High-Elevation Rock Outcrop Vegetation of the Southern Appalachian Mountains
Author(s): Susan K. Wiser, Robert K. Peet, Peter S. White
Source: Journal of Vegetation Science, Vol. 7, No. 5 (Oct., 1996), pp. 703-722
Published by: Blackwell Publishing
Stable URL: http://www.jstor.org/stable/3236382
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Journal of VegetationScience 7: 703-722, 1996
? IAVS;OpulusPress Uppsala. Printed in Sweden
703
High-elevation rock outcrop vegetation of the
Southern Appalachian Mountains
Wiser, Susan K.12, Peet, Robert K1. & White, Peter S.1
Department of Biology, CB #3280, University of North Carolina, Chapel Hill, NC 27599-3280, USA;
2Presentaddress: LandcareResearch,P.O. Box 69, Lincoln,New Zealand;Fax + 64 3 325 2418.
Abstract. Species compositionpatternsand vegetation-environmentrelationshipswere quantifiedfor high-elevationrock
outcrops of the SouthernAppalachianMountains,an infrequent and insular habitat in a forested landscape. Outcrops
occur over a wide geographicrange encompassingextensive
variationin both geology and climate. Geographic-scalefactors interact with site-scale factors to produce variation in
vegetationamongoutcrops.Similarly,site-scale factorsinteract with micro-scalefactorsto producevariationin vegetation
within outcrops.To provide a quantitatively-basedclassification of outcropvegetationwe used a TWINSPANanalysis of
154 100-m2plots. We recognized nine communitiesthat primarily correspond to different combinations of elevation,
bedrocktype, geography,and moisture.Withinoutcropsof a
single bedrocktype, vegetation composition of 100-m2plots
was consistentlycorrelatedwith elevation and solarradiation,
but relationshipsto soil nutrientsvaried with bedrock type.
Both site-scale (100 m2)factors (e.g. elevation, slope, aspect,
andbedrocktype) andplot-scale ( 1-m2)micrositefactors(e.g.
soil depth, vegetation height, soil nutrients) were strongly
correlatedwith species composition at the 1-m2level. Environmentcan be used to predictcompositionmore effectively
for 100-m2plots on a single bedrock type than either across
bedrock types or at a 1-m2 scale. Composition-environment
relationshipsresemble those described for outcrop systems
from otherregions with pronouncedtopographicrelief more
than they do those described for the nearby but flatter and
lower-elevationoutcropsof the SoutheasternPiedmont.There
is strong spatial autocorrelationin this community,perhaps
owing to dispersallimitation.Consequently,a comprehensive
conservationstrategymust includereservationof both a range
of geologic types and a range of geographiclocations.
Keywords: CorrespondenceAnalysis; Disjunct distribution;
Endemic species; Insularhabitat;Partialordination.
Nomenclature: Kartesz 1994, except for the recognition of
Houstonia longifolia var. glabra Terrell.
Introduction
Rock outcrop vegetation in predominantly forested
landscapes is generally insular and of infrequent occur-
rence. As a consequence, outcrop communities are of
interest both because they harbor rare species and community types, and because they serve as a model system
for study of patterns and processes in insular communities. The species composition of outcrop communities,
like that of all vegetation, is influenced by multiple
environmental factors that vary at differing spatial scales.
Consequently, the influence of locally variable factors
like aspect, slope, and elevation may be obscured by
geographic-scale variation in geology and climate. Similarly, consistent relationships between small-scale compositional variation and microenvironment may be obscured by site-scale and geographic variation in environment. Consequently, attempts to generalize about
vegetation-environment relations on outcrops require
attention to sampling scale (see Larson et al. 1989).
Inconsistencies among the patterns previously described
for outcrop vegetation (e.g. the importance of soil depth
vs. geology vs. topography) may result from inconsistencies in sampling scale (cf. 1-m2 plots of Maycock &
Fahselt 1992 vs. 25-m2 plots of Burgman 1987 and 100300-m2 releves of Makirinta 1985) and the range of
environmental variation (particularly of bedrock types)
examined (cf. Ashton & Webb 1977 and Maycock &
Fahselt 1992 vs. Sharitz & McCormick 1973; Collins et
al. 1989).
Within the Southern Appalachian landscape, highelevation (> 1200 m a.s.l.) rock outcrops are uncommon,
spatially isolated from each other, and possessed of one of
the richest floras of rare species of any habitat in the
region. These rare species, which include numerous
endemics as well as disjuncts from far to the north,
indicate that the outcrop vegetation may harborremnants
of a now largely vanished Pleistocene alpine flora
(Ramseur 1960; White et al. 1984; Billings 1988). Their
limited extent, limited economic importance, and frequent inaccessibility has resulted in these outcrops being
little studied in contrast to other vegetation in the region.
This paper describes the vegetation of Southern Appalachian high-elevation outcrops and how composition varies with environment and geography. These
relationships are examined at several spatial scales to
Wiser, S.K. et al.
704
KV j
TN(/I
VA
NC
SC
GA
Fig. 1. Mapof studyareashowingplotlocations(smallsquares),majorpeaksandbedrocktypes.
address the following questions. (1) Do vegetationenvironmentrelationshipsvary with scale of observation? (2) Do vegetation-environmentrelationshipsvary
with the geographicextentof the areaconsidered,andif
so, what environmentalfactors are importantwhen
vegetation is studied over large areas? (3) To what
extent are vegetation-environmentcorrelationsconsistent across bedrocktypes and across the region? (4) To
what extent are these observed correlations consistent
with those observed in outcropvegetation studiedoutside the region?
Study area
This study includes SouthernAppalachianhigh-elevation outcrops> 100 m2in areaand > 1200 m a.s.l. in
the high peaks region of western North Carolinaand
eastern Tennessee, (between 35? and 37? N; Fig. 1).
Sites > 1200 m are thoughtto have been near or above
treeline during the last glacial maximum (Delcourt &
Delcourt 1985, 1988). Except for Mt. Rogers peaks >
1200m do not occurNorthof the Virginia-NorthCaro-
lina stateline. The absenceof high peaks and associated
Pleistocene alpine vegetation causes a naturalbiogeographicboundary.
The regional terrainconsists of typically rounded,
forested summits; more rarely peaks have a rugged
relief with rock outcrops present (Fenneman 1938).
High-elevation outcrops occur on rocks that range in
compositionfrom felsics like granite,gneiss and schist
to mafics like gabbro and amphibolite, all largely of
Precambrianorigin (Table 1). Mafic rocks have higher
iron and magnesiumcontentand lower aluminumcontent thando felsic rocks, and generallyweatherto more
fertilesoils. Maficrocksaremostfrequentin thenorthern
partof the study area.Rock outcropsoils are generally
lumpedin the USDA classificationas Entisols or Lithic
Haplumbrepts(Brady 1984).
Few meteorologicalstationsoccuron the highpeaks,
but available data suggest that mean annualprecipitationrangesfrom 1270to 2000 mm (Shanks1954;Ruffner
1985), generally increasing with elevation. Most
precipitationcomes from southwesterlywinds, resulting in a southwest to northeastgradientof decreasing
precipitation(Dickson 1959). Precipitationis season-
- High-elevation rock outcrop vegetation -
Data collection
Table 1. Summary of bedrock types in the study area.
Bedrock type
Mafic
Amphibolite
Metagabbro
Metabasalt
Intermediate
Meta-arkose
Felsic
Quartzite
Metagraywacke
Geographicarea
No. plots
ThreeTop Mt., Bluff Mt.,
Phoenix Mt., PotatoHill
Roan Mt. Massif
HangingRock
28
13
3
GrandfatherMt., Linville Gorge
(HawksbillMt.)
26
Linville Gorge (TableRock)
GreatCraggyMts.,
Black Mts.
Balsam Mts.
Muscovite-biotitegneiss
Anakeestasulfitic slate
GreatSmoky Mts.
Sandstoneand conglomerate GreatSmoky Mts.
Whiteside quartz-diorite
Vicinity of Highlands,
North Carolina
705
1
27
9
16
1
30
ally bimodal with peaks in mid-summerand mid-winter, anda low in the autumn.MeanJulytemperaturesare
cool for the region (17 ?C at 1618 m and 15 ?C at
1991 m). Frostsoccurfromlate Septemberto mid May.
On GrandfatherMountain, one of the region's most
exposed peaks, mean wind speed rangesfrom 18.5 km/
hr in the summerto 33 km/hrin December,with gusts to
270 km/hrrecorded(dataprovidedby GrandfatherMt,
Inc.).
Althoughthe highest peaks of the SouthernAppalachians arenow forestedto theirsummits,it is likely that
climatic treeline occurrednear 1450 m during the full
glacial (ca. 18000 B.P.; Delcourt & Delcourt 1985,
1988). On exposed, windy peaks the treelineis usually
lower so the 1200 m sampling cutoff roughly matches
the lower distributionallimit of the putativePleistocene
alpine relicts. As climates warmed, treeline and true
alpine vegetationmoved upward,but likely persistedin
the region until ca. 12 500 B.P. (Delcourt & Delcourt
1985, 1988).
Despite the long absenceof a climatictreeline,highelevation outcrops support plant species with strong
alpine and arcticaffinities (Wiser 1994), such as Geum
radiatum,Juncus trifidusand Sibbaldiopsistridentata.
Much of the rest of the outcropflora is adaptedto open,
treeless habitatsthathave abundantsunlight(cf. Baskin
& Baskin 1988; Wiser 1994). Vegetation surrounding
high-elevationoutcropsincludesPicea-Abiesforestand
grassy balds at the highest elevations (> 1550 m), with
northernhardwoodforest (dominatedby Fagus grandifolia andBetula alleghaniensis) or oak forest (Quercus
rubra and Q. prinus) at the lower elevations (1200 1800 m). Heath-dominatedshrublandsoccur as surroundingvegetation over a broadrange of elevations.
Study sites were located on 42 peaks in 11 localities
(Fig. 1) selected to maximize the numberof combinations of rock type, elevation, aspect, longitude, and
latitudesampled.Potentialsites were identifiedby visual
reconnaissance,searchesof publishedand unpublished
literature,aereal photographs,topographicmaps, and
personalrecommendations.Outcropswere requiredto
haveherbaceousplantspecies as a prominentcomponent
of the vegetation,> 5 % of the areaas exposed bedrock,
and> 75 %of the areawith bedrockwithin 20 cm of the
surface.Sites rangedfrom large,rocky ridges and clifffaces with little forest in view and minimal shading,to
protectedsites atcliff bases or seepageslopes surrounded
by forest and at least partially shaded. Grassy balds,
severelytrampledoutcrops,andsites requiringtechnical
climbing equipmentwere excluded from this study.
Plots of 10 m x 10 m (100-m2) were sampled for
comparisonsbetween outcrops and between localities
on a given outcrop,whereas 1 mx 1 m (1 m2) subplots
were sampled to examine microhabitatswithin outcrops. The largerplot was visually stratifiedinto types
according to vegetation height and dominant growth
form (i.e. woody, graminoid,forb), and 1-2 1-m2subplots were randomlyplaced within each type. Two to
seven 1-m2subplotswere sampledwithin each 100-m2
plot, depending on vegetation heterogeneity. At both
plot and subplotlevels, all vascularplant species were
recordedand cover estimates made by SKW using the
ten-class cover scale of Peet et al. (1990): 1 =<0.1 %; 2
=0.1-1%; 3=> 1-2%; 4=>2-5%; 5=>5- 10%;6=>
10-25 %;7 = >25-50%; 8=>50-75 %;9=>75-95 %;
10 = > 95 - 100 %). This scale was designed to allow
accurateestimationto within one class and to be interconvertiblewith other commonly used cover scales. A
total of 154 100-m2plots and 596 1-m2 subplots were
sampled. Voucher specimens have been deposited at
NCU. Plot data are availableupon request.
Site parametersmeasuredon 100-m2plots
Near the centerof each 100-m2plot, latitude,longitude, elevation, slope and aspect were determined.Topographicposition was recordedas an index from 1 to
10 with 1 being the outcrop base and 10 being the
outcrop summit. Percent exposed bedrock was estimated visually. Outcropswere categorized by vertical
relief (1 = < 5 m high; 2 = 5-16 m; 3 = 16-32 m; 4 = 32
- 64 m; 5 = > 64 m). A three-pointrock surfacefracturing
index was definedrangingfromnearlysmoothoutcrops
with ledges and cracks < 0.3 m wide designated ' ', to
highly fracturedand angularoutcropswith ledges and
cracks > 0.3 m wide designated '3'. Horizontal and
706
Wiser, S.K. et al.
vertical distance to the nearest landformor vegetation
higher than the plot were estimated in four directions
fromthe plot center(towards,opposite andperpendicularto the directionof maximumexposure).Surrounding
vegetationwas classifiedfollowing Schafale& Weakley
(1990) as Picea-AbiesForest,NorthernHardwoodsForest, HeathBald, GrassyBald, High-ElevationRed Oak
Forest,ChestnutOak Forest, or Pine-OakHeath.
Samples of dominantrock types were collected on
each plot, and identified by Charles Troop, Dept. of
Geology, University of North Carolinaat Chapel Hill.
Plots were then classed as mafic, felsic, or intermediate
(intermediateincluded felsic outcrops with frequent
veins or small intrusionsof mafic rock).
Outcrop area was classified from measurements
on orthophotoquadranglemaps as: 1 = not visible; 2 =
visible and < 0.25 ha; 3 = 0.25-1.0 ha; 4 = 1-9 ha;
5 = 9-25 ha, 6 = > 25 ha.
Site parametersmeasuredon I -m2subplots
Percent slope, topographicposition index, distance
and height to protecting landformsor vegetation, and
maximumvegetationheightwere determinedforeach 1m2 subplot.Average soil depthwas calculatedbased on
16 measurementstaken on a grid within each subplot
using a graduatedsteel pin. Percent sky obstructedby
rock ledges or vegetation was measuredusing a spherical densiometer (Lemmon 1956). Percent cover of
lichens, mosses, rock andbaresoil were estimatedvisually. Potential water sources were recorded(perennial
seepage,driporrunofffromabove, directprecipitation).
In each subplot,soil sampleswere collectedfromthe
top 10 cm of soil below the litter layer. Soils were airdried,sieved and analyzedfor pH, percentorganicmatter and available potassium, calcium, magnesium,
phosphorus,sulfate, sodium, copper,boron,iron, manganese, aluminum, and zinc (Mehlich 3 extractant,
Mehlich 1984; BrooksideLaboratoryAssociation,Inc.,
New Knoxville, OH). Percentorganicmatterwas determined by loss-on-ignition,andmoistureholdingcapacity as waterheld in fully saturatedsoil as a percentof dry
weight. Soil parametervalues were averaged across
component 1-m2 subplots to provide a representative
value for each 100-m2plot.
Data analysis
Calculatedsite parametersand indices
PrincipalComponentsAnalysis (PCA) on plot longitude and latitude was used to determine relative
position on the long (NE - SW) axis of the mountains,
andrelativepositionon the shorter(SE - NW) axis of the
mountains.
Potentialsolarbeamirradiationwas calculatedbased
on slope, aspect and latitude (Frank& Lee 1966). Aspect was transformedinto a linearvariable(Beers et al.
1966) where the optimal aspect for growth of a given
species or vegetation type (Amax) was assigned the maxi-
mum value of 2.00, and the opposite direction was
assigned a value of 0.00. Aspects were calculatedas
A' = cos(Amax -A)+1,
(1)
whereA is the measuredaspect in degrees andA' is the
transformedaspectcode. A procedureanalogousto that
of Dargie et al. (1987) was used to determinethe optimal Amax(=10?) with subsequent increments 20, 5, and
1 tested to find the best fit to a Canonical Correspondence Analysis constrainedto be the maximumfit to the
transformedaspect (cf. Reed et al. 1993).
Two exposureindices were calculatedfor each plot
andsubplot.Thefirstis a modificationof thatof Callaway
et al. (1987):
protection = 0.25
((ER - EP)/D)
(2)
whereER = elevation of structureshigherthanthe plot;
EP = plot elevation;D = distancefromplot to the higher
structure,averagedover observationsmade at four 90?
intervals with one being in the direction of the plot's
maximumdownwardslope. If the plot was locatedon a
rockface whose slope extended above the plot, that
rockface was assumedto protectthe plot on its surface
from exposure in thatdirection.
Because exposureis not linearlyrelatedto the height
and distance of protecting structures,we calculated a
second index (P. Robinson, UNC Geography Dept.,
pers. comm.). Exposurein each of the four 90? intervals
examined was defined as '1' (totally protected)when
the height of neighboringlandformsor vegetation was
greater than 10 times the distance to the plot, as '5'
(totally exposed) when their height was less than 0.1
times the distance to the plot, or '3' when they were
intermediatein height relative to distance to the plot.
Scores were averagedto producea plot exposureindex
rangingfrom 1 (fully protected)to 5 (fully exposed).
To satisfy normalityassumptionsof some statistical
analyses, water holding capacity, manganese, copper,
zinc, organic matter, calcium, phosphorous, magnesium, sodium and sulfate were log-transformed,and
iron andpotassiumwere square-roottransformed(100m2 plots). For 1-m2subplots the transformationswere
identical, except that iron was not transformedand
boronwas log-transformed.
To reducecollinearityandfacilitateinterpretationof
- High-elevation rock outcrop vegetation -
on thefirstfive axesof
Table2. Loadingsof soilparameters
PCA.Thehighestloadingfor eachsoil
the varimax-rotated
is in bold. Unitsfor all variablesareppmexcept
parameter
pH, organicmatter(%),andwaterholdingcapacity(%dry
%varianceexplained.
weight).Cumvar.= Cumulative
Axis
Name
Soil
Cations Moisture
Iron
Axis
pH
Axis
Sulfate
Axis
0.82
0.20
0.61
0.03
0.19
0.13
0.04
0.18
0.16
0.71
0.12
0.19
0.05
0.09
0.27
-0.13
0.03
0.50
- 0.08
0.19
- 0.04
0.14
- 0.21
0.06
- 0.17
- 0.07
0.72
0.78
- 0.20
0.07
68.5
76.6
pH
Axis
Iron
Axis
100-m2plots, N = 154
pH
Boron
Aluminum
Sqrt (iron)
Sqrt (potassium)
elog (calcium)
elog(copper)
elog(magnesium)
elog(manganese)
elog(sodium)
elog(organicmatter)
elog(phosphorus)
elog(sulfate)
elog(waterhold.cap.)
elog (zinc)
Cum. var.
Axis
Name
pH
elog (boron)
aluminum
iron
Sqrt (potassium)
elog (calcium)
elog (copper)
elog (magnesium)
elog (manganese)
elog (sodium)
elog (organicmatter)
elog (phosphorus)
elog (sulfate)
elog (waterhold. cap.
elog (zinc)
Cum. var.
-
-
-
0.15
0.39
0.32
0.29
0.51
0.91
0.11
0.85
0.72
0.00
0.21
0.15
0.12
0.05
0.81
-0.27
0.05
- 0.02
0.04
0.62
0.08
- 0.22
0.09
0.17
0.42
0.92
- 0.30
- 0.06
0.83
0.22
0.13
0.71
0.06
0.76
0.03
- 0.05
0.67
0.03
0.23
- 0.02
0.01
-0.27
0.43
- 0.07
- 0.13
28.8
44.6
58.7
1-m2plots, N = 577
Soil
Sulfate
Axis
Cations Moisture
-
-
0.21
0.41
- 0.46
- 0.22
0.46
0.92
0.15
0.86
0.76
0.04
0.24
0.14
-0.20
0.03
0.80
- 0.20
0.04
0.03
- 0.03
0.68
0.12
-0.21
0.17
0.17
0.43
0.90
- 0.12
0.04
0.73
0.32
0.01
0.28
0.48
0.11
0.21
- 0.08
0.54
-0.11
0.10
-0.14
- 0.06
0.57
0.86
- 0.06
- 0.04
0.86
0.19
0.46
- 0.15
0.08
- 0.01
0.17
0.19
0.20
0.62
- 0.06
-0.31
-0.16
0.06
- 0.16
- 0.02
0.68
- 0.06
0.85
0.07
- 0.10
0.25
0.07
0.06
0.10
0.09
-0.53
0.15
- 0.07
- 0.15
0.30
0.43
0.55
0.66
0.74
soil differences, soil nutrientvariationwas reduced to
five principalcomponents.A VARIMAX rotationwas
employed to produce a more interpretablestructure
(Dunteman1989). The first five PCA axes accountfor
76.6 %of the soil nutrientvariationamong 100-m2plots
and73.8 %of the variationin soil nutrientsamong 1-m2
subplots (Table 2). Axis names derive from the soil
parameterwith the highest loadings on that axis.
Classification and ordination
To first examine compositional variation, TWINSPAN (Hill 1979, see review in Kent & Ballard 1988)
was used to classify the outcropvegetationdatafromthe
100-m2plots into communities.The programwas run
using default options, except that pseudospecies cut
707
levels (sensu Hill 1979) used were 5 % and 50 %cover.
As TWINSPAN requires splits at each iteration and
distance down the hierarchy is not related to group
homogeneity, we chose final division levels to maximize interpretabilityof communitiesin terms of major
environmentaland geographicgradients.To assurethe
robustnessof the resultantclassification, we devised a
secondclassificationusing S0rensen'ssimilaritycoefficient with the group average linkage cluster analysis
algorithm.This producednearly identicalresultsto the
TWINSPAN analysis. Constancy(i.e. percent of plots
of a communitywith species present)andmeancover in
plots of occurrencewere calculatedfor both prevalent
species (i.e. those n species with the highest constancy,
where n equals the mean species richness for the community; see Curtis 1959), and regionally rare species.
Homoteneity(sensu Peet 1981), an index of the relative
uniformity of a community type, was calculated for
each type as the sum of the constancy values of the
prevalentsdividedby the sum of the constancyvalues of
all the species (Curtis1959; Peet 1981).
Vegetation-environmentrelationshipswere examined using DetrendedCorrespondenceAnalysis (DCA),
CanonicalCorrespondence
Analysis(CCA),partialDCA
and partialCCA. All runs of DCA used detrendingby
segmentsandnon-linearrescalingas advocatedby Knox
(1989). Correlationsbetween environmentalvariables
and ordination axes were assessed using Pearson's
correlationcoefficient. CCA adds the constraintthat
ordinationaxes mustbe linearcombinationsof measured
environmentalvariables (ter Braak 1987, 1988). DCA
and CCA eigenvaluesprovide a measureof the amount
of variationin the species data accountedfor by each
axis; the total inertia (eigenvalues summed across all
axes) indicates the total variance in the species data
accountedfor by the ordination.With CCA, the sum of
canonicaleigenvaluesindicatesthe amountof variation
explained by the site parameterssupplied (ter Braak
1988). Monte Carlopermutationswere appliedto CCA
analyses to determineif the strengthof species sorting
alongtheenvironmentalvariableswas greaterthanwould
be expectedby chance (terBraak1988; Crowley 1992).
of compositionalvariationamong1-m2
Interpretation
subplots may be complicated by overall 100-m2 plot
differences. Ter Braak (1986) suggested using partial
ordination,a techniqueallowing designatedvariablesto
be treatedas covariables,to analyzenested data.Variation in the species by site matrix accounted for by
covariablesis subtractedfrom the databeforeextraction
of ordinationaxes,therebyallowingexaminationof strictly
small-scalevariation.PartialDCA of the 1-m2data,with
scores on DCA axes 1 -4 for the 100-m2plot to which
the 1-m2subplotbelongedas covariables,allowedanalysis of subplot-scale variation and its relationship to
708
Wiser, S.K. et al.
environmentalvariation measuredat this scale.
An approach analogous to that of Borcard et al.
(1992) was used to quantifyspecies patternsthatreflect
differences among microhabitatsfrom those reflecting
site differences. Toward this end, four analyses were
made of the 1-m2subplotdata.First,two separateCCA
analyses were conducted. CCA analysis 1 was constrainedby DCA scores for the 100-m2plots, and thus
representsthe variationcontained in the 100-m2plots
where some is specific to the 100-m2scale and some is
shared with the 1-m2 scale owing to spatial autocorrelation. CCA analysis 2 was constrainedby site
parametersmeasuredon 1-m2subplots,andthus represents the variation attributableto environmentaldata
collected at the 1-m2scale, some of which is specific to
the 1-m2scale andsome of which is sharedwith the 100m2 scale owing to spatial autocorrelation.Next, two
partial CCA ordinations were conducted. Analysis 3
used DCA scores for the 100-m2 plots as covariables
and constrainedremainingvariationby measuredsite
parameters,with the result that this analysis is influenced only by informationexclusively presentat the 1m2level. Analysis 4 used site parametersas covariables
and constrainedthe CCA by 100-m2DCA scores, with
the result that the analysis is influenced only by information exclusively present at the 100-m2 level. The
percentof the total variationof species data accounted
for by each analysis is obtainedby dividing the sum of
the canonicaleigenvalues by the total inertiaandmultiplying by 100. By addingthis value for analyses 1 and 3
or for 2 and4, the total amountof explainedvariationin
the data is obtained.This can be partitionedas: (a) that
accountedfor by differences among 100-m2plots only
[analysis 4], (b) that accounted for by site parameters
measuredon 1-m2 subplots only [analysis 3] , (c) that
sharedby the two plot sizes [step 2 - step 3, or step 1 step 4], and (d) unexplained variation and stochastic
fluctuations[100 - total explained variation].Although
an analogousapproachemploying dummyvariablesto
indicate plot membership to examine subplot differences would have been possible (Palmer1990; Lavorel
et al. 1991), the large number of plots analyzed here
would have requiredunreasonablenumbersof dummy
variables.
'Stepwise' CCA selected fromfive to nine microenvironmental variables in the analyses partitionedby
bedrocktype and 19 microenvironmentalvariablesfor
the complete data set. All the selected microenvironmental parameterswere retained as the primarygoal
was to determine the maximum amount of variation
they could explain (cf. 0kland & Eilertsen 1994).
To determineif environmentalgradientsinfluencing
vegetationwere the same on differentbedrocktypes and
if patternsvaried with geographic extent, the datasets
were partitionedby bedrocktype (see Peet 1981). Plots
and subplots having seepage were deleted from this
portionof the analysis as seepage influencedboth soils
and vegetation,but occurredinconsistentlyacross bedrocktypes.At least 10 100-m2plots and30 1-m2subplots
remainedin six of the bedrocktypes. These six included
two mafic (amphibolite and metagabbro),one intermediate (meta-arkose) and three felsic types (metagraywacke,Anakeestaslate, Whitesidequartz-diorite).
CCA was also used to compareabilities of the two
exposure indices to explain variationin compositional
data (see Reed et al. 1993). Two analyses were conducted, each constrainedby one exposure index. For
both plot sizes, the second exposure index explained
more of the variation in the species data, and consequentlywas used in all analyses.
DCA and CCA ordinationsand Monte Carlo tests
were performedusing the computerpackageCANOCO
(version 3.10, ter Braak 1990). Ordinationbiplots were
produced using SYGRAPH (version 5.0, Wilkinson
1990).TWINSPANandclusteranalysiswereperformed
using the computerpackage PC-RECCE(Hall 1992).
Other statistical analyses were performedusing SAS
(version 6.04, Anon. 1987).
Results
294 vascularplant species were encounteredin 154
100-m2plots. Species richnessaveraged18 per 100-m2
plot and 6 per 1-m2 subplot.
Nine TWINSPAN communities were selected to
characterizethehigh-elevationoutcropvegetation(Figs.
2 and 3, Table 3). Although the TWINSPANdivisions
partlyreflect geographicposition, local site factorsalso
strongly influence composition. Within each locality
(Fig. 1), this resultedin delineationof 2 to 5 communities. Only one communityis restrictedto a single locality and no one communityoccurs on all.
The firstTWINSPANdichotomydifferentiatedvegetationtypes accordingto elevation (Figs. 2 -4). Among
higher elevation communities, furtherdivisions correspond to additionalpartitioningby elevation, geography, geology andpresenceof abundantseepage (Fig. 2).
Among lower elevation communities,furtherdivisions
distinguish communities that differ in geography or
bedrocktype. Highest species richness (37 - 43 species
per 100-m2 plot) occurred in communities on mafic
bedrockat 1320 - 1360 m. The two communitieswith
thelowest speciesrichnessoccuratthehighestelevations
(Table 3).
709
- High-elevation rock outcrop vegetation I
I
HIGHERELEVATIONS
LOWERELEVATIONS
I
FEL'SIC ROCK
WIT H SEEPAnE
OR MAFICROCK
ABUNDANT
SEEPAGE
SOUTHERN
I
MID - HIGH
ELEV,ATIONS
FELSIC
HIGHER
ELEVATIONS
I
LITTLE
SEEPAGE
NORTHERN
& CENTRAL
I
SOMEWHAT
LOWER
ELEVATIONS,
OR LESS
EXPOSEDSITES
LOWSOL.RtAD., HIGHSOL.RAD.,
AMPHIBOL
ITE
OTHERROCK
OR METABASALT TYPES
HIGHEST
ELEVATIONS,
EXPOSEDSITES
I
D.,OTHER
OTHER
ROCK,OR
ANAKEESTA
SLATE>1980 n
~A
ANAKEESTA
SLATE
I
Fig. 2. Hierarchicalrelationshipsof
TWINSPAN
andassociated
communities
environmental
contrasts.
,
A .oI
'9
_C
Communitycharacterization
Community names employed below derive from
two species thathave constancygreaterthan55 %which
distinguish the community by either their presence or
high constancy.
Carex misera, Saxifraga michauxii and Vaccinium
corymbosumhave high constancyandoccurin all communitytypes, which may be explainedby theirabilityto
readily invade disturbedoutcrops. Scirpus cespitosus,
Sorbus americana, Rhododendroncatawbiense, Polypodium appalachianum and Agrostis perennans each
occur in eight of the nine communities.
The Coreopsismajor-Schizachyrium
scopariumoutcrop communityoccurs at low-to-midelevations(12501700 m) on mafic rock, or felsic rock with perennial
seepage. Soils have higherpH, magnesiumand manganese than do those from other outcrop communities.
Saxifraga michauxii, Quercus rubra, Dichanthelium
acuminatum,Kalmia latifolia, Danthonia spicata and
Paronychiaargycomahavehighconstancy.Whenpresent
on outcrops,Allium cernuum,and the regionally rare
MuhlenbergiaglomerataandHeucheralongiflora,occur
only in this community(Table 3). Surroundingvegetation is predominantlydeciduous forest with Q. rubra,
Acer rubrumand Tsuga caroliniana.On steeperslopes
and at slightly higherelevationson the same peaks, this
community is replaced by the Paronychia argycomaPolypodiumappalachianumcommunity(see below).
The Selaginella tortipila-Carexumbellataoutcrop
communityusually occurs below 1600 m on felsic bedrock andis primarilyconfinedto the southernpartof the
to
a
;o_
It. - '9t q
, '
'
I,~C1
'9-~~~~~~~~~;
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9=
o.
9
~
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.-
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p --
%A
0'9'
ll" '--
11s4
study area.It predominateson Whitesidequartz-diorite
outcrops,locally referredto as 'granitedomes'. These
smooth,south-facingoutcropswith shallow slopes (x =
26?) are typically dominatedby Selaginella tortipila
mats, comprising20 to 100 % of the total cover. Soils
tend to be lower in major cations and micronutrients
than those of the other communities. Mid-summer
droughtstressis marked.Krigiamontana,Dichanthelium
acuminatum,andHoustonialongifoliavar.glabrareach
their highest constancy here. On the outcrops studied,
the regionally rareJuniperus communisvar. depressa
occurs only in this community.Surroundingvegetation
is predominantlydeciduousforest with Quercusrubra,
Q. prinus, Q. alba, Pinus rigida, P. strobus and Acer
rubrumdominant,andanunderstoryof ericaceousshrubs
including Rhododendronspp., Kalmia latifolia, Vaccinium spp. This community occurs less commonly
north of the Black Mts. (Fig. 5, below) owing to the
scarcity of smooth, flat outcrops on relatively lowelevation ridgetops.
TheAroniaarbutifolia-Kalmialatifoliaoutcropcommunity occurs on shallow slopes (x = 27?) over felsic
bedrockat low-to-midelevations (1200-1700 m). South
of Asheville, this communityis encounteredunderenvironmentalconditions uncommon there - either at low
elevations on north-facingslopes or at high elevations
on south-facing slopes where S. tortipila is sparse or
absent.Amelanchierarborea, Scirpus cespitosus,Acer
rubrum, Rhododendron catawbiense, Leiophyllum
buxifolium,Galax urceolata, and Gaylussacia baccata
have high constancy.On outcropsXerophyllumasphodeloides, a species disjunct from the coastal plain of
710
Wiser, S.K. et al.
Table 3. Classification of high-elevation rock outcrop communities provided by TWINSPAN. The mean cover class for plots where
the species is present in the community is followed by the constancy in each community. + = present in community, but not prevalent
(see text), * = regionallyrarespecies. Species appearingin communitynames in bold.
Community
Coreopsis- SelaginellaSchizachyrium Carexumb.
AroniaKalmia
Chelone- Paronychia-Deschampsia- PiceaAsterCalamagr.Oxypolis Polypodium Angelica Leiophyl. Rhodod.car. Menziesia
15
27
11
4
23
29
16
11
18
1441
1395
1370
1496
1504
1734
1615
1895
1877
Homoteneity (see text)
Mean species richness (per 100 m2)
Total rare species
0.467
0.475
0.550
0.644
0.584
0.502
0.567
0.643
0.569
24
16
22
26
21
19
13
13
16
9
8
7
12
11
17
6
9
10
MUGL Muhlenbergiaglomerata*
HELO Heuchera longiflora*
+
+
3 33
2 33
+
+
+
+
22 36
36
Number of plots
Mean elevation (m)
ALCE
VISA
CABI
Allium cernuum
Viola sagittata
Carex biltmoreana*
SCSC
Schizachyriumscoparium
COMA
SOBI
Coreopsis major
Solidago bicolor
QURU
DECA
CADI
PHOP
Quercusrubra
Deschampsia cespitosa*
Campanuladivaricata
Physocarpusopulifolius
HOCA
SOUL
Houstonia caerulea
JUCO
ANVI
SETO
HOLO
Juniperuscommunisvar. depressa*
Andropogonvirginicus
Selaginella tortipila
Houstonia longifolia var. glabra
DASE
DACO
Danthonia sericea
Danthonia compressa
DIAC
Dichantheliumacuminatum
CAUM
KRMO
Carex umbellata
Krigia montana*
TOGL
XEAS
Tofieldiaglutinosa ssp. glutinosa*
Xerophyllumasphodeloides
GABA
CLAC
Gaylussacia baccata
Clethra acuminata
UVPU
VINU
LYQU
Uvulariapuberula
Viburnumnudumvar. cassinoides
Lysimachiaquadrifolia
AMAR
Amelanchier arborea
SOPU
Solidago puberula
KALA
ACRU
VAPA
GAUR
ARAR
IRVE
SCCA
LIHE
HUPO
HESP
FIRU
CHOB
Kalmia latifolia
Acer rubrum
Vaccinium pallidum
Galax urceolata
Aronia arbutifolia
Iris verna
+
3
2
2
2
73
80
40
60
+
+
+
2 47
3 33
2 33
+
+
+
+
3 67
3 27
3 53
+
+
+
+
+
+
+
+
+
+
33 60
60
+
+
3 40
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
4 45
4 64
3 45
2 45
3 55
2 36
2 82
2 55
4 82
3 73
4 45
3 64
3 91
3 36
4 82
2 55
Sanguisorbacanadensis*
+
Juncus acuminatus
Carex crinita
+
DRRO
SOPA
Drosera rotundifolia
Solidago patula var.patula
+
OXRI
Oxypolis rigidior
+
ASCO
HOSE
Aster cordifoliusvar. sagittifolius
Houstonia serpyllifolia
+
+
THCL
Thalictrum clavatum
+
PAAR
Paronychia argyrocoma
SETE
HEVI
Sedum telephioides
Heuchera villosa
VACO
Vacciniumcorymbosum
+
+
+
ATAS Athyriumfilix-femina ssp. asplenioides
RHMA Rhododendronmaximum
Chelone lyonii
Danthonia spicata
2 50
+
2+35
+
2 35
3 66
+
3 36
+
+
+
+
+
+
2 75
+
+
+
+
3 52
+
+
+
+
+
+
+
+
3 50
4 50
+
+
+
+
+
+
2 50
+
+
+
+
5 36
+
+
+
SACA
Parnassia asarifolia
+
+
4 50
3 50
5 100
JUAC
CACR
CHLY
DASP
+
+
5 36
Huperzia porophila*
Heuchera sp. 1 (sp. nov.)
Filipendula rubra*
Chelone obliqua
PAAS
+
+
+
+
+
+
+
3 41
7 93
2 63
3 44
4 56
2 70
2 67
2 78
+
+
2 44
2 37
3 44
Scirpus cespitosus*
Liatris helleri*
Hypericum buckleyi*
Arisaema triphyllum
Carex ruthii*
+
+
Solidago uliginosa*
HYBU
ARTR
CARU
+
+
+
+
+
+
+
+
+
30
22 30
3
3
2
2
4
60
60
47
33
40
2 33
+
+
+
+
+
+
+
3 74
+
+
2 41
2 52
+
+
2 62
245
3 39
+
+
+
+
+
+
+
36
22 36
2 74
3 91
2 65
2 61
+
4 37
+
2 50
3 50
3 50
3 75
3 100
3 100
4 100
3 75
2 75
2 75
4 50
2 50
3 50
3 75
2 50
4 65
44
44 44
+
4 55
+
+
+
+
3 48
3 45
2 61
+
+
+
+
- High-elevation rock outcrop vegetation -
711
Table3, cont.
Community
Coreopsis- SelaginellaSchizachyrium Carexumb.
3 87
2 40
+
SAMI
POAP
HOPU
Saxifragamichauxii
Polypodium appalachianum
Houstoniapurpureavar. montana*
ZILE
Zigadenus leimanthoides*
HUAP
MIGR
JUTR
GERA
ARLY
HYMG
DEFL
AGPE
DISE
SITR
ANTR
RUAC
PRRO
ALCR
RHVA
BEAL
RHCA
LEBU
Huperziaappalachiana*
Minuartiagroenlandica*
Juncus trifidus*
Geumradiatum*
Arabis lyrata*
Hypericum mitchellianumlgraveolens* +
3 33
Deschampsiaflexuosa
3 40
Agrostisperennans
+
Diervilla sessilifolia
+
Sibbaldiopsistridentata
+
Angelica triquinata
Rumexacetosella
Prenanthesroanensis*
Alnus viridis ssp. crispa*
Rhododendronvaseyi*
+
Betula alleghaniensis
3 53
Rhododendroncatawbiense
Leiophyllum buxifolium
PIRU
Picea rubens
SOSP
Solidago spithamaea*
VIMA Viola macloskeyi
ASMO Aspleniummontanum
CAMI Carexmisera*
RHCL Rhododendroncarolinianum
SOGL Solidago glomerata
CACA Calamagrostiscainii*
GELI
Gentiana linearis*
3 33
+
+
+
3 33
+
AroniaKalmia
+
+
Chelone- Paronychia-Deschampsia- PiceaCalamagr.- AsterOxypolis Polypodium Angelica Leiophyl. Rhodod.car. Menziesia
3 100
+
+
+
+
2 48
+
+
3 48
+
+
+
+
+
+
+
3 50
+
+
3 65
2 43
+
+
+
+
+
3 87
3 78
2 70
+
3 73
6 73
3 48
3 78
+
+
+
+
+
+
+
+
+
+
4 36
4 50
2 35
2 65
+
CABR
Carex brunnescens
+
+
SOAM
ASAC
MEPI
VAER
ABFR
RUID
PHCO
Sorbusamericana
Aster acuminatus
Menziesia pilosa
Vacciniumerythrocarpum
Abiesfraseri
Rubus idaeus*
Phegopteris connectilis*
+
+
New Jersey, occurs only in this community, but may
grow in adjacent,shallow-soiled woodlands. The predominanceof woody species reflectstherapidgradation
into heath balds and may be related to the generally
deepersoils of this community.Surroundingvegetation
ranges from heath balds dominatedby Rhododendron
catawbiense to deciduous or conifer forests. At higher
elevations, underotherwise similar conditions,it is recatawbiense
placed by the Picea rubens-Rhododendron
outcropcommunitydescribedbelow.
The Chelone obliqua-Oxypolisrigidior wet outcrop
community is a species-rich, broad-leavedherb community occurringon low-to-mid elevation (1262-1725
m) felsic outcropswith abundantseepage. It occurs on
steep,loweroutcropslopes,farbelow thenearestsummit.
Sites are highly protected, shady and constantly wet.
Saxifraga michauxii,Aster divaricatus,and Houstonia
serpyllifolia are ubiquitous. On outcrops, Chelone
obliqua,Filipendula rubraandHuperziaporophila are
uniqueto this community,the lattertwo being regionally
rare.The surroundingdeciduousforest is dominatedby
Betula alleghaniensis, Acer rubrum,and Tsuga caro-
2 45
+
+
+
+
2 50
+
+
3 90
+
+
2 75
2 38
2 91
3 100
2 44
+
+
+
+
+
+
+
2 36
+
+
+
+
+
55
52
45
38
59
38
+
+
+
+
4 69
+
+
+
2 56
3 88
5 81
4 73
+
3 39
+
+
3 81
+
+
+
+
+
3 41
3 38
2 45
+
2 50
+
+
+
3
3
2
4
2
3
3 55
+
+
+
4 65
+
3 57
4 35
2 45
+
+
+
+
+
+
+
+
+
3
2
3
3
2
63
50
56
44
44
3 44
+
+
+
2
4
4
4
5
2
36
100
100
64
91
64
4 89
3 61
+
2 38
3 44
2 45
2 55
+
2 36
3 55
3
3
3
3
4
72
83
67
44
61
+
+
liniana, or Picea-Abies forest.
The Paronychia argycoma-Polypodium appalachianum outcrop community usually occurs at mid
elevations (1347 - 1585 m) on highly exposed, SW toNW-facingslopes,primarilyoveramphiboliteandmetabasalt, both mafic rock types (Fig. 6, below). Most
occurrences are north of GrandfatherMt. Saxifraga
michauxii,Rhododendroncatawbiense,Athyriumfilixfemina ssp. asplenioides,Danthoniaspicata,Houstonia
purpurea var. montana, Carex misera, Sedum telephioides, Sorbus americana, Sibbaldiopsis tridentata,
Vacciniumcorymbosum,andHeucheravillosa all have
high constancy. Surrounding vegetation is usually
Quercusrubra,with grassorheathbaldsless commonly
as the matrix.
TheDeschampsiaflexuosa-Angelicatriquinataoutcrop communityoccursprimarilyover metagabbroand
metagraywackeat mid to high elevations(1650-1900 m)
on SE to SW-facing slopes, or as much as 170 m lower
on NW-facing slopes. The Paronychiaargycoma-PolypodiumappalachianumandPicea rubens,Leiophyllum
buxifoliumcommunities,foundwithinthe sameelevation
Wiser, S.K. et al.
712
1. Coreopsis/Schizachrium
2. Selaginella/Carex umb.
3. Aronia/Kalmia
4. Chelone/Oxypolis
5. Paronychia/Polypodium
6. Deschampsia/Angelica
7. Picea/Leiophyllum
* 8. Calamagrostis/Rhodod. car.
* 9. Aster/Menziesia
o
*
a
*
A
+
x
5
4
*c.
11)
v,
Q
9:
*I
I
*-
6c
3
oO0 o
+
.
*
0*
I
+
++f
e
0
*
+ +
#X x
t
o
2
x
x
+
O
0O
x
1
+
0O
0
0
0
Ic
1
I
I
2
3
{
4
DCA Axis 1
range, are poorly represented on these rock types.
Saxifragamichauxii,Rhododendroncatawbiense,Krigia
montana and Athyriumfilix-femina ssp. asplenioides
have high constancy. Often the matrix vegetation is
grass or shrubbald resultingfrom past burningand/or
grazing(Gersmehl1973;Barden1978;Stratton& White
1982). The importanceof Angelica triquinatamay relate to its preference for balds (McLeod 1988) which
could allow persistenceon adjacentoutcropsby a spatial mass effect (sensu Shmida & Ellner 1984). Exotic
species are rarein the high-elevationoutcropflora, but
six of the eight exotic species encountered (i.e.
Polygonumaviculare,Phleumpratense,Poa compressa,
Rumex acetosella, Taraxacum officinale, Trifolium
pratense) either occur only in, or reach their highest
constancy in this community. Presence of exotics reflects both theiroccurrencein surroundinggrassy balds
and the high potentialsolar radiationof these outcrops.
On outcrops,Alnus viridis ssp. crispa, a regionallyrare
species, is unique to this community.
The Picea rubens-Leiophyllumbuxifoliumoutcrop
communityoccurs over highly fracturedfelsic to mafic
bedrockatmid-elevations(1400-1800 m). Aspectranges
from northeastto southeast. This community is most
prevalentin the GrandfatherMt. region, but also occurs
in the Smoky Mts. and on the Roan Mt. massif. Rhododendroncatawbiense, Saxifraga michauxiiand Sorbus
americana have high constancy. Surroundingvegetation is eitherheath bald or northernhardwoodforest.
The Calamagrostiscainii-Rhododendroncarolinianum outcrop community is confined to the felsic
Anakeesta slate outcrops in the Great Smoky Mts. It
6
Fig. 3. DCA ordinationof all 100-m2
plots in the studyareacoded by the 9
TWINSPAN communities.
occursat high elevations (1650-2000 m) on steep (x =
60?), predominantly southeast or southwest-facing
slopes. While soils are generally low in majorcations,
they are high in boron, iron, copper, and manganese,
conditionsmore typical of soils over mafic rock. Carex
misera, Saxifraga michauxii,Leiophyllumbuxifolium,
Solidago glomerata and Gentiana linearis have high
constancy.Gentianalinearis, a species consideredrare
in Tennessee,occursonly on these outcropsandin other
high-elevation communities nearby. Calamagrostis
cainii, a local SouthernAppalachianendemic, reaches
its highest abundanceand constancyhere and is otherwise known from only two smallerpopulationson outcrops some 100 km away (Wiser 1991). Surrounding
vegetation is Picea-Abies forest. At lower elevations
undersimilarconditionsthis communityis replacedby
the Picea rubens-Leiophyllumbuxifoliumcommunity.
TheAsteracuminatus-Menziesiapilosa
outcropcommunity usually occurs above 1700 m on the highest
elevation outcropsstudied (i.e. the highest summits of
GrandfatherMt., Mt. Craig, Roan High Bluff, and Mt.
Buckley in the GreatSmoky Mts., and nearthe summit
of CraggyPinnacle;Fig. 7) in settings with low potential solar radiation over highly fractured bedrock.
Saxifragamichauxii,Carex misera, Sorbusamericana,
Solidago glomerata,Heucheravillosa andAbiesfraseri
have high constancy. Outcrops typically occur in a
Picea-Abiesforestmatrix,andthe most constantspecies
arecommon in these forests. With slightly lower elevation or exposureon a given mountain,this communityis
replaced by the Picea rubens-Leiophyllumbuxifolium
outcropcommunity.
713
- High-elevation rock outcrop vegetation -
6
5
GEOLOGY
4
C\)
.
n.
..
..
-<
3
SOIL MOISTURE
SEEPAGE
o
SOLAR RAD'
PH AXIS
2
EXPOSURE
TOPO POS,
\
'CATIONS
1
Fig. 4. Biplotsof standscoresand
environmental
correlationsfor the
DCAordination
of all 100-m2plots
inthestudyarea.Codesforenvironmentalparameters
areas in Table4.
0
0
I
I
1
2
AXIS
\FE
ASPECT
I
I
I
I
3
4
DCA Axis 1
5
6
The only previousclassificationof SouthernAppalachianhigh-elevationoutcropvegetationis thatof Schafale
& Weakley (1990) basedexclusively on subjectivefield
evaluation.Theydistinguishedgranitedomecommunities
(onWhitesidequartz-diorite
outcrops)andhigh-elevation
seep communities from other high-elevation cliff
communities,termedhigh-elevationrockysummits.We
similarly recognize granite dome communities (Selaginella tortipila-Carexumbellatacommunity)and one
type of seepage community(Cheloneobliqua-Oxypolis
rigidior community) as distinct. Schafale & Weakley
pointedout thathigh-elevationseeps vary considerably
in composition. We distribute seepage slopes across
severaldifferentcommunitiesbecauseof strongfloristic
similarity to nearby outcrop sites lacking seepage.
Schafale & Weakley defined three geographicvariants
of high-elevationrockysummits.Incontrast,ourfloristicbasedclassificationcorrelatesmorestronglywith differences in elevation, bedrock type, and surrounding
vegetationcompositionthan with geography.
they inhabit (Fig. 8). As a group, rare species are not
confined to a particularcommunitytype or geographic
region. Geum radiatum, Huperzia selago, Solidago
spithamaea, Prenanthes roanensis and Carex misera
are most frequentin the northernpartof the study area,
either above 1600 m on felsic or intermediatebedrock,
or as much as 250 m lower on steep slopes of mafic
outcrops. Muhlenbergia glomerata and Deschampsia
cespitosa occur only in communitieson mafic bedrock.
Carex biltmoreana, Solidago uliginosa, Hypericum
buckleyi,Tofieldiaglutinosassp.glutinosaandJuniperus
communis var. depressa generally occur south of
Asheville on felsic outcrops below 1800 m. Huperzia
porophila and Filipendula rubra each occurred on a
single seepage slope in the Chelone obliqua-Oxypolis
rigidior community. Scirpus cespitosus and Liatris
helleri occurup to 1990 m and 1620 m respectivelyand
descendto elevationsbelow thosestudied(AlanWeakley
pers. comm.). Although both species occur on mafic
sites, they are most abundantand constant on felsic
bedrockin the Aroniaarbutifolia-Kalmialatifolia community.
Rare species
Soil properties
In comparisonto other SouthernAppalachianvegetationtypes, high-elevationoutcropsharborhigh numbers of regionally rare species (Table 3). Despite sharing a restrictionto high-elevation outcrops,individual
rarespecies vary considerablyas to the type of outcrop
The outcropsoils were highly organicwith low pH
( x organicmattercontent= 31%,x pH = 4.1). ThatpH
has low loadingsuntil the fourthPCA axis suggests that
pH is not a strongindicatorof soil nutrientstatusin these
soils. ThepositivecorrelationbetweenpH andaluminum
Comparisonto previous classifications
714
Wiser, S.K. et al.
Fig. 5. A geographicoutlier of the Selaginella tortipila-Carexumbellataoutcropcommunity on Hawksbill Mountain,Linville
Gorge,NorthCarolina. At these elevationsPinuspungens andP. rigida dominateadjacentforests. Dense Selaginella mats, such as
picturedhere, are rarein nearbyareasowing to abrasionfrom hikers and rock climbers.
Fig. 6. This example of the Paronychia argycoma-Polypodiumappalachianum outcrop community occurs on Bluff Mt. in
NorthwesternNorth Carolina. Saxifragamichauxii,widespreadon outcropcommunities,is flowering in the foreground.
- High-elevation rock outcrop vegetation -
715
communities
atthehighestelevations(1700m+)usuallyoccuronhighlyfracturedbedrockonhighlyexposedsites
Fig.7. Outcrop
asshownhereonGrandfather
NorthCarolina.Thesurrounding
forestis Picea-Abies. Onthesteepestslopes,herbaceous
Mountain,
speciespersistin onlya few cracksandcrevices.
also is contraryto conventionalwisdom (Brady 1984).
This correlationholds even when organicmatterinfluence is removed throughpartialcorrelation,or unusually high or low aluminum soils are excluded from
analysis.
Perennialseepage occurredon 28 100-m2plots over
a range of bedrocktypes. Seepage slopes tend to occur
fartherbelow summits than do outcrops without seepage (x = 103 m below summitvs. 38 m below summit
for non-seepageslopes);p < 0.0001 by t-tests). Seepage
presencerelatesto rock permeability,the strikeand dip
of metamorphicfoliation or outcropfractures,andtopographic influences on sub-surface flow (Boorman &
Platt 1958; Schafale & Weakley 1990). Groundwater
tendsto follow rockformationson mountainslopes and
moist habitats often develop on and near downslope
outcrops (Hursh & Haasis 1931). Soils from 100-m2
plots with seepage have higher waterholding capacity,
pH, and sodium and lower sulfatethando those lacking
seepage (all p < 0.01 by t-tests).
Over a 100-m2 plot, seepage presence is rarely, if
ever, uniform.In 100-m2plots with seepage, individual
1-m2subplotswith seepage tend to have steeper slopes
(x = 42? vs. 34?; p = 0.007 by a t-test), higher pH,
sodium,manganese,andlower phosphorusthando non-
seepage microhabitats(all p < 0.01 by t-tests). These
differences are probablya consequence of transportof
cations leached from higher rocks and soils.
On 100-m2 plots lacking seepage, significant, but
small soil differences are apparenton mafic (43 plots)
vs. felsic rock (55 plots). Boron,copperandphosphorus
are higher,and sodium is lower in soils over mafic rock
than in those over felsic rock (all p < 0.01 by a t-test,
Fig. 4). Similarpatternsemerge for 1-m2subplots.
As soil pH and cations are usually elevated in soils
over mafic rock elsewhere, the lack of strong differences between mafic and felsic bedrockin magnesium,
manganese and pH and only small differences in calcium are surprising.Nonetheless, nine of the 12 plots
with the highest loadings on the cations axis occur on
mafic rock or on rock with occasional mafic veins; the
remaining three plots high in cations are on seepage
slopes over felsic rock. Soils formed over metabasalt,a
mafic rock, may differ in nutrientswith slope position
(Rohrer 1983). Non-ridgetopsoils retain moisture and
nutrientsandhave high relativeamountsof phosphorus,
potassium,calcium,magnesiumandmanganese,whereas
ridgetopsoils arethin, moisturequicklyevaporates,and
downslope leaching results in only intermediatelevels
of these nutrients(Rohrer1983).
716
Wiser, S.K. et al.
6
HUAP
FRU
CHOB
5
4
_
sEm-BP
ZRI
AC$gJLOHYBU
LEBU
SCDI
ASDI
SOCMARARAR HOSE
LHE
GAUR
CAUM
RMO
CABI KALA
3
x
DIAC
2
QURU
VACO
AGPE
DASP
A.
CAP
If iR
S'ITR
A
SFATR
SCSC COMA
ASAC
PHCO
*_
1
CACA
MEPIABFR
CAM/
RHCA SOAM
ANTRSYS90
AORLY
ATA.J4UP
SAMI
JUTJ
RH VA
DEFL
u
GBLI
PIRU
ZILE
HYMG
C2
CARU
RHCL
HBVI
SACA
Fig. 8. Species scores for a) species with high
0
HELO
DECA
MUGL
II -
-1
0
1
II
2
II
3
DCA Axis 1
I
I
4
5
Scale and relationshipsbetweencompositionand
environment
Across the SouthernAppalachianregion, the environmentalvariablesthatcorrelatewith floristic composition of the 100-m2plots are many and their patterns
complex (Fig. 4, Table 4); similar DCA eigenvalues
across the first three axes suggest highly multidimensional data.The first DCA axis correlatesmost strongly
with elevation and fractureindex and moderatelywith
potential solar radiation,aspect and SE-NW location
(Fig. 4, Table 4). These correlationssuggest that this
DCA axis correspondsto a complex temperature-moisture gradient from hot, dry sites to cool, moist ones.
DCA axis 2 correlates strongly with mafic vs. felsic
bedrockand SW-NE location, and moderatelywith the
ironandsulfatesoil axes (Fig. 4, Table4). Maficbedrock
predominatesin the northeastportionof the study area
and diminishesin prominenceto the southwest.
Within each bedrocktype except Whiteside quartz
diorite,vegetationrelatesstronglyto elevation(Table4)
with the strengthof this relationshipcorrespondingto
the elevation span sampled. When this span is low
(<500 m, i.e. amphibolite,metagabbro,Anakeestaslate),
the dominantvegetation gradientrelates more strongly
to potential solar radiation.The relationshipbetween
vegetationcompositionand soil attributesvariesamong
bedrock types. However, the importanceof some soil
variables may be a consequence of long gradients or
I
6
incommunity
mentioned
constancy
descriptions
(bold)andb) regionallyrarespecies(asdefined
by the NorthCarolinaor TennesseeHeritage
italics).Regionallyrarespecieswith
Programs;
highconstancyarein bolditalics.Speciescodes
areprovidedin Table3.
extremevalues for the particularnutrient.In particular,
the significanceof the pH andcations axes on amphibolite and the sulfateaxis on meta-arkosemay resultfrom
long gradients, whereas extreme soil values may be
importantin the case of the sulfate axis on metagabbro.
Otherparametersstronglycorrelatedwith 100-m2scale
compositionon individualbedrocktypes are slope (amphiboliteand metagabbro),exposure (Anakeestaslate),
fracturingindex (metagraywackeand Whitesidequartz
diorite),and percentrock, outcropheight and area,and
aspect (metagraywacke)(Table 4).
For 1-m2 subplots on metagabbro, meta-arkose,
Anakeestaslate,andmetagraywacke,DCA axis 1 scores
correlatehighly (Pearson's r > 0.80; p < 0.0001) with
corresponding100-m2DCA axis 1 scores. In contrast,
over amphibolite DCA axis 2 of the 1-m2 subplots
surpassesaxis 1 in correlationstrengthwith 100-m2plot
DCA axis 1 scores (r = 0.73, p < 0.0001), revealing a
primary compositional gradient at this scale distinct
fromthatrepresentedby variationamong 100-m2plots.
Over Whiteside quartzdiorite, gradientstructurealso
differsfor 1-m2subplotsas theirscores areonly moderately correlated(r < 0.53) with the respective 100-m2
plot scores.
After removal of the influence of 100 m2 variation,
soil depth, percent exposed bedrock, maximum vegetationheightandsoil chemistry(cations,pH, andsulfate
axes) arehighly correlatedwith compositionalvariation
among all 596 1-m2 subplots (Table 4). As expected,
717
- High-elevation rock outcrop vegetation -
Table 4. Correlationsbetween site parametersandDCA axes forbothplot sizes at the largegeographicextentof the entirestudyarea
and smaller geographicextent of individualbedrocktypes. Significance levels are indicated as: * = p < 0.05; **= p < 0.01;
*** = p < 0.001; *** = p < 0.0001. When significant correlations are many, only those withp < 0.0001 are shown. fracture = rock
fracturingindex; solrad = potential solar radiation;sw-ne, se-nw, = relative long and short geographic axes of the mountains,
respectively;geology = index from 1 to 3 indicatingbroadgeologic categories(i.e. 1 = mafic, 2 = intermediate,3 = felsic); area=
outcropareacategory;height = outcropverticalrelief category;topopos = topographicposition index; exposure= exposureindex;
rock = %exposedbedrock;depth = soil depth;maxveght= maximumvegetationheight;moss = %cover of moss; baresoil= %cover
of baresoil; shade= %sky obstructed;seepage,dirppt,drip,runoff= 1 for presenceof seepage, directprecipitation,dripfrom above
or runoff as moisturesources, 0 for absence;soilmoist = soil moistureholding capacity;PCA soil axes names are as in Table 2.
100-m2plots
DCA Axis 1
Corr.coeff.
Bedrocktype
Var.
ALL BEDROCKTYPES
n = 154 (100m2)
n= 596 (1m2)
elevation
fracture
solrad
se-nw
slope
AMPHIBOLITE
n = 27
n= 108
METAGABBRO
n=13
n =49
META-ARKOSE
n = 25
n = 94
METAGRAYWACKE
n=19
n = 78
ANAKEESTA SLATE
n=10
n = 30
WHITESIDEQUARTZ
DIORITE
n= 17
n=66
0.7614****
0.6839****
-0.4591****
Var.
DCA Axis 2
Corr.coeff.
geology
sw-ne
iron axis
0.7131****
-0.6925****
-0.3874****
-0.4919****
0.3806****
0.3455****
-0.3329****
-0.3035****
-0.3021****
sulfate axis
depth
rock
slope
-0.2107****
0.2234****
-0.1815****
-0.1208**
cations
maxveght
rock
ph axis
depth
dir ppt
drip
moss
seepage
0.7040****
rock
runoff
depth
maxveght
0.3374***
0.2701**
-0.2529**
-0.2860**
sulfate axis -0.3701****
.4104***
- 0.3822**
- 0.3570*
- 0.2905*
iron axis
sw-ne
0.4759****
0.3952****
0.3973****
0.3111****
slope
solrad
iron axis
ph axis
cations
-0.8433****
0.6092***
-0.5013**
0.5087**
0.4754*
elevation
sulfate axis
slope
solrad
0.9283****
- 0.7481**
0.7372**
elevation
- 0.8199***
cations
rock
maxveght
shade
elevation
sulfate axis
- 0.8533****
- 0.5934**
soilmoist
- 0.5677**
iron axis
topopos
depth
elevation
fracture
rock
area
sulfate axis
rock
ph axis
-0.9483****
-0.6098**
0.5471*
height
slope
cations
fracture
0.6376**
0.5439*
-0.5183*
0.5330*
sulfate axis
depth
slope
rock
cations
solrad
elevation
0.8096**
-0.7415*
0.7267*
exposure
- 0.6650*
baresoil
iron axis
fracture
slope
- 0.5372*
sulfate axis
area
eepage
aspect
cations
rock
1-m2subplotswith 100 m2
scores partialedout
DCA Axis 2
DCA Axis 1
Var.
Corr.coeff.
Var.
Corr.coeff.
0.3506****
0.3147****
0.1590****
0.1871****
0.1549****
0.1608****
0.1318**
0.1303**
0.1279**
none sig.
0.4190****
0.3592***
0.2475*
depth
rock
dir ppt
shade
drip
0.3138**
-0.2974**
0.4043****
-0.2951**
-0.2697**
-0.5425****
0.3414**
-0.3065**
-0.2796*
runoff
0.2331*
0.5317*
0.4847*
0.4662*
0.7429***
0.6201**
0.5246*
solrad
soil depth is strongly correlated with percent exposed
bedrock; hereafter their covariation is discussed as one
complex soil depth gradient.
Among 1-m2 subplots on individual bedrock types,
the soil depth gradient is strongly correlated with compositional variation over amphibolite, meta-arkose,
metagraywacke and Whiteside quartz diorite (Table 4).
In contrast, over metagabbro maximum vegetation height
and shade relate more strongly to composition than does
0.5063*
depth
sulfate axis
runoff
rock
shade
exposure
0.3966*
none sig.
-0.4220***
0.3643**
0.3357**
0.3264**
-0.3814**
0.3306**
ph axis
moss
soilmoist
-0.4411***
- 0.3254**
- 0.2894*
soil depth, and over Anakeesta slate only the amount of
bare soil present relates to composition.
Among 100-m2 plots on a bedrock type, total inertia
is three to four times lower than for the entire data set, in
part due to decreased sample sizes. Reducing geologic,
and as a result geographic, variation in the data reduces
dimensionality and thus total inertia. Measured site
parameters account for 78 - 93 % of compositional variation vs. 27 % at the larger geographic extent.
718
Wiser, S.K. et al.
For 1-m2subplots,both across the region andwithin
bedrocktypes, total inertiais two to threetimes greater
than for 100-m2 plots. For subplots, site parameters
account for less compositional variationand are more
weakly correlatedwith the ordinationaxes. Across the
studyarea,4 %of the compositionalvariationamong 1m2 subplotsis due to compositionaldifferencesamong
the 100-m2plots to which they belong (Table5). Within
each of the six bedrocktypes, variationamongthe 100m2 plots accounts for 7 - 10 % of the variationamong
1-m2subplots(Table5). Afterpartiallingoutthe 100-m2
plot score, measured site parametersaccount for an
additional 7 % of compositional variation among all
1-m2 subplots and from 14- 23% of the remaining
compositional variation within bedrock types. Across
the study area, 87 % of the compositional variation
among 1-m2 subplots is explained by neither 100-m2
plot scores or measuredsite parameters.Withinbedrock
types this decreasesto 49 - 74 %.
Discussion
Variationin gradients at differentscales
Observationalscale, both spatial extent and plot
size, influencedetectionof compositionalvariationand
ecologicalpattern(e.g. Allen & Starr1982;Meentemeyer
& Box 1987; O'Neill 1988; Wiens 1989; Reed et al.
1993). Large extents may be requiredto detect subtle,
geographicgradientsin species composition. Plot size
can influence which environmentalvariablesareuseful
in predictingcompositionas well as the degreeto which
plant-plantinteractions obscure environmentaldeterminism (Reed et al. 1993).
Reed et al. (1993) found predictabilityof composition from site parametersto decrease with increased
spatialextentand suggestedthatthis reflectsmorecomplex gradient structureand increased interactionsbetween site parameters.Higher total inertiaand reduced
ability of site parametersto account for compositional
variationacross all SouthernAppalachianoutcrops,as
opposed to within bedrocktypes, likely reflects similar
complex gradientstructureand is consistentwith Reed
et al's interpretation.Across outcrops, geologic and
geomorphiccomplexity increasewith increasedextent.
At the regional extent, climatic variation,disturbance,
andhistoricalinfluences (cf. van derMaarelet al. 1987)
furtherreducethe abilityof measuredsite parametersto
explain compositionalvariation,althoughbedrockdifferences overrideclimatic variationin plant communities elsewhere(Orloci& Stanek1979;Kirkpatrick1982).
Higher total inertiamay also reflect the larger sample
size when all bedrocktypes are combined.
Despite considerableenvironmentalvariation,particularly in geology and climate, there are consistent
compositional patterns, both regionally and on most
bedrock types. Elevation and potential solar radiation
relate stronglyto composition, both within and among
bedrocktypes. The sulfate and iron PCA soil axes are
both importantacross the region. Withinbedrocktypes
the formeris importantover bedrocktypes that ascend
to higher elevations, whereas the latteris importanton
the two bedrocktypes occurringpredominantlyat lower
elevations. The soil depth gradientis importantacross
most bedrocktypes.
On different bedrock types or on north vs. south
slopes, 1-m2subplotsmay differ because of these overall site contrasts as well as because of microhabitat
differences. Among 100-m2 plots with similar site
conditions, subplot differences due to microhabitat
should become more apparent.Accordingly, within a
bedrock type, variationamong 100-m2plots accounts
for less of the variation among 1-m2 subplots than
among bedrock types (Table 5). Similar observations
havebeenmadein saxicolouslichencommunities,where
parameterssuch as overall slope, aspect, and altitude
determinespecies distributionpatternswithinrockfaces
in conjunction with microsite factors (John & Dale
1990), and along the Niagara escarpment, although
micrositepositionhadthe largestinfluencethere(Larson
et al. 1989).
A reducedcorrelationbetween vegetationcomposition and environment at smaller plot sizes was also
observedby Reed et al. (1993). On the outcropsthismay
be caused by (1) increased importanceof plant-plant
interactionson smaller subplots (Kershaw & Looney
1985; Reed et al. 1993), (2) increasedvariancedue to
small samplesize andthe associatedvariationin sample
composition (Reed et al. 1993), or (3) competitionfor
regenerationsites. At a small scale, plant-plantinteractions are importanton Southeasternpiedmontoutcrops
(Sharitz& McCormick 1973; Meyer et al. 1975), but
competitionand niche differentiationmay be unimportant in limestone pavement communities of Britain
(Silvertown 1983).
After 100-m2 plot variation is partitionedout, the
environmentalvariablesthatcorrelatewith composition
at the 1-m2 scale are generally different from those
importantat 100 m2.This agreeswith Reed et al. (1993)
and Castroet al. (1986) who found differentpredictive
parametersfor different size plots. While slope and
potentialsolar radiationare importantregion-wideand
within certainbedrocktypes on 100-m2plots, they are
rarely correlatedwith variation among 1-m2 subplots
(although they do vary at this scale). The relative
importanceof soil variables also differ between plot
sizes.
719
- High-elevation rock outcrop vegetation -
Gradientcomparisonsamong bedrocktypes
Comparisonswithpatterns on other outcrops
The consistent relationshipsof elevation, potential
solar radiationand aspect to composition across bedrocktypes echoes the generalimportanceof these gradients for Southern Appalachian community composition. Elevation, a complex gradientthat parallels temperature, moisture, and soils gradients, is usually a
dominant environmentalcorrelate with vegetation in
mountainous terrain,including the Southern Appalachians (e.g. Whittaker1956; Day & Monk 1974; Lindsay & Bratton1979; Golden 1981; Callawayet al. 1987;
McLeod 1988). Further,maximumelevation in a range
may have influencedhigh-elevationspecies persistence
duringthe warmestpostglacial times (Whittaker1956;
White et al. 1984; White & Miller 1988). The second
majoroutcropgradientcorrespondsto topographic/moisture gradients,generally describedvia indices derived
from topographicposition, aspect, or exposure (Whittaker1956;Day & Monk 1974;Callawayet al. 1987), or
measuresof potentialsolarradiationandaspect(Lindsay
& Bratton1979; McLeod 1988).
In mountainforests, soil variationis often closely
linked with aspect, slope and topographic position
(Mowbray & Oosting 1968; Jenny 1980; c.f. Allen &
Peet 1990). In this study, compositional relationships
with soil were found to change with geology, but no
consistent relationships with aspect, slope and topographic position were found. Geology influences soil
chemistry and drainage as well as correlations with
slope position. Analogous inconsistencies in correlations of slope positionandaspectwith SouthernAppalachian forest soil propertieshave been found between
soils derivedfrom graniticbiotite gneiss andthose from
highly siliceous sandstoneand siltstone (Losche et al.
1970).
On outcrops elsewhere, small-scale compositional
variationmost often relates to soil depth/soil moisture
gradientstypically consideredto representsuccessional
sequences (e.g. Oosting & Anderson 1937, 1939;
Quarterman1950; Burbanck& Platt 1964; Sharitz &
McCormick1973;Silvertown1983;Ohsawa& Yamane
1988; Collins et al. 1989). The importanceof the soil
depthgradienthere agrees with these findings.
Previous comparisonsof vegetation on outcropsof
different bedrock types have attributeddifferences to
geology (Ware1990;Fuls et al. 1992), disturbance(Fuls
et al. 1992), and combinationsof moisture,aspect and
slope (Fuls et al. 1992). Compositionalvariationamong
outcropsites on particularbedrocktypeshas been attributed to differencesin elevation (Ashton & Webb 1977;
Maycock& Fahselt 1992), solarradiation,slope, aspect,
or exposure (Winterringer& Vestal 1956; Ashton &
Webb 1977;Whitney& Moeller 1982;Makirinta1985),
moisture(Maycock& Fahselt 1992), degree of shading
(e.g. Quarterman1950), substrate texture (Burgman
1987; Maycock & Fahselt 1992), geographicposition
(Burgman 1987) and soil chemistry (Jarvis 1974;
Makirinta 1985). In Southern Appalachian outcrops,
strong relationships between composition and elevation, slope, aspect and relatedparameters,both within
and among bedrock types, resemble patternson outcrops in other mountainouslocalities or areas of high
relief (e.g. Winterringer& Vestal 1956;Ashton& Webb
1977; Whitney & Moeller 1982; Maycock & Fahselt
1992; John & Dale 1990). This contrastswith results
from outcropswhich occur in localities lacking strong
local relief such as those of the nearby Southeastern
piedmont where such parametersare weakly, if at all,
relatedto composition.
As insular habitats, outcrops are rare in the landscape and determinationof general patternsbetween
compositionand environmentmay requirestudyover a
wide geographic range. However, study of vegetation
Table 5. Percentages of variation of species composition on 1-m2 subplots accounted for by (1) variation among 100-m2 plots,
(2) site parameters measured for 1-m2 subplots, (3) variation shared between the two plot sizes. Based on partial CCA analyses.
% of variationexplained
100-m2 standscores
Complete data set
Amphibolite
Metagabbro
Meta-arkose
Whiteside quartz-diorite
Metagraywacke
AnakeestaSlate
Microenvironment
100-m2stand scores
+ microenvironment
Total
3.6
7.3
2.2
13.1
8.8
13.2
8.8
8.8
11.5
19.0
14.0
22.7
17.0
19.3
14.4
19.4
3.5
6.7
5.1
4.6
3.9
12.8
26.3
42.6
30.9
32.7
29.8
51.2
720
Wiser, S.K. et al.
over a wide geographic extent may result in geographic
variation induced by either dispersal limitation or largescale environmental shifts obscuring patterns that are
clear and consistent at smaller scales. Owing to their
rarity and isolation, insular habitats have discontinuous
distributions along environmental gradients. Thus, differences between locations may be pronounced and
consistent microscale patterns may be obscured. Our
study provides an approach to overcome some of these
problems. We overcame the obscuring influence of largescale geologic variation by partitioning our data by
bedrock type. In other localities or on other types of
habitat islands useful partitions might be geographic
position or elevation (e.g. Peet 1981). The application of
partial ordination allowed us to segregate aspects of
small-scale (lm2) pattern into those related to site
(100 m2) differences and those related to microhabitat
(1 m2). Strong spatial autocorrelation of composition of
insular habitats has important conservation implications. For the outcrops, a reserve strategy must include
sites from both a range of bedrock types and a range of
geographic locations to be sufficiently representative.
Study of vegetation of insular habitats by use of samples
collected at multiple scales over wide geographic ranges,
together with strategic application of analytical techniques offers an opportunity to continue to advance our
knowledge and understanding of how environmental
factors and dispersal processes combine to determine
the distribution and abundance of plant species of insular vegetation.
Acknowledgements. We thankR.B Allen, D.W. Larsonand
two anonymousreviewers for comments on earlierdrafts of
themanuscript.R.B. Allen helpedwith field datacollection.P.
Aune helped process soils and enter data. A. Weakley, A.
Radford,J. Nekola, and R. LeBlond helped with plantidentification. G. Hall provided a computerprogramto calculate
potentialsolarradiation.We especially appreciatethe technical and logistic support of the National Park Service, the
National Forest Service, Highlands Biological Station, the
North CarolinaDivision of Parks and Recreation,the North
CarolinaandTennessee NaturalHeritagePrograms,Grandfather Mt. Inc., Uplands Field Research Laboratory,and Mrs.
Alvera Henley. This materialis based on researchsupported
by a National Science Foundation GraduateFellowship to
SKW,the CatherineH. BeattieFellowshipof the GardenClub
of America, the North Carolina Nature Conservancy, the
NorthCarolinaWildflowerProtectionSociety,theNorthCarolina Botanical Garden, and the H.V. Wilson Fund of the
Departmentof Biology, University of NorthCarolina.
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Received 3 June 1995;
Revision received 16 February1996;
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