Enzyme Polymorphisms in Drosophzla Perszmzlzs1

MICROGEOGRAPHIC DIFFERENTIATlON OF CHROMOSOMAL AND ENZYME POLYMORPHISMS IN DROSOPHZLA PERSZMZLZS1

CHARLES E. TAYLOR Department of Biology, University of California, Riverside, California 92505

AND JEFFREY R. POWELL Department of Biology, Yale University, New Haven, Connecticut 06520

Manuscript received June 28, 1976 Revised copy received November 11, 1976

ABSTRACT

We studied microgeographic and temporal genetic differentiation in natural populations of Drosophila persimilis with respect to chromosome inversion and enzyme polymorphisms. Both inversion frequencies and allozyme frequencies varied significantly over short distances. Neither differed significantly between morning and evening collections. Because several studies of the dispersal behavior of this species have been performed, we attempt to fit the observed data to mathematical models which relate dispersion to random genetic drift and to spatially varying selection coefficients. We conclude that the observations are due at least partly to behavioral differences among genotypes. i.e., habitat preferences. These results have implications for genetic load theory and models of selection in heterogeneous environments.

HOWARDLEVENE ( 1953) demonstrated that conditions for maintaining stable polymorphisms are more easily met when environments are variable than when they are uniform. This association between genetic and environmental variation has since been explored in much detail with mathematical models (see, for example CHRISTIANSEN1975; GILLEPSIE1975; TAYLOR1976; and HEDRICK,GINE- VAN and EWING1976). The consensus clearly is that there should be a positive correlation between genetic variation in populations and heterogeneity of the environment in which they live. The situation in nature is less clear. VANVALEN (1965), for example, found a correlation for variation of bill size and niche width in birds, but WILLSON (1969) found none. DACUNHA and DOBZHANSKY(1954) found a positive correlation between environmental and inversion variation in natural population of Drosophila willistorzi, but AYALA,POWELL and TRACY(1972) found no such correlation for allozymes. In some other species environmental variation does seem to encourage allozyme variation in nature (HAMRICKand ALLARD1972) and in the laboratory (POWELL1971; MCDONALDand AYALA1974). This list of studies

Research supported by National Sclence Foundation Grant BMS 75-13544..

Genetics 85: 681-695 April, 1977 682 C. E. TAYLOR AND J. R. POWELL is by no means exhaustive, but illustrates that the association between genetic and environmental variation is not striking, in spite of theoretical expectations. The study reported below is one of a series directed toward better understanding this association. We collected Drosophila persimilis from several ecologically distinct areas within a few hundred meters of each other. Frequencies of gene arrangements (inversions) and allozymes were found to differ among these areas. The analysis and discussion are concerned with the causation of these differences-whether they were due solely to natural selection or random genetic drift, or whether there were also behavioral differences among the genotypes.

MATERIALS AND METHODS

This study was carried out in the vicinity of the Mather Plant Research Station of the Carnegie Institution of Washington in Toulumne County, California during July 1975. The station is on the western slope of the Sierra Nevada Mountains at about 4600 ft. elevation. This area has been described by CLAUSEN,KECK and HIESEY(1940). Five ecologically distinct areas were chosen on the basis of physical factors (degree of shading, moisture, etc.) and biotic factors (eg., plant species). These are given the designations Area A through Area E (see Figure 1). Besides spatial heterogenetity, we also studied temporal differences. Drosophila in this region have two distinct activity periods; about 2-3 hrs after sunrise and 2 hrs before sunset. Collections from all five areas were made during the afternoon activity period. In addition, we analyzed

c open woods X X CD X

0- 100 200

FIGURE1.-Location of habits from which flies were colllected. Letters refer to different collections. Nearly all traps were placed at the locations marked with "X" 's. ENZYME POLYMORPHISMS 683

morning collections from two areas: collection F was made at Area B in the morning, and G at Area C in the morning. Descriptions of habitats Area A: Open meadow: This is an open, low-lying meadow. Much of it is dry and hot (during the day), but near one edge is a vernal pond where the territory becomes moist, even boggy. The area corresponds nicely to ORNDUFF’S(1974) montane meadow community. There are many species of herbaceous plants, the most conspicuous of which are Oenothera hookeri, Iris missouriensis, Achillaea lanulosa, Sidalcea reptans, Prunella vulgaris, Patentilla gracilis, and sedges (Carex spp.) . Area B: Heavy, well-shaded woods. This area is a thick woods immediately adjacent to the vernal pond of the meadow. It hosts a dense mixed stand of Pinus ponderosa, Quercus kdlogi, and Calocedrus decurrens. The ground is thickly covered with pine needles and except for scattered Pteridium aquilinum and Galium aparine, is conspicuously devoid of herbaceous ground cover. Arect C: Open woodland/chaparral. This is a dry, mostly open area dominated by Calocedrus decurrens, Quercus kellogi, Q. crysolepis, Pinus ponderosa and Arctostaphylos mariposa. Some parts of it are thickly populated with the shrub Ceanothus integerrimus. Other conspicuous plants are Lotus neo-incanus, Monardella odoratissima, Bromus spp. and Festuca spp. Part of this area is a steep, rocky, xeric slope facing southeast, Area C is higher than Area A and surrounds A in a semi-circular manner. Area D: Dry open woodland/chaparral. This is a dry open woodland to the west of Area B which is similar to Area C and G. Much of it is on a southern slope. It has essentially the same plants as Area C. Area E: Dense, very wet woods. This cool, moist area has a wide stream trickling through it. Calocedrus decurrens and Pinus ponderosa are denser here than in any other area. The forest floor is thickly covered with Prunella vulgarus, Mimulus moschatus, Galium aparine, Fragaria platypetala, Plantago sp., Osmorrhiza sp. and several fungus species. This area differs from Area B in having more dense and varied vegetation. The understory is well developed and is especially rich in fungus, a food source for many Drosophila species. Fermenting banana traps were placed in the localities indicated on Figure 1. Traps were set about one hour before the activity period began and removed immediately after the activity period was over. In this area some 14 species of Drosophila are attracted to banana baits (COOPERand DOBZHANSKY1956), about 90% of which belong to four species of the obscura group: D. pseudoobscura, D. persimilis, D. azteca, and D. miranda. During July 1975 these species occurred in the following frequencies, respectively: 9.0%. 78.1%, 10 5%, 2.4%. D pseudoobscura was rela- tively infrequent in 1975. Only D. persimilis could be collected in numbers large enough for meaningful analysis. Upon collecting, all flies were etherized and classified if possible. Not all obscura group flies can be easily classified to species by morphology, although both the salivary gland chromosome banding patterns and electrophoretic allozyme patterns are diagnostic (DOBZHANSKYand EPLING 1944; AYALAand POWE~L1972). Qbscura group males from nature were brought directly to thc laboratory and used for electrophoresis. These males were assayed for Est-5 or Me-I and Me-2, two enzyme systems which allow nearly perfect diagnosis of species. Females were brought to the laboratory and placed singly into bottles with cornmeal.molasses Drosophila medium One F, larva from each culture was examined for the gene arrangements of the salivary gland chromosomes. They were squashed and stained with aceto-orcein in a manner developed by LAWRENCE HARSHMAN and BETTYMOORE (HARSHMAN 1976). One F, adult emerging from the isofemale cultures was assayed for each enzyme locus. Thus two genes were sampled for each line (females were used for all assays). Nine reliable and polymorphic loci were chosen for the study. Our techniques of horizontal starch gel electrophoresis were those described in AYALAet al. (1972) with the foliowing modifications and additions: No NAD+ was added to gel buffer system “B.” Malic enzyme and phosphoglucomutase were assayed in gel buffer system ‘C’ using elactrostarch. Xanthine dehydrogenase (Xdh) was studied using 684 C. E. TAYLOR AND J. R. POWELL TABLE 3

Frequencies of 3rd chromosome gene arrangemenis of D. persimilis in the seuen diflerent colleciions at Maiher, California

Collection Wtl KL ST MDfSE Sample size A 0.75 0.16 0.04 0.04. 226 B 0.72 0.13 0.09 0.05 20’2 C 0.66 0.14 0.14 0.07 168 D 0.73 0.11 0.10 0.06 134 E 0.60 0.23 0.13 0.04 70 F 0.69 0.17 0.06 0.08 146 G 0.69 0.13 0.13 0.03 194 Mean and total 0.702 0.147 0.099 0.053 1200

Abbreviations given in text. gel buffer system “B.” The Xdh stain buffer was 100 ml 0.05 M tris-HC1 (pH 7.5), 100 mg hypoxanthine (dissolved by heating prior to using as stain), 20 mg p-nitroblue-tetrazolium (NBT), 30 mg NAD+, 15 mg KCl and 5 nig phenazine methosulfate (PMS). P-Hydrozybularate dehydrogenase was stained in 100 ml 0.05 M tris-HCI (pH8.6), 1.26 g DL-P-hydroxybutarate, 25 mg NBT, 50 mg NAD, 10 mg MgC1.575 mg NaCl and 5 mg PMS.

RESULTS Five different gene arrangements were found for the third chromosome 01 D.persimilis. These are described in DOBZHANSKYand EPLING (1 944) and are named Standard (ST),Whitney ( WH). Klamath (KL), Mendocino (MD),and Sequoia (SE). Only one SE was found and that in Area A; therefore we coin- bined SE with the second rarest arrangement (MD)in thc following data. Tablo 1 presents the frequencies of the different gene arrangements in the seven different collections. The WHinversion was by far the commonest in all collections, ranging in frequencies from 0.60 to 0.75; the KL arrangement ranged from 0.1 1

TABLE 2

Allele frequencies in the seuen colleciions of D. persimilis for leucine amino peptidase (LAP) and phosphoglucomutase (PGM)

LAP Collection i .no 1.15 0.90 Sample size 1.oo 1.3G Sample size A 0.825 0.154 0.016 315 0.408 0.592 287 B 0.810 0.173 0.016 306 0.498 0.502 247 C 0.831 0.1% 0.024 249 0.456 0.544 239 D 0.898 0.093 0.008 236 0.366 0.634 216 E 0.795 0.170 0.034 88 0.258 0.742 83 F 0.773 0.213 0.014 282 0.378 0.622 241 G 0.818 0.170 0.011 352 0.422 0.578 275 Mean and sums 0.822 0.162 0.0116 1828 0.413 0.587 1594

Numbers directly under “LAP“ and “PGM” refer to alleles. To calculate xz LAP alleles 1.15 and 0.90 were combined because the 0.90 class was rare (N56). ENZYME POLY MORPHISMS

TABLE 3 Allele frequencies in seven collections of D. persimilis for hydroxybutaraie dehydrogenase (HBDH) and xanthine dehydrogenase (XDH)

HBDN XDIi ColleLtion F S Sample size 0.97 1.00 1.02 Other Sample size A 0.088 0.912 204 0.112 0.874 0.014 0 214 B 0.115 0.885 132 0.117 0.847 0.031 0.005 196 C 0.090 0.910 155 0.131 0.800 0.069 0 160 D 0.058 0.942 137 0.126 0.847 0.021 0.005 190 E 0.097 0.9083 62 0.121 0.818 0.061 0 66 F 0.109 0.891 138 0.099 0.838 0.063 0 142 G 0.088 0.912 136 0.111 0.815 0.068 0.006 162 Means and sums 0.093 0.907 1024 0.117 0.838 0.042 0.m 1130

x2 for XDH was calculated combining “others” with allele 1.02. to 0.23 and the ST from 0.04 to 0.14. -&ID was present in low frequencies in all areas, achieving a maximum of 0.08. These frequencies are within the range of inversion frequencies observed by E. B. SPIES, TH. DOBZIIANSKY,and thelr co- workers in past years (reviewed in DOBZHANSKY1963). Inversion frequencies did not differ significantly between the morning and evening collections from the same areas. For the collections in the dry open woods (C us. G.) the x2 value was 4.32 with 3 degrees oi freedom (0.1 < p < 0.5), and in the damp, shady woods (B us. F) the x2 value was 2.78 with 3 degrees of freedom (0.1 < p < 0.5). Since neither of these differences was statistically significant, the two collection times were pooled for subsequeni analysis. Inversion frequencies did differ significantly among the various areas (x2= 27.55; 12 degrees of freedom; p < 0.01). The most aberrant area was A, the open meadow, which is also the most different in vegetation. Tables 2-6 present the results of the electrophoretic analysis of the nine poly-

TABLE 4 Allele frequencies in seven collections of D. persimilis for NAD-dependent malic dehydrogenase (MDH) and one of two loci coding for malic enzyme or NADP-dependent malic dehydrogenase (Me-2)

i?tDH Me-2 Collection 1 .00 1.03 Sample size 1.04 1.02 Other Sample size A 0.941 0.059 202 0.820 0.176 0.004 272 B 0.922 0.078 204 0.810 0.190 0 232 C 0.967 0.033 152 0.824 0.1 76 0 204 D 0.965 0.035 144 0.850 0.145 0.005 200 E 0.984 0.016 64 0.826 0.174 0 86 F 0.932 0.068 132 0.852 0.148 0 236 G 0.903 0.092 153 0.851 0.145 0.004 262 Means and sums 0.941 0.059 1051 0.834 0.164 0.0052 1492 686 C. E. TAYLOR AND J. R. POWELL TABLE 5 Allele frequencies in seven collections of D. persimilis at one locus for malic enzym (ME-1) and octanol dehydrogenase (ODH)

ME-I ODH Collection 0.98 0.99 1.00 Other Sample size 1.00 1.05 Sample size A 0.114 0.821 0.061 0.004 280 0.970 0.030 200 B 0.082 0.861 0.043 0.008 244 0.989 0.011 180 C 0.095 0.842 0.063 0 222 0.967 0.033 152 D 0.069 0.877 0.049 0.005 204 0.959 0.041 145 E 0.125 0.761 0.102 0.01 1 88 1.00 0.0 64 F 0.122 0.845 0.025 0.0018 238 0.980 0.020 152 G 0.146 0.780 0.071 0.004 268 0.955 0.045 156 Means and sums 0.108 0.831 0.056 0.005 1544 0.972 0.028 1049

~ ~ ~~- -~

x2 for ME-I was calculated combining “others’’ with allele 1.00. morphic loci. The allele designations refer to the mobility of the proteins in our electrophoretic procedure. Some of these allele designations are the Same as given in AYALAand POWELL(1972) ; allelic variation at loci not reported previously are designated in the usual manner of relative mobility. HBDH had only two alleles which migrate so slowly that their relative mobilities could not be deter- mined; consequently we merely designated the faster migrating allele F and the slower allele S. To our knowledge, the Mather population of D.persimilis has not previously been characterized for allozyme frequencies. For this study we examined only loci known to be polymorphic elsewhere, so mean levels of heterzygosity and pro- portion of loci polymorphic cannot be estimated from these data. For each allozyme locus, the morning and evening collections from the dry, open woods (C us. G) and the moist, shady woods (B us. F) were compared with x2 tests. The results are shown in Table 7. Of 18 separate, independent tests two,

TABLE 6

Allele frequencies in the seuen collections of D. persimilis at one esterase locus (EST-5)

EST-5 Collection 108 1.10 1.12 1.14 1.16 Other Sample size A 0.004 0.034 0.794 0.142 0.023 0.004 267 B 0.026 0.026 0.810 0.1 OB 0.030 0 23 1 C 0.010 0.043 0.769 0.154 0.014 0.010 208 D 0 0.024 0.812 0.14.0 0.024 0 207 E 0.011 0.067 0.756 0.133 0.033 0 90 F 0.019 0.043 0.814 0.097 0.026 0 269 G 0.007 0.041 0.838 0.085 0.022 0.007 271 Means and sums 0.011 0.038 0.804 0.120 0.024 0.003 1543

x2 was calculated combining alleles 1.08 and 1.10 and combining “others” with allele 1.16. ENZYME POLYMORPHISMS 687

TABLE 7

Chi-square tests of comparison between allozyme frequencies in D. persimfiis colleciions at Mather, California

Morning us. Evening Habitats

Locus df B us. F C us. G df LAP 2 1.50 2.06 4 13.36** PGM 1 7.18*+ 0.62 5 20.70*** HBDH 1 0.03 0.00 4 3.49 XDH 2 1.61) 0.32 8 12.65 MDH I 0.12 4.48* 5 9.91 Me-2 1 1.43 0.65 4 1.34 Me-I 2 3.41 3.39 8 12.66 ODH 1 0.41 0.24 3 4.11 Est-5 3 0.52 5.74 12 11.28 Composite 14 16.20 17.50 53 89.50***

* p < .05. ** p < .Ol. *** p < .om. or 11%, were significant at the 5% level. This may well have resulted from chance alone, for when all of the independent tests were combined by adding x2 values and degree of freedom, the AM and PM collections did not differ significantly in either area (C us. G; x2 = 17.50, d.f. = 14; 0.1 < p < 0.3 : B US. F; x2 E 16.20, d.f. = 14; 0.1 < p < 0.5). As With the inversions, we conclude that if there are genotypic differences between the flies active in the morning and those active in the evening, we were unable to detect them. Allozyme frequencies were compared among the separate areas with x2 tests also. In all cases, except those which showed differences between the AM and PM collection, the morning and evening collections were pooled. The results are shown in Table 7. Two loci (Lapand Pgm) show significant heterogeneity among the collections. One of these, Pgm, is sex-linked while Lap is autosomal. The other seven loci show no apparent heterogeneity among the collections. The probability levels associated with these comparisons tends to be lower, on the average, than those of the AM US. PM collections: several comparisons show 0.05 < p < 0.1, for example. Consequently, when the independent tests were combined by adding xz values and degrees of freedom, the differences among areas becomes highly significant, x2 = 89.50, d.f = 53, p < 0.001. We conclude that flies collected from the different areas do differ in allozyme frequencies. though this may not be true at each locus individually. It may be of interest to note that the allozyme locus that is most strongly heterogeneous among the areas, Pgm, is sex-linked. None of these loci are on the third chromosome and are therefore not linked to the inversion polymorphism. 688 C. E. TAYLOR AND J. R. POWELL

ANALYSIS The question now becomes “What is responsible for the differences in gene and inversion frequencies which are observed among habitats”? There are several explanations which might account for this variation-habitat choice, natural selection acting through differential survivorship, random genetic drift, and nonuniform dispersal rates by the various genotypes. To evaluate the effectiveness of these explanations requires ciiiie steepness and dispersal to be estimated. Cline steepness was measured by comparing the mean pairwise difference of inversion frequency among areas to the mean pairwise distance between the median trap in each area. which was 335 meters. The average difference of inversion frequencies between areas for WH us the pooled altes- natives is 0.072. Some of this is due to sampling error and should be removed for measuring cline steepness. The total variance of inversion frequencies is uT2= 0.00352. The sampling variance is estimated to be uE2= p(l-p),” = 0.000875. The average difference in real gene frequencies among habitats is then calculated to equal the observed mean difference times (UT2-t~~~)/u~‘. which is 0.054. The importance to be attached to this difference depends on dispersal over the areas studied. By releasing large numbers of marked flies we have estimated that the variance in position increases approximately 45,000 m2/day (POWELLet al. 1976). A fly lives and disperses for a median of seven days if we assume 10% mortality per day as estimated by DOBZHANSKYand WRIGHT(1943). Thus the variance in position between eclosion site and adult position at capture (P)should be approximately 7 x 45,000 m2 = 315,000 m2. The standard deviation of d:s- persal is the square root of this, 561 m = 1. Random genetic drift: Random genetic drift by the populations occupying different habitats might result in differentiation among the populations. Dispersal of the flies would tend to smooth these out. The degree of differentiation would depend on the amount of movement among habitats and the density of flies. The differences among populations might be long-lasting, in which case the stepping stone model of KIMURAand WEiss (1964) or the continuous analogue of MAL^^- COT (1969) would provide appropriate descriptions of this drift. Or they may he

TABLE 8

Numbers of inversions types from flies captured early and late in the season from several habitats

Early Late Hahitat In KL ST ‘MD WT KL ST AID A 26 11 4 1 147 26 5 8 B+F 151 31 17 13 94 21 8 9 C+G 158 36 45 11 83 15 6 8 E 4 5 0 0 59 18 11 2

Area E is omitted from early x? because of small sample size. x2= 15.14 x2 = 16.35 df=6 N=5M af=g ~=520 P = 0.019 P = 0.059 ENZYME POLYMORPHISMS 689 transient, resulting from bottlenecks in population size over the winter, but are smoothed out as the season progresses. The importance of both can be eslimated. Inversion frequencies of flies caught during the first hall of the season are compared to those caught during the second half of the season in Table 8. The distinc- tion between “early” and “late” was based on the median fly which was caught. Those caught an or before this date are “early,” those after are ‘‘late.’’ With nearly equal sample sizes the deviations from the expectation of randomness gave xz values with nearly identical probabilities. For the first half of the season x2 = 15.14 with 6 degrees of freedom, and for the second half x2 = 16.35 with 9 degrees of freedom. In both cases the probability of observing a deviation this large or larger, under the null hypothesis, is < .06. Thus the differences among the areas were not smoothed out as the season progressed, indicating that they were not the transient result of a bottleneck. This would not preclude longer-lasting effects of genetic drift described by models of KIMURAand WEISS( 1964) or MALBCOT(1 969). Unusual highs or lows of gene frequency may persist for many generations in these models. Both models give essentially the same predictions. Because it was easier ic estimate parameters for the latter model, our analysis was directed toward the model of MAL~COTas described by CAVALLI-SFORZAand BODMER( 1971 ) . Assuming no selection, the variance in gene frequencies among areas, uZ, is related to the kinship coefficient,fo, bp the relation

and 1 fo = 1 8TSP - -)}-l { + ( log2b In these expressions x is the distance between habitats, 6 is the population density, and b is the “coefficient of recall.” The other terms are as defined earlier. Using the technique of DOBZHANSKYand WRIGHT(1943), 6 was estimated from the release experiment to be 0.0098 D.persimiZis/nz2. The coefficient of recall indicates how strongly the population is returned IO its equilibrium when perturbed by chance. It is equal to the sum of the forward and backward mutation rates when there is no selection, and becomes larger as a function of selection coefficients when heterosis is present. Long range migration increases it further. Equa- tion (1) and (2) represent two equations for the two unknown b and fo. When they are solved b is found to be less than 10-”. Thus, if drift alone caused the differences observed, then the coefficient of recall would have to be less than This is much smaller than the true value must certainly be for either inversions or allozymes, and indicates that random genetic drift is unlikely to be an important agent p-oducing the observed gene frcqlxency differences. This estimate may be incorrect, because the over-wintering population is probably smaller than even the unusually sparse 1975 population. The amount of drift should depend largely on this bottleneck value. Using a population density 1/100 that observed during the summer, however, b is still estimated to be less than lO-‘O. Because we believe 690 C. E. TAYLOR AND J. R. POWELL this value is unrealistically low, we conclude that agencies other than random genetic drift are almost certainly involved in sustaining the differences among areas. Nonuniform dispersal: In theory, the difference among areas might be due to nonuniform dispersal rates by the various genotypes. Judged by the relative den- sities of their fly populations, the wet woods is a generally favorable area and the open meadow is a generally unfavorable area for these flies. If all genotypes prefer the same areas, but one. say WiijWU, tended to be more active thaii WH/ST, then the frequency of WHwould be higher in the meadow and lower in the woods. Separate mass release experiments, which will be reported elsewhere, rule out the liklihood of this explanation being correct. It is mentioned here because these data, by themselves, cannot rule it out. Habitat choice: Habitat preferences may differ among the genotypes so that WH/WH genotypes, say, prefer moist open meadows while WHJST prefer dry woods. This might happen if carriers of WHJWH function better in moister areas, so that flies “prefer” it there, while WH/ST function better in drier areas, so those flies “prefer” it there. Differences in gene frequencies between the habitats could arise from nonrandom dispersal alone. Homing by the flies, another form of habitat selection, could also give rise to differences among allele frequencies of the magnitude observed. Natural selection: Alternatively, differences in gene frequency might arise if natural selection varies from habitat to habitat. Random movement by the flies wculd tend to smooth them out. ’The degree of differentiation would depend on the amount of movement, the distances separating the habitats, and the difference between selection coefficients there. It would also depend on the pattern in which the habitats are arranged. HANSON(1966) has studied mathematical models of populations which dis- perse over an infinite, two-dimensional surface. He assumed selection to be uniform over this plane except for a circular hole, where another regime prevails. Suppose the genotypes AA, Aa, and aa have relative (Darwinian) fitnesses l-k, l-k, and 1 inside the hole and 1 + k, 1 4- k, and 1 on the outside. Then HANSON showed that the frequency of the A allele at position r standard deviations of dispersal from the center of the hole, p (r), satisfies an ordinary differential equation, O=2kp2(1--p) + 2k(p’)’ (1-3p) + [r’p’+p”] [lfk(2p-3p2)]. (3)

The boundary conditions are p’ = 0 for r = 0 and p 10 for k negative and p = 1 for k positive when r is large. Figure 2 shows numerical solutions to this equation when k = 0.1 and the radius of the hole vanes from 2 to 10 standard deviations of dispersal. It is clear that unless the diameter of the hole is at least 6 standard deviations of dispersal alone would obliterate the effects of selections. For D.persimilis at Mather this would be 3,366m, or more than 2 miles. Since the distances among collection areas were only a small fraction of the “critical radius”, the difference of inversion and allozyme frequencies we observed are unlikely to have been the result of differential survivorship. ENZYME POLYMORPHISMS 69 1

0.20 --

- ---.-----+ -.

FIGURE2.-Numerical solutions of equation (3) showing gene frequencies away from the center of a hole. The values of R indicate the radius of the hole in standard deviations of dispersal.

Not all models of natural selection in heterogenous environments lead to this conclusion. SLATKIN( 1973) has derived expressions for gene frequencies along a linear cline. Suppose that the genotypes AA, Aa, and aa have fitnesses 1 +s, 1 + h, 1 - s at one side of the transition point and 1 - s, 1 + h, Ifs on the other side. The frequency of the A allele is designated p(x) at position x along the line. SLATKIN(1973) derived expression for the maximum change in gene frequency to be

when h > 0 and

when h i 0. These equations permit selection coefficients to be calculated. SPIESS( 1957) has estimated h/s to lie between 0 and 2 in population cages of D.persimilis. With an average distance between habitats of 335 m and an average differences in gene frequency of 0.054, the slope of the cline [dp/dx],,, is .054/335=0.00016. Taking 1 = 561 m and hJs = 2, the selection coefficients may be estimated from equations (4) and (5) to be s = 0.10. With h/s = 0 it is s = 0.05. In either case it is evident that under this model, weak selection would be enough to sustain the differences which were observed for both allozyme and inversion frequencies. Neither of these models, hole in a plane or linear cline, is likely to provide a very realistic picture of the habitats in the areas studied. We think that a more 692 C. E. TAYLOR AND J. R. POWELL reasonable model than either of the above is a “quilt-like” arrangement, with one pattern here and another there, alternating in patches. Representing the migration rate among patches by m,the gene frequencies in the two patch types by pl and pz, and the selection coefficients against the homo- zygotes by s1 and sz in habitat type 1 and s3 and siin habitat 2, thefi we can write

The necessary parameters can be estimated. The standard deviation of dispersal is 561 m and the mean distance between the centers in the areas is 335 m. These areas are less than 1 standard deviation cjf dispersion apart. Using this value and simple models oi diffusion, we estimated the migration rate among patches to be at least 33%. Almost certainly heterosis is involved with these inversions. The extreme equilibrium inversion frequencies values reported by DOBZHANSKY (1948) in his study of altitudinal variation of this species along a transect which includes Mather were 0.60 and 0.91. We may suppose that 0.60 is the equilibrium frequency in one patch and 0.90 is the equilibrium for the other patch. The amount of differentiation observed would depend on the magnitude of selection coefficients in the two regions. Numerical solutions of the equations above show that selection coefficients of 10% are able to produce differences in gene frequency of less than 0.01. Even selection coefficients of 50% are able to produce differences between the habitats of only 4%. This is extremely strong selection and is still unable to produce differences as large (5.4%) as were observed. We infer then, that habitat choice is an important factor involved in establish- ing the observed genetic variance among collection areas. The alternative explanations seem unlikely. Results from experiments which will be reported in detail elsewhere tend to support this conclusion. Flies were captured from different habitats and marked according to their origin. They were then released from a common site and recaptured on subsequent evenings. There was a tendency for flies to return to the habitat type in which they were originally found.

DISCUSSION Habitat selection of the type hypothesized here has been observed in other species as well. For example, the color morphs of Biston betularia exhibit preferences for different substrates (KETTLEWELL1955). The peppered morph prefers to rest on mottled background while the black, carbonaria, form prefers uniforinly dark surfaces. Nlcny other species which are polymorphic for color select habitats so that the individuals are better camouflaged (see e.g., MAYR1963, p. 246ff). The two sexes, of course, frequently differ in feeding habits (see e.g., MAYR 1963). In all these cases habitat preferences may be thought to produce microgeographic variation in gene frequencies. ENZYME POLYMORPHISMS 693 To what extent these examples might be generalized is unclear. That they might be of general importance comes from observations on the microgeographic variation in allozymes (RICHMOND,personal communication) and inversions (STALKER1976; KRIMBASand ALEVIZOS1973) of other species of Drosophila. The dispersal behavior of the species on which these observations were made are not known, however. If these species are quite sedentary, then the observed variance may have resulted entirely Irom difl‘erential survivorship or random genetic drift rather than habitat choice. Much is known of dispersal of D. persimilis (DOBZHANSKYand POWELL1974; POWELLet al. 1976). The observed genetic differences among D.prsimilis captured in different habitats may be due to behavioral differences among genotypes: different genotypes seek out different parts of the environment. This refers speci- fically to spatial variation because, it may be recalled, we did not detect any pro- nounced genetic difference between flies captured in the morning uersus evening. Our observations do not rule out the possibility that traditional natural selection (e.g, viability) may also be involved to some extent. Indeed, the implications of habitat choice are that genotypes choose areas where they are most adapted. (This has not been explicitly proven.) The reason we conclude that habitat choice must be occurring is that under any realistic model. selection coefficients would have to be quite large if natural selection were the only Iactor causing the observed patterns. Thus, we believe that we have obtained evidence that environmental heterogeneity is important in maintaining high levels of genetic variation in natural populations of Drosophila persimilis. Furthermore, because genotypes exhibiting habitat choice would tend to maximize their individual fitness, much of the genetic variation may be maintained without an unduly heavy genetic load (TAY- LOR 1975).

We thank the Carnegie Institution of Washington’s Plant Biology Department at Stanford University and especially DR MALCOLMNons for allowing us to use their facilities at Mather; MICHAELand Jo ANN ANDREGG,for assistance in collecting; and L. HARSHMAN.C. ROWE, ann’ M. JACKSONfor assistance in the laboratory. PROFESSSORSR. C. LEWONTIN,TIMOTHY PROUT and BRUCEWALLACE made helpful comments on the manuscript. Finally we acknowledge our great debt to PROFESSOR‘~IIEODOSIUS DOBZHANSKY whose stimulating skepticism inspired much of this work; we are deeply sorrowed he did not live to see these final results.

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