United States Department of Agriculture

Forest Rocky Mountain General Technical Report August 2017

Service Research Station RMRS-GTR-366

Assessment of Aspen Ecosystem Vulnerability 

to Climate Change for the Uinta-WasatchCache and Ashley National Forests, Utah

Janine Rice, Tim Bardsley, Pete Gomben, 

Dustin Bambrough, Stacey Weems, Allen Huber, and Linda A. Joyce
Rice, Janine; Bardsley, Tim; Gomben, Pete; Bambrough, Dustin; Weems, Stacey; Huber, 

Allen; Joyce, Linda A. 2017. Assessment of aspen ecosystem vulnerability to 

climate change for the Uinta-Wasatch-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.

Abstract

Aspen ecosystems are valued because they add biodiversity and ecological value to 

the landscape. They provide rich and productive habitats and increase aesthetic value. 

Climate change poses the risk of altering and disrupting these ecosystems, and it may 

worsen the effects of non-climate stressors. To provide scientific information for land 

managers facing the challenge of helping aspen ecosystems adapt to climate change, 

we developed an aspen vulnerability assessment on the Uinta-Wasatch-Cache and 

Ashley National Forests. Literature-based information and expert elicitation are used to 

define (a) components of sensitivity and exposure to climate change and (b) the capacity of these ecosystems to adapt to expected changes. Aspen ecosystems benefit from 

fire and quickly reproduce. Yet, aspen trees are susceptible to drought and heat that is 

projected to become more frequent and intense in the future. Some aspen-associated 

plant and animal species may benefit from the expected changes in disturbance regimes and stand structure, while others may experience population reductions or stress 

as a result of drought and heat. Overall, vulnerability is defined as moderate because 

although persistence of aspen ecosystems is likely, a dynamic spatial and temporal 

response to climate change is expected.

Keywords: exposure, sensitivity, adaptive capacity, vulnerability assessment
Authors

Janine Rice is a Research Ecologist with Rice Consulting LLC Fort Collins, Colorado.

Tim Bardsley is a Senior Service Hydrologist with the National Weather Service in 

Reno, Nevada.

Pete Gomben is the Environmental Coordinator with the Uinta-Wasatch-Cache 

National Forest in South Jordan, Utah.

Dustin Bambrough is the Ecosystem Staff Officer with the Ashley National Forest in 

Vernal, Utah.

Stacey Weems is a Soil Scientist with the Uinta-Wasatch-Cache National Forest in 

South Jordan, Utah.

Allen Huber is an Ecologist with the Ashley National Forest in Vernal, Utah.

Linda A. Joyce is a Quantitative Research Ecologist at the Rocky Mountain Research 

Station in Fort Collins, Colorado.

Acknowledgments

We wish to thank the following reviewers: Paul Rogers, Karen Mock, Sam St. Clair, 

Dale Bartos, and Wayne Shepperd. This project was funded by the Uinta-WasatchCache and Ashley National Forests. We also wish to thank Western Water Assessment 

for participating in this project.

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.

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Contents

Aspen Vulnerability Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

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

Method of Vulnerability Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Aspen Distribution and Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Persistent Aspen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Seral Aspen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Riparian Aspen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Vulnerability Assessment Framework . . . . . . . . . . . . . . . . . . . . . . . . 4

Climate in the Uinta-Wasatch-Cache and Ashley National 

Forests, Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Observed Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Precipitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Snow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Projected Changes in Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Projected Trends for Snow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Extreme Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Vulnerability of Uinta-Wasatch-Cache and Ashley National 

Forests Aspen Ecosystems to Climate Change . . . . . . . . . . . . 18

Range Shift Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Southern Range Limit Proximity . . . . . . . . . . . . . . . . . . . . . . . . 18

Elevation Range Shift Capacity . . . . . . . . . . . . . . . . . . . . . . . . . 18

Vulnerability of Aspen-Associated, Cold-Adapted Foundation 

or Keystone Species to Climate Change . . . . . . . . . . . . . . . . . 26

Understory Vegetation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Birds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Limited Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Sensitivity to Extreme Climatic Events (Drought, Heat, Floods) . . . 32

Sensitivity to Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Sensitivity to Extreme Heat . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Sensitivity to Floods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Intrinsic Adaptive Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Factors That Strengthen Adaptive Capacity to 

Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Factors That Weaken Adaptive Capacity . . . . . . . . . . . . . . . . . . 37

Dependence on Specific Hydrologic Condition . . . . . . . . . . . . . . . . 37

Hydrologic Regime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Hydrologic Regime Changes and Effects on Aspen 

Ecosystems ...................................... 38
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Potential for Climate Change to Exacerbate the Effects of 

Non-Climate Stressors, or Vice Versa . . . . . . . . . . . . . . . . . . . 39

Climate Change and Herbivory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Climate Change, Fire, and Bark Beetle Outbreaks . . . . . . . . . . . . . 41

Fire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Conifer Bark Beetle Outbreaks in Seral Aspen . . . . . . . . . . . . . 43

Climate Change, Insects and Diseases, Sudden Aspen 

Mortality and Regeneration . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Likelihood of Managing or Alleviating Climate Change Effects . . . . 44

Climate Change Adaptation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Management Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Appendix A—Aspen Ecosystem Vulnerability Assessment . . . . . . . . 61

Vulnerability Assessment Development Process . . . . . . . . . . . . . . . 61

Summary of Uinta-Wasatch-Cache and Ashley National 

Forests Aspen Ecosystem Vulnerability . . . . . . . . . . . . . . . . . 61

Appendix B—Climate Model Projections . . . . . . . . . . . . . . . . . . . . . . . 62

Projections for Temperature and Precipitation (CMIP5) . . . . . . . . . . 62

Appendix C—Coupled Model Intercomparison Project Phase 5 . . . . 66
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Aspen Vulnerability Summary

Aspen ecosystems: Aspen are the most widely distributed tree in North America with high 

ecological and social value. They are associated with less water use than other ecosystems, 

good quality forage and habitats, and rich biodiversity of plants, birds, and wildlife. These 

ecosystems are highly productive and are rich in soil nutrients. Their high aesthetic value 

promotes economic benefits through tourism. Aspen are more common in the Wasatch 

Range and less so in the Uinta Mountains of northeastern Utah. These aspen stand types can 

be (a) seral, in the process of succession to conifers, (b) in riparian areas, or (c) persistent, 

dominated by aspen. Seral stands may give way to conifer succession over time in the absence 

of disturbance, while persistent stands remain dominated by aspen over long periods. Seed 

reproduction is not commonly observed, and most aspen regeneration appears to be from root 

suckering.

Aspen vulnerability to climate change: Moderate

Current conditions: Most of the aspen stands on the Wasatch Range occur between 6,000 

and 10,000 feet elevation, and in the Uinta Mountains, between 7,000 and 11,000 feet elevation. Fire suppression and stresses from drought, insects and diseases, and human land uses 

have contributed to the general decline in the amount of aspen cover. There are some small 

areas where aspen is expanding, however. Of the three aspen types (seral, persistent, or riparian), most aspen stands are mixed with conifers.

Exposure: More intense and frequent multi-year drought and extreme heat are expected 

to adversely affect aspen ecosystems, potentially causing mortality and/or hindering 

reproduction.

Sensitivity: Aspen trees at lower elevations and southerly aspects may be particularly vulnerable to more frequent and intense multi-year drought and heat. These conditions have recently 

been associated with rapid aspen decline in persistent and seral stands. The conditions can be 

compounded by insects, disease, and ungulate over-browsing.

Adaptive capacity: Ecosystem adaptive capacity to climate change may be raised by high 

biodiversity, which can expand the range of biotic responses to climate change. Seral stands 

have higher bird biodiversity than persistent stands. Aspen trees regenerate quickly and are 

benefitted by fire, which is likely to increase in frequency, size, and intensity in the future. 

Aspen trees can share root systems and can distribute water and nutrients to tree stems that 

may not have access to water. Leaf fluttering cools leaves and is an adaptive mechanism to 

heat. However, adaptive capacity is lowered by aspen’s inability to compete with conifers, 

high susceptibility to a number of insects and diseases, and inability to adapt to climate warming and drying that exceed tolerance levels.

Non-climate stressors: Fire, insects and diseases, ungulate grazing, and competition with conifers may interact with climate warming and drying, and in some cases, they may exacerbate 

the adverse effects of non-climate stressors on aspen ecosystems.
USDA Forest Service RMRS-GTR-366. 2017. 1

Introduction

Climate-driven changes associated with recent temperature warming have become 

increasingly apparent in western United States landscapes over the past decade. More 

frequent and severe fire and insect outbreaks, less snowpack at mid- and low-elevations, 

and shifts to earlier timing of snowmelt and runoff have been linked to recent warming 

(Bentz et al. 2009; Stewart 2009; Stewart et al. 2005; Westerling et al. 2014). Future 

warming is projected to add another 2 to 6 °F to average temperatures by mid-century 

(see table 2 in Climate section). This warming brings the potential of ecological impacts 

that will combine with existing stressors in complex ways.

Natural resource managers are developing strategies to increase ecosystem resilience 

and adaptation in the face of climate change, and vulnerability assessment is a critical 

part of this process. Vulnerability is defined as the propensity or predisposition to be 

adversely affected, encompassing elements of sensitivity or susceptibility to harm and 

lack of ability to cope or adapt (IPCC 2014). Vulnerability assessment considers exposure, sensitivity, and adaptive capacity. The character, magnitude, and rate of climate 

variation to which a system is exposed, system sensitivity to those changes, and system 

resilience and adaptive ability to cope with changes, are all factors that when combined, 

define vulnerability (Glick et al. 2011). The goal of a vulnerability assessment is to 

identify the components of ecosystems and associated services that may be at risk from 

a changing climate, why they are vulnerable, and how existing stressors may interact 

to exacerbate vulnerability. Knowledge gained serves as a platform for land managers 

to identify and prioritize strategies and activities that can help minimize the impacts of 

climate change (Glick et al. 2011) and capitalize on any benefits from climate change.

This report presents an assessment of the vulnerability of aspen ecosystems to 

climate change on the Uinta-Wasatch-Cache and Ashley National Forests (NFs). It is a 

collaborative effort between the Rocky Mountain Research Station and these National 

Forests. Current scientific information in the literature is synthesized, vulnerability 

is ranked using seven criteria, and scientific experts and National Forest managers 

are engaged to review the vulnerability rankings and supporting documentation (see 

Appendix A for a summary of methods and vulnerability results). This report provides 

current scientific information relevant to the vulnerability of aspen ecosystems and 

reveals gaps where information is limited or non-existent. The assessment is intended to 

form a foundation of scientific information that can be updated as more becomes available. It can also be used to inform discussions in developing climate adaptation options 

for aspen ecosystems and for forest planning and NEPA documents.
2 USDA Forest Service RMRS-GTR-366. 2017.

Method of Vulnerability Assessment

Aspen Distribution and Types

Aspen ecosystems exist in a wide variety of environmental conditions and have 

differing ecological patterns and dynamics in response to conditions. In this report, we 

divide aspen into functional types: persistent (sometimes referred to as stable), seral, 

and riparian. These three functional types are often integrated.

These three aspen types are found on the mountainous terrain of the Wasatch Range 

and Stansbury Mountains (collectively called the Wasatch Range from here forward) 

(fig. 1a) and in the east-west trending Uinta Mountains. Aspen coverage is present but 

less extensive in the Uinta Mountains (fig. 1b).

Figure 1—Aspen distribution in the Uinta-Wasatch-Cache and Ashley National Forests. Data from USDA 2013a. Note: Aspen types of seral, persistent, and riparian are not differentiated as this information is not available.
USDA Forest Service RMRS-GTR-366. 2017. 3

Persistent Aspen

Rogers et al. (2014) define persistent aspen types as remaining dominated by aspen 

over long time periods (>80 to 120 years), with little or no conifer invasion (fig. 2). 

Small-scale disturbances of individual or small groups of trees, termed “gap-phase” 

stand dynamics, characterize persistent aspen types that often have multiple age classes 

(Rogers et al. 2014). Stands are often of uneven age with basal area remaining relatively 

unchanged over time as small group or individual tree mortality events, such as insects, 

disease, or drought stress, allow canopy succession from smaller aspen trees (Mueggler 

1985b; Rogers et al. 2014). Persistent aspen types were further differentiated by Rogers 

et al. (2014) as (a) elevation or aspect limited types typically on south-facing or moderate slopes, (b) terrain isolated types typically in snow pockets, avalanche chutes, 

isolated rocky slopes, or moraines, and (c) Colorado Plateau types on flat or modest 

slopes.

Figure 2—Persistent aspen on the Tavaputs Plateau, Ashley National Forest. Photo by A. Huber.

Seral Aspen

Seral aspen types are presumed to be in a state of transition to shade-tolerant conifers, with typically even-aged aspen stands giving way to conifer dominance over 

a period of decades or a century in the absence of disturbance (Rogers et al. 2014) 

(fig. 3). In the southern and central Rocky Mountains, seral aspen types dominate across 

these landscapes (Rogers et al. 2002). The initial stage of these stands is characterized 

Figure 3—Seral Aspen in the Uinta Mountains, Ashley National Forest. Photo by A. Huber.
4 USDA Forest Service RMRS-GTR-366. 2017.

by a stand-replacing disturbance that initiates aspen regeneration. Aspen trees typically 

regenerate through root suckering, although seed reproduction can occur and may be 

more common than previously thought (Krasnow and Stephens 2015; Long and Mock 

2012; Rogers et al. 2014).

Riparian Aspen

These aspen types found near perennial or ephemeral streams or wetlands can be 

persistent or seral, but they are commonly seral. Riparian aspen are more resistant 

to wildfire than aspen found in other landscape types. They may have even greater 

biodiversity than other aspen types as a result of their proximity to water (Rogers et al. 

2014). Water-sharing aspen ramets (suckers sprouting from aspen roots) can spread into 

dry upland areas where conditions allow. Many wildlife species utilize these areas for 

water and protective cover, thereby adding biodiversity in these areas. Wild and domestic ungulates have a high utilization of these productive and nutrient rich sites (Rogers 

and Mittanck 2014).

Vulnerability Assessment Framework

We take a holistic approach to assessing the climate change vulnerability of aspen 

ecosystems in the Uinta-Wasatch-Cache and Ashley NFs. This vulnerability assessment uses current scientific literature and expert elicitation to provide evidence for 

vulnerability rankings of aspen ecosystems. The vulnerability approach is based 

on the Northeastern Association of Fish and Wildlife Agencies (NEAFWA) model 

(Manomet 2012). This model has been applied in Massachusetts (Manomet 2010), 

14 northeastern States (Manomet 2012), the Badlands National Park in South Dakota 

(Amberg et al. 2012), and the Gunnison Basin in Colorado (Neely et al. 2012). In this 

application, we have modified the original NEAFWA model such that 7 criteria are 

used to assess aspen vulnerability to climate change and current stressors for the mid21st century (table 1). This assessment synthesizes currently available information on 

how climate change may affect ecosystem function, disturbance regimes, and plant and 

animal species. Human influences that affect aspen ecosystems, which may interact 

with climate change, are also considered along with management activities that may 

alleviate stressors and climate change effects.

This approach allows for an efficient means to assess vulnerability of aspen ecosystems. Scientific studies conducted in these NFs are incorporated when available. 

When such local information is unavailable, we draw on studies that have been 

conducted in the Rocky Mountains, the western United States, or other areas with similar ecological characteristics. Vulnerability conclusions are contingent on the available 

information and we reveal where knowledge gaps exist. National Forest land manager 

input was used to organize information in a manner relevant to management activities. 

Expert elicitation from university experts, Forest Service researchers, and National 

Forest staff helps ensure that the scientific literature used to assess vulnerability is 

accurate and complete. These experts also provide input on vulnerability rankings.
USDA Forest Service RMRS-GTR-366. 2017. 5

1. Range shift capacity

Southern range limit proximity

•	 Ecosystems that are less than 125 miles north of their southern range limit have a higher vulnerability as unsuitable climates shifting northward are likely to adversely affect the ecosystem and cause a range contraction.

•	 Ecosystems that are more than 125 miles north of their southern range limit have a Low vulnerability as 

unsuitable climates may not shift far enough northward to adversely affect the ecosystem and cause a 

range contraction.

Upslope migration potential 

Note: The elevation range shift potential of plants are likely to have a complex response to temperature 

warming with environmental factors as well as climate causing irregular range shifts. This criterion accounts 

for whether upslope area exists to make range shifts possible under climate change, and other potential 

restrictions to these shifts such as, suitable soils, ungulate browsing, disturbance, or microsite conditions may 

inhibit upslope migration.

•	 Biota living at high elevations (for example the alpine life zone or near peak tops) are likely to have a Very High 

vulnerability to climate change since upslope migration is simply not a possibility. 

•	 Middle elevation biota have a High, Moderate, or Low vulnerability as some degree of upslope area may exist 

for biota to migrate and extend their range upslope. This assumes environmental conditions and a means to 

migrate allow for an upslope expansion. 

•	 Low elevation biota have a Very Low vulnerability as they have the most available land area existing upslope, 

and the highest potential to extend their range upslope. This assumes environmental conditions and a means 

to migrate allow for an upslope range expansion. 

2. Vulnerability of cold-adapted, foundation, or keystone species occupying aspen ecosystems to climate 

change

•	 Cold-adapted species are those that have adaptive mechanisms to tolerate cold environments, and are sensitive to warm temperatures. These species are differentiated from warm-adapted species that tolerate warm to 

hot temperatures.

•	 Foundation species are those that have substantial influences on ecosystem structure and function as a consequence of their high biomass. 

•	 Keystone species are those that exert strong effects on the structure and function of their ecosystem, despite 

having a low biomass. 

Vulnerability is assigned based on the degree of species sensitivity to exposure of a warmer and drier climate and 

its ability to adapt and persist. 

•	 A Very High vulnerability is assigned if species have a high risk of being eliminated from aspen ecosystems.

•	 A High, Moderate, to Low vulnerability is assigned if species are likely to be hampered to a high, moderate or low degree, but not eliminated.

•	 Very Low vulnerability is assigned if species are not hampered, and have a high likelihood of persisting 

or expanding.

3. Sensitivity to extreme climatic events (drought, heat, flood)

Sensitivity is the degree to which aspen ecosystems serve as species habitats are affected by changes in 

climate such as droughts, floods, and extreme heat.

•	 Very High sensitivity is assigned when higher frequencies or severities of extreme events raises the risk to 

greatly disrupt aspen ecosystems.

•	 A High, Moderate, or Low sensitivity is assigned when higher frequencies or severities of extreme events 

raise the risk to disrupt aspen ecosystems to a high, moderate, or low degree.

•	 Very Low sensitivity is assigned when increased frequency or severity of extreme events is unlikely to significantly affect aspen ecosystems.

Table 1—Criteria and associated rationale used to establish the vulnerability to climate change for aspen ecosystem 

processes and biota. For each criterion, vulnerability can be assigned a score of either Very Low, Low, Moderate, 

High or Very High vulnerability.

(continued)
6 USDA Forest Service RMRS-GTR-366. 2017.

4. Intrinsic adaptive capacity to climate change

Intrinsic adaptive capacity is the inherent ability of ecosystems to accommodate or cope with the effects of climate 

change.

•	 Very High vulnerability is assigned when adaptive mechanisms, such as slow recovery periods, low biodiversity, species ability to mitigate or adapt to climate changes are low, thus contributing to a low adaptive capacity.

•	 A High, Moderate, or Low vulnerability is assigned when recovery periods, biodiversity, species ability to mitigate and adapt to climate changes are high, moderate, or low.

•	 Very Low vulnerability is assigned when there are short recovery periods, high biodiversity, and a high ability 

of species to mitigate and adapt to climate change.

5. Dependence on a specific hydrologic regime

The hydrologic regime is the characteristic pattern of water flowing through an ecosystem, and is dependent 

on climate to determine the rate, timing, and volume in groundwater and surface water moving through the 

ecosystem. 

•	 Very High vulnerability is assigned when ecosystems function within a relatively narrow hydrologic regime. For 

example, snow-driven aquatic ecosystems, with hydrologic processes and cold-adapted biotas like fish that 

are highly dependent on stream flow from snowmelt have a high vulnerability. 

•	 High, Moderate, or Low vulnerability is assigned when ecosystems are less dependent on a narrowly functioning hydrologic regime. Biota can withstand some variability. For example, vegetation depends on moisture 

during the growing season but is not dependent on a specific form and can withstand annual variation or 

periods of drought.

•	 Very Low vulnerability is assigned when ecosystems are not dependent on a narrowly functioning hydrologic 

regime. Biota are not dependent on a specific form or timing of moisture. An example would be an ecosystem 

that can withstand periods of little to no moisture along with periods of elevated moisture.

6. Potential for climate change to exacerbate effects of non-climate stressors, or vice versa

Climate change effects of warming and drying can exacerbate or worsen non-climate stressors. For example, 

human water withdrawal (a potential stressor) lowers water levels in streams and lakes, and climate warming can 

increase evaporation, further lowering water levels.

•	 Very High vulnerability is assigned when there is a high probability that climate change may worsen the effects of a non-climate stressor, or that the non-climate stressor may worsen the effects of climate change.

•	 High, Moderate, or Low vulnerability is assigned when there is some probability that climate change may 

worsen the effects of a non-climate stressor, or that the non-climate stressor may worsen the effects of climate change.

•	 Very Low vulnerability is assigned when there is a very low probability that climate change may worsen the 

effects of a non-climate stressor, or that the non-climate stressor may worsen the effects of climate change.

7. Likelihood of managing or alleviating climate change effects

•	 Ecosystems have Very High vulnerability when there are no known feasible management approaches that 

could be employed, or the likelihood of effectiveness is very low to mitigate the effects of climate change and 

reduce non-climate stressors. 

•	 Ecosystems have a High, Moderate, or Low vulnerability when feasible management approaches exist, (for 

example, controlled burning or coppicing to promote suckering, fencing to reduce browsing pressure on suckers), and have been shown to have a high, moderate, or low effectiveness in mitigating the effects of climate 

change and reducing non-climate stressors.

•	 Ecosystems have a Very Low vulnerability when feasible management approaches exist, (for example, 

controlled burning or coppicing to promote suckering, fencing to reduce browsing pressure), and have been 

shown to be very effective in mitigating the effects of climate change and reducing non-climate stressors.

Table 1—(Continued).
USDA Forest Service RMRS-GTR-366. 2017. 7

The assessment is intended to provide an initial literature-based synthesis on vulnerability and to provide a basic framework of information that can be updated as more 

becomes available. The vulnerability assessment is intended to assist in the development of climate adaptation options for aspen ecosystems and to provide reference 

information for forest planning and NEPA documents.

Seven criteria define different factors of vulnerability to climate change and nonclimate stressors. Vulnerability is scored Very Low, Low, Moderate, High, or Very 

High for each of the seven criteria. When several vulnerability indicators are included 

in one criterion, the score is evenly weighted, and individual sections describe the 

different characteristics of those vulnerability criteria. The final vulnerability ranking 

is determined by averaging the 7 criteria scores into a final score ranging from 1 to 5 

(Very Low=1, Low=2, Moderate=3, High=4 and Very High=5) (table A1).
8 USDA Forest Service RMRS-GTR-366. 2017.

Climate in the Uinta-Wasatch-Cache and Ashley National 

Forests, Utah

Observed Climate

The Uinta-Wasatch-Cache and Ashley NFs encompass some of the wettest and coolest terrain in the State of Utah (fig. 4). That, combined with high elevation and cooler 

temperatures, has historically permitted large snowpacks to accumulate in winter and 

melt in the spring and summer, acting as Utah’s largest reservoir, or storage mechanism 

for water. This snowmelt is a major water source for aspen ecosystems.

Figure 4—Annual Mean Temperature (°F) (left) and Total Annual Precipitation (inches) (right) for 1981–2010 over the State of Utah based on 

observed climate and spatially interpolated using the Parameter-elevation Relationships on Independent Slopes (PRISM) model. The resolution 

is at 800 meters (http://prism.oregonstate.edu). Hillshade data credit: Esri, USGS, NGA, NASA, CGIAR, N Robinson, NCEAS, NLS, OS, NMA, 

Geodatastyrelsen, Rijkswaterstaat, GSA, Geoland, FEMA, Intermap, and the GIS user community.)

Temperature

The State of Utah’s Climate Division 5 (fig. 5), encompasses most of the UintaWasatch-Cache and Ashley NFs as well as adjacent lands outside of the forest boundary 

in northeastern Utah. We use the Climate Division 5 boundary to present the historical climate (temperature, precipitation) and climate projections for the mid-century. 

Temperatures have increased in Climate Division 5 as well as throughout Utah and the 

western United States over the past century and most rapidly since 1970.
USDA Forest Service RMRS-GTR-366. 2017. 9

The average annual temperature in Climate Division 5 has risen over the last century 

with a statistically significant trend of 0.2 °F per decade since 1900, and 0.5 °F per 

decade since 1970 (Mann-Kendal p value <0.01) (fig. 6).

Precipitation

The precipitation record in Utah and Climate Division 5 is dominated by large interannual and decadal variability. No long-term trends have yet been observed in seasonal 

or annual precipitation in northern Utah (fig. 7).

Snow

Studies of the western United States have indicated a tendency towards decreasing 

snow water equivalent (SWE) and earlier snowmelt peak and runoff, most notably in 

coastal and lower elevation areas (Mote 2006; Mote et al. 2005; Regonda et al. 2005). 

Figure 5—Utah’s Climate Division 5 overlaid on the Uinta-Wasatch-Cache and Ashley National 

Forest Boundaries (http://www.ncdc.noaa.gov/monitoring-references/maps/us-climate-divisions.

php). Climate Division 5 encompasses the majority of the Uinta-Wasatch-Cache and Ashley 

NFs. Hillshade data credit: Esri, USGS, NGA, NASA, CGIAR, N Robinson, NCEAS, NLS, OS, 

NMA, Geodatastyrelsen, Rijkswaterstaat, GSA, Geoland, FEMA, Intermap and the GIS user 

community.)
10 USDA Forest Service RMRS-GTR-366. 2017.

Figure 6—Utah Climate Division 5 temperature anomaly of the mean annual temperature (°F), 

1900–2014. Annual departures are relative to the 1901–2000 average. The dashed black line 

and orange lines are the 1900–2014 and 1970–2014 linear trends, respectively. Both upward 

trends are statistically significant. The average annual temperature in Climate Division 5 has risen over the last century with a statistically significant trend of 0.2°F per decade since 1900, and 

0.5°F per decade since 1970 (Mann-Kendal p value <0.01). The gray line is the 10-year running 

average. For Utah, Climate Division 5 encompasses the majority of the Uinta-Wasatch-Cache 

and Ashley National Forests (Source: NOAA-NCDC, http://www.ncdc.noaa.gov/cag/).

Figure 7—Utah Climate Division 5 average annual precipitation (inches), 1900–2014. The dashed 

red line is the 1901–2000 average, and the green line is the 1900–2014 linear trend, both of which 

shows no trend (source: NOAA-NCDC, http://www.ncdc.noaa.gov/cag/).
USDA Forest Service RMRS-GTR-366. 2017. 11

Warming temperatures have led to more winter precipitation falling as rain instead of 

snow in Utah. Gillies et al. (2012) documented a 9 percent decrease in the proportion 

of winter precipitation (January–March) falling as snow from 1950 to 2010 in Utah, a 

combined result from a significant increase in rainfall and a minor decrease in snowfall. 

They also reported that a decrease in snow depth across Utah, accompanied by consistent decreases in snow cover and decreases in surface albedo. Julander and Clayton 

(2014) identify 19 ongoing reference snow course sites across Utah that they deemed 

appropriate for long-term SWE studies because they are not compromised by site 

characteristics, most notably vegetation encroachment. None of these snow courses show 

significant increasing trends in April 1 SWE. Only 16 percent (3 of the 19) reference sites in 

southcentral and southeastern Utah show statistically significant downward trends in April 1 

SWE over their respective periods of record varying from 60 to 85 years.

Projected Changes in Climate

Global Climate Models (GCMs) are quantitative tools used to explore the range of possible future climate conditions. Global climate models simulate the complex interactions 

among the land, oceans, and atmosphere and are based on fundamental scientific principals 

using advanced mathematics in computationally intensive simulations. These climate model 

outputs have a range of projections from different trajectories of future greenhouse gas 

concentrations. Representative Concentration Pathways (RCPs) are 4 greenhouse gas 

(GHG) concentration trajectories over the 21st century that are used by climate models in the 

5th assessment report of the Intergovernmental Panel on Climate Change (IPCC 2014).

The four pathways are RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5. The first pathway 

has the lowest forcing (radiative forcing is a cumulative measure of human emissions 

of greenhouse gases) of RCP 2.6, and assumes that global annual GHG emissions peak 

between 2010–2020 and then decline. Greenhouse gas emissions in RCP 4.5 peak 

around the year 2040 and then decline. In RCP 6, GHG emissions peak around 2080 

and then decline. The largest forcing occurs with RCP 8.5, where emissions continue to 

rise throughout the 21st century.

The Coupled Model Intercomparison Project phase 5 (CMIP5) uses the four 

standardized greenhouse gas concentration scenarios or RCPs. This project was established by the Working Group on Coupled Modeling (WGCM) to provide a standard 

experimental protocol for studying the output of coupled atmosphere-ocean general 

circulation models (AOGMCs). This project supports diagnosis, validation, intercomparison, documentation, and data access for the more than 20 international climate 

modeling groups.

The worldwide climate modeling centers comprise a total of 62 GCM models, 

sometimes having multiple runs of the same model (see Appendix C for list of models). 

While each center uses the same fundamental physical principles to drive their models, 

some climate processes are represented differently in each model. Future simulations 

of temperature, and especially precipitations, vary among different models attributed to 

different modeling methods and ways of incorporating climate processes in them.
12 USDA Forest Service RMRS-GTR-366. 2017.

Although GCMs have advanced significantly in the past several decades to include 

additional processes and higher spatial resolution, even the highest resolution existing 

GCMs are not able to adequately represent the steep mountainous terrain of the Uinta 

Mountains and Wasatch Range. A variety of downscaling methods have been developed 

to translate GCM output to scales capturing the terrain variability relevant to resource 

managers. In this study, we utilized the Bias-Correction Spatial Disaggregation (BCSD) 

method (http://gdo-dcp.ucllnl.org) to represent the mountainous terrain of the Uinta 

Mountains and Wasatch Range.

Downscaled temperature and precipitation climate projections in Utah’s Climate 

Division 5 for the middle-low forcing climate scenario RCP 4.5 show an average of 

3.7 °F increase in annual temperature, and on average, a small annual precipitation 

increase by mid-century compared to a 1981–2010 baseline (table 2, figs. 8 and 9) 

(downscaling technique by Maurer et al. [2007]). Nighttime low temperatures are 

expected to rise as much as daytime high temperatures. Projections indicate that 

summer temperatures may warm somewhat more than winter and spring (fig. 8).

While there is a high degree of confidence that temperatures in all seasons will continue to increase, there is less confidence with projected changes in precipitation. The 

RCP 4.5 projections on average indicate about a 4 percent increase in annual precipitation, but about one-third of the 71 model runs indicate decreases in future mean annual 

precipitation. There is higher model run agreement that winters will be wetter, with 

75 percent of model runs indicating an increase in average winter precipitation.

In fig. 10, the 10th percentile (+2.2 °F) and 90th percentile (+5.8 °F) of the projected 

temperature increases were uniformly added to the PRISM 1981–2010 observed mean 

temperatures. Under the 90th percentile warming, annual mean temperatures at upper 

elevations in the Uinta Mountains (+5.8 °F) are raised to just below or above freezing 

levels, while the majority of upper elevation areas in the Wasatch Range are raised 

above freezing.

Table 2—Projected changes in mean annual temperature and precipitation from 1981–2010 to 

2035–2064 for northeastern Utah Climate Division 5 under RCP 4.5.

Projected changes by 2035–2064a Mean 10thb 50thc 90thd

Change in mean annual temperature (°F) 3.7 2.2 3.7 4.9

Change in mean annual precipitation (%) 4.2 -5.8 3.2 15.1

a

 Projections are based on 71 model runs from 1/8° CMIP5 BCSD (bias-correction and spatial 

disaggregation) for the Representative Concentration Pathway (RCP) 4.5. Accessed from: 

http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/dcpInterface.html

b The 10th percentile value has 10 percent of model outputs that are less than or equal to the 

value, while 90 percent are above the value.

c

 The 50th percentile value has 50 percent of the model outputs less than or equal to the value, 

while 50 percent is above the value.

d The 90th percentile value has 90 percent of the model outputs less than or equal to the value, 

while 10 percent is above the value.
USDA Forest Service RMRS-GTR-366. 2017. 13

Figure 8—Annual and seasonal projected change in temperature for Climate Division 5 2035–2064 relative 

to 1981–2010 for 71 model runs from the RCP 4.5 of the Climate Model Intercomparison Project phase 5 

(CMIP5). Dots represent the average change, while the whiskers represent the 10th and 90th percentiles, 

and the boxes represent the 25th and 75th percentiles of the 71 model runs. See Appendix A for projections 

of RCP 2.6, RCP 6.0, and RCP 8.5 (Reclamation 2014).

Figure 9—Annual and seasonal projected change in precipitation for 2035–2064 relative to 1981–2010 from 

71 model runs from the RCP 4.5 of the Climate Model Intercomparison Project phase 5 (CMIP5 Appendix D). 

Dots represent the average change, while the whiskers represent the 10th and 90th percentiles, and the boxes 

represent the 25th and 75th percentiles of all model runs. See Appendix B for projections of RCP 2.6, RCP 6.0, 

and RCP 8.5 (Reclamation 2014).
14 USDA Forest Service RMRS-GTR-366. 2017. Figure 10—Mean 1981–2010 PRISM temperatures (left), mean 1981–2010 temperature plus 2.2°F, the 10th percentile of projections for 2035–2065 (center), and mean 1981–2010 temperature plus 4.9°F, the 90th percentile of projections for 2035–2065 (right). 
USDA Forest Service RMRS-GTR-366. 2017. 15

Projected Trends for Snow

As temperatures rise, more rainfall and less snow is expected in the Uinta Mountains 

and Wasatch Range (fig. 11). Klos et al. (2014) projected that by mid-century, a large 

portion of the Wasatch Range will receive more than 50 percent of December to 

February precipitation in the form of rain. Most of the Uinta Mountains have more than 

90 percent of precipitation falling as snow in both the historic and mid-century 2035 

to 2065 time periods. The decrease in the amount of moisture received as snow would 

result in less snowpack and drier soil moisture during the growing season.

Warmer temperatures, in the absence of changes in precipitation, are expected to 

lead to earlier runoff, and average annual runoff volume will decrease due to increases 

in evapotranspiration. A recent study in the Wasatch and western Uinta Mountains has 

modeled a shift in timing of the center of runoff, the date when half of the water year 

runoff has occurred, by approximately 3 days earlier per 1 °F warming. In the same 

Figure 11—The percent of total precipitation received as snow mean of the months of December, January and February. Modeled for historic (1979–

2012) (left), and mid-century (2035 to 2065) (right) using the high emissions scenario (RCP8.5) and averaged over 21 CMIP5 climate models (Klos and 

others 2014). (Note: Areas in light grey to white in southwestern Wyoming are where precipitation was excluded from model runs since the amounts were 

below a minimum threshold.) Hillshade background from: Esri. Their sources are: UGSG, NGA NASA, CGIAR, N Robinson, NCEAS, NLS, OS, NMA, 

Geodatastyrelsen, Rijkswaterstaat GSA, Geoland, FEMA, Intermap, and the GIS User Community. Downloaded from: http://www.arcgis.com/home/item.

html?id=9c5370d0b54f4de1b48a3792d7377ff2. 
16 USDA Forest Service RMRS-GTR-366. 2017.

study, the average modeled decrease in annual volume was approximately 4 percent 

per 1 °F (Bardsley et al. 2013). Changes in runoff timing are expected regardless of 

potential changes in future precipitation and have implications to ecosystems and water 

management, while changes in annual volume caused by increasing temperatures could 

be offset by increasing precipitation.

Extreme Events

Relatively infrequent extreme events often exert a disproportionate impact on 

species and ecosystems. Recent droughts during the 1930s, 1950s, late 1970s, late 

1980s, and 2000s have been much less severe or persistent than many droughts in 

previous centuries. Prolonged drought periods lasting several decades, also called mega 

droughts, have been recorded from tree rings during the 1200s, late 1400s, and 1800s 

(Bekker et al. 2014; DeRose et al. 2015; MacDonald and Tingstad 2007). MacDonald 

and Tingstad (2007) reported 19 episodes of single-year or multi-year extreme droughts 

over the last 500 years.

Severe and extreme intensity droughts were recurrent events in the Uinta Mountain 

region, averaging 2 to 5 times per century since the 1400s (MacDonald and Tingstad 

2007). Bekker et al. (2014) found that most Wasatch Range droughts were during 

the 1400s and 1500s and the 1700s. The 1800s had fewer but the longest duration 

droughts. Three droughts have been recorded during the 1930s, the late 1950s, and the 

early 2000s. In both the Uinta Mountains and Wasatch Range, the 1900s was a relatively wet period compared to previous centuries, with the least recurrence of drought 

(Bekker et al. 2014; MacDonald and Tingstad 2007).

The recent drought events in the Wasatch Range and Uinta Mountains have been 

correlated with periods of decreased eastern Pacific sea surface temperatures (Kunkel 

et al. 2013; MacDonald and Tingstad 2007). Recent drought as measured by the Palmer 

Drought Severity Index has increased in Utah’s Climate Division 5 since 1970, due 

mostly to increasing temperatures driving more rapid drying.

There is high climate model agreement that more extreme heat will occur by the 

mid-21st century. Kunkel et al. (2013) projections show an increase of 5 to 10 days 

per year where temperatures exceed 95 °F in northern Utah. The largest number of 

projected extreme heat days is in lower elevations around the Uinta Mountains and 

Wasatch Range (see figure 23 in Kunkel et al. 2013). Multiple-day periods of extreme 

high temperatures are expected to increase as the climate warms (Lukas et al. 2014). 

Extreme heat events have been increasing over the past 30 years, but the number of 

events occurring from 2003 to 2012 did not exceed the amount experienced during the 

1930s (Lukas et al. 2014).
USDA Forest Service RMRS-GTR-366. 2017. 17

Fewer storm events with more precipitation per event have been happening in Utah 

since the mid-20th century (Gillies et al. 2012). Bekker et al. (2014) found that extremely wet periods, or pluvials, during the 17th century were wetter than the early 1900s 

pluvial, but was dwarfed in comparison to the 1980s flood event in the Wasatch Front. 

A climate reconstruction for the Bear River in the Wasatch Range based on tree ring 

records by DeRose et al. (2015) found that the latter half of the 20th century was the 

second wettest in 1,200 years. High flows in the Uinta Mountains were also recorded 

from the late 16th to mid-17th centuries and the first half of the 20th century (Carson and 

Munroe 2005). Extreme peak flow events have been increasing in the Uinta Mountains 

since the 1960s as a result of high precipitation and cold winter and early spring temperatures that preserve snowpack (Carson 2007). Kunkel et al. (2013) report no observed 

increase in days with precipitation exceeding 1 inch from 1980 to 2000 on the southwestern United States, but projections show the number of days with more than 1 inch 

of precipitation to increase by the end of the 21st century for northern Utah. Extreme 

precipitation events and extreme heat are projected to increase for the region by the end 

of the 21st century across the United States, while consecutive dry days are projected to 

also increase (Kunkel et al. 2013; Wuebbles et al. 2014). These projections would tend 

to lead to enhanced risk of both flood and drought in a warmer future climate.
18 USDA Forest Service RMRS-GTR-366. 2017.

Vulnerability of Uinta-Wasatch-Cache and Ashley National 

Forests Aspen Ecosystems to Climate Change

Range Shift Capacity

Summary: A moderate vulnerability is assigned as aspen have some capacity for range 

shifts, specifically:

•  Aspen is likely to remain several hundred miles north of its southern range limit, which 

currently extends through Arizona and Mexico. Low vulnerability is assigned.

•  Upslope migration is limited, especially in the Wasatch Range. Migration may have 

variable success as conifer competition, suitable soils, and microsite conditions are 

needed to support the biota. High vulnerability is assigned.

Information confidence:

•  The potential for aspen to remain well north of its southern range limit is supported by 

three studies, two of which are bioclimatic modeling studies.

•  The potential for aspen to shift ranges, given favorable conditions, is supported by 

22 studies.

Southern Range Limit Proximity

Aspen is the most widely distributed native tree species in North America. Aspen 

covers mountainous landscapes from Alaska, extending south through Arizona; a few 

pockets grow at its southern range limit in central Mexico (Little 1971). Aspen extends 

from the Pacific Northwest and California, throughout the Rocky Mountains to the 

upper Midwest and northeastern United States into Canada (Little 1971). Aspen on the 

Uinta Mountains and Wasatch Range is several hundred miles north of the southern 

range limit. Under a changing climate, suitable habitat for aspen is projected to remain 

extended south through Arizona during the mid-21st century (Gray and Hamann 2013; 

Rehfeldt et al. 2006), although fewer models project aspen presence in Arizona for the 

2071 to 2100 time period (Gray and Hamann 2013). Aspen is projected to remain present in the Uinta Mountains and Wasatch Range through the mid-21st century, and it is 

likely to remain at least 125 miles north of the southern range limit, so vulnerability of 

this criterion is low.

Elevation Range Shift Capacity

Aspen stands in the Uinta Mountains and Wasatch Range cover the montane and 

subalpine life zones. The montane life zone extends from about 8,000 to 10,000 feet 

elevation. The subalpine life zone extends from about 10,000 feet elevation to tree line, 

which is about 11,500 feet in the Wasatch and Uinta Mountain Ranges. In the Wasatch 

Range, aspen spans elevations from about 4,300 to 11,500 feet, with very few aspen 

stands occurring below 6,000 feet or above 10,000 feet (fig. 12). In the Uinta Mountains, 

aspen stands span elevations from 5,800 to 12,400 feet, with very few below 7,000 feet 

or above 11,000 feet (fig. 13). The potential upslope expansion of aspen ecosystems in the 

subalpine zone is limited in areas where aspen stands are found close to peak tops. 
USDA Forest Service RMRS-GTR-366. 2017. 19

Figure 12—Wasatch Range aspen elevation distribution (purple), and total Wasatch Range land area 

elevation distribution (blue). The number of approximately 100 ft2 or 30 m2 grid cells were calculated from 

the LANDFIRE data set that were classified aspen or aspen conifer mixed forests (USDA 2013a), and the 

elevation distributions were calculated from a Digital Elevation Model (USGS 2014).

Figure 13—Uinta Mountains aspen elevation distribution (purple), and total Uinta Mountains land area 

elevation distribution (blue). The number of approximately 100 ft2

 or 30 m2 grid cells were calculated from 

the LANDFIRE data set that were classified aspen or aspen conifer mixed forests (USDA 2013a), and the 

elevation distributions were calculated from a Digital Elevation Model (USGS 2014).
20 USDA Forest Service RMRS-GTR-366. 2017.

The Wasatch Range has peak elevations extending to about 11,000 feet, offering limited upslope area for aspen tree migration. The extent of potential habitat that would 

support aspen is projected to shrink as a result of climate change, especially in the Wasatch 

Range, and less land area is available at higher elevations for aspen to exist (fig. 12). The 

Uinta Mountains have area above 11,500 feet extending to about 13,000 feet elevation, 

which could offer some potential area for upslope expansion, assuming environmental conditions such as soils are suitable to support aspen.

In seral aspen types, aspen range movement can be inhibited by the presence or 

encroachment of conifers. Seral or mixed aspen-conifer stands are often successional 

to conifers; aspen are outcompeted and eventually replaced by more shade-tolerant 

conifers (Calder et al. 2011; Calder and St. Clair 2012; Shepperd et al. 2001). Without 

disturbances such as fire, conifer insect pathogens, or disease, the conifers frequently 

replace aspen (Shinneman et al. 2013), resulting in a local contraction of aspen 

coverage. Conversely, aspen may expand following fires, which may promote aspen 

dominance in the local landscape (Kulakowski et al. 2013b) if climate and herbivory 

rates are suitable for aspen persistence.

The persistent aspen type can exist in pure stands with dense patches of varying size 

within a matrix of other vegetation types (Cottam 1954; Shinneman et al. 2013). These 

isolated pure stands can be relatively stable over time because these aspen stands appear 

unaffected by fire and conifer succession (Smith and Smith 2005). Such aspen types 

may not contract if microclimate conditions are stable, but they also may not expand 

into the surrounding vegetation matrix, as they are not shade tolerant.

Bioclimatic models project that aspen climate profiles, or climates that would support aspen, will contract from lower elevations and expand upslope (Rehfeldt et al. 

2006, 2009, 2015) (fig. 14). The aspen bioclimate projections use climate variables, 

including mean annual temperature and precipitation, warmest and coldest month mean 

temperature, seasonal precipitation, growing degree days, frost free period, dryness indexes, and first and last freezing dates. Current aspen distribution modeled by Rehfeldt 

et al. (2009) were in close agreement with aspen distribution defined by Little’s (1971) 

range map.

Bioclimatic models provide a means to spatially define areas that are likely to have 

a climate that supports or does not support a particular tree species, such as aspen. A 

caveat on bioclimatic model projections is that the potential for aspen trees to shift 

ranges is dependent on other environmental conditions as well. For example, suitable 

soil conditions, topography, and disturbance, as well as the absence of vegetation 

competition, and the ability or inability of aspen to migrate by natural seeding or 

suckering, are factors that need consideration as well. These different factors, as 

well as climate, contribute to govern the establishment and mortality of aspen 

(Kulakowski et al. 2013a). Aspen extent expansions as well as contractions have 

been documented in many areas of the western United States since Euro-American 

settlement (Kashian et al. 2007; Kulakowski et al. 2013a, 2006; Zier and Baker 2006). 
USDA Forest Service RMRS-GTR-366. 2017. 21 Figure 14—Climate profile projections of aspen for current (mean of years 1961–1990), in blue, and 2060 (mean of years 2056–2065), overlain in pink. This shows the potential footprint of how climate that is suitable for aspen might shrink with climate change. Model scores using three climate model A2 scenarios from GFDL (left), CGCM3 (middle), and Hadley (right), in which a ≥50% model voting average is represented as a potential climate profile for aspen across the area. These scores do not necessarily project aspen presence in the future, but potential areas with climate conditions that could support aspen. Some high elevation areas of the Uinta Mountains do not have current aspen climate profile with scores above 50%, these are not shown in entirety as the 2060 climate profile projections overlay these areas. GFDL 2060 represents bioclimate model outputs for aspen climate profile using the Geophysical Fluid Dynamics Laboratory climate. CGCM3 2060 represents bioclimate model outputs for aspen climate profile using the Coupled Global Climate Model 3. Hadley 2060 represents bioclimate model outputs for aspen climate profile us- ing the Hadley climate model data. (Climate profile scores downloaded from: http://forest.moscowfsl.wsu.edu/climate/ and modeled by Rehfeldt et al. (2006, 2009). Hillshade background from: Esri. Their sources are: UGSG, NGA NASA, CGIAR, N Robinson, NCEAS, NLS, OS, NMA, Geodatastyrelsen, Rijkswaterstaat GSA, Geoland, FEMA, Intermap, and the GIS User Community. Downloaded from: http://www.arcgis.com/home/item.html?id=9c5370d0b54f4de1b48a3792d7377ff2.)
22 USDA Forest Service RMRS-GTR-366. 2017.

Aspen establishment or range expansion can be enhanced when disturbance 

removes conifer competition (Kulakowski et al. 2013a; Landhausser et al. 2010), 

or when aspen suckers or seedlings are protected from herbivory (Kay and Bartos 

2000). Additionally, aspen types may also react differently to climate change and 

disturbance, and the different responses need to be considered in addition to bioclimatic model projections and other environmental factors.

Aspen grow on a variety of soil types. Aspen does well on soils rich in organic matter and minerals of the Mollisol soil order (Cryer and Murray 1992), soils derived from 

basic igneous rock like basalt, and soils derived from neutral or calcareous shales or 

limestones (Howard 1996). However, aspen can also exist on lithic, poorly developed 

soils (which contain large amounts of debris from previously formed rocks) that have 

lower productivity (Shepperd, U.S. Forest Service, Colorado State University, personal 

communication 2015). The National Forest lands in the Wasatch Range have aspen on 

soils derived from 24 different rock types (table 3 and fig. 15). The National Forest 

lands in the Uinta Mountains have aspen on soils derived from 14 different rock types 

(table 3 and fig. 16). The rock types underlying aspen with the most area are conglomerate and sandstone in the Wasatch Range, and sandstone and arenite in the Uinta 

Mountains (table 3).

Aspen range movement can be hindered by browsing, competition with conifers, 

slow rate of spread, unavailable area with suitable soils, or environmental conditions. 

Aspen establishment can also be hindered by changes in soil properties as a result 

of conifer presence (Buck and St. Clair 2012), or by ungulate over-browsing (Kay 

and Bartos 2000). Fire or other disturbance that opens the tree canopy is required for 

aspen persistence over time since aspen can be outcompeted and succeeded by shadetolerant conifers, such as Engelmann spruce, subalpine fir, or lodgepole pine (Mueggler 

1985b; Smith and Smith 2005; Calder et al. 2012). Conifer presence in aspen stands 

lowers light levels and changes soil chemistry by reducing nutrients such as nitrogen, 

disadvantaging aspen in the same stands (Calder et al. 2011; Smith and Smith 2005). 

Aspen above and below ground growth and biomass is less in mixed conifer-aspen 

stands compared to pure stands (Shepperd et al. 2001). Aspen seedling establishment 

and upslope expansion in west-central Alberta, Canada, was found to be highest on 

exposed mineral soils, and the highest numbers of seedlings were found on concave 

microsites in areas of moisture collection (Landhausser et al. 2010); thus, topography 

can enhance or limit aspen establishment. Elevation range shifts may also be constrained by the slow spreading of lateral roots and hence by suckering, which is 1 to 

2 tree heights away from an existing tree (Shepperd et al. 2001). Given that aspen have 

limited upslope areas in the Wasatch Range especially, and that soil conditions, slow 

spreading reproduction ability, and herbivory can inhibit their range expansion, vulnerability of this criterion is high (fig. 17).
USDA Forest Service RMRS-GTR-366. 2017. 23

Table 3—Rock type and the percentage of National Forest land occupied by aspen for the Wasatch Range and Uinta Mountains. 

Rock type data source: USGS. Aspen location data source: USDA (2013a).

Wasatch Range rock 

types on National 

Forest land

Area (acres) of 

aspen occupying rock type

Percent of National 

Forest land rock 

type occupied by 

aspen

Uinta Mountains rock 

types on National 

Forest land

Area (acres) 

of aspen 

occupying 

rock type

Percent of National 

Forest land rocky 

type occupied by 

aspen

conglomerate 95,807 27 sandstone 48,572 22

sandstone 76,817 16 arenite 27,289 4

dolostone (dolomite) 31,315 13 glacial drift 23,545 4

limestone 23,516 11 conglomerate 23,042 12

shale 21,916 11 shale 10,019 32

gladial drift 11,225 18 alluvium 8,875 8

metamorphic rock 10,810 16 dacite 7,931 26

arenite 10,218 11 landslide 7,518 13

mudstone 9,388 13 limestone 6,389 12

carbonate 7,984 15 dolostone (dolomite) 5,648 18

alluvium 7,030 5

fine-grained mixed 

clastic 4,871 22

fine-grained mixed 

clastic 6,022 13 mudstone 4,186 25

medium-grained 

mixed clastic 4,633 12 quartzite 1 0.2

granodiorite 3,080 11 oil shale 0.4 0.0009

dacite 1,506 3

quartzite 452 21

orthoquartzite 168 21

siltstone 108 9

clay or mud 87 0.4

landslide 76 6

coarse-grained mixed 

clastic 201 5

ash-flow tuff 15 18

rhyolite 3 13

folian 1 0.1
24 USDA Forest Service RMRS-GTR-366. 2017.

Figure 15—Wasatch Mountain Range rock types underlying aspen distribution. Colored areas are soil types where aspen occurs. (Aspen location 

data USDA (2013a). Rock Type data source: USGS. http://mrdata.usgs.gov/geology/state/. Hillshade background from: Esri. Their sources are: 

UGSG, NGA NASA, CGIAR, N Robinson, NCEAS, NLS, OS, NMA, Geodatastyrelsen, Rijkswaterstaat GSA, Geoland, FEMA, Intermap, and the 

GIS User Community. Downloaded from: http://www.arcgis.com/home/item.html?id=9c5370d0b54f4de1b48a3792d7377ff2.)
USDA Forest Service RMRS-GTR-366. 2017. 25

Figure 16—Uinta Mountain Range rock types underlying aspen distribution. Colored areas are where aspen occurs. (Aspen locations USDA (2013a). 

Rock type data source is USGS. http://mrdata.usgs.gov/geology/state/. Hillshade background from: Esri. Their sources are: UGSG, NGA NASA, 

CGIAR, N Robinson, NCEAS, NLS, OS, NMA, Geodatastyrelsen, Rijkswaterstaat GSA, Geoland, FEMA, Intermap, and the GIS User Community. 

Downloaded from: http://www.arcgis.com/home/item.html?id=9c5370d0b54f4de1b48a3792d7377ff2.)
26 USDA Forest Service RMRS-GTR-366. 2017.

Figure 17—Aspen landscape with potential range shift areas if suitable conditions allow: (photo by A. Huber).

Vulnerability of Aspen-Associated, Cold-Adapted Foundation or 

Keystone Species to Climate Change

Summary: A range of low to high vulnerability is assigned for species in aspen ecosystems 

because some will likely persist and adapt or take advantage of changes in environmental 

conditions, while others will be hampered by climate warming and drying.

•  Understory vegetation associated with aspen has low to high vulnerability to climate 

change, as vulnerability varies with environmental conditions and plant tolerances 

to warmer and drier conditions. Species such as grasses, shrubs, and some forbs may 

expand during drier and warmer conditions. Understory species relatively shaded by 

aspen cover may also have a lower vulnerability. Other species, for example some 

forbs, that are exposed to heat and drought beyond tolerance levels likely have a high 

vulnerability.

•  Birds associated with aspen communities are likely to have a low to high vulnerability 

to climate change. Vulnerability varies depending on bird life history habits. Drought 

and heat associated with climate change can hamper birds, but some species can benefit 

(for example, drier conditions that promote more fire may benefit birds that benefit 

from a young forest structure). Birds that are dependent on mature forest structure 

(for example, goshawk) may have a higher vulnerability if climate change reduces the 

amount of mature forests or reduces tree sizes.

Information confidence:

•  Moderate vulnerability of understory vegetation is supported by nine studies, five of 

which are in Utah or northeast Utah, one from the Blue Mountains, Oregon, and three 

from Colorado.

•  Moderate vulnerability of birds is supported by seven studies. Species-specific information on vulnerability is limited.
USDA Forest Service RMRS-GTR-366. 2017. 27

A set of species living in aspen ecosystems is selected to capture different influences 

on ecological function, the range of biotic environmental tolerances, and vulnerability 

to climate conditions that are expected to develop in the Wasatch and Uinta Mountain 

Ranges. Understory vegetation is selected as it provides forage for a wide variety of animals and has high biodiversity. Birds are selected as they have a high diversity in aspen 

forests and depend on insects and plants in aspen forests. Cold-adapted species were 

not identified or included in this assessment. The foundation and keystone species that 

dominates aspen ecosystems are aspen trees, which are addressed in the other criteria 

of this assessment. Pollinators have a symbiotic relationship with understory plants, but 

limited information is available to assess their vulnerability on these forests.

Understory Vegetation

Grasses, forbs, and shrubs in aspen understories have high diversity, richness, and 

productivity compared to other forest types (Chong et al. 2001; Mueggler 1985a). 

The Mueggler (1988) study that compiled aspen communities across Utah, Idaho, and 

Nevada found that three communities were prevalent in persistent aspen stands of the 

Wasatch Range and Uinta Mountains. These stands had communities of (a) persistent 

aspen with understory tall forbs (common in the Wasatch Range but not the Uinta 

Mountains), (b) persistent aspen with the shrub Symphoricarpos oreophilus (common 

in the Uinta Mountains) mixing with forbs and grasses, or (c) persistent aspen with 

both Symphoricarpos oreophilus and Amelanchier alnifolia shrubs that mixed with 

forbs and grasses. Other shrubs also mixed with the dominant shrub species mentioned 

above, such as Prunus virginiana, Rosa woodsia, or Pachystima myrsinites. Some of 

the forbs in these stands included: Valeriana occidentalis, Osmorhiza occidentalis, 

Hackelia floribunda, Delphinium occidentale, Thalictrum fendleri, and Geranium 

viscosissimum (see Mueggler 1988 for full list). Grasses such as Bromus carinatus, 

Agropyron tachycaulum, Elymus glaucus, and Poa pratensis and the sedge Carex hoodii

were also found in the shrub communities mixing with the persistent aspen types on the 

Wasatch Range and Uinta Mountains. The most common community types found in the 

Uinta Mountains are seral and persistent aspen mixing with Symphoricarpos oreophilus

shrubs and grasses Calamagrostis rubescens or Bromus carinatus. Another common aspen community type in the Uinta Mountains is aspen mixing with Juniperus communis

and the sedge Carex geyeri (Mueggler 1988).

Mueggler (1988) found 2 major and several minor or incidental seral aspen community types that were in the Uinta Mountains and Wasatch Range. These communities 

were (a) seral aspen mixing with Abies lasiocarpa and tall forbs (tall forbs being uncommon in the Uinta Mountains) or (b) seral aspen mixing with Abies lasiocarpa and 

graminoids Carex rossii or Bromus anomalus. Picea engelmannii was often with the 

Abies lasiocarpa trees in the seral aspen. Tall forbs that were common, especially in the 

Wasatch Range, were: Rudbeckia occidentalis, Aster engelmannii, Valeriana occidentalis, Delphinium occidentalis, and Osmorhiza occidentalis. A shrub layer was sometimes 
28 USDA Forest Service RMRS-GTR-366. 2017.

present with Symphoricarpos oreophilus (especially in the Uinta Mountains), Rosa 

woodsii, and Berberis repens. Minor or incidental occurrences of seral aspen community types on the Uinta Mountains included aspen mixing with Pinus contorta or 

Abies lasiocarpa in conjunction with Juniperus communis in the understory. Seral 

aspen also mixed with Pinus ponderosa and had understory species of Symphoricarpos 

oreophilus, Berberis repens, Poa fendleriana, Taraxacum officinale, and Achillea 

millefolium. Seral aspen was found mixing with Picea pungens and had understory 

species of Taraxacum officinale, Achillea millefolium, Symphoricarpos oreophilus, 

Bromus anomalus, Fragaria vesca, and Poa pratensis. The seral aspen also mixed with 

Pinus contorta and had the sedge Carex geyeri dominating the understory. Pseudotsuga

menziesii mixed with aspen and the understory was dominated by Symphoricarpos 

oreophilus or Juniperus communis. Other minor and incidental occurrences in the Wasatch 

Range included seral aspen mixing with Pinus contorta and the understory shrub 

Symphoricarpos oreophilus or the forbs Thalictrum fendleri with Achillea millefolium 

in some stands. In the Bear River Mountains of the Wasatch Range, aspen mixed with 

Abies lasiocarpa and the shrubs Shepherdia canadensis, Symphoricarpos oreophilus, or 

Amelanchier alnifolia, or the sedge Carex geyeri. See Mueggler (1988) for a full description of seral aspen species and community types in the Wasatch Range and Uinta 

Mountains.

Warming and drying may inhibit the growth and survival of some understory plants, 

while others may benefit and expand. Aspen dieback from drought in seral aspen types 

of southwestern Colorado caused understory communities to shift structure and to 

reduce forb cover and richness (Anderegg et al. 2012a). This study found increased 

shrub cover in aspen stands affected by sudden aspen mortality, suggesting a potential conversion to shrub cover. A study by Korb et al. (2014) in seral aspen stands of 

southwestern Colorado found understory species that were associated with high aspen 

mortality stands were: yarrow (Achillea lanulosa), aspen fleabane (Erigeron speciosus), 

harebell (Campanula rotundifolia), and sego lily (Calochortus nuttallii). This suggests 

that these species are benefitted by the loss of aspen dieback during drought. The Korb 

et al. (2014) study also found grass biomass was higher in stands with high aspen 

mortality from sudden aspen mortality events compared to stands with low aspen mortality rates. Understory shrubs, dominated by roundleaf snowberry (Symphoricarpos 

rotundifolius), were not found to differ across different amounts of aspen mortality, 

suggesting that shrubs are resistant to the effects of drought and heat-induced mortality of aspen (Korb et al. 2014). The shift in aspen understory composition observed in 

southeastern Colorado may be an example of how understory vegetation may respond 

if drought-induced aspen dieback occurs in Utah forests. Some understory species, such 

as roundleaf snowberry, grasses, and the forbs mentioned above, may be more tolerant 

to drought and heat, which may lower their vulnerability to the expected increase in 

drought and warmer temperatures that would cause aspen dieback.
USDA Forest Service RMRS-GTR-366. 2017. 29

The effects of climate change on understory species may be reduced or magnified 

as a result of aspen stand structure and tree canopy composition. Moisture stress on 

understory vegetation may be reduced by a leafed out persistent aspen stand that reduces air movement. Wind velocity at 5 feet above the ground was measured at almost 

0 when winds were above 25 miles per hour above the tree canopy in north central 

Utah (Shepperd and Jones 1985), so understory vegetation in mature, persistent aspen 

stands are less exposed to drying from wind. Conversely, moisture loss and drying can be 

magnified by ungulate browsing of aspen suckers and understory vegetation. Browsing 

causes reduced understory and lower volume tree canopies as was found in the Bear River 

Mountains in northeastern Utah (Carter and Chard 2011) and Blue Mountains in Oregon 

(Endress et al. 2012). (Also see section on Climate Change and Grazing). Stam et al. 

(2008) found on the Dixie and Fishlake National Forests in southeastern Utah that the 

presence of as little as 10 to 20 percent conifer cover in aspen stands can reduce understory productivity.

As specific information on climate change vulnerability for the numerous aspen 

understory species is limited, a range of vulnerability from low to high is assigned. 

Species in the aspen understory may respond differently to climate change according to 

environmental tolerances to heat and drying, stand conditions, community composition, 

conifer presence, and the degree of herbivory and disturbance. Understory species in areas where drought and heat exceed tolerance levels have a high vulnerability to climate 

change—whereas other species may have low vulnerability since they are more tolerant 

of warmer and drier conditions. For example, shrubs, grasses, and some forbs may persist and become more dominant in the understory community during drought periods. 

Some understory species in persistent aspen stands may also have a low vulnerability 

since the tree canopy provides protection from heat and drying.

Birds

A large diversity of birds use aspen ecosystems, including birds of prey, small birds 

or songbirds, cavity nesters, and game birds. Here, we draw on the literature for birds 

in western United States aspen forests because few studies have been conducted in the 

Wasatch Range and Uinta Mountains. We assume similar characteristics for birds in 

these Utah mountain aspen stands. Common nighthawks and birds of prey occupying 

aspen stands can include the great horned owl, and northern goshawks, which have 

been observed nesting in aspen stands (Goshawk monitoring data, Ashley NF 2014b). 

Game birds can include ruffed grouse and mourning doves. Cavity nesting birds can 

include northern flicker, red-naped sapsucker, hairy woodpecker, downy woodpecker, 

Lewis’s woodpecker, house wren, mountain bluebird, and black-capped and mountain 

chickadees. Several small birds use aspen forests: warbling vireo, yellow-rumped warblers, chipping, white-crowned, and song sparrows, American robin, Swainson’s and 

hermit thrush, western wood peewee, dusky flycatcher, the breeding broad-tailed hummingbird, and the migrating rufous hummingbird (Debyle 1981). On the Ashley NF, the 

top 5 most abundant species in aspen forests over 2 years of surveys were the warbling 

vireo, yellow-rumped warbler (Audubon’s race), dark-eyed junco, American robin, and 
30 USDA Forest Service RMRS-GTR-366. 2017.

hermit thrush (Bird Surveys, Ashley NF 2014a). Not all aspen-associated birds nest in 

aspen stands, however; as Debyle (1981) noted in a Utah study, of the 33 bird species 

he observed in a 10 acre aspen stand in the Wasatch Range, 12 to 19 species nested in 

aspen over a 4-year period, while others utilized aspen but did not breed there. The bird 

diversity in mixed aspen-conifer forests is probably the highest, as there are a diverse 

set of niches in this forest type (Debyle 1985c).

Bird species composition and populations are tied to forest structure, which is influenced by climate and disturbance. Aspen-associated cavity nesting birds may benefit 

from disturbances in nearby conifer forests or seral aspen types that create more food 

(for example, bark beetles) and snags that provide more nesting and shelter habitat. 

Bird populations and survival rates were found to increase in conifer forests of British 

Columbia after bark beetle outbreaks that made more food and nesting resources available (Edworthy et al. 2011; Norris et al. 2013). A study by Kulakowski et al. (2013b) in 

northwestern Colorado subalpine forests found that compound disturbances from fire, 

conifer bark beetle outbreaks, and wind events reduced regeneration of conifers and 

favored initial stand dominance of aspen. They hypothesized that since aspen are less 

susceptible to fire, bark beetles, and wind than conifers, the probability and severity of 

future disturbance may eventually be diminished by an increased dominance of aspen 

after an increase in disturbance reduces conifer presence. Aspen-associated birds may 

benefit if aspen trees increase as a result of more fire and conifer bark beetle outbreak 

activity due to climate change that give aspen a competitive advantage.

Species that prefer a mature forest structure may be hampered by a loss of mature 

trees associated with the climate warming and drying and more fire. The northern goshawk (Squires and Reynolds 1997) and blue grouse, yellow-rumped warbler, warbling 

vireo, dark-eyed junco, house wren, and hermit thrush (Debyle 1981) are examples. 

The MacGillivray’s warbler, chipping and song sparrows, and lazuli bunting have 

historically occurred in younger aspen stands in northern Utah (Debyle 1981). These 

species would likely not be hampered if a younger forest structure developed with 

warmer and drier conditions and more frequent fire.

Drought, which is projected to increase in frequency, duration, and severity (Ault

et al. 2014) that causes stress to birds may also have variable effects. The Smith (1982) 

study in northern Utah and southern Idaho found that during the drought of 1977, the 

density of insect-eating birds declined, hummingbirds were absent, and seed-eating 

finches increased in a mixed meadow-aspen-spruce-fir landscape of northern Utah. 

Bird population density declined markedly in the aspen stands and only slightly in the 

spruce-fir during this drought (Smith 1982).

The Cornell Lab of Ornithology (2014) has noted an overall 20 percent decline in 

bird populations in western U.S. forests since the late 1960s. Major threats to these 

forests are noted as exurban development and exotic insect pests and diseases. Birds associated with western aspen and other forests have had mixed population changes from 

1968 to 2012 (National Audubon Society (2014). The Hammond’s flycatcher increased 
USDA Forest Service RMRS-GTR-366. 2017. 31

0.5 percent per year, lazuli bunting increased 0.2 percent per year, and the blackheaded 

grosbeak increased 0.9 percent per year, all of which are associated with other forest 

types. Declining bird populations included the MacGillivray’s warbler (–1.1 percent 

per year), the rufous hummingbird (–2 percent per year), the western wood peewee 

(–1.6 percent per year), and the dusky flycatcher (–0.7 percent per year).

Species-specific information about how bird populations change in response to 

warmer and drier climate and forest disturbance is needed. Available information points 

to a mixed vulnerability of aspen-associated birds. Bird species sensitive to drought or 

dependent on mature aspen trees likely have a high vulnerability. More frequent drought 

and a loss of mature aspen stands may occur with more frequent fire. Other birds able 

to capitalize on changing conditions such as more snags from bark beetle outbreaks or 

younger forest structures are likely to have a low vulnerability. Thus, birds’ vulnerability is likely to span from low to high vulnerability to climate change.

Limited Knowledge

Pollinators

Pollinators could be hindered by the changes in climate. Very few studies have been 

conducted on these forests with respect to the potential impacts of climate change on 

pollinators. Even more broadly, there is limited understanding of the complex interactions between plants and pollinators under climate change (Forrest 2015). Pollinators 

provide a supporting ecosystem service that ensures seed production and maintains 

understory plants. Pollinators add biodiversity to aspen stands and the surrounding 

landscape. Warren et al. (1988) study in the Wasatch Range and Uinta Mountains found 

that the insect order hymenoptera (sawflies, wasps, bees, and ants) dominated at about 

5,000 feet elevation, while the insect order lepidopterans (butterflies and moths), and 

more commonly dipterans (flies), dominated in subalpine meadows at 10,500 feet 

elevation. Because of the important services that pollinators provide, we review literature from other areas assuming similar traits and characteristics for pollinators in the 

Uinta-Wasatch-Cache and Ashley NFs. Additional study is needed to determine the 

application of these results to the Uinta-Wasatch-Cache and Ashley NFs.

Pollinators could be hindered by the direct effects of a changing climate or by the 

climate-change responses of plants they pollinate. Snowpack loss may play a role in 

hampering pollinators; for example, Rocky Mountain Apollo butterfly eggs and larvae 

may lose insulating snow cover and not survive winter freezing as was found in meadows of Alberta, Canada (Matter et al. 2011). Droughts and heat waves have been noted 

to cause a strong decline in bumble bees in Europe, and their late summer phenology 

puts them at higher risk of exposure to drought and heat (Rasmont and Iserbyt 2012). 

Pollinators may be more vulnerable to bloom scarcity during dry years, or when early 

spring frost damages and reduces flower abundance, as has been found in the montane 

and subalpine meadows of the western Colorado Rockies (Aldridge et al. 2011; Inouye 

2008). Generally, pollinators advance their phenology earlier than plants in response to 

environmental cues, such as warming (Schweiger et al. 2010). While these responses 
32 USDA Forest Service RMRS-GTR-366. 2017.

may decouple the timing of blooming plants with pollinator availability, most evidence 

to date suggests that earlier blooming and emergence of pollinators is not a major threat 

to pollinators (Forrest 2015; Forrest and Thomson 2011; Iler et al. 2013; Gezon et al. 

2016). Fragmentation of habitat, invasive species, and habitat degradation has also been 

noted to play a role in hampering pollinators globally (Schweiger et al. 2010)

Sensitivity to Extreme Climatic Events (Drought, Heat, Floods)

Summary: Aspen are assigned a high vulnerability to extreme climatic events as follows:

•  Multi-year or multi-decade severe droughts may increase in the future causing aspen 

dieback and extent reductions in some areas, especially on south and west-facing 

slopes, at lower elevations, and in areas with poor soils. Very High vulnerability is 

assigned.

•  Extreme heat events are likely to increase with climate change. Aspen ecosystem species, especially in low elevation areas living in areas at the edge of their heat tolerance, 

are especially sensitive. Very High vulnerability is assigned.

•  Aspen has a low sensitivity to flooding since most aspen extent is on hillslopes that are 

not subject to water inundation that hamper trees. However, aspen in areas of moisture 

collection, such as riparian aspen, can be hampered when exposed to long periods of 

water-logged soil. Low sensitivity is assigned.

Information confidence:

•  Sensitivity to drought is supported by 16 studies.

•  Sensitivity to extreme heat is supported by eight studies.

•  Sensitivity to flooding is supported by four studies.

Sensitivity to Drought

Historical droughts (below average precipitation over an extended period) in the 

Wasatch Range and Uinta Mountains have mostly associated with below-average 

cold season (October-March) precipitation, a season during which most of the annual 

precipitation falls (MacDonald and Tingstad 2007). Decreased precipitation in the cold 

season lengthens the duration of summer water deficits.

Future drought may become more intense and prolonged. Kunkel et al. (2013) 

had such high model agreement (>67 percent) that the consecutive number of dry 

days would increase 5 to 10 days per year in northern Utah by the mid-21st century. 

Ault et al. (2014) projected the risk for decade-scale mega drought to be 80 percent at 

the end of this century for the southwestern United States. Cook et al. (2015) found that 

drought across the southwestern United States would significantly exceed those of the 

worst drought period since the Medieval Warm Period during the 1200s. Their study 

had high model agreement across 17 models under both a moderate and high climate 

warming scenario. Higher elevations may not experience as much drying or drought 

since cooler temperatures and more precipitation are characteristic of these areas (Lukas 

et al. 2014). However, some snowpack loss is projected for higher elevations, although 
USDA Forest Service RMRS-GTR-366. 2017. 33

less than lower elevation snowpack loss (Christensen and Lettenmaier 2007). Snow 

as a percent of winter precipitation is projected to change from 90 percent to less than 

50 percent in many areas of the Wasatch Range by mid-century (Klos et al. 2013). This 

would contribute to drier conditions in the Wasatch Range late in the growing season 

that could intensify the effects of drought and hamper biota. In contrast, the Uinta 

Mountains are projected to retain more than 90 percent of winter precipitation as snow 

(Klos et al. 2013) (see Climate section of this report).

Aspen ecosystems are highly sensitive to multi-year severe drought since aspen 

trees have a low tolerance (Worrall et al. 2008; Korb 2012), and other aspen ecosystem 

biota can be hindered by drought as well as (see Vulnerability of Aspen-Associated, 

Cold-Adapted Foundation or Keystone Species to Climate Change section above). 

Rapid aspen tree dieback has been attributed to drought during the 2000s in North 

America (Worrall et al. 2013). Aspen dieback in Utah was estimated at about 9 percent 

of the aspen forest type from 2002 to 2007 (Worrall et al. 2013). Anderegg et al. (2015) 

southwestern Colorado study found that the lethal water stress threshold for aspen was 

reached during the early 2000s drought. This corresponded to a loss of vascular transport capacity in the tree from air entering into the xylem (the vascular tissue in plants 

that conducts water and dissolved nutrients upward from the root). After the drought 

ends and soil moisture is higher, the legacy of drought, xylem cavitation (where high 

water tensions cause sap to vaporize and air fills the chamber) in branches and in 

roots still remains, which reduces water transport from soil to above ground tree parts 

(Anderegg et al. 2012b). Anderegg et al. (2014) found that the drought damaged aspen 

trees had a 5-fold lower hydraulic conductivity and a 7-fold lower assimilation than 

aspen trees not damaged by drought.

Stand structure and age may play a role in aspen sensitivity to mortality from 

drought. Bell et al. (2014) found that forest structure and successional stage affected 

the degree of mortality in stands. High densities, basal areas, tree diameters, and low 

stand age were modeled to be more sensitive to mortality associated with drought in 

the Rocky Mountains and Intermountain Region. Post-successional stage stands that 

survived without encroachment by conifers with low basal areas, low stand densities, 

and high-age stands were the least sensitive to mortality from drought. Korb (2012) 

observed that in pure aspen stands of western Colorado, the highest levels of dieback 

were associated with larger diameter trees (>12 cm diameter breast height), low basal 

area, and low stand density.

Aspen dieback has been associated with southern to western-facing slopes, and 

also with lower elevations, top slope positions, and poor soils (Evans 2010; Worrall 

et al. 2010, 2008, 2013). On the Uinta-Wasatch-Cache and Ashley NF, 34 percent of 

total aspen stand area are on south-facing slopes and 22 percent on west-facing slopes 

(derived from GIS data not shown). Given the high sensitivity of aspen to multi-year 

severe drought, a very high vulnerability is assigned to this criterion.
34 USDA Forest Service RMRS-GTR-366. 2017.

Sensitivity to Extreme Heat

Climate models have high agreement that more extreme heat will occur in the future. 

Temperature projections compared to late 20th century data indicate an increase of 5 to 

10 days per year in the number of days that temperatures exceed 95 °F by the mid-21st

century for northern Utah (Kunkel et al. 2013). The most extreme heat days are projected for the lower elevations around the Uinta Mountains and Wasatch Range (see 

figure 23 in Kunkel et al. 2013).

Aspen are greatly hampered by extreme heat. Aspen tree photosynthesis declines 

at air temperatures above 77 °F (Lieffers et al. 2001). The aspen clone, or group of 

individual trees connected by a shared root system, has optimal growth when soil 

temperatures are 74 °F (Perala 1990). Aspen trees living in stands that have had portions die from drought are particularly susceptible to heat stress as the remaining live 

trees receive more solar radiation (Korb et al. 2014). Extreme temperatures magnify 

the effects of drought, further hampering aspen trees or reducing tree populations 

(Hogg et al. 2008; Worrall et al. 2008), as well as birds, flowering herbs, and aspen 

understory insects (Smith 1982).

Aspen stand topographic position and stand structure can raise or lower the effects 

of extreme heat. Aspen on south and west-facing slopes and lower elevations can have 

amplified exposure to heat compared to other aspects (see Sensitivity to Drought section above). In addition, heat is increased when canopy cover is reduced, such as with 

sudden aspen mortality (Korb et al. 2014), or when aspen layers within the canopy are 

reduced by over-browsing (Rogers 2015b). Aspen trees are susceptible to mortality 

during heat stress, especially during multi-year severe drought, and are assigned a very 

high vulnerability to extreme heat. Lower elevations are especially sensitive since extreme heat is projected to be more intense there.

Sensitivity to Floods

The future may hold more intense flooding in northeastern Utah. Kunkel et al. (2013) 

project the number of days with precipitation >1 inch increases by 10 to 50 percent 

in northern Utah (<50 percent model agreement). As discussed in the Climate section 

above, there is high model agreement (>70 percent) that winters will become slightly 

wetter in the Wasatch Range and Uinta Mountains, with more rain, especially in the 

Wasatch Range. However, future flooding risk and the magnitude or timing of changes 

in precipitation is not clear.

Topographic position affects aspen sensitivity to flooding in different ways. Aspen 

ecosystems that are in areas of moisture collection or along streams may be most 

susceptible to water inundation by flooding. High soil moisture can promote fungal 

diseases in aspen trees (Hinds 1985). Aspen tree regeneration by root suckering was 

found to be reduced by increased flooding and flooding in combination with warmer 

temperatures (Bates et al. 1998). Areas inundated by water over several years can kill 

aspen roots, which has been observed near beaver dams (Debyle 1985a). Aspen in 
USDA Forest Service RMRS-GTR-366. 2017. 35

upslope areas may be less exposed to water inundation from flooding, as these areas 

do not collect moisture. However, intense flooding can cause landslides in upslope 

areas, which could result in areas of stand mortality. Most aspen ecosystems in the 

Uinta-Wasatch-Cache and Ashley NFs are on hillslopes, and given that an extended 

time period of water inundation or an intense flood that causes a landslide is needed 

to hamper aspen, they are likely to have a low sensitivity to flooding that may become 

more intense in the future.

Intrinsic Adaptive Capacity

Summary: Factors both raise and lower vulnerability, moderate vulnerability is assigned.

Factors: raising adaptive capacity are as follows:

•  Aspen trees have mechanisms that increase its water use efficiency and heat tolerance, 

raising its ability to adapt to climate change.

•  Aspen have high biodiversity and productivity and the ability to recover quickly after 

disturbances such as fire, which raise its adaptive capacity.

Factors that lower adaptive capacity:

•  Aspen are susceptible to numerous insects and diseases and are hampered by competition with conifers where they coexist with aspen. Seedlings are susceptible to 

over-browsing by ungulates. The ability of aspen to genetically adapt to new climate 

conditions requires seeding, which is episodic, and the amount of genetic adaptation 

possible may be overtaken by the rate of climate change.

Information confidence:

•  Factors that strengthen adaptive capacity are supported by 24 studies.

•  Factors that weaken adaptive capacity are supported by eight studies.

Factors That Strengthen Adaptive Capacity to Climate Change

Aspen climate change adaptive mechanisms

Aspen trees have many mechanisms that raise their adaptive capacity to drought 

and heat. Aspen leaf shape is such that it trembles at the slightest breeze (Jones and 

DeByle 1985b), which helps cool the leaves, raising the ability to withstand heat. Aspen 

transpire less water when leaves are not present (DeByle 1985b) and use less water 

than conifers (Gifford et al. 1984; Jones et al. 1985). More snowpack is accumulated 

in aspen stands as aspen tree structure allows for less canopy snow interception than 

conifers (DeByle 1985b). The higher amount of snow accumulation in aspen stands 

can increase water availability during the growing season and the amount of watershed 

runoff compared to conifer forests (Ryel et al. 2006). Additionally, trees in aspen clone 

systems have connected roots that can become less dependent on parent root systems as 

trees age or remain functionally interconnected for a generation or more (DesRochers 

and Lieffers 2001; Shepperd et al. 2006; Shepperd and Smith 1993). The connected 

root systems can benefit the whole clone system as trees that have tapped into the water 

table can transport water to other trees that don’t have access to the water table (DeByle 

1985b). Thus, aspen clones have strengthened adaptive capacity to drought and water 

stress.
36 USDA Forest Service RMRS-GTR-366. 2017.

Diversity and Life History Traits

Plant, bird, and invertebrate diversity is higher in aspen ecosystems compared to other forest types (Chong et al. 2001; Griffis-Kyle and Beier 2003). When there is diversity 

among aspen clones, the response to environment can be more variable; for example, 

the timing of leaf out has been observed to be different among clones (Cottam 1954; 

Greene 1971). This enlarges the scope of environmental tolerances by biota, which may 

increase adaptive capacity.

Two major genetic clusters of aspen have been identified in North America: (a) a 

southwestern cluster with two subclusters occupying areas west of the Continental 

Divide and south of Washington, Idaho, and Montana, and (b) a northern cluster that is 

north of these boundaries that correspond to the area covered by ice in the last glacial 

maximum (Callahan et al. 2013). The southwestern cluster of which the Uinta-WasatchCache and Ashley NFs are located was determined to have less genetic diversity within 

populations compared to the northern cluster, but the populations across the landscape 

were more distinct from each other. The southwest cluster aspen populations are highly 

valuable from an evolutionary standpoint as they represent a large portion of aspen’s 

genetic variation and evolutionary history (Callahan et al. 2013).

Reproductive and life history traits of aspen also serve to raise adaptive capacity. 

While aspen trees are relatively short lived, few live up to 200 years (Perala 1990). 

Clones vary in size and can propagate aspen ramets, potentially allowing genets (a 

group of genetically identical individuals that have originated from a single ancestor 

by suckering) to live for thousands of years (Ally et al. 2008; Kemperman and Barnes 

1976). Aspen can reproduce by seed or by suckering from clones. Expansion of clones 

is rapid as new aspen shoots can sucker asexually after 1 year and form clones that 

vary in size and characteristics (Jones and Trujillo 1975). The growth of aspen ramets 

is rapid during the first 20 years, and roots can spread at a rate of 3 to 6 feet per year 

(Buell and Buell 1959; Perala 1990). The rapid growth of ramets serves to quicken 

recovery after a disturbance that kills or stresses parent aspen trees, such as fire, which 

can raise adaptive capacity.

Seed reproduction is a strong contributor to genetic diversity among aspen populations (Mock et al. 2008), which would expand the range of potential population 

responses to climate change and thus raise adaptive capacity. Aspen seed reproduction 

is not as common as by suckering, but seed reproduction has recently been found more 

common than previously thought, thus offering a potential means for aspen migration 

under climate change (Krasnow and Stephens 2015; Mock et al. 2008; Romme et al. 

2005).

Genetic diversity can also increase adaptive capacity. One clone in central Utah 

named Pando is estimated at 114 acres (DeWoody et al. 2008), and many aspen genotypes have been found to be contained adjacent to this aspen grove. This signifies that 

aspen reproduction by seeding and genetic diversity in aspen stands is greater than 
USDA Forest Service RMRS-GTR-366. 2017. 37

previously thought (Long and Mock 2012). The ability of tree species to genetically 

adapt to changing climate conditions is greatest when there are large populations with 

high genetic variability and opportunities are available for more genetically adapted 

species to establish (Alberto et al. 2013). How aspen trees and other aspen-associated 

plant species might genetically adapt to future climate warming and drying is an area of 

research in need of further study.

Factors That Weaken Adaptive Capacity

Ability to adapt to multiple and severe stressors

Aspen extent reductions have been observed in the western United States and are 

attributed to: conifer competition, fire suppression, over-browsing by ungulates, or 

fluctuations in forest populations from intermittent fires that temporarily reduce tree 

populations (Bartos 2000; Bartos and Campbell 1998; Kashian et al. 2007; Kulakowski 

et al. 2013a; Worrall et al. 2013). Aspen are not adapted to shade, but facilitate the 

succession of shade-tolerant conifers. Bell et al. (2014) implied that conifer competition under warmer and drier conditions could accelerate the loss of aspen. While aspen 

reproduce quickly following disturbance, aspen dieback was attributed to multiple 

stressors of insects and pathogens killing aspen trees stressed by multi-year severe 

drought and heat (Worrall et al. 2010). Additionally, the rate of expected climate change 

may be too fast for plant adaptive responses to keep pace, a conclusion of 8 in 12 studies investigating this aspect (Franks et al. 2014). In the case of aspen, reproduction from 

seed is episodic, with reproduction typically from suckering. The seed reproduction 

would be required for gene flow that would allow a new generation of aspen to genetically adapt to a different climate.

Dependence on Specific Hydrologic Condition

Summary: Aspen ecosystems are not dependent on a narrow hydrologic regime but require 

adequate moisture for growth. Biota are not dependent on the form of moisture, and when 

they receive adequate moisture, they are likely to persist in the snow-dominated regime that 

will become more rain-dominated in the future. Moderate vulnerability is assigned.

Information confidence:

•  Snowpack loss, especially at lower and mid-elevations, and future shifts to more rain are 

supported in the literature in the study area and outside of it (four studies included here). 

The effects of this shift to more rain in aspen ecosystems have three studies supporting 

them.

Hydrologic Regime

Aspen ecosystems in the Uinta Mountains and Wasatch Range receive most of their 

moisture from snow and occupy a snow-dominated hydrologic regime that is expected 

to shift to more rain in the future. Lower elevations may have rain as well as snowmelt 

influencing runoff and are an area of further study. The shift to more rain has already 

been happening across the State of Utah since the 1970s. As a result, snow depth and 

snow cover have also been trending lower in the State (Gillies et al. 2012). The trend 
38 USDA Forest Service RMRS-GTR-366. 2017.

does have year to year variability since precipitation and temperature vary across 

time. Annual precipitation in 8 Utah aspen stands was found to vary from 16 to 44 

inches (elevations varied from 7,200 to 9,850 feet) (Jones and DeByle 1985a). Jones 

and Horell (2008) projected snowpack loss to be elevation-dependent in the Wasatch 

Range. For a 1.8 °F (1 °C) temperature increase, snowpack loss ranged from 20 percent 

at the base to 4 percent at the top of the Ben Lomond Range. The Oquirrh Mountains 

southwest of Salt Lake City were projected to have a 16 percent loss at the base and 

2 percent loss at the top with a 1.8 °F (1 °C) temperature increase (Jones and Horel 

2008). By the mid-21st century, a transition from snow to more winter rain may also be 

more common in the Wasatch Range compared to the Uinta Mountains; see figure 9 in 

the Climate section of this report (Klos et al. 2014). Warmer temperatures may extend 

the growing season, but that shift from snow to more rain during winter may make it 

become drier late in the season.

Hydrologic Regime Changes and Effects on Aspen Ecosystems

Aspen ecosystems do not depend on a particular form of precipitation, but they do 

require adequate moisture for growth and reproduction throughout the growing season. 

Aspen reproduction by seed in early spring requires consistent soil moisture for success (McDonough 1985). Snow and accumulation of soil water and storage is higher in 

aspen stands compared to conifer forests (Burke and Kasahara 2011), but evapotranspiration during summer is higher in aspen (LaMalfa and Ryle 2008). The availability 

of moisture throughout the growing season can be compromised with earlier snowmelt 

that contributes to longer periods of moisture deficit, especially affecting late growing 

season growth. As discussed in the Sensitivity to Extreme Climatic Events section 

above, warmer temperatures resulting in more evaporation and more intense and longer 

periods of drought that are expected with climate change would compound the effects 

of less moisture availability late in the growing season, adversely affecting aspen and 

associated species.

The expected hydrologic regime shifts of more rain instead of snow are likely to 

have spatially variable effects on aspen. Some areas, such as lower elevations where 

species could exist at the edge of heat and moisture tolerances, may be more affected 

by loss of snowpack that contributes to drier growing season conditions. This could 

contribute to species dieback and hinder plant function and reproduction. At higher 

elevations (fig. 14), aspen may receive adequate moisture and species would suffer 

little to no adverse effects. The information on how changes in the hydrologic regime 

are likely to affect aspen ecosystems across the landscape is an area of further study. 

However, given the likelihood of aspen persistence in areas that will likely have adequate moisture throughout the growing season, such as at higher elevations, a moderate 

vulnerability is assigned to this criterion.
USDA Forest Service RMRS-GTR-366. 2017. 39

Potential for Climate Change to Exacerbate the Effects of NonClimate Stressors, or Vice Versa

Summary: Moderate vulnerability is assigned because climate change has potential to exacerbate the effects of non-climate stressors, specifically as follows:

•  Climate warming, drought, and floods can intensify the effects of grazing that can 

reduce or stop aspen regeneration, especially when ungulate grazing is intense. High 

vulnerability is assigned.

•  Future warming, drying, and less snowpack raise the potential for more frequent, severe, 

and larger fires and more conifer mortality from bark beetle outbreaks, thus lowering 

conifer competition for aspen. This would likely benefit aspen by promoting regeneration and the dominance of aspen on the landscape. Low vulnerability is assigned.

•  Drought has been linked to increased susceptibility to insects and diseases. Future 

increases in the magnitude and intensity of drought could exacerbate the effects of 

insects and diseases, and vice versa. However, the regeneration of an aspen stand after 

a mortality event from drought and/or insects and diseases can occur if not imperiled by 

continued drought or over-browsing of ungulates. Moderate vulnerability is assigned.

Information confidence:

•  Grazing and climate exacerbation is supported by 11 studies.

•  Climate change exacerbation of fire and bark beetles is supported by 16 studies.

•  Climate change exacerbation of insects and disease and sudden aspen mortality is supported by 21 studies.

Climate Change and Herbivory

Grazing and browsing in aspen ecosystems on the Uinta-Wasatch-Cache and Ashley 

NFs is by wildlife and domestic livestock. This over-browsing can reduce or even stop 

the successful regeneration of trees, especially when combined with drought, shallow 

soil depth, or hydrologic conditions such as high water tables (Johnston 2001; O’Brien 

et al. 2010). Monitoring data on the Ashley NF show that current aspen regeneration is 

abundant where domestic and wild ungulate (hoofed animal) grazing is ongoing, and 

aspen expansion is also indicated (fig. 18). In some instances, minor scale moderate to 

heavy ungulate grazing is impacting aspen regeneration (Goodrich and Huber 2015).

Other areas of Utah south and west of the Ashley NF are experiencing declines 

in tree regeneration as a result of over-browsing. For example, Rogers et al. (2015) 

found moderate to high elk herbivory had a negative influence on aspen stands of Wolf 

Creek Ranch in northwestern Utah, which is private land that borders the study area of 

this assessment. Regeneration of aspen was below replacement levels on one half of 

the study area (5,765 acres [2,333 ha] of aspen stands), and many aspen stands were 

reduced to nearly a single layer of aspen dominated by aging canopy trees (Rogers et 

al. 2015). Kay and Bartos (2000) found that aspen subjected to deer browsing failed to 

regenerate or had lower stem densities compared to plots that were protected by fencing 

on the Dixie and Fishlake National Forests in Utah. High elk populations and heavy 

aspen browsing in the drought-prone Tavaputs Plateau of eastern Utah was found to 
40 USDA Forest Service RMRS-GTR-366. 2017.

reduce aspen regeneration as well, especially in pure aspen stands and in areas with 

flatter slopes (Rogers and Mittanck 2014). Martin and Maron (2012) found that less 

winter snowpack allowed more elk herbivory of aspen and contributed to aspen habitat 

deterioration and lower bird populations in Arizona. In some cases, however, the effects 

of current ungulate browsing are not definitively linked to a reduction or lack of aspen 

regeneration as Rogers et al. (2010) found on Cedar Mountain in southern Utah. They 

did not find clear evidence of current ungulate suppression of regeneration, but they did 

find unhealthy aspen stands in drought-prone areas. They suggested that land use history (including previous herbivory) altered disturbance regime, while soils and geology 

were factors influencing the aspen conditions in this area.

Grazing and aspen sucker or seedling browsing by the different types of grazing animals vary across landscapes over time and according to environmental condition. Wan 

et al. (2014) study across all Utah’s National Forests found aspen regeneration benefitted from larger and more severe fires. Greater light availability in high severity fire sites 

was found to increase aspen growth and the defense chemistry against browsing. Aspen 

have a chemical defense system of phenolic glycosides in leaves, which deter insect and 

in some cases ungulate foraging. On the Fishlake National Forest, Utah, damage from 

browsing was 60 percent lower in moderate or high intensity burn areas compared to 

low intensity burns (Wan et al. 2014). Villalba et al. (2014) found that the availability 

of higher quality forage was a driving factor in the choice of what sheep graze. When 

the nutritional quality of grasses and forbs declined, aspen were grazed more heavily 

despite higher concentrations of chemical defenses. Jones et al. (2011) study in Lassen 

National Forest, California, found that cattle utilized understory meadow vegetation 

early in the growing season and shifted to aspen suckers by mid-season, while using 

aspen for forage mostly in the late growing season.

Figure 18—Dahlgren Creek on the Uinta-Wasatch-Cache National Forest. Photo on left: At year 2 post logging and burning, abundant aspen sprouts 

are about 1–2 feet tall. Sprouts of this size are vulnerable to ungulate browsing. Additional monitoring was needed to determine sustainability. Photo 

on right: At year 6 post logging and burning, canopy cover of aspen is about 60% and the average height of sprouts is about 6 ft. Cattle were permitted here each year since the 2008 burn. Sustainability of aspen concurrent with cattle and wild ungulate use is indicated (Zobell and Goodrich 2015).

21 June 2010 4 Sept. 2014
USDA Forest Service RMRS-GTR-366. 2017. 41

How climate change may exacerbate the effects of grazing in aspen ecosystems depends on many factors: stand age structure, grazing and wildlife management, soil and 

hydrologic conditions, and the occurrence of drought. For example, if there is less snow 

on the ground and little forage available, herbivory of aspen may increase. A high vulnerability is assigned as climate change has a high potential of exacerbating deleterious 

effects of grazing and browsing in aspen ecosystems, but in some cases, management 

may partially offset these effects through reducing wildlife and cattle numbers, the 

season of grazing, or grazing intensity.

Climate Change, Fire, and Bark Beetle Outbreaks

Fire

Climate warming and drying have recently been observed to alter fire behavior. 

The last decade has seen a lengthening of the fire season, more frequent fires larger 

than 1,000 acres (405 ha), and burned areas that have become larger as compared to 

the 1970s and 1980s in the western United States (Dennison et al. 2014; Westerling et 

al. 2014). This upswing in fire activity has been attributed to warming, drying, earlier 

springs, and less snowpack (Westerling et al. 2014). Although their study time period 

was shorter, Dillon et al. (2011) found a statistically increasing trend in the annual 

area burned and area burned severely between 1984 and 2006 in the southern Rocky 

Mountains (including the Wasatch Range and Uinta Mountains), the Mogollon Rim, 

and the Colorado Plateau. The more important predictors of severe fire occurrence 

tended to be topographic variables, rather than climate or weather variables; however, 

when dry conditions prevailed, regional climatic controls appeared to overwhelm topographic effects (Dillon et al. 2011).

Aspen generally has a low fire potential when stands are healthy and have a lush understory. Most aspens on the Uinta-Wasatch-Cache and Ashley NFs have been modeled 

to have a very low or low potential for an intense fire that may be difficult to suppress 

(fig. 19) (U.S. Department of Agriculture 2013b). High fuel moisture content lowers 

burn risk, and can enable aspen forests to serve as fire breaks. Fires in conifer forests 

that move into aspen stands have been observed to drop to the ground and burn a short 

distance (Fechner and Barrows 1976). Aspen forests will burn, however, when low fuel 

moisture and fuel continuity are present. Downed wood, shrubs, and conifer presence in 

aspen stands can increase the chance of high severity fire and aspen mortality (Brown 

and Simmerman 1986). Persistent aspen stands without conifer presence are less susceptible to fire than stands with conifers present (Shinneman et al. 2013), and riparian 

aspen are the least susceptible to fire (O’Brien et al. 2010). DeRose and Leffler (2014) 

modeled aspen fire behavior, which varied across different aspen stand composition and 

fire weather. Crowning and torching were not simulated to occur in aspen-dominated 

stands when there were moderate weather conditions. Crown fires occurred under 

severe and extreme fire weather, but not under moderate or high fire weather. Aspen 

trees are considered fire-adapted as they are early successional, being the first to 
42 USDA Forest Service RMRS-GTR-366. 2017.

regenerate, often prolifically after a fire, and sometimes by seed (Romme et al. 1997; 

Krasnow and Stephens 2015; Long and Mock 2012; Rogers et al. 2014). There are aspen stands that are relatively persistent and where fire is rare, especially when conifers 

are not present or where topographic or hydrologic conditions inhibit fire (Rogers et 

al. 2010). Most aspen stands require fire to persist because this disturbance opens the 

canopy allowing adequate light to promote regeneration (Shinneman et al. 2013).

Current and future fire disturbance regimes are likely to benefit aspen ecosystems, 

provided that ungulate herbivory pressure is low during the initial establishment or 

regeneration period. The potential increase in fire occurrence and size associated with 

climate change suggests an increased likelihood of aspen tree dominance in the future. 

Wan et al. (2014) found that increased fire size and severity had a positive effect on 

Figure 19—Wildland fire potential for aspen stands on the Uinta-Wasatch-Cache and Ashley 

National Forests, and the percent of total aspen extent by wildfire potential class is given in the 

legend. Higher fire potential has an elevated probability of experiencing high-intensity fire with 

torching, crowning, and other forms of extreme fire behavior under weather conditions conducive to fire (data from the Fire Modeling Institute, USDA 2013b).
USDA Forest Service RMRS-GTR-366. 2017. 43

aspen regeneration in National Forests across Utah. They contend that future fire 

regimes with larger and more severe fires would have positive effects on aspen regeneration, assuming climate conditions and ungulate herbivory don’t dampen the positive 

effects. Kulakowski et al. (2013b) study in northwestern Colorado subalpine forests 

asserted that increased dominance of aspen could reduce the probability and severity 

of future fire disturbance and increase the resilience of forests. As most aspen stands 

are dependent on fire and would be benefitted by increased frequency and extent, a low 

vulnerability is assigned to this criterion.

Conifer Bark Beetle Outbreaks in Seral Aspen

Conifer forests in the western United States have experienced large areas of mortality from bark beetle outbreaks as (a) warmer temperatures have reduced cold-induced 

bark beetle mortality, (b) drought stress has reduced tree defenses against bark beetles, 

and (c) fire suppression has created many mature forests susceptible to bark beetles 

(Bentz et al. 2009). Conifer mortality from future bark beetle outbreaks is expected to 

expand to higher latitudes and altitudes, although spatial and temporal variability of 

outbreaks is expected (Bentz et al. 2010).

How aspen may respond to conifer mortality from bark beetle outbreaks is a new 

area of scientific investigation. It is hypothesized that conifer mortality from bark 

beetles would result in a pulse of aspen recruitment as a result of competition release, if 

aspen are present within conifer stands. However, it remains unclear if this is the case, 

since many factors affect aspen regeneration: (a) surviving conifers may limit aspen 

regeneration by shading them, (b) new aspen suckers may be hindered by ungulate 

grazing, (c) canopy openings may expose aspen to severe weather that inhibits them, 

(d) they may be subjected to damage from falling snags, and (e) climate warming and 

drying may inhibit aspen sucker growth (Pelz and Smith 2013). Bretfeld et al. (2015) 

study of aspen in a severe bark beetle outbreak area of northern Colorado found increased radial growth of aspen but no change in aspen suckering as the release from 

conifer competition was dedicated to radial growth instead of suckering. Given the 

potential for bark beetle outbreaks to benefit aspen recruitment and growth, a low 

vulnerability is assigned to this criterion, but with the caveat that little scientific investigation has been completed as yet.

Climate Change, Insects and Diseases, Sudden Aspen Mortality and 

Regeneration

Sudden mortality of large areas of aspen trees was first noted by Worrall et al. (2008) 

in southwestern Colorado. The cause of this aspen mortality event has been associated 

with several physical and biological factors. Predominant factors such as multi-year 

severe drought and heat have been linked with the sudden mortality (Rehfeldt et al. 

2009; Worrall et al. 2010, 2013). High density stands and presence of conifers have 

been used to explain patterns of mortality by the recent sudden aspen mortality events 

in the Intermountain West and Rocky Mountains (Bell et al. 2014) (also see Sensitivity 

to Drought section).
44 USDA Forest Service RMRS-GTR-366. 2017.

Insects and disease can contribute to worsen the degree of sudden aspen mortality 

associated with drought and heat (Marchetti et al. 2011), thus the effects of climate 

warming and drying can be exacerbated. Primary agents that were attributed to increased damage and mortality of aspen during the early 2000s drought in Utah are: 

Cytospora canker, sooty bark canker, other unidentified cankers, Phellinus decay, 

bronze poplar borer, poplar borer, eastern poplar borer, poplar dicerca, and mechanical 

damage from animals (Guyon and Hoffman 2011). Damaging but not killing agents 

to aspen trees are: large aspen tortrix, aspen leaf tier, aspen two leaf tier, aphids, 

aspen leaf miner, blotch miners, leaf rollers, forest tent caterpillars, poplar petiole 

gall, mites, aspen skeletonizer, lace bugs, and leaf beetles (Guyon and Hoffman 2011; 

St. Clair et al. 2010). The leaf defoliating gypsy moth has been found in Utah but 

eradicated, with continuous monitoring showing it has not been present since 2008 

(UDAF 2015). If the gypsy moth were present, potential future invasions modeled 

by Logan et al. (2007) showed an expansion of the moth into higher elevations of the 

Wasatch Range and Uinta Mountains where suitable climates are expected to develop.

The recent mortality of aspen across the western United States has been associated with multiple interacting factors of drought as well as insects and diseases 

(Kliejunas et al. 2009; Marchetti et al. 2011; St. Clair et al. 2010). While new invasive 

insects as well as already present ones threaten damage and mortality to aspen, the 

ability of aspen to quickly regenerate may offset deleterious effects. Given that aspen 

persist despite damage and mortality from insects and disease, a moderate vulnerability 

is assigned to this criterion.

Likelihood of Managing or Alleviating Climate Change Effects

Summary: There are numerous management options to mitigate stressors on aspen 

ecosystems and have the potential to reduce the effects of climate change, however, the 

effectiveness in mitigating future climate change is untested. Management actions can be 

overwhelmed by extreme conditions, and some options may not be feasible or are limited to 

the degree they can offset the effects of climate change. Climate adaptation is an area of further study and is an iterative process that requires long-term planning and monitoring. High 

vulnerability is assigned.

Information confidence:

•  Management responses for aspen and adaptation are supported by 21 studies.

Climate Change Adaptation

Adaptation to climate change is a complex challenge, and a new and growing body 

of science has developed to support and guide adaptation to climate change (Moss et al. 

2013). Developing and implementing climate adaptation options face the challenges of: 

limited financial resources available for management activity, conflicting social political 

values, and policy direction; and limited or unclear information to guide adaptation option development, such as multiple trajectories of future climate.
USDA Forest Service RMRS-GTR-366. 2017. 45

The determination of success for climate adaptation actions are an area in need of 

further scientific study, and is defined by multiple objectives from economic, institutional, policy, ecological, social, and political viewpoints (Moser and Boykolf 2013). 

Doria et al. (2009) used expert elicitation to define successful adaptation to climate 

change as “any adjustment that reduces the risks associated with climate change, or 

vulnerability to climate change impacts, to a predetermined level, without compromising economic, social, and environmental sustainability.” Few examples of successful 

climate change adaptation exist, while adaptation to past climate or non-climate 

stressors are numerous (Moser and Boykolf 2013). While the degree of climate adaptation effectiveness of management actions is an area of further study, numerous aspen 

management actions have been used to protect, maintain, and restore aspen ecosystems 

(table 3). These actions need careful consideration of management goals, the evaluation 

of effectiveness, learning by doing and sharing of best practices, and may need to apply 

methods in innovative ways to meet new challenges of future climate change (Bierbaum 

et al. 2013; Mawdsley et al. 2009). Despite the challenges of climate adaptation there is 

a strong call to develop climate adaptation science and implement actions that mitigate 

climate change (Moss et al. 2013). Climate adaptation is an iterative process that requires long-term planning and monitoring.

Management Strategies

Rogers (2015a) recommends a strategic approach to the management of aspen by 

incorporating the following: knowledge of aspen types (persistent, seral and mixed 

aspen-conifer, and riparian discussed in the Introduction), monitoring, historic disturbance, and collaborative problem-solving. Before management action is taken, 

Shepperd et al. (2006) recommend a careful investigation of size, age, vigor, and 

successional status of aspen clones. They also recommend consideration of soils, site 

productivity, competition from other plants, and the potential impact of browsing animals on new regeneration. Treatments may include doing nothing or using harvesting, 

prescribed fire, mechanical root stimulation, removal of competing vegetation, protection from herbivory, or in limited cases aspen seed regeneration (Long and Mock 2012). 

Bartos and Campbell (1998) outlined 5 risk factors for aspen decline in Utah as follows:

(1) Conifer under and over story cover is >25 percent.

(2) Aspen canopy cover is <40 percent.

(3) Dominant aspen trees are >100 years old.

(4) Aspen regeneration 5 to 15 feet tall is <500 stems/acre.

(5) Sagebrush cover is >10 percent.
46 USDA Forest Service RMRS-GTR-366. 2017.

Within these parameters, O’Brien et al. (2010) recommended a four step process for 

the management of aspen. Although no guideline for aspen management can anticipate 

all situations, they offer general guidelines to think holistically in terms of aspen management. O’Brien et al. (2010) four step process is:

Step 1: Assess the condition of aspen in the landscape/area including the determination of the aspen type and significance of aspen in the project area.

o Is aspen a significant part of the diversity, composition, and function of 

the landscape? If yes, treatment may be warranted. Late successional 

forests that have converted to conifer dominance with scattered remnant 

aspen may need to be considered as well. These sites may have historically been dominated by aspen (Dale Bartos, U.S. Forest Service, personal 

communication, 2015).

o Is the trajectory for aspen without treatment to move outside of the sustainable conditions at the landscape level (for example, aerial cover, stand 

structure, stand composition, overstory/understory cover)? If yes, management changes or actions may be warranted.

Step 2: Rely on site-specific data to target the underlying cause(s) of problematic 

condition(s). See O’Brien et al. 2010.

Step 3: Select response options(s) relevant to the particular stand type, problematic condition(s), underlying causes of the problematic condition(s), and 

landscape context.

Step 4: Monitor.

o Monitoring should be consistent and implemented throughout the aspen 

restoration process.

A summary of potential management responses drawing on several literature sources 

are given in table 4.

Table 4—Summary of possible management responses and goals. Compiled from O’Brien et al. (2010), Rogers et al. (2014), or 

other studies cited. Note: Combinations of responses are possible, or using more intensive responses as indicated by monitoring 

results.

Reduce Stressors, Revitalize Existing Stands and Promote Aspen Recruitment

Seral aspen types

Cut subdominant conifers

Cutting of aspen and conifers. The amount of animal browsing needs to be considered as aspen regeneration may be consumed, posing the risk of die-out of the aspen stand (Kay and Bartos 2000). Selective cutting may be a preferred option to 

stimulate aspen regeneration.

Burn aspen and conifers, or allow wildfires to burn and create new sites for aspen to occupy. Restore the natural fire regime.

Selectively cut overstory conifers

Hinge trees to impede ungulate access (Kota and Bartos 2010) Note: O’Brien et al. (2010) report variable results with this treatment and Walters et al. (1982) noted logging wounds predisposed aspen trees to insect and disease attacks. Using tracked 

feller-bunchers to remove conifers can avoid excessive damage to existing trees. Damage from mechanical removal can delay 

recruitment (Jones et al. 2005).
USDA Forest Service RMRS-GTR-366. 2017. 47

Girdle conifers

In conifer dominated stands, create scattered canopy gaps in conifer over story so the aspen component will persist over time in 

later successional forests. 

Persistent Aspen Types

Restore structural diversity where absent (use vegetation treatments to simulate gap/phase dynamics). Rogers et al. (2014) note 

that terrain isolated persistent aspen types need little active management as long as ungulate over-browsing is not an issue.

Address a potential causes of a lapse in recruitment

Simulate gap/phase dynamics with vegetation manipulation, not large-scale and high severity disturbances

Riparian Aspen Types

Limit domestic browsing and other human activities where possible (Newlon and Saab 2011)

Careful mechanical harvest to restore aspen (Shepperd et al. 2006). For example, removal of unwanted trees in riparian areas.

Grazing Management Responses

Change the length and/or timing, class or number of livestock, or change the placement of salt and nutritional supplements. The 

nutritional value of aspen is higher in fall compared to others forage, and suckers may need protection during the fall (Shepperd 

et al. 2006).

Fence or temporarily fence to reduce livestock and/or wild ungulate pressure on aspen suckers

Rest excessively browsed aspen when fencing or changes in livestock grazing are not sufficient or feasible or when actions are 

needed across the landscape

Change annual browse utilization limits in grazing systems to ensure aspen sucker recruitment into the > 6 foot height class.

Improve and increase the availability of native vegetation for wildlife outside aspen stands of concern

Recreation Management Responses

Prevent or reduce dispersed camping within aspen

Post or sign dispersed camping in appropriate locations

Monitor

Monitor for successful regeneration of aspen. Also see Fowler (2014) study that discusses efficient distance method sampling 

routines, and Shepperd et al. (2006) study that discusses aspen monitoring and assessment techniques.

Monitor browsing level: 30 percent threshold suggested by Olmsted (1979) and a 20% threshold is suggested by Jones et al. 

(2005)

Monitor for signs of risk factors from Shepperd et al. (2006): 

 Conifer understory and overstory cover is >25% 

 Aspen cover is <40%

 Dominant aspen trees are greater than 100 years old

 Sagebrush cover is >10%

 Aspen recruitment levels on stems >6 feet but less than the canopy height <500/acre is not self-replacing.

 Aspen regeneration levels of suckers <6 ft in height: >1000/acre are self-replacing

 500–1000/acre is marginal

 <500/acre is not self-replacing 

Collaborate

Use collaborative problem solving (Rogers 2015a)

Climate Change and Sudden Aspen Mortality Responses

Establish new stands in a climatically suitable habitat (Krasnow and Stephens 2015)

•	 Aspen root separation (Documented successful in some settings to increase the area covered by a clone)

•	 Outplant seedlingsa

, transplant ramets, disperse seeds to a suitable microclimate after disturbance

Sudden Aspen Mortality Management (Worrall et al. 2014)

•	 Use coppice cutting to promote the regeneration of stands with <50% mortality, above 50% mortality has been shown to 

have little regeneration potential (Shepperd et al. 2015). 

•	 Ensure there are significant patches of aspen trees <40 years old on the landscape as these trees are less susceptible 

to drought

•	 Classify aspen habitat by suitability of future climate. Facilitate migration to new areas where suitable climate exists.

•	 Improve resilience by reducing stressors (as listed above)

 a

 Note: Outplanting aspen in the wild has been found not to be very successful in Steamboat Springs, Colorado. W. Shepperd found a 50% loss of 

plantings even though a drip irrigation system was going to each plant (Dale Bartos (2015) personal communication).
48 USDA Forest Service RMRS-GTR-366. 2017.

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Appendix A—Aspen Ecosystem Vulnerability Assessment

Vulnerability Assessment Development Process

The information in this literature-based vulnerability assessment involved three sets 

of reviews to vet the structure and content of the information:

•  A first draft was compiled based on searches of literature relevant to the seven 

vulnerability criteria (table A1) for aspen ecosystems. Information was interpreted 

and synthesized to pull out key points relevant to the vulnerability criteria. This 

draft was reviewed by the Uinta-Wasatch-Cache and Ashley National Forests 

staff. Suggestions for structure of content and ecological information specific to 

the Uinta-Wasatch-Cache and Ashley National Forests were implemented in a 

second draft.

•  The second draft was reviewed by experts and suggestions for clarifications and 

additions of scientific information. Their assessment of vulnerability scores for 

each criterion was incorporated in a third draft.

•  The third draft was reviewed by the Uinta-Wasatch-Cache and Ashley National 

Forests staff before submission to publication.

Summary of Uinta-Wasatch-Cache and Ashley National Forests 

Aspen Ecosystem Vulnerability

Climate change vulnerability across the indicators was derived from the qualitative 

literature summaries of available science. Categories for each of the seven vulnerability 

criteria spanned from moderate to very high with overall vulnerability of aspen ecosystems as moderate. Sensitivity to Extreme Climatic Events and Likelihood of Managing 

or Alleviating Climate Change Effects was assigned High vulnerability, and all other 

criteria were assigned a moderate rating. The average of these seven criteria fall in the 

moderate category.

Table A1—Wasatch Range and Uinta Mountain vulnerability score by criteria and 

the overall vulnerability score.

Vulnerability criteria Vulnerability

Range shift capacity Moderate 

Vulnerability of cold-adapted, foundation or keystone species Moderate

Sensitivity to extreme climatic events High

Intrinsic adaptive capacity Moderate

Dependence on specific hydrologic condition Moderate 

Potential for climate change to exacerbate the effects of nonclimate stressors, or vice versa Moderate 

Likelihood of managing or alleviating climate change effects High 

Overall vulnerability Moderate 
62 USDA Forest Service RMRS-GTR-366. 2017.

Appendix B—Climate Model Projections

Projections for Temperature and Precipitation (CMIP5)

Table B1—Projected changes in temperature and precipitation from 1981–2010 to 2035–2064 for 

northeastern Utah Climate Division 5, combined for 231 model runs of RCP 2.6, RCP 4.5, RCP 

6.0, and RCP 8.5. See figs. 6 and 7 for graphs of projections of RCP 4.5 that are not graphed 

below.

Projected changes by 2035–2064a Mean 10th 50th 90th

Change in annual average temperature (°F) 3.8 2.2 3.7 5.8

Change in annual average precipitation (%) 4.0 –6.0 3.1 14.4

a

 Projections are based on 231 model runs from 1/8° CMIP5 BCSD (bias-correction and 

spatial disaggregation) including all Representative Concentration Pathways (RCPs). See 

Appendix C for Models. Accessed from: http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/

dcpInterface.html.

Figure B1—Annual and seasonal temperature change projections for 2035–2064 relative to 1981–2010 for 

the Representative Concentration Pathway (RCP) 2.6. There are 53 model runs included in this projection.
USDA Forest Service RMRS-GTR-366. 2017. 63

0	

1	

2	

3	

4	

5	

6	

7	

8	

Annual	 Winter		 Spring	 Summer	 Fall	

Mean	temperature	change	(°F)	

0	

1	

2	

3	

4	

5	

6	

7	

8	

Annual	 Winter		 Spring	 Summer	 Fall	

Mean	temperature	change	(°F)	

Figure B2—Annual and seasonal temperature change projections for 2035–2064 relative to 1981–2010 for 

the Representative Concentration Pathway (RCP) 6.0. There are 37 model runs included in this projection.

Figure B3—Annual and Seasonal temperature change projections for 2035–2064 relative to 1981–2010 for 

the Representative Concentration Pathway (RCP) 8.5. There are 70 model runs included in this projection.
64 USDA Forest Service RMRS-GTR-366. 2017.

-25	

-20	

-15	

-10	

-5	

0	

5	

10	

15	

20	

25	

30	

Annual	 Winter		 Spring	 Summer	 Fall	

Precipita9on	change	(%)	

-25	

-20	

-15	

-10	

-5	

0	

5	

10	

15	

20	

25	

30	

Annual	 Winter		 Spring	 Summer	 Fall	

Precipita9on	change	(%)	

Figure B4—Annual and seasonal precipitation percent change projection for 2035–2064 relative to 1981–

2010 for the Representative Concentration Pathway (RCP) 2.6. There are 53 model runs included in this 

projection.

Figure B5—Annual and seasonal precipitation percent change projection for 2035–2064 relative to 1981–

2010 for the Representative Concentration Pathway (RCP) 6.0. There are 37 model runs included in this 

projection.
USDA Forest Service RMRS-GTR-366. 2017. 65

-25	

-15	

-5	

5	

15	

25	

35	

Annual	 Winter		 Spring	 Summer	 Fall	

Precipita8on	change	(%)	

Figure B6—Annual and seasonal precipitation percent change projection for 2035–2064 relative to 1981–

2010 for the Representative Concentration Pathway (RCP) 8.5. There are 70 model runs included in this RCP 

projection.
66 USDA Forest Service RMRS-GTR-366. 2017.

Appendix C—Coupled Model Intercomparison Project 

Phase 5

We acknowledge the World Climate Research Programme’s Working Group on 

Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in table C1 of this paper) 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.

Table C1—Climate Modeling Groups for CMIP5.

Modeling center (or Group) Institute ID Model name

Commonwealth Scientific and Industrial Research Organization 

(CSIRO) and Bureau of Meteorology (BOM), Australia CSIRO-BOM ACCESS1.0ACCESS1.3

Beijing Climate Center, China Meteorological Administration BCC BCC-CSM1.1

BCC-CSM1.1(m)

Instituto Nacional de Pesquisas Espaciais (National Institute for 

Space Research) INPE BESM OA 2.3a

College of Global Change and Earth System Science, Beijing 

Normal University GCESS BNU-ESM

Canadian Centre for Climate Modelling and Analysis CCCMA

CanESM2

CanCM4

CanAM4

University of Miami - RSMAS RSMAS CCSM4(RSMAS)

National Center for Atmospheric Research NCAR CCSM4

Community Earth System Model Contributors NSF-DOE-NCAR

CESM1(BGC)

CESM1(CAM5)

CESM1(CAM5.1,FV2)

CESM1(FASTCHEM)

CESM1(WACCM)

Center for Ocean-Land-Atmosphere Studies and National Centers for Environmental Prediction COLA and NCEP CFSv2-2011

Centro Euro-Mediterraneo per I Cambiamenti Climatici CMCC

CMCC-CESM

CMCC-CM

CMCC-CMS

Centre National de Recherches Météorologiques / Centre Européen de Recherche et Formation Avancée en Calcul Scientifique

CNRM-CERFACS

CNRM-CM5

CNRM-CM5-2

Commonwealth Scientific and Industrial Research Organization in collaboration with Queensland Climate Change Centre of 

Excellence

CSIRO-QCCCE CSIRO-Mk3.6.0

EC-EARTH consortium EC-EARTH EC-EARTH

LASG, Institute of Atmospheric Physics, Chinese Academy of 

Sciences and CESS,Tsinghua University LASG-CESS FGOALS-g2
USDA Forest Service RMRS-GTR-366. 2017. 67

LASG, Institute of Atmospheric Physics, Chinese Academy of 

Sciences LASG-IAP FGOALS-glFGOALS-s2

The First Institute of Oceanography, SOA, China FIO FIO-ESM

NASA Global Modeling and Assimilation Office NASA GMAO GEOS-5

NOAA Geophysical Fluid Dynamics Laboratory NOAA GFDL

GFDL-CM2.1

GFDL-CM3

GFDL-ESM2G

GFDL-ESM2M

GFDL-HIRAM-C180

GFDL-HIRAM-C360

NASA Goddard Institute for Space Studies NASA GISS

GISS-E2-H

GISS-E2-H-CC

GISS-E2-R

GISS-E2-R-CC

National Institute of Meteorological Research/Korea Meteorological Administration NIMR/KMA HadGEM2-AO

Met Office Hadley Centre (additional HadGEM2-ES realizations 

contributed by Instituto Nacional de Pesquisas Espaciais)

MOHC

(additional realizations by INPE)

HadCM3

HadGEM2-CC

HadGEM2-ES

HadGEM2-A

Institute for Numerical Mathematics INM INM-CM4

Institut Pierre-Simon Laplace IPSL

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 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

MIROC MIROC4h

MIROC5

Max-Planck-Institut für Meteorologie (Max Planck Institute for 

Meteorology) MPI-M

MPI-ESM-MR 

MPI-ESM-LR

MPI-ESM-P

Meteorological Research Institute MRI

MRI-AGCM3.2H

MRI-AGCM3.2S

MRI-CGCM3

MRI-ESM1

Nonhydrostatic Icosahedral Atmospheric Model Group NICAM NICAM.09

Norwegian Climate Centre NCC NorESM1-M

NorESM1-ME

a

 Model output not yet available.
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