regeneration dynamics of great basin bristlecone pine in ... · draft 1 1 regeneration dynamics of...

Draft

Regeneration Dynamics of Great Basin Bristlecone Pine in Southern Nevada

Journal: Canadian Journal of Forest Research

Manuscript ID cjfr-2019-0404.R1

Manuscript Type: Note

Date Submitted by the Author: 17-Feb-2020

Complete List of Authors: Burton, Philip; University of Northern British Columbia, Ecosystem Science and ManagementSimons, Jesy; University of Nevada Las Vegas; Modoc Wildlife RefugeBrittingham, Steve; n/aThompson, Daniel; University of Nevada Las Vegas, School of Life SciencesBrooks, Darin; College of the North Atlantic - Corner Brook CampusWalker, Lawrence; University of Nevada Las Vegas, School of Life Sciences

Keyword: Clark's nutcracker, fertile islands, forest fire, heat load, <i>Pinus longaeva</i>

Is the invited manuscript for consideration in a Special

Issue? :Not applicable (regular submission)

https://mc06.manuscriptcentral.com/cjfr-pubs

Canadian Journal of Forest Research

Draft

1

1 Regeneration Dynamics of Great Basin Bristlecone Pine in Southern Nevada

2

3

4 Philip J. Burton1

5 Jesy Simons2, 3

6 Steve Brittingham4

7 Daniel B. Thompson2

8 Darin W. Brooks5

9 Lawrence R. Walker2

10

11

12 1 Ecosystem Science and Management Program, University of Northern British

13 Columbia, Terrace, BC Canada V5G 1K7

14 2 School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154-4004

15 USA

16 3 Current address: Modoc Wildlife Refuge, Alturas, CA 96101-1610 USA

17 4 Mt. Charleston, NV 89124-9102 USA

18 5 College of the North Atlantic, Corner Brook, NL Canada A2H 6H6

19

20

21

Page 1 of 19



Draft

2

22 Abstract

23 Great Basin bristlecone pine (Pinus longaeva) is an important and long-lived tree species found

24 at high elevations in the interior southwest of the USA, but little is known about its regeneration

25 requirements and response to disturbance. We conducted extensive surveys of seedling

26 regeneration and environmental attributes of regeneration sites in undisturbed forest dominated

27 by this species in the Spring Mountains of southern Nevada. Additional surveys tallied new

28 seedling densities and site attributes four years after a wildfire in the same area. Seedlings,

29 saplings, and juvenile trees were less abundant than adult trees in the unburned forest and soils

30 had lower bulk density, and greater depth, moisture, and soil organic matter under adult trees

31 than in open areas. Seedling distributions in both unburned and burned forest showed a negative

32 relationship to a heat load index governed by aspect. The density of new seedlings after the fire

33 was negatively related to distance from unburned forest edges. Seedlings were found in clusters

34 and were associated with adult trees (live or dead) in both unburned and burned stands. Seedling

35 emergence from animal-dispersed caches was more frequent in burned than unburned habitats.

36 These natural regeneration dynamics provide potential guidance for restoration efforts in this

37 ecosystem.

38

39 Key words: Clark’s nutcracker, fertile islands, forest fire, heat load, Pinus longaeva

40

41

Page 2 of 19



Draft

3

42 Introduction

43 The Great Basin bristlecone pine (Pinus longaeva D.K. Bailey) is the longest-living, non-clonal

44 plant, with some individual trees surviving more than 4,000 years (LaMarche and Mooney

45 1972). Yet Pinus longaeva adults have relatively thin bark and are considered sensitive to fire

46 (Fryer 2004) and to white pine blister rust, Cronartium ribicola J.C. Fisch (Kinloch 2003, Vogler

47 et al. 2006). To date, however, Pinus longaeva remains the only North American five-needle

48 pine species with no confirmed incidence of white pine blister rust in wild populations (Bentz et

49 al. 2017, Miller et al. 2017). As a subalpine tree, bristlecone pine is vulnerable to a warming

50 climate as more competitive species move upslope. As a long-lived species, regeneration is

51 dependent on only a few seedlings surviving over the course of centuries to replace each adult.

52 However, regeneration dynamics of bristlecone pine are poorly understood (Fryer 2004, Stritch

53 et al. 2011), including seed bank dynamics, seed dispersal mechanisms and distances, and

54 seedling microsite preferences. Anecdotal observations suggest that Clark’s Nutcracker

55 (Nucifraga columbiana Wilson) may play an important role in seed dispersal (Fryer 2004).

56 Great Basin bristlecone pine forms nearly pure stands with sparse understories at

57 elevations above 2800 m in the Spring Mountains of southern Nevada, USA (Abella et al. 2012).

58 In July of 2013, the Carpenter-One Fire burned 11,000 ha of subalpine forests in the Spring

59 Mountains National Recreation Area (SMNRA) of southern Nevada (Kallstrom 2013, Hermann

60 2017), killing most trees within its perimeter. That recent disturbance provided an opportunity to

61 examine regeneration dynamics of this slow-growing tree species with and without fire. This

62 study reports the results of surveys for bristlecone pine seedlings along the entire elevation range

63 of the species throughout the Spring Mountains, and in a large burned area four years after the

64 fire. Our objective was to characterize microhabitats and densities of bristlecone pine seedlings

65 before and after fire, and to understand the environmental factors contributing to seedling

66 establishment. To our knowledge, this work constitutes the first quantitative comparison of pre-

67 and post-fire natural regeneration dynamics of Great Basin bristlecone pine (hereafter referred to

68 simply as bristlecone pine).

69

70 Methods

71 In June and July 1992, we measured bristlecone pine regeneration along eight transects through

72 unburned bristlecone pine forest and woodland in the Spring Mountains of southern Nevada,

Page 3 of 19



Draft

4

73 generally to the west and northwest of the Mt. Charleston townsite. Bristlecone pine in this area

74 is found at elevations from 2500 to 3500 m, occasionally associated with Pinus ponderosa

75 Douglas ex Lawson, P. flexilis James, Abies concolor (Gordon) Lindley ex Hildebrand, or

76 Populus tremuloides Michaux (Abella et al. 2012). Each transect, ranging in length from 100 to

77 720 m, was subdivided into continuous plots 6 m wide by 10 m long, beginning one plot below

78 the lowest elevation of bristlecone pine occurrence and continuing upslope on a compass bearing

79 until one plot above the upper tree line (always dominated by bristlecone pines) or until a tree-

80 covered ridgetop was reached (total = 343 plots, 20,580 m2). The eight transects were located to

81 represent the full range of aspects and elevations where bristlecone pines occur in the Spring

82 Mountains, but were also influenced by accessibility. Each contiguous 60 m2 plot was considered

83 an “extensive” plot, in which we measured aspect, elevation, slope, and the number, height, and

84 diameter at breast height (DBH) of every bristlecone pine individual, categorized as seedling

85 (<50 cm tall), sapling (51-200 cm tall), juvenile (>200 cm tall, DBH <10cm), or adult (>10 cm

86 DBH). We also estimated forest overstory cover in four categories (1 = no overstory; 2 = 1-50%

87 cover; 3 = 50-90% cover; 4 = >90% cover). The distance from each seedling to its nearest living

88 bristlecone pine neighbor (of any size) was also recorded.

89 In one randomly located 20 m x 20 m “intensive” plot in each of seven of our eight transects,

90 we counted all individual woody plants, tallied by species and size class (seedlings, saplings,

91 juveniles, and adults, as above), and tested for differences in soil conditions under adult

92 bristlecone pines and in the open between canopies. We collected two, 5-cm deep samples of

93 mineral soil (in metal tins, following removal of surface organic matter) in each of the two

94 habitats from five locations in each intensive plot (total = 140 samples). We also measured

95 mineral soil depth (mean of 20 probes near each sample). After passing soils through a 2 mm

96 sieve we measured pH in a 1:2 soil:water paste, and determined gravimetric soil moisture (% dry

97 mass) by weighing samples before and after drying at 105 oC for 36 hours. Soil organic matter

98 (SOM) was determined by mass loss on combustion at 550 oC for 4 hours. We also estimated

99 bulk density (g/cm3) using dry mass and volume of the sieved fines. This method represents an

100 overestimate of actual field bulk density because pore spaces and rocks (14-70% of volume) in

101 these skeletal soils are not incorporated in the calculation (see discussion in Chapin et al. 1994).

102 In September and October 2017, we sampled areas burned by the 2013 Carpenter-One Fire in

103 the SMNRA west and southwest of Mt. Charleston townsite, 1.5 to 8 km from areas sampled in

Page 4 of 19



Draft

5

104 1992, focusing on the pure bristlecone pine forest above 3000 m (Fig. S1). We recorded post-fire

105 bristlecone pine seedlings, defined as <5 mm in basal diameter and <12 cm tall, determined (on

106 the basis of woodiness absence and few bud scale scars) to be newly emerged since the 2013 fire

107 instead of fire survivors; this differs from our 1992 definition of seedlings. All five-needle pine

108 seedlings were considered to be Pinus longaeva, as the burned woodland and surrounding forest

109 consisted almost exclusively of this species, and all three excavations of seedling caches revealed

110 ungerminated seeds less than 7 mm in length, too small to be P. flexilis, the other five-needled

111 pine in the area. A total of twenty-five transects, ranging from 36 to 186 meters in length, were

112 located in any direction that maximized overlap with burned forest. Most transects ran along a

113 contour, and most transects had <5% cover of post-fire herbaceous vegetation.

114 In each transect, we looked for bristlecone pine seedlings in 6 m wide, 10 m long plots (total

115 = 246 plots, 14,760 m2). At each transect end plot (n = 50) and in each additional plot containing

116 seedlings (n=21), we took the following measurements: UTM coordinates, aspect, elevation,

117 slope, distance to nearest adult tree (live or dead), distance to forest edge (using GPS waypoints

118 collected in the field and digitized live tree positions visible in post-fire Google EarthTM aerial

119 imagery, analyzed using QGIS 3.10; QGIS Development Team 2009), and burn severity (low =

120 most adult trees in the plot survived, moderate = most adult trees killed but mostly scorched, and

121 severe = no surviving trees, strongly charred). For plots in which no seedlings were found,

122 elevation, aspect, slope, and distance to forest edge (green adult trees) were estimated by linear

123 interpolation of values found in the nearest plots with measurements.

124 Although omitted from the 1992 survey, signs of white pine blister rust were searched for on

125 seedlings and surviving trees encountered in and around the 2017 survey area. In both years,

126 where multi-seedling clusters were found, we recorded the number of seedlings per cluster.

127 Separate statistical analyses were conducted to assess environmental effects on seedling

128 presence/absence, and on seedling density, before and after the fire. The effects of elevation,

129 aspect, slope, cover of mature trees, and distance to forest edge were analyzed as single and

130 multiple factors for their effects on seedling presence/absence (where seedling caches were

131 treated as one regeneration microsite location) at the plot level using logistic regression

132 (LOGISTIC procedure, SAS Institute 2012). Aspect was evaluated separately (as difference from

133 south, 180 degrees azimuth, or difference from southwest, 225 degrees), and in combination with

134 slope to calculate potential incident radiation and heat load (McCune and Keon 2002). Burn

Page 5 of 19



Draft

6

135 severity effects on 2017 regeneration microsite presence/absence were determined using both

136 ground-based descriptions of burn severity ranked on a three-point scale, and satellite-based

137 mapping of burn severity ranked on a four-point scale (see Supplementary Material 1). As most

138 plots had no seedlings, zero-inflated Poisson regression was used to test for seedling density

139 response to aspect (both years) and to the distance from intact forest (2017) using the GENMOD

140 procedure in SAS (SAS Institute 2012). Categorical means for stem densities by size class and

141 environmental categories and Spearman rank correlations of seedling density with soil attributes

142 were also calculated (using the MEANS and CORR procedures, SAS Institute 2012).

143

144 Results

145 The survey of unburned forest in 1992 encountered a total of 76 seedlings (<50 cm tall) over a

146 sample area of 20,580 m2, for an overall density of 36.9 seedlings/ha. Adult trees were more

147 abundant than seedlings or saplings in this forest (Fig. 1, inset). Bristlecone pine regeneration

148 was concentrated in a few locations: 38 seedlings found as the only ones in 38 plots, and another

149 38 seedlings shared 16 plots with at least one other seedling, while 289 plots had no seedlings at

150 all. In the extensive unburned plots, logistic regression of bristlecone pine seedling

151 presence/absence showed a significant negative response to solar radiation (p=0.0001) which

152 was mostly due to the influence of aspect (p<0.0001; Table 1). The strongest predictor of pre-

153 burn seedling density was incident solar radiation (MJ.cm-2.yr-1), where non-zero density

154 (stems/ha) = e(5.7876 – 0.4429 solar radiation) (Wald’s χ 2=43.27, p<0.0001) with odds of density = 0

155 being e(-1.5986 + 4.1081 solar radiation) (Wald’s χ 2=15.45 and p<0.0001). Elevation, slope, and overstory

156 cover had no significant value as predictors of seedling presence (Table 1). Only one multi-factor

157 logistic regression model was significant, in which elevation and overstory density both

158 exhibited a negative influence on seedling presence, but the interactive effect of these two factors

159 was positive (Table 1). Plots with seedlings were most likely to be encountered at lower

160 elevations with denser tree cover, and on steeper north-facing slopes (Table S2).

161 Nearest neighbors within 1 m of seedlings were three times more likely to be other seedlings

162 (n=15) than larger bristlecone pines (n=5); at distances >1 m, the nearest neighbors to seedlings

163 were less likely to be seedlings (n=5) than larger pines (n=51). Nearest neighbor seedling

164 distances to other bristlecone pine seedlings were 1.03 + 0.29 m (n=21), to saplings 2.42 + 0.27

165 m (n=22), to juveniles 2.38 + 0.45 m, and to adults 3.01 + 0.41 m (n=24). Only one seedling

Page 6 of 19



Draft

7

166 cluster was found, having 6 seedlings within 5 cm of each other, suggestive of a seed cache. In

167 the intensive plots in unburned forest, soils under adult bristlecone pines were deeper (F=8.01,

168 p=0.005), wetter (F=4.81, p=0.030), had higher soil organic matter (F=8.10, p=0.005), and had

169 lower bulk density (F=20.28, p<0.001) than soils away from bristlecone pine canopies, while pH

170 did not differ significantly (F=0.16, p=0.689; Table 2). Adult bristlecone pine trees were

171 positively associated with wetter sites (rho=0.75, p=0.03), while non-adults were positively

172 associated with low pH soils (rho=0.71, p=0.05).

173 In the burned forest surveyed in 2017, 72 new bristlecone pine seedlings (<12 cm tall) were

174 encountered over a sample area of 14,760 m2, for an overall density of 48.8 seedlings/ha. No

175 living saplings or juvenile trees were found in moderately or severely burned forest. No

176 confirmed symptoms of white pine blister rust were observed on any bristlecone pine trees in the

177 area. Most seedlings were found in lightly burned (n=39 seedlings, 54%) forest, with other plant

178 cover averaging less than 1% overall. Most seedlings (n=49, 68%) were found <100 m from the

179 edge of the unburned forest, but some (n=15, 21%) were found more than 300 m from living

180 adult trees (Fig. 2, Table S3). Seedlings were often found in clusters (30 of 72 new seedlings, in

181 7 caches of 2-9 seedlings each). Three of these clusters were excavated and we confirmed that

182 each consisted of individual seedlings, not sprouts from a single root crown (Fig. 3).

183 Observations further suggest that cache locations are concentrated on south-facing slopes near

184 ridge crests, where snow cover is potentially lower.

185 As in the pre-burn survey, post-burn seedling presence was negatively related to heat load

186 index (p<0.0001), solar radiation (p=0.0002), and southwest-facing aspects (p<0.0001; Table 3).

187 Seedlings were generally found at lower elevations (p=0.0036) and on steeper slopes (p=0.0210)

188 within the area sampled in 2017 (Table 3). Seedling occurrence was negatively associated with

189 the burn severity as described in the field (p=0.0001), but bore no significant relationship to burn

190 severity based on satellite mapping (p=0.6427; Table 3). The distance of individual bristlecone

191 pine seedlings to an adult tree (live or dead) averaged 2.47 + 0.38 m. Distance to intact forest

192 emerged as a significant predictor of seedling density only after the large number of zero

193 densities was accounted for by the effect of aspect (Fig. 2).

194

195 Discussion

Page 7 of 19



Draft

8

196 Seedlings of Great Basin bristlecone pine (Pinus longaeva) were relatively rare in both burned

197 and unburned habitats. Baker (1992) likewise found fewer seedlings and saplings than adults in 5

198 of 6 sites in Colorado supporting the related Rocky Mountain bristlecone pine, Pinus aristata

199 Engelmann. It is widely recognized that infrequent recruitment events and low densities can still

200 be sufficient to maintain populations of long-lived trees (Platt et al. 1988, Wiegard et al. 2005). If

201 the overall size class structure shown in Fig. 1 is stable, it suggests there are constraints that limit

202 the recruitment of saplings into juvenile size classes.

203 Seedlings in the unburned forest, though found on diverse physical microsites, tended to be

204 clustered (at least at the plot level) and constrained by factors associated with aspect and solar

205 radiation (Table 1). This result may partially explain their observed affinity for the shelter of

206 adult trees, where soil moisture, soil depth, organic matter (and presumably shade) were greater

207 and bulk density was lower (Table 2). The protective role of adult trees may be more important

208 at high elevations, as indicated by the positive interactive effects of elevation and overstory

209 density in the pre-burn forest (Table 1). Similar facilitation effects for Great Basin bristlecone

210 pine seedlings were observed in the White Mountains of California by Maher et al. (2015) and

211 for post-fire recruitment of Pinua aristata by Coop and Schoettle (2009). Proximity to adult trees

212 and a clustering of seedlings may also reflect dispersal limitations.

213 Aspect effects on seedling establishment also prevailed after the 2013 fire. In the post-burn

214 environment, heat load and aspect differences from southwest were slightly more important than

215 incident solar radiation and aspect differences from south, which prevailed in the pre-burn forest.

216 The greater importance of heat load avoidance in the distribution of seedlings sampled in 2017

217 may be associated with greater overall openness and warmer conditions than experienced in the

218 1980s and early 1990s. ClimateWNA (Wang et al. 2016) interpolations were performed for the

219 four years prior to post-burn sampling (2014-2017) and for 4- and 10-yr windows (1989-1992

220 and 1983-1992) prior to pre-burn sampling. The 2014-2017 conditions exhibited mean annual

221 temperatures more than 2 oC warmer than the earlier periods, but climate moisture deficit was

222 estimated to be slightly less prior to 2017 than to 1992.

223 With many plots hundreds of meters from the nearest living adult tree, distance to forest also

224 emerged as a significant limitation to post-fire bristlecone pine regeneration, though still

225 contingent on aspect effects (Fig. 2). Coop and Shoettle (2009) likewise found that Rocky

226 Mountain bristlecone pine regeneration was concentrated near burn edges and surviving adult

Page 8 of 19



Draft

9

227 trees. It appears that the legacy of even dead trees persists in the burned landscape, with most

228 seedlings found within 3 m of live or dead mature trees. Whether the importance of these trees is

229 through the provision of shade, less compact soils, nutrients, or perches inducing local disperser

230 activity remains to be determined.

231 Our findings are consistent with an interpretation of the importance of animal dispersal in the

232 regeneration of Great Basin bristlecone pine (Lanner 1988). Most seedlings in 2017 were found

233 within 100 m of forest edge, yet individual post-fire seedlings were found more than 300 m from

234 the nearest intact forest edge (Fig. 2). Although those distant seedlings were not identified as

235 emerging from seed caches, it is possible that they were associated with seeds that did not

236 germinate or with seedlings that had died. Many (30 of 72) of the post-fire seedlings encountered

237 were found in caches, which may have been created by Clark’s nutcracker or the endemic

238 Palmer’s chipmunk (Neotamias palmeri Merriam), both of which were observed foraging in the

239 study area. Clark’s nutcracker, in particular, is known to be an important disperser of other five-

240 needle pines (Hutchins and Lanner 1982, Coop and Schoettle 2009). Palmer’s chipmunk is

241 known to consume and cache seeds too (Hirshfeld 1975), or it may facilitate secondary dispersal

242 in the process of pilfering nutcracker caches (Pansing et al. 2017). Clark’s nutcracker may also

243 contribute to some of the microsite differences observed in Great Basin bristlecone pine

244 regeneration, if indeed it preferentially caches seeds in some locations over others. The fact that

245 more seed caches were found post-fire (at 7 of 21 regeneration microsites) than in the wide-

246 ranging pre-fire surveys further supports the interpretation that Clark’s nutcracker preferentially

247 caches seeds in recently burned areas, and that fires are important for five-needle pine forest

248 renewal (Coop and Schoettle 2011). Although only one of the 54 unburned regeneration

249 microsites was identified as a cache, some of the larger seedlings encountered in 1992 may have

250 been the sole survivors of those emerging from seed caches.

251

252 Conclusions

253 Our extensive survey of 35,340 m2 in sample plots concludes that aspect, the influence of adult

254 trees (live or dead), and dispersal all can be important to the regeneration of Great Basin

255 bristlecone pine. With sparse regeneration encountered four years after fire, we conclude that

256 post-fire recovery of Great Basin bristlecone pine forests can be a lengthy process, but is

257 gradually achieved through natural processes. The severe environment encountered at high

Page 9 of 19



Draft

10

258 elevations in semi-arid regions accentuates the importance of microsite protection, moisture

259 availability, and nutrients. Caching by birds or rodents can ameliorate some of the environmental

260 challenges for Great Basin bristlecone pine regeneration by burying seeds, may reflect site

261 selection in the caching process, and is important for forest regeneration after large wildfires.

262 Protecting healthy populations of these dispersers is essential, and managers may wish to

263 emulate some of the microsite selection patterns documented here and in related studies when

264 undertaking restoration efforts.

265

266 Acknowledgements

267 Joanne Baggs and Espen Walker assisted with collection of the 1992 data, which was supported

268 by the University of Nevada Las Vegas. Carla Burton and Billy Blanchar assisted with collection

269 of the 2017 data, which was partially supported by a sabbatical from the University of Northern

270 British Columbia. Kristen Waring (Northern Arizona University) and Nicholas Wilhelmi (US

271 Forest Service) reviewed photographs showing potential blister rust infection. We thank Kristen

272 Waring, Alana Clason, Vern Peters, the Associate Editor, and two anonymous reviewers for

273 constructive comments on the manuscript.

274

275 References

276 Abella, S.R., Hurja, J.C., Merkler, D.J., Denston, C.W., and Brewer, D.G. 2012. Overstory-

277 understory relationships along forest type and environmental gradients in the Spring

278 Mountains of southern Nevada, USA. Folia Geobot. 47: 119–134.

279 Bentz, B.J., Hood, S.M., Hansen, E.M., Vandygriff, J.C., and Mock, K.E. 2017. Defense traits in

280 the long‐lived Great Basin bristlecone pine and resistance to the native herbivore mountain

281 pine beetle. New Phytol. 213(2): 611–624.

282 Chapin, F.S., Walker, L.R., Fastie, C.L., and Sharman LC. 1994. Mechanisms of primary

283 succession following deglaciation at Glacier Bay, Alaska. Ecol. Monogr. 64: 149–175.

284 Coop, J.D., and Schoettle, A.W. 2009. Regeneration of Rocky Mountain bristlecone pine (Pinus

285 aristata) and limber pine (Pinus flexilis) three decades after stand-replacing fires. For. Ecol.

286 Manage. 257(3): 893–903.

287 Coop, J.D., and Schoettle, A.W. 2011. Fire and high-elevation, five-needle pine (Pinus aristata

288 & P. flexilis) ecosystems in the southern Rocky Mountains: What do we know? In The

Page 10 of 19



Draft

11

289 Future of High-Elevation, Five-Needle White Pines in Western North America: Proceedings

290 of the High Five Symposium 28-30 June 2010, Missoula, Montana. Edited by Keane RE,

291 Tomback DF, Murray MP, Smith CM. RMRS-P-63, USDA Forest Service. Fort Collins, CO.

292 pp. 164–175.

293 Fryer, J.L. 2004. Pinus longaeva. In Fire Effects Information System, [Online]. USDA Forest

294 Service, Rocky Mountain Research Station, Fire Sciences Laboratory. Available at

295 https://www.fs.fed.us/database/feis/plants/tree/pinlon/all.html [viewed 14 Sept. 2017].

296 Herrmann, C.R. 2017. Living on the Edge: Assessing the Effects of Catastrophic Fire on Plants

297 Utilized by Two Endemic Species of Spring Mountains Butterflies. Masters Thesis,

298 University of Nevada Las Vegas, Las Vegas, NV 56 p.

299 Hirshfeld, J. 1975. Reproduction, Growth and Development of Two Species of Chipmunk:

300 Eutamias panamintinus and Eutamias palmeri. Masters Thesis, University of Nevada Las

301 Vegas, Las Vegas, NV.

302 Hutchins, H.E., and Lanner, R.M. 1982. The central role of Clark’s Nutcracker in the dispersal

303 and establishment of whitebark pine. Oecologia 55: 192–201.

304 Kallstrom, C. 2013. Carpeter 1 Fire Burn Area Emergency Response Biologist Specialist Report.

305 US Fish and Wildlife Service, Las Vegas, NV. 12 p.

306 Kinloch, B.B. 2003. White pine blister rust in North America: past and prognosis.

307 Phytopathology 93(8): 1044–1047.

308 LaMarche, V.C., and Mooney, H.A. 1972. Recent climatic change and development of the

309 bristlecone pine (P. longaeva Bailey) krummholz zone, Mt. Washington, Nevada. Arct. Alp.

310 Res. 4(1): 61–72.

311 Lanner, R.M. 1988. Dependence of Great Basin bristlecone pine on Clark’s Nutcracker for

312 regeneration at high elevation. Arct. Alp. Res. 20: 358–362.

313 Maher, C.T., Barber, A.L., and Affleck, D.L. 2015. Shelter provided by wood, facilitation, and

314 density-dependent herbivory influence Great Basin bristlecone pine seedling survival. For.

315 Ecol. Manage. 342: 76–83.

316 McCune, B., and Keon, D. 2002. Equations for potential annual direct incident radiation and heat

317 load. J. Veg. Sci. 13(4): 603–606.

318 Miller, S., Schoettle, A., Burns, K., Sniezko, R., and Champ, P. 2017. Preempting the pathogen:

319 Blister rust and proactive management of high-elevation pines. Science You Can Use

Page 11 of 19



Draft

12

320 Bulletin 24. Rocky Mountain Research Station, US Forest Service, Fort Collins, CO. 11 p.

321 Available at https://www.fs.usda.gov/treesearch/pubs/54095 [viewed 7 November 2019].

322 Pansing, E.R., Tomback, D.F., Wunder, M.B., French, J.P., and Wagner, A.C. 2017. Microsite

323 and elevation zone effects on seed pilferage, germination, and seedling survival during early

324 whitebark pine recruitment. Ecol. Evol. 7(21): 9027–9040.

325 Platt, W.J., Evans, G.W., and Rathbun, S.L. 1988. The population dynamics of a long-lived

326 conifer (Pinus palustris). Amer. Nat. 131(4): 491–525.

327 QGIS Development Team. 2009. QGIS Geographic Information System. Open Source

328 Geospatial Foundation, http://qgis.org.

329 SAS Institute. 2012. SAS release 9.4. SAS Institute, Carey, NC.

330 Stritch, L., Mahalovich, M., and Nelson, K.G. 2011. Pinus longaeva. The IUCN Red List of

331 Threatened Species 2011: e.T34024A9830878. Available at

332 http://dx.doi.org/10.2305/IUCN.UK.2011-2.RLTS.T34024A9830878.en. [viewed 18 Nov.

333 2018].

334 Vogler, D.R, Delfino-Mix, A., and Schoettle, A.W. 2006. White pine blister rust in high-

335 elevation white pines: Screening for simply-inherited, hypersensitive resistance. In

336 Proceedings of the 53rd Western International Forest Disease Work Conference, September

337 26-30, 2005, Jackson, Wyoming. Compiled by Guyon, J.C.. USDA Forest Service, Ogden,

338 UT. pp 73–82.

339 Walker, L.R. 1993. Regeneration of bristlecone pine (abstract). Proceedings, 37th Annual

340 Meeting of the Arizona-Nevada Academy of Science, 17 April 1993, Las Vegas, NV. J.

341 Arizona-Nevada Acad. Sci. 28: 18.

342 Wang, T., Hamann, A., Spittlehouse, D., and Carroll, C. 2016. Locally downscaled and spatially

343 customizable climate data for historical and future periods for North America. PloS

344 One 11(6): e0156720.

345 Weiss, L., Shiels, A.B., and Walker, L.R. 2005. Soil impacts of bristlecone pine (Pinus

346 longaeva) tree islands on alpine tundra, Charleston Peak, Nevada. West. N. Amer. Nat. 65:

347 536–540.

348 Wiegand, K., Jeltsch, F., Ward D. 2004. Minimum recruitment frequency in plants with episodic

349 recruitment. Oecologia 141(2): 363–372.

Page 12 of 19



https://www.fs.usda.gov/treesearch/pubs/54095

http://qgis.org/

http://dx.doi.org/10.2305/IUCN.UK.2011-2.RLTS.T34024A9830878.en

Draft

13

350 Table 1. Logistic regression models predicting the presence vs. absence (df=1) of seedlings (<50

351 cm tall) in 1992 (pre-burn) extensive plots (n=343).

Single-factor statistical models:

Predictor Intercept Intercept std.

error

Coefficient Coefficient std.

error

Wald’s

χ2

Prob.

> χ2

Aspect (diff.

from south)-3.2964 0.4566 0.0149 0.00364 16.6801 <0.0001

Solar radiation 1.4822 0.8038 -3.9828 1.0331 14.8610 0.0001

Heat load

index1.0844 0.8562 -3.2178 1.0092 10.1660 0.0014

Aspect (diff.

from SW)-2.6202 0.3613 0.0107 0.00344 9.6313 0.0019

Elevation -1.2056 2.2477 0.00016 0.000781 0.0442 0.8335

Slope -2.3973 0.5805 0.0252 0.0192 1.7092 0.1911

Overstory

cover-1.8694 0.4618 0.0724 0.1607 0.2029 0.6524

Significant Multi-factor statistical models:

Predictors Intercept First

Coefficient

Second

Coefficient

Interaction

Coefficient

Wald’s

χ2

Prob.

> χ2

Elevation, over

story density29.4706 -0.0113 elev.

-8.3519

denscode

+0.00302 elev.

x denscode7.9688 0.0467

352

Page 13 of 19



Draft

14

353 Table 2. Soil parameters from 140 samples in 1992 intensive plots (mean + SE) for open and

354 canopy sites (not under or under the canopy of an adult bristlecone pine, respectively). F values

355 and P values are from two-way Kruskal-Wallis tests with spatially auto-correlated variance due

356 to plots (nested within transects) accounted for with Type III sums of squares.

Soil Attribute Open Canopy F value Prob.>F

Depth (cm) 13.34 + 0.52 15.43 + 0.55 9.65 0.0024

Water (%) 2.85+ 0.27 3.91 + 0.43 10.95 0.0013

pH 6.98 + 0.11 7.05 + 0.07 0.90 0.3450

Organic matter (%) 7.05 + 0.61 10.71 + 1.16 14.24 0.0003

Bulk density (g/cm3) 1.09 + 0.03* 1.08 + 0.17* 35.25 <0.0001*

357 *although means are not very different, median values are 1.03 and 0.88 for open and canopy

358 positions, respectively.

359

Page 14 of 19



Draft

15

360 Table 3. Individual logistic regression models predicting the presence vs. absence (df=1) of new

361 seedlings (<12 cm tall) in 2017 (post-burn) plots (n=248).

Predictor Intercept

Intercept

std. error Coefficient

Coefficient

std. error

Wald’s

χ 2 Pr > χ2

Heat load index 6.5599 1.7810 -9.3158 1.9077 23.85 <0.0001

Aspect (diff.

from SW)-3.6127 0.4207 0.0186 0.00399 21.68 <0.0001

Burn severity

(field assessed)0.0435 0.5935 -1.0445 0.2721 14.74 0.0001

Aspect (diff.

from south)-3.8232 0.5283 0.0219 0.00571 14.72 0.0001

Solar radiation 3.6325 1.5630 -6.3653 1.7136 13.80 0.0002

Elevation 31.2106 11.4573 -0.0103 0.00354 8.47 0.0036

Slope -3.1413 0.4552 0.0517 0.0224 5.33 0.0210

Distance to forest -1.8787 0.2911 -0.0050 0.00265 3.57 0.0590

Burn severity

(from MTBS*)-2.5657 0.5648 0.1266 0.2728 0.22 0.6427

362 *categories mapped by the Monitoring Trends in Burn Severity program, mtbs.gov; see

363 Supplementary Material 1.

Page 15 of 19



Draft

16

364 Figure Captions

365

366 Fig. 1. Size class structure of unburned bristlecone pine populations across 8 transects sampled

367 in 1992. Inset: mean proportional abundance in each broad size class (see Methods for size class

368 definitions).

369

370 Fig. 2. Relationship of bristlecone pine seedling densities as related to distance from intact forest

371 in post-burn (2017) forest, with zero-inflated Poisson regression model (Wald’s χ2 = 8.70,

372 p=0.0032), in which the odds of zero density is determined separately as a function of aspect

373 (degrees difference from southwest), for which χ2 = 20.49, p<0.0001. Expressed in stems/ha, y =

374 e(6.6696 – 0.0063 distance to forest, m).

375

376 Fig. 3. Cache of bristlecone pine seeds in burned forest that resulted in 9 seedlings.

377

Page 16 of 19



Draft

Fig. 1.

Page 17 of 19



Draft

Fig. 2.

Page 18 of 19



Draft

Fig. 3.

Page 19 of 19



regeneration dynamics of great basin bristlecone pine in ... · draft 1 1 regeneration dynamics of...

Documents