Long-Term and Broad Scale Change in Wooded Shrublands A

University of Nevada, Reno

Plant Community Dynamics in the Great Basin: Long-Term and Broad Scale Change in Wooded Shrublands

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Natural Resources and Environmental Science

by Cody Ernst-Brock Dr. Elizabeth A. Leger/Thesis Advisor

December 2018

THE GRADUATE SCHOOL

We recommend that the thesis prepared under our supervision by

CODY ERNST-BROCK

Entitled

Plant Community Dynamics in the Great Basin: Long-Term and Broad Scale Change in Wooded Shrublands

be accepted in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

Elizabeth A. Leger, Ph.D., Advisor

Benjamin W. Sullivan, Ph.D., Committee Member

Lee Turner, Ph.D., Committee Member

Elizabeth G. Pringle, Ph.D. , Graduate School Representative

David W. Zeh, Ph.D., Dean, Graduate School

December, 2018

Abstract

Expansion of native pinyon-juniper (Pinus monophylla-Juniperus osteosperma) woodlands can decrease shrub and herbaceous cover in the Intermountain West, affecting habitat quality and biodiversity. Changes in the range and cover of other plant communities, including forbs and invasive grasses, are also occurring. Removing woodlands in former sagebrush ecosystems has a long management history, with interest in understory plant community responses. We revisited a restoration site in western

Nevada, 32 years after tree thinning treatments had occurred, and conducted vegetation measurements within historic treatment plots. Our findings suggest tree thinning and removal can increase shrub and perennial grass cover, but tree recolonization over the long-term is possible. We also used vegetation data repeatedly collected at unmanipulated monitoring plots to calculate change in foliar and litter cover during 2011-2017. Increases in pinyon-juniper dominance influenced decreases in foliar cover of shrubs and sage- grouse preferred forbs, and litter cover of all types increased significantly.

Acknowledgements

I would like to thank my advisor, Beth Leger, for her unwavering guidance, support, and expertise. Beth always pushed me to do my best work, and was a great traveling partner, mentor, and friend. Thank you to Lee Turner and the Nevada Department of Wildlife, for their support, collaboration, and confidence in my skills and abilities. I would also like thank my other committee members, Ben Sullivan and Beth Pringle, and my co-author,

Robin Tausch, for invaluable feedback on my writing and work. Thank you to Lynn

Zimmerman, my first mentor, and the Great Basin Institute, for teaching me so much and giving me endless opportunities for professional development and personal growth. I would also like to thank our Vegetation/Habitat Assessment field crews for their hard work and travel to remote locations across Nevada to collect the vegetation data that made this work possible. I thank my family: Chelsa and Marcello Rostagni, Kimberly

Brock, Bill Ernst, and Beverly Ernst, for their steady encouragement throughout my time in graduate school, and their enthusiastic celebration of higher education. Lastly, my partner and love, Todd Granberry, for the pep talks, dinners, feedback, understanding, and laughter.

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Table of Contents

Abstract…………………………………………………………………………………….i

Acknowledgements………………………………………………………………………..ii

Tables of Contents……………………………………………………………………..…iii

List of Tables and Figures Chapter 1………………………..…..………………………...iv

List of Tables and Figures Chapter 2………………..…..………………………..………..v

Background………………………..…..…………………………………..…………..…..1

Chapter 1: Long-term vegetation responses to pinyon-juniper reduction treatments in shrublands of Nevada, USA………………………..…..…………………………...... 7

Chapter 2: Changes in plant community composition and ground cover in sagebrush steppe: effects of pinyon-juniper cover and environmental variables……………..….....51

Chapter 1 Appendix..……………..…..………………………..…..…………………...109

Chapter 2 Appendix…………...………………………..…..…………………………...131

Chapter 1: List of Tables

Table 1. Seed mix components and kilograms (kg) per hectare that were broadcast seeded at the Wellington Hills woodland reduction field site (western Nevada, U.S.) in

1984.

Table 2. Results from mixed models using the restricted maximum likelihood method to determine overall model significance. Responses are: average foliar cover and density of target species, plant functional groups, and litter categories calculated via line-point intercept and density belt sampling; average gap lengths (in binned length categories) between perennial species, calculated via canopy gap measurements; total, native/introduced, and invasive species richness calculated via timed species inventories.

Chapter 1: List of Figures

Figure 2. Foliar cover of target species and functional groups at the Wellington Hills field site in western Nevada, U.S.

Figure 3. Overall average species foliar cover at the Wellington Hills field site in western

Nevada, U.S., for each treatment.

Figure 4. Total P. monophylla density (average trees/hectare) for 4 size classes (depicted in legend) and standing dead trees summed across all blocks in each treatment.

Figure 5. Foliar cover of seeded grasses at the Wellington Hills field site in western

Nevada, U.S. Native seeded species: P. secunda. Introduced seeded species: T. intermedium, A. cristatum, and B. inermis.

Figure 6. Average perennial canopy gaps (binned into different cm gap length categories) at the Wellington Hills field site in western Nevada, U.S.

Chapter 2: List of Tables

Table 2. Vegetation functional groups, litter types, and target grass species used in all models

Table 3a. Variables and covariates used in broad models

Table 3b. Variables and covariates used in seasonal models

Table 4a. % Foliar cover change values for all monitoring plots, regardless of vegetation type

Table 4b. % Foliar cover change values for sagebrush vegetation monitoring plots

Table 4c. % Foliar cover change values for Phase I vegetation monitoring plots

Table 4d. % Foliar cover change values for Phase II vegetation monitoring plots

Table 4e. % Foliar cover change values for Phase III vegetation monitoring plots

Table 5a. Broad model, vegetation functional groups

Table 5a continued. Broad model, vegetation functional groups, starting cover of functional groups/species

Table 5b. Broad model, target grass species

Table 6a. Seasonal model, vegetation functional groups

Chapter 2: List of Figures

Figure 1. Map of project monitoring plot locations across Nevada and eastern California.

Figure 2. Vegetation monitoring plot layout. Three 50-m transect tapes are extended from plot center, typically oriented at 0°, 120°, and 240°. Total area of each monitoring plot is 9510-m2.

Figure 3. Histograms of range of foliar cover change for selected vegetation functional groups.

Figure 4. Litter % foliar cover change among vegetation types.

Figure 5. Forbs % foliar cover change among vegetation types.

Figure 6. Shrubs % foliar cover change among vegetation types.

Figure 7. Trees, woody, nonwoody % foliar cover change among vegetation types.

Figure 8. Bromus tectorum % foliar cover change among vegetation types.

Figure 9. Perennial grass species % foliar cover change among vegetation types.

vii

Figure 10. Perennial Grasses % foliar cover change among vegetation types.

Figure 11. Sagebrush cover and minimum annual temperature

Figure 12. Litter cover and annual precipitation

Figure 13. Shrub cover and minimum fall temperature

Figure 14. Forb cover and summer maximum temperature

Figure 15. Litter cover and winter precipitation

Background

The Intermountain West has experienced landscape-scale changes in vegetation distribution, range, composition, and cover over the past century (Allen and Breshears,

1998; Bertrand et al., 2011; Langley et al., 2018; Vitt et al., 2010), and shifts within the vegetation understory of wooded shrublands have been attributed, in part, to the expansion in density and range of native singleleaf pinyon pine (Pinus monophylla Torr.

& Frém) and Utah juniper (Juniperus osteosperma [Torr.] Little) (Miller and Tausch,

2001; Tausch et al., 2009; Weisberg et al., 2007). Proposed explanations for the expansion of pinyon-juniper woodlands include: increased grazing pressure, changes in climate and C02 levels, shifts in fire size and frequency, and recovery after human harvest, (Barger et al., 2009; Breshears et al., 2005; Brockway et al., 2002; Chambers and

Pellant, 2008; Miller and Tausch, 2001; Miller and Wigand, 1994; Romme et al., 2009).

Although these native woodlands provide habitat and cover for certain species (Balda and

Kamil, 1998; Watkins et al., 2007), their expansion into former sagebrush (Artemisia tridentata) steppe can negatively affect sagebrush-obligate species including the greater sage-grouse (Centrocercus urophasianus), that rely on sagebrush habitat for nesting, cover, and forage (Bates et al., 2017; Coates et al., 2016, 2017; Davies et al., 2011;

Prochazka et al., 2017). Pinyon-juniper expansion also affects understory vegetation, partly due to the ability of these woodlands to exploit significant levels of available ground water (Bates et al., 2000; Roundy et al., 2014). Additional shifts in vegetation observed throughout the Great Basin include the loss of forbs (Nowak et al., 2017), loss of sagebrush cover (Bradley, 2010), and increases in invasive species cover, including cheatgrass (Bromus tectorum) (Chambers et al., 2007).

Woodland thinning and removal practices have become increasingly common land management strategies as a result of these undesirable changes in vegetation cover and composition, specifically in areas where the desired habitat may be shrublands or grasslands rather than woodlands (Archer et al., 2012; Bates et al., 2007; DeLuca et al.,

2010; Redmond et al., 2013). Site conditions (location, elevation, slope, aspect), and annual and seasonal weather patterns also influence observed changes in vegetation community composition. In order to capture these changes in vegetation, inform projections of upcoming change, and provide data for management and restoration decisions, multi-year, widespread monitoring is needed (Boswell et al., 2017; Chambers and Wisdom, 2009; DeLuca et al., 2010; Elzinga et al., 1998; Havstad and Herrick, 2003;

Pilliod et al., 2017; Severson et al., 2017).

Thesis Summary

This thesis addresses the use of vegetation monitoring data to inform long-term and broad scale vegetation change across the Great Basin through:

1. Examining the efficacy of varying woodland reduction techniques three decades

after original treatments were conducted, by comparing vegetation composition at

control and treatment plots within a historic site to determine restoration effects.

2. Determining what environmental factors and site conditions most influence

vegetation change over time, and what vegetation functional groups and species

are experiencing the largest changes, by examining cover change at

unmanipulated control plots across Nevada and eastern California in relationship

to varying site locations and weather conditions.

3. Understanding how varying levels of initial tree cover and density affect

vegetation responses to restoration treatments and environmental conditions over

time.

References

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Langley, J.A., Chapman, S.K., La Pierre, K.J., Avolio, M., Bowman, W.D., Johnson, D.S., Isbell, F., Wilcox, K.R., Foster, B.L., Hovenden, M.J., Knapp, A.K., Koerner, S.E., Lortie, C.J., Megonigal, J.P., Newton, P.C.D., Reich, P.B., Smith, M.D., Suttle, K.B., Tilman, D., 2018. Ambient changes exceed treatment effects on plant species abundance in global change experiments. Glob. Chang. Biol. 1–12. doi:10.1111/gcb.14442 Miller, R., Tausch, R., 2001. The role of fire in pinyon and juniper woodlands: A descriptive analysis, in: Galley, K.E.M., Wilson, T.P. (Eds.), Proceedings of the Invasive Species Workshop: The Role of Fire in the Control and Spread of Invasive Species. Fire Conference 2000: The First National Congress on Fire Ecology, Prevention, and Management. Miscellaneous Publication No. 11, Tall Timbers Res. Tallahassee, FL, pp. 15–30. Miller, R.F., Wigand, P.E., 1994. Holocene changes in semiarid pinyon-juniper woodlands. Bioscience 44, 465–474. doi:10.2307/1312298 Nowak, R.S., Nowak, C.L., Tausch, R.J., 2017. Vegetation dynamics during last 35,000 years at a cold desert locale: Preferential loss of forbs with increased aridity. Ecosphere 8, 1–23. doi:10.1002/ecs2.1873 Pilliod, D.S., Welty, J.L., Toevs, G.R., 2017. Seventy-Five Years of Vegetation Treatments on Public Rangelands in the Great Basin of North America. Rangelands 39, 1–9. doi:10.1016/j.rala.2016.12.001 Prochazka, B.G., Coates, P.S., Ricca, M.A., Casazza, M.L., Gustafson, K.B., Hull, J., 2017. Encounters with pinyon-juniper influence riskier movements in greater sage- grouse across the great basin. Rangel. Ecol. Manag. 70. doi:10.1016/j.rama.2016.07.004 Redmond, M.D., Cobb, N.S., Miller, M.E., Barger, N.N., 2013. Long-term effects of chaining treatments on vegetation structure in piñon-juniper woodlands of the Colorado Plateau. For. Ecol. Manage. 305, 120–128. doi:10.1016/j.foreco.2013.05.020 Romme, W.H., Allen, C.D., Bailey, J.D., Baker, W.L., Bestelmeyer, B.T., Brown, P.M., Eisenhart, K.S., Floyd, M.L., Huffman, D.W., Jacobs, B.F., Miller, R.F., Muldavin, E.H., Swetnam, T.W., Tausch, R.J., Weisberg, P.J., 2009. Historical and Modern Disturbance Regimes, Stand Structures, and Landscape Dynamics in Piñon–Juniper Vegetation of the Western United States. Rangel. Ecol. Manag. 62, 203–222. doi:10.2111/08-188R1.1 Roundy, B.A., Young, K., Cline, N., Hulet, A., Miller, R.F., Tausch, R.J., Chambers, J.C., Rau, B., 2014. Piñon–Juniper Reduction Increases Soil Water Availability of the Resource Growth Pool. Rangel. Ecol. Manag. 67, 495–505. doi:10.2111/REM- D-13-00022.1 Severson, J.P., Hagen, C.A., Maestas, J.D., Naugle, D.E., Forbes, J.T., Reese, K.P., 2017.

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Chapter 1

Long-term vegetation responses to pinyon-juniper reduction treatments in

shrublands of Nevada, USA

Cody Ernst-Brock a*

Lee Turner b

Robin J. Tausch c

Elizabeth A. Leger a

a Department of Natural Resources and Environmental Science, University of Nevada,

Reno, 1664 N. Virginia Street, Mail Stop 186, Reno, NV 89512, USA b Nevada Department of Wildlife, 6980 Sierra Center Pkwy #120, Reno, NV 89511, USA c Range Scientist, Retired, US Department of Agriculture (USDA) Forest Service, Rocky

Mountain Research Station, Reno, NV 89509, USA

* Correspondence: [email protected]

Phone: (775) 225-4210

This work was funded by the Nevada Department of Wildlife. Dr. Lee Turner, co-author, works for this organization and played a role in designing the overall methodology used in this and other plant survey projects. Dr. Turner also participated in the writing of this

manuscript and has agreed to submit this data for publication.

Abstract

Expansion of native pinyon-juniper (Pinus monophylla-Juniperus osteosperma)

woodlands can decrease shrub and herbaceous cover in the Intermountain West, U.S.,

affecting habitat quality and biodiversity. Removing pinyon-juniper woodlands in

former sagebrush ecosystems to increase understory cover has a long management

history, and short- and long-term monitoring reveal different understory plant

community responses. We revisited a 500 mm average precipitation wooded

shrubland site in the sagebrush steppe of western Nevada, 32 years after three types

of tree thinning treatments and seeding had occurred in a mature, closed-canopy

woodland. We measured vegetation foliar cover and density within plots arranged in

a 3-block randomized design. We found significantly lower cover of P. monophylla in

treated plots (average of 2-8%), relative to controls (32%). However, P. monophylla

seedlings (<0.5 m tall) were detected throughout all plots (average of 86–160 trees/ha

in treated plots, 111 in controls). Cover of perennial graminoids and shrubs was

higher in all treatments (600-860% higher grass cover and 440-540% higher shrub

cover) than controls. Cover of invasive annual species, primarily Bromus tectorum,

was highly variable and not significantly different among plots, but B. tectorum had

the highest cover of all species in two of the three treatment types. Control plots

contained significantly larger perennial canopy gaps compared to all treatments

(average of 318 cm vs. 104-133 cm), and had significantly more woody litter cover

than clear cut plots (average of 14% vs. 3%). These results suggest tree thinning and

removal in tree dominated woodlands can increase shrub and perennial grass cover

and reduce litter and canopy gaps, especially in conjunction with seeding, but that

tree recolonization over the long-term is inevitable. Perennial forbs did not respond

well to treatments (<1% average foliar cover in all plots), and seeding or other

treatments may be needed to improve their response. Further, if tree seedlings

survive, these plots will return to tree dominance without additional treatments.

Keywords

long-term, pinyon-juniper, woodland reduction, Great Basin, forbs, seeding

Introduction

Over the last 150 years, there have been increases in the cover of Pinus and

Juniperus species within the Intermountain West. Hypothesized explanations for this tree expansion include changes in fire size and frequency (including fire suppression), increased habitat suitability after the Pleistocene, favorable responses to C02 increases during the industrial era, recovery from human harvest, and direct and indirect effects of the introduction of grazing animals during European settlement, among other possible mechanisms (Barger et al., 2009; Breshears et al., 2005; Brockway et al., 2002; Miller and Tausch, 2001; Miller and Wigand, 1994; Romme et al., 2009). In the western Great

Basin, the density and range of singleleaf pinyon pine (Pinus monophylla Torr. & Frém) and Utah Juniper (Juniperus osteosperma [Torr.] Little) woodlands (hereafter, pinyon- juniper) have increased as these woody species have expanded into former sagebrush- dominated ecosystems or expanded their density and cover in already occupied sites

(Miller and Tausch, 2001; Tausch et al., 2009; Weisberg et al., 2007). These dynamics have been observed throughout Western states, with different species of Pinus and

Juniperus expanding in different regions, but similar outcomes have been observed

(Romme et al., 2009). For example, when pinyon-juniper density and dominance increases, understory vegetation tends to decline due to the ability of pinyon-juniper to acquire large portions of available ground water (Bates et al., 2000; Roundy et al.,

2014b), and shrub cover can decrease by as much as 50% once tree cover exceeds 20%

(Bybee et al., 2016), leading to larger canopy gaps and the increased potential for soil erosion and runoff (Pierson et al., 2010, 2013, 2015; Williams et al., 2014). Changes in vegetation density, quantity, and diversity can negatively impact habitat suitability for

11 wildlife, altering forage and cover availability for sagebrush-dependent species including the greater sage-grouse (Centrocercus urophasianus) (Bombaci and Pejchar, 2016;

Coates et al., 2017; Connelly et al., 2004; Huffman et al., 2017; Severson et al., 2017).

Additionally, fires in pinyon-juniper stands can transition communities to dominance by invasive annual species, which are highly competitive and prevent native vegetation recovery (Chambers et al., 2014; Davies and Johnson, 2017). As a result, the use of woodland reduction practices have become an increasingly common land management practice in areas where shrub and grassland habitats are a better fit for management goals

(Archer et al., 2012; Bates et al., 2007; DeLuca et al., 2010; Redmond et al., 2013).

An important element of woodland reduction treatments is understanding both short-term and long-term vegetation responses. As pinyon-juniper thinning and removal treatments become more common, there have been many short-term (6 years or less post- treatment) studies that have addressed the efficacy of various treatments (Bybee et al.,

2016; McIver et al., 2014; Provencher and Thompson, 2014; Redmond et al., 2014;

Stephens et al., 2016; Williams et al., 2017). These studies have revealed important considerations for management, including the insight that selection and application of pinyon-juniper thinning and removal treatments should be informed by initial site conditions (Bates and Davies, 2016; Stephens et al., 2016), as initial tree density and dominance can strongly affect treatment outcomes (Bates et al., 2017; Bybee et al., 2016;

Roundy et al., 2014b; Williams et al., 2017). For example, mastication (mechanical tree shredding treatments) in tree-dominated sites (tree cover ≥ 25%) resulted in increased cover of cheatgrass (Bromus tectorum L.) when compared to untreated controls (Bybee et al., 2016), an impact that can decrease ecosystem stability and increase fire risk (Balch et

12 al., 2013). Short-term studies of understory vegetation responses to other types of woodland reduction treatments also show shifts from native perennials to dominance by invasive annuals (Davis and Harper, 1964; Redmond et al., 2014; Stephens et al., 2016).

In contrast, longer-term studies have found that initial vegetation responses observed in short-term studies (like increased cover of invasive species) tend to decline over time

(Skousen et al., 1989; Tausch and Tueller, 1977). While some long-term studies exist, they are unbalanced among different treatment methods: mechanical removal and burning treatments have been studied over time frames almost twice as long as thinning treatments (Bombaci and Pejchar, 2016). Consequently, many researchers have noted the need for additional longer-term monitoring efforts associated with woodland reduction projects (Bates et al., 2017a; Bates and Davies, 2016; Bombaci and Pejchar, 2016;

Bristow et al., 2014; Bybee et al., 2016; Miller et al., 2005; Provencher and Thompson,

2014).

Because some effects of pinyon-juniper thinning and removal may not be evident for many years (Bristow et al., 2014; Huffman et al., 2013), long-term studies are important for understanding how plant communities after treatments, including if and how fast trees recolonize sites. Tree recolonization is dependent on many factors, including seasonal weather patterns, site characteristics, treatment methods, seed bank, and the number of trees remaining after treatments are implemented (Clifford et al., 2011;

Williams et al., 2017). Pinyon-juniper seedlings and seeds persist after many types of treatment, often requiring follow-up treatments (Bates et al., 2017; Evans, 1988; Tausch and Tueller, 1977). Because treatments are expensive (Provencher and Thompson, 2014;

Taylor et al., 2013), additional long-term monitoring is needed to fully understand plant

13 community impacts. Revisiting treated sites decades after treatments initially occurred will allow researchers to draw robust conclusions about longstanding ecological consequences of fuel-reduction activities, including the likelihood that treated areas will need to be treated again to maintain shrub, grass, and forb dominance. (Bates et al., 2007;

Havrilla et al., 2017).

Managers have many woodland reduction treatment options (Bates and Davies,

2017; Tausch et al., 2009). Treatment types vary in the level of site disturbance, density of trees left/removed, and post-treatment strategies. For example, mastication is often used when the goal is increasing biodiversity and enhancing wildlife habitat. However, mastication may also have unintended effects, including facilitation of the spread of non- native plant species (Coop et al., 2017), relative to other treatment methods like prescribed fire and cutting (Bates et al., 2017a). The use of seeding in conjunction with woodland reduction treatments can have a marked effect on the resulting vegetation structure as the landscape recovers post-treatment (Redmond et al., 2014; Stephens et al.,

2016). While seeding of productive, non-native grasses may have been important to meet forage goals when projects were implemented (Tausch et al., 2009), they may interfere with the recovery of native forbs and shrubs, which is important to consider if habitat restoration for wildlife is the management goal (Gallo et al., 2016). Further, invasive species density can increase after some pinyon-juniper thinning and removal treatments take place, and higher pre-treatment tree density can result in higher invasive species response after treatment (Bybee et al., 2016; Havrilla et al., 2017; Huffman et al., 2013;

Roundy et al., 2014b). Additionally, the choice of equipment used to implement woodland reduction may have an impact on the response of vegetation, particularly

14 annual plants (Stephens et al., 2016). Considering potential responses to different treatment methods can enhance our ability to reduce risk and make management decisions consistent with land use goals.

Here, we present outcomes 32 years after woodland reduction treatments were established in western Nevada in 1984. Three levels of tree harvest and plant material dispersal treatments were conducted within a mature, closed-canopy woodland (average of 642 P. monophylla per hectare in control plots), with the goal of finding the most effective management strategies to balance wood harvesting and forage production. To our knowledge, this study represents one of the longest-term woodland reduction studies in Great Basin pinyon-juniper woodlands, and is the longest-term study of hand-cutting treatments in this ecosystem (Bristow et al., 2014). We present plant community responses to pinyon-juniper thinning and removal treatments, addressing a substantial knowledge gap regarding the long-term outcomes of projects that aim to reduce the risk of fire and restore sagebrush ecosystems. We examined the effects treatments had on multiple plant community responses, including pinyon-juniper cover and density, cover and density of shrubs, and the cover of perennial grasses, forbs, seeded species, weedy and invasive species. We also quantified differences among treatments in ground cover, perennial canopy gaps, and richness and cover of all species, native or introduced species, and invasive species, and examined the relationship between foliar cover of pinyon- juniper and selected response variables, including perennial graminoids, shrubs, and total foliar cover.

In treated plots, we expected to see greater foliar cover of perennial bunchgrasses and shrubs, and smaller perennial canopy gaps. As monitoring occurred 32 years post-

15 treatment, we hypothesized that we would observe reduced foliar cover and density of trees in treated plots, but were also aware that other studies have shown that pinyon- juniper can recolonize sites in half the amount of time since treatments had occurred at our site (Bristow et al., 2014; Tausch and Tueller, 1977). We also expected that we might continue to observe greater foliar cover of invasive species in treated plots, though other studies have found that weeds can decline over time (Skousen et al., 1989; Tausch and

Tueller, 1977). We predicted that we would measure greater cover of seeded species, especially highly competitive non-native grasses (Redmond et al., 2013) and greater cover of both woody and herbaceous litter in plots that had previously undergone treatments compared to controls. Furthermore, we expected to observe greater overall species richness and cover in treated plots. Finally, as has been observed in other studies, we expected to see decreases in native species foliar cover as pinyon-juniper cover increased.

Materials and Methods

Site Description and Experimental Design

The study site is located in the Wellington Hills, an area on the north end of the

Sweetwater Mountains in western Nevada (Fig. 1, Fig. S1, UTM 291845 E, 4273659 N;

11S) in the Sierra Nevada-Influenced ecoregion (Bryce et al., 2003). Mean annual temperature and precipitation from 1981 to 2010 was 6.6°C and 507.7 mm, respectively

(http://prism.oregonstate.edu). Elevation at the site ranges from 2187 to 2238 m, with a

7% average slope. Soils at the study site are classified as a very gravelly coarse sand,

Toejom Series (https://soilseries.sc.egov.usda.gov/OSD_Docs/T/TOEJOM.html), with

16 typical native vegetation comprised of singleleaf pinyon, antelope bitterbrush (Purshia tridentata (Pursh) DC.), mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana (Rydb.) Beetle), curl-leaf mountain mahogany (Cercocarpus ledifolius Nutt.), bluegrass (Poa L.), and desert needlegrass (Achnatherum speciosum (Trin. & Rupr.)

Barkworth). The study was designed as a complete randomized block design with three main treatments and a non-treated control randomly located in one of four plots within each of three blocks (Fig. 1, Fig. S1) in mature, closed-canopy woodlands. Pre-treatment tree density data is not available, however, the entire site was largely tree dominated prior to treatment, with the relative abundance of pinyon and juniper largely consistent across the site (Tausch, personal observation). Slopes leading to the study site are fairly steep, and we did not observe evidence of grazing on the treatment site. Each of the tree treatment plots was 0.405 hectares in size, and treatments (all conducted in 1984) were:

(1) a clear cut, (2) a cut leaving a trunk cross-sectional area of 1.86 m2 per acre (20 ft2 :

20 BAF), (3) a cut leaving 3.72 m2 per acre (40 ft2 : 40 BAF), and (4) an uncut control.

For simplicity, the two intermediate treatments leaving 1.86 m2 and 3.72 m2 per acre are hereafter referred to as 20 and 40 BAF treatments, respectively. During harvest, all seedlings and saplings (≤ 0.5 m tall and 0.5-3 m tall, respectively) were removed. Next, starting with the largest trees, healthy mature trees were selected to remain. These selected trees decreased in size until their cross-sectional area summed to the required

1.86 or 3.72 m2. per acre that would remain. All remaining unselected trees were removed. All treated plots were broadcast seeded during the fall after treatments with a mix of shrubs, perennial grasses, and forbs (Table 1).

Figure 1. Imagery of Wellington Hills field site, located in western Nevada, U.S., showing blocks and numbered plots. The area was treated in 1984 with three different woodland reduction treatments and one control: Plots 1, 9, 11 = clear cut treatment, plots 2, 5, 10 = 40 BAF (Basal Area Factor, a cut leaving a trunk cross-sectional area of 1.86 or 3.72 m2 per acre) treatment, plots 3, 6, 7 = 20 BAF treatment, plots 4, 8, 12 = untreated controls.

Scientific Name Common Name Status Seeded kg / ha Bassia prostrata1 forage kochia Introduced 0. 28 kg / ha Artemisia tridentata ssp. vaseyana mountain big sagebrush Native 0. 28 kg / ha Krascheninnikovia lanata2 winterfat Native 0. 28 kg / ha Agropyron cristatum crested wheatgrass Introduced 2.24 kg / ha Thinopyrum intermedium3 intermediate wheatgrass Introduced 2.24 kg / ha Bromus inermis smooth brome Introduced 2.24 kg / ha Poa secunda4 Sandberg bluegrass Native 2.24 kg / ha Sanguisorba minor small burnet Introduced 1.12 kg / ha Medicago sativa alfalfa Introduced 1.12 kg / ha Linum lewisii Lewis flax Native 0. 28 kg / ha Astragalus cicer chickpea milkvetch Introduced 0. 28 kg / ha 1 Formerly Kochia prostrata 2 Formerly Ceratoides lanata 3 Formerly Agropyron intermedium 4 Formerly Poa ampla

Table 1. Seed mix components and kilograms (kg) per hectare that were broadcast seeded at the Wellington Hills woodland reduction field site (western Nevada, U.S.) in 1984. Species in bold were observed in our 2016 survey.

In the original study design, treatment plots were further divided into nine square sub-plots (Fig. S2) and these sub-plots underwent a range of sub-treatments, which included a variety of harvest and burn treatments (Table S1). Unfortunately, records detailing the randomized placement of the sub-treatments were misplaced, but we designed our sampling to measure vegetation characteristics across sub-treatments (Fig.

S2 and S3). Thus, we cannot analyze long-term effects of the sub-treatments, and they essentially add error to the main treatments. Other non-random factors affected plots.

Within three years of original treatments, the bulk of trees left in 20 and 40 BAF treatments were affected by bark beetles (Tausch, personal observation). Additionally, woodcutters harvested some of the trees from the western edge of Block 1 in the first several years after treatments. Finally, the Jackass Flat Fire, a major wildfire that occurred in 2006, burned around the project site, and affected the western edge of Block

1, where a small fire ignited. We designed our vegetation sampling to maximize our ability to measure differences among the four main treatments, despite these issues.

Vegetation Measurements

We recorded vegetation measurements in July 2016, using a modification of the

Assessment, Inventory, and Monitoring (AIM) strategy (Taylor et al., 2014) that allows for comparisons with other data collected at additional restoration sites. Data were collected by Nevada Department of Wildlife vegetation survey technicians. Technicians were calibrated through repeated sampling along the same transect until all observers were within a 10% absolute deviation from one another. Nine transects, each 15 m in length, were established within 20 and 40 BAF treatment plots, all oriented at 70° (Fig.

S2), and three 45 m length transects were oriented at 70° in control and clear cut transects

(Fig. S3). Thus, sampling occurred in the same intensity across all sub-treatments, even though their precise locations within the larger treatment plots were unknown.

We quantified ground cover, vegetation composition to species, proportion of soil surface in large intercanopy gaps, density of woody species, and overall species richness.

We used line-point intercept sampling to catalog foliar cover by species and ground cover with a reading of intercepted plants and ground cover taken at the drop of a pin flag each meter. Along each sampling transect, we measured gaps in the canopy between perennial species, recording all gaps greater than 20 cm. We then classified measures into gap length categories (20-24 cm, 25-50 cm, 51-100 cm, 101-200 cm, 201+ cm). Shrub and tree density counts were within a 30 or 90-m² belt area around each transect, and all woody species within each transect were cataloged according to species and size class.

Tree size classes were: <0.5 m tall, 2-10 cm DRC (diameter at root collar—ground level),

11-20 cm DRC, and >20 cm DRC, while shrub size classes were: 0-5 cm tall, 5-50 cm tall, and >50 cm tall. Finally, a species search (either 2 minutes per sub-plot encompassing one of nine segmented transects, or 18 minutes total throughout clear cut and control plots) was completed, cataloging all species encountered. Total species counts comprised all taxa identified to family at minimum, and cataloged as native/introduced or invasive according to USDA plants database (USDA and NRCS,

2018). Dead beyond recognition species were not included in overall richness counts, as we could not reliably determine if they were separate species from others already cataloged.

Statistical Analyses

We used mixed models incorporating block as a random effect to examine the influence of the four main treatments on response variables, and we present test statistics

(F ratios) and P-values for these models. Due to the small number of replicates per treatments (3 blocks) and the unique nature of this long-term study, we conducted pairwise contrasts of all treatments regardless of overall model significance and use these contrasts to compare responses among treatments. This approach to analysis increases the risk of a Type 1 error, but as long-term studies in this system are rare, we judged Type II error to be a larger concern. In all figures, we present results of the pairwise comparisons but indicate when overall models were not significant, and in the results text, we specify when significant differences among treatments are only seen in pairwise comparisons. All analyses were conducted using R (R Core Team, 2017), with  = 0.05, not adjusted for multiple comparisons. In some cases, data were transformed to improve the distribution of the residuals and reduce heteroscedasticity, and transformations are noted in associated tables. Because the western edge of our study site had been subject to multiple disturbances, analyses were conducted with and without Block 1 to determine if there was any difference in responses. Removing Block 1 did not change the significance of responses, so it was retained for results shown here.

P. monophylla density was analyzed by tree size classes, and we extrapolated density measurements from our survey area to average trees per hectare. Average trees per hectare were calculated by taking the mean of P. monophylla counts in each size class

22 over the three (or nine) transect belts at each monitoring plot and converting those counts to trees/ha. In plot 9 (clear cut), density was inadvertently conducted on only one of three transects, so values are based on only one count, rather than the average of three transects.

Foliar cover of shrubs was analyzed to examine responses to treatments. Shrub responses were analyzed as a group (all shrubs), for all sagebrush subspecies together (all sagebrush), and separately for two species, E. viridis and P. tridentata, because they are considered important wildlife forage (Anderson, 2001; Zlatnik, 1999). Although A. tridentata ssp. vaseyana was among the species originally seeded after treatments, this and other subspecies of sagebrush also occur naturally on the landscape, including outside of the project area, and it is likely that many of the sagebrush shrubs in our plots were not seeded. In our analyses of foliar cover of seeded species, we included control plots even though they were not seeded during the original treatment process; presence of seeded species in control plots would indicate colonization of non-treated areas.

For foliar cover analyses using line-point intercept data, we chose to use the category of “Any Hit” average, which combines like functional groups that are hit during a single pin drop into one group. For example, if two perennial grasses were in contact with the pin on a single drop, they would count as one instance. By using the Any Hit method as opposed to the “All Hit” method, we ensure we are not over-counting functional group foliar cover (although using the Any Hit method for individual species may result in cover values exceeding 100% (Karl et al., 2017)). The “First Hit” data category was used for bare ground, woody litter, and herbaceous litter, counting only

23 instances where these indicators were not located under other vegetation. Foliar cover of all species, native/introduced species (native species and the six introduced species that were seeded as part of this treatment), and invasive species was determined using line- point intercept measurements of individual species data grouped into the aforementioned categories, using the First Hit data category.

For comparisons of relationships between foliar cover of pinyon-juniper and native herbaceous and shrub vegetation, regression analyses were used. Pinyon-juniper foliar cover in each plot was regressed against foliar cover of all shrubs, all perennial grasses, and total foliar cover of all species.

Significance of pairwise comparisons is indicated with lowercase letters (Fig. 2, 5,

6, S5-S8), where the upper and lower whiskers of each box plot represent the minimum and maximum values observed for each species or indicator, the center line shows the median value, and the upper and lower boundaries of each box depict the upper and lower quartiles, with values intermediate between the maximum or minimum observation and the median observation. Individual transect values are depicted as dots on some figures, for foliar cover/ground cover responses, though transects were averaged within each block for analysis. All numeric details regarding box plots can be found in supplemental tables S2-1 to S9-3.

Results

There was a significant relationship between pinyon-juniper cover and foliar cover of perennial grasses (R2 = 0.832, P < 0.0001, slope = -1.07), shrubs (R2 = 0.497, P =

0.0105, slope = -0.69), and total species (R2 = 0.857, P < 0.0001, slope = -0.83) (Fig. S4a- c). Overall, the strongest treatment effects were seen in the increase in foliar cover of perennial grasses, decrease in foliar cover of P. monophylla, increase in foliar cover of P. tridentata and the category of “all shrubs”, increases in the cover of three non-native seeded grasses (T. intermedium, B. inermis, and A. cristatum), as well as a decrease in P. monophylla density and size of overall canopy gaps. Other response variables (including

P. tridentata and E. viridis density and herbaceous litter) showed weaker responses to treatments (Table 2).

Response Variable F-statistic1 P-value A. Focal species/groups—Average Foliar Cover Pinus monophylla 29.5 0.0005*** Perennial grasses 31.4 0.0050** All shrubs t 8.4 0.0145* Purshia tridentata t 7.6 0.0181* Bromus tectorum 1.1 0.4156 All sagebrusht 2.9 0.1213 B. Average Density—Trees and Shrubs Pinus monophylla / ha (< 0.5 m) 0.7 0.5683 Pinus monophylla / ha (2-10 cm DRC) 0.6 0.6312 Pinus monophylla / ha (11-20 cm DRC) 14.1 0.0040** Pinus monophylla / ha (>20 cm DRC) 11.2 0.0072** Ephedra viridis / ha (All size classes) 4.3 0.0597~ Purshia tridentata / ha (All size classes) 4.2 0.0646~ C. Seeded Graminoids—Average Foliar Cover Thinopyrum intermedium t 5.9 0.0319* Agropyron cristatum 6.6 0.0252* Bromus inermis t 6.4 0.0263* Poa secunda t 2.6 0.1710 D. Treatments—Seeded Grass Average Foliar Cover 20 BAF 6.3 0.0273* 40 BAF 19.9 0.0016** Clear Cut 4.9 0.0462** Control 0.6 0.6159

E. Soil surface and subsurface—Average Cover Herbaceous litter 4.0 0.0710~ Total litter 4.3 0.0616~ Woody litter 2.0 0.2161 Bare soil 1.2 0.3772 F. Length Average (cm)—Canopy Gap All Gaps t 6.3 0.0277* Gaps 25 - 50 cm 2.9 0.1267 Gaps 101 - 200 cm 3.2 0.1070~ Gaps 201+ cm 2.3 0.1762 G. Species Richness (Tally) All Species 3.2 0.1059~ Native/Introduced Species b 2.6 0.1459 Invasive Species 1.8 0.2561 H. Species Groupings (Average Foliar Cover) All Species 9.9 0.0097** Native/Introduced Species 2.9 0.1228 Invasive Species 1.2 0.3962 1 Error degrees of freedom for all analyses were 6 t Denotes logged value b Denotes Box-Cox transformation ~Indicates significance in pairwise contrasts only, with differences shown in figures

Table 2. Results from mixed models using the restricted maximum likelihood method to determine overall model significance. Values are F-ratios and p-values from each model. Significant p-values are bolded and indicate overall model significance; significance in associated figures is shown from pairwise contrasts among treatments. Responses are: average foliar cover and density of target species, plant functional groups, and litter categories calculated via line-point intercept and density belt sampling (Table 2A-E, H); average gap lengths (in binned length categories) between perennial species, calculated via canopy gap measurements (Table 2F); total, native/introduced, and invasive species richness calculated via timed species inventories (Table 2G).

Pinyon-juniper cover and density

Thirty-two years after treatment, P. monophylla foliar cover was significantly lower in treatment plots (average of 2-8%) compared to control plots (32%), with no differences among treatment types (Table 2A, Fig. 2a). Density of larger P. monophylla trees (both 11-20 cm DRC and >20 cm DRC) was also significantly lower in all treated

26 plots, regardless of treatment type (Table 2B, Fig. S5c & S5d). P. monophylla contributed the greatest percent foliar cover of any species in control plots (Fig. 3a), and the majority of those trees were in the largest size class (>20 cm DRC) (Fig. 4). No significant differences in density were found in smaller size classes of P. monophylla (< 0.5 m and

2-10 cm DRC) among treatments or controls (Table 2B, Fig. S5a & S5b), and P. monophylla seedlings (< 0.5 m tall) were detected throughout all plots (average of 86-160 trees/ha in treated plots vs. 111 in controls). Juniperus osteosperma was observed within field site boundaries during species richness searches, but was not detected in line-point intercept sampling, indicating the dominance of P. monophylla in this section of pinyon- juniper woodlands.

Figure 2. Foliar cover of target species and functional groups at the Wellington Hills field site in western Nevada, U.S. Significance of pairwise comparisons is indicated with lowercase letters, and individual transect values are depicted as dots on figures, though transects were averaged within each block for analysis. 20 BAF treatment indicates a cut leaving a trunk cross-sectional area of 1.86 m2 per acre, 40 BAF treatment indicates a cut leaving a trunk cross-sectional area of 3.72 m2 per acre, and clear cut treatment indicates

28 the removal of all trees. Overall model significance (P < 0.05; Table 2) is indicated with * after subfigure headings.

Figure 3. Overall average species1 foliar cover at the Wellington Hills field site in western Nevada, U.S., for each treatment: 20 BAF treatment indicates a cut leaving a trunk cross- sectional area of 1.86 m2 per acre, 40 BAF treatment indicates a cut leaving a trunk cross- sectional area of 3.72 m2 per acre, and clear cut treatment indicates the removal of all trees. Values are means and standard errors calculated across blocks, and are shown for all species detected during line-point intercept sampling; the total number of species observed in each treatment is indicated in each plot. 1ACHY: Achnatherum hymenoides, ACPI2: Achnatherum pinetorum, ACTH7: Achnatherum thurberianum, AGCR: Agropyron cristatum, ARHO: Arabis hoffmannii, ARHO2: Arabis holboellii, ARAR8: Artemisia arbuscula, ARTR2: Artemisia tridentata, ATCA2: Atriplex canescens, BRIN2: Bromus inermis, BRTE: Bromus tectorum, CALOC: Calochortus, CHDO: Chaenactis douglasii, CHVI8: Chrysothamnus viscidiflorus, COPA3: Collinsia parviflora, DEPI: Descurainia pinnata, ELEL5: Elymus elymoides, EPVI: Ephedra viridis, ERIAS: Eriastrum, ERSP3: Eriastrum sparsiflorum, ERNA10: Ericameria nauseosa, ERBL2: Erigeron bloomeri, ERUM: Eriogonum umbellatum, ERCI6: Erodium cicutarium, GARA2: Gayophytum ramosissimum, GIIN2: Gilia

29 inconspicua, KOMA: Koeleria macrantha, MEAL6: Mentzelia albicaulis, MIGR: Microsteris gracilis, PHLO2: Phlox longifolia, PIMO: Pinus monophylla, POFE: Poa fendleriana, POSE: Poa secunda, PUTR2: Purshia tridentata, RIVE: Ribes velutinum, SIAL2: Sisymbrium altissimum, THIN6: Thinopyrum intermedium, TRDU: Tragopogon dubius

Figure 4. Total P. monophylla density (average trees/hectare) for 4 size classes (depicted in legend) and standing dead trees summed across all blocks in each treatment (20 BAF treatment indicates a cut leaving a trunk cross-sectional area of 1.86 m2 per acre, 40 BAF treatment indicates a cut leaving a trunk cross-sectional area of 3.72 m2 per acre, and clear cut treatment indicates the removal of all trees) at the Wellington Hills field site in western Nevada, U.S.

Figure 5. Foliar cover of seeded grasses at the Wellington Hills field site in western Nevada, U.S. Significance of pairwise comparisons is indicated with lowercase letters, and individual transect values are depicted as dots on figures, though transects were averaged within each block for analysis. 20 BAF treatment indicates a cut leaving a trunk cross-sectional area of 1.86 m2 per acre, 40 BAF treatment indicates a cut leaving a trunk cross-sectional area of 3.72 m2 per acre, and clear cut treatment indicates the removal of all trees. Native seeded species: P. secunda. Introduced seeded species: T. intermedium, A. cristatum, and B. inermis. Overall model significance (P < 0.05; Table 2) is indicated with * after subfigure headings.

Foliar cover and density of shrubs (including key wildlife shrubs)

Artemisia tridentata foliar cover was significantly higher in 20 BAF treated plots relative to controls in pairwise contrasts (10% vs. 2%, respectively), with intermediate values in 40 BAF and clear cut treatments (Fig. 2c). No significant differences in A. tridentata density were found among treatments and controls (data not shown), although there were generally higher A. tridentata densities in treated plots (average of 1173-1778 plants/ha vs. 457 plants/ha in controls). Foliar cover of all shrubs was significantly greater in all categories of treatment (average of 25-27%) compared to controls (average of 5%) (Table 2A; Fig. 2d). Overall modeling of shrub density revealed near significance

(P=0.059), and in pairwise comparisons, density of shrubs in 20 and 40 BAF treatments was significantly higher (P < 0.05) than controls, with intermediate shrub densities in clear cut treatments (average of 2371-3666 shrubs/ha in treatments vs. 901 shrubs/ha in controls). Purshia tridentata foliar cover was significantly greater in all treatments relative to controls (average of 12%-15% vs. 2%) (Fig. 2e), and pairwise contrasts revealed significantly higher densities of P. tridentata in 20 and 40 BAF treatments compared to controls (311-351% more in treatments), with intermediate values in clear cut treatments (Fig. S5e). While there were no significant differences in foliar cover or density of E. viridis among treatments and controls (data not shown), pairwise comparisons of density revealed significantly more E. viridis in 40 BAF treatments

(average of 308 shrubs/ha) compared to clear cut and controls plots (average of 111 and

86 shrubs/ha, respectively), with intermediate values in 20 BAF treatments (Table 2B;

Fig. S5f). Evaluation of foliar cover composition (by species) within each treatment

32 group showed rubber rabbitbrush (Ericameria nauseosa (Pall. ex Pursh) G.L. Nesom &

Baird) and yellow rabbitbrush (Chrysothamnus viscidiflorus (Hook.) Nutt.) were only present in clear cut plots (Fig. 3d).

Foliar cover of perennial grasses, forbs, and seeded species

Cover of perennial grasses was significantly higher in treated plots compared to controls (Table 2A), and clear cut treatments exhibited significantly greater foliar cover

(average of 43%) than 20 and 40 BAF treatments (average of 30%) (Fig. 2b).

Intermediate wheatgrass (Thinopyrum intermedium ((Host) Barkworth & D.R. Dewey), performed particularly well in treatments (average of 14-25% foliar cover), compared to

Poa secunda (average of 0-1.5% foliar cover), which had the lowest cover. Foliar cover of Bromus inermis and Agropyron cristatum was intermediate (average of 4-9%) (Fig.

5a-d, Fig. S6). T. intermedium was the most abundant seeded species and differed strongly among treated and control plots (Table 2C, 2D), with pairwise comparisons revealing significantly greater T. intermedium cover in all treated plots relative to controls (Fig. 5a, Fig. S6). T. intermedium also contributed the greatest amount of foliar cover of any species in clear cut plots (Fig. 3d). Crested wheatgrass (Agropyron cristatum

(L.) Gaertn.) had significantly higher foliar cover in 20 BAF and clear cut plots relative to controls, with intermediate cover in the 40 BAF treatment (Fig. 5b; Table 2C).

Significantly greater foliar cover of smooth brome (Bromus inermis Leyss.) was seen in all treated plots when compared to controls (Fig. 5c).

Small amounts of native, non-seeded perennial grasses were measured. Because of low abundance, we did not analyze differences in individual species among treatments, but observations included E. elymoides (2% cover in treated plots, 2% in controls),

Achnatherum thurberianum (0-1% in treated plots, 1% in controls), Achnatherum hymenoides (0-1% in treated plots, 0% in controls), Achnatherum pinetorum (0-1% in treated plots, 1% in controls), and Poa fendleriana (0-1% in treated plots, 0% in controls). Seeded grasses did appear in control plots, but at low levels (<1.5% foliar cover) (Fig. S6a). Six of eleven seeded species were not observed in any manner during sampling, including forage kochia (Bassia prostrata (L.) A.J. Scott), winterfat

(Krascheninnikovia lanata (Pursh) A. Meeuse & Smit), and all four seeded forbs (Table

1). Overall, average perennial forb cover was low and there were no differences in foliar cover of perennial forbs among different treatments (average of 0.25-0.50% foliar cover) or between treatments and controls (average of 0.50% foliar cover in controls).

Cover of weedy and invasive species

B. tectorum foliar cover was generally higher in treated plots compared to controls, although there was high variability within treatment plots and neither overall models nor pairwise comparisons were significant (Table 2A, Fig. 2f). B. tectorum contributed the greatest amount of foliar cover (average of 24-27%) of any species in 20 and 40 BAF treatment plots and was the second highest contributor to cover in the clear cut treatments (20%, Fig. 3b-d). Only three other invasive species were observed at detectable levels during line-point intercept sampling: redstem stork’s bill (Erodium

34 cicutarium (L.) L’Her. ex Aiton), tall tumblemustard (Sisymbrium altissimum L.), and yellow salsify (Tragopogon dubis Scop.). Two additional invasive species were observed during species richness searches only: herb sophia (Descurainia sophia (L.) Webb ex

Prantl) and prickly Russian thistle (Salsola tragus L.). All five of these species contributed negligible amounts of foliar cover in plots and showed no significant differences among treatments (data not shown).

Ground cover

The strongest treatment effects on ground cover were observed for herbaceous and total litter, followed by woody litter, though no differences were significant in the overall models (Table 2E). In pairwise comparisons, there was significantly less herbaceous litter in 20 and 40 BAF treatments relative to the clear cut treatment (average of 60-62% vs 73% cover in clear cuts), while no significant differences were observed between any treatments and controls (Fig. S7a). Total litter was also significantly lower in 20 and 40 BAF treatments relative to the clear cut treatment (average of 64-65% vs

74% cover), again with no significant differences observed between any treatments and controls (Fig. S7b). Significantly greater cover of woody litter was observed in control plots relative to clear cut treatments (average of 14% vs. 3%), with intermediate values in

20 and 40 BAF treatments (Fig. S7c). Finally, there were no significant differences in the percent cover of bare soil among treatments, controls, or overall (Fig. S7d).

Size of perennial canopy gaps

Mixed models indicated significant differences among treatments in overall average gap size (Table 2F). Pairwise comparisons of binned gap length groups revealed significant differences between control plots and some treatments for most gap length categories (Fig. 6). Control plots had larger average gaps in perennial canopy (Fig. 6a), while treated plots had a greater proportion of smaller gaps (Fig. 6b). No differences were observed in pairwise comparisons for binned gap lengths of 20-24 cm and 51-100 cm

(data not shown). For canopy gaps in the range of 101-200 cm, significantly more were observed in controls compared to clear cut plots, with intermediate values in 20 and 40

BAF treated plots (Fig. 6c). For canopy gaps greater than 200 cm, significantly more were observed in controls compared to 40 BAF plots, with intermediate values in 20 BAF

36 and clear cut plots (Fig. 6d).

Figure 6. Average perennial canopy gaps (binned into different cm gap length categories) at the Wellington Hills field site in western Nevada, U.S. Significance of pairwise comparisons is indicated with lowercase letters, and individual transect values are depicted as dots on figures, though transects were averaged within each block for analysis. 20 BAF treatment indicates a cut leaving a trunk cross-sectional area of 1.86 m2 per acre, 40 BAF treatment indicates a cut leaving a trunk cross-sectional area of 3.72 m2 per acre, and clear cut treatment indicates the removal of all trees. Overall model significance (P < 0.05; Table 2) is indicated with * after subfigure headings.

Overall, native/introduced, and invasive species richness and cover

Across the whole site, we observed 71 species total, comprising 65 native/introduced and 6 invasive species (Table S11). In pairwise comparisons, we observed significantly greater numbers of overall species in 20 BAF treated plots when compared to control plots (Table 2G), with intermediate values for 40 BAF and clear cut treatments (Fig. S8a). Foliar cover of all species, including trees, shrubs, forbs, and grasses, was significantly higher in treated plots (average of 72-82%) relative to controls

(average of 56%) (Fig. S8b). No significant differences in richness were found for native/introduced species only (Fig. S8c), but in pairwise comparisons, native/introduced species foliar cover was significantly higher in clear cut (average of 68%) vs. control plots (average of 53%) (Fig. S8d). Invasive species richness and cover were greater in treated plots in general (foliar cover average of 14-17% vs. 2% in controls), although there was high variability within treatments and differences were not significant overall

(Table 2G & 2H) or in pairwise contrasts (Fig. S8e and S8f).

Discussion

Woody expansion has been observed worldwide for over a century (Chambers et al., 1999; Miller et al., 2005; Miller and Wigand, 1994; Weisberg et al., 2007). In the

Great Basin, U.S., increases in the range, density, and cover of pinyon-juniper woodlands are reducing shrub and herbaceous cover, which in turn is affecting habitat quality for shrub-dependent wildlife species (Miller et al., 2005). Additionally, as tree cover increases and understory canopy cover decreases, susceptibility to soil erosion is increased, which can reduce overall site productivity (Pierson et al., 2013, 2010;

Williams et al., 2014). In areas where sagebrush steppe habitats are desired, pinyon-

38 juniper thinning and removal treatments have been widely used to achieve this management goal, but exhibit varying levels of success when revisited decades after initial treatments were conducted (Bristow et al., 2014; Redmond et al., 2013; Tausch and

Tueller, 1977). In some areas, tree thinning and removal have resulted in increases in cover of perennial forbs and grasses, a decrease in cover of invasive weeds, and reductions in woody fuel accumulation (Bates et al., 2017a, 2005; Roundy et al., 2014b), consistent with management goals. In other studies, long-term monitoring has shown that restocking of trees after treatments can occur in as little as 15 years or so after treatment

(Bates et al., 2017b; Bristow et al., 2014; Tausch and Tueller, 1977), indicating that treatments need to be repeated to maintain desired shifts in community composition.

In this study, we observed that tree cover remained low in treated plots for over

30 years, but also detected P. monophylla seedlings in all treated and control plots, indicating that treatment effects may not persist. Based on the high cover of litter and nurse shrubs remaining on site to promote establishment, it is likely that P. monophylla seedlings will continue to proliferate, with recruitment likelihood also dependent on future precipitation levels (Castro et al., 2011; Chambers et al., 1999; Weisberg et al.,

2007). Consistent with other long-term studies of woodland reduction techniques (Bates et al., 2007; Gallo et al., 2016; Redmond et al., 2013), we observed that shrubs and grasses increased in response to treatments, with especially strong responses from the non-native seeded grasses. Of these, T. intermedium, A cristatum, and B. inermis had strong responses on treated sites, while native seeded P. secunda performed poorly.

Perennial forb responses to woodland reduction can be particularly sensitive to treatment

39 type and site vegetation composition pre-treatment (Bates et al., 2017b; Miller et al.,

2005; Roundy et al., 2014b), and in our study, all plots had very low cover of perennial forbs, indicating that factors other than treatment type (including pre-treatment woodland density and weather patterns associated with the sampling year) may have constrained perennial forb response (Bates et al., 2018). Untreated controls had the largest average gaps in perennial canopy, as has been observed in other studies (Pierson et al., 2015; Reid et al., 1999), and highest cover of woody fuels. We observed these overall treatment effects despite not controlling for particular sub-treatments within blocks (as information on original sub-treatment design was lost), indicating that main-plot treatments of clearing trees had strong impacts on vegetation responses, despite different methods of dealing with downed vegetation.

Different woodland reduction treatments are known to yield different effects on understory vegetation (Huffman et al., 2013; McIver et al., 2014; Stephens et al., 2016), and while all treatments at our site had some effect, the clear cut treatment consistently had the most positive vegetation responses. For example, tree seedlings were observed in the highest numbers in the 20 and 40 BAF treatments, demonstrating that clear cutting may be the best option to maintain tree absence in the long term. Clear cut plots also had significantly greater foliar cover overall compared to controls, and significantly greater foliar cover of seeded bunchgrasses and all shrubs compared to other treatments, indicating potential benefits of removing all trees from treatment sites. However, the complete removal of all trees from a site may be a more expensive treatment to

40 implement (https://www.firescience.gov/projects/05-S-08/project/05-S-

08_CostOfTreatments.pdf).

While some studies have suggested that initial weed response to treatments does not endure over time (Bates et al., 2005; Redmond et al., 2013), we saw evidence that weedy invasive species remained, and were patchy and variable in our sites. Though cover of B. tectorum, the most abundant invasive species at our site, was not significantly higher in cover in treated sites, visual inspection of cover results from individual transects indicates areas of high cover in some treatments (Fig. 2f), and B. tectorum had either the highest or second highest cover in treated sites. This observed variation in B. tectorum may be due to legacy effects from unknown sub-plot treatments and the timing of treatment implementation, as other studies have suggested that slash/burn treatments applied in the winter/early spring can reduce B. tectorum response because perennial herbaceous vegetation remains largely intact (Bates and Davies, 2017).

While these treatments have prevented trees from re-dominating the site more than three decades after original actions, the lack of forbs in any plot demonstrates that additional restoration methods or a change in approach may be needed to maximize habitat value. As vegetation monitoring was conducted during a single year, annual weather patterns may have affected the measured forb response (Bates et al., 2018). It is also possible that the environmental characteristics of our study site were not conducive for forbs, regardless of the presence of pinyon-juniper (Barga et al., 2018). Perennial forb cover may have also remained low after treatments as pinyon-juniper was not treated until it had become a mature, closed canopy woodland, and no seed sources remained

41 nearby for natural regeneration (Miller et al., 2005). Treating pinyon-juniper before it becomes a mature, closed canopy woodland can result in increased recovery of un-seeded perennial forbs (Bates et al., 2017a; Williams et al., 2017), and seeding forbs after tree shredding can increase perennial forb cover (Roundy et al., 2014a). However, in our study, none of the four forbs or two subshrubs that were seeded during original treatments were observed within the field site, consistent with other studies that have had similar challenges seeding forbs after mechanical treatments (Hulet et al., 2010; McAdoo et al., 2017). It is possible that other forb species or seed sources, including a greater emphasis on native or locally-collected seeds, could be used with greater success.

Although maintaining and increasing perennial bunchgrasses are key to preventing establishment and dominance by non-native annual grasses and providing forage for grazing animals (Chambers et al., 2007; Davies et al., 2010), in this study, the seeding of highly competitive introduced bunchgrasses may have been a detriment to establishment of perennial forbs and native bunchgrasses after treatment (Gunnell et al., 2010; Knutson et al., 2014). Additionally, the presence of B. tectorum throughout all plots may have affected forb response, as it is highly competitive in these systems (Chambers et al.,

2007). In a larger context, the lack of forbs at this site supports other research demonstrating a decline in Great Basin forb prevalence over the last 15,000 years in response to an increasingly arid climate (Nowak et al., 2017).

Conclusions

Monitoring the expansion of pinyon-juniper woodlands into sagebrush ecosystems has been long recommended (Miller and Wigand, 1994), as longer-term monitoring is needed to capture nuances in ecological response to tree expansion and tree removal (Bates et al., 2017; Havrilla et al., 2017; Miller et al., 2005). Long-term monitoring of tree removal is especially needed because treatment effects may not be observed for years or even decades post-treatment (Tausch and Tueller, 1977; Weisberg et al., 2007). As Great Basin vegetation management goals evolve, increasing the scope and timeframe of monitoring efforts may be particularly important for understanding the long-term response of sagebrush obligate species to habitat restoration (Gallo et al.,

2016). Based on our findings, in wooded shrublands where a return to sagebrush steppe habitat is desired, conducting clear cutting in conjunction with seeding may be one of the best tools to ensure increased cover of shrubs and forage grasses. Additional research will be necessary to ensure a healthy perennial forb response and prevent dominance of invasive B. tectorum. Further, while all treatments suppressed tree cover over the 32 year period, tree seedlings have returned, especially in the partially-thinned treatments, and larger, mature trees (75+ years old) will continue to produce seed crops, reaching maximum production between 160-200 years based on longevity estimates (Zouhar,

2001). In the absence of increases in fire frequency, additional mechanical clearing may need to occur for these communities to remain dominated by shrubs and grasses.

Acknowledgements

Maria Jesus, for assistance with all aspects of research planning, monitoring, and data analysis. Dave Miceli, for help with data collection and spatial analyses, and the 2016

NDOW field crew leaders and technicians.

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Chapter 2

Changes in plant community composition and ground cover in sagebrush steppe:

effects of pinyon-juniper cover and environmental variables

Cody Ernst-Brock a*

Elizabeth A. Leger a

a Department of Natural Resources and Environmental Science, University of Nevada,

Reno, 1664 N. Virginia Street, Mail Stop 186, Reno, NV 89512, USA

* Correspondence: [email protected]

Phone: (775) 225-4210

This work was funded by the Nevada Department of Wildlife.

Abstract

Changes in the range, distribution, and cover of plant communities are occurring in the Great Basin. These changes include increases in cover and distribution of pinyon pine (Pinus monophylla) and Utah juniper (Juniperus osteosperma) (hereafter referred to as pinyon-juniper), decreases in forbs, and increases in annual, invasive cheatgrass

(Bromus tectorum). Using vegetation data repeatedly collected across northern Nevada and eastern California during 2011-2017, we calculated change in foliar cover for vegetation functional groups, litter, and target grass species, and determined initial cover of vegetation functional groups and species at 229 individual monitoring plots across 19 sites. We obtained site-specific weather data for the observational period, including annual and seasonal precipitation, temperature minimums and maximums, and locational data including slope, aspect, latitude, and longitude. We assigned each plot a vegetation- type ranking based on the relative dominance of sagebrush or pinyon-juniper within the monitoring area (sagebrush or pinyon-juniper Phases I-III). We used random forest and mixed modeling techniques to determine which of these variables had the strongest associations with change over time. Overall, we saw that vegetation type was consistently among the top predictors of vegetation and litter change, and that environmental variables had fewer predictable associations with change. As pinyon-juniper dominance increased in plots (moving from Phase I to III), we saw decreases in foliar cover of shrubs and sage-grouse preferred forbs, and a trend toward decreases in total forbs, sagebrush, and all perennial nonwoody species. Conversely, litter of all types (herbaceous, woody, total) increased significantly in Phase II and III woodlands. Increased winter precipitation was

53 associated with increases in herbaceous litter, and litter had the greatest cover increases in all sampling plots regardless of vegetation type. Increased winter precipitation was also associated with a trend towards B. tectorum cover increase. B. tectorum increased significantly in areas with higher initial litter cover, while bluebunch wheatgrass

(Pseudoroegneria spicata) decreased in these areas. Higher maximum summer temperatures were associated with decreases in foliar cover of sage-grouse preferred forbs, while areas with higher fall minimum temperatures showed decreases in all shrub categories (sagebrush, non-sagebrush shrubs, and total shrubs). Finally, cover of squirreltail (Elymus elymoides) decreased in areas with higher summer maximum temperatures, and trended towards decrease in areas with higher fall minimum temperatures. This information can be used to predict future changes in these communities, and continued long-term vegetation monitoring will be crucial to inform broader evaluations of vegetation change and help determine appropriate management strategies in the Great Basin.

Keywords

Great Basin, vegetation change, monitoring, pinyon-juniper, forbs

Introduction

As climates and management practices change, plant communities in the intermountain west have responded through changes in vegetation composition, cover, richness, range, and distribution (Allen and Breshears, 1998; Langley et al., 2018; Lenoir et al., 2008; Vitt et al., 2010). While there is uncertainty about how vegetation will continue to change, data on past vegetation changes can be used in conjunction with forecast modeling to predict how communities may shift in the future under different conditions (Creutzburg et al., 2014; Franklin et al., 2016; Hardegree et al., 2018; Homer et al., 2015).

The Great Basin encompasses much of Nevada, and is home to large areas of sagebrush shrublands that have undergone a variety of landscape-scale changes, prompting increased interest in research regarding effective management strategies

(Chambers and Wisdom, 2009). The climate in the Great Basin is becoming warmer, leading to less available water (Chambers and Pellant, 2008) and increased fire size and frequency (McKenzie et al., 2004), and the sagebrush steppe community has seen changes in vegetation including increased invasive species cover (Chambers et al., 2007), increased bare ground (Homer et al., 2015), loss of sagebrush (Artemisia tridentata) shrub cover (Bradley, 2010), and loss of forbs (Nowak et al., 2017). We are also observing an expansion of singleleaf pinyon (Pinus monophylla) and Utah juniper

(Juniperus osteosperma) woodlands (hereafter referred to as pinyon-juniper, or P-J) into former sagebrush steppe communities (Miller and Tausch, 2001; Tausch et al., 1981;

Weisberg et al., 2007), with a variety of potential causes and impacts.

Over the last century, pinyon-juniper woodlands have expanded into former sagebrush communities for multiple reasons including suppressed wildfire, increased grazing pressure, and climatic changes (Brockway et al., 2002; Chambers and Pellant,

2008; Miller and Tausch, 2001). While pinyon-juniper woodlands provide important habitat for species like the pinyon jay (Gymnorhinus cyanocephalus) (Balda and Kamil,

1998) and mule deer (Odocoileus hemionus) (Watkins et al., 2007), expansion of these trees into sagebrush steppe vegetation can be detrimental to sagebrush-obligate species like the greater sage-grouse (Centrocercus urophasianus), that depend on sagebrush for cover from predators, habitat for lekking and nesting, and the support of annual and perennial forbs crucial for forage (Bates et al., 2017; Coates et al., 2017, 2016; Davies et al., 2011; Prochazka et al., 2017). Effects of tree expansion on other vegetation can be via direct competition: for example, there can be lower levels of success in meeting restoration goals as tree cover increases, presumably due to competition for soil resources

(Boyd et al., 2017; Davies et al., 2011). Pinyon-juniper expansion into sagebrush ecosystems also has indirect effects on vegetation by facilitating an increase in invasive, annual grasses like cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput- medusae) throughout the Great Basin (Prevéy et al., 2010). Increases in pinyon-juniper range and density can lead to greater tree crown connectivity, increasing fire susceptibility and intensity of fire regimes that in turn promote establishment and expansion of B. tectorum through its ability to germinate early and exploit available ground water before other species can reestablish after a burn (Chambers et al., 2007).

Forecast modeling has projected that even under circumstances of no additional climate change, pinyon-juniper will continue to expand over the next century (Creutzburg et al., 2014), while A. tridentata is projected to decrease in distribution, range, and climate niche availability (Schlaepfer et al., 2012; Still and Richardson, 2015). There is less modeling information available for forbs and graminoids in the Great Basin, but studies have shown that with increasing aridity in the current post-glacial period, forbs and perennial bunchgrasses are generally decreasing over time (Anderson and Inouye,

2001; Nowak et al., 2017).

Precipitation, temperature, and site condition (vegetation type, slope, aspect) all have an effect on changes in vegetation community composition, and some of these factors may have a larger effect than others. Multi-year, widespread monitoring that captures vegetation change over time across a wide variety of site conditions and climates is needed to inform projections of future change and help determine effective habitat management strategies (Boswell et al., 2017; Chambers and Wisdom, 2009; DeLuca et al., 2010; Elzinga et al., 1998; Havstad and Herrick, 2003; Pilliod et al., 2017b; Severson et al., 2017). Further, monitoring change of individual species across site conditions can allow us to better understand the effects of longer-term climate-related change on target species specifically important in Great Basin ecosystems.

Here, our goals are to use widespread vegetation monitoring to identify which species and functional groups are experiencing the largest changes abundance in the

Great Basin, and to identify the nature of the effects of pinyon-juniper abundance on other elements of Great Basin plant communities. To explore the relationships between

57 weather, site conditions, and change in vegetation community type and composition, we performed analyses using a large-scale data set of vegetation characteristics recorded repeatedly at multiple field sites in northern Nevada and eastern California over seven years (2011-2017). Pinyon-juniper abundance in sagebrush communities has been classified into several categories (Phases I-III) depending on vegetation characteristics:

Phase I retains shrubs and forbs as the dominant vegetation although trees are present,

Phase II sees trees and shrubs/forbs as codominant, and Phase III is characterized by tree dominance (Miller et al., 2005; Tausch et al., 2009). Focusing on sagebrush steppe communities in a variety of these phases (including sagebrush areas with little to no tree cover), we asked:

(1) What effect does vegetation type and initial plant community composition

have on vegetation functional group, litter cover, and species change over time,

and which community components show the largest changes over the sampling

period?

(2) How do environmental variables affect these changes, and what environmental

variables are the strongest predictors of change in functional groups, litter, or

species abundance?

Our environmental variables included annual and seasonal precipitation, maximum temperatures, and minimum temperatures, as well as latitude, longitude, slope, and aspect. One challenge of widespread vegetation sampling is that, by necessity, plant communities are sampled over a range of dates. We also investigate how this experimental design factor affects patterns of change. We expected to see increases in B.

58 tectorum cover in areas with higher precipitation and temperature, and decreases in cover in areas with higher initial shrub (especially sagebrush) cover (Prevéy et al., 2010). We predicted that we would see general decreases in perennial forbs, and relatively little change in woody shrubs and trees across sites, given the limited sampling time frame.

Given the results of others, we expected to see the largest decreases in perennial forbs in areas with the most pinyon-juniper cover (Williams et al., 2017), and expected areas with high tree cover to show decreases in shrubs and bunchgrasses as well. Due to climate conditions (wetter in the northern Great Basin, more monsoonal in the eastern Great

Basin), we expected increases in latitude to show greater increases in B. tectorum and increases in longitude to show increased tree cover and reduced shrub cover.

Materials and Methods

Site Description and Experimental Design

Vegetation monitoring plots were established in nineteen field sites across Nevada and eastern California (Fig. 1). Monitoring was established in areas where vegetation restoration had taken place or was slated to take place in the future. The locations of monitoring plots were determined using stratified random samplin58g to place plots within project boundaries, in areas of similar soil map units, and with access by roads.

Within each field site, control and treatment plots were established to track vegetation change pre- and post-restoration over time. For this analysis, we focused only on control plots that had been monitored at least twice between 2011 and 2017, and excluded any

59 areas that experienced wildfire or any treatments during this time frame. This resulted in

229 unmanipulated plots for further analysis (Table 1).

Vegetation Measurements

Vegetation measurements were recorded using a modification of the Assessment,

Inventory, and Monitoring (AIM) strategy (Taylor et al., 2014). Monitoring plots were established by running three 50-m transect tapes in a spoke design, oriented at 0°, 120°, and 240°, encompassing a total circular area of 9510-m2 (Fig. 2). We quantified vegetation foliar cover and ground cover using line-point intercept sampling techniques, where a pin flag was dropped every meter on each transect tape and all intercepted plant species and ground cover materials were recorded. Cover values were averaged among the three transect tapes, resulting in one value per plot. Field crews collected data at these plots after completing training and calibration activities to ensure relative uniformity in monitoring, verified by repeated data collection until all observers were within a 10% absolute deviation from one another.

We calculated vegetation change for each plot by subtracting foliar cover values recorded during the first year sampling occurred from the most recent recorded foliar cover values for functional groups and species. We calculated change for all plots, regardless of the number of years between sampling years, and then examined a subset plots with monitoring occurrences spanning the longest timeframe (six years between sampling in the 2011-2017 time frame for 50 plots). In this preliminary assessment, similar patterns of change were observed between this subset of longest-term

60 observations and the entire dataset, so we performed subsequent analyses on our entire set of monitoring data, including sampling year and month in our analysis to account for differences among sampling timeframes, as described below.

Environmental Measurements

Weather variables over the course of the observational period were calculated for each plot using data obtained from the PRISM database (PRISM Climate Group, Oregon

State University, USA; http://prism.oregonstate.edu). Rasters of monthly average precipitation (millimeters) and minimum and maximum temperature (degrees Celsius) were downloaded as .asc files and imported in program R (v.3.5.1; R Development Core

Team, 2018). Monitoring plot location data was also imported into R as a .csv and converted into a spatial points data frame. Next, average precipitation and minimum and maximum temperature for each monitoring plot were calculated in R, both by season and water year. Data by average water year for each plot location was calculated using monthly data for each monitoring year from October 1 of one year to September 30 of the next, and average seasonal data was calculated using the following parameters: winter:

December-February, spring: March-May, summer: June-August, fall: September-

November. As monitoring plots were sampled over various time frames across years, we took care to confirm weather data was calculated individually for each plot to ensure we only took into account the weather time frame corresponding with that plot’s specific monitoring time frame. For each plot, we used latitudinal and longitudinal coordinates recorded in the field by monitoring technicians at plot center locations, and slope and

61 aspect were determined using a 10-m digital elevation model by a geospatial analyst using the Extract Values to Points tool in ArcMap 10.4.1 (ESRI, 2016). To examine change by vegetation community types, we designated each plot as either having sagebrush-dominated vegetation, or pinyon-juniper expansion into sagebrush at Phase I,

II, or III. The difference between Phases I-III was determined by our geospatial analyst, who examined aerial photographs using a combination of imagery from the 2015

National Agriculture Imagery Program (NAIP), relevant yearly Google imagery, and

ArcMap base maps (ESRI, 2016). All plots in question were then assigned a vegetation- type ranking using the guidelines described in the USGS Piñon and Juniper Field Guide

(Tausch et al., 2009). Any plots located in riparian areas and aspen stands were not used for this analysis due to their infrequent number and limited geographic distribution.

Statistical Analyses

To ask what broad environmental factors and specific seasonal environmental variables were most predictive of change in the cover of litter, target grass species, and vegetation functional groups, we used the randomForest package in R (Liaw and Wiener,

2002) to determine which abiotic and vegetation community composition factors to include in subsequent multiple regression models. We selected species, functional groups, and ground cover types of interest, including several different litter types, perennial grasses, annual and perennial forbs, sage-grouse preferred forbs, several shrub categories, trees, all woody species, perennial nonwoody species, six target perennial grass species, and B. tectorum (Table 2). We chose specific perennial grass species to

62 examine individually because this functional group is easily detected using line-point intercept sampling and is an important component of the Great Basin ecosystem. We chose to look at B. tectorum because it is an invasive, annual grass that poses a persistent threat to habitat management, restoration, and fire capacity in the west (Chambers et al.,

2007). We included the starting cover of the aforementioned functional groups as covariates in our broad models to determine what effect initial vegetation community composition had on vegetation change over time. Additional variables used in models included the dominant vegetation type on each plot (sagebrush or Phase I-III pinyon- juniper), the start month/year and end month/year sampling occurred on each plot, and the number of days between sampling occurrences in different years. For example, if a plot was sampled originally on June 1st 2011, and resampled on June 30th 2017, the number of days between sampling would be 29. We limited our analysis to plots with a

‘days between sampling’ value of 62 or less (~2 months) to reduce any issues with strong seasonal differences in sampling time frames among years. We then used our plot- specific environmental and locational data (precipitation, temperature, slope, and aspect) to investigate the relationship between these variables and vegetation cover change over time.

We conducted random forest models on two different subsets of data: first, the broadest suite of environmental variables, with a focus on annual weather variables, and second, on a narrower suite of variables, focused on seasonal weather variables. For both our broad and seasonal models, we first reduced our dataset by removing variables that were highly correlated (>0.70 Pearson’s correlation coefficient). Weather data by water

63 year was used for our broad models. For all models, numeric data were scaled, and random forest analysis was used to determine the variables that most influenced change in vegetation functional groups, litter, and target grass species. For our broad models, we identified the top twenty variables associated with each response (Table 3a). We then used multiple regression in a mixed model framework to examine the relative influence of these variables on change over time. In all models, we included project site as a random effect and included the covariate ‘days between sampling’. Years between sampling occurrences was not included as a covariate in analyses due to high correlation with other time frame related covariates. We present standardized coefficients and indications of significance for significant (P <0.05) and nearly significant (P<0.10) variables from these models.

We then performed a second set of analyses in which we included seasonal environmental variables of specific interest. These seasonal variables were not included in the broad model, as they are highly correlated with annual weather, but we focused on them during this second analysis due to their known influences on vegetation in this region. These included: average winter precipitation and minimum temperature, average fall minimum temperature, and average summer maximum temperature, in addition to other variables of interest (Table 3b). In this analysis, we considered only the initial vegetation cover value for the functional group in question (for example, starting perennial graminoid cover would be the only initial cover value included in a model to determine covariate influence on perennial grass change over time). These analyses were conducted in the same mixed model framework outlined above, after removal of any

64 highly correlated variables and scaling of numeric values, and we present coefficients and indications of significance and near significance.

Results

Our analysis encompassed 19 sites, with an average of 12 monitoring plots per site (Table 1). Average annual precipitation at these sites was 327mm, and 90% of sites have an annual precipitation below 400mm. Average elevation across sites was 2113m, with an average of -0.5 °C minimum and 15.6 °C maximum temperatures. Time frames between monitoring occurrences at plots were variable, with 16% of plots monitored with one year in between sampling, 23% of plots with two years between sampling, 14% of plots with three years, 18% of plots with four years, 7% of plots with five years, and 22% of plots with six years between sampling (Table S1). Days between sampling averaged

24, with a range from 0 to 62. We had 76 plots in sagebrush, 65 in Phase I pinyon- juniper, 72 in Phase II, and 16 in Phase III.

(1) What effect does vegetation type and initial plant community composition have on vegetation functional group and species change over time, and which of these show the largest changes over the sampling period?

We observed variable ranges of change for different vegetation functional groups across our monitoring time frame (Fig. 3). In both the broad and seasonal models, the initial cover of the functional group targeted for analysis almost always had a significant effect on cover change over time (data not shown). Vegetation type (sagebrush, Phase II,

Phase III) also often had a significant effect on cover change in many of the targeted functional groups (8 of 20 responses in the broad model, 15 of 20 responses in the seasonal model), and therefore we also present change for all variables separately by vegetation type, calculated from field data (Tables 4b-4e). Phase I vegetation type was not a significant factor affecting cover change for any functional group in any model.

When examining monitoring plots by their dominant vegetation type, the greatest significant increases in average cover among functional groups and species were within the categories of herbaceous litter and total litter, in sagebrush, Phase II, and Phase III vegetation types in our broad model (Table 5a, Fig. 4), and in Phase II and Phase III in our seasonal model (Table 6a, Fig. 4). The largest cover increases observed in woody litter were in Phase III vegetation in both the broad and seasonal models (Table 5a, 6a,

Fig. 4). While litter increases were similar between sagebrush plots and Phase I plots, litter cover doubled in Phase II and increased above 50% in Phase III woodlands (Tables

4b-4e). All sage-grouse preferred forbs and all shrubs (sagebrush and other shrubs combined decreased), and total forbs and perennial nonwoody cover trended towards decrease in Phase III in our seasonal models (Table 6a, Fig. 5, 6, 7). Significant increases of B. tectorum were observed in sagebrush vegetation in our seasonal model, with a trend towards increase in needle and thread (Hesperostipa comata) (Table 6b, Fig. 8, 9). All tree cover increased, and all sagebrush cover trended toward a decrease in Phase II and

III vegetation types, in both broad and seasonal models (Table 5a, 6a, Fig. 6, 7).

Perennial graminoids and perennial nonwoody species cover increased significantly only in sagebrush in both the broad and seasonal models (Table 5a, 6a, Fig. 7, 10). Basin

66 wildrye (Leymus cinereus) cover decreased in Phase III vegetation in both models

(significantly in the seasonal model, and trending in the broad model), and bluebunch wheatgrass (Pseudoroegneria spicata) cover trended toward decrease in Phase III in our seasonal model (Table 6b, Fig. 9).

While days between sampling almost never appeared in top variables, start and end month frequently mattered (Tables S3a & b, S4a & b). We were more likely to see greater change in herbaceous litter with earlier sampling, and change in woody litter with later sampling. Sample year mattered for some responses, including change in perennial grasses, all litter categories, and Sandberg bluegrass (Poa secunda).

Starting cover values for functional groups and species in our broad models were frequently associated with change in other responses (Tables 5a & b). For example, sage- grouse preferred forbs showed significant cover increases in areas with high initial cover of non-sagebrush shrubs and P. spicata, and a trend towards decreased cover in areas with greater initial P. secunda cover. Areas with high initial tree cover showed significant increases in woody litter (Table 5a), while areas with high initial total litter cover showed a significant increase in B. tectorum cover (Table 5b). Sites with higher initial woody litter cover showed increased cover (significant or near-significant) for many functional groups in broad models, and decreased cover for sage-grouse preferred forbs (Tables 5a

& b). Sites with high initial perennial grass cover showed cover increases of perennial forbs and several individual perennial grass species, including squirreltail (Elymus elymoides), P. secunda, L. cinereus, and P. spicata.

(2) How do annual or seasonal environmental variables affect these changes, and what environmental variables are the strongest predictors of change in functional groups and species?

In our broad models, sites with increased average minimum temperatures showed significant decreases in all categories of shrub cover, including sagebrush (Fig. 11), non- sagebrush shrubs, all shrubs combined, and a trend towards increases in tree cover (Table

5a). Sites with greater precipitation showed significant increases in total (Fig. 12) and woody litter cover, as well as non-sagebrush shrub cover (Table 5a). Increases in aspect

(moving from north to east to south to west) showed significant decreases in all woody cover and a trend towards decreased tree cover, while higher longitude resulted in significant cover increases for these functional groups. All shrub cover decreased significantly when longitude increased. An increase in slope resulted in a significant decrease in woody litter cover, while an increase in latitude showed a trend towards a decrease in all sage-grouse preferred forbs. The aforementioned variables did not have a significant effect on cover change for any specific grass species in our larger models, with the exception of L. cinereus, which saw a trend towards cover decreasing with increased longitude and increasing with increased latitude (Table 5b).

Overall, seasonal variables revealed similar patterns for litter and functional groups, but were slightly better at predicting change in specific grass species. In our seasonal models (Tables 6a & b), sites with increased average fall minimum temperature showed decreases in all categories of shrub cover (sagebrush, non-sagebrush shrubs, all

68 shrubs combined, Fig. 13) and a trend towards decrease in E. elymoides cover. Areas with warmer summer maximum temperatures showed decreases in cover of all forbs (Fig.

14.), sage-grouse preferred forbs, E. elymoides, and a trend towards decreases in perennial forbs (Tables 6a & b). Increases in average winter precipitation resulted in increases in cover of herbaceous and total litter categories (Fig. 15), non-sagebrush shrubs, and a trend toward cover increases of woody litter and B. tectorum (Tables 6a & b). Sites with aspects trending south and west showed decreases in all woody species and tree cover, while increases in slope negatively affected woody litter cover and resulted in cover increases of non-sagebrush shrubs, Indian ricegrass (Achnatherum hymenoides), and a trend towards perennial grasses. Decreases in longitude resulted in a trend towards increased sagebrush cover.

Discussion

Analyses of change over time within Great Basin vegetation types show that invasive species and litter cover are increasing (Pilliod et al., 2017a), and pinyon-juniper woodlands are expanding (Bradley and Fleishman, 2008; Romme et al., 2009). As pinyon-juniper expands into former sagebrush steppe and tree canopies close, resources including precipitation and sunlight necessary to support important herbaceous vegetation including perennial graminoids and sage-grouse preferred forbs are limited (Miller et al.,

2005; Petersen and Stringham, 2008). Our observations support other research that has found that increasing tree cover can negatively impact understory plant communities

(Archer et al., 2012; Tausch et al., 2009), and that initial community composition can

69 affect species’ foliar cover change over time across a wide range of vegetation communities and site conditions (Mitchell et al., 2017; Reisner et al., 2013). We observed decreases in cover of forbs, including sage-grouse preferred forbs, in areas of higher tree cover, and sagebrush steppe was the only vegetation type in which we observed any cover increases of perennial grasses. Perennial and annual forbs and sage-grouse preferred forbs decreased in foliar cover by almost 300% between Phase II and Phase III woodlands, while perennial grass cover decreased by more than 75%.

As others have observed (Vitt et al., 2010), we also found that environmental factors like precipitation and temperature had varied effects on different vegetation functional groups and species that commonly occur throughout the Great Basin (Mitchell et al., 2017), with generally stronger effects observed for temperature than precipitation in our broad model. We also saw changes across latitude and longitude, and effects of slope and aspect. Specifically, as longitude increased (i.e. in more western sites), we observed larger decreases in shrubs and sagebrush and increases in tree foliar cover, while higher latitude sites (more northern sites) showed decreases in sage-grouse preferred forbs. Increased longitude showed a trend toward decreases in L. cinereus foliar cover, while increased latitude showed a trend toward increases. From these results, if management goals are to maintain sagebrush, perennial grass, and forb cover in areas with pinyon-juniper expansion, managers may want to prioritize tree removal treatments in more western and northern sites. We also saw that increases in slope resulted in a trend toward increases in perennial grasses and significant increases in non-sagebrush shrubs, and significant decreases in woody litter, while increased aspect showed decreases in tree

70 and general woody foliar cover. These observations could also be used to prioritize any tree removal treatments within sites. Finally, we determined that initial vegetation community composition was associated with changes in foliar cover, indicating that one- time surveys of plant communities could be used to predict short-term changes in species and functional groups. For example, in our study, areas with higher initial cover of sagebrush showed a trend towards decreases in B. tectorum cover, while higher initial cover of total litter showed increases, and higher initial woody litter cover led to increases in cover of P. secunda and P. spicata, with a trend towards L. cinereus.

Although our sampling time frame for this project is relatively brief, these short-term observations support longer-term research by others indicating similar vegetation shifts

(Anderson and Inouye, 2001) across a wide geographic range.

Annual weather patterns can effect vegetation community change over time

(Chambers and Pellant, 2008; Loarie et al., 2009), and the responses to short-terms measurements, such as we show here, may be indicative of longer-term trends related to gradual climate change. Other studies have found that climate change has influenced the timing of plant phenological events, including leaf emergence and flowering, shifts in vegetation range and distribution, and vegetation die-off (Breshears et al., 2005; Kelly and Goulden, 2008; Sykes, 2009). In addition to annual weather, changes in seasonality also affect plant communities. Here, we found that our seasonal models (which partitioned precipitation and temperature minimums and maximums by spring, summer, fall, and winter) were slightly better at predicting change in particular grass species, and that they showed similar trends in vegetation change when compared to our broad models

71 that looked at precipitation and temperature annually, by water year. For example, our analyses showed that increases in average winter precipitation resulted in trends toward increases in B. tectorum foliar cover, which is consistent with other studies (Bradley and

Mustard, 2008). Further, in our study, increases in average summer maximum temperature showed decreases in E. elymoides cover, and might indicate that this species is susceptible to warming temperatures. Forecast modeling has predicted decreases in range and cover of A. tridentata in upcoming decades (Schlaepfer et al., 2012; Still and

Richardson, 2015), and our short-term models demonstrate that increases in annual and seasonal average minimum temperature are associated with decreases in shrub and sagebrush foliar cover. Continuing monitoring over time will allow us to see how vegetation changes to a wider response of weather conditions, and will be useful for modeling change in sagebrush steppe communities.

A loss of forbs in the vegetation understory of the Great Basin has been observed in other studies (Nowak et al., 2017), and we found that forb foliar cover, including sage- grouse preferred forbs, has been decreasing with increasing maximum temperatures over the short term. As forbs are of specific management interest due to their importance as forage for some sagebrush-obligate species and attraction of pollinators, it may be worth the effort to use additional monitoring techniques to study their change over time, like quadrat sampling, as LPI-monitoring is not optimal at detecting small forbs. Further, though we analyzed forbs here as functional groups, a closer examination of the change over time in particular forb species may identify species that are resilient to current conditions, and could be prioritized in restoration efforts.

Increases in litter can have mixed effects in vegetation communities, and it is noteworthy that litter was increasing across all community types. Greater litter cover can help combat erosion (Pierson et al., 2015, 2007; Reid et al., 1999), but can also confer a greater risk of fire susceptibility as a layer of fine fuels (Miller and Tausch, 2001). We found that increasing winter and annual precipitation showed increases in litter cover of all types over our short-term monitoring time frame. Litter is also known to increase success of B. tectorum establishment (Bates et al., 2007), which would be detrimental in these systems. Longer-term monitoring could determine if there are years where we observe decreases in litter, due to factors such as increased decomposition under particularly wet winters or other climatic conditions.

This project was intended to develop a modeling framework to answer questions about what abiotic and vegetation community factors influenced vegetation change over time in the Great Basin, and there are a number of future directions we plan to pursue. As we continue to develop models, we plan on including additional abiotic data, like site soil characteristics, and examine changes in other vegetation responses, including species richness and woody shrub and tree density. We would also like to examine the change in species and functional group foliar cover as a function of continuous change in pinyon- juniper foliar cover, as a complement to the categorical vegetation communities examined here. Additionally, we are interested in examining whether there are effects interactions between environmental variables on vegetation functional group cover, asking, for example, if there are interactions between precipitation and temperature.

While we chose to use perennial grasses and B. tectorum to run species-specific analyses

73 of change because they are common and relatively easy to detect using line-point intercept sampling, we would also like to examine other specific species of interest, including forbs. Additionally, repeated monitoring at these sites in future decades will allow us to capture greater changes in woody vegetation like shrubs and trees, which take longer periods to shift in foliar cover than the limited time frame employed for these initial analyses. As start month and year, and end month and year matter (Tables S3-S4), we note that conducting subsequent resampling of plots in the same time frame would be helpful for future monitoring efforts. Continued vegetation monitoring is crucial to reveal additional long-term trends in vegetation community composition and cover changes.

Conclusions

Vegetation community cover, richness, range, and distribution change through interactions with annual and seasonal weather patterns, and are also affected by vegetation community composition. Changes in vegetation across the Intermountain West have been attributed, in part, to larger climatic shifts, annual and seasonal weather patterns, and increasing expansion of pinyon-juniper into former sagebrush steppe. As land managers determine the best methods for restoration and conservation of Great

Basin habitat critical to sagebrush-obligate species, vegetation data collected from repeated monitoring can be used to inform decision-making and forecast modeling. Our analyses have shown that in the short term, vegetation functional groups necessary to support sagebrush-obligate species like shrubs and forbs are decreasing in cover in areas with high pinyon-juniper tree cover, as has been observed in other research (Miller et al.,

2005; Rowland et al., 2008; Williams et al., 2017), with larger changes in western and northern sites. Concurrently, litter and cheatgrass cover are increasing, promoting greater habitat susceptibility to high intensity wildfires and further expansion of invasive species.

Continued collaboration among management agencies and further research on vegetation change, including vegetation monitoring, will be essential to address these shifts and predict future patterns of change.

Acknowledgements

The Nevada Department of Wildlife for project funding, Dave Miceli, for help with spatial analyses, the 2011-2017 NDOW field crew leaders and technicians, for data collection, and Matt Forister, for help with statistical analyses.

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Figures

Figure 1. Map of project monitoring plot locations across Nevada and eastern California.

Figure 2. Vegetation monitoring plot layout. Three 50-m transect tapes are extended from plot center, typically oriented at 0°, 120°, and 240°. A 5-m buffer zone around plot center is not sampled due to potential trampling of vegetation while surveying. Total area of each monitoring plot is 9510-m2.

Figure 3. Histograms of range of foliar cover change for selected vegetation functional groups.

Figure 4. Litter % foliar cover change among vegetation types. Values are means and standard errors of absolute vegetation change calculated from field data, and are not adjusted for factors (e.g. start month, latitude, etc.) included in multiple regression models.