Infestations Within the Ozark and Ouachita National Forests

Forest Ecology and Management 259 (2010) 1938–1945

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Forest Ecology and Management

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Stand and individual tree characteristics associated with Enaphalodes rufulus (Haldeman) (Coleoptera: Cerambycidae) infestations within the Ozark and Ouachita National Forests

L.J. Haavik *, F.M. Stephen

Department of Entomology, 1 University of Arkansas, 319 AGRI, Fayetteville, AR 72701, USA

ARTICLE INFO ABSTRACT

Article history: Many oak decline events have been reported within the past century in the eastern U.S., and important Received 18 December 2009 causal factors often differ among them. Coincident with a recent decline event in upland oak-dominant Received in revised form 2 February 2010 forests of Arkansas, Missouri, and Oklahoma was an unexpected outbreak of a native cerambycid beetle, Accepted 4 February 2010 Enaphalodes rufulus (Haldeman), the red oak borer. A large range in estimates of oak mortality throughout affected forests was presumably due to variation in species composition, where oak-dominant areas Keywords: experienced the greatest mortality. We chose eight sites across the Ozark and Ouachita National Forests of Oak decline Arkansas, similar both topographically and by oak dominance, to determine if other stand or tree Cohort senescence characteristics were important factors in variation of E. rufulus infestations across these forests. At each site, Wood borer Physiological age we sampled 125 dead, declining or healthy host Quercus rubra L., northern red oak. We created an Classification tree estimate of the E. rufulus population level at each site during the recent outbreak using counts of dated larval gallery scars within a subset (n = 120) of all Q. rubra sampled (n = 976). We used classification tree partitioning to determine host tree characteristics that differed among dead, declining, and healthy Q. rubra. We also used classification tree partitioning, followed by logistic regression to determine stand characteristics that varied significantly among high, moderate and low infestation stands as well as between forests. Models indicated that trees which died were smallest, grew the least during the borer outbreak, and were apparently suppressed. These dying trees were likely poor competitors for resources, allowing neighboring survivors to experience a growth release during the E. rufulus outbreak. Larval survivorship was higher in trees which died, though larval densities were not greatest within these trees, which suggests that resistance in these individuals was compromised. At the stand level, differences between forests were apparently more important than those due to borer infestation. E. rufulus populations were higher at sites with lower Q. rubra basal area. This reduced basal area was likely a result of greater Q. rubra mortality at these sites during the borer outbreak in the early 2000s. ß 2010 Elsevier B.V. All rights reserved.

1. Introduction and Lachance, 1992; Thomas et al., 2002). Due to this complexity, several forest decline theories have arisen. In general these Many forest decline events have been reported throughout the theories encompass some combination of site inﬂuence or forest past three centuries on several continents (e.g. North America, history, climatic extremes and secondary invaders such as Europe, Australia, Sinclair, 1965; Kessler, 1992; Thomas et al., pathogenic fungi and/or insect attack (Manion and Lachance, 2002; Jurskis, 2005) affecting a variety of forest types either at the 1992). genus level (e.g. oak decline, Balch, 1927) or at the individual Upland oak-hickory forests in Missouri, Arkansas and Okla- species level (e.g. sugar maple decline, Minorsky, 2003). Search for homa experienced an oak decline event in the late 1990s and early primary causal mechanisms is complicated by the fact that decline 2000s affecting over 121,000 ha (300,000 acres) of public forest events arise from a complex of interacting biotic and abiotic factors land (Starkey et al., 2004). White oak species (Quercus section (Sinclair, 1965; Mueller-Dombois, 1987; Manion, 1991), and Leucobalanus) were less affected than red oak species (Quercus important factors often vary by speciﬁc decline event (Manion section Lobatae)(Starkey et al., 2004; Heitzman et al., 2007; Fan et al., 2008). A native cerambycid, Enaphalodes rufulus (Haldeman), the red oak borer, was an important secondary invader attacking * Corresponding author. Tel.: +1 479 575 3384; fax: +1 479 575 3197. members of the red oak group, primarily Q. rubra L., Quercus E-mail address: [email protected] (L.J. Haavik). coccinea Muenchh., and Quercus velutina Lam. (Stephen et al., 2001;

Starkey et al., 2004; Fan et al., 2008). This decline event and and the USDA Forest Service websites. Potential sites were located concurrent E. rufulus outbreak were unique in two ways. To date, it using the following criteria: oak-hickory or shortleaf pine-oak is the only oak decline event in the eastern U.S. found to be dominant forest type according to southern forest inventory and associated with E. rufulus (Millers et al., 1989). E. rufulus densities analysis (USDA Forest Service, 2001), comparable topography (ridge were 10–100 times greater than anything previously reported for tops and adjacent north and south facing slopes), and accessibility by this species within other eastern U.S. oak forests (Hay, 1974; road (within 400 m of nearest road). We selected sites which were as Donley and Rast, 1984; Fierke et al., 2005). similar as possible in topography and dominant species composition History of these second growth forests may be important in the in an attempt to hold these variables constant so that importance of recent oak decline event, as much of Ozark and Ouachita upland other variables could be observed more clearly. Generally, we forests were clear cut in the early 1900s and regeneration occurred avoided prescribed burn areas, although this was more difficult in primarily through stump sprouting (Strausberg and Hough, 1997). the Ouachita National Forest, as most oak dominant stands were Fire suppression followed throughout much of the 20th century, included in these burn areas. We visited >100 potential sites located resulting in a current simplified canopy structure of even-aged by the GIS, and finally selected eight sites somewhat evenly stands reaching maturity with little oak regeneration in the distributed throughout these national forests, that exhibited a range understory (Strausberg and Hough, 1997; Soucy et al., 2005). of observable Q. rubra mortality. Four sites were located within the Mortality estimates for this recent Ozark/Ouachita Mountains oak Ozark National Forest and four were located within the Ouachita decline event vary substantially, and range from 2% to 100% of National Forest (Fig. 1). We collected data from three stands at each basal area, apparently depending largely on species composition of study site: one on the ridge top, and one each on the adjacent south stands. Red oak dominant stands experienced 30–100% mortality, and north facing slopes. At one site in the Ouachita National Forest, whereas all stands on average, regardless of species composition, Fork Mountain, the north facing slope consisted of 100% Q. rubra experienced 2–15% mortality (Starkey et al., 2004; Guldin et al., mortality, so we collected north facing slope data from a nearby 2006; Heitzman et al., 2007). Some variation in mortality both at slope, Rattlesnake Mountain, which was 3 km north of Fork the stand and individual tree level may be due to factors other than Mountain. We collected individual tree data (described in Section species composition. Fierke et al. (2007) found that Q. rubra 2.2)from35Q. rubra at each stand, or from all live Q. rubra present, mortality and E. rufulus infestation varied by aspect as well as 105 trees per study site, and 20 dead standing or fallen Q. rubra species richness, though that study did not compare stands with per site. Overall sample sizes were: 815 live and 161 dead Q. rubra. similar aspects and different levels of E. rufulus infestation. Climate in the Ozark/Ouachita region is temperate with hot Many forest decline theories predict that advancing stand age is summers and mild winters. Mean January temperature is 4 8C, of primary importance in a decline event (Sinclair, 1965; Mueller- mean August temperature is 27 8C, and the annual mean is 16 8C. Dombois, 1987; Manion, 1991). Oak et al. (1991) found that a ratio Most precipitation occurs during spring and fall, totaling 124 cm in of site index to actual tree age as a measure of physiological age the Ozark Mountains and 150 cm in the Ouachita Mountains was a better predictor of stand maturity and susceptibility to oak (NCDC, 2009). Rock formations of limestone, sandstone and shale decline than actual tree age. If age-related changes in host comprise much of the Ozark Plateau, which is characterized by susceptibility were an important factor in E. rufulus population deep valleys, steep ledges and cliffs with elevations up to 750 m increase, then stands and/or trees which were old physiologically with slopes facing all cardinal directions (Adamski et al., 1995). The may have been the most likely to experience high borer Ouachita Mountains are oriented such that ridges run east to west populations. with maximum elevations reaching 790 m, where upper slopes are The objective of this study was to determine if particular tree or steep, gradually leveling off at lower elevations into U-shaped stand characteristics differed among areas with higher E. rufulus valleys (Guldin, in review). Soils in both forests are generally rocky, infestation density compared to those with lower populations. acidic and clay-rich, with low organic matter content (Adamski Specific characteristics measured at the stand level were mean et al., 1995). stand physiological age, basal area, density, species evenness and slope aspect. At the individual tree level we evaluated tree size 2.2. Field data collection (DBH), number of live or dead main stems sharing the same root system, actual age and physiological age. A quantitative estimate of To estimate stand variables, we sampled 7–10 variable radius the E. rufulus population during the outbreak within each study points per stand at each of the 24 stands with a 1 m basal area area was necessary to establish infestation levels for comparison. prism. Each sampling point was sufficient distance from the others Larval galleries leave exactly dateable scars within host tree-rings to avoid overlap in sampling radii. Tree species and diameter at (Muzika and Guyette, 2004; Haavik and Stephen, submitted for breast height (DBH) of all tallied trees were recorded in order to publication), and counts of these scars dated to the outbreak time calculate stand density and a species evenness index (Shannon, period were used to estimate infestation at the site level. To 1948) for each stand. Exact stand location, site index, slope angle determine individual tree infestation densities, counts of scars or and direction and site burn history are listed in Table 1. an indicator of second year larval survival may be useful as host Data collected at the individual tree level included: DBH, tree suitability is likely to be more important during larval develop- height using a Haga1 altimeter and counts of live and dead ment within trees than susceptibility at initial colonization dominant stems apparently utilizing the same root system. We (Haavik et al., 2010). used site index charts developed for Q. rubra and Q. velutina in the Boston Mountains of Arkansas to determine mean tree height at 2. Materials and methods age 50 using mean age at breast height and mean tree height per stand (Carmean et al., 1989). We also extracted, for age and growth 2.1. Study sites data, one increment core per tree on the west facing side of the bole at breast height. This direction was specified to avoid capture of We searched for study sites with a geographic information any reaction wood and to maintain consistency of sampling among system (GIS) developed within Environmental Systems Research trees growing on various aspects and at various sites. We cut cross- Institute’s (ESRI) ArcGIS 9.2 software and data layers downloaded sections from fallen and standing dead trees at approximately from GeoStor, run by the Arkansas Geographic Information Office, breast height and brought them back to the lab for processing the University of Arkansas’s Center for Advanced Spatial Technology along with the increment cores. 1940 L.J. Haavik, F.M. Stephen / Forest Ecology and Management 259 (2010) 1938–1945

Fig. 1. Map of the state of Arkansas with the Ozark and Ouachita National Forests in dark gray. Black dots represent UTM coordinates of site locations. Site names in the Ozark National Forest (west to east): Mule Farm, Red Star, Cowell and Stack Rock. Site names in the Ouachita National Forest (clockwise beginning at center north): Dry Creek Mountain, Flatside, Fork/Rattlesnake Mountains and Talimena. Inset: UTM coordinate locations of all live trees sampled (white dots) at Red Star overlaid on a digital elevation model, as an example of topography and spatial layout of the three stands (south, north and ridge) at each site.

Table 1 Site name according to local geography, exact location and background topographical information.

Site name UTM coord.a Elevationb Aspect Treesc Site indexd Slope directione (8) Slope steepnessf (8) Burn yearsg

Mule Farm 426427, 3960826 685 Ridge 35 15 South 35 14 140 28 North 35 16 320 27

Red Star 453091, 3970897 750 Ridge 35 14 South 35 13 160 22 North 35 18 340 14

Cowell 488167, 3967424 633 Ridge 35 15 South 35 14 160 27 North 34 18 340 36

Stack Rock 507522, 3969035 560 Ridge 35 16 South 35 15 120 19 North 35 17 345 22

Dry Creek Mountain 421005, 3878915 575 Ridge 35 10 South 35 11 170 18 North 35 14 350 36

Flatside 508658, 3857814 443 Ridge 35 12 2001 South 35 12 190 23 2001 North 35 14 10 31 2001

Fork Mountain 405103, 3812246 512 Ridge 28 9 South 35 9 160 27

Rattlesnake Mountain 406001, 3813454 556 North 18 13 340 37 1998

Talimena 367539, 3837775 646 Ridge 35 9 South 35 12 170 25 North 35 13 350 22

a UTM zone 15N. b Estimated elevation in meters at the ridge top stand by ArcGIS 9.2. c Number of live individual Q. rubra sampled. d Site index, or mean height of trees at age 50 in meters. e Direction in degrees of slope face. f Steepness slope in degrees measured with a Suunto1 clinometer. g Recorded years of prescribed burns (if any) according to USDA Forest Service spatial data records. L.J. Haavik, F.M. Stephen / Forest Ecology and Management 259 (2010) 1938–1945 1941

2.3. Lab data collection and processing evaluate site and tree infestation levels. We transformed the response variables, number of borer scars and proportion of 2.3.1. Tree-rings successful borer scars, using the Box–Cox method (Box and Cox, We mounted cores and sanded them along with dead tree 1964) as assumptions of normality were violated according to cross-sections with progressively finer sandpaper, beginning with residual plots, normal probability plots or the Shapiro–Wilk test 36 grit and ending with 600 grit. We then crossdated all cores and (Shapiro and Wilk, 1965). Data presented are untransformed cross-sections according to standard techniques (Douglass, 1941; values. Stokes and Smiley, 1996) using Q. rubra master chronologies We used classification and regression tree partitioning (Brei- developed individually by skeleton plots for each of the eight study man et al., 1984) to determine important characteristics of dead, sites. We measured individual tree-ring width series to the nearest declining and healthy individual Q. rubra. Partitioning techniques 0.001 mm using a Velmex ‘‘TA’’ system (Velmex Inc., 2008)in are non-parametric, and a combination of continuous and conjunction with the ‘‘MeasureJ2X’’ software program (VoorTech categorical variables can be used for both descriptors as well as Consulting, 2007). We used the computer program COFECHA as a the response (Breiman et al., 1984; De’ath and Fabricius, 2000). In a quality control tool to check for errors in measurements and similar study, Fan et al. (2006) found this type of partitioning crossdating (Holmes, 1983), and then the program ARSTAN (Cook superior to logistic regression in describing important character- and Holmes, 1986) to standardize individual tree-ring series. We istics associated with tree survival. Partitioning includes two selected a linear detrending, and separated live trees by decline processes. First, it repeatedly splits a single response variable, e.g. status based on the sign of the linear detrending slope, i.e. positive tree decline status, by variation in the specified descriptor slopes indicated healthy trees and negative slopes indicated variables into more homogeneous groups. Second, these groups declining trees. We used Duncan’s method to determine age of may become too small, and they may require pruning, or lumping cores with missed pith by less than 5 years (Duncan, 1989). If we back into a larger group of observations, according to a pre- missed pith by more than five years, we re-cored trees for better specified rule. Groups are first termed branches as the tree accuracy. For some trees sampled, age was not possible to continues to spit into smaller groups, and finally leaves at terminal determine due to heart rot, carpenter ant galleries, or scars at groups (De’ath and Fabricius, 2000). We used a prune rule of 5%, the pith. We calculated decadal growth of each individual tree from where each leaf was required to contain at least 5% of all 1980–1990 and 1990–2000, time periods which include the rise, or observations. To ensure this pruning rule was sufficient, we used a incipient stage and outbreak of E. rufulus (Haavik and Stephen, cross-validation rule of five, where every fifth observation was unpublished). We carefully recorded year of death for all dead dropped, and the variance explained by this folded model was cross-sections that were not too decayed at the outer-most compared to the overall model (De’ath and Fabricius, 2000). sapwood ring, and omitted the time period from 2000 to present in Partitioning does, however, require a large number of growth calculations as many of the dead Q. rubra died just before or observations to be an effective modeling method and the number just after 2001, when populations of E. rufulus were at their peak at of stands in this data set were limited compared to the number of most sites (Haavik and Stephen, unpublished). It is unclear individual trees. We used classification tree partitioning for stand- whether tree mortality was directly caused by borers alone or a level characteristics, followed by binomial logistic regression combination of oak decline factors. Physiological age was models to examine differences in stand variables by infestation calculated as the ratio site index to actual age at breast height level. For logistic regression, high infestation stands were coded as according to Oak et al. (1991). Ages and physiological ages were one and low infestation stands were coded as zero. For a separate determined as ages in year 2000, not age when trees were sampled. model, stands located in the Ozark Mountains were coded as one This permitted age comparisons among currently living trees and and those located in the Ouachita Mountains were coded as zero. trees which died prior to sampling in 2008. Statistical significance was determined at P < 0.05, and error bars represent one standard error of the mean. 2.3.2. Borer scars We felled and sampled 15 trees from the ridge top stand per site 3. Results (120 total) in order to date and count larval gallery scars according to a previously developed sampling strategy. The sampling plan 3.1. Site and tree infestation included cutting varying numbers of 5 cm thick cross-sections from the lower 20% of tree boles (Haavik and Stephen, submitted Mean number of E. rufulus scars dated to the recent outbreak for publication). Counts of scars recorded during the outbreak time differed by site (Fig. 2(A); P < 0.0001; F = 15.925; df = 7,70). In period represent an estimate of site-level infestations. All dead order to extrapolate statistical differences found among the 10 live trees sampled for borer scars were removed from this data set due trees sampled at each site to the stand level, we divided sites to sapwood decay preventing exact dating of some scars within according to three levels of infestation: high, moderate and low some dead trees. Borer scars were grouped in one of two (Fig. 2(B)). Mule Farm and Flatside were designated as high categories: either larvae that survived to pupation and likely infestations, with a combined mean of 22.52 Æ 2.40 scars m of host adulthood or those that survived partially through their second bole during the outbreak. Dry Creek Mountain and Fork Mountain year of feeding. We termed the latter ‘‘unsuccessfuls’’ and the were designated as moderate infestations, with a combined mean of former ‘‘successfuls’’. These two categories were identifiable based 11.24 Æ 1.23 scars m of host bole during the outbreak, and the on knowledge of E. rufulus biology, as sapwood/heartwood tunnel remaining sites (Talimena, Cowell, Stack Rock and Red Star) were low length and width is easily identifiable for larvae that survived to infestations, with a combined mean of 5.02 Æ 0.72 scars m of host become adults (Fierke et al., 2005). Any galleries observably bole during the outbreak. smaller than full-sized fourth instar larvae were grouped into the To estimate infestations at the tree level, we divided trees by ‘‘unsuccessful’’ category. their decline status as determined from long-term growth patterns, i.e. healthy, declining or dead, and first searched for 2.4. Data analysis differences in density of borer scars among these groups. This model was significant (P = 0.0511; F = 3.063; df = 2,102), wherein We analyzed all data with JMP 8.0 (SAS, 2009). We used one- declining trees contained more borer scars than healthy trees, and way analysis of variance and Tukey’s test for mean separations to the number of scars in dead trees was no different than the others. 1942 L.J. Haavik, F.M. Stephen / Forest Ecology and Management 259 (2010) 1938–1945

(1980–1990) and during outbreak (1990–2000), site infestation level (high, moderate or low), physiological age, actual age, DBH, number of dominant stems apparently growing from the same root system (live trees only) and number of these stems that were dead. The final tree split three times by decadal radial growth during the outbreak (1990–2000), three times by DBH, and once by site infestation level with a total of seven splits (Fig. 4). The final model explained 21.8% of the variance in these data. Decadal growth during the outbreak (1990–2000) was the first splitting criterion, and a majority of the dying trees grew less than 13.586 mm during this time period. A majority of these dying trees were also smaller than 21.1 cm in DBH; those that were greater than 21.1 cm were mostly located at high infestation sites. Dying trees that grew more than 13.586 mm during the outbreak decade were also smaller than 27.1 cm in DBH. Most healthy trees grew more than 13.586 mm during the outbreak decade although similar propor- tions were smaller or larger than 27.1 cm in DBH. Of those healthy trees which were larger than 27.1 cm in DBH, a majority grew more than 18.047 mm during the outbreak. Of those, the greater part Fig. 2. Mean number of E. rufulus scars m of Q. rubra bole within live trees during the was smaller than 36.3 cm in DBH. Of healthy trees larger than outbreak by site (A) and subsequently assigned infestation level (B), where H = high, 36.3 cm in DBH, a majority grew more than 23.825 mm during the M = moderate, and L = low E. rufulus infestations. Letters above bars indicate outbreak, although many grew less than 23.825 mm. Declining statistically significant differences at the 0.05 level (A) and error bars represent one trees were found throughout many branches and leaves of the standard error of the mean. Ten live trees were sampled at all sites except Cowell and Flatside (n = 9). classification tree, and in general, they grew less during the outbreak than healthy trees whenever the classification tree was Declining trees contained a mean of 17.48 Æ 1.99 borer scars m bole, split by growth. If declining trees grew less than 13.586 mm during healthy trees contained a mean of 12.094 Æ 1.42 borer scars m bole, the outbreak, most were larger than 21.1 cm in DBH, and found at and dead trees contained a mean of 15.12 Æ 1.98 borer scars m bole. moderate or low infestation sites. The proportion of successful scars as an indicator of general Seventy-nine percent of dead Q. rubra sampled died in 1999 or survivorship proved a better model, as means separations tests thereafter, and 50% died between 1999 and 2002 (Fig. 5). The indicated that all three decline status categories were statistically number of trees which died prior to 1999 may have been different (Fig. 3, P < 0.0001; F = 13.0751; df = 2,102). Approximately underestimated due to sapwood decomposition of individuals two-thirds of E. rufulus larvae were successful within trees that died, whose death date we were unable to decipher. This was not of half were successful within declining trees, and only one-third were primary concern as study objectives were to sample characteristics successful within healthy trees. of trees whose deaths were associated with the recent E. rufulus outbreak. 3.2. Tree characteristics 3.3. Stand characteristics We used classification tree partitioning with tree decline status as the response variable to determine important characteristics We also used a classification tree to partition stand character- that differed among dead, declining and healthy trees. Potential istics. Potential descriptor variables were aspect (north, south or descriptors were: decadal radial growth (mm) pre-outbreak ridge), basal area, Q. rubra basal area, density, Q. rubra density, Shannon index of species evenness, percent Q. rubra, site index and mean physiological age of stands. The classification tree split twice, first by mean physiological age of stands and second by Q. rubra basal area (Fig. 6). This final model explained 63.9% of the variance in these data. All of the moderate infestation stands were split to the right-most leaf of the tree, and were older physiologically (smaller numerical values indicate older physiological age) than all high infestation stands and most low infestation stands. All high infestation stands were split to the left main branch of the tree, and then to the center leaf with a Q. rubra basal area of less than 9m2 haÀ1. Most low infestation stands were young physiologically (left main branch), and had a Q. rubra basal area >9m2 haÀ1. Since the classification tree was able to partition moderate infestation stands apart from the others with the first splitting criterion, they were eliminated from logistic regression models with infestation level as the response. Models including mean stand physiological age and/or Q. rubra basal area were not significant, though a model with the species evenness index as the descriptor was significant (P = 0.0208, R2 = 0.2331). High infestation stands had greater species evenness index values compared to low infestation stands. The only significant variable included in the Fig. 3. Mean proportion of successful E. rufulus larvae in dead, declining and healthy host Q. rubra. Letters above bars indicate statistically significant differences at the final model of stand descriptors by forest was mean stand 2 0.05 level, and error bars represent one standard error of the mean. Sample sizes physiological age (P < 0.0001, R = 0.6862). This model was were: 27 dead, 39 declining and 39 healthy trees. consistent with the classification tree, where stands in the L.J. Haavik, F.M. Stephen / Forest Ecology and Management 259 (2010) 1938–1945 1943

Fig. 4. Classiﬁcation tree of dying, declining and healthy trees split by characteristics described in the text. Each small plot displays proportion of dying (black bars), declining (light gray bars) and healthy (dark gray bars) trees in each branch or leaf (terminal group) of the classiﬁcation tree, with number of observations in parentheses at the top right corner. Characteristics used for each split are in the main title position above each plot along with the values used at each split. Growth* is the decadal radial growth from 1990–2000 in mm. Infest refers to the infestation level of the site. Total n was 920, or 165 dying, 403 declining and 352 healthy trees.

Ouachita Mountains were physiologically older than stands in the species dominance and topography. Sites were grouped into borer Ozark Mountains. infestations of high, moderate or low levels as carefully as possible using statistical differences as guidelines (Fig. 2(B)). At the 4. Discussion individual tree level, dead trees did not contain signiﬁcantly more

4.1. Stand and tree infestation level

Sites varied by density of E. rufulus scars found within sampled boles during the outbreak time period (Fig. 2(A)), indicating geographic variation in borer densities among stands of similar

Fig. 6. Classification tree of E. rufulus stand-level infestations by characteristics described in the text. Each small plot displays the proportion of high (black bars), moderate (light gray bars) and low (dark gray bars) infestation stands in each branch or leaf of the classification tree, with number of observations in parentheses at the top left corner. Characteristics used for each split are in the main title position above each plot along with the values used at each split, where Q. rubra BA is Q. rubra basal area within a stand. Phys age is mean physiological age (site index/ Fig. 5. Mortality dates of dying Q. rubra by proportion of dying trees that died within actual tree age) of all Q. rubra sampled in a stand, where smaller numerical values a specific year. Total number of dead trees whose cross-sections contained at least a indicate physiologically older stands. Total n was 24, or 6 high, 6 moderate and 12 portion of the outer-most sapwood ring to date year of death was 126. low infestation stands. 1944 L.J. Haavik, F.M. Stephen / Forest Ecology and Management 259 (2010) 1938–1945 or less borer tunnels and/or scars than either healthy or declining causal factor leading to eventual dieback and mortality events trees, which suggests that larval densities were not indicative of when the resulting even-aged stands became over-mature, as tree infestation level. One study found that dead or dying red oaks many other authors have suggested (Kessler, 1992; Starkey et al., contained more evidence of E. rufulus infestation than healthy trees 2004; Soucy et al., 2005; Kabrick et al., 2008). It is likely that all (Heitzman et al., 2007), while another did not find any differences stands sampled were of a susceptible age for a decline event. (Fan et al., 2008). Trees that died may have been weakened enough physiologically prior to E. rufulus attack so that relatively few 4.3. Stand characteristics borers were required to kill them. Alternatively, during the dying phase they may have become an ephemeral host resource and The stand classification tree explained more than half of the adult borers abandoned them in search of more suitable hosts for variation within these data (Fig. 6), as did the regression model with oviposition. Little is known about host selection in this species due forest as the response variable. Partitioning indicated that moderate to cryptic nature of adults (Hay, 1969). Second year larval survival infestation stands were physiologically older than the others, and as indicated by differing sizes of tunnels and phloem gallery scars logistic regression indicated that stands in the Ouachita Mountains exhibited a clear statistical pattern by decline status (Fig. 3), were physiologically older than those in the Ozark Mountains. All suggesting that resistance was compromised in dying host trees. moderate infestation stands occurred within the Ouachita Moun- tains, while high and low infestation stands existed within both 4.2. Tree characteristics forests. Poorer quality sites existed in the Ouachita Mountains compared to the Ozark Mountains, as indicated by lower site index Decadal growth during the outbreak (1990–2000) and DBH values (Table 1), which directly influenced calculations of physio- were the most important predictor variables of tree decline status logical age. Stand-level differences between these two forests were by classification tree partitioning (Fig. 4). The remaining potential greater than differences observed among site infestation levels as descriptor variables were apparently not important as most were indicated by explanatory power of regressions. not used to split the final classification tree. Partitioning Q. rubra basal area was not a significant predictor of high or low successfully split healthy versus dying trees on the left or right infestationstandsaccordingto logistic regression, whilethe Shannon main branches of the classification tree, respectively. Declining species evenness index was a significant predictor. Shannon index trees did not partition as well, and occurred throughout both main values were dependent on Q. rubra basal area, as Q. rubra was the branches of the classification tree. Other studies found that a range dominant species in most stands, and species abundance is a of Q. rubra size classes experienced dieback during the recent oak component of evenness. Both Q. rubra basal area and the Shannon decline event (Guldin et al., 2006; Heitzman et al., 2007). A broader index varied in the same manner with respect to high or low set of potential descriptor variables may be necessary to determine infestations, where high infestation stands had a lower Q. rubra basal differences between declining and healthy trees, such as percent areaand a higher evennessindex value. A study conducted during the canopy dieback, crown width or transparency. outbreak found Q. rubra to be the most important species in high risk Many dying trees did not experience mortality until 1999 or stands, with more trees dead or dying in these areas (Heitzman and thereafter (Fig. 5). Slow growth for several years prior to death Guldin, 2004). Another study from the same time period determined suggests that these individuals were not important competitors for that species richness was lower in stands with higher E. rufulus resources, which likely allowed neighboring healthy trees to densities (Fierke et al., 2007). Since our study took place seven years experience a growth release. Severe crown dieback was evident post-disturbance, stand-level measurements likely reflect character- among many dying Q. rubra during the recent oak decline event istics of recovering stands rather than stands influencing outbreak (Starkey et al., 2004; Guldin et al., 2006). This would provide conditions. Stands with a large Q. rubra component and low species nearby healthy trees with more light in the crowded canopy richness may have been more susceptible to borer-associated conditions of dense stands (Chapman et al., 2006; Masters et al., mortality during the outbreak, and post-outbreak appear to have 2007). Since dead trees were often smaller, and did not differ from lost some of this Q. rubra component, resulting in greater species live trees in age or physiological age, they were likely suppressed. evenness within these stands. This is consistent with the fact that these trees did not contain more borer holes during the outbreak than live trees, yet they died 4.4. Conclusions anyway, presumably due to inferior capacity for resource acquisition and/or reduced resistance to E. rufulus or other Radial growth during the recent E. rufulus outbreak and size of secondary invaders, such as root pathogens (Armillaria spp). Three trees were the most important variables separating healthy, species of Armillaria infect Q. rubra and are widespread throughout declining and dying host Q. rubra. Most dying Q. rubra experienced the region (Bruhn et al., 2000; Kelley et al., 2009), yet their mortality in 1999 or thereafter, although they exhibited reduced influence is unknown at these study sites. growth for at least a decade prior to death. This suggests that they The largest Q. rubra that died were located at sites with high were poor competitors for resources, which allowed healthy trees densities of E. rufulus, which may be related to population growth to experience a growth release during this same time period. Tree at these sites. Borer populations transitioned from endemic to age did not apparently differ by decline status, yet smaller size of incipient in the early 1980s at these sites, at least three generations dead trees compared to live trees implies that they were also earlier than at sites sustaining lower E. rufulus densities during the suppressed individuals, unable to survive E. rufulus infestation. outbreak (Haavik and Stephen, unpublished). Several generations High infestation stands had greater species evenness, which was of populations building at these sites prior to the outbreak resulted influenced by lower Q. rubra basal area in these stands compared to in higher eruptive densities in the late 1990s and early 2000s, and less infested stands. Greater Q. rubra mortality within these stands perhaps greater larval survivorship in larger trees. during the recent borer outbreak and concurrent oak decline event Surprisingly, neither age nor physiological age was used to split likely led to observed lower Q. rubra basal area in these stands. the classification tree. Individual trees did not apparently differ in age by decline status, though age-related changes in tree Acknowledgements physiology may have been an important factor in the recent decline event. The early 20th century logging and subsequent fire Authors thank Larry Galligan, Josh Jones, Geoff Gardner, Sam suppression history of these forests was probably an important Green, Jarrett Bates, Matt McCall, and Tyler CarlLee for field and L.J. Haavik, F.M. Stephen / Forest Ecology and Management 259 (2010) 1938–1945 1945 laboratory assistance. We are grateful to Junhee Han and Andy Hay, C.J., 1974. Survival and mortality of red oak borer larvae on black, scarlet, and northern red oak in eastern Kentucky. Ann. Entomol. Soc. Am. 67, 981–986. Mauromoustakos for statistical advice, and Sharon Billings, J.M. Heitzman, E., Guldin, J.M., 2004. Impacts of oak decline on forest structure in Guldin, T.J. Kring, R.G. Luttrell, D.W. Stahle, and an anonymous Arkansas and Oklahoma: preliminary results. In: Connor, K.F. (Ed.), Proc. referee for helpful comments on the manuscript. Support for this 12th Biennial South. Silvicultural Res. Conf., Gen. Tech. Rep. SRS-71. 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