Effects of Moderate Densities of Glossy Buckthorn on Forested Plant Communities in Southwest New Hampshire, USA Author(s): Catherine Owen Koning , Rhine Singleton Source: Natural Areas Journal, 33(3):256-263. 2013. Published By: Natural Areas Association DOI: http://dx.doi.org/10.3375/043.033.0304 URL: http://www.bioone.org/doi/full/10.3375/043.033.0304
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BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions, research libraries, and research funders in the common goal of maximizing access to critical research. R E S E A R C H A R T I C L E ABSTRACT: To investigate the hypothesis that Frangula alnus, glossy buckthorn, is causing a decrease in native plant diversity in forested plant communities of southwest New Hampshire, thirty nine 20-m x 20-m plots were established in five different forest types, and all buckthorn saplings and seedlings were removed from 15 of the plots. A nested plot design was used to sample shrubs and herbs. Treatment plots were kept free of buckthorn for five years. There was a positive relationship between pre-treat- ment buckthorn density and percent openness of the forest canopy, and with basal area of white pine • (Pinus strobus), but not with soil wetness indicators. No significant changes in overall plant diversity or stem density were detected after buckthorn was removed, although stem density of woody plants, and seedlings of Acer rubrum did show significant increases in the treatment plots when compared to controls, but these effects were only seen in areas with the highest densities of buckthorn. No effects of buckthorn were observed below an average of 8.25 stems per m2. Compared to other areas of the Effects of Moderate northeastern United States, the densities of buckthorn were very low. Buckthorn seedling densities showed small increases in the control and monitoring plots, perhaps indicating a slow build-up to a Densities of Glossy “threshold” density, beyond which greater impacts on native species may be seen. Buckthorn on Index terms: forest management, Frangula alnus, glossy buckthorn, invasive species
Forested Plant INTRODUCTION bomb. Some invasive species have persisted at low levels of abundance for decades, and Invasive species can wreak economic, so- then spread aggressively over a relatively Communities in cial, and ecological havoc on scales ranging short period of time (Sandlund et al. 1999; from local to global (Mack et al. 2000). Mack et al. 2000). These ‘lag times’ are Southwest New Impacts can include decreased biomass presumed to result from low initial popula- of native species, local extinction of spe- tion density, researchers’ inability to detect Hampshire, USA cies, loss of community relationships, and the exotics, climatic shifts, addition of complete alteration of ecosystem structure atmospheric pollutants, lack of dispersers and function (Sandlund et al. 1999; Mack that can recognize and use the propagules, Catherine Owen Koning1,2 et al. 2000; Christian 2001; Ludsin and presence of predators, or lack of available Wolfe 2001; Heneghan et al. 2002). In habitat in the beginning, particularly in 1 Franklin Pierce University addition, alien species generate huge eco- areas that later become disturbed (Crooks 40 University Drive nomic costs, in terms of lost harvestable and Soule 1999). Rindge NH 03461 value, lost ecosystem services, and cost of control (Mooney 1999; Mack et al. 2000; Once an exotic species becomes estab- Jenkins 2002). This cost has been estimated lished, managers need to remove and Rhine Singleton1 at $138 billion in the United States alone control the spread of these plants. The (Mack et al. 2000). difficulty of complete eradication in many cases has led to the recent realization that While the impacts of some invasive spe- the goal may be reduction of the target • cies have been clearly documented, it is population to a “non-threatening level” common for severe negative impacts to be (Mack et al. 2000). However, a “non-threat- inferred without adequate quantification. In ening level” has yet to be defined for most a detailed review of the scientific literature invasive species. For the land manager, the in 1995, Anderson pointed out that several presence of an invasive species leads to assumptions about the impact of the inva- several questions: Is the invasive species sive purple loosestrife (Lythrum salicaria) pushing out native species; is it increasing on native species had very little scientific in abundance beyond that “non-threatening 2 Corresponding author: koningc@franklin- information to support them. Since then, level;” and will management activities be pierce.edu; 603-899-4322 a number of studies have demonstrated cost-effective? more clearly negative effects (e.g., Gaudet and Keddy 1995; Weihe and Neely 1997; This study focuses on one invasive plant Farnsworth and Ellis 2001). species, the woody shrub glossy buckthorn (Frangula alnus Mill., formerly known When an invasive plant occurs at low as Rhamnus frangula L.), in mature sec- densities but high frequencies, conserva- ond-growth forests of southwestern New Natural Areas Journal 33:256–263 tionists tend to assume the presence of Hampshire, USA. A European species, the biological equivalent of a ticking time glossy buckthorn’s original point of in-
256 Natural Areas Journal Volume 33 (3), 2013 troduction to North America has not been at lower density in most upland com- these subplots were averaged within each identified. Glossy buckthorn was reported munities, including mixed hardwood and 20-m x 20-m plot for analysis. Pre-treat- in Ontario, Canada, before 1900, where it mixed coniferous forests. The focus of this ment data were collected in June of 2003 was known to have escaped from cultiva- study is to determine whether buckthorn on percent cover and stem density for all tion. It did not spread widely beyond the has already surpassed the “non-threaten- vascular plant species, and percent cover originally reported areas until 1970. Since ing level” in these areas. Specifically, the for mosses. In the 1-m x 1-m herb plots, that time, it has become a dominant plant goals are to: (1) assess the impact of glossy only herbaceous plants and woody seed- in wetlands and in those mesic habitats buckthorn on forested plant communities, lings were considered (individuals were where it receives enough light (Catling and (2) determine if densities of buckthorn considered saplings if they were greater Porebski 1994). In the northern Allegheny in unmanaged forests are changing, and than 1 m tall or 0.5 m for short-statured Plateau riparian savanna, invasion by buck- (3) determine if management efforts can species such as Vaccinium angustifolia). thorn reduced percent cover and changed reverse the effects of buckthorn. In the shrub plots, all saplings and shrubs the dominant species composition of the were identified and counted. In the 20-m herbaceous layer (Possessky et al. 2000), x 20-m plots, all trees (≥ 10 cm dbh) were METHODS although it did not affect herbaceous spe- identified and tagged, and the diameter at cies richness overall. An undisturbed native breast height was measured (dbh = 1.3 m bog community in Wisconsin was invaded Study location, design, and data above the forest floor). by buckthorn in 1955. After those coloniz- collection ers reached maturity and began to produce Canopy photographs were used to assess fruit, about 12 years later, the glossy buck- All study areas are located on land owned overall light levels in each of the forest thorn biomass in the bog increased loga- by Franklin Pierce University in Rindge, types. A Nikon Coolpix 995 camera with a rithmically, resulting in a dense tall shrub New Hampshire (42.78oN, 72.06oW), at el- fisheye FC–E8 lens was used to photograph canopy, which competed aggressively with evations ranging from 310 – 360 m AMSL. the canopy at a height of 2 m above the native vegetation (Reinartz 1997; Reinartz A stratified random sampling design was ground in the center of each of the 5-m and Kline 1998). Other studies found that used. Forested areas were categorized by x 5-m shrub plots. A level was used to exotic shrub species such as buckthorn had former land use, based on historical records ensure that the camera was pointed verti- no greater dominance in the community, and on landscape features (stonewalls, cally. Photos were checked for blooming or effect on diversity, than native species presence/absence of barbed wire, soil mi- (excessive light making vegetation appear did (Houlahan and Findlay 2004). crotopography, presence/absence of stumps white; Leblanc et al. 2005) and re-taken indicating logging), and by dominant if necessary. Photographs were analyzed Although the U.S. Forest Service classi- tree species. In each of five forest types using the software Hemisfer to calculate fies buckthorn in its highest category for (coded A through E, Table 1), one set of canopy openness, a measure of the percent invasiveness in the Northeastern U.S. (U.S. three 20-m x 20-m plots was established area of the canopy open to sky (Schleppi Forest Service 1999), it varies in abundance in each of three different forest stands. In et al. 2007). Threshold, the cutoff light throughout the region and is not as preva- the C plots, one of the forest stands was level that is used to determine whether lent in northern New England as in areas destroyed, resulting in an n = 2 for that each pixel is considered vegetation or sky, further south (Magee and Ahles 1999). forest type. In each set, pre-treatment data was determined automatically by Hemisfer Nevertheless, in white pine (Pinus strobus) were collected on buckthorn density; the using the procedure of Nobis and Hunziker dominated forests of southeastern New plot with less than 5 stems of buckthorn (2005). Hampshire, Frappier et al. (2003) reported (0.03 stems per m2) became the monitoring that woody seedling density, herb cover, plot, the purpose of which was to determine Soil moisture in each plot was evaluated and species richness were all negatively whether buckthorn density was changing indirectly using a wet soil metric based correlated with buckthorn density. In ad- (the D forest had no areas of low buck- on a system of wetland plant indicators dition, experimental removal of buckthorn thorn density, so no monitoring plots were developed by the U.S. Fish and Wildlife resulted in an increase in first year tree established). The monitoring plots had no Service (USFWS 1996). In this system, seedling density suggesting that buckthorn apparent differences from the other areas, used reliably across the U.S. in delineating does have a negative effect on native forest and did not stand out in the subsequent jurisdictional wetlands, each plant species plant species (Frappier et al. 2004). ordination analyses. Of the two remaining has been assigned a region-specific indica- plots, one plot was randomly chosen to be tor status based on its affinity to wetlands: In the forests of southwestern New Hamp- the treatment plot (all buckthorn removed), obligate species are those that are found shire, buckthorn is one of very few invasive and one was chosen to be the control plot. in wetlands 99% of the time (in the wet- plant species (New Hampshire Dept. of A nested plot design was used, with five test of the wetlands), facultative-wetland Resources and Economic Development 5-m x 5-m shrub plots located within species are found in wetlands 67% – 98% 2011). Although it reaches its highest den- each quadrant and center of each 20-m of the time, facultative species are those sity in wet or highly disturbed areas (e.g., x 20-m plot, and 1-m x 1-m herb layer that are found in wetlands 33% – 66% of Houlahan and Findlay 2004), it is present plots within each shrub plot. Data from the time, facultative-upland species are
Volume 33 (3), 2013 Natural Areas Journal 257 Table 1. Characteristics of forest communities sampled. 1 = Three of the initial nine plots in the C forest type were destroyed for development in 2004 so were omitted; 2 = D plots had no monitoring plots.
'! ' ' ' 3 ' % ' ' 3 0 0 ' # $# +'' ' ' 77 6 7 7 +''64'$''64'$'# ' 77 7 6 7 # ,'' ,' , , 0 ' # # # # ! ' '. #' 3$6/ $ 2 $ 2 $ 2 $ 2 $ 2 '2 562** 54295 52666277 542)5 8295 752)5 55298 &2&5 552&6 2 )278 &284 5727&(2)& 552(5 8265 )258 62(7 92&8 92)6 2 4255 4277 42440 52(& 527( 4244 0 67249 &24* .2/' 1 4268 428( 42*(524( 562(( &2&) 4244 0 4285 42(8 2 424* 426) 42444244 525) 52)8 (28& 72(6 4244 0 '2 62&& 628* 626462&7 4244 4244 4244 0 4244 0 2 5258 52*7 726772&8 4244 4244 4244 0 4244 0 4276 42)* 62))82)& 4244 4244 4244 0 4244 0 '2 424( 4258 42*5528) 5248 5274 4298 5265 4244 0 2 52&6 625( 4266428) 4276 42(* 4277 42(9 4244 0 .2/' ##2 4244 0 4268427* 42(* 42&8 4244 0 5264 6256 2 42(4 5267 42965244 4244 4244 4244 0 4244 0 ' 2 424) 4269 42((529) 4249 4257 4249 4256 4244 0 42440427)0 424404255042590 ! # 6)27& 6&2)) 84287 8)288 7(24& ! #' ' ' '$6 )2)9 55264 5)2695(267 54247 56259 6)2() 5&2(5 97297 6(287 ' 927& 62(4 928452*) )287 729& )2&4 6268 54286 725* ' 42*7 4294 42(4428( 5266 428) 42*7 4289 42(( 428* -'' )2(& 428& )2**42&4 542&) 429* 542)7 42(9 5425( 42(5 '# ' 0 $ '"0 ' # ' ' '$6 42(* 527( 42484249 425& 427( (247 72(6 42&) 42&4 '# ' 0 $ '"0' ' # ' ' '$6 425* 4286 42454247 4248 4256 5266 42)7 424* 4'25& found in wetlands 2% – 32% of the time, to obtain the wetness indicator metric for were “weeded” to keep the buckthorn out and upland species are found in wetlands each plot. in 2005 and 2006. In 2008, data were col- only 1% of the time. Each species found lected in all plots using the same methods in the plot was assigned a wetland indica- After data collection, all buckthorn trees, described earlier. tor status from 1–5 (1 = obligate wetland saplings, and seedlings were removed from Data analysis species, 5 = upland species); this number the 20-m x 20-m treatment plots. Smaller was weighted by the proportion of the individuals were removed by hand. Most Non metric multidimensional scaling total percent cover for that species. Each were cut and a 50.2% solution of glypho- (NMS) was used to ordinate the rela- species’ weighted wetland indicator status sate (Roundup brand) was applied imme- tive stem density data for the 39 plots, numbers were then averaged for each plot diately to the cut stump. Treatment plots averaging the subplot data first, using the
258 Natural Areas Journal Volume 33 (3), 2013 program PC–ORD (McCune and Medford clubmosses). Microsoft Excel and PASW with the highest correlations with axis 1 1999), and following the recommenda- statistics Ver. 13 (SPSS 2009) were used were white pine trees (r2 = 0.603), buck- tions in McCune and Grace (2002). The for the statistical analyses. thorn saplings (r2 = .576), and with axis distance measure used was Sorensen, with 2 black birch (Betula lenta) saplings ( r2 = a random starting configuration, 10 runs .424) and hay-scented fern (Dennstaedia RESULTS 2 with real data, 200 iterations, choosing a punctilobula) (r = .361), and for axis 3, 3-dimensional solution with final stability the goldthread (Coptis trifolia) and spruce A total of 101 vascular plant species were of 0.00042, and final stress of 10.09 for the (Picea) trees showed the highest correla- found in the herb plots and 29 woody shrub tions (r2 = 0.583 and 0.484). ordination of 2003 data. The hypothesis that or sapling species in the shrub plots. The communities with more light availability NMS ordination of plots into species space and wetter conditions will have greater for the before-treatment data is shown Factors Influencing Buckthorn buckthorn density was tested using linear in Figure 1. Axes 1, 2, and 3 explained Abundance regression and multiple regression models 39.3%, 16.9%, and 34.0% of the variation and with environmental variable overlays respectively, for a cumulative of 90.3% Pre-treatment buckthorn seedling density using NMS. of the variation. The two environmental in the herb plots was significantly differ- parameters, wetland indicator status and ent among the five forest types (df = 4, F Differences in pre-treatment buckthorn percent canopy openness, showed the = 22.67, p < 0.001); the white pine forest density, and differences in change in buck- strongest correlation with Axis 3 (r2 = 0.232 D plots had the highest density, and were thorn stem density among different forest and 0.407 respectively). This ordination significantly different from all the other types and between treatment types in the shows a fairly clear separation among the forest types (p < 0.001). Buckthorn was herb and shrub plots, were tested using five forest types, except for some overlap significantly more abundant in plots with ANOVA with Bon Ferroni post-hoc testing. between the C plots (mixed conifer forest higher light levels as measured by canopy In addition, linear regression was used to on former pasture) and the D plots (white openness. Figure 2 shows that buckthorn test for a possible relationship between pine forest on former pasture). The species density from the 5-m x 5-m sample plots buckthorn density and basal area of white pine, and between buckthorn density and canopy openness and wetland indicator metric. All stem density data were log10 transformed to approach normal distribu- tions (Zar 1999); data distributions were checked for each transformation. Percent cover data were transformed using the arcsine transformation.
A repeated measures ANOVA was used to test for the effect of buckthorn removal on herb diversity (based on the Shan- non-Wiener index) and on herb species richness, total herb stem density, and total percent herb cover. To test for treatment effects on individual species in each forest type, the change in stem density in each herb plot or shrub plot was calculated by subtracting stem density before treatment (2003) from stem density after treatment (2008). The change in stem density in the control plots was then compared to the treatment plots in each forest type using a t-test. Only species that had a frequency of 10% or more across all herb or shrub plots in each forest type were tested, and only plots which had the species either before or after treatment were used. Percent Figure 1. NMS ordination of plots in species space. A = mixed pine/hardwoods on formerly cultivated cover data were treated similarly to stem land; B = mixed hardwoods on former pasture; C = conifers on former pasture; D = white pine on for- density but were only analyzed for species mer pasture; E = Spruce wetland on formerly logged areas. LT_TRA = Light transmission; WETIND with no stem counts (e.g., mosses and = Wetness indicators.
Volume 33 (3), 2013 Natural Areas Journal 259 averaged across the 20-m x 20-m plots was greater when the canopy was more open (df = 38, p = 0.0043, r2 = 0.20). This increase in buckthorn density with light was also true for the 1-m x 1-m herb plots averaged across the 20-m x 20-m plots (df = 38, p = 0.0056, r2 = 0.19).
There was no significant relationship between buckthorn stem density and soil wetness indicators (df = 38, p-value = 0.68, r2 = 0.0047). A multiple regression of buckthorn density vs. canopy openness and wetness indicator species was consis- tent with the results from the individual simple regression analyses (df = 38, p = 0.0069, r2 = 0.24, p light = 0.0019, p wetind = 0.172).
A regression of average buckthorn Figure 3. Buckthorn density (number of seedlings and saplings per meter squared) as a function of density in the 20-m x 20-m plots vs. white pine basal area. Density is averaged across the five 5-m x 5-m shrub plots nested within the 20-m total basal area of white pine revealed a x 20-m plots. significant positive relationship between these two variables (Figure 3, df = 38, p 0.66, r2 = 0.0053) or species richness (df Effects of buckthorn removal = 1.28x10-7, r2 = 0.534). = 38, p = 0.73, r2 = 0.0033). There also was no significant relationship between After treatment, buckthorn seedling density Regression analysis showed that pre-treat- pre-treatment buckthorn stem density in the in the herb plots increased in the control ment buckthorn density (seedlings plus herb plots and total stem density per m2 (df plots by a mean of 0.26 stems per m2 saplings averaged across the 1-m2 herb = 38, p = 0.46, r2 = 0.015), woody stem (s.d. = 0.83) over the 5-year study period, plots within the 20-m x 20-m plots) was density (df = 38, p = 0.81, r2 = 0.0015), averaged over all forest types, and in the not significantly related to the Shannon- or herb stem density (df = 38, p = 0.45, monitoring plots by 0.29 stems per m2 (s.d. Wiener diversity index (H) (df = 38 p = r2 = 0.016). = 1.04), but decreased in the treatment plots, as expected, by an average of 2.51 stems per m2 (s.d. = 5.88). A paired t-test showed no significant difference between the pre- and post-treatment stem densities in the control and monitoring plots; but, not surprisingly, there was a significant difference in the treatment plots (df = 13, p < 0.05). Buckthorn sapling density in the 5-m x 5-m plots also did not change significantly in either the control or monitoring plots, but did decrease in the treatment plots, again as expected as the result of the removal.
A repeated measures ANOVA comparing all treated herb plots to control herb plots found no significant treatment effect of buckthorn removal on the total number of non-buckthorn stems (df = 1, F = 0.048, p = 0.828), plot richness (df = 1, F = 0.491, p = 0.485), and Shannon-Wiener Diversity (df = 1, F = 0.499, p = 0.481). Time and Figure 2. Buckthorn density (number of saplings and seedlings per meter squared) as a function of % forest type did have a significant effect on canopy openness in the 5-m x 5-m shrub plots. Density is averaged across the five 5-m x 5-m shrub plots all three variables (p < 0.001). nested within the 20-m x 20-m plots.
260 Natural Areas Journal Volume 33 (3), 2013 Eighteen individual native species in each white pine D forest. The results of this buckthorn shrubs were associated with forest type occurred frequently enough study support those reported by Frappier greater basal area of shade tolerant trees in the 1-m x 1-m herb plots for statisti- et al. (2004), who found that buckthorn and lower light levels than live buckthorn cal testing. Significant differences were was having a strong suppressive effect on shrubs. Sanford et al. (2003) also found that found only in the white pine forests (D the first-year seedlings of several native glossy buckthorn exhibited low survival in forests), which had the highest buckthorn trees, including Acer rubrum, Fraxinus the forest understory. In our study, when stem density (Table 2). Red maple (Acer americana, Pinus strobus, and Quercus all forest types were considered together, rubrum) increased in the treatment plots, rubra. However, they did not detect any buckthorn density in the control and moni- but decreased in the control plots. All effects on other species, despite the fact toring plots did not show any statistically woody species together also showed a that their studies were conducted only significant change. significant difference in the treatments vs. in white pine forests with 90% or more the control plots in the D forest, with the buckthorn cover. The buckthorn density We did observe natural mortality of buck- control plots showing an average decrease in this study is much lower, leading us to thorn saplings in some of our A plots of 10.27 stems per plot from 2003 to 2008, suggest that the buckthorn densities we where light gaps were filling in, which is while the controls only showed an average experienced in the A, B, C, and E forests consistent with Cunard and Lee’s (2009) decrease of 1.93 woody stems per plot. conclusion that “patience is a virtue,” be- are still below the “non-threatening” level. cause buckthorn density declines as forest Thus we can posit that the “threshold” Red maple, hazelnut (Corylus cornuta), succession proceeds. Future study in the or “non-threatening” level of buckthorn balsam fir (Abies balsamea), and white pine monitoring and control plots will determine were the only species occurring frequently is higher than 1.5 seedlings and saplings 2 whether buckthorn density is increasing or enough as saplings in the 5-m x 5-m plots stems per m (the highest average density decreasing as forests mature. to be tested for an effect of buckthorn in the A, B, C, and E forests), but less than 2 removal. For these species, the change 8.25 stems per m (the density in the white While it remains to be seen whether pa- in stem density from 2003 to 2008 in the pine D forests). tience is a virtue, or if we are sitting on treatment plots was not significantly differ- a ticking time bomb, it is easy to remove ent than the change in the control plots. In Sanders (1993) also found that pine forests occasional stems of buckthorn, so our addition, the change in total sapling density with lower overstory density had higher advice to our own land managers is to across all species was not different in the glossy buckthorn densities. In her study, err on the side of caution and remove the a marked increase in glossy buckthorn treatment than in the control plots. buckthorn in the less invaded forests before seemed to be the result of the presence it becomes a problem. of many fruiting-aged individuals at the DISCUSSION time of self-pruning of the 30 – 45 year old overstory pines; presumably the loss ACKNOWLEDGMENT Glossy buckthorn frequently invades in of the lower pine branches with age al- disturbed and wet areas (e.g., Reinartz lowed greater light levels required for the This research was supported by Faculty 1997; Reinartz and Kline 1998), but seeds to germinate. She also found that Research Funds from Franklin Pierce Uni- relatively little is known about its role in buckthorn seed production was lowest versity. The authors thank their many field second-growth forests that have not been in the smallest height class, while 89% assistants, including Virgil Wetmore, Tracy recently altered. In this study, the white – 100% of the plants in the medium and Gora, Catrina Capucci, Eric Feldbaum, Tim pine forest on formerly pastured land had tall height classes produced seeds. Sanders Foley, Jerry Breault, and Neel Patel. the highest density of buckthorn stems, (1993) also speculated that the preference while the mixed hardwood, later succes- of birds to use pines as a roosting site may sional forests on former pasture, had the explain the increased frequency of glossy Catherine Owen Koning is a wetland lowest. Canopy openness was positively buckthorn in pine stands relative to the scientist and Professor of Environmental correlated with buckthorn density and mixed deciduous stands. Science at Franklin Pierce University. may be a significant factor in determining which areas were the most invaded, while In this part of New England, white pine Rhine Singleton is a forest ecologist and soil wetness indicators were not. forests usually succeed into mixed hard- Associate Professor of Environmental wood forest communities, such as the B Science and Biology at Franklin Pierce In this study, buckthorn affected only one forest type in this study. In these mature University. individual species, and only in the white second-growth forests, an important factor LITERATURE CITED pine forest on former pasture (D forest), to consider is the possibility that buckthorn is competitively excluded as succession which had the highest densities of buck- Anderson, M.G. 1995. Interactions between thorn. However, buckthorn removal had proceeds. In mid-successional secondary Lythrum salicaria and native organisms: a a significant positive effect on all woody forests in southeastern New Hampshire, critical review. Environmental Management species, considered collectively, in the Cunard and Lee (2009) found that dead 19:225-231.
Volume 33 (3), 2013 Natural Areas Journal 261 Table 2. Changes in number of stems in each herb plot (change in stems = #stems in 2008 - #stems in 2003). * = significant difference between control and treatment plots at p < 0.05, ** = significant at p < 0.01. ID = Insufficient data (not enough occurrences of that species in that forest type; a minimum of 14 herb plots was required). 1 = seedlings only; 2 = percent cover; 3 = not including Frangula alnus.
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262 Natural Areas Journal Volume 33 (3), 2013 Catling, P.M., and S.Z. Porebski. 1994. The land plant diversity. Conservation Biology frangula L.: a threat to riparian plant com- history of invasion and current status of 18:1132-1138. munities of the northern Allegheny plateau. glossy buckthorn, Rhamnus frangula, in Jenkins, P.T. 2002. Paying for protection from Natural Areas Journal 20:290-292. southern Ontario. Canadian Field Naturalist invasive species. Issues in Science and Reinartz, J.A. 1997. Controlling glossy buck- 108:305-310. Technology 19:67-72. thorn (Rhamnus frangula L.) with winter herbicide treatments of cut stumps. Natural Christian, C.E. 2001. Consequences of a bio- Leblanc, S.G., J.M. Chen, R. Fernandes, D.W. Areas Journal 17:38-41. logical invasion reveal the importance of Deering, and A. Conley. 2005. Methodology mutualism for plant communities. Nature comparison for canopy structure parameters Reinartz, J.A., and J. Kline. 1998. Glossy 413:635-639. extraction from digital hemispherical pho- buckthorn (Rhamnus frangula), a threat to Crooks, J.A., and M.E. Soulé. 1999. Lag times tography in boreal forests. Agricultural and the vegetation of the Cedarburg Bog. Field Station Bulletin, The University of Wiscon- in population explosions of invasive spe- Forest Meteorology 129:187-207. sin – Milwaukee 21:20-35. cies: causes and implications. Pp. 103-125 Ludsin, S.A., and A.D. Wolfe. 2001. Biologi- Sanders, L. 1993. The “Kudzu” of the northeast: in O.T. Sandlund, P.J. Schei and A. Viken, cal invasion theory: Darwin’s contributions eds., Invasive Species and Biodiversity Rhamnus frangula (glossy buckthorn): its from the Origin of Species. Bioscience range history, phytophagous insects, and Management. Based on a selection of papers 51:780-790. presented at the Norway/UN Conference on invasion patterns and processes in selected pine forests in Massachusetts. M.S. thesis, Alien species, Trondheim, Norway. Popula- Mack, R.N., D. Simberloff, W.M. Lonsdale, University of Vermont, Burlington. tion and Community Biology Series, v. 24, H. Evans, M. Clout, and F. Bazzazz. 2000. Kluwer Academic Publishers, Dordrecht, Biotic invasions: causes, epidemiology, Sandlund, O.T., P.J. Schei, and Å. Viken (eds.) The Netherlands. global consequences and control. Ecological 1999. Invasive Species and Biodiversity Applications 10:689-710. Management. Kluwer Academic Publishers, Cunard, C., and T.D. Lee. 2009. Is patience a The Netherlands. virtue? Succession, light, and the death of Magee, D.W., and H.E. Ahles. 1999. Flora of the invasive glossy buckthorn (Frangula alnus). Northeast: a manual of vascular flora of New Sanford, N., R. Harrington, and J. Fownes. Survival and growth of native and alien Biological Invasions 11:577-586. England and adjacent New York. University of Massachusetts Press, Amherst. woody seedlings in open and understory Farnsworth, E.J., and D.R. Ellis. 2001. Is purple McCune, B, and Grace, J. 2002. Analysis of environments. Forest Ecology and Manage- loosestrife (Lythrum salicaria) an invasive ment 13:377-385. threat to freshwater wetlands? Conflicting Ecological Communities. MJM Software, Gleneden, Ore. Schleppi, P., M. Conedera, I. Sedivy, and A. evidence from several ecological metrics. Thimonier. 2007. Correcting non-linearity Wetlands 21:199-209. McCune, B,. and M.J. Mefford. 1999. PC–ORD. and slope effects in the estimation of the Frappier, B., R.T., Eckert, and T.D. Lee. 2003. Multivariate analysis of ecological data, leaf area index of forests from hemispherical Potential impacts of the invasive exotic shrub version 4. MjM Software Design, Gleneden, photographs. [SPSS] Statistical Package for Rhamnus frangula (Glossy Buckthorn) on Ore. the Social Sciences. 2009. PASW statistics forests of Southern New Hampshire. North- Mooney, H.A. 1999. A global strategy for deal- Ver. 13. IBM Corp., Chicago. eastern Naturalist 10:277-296. ing with alien invasive species. Pp. 497-518 U.S. Forest Service. 1999. Eastern Region inva- in Frappier, B., R.T. Eckert, and T.D. Lee. 2004. O.T. Sandlund, P.J. Schei, and Å. Viken, sive plants, ranked by degree of invasiveness Experimental removal of the non-indig- eds. Invasive Species and Biodiversity as based on information from States. U.S. Management. Kluwer Academic Publishers, enous shrub Rhamnus franglual (Glossy Department of Agriculture, Forest Service. The Netherlands. Available online
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