1.2.1. Regional Climate Projections and Uncertainties for the Sagebrush Region

Compared to temperatures from the baseline period from 1980 to 2010, predicted future temperatures for the sagebrush region include a median annual increase under representative concentration pathway (RCP) 4.5 of 1.5 °C by 2050, and 2.0 °C by 2100 (Palmquist and others, 2021). Under RCP8.5, the projected increases in temperature are more than double those increases expected under RCP4.5, which emphasizes the importance of considering various emission scenarios when assessing climate impacts (U.S. Global Change Research Program, 2017).

Regional precipitation projections are more complex than those projections for temperature. Under RCP4.5, the median change in annual precipitation is relatively modest and has an increase of less than 20 millimeters (U.S. Global Change Research Program, 2017). However, some parts of the sagebrush range are projected to experience substantial increases in precipitation and exceed 100 millimeters by the end of the century (Bradford and others, 2020; U.S. Global Change Research Program, 2017). Other parts, especially in the southern part of the region, may have a decline in precipitation that further decreases soil water availability; when coupled with increases in temperature, this decline will decrease habitat suitability for sagebrush (Palmquist and others, 2021; Doherty and others, 2022).

Rising temperatures and shifting precipitation will alter seasonal patterns of soil moisture availability (Bradford and others, 2020). Interannual variability and the frequency of extreme weather events represent large sources of uncertainty among GCMs. Although there is no consensus across GCMs with respect to changes in precipitation, most agree that the intensity and frequency of extreme weather events will increase with rising temperatures (Breshears and others, 2016; Armal and others, 2018). Under RCP8.5, the impact of extreme weather events will be more severe than RCP4.5 (U.S. Global Change Research Program, 2017).

All climate projections are made with some degree of uncertainty, and the projected changes differ across emissions scenarios further amplify that uncertainty. However, managing natural resources has always involved uncertainty about fluctuations in climate and biotic populations. The uncertainty about changes in precipitation and temperatures and enhanced variability presents additional challenges. Resource management professionals may want to focus on conserving existing diversity and ecosystem functionality while being aware of the degree of uncertainty and planning for timelines consistent with expected responses.

1.3.1. Big Sagebrush

Big sagebrush is the dominant species in big sagebrush plant communities and is especially abundant in sagebrush ecosystems. Limited research has been done on the response of big sagebrush to CO₂ enrichment. Big sagebrush may improve water-use efficiency when CO₂ levels are temporarily elevated (Lucash and others, 2005); however, the implications of prolonged CO₂ enrichment on long-term big sagebrush growth and survival and ecosystem dynamics are unknown. The long-term effects of elevated CO₂ concentrations on big sagebrush may be restricted as plant growth becomes limited by other resources (for example, water and nutrients) after plants have acclimated to elevated CO₂ conditions. This limitation by other resources has been observed in other ecosystems (Idso and Idso, 2001; Ainsworth and Long, 2005).

Experimental temperature manipulations on big sagebrush have shown different results depending on ambient climate conditions. In high elevations and in cool sites, experimental warming tends to increase aboveground biomass and growth rate of big sagebrush (Harte and Shaw, 1995; Perfors and others, 2003). However, some studies suggest that temperature increases do not necessarily improve sagebrush photosynthetic performance (Loik and Harte, 1996). In contrast, at low-elevation sites, warming has had a negative effect by reducing the reproductive capacity of big sagebrush (Karban and Pezzola, 2017). This decrease in reproductive success can limit seedling recruitment and, ultimately, its survivability in these areas.

Precipitation has a large effect on big sagebrush performance (table 2). Sagebrush may benefit from increasing cool-season precipitation. Bates and others (2006) found that fall precipitation had a significant positive effect on big sagebrush growth. Furthermore, large precipitation events have been associated with increased sagebrush growth (Holdrege and others, 2021). Precipitation reduction experiments have shown declines in sagebrush growth and reproductive capacity after multiple years of treatment. Seedling establishment experiments with reduced precipitation found that seedlings are less likely to sprout and survive past a year or two (Booth and Bai, 2000; Shriver and others, 2018; Schlaepfer and others, 2021).

Extreme weather events and climatic variability can play a large role in shaping sagebrush plant communities. Interannual variability in precipitation can strongly affect seedling establishment in mature sagebrush stands, and an increase in drought frequency may lead to population declines (Karban and Pezzola, 2017). Karban and Pezzola (2017) also found an increase in flower production during a multiyear drought followed by branch die-off. High-temperature drought conditions can even lead to stand mortality, particularly when extreme droughts are followed by heavy precipitation (Renne, Schlaepfer, and others, 2019). Additionally, the increasing frequency of heavy downpours may cause mortality by inducing anoxic root conditions through flooding (Renne, Schlaepfer, and others, 2019). Seedling recruitment is also affected by current and recent past conditions, primarily temperatures and soil moisture (Bishop and others, 2020).

The response of big sagebrush to climate change is likely multifaceted and contingent on location and climate conditions. Although big sagebrush in some regions may experience benefits from temperature and precipitation shifts, the southern part of its range may have population declines because of reduced water availability. Moreover, increasing variability and extreme weather events are likely to have negative effects on sagebrush.

1.3.2. Other Evergreen (Semideciduous) Shrubs

In addition to big sagebrush, other shrub species, such as Purshia tridentata (Pursh) DC. (antelope bitterbrush) or Grayia spinosa (Hook) Moq. (spiny hopsage) contribute to early successional communities and provide key forage resources for wildlife within sagebrush ecosystems. Nondominant shrubs include many species with different life histories in various climatic and soil conditions within big sagebrush landscapes. Consequently, the response to climate change likely varies among species. This section discusses the results of studies on these nondominant shrub species in big sagebrush communities; however, there is a large knowledge gap in the understanding of how climate impacts these species.

Increased atmospheric CO₂ can improve water-use efficiency in other evergreen shrubs, which suggests a potential positive effect on their water conservation abilities (Hamerlynck and others, 2000). Hamerlynck and others (2000) found that elevated CO₂ levels may lead to some resistance to high-temperature droughts. This resistance indicates a potential advantage for these shrubs to adapt to changing climate conditions. Knowledge about other shrub responses to temperature changes is also limited. Based on general principles, their responses will vary depending on their location, local climatic conditions, and other species present (Kopp and Cleland, 2015). In high-elevation, cool sites, they may benefit from warming, similar to the observed effects in big sagebrush. Conversely, in low-elevation, hot sites, these species could experience detrimental effects on reproductive capacity and overall performance.

The response of other evergreen shrubs to changes in precipitation remains uncertain. Their responses may differ depending on the specific location and the extent of changes in precipitation patterns. Understanding how they adapt to shifts in water availability will be crucial in predicting their survival and ecological role within sagebrush ecosystems. The impacts of extreme weather events and interannual variability on other evergreen shrubs are also understudied. However, given the importance of water availability and temperature for plant growth and survival, it can be assumed that extreme weather events and fluctuations in precipitation and temperature will likely affect their performance and distribution. Although some studies suggest potential benefits, such as improved water-use efficiency and resistance to high-temperature droughts under elevated CO₂ levels (Hamerlynck and others, 2000), further research is needed to fully understand their adaptive strategies in changing climate conditions.

1.3.3. Perennial Bunchgrasses

Grasses are the primary forage resources for livestock, ungulates such as elk, other herbivorous wildlife, and feral horses. Grasses are also the dominant herbaceous plant functional type in most big sagebrush plant communities and vital components of sagebrush ecosystems (Pennington and others, 2019). Understanding the response of bunchgrasses to climate change (table 2) can aid predictions regarding the overall resilience of big sagebrush plant communities.

Elevated CO₂ experiments have shown mixed results and outcomes vary depending on the photosynthetic type of grasses. Initially, studies suggested that elevated CO₂ levels benefited cool-season (C₃) grass species (Ainsworth and Long, 2005; Lee and others, 2011). However, after prolonged exposure to elevated CO₂ levels, C₃ and warm-season (C₄) grasses show similar performance in water-use efficiency and photosynthetic rate (Hunt and others, 1996). In addition, some studies found that sustained exposure to elevated CO₂ effectively mitigated drought for C₄ grass species (Reich and others, 2018), an effect that was not observed in C₃ grass species (Morgan and others, 2011). Overall, CO₂ enrichment has a relatively minor role in determining grass responses to climate change compared with changes in temperature and precipitation.

The expected shifts in precipitation seasonality in areas with little change to annual precipitation or projected increases may cause increases in water availability beyond depths that are accessible to most perennial grass species (Palmquist and others, 2016; Jordan and others, 2020). However, the effects may differ in wet areas of the sagebrush region, particularly in high-elevation sites where shorter snowpack durations and increased rainfall can increase water availability for perennial bunchgrasses (Bates and others, 2006). Other studies have found that in the short-term, perennial grasses are relatively resistant to changes in precipitation regime (Adler and others, 2009). It is also possible that the hydraulic redistribution of water by woody species may buffer perennial grass response to increases in deep soil water availability (Richards and Caldwell, 1987; Lee and others, 2018). However, no experimental study has looked at the role of hydraulic redistribution under altered precipitation regimes and warmer temperatures.

Cool-season grasses are generally the dominant functional type across the northern part of the sagebrush region. Warm-season grasses tend to have higher proportional cover in the warmer southern parts of the region, but some grasses are present in pockets across the region (Havrilla and others, 2023). Cool-season species are generally negatively affected by temperature increases, particularly towards the end of their growing season (Williams and others, 2007); however, grasses show resilience to the adverse effects of high temperatures (Munson and others, 2011). Warm-season species benefit from increased temperatures, and elevated temperatures can increase productivity provided that water availability remains sufficient (Du and others, 2011). Temperature changes can also affect flowering time. Increased temperature can advance C₃ grass flowering time and potentially delaying C₄ species (Hartman and Nippert, 2013).

Perennial bunchgrasses show some degree of acclimation to short periods of high temperature with extreme weather and climate variability. They also show resistance to moderate drought conditions but not to extreme droughts (Seleiman and others, 2021). Elevated CO₂ has been found to alter the resilience of grasses to extreme droughts. However, the resilience is species specific and related to how different species store sugars, which suggests that some species will be more adapted to increased interannual variability (Bushey and others, 2023). Additionally, the type of sustained or repeated drought can affect grass responses (Winkler and others, 2019). Increasing variability in climate conditions may ultimately decrease overall productivity because of decreased abundance (Gherardi and Sala, 2015).

The responses of perennial bunchgrasses to climate change are complex and depend on their photosynthetic pathway type, as well as overarching climate and soil conditions. Although CO₂ enrichment may have positive effects on perennial bunchgrasses, changes in temperature and precipitation appear to be more significant drivers of responses. These responses are likely to favor C₄ species with increasing annual temperatures (Du and others, 2011; Morgan and others, 2011). However, decreases in precipitation in dry parts of the region are likely to negatively affect all grasses (Shi and others, 2020). Finally, increased interannual variability and drought conditions will have a negative effect on productivity and abundance of perennial bunchgrasses, and resilience will vary at the species level (Havrilla and others, 2023).

1.3.4. Perennial Forbs

Perennial forbs constitute the largest number of species in sagebrush ecosystems, and their responses to climate change will shape the potential future biodiversity of these communities. Perennial forbs have variable responses to climate change factors (table 2). Their interactions with CO₂, temperature, precipitation, and extreme weather events are affected by their functional role and regional conditions. One general trend is a shift toward earlier flowering dates, particularly for spring species, such as Phlox hoodii Richardson (spiny phlox) or Balsamorhiza sagittata (Pursh) Nutt. (arrowleaf balsamroot). Outside of core sagebrush areas, especially in the southern part of the region, there may be a decline in perennial forb productivity and species richness because of a decrease in water availability (Pennington and others, 2019). Finally, although perennial forbs may be resilient to low levels of drought and increased variability, the projected increase in the frequency of extreme weather events and multiyear droughts is likely to have negative effects on productivity and species richness across the region (Munson and others, 2013).

Although the understanding of forb responses to CO₂ enrichment is limited, studies of dryland forb species show that CO₂ enrichment can have a range of effects, especially when considered with other climate variables and human-caused disturbances. Notably, one study found a reduction in forb productivity and fractional cover when exposed to elevated CO₂ and nitrogen deposition (Crous and others, 2010), whereas the same treatment had a positive effect on forb species in a Mediterranean-climate annual grassland system (Zavaleta and others, 2003). However, across most studies, forb response was not related to CO₂ treatment; instead, it was dominated by the variability of temperature and precipitation among years (Zavaleta and others, 2003, Lee and others, 2011).

Observational studies suggest that perennial forbs in big sagebrush communities are already beginning to have phenological responses to increases in temperature. Flowering has advanced as much as 17 days for early-season species (Bloom and others, 2022). Although temperature has shown negligible effects on photosynthetic rates in some forb species (Loik and Harte, 1996), prairie warming experiments revealed long-term negative effects on forb cover (Morgan and others, 2011). The response of forbs to temperature increases will likely be variable as a functional group; some species benefit from warmer temperatures, whereas others respond negatively, depending on their ecological niche (Lee and others, 2011). One potential general trend for forb species is the reduction of total species number in parts of the sagebrush region where temperature increases will shorten the overall growing season (Cross and Harte, 2007). This trend is consistent with relationships that show species richness decreases in big sagebrush communities as mean annual temperature increases and water availability declines (Jordan and others, 2020).

Responses to precipitation regimes may also be species specific and depend on functional roles. In general, forbs seem to be more responsive to changes in year-to-year precipitation variability than average precipitation levels (de Valpine and Harte, 2001). However, long-term reductions in precipitation in the southern part of the sagebrush region may reduce overall species richness and productivity of forbs, which is consistent with the general species richness and productivity relationship for dryland ecosystems (Maestre and others, 2012).

Interannual variability of precipitation and temperature are controls on forb cover and apparent richness (Zavaleta and others, 2003; Lee and others, 2011). As climate change progresses, the persistence of forb species in big sagebrush ecosystems is likely to be strongly affected by climatic variability.

1.3.5. Invasive Species

The spread of invasive species, including annual grasses and short-lived forbs, is becoming an important topic when discussing the potential future structure and function of sagebrush ecosystems. However, the understanding of invasive species responses to climate change remains limited. Elevated CO₂ studies specifically focused on invasive annual grasses and how CO₂ enrichment may affect the performance and dynamics of invasive species in sagebrush ecosystems are limited. Consequently, responses of invasive annual grasses to elevated CO₂ levels have not been extensively studied, although Blumenthal and others (2016) found no positive effect of CO₂ enrichment on cheatgrass in a grassland system.

Temperature changes can profoundly affect the phenology and growth patterns of invasive annual grasses. Observational studies have shown that temperature increases are already affecting the flowering and growth timing of these species (Boyte and others, 2016). These studies have also shown that increases in temperature are correlated with higher invasive annual grass biomass (Howell and others, 2020), which is consistent with experimental warming studies (Blumenthal and others, 2016). Temperature increases will also decrease snowpack, which has been linked to an increase in cheatgrass survivability and establishment (Compagnoni and Adler, 2014a, b; Smull and others, 2019).

The timing of precipitation often determines the success and abundance of invasive annual grasses. Although the response of invasive annual grasses to average precipitation levels remains understudied, their population dynamics are affected by interannual variability in precipitation (Copeland and others, 2019). Variability in year-to-year precipitation patterns can have positive and negative effects on growth, reproductive success, and overall abundance of invasive annual grasses within sagebrush ecosystems (Shriver and others, 2018). Because annuals are dependent on seeds between generations, the presence of a seed bank can facilitate the survival of invasive annual grasses through unfavorable weather (Copeland and others, 2019).

Invasive annual grasses may also be resilient to extreme weather events, such as droughts and fluctuations in temperature. For example, drought may indirectly increase cheatgrass abundance by increasing wildfire probabilities and perpetuating the cheatgrass–wildfire cycle (Coates and others, 2016). The ability of invasive annual grasses to cope with these extremes may depend on the availability of moisture resources, timing and duration of weather, and the overall sensitivity of the invasive annual grass populations (Williamson and others, 2020). Understanding how invasive annual grasses respond to extreme weather events is critical for predicting climate change impacts on their dynamics and persistence.

Understanding the responses of invasive annual grasses to climate change in sagebrush ecosystems is primarily limited to the most prevalent invader, cheatgrass. More research is needed to explore how CO₂ enrichment, temperature changes, alterations in precipitation patterns, and extreme weather events will affect the dynamics of other invasive plant populations. Similar to cheatgrass, other invasive annual grasses are likely to spread into core sagebrush habitat as climate change progresses and impacts the ecological functioning of sagebrush ecosystems (Doherty and others, 2022). Potential future research on the responses of other invasive annual grass species to climate change will be essential for effective conservation and management strategies for big sagebrush plant communities.

1.4.1. Insights About Climate Effects From Species Distribution Models

Species distribution models integrate observed locations of plant functional types or species with environmental variables (primarily climate and potentially soil) to characterize environmental suitability for a species. Projections of environmental suitability can be contrasted with these definitions of environmental suitability for a species to determine how the geographic distribution of areas that can support that species may change under altered climate conditions (table 3).

In the sagebrush region, big sagebrush is the most frequently modeled species, and multiple efforts map its current and potential range using various factors such as climate, ecohydrology, and existing land use (Shafer and others, 2001; Bradley, 2010; Schlaepfer and others, 2012b; Still and Richardson, 2015; Tredennick and others, 2023a). Often, the distribution of sagebrush ecosystems is based on the range of big sagebrush and the assumption that it is an umbrella species representing other components of the plant community, such as perennial bunchgrasses and forbs (Tredennick and others, 2023a).

Big sagebrush is in a diverse range of temperature conditions and seasonal precipitation patterns. However, the species is primarily in regions where a substantial amount of precipitation falls during the cool season and can percolate to the deep soil layers (Schlaepfer and others, 2012b). Schlaepfer and others (2012b) defined this ecohydrological niche as conditions that are critical for suitable habitat to support big sagebrush and found that results from their SDM built upon ecohydrological variables generally aligned with traditional climatic SDM results. Ecohydrological and climatic SDMs indicate that the south edge of the sagebrush range is expected to move northward because of higher temperatures and decreased precipitation (Still and Richardson, 2015; Tredennick and others, 2016). The east edge of the big sagebrush range that borders the Great Plains may move westward because of an increase in summer precipitation that favors herbaceous species (Still and Richardson, 2015). Consistent predictions from these models indicate that big sagebrush is likely to expand its range in the northern part of its distribution (Renwick and others, 2018). As temperatures increase, big sagebrush is also projected to expand into high elevations (Bradford and others, 2014). These results are consistent with state-level distribution modeling efforts (Homer and others, 2012) and provide insights into how big sagebrush populations may respond to ongoing climate change. All the SDMs emphasize the importance of considering ecohydrological and climatic conditions when predicting potential future species distributions in the sagebrush region.

The use of big sagebrush as a representative and an umbrella species allows researchers to model and infer the potential climate change impacts on sagebrush ecosystems and other species such as perennial bunchgrasses and forbs. Scientists can use SDMs to begin exploring how climate-induced changes in sagebrush distribution may cascade through the entire ecosystem and impact the ecological dynamics of these valuable habitats. However, understanding the response of a single species may provide only limited information on the potential shifts in distribution for other key functional types.

Species distribution models for subdominant species have received limited attention, and further research in this area is needed. The SDMs for perennial C₃ grass species indicate a range expansion at the north edge of their distributions (Havrilla and others, 2023). The SDMs for C₄ grass species indicate a more substantial increase in expected range, and particularly in areas dominated by C₃ perennial grass species (Havrilla and others, 2023). This predicted shift from C₃ suitability to C₄ suitability is consistent with process-based modeling projections (Palmquist and others, 2021). The distribution of forb species has been overlooked, and there have been no attempts to create SDMs that incorporate climate change-induced range shifts for species in this functional type. There are few SDMs available for many of the abundant forb species in the sagebrush region (Barga and others, 2018) despite their relevance as forage species for greater sage grouse (Pennington and others, 2016) and pygmy rabbits (Germaine and others, 2020).

There have been more attempts to develop SDMs for invasive species because of their ecological effect and high economic cost (Maher and others, 2013; Chambers and others, 2019). However, most of these SDMs focus on the current distribution of individual species rather than modeling their potential range under climate shifts (Tarbox and others, 2022). Modeling products for invasive annual grass species were reviewed by Tarbox and others (2022) and have an accompanying dataset collection in Shyvers and others (2022). Cheatgrass is one invasive species for which SDMs have been developed; two SDMs developed by Bradley (2009) and Bradley and others (2016) predict the shift in suitability of cheatgrass under projected climate changes across the sagebrush region. Both SDMs indicate an expansion in cheatgrass habitat into parts of the Intermountain West because of a decrease in summer precipitation and increased temperatures (Bradley, 2009; Bradley and others, 2016). The most recent SDM projects a decline in cheatgrass suitability in the southern part of the Great Basin where temperature increases and precipitation declines will reduce habitat for C₃ annual grasses (Bradley and others, 2016).

1.4.2. Plant Community Response Types to Climate Change Based on Observed or Experimental Studies

This section reviews climate change impacts on sagebrush plant communities by examining experimental studies that manipulate single or multiple climate variables. Unlike the potential climate change effects estimated in SDMs, experimental studies provide insights into local to landscape-scale expectations of climate change effects and potential threats that shape community-level responses to climate change.

This section includes various experimental approaches (fig. 3), such as space-for-time substitutions, experimental warming, precipitation shifts, and CO₂ enrichment experiments (Harte and Shaw, 1995; Bates and others, 2006; Jordan and others, 2020). Multiple response types observed for plant communities that are affected by local environmental factors including the prevailing climate were identified. Different response types are framed by their resistance and (or) resilience to compositional shifts in big sagebrush plant communities. The following response types were defined:

These response types help describe how big sagebrush plant communities may resist or adapt to climate-induced changes and identify the pathways through which these communities may change because of ongoing environmental shifts.

1.4.3. Modeling Region-Wide Effects of Climate Change on Big Sagebrush Plant Communities

Five response types identified in section 1.4.2. “Plant Community Response Types to Climate Change Based on Observed or Experimental Studies” highlight possible trajectories of plant communities within the sagebrush region. However, because of the limited spatial and temporal scope of field studies, these response type categories do not completely capture the potential effects of climate change on big sagebrush plant communities at regional (for example, multi-State) and long-term (for example, multidecadal) scales.

There are multiple methods for modeling how shifts in climate will impact the suitability of big sagebrush plant communities, including process-based and statistical models (refer to sec. 3.3. “Analytical Approaches for Assessing Potential Long-Term Effects of Climate Change on Plant Communities” for further description). Studies assessing potential geographically broad shifts in climatic suitability for big sagebrush plant communities can complement findings from individual field studies. This section discusses how the results of these plant community-level efforts overlap and identifies aspects of consistency or divergence with other types of studies described previously.

All available studies that examine community-level climate change effects in big sagebrush ecosystems consider the effects on big sagebrush suitability. A few studies focus on modeling climatic suitability for the big sagebrush plant community (Doherty and others, 2022). Some studies use big sagebrush as an umbrella species (Schlaepfer and others, 2021; Tredennick and others, 2023a) to represent potential effects on the broader plant community. Other studies model projected shifts in climate suitability for individual plant functional types within big sagebrush plant communities (Palmquist and others, 2021; Rigge, Shi, and Postma, 2021; Zimmer and others, 2021).

For most models, big sagebrush is expected to remain viable across much of the sagebrush region under the moderate emissions RCP4.5 and the higher emissions RCP8.5 (Palmquist and others, 2021; Rigge, Shi, and Postma, 2021; Zimmer and others, 2021) and under the new shared socioeconomic pathway (SSP) climate scenarios SSP4.5 and SSP8.5 (Tredennick and others, 2023a). The areas of sustained climatic suitability for big sagebrush plant communities overlap with the areas identified as core habitat (for example, abundant big sagebrush and perennial grasses with minimal annual grasses, human effects, or conifers) by Doherty and others (2022). Schlaepfer and others (2021) found that regeneration across some of the areas of stability will be negatively affected under RCP8.5.

Projections of geographic patterns of big sagebrush response to climate change can vary among studies. Most models project declines in climatic suitability at the southern part of the sagebrush range and are consistent with most field experiments and observations (Palmquist and others, 2021; Schlaepfer and others, 2021; Zimmer and others, 2021). However, this pattern is not fully supported by Rigge, Shi, and Postma (2021) projections for sagebrush cover under RCP8.5, which showed moderate declines in cover in the northern part of the range and little change in the southern part of the range. Rigge, Shi, and Postma (2021) project a loss in sagebrush cover in parts of Montana under RCP8.5, which is consistent with other models using this climate scenario (Palmquist and others, 2021). Other projections suggest either minimal changes to sagebrush suitability (Zimmer and others, 2021) or increases in climatic suitability by mid-21st century (Palmquist and others, 2021), which may indicate that the RCP8.5 for the end of the century is an extreme scenario. Models are also split on the expansion of big sagebrush climatic suitability at high-elevation sites (Palmquist and others, 2021; Zimmer and others, 2021). Despite the differences in the projected responses of climatic suitability for big sagebrush across models, most conclude that shifts in suitability will be small. Instead, the interactive effects of climate with disturbances and invasive species may affect most of the region. All models suggest that these interactive effects are important areas for potential future research.

Beyond shifts in climatic suitability for big sagebrush, climate change is likely to impact the composition of grasses and forbs across the region. Only Rigge, Shi, and Postma (2021) and Palmquist and others (2021) independently project shifts in the suitability for herbaceous functional types. Zimmer and others (2021) project shifts in total forage availability but do not differentiate plant functional types within that group. Rigge, Shi, and Postma (2021) and Palmquist and others (2021) project increases in suitability for perennial herbaceous species across most sagebrush plant communities in Wyoming and Colorado, but project decreases in the southern part of the range. Zimmer and others (2021) project consistent forage increases. All three studies project decreases in forage or perennial herbaceous species across most of the southern parts of the big sagebrush region except in some high-elevation areas (Palmquist and others, 2021; Rigge, Shi, and Postma, 2021; Zimmer and others, 2021), which is consistent in areas with observed increases in bare ground and similar climatic conditions (Shi and others, 2018). Palmquist and others (2021) is the only study to separate C₃ and C₄ perennial grasses, which make up the largest component of forage in most of the sagebrush region. They projected decreases in the biomass of C₃ species and potential increases in the biomass of C₄ species, which may indicate that replacement of C₃ species as climate change progresses (Palmquist and others, 2021). This potential regional shift in relative biomass of C₃ compared to C₄ grasses is consistent with Havrilla and others (2023) species distribution models for C₃ and C₄ perennial grasses.

Climate change may also affect the severity of invasive or locally nonnative species that alter big sagebrush plant communities. Although little is known about how cheatgrass and conifers will interact to affect big sagebrush plant communities in the future, Zimmer and others (2021) suggested that potential future climate conditions may limit the expansion of conifers, but the potential for conifer expansion varies substantially among the climate models evaluated in their study.

2.1.1. Category One—Increased Ecohydrological Growing Season Length and Increased Precipitation

In areas that are projected to have a Category One impact, the overall consequence will be positive for livestock grazing with increased production and an extended growing season. However, management will need to monitor the woody component of plant communities to be aware of possible increases. The primary high confidence consequence of climate change is increasing temperatures, which is the expected main driver of any projected shifts in areas with climate conditions that support big sagebrush (Kleinhesselink and Adler, 2018; Renwick and others, 2018). At the north edge of their range and in high-elevation sites, forage grass and forb species are expected to benefit from higher temperatures because of an extended ecohydrological growing season. This benefit is because of an increase in growing degree days that leads to an increase in aboveground production (Schlaepfer and others, 2012a; Palmquist and others, 2016; Renwick and others, 2018). Additionally, the phenology of herbaceous species is likely to advance as snowpack melts earlier (Bloom and others, 2022). This advancement in phenology is likely to lengthen the livestock grazing season.

The northeast edge of the big sagebrush region and some high-elevation sites are projected to experience increased precipitation (fig. 2), which can also result in an increase in forage production. The timing and amount of precipitation determine water availability at different depths within the soil profile and the competitive advantage of either herbaceous or woody species (Schlaepfer and others, 2012a; Lauenroth and others, 2014; Renne, Schlaepfer, and others, 2019). Most precipitation increases are expected to occur in the late fall and early spring (Palmquist and others, 2016). As precipitation occurrences become larger or happen during cooler periods, a greater proportion of water will percolate to deep soil layers and make it less accessible to forage species and more favorable for woody species (Holdrege and others, 2021, 2023). In locations such as northern Montana and the upper Green River Basin in Wyoming, the projected increase in production would benefit forage species, but it may also increase big sagebrush cover and abundance. Northern Montana and the upper Green River Basin in Wyoming represent locations with expected forage increases. Although other areas across the big sagebrush region may experience increases in productivity, it is also possible that slow plant response to rapid climate change may lead to lower overall productivity by the end of the 21st century (Felton and others, 2022).

2.1.2. Category Two—Increased Ecohydrological Growing Season Length With Decreased or Static Precipitation

In areas that are projected to have a Category Two impact may likely be the most stable areas within the big sagebrush region. It is expected that the longer growing season length, through increased plant growth potential during the early spring season (Bradford and others, 2020) will benefit herbaceous species, thereby promoting the production of forage and reducing bare ground. The largest threat to big sagebrush plant communities under these conditions is an increase in suitability for invasive annual grasses. Cheatgrass completes its seasonal growth cycle early in the year (Harris, 1967), and benefits from an advanced growing season and reduced snowpack (Compagnoni and Adler, 2014b; Smull and others, 2019181). Consequently, high-elevation sites that have previously been resistant to cheatgrass establishment may experience an increase in cheatgrass abundance, which would reduce forage availability. However, high cover of C₃ perennial bunchgrasses can sometimes decrease the probability of cheatgrass invasion (Chambers and others, 2014). Management of high-elevation communities, such as in the intermountain parts of Colorado, Nevada, and Utah, may benefit from monitoring to identify areas of nonnative plant establishment before they reach critical abundance levels (Chambers, Maestas, and others, 2017).

For livestock grazing, areas with a Category Two impact could have an increase in the growing season length that advances the phenology of forage species such that grazing may begin earlier in the year to capitalize on earlier spring production. Thus, an increase in forage production may enable increases is animal stocking rates in these areas. However, any decision to increase grazing intensity may need to consider perennial bunchgrass cover and monitor to ensure that cover either increases or is stable to minimize the establishment of nonnative species.

2.1.3. Category Three—Decreased Ecohydrological Growing Season Length and Increased Precipitation

Areas that are projected to have a Category Three impact will likely represent a smaller part of the sagebrush region than Categories One or Two impacts. Similar to Category Two impacts, Category Three impacts represents relative stability in potential future forage production. Areas likely to experience these conditions include parts of the Great Basin and the Colorado Plateau. The decrease in the ecohydrological growing season is because of the extended time when potential evapotranspiration exceeds precipitation in the spring and fall, which decreases water availability for plant growth. This decrease is likely to reduce the overall production of forage species. In addition, most of the precipitation increase is expected to occur in the late fall and early spring (Palmquist and others, 2016) and the amount of precipitation is likely to increase (IPCC, 2022). Studies that simulate both changes have demonstrated that this precipitation regime is most likely to favor woody species more than perennial grasses similar to the Category One impact (Bates and others, 2006; Holdrege and others, 2021).

Shifts in seasonal and soil depth patterns of soil moisture availability under the Category Three impact conditions suggest the primary consequence will be a shift in growing season rather than an increase in forage production. This shift toward warmer, drier conditions may increase climatic suitability for C₄ perennial grass species (Palmquist and others, 2021). If a shift toward C₄ grasses occurs, managers may need to consider the later green up of C₄ species in their planning. Under this response category, cheatgrass persistence and establishment is still a threat.

Considering these potential changes in the composition of big sagebrush plant communities, managers may consider three steps when monitoring livestock grazing allotments in areas that are experiencing decreased ecohydrological growing season length and increased precipitation:

2.1.4. Category Four—Decreased Growing Season Length and Decreased or Static Precipitation

Areas that have a projected Category Four impact represent the south edge of the big sagebrush distribution, where most modeling efforts indicate that temperature increases will likely decrease the growing season by increasing evaporative demand at the beginning and end of the thermal growing season. This decrease can thereby reduce soil water availability and accelerate senescence (Bradford and others, 2020; Maurer and others, 2020126). In northern New Mexico and Arizona, forage species are likely to decrease in production (Kleinhesselink and Adler, 2018; Shi and others, 2018) and ultimately reduce available forage for livestock grazing. It is probable that a reduction in livestock grazing may be necessary to ensure the persistence of native species and to prevent the establishment of nonnative species. Furthermore, the shortened ecohydrological growing season may necessitate a reduction in grazing period length.

Overall climatic suitability for big sagebrush and other native perennial species is also expected to diminish under the Category Four impact category. Monitoring efforts may benefit from focusing on quantifying the extent bare ground cover increases that results from the loss of biocrust and perennial grass species.

2.1.5. Interannual Variability and Extreme Events

The growing likelihood of extreme climate is an added complexity to the four impact categories (Parmesan and others, 2000; Smith, 2011). More extreme weather events can directly impact forage production and have lasting effects (Hoover and others, 2014, 2015). Although extreme weather events may affect woody species, big sagebrush has some drought resistance (K.J. Clause and J. Randall, Bureau of Land Management, written commun., 2014; Hoover and others, 2015). By comparison, most herbaceous forage species do not have similar drought resistance; for example, C₃ perennial grasses recover slowly following mortality events (Hoover and others, 2015, Breshears and others, 2016), although they may be resilient on decadal scales.

Beyond extreme weather events, interannual variability in precipitation can affect the production of perennial grasses within big sagebrush communities (Hsu and others, 2012; Gherardi and Sala, 2019; Hou and others, 2021), although this variability may not affect the coexistence of herbaceous and woody species (Adler and others, 2009). Consistent forage production is unlikely under response categories that have increasing interannual variability in precipitation, and managers might anticipate fluctuations in production as interannual variability rises (Klemm and others, 2020).

2.1.6. Overall Implications for Forage Resources

The impact categories follow the general expectation that the northeastern part and high-elevation areas within the range of big sagebrush will likely experience overall increases in forage production, whereas the southeastern part and low-elevation areas will experience decreases. Despite the positive outcomes in the northeastern and high elevation areas, the anticipated changes in seasonality and the increasing amounts of precipitation are more likely to favor big sagebrush more than forage species. Moreover, increased interannual variability and the increasing rate of extreme weather events is expected to have negative effects on forage production. Given these circumstances, a one-size-fits-all future management plan for livestock grazing in big sagebrush ecosystems is not feasible. Instead, managers may need to carefully consider the specific climate projections for forage species in their region to determine if forage species in grazing allotments will benefit or suffer from rising temperatures and changing precipitation.

In favorable conditions, vegetation monitoring in grazing allotments may incorporate a focus on the growth of woody and invasive species. This approach will enhance the understanding of how changing precipitation is affecting the balance between shrubs and herbaceous species, particularly perennial grasses. In unfavorable conditions, managers may need to consider shifting the grazing dates for allotments and potentially eventually reducing the overall animal use months as well. Vegetation monitoring would benefit from focusing on the persistence of C₃ and C₄ grasses. Finally, managers may need to continuously monitor drought indicators and remain prepared to adjust grazing intensities in the aftermath of drought periods.

2.3.1. Maintaining Connectivity and Wildlife Habitat

As climate change reshapes the potential distribution of sagebrush, the distribution and abundance of wildlife habitat provided by intact big sagebrush plant communities is also expected to shift (Palmquist and others, 2021; Rigge, Shi, and Postma, 2021; Havrilla and others, 2023). This section focuses on three aspects of wildlife habitat that will likely be affected by the expected shifts in sagebrush vegetation: habitat fragmentation, migration routes, and habitat restoration.

Habitat fragmentation because of climate-driven shifts in vegetation is not limited to sagebrush ecosystems (Mantyka-pringle and others, 2012). In widely distributed vegetation types, changes across elevation gradients may isolate some communities as they move upslope and are replaced by other species at lower elevations (Hsiung and others, 2018). This fragmentation has the potential to alter wildlife movement, disrupt gene flow, and constrain species' adaptive capacity (Andrén, 1994; Fahrig, 2003). For example, the risk of isolating high-elevation big sagebrush habitats raises concerns about diminished connectivity that can impede wildlife movement and hinder their capacity to cope with interannual variability in forage availability (Love and others, 2023). To mitigate these challenges, managers may consider prioritizing conservation and restoration of corridors between areas of high-quality sagebrush habitat (Chambers, Maestas, and others, 2017).

Increasing connectivity between areas of intact sagebrush plant communities will also serve to mitigate the effects of shifts in the timing of soil moisture availability and plant growth because of changes in phenology associated with altered precipitation. These shifts in the timing and productivity of forage may have a negative effect on wildlife species, particularly ungulate game species, reliant on these ecosystems during migration (Merkle and others, 2016; Aikens and others, 2017; Bloom and others, 2022). The temporal shifts in soil moisture availability and plant growth could disrupt wildlife migration seasonal timing and potentially routes. Beyond changes to vegetation, increases in temperature are also likely to affect animal movement, but these animal effects are outside the focus of this synthesis.

In the context of climate-induced changes in wildlife habitat connectivity and shifts in the phenology of plant species, avoiding wildlife population declines may depend on effective habitat restoration (Davies and others, 2011; Chambers, Beck, and others, 2017). As areas of sagebrush are lost because of climate-induced drought and (or) wildfires, resource managers may consider implementing climate resilient restoration strategies. Techniques such as reseeding with locally adapted subspecies and (or) genotypes of big sagebrush, preventing invasive plant establishment, and adopting adaptive land management practices that stimulate sagebrush recovery (such as seeding with perennial grasses across multiple years) are potential options to improve conditions for wildlife (Brabec and others, 2017; Germino and others, 2018; Applestein and others, 2021).

2.3.2. Management to Minimize Invasive Annual Grasses

Invasive annual grasses have already affected large parts of the sagebrush region because of their ability to exploit a broad ecological niche and show resilience to changing climate conditions. To maintain sagebrush habitat for wildlife, managers may use monitoring data that can serve as an early detection system for invasive annual grass species (Bradley, 2009; Chambers, Maestas, and others, 2017). The BLM monitors vegetation through the AIM Strategy across the lands it manages. Managers may want to recognize the value that AIM sampling provides for understanding presence and absence of invasive plant species. As AIM sampling continues, it can provide information about how invasive plant abundance is changing across time. In addition, satellite-based imaging products such as the U.S. Department of Agriculture Rangeland Analysis Platform and the US Geological Survey Rangeland Condition Monitoring Assessment and Projection (RCMAP) may be useful to detect abundance trends for invasive annual grasses (Jones and others, 2018; Rigge and others, 2023). By quickly identifying the presence of these invasive species, swift and effective responses, including targeted herbicide applications, manual removal efforts, or prescribed burns, can be aimed at preventing the establishment and proliferation of these invasive species (Germino and others, 2016; Shinneman and others, 2023).

2.3.3. Managing Conifer Expansion in the Context of Climate Change

Since at least the 1990s, coniferous tree species, such as pinyon pine and juniper, have been expanding into sagebrush ecosystems (Maestas and others, 2021). Although this expansion has negative effects for sagebrush habitat and wildlife populations (Doherty and others, 2022), ongoing and predicted shifts in precipitation patterns may continue to support conifer expansion and potentially reduce the long-term effectiveness of conifer-reduction management strategies (Zimmer and others, 2021).

Proactive vegetation management strategies, such as selective thinning or the targeted removal of expanding conifers, are used to maintain a balance between sagebrush and coniferous trees (Davies and Bates, 2019). This approach preserves habitat for sagebrush-dependent wildlife species while effectively countering the expansion of conifers (Davies and Bates, 2014). However, expected expansion of conifers and the expected increase in precipitation may make proactive efforts to limit conifer expansion more costly as conifers expand at an increased rate (Maestas and others, 2021).

2.4.1. Increased Wildfire Risks

The increased frequency and severity of wildfires because of climate change poses risks to recreation activities across the sagebrush region, including smoke inhalation and wildfire risk for public recreators. These risks are compounded during periods of high interannual variability that lead to fine fuel buildup and consequently more intense wildfires (Pilliod and others, 2017). In areas that may have cheatgrass expansion, wildfire risks are likely to increase. Activities such as hiking and camping will be particularly affected, as wildfire may temporarily restrict access (Brice and others, 2020). Recreational decisions can proactively mitigate wildfire risks by prioritizing visitor safety, for example, through the use of fire restrictions and seasonal closures.

2.4.2. Altered Recreational Seasons and Activities

Climate-induced shifts in vegetation and altered wildfire regimes are also likely to impact the timing of forage availability and habitat quality for wildlife (Abatzoglou and Kolden, 2011; Coates and others, 2016; Aikens and others, 2017). The shifts in temperature and precipitation patterns because of climate change can affect the timing of natural occurrences and potentially affect recreational activities such as birdwatching, off-road vehicle use, hunting, and shed antler and horn collection (Munson and Long, 2017; Bloom and others, 2022). For example, phenological shifts may alter bird migratory behavior and affect the seasonal timing of birdwatching (Munson and Long, 2017). The timing of mammal migrations may also change because migrating populations alter behavior to match forage availability (Aikens and others, 2017). Thus, hunting and antler collecting seasons may need to be flexible.

2.4.3. Infrastructure and Facilities Vulnerability

The intensification of extreme weather and increased erosion rates pose risks to infrastructure and recreational facilities on BLM lands that can potentially lead to disruptions in recreational access. Infrastructure and facility vulnerability is especially high in areas like the Great Basin where cheatgrass has altered the fire cycle and in regions where expected declines in perennial herbaceous cover will increase the risk of erosion (Bradley and others, 2018; Edwards and others, 2019; Shi and others, 2020). Trails, roads, campsites, and visitor centers may be vulnerable to damage, which emphasizes the need for resilient infrastructure. Climate adaptive fire management practices (manual fine fuel reduction or targeted grazing) can reduce risk to infrastructure, and restoration techniques (reseeding) that increase perennial herbaceous cover can reduce erosion risk (Chambers, Beck, and others, 2017; Shinneman and others, 2023).

2.4.4. Opportunities for Enhanced Educational and Interpretive Programs

Shifts in big sagebrush vegetation because of climate change provide an opportunity to enhance climate change related educational and interpretive programs. Engaging individuals on the topic of climate change by highlighting visible changes to the resources they care about was identified as a positive climate change education strategy (Monroe and others, 2019). Developing informative signs along trails and displays in visitor centers that highlight the ecological changes from climate change can support education efforts.

2.5.1. Vegetation Changes and Restoration Targets

Ecological resilience of big sagebrush ecosystems is a measure of their ability to recover after disturbances, including development (Chambers, Maestas, and others, 2017). Climate change may reduce ecological resilience in the big sagebrush region (Bradford and others, 2019). Reductions in resistance or resilience may decrease the success of reclamation treatments and suggest that adjustments to expected vegetation composition and cover may be necessary (Chambers, Maestas, and others, 2017). As resilience shifts, the BLM may consider setting targets for reclamation that prevent invasive annual grass establishment, and managers may consider utilizing climate-adapted seed sources to accomplish this (Brabec and others, 2017), applying repeated restoration treatment that enhance the likelihood of successful plant establishment (Shriver and others, 2018), and using assisted migration of plant species to foster the establishment of climatically viable perennial herbaceous species (Havrilla and others, 2023).

2.5.2. Development Site Selection

Shifts in the resistance and resilience of sagebrush communities are also likely to affect decisions about where surface disturbances may occur (Chambers, Beck, and others, 2017). The heightened potential for more frequent and intense wildfires means that assessing shifts in wildfire vulnerability will be important before any land development (Brice and others, 2020). For example, when possible, well-pad placement could also integrate considerations of nearby sagebrush habitats and wildlife populations, particularly near migration corridors and lekking areas (Chambers, Beck, and others, 2017). Site selection may need to avoid intact communities with projected decreases in resistance and resilience caused by increased temperature and lower precipitation (Palmquist and others, 2021; Zimmer and others, 2021; Holdrege and others, 2024a).

2.5.3. Intensive Use Projects

High-intensity use projects, such as solar energy development, are a growing consideration for the BLM. Expected shifts in sagebrush habitat and the changes to resistance and resilience across the region may act as guides for these projects (Chambers, Maestas, and others, 2017; Palmquist and others, 2021). Climate-induced shifts that result in reduced sagebrush cover and density can put a higher value on remaining sagebrush patches where development could be avoided (Chambers, Beck, and others, 2017). The development of intensive projects, such as solar fields, can amplify these effects by fragmenting or removing critical habitats. As such, development may need to avoid important breeding areas for wildlife populations and migration corridors, particularly for species of concern like greater sage grouse and ungulate game species. Finally, the loss and fragmentation of sagebrush habitats because of high-intensity use projects may lower the resilience and connectivity of remaining sagebrush patches.

3.4.1. Holdrege and others (2024)—Remote Sensing Estimates of Ecological Integrity Combined with Process-Based Modelling Projections of Change

Overview.—Holdrege and others (2024a) used estimates of sagebrush ecological integrity (SEI; from Doherty and others, 2022), and combined these estimates with projections of vegetation change to create projections of SEI under climate change. STEPWAT2, a process-based simulation model, was used to estimate changes in sagebrush, perennial grasses and forbs, and annual grasses and forbs, in response to climate change. These projected changes were then used to calculate a modified SEI that was a projection of potential future SEI under climate change. This dataset can help users assess whether areas that had high ecological integrity from 2017 to 2020 are projected to experience conditions that will be favorable for maintaining that ecological integrity, or whether climatic suitability is likely to decline in the future. Doherty and others (2022) created layer of projected future SEI classes, using similar methods as Holdrege and others (2024a). Individuals wishing to use climate change projections of SEI may want to use the layers from Holdrege and others (2024a), because they represent an update of the work started by Doherty and others (2022) and are different in that they (1) used a slightly updated version of the STEPWAT2, (2) ran simulations for multiple climate scenarios, and (3) ran simulations for multiple ecological assumptions.

Pros.—This dataset directly provides information on which areas had high SEI historically and are likely to be climatically suitable to maintain high SEI in the future, which may be useful for prioritizing management efforts. Many climate scenarios were used, allowing for a fairly robust accounting of climate uncertainty.

Cons.—The greatest source of uncertainty in SEI projections is likely the uncertainty in STEPWAT2 simulation output, therefore these results have similar limitations as Palmquist and others (2021). Additionally, projections of SEI assume cover of conifers, and the amount of human modification on the landscape, will remain fixed because projections of these factors were not available. Remotely sensed estimates of vegetation cover used for calculating historical SEI also contain errors.

Article citation.—Holdrege, M.C., Palmquist, K.A., Schlaepfer, D.R., Lauenroth, W.K., Boyd, C.S., Creutzburg, M.K., Crist, M.R., Doherty, K.E., Remington, T.E., Tull, J.C., Wiechman, L.A., and Bradford, J.B., 2024, Climate change amplifies ongoing declines in sagebrush ecological integrity: Rangeland Ecology & Management, v. 97, p. 25–40, https://doi.org/10.1016/j.rama.2024.08.003.

Dataset citation.—Holdrege, M.C., Schlaepfer, D.R., Palmquist, K.A., Theobald, D.M., and Bradford, J.B., 2024, Current and projected sagebrush ecological integrity across the Western U.S., 2017–2100: U.S. Geological Survey data release, https://doi.org/10.5066/P13RXYZJ.

Format.—Rasters (GeoTIFF).

Resolution.—90 meter (m).

Extent.—The sagebrush region.

Climate Scenarios.—RCP4.5 and RCP8.5 from 2031 to 2060 and from 2071 to 2100 (median across 13 GCMs, as well as high and low estimates provided).

Variables.—SEI (continuous variable, ranging between 0 and 1), SEI classes (core sagebrush areas, growth opportunity areas, other rangeland areas), and Q (“quality”) scores (continuous variable, ranging between 0 and 1) for sagebrush, perennial forbs and grasses, and annual forbs and grasses.

3.4.2. Tredennick and others (2023)—Statistical Models Relating Sagebrush Cover and Climate

Overview.—Tredennick and others (2023a) created correlation-based models (largely relying on time-series) relating sagebrush cover (from the RCMAP products) to climate. They used two climate variables as predictors (spring and summer precipitation, and spring and summer temperature), while also accounting for sagebrush cover in the previous year and surrounding grid-cells. Their study area was restricted to sage-grouse core areas in Wyoming, and they fit separate models to each core area. For a given sage-grouse core area, climate and sagebrush cover data from each year from 1985 to 2018 in 100-m grid-cells were used to fit a regression model. Future climate conditions were then input into the model to predict future sagebrush cover. The datasets include spatial projections of sagebrush cover for individual sage-grouse core areas for multiple periods and emissions scenarios.

Pros.—The authors chose only two climate metrics, and fit simple relationships (log-linear) in the model. Although they may be missing some more complex relationships (for example, other climate variables and their interactions), their approach is less likely to turn up spurious relationships, and the results have a high resolution.

Cons.—Because separate models were fit to each sagebrush core area in Wyoming, each model is based on data from a small area, and as such only includes a small amount of spatial climate variation. Most of the climate variability included in the model is from year-to-year variation. Therefore, sagebrush cover predictions under future climate conditions are likely extrapolating beyond climate conditions used to fit the model. Additionally, because separate models were fit to small areas, any given model may be partially capturing artifacts of a given location instead of broad underlying trends for this part of the sagebrush region. The evidence for this possible limitation is that models for different sage-grouse core areas show a range of responses including negative and positive temperature and precipitation responses.

Article citation.—Tredennick, A.T., Monroe, A.P., Prebyl, T., Lombardi, J., and Aldridge, C.L., 2023, Dynamic spatiotemporal modeling of a habitat‐defining plant species to support wildlife management at regional scales: Ecosphere, v. 14, no. 6, 20 p., https://doi.org/10.1002/ecs2.4534.

Dataset citation.—Tredennick, A.T., Monroe, A.P., Prebyl, T., Lombardi, J., and Aldridge, C.L., 2023, Sagebrush projections for greater sage-grouse core areas in Wyoming, USA, 2018–2100: U.S. Geological Survey data release, https://doi.org/10.5066/P9G58V48.

Format.—Network Common Data Form (netCDF) files.

Resolution.—100 m.

Extent.—Parts of Wyoming (data used was from greater sage-grouse core areas, which are spread across the State). Refer to the article for a map of the core areas.

Climate Scenarios.—Emissions pathways were SSP126, SSP245, and SSP585 and periods were from 2018 to 2045, from 2046 to 2070, and from 2071 to 2100. The results provided are weighted averages of 18 GCMs.

Variables.—Sagebrush cover.

3.4.3. Doherty and others (2022)—Remote Sensing Estimates of Ecological Integrity Combined with Process-Based Modelling Projections of Change

Overview.—Doherty and others (2022) used remotely sensed data to calculate SEI. This calculated SEI was used to create a dataset of SEI classes where pixels across the sagebrush region were categorized as “belonging to core sagebrush areas,” “growth opportunity areas,” or “other rangeland areas.” High sagebrush ecological integrity (designated as “core sagebrush areas”) was defined as areas with an adequate cover of sagebrush and perennial grasses and forbs and no or limited annual grasses and forbs, trees, and human modification of the landscape. Data on projected relative changes in sagebrush, perennial grasses and forbs, and annual grasses and forbs in response to climate change (from Palmquist and others, 2021), were used to calculate a modified SEI that was a projection of potential future SEI under climate change. This projected SEI was used to classify areas in the future (under a single climate scenario) as “core sagebrush areas,” “growth opportunity areas,” or “other rangeland areas.” This dataset can help users assess whether areas that had high ecological integrity from 2017 to 2020 are projected to experience conditions that will be favorable for maintaining that ecological integrity, or whether climatic suitability is likely to decline under future climate conditions. Holdrege and others (2024a) also created projections of future SEI using the newer (projected) dataset that may be a more appropriate representation of SEI because they represent an extensive update of the projections made by Doherty and others (2024).

Pros.—This dataset combines remotely sensed estimates of ecological integrity with estimates of potential changes in sagebrush plant communities in response to climate change. Thereby, this dataset directly provides information on how those core sagebrush areas might respond to climate change.

Cons.—The data layer providing projections of SEI classes incorporates STEPWAT2 simulation results, and therefore it has similar limitations as Palmquist and others (2021). Additionally, the analysis was only done using the median vegetation response (across GCMs) under a single climate scenario and period, so uncertainty in climate change is not considered. Remotely sensed estimates of vegetation cover used for calculating historical SEI also contain errors.

Article citation.—Doherty, K., Theobald, D.M., Bradford, J.B., Wiechman, L.A., Bedrosian, G., Boyd, C.S., Cahill, M., Coates, P.S., Creutzburg, M.K., Crist, M.R., Finn, S.P., Kumar, A.V., Littlefield, C.E., Maestas, J.D., Prentice, K.L., Prochazka, B.G., Remington, T.E., Sparklin, W.D., Tull, J.C., Wurtzebach, Z., and Zeller, K.A., 2022, A sagebrush conservation design to proactively restore America’s sagebrush biome: U.S. Geological Survey Open-File Report 2022–1081, 38 p., https://doi.org/10.3133/ofr20221081.

Dataset citation.—Doherty, K., Theobald, D.M., Holdrege, M.C., Wiechman, L.A., and Bradford, J.B., 2022, Biome-wide sagebrush core habitat and growth areas estimated from a threat-based conservation design: U.S. Geological Survey data release, https://doi.org/10.5066/P94Y5CDV.

Format.—Rasters (GeoTIFF).

Resolution.—30 m.

Extent.—The sagebrush region.

Climate Scenarios.—RCP8.5 from 2030 to 2060 (median across 13 GCMs provided).

Variables.—Layers provide SEI classes (pixels fall in one of three categories: core sagebrush areas, growth opportunity areas, and other rangeland areas). Five layers provide SEI classes for one of five historical periods (between 1998 and 2020), and one layer provides projected future SEI classes under climate change.

3.4.4.Palmquist and others (2021)—Process-Based Modeling of Plant Functional Group Responses to Climate Change

Overview.—Palmquist and others (2021) used an individual plant-based simulation model (STEPWAT2) to simulate growth of plant functional types in sagebrush ecosystems, including big sagebrush, C₃ and C₄ perennial grasses, cheatgrass, and perennial forbs. The STEPWAT2 model simulates plant growth based on the amount of available water that is estimated in the soil (which is based on temperature, precipitation, and soil type). They simulated sagebrush plant communities at 200 sites, and these results were then extrapolated across the sagebrush region. Simulations were conducted under current climate conditions, for multiple emissions scenarios, periods, and GCMs to ensure that uncertainty induced by different climate scenarios was well represented.

Pros.—The model was designed for dryland ecosystems and specifically for use in sagebrush ecosystems. Because it is process-based, results may be more robust under future (potentially novel) climate conditions. These results represent one of the most extensive process-based modeling efforts of plant functional type specific responses to climate change across the sagebrush region.

Cons.—STEPWAT2 does not incorporate the land-use history of a given location, or the actual vegetation currently observed there. Therefore, output is most appropriately viewed as a rough estimate of the potential amount of biomass of each plant functional type that the climate of a given location can support, and how that might change with a changing climate. In addition, STEPWAT2 results have been validated only in limited context, primarily with spatial comparisons. Thus, the confidence in STEPWAT2 estimates of impacts from long-term climatic shifts remains difficult to assess.

Article citation.—Palmquist, K.A., Schlaepfer, D.R., Renne, R.R., Torbit, S.C., Doherty, K.E., Remington, T.E., Watson, G., Bradford, J.B., and Lauenroth, W.K., 2021, Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients: Global Change Biology, v. 27, no. 20, p. 5169–5185, https://doi.org/10.1111/gcb.15776.

Dataset citation.—Palmquist, K.A., Renne, R.R., Schlaepfer, D.R., Lauenroth, W.K., and Bradford, J.B., 2022, High-resolution maps of projected big sagebrush plant community biomass for 52 future climate scenarios using multivariate matching algorithms: U.S. Geological Survey data release, https://doi.org/10.5066/P9DR9G1Y.

Format.—Rasters (GeoTIFF).

Resolution.—30 arcsecond (less than 1 kilometer [km]).

Extent.—The sagebrush region.

Climate Scenarios.—RCP4.5 and RCP8.5 from 2030 to 2060, and from 2070 to 2010 (13 GCMs per RCP and period).

Variables.—Aboveground biomass (grams per square meter) of big sagebrush, C₃ and C₄ perennial grasses, cheatgrass, and perennials forbs.

3.4.5. Rigge, Shi, and Postma (2021)—Statistical Modeling Approach Used to Relate Plant Cover to Climate and Other Factors

Overview.—Rigge, Shi, and Postma (2021) used a correlation approach to model vegetation cover as a function of soil, topography, and climate variables. They used generalized additive models, which allowed for fitting flexible (nonlinear) relations. Subsequently, Rigge and others (2023) used the same approach except they used a deep neural network model. They separately modeled shrub, sagebrush, herbaceous, and annual herbaceous cover using data from a random subset of pixels across the sagebrush region each year from 1985 to 2018. Therefore, the relationships captured by their models represent a combination of spatial and temporal patterns found in the data. The vegetation cover values used as the response variables in the models are estimates based on Landsat satellite data. They used the models to predict future cover by inputting future climate conditions from two emissions scenarios (RCP4.5 and RCP8.5) and three periods. Note that the older version of this dataset, which corresponds to the Rigge, Shi, and Postma (2021) manuscript are available at https://doi.org/10.5066/P9EC2094, however, they recommend using the newer version (https://doi.org/10.5066/P9J490BH).

Pros.—The models Rigge, Shi, and Postma(2021) fit represented cover under current conditions at a high resolution. This dataset provides some of the most complete projections (with regard to spatial coverage and plant functional types modeled) available from a correlation-based model in the sagebrush region.

Cons.—Correlational models may not extrapolate well to novel conditions because the relations represented in the model are not necessarily causal. However, Rigge and others (2023) contend that because of the large climate envelope covered by the sagebrush region, most future climate conditions they assessed included few truly novel conditions. Rigge, Shi, and Postma (2021) noted that in the southern Great Basin and southern Colorado Plateau the model projected increases in sagebrush cover in response to climate change, which they suspect is model error. However, Rigge, Shi, and Postma (2023) state that the new estimates have fewer errors.

Article citation.—Rigge, M., Shi, H., and Postma, K., 2021, Projected change in rangeland fractional component cover across the sagebrush biome under climate change through 2085: Ecosphere, v. 12, no. 6, art. e03538, 25 p., https://doi.org/10.1002/ecs2.3538.

Dataset citation.—Rigge, M., Postma, K., Bunde, B., and Shi, H., 2023, Projections of rangeland fractional component cover across Western US rangelands for RCP4.5 and RCP8.5 scenarios for the 2020s, 2050s, and 2080s time-periods: U.S. Geological Survey data release, https://doi.org/10.5066/P9J490BH.

Format.—Rasters (GeoTIFF).

Resolution.—30 m.

Extent.—Rangelands across the Western United States.

Climate Scenarios.—RCP4.5 and RCP8.5 for 2020s, 2050s, and 2080s (results are based on the median output of 15 GCMs).

Variables.—Cover of shrubs, sagebrush, herbaceous plants, annual herbaceous plants, litter, and bare ground.

3.4.6. Schlaepfer and others (2021)—Process-Based and Statistical Models Used to Estimate Future Sagebrush Regeneration

Overview.—Schlaepfer and others (2021) used two different models to estimate future regeneration probability of sagebrush. They used a process-based germination and individual seedling survival model (GISSM), which relies on daily weather and ecohydrological variables (including various soil moisture metrics), to estimate the potential regeneration probability of big sagebrush under natural conditions (in other words, under conditions with no disturbance, no invasion by annual grasses, and so forth). They used a second, correlation-based (regression) model (Shriver and others, 2018) to estimate the probability that restoration succeeds following fire and seeding (based on measurements made across multiple wildfire sites). The Shriver and others (2018) regression model estimates this probability based on two variables (mean temperature and spring soil moisture). Projections of regeneration probability (GISSM) and probability of restoration success (Shriver and others, 2018) were made under multiple climate scenarios and time periods.

Pros.—These results may present the most complete, spatially explicit, modeling results of big sagebrush regeneration responses to climate change.

Cons.—Both models are subject to the limitations that all models of the future share—there is not a way to directly test their predictions. Additionally, they assume the availability of big sagebrush seeds, which may or may not be reasonable depending on the history of the particular location.

Article citation.—Schlaepfer, D.R., Bradford, J.B., Lauenroth, W.K., and Shriver, R.K., 2021, Understanding the future of big sagebrush regeneration—Challenges of projecting complex ecological processes: Ecosphere, v. 12, no. 8, art. e03695, 26 p., https://doi.org/10.1002/ecs2.3695.

Dataset citation.—Schlaepfer, D.R., and Bradford, J.B., 2021, Simulated rangewide big sagebrush regeneration estimates and relationships with abiotic variables as function of soils under historical and future climate projections: U.S. Geological Survey data release, https://doi.org/10.5066/P9MB2QB8.

Format.—netCDF.

Resolution.—10 km.

Extent.—The projections from the Schriver2018 model are restricted to the central and northern Great Basin and Snake River Plain (because data used to fit that model were only from that area). The projections from the GISSM model cover the entire sagebrush region.

Climate Scenarios.—Projections were made for two scenarios (RCP4.5 and RCP8.5) and periods (from 2020 to 2050 and from 2070 to 2099). Median projected values across GCMs were provided.

Variables.—Regeneration probability (GISSM) and probability of restoration success (Schriver2018) of big sagebrush.

3.4.7. Zimmer and others (2021)—Multi-Model Comparison of Vegetation Responses to Climate Change

Overview.—Zimmer and others (2021) combined results from studies that were available before 2020 that created spatial estimates (through correlation or process-based modeling) of vegetation responses to climate change. They compiled results for studies done within the sagebrush region and estimated responses of cheatgrass (3 studies), forage production (3 studies), pinyon-juniper (5 studies), or sagebrush (3 studies) to climate change. They digitized results from figures in published articles and therefore did not have to rely only on studies that had also published their data. By using this approach, they were able to incorporate results from some studies that are not individually listed in the “Available Datasets Relevant to Climate Change Impacts on Big Sagebrush Plant Communities” section of this report. The final dataset Zimmer and others (2021) created includes rasters that count the number of studies projecting positive or negative climate responses in a given pixel for each of the vegetation components they considered. Since Zimmer and others (2021) completed their work, some additional datasets have become available (for example, Palmquist and others, 2021; Rigge, Shi, and Postma, 2021); therefore, their study is not a complete account of all available datasets projecting vegetation responses to climate change in the sagebrush region.

Pros.—Zimmer and others (2021) compared the results of multiple studies that used different methods and approaches. This method may be the best way to assess the level of confidence in the direction of projected change because there are many sources of uncertainty in estimates of sagebrush ecosystem responses to climate change.

Cons.—Zimmer and others (2021) combined results from studies that modeled different response variables that have different units (for example, cover, presence, and net primary productivity). Therefore, the magnitude of responses could not readily be combined, and the data product they created is only able to provide information on confidence in the direction of climate responses (in other words, the number of studies projecting positive or negative responses). As such, this dataset would not be directly useful if an analyst wants to have a continuous variable (for example, change in cover) that estimates magnitude of climate change response. The resolution may also be too coarse for applications requiring spatial resolution greater than about 15 square kilometers (km²).

Article citation.—Zimmer, S.N., Grosklos, G.J., Belmont, P., and Adler, P.B., 2021, Agreement and uncertainty among climate change impact models—A synthesis of sagebrush steppe vegetation projections: Rangeland Ecology & Management, v. 75, p. 119–129, https://doi.org/10.1016/j.rama.2020.12.006.

Dataset citation.—Zimmer, S., Grosklos, G., Belmont, P., and Adler, P., 2020 Agreement and uncertainty among climate change impact models—A synthesis of sagebrush steppe vegetation predictions: HydroShare data release, https://doi.org/10.4211/hs.e6b15828d20843eab4e2babd89787f41.

Format.—Rasters (GeoTIFF).

Resolution.—About 15 km².

Extent.—Their study area included BLM land in the Intermountain West, specifically focusing on the Northern Basin and Range, Central Basin and Range, Wyoming Basin, and Colorado Plateaus U.S. Environmental Protection Agency Level III Ecoregions (https://gaftp.epa.gov/EPADataCommons/ORD/Ecoregions).

Climate Scenarios.—When available, Zimmer and others (2021) separately compiled results for low (for example, RCP4.5) and high (for example, RCP8.5) emissions scenarios, and they focused on the latest periods available (generally the end of 21st century).

Variables.—Count rasters are provided for cheatgrass, forage production, pinyon-juniper, and sagebrush and provide the number of studies with positive or negative projected change at each grid-cell.

3.4.8. Comer and others (2019)—Habitat Climate Change Vulnerability Index

Overview.—Comer and others (2019) created the Habitat Climate Change Vulnerability Index (HCCVI) for different vegetation types, including sagebrush dominated vegetation types. The HCCVI estimates how vulnerable the vegetation in a given location is to climate change. It applies to a vegetation type instead of a specific species or plant functional group. The HCCVI is a mean of multiple scores or subindices including climate exposure, sensitivity, and adaptive capacity. Climate exposure incorporates how projected future climate in a location will compare to the historical spatial variability in climate for the vegetation type and how different future climate will be from historical climate for that location. The sensitivity score attempts to quantify ecosystem stressors that are likely to affect ecological responses to climate change by including estimates of factors such as insect disease risk, invasive plants, and the amount of human modification of the landscape. The ecosystem adaptive capacity score was calculated as a fixed metric (in other words, does not vary spatially) for the given vegetation type, and incorporates factors such as diversity within functional species groups, and the amount of topographic and climate variability across the area occupied by the vegetation type.

Pros.—Spatial layers of the HCCVI were created for multiple sagebrush dominated vegetation types such as “inter-mountain basin big sagebrush steppe,” which makes it relevant for the sagebrush region. The HCCVI provides a different independent perspective on climate vulnerability relative to the other datasets listed in this report.

Cons.—The HCCVI applies to a given vegetation type, and therefore it cannot directly account for potentially different responses by different plant functional groups (for example, sagebrush may respond differently to changes in precipitation seasonality than C₄ grasses will). Sometimes, it may be challenging to interpret HCCVI because it is a mean of many different scores; all scores are measures of different factors and likely have varying degrees of uncertainty and error.

Article citation.—Comer P.J., Hak, J.C., Reid, M.S., Auer, S.L., Schulz, K.A., Hamilton, H.H., Smyth, R.L., Kling, M.M., 2019, Habitat Climate Change Vulnerability Index applied to major vegetation types of the Western Interior United States: Land, v. 8, no. 7, art. 108, 27 p., https://doi.org/10.3390/land8070108.

Dataset citation.—Not applicable.

Where to Download.—The main landing page for the data and supplementary material is available at https://databasin.org/galleries/6704179ca499490bafd2e9080df1908a. The geodatabase (folder ending in “.gdb”) that has the spatially explicit HCCVI data for each vegetation type is available at https://tranxfer.natureserve.org/download/Longterm/Ecology/BLM/.

Format.—Geodatabase.

Resolution.—Data are provided for 100 km² hexagon shaped polygons.

Extent.—Spatial datasets are available for 52 different vegetation types. Each vegetation type has a different extent, but collectively they cover the interior Western United States.

Climate Scenarios.—RCP4.5 (from 2040 to 2069).

Variables.—The HCCVI (a unitless index that ranges from 0 to 1) and scores or indices used for calculating HCCVI including adaptive capacity, resilience, and exposure.

3.4.9. Renwick and others (2018)—Multi-Model Comparison of Sagebrush Responses to Climate Change

Overview.—Renwick and others (2018) used four different models to estimate sagebrush responses to climate change. Although they did not create a raster layer of projected responses, they estimated projected sagebrush responses at 714 sites across the sagebrush region. For each location, they projected responses using 1 time-series correlation-based model, 1 spatial correlation-based model, and 2 process based models. This study is one of only two multimodel comparisons that we are aware of in the sagebrush region (the other is Zimmer and others [2021]). This study helps assess the confidence in the direction of the responses of big sagebrush to climate change across its range.

Pros.—Because this study used multiple independently developed correlation and process-based models, greater confidence is possible in projections in areas where there is agreement among models.

Cons.—Because model projections were made for point locations this dataset will not be usable as is for individuals who want a raster layer of projected sagebrush responses.

Article citation.—Renwick, K.M., Curtis, C., Kleinhesselink, A.R., Schlaepfer, D., Bradley, B.A., Aldridge, C.L., Poulter, B., and Adler, P.B., 2018, Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub: Global Change Biology, v. 24, no. 1, p. 424–438, https://doi.org/10.1111/gcb.13900.

Dataset citation.—Same as the article citation.

Where to Download.—The file ”merged_data_GCM.csv” includes the projections for all climate scenarios and models and is available at https://github.com/krenwick/sageseer/tree/master/Products.

Format.—Comma-separated values (.CSV) file

Resolution.—Not a raster dataset (data for point locations).

Extent.—Projections were made for 714 sites with documented sagebrush presence scattered evenly across the sagebrush region.

Climate Scenarios.—RCP4.5 and RCP8.5 from 2070 to 2099.

Variables.—Because the models did not all have the same response variables, the following data for multiple response variables are provided: maximum potential percentage of sagebrush cover (spatial correlation model), annual change in percentage of sagebrush cover (temporal correlation model), percentage of sagebrush cover (dynamic global vegetation model), and percentage of years with sagebrush regeneration (seedling survival model).