The American Midland Naturalist Published Quarterly by the University of Notre Dame, Notre Dame, Indiana

The American Midland Naturalist Published Quarterly by The University of Notre Dame, Notre Dame, Indiana

Vol. 109 APRIL, 1983 No. 2

Multivariate Assessment of Environmental Preferences of Cyprinid Fishes of the Illinois River, Oklahoma

JAMES D. FELLEY1 and LOREN G. HILL Oklahoma Biological Survey and Department of Zoology, University of Oklahoma, Norman 73019

ABSTRACT: Cyprinid fishes were collected from the Oklahoma drainage of the Il- linois River in all seasons of 1978 and 1979. The Illinois River and its tributaries drain the Ozark Plateau and the Boston Mountains and support an Ozarkian fish fauna. Species included in this analysis were Campostoma anomalum, Nocomis asper, Notropis boops, N. nubilus, N. pilsblyi, N. rubellus, N. whipplei, Pimephales notatus, Phoxinus erythrogaster and Semotilus atromaculatus. Fishes were collected and 17 environmental variables measured from each of 15 localities sampled in every season. Species distributions were characterized in reference to each variable as follows: the value of a variable at each location was weighted by the number of individuals of a species present, and the mean of these weighted values was taken as that species' preferred state for that variable. Principal components analysis, with rotation of the component solution to simple structure, was used to elucidate the relationships among variables in terms of species distributions. In most seasons, components related to species preferences for upstream vs. downstream locations, different foods, and slow- vs. fast-water habitats. For most species, differences in habitat preference between seasons were related to breeding (in the spring) and to preference for warmer locations during the rest of the year.

INTRODUCTION The distribution of a species is constrained by its environmental tolerances and by interactions, such as competition and predation, with other species (Smith and Powell, 1971). Within these limits, distribution is related to preferences for given environmental condition. The relationship between environmental conditions and distribution has been shown for cyprinids in particular (e.g., Matthews and Hill, 1979 a and b; Mat- thews and Maness, 1979). Different tolerances and preferences of separate species may result in differing patterns of distribution, and seasonal or daily changes in environmental conditions may lead to movement of a species. One way to characterize the distribution of a species relative to an environmental variable is by the mean of the variable over all collected individuals (Felley, 1980). This mean is the state of that variable found at locations where individuals are most likely to occur, and can be used as an estimate of a species' preference for the variable. Though species distributions may be so characterized for any number of variables, not all of these will be of equal importance in affecting a species' choice of habitat. A given environmental variable may directly influence a species' habitat choice. Alter- natively, a variable may have no effect on choice of habitat but may be functionally related to a variable that does have an effect (for example, if a species' occurrence is af- Present address: Department of Biology, McNeese State University, Lake Charles, Loui- siana 70609.

209 210 THE AMERICAN MIDLAND NATURALIST 109(2) fected by current speed, variables such as substrate type or amount of debris present would be correlated with it). Finally, a variable may be unrelated to habitat choice. In- vestigation of species distribution according to different environmental variables must take into account the possible confounding relationships among the variables themselves. Baker and Ross (1981) investigated cyprinid distributions in reference to different environmental variables and related distributional patterns to habitat segregation among the species, along a number of ecological axes. They showed that analysis of species preferences (as suggested above) and identification of patterns of covariance among the variables can point to trends in habitat partitioning among the species. In this case, covarying variables are those reflecting a common trend in species distributions. Multivariate procedures (such as multivariate analysis of variance and components analysis) are uniquely suited to identification of sets of covarying variables. We used components analysis to investigate distribution of members of the family Cyprinidae in different seasons in the Oklahoma drainage of the Illinois River.

MATERIALS AND METHODS The Illinois River drains portions of the Boston Mountains and the Ozark Plateau in Arkansas and Oklahoma. In Oklahoma, the Illinois River drains a limestone/sand- stone topography, and headwaters are heavily influenced by springs. Figure 1 il- lustrates the Oklahoma drainage of the Illinois River and our collection localities. The fish fauna of the Illinois River is typical of Ozark streams; cyprinid species regularly collected and included in our analysis were as follows: Campostoma anomalum stoneroller; Nocomis asper redspot chub; Notropis boops bigeye shiner; N. nubilus Ozark minnow; N. pilsbgi duskystripe shiner; N. rubellus rosyface shiner; N. whipplei steelcolor shiner; Pimephales notatus bluntnose minnow; Plwxinus erythrogaster southern redbelly dace, and Semotilus atromaculatus creek chub. All of these species were collected in at least seven of our eight collecting seasons. Fish were collected at 15 localities in the Illinois drainage in spring, summer, autumn and winter of 1978 and 1979. In every season (calendar-defined, e.g., "spring" was 21 March to 21 June) we collected fish once at each locality. Collections were obtained by seine (3.7 x 1.5 m, 3 mm mesh) over small discrete areas (never more than 40 m2, often smaller) representing microhabitats. A microhabitat was an area determined in the field to be homogeneous for the following parameters: water clarity, substrate type, current speed, presence or absence of cover (structure or vegetation in which fish might hide), presence or absence of debris (leaves and sticks on the bottom), and presence or absence of emergent vegetation. Thus we attempted to minimize the possibility of seining through environments recognized as different by the fishes. So defined, a microhabitat was our sampling unit, and only one microhabitat was sampled at a location in a season. Water clarity was measured as Secchi disc depth, in meters. Water clear to the bottom was arbitrarily coded as 2 m. Substrate type was coded from 0-5 representing mud, sand, gravel, rubble, boulders, bedrock, respectively. Current speed was measured as seconds required for an object to float 10 m. Still water was arbitrarily assigned a value of 180 sec. Cover, debris and vegetation were each coded 1/0 for presence/absence. Additional variables measured at each location were stream width (m), maximum stream depth at the location sampled (m), depth of the stream at the sampled microhabitat (termed capture depth, measured in m), conductivity, pH and temperature. Fishes were preserved in 10% formalin. Up to 10 individuals of each species collected at a location were examined for gut contents. Gut contents were divided into four categories (terrestrial invertebrates, aquatic invertebrates, filamentous algae and detritus; Minckley, 1963) and percentages of volume of these categories were estimated 1983 FELLEY & HILL: FISH ENVIRONMENTAL PREFERENCES 211

for each individual. Stream order (which ranged from 2-4 at our collection localities) was determined from 1/250,000 topographic maps. Treatment of variables. —The values of environmental variables at each location were weighted by the number of individuals of a species collected there. For example, if 15 individuals of a species occurred at one location, and a single individual at a second, the values of the environmental variables at the first location would be weighted 15 times more heavily than those of the second location. For data coded 1/0 as presence/absence (debris, cover, vegetation) the result of this weighting procedure gave the percentage of individuals of a species that were collected at locations where that variable was coded "1." Temperature was averaged in the following manner for each species in a season: The average temperature for all locations was computed for that season and this value was subtracted from the temperature mean of each species collected in that season. So expressed, negative temperature averages indicated a preference for temperatures lower than the drainage mean; positive values indicated preference for temperatures higher than the average. Because pH is a power function (negative logarithm of hydrogen ion concentration), geometric means of pH values

Fig. 1. —Locations sampled for cyprinid fishes in the drainage of the Illinois River, Oklahoma 212 THE AMERICAN MIDLAND NATURALIST 109(2) were calculated for all species (Sokal and Rohlf, 1969). Means for food type percentages were calculated for each species. The categories of terrestrial and aquatic prey were combined into the variable "prey" for the analyses described below. This differen- tiated among cyprinids eating animal prey, filamentous algae or detritus. Statistical analyses were performed on the means of the variables for all species. Statistical analyses. —Statistical analyses were done using the Statistical Analysis System (SAS; Barr et al., 1976) on a 370 IBM computer. Variable means were correlated across species in each season. The resulting correlation matrices were then subjected to principal components analysis (Mulaik, 1972) and rotated using the Varimax procedure. Principal components analysis expresses the correlations among variables in terms of underlying "components," unrelated, artificial variables to which the observed variables are variously correlated. Correlations of observed variables to rotated components are referred to as loadings (Mulaik, 1972). Most principal components solutions are not rotated. In the unrotated solution, the first component accounts for the most variance among observations. Each successive component is orthogonal to all preceding components and extracts the maximum amount of variance not accounted for by preceding components. Interpretation of observed variable loadings on unrotated components assumes that the relationships of interest among observed variables lie along axes of maximum variance. Psychologists who pioneered the use of factor analytic models (including principal components analysis) developed a set of criteria for rotation of the principal component solution to "simple structure." This rotation results in a representation of the components where only a few variables are loaded heavily on each component (Mulaik, 1972). The rotated solution resolves the observed variables into a number: of sets, each set including a group of variables that tend to covary highly. Variables that correlate, highly to a component rotated to simple structure are interrelated. They share some at- tribute not shared with variables slightly correlated to that component. Within the assumptions of component analysis, a component may be interpreted in reference to those variables that correlate most strongly to it. All variables that loaded at ± .50 or greater were considered in interpreting that component. We considered a variable that correlated at a value of ± .70 or greater to be highly related to that component; a variable that loaded at less than ± .50 was considered to be unrelated. Only those components with high loadings for 2 or more variables were interpreted. Only those components with eigenvalues greater than 1 were subjected to rotation. Due to the small number of species included, correlations among variable means might inac- curately reflect actual relationships of the variables in terms of species preferences. We therefore sampled in 2 years, to see if comparable components emerged in the same seasons.

RESULTS For each season we averaged a species' preferences in the 2 years (Table 1). Though the environment itself may change in a year, we believe that species preferences pro- bably do not change year by year. However, for purposes of analysis we considered each season separately, giving us eight sampling periods for analysis. We examined the rotated component solution for all seasons (Tables 2-5), search- ing for pairs of variables that loaded highly on the same component in at least four of the eight seasons. Examination of all possible pairs allowed identification of those variables that covaried highly in most seasons. Each set of covarying variables was interpreted as reflecting a specific trend in habitat partitioning among the species. The resulting groups of observed variables defined three general types of components. Scores of species on components of each type were calculated, and species ranked according to their scores on each component. TABLE 1. -Environmental means in different seasons (averaged for 2 years) for species included in further analyses. Variables (their names here abbreviated) are explained in the text and in the footnotes below. Units are given under each variable's name. Values of vegetation, cover FELLEY & and debris represent the proportion of individuals of each species collected at locations where the particular variable was coded "1." Substrate type is a coded variable. Percentages of food and detritus are averages of percent volume of those food types for all individuals assessed for gut contents. Percentage volume of filamentous algae (the third category of food type) can be calculated for a species in a season by subtracting the values of food and detritus percentages from 100% HILL: FISH ENVIRONMENTAL PREFERENCES Species Season Clan' Veg. Subst.2 Coy. Debr. Curr.3 Capt. Depth Width Cond.* pH Detr. Prey Order Temp. Depth (m) (sec) (m) (m) (m) (C) Campostoma SP 1.87 .10 2.1 .4 .1 73 .61 1.30 20.3 131 7.4 100 0 3.8 .9 anomalum SU 1.94 .30 2.3 .4 .4 87 .46 1.11 11.4 260 7.7 97 0 3.3 - .1 FA 1.73 .30 2.2 .7 .7 100 .52 .92 14.5 228 7.5 97 0 3.3 1.1 WI 1.47 .15 2.2 .9 .5 145 .74 1.23 19.4 147 7.5 100 0 3.4 - .6 Nocomis SP 1.00 0.00 1.5 .5 .5 105 .83 1.14 13.2 155 8.1 5 95 4.0 - .2 asper SU 2.00 .50 2.2 .5 .6 52 .46 .49 6.2 243 7.6 0 100 2.5 -1.6 FA 2.00 0.00 1.2 .6 .6 135 .55 .89 8.0 163 7.3 5 95 2.9 3.0 WI 2.00 .25 1.5 1.0 1.0 150 .68 .92 7.7 129 7.8 28 65 2.3 2.1 Notropis SP 1.82 .30 2.4 .5 .1 112 .52 1.42 17.8 152 7.0 43 50 3.5 .6 boops SU 1.56 .40 2.3 .5 .4 81 .58 1.11 13.5 203 7.8 16 52 3.4 1.1 FA 1.00 0.00 .6 0.0 .7 180 .62 .83 8.3 193 8.6 48 38 3.3 - .5 WI 1.90 .15 1.6 1.0 .2 160 .74 1.32 25.5 137 7.7 41 59 3.7 .8 N. SP 1.92 .20 2.5 .5 .4 80 .71 1.42 17.2 142 7.4 99 1 3.4 -2.1 nubilus SU 1.55 .30 2.9 .5 0.0 131 .25 1.20 20.0 241 7.9 93 7 3.7 1.4 FA 1.77 0.00 2.6 .5 .5 123 .49 1.11 19.4 188 7.8 94 6 3.7 .6 WI 1.83 .15 1.8 1.0 .2 170 .86 1.26 17.4 129 7.9 100 0 3.8 .1

I•J ND

TABLE 1. -Continued Species Season Clan' Veg. Subst.2 Coy. Debr. Curr.3 Capt. Depth Width Cond.4 pH Detr. Prey Order Temp. Depth (m) (sec) (m) (m) (m) (C) N. SP 1.87 .40 2.0 .2 .2 102 .62 1.08 16.3 132 7.2 42 50 3.3 - .2 SU 1.85 .15 2.3 .5 .1 54 .43 1.05 16.9 250 7.8 24 66 3.8 1.6 THE AMERICAN MIDLAND NATURALIST FA 1.82 .30 2.2 .6 .3 90 .46 .95 16.6 187 7.4 50 26 3.6 1.3 WI 1.85 0.00 2.1 .8 .6 123 .80 .98 15.1 127 7.7 49 47 3.3 .3 N. SP 1.83 0.00 1.7 .1 .3 84 .43 1.23 16.0 155 7.3 8 92 3.9 .2 rubellus SU 1.68 0.00 2.1 .9 .4 53 .58 .98 28.0 253 7.7 10 90 3.6 1.0 FA 2.00 0.00 1.7 .9 .2 75 .46 .92 14.8 186 7.4 20 80 3.7 2.2 WI 1.62 0.00 2.1 .5 .2 66 .83 1.23 16.9 142 7.5 8 92 3.5 .2 N. SP 1.74 1.00 1.6 .2 .1 131 .62 1.11 23.4 138 6.9 29 71 4.0 1.0 whipplei SU 1.76 .10 1.8 .8 .1 147 .65 .95 24.6 221 7.3 5 90 3.8 - .5 FA 1.60 0.00 1.2 .8 .2 160 .46 .92 23.7 110 8.2 0 100 4.0 .5 WI 2.00 0.00 2.0 1.0 1.0 150 .62 .92 21.5 140 7.7 20 80 3.0 0.0 Pirnephales SP 1.25 0.00 .2 0.0 .5 110 .37 .83 17.8 172 7.3 100 0 4.0 .7 notatus SU 0.83 .50 2.6 .8 .2 100 .43 1.32 24.0 207 7.7 75 25 3.5 .5 FA 1.50 0.00 0.0 0.0 1.0 150 .42 .92 18.5 190 7.8 100 0 4.0 1.0 WI 2.00 0.00 .5 1.0 0.0 180 .62 1.23 18.5 140 7.7 100 0 4.0 -1.5 Phoxinus SP 2.00 0.00 2.0 .2 .2 67 .68 .74 3.6 123 7.1 61 20 2.0 -1.9 eqthrogaster SU 2.00 .30 2.2 .3 .7 52 .49 .65 3.2 207 7.3 30 70 2.0 -1.5 FA 2.00 .30 2.0 .7 .9 74 .62 .62 3.1 157 6.6 43 40 2.0 -1.6 WI 2.00 .05 2.1 .8 1.0 125 .55 .55 4.3 138 7.7 54 44 2.0 1.6 Semotilus SP 0.00 .50 2.0 1.0 0.0 180 .31 .62 1.8 140 7.6 0 100 2.0 -2.8 atronzaculatus SU 0.00 .60 2.4 .6 .2 56 .49 .64 3.1 275 7.5 10 90 2.0 -2.8 FA 0.00 .70 2.3 .8 .8 68 .62 .62 3.4 228 6.7 0 100 2.0 -1.0 WI 0.88 .50 2.4 .9 1.0 161 .46 .49 4.0 166 7.6 0 100 2.0 2.0 1Secchi disc depth. Water clear to the bottom was assigned a value of 2.0 m 2Coded 0-5 as follows: mud, sand, gravel, rubble, boulders, bedrock 3Time in seconds for an object to float 10 m. Still water was assigned a value of 180 secs 4Measured in micromhos/cm 1983 FELLEY & HILL: FISH ENVIRONMENTAL PREFERENCES 215

One of the recurring components usually had high loadings for such variables as stream order, pH, temperature, capture depth and debris. This component contrasted species found primarily in downstream areas with those found in upstream locations. Headwater species were found in areas characterized by lower pH and more constant year-round temperatures than downstream areas, due to the influence of springs on the physicochemistry of the headwaters (Hynes, 1970). Upstream areas tended to be choked with debris in some seasons, and species characteristic of headwaters tended to be collected in shallower water than species in downstream locations. In the different seasons, the following components were judged to reflect headwater-downstream habitat partitioning of species: Component I of spring 1978 (abbreviated CI-SP78), CII-SP79, CII-SU78, CIII-SU79, CI-FA78, CI-FA79, CI-W178, CI-W179. Scores of the species on each of these components were calculated, and the species ranked according to their scores. The ranks of a species on all these components were then averaged. The upstream-downstream component type reflected the existence of two species assemblages in the drainage (Table 6). One set, found in the spring-influenced headwaters, included Nocomis asper, Phoxinus erythrogaster and Semotilus atromaculatus. These species had average ranks of six or greater on this type of component. Semotilus and Phoxinus were never found away from springheads; Nocomis was ubiquitous in the drainage but more prevalent in the headwaters. The other species regularly collected formed the downstream assemblage. All had average ranks of less than five. None of the downstream forms were collected with any regularity in the headwaters, except for Campostoma anomalum and Notropis pilsbgi. In spring, breeding N. pilsbgi were common over riffles in the extreme headwaters. A second type of component distinguished species found in current-influenced areas and species found more often in quiet water and pools. In terms of species means, variables that correlated to this type of component included substrate type, debris, vegetation and current. Depending on the season, stream depth and width loaded either on this component (reflecting the different morphologies of pools and flowing water locations) or on the upstream-downstream component (reflecting the size differences between headwater streams and larger bodies of water downstream). In the

TABLE 2. —Component loadings of environmental means for cyprinid species from the Illinois drainage in spring. The representations below are the principal components rotated to simple structure. Only variables with high loadings are included. Component III in 1979 had high loadings for only two variables, and was not interpreted Year Component II III 1978 Stream order .84 % prey in gut .94 Stream width .91 Conductivity .82 % detritus in gut -.93 Stream depth .71 pH .81 Vegetation .69 Capture depth -.80 Debris .74 Substrate -.73 Temperature .69 Current .62 1979 pH .91 Stream order .95 Capture depth .84 Stream width .86 Substrate .82 Stream depth .85 Clarity .73 Conductivity -.68 216 THE AMERICAN MIDLAND NATURALIST 109(2) various seasons, the following components (Tables 2-5) were judged to reflect quiet water vs. flowing water habitat partitioning: CIII-SP78, CI-SP79, CI-SU79, CII- SU79, CIII-FA78, CII-FA79, CII-W179. Average ranks of species on these components are presented in Table 6. Species characteristic of pools and slow water included Notropis boops, N. whipplei and Pimephales notatus, with average ranks of six or more on this component type. Species found more often in flowing water were Campostoma, Notropis nubilus and N. rubellus. Nocomis, N. pilsbgi, Phoxinus and Semotilus were found in both fast and slow water locations. The low rank for Semotilus reflects its occurrence near vegetation and cover, even in flowing water conditions. For many species, preferences for fast or slow water changed over the year. In particular, N. boops, characteristic of quiet water and areas with cover during most of the year, was found breeding over riffles in the spring. Other species seen breeding over riffles included Campostoma, N. nubilus, N. pilsbgi and N. rubellus (as also noted by Moore and Paden, 1950). Nocomis and Semotilus are nest- builders (Pflieger, 1975); neither was observed breeding at any of our localities. The third type of component that recurred throughout this study reflected food preferences of the various species. In particular, this component contrasted herbivorous species with carnivorous ones. The following components were interpreted as reflecting food preferences of the species: CII-5P78, CI-SU78, CII-FA78, CII-W178. In other seasons, the food variables loaded on either of the two types of components described above, or on components that were not rotated or interpreted. Campostoma and N. nubilus were almost exclusively herbivorous, individuals rarely having anything in their guts but detritus and periphyton (Table 6). Pimephales notatus was primarily herbivorous but an occasional individual had eaten benthic invertebrates. Notropis boops, N. pilsbgi and Phoxinus were omnivorous (Table 1), most individuals having both aquatic invertebrates and large amounts of periphyton in their guts. Nocomis, N. rubellus, N. whipplei and Semotilus were almost exclusively predaceous. Nocomis fed on benthic invertebrates only, while in the spring, summer and autumn, terrestrial invertebrates were often found in the guts of the other three forms. Semotilus fed almost entirely on flying insects in summer and autumn. Movements of the species in the drainage were related to water temperature and to breeding. In winter, only two species had negative temperature means, being found primarily in areas cooler than the drainage average (Campostoma and Pimephales, Table

TABLE 3. —Component loadings of environmental means for cyprinid species from the Illinois drainage in summer. The representations below are the principal components rotated to simple structure. Only variables with high loadings are included. Component III in 1979 had high loadings for only two variables, and was not interpreted Year Component II III 1978 Cover .86 Temperature .94 % prey in gut .83 pH .85 Conductivity .82 Stream order .82 % detritus in gut -.77 Stream depth .76 Debris -.72

1979 Clarity -.96 Conductivity .92 Stream order .87 Cover .87 Vegetation .90 % prey in gut .84 Substrate -.86 Current .84 pH .81 Stream width .78 Debris .70 Temperature .80 Capture depth .78 Stream depth .64 1983 FELLEY & HILL: FISH ENVIRONMENTAL PREFERENCES 217

1). In winter, upstream areas were warmer than downstream, due to the relatively constant temperatures of the spring-influenced headwaters. Some species of the downstream communities responded by moving towards these upstream areas. This is reflected in a decrease in the value of stream order for the species in winter, as compared to summer, and is especially evident for N. pilsbryi (Table 1). In summer, species of the downstream assemblage again sought warmer locations, some moving away from the headwaters. Changes in habitat choice due to breeding have been noted above for some species. Habitat choice also changed with age in some species. Young-of-the-year Nocomis were always found in vegetation or cover of some sort, while adults were found more often in open, current-influenced localities. Larger N. pilsbgi were often found in upstream areas over riffles and in flowing water, while young individuals were more prevalent in

TABLE 4. - Component loadings of environmental means for cyprinid species from the Illinois drainage in autumn. The representations below are the principal components rotated to simple structure. Only variables with high loadings are included. Component III in 1979 had high loadings for only two variables, and was not interpreted Year Component

II III 1978 Stream width .89 % prey in gut -.94 Conductivity .83 Debris -.87 % detritus in gut .95 Capture depth .79 Stream depth .81 Clarity -.78 Temperature -.78 Stream order .73 Current .65 1979 Debris -.97 Cover -.94 Stream order .91 Clarity -.88 pH .88 Current .71 Capture depth -.87 % prey in gut .69 Temperature .85 Steam width .82 Stream depth .76

TABLE 5. - Component loadings of environmental means for cyprinid species from the Illinois drainage in winter. The representations below are the principal components rotated to simple structure. Only variables with high loadings are included Year Component

I II 1978 Stream width .99 % prey in gut -.94 Stream order .98 % detritus in gut .93 Debris -.97 Conductivity -.66 Stream depth .93 Temperature -.85 Clarity -.77 Capture depth .75

1979 Stream order .91 Vegetation .84 % detritus in gut .82 Capture depth .80 Stream width .77 Cover .73 Substrate -.75 Temperature -.72 Current .68 218 THE AMERICAN MIDLAND NATURALIST 109(2) downstream, slow-water habitats. Matthews et al. (1978) also noted a similar pattern of distribution for N. pi lsbgi of different age groups.

DISCUSSION Various multivariate methods, including components analysis, have been used to investigate fish communities (Echelle and Schnell, 1976; Smith and Powell, 1971; Stevenson et al., 1974) and to characterize the environment of collection localities, subsequently relating the fish fauna to the different localities (Harrel, 1978; Gorman and Karr, 1978; Matthews and Hill, 1980). These studies focused on sampled localities rather than species. This study, like that of Baker and Ross (1981) focused on species' environmental preferences as determined by their distributions in a drainage. Baker and Ross (1981) used multiple discriminant analysis to investigate species distributions, thus using species means and variances for all environmental variables. We did not use discriminant analysis because in some seasons our data did not satisfy all the assumptions of this technique. When in a season a species was collected from only one location, the species demonstrated no variance for any variable, thereby precluding use of multivariate methods that assume equal variance/covariance matrices among statistical populations. We therefore used components analysis on species means only. We stress that the different statistical methods used here and by Baker and Ross (1981) are aimed at similar questions. Both are analyses of species habitat choice in terms of physicochemical variables; neither explicitly includes interactions with other species. Factor analytic methods (including components analysis) are inappropriate to many ecological questions. Gauch et al. (1977) summarized a number of criticisms of factor analysis techniques used in ordination studies. Briefly, their most telling point was that factor analyses rely on correlations as estimators of linear relationships among variables. However, a species' abundance is usually not linearly related to an environmental gradient. A species will typically be rare in areas near the limits of its tolerance, and common at some optimum between the extremes. However, analysis of optima (estimated as species means in this study) allows use of standard multivariate methods such as multiple discriminant analysis and component analysis. The criticisms of Gauch et al. (1977) are not relevant to such studies if no ordinations are attempted. Rather, linear relationships among species preferences indicate similar trends in habitat partitioning relative to the variables. We found two groups of species, one

TABLE 6. -Average ranks of cyprinid species of the Illinois River on upstream-downstream, flowing water-quiet water, and food preference components identified in the text. Ranks close to 1 on these three types of components identify species that prefer, respectively, downstream locations, flowing water conditions, and preference for prey as opposed to detritus. Ranks closer to 9 identify species preferring converse situations or food Species Upstream- Flowing water- Food downstream quiet water preference Campostoma anomalum 3.8 5.4 8.5 Nocomis asper 6.0 5.1 2.5 Notropis boops 4.9 6.2 4.8 N nubilus 3.1 3.7 8.0 N. pilsbryi 4.2 4.3 5.8 N rubellus 3.0 5.4 2.2 whipplei 4.6 6.0 1 . 7 Pimephales notatus 4.2 6.0 7.5 Phoxinus erythrogaster 8.1 4.9 7.5 Sernotilus atrornaculatus 8.3 7.0 3.3 1983 FELLEY & HILL: FISH ENVIRONMENTAL PREFERENCES 219

group preferring areas of low pH and low order streams, the other high pH and high order streams. The linear relationship between species optima for pH and stream order indicates common trends in distribution relative to these variables, and points to a single trend in habitat partitioning. Principal components analysis identifies orthogonal (uncorrelated) axes describing data set structure, as does multiple discriminant analysis (Pimentel, 1981). Varimax rotation of the principal components solution retains this orthogonality. If the components represent actual environmental axes along which species segregate, it is unreasonable to demand that these axes be unrelated. When possible, an oblique rotation (allowing the components to become correlated) was done and compared to the orthogonal rotations. In all cases, the results were interpreted identically; only the loadings of the variables were changed. Thus, the assumption of unrelated axes seems justified for this study. The three main contributors to species segregation related to longitudinal zonation, influence of current and food choice. Longitudinal zonation (Shelford, 1911; Sheldon, 1968; Whiteside and McNatt, 1972) was demonstrated in the headwater-downstream component. The cyprinid fish fauna of the Illinois River drainage was divisible into three assemblages, including a headwater group (Nocomis, Phoxt'nus, Semotilus), a midstream group (the other species included in this study), and a large river/lake group derived from Lake Tenkiller. This assemblage included Notemzgonus crysoleucas the golden shiner; Notropis atherinoides the emerald shiner; and N. lutrensis the red shiner. We collected these forms only at the Illinois River location closest to the lake, and did not include them in the analysis. In most seasons, the second type of component (separating species preferring rocky mainstream habitats from those typical of slow-water areas) did not directly involve the current speed variable. The effect of fast water on other variables (debris, substrate, vegetation) was most often reflected by this component, but in general the cyprinid species we obtained did not occupy the fastest current. Two species that were quite characteristic of the fastest current were Hybopsis x-punctata the gravel club; and Notropis greenei the wedgespot shiner. Perhaps due to problems in seining in fast current, or due to actual scarcity of these species, we obtained them in only a few of the seasons, and did not include them in the analysis. Baker and Ross studied species distributions in reference to a different set of environmental variables. They found that cyprinids in a southern Mississippi river system tended to segregate by depth in the water column (a variable we did not measure) and by preference for vegetated vs. nonvegetated areas. They also demonstrated a longitudinal zonation effect that was not reflected in their multivariate analysis, possibly due to their choice of variables. Table 1 presents data that most investigators can generate from field data. Does one need to go further, to subject such data to exhaustive multivariate analysis? Our results suggest that there is additional information extractable by means of multivariate analyses. We used components analysis to summarize data on species preferences, not to augment the data. From the 17 variables we measured, we discerned three trends in ecological segregation of Illinois River cyprinids. These trends are not immediately ap- parent upon perusal of the data set contained in Table 1. The value of multivariate techniques lies in reducing a large number of environmental variables to a manageable few by identifying those variables that show the same trend in species' distributions. Our study points to the limits inherent to descriptive studies of species segregation. Longitudinal zonation of Illinois River fish assemblages could be caused by any com- bination of the variables that related to the headwater-downstream component, or by some variable we did not measure. Segregation of species according to "current speed" may in fact be segregation according to debris or cover, for some species. None of the 220 THE AMERICAN MIDLAND NATURALIST 109(2) components that recur in our analysis can be shown to be causally related to the variables measured in this study. Critical tests of tolerances and preferences are needed to ascertain the variables important in habitat choice by a species. However, descriptive studies of ecological segregation do point to those environmental variables that should be so tested.

Acknowledgments. -WWe would like to thank William J. Matthews and Stephen T. Ross for reviewing this manuscript. William D. Shepard, E. Gus Cothran and Marian Cothran, M. An- thony Schene, Daniel Fong, Michael E. Douglas, Shirley J. Starks and Kenneth Asbury aided in collection of specimens. Collection equipment and support for travel were made available by the Oklahoma Biological Survey.

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SUBMITTED 5 OCTOBER 1981 ACCEPTED 29 OCTOBER 1982