then modeled and analyzed for 

trends. Development of the CS models involved organizing a small fraction of existing datasets for trout species 

(Isaak et al. 2015), but even this initial effort yielded 

significant improvements in the ability to predict where 

trout populations are most likely to persist, has assisted 

monitoring efforts, and is setting the stage for developing 

more precise models in the near future. For example, the 

spatially explicit CS model predictions are being used to 

guide an interagency crowd-sourcing campaign to collect environmental DNA (eDNA) samples from 7,000 

locations throughout the native range of bull trout, which 

includes the northern portion of the IAP region (Young et 

al. 2017). Those samples will be paired with new spatial 

stream-network models (Isaak et al. 2014; Ver Hoef et al. 

2006) to model bull trout occurrence at high resolution (<1 

mile) across broad areas to provide accurate predictions of 

distribution and abundance and a better understanding of 

environmental constraints. This new generation of eDNA 

samples could be compared to historical occurrence datasets to provide broad-scale climate trend assessments. The 

bull trout eDNA samples also contain the DNA of many 

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 103

Figure 5.7—Distribution of cold-water habitats with probabilities of occupancy greater than 0.1 for juvenile bull trout for (a–b) 

the baseline period (2000s) and (c–d) late-century scenario (2080s). Panels a and c illustrate occupancy when brook trout are 

absent; panels b and d illustrate occupancy when brook trout prevalence is 50 percent.

Table 5.6—Number and length of cold-water habitats for juvenile bull trout by probability of occurrence for three climate 

periods and two brook trout invasion scenarios in the Intermountain Adaptation Partnership region.

Probability of occurrence (percent)

Period <25 25–50 50–75 75–90 >90 Total

Cold-water habitat number ------------------------------------------Number---------------------------------------------

 0% brook trout prevalence 2000s 406 289 141 70 78 984

2040s 538 216 90 31 23 898

2080s 387 215 76 22 12 712

 50% brook trout prevalence 2000s 474 301 132 52 25 984

2040s 608 211 56 19 4 898

2080s 456 197 43 13 3 712

Cold-water habitat length -------------------------------------------Miles----------------------------------------------

 0% brook trout prevalence 2000s 1,158 1,480 1,245 1,003 2,806 7,692 

2040s 1,630 1,232 874 464 766 4,967

2080s 1,059 999 645 289 344 3,336

 50% brook trout prevalence 2000s 1,452 1,950 1,651 1,097 1,542 7,692

2040s 1,994 1,531 723 529 190 4,967

2080s 1,337 1,180 463 216 140 3,336

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
104 USDA Forest Service RMRS-GTR-375. 2018

other aquatic taxa, so will help establish baseline conditions for many species that lack data. Moreover, thousands 

of additional eDNA samples are now being collected annually across the western United States through partnerships 

with the National Genomics Center for Wildlife and Fish 

Conservation (http://www.fs.fed.us/research/genomicscenter), so a taxonomically diverse and geographically 

comprehensive monitoring system for aquatic species is 

emerging.

For native bull trout and cutthroat trout, the CS models 

provided accurate, spatially explicit predictions of habitat 

occupancy throughout the IAP region with respect to 

current conditions. Assuming that species responses are related to the effects of climate on stream ecosystems—and 

the accuracy of the models supports this contention—the 

models also provide reasonably robust projections of 

habitat occupancy in light of anticipated climate change. 

Although both native trout species are regarded as coldwater taxa, their exact responses to a changing climate 

are expected to differ. Bull trout, and most members of 

the genus Salvelinus, are adapted to some of the coldest 

freshwater environments in the Northern Hemisphere 

(Klemetsen et al. 2003). These species also tend to inhabit 

highly variable environments, often with strong gradients 

in productivity that appear to favor migration as a life history tactic (Klemetsen 2010). It is unsurprising, therefore, 

that a species with those attributes near the southern end of 

its distribution would be susceptible to range contractions 

as temperatures warm. In the IAP region, we anticipate declines in bull trout distributions, but the species is unlikely 

to be extirpated from the region because many climate refuge habitats will persist. As climate change proceeds this 

century, it is possible that conditions favoring migratory 

or resident life histories will change, although it is unclear 

how these conditions would be accommodated or exploited 

by bull trout. As we learn more about the extent and 

prevalence of populations occupying CWHs with varying 

probabilities of occupancy, an understanding of the environmental drivers of bull trout life history may emerge.

Cutthroat trout, in contrast, can accommodate a wider 

range of thermal environments, consistent with their 

broad latitudinal distribution and an evolutionary history. 

Since the late Miocene or early Pliocene, this species was 

exposed to intervals cycling between warm/dry and cool/

moist periods in western North America (McPhail and 

Lindsey 1986; Minckley et al. 1986). Cutthroat trout are 

relatively plastic with respect to life history strategies, 

ranging from highly migratory populations dependent on 

large rivers or lakes to promote growth and fecundity, to 

resident populations that move little and have been isolated 

for decades to centuries (Northcote 1992; Peterson et al. 

2013b). Although we anticipate net losses in cutthroat 

distribution in the IAP region, they are not expected to 

be as severe as for bull trout, and some basins that are 

currently too cold to support cutthroat trout may become 

high-quality climate refugia in the future (Al-Chokhachy et 

al. 2013; Coleman and Fausch 2007; Cooney et al. 2005). 

Of greater importance may be how nonnative salmonids, 

which often displace or replace cutthroat trout, respond to 

warming conditions (Wenger et al. 2011a). These factors 

do not represent similar risks to the six cutthroat trout 

subspecies, primarily because of the large differences 

in quality and quantity of habitats currently occupied. 

For example, Yellowstone and westslope cutthroat trout 

are widely distributed, occupy many streams throughout 

their ranges, and exhibit a broad array of life histories. 

However, remaining subspecies often persist in small, 

isolated headwater habitats that may be especially vulnerable to brook trout invasions (Benjamin and Baxter 2012; 

Dunham et al. 2002a).

The presence of brook trout is problematic for both bull 

trout and cutthroat trout. The tolerance of brook trout to 

cold temperature is nearly equivalent to that of cutthroat 

trout, and brook trout favor the low-gradient environments 

preferred by cutthroat trout and bull trout (Wenger et al. 

2011a). However, very large habitats appear less likely to 

be invaded by brook trout, possibly because this species 

prefers small streams but also because large systems usually contain other salmonid species, such as rainbow trout 

or brown trout, that compete with brook trout (Fausch et 

al. 2009). Rainbow trout and brown trout are expected to 

shift their distribution upstream as temperature isotherms 

optimal for these species move in that direction (Isaak 

and Rieman 2013; Wenger et al. 2011b), but may be 

constrained by unsuitable stream steepness because these 

species are rare where slopes exceed 4 percent (Isaak et 

al. 2017b). Where overlap occurs, both species appear to 

have negative effects on cutthroat trout, but cold, steep 

headwater streams that resist their invasions are expected 

to remain widespread.

Most current and future CWHs occur on public lands, 

mostly national forests, emphasizing the critical role of the 

USFS in conservation of native fish. Exploring an array 

of conservation strategies will be important because most 

of the CWHs are outside designated wilderness areas or 

national parks so are subject to various land management 

activities. Conservation options will vary by location 

because current and future CWHs are expected to be 

more abundant and persistent in some river basins than 

others across the IAP region. Where CWHs are abundant, 

maintaining those conditions and avoiding significant new 

impairments may be all that is necessary to ensure the 

persistence of native fish populations. In contrast, very 

few habitats that function as climate refugia may occur in 

other basins or where current habitats for some species or 

subspecies are very limited. Those circumstances favor 

strategic, active management to promote population persistence, whether by manipulating habitat or fish populations, 

or both. And because many CWHs are in landscapes that 

have multiple resource values, balancing among competing 

interests will remain an underlying theme of public land 

management (Rieman et al. 2010). Retaining native populations of aquatic organisms in many of these areas may 

require conservation investments that are unsustainable or 

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 105

could prove ineffective if climate warming accelerates appreciably this century. In these circumstances, reallocating 

investment resources to areas where native populations are 

more likely to persist may be preferable.

Climate Adaptation Options

Many things can be done to adapt to climate change and 

improve the resilience of aquatic species in the IAP region 

(Chapter 14). Climate change adaptation options for aquatic 

species have been the subject of a number of comprehensive 

reviews for the IAP region (Rieman and Isaak 2010) and the 

Pacific Northwest (Beechie et al. 2013; Isaak et al. 2012a; 

ISAB 2007; Luce et al. 2012; Williams et al. 2007, 2015; 

Young et al., in press b). Several key themes emerge from 

these reviews: (1) be strategic; (2) implement monitoring 

programs; (3) restore and protect natural flow, sediment, 

and temperature regimes; (4) manage fluvial connectivity; 

(5) remove or suppress nonnative species, and (6) consider 

assisted migration.

Be strategic—Prioritize watershed restoration such 

that the most important work is done in the most important 

places because the funds, labor, and time available for management of native fish populations are limited (Peterson et 

al. 2013a). Efforts are directed at only a few of the locations 

and problems that could be addressed. For example, climate 

refugia for native trout that are in wilderness areas may 

neither require nor be amenable to habitat modification to 

ensure the persistence of those populations. Similar refugia 

outside protected areas could be targeted to improve habitat 

conditions or remove or reduce nonnative species presence, 

particularly if doing so increases the probability of occupancy of such habitats by native species.

Implement monitoring programs—Being strategic 

means reducing current and future uncertainties for decisionmaking. More data are needed for streamflow (more 

sites), stream temperature (annual data from sensors maintained over many years), and species distributions. These 

data could be used for better status and trend descriptions, 

and to develop robust (or more accurate) models for species to understand their response to climate change, natural 

variation, and land management. The feasibility of monitoring at small to broad scales is increasing with the advent 

of rapid, reliable eDNA inventories of aquatic organisms 

(McKelvey et al. 2016; Thomsen et al. 2012) and the availability of inexpensive, reliable temperature and flow sensors 

(USEPA 2014).

Restore and maintain natural flow, sediment, and 

thermal regimes—Persistence of native species can be 

enhanced using a variety of habitat techniques to improve 

stream shade, narrow unnaturally widened channels, 

minimize flow diversions, and improve stream substrate 

conditions. Actions may include decommissioning or 

relocating roads away from streams (Al-Chokhachy et al. 

2016a; Zurstadt 2015), limiting seasonal grazing in some 

areas, and managing streamside riparian forest buffer 

zones to maintain effective shade and cool, moist riparian 

microclimates (Nusslé et al. 2015). Tactics may also involve 

directly managing water, such as increasing water storage 

in headwater reservoirs, restoring populations of American 

beaver (Castor canadensis) (Bouwes et al. 2016; Pollock et 

al. 2014), or acquiring water rights to maintain or enhance 

summer streamflows (Elmore et al. 2015). Such actions 

obviously have implications and consequences far beyond 

enhancing the persistence of native fish populations, but being open to opportunities is part of strategic thinking.

Manage connectivity—Obstacles to fish migration 

may be removed in hopes of enhancing the success of 

migratory life history forms, or permitting native species 

to reoccupy former habitat or supplement existing populations. This also presents a dilemma: Accessible waters can 

be invaded by nonnative species that sometimes replace 

native species (Fausch et al. 2009). The alternative is the 

installation of barriers to prevent these invasions. Native 

populations above barriers may be secure if they can adopt 

resident life histories, but could be susceptible to loss from 

catastrophic events in small habitats and will require human 

intervention for refounding or supplementation. Barriers 

are also temporary, and eventually will require reconstruction if nonnative species still remain downstream. Barriers 

may also be associated with small headwater diversion 

structures that sometimes route fish out of streams, where 

they are susceptible to stranding when water ditches are 

seasonally dewatered (Roberts and Rahel 2008; Walters et 

al. 2013). Headwater diversions are numerous and may be 

difficult to locate, so tools for locating them may be useful. 

For example, the Trout Unlimited Water Transaction Tool 

(McFall 2017) shows the locations of all diversion points in 

the Idaho Department of Water Resources database relative 

to the CS native trout refuge streams within Idaho. The tool 

enables users to identify and visit points of diversions in 

critical trout habitats to determine their potential impact to 

fish populations and design mitigation strategies.

Remove nonnative species—Removal of nonnative 

fish species will be essential to maintain or restore some 

populations. These efforts typically consist of chemical 

treatments or electrofishing, and both tend to be feasible 

only in smaller, simpler habitats (Shepard et al. 2002). 

Both are also costly, in part because they need to be conducted on multiple occasions to be effective (Peterson et 

al. 2008). Chemical treatments are controversial because 

of their perceived effects on water quality. Furthermore, 

success with either method is obtained only if the source 

of nonnative species is removed, often by the installation 

of a migration barrier. Unauthorized introductions are also 

common, and can undermine conservation efforts. Finally, 

using control measures to manage the abundance of nonnative species rather than removing them has been applied in 

some areas (e.g., the removal of lake trout to promote bull 

trout persistence or regular electrofishing to depress brook 

trout and favor cutthroat trout). Such activities are likely to 

be successful only if conducted at regular intervals for the 

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
106 USDA Forest Service RMRS-GTR-375. 2018

foreseeable future, which assumes funding and enthusiasm 

for such ventures will be available indefinitely.

Consider assisted migration—Moving native fish species from one location to another, a historically common 

activity in fish management, has typically been used to 

found populations in previously fishless waters. This tactic 

may be further pursued in the IAP region where a few basins are currently fishless (or have only limited populations 

of nonnative species) because of natural barriers such as 

waterfalls, and may create high-quality climate refugia in 

the near future. Moving native fish to such areas is feasible 

but controversial because other at-risk native taxa may be 

vulnerable to predation or competition with native fish species. Reintroductions of native species (Dunham et al. 2011, 

2016) may also be performed when natural refounding is not 

an option, such as where populations are isolated and periodically fail, or suffer population bottlenecks. Management 

intervention at this level will require an understanding of 

genetic principles and broodstock establishment.

In conclusion, responding to the environmental trends 

associated with climate change will require a diverse portfolio that includes many of the actions described earlier. We 

need to adapt our mindsets and administrative processes 

to a new paradigm of dynamic disequilibrium. Under this 

paradigm, stream habitats will become more variable, 

undergo gradual shifts through time, and sometimes decline. 

Many populations are resilient enough to persist in, or track, 

suitable habitats, but others could be overwhelmed by future 

changes. It is unlikely that we will be able to preserve all 

populations of aquatic species as they currently exist this 

century. But as better information continues to be developed 

in the future, managers will have ever more precise tools at 

their disposal to know when and where resource commitments are best made to enhance the resilience of existing 

populations or to benefit other species for which management was previously not a priority. There is much to do as 

climate change adaptation continues in future years (Chapter 

14), and USFS lands will play an increasingly important 

role in providing refuge habitats for aquatic biodiversity.

Acknowledgments

We thank the many biologists who contributed ideas, 

refinements, and data to the assessment described in this 

chapter and who participated in workshops in Boise, 

Idaho Falls, Ogden, Reno, and Salt Lake City. Comments 

provided by Caleb Zurstadt, Dan Dauwalter, and Robert AlChokhachy improved the quality of the final assessment.

References

Al-Chokhachy, R.; Alder, J.; Hostetler, S.; [et al.]. 2013. Thermal 

controls of Yellowstone cutthroat trout and invasive fishes 

under climate change. Global Change Biology. 19: 3069–3081.

Al-Chokhachy, R.; Black, T.A.; Thomas, C.; [et al.]. 2016a. 

Linkages between unpaved forest roads and streambed 

sediment: Why context matters in directing road restoration. 

Restoration Ecology. 24: 589–598.

Al-Chokhachy, R.; Roper, B.B.; Bowerman, T.; [et al.]. 2010. 

A review of bull trout habitat associations and exploratory 

analyses of patterns across the interior Columbia River 

Basin. North American Journal of Fisheries Management. 30: 

464–480.

Al-Chokhachy, R.; Schmetterling, D.; Clancy, C.; [et al.]. 2016b. 

Are brown trout replacing or displacing bull trout populations 

in a changing climate? Canadian Journal of Fisheries and 

Aquatic Sciences. 73: 1395–1404

Barnett, T.P.; Pierce, D.W.; Hidalgo, H.G.; [et al.]. 2008. Humaninduced changes in the hydrology of the western United States. 

Science. 319: 1080–1083.

Beechie, T.; Imaki, H.; Greene, J.; [et al.]. 2013. Restoring 

salmon habitat for a changing climate. River Research and 

Applications. 29: 939–960.

Behnke, R. 2002. Trout and salmon of North America. New York, 

NY: Simon and Schuster. 384 p.

Benjamin, J.R.; Baxter, C.V. 2012. Is a trout a trout? A rangewide comparison shows nonnative brook trout exhibit greater 

density, biomass, and production than native inland cutthroat 

trout. Biological Invasions. 14: 1865–1879.

Benjamin, J.R.; Dunham, J.B.; Dare, M.R. 2007. Invasion by 

nonnative brook trout in Panther Creek, Idaho: Roles of local 

habitat quality, biotic resistance, and connectivity to source 

habitats. Transactions of the American Fisheries Society. 136: 

875–888.

Blaustein, A.P.; Beatty, J.J.; Olson, D.H.; [et al.]. 1995. The 

biology of amphibians and reptiles in old-growth forests in the 

Pacific Northwest. Gen. Tech. Rep. PNW-GTR-337. Portland, 

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

Northwest Research Station. 98 p.

Bouwes, N.; Weber, N.; Jordan, C.E.; [et al.]. 2016. Ecosystem 

experiment reveals benefits of natural and simulated beaver 

dams to a threatened population of steelhead (Oncorhynchus 

mykiss). Scientific Reports. 6: doi:10.1038/srep28581.

Bozek, M.A.; Young, M.K. 1994. Fish mortality resulting from 

delayed effects of fire in the Greater Yellowstone Ecosystem. 

Great Basin Naturalist. 54: 91–95.

Bradford D.F. 1983. Winterkill, oxygen relations, and energy 

metabolism of a submerged dormant amphibian, Rana muscosa. 

Ecology. 64: 1171–1183.

Brown, C.; Hayes, M.P.; Green, G.A.; [et al.]. 2015. Yosemite 

toad conservation assessment. R5-TP-040. Vallejo, CA: U.S. 

Department of Agriculture, Forest Service, Pacific Southwest 

Region.

Brown, C.; Kiehl, K.; Wilkinson, L. 2012. Advantages of longterm, multi-scale monitoring: Assessing the current status of the 

Yosemite toad (Anaxyrus [Bufo] canorus) in the Sierra Nevada, 

California, USA. Herpetological Conservation and Biology. 7: 

115–131.

Burns, E.R.; Zhu, Y.; Zhan, H.; [et al.]. 2017. Thermal effect 

of climate change on groundwater-fed ecosystems. Water 

Resources Research. 53: 3341–3351.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 107

California Department of Fish and Game [CDFG]. 2011. A status 

review of the mountain yellow-legged frog (Rana sierrae and 

Rana muscosa). Report to the Fish and Game Commission. 

Sacramento, CA: State of California, Natural Resources 

Agency, Department of Fish and Game. 51 p.

Coleman, M.A.; Fausch, K.D. 2007. Cold summer temperature 

limits recruitment of age-0 cutthroat trout in high-elevation 

Colorado streams. Transactions of the American Fisheries 

Society. 136: 1231–1244.

Comte, L.; Grenouillet, G. 2013. Do stream fish track climate 

change? Assessing distribution shifts in recent decades. 

Ecography. 36: 1236–1246.

Cooney, S.J.; Covich, A.P.; Lukacs, P.M.; [et al.]. 2005. Modeling 

global warming scenarios in greenback cutthroat trout 

(Oncorhynchus clarki stomias) streams: Implications for 

species recovery. Western North American Naturalist. 65: 

371–381.

Corn, P.S. 2005. Climate change and amphibians. Animal 

Biodiversity and Conservation. 28: 59–67.

Craine, J.M.; Battersby, J.; Elmore, A.J.; [et al.]. 2007. Building 

EDENs: The rise of environmentally distributed ecological 

networks. BioScience. 57: 45–54.

Crête-Lafrenière, A.; Weir, L.K.; Bernatchez, L. 2012. Framing 

the Salmonidae family phylogenetic portrait: A more complete 

picture from increased taxon sampling. PLoS ONE. 7: e46662.

Dunham, J.B.; Adams, S.B.; Schroeter, R.E.; [et al.]. 2002a. Alien 

invasions in aquatic ecosystems: Toward an understanding of 

brook trout invasions and potential impacts on inland cutthroat 

trout in western North America. Reviews in Fish Biology and 

Fisheries. 12: 373–391.

Dunham, J.B.; Baxter, C; Fausch, K.D.; [et al.]. 2008. Evolution, 

ecology, and conservation of Dolly Varden, white spotted char, 

and bull trout. Fisheries 33: 537–550.

Dunham, J.B.; Gallo, K.; Shively, D.; [et al.]. 2011. Assessing the 

feasibility of native fish reintroductions: A framework applied 

to threatened bull trout. North American Journal of Fisheries 

Management. 31: 106–115.

Dunham, J.B.; Rieman, B.E.; Chandler, G.L. 2003. Influences of 

temperature and environmental variables on the distribution 

of bull trout within streams at the southern margin of its 

range. North American Journal of Fisheries Management. 23: 

894–904.

Dunham, J.B.; Rieman, B.E.; Peterson, J.T. 2002b. Patch-based 

models to predict species occurrence: Lessons from salmonid 

fishes in streams. In: Scott, J.M.; Heglund, P.J.; Morrison, M.; 

[et al.], eds. Predicting species occurrences: issues of scale and 

accuracy. Covelo, CA: Island Press: 327–334.

Dunham, J.B.; Rosenberger, A.E.; Luce, C.H.; [et al.]. 2007. 

Influences of wildfire and channel reorganization on spatial and 

temporal variation in stream temperature and the distribution of 

fish and amphibians. Ecosystems. 10: 335–346.

Dunham, J.B.; White, R.; Allen, C.S.; [et al.]. 2016. The 

reintroduction landscape. In: Jachowski, D.S.; Millspaugh, 

J.J.; Angermeier, P.L.; [et al.], eds. Reintroduction of fish and 

wildlife populations. Berkeley, CA: University of California 

Press: 79–103.

Dunham, J.B.; Young, M.K.; Gresswell, R.E.; [et al.]. 2003. 

Effects of fire on fish populations: Landscape perspectives on 

persistence of native fishes and non-native fish invasions. Forest 

Ecology and Management. 178: 183–196.

Eby, L.A.; Helmy, O.; Holsinger, L.M.; [et al.]. 2014. Evidence of 

climate-induced range contractions for bull trout in a Rocky 

Mountain watershed, U.S.A. PLoS ONE 9: e98812.

Elmore, L.R.; Null, S.E.; Mouzon, N.R. 2015. Effects of 

environmental water transfers on stream temperatures. River 

Research and Applications. 32: 1415–1427.

Fausch, K.D.; Rieman, B.E.; Dunham, J.B.; [et al.]. 2009. Invasion 

versus Isolation: Trade-offs in managing native salmonids with 

barriers to upstream movement. Conservation Biology. 23: 

859–870.

Ficke, A.D.; Myrick, C.A.; Hansen, L.J. 2007. Potential impacts of 

global climate change on freshwater fisheries. Reviews in Fish 

Biology and Fisheries. 17: 581–613.

Goode, J.R.; Buffington, J.M.; Tonina, D.; [et al.]. 2013. Potential 

effects of climate change on streambed scour and risks to 

salmonid survival in snow-dominated mountain basins. 

Hydrological Processes. 27: 750–765.

Halofsky, J.E.; Peterson, D.L.; Dante-Wood, S.K.; [et al.], eds. 

2018. Climate change vulnerability and adaptation in the 

Northern Rocky Mountains. Gen. Tech. Rep. RMRS-GTR-374. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station.

Hamlet, A.F.; Lettenmaier, D.P. 2007. Effects of 20th century 

warming and climate variability on flood risk in the western 

U.S. Water Resources Research. 43: W06427

Hamlet, A.F.; Elsner, M.M.; Mauger, G.S.; [et al.]. 2013. An 

overview of the Columbia Basin climate change scenarios 

project: Approach, methods, and summary of key results. 

Atmosphere-Ocean. 51: 392–415.

Hauer, F.R.; Baron, J.S.; Campbell, D.H.; [et al.]. 1997. 

Assessment of climate change and freshwater ecosystems of the 

Rocky Mountains, USA and Canada. Hydrological Processes. 

11: 903–924.

Hayes, M.P.; Quinn, T., eds. 2015. Review and synthesis of 

the literature on tailed frogs (genus Ascaphus) with special 

reference to managed landscapes. Coop. Monitor. Eval. Res. 

Rep. CMER 01-107. Olympia, WA: Washington Department of 

Natural Resources, Washington State Forest Practices Adaptive 

Management Program.

Hershler, R. 1998. A systematic review of the hydrobiid snails 

(Gastropoda:Rissooidea) of the Great Basin, western United 

States: Part I. Genus Pyrgulopsis. Veliger. 41: 1–132.

Hershler, R.; Liu, H.P; Howard, J. 2014. Springsnails: A new 

conservation focus in western North America. BioScience. 64: 

693–700.

Horizon Systems Corp. [n.d.] NHDPlus home. http://www.horizonsystems.com/NHDPlus/index.php, ver. 2 [Accessed April 26, 

2017].

Hossack, B.R.; Pilliod, D.S. 2011. Amphibian responses to wildfire 

in the western United States: Emerging patterns from shortterm studies. Fire Ecology. 7: 129–144.

Hossack, B.R.; Corn, P.S.; Fagre D.B. 2006. Divergent patterns of 

abundance and age-class structure of headwater stream tadpoles 

in burned and unburned watersheds. Canadian Journal of 

Zoology. 84: 1482–1488.

Hovingh, P. 2004. Intermountain freshwater mollusks, USA 

(Margaritifera, Anodonta, Gonidea, Valvata, Ferrissia): 

Geography, conservation, and fish management implications. 

Monographs of the Western North American Naturalist. 2: 

109–135.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
108 USDA Forest Service RMRS-GTR-375. 2018

Howell, P.J.; Dunham, J.B.; Sankovich, P.M. 2010. Relationships 

between water temperatures and upstream migration, cold water 

refuge use, and spawning of adult bull trout from the Lostine 

River, Oregon, USA. Ecology of Freshwater Fish. 19: 96–106.

Isaak, D.J.; Rieman, B.E. 2013. Stream isotherm shifts from 

climate change and implications for distributions of ectothermic 

organisms. Global Change Biology. 19: 742–751.

Isaak, D.J.; Luce, C.; Rieman, B.; [et al.]. 2010. Effects of 

climate change and recent wildfires on stream temperature and 

thermal habitat for two salmonids in a mountain river network. 

Ecological Applications. 20: 1350–1371.

Isaak, D.J.; Muhlfeld, C.C.; Todd, A.S.; [et al.]. 2012a. The past 

as prelude to the future for understanding 21st-century climate 

effects on Rocky Mountain trout. Fisheries. 37: 542–556.

Isaak, D.J.; Peterson, E.; Ver Hoef, J.; [et al.]. 2014. Applications 

of spatial statistical network models to stream data. Wiley 

Interdisciplinary Reviews–Water. 1: 27–294.

Isaak, D.J.; Wenger, S.J., Peterson, E.E.; [et al.]. 2016a. NorWeST 

modeled summer stream temperature scenarios for the western 

U.S. Data archive. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station.

Isaak, D.J.; Wenger, S.J., Peterson, E.E.; [et al.]. 2017a. The 

NorWeST database and summer temperature scenarios: A 

crowd-sourced database and new geospatial tools foster a 

user-community and predict broad climate warming of rivers 

and streams in the western U.S. Water Resources Research. 53: 

9181–9205.

Isaak, D.J.; Wenger, S.J.; Young, M.K. 2017b. Big biology meets 

microclimatology: Defining thermal niches of ectotherms 

at landscape scales for conservation planning. Ecological 

Applications. 27: 977–990.

Isaak, D.J.; Wollrab, S.; Horan, D.; [et al.]. 2012b. Climate change 

effects on stream and river temperatures across the northwest 

U.S. from 1980–2009 and implications for salmonid fishes. 

Climatic Change. 113: 499–524.

Isaak, D.; Young, M.K.; Luce, C.; [et al.]. 2016b. Slow climate 

velocities of mountain streams portend their role as refugia for 

cold-water biodiversity. Proceedings of the National Academy 

of Sciences, USA. 113: 4374–4379.

Isaak, D.J.; Young, M.K.; Nagel, D.; [et al.]. 2015. The cold-water 

climate shield: Delineating refugia to preserve salmonid 

fishes through the 21st century. Global Change Biology. 21: 

2540–2553.

Independent Science Advisory Board [ISAB]. 2007. Climate 

change impacts on Columbia River basin fish and wildlife. 

ISAB Clim. Change Rep. ISAB 2007-2. Portland, OR: 

Northwest Power and Conservation Council.

Jennings, M.R. 1996. Status of amphibians. In: Sierra Nevada 

ecosystem project: Final report to Congress, Vol. 2, 

Assessments and scientific basis for management options. Rep. 

37. Davis, CA: University of California, Davis, Centers for 

Water and Wildland Resources: 921–944.

Jennings, M.R.; Hayes, M.P. 1994. Amphibian and reptile species 

of special concern status in California. Unpublished report on 

file with: California Department of Fish and Game, Rancho 

Cordova, CA. 255 p.

Jyväsjärvi, J.; Marttila, H.; Rossi, P.M.; [et al.]. 2015. Climateinduced warming imposes a threat to north European spring 

ecosystems. Global Change Biology. 21: 4561–4569.

Kagarise Sherman, C. 1980. A comparison of the natural history 

and mating system of two anurans: Yosemite toads (Bufo 

canorus) and black toads (Bufo exsul). PhD dissertation. Ann 

Arbor, MI: University of Michigan. 394 p.

Kagarise Sherman, C.; Morton, M.L. 1984. The toad that stays on 

its toes. Natural History. 93: 72–78.

Kagarise Sherman, C.; Morton, M.L. 1993. Population declines 

of Yosemite toads in the eastern Sierra Nevada of California. 

Journal of Herpetology. 27: 186–198.

Kanda, N.; Leary, R.F.; Allendorf, F.W. 2002. Evidence of 

introgressive hybridization between bull trout and brook trout. 

Transactions of the American Fisheries Society. 131: 772–782.

Karlstrom, E.L. 1962. The toad genus Bufo in the Sierra Nevada of 

California: Ecological and systematic relationships. University 

of California Publications in Zoology. 62: 1–104.

Karna, D.W.; Millemann, R.E. 1978. Glochidiosis of salmonid 

fishes. III. Comparative susceptibility to natural infection with 

Margaritifera margaritifera (L.) (Pelecypoda: Margaritanidae) 

and associated histopathology. Journal of Parasitology. 64: 

528–537.

Klemetsen, A. 2010. The charr problem revisited: Exceptional 

phenotypic plasticity promotes ecological speciation in 

postglacial lakes. Freshwater Reviews. 3: 49–74.

Klemetsen, A.; Amundsen, P.A.; Dempson, J.B.; [et al.]. 2003. 

Atlantic salmon Salmo salar L., brown trout Salmo trutta L. 

and Arctic charr Salvelinus alpinus (L.): A review of aspects of 

their life histories. Ecology of Freshwater Fish. 12: 1–59.

Knapp, R.A.; Fellers, G.M.; Kleeman, P.M.; [et al.]. 2016. Largescale recovery of an endangered amphibian despite ongoing 

exposure to multiple stressors. Proceedings of the National 

Academy of Sciences, USA. 113: 11889–11894.

Kovach, R.P.; Al-Chokhachy, R.; Whited, D.C.; [et al.]. 2017. 

Climate, invasive species and land use drive population 

dynamics of a cold-water specialist. Journal of Applied 

Ecology. 54: 638–647.

Kovach, R.P.; Gharrett, A.J.; Tallmon, D.A. 2012. Genetic change 

for earlier migration timing in a pink salmon population. 

Proceedings of the Royal Society of London B: Biological 

Sciences. 279: 3870–3878.

Lacan, I.; Matthews, K.; Feldman, K. 2008. Interaction of an 

introduced predator with future effects of climate change 

in the recruitment dynamics of the imperiled Sierra Nevada 

yellowlegged frog (Rana sierrae). Herpetological Conservation 

and Biology. 3: 211–223.

Lee, S-Y.; Ryan, M.E.; Hamlet, A.F. 2015. Projecting the 

hydrologic impacts of climate change on montane wetlands. 

PLoS ONE. 10: e0136385.

Leppi, J.C.; DeLuca, T.H.; Harrar, S.W.; [et al.]. 2012. Impacts 

of climate change on August stream discharge in the CentralRocky Mountains. Climatic Change. 112: 997–1014.

Loarie, S.R.; Duffy, P.B.; Hamilton, H.; [et al.]. 2009. The velocity 

of climate change. Nature. 462: 1052–1055.

Loxterman, J.L.; Keeley, E.R. 2012. Watershed boundaries and 

geographic isolation: Patterns of diversification in cutthroat 

trout from western North America. BMC Evolutionary Biology. 

12: 38.

Luce, C.H.; Holden, Z.A. 2009. Declining annual streamflow 

distributions in the Pacific Northwest United States, 1948–

2006. Geophysical Research Letters. 36: L16401.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 109

Luce, C.; Morgan, P.; Dwire, K.; [et al.]. 2012. Climate change, 

forests, fire, water, and fish: Building resilient landscapes, 

streams, and managers. Gen. Tech. Rep. RMRS-GTR-290. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station.

Luce, C.H.; Staab, B.P.; Kramer, M.G.; [et al.]. 2014. Sensitivity of 

summer stream temperatures to climate variability in the Pacific 

Northwest. Water Resources Research. 50: 1–16.

Magnuson, J.J.; Crowder, L.B.; Medvick, P.A. 1979. Temperature 

as an ecological resource. American Zoologist. 19: 331–343.

Mantua, N.J.; Raymond, C.L. 2014. Climate change, fish, and 

aquatic habitat in the North Cascade Range. In: Raymond, 

C.L.; Peterson, D.L.; Rochefort, R.M., eds. Climate change 

vulnerability and adaptation in the North Cascades region, 

Washington. Gen. Tech. Rep. PNW-GTR-892. Portland, 

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

Northwest Research Station: 235–270.

Mantua, N.J.; Tohver, I.; Hamlet, A. 2010. Climate change impacts 

on streamflow extremes and summertime stream temperature 

and their possible consequences for freshwater salmon habitat 

in Washington State. Climatic Change. 102: 187–223.

Martinez, P.J.; Bigelow, P.E.; Deleray, M.A.; [et al.]. 2009. Western 

lake trout woes. Fisheries. 34: 424–442.

McCullough, D.A.; Bartholow, J.M.; Jager, H.I.; [et al.]. 2009. 

Research in thermal biology: Burning questions for coldwater 

stream fishes. Reviews in Fisheries Science. 17: 90–115.

McFall, Sean. 2017. Water Transaction Tool, Idaho. Trout 

Unlimited. https://public.tableau.com/profile/sean.mcfall#!/

vizhome/ClimateShieldIdaho/Story1 [Accessed October 25, 

2017].

McKay, L.; Bondelid, T.; Dewald, T.; [et al.]. 2012. NHDPlus 

version 2: User guide. ftp://ftp.horizon-systems.com/NHDPlus/

NHDPlusV21/Documentation/NHDPlusV2_User_Guide.pdf 

[Accessed September 16, 2016].

McKelvey, K.S.; Young, M.K.; Knotek, W.L.; [et al.]. 2016. 

Sampling large geographic areas for rare species using 

environmental DNA: A study of bull trout occupancy in western 

Montana. Journal of Fish Biology. 88: 1215–1222.

McKelvey, K.S.; Young, M.K.; Wilcox, T.M.; [et al.]. 2016. 

Patterns of hybridization among cutthroat and rainbow trout in 

northern Rocky Mountain streams. Ecology and Evolution. 6: 

688–706.

McPhail, J.D.; Lindsey, C.C. 1986. Zoogeography of the 

freshwater fishes of Cascadia (the Columbia system and 

rivers north to the Stikine). In: Hocutt, C.H.; Wiley, E.O., eds. 

Zoogeography of North American freshwater fishes. New York, 

NY: Wiley: 615–637.

Metcalf, J.L.; Love Stowell, S. Kennedy, C.M.; [et al.]. 2012. 

Historical stocking data and 19th century DNA reveal humaninduced changes to native diversity and distribution of cutthroat 

trout. Molecular Ecology. 21: 5194–5207.

Metzger, G.; Espindola, A.; Waits, L.P.; Sullivan, J. 2015. Genetic 

structure across broad spatial and temporal scales: Rocky 

Mountain tailed frogs (Ascaphus montanus; Anura: Ascaphidae) 

in the inland temperate rainforest. Journal of Heredity. 106: 

700–710.

Meyers, T.R.; R.E. Millemann. 1977. Glochidiosis of salmonid 

fishes. I. Comparative susceptibility to experimental 

infection with Margaritifera margaritifera (L.) (Pelecypoda: 

Margaritanidae). Journal of Parasitology 63: 728–733.

Miller, D.; Luce, C.; Benda, L. 2003. Time, space, and episodicity 

of physical disturbance in streams. Forest Ecology and 

Management. 178: 121–140.

Minckley, W.L.; Hendrickson, D.A.; Bond, C.E. 1986. Geography 

of western North American freshwater fishes: Description and 

relationships to intracontinental tectonism. In: Hocutt, C.H.; 

Wiley, E.O., eds. Zoogeography of North American freshwater 

fishes. New York, NY: Wiley: 519–614.

Mladenka, G.C.; Minshall, G.W. 2001. Variation in the life history 

and abundance of three populations of Bruneau hot springsnails 

(Pyrgulopsis bruneauensis). Western North American 

Naturalist. 61: 204–212.

Morelli, T.L.; Daly C.; Dobrowski, S.Z.; [et al.]. 2016. Managing 

climate change refugia for climate adaptation. PLoS ONE. 11: 

e0159909.

Mote, P.W.; Salathé, E.P. 2010. Future climate in the Pacific 

Northwest. Climatic Change. 102: 29–50.

Mote, P.W.; Hamlet, A.F.; Clark, M.P.; [et al.]. 2005. Declining 

mountain snowpack in western North America. Bulletin of the 

American Meteorological Society. 86: 39–49.

Mote, P.W.; Parson, E.A.; Hamlet, A.F.; [et al.]. 2003. Preparing 

for climatic change: The water, salmon, and forests of the 

Pacific Northwest. Climatic Change. 61: 45–88.

Mullally, D.P.; Cunningham, J.D. 1956. Ecological relations 

of Rana muscosa at high elevations in the Sierra Nevada. 

Herpetologica. 12: 189–198.

Mullen, L.B.; Woods, H.A.; Schwartz, M.K.; [et al.]. 2010. Scaledependent genetic structure of the Idaho giant salamander 

(Dicamptodon aterrimus) in stream networks. Molecular 

Ecology. 19: 898–909.

Murphy, G. 1942. Relationship of the fresh water mussel to trout in 

the Truckee River. California Fish and Game 28: 89–102.

Narum, S.R.; Campbell, N.R.; Meyer, K.A.; [et al.]. 2013. Thermal 

adaptation and acclimation of ectotherms from differing aquatic 

climates. Molecular Ecology. 22: 3090–3097.

Northcote, T.G. 1992. Migration and residency in stream 

salmonids: Some ecological considerations and evolutionary 

consequences. Nordic Journal of Freshwater Research. 67: 

5–17.

Nussbaum, R.A. 1969. Nests and eggs of the Pacific giant 

salamander, Dicamptodon ensatus (Eschscholtz). 

Herpetologica. 25: 257–262.

Nusslé, S.; Matthews, K.R.; Carlson, S.M. 2015. Mediating 

water temperature increases due to livestock and global 

change in high elevation meadow streams of the Golden Trout 

Wilderness. PLoS ONE. 10: e0142426.

O’Brien, C.; Blinn, D.W. 1999. The endemic spring snail 

Pyrgulopsis montezumensis in a high CO2

 environment: 

Importance of extreme chemical habitats as refugia. Freshwater 

Biology. 42: 225–234.

Peterson, D.P.; Fausch, K.D.; Watmough, J.; [et al.]. 2008. 

When eradication is not an option: Modeling strategies for 

electrofishing suppression of nonnative brook trout to foster 

persistence of sympatric native cutthroat trout in small streams. 

North American Journal of Fisheries Management. 28: 

1847–1867.

Peterson, D.P.; Rieman, B.E.; Horan, D.L.; [et al.]. 2013a. Patch 

size but not short-term isolation influences occurrence of 

westslope cutthroat trout above human-made barriers. Ecology 

of Freshwater Fish. 23: 556–571.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
110 USDA Forest Service RMRS-GTR-375. 2018

Peterson, D.P.; Wenger, S.J.; Rieman, B.E.; [et al.]. 2013b. Linking 

climate change and fish conservation efforts using spatially 

explicit decision support models. Fisheries. 38: 111–125.

Pilliod, D.S.; Peterson, C.R. 2001. Local and landscape effects 

of introduced trout on amphibians in historically fishless 

watersheds. Ecosystems. 4: 322–333.

Pilliod, D.S.; Goldberg, C.S.; Arkle, R.S.; [et al.]. 2013. Estimating 

occupancy and abundance of stream amphibians using 

environmental DNA from filtered water samples. Canadian 

Journal of Fisheries and Aquatic Sciences. 70: 1123–1130.

Pilliod, D.S.; Hossack, B.R.; Bahls, P.F.; [et al.]. 2010. Non-native 

salmonids affect amphibian occupancy at multiple spatial 

scales. Diversity and Distributions. 16: 959–974.

Poff, N.L.; Brinson, M.M.; Day, J.W.J. 2002. Aquatic ecosystems 

and global climate change: Potential impacts on inland 

freshwater and coastal wetland ecosystems in the United States. 

Online report. Washington, DC: Pew Center on Global Climate 

Change. http:www.pewclimate.org/projects/aquatic [Accessed 

September 16, 2016].

Pollock, M.M.; Beechie, T.J.; Wheaton, J.M.; [et al.]. 2014. Using 

beaver dams to restore incised stream ecosystems. BioScience. 

64: 279–290.

Pope, K.L.; Matthews, K.R. 2001. Movement ecology and seasonal 

distribution of mountain yellow-legged frogs, Rana muscosa, 

in a high-elevation Sierra Nevada basin. Copeia. 2001(3): 

787–793.

Rieman, B.E.; Dunham, J.B. 2000. Metapopulations and 

salmonids: A synthesis of life history patterns and empirical 

observations. Ecology of Freshwater Fish. 9: 51–64.

Rieman, B.E.; Isaak, D.J. 2010. Climate change, aquatic 

ecosystems, and fishes in the Rocky Mountain West: 

Implications and alternatives for management. Gen. Tech. 

Rep. RMRS-GTR-250. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station.

Rieman, B.E.; McIntyre, J.D. 1993. Demographic and habitat 

requirements for conservation of bull trout. Gen. Tech. Rep. 

INT-302. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Forest and Range Experiment Station.

Rieman, B.E.; McIntyre, J.D. 1995. Occurrence of bull trout 

in naturally fragmented habitat patches of varied size. 

Transactions of the American Fisheries Society. 124: 285–296.

Rieman, B.E.; Hessburg, P.F.; Luce, C.; [et al.]. 2010. Wildfire 

and management of forests and native fishes: Conflict or 

opportunity for convergent solutions? BioScience. 60: 460–468.

Rieman, B.E.; Isaak, D.; Adams, S.; [et al.]. 2007. Anticipated 

climate warming effects on bull trout habitats and populations 

across the interior Columbia River basin. Transactions of the 

American Fisheries Society. 136: 1552–1565.

Rieman, B.E.; Lee, D.C.; Thurow, R.F. 1997. Distribution, status, 

and likely future trends of bull trout within the Columbia River 

and Klamath River basins. North American Journal of Fisheries 

Management. 17: 1111–1125.

Rieman, B.E.; Peterson, J.T.; Myers, D.L. 2006. Have brook 

trout (Salvelinus fontinalis) displaced bull trout (Salvelinus 

confluentus) along longitudinal gradients in central Idaho 

streams? Canadian Journal of Fisheries and Aquatic Sciences. 

63: 63–78.

Roberts, J.J.; Rahel, F.J. 2008. Irrigation canals as sink habitat for 

trout and other fishes in a Wyoming drainage. Transactions of 

the American Fisheries Society. 137: 951–961.

Roscoe, E.J.; Redelings, S. 1964. The ecology of the freshwater 

pearl mussel Margaritifera margaritifera (L.). Sterkiana. 16: 

19–32.

Schindler, D.E.; Augerot, X.; Fleishman, E.; [et al.]. 2008. Climate 

change, ecosystem impacts, and management for Pacific 

salmon. Fisheries. 33: 502–506.

Sedell, E.R.; Gresswell, R.E.; McMahon, T.E. 2015. Predicting 

spatial distribution of postfire debris flows and potential 

consequences for native trout in headwater streams. Freshwater 

Science. 34: 1558–1570.

Sepulveda, A.J.; Lowe, W.H. 2009. Local and landscape-scale 

influences on the occurrence and density of Dicamptodon 

aterrimus, the Idaho giant salamander. Journal of Herpetology. 

43: 469–484.

Sepulveda, A.J.; Lowe, W.H. 2011. Coexistence in streams: Do 

source–sink dynamics allow salamanders to persist with fish 

predators? Oecologia. 166: 1043–1054.

Shepard, B.B.; May, B.E.; Urie, W. 2005. Status and conservation 

of westslope cutthroat trout within the western United States. 

North American Journal of Fisheries Management. 25: 

1426–1440.

Shepard, B.B.; Spoon, R.; Nelson, L. 2002. A native westslope 

cutthroat trout population responds positively after brook trout 

removal and habitat restoration. Intermountain Journal of 

Sciences. 8: 193–214.

Smith, G.R.; Dowling, T.E.; Gobalet, K.W.; [et al.]. 2002. 

Biogeography and timing of evolutionary events among Great 

Basin fishes. Great Basin aquatic systems history. Smithsonian 

Contributions to the Earth Sciences. 33: 175–234.

Smith, J.; Tirpak, D., eds. 1989. Potential impacts of global climate 

change on the United States. Report to Congress, PM-221. 

Washington, DC: U.S. Environmental Protection Agency, 

Office of Policy, Planning and Evaluation, Office of Research 

and Development. 689 p.

Stagliano, D.M. 2005. Freshwater mussels in Montana: 

Comprehensive results from 3 years of SWG funded surveys. 

Report to the Montana Department of Fish, Wildlife and Parks. 

Helena, MT: Montana Natural Heritage Program. 74 p.

Stewart, I.T.; Cayan, D.R.; Dettinger, M.D. 2005. Changes toward 

earlier streamflow timing across western North America. 

Journal of Climate. 18: 1136–1155.

Stone, J.; Barndt, S.; Gangloff, M. 2004. Spatial distribution and 

habitat use of the western pearlshell mussel (Margaritifera 

falcata) in a western Washington stream. Journal of Freshwater 

Ecology. 19: 341–352.

Thomsen, P.; Kielgast, J.O.S.; Iversen, L.L.; [et al.]. 2012. 

Monitoring endangered freshwater biodiversity using 

environmental DNA. Molecular Ecology. 21: 2565–2573.

University of Washington, Climate Impacts Group. 2010. Pacific 

Northwest (PNW) Hydroclimate Scenarios Project (2860). 

http://warm.atmos.washington.edu/2860 [Accessed September 

29, 2017].

USDA Forest Service [USDA FS]. [n.d.a]. Climate Shield 

cold-water refuge streams for native trout. U.S. Department 

of Agriculture, Forest Service, Rocky Mountain Research 

Station, Air, Water, & Aquatic Environments Program. http://

www.fs.fed.us/rm/boise/AWAE/projects/ClimateShield.html 

[Accessed April 26, 2017].

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
USDA Forest Service RMRS-GTR-375. 2018 111

USDA Forest Service [USDA FS]. [n.d.b]. NorWeST regional 

database and modeled stream temperatures. U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Air, Water, & Aquatic Environments Program. www.fs.fed.us/

rm/boise/AWAE/projects/NorWeST.html [Accessed April 21, 

2017].

USDA Forest Service [USDA FS]. [n.d.c]. Western U.S. stream 

flow metrics. U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station, Air, Water, & Aquatic 

Environments Program. http://www.fs.fed.us/rm/boise/AWAE/

projects/modeled_stream_flow_metrics.shtml [Accessed April 

26, 2017].

USDOI Fish and Wildlife Service [USFWS]. 1985. Paiute 

cutthroat trout (Oncorhynchus clarki seleniris) recovery 

plan. Portland, OR: U.S. Department of the Interior, Fish and 

Wildlife Service. 117 p.

USDOI Fish and Wildlife Service [USFWS]. 1995. Lahontan 

cutthroat trout (Oncorhynchus clarki henshawi) recovery 

plan. Portland, OR: U.S. Department of the Interior, Fish and 

Wildlife Service. 157 p.

USDOI Fish and Wildlife Service [USFWS]. 2014. Revised draft 

recovery plan for the coterminous United States population 

of bull trout (Salvelinus confluentus). Portland, OR: U.S. 

Department of the Interior, Fish and Wildlife Service. 151 p.

U.S. Environmental Protection Agency [USEPA]. 2014. Best 

practices for continuous monitoring of temperature and flow in 

wadeable streams. EPA/600/R-13/170F. Washington, DC: U.S. 

Environmental Protection Agency, Global Change Research 

Program, National Center for Environmental Assessment.

Ver Hoef, J.M.; Peterson, E.E.; Theobald, D.M. 2006. Spatial 

statistical models that use flow and stream distance. 

Environmental and Ecological Statistics. 13: 449–464.

Walters, A.W.; Bartz, K.K.; McClure, M.M. 2013. Interactive 

effects of water diversion and climate change for juvenile 

Chinook salmon in the Lemhi River Basin (USA). Conservation 

Biology. 27: 1179–1189.

Wenger, S.J.; Isaak, D.J.; Dunham, J.B.; [et al.]. 2011a. Role of 

climate and invasive species in structuring trout distributions in 

the interior Columbia River Basin, USA. Canadian Journal of 

Fisheries and Aquatic Sciences. 68: 988–1008.

Wenger, S.J.; Isaak, D.J.; Luce, C.H.; [et al.]. 2011b. Flow regime, 

temperature, and biotic interactions drive differential declines 

of Rocky Mountain trout species under climate change. 

Proceedings of the National Academy of Sciences, USA. 108: 

14175–14180.

Wenger, S.J.; Luce, C.H.; Hamlet, A.F.; [et al.]. 2010. Macroscale 

hydrologic modeling of ecologically relevant flow metrics. 

Water Resources Research. 46: W09513.

Whiteley, A.R.; Hastings, K.; Wenburg, J.K.; [et al.]. 2010. Genetic 

variation and effective population size in isolated populations of 

coastal cutthroat trout. Conservation Genetics. 11: 1929–1943.

Wiens, J.J., Ackerly, D.D., Allen, A.P.; [et al.]. 2010. Niche 

conservatism as an emerging principle in ecology and 

conservation biology. Ecology Letters. 13: 1310–1324.

Williams, J.E.; Haak, A.L.; Gillespie, N.G.; [et al.]. 2007. The 

Conservation Success Index: Synthesizing and communicating 

salmonid condition and management needs. Fisheries. 32: 

477–493.

Williams, J.E.; Neville, H.M.; Haak, A.L.; [et al.]. 2015. Climate 

change adaptation and restoration of western trout streams: 

Opportunities and strategies. Fisheries. 40: 304–317.

Young, B.E.; Hall, K.R.; Byers, E.; [et al.]. 2012. Rapid assessment 

of plant and animal vulnerability to climate change. In: Brodie, 

J.F.; Post, E.S.; Doak, D.F., eds. Wildlife conservation in a 

changing climate. Chicago, IL: University of Chicago Press: 

129–152.

Young, M.K.; Isaak, D.J.; McKelvey, K.S.; [et al.]. 2016. Climate, 

demography, and zoogeography predict introgression thresholds 

in salmonid hybrid zones in Rocky Mountain streams. PLoS 

One. 11: e0163563.

Young, M.K.; Isaak, D.J.; McKelvey, K.S.; [et al.]. 2017. 

Ecological segregation moderates a climactic conclusion to 

trout hybridization. Global Change Biology. 12: 521–523.

Young, M.K.; Isaak, D.J.; Spaulding, S.; [et al.]. 2018. Climate 

vulnerability of native salmonids in the Northern Rockies. In: 

Halofsky, J.E.; Peterson, D.L.; Dante-Wood, S.K. [et al.], eds. 

Climate change vulnerability and adaptation in the Northern 

Rocky Mountains. Gen. Tech. Rep. RMRS-GTR-374. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station.

Young, M.K.; McKelvey, K.S.; Pilgrim, K.L.; [et al.]. 2013. 

DNA barcoding at riverscape scales: Assessing biodiversity 

among fishes of the genus Cottus (Teleostei) in northern Rocky 

Mountain streams. Molecular Ecology Resources. 13: 583–595.

Young, Michael K.; Isaak, Daniel J.; McKelvey, Kevin S.; [et 

al.]. 2017. Species occurrence data from the Rangewide Bull 

Trout eDNA Project. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service Research Data Archive. https://doi.

org/10.2737/RDS-2017-0038. http://www.fs.fed.us/rm/boise/

AWAE/projects/BullTrout_eDNA.html [Accessed October 25, 

2017].

Zurstadt, C. 2015. Deposition of fine sediment in the South Fork 

Salmon River watershed, Payette and Boise National Forests, 

Idaho. Unpublished report on file with: Payette National Forest, 

McCall, ID.

Chapter 5: Effects of Climate Change on Native Fish and Other Aquatic Species
112 USDA Forest Service RMRS-GTR-375. 2018

Introduction

Projected rapid changes in climate will affect vegetation 

assemblages in the Intermountain Adaptation Partnership 

(IAP) region directly and indirectly. Direct effects include 

altered vegetation growth, mortality, and regeneration, and 

indirect effects include changes in disturbance regimes 

(Chapter 8) and interactions with altered ecosystem processes (e.g., hydrology, snow dynamics, nonnative species) 

(Bonan 2008; Hansen and Phillips 2015; Hansen et al. 

2001, 2016; Notaro et al. 2007). Some species may have 

decreased abundance, whereas others may expand their 

range (Landhäusser et al. 2010). New vegetation communities may form, and historical vegetation complexes may 

shift to other areas of the landscape or become rare. The 

consequences of land management policies and activities, 

including fire exclusion, fuels treatments, and grazing, interact with potential climate change effects.

Here we assess the effects of climate change on vegetation in the IAP region, based on species autecology, 

disturbance regimes, current conditions, and modeling results (table 6.1). We summarize how climate change affects 

vulnerability of important tree species, vegetation types, 

and resources of concern (box 6.1). We have integrated 

modeling results with a detailed synthesis of climate change 

literature for western North America.

This assessment is focused on vegetation types listed in 

table 6.1, where the vulnerability of each vegetation type 

is inferred from the aggregate vulnerability of its dominant 

species (table 6.2). Vulnerability is also considered with 

respect to heterogeneous landscapes, including both vegetation disturbance and land use history.

All projections of future conditions contain uncertainty 

(box 6.2). Uncertainty can result from a lack of information 

or from a disagreement about what is known or predictable. Uncertainty can also result from known and unknown 

errors. It may have many sources, including quantifiable 

errors in data, ambiguously defined concepts or terminology, 

and uncertain projections of human behavior. Uncertainty 

can be represented by quantitative measures (e.g., a range 

of values) or by qualitative statements (e.g., judgment of a 

team of experts).

Chapter 6: Effects of Climate Change on 

Forest Vegetation

Patrick N. Behrens, Robert E. Keane, David L. Peterson, and Joanne J. Ho

Climate Change Assessment Techniques

Ecologists have invested considerable effort to project 

the effects of climate change on ecosystem processes 

across various scales (Clark et al. 2001; Joyce et al. 2014; 

Schumacher et al. 2006). Using traditional field methods to 

explore climate change response is difficult because of the 

complex interactions between ecological processes, disturbance, and climate at multiple temporal and spatial scales 

(McKenzie et al. 2014).

Four techniques exist to assess and project the effects of 

climate change on vegetation and related resource concerns. 

First, expert opinion involves experts in the fields of climate change, ecology, and vegetation dynamics qualitatively 

assessing what will happen to vegetation under various climate change scenarios. Second, field assessment involves 

monitoring or remote sensing to monitor vegetation change 

as the climate warms. Field sampling involves establishing 

plots across the landscape, detecting change between plot 

measurements, and correlating these changes to climate 

data. Demographic studies track individuals over time, rather than using plot-scale inventories, to understand the role 

of climate relative to other factors. The U.S. Department 

of Agriculture Forest Service (USFS) Forest Inventory and 

Analysis database, the only demographic dataset in the IAP 

region, has not been analyzed for the interaction of vegetation and climate. Although field assessment techniques 

are the most reliable and useful, they are often intractable 

because of the large areas and long time periods for which 

sampling is needed to detect changes.

Third, statistical analysis can be used to create empirical models that project climate change response. Many 

studies that project habitat, range, or occupational shifts of 

tree species from climate warming use species distribution 

models (SDMs; also called bioclimatic envelope models or 

niche models) to project future geographic ranges (Hansen 

and Phillips 2015; Iverson and Prasad 2002; Warwell et al. 

2007). However, SDMs are inherently flawed for projecting future species distributions because they rely on recent 

or historical climate-species relationships, resulting in 

predictions of potential species habitat, not actual species 

distribution (Iverson and McKenzie 2013). One of the 

biggest limitations of this approach is that most species 

distributions are not in equilibrium with climate, thereby 

causing SDMs to miss areas favorable for a species but 

where the species is currently absent. In addition, SDMs do 

not include critical ecological processes (e.g., reproduction, 
USDA Forest Service RMRS-GTR-375. 2018 113

Table 6.1—Vegetation types included in the IAP vulnerability assessment.

Vegetation typea Description

Subalpine pine forest Forest communities dominated or co-dominated by bristlecone, limber, and/or whitebark 

pine for long periods of time. Other co-dominant trees may include subalpine fir, 

Engelmann spruce, white fir, and aspen.

Subalpine spruce-fir forest Upland forest communities in which the most shade-tolerant tree capable of occupying 

the site is subalpine fir, Engelmann spruce, and/or blue spruce. Major seral species 

include lodgepole pine, aspen, and Douglas-fir.

Mesic mixed conifer forest Upland forest communities where the most shade-tolerant tree capable of occupying 

the site is grand fir, white fir, Shasta red fir, mountain hemlock, or Sierra lodgepole pine. 

Major seral species include lodgepole pine, Douglas-fir, ponderosa pine, Jeffery pine, and 

aspen.

Dry mixed conifer forest Upland, lower montane, forest communities where the most shade-tolerant tree capable 

of occupying the site is Douglas-fir, white fir, or limber pine; and woodland species such 

as curl-leaf mountain mahogany, Gambel oak, bigtooth maple, pinyons, and junipers are 

usually present. Ponderosa pine is a major seral species. Lodgepole pine is absent. Aspen 

is sometimes an important seral species.

Aspen-mixed conifer forest Upland forest communities where the most shade-tolerant tree capable of occupying the 

site is a conifer species but aspen is (or was) an important component due to periodic 

disturbances. Following a disturbance, conifers can return to dominance in less than 150 

years.

Persistent aspen forest Upland forest communities dominated by aspen in which succession to conifer 

dominance is not possible or takes longer than 150 years.

Ponderosa pine forest Upland forest communities where ponderosa pine is the only forest tree species capable 

of occupying the site, or where natural under-burning periodically eliminates other 

conifers and maintains ponderosa pine dominance.

Riparian forest Forest communities occurring adjacent to water bodies or around seeps and springs. 

They may be dominated by any of the species listed above in addition to cottonwoods, 

willows, alders, birch, or nonnative trees such as saltcedar and Russian olive.

a

Vegetation types are those used by the U.S. Forest Service Intermountain Region.

tree growth, competitive interactions, disturbance) (Iverson 

and McKenzie 2013; Watling et al. 2012).

Finally, the most effective technique uses modeling to 

assess climate-mediated vegetation responses (Gustafson 

2013; Iverson and McKenzie 2013; McKenzie et al. 2014), 

incorporating projected future climate into ecological models to simulate climate change effects (Baker 1989; He et 

al. 2008; Keane et al. 2004; Merriam et al. 1992; Perry and 

Millington 2008). Many existing models simulate ecological 

change at broad (global, regional) and fine (point, ecosystem, stand) scales (Bugmann 2001; Cramer et al. 2001). 

However, models focused on large spatial scales (50–500 

square miles) are best suited for projecting climate change 

effects because most ecosystem processes operate and most 

management decisions are made at large scales (Cushman et 

al. 2007; Littell et al. 2011; McKenzie et al. 2014).

To realistically model species composition changes, a 

mechanistic, process-driven simulation approach is needed 

to emphasize physical drivers of vegetation dynamics that 

are directly related to climate (Falk et al. 2007; Gustafson 

2013; McKenzie et al. 2014). However, mechanistic model 

design is complex, containing detailed parameterization of 

species life histories and physiologies, interacting disturbance factors, and high-resolution modeling over large areas 

(Lawler et al. 2006). Dynamic global vegetation models 

operate at scales from regional (hundreds of miles) to global 

(degrees of latitude and longitude), projecting aggregates of 

species as life forms or plant functional types, which may 

not be directly relevant for resource managers (Bachelet 

et al. 2003; Bonan 2008; Neilson et al. 2005). Most of 

these models project shifts to more drought-tolerant and 

disturbance-tolerant species in a warmer climate. In some 

models, increased water-use efficiency in trees, induced by 

elevated carbon dioxide (carbon dioxide fertilization), may 

offset this general shift in vegetation as forests expand into 

areas where the climate is currently too dry (Bachelet et al. 

2003).

Ecosystem models that accurately project climate change 

effects must simulate disturbances, vegetation, climate, and 

their interactions across multiple spatial scales (Purves and 

Pacala 2008), but few models simulate ecosystem processes 

with the mechanistic detail needed to realistically represent 

important interactions (Keane et al. 2015b; Riggs et al. 

2015) (table 6.2). For example, direct interactions between 

climate and vegetation may be more realistically represented 

by simulating the daily dynamics of carbon (photosynthesis, 

respiration), water (evapotranspiration), and nutrients at 

the plant level than by simulating vegetation development 

Chapter 6: Effects of Climate Change on Forest Vegetation
114 USDA Forest Service RMRS-GTR-375. 2018

Box 6.1—Summary of the Primary Effects of Climate Change on Vegetation Types in the IAP Region

Syntheses of autecological information, empirical data, and modeling were used to identify expected responses of 

forest vegetation in the IAP region through the end of the 21st century, summarized here for vegetation types (table 

6.1)

Subalpine Pine Forest

Highly vulnerable 

• Whitebark pine will be especially vulnerable, because warming is expected to exacerbate existing stressors 

(white pine blister rust, mountain pine beetle, fire exclusion).

• Limber pine, Engelmann spruce, and white fir may grow faster with less snowpack (longer growing season), 

although limber pine could be stressed by more bark beetles.

• Great Basin and Rocky Mountain bristlecone pines growth may decrease but with high variability among 

locations.

• Quaking aspen will be minimally affected by a warmer climate, especially compared to aspen at lower 

elevations. 

Subalpine Spruce-Fir Forest

Moderately vulnerable 

• Subalpine fir, Engelmann spruce, and blue spruce may grow faster in the upper subalpine zone because of less 

snowpack (longer growing season).

• Lodgepole pine will be more susceptible to mountain pine beetle.

• Quaking aspen will be minimally affected by a warmer climate, especially compared to aspen at lower 

elevations. 

• Douglas-fir could increase at the lower end of the subalpine zone.

• Increased wildfire could reduce the distribution of all subalpine species except aspen.

Mesic Mixed Conifer Forest

Moderately vulnerable; some winners, some losers

• Douglas-fir, ponderosa pine, and Jeffrey pine (early seral, fire tolerant) may become relatively more common 

than other (late seral) species that are less fire tolerant, but they will probably grow slower.

• Shasta red fir will grow slower, and distribution may decrease because of increased wildfire.

• Lodgepole pine and quaking aspen, which regenerate rapidly after wildfire, will persist across the landscape, 

possibly with increased stress from insects and pathogens.

Dry Mixed Conifer Forest

Moderately vulnerable; some winners, some losers

• Curl-leaf mountain-mahogany, Gambel oak, and bigtooth maple can cope with both drier soils (drought 

tolerant) and increased wildfire (vigorous sprouting), and they may become more abundant in some locations.

• Two-needle pinyon and singleleaf pinyon are sensitive to long periods of drought combined with insects, and 

they may have reduced growth and some mortality; frequent wildfire may reduce abundance.

• Limber pine may be challenged by a combination of mountain pine beetles, white pine blister rust, and 

increasing wildfire.

• Douglas-fir and white fir growth will decrease; white fir will be less abundant if wildfire frequency increases.

Aspen-Mixed Conifer Forests

•	 Moderately vulnerable, depending on vegetation

• Mature spruce-fir forest will become less common if wildfire frequency increases.

• At higher elevations, early-seral species such as quaking aspen will become more abundant and possibly more 

widely distributed.

• At lower elevations, ponderosa pine will persist, and quaking aspen and Gambel oak will become more 

abundant.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 115

Box 6.1—continued.

• Changes in species distribution and abundance will depend on topography (north vs. south aspect, canyons vs. 

side slopes, etc.).

Persistent Aspen Forests

Moderately vulnerable, depending on vegetation

• Mature spruce-fir forest will become less common if wildfire frequency increases.

• Aspen will maintain dominance because of its ability to sprout after wildfire. 

• At lower elevations, ponderosa pine will persist, and quaking aspen and Gambel oak will become more 

abundant.

• Douglas-fir will probably persist because it has relatively high drought and fire tolerance, but will grow slower. 

Montane Pine Forests

Moderately vulnerable

• Ponderosa pine will maintain and probably increase dominance over associated species that are less tolerant of 

drought and wildfire, but it may grow slower. 

• Limber pine and bristlecone pine will probably persist at higher elevations where fuel loads are low. 

• If bark beetles become more prevalent, they could increase stress and mortality in pine species, especially 

during drought periods.

Riparian Forests

Highly vulnerable

• Vegetation dominance will transition to species that are more tolerant of seasonal drought, including ponderosa 

pine and other deep-rooted conifers. 

• Hardwood species that rely on periodic high water levels for regeneration will become less common. 

• Riparian forests associated with small or transient water sources (e.g., springs) will be more susceptible than 

forests near large water sources (e.g., rivers). Low-elevation riparian forests near small water sources will be 

more susceptible than high-elevation forests with persistent snowpack.

• Saltcedar will persist in riparian areas because it is more drought tolerant than native vegetation, but tamarisk 

beetle is a promising biocontrol.

annually using state-and-transition modeling approaches 

(Keane et al. 2015a).

Forest Vegetation Responses 

to Climate

The effects of climate change on forest vegetation 

are likely to be driven primarily by vegetation responses 

to altered disturbance regimes, and secondarily through 

direct effects on vegetation through shifts in regeneration, 

growth, and mortality (Dale et al. 2001; Flannigan et al. 

2009; Temperli et al. 2013) (box 6.3). Effects on vegetation 

caused by a changing climate (Chapter 3) will vary over 

different spatial and temporal scales. Trees will respond to 

reduced water availability, higher temperatures, and changes 

in growing season in different ways, but because trees are 

stationary organisms, altered vegetation composition and 

structure will be the result of changes in plant processes and 

responses to disturbance. This section discusses responses of 

trees and other forest vegetation to projected climate.

Individual Plant Effects

There are several important modes of response of plants 

to changing climates (Joyce and Birdsey 2000). The first 

is changes in productivity, which could increase in some 

locations because of increasing temperatures, longer growing seasons, and improved water-use efficiency (Aston 

2010; Joyce 1995). The window of successful seedling 

establishment will change (Ibáñez et al. 2007), and increasing drought and high temperatures may narrow the time for 

effective regeneration in low-elevation forests and widen 

the window in high-elevation forests. Climate may directly 

cause tree mortality through the effects of increased temperature on moisture stress in trees. Extreme climatic events, 

such as late growing-season frosts and high winds causing 

breakage and blowdowns, may increase because of projected increases in climatic variability (Notaro 2008), and 

these events may cause mortality (Joyce et al. 2014; Vanoni 

Chapter 6: Effects of Climate Change on Forest Vegetation
116 USDA Forest Service RMRS-GTR-375. 2018

Table 6.2—Dominant tree species in each vegetation type (see table 6.1) in each IAP subregion. Indicator species are shown in 

bold text.

Vegetation 

typea

Middle 

Rockies

Greater 

Yellowstone

Uintas and 

Wasatch Front Plateaus Great Basin

Intermountain 

Semi Desert

Subalpine pine 

forest

PNVb

Whitebark 

pine

PNV

Whitebark pine

PNV

Whitebark pine

Limber pine

PNV

Limber pine

GB bristlecone 

pinec

PNV

Limber pine

GB bristlecone 

pine

Subalpine 

spruce-fir 

forest

PNV

Subalpine fir

Engelmann 

spruce

Seral

Lodgepole 

pine

Douglas-fir

Western larch

PNV

Subalpine fir

Engelmann 

spruce

Seral

Lodgepole pine

Douglas-fir

PNV

Subalpine fir

Engelmann 

spruce

Seral

Lodgepole pine

Douglas-fir

PNV

Subalpine fir

Engelmann 

spruce

Blue spruce

Seral

Douglas-fir

PNV

Subalpine fir

Engelmann 

spruce

Blue spruce

Seral

Lodgepole 

pine

Douglas-fir

Mesic mixed 

conifer forest

PNV

Grand fir

Douglas-fir

Seral

Lodgepole 

pine

Douglas-fir

Ponderosa 

pine

Western larch

PNV

Douglas-fir

Seral

Lodgepole pine

PNV

White fir

Douglas-fir

Seral

Lodgepole pine

Douglas-fir

PNV

White fir

Douglas-fir

Seral

Douglas-fir

Ponderosa pine

PNV

White fir

Sierra white fir

Shasta red fir

Mountain 

hemlock

Sierra 

lodgepole pine

Seral

Sierra 

lodgepole pine

Western white 

pine

Jeffrey pine

Ponderosa pine

Dry mixed 

conifer forest

PNV

Douglas-fir

Grand fir

Seral

Ponderosa 

pine

Douglas-fir

PNV

Douglas-fir

Limber pine

Seral

Limber pine

PNV

White fir

Douglas-fir

Seral

Ponderosa pine

Gambel oak

Curl-leaf mtn.- 

mahogany

Bigtooth maple

Rocky Mtn. 

juniper

PNV

White fir

Douglas-fir

Seral

Ponderosa pine

Gambel oak

Curl-leaf mtn.- 

mahogany

Bigtooth maple

Utah juniper

Two-needle 

pinyon

PNV

White fir

Sierra white fir

Douglas-fir

Seral

Ponderosa 

pine

Jeffrey pine

Gambel oak

Curl-leaf mtn.- 

mahogany

Bigtooth 

maple

Utah juniper

Singleleaf 

pinyon

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 117

Vegetation 

typea

Middle 

Rockies

Greater 

Yellowstone

Uintas and 

Wasatch Front Plateaus Great Basin

Intermountain 

Semi Desert

Aspen-mixed 

conifer forest

PNV

Subalpine fir

Engelmann 

spruce

Grand fir

Douglas-fir

Seral

Aspen

Lodgepole 

pine

Douglas-fir

Ponderosa 

pine

PNV

Subalpine fir

Engelmann 

spruce

Douglas-fir

Seral

Aspen

Lodgepole pine

Douglas-fir

PNV

Subalpine fir

Engelmann 

spruce

White fir

Douglas-fir

Seral

Aspen

Lodgepole pine

Douglas-fir

Ponderosa pine

Gambel oak

Curl-leaf mtn.- 

mahogany

Bigtooth maple

PNV

Subalpine fir

Engelmann 

spruce

Blue spruce

White fir

Douglas-fir

Seral

Aspen

Douglas-fir

Ponderosa pine

Gambel oak

Curl-leaf mtn.- 

mahogany

Bigtooth maple

PNV

White fir

Sierra white fir

Shasta red fir

Seral

Aspen

Sierra 

lodgepole pine

Jeffrey pine

Western 

juniper

Persistent 

aspen forest

None PNV

Aspen

Subalpine fir

Engelmann 

spruce

Douglas-fir

Seral

Aspen

Lodgepole pine

PNV

Aspen

Subalpine fir

Engelmann 

spruce

White fir

Douglas-fir

Seral

Aspen

Lodgepole pine

PNV

Aspen

Subalpine fir

Engelmann 

spruce

Blue spruce

White fir

Douglas-fir

Seral

Aspen

Douglas-fir

Ponderosa pine

Gambel oak

Curl-leaf mtn. 

mahogany

Bigtooth maple

PNV

Aspen

White fir

Sierra white fir

Shasta red fir

Seral

Aspen

Sierra 

lodgepole pine

Jeffrey pine

Western 

juniper

PNV

Aspen (snow 

pockets)

Montane pine 

forest

PNV

Douglas-fir

Ponderosa 

pine

Grand fir

Limber pine

Seral

Ponderosa 

pine

Douglas-fir

Limber pine

PNV

Limber pine

Douglas-fir

Seral

Limber pine

PNV

Limber pine

Ponderosa pine

Douglas-fir

White fir

GB bristlecone 

pine

Seral

Limber pine

GB bristlecone 

pine

Ponderosa pine

PNV

Limber pine

GB bristlecone 

pine

Ponderosa pine

Douglas-fir

White fir

Seral

Limber pine

GB bristlecone 

pine

Ponderosa pine

PNV

Limber pine

GB bristlecone 

pine

Ponderosa 

pine

Jeffrey pine

Douglas-fir

White fir

Shasta red fir

Seral

Limber pine

GB bristlecone 

pine

Ponderosa 

pine

Jeffrey pine

Douglas-fir

Table 6.2—Continued.

Chapter 6: Effects of Climate Change on Forest Vegetation
118 USDA Forest Service RMRS-GTR-375. 2018

Vegetation 

typea

Middle 

Rockies

Greater 

Yellowstone

Uintas and 

Wasatch Front Plateaus Great Basin

Intermountain 

Semi Desert

Riparian forest PNV

Subalpine fir

Engelmann 

spruce

Grand fir

Douglas-fir

Ponderosa 

pine

Aspen

Black 

cottonwood

White alder

Sitka alder

Thinleaf alder

Water birch

PNV

Subalpine fir

Engelmann 

spruce

Blue spruce

Douglas-fir

Aspen

Lodgepole pine 

Narrowleaf 

cottonwood

Black 

cottonwood

Balsam 

cottonwood

Water birch

Thinleaf alder

Boxelder

Crack willow

PNV

Subalpine fir

Engelmann 

spruce

Blue spruce

Douglas-fir

Ponderosa pine

Aspen

Lodgepole pine

Narrowleaf 

cottonwood

Fremont 

cottonwood

Water birch

Thinleaf alder

Boxelder

Velvet ash

Crack willow

Salt cedar

PNV

Subalpine fir

Engelmann 

spruce

Blue spruce

White fir

Douglas-fir

Ponderosa pine

Aspen

Narrowleaf 

cottonwood

Fremont 

cottonwood

Water birch

Thinleaf alder

Boxelder

Velvet ash

Crack willow

Salt cedar

PNV

Subalpine fir

Engelmann 

spruce

Blue spruce

White fir

Sierra white fir

Shasta red fir

Sierra 

lodgepole pine

Douglas-fir

Jeffrey pine

Ponderosa pine

Aspen

Lodgepole 

pine

Narrowleaf 

cottonwood

Black 

cottonwood

Lanceleaf 

cottonwood

Water birch

Thinleaf alder

aVegetation types are those used by the U.S. Forest Service Intermountain Region.

b PNV indicates potential natural vegetation.

c “GB bristlecone pine” indicates Great Basin bristlecone pine.

Table 6.2—Continued.

et al. 2016). There will also be disruptions in phenology

in a warmer climate, with some plants suffering damage or 

mortality when phenological cues and events are mistimed 

with new climates (e.g., flowering during dry portions of the 

growing season) (Cayan et al. 2001). In addition, the genetic 

limitation of species or trees to respond to climate change 

will vary greatly among species and populations (Hamrick 

2004). For example, species restricted to a narrow range of 

habitat conditions may become maladapted to new climates 

(St. Clair and Howe 2007).

Plants can respond to climate-mediated changes in different ways (Aitken et al. 2008). Direct effects of temperature 

at the cellular level may increase photosynthesis and respiration (Waring and Running 1998). Photosynthesis rates 

increase with temperature up to an optimum and decline 

thereafter, although potential effects on tree growth vary by 

species and local soil and moisture conditions. In the IAP 

region, any decrease in tree growth would be expected to 

occur at low elevations, whereas some trees at high elevations may have increased growth. Respiration increases 

with temperature, and respiration occurs even when stomata 

are closed, so high temperatures coupled with low water 

availability may result in high respirational losses with few 

photosynthetic gains (Ryan et al. 1995).

Increased atmospheric carbon dioxide levels may also directly modify physiological growth processes at the cellular 

level. Water-use efficiency may increase for some conifer 

species, potentially compensating for lower water availability (Waring and Running 1998). Leaf biomass is usually 

the first to increase as plants attempt to optimize photosynthesis by growing more leaf tissue (i.e., leaf area), although 

increased leaf area can be transitory depending on available 

water and nitrogen. Higher atmospheric carbon dioxide 

levels and temperatures can also interact to increase growth, 

especially if warmer temperatures are closer to temperature 

optima for photosynthesis.

Another direct effect of warming temperatures is longer 

growing seasons (Cayan et al. 2001; McKenzie et al. 2009). 

In addition, future climate may be more variable, affecting 

dormancy regulation, bud burst, and early growth (Hanninen 

1995; Harrington et al. 2010). Plant phenological cues 

may be disrupted or triggered inappropriately because of 

high weather variability, a response that may be fatal for 

seedlings. Warmer temperatures may reduce growing-season 

frosts in mountain valleys, thereby allowing more frostsusceptible species, such as ponderosa pine (Pinus ponderosa) to exist in habitats currently occupied by lodgepole pine 

(Pinus contorta var. latifolia), subalpine fir (Abies lasiocarpa), and Engelmann spruce (Picea engelmannii). Increased 

temperatures may result in decreased winter chilling, which 

could result in delayed bud burst, reduced flowering, and 

reduced seed germination (Chmura et al. 2011).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 119

Box 6.2—Uncertainty and Climate Change Effects on Vegetation

Global Climate Models (GCMs) that project rapidly warming climates have a high degree of uncertainty. 

Although it is clear that increasing atmospheric carbon dioxide will cause a significant increase in temperature 

(IPCC 2007), uncertainty exists about the magnitude and rate of climate change (Roe and Baker 2007; Stainforth et 

al. 2005). This uncertainty is generally higher for climate projections made at fine resolutions and for longer time 

periods (Knutti and Sedlacek 2013). The range of possible projections of future climate from GCMs (anywhere from 

a 1.6 to 8 oC increase in global average annual temperature) is much greater than the variability of climate over 

the past 3 centuries (Stainforth et al. 2005), and the variability across GCMs is greater than the variability in each 

model’s climate projections. 

Because it is impossible to know whether society will respond to climate change by employing technological 

innovations to minimize carbon dioxide emissions or to mitigate its effects, most GCMs also simulate a range of 

scenarios that capture different strategies and socioeconomic policies to deal with climate change, introducing 

yet another source of uncertainty. Moreover, it is the high variability of climate extremes, not the gradual change 

of average climate, that will drive most ecosystem responses to disturbance and plant dynamics—and these rare, 

extreme events are the most difficult to project (Easterling et al. 2000). 

Yet another source of uncertainty is introduced when we try to project how the Earth’s vegetation and ecosystems 

will respond to climate change (Araujo et al. 2005). Mechanistic ecological simulation of climate, vegetation, 

and disturbance dynamics across landscapes is still evolving (Keane and Finney 2003; Sklar and Costanza 1991; 

Walker 1994). Many current ecosystem simulation models are missing important direct interactions of disturbance, 

hydrology, and land use with climate that will affect plant distributions (Notaro et al. 2007). Little is known about 

the interactions among climate, vegetation, and disturbance, and interactions among different disturbance regimes 

(e.g., fire and beetles) could create novel landscape behaviors. It is also difficult to determine how plant and animal 

reproduction, growth, and mortality will respond to changing climate (Gworek et al. 2007; Ibanez et al. 2007; 

Keane et al. 2001; Lambrecht et al. 2007). These modeling uncertainties greatly increase as projections are made 

further into the future and at finer spatial scales (Xu et al. 2009).

Uncertainties need to be considered when using this assessment for analysis, planning, and project management. 

Sometimes there is less uncertainty in implementing conventional restoration designs than in designing restoration 

or treatment plans that attempt to account for climate change effects. For example, including climate change 

in restoration of western larch ecosystems may be more straightforward than for ponderosa pine ecosystems. 

Because all climate effects will be manifest in different ways on different landscapes, there is no “one-size-fits-all” 

prescription that can be adopted everywhere.

Much of the water used by trees in mountain forests 

comes from snowmelt, so amount and duration of snowpack 

influence regeneration and growth patterns of tree species 

and forest communities. Warmer temperatures will cause 

earlier snowmelt, leading to an earlier start of the growing 

season, and longer periods of low soil moisture during the 

rest of the growing season. In contrast, less snowpack will 

create longer growing seasons in subalpine communities 

where cold and snowpack duration limit tree regeneration 

and growth, potentially facilitating increased productivity 

(Peterson and Peterson 2001) and regeneration (Woodward 

et al. 1994).

Climate change can indirectly affect vegetation by altering mycorrhizal dynamics (Amaranthus et al. 1999). Many 

trees, particularly in the seedling and sapling stages, need 

mycorrhizae to survive, especially in areas with chronic 

water shortage (Mohatt et al. 2008; Walker et al. 1995). 

Migration of tree species to more favorable sites in future 

climates may be governed by the ability of mycorrhizae to 

also populate these areas (Lankau et al. 2015). Mycorrhizal 

responses following wildfire are important because fire is expected to increase significantly in a warmer climate (Chapter 

8). Establishment of trees in burned areas can be delayed for 

decades or even centuries (Little et al. 1994), as both mycorrhizae and trees revegetate the area (Schowalter et al. 1997).

Migrating to a new site has historically been the main 

response of plants to climate change (Huntley 1991), requiring that species have the ecological ability to quickly occupy 

available sites and the genetic capacity to survive and reproduce successfully (Davis et al. 2005). Most tree species in 

the IAP region are long lived and genetically diverse, so they 

can survive wide fluctuations of weather, but the interaction 

of increasing drought and modified disturbance regimes will 

play a role in the future distribution and abundance of forest 

species (Allen et al. 2010) (Chapter 8).

A warmer climate is expected to facilitate upward shifts 

in the elevation distribution of plant species. For example, 

Lenoir et al. (2008) found that some plant species have 

moved upward in elevation at a rate of 100 feet per decade, 

but it is unclear whether such shifts will drive long-term 

changes in forest communities. For example, wildfire plays a 

dominant role in most ecosystems in western North America, 

and increasing wildfire frequency and extent may overwhelm 

potential shifts in forest species distribution. The potential 

for tree populations to migrate may vary among diverse 

mountain ranges, depending on local biophysical conditions.

Chapter 6: Effects of Climate Change on Forest Vegetation
120 USDA Forest Service RMRS-GTR-375. 2018

Box 6.3—How Do Climate Change Vulnerability Assessments and Adaptation Inform Ecological 

Restoration?

In an ideal sense, ecological restoration is defined as the practice of reestablishing historical plant and animal 

communities in a given area and the renewal of ecosystem and cultural functions necessary to maintain these 

communities now and into the future (Egan and Howell 2001). However, this ideal may be difficult to manage 

because: (1) little is known about historic conditions, (2) many key species may already be lost, (3) some efforts 

may be prohibitively expensive, and (4) future climates will create novel ecosystems. As a result, The Society for 

Ecological Restoration has opted for a definition that states that ecological restoration is “the process of renewing 

and maintaining ecosystem health.”

The U.S. Forest Service manual direction (FSM 2020) includes objectives and a policy for restoration:

•	 Restore and maintain ecosystems that have been damaged, degraded, or destroyed by reestablishing the 

composition, structure, pattern, and ecological processes.

•	 Manage for resilient ecosystems that have a greater capacity to withstand stressors, absorb and recover from 

disturbances, and reorganize and renew themselves, especially under changing and uncertain environmental 

conditions.

•	 Achieve long-term ecological sustainability and provide a broad range of ecosystem services to society.

The Forest Service emphasizes ecosystem restoration across all National Forest System lands with the goal of 

attaining resilient ecosystems. All strategic plans, including the Forest Service Strategic Plan and land management 

plans, must include goals and objectives to sustain the resilience and adaptive capacity of aquatic and terrestrial 

ecosystems by reestablishing, maintaining, or modifying their composition, structure, function, and connectivity. 

The goals and objectives must be established within this framework as defined by laws, Indian treaties and Tribal 

values and desires, and regulations. The goals and objectives must also consider public values and desires, social 

concerns, economic sustainability, the historical range of variability, ecological integrity, current and likely future 

ecological capabilities, a range of climate and other environmental change projections, the best available scientific 

information, and technical and economic feasibility to achieve desired conditions for National Forest System lands. 

A primary element of an integrated approach is to identify and eliminate or reduce stressors that degrade or 

impair ecosystems. Restoration activities should also take into account social and ecological influences at multiple 

scales and incorporate the concept of a dynamic system and ecological trajectory. Some ecosystems may have been 

altered to such an extent that reestablishing components of the historical range of variability may not be ecologically 

or economically possible. Therefore, goals and activities can focus on restoring the underlying processes that create 

functioning ecosystems. 

Functional restoration, an alternative concept used in the Forest Service, is defined as the “restoration of abiotic 

and biotic processes in degraded ecosystems.” Functional restoration focuses on underlying processes that may 

be degraded, regardless of the structural condition of the ecosystem. As contrasted with ecological restoration 

that tends to seek a historical reference condition, functional restoration focuses on dynamic processes that drive 

structural and compositional patterns. Functional restoration aims to restore functions and improve structures with 

a long-term goal of restoring interactions between function and structure. However, a functionally restored system 

may look quite different than the historical reference condition in terms of structure and composition. In this case, 

disparities cannot be easily resolved, because a threshold of degradation has been crossed, or environmental drivers 

(e.g., climate) that influenced structural and compositional development have changed.

Reproduction

Cone and seed crops of some tree species could be affected by climate change (Ibáñez et al. 2007; LaDeau and 

Clark 2001). Low-elevation, xeric forests may have fewer 

and smaller cone crops because of increased stand density 

and water stress. Cone crops may also have a lower percentage of viable seed because of increased stress. Infrequent 

cone crops coupled with low seed production may cause 

reduced regeneration in recently burned areas, in some 

cases resulting in dominance of nonforest vegetation. The 

opposite may be true in higher, colder environments, where 

increased temperatures will increase growing season length 

and thereby increase potential for more cone crops with 

more seeds. Spruce-fir communities may produce so much 

seed that they overwhelm regeneration of other conifers, 

especially after mixed-severity fires. Species such as whitebark pine (Pinus albicaulis) and lodgepole pine have unique 

cone characteristics; whitebark pine cones require birds for 

seed dispersal, and lodgepole pine cones may be serotinous 

and opened only by fire.

Growth and Mortality

Climate adversely affects growth and mortality through 

decreased water availability, resulting in shorter effective 

growing seasons (Bugmann and Cramer 1998; Chmura et 

al. 2011; Keane et al. 2001; Williams et al. 2010). Extended 

droughts require conifers to close stomata longer to conserve water. Ponderosa pine and limber pine (Pinus flexilis) 

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 121

have excellent stomatal control, and stomata can remain 

closed for long periods of time; Douglas-fir (Pseudotsuga 

menziesii) has poor stomatal control, which can drive leaf 

water potentials to low values and contribute to physiological damage (Sala et al. 2005). If photosynthetic production 

cannot exceed respiration demands, then plants become 

stressed.

If physiological damage is high enough, carbon storage 

in plant cells may decline as a result of stomatal closure 

and insufficient carbon assimilation to meet demands for 

tissue maintenance. In addition, lack of water for uptake, 

especially while stomata are open, can greatly reduce hydraulic conductance (McDowell et al. 2008; Sevanto et al. 

2014). Both of these physiological responses to low water 

supply, which typically occur during prolonged drought, 

can substantially reduce vigor, making weakened trees more 

susceptible to other stresses. In the most extreme cases, the 

ultimate outcome is tree mortality, often facilitated by bark 

beetles or other insects.

In mesic ecosystems in the IAP region, a warmer climate 

may enhance growth and decrease mortality (Wu et al. 

2011). Earlier growing seasons with ample moisture, as projected for some forests, may promote increased productivity. 

This will be especially true at higher elevations where cold 

temperatures, not moisture, limit tree growth. Increased 

biomass will also amplify competition between species, 

thereby favoring shade-tolerant individuals in the absence of 

disturbance. Increased biomass could also reduce resistance 

to forest insect and diseases (Chapter 8).

Regeneration

Microsite conditions required for successful establishment of tree species are typically rare, so seed germination 

and survival, especially for seeds that are wind dispersed, 

are rarely successful (Anderson and Winterton 1996). 

Suitable moisture conditions must persist for long periods 

of time for seed germination and early seedling growth. In 

dry forests, most of the successful regeneration occurs in 

years when soils are moist for an adequate time and heating 

at the soil level does not kill developing leaves and stems. 

A warmer climate may decrease the frequency of highregeneration years, and regeneration may become rare on 

the driest sites. In contrast, regeneration may be enhanced 

by warming at high elevation because earlier snowmelt will 

provide more time for seedlings to survive and grow (Butler 

1986).

During mild winters, seed chilling requirements may not 

be met for some species, thereby reducing germination. In 

addition, germination may be delayed to drier times during the growing season. For example, Nitschke and Innes 

(2008) found that in a warmer climate, chilling requirements 

were not met for most low-elevation tree species in British 

Columbia. High soil temperatures can stress both germinants and established seedlings (Rochefort et al. 1994). 

Climate change may also affect the dispersal properties of 

seeds. For example, rodent and bird species that disperse 

seeds may shift habitats because of climate-mediated 

changes (Tomback 1998). Longer and drier summers and 

autumns suggest that seed dispersal may occur when the 

ground and litter are dry and unsuitable for seed germination 

and establishment (Neilson et al. 2005).

Genetics and Species Adaptation

Climate affects plant phenotypes and is an agent of natural selection. Plant adaptations to local environments have 

often developed a clinal (or continuous) response to abiotic 

and biotic factors. In addition, ecotypic (or discontinuous) 

response to environmental gradients may play an important 

role, depending on local soils and topography. Therefore, a 

combination of clinal and ecotypic environmental gradients 

determines long-term plant survival and persistence across 

the landscape.

Natural selection, migration, genetic drift, and mating 

system determine species genetic composition. Thus, the 

ability of plant populations to respond to climate change 

is influenced by underlying patterns of genetic variation. 

Molecular markers can reveal significant genetic diversity 

and divergence among populations. Populations may 

diverge because of fire, volcanic activity (Hansen 1949), 

glaciation (Hamrick 2004), seed dispersal agents (Lorenz 

and Sullivan 2009), and pollinator history. Plants that are 

pollinated by insects or rely on animals to disperse seed are 

more vulnerable to climate change than plants with winddispersed seed, because of the requirement for interaction 

with another organism.

Genetic diversity allows species to adapt to changing 

environments, colonize new areas, occupy new ecological niches, and produce substantial and robust progeny 

that persist in the long term (Ledig and Kitzmiller 1992). 

Populations within a species adapt to environmental change 

over time. Species and populations of plants most vulnerable to climate change are typically (1) rare species or genetic 

specialists, (2) species with limited phenotypic plasticity, 

(3) species or populations with low genetic variation, (4) 

populations with low dispersal or colonization potential, (5) 

populations at the trailing edge of a species range, (6) populations at the lower-elevation limit of their distribution, and 

(7) populations threatened by habitat loss, fire, insects, or 

disease (Spittlehouse and Stewart 2003; St. Clair and Howe 

2011). The ability of a species to respond to environmental 

change is closely tied to its adaptive strategy (e.g., specialist 

or generalist) (table 6.3), mechanisms that shape its genetic 

structure, and the rate of environmental change.

Fragmentation is a critical issue for plant populations 

because isolation and small populations promote inbreeding 

and loss of genetic diversity (Broadhurst et al. 2008; Potter 

et al. 2015). Gene flow from adjacent populations can increase the rate of adaptation by introducing genetic variation 

that is preadapted to warmer or drier climates (Aitken et al. 

2008). This knowledge allows resource managers to select 

an appropriate population or seed source to increase the 

likelihood of desired revegetation or restoration (box 6.4).

Chapter 6: Effects of Climate Change on Forest Vegetation
122 USDA Forest Service RMRS-GTR-375. 2018

Table 6.3—Summary of attributes characterizing plant species’ adaptive strategies.a

Adaptive strategy

Attributes Specialist Generalist

Factor controlling phenotypic expression of adaptive 

traits

Genotype Environment

Mechanisms for accommodating environmental 

heterogeneity

Genetic variation Phenotypic plasticity

Range of environments where physiological processes 

function optimally

Small Large

Slope of clines for adaptive traits Steep Flat

Partitioning of genetic variation in adaptive traits Mostly among populations Mostly within populations

a

Modified from Rehfeldt (1994).

Box 6.4—Using Historical Range and Variability to Assess and Adapt to Climate Change

To effectively implement ecosystem-based management, land managers often find it necessary to obtain a reference, 

or benchmark, to represent the conditions that describe fully functional ecosystems (Cissel et al. 1994; Laughlin et al. 

2004). Contemporary conditions can be evaluated against this reference to determine status, trend, and magnitude 

of change, and to design treatments that provide society with valuable ecosystem services while returning declining 

ecosystems to a more sustainable condition (Hessburg et al. 1999; Swetnam et al. 1999). Reference conditions are 

assumed to represent the dynamic character of ecosystems and landscapes, varying across time and space (Swanson et 

al. 1994; Watt 1947). 

The concept of historical range and variability (HRV) was introduced in the 1990s to describe past spatial and 

temporal variability of ecosystems (Landres et al. 1999), providing a spatial and temporal foundation for planning and 

management. HRV has sometimes been equated with “target” conditions (Harrod et al. 1999), although targets can be 

subjective and somewhat arbitrary, representing only one possible situation from a range of potential conditions (Keane 

et al. 2009). HRV encompasses a full range of conditions that have occurred across multiple spatial and temporal scales. 

HRV represents a broad historical envelope of possible ecosystem conditions—burned area, vegetation cover type 

area, patch size distribution—that can provide a time series of reference conditions. This assumes that:

• Ecosystems are dynamic, not static, and their responses to changing processes are represented by past variability

• Ecosystems are complex and have a range of conditions within which they are self-sustaining, and beyond this 

range they transition to disequilibrium (Egan and Howell 2001)

• Historical conditions can serve as a proxy for ecosystem health

• Time and space domains that define HRV are sufficient to quantify observed variation

• Ecological characteristics being assessed for an ecosystem or landscapes match the management objective (Keane 

et al. 2009). 

The use of HRV has been challenged because a warmer climate may permanently alter the environment of 

ecosystems beyond what was observed under historical conditions (Millar et al. 2007a), particularly altered disturbance 

processes, shifts in plant species distribution, and hydrologic dynamics (Notaro et al. 2007). However, a critical 

evaluation of possible alternatives suggests that HRV is still a viable approach in the near term because it has relatively 

low uncertainty. 

An alternative to HRV is projecting future landscape characteristics in a changing climate using complex empirical 

and mechanistic models. However, the range of projections for future climate from commonly used GCMs is quite 

broad (Chapter 3; Stainforth et al. 2005). Additional uncertainty accrues from unknown technological advances, 

behavioral adaptations, and human population growth (Schneider et al. 2007). Moreover, variability of climate extremes, 

not the gradual change of average climate, will drive most ecosystem response to climate-mediated disturbance and 

plant dynamics (Smith 2011). Despite these uncertainties, it will be useful to quantify future range and variability (FRV) 

for landscapes where it is feasible and appropriate (Araujo et al. 2005; Keane et al. 2009). 

Given cumulative uncertainties, time series of HRV may have lower uncertainty than simulated projections of future 

conditions, especially because large variations in past climates are already captured in the time series. It may be prudent 

to wait until simulation technology has improved enough to create credible FRV landscape pattern and composition. 

In the meantime, attaining HRV would be a significant improvement in the functionality of most ecosystems in the IAP 

region, and would be unlikely to result in negative outcomes from a management perspective. As with any approach to 

reference conditions, HRV is useful as a guide, not a target, for restoration and other management activities.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 123

Some species may not be able to migrate quickly 

enough to keep pace with projected rates of climate 

change (30–300 feet per year) (Davis 1989; Malcolm et al. 

2002). Slow rates of migration may be further impeded by 

landscape fragmentation (Davis and Shaw 2001; Davis et 

al. 2005). Therefore, adaptation may be a more important 

response to climate change than migration. Some authors 

suggest that long-lived species with high levels of genetic variation can respond favorably to climate change 

(Hamrick 2004; Hamrick et al. 1992). However, others 

dispute the ability of forest trees to adapt or migrate and 

suggest trees may be restricted by their long lifespans, 

generation intervals, and juvenile phases (Etterson and 

Shaw 2001; Jump and Peñuelas 2005; Parmesan 2006). 

Because plant populations are genetically adapted to local 

climates, the climatic tolerance of individual populations 

will be critical.

Adaptive strategies for conifers in the IAP region are 

well documented (Rehfeldt 1994). Differences in adaptive 

strategy can be characterized by varietal modifications 

(e.g., Pinus ponderosa var. ponderosa versus var. scopulorum), different elevations, and variable geography. For 

example, P. ponderosa var. ponderosa is characterized as 

having an intermediate (neither generalist nor specialist) 

adaptive strategy, but at high elevation it has a specialist 

strategy (genetic variation is organized into numerous local 

populations, finely tuned to site-specific gradients). Rocky 

Mountain Douglas-fir (Pseudotsuga menziesii var. glauca) 

is characterized as having a specialist adaptive strategy, 

but at high elevation it has a generalist adaptive strategy 

(genetic variation is organized into one or a few populations capable of surviving, growing, and reproducing 

over a broad range of environments) (Rehfeldt 1989). A 

generalist adaptive strategy is considered more beneficial 

for responding to climate change (table 6.3).

Patterns of adaptive variation in other native plants 

(shrubs, forbs, grasses, sedges) are both clinal and ecotypic. These patterns involve multiple life forms (annual, 

biennials, perennials) and different ploidy levels (multiple 

copies of DNA, such as 4X, 6X, or 8X), where 2X is the 

base level, in which one copy of DNA is inherited on 

both the maternal and paternal sides. Grasses are largely 

generalists and less vulnerable to climate change, although 

ecotypic variation can overlie the generalist adaptive strategy. Forbs, which are mostly insect pollinated and coupled 

with longer growing seasons and changes in phenology, 

are considered more vulnerable to climate change than 

trees and grasses.

Stressors: Biotic and Abiotic 

Disturbances

A warming climate will rarely be the direct agent of 

change for tree species and communities. Most changes in 

vegetation will occur in response to disturbance or some 

combination of other stressors to climate change (Keane 

et al. 2015a; McKenzie et al. 2009; Peterson et al. 2014a, 

b). The biggest changes across the IAP region are likely 

to be altered water balance and increasing disturbances 

such as wildfire, insects, and nonnative species (Chapter 

8). Disturbances in combination with other stressors (e.g., 

drought) will create disturbance regimes in which multiple 

factors interact to modify ecosystem structure and function 

(Iverson and McKenzie 2013; McKenzie et al. 2009).

Wildfire is pervasive throughout forest ecosystems in 

western North America and was historically a dominant 

landscape disturbance agent in the IAP region. Fire exclusion since the 1920s has disrupted annual occurrence, 

spatial extent, and cumulative area of wildfires, resulting 

in increased surface fuel loads, tree densities, and ladder 

fuels, especially in low-elevation, dry conifer forests. 

Wildfire regimes, defined by fire frequency, annual area 

burned, severity, and pattern, are greatly influenced 

by variability in landscape environmental conditions 

including vegetation distribution, climate, weather, and 

topography (McKenzie et al. 2011). Regionally, years with 

high area burned are correlated with drought, so if drought 

increases as expected, area burned is expected to increase 

significantly (McKenzie et al. 2004; Peterson et al. 2014a).

Fire history determines composition and structure of 

most forests in the IAP region. At the lowest and driest elevations, frequent surface fires historically consumed litter 

and dead wood and killed seedlings and smaller trees. Fuel 

accumulations over several decades indicate that future 

fires may be larger and more intense and may cause higher 

rates of tree mortality than historical fire (box 6.3). Fire 

exclusion has not affected fire regimes as much where fires 

were historically infrequent because of relatively cool, 

wet conditions (e.g., high elevation) (Romme and Despain 

1989; Schoennagel et al. 2004). However, earlier onset 

of snowmelt, predicted to occur with changing regional 

climate, will reduce fuel moisture, making these systems 

flammable for longer periods of time and potentially leading to increased area burned (Miller et al. 2009).

Fire exclusion has resulted in increased tree regeneration and denser forest canopies, coupled with accumulation 

of understory and canopy fuels in dry forests (Ferry et al. 

1995; Keane et al. 2002) (fig. 6.1). These conditions create 

competition for water, light, and nutrients, making trees in 

fire-excluded forests susceptible to mortality from biotic 

and abiotic stressors, such as insects (Anderegg et al. 

2012; Wikars and Schimmel 2001), drought (Allen et al. 

2010), and fire (Hood et al. 2007).

Native insects and diseases naturally occur throughout 

forest cover types of the IAP region (Chapter 8). The level 

of insect and disease activity fluctuates with the availability of host material, stand conditions, environmental 

factors, and abundance of parasites and predators. These 

agents typically occur at endemic levels within forest ecosystems and affect mature and weakened trees.

Climate and forest composition and structure influence insect activity and outbreaks. Mountain pine beetle 

(Dendroctonus ponderosae) is an integral component of 

forest ecosystem processes because of its role in stand 

Chapter 6: Effects of Climate Change on Forest Vegetation
124 USDA Forest Service RMRS-GTR-375. 2018

thinning and redistribution of resources and nutrients. It 

is responsible for tree mortality across large areas (Logan 

et al. 2003), causing significant ecological and economic 

impacts. Many bark beetle life history traits that influence 

population success are temperature dependent (Bentz 

and Jӧnsson 2015); warming temperatures have directly 

increased bark beetle-caused tree mortality in some areas 

of western North America (Safranyik et al. 2010; Weed 

et al. 2015) (fig. 6.2). Temperature increases will affect 

tree distribution and tree vigor (Chapman et al. 2012; Hart 

et al. 2013). Therefore, future bark beetle-caused tree 

mortality will depend not only on the spatial distribution of 

live host trees and heterogeneity of future landscapes but 

also on the ability of beetle populations to adapt to changing conditions.

Fungal diseases, dwarf mistletoes (Arceuthobium spp.), 

root diseases, needle casts and blights, and abiotic diseases 

affect forest ecosystems, although the effects of climate 

change on forest diseases are difficult to project. The 

effects of climate change on root disease contribute significantly to mortality and loss of tree vigor, although little 

is known about climate-disease relationships. Climatemediated changes to forest tree diseases will be dictated by 

Figure 6.1—Area where fire 

has been excluded for many 

decades. Dense stands of 

ponderosa pine and other 

species create fuel ladders 

that can facilitate crown 

fires (photo: U.S. Forest 

Service).

Figure 6.2—Stand containing 

lodgepole pine killed by 

mountain pine beetle. This 

insect has killed lodgepole 

pine across large areas of 

western North America, 

including the Intermountain 

Adaptation Partnership 

region, during the past 20 

years. Chronic damage from 

the beetle may become 

more common in a warmer 

climate (photo: U.S. Forest 

Service).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 125

disease and host tree responses to new climates and their 

interactions (Sturrock et al. 2010). Interactions among biotic diseases, abiotic stressors, and host species will drive 

future pathogen outbreaks.

Soil characteristics, aspect, elevation, and forest stand 

structure contribute to effective moisture availability for 

tree establishment and growth, helping to shape spatial 

patterns of forests. Global climate models (GCMs) indicate 

that the IAP region will have longer, warmer summers 

(Chapter 3). Seral species such as ponderosa pine, which 

can establish on bare soil where high surface temperatures 

(up to 150 °F) exclude other species, have deep roots that 

can reach water and avoid competition with shallow-rooted 

species. In the absence of disturbance, shade-tolerant tree 

species can establish and grow in the understory, allowing 

them to take up water from the nutrient-rich soil surface. 

Leaf surface area increases over time, with leaf areas in 

excess of 6 square feet per square foot of soil surface area 

in some forests. Transpiration also increases over time, 

with the potential to deplete soil water needed to keep trees 

hydrated throughout the summer.

Climate Change Assessment 

for Tree Species

Here we assess vulnerability for tree species, vegetation 

types, and resources of concern in the IAP region, based on 

(1) ecological characteristics, (2) disturbance interactions, 

(3) current and historical conditions, and (4) potential 

climate change responses (table 6.4). Most of the material in this section was derived from published literature, 

although observational information is included for context. 

Scientific literature on climate change effects is limited for 

some species and forest types, making it necessary in some 

cases to augment the literature with expert knowledge to 

develop inferences.

Tree Species

Tree species in the IAP region will respond to climate 

change through modification, contraction, and expansion. 

First, a species could increase or decrease in productivity in situ within its current range because of increasing 

temperatures and adequate precipitation (modification, 

or acclimatization). Second, a species may diminish or be 

extirpated, if conditions change enough to become inhospitable to that species (Allen et al. 2010) (contraction). 

Finally, a species could migrate to areas that are more 

conducive to establishment and growth (Johnstone and 

Chapin 2003) (expansion). Any species can have multiple 

modes of response to climate change, and most species 

will respond to future climates via all three modes.

Application of these three modes to determine future 

species dynamics requires integration of variability and 

scale. For example, assessment of species migration 

requires a long temporal scope to evaluate species range 

shifts (Prentice et al. 1991). A tree species could become 

Table 6.4—Categories used to assess vulnerability of species and vegetation types.

Evaluation category Description Example

Habitat, ecosystem function, or 

species

Specific biophysical or social entity of interest Whitebark pine

Broad-scale climate change effect Overarching change in climate that is expected 

to affect a resource

Warming temperatures

Current condition, existing stressors Current status of resource relative to desired 

conditions, including factors that are reducing 

the quality or quantity of the resource

Reduced abundance, wildfire, 

mountain pine beetle, white pine 

blister rust

Sensitivity to climatic variability and 

change

Specific sensitivity of a habitat, species, or 

ecosystem function that responds to climate 

Low ability to compete with 

encroaching conifers

Expected effects of climate change How specific habitat, species, or ecosystem 

function is expected to respond to climate 

change (develop inferences from model 

projections and known responses to climatic 

variability)

Regeneration may be reduced by 

combination of warming and low 

seed availability

Adaptive capacity Ability to adjust to climate change, to moderate 

potential damages, or to cope with the 

consequences; usually more appropriate for 

species than for systems and processes

Variable: unable to compete 

with other tree species, but birdmediated seed dispersal allows 

rapid colonization of burned 

areas

Exposure The extent to which each species’ physical 

environment will change 

High

Chapter 6: Effects of Climate Change on Forest Vegetation
126 USDA Forest Service RMRS-GTR-375. 2018

established in a “new” environment made suitable by 

climate change, such as subalpine tree expansion, but variability in climate may prevent long-term establishment. In 

addition, shifts in species distribution and abundance will 

be governed primarily by disturbance, not competition, 

so disturbance adaptations will be more important than 

climatic niches.

Most of the information on vulnerability of tree species 

to climate change was derived from recent summaries 

on projected climate change effects (Bollenbacher 2012; 

Devine et al. 2012; Keane et al. 2015a) and older literature 

on autecology and silviculture (Burns and Honkala 1990; 

Minore 1979). The following summaries integrate genetic, 

morphological, ecological, and disturbance characteristics 

to project how a tree species will respond to a warmer 

climate.

In general, the literature is inconsistent on the response 

of tree species to climate change. Results from SDMs 

often differ from other sources that include gap modeling, 

mechanistic ecosystem simulation, and field data summaries. As a result, we do not emphasize SDM results 

in assessment evaluations. Most climate change studies 

project few species changes after moderate warming (e.g., 

B1, B2, A1B, RCP 4.5 scenarios) but major species shifts 

under the most extreme emissions scenarios (e.g., A1, RCP 

8.5). Timeframe also affects inferences about vulnerability. 

Management timeframes of 10 to 50 years are not long 

enough to effectively evaluate changes in wildfire, native 

insects, and tree growth because ecosystem response to 

disturbance may require two to five times the disturbance 

return interval. Finally, projections by GCMs vary, so 

the magnitude and rate of climate change, especially by 

the end of the 21st century, are uncertain (but are always 

considerably warmer). We have confidence in these 

projections at broad spatial scales, but less confidence for 

specific locations.

Douglas-fir (Pseudotsuga menziesii)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

Autecology

Douglas-fir (fig. 6.3) is found throughout the IAP region, 

growing in pure and mixed conifer stands (Hermann and 

Lavender 1990), often associated with ponderosa pine, 

Jeffrey pine (Pinus jeffreyi), grand fir (Abies grandis), 

subalpine fir, and quaking aspen (Populus tremuloides). 

Regeneration is most successful where Douglas-fir is seral 

(Ryker and Losensky 1983), and seedling growth is strongly 

limited by moisture and competing vegetation. Douglas-fir 

is intermediate in shade tolerance, tolerating drought better than most competitors (except for ponderosa pine and 

Jeffrey pine) by keeping stomata open to extract soil water 

at low soil water potentials (Sala et al. 2005; Stout and Sala 

2003). The species exhibits high genetic differentiation, 

which is strongly associated with geographic or topographic 

features (Rehfeldt 1978). Seed sources on south aspects 

have adaptive characteristics for a shorter growing season 

and drier soils and may survive under drought stress better 

than seedlings from north aspects.

Disturbance Interactions

Mature Douglas-fir is resistant to fire injury because 

of its thick bark, deep main roots, and high crowns (Ryan 

and Reinhardt 1988). Ponderosa pine and western larch 

can survive fire across all life stages, so on sites with 

frequent fires where Douglas-fir is associated with these 

other species, its cover is usually kept low by fire (Agee 

1991). Douglas-fir is subject to damage from a variety of 

agents that may increase under future climates (Hermann 

and Lavender 1990), including Douglas-fir beetle 

Figure 6.3—Douglas-fir. 

Growth of Douglas-fir 

in the Intermountain 

Adaptation Partnership 

region is expected to 

decrease in a warmer 

climate (photo: C. 

Restaino, used with 

permission).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 127

(Dendroctonus pseudotsugae), western spruce budworm 

(Choristoneura occidentalis), and Douglas-fir tussock 

moth (Orgyia pseudotsugata). The latter two insects attack 

trees of all ages at periodic outbreak intervals, often resulting in severe defoliation during outbreak years. Armillaria 

(Armillaria solidipes) and annosus (Heterobasidion annosum) root diseases may intensify in infection and widen 

in distribution to cause high tree mortality. Annosus root 

disease is particularly lethal in Douglas-fir (Hagle 2003). 

Of the many heart rot fungi (more than 300) attacking 

Douglas-fir, the most damaging and widespread is red ring 

rot (Porodaedalea pini).

Historical and Current Conditions

Historical frequent wildfire kept Douglas-fir from 

becoming established on some dry sites where it was associated with ponderosa pine. The cumulative effects of fire 

exclusion and logging have allowed Douglas-fir to become 

more dominant across some portions of the IAP region, 

often with high stem densities in fire-excluded stands. This 

has created areas where both canopy and surface fuels 

are high (Keane et al. 2002), predisposing Douglas-fir 

forests to future crown fires. In addition, these dense stand 

conditions have contributed to decreased vigor, which 

makes species susceptible to western spruce budworm and 

Douglas-fir beetle outbreaks.

Climate Change Responses

Some studies suggest that Douglas-fir distribution will 

increase in a warmer climate (Morales et al. 2015) and that 

growth will increase (Soulé and Knapp 2013), although 

a recent study provides convincing evidence that growth 

will decrease throughout its range (Restaino et al. 2016). 

It is likely that multiple factors will contribute to reduced 

distribution and vigor of Douglas-fir forests in some locations. Increased heat loading following severe wildfires 

is expected to be more common in the future, and may 

reduce Douglas-fir regeneration at lower-elevation sites 

and on south aspects (Kemp 2015). Douglas-fir may also 

face increasing competition from ponderosa pine, which 

is more drought tolerant (Stout and Sala 2003), and it 

may not have the genetic potential to rapidly migrate to 

more conducive sites (Aitken et al. 2008). In addition, 

Douglas-fir could have less resistance to the native insects 

previously mentioned if it is chronically stressed by low 

soil moisture. Increased wildfires, coupled with adverse 

effects of fire exclusion, could reduce tree survival in the 

future and make trees more susceptible to Douglas-fir beetle (Hood and Bentz 2007; Hood et al. 2007). Klopfenstein 

et al. (2009) projected that the range of Armillaria root 

rot will remain constant in a warmer climate, and if areas 

where Douglas-fir is maladapted increase, susceptibility to 

root rot could also increase. With limited genetic diversity 

at low to middle elevations and a more generalist strategy 

at higher elevations (St. Clair and Howe 2007), Douglas-fir 

may retract from the driest portions of its range.

Grand Fir (Abies grandis)

(Middle Rockies subregion)

Autecology

Grand fir is found on a wide variety of sites, including 

stream bottoms, valleys, and mountain slopes in the Middle 

Rockies of the IAP region (Foiles et al. 1990), typically 

in association with other conifer species. Grand fir grows 

best on rich soils of valley bottoms but also grows well 

on shallow exposed soils of mountain ridges, if moisture 

is adequate (Antos and Shearer 1980). Grand fir is either 

an early- or late-seral species, depending on site moisture 

(Ferguson and Johnson 1996). On productive mesic sites, 

it grows rapidly to compete with other seral species in the 

overstory, but other conifer species can outcompete it. On 

drier sites, it is the most shade-tolerant species and can 

dominate the understory. Grand fir can also share dominance 

with subalpine fir, especially in narrow valley bottoms, 

where it can exert dominance in lower elevational zones 

(Antos and Shearer 1980). Grand fir has high shade tolerance but low drought tolerance. It forms associations with 

ectomycorrhizae and arbuscular mycorrhizae, which may 

allow it to outcompete some shade-tolerant conifers. It has 

low frost tolerance but can tolerate fluctuating water tables.

Disturbance Interactions

Grand fir is susceptible to fire damage in moist creek 

bottoms but is more resistant on dry hillsides where roots 

are deeper and bark is thicker (Ryan and Reinhardt 1988). 

Wildfires that burn grand fir stands are stand replacing or 

mixed severity, generating sufficient heat to kill even mature 

trees (Arno 1980; Arno et al. 2000). Grand fir is susceptible 

to Armillaria and annosus root diseases, which can cause 

high levels of tree mortality (Hagle et al. 2003). Numerous 

insects attack grand fir, including western spruce budworm 

and Douglas-fir tussock moth, which cause widespread 

defoliation, top kill, and mortality. The western balsam bark 

beetle (Dryocoetes confusus) and fir engraver (Scolytus

ventralis) are the principal bark beetles that attack grand fir 

(Foiles et al. 1990).

Historical and Current Conditions

Fire exclusion has increased grand fir on both dry and 

mesic sites, and higher tree densities have stressed grand 

fir, making it more susceptible to root rot and insect attacks. 

Therefore, the condition of most grand fir stands depends 

on the last severe fire; if fire exclusion has caused grand fir 

to dominate in both the overstory and understory, then these 

stands are usually stressed because of high densities and 

increased root rot and insects. However, in early-seral stands 

where high grand fir regeneration has not yet occurred, an 

increase in fir is likely with continued fire exclusion.

Chapter 6: Effects of Climate Change on Forest Vegetation
128 USDA Forest Service RMRS-GTR-375. 2018

Climate Change Responses

On dry sites, increased drought and longer growing seasons will exacerbate stress caused by competition, resulting in 

high mortality of grand fir, mainly from insects and disease. 

Nitschke and Innes (2008) used a gap model to project major 

declines in grand fir, and Coops and Waring (2011) used a 

mechanistic model to simulate a nearly 50 percent decrease 

in the range of grand fir compared to historical distributions. 

However, increased productivity may lead to increased grand 

fir populations in locations with higher soil moisture (Aston 

2010; Urban et al. 1993). As noted earlier, increased densities 

may also lead to increased stress. Longer fire seasons and 

high fuel loadings from fire exclusion will probably lead to 

large, severe fires that may reduce grand fir in drier locations. 

In summary, although grand fir is often stressed by high stem 

densities, the species is likely to tolerate changes in climate 

and remain on the landscape at levels that are closer to historical conditions rather than its current abundance.

Shasta Red Fir (Abies magnifica)

(Great Basin and Semi Desert subregion)

Autecology

Shasta red fir grows best in areas with cold, wet winters and warm, dry summers (Lanner 1983; Oosting and 

Billings 1943; Rundel et al. 1977). The growing season in 

these areas is short, with snow often on the ground in July 

(Barbour 1988; Barbour et al. 1991; Holland 1986; Mitchell 

and Moir 1976). Red fir can be found growing at lower 

elevations in canyons and other protected places where 

significant cold air drainage keeps soil and air temperatures 

low (Parker 1984). The species also occurs at high elevation 

on mountain ranges that continue in active formation, where 

it thrives on young, xeric soils. Red fir has a high frost 

tolerance and low drought tolerance. It is a late-seral species 

nearly everywhere it is found. Although red fir grows best 

in full sunlight, it can survive and grow for long periods in 

relatively dense shade.

Disturbance Interactions

Shasta red fir sustains moderate damage from lowseverity fires but is often killed by mixed-severity fires 

(Atzet and Wheeler 1982). Openings created in mixed 

red fir and white fir (Abies concolor) stands in the Sierra 

Nevada tend to regenerate more readily to red fir (Parker 

1986). Red fir is susceptible to windthrow after partial 

cutting, especially when marginal codominant and lower 

crown classes are left as the residual stand (Gordon 

1973). Root diseases such as annosus root rot contribute 

significantly to lack of wind firmness. Other diseases that 

reduce tree vigor include dwarf mistletoe and cytospora

(Cytospora spp.) canker, which, in turn, make trees susceptible to fir engraver attack.

Historical and Current Conditions

Native Americans used Shasta red fir forests for 

hunting mule deer (Odocoileus hemionus) and for other 

sources of food and materials during summer. Mining, 

logging, water diversions, railroad development, and 

sheep grazing altered some lower-elevation fir forests 

during the late 19th and early 20th centuries (Meyer 

n.d.). Burning was used to promote growth of grasses 

and forbs and to remove fuel and young trees from the 

understory (McKelvey and Johnston 1992), thus reducing 

fir regeneration. Starting in the 1950s, timber harvest and 

extensive road infrastructure began in portions of red fir 

forest, with silvicultural techniques that create even-aged 

stands being implemented (Potter 1998). By the 1990s, 

silvicultural practices emphasized shelterwood cutting and 

uneven-aged silvicultural systems (Laacke and Tappeiner 

1996). Despite this history of resource use, red fir is 

largely undisturbed in many higher-elevation and isolated 

locations.

Climate Change Responses

Shasta red fir is expected to sustain moderate effects 

from a warmer climate. If snowpack decreases as expected, a longer growing season may increase growth at 

higher elevations. Regeneration could also improve under 

these conditions. Lower-elevation populations may grow 

more slowly where soil moisture is limited in summer. 

Red fir is typically found in forests with mixed-severity 

fire regimes, so if wildfire becomes more frequent than 

historical records indicate, especially where fuel loadings 

are elevated, fire severity could cause crown fires with 

high mortality in younger trees (older trees have thick 

bark and high crowns). Increased fire could produce a 

more open forest structure over decades to centuries.

Subalpine Fir (Abies lasiocarpa)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

Autecology

Although widely distributed, subalpine fir grows 

within a narrow range of mean temperatures of 25 to 40 

°F, with average January temperatures of 5 to 25 °F. Cool 

summers, cold winters, and deep winter snowpack are 

more important than precipitation in determining where it 

grows. Subalpine fir ranges from lower valleys to the upper subalpine zone in the IAP region, typically mixed with 

other species, most notably Douglas-fir and Engelmann 

spruce. Subalpine fir is shade tolerant; partial shade 

usually favors seedling establishment and early survival 

(Knapp and Smith 1982). It is relatively intolerant of 

drought, and seedlings can be killed by lengthy droughts. 

It is a prolific seeder, often having large cone crops every 

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 129

2 to 3 years (Alexander et al. 1990), and although dense 

mats of seedlings can occur, they are also susceptible to 

many herbivores and pathogens.

Disturbance Interactions

Subalpine fir is highly susceptible to fire damage because of thin bark, shallow roots, and low, dense crowns 

(Ryan and Reinhardt 1988). Even low-intensity fire can 

cause mortality, and frequent fires can eliminate subalpine fir from both the overstory and understory, thereby 

maintaining more fire-adapted species such as lodgepole 

pine (Little et al. 1994; Murray et al. 1995; Wadleigh 

and Jenkins 1996). In spruce-fir forests, the most important insects are western spruce budworm and western 

balsam bark beetle (Drycoetes confusus). Fir broom rust 

(Melampsorella caryophyllacearum) and wood rotting 

fungi are responsible for most disease losses, but root and 

butt rots may be important locally. Decades of intense 

competition, coupled with a period of moderate to severe 

drought, can cause mortality in subalpine fir stands.

Historical and Current Conditions

Effects of fire exclusion have not yet become manifest 

in most subalpine fir ecosystems because of historically 

infrequent fire and slow successional advancement. 

However, abundance of subalpine fir has increased in 

some landscapes (Keane et al. 1994). These dense stands 

have become stressed from competitive interactions, 

resulting in susceptibility to disturbances and drought. 

If these stands continue to escape fire, the seed sources 

of co-located, fire-adapted species may be eliminated, 

and high-elevation sites could be converted to grass and 

shrublands (Keane 2001). In addition, if fire is excluded 

from these dense forests, fuels will accumulate, inevitably 

leading to high-severity fires (Keane 2001; Morgan et al. 

1994b). Recent USFS Forest Health Monitoring data in 

the IAP region indicate that dieback of subalpine fir is 

occurring in some locations, attributed to a complex of 

drought, insects, and pathogens.

Climate Change Responses

Because subalpine fir is adapted to moist growing 

conditions, it is likely to respond poorly to increasing 

temperatures and drought (Alexander et al. 1990; Brunelle 

et al. 2005; Whitlock and Bartlein 1993). However, it is 

a good competitor and may be able to expand its range at 

treeline (Little et al. 1994; Rochefort et al. 1994; Villalba 

et al. 1994) and increase growth in a longer growing season (Peterson et al. 2002). Seedling establishment may be 

the bottleneck for subalpine fir establishment in the future 

because the species needs long periods of high moisture 

for germination and seedling establishment (Urban et al. 

1993), and years that meet these conditions may be less 

frequent in the future. If stand densities increase, competitive stress will increase, making fir more vulnerable to 

insects, disease, and abiotic factors. If wildfire increases 

where subalpine fir is dominant, abundance would 

decrease from the direct effects of higher temperature. 

Subalpine fir is likely to shift across the high mountain 

landscape, with expansion balancing retraction, although 

fire, disease, and insects may limit abundance.

White Fir (Abies concolor var. concolor)

(Uintas and Wasatch Front, Plateaus, 

Great Basin and Semi Desert 

subregions)

Autecology

White fir is distributed throughout most of the American 

Southwest, from canyon bottoms and ravines up to 

ridgetops. It is a dominant, late-seral component of some 

habitat types in Utah and develops best on gentle slopes 

(Laacke 1990), although the rooting habit is adaptable to 

depth of the soil profile. It can survive for long periods as a 

suppressed tree in the understory, then respond with rapid 

growth if light becomes available. Within mixed conifer 

forests, white fir tends to achieve dominance on moist 

sites, especially if long fire return intervals provide the opportunity for it to mature to a point at which it is moderately 

fire tolerant. White fir is sensitive to frost damage (Laacke 

1990), and is susceptible to windthrow following partial 

cutting.

Disturbance Interactions

In mixed conifer forests with an intact low-severity fire 

regime, white fir rarely attains dominance because it is more 

fire sensitive than its associates (Agee 1982; Alexander et 

al. 1984). Thus, many white fir habitat types are in mid-seral 

stages, with various species dominating the overstory and 

white fir dominating the reproductive size classes. White fir 

mistletoe (Phoradendron bolleanum subsp. pauciflorum) 

and white fir dwarf mistletoe (Arceuthobium abietinum f. 

sp. concoloris) damage white fir, causing spike tops, loss 

of vigor, and increased susceptibility to bark beetles (Bega 

1978). White fir is susceptible to a number of decay fungi 

including annosus root disease, Armillaria root disease, 

laminated root rot (Phelllinus weirii), yellow cap fungus 

(Pholiota limonella), Indian paint fungus (Echinodontium 

tinctorium), and white pocket rot (Phellinus mini). Fir 

engraver beetle causes major losses throughout the range of 

white fir (Wilson and Tkacz 1996).

Historical and Current Conditions

White fir, which has historically been dominant on wetter 

sites and codominant in drier mixed conifer forests, has increased in abundance in areas where fire has been excluded. 

In some cases, the understory in fire-excluded stands is 

dense, and surface fuels are high, conditions conducive to a 

crown fire (Dahms and Geils 1997; McKelvey and Johnston 

1992). If dense stands escape fire, the seed sources of other 

fire-adapted species may be eliminated, and some sites may 

have increased dominance of grass and shrublands (Keane 

2001). White fir mortality following wildfire is often 

Chapter 6: Effects of Climate Change on Forest Vegetation
130 USDA Forest Service RMRS-GTR-375. 2018

100 percent, although associated species such as ponderosa 

pine and Douglas-fir often survive. White fir has never been 

a primary timber species, although it has been logged in 

some places. It was often left uncut where more valued species were removed, becoming the residual dominant.

Climate Change Responses

White fir has high shade tolerance but low drought 

tolerance, so low soil moisture will have the greatest effects in well-drained soils and on south aspects. Sudden 

temperature increases during May and June can cause 

damage nearly identical to that of spring frosts, which 

may be an issue for some fir populations. A modeling 

study in California suggested that effects of climate 

change on white fir will be moderate (Battles et al. 

2008), and although this may be true in the IAP region, 

wildfire will play a major role in its future distribution 

and abundance. White fir is typically found in forests 

with low-severity and sometimes mixed-severity fire regimes, so if fire becomes more frequent than historically, 

especially where fuel loadings are elevated, fire severity 

could cause crown fires with high mortality rates. Over 

decades to centuries, increased fire could produce a more 

open forest structure with fewer white fir in both the 

canopy and understory.

Rocky Mountain Juniper (Juniperus 

scopulorum)

(Uintas and Wasatch Front subregion)

Autecology

Rocky Mountain juniper grows in dry, sub-humid 

climates. It is a drought-enduring species with a shallow 

but fairly extensive lateral root system. Rocky Mountain 

juniper is normally a component of early-seral or near 

late-seral vegetation. It is relatively shade tolerant during the seedling and sapling stages, but it later becomes 

more intolerant and is unable to endure excessive shade. 

In Utah, junipers have been observed occupying sagebrush stands under certain conditions; twoneedle pinyon 

(Pinus edulis) generally follows and tends to replace 

juniper. Pinyon-juniper communities may encroach into 

grasslands that have been overgrazed or disturbed. Once 

established, Rocky Mountain juniper competes well with 

understory vegetation for water and nutrients.

Recent paleobotanical studies indicate the macroclimate covering much of the Rocky Mountain juniper 

range has changed from mesic to more xeric conditions. 

Juniper is generally less drought resistant than other 

juniper species, and high temperatures are not favorable 

for regeneration or growth. Rocky Mountain juniper 

was present in western Nebraska and the Laramie Basin 

of Wyoming as recently as 1,000 years BP, with some 

trees over 50 inches in diameter (Tauer et al. 1987; Van 

Devender 1987).

Disturbance Interactions

Rocky Mountain juniper is susceptible to loss from 

erosion simply because it is often established on exposed 

sites where soils are readily eroded. It is susceptible to 

death or injury from fire, primarily because the bark is 

thin, and the lower branches contain volatile oils and 

normally extend to the ground (Hepting 1971; Noble 

1990; Sieg 1997). Rocky Mountain juniper has a compact 

crown when young, and because it grows slowly, is 

susceptible to fire for the first 20 years or more (Crane 

1982; Fischer and Clayton 1983; Hansen and Hoffman 

1988; Mitchell 1984; Mueggler 1976; Stanton 1974). 

As trees mature, they develop thicker bark and a more 

open crown, allowing them to potentially survive surface 

fires. Large-diameter junipers have been documented to 

survive four to six fires.

Postfire reestablishment is solely by seed (Floyd et al. 

2000), and animal transport of seeds is an important factor (Paysen et al. 2000). Regeneration is often high after 

old trees burn (Stanton 1974; Wright 1972). Frequent 

fires in pinyon-juniper habitat can maintain a grassland 

setting, and the absence of fire will allow conversion to 

woodlands (Gruell 1986). After fire in pinyon-juniper, 

junipers usually establish first, followed by pinyon pine, 

which may eventually replace juniper on higher-elevation 

sites (Holland 1990). The nonnative annual cheatgrass 

(Bromus tectorum) has become increasingly common in 

the understory over the past few decades, providing abundant fine surface fuels and increasing the potential for 

more frequent wildfires (Shinneman and Baker 2009).

Historical and Current Conditions

Rocky Mountain juniper was a source of fuel (charcoal) 

for the mining industry between the 1860s and 1920s 

(Young and Budy 1979), and it has been used extensively 

for firewood, fence posts, and other needs, with local 

deforestation occurring in some locations. In some lowerelevation sites, juniper has been cut or removed from the 

landscape through chaining and herbicides to encourage 

the growth of grasses and forage for livestock grazing. 

Persistent woodlands of Rocky Mountain juniper, pinyon 

pine, or a mixture of both are found where local soils and 

climate are favorable, and wildfire has been infrequent 

(Romme et al. 2009). Pinyon-juniper savannas are found 

where local soils and climate are suitable for both trees 

and grasses, and low-severity fires have been relatively 

frequent. Wooded shrublands are found where local soils 

and climate support a shrub community, but trees have 

increased during moist climatic conditions and periods 

without wildfire. Large increases in juniper density have 

occurred in portions of all types of pinyon-juniper vegetation, which may have been driven by factors such as natural 

range expansion, livestock grazing since the 1880s (which 

reduced fuels and probably decreased fire frequency), fire 

exclusion, climatic variability, and carbon dioxide fertilization (Romme et al. 2009).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 131

Climate Change Responses

Rocky Mountain juniper is drought tolerant, and 

reduced soil moisture is not expected to have a significant 

effect on its abundance and distribution, although its 

growth and expansion into adjacent shrub-steppe systems 

could be slowed. The future of Rocky Mountain juniper 

will largely depend on spatial and temporal patterns 

of wildfire, which is expected to increase in frequency 

(Floyd et al. 2004). Junipers can generally survive lowseverity fire if they are at least 20 years old, so if fires 

occur more frequently than that, tree mortality will be 

high. After an initial fire, accumulation of surface fuels 

and tree regeneration could be slow because of moisture 

limitations, resulting in a sparse canopy and disconnected fuels (Rocca et al. 2014). The long-term condition 

of juniper is complicated by nonnative annual grasses, 

especially cheatgrass, which increases surface fuels and 

fire frequency.

Utah Juniper (Juniperus osteosperma)

(Plateaus, Great Basin and Semi Desert 

subregions)

Autecology

Utah juniper is a late-seral species in several pinyonjuniper, sagebrush (Artemisia spp.)-grassland, and shrubsteppe habitats. Utah juniper tolerates dry soils (Hickman 

1993; Lanner 1983; Meeuwig and Bassett 1983), commonly 

growing on alluvial fans and dry, rocky hillsides (Barney 

and Frischknecht 1974; Hitchcock and Cronquist 1973; 

Pieper 1977; Shantz and Piemeisel 1940) with shallow, 

alkaline soils (Bunderson et al. 1985). Utah juniper is shade 

intolerant (Meeuwig and Bassett 1983); it is a late-seral 

species in areas where stands are open and regeneration 

can occur without competition for light. Utah juniper has 

a taproot that extends deep into the soil, responding to low 

nutrient levels in the soil by developing extensive fine roots. 

Juniper competes more efficiently for soil moisture than do 

herbaceous understory plants, and is more likely to maintain 

a stable population as understory plants decrease (Austin 

1987; Everett et al. 1983; Springfield 1976).

Disturbance Interactions

Utah juniper is generally not fire tolerant, although trees 

more than 4 feet tall are capable of surviving low-intensity 

fires (Bradley et al. 1992; Springfield 1976). Cheatgrass has 

become increasingly common in the understory over the 

past few decades, continually providing abundant fine surface fuels on and increasing the potential for more frequent 

wildfires (Shinneman and Baker 2009).

Historical and Current Conditions

Utah juniper was a source of fuel (charcoal) for the 

mining industry between the 1860s and 1920s (Young and 

Budy 1979), and has been used extensively for firewood, 

fence posts, and other needs, with local deforestation in 

some locations. In some lower-elevation locations, juniper 

has been removed from the landscape through chaining 

and herbicides to encourage growth of grasses and forage 

for livestock grazing. Persistent woodlands of juniper or 

pinyon pines, or a mixture of both, are found where local 

soils and climate are favorable, and wildfire has been infrequent (Romme et al. 2009). Pinyon-juniper savannas are 

found where local soils and climate are suitable for both 

trees and grasses, and low-intensity fires are relatively 

frequent. Wooded shrublands are found where local soils 

and climate support a shrub community, but trees have 

increased during moist climatic conditions and periods 

without wildfire. Large increases in juniper density have 

occurred in portions of all types of pinyon-juniper vegetation, which may have been driven by factors such as natural 

range expansion, livestock grazing (since the 1880s, which 

reduced fuels and probably decreased fire frequency), fire 

exclusion, climatic variability, and carbon dioxide fertilization (Romme et al. 2009).

Climate Change Responses

Utah juniper is drought tolerant, and reduced soil 

moisture is not expected to have a significant effect on its 

abundance and distribution, although growth may decline 

even as it spreads into adjacent shrub-steppe systems. The 

future of Utah juniper will largely depend on spatial and 

temporal patterns of wildfire, which is expected to increase 

in frequency (Floyd et al. 2004). Junipers can generally survive fire only if they are tall enough for the crown to escape 

flames. Following an initial fire, accumulation of surface 

fuels and tree regeneration will probably be slow because 

of moisture limitations, resulting in a sparse canopy and 

disconnected fuels (Rocca et al. 2014). The long-term condition of juniper is complicated by nonnative annual grasses, 

especially cheatgrass, which increases surface fuels and fire 

frequency.

Western Larch (Larix laricina)

(Middle Rockies subregion)

Autecology

Western larch grows in relatively cool, moist forests in 

the Middle Rockies portion of the IAP region (Habeck 1990; 

Schmidt and Shearer 1990), typically associated with several 

other conifer species. It is often found in locations that have 

relatively high snowfall, and is rarely found in xeric sites 

(Gower et al. 1995). Cone and seed production is abundant 

when trees are older than 30 years, with good seed crops 

occurring every 10 to 14 years (Owens 2008). Seed germinates best on seedbeds exposed by burning or mechanical 

scarification (Antos and Shearer 1980; Beaufait et al. 1977; 

Schmidt 1969; Shearer 1976), and young seedlings grow fast 

on suitable sites, although drought reduces seedling survival 

(Schmidt and Shearer 1995). Shade intolerant, larch grows 

fast with tall, open crowns, allowing it to outcompete other 

Chapter 6: Effects of Climate Change on Forest Vegetation
132 USDA Forest Service RMRS-GTR-375. 2018

species on mesic sites (Milner 1992). It is moderately drought 

tolerant and can survive seasonal drought, but performs 

poorly when droughts last more than 2 years.

Disturbance Interactions

Western larch depends on open-canopy, high-light 

environments and mineral soil seedbeds created by fire for 

successful regeneration (Schmidt et al. 1976). It can survive 

intense fire because of thick bark (Ryan and Reinhardt 1988), 

high crowns, deep roots, and epicormic branch production 

(Fiedler and Lloyd 1995; Harrington 2012; Schmidt and 

Shearer 1995; Schmidt et al. 1976), often surviving crown 

fires that kill other species (Marcoux et al. 2015). Seeds are 

wind dispersed across large burns, and if mature lodgepole 

pine occurs with larch, regeneration may be dominated by 

both species (Hopkins et al. 2013).

Western dwarf mistletoe (Arceuthobium campylopodum) 

is a damaging, parasitic plant of larch (Schmidt and Shearer 

1990). It infects seedlings and persists throughout the life of 

the tree, causing reduced growth, water loss, and deformities. 

Cool, wet springs favor foliar diseases such as larch needle 

cast (Meria larisis), which, in turn, can reduce cone production. Larch needle blight (Hypodermella laricis), brown trunk 

rot (Fomitopsis officinalis), and red ring rot (Phellinus pini) 

are also important pathogens. Western spruce budworm and 

the nonnative larch casebearer (Coleophora laricella) are 

the two most serious insect pests (DeNitto 2013; Schmidt 

and Fellin 1973). Although neither insect causes substantial 

mortality, episodic outbreaks can cause severe defoliation and 

reduce growth and cone production (Schmidt et al. 1976).

Historical and Current Conditions

Western larch was formerly an important timber species, 

but extensive logging during the 20th century removed many 

of the large larches, reducing its dominance on the landscape 

(Arno 2010). Reduced seed sources for regeneration and fire 

exclusion have reduced burned mineral soil seedbeds where 

larch can regenerate. Continued fire exclusion has increased 

stand densities and increased surface fuel loads, which will 

make future fires more intense than they have been historically. Considerable effort is underway to increase the distribution 

and abundance of western larch in locations where it was 

previously more common.

Climate Change Responses

Western larch may be susceptible to a warmer climate 

because of its narrow geographic and elevation distribution 

and its uncertain association with wildfire. If fire increases, 

larch may have a colonization advantage, as long as fire 

mortality is moderate and mature trees remain to serve as 

seed sources. Without seed sources, regeneration may require 

assistance from management through planting. If fire exclusion continues, stand densities will increase and larch may be 

outcompeted by shade-tolerant competitors, making it more 

susceptible to insects and disease. When dense stands burn, 

crown fires may kill older, seed-producing trees (Hopkins 

et al. 2013). Keane et al. (1996) simulated major declines 

for western larch under fire exclusion and moderate climate 

change, but found it increased as more fire was allowed 

to burn over many decades. Larch can take advantage of 

changes in productivity in colder sites, as long as these areas 

burn with low intensity and larch survives the fires to provide 

seed for regeneration.

Great Basin Bristlecone Pine (Pinus 

longaeva) and Rocky Mountain 

Bristlecone Pine (P. aristata)

(Uintas and Wasatch Front, Plateaus, 

Great Basin and Semi Desert 

subregions)

Autecology

Great Basin bristlecone pine occurs in montane, subalpine, 

and treeline communities from 7,200 to 12,000 feet elevation 

(Hickman 1993; Lanner 1999), typically in multi-aged stands 

(Bradley et al. 1992). It grows in pure stands at treeline and in 

the upper subalpine zone, and is codominant with limber pine 

at lower elevations (Critchfield and Allenbaugh 1969; Vasek 

and Thorne 1977). Great Basin bristlecone pine is drought 

tolerant (Bare 1982; Tang et al. 1999), occurring in climates 

that are cold in winter and dry in summer. It establishes 

quickly in open mesic sites (Hawksworth and Bailey 1980), 

but competes poorly for water and nutrients, and is usually 

excluded from productive sites (Beasley and Klemmedson 

1973; Hiebert 1977).

Rocky Mountain bristlecone pine occurs from 8,200 to 

11,000 feet elevation (FNAA 2009) and is common on steep, 

dry, south- or west-facing slopes. It grows in cold, continental 

climates, with precipitation patterns influenced by summer 

monsoons bringing afternoon rain. Rocky Mountain bristlecone pine is commonly found on unproductive sites with 

nutrient-poor, acidic soils. This species often occurs in pure 

stands or mixed with limber pine.

Disturbance Interactions

As a thin-barked species (Zavarin and Snajberk 1973), 

Great Basin bristlecone pine is adapted to survive only 

low-intensity surface wildfires, although fire is infrequent at 

high-elevation sites (Bradley et al. 1992). White pine blister 

rust (Cronartium ribicola) is present in some stands, but it 

rarely has a significant effect on populations. Most highelevation pines eventually die from root rot decay or soil 

erosion, which exposes and kills roots (Lanner 1999). Small 

wildfires may kill a few trees.

Wildfires are common in Rocky Mountain bristlecone pine 

sites, but are usually small in extent and cause minimal damage because patchy stand structure and low fuel loadings limit 

fire spread (Crane 1982). Although fire is not a major disturbance factor, Rocky Mountain bristlecone pine is favored in 

early postfire succession because it is a shade-intolerant seral 

species (Baker 1992; Schoettle 2003). Blister rust has been 

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 133

recorded in this species only recently (Blodgett and Sullivan 

2004) and is rarely observed in the IAP region.

Historical and Current Conditions

Great Basin bristlecone pine and Rocky Mountain 

bristlecone pine are located at high elevation in relatively 

inaccessible locations. Because these species have no commercial value, they generally remain undisturbed by human 

activity and exist in intact subalpine forests and woodlands.

Climate Change Responses

Great Basin bristlecone pine and Rocky Mountain 

bristlecone pine are tolerant of cold temperatures and deep 

snowpack in winter, low soil moisture in summer, and high 

winds. Therefore, they are expected to be moderately vulnerable to climate change, with considerable variation among 

sites. A recent study showed that Great Basin bristlecone has 

a threshold at 60 to 250 vertical feet below treeline, above 

which trees have a positive growth response to temperature 

(Salzer et al. 2014). Growth chronologies from 250 feet 

or more below treeline had a change in climate response 

and did not correlate strongly with temperature-sensitive 

chronologies developed from trees growing at upper treeline. 

At the highest sites, trees on south-facing slopes grew faster 

than trees on north-facing slopes. High growth rates on the 

south aspect have declined since the mid–1990s, suggesting 

that temperature may no longer be as limiting to growth. 

Therefore, increasing warmth may lead to a divergence 

between growth and temperature at previously temperaturelimited sites. Neither species of bristlecone pine is expected to 

change in distribution and abundance significantly during the 

21st century. Increased wildfire could affect Rocky Mountain 

bristlecone pine in mixed-species stands with high surface 

fuels, but not in higher-elevation locations where trees are 

scattered and fuels are low.

Jeffrey Pine (Pinus jeffreyi)

(Great Basin and Semi Desert subregion)

Autecology

Jeffrey pine is shade intolerant and drought adapted, occupying low- to mid-elevation, dry forests (Minore 1979). It 

is both an early- and late-seral species, often associated with 

other conifer species on moist sites. Moisture typically limits 

growth, especially in summer, and distribution of Jeffrey pine 

on drier sites is limited by available soil moisture, which, in 

turn, is affected by soil texture and depth. Jeffrey pine tolerates dry soil conditions by efficiently closing stomata to avoid 

water loss and xylem cavitation (Sala et al. 2005), tolerating 

intense drought, and drawing groundwater at low soil water 

potentials. Jeffrey pine is associated with several species 

of ectomycorrhizae, giving it the capacity to survive in dry 

environments. Soil texture, plant competition, and seedbed 

conditions reduce seed germination and limit seedling survival and growth, although it can often germinate under moisture 

stress (Oliver and Ryker 1990).

Disturbance Interactions

Disturbance plays a major role in Jeffrey pine forests. The 

most damaging of the tree-killing insects are several species 

of Dendroctonus (Oliver and Ryker 1990), followed by ips 

beetles, all of which are native and present naturally in many 

stands. Dwarf mistletoe is widespread in Jeffrey pine stands 

but rarely fatal. Bark beetles can cause extensive mortality 

given availability of preferred host stand conditions. Jeffrey 

pine has a high capacity to survive fire (Minore 1979; Ryan 

and Reinhardt 1988), and wildfire favors the growth of large 

(thicker bark) Jeffrey pine by killing its primary competitors 

and small-diameter Jeffrey pines (Arno 1988; Steele et al. 

1986).

Historical and Current Conditions

Fire exclusion, mining, timber harvest, and livestock 

grazing have contributed to reductions in distribution and 

abundance of Jeffrey pine. Changes in fire regime have altered the composition and structure of many dry forests, with 

area burned by surface fires decreasing and crown fires increasing in many areas (Hann et al. 1997). Landscapes where 

fire has been excluded for many decades typically have high 

stand densities and surface fuel loadings, setting the stage for 

future crown fires.

Climate Change Responses

Jeffrey pine is expected to be relatively tolerant of increasing temperatures and longer droughts. This species has high 

phenotypic plasticity and is therefore adapted to drought, 

although regeneration may decrease if precipitation decreases 

or becomes more variable. Some studies project an increase 

in distribution for ponderosa pine in western North America 

(Hansen et al. 2001; Morales et al. 2015; Nitschke and Innes 

2008) that may be true for Jeffrey pine as well. Advancing 

competition resulting from fire exclusion, increased wildfire 

extent and intensity, and potential increases in mountain 

pine beetle, western pine beetle (Dendroctonus brevicomis), 

several Ips species, and western pine shoot borer (Eucosma 

sonomana) will dictate the future of Jeffrey pine. If fires are 

too frequent, established regeneration will not grow above the 

lethal scorch height. Increasing wildfire extent and severity 

(crown fires) could also eliminate the mature Jeffrey pine 

trees that provide seed sources for populating future burns.

Limber Pine (Pinus flexilis)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

Autecology

Limber pine is a shade-intolerant, early-seral species 

(Steele 1990) that is slow growing but long lived. It occupies xeric sites across a wide range of elevations (Jackson 

et al. 2010). Because it is easily killed by fire, the species 

Chapter 6: Effects of Climate Change on Forest Vegetation
134 USDA Forest Service RMRS-GTR-375. 2018

is found in fire-protected sites (e.g., rocky outcrops) with 

infrequent fires of low severity (Steele 1990). It can be 

associated with a wide range of other conifer species and 

quaking aspen (Langor 2007; Steele 1990). It is associated 

with both ectomycorrhizae and arbuscular mycorrhizae that 

facilitate its ability to exist in extremely dry environments. 

Limber pine seedlings are poor competitors with grass, but 

grow reasonably well on rocky substrates and with shrubs. 

Limber pine has difficulty competing with encroaching 

species on productive mesic sites and is often succeeded 

by Douglas-fir and subalpine fir. Its seeds are dispersed by 

rodents and by Clark’s nutcracker (Nucifraga columbiana), 

which relies on pine seeds as a food source and caches them 

throughout the subalpine zone (Lanner 1980; Lanner and 

Vander Wall 1980).

Disturbance Interactions

Thin bark and low crowns make limber pine susceptible 

to damage from wildfire. It is also susceptible to white pine 

blister rust, and some stands in newly infected areas are 

currently undergoing high mortality (Smith et al. 2013). 

Limber pine also facilitates the expansion of currant (Ribes

spp.) into traditional grasslands (Baumeister and Callaway 

2006), thus increasing rust infections and subsequent mortality. Mountain pine beetle (Jackson et al. 2010) and severe 

dwarf mistletoe infections can cause mortality. Porcupine 

(Erethizon dorsatum) damage is prevalent in some areas.

Historical and Current Conditions

Fire exclusion has allowed limber pine to expand its 

range from fire-protected sites into areas where frequent 

fires historically restricted it (Arno and Gruell 1983; Brown 

and Schoettle 2008). Expansion into some grass and shrub 

rangelands has facilitated expansion of other species as 

well (e.g., Douglas-fir) (Baumeister and Callaway 2006; 

Jackson et al. 2010). Some of the newly established limber 

pine forests have suffered recent mortality from white pine 

blister rust, mountain pine beetle, and red belt (Fomitopsis 

pinicola) (Jackson et al. 2010; Langor 2007; Taylor and 

Sturdevant 1998). Increasing wildfire extent has also affected some stands.

Climate Change Responses

Limber pine has a generalist adaptive strategy with broad 

phenotypic plasticity (Devine et al. 2012; Feldman et al. 

1999), so it is expected to be moderately vulnerable to climate change. The ability of limber pine to occupy shallow, 

infertile soils and tolerate periods of drought will confer 

resistance to warmer temperatures and drought. Reduced 

snowpack could increase growth of limber pine at higher 

elevations by lengthening the growing season (Aston 2010). 

However, warmer temperatures could also reduce soil 

moisture for seed germination and seedling growth, and lack 

of ectomycorrhizal associations could inhibit establishment 

in some locations (Coop and Schoettle 2009). Increasing 

wildfire extent and intensity may impact some limber pine 

stands in the future, causing higher mortality and reducing 

encroachment into grasslands.

Lodgepole Pine (Pinus contorta var.

latifolia, P.c. var. murrayana)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Great Basin and Semi Desert 

subregions)

Autecology

Lodgepole pine has broad ecological amplitude and environmental tolerance, including both the murrayana variety

in the western portion of the IAP region and the latifolia

variety elsewhere in the region (Lotan and Critchfield 1990). 

It grows well on gentle slopes and in basins but is also 

found on steep slopes and shallow soils. It is shade intolerant but highly tolerant of frost and drought. Lodgepole pine 

grows in pure stands and in association with many other 

conifer species, including subalpine fir, Engelmann spruce, 

Douglas-fir, and western larch (Steele et al. 1983). It can be 

either early or late seral, depending on location. Its ability 

to remain on xeric landscapes is enhanced by its association 

with many types of mycorrhizae. Lodgepole pine is generally a prolific seed producer, and the prevalence of cone 

serotiny in most individuals of the latifolia variety promotes 

rapid regeneration following wildfire (Hardy et al. 2000).

Disturbance Interactions

Fire plays a critical role in lodgepole pine forest succession (Brown 1973; Lotan et al. 1984). Mature lodgepole 

pine appears to be able to survive low-intensity fire, despite 

having thin bark (Ryan and Reinhardt 1988). In many cases, 

natural regeneration is prolific via abundant seed from 

serotinous cones (Lotan and Perry 1983; Nyland 1998), although drought is a common cause of mortality in first-year 

seedlings. Mountain pine beetle has played a significant role 

in the dynamics of lodgepole pine ecosystems. Beetles and 

wildfire create an important stress complex for lodgepole 

pine in some locations (Brown 1973; Geiszler et al. 1980), 

but can also act independently (Axelson et al. 2009; Moran 

and Corcoran 2012).

Historical and Current Conditions

Advancing succession associated with fire exclusion is 

contributing to replacement of lodgepole pine by subalpine 

fir in some areas of the IAP region. Concurrent increases 

in recently burned areas are creating new lodgepole stands, 

some of which may become very dense. Increased drought 

in these dense stands may exacerbate stress from other 

factors, including competition and insects. Warming 

temperatures have contributed to unprecedented mountain 

pine beetle outbreaks in lodgepole pine in western North 

America, including in the IAP region, causing 100 percent 

mortality in many mature lodgepole pine stands (Carroll et 

al. 2003; Jenkins et al. 2008; Page and Jenkins 2007).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 135

Climate Change Responses

Longer drought periods and warmer temperatures in drier 

lodgepole pine forests may cause decreased growth and 

regeneration, perhaps resulting in a transition to more xeric 

tree species. Chhin et al. (2008) and Nigh (2014) projected 

that growth will decrease in moderate future warming, but 

the species probably has sufficient genetic capacity to compensate for this loss. Given that lodgepole pine is a generalist 

and capable of regenerating and growing in a wide range 

of environments, it is likely that any reduction in lodgepole 

pine dominance in dry sites would occur only under extreme 

warming scenarios over many decades to centuries.

In high-elevation subalpine systems where seasonal 

drought is not a problem, a warmer climate may increase 

productivity (Aston 2010; Johnstone and Chapin 2003). 

Wang et al. (2006) found major increases in lodgepole pine 

productivity under future climates with moderate warming, 

but decreased productivity and perhaps local extinctions 

were associated with extreme warming. Romme and Turner 

(1991) projected increases in the lodgepole pine zone in 

the Greater Yellowstone Area under moderate warming. 

Lodgepole pine could migrate into upper subalpine areas 

where it is currently excluded by cold, windy conditions 

(Hamann and Wang 2006; Romme and Turner 1991). The 

latifolia variety is well adapted to increased fire occurrence, depending on level of serotiny (Turner et al. 1999), 

although if fire is too frequent, it could be eliminated from 

sites where fire returns before established seedlings and 

saplings become reproductively mature (Larson et al. 2013). 

Projected increases in climatic conditions that facilitate 

mountain pine beetle outbreaks (higher reproductive rates) 

(Bentz et al. 2010) could reduce the abundance of lodgepole 

pine in some landscapes (Creeden et al. 2014; Gillette et al. 

2014) (Chapter 8), especially where fire has been excluded 

(Temperli et al. 2013).

Ponderosa Pine (Pinus ponderosa var.

ponderosa, P.p. var. scopulorum)

(Middle Rockies, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

Autecology

Ponderosa pine is shade intolerant and drought adapted, 

occupying low-elevation, dry forests (Minore 1979), and 

is both an early- and late-seral species, often associated 

with Douglas-fir and grand fir on moister sites. In the IAP 

region, Pacific ponderosa pine (var. ponderosa) extends 

from the central mountains of Idaho to the east side of the 

Sierra Nevada in Nevada. The Rocky Mountain variety (var. 

scopulorum) extends from the eastern mountains of Nevada 

to the central and northern mountains of Utah. (Note that 

Washoe pine [P. p. subsp. washoensis], which is found in 

a few locations in the Great Basin and northeastern slope 

of the Sierra Nevada, is no longer considered a discrete 

subspecies and is not included in the assessment.) For both 

the Pacific and Rocky Mountain varieties, moisture typically limits growth, especially in summer, and distribution 

of ponderosa pine on drier sites is limited by available soil 

moisture, which, in turn, is affected by soil texture and 

depth. Ponderosa pine seedlings are susceptible to frost 

damage, which can exclude this species from low valleys 

(Shearer and Schimidt 1970). Ponderosa pine tolerates 

dry soil conditions by efficiently closing stomata to avoid 

water loss and xylem cavitation (Sala et al. 2005), tolerating 

intense drought, and drawing groundwater at low soil water 

potentials.

Cone crop periodicity in ponderosa pine varies greatly, 

but it is a poor seed producer in some areas. Natural 

regeneration is sporadic and is best when a heavy seed 

crop is followed by favorable weather in the next growing 

season (Heidmann 1983; Shearer and Schmidt 1970). The 

Rocky Mountain variety is highly inbred, and its vulnerability could be further compromised with limited gene 

flow between populations (Potter et al. 2015). Soil texture, 

plant competition, and seedbed conditions reduce seed germination and limit seedling survival and growth, although 

ponderosa pine can often germinate under moisture stress 

(Oliver and Ryker 1990). Young seedlings are susceptible to 

cold night temperatures and deep frosts, and trees occasionally suffer winter desiccation in drying winds.

Disturbance Interactions

Disturbance plays a major role in sustaining ponderosa 

pine forests. Over 100 species of insects attack the Pacific 

variety, and over 50 species attack the Rocky Mountain 

variety. The most damaging of the tree-killing insects are 

several species of Dendroctonus (Oliver and Ryker 1990), 

followed by ips beetles, both of which are present naturally 

in all stands. Dwarf mistletoe is widespread but rarely fatal. 

In the absence of fire or another disturbance that reduces 

stem density, bark beetles can cause extensive tree mortality. 

Ponderosa pine has a high capacity to survive fire, better 

than all of its competitors except western larch (Minore 

1979; Ryan and Reinhardt 1988). Thus, wildfire favors 

the growth of large-diameter ponderosa pine by killing its 

primary competitors and small-diameter ponderosa pines 

(Arno 1988; Steele et al. 1986).

Historical and Current Conditions

Wildfire historically promoted ponderosa pine dominance across most low-elevation savannas because of its 

high resistance to fire, including high-intensity fire. Fire 

exclusion, mining, timber harvest, and livestock grazing 

caused major reductions in ponderosa pine forests (Jain and 

Graham 2005). Changes in fire regime altered the composition and structure of the remaining dry forests (Hann et al. 

1997), with area burned by surface fires decreasing (Page 

and Jenkins 2007), mean fire return interval increasing, and 

crown fires increasing (Hann et al. 1997). Mid-seral structures have increased, often containing dense stands of small 

ponderosa pine, Douglas-fir, and grand fir. The proportion of 

Chapter 6: Effects of Climate Change on Forest Vegetation
136 USDA Forest Service RMRS-GTR-375. 2018

dry forests occupied by late-seral, single-storied ponderosa 

pine has declined significantly, and Douglas-fir or grand fir 

is often common in the understory.

Climate Change Responses

Ponderosa pine is expected to be relatively tolerant of 

increasing temperatures and longer droughts. The Rocky 

Mountain variety has relatively high phenotypic plasticity and is therefore better adapted to drought, although 

regeneration may decrease if precipitation decreases or 

becomes more variable. Morales et al. (2015) projected an 

11 percent increase in the range of ponderosa pine in the 

western United States, and Nitschke and Innes (2008) used 

gap modeling to project replacement of dry Douglas-fir with 

ponderosa pine in British Columbia. Hansen et al. (2001) 

projected that the range of ponderosa pine will expand in 

the western United States, whereas most other tree species 

ranges will decrease. Although species distribution models 

suggest that the range of ponderosa pine may decrease (Bell 

et al. 2014; Franklin et al. 1991; Gray and Hamann 2013) 

and rise in elevation (Crimmins et al. 2011) in a warmer climate, these projections are questionable because they do not 

consider on-the-ground growth processes and competition.

Advancing competition resulting from fire exclusion, 

increased wildfire extent and severity, and the potential for 

increased susceptibility to insects in warmer, drier conditions will dictate the future of ponderosa pine in the IAP 

region (Hann et al. 1997; Miller and Keen 1960; Negrón and 

Fettig 2014). If fires are too frequent, regenerating trees will 

not grow above the lethal scorch height and will not reach 

maturity. Increasing wildfire severity could also eliminate 

mature ponderosa pine trees that provide seed sources for 

populating future burns.

Singleleaf Pinyon (Pinus monophylla)

(Great Basin and Semi Desert subregion)

Autecology

Singleleaf pinyon is adapted to a wide variety of sites. It 

usually grows on pediments; dry, rocky slopes; ridges; and 

alluvial fans between 4,500 and 7,500 feet elevation (Lanner 

1999; Stephenson and Calcarone 1999). It is frost resistant, 

drought tolerant, and shade intolerant (Lanner 1983), typically growing on shallow, well-drained, low-fertility soils, 

although it has been found on more productive soils as well 

(Evans 1988; Gottfried and Severson 1993; Gottfried et 

al. 1995). Pinyon pine typically grows in association with 

juniper species, where juniper dominates lower elevations of 

their range and pinyon the upper. Pinyon-juniper woodlands 

typically progress toward increased tree density and canopy 

cover over time (Everett 1985; Meeuwig et al. 1990; Short 

and McCulloch 1977; West et al. 1975), often expanding 

into adjacent grass and shrublands (Burwell 1998; West et 

al. 1975). Understory species make up a small portion of 

the total biomass in denser stands, although they may be 

important forage species and typically persist following 

disturbance (Everett and Koniak 1981).

Disturbance Interactions

In the Great Basin, there is evidence of both frequent, 

low-intensity fires carried by once-abundant perennial 

grasses, and less frequent, local stand-replacement fires during extreme conditions. Fires burned in irregular patterns, 

producing a mosaic of burned and unburned landscape. On 

high-productivity sites where sufficient fine fuels existed, 

fires burned every 15 to 20 years, and on less productive 

sites with patchy fuels, fire intervals were 50 to 100 years 

or longer. Fire frequency in singleleaf pinyon communities 

varies with fuel loads and ignition source, which, in turn, 

vary with habitat type, aspect, topography, stand history, 

and climatic conditions (Gruell 1999; Paysen et al. 2000). 

Cheatgrass has become increasingly common in the understory over the past few decades, continually providing 

abundant fine surface fuels and increasing the potential for 

more frequent wildfires (Shinneman and Baker 2009).

Pinyon dwarf mistletoe (Arceuthobium divaricatum) can 

cause extensive damage (Hawksworth and Wiens 1972), 

leaving trees susceptible to insect attack. Pinyon blister 

rust (Cronartium occidentale) occurs extensively on Ribes 

species in most western States but infects singleleaf pinyon 

only sporadically (Stillinger 1944), occasionally girdling 

small trees. Black stain root disease (Ophiostoma wageneri) 

occasionally kills singleleaf pinyon (Smith 1967b; Wagener 

and Mielke 1961). The disease spreads by root contact, and 

infection is confined to xylem in the roots and lower trunk. 

Pinyon ips (Ips confusus) is commonly found in pinyon 

woodlands, with outbreaks occurring when trees are stressed 

(Chapter 8).

Historical and Current Conditions

Singleleaf pinyon was a source of fuel (charcoal) for the 

mining industry between the 1860s and 1920s (Young and 

Budy 1979), and it has been used extensively for firewood 

and other uses, with local deforestation in some locations. In 

some lower-elevation locations, pinyon has been removed 

from the landscape to encourage the growth of grasses and 

forage for livestock grazing. Persistent woodlands of pinyon 

pine or juniper species, or a mixture of both, are found 

where local soils and climate are favorable, and wildfire has 

been infrequent (Romme et al. 2009). Pinyon-juniper savannas are found where local soils and climate are suitable for 

both trees and grasses, and low-intensity fires have been 

relatively frequent. Large increases in junipers have occurred in portions of pinyon-juniper woodlands (Romme et 

al. 2009). Damage to cryptobiotic crusts has caused erosion 

in some pinyon-juniper woodlands.

Climate Change Responses

Singleleaf pinyon is drought tolerant, and reduced soil 

moisture is not expected to have a significant effect on its 

abundance and distribution, although its growth may decrease over time. It is not as drought tolerant as the juniper 

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 137

species with which it is associated, and may decrease in 

abundance where the species compete. However, it may be 

able to outcompete ponderosa pine at higher elevations.

The future of singleleaf pinyon will largely depend on 

spatial and temporal patterns of wildfire, which is expected 

to increase in frequency (Floyd et al. 2004). Pinyon is only 

moderately fire tolerant and is easily engaged in crown fires 

because of low crowns and high concentrations of volatile 

chemicals. After an initial fire, accumulation of surface fuels 

and tree regeneration is likely to be slow (unless Gambel oak 

[Pinus gambelii] is present) because of moisture limitations, 

resulting in a sparse canopy and disconnected fuels (Rocca 

et al. 2014). If fire frequency is high in areas where pinyon 

is codominant with ponderosa pine, the latter species will 

become more common and pinyon will become less common. The long-term condition of juniper is complicated by 

nonnative annual grasses, which increase surface fuels and 

fire frequency. Insects, especially pinyon ips, will also be an 

important stressor, especially during extended droughts.

Twoneedle Pinyon (Pinus edulis)

(Plateaus subregion)

Autecology

Pinyon-juniper woodlands are found between the low 

plains covered by grassland, desert shrub, or chaparral 

vegetation and the high mountains just below the zone dominated by either submontane shrubs or ponderosa pine. They 

grow best on higher, wetter sites of the woodland zone, just 

below ponderosa pine (Fowells 1965; Jameson et al. 1962). 

Twoneedle pinyon grows in semiarid to arid climates, often 

associated with oneseed juniper (Juniperus monosperma)

and Utah juniper. Pinyon is drought tolerant and shade intolerant, and seedlings require extra moisture or shade until 

their elongating taproots reach deeper substrates (Mitchell 

1984). The extensive root system of established pinyons and 

relatively rapid rate of root elongation, especially of young 

seedlings, enhance the ability of pinyon to survive in dry 

environments.

Disturbance Interactions

Small pinyon pines are sensitive to fire and may be killed 

by low-intensity fire (Floyd et al. 2000; McCulloch 1969), 

whereas larger trees tend to be somewhat resistant to surface 

fire because foliage is high enough above the ground to 

avoid crown scorch or other damage (Dwyer and Pieper 

1967; Wittie and McDaniel 1990). Cheatgrass has become 

increasingly common in the understory over the past few 

decades, continually providing abundant fine surface fuels 

and increasing the potential for more frequent wildfires 

(Shinneman and Baker 2009). Foliage diseases include 

needle casts (Elytroderma deformans, Bifusella saccata) and 

needle rusts (Coleosporium jonesii, C. crowellii) (Fowells 

1965; Hepting 1971). Pinyon blister rust and pinyon dwarf 

mistletoe damage stems; the latter species is considered the 

major pathogen of pinyon.

Historical and Current Conditions

Pinyon-juniper woodland expansion since the time of 

settlement has been attributed to several factors, including 

a warming climate, fire exclusion, increased populations of 

seed-dispersing birds and mammals, and reduced competition from grasses resulting from overgrazing by livestock 

(Everett 1987; Jameson 1970). In the absence of wildfire, 

fuels have accumulated in some stands, especially in 

more mesic sites, increasing the possibility of crown fire. 

Hazardous fuels reduction, including prescribed burning, 

has been used in some locations.

Climate Change Responses

Twoneedle pinyon is drought tolerant, and reduced soil 

moisture is not expected to have a significant effect on 

its abundance and distribution, although its growth may 

decrease over time. It is not as drought tolerant as juniper, 

and may decrease in abundance where the species co-occur. 

However, it may outcompete ponderosa pine at higher 

elevations. Since 2000, twoneedle pinyon at low-elevation 

sites in northern New Mexico has suffered significant 

mortality associated with extended drought and pinyon Ips

(Breshears et al. 2009) (Chapter 8), and although similar 

mortality has not been widespread in Utah, it may be possible during long droughts. If pinyon mortality increases in 

the future, juniper would probably become more dominant.

The future of twoneedle pinyon will largely depend on 

spatial and temporal patterns of wildfire, which is expected 

to increase in frequency (Floyd et al. 2004). Pinyon pine 

is only moderately fire tolerant, and it is easily engaged in 

crown fires because of low crowns and high concentrations 

of volatile chemicals. After an initial fire, accumulation of 

surface fuels and tree regeneration will probably be slow 

(unless Gambel oak is present) because of moisture limitations, resulting in a sparse canopy and disconnected fuels 

(Rocca et al. 2014). If fire frequency is high in areas where 

pinyon pine is codominant with ponderosa pine, the latter 

species will become more common and pinyon pine will 

become less common. The long-term condition of juniper 

is complicated by nonnative annual grasses, which increase surface fuels and fire frequency. Insects, especially 

pinyon Ips, will also be an important stressor, especially 

during extended droughts.

Western White Pine (Pinus monticola)

(Great Basin and Semi Desert subregion)

Autecology

Western white pine occupies the extreme western Great 

Basin portion of the IAP region and is typically associated 

with other conifer species. It is limited by moisture at 

lower elevations and by temperature at higher elevations. 

Western white pine grows on a variety of sites, but is more 

common along moist creek bottoms, lower benches, and 

northerly slopes. Seedling establishment is favored by 

Chapter 6: Effects of Climate Change on Forest Vegetation
138 USDA Forest Service RMRS-GTR-375. 2018

partial shade in severe sites (Graham 1990) but minimal 

shade on northern slopes. Once established, it grows best 

in full sun. Seedlings have low drought tolerance, and 

first-year seedlings are subject to mortality from high 

surface temperatures on exposed sites. White pine attains 

dominance only after wildfire or in silvicultural systems 

that favor it. A generalist species with broad climate and 

environmental tolerances (Devine et al. 2012), western 

white pine adapts to different conditions through phenotypic plasticity and selective genetic differences.

Disturbance Interactions

Historically, white pine forests originated from wildfires, 

especially stand-replacing burns, but they were also maintained by frequent low-intensity fires (Barrett et al. 1991). 

When mature, white pine has thick bark and a high crown, 

which make it tolerant of fire. White pine blister rust has 

greatly decreased survival and vigor of white pine (Fins 

et al. 2002; Harvey et al. 2008), virtually eliminating this 

species in some locations. Armillaria root rot causes foliar 

chlorisis and root mortality, as well as reduced growth. 

Annosus root disease and laminated root rot also cause 

reduced vigor and some mortality. Bark beetles attack 

western white pine, killing groups of trees in mature forests, 

especially those weakened by blister rust (Chapter 8).

Historical and Current Conditions

Western white pine stands were previously more dominant in western North America (Harvey et al. 2008). It is 

much less abundant in mixed conifer forests as a result of 

logging, fire exclusion, and blister rust (Fins et al. 2002). 

This decline will probably continue to reduce abundance, 

and in some cases, cause local extirpation in the absence of 

assertive restoration.

Climate Change Responses

Western white pine may be well adapted to a warmer 

climate in some portions of its range (Loehman et al. 2011). 

It can disperse seeds into burned areas, which are likely to 

increase in the future, and a warmer climate may increase its 

productivity in some locations. However, the prevalence of 

white pine blister rust will make it difficult for white pine to 

persist in most forests (Fins et al. 2002; Harvey et al. 2008), 

and it is expected to continue to decline throughout much of 

its range.

Whitebark Pine (Pinus albicaulis)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch Front 

subregions)

Autecology

Whitebark pine is an important component of upper subalpine forests in the IAP region (Arno and Hoff 

1990). It supports unique components of floral and faunal 

diversity and promotes community development and stability (Tomback and Achuff 2010; Tomback et al. 2001). 

It is a long-lived tree, tolerates moderate shade (Minore 

1979), grows slowly, and tolerates long periods of drought 

(Callaway et al. 1998). In the absence of wildfire, whitebark 

pine is replaced by subalpine fir and Engelmann spruce 

in some locations (Arno and Hoff 1990). Whitebark pine 

has a mutualistic relationship with Clark’s nutcracker, 

which caches and disperses seeds (Tomback 1982, 1983). 

Whitebark pine is genetically diverse (Keane et al. 2012), 

allowing it to exist across many environments.

Disturbance Interactions

Whitebark pine fire regimes are complex and variable 

in space and time (Morgan et al. 1994b). Most fires in the 

upper subalpine zone burn in mixed-severity patterns that 

facilitate long-term survival of the species (Keane et al. 

1994). Mountain pine beetle can damage mature stands, 

often causing high mortality. White pine blister rust is also 

damaging, preventing tree development and often causing 

mortality. Whitebark pine has some resistance to white pine 

blister rust, and although efforts at developing rust-resistant 

seed for regenerating burned and treated areas hold promise, 

restoration will need to occur at large spatial scales to be 

effective.

Historical and Current Conditions

Whitebark pine, a candidate species for listing under 

the U.S. Endangered Species Act (USFWS 2011), has been 

declining since the early 20th century from the combined 

effects of mountain pine beetle-caused mortality, fire exclusion, and spread of white pine blister rust (Schwandt 2006; 

Tomback and Achuff 2010) (fig. 6.4). Within the last decade, 

outbreaks of mountain pine beetle and increasing damage 

and mortality from blister rust have resulted in cumulative 

whitebark pine losses that have altered high-elevation community composition and ecosystem processes throughout 

much of western North America.

Climate Change Responses

Although whitebark pine was able to persevere through 

climatic variability in the past, it will be highly exposed to 

future climate change because of its confined distribution 

to upper subalpine environments. It is expected to continue 

to decline in abundance and vigor in a warmer climate, not 

because it is poorly adapted to an altered climate, but because it is experiencing so much stress from blister rust and 

mountain pine beetle that regeneration capability is greatly 

reduced (Bartlein et al. 1997; Bentz et al. 2016; Devine et 

al. 2012). In some cases, whitebark pine populations are so 

low that Clark’s nutcracker is acting more as a seed predator 

than a seed disperser (Keane and Parsons 2010; Leirfallom 

et al. 2015). A warmer climate is expected to exacerbate this 

decline in most locations.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 139

Figure 6.4—Whitebark pine. This species, which has been 

subjected to mortality from white pine blister rust for 

decades, may be more susceptible to mountain pine 

beetles in a warmer climate (photo: J. Beck, National Park 

Service).

Blue Spruce (Picea pungens)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

Autecology

The shallow roots of blue spruce restrict it to moist 

sites where water is close to the surface (Lanner 1983). 

Blue spruce occurs at middle elevations on montane 

streambanks, well-drained floodplains, first-level terraces, ravines, intermittent streams, and gentle slopes 

(Fechner 1985; Hess and Alexander 1986; Lanner 1983). 

Spruce grows in cool climates that are sub-humid to 

humid and characterized by low summer temperatures 

and low winter precipitation. It is a pioneer species in 

riparian communities that are subject to periodic disturbances, such as scouring and flooding (Baker 1990; 

Fechner 1990; Szaro 1990). It is a shade-tolerant, midto late-seral species in montane and subalpine zones 

(Baker 1988; Schmidt and Larson 1989).

Disturbance Interactions

Blue spruce is easily killed by fire (Jones 1974; 

Wright and Bailey 1982). Insects and disease reduce 

growth, viability, and vigor of spruce (Fechner 1985; 

Walters 1978) (Chapter 8). Heart and root rots, cone 

rusts, nematodes, snow molds, canker, and tip blight can 

reduce the vigor of spruce (Fechner 1990; Nelson and 

Krebill 1982) and can cause mortality in older, low-vigor 

trees.

Historical and Current Conditions

Because blue spruce is located at high elevation and 

has no commercial value for timber, it has been relatively free of human influence, except in stands where it 

may have been associated with harvest of other species, 

such as Engelmann spruce. Western spruce budworm has 

killed patches of spruce and often other species in some 

locations, but this appears to be a normal occurrence in 

older, low-vigor stands.

Climate Change Responses

Climate change may reduce the functionality of 

riparian and wet meadow locations where blue spruce 

is commonly found. Therefore, its distribution and 

abundance could decrease locally if growth and vigor decline over time. Wildfire is currently uncommon in blue 

spruce communities, but if it becomes more frequent in a 

warmer climate, blue spruce will decrease in abundance 

because of fire. If fire frequency is high enough, spruce 

may not achieve dominance in the overstory.

Engelmann Spruce (Picea engelmannii)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and 

Semi Desert subregions)

Autecology

Engelmann spruce is widely distributed and is a major 

component of high-elevation forests in the IAP region 

(Alexander and Shepperd 1990) It occupies very cold 

environments in some locations. It is shade tolerant, 

although not as much as its common associate subalpine 

fir. This species is not drought tolerant, especially as a 

seedling (Alexander and Shepperd 1990), but tolerates 

frost and seasonal standing water. Pure Engelmann 

spruce is found in wet areas, but the species is usually 

mixed with other conifer species in upland locations. 

Seeds germinate in a variety of substrates, including 

litter and decomposed humus. Following establishment, 

survival is favored by adequate soil moisture, cool temperatures, and some shade.

Disturbance Interactions

Engelmann spruce is highly susceptible to fire injury 

and death, but some large spruce can survive severe 

burns (Bigler et al. 2005; Wadleigh and Jenkins 1996). It 

survives fire better than its primary associate, subalpine fir 

(Ryan and Reinhardt 1988). Surviving spruce can provide 

abundant seed in burned areas, although the subsequent 

forest may or may not be dominated by both spruce and 

Chapter 6: Effects of Climate Change on Forest Vegetation
140 USDA Forest Service RMRS-GTR-375. 2018

other species (e.g., subalpine fir) (Pfister et al. 1977). 

Engelmann spruce is susceptible to windthrow, especially 

after timber harvest and thinning. Several insect species 

are associated with Engelmann spruce (Chapter 8).

Historical and Current Conditions

Recent trends in Engelmann spruce forests across the 

IAP region are unclear. Advancing succession during many 

decades of fire exclusion has probably increased spruce 

abundance in subalpine and upper subalpine landscapes. 

But logging and fire have reduced spruce at lower elevations, where it occurs in seasonally wet areas and frost 

pockets. Several locations throughout the IAP region 

with mature Engelmann spruce have sustained extensive 

mortality from spruce beetle (Dendroctonus rufipennis) 

outbreaks.

Climate Change Responses

Some losses of Engelmann spruce are likely in drier 

portions of its range, especially in seasonally moist sites 

that will be drier in the future. Some mortality may have 

already occurred from recent drought (Liang et al. 2015). 

Higher temperatures can increase growth in some locations (Luckman et al. 1984) and reduce growth in other 

locations (Alberto et al. 2013). If wildfire frequency 

increases, it will probably reduce the extent of mature 

spruce, although it readily establishes following wildfire. 

Spruce beetle can cause greater stress in a warmer climate, 

especially in mature stands (Bentz et al. 2010). Although 

Engelmann spruce is sensitive to climate, it will probably 

persist in high-elevation landscapes, because of its genetic 

capacity to adapt to climatic variability by taking advantage of suitable microsites (Jump and Peñuelas 2005).

Quaking Aspen (Populus tremuloides)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

Autecology

Quaking aspen is abundant in the IAP region, with its 

distribution limited by water availability and growingseason temperature. Aspen stems are relatively short lived 

and maintained by disturbance (Mueggler 1985; Rogers 

2002), although belowground genets of aspen clones can 

survive for millennia. It is shade intolerant and sprouts 

aggressively following disturbance (usually fire), which 

kills most of the live stems, thus stimulating vegetative 

propagation (suckering) (Bartos 1978) and facilitating 

rapid reoccupation of the site. This species has substantial 

phenotypic variation, as evidenced by varied foliar morphology, stem morphology, and phenology among different 

clones.

Disturbance Interactions

Browsing of post-disturbance suckers by ungulates—

including elk (Cervus elaphus), moose (Alces alces), 

and cattle—frequently damages seedlings and sprouted 

stems (Eisenberg et al. 2013; White et al. 1998), and in 

some cases mature trees, thus increasing susceptibility to 

insects and pathogens. Wildfire can kill aboveground stems 

(Bartos 1998) but also promotes new seedlings and suckering by eliminating conifers (Campbell and Bartos 2001; 

Shepperd et al. 2001). Following disturbance, aspen dominates a site for 40 to 80 years; thinning from insects and 

disease and succession (shading) by conifers eventually 

reduce aspen abundance (Mueggler 1985; Rogers 2002). 

Hypoxylon canker (Hypoxylon mammatum) causes significant damage in some locations (Perala 1990). Young trees 

can be killed by small rodents and mammals (Eisenberg et 

al. 2013).

Historical and Current Conditions

Since around 1970, aspen has been in a period of general decline that may be at least partly attributed to wildfire 

exclusion, allowing plant succession to proceed toward 

conditions that ordinarily exclude aspen (Campbell and 

Bartos 2001; Frey et al. 2004). Recent episodes of aspen 

dieback (“sudden aspen decline”) have been superimposed 

on this general decline; the epidemiology begins with 

death of branch tips and progresses to death of mature 

trees and eventually death of entire clones (Frey et al. 

2004). Dieback is suspected to be caused by periods of 

drought (Worrall et al. 2013). The worst symptoms are 

generally found at lower elevations.

Climate Change Responses

Seral aspen communities will respond to a warmer 

climate differently than mature aspen communities (Rice et 

al. 2017). Aspen on warmer sites could suffer high mortality because of increasing water deficit (Hogg and Hurdle 

1995; Ireland et al. 2014). Extreme droughts (Frey et al. 

2004) and high temperatures (Perala 1983) are of special 

concern, especially at the margins of aspen distribution at 

low elevation, and may weaken trees enough that insects 

and pathogens can cause tree mortality (Rice et al. 2017). 

Increased wildfire frequency, particularly on moist sites, is 

likely to favor aspen regeneration in the future by removing conifers. If future wildfires are severe, however, they 

may kill shallow root systems and locally extirpate aspen. 

In some locations, declining stands may have little regeneration because of ungulate herbivory (Rogers et al. 2013).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 141

Fremont Cottonwood (Populus fremontii)

(Southern Greater Yellowstone, Uintas 

and Wasatch Front subregions)

Lanceleaf Cottonwood (Populus ×

acuminata)

(Great Basin and Semi Desert subregion)

Narrowleaf Cottonwood (Populus 

angustifolia)

(Southern Greater Yellowstone, Uintas 

and Wasatch Front, Plateaus, Great 

Basin and Semi Desert subregions)

Balsam Cottonwood (Populus 

balsamifera)

(Middle Rockies subregion)

Autecology

The four cottonwood species in the IAP region—Fremont 

cottonwood, lanceleaf cottonwood, narrowleaf cottonwood, 

and balsam cottonwood—grow primarily in seasonally wet 

to moist open-canopy sites, typically along streams and rivers. Cottonwood often dominates riparian communities on 

alluvial sites from 4,000 to 6,000 feet elevation, with other 

hardwood species, shrubs, and grasses in the understory. 

Cottonwood is shade and drought intolerant, requiring access to the water table during most of the growing season 

(Rood et al. 2003). High streamflows facilitate seedling 

establishment through scouring and deposition of alluvial 

sediments for germination of windborne seeds. High numbers of seedlings often become established after a flood, but 

thin over time. Seedlings and saplings are frequently injured 

and sometimes killed by early or late frosts (DeBell 1990).

Disturbance Interactions

Cottonwood is somewhat fire tolerant owing to its thick 

bark and high branches. It is a weak stump sprouter, but 

rarely regenerates from suckers (Brown 1996). Cottonwood 

can resprout and survive low-intensity fires in the short 

term (Gom and Rood 1999), but fire injuries can introduce 

diseases that weaken and sometimes kill trees (Borman and 

Larson 2002). Several insects attack cottonwood. Many 

fungal species cause decay in cottonwood, but only brown 

stringy heart rot (Spongipellis delectans) and yellow laminated butt rot (Pholiota populnea) cause significant damage. 

Russian olive (Elaeagnus angustifolia) and saltcedar 

(Tamarix spp.) are aggressive nonnative trees that can outcompete cottonwood in some locations, particularly during 

or after drought (Shafroth et al. 2002).

Historical and Current Conditions

Cottonwood species are well distributed within their 

respective habitats in the IAP region, although degradation 

of riparian areas by grazing and other land uses have damaged some trees and the functional integrity of the riparian 

system. Russian olive and saltcedar have displaced cottonwoods in many locations, thus altering local hydrological 

function, because the nonnative species take up more water 

than native species. Biological control releases of the nonnative northern tamarisk beetle (Diorhabda carinulata) in the 

Southwest, starting in the 1990s, have caused rapid mortality and decline in vigor in many saltcedar populations (Sher 

and Quigley 2013; Tracy and Robbins 2009).

Climate Change Responses

As snowpack declines and melts earlier with warming 

temperatures, there will be reduced, attenuated river flows, 

along with a possible shift in timing of peakflows. These 

shifts may decrease germination and establishment of 

young cottonwoods, depending on the relative timing of 

floods and seed production (Whited et al. 2007). Altered 

hydrological flow, which can also be caused by withdrawal 

for human use, will affect both floodplain interaction and 

water available to cottonwoods, which, in turn, can affect 

recruitment and establishment of seedlings (Auble and Scott 

1998; Beschta and Ripple 2005). Upland conifers can potentially establish in the riparian zone if the local water table 

has dropped, increasing competition with cottonwoods. 

Long-term transport of seeds provides cottonwood with 

an effective mechanism for regeneration across large landscapes, conferring some resilience to future climate.

Sitka Alder (Alnus viridis subsp. sinuata)

(Middle Rockies subregion)

Thinleaf Alder (Alnus incana subsp.

tenuifolia)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

White Alder (Alnus rhombifolia)

(Middle Rockies subregion)

Autecology

Sitka alder and thinleaf alder are small, deciduous 

trees or shrubs found on a wide range of soils and wide 

range of elevations. Sitka alder is usually multistemmed 

and bushy, forming dense thickets. White alder is a deciduous, medium to large tree found on a variety of soils 

typically near permanent streams at low to mid-elevations. All species are found on moist, cool sites, typically 

riparian areas or other locations where a reliable water 

Chapter 6: Effects of Climate Change on Forest Vegetation
142 USDA Forest Service RMRS-GTR-375. 2018

source is available; for example, Sitka alder is often 

located in avalanche tracks. These species are associated 

with other hardwood and shrub species, mixed with or intermittent with overstory conifer species. All species are 

moderately shade tolerant (Haeussler and Coates 1986). 

Seeds require a moist mineral soil for germination, which 

normally takes place in the spring. Thinleaf alder can also 

propagate by cloning (Hall 1973). All alder species fix 

nitrogen through their association with actinomycetes.

Disturbance Interactions

Many sites occupied by alder species are subject to periodic flooding. Although tops may be damaged or killed, 

all species can sprout from root crowns. Wind-dispersed 

seeds readily germinate on alluvial soils exposed by 

floods or covered by sediment, and on bare soil created 

by wildfire, avalanches, and soil slumps. Alders have thin 

bark, and stems are easily killed by fire. Although alder 

can be killed by severe fire (Barro et al. 1989), it can also 

sprout following top kill by fire (Fischer and Bradley 

1987). Although alder wood is resilient and somewhat

limber, avalanches can damage Sitka alder and thinleaf 

alder, which often reproduce by sprouting (Oliver et al. 

1985).

Historical and Current Conditions

Alders have rarely been disturbed by human activity because they have no timber value. They have been 

subjected to some stress in riparian areas that have been 

disturbed by water withdrawals or livestock grazing.

Climate Change Responses

In general, higher temperatures are not expected to 

have significant direct effects on alder species because alders are usually located in riparian areas that are buffered 

from temperature increases. However, smaller riparian 

areas may become drier in a warmer climate, especially 

if they rely on adjacent snowpack. Lower levels of soil 

moisture could reduce the vigor of alder and other species. Increased frequency of wildfire may be a significant 

stressor for white alder because it may not sprout vigorously after fire (Fryer 2014), possibly making associated 

species more competitive. Sitka alder and thinleaf alder 

can sprout after wildfire, so increased disturbance will 

probably not affect their distribution and abundance.

Velvet Ash (Fraxinus velutina)

(Uintas and Wasatch Front, Plateaus 

subregions)

Autecology

Velvet ash (also called desert ash or Arizona ash) is 

a deciduous tree with spreading branches and a rounded 

crown (if it has sufficient sunlight) that grows up to 30 

feet tall when mature. It is found in riparian areas in 

canyons and along streambanks in desert mountains of 

southern Utah and southern Nevada above 3,000 feet 

elevation. Velvet ash grows in a variety of substrates, 

including alkaline soils. The presence of this species in 

the desert generally indicates a permanent underground 

water supply. It is shade intolerant, regenerates through 

wind dispersal of winged seeds, and can sprout from the 

base when damaged.

Disturbance Interactions

Velvet ash is easily top-killed by fire, but stumps can 

sprout vigorously following fire and mechanical damage and can attain prefire heights in 8 years (Winkel 

and Syzdek 2015). North American ash populations are 

at substantial risk from the introduction of emerald ash 

borer (Agrilus planipennis), which has now reached as 

far west as Colorado. Large-scale mortality of ash trees, 

as a result of borer infestations, would probably result in 

significant modifications in the composition and successional dynamics of many natural forests (MacFarlane and 

Meyer 2005) (Chapter 8).

Historical and Current Conditions

Little is known about the historical distribution or 

uses of velvet ash. It has no commercial value for timber 

but may have been used for firewood in some locations. 

Its populations are probably mostly intact, except where 

riparian areas have been modified.

Climate Change Responses

As soil moisture declines in a warmer climate, 

marginal riparian sites for velvet ash may become less 

favorable for regeneration and survival of young trees. 

With increases in fire frequency, there are likely to be 

increased vegetative regeneration and decreased production of seedlings following fire; fire would probably kill 

seeds on or near the soil surface, restricting seedling 

recruitment to surviving seed-producing trees. Lowintensity fires may promote regeneration by thinning 

stands and stimulating sprouting. Increased temperatures 

may promote ash seedling and mature tree growth by 

increasing soil temperatures. Browsing pressure on ash 

may increase with increased drought, as upland grasses 

and forbs desiccate and senesce earlier, or are replaced by 

less palatable species.

Water Birch (Betula occidentalis)

(Middle Rockies, Southern Greater 

Yellowstone, Uintas and Wasatch 

Front, Plateaus, Great Basin and Semi 

Desert subregions)

Autecology

Water birch is primarily a riparian species, occurring 

near waterways, wet swales, marshes, ravines, bogs, and 

moist woodlands (Arno and Hammerly 1977; Welsh et 

al. 1987). Water birch is common along streams in steep 

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 143

areas of the IAP region, especially in coarse-textured, 

moist to wet soils (Sutton and Johnson 1974). Although 

common in semiarid climates (Arno and Hammerly 

1977), water birch is not particularly drought tolerant 

(Merigliano 1996) but is moderately shade tolerant and 

flood tolerant. In the Great Basin, riparian habitats with 

water birch are found in upland habitats ranging from 

mountain big sagebrush (Artemisia tridentata subsp. 

vaseyana) shrublands (Manning and Padgett 1989) to fir 

forests (Lanner 1983).

Disturbance Interactions

Water birch often forms clumps by sprouting from the 

base of the trunk (Harrington 1964). Sprouts can develop 

after top kill by flooding or other physical injury (Hansen 

et al. 1995; Skinner et al. 2006) or without aboveground 

damage (Lanner 1983). This species can regenerate 

quickly following damage and disturbance.

Historical and Current Conditions

Little is known about the historical distribution and 

use of water birch. It has little commercial value but is 

sometimes used for firewood and fence posts. Birch is 

used as browse by ungulates, including livestock, to some 

extent. Birch stems may have increased in some areas 

where American beaver (Castor canadensis) populations 

were reduced or extirpated.

Climate Change Responses

Water birch adapts well to a wide range of climate 

and water availability (Disalvo and Hart 2002). As soil 

moisture declines with a warmer, drier climate, marginal 

riparian sites for birch may become less favorable for 

regeneration and survival of young trees. With increased 

fire frequency, there are likely to be better vegetative 

regeneration and decreased production of seedlings following fire events. Fire would probably kill seeds on or 

near the soil surface, restricting seedling recruitment to 

surviving seed-producing trees. Low-intensity fires may 

promote regeneration by thinning stands and stimulating 

sprouting. Birch productivity may benefit from increased 

temperatures because seedling and mature tree growth 

may increase with increasing soil temperatures. Browsing 

pressure may increase with increased drought, as upland 

grasses and forbs desiccate and senesce earlier, or are 

replaced by less palatable species.

Boxelder (Acer negundo)

(Southern Greater Yellowstone, 

Uintas and Wasatch Front, Plateaus 

subregions)

Autecology

Boxelder is a fast-growing and fairly short-lived hardwood that grows in riparian and palustrine communities. 

It generally grows on moist sites along lakes and streams, 

on floodplains, and in low-lying wet places where its 

shallow root system can find abundant moisture (Lanner 

1983). Resilient to climate extremes (Preston 1948), 

boxelder is drought tolerant once established and can 

withstand short periods of flooding (Sutton and Johnson 

1974). It is moderately shade tolerant but does not 

reproduce in its own shade. Boxelder roots are shallow 

and spreading, except in deep soils (Preston 1948; Sutton 

and Johnson 1974). It tolerates a wide range of soils but 

grows more vigorously in well-drained soils (Medina 

1986).

Disturbance Interactions

Boxelder grows on moist bottomland sites, which are 

seldom subject to burning. This thin-barked species is 

easily injured by fire (Van Dersal 1938), regenerating via 

sprouting and seeds. It produces large annual crops of 

wind-dispersed seeds that germinate on a wide variety 

of soils. It also sprouts from the root crown, stump, or 

exposed roots following top kill by mechanical damage (Hansen and Hoffman 1988; Nix and Cox 1987). 

Verticillium wilt (Verticillium albo-atrum) is the only 

notable disease that kills boxelder, although it is also 

susceptible to stem canker caused by eutypella canker 

(Eutypella parasitica). Boxelder bugs (Boisea trivittata) 

infest boxelder trees and other maples, but do not cause 

significant damage.

Historical and Current Conditions

Boxelder was used for windbreaks and erosion control 

in many parts of the West. It has no commercial value 

but is sometimes used for firewood. It is used as browse 

by ungulates, and although it is unpalatable to livestock, 

the animals may damage stems while seeking shade. It is 

possible that boxelder stems have increased in some areas 

where American beaver populations were reduced or extirpated (Dieter and McCabe 1989). It is probably mostly 

intact from an ecological perspective.

Climate Change Responses

Boxelder exists across a broad range of soils and 

topographic locations, but as soil moisture declines in 

a warmer climate, marginal riparian sites may become 

less favorable for regeneration and survival of young 

trees. With increased fire frequency, there are likely to be 

increased vegetative regeneration and decreased production of seedlings following fire. Fire is likely to kill seeds 

on or near the soil surface, restricting seedling recruitment to surviving seed-producing trees. Low-intensity 

fires may promote regeneration by thinning stands and 

stimulating sprouting. Boxelder productivity may benefit 

from increased temperatures because seedling and mature 

tree growth may increase with increasing soil temperatures. Browsing pressure on boxelder may increase with 

increased drought, as upland grasses and forbs desiccate 

and senesce earlier, or are replaced by less palatable 

species.

Chapter 6: Effects of Climate Change on Forest Vegetation
144 USDA Forest Service RMRS-GTR-375. 2018

Gambel Oak (Quercus gambelii)

(Uintas and Wasatch Front, Plateaus, 

Great Basin and Semi Desert 

subregions)

Autecology

Gambel oak is a small deciduous tree or large shrub that 

is widespread in foothills and lower mountain locations of 

the IAP region. The tree typically grows at between 3,000 

and 10,000 feet elevation, where average annual precipitation is 10 to 24 inches. Oak height is typically 10 to 30 feet 

depending on soil type and water availability. Branches 

are irregular and crooked, making them flexible enough 

to bend without breaking when covered with snow. Deep 

roots, xeromorphic leaves, and efficient water transport 

contribute to the high drought tolerance of Gambel oak 

(Kolb and Stone 2000), which grows in both pure stands 

and associated with ponderosa pine, pinyon pine, and other 

hardwood tree and shrub species. In most of its range, 

Gambel oak regeneration depends more on sprouting than 

establishment from seed (Clary and Tiedemann 1986; 

Larsen and Johnson 1998).

Disturbance Interactions

Gambel oak responds to fire by vegetative sprouting 

from its lignotuber and rhizomes, and even the stems can 

survive low-intensity fires (Harper et al. 1985) (fig. 6.5). 

Fire frequency in oak stands depends on accumulation of 

fuels by both oak and associated species (Mitchell 1984). 

Following wildfire, sprouts continue to grow, and natural 

thinning occurs, adding dead stems to the fuel bed. In 

the absence of fire, sprouts form young poles. At the pole 

stage, fires cause 100 percent stem mortality, either creating openings within stands for resprouting or cycling back 

to a grass-forb stage. In the absence of fire, Gambel oak 

stands reach maturity in 60 to 80 years. Dense understories 

of oak may serve as ladder fuels that carry fire to overstory 

conifers, increasing fire risk to adjacent species. Fire in 

some ponderosa pine stands can convert to thickets of 

Gambel oak, initiating a Gambel oak successional stage 

after the competing ponderosa pine overstory is removed 

(Dick-Peddie and Moir 1970). Late-spring frosts that kill 

oak leaves can cause extreme fire behavior later in the 

summer; the dead leaves tend to cling to the stem and act 

as dry aerial fuels (Jester et al. 2012). Many insects and 

diseases are associated with Gambel oak.

Historical and Current Conditions

Gambel oak acorns have been an important food for 

Native Americans for thousands of years, and the species 

is widely used for firewood. Oak density has been reduced 

in some areas with herbicides, mechanical treatments, 

and prescribed burning, typically to reduce fire hazard 

and protect overstory species such as ponderosa pine. In 

some areas where multiple wildfires have occurred in the 

past 30 years, oak appears to be increasing in dominance 

through sprouting and mortality of conifers (e.g., Adams 

and Dockter n.d.) combined with slow regeneration of the 

overstory.

Figure 6.5—Gambel oak 

sprouts vigorously 

following wildfire, 

as shown in both 

the foreground and 

background. The 

distribution and 

abundance of this 

species may increase 

in a warmer climate, 

replacing conifers as 

a dominant species in 

some locations (photo by 

Heath Haussamen, used 

with permission).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 145

Climate Change Responses

Gambel oak is very tolerant of low soil moisture, providing an advantage in a warmer climate with more droughts. 

Oaks sprout readily following wildfire, and with an expected 

increase in fire in the future, oaks may retain dominance 

or codominance in most locations. Being adapted to both 

drought and fire will improve the competitive status of oak 

with co-occurring tree species such as ponderosa pine and 

pinyon pines and probably with other shrub species, except 

at the lowest elevations where shrub-steppe systems dominate. Therefore, it is likely that Gambel oak will increase 

in abundance and possibly distribution in a warmer climate 

with more fire.

Curl-Leaf Mountain Mahogany 

(Cercocarpus ledifolius)

(Uintas and Wasatch Front, Plateaus, 

Great Basin and Semi Desert 

subregions)

Autecology

Curl-leaf mountain mahogany is a drought-tolerant, 

somewhat shade-tolerant, slow-growing tree or tall shrub 

(Lacey and Mosley 2002; Lanner 1983) found at 4,000 to 

8,000 feet elevation in the IAP region (Brotherson 1990), 

typically in scattered patches and in extensive pure stands 

on dry, rocky slopes between conifer and desert steppe communities (Munz 1973; Stubbendieck et al. 1992). The root 

system is shallow and spreads widely (Sutton and Johnson 

1974), typically in shallow to deep, well-drained, lowfertility sandy loam soils (Davis 1990; Hickman 1993).

Disturbance Interactions

Wildfires usually cause mortality of curl-leaf mountain 

mahogany, although older plants with thick bark may 

survive low-intensity fires (Gruell et al 1985; Martin and 

Johnson 1979). Postfire regeneration is primarily by seedling establishment (Gruell et al. 1985), and sprouting after 

fire is rare (Tisdale and Hironaka 1981). Several species of 

insects, including mountain-mahogany looper (Iridopsis 

clivinaria), feed on mountain mahogany, but do not generally cause significant damage.

Historical and Current Conditions

Curl-leaf mountain mahogany was used by Native 

Americans to make bows and other small implements. 

Euro-Americans first used it as fuel for mining in the 

1860s. The species provides forage for ungulates and 

wildlife. Livestock can damage productivity where grazing is heavy (Smith 1967a). Fire exclusion has facilitated 

increased mountain mahogany abundance and successful 

regeneration in some locations (Gruell 1982; Kay 2003), 

allowing it to compete with more fire-adapted species. 

Mountain mahogany is occasionally killed with herbicides, 

mechanical removal, or prescribed fire to improve range 

quality or reduce fuel bed continuity.

Climate Change Responses

Curl-leaf mountain mahogany is drought tolerant, so 

it should continue to be productive in a warmer climate 

with more droughts, especially compared to other species. 

However, if wildfire frequency and extent increase as 

expected, it will be at a disadvantage because it is not fire 

tolerant and does not regenerate by sprouting. If wildfire is 

sufficiently frequent, new seedlings may be successively 

killed, thus reducing the abundance of mountain mahogany 

across fire-prone landscapes.

Bigtooth Maple (Acer grandidentatum)

(Uintas and Wasatch Front, Plateaus, 

Great Basin and Semi Desert 

subregions)

Autecology

Bigtooth maple is an important component of montane 

riparian communities in the IAP region (Fitzhugh et al. 

1987; Moir 1982), typically located in canyons, in ravines, 

along mountain streams, and on lower slopes (Alexander 

et al. 1984; Cronquist et al. 1997) at 4,000 to 7,000 feet 

elevation. It is more abundant in the bottom than in the 

top of snowmelt drainages. In Idaho, it grows on hillsides, 

below springs and seeps, and on secondary floodplains 

of narrow canyon drainages (Hall and Hansen 1997). 

It is found on upper slopes in the Wasatch Mountains, 

although it is more common on mesic, north-facing slopes 

than on drier south-facing slopes (Dina and Klikoff 1973; 

Ehleringer et al. 1992). Bigtooth maple is drought tolerant 

(Sorenson et al. 1984; Sutton and Johnson 1974) and cold 

hardy, and tolerates summer temperatures above 100 °F 

(Sorenson et al. 1984).

Disturbance Interactions

Although bigtooth maple can be top-killed by fire, 

plants can survive by sprouting from the root crown 

(Bradley et al. 1992; Harper et al. 1992). In a severe burn, 

this species is likely to be killed (Harper et al. 1992). 

Smaller stems are more likely to be killed by fire, clearing 

areas for new tree seedlings and sprouts from surviving 

larger trees.

Historical and Current Conditions

Little is known about the historical distribution and 

use of bigtooth maple. It has no economic value except as 

firewood. The species is used for forage and cover by native ungulates and for cover by livestock (Hall and Hansen 

1997). Bigtooth maple is useful for restoration of sites 

where vegetation has been denuded because it establishes 

deep roots, even in infertile soils (Barker 1977).

Chapter 6: Effects of Climate Change on Forest Vegetation
146 USDA Forest Service RMRS-GTR-375. 2018

Climate Change Responses

Because bigtooth maple is drought tolerant, its productivity may be relatively stable in a warmer climate, 

especially because it is located in canyons and other places 

where water is typically present. As soil moisture declines 

in a warmer climate, marginal riparian sites for maple may 

become less favorable for regeneration and survival of 

young trees. With increased fire frequency, there are likely 

to be increased vegetative regeneration and decreased production of seedlings in some locations. Low-intensity fires 

may promote regeneration by thinning stands and stimulating sprouting. Browsing pressure on maple could increase 

with increased drought, as grasses and forbs desiccate and 

senesce earlier, or are replaced by less palatable species.

Crack Willow (Salix fragilis)

(Southern Greater Yellowstone, 

Uintas and Wasatch Front, Plateaus 

subregions)

Autecology

Crack willow is native to Europe and western Asia, 

where it is found in riparian habitats, usually growing beside rivers and streams and in marshes and wet meadows. 

It grows in similar habitats in the IAP region. The tree 

grows rapidly to a height of 30 to 60 feet, occasionally 

reaching 90 feet. Stem fragments are spread by water, and 

suckers spread locally. Crack willow outcompetes native 

species in riparian sites and forms dense, often pure stands 

along channels (Czarapata 2005), in some cases causing 

blockages, flooding, and structural changes in waterways 

(Weedbusters n.d.). This species is susceptible to wind, ice, 

and snow damage.

Disturbance Interactions

Crack willow responds favorably to periodic flooding. 

Broken twigs and branches can take root readily, enabling 

the species to colonize new areas as broken twigs fall into 

waterways and can be carried some distance downstream. 

Crack willow is assumed to respond to wildfire like most 

willow species, by sprouting from the root crown following top kill.

Historical and Current Conditions

Crack willow is now well established in many riparian 

areas in the IAP region. It was planted for erosion control 

and water uptake in some locations where rapid plant 

growth was desired. Although a nonnative species, crack 

willow is not listed as a noxious weed in any State in the 

IAP region, and it provides habitat for native bird species.

Climate Change Responses

As soil moisture declines in a warmer climate, marginal 

riparian sites for crack willow may become less favorable 

for regeneration and survival of young trees. With increased 

fire frequency, there are likely be increased vegetative 

regeneration and decreased production of seedlings in some 

locations. Even if this species is inhibited somewhat by a 

warmer climate, it is unclear whether native species could 

outcompete it.

Saltcedar (Tamarix spp.)

(Uintas and Wasatch Front, Plateaus 

subregion)

Autecology

Saltcedar (five species) is a nonnative, shrub-like tree 

with numerous large basal branches and a deep, extensive 

Figure 6.6—Saltcedar. 

This species has caused 

widespread damage in 

riparian areas, although 

the recently introduced 

tamarisk beetle is a 

promising biocontrol 

(photo: M. Mejia, Bureau 

of Land Management).

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 147

root system that extends to the water table and is capable of 

extracting water from unsaturated soil layers. Saltcedar is 

found on lakeshores, in riparian floodplain habitats, on seasonally submerged sites, and in fine fluvial substrates (Diggs 

et al. 1999; Welsh et al. 1987). It is competitively superior to 

most native species under dry, saline conditions (Stromberg 

1998; Vandersande et al. 2001), and few species can tolerate 

the understory environment (Brotherson and Winkel 1986) 

(fig. 6.6). Saltcedar is less sensitive to changes in groundwater availability than native riparian trees with which it is 

commonly associated. Greater tolerance of water stress can 

lead to saltcedar dominance on relatively dry riparian sites 

(Horton et al 2001; Smith et al. 1998; Stromberg 1998). 

Seedlings establish as flood waters recede, leaving moist 

deposits of bare soil along riparian corridors. Its small, 

wind- and water-dispersed seeds make it ideally suited as a 

pioneer species on these sites. Saltcedar is also early seral 

after fire (Busch and Smith 1993; Stuever et al. 1997). It is 

listed as a noxious weed in Nevada.

Disturbance Interactions

Evidence for specialized adaptation to wildfire in 

saltcedar remains unclear, despite its efficient postfire 

recovery—it is usually top-killed by fire but sprouts readily 

from the root crown (Busch 1995). Flammability increases 

with accumulation of dead and senescent woody material 

within the plant. When plants burn under high fuel loads, 

fire tends to be more severe, increasing the likelihood of 

killing the root crown of some individuals (Hohlt et al. 

2002). Saltcedar plants can have many stems and high rates 

of stem mortality, resulting in a dense accumulation of 

dead, dry branches. Fire hazard peaks in tamarisk stands at 

10 to 20 years of age (Ohmart and Anderson 1982). With a 

combination of flood suppression, water stress, and invasion 

by saltcedar, wildfires have replaced floods as the primary 

disturbance factor in many southwestern riparian systems.

Historical and Current Conditions

Saltcedar was introduced in North America in the 1800s, 

spreading rapidly in the southwestern and intermountain 

western United States in the 1920s, and altering the ecology and hydrology of riparian areas in this broad region. 

Control of saltcedar has proven to be challenging. Cutting, 

burning, and herbicides have been used in various combinations to reduce saltcedar populations, but treatments need 

to be conducted at large spatial scales to make a significant 

difference (Racher and Mitchell 1999). Biological control 

releases of the nonnative northern tamarisk beetle in the 

Southwest, starting in the 1990s, have caused rapid mortality and decline in vigor in many saltcedar populations (Sher 

and Quigley 2013; Tracy and Robbins 2009). The success of 

the beetle as a biological control agent is aiding the recovery 

of previously suppressed native riparian species. However, 

because the endangered southwestern willow flycatcher 

(Empidonax traillii extimus) now uses saltcedar as habitat, 

concern exists about beetles causing the loss of flycatcher 

habitat, and introduction of beetles has been restricted in 

some locations.

Climate Change Responses

Saltcedar is more drought tolerant and more efficient 

at obtaining water than most native species with which it 

is associated in riparian areas, so it is not expected to be 

vulnerable to a warmer climate. It also sprouts readily after 

wildfire, so it will be able to persist in a warmer climate 

with more fire. Despite efforts to control saltcedar, it would 

appear to be a permanent fixture in many riparian systems 

regardless of climate change.

Climate Change Assessment for 

Forest Vegetation Types

Vegetation types are broad species assemblages used 

to identify the geographic distribution of vegetation in the 

USFS Intermountain Region (table 6.1). These types are 

used to characterize broad landscapes for mapping, planning, and various aspects of vegetation management, but do 

not have specific spatial definitions. Here we describe the 

likely response of forest vegetation types to climate change, 

based on the preceding species descriptions (box 6.3).

Subalpine Pine Forest

Subalpine forests dominated by whitebark pine will be 

highly vulnerable in a warmer climate, primarily because 

this species is already subjected to considerable stress from 

white pine blister rust and mountain pine beetle (Chapter 

8). As a result, populations are in decline and reproductive 

capacity is limited, even when germination conditions are 

suitable. In areas where wildfire has been excluded for many 

decades, subsequent fuel loading may create intense future 

fires that lead to mortality of mature trees. Decline in whitebark pine would have cascading effects on other species that 

eat its seeds, especially Clark’s nutcracker. Subalpine forests 

in which bristlecone pine is a major component are mostly 

in dry locations that could become increasingly stressed by 

low soil moisture, which would reduce growth.

Other subalpine forests are expected to be moderately 

affected by a warmer climate. Limber pine, subalpine fir, 

Engelmann spruce, and white fir may all have increased 

growth in the upper subalpine zone because of a longer, 

snow-free growing season. These species may migrate to 

higher elevations where conditions are suitable, although 

this would be a slow process over many decades. If wildfire 

increases in the subalpine zone, especially where it has been 

excluded in the past, crown fires may be prevalent, quickly 

eliminating mature trees across the landscape. Limber pine 

is challenged by mountain pine beetle and white pine blister 

rust (Chapter 8). Quaking aspen found in subalpine forests 

will be minimally affected by a warmer climate, especially 

compared to aspen at lower elevations.

Chapter 6: Effects of Climate Change on Forest Vegetation
148 USDA Forest Service RMRS-GTR-375. 2018

Subalpine Spruce-Fir Forest

Spruce-fir forest will be moderately vulnerable to a 

warmer climate. Subalpine fir, Engelmann spruce, and blue 

spruce may all have increased growth in the upper subalpine 

zone because of a longer, snow-free growing season, so 

overall productivity could increase. These species may 

migrate to higher elevations where conditions are suitable, 

although this would be a slow process over decades to centuries. If wildfire increases in the subalpine zone, especially 

where it has been excluded in the past, crown fires may 

be prevalent, quickly eliminating mature trees across the 

landscape.

Often a seral species in spruce-fir forests, lodgepole pine 

is a host of mountain pine beetle. Bark beetle outbreaks in 

Engelmann spruce and lodgepole pine are often severe and 

can accelerate succession in areas of high tree mortality 

(Chapter 8). Most subalpine species are fire intolerant, but 

because most lodgepole pine populations have serotinous 

cones and the potential for rapid, dense regeneration, it is 

likely to persist in high-elevation landscapes. Quaking aspen 

in subalpine forests will be minimally affected by a warmer 

climate, especially compared to aspen at lower elevations. 

Where Douglas-fir is a seral species, it could increase in 

distribution and abundance where sufficient soil water is 

available. In addition, Douglas-fir is more fire tolerant than 

any of its associates, so it may become more common if fire 

increases.

Mesic Mixed Conifer Forest

The composition of mesic mixed conifer forest varies 

greatly across the IAP region, with site conditions and 

species assemblages determining vulnerability to climate 

change. In general, late-seral forests may become increasingly susceptible to wildfire, especially where fire has been 

excluded for many decades and fuel loads are elevated. 

Shasta red fir has some fire tolerance, but other firs and 

lodgepole pine are subject to high mortality from intense 

fires. The firs are intolerant of low soil moisture, so as snowpack declines and summer temperature increases, growth 

and productivity will probably decrease, except on north 

aspects.

Douglas-fir, ponderosa pine, and Jeffrey pine have high 

tolerance to fire and can survive mixed- severity fires. 

Therefore, if wildfire extent and intensity increase in the 

future (Chapter 8), these species may become relatively 

more common, and late-seral species may become less 

common. Douglas-fir, ponderosa pine, and Jeffrey pine are 

all tolerant of dry soils, so they are likely to persist across 

the landscape, but their growth rates will probably decrease. 

Lodgepole pine and quaking aspen, which are also common in this forest type, both respond to wildfire with rapid, 

abundant regeneration and are expected to persist across the 

landscape, possibly with increased stress from insects and 

pathogens (Chapter 8).

Dry Mixed Conifer Forest

The composition of dry mixed conifer forest varies 

across the IAP region, with site conditions and species 

assemblages determining vulnerability to climate change. 

Located in lower-elevation montane sites, often on steep 

slopes and shallow soils, this forest type contains some of 

the most drought-tolerant species in the region. Common 

seral species include ponderosa pine, which is fire tolerant 

and regenerates well after fire, and quaking aspen, which 

sprouts heavily and reproduces after fire. The woodland 

species curl-leaf mountain mahogany, Gambel oak, and 

bigtooth maple are drought tolerant, and the latter two 

sprout vigorously after fire. Therefore, a major component 

of mixed conifer forest is expected to be able to cope with 

both drier soils and increased wildfire.

Twoneedle pinyon and singleleaf pinyon are drought 

tolerant, and although intense fire typically kills them, 

they can usually regenerate successfully if competition is 

minimal. Singleleaf pinyon at its lowest elevational extent 

in northern New Mexico has undergone significant mortality 

from prolonged drought and pinyon engraver beetles during 

the past 15 years (Floyd et al. 2009) (Chapter 8), so this species may be susceptible to increasing drought in the future. 

Limber pine, which is considered late seral in these forests, 

is drought tolerant, but may be challenged by mountain pine 

beetle, white pine blister rust, and increasing (usually fatal) 

wildfire (Chapter 8).

Other species such as Douglas-fir and white fir are not 

nearly as drought tolerant as other mixed conifer species. 

Their growth will probably decrease in a warmer climate, 

and although Douglas-fir has relatively high fire tolerance, 

white fir tolerates fire only when it has large-diameter and 

thick bark. In a warmer climate with more fire, it will be 

increasingly difficult for these conifer species to compete 

with early-seral and woodland species that are more tolerant 

of both drought and fire. Therefore, it is likely that earlyseral species will become more dominant in the future, and 

late-seral species will become less common and perhaps 

confined to north aspects and valley bottoms.

Aspen-Mixed Conifer Forest

The composition of this forest type is diverse, distinguished by the prominent role of quaking aspen as an 

early-seral species, often in combination with other conifer 

and woodland species. Response to climate change will 

depend on associated species, ranging from high to low elevation, and from north to south aspects. Increased wildfire 

frequency and extent will be the primary factor determining 

future composition and structure of aspen-mixed conifer 

forests.

Most of the higher-elevation, late-seral species in this 

forest type (firs, Engelmann spruce) are readily killed by 

fire, especially when immature. If wildfire reaches into the 

subalpine zone, it is likely that mature spruce-fir forests 

will become less common, or will persist only on northern 

slopes and in valley bottoms. Therefore, early-seral species, 

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 149

especially aspen, will attain increasing dominance because 

of their ability to resist fire or regenerate after it occurs. 

This will also be true at lower elevations in this forest type, 

where species such as ponderosa pine can readily survive intense fires, and other species such as aspen and Gambel oak 

sprout aggressively after fire. Productivity in these systems 

will probably be lower in a warmer climate with more fire. 

But the more fire-tolerant species will persist, especially in 

drier locations, where they can outcompete species that are 

susceptible to drought and fire.

Persistent Aspen Forest

Quaking aspen can persist for many decades in some 

forests in the IAP region, where productivity is relatively 

low and conifer species do not compete well. Succession 

proceeds slowly in persistent aspen forests, even in the 

absence of wildfire, especially at the higher elevations of 

the subalpine zone. The late-seral species in this forest type 

(firs, spruces) are readily killed by fire, especially when immature. Consequently, if wildfire reaches into the subalpine 

zone, it is likely that mature spruce-fir forests will become 

less common, or will persist only on northern slopes and in 

valley bottoms. Therefore, aspen will maintain dominance 

because of its ability to sprout aggressively after fire.

This will also be true at lower elevations in this forest 

type, where species such as ponderosa pine can readily 

survive intense fires, and other species such as aspen and 

Gambel oak sprout aggressively after fire. Douglas-fir will 

probably persist at some locations on the landscape because 

it has relatively high drought tolerance and fire tolerance. 

Productivity in these systems will probably be lower in a 

warmer climate with more fire. But the more fire-tolerant 

species will persist, especially in drier locations, where they 

can outcompete species that are susceptible to drought and 

fire.

Montane Pine Forest

Ponderosa pine is a dominant species in drier montane 

locations throughout much of the IAP region. Several 

other conifer species are included in this forest type, but 

are rarely as abundant as ponderosa pine, except in wetter 

locations (north aspects, valley bottoms). Ponderosa pine is 

persistent in these systems because it is tolerant of drought 

and very tolerant of fire. Consistently drier soils will cause 

this species to grow slower, but mortality will be rare unless 

drought lasts for several consecutive years and biotic agents 

cause additional stress (Chapter 8).

The expected increase in frequency and extent in a 

warmer climate will favor ponderosa pine over its less 

fire-tolerant competitors, thus ensuring dominance in most 

forests. But limber pine and bristlecone pine will probably 

persist at higher elevations, where fuel loads are typically 

low. An exception might be in areas where fire exclusion has 

increased stand density and fuel loads conducive to crown 

fires, but even then, regeneration of ponderosa pine will 

probably be sufficient to maintain dominance after fire. If 

insects become more prevalent in a warmer climate (Chapter 

8), they could increase stress and mortality in pine species, 

especially during drought periods.

Riparian Forest

Riparian forests are distributed throughout the IAP region, 

adjacent to lakes, streams, seeps, springs, and high water 

tables. Vegetation is extremely diverse, including a broad 

range of conifer and hardwood species. Many of these species occur only in riparian systems, providing habitat for 

numerous wildlife species. In some lower-elevation, drier 

locations, nonnative saltcedar and Russian olive have been 

present, and, in some cases, dominant for many decades, displacing native species and reducing available groundwater.

Riparian systems will be one of the most vulnerable 

vegetation types in a warmer climate because they depend 

on reliable water supply. Higher temperatures will accelerate 

evapotranspiration as soils dry faster and as vegetation takes 

up water earlier and faster during the growing season. Both 

surface and subsurface water flows will decrease if snowpack 

decreases and melts earlier, precluding recharge during dry 

summers (Chapter 4). At a minimum, this will alter vegetation dominance to species that are more tolerant of seasonal 

drought, including ponderosa pine and other deep-rooted 

conifers. Hardwood species that rely on periodic high water 

levels for regeneration could become less common. Riparian 

forests associated with small or transient water sources (e.g., 

springs) will be more susceptible than forests near large 

water sources (e.g., rivers). Low-elevation riparian forests 

near small water sources will be more susceptible than highelevation forests that have long duration of snowpack.

References

Adams, K.R.; Dockter, A.R. [n.d.]. Five years of fire recovery in 

Mesa Verde National Park, USA. https://www.nps.gov/meve/

learn/management/upload/mesa_verde_fire_ecology_adams_

dockter.pdf [Accessed October 30, 2016].

Agee, James K. 1982. True fir management for wilderness, water, 

recreation and wildlife values. In: Oliver, C.D.; Kenady, R.M., 

eds. Proceedings of the biology and management of true fir 

in the Pacific Northwest symposium; 1981 February 24-26; 

Seattle-Tacoma, WA. Contribution 45. Seattle, WA: University 

of Washington, College of Forest Resources: 227–237.

Agee, J.K. 1991. Fire history of Douglas-fir forests in the Pacific 

Northwest. In: Ruggiero, L.F.; Aubry, K.B.; Carey, A.B.; Huff, 

M.H., eds. Wildlife and vegetation of unmanaged Douglas-fir 

forests. Gen. Tech. Rept. PNW-GTR-285. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific Northwest 

Research Station: 25–33.

Aitken, S.N.; Yeaman, S.; Holliday, J.A.; [et al.]. 2008. Adaptation, 

migration or extirpation: Climate change outcomes for tree 

populations. Evolutionary Applications. 1: 95–111.

Alberto, F.J.; Aitken, S.N.; Alía, R.; [et al.]. 2013. Potential for 

evolutionary responses to climate change—evidence from tree 

populations. Global Change Biology. 19: 1645–1661.

Chapter 6: Effects of Climate Change on Forest Vegetation
150 USDA Forest Service RMRS-GTR-375. 2018

Alexander, B.G.; Ronco, F.; Fitzhugh, E.L.; Ludwig, J.A. 1984. 

A classification of forest habitat types of the Lincoln National 

Forest, New Mexico. Gen. Tech. Rep. RM-GTR-104. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Forest and Range Experiment Station. 29 p.

Alexander, R.R.; Shearer, R.C.; Shepperd, W.D. 1990. Abies 

lasiocarpa (Hook.) Nutt. subalpine fir. In: Burns, R.M.; 

Honkala, B.H., eds. Silvics of North America: Volume 1, 

conifers. Washington, DC: U.S. Department of Agriculture, 

Forest Service. 149–166.

Alexander, R.R.; Shepperd, W.D. 1990. Picea engelmannii Parry 

ex Engelm. Engelmann spruce. In: Burns, R.M.; Honkala, B.H., 

eds. Silvics of North America: Volume 1, conifers. Washington, 

DC: U.S. Department of Agriculture, Forest Service: 403–444.

Allen, C.D.; Macalady, A.K.; Chenchouni, H.; [et al.]. 2010. A 

global overview of drought and heat-induced tree mortality 

reveals emerging climate change risks for forests. Forest 

Ecology and Management. 259: 660–684.

Amaranthus, M.P.; Cazares, E.; Perry, D.A. 1999. The role of soil 

organisms in restoration. In: Meurisse, R.T.; Ypsilantis, W.G.; 

Seybold, C., eds. Proceedings: Pacific Northwest forest and 

rangeland soil organism symposium: Organism functions and 

processes, management effects on organisms. Gen. Tech. Rep. 

PNW-GTR-461. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station: 179–189.

Anderegg, W.R.L.; Berry, J.A.; Smith, D.D.; [et al.]. 2012. The 

roles of hydraulic and carbon stress in a widespread climateinduced forest die-off. Proceedings of the National Academy of 

Sciences, USA. 109: 233–237.

Anderson, L.J.; Winterton, A.J. 1996. Germination as a 

determinant of seedling distributions among natural substrates 

in Picea engelmanni (Pinaceae) and Abies lasiocarpa

(Pinaceae). American Journal of Botany. 83: 112–117.

Antos, J.A.; Shearer, R.C. 1980. Vegetation development on 

disturbed grand fir sites, Swan Valley, northwestern Montana. 

Res. Pap. INT-RP-251. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Forest and Range 

Experiment Station.

Araújo, M.B.; Whittaker, R.J.; Ladle, R.J.; Erhard, M. 2005. 

Reducing uncertainty in projections of extinction risk from 

climate change. Global Ecology and Biogeography Letters. 14: 

529–538.

Arno, S.F. 1980. Forest fire history of the northern Rockies. 

Journal of Forestry. 78: 460–465.

Arno, S.F. 1988. Fire ecology and its management implications 

in ponderosa pine forests. In: Ponderosa pine: The species and 

its management, September 1987, Spokane, WA. Pullman, WA 

Washington State University, Extension Service: 133–139.

Arno, S.F. 2010. The Seeley Lake larch: Living link to Indian and 

frontier history. Forest History Today. Spring/Fall 2010: 13–19.

Arno, S.F.; Gruell, G.E. 1983. Fire history at the forest-grassland 

ecotone in southwestern Montana. Journal of Range 

Management. 36: 332–336.

Arno, S.F.; Hammerly, R.P. 1977. Northwest trees. Seattle, WA: 

The Mountaineers. 222 p.

Arno, S.F.; Hoff, R. 1990. Pinus albicaulis Engelm. whitebark 

pine. In: Silvics of North America. Volume 1, conifers. Agric. 

Handbk. Washington, DC: U.S. Department of Agriculture, 

Forest Service: 268–279.

Arno, S.F.; Parsons, D.J.; Keane, R.E. 2000. Mixed-severity fire 

regimes in the northern Rocky Mountains: Consequences 

of fire exclusion and options for the future. In: Wilderness 

science in a time of change conference, volume 5: Wilderness 

ecosystems, threat and management, Missoula, MT, May 23-27, 

1999. Proceedings RMRS-P-15-Vol 5. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station: 225–232.

Aston, I.W. 2010. Observed and projected ecological response to 

climate change in the Rocky Mountains and Upper Columbia 

Basin: A synthesis of current scientific literature. Nat. Res. Rep. 

NPS/ROMN/NPR-2010/220. Fort Collins, CO: National Park 

Service. 98 p.

Atzet, T.; Wheeler, D.L. 1982. Historical and ecological 

perspectives on fire activity in the Klamath geological province 

of the Rogue River and Siskiyou National Forests. Portland, 

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

Northwest Region. 16 p.

Auble, G.T.; Scott, M.L. 1998. Fluvial disturbance patches and 

cottonwood recruitment along the upper Missouri River, 

Montana. Wetlands. 18: 546–556.

Austin, Dennis D. 1987. Plant community changes within a mature 

pinyon-juniper woodland. The Great Basin Naturalist. 47: 

96–99.

Axelson, J.N.; Alfaro, R.I.; Hawkes, B.C. 2009. Influence of 

fire and mountain pine beetle on the dynamics of lodgepole 

pine stands in British Columbia, Canada. Forest Ecology and 

Management. 257: 1874–1882.

Bachelet, D.; Neilson, R.P.; Hickler, T.; [et al.]. 2003. Simulating 

past and future dynamics of natural ecosystems in the United 

States. Global Biogeochemical Cycles. 17: 1045.

Baker, W.L. 1988. Size-class structure of contiguous riparian 

woodlands along a Rocky Mountain river. Physical Geography. 

9: 1–14.

Baker, W.L. 1989. A review of models of landscape change. 

Landscape Ecology. 2: 111–133.

Baker, W.L. 1990. Climatic and hydrologic effects on the 

regeneration of Populus angustifolia James along the Animas 

River, Colorado. Journal of Biogeography. 17: 59–73.

Baker, W.L. 1992. Structure, disturbance, and change in the 

bristlecone pine forests of Colorado, U.S.A. Arctic and Alpine 

Research. 24: 17–26.

Barbour, M.G. 1988. Californian upland forests and woodlands. In: 

Barbour, M.G.; Billings, W.D., eds. North American terrestrial 

vegetation. New York, NY: Cambridge University Press: 

131–164.

Barbour, M.G.; Berg, N.H.; Kittel, G.F.; Kunz, M.E. 1991. 

Snowpack and the distribution of a major vegetation ecotone in 

the Sierra Nevada of California. Journal of Biogeography. 18: 

141–149.

Bare, B.B. 1982. The economics of true fir management. 

In: Oliver, C.D.; Kenady, R.M., eds. Proceedings of the 

biology and management of true fir in the Pacific Northwest 

symposium; 1981 February 24-26; Seattle-Tacoma. Contrib. 

45. Seattle, WA: University of Washington, College of Forest 

Resources: 9–14.

Barker, P.A. 1977. Canyon maple—A colorful mountaineer. 

American Forests. 83: 22–25.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 151

Barney, M.A.; Frischknecht, N.C. 1974. Vegetation changes 

following fire in the pinyon-juniper type of west-central Utah. 

Journal of Range Management. 27: 91–96.

Barrett, S.W.; Arno, S.F. 1991. Classifying fire regimes and 

defining their topographic controls in the Selway-Bitterroot 

Wilderness. In: Andrews, P.L.; Potts, D.F., eds. Proceedings of 

the 11th conference on fire and forest meteorology. Missoula, 

MT: Society of American Foresters: 299–307.

Barrett, S.W.; Arno, S.F.; Key, C.H. 1991. Fire regimes of western 

larch-lodgepole pine forests in Glacier National Park, Montana. 

Canadian Journal of Forest Research. 21: 1711–1720.

Barro, S.C.; Wohlgemuth, P.M.; Campbell, A.G. 1989. Postfire interactions between riparian vegetation and channel 

morphology and the implications for stream channel 

rehabilitation choices. In: Abell, D.L., tech. coord. Proceedings 

of the California riparian systems conference: Protection, 

management, and restoration for the 1990’s. Gen. Tech. Rep. 

PSW-GTR-110. Berkeley, CA: U.S. Department of Agriculture, 

Forest Service, Pacific Southwest Forest and Range Experiment 

Station: 51–53.

Bartlein, P.J.; Whitlock, C.; Shafer, S.L. 1997. Future climate in 

the Yellowstone National Park region and its potential impact 

on vegetation. Conservation Biology. 11: 782–792.

Bartos, D. 1998. Aspen, fire and wildlife. Spokane, WA: The 

Wildlife Society, Northwest Section, Oregon and Washington 

Chapters: 44–48.

Bartos, D.L. 1978. Modeling plant succession in aspen ecosystems. 

In: Hyder, D.N., ed. Proceedings of the first international 

rangeland congress. Denver, CO: Society for Range 

Management: 208–211.

Battles, J.J.; Robards, T.; Das, A.; [et al.]. 2008. Climate 

change impacts on forest growth and tree mortality: A datadriven modeling study in the mixed conifer forest of the 

Sierra Nevada, California. Climatic Change. 87 (Suppl. 1): 

S193–S213.

Baumeister, D.; Callaway, R.M. 2006. Facilitation by Pinus flexilis

during succession: A hierarchy of mechanisms benefits other 

plant species. Ecology. 87: 1816–1830.

Beasley, R.S.; Klemmedson, J.O. 1973. Recognizing site adversity 

and drought-sensitive trees in stands of bristlecone pine (Pinus 

longaeva). Economic Botany 27: 141–146.

Beaufait, W.R.; Hardy, C.E.; Fischer, W.C. 1977. Broadcast 

burning in larch-fir clearcuts: the Miller Creek-Newman Ridge 

study. Res. Pap. INT-RP-175. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Forest and Range 

Experiment Station. 53 p.

Bega, Robert V., tech. coord. 1978. Diseases of Pacific Coast 

conifers. Agric. Handbk 521. Washington, DC: U.S. 

Department of Agriculture. 206 p.

Bell, D.M.; Bradford, J.B.; Lauenroth, W.K. 2014. Early indicators 

of change: Divergent climate envelopes between tree life stages 

imply range shifts in the western United States. Global Ecology 

and Biogeography. 23: 168–180.

Bentz, B.J.; Duncan, J.P.; Powell, J.A. 2016. Elevational shifts in 

thermal suitability for mountain pine beetle population growth 

in a changing climate. Forestry. 89: 271–283.

Bentz, B.J.; Jönsson, A.M. 2015. Modeling bark beetle responses 

to climate change. In: Vega, F.; Hofstetter, R., eds. Bark beetles, 

biology and ecology of native and invasive species. San Diego, 

CA: Academic Press: 533–554.

Bentz, B.J.; Régnière, J.; Fettig, C.J.; [et al.]. 2010. Climate change 

and bark beetles of the western United States and Canada: 

direct and indirect effects. BioScience. 60: 602–613.

Beschta, R.L.; Ripple, W.J. 2005. Rapid assessment of riparian 

cottonwood recruitment: Middle Fork John Day River, 

northeastern Oregon. Ecological Restoration. 23: 150–156.

Bigler, C.; Kulakowski, D.; Veblen, T.T. 2005. Multiple 

disturbance interactions and drought influence fire severity in 

Rocky Mountain subalpine forests. Ecology. 86: 3018–3029.

Blodgett, J.T.; Sullivan, K.F. 2004. First report of white pine blister 

rust on Rocky Mountain bristlecone pine. Plant Disease. 88: 

311.

Bollenbacher, B. 2012. Characteristics of primary tree species 

in the Northern Region. Missoula, MT: U.S. Department of 

Agriculture, Forest Service. Northern Region. Various pagings.

Bonan, G.B. 2008. Forests and climate change: forcings, 

feedbacks, and the climate benefits of forests. Science. 320: 

1444–1449.

Borman, M.M.; Larson, L.L. 2002. Cottonwood: Establishment, 

survival, and stand characteristics. Corvallis, OR: Oregon State 

University, Extension Service. 12 p.

Bradley, A.F.; Noste, N.V.; Fischer, W.C. 1992. Fire ecology of 

forests and woodlands in Utah. Gen. Tech. Rep. INT-287. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station. 128 p.

Breshears, D.D.; Myers, O.B.; Meyer, C.W.; [et al.]. 2009. 

Tree die-off in response to global change-type drought: 

mortality insights from a decade of plant water potential 

measurements. Frontiers in Ecology and the Environment. 7: 

185–189.

Broadhurst, L.M.; Lowe, A.; Coates, D.J.; [et al.]. 2008. Seed 

supply for broadscale restoration: maximizing evolutionary 

potential. Evolutionary Applications. 1: 587–597.

Brotherson, J.D. 1990. Mineral-nutrient relationships of the 

mountain mahoganies (Cercocarpus). In: Johnson, K.L., ed. 

Proceedings, 5th Utah shrub ecology workshop: The genus 

Cercocarpus; 1988 July 13-14; Logan, UT. Logan, UT: Utah 

State University, College of Natural Resources: 43–60.

Brotherson, J.D.; Winkel, V. 1986. Habitat relationships of 

saltcedar (Tamarix ramosissima). The Great Basin Naturalist. 

46: 535–541.

Brown, J.K. 1973. Fire cycles and community dynamics of 

lodgepole pine forests. In: Management of lodgepole pine 

ecosystems. Pullman, WA: Washington State University Press: 

23–55.

Brown, J.K. 1996. Fire effects on aspen and cottonwood. In: 

Aspen and cottonwood in the Blue Mountains workshop. 1996, 

April 2–4. La Grande, OR: Blue Mountains Natural Resources 

Institute. 11 p.

Brown, P.M.; Schoettle, A.W. 2008. Fire and stand history in two 

limber pine (Pinus flexilis) and Rocky Mountain bristlecone 

pine (Pinus aristata) stands in Colorado. International Journal 

of Wildland Fire. 17: 339–347.

Brunelle, A.; Whitlock, C.; Bartlein, P.; Kipfmueller, K. 2005. 

Holocene fire and vegetation along environmental gradients in 

the Northern Rocky Mountains. Quaternary Science Reviews. 

24: 2281–2300.

Bugmann, H. 2001. A review of forest gap models. Climatic 

Change. 51: 259–305.

Chapter 6: Effects of Climate Change on Forest Vegetation
152 USDA Forest Service RMRS-GTR-375. 2018

Bugmann, H.; Cramer, W. 1998. Improving the behavior of forest 

gap models along drought gradients. Forest Ecology and 

Management. 103: 247–263.

Bunderson, E.D.; Weber, D.J.; Davis, J.N. 1985. Soil mineral 

composition and nutrient uptake in Juniperus osteosperma in 

17 Utah sites. Soil Science. 139: 139–148.

Burns, R.M.; Honkala, B.H. 1990. Silvics of North America: 

Volume 1, conifers. Washington, DC: U.S. Department of 

Agriculture, Forest Service. 675 p.

Burwell, T. 1998. Successional patterns of the lower montane 

treeline, eastern California. Madroño. 45: 12–16.

Busch, D.E. 1995. Effects of fire on southwestern riparian plant 

community structure. The Southwestern Naturalist. 40: 

259–267.

Busch, D.E.; Smith, S.D. 1993. Effects of fire on water salinity 

relations of riparian woody taxa. Oecologia. 94: 186–194.

Butler, D.R. 1986. Conifer invasion of subalpine meadows, central 

Lemhi Mountains, Idaho. Northwest Science. 60: 166–173.

Callaway, R.; Sala, A.; Carey, E.; Keane, R.E. 1998. Replacement 

of whitebark pine by subalpine fir: The consequences for stand 

carbon, water, and nitrogen cycles. Contract Completion Rep. 

Res. Joint Venture Agree. INT-95086-RJVA. Missoula, MT: 

U.S. Department of Agriculture, Forest Service, Fire Sciences 

Laboratory. Various paging.

Campbell, R.B.; Bartos, D. 2001. Aspen ecosystems—Objectives 

for sustaining biodiversity. In: Sustaining aspen ecosystems in 

western landscapes, proceedings. RMRS-P-18. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 299–306.

Carroll, A.L.; Taylor, S.W.; Régnière, J.; Safranyik, L. 2003. 

Effects of climate change on range expansion by the mountain 

pine beetle in British Columbia. In: Shore, T.L.; Brooks, J.E.; 

Stone, J.E., eds. Mountain pine beetle symposium: Challenges 

and solutions. Victoria, British Columbia, Canada: Natural 

Resources Canada, Canadian Forest Service: 223–231.

Cayan, D.R.; Dettinger, M.D.; Kammerdiener, S.A.; [et al.]. 2001. 

Changes in the onset of spring in the western United States. 

Bulletin of the American Meteorological Society. 82: 399–415.

Chapman, T.B.; Veblen, T.T.; Schoennagel, T. 2012. 

Spatiotemporal patterns of mountain pine beetle activity in the 

southern Rocky Mountains. Ecology. 93: 2175–2185.

Chhin, S.; Hogg, E.T.; Lieffers, V J.; Huang, S. 2008. Potential 

effects of climate change on the growth of lodgepole pine 

across diameter size classes and ecological regions. Forest 

Ecology and Management. 256: 1692–1703.

Chmura, D.J.; Anderson, P.D.; Howe, G.T.; [et al.]. 2011. Forest 

responses to climate change in the northwestern United States: 

Ecophysiological foundations for adaptive management. Forest 

Ecology and Management. 261: 1121–1142.

Cissel, J.H.; Swanson, F.J.; McKee, W.A.; Burditt, A.L. 1994. 

Using the past to plan the future in the Pacific Northwest. 

Journal of Forestry. 92: 30–31, 46.

Clark, J.S.; Carpenter, S.R.; Barber, M.; [et al.]. 2001. Ecological 

forecasts: An emerging imperative. Science. 293: 657–660.

Clary, W.P.; Tiedemann, A.R. 1986. Distribution of biomass within 

small tree and shrub form Quercus gambelii stands. Forest 

Science. 32: 234–242.

Coop, J.D.; Schoettle, A.W. 2009. Regeneration of Rocky 

Mountain bristlecone pine (Pinus aristata) and limber pine 

(Pinus flexilis) three decades after stand-replacing fires. Forest 

Ecology and Management. 257: 893–903.

Coops, N.C.; Waring, R.H. 2011. A process-based approach to 

estimate lodgepole pine (Pinus contorta Dougl.) distribution in 

the Pacific Northwest under climate change. Climatic Change. 

105: 313–328.

Cramer, W.; Bondeau, A.; Woodward, F.I.; [et al.]. 2001. Global 

response of terrestrial ecosystem structure and function to CO2

and climate change: results from six dynamic global vegetation 

models. Global Change Biology. 7: 357–373.

Crane, M.F. 1982. Fire ecology of Rocky Mountain Region forest 

habitat types. Final rep. contract 43-83X9-1-884. Missoula, 

MT: U.S. Department of Agriculture, Forest Service, Northern 

Region. 272 p.

Creeden, E.P.; Hicke, J.A.; Buotte, P.C. 2014. Climate, weather, 

and recent mountain pine beetle outbreaks in the western 

United States. Forest Ecology and Management. 312: 239–251.

Crimmins, S.M.; Dobrowski, S.Z.; Greenberg, J.A.; [et al.]. 2011. 

Changes in climatic water balance drive downhill shifts in plant 

species’ optimum elevations. Science. 331: 324–327.

Critchfield, W.B.; Allenbaugh, G.L. 1969. The distribution of 

Pinaceae in and near northern Nevada. Madroño. 20: 12–25.

Cronquist, A.; Holmgren, N.H.; Holmgren, P.K. 1997. 

Intermountain flora: Vascular plants of the Intermountain West, 

U.S.A. volume 3, part A: Subclass Rosidae (except Fabales). 

New York. NY: New York Botanical Garden. 446 p.

Cushman, S.A.; McKenzie, D.; Peterson, D.L.; [et al.]. 2007. 

Research agenda for integrated landscape modeling. Gen. Tech. 

Rep. RMRS-GTR-194. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 

50 p.

Czarapata, E.J. 2005. Invasive plants of the upper Midwest: An 

illustrated guide to their identification and control. Madison, 

WI: University of Wisconsin Press. 236 p.

Dahms, C.W.; Geils, B.W., tech. eds. 1997. An assessment of 

forest ecosystem health in the Southwest. Gen. Tech. Rep. RMGTR-295. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Forest and Range Experiment 

Station. 97 p.

Dale, V. H.; Joyce, L. A.; McNulty, S.; Neilson, R.P.; [et al.]. 

2001. Climate change and forest disturbances. BioScience 51: 

723–734.

Davis, J.N. 1990. General ecology, wildlife use, and management 

of the mountain mahoganies in the Intermountain West. 

In: Johnson, K.L., ed. Proceedings, 5th Utah shrub ecology 

workshop: The genus Cercocarpus; 1988 July 13-14; Logan, 

UT. Logan, UT: Utah State University, College of Natural 

Resources: 1-13.

Davis, M.B. 1989. Lags in vegetation response to greenhouse 

warming. Climatic Change. 15: 75–82.

Davis, M.B.; Shaw, R.G. 2001. Range shifts and adaptive 

responses to Quaternary climate change. Science. 292: 

673–679.

Davis, M.B.; Shaw, R.G.; Etterson, J.R. 2005. Evolutionary 

responses to changing climates. Ecology. 86: 1704–1714.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 153

DeBell, D.S. 1990. Populus trichocarpa Torr. and Gray black 

cottonwood. In: Burns, R.M.; Honkala, B.H., eds. Silvics of 

North America: Volume 2 hardwoods. Washington, DC: U.S. 

Department of Agriculture, Forest Service: 1322–1355.

DeNitto, G. 2013. FHP annual report for the Northern Region. 

Rep. R1-FHP-2013. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Northern Region, Forest Health 

and Protection. Various paging.

Devine, W.; Aubry, C.; Bower, A.; [et al.]. 2012. Climate change 

and forest trees in the Pacific Northwest: A vulnerability 

assessment and recommended actions for National Forests. 

Olympia, WA: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Region. 102 p.

Dick-Peddie, W.A.; Moir, W.H. 1970. Vegetation of the Organ 

Mountains, New Mexico. Sci. Ser. 4. Fort Collins, CO: 

Colorado State University, Range Science Department. 28 p.

Dieter, C.D.; McCabe, T.R. 1989. Habitat use by beaver along 

the Big Sioux River in eastern South Dakota. In: Gresswell, 

R.E.; Barton, B.A.; Kershner, J.L., eds. Practical approaches 

to riparian management: An educational workshop. BLMMIT-PT-89-0001-4351. Billings, MT: U.S. Department of the 

Interior, Bureau of Land Management, Montana State Office: 

135–140.

Diggs, G.M.; Lipscomb, B.L.; O‘Kennon, R.J. 1999. Illustrated 

flora of north-central Texas. Sida Bot. Misc. 16. Fort Worth, 

TX: Botanical Research Institute of Texas. 1640 p.

Dina, S.J.; Klikoff, L.G. 1973. Carbon dioxide exchange by several 

streamside and scrub oak community species of Red Butte. The 

American Midland Naturalist. 89: 70–80.

Disalvo, A.C.; Hart, S.C. 2002. Climatic and stream-flow 

controls on tree growth in a western montane riparian forest. 

Environmental Management. 30: 678–691.

Dwyer, Don D.; Pieper, Rex D. 1967. Fire effects on blue gramapinyon-juniper rangeland in New Mexico. Journal of Range 

Management. 20: 359–362.

Easterling, D.R.; Meehl, G.A.; Parmesan, C.; [et al.]. 2000. 

Climate extremes: Observations, modeling, and impacts. 

Science. 289: 2068–2074.

Egan, D.; Howell, E.A., eds. 2001. The historical ecology 

handbook. Washington, DC: Island Press. 469 p.

Ehleringer, J.R.; Arnow, L.A.; Arnow, T.; [et al.]. 1992. Red Butte 

Canyon Research Natural Area: History, flora, geology, climate, 

and ecology. The Great Basin Naturalist. 52: 95–121.

Eisenberg, C.; Seager, S.T.; Hibbs, D.E. 2013. Wolf, elk, and aspen 

food web relationships: context and complexity. Forest Ecology 

and Management. 299: 70–80.

Etterson, J.R.; Shaw, R.G. 2001. Constraint to adaptive evolution 

in response to global warming. Science. 294: 151–154.

Evans, R.A. 1988. Management of pinyon-juniper woodlands. 

Gen. Tech. Rep. INT-GTR-249. Ogden, UT: U.S. Department 

of Agriculture, Forest Service, Intermountain Research Station. 

218 p.

Everett, R.L. 1985. Great Basin pinyon and juniper communities 

and their response to management. In: Symposium on the 

cultural, physical and biological characteristics of range 

livestock industry in the Great Basin: Proceedings, 38th annual 

meeting of the Society for Range Management; 1985 February 

11-14; Salt Lake City, UT. Denver, CO: Society for Range 

Management: 53–62.

Everett, R.L. 1987. Allelopathic effects of pinyon and juniper litter 

on emergence and growth of herbaceous species. In: Frasier, 

G.W.; Evans, R.S., comps. Proceedings, symposium on seed 

and seedbed ecology of rangelands. Washington, DC: U.S. 

Department of Agriculture, Agricultural Research Service: 

62–67.

Everett, R.L.; Koniak, S. 1981. Understory vegetation in fully 

stocked pinyon-juniper stands. The Great Basin Naturalist. 41: 

467–475.

Everett, R.L.; Sharrow, S.H.; Meeuwig, R.O. 1983. Pinyonjuniper woodland understory distribution patterns and species 

associations. Bulletin of the Torrey Botanical Club. 110: 

454–463.

Falk, D.A.; Miller, C.; McKenzie, D.; Black, A.E. 2007. Crossscale analysis of fire regimes. Ecosystems. 10: 809–823.

Fechner, G.H. 1985. Silvical characteristics of blue spruce. Gen. 

Tech. Rep. RM-GTR-117. Fort Collins, CO: U.S. Department 

of Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station. 117 p.

Fechner, G.H. 1990. Picea pungens Engelm. blue spruce. In: 

Burns, R.M.; Honkala, B.H., tech. coords. Silvics of North 

America: Volume 1, conifers. Agric. Handbk. 654. Washington, 

DC: U.S. Department of Agriculture, Forest Service: 238–249.

Feldman, R.; Tomback, D.F.; Koehler, J. 1999. Cost of mutualism: 

Competition, tree morphology, and pollen production in limber 

pine clusters. Ecology. 80: 324–329.

Ferguson, D.E.; Johnson, F.D. 1996. Classification of grand fir 

mosaic habitats. Gen. Tech. Rep. INT-GTR-337. Ogden, UT: 

U.S. Department of Agriculture, Forest Service, Intermountain 

Research Station.

Ferry, G.W.; Clark, R.G.; Montgomery, R.E.; [et al.]. 1995. Altered 

fire regimes within fire-adapted ecosystems. In: LaRoe, E.T.; 

Farris, G.S.; Puckett, C.E. Our living resources: A report to the 

nation on the distribution, abundance, and health of U.S. plants, 

animals, and ecosystems. Washington, DC: U.S Department of 

the Interior, National Biological Service: 222–224.

Fiedler, C.E.; Lloyd, D.A. 1995. Autecology and synecology of 

western larch. In: Schmidt, W.C.; McDonald K.J., comps. 

Proceedings, symposium on ecology and management of 

Larix forests: A look ahead. Gen. Tech. Rep. GTR-INT-319. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station: 118–122.

Fins, L.; Byler, J.; Ferguson, D.; [et al.]. 2002. Return of the giants: 

restoring white pine ecosystems by breeding and aggressive 

planting of blister rust-resistant white pines. Journal of Forestry. 

100: 20–26.

Fischer, W.C.; Bradley, A.F. 1987. Fire ecology of western 

Montana forest habitat types. Gen. Tech. Rep. INT-GTR-223. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station.

Fischer, W.C.; Clayton, B.D. 1983. Fire ecology of Montana forest 

habitat types east of the Continental Divide. Gen. Tech. Rep. 

INT-GTR-141. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Forest and Range Experiment 

Station.

Fitzhugh, E.L.; Moir, W.H.; Ludwig, J.A.; Ronco, F. 1987. Forest 

habitat types in the Apache, Gila, and part of the Cibola 

National Forests, Arizona and New Mexico. Gen. Tech. 

Rep. RM-GTR-145. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and Range 

Experiment Station.

Chapter 6: Effects of Climate Change on Forest Vegetation
154 USDA Forest Service RMRS-GTR-375. 2018

Flannigan, M.D.; Krawchuk, M.A.; de Groot, W.J.; [et al.]. 2009. 

Implications of changing climate for global wildland fire. 

International Journal of Wildland Fire. 18: 483–507.

Flora of North America Association [FNAA]. 2009. Flora of 

North America: The flora. http://www.fna.org/FNA [Accessed 

October 26, 2016].

Floyd, M.L.; Hanna, D.D.; Romme, W.H. 2004. Historical and 

recent fire regimes in piñon-juniper woodlands on Mesa 

Verde, Colorado, USA. Forest Ecology and Management. 198: 

269–289.

Floyd, M.L.; Romme, W.H.; Hanna, D.D. 2000. Fire history and 

vegetation pattern in Mesa Verde National Park, Colorado, 

USA. Ecological Applications. 10: 1666–1680.

Floyd, M.L.; Clifford, M.; Cobb, N.S.; [et al.]. 2009. Relationship 

of stand characteristics to drought-induced mortality in 

three Southwestern piñon-juniper woodlands. Ecological 

Applications. 19: 1223–1230.

Foiles, M.W.; Graham, R.T.; Olson, D.F. 1990. Abies grandis

(Dougl. ex D. Don) Lindl. grand fir. In: Burns, R.M.; Honkala, 

B.H., eds. Silvics of North America: Volume 1, conifers. 

Washington, DC: U.S. Department of Agriculture, Forest 

Service: 132–155.

Fowells, H.A., comp. 1965. Silvics of forest trees of the United 

States. Agric. Handbk. 271. Washington, DC: U.S. Department 

of Agriculture.

Franklin, J.F.; Swanson, F.J.; Harmon, M.E.; [et al.]. 1991. Effects 

of global climatic change on forests in northwestern North 

America. The Northwest Environmental Journal. 7: 233–254.

Frey, B.R.; Lieffers, V.J.; Hogg, E.H.; Landhäusser, S.M. 2004. 

Predicting landscape patterns of aspen dieback: Mechanisms 

and knowledge gaps. Canadian Journal of Forest Research. 34: 

1379–1390.

Fryer, J.L. 2014. Alnus rhombifolia. In: Fire Effects Information 

System. Missoula, MT: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station, Missoula Fire 

Sciences Laboratory. http://www.fs.fed.us/database/feis/plants/

tree/alnrho/all.html [Accessed September 6, 2017].

Geiszler, D.R.; Gara, R.I.; Driver, C.H.; [et al.]. 1980. Fire, fungi, 

and beetle influences on a lodgepole pine ecosystem of southcentral Oregon. Oecologia. 46: 239–243.

Gillette, N.E.; Wood, D.L.; Hines, S.J.; [et al.]. 2014. The once and 

future forest: Consequences of mountain pine beetle treatment 

decisions. Forest Science. 60: 527–538.

Gom, L.A.; Rood, S.B. 1999. Fire induces clonal sprouting 

of riparian cottonwoods. Canadian Journal of Botany. 77: 

1604–1616.

Gordon, D.T. 1973. Damage from wind and other causes in mixed 

white fir-red fir stands adjacent to clearcuttings. USDA Forest 

Service, Res. Pap. PSW-RP-90. Berkeley, CA: U.S. Department 

of Agriculture, Forest Service, Pacific Southwest Forest and 

Range Experiment Station.

Gottfried, G.J.; Folliott, P.F.; DeBano, L.F. 1995. Forests and 

woodlands of the sky islands: Stand characteristics and 

silvicultural prescriptions. In: DeBano, L.F.; Ffolliott, P.F.; 

Ortega-Rubio, A.; [et al.], tech. coords. Biodiversity and 

management of the Madrean Archipelago: The sky islands 

of southwestern United States and northwestern Mexico: 

Proceedings; September 19-23, 1994; Tucson, AZ. Gen. Tech. 

Rep. RM-GTR-264. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and Range 

Experiment Station: 152–164.

Gottfried, G.J.; Severson, K.E. 1993. Distribution and 

multiresource management of piñon-juniper woodlands in the 

southwestern United States. In: Aldon, E.F.; Shaw, D.W., tech. 

coords. Managing piñon-juniper ecosystems for sustainability 

and social needs: Proceedings; April 26-30, 1993; Santa Fe, 

NM. Gen. Tech. Rep. RM-GTR-236. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Forest and Range Experiment Station: 108–116.

Gower, S.T.; Kloeppel, B.D.; Reich, P.B. 1995. Carbon, nitrogen, 

and water use by larches and co-occurring evergreen conifers. 

In: Schmidt, W.C.; McDonald, K.J., eds. Ecology and 

management of Larix forests: A look ahead. October 5–9, 1992, 

Whitefish, MT. Gen. Tech. Rep. INT-GTR-319. Ogden, UT: 

U.S. Department of Agriculture, Forest Service, Intermountain 

Region: 110–117.

Graham, R.T. 1990. Pinus monticola Dougl. ex D. Don western 

white pine. In: Burns, R.M.; Honkala, B.H., eds. Silvics of 

North America: Volume 1, conifers. Washington DC: U.S. 

Department of Agriculture, Forest Service: 348–353.

Gray, L.K.; Hamann, A. 2013. Tracking suitable habitat for tree 

populations under climate change in western North America. 

Climatic Change. 117: 289–303.

Gruell, G.E. 1982. Fire’s influence on vegetative succession—

wildlife habitat implications and management opportunities. 

In: Eustace, C.D., comp. Proceedings, Montana Chapter of the 

Wildlife Society. Billings, MT: The Wildlife Society: 43–50.

Gruell, G.E. 1986. Post-1900 mule deer irruptions in the 

Intermountain West: Principle cause and influences. Gen. 

Tech. Rep. INT-GTR-206. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station.

Gruell, George E. 1999. Historical and modern roles of fire 

in pinyon-juniper. In: Monsen, S.B.; Stevens, R., comps. 

Proceedings: Ecology and management of pinyon-juniper 

communities within the Interior West: Sustaining and restoring 

a diverse ecosystem; September 15-18, 1997; Provo, UT. Proc. 

RMRS-P-9. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station: 24–28.

Gruell, G.; Bunting, S.; Neuenschwander, L. 1985. Influence 

of fire on curlleaf mountain-mahogany in the Intermountain 

West. In: Lotan, J.E.; Brown, J.K., comps. Fire‘s effects on 

wildlife habitat, symposium proceedings; 1984 March 21; 

Missoula, MT. Gen. Tech. Rep. INT-GTR-186. Ogden, UT: 

U.S. Department of Agriculture, Forest Service, Intermountain 

Research Station: 58–72.

Gustafson, E. 2013. When relationships estimated in the past 

cannot be used to predict the future: Using mechanistic models 

to predict landscape ecological dynamics in a changing world. 

Landscape Ecology. 28: 1429–1437.

Gworek, J.R.; Vander Wall, S.B.; Brussard, P.F. 2007. Changes 

in biotic interactions and climate determine recruitment of 

Jeffrey pine along an elevation gradient. Forest Ecology and 

Management. 239: 57–68.

Habeck, J.R. 1990. Old-growth ponderosa pine-western larch 

forests in western Montana: Ecology and management. The 

Northwest Environmental Journal. 6: 271–292.

Haeussler, S.; Coates, D. 1986. Autecological characteristics 

of selected species that compete with conifers in British 

Columbia: A literature review. Land Manage. Rep. 33. Victoria, 

BC, Canada: Ministry of Forests, Information Services Branch.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 155

Hagle, S.K.; Gibson, K.; Tunnock, S. 2003. Field guide to diseases 

and insect pests of northern and central Rocky Mountain 

conifers. Rep. R1-03-08. Missoula, MT: U.S. Department 

of Agriculture, Forest Service, State and Private Forestry, 

Northern Region and Intermountain Region.

Hall, F.C. 1973. Plant communities of the Blue Mountains in 

eastern Oregon and southeastern Washington. R6 Area Guide 

3-1. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Region.

Hall, J.B.; Hansen, P.L. 1997. A preliminary riparian habitat type 

classification system for the Bureau of Land Management 

districts in southern and eastern Idaho. Tech. Bull. 97-11. 

Boise, ID: U.S. Department of the Interior, Bureau of Land 

Management.

Hamann, A.; Wang, T. 2006. Potential effects of climate change 

on ecosystem and tree species distribution in British Columbia. 

Ecology. 87: 2733–2786.

Hamrick, J.L. 2004. Response of forest trees to global 

environmental changes. Forest Ecology and Management. 197: 

323–335.

Hamrick, J.L.; Godt, M.J.; Sherman-Broyles, S.L. 1992. Factors 

influencing levels of genetic diversity in woody plant species. 

New Forests 6: 95–124.

Hann, W.J.; Jones, J.L.; Karl, M.G.; [et al.]. 1997. Landscape 

dynamics of the basin. In: Quigley, T.M.; Arbelbide, S.J., 

eds. An assessment of ecosystem components in the Interior 

Columbia Basin and portions of the Klamath and Great Basins: 

Volume II. Gen. Tech. Rep. PNW-GTR-405. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific Northwest 

Research Station: 338–1055.

Hanninen, H. 1995. Effects of climatic change on trees from 

cool and temperate regions: An ecophysiological approach to 

modelling of bud burst phenology. Canadian Journal of Botany. 

73: 183–199.

Hansen, A.J.; Neilson, R.P.; Dale, V.H.; [et al.]. 2001. Global 

change in forests: Responses of species, communities, and 

biomes. BioScience. 51: 765–779.

Hansen, A.J.; Phillips, L.B. 2015. Which tree species and biome 

types are most vulnerable to climate change in the US Northern 

Rocky Mountains? Forest Ecology and Management. 338: 

68–83.

Hansen, H.P. 1949. Post-glacial forests in west central Alberta, 

Canada. Torrey Botanical Club Bulletin. 76: 278–289.

Hansen, P.L.; Hoffman, G.R. 1988. The vegetation of the Grand 

River/Cedar River, Sioux, and Ashland Districts of the Custer 

National Forest: A habitat type classification. Gen. Tech. 

Rep. RM-GTR-157. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and Range 

Experiment Station.

Hansen, P.L.; Pfister, R.D.; Boggs, K.; Cook, B.J.; Joy, J.; 

Hinckley, D.K. 1995. Classification and management of 

Montana’s riparian and wetland sites. Misc. Pub. 54. Missoula, 

MT: University of Montana, School of Forestry, Montana 

Forest and Conservation Experiment Station.

Hardy, C.C.; Keane, R.E.; Stewart, C.A. 2000. Ecosystem-based 

management in the lodgepole pine zone. In: Smith, H.Y., ed. 

The Bitterroot ecosystem management research project: What 

we have learned. Missoula, MT, May 18–20, 1999. Proceedings 

RMRS-P-17. Fort Collins CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station: 31–35.

Harper, K. T.; Sanderson, S. C.; McArthur, E. D. 1992. Riparian 

ecology in Zion National Park, Utah. In: Clary, W.P.; McArthur, 

E.D.; Bedunah, D.; Wambolt, C.L., comps. Proceedings, 

symposium on ecology and management of riparian shrub 

communities; May 29-31, 1991; Sun Valley, ID. Gen. 

Tech. Rep. INT-GTR-289. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station: 

32–42.

Harper, K.T.; Wagstaff, F.J.; Kunzler, L.M. 1985. Biology 

management of the Gambel oak vegetative type: A literature 

review. Gen. Tech. Rep. INT-GTR-179. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station.

Harrington, C.A.; Gould, P.J.; St. Clair, J.B. 2010. Modeling the 

effects of winter environment on dormancy release of Douglasfir. Forest Ecology and Management. 259: 798–808.

Harrington, H.D. 1964. Manual of the plants of Colorado. 2nd ed. 

Chicago, IL: The Swallow Press.

Harrington, M.G. 2012. Duff mound consumption and cambium 

injury for centuries-old western larch from prescribed burning 

in western Montana. International Journal of Wildland Fire. 22: 

359–367.

Harrod, R.J.; McRae, B.H.; Hartl, W.E. 1999. Historical stand 

reconstruction in ponderosa pine forests to guide silvicultural 

prescriptions. Forest Ecology and Management. 114: 433–446.

Hart, S.J.; Veblen, T.T.; Eisenhart, K.S.; [et al.]. 2013. Drought 

induces spruce beetle (Dendroctonus rufipennis) outbreaks 

across northwestern Colorado. Ecology. 95: 930–939.

Harvey, A.E.; Byler, J.W.; McDonald, G.I.; [et al.]. 2008. Death of 

an ecosystem: perspectives on western white pine ecosystems 

of North America at the end of the twentieth century. 

Gen. Tech. Rep. RMRS-GTR-208. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station.

Hawksworth, F.G.; Bailey, D.K. 1980. Bristlecone pine. In: Eyre, 

F. H., ed. Forest cover types of the United States and Canada. 

Washington, DC: Society of American Foresters: 89–90.

Hawksworth, F.G.; Wiens, D. 1972. Biology and classification 

of dwarf mistletoes (Arceuthobium). Agric. Hndbk. 401. 

Washington, DC: U.S. Department of Agriculture.

He, H.; Keane, R.E.; Iverson, L. 2008. Forest landscape models, 

a tool for understanding the effect of the large-scale and longterm landscape processes. Forest Ecology and Management. 

254: 371–374.

Heidmann, L.J. 1983. Seed production in southwestern ponderosa 

pine on a sedimentary soil. Res. Note. RM-RN-434. Flagstaff, 

AZ: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station. 2 p.

Hepting, George H. 1971. Diseases of forest and shade trees of 

the United States. Agric. Handbk. 386. Washington, DC: U.S. 

Department of Agriculture.

Hermann, R.K.; Lavender, D.P. 1990. Pseudotsuga menziesii

(Mirb.) Franco Douglas-fir. In: Burns, R.M.; Honkala, B.H., 

eds. Silvics of North America: Volume 1, conifers. Washington, 

DC: U.S. Department of Agriculture, Forest Service: 

1119–1133.

Hess, K.; Alexander, R.R. 1986. Forest vegetation of the Arapaho 

and Roosevelt National Forests in central Colorado: A habitat 

type classification. Res. Pap. RM-RP-266. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station.

Chapter 6: Effects of Climate Change on Forest Vegetation
156 USDA Forest Service RMRS-GTR-375. 2018

Hessburg, P.F.; Smith, B.G.; Salter, R.B. 1999. Detecting change 

in forest spatial patterns from reference conditions. Ecological 

Applications. 9: 1232–1252.

Hiebert, R.D. 1977. The population biology of bristlecone 

pine (Pinus longaeva) in the eastern Great Basin. Doctoral 

dissertation. Lawrence, KS: University of Kansas.

Hickman, J.C., ed. 1993. The Jepson manual: Higher plants of 

California. Berkeley, CA: University of California Press.

Hitchcock, C.L.; Cronquist, A. 1973. Flora of the Pacific 

Northwest. Seattle, WA: University of Washington Press.

Hogg, E.H.; Hurdle, P.A. 1995. The aspen parkland in western 

Canada: A dry-climate analogue for the future boreal forest? 

Water Air and Soil Pollution. 82: 391–400.

Hohlt, J.C.; Racher, B.J.; Bryan, J.B.; [et al.]. 2002. Saltcedar 

response to prescribed burning in New Mexico. In: Wilde, 

G.R.; Smith, L.M., eds. Research highlights—2002: Range, 

wildlife, and fisheries management. Vol. 33. Lubbock, TX: 

Texas Tech University, College of Agricultural Sciences and 

Natural Resources: 25.

Holland, Robert F. 1986. Preliminary descriptions of the terrestrial 

natural communities of California. Sacramento, CA: California 

Department of Fish and Game.

Holland, Carol J. 1990. Pinyon-juniper management in Region 3. 

In: Loftis, D.L., ed. Silvicultural challenges and opportunities 

in the 1990’s: Proceedings of the national silvicultural 

workshop; July 10-13, 1989; Petersburg, AK. Washington, 

DC: U.S. Department of Agriculture, Forest Service, Timber 

Management: 206–216.

Hood, S.; Bentz, B.J. 2007. Predicting post-fire Douglas-fir beetle 

attacks and tree mortality in the northern Rocky Mountains. 

Canadian Journal of Forestry. 37: 1058–1069.

Hood, S.; Bentz, B.; Gibson, K.; [et al.]. 2007. Assessing post-fire 

Douglas-fir mortality and Douglas-fir beetle attacks in the 

northern Rocky Mountains. Gen. Tech. Rep. RMRS-GTR-199. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station.

Hopkins, T.A.; Larson, J.; Belote, R.T. 2013. Contrasting effects of 

wildfire and ecological restoration in old-growth western larch 

forests. Forest Science. 60: 1005–1013.

Horton, J.L.; Kolb, T.E.; Hart, S.C. 2001. Physiological response 

to groundwater depth varies among species and with river flow 

regulation. Ecological Applications. 11: 1046–1059.

Huntley, B. 1991. How plants respond to climate change: 

Migration rates, individualism and the consequences for plant 

communities. Annals of Botany. 67: 15–22.

Ibáñez, I.; Clark, J.S.; LaDeau, S.; Hille Ris Lambers, J. 2007. 

Exploiting temporal variability to understand tree recruitment 

response to climate change. Ecological Monographs. 77: 

163–177.

Intergovernmental Panel on Climate Change [IPCC]. 2007. 

Climate change 2007: The physical science basis. Climate 

change 2007 working group I contribution to the fourth 

assessment report of the IPCC. Cambridge, United Kingdom 

and New York, NY: Cambridge University Press.

Ireland, K.B.; Moore, M.M.; Fulé, P.Z.; [et al.]. 2014. Slow 

lifelong growth predisposes Populus tremuloides trees to 

mortality. Oecologia. 175: 847-859.

Iverson, L.R.; McKenzie, D. 2013. Tree-species range shifts in a 

changing climate: Detecting, modeling, assisting. Landscape 

Ecology. 28: 879–889.

Iverson, L.R.; Prasad, A.M. 2002. Potential redistribution of tree 

species habitat under five climate change scenarios in the 

eastern US. Forest Ecology and Management. 155: 205–222.

Jackson, M.; Gannon, A.; Kearns, H.; Kendall, K.C. 2010. Current 

status of limber pine in Montana. Num. Rep. 10-06. Missoula, 

MT: U.S. Department of Agriculture, Forest Service, Northern 

Region, Forest Health and Protection.

Jain, T.B.; Graham, R.T. 2005. Restoring dry and moist forests of 

the inland northwestern U.S. In: Stranhauf, J.A.; Madsen, P., 

eds. Restoration of boreal and temperate forests. New York, 

NY: CRC Press: 463–480.

Jameson, D. A. 1970. Degradation and accumulation of inhibitory 

substances from Juniperus osteosperma (Torr.) Little. Plant and 

Soil 33: 213–224.

Jameson, D.A.; Williams, J.A.; Wilton, E.W. 1962. Vegetation and 

soils of Fishtail Mesa, Arizona. Ecology 43: 403–410.

Jenkins, M.J.; Hebertson, E.; Page, W.; Jorgensen, A. 2008. Bark 

beetles, fuels, fires and implications for forest management in 

the Intermountain West. Forest Ecology and Management. 254: 

16–34.

Jester, N.; Rogers, K.; Dennis, F.C. 2012. Gambel oak 

management. Fact Sheet 6.311. Fort Collins, CO: Colorado 

State University, Extension.

Johnstone, J.F.; Chapin, F.S. 2003. Non-equilibrium succession 

dynamics indicate continued northern migration of lodgepole 

pine. Global Change Biology. 9: 1401–1409.

Jones, J.R. 1974. Silviculture of southwestern mixed conifers and 

aspen: The status of our knowledge. Res. Pap. RM-RP-122. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station.

Joyce, L.A. 1995. Productivity of America’s forests and climate 

change. Gen. Tech. Rep. RMRS-GTR-271. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station.

Joyce, L.A.; Birdsey, R A. 2000. The impact of climate change on 

America’s forests: A technical document supporting the 2000 

USDA Forest Service RPA assessment. Gen. Tech. Rep. RMRSGTR-59. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station.

Joyce, L.A.; Running, S.W.; Breshears, D.D.; [et al.]. 2014. 

Forests. In: Melillo, J.M.; Richmond, T.C.; Yohe, G.W., eds. 

Climate change impacts in the United States: third National 

Climate Assessment. Washington, DC: U.S. Global Change 

Research Program: 175–194.

Jump, A.S.; Peñuelas, J. 2005. Running to stand still: Adaptation 

and the response of plants to rapid climate change. Ecology 

Letters. 8: 1010–1020.

Kay, C.E. 2003. Long-term vegetation change on Utah’s Fishlake 

National Forest: A study in repeat photography. Logan, UT: 

Utah State University, Extension.

Keane, R.E. 2001. Successional dynamics: Modeling an 

anthropogenic threat. In: Tomback, D.; Arno, S.; Keane, R., 

eds. Whitebark pine communities: Ecology and restoration. 

Washington, DC: Island Press: 159–192.

Keane, R.E.; Austin, M.; Dalman, R.; [et al.]. 2001. Tree mortality 

in gap models: Application to climate change. Climatic Change. 

51: 509–540.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 157

Keane, R.E.; Cary, G.; Davies, I.D.; [et al.]. 2004. A classification 

of landscape fire succession models: spatially explicit models of 

fire and vegetation dynamic. Ecological Modelling. 256: 3–27.

Keane, R.E.; Finney, M.A. 2003. The simulation of landscape fire, 

climate, and ecosystem dynamics. In: Veblen, T.T.; Baker, W.L.; 

Montenegro, G.; Swetnam, T.W., eds. Fire and global change in 

temperate ecosystems of the western Americas. New York, NY: 

Springer-Verlag: 32–68.

Keane, R.E.; Hessburg, P.F.; Landres, P.B.; Swanson, F.J. 2009. 

A review of the use of historical range and variation (HRV) in 

landscape management. Forest Ecology and Management. 258: 

1025–1037.

Keane, R.E.; Loehman, R.; Clark, J.; [et al.]. 2015a. Exploring 

interactions among multiple disturbance agents in forest 

landscapes: Simulating effects of fire, beetles, and disease under 

climate change. In: Perera, A.H.; Remmel, T.K.; Buse, L.J., eds. 

Modeling and mapping forest landscape patterns. New York: 

Springer: 201–231.

Keane, R.E.; McKenzie, D.; Falk, D.A.; [et al.]. 2015b. 

Representing climate, disturbance, and vegetation interactions 

in landscape models. Ecological Modelling. 309–310: 33–47.

Keane, R.E.; Morgan, P.; Menakis, J.P. 1994. Landscape 

assessment of the decline of whitebark pine (Pinus albicaulis) 

in the Bob Marshall Wilderness Complex, Montana, USA. 

Northwest Science. 68: 213–229.

Keane, R.E.; Parsons, R. 2010. Restoring whitebark pine forests of 

the northern Rocky Mountains, USA. Ecological Restoration. 

28: 56–70.

Keane, R.E.; Ryan, K.C.; Running, S.W. 1996. Simulating effects 

of fire on northern Rocky Mountain landscapes with the 

ecological process model Fire-BGC. Tree Physiology. 16: 

319–331.

Keane, R.E.; Tomback, D.F.; Aubry, C.A.; [et al.]. 2012. A rangewide restoration strategy for whitebark pine forests. Gen. Tech. 

Rep. RMRS-GTR-279. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station.

Keane, R.E.; Veblen, T.; Ryan, K.C.; [et al.]. 2002. The cascading 

effects of fire exclusion in the Rocky Mountains. In: Baron, 

J., ed. Rocky Mountain futures: An ecological perspective. 

Washington, DC: Island Press: 133–153.

Kemp, K. 2015. Resilience and regeneration after wildfire in dry 

mixed-conifer forests of the U.S. northern Rockies http://

figshare.com/articles/Kemp_NRFSNPresentation_PDF_

pdf/1333592 [Accessed October 25, 2016].

Klopfenstein, N.B.; Kim, M.; Hanna, J.W.; [et al.]. 2009. 

Approaches to predicting potential impacts of climate change 

on forest disease: An example with Armillaria root disease. 

Res. Pap. RMRS-RP-76. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station.

Knapp, A.K.; Smith, W.K. 1982. Factors influencing understory 

seedling establishment of Engelmann spruce (Picea 

engelmannii) and subalpine fir (Abies lasiocarpa) in southeast 

Wyoming. Canadian Journal of Botany. 60: 2753–2761.

Knutti, R.; Sedlacek, J. 2013. Robustness and uncertainties in the 

new CMIP5 climate model projections. Nature Climate Change. 

3: 369–373.

Kolb, T. E.; Stone, J. E. 2000. Differences in leaf gas exchange and 

water relations among species and tree sizes in an Arizona pineoak forest. Tree Physiology. 20: 1–12.

Laacke, R.J. 1990. Abies concolor (Gord. and Glend.) Lindl. ex 

Hildebr. white fir. In: Burns, R.M.; Honkala, B.H., tech. coords. 

Silvics of North America: Volume 1, conifers. Agric. Handbk. 

654. Washington, DC: U.S. Department of Agriculture, Forest 

Service: 36–46.

Laacke, R.J.; Tappeiner, J.C. 1996. Red fir ecology and 

management. In: Erman, D.C., ed. Sierra Nevada Ecosystem 

Project: Final report to Congress, Volume III. Davis, CA: 

University of California, Wildland Resources Center Report: 

chapter 10.

Lacey, J.; Mosley, J. 2002. 250 plants for range contests in 

Montana. MONTGUIDE MT198402 AG 6/2002. Range E-2 

(Misc.). Bozeman, MT: Montana State University, Extension 

Service.

LaDeau, S.L.; Clark, J.S. 2001. Rising CO2

 levels and the 

fecundity of forest trees. Science. 292: 95–98.

Lambrecht, S.C.; Loik, M.E.; Inouye, D.W.; Harte, J. 2007. 

Reproductive and physiological responses to simulated climate 

warming for four subalpine species. New Phytologist. 173: 

121–134.

Landhäusser, S. M.; Deshaies, D.; Lieffers, V.J. 2010. Disturbance 

facilitates rapid range expansion of aspen into higher elevations 

of the Rocky Mountains under a warming climate. Journal of 

Biogeography 37:68–76.

Landres, P.B.; Morgan, P.; Swanson, F.J. 1999. Overview and use 

of natural variability concepts in managing ecological systems. 

Ecological Applications. 9: 1179–1188.

Langor, D.W. 2007. Status of limber pine (Pinus flexilis) in 

Alberta. In: Peters, S.; Gutsell, R.; Sharp, N.; Matthais, L., 

eds. Edmonton, Alberta, Canada: Alberta Sustainable Resource 

Development and Alberta Conservation Association.

Lankau, R.A.; Zhu, K.; Ordonez, A. 2015. Mycorrhizal strategies 

of tree species correlate with trailing range edge responses to 

current and past climate change. Ecology. 96: 1451–1458.

Lanner, R.M. 1980. Avian seed dispersal as a factor in the ecology 

and evolution of limber and whitebark pines. In: Dancik, B.P.; 

Higginbotham, K.O., eds. Sixth North American Forest Biology 

Workshop. Edmonton, Alberta, Canada: University of Alberta: 

15–47.

Lanner, R.M. 1983. Trees of the Great Basin: A natural history. 

Reno, NV: University of Nevada Press. 215 p.

Lanner, R.M. 1999. Conifers of California. Los Olivos, CA: 

Cachuma Press.

Lanner, R.M.; Vander Wall, S.B. 1980. Dispersal of limber pine 

seed by Clark‘s nutcracker. Journal of Forestry. 78: 637–639.

Larsen, D.R.; Johnson, P.S. 1998. Linking the ecology of 

natural oak regeneration to silviculture. Forest Ecology and 

Management. 106: 1–7.

Larson, A.J.; Belote, R.T.; Cansler, C.A.; [et al.]. 2013. Latent 

resilience in ponderosa pine forest: Effects of resumed frequent 

fire. Ecological Applications. 23: 1243–1249.

Laughlin, D.C.; Bakker, J.D.; Stoddard, M.T.; [et al.]. 2004. 

Toward reference conditions: Wildfire effects on flora in an old 

growth ponderosa pine forest. Forest Ecology and Management. 

199: 137–152.

Lawler, J.J.; White, D.; Neilson, R.P.; Blaustein, A.R. 2006. 

Predicting climate-induced range shifts: model differences and 

model reliability. Global Change Biology. 12: 1568–1584.

Chapter 6: Effects of Climate Change on Forest Vegetation
158 USDA Forest Service RMRS-GTR-375. 2018

Ledig, F.T; Kitzmiller, J.H. 1992. Genetic strategies for 

reforestation in the face of global climate change. Forest 

Ecology and Management. 50: 153–169.

Leirfallom, S.; Keane, R.E.; Tomback, D.; Dobrowski, S. 2015 

The effects of seed source mortality on whitebark pine (Pinus 

albicaulis) regeneration dynamics after wildfire. Canadian 

Journal Forest Research. 45: 1597–1606.

Lenoir, J.; Gégout, J.C.; Marquet, P.A.; [et al.]. 2008. A significant 

upward shift in plant species optimum elevation during the 20th

century. Science. 320: 1768–1771.

Liang, Y.; He, H.S.; Wang, W.J.; [et al.]. 2015. The site-scale 

processes affect species distribution predictions of forest 

landscape models. Ecological Modelling. 300: 89–101.

Littell, J.S.; McKenzie, D.; Kerns, B.K.; [et al.]. 2011. Managing 

uncertainty in climate-driven ecological models to inform 

adaptation to climate change. Ecosphere. 2: 102–111.

Little, R.L.; Peterson, D.L.; Conquest, L.L. 1994. Regeneration 

of subalpine fir (Abies lasiocarpa) following fire: Effects of 

climate and other factors. Canadian Journal of Forest Research. 

24: 934–944.

Loehman, R.A.; Clark, J.A.; Keane, R.E. 2011a. Modeling effects 

of climate change and fire management on western white pine 

(Pinus monticola) in the Northern Rocky Mountains, USA. 

Forests. 2: 832–860.

Logan, J.A.; Régnière, J.; Powell, J.A. 2003. Assessing the impacts 

of global warming on forest pest dynamics. Frontiers in 

Ecology and the Environment. 1: 130–137.

Lorenz, T.J.; Sullivan, K.A. 2009. Seasonal differences in space 

use by Clark’s nutcrackers in the Cascade Range. The Condor. 

11: 326–340.

Lotan, J.E.; Brown, J.K.; Neuenschwander, L.F. 1984. Role of fire 

in lodgepole pine forests. In: Baumgartner, D.M.; Krebill, R.G.; 

Arnott, J.T.; Weetman, G.F., eds. Lodgepole pine: The species 

and its management. May 8-10, 1984; Spokane, WA. Pullman, 

WA: Washington State University, Cooperative Extension: 

133–152.

Lotan, J.E.; Critchfield, W.B. 1990. Pinus contorta Dougl. ex. 

Loud. lodgepole pine. In: Burns, R.M.; Honkala, B.H., tech. 

eds. Silvics of North America: Volume 1, conifers. Agric. 

Handbk. 654. Washington, DC: U.S. Department of Agriculture, 

Forest Service: 648–666.

Lotan, J.E.; Perry, D.A. 1983. Ecology and regeneration of 

lodgepole pine. Agric. Handbk. 606. Washington, DC: U.S. 

Department of Agriculture, Forest Service.

Luckman, B.H.; Jozsa, L.A.; Murphy, P.J. 1984. Living sevenhundred-year-old Picea engelmannii and Pinus albicaulis in the 

Canadian Rockies. Arctic and Alpine Research. 16: 419–422.

MacFarlane, D.; Meyer, S.P. 2005. Characteristics and distribution 

of potential ash tree hosts for emerald ash borer. Forest Ecology 

and Management. 213: 15–24.

Malcolm, J.R.; Markham, A.; Neilson, R.P.; Garaci, M. 2002. 

Estimated migration rates under scenarios of global climate 

change. Journal of Biogeography. 28: 835–849.

Manning, M.E.; Padgett, W.G. 1989. Preliminary riparian 

community type classification for Nevada. Unpub. rep. 

Missoula, MT: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station, Fire Sciences Laboratory.

Marcoux, H.M.; Daniels, L.D.; Gergel, S.E.; [et al.]. 2015. 

Differentiating mixed- and high-severity fire regimes in mixedconifer forests of the Canadian Cordillera. Forest Ecology and 

Management. 341: 45–58.

Martin, R.E.; Johnson, A.H. 1979. Fire management of Lava Beds 

National Monument. In: Linn, Robert M., ed. Proceedings, 1st 

conference on scientific research in the national parks: Volume 

2; November 9-12, 1976; New Orleans, LA. NPS Trans. and 

Proc. Ser. 5. Washington, DC: U.S. Department of the Interior, 

National Park Service: 1209–1217.

McCulloch, C.Y. 1969. Some effects of wildfire on deer habitat in 

pinyon-juniper woodland. Journal of Wildlife Management. 33: 

778–784.

McDowell, N.; Pockman, W.T.; Allen, C.D.; [et al.]. 2008. 

Mechanisms of plant survival and mortality during drought: 

Why do some plants survive while others succumb to 

drought? New Phytologist. 178: 719–739.

McKelvey, K.S.; Johnston, J.D. 1992. Historical perspectives on 

forests of the Sierra Nevada and the Transverse Ranges of 

southern California: Forests condition at the turn of the century. 

In: Verner, J.; McKelvey, K.S.; Noon, B.R., tech. coords. The 

California spotted owl: A technical assessment of its current 

status. Gen. Tech. Rep. PSW-GTR-133. Albany, CA: U.S. 

Department of Agriculture, Forest Service, Pacific Southwest 

Research Station: 225–246.

McKenzie, D., Gedalof, Z.; Peterson, D.L.; Mote, P. 2004. 

Climatic change, wildfire, and conservation. Conservation 

Biology. 18: 890–902.

McKenzie, D.; Miller, C.; Falk, D.A., eds. 2011. The landscape 

ecology of fire. Dordrecht, The Netherlands: Springer Ltd.

McKenzie, D.; Peterson, D.L.; Littell, J.S. 2009. Global warming 

and stress complexes in forests of western North America. 

In: Bytnerowicz, A.; Arbaugh, M.J.; Riebau, A.R.; Andersen, 

C., eds. Wildland fires and air pollution. Dordrecht, The 

Netherlands: Elsevier: 317–337.

McKenzie, D.; Shankar, U.; Keane, R.E.; [et al.]. 2014. Smoke 

consequences of new wildfire regimes driven by climate 

change. Earth‘s Future. 2: 35–59.

Medina, A.L. 1986. Riparian plant communities of the Fort 

Bayard watershed in southwestern New Mexico. Southwestern 

Naturalist. 31: 345–359.

Meeuwig, R.O.; Bassett, R.L. 1983. Pinyon-juniper. In: Burns, 

R.M., comp. Silvicultural systems for the major forest types of 

the United States. Agric. Handbk. 445. Washington, DC: U.S. 

Department of Agriculture, Forest Service: 84–86.

Meeuwig, R.O.; Budy, J.D.; Everett, R.L. 1990. Pinus monophylla

Torr. and Frem. singleleaf pinyon. In: Burns, R.M.; Honkala, 

B.H., tech. coords. Silvics of North America: Volume 

1, conifers. Agric. Handbk. 654. Washington, DC: U.S. 

Department of Agriculture, Forest Service: 380–384.

Meyer, M.D. [n.d.]. Natural range of variation of red fir forests in 

the bioregional assessment area. Albany, CA: U.S. Department 

of Agriculture, Forest Service, Pacific Southwest Region. 

http://www.fs.usda.gov/Internet/FSE_DOCUMENTS/

stelprdb5434332.pdf [Accessed October 29, 2016].

Merigliano, M.F. 1996. Ecology and management of the South 

Fork Snake River cottonwood forest. Tech. Bull. 96-9. 

Boise, ID: U.S. Department of the Interior, Bureau of Land 

Management, Idaho State Office.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 159

Merriam, G.; Henein, K.; Stuart-Smith, K. 1992. Landscape 

dynamics models. In: Turner, M.G.; Gardner, R.H., eds. 

Quantitative methods in landscape ecology: The analysis and 

interpretation of landscape heterogeneity. New York, NY: 

Springer-Verlag: 399–416.

Millar, C.I.; Stephenson, N.L.; Stephens, S.L. 2007. Climate 

change and forests of the future: Managing in the face of 

uncertainty. Ecological Applications. 17: 2145–2151.

Miller, J.M.; Keen, F.P. 1960. Biology and control of the western 

pine beetle: A summary of the first fifty years of research. Misc. 

Pub. 800. Washington, DC: U.S. Department of Agriculture.

Miller, J.D.; Safford, H.D.; Crimmins, M.; Thode, A.E. 2009. 

Quantitative evidence for increasing forest fire severity in the 

Sierra Nevada and southern Cascade Mountains, California and 

Nevada, USA. Ecosystems. 12: 16–32.

Milner, K.S. 1992. Site index and height growth curves for 

ponderosa pine, western larch, lodgepole pine, and Douglas-fir 

in western Montana. Western Journal of Applied Forestry. 7: 

9–14.

Minore, D. 1979. Comparative autecological characteristics of 

northwestern tree species: A literature review. Gen. Tech. Rep. 

PNW-GTR-087. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Forest and Range Experiment 

Station.

Mitchell, J.M. 1984. Fire management action plan: Zion 

National Park, Utah. Record of Decision. Springdale, UT: 

U.S. Department of the Interior, National Park Service, Zion 

National Park.

Mitchell, R.; Moir, W. 1976. Vegetation of the Abbott Creek 

Research Natural Area, Oregon. Northwest Science. 50: 42–58.

Mohatt, K.; Cripps, C.L.; Lavin, M. 2008. Ectomycorrhizal fungi 

of whitebark pine (a tree in peril) revealed by sporocarps and 

molecular analysis of mycorrhizae from treeline forests in the 

Greater Yellowstone Ecosystem. Botany. 86: 14–15.

Moir, W.H. 1982. A fire history of the High Chisos, Big Bend 

National Park, Texas. The Southwestern Naturalist. 27: 87–98.

Morales, J.M.; Mermoz, M.; Gowda, J.H.; Kitzberger, T. 2015. A 

stochastic fire spread model for north Patagonia based on fire 

occurrence maps. Ecological Modelling. 300: 73–80.

Moran, C.J.; Corcoran, M.A. 2012. Do mountain pine beetle 

outbreaks change the probability of active crown fire in 

lodgepole pine forests? Comment. Ecology. 93: 939–950.

Morgan, P.; Bunting, S.C.; Keane, R.E.; Arno, S.F. 1994b. Fire 

ecology of whitebark pine (Pinus albicaulis) forests in the 

Rocky Mountains, USA. In: Schmidt, W.C.; Holtmeier, 

F.K., eds. Proceedings of the international symposium on 

subalpine stone pines and their environment: The status of our 

knowledge; September 5–11, 1992; St. Moritz, Switzerland. 

Gen. Tech. Rep. INT-GTR-309. Ogden, UT: U.S. Department 

of Agriculture, Forest Service, Intermountain Forest and Range 

Experiment Station: 136–142.

Mueggler, W.F. 1976. Ecological role of fire in western woodland 

and range ecosystems. In: Use of prescribed burning in 

western woodland and range ecosystems: proceedings of the 

symposium; March 18-19, 1976; Logan, UT. Logan, UT: Utah 

State University, Agricultural Experiment Station: 1–9.

Mueggler, W.F. 1985. Vegetation associations. In: DeByle, N.V.; 

Winokur, R.P. eds., Aspen: Ecology and management in the 

western United States. Gen. Tech. Rep. GTR-RMRS-119. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service: 

45–55.

Munz, P.A. 1973. A California flora and supplement. Berkeley, CA: 

University of California Press.

Murray, M.P.; Bunting, S.C.; Morgan, P. 1995. Subalpine 

ecosystems: the roles of whitebark pine and fire. In: Greenlee, 

J.M., ed. Fire effects on rare and endangered species and 

habitats conference. Coeur d’Alene, ID. Fairfield, WA: 

International Association of Wildland Fire: 295–299.

Negrón, J.F.; Fettig, C.J. 2014. Mountain pine beetle, a major 

disturbance agent in US western coniferous forests: A synthesis 

of the state of knowledge. Forest Science. 60: 409–413.

Neilson, R.P.; Pitelka, L.F.; Solomon, A.M.; [et al.]. 2005. 

Forecasting regional to global plant migration in response to 

climate change. BioScience. 55: 749–760.

Nelson, D.L.; Krebill, R.G. 1982. Occurrence and effect of 

Chrysomyxa pirolata cone rust on Picea pungens in Utah. The 

Great Basin Naturalist. 42: 262–272.

Nigh, G. 2014. Mitigating the effects of climate change on 

lodgepole pine site height in British Columbia, Canada, with a 

transfer function. Forestry. 87: 377–387.

Nitschke, C.R.; Innes, J.L. 2008. A tree and climate assessment 

tool for modelling ecosystem response to climate change. 

Ecological Modelling. 210: 263–277.

Nix, L.E.; Cox, S.K. 1987. Cherrybark oak enrichment plantings 

appear successful after seven years in South Carolina 

bottomlands. In: Phillips, D.R., comp. Proceedings of the fourth 

biennial southern silvicultural research conference; November 

4-6, 1986; Atlanta, GA. Gen. Tech. Rep. SE-GTR-42. 

Asheville, NC: U.S. Department of Agriculture, Forest Service, 

Southeastern Forest Experiment Station: 129–132.

Noble, D.L. 1990. Juniperus scopulorum Sarg. Rocky Mountain 

juniper. In: Burns, Russell M.; Honkala, Barbara H., tech. 

coords. Silvics of North America: Volume 1, conifers. Agric. 

Handbk. 654. Washington, DC: U.S. Department of Agriculture, 

Forest Service: 116–126.

Notaro, M. 2008. Response of the mean global vegetation 

distribution to interannual climate variability. Climate 

Dynamics. 30: 845–854.

Notaro, M.; Vavrus, S.; Liu, Z. 2007. Global vegetation and 

climate change due to future increases in CO2

 as projected by 

a fully coupled model with dynamic vegetation. Journal of 

Climate. 20: 70–88.

Nyland, R.D. 1998. Patterns of lodgepole pine regeneration 

following the 1988 Yellowstone fires. Forest Ecology and 

Management. 111: 23–33.

Ohmart, R.D.; Anderson, B.W. 1982. North American desert 

riparian ecosystems. In: Bender, G.L., ed. Reference handbook 

on the deserts of North America. Westport, CT: Greenwood 

Press: 433–479.

Oliver, C.D.; Adams, A.B.; Zasoski, R.J. 1985. Disturbance 

patterns and forest development in a recently deglaciated valley 

in the northwestern Cascade Range of Washington, U.S.A. 

Canadian Journal of Forest Research. 15: 221–232.

Oliver, W.W.; Ryker, R.A. 1990. Pinus ponderosa Dougl. ex 

Laws ponderosa pine. In: Burns, R.M.; Honkala, B.H., eds. 

Silvics of North America: Volume 1, conifers. Agric. Handbk. 

654. Washington, DC: U.S. Department of Agriculture, Forest 

Service: 348–353.

Oosting, H.J.; Billings, W.D. 1943. The red fir forest of the Sierra 

Nevada: Abietum magnificae. Ecological Monographs. 13: 

260–273.

Chapter 6: Effects of Climate Change on Forest Vegetation
160 USDA Forest Service RMRS-GTR-375. 2018

Owens, J.N. 2008. The reproductive biology of western larch. 

Moscow, ID: University of Idaho, Inland Empire Tree 

Improvement Cooperative, and the Forest Genetics Council of 

British Columbia.

Page, W.G.; Jenkins, M.J. 2007. Mountain pine beetle-induced 

changes to selected lodgepole pine fuel complexes within the 

intermountain region. Forest Science. 53: 507–518.

Parmesan, C. 2006. Ecological and evolutionary responses to 

recent climate change. Annual Review of Ecology, Evolution, 

and Systematics. 37: 637–669.

Parker, A.J. 1984. Mixed forests of red and white fir in Yosemite 

National Park, California. The American Midland Naturalist. 

112: 15–23.

Parker, A.J. 1986. Environmental and historical factors affecting 

red and white fir regeneration in ecotonal forests. Forest 

Science. 32: 339–347.

Paysen, T.E.; Ansley, R. J.; Brown, J.K.; [et al.]. 2000. Fire in 

western shrubland, woodland, and grassland ecosystems. In: 

Brown, J.K.; Smith, J.K., eds. Wildland fire in ecosystems: 

Effects of fire on flora. Gen. Tech. Rep. RMRS-GTR-42-

volume 2. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station: 121–159.

Perala, D.A. 1983. Modeling aspen and red pine shoot growth to 

daily weather variations. Res. Pap. NC-RP-236. St. Paul, MN: 

U.S. Department of Agriculture, Forest Service, North Central 

Forest Experiment Station.

Perala, D.A. 1990. Populus tremuloides Michx. quaking aspen. 

In: Burns, R.M.; Honkala, B.H., eds. Silvics of North America: 

Volume 2, hardwoods. Washington DC: U.S. Department of 

Agriculture, Forest Service: 348–353.

Perry, G.L.W.; Millington, J.D.A. 2008. Spatial modelling of 

succession-disturbance dynamics in forest ecosystems: 

Concepts and examples. Perspectives in Plant Ecology, 

Evolution and Systematics. 9: 191–210.

Peterson, D.L.; Vose, J.M.; Patel-Weynand, T. 2014a. Climate 

change and United States forests. Dordrecht, The Netherlands: 

Springer.

Peterson, D.W.; Kerns, B.K.; Donson, E.K. 2014b. Climate 

change effects on vegetation in the Pacific Northwest: A 

review and synthesis of the scientific literature and simulation 

model projections. Gen. Tech. Rep. PNW-GTR-900. Portland, 

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

Northwest Research Station.

Peterson, D.W.; Peterson, D.L. 2001. Mountain hemlock growth 

responds to climatic variability at annual and decadal scales. 

Ecology. 82: 3330–3345.

Peterson, D.W., D.L. Peterson, and G.J. Ettl. 2002. Growth 

responses of subalpine fir (Abies lasiocarpa) to climatic 

variability in the Pacific Northwest. Canadian Journal of Forest 

Research 32: 1503–1517.

Pfister, R.D.; Kovalchik, B.L.; Arno, S.F.; Presby, R.C. 1977. 

Forest habitat types of Montana. Gen. Tech. Rep. INT-GTR-34. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station.

Pieper, R.D. 1977. The southwestern pinyon-juniper ecosystem. 

In: Aldon, E.F.; Loring, T.J., tech. coords. Ecology, uses, and 

management of pinyon-juniper woodlands: Proceedings of 

the workshop; March 24-25, 1977; Albuquerque, NM. Gen. 

Tech. Rep. RM-GTR-39. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and Range 

Experiment Station: 1–6.

Potter, D.A. 1998. Forested communities of the upper montane in 

the central and southern Sierra Nevada. Gen. Tech. Rep. PSWGTR-169. Albany, CA: U.S. Department of Agriculture, Forest 

Service, Pacific Southwest Research Station.

Potter, K.M.; Hipkins, V.D.; Mahalovich, M.F.; Means, R.E. 

2015. Nuclear genetic variation across the range of ponderosa 

pine (Pinus ponderosa): Phylogeographic, taxonomic and 

conservation implications. Tree Genetics and Genomes. 11: 

1–23.

Prentice, I.C.; Bartlein, P.J.; Webb, T. 1991. Vegetation and 

climate change in eastern North America since the last glacial 

maximum. Ecology. 72: 2038–2056.

Preston, R.J. 1948. North American trees. Ames, IA: Iowa State 

College Press.

Purves, D.; Pacala, S. 2008. Predictive models of forest dynamics. 

Science. 320: 1452–1453.

Racher, B.J.; Mitchell, R.B. 1999. Management of saltcedar in 

eastern New Mexico and Texas. In: Wester, D.B.; Britton, C.M., 

eds. Research highlights—1999: Noxious brush and weed 

control: range, wildlife, and fisheries management. Vol. 30. 

Lubbock, TX: Texas Tech University, College of Agricultural 

Sciences and Natural Resources: 14–15.

Rehfeldt, G.E. 1978. Genetic differentiation of Douglas-fir 

populations from the northern Rocky Mountains. Ecology. 

1264–1270.

Rehfeldt, G.E. 1989. Ecological adaptations in Douglas-fir 

(Pseudotsuga menziesii var. glauca): A synthesis. Forest 

Ecology and Management. 28: 203–215.

Rehfeldt, G.E. 1994. Evolutionary genetics, the biological 

species, and the ecology of the Cedar-Hemlock forests. In: 

Baumgartner, D.M.; Lotan, J.E.; Tonn, J.R., eds. Interior cedarhemlock-white pine forests: Ecology and management. March 

2-4, 1993, Spokane, WA. Pullman, WA: Washington State 

University, Cooperative Extension: 91–100.

Restaino, C.M., Peterson, D.L.; Littell, J.S. 2016. Increased water 

deficit decreases Douglas-fir growth throughout western US 

forests. Proceedings of the National Academy of Sciences, 

USA. 113: 9557–9562.

Rice, J.; Bardsley, T.; Gomben, P.; [et al.]. 2017. Assessment of 

aspen ecosystem vulnerability to climate change for the UintaWasatch-Cache and Ashley National Forests, Utah. Gen. Tech. 

Rep. RMRS-GTR-366. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 

67 p.

Riggs, R.A.; Keane, R.E.; Cimon, N.; [et al.]. 2015. Biomass 

and fire dynamics in a temperate forest-grassland mosaic: 

Integrating multi-species herbivory, climate, and fire with the 

FireBGCv2/GrazeBGC system. Ecological Modelling. 296: 

57–78.

Rocca, M.E.; Brown, P.M.; MacDonald, L.H; Carrico, C.M. 2014. 

Climate change impacts on fire regimes and key ecosystem 

services in Rocky Mountain forests. Forest Ecology and 

Management. 327: 290–305.

Rochefort, R.M.; Little, R.L.; Woodward, A.; Peterson, D.L. 

1994. Changes in subalpine tree distribution in western North 

America: A review of climatic and other causal factors. The 

Holocene. 4: 89–100.

Roe, G.H.; Baker, M.B. 2007. Why is climate sensitivity so 

unpredictable? Science. 318: 629–632.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 161

Rogers, P. 2002. Using forest health monitoring to assess aspen 

forest cover change in the southern Rockies ecoregion. Forest 

Ecology and Management. 155: 223–236.

Rogers, P.C.; Eisenberg, C.; St. Clair, S.B. 2013. Resilience in 

quaking aspen: Recent advances and future needs. Forest 

Ecology and Management. 299: 1–5.

Romme, W.H.; Allen, C.D.; Bailey, J.D. 2009. Historical and 

modern disturbance regimes, stand structures, and landscape 

dynamics in piñon-juniper vegetation of the western United 

States. Rangeland Ecology and Management. 62: 203–222.

Romme, W.H.; Despain, D G. 1989. Historical perspective on the 

Yellowstone fires of 1988. BioScience. 39: 695–699.

Romme, W.H.; Turner, M.G. 1991. Implications of global climate 

change for biogeographic patterns in the greater Yellowstone 

ecosystem. Conservation Biology. 5: 373–386.

Rood, S.B.; Braatne, J.H.; Hughes, F.M. 2003. Ecophysiology of 

riparian cottonwoods: Stream flow dependency, water relations 

and restoration. Tree Physiology. 23: 1113–1124.

Rundel, P.W.; Parsons, D.J.; Gordon, D.T. 1977. Montane and 

subalpine vegetation of the Sierra Nevada and Cascade Ranges. 

In: Barbour, M.G.; Major, J., eds. Terrestrial vegetation of 

California. New York, NY: John Wiley and Sons: 559–599.

Ryan, K.C.; Reinhardt, E.D. 1988. Predicting postfire mortality of 

seven western conifers. Canadian Journal of Forest Research. 

18: 1291–1297.

Ryan, M.G.; Gower, S.T.; Hubbard, R.M.; [et al.]. 1995. Woody 

tissue maintenance respiration of four conifers in contrasting 

climates. Oecologia. 101: 133–140.

Ryker, R.A.; Losensky, J. 1983. Ponderosa pine and Rocky 

Mountain Douglas-fir. Silvicultural systems for the major forest 

types of the United States. Agric. Handbk. 445. Washington, 

DC: U.S. Department of Agriculture: 53–55.

Safranyik, L.; Carroll, A.; Régnière, J.; [et al.]. 2010. Potential for 

range expansion of mountain pine beetle into the boreal forest 

of North America. The Canadian Entomologist. 142: 415–442.

Sala, A.; Peters, G.D.; McIntyre, L.R.; Harrington, M.G. 2005. 

Physiological responses of ponderosa pine in western 

Montana to thinning, prescribed fire and burning season. Tree 

Physiology. 25: 339–348.

Salzer, M.W; Larson,E.R.; Bunn, A.G.; Hughes, M.K. 2014. 

Changing climate response in near-treeline bristlecone pine 

with elevation and aspect. Environmental Research Letters. 

9.11: 114007.

Schmidt, W.C. 1969. Seedbed treatments influence seedling 

development in western larch forests. Res. Note INT-RN-93. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station.

Schmidt, W.C.; Fellin, D.G. 1973. Western spruce budworm 

damage affects form and height growth of western larch. 

Canadian Journal of Forest Research. 3: 17–26.

Schmidt, W.C.; Larson, M. 1989. Silviculture of western inland 

conifers. In: Burns, R.M., comp. The scientific basis for 

silvicultural and management decisions in the National Forest 

System. Gen. Tech. Rep. WO-GTR-55. Washington, DC: U.S. 

Department of Agriculture, Forest Service: 40–58.

Schmidt, W.C.; Shearer, R.C. 1990. Larix occidentalis Nutt. 

western larch. In: Burns, R.M.; Honkala, B.H., eds. Silvics 

of North America: Volume 1, conifers. Agric. Handbk. 654. 

Washington, DC: U.S. Department of Agriculture, Forest 

Service: 348–353.

Schmidt, W.C.; Shearer, R.C. 1995. Larix occidentalis: A pioneer 

in the North American West. In: Schmidt, W.C.; McDonald, 

K.J., eds. Proceedings of an international symposium: Ecology 

and management of Larix forests: A look ahead; 1992; October 

5-9, 1992; Gen. Tech. Rep. INT-GTR-319 Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Research Station: 33–37.

Schmidt, W.C.; Shearer, R.C.; Roe, A.L. 1976. Ecology and 

silviculture of western larch forests. Tech. Bull. 1520. 

Washington, DC: U.S. Department of Agriculture, Forest 

Service.

Schneider, S.H.; Semenov, S.; Patwardhan, A.; [et al.]. 2007. 

Assessing key vulnerabilities and the risk from climate change. 

In: Parry, M.L.; Canziani, O.F.; Palutikof, P.J.; [et al.], eds. 

Climate change 2007: Impacts, adaptation and vulnerability. 

Contribution of working group II to the fourth assessment 

report of the Intergovernmental Panel on Climate Change. 

Cambridge, United Kingdom and New York, NY: Cambridge 

University Press: 779–810.

Schoennagel, T.L.; Veblen, T.T.; Romme, W.H. 2004. The 

interaction of fire, fuels, and climate across Rocky Mountain 

landscapes. BioScience. 54: 651–672.

Schoettle, A.W. 2003. Patterns of white pine regeneration after fire 

and its implications for forest establishment in the presence of 

white pine blister rust—A research program within the U.S. 

National Fire Plan. In: Parks Canada whitebark and limber 

pine workshop: workshop proceedings; February 18-19, 2003; 

Calgary, Alberta. Ottawa, Ontario, Canada: Parks Canada: 

14–15.

Schowalter, T.; Hansen, E.; Molina, R.; Zhang, Y. 1997. Integrating 

the ecological roles of phytophagous insects, plant pathogens, 

and mycorrhizae in managed forests. In: Kohm, K.A.; Franklin, 

J.F., eds. Creating a forestry for the 21st century: the science 

of ecosystem management. Washington, DC: Island Press: 

171–189.

Schumacher, S.; Reineking, B.; Sibold, J.; Bugmann, H. 2006. 

Modeling the impact of climate and vegetation on fire regimes 

in mountain landscapes. Landscape Ecology. 21: 539–554.

Schwandt, J.W. 2006. Whitebark pine in peril: A case for 

restoration. Rep. R1-06-28. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Northern Region. 20 p.

Sevanto, S.; McDowell, N.G.; Dickman, L.T.; [et al.]. 2014. 

How do trees die? A test of the hydraulic failure and carbon 

starvation hypotheses. Plant, Cell and Environment. 37: 

153–161.

Shafroth, P.B.; Stromberg, J.C.; Patten, D.T. 2002. Riparian 

vegetation response to altered disturbance and stress regimes. 

Ecological Applications. 12: 107–123.

Shantz, H.L.; Piemeisel, R.L. 1940. Types of vegetation in 

Escalante Valley, Utah, as indicators of soil conditions. Tech. 

Bull. 713. Washington, DC: U.S. Department of Agriculture.

Shearer, R.C. 1976. Early establishment of conifers following 

prescribed broadcast burning in western larch/Douglas-fir 

forests. In: Proceedings from the Tall Timbers Fire Ecology 

Conf. 14 and Intermountain Fire Research Council Fire and 

Land Management Symposium. Tallahassee, FL: Tall Timbers 

Research Station: 481–500.

Shearer, R.C.; Schmidt, W.C. 1970. Natural regeneration in 

ponderosa pine forests of western Montana. Res. Pap. INTRP-86. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Forest and Range Experiment Station.

Chapter 6: Effects of Climate Change on Forest Vegetation
162 USDA Forest Service RMRS-GTR-375. 2018

Shepperd, W.D.; Bartos, D.L.; Mata, S.A. 2001. Above- and 

below-ground effects of aspen clonal regeneration and 

succession to conifers. Canadian Journal of Forest Research. 

31: 739–745.

Sher, A.; Quigley, M. 2013. Tamarix: A case study of ecological 

change in the American West. Oxford, United Kingdom: 

Oxford University Press.

Shinneman, D.J.; Baker, W.L. 2009. Environmental and climatic 

variables as potential drivers of post-fire cover of cheatgrass 

(Bromus tectorum) in seeded and unseeded semiarid 

ecosystems. International Journal of Wildland Fire. 18: 

191–202.

Short, H.L.; McCulloch, C.Y. 1977. Managing pinyon-juniper 

ranges for wildlife. Gen. Tech. Rep. RM-47. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station. 10 p.

Sieg, C.H. 1997. The role of fire in managing for biological 

diversity on native rangelands of the Northern Great Plains. In: 

Uresk, D.W.; Schenbeck, G.L.; O’Rourke, J.T., tech. coords. 

Conserving biodiversity on native rangelands: Symposium 

proceedings; August 17, 1995; Fort Robinson State Park, 

NE. Gen. Tech. Rep. RM-GTR-298. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Forest and Range Experiment Station: 31–38.

Skinner, C.N.; Taylor, A.H.; Agee, J.K. 2006. Klamath Mountains 

bioregion. In: Sugihara, N.G.; van Wagtendonk, J.W.; Shaffer, 

K.E., eds. Fire in California’s ecosystems. Berkeley, CA: 

University of California Press: 170–194.

Sklar, F.H.; Costanza, R. 1991. The development of dynamic 

spatial models for landscape ecology: A review and prognosis. 

In: Turner, M.G.; Gardner, R.H., eds. Quantitative methods 

in landscape ecology. New York, NY: Springer-Verlag. 82: 

239–288.

Smith, C.M.; Langor, D.W.; Myrholm, C.; [et al.]. 2013. Changes 

in white pine blister rust infection and mortality in limber pine 

over time. Canadian Journal of Forest Research 43: 919–928.

Smith, D.R. 1967a. Effects of cattle grazing on a ponderosa pinebunchgrass range in Colorado. Tech. Bull. 1371. Washington, 

DC: U.S. Department of Agriculture, Forest Service.

Smith, M.D. 2011. The ecological role of climate extremes: 

Current understanding and future prospects. Journal of Ecology. 

99: 651–655.

Smith, R.S. 1967b. Verticicladiella root disease of pines. 

Phytopathology 57:935–938.

Smith, S.D.; Devitt, D.A.; Sala, A.; [et al.]. 1998. Water relations 

of riparian plants from warm desert regions. Wetlands. 18: 

687–696.

Sorenson, E.; Williams, C. F.; Walser, R. H.; Davis, T. D.; Barker, 

P. 1984. Growth response of Acer grandidentatum Nutt. to 

chilling treatments. Journal of Environmental Horticulture. 2: 

128–130.

Soulé, P.; Knapp, P. 2013. Radial growth rates of two co-occurring 

coniferous trees in the Northern Rockies during the past 

century. Journal of Arid Environments. 94: 87–95.

Spittlehouse, D.L.; Stewart, R.B. 2003. Adaptation to climate 

change in forest management. British Columbia Journal of 

Ecosystems and Management. 4: 1–11.

Springfield, H.W. 1976. Characteristics and management of 

Southwestern pinyon-juniper ranges: the status of our 

knowledge. Res. Pap. RM-RP-160. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Forest and Range Experiment Station.

St. Clair, J.B.; Howe, G.T. 2007. Genetic maladaptation of coastal 

Douglas-fir seedlings to future climates. Global Change 

Biology. 13: 1441–1454.

St. Clair, J.B., Howe, G.T. 2011. Strategies for conserving forest 

genetic resources in the face of climate change. Turkish Journal 

of Botany 35: 403–409.

Stainforth, D.A.; Aina, T.; Christensen, C.; [et al.]. 2005. 

Uncertainty in predictions of the climate response to rising 

levels of greenhouse gases. Nature. 433: 403–406.

Stanton, F. 1974. Wildlife guidelines for range fire rehabilitation. 

Tech. Note 6712. Denver, CO: U.S. Department of the Interior, 

Bureau of Land Management.

Steele, R. 1990. Pinus flexilis James limber pine. In: Burns, 

R.M.; Honkala, B.H., eds. Silvics of North America: Volume 

1, conifers. Agric. Handbk. 654. Washington DC: U.S. 

Department of Agriculture, Forest Service: 348–353.

Steele, R.; Cooper, S.V.; Ondov, D.M.; [et al.]. 1983. Forest habitat 

types of eastern Idaho-western Wyoming. Gen. Tech. Rep. INTGTR-144. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Forest and Range Experiment Station. 

122 p.

Steele, R.; Arno, S.F; Geier-Hayes, K. 1986. Wildfire patterns 

change in central Idaho’s ponderosa pine-Douglas-fir forest. 

Western Journal of Applied Forestry. 1: 16–19.

Stephenson, J.R.; Calcarone, G.M. 1999. Mountain and foothills 

ecosystems: Habitat and species conservation issues. In: 

Stephenson, J.R.; Calcarone, G.M. Southern California 

mountains and foothills assessment. Gen. Tech. Rep. PSWGTR-172. Albany, CA: U.S. Department of Agriculature, Forest 

Service, Pacific Southwest Research Station: 15–60.

Stillinger, C.R. 1944. Notes on Cronartium occidentale. Northwest 

Science 28:11–16.

Stout, D.L.; Sala, A. 2003. Xylem vulnerability to cavitation in 

Pseudotsuga menziesii and Pinus ponderosa from contrasting 

habitats. Tree Physiology. 23: 43–50.

Stromberg, J. 1998. Dynamics of Fremont cottonwood (Populus 

fremontii) and saltcedar (Tamarix chinensis) populations along 

the San Pedro River, Arizona. Journal of Arid Environments. 

40: 133-155.

Stubbendieck, J.; Hatch, S.L.; Butterfield, C.H. 1992. North 

American range plants. 4th ed. Lincoln, NE: University of 

Nebraska Press.

Stuever, M.C.; Crawford, C.S.; Molles, M.C.; [et al]. 1997. Initial 

assessment of the role of fire in the Middle Rio Grande bosque. 

In: Greenlee, J.M., ed. Fire effects on rare and endangered 

species and habitats conference. Coeur d’Alene, ID. Fairfield, 

WA: International Association of Wildland Fire: 275–283.

Sturrock, R.N.; Frankel, S.J.; Brown, A.V.; [et al.]. 2010. Climate 

change and forest diseases. Plant Pathology. 60: 133–149.

Sutton, Richard F.; Johnson, Craig W. 1974. Landscape plants from 

Utah’s mountains. EC-368. Logan, UT: Utah State University, 

Cooperative Extension.

Chapter 6: Effects of Climate Change on Forest Vegetation
USDA Forest Service RMRS-GTR-375. 2018 163

Swanson, F.J.; Jones, J.A.; Wallin, D.O.; Cissel, J.H. 1994. Natural 

variability: Implications for ecosystem management. Volume 

II: Ecosystem management principles and applications. In: 

Eastside forest ecosystem health assessment. Gen. Tech. Rep. 

PNW-GTR-318. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station: 80–94.

Swetnam, T.W.; Allen, C.D.; Betancourt, J.L. 1999. Applied 

historical ecology: Using the past to manage for the future. 

Ecological Applications. 9: 1189–1206.

Szaro, R.C. 1990. Southwestern riparian plant communities: 

Site characteristics, tree species distributions, and size-class 

structures. Forest Ecology and Management. 33/34: 315–334.

Tang, K.; Feng, X.; Funkhouser, G. 1999. The δ13C of tree rings 

in full-bark and strip-bark bristlecone pine trees in the White 

Mountains of California. Global Change Biology. 5: 33–40.

Tauer, C.G.; Harris, K.D.; Van Haverbeke, D.F. 1987. Seed source 

influences juniper seedling survival under severe drought stress. 

Res. Note RM-RN-470. Fort Collins, CO: U.S. Department of 

Agriculture, Rocky Mountain Forest and Range Experiment 

Station.

Taylor, J.; Sturdevant, N. 1998. Limber pine mortality on the Lewis 

and Clark National Forest, Montana. For. Health Protect. Rep. 

98-5. Missoula, MT: U.S. Department of Agriculture, Forest 

Service, Northern Region: 1–7.

Temperli, C.; Bugmann, H.; Elkin, C. 2013. Cross-scale 

interactions among bark beetles, climate change, and wind 

disturbances: A landscape modeling approach. Ecological 

Monographs. 83: 383–402.

Tisdale, E.W.; Hironaka, M. 1981. The sagebrush-grass region: 

A review of the ecological literature. Bull. 33. Moscow, ID: 

University of Idaho, Forest, Wildlife and Range Experiment 

Station.

Tomback, D.F. 1982. Dispersal of whitebark pine seeds by Clark’s 

nutcracker: A mutualism hypothesis. Journal of Animal 

Ecology. 51: 451–467.

Tomback, D.F. 1983. Nutcrackers and pines: coevolution or 

coadaptation? In: Nitecki, M.H., ed. Coevolution. Chicago, IL: 

University of Chicago Press: 179–223.

Tomback, D.F. 1998. Clark’s nutcracker (Nucifraga columbiana). 

The Birds of North America. 331: 1–23.

Tomback, D.F.; Achuff, P. 2010. Blister rust and western forest 

biodiversity: Ecology, values and outlook for white pines. 

Forest Pathology. 40: 186–225.

Tomback, D.; Arno, S.F.; Keane, R.E. 2001. Whitebark pine 

communities: ecology and restoration. Washington, DC: Island 

Press.

Tracy, J.L.; Robbins, T.O. 2009. Taxonomic revision and 

biogeography of the Tamarix-feeding Diorhabda elongata

(Brullé, 1832) species group (Coleoptera: Chrysomelidae: 

Galerucinae: Galerucini) and analysis of their potential in 

biological control of Tamarisk. Auckland, New Zealand: 

Magnolia Press.

Turner, M.G.; Romme, W.H.; Gardner, R.H. 1999. Prefire 

heterogeneity, fire severity, and early postfire plant 

reestablishment in subalpine forests of Yellowstone National 

Park, Wyoming. International Journal of Wildland Fire. 9: 

21–36.

Urban, D.L.; Harmon, M.E.; Halpern, C.B. 1993. Potential 

response of Pacific Northwestern forests to climatic change, 

effects of stand age and initial composition. Climatic Change. 

23: 247–266.

U.S. Fish and Wildlife Service [USFWS]. 2011. Endangered and 

threatened wildlife and plants: 12-month finding on a petition 

to list Pinus albicaulis as endangered or threatened with critical 

habitat. Federal Register. 76: 42631-42654.

Van Dersal, W.R. 1938. Native woody plants of the United States, 

their erosion-control and wildlife values. Washington, DC: U.S. 

Department of Agriculture.

Vandersande, M.W.; Glenn, E.P.; Walworth, J.L. 2001. Tolerance 

of five riparian plants from the lower Colorado River to salinity 

drought and inundation. Journal of Arid Environments. 49: 

147–159.

Van Devender, T.R. 1987. Late quaternary history of pinyonjuniper-oak woodlands dominated by Pinus remota and Pinus 

edulis. In: Everett, R.L., comp. Proceedings, pinyon-juniper 

conference; January 13-16, 1986; Reno, NV, Gen. Tech. Rep. 

INT-GTR-215. U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station, Ogden, 

UT: 99–103.

Vanoni, M.; Bugmann, H.; Nötzli, M.; Bigler, C. 2016. Drought 

and frost contribute to abrupt growth decreases before tree 

mortality in nine temperate tree species. Forest Ecology and 

Management. 382: 51–63.

Vasek, F.C.; Thorne, R.F. 1977. Transmontane coniferous 

vegetation. In: Barbour, M.G.; Major, Jack, eds. Terrestrial 

vegetation of California. New York: John Wiley and Sons: 

797–832.

Villalba, R.; Veblen, T.T.; Ogden, J. 1994. Climatic influences on 

the growth of subalpine trees in the Colorado Front Range. 

Ecology. 75: 1450–1462.

Wadleigh, L.; Jenkins, M.J. 1996. Fire frequency and the 

vegetative mosaic of a spruce-fir forest in northern Utah. Great 

Basin Naturalist. 56: 28–37.

Wagener, W.W.; Mielke, J.L. 1961. A staining-fungus root disease 

of ponderosa, Jeffrey, and pinyon pine. Plant Disease Reporter. 

45: 831–835.

Walker, R.F.; Geisinger, D.R.; Johnson, D.W.; Ball, J.T. 1995. 

Interactive effects of atmospheric CO2

 enrichment and soil N 

on growth and ectomycorrhizal colonization of ponderosa pine 

seedlings. Forest Science. 41: 491–500.

Walters, J.W. 1978. A guide to forest diseases of southwestern 

conifers. R3 78-9. Albuquerque, NM: U.S. Department of 

Agriculture, Forest Service, Southwest Region, Forest Insect 

and Disease Management.

Wang, T.; Hamann, A.; Yanchuk, A.; [et al.]. 2006. Use of response 

functions in selecting lodgepole pine populations for future 

climates. Global Change Biology. 12: 2404–2416.

Waring, R.H.; Running, S.W. 1998. Forest ecosystems: Analysis at 

multiple scales. 2nd ed. San Diego, CA: Academic Press.

Warwell, M.V.; Rehfeldt, G.E.; Crookston, N.L. 2007. Modeling 

contemporary climate profiles of whitebark pine (Pinus 

albicaulis) and predicting responses to global warming. In: 

Goheen, E.M.; Sniezko, tech. coords. Proceedings of the 

conference on whitebark pine: A Pacific Coast perspective. 

August 27-31, 2006; Ashland, OR. R6-NR-FHP-2007-01. 

Ashland, OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Region: 139–142.

Chapter 6: Effects of Climate Change on Forest Vegetation
164 USDA Forest Service RMRS-GTR-375. 2018

Watling, J.I.; Romañach, S.S.; Bucklin, D.N.; [et al.]. 2012. Do 

bioclimate variables improve performance of climate envelope 

models? Ecological Modelling. 246: 79–85.

Watt, A.S. 1947. Pattern and process in the plant community. 

Journal of Ecology. 35: 1–22.

Weed, A.S.; Bentz, B.J.; Ayres, M.P.; Holmes, T.P. 2015. 

Geographically variable response of Dendroctonus ponderosae

to winter warming in the western United States. Landscape 

Ecology. 30: 1075–1099.

Weedbusters. n.d. Crack willow. http://www.weedbusters.org.

nz/weed-information/salix-fragilis/59 [Accessed October 30, 

2016].

Welsh, S.L.; Atwood, N.D.; Goodrich, S.; Higgins, L.C., eds. 1987. 

A Utah flora. The Great Basin Naturalist Memoir 9. Provo, UT: 

Brigham Young University.

West, N.E.; Rea, K.H.; Tausch, R.J. 1975. Basic synecological 

relationships in pinyon-juniper woodland understory vegetation 

related to climate. In: Gifford, G.F.; Busby, F.E., eds. The 

pinyon-juniper ecosystem: A symposium, May 1975, Logan, 

UT. Logan, UT: Utah State University, Agricultural Experiment 

Station: 41–53.

White, C.A.; Olmsted, C.E.; Kay, C.E. 1998. Aspen, elk, and fire in 

the Rocky Mountain National Parks of North America. Wildlife 

Society Bulletin. 26: 449–462.

Whited, D.C.; Lorang, M.S.; Harner, M.J.; [et al.]. 2007. Climate, 

hydrologic disturbance, and succession: drivers of floodplain 

pattern. Ecology. 88: 940–953.

Whitlock, C.; Bartlein, P.J. 1993. Spatial variations of Holocene 

climatic change in the Yellowstone region. Quaternary 

Research. 39: 231–238.

Wikars, L.O.; Schimmel, J. 2001. Immediate effects of fire-severity 

on soil invertebrates in cut and uncut pine forests. Forest 

Ecology and Management. 141: 189–200.

Williams, A.P.; Allen, C.D.; Millar, C.I.; [et al.]. 2010. Forest 

responses to increasing aridity and warmth in the southwestern 

United States. Proceedings of the National Academy of 

Sciences, USA. 107: 21289–21294.

Wilson, J.L.; Tkacz, B.M. 1996. Historical perspectives on forest 

insects and pathogens in the Southwest: Implications for 

restoration of ponderosa pine and mixed conifer forests. In: 

Covington, W.; Wagner, P.K., tech. coords. Conference on 

adaptive ecosystem restoration and management: Restoration of 

Cordilleran conifer landscapes of North America: Proceedings; 

June 6-8, 1996; Flagstaff, AZ. Gen. Tech. Rep. RM-GTR-278. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station: 26–31.

Winkel, V.K.; Syzdek, D.J. 2015. Response of vegetation after 

wildfire on the Warm Springs Natural Area in Moapa, Nevada. 

Presentation at the annual meeting of the Society of Ecological 

Restoration Southwest chapter, November 21, 2015. http://

chapter.ser.org/southwest/files/2016/03/Winkel_WSNA-FirePresentation-November-2015D_2.pdf [Accessed October 30, 

2016].

Chapter 6: Effects of Climate Change on Forest Vegetation

Wittie, Roger D.; McDaniel, Kirk C. 1990. Effects of tebuthiuron 

and fire on pinyon-juniper woodlands in southcentral New 

Mexico. In: Krammes, J. S., tech. coord. Effects of fire 

management on southwestern natural resources: Proceedings 

of the symposium; November 15-17, 1988; Tucson, AZ. Gen. 

Tech. Rep. RM-GTR-191. Fort Collins, CO: U.S. Department 

of Agriculture, Forest Service, Rocky Mountain Forest and 

Range Experiment Station: 174–179.

Woodward, A.; Silsbee, D.G.; Schreiner, E.G.; Means, J.E. 1994. 

Influence of climate on radial growth and cone production 

in subalpine fir (Abies lasiocarpa) and mountain hemlock 

(Tsuga mertensiana). Canadian Journal of Forest Research. 24: 

1133–1143.

Worrall, J.J.; Rehfeldt, G.E.; Hamann, A.; [et al.]. 2013. Recent 

declines of Populus tremuloides in North America linked to 

climate. Forest Ecology and Management. 299: 35–51.

Wright, H.A. 1972. Shrub response to fire. In: McKell, C.M.; 

Blaisdell, J.P.; Goodin, J.R., eds. Wildland shrubs—Their 

biology and utilization: proceedings of a symposium; July 

1971; Logan, UT. Gen. Tech. Rep. INT-GTR-1. Ogden, UT: 

U.S. Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station: 204–217.

Wright, H.A.; Bailey, A.W. 1982. Fire ecology: United States and 

southern Canada. New York, NY: John Wiley and Sons.

Wu, Z.; Dijkstra, P.; Koch, G.W.; [et al.]. 2011. Responses of 

terrestrial ecosystems to temperature and precipitation change: 

A meta-analysis of experimental manipulation. Global Change 

Biology. 17: 927–942.

Xu, C.; Gertner, G.Z.; Scheller, R.M. 2009. Uncertainties in the 

response of a forest landscape to global climatic change. Global 

Change Biology. 15: 116–131.

Young, J.A.; Budy, J.D. 1979. Historical use of Nevada’s pinyonjuniper woodlands. Journal of Forest History. 23: 112–121.

Zavarin, E.; Snajberk, K. 1973. Variability of the wood 

monoterpenoids from Pinus aristata. Biochemical Systematics. 

1: 39–44.
USDA Forest Service RMRS-GTR-375. 2018 165

Introduction

Nonforest ecosystems, as they are addressed in this 

chapter, contain woodland, shrubland, herbaceous, wetland, 

or riparian vegetation types. They are estimated to occupy 

over 30 million acres and 50 percent of the U.S. Department 

of Agriculture Forest Service (USFS) Intermountain Region 

(table 7.1). These diverse ecosystems range in elevation 

from desert floors to mountain peaks above 11,000 feet and 

occupy a wide variety of sites, from deep and highly productive soils to very shallow nonproductive soils. Other than 

riparian and wetland ecosystems, nonforest vegetation types 

tend to occur in more arid environments or are otherwise 

controlled by edaphic features such as soil depth, drainage, 

or chemical (saline) characteristics.

The diversity and varied conditions of nonforest ecosystems in the Intermountain Adaptation Partnership (IAP) 

region present challenges for studying the effects of climate 

change. These ecosystems have been exposed to a wide 

variety of uses and impacts, resulting in varied ecological 

conditions across landscapes. Some ecosystems will be less 

resilient to environmental changes such as increasing carbon 

dioxide and other greenhouse gases, warming temperatures, 

and altered amount and timing of seasonal and annual 

precipitation. The objective of this chapter is to provide 

insight into the climate change vulnerability of nonforest 

ecosystems in the IAP region. Climate change vulnerability 

can be defined as the degree to which a system is susceptible 

to and unable to cope with adverse effects of climate change 

(IPCC 2007). This information is intended to provide a basis 

for developing adaptation actions to increase resilience of 

nonforest ecosystems in the IAP region (Chapter 14).

Vulnerability Assessment 

Methods

Climate change vulnerability is a function of the exposure of a system, its sensitivity, and its adaptive capacity 

(IPCC 2007). In a climate change context, exposure can be 

thought of as the degree, duration, or extent of deviation 

in climate to which a system is exposed. Sensitivity is the 

degree to which a system is affected, either positively or 

negatively and directly or indirectly, by climate-related 

Chapter 7: Effects of Climate Change on 

Nonforest Vegetation

Wayne G. Padgett, Matthew C. Reeves, Stanley G. Kitchen, David L. Tart, 

Jeanne C. Chambers, Cheri Howell, Mary E. Manning, and John G. Proctor

stimuli (IPCC 2007). Adaptive capacity is the ability of 

a system to adjust to climate change (including climatic 

variability and extremes) by moderating potential damages, 

taking advantage of opportunities, or coping with the consequences (IPCC 2007).

In considering the potential vulnerability of nonforest ecosystems to the effects of climate change in the 

IAP region, we modeled our assessment on work done 

by NatureServe (Comer et al. 2012) for the Mojave and 

Sonoran Deserts. NatureServe evaluated sensitivity of 

ecosystems to the direct effects of climate change, as well as 

their resilience to climate change (based on landscape condition, invasive species, and adaptive capacity). The combined 

relative ratings for sensitivity and resilience were used to 

determine climate change vulnerability by the year 2060 for 

each vegetation cover type.

For our nonforest vegetation vulnerability assessment, a 

team of experts evaluated sensitivity and adaptive capacity 

(as already defined). Adaptive capacity incorporates factors such as landscape condition, characteristic species and 

genetic diversity, and occurrence of invasive species. For 

example, degraded landscape condition, loss of native species and genetic diversity, and high abundance of invasive 

species would lower the adaptive capacity of an ecosystem. 

We relied on published literature and expert evaluations to 

establish a broad rating system that included five categories 

for evaluating the sensitivity and adaptive capacity of the 

vegetation cover types discussed in this report (table 7.2). 

We also developed numerical vulnerability scores, which 

combined sensitivity and adaptive capacity (e.g., a value 

of 5 was used for high sensitivity and low adaptive capacity and a value of 1 was given to low sensitivity and high 

adaptive capacity) (table 7.2). This system creates some 

transparency in the assessment process and provides a 

means to update the assessment with new information as it 

becomes available.

Vulnerability of Nonforest 

Ecosystems to Climate Change

Many of the rangelands in the IAP region have sustained, 

at one time or another, unmanaged livestock grazing. In 

1902, Albert Potter, a staff member under Gifford Pinchot, 
166 USDA Forest Service RMRS-GTR-375. 2018

the first USFS chief, evaluated the conditions of forests and 

rangelands in Utah (Prevedel and Johnson 2005). Potter’s 

diary provides detailed descriptions of the effects of unmanaged sheep and cattle grazing on the vegetation and soils 

of the forest reserves throughout Utah at that time (Potter 

1902). As he traveled from northern to southern Utah, 

Potter often referred to lands that were “heavily grazed” 

and “heavily stocked” and described lands that were “badly 

tramped out” and “bare of vegetation.” These historical uses 

often led to a change in site potential and ecological states. 

Degraded ecological condition from unmanaged grazing, 

combined with landscape fragmentation, will render many 

sites less resilient to changing climate. These sites have lost 

their diversity in species, structure, and genetic composition, 

and many plants on these sites have decreased vigor, lowering their ability to respond to and cope with the direct (e.g., 

increased temperatures) and indirect effects (e.g., increased 

fire) of climate change.

Other primary management concerns in the IAP region 

include invasive species and uncharacteristic fire regimes, 

or fire regimes (intensity, severity, extent, and timing of fire) 

that differ from those before Euro-American settlement. 

Many low-elevation sagebrush habitats now have significantly shortened fire return intervals (Balch et al. 2013). 

Increasing dominance by invasive cool-season, annual 

grasses has created a positive feedback cycle, characterized 

by frequent fire followed by increased dominance of annual 

grasses creating fuel conditions that facilitate combustion 

(Balch et al. 2013). The invasive species of greatest concern 

is cheatgrass (Bromus tectorum), although other invasive 

annuals such as medusahead (Taeniatherum caput-medusae) 

are growing concerns throughout the region. The expansion 

of these and other species may be supported by elevated 

atmospheric carbon dioxide concentrations, increased area 

burned, and increased soil disturbance (Chambers et al. 

2014; Nowak et al. 2004). In addition, the frequent-fire 

cycle may be exacerbated by wetter and warmer winters, 

which promote cool-season grass growth (fuel production), 

increased fuel levels and continuity, and increased area 

burned (if ignitions occur) (Bradley et al. 2016). Where 

improper grazing occurs, it can also accelerate annual grass 

invasion, resulting in changes in the fire cycle, especially in 

the drier sagebrush types.

Land use legacies, coupled with changing climate, pose 

unique challenges for managers in the region. Potential 

interactions between land use change, management, and 

climate change are not well understood, but the extent to 

which ecosystem resilience has been affected by human 

Table 7.1—Amount of non-forest vegetation cover types in the IAP region, developed from LANDFIRE data.

IAP Region

Middle 

Rockies

Southern 

Greater 

Yellowstone

Uintas and 

Wasatch Front Plateaus

Great Basin 

and Semi 

Desert

---------------------------------------------------------Percent-----------------------------------------------------

Forest 49.3 62.0 65.5 55.4 45.6 15.0

Non-forest 50.7 38.0 34.5 44.6 54.4 85.0

Pinyon-juniper shrublands 

and woodlands 12.6 0.0 0.0 4.9 29.2 37.0

Oak-maple woodlands 2.2 0.0 0.1 9.7 4.4 0.5

Mountain-mahogany 

woodlands 2.1 0.1 0.0 2.3 3.2 6.1

Mountain big sagebrush 

shrublands 13.0 17.9 12.0 13.4 3.5 11.4

Dry big sagebrush 

shrublands 6.5 2.3 0.5 5.4 3.3 20.2

Mountain shrublands 2.2 3.7 2.8 1.4 1.4 0.3

Dwarf sagebrush shrublands 1.2 0.7 0.0 0.3 4.3 1.6

Blackbrush shrublands 0.5 0.0 0.0 0.0 0.1 2.2

Salt desert shrublands 0.3 0.0 0.1 0.4 0.3 1.1

Grasslands 4.3 9.9 2.1 1.0 0.7 1.9

Subalpine forb 2.5 1.6 7.9 2.4 1.5 0.6

Alpine 1.6 0.5 5.7 1.6 1.0 0.3

Riparian 1.3 0.5 1.6 1.9 1.5 1.8

Wetland 0.6 0.7 1.6 0.0 0.0 0.2

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 167

uses will ultimately affect the ability of those ecosystems to 

respond to changing climate.

Climate change projections for the IAP region (Chapter 

3) indicate that average annual minimum and maximum 

temperatures are likely to increase by 5 to 12 oF, mean annual precipitation will remain the same or increase slightly, 

extreme events (e.g., drought and extreme precipitation 

events) will occur more frequently and be more severe, 

and concentrations of carbon dioxide and other greenhouse 

gases in the atmosphere will continue to increase through 

the end of the 21st century. Minimum daily temperatures 

in the Great Basin in the 20th century increased more than 

maximum temperatures (Chambers 2008). In addition, these 

increased minimum daily temperatures have resulted in 

longer frost-free periods. Projections vary somewhat by subregion, but even where precipitation is projected to increase 

slightly, higher temperatures are likely to lead to greater 

effective drought and soil water deficit.

Despite increased moisture stress, net primary productivity (NPP) of vegetation in the IAP region may increase with 

warming temperatures due to greater water-use efficiency 

associated with carbon dioxide fertilization effects (Reeves 

et al. 2014). Projections suggest that there will be a greater 

increase in NPP in the northern cooler and wetter portions of 

the IAP region (Southern Greater Yellowstone and Middle 

Rockies subregions). A short decline in NPP will precede 

a smaller increase in NPP in the southern warmer and drier 

portions of the region (Plateaus and Great Basin and Semi 

Desert subregions) (fig. 7.1). However, the capacity to 

respond to carbon dioxide fertilization varies greatly among 

and within plant functional groups, suggesting that changes 

in NPP will not be expressed uniformly by species within 

plant communities. Ecosystem response to climate change 

throughout the IAP region will vary with local site characteristics (e.g., water holding capacity, soil characteristics) 

and ecological condition.

Paleoecological studies have shown that species respond 

individualistically and at different rates with changing climates, resulting in reshuffling species associations and novel 

community combinations (Delcourt and Delcourt 1981; 

Williams and Jackson 2007). Thus, each species is likely to 

respond differently to future climatic changes and carbon 

dioxide fertilization (Anderson and Inouye 2001), depending 

on physiological tolerances and the competitive ability of 

the species. Consequently, we are likely to see new vegetation communities in the IAP region under changing climate. 

However, because vegetation types, or groups of associated 

species, are widely known and provide a convenient unit of 

assessment, we discuss climate change effects by vegetation 

type, highlighting likely species-level responses.

Table 7.2—Vulnerability ratings for sensitivity and adaptive capacity of non-forest cover types in the IAP region, based on 

published literature and expert evaluations by a team of scientists.

Sensitivity 

rating

Sensitivity 

score

Adaptive 

capacity 

rating

Adaptive 

capacity 

score

Combined 

score Vulnerability

Alpine H 5 L 5 10 Very High

Dry big sagebrush shrublands H 5 L 5 10 Very High

Low-elevation riparian H 5 L-M 4 9 High-Very High

Subalpine forb communities H 5 M 3 8 High

Persistent pinyon-juniper 

woodlands H 5 M 3 8 High 

High-elevation riparian M-H 4 L-M 4 8 High 

Mountain-mahogany 

woodlands M 3 L-M 4 7 Moderate-High

Mountain big sagebrush 

shrublands M 3 L-M 4 7 Moderate-High 

Mountain grasslands M 3 L-M 4 7 Moderate-High

Salt desert shrublands M 3 L-M 4 7 Moderate-High

Mid-elevation riparian M-H 4 M 3 7 Moderate-High

Blackbrush L-M 2 L 5 7 Moderate-High

Dwarf sagebrush shrublands M-H 4 M-H 2 6 Moderate 

Sprouting sagebrush M 3 M 3 6 Moderate 

Oak-maple woodlands L-M 2 M 3 5 Low-Moderate

Mountain shrublands L-M 2 M-H 2 4 Low-Moderate

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
168 USDA Forest Service RMRS-GTR-375. 2018

Woodland Ecosystems

Woodland ecosystems include vegetation stands with 

at least 10 percent cover of tree species that are typically 

less than 40 feet tall at maturity, and often less than 16 

feet tall on relatively harsh sites. Woodlands, in general, 

are more abundant in Utah and Nevada than in Idaho or 

Wyoming (table 7.1). Three woodland types are included in 

this assessment: persistent pinyon-juniper, oak-maple, and 

mountain mahogany. Persistent pinyon-juniper woodlands 

are those dominated by pinyon pine (Pinus edulis, P. monophylla) or juniper, either in combination or as individual 

species. Oak-maple woodlands are dominated by Gambel 

oak (Quercus gambelii) or bigtooth maple (Acer grandidentatum), or both; mountain mahogany woodlands are 

dominated by curl-leaf mountain mahogany (Cercocarpus 

ledifolius). These woodland types generally occur on midelevation sites (but can be found on south-facing slopes at 

higher elevations) and are found on a wide variety of soils.

Persistent Pinyon-Juniper Woodlands

Three general pinyon-juniper vegetation types have been 

defined based on canopy structure, characteristics of the 

understory, and historical disturbance regimes (Romme et al. 

2009): persistent pinyon‐juniper woodlands, wooded shrublands, and pinyon‐juniper savannas. Pinyon-juniper savannas 

are uncommon in the IAP region and are not described here. 

Persistent pinyon-juniper woodlands are those that were 

historically dominated by pinyon (singleleaf pinyon [Pinus 

monophylla] or twoneedle pinyon [P. edulis]) or juniper, 

or both, and where fire was rare, usually because of poor 

soil conditions and low surface fuel levels and continuity. 

Wooded shrublands are characterized by a dominant shrub 

component (most notably mountain big sagebrush [Artemisia 

tridentata ssp. vaseyana] and Wyoming big sagebrush [A. 

t. ssp. wyomingensis], but wooded shrublands also occur in 

dwarf sagebrush ecosystems). The density of pinyon and 

juniper in various combinations increases and decreases over 

time in response to climate and disturbance, including fire 

and insect outbreaks.

Only those plant communities that historically occurred 

as tree-dominated sites for a majority of time under preEuro-American natural disturbance regimes are included in 

our persistent pinyon-juniper woodlands discussion. Many 

sites now dominated by pinyon pines or junipers, or both, 

were historically dominated by sagebrush or other shrubby 

species because of more frequent fire and lack of grazing, 

and these are not included in the woodlands discussion. 

They are, however, included in the discussions of the shrubland landscapes they now occupy.

In many areas where Wyoming big sagebrush, mountain 

big sagebrush, black sagebrush (Artemisia nova), and low 

sagebrush (Artemisia arbuscula) species historically dominated the landscape, expansion by pinyon pine and juniper, 

and to a lesser extent, other conifers, is occurring (Miller 

and Tausch 2001). In advanced stages of expansion, dense 

woodlands completely replace shrubland communities, and 

these changes are commonly attributed to a lengthening of 

fire-free intervals associated with 20th-century fire suppression. However, livestock grazing and climatic conditions 

favorable for tree establishment in the early 20th century also 

affected vegetation (Miller and Tausch 2001). Burkhardt and 

Tisdale (1969) found that western juniper (Juniperus occidentalis) had more than doubled its distribution between the 

Figure 7.1—Average 

and standard 

deviation of net 

primary production 

under the A1B, A2, 

and B2 climate 

change scenarios 

for five subregions 

in the Intermountain 

Adaptation 

Partnership region 

(data from Reeves et 

al. [2014]).

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 169

1860s, when Euro-American settlement of the West began, 

and the time of their study about 100 years later. Miller et al. 

(2008) found that 50 to 75 percent of the sagebrush-steppe 

communities in portions of Idaho, Oregon, Nevada, and 

Utah supported expansion of western juniper, Utah juniper 

(Juniperus osteosperma), or singleleaf pinyon by 1920. 

This rate of expansion has decreased, possibly because of a 

reduction in the rate of establishment (Miller et al. 2008).

To determine the degree to which pinyon-juniper 

woodlands have expanded in the Intermountain Region, 

we compared LANDFIRE biophysical setting (BpS) 

(LANDFIRE 2008) and existing vegetation type (EVT) 

(LANDFIRE 2012) data for the acreage dominated by 

sagebrush shrublands and pinyon-juniper woodlands and 

shrublands. The BpS layer represents vegetation cover 

types that may have been present before Euro-American 

settlement. This layer is based on both the current physical 

environment (NatureServe’s ecological systems classification [Comer et al. 2003]) and an approximation of historical 

disturbance regimes. The EVT layer is an approximation of 

existing land cover types that relies on decision tree models, 

field data, Landsat imagery, elevation, and biophysical gradient data as predictors of vegetation. 

Table 7.3 shows the difference in acres of pinyon-juniper 

woodlands and shrublands and sagebrush shrublands 

between the BpS and EVT layers for each IAP subregion, 

estimating change in dominance of sagebrush and pinyonjuniper dominated landscapes in the Intermountain Region 

since Euro-American settlement. It indicates that pinyonjuniper has increased the most in the Great Basin and Semi 

Desert subregion. Pinyon-juniper has also increased, but to 

a lesser degree, in the Plateaus and the Uintas and Wasatch 

Front subregions.

Vegetation Type Description and Distribution

Persistent pinyon-juniper woodlands are dominated by 

singleleaf pinyon or twoneedle pinyon, and by western 

juniper or Utah juniper in various combinations. Persistent juniper woodlands occur throughout the Great Basin and Semi 

Desert, Plateaus, and Uintas and Wasatch Front subregions, 

Table 7.3—LANDFIRE-derived estimates (percent of the landscape) of change in dominance 

of sagebrush and pinyon-juniper dominated landscapes in the Intermountain Region 

since Euro-American settlement. The biophysical settings (BpS) layer (LANDFIRE 2008) 

represents the vegetation cover type that may have dominated the landscape prior to 

Euro-American settlement. The existing vegetation type (EVT) layer (LANDFIRE 2012) 

is an approximation of existing land cover types that relies on decision tree models, 

field data, Landsat imagery, elevation, and biophysical gradient data as predictors of 

vegetation.

Subregion and cover type BpS EVT

Difference

(EVT – BpS)

----------------------Percent---------------------------

Middle Rockies

Pinyon-juniper woodlands and shrublands 0.0 0.0 0.0

Sagebrush shrublands 100.0 100.0

Southern Greater Yellowstone

Pinyon-juniper woodlands and shrublands 0.0 0.2 +0.2

Sagebrush shrublands 100.0 99.8

Uintas and Wasatch Front

Pinyon-juniper woodlands and shrublands 4.5 20.4 +15.9

Sagebrush shrublands 95.5 79.6

Plateaus

Pinyon-juniper woodlands and shrublands 48.1 72.2 +24.1

Sagebrush shrublands 51.9 27.8

Great Basin and Semi Desert

Pinyon-juniper woodlands and shrublands 0.3 52.7 +52.4

Sagebrush shrublands 99.7 47.3

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
170 USDA Forest Service RMRS-GTR-375. 2018

but are relatively insignificant in the Middle Rockies and 

Southern Greater Yellowstone subregions (fig. 7.2). In the 

IAP region, persistent pinyon-juniper woodlands generally 

make up between 2 and 10 percent of the total woodland areas in any given geographic area (Miller et al. 1999), but they 

are particularly abundant on portions of the Colorado Plateau 

at lower elevations (Romme et al. 2009).

Species composition of pinyon-juniper woodland varies 

across the IAP region. Western juniper occurs along the 

western edge of the Great Basin and Semi Desert subregion 

in southwestern Idaho and northwestern Nevada (fig. 7.2a). 

Utah juniper is the most common tree in the Great Basin and 

Semi Desert subregion, and is widely distributed throughout 

the Plateaus, and Uintas and Wasatch Front subregions; it 

is much less abundant in the Middle Rockies and Southern 

Greater Yellowstone subregions (Lanner 1983) (fig. 7.2b). 

Singleleaf pinyon is mostly limited to woodlands in the 

California, Nevada, and extreme southwestern Utah portions 

of the Great Basin and Semi Desert subregion (fig. 7.2c). 

A few disjunct populations occur in other National Forest 

lands in Utah, notably in the Mollens Hollow Research 

Natural Area on the Logan District of the Uinta-WasatchCache National Forest. Twoneedle pinyon occurs at lower 

elevations of National Forests in the Plateaus subregion 

and in adjacent landscapes of the Uintas and Wasatch Front 

subregion (fig. 7.2d).

Figure 7.2—Modeled distribution of juniper and pinyon pine species in the Intermountain Adaptation Partnership region: (a) 

western juniper, (b) Utah juniper, (c) singleleaf pinyon, and (d) twoneedle pinyon. Data are from USDA FS (2017). Model 

projections to 2090 are based on two global circulation models (HadCM3GGa1, CGCM2_ghga), assuming an increase in 

greenhouse gas emissions of 1 percent per year since 1990 (see Rehfeldt et al. [2006]). 

a) b)

c) d)

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 171

Pinyon-juniper woodlands often occur on rocky upland 

sites with shallow and coarse-textured soils that support 

sparse herbaceous vegetation cover (fig. 7.3). Curl-leaf 

mountain mahogany may be a codominant or subdominant 

woodland species. Immediately after disturbance, these sites 

are dominated by shrubs, grasses, or forbs, or a combination, which may persist for long periods of time.

The age of many pinyon and junipers in persistent stands 

throughout the West suggests that natural stand-replacement 

fires of mixed to high severity may be infrequent to rare, averaging 100 to 500 years (Bauer and Weisberg 2009; Miller 

et al. 1999; Romme et al. 2009). Low-intensity surface 

fires had a very limited role in affecting stand structure and 

dynamics in most persistent woodlands historically; most 

fires were high-severity, stand-replacement fires (Romme et 

al. 2009). However, fire history is often difficult to measure 

in these ecosystems because of the lack of fire scar evidence 

in many pinyon-juniper ecosystems (Baker and Shinneman 

2004).

Sensitivity to Climate Change: High

Occupying the transition zone between mesic forests at 

higher elevations and xeric environments too dry for trees 

at lower elevations, pinyon-juniper woodlands may be 

highly sensitive to changes in temperature and precipitation 

(Romme et al. 2009). Climate envelope model projections 

for species dominant in pinyon-juniper woodlands indicate 

a significant contraction of this type in Nevada and Utah 

(classified as Great Basin conifer forest by Rehfeldt et al. 

2012). The likely causes of these projected contractions 

include higher temperatures and increasing drought stress.

In addition to the direct effects of climate change, 

pinyon-juniper woodlands may be sensitive to the indirect 

effects of climate change, including increased area burned 

(McKenzie et al. 2004) and insect outbreaks (Romme et al. 

2009). For example, a major pinyon pine mortality event in 

2002–2004 in Colorado, Arizona, New Mexico, and Utah 

resulted from high temperatures, drought, and bark beetle 

outbreaks (Romme et al. 2009). Fire directly causes tree 

mortality, and warm and dry conditions after fires may also 

inhibit tree regeneration, affecting species composition and 

long-term vegetation trajectories (Floyd et al. 2015).

As a result of these sensitivities to the direct and indirect 

effects of warming, persistent pinyon-juniper woodlands 

are rated as highly sensitive to climate change (table 7.2). 

However, Utah juniper, which is the most common juniper 

in the region, has been observed moving downslope into 

communities currently dominated by sagebrush. At the same 

time, pinyon pines have been observed moving upslope. It 

is unclear which novel communities will form in a changing 

climate, but some new communities that include juniper and 

possibly pinyon are likely to remain, at least on portions of 

the landscape.

Adaptive Capacity: Moderate

Persistent pinyon-juniper woodlands are a complex set 

of ecosystems with a high degree of variation among sites 

(Romme et al. 2009). Many sites on which this vegetation 

type occurs have relatively low abundance of invasive 

species, and because many sites with persistent pinyonjuniper woodlands occur in well-protected, rocky areas 

with relatively little pressure from livestock grazing and 

other human uses, their ecological condition has not been 

degraded. However, with climate change, they may be affected by invasive species from adjacent plant communities, 

specifically invasive annual grasses such as cheatgrass, 

particularly at the lower-elevation ecotones (Chambers et al. 

2014). Cheatgrass invasion significantly shortens fire return 

intervals (Chambers et al. 2014) and could cause major 

ecological change in these woodlands. For this reason, the 

Figure 7.3—Utah juniper. The 

presence of very old Utah 

juniper suggests that this 

rocky site would only rarely 

develop a grassy understory 

capable of carrying a surface 

fire (from Tausch and Hood 

[2007]).

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
172 USDA Forest Service RMRS-GTR-375. 2018

adaptive capacity of pinyon-juniper woodlands is rated as 

moderate (table 7.2).

Vulnerability to Climate Change: High

The vulnerability of persistent pinyon-juniper is high because of high sensitivity to the direct and indirect effects of 

climate change and moderate adaptive capacity (table 7.2). 

Comer et al. (2012) found that the vulnerability of Great 

Basin pinyon-juniper woodlands in the Mojave Desert, 

south of the Great Basin, was moderate, because although 

these ecosystems were highly sensitive to climate change 

(they are projected to contract with warming), their adaptive 

capacity was also high. In our assessment, we gave greater 

importance to the effects of climate change on adjacent 

landscapes that would indirectly affect the resilience of the 

persistent pinyon-juniper woodlands, leading to a vulnerability rating of high.

Oak-Maple Woodlands

Vegetation Type Description and Distribution

Oak-maple woodlands are dominated by mature stands 

of bigtooth maple or Gambel oak, or both, under natural 

disturbance regimes. These woodlands are most abundant in 

the Uintas and Wasatch Front subregion and are also found 

in the Plateaus subregion (table 7.1, fig. 7.4). Gambel oak is 

more widespread in the Plateaus subregion, occurring over 

a greater range of elevations, but generally does not extend 

north of Brigham City in northern Utah. Bigtooth maple, 

on the other hand, extends through central Utah into the 

Southern Greater Yellowstone subregion. Although characteristic of these woodlands, both species (especially Gambel 

oak) occur as subdominant components of mountain 

shrubland communities, and boundaries between these vegetation types are sometimes arbitrary.

Historical fire regimes in oak-maple woodlands are not 

well understood because of a lack of physical evidence such 

as fire scars (Kaufmann et al. 2016). However, these woodlands are well adapted to fire. Immediately after disturbance, 

these sites are dominated by shrubs, grasses, or forbs. Both 

dominant tree species, as well as many of the associated 

shrubs and herbaceous species, sprout from the root crown 

following top kill, so postdisturbance grass-forb dominance 

is short lived.

Sensitivity to Climate Change: Low to Moderate

Climate envelope model projections show a slight restriction of current habitats of Gambel oak and an expansion of 

its climate envelope into Idaho and Montana by 2060; a few 

of these models show expansion into eastern Nevada as well 

(Rehfeldt et al. 2006). During that same time period, some 

models indicate an expansion of the bigtooth maple climate 

envelope into eastern Idaho and Montana, although the 

distribution throughout much of its current range decreases. 

For these reasons, we have determined that this vegetation 

type has a low to moderate sensitivity to the effects of climate change (table 7.2).

Adaptive Capacity: Moderate

Gambel oak and bigtooth maple sprout after fire, and can 

easily reestablish following disturbance (Engel 1983). In addition, there are many species associated with Gambel oak 

or bigtooth maple communities (Simonin 2000; Tollefson 

2006), many of which sprout following fire. This diversity 

of fire-adapted species provides these communities with 

significant adaptive capacity. However, adaptive capacity 

a) b)

Figure 7.4—Modeled distribution of (a) bigtooth maple and (b) Gambel oak in the Intermountain Adaptation Partnership region. 

Data are from USDA FS (2017). Model projections to 2090 are based on two global circulation models (HadCM3GGa1, 

CGCM2_ghga), assuming an increase of greenhouse gas emissions of 1 percent per year since 1990 (see Rehfeldt et al. 

[2006]). 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 173

of these ecosystems is affected to some degree by the 

number of invasive species capable of invading following 

disturbance, which can lower species diversity and alter fire 

regimes. This type is given a moderate adaptive capacity 

rating because of the potential for invasive species establishment (table 7.2).

Vulnerability to Climate Change: Low to Moderate

The vulnerability of oak-maple woodlands is rated as 

low to moderate because of the low to moderate sensitivity 

and moderate adaptive capacity to climate change (table 

7.2). Although the current locations of these woodlands may 

change over time, the amount of land covered by this vegetation type may increase to some degree outside its current 

distribution.

Mountain Mahogany Woodlands

Vegetation Type Description and Distribution

Curl-leaf mountain mahogany woodlands typically occur 

throughout the IAP region in isolated patches on warm, 

rocky ridges and on other sites with dry, coarse-textured 

soils, primarily on western or southern exposures (Davis 

and Brotherson 1991). These woodlands are most common 

in the Great Basin and Semi Desert, Plateaus, and Uintas 

and Wasatch Front subregions (table 7.1). Historically, 

this type was restricted to rocky areas that were probably 

protected from fire, but curl-leaf mountain mahogany, like 

pinyon-juniper (although to a lesser extent), has expanded 

because of fire exclusion in habitats where frequent fires 

historically kept it in check (Davis and Brotherson 1991). 

Most often, curl-leaf mountain mahogany is killed by 

fire, and regeneration is only by seed (Gruell et al. 1985). 

However, early postfire recolonization by mountain mahogany is facilitated by seeds that are well adapted for wind 

dispersal. Consequently, this species is often among the 

first nonsprouting shrubs and trees to reoccupy a burn when 

unburned plants provide a seed source nearby. Curl-leaf 

mountain mahogany can survive for long periods (Riegel 

et al. 2006), and on sites that have sustained long fire-free 

periods, mahogany trees have been found to be over 400 

years old (Dealy 1975).

Sensitivity to Climate Change: Moderate

Climate envelope models project a significant restriction 

in the climate envelope of curl-leaf mountain mahogany 

(Rehfeldt et al. 2006). The species occurs across a broad 

elevational gradient (7,000–11,000 feet), which suggests 

some resilience to climate change. Curl-leaf mountain 

mahogany is often found on soils that have low fertility 

(Gucker 2006) or contain calcium carbonates (although 

this trait does not seem to be as evident in the Great Basin 

as elsewhere in its distribution) (Gonella and Neel 1995). 

These traits, combined with relatively high predation of its 

seeds (Dealy 1979), suggest the species may not be a good 

competitor. However, the affinity of the species for poor 

soils suggests it is tolerant of poor conditions, and it could 

potentially expand into areas where other species become 

less competitive in warmer and drier conditions. For these 

reasons, and because of the similarity of some mountain mahogany woodland sites to those of persistent pinyon-juniper 

woodland sites, the sensitivity of these woodlands is rated as 

moderate (table 7.2).

Adaptive Capacity: Low to Moderate

The lack of fire since the early 1900s has allowed 

curl-leaf mountain mahogany to expand to some degree 

and occupy new habitats. Livestock grazing has also been 

largely absent from these woodland communities because 

of the difficult terrain and sparse forage (USDA FS 2013). 

However, abundance of invasive species has increased in 

some of these communities, potentially affecting fire return 

intervals and resilience. In addition, this vegetation type 

generally does not have a high level of site diversity. For 

these reasons, and because the species grows slowly and 

does not sprout following fire, the adaptive capacity of 

mountain mahogany woodlands is rated as low to moderate 

(table 7.2).

Vulnerability to Climate Change: Moderate to High

The vulnerability of mountain mahogany woodlands 

to climate change is rated moderate to high because of the 

moderate sensitivity rating and the low to moderate adaptive 

capacity rating (table 7.2). These communities are limited to 

specific sites and have few places where they can expand.

Shrubland Ecosystems

Shrubland ecosystems are vegetation communities with 

at least 10 percent cover of shrub species that are generally 

less than 6.5 feet tall at maturity, and often less than 1.5 feet 

tall on relatively harsh sites. Shrubland ecosystems include 

those dominated by dwarf and big sagebrush or a variety of 

upland shrub species, as well as all salt desert communities. 

The term shrub-steppe is often applied to shrubland ecosystems when herbaceous understory vegetation (generally 

perennial grasses and forbs) is sufficiently abundant to codominant. Mountain big sagebrush shrubland (shrub-steppe) 

is the most common shrubland type in the IAP region. 

Mountain big sagebrush and dry big sagebrush shrublands 

make up nearly 40 percent of the nonforest vegetation in the 

IAP region (table 7.1). As already noted (table 7.3), much of 

the area historically dominated by these shrublands, as well 

as other sagebrush-dominated shrublands, has been invaded 

by pinyon pine or juniper. Mountain shrublands, though 

present throughout the region, are more extensive in the 

northern subregions (Middle Rockies and Southern Greater 

Yellowstone). Dry big sagebrush shrublands are most abundant on National Forest lands in the Great Basin and Semi 

Desert subregion. Dwarf sagebrush shrublands also occur 

throughout the region, but are most abundant in the Plateaus 

subregion. Blackbrush and salt desert shrublands occupy 

only minor portions of National Forest lands in the region, 

but are more widespread on adjacent landscapes at lower 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
174 USDA Forest Service RMRS-GTR-375. 2018

elevations in the Plateaus and Great Basin and Semi Desert 

subregions.

Various species and varieties of sagebrush have been 

combined into four unique sagebrush types because of 

similarities in environments they inhabit, plant structure, or 

response to disturbances. These sagebrush types are:

• Mountain big sagebrush shrublands—

Mountain big sagebrush and Bonneville big 

sagebrush (Artemisia tridentata ssp. vaseyana × 

wyomingensis).

• Dry big sagebrush shrublands—Wyoming big 

sagebrush and basin big sagebrush (Artemisia 

tridentata ssp. tridentata).

• Sprouting sagebrush shrublands—Mountain 

silver sagebrush (A. cana ssp. viscidula), snowfield 

sagebrush (A. spiciformis), and threetip sagebrush 

(A. tripartita). Timberline sagebrush (A. rothrockii) 

is endemic to the Sierra Nevada in California and 

has very limited distribution within the region. Thus, 

it is not addressed in any detail in this report.

• Dwarf sagebrush shrublands—Low sagebrush, 

black sagebrush, scabland sagebrush (A. rigida), 

Bigelow sagebrush (A. bigelovii), Owyhee sagebrush 

(A. papposa), budsage (A. spinescens), and pygmy 

sagebrush (A. pygmaea).

Although Wyoming and various low-growing sagebrush 

species are common throughout the region, mountain big 

sagebrush communities occupy the greatest area of USFS 

lands (table 7.1). Wyoming and basin big sagebrush types 

were aggregated because of similarities in life history traits, 

and because they represent critical habitats for many species 

of birds and wild and domestic ungulates. However, basin 

big sagebrush occupies sites with deeper soils (often on 

alluvial fans). These conditions tend to increase available 

moisture, with higher coverage by perennial bunchgrasses, 

suggesting these sites may be more resilient and resistant to 

various threats (Chambers et al. 2013). Similarly, the low 

or dwarf sagebrush species were combined for their common physical structure, unique habitats they represent, and 

similar life histories. Finally, all sprouting sagebrush species 

were combined because of their similar response to fire.

Overall, about 10 percent of the sagebrush-steppe of the 

Southwest and Intermountain West has been converted to 

dryland or irrigated agriculture (Noss et al. 1995). Over 99 

percent of the remaining sagebrush-steppe has been affected 

by livestock, and about 30 percent of that area has been 

heavily grazed. In addition, much of the sagebrush in the 

IAP region contains annual invasive species, with impacts 

concentrated in lower-elevation, more xeric sagebrush 

landscapes (Miller et al. 2011). Various nonnative perennial 

species, such as crested wheatgrass (Agropyron cristatum 

and A. desertorum), intermediate wheatgrass (Thinopyrum 

intermedium), smooth brome (Bromus inermis), and forage 

kochia (Bassia prostrata), have been seeded for forage, 

fire breaks, or erosion control throughout the region. These 

species now dominate large areas, and continue to be seeded 

during postfire rehabilitation across much of the region despite some concerns for impacts on native species diversity 

(Davies et al. 2013; Lesica and Deluca 1996).

Effects of Climate Change

Several recent studies modeled the effects of climate 

change on sagebrush shrublands in the western United 

States (Balzotti et al. 2016; Bradley 2010; Schlaepfer et 

al. 2012; Still and Richardson 2015). Each of these studies 

concluded that climate change is likely to have significant 

effects on sagebrush ecosystems. Climate change risk to 

sagebrush is most pronounced in southern Nevada because 

decreased summer precipitation and increased temperatures 

there could make current sagebrush habitat climatically 

unsuitable in the future (Bradley 2010; Schlaepfer et al. 

2012). Still and Richardson (2015) projected a 39 percent 

loss of the climate suitable for Wyoming big sagebrush 

across its range in the West. Neilson (2005) projected a 

loss of 12 percent of all current sagebrush habitat with each 

1.8-°F increase in temperature, and the southern limit of 

suitable climate for many sagebrush species may shift to the 

northern Great Basin.

Sagebrush species, however, commonly hybridize, 

which has been shown to provide greater ability to adapt to 

changing environments (Hoffman and Sgrò 2011; McArthur 

2000). In addition, all major species of sagebrush included 

in this discussion have both diploid and polyploid populations (McArthur 2000). Polyploids are smaller with slower 

growth rates that make them better adapted to stressful 

environments than their diploid relatives (Sanderson et al. 

1989). Sagebrush, as a complex, may have greater ability to 

adapt to climate change than other associated taxa. It is impossible, however, to understand what effect new genotypes 

could have on future generations of sagebrush, how quickly 

they may develop, and how emergence of new genotypes 

may affect their ability to occupy sites that are becoming 

increasingly warmer and drier.

Mountain Big Sagebrush Shrublands

Vegetation Type Description and Distribution

Mountain big sagebrush plant communities occur 

throughout the IAP region and are generally found at 

elevations between 4,500 and 10,200 feet on moderately 

deep to deep, well-drained soils and on sites that are more 

cool and mesic than those associated with Wyoming big 

sagebrush plant communities (Blaisdell et al. 1982; Tueller 

and Eckert 1987; West et al. 1978; Winward 1980; Winward 

and Tisdale 1977). Mountain big sagebrush communities 

are dominated by mountain big sagebrush or xeric big sagebrush for long periods of time under historical disturbance 

regimes. Basin big sagebrush, snowfield sagebrush, mountain silver sagebrush, or threetip sagebrush may also occur 

as minor components in this vegetation type. Other shrub 

taxa, such as yellow rabbitbrush (Chrysothamnus viscidiflorus), rubber rabbitbrush (Ericameria nauseosa), mountain 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 175

snowberry (Symphoricapos oreophilus), Woods’ rose (Rosa 

woodsii), Saskatoon serviceberry (Amalenchier alnifolia), 

and chokecherry (Prunus virginiana) may be present at 

subdominant levels. Except where degraded by chronic 

overgrazing, the herbaceous understory of mountain big 

sagebrush communities supports a rich variety of perennial 

grasses and forbs that are critical for system resilience and 

wildlife habitat, and codominates even in late-seral communities. Natural fire regimes maintain spatial and temporal 

mosaics of herb-dominated to shrub-dominated patches 

in various stages of succession, and prevent conversion to 

conifer forests or woodlands.

Historically the presettlement fire return intervals for 

mountain big sagebrush were relatively short, (35–80 years) 

(Heyerdahl et al. 2006; Kitchen and McArthur 2007; Miller 

et al. 2001) compared to Wyoming big sagebrush (more than 

100 years) (Baker 2006; Lesica et al. 2007). On cooler, more 

mesic sites, fire-free intervals have increased to between 50 

and 150 years. The lack of fire, combined with the effects of 

livestock herbivory, has caused much of the increase in pinyon pines and juniper, with a consequent loss of herbaceous 

and shrub cover throughout much of the range of mountain 

big sagebrush (Crawford et al. 2004; Miller and Rose 1999).

Sensitivity to Climate Change: Moderate

Mountain big sagebrush shrublands have moderate 

sensitivity to climate change. Sensitivity to climate change 

varies with elevation, with lower-elevation stands more 

sensitive than those at higher elevations (Balzotti et al. 

2016). Mountain big sagebrush growth is dependent on temperature, precipitation, and maximum snow depth (Poore 

et al. 2009). Winter precipitation has the strongest relationship with growth (Poore et al. 2009). At higher elevations 

growth is positively correlated with temperature, but lower 

elevations may experience decreased growth with warming. 

Likewise, production in higher-elevation vegetation communities may increase in the future (Reeves et al. 2014). Given 

that increased temperatures and a reduction in snowpack are 

likely with climate change, mountain big sagebrush growth 

rates are likely to decrease at lower elevations but could be 

improved at temperature-limited sites toward the higher end 

of the species distribution, thus potentially having significant and asymmetric effects on sagebrush cover.

Adaptive Capacity: Low to Moderate

Adaptive capacity of mountain big sagebrush shrublands 

is rated as low to moderate (table 7.2), depending on elevation and site conditions, land use history, fire suppression, 

and abundance of invasive species. A few areas of mountain 

big sagebrush shrublands have been converted to agricultural lands, and most of those that remain are used for domestic 

livestock grazing because of the palatable herbaceous 

undergrowth. Those that have had chronic improper grazing 

typically have high sagebrush canopy cover and low vigor 

of native herbaceous species, and thus may have invasive 

plant species present in varying amounts. In intact mountain 

big sagebrush shrublands, species and functional type diversity may confer resilience to climate change.

Mountain big sagebrush is easily killed by fire and does 

not resprout; postfire recovery is from seed that survives 

fire or disperses from unburned areas. Although recovery 

for mountain big sagebrush is often rapid (15–35 years) 

(Kitchen and McArthur 2007; Nelson et al. 2014), longer 

recovery times (50–150 years) are expected if residual 

seed are absent or if seedlings fail to establish from the 

short-lived seed bank (Baker 2006, 2011; Nelson et al. 

2014). Postfire recovery is currently problematic on warmer 

and drier sites and may become a problem on cooler and 

moister sites in the future if the frequency and intensity of 

fires increase as projected (Abatzoglou and Kolden 2013). 

Regeneration of big sagebrush postfire is strongly linked to 

winter and spring precipitation (Nelson et al. 2014), which 

is not projected to change significantly in the IAP region 

(Chapter 3).

With increased fire severity and frequency, there is likely 

to be a shift in community composition to dominance by 

fire-adapted shrub and herbaceous species and possibly 

nonnative species. Fire-adapted shrub species (e.g., rubber rabbitbrush, yellow rabbitbrush, mountain snowberry, 

Wood’s rose, Saskatoon serviceberry, chokecherry) may 

increase in abundance following fire (Fischer and Clayton 

1983; Smith and Fischer 1997). In addition, more spring and 

winter precipitation and increased minimum temperatures 

may facilitate the establishment of nonnative annual grasses 

(particularly cheatgrass, which germinates in winter to early 

spring) or other invasive species, although this pattern is seldom observed in the cooler, moister mountain big sagebrush 

communities with healthy herbaceous understories.

Overall, mountain big sagebrush shows higher adaptive capacity than Wyoming big sagebrush, but is likely 

to be stressed somewhat by drought as climate patterns 

change (Balzotti et al. 2016). Compositional shifts in 

herbaceous species are likely. Mountain big sagebrush may 

be able to persist on mesic sites (Chambers et al. 2013), 

but mountain big sagebrush communities may be subject 

to upslope pressure from woodland tree species (unless 

disturbance or disturbance surrogates are used to reset 

successional processes). Conifer expansion, especially 

by juniper and pine species, into sagebrush communities 

is especially pronounced in the Great Basin (Miller et al. 

2008). Interruptions to wildfire cycles and favorable climatic periods, combined with other factors, have led to the 

proliferation of trees, often occurring in sagebrush sites that 

previously did not support trees. Consequently, land cover 

type has gradually shifted from shrubland to woodland 

across numerous sites (Miller et al. 2011). These transitions 

significantly reduce resilience to changing climates, as the 

increased abundance of trees negatively affects soil moisture 

available for perennial herbaceous species. Conversely, 

mountain big sagebrush could expand into drier persistent 

aspen stands, as these areas are likely to be negatively affected by climate change (Chapter 6). This species is well 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
176 USDA Forest Service RMRS-GTR-375. 2018

adapted to the soils on which these aspen stands occur, and 

this replacement is already occurring in some areas.

Subspecies of big sagebrush can hybridize or undergo 

polyploidization, offering greater genetic diversity and 

potentially providing the species with the capacity to 

undergo selection and adapt to shifting climatic regimes 

(Poore et al. 2009). Garrison et al. (2013) found that what 

has been called Bonneville big sagebrush (Garrison 2006; 

McArthur and Sanderson 1999; Rivera et al. 2011; Winward 

2004) has been shown to be a hybrid between mountain 

big sagebrush and Wyoming big sagebrush. This hybrid is 

found in southeastern Idaho and extreme northern Utah. 

Hybridization creates a greater level of uncertainty regarding the future distribution of this subspecies, as well as all 

other species and varieties of sagebrush. The ability of the 

expected new hybrids to survive on changing habitats under 

future climates is poorly understood at this time. Bonneville 

big sagebrush has also been observed in southern Utah, 

where it occupies sites ecologically similar to Wyoming 

big sagebrush. Hybridization contributes to the evolution of 

sagebrush (McArthur and Sanderson 1999), which may at 

least maintain morphologically similar sagebrush communities in the future.

Vulnerability to Climate Change: Moderate to High

Vulnerability of mountain big sagebrush shrublands varies from moderate to high because of the broad elevational 

range at which mountain big sagebrush occurs, and because 

of the wide range in current conditions of these shrubland 

communities (table 7.2). Factors contributing to the vulnerability of these communities include livestock grazing, 

expansion of pinyon-juniper shrublands, altered wildfire regimes, and nonnative invasive species, including cheatgrass 

and seeded forage species.

Dry Big Sagebrush Shrublands

Vegetation Type Description and Distribution

Dry big sagebrush shrublands are those dominated by 

Wyoming big sagebrush, basin big sagebrush, Parish big 

sagebrush (A. t. ssp. parishii), or sand sagebrush (A. filifolia) 

for long periods of time under historical disturbance regimes. Small amounts of threetip sagebrush may also occur 

in this vegetation type. The perennial herbaceous understory 

is less productive and less diverse in this vegetation type 

than in mountain big sagebrush-steppe and may be codominant or subdominant in intact communities.

Wyoming big sagebrush occurs throughout the IAP 

region in locations where winter or spring precipitation is 

sufficiently reliable to support spring growth; it is often 

found in areas receiving 8 to 16 inches of precipitation annually (Welsh et al. 2008). It typically grows in the warm, 

dry conditions of valleys and foothills, generally below 

6,500 feet elevation (Welsh et al. 2008; Winward and 

Tisdale 1977), and often below National Forest boundaries. 

Soils on which Wyoming big sagebrush occurs are often 

underlain by an argillic, caliche, or silica layer (Miller et 

al. 2011). Basin big sagebrush also occurs throughout the 

region, but most of its habitat has been converted to agricultural use and other development because it typically occurs 

in valley bottoms on highly productive soils. Surviving 

stands are common in the deep soils of canyon bottoms and 

other areas of soil aggradation. Sand sagebrush is limited 

in the IAP region to southern Utah and possibly the Spring 

Mountains of southern Nevada. Parish big sagebrush is 

found on the Bridgeport District of the Humboldt-Toiyabe 

National Forest (central Nevada). Small populations also 

occur in southern Utah (Shultz 2006).

Sensitivity to Climate Change: High

Climate change is projected to have significant effects 

on dry big sagebrush shrublands, and these ecosystems 

are highly sensitive to a changing climate (table 7.2). 

Projections suggest potential loss of more than one-third 

of the climatically suitable area of Wyoming sagebrush by 

2050 (Still and Richardson 2015). Amount and timing of 

precipitation control seeding establishment at low elevations because soil water content primarily controls seedling 

survival (Nelson et al. 2014; Poore et al. 2009; Schlaepfer et 

al. 2014). Conditions suitable for seedling establishment are 

infrequent under contemporary climatic conditions and are 

likely to become less frequent with climate change. Thus, 

these ecosystems remain vulnerable to drought, and sagebrush establishment is likely to be more difficult as years 

with adequate snowfall become less frequent (Meyer and 

Warren 2015). Even after seedling establishment, drought 

and increased summer temperature can affect survival and 

growth of adult plants because growth is positively correlated with winter precipitation and winter snow depth 

(Poore et al. 2009). Hence, if drought events increase in 

frequency and severity in the future, big sagebrush biomass 

and the abundance and diversity of perennial grasses and 

forbs may decrease.

Adaptive Capacity: Low to Moderate

Adaptive capacity of dry big sagebrush ecosystems to 

climate change is low (table 7.2) because of the effects of 

historical grazing on the composition and structure of these 

warmer and drier sites, fragmentation with conversion to 

agricultural uses (Noss et al. 1995), and oil and gas development, which is prominent in the IAP in the Uinta Basin of 

eastern Utah. Prior to Euro-American settlement in the West, 

much of the land occupied by Wyoming big sagebrush shrubland had understories dominated by spatially discontinuous 

perennial grasses. These communities carried fires only 

when humidity was low and winds were high, or after several wet years when fine fuels could accumulate (Hull and 

Hull 1974; Mensing et al. 2006; Vale 1975). These fire-free 

intervals were relatively long in comparison to other more 

mesic sagebrush-dominated sites, often 100 to 200 years 

or more. Where perennial bunchgrasses and shrubs have 

been lost to improper livestock grazing and invasion by 

annual grasses, fire frequency has increased dramatically, to 

more than double that of sagebrush shrublands with intact, 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 177

native understory in the Great Basin (Balch et al. 2013). 

Observations of increased fire frequencies were reported as 

early as the early to mid–1900s after these annual grasses 

had invaded much of the Intermountain West (Pickford 

1932; Piemeisel 1951; Robertson and Kennedy1954).

Strong negative relationships exist between cover 

of cheatgrass and perennial native grasses and forbs in 

Wyoming big sagebrush shrublands (Anderson and Inouye 

2001; Chambers et al. 2014; West and Yorks 2002). 

Chambers et al. (2007) found that on relatively intact sites, 

native perennial herbaceous vegetation resprouted after 

fire, which then limited the growth and reproduction of 

cheatgrass. About 15 percent cover of perennial native 

herbaceous species is required to prevent an increase of 

medusahead or cheatgrass following fire or management 

treatments in these shrublands (Chambers et al. 2014; 

Davies et al. 2008).

The genetic variability within these species of sagebrush, 

how that variability is spread across the distribution of the 

species, and the relationship of this variability to climate 

change effects on the species are of critical importance 

(Chaney et al. 2017). Cytotypic variation, or individuals 

within a species that have different chromosomal factors 

(e.g., diploid versus tetraploid) than others within the same 

species, may be as important as subspecific variation in 

explaining adaptation and functional diversity within the big 

sagebrush complex (Brabec et al. 2016). 

Research has also shown that minimum temperatures 

play a bigger role in the probability of sagebrush survival 

than water-related responses (Brabec et al. 2016; Chaney 

et al. 2017). In common garden studies, Chaney et al. 

(2017) found greater survival from cytotypes collected from 

regions with greater seasonal differences in temperature 

and higher summer precipitation (interior regions of the 

continent) than those collected from regions with moderate 

winter temperatures and drier summers. They also found 

that Wyoming big sagebrush had a greater physiological 

avoidance and resistance to freezing than mountain big 

sagebrush. These differences may have been the result of a 

greater insulating effect of snow cover at higher elevations 

where mountain big sagebrush occurs, and the resulting 

differences in the need to adapt to cold temperatures by the 

more exposed Wyoming big sagebrush. The importance of 

integrating genetic diversity into our understanding of the 

adaptive capacity of all sagebrush species is becoming more 

evident as the research in this area begins to evaluate how 

these cover types will respond to climate change.

Vulnerability to Climate Change: Very High

Dry big sagebrush shrublands have a very high vulnerability to climate change because of high sensitivity and 

low adaptive capacity (table 7.2). Evidence of this is found 

in the loss of this type across large areas of southern Utah 

in response to the 2002–2003 drought. Dry big sagebrush 

shrublands occupying lower elevations of the Great Basin 

are expected to be some of the most vulnerable to climate 

change. Western Wyoming, eastern Idaho, and higher 

elevations in the Great Basin are predicted to retain or gain 

climatically suitable areas for the most abundant component 

of dry big sagebrush shrublands, Wyoming big sagebrush 

(Still and Richardson 2015). Although suitable Wyoming 

big sagebrush habitat is projected to expand in some areas 

within and beyond the IAP region, its overall distribution 

is projected to decrease by at least 39 percent (Still and 

Richardson 2015). The distances between current and projected future habitats capable of supporting Wyoming big 

sagebrush often exceed the estimated migration rate of 6 to 

19 miles per century (McLachlan et al. 2005; Yansa 2006). 

Thus, this species may lose significantly more habitat to 

climate change than it can gain (Still and Richardson 2015) 

without active assistance.

Sprouting Sagebrush Shrublands

Vegetation Type Description and Distribution

Sprouting sagebrush shrublands include communities 

dominated by mountain silver sagebrush, snowfield sagebrush, threetip sagebrush, or timberline sagebrush. These 

species are all capable of sprouting from the root crown 

following fire or other form of top kill, and because of their 

ability to sprout, a postdisturbance stage dominated by 

grasses and forbs is short lived.

Mountain silver sagebrush occurs through most of the 

IAP region (fig. 7.5), commonly on heavy soils in riparian 

terraces and in areas with high snowpack in mountainous 

areas (McArthur 2000). In the Sierra Nevada, similar sites 

are occupied by Bolander silver sagebrush (A. cana ssp. 

bolanderi) (Shultz 2006). In some areas around the Greater 

Yellowstone Area, silver sagebrush has replaced lodgepole 

pine (Jakubos and Romme 1993).

There is some disagreement on the distribution of 

threetip sagebrush in the literature. Shultz (2006) describes 

this variety as occurring in portions of Idaho, Nevada, and 

Wyoming, whereas Winward (2004) includes northern Utah 

in the distribution of this variety. Much of its habitat has 

been converted to agriculture because of the productive 

soils on which it occurs. Remaining populations are isolated 

throughout its presettlement distribution (Shultz 2006).

Timberline sagebrush is a California endemic and is 

uncommon in the IAP region (fig. 7.5). It occurs in deep 

soils along forest margins of the Sierra Nevada in California 

and Nevada (McArthur 2000), and collections on or near the 

Bridgeport District in Humboldt-Toiyabe National Forest 

appear to generally be above 10,000 feet elevation (Jepson 

Flora Project 2016). Because it is rare in the region, we did 

not include it in this assessment.

Snowfield sagebrush occurs at high elevations in the 

IAP region throughout northern and central Utah, western 

Wyoming, central and southeastern Idaho, and the eastern 

Sierras. It typically occurs at higher elevations than, or as 

inclusions within, mountain big sagebrush shrublands in 

areas where snow depth and subsequent soil moisture are 

higher. However, it is included here because of its ability to 

sprout in response to fire.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
178 USDA Forest Service RMRS-GTR-375. 2018

Sensitivity to Climate Change: Moderate

Warmer and drier climates will negatively affect the vigor 

and abundance of sprouting sagebrush species, which are 

adapted to more mesic conditions. Although these species 

can sprout following disturbance, they also reproduce by 

seed. Like other sagebrush species, however, seed viability is 

short for many species, including silver sagebrush (Romo and 

Young 2002). Seed viability is likely to be negatively affected 

by increased temperatures, prolonged droughts, and irregular 

precipitation patterns. For these reasons, the sensitivity of 

sprouting sagebrush shrublands is rated as moderate (table 7.2).

Adaptive Capacity: Moderate

All three subspecies of sagebrush in these communities 

sprout after fire. In addition, silver sagebrush spreads by 

underground rhizomes (Schultz and McAdoo 2002) and 

therefore can recover more quickly than other species of 

sagebrush following disturbance. These factors, when combined with the more mesic habitat conditions, led to a rating 

of moderate adaptive capacity (Balch et al. 2013) (table 7.2).

Vulnerability to Climate Change: Moderate

Sprouting sagebrush shrublands have been given a moderate climate change vulnerability rating because of their 

moderate sensitivity and adaptive capacity to climate change 

(Balch et al. 2013) (table 7.2). Although the sagebrush species in this type can sprout, their higher dependence on soil 

moisture than other sagebrush shrublands makes them vulnerable to increasing temperatures and drought. In addition, 

increased fire frequency and severity (particularly in threetip 

sagebrush communities) may cause a shift in community 

composition to dominance by fire-adapted herbaceous or 

nonnative species. Other fire-adapted shrub species (e.g., 

rubber and yellow rabbitbrush) may increase, particularly 

following fire. Nonnative invasive species respond favorably 

after fire, and if present, may increase in cover and density. 

Understory composition in both silver and threetip sagebrush 

communities may possibly shift to more xeric grassland species (e.g., bluebunch wheatgrass [Pseudoroegneria spicata], 

needle-and-thread [Hesperostipa comata]), which are better 

adapted to warmer and drier conditions. Sprouting sagebrush 

species may shift landscape position to sites with more moisture and cooler temperatures (e.g., higher-elevation, lower 

landscape position, and northeast aspects).

Dwarf Sagebrush Shrublands

Vegetation Type Description and Distribution

Dwarf sagebrush shrublands are those communities 

dominated by low sagebrush (including the subspecies low 

sagebrush [A. a. ssp. arbuscula], alkali sagebrush [A. a. ssp. 

longiloba], cleftleaf low sagebrush [A. a. ssp. thermopola],

and Lahontan sagebrush [A. a. ssp. longicaulis]), black 

sagebrush, Bigelow sagebrush, Owyhee sagebrush, scabland 

sagebrush, or pygmy sagebrush. These dwarf sagebrush 

shrublands occur across a broad elevational range, often on 

sites with shallow or rocky soils, or on soils with high clay 

content. The abundance and diversity of perennial grasses 

and forbs vary but are generally similar to or less than those 

associated with dry big sagebrush shrubland communities. 

Fires were rare historically because fine fuels are typically 

low, but when fires occur, the grass-forb stage can persist for 

long periods of time on harsh sites or where erosion occurs 

after fire (Young 1983). Pinyon and juniper may invade on 

the more mesic sites in the absence of disturbance. Some 

sites are susceptible to invasion by introduced annual grasses, and where this occurs, fire frequency often increases.

Dwarf sagebrush species occur throughout the IAP 

region (fig. 7.6). Black sagebrush and one or more varieties 

of low sagebrush are found throughout most of the region. 

Bigelow sagebrush occurs in the southern portions of Utah 

and Nevada. Scabland and Owyhee sagebrush are limited 

to the western and southern portions of Idaho, and northeastern Nevada. Lahontan sagebrush is generally restricted 

to northwestern Nevada and adjacent areas in California 

and Oregon. Pygmy sagebrush is uncommon but is locally 

abundant in east-central and eastern Nevada, western Utah, 

and the Uinta Basin of northeastern Utah (Ulev 2005).

Low, Bigelow, and black sagebrush occur across a broad 

geographic and elevational range. Black sagebrush generally occurs between 4,600 and 8,500 feet elevation in the 

Figure 7.5—Distribution of silver sagebrush, timberline 

sagebrush, and threetip sagebrush in the western United 

States (from Mahalovich and McArthur [2004]). 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 179

Intermountain West, and up to 11,000 feet in Nevada (Fryer 

2009). Low sagebrush ranges from 2,300 feet to over 11,000 

feet in Nevada (Steinberg 2002), but tends to occur primarily above 8,000 feet in a band across central Nevada, from 

Ely to Bridgeport. Bigelow sagebrush ranges in elevation 

between 3,000 and 7,000 feet in Nevada and Utah (Howard 

2003). Scabland and pygmy sagebrush have a narrower 

distribution, but elevational range for pygmy sagebrush 

is 5,000 to 11,000 feet in Nevada (Ulev 2005). Pygmy, 

Bigelow, scabland, and alkali sagebrush grow in edaphically limited habitats, and all other dwarf sagebrush species 

generally occur on shallow or rocky soils, making them 

more resistant to cheatgrass dominance, and therefore more 

resistant to the large or severe fires to which other sagebrush 

shrublands have been subjected.

Sensitivity to Climate Change: Moderate to High

All low-growing sagebrush species are likely to be 

negatively affected by higher temperatures and increased 

periods of drought. As with all sagebrush species, seed 

viability of dwarf sagebrush species is short and their dependence on spring soil moisture will make them susceptible 

to prolonged droughts and to changes in climate that may 

otherwise affect the timing and amount of spring moisture. 

Increases in fire, coupled with drought, could inhibit regeneration of the dwarf sagebrush species, particularly on harsh 

sites (Young 1983).

Adaptive Capacity: Moderate to High

Dwarf sagebrush shrublands are likely to have a 

moderate to relatively high adaptive capacity to climate 

change (table 7.2). Species in these shrublands have 

broad distributions and occur over a wide elevational 

range in the IAP region. Adaptive capacity may be 

moderated, however, because of the relatively low productivity characterizing these species, especially where 

other risk factors (e.g., nonnative annual grasses) are 

present. Sites dominated by scabland sagebrush occur 

over a narrower range in elevation (McWilliams 2003), 

and thus it may be more susceptible to the effects of 

climate change because alternative suitable sites may not 

be available.

None of the dwarf sagebrush species can sprout 

following fire, with the possible exception of hybrids 

between black and silver sagebrush; sprouting is thought 

to be a heritable trait in crosses between nonsprouting and sprouting sagebrush species (McArthur 1994). 

Hybridization may play a role in increasing adaptive 

capacity of other dwarf sagebrush species to the effects 

of climate change. In central Nevada, black sagebrush 

commonly forms hybrids at all elevations. Lahontan 

sagebrush is a putative stable hybrid between low 

sagebrush and Wyoming big sagebrush (McArthur and 

Sanderson 1999).

a) b)

Figure 7.6—Distribution of low sagebrush species in the western United States: (a) low, Bigelow, and Lahontan sagebrush; and 

(b) fringed, black, pygmy, and Owyhee sagebrush (from Mahalovich and McArthur [2004]).

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
180 USDA Forest Service RMRS-GTR-375. 2018

Vulnerability to Climate Change: Moderate

Dwarf sagebrush shrublands are rated as moderately vulnerable because sensitivity and adaptive capacity are rated 

as moderate to high (table 7.2). Climate change is likely 

to result in shifts in the distribution of conditions suitable 

to support the dwarf sagebrush species in the region. All 

dwarf sagebrush species are intolerant of fire, and most do 

not sprout following fire. Because of the low productivity of 

these sites, however, cheatgrass may not be able to establish 

on harsh sites (Chambers et al. 2013). Thus, these ecosystems may be more likely to resist a significant change in 

fire regimes. However, these sites will be exposed to higher 

temperatures and more erratic precipitation patterns, reducing the ability of seedlings to establish during unfavorable 

years.

Mountain Shrublands

Vegetation Type Description and Distribution

Mountain shrublands are typically associated with 

mountain big sagebrush shrublands, oak-maple woodlands, 

and pinyon-juniper woodlands, as well as montane and 

subalpine forests. They can occur as large patches within 

wooded and forested landscapes. Combinations of species 

such as chokecherry, serviceberry (Amelanchier alnifolia), 

snowberry, currant (Ribes spp.), rose (Rosa spp.), maple 

(Acer spp.), sumac (Rhus spp.), ceanothus (Ceanothus

spp.), Scouler willow (Salix scouleriana), elderberry 

(Sambucus spp.), thimbleberry (Rubus parviflorus), 

alderleaf mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), wild crab apple 

(Peraphyllum ramosissimum), and mountain ash (Sorbus 

scopulina) are common. Mountain big sagebrush is also 

common as a subdominant element. Species dominating 

the overstory of these shrublands are typically adapted to a 

wide range of elevations (table 7.4). In addition to the wide 

variety of shrub species, there is an even greater diversity 

of associated perennial herbaceous species that occur in 

the understory.

Sensitivity to Climate Change: Low to Moderate

High species diversity, coupled with the broad elevational range over which these communities occur, is likely 

to result in relatively low sensitivity of mountain shrublands 

to climate change (table 7.2). Though not directly related 

to the IAP region, studies in Alberta, Canada, found little 

change in the spring flowering response of either serviceberry or chokecherry between 1936 and 2006 (Beaubien 

and Hamann 2011). However, declining snowpacks, more 

frequent and severe droughts, and warmer temperatures may 

cause hotter fires and, at the same time, sites may become 

drier, causing variable amounts of mortality, depending on 

site conditions.

Adaptive Capacity: Moderate to High

Montane shrublands were historically maintained by 

relatively frequent fire (approximately every 30 years or 

less) (Smith and Fischer 1997), and most montane shrubs 

sprout following fires. Stressors to these shrublands include 

fire exclusion and resulting conifer encroachment, browsing 

by both native wildlife and domestic livestock, and insects 

and disease. As noted earlier, the diversity of species in 

these communities is often very high. However, there is the 

potential that more frequent and severe fires will decrease 

resilience. Loss of topsoil and creation of hydrophobic 

(water-repellent) soils after frequent, hot fires, can lead to 

loss of species over time (DeBano 1981; Wellner 1970). As 

sites become drier, there may be a shift away from mesic 

species to more xeric and fire-adapted shrubs, such as rubber 

rabbitbrush, yellow rabbitbrush, bitterbrush, and mountain 

big sagebrush.

Vulnerability to Climate Change: Low to Moderate

Of all the ecosystems in the IAP region, montane shrublands appear to have the lowest vulnerability to climate 

change (table 7.2) because of high species diversity, high 

sprouter diversity, wide range in elevation, and broad distribution of dominant overstory species. Even with increasing 

temperatures and uncertain precipitation, species of the 

Table 7.4—Elevation ranges of species that dominate or codominate the overstory of mountain shrublands in the 

IAP region. 

Species Elevation Source

Feet

Saskatoon serviceberry (Amelanchier alnifolia) 4,000-9,500 Welsh et al. (2008)

Utah serviceberry (Amelanchier utahensis) 3,000-9,000 Welsh et al. (2008)

Birchleaf mountain-mahogany (Cercocarpus montanus) 3,900-9,800 Cronquist et al. (1997)

Chokecherry (Prunus virginiana) 3,100-10,170 Johnson (2000)

Skunkbush sumac (Rhus trilobata) 2,900-7,700 Pendleton et al. (1989)

Thimbleberry (Rubus parviflorus) 4,700-9,000 Gucker (2012)

Scouler willow (Salix scouleriana) Sea level-10,000 Anderson (2001)

Mountain snowberry (Symphoricarpos oreophilus) 4,000-10,000 Aleksoff (1999)

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 181

montane shrublands are probably the most capable of expanding into niches at higher elevations and onto adjacent, 

more mesic portions of the landscapes in which they occur.

Blackbrush Shrublands

Vegetation Type Description and Distribution

Blackbrush shrublands are very limited on National 

Forest lands in the IAP region, occurring at the lowest 

elevations on the southern edge of the region in the Spring 

Mountains National Recreation Area in Humboldt-Toiyabe 

National Forest and on the Moab District in Manti-La Sal 

National Forest. Distinct ecotypes of blackbrush (Coleogyne 

ramosissima) occur in the region: one entering the Great 

Basin and Semi Desert subregion from the adjacent Mojave 

Desert to the south, and the other in the Plateaus subregion 

(Richardson and Meyer 2012; Richardson et al. 2014). 

Communities are dominated by blackbrush with jointfir 

(Ephedra spp.), burrobush (Ambrosia dumosa), hedgehog 

cactus (Echinocereus spp.), spiny menodora (Menodora 

spinosa), various goldenbush species (Ericameria spp.), 

prickly pear (Opuntia spp.), Apache plume (Fallugia 

paradoxa), and others sometimes present as subdominants. 

Historically, interspaces in these communities were probably mostly bare, even during years of higher precipitation, 

because of competition from blackbrush (Brooks et al. 

2007). Perennial grasses and seral shrubs probably occurred 

sporadically in areas where blackbrush cover was low 

(Brooks et al. 2007).

Sensitivity to Climate Change: Low to Moderate

As a long-lived, stress-tolerant shrub, blackbrush has 

relatively low sensitivity to the direct effects of climate variability in the absence of disturbance (Kitchen et al. 2015). It 

sheds its microphyllous leaves in response to drought stress, 

is well adapted to high temperatures (Munson et al. 2011; 

Summers et al. 2009), and occurs on shallow soils with a 

rooting system that allows it to capture soil water opportunistically (Schwinning et al. 2005, 2008).

Adaptive Capacity: Low

There is a high level of genetic differentiation between 

populations of blackbrush that occur in the Mojave Desert 

(those of the Spring Mountains in southern Nevada) and 

those of the Colorado Plateau (Dixie and Manti-La Sal 

National Forests), which has implications for population 

persistence and migration in response to climate change 

(Richardson and Meyer 2012; Richardson et al. 2014). 

Pendleton et al. (2015) found records that indicate blackbrush has the ability to migrate in response to changes in 

climate, but that the rate at which climate change is expected to occur may preclude natural migration because of its 

episodic recruitment. In addition, blackbrush communities 

have little resistance to invasive plant species and very low 

resilience to the fires accompanying the increase in invasive 

annual grasses. Large areas of blackbrush in the Mojave 

Desert, where red brome (Bromus rubens) has increased 

significantly, have burned in the past decade (Pendleton et 

al. 2015). Blackbrush does not sprout after fire, and the species is not regenerating in these burned areas (Pendleton et 

al. 2015).

Vulnerability to Climate Change: Moderate to High

Despite the low sensitivity of blackbrush to the direct 

effects of climate change, vulnerability is rated as moderate 

to high (table 7.2) because of its lack of resistance to invasion by exotic species and its inability to resprout following 

fire. With increased area burned under changing climate 

(Abatzoglou and Kolden 2013), a loss of dominance by 

blackbrush is likely to occur, dominance by invasive annual grasses will increase, and a subsequent increase in fire 

frequency and size may occur with increased horizontal fuel 

continuity.

With climate change, there may be some expansion of 

blackbrush communities onto adjacent sites that are currently higher in elevation or on sites that have somewhat higher 

available soil moisture. This expansion is more probable in 

the Plateaus subregion, where invasive species have had less 

impact on fire and existing blackbrush communities, and 

where some evidence exists for contemporary blackbrush 

migration (Kay 2015). Expansion is much less likely on 

National Forest lands close to the Mojave Desert, where 

replacement of blackbrush by invasive species is already 

resulting in net loss of the blackbrush vegetation type.

Salt Desert Shrublands

Vegetation Type Description and Distribution

North American salt desert shrublands are dominated by 

a mixture of drought- and salt-tolerant (halophytic) shrub, 

sub-shrub, and herbaceous species and occupy landscapes 

too dry or too salty to support sagebrush. Salt desert shrublands are a minor component on National Forest lands in 

the IAP region, occurring primarily in the Utah and Nevada 

portions of the region (fig. 7.7), where their distribution 

on National Forest lands is limited to lower elevations. 

However, this type is extensive on adjacent lands managed 

by the Bureau of Land Management in Nevada and Utah as 

well as outside the region in southeastern Wyoming.

Salt desert shrublands are dominated primarily by species 

belonging to the Chenopod plant family, such as greasewood 

(Sarcobatus spp.), fourwing saltbush (Atriplex canescens), 

shadscale (A. confertifolia), Gardner saltbush (A. gardneri) 

and close relatives, mat saltbush (A. corrugata), winterfat 

(Krascheninnikovia lanata), gray molly (Bassia americana), 

spiny hopsage (Grayia spinosa), iodine bush (Allenrolfea 

occidentalis), and seepweed (Sueda spp.), along with a variety of other shrub species (Blaisdell and Holmgren 1984). 

Perennial grasses are often codominant, with the relative importance of warm and cool-season species dependent on the 

reliability of seasonal moisture for the sites. Common warm 

season grasses can occur in areas with warm, wet summers, 

which occur where salt desert shrublands are found in 

the extreme southern portions of the region. Cool-season 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
182 USDA Forest Service RMRS-GTR-375. 2018

grasses can occur elsewhere in the region, where spring is 

typically cooler and wetter (Paruelo and Lauenroth 1996). 

In the southern salt desert shrublands, warm season grasses 

include galleta grass (Pleuraphis jamesii), blue grama 

(Bouteloua gracilis), alkali sacaton (Sporobolus airoides), 

sand dropseed (Sporobolus cryptandrus), and saltgrass 

(Distichlis spicata). Common cool-season grasses include 

Indian ricegrass (Achnatherum hymenoides), squirreltail 

(Elymus elymoides), Salina wildrye (Leymus salinus), 

needle-and-thread grass (Hesperostipa comata), and purple 

three-awn (Aristida purpurea). A diverse mixture of native 

forbs responds opportunistically to variability in the timing 

and amount of precipitation and support a rich diversity of 

desert pollinators. Total plant cover in these communities is 

typically 20 percent or less, and height of shrubs is usually 

less than 1.5 feet (West 1983).

Cheatgrass establishment in dry salt desert communities 

is limited by low and sporadic precipitation (Meyer et al. 

2001), but has been observed to be increasing. With increasing cheatgrass comes the potential for impacts from fire, 

which was not historically a significant disturbance factor 

(West 1994).

Sensitivity to Climate Change: Moderate

Many of the species associated with salt desert shrublands have wide ecological distributions and are tolerant 

of a wide range of climatic conditions. Species typically 

combine various morphological and physiological attributes (such as small, heavily protected leaves, high 

root-to-shoot ratios) that enable them to tolerate stress with 

others (such as seed and shoot dormancy) that facilitate 

stress avoidance. The effects of climate change on these 

plant communities will include both positive and negative 

shifts for individual species. However, the plant communities are likely to be relatively insensitive to the direct 

effects of climate change.

Adaptive Capacity: Low to Moderate

Many of the species that characterize salt desert ecosystems are fire intolerant (Chambers et al. 2013; Meyer 

et al. 2001). With the introduction of nonnative annual 

grasses, an increase in fine fuels may allow for increased 

area burned (West 1994), which would likely decrease 

the abundance of many characteristic species in this type. 

Disturbed salt desert shrublands are particularly susceptible to invasion by nonnative halophytic species such as 

halogeton (Halogeton glomeratus) and Russian thistle 

(Salsola spp.). Halogeton is a succulent summer annual 

that quickly spreads and establishes in disturbed areas 

(such as roadways and livestock watering areas) within 

intact perennial communities. It is a prolific seed producer, 

and seeds may remain in the soil seed bank for 10 years 

or more (Cronin and Williams 1966). Once established, 

halogeton prevents natural regeneration of native shrubs, 

such as winterfat (Eckert 1954; Harper et al. 1996; Kitchen 

and Jorgensen 1999) and Gardner saltbush (Goodrich and 

Zobell 2011). Today, halogeton stands are frequently found 

adjacent to remnant winterfat communities throughout the 

Great Basin (Kitchen and Jorgensen 2001).

Vulnerability to Climate Change: Moderate to High

With moderate sensitivity and low to moderate adaptive capacity, salt desert shrublands have moderate to high 

vulnerability to climate change (table 7.2). Risks of direct 

and indirect (i.e., fire) effects of introduced species render 

the vulnerability of this vegetation type relatively high to the 

combination of future impacts. Climate change is expected 

to result in more extreme precipitation events (West 1994). 

The combination of wet years and the fertilization effects 

of increased atmospheric carbon dioxide may result in an 

increase in annual grasses, which will in turn be more likely 

to fuel wildfire (Bradley et al. 2016; Salo 2005; Smith et al. 

1987). Most of the dominant woody species in salt desert 

shrublands are poorly adapted to fire, and they will be vulnerable to increases in fire frequency.

Alpine Forblands and Grasslands

Alpine forblands and grasslands include communities 

dominated by either a variety of broadleaf forb species or 

by grasses, as well as the wide variety of species that occur 

in alpine ecosystems. Edaphic and climatic factors in these 

communities inhibit the establishment or significant growth 

of woody species.

Figure 7.7—Distribution of salt desert shrublands in the 

western United States (derived from West [1983]).

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 183

Alpine Communities

Vegetation Type Description and Distribution

Alpine ecosystems occur at the highest elevations above 

treeline in the IAP region, at elevations generally above 

8,000 feet in the northern portions to over 11,000 feet in 

the south. Although relatively small in area, they have 

high aesthetic value and high visitor and recreational use. 

They are possibly the ecosystems in the IAP region that are 

most at risk from the effects of climate change because of 

their shrinking habitat. These high-elevation locations are 

characterized by a very short growing season. Alpine plant 

communities are diverse and complex across the IAP region 

(Hayward 1952) and can include a variety of growth forms, 

including upland krummholz, shrubland, grassland, and 

herbaceous communities, herbaceous wetlands, and sparsely 

vegetated bedrock and scree communities (NatureServe 

2013). These diverse types have been combined here 

because of the relatively small area they cover within the 

region, and because they are expected to have similar (negative) responses to climate change.

Sensitivity to Climate Change: High

The length and depth of snow cover, which are strongly 

correlated with mean temperature and precipitation, are 

key factors controlling alpine ecosystems (Beniston 2003). 

Snow cover provides frost protection for alpine plants in 

the winter, as well as the water supply in spring. Reduced 

snowpack with warming is likely to cause major changes 

in alpine plant communities (Gottfried et al. 2012). Alpine 

plants may be at greater risk from competition from plant 

species that are adapted to warmer temperatures and 

longer growing seasons. Research from the European Alps 

showed a significant increase in species richness in alpine 

ecosystems with the invasion of plants from lower altitudes 

(Pauli et al. 2003). It will be essential to account for new 

competitive interactions among species to better predict the 

responses of individual alpine species and entire communities to climate change (Alexander et al. 2015).

Adaptive Capacity: Low

The adaptive capacity of plant species in alpine ecosystems to climate change is likely to be low (table 7.2) 

because they have limited geographic space into which they 

can expand, and they are isolated communities (Alo and 

Wang 2008). In addition, the physiological traits that allow 

their persistence in alpine climates also reduce their ability 

to adapt to changing climates. The fate of individual species 

in a changing climate is likely to depend on their individual 

ecophysiological responses to the direct effects of increased 

temperatures and carbon dioxide levels, as well as the indirect effects of rising temperatures, such as the length of the 

snow-free period (Pauli et al. 2003).

The introduction of mountain goats (Oreamnos americanus), a nonnative species, to nearly every mountain range 

in Utah with alpine vegetation and the Ruby Mountains 

in Nevada has the potential to impact existing native 

vegetation, introduce noxious and invasive weeds, and result 

in a significant reduction of ground cover. As a result, there 

is potential for loss of native plants from trampling and 

subsequent soil erosion, further decreasing the capacity of 

alpine plant communities to adapt to climate change.

Vulnerability to Climate Change: Very High

The composition and distribution of alpine ecosystems 

will be affected by decreasing snowpack. For high-elevation 

vegetation, climate change may affect seed germination and 

survival by modifying moisture availability and therefore result in reduced plant success. Specific effects will depend on 

vulnerability thresholds of the characteristic species and the 

rate and magnitude of changes over time (Beniston 2003). In 

addition, climate change could lead to a mismatch between 

plant flowering and pollinator emergence (Parmesan 2006), 

which could adversely affect both plants and pollinators.

Alpine communities often have a relatively high number 

of endemic species because they are isolated (Beniston 

2003), meaning that highly endemic alpine biota will have a 

disproportionately high risk of extinction (Parry et al. 2007). 

Local extinctions of otherwise widespread alpine species 

such as arctic gentian (Gentianodes algida) and alpine 

chaenactis (Chaenactis douglasii var. alpina) have already 

occurred in portions of Idaho because of habitat loss and 

fragmentation (USEPA 1998). Warming temperatures and 

longer growing seasons are likely to allow more competitive 

shrubs, trees, and herbs to expand upslope from adjacent 

ecosystems and potentially outcompete existing alpine vegetation (Alexander et al. 2015).

Mountain Grasslands

Vegetation Type Description and Distribution

Grasslands are areas where grasses and grass-like species dominate and trees and shrubs have no more than a 

minor presence. Forbs are typically present, although forb 

abundance and diversity vary, and forbs are subdominant to 

grasses. Grasslands that occur on the mid- to high-elevation 

landscapes are composed primarily of perennial cool-season 

bunchgrasses. Typical species for higher elevations include 

slender wheatgrass (Elymus trachycaulus), mountain brome 

(Bromus carinatus), needlegrasses (Achnatherum spp.), and 

blue grasses (Poa). Dominant species at middle elevations 

may include bluebunch wheatgrass, Idaho fescue (Festuca 

idahoensis), and Hood sedge (Carex hoodii). On many sites 

that have transitional winter- and summer-dominant weather 

patterns, a mixture of cool and warm season grasses can 

coexist.

Boulder Top Mountain on the Aquarius Plateau in 

Dixie National Forest has broad landscapes dominated by 

a low-growing fescue that was historically included in the 

sheep fescue (Festuca ovina) complex. Welsh et al. (2008) 

note that there are native forms of Festuca ovina, whereas 

another database (NRCS 2017) indicates that this species is 

entirely introduced. The ecosystems on the Aquarius Plateau 

appear to be native grasslands and are treated as such here. 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
184 USDA Forest Service RMRS-GTR-375. 2018

These apparent native grassland communities occur on one 

of the largest contiguous flat-top landscapes above 11,000 

feet elevation in the IAP region. Youngblood (1980) also 

recognized grassland communities on the Bridger-Teton 

National Forest dominated by spike fescue (Leucopoa 

kingii), bluebunch wheatgrass, and Idaho fescue. This important cover type is very limited in distribution in the IAP 

region.

Sensitivity to Climate Change: Moderate

Determining the sensitivity of grasslands to climate 

change is complex. As noted earlier, cool-season grasses occur in areas with cool, wet springs, which occur throughout 

most of the IAP region. Warm season grasses occur in areas 

with warm, wet summers, which occur at lower elevations 

in the southern portion of the IAP region (Paruelo and 

Lauenroth 1996). Some studies, based solely on projected 

increases in temperature, suggest that grasslands dominated 

by cool-season grasses may decline and that grasslands 

dominated by warm season grasses could, at the same time, 

expand into those environments. To further complicate this 

assessment, the increased atmospheric carbon dioxide favors 

cool-season grasses and enhances biomass production. 

However, warming favors warm season grasses because of 

increased water-use efficiency (Morgan et al. 2004, 2007). 

For these reasons, we cautiously rank sensitivity of these 

ecosystems as moderate (table 7.2).

Adaptive Capacity: Low to Moderate

The adaptive capacity of these grassland communities 

is rated as low to moderate because of historical impacts, 

and inherent adaptive capacity of species dominating these 

sites (table 7.2). Many low-elevation grasslands have been 

converted to agricultural use. Those grasslands that remain, 

particularly at lower elevations, are often highly disturbed, 

fragmented, and frequently occupied by many nonnative 

invasive plant species (Finch 2012). More frequent or severe 

fire associated with climate change may encourage further 

expansion of invasive species in grasslands, especially at 

lower elevations where adjacent landscapes are dominated 

by annual grasses (Bradley et al. 2016).

Vulnerability to Climate Change: Moderate to High

With moderate climate sensitivity and low to moderate 

resilience, these cool-season grass-dominated communities are rated as having a moderate to high vulnerability to 

climate change (table 7.2). Although some studies suggest 

that cool-season grasses will respond positively to increased 

carbon dioxide levels, other models show that these same 

species will decline because of increasing temperatures. 

Warm season grasses have been shown to be favored by 

increased temperatures alone because of increased water-use 

efficiency (Morgan et al. 2004, 2007); thus, they may have 

a competitive advantage over cool-season grasses and could 

expand into the region from warmer and drier climates to 

the south. Increasing fire would also encourage more invasive species in grasslands (Bradley 2009; D’Antonio and 

Vitousek 1992), converting many warmer and drier systems 

to invasive annual grasslands.

Subalpine Forb Communities

Vegetation Type Description and Distribution

Subalpine forb communities are upland communities 

dominated by non-grass herbaceous species, commonly 

called forbs (Ellison 1954; Shiflet 1994). Grasses are typically present but are subdominant (Shiflet 1994). If present, 

trees and shrubs constitute only a minor element of these 

communities (Ellison 1954). Subalpine forb communities 

occur at moderate to high elevations (7,000–11,000 feet) 

where forb growth and reproduction are favored by topographic, edaphic, and climatic conditions (Shiflet 1994). 

Mean annual precipitation is 25 to 40 inches. These communities can be found in various patch sizes, from small 

subalpine meadows to a dominant vegetation type covering 

miles of ridgetops and gentle slopes. They are most extensive in areas where midsummer thunderstorms of late July 

to mid-August coincide with the prime flowering season in 

the subalpine zone. Subalpine forb communities merge into 

mountain sagebrush-steppe, subalpine conifer forest, and 

aspen forest ecosystems and share numerous species with 

each (Ellison 1954).

Subalpine forb communities are limited in the IAP region 

(fig. 7.8). Subalpine forb communities are especially prominent 

on the Wasatch Plateau in central Utah (Ellison 1954), in the 

Teton Range of the Idaho-Wyoming border, and in the Wind 

Figure 7.8—Distribution of tall subalpine forb communities (in 

orange) in the Intermountain Adaptation Partnership region. 

Forested area is shown in green (from U.S. Forest Service, 

http://www.fs.fed.us/wildflowers/beauty/Tall_Forb/what.

shtml).

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 185

River Range of western Wyoming (Gregory 1982). These 

communities have also been found in the Jarbidge Mountains 

and Ruby Mountains of northern Nevada (Lewis 1971, 1975; 

Loope 1970) and in small amounts elsewhere in the region.

Subalpine forb communities are characterized by high 

vascular plant species diversity. For example, 54 forb genera 

(65 native, mostly perennial species) representing 22 families are found on 30 acres of the Elk Knoll Research Natural 

Area administered by the Manti-La Sal National Forest 

(unpublished records on file at the USFS, Shrub Sciences 

Laboratory, Provo, Utah). In addition to forbs, 11 grass and 

11 shrub species are found at subdominant to incidental 

levels.

Subalpine forb communities include species assemblages 

classified as tall forb, which are typically associated with 

deep soils (fig. 7.9a) (Shiflet 1994), as well as assemblages 

of short forbs that occur on well-drained, typically shallow and rocky soils (fig. 7.9b). In addition, there are a 

variety of mixed and intermediate phases that combine 

elements of each. Common tall forb species include false 

hellebore (Veratrum californicum), false springparsley (Pseudocymopterus montanus), western sweetroot 

(Osmorhiza occidentalis), licorice root (Ligusticum filicinum), biscuit root (Lomatium spp.), valerian (Valeriana

spp.), one-flower helianthella (Helianthella uniflora), showy 

goldeneye (Viguiera multiflora), geraniums (Geranium 

spp.), peavine (Lathryus spp.), lupines (Lupinus spp.), 

American vetch (Vicia americana), elk weed (Fraseria 

speciosa), larkspur (Delphinium xoccidentale), columbine 

(Aquilegia spp.), jacobsladder (Polemonium foliosissimum), 

bluebells (Mertensia spp.), asters (Symphiotrichum spp.), 

and paintbrushes (Castilleja spp.), among many others. Common shorter forbs include various buckwheats 

(Eriogonum spp.), yarrow (Achillea millifolium), agoseris 

(Agoseris spp.), scarlet gilia (Ipomopsis aggregata), beebalm (Mondardella spp.), cinquefoil (Potentilla spp.), 

penstemons (Penstemon spp.), groundsels (Packera spp.), 

and paintbrushes (Castilleja spp.). Common grasses include 

slender wheatgrass, mountain brome, Porter brome (Bromus 

porteri), bluegrass (Poa spp.) and needlegrasses.

Sensitivity to Climate Change: High

Species that occur in subalpine forb communities occur 

across a broad elevational range and occupy a wide variety 

of habitats, but little literature is available regarding the 

specific requirements for the establishment and maintenance 

of these ecosystems. Soil characteristics are critical for 

preservation of the tall forb assemblages (Lewis 1993). 

Where those deep soils have eroded, the type has been 

compromised and in some cases, sites are no longer capable 

of maintaining species that once dominated (Shiflet 1994). 

These communities respond to summer rainfall, and it is 

unclear whether these precipitation events will increase or 

decrease in frequency and amounts with changing climate. 

However, higher temperatures will lead to reduced soil 

moisture and are likely to alter the conditions necessary to 

support these unique ecosystems. Although species in these 

communities may be able to move to higher elevations with 

warming, lack of soil development at higher elevations may 

prevent their establishment.

Figure 7.9—Subalpine forb communities in the Intermountain Adaptation Partnership region: (a) a subalpine tall forb community 

occurring on deep, productive soils, and (b) a subalpine low forb community occurring on shallow, well-drained soils 

(photos: W. Padgett, U.S. Forest Service). 

a) b)

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
186 USDA Forest Service RMRS-GTR-375. 2018

Adaptive Capacity: Moderate

Many acres of this cover type have been degraded or 

lost because of historical livestock grazing at unsustainable levels (Ellison 1954; Lewis 1993; McArthur et al. 

2013). Heavy grazing has resulted in a loss of productive 

topsoil in many places, which limits the establishment and 

growth of many dominant native species (Shiflet 1994). On 

the Wasatch Plateau of central Utah, Lewis (1993) found 

significant improvement in conditions once livestock were 

removed from sites that had lost tall forb species through 

excessive grazing in the late 1800s. This is not always the 

case; intensive grazing by livestock and subsequent loss of 

topsoil can result in establishment of species such as tarweed (Madia glomerata) that can remain in place for years 

(Shiflet 1994). Because much of the area in subalpine forb 

communities is in a degraded condition, adaptive capacity is 

rated as moderate (table 7.2).

Vulnerability to Climate Change: High

Although some subalpine forb communities may be 

able to move higher in elevation where current alpine 

environments occur, the lack of soil development at higher 

elevations may support only the lower-growing species 

found in this vegetation cover type. In some areas, such 

as the Wasatch Plateau in central Utah, the tall forb communities occur at the highest elevations of the plateaus, and 

therefore the vulnerability to the communities is high to 

very high. In addition, increased drought stress with higher 

temperatures is likely to stress species in these communities. 

The overall vulnerability of this type to climate change is 

therefore high (table 7.2).

Riparian and Wetland Communities

Riparian and wetland communities occupy about 1 

percent of the land surface in the Great Basin (Sada 2008), 

and they very likely occupy about that same percentage of 

the landscape throughout the IAP region. Though the area 

in these types is relatively small, they have very high species diversity and support a variety of ecosystem functions 

(Naiman and Dècamps 1997). From high to low elevation, 

riparian and wetland communities throughout the region 

have been subjected to relatively high impacts from human 

uses, including road construction, land development, conversion to agricultural uses, and changes in stream discharge 

because of dam construction and water diversions. In addition, these areas have been affected by intensive use by 

domestic livestock, beaver removal, and nonnative species 

(Sada 2008).

Riparian and wetland communities are described by elevation in this report. This organization was chosen because 

of differences in stream size, localized climates, species 

composition and associated structure, and processes such 

as erosion, transport, and deposition that dominate these 

communities at different elevations. Historical and current 

impacts and threats and predicted responses to climate 

change also tend to vary by elevation.

High-elevation areas often have smaller and steeper 

stream channels, with some large snowmelt- and spring-fed 

wetlands. Where stream systems are characterized by steep 

gradients, they tend to be dominated by erosional processes. 

Riparian and wetland vegetation composition and sometimes structure vary with elevation (Engelhardt et al. 2015).

Middle elevations often have larger stream channels with 

lower gradients. They are dominated by transport processes, 

moving sediments from higher elevation to lower-elevation 

stream channels. Riparian and wetland vegetation composition and structure are highly variable, with trees, low and 

tall shrubs, and herbaceous species.

Low elevations have the largest channels and are often 

dominated by depositional processes. Most streams are 

alluvial and armored by riparian vegetation. Historically, 

the largest cottonwood gallery forests and natural wetlands 

occurred at lower elevations. Low-elevation riparian areas 

have a highly variable vegetation structure and contain trees, 

low and tall shrubs, and herbaceous species.

Across elevations, wetlands can vary in size and are 

dependent on water availability and site characteristics 

(e.g., valley bottom and associated stream type). Species 

composition varies with elevation. Upper-elevation wetlands 

are typically dependent on snowpack and snowmelt to 

sustain their water supply. They are often characterized by 

herbaceous species (sedges and rushes) but may also have 

low-growing willows as a community dominant. Drainage 

and development have eliminated many lower-elevation 

wetlands.

All riparian areas can be influenced by beaver activity, 

which results in ponding and flooding because of dam 

building. Historically, beaver occurred throughout the IAP 

region, except in the Great Basin. Much has been written 

on the hydrological and ecological roles that beaver populations play in riparian ecosystems (Jenkins and Busher 1979). 

Beaver dams can reduce peak discharge and stream velocity, 

and they can reduce sediment flows by increasing deposition 

in the ponded areas (Collen and Gibson 2001). Beaver dams 

also spread water over broad areas, expanding habitat for 

riparian and wetland species (Pollock et al. 2003). The widespread removal of beaver has resulted in significant changes 

to stream hydrology, geomorphology, and ultimately the 

ability of valley bottoms to support healthy and diverse 

riparian and wetland ecosystems (Pollock et al. 2003). The 

introduction or reintroduction of beaver, however, does not 

always have a significant positive effect (Rosell et al. 2005). 

Locations for reintroductions must be carefully considered.

Sensitivity

Watershed geomorphic and hydrological characteristics, 

as well as climatic factors such as temperature, precipitation 

type, and precipitation amount, influence the volume and 

timing of streamflows (Patten 1998). Whereas base flow 

conditions result from the gradual release of groundwater 

and snowmelt, periodic flooding can result from either rapid 

spring snowmelt or high-intensity summer thunderstorms. 

The distribution, health, composition, and maintenance 

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 187

of riparian communities depend on volume and timing of 

streamflows (Auble et al. 1994; Poff et al. 1997; Scott et al. 

1996, 1997; Stromberg 1993; Stromberg and Patten 1995).

The Great Basin and Semi Desert and Plateaus subregions are among the driest areas in the western United 

States. Climate change is likely to have the greatest effects 

in these relatively hot and dry portions of the region (Perry 

et al. 2012). Water availability is projected to decrease 

because of increased drought, earlier runoff, and lower 

late-spring and summer streamflows. High flows required 

for channel maintenance will be reduced. Plant community 

composition and structure will be affected by increased water stress, and drought-tolerant species are likely to replace 

riparian and wetland species. In addition, geomorphic and 

hydrological processes and dynamics that have been responsible for riparian and wetland ecosystem development at 

lower elevations have already been affected by construction 

of dams and water diversions in most places.

Adaptive Capacity

From high to low elevations, most riparian and wetland 

systems have been altered from historical conditions, 

resulting in changes in stream geomorphic and hydrological processes, including stream downcutting and channel 

straightening. Stream discharge has been reduced because of 

dam construction and water diversions. These changes have 

decreased water availability to riparian ecosystems because 

of greatly reduced floodplain access and recharge. Riparian 

areas and wetlands have also been affected by domestic 

livestock grazing, road construction, and nonnative species 

(Sada 2008).

Riparian systems are inherently driven by frequent disturbances, in particular seasonal floods or high water flows 

(Kauffman 2001). These flows affect the movement and deposition of sediment and large woody debris (Nakamura et 

al. 2000). The flow regime of riparian systems is of primary 

importance in maintaining their ecological integrity (Poff 

et al. 1997). The magnitude, frequency, duration, timing, 

and rate of change of streamflows directly and indirectly 

affect water quality, energy sources, physical habitat, and 

the biotic interactions within the stream systems. The modification of any one of these can have a cascading effect on 

ecological integrity.

Changes in flow regimes, whether through climate 

change or through human-caused alterations such as those 

from water diversions and dams, impact the amount, season, 

and timing of flows. This can substantially alter associated 

riparian and wetland species because of their dependence on 

fluvial geomorphic process, surface water, and groundwater 

(Merritt et al. 2010; Nilsson and Berggren 2000; Poff et al. 

1997). Floods are responsible for erosion, transport, and deposition of sediments, as well as the amounts and location of 

vegetation and debris. Many dominant riparian species, such 

as cottonwoods and willows, are pioneer species that depend 

on these events to provide bare, moist substrates necessary 

for seed germination and plant establishment (Cooper et al. 

2003; Scott et al. 1996; Stella et al. 2011).

Vulnerability

Factors considered in characterizing the vulnerability of 

each riparian and wetland vegetation type to climate change 

include regeneration success, response to disturbance 

(changes in amount, timing, and location of runoff), and 

plant life history traits.

High-Elevation Riparian and 

Wetland Communities

Vegetation Type Description and Distribution

High-elevation riparian and wetland communities include 

forests, shrublands, and herbaceous communities occurring in meadows, adjacent to streams and water bodies, or 

around seeps and springs. High-elevation wetland sites are 

often associated with bogs, fens, springs, and streams at 

low-gradient sites, such as glacial cirque floors and slumps, 

or around small lakes and ponds proximal to high ridgelines. These communities generally occur above 8,500 feet 

elevation throughout the IAP region. As noted previously, 

upper-elevation streams are erosional in nature, providing 

sediments to their connected systems.

Forest communities occur near the boundary between 

high- and mid-elevation riparian and wetland communities 

and can include species such as aspen and conifers, including subalpine fir (Abies lasiocarpa) and spruce (Picea spp.); 

cottonwoods generally do not occur at these elevations. Lowgrowing willows such as Wolf’s (Salix wolfii) and plainleaf 

(S. planifolia) can dominate broad meadows, along with other 

shrubs such as resin birch (Betula glandulosa) and bog blueberry (Vacinnium occidentale). Some tall willows, such as 

Drummond’s (Salix drummondiana), may also occur. Highelevation sedges (e.g., Carex aquatilis, C. illota, C. limosa, 

C. scopulorum, C. luzulina) can dominate these wetland and 

riparian systems, along with tufted hairgrass (Deschampsia 

cespitosa) and alpine bentgrass (Agrostis humilis).

Existing stressors in high-elevation riparian and wetland 

communities include drought, livestock grazing (particularly 

domestic sheep), and grazing by both introduced ungulates 

(e.g., mountain goats), and large populations of native 

ungulates. In addition, recreational uses can be significant, 

especially in areas adjacent to high populations and relatively 

easy access. Roads in the valley bottoms are a major factor 

affecting erosional processes. Improper all-terrain vehicle use 

can also cause severe soil and vegetation damage, particularly 

in seasonally wet riparian areas, meadows, and peatlands.

Sensitivity to Climate Change: Moderate to High

Warming temperatures and reduced snowpack may result 

in the loss of high-elevation riparian and wetland habitats, 

resulting in drier, less productive systems. With rising temperatures, frigid snow- and water-dependent ecosystems in 

the upper portions of watersheds will have very little room to 

move upslope. Elevating temperatures will increase competition from riparian species now occurring at lower elevations, 

and smaller snowpacks will increase competition from upland 

species that occupy drier sites.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
188 USDA Forest Service RMRS-GTR-375. 2018

Adaptive Capacity: Low to Moderate

Although these ecosystems have been less impacted by 

humans than mid- and low-elevation riparian and wetland 

communities, existing stressors still include drought, livestock 

grazing, introduced ungulates (e.g., mountain goats), and 

large populations of native ungulates, as well as some recreational uses. There tend to be few invasive species in these 

high-elevation ecosystems, and because of historically late 

seasonal snow cover and associated later plant growth, these 

ecosystems have had shorter grazing seasons by domestic 

livestock. Like riparian and wetland species of mid- to lower 

elevations, nearly all tree species occurring in these areas 

sprout following fire. These combined factors result in a low 

to moderate adaptive capacity for these communities (table 

7.2).

Vulnerability to Climate Change: High

High-elevation riparian and wetland communities have a 

high vulnerability to climate change because of moderate to 

high sensitivity and low to moderate adaptive capacity (table 

7.2). Mid-elevation riparian and wetlands communities are 

likely to move higher in elevation with warming climate. 

Systems currently in place are in danger of losing their water 

source, and soil moisture is likely to be reduced as snowpack 

amount and duration decrease.

Mid-Elevation Riparian and 

Wetland Communities

Vegetation Type Description and Distribution

Mid-elevation riparian and wetland communities include 

forests, shrublands, and herbaceous communities occurring 

adjacent to streams, in wet meadows, and surrounding water 

bodies, or proximal to seeps and springs. These communities 

generally occur between 5,500 and 8,500 feet throughout the 

IAP region. As noted earlier, mid-elevation streams transport 

sediments from these and higher-elevation riparian areas to 

the lower-elevation systems.

Mid-elevation riparian communities may be dominated 

by a variety of tree, shrub, and herbaceous species. Tree species, such as narrowleaf cottonwood (Populus angustifolia), 

quaking aspen (P. tremuloides), western river birch (Betula 

occidentalis), and thinleaf alder (Alnus incana) occur in 

these areas. Conifer species dominating adjacent landscapes, 

such as Douglas-fir (Pseudotsuga menziesii), white fir (Abies 

concolor), Engelmann spruce (Picea engelmannii), and blue 

spruce (P. pungens) may also occur at stream edges. Shrubs 

include mid-elevation willows, such as Booth’s willow (Salix 

boothii), Drummond’s willow, shining willow (S. lucida 

subsp. caudata), and dusky willow (S. melanopsis), and a 

variety of herbaceous meadow and wetland species. At the 

lower range of these communities, Nebraska sedge (Carex 

nebrascensis) can dominate meadows, along with tufted 

hairgrass.

Sensitivity to Climate Change: Moderate to High

Riparian areas, because of their high water tables, have 

some of the highest capacity to adapt to changing climates. 

However, as snowpacks are reduced and seasonality of runoff 

changes, the amount of water available for subsurface storage 

is likely to be reduced. Increasing temperatures will increase 

competition from invasive and riparian species from lower 

elevations, and reduced water tables will increase competition 

from adjacent upland species. Thus, the species composition 

of these riparian areas could change considerably in a changing climate.

Adaptive Capacity: Moderate

Adaptive capacity of these mid-elevation riparian and 

wetland ecosystems is moderate (table 7.2) and may be less 

in areas subjected to a wide variety of human influences. 

Historically, these ecosystems were affected by heavy 

livestock grazing. In addition, these areas have been used 

as locations for road construction, concentrated recreational 

uses, and several other developments. Many nonnative 

invasive species, such as Canada thistle (Cirsium arvense), 

nodding plumeless thistle (Carduus nutans), scotch thistle 

(Onopordum acanthium), and bull thistle (Cirsium vulgare), 

occur in these habitats. Waterways provide a means for 

dispersing these species widely. Because of the high level and 

variety of human impacts on these riparian ecosystems, many 

of these mid-elevation communities have lost resilience. 

These systems typically have high fuel moisture and are not 

very susceptible to wildland fire. When fires occur, however, 

they often move from adjacent upland communities into these 

environments (Dwire and Kauffman 2003).

Vulnerability to Climate Change: Moderate to High

Climate change vulnerability of mid-elevation riparian and 

wetland communities is rated as moderate to high because 

these communities have moderate to high sensitivity and 

moderate adaptive capacity to the effects of climate change 

(table 7.2). Mid-elevation riparian plant species may have the 

ability to move upward in elevation, but where resilience has 

been compromised by human uses, these systems may not be 

able to easily adjust to changes in their environment. Invasive 

species that already dominate many mid-elevation sites are 

likely to expand their dominance. As riparian areas become 

drier, upland species will continue to expand into these sites.

Low-Elevation Riparian and 

Wetland Communities

Vegetation Type Description and Distribution

Low-elevation riparian and wetland communities include 

forests, shrublands, and herbaceous communities occurring 

adjacent to streams and water bodies, in meadows, or around 

seeps and springs. These communities generally occur below 

about 5,500 feet throughout the IAP region. Lower-elevation 

streams are generally where sediments from mid- and upperelevation sources are deposited.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 189

These riparian communities may be dominated by a 

variety of tree, shrub, and herbaceous species. Tree species include narrowleaf cottonwood, lanceleaf cottonwood 

(Populus ×acuminata), Fremont cottonwood (P. fremontii), 

black cottonwood (P. balsamifera ssp. trichocarpa), and box 

elder (Acer negundo), as well as a wide variety of nonnative 

tree species. Shrubs include a wide variety of willows, such 

as yellow willow (Salix lutea), Geyer willow (S. geyeriana), 

Booth willow, Pacific willow (S. caudata) and narrowleaf 

willow (S. exigua). Beaked sedge (Carex utriculata), 

Nebraska sedge, and Baltic rush (Juncus arcticus) grow at 

many elevations, but are typically common at lower elevations. Low-elevation wetland and riparian communities are 

limited in their occurrence on National Forest System lands 

throughout the region because most of these habitats occur 

near or below the forest boundaries.

Sensitivity to Climate Change: High

Although riparian and wetland species at lower elevations 

in the IAP region may not be adapted to increasing temperatures, species from adjacent geographic areas could replace 

species that currently dominate these ecosystems. However, 

the low-elevation riparian and wetland communities are more 

likely to be affected by decreased flows and water availability 

through continued diversions. In addition, the timing of water 

availability (because of lower snowpacks) is likely to affect 

species with high water demands throughout the summer. 

Changes in the amount and timing of runoff events could 

greatly impact water tables and soil moisture relationships 

and eliminate much of the riparian and wetland habitats that 

remain at these lower elevations. Much has been written on 

the hydrological requirements for the germination of various 

cottonwoods and willows (Auble and Scott 1998; Mahoney 

and Rood 1998; Siegel and Brock 1990; Young and Clements 

2003). The connections among changes in climate, hydrology (timing and amount of flows), and the ability of these 

species to continue to germinate and establish are only now 

being investigated (Gori et al. 2014; Smith and Finch 2016; 

Stromberg et al. 2010). However, climate change has the 

potential to greatly affect the ability of these woody riparian 

dominant species to germinate and establish in the future; accordingly, low-elevation riparian and wetland ecosystems are 

rated as highly sensitive to climate change (table 7.2).

Adaptive Capacity: Low to Moderate

Many low-elevation riparian and wetland communities 

have been degraded from a wide variety of human influences 

(e.g., fig. 7.10), such as road construction, concentrated recreational uses, and other development. These areas have also 

been subjected to excessive, unmanaged livestock grazing, especially in the past. Management efforts by Federal agencies 

since the early 1980s have focused on reducing impacts and 

improving conditions of these systems.

As a result of historical land uses, many nonnative 

invasive species occur in these habitats. For example, these 

areas have had some of the greatest increases in nonnative 

invasive woody species, such as tamarisk (Tamarix chilensis, 

T. ramosissima) and Russian olive (Elaeagnus angustifolia), 

as well as nonnative invasive herbaceous species. Many of 

these herbaceous species are listed as noxious. Many lowelevation wetlands in the region have become dominated by 

the nonnative common reedgrass (Phragmites australis) (fig. 

7.11). Purple loosestrife (Lythrum salicaria) can also invade 

wetlands and replace existing native wetland species.

Vulnerability to Climate Change: High to Very High

The direct effects of reduced flows and changes in timing and duration of spring runoff because of climate change 

will reduce resilience in low-elevation riparian and wetland 

communities, and thus their vulnerability to climate change 

is rated as high to very high (table 7.2). These systems have 

also been affected by upstream diversions of water and wetland drainage, and by livestock grazing, development, road 

construction, and concentrated recreational uses. Additional 

pressures on these already vulnerable ecosystems could have 

significant effects in the future.

Figure 7.10—Heavily grazed 

riparian area. Heavy livestock 

grazing in riparian areas 

inhibits regeneration and 

growth of woody riparian 

species such as cottonwoods 

and willows (photo: W. 

Padgett, U.S. Forest Service).

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
190 USDA Forest Service RMRS-GTR-375. 2018

Figure 7.11—Common 

reedgrass that has invaded 

and dominated lowelevation wetlands along 

the Great Salt Lake in 

northern Utah (photo: W. 

Padgett, U.S. Forest Service).

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types

References

Abatzoglou, J.T.; Kolden, C.A. 2013. Relationships between 

climate and macroscale area burned in the western United 

States. International Journal of Wildland Fire. 22: 1003–1020.

Aleksoff, K.C. 1999. Symphoricarpos oreophilus. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.feis-crs.org/feis/faces/

index.xhtml [Accessed March 30, 2016].

Alexander, J.; Diez, J.; Levine, J. 2015. Novel competitors shape 

species’ responses to climate change. Nature. 525: 515–518.

Alo, C.A.; Wang, G. 2008. Hydrological impact of the potential 

future vegetation response to climate changes projected by 8 

GCMs. Journal of Geophysical Research: Biogeosciences. 113: 

G3.

Anderson, J.E.; Inouye, R.S. 2001. Landscape-scale changes in 

plant species abundance and biodiversity of a sagebrush steppe 

over 45 years. Ecological Monographs. 71: 531–556.

Anderson, M.D. 2001. Salix scouleriana. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.feis-crs.org/feis/faces/

index.xhtml [Accessed March 30, 2016].

Auble, G.T.; Friedman, J.M.; Scott, M.L. 1994. Relating riparian 

vegetation to present and future stream-flows. Ecological 

Applications. 4: 544–554.

Auble, G.T.; Scott, M.L. 1998. Fluvial disturbance patches and 

cottonwood recruitment along the upper Missouri River, 

Montana. Wetlands. 18: 546–556.

Baker, W.L. 2006. Fire and restoration of sagebrush ecosystems. 

Wildlife Society Bulletin. 34: 177–185.

Baker, W.L. 2011. Pre-Euro-American and recent fire in sagebrush 

ecosystems. In: Knick, S.T.; Connelly, J.W., eds. Greater 

Sage-grouse: Ecology and conservation of a landscape species 

and its habitats. Berkeley, CA: University of California Press: 

185–201.

Baker, W.L.; Shinneman, D.J. 2004. Fire and restoration of piñonjuniper woodlands in the western United States: A review. 

Forest Ecology and Management. 189: 1–21.

Balch, J.K.; Bradley, B.A.; D’Antonio, C.; Gomez-Dans, J. 2013. 

Introduced annual grass increases regional fire activity across 

the arid western USA (1980-2009). Global Change Biology. 19: 

173–183.

Balzotti, C.S.; Kitchen, S.G.; McCarthy, C. 2016. Beyond the 

single species climate envelope: A multifaceted approach to 

mapping climate change vulnerability. Ecosphere. 7: e01444.

Bauer, J.M.; Weisberg, P.J. 2009. Fire history of a central Nevada 

pinyon-juniper woodland. Canadian Journal of Forest Research. 

39: 1589–1599.

Beniston, M. 2003. Climatic change in mountain regions: A review 

of possible impacts. Climatic Change. 59: 5–31.

Beaubien, E.; Hamann, A. 2011. Spring flowering response to 

climate change between 1936 and 2006 in Alberta, Canada. 

BioScience. 61: 514–524.

Blaisdell, J.P.; Holmgren, R.C. 1984. Managing Intermountain 

rangelands–salt-desert shrub ranges. Gen. Tech. Rep. INT-163. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station. 52 p.

Blaisdell, J.P.; Murray, R.B.; McArthur, E.D. 1982. Managing 

Intermountain rangelands–sagebrush-grass ranges. Gen. Tech. 

Rep. INT-134. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Forest and Range Experiment 

Station. 41 p.

Brabec, M.M.; Germino, M.J.; Shinneman, D.J. [et al.]. 2015. 

Challenges of establishing big sagebrush (Artemisia tridentata) 

in rangeland restoration: Effects of herbicide, mowing, wholecommunity seeding, and sagebrush seed sources. Rangeland 

Ecology and Management. 68: 432–435.

Bradley, B.A. 2009. Regional analysis of climate change on 

cheatgrass invasion shows potential risk and opportunity. 

Global Change Biology. 15: 196–208.
USDA Forest Service RMRS-GTR-375. 2018 191

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types

Bradley, B.A. 2010. Assessing ecosystem threats from global and 

regional change: Hierarchical modeling of risk to sagebrush 

systems from climate change and invasive species in Nevada, 

USA. Ecography. 33: 198–208.

Bradley, B.A.; Curtis, C.A.; Chambers, J.C. 2016. Bromus

response to climate and projected changes with climate change. 

In: Germino, M.J.; Chambers, J.C.; Brown, C.S, eds. Exotic 

brome-grasses in arid and semiarid ecosystems of the western 

US: Causes, consequences, and management implications. 

Cham, Switzerland: Springer: 257–274.

Brooks, M.L.; Esque, T.C.; Duck, T. 2007. Creosotebush, 

blackbrush, and interior chaparral shrublands [Chapter 6]. In: 

Hood, S.M.; Miller, M., eds. Fire ecology and management 

of the major ecosystems of southern Utah. Gen. Tech. Rep. 

RMRS-GTR-202. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station: 

97–110.

Burkhardt, J.W.; Tisdale, E.W. 1969. Nature and successional 

status of western juniper vegetation in Idaho. Journal of Range 

Management. 22: 264–270.

Chambers, J.C. 2008. Climate change and the Great Basin. In: 

Chambers, J.C.; Devoe, N.; Evenden, A. eds. Collaborative 

management and research in the Great Basin: Examining the 

issues and developing a framework for action. Gen. Tech. 

Rep. RMRS-GTR-204. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station: 

29–32.

Chambers, J.C.; Bradley, B.A.; Brown, C.S.; [et al.]. 2013. 

Resilience to stress and disturbance, and resistance to Bromus 

tectorum L. invasion in cold desert shrublands of western North 

America. Ecosystems 17: 360–375.

Chambers, J.C.; Miller, R.F.; Board, D.I.; [et al.]. 2014. Resilience 

and resistance of sagebrush ecosystems: Implications for state 

and transition models and management treatments. Rangeland 

Ecology and Management. 67: 440–454.

Chambers, J.C.; Roundy, B.A.; Blank, R.R.; [et al.]. 2007. What 

makes Great Basin sagebrush ecosystems invasible by Bromus 

tectorum? Ecological Monographs. 77: 117–145.

Chaney, L.; Richardson, B.A.; Germino, M.J. 2017. Climate drives 

adaptive genetic responses associated with survival in big 

sagebrush (Artemisia tridentata). Evolutionary Applications. 

22: 699–710.

Collen, P.; Gibson, R.J. 2001. The general ecology of beavers 

(Castor spp.) as related to their influence on stream ecosystems 

and riparian habitats, and the subsequent effects on fish—A 

review. Reviews in Fish Biology and Fisheries. 10: 439–461.

Comer, P.; Faber-Langendoen, D.; Evans, R.; [et al.]. 2003. 

Ecological systems of the United States: A working 

classification of U.S. terrestrial systems. Arlington, VA: 

NatureServe.

Comer, P. J.; Young, B.; Schulz, K.; [et al.]. 2012. Climate change 

vulnerability and adaptation strategies for natural communities: 

piloting methods in the Mojave and Sonoran deserts. Report to 

the U.S. Fish and Wildlife Service. Arlington, VA: NatureServe.

Cooper, D.J.; Andersen, D.C.; Chimner, R.A. 2003. Multiple 

pathways for woody plant establishment on floodplains at local 

to regional scales. Journal of Ecology. 91: 182–196.

Crawford, J.A.; Olson, R.A.; West, N.E.; [et al.]. 2004. Ecology 

and management of sage-grouse and sage-grouse habitat. 

Journal of Range Management. 57: 2–19.

Cronin, E.H.; Williams, M.C. 1966. Principles for managing 

ranges infested with halogeton. Journal of Range Management. 

19: 226–227.

Cronquist, A.; Holmgren, N.H.; Holmgren, P.K. 1997. 

Intermountain flora: Vascular plants of the Intermountain West, 

USA. Volume 3, Part A: Subclass Rosidae (except Fabales). 

New York, NY: The New York Botanical Garden. 446 p.

D’Antonio, C.M.; Vitousek, P.M. 1992. Biological invasions by 

exotic grasses, the grass/fire cycle, and global change. Annual 

Review of Ecology and Systematics. 23: 63–87.

Davies, K.W.; Boyd, C.S., Nafus, A.M. 2013. Restoring the 

sagebrush component in crested wheatgrass–dominated 

communities. Rangeland Ecology and Management. 66: 

472–478.

Davies, K.W.; Sheley, R.L.; Bates, J.D. 2008. Does prescribed 

fall burning Artemisia tridentata steppe promote invasion or 

resistance to invasion after a recovery period? Journal of Arid 

Environments. 72: 1076−1085.

Davis, J.N.; Brotherson, J.D. 1991. Ecological relationships of 

curlleaf mountain-mahogany (Cercocarpus ledifolius Nutt.) 

communities in Utah and implications for management. The 

Great Basin Naturalist. 51: 153–166.

Dealy, J.E. 1975. Ecology of curl-leaf mahogany (Cercocarpus 

ledifolius Nutt.) in Oregon and adjacent areas. Doctoral 

dissertation. Corvallis, OR: Oregon State University. 168 p.

DeBano, L.F. 1981. Water repellent soils: A state-of-the-art. 

Gen. Tech. Rep. PSW-46. Berkeley, CA: U.S. Department 

of Agriculture, Forest Service, Pacific Southwest Forest and 

Range Experiment Station. 21 p.

Delcourt, P.A.; Delcourt, H.R. 1981. Vegetation maps for eastern 

North America: 40,000 yr B.P. to the present. In: Romans, R.C., 

ed. Geobotany II. New York, NY: Plenum: 123–165.

Dwire, K.A.; Kauffman, J.B. 2003. Fire and riparian ecosystems 

in landscapes of the western USA. Forest Ecology and 

Management. 178: 61–74.

Eckert, R.E., Jr. 1954. A study of competition between whitesage 

and halogeton in Nevada. Journal of Range Management. 7: 

223–225.

Ellison, L. 1954. Subalpine vegetation of the Wasatch Plateau, 

Utah. Ecological Monographs. 24: 89–184.

Engel, D.M.; Bonham, C.D.; Bartel, L.E. 1983. Ecological 

characteristics and control of Gambel oak. Journal of Range 

Management. 36: 363–365.

Engelhardt, B.M.; Chambers, J.C.; Weisberg, P.J. 2015. 

Geomorphic predictors of riparian vegetation in small mountain 

watersheds. Journal of Plant Ecology. 8: 593–604.

Fernandez, D.P.; Neff, J.C.; Cho-ying, H.; [et al.]. 2013. Twentieth 

century carbon stock changes related to piñon-juniper 

expansion into a black sagebrush community. Carbon Balance 

and Management. 8: 8.

Finch, D.M., ed. 2012. Climate change in grasslands, shrublands, 

and deserts of the interior American West: A review and needs 

assessment. Gen. Tech. Rep. RMRS-GTR-285. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 139 p.

Fischer, W.C.; Clayton, B.D. 1983. Fire ecology of Montana forest 

habitat types east of the Continental Divide. Gen. Tech. Rep. 

INT-GTR-141. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Forest and Range Experiment 

Station. 83 p.
192 USDA Forest Service RMRS-GTR-375. 2018

Floyd, M.L.; Romme, W.H.; Rocca, M.E.; [et al.]. 2015. Structural 

and regenerative changes in old-growth piñon-juniper 

woodlands following drought-induced mortality. Forest 

Ecology and Management. 341: 18–29.

Fryer, J.L. 2009. Artemisia nova. In: Fire Effects Information 

System. Missoula, MT: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station, Fire Sciences 

Laboratory. http://www.fs.fed.us/database/feis/ [Accessed 

March 30, 2016].

Garrison, H. 2006. Study of a putative hybrid taxon in the 

Artemisia tridentata complex. Master of Science Thesis. Logan, 

UT: Utah State University.

Garrison, H.D.; Shultz, L.M.; McArthur, E.D. 2013. Studies of 

a new hybrid taxon in the Artemisia tridentata (Asteraceae: 

Anthemideae) complex. Western North American Naturalist. 

73: 1–19.

Glenn, E.P.; Hodges, C.N.; Lieth, H.; [et al.]. 1992. Climate: 

Growing halophytes to remove carbon from the atmosphere. 

Environment. 34: 40–43.

Gonella, M.P.; Neel, M.C. 1995. Characterizing rare plant habitat 

for restoration in the San Bernardino National Forest. In: 

Roundy, B.A.; McArthur, E.D.; Haley, J.S.; Mann, D.K., 

comps. Proceedings: wildland shrub and arid land restoration 

symposium; 1993 October 19-21; Las Vegas, NV. Gen. 

Tech. Rep. INT-GTR-315. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station: 

81–93.

Goodrich, S.K.; Zobell, A. 2011. Trend of Gardner saltbush and 

halogeton in the lower Green River Basin, Wyoming. In: 

Monaco, T.A.; Schupp, E.W.; Pendleton, R.L.; [et al.], comps. 

Proceedings—Threats to shrubland ecosystem integrity; 2010 

May 18-20; Logan, UT. Natural Resources and Environmental 

Issues, Volume 17. Logan, UT: S.J. and Jessie E. Quinney 

Natural Resources Research Library: 291–297.

Gori, D.; Cooper, M.S.; Soles, E.S.; [et al.]. 2014. Gila River 

flow needs assessment. The Nature Conservancy. http://

nmconservation.org/Gila/GilaFlowNeedsAssessment.pdf 

[Accessed January 13, 2017].

Gottfried, M.; Pauli, H.; Futschik, A.; [et al.]. 2012. Continentwide response of mountain vegetation to climate change. 

Nature Climate Change. 2: 111–115.

Gregory, S. 1982. Subalpine forb community types of the 

Bridger-Teton National Forest, Wyoming. Ogden, Utah: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region.

Gruell, G.; Bunting, S.; Neuenschwander, L. 1985. Influence of 

fire on curlleaf mountain-mahogany in the Intermountain West. 

In: Lotan, J.E.; Brown, J.K., comps. Fire‘s effects on wildlife 

habitat—Symposium proceedings; 1984 March 21; Missoula, 

MT. Gen. Tech. Rep. INT-186. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station: 

58–72.

Gucker, C.L. 2006. Cercocarpus ledifolius. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.fs.fed.us/database/feis/ 

[Accessed March 30, 2016].

Gucker, C. 2012. Rubus parviflorus. In: Fire Effects Information 

System. Missoula, MT: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station, Fire Sciences 

Laboratory. http://www.fs.fed.us/database/feis/ [Accessed 

March 30, 2016].

Harper, K.T.; Van Buren, R.; Kitchen, S.G. 1996. Invasion of alien 

annuals and ecological consequences in salt desert shrublands 

of western Utah. In: Barrow, J.R.; McArthur, E.D.; Sosebee, 

R.E.; Tausch, J.R., comps. Proceedings—Symposium on 

shrubland ecosystem dynamics in a changing environment; 

1995 May 23–25; Las Cruces, NM. Gen. Tech. Rep. INTGTR-338. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Research Station: 58–65.

Hayward, C.L. 1952. Alpine biotic communities of the Uinta 

Mountains, Utah. Ecological Monographs. 22: 93–120.

Heyerdahl, E.K.; Miller, R.F.; Parsons, R.A. 2006. History of fire 

and Douglas-fir establishment in a savanna and sagebrush–

grassland mosaic, southwestern Montana, USA. Forest Ecology 

and Management. 230: 107–118.

Hoffmann, A.A.; Sgrò, C.M. 2011. Climate change and 

evolutionary adaptation. Nature. 470: 479–485.

Hooker, T.D.; Stark, J.M.; Norton, U.; [et al.]. 2008. Distribution 

of ecosystem C and N within contrasting vegetation types in a 

semiarid rangeland, in the Great Basin, USA. Biogeochemistry. 

90: 291–308.

Howard, J.L. 2003. Artemisia bigelovii. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.fs.fed.us/database/feis/

plants/shrub/artbig/all.html [Accessed March 30, 2016].

Hull, A.C., Jr.; Hull, M.K. 1974. Presettlement vegetation in Cache 

Valley, Utah and Idaho. Journal of Range Management. 27: 

27–29.

Intergovernmental Panel on Climate Change [IPCC]. 2007. 

Climate change 2007: Impacts, adaptation, and vulnerability; 

contribution of working group II to the fourth assessment report 

of the Intergovernmental Panel on Climate Change, (ed.) M.L. 

Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden, and 

C.E. Hanson. Cambridge, UK: Cambridge University Press. 

976 p.

Jakubos, B.; Romme, W.H. 1993. Invasion of subalpine meadows 

by lodgepole pine in Yellowstone National Park, Wyoming, 

USA. Arctic and Alpine Research. 25: 382–390.

Jenkins, S.H.; Busher, P.E. 1979. Castor canadensis. Mammalian 

Species. 120: 1–8.

Jepson Flora Project. 2016. Artemisia rothrockii (Rothrock 

sagebrush). The Jepson Herbarium. http://ucjeps.berkeley.edu/

eflora/eflora_display.php?tid=1238 [Accessed March 30, 2016].

Johnson, K.A. 2000. Prunus virginiana. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.fs.fed.us/database/feis/

plants/tree/pruvir/all.html [Accessed March 30, 2016].

Kauffman, J.B. 2001. Workshop on the multiple influences 

of riparian/stream ecosystems on fires in western forest 

landscapes: Summary report to Rocky Mountain Forest and 

Range Experiment Station, Stream Systems Technical Center, 

Fort Collins, CO. Corvallis, OR: Oregon State University, 

Department of Fisheries and Wildlife. 209 p.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 193

Kaufmann, M.R.; Huisjen, D.W.; Kitchen, S.; [et al.]. 2016. 

Gambel oak ecology and management in the southern Rockies: 

The status of our knowledge. SRFSN Publication 2016-1. Fort 

Collins, CO: Colorado State University, Southern Rockies Fire 

Sciences Network. 16 p.

Kay, C. 2015. Long-term vegetation change in Utah’s Henry 

Mountains: A study in repeat photography. Publication Number 

BLM-UT-GI-14001-8002. Providence, UT: U.S. Department 

of the Interior, Bureau of Land Management. https://www.blm.

gov/style/medialib/blm/wo/blm_library/misc_pubs.Par.74891.

File.dat/Kay2015_HenryMtns.pdf [Accessed February 13, 

2017].

Kitchen, S.G.; Jorgensen, G.L. 1999. Annualization of rodent 

burrow clusters and winterfat decline in a salt-desert 

community. In: McArthur E.D.; Ostler, W.K.; Wambolt, C.L. 

comps. Proceedings: shrubland ecotones; 1998 August 12-14; 

Ephraim, UT. Proc. RMRS-P-11. Odgen, UT: U.S. Department 

of Agriculture, Forest Service, Rocky Mountain Research 

Station: 175–180.

Kitchen, S.G.; Jorgensen, G.L. 2001. Winterfat decline and 

halogeton spread in the Great Basin. In: McArthur, E.D.; 

Fairbanks, D.J., comps. Shrubland ecosystem genetics and 

biodiversity: Proceedings; 2000 June 13-15; Provo, UT. 

Proceedings RMRS-P-21. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station: 

200–203.

Kitchen, S.G.; McArthur, E.D. 2007. Big and black sagebrush 

landscapes. In: Hood, S.M.; Miller, M., eds. Fire ecology 

and management of the major ecosystems of southern Utah. 

Gen. Tech. Rep. RMRS-GTR-202. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station: 73–95.

Kitchen, S.G.; Meyer, S.E.; Carlson, S.L. 2015. Mechanisms 

for maintenance of dominance in a nonclonal desert shrub. 

Ecosphere. 6: 252.

Kropp, B.R.; Hutchison, L.J. 1996. Gigasperma americanum, a 

new hypogeous member of the Basidiomycota associated with 

Cercocarpus ledifolius in Utah. Mycologia. 88: 662–665.

LANDFIRE. 2008. Biophysical settings layers, LANDFIRE 1.1.0. 

U.S. Department of the Interior, Geological Survey. http://

landfire.cr.usgs.gov/viewer/ [Accessed March 27, 2016].

LANDFIRE. 2012. Existing vegetation type layers, LANDFIRE 

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

http://landfire.cr.usgs.gov/viewer/ [Accessed March 27, 2016].

Lanner, R.M. 1983. Trees of the Great Basin: A natural history. 

Reno, NV: University of Nevada Press. 215 p.

Lesica, P.; Cooper, S.V.; Kudray, G. 2007. Recovery of big 

sagebrush following fire in southwestern Montana. Rangeland 

Ecology and Management. 60: 261–269.

Lesica, P.; DeLuca, T.H. 1996. Long-term harmful effects of 

crested wheatgrass on Great Plains grassland ecosystems. 

Journal of Soil and Water Conservation. 51: 408–409.

Lewis, M.E. 1971. Flora and major plant communities of the 

Ruby-East Humboldt Mountains; with special emphasis on 

Lamoille Canyon. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Humboldt National Forest.

Lewis, M.E. 1975. Plant communities of the Jarbridge Mountain 

complex; Humboldt National Forest. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Region.

Lewis, M.E. 1993. Successional changes in the tall forb type: 

Wasatch Plateau. Report. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Region. 75 p.

Loope, L.L. 1970. Subalpine and alpine vegetation of northeastern 

Nevada. Ph.D. dissertation. Durham, NC: Duke University. 

292 p.

Mahalovich, M.F.; McArthur, E.D. 2004. Sagebrush (Artemisia

spp.) seed and plant transfer guidelines. Native Plants Journal. 

5: 141–148.

Mahoney, J.M.; Rood, S. 1998. Streamflow requirements for 

cottonwood seedling recruitment—An integrative model. 

Wetlands. 18: 634–645.

McArthur, E.D. 1994. Ecology, distribution, and values of 

sagebrush within the Intermountain Region. In: Monsen, S.B.; 

Kitchen, S.G., comps. Proceedings—ecology and management 

of annual rangelands; 1992 May 18-22; Boise, ID. Gen. 

Tech. Rep. INT-GTR-313. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station: 

347–351.

McArthur, E.D. 2000. Sagebrush systematics and distribution. In: 

Entwistle, P.G.; DeBolt, A.M.; Kaltenecker, J.H.; Steenhof, K., 

comps. Proceedings: Sagebrush steppe ecosystems symposium. 

Bureau of Land Management Publication No. BLM/ID/PT001001+1150. Boise, ID: Bureau of Land Managment: 9–14.

McArthur, E.D.; Richardson, B.A.; Kitchen, S.G. 2013. Great 

Basin Experimental Range: Annotated bibliography. Gen. 

Tech. Rep. RMRS-GTR-305WWW. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station. 97 p.

McArthur, E.D.; Sanderson, S.C. 1999. Ecotone: Introduction, 

scale, and big sagebrush example. In: McArthur, E.D.; Ostler, 

K.W.; Wambolt, C.L., comps. Proceedings: Shrubland ecotones. 

Proceedings RMRS-P-11. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station: 

3–8.

McKell, C.M. 1989. Shrub palatability. In: McKell, C.M., ed. The 

biology and utilization of shrubs. San Diego, CA: Academic 

Press, Inc.: 267–281.

McKenzie, D.; Gedalof, Z.E.; Peterson, D.L.; Mote, P. 2004. 

Climatic change, wildfire, and conservation. Conservation 

Biology. 18: 890–902.

McLachlan, J.S.; Clark, J.S.; Manos, P.S. 2005. Molecular 

indicators of tree migration capacity under rapid climate 

change. Ecology. 86: 2088–2098.

McWilliams, J. 2003. Artemisia rigida. In: Fire Effects Information 

System. Missoula, MT: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station, Fire Sciences 

Laboratory. http://www.fs.fed.us/database/feis/ [Accessed 

March 30, 2016].

Mensing, S.; Livingston, S.; Barker, P. 2006. Long-term fire history 

in Great Basin sagebrush reconstructed from macroscopic 

charcoal in spring sediments, Newark Valley, Nevada. Western 

North American Naturalist. 66: 64–77.

Merritt, D.M.; Nilsson, C.; Jansson, R. 2010. Consequences of 

propagule dispersal and river fragmentation for riparian plant 

community diversity and turnover. Ecological Monographs. 80: 

837–858.

Meyer, S.E. 2003. Atriplex L. saltbush. In: Bonner, F.T., tech. 

coord. Woody plant seed manual. Washington, DC: U.S. 

Department of Agriculture, Forest Service. http://www.nsl.

fs.fed.us/A%20genera.pdf [Accessed March 30, 2016].

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
194 USDA Forest Service RMRS-GTR-375. 2018

Meyer, S.E.; Garvin, S.C.; Beckstead, J. 2001. Factors mediating 

cheatgrass invasion of intact salt desert shrubland. In: 

McArthur, E.D.; Fairbanks, D.J., comps. Shrubland ecosystem 

genetics and biodiversity: Proceedings; 2000 June 13-15; 

Provo, UT. Proceedings RMRS-P-21. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station: 224–232.

Meyer, S.E.; Warren, T.W. 2015. Seeding big sagebrush 

successfully on Intermountain rangelands. Great Basin 

Factsheet No. 10. Sage Grouse Initiative. http://www.

sagegrouseinitiative.com/seeding-big-sagebrush-successfullyon-intermountain-rangelands/ [Accessed November 10, 2016].

Millar, C.I.; Stephenson, N.L. 2015. Temperate forest health in an 

era of emerging megadisturbance. Science. 349: 823–826.

Miller, R.F.; Baisan, C.; Rose, J.; Pacioretty, D. 2001. Pre- and 

post-settlement fire regimes in mountain big sagebrush steppe 

and aspen: The Northwestern Great Basin. Final Report to 

the National Interagency Fire Center. http://fresc.usgs.gov/

products/papers/fr-nifc.pdf [Accessed November 10, 2016].

Miller, R.F., Knick, S.T.; Pyke, D.A.; [et al.]. 2011. Characteristics 

of sagebrush habitats and limitations to long-term conservation. 

In: Knick, S.T.; Connelly, J.W., eds. Greater sage-grouse: 

Ecology and conservation of a landscape species and its 

habitats. Studies in Avian Biology, Volume 38. Berkeley, CA: 

University of California Press: 145–184.

Miller R.F.; Rose, J.A. 1999. Fire history and western juniper 

encroachment in sagebrush steppe. Journal of Range 

Management. 52: 550–559.

Miller, R.F.; Tausch, R.J. 2001. Role of fire in juniper and pinyon 

woodlands: A descriptive analysis. In: Proceedings of the 

invasive species workshop: Tall Timbers Research Station 

Miscellaneous Publication, No. 11: 15–30.

Miller, R.F.; Tausch, R.J.; McArthur, E.D.; [et al.]. 2008. Age 

structure and expansion of piñon–juniper woodlands: A regional 

perspective in the Intermountain West. Research Paper RMRSRP-69. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station. 15 p.

Miller, R.F.; Tausch, R.; Waichler, W. 1999. Old-growth juniper 

and pinyon woodlands. In: Monsen, S.B.; Stevens, R., comps. 

Proceedings: Ecology and management of pinyon-juniper 

communities within the Interior West; September 15-18, 

1997; Provo, UT. Proceedings RMRS-P-9. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station: 375–384.

Morgan, J.A.; Milchunas, D.G.; LeCain, D.R.; [et al.]. 2007. 

Carbon dioxide enrichment alters plant community structure 

and accelerates shrub growth in the shortgrass steppe. 

Proceedings of the National Academy of Sciences, USA. 104: 

14724–14729.

Morgan, J.A.; Pataki, D.E.; Korner, C.; [et al.]. 2004. Water 

relations in grassland and desert ecosystems exposed to 

elevated atmospheric CO2

. Oecologia. 140: 11–25.

Mozingo, H.N. 1987. Shrubs of the Great Basin: A natural history. 

Reno, NV: University of Nevada Press.

Munson, S.M., Belnap, J.; Schelz, C.D.; [et al.]. 2011. On the brink 

of change: Plant responses to climate on the Colorado Plateau. 

Ecosphere. 2: 68.

Naiman, R.J.; Dècamps, H. 1997. The ecology of interfaces: 

Riparian zones. Annual Review of Ecology and Systematics. 

28: 621–658.

Nakamura, F.; Swanson, F.J.; Wondzell, S.M. 2000. Disturbance 

regimes of stream and riparian systems—A disturbance-cascade 

perspective. Hydrological Processes. 14: 2849–2860.

Natural Resources Conservation Service [NRCS]. 2017. The 

PLANTS Database. Greensboro, NC: National Plant Data 

Team. http://plants.usda.gov [Accessed July 12, 2017].

NatureServe. 2013. International ecological classification standard: 

Terrestrial ecological classifications. NatureServe central 

databases. Arlington, VA: NatureServe.

Neff, J.C.; Barger, T.N.N.; Baisden, W.T.; [et al.]. 2009. Soil 

carbon storage responses to expanding pinyon-juniper 

populations in southern Utah. Ecological Applications. 19: 

1405–1416.

Nelson, Z.J.; Weisberg, P.J.; Kitchen, S.G. 2014. Influence of 

climate and environment on post-fire recovery of mountain big 

sagebrush. International Journal of Wildland Fire. 23: 131–142.

Neilson, R.P.; Lenihan, J.M.; Bachelet, D.; Drapek, R.J. 2005. 

Climate change implications for sagebrush ecosytems. 

Transactions of the North American Wildlife and Natural 

Resources Conference: 145–159.

Nilsson, C.; Berggren, K. 2000. Alterations of riparian ecosystems 

caused by river regulation. Bioscience. 50: 783–792.

Noss, R.F.; LaRoe, E.T., III; Scott, J.M. 1995. Endangered 

ecosystems of the United States: A preliminary assessment of 

loss and degradation. Biological Report 28. Washington, DC: 

U.S. Department of the Interior, National Biological Service.

Nowak R.S.; Ellsworth, D.S.; Smith, S.D. 2004. Functional 

responses of plants to elevated atmospheric CO2

—Do 

photosynthetic and productivity data from FACE experiments 

support early predictions? New Phytologist. 162: 253–280.

Otsyina, R.M.; McKell, C.M.; Malecheck, J.M.; Van Epps, G.A. 

1984. Potential of Atriplex and other chenopod shrubs for 

increasing range productivity and fall and winter grazing. In: 

Tiedemann, A.R.; McArthur, E.D.; Stutz, H.C.; [et al.], comps. 

Proceedings—Symposium on the biology of Atriplex and 

related chenopods; 1983 May 2-6; Provo, UT. Gen. Tech. Rep. 

INT-172. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Forest and Range Experiment Station: 

215–219.

Parmesan, C. 2006. Ecological and evolutionary responses to 

recent climate change. Annual Review of Ecology, Evolution, 

and Systematics. 37: 637–669.

Parry, O.F.; Canziani, J.P.; Palutikof, P.J.; [et al.], eds. 2007. 

Climate change 2007: Impacts, adaptation, and vulnerability; 

contribution of working group II to the fourth assessment report 

of the Intergovernmental Panel on Climate Change. Cambridge, 

UK: Cambridge University Press.

Paruelo, J.M.; Lauenroth, W.K. 1996. Relative abundance of plant 

functional types in grasslands and shrublands of North America. 

Ecological Applications. 6: 1212–1224.

Patten, D.T. 1998. Riparian ecosystems of semi-arid North 

America: Diversity and human impacts. Wetlands. 18: 498–512.

Pauli, H.; Gottfried, M.; Grabherr, G. 2003. Effects of climate 

change on the alpine and nival vegetation of the Alps. Journal 

of Mountain Ecology. 7: 9–12.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 195

Pendleton, R.L.; Pendleton, B.K.; Harper, K.T. 1989. Breeding 

systems of woody plant species in Utah. In: Wallace, A.; 

McArthur, E.D.; Haferkamp, M.R., comps. Proceedings—

Symposium on shrub ecophysiology and biotechnology; 

1987 June 30-July 2; Logan, UT. Gen. Tech. Rep. INT-256. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station: 5–22.

Pendleton, R.L.; Pendleton, B.K.; Meyer, S.E.; [et al.]. 2015. 

Blackbrush (Coleogyne ramosissima Torr.): State of our 

knowledge and future challenges. In: Huenneke, L.F.; van 

Riper, C., III; Hays-Gilpin, K.A., eds. The Colorado Plateau VI: 

science and management at the landscape scale. Tucson, AZ: 

University of Arizona Press: 142–155.

Perry, L.G.; Andersen, D.C.; Reynolds, L.V.; [et al.]. 2012. 

Vulnerability of riparian ecosystems to elevated CO2

 and 

climate change in arid and semiarid western North America. 

Global Change Biology. 18: 821–842.

Pickford, G.D. 1932. The influence of continued heavy grazing and 

promiscuous burning on spring–fall ranges in Utah. Ecology. 

13: 159–171.

Piemeisel, R.L. 1951. Causes affecting change and rate of change 

in a vegetation of annuals in Idaho. Ecology. 32: 53–72.

Poff, N.L.; Allan, J.D.; Bain, M.B.; [et al.]. 1997. The natural flow 

regime: A paradigm for river conservation and restoration. 

Bioscience. 47: 769–784.

Pollock, M.M.; Heim, M.; Werner, D. 2003. Hydrologic and 

geomorphic effects of beaver dams and their influence on 

fishes. American Fisheries Society Symposium. 37: 1–21.

Poore, R.E.; Lamanna, C.A.; Ebersole, J.J.; Enquist, B.J. 2009. 

Controls on radial growth of mountain big sagebrush and 

implications for climate change. Western North American 

Naturalist. 69: 556–562.

Potter, A.F. 1902. Diary of Albert F. Potter (Former Associate 

Chief of Forest Service) July, 1902 to November 22, 1902. 

58 p.

Prevedel, D.A.; Johnson, C.M. 2005. Beginnings of range 

management: Albert F. Potter, first Chief of Grazing, U.S. 

Forest Service, and a photographic comparison of his 1902 

Forest Reserve Survey in Utah with conditions 100 years later. 

R4-VM 2005-01. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Region. 94 p.

Rau, B.M.; Johnson, D.W.; Blank, R.R.; [et al.]. 2011. Transition 

from sagebrush steppe to annual grass (Bromus tectorum): 

Influence on belowground carbon and nitrogen. Rangeland 

Ecology and Management. 64: 139–147.

Reeves, M.C.; Moreno, A.L.; Bagne, K.E.; Running, S.W. 2014. 

Estimating climate change effects on net primary production 

of rangelands in the United States. Climatic Change. 126: 

429–442.

Rehfeldt, G.E.; Crookston, N.L.; Saenz-Romero, C.; Campbell, 

E.M. 2012. North American vegetation model for land-use 

planning in a changing climate: A solution to large classification 

problems. Ecological Applications. 22: 119–141.

Rehfeldt, G.E.; Crookston, N.L.; Warwell, M.V.; Evans, J.S. 

2006. Empirical analyses of plant-climate relationships for the 

western United States. International Journal of Plant Sciences. 

167: 1123–1150.

Richardson, B.A.; Meyer, S.E. 2012. Paleoclimate effects and 

geographic barriers shape regional population genetic structure 

of blackbrush (Coleogyne ramosissima: Rosaceae). Botany. 90: 

293–299.

Richardson, B.A.; Kitchen, S.G.; Pendleton, R.L.; [et al.]. 2014. 

Adaptive responses reveal contemporary and future ecotypes in 

a desert shrub. Ecological Applications. 24: 413–427.

Riegel, G.M.; Miller, R.F.; Skinner, C.N.; Smith, S.E. 2006. 

Northeastern Plateaus Bioregion. In: Sugihara, N.G.; van 

Wagtendonk, J.W.; Fites-Kaufmann, J.; [et al.], eds. Fire in 

California’s ecosystems. Berkeley, CA: University of California 

Press: 225–263.

Rivera, S.; Shultz, L; Hernandez, A.J.; Ramsey, R.D. 2011. GIS 

ordination approach to model distribution of shrub species in 

northern Utah. Natural Resources and Environmental Issues. 

17: 1–12.

Robertson, J.H.; Kennedy, P.B. 1954. Half-century changes on 

northern Nevada ranges. Journal of Range Management. 7: 

117–121.

Romme, W. H.; Allen, C.D.; Bailey, J.D.; [et al.]. 2009. Historical 

and modern disturbance regimes, stand structures, and 

landscape dynamics in piñon-juniper vegetation of the western 

United States. Rangeland Ecology and Management. 62: 

203–222.

Romo, J.T.; Young, J.A. 2002. Temperature profiles and the effects 

of field environments on germination of silver sagebrush. 

Native Plants Journal. 3: 5–13.

Rosell, F.; Bozser, O.; Collen, P.; Parker, H. 2005. Ecological 

impact of beavers Castor fiber and Castor canadensis and their 

ability to modify ecosystems. Mammal Review. 35: 248–276.

Rowland, M.M.; Suring, L.H.; Leu, M.; [et al.]. 2011. Sagebrushassociated species of conservation concern. In: Hanser, S.E.; 

Leu, M.; Knick, S.T.; Aldridge, C.L., eds. Sagebrush ecosystem 

conservation and management: ecoregional assessment tools 

and models for the Wyoming Basins. Lawrence, KS: Allen 

Press: 46–68.

Sada, D. 2008. Great Basin riparian and aquatic ecosystems. In: 

Chambers, J.C.; Devoe, N.; Evenden, A., eds. Collaborative 

management and research in the Great Basin—Examining 

the issues and developing a framework for action. Gen. Tech. 

Rep. RMRS-GTR-204. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station: 

49–54.

Salo, C. 2005. Red brome (Bromus rubens subsp. madritensis) 

in North America: Possible modes for early introductions, 

subsequent spread. Biological Invasions. 7: 165–180.

Sanderson, S.C.; McArthur, E.D.; Stutz, H.C. 1989. A relationship 

between polyploidy and habitat in western shrub species. 

In: Wallace, A.; McArthur, E.D.; Haferkamp, M.R., comps. 

Proceedings on shrub ecophysiology and biotechnology. 

Gen. Tech. Rep. INT-256. Ogden, UT: U.S. Department of 

Agriculture, Forest Service: 23–30.

Schlaepfer, D.R.; Lauenroth, W.K; Bradford, J.B. 2012. Effects 

of ecohydrological variables on current and future ranges, 

local suitability patterns, and model accuracy in big sagebrush. 

Ecohydrology. 35: 374–384.

Schlaepfer, D.R.; Lauenroth, W.K.; Bradford, J.B. 2014. Modeling 

regeneration responses of big sagebrush (Artemisia tridentata) 

to abiotic conditions. Ecological Modeling. 286: 66–77.

Schultz, B.; McAdoo, K. 2002. Common sagebrush in Nevada. 

Special Publication SP-02-02. Reno, NV: University of Nevada, 

Cooperative Extension. 9 p.

Schwinning, S.; Belnap, J.; Bowling, D.R.; Ehleringer, J.R. 

2008. Sensitivity of the Colorado Plateau to change: Climate, 

ecosystems, and society. Ecology and Society. 13: 28.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
196 USDA Forest Service RMRS-GTR-375. 2018

Schwinning, S., Starr, B.I.; Wojcik, N.J.; [et al.]. Sanford. 

2005. Effects of nitrogen deposition on an arid grassland in 

the Colorado plateau cold desert. Rangeland Ecology and 

Management. 58: 565–574.

Scott, M.L.; Auble, G.T.; Friedman, J.M. 1997. Flood dependency 

of cottonwood establishment along the Missouri River, 

Montana, USA. Ecological Applications. 7: 677–690.

Scott M.L.; Friedman, J.M.; Auble, G.T. 1996. Fluvial process and 

the establishment of bottomland trees. Geomorphology. 14: 

327–339.

Shiflet, T.N., ed. 1994. Rangeland cover types of the United States. 

Denver, CO: Society for Range Management.

Shultz, L.M. 2006. Artemisia tripartita subsp. tripartita. In: Flora 

of North America. Vol. 19, 20, and 21. New York, NY: Flora of 

North America.

Siegel, R.S.; Brock, J.H. 1990. Germination requirements of key 

Southwestern woody riparian species. Desert Plants. 10: 3–8.

Simonin, K.A. 2000. Quercus gambelii. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.fs.fed.us/database/feis/

plants/tree/quegam/all.html [Accessed March 30, 2016].

Smith, A.D.; Beale, D.M. 1980. Pronghorn antelope in Utah: Some 

research and observations. Publication No. 80-13. Salt Lake 

City, UT: Utah Division of Wildlife Resources. 88 p.

Smith, D.M.; Finch, D.M. 2016. Riparian trees and aridland 

streams of the southwestern United States: An assessment of 

the past, present, and future. Journal of Arid Environments. 

135: 120–131.

Smith, J.K.; Fischer, W.C. 1997. Fire ecology of the forest habitat 

types of northern Idaho. Gen. Tech. Rep. INT-363. Ogden, UT: 

U.S. Department of Agriculture, Forest Service, Intermountain 

Region. 142 p.

Smith, S.D.; Strain, B.R.; Sharkey, T.D. 1987. Effects of CO2

enrichment on four Great Basin grasses. Functional Ecology. 1: 

139–143.

Steinberg, P.D. 2002. Artemisia arbuscula. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.fs.fed.us/database/feis/ 

[Accessed March 30, 2016].

Stella, J.C.; Hayden, M.K.; Battles, J.J.; [et al.]. 2011. The role of 

abandoned channels as refugia for sustaining pioneer riparian 

forest ecosystems. Ecosystems. 14: 776–790.

Still, S.M.; Richardson, B.A. 2015. Protections of contemporary 

and future climate niche for Wyoming big sagebrush (Artemisia 

tridentata subsp. wyomingensis): A guide for restoration. 

Natural Areas Journal. 35: 30–43.

Stromberg, J. 1993. Instream flow models for mixed deciduous 

riparian vegetation within a semiarid region. Regulated Rivers. 

8: 225–235.

Stromberg, J.C.; Lite, S.J.; Dixon, M.D. 2010. Effects of stream 

flow patterns on riparian vegetation of a semiarid river: 

Implications for a changing climate. River Research and 

Applications. 26: 712–729.

Stromberg, J.C.; Patten, D.T. 1995. Instream flow and cottonwood 

growth in the eastern Sierra Nevada of California USA. 

Regulated Rivers. 12: 1–12.

Summers, H.A.; Smith, B.N.; Hansen, L.D. 2009. Comparison 

of respiratory and growth characteristics of two co-occurring 

shrubs from a cold desert, Coleogyne ramosissima (blackbrush) 

and Atriplex confertifolia (shadscale). Journal of Arid 

Environments. 73: 1–6.

Tausch, R.J.; Hood, S. 2007. Pinyon/juniper woodlands. In: Hood, 

S.M.; Miller, M., eds. Fire ecology and management of the 

major ecosystems of southern Utah. Gen. Tech. Rep. RMRSGTR-202. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station: 57–71.

Tollefson, J.E. 2006. Acer grandidentatum. In: Fire Effects 

Information System. Missoula, MT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, 

Fire Sciences Laboratory. http://www.fs.fed.us/database/feis/

plants/tree/acegra/all.html [Accessed March 30, 2016].

Tueller, P.T.; Eckert, R.E., Jr. 1987. Big sagebrush (Artemisia 

tridentata vaseyana) and longleaf snowberry (Symphoricarpos 

oreophilus) plant associations in northeastern Nevada. The 

Great Basin Naturalist. 47: 117–131.

Ulev, E.D. 2005. Artemisia pygmaea. In: Fire Effects Information 

System. Missoula, MT: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station, Fire Sciences 

Laboratory. http://www.fs.fed.us/database/feis/ [Accessed 

March 30, 2016].

U.S. Environmental Protection Agency [EPA]. 1998. Climate 

change and Idaho. EPA 236-F-98-007f. Washington, DC: 

Environmental Protection Agency. 4 p.

U.S. Department of Agriculture, Forest Service [USDA FS]. 2013. 

Inyo National Forest assessment. Bishop, CA: U.S. Department 

of Agriculture, Forest Service, Inyo National Forest. 229 p.

U.S. Department of Agriculture, Forest Service [USDA FS]. 2017. 

Plant species and climate profile predictions. Rocky Mountain 

Research Station Moscow Forestry Sciences Laboratory. http://

forest.moscowfsl.wsu.edu/climate/species/index.php [Accessed 

October 26, 2017].

U.S. Department of Agriculture, Forest Service [USDA FS]. [n.d.]. 

What is a tall forb community? Rangeland Management and 

Vegetation Ecology—Botany Program. http://www.fs.fed.us/

wildflowers/beauty/Tall_Forb/what.shtml [Accessed October 

26, 2017].

Utah State University [USU] Extension. 2016. Range plants of 

Utah. http://extension.usu.edu/rangeplants/ [Accessed March 

14, 2016].

Vale, T.R. 1975. Presettlement vegetation in the sagebrush-grass 

area of the Intermountain West. Journal of Range Management. 

28: 22–36.

Welch, B.L. 1989. Nutritive value of shrubs. In: McKell, C.M., 

ed. The biology and utilization of shrubs. San Diego, CA: 

Academic Press, Inc.: 405–424.

Wellner, C.A. 1970. Fire history in the Northern Rocky Mountains. 

In: Symposium, the role of fire in the Intermountain West. 

October 27-29; Missoula, MT. Missoula, MT: University of 

Montana, School of Forestry: 42–64.

Welsh, S.L.; Atwood, N.D.; Goodrich, S.; Higgins, L.C., eds. 

2008. A Utah flora, fourth edition, revised. 2004-2008 summary 

monograph. Provo, UT: Brigham Young University. 1019 p.

West, N.E. 1983. Intermountain salt desert shrubland. In: West, 

N.E., ed. Temperate deserts and semi-deserts. Amsterdam: 

Elsevier Scientific Publishing Company.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types
USDA Forest Service RMRS-GTR-375. 2018 197

West, N.E. 1994. Effects of fire on salt-desert shrub rangelands. In: 

Monsen, S.B.; Kitchen, S.G., comps. Proceedings—Ecology 

and management of annual rangelands; 1992 May 18-22; 

Boise, ID. Gen. Tech. Rep. INT-GTR-313. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Research Station: 71–74.

West, N.E.; Tausch, R.J.; Rea, K.H.; Tueller, P.T. 1978. Taxonomic 

determination, distribution, and ecological indicator values of 

sagebrush within the pinyon-juniper woodlands of the Great 

Basin. Journal of Range Management. 31: 87–92.

West, N.E.; Yorks, T.P. 2002. Vegetation responses following 

wildfire on grazed and ungrazed sagebrush semi-desert. Journal 

of Range Management. 55: 171–181.

Williams, J.W.; Jackson, S.T. 2007. Novel climates, no-analog 

communities, and ecological surprises. Frontiers in Ecology 

and the Environment. 5: 475–482.

Winward, A.H. 1980. Taxonomy and ecology of sagebrush in 

Oregon. Station Bulletin 642. Corvallis, OR: Oregon State 

University, Agricultural Experiment Station. 15 p.

Winward, A.H. 2004. Sagebrush of Colorado: Taxonomy, 

distribution, ecology, and management. Denver, CO: Colorado 

Division of Wildlife, Department of Natural Resources. 46 p.

Winward, A.H.; Tisdale, E.W. 1977. Taxonomy of the Artemisia 

tridentata complex in Idaho. Bulletin Number 19. Moscow, ID: 

University of Idaho, College of Forestry, Wildlife and Range 

Sciences, Forest, Wildlife and Range Experiment Station. 15 p.

Wisniewski, J.; Dixon, R.K.; Kinsman, J.D.; [et al.]. 1993. Carbon 

dioxide sequestration in terrestrial ecosystems. Climate 

Research. 3: 1–5.

Yansa, C.H. 2006. The timing and nature of late Quaternary 

vegetation changes in the northern Great Plains, USA and 

Canada: A reassessment of spruce phase. Quaternary Science 

Reviews. 25: 263–281.

Young, R.P. 1983. Fire as a vegetation management tool in 

rangelands of the Intermountain region. In: Monsen, S.B., 

Shaw, N., comps. Managing Intermountain rangelands—

Improvement of range and wildlife habitats: Proceedings of 

symposia; 1981 September 15-17; Twin Falls, ID; 1982 June 

22-24; Elko, NV. Gen. Tech. Rep. INT-157. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station: 18–31.

Young, J.A.; Clements, C.D. 2003. Germination of seeds of 

Fremont cottonwood. Journal of Range Management. 56: 

660–664.

Youngblood, A.P. 1980. Vegetation analysis for the Cache Creek 

EIS. Report to the Bridger-Teton National Forest. 30 p.

Chapter 7: Effects of Climate Change on Nonforest Vegetation Types

In accordance with Federal civil rights law and U.S. Department of Agriculture (USDA) civil rights regulations and policies, the USDA, its Agencies, offices, and employees, and institutions participating in or 

administering USDA programs are prohibited from discriminating based on race, color, national origin, 

religion, sex, gender identity (including gender expression), sexual orientation, disability, age, marital status, family/parental status, income derived from a public assistance program, political beliefs, or reprisal 

or retaliation for prior civil rights activity, in any program or activity conducted or funded by USDA (not 

all bases apply to all programs). Remedies and complaint filing deadlines vary by program or incident.

Persons with disabilities who require alternative means of communication for program information (e.g., 

Braille, large print, audiotape, American Sign Language, etc.) should contact the responsible Agency or 

USDA’s TARGET Center at (202) 720-2600 (voice and TTY) or contact USDA through the Federal Relay 

Service at (800) 877-8339. Additionally, program information may be made available in languages other 

than English.

To file a program discrimination complaint, complete the USDA Program Discrimination Complaint 

Form, AD-3027, found online at How to File a Program Discrimination Complaint and at any USDA 

office or write a letter addressed to USDA and provide in the letter all of the information requested in 

the form. To request a copy of the complaint form, call (866) 632-9992. Submit your completed form or 

letter to USDA by: (1) mail: U.S. Department of Agriculture, Office of the Assistant Secretary for Civil 

Rights, 1400 Independence Avenue, SW, Washington, D.C. 20250-9410; (2) fax: (202) 690-7442; or (3) 

email: program.intake@usda.gov.

To learn more about RMRS publications or search our online titles:

RMRS web site at: https://www.fs.fed.us/rmrs/rmrs-publishing-services