Genetic analysis of a rare and a widespread species of Echinacea (asteraceae).
Genetic aspects of rarity have received increasing attention in recent years (e.g., volumes by Soule and Wilcox 1980; Frankel and Soul6 1981; Schoenewald-Cox et al. 1983; Soule 1986; Falk and Holsinger 1991), as have the evolutionary consequences of habitat fragmentation for more widespread species of plants (Holsinger 1993). Rare species are often expected to be genetically depauperate, perhaps as a result of founder effect, genetic drift, and/or inbreeding in small populations. Some endemics seem to be adapted to a narrow set of environmental conditions, which might limit the genetic diversity maintained by selection. In evaluating a species' genetic variability it is important to recognize that variability at the level of the individual, the population, and the entire species can be relevant. If populations tend to be differentiated, perhaps because of isolation or diversifying selective forces, then a species with a large range could maintain higher levels of genetic diversity overall than a species with a restricted range even if within-population estimates of variability were similar for both. Furthermore, the effect of any one population's extinction on species-wide genetic variation depends greatly on the level of among-population differentiation. Thus, an analysis of population genetic structure is necessary to evaluate fully the impact of rarity on genetic variation.
Studies of genetic variability in rare taxa have not always supported the expectation that rare taxa are genetically depauperate relative to widespread species. In fact, Stebbins (1980)concluded that no correlation exists between the rarity or commonness of a species and the genetic variability present in its populations. Despite continuing inconsistencies, recent reviews of plant isozyme studies (Hamrick and Godt 1990; Hamrick et al. 1991; Karron 1987, 1991) concluded that overall geographically restricted species tend to have less genetic variability than widespread species. Karron (1987, 1991) pointed out the difficulty of drawing conclusions about such associations when pooling information from unrelated taxa and suggested that, because closely related congeners may share many ecological similarities, a common species can serve as a control for a rare congener (see also Kruckeberg and Rabinowitz 1985). Such comparative studies are still infrequent (Falk 1990). It should be noted, however, that some life-history traits are correlated with levels and distribution of genetic variability in plant populations (Hamrick and Godt 1990, and reviews cited therein), such that even congeneric comparisons may be misleading if the species compared do not share other important ecological traits.
The purpose of this study is to evaluate population genetic structure and investigate the association of geographic range with genetic variability by comparing a rare species with a well-matched widespread congener. Federally listed as an endangered species, Echinacea tennesseensis (Beadle) Small (Asteraceae) is found in only a few populations within a 23-km range near Nashville, Tennessee. This narrow endemic grows in island-like habitats called limestone glades (Quarterman 1989), which are forest openings where the rocky soil is too shallow to support woody vegetation. Although the plant is not found on most extant limestone glades, it can grow rather densely where it does occur (averaging up to 21 plants/m.sup.2, Drew 1991). The morphologically similar Echinacea angustifolia DC. var. angustifolia was considered a very close relative of the endemic (McGregor 1968) but is a widespread prairie species that ranges from Texas to southern Canada (fig. 1). Because these species are closely related congeners, the confounding effects of disparate phylogenetic histories are minimized (Karron 1987, 1991). The species are similar in life-history traits and mating system: both are herbaceous perennials that are nonclonal, insect-pollinated, obligate outcrossers (McGregor 1968; Hemmerly 1976). Both are patchy in their spatial distribution. Overall, this study examines two species for which geographical range is the most obvious difference that might correlate with differing levels of genetic variability.
The close relationship between E. tennesseensis and E. angustifolia is undisputed; in fact, because of the morphological similarities between the two taxa not all taxonomists have considered them as separate species (McGregor 1968 versus Cronquist 1980). Therefore, before comparing actual levels of polymorphism in E. tennesseensis and E. angustifolia, a preliminary question to ask is whether these two taxa are genetically distinct, or whether, instead, "E. tennesseensis" populations are simply marginal/disjunct populations of the widespread species (e.g., see Wyatt et al. 1992, for such a case). An undisputed species, morphologically distinctive Echinacea purpurea (L.) Moench., has been included in the evaluation of genetic similarity at isozyme loci to provide a context within which to evaluate the genetic distinctiveness of E. tennesseensis and E. angustifolia.
MATERIALS AND METHODS
Collection of Samples
Sampling occurred in the spring and summer of 1988 and 1990. All five populations of Echinacea tennesseensis then known to exist (U.S. Fish and Wildlife Service 1989) were sampled. Sites are 6 to 13 km from their nearest neighbor. Two of the sites consist of a few subpopulations separated by 100 to 200 m, and at these sites two subpopulations were sampled (TN-2 and TN-3, TN-4 and TN-5). Nine populations of Echinacea angusttfolia were sampled from four states throughout its range. Within a state, populations were usually sampled in pairs such that the distance between the two populations (about 12 to 14 km) would be comparable to the distances separating E. tennesseensis populations. The three populations sampled in Kansas were more widely separated (24 to 131 km apart). One Tennessee and one Missouri population of Echinacea purpurea were also sampled. Vouchers from all Echinacea populations sampled have been deposited in the Vanderbilt University Herbarium (VDB).
For E. tennesseensis and E. angustifolia, parallel transects were aligned over a population (or a concentration of plants, for a couple of extensive E. angustifolia populations), and every xth individual along a transect was sampled. The specific number of transects and frequency of sampling depended on the density of the individuals in the population. Both E. purpurea populations were much smaller than populations of the other two species, thus an attempt was made to sample each individual. Individuals were randomly selected from these collections for electrophoretic analysis. Leaves were stored in moist reclosable bags on ice for up to a few days until they could be refrigerated.
Electrophoresis procedures generally follow Werth (1985). Leaves were homogenized on ice in the simple extraction buffer to which 10% polyvinylpyrrolidone and 0.6% mercaptoethanol were added immediately before grinding. Either crude homogenate or supernatant from centrifuged homogenate was adsorbed onto filter paper wicks and loaded onto 12% starch gels. Greenhouse-grown plants of E. tennesseensis and E. angustifolia were used as marker genotypes on gels throughout this study. Sometimes frozen (-68C) wicks from field-collected plants were also used as markers, aiding in the comparison of genotypes from populations sampled in different months or years.
Four continuous buffer systems were used to resolve 18 putative loci coding for 12 enzyme systems: (1) tris-borate EDTA pH 8 for Fructose1,6-diphosphatase (FDP) (126.96.36.199), Leucine aminopeptidase (LAP) (188.8.131.52), Phosphoglucoisomerase (PGI) (184.108.40.206), and Phosphoglucomutase (PGM) (220.127.116.11); (2) tris-citrate pH 8, for Acid phosphatase (ACP) (18.104.22.168) and Peroxidase (PRX) (22.214.171.124); (3) tris-borate EDTA pH 9.1 ("Salamander B"), for Alcohol dehydrogenase (ADbO (126.96.36.199); (4) a modification of (3), where the gel buffer is a 1:9 dilution of the electrode buffer, for Glucose-6-phosphate dehydrogenase (G6PDH) (188.8.131.52), Glutamate dehydrogenase (GDH) (184.108.40.206), Malate dehydrogenase (MDH) (220.127.116.11), Phosphogluconate dehydrogenase (PGD) (18.104.22.168), and Superoxide dismutase (SOD) (22.214.171.124).
Because some enzymes are known to be more variable than others for most plant species (Gottlieb 1981), the use of different sets of isozymes when comparing species' genetic variability could be misleading. Therefore, isozymes resolvable for only one species were excluded from data analysis and are not listed above.
Staining protocols generally followed Werth (1985) except for FDP, which followed Soltis et al. (1983). Any modifications are noted in Baskauf (1993).
Allele frequencies, measures of genetic variability, and Nei's (1978) unbiased genetic identity were calculated using BIOSYS-1 (Swofford and Selander 1989).[X.sup.2] goodness-of-fit tests of genotype frequencies for deviations from HardyWeinberg expectations (using the Levene correction for small samples) and [X.sup.2] contingency tests to examine the independence of allele frequencies among populations of a species were performed. Hierarchical cluster analysis (UPGMA) (Sneath and Sokal 1973) was used to group populations by genetic similarity.
Jackknifed means and standard errors were calculated for Nei's (1978) unbiased genetic distance using NEIC (Lessios 1990) to test whether
between-species variation in genetic distance exceeds within-species variation. The procedure follows Mueller and Ayala (1982).
Wright's (1978) F-statistics ([F.sub.is],[F.sub.st],) are useful in evaluating how variability is partitioned within and among populations of a species. Jackknifed means and standard errors of F-statistics were calculated by the methods of Weir and Cockerham (1984). These procedures correct for the effects of sample size and number of populations sampled as well as providing a weighting scheme for multiple alleles at a locus. T-tests were used to determine whether an F-statistic value differs significantly from zero.
The level of heterozygosity present within populations for E. tennesseensis and E. angustifolia was compared by split-plot ANOVA, in which populations represent whole plots and loci represent the split-plot treatments, following Weir (1990). Some have attempted to simply use the variation in heterozygosity among loci when calculating the standard error for average heterozygosity, but such a procedure was not used because it makes the unlikely assumptions that single-locus heterozygosities are independent and that expected heterozygosity levels are the same for all loci (Weir 1990). The ANOVA was carried out using the general linear models procedure of the Statistical Analysis System (SAS Institute 1988). All effects were considered random except for the effect caused by loci. Because of limitations in computer memory, the entire data set for E. angustifolia could not be used in a single analysis. Instead, two separate analyses were carried out which differed only in that alternate halves of the data from the Kansas sites were included in each run. The effect was as if each Kansas population had been sampled along the transects at half the actual sampling frequency. In a between-species ANOVA, comparing heterozygosity levels in E. tennesseensis and E. angustifolia species were considered fixed effects, and populations for each species were pooled because of insufficient computer memory. Again, only half the individuals sampled for Kansas populations were included in the data for E. angustifolia.
Of the 18 putative isozyrne loci analyzed, 8 are considered invariant across all three species: 1 locus each at GDH-1, G6PDH, PGD, SOD, and 4 MDH loci. Allele frequencies for all polymorphic loci are given in Baskauf (1993). Echinacea tennesseensis and Echinacea angustifolia are monomorphic for the same allele at 50% of the loci sampled. However, marked differences exist in allele frequencies at four (22%) of the loci. At the remaining loci (28%), E. tennesseensis alleles tend to be a subset of those found in E. angustifolia. Only two alleles observed in the rare species were absent in the widespread species: a GDH-2 allele present at a high frequency (0.896), and an ACP allele occurring at a low frequency (0.038) in one population.
Interpopulation genetic identity values within species are consistently high (table 1). The mean genetic identity among E. tennesseensis populations is 0.991; the mean among E. angustifolia populations is 0.984. In contrast, E. tennesseensis and E. angustifolia have a mean identity value of 0.826. Pairwise interspecific identities are significantly lower than pairwise intraspecific identities (P < 0.05), as determined by the jackknifing procedure of Mueller and Ayala (1982).
Echinacea purpurea provides a useful context in which to consider the level of genetic divergence estimated between E. tennesseensis and E. angustlfolia. Echinacea purpurea is fixed for a unique allele at only one locus (PGI-I). Interestingly, the two E. purpurea populations themselves do not share any alleles at another locus (ACP). Echinacea purpurea is less homogeneous genetically than is E. tennesseensis or E. angustifolia, and its intraspecific genetic identity value is correspondingly lower (table 1). Echinacea purpurea has a mean genetic identity of 0.813 with E. tennesseensis and of 0.748 with E. angustifolia. Only the latter comparison is statistically significant (P < 0.05). UPGMA analysis results in populations being clustered according to putative species membership (fig. 2), confirming the relative level of dissimilarity among the species as compared to the similarity of populations within a given species.
Within both E. tennesseensis and E. angustifolia, populations tend to be genetically differentiated from each other, as indicated by [X.sup.2] contingency tests of allele frequencies at each polymorphic locus (P < 0.00001). At each E. tennesseensis site with subdivided populations even the "subpopulations" show overall significant heterogeneity at polymorphic loci; therefore, each subpopulation is considered a separate population in all analyses. Jackknifed means [+ or -] 1 SE) of the Fs. statistic are 0.092 [+ or -] 0.014) for E. tennesseensis with five polymorphic loci, and 0.072 (+ 0.015) for E. angustifolia with eight polymorphic loci. Therefore, less than 10% of the total genetic variability of either species is caused by differences among populations (although both Fsx values differ significantly from zero, P < 0.001), with the remainder of the variation caused by genetic heterogeneity within populations.
Genotype frequencies within Echinacea populations do not often deviate significantly from the Hardy-Weinberg expectations. Significant deviations (P < 0.05) occurred in I out of 29 tests (3.4%) for all E. tennesseensis
populations, and in 10 of the total 61 (16.4%) tests carried out for E. angustifolia. Likewise, both Echinacea species have [F.sub.IS] values close to 0, as would be expected for obligate outcrossers, although the [F.sub.IS] value for E. angustifolia is significantly different from 0 (P < 0.001). Jackknifed means [+ or -] I SE) are 0.025 [+ or -] 0.015) and 0.080 [+ or -] 0.020) for E. tennesseensis and E. angustifolia, respectively.
Although both E. tennesseensis and E. angustifolia show genetic variability for soluble enzymes, variability is higher in the wide ranging E. angustfolia. At the species level, 27.8% of the isozyme loci are polymorphic for E. tennesseensis as opposed to 44.4% for E. angustfolia. A total of 27 alleles was observed among 18 loci for E. tennesseensis (a mean of 1.5 alleles per locus), as compared with 45 alleles for E. angustlfolia (a mean of 2.5 alleles per locus). The contrast is not simply the result of having sampled the latter species over a larger area, because the same trends in genetic variability are evident at the "state" level where closely spaced E. angustifolia populations were sampled. In fact, every E. tennesseensis population has a lower level of heterozygosity than the least heterozygous E. angustifolia population (table 2). Examining means over populations, E. tennesseensis has fewer polymorphic loci (23% versus 40%), fewer alleles per locus ( 1.3 versus 1.9), and lower levels of observed heterozygosity (0.069 versus 0.152) than does E. angustifolia. Split-plot ANOVA found no significant differences in heterozygosity among populations for a single species (regardless of which half of the Kansas data is included in the case of E. angustifolia). However, heterozygosity is significantly different (P = 0.0001) between the two species when all populations of a species are pooled.
The endemic Echinacea tennesseensis has substantially less genetic variability than its widespread prairie relative Echinacea angustifolia. This is true not only at the species level but also at the population level, in which estimates of genetic diversity such as heterozygosity and percent polymorphic loci are on average about twice as great for the wide-ranging species. Estimates of genetic variability for the two species are comparable to the means given for the "endemic" and "widespread" categories from a compilation of plant studies in Hamrick and Godt (1990) (table 2). Thus, the contrast in genetic diversity for these closely related and ecologically similar species is consistent with the generalization that rare species tend to be genetically depauperate.
Species lacking genetic variability may have limited evolutionary potential under heterogeneous or changing environments (e.g., Frankel 1970, 1974; Franklin 1980; Soule 1980; Beardmore 1983; Bradshaw 1984; Antonovics 1984; Lande and Barrowclough 1987; Huenneke 1991). Although E. tennesseensis has lower levels of genetic diversity than E. angustifolia, the endemic is not entirely devoid of variability. Some rare plant species are much more depauperate. For example, Pinus torreyana shows no variability within populations, although the two extant populations are fixed for different alleles at two loci (Ledig and Conkle 1983). A past genetic bottleneck has been hypothesized for the species. Neither Pedicularisfurbishiae (Waller et al. 1987), a federally listed endangered species, nor Howellia aquatilis (Lesica et al. 1988), an endangered species candidate, show variability at any loci within or among the populations analyzed. The former species is subject to frequent extinction/recolonization events, and the latter species can experience dramatic fluctuations in population size. These processes can decrease genetic variability both within and between populations, because population crashes and colonization events, even if rare, can have a strong effect on the effective population size (Wright 1940; Nei et al. 1975; Lande and Barrowclough 1987; McCauley 1993).
What processes may have affected levels of genetic variation in the endemic? Despite a restricted range, relatively large local population sizes may be a major factor favoring the retention of some genetic variability in E. tennesseensis. Population estimates for the sampled sites range from about 4000 to 90,000 (Drew 1991), and random genetic drift should not erode genetic variability very rapidly in such a situation. However, little is known of the long-term stability of these populations. With a few localized but isolated populations, it is possible that dramatic population fluctuations or extinction and colonization events have occurred historically and played a role in decreasing the genetic variability of E. tennesseensis relative to the more continuously distributed E. angustifolia. Directional selection for
specialization in unique habitats could also restrict genetic variability in some endemics, but these two species show similar photosynthetic responses to light and soil moisture conditions (Baskauf 1993), and the endemic grows well in nonglade soils.
Although the two Echinacea species differ appreciably in absolute levels of genetic variability, a similar proportion of the variability is distributed within and among populations for both. This is despite the fact that the most distant E. angustifo/ia populations sampled are about 1300 km apart, as opposed to the 23 km separating the most distant E. tennesseensis populations. In their review, Hamrick and Godt (1990) also found that rare and widespread species generally did not differ in how they partitioned their variability. The Echinacea taxa are typical of outcrossing species in that the largest proportion of variability occurs within populations. The proportion caused by differences among populations (< 10%) is somewhat lower than commonly observed. Hamrick and Godt (1990), using Nei's Gsr statistic, which is similar to Wright's Fsr (Nei 1973), report a mean of nearly 20% for 124 outcrossing animal-pollinated species.
Echinacea tennesseensis and E. angustifolia are genetically distinct taxa, as indicated by the significant difference of within-species genetic identities as compared with the between-species genetic identities. That the morphologically distinctive E. purpurea and E. tennesseensis show a mean genetic identity not much lower than that found for the E. tennesseensis-E. angustifolia comparison is compatible with this conclusion.
The prospects for conservation of E. lennesseensis are encouraging. The species is not totally bereft of genetic variability and appears well adapted to its localized habitat. Its restriction to limestone glades appears caused mostly by intolerance of long-term shading (Baskauf 1993), as is the case for some other glade endemics (Baskin and Baskin 1988). However, extinction because of environmental stochasticity is a risk for any highly localized species limited to a few populations (Lande 1988; Simberloff 1988). The low level of population differentiation observed for E. tennesseensis suggests that the origin of seed used in establishing any new populations probably is not a critical consideration. Overall, it appears that protection of natural populations combined with the establishment of new populations and seed storage should greatly alleviate the threat of extinction for E. tennesseensis.
We thank S. J. Baskauf for valuable field assistance and technical support. Information aiding in locating collection sites was kindly provided by P. Somers, R. L. McGregor, W. T. Barker, G. E. Larson, and B. Lipscomb. We thank the Tennessee Department of Conservation, The Nature Conservancy of Tennessee, and the Missouri Department of Natural Resources for permission to collect leaves at protected sites. B. Schuette kindly collected leaves from the Missouri site. The Tennessee Department of Conservation, through the assistance of P. Somers and P. B. Hamel, provided computer facilities necessary to run the NEIC program, and advice from M. Dietrich and P. Hancock facilitated the SAS analysis. C. W. dePamphilis, E. S. Menges, and an anonymous reviewer provided constructive comments on an earlier draft of this manuscript. The research was supported by grants to C. J. Baskauf from the Tennessee Department of Conservation, Sigma Xi, and Vanderbilt University.
Antonovics, J. 1984. Genetic variation within populations. Pp. 229-241 in R. Dirzo and J. Samkhan, eds. Perspectives on plant population ecology. Sinauer, Sunderland, Mass.
Baskin, J. M., and C. C. Baskin. 1988. Endemism in rock outcrop plant communities of unglaciated eastern United States: An evolution of the roles of the edaphic, genetic, and light factors. Journal of Biogeography 15:829-840.
Baskauf, C.J. 1993. Comparative population genetics and ecophysiology of a rare and a widespread species of Echinacea (Asteraceae). Ph.D. diss. Vanderbilt University, Nashville, Tenn.
Beardmore, J.A. 1983. Extinction, survival, and genetic variation. Pp. 125-163 in C. M. SchonewaldCox et al., eds. Genetics and conservation. Benjamin/Cummings, Menlo Park, Calif.
Bradshaw, A.D. 1984. Ecological significance of genetic variation between populations. Pp. 213-228 in R. Dirzo and J. Sarukhan, eds. Perspectives on plant population ecology. Sinauer, Sunderland, Mass.
Cronquist, A. 1980. Vascular flora of the Southeastern United States, vol. 1. Asteraceae. University of North Carolina Press, Chapel Hill.
Drew, M.B. 1991. The role of Tennessee coneflower, Echinacea tennesseensis, in its native habitat: the vegetation and a demographic analysis. Master's thesis. University of Tennessee, Knoxville.
Falk, D.A. 1990. Integrated strategies for conserving plant genetic diversity. Annals of the Missouri Botanical Garden 77:38-47.
Falk, D. A., and K. E. Holsinger, eds. 1991. Genetics and conservation of rare plants. Oxford University Press, New York.
Fiedler, P. L. 1986. Concepts of rarity in vascular plant species, with special reference to the genus Calochortus Pursh (Liliaceae). Taxon 35:502-518.
Frankel, O.H. 1970. Variation, the essence of life. Sir William Macleay Memorial Lecture. Proceedings of the Linnean Society 95:158-169.
______. 1974. Genetic conservation: our evolutionary responsibility. Genetics 78:53--65.
Frankel, O. H., and M. E. Soul& 1981. Conservation and evolution. Cambridge University Press, Cambridge.
Franklin, I. R. 1980. Evolutionary change in small populations. Pp. 135-149 in M. E. Soulfi and B. A. Wilcox, eds. Conservation biology: an evolutionary-ecological perspective. Sinauer, Sunderland, Mass.
Gottlieb, L. D. 1981. Electrophoretic evidence and plant populations. Progress in Phytochemistry 7:146.
Hamrick, J. L., and M. J. W. Godt. 1990. Allozyme diversity in plant species. Pp. 43-63 in A.H.D. Brown et al., eds. Plant population genetics, breeding, and genetic resources. Sinauer, Sunderland, Mass.
Hamrick, J. L., M. J. W. Godt, D. A. Murawski, and M.D. Loveless. 1991. Correlations between species traits and allozyme diversity: implications for conservation biology. Pp 75-86 in D. A. Falk and K. E. Holsinger, eds. Genetics and conservation of rare plants. Oxford University Press, New York.
Hemmerly, T.E. 1976. Life cycle strategy of a highly endemic cedar glade species: Echinacea tennesseensis (Compositae). Ph.D. diss. Vanderbilt University, Nashville, Tenn.
Holsinger, K.E. 1993. The evolutionary dynamics of fragmented plant populations. Pp. 198-215 in P.
M. Kareiva et al., eds. Biotic interactions and global change. Sinauer, Sunderland, Mass.
Huenneke, L.F. 1991. Ecological implications of genetic variation in plant populations. Pp. 31-44 in D. A. Falk and K. E. Holsinger, eds. Genetics and conservation of rare plants. Oxford University Press, New York.
Karron, J.D. 1987. A comparison of levels of genetic polymorphism and self-compatibility in geographically restricted and widespread plant congeners. Evolutionary Ecology 1:47-58.
_____. 1991. Patterns of genetic variation and breeding systems in rare plant, species. Pp. 87-98 in D. A. Faik and K. E. Holsinger, eds. Genetics and conservation of rare plants. Oxford University Press, New York.
Kruckeberg, A. R., and D. Rabinowitz. 1985. Biological aspects of endemism in higher plants. Annual Review of Ecology and Systematics 16:447479.
Lande, R. 1988. Genetics and demography in biological conservation. Science 241:1455-1460.
Lande, R., and G. F. Barrowclough. 1987. Effective population size, genetic variation, and their use in population management. Pp. 87-124 in M. E. SoulS, ed. Viable populations for conservation. Cambridge University Press, Cambridge.
Ledig, F. T., and M. T. Conkle. 1983. Gene diversity and genetic structure in a narrow endemic, Torrey pine (Pinus torreyana Parry ex Carr.). Evolution 37: 79-85.
Lesica, P., R. F. Leary, F. W. Allendorf, and D. E. Bilderback. 1988. Lack of genetic diversity within and among populations of an endangered plant, Howellia aquatilis. Conservation Biology 2:275-282.
Lessios, H.A. 1990. A program for calculating Nei's genetic distances and their jackknifed confidence intervals. Journal of Heredity 81:422.
McCauley, D.E. 1993. Genetic consequences of extinction and recolonization in fragmented habitats. Pp. 217-233 in P.M. Kareiva et al., eds. Biotic interactions and global change. Sinauer, Sunderland, Mass.
McGregor, R.L. 1968. The taxonomy of the genus Echinacea (Compositae). University of Kansas Science Bulletin 48:113-142.
Mueller, L. D., and F. J. Ayala. 1982. Estimation and interpretation of genetic distance in empirical studies. Genetical Research 40:127-137.
Nei, M. 1973. Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences, USA 70:3321-3323.
_____. 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89:583-590.
Nei, M., T. Maruyama, and R. Chakraborty. 1975. The bottleneck effect and genetic variability in populations. Evolution 29:1-10.
Quarterman, E. 1989. Structure and dynamics of the limestone cedar glade communities in Tennessee. Journal of the Tennessee Academy of Science 64: 155-158.
SAS Institute. 1988. SAS/STAT user's guide, release 6.03 edition. SAS Institute, Cary, N.C. Schonewald-Cox, C. M. S. M. Chambers, B. MacBryde, and W. L. Thomas, eds. 1983. Genetics and conservation. Benjamin/Cummings, Menlo Park, Calif.
Simberloff, D. 1988. The contribution of population and community biology to conservation science. Annual Review of Ecology and Systematics 19:473511.
Sneath, P. H. A., and R. R. Sokal. 1973. Numerical taxonomy. Freeman, San Francisco, Calif.
Soltis, D. E., C. H. Haufler, D.C. Darrow, and G. J. Gastony. 1983. Starch gel electrophoresis of ferns: a compilation of grinding buffers, gel and electrode buffers, and staining schedules. American Fern Journal 73:9-27.
Soule, M. E. 1980. Thresholds for survival: maintaining fitness and evolutionary potential. Pp. 151169 in M. E. Soul6 and B. A. Wilcox, eds. Conservation biology: an evolutionary-ecological perspective. Sinauer, Sunderland, Mass.
______, ed. 1986. Conservation biology: the science of scarcity and diversity. Sinauer, Sunderland, Mass.
Soule, M. E., and B. A. Wilcox, eds. 1980. Conservation biology: an evolutionary-ecological perspective. Sinauer, Sunderland, Mass.
Stebbins, G.L. 1942. The genetic approach to problems of rare and endemic species. Madrofio 6:241258.
_______. 1980. Rarity of plant species: a synthetic viewpoint. Rhodora 82:77-86.
Swofford, D. L., and R. K. Selander. 1989. Biosys-1, a computer program for the analysis of allelic variation in genetics. Release 1.7. User's manual. University of Illinois, Urbana.
U.S. Fish and Wildlife Service. 1989. Tennessee coneflower recovery plan. U.S. Fish and Wildlife Service, Asheville, N.C.
Waller, D. M., D. M. O'Malley, and S.C. Gawler. 1987. Genetic variation in the extreme endemic Pedicularis furbishiae (Scrohulariaceae). Conservation Biology 1:335-340.
Weir, B.S. 1990. Genetic data analysis: methods for discrete population genetic data. Sinauer, Sunderland, Mass.
Weir, B. S., and C. C. Cockerham. 1984. Estimating F-statistics for the analysis of population structure. Evolution 38:1358-1370.
Werth, C.R. 1985. Implementing an isozyme laboratory at a field station. Virginia Journal of Science 36:53-73.
Wright, S. 1940. Breeding structure of populations in relation to speciation. American Naturalist 74: 232-248.
________. 1978. Variability within and among natural populations, vol. 4. Evolution and the genetics of populations. The University of Chicago Press, Chicago.
Wyatt, R., E. A. Evans, and J. C. Sorenson. 1992. The evolution of self-pollination in granite outcrop species of Arenaria (Caryophyllaceae). VI. Electrophoretically detectable genetic variation. Systematic Botany 17:201-209.
|Printer friendly Cite/link Email Feedback|
|Author:||Baskauf, Carol J.; McCauley, David E.; Eickmeier, William G.|
|Date:||Feb 1, 1994|
|Previous Article:||Using phylogenies to test hypotheses of adaptation: a critique of some current proposals.|
|Next Article:||Rate limits for mispairing and compensatory change: the mitochondrial ribosomal DNA of antelopes.|