Niche Pattern in a Forest-Floor Small-Mammal Fauna

Niche Pattern in a Forest-Floor Small-Mammal FaunaAuthor(s): Raymond D. Dueser and H. H. Shuggart, Jr.Reviewed work(s):Source: Ecology, Vol. 60, No. 1 (Feb., 1979), pp. 108-118Published by: Ecological Society of AmericaStable URL: http://www.jstor.org/stable/1936473 .Accessed: 08/09/2012 10:14

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Ecology, 60(1), 1979, pp. 108-118 ?) 1979 by the Ecological Society of America

NICHE PATTERN IN A FOREST-FLOOR SMALL-MAMMAL FAUNA1' 2

RAYMOND D. DUESER:3 Resource Ecology Program, University of Michigain,

Ann Arbor, Michigan 48104 USA

AND

H. H. SHUGART, JR.

Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830 USA

Abstract. This study examines the relationships among 4 small mammal species in 2nd-growth mesic forest on Walker Branch Watershed in eastern Tennessee, USA. Populations of Bltarinna brevicauda, Peromyscus leucopus, Ochrotomys nuttalli and Tamias striatus were live-trapped on 9 0.36- ha grids during the summer of 1973. Eight measures of physical habitat structure were used in discriminant analysis of the microhabitats occupied by these 4 species. Three statistically significant discriminant functions were calculated. Each discriminant function is represented as an axis in a 3- dimensional discriminant space. These 3 axes are interpreted as vegetation type, vegetation structure and litter-soil surface characteristics. The positions of the species in the discriminant space characterize the microhabitat configurations of the species relative to the ecological properties attributed to the axes. Each species differs significantly from every other species on at least 1 axis. The observed species differences are conservative estimates of microhabitat (structural niche) segregation.

We propose measures of niche position (i.e., exploitation specialty) and niche breadth based on the discriminant analysis. Species i is represented by a cloud of ni sample points in the discriminant space. Sample point j for species i lies the distance dij from the origin of the space. The average of these distances (di) represents the average "position" for species i relative to the origin. Because this origin represents the average of the microhabitats sampled on the watershed, and because the microhabitats actually occurring on the watershed are assumed to vary continuously, the likelihood of a species encountering favored microhabitat on Walker Branch decreases as d increases. This d is, thus, interpreted as an index of niche position relative to the average of the microhabitats sampled. Variability among the dij values for species i (vi) measures degree of specialization, a direct measure of niche breadth for species i. Our data indicate that d and v are inversely related: breadth decreases as position becomes increasingly specialized.

We incorporate measures of niche position, niche breadth and population abundance into an analysis of community "niche pattern." This niche pattern characterizes the 4 species as follows: Peromyscus is an abundant generalist, well-adapted to the watershed as a whole. Ochrotomys, the only other mouse, is a relatively rare specialist, poorly adapted to the watershed. Tamias occupies an intermediate position between Peromyscus and Ochrotomys, and exhibits intermediate abundance. Although we have little data for Bl/arinna, this rare species appears to be poorly adapted to the watershed. Species differences in niche breadth appear to be determined more by the relative frequencies and carrying capacities of the species exploitation specialties than by the relative efficiencies with which the species exploit some critical limiting factor(s). Although we have no experimental evidence, the niche pattern observed for this community is consistent with an inference of competitive coexistence. The niche parameters of transient species which are infrequently encountered on Walker Branch are briefly discussed.

Key words: Blarina; competiti.ve coexi.stence; discriminant analvsis; haibitait structure; niche breaidth; niche pattern; niche position; Ochrotomys; Peromyscus; resource partitioning; specialization; Tamias; Tennessee.

INTRODUCTION

Analysis of the mechanisms and evolutionary con- sequences of the coexistence of ecologically similar species is an area of long-standing interest in ecology

I Manuscript received 27 September 1976; accepted 1 Au- gust 1978.

2 Contribution Number 319 from the Eastern Deciduous Forest Biome, United States-International Biological Pro- gram. Publication Number 1214, Environmental Sciences Division, Oak Ridge National Laboratory.

3 Present address: Department of Environmental Sciences, University of Virginia, Charlottesviile, Virginia 22903 USA.

(MacArthur 1965, 1972). Such analyses are concerned ultimately with natural limits to ecological similarity (Miller 1967, May 1974), and are focused on the ways in which species partition time, space and food resources (Pianka 1973, 1976). The unifying concept in the study of resource partitioning and competitive coexistence is the ecological niche (Cody 1974, Schoener 1974). Hutchinson (1957, 1965, 1967) introduced the concept of a niche as an n-dimensional hypervolume, expressed as the range and combination of environmental factors that permit a species to persist in a community. Although its application has not always

February 1979 NICHE PATTERN IN A SMALL-MAMMAL FAUNA 109

TABLE 1. Designation, descriptions and sampling methods for the 8 habitat-structure variables included in the observation vector for multiple discriminant function analysis

Mnemonic Variable Methods

ABIS Understory tree dispersion Average of distances in metres from trap to nearest understory vegetation (<7.50 cm diameter at breast height (DBH) and -2.00 m in height), in quarters (Cottam and Curtis 1956).

AEOR Evergreenness of over- Percentage of points with evergreen canopy, from 21 vertical ocular tube sightings story along 2 20-iM2 transects centered on the trap (James and Shugart 1971).

AHCT Vertical herbaceous foliage Average of numbers of live herbaceous stem contacts with a 0.80-cm diameter density metal rod rotated 360?, describing a 1.00-M2 ring centered on the trap and

parallel to the ground, at heights of 0.05, 0.10, 0.20, 0.40, 0.60, . . ., 2.00 m above ground level.

APCM Litter-soil compactability Percent compaction of litter-soil core sample.

ASAM Tree stump size Average of diameters in centimetres of nearest stump a7.50 cm in diameter per quarter around trap, within 10.00 m of trap.

ASNR Tree stump density Average of numbers of tree stumps -'7.50 cm in diameter per quarter around trap, within 10.00 m of trap.

AUDR Index of shrub-level Percentage of points with shrub-level vegetation (<2.00 m in height) from 21 vegetation density step-point samples along 2 perpendicular 20-m2 transects centered on the trap

(modified from Evans and Love 1956 and James and Shugart 1971).

AWAT Vertical woody foliage Same as AHCT, for live woody stem contacts. density

been consistent with Hutchinson's intention (Whitta- ker et al. 1973), this abstract graphical representation has transformed the niche concept from a descriptive to a rich heuristic construct (MacArthur 1968). Sub- sequent speculation on limiting similarity, resource partitioning and competitive coexistence generally has been expressed in terms of the expected geometrical properties of niches (e.g., Levins 1968).

Green (1971) discussed 3 practical problems encountered in any empirical application of the hypervolume niche concept: (1) a large proportion of the environmental factors measured may be correlated, invariant or irrelevant; (2) reduction of a data set to factors of probable relevance results in a large mass of multidimensional information which is difficult to interpret; and (3) although 2 hypervolumes may be similar for the environmental factors considered, this similarity neither demonstrates overall niche congru- ence nor predicts the effect of considering additional factors. Maguire (1967) proposed using multivariate statistical procedures such as discriminant function analysis to derive objective measures of niche geometry. Discriminant analysis retains the geometrical character of the hypervolume concept by describing the distributions of species on a number of continuous, explicitly defined variables (Fuji 1969). Several recent studies involving ecological comparisons of species have followed this general line of reasoning (James 1971, M'Closkey and Fieldwick 1975, M'Closkey 1976). Green (1971, 1974), in particular, discusses both the statistical assumptions underlying discriminant analysis and the reasons for using discriminant analysis as a quantitative representation of the hypervolume niche concept.

Dueser and Shugart (1978) used discriminant analysis to detect and characterize microhabitat differences among the species in a forest-floor small-mammal fauna. These species include 1 insectivore, the short-tailed shrew (Bl/asinni brevicauda), 2 cricetid rodents, the white-footed mouse (Peromyscus lc uopus) and the golden mouse (Ochrootomys niutt(llli), and I sciurid rodent, the eastern chipmunk (Tainis striai- tus). That study examined the responses of these species to a broad spectrum of measures of habitat structure and identified the variables by which the microhabitat configuration of each species could be distinguished, on the average, from the microhabitats of the other species. The present study extends these analyses. Our specific objectives are: (1) to characterize species hypervolumes as a function of the structure of the environment, (2) to reduce the dimensionality of the observations to a few interpretable and independent axes, (3) to test species relationships in the context of structural niche geometry and dimensionality, and (4) to characterize the niche pattern (Shugart and Patten 1972) for this fauna.

STUDY AREA, SPECIES AND SAMPLING PROCEDURES

The characteristics of the study area, the small mammal species observed and the sampling methods and procedures are reported elsewhere (Dueser and Shugart 1978). All field work was conducted on Walk- er Branch Watershed at Oak Ridge National Labora- tory, Anderson County, eastern Tennessee. This 97.5- ha watershed supports well-stocked deciduous and mixed deciduous-evergreen forest. Four principal forest stand types are recognized: oak-hickory (Quercus

110 RAYMOND D. DUESER AND H. H. SHUGART, JR. Ecology, Vol. 60. No. I

TABLE 2. Sample estimates of the mean (v) and standard deviation (s) for each small mammal species on the 8 habitat variables inCILUded in the observation vector for mUltiple discriminant analysis. Four-letter mnemonics for variables and variable definitions are from Table I

Blarinta Peromnvscus OchrotomNvs Taticias bre'icauda leucopus tiuttalli striatuis

(n = 5) (n = 167) (n = 12) (n = 71)

Variable rs x s . s r s

ABIS 1.9 0.74 2.5 1.17 2.2 0.93 2.0 0.77 AEOR 1.0 2.24 4.4 15.43 58.3 32.76 8.3 19.44 AHCT 8.3 10.08 4.3 5.79 10.4 9.09 3.1 3.97 APCM 10.0 1.04 13.3 3.54 10.7 1.38 12.6 3.17 ASAM 19.8 3.56 47.9 28.18 14.2 11.95 40.3 27.05 ASNR 0.8 0.52 1.1 0.58 0.4 0.33 1.3 0.67 AUDR 67.4 24.72 53.0 22.72 71.6 22.92 46.5 20.88 AWAT 3.3 2.46 4.0 3.07 10.0 7.13 3.4 2.78

spp. and Car-va spp.), chestnut oak (Querus printis), pine (Pin,is spp., mostly P. echinata), and yellow pop- lar (Liriodendr-on tuilipifera) (Grigal and Goldstein 1971). Small-mammal populations were sampled intensively with 9 0.36-ha live-trapping grids, 3 grids each for the oak-hickory, chestnut oak and pine forest stand types. Trapping continued bi- or tri-weekly from December 1972 through February 1974. Data reported here are from the 6 trapping periods between 1 May and 16 August 1973, including 9696 trap nights in 22 d of trapping.

Blarintn brevic(auda is a fossorial species active day or night during every season. Although primarily a tunneling species, this shrew frequently is active on the surface. Blarina occurs most commonly on for- ested sites and occurs more predictably in deciduous than in evergreen forest stands. Peromyscus leu(opus is a primarily nocturnal, ground-dwelling species active during every season. This species generally is associated with the woody stages of secondary succession, and is more common on wooded than on grassy sites; deciduous forest is preferred over evergreen. Ochrotomvs nutta/lli is a nocturnal, ground- or arboreal-nesting species active during every season. This species occurs only on wooded sites having a particular, characteristic physiognomy. Although the overstory vegetation may be deciduous, it more commonly is mixed deciduous and evergreen. Whatever the overstory composition, however, these sites typically have dense ground cover and thicket undergrowth of shrub and vine species such as blackberry (Ruhu.s), green- brier (Stnilax) or, more commonly, honeysuckle (Lo-

TABLE 3. Number of captures and summer habitat characterizations in each forest type for 4 forest-floor small mammal species

Pero- Ochro- Forest Blarinna nm vscuCs toniYs Taniias type brevicauda leucopus nuttalli striatus

Oak-hickory 1 119 0 39 Chestnut oak 0 23 0 16 Pine 4 25 12 16

nicera). Taimiais stritatus is a diurnal, fossorial species. Individuals generally hibernate during midwinter. Taimiais commonly occurs in deciduous forests, along forest edges and in semi-open brushlands, and typically is more abundant in deciduous than in evergreen forests. Dueser et al. (1975) provide extensive literature documentation for these natural history summaries.

Habitat variables were selected to provide seasonal measures of habitat structure at a trap station. Three independent sampling units were centered on each trap station: a 1.0-m2 ring, 2 perpendicular 20-im2 transects and a 10-m radius circular plot. Altogether, 29 separate variables were observed on these 3 sampling units (Dueser and Shugart, 1978). Because many of these 29 variables were significantly correlated and/or conceptually similar, a subset of 8 important variables was selected for multiple discriminant analysis (Table 1). Each of these 8 variables is explicitly interpretable and seasonally stable, and each produced an F-value significant at the .01 level of probability in an initial univariate analysis of variance for overall species differences. Each has a correlation <.75 with any other variable, regardless of the statistical significance of the correlation. Thus, this subset contains only a few more or less nonredundant variables with power to discrim- inate among species. Means and standard deviations for each species for each variable are summarized in Table 2.

RESULTS

Caipture records

The 255 summer captures and habitat characterizations include 2% Blarinna, 66% Peromyscus, 5% Och- rotomvs and 27% Ttamiais (Table 3). Overlap in capture sites occurred between Blarinal and Peromyscus, Bl/a- rinai and Och rotomys, Peromyscus and Ochrotomvs, and Peromyscuis and Taimiais; only Peromyscus and Taimiais exhibited statistically significant pairwise as- sociation in the capture sites at which they were observed. Blarina was observed primarily in the pine forest type, Peromyscus and Taimias in the oak-hickory, and Ochrotomys in the pine. Dueser and Shugart


DF3

2- Blarina

Tamlas Peromyscus Ochrotomys

DF2 - DF1

FIG. I. Positions of 4 small-mammal species in the discriminant 3-space. See text for explanation of the transfor- mation of an individual observation or a species' mean from the measurement space to a position in this discriminant space.

(1978) have discussed the summer capture records and habitat characterizations for these 4 species on Walker Branch. Although the sample sizes for Ochrotomys and particularly Bl/rin are small, these infrequently captured species are included in subsequent analyses for purposes of comparison.

Dis( riminant (calculations

Multivariate analyses with g = 4 species (sample groups) and p = 8 variables in the observation vector used routines from Cooley and Lohnes (1971). Dis- criminant analysis began with a test of the null hy- pothesis of homogeneity of within-species variance- covariance matrices. Because this test requires (n, - 1) a p, for i = 1, 2, . . ., , it was run with the Bl/- r-inba sample excluded. These data do not meet the assumption of equality of sample variance-covariance matrices (F = 2.600, df= 72/2734, P < .005). This result indicates that the multivariate representations

TABLE 5. Linear correlation (r) between each discriminant function (DFI, DF2, DF3) and each habitat variable in the observation vector. Mnemonics are from Table 1

Variable DFI DF2 DF3

ABIS -0.061 -0.605 -0.402 AEOR 0.930 0.203 -0.093 AHCT 0.394 -0.346 0.295 APCM -0.258 -0.151 -0.534 ASAM -0.411 -0.230 -0.563 ASNR -0.461 0.270 -0.223 AUDR 0.318 -0.425 0.258 AWAT 0.644 -0.233 -0.175

of these 3 species in the sample space differ significantly in size or shape, regardless of differences or similarities in position. The formal test of the null hy- pothesis of equality of species centroids in the measurement space is not, therefore, strictly valid.

Nevertheless, the analysis was completed with all 4 species included and the ecological significance of each discriminant functions was judged according to whether it (1) could be interpreted in an ecologically meaningful and consistent manner, (2) contributes more to the spatial separation of species than any discriminant function that fails to satisfy (1), and (3) provides obvious separation between 2 or more species consistent with the ecological interpretation of the discriminant function (Green 1974). As might be expected from the screening procedure by which variables were selected for discriminant analysis, the 4 species do not have a common centroid (F = 3.250, df = 24/708, P < .01); these samples differ in position, size and/or shape in the space defined by the observation vector. We proceed with the analysis because the discriminant functions are interpretable ecologically and each contributes meaningfully to species separation (conditions 1 and 3 above).

DFI accounts for 70% of the discriminating information available in the measurement variables, DF2 for 20%, and DF3 for 10%lo (Table 4). The coefficients for transforming an individual observation vector from

TABLE 4. Summary of multiple discriminant analysis. **P s .025, ****P f ' .005. DFI, DF2, and DF3 are the 3 possible discriminant functions. Mnemonics are from Table 1

Information DFI DF2 DF3

Eigenvalue 0.502 0.142 0.070 Chi-square test for significance of discriminant function 150**** 50**** 17** Degrees of freedom 24 14 6 Percentage of discriminating inforrnation 70 20 10 Cumulative percentage of discriminating information 70 90 100 Normalized eigenvectors (w) ABIS 0.13828 -0.52369 -0.32761

AEOR 0.03411 0.02877 -0.02793 AHCT 0.00859 -0.08023 0.05855 APCM -0.03271 0.04008 -0.12888 ASAM -0.00481 -0.00843 -0.01753 ASNR -0.29559 0.26309 -0.39703 AUDR -0.00295 -0.02103 0.01514 AWAT 0.07742 -0.10679 -0.06787

112 RAYMOND D. DUESER AND H. H. SHUGART, JR. Ecology, Vol. 60, No. 1

DF2 aI I

1.5 Tamias

Bla rina

0

Perom yscus

-1.5 'Ochrotomys

l . l l lDF1

-3 0 3

DF3 I I T b Bla rina

1.5

Peromyscus

Tami

-1.5 Ochrotomys

I IFD F I -3 0 3

DF3 I C

1.5 B/arina

Tam ias 0

Peromyscus Ochrotomys

-1.5

I I I I I DF2

-3 0 3

FIG. 2. Ninety-five percent confidence ellipses for the bivariate species means on each pair of discriminant axes. These confidence regions were computed from bivariate sample means, variances and covariances using the principal axes technique of Sokal and Rohlf (1969:526).

a point in measurement space to a point in the discriminant space were computed as the normalized eigenvectors (w) associated with the eigenvalue for each function. An observation is transformed by the expression D = >wixi, where x is the deviation of the value of variable i from the grand mean for variable i and w is the value of eigenvector i.

Composition of discriminant space

Each discriminant function can be represented graphically as an independent, normalized (i.e., ,u = 0, 0.2 = 1) discriminant axis (Fig. 1). Each axis is interpreted ecologically from the correlation between

the discriminant function and each of the measurement variables (Table 5). Evergreenness of the overstory (r = .930) is the predominant variable in DF 1. Vertical foliage density of woody vegetation (.644), and density (-.461) and size of stumps (-.411) also are important. Conceptually, these variables describe a complex gradient from evergreen overstory, high vertical foliage density, low stump density and small stump size, at I extreme, to deciduous overstory, low vertical foliage density, high stump density and large stump size, at the other. This pattern of covariation among these particular variables on Walker Branch characterizes the gradient from midsuccessional mixed pine-hardwood forest with dense honeysuckle undergrowth, on previously cleared and tilled sites, to mature mixed hardwood forest on relatively undisturbed sites. Species positions on DF1 also reflect this evergreen-deciduous vegetation gradient (Fig. 1). In particular, the separation of Ochrotomys from the other 3 species is consistent with the observed restriction of Ochrotomys to the pine forest type.

Two variables conceptually similar to one another characterize DF2. Average distance to nearest understory tree (-.605) and density of shrub-stratum vegetation (-.425) both are measures of the density or shrubbiness of woody vegetation. The pattern of covariation among these variables describes a gradient from relatively sparse shrub stratum under relatively dense canopy to dense shrub stratum under open canopy. The 4 species are distributed near the origin, with Tamias toward the sparse shrub end of the axis and Blarina toward the dense. Three presumably unrelat- ed variables characterize DF3. Average stump diameter (-.563), litter-soil compactability (-.534) and average distance to nearest understory tree (-.402) do not in themselves describe a conspicuous gradient. Nevertheless, this pattern of covariation among these variables is another aspect of the Walker Branch successional gradient described for DF1, related primarily to surface features and litter-soil characteristics rather than forest vegetation type. Although consid- erations of sample size preclude an unequivocal interpretation, the separation of Blarina from the other species on this axis does accurately reflect the capture of Blarina in the relatively deciduous portions of the pine grids. This species was associated with deciduous vegetation on the 1st axis, dense undergrowth on the 2nd, and now, a disturbed surface on the 3rd.

In summary, group positions on DF1 can be regard- ed as a function of species' responses to forest vegetation type; on DF2, the response to forest vegetation structure; and on DF3, the response to forest-floor characteristics. These results describe Ochrotomys as a midsuccessional species favoring evergreen forest with heavy undergrowth; Peromyscus and Tamias as species favoring deciduous forest and responding to the density of the shrub stratum vegetation; and Bla-


TABLE 6. Species pair-wise overlaps calculated from the 95% confidence ellipses for the species observations on discriminant axes 1 and 2 (Fig. 3). Overlap is calculated as the ratio of the area of overlap for a pair of species to the cumulative area for those 2 species, expressed as a percentage

Species pair % Overlap

Blarina-Peromx'scus 38 Blarina-Ochrotomvs 16 Blarina-Tamias 28 Peromv scus-Ochrotomv's 24 PeromrNscus-Tamiias 47 OchrototnNXs-Tamias 16

rina as a species favoring midsuccessional mixed forest with heavy undergrowth. Although these characterizations apply at the level of the microhabitat rather than the forest type, the characterizations for Ochro- tomys Peromyscus and Tamias are consistent with both the literature and the microhabitat configurations described previously for these species (Dueser and Shugart, 1978). The characterization for Blarina would not have been predicted based on previous studies, but is consistent with the capture site loca- tions included in this particular sample (Table 3).

Nic he segregation

Given the statistical independence and interpreta- bility of these 3 axes, the discriminant space provides a parsimonious representation of the realized niche as discussed for other vertebrate communities by Schoe- ner (1968, 1974), Pianka (1973), Cody (1974) and M'Closkey (1976), among others. The similarity of any 2 structural niches is an inverse function of the distance between their positions in this space. Figure 2 provides a graphical evaluation of statistical differences between species. The 95% confidence ellipse for each mean is plotted on each pair of discriminant axes, around the bivariate mean for the species. The area of an ellipse is a function of the sample variance on each discriminant function and of the confidence coefficient (1 - a) selected. The orientation of an ellipse is a function of the covariate relationship between the axes. Incorporation of this covariate relationship makes this evaluation of statistical differences between species more realistic than unidimensional testing.

Nonoverlap between any pair of ellipses reveals that these species differ in their position in the discriminant space. Inspection of this figure reveals that each species is segregated from each other on at least one discriminant axis. Specifically, Ochrotomys is segregated from the other species on DF1 (forest vegetation type); Tamias is segregated from Peromyscus, and perhaps Ochrotomys, on DF2 (forest vegetation structure); and B/arinna is segregated from both Taimiais and Peromyscus on DF3 (forest-floor features). It should

[DF2 I l I I

- Peromyscus- 3

Tam/as

0

-3 Ochro tomys Blarina

I I I I I DF1

-6 0 6

FIG. 3. Ninety-five percent confidence ellipses for the species observations on discriminant axes I and 2. The confidence regions were computed from bivariate sample means, variances and covariances using the principal axes technique of Sokal and Rohlf (1969:526).

be emphasized that the separation observed between species is separation on the basis of the variables included in the observation vector. Separation between structural niches could actually be greater for any pair of species because additional variables not measured here might provide additional bases for segregation. Significant separation does not necessarily imply causality. As Green (1974) has noted, statistical evidence alone is insufficient to establish even a likelihood of causality.

Niche overlap

Niche overlap is measured as the joint or shared use of niche space (Levins 1968). Figure 3 illustrates the 95% confidence ellipse for the observations for each species on DF1 and DF2. These ellipses are interpreted as utilization functions for the microhabitats available on Walker Branch. Although overlap (or in- tersection) could be calculated as the actual overlap of the probability distribution functions of 2 species in a discriminant space (Green 1974), this calculation is complicated both by heterogeneity of dispersions and dimensionality >1. Similarly, although overlap could be calculated from the projections of each utilization function onto the individual axes, this measure would greatly overestimate multidimensional overlap with independent axes (May 1975). A simple measure of overlap can be obtained from Fig. 3, however, as the ratio of the area of overlap for a pair of species to the cumulative area for those 2 species, expressed as a percentage (Table 6). Interpretations involving Blarina should take into account the fact that the third discriminant function, the axis on which this species was discriminated, is not considered in these measure- ments of overlap.

As might be expected, the greatest overlap occurs between Peromyscus and Tamias, both of which were


TABLE 7. Structural niche specialization measured as the distance (d) of a species position (exploitation specialty) from the origin of the discriminant 3-space and the relative variability (v) in this distance

Species d v n

Peromyscus leucopus 1.40 53.24 167 Tamias striatus 1.53 45.83 71 Ochrotomvs nuttalli 3.04 33.02 12

widespread on the watershed. Intermediate overlap occurs between Blarina and Peromyscuws, both of which were associated with relatively dense undergrowth under deciduous canopy. Somewhat lower overlap occurs between Blarina and Taimiais and between Ochrotomys and Peromyscus. Each of these 2 pairs contrasts a species associated with relatively dense undergrowth with 1 associated with relatively sparse undergrowth. The lowest overlap occurs between Ochrotomys and Blarina and between Ochro- tomys and Taimias. Each of these 2 pairs contrasts a species associated with evergreen canopy with a species associated with deciduous or mixed canopy. These estimates of overlap are intuitively consistent with the foregoing analyses, and they appear to reflect the ecological reality of structural niche relationships among these species. These estimates of overlap are not, in our opinion, interpretable directly as pairwise competition coefficients.

Niche breadth

Niche breadth refers to the exploitation by a species of a particular resource or niche dimension (Schoener 1968), and is interpreted as an inverse index of specialization. Although niche breadth occasionally is described as an innate property of a species, this concept is most useful as a measure of variability in resource use (Vandermeer 1972, Pianka 1974). Referring specifically to a single discriminant axis, M'Closkey (1976) suggests using the standard deviation of the transformed sample points (discriminant scores) for a species as a measure of niche breadth. This measure is not directly applicable in a multidimensional context. Referring to a discriminant 2-space, Green (1971) suggests using the range of each of the projected limits of the confidence ellipse for the sample observations for a species as an estimate of niche breadth. The equal scaling of the axes facilitates direct comparison between species both on and between axes. From inspection of Fig. 3, in which the covariation between axes is retained for each sample, the species rank in order of decreasing breadth on DFI as Ochrotomys, Tamias, Peromyscus and Bl/arinna. The ranking on DF2 is B/lrinna, Ochrotomys, Peromyscus and Tamias. Ochrotomys is relatively broad on both dimensions. Peromyscus is relatively narrow on both. This measure of niche breadth does not corroborate the impres-

sion that Ochrotomys, and perhaps even Barina, has a "narrow" structural niche (i.e., is a microhabitat specialist) relative to Peromyscus and Tamias.

We therefore propose an alternative measure of niche breadth, namely the variability of the distances of the sample points for a species from the origin of the discriminant space. Species i is represented by a cloud of ni points in this space. By the Pythagorean theorem, sample point j for species i lies the distance dij from the origin. The average observation for species i relative to this origin lies on the surface of a sphere of radius di (=Idijlni) around the origin. Al- though the explicit dimensionality of the discriminant space is lost through this calculation, the distance di preserves the relationship among the 3 original axes for species i. Consistent with previous discussions of niche geometry, we refer to this distance di as the niche "position" of species i relative to the origin of the discriminant space. Since this origin represents the average microhabitat sampled on the watershed, the likelihood of a species encountering favored microhabitat on Walker Branch decreases as d incIeases. This d is, thus, an index of niche position or exploitation specialty relative to the average of the microhabitats sampled. Variability among d values for a species measures degree of specialization, a direct estimate of niche breadth. An appropriate statistic for comparing variation among samples known to have significantly different means is the coefficient of variation (v). This index of specialization has the property of associating niche breadth with niche position, and position with resource availability.

Table 7 summarizes d and v for the 3 most frequently observed species. These measures reveal a consistent inverse relationship between niche position and niche breadth: breadth decreases as position becomes increasingly specialized in relation to the average microhabitat sampled on the watershed. Och- rotomys is farthest from the origin and least variable. Peromyscus is nearest the origin and most variable. Tamias is intermediate in both respects. As a point of interest, these values for Blarina are d = 1.98 and v = 25.79. This infrequently observed species fits the general pattern of decreasing variability with increasing specialization. Although there appears to be a sample- size effect associated with these statistics, these results are both theoretically and empirically consistent with the foregoing analyses. The apparent relationship between position and breadth implies that the abundance of a species on Walker Branch is influenced by the availability of a particular microhabitat configuration.

DISCUSSION

Niche analysis has progressed from description to the testing of hypotheses related to concepts such as the limiting similarity of coexisting species, species


packing in equilibrium communities and niche shifts between communities (Pianka 1976, Christiansen and Fenchel 1977). Following Hutchinson (1957) and Lev- ins (1968), much of this analysis assumes that the geo- metric properties of species niches, such as relative position, breadth and overlap, meaningfully describe species relationships within a community. As an ex- tension of this analysis, it is logical to compare patterns in niche geometry between communities or between taxonomic groups (e.g., Cody 1968, 1974; Colwell and Futuyma 1971; Pianka 1973; Brown 1975). Questions typically underlying such comparisons might be: "Does the proportion of generalist ('broad- niched') species differ among communities, perhaps as a function of species diversity or productivity?"; "Do communities in which species composition fluc- tuates seasonally exhibit niche packing comparable to temporally stable communities?"; or "Do progressive changes in population abundance during succession produce shifts in niche breadth and/or overlap in a community?"

With these types of questions in mind, Shugart and Patten (1972) proposed incorporating measures of niche position (exploitation specialty), niche breadth and population abundance in optimal habitat into a community niche pattern. Niche pattern provides a framework for examining covariation among these 3 parameters. In describing the niche pattern for the forest-floor small-mammal fauna on Walker Branch (Fig. 4), we have substituted new indices for those proposed by Shugart and Patten (1972). The measure of niche position for each species is the d statistic; the measure of niche breadth is the v' associated with d (Table 7). d measures specialization as a function of position in niche space, with specialization increasing as d increases; v measures variability in specialization, with variability increasing as v increases. A measure of abundance in optimal habitat is estimated for each species as follows. If the di sampling distribution is normally distributed, then the frequency of species occurrence at d is, by definition, (2g(T2)0-1'2. The prod- uct of this frequency and the actual number of indi- viduLals captured is the expected abundance (1 in optimal habitat. As interpreted here, a assumes that the 4 small-mammal species were censused equally objec- tively by the live-trapping procedures employed. This assumption is always open to question, particularly for Blarina (Smith et al. 1975).

Peromyscus occupies a near-average niche position (low d), has great variability in niche configuration (high l') and is abundant at its optimal site (high a) (Fig. 4). Such properties describe a generalist that is well adapted to Walker Branch as a whole. Peromys-

cus was abundant at all sites sampled on the watershed. This ubiquity involves a combination of near niche position relative to the average microhabitat sampled and high variability in this position. This

a

90-

60-

Peromyscus 30 -

0

V Ochrotom ys

FIG. 4. Niche pattern for the forest-floor small-mammal fauna on Walker Branch Watershed. Niche pattern incor- porates measures of niche position (d), relative niche breadth (v) and population abundance in optimal habitat (a). See text for explanation of calculation of d, i, and (.

niche pattern is consistent with the broad distribution and habitat diversity of this species elsewhere (Baker 1968).

Ochrotomys occupies an extreme position (high d), has little variability in niche configuration (low v) and occurs in low abundance even at its optimal site (low a). These properties describe a specialist that is poorly adapted to Walker Branch as a whole. In fact, Och- rotomys was absent from most of the total area sampled but was moderately abundant in those portions offering a particular microhabitat configuration. The apparent rarity of this species on the watershed is associated with a combination of extreme niche position in relation to the average microhabitat available and low variability in this position. This niche pattern supports the suggestion by Linzey and Linzey (1971) that this species is highly susceptible to influence by ex- ternal or successional habitat alterations.

Taimias occupies a position between Peromvsycus and Ochrotomys, less variable than the former and less extreme than the latter. This species also is intermediate in abundance. Bl/rinna occupies a moderate position (moderate d), has little variability (low v) and occurs in relatively low abundance (low a). According to these data, Blarina has a narrow, somewhat specialized niche and is poorly adapted to the watershed as a whole, favoring specific successional deciduous forest sites. Although this specialization is not sug- gested by previous field studies for this species, it is consistent with our observations of Blarina on Walker Branch. We believe the abundance of Blarina on the

116 RAYMOND D. DUESER AND H. H. SHUGART, JR. Ecology, Vol. 60, No. I

watershed to be limited at least in part by the relative availability of favored microhabitats.

McNaughton and Wolf (1970) examined the relationships between dominance, niche breadth and degree of specialization in plant communities. They measured dominance as the relative abundance of a species under optimal conditions and niche breadth as the constancy of relative abundance over a range of conditions. Although their particular measure of niche breadth has been criticized on both conceptual (Whit- taker et al. 1973) and practical grounds (Shugart 1970), the trends they describe probably are real. Their analyses revealed both a positive correlation between dominance and niche breadth and, as expected, an inverse correlation between niche breadth and specialization. McNaughton and Wolf (1970) interpreted these correlations as indicating that the dominant species in a community is broad-niched relative to the subordinate species, and is thus able to maintain itself over a broad range of the conditions to which the community is exposed; this species thus appears to be an ecological generalist, with each subordinate species exhibiting some degree of specialization. Substituting the term abundant for dominant, this interpretation applies equally well to the niche pattern observed for the small-mammal fauna on Walker Branch.

McNaughton and Wolf (1970) also considered the question of what determines differences in niche breadth between species. They reasoned that these differences could be determined either by the relative efficiencies with which the species exploit some critical limiting factor(s) or by the relative frequencies and carrying capacities of the exploitation specialties of the species. We have no data dealing explicitly with species efficiencies in our community, and we doubt that conclusive tests of the first alternative are possible under natural conditions. Our data do reveal exploitation specialties, however, and we believe that the second alternative explains the niche pattern described for this small-mammal community. As discussed above, Walker Branch supports a mixture of deciduous and evergreen forest, with stands ranging from midsuccessional pine through mature hardwood; most of the watershed, however, is in an advanced stage of hardwood succession (Grigal and Goldstein 1971). Given this forest composition, the abundances and distributions of these small mammal species are consistent with the species exploitation specialties reported here and elsewhere. In particular, the "specialty" of the conspicuous generalist (i.e., Peromyscus in forest habitat) is more abundantly represented on Walker Branch than is the specialty of the extreme specialist (i.e., Ochrotomys in pine-honeysuckle thickets). Although the species composition of this relatively depauperate community probably would not shift in any major way during succession, we believe the niche pattern would shift substantially as population abundances changed.

In an argument conceptually similar to that of McNaughton and Wolf (1970), Vandermeer (1972) postulated that niche breadth is density-dependent, reflecting the sequential addition of suboptimal habitats (his term) to the range of habitats utilized by a species. According to this model of the niche breadth- density profile, niche breadth increases asymptotically with population density. Because our data represent a single season, during which population densities were relatively constant, they do not conform strictly to the dynamic conditions considered by Vandermeer (1972). Nevertheless, assuming that the 4 species considered here utilize habitats on similar spatial scales, we would expect from his model to observe the positive overall relationship between v and a shown in Fig. 4. M'Closkey (1976) also observed a positive correlation between the niche breadth of permanent resident species and population density in a seasonal rodent community. For Peromyscus, and perhaps Tamias, we would expect to see this density depen- dence in niche breadth as populations fluctuate seasonally or annually on Walker Branch. It is doubtful, however, that Ochrotomys, which our study and others describe as a conspicuous specialist, would exhibit this density response within this particular habitat matrix. This prediction could be tested either with habitat tailoring such as conducted by Rosenzweig (1973), on the assumption that habitat structure is the key to low abundance and restricted distribution, or with population manipulations such as conducted by Koplin and Hoffman (1968) and Schroder and Rosen- zweig (1975), on the assumption that interspecific competition is the key factor. Again, we would expect the niche breadth-density profiles of these species to shift during succession on Walker Branch, probably in accord with Vandermeer's (1972) model.

Why do these small mammal species, each of which differs from the others in body size, activity pattern and/or trophic adaptations, occur in structurally different microhabitats? Do these species differences and the resulting niche pattern imply a competitive coexistence? Although a conclusive answer would re- quire experimentation (Grant 1972), our data are consistent with an interpretation invoking interspecific competition. These species are separated completely, on the average, in 3 structural niche dimensions. The position of each species in the discriminant space provides an internally consistent, subjectively valid physical description of the structural niche (i.e., exploitation specialty) for that species. Species positions tend to be complementary in the sense of Schoener (1974); species which are similar on 1 axis differ on another. Complementarity is also evident in the relative similarity of niche pattern for 2 species which are dissim- ilar otherwise (i.e., Peromyscus and Taimias) and, conversely, the relative dissimilarity of niche pattern for 2 species which are most similar otherwise (i.e., Peromyscus and Ochrotomys). Previous authors also


have interpreted similar instances of complementarity as convincing evidence of competitive coexistence among rodent species (Rosenzweig and Winakur 1969, M'Closkey 1976).

Assuming that this niche pattern does reflect the ecological and evolutionary adjustments of these species to competition, why should species responses to habitat structure contain so much information about the organization of this community? M'Closkey (1976) has speculated that structural habitat division by rodents is either the means by which coexistence is achieved or is correlated with other niche dimensions (e.g., food) responsible for coexistence. Habitat structure probably often determines the distribution and density of food and the foraging characteristics of the species. If indeed food resources are correlated with habitat structure, microhabitat differences imply either negative or positive complementarity on a second dimension, and a single dimension reflects the organization of the community. This argument might be particularly pertinent to the small-mammal community on Walker Branch. Temperate deciduous forest char- acteristically supports fewer rodent species than a comparable area of physiognomically simple desert habitat. Brown (1973, 1975) and Brown and Lieberman (1973) concluded that seed size selection is the principal mechanism of coexistence among seed-eating desert rodents. Brown (1973) attributed the greater diversity of desert rodents to the potential for partitioning an omnipresent, particulate food resource (seeds) of varying size. He reasoned further that the lower species diversity of rodent communities in mesic forests may reflect the failure of these habitats to produce numerous seeds of varied size present throughout the year. By this reasoning, microhabitat segregation should be particularly important for forest-floor small mammals.

We conclude by speculating on the niche pattern for the entire small-mammal fauna known for Walker Branch. Although the 4 species considered above con- stitute the resident forest-floor fauna, 4 other rodents were observed sporadically during 15 mo of trapping. We captured <5 individuals each of Pitymys pineto- rum (pine vole) and Mus musculus (house mouse). Pitymys is a native grassland species; Mus is an introduced commensal species which has had little suc- cess at invading native faunas in the eastern deciduous forest biome. These species are poorly adapted to this forest and would exhibit little selectivity; a combination of competitive pressures and inefficient exploitation precludes their sustaining high abundance. We would expect them to occupy extreme niche positions (high d), exhibit high variability (high v) and occur in low abundance (low a) even in optimal habitat. In Fig. 4, these species would fall near the diagonal between d and v, far from the origin. Glaucomys volans (flying squirrel) and Sciurus carolinensis (gray squirrel) were widespread but not abundant on Walker Branch.

These larger, arboreal species may use space on a different scale from the forest-floor species, and may have specialized microhabitat requirements, particularly for nesting. These species are well adapted to this forest and would exhibit selectivity; their abundance would vary with resource availability, perhaps with an upper limit set by social behavior. We would expect them to occupy near-average niche positions (low d), exhibit low variability (low v) and occur in low to moderate abundance (low a). In Fig. 4, these species would fall near the diagonal between d and v, near the origin. Adding 2 transient, poorly adapted gener- alists and 2 resident, well-adapted specialists to this community generates a niche pattern similar in composition to that for the diverse (20 species) avian community studied by Shugart and Patten (1972).

ACKNOWLEDGMENTS

J. C. Randolph assisted in planning this research and pro- vided constructive comments throughout the study. L. E. Tucker assisted capably with all phases of the field work. R. H. Strand assisted with computer programming and data reduction. Bobbie Dueser assisted with the habitat characterizations and typed several early manuscript drafts. J. A. Kad- lec, F. C. Evans and G. W. Fowler commented constructively on an earlier presentation of these results and ideas. R. H. Gardner, W. F. Harris, G. M. Hornberger, W. E. Odum and R. K. Rose commented constructively on the manuscript. Comments from an anonymous reviewer are particularly ap- preciated. P. Taylor assisted in preparing the final manuscript. R. D. Dueser was supported during the period of this research by a graduate fellowship from the Institute for En- vironmental Quality at the University of Michigan. This research also was supported in part by the Eastern Deciduous Forest Biome, United States-International Biological Project, funded by the National Science Foundation under Inter- agency Agreement AG-199, BMS69-01147 A09 with the En- ergy Research and Development Administration-Oak Ridge National Laboratory, and in part by the Energy Research and Development Administration under contract with the Union Carbide Corporation.

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Documents

Niche Pattern in a Forest-Floor Small-Mammal Fauna