A Discriminant-Function 

Forest Service Approach to Ecological 

Northeastern Forest 

Experiment Station Site Classification in 

Research Paper NE-686 Northern New England 

James Fincher 

Marie-Louise Smith 
Abstract 

Describes one approach to ecologically based classification of upland forest 

community types of the White and Green Mountain physiographic regions. The 

classification approach is based on an intensive statistical analysis of the 

relationship between the communities and soil-site factors. Discriminant functions 

useful in distinguishing between types based on soil-site factors most strongly 

correlated with their distribution over the landscape are presented. 

The Authors 

JAMES FINCHER, ecologist, received a B.S. degree in forest resource management 

in 1988 from the University of Montana and an MS. degree in soil science in 1991 

from the University of New Hampshire. He is an ecologist with the USDA Forest 

Service on the Chatham Area, Tongass National Forest, Sitka, Alaska. 

MARIE-LOUISE SMITH, research ecologist, received a B.S. degree in natural 

resources in 1989 from the University of Michigan, and an M.S. degree in forestry in 

1992 from the University of Wisconsin Madison. She joined the Northeastern Forest 

Experiment Station in 1990 and has been developing methodologies for ecologically 

based forest site classification at the Station's Forestry Science Laboratory, in 

Durham, New Hampshire. 

Manuscript received for publication 21 July 1993 

USDA FOREST SERVICE 

5 RADNOR CORP CTR STE 200 

P.O. BOX 6775 

RADNOR, PA 1 9087-8775 

February 1994 
Introduction 

Qualitative investigations of the ecological and productive 

potential of forest land in northern New England from soil, 

topographic, and vegetative characteristics have a long 

history (Tuckerman 1860; Bray 191 5; Nichols 191 8; Adams 

et al. 1920; Heimberger 1934; Hazard 1937; Stanley 1938; 

Westveld 1951, 1952, 1954). Only more recently has there 

been a more quantitative approach to ecological site 

characterization, primarily in terms of productivity related to 

suites of site and soil characters (Post and Curtis 1970; Leak 

1976,1978,1980,1982). 

Leak (1982) discussed the conceptual model upon which 

classification of communities in northern New England should 

be based. He enumerated physiographic region, climate 

(elevation, latitude), mineralogy of the glacial drift, and 

habitat, defined on the basis of soil substrate, as the 

hierarchy best able to account for differences in distribution of 

vegetation in northern New England. In an analysis of the 

soil- vegetation relationship in the southern White Mountains, 

Leak demonstrated that habitats distinguished based on land 

form, soil materials, and vegetation differed in a quantitatively 

significant manner with respect to stand composition, 

understory vegetation, biomass, volume, and diameter 

development by species. These findings indicate that there 

are distinct relationships between soil-site factors and forest 

plant communities in northern New England and that further 

investigation using quantitative methods to determine the 

strength of this correlation is warranted. 

Quantitative analysis of patterns of soil-site factors in 

relationship to plant communities has proven valuable in the 

development of ecological classifications in similar ecological 

regions in the province of New Brunswick, Canada (Zelazny 

et al. 1989) and in the Lake States (Pregitzer and Barnes 

1984; Spies and Barnes 1985; Host et al. 1988). This 

methodology is being used to help delineate units of land with 

a unique combination of potential natural community, soil, 

landscape features, and climate, and which differ from other 

units in their ability to produce vegetation and respond to 

management. Such an approach should allow more accurate 

ecological classification of sites, enhance our understanding 

of successional pathways of disturbed forest environments, 

and contribute iriformation that can be used to develop 

management strategies for forested lands predicated on a 

site's fullest, most natural potential. 

The objectives of this study were to: 1) develop a preliminary 

classification of forest plant communities found on lithic, 

basal till, ablation till, and outwash parent materials at similar 

latitudes across the White and Green Mountains of northern 

New England; and 2) identify the site and soil-physical factors 

that best discriminate between communities delimited by this 

classification across and within these two physiographic 

regions. 

Study Area 

Lull's (1968) published physiographic regions (Fig. I), 

adapted from Fenneman (1938) for the New England and 

adjacent states, divide New Hampshire and Vermont into five 

principal physiographic regions. Sampling was conducted on 

the Bartlett and Hubbard Brook Experimental Forests and 

surrounding areas in the White Mountain region and on the 

Middlebury and Rochester Ranger Districts of the Green 

Mountain National Forest within the Green Mountain Region 

(Fig. 2). 

Landscapes in both regions reflect the influence of glaciation. 

The major landforms have been shaped by erosional 

processes, but the soils of both regions have weathered 

primarily from a thin mantle of glacial drift of mostly Iota1 

origin. Glacial till consisting of a mixture of boulders, stones, 

sand, silt, and clay is the dominant soil parent material 

located within the study area, though glacial outwash and 

sediments are common in valleys. The soils on the rolling 

hilly lower landscapes, near streams, generally are without 

pan layers, while those at higher elevations and on smooth 

elliptical landforms usually have compact till layers in the 

substratum (Driers and Vieira 1977). Although the glacial and 

soil-forming processes over the study areas are similar, soil 

mineralogy and characteristics differ. Soils of the Bartlett area 

are weathered primarily from granitic drift characterized by 

coarse texture and low fertility. Soils of the Hubbard Brook 

area are weathered from glacial drift derived from crystalline 

schist, are somewhat more fertile, and have a more loamy 

texture. Gneiss, mica schist, and quartzite are the primary 

components of the bedrock and drift from which soils have 

weathered in the study area in Vermont. Leak (1 978) 

presented evidence that species composition and site index 

for a given habitat or type vary among glacial drifts with 

different mineralogies. 

Methods 

Field Procedures 

A total of 150 upland northern hardwood stands were 

sampled in 1989. Stands sampled must have met the 

following criteria: 1) The sample stand must have been 

located on lithic, basal till, ablation till, or outwash parent 

material; 2) The site must have been relatively undisturbed 

and contain predominantly tolerant species. Areas with a 

recent history of cutting or which appeared to have been 

cultivated or pastured at any period were omitted. Areas that 

represented obvious ecotones were avoided; 3) Plot 

locations ranged in elevation from 21 5 to 800 m. 

One 500-m2 (1 2.5-m-radius) circular plot was established in 

each suitable stand. The absolute cover, the percentage of 

the ground surface covered by the live foliage area of a plant 

species, was estimated for all vascular plant species on the 

sample plot. Cover values were estimated to the nearest 1 

percent for species with less than 10 percent total cover, and 

to the nearest 5 percent when total cover exceeded 10 

percent. 

The canopy was divided into cover layers on the basis of 

plant form, consisting of dominant I codominant, 

intermediate, and seedling /sapling tree species, tall and low 

shrubs, ferns, forbs, grasses, and mosses. Tree species that 
Figure l .-Major physiographic regions of Vermont and 

New Hampshire. 

were more than 23 cm in diameter at breast height (dbh) 

were considered as dominants / codominants; those ranging 

from 3.7 m in height to less than 23 cm dbh were 

intermediates; and coniferous species between 15 cm and 

3.7 m in height were considered as seedlings / saplings, as 

were deciduous species between 30 cm and 3.7 m in height. 

Different minimum heights were used because survival rates 

differ between conifer and deciduous seedlings (Leak et al. 

1987; Leak and Wilson 1958). 

A soil profile was described and classified using standard soil 

survey procedures (Soil Survey Staff 1981). Depth of pits 

generally was to 100 cm unless a restrictive layer was 

encountered. Samples of the C horizon were collected and 

analyzed for particle-size distribution using wet-sieving 

procedures. The samples were sieved into five size classes: 

very coarse sand (2 to 1 mm), coarse sand (1 to 0.5 mm), 

medium sand (0.5 to 0.25 mm), fine to very fine sand (0.25 to 

0.05 mm), and silt/clay (< 0.05 mm). Table 1 lists the soil-site 

factors measured at each plot. As the focus of this study was 

on field-identifiable characteristics of both vegetation and soil, 

no chemical analyses were performed. 

Numerical Analysis 

Data analysis was divided into the following procedures: 

1) Stands were classified using the two-way indicator-species 

analysis, TWINSPAN ( Hill 1979a), a polythetic divisive 

technique. TWINSPAN emphasizes differential species and 

produces an ordered samples X species matrix designed to 

show sharp relief between groups of species or samples. 

Ideally, a differential species is one with clear ecological 

preferences so that it s presence can be used to identify 

particular environmental conditions. 

2) Stands were ordinated using detrended correspondence 

analysis, DECORANA (Hill 1979b). TWINSPAN groups were 

examined in the DECORANA ordination space to evaluate 

within-group compositional consistency and to facilitate 
NORTHERN HALF 

EXPERIMENTAL FOREST 

HUBBARD BROOK 

EXPERIMENTAL FOREST 

Figure 2.-The study area. 

Table l .-Soil-site factors measured. 

Soil-site factor Unit of measurement 

Slope Percent 

Aspect ~e~rees-azimuth 

Elevation Meters 

Percent bare ground Percent plot surface area 

Percent surface boulders Percent plot surface area 

Parent material Granite, schist 

Texture C horizon Percent in 2 to 1 mm, 1 to 0.5 

mm, 0.5 to 0.25 mm, 0.25 to 

0.05 mm, and c 0.05 mm 

size classes 

Soil drainage class VP=l, P=2, SP=3, MW=4, 

W=5, EW=6 

Depth to impermeable layer Centimeters 

Organic-matter depth Centimeters 

Depth to mottling Centimeters 

Rooting depth Centimeters from top of 

1 

mineral soil 

determination of environmental gradients that influence the 

distribution of community types. 

3) The relationship of soil-site factors to the community types 

identified through classification and ordination was analyzed 

by linear discriminant analysis, a statistical technique in 

which linear combinations of variables are used to distinguish 

between two or more categories or cases. The variables 

"discriminate" between groups of cases and predict into 

which category or group a case falls based on the values of 

those variables (Norusis 1985). To some extent, ecological 

studies violate the assumptions of this predictive procedure. 

For example, there may be prediction bias if the number of 

independent variables is large relative to sample size or 

when multivariate normality cannot be assumed (see Verbyla 

1986). However, this limitation does not diminish the 

descriptive value of the analysis. Discriminant analysis 

followed the procedures described in Wilkinson (1988). 

Results and Discussion 

TWINSPAN classification, which is based on the cover 

attributes of plant species, resulted in the identification of 

eight forest-community types. Community- type names were 

derived by denoting the dominant tolerant tree species. 

Dominant understory species were included in the names of 

two types because they were found almost exclusively in 

those two communities. Names and abbreviations for 

community types are listed in Table 2. TWINSPAN 

classification was effective in displaying apparent community 

types among the forest stands sampled. However, it did not 

indicate whether the samples within the groups and between 

the groups occupy similar ecological space. DECORANA 

analysis allows visualization of the similarity of samples and 

inference of the environmental gradients associated with their 

distribution. The first and second axes of the detrended 

correspondence analysis ordination of samples accounted for 

61 and 35 percent of the variation in sample DECORANA 

ordination scores. Rooting depth (r=0.42, PC 0.001) and 

elevation (k0.59, P< 0.001) had the highest correlations with 

axes 1 and 2, respectively. A mosaic diagram was 

constructed by plotting these two axes, showing the general 

relationship among rooting depth, elevation, and community 

types (Fig. 3). Rooting depth decreases from the origin of 

axis 1, with elevation increasing from the origin of axis 2. 

Table 2.--Community types and abbreviated codes 

referred to in the text 

Abbreviated code Community type 

FAGRIACSNARTR Fagus grandifolia/Acer 

saccharum/Arisaema 

triphyllum 

FAG RIACSA F. grandifo/ia/A. saccharum 

FAGRIACSNPIRU F. grandifolidA. 

saccharum/Picea rubens 

FAGRKSCA F, grandifoli~suga 

canadensis 

TSCA T. canadensis 

TSCNPI RU T. canadensis/P. rubens 

PIRUIABBA P. rubens/Abies balsamea 

PI RUIABBANAAN P. rubens/A. 

balsame~accinium 

angustifolium 
x FAGR/ACSA/ARTR 

x FAGRrrSCA 

4 TSCA 

+ TSCA/PIRU 

PIRUIABBA 

- PIRUIABBANAAN 

0 100 200 300 400 500 600 

AXIS 1 

Figure 3.-Location of 147 study plots with respect to DECORANA axes 1 and 2. Axis values are expressed in 

units of standard deviations of eigenvectors x 100. Symbols represent community type membership identified 

in TWINSPAN analysis. 

Relationship Between Vegetation and Soil-Site Factors 

In the field, the transition between conifer-and 

hardwood-dominated community types was distinct, while the 

transition between hardwood community types tended to be 

more gradual. This relationship is illustrated in the graphic of 

DECORANA scores, which suggest that the species 

composition of the hardwood community types is more 

homogeneous than that of the conifer community types. 

The relationship between vegetation and soil-site factors was 

examined using two approaches. The first consisted of a 

simple comparison of soil taxonomic units and the community 

types. In the second approach, direct discriminant function 

analysis was used to determine the relationship between 

community types and soil-site factors. As stated previously, 

the focus of this study was on field-identifiable characteristics 

of both vegetation and. site, so physical characteristics were 

used to analyze soil-site and community-type relationships. 

Soil taxonomic units and community types. Tables 3 and 4 

show the distribution of sample stands within each 

community type across the study area by parent material and 

soil taxonomic group. The pattern of sample stand 

distribution indicates that communities are responsive to the 

influence of soil and site characteristics expressed in this 

manner; however, the variability in the range of distribution 

suggests that the community types do not respond in a 

uniform manner to soil-site factors expressed at this scale. 

Table 3.-Distribution of community types by parent material 

Till 

Community type Firm Loose Compact Lithic Outwash Other Total 

FAG R/ACSNARTR 5 2 12 1 - 3 23 

FAG RIACSA 8 4 11 - 6 - 29 

FAGR/ACSA/PIRU 4 2 6 2 1 1 16 

FAG RITSCA 7 3 7 1 3 4 25 

TSCA - 1 2 4 2 - 9 

TSCA/PIRU 2 3 5 4 4 1 19 

PIRU/ABBA 3 - 2 12 4 - 21 

PI RU/ABBA/VAAN - - - 5 - - 5 

Total 3 1 15 45 29 20 7 147 
Table 4.-Occurrences of the community types by soil subgroups, In percent 

Community type 

FAGR FAGR FAGR FAGR TSCA TSCA PlRU PlRU 

ACSA ACSA ACSA TSCA PlRU ABBA ABBA 

Soil ARTR PlRU VAAN 

n=23 n=29 n=16 n=25 n=9 n=19 n=21 n=5 

Spodosols 

Typic Haplorthods 35 42 31 56 33 63 24 - 

Typic Fragiorthods 4 29 13 16 23 22 - - 

Typic Fragiaquods - - - 4 - - - - 

Aquic Haplorthods - 7 - 12 - - 10 - 

Aquic Fragiorthods 27 3 6 8 - - 10 - 

Lithic Haplorthods 4 - 6 - 44 5 43 80 

lnceptisols 

Typic Fragiochrept 9 3 13 4 - - - - 

Typic Dystrochrept 4 13 18 - - - - - 

Aquic Fragiochrept 9 - 6 - - - - - 

Aquic Dystrochrept 4 - - - - - - - 

Fluventic Dystrochrept 4 3 - - - 5 - - 

Lithic Dystrochrept - - 6 - - 5 14 20 

Correspondence between the various levels of soil taxonomy 

(Soil Survey Staff 1975) and the eight community types is 

highly variable. Eight community types identified in this study 

occurred on 2 soil orders, 3 suborders, 5 great groups, 12 

subgroups, and 40 families. Eighty-six of the soils sampled 

belong to either coarse-loamy, mixed; loamy-skeletal, mixed; 

or sandy, mixed soil families. 

The variability in the occurrence of the community types on 

soil subgroups reflects the variability displayed in the 

distribution of community types by parent material. The 

distribution of hardwood-dominated community types is more 

broad than for conifer-dominated type's. The latter tend to 

occur primarily on spodosols, but may be found on 

inceptisols developed from outwash or lithic parent materials. 

For example, the PlRU I ABBA / VAAN community type was 

found only on lithic sites. Soil depth to restrictive layer seems 

the soil-site factor that best accounts for the relationship 

between soil taxonomic units and conifer community types. 

Inference could also be made concerning the relationship 

among elevation, spodic development, and conifer 

community types. The relationship between soil taxonomic 

units and hardwood community types is not so obvious. The 

hardwood community types are broadly distributed, 

suggesting two possible hypotheses: it may be that hardwood 

community types occur on a broad continuum not strongly 

associated with physical soil-site factors, or they are more 

responsive to soil-site factors not discernible at the soil 

subgroup level. 

These inferences on the relationship between soil subgroups 

and plant community types are primarily qualitative and 

reflect the modest utility of soil-subgroup classification to 

distinguish the vegetation potential of forested sites. 

Discriminant functions and community types. 

Discriminant-function analysis (Wilkinson 1988) identified 

eight soil-site factors from among those listed in Table 1 

(significant at P < 0.05), as the most effective predictors of 

community type membership (Table 5). However, 

simultaneous comparison of the mean values of the soil-site 

factors, by community type (Table 6), suggests that there is 

no simple relationship between community types and soil-site 

factors. 

Using a pooled variance covariance matrix, seven 

discriminant hrnctions were obtained. Each function 

represents a dimension along which the community types 

Table S.-Soil-site factors that best discriminate among 

the eight community types 

Soil-site factor F value Significance 

Lithic 14.448 0.000 

Elevation 13.435 0.000 

Soil depth to impermeable layer 8.31 1 0.000 

% exposed bedrock 8.1 89 0.000 

% moss-covered bedrock 7.168 0.000 

Rooting depth 5.398 0.000 

% coarse fragments in rooting 2.91 1 0.007 

zone 

Organic-matter depth 2.584 0.01 7 
Table 6.-Mean values of soil-site factors by community type 

Community type 

Soil-site factor FAGR FAGR FAGR FAGR TSCA TSCA PlRU PlRU 

ACSA ACSA ACSA TSCA PlRU ABBA ABBA 

ARTR PlRU VAAN 

Lithic (%) 4 0 13 0 4 15 62 100 

Elevation (m) 480 490 51 2 394 308 409 625 585 

Depth to impermeable layer (cm) 86 1 00 85 106 73 89 54 3 1 

Organic-matter depth (cm) 12 14 14 16 I1 19 18 13 

Rooting depth (cm) 58 62 60 63 47 50 38 32 

Coarse fragments rooting zone j%) 24 24 17 25 32 19 14 20 

Moss-covered bedrock (%) 0 0 1 0 2 1 3 7 

Exposed bedrock (%) 0 0 0 0 4 1 1 9 

differ. The first three of these functions account for the 

majority of discriminating power (see Tabachnick and Fidell 

1989), with no additional information forthcoming from the 

remaining functions. The meaning of the significant functions 

can be inferred from the pattern of correlation between the 

soil-site factors and the first three functions (Table 7). 

Soil-site factors that display the highest correlation with each 

function can be viewed as representing a gradient important 

in determining plant-community distribution. Soil-site factors 

with correlations greater than 0.55 are considered the most 

impoftant factors in determining this distribution (see Comrey 

1973). Function 1 represents a gradient primarily associated 

with the increasing likelihood of a community type occurring 

on a lithic site as soil depth decreases with an increase in 

elevation. Function 2 represents a gradient associated 

primarily with increasing elevation. Function 3 represents a 

gradient of decreasing depth of organic matter. 

Community types were ordinated along the environmental 

gradients determined by the eight soil-site factors by the 

calculation of canonical discriminant-function group mean 

scores by community type. Unstandardized group 

classification coefficients and constants were used to assign 

community type membership to a sample based on the eight 

soil-site factors. Classification accuracy of samples ranged 

from 67 percent correctly classified for the TSCA community 

type to 20 percent correctly classified for the 

PiRU/ABBA/VMN community type, with an average correct 

classification of 42 percent. The simple numerical probability 

of guessing the correct community type is 12.5 percent. 

Discriminant-function analysis computed for a stratified data 

set, simulating the hierarchical breaks produced in the 

polythetic divisive groupings delimited by TWINSPAN 

analysis, increased the average probability of correctly 

classifying samples at the community type level from 42 to 47 

percent (Table 8). One canonical discriminant function, 

standardized by conditional within-group standard deviations, 

was computed for each division (Table 9). The interpretation 

of these functions was inferred from the pattern of pooled 

within-group correlations between the soil-site factors and 

each function. Correlation between soil-site factors and each 

function that was greater than 0.55 (accounting for 30 

percent overlapping variance) was interpreted as identifying 

the most significant factors associated with the hierarchical 

distribution of the community types. 

The function for Division 1 identifies 11 soil-site factors as 

effective discriminators between the hardwood- and 

softwood-dominated community types. The likelihood of the 

community types occurring on a lithic site displayed the 

highest correlation (r = -0.76) Four percent of 

hardwood-dominated stands sampled were found on lithic 

sites compared to 45 percent for softwood-dominated stands. 

Lithic sites tend to be somewhat nutrient poor and seasonally 

saturated or droughty depending on slope position. 

Evergreen foliage, shallow rooting systems, and 

Table 7.-Pooled within-group correlation between sil-site factors and canonical 

discriminant functions 

Soil-site factor Function 1 Function 2 Function 3 

Lithic 0.89 0.1 9 -0.21 

Soil depth to impermeable layer -0.61 0.01 0.04 

Elevation 0.57 -0.71 0.18 

Percent moss-covered bedrock 0.47 0.22 0.44 

Rooting depth -0.47 0.22 0.44 

% exposed bedrock 0.44 0.52 0.36 

% coarse fragments rooting zone -0.23 0.27 0.23 

Organic-matter depth 0.08 -0.06 -0.55 
Table 8.--Summary and comparison of community classification results using significant soil-site factors as the 

classification function coefficients on an unstratified data set and on a data set stratified by TWINSPAN divisions 

Unstratified 

Community type % classified correctly 

FAG WACSNARTR 30 

FAGRIACSA 41 

FAG WACSNPI RU 25 

FAG RjTSCA 48 

TSC A 67 

TSCNPI RU 42 

PIRUIABBA 57 

PIRUIABBANAAN 20 

Stratified by TWINSPAN divisions 

Community type % classified correctly 

FAGR/ACSNARTR 57 

FAGRIACSA 43 

FAG RIACSNPI RU 14 

FAG RITSCA 67 

TSCA 50 

TSCNPIRU 50 

PIRUIABBA 43 

PIRUIABBANAAN 18 

Average 42 Average 47 

cold-hardiness of conifers give sites a c,ompetitive advantage. 

Rooting depth (r = 0.53), depth to impermeable layer (r = 

0.50), and percent exposed bedrock (r = -0.36) are the next 

highest correlated soil-site factors, and are related to or 

influenced by soil depth. 

Six soil-site factors were identified as effective discriminators 

between the FAGRIACSNARTR, FAGRIACSA, and 

FAGR/ACSA/PIRU community types and the FAGWSCA 

types differentiated at Division 2. The Bartlett area (r = -0.72) 

and elevation (r = 0.60) had the highest correlations with this 

function. FAGRIACSNARTR and FAGRIACSNPIRU 

community types were not encountered during sampling in 

the Bartlett area; FAGRjTSCA was found primarily in the 

Bartlett area. The relationship between community types and 

the other four soil-site factors, percentage of 0.25- to 

0.05-mm sand (r = -0.40), percentage of 0.50- to 0.25-mm 

sand (4 = -0.37), the Vermont area, and the percentage of 

silt/clay suggest why this may be the case. Bartlett soils are 

weathered primarily from granitic drift and generally are more 

coarse than soils weathered from the tills derived from 

metamorphosed mudstones and sandstones found in the 

Hubbard Brook and Vermont sampling areas. Soils of the 

TSCNFAGR community type generally are more coarse than 

those associated with the other three community types. 

Texture influences water holding capacity and the percentage 

of humus and nitrogen present. A coarse textured soil may 

contain less organic matter and nitrogen than one of a finer 

texture (Brady 1984). This suggest that the FAGRITSCA 

community type occupies sites that are less fertile, and 

possibly limited by moisture availability, characteristics 

common in the Bartlett area. The low species diversity in the 

community types associated primarily with the Bartlett area 

seems to support this observation. Marchand (1 987) noted 

that hemlock usually occupies the less fertile sites among the 

hardwood-dominated stands. 

Six soil-site factors were identified as effective discriminators 

between the TSCA and TSCNPIRU community types and 

the PIRUIABBA and PIRUIABBWAAN types at Division 3. 

Elevation (r = -0.95) had the highest correlation with this 

function. Conifers segregate themselves distinctly along the 

elevation gradient (Cogbill and White 1991); this relationship 

is demonstrated in this function. As a general rule in 

conifer-dominated communities, hemlock dominates at lower 

and midslope elevations, while red spruce dominates the 

shallow, rocky midslope to upperslope positions, eventually 

giving way to balsam fir at higher elevations. The other five 

soil-site factors correlated with this function are strongly 

related to the landforms associated with increasing elevation. 

The percentage of moss-covered (r = 0.96) and exposed 

bedrock (r = 0.72) are the soil site factors that act as effective 

discriminators between the FAGRIACSNARTR and 

FAGRIACSA community types and the FAGRIACSNPIRU 

types at Division 4. Red spruce is characteristically found on 

sites with shallow, rocky soils. However, overall classification 

accuracy for the FAGRIACSNPIRU samples was poor. 

Four soil-site factors discriminate between the TSCA and 

TSCAIPIRU community types at Division 5: organic matter 

depth (r = -0.40), percent coarse fragments in the rooting 

zone (r = 0.39), elevation (r = -0.38), and percent exposed 

bedrock (r = 0.36). The correlations between these factors 

and the function are less than the critical value of 0.55; 

however, 89 percent classification accuracy suggests that the 

interaction between these factors is significant enough to 

allow good discrimination between the community types. 

Comparison of the unstandardized means for these four 

soil-site factors indicates that the TSCA community type 

generally occupies sites with a higher percentage of exposed 

bedrock and coarse fragments in the rooting zone, while the 

TSCNPIRU community type is found at higher elevations 

with a greater depth of organic matter. 

The percentage of exposed bedrock (r = 0.89) and 

moss-covered bedrock (r = 0.71) are effective discriminators 

between the PIRUIABBA community types at Division 6. The 

PIRUIABBANAAN type generally has a higher percentage of 

exposed and moss-covered bedrock, occupying sites 

typically found on ridge and mountain summits. 

Two soil-site factors, depth to mottles (r = 0.88) and the 

Bartlett area (r = -0.77), discriminate between the 
Table 9.--Soil-site factors that best discriminate between the polythetic divisive groupings 

produced by TWINSPAN analysis -- - - - 

Pooled 

Soil-site factor Function 1 Function 2 within-group F value Significance 

correlation 

Division 1 : Northern Hardwood vs. Conifers 

Lithic 

Rooting depth 

Depth to impermeable layer 

% exposed bedrock 

Vermont 

Compact till 

Firm till 

Bartlett 

% moss-covered bedrock 

Organic-matter depth 

% coarse fragments rooting zone 

Constant 

Division 2: FAGRIACSNARTR, FAGRIACSA, 

and FAGRIACSAPIRU vs. FAGR/TSCA 

Bartlett 

Elevation 

% 0.25 mm sand 

% 0.5 rnm sand 

Vermont 

% siltlclay 

Constant 

Division 3: TSCA and TSCNPIRU vs. 

PIRUIABBA and PIRUIABBANAAN 

Elevation 

Depth to impermeable layer 

Lithic 

Rooting depth 

No impermeable layer 

% coarse fragments rooting zone 

Constant 

Division 4: FAGRIACSNARTR and 

FAGRIACSA vs. FAGRIACSAIPIRU 

% moss-covered bedrock 

% exposed bedrock 

Constant 

Division 5: TSCA vs. TSCNPIRU 

Organic-matter depth 

% coarse fragments rooting zone 

Elevation 

% exposed bedrock 

Constant 

- - 

Continued 
Table 9.4ontInued 

Soil-site factor 

Pooled 

Function 1 Function 2 within-group F value Significance 

Division 6: PIRUIABBA vs. PIRUIABBWA 

% exposed bedrock 0.023 0.246 0.89 9.546 0.005 

% moss-covered bedrock 0.012 0.070 0.71 6.126 0.021 

Constant -0.723 -2.620 

Division 7: FAGWACSNARTR vs. FAGRIAC 

Mottling depth 0.079 0.127 0.88 11.017 0.002 

Bartlett -1.348 0.21 5 0.77 8.425 0.005 

Constant -1.295 -2.575 

FAGRIACSNARTR community types and the FAGRIACSA during sampling in the Bartlett area. This interaction of 

types at Division 7. Examination of mean depth to mottling mottling depth and community distribution along with our 

indicates that the FAGRIACSNARTR community type is knowledge of soils within the study area suggest that the 

more likely to occur on sites with wetter soil moisture FAGWACSNARTR community type is strongly related to soil 

regimes. The FAGWARTWACSA type was not encountered moisture, mineralogy, andlor texture. 

Table 10.--Schematic of decision rules for assignment of samples to site types 

Division 1 Northern Hardwood vs. Conifers 

If value of Function 1 > Function 2 then Division 2 

If value of Function 2 > Function 1 then Division 3 

Division 2 FAGWACSNARTR 

FAG FUACSA vs . FAG RITSCA 

FAGWACSAJPIRU 

If value of Function 1 > Function 2 then Division 4 

If value of Function 2 >Function 1 then FAGRITSCA 

Division 3 TSCA PIRUIABBA 

TSCNPIRU vs. PIRUIABBANAAN 

If value of Function 1 > Function 2 then Division 5 

If value of Function 2 > Function 1 then Division 6 

Division 4 FAG FUACSAIARTR 

FAGRlACSA vs. FAGWACSNPIRU 

If value of Function 1 > Function 2 then Division 7 

If value of Function 2 > Function 1 then FAGWACSNPIRU 

Division 5 TSCA vs. TSCNPIRU 

If value of Function 1 > Function 2 then TSCA 

If value of Function 2 > Function 1 then TSCAlPlRU 

Division 6 PIRUIABBA vs. PIRU/ABBWAAN 

If value of Function 1 > Function 2 then PIRUIABBA 

If value of Function 2 > Function 1 then PIRU/ABBWAAN 

Division 7 FAG RIACSNARTR vs. FAGRIACSA 

If value of Function 1 > Function 2 then FACWACSNARTR 

If value of Function 2 > Function 1 then FAGWACSA 
Use of Discriminant Functions for 

Delineation of Site Types 

Use of the discriminant functions developed to distinguish 

between community types on the basis of soil-site characters 

can be expressed as a series of decision rules driven by the 

function solutions at any given divisional level (Table 10). 

Sample values of significant soil-site factors (elevation, 

rooting depth, etc.) identified for a given level are multiplied 

by the function coefficients for those variables listed in Table 

9 and then summed with their constant for that function. The 

function with the largest value at each level determines the 

next level to be computed until a classification of that sample 

into a community type is reached, i.e., there are no more 

functions to compute. 

Summary and Conclusions 

Discriminant-function analysis of the eight community types 

provided a view of the relationship of the community types to 

each other as a whole. However, simulating the hierarchical 

breaks produced in the polythetic divisive groups delimited by 

TWINSPAN analysis not only provided a modest increase in 

classification accuracy but also the opportunity to account for 

in greater detail the relationship between community 

distribution over the landscape and soil-site factors. This is 

an improvement over more general methods of interpretation 

of ordination axes which usually involve only simple 

correlation of soil and site factors with one or two complex 

axes, as in DECORANA. In TWINSPAN classification, each 

"break" or division produced is the product of a separate 

ordination for that data subset or cluster. Consequently, the 

various divisions at a given level may be focusing on different 

community gradients that are important for the individual data 

subsets rather than on a smaller segment of a single 

complex gradient. Discriminant-function analysis of the 

stratified data set provided an opportunity to assess the 

relative contribution of soil-site factors to the composition and 

distribution of communities defined in this way. 

The improvement in the classification accuracy provided by 

the stratification is associated primarily with the hardwood 

community types. Accuracy in classification of the conifer 

community types declined in all cases except one by the 

same stratification. Discriminant-function analysis of the first 

TWINSPAN division strongly favored the hardwood 

community types. Classification accuracy for hardwood types 

was 87 percent compared to 63 percent for conifer types. 

The mosaic diagram of DECORANA scores for axes 1 and 2 

allows visualization of the similarity of samples. The transition 

between hardwood community types is gradual, whereas the 

transition between conifer types is more distinct. This 

suggests that the environment occupied by hardwood types 

is less distinctive than that occupied by conifer types in 

physical soil-site factors. This within-group similarity would be 

maximized in discriminant-function analysis. Group 

assignment is based on the distance of the sample's 

canonical discriminant score from the canonical 

discriminant-function group mean scores. Probability of group 

membership is computed based on these distances and the 

sample is assigned to the group with the highest probability. 

Due to the variation in the conifer-dominated samples, it is 

highly likely that any such sample that overlaps the 

hardwood-dominated community type's ecological space will 

be closer to the hardwood group mean than the conifer group 

mean, leading to misclassification. The resulting modest 

classification accuracy for the conifer community types at this 

first division greatly influences the ultimate classification 

results. 

It should be noted that the interpretation of the classification 

accuracy probably is biased because the plots used to 

compute the canonical discriminant functions also were used 

in the determination of classification accuracy. The sample 

size of several of the community types was too small to 

conduct a bootstrap method of validation (Verbyla 1986). 

Therefore, classification of new samples from the study area 

would greatly enhance our understanding of the 

effectiveness of the classification function coefficients to 

predict group membership. 
Literature Cited 

Adams, C. C.; Burns, G. P.; Hankinson, T. L.; Moore, B.; 

Taylor N. 1920. Plants and animals of Mount Marcy, 

New York. Parts I, II, and Ill. Ecology. 1 : 71 -94, 204-233, 

274-288. 

Bray, W. L. 191 5. The development of the vegetation of 

New York State. Tech. Publ. 3. Syracuse, NY: New York 

State College of Forestry. 186 p. 

Cogbill, C. V.; White, P. S. 1991. The latitude-elevation 

relationship for spruce- fir forest and treeline along the 

Appalachian Mountain chain. Vegetation. 94: 153- 175. 

Comrey, A. L. 1973. A first course in factor analysis. New 

York: Academic Press. 235 p. 

Driers, R. W.; Vieira, F. J. 1977. Soil survey of Carroll 

County, New Hampshire. Washington, DC: U. S. 

Department of Agriculture, Soil Conservation Service, 

National Cooperative Soil Survey. 161 p. 

Fenneman, N. M. 1938. Physiography of eastern United 

States. New York: McGraw Hill. 71 4 p. 

Hazard, H. E. 1937. Plant indicators of pure white pine 

sites in southern New Hampshire. Journal of Forestry. 

35: 477-486. 

Heimberger, G. C. 1934. Forest-type studies in the 

Adirondack Region. Mem. 165. Ithaca, NY: Cornell 

University Agricultural Experiment Station. 122 p. 

Hill, M. 0.1979a. DECORANA-a FORTRAN program for 

detrended correspondence analysis and reciprocal 

averaging. Ithaca, NY: Cornell University. 

Hill, M. 0.1979b. TWINSPAN-a FORTRAN program for 

arranging multivariate data in an ordered two-way 

table by classification of the Individuals and attributes. 

Ithaca, NY: Cornell University. 

Host, G. E.; Pregitzer, K. S.; Ramm, C. W.; Lusch, D. P.;. 

Cleland, D. T. 1988. Variation in overstory biomass 

among glacial landforms and ecological land units in 

northeastern Lower Michigan. Canadian Journal of 

Forest Research. 18: 659-688. 

Leak, W. B. 1976. Relation of tolerant species to habitat In 

the White Mountains of New Hampshire. Res. Pap. 

NE-351. Upper Darby, PA: U. S. Department of Agriculture, 

Forest Service, Northeastern Forest Experiment Station. 

10 p. 

Leak, W. B. 1978. Relationship of forest vegetation to 

habltat on two types of glacial drift in New Hampshire. 

Res. Note NE-257. Broomall, PA: U. S. Department of 

Agriculture, Forest Service, Northeastern Forest 

Experiment Station. 5 p. 

Leak, W. B. 11 980. The influence of habitat on silvicultural 

prescriptions in New England. Journal of Forestry. 78: 

329-338. 

Leak, W. B. 1982. Habitat mapping and Interpretation in 

New England. Res. Pap. NE- 496. Broomall, PA: U. S. 

Department of Agriculture, Forest Service, Northeastern 

Forest Experiment Station. 28 p. 

Leak, W. B.; Solomon, D. S.; DeBald, P. S. 1987. 

Sllvicultural guide for northern hardwood types in the 

Northeast (revised). Res. Pap. NE-603. Broomall, PA: U. 

S. Department of Agriculture, Forest Service, Northeastern 

Forest Experiment Station. 36 p. 

Leak, W. B.; Wilson, R. W. 1958. Regeneration after 

cutting of old-growth northern hardwoods in New 

Hampshire. Stn. Pap. 103. Upper Darby, PA: U. S. 

Department of Agriculture, Forest Service, Northeastern 

Forest Experiment Station. 8 p. 

Lull, H. W. 1968. A forest atlas of the Northeast. Upper 

Darby, PA: U. S. Department of Agriculture, Forest 

Service, Northeastern Forest Experiment Station. 46 p. 

Marchand, P. J. 1987. North Woods: an inside look at the 

nature of forests in the Northeast. Boston, MA: 

Appalachian Mountain Club. 146 p. 

Nichols, G. E. 191 8. The vegetation of northern Cape 

Breton Island, Nova Scotia. Transactions of the 

Connecticut Academy of Arts and Science. 22: 79-98. 

Norusis, M. J. 1985. SPSS advanced statistics guide. New 

York: McGraw-Hill. 505 p. 

Post, B. W.; Curtis, R. 0. 1970. Estimation of northern 

hardwood site index from soils and topography on the 

Green Mountains of Vermont. Bull. 664. Burlington, VT: 

Vermont Agricultural Experiment Station. 16 p. 

Pregitzer, K. S.; Barnes, B. V. 1984. Classification and 

comparlson of upland hardwood and conifer 

ecosystems of the Cyrus A. McCormick Experimental 

Forest, Upper Michigan. Canadian Journal of Forest 

Research. 14: 362-375. 

Spies, T. A.; Barnes, B. V. 1985. A multifactor ecological 

classification of northern hardwood and conifer 

ecosystems of Sylvania Recreation Area, Upper 

Peninsula, Michigan. Canadian Journal of Forest 

Research. 15: 949-960, 

Stanley, 0. B. 1938. Indicator significance of lesser 

vegetation in the Yale Forest near Keene, New 

Hampshire. Ecology. 19: 188-207. 

Soil Survey Staff. 1975. SOH taxonomy: a basic system of 

soil classification for making and interpreting soil 

surveys. Agric. Handb. 436. Washington, DC: U. S. 

Department of Agriculture. 754 p. 
Soil Survey Staff. 1981. Examination and description of 

soils in the field, chapter 4. in: Soil survey manual, rev. 

ed. 430-V-SSM. Washington, DC: U. S. Department of 

Agriculture, Soil Conservation Service. 

Tabachnick, B. G.; Fidell, L. S. 1989. Using multivariate 

statistics, 2nd ed. New York: Harper and Row. 746 p. 

Tuckerman, E. 1860. The vegetation of the White 

Mountains. In: King, T. S., ed. The White Hills: their 

legends, landscape, and poetry. Boston, MA: Crosby, 

Nichols, Lee, and Company: 230-241. 

Van Diver, D. B. 1987. Roadside geology of Vermont and 

New Hampshire. Missoula, MT: Mountain Press 

Publishing Company. 230 p. 

Verbyla, D. 1986. Potential prediction bias in regression 

and discriminant analysis. Canadian ?ournal of Forest 

Research. 16: 1255-1 257. 

Westveld, M. 1951. Vegetation mapping as a guide to 

better silviculture. Ecology. 32: 508-51 7. 

Westveld, M. 1952. A method of evaluating forest sRe 

quality from soil, forest cover, and indicator plants. 

Stn. Pap. 48. Upper Darby, PA: U. S. Department of 

Agriculture, Forest Service, Northeastern Forest 

Experiment Station. 2 p. 

Westveld, M. 1954. Use of plant indicators and an index of 

site quality. Stn. Pap. 69. Upper Darby, PA: U. S. 

Department of Agriculture, Forest Service, Northeastern 

Forest Experiment Station. 5 p. 

Wilkinson, Leland. 1988. SYSTAT: the system for 

statistics. Evanston, IL: SYSTAT, Inc. 822 p. 

Zelazny, V. F.; Ng T. T. M.; Hayter, M. G.; Bowling, C. L.; 

Bewick, D. A. 1989. Field guide to forest site 

classification in Brunswick: Napadogan-Tobique SRe 

Region. Fredericton, NB: New Brunswick Department of 

Natural Resources and Energy. 43 p. 
Fincher, James M.; Smith, Marie-Louise. 1994. A discrimlnant function 

approach to ecological site classification in northern New England. 

Res. Pap. NE-686. Radnor, PA: U.S. Department of Agriculture, Forest 

Service, Northeastern Forest Experiment Station. 12 p. 

Describes one approach to ecologically based classification of upland forest 

community types of the White and Green Mountain physiographic regions. 

The classification approach is based on an intensive statistical analysis of the 

relationship between the communities and soil-site factors. Discriminant 

functions useful in distinguishing between types based on soil-site factors 

most strongly correlated with their distribution over the landscape are 

presented. 

Keywords: land classification; site; soils; northern hardwoods 

*U. 5. GOVERNMENT PRINTING OFFICE: 1994-5 50- 1 12/800 1 1 
Headquarters of the Northeastern Forest Experiment Station is in Radnor, Pennsylvania. Field laboratories are maintained at: 

Amherst, Massachusetts, in cooperation with the University of Massachusetts 

Burlington, Vermont, in cooperation with the University of Vermont 

Delaware, Ohio 

Durham, New Hampshire, in cooperation with the University of New Hampshire 

Hamden, Connecticut, in cooperation with Yale University 

Morgantown, West Virginia, in cooperation with West Virginia University 

Orono, Maine, in cooperation with the University of Maine 

Parsons, West Virginia 

Princeton, West Virginia 

Syracuse, New York, in cooperation with the State University of New York, 

College of Environmental Sciences and Forestry at Syracuse University 

University Park, Pennsylvania, in cooperation with The ~enns~lvania State University 

Warren, Pennsylvania 

Persons of any race, color, national origin, sex, age, religion, or with any handicapping condition are welcome to use and enjoy all facilities, programs, and services of 

the USDA. Discrimination in any form is strictly against agency policy and should be 

reported to the Secretary of Agriculture, Washington, DC 20250. 

"Caring for the Land and Serving People Through Research"