Draft - TSpace Repository: Home...Draft 5 74 gaps to recruit to the canopy. However Webb and Scanga...

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Ecological impact of a microburst windstorm in a northern

hardwood forest.

Journal: Canadian Journal of Forest Research

Manuscript ID cjfr-2017-0206.R1

Manuscript Type: Note

Date Submitted by the Author: 25-Aug-2017

Complete List of Authors: Battles, John; University of California Berkeley, Department of Environmental Science, Policy, and Management Cleavitt, Natalie; Cornell University Saah, David; University of San Francisco, Department of Environmental Science Poling, Benjamin; Virginia Polytechnic Institute and State University,

Department of Forest Resources and Environmental Conservation Fahey, Timothy; Cornell University, Natural Resources

Keyword: treefall, gap dynamics, thunderstorm, intermediate disturbance, Hubbard Brook Experimental Forest

Is the invited manuscript for consideration in a Special

Issue? : N/A

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

Canadian Journal of Forest Research

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TITLE: Ecological impact of a microburst windstorm in a northern hardwood forest. 1

2

AUTHORS: John J. Battles1, Natalie L. Cleavitt

2, David S. Saah

3, Benjamin T. Poling

4, and Timothy 3

J. Fahey2

4

AFFILIATION AND ADDRESS 5

1Department of Environmental Science, Policy and Management, 130 Mulford Hall #3114, 6

University of California, Berkeley, Berkeley, CA, USA 94720 7

510-643-0684 (office), ([email protected]) 8

2 Department of Natural Resources, Cornell University, Fernow Hall, Ithaca, NY 9

14853 ([email protected]; [email protected]) 10

3 University of San Francisco, 2130 Fulton Street, San Francisco, CA 94117-1080 11

([email protected]) 12

4 Department of Forest Resources and Environmental Conservation, Virginia Tech, 13

Blacksburg, VA 24061 ([email protected]) 14

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ABSTRACT 15

We quantified damage to a northern hardwood forest (Hubbard Brook Experimental 16

Forest, New Hampshire) by a microburst windstorm. These storms may be important in 17

regulating the structure and composition of northeastern U.S. forests, but few studies of 18

damage patterns from microbursts have been reported. In the 600-ha area most heavily 19

impacted by the microburst at Hubbard Brook, 4.6% of the canopy was removed. Although 20

most disturbances were small (< 200 m2), much (22%) of the area damaged by the storm was 21

associated with one 5.2 ha blowdown within which 76% of the trees suffered severe damage. 22

Roughly one-half of the damaged trees were uprooted and one-quarter snapped-off with few 23

differences among tree species. The remaining trees in the blowdown either avoided damage 24

or suffered less severe damage (i.e., leaning but not snapped or uprooted). Regeneration of 25

shade-intolerant (pin cherry) and mid-tolerant (yellow birch, red maple) trees was present in 26

the large canopy gaps. While recruitment opportunities in these large gaps may be important 27

for maintaining populations of pioneer species, the limited spatial extent of microbursts 28

suggests that they play a minor role in the overall dynamics of the northeastern forest. 29

KEYWORDS: treefall, gap dynamics, thunderstorm, intermediate disturbance, Hubbard Brook 30

Experimental Forest 31

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INTRODUCTION 32

For the northern hardwood forests of the northeastern United States, vegetation 33

change is dominated by tree-by-tree replacement in small gaps caused by the death of one or a 34

few canopy trees. In mature forests, these gaps are thought to support stability by promoting 35

the persistence of shade-tolerant trees. Floristic diversity is maintained in the landscape by 36

large infrequent disturbances (LIDs, sensu Turner and Dale 1998) that provide recruitment 37

opportunities for shade-intolerant and pioneer tree species (Spurr 1956, Bormann and Likens 38

1979, Hibbs 1983). However this "nested bicycle" concept of the disturbance regime (sensu 39

Worrall et al. 2005) does not consider the potential role of intermediate disturbances in the 40

dynamics of these forests. Stueve et al. (2011) argued that the impact of intermediate 41

disturbances on forest composition and structure is often underestimated. They defined 42

intermediate disturbances as events that create patches of catastrophic damage (>70% canopy 43

removal) that are clearly more severe and larger than canopy gaps but that are also less severe 44

and more frequent than LIDs. Their reconstruction via remote sensing estimated that 45

intermediate windstorms in the Great Lakes region caused as much canopy damage in terms of 46

severity and extent as LIDs (Stueve et al. 2011). 47

Windstorms are the most likely source of either a LID or an intermediate disturbance; 48

other potential agents such as fires and floods are uncommon in the northern hardwood forest 49

(Lorimer and White 2003, Vanderwel et al. 2013). High winds are associated with a variety of 50

storm types: hurricanes, extra-tropical cyclonic storms and frontal thunderstorms all produce 51

winds capable of uprooting and snapping trees; and hurricanes, tornadoes, downbursts, 52

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derechos, and microbursts often create large gaps in the eastern United States (Peterson 2000). 53

As noted by Mitchell (2013), the role of wind as a recurrent driver of ecosystem processes 54

depends on its spatial extent, intensity, and frequency. 55

Microbursts are at the low end of the extent and intensity gradient of damaging 56

windstorms. They are often associated with strong thunderstorms and usually defined as 57

having a horizontal dimension less than 4 km in extent to distinguish them from downbursts 58

and derechos that are much more extensive (Fujita 1981). Wind speeds in microbursts vary 59

considerably, but the winds produced are capable of uprooting and snapping mature trees 60

(Hjelmfelt 2007). The forest disturbance created by microbursts and other straight line winds 61

fits Stueve et al.'s (2011) definition of an intermediate disturbance. Typically, 30-70% of canopy 62

trees are killed across a limited extent of the forest creating a complex mosaic of gaps (Woods 63

2004, Nagel and Diaci 2006, Hanson and Lorimer 2007) 64

Lorimer and White (2003) summarized information about natural forest disturbances for 65

the northeastern United States and noted that the limited information on damage patterns 66

associated with intermediate windstorms constrained the accuracy of estimates of recurrence 67

intervals for wind disturbances especially in inland areas where Atlantic hurricanes are 68

uncommon. Based on land survey and tree-ring evidence, intermediate windstorms were 69

common throughout the temperate forest region but the role they play in shaping natural 70

forest dynamics is unclear (Frelich and Lorimer 1991). Buchanan and Hart's (2012) analysis of 71

tree rings suggested that intermediate disturbances in the eastern deciduous forest were 72

critical to the persistence of white oak (Quercus alba L.), a mid-tolerant species the needs large 73

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gaps to recruit to the canopy. However Webb and Scanga (2001) found that the disturbance 74

caused by a moderate-severity windstorm in a mixed hardwood-pine forest in Minnesota did 75

not lead to the establishment of light-demanding species. 76

On 2 June 2013 a severe thunderstorm resulted in a microburst at the Hubbard Brook 77

Experimental Forest (HBEF). The HBEF is the site of a comprehensive, long-term study of 78

northern hardwood ecosystems, and the forest has been intensively monitored for over 50 79

years; hence, the microburst at the HBEF provided an exceptional opportunity to evaluate the 80

effects of a typical intermediate windstorm in the context of a well-characterized forest 81

landscape. The HBEF has experienced only two other natural disturbance events of comparable 82

severity since the early 20th

century: a hurricane in 1938 (Peart et al. 1992) and an intense ice 83

storm in 1998 (Rhoads et al. 2002). The overall goal of this study was to evaluate the 84

contribution of microbursts to the dynamics of the northern hardwood forests. We 85

characterized the disturbance to HBEF caused by this windstorm to inform our evaluation. 86

Specifically, we addressed the following questions: 1) What was the extent and severity of the 87

disturbance? 2) Were canopy species differentially impacted by the storm? 3) Did the storm 88

provide recruitment opportunities for the less shade-tolerant species? 89

METHODS 90

Study Area. The Hubbard Brook Experimental Forest (HBEF) is a 3,160 ha reserve located in the 91

White Mountains of central New Hampshire, USA (43°56′N, 71°45′W). The climate is 92

continental, characterized by short, warm summers and long, cold winters. The soils are 93

primarily well-drained Spodosols (coarse, loamy, mixed, frigid, Typic Haplorthods) with sandy 94

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loam to loamy sand textures, but with considerable, local variation in soil type and depth 95

(Johnson et al. 2000). The HBEF is considered a northern hardwood forest, with the highest 96

elevations supporting a subalpine conifer forest. 97

Hubbard Brook Valley was selectively logged in the late 1800s and then again between 98

1906 and 1920. By 1920, 40% of the valley was “cutover” (C.V. Cogbill, personal 99

communication). The next major disturbance was the 1938 hurricane that caused extensive 100

blowdown, and subsequent salvage logging. The most intense blowdowns were in the 101

northeastern corner of the valley, on fairly steep south or southeast-facing slopes and ridges 102

(Peart et al. 1992). A more recent disturbance occurred in 1998 when an ice storm caused 103

considerable structural damage to the forest in an elevation band between 600 and 800 m 104

(Rhoads et al. 2002). Thus, the age structure of the forest in Hubbard Brook Valley can be 105

described as multi-aged (mainly 60–120 years old). The stands of mature forest are now 106

dominated by American beech (Fagus grandifolia Ehrh.), sugar maple (Acer saccharum Marsh.), 107

and yellow birch (Betula alleghaniensis Britt.) with red spruce (Picea rubens Sarg.) and balsam 108

fir (Abies balsamea (L.) Mill.) found primarily on ridges and rocky areas (van Doorn et al. 2011). 109

The microburst at Hubbard Brook was associated with a severe thunderstorm that 110

moved through the region during the afternoon of June 2, 2013. Radar images depict a fast 111

moving storm tracking northeast across New England with sustained winds at the storm center 112

of 92.5 km h-1

. There were multiple reports of power outages and fallen trees in the storm’s 113

path. Brief, heavy rainfall accompanied the storm (NOAA 2016). In HBEF, total rainfall the day of 114

the storm averaged 2.3 cm (standard error among 25 rain gauges = 0.5 cm, Campbell 2016). 115

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Disturbance extent. Based upon field reconnaissance in July 2013, we identified the 600-116

ha area of the HBEF with the most severe damage from the microburst storm (Fig. S1, storm 117

impact area). This area surrounded the epicenter of the storm -- the single largest blowdown 118

found at HBEF. Within this area, we conducted line intersect sampling along 12 km of N-S 119

transects. These transects followed our existing network of permanent plots (Fig. S1, van Doorn 120

et al. 2011). A gap was defined as the open understory area created by storm damage to at 121

least one canopy tree (a gapmaker). We estimated the pre-storm canopy position of storm-122

damaged trees using 15 cm diameter at breast height (DBH, breast height = 1.37 m) as the 123

approximate minimum DBH of canopy trees (van Doorn et al. 2011). We expressed the area 124

affected as the “expanded gap” ‒ the area extending to the bases of trees (DBH ≥ 10 cm) 125

bordering the gap (Schliemann and Bockheim 2011). For all gaps that intersected a line, we 126

estimated the area of the expanded gap. For all but two gaps, we measured the length of the 127

major and minor axes and noted the gap shape to inform approximations of gap area and 128

perimeter. For the two largest gaps (epicenter plus second largest gap, both > 0.35 ha in area), 129

we used a handheld global positioning device (realized accuracy < 7m , GPSMAP 60, Garmin) to 130

record the location of the border trees and subsequently calculated the area from the 131

perimeter defined by these points. We noted the species, mode of damage (snapped, 132

uprooted, leaning, or standing dead) and the direction of fall (compass bearing) for all 133

gapmakers with the exception of the epicenter (see "Epicenter conditions"). 134

The gap fraction, defined as the percentage of ground area in expanded gaps, was 135

calculated from the line intersects. To estimate gap fraction with line intersects it is necessary 136

to account for the greater probability of intersecting a large gap compared to a small gap (De 137

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Vries 1986). The intersection probability is a function of the perimeter of the smallest convex 138

cover (Battles et al. 1995). We used the empirical estimates in Battles and Fahey (1996) to 139

calculate the gap area and the convex cover perimeter from measurements of the major and 140

minor axes of the gaps. Variance and subsequent confidence intervals were estimated from the 141

differences in gap fraction observed for each transect (n=5). The contribution to the variance 142

was weighted by the length of each transect (De Vries 1986). Estimates of gap abundance and 143

gap size distribution were corrected as described above to account for size-related differences 144

in the probability of intersection (Battles and Fahey 1996). We also constructed wind rose 145

diagrams to illustrate patterns in the direction of tree fall across the storm damage area (Fig. 146

S1). We analyzed the epicenter separately and then summarized tree fall direction by line 147

transect. 148

To extend our analysis of wind disturbance to the entire HBEF, we used normalized 149

difference vegetation index (NDVI) values from pre- and post-microburst Landsat imagery 150

(sensu Stueve et al. 2011). In Google Earth Engine (2015), we calculated a mean pre-151

disturbance NDVI from cloud-free pixels for the two leaf-on seasons prior to the storm (June 1- 152

August 30; 2011 and 2012). Post-disturbance values were estimated for the two leaf-on seasons 153

after the storm (June 3 - August 30, 2013; June 1 -August 30, 2014). Disturbance intensity was 154

measured as Δ NDVI -- the pre-storm NDVI minus the post-storm NDVI. To calibrate Δ NDVI as a 155

measure of storm impact, we analyzed 100 randomly located test plots superimposed on high-156

resolution satellite imagery (World View 2, 2014, Digital Globe). Plot size approximated the 157

scale of a Landsat pixel (circular plots, 908 m2 in area); each plot circumscribed a grid of 33 158

points. The status of the canopy at each grid point was visually inspected and classified as 159

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recently damaged (presumably by the microburst) or not. The fraction of points damaged (% 160

Blowdown) was compared to the Δ NDVI for each test plot. We applied linear regression with 161

changepoint estimation (Muggeo 2008) to determine the detection threshold of Δ NDVI. 162

Statistical analyses were conducted in R (R Core Team 2016). 163

Epicenter conditions. The epicenter (Fig. S1) included two plots (0.05 ha) from the 164

forest-wide permanent plot network. We located all the tagged trees (trees ≥ 10 cm DBH) on 165

these plots, re-measured them using established protocols (van Doorn et al. 2011) and 166

classified damage. In the epicenter, we added an additional damage category, "pinned," to 167

account for structurally intact trees whose stems were bent under the weight of downed boles. 168

We augmented these two plots with five additional 0.05 ha sample plots located at 100 m 169

intervals along a line transect that defined the major axis of the epicenter (Fig. S1). Tree 170

species, DBH, tree vigor, and damage type were recorded for all trees in these plots. 171

Gapmaker susceptibility. To test for species differences in susceptibility to the storm, we 172

calculated pre-disturbance relative density of stems large enough to be gapmakers (i.e., DBH ≥ 173

15 cm) for the 60 permanent plots in the storm impact area (Fig. S1). Under the assumption of 174

equal susceptibility, these pre-storm relative densities should match the relative abundance of 175

gapmakers measured along the transects. This assumption was tested using a Χ2-test for 176

independence. To quantify the influence of tree size (DBH) on the risk of treefall, we used the 177

post-storm inventories from the epicenter. For the 149 trees (DBH ≥ 10 cm) sampled, we 178

evaluated the probability of tree fall (snapped or tip-up) as a function of DBH and species using 179

logistic regression (sensu Peterson 2007) 180

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Tree regeneration. In August 2014, we measured tree recruitment in the most severely 181

disturbed areas by the storm. We sampled the epicenter and three other large gaps (90th

182

percentile of gap area, minimum area > 300 m2) created by the microburst. Three to five 183

circular plots (2 m radius, 12.57 m2) were established per gap with more plots in larger gaps (n = 184

17). Approximately half of each plot was on intact forest floor and half on exposed mineral soil 185

created by uprooted trees. Recruits were defined as tree stems < 2 cm DBH. Regeneration was 186

re-assessed in September 2015, the third growing season after the storm. 187

RESULTS 188

In the 600-ha landscape that was most disturbed by the microburst storm (i.e., storm 189

impact area, Fig. S1), the lines intersected 48 discrete canopy gaps. On average, there were 2.4 190

gaps ha-1

(95%CI = ±0.9 gaps ha-1

) indicating that there were 1,440 ± 540 gaps created by the 191

storm which disturbed 4.6% (95%CI = ±1.3%) of the canopy in the sample area. Most of these 192

canopy gaps were small: 86% were <200 m2

in area (Fig. 1) and 55% were formed by damage to 193

a single canopy tree. However, much of the disturbed area was associated with a few large, 194

multi-tree blowdowns. The five largest gaps, each created by more than 20 gapmakers, 195

accounted for 40% of the disturbance by area. The largest gap, the epicenter of the storm, was 196

5.2 ha in extent and comprised 22% of the total gap area (Fig. S1). 197

The direction of treefall in most gaps matched the direction of the storm track, namely 198

north by northeast (Fig. S1). The exceptions were the gaps west of the epicenter (Fig. S1B). In 199

these gaps, trees fell from southeast to southwest. 200

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The changepoint regression (Fig. S2) indicated the smallest disturbance reliably detected 201

by Δ NDVI had approximately 12.5% of blowdown in the test plot. Thus, gaps smaller than 113.5 202

m2 (12.5% of 908 m

2) were not captured by the Landsat analysis. Within the storm impact area, 203

Δ NDVI estimated that 3.29% of the area was disturbed. The estimate from line intersect 204

sampling, excluding gaps smaller than 113.5 m2, was 3.75% (95%CI = ±0.8%). For the entire 205

HBEF, Δ NDVI indicated 0.65% of the forest was impacted by the wind storm. 206

In the storm impact area, half of the trees damaged by the storm were uprooted (Table 207

1). Broken tree stems (snap) were the next most common accounting for approximately 26% of 208

the gapmakers. The distribution of damage types was consistent across species. The biggest 209

outlier was American beech that uprooted less frequently than the other common species. We 210

detected no species-specific susceptibility to the windstorm. The pre-storm abundance of 211

potential gapmakers was not independent of the observed gapmaker composition (Table S1, Χ2 212

= 0.08, df = 7, p = 1). 213

In the epicenter, 76% of the canopy trees were killed or damaged by the storm (Table 214

S2). Uprooted trees were again the most common form of disturbance (48.3%) followed by 215

snapped trees (30%, Table 2). Collateral damage was much more common in the epicenter 216

compared to the smaller gaps; 14.2% of gapmakers were pinned by their fallen neighbors 217

(Table 2). There was also greater variation among species in their susceptibility to disturbance. 218

For example, the fraction of intact stems for the two most abundant species in the epicenter 219

varied from 9% intact for red spruce to 32% for yellow birch (Table S2). Based on results from 220

logistic regression (Table S3), red spruce was almost nine times more likely to be snapped or 221

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uprooted than the most common hardwood species, yellow birch (95%CI of odds ratio: 2.93 to 222

29.7). In terms of the kind of damage, deciduous species were equally likely to snap as uproot 223

whereas conifers were three times more likely to uproot (Table 2). Susceptibility to tree fall 224

increased with DBH in the epicenter (p < 0.05, Table S3). For a 1 cm increase in DBH, the odds of 225

falling increased by 1.05 (95%CI: 1.01 to 1.10). 226

The largest gaps provided opportunities for recruitment of species less tolerant of shade 227

(Table 3). Two mid-tolerant species, red maple (Acer rubrum L.) and yellow birch, dominated 228

regeneration in the seedling plots with almost 8 stems m-2

in 2015 (Table 3). The four species 229

more tolerant of shade -- sugar maple, American beech, red spruce, and eastern hemlock 230

(Tsuga canadensis (L.) Carr.) -- represented only 13% of the seedlings present in 2015. In 231

addition, pin cherry (Prunus pensylvanica L. f.), an important pioneer species (Marks 1974), 232

successfully established seedlings in the gap. 233

DISCUSSION 234

The 2013 windstorm at the HBEF resulted in a damage pattern that is characteristic of 235

microbursts (Hjelmfelt 2007). The epicenter apparently marked the position of a downburst 236

that hit at the southern tip and then spread windward as the gust front dissipated. Thus in the 237

epicenter and the nearby gaps, treefall tracked the movement of the storm front (Fig. S1A, S1C-238

D). However, one km west of the epicenter there was a strong southern direction to the treefall 239

(Fig. S1B) possibly reflecting rotation associated with the descending current of air. The damage 240

within the HBEF was also was concentrated in the vicinity (< 1.5 km) of the epicenter. Based on 241

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the Δ NDVI analysis, the 600-ha area surrounding the epicenter accounted for 97% of the 242

disturbed area in the HBEF. 243

The Δ NDVI provided a robust measure of storm impact. The Δ NDVI estimate of 244

disturbance was statistically indistinguishable from the line-intersect estimate once the small 245

gaps were excluded. The Landsat results also matched field observations ‒ most of the large 246

gaps were in the storm impact area. 247

The Δ NDVI detected a disturbance complex approximately 7 km northeast of the 248

epicenter (Fig S3, near Elbow Pond). Field reconnaissance immediately after the storm 249

attributed these large gaps to wind damage. The location of the gaps along the storm track and 250

their similarity in damage pattern to the epicenter suggest another microburst from the same 251

thunderstorm damaged forests just outside of the HBEF. 252

Most of the damage from the microburst occurred in a small percentage of large, 253

severely disturbed patches (Fig. 1). Few studies of comparable intermediate or moderate 254

windstorms have been reported even though they are common throughout temperate zone 255

forests. Hanson and Lorimer (2007) described immediate impacts of a moderate windstorm 256

associated with a thunderstorm in old-growth hemlock-hardwood forests in Wisconsin. They 257

observed that although over 90% of the canopy gaps were <500 m2 in area, about two-thirds of 258

the disturbed area was in larger gaps (0.05 to 0.5 ha). However, in contrast to the HBEF 259

microburst, no very large patches were created by this storm in which maximum wind speeds 260

were measured at 112.7 km h-1

(70 mph). Evans et al. (2007) documented the distribution of 261

wind damage resulting from an organized complex of thunderstorms in northwestern 262

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Pennsylvania. The distribution of blowdown patch size was highly skewed across the storm 263

swath. The upper quartile of patches accounted for 73% of the wind-damaged area. Nagel and 264

Diaci (2006) reported on intermediate windstorm damage in old-growth beech-fir forest in 265

central Europe (Slovenia). Their map of the disturbances suggested that several large gaps (> 266

0.1 ha) comprised most of the disturbed area. Greenberg and McNab (1998) quantified damage 267

to an oak forest resulting from downbursts associated with a hurricane in North Carolina. Five 268

large gaps (0.2 to 1.1 ha) were observed in this downburst disturbance. Thus, for intermediate 269

or moderate wind disturbances large canopy gaps typically constitute much of the disturbed 270

area. 271

The overall susceptibility of forests to wind disturbance depends upon forest structure 272

and species composition. Both the spacing between trees and the vertical distribution of tree 273

crowns influence the risk of wind damage (Quine and Gardiner 2007). Across the storm impact 274

area at HBEF, canopy trees were damaged in proportion to their abundance (Table S1). This 275

similarity in susceptibility may be due to the relative homogeneity in the topography and 276

canopy structure in the storm impact area. In contrast, within the epicenter, red spruce seemed 277

particularly vulnerable (Table S2, Table S3) but with more than 75% of the trees damaged, 278

differences among species are unlikely to affect the trajectory of recovery. 279

Tree size had a moderate influence on susceptibility to tree fall in the epicenter. This 280

result reinforces the existing evidence that larger trees are at greater risk of wind damage in 281

the temperate forests of the northeastern United States (Canham et al. 2001, Peterson 2007). 282

We tested for a unimodal pattern in the size-dependency to wind damage. Everham and 283

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Brokaw (1996) argued that intermediate-sized trees were generally most susceptible. However 284

including the quadratic of tree size (DBH2) in the general linear model (Table 3S) did not 285

improve the model nor was DBH2 a significant parameter (p > 0.26). For the size range included 286

in our measurements (DBH ≥ 10 cm), the probability of tree fall increased linearly with DBH. 287

Two principal modes of damage characterize windstorm effects on canopy trees: 288

uprooting and snapping. These contrasting modes of disturbance differentially influence the 289

plant regeneration niche because of their contrasting effects on microenvironment, especially 290

soil substrate (Mitchell 2013). The proportion of trees uprooted varies widely among 291

windstorms depending upon the nature of the wind event as well as forest and site 292

characteristics (Peterson 2007). Wetter conditions at the time of severe wind events lead to a 293

higher proportion of uprooting because rooting strength is reduced in wet soils (Schaetzl et al. 294

1989). The wetness of the soil at HBEF may have contributed to the predominance of uprooted 295

trees (Table 1, Table 2) given that more than 2 cm of rain fell on the day of the microburst. Not 296

surprisingly, uprooted trees were also more common on poorly-drained soils (unpublished 297

data). 298

The large canopy gaps caused by the microburst provided opportunities for the 299

establishment of less shade-tolerant species (Table 3). In particular, the shade-intolerant pin 300

cherry (Marks 1974) and mid-tolerant red maple and yellow birch (Niinemets and Valladares 301

2006) exhibited high seedling abundance in the most severely disturbed locations (i.e., near 302

uprooted trees) in the large gaps. Peterson and Carson (2004) also found that pioneer trees 303

preferentially recruited on treefall mounds. Pin cherry regeneration is supplied by the dormant 304

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soil seed bank (Marks 1974) which has accumulated in the HBEF as a result of repeated 305

disturbance by logging as well as the 1938 hurricane (Thurston et al. 1992). This microburst 306

resulted in disturbances of sufficient severity to contribute to the persistence of pin cherry 307

populations in northern hardwood forest (Marks 1983), but the significance of the contribution 308

depends on the frequency of microbursts across the landscape. Moreover, we purposely 309

sampled tree regeneration in the largest gaps with half the plot area located on exposed 310

mineral soil. Thus while the microburst did create disturbances that are qualitatively different 311

frequent small gaps (sensu Romme et al. 1998), we cannot quantify the abundance of shade-312

tolerant recruits in the post-storm landscape from our sampling scheme. 313

It is challenging to measure the point recurrence interval of microbursts in temperate 314

forests (Lorimer and White 2003) in part because the spatial extent of damaging gusts is often 315

not well constrained. However with a combination of field data and remote sensing, we 316

obtained a validated forest-wide estimate of 0.65% for the June 2, 2013 storm. To estimate the 317

frequency, we compiled extreme wind speed data for 41 airport stations in the six-state region 318

(CT, MA, NH, NY, PA, VT) excluding coastal areas. These records include 3-second peak gusts 319

and denote whether the gust was associated with a thunderstorm (NIST 2016). Across 41 320

weather stations with an average record length of 32 years, there were 29 thunderstorms with 321

gusts exceeding 112.7 km h-1

(70 mph). Assuming these conditions could potentially generate 322

microbursts, the return time is 45 years (1,312 station-years/29 storms), and the recurrence 323

interval for canopy gap formation from microbursts at HBEF is 6,923 years (45 years/0.0065). 324

This estimate is at the high-end of the return times for wind and ice storms (1,000 - 7,500 years) 325

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inferred from pre-settlement land surveys for northern hardwood forests (Seischab and Orwig 326

1991, Lorimer and White 2003). 327

Observations from the HBEF provide some further context for judging the role of large 328

disturbances in the northern hardwood forest. Two major natural disturbances were recorded 329

for the HBEF in the 20th

century, a hurricane in 1938 and a severe ice storm in 1998. The 1938 330

hurricane caused only light damage throughout most of the HBEF, in part because most stands 331

were young and hence less susceptible to severe wind damage (Foster 1988); Peart et al. (1992) 332

noted that the heaviest damage in the HBEF (>80% basal area mortality) was confined to areas 333

that were not heavily logged at the turn of the 20th

Century. Thus, damage by the 1938 334

hurricane was certainly much lower than would have occurred in unmanaged forest. The 1998 335

ice storm caused severe canopy damage (e.g., reduction in leaf area index) that ranged from 336

20% to 60% over an area of about 300 ha between 600 and 800 m elevation, mostly on the 337

south-facing slope of the HBEF (Rhoads et al. 2002). Tagged-tree inventories indicate that tree 338

mortality from 1998-2012 in the area affected by the 1998 ice storm averaged 3.5% yr-1

(95% CI 339

= 1.8-8.6 % yr-1

) at the HBEF (van Doorn 2014). Thus during the 14 years following the ice storm, 340

approximately 40% of the adult trees died. This rate represents more than a doubling of the 341

background mortality rate for canopy trees (i.e., trees > 15 cm DBH) at HBEF (van Doorn et al. 342

2011). However the nature of the ice storm disturbance was diffuse (White and Jentsch 2001). 343

Leaf area was reduced (Rhoads et al. 2002) and trees were injured, but the storm did not create 344

well-defined canopy gaps and attendant steep gradients in resource availability. The primary 345

responses of the tree community to this event were a temporary decrease in productivity 346

(Battles et al. 2014) and a disproportionate increase of American beech recruitment in the 347

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understory (Weeks et al. 2009). In contrast, the 2013 microburst created many small canopy 348

gaps and a few large openings. While only 4.6% of the canopy in storm impact area was 349

disturbed, the larger gaps supported the recruitment of the shade-intolerant and pioneer tree 350

species (Table 3). 351

In sum, intermediate disturbances are a common cause of large canopy gaps in the 352

inland Northeast and play a role in shaping forest structure and composition. In particular, they 353

provide opportunities to maintain populations of pioneer species in a landscape typically 354

dominated by fine-scale disturbances (Marks 1983). Given the long dispersal distances for many 355

pioneer species like birches and aspens, even point return intervals of several thousand years 356

may be sufficient for population maintenance. However, we suggest that individual and small-357

group tree mortality resulting from less intense winds and tree senescence is the predominant 358

driver of forest dynamics in the region. 359

ACKNOWLEDGEMENTS 360

Financial support was provided by the National Science Foundation (NSF) Long-Term 361

Ecological Research (DEB 1114804) and the Research Experience for Undergraduate (DBI/EAR 362

0754678) programs. We are grateful for the research assistance provided by Noah Shephard, 363

Steve Harshman, Madeline Montague, Charlotte Higginson, Jamie Kellner, Carrie Levine, and 364

Samuel Battles. The Hubbard Brook Experimental Forest is administered by the USDA, Forest 365

Service Northern Research Station, Newtown Square, PA. We appreciate the constructive 366

criticisms provided by Alejandro A. Royo, Chris Peterson, and an anonymous reviewer for an 367

earlier version of this manuscript. 368

369

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Table 1. Distribution of the mode of damage by species for

gapmakers in the area most impacted by the microburst at Hubbard

Brook Experimental Forest, NH. Results are in percent of total (%); n

is the number of trees sampled in 12 km of line intersects.

Species* n Leaning Snap Standing Uprooted

Sugar maple 52 25.0 28.8 3.8 42.3

Yellow birch 60 11.7 25.0 3.3 60.0

American beech 56 8.9 26.8 28.6 35.7

Red spruce 80 16.3 26.3 0.0 57.5

Balsam fir 11 27.3 18.2 0.0 54.5

Other 12 25.0 25.0 0.0 50.0

TOTAL 271 16.2 26.2 7.4 50.2

*Other includes: red maple, paper birch (Betula papyrifera Marsh.),

eastern hemlock, and white ash (Fraxinus americana L.).

Table 2. Distribution of the mode of damage by species for the trees

in the epicenter of the microburst at Hubbard Brook Experimental

Forest, NH. Results are in percent of total (%); n is the number of

trees sampled in seven, 0.05 ha plots.

Species* n Leaning Pinned Snap Uprooted

Balsam fir 16 25.0 12.5 37.5 25.0

Red maple 12 0.0 16.7 41.7 41.7

Sugar maple 5 0.0 0.0 60.0 40.0

Yellow birch 31 12.9 16.1 32.3 38.7

American beech 6 16.7 33.3 50.0 0.0

Red spruce 41 0.0 4.9 17.1 78.0

Other 9 0.0 44.4 22.2 33.3

TOTAL 120 7.5 14.2 30.0 48.3

*Other includes: striped maple (Acer pensylvanicum L.), paper birch,

and eastern hemlock.

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Table 3. Differences in recruitment by species in large gaps

following the microburst at Hubbard Brook Experimental Forest,

NH. The mean and standard error (se) are reported. Density

reported in stems m-2

; sample includes 17 plots (12.57 m2) in

four large gaps.

Species* Density 2014 Density 2015

Mean se mean se

Red maple 6.5 2.3 4.2 1.3

Yellow birch 3.6 0.8 3.6 0.6

Pin cherry 2.4 0.7 1.0 0.3

Shade-tolerant species 1.5 0.3 1.5 0.3

TOTAL 14.3 3.2 10.8 1.9

*Shade-tolerant species includes: sugar maple, American beech,

red spruce, and eastern hemlock (Niinemets and Valladares 2006).

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Figure 1. Size-frequency distribution of canopy gaps caused by the 2013 microburst at Hubbard Brook Experimental Forest, NH based on results from line intersect sampling in the storm impact area (Fig. S1).

119x92mm (300 x 300 DPI)

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Figure S1. Caption on next page.

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Figure S1. Spatial pattern of wind disturbance in the Hubbard Brook Experimental Forest

(HBEF), NH resulting from a microburst storm on June 2, 2013. Above: position of the large

blowdown (“epicenter”) and the 600 ha storm impact area within the HBEF. Inset below:

position and size of canopy gaps sampled along line transects in the intensive sampling

area. Also shown are “wind rose” diagrams indicating the frequency of tree falls in

different compass directions for five areas: epicenter (A ); gaps along the most western

transect line (B); gaps along the transect just west of the epicenter (C); gaps, excluding the

epicenter, along the middle transect line (D); and gaps along the two most eastern

transect lines (E). In the wind rose diagrams, dark gray signifies snapped trees while light

gray denotes uprooted trees.

Figure S2. Detection threshold of Δ NDVI (NDVI_Difference) based on analysis of 100

randomly located test plots. The best segmented regression model (blue line) identified

two changepoints: NDVI_Difference = 0.044 and 0.06 (R2 = 0.75, p < 0.01). The location of

these breakpoints are indicated with dashed vertical lines. The shaded area around the

regression line is the 95% confidence interval. Note: positive difference values indicate

pixels with lower NDVI after the storm. Points represent results from each test plot.

Blowdown (%) calculated from the fraction of 33 grid locations that were in blowdown.

The lower changepoint (0.044) suggests that the NDVI_Difference could reliably detect

disturbances when ≥ 12.5% of the pixel was blowdown.

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Table S1. Summary of composition and damage in the storm damage

area. A) Pre-storm structure based on the 60 permanent plots

(sampled in 2005) in the storm damage area. Results reported are

means (n = 60 plots) and standard errors (SE). B) The comparison

between pre-storm density and gapmaker composition relies

primarily on the relative density (rDEN) of trees that could potentially

be gapmakers (i.e., stems ≥ 15 cm DBH). This expected frequency,

estimated from 2005 inventory, is compared to the relative

abundance (rGM) of the observed gapmakers (n = 271). Also included

is the relative basal area by species pre-storm (rBA).

*BEAL = yellow birch (Betula alleghaniensis Britt.);

PIRU = red spruce (Picea rubens Sarg.);

ACSA = sugar maple (Acer saccharum Marsh.);

FAGR = American beech (Fagus grandifolia Ehrh.);

ACRU = red maple (Acer rubrum L.);

ABBA = balsam fir (Abies balsamea (L.) Mill.);

BEPA = paper birch (Betula papyrifera Marsh.);

TSCA = eastern hemlock (Tsuga canadensis (L.) Carr.);

ACPE = striped maple (Acer pensylvanicum L.).

A. Pre-storm structure

Basal area (m2

ha-1

) Density (stems ha-1

)

Mean SE Mean SE

30.5 0.8

582 30

B. Comparison between pre-storm and gapmaker composition

Species*

rBA

(%, pre-storm)

rDEN

(%, pre-storm)

rGM

(%)

BEAL 21.4 26.3 22.1

PIRU 13.3 21.4 29.4

ACSA 16.7 18 19.1

FAGR 16.4 14 20.6

ACRU 9.1 6.8 2.2

ABBA 12.9 6.2 4

BEPA 4.8 5.8 1.5

TSCA 2.8 1.4 0.3

ACPE 2.4 0 0

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Table S2. Summary of composition and damage in the epicenter of the disturbance. “Pre-live” refers to

all the live and recently dead trees in the plots. Note that 2005 basal area for the 10 plots surrounding

the epicenter (including the two plots in the epicenter) was 29.8 m2

ha-1

(standard error = 2.2). “Post-

live” refers to live trees after the storm. “Post-intact” refers to all the live trees that are NOT pinned,

tipped, or snapped. Results reported are means (n = 7 plots) with standard error in parentheses. Post-

storm survival defined as the fraction of stems that survived the storm; Post-storm intact defined as the

fraction of live trees that are alive and NOT pinned, tipped, or snapped. Estimates based on basal area

and on density. A) Results reported for all seven plots; B) Results reported by species. Note: rBA =

relative basal area.

A. Stand summary

Basal area (m2

ha-1

)

Density (stems ha-1

)

Pre-live Post-live Post-intact Pre-live Post-live Post-intact

27.6 (2.4) 15.7 (2.9) 5.3 (1.5)

434(44) 231 (40) 106 (25)

*BEAL = yellow birch (Betula alleghaniensis Britt.); PIRU = red spruce (Picea rubens Sarg.); ACRU =

red maple (Acer rubrum L.); ACSA = sugar maple (Acer saccharum Marsh.), ABBA = balsam fir (Abies

balsamea (L.) Mill.); FAGR = American beech (Fagus grandifolia Ehrh.); BEPA = paper birch (Betula

papyrifera Marsh.); TSCA = eastern hemlock (Tsuga canadensis (L.) Carr.); ACPE = striped maple (Acer

pensylvanicum L.); ACSP = mountain maple (Acer spicatum Lam.).

B. Species basis

Species* Pre-live rBA (%) Post-storm by basal area Post-storm by density

%survive %intact

%survive %intact

BEAL 45.0

69 26 66 32

PIRU 28.1

47 3 37 9

ACRU 6.6

30 8 31 8

ACSA 5.8 39 8 50 17

ABBA 5.6 38 27 59 45

FAGR 3.6 71 44 80 50

BEPA 2.4 52 31 60 20

TSCA 2.2 100 81 100 67

ACPE 0.4 73 0 75 0

ACSP 0.3 0 0 66 32

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Table S3. Details from logistic regression of tree fall predictors in the

epicenter. Tree fall was defined as trees that were snapped or uprooted

during the storm. DBH is the diameter at breast height (1.37 m); four letter

codes refer to tree species*. Species effects of tree fall relative to the most

common hardwood species in the epicenter, yellow birch (Betula

alleghaniensis Britt.).

A. Model summary Deviance Residuals:

Min 1Q Median 3Q Max

-2.3253 -0.9865 0.4957 0.8040 1.5148

Coefficients:

Estimate Std. Error z value Pr(>|z|)

Intercept -1.43998 0.69677 -2.067 0.038766 *

DBH 0.04996 0.02024 2.469 0.013556 *

ABBA 0.40814 0.60656 0.673 0.501025

ACRU 1.48913 0.76086 1.957 0.050328

ACSA 1.39804 1.15366 1.212 0.225576

BEPA -0.14043 0.99108 -0.142 0.887321

FAGR -0.43449 0.79380 -0.547 0.584140

PIRU 2.16552 0.58580 3.697 0.000218 ***

OTHER 0.18645 0.88116 0.212 0.832426

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05

(Dispersion parameter for binomial family taken to be 1)

Null deviance: 196.23 on 148 degrees of freedom

Residual deviance: 162.72 on 140 degrees of freedom

AIC: 180.72

B. Odds ratio

Parameter Mean CI_2.5% CI_97.5%

Intercept 0.24 0.06 0.88

DBH 1.05 1.01 1.10

ABBA 1.50 0.46 5.02

ACRU 4.43 1.09 23.21

ACSA 4.05 0.56 82.42

BEPA 0.87 0.10 6.10

FAGR 0.65 0.12 2.92

PIRU 8.72 2.93 29.73

OTHER 1.20 0.20 6.93

*PIRU = red spruce (Picea rubens Sarg.); ACRU = red maple (Acer rubrum L.); ACSA = sugar maple (Acer

saccharum Marsh.), ABBA = balsam fir (Abies balsamea (L.) Mill.); FAGR = American beech (Fagus

grandifolia Ehrh.); BEPA = paper birch (Betula papyrifera Marsh.); OTHER includes uncommon species

in the plot.

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Figure S3. Map of potential gaps caused in and around Hubbard Brook Experimental Forest associated with the

2013 microburst storm. Red pixels identify locations with Δ NDVI (NDVI_Difference) > 0.044. Disturbances

associated with harvest or development were deleted. Note: contour interval of the base map (United Stated

Geological Service) is 50 feet.

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