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Evolution, 55(4), 2001, pp. 677±683

EVOLUTIONARY RATES AND DIVERSITY IN FLOWERING

TIMOTHY G. BARRACLOUGH1 AND VINCENT SAVOLAINEN2 1Department of Biology and NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berkshire SL5 7PY, United Kingdom E-mail: [email protected] 2Molecular Systematics Section, Jodrell Laboratory, Royal Botanic Gardens, Kew, Richmond Surrey TW9 3DS, E-mail: [email protected]

Abstract. Genetic change is a necessary component of speciation, but the relationship between rates of speciation and molecular remains unclear. We use recent phylogenetic data to demonstrate a positive relationship between species numbers and the rate of neutral molecular evolution in ¯owering plants (in both plastid and nuclear ). Rates of protein and morphological evolution also correlate with the neutral substitution rate, but not with species numbers. Our ®ndings reveal a link between the rate of neutral molecular change within populations and the evolution of species diversity.

Key words. Angiosperms, DNA, molecular evolution, speciation, species richness.

Received July 17, 2000. Accepted October 31, 2000.

Speciation is dependent on genetic change: changes at the Chase et al. (1993) based on DNA sequences of rbcL, a plastid DNA level allow populations to diverge and ultimately to encoding the large subunit of ribulose-1,5-biphosphate- form new species (Harrison 1991; Coyne 1992; Coyne and carboxylase/oxygenase (RUBISCO), we found evidence for Orr 1999). However, the relationship between rates of spe- a positive relationship between rates of DNA change and ciation and molecular evolution remains uncertain. Many au- species diversi®cation (Barraclough et al. 1996; Savolainen thors argue that rates of genetic change and speciation are and Goudet 1998). However, this result relied on a prelim- closely linked. For example, bursts of genetic change may inary phylogenetic analysis, in terms of the classi®cation used occur at speciation events, as a result of population structures and incomplete sampling of angiosperm families. Further- associated with speciation (Mayr 1963; Carson and Temple- more, subsequent power analyses raised serious doubts over ton 1984; Gavrilets and Hastings 1996; Templeton 1996). the robustness of the pattern (Savolainen and Goudet 1998). Alternatively, the divergence of new species may be driven Since then, comprehensive multigene and nonmolecular data by ``background'' rates of genetic change within populations have been produced for angiosperms, as well as a new clas- (Coyne 1994; Orr 1995). However, there may also be no si®cation based on the combined data (Watson and Dallwitz relationship between speciation and rates of genetic change, 1991, 1999; APG 1998; Soltis et al. 1999; Qiu et al. 1999). for example, if speciation is limited by the formation of iso- These data provide the opportunity for comprehensive and lated populations rather than by rates of genetic divergence robust tests of the correlation between the rate of DNA evo- (Allmon 1992), or if population structure at speciation has lution and species richness. no in¯uence on rates of genetic change (Coyne 1994). In In addition, we use the recent data to perform new analyses addition, the nature of DNA change typically involved in investigating the possible role of adaptive changes in ex- speciation remains unknown. Recent work highlights the role plaining the observed relationship. One explanation for a pos- of ecological and adaptive changes in promoting species di- itive relationship between sequence change and species num- vergence (Orr and Smith 1998; Rundle et al. 2000), but in- bers might be that genetic change at the chosen loci is as- trinsic factors affecting the origin of neutral genetic variation sociated with the adaptive radiation of angiosperm families. within lineages may also play a major role (Orr 1995). Re- For example, substitutions at the rbcL locus have been linked solving these issues is fundamental for understanding the link to differences in photosynthetic pathways among plants oc- between evolution occurring within populations and the or- cupying different habitats (Hudson et al. 1990). Hence, igin of species diversity (Williams 1992), but to date evidence changes at the rbcL locus might, in principle, be associated has been scarce (Mindell et al. 1989; but see Sanderson 1990). with the adaptive radiation of lineages among habitat Here we use sister-group comparisons to demonstrate a types. If this were the case, we might expect the rate of amino positive relationship between species richness and the rate acid substitutions (nonsynonymous mutations) at the rbcL of neutral molecular evolution in ¯owering plants. Flowering locus to display the strongest relationship. Our previous work plants (angiosperms) are an ideal study group for investi- did not investigate this possibility. Thus, we test whether gating these questions. Not only are they the product of one synonymous or nonsynonymous changes display the stronger of the major radiations of organisms on earth, but they have relationship with species numbers. We also perform related also been the focus of the most comprehensive molecular analyses comparing sites which differ in their effects on the systematics project carried out on any equivalent-sized group functional secondary structure of 18S rDNA (details in Meth- of organisms (Chase et al. 1993, Soltis et al. 1999, 2000). In ods). addition, the rate of DNA evolution in both plastid and nu- A second possible adaptive explanation would be if fast clear genes has been shown to vary widely among lineages rates of sequence change lead to increased rates of functional (Clegg et al. 1994, 1997), although the causes are still not phenotypic change within lineages. In this case, phenotypic fully understood. Previously, using an early phylogeny by change could be an intermediate factor linking rates of mo- 677 ᭧ 2001 The Society for the Study of Evolution. All rights reserved. 678 T. G. BARRACLOUGH AND V. SAVOLAINEN lecular evolution to the adaptive radiation of families. To where N1 and N2 are the numbers of species in sister families investigate this possibility, we consider rates of morpholog- 1 and 2. We use (X1)±(X2) as the branch length contrast, where ical change among angiosperm families. Morphological rates X1 and X2 are the branch lengths. Signi®cance of the asso- have been found to correlate with rates of DNA change in ciation was assessed by least squares regression forced some other groups (Omland 1997), but the correlation with through the origin (Harvey and Pagel 1991). species numbers has not been tested in previous studies. In We perform additional analyses to investigate the effects addition, is one aspect of the phenotype that has of several possible sampling artifacts on our results. First, been scored for all plant families. Therefore, we use mor- our analyses rely on accurate knowledge of sister re- phological characters from an online database of angiosperm lationships. The three-gene phylogeny does not include all families (Watson and Dallwitz 1991, 1999) to test whether angiosperm families, and therefore missing families would morphological rates of change are correlated with species be likely to disrupt some of our sister pairs if they were richness and/or molecular rates within angiosperms. included in the phylogeny. We assessed the likely impact of incomplete sampling by repeating our analyses including METHODS only those sister family pairs also found in analyses with complete taxonomic representation, but based mostly on few- We use the recently published phylogenetic analysis by er genes (Qiu et al. 1999; Chase et al. 2000; Savolainen et Soltis et al. (1999) and Soltis et al. (2000), based on three al. 2000). Second, the three-gene phylogeny may contain genes from both plastid and nuclear genomes (rbcL, atpB, errors in topology simply due to weak signal or sampling 18S rDNA, total 4811 base pairs). This new phylogeny of error in the data. We assessed the possible impact of these angiosperms is the most encyclopedic so far: the is well errors by repeating our analysis including only those sister resolved, well supported, and includes 75% coverage of plant families judged to be strongly supported by Soltis and co- families as de®ned by the new classi®cation by the Angiosperm workers (jackknife support Ͼ 85%; Soltis et al. 1999). Fi- Phylogeny Group (APG 1998). The matrix is available from nally, one possible bias affecting our analyses is that max- the website http://www.wsu.edu:8080/ϳsoltilab/three࿞gene࿞ imum parsimony (and possibly maximum likelihood) may /nature.html. We identi®ed all sister family pairs from reconstruct longer branch length in families in which more the phylogeny (listed in the Appendix), where sister families terminals were sampled, the so-called node density effect are de®ned as two families derived directly from a single (Sanderson 1990). If the angiosperm phylogeny tended to common ancestor. We compare sister families so as to max- include more terminals for families with more species, this imize the number of comparisons in our analyses, without could lead to a bias. We controlled for this effect by repeating including nested comparisons. Our analysis only relies on the the analysis including only those comparisons with equal families being sister and does not depend upon their numbers of terminal taxa sampled in each sister family. status as families. Species numbers were taken from an online We repeated all analyses for each of the three loci sepa- angiosperm database (Watson and Dallwitz 1991, 1999) and rately, to test for homogeneity of effect among DNA regions adjusted in cases for which the APG classi®cation differs and between the plastid and nuclear genomes. To test whether from previous classi®cations with respect to the family mem- the strength of relationship between species numbers and bership of genera. rates of DNA change differs between synonymous and non- The branch lengths of each family pair were reconstructed synonymous sites, we translated the rbcL and atpB exons into from the three-gene data set using both maximum parsimony amino acids (using the universal translation table in Mac- and maximum likelihood. Parsimony branch lengths were version 3.04, Maddison and Maddison 1992). The reconstructed using ACCTRAN optimization in PAUP* ver- number of synonymous substitutions (namely those that do sion 4.0b2a (Swofford 2000). Maximum-likelihood branch not affect amino acid sequence) on each branch was calcu- lengths were ®tted using the Hasegawa-Kishino-Yano model lated as the total number of base substitutions in rbcL and of DNA evolution (HKY85, Hasegawa et al. 1985) with base atpB combined, minus the number of amino acid substitu- frequencies and transition/transversion ratios estimated from tions. Note that if multiple substitutions leading to amino the data. Branch lengths obtained allowing rate heterogeneity acid changes have occurred within a single codon, for ex- among sites were very strongly correlated with those obtained ample, at both the ®rst and second positions, our approach using the HKY85 model without rate variation, and so we would overestimate the frequency of synonymous substitu- present only the results using the computationally simpler tions. However, the frequencies of ®rst and second position model. Where more than one terminal was included changes between sister families are so low (less than 1% at per family, we calculated the branch length for the family by both positions) that this effect is likely to be negligible in progressively averaging branch lengths at each node within our dataset. We then regressed species numbers against the the family, starting from the tips (see Barraclough et al. 1996; rates of synonymous and nonsynonymous substitutions sep- Savolainen and Goudet 1998). arately. We also used information on the secondary structure Since sister-families are, by de®nition, the same age, their of 18S rDNA to compare substitution rates between stem and branch lengths re¯ect relative rates of sequence change: the loop sites (Soltis and Soltis 1998). Stem sites are constrained family with the longer branch has experienced a faster rate because single mutations would disrupt the base pairing nec- of nucleotide substitution. Thus, we test for an association essary for the stem structure, whereas individual loop sites between relative branch lengths and species numbers. Be- can change without affecting functional secondary structure, cause diversi®cation is an exponential process (Purvis 1996), that is, they are effectively neutral. Thus, if adaptive mech- we use Log(N1)ÐLog(N2) as the species richness contrast, anisms explain the relationship, we would expect a stronger EVOLUTIONARY RATES AND SPECIES DIVERSITY 679

FIG. 1. The relationship between contrasts of maximum parsimony branch lengths and contrasts of maximum likelihood branch lengths across sister family pairs for the combined molecular data. For both FIG. 2. The relationship between contrasts in species numbers and axes, contrasts were calculated as (X1-X2), where X1 and X2 are the molecular branch lengths. We use Log(N1)±Log(N2) and (X1)±(X2) branch lengths of sister families 1 and 2 respectively; family 1 has as contrasts, where N1 and N2 are the numbers of species in sister the longer branch under maximum parsimony. The line was ®tted families 1 and 2, X1 and X2 are the maximum parsimony branch by least squares regression forced through the origin (t ϭ 44.7, P lengths, and family 1 has the longer branch. Points above the X- Ͻ 0.0001). axis represent a positive association. The line was ®tted by least squares regression forced through the origin. Statistics are given in Table 1. relationship for stem and nonsynonymous sites rather than for loop and synonymous sites. Finally, we used 440 morphological characters from the completeness, between synonymous versus nonsynonymous online database of Watson and Dallwitz (1991, 1999) to cal- and stem versus loop sites, and between different categories culate relative rates of morphological change between each of morphological characters. However, these are not inde- pair of sister families. The characters include vegetative and pendent tests but are used to determine the in¯uence of var- reproductive morphological characters and were chosen by ious subsets of the data on the overall relationship. Hence the authors to present a broad morphological description of we do not correct for multiple P-values in these analyses. each family suitable for taxonomic and identi®cation pur- Our three central tests are for the correlations between species poses. For each terminal taxon in the Soltis et al. (1999) numbers and overall rates of morphological and molecular matrix, we pasted in the morphological data for its family evolution. from the Watson and Dallwitz (1999) database. As a result, the data were identical for all representatives within a family, RESULTS but we reconstructed the number of morphological changes among families onto branches of the tree using maximum Maximum likelihood and parsimony yield branch lengths parsimony. The difference in branch length between sister that are highly correlated (Fig. 1). The results we obtain families re¯ects their relative rates of change in the mor- subsequently are qualitatively the same in each case, and so phological characters used. Hence, we used (X1)Ð(X2) as the for conciseness we present only the results using maximum contrast in morphological branch length between sister fam- parsimony. ilies 1 and 2. We repeated our analyses for all characters, Figure 2 shows the relationship between contrasts of spe- and vegetative characters and reproductive characters (in- cies numbers and branch lengths. In a signi®cant proportion cluding ¯oral, and ) separately. Note that the mor- of sister family pairs, the more species-rich family also has phological data included polymorphic characters. These were the longer branch (57/89, P ϭ 0.005, sign test), supporting coded as genuine polymorphic characters, using the brackets a relationship between diversi®cation rates and the rate of notation in PAUP* and included in the analyses. Because nucleotide substitution. Results from regression analyses are larger families may be more likely to display polymorphism shown in Table 1. The relationship between species numbers than small families, this could lead to a bias in our analyses and DNA change is robust to the three possible sources of that larger families tend to display greater apparent rates of sampling artifact or error. The relationship is weaker in the change. We discuss this bias further below. jackknife treatment (the sample size is lowest in this treat- Note that we performed a relatively large number of tests ment), but the effect is still signi®cant. There is large scatter to compare the strength of relationship in different subsets about the regression line, suggesting unsurprisingly that the of the data: within each of the genes separately, including/ relationship is not the only cause of variation in diversi®- excluding nodes differing in sampling effort, support or likely cation rates and molecular evolution between sister families, 680 T. G. BARRACLOUGH AND V. SAVOLAINEN

TABLE 1. Regressions between contrast of species numbers, and molecular and morphological branch lengths among sister families of ¯owering plants. Analyses were repeated on subsets of nodes based on three criteria: complete nodes judged unlikely to be affected by addition of missing families, nodes with jackknife scores Ͼ85%, and nodes with an equal number of terminal taxa sampled in both sister families. Probabilities: ns P Ͼ 0.05, * P Ͻ 0.05, ** P Ͻ 0.01, *** P Ͻ 0.001.

Robustness analyses:

All comparisons Complete Jackknife n ϭ 89 sampling Ͼ85% Equal terminals n ϭ 54 n ϭ 48 n ϭ 53 Y-variable X-variable Slope tP P P P species numbers total DNA 0.03 4.8 Ͻ0.0001 *** * *** species numbers rbcL 0.06 4.3 Ͻ0.0001 * ns ** species numbers atpB 0.06 4.2 Ͻ0.0001 ** * *** species numbers 18S 0.06 3.0 0.003 ** ns * species numbers synonymous 0.04 4.7 Ͻ0.0001 *** * ** species numbers nonsynonymous 0.08 2.9 0.005 ns ns ** species numbers loop 0.21 3.4 0.001 * ns * species numbers stem 0.07 2.4 0.016 ** ns ns species numbers total morphology 0.06 1.2 0.23 ns ns ns species numbers vegetative 0.27 2.1 0.04 * ns ns species numbers reproductive 0.03 0.6 0.59 ns ns ns total morphology total DNA 0.06 4.3 Ͻ0.0001 *** * ** total morphology synonymous 0.08 3.9 0.0002 ** * ** total morphology nonsynonymous 0.12 1.8 0.08 ns ns ns vegetative total DNA 0.01 2.0 0.05 * * ns reproductive total DNA 0.05 4.3 Ͻ0.0001 *** ns ** but the relationship is consistently signi®cant across treat- productive characters than vegetative characters. However, ments. there is no signi®cant relationship between morphological Comparing results among DNA regions is complicated by change and species numbers: the marginal relationship be- the fact that lengths of DNA and average rates of change tween vegetative change and species numbers is sensitive to vary among regions, but the species richness contrasts used the robustness analyses. This lack of relationship is in the are the same for each treatment. As a result, slopes tend to opposite direction to the possible bias outlined above that be greater for shorter length gene sequences or slower evolv- polymorphic characters may be more common in species-rich ing DNA regions (because fewer changes have accumulated). families, thereby increasing the branch lengths of species- However, t-and P-values are unaffected by this complication rich families. and therefore we base our comparisons between treatments on these values. Rates of change among the three loci are DISCUSSION highly correlated, and all three regions show a signi®cant relationship with species numbers when analyzed separately Together, our results show that rates of amino acid and (Table 1). structural ribosomal DNA substitutions, morphological Table 1 shows the relationship between species numbers change and diversi®cation rates all correlate with the neutral and rates of synonymous versus nonsynonymous substitu- substitution rate. The results appear to be robust to likely tions. Both synonymous and nonsynonymous substitutions sampling errors or biases affecting the data. The morpho- display a signi®cant relationship with species numbers, but logical dataset comprises an arbitrary selection of morpho- it is synonymous changes that show the strongest effect. The logical characters chosen by Watson and Dallwitz (1991) to rate of nonsynonymous substitutions strongly correlates with re¯ect broad morphology of plant families. Although the the rate of neutral change (n ϭ 89, t ϭ 8.1, P Ͻ 0.0001, least morphological rates may represent only a rough estimate of squares regression of contrasts), but when we control for this some ideal measure of overall morphological change, we can- association, there is no residual relationship between non- not think of speci®c biases that are likely to affect the sample synonymous substitutions and species numbers (n ϭ 89, t ϭ of characters used and believe the lack of relationship be- 0.04, P Ͼ 0.9, least-squares regression). Similar results were tween morphological rates and species numbers re¯ects a found comparing stem and loop sites in 18S rDNA. Both genuine pattern. Therefore, we ®nd no evidence for adaptive categories display a signi®cant relationship with species explanations of the relationship between molecular rates and numbers, but the effect is strongest in loop regions, where species numbers, either those directly affecting the loci we substitutions are expected to be effectively neutral because consider, or via the effects of sequence change on rates of they do not affect the secondary structure of the 18S rDNA. morphological change. Thus, neutral changes display a stronger pattern than func- We can think of three possible explanations for the ob- tional changes in both protein-coding and ribosomal DNA served patterns. First, generation times may vary among an- regions. giosperms, perhaps speeding up the rates of phyletic change Rates of morphological change are signi®cantly correlated and speciation in absolute time (Bromham et al. 1996; Gaut with rates of molecular change, particularly with the rate of et al. 1996). There is insuf®cient variation between the simple synonymous substitution. The effect is stronger among re- distinction of annual and perennial life-cycle to explain our EVOLUTIONARY RATES AND SPECIES DIVERSITY 681 observations (data not shown), but it remains possible that G. M. Plunkett, P. S. Soltis, S. M. Swensen, S. E. Williams, P. factors such as seed bank duration or the number of cell cycles A. Gadek, C. J. Quinn, L. E. Eguiarte, E. Golenberg, G. H. Learn, Jr, S. W. Graham, S. C. H. Barrett, S. Dayanandan, and V. A. in the germ line could have an effect. Second, population Albert. 1993. of seed plants: an analysis of nu- size could be an intermediary factor. All modes of speciation cleotide sequences from the plastid gene rbcL. Ann. Mo. Bot. involve population division and so species-rich lineages may Gard. 80:528±580. be characterized by, on average, lower population sizes. Chase, M. W., D. E. Soltis, P. S. Soltis, P. J. Rudall, M. F. Fay, W. H. Hahn, S. Sullivan, J. 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Evol. 21:160±174. We thank L. Watson for sending the morphological matrix, Hudson, G. S., J. D. Mahon, P. A. Anderson, M. J. Gibbs, M. R. P. Soltis for sending the secondary structure of 18S rDNA; Badger, T. J. Andrews, and P. R. Whitfeld. 1990. Comparison N. Salamin and E. Guldner for helping to process the data; of rbcL genes for the large subunit of ribulose-bisphosphate and D. Baum, A. Burt, M. Chase, D. Charlesworth, J. Coyne, carboxylase from closely related C3 and C4 plant species. J. Biol. Chem. 265:808±814. P. Harvey, and an anonymous referee for critical comments Kellogg, E. A., and N. D. Juliano. 1997. The structure and on the manuscript. VS was supported by the Swiss National of RuBisCO and their implications for systematic studies. Am. Science Foundation and the Royal Botanic Gardens, Kew, J. Bot. 85:413±428. and TGB by a Royal Society University Research Fellowship. Maddison, W. P., and D. R. Maddison. 1992. MacClade vers. 3.04. 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2000. Natural selection and parallel speciation in sympatric APPENDIX. Continued. sticklebacks. Science 287:306±308. Sanderson, M. J. 1990. Estimating rates of speciation and evolution: Number Parsimony Likelihood a bias due to homoplasy. Cladistics 6:387±391. of branch branch Savolainen, V., and J. Goudet. 1998. Rate of gene sequence evo- Family pairs species lengths lengths lution and species diversi®cation in ¯owering plants: a re-eval- Hyacinthaceae 600 63.5 0.0152 uation. Proc. R. Soc. Lond. B 265:603±607. Themidaceae 70 48 0.0122 Savolainen, V., M. F. Fay, D. C. Albach, A. Backlund, M. van der Bank, K. M. Cameron, S. A. Johnson, M. D. LledoÂ, J.-C. Pintaud, Asphodelaceae 750 123 0.0288 M. Powell, M. C. Sheahan, D. E. Soltis, P. S. Soltis, P. Weston, Xanthorrhoeaceae 66 24 0.0058 W. M. Whitten, K. J. Wurdack, and M. W. Chase. 2000. Phy- Tecophilaeaceae 22 89.5 0.0204 logeny of the : a nearly complete familial analysis based Ixilirionaceae 3 102 0.0253 on rbcL gene sequences. Kew Bull. 55:257±309. Orchidaceae 19500 150 0.0346 Soltis, P. S., and D. E. Soltis. 1998. Molecular evolution of 18S Hypoxidaceae 150 96 0.0249 rDNA in angiosperms: implications for character weighting in phylogenetic analysis. Pp 188±210 in D. E. Soltis, P. S. Soltis, Liliaceae 400 98 0.0205 and J. J. Doyle, eds. Molecular systematics of plants. II. DNA Smilicaceae 317 77 0.0190 sequencing. Kluwer Academic, Dordrecht, The Netherlands. Alstroemeriaceae 200 91 0.0212 Soltis, P. S., D. E. Soltis, and M. W. Chase 1999. Angiosperm Colchicaceae 200 93 0.0235 phylogeny inferred from multiple genes as a tool for comparative Cyclanthaceae 180 51 0.0107 biology. Nature 402:402±404. Pandanaceae 700 74 0.0188 Soltis, D. E., P. S. Soltis, M. W. Chase, M. E. Mort, D. C. Albach, M. Zanis, V. Savolainen, W. H. Hahn, S. B. Hoot, M. F. Fay, Stemonaceae 23 72 0.0158 M. Axtell, S. M. Swensen, K. C. Nixon, and J. S. Farris. 2000. Velloziaceae 270 113 0.0270 Angiosperm phylogeny inferred from a combined data set of Dioscoreaceae 625 77 0.0177 18S rDNA, rbcL, and atpB sequences. Bot. J. Linn. Soc. 133: Taccaceae 31 64 0.0189 381±461. Zosteraceae 18 125 0.0415 Swofford, D. L. 2000. PAUP*: phylogenetic analysis using parsi- Hydrocharitaceae 100 138 0.0382 mony (* and other methods). vers. 4.0b2a Sinauer Associates, Sunderland, MA. Costaceae 200 49.25 0.0117 Templeton, A. R. 1996. Experimental evidence for the genetic tran- Marantaceae 450 50.5 0.0115 silience model of speciation. Evolution 50:909±915. Zingiberaceae 1000 131.75 0.0307 Watson, L., and M. J. Dallwitz 1991. The families of angiosperms: Cannaceae 9 68 0.0160 automated descriptions, with interactive identi®cation and in- Strelitziaceae 7 40.25 0.0087 formation retrieval. Aust. Syst. Bot 4:681±695. Lowiaceae 2 56 0.0132 ÐÐÐ. 1999. The families of ¯owering plants: descriptions, illus- trations, identi®cation, and information. http://biodiversity. Commeliinaceae 500 139 0.0358 uno.edu/delta/. Retrieval version: 19 Aug. 1999. Pontederiaceae 30 117 0.0285 Williams, G. C. 1992. Natural selection: domains, levels and chal- Poaceae 8700 205 0.0487 lenges. Oxford Univ. Press, Oxford, U.K. Restionaceae 320 119 0.0301 Cyperaceae 4500 159.5 0.0352 Corresponding Editor: D. Baum Juncaceae 400 127 0.0352 Cactaceae 1400 21 0.0047 Portulacaceae 450 36 0.0094 APPENDIX Caryophyllaceae 2200 89 0.0272 Sister family pairs, species numbers, and maximum-parsimony (MP) Amaranthaceae 2360 110 0.0253 and maximum-likelihood (ML) branch lengths. Dioncophyllaceae 3 46 0.0127 Number Parsimony Likelihood Ancistrocladaceae 20 27 0.0069 of branch branch Frankeniaceae 90 98 0.0241 Family pairs species lengths lengths Tamaricaceae 120 68 0.0149 Annonaceae 2300 127 0.0291 Plumbaginaceae 775 130.5 0.0300 Eupomatiaceae 2 50 0.0128 Polygonaceae 800 80 0.0206 Himantandraceae 2 51 0.0129 Santalaceae 400 83 0.0190 Degeneriaceae 1 30 0.0066 Loranthaceae 940 167 0.0395 Canallaceae 16 95.5 0.0224 Berberidopsidaceae 3 23 0.0057 Winteraceae 90 65 0.0145 Aetoxicaceae 1 39 0.0090 Gomortegaceae 1 31 0.0072 Myrothamnaceae 2 45 0.0103 Antherospermataceae 12 23 0.0069 Gunneraceae 50 89 0.0216 Piperaceae 2000 202 0.0475 Didymelaceae 2 133 0.0330 Saururaceae 7 59 0.0127 Buxaceae 100 63 0.0140 Illiciaceae 42 37 0.0087 Platanaceae 9 28 0.0074 Schisandraceae 47 32 0.0072 Proteaceae 1050 83 0.0184 Anthericaceae 250 56 0.0145 Lardizabalaceae 35 61.5 0.0144 Behniaceae 1 31 0.0064 Circaeasteraceae 1 180 0.0430 Alliaceae 645 135 0.0331 Berberidaceae 575 73.5 0.0186 Asparagaceae 370 89 0.0211 Ranunculaceae 1500 117.625 0.0251 EVOLUTIONARY RATES AND SPECIES DIVERSITY 683

APPENDIX. Continued. APPENDIX. Continued.

Number Parsimony Likelihood Number Parsimony Likelihood of branch branch of branch branch Family pairs species lengths lengths Family pairs species lengths lengths Haloragaceae 120 102.5 0.0245 4 83 0.0200 Penthoraceae 3 41 0.0089 Malvaceae 2330 93.21875 0.0198 Pterostemonaceae 2 29 0.0074 Vochysiaceae 200 100 0.0244 Iteaceae 17 43 0.0090 Heteropyxidaceae 3 38 0.0076 Paeoniaceae 33 151 0.0358 Memecyclaceae 430 61 0.0148 Daphniphyllaceae 35 46 0.0106 Melastomataceae 3000 83 0.0222 Elaegnaceae 50 109.5 0.0246 Lythraceae 600 111 0.0243 Barbeyaceae 1 55 0.0137 Onagraceae 650 104 0.0272 Tetreamelaceae 2 58 0.0135 Tetrameristaceae 4 31 0.0067 Begoniaceae 920 101 0.0243 Pelliceraceae 1 66 0.0155 Coriariaceae 15 56 0.0126 Actinidaceae 350 52 0.0114 Corynocarpaceae 5 49 0.0112 Ericaceae 2700 89.5 0.0228 Juglandaceae 59 33.5 0.0073 Clethraceae 120 41 0.0100 Myricaceae 40 44 0.0105 Cyrillaceae 13 61 0.0143 Casuarinaceae 70 64 0.0152 300 32 0.0077 Betulaceae 157 40 0.0088 Sapotaceae 1100 50 0.0125 Polygalaceae 800 159 0.0362 Halesiaceae 5 31 0.0080 Surianaceae 5 81 0.0208 Styracaceae 175 49 0.0114 Krameriaceae 25 86 0.0200 Hydrangeaceae² 310 55.625 0.0120 Zygophyllaceae 200 140 0.0339 Loasaceae 250 57.75 0.0124 Trigoniaceae 35 74 0.0184 Cornaceae 110 82.5 0.0184 Dichapefalaceae 200 72 0.0169 Nyssaceae 10 40.5 0.0098 Irvingiaceae 20 94 0.0265 Verbenaceae 1035 81 0.0184 Caryocaraceae 25 88 0.0222 Myoporaceae 90 47 0.0118 Medusagynaceae 1 49 0.0118 Gesneriaceae 2850 102.75 0.0218 600 56 0.0132 Utriculariaceae 245 140.5 0.0313 Malsherbiaceae 27 65 0.0151 Solanaceae 2930 73.125 0.0169 Turneraceae 120 136 0.0335 Convolvulaceae 1930 134 0.0310 Putranjivaceae 200 124 0.0308 Montiniaceae 4 105 0.0254 Humiriaceae 50 34 0.0087 Hydroleaceae 20 131 0.0312 Hypericaceae 360 83 0.0272 3700 72.5 0.0178 Podostemaceae 130 156 0.0477 Gelsemiaceae 11 43 0.0119 Ixerbaceae 1 53 0.0107 Gentianaceae 970 87 0.0212 Aphloiaceae 1 111 0.0264 Loganiaceae 30 102 0.0242 Crossosomataceae 9 49 0.0115 Garryaceae 18 39 0.0086 Stachyuraceae 10 18 0.0040 Aucubaceae 3 37 0.0094 Geraniaceae 750 153.25 0.0362 Calyceraceae 40 25 0.0067 Vivianiaceae 30 122 0.0335 Goodniaceae 300 68 0.0185 Greyiaceae 3 14 0.0033 Argophyllaceae 15 57 0.0135 Francoaceae 2 27 0.0063 Phellinaceae 12 39 0.0088 Brassicaceae 4130 101.5 0.0246 Donatiaceae 2 32 0.0077 Resedaceae 70 72 0.0232 Stylidiaceae 150 157 0.0370 Batidaceae 2 147 0.0364 Lobeliaceae 400 105 0.0287 Koeberliniaceae 1 87 0.0214 Campanulaceae 1800 113.5 0.0242 Moringaceae 12 35 0.0084 Araliaceae 700 38.5 0.0094 Caricaceae 55 64 0.0156 Apiaceae 2850 82.5 0.0186 Tropaeolaceae 92 57 0.0147 Escalloniaceae 150 62 0.0145 Akaniaceae* 3 19 0.0049 Eremosynaceae 1 141 0.0341 100 52 0.0143 Caprifoliaceae 810 43 0.0119 Meliaceae 550 67.5 0.0139 Dipsacaceae 150 39 0.0097 Anacardiaceae 600 57 0.0127 Helwingiaceae 5 41 0.0099 Burseraceae 500 66 0.0156 Aquifoliaceae 400 54 0.0118 Sarcolaenaceae 40 54 0.0119 * Includes Bretschneideraceae (Angiosperm Phylogeny Group 1998). Dipterocarpaceae 580 53 0.0131 ² Includes Hydrostachyaceae (Soltis et al. 1999, 2000).